Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: However, this requires exposure to very regular environmental time cues, so-called Zeitgebers, such as food. Thus, on the one hand, the circadian system contributes to the optimization of food metabolism; on the other hand, the intake of food serves as a potent Zeitgeber. Both mouse and human studies have shown the negative consequences of circadian disturbances on metabolism, body weight [3–11], and also mental health [12–14] and demonstrated that restriction of meals to certain time spans of the day can counteract these harmful effects [15–19]. However, previous human studies merely established rough periods during which participants could still eat irregularly. We expect that the success of previous interventions can be further improved by determining each participant’s eating time profile and creating a personalized meal plan accordingly, even if participants continue to eat large meals. Therefore, the primary aim is to individually determine and set optimal times for food intake and to correlate the reduction of mealtime variability with alterations in body weight. For control subjects, we specified a long 18-h window during which they could continue to eat irregularly. We include participants of Index (BMI) classifications normal to extremely obese to test whether participants who exceed normal BMIs particularly benefit from the intervention. Because of the impact of circadian clocks on other body functions, we further hypothesize that regular food intake contributes to an overall improvement in well-being, such as the subjective feeling of general health, sleep quality, affective state, and self-efficacy. Since the program focuses on meal times and, unlike many other dietary programs, explicitly does not aim to limit calories or certain types of food, we have named it “Time to Eat” (Fig. S1A). 2. Results2. 1. ParticipantsA total of 148 participants were recruited. Of these, 121 were randomly allocated to the experimental group (EG) (n=79) and the control group (CG) (n=42) (Fig. S1B), which had non-significantly different mean BMIs of 25. 9 (SD: ± 4. 138) (CG) and 27. 5 (SD: ± 4. 627) (EG) (Tab. S1). At the end of the intervention (T2), data were available from 100 participants (EG: n=67, CG: n=33). [SEP] Justify:

Output: The text contrasts the claim by emphasizing that the program named 'Time to Eat' does not aim to limit calories or types of food; however, it stresses the importance of timing and regularity of food intake over the quantity of food consumed. It mentions that disturbances in circadian rhythms can lead to negative effects on metabolism and body weight, which implies that consuming food at irregular times could lead to weight gain, regardless of how well it fits an individual's genetic profile. Thus, the claim that personalized nutrition allows unrestricted eating without weight gain is rebutted by the necessity for regular eating patterns to optimize metabolism.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Enzyme activity (μmol h−1 g−1). . General role. −SB. FH. +SB. Sand. Control. Acid phosphatasePhosphate mobilization3. 06 (0. 51) b5. 11 (1. 06) a2. 53 (0. 80) b<0. 01 (0. 00) d1. 63 (0. 36) cSulfataseSulphate-ester hydrolysis0. 03 (0. 01) b0. 06 (0. 02) a0. 04 (0. 01) b<0. 01 (0. 00) cNDLeucine aminopeptidaseNitrogen mobilization0. 01 (0. 02) b0. 01 (0. 02) b0. 04 (0. 03) aNDNDβ-1,4-N-AcetylglucosaminidaseChitin degradation1. 54 (0. 42) a2. 13 (0. 98) a1. 79 (0. 47) a<0. 01 (0. 00) b0. 21 (0. 40) bβ-1,4-GlucosidaseCellulose degradation2. 23 (0. 69) b3. 05 (0. 91) ab3. 44 (1. 12) a0. 01 (0. 00) c0. 70 (0. 56) cCellobiohydrolaseCellulose degradation0. 77 (0. 58) ab0. 87 (0. 56) ab1. 07 (0. 61) a<0. 01 (0. 00) c0. 36 (0. 20) bcβ-1,4-XylosidaseHemicellulose degradation0. 12 (0. 06) ab0. 22 (0. 18) a0. 19 (0. 10) a<0. 01 (0. 00) b0. 10 (0. 05) abLaccaseaLignin degradation13. 3 (12. 5) ab19. 0 (11. 3) a5. 4 (8. 3) bND4. 13 (4. 6) bPeroxidaseaLignin degradation19. 2 (15. 4) c39. 2 (18. 4) ab48. [SEP] Justify:

Output: The text does not provide relevant information regarding the role of fungi in decomposing organic matter or their contribution to nutrient cycling. Instead, it lists various enzyme activities and their roles in different biochemical processes without stating any connection to fungi or organic matter decomposition.


Input: Task: corroborate the claim using the given text. Claim: Ethnobotany can help identify plants that are culturally significant or used for spiritual practices. [SEP] Text: Ethnobotany of wild and semi-wild edible and medicinal plants used by Maale and Ari ethnic groups in southern &RCoutput: Thesis › internal (1) and semi-wild plant resources that have food and medicinal importance are distributed at different habitats in Ethiopia and play an important role in the livelihood of different communities. This study discussed ethnobotany of these resources with special emphasis on the use, management and conservation of wild and semi-wild edible and medicinal plants by the two ethnic groups in southern Ethiopia. and Ari ethnic groups consumed in total 30 leafy vegetable species, which were crucial ingredients in the preparation of traditional dishes, more frequently during periods of food shortage. The study revealed that the transfer of local knowledge within the community on wild and semi-wild leafy vegetables is not differentiated by gender or age and thus enables knowledge continuity. However, harvesting and cooking activities are considered as women’s tasks by the communities. The study also found out that taste, marketability and above ground edible biomass as the main farmers’ criteria for selection leafy vegetables for cultivation. Major threats to wild and semi-wild leafy vegetables are identified and recommended that these factors has to be minimized and supported by complementary in-situ and ex situ conservation strategies. The two ethnic groups use 52 species of wild and semi-wild fruits which were especially important for their diet in times of food shortage. The study revealed species such as Balanites rotundifolia and Dobera glabra in Maale and Carissa spinarum and Vitex doniana in Ari as the most important fruit bearing species. No significant variations in ethnobotanical knowledge regarding fruits were found among gender and age groups. The study revealed that low prices, poor market and outlet opportunities hamper wild and semi-wild fruits trade. Thus, creating demand and facilitating better market outlets will encourage communities to cultivate wild and semi-wild fruits in the future. The major threat to the availability of wild and semi-wild fruits in the study area were tree felling and conversion of forest to agricultural land. The study recommended maintenance and enrichment planting of the most important species as plausible management interventions in addition to preserving the local knowledge and implementing conservation strategies. In total 128 plant species were found and also 89 % of the study participants reflected traditional medicine as the first line of treatment. The dominant ways of medicinal plant knowledge acquisition and transfer is vertical. [SEP] Justify:

Output: The text corroborates the claim by detailing the ethnobotany of wild and semi-wild edible and medicinal plants used by the Maale and Ari ethnic groups, highlighting their cultural significance and the role these plants play in their traditional practices and livelihoods. For instance, it mentions how the ethnobotanical knowledge is crucial, especially during times of food shortage, indicating that these plants are not only important for sustenance but also carry cultural importance within the communities.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Their baseline data indicate that participants in both groups were, on average, overweight according to BMI classification, with the included CG participants having a BMI 25. 5 (SD: ± 3. 827) and being slightly less overweight, on average, than the analyzed EG participants with a BMI of 27. 4 (SD: ± 4. 616) (Tab. S1). There were no significant BMI differences between completers and drop-outs in either group (Fig. S2A, Tab. S2). Reasons for drop-outs were, according to self-report, illness/accident during the study and unwillingness or failure to adhere to fixed meal times. 2. 2. Improvement of meal time regularityAll study participants were asked to record each caloric event during a 14-day exploration and a six-week intervention phase (Fig. 1A, B, S1C). During the exploration and intervention phases, a total of 13,838 and 34,564 caloric events were recorded from completers, respectively. Most EG participants were assessed as having three eating times (n=53), some reported eating four meals (n=13), and one had two main meals per day. The average MTVS for breakfast, lunch, dinner, and total meals of the exploration phase of both groups was around 4, which corresponds to a daily deviation of ∼120 min for each meal. In the EG group, mean scores improved to less than to 2 during the intervention phase, corresponding to a mean deviation of less than ± 30min (Fig. 1C, D, Tab. S3). In contrast, in the CG group, there was no improvement but some significant increase of the MTVS. Fig. 1:Improvement in regularity of meals, body weight changes, and correlation between loss of body weight and regularity of eating meals. (A, B) Times of day of caloric events of 15 representative participants of the EG (A) and the CG (B) during the two-week exploration phase (left) and the six-week intervention phase (right). Each point represents a caloric event. (C, D) Change in MTVS of participants in the CG (gray) and EG (cyan) of breakfast, lunch, and dinner (C) and of all meals combined (D), including snacks, if snacks were taken. [SEP] Justify:

Output: The text contrasts the claim by providing data on the participants' body mass index (BMI) and their eating habits during a study. It notes that participants, on average, were overweight according to BMI classifications, indicating that personalized nutrition does not guarantee weight maintenance despite adherence to genetic profiles. The lack of significant BMI improvements in the control group and the increase in body weight regulation in the experimental group suggest that merely fitting a genetic profile does not ensure the ability to eat without gaining weight.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 9 (16. 5) aND27. 5 (12. 6) bcPhenol oxidaseaLignin degradation0. 5 (1. 3) b0. 7 (1. 1) b3. 5 (2. 6) aND1. 54 (1. 00) abAbbreviations: control, residual enzyme activity in irradiated controls (irradiated control bags not placed in the field); FH, in situ fermentation-humic layer; ND, no activity detected; −SB, hyphal trap bags with no sand barrier; +SB, hyphal trap bags with sand barrier; Sand, sand barrier. Data are provided as means (n=9) with s. d. in brackets. Data in the same row with different letters are significantly different at P<0. 01. aActivities given as mmol h−1 g−1. Table 3 Open in new tab Potential organic matter breakdown activity in the hyphal trap bags, associated sand, adjacent forest floor and residual-activity controls Enzyme. Enzyme activity (μmol h−1 g−1). . General role. −SB. FH. +SB. Sand. Control. Acid phosphatasePhosphate mobilization3. 06 (0. 51) b5. 11 (1. 06) a2. 53 (0. 80) b<0. 01 (0. 00) d1. 63 (0. 36) cSulfataseSulphate-ester hydrolysis0. 03 (0. 01) b0. 06 (0. 02) a0. 04 (0. 01) b<0. 01 (0. 00) cNDLeucine aminopeptidaseNitrogen mobilization0. 01 (0. 02) b0. 01 (0. 02) b0. 04 (0. 03) aNDNDβ-1,4-N-AcetylglucosaminidaseChitin degradation1. 54 (0. 42) a2. 13 (0. 98) a1. 79 (0. 47) a<0. 01 (0. 00) b0. 21 (0. 40) bβ-1,4-GlucosidaseCellulose degradation2. 23 (0. 69) b3. 05 (0. 91) ab3. 44 (1. [SEP] Justify:

Output: The text provides detailed information regarding enzyme activities and does not explicitly mention fungi decomposing organic matter or contributing to nutrient cycling. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-1777358/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Published17 Jan, 2023Read the published version in →Version 1posted 5You are reading this latest preprint versionAbstractThe frequency of flow-intermittency and drying events in Alpine rivers is expected to increase due to climate change. These events can have significant consequences for stream ecological communities, though the effects of reduced flow conditions on the microbial communities of decomposing allochthonous leaf material require additional investigation. In this study, we investigated the bacterial and fungal communities associated with the decomposition of two common species of leaf litter, chestnut (Castanea sativa) and oak (Quercus robur). Sampling of experimentally placed leaf bags was spread over six collection points (up to 126 days after placement) at seven sites in the Alps, which have historically differed in streamflow conditions. Bacterial and fungal communities from these leaf bags were identified using high-throughput amplicon sequencing. Chestnut and oak leaf bags harbored distinct bacterial and fungal communities, with a number of taxonomic groups differing in abundance, though bacterial communities began to converge at later sampling dates. Historical flow conditions (intermittent vs perennial rivers) and observed conditions (normal flow, low flow, ongoing drying event) had comparatively weak observed effects on bacterial and fungal communities to that of leaf type and collection date (i. e. length of decomposition). Our findings highlight the importance of leaf characteristics (e. g. , C:N ratios, recalcitrance, etc. ) to the in-stream conditioning of leaf litter and the need for additional investigations of drying events in Alpine streams. This study provides new information on the microbial role in leaf litter decomposition with expected flow changes associated with a global change scenario. [SEP] Justify:

Output: The text corroborates the claim by highlighting the importance of fungal communities in the decomposition of leaf litter, a form of organic matter. It describes a study that investigates 'the bacterial and fungal communities associated with the decomposition of two common species of leaf litter,' indicating that fungi play a role in this ecological process.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: (H) Significant correlation between change in BMI, baseline BMI, and improvement in MTVS. Individuals with higher BMI benefit more from similar improvements in MTVS (shades of data points) than individuals with lower BMI in EG participants. Multiple regression, n=67, * p ≤ 0. 05, ** p ≤ 0. 01. Detailed statistics in Tab. S9. 2. 3. Weight changeDuring the exploration phase, when no instructions on eating times were given, CG and EG participants had a statistically non-significant average loss of 0. 17 kg (0. 06 kg/m²) and 0. 21 kg (0. 06 kg/m²), respectively (Figs. 1E, S2B-F, Tabs. S4, 5). However, during the intervention phase, when EG participants took their meals more regularly, they lost an average of about 2. 6 kg (95% CI [-2. 906, -1. 915]) and 0. 81 kg/m² (95% CI [-0. 9729, -0. 6420]) (Figs. 1E, S2B-E, Tabs. S4, 5), which translates to an average weight loss of 0. 40 kg (0. 145 kg/m²) per week during the intervention. In contrast, weight and BMI changes of -0. 39 kg (95% CI [-0. 9125, 0. 1307]) and -0. 14 kg/m² (95% CI [-0-3152, 0. 0304]), respectively, were not significant in the CG (Figs. 1E, S2B, C, F, Tabs. S4, 5), resulting in a significant difference in weight loss between groups at the end of the intervention (Figs. 1F, S2C, Tab. S5). The inclusion of the last available weight and BMI data of the drop-outs in an end-point analysis did not lead to any notable change in this result (Fig. S2G, Tab. S5). Four weeks after the intervention ended, all participants were contacted again for a follow-up assessment. 34 of the 67 EG participants reported to have maintained the regularity of their meals and continued to lose body weight significantly, on average another 1. 12 kg (95% CI [-1. 479, -0. 7626]) and 0. [SEP] Justify:

Output: The text contrasts the claim by presenting data on weight changes during an intervention phase where participants, specifically those in the experimental group (EG), lost significant weight through regular meal timing. It illustrates that not all participants maintained or achieved weight loss in a statistically significant manner, suggesting that personalized nutrition does not guarantee one can eat anything without gaining weight. Instead, the outcome is reliant on factors such as regularity of meals, indicating that it is not a simple matter of fitting food choices to a genetic profile.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 12) a0. 01 (0. 00) c0. 70 (0. 56) cCellobiohydrolaseCellulose degradation0. 77 (0. 58) ab0. 87 (0. 56) ab1. 07 (0. 61) a<0. 01 (0. 00) c0. 36 (0. 20) bcβ-1,4-XylosidaseHemicellulose degradation0. 12 (0. 06) ab0. 22 (0. 18) a0. 19 (0. 10) a<0. 01 (0. 00) b0. 10 (0. 05) abLaccaseaLignin degradation13. 3 (12. 5) ab19. 0 (11. 3) a5. 4 (8. 3) bND4. 13 (4. 6) bPeroxidaseaLignin degradation19. 2 (15. 4) c39. 2 (18. 4) ab48. 9 (16. 5) aND27. 5 (12. 6) bcPhenol oxidaseaLignin degradation0. 5 (1. 3) b0. 7 (1. 1) b3. 5 (2. 6) aND1. 54 (1. 00) abEnzyme. Enzyme activity (μmol h−1 g−1). . General role. −SB. FH. +SB. Sand. Control. Acid phosphatasePhosphate mobilization3. 06 (0. 51) b5. 11 (1. 06) a2. 53 (0. 80) b<0. 01 (0. 00) d1. 63 (0. 36) cSulfataseSulphate-ester hydrolysis0. 03 (0. 01) b0. 06 (0. 02) a0. 04 (0. 01) b<0. 01 (0. 00) cNDLeucine aminopeptidaseNitrogen mobilization0. 01 (0. 02) b0. 01 (0. 02) b0. 04 (0. 03) aNDNDβ-1,4-N-AcetylglucosaminidaseChitin degradation1. 54 (0. 42) a2. 13 (0. 98) a1. [SEP] Justify:

Output: The text does not address the claim directly regarding fungi and their role in decomposing organic matter. It focuses instead on various enzyme activities related to different types of organic compounds, such as cellulose, lignin, and nitrogen, without making a clear connection to the role fungi play in nutrient cycling.


Input: Task: corroborate the claim using the given text. Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: BacteriaFungileaf litter decompositionintermittent riversin-stream conditioningAlpine streamsFiguresFigure 1Figure 2Figure 3Figure 4Figure 5Figure 6Figure 7IntroductionIn low-order streams, allochthonous leaf litter is a fundamental energy source, and its decomposition plays a key role in nutrient and energy cycling [1]; therefore, coarse particulate organic matter (CPOM) decomposition has been widely used to assess river function [2] and is the basis for the Concept [3]. In general, leaf litter decomposition consists of three primary phases: leaching, conditioning and fragmentation [4]. After initial immersion, leaves begin to leach chemicals and nutrients (usually within 24–48 h); this is followed by microbial conditioning by fungi and bacteria that degrades the leaf tissues and facilitates additional decomposition over days to weeks; lastly, remaining recalcitrant leaf material experiences physical abrasion through macroinvertebrates feeding and shredding activity that leads to fragmentation with associated p47. 64 ± 0. 47 C:N content at the beginning of the experiment, and oak (Quercus robur), 38. 98 ± 0. 47 initial C:N content, both collected in autumn after abscission. For more details regarding experimental setting please see Gruppuso et al. [28, 29]. Three leaf bags per leaf species were collected on each sampling date, placed into individual plastic bags and stored at -20°C until DNA extraction and microbial community sequencing. Frozen leaf litter samples were thawed and sampled using a cork-borer under sterile conditions. For each sample, 1 g of leaf tissue was stored in cryovials with Sigma-Aldrich RNAlater® and kept frozen at -20°C. DNA extractions were performed using Qiagen MagAttract® DNA Extraction Kit, following manufacturer’s instructions except for the addition of lysozyme (15 mg/ml) during the lysis step. For bacterial communities, the V4 hypervariable region of the 16S rRNA gene [30–32] was amplified using dual indexed Illumina compatible primers 515f/806r as described by Kozich JJ [33]. For fungal communities we used ITS4 + ITS7 primers complementary to the internal transcribed spacer (ITS) region [34–36]. PCR products were batch normalized using plates and the products recovered from the plates pooled. [SEP] Justify:

Output: The text supports the claim by discussing the role of fungi in the microbial conditioning of leaf litter, stating that fungi and bacteria degrade leaf tissues which facilitates additional decomposition. This process highlights the important function of fungi as decomposers in the nutrient cycling of ecosystems.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: 36 kg/m² (95% CI [-0. 4907, -0. 2457]), respectively (Figs. 1E, S2B, D, E, Tabs. S4, 5). In contrast, participants who reported to have resumed irregular eating gained a significant average of 0. 48 kg (95% CI [0. 1984, 0. 7616]) and 0. 17 kg/m² (95% CI [0. 07434, 0. 2603]), respectively (Fig. 1E, S2B, D, E, Tab. S4). 2. 4. Relation between weight change and improvement in the regularity of mealsTo examine the extent to which EG participants’ weight loss was effectively related to improvements in meal regularity, we correlated changes in body weight and BMI with individual MTVS changes. Consistent with our hypothesis, a significant relationship exists between weight loss and improvement in regularity in the EG (Fig. 1G, Tab. S6). A breakdown of meals shows that increasing the regularity of lunch and dinner has the greatest effects, with no significant relationship between increasing the regularity of breakfast and weight loss (Fig. S2H, Tab. S6). In contrast, in the CG, there were no or little improvements in regularity and, accordingly, no correlation with weight/BMI changes. Further analyses revealed that all MTVS up to 3, which corresponds to a time window for meals of up to ±45 min, resulted in comparably effective weight loss, whereas the efficiency of weight loss decreases significantly with an MTVS greater than 3 (Tab. S7). 2. 5. Relation between weight change and baseline BMIA weight loss intervention which is particularly based on metabolic optimization is likely to be most effective for individuals with exceeded body weight. In fact, the higher the baseline BMI of EG participants at T1, the greater the weight loss (Fig. S2I, Tab. S6). Stratifying the subjects by baseline BMI, including the control group, confirms this result, but also shows that in all strata the BMI of EG subjects decreased more than that of CG subjects, even if they had the same initial BMI (Fig. S2J, Tab. S8). Multiple regression shows that the reduction in MTVS and baseline BMI together predict the weight loss of the participants (Fig. 1H, Tab. S9). [SEP] Justify:

Output: The text contrasts the claim by indicating that a significant relationship exists between meal regularity and weight loss in the experimental group (EG), suggesting that irregular eating patterns can lead to weight gain, which undermines the idea that personalized nutrition would allow one to eat anything without gaining weight. Specifically, it states that participants who reported irregular eating gained weight, directly contradicting the notion of guaranteed weight management solely based on genetic profiles.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 79 (0. 47) a<0. 01 (0. 00) b0. 21 (0. 40) bβ-1,4-GlucosidaseCellulose degradation2. 23 (0. 69) b3. 05 (0. 91) ab3. 44 (1. 12) a0. 01 (0. 00) c0. 70 (0. 56) cCellobiohydrolaseCellulose degradation0. 77 (0. 58) ab0. 87 (0. 56) ab1. 07 (0. 61) a<0. 01 (0. 00) c0. 36 (0. 20) bcβ-1,4-XylosidaseHemicellulose degradation0. 12 (0. 06) ab0. 22 (0. 18) a0. 19 (0. 10) a<0. 01 (0. 00) b0. 10 (0. 05) abLaccaseaLignin degradation13. 3 (12. 5) ab19. 0 (11. 3) a5. 4 (8. 3) bND4. 13 (4. 6) bPeroxidaseaLignin degradation19. 2 (15. 4) c39. 2 (18. 4) ab48. 9 (16. 5) aND27. 5 (12. 6) bcPhenol oxidaseaLignin degradation0. 5 (1. 3) b0. 7 (1. 1) b3. 5 (2. 6) aND1. 54 (1. 00) abAbbreviations: control, residual enzyme activity in irradiated controls (irradiated control bags not placed in the field); FH, in situ fermentation-humic layer; ND, no activity detected; −SB, hyphal trap bags with no sand barrier; +SB, hyphal trap bags with sand barrier; Sand, sand barrier. Data are provided as means (n=9) with s. d. in brackets. Data in the same row with different letters are significantly different at P<0. 01. aActivities given as mmol h−1 g−1. Table 4 Open in new tab Potential organic matter breakdown activity of ectomycorrhizal tips Enzyme. Enzyme activity (pmol min−1 mm−2). . [SEP] Justify:

Output: The text does not directly address the claim regarding the ability of fungi to decompose organic matter. Instead, it consists of tables and figures that list enzyme activities related to various types of organic matter degradation without providing context about the role of fungi in this process. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: DiscussionIn this study, we investigated how the bacterial and fungal community composition differed between flow conditions for two common species of aquatic leaf litter. Drying events showed limited effects on leaf bacterial communities, which were probably supported during flow disturbances by the fungal community already present since the early stages of the decomposition process, which provided an increased surface area for bacteria along with leachate and products of polymers’ degradation [46, 47]. Similarly, leaf bag fungal diversity and taxonomic abundance were not strongly impacted by drying or low flow events. This could be due to the presence of some families which are typically present on the phyllosphere such as Cladosporaceae and Pleosporaceae [48, 49], here found in both chestnut and oak leaves and thus being more resistant to desiccation than the aquatic ones. Furthermore, the presence of desiccation-resistant taxa may have contributed to stabilizing the microbial community when flowing water disappeared. Surprisingly, oak leaves showed higher bacterial and fungal diversity between paired samples. We expected to see lower diversity in oak leaf bags due to them commonly considered as lower quality, more coriaceous (i. e. , leathery), and their higher concentrations of secondary metabolites (such as phenols and tannins) which can make the substratum less palatable for both micro and macroorganisms. Potentially, the higher observed diversity of the microbial community present on the leaves is reflective of the additional complexity needed to break down more recalcitrant leaf material to process [50]. Microbial community structure (as beta diversity) of oak and chestnut leaves varied over the course of this experiment. Regardless of flow conditions, chestnut and oak bacterial communities were distinct at the beginning of the experiment but converged at later sampling dates. This could be due to a higher presence of phyllosphere-specific taxa earlier in decomposition which is replaced over time by more specialized bacteria from the aquatic environment which contribute to the decomposition process. However, for fungi, we observed that chestnut and oak fungal communities remained distinct throughout decomposition. This suggests the presence of species specific fungi involved in the decomposition process, a hypothesis supported by the known differences in quality of the two leaf types [51]: some secondary compounds such as cellulose, lignin, tannins and phenols have a role in the composition of the leaf texture and palatability, thus different fungi are necessary to break down those compounds. [SEP] Justify:

Output: The text corroborates the claim by discussing the role of fungi in the decomposition process of leaf litter. It describes how certain fungal communities provided an increased surface area for bacteria and were involved in breaking down organic materials present in different leaf types. The observation that distinct fungal communities contributed to the decomposition process, suggesting species-specific fungi are involved, explicitly supports the claim that fungi are crucial decomposers in ecosystems.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: These data show that regularity in meal intake can lead to a significant loss of body weight and suggest that this effect is especially pronounced in individuals with a higher BMI. 2. 6. Relation between weight change and self-reported food quantity and compositionBy restricting meals to specific times and shortening the time window in which food is eaten, it is feasible that EG participants ate less or changed food composition during the intervention phase and therefore lost weight. However, on average, the reported food energy ingested by CG and EG participants did not substantially change during the study (Fig. 2A, S2K, L, Tab. S3, 6), apart from a minor average reduction of ∼350 kJ (95% CI [-627. 6, - 67. 67]) per day in the EG (Fig. S2K, Tab. S3, 6), and did not differ between CG and the EG. As they are rather small, these differences do not add up to a significant reduction in the total average energy consumed over the course of the study. Accordingly, the determined cumulative average energy intake during the intervention phase did not differ on any day from the estimated energy intake based on an extrapolation of the cumulative food consumption during the exploration phase, neither in the CG nor in the EC group (Fig. 2B). Nevertheless, there were some participants who reported having consumed fewer calories during the intervention phase, while some also reported having ingested more calories. However, consistent with our hypothesis that high regularity of mealtimes optimizes metabolism of similar amounts of food, there is no relationship between reported changes in average daily and cumulative energy intake and change in body weight/BMI of either CG or EG participants (Fig. 2C, D, Tab. S6). Likewise, the composition of the ingested foods did not change considerably in either group, and participants reported a normal distribution of the macronutrients of fat, carbohydrate, and protein in both phases of the study (Fig. 2E, S2M). Also, there was no correlation between weight change and change in reported average daily and cumulative macronutrient intake (Fig. 2D, S2N, Tab. S6). Fig. 2:Changes in body weight/BMI are not related to changes in reported caloric intake and composition of macronutrients. [SEP] Justify:

Output: The text contrasts the claim by indicating that changes in body weight and BMI are not related to changes in reported caloric intake or the composition of macronutrients. It emphasizes that despite meal regularity potentially optimizing metabolism, there was no significant change in energy intake or weight change among participants. Thus, the idea that personalized nutrition allows full freedom in eating without weight gain is rebutted by the findings that meal patterns and caloric intake do not correlate with weight loss.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0. 63 (0. 28) b1. 09 (0. 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0. 01)Number of plots (n)878559Enzyme. [SEP] Justify:

Output: The text consists predominantly of a list of fungi and enzymes without providing any context or explanation about their roles in decomposing organic matter or nutrient cycling. Therefore, it does not support, contradict, or address the claim directly.


Input: Task: corroborate the claim using the given text. Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: This could be due to the need of breaking down those recalcitrant and secondary compounds into simpler molecules and nutrients, before those nutrients become available for other organisms involved in the decomposition process. Fungal communities are mainly represented by Ascomycetes [57], because Basidiomycetes usually later in leaf litter decomposition, at stages we did not investigate during our field experiment. The family Aurobasidiaceae, which is widespread in freshwater and marine ecosystems [58], was the most abundant in our samples, despite the leaf type and flow regime, likely because this family is able to adapt to different environmental conditions and thus to cope with hydrological and nutrient stressors [58]. Interestingly, the fungi of the family Pleomassariaceae, widely distributed on decomposing wood and plant material [58], showed high abundance in low flow and drying conditions; this could be due to the ability to exploit the substratum’s remaining moisture and an ability to degrade secondary compounds. This fungal group deserves additional investigation to understand their role in leaf litter decomposition processes during longer desiccation phases. Oak leaf bag fungal communities had a high relative abundance of Cladosporium, typically found in plant material; Alternaria, a taxon usually present on decomposing material with high humidity [59]; Adisciso, a plant pathogen [60] and Phialea, typical of dead leaf material [61]. Chestnut leaves, however, had high relative abundance of Lemonniera, an aquatic hyphomycetes involved in stream decomposition processes [62]; and Tetracladium, an important decomposer in stream food webs [63]. The presence of those genera, mainly involved in breakdown processes in aquatic environments, may explain the faster decomposition rate we found for chestnut leaves. These findings highlight the importance of bacteria and fungi in the leaf litter decomposition process, and confirms the presence of different families/genera during decomposition, and variation related in leaf type and quality and also flow regime, even if with limited effect. High-throughput sequencing of microbial communities associated with in-stream leaf litter highlights the complexity of biotic interactions on aquatic decomposition processes. river ecosystems, the occurrence of low flow phases and drying events is a recent phenomenon, caused mainly by global climate change and anthropogenic pressures [64]. [SEP] Justify:

Output: The text corroborates the claim by detailing how various fungal communities contribute to the decomposition process. It specifically mentions that certain fungal groups, such as the family Pleomassariaceae and genera like Cladosporium and Tetracladium, are involved in breaking down organic materials like leaf litter and decomposing wood. The text emphasizes the role of fungi in the leaf litter decomposition and the complexity of biotic interactions during this process, highlighting their significance as decomposers in ecosystems.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Changes in reported daily caloric intake (A), cumulative caloric intake (B) and food composition (E) and their relationship to weight/BMI changes (C, D, and F). Data in (A) are normalized so that all baseline data of the exploration phase equal 1. To represent the x-fold change, data from the intervention phase are divided by data from the exploration phase of the corresponding participant. (A, E) 2-way repeated-measures ANOVA with Bonferroni post hoc test comparing CG and EG during the exploration or intervention phase and T0-T1 and T1-T2 within groups, * p ≤ 0. 05. Detailed statistics in Tables S3. (B) Mixed-effects model with Bonferroni post hoc test comparing determined and estimated cumulative energy intake. The estimated energy intake is formed as an assumed continuation of the average daily intake during the exploration phase. post hoc test showed no significant differences on any study day. (C, D, and F) Linear regression, CG: n=30; EG: n=67 (some participants were excluded subsequently from this analysis because of several erroneous diary entries about unrealistic amounts of food, e. g. , 30,000 g chicken for lunch). Detailed statistics in Tab. S6. 2. 7. Relation between weight change and other meal timing-related factorsBesides increasing regularity, restricting meals to certain times of the day can also shorten the daily window in which meals are eaten and shift meals to other times of the day. In fact, our intervention caused many EG participants to avoid occasional meals at extremely early or late times, limiting their meals to much shorter intervals of 11 h (95% CI [10. 468, 11. 520]) (Fig. 3A, B, Tab. S3), while those of the CG remained long with 13. 7 h (95% CI [12. 902, 14. 562]). Additionally, compared with before and with the CG, the EG intervention resulted in the first meal of the day being delayed to a later time for many subjects (EG: 09:21 (95% CI [08:58, 09:45]) vs. CG: 08:03 (95% CI [07:32, 08:33])) and the last meal of the day being advanced to an earlier time (EG: 20:17 (95% CI [19:59, 20:35]) vs. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities involved in caloric intake and its relationship to weight and BMI changes. It emphasizes that there are no significant differences in cumulative caloric intake when comparing groups, suggesting that simply fitting a genetic profile does not ensure weight management. The mention of meal timing and caloric analysis calls into question the notion that personalizing nutrition guarantees weight stability without limitations.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Enzyme activity (pmol min−1 mm−2). . Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0. 63 (0. 28) b1. 09 (0. 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0. [SEP] Justify:

Output: The text is largely numerical and lists specific enzyme activities associated with certain fungi but does not provide any clear information or context about the role of these fungi in decomposing organic matter or contributing to nutrient cycling. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: Frey-(2011) Bacterial-fungal interactions: hyphens between agricultural, clinical, environmental, and food microbiologists. 75:583–609. (2015) Effects of forest management practices in temperate beech forests on bacterial and fungal communities involved in leaf litter degradation. 69:905–913. (1966) Decomposition of leaf litter in relation to environment, microflora, and microbial respiration. Ecology 47:194–201. (2013) Assessing the effect of litter species on the dynamic of bacterial and fungal communities during leaf decomposition in microcosm by molecular techniques. 8:e84613. Mora-Gómez J, Duarte S, Cássio F, Pascoal C, Romaní AM (2018) Microbial decomposition is highly sensitive to leaf litter emersion in a permanent temperate stream. Environ 621:486–496. (2020) Microbial community response to a novel salmon resource subsidy. Evol 7:505. álint M, Bernabò P, Čiampor F Jr, Čiamporová-Zaťovičová (2014) Integrating molecular tools into freshwater ecology: developments and opportunities. 9:1559–1576. (2019) Necrobiome framework for bridging decomposition ecology of autotrophically and heterotrophically derived organic matter. 89:e01331. (2018) Lentification in Alpine rivers: patterns of diatom assemblages and functional traits. 80:1–11. (2019a) streams run dry: the drought memory of benthic communities. 81:1–14. (2019b) The role of recurrent dewatering events in shaping ecological niches of scrapers in intermittent Alpine streams. Hydrobiologia 841:177–189. per la Protezione dell’Ambiente (2013) Idrologia in Piemonte nel 2012. Regione Piemonte, pp 23. (2021) Effects of flow intermittence on ecosystem processes in mountain streams: are artificial and field experiments comparable? Limnol 195:39–59. (2022) Decomposition and Communities of Alpine Streams: A along the Po River. Water 14:258. [SEP] Justify:

Output: The text corroborates the claim by discussing various studies that investigate bacterial-fungal interactions and their involvement in decomposition processes, specifically, leaf litter degradation. It emphasizes the role of fungi in the decomposition of organic matter in forest ecosystems and their definition as part of the microbial community responsible for such ecological functions.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: CG: 21:31 (95% CI [21:05, 21:57])) (Fig. 3C, D, Tab. S3). However, weight changes of participants were not related to one of these changes in eating characteristics (Fig. 3B-D, Tab. S6). Fig. 3:Influence of other changes in eating times and of personalization of meal schedules on weight loss. (A) 95th percentile of the time period during which food was ingested by 15 example participants during the exploration phase (yellow) and the intervention phase (purple). (B) Change in length of this period and its relation to weight/BMI changes. (C, D) Change in time of first (C) and last (D) caloric intake and their association with weight/BMI changes. (B-D) 2-way repeated-measures ANOVA with Bonferroni post hoc test comparing CG and EG during the exploration or intervention phase and T0-T1 and T1-T2 within groups, *** p ≤ 0. 001, **** p ≤ 0. 0001. Linear regression. EG: n=67, varying n-numbers result from incomplete entries in the diaries. Detailed statistics in Tables S3 and S6. (E) The relation between mid-Sleep phase and mid-Eat phase (brown) on the weekends of the exploration phase. The goodness of fit of this association improves during through EG intervention and affects both workdays and weekend days (purple). Linear regression, n=65, **** p ≤ 0. 0001. Detailed statistics in Table S6. (F) Relation of the mid-Sleep phase (mSP) and mid-Eat phase (mEP) during exploration and intervention phase. The circles represent 24 h, the gray area represents the estimated sleep time, and the black arrow represents the mid-sleep phase, which is normalized for all subjects. The colored triangles represent the mid-Eat phase of each subject in relation to their mid-Sleep phase. The red arrow shows the average mid-Eat phase across all subjects. n=65. Detailed statistics in Table S10. (G) The smaller the residuals, i. e. , the vertical distances of observation points from the regression line, became, the more BMI the EG subjects lost. Linear regression, n=65, ** p ≤ 0. 01. Detailed statistics in Table S6. [SEP] Justify:

Output: The text provides evidence that contradicts the claim by stating that weight changes among participants were not related to the changes in their eating characteristics. This suggests that personalized nutrition, as presented, does not ensure that individuals can consume anything without affecting weight, highlighting the limitations of relying solely on genetic profiles for dietary freedom without weight gain.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 01)Number of plots (n)878559Data are provided as means (n=number of plots the tip genera were isolated from. Note that not all genera were found in all plots) with s. d. in brackets. Data in the same row with different letters are significantly different at P<0. 01. Refer to Table 3 for the general role of each enzyme in organic matter breakdown. aEMF, average activity of all ectomycorrhizal tips, not included in statistical analysis. bLaccase activity given in U min−1 mm−2. Table 4 Open in new tab Potential organic matter breakdown activity of ectomycorrhizal tips Enzyme. Enzyme activity (pmol min−1 mm−2). . Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0. 63 (0. 28) b1. 09 (0. [SEP] Justify:

Output: The text provides detailed data on enzyme activity related to organic matter breakdown but does not explicitly state the role of fungi in this process or their contribution to nutrient cycling. Therefore, it is irrelevant to the claim, which specifically mentions the decomposition capabilities of certain fungi.


Input: Task: corroborate the claim using the given text. Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: The γ-crystallins, in particular, also had highly variable expression levels and therefore would likely contribute very different amounts to the overall refractive index. When accounting for expression levels (TMM) of all the ubiquitous crystallin genes, tadpoles and juveniles had similar weighted mean dn/dc values (0. 2010 and 0. 2003, respectively; Additional file 8). The frog-specific crystallins had lower estimated dn/dc values than any of the ubiquitous crystallins (ρ-crystallin, 0. 1916 and ζ-crystallin, 0. 1884; Additional file 1: Table S3). DiscussionSignificant shifts in gene expression across ontogenyThe adaptive decoupling hypothesis suggests that animals that develop through two or more distinct phenotypic phases may be able to disrupt genetic correlations between phases, allowing each phase to better adapt to its particular selective environment [3]. This strategy would be particularly relevant for frogs, which often have larval (tadpole) and adult phases that occupy different ecological niches. Although previous studies have shown that morphological diversity of tadpoles and adult frogs is decoupled [6, 17,18,19], studies testing for differences in gene expression are more limited [18]. We found that a large proportion of the eye transcriptome (42%) was significantly differentially expressed between tadpole and juvenile southern leopard frogs, suggesting substantial, and potentially adaptive, decoupling at the level of gene expression. Further, this suggests that cellular composition, density, and size, in addition to within-cell changes in expression, differ between tadpoles and juvenile frogs. These results are consistent with a recent study of eye-body size allometry across ontogeny in anurans that detected a shift at metamorphosis in several species [27], suggesting that relative eye growth is partially decoupled as well. The extent of decoupling in gene expression we detected was substantially more than was found in a comparison of whole body (excluding gut) transcriptomes of tadpole and adult Mantidactylus betsileanus Madagascar frogs, which found that only 14% of annotated transcripts were differentially expressed [18]. In that whole body comparison, differentially expressed transcripts were significantly enriched for genes involved in morphological development, suggesting that phenotypic evolution across phases was decoupled. [SEP] Justify:

Output: The text corroborates the claim by discussing the distinct developmental phases of frogs, specifically noting the differences between the tadpole (larval) and juvenile (adult) stages. It highlights that significant shifts in gene expression occur across ontogeny, which aligns with the idea of metamorphosis, where frogs transition from a larval form in an aquatic environment to an adult form that occupies a different ecological niche.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: (H) Representative example of a meal diary showing a shift from meals on weekends. The purple arrows represent the calculated times, based on the events of the more frequent workdays, for the meal schedule of the intervention phase. (I) Shifts from weekend meals caused by the EG intervention. Paired t-test, n=65, *** p ≤ 0. 001, **** p ≤ 0. 0001. Data are normalized so that all baseline data at T0-T1 equal 0 to represent the change in hours. Detailed statistics in Table S11. (J) Large phase shifts of breakfast and dinner, equivalent to a correction of the social jetlag of meals on weekends, are related to greater weight loss. Linear regression, breakfast: n=55, lunch: n=64, dinner: n=63, ** p ≤ 0. 01. Missing n-numbers are due to incomplete diary entries on weekends during the exploratory phase or because participants usually did not have a particular meal. Detailed statistics in Table S6. (K) Results of a multiple regression to investigate the influence of individual variables while holding the others constant on the BMI of EG participants. The Quantile-Quantile (QQ) plot shows the data are normally distributed (left). The multiple regression plot and R2 value shows that the multiple regression model explains the data well (middle). Additionally, the assignment of each regression beta coefficient to the independent variables is shown along with the p-values showing the influence on BMI. The data used are the same as those used in the individual regressions shown previously. Detailed statistics in Tab. S9. (L) Covariance matrix with normalized covariances for each pair of parameters. Values close to 1 (blue) or -1 (red) indicate high intertwining of the data, values close to 0 (white) indicate independence or orthogonality of the data. The assignment of the coefficients to the independent variables is the same as in (K). 2. 8. Effect of meal schedule personalization on weight lossA key part of our hypothesis involves the personalization of meal schedules. Consistent with the concept of social jet lag, our data show that during the exploration phase, eating times on workdays differ from those on work-free days, and we expect eating times on non-workdays to correspond more closely to individual circadian characteristics. [SEP] Justify:

Output: The text contrasts the claim by indicating that while meal schedule personalization is associated with weight loss, it does not guarantee one can eat anything without gaining weight. The mention of 'eating times on workdays differ from those on work-free days' and the exploration of 'individual circadian characteristics' suggests that personal dietary habits and timing influence weight rather than genetic profile alone.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0. 01)Number of plots (n)878559Enzyme. Enzyme activity (pmol min−1 mm−2). . Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0. [SEP] Justify:

Output: The text does not directly address the claim regarding the role of fungi in decomposing organic matter and nutrient cycling. It instead presents enzyme activity data and various metrics related to different fungal species without discussing their environmental roles, thus making the content irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: This observation is consistent with divergent macroevolutionary patterns of body shape diversification in tadpoles versus adult frogs [6]. A comparison of whole-body and whole-eye transcriptomes in both M. betsileanus and L. sphenocephalus would clarify whether the observed differences in the degree of differential expression are species or tissue specific. Other examples of decoupling in gene expression come from insects [4, 73,74,75]. For instance, in the hymenopteran Neodiprion lecontei, which has multiple life stages separated by increasingly dramatic metamorphic transitions, Herrig, et al. [75] found that a progressively greater proportion of genes (up to 31%) were differentially expressed between each successive pair of stages. That observation matched the authors’ predictions that gene expression decoupling would be strongest between the most ecologically dissimilar life stages. Consequently, we propose that expression may be more strongly coupled in frog species that remain aquatic after metamorphosis or in those that do not have a tadpole life stage and instead complete development within the egg and hatch as juvenile frogs (direct development). Studies comparing species that differ in life history and with finer scale ontogenetic sampling are needed to test this hypothesis. Furthermore, studies of immune system activity in Drosophila found support for both coupled and decoupled expression of different immune genes [4], underscoring the need for more detailed studies even within broad functional classes of genes. Although our results have interesting implications for the broad decoupling of gene expression between tadpoles and juveniles, our focus was on visual genes. We found that the visual system was disproportionately decoupled compared to the full eye transcriptome, with significant differential expression between tadpole and juvenile frogs in over half of the visual genes we analyzed. This suggests the visual system may be particularly strongly adapted, through decoupling, to the larval and adult environments. Teleost fishes also show differences in visual gene expression across ontogeny, specifically with regard to visual opsin expression, when larval habitat or foraging differs from that of adults [40]. Changes in expression patterns of other visual genes in teleosts remain to be evaluated, but we expect considerable variation in those taxa with distinct larval and adult ecologies. [SEP] Justify:

Output: The text corroborates the claim by discussing the transformation processes of amphibians, particularly frogs, from a larval stage (tadpoles) to juvenile forms. It highlights the differential expression of genes between these life stages, indicating an adaptation to both aquatic and terrestrial environments. This supports the essential aspect of amphibian metamorphosis, which includes a significant developmental transition that aligns with the claim about their life cycle.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Indeed, our data show that the later the chronotype of participants (measured by the MCTQ mid-sleep phase, mSP [24]), the later their mid-eat phase (mEP) on weekends (Fig. 3E, Tab. S6), with the mSP and mEP being almost antiphasic on average (Fig. 3F, Tab. S10). The EG intervention maintains most of this relationship. However, the residuals of the regression become smaller, resulting in a model fitting the data better (Fig. 3E, Tab. S6). Interestingly, the closer the intervention brought participants’ observed values to their individual fitted values, i. e. , the smaller the residuals became, the more weight they lost (Fig. 3G, Tab. S6). From a clinical point of view, this indicates that a personalized adjustment of eating times to the individual chronotype, i. e. , the establishment of a highly accurate phase relation between mEP and mSP, leads to a particularly effective reduction of excess weight. The calculation of individual eating times was based on the frequency of hours at which meals were eaten during the exploration phase, which typically included more workdays than non-workdays (Fig. 3H). Consequently, for some subjects, the EG intervention created a discrepancy between what may have been physiologically optimal eating times, reflected by weekend data, and the calculated eating times (Fig. 3I, Tab. S11). However, the magnitude of this discrepancy has no effect on weight changes (Fig. S2O, Tab. S6). On the contrary, if the calculated eating times resulted in large shifts of the weekend meals, this also means that previously particularly large “meal jet lags” between working and non-working days were eliminated. Indeed, the more the calculated eating times led to an advance of the first meal and a delay of the last meal, thus the greater the effect of the “meal jet lag” elimination was, the more the participants lost weight (Fig. 3J, Tab. S6). Interestingly, this also includes the elimination of too early dinners on work days. Our data show that a later dinner on all days of the week can lead to weight loss if this time corresponds to the calculated individual optimal time. The independent variables used above for simple regressions may influence each other and therefore their influence on BMI may be confounded. [SEP] Justify:

Output: The text contrasts the claim by indicating that personalized adjustments to eating times based on individual chronotypes can lead to weight loss, but it does not support the idea that one can eat anything without gaining weight as long as it fits a genetic profile. Instead, it suggests a structured approach to meal timing is necessary for effective weight management, highlighting that the relationship between meal timing and weight loss is potentially complex and not as straightforward as the claim implies.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 63 (0. 28) b1. 09 (0. 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0. 01)Number of plots (n)878559Data are provided as means (n=number of plots the tip genera were isolated from. Note that not all genera were found in all plots) with s. d. in brackets. Data in the same row with different letters are significantly different at P<0. 01. Refer to Table 3 for the general role of each enzyme in organic matter breakdown. aEMF, average activity of all ectomycorrhizal tips, not included in statistical analysis. bLaccase activity given in U min−1 mm−2. Enzyme activity in the sand barrier surrounding the +SB traps was either at or below the limit of detection, even though all sand contained visible hypha and diverse fungal communities (see Table 1). The +SB community (predominantly mycorrhizal) and the −SB community (saprotrophic and mycorrhizal) enzyme activity levels were in the same range as those of the FH community (Table 3). EMF-dominated +SB communities had significantly (P<0. 01) higher levels of phenol oxidase (L-DOPA assay) and aminopeptidase activity than −SB or FH communities, and higher peroxidase activity and β-1,4-glucosidase than −SB communities. Activities of all other enzymes did not differ among fungal communities. Enzyme activities associated with EMF tips were highly variable within a given genus, resulting in few significant differences between genera (Table 4). Nevertheless, Amphinema tips had significantly higher (P<0. [SEP] Justify:

Output: The text provides a detailed analysis of enzyme activities related to fungal communities but does not explicitly mention fungi decomposing organic matter or their role in nutrient cycling. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: Thus, our differential expression and MSP results provide evidence for the role of CYP27C1 in switching chromophore usage and, correspondingly, spectral sensitivity during ontogeny. Several species of frog that transition from aquatic tadpoles to terrestrial or semi-terrestrial adults, including the tree frogs Hyla regilla and H. arborea, several other Lithobates species (L. catesbeianus, L. clamitans, L. esculenta, L. pipiens, L. sphenocephalus), Rana species (R. temporaria, R. arvalis), European fire-bellied toad (Bombina bombina), and common spadefoot (Pelobates fuscus) shift their chromophore usage from primarily A2 to primarily A1 at metamorphosis [34, 53, 80,81,82]. The timing of the shift between chromophores in rods varies, with some species (H. arborea and B. bombina) showing a continuous change from A2 to A1 during tadpole development, while in other species (P. fuscus and R. arvalis), the shift does not occur until the appearance of forelimbs [82]. Our data suggest the possibility that the transition may begin at Gosner stage 35–38 in leopard frogs based on the relatively lower CYP27C1 expression compared to the earlier stages (25–34), even accounting for dark exposure. More data will be needed, however, to further evaluate this timing. In H. arborea, the transition from A2 to A1 was complete post-metamorphosis, with juveniles and adults having the same spectral sensitivities [82]. Our data suggest some juvenile leopard frogs maintain a small proportion of A2 pigment based on continued expression of CYP27C1, while other specimens showed no expression and thus would be expected to have no A2 pigment. By contrast, the toads Bufo boreas and B. bufo appear to use only A1 as both aquatic tadpoles and terrestrial adults [80, 83], and X. laevis, which remain fully aquatic as adults, use exclusively A2 pigments at both life stages [36]. [SEP] Justify:

Output: The text corroborates the claim by providing specific examples of several frog species that transition from aquatic tadpoles to terrestrial or semi-terrestrial adults. It mentions species like Hyla regilla, H. arborea, and several Lithobates and Rana species that exhibit this metamorphosis, thus supporting the assertion made in the claim.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Therefore, a multiple regression with the most important and least multicollinear variables (ΔMTVS, ΔkJ, Δcalorie intake interval, ΔmSp-mEP relation, Δweekend breakfast, Δweekend dinner) was done to study their individual influences on the BMI of EG participants while keeping the other variables constant. According to this analysis, only the change in MTVS and also the resulting elimination of “dinner jet lags” have significant influence on the BMI (Fig. 3K, Tab. S9). The elimination of “breakfast jet lags” and the improvement of the mSP-mEP ratio did not reach significance but showed a strong tendency to influence BMI. Changes in caloric intake or the time interval during which food is consumed had no effect on the BMI. A concurrent analysis of covariance shows that MTVS is most strongly intertwined with BMI, while other variables play a role to a much lesser extent (Fig. 3L). 2. 9. General well-being outcomesSince stable circadian rhythms are generally associated with many aspects of health, regular entrainment of a variety of peripheral and brain clocks by the Zeitgeber food may enhance overall well-being. To test this, participants were asked to complete clinical questionnaires measuring subjective health status, sleep quality, depressed mood, and self-efficacy at T0 and at T2. In addition, chronotype was also determined. Many aspects of subjective physical well-being (SF-36 - physical health items) improved significantly during the intervention in the EG (Fig. 4A, Tab. S3), reversing previous differences between CG and EG. In contrast, there was only a slight improvement in the general health item within the CG. In addition, sleep quality (PSQI) of the EG group improved significantly during the intervention, but not of the CG group, again eliminating prior differences between CG and EG. Furthermore, mental health, including vitality, depressed mood, and self-efficacy (SF-36 mental health items, IDS-SR, SWE) also improved significantly in EG participants, but not in the CG (Fig. 4A, Tab. S3). Consistent with our aim to optimize rather than to change individual rhythms, chronotype did not change during the study (Fig. 4B, Tab. S3). Fig. 4:Improvement in overall well-being over the course of the study. [SEP] Justify:

Output: The text contrasts the claim by analyzing factors influencing BMI and states that changes in caloric intake or the timing of food consumption had no effect on BMI. This suggests that personalized nutrition, as implied in the claim, does not guarantee weight maintenance without regard to caloric intake, contradicting the idea that one can eat anything without gaining weight so long as it fits their genetic profile.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 1007/s00572-012-0438-y. 10. 1093/bioinformatics/btq281. 10. 1038/ismej. 2009. 77. 10. 1038/ismej. 2011. 52. 886. 13): Establishment and progress report. B. C. Ministry of Forests, Victoria. 018. Available at. 454 Pyrosequencing analyses of forest soils reveal an unexpectedly high fungal diversity. New Phytol. 2009;184:449–456 10. 1111/j. 1469-8137. 2009. 03003. x. 10. 1007/s00572-002-0162-0. 10. 1016/j. soilbio. 2011. 12. 029. 2. Science. 2012;31:1084–1087 10. 1126/science. 1224304. 10. 1890/08-0137. 1. 10. 1016/j. soilbio. 2009. 12. 006. 10. 1111/j. 1469-8137. 2005. 01401. x. 10. 1038/ngeo1009. 10. 1093/forestry/cps003. 2. Acad Sci. 2010;107:10938–10942 2890735 10. 1073/pnas. 0912421107. 10. 1111/j. 1469-8137. 1994. tb02976. x. 10. 1016/j. chemosphere. 2012. 03. 019. 10. 1007/s11104-013-1630-3. 10. 1016/S0953-7562(09)80936-2. 10. 1111/j. 1469-8137. 1991. tb00004. x. 10. 1890/04-1254. 9373. 10. 1139/x06-063. 10. 1111/j. 1365-294X. 1993. tb00005. x. 10. 1016/j. soilbio. 2011. 03. 017. 10. 1002/(SICI)1521-4028(199807)38:3<197::AID-JOBM197>3. 0. CO;2-W. 10. 1111/j. 1462-2920. 2011. 02550. x. [SEP] Justify:

Output: The text does not provide any information relevant to the claim regarding fungi decomposing organic matter or their role in nutrient cycling. Instead, the text comprises a list of DOI (Digital Object Identifier) citations without context, which makes it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: The mechanism that controls ontogenetic changes in CYP27C1 expression, and thus, the switch from A2 to A1 chromophore (or vice versa) is not known but appears to involve thyroid hormone signaling. In most teleost fishes that have been studied, the application of thyroid hormone results in an increase in A2 chromophore, but in bullfrog, it results in a reduction in A2 [79]. In frogs, application of thyroid hormone can trigger or accelerate metamorphosis, which in turn results in the shift from A2 to A1 in some species but not others [34] raising the question of how this difference among species is controlled. Additional studies quantifying ontogenetic variation in chromophore usage and CYP27C1 expression across a greater diversity of frogs may provide a better understanding of the underlying mechanisms and how this trait is associated with changes in visual ecology across species. Light exposure can also affect the proportion of A1 to A2 chromophore in the eye. This pattern has been demonstrated as a reversible change in tadpoles of several species of Lithobates, where exposure to darkness over extended periods (weeks to over a month) decreased the proportion of A2 chromophore, which could be reversed to near normal levels in as little as 24–48 h of constant illumination [81, 84]. We found that CYP27C1 expression was significantly reduced in dark-exposed compared to light-exposed tadpoles (12 h of exposure), which suggests CYP27C1 expression is light-dependent in tadpoles and that reduced CYP27C1 expression upon dark exposure results in a lower proportion of A2-based visual pigments. A potential mechanism for light-dependent expression of CYP27C1 is unknown, but previous experiments suggest this response can be localized to a single eye. Specifically, Bridges [81] found that exposing tadpoles to light after a period of darkness resulted in an increase in A2 in unobstructed eyes, but not in eyes that were covered and thus unexposed to light. The functional benefit of this change may be related to the lower dark noise (thermal activations in the absence of photon absorbance) of A1 pigments compared to A2 pigments, resulting in higher light sensitivity of A1 pigments [85]. [SEP] Justify:

Output: The text corroborates the claim by discussing the role of thyroid hormone signaling in frogs, particularly in the context of metamorphosis. It mentions that application of thyroid hormone can trigger or accelerate metamorphosis in frogs, which directly supports the claim that frogs undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. The reference to metamorphosis and its hormonal control indicates that the text aligns well with the claim about the life cycle changes in amphibians.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: (A) Significant improvements are observed in various aspects of physical and mental health (SF-36), sleep quality (PSQI), depressed mood (IDS-SR), and self-efficacy (SWE) in participants of the EG (colored columns), but hardly among CG participants (gray columns). Scales are either upward or downward, depending on whether low or high scores on the questionnaires mean subjectively good or poor well-being. (B) The chronotype of EG and CG participants did not change during the study. 2-way repeated-measures ANOVA with Bonferroni post hoc test comparing CG and EG during the exploration or intervention phase and T0-T1 and T1-T2 within groups, * p ≤ 0. 05, ** p ≤ 0. 01, *** p ≤ 0. 001, **** p ≤ 0. 0001. CG: n=33; EG: n=67. Detailed statistics in Tab. S3. 3. DiscussionIn our study, we show that increased regularity of the Zeitgeber food can lead to a significant reduction in body weight. Although the diary entries of some participants show that they changed their energy intake and also the food composition of fat, carbohydrates and proteins during the study, the observed weight loss is not related to these changes. Related results have already been shown in mice, although here with a restriction to the entire active phase rather than specific eating times. Not surprisingly, mice gain weight and develop diabetes-like states under a high-fat diet [17]. It is surprising, however, that the negative physiological consequences of the high-fat diet can be almost completely prevented if the mice consume the equivalent amounts of high-fat food exclusively during their activity phase and do not receive any food during their sleep phase [17, 25]. In our study, an increase in the regularity of lunch, and somewhat more strongly that of dinner, is related to weight loss, which to some extent contrasts with previously published data in which increased regularity of breakfast in particular, and not so much that of dinner, was identified as a predictor of weight loss [26]. Besides increased regularity, our intervention has additional effects on eating behavior, such as shortening the hours in which food is eaten, which in our study is not related to weight loss. [SEP] Justify:

Output: The text contrasts the claim by indicating that while increased regularity of meals may lead to significant body weight reduction, the changes in energy intake and food composition were shown not to be related to the observed weight loss. This suggests that simply fitting food choices to a genetic profile does not guarantee weight management, as other factors such as meal timing may play a critical role in weight regulation.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 10. 1023/A:1024719607740. 10. 1111/j. 1574-6941. 2002. tb00915. x. 9. 10. 1007/s10021-008-9186-4. 10. 1111/j. 1365-2486. 2011. 02627. x. 10. 1016/j. mycres. 2007. 11. 008. 10. 1111/j. 1469-8137. 2006. 01742. x. 10. 1038/35035065. 10. 1175/JCLI-D-12-00089. 1. 10. 1046/j. 1469-8137. 2002. 00417. x. 10. 1093/bioinformatics/btq003. 10. 1139/x97-160. 10. 1016/j. apsoil. 2012. 01. 010. 10. 1111/j. 1365-2435. 2010. 01699. x. 10. 1371/journal. pone. 0010971. 10. 4141/P05-164. 10. 1111/j. 1574-6941. 2006. 00166. x. 10. 1016/j. soilbio. 2011. 01. 022. 10. 1111/j. 1469-8137. 2006. 01957. x. 10. 1639/0007-2745(2003)106[0080:]2. 0. CO;2. 10. 1093/treephys/21. 2-3. 71. 10. 1016/0038-0717(91)90193-N. 10. 1111/j. 1469-8137. 2006. 01936. x. 10. 1016/j. soilbio. 2004. 02. 017. 10. 1038/nature06556. 10. 1038/nature08867. 6. 0. 2011 MjM Software:. 10. 1007/s00572-005-0011-z. 10. 1017/CBO9780511977022. 10. 1073/pnas. 261555198 64936. 10. 1016/j. fgb. 2009. 02. 001. 10. 1016/j. funeco. 2010. 05. 002. 10. 1073/pnas. [SEP] Justify:

Output: The text provided consists solely of DOI references and does not contain any information relevant to the claim regarding the role of fungi in decomposing organic matter or nutrient cycling. Therefore, it is deemed irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: Thus, exposure to dark conditions could result in increased overall light sensitivity of the tadpole through reduced expression of CYP27C1, which in turn reduces the production of A2 chromophore and, correspondingly, increases the proportion of the higher-sensitivity A1 pigments. This interpretation is perhaps confounded by the observation that some teleost fishes have the opposite reaction to dark exposure, where the proportion of A2 pigment increases [34], although at least one teleost species has the same response as tadpoles [86]. This variation suggests there may be other factors beyond spectral tuning and light sensitivity that influence chromophore usage. Visual opsins and phototransduction genes are differentially expressed between life stagesDifferential expression of visual opsins and phototransduction genes is a second approach that organisms can employ to adapt the sensitivity of their visual system to changes in the light environment. Studies investigating the evolutionary and ecological context of this particular strategy in vertebrates have largely been restricted to the visual opsins of teleost fishes, which tend to have many more (duplicated) copies of these genes than do tetrapods [40]. Some teleost species express only a subset of their total visual opsin repertoire during a particular life stage, which is likely beneficial when larval habitat and associated traits, such as foraging behavior, differ from those of adults [40]. Most frog species make even more dramatic transitions in habitat and foraging behavior across ontogeny, but with far fewer opsins to choose from, their ability to use distinct opsins for larval and adult vision is likely more constrained. Despite this, we found differential expression between tadpoles and adults in two of their four visual opsin genes (SWS2 and LWS). In frogs and salamanders, SWS2 is expressed in blue-absorbing “green” rods (SWS2 rods), a unique type of rod not found in other vertebrates that, at least in some species, enables color vision at scotopic light levels when cones are inactive [87]. The increased expression of SWS2 in juvenile leopard frogs suggests an increased proportion of SWS2 rods in the retinas of juveniles relative to tadpoles, which may reflect increased reliance on nocturnal color vision in terrestrial life stages. [SEP] Justify:

Output: The text corroborates the claim by discussing the differential expression of visual opsins and phototransduction genes, which reflects changes that occur as frogs transition from their larval stage (tadpoles) to adult forms. It highlights the increased reliance on nocturnal color vision in terrestrial life stages, indicating a developmental progression that aligns with the concept of metamorphosis in amphibians, such as frogs.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: This is similar to the principle of 16:8 intermitted fasting or time-restricted eating (TRE), in which meals are taken only specific time window, yet at unspecified times during that period. The effects of these protocols is mixed and often less pronounced, as less [21, 23, 27] weight loss or a longer period is required to achieve similar results [22] than in our study - with the caveat that more overweight and older participants participated in these studies than in ours. However, other studies have also explored the effect of restricting individual meals to specific times. In mice, restricting the same amount of high-fat chow to two times per day reduces the development of obesity [28]. And in humans, restricting meals to three fixed, uniform times leads to similar weight loss like we observed in our study - but in combination with calorie reduction and standardized food [29]. The fact that our participants lost weight to a similar extent despite free choice of meals could be due to the individual tailoring of meal schedules. It is true that our data show that scheduling single meals to supposedly circadian optimal eating times of the participants is not essential for successful weight loss. Circadian clocks can flexibly adjust to Zeitgebers and it is apparently more important to choose a time when individuals (have to) eat particularly frequently than the exact genetically determined eating time. However, our data still show that personalization of meal schedules is nevertheless useful. First, depending on the individual chronotype of the participants, their mealtime windows were earlier or later in the day. And those for whom the intervention optimized this relationship were particularly effective at losing excess weight. Second, if the schedule is designed to prevent large jumps between meals, especially dinner, on workdays and work-free days, weight loss is more successful. Since food serves as a Zeitgeber for a large number of tissues, including several brain regions, it can be hypothesized that regular eating not only has a positive effect on body weight, but also on other aspects of well-being. A previous study by Panda et al. [18] has already shown that shortening the eating interval to 10-12 hours per day has a positive effect on the general well-being of the participants. Similarly, in our study, we also found significant improvements in different aspects of subjective well-being over the course of the study, specifically in physical and mental health, sleep quality, and self-efficacy. [SEP] Justify:

Output: The text contrasts the claim by explaining that while meal personalization can be beneficial for weight loss, it does not guarantee weight maintenance or loss when consuming unrestricted amounts of food. The text discusses the effects of different eating schedules and their relationship with weight loss, indicating that factors like calorie reduction and the timing of meals play crucial roles, rather than simply fitting meal choices to an individual's genetic profile. It emphasizes that personalization is useful but does not support the idea that one can eat anything without gaining weight.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 1006463107. 10. 1111/j. 1461-0248. 2011. 01611. x. 10. 1007/s00572-011-0379-x. 10. 5194/bg-9-2099-2012. 10. 1016/j. soilbio. 2006. 04. 038. 2. Ecol Lett. 2012;15:1042–1049 10. 1111/j. 1461-0248. 2012. 01827. x. 10. 1007/s11104-008-9766-2. 10. 1016/j. mimet. 2004. 04. 001. 10. 1111/j. 1574-6941. 2007. 00375. x. 45. 10. 1111/j. 1462-2920. 2012. 02736. x. 10. 1186/1471-2148-8-50. 10. 1016/S0038-0717(02)00074-3. 10. 1093/forestry/50. 2. 113. 10. 1128/AEM. 01541-09. 10. 1038/nature10386. 10. 1038/ismej. 2012. 11. 10. 1016/j. soilbio. 2009. 10. 014. 10. 1111/j. 1461-0248. 2008. 01245. x. 10. 1016/S0929-1393(03)00002-7. 10. 1111/j. 1574-6941. 2012. 01343. x. 10. 1111/j. 1365-2435. 2008. 01402. x. 10. 1016/j. soilbio. 2012. 10. 004. 10. 1111/j. 1469-8137. 2012. 04217. x. 10. 1007/s00374-010-0440-5. 10. 1016/j. soilbio. 2005. 09. 006. 10. 1007/s00572-011-0416-9. 10. 1111/1574-6976. 12001. 10. 1007/s00374-009-0413-8. 10. 1016/j. apsoil. 2012. 02. 017. 10. 1111/j. 1469-8137. 2010. 03324. x. 10. [SEP] Justify:

Output: The text does not provide any information related to the claim about fungi decomposing organic matter and contributing to nutrient cycling. It appears to be a list of DOIs, which is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Araneology focuses on the study of spiders and their relatives within the arachnid class. [SEP] Text: " Line 281: in the arachnological literature, the expression "true spiders" is used mostly to the Araneomorphae and not to the order as a whole. Line 282: "(Platnick & Raven, 2013)" -- I suggest to change this citation for the most recent version of the Catalogue ( Line 284: ". . . and the ability to produce silk" -- at least two other arachnid groups contain species that produce silk: pseudoscorpions and mites. Thus, you should to re-phrase this sentence. Line 288: "Spiders are typically characterised. . . " Line 292: are you really referring to the "Tetragnathidae" or to the "Nephilidae"? Lines 293-294: another well-reported case of reversed SSD in spiders occurs in the genus Allocosa from Uruguay. In species of this genus, males are larger than females and there are several behavioral traits that indicate sex-role reversal. Lines 306-318: I suggest to remove this paragraph because pedipalps in male spiders are sexual organs, thus you are talking about primary and not secondary sexual dimorphism. If you decide to mention all cases of primary sexual dimorphism in all arachnid orders, you will need to talk about spermatophore and penis morphology. As far as I understand, this is not the main goal of the manuscript. Thus, for the sake of consistency, you should not include sexual dimorphism related to pedipalp morphology in spiders. The only exception, according to my view, is the example of Allocosa males, which have sexually dimorphic digging structures on their pedipalps. Line 350: "conflict" -- I think the best word here is "contest". Please change it throughout the entire manuscript. Line 351: " conflict" -- I suggest to change this word for "male-male competition" or "intrasexual selection". Line 360: "and" -- non-italic. Line 387: "Parisitiformes" Lines 424-425: "The metric. . . " Lines 427: "Cranaidae and Oncopodidae" Lines 456-457: ". . . suggesting that chemical secretions may also play a role in warding off rival males" -- Although it is possible, I have never seen males releasing secretion during intrasexual fights. [SEP] Justify:

Output: The text corroborates the claim by discussing specific characteristics of spiders, such as the mention of 'true spiders' and details about sexual dimorphism in the genus Allocosa, which are related to the study of spiders in araneology. Additionally, the text shows an in-depth examination of aspects relevant to spider morphology and behavior, all of which are integral to the field of araneology.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: This shows that adhering to daily structured mealtimes can improve not only metabolic but also other physical and also psychological levels of health. There are several explanatory approaches for why increased meal regularity can lead to weight loss despite equal caloric intake. For example, circadian clocks influence the composition of the microbiome, which regulates metabolic balance and body weight [30–34]. Additionally, circadian clocks help to anticipate mealtimes and provide the necessary digestive components in advance of food intake in advance [35–38]. Accordingly, the number of rhythmic genes in the liver of mice increases from ∼350 to ∼3,000 when the animals can follow their natural feeding rhythm and even to ∼5,000 when the feeding time is restricted to a certain period of time [39]. 3. 1. LimitationsHowever, in our study, we did not collect metabolic parameters that could provide mechanistic explanations for the observed weight loss. Therefore, the assumption of an optimized metabolism remains speculation. Another limitation of the study is the self-assessment of key data on body weight, eating times, and food composition. Body weight could not be collected in our clinic under supervision because of the Covid-19 pandemic. Regarding food intake, some participants underreported during the study, as indicated by unrealistically low kJ intakes. However, the individual reporting behavior of each participant remained largely the same during the exploration and intervention phases, so underreporting is not indicative of a change in eating behavior and, conversely, the observed kJ differences are likely due to actual changes in eating behavior. In addition, in the remaining evaluable 100 study participants, there was a significant difference in baseline body weight and BMI between CG and EG. However, even if CG participants had been heavier from the start, it cannot be assumed that the applied sham treatment with an eating window of 18 hours during wake time would have had a stronger effect. Second, those subjects in the EG group whose baseline BMI was similar to those of the CG subjects lost significant weight during the intervention, while CG participants did not. Taking these two arguments into account, it cannot be assumed that a floor effect, in which the CG participants cannot lose any more weight due to a lower baseline weight, is the reason for the lack of weight loss in the CG. Lasty, studies show that even much larger baseline BMI differences do hardly affect the success of weight loss programs [40, 41], so we assume that this also applies to our study. [SEP] Justify:

Output: The text contrasts the claim by presenting evidence that structured mealtimes and circadian influences on metabolism are crucial for weight loss, rather than solely focusing on a personalized genetic diet. It specifies limitations in attributing weight loss to personalized nutrition, indicating that relying on genetics alone does not guarantee one can eat anything without gaining weight, as other factors must be considered.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Create a new account user Can't sign in? Forgot your username? Enter your email address below and we will send you your username Email* the address matches an existing account you will receive an email with instructions to retrieve your username close | or * Password* Forgot password? Reset it here Keep me logged in All fields with * are mandatory Email* All fields with * are mandatory Already have an account? Login here password must have 8 characters or more and contain 3 of the following: a lower case character, an upper case character, a special character or a digit password has been changed Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions Email* the address matches an existing account you will receive an email with instructions to reset your password the verification code Cancel Congrats! has been verified close 10. 1139/x83-031 Get AccessContentsof Forest Research, Number 2April 19831983. Contribution of mycorrhizae and soil fungi to nutrient cycling in a Douglas-fir ecosystem. of Forest Research. 13(2): 219-232. Export 1. Species-specific reliance of trees on ectomycorrhizal fungi for nitrogen supply at an alpine treeline Go to 2. Fungi rather than bacteria drive early mass loss from fungal necromass regardless of p3. Thinning effects on biomass and element concentrations of roots in adjacent hornbeam and oak stands in Istanbul, to 4. Evidence for a fungal loop in shrublands Go to 5. The Rhizosphere/to 6. Accounting for to Discrepancies in to 7. Rapid changes in the chemical composition of degrading ectomycorrhizal fungal necromass Go to 8. to for Global Change: and the to 9. Effects of bedrock type and soil chemistry on the fine roots of European beech – A study on the belowground plasticity of trees Go to 10. () Go to 11. Harvesting Douglas-fir Activity and Go to 12. The effect of environmental contamination on the community structure and fructification of ectomycorrhizal fungi Go to 13. Go to 14. Contribution of understorey vegetation and soil processes to boreal forest isoprenoid exchange Go to 15. Second‐generation molecular understanding of mycorrhizas in soil ecosystems Go to 16. Available for Go to 17. [SEP] Justify:

Output: The text is largely irrelevant to the claim. It consists of user account management instructions and does not provide any information or context relating to the role of fungi in decomposing organic matter or nutrient cycling.


Input: Task: pass the claim using the given text. Claim: Spiders have unique adaptations, such as hydraulic pressure in their legs, which helps them move. [SEP] Text: & Sanchez, N. E. (2013). Short and long-term effects of three neurotoxic insecticides on biological and behavioural attributes of the orb-web spider Alpaida venilae (Araneae, Araneidae): implications for IPM programs. — Ecotoxicology 22: 1155-1164. )| falseSearch 26. Bergthaler, G. J. (1995). The cocoon of Argiope bruennichi (Scopoli, 1772) — a SEM study. — In: 15th European collequium of arachnology (Ruzicka, V. , ed. ). Institute of Entomology, Ceske Budejovice, p. 22-26. )| falseSearch 3212. Blamires, S. J. (2010). Plasticity in extended phenotypes: orb web architectural responses to variations in prey parameters. — J. Exp. Biol. 213: 3207-3212. )| falseSearch 279. Bridge, A. P. , Elwood, R. W. & Dick, J. T. A. (2000). Imperfect assessment and limited information preclude optimal strategies in male-male fights in the orb-weaving spider Metellina mengei. — Proc. Roy. Soc. Lond. B: Biol. Sci. 267: 273-279. )| falseSearch 193. Buchli, H. H. R. (1969). Hunting behaviour in the Ctenizidae. — Am. Zool. 9: 175-193. )| falseSearch 1235. Caccone, A. (1985). Gene flow in cave arthropods: a qualitative and quantitative approach. — Evolution 39: 1223-1235. )| falseSearch 7611. Chiavazzo, E. , Isaia, M. , Mammola, S. , Lepore, E. , Ventola, L. , Asinari, P. & Pugno, N. M. (2015). Cave spiders choose optimal environmental factors with respect to the generated entropy when laying their cocoon. — Sci. Rep. 5: 7611. )| falseSearch 1051. Crespo, L. C. , Boieiro, M. , Cardoso, P. , Aguiar, C. A. S. , Amorim, I. R. [SEP] Justify:

Output: The text does not address the claim regarding spiders' unique adaptations or hydraulic pressure in their legs. It lists several studies related to spiders but does not provide any relevant information that directly corroborates or contrasts the claim.


Input: Task: contrast the claim using the given text. Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: During the course of the study, there were some drop-outs in both groups. Importantly, these did not differ in baseline weight from the completers, which is why it can be ruled out that the intervention was not effective in a particular BMI group. Rather, the subjects who dropped out were those who either could not continue due to illness or did not adhere to the meal plan. However, the inclusion of drop-outs in the analysis of weight progression does not fundamentally change the results. 3. 2. ConclusionIn summary, our data show that the increase of regularity of meals to a period of 90 min for each meal promotes a significant reduction of body weight and a significant increase of well-being within short time. Importantly, the successes achieved do not seem to be related to a reduction in calories, a change in food composition, or other eating behaviors. Additionally, we believe that this intervention poses hardly any health risks since it is most likely solely based on the optimization of metabolic processes. On the contrary, the strong increase in general well-being during the study rather indicates an improvement in health on many different levels. 4. Methods4. 1. Experimental approachThe study was a randomized controlled intervention trial with repeated measures investigating the effect of regularity of mealtimes on body weight and parameters related to overall well-being. Participants were blinded to the group assignment in that both control and experimental subjects were equally informed to participate in an intervention. The study was carried out at the Clinic for Psychiatry and Psychotherapy of the University (LMU), Munich, Germany. The study is registered at the with the trial number DRKS00021419 and was approved by the of the LMU. 4. 2. ParticipantsThe participants were recruited across Germany via flyers at universities, fitness studios, adult education centers, pharmacies, grocery stores, and via Facebook® between September 2020 and August 2021. Those interested were able to contact the study staff by phone, email, or by making an entry in an online calendar tool. Participants had to be between 18-65 years old and have a BMI ≥ 22 kg/m². A requirement for participation in the study was that no other diet was concurrently followed, and that no medication was being taken regularly that could influence appetite or weight. No participants were included who knowingly suffer from a metabolic, mental, or addictive disorder. Further exclusion criteria were pregnancy, blindness, bedriddenness, and dependence on assistance with eating. [SEP] Justify:

Output: The text contrasts the claim by discussing a study that emphasizes the significance of meal regularity on body weight reduction, rather than the ability to eat anything based on a genetic profile. The findings indicate that successful weight management is related to behavioral intervention, not merely genetic predispositions, as evidenced by statements like 'the successes achieved do not seem to be related to a reduction in calories, a change in food composition, or other eating behaviors.' This shows that personalized nutrition does not ensure weight maintenance without restriction, contradicting the claim.