Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: EMF taxon-specific activities were determined by averaging the activity of the (up to) seven EMF tips per plot, whose identities were confirmed by morphological and molecular identification. Identification of fungal communities Sequencing of ectomycorrhizal tips DNA was extracted from EMF tips using the Sigma Extract-N-Kit (Sigma-). Extraction solution (25 μl) was added to each EMF tip that was incubated at 95 °C for 10 min, after which 25 μl of dilution solution was added. The ITS1f and ITS4 primers (White et al. , 1990; Gardes and Bruns, 1993) were used to amplify the fungal ITS1, 5. 8S and ITS2 region. Each 50 μl reaction contained 1. 5 μl of template DNA, 2. 5 μl of each 10 μm primer and 25 μl GoTaq master mix (). Following an initial denaturation step of 95 °C for 3 min, amplification proceeded for 35 cycles of 94, 50 and 72 °C per min, with a final extension step of 10 min at 72 °C. PCR products were visualized on 1. 4% agarose gels (SYBR Safe; ). PCR products producing single bands were cleaned using the Mag-Bind E-Z pure (Omega Bio-tek Inc. , ) system and sequenced (Applied Biosystems; 3130xl ). If more than one band was produced (that is, from some tips morphologically identified as Cenococcum spp. ), bands were extracted from the gel using an E. Z. N. A gel extraction kit (Omega Bio-tek Inc. ) before cleanup and sequencing. Sequences were submitted for comparison with the GenBank databases using the BLAST algorithm (Altschul et al. , 1997). Sequencing of fungi in hyphal trap bag and FH substrates Total community DNA was extracted from 0. 5 g of all +SB, −SB and FH samples using the (Laboratories Inc. , ). DNA was extracted from 5 g sand samples using a previously published bead-beating method (Phillips et al. , 2006) suitable for large samples. Duplicate DNA extractions were performed for each sample and pooled. The ITS1 and partial 5. [SEP] Justify:

Output: The text does not address the claim regarding the ability of fungi to decompose organic matter. Instead, it focuses on methodological details related to the identification and sequencing of fungal communities without discussing their roles in nutrient cycling or decomposition. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Ethnobotanists often conduct fieldwork to document indigenous knowledge about plant use. [SEP] Text: They all have indigenous knowledge in treating dysmenorrhea at Botlokwa village, Limpopo Province. Three of the women were trained THPs, and five of them acquired indigenous knowledge through oral translation and observation either from the elders in the family or community or when they were treated for dysmenorrhea. Table 1 outlines the demographic data of the participants. Table 1. Demographical data of the participants. AgePractice typeYears of practiceEducational status28 yearsTHP6 yearsTeachers diploma33 yearsIKH21 yearsTeachers diploma47 yearsIKH30 yearsAdministration certificate47 yearsIKHUnsure (Teenage years)Social worker55 yearsIKH20 yearsHigh school level63 yearsTHP27 yearsRetired nurse67 yearsIKHUnsure (Teenage years)High school level89 yearsTHP53 yearsNever schooledThe data produced were rich descriptions and narratives that were oral and visual. The central theme that emerged strongly was holistic understanding of dysmenorrhea meaning and was associated to process or journey connected to women health, the description further grouped women’s health issues together. The findings showed that the participants of Batlokwa ethnicity had their own point of view towards the meaning of dysmenorrhea, which is influenced by their cultural orientation. Holistic understanding of dysmenorrhea meaningThe presented photographs and meanings attached revealed that Batlokwa women understand dysmenorrhea as a holistic illness. Dysmenorrhea is understood as not only a physical illness, but interdependent with mental, emotional, spiritual, social, economic, and environmental factors. Participant #3: “selumi” (dysmenorrhea) means that mind, body, emotion, spirit and environment are not balancing”. Participant #6: “Dysmenorrhea is addressed within a holistic approach, we consider emotional, mental, spiritual, including the environment in which the woman comes from”. Participant #8: “It is women reproductive system illness affecting body, mind, spirit, because our ways of healing looks holistically at the body, mind and spirit”. [SEP] Justify:

Output: The text corroborates the claim by describing how individuals in the Botlokwa village possess indigenous knowledge related to treating dysmenorrhea, which likely stems from fieldwork and interactions with their environment and community. The text illustrates that the understanding and treatment approaches are deeply rooted in cultural practices and oral traditions, aligning with the concept that ethnobotanists aim to document such indigenous knowledge.


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 discussing the importance of adjusting eating times to individual chronotypes for effective weight loss. It emphasizes that merely fitting food to a genetic profile without considering chronotype and meal timing may not guarantee weight maintenance, as evidenced by findings that those who aligned their eating times with their biological rhythms experienced more significant weight loss. This indicates that there are other factors influencing weight management, which contradicts the idea that personalized nutrition alone ensures weight control.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 8S regions were amplified using the ITS1f (Gardes and Bruns, 1993) and ITS2r (White et al. , 1990) primer pair (). Amplicons were generated for 454-pyrosequencing in a single-step reaction using the following fusion primers: 5′-TitaniumA-Multiplex Identifier-ITS1f-3′ and 5′-TitaniumB-ITS2r-3′ (S2). Triplicate amplifications were performed for each sample. Each 50 μl amplification reaction contained 0. 2 μm each primer, 200 μm dNTP mix, 2 mm MgSO4, 1 × PCR reaction buffer, 1 (Invitrogen) and 5, 10 or 20 ng of sample DNA. Following an initial denaturation step of 94 °C for 2 min, amplification proceeded for 35 cycles of 94 and 55 °C per 30 s, and 68 °C per min, with a final extension of 68 °C for 10 min. PCR products were visualized on 1. 4% agarose gels (SYBR Safe; Invitrogen), replicate reactions were pooled and PCR amplicons were cleaned using the Mag-Bind E–Z pure (Omega Bio-tek Inc. ) purification system. Amplicon concentration was determined spectrophotometrically (NanoDrop ND-1000 Spectrophotometer) and both concentration and purity (that is, complete removal of primer-dimers) were verified on a 1. 4% agarose gel (SYBR Safe; Invitrogen). Equimolar PCR amplicons from each sample (equivalent to 200 ng each) were pooled to create two that which were sequenced on half a plate each using the 454 platform (Roche Diagnostics, Basel, Switzerland) at the Génome Québec Innovation Center, Montreal, Quebec, Canada. Results were delivered as tag-sorted sequences, quality controlled for the presence of the complete primer-tag. Bioinformatic analysis Primer sequences were removed and additional quality filtering and trimming was performed using (Schloss et al. , 2009). Sequences with any ambiguous (N) bases, more than eight homopolymers, shorter than 180 or longer than 400 bp, or with greater than 1 bp difference in the primer sequence were removed. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses solely on the technical details of PCR amplification and sequencing procedures, without mentioning fungi or their role in decomposing organic matter or nutrient cycling.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: navigation Apply for support FAQ Be involved toggle overview Mission statement PAGES logos fellows Meeting minutes us Supporters and partners Supporters and partners organization Scientific partners -of involved Be involved mailing lists Apply to be on the SSC Write for and education Stakeholder engagement Stakeholder engagement Engaging with stakeholders guidelines Endorsed and affiliated Former initiatives and groups Data stewardship Data guidelines PAGES databases External databases webinars PAGES awardees PAGES awardees Scholarship recipients Early-Guest scientists -Menu layer 3 left side Menu layer 3 right side and integrating paleoecological and traditional knowledge to preserve the belt Gil-and > Access contents of this issue > Download this 10. 22498/pages. 30. 1. 20 Graciela Gil-Romera1,2, M. Fekadu1,3, L. Bittner4,5, M. Zech4, H. F. Lamb6,7, L. Opgenoorth1, S. Demissew3, Z. Woldu3 and G. Miehe8 African mountain biomes are social-ecological systems that provide critical ecosystem services but are at risk due to increasing human pressure and climate change. Their conservation require current-day ecological analyses, but also a long-term perspective, integrating local knowledge and paleoecology. Fire in the Afromontane biome biome is a globally important biodiversity hotspot (Burgess et al. 2007), supporting the livelihoods of more than 200 million people by providing essential natural resources and ecosystem services (e. g. protection from soil erosion and floods, and water, food and timber provision) (Solomon et al. 2019). biome covers widely scattered mountains extending from along the to Mozambique and (Fig. 1a). The biome occurs between ca. 2000 to 4000 m asl including several vegetation belts: relatively dry woodland transitioning to wetter woodland from ca. 2000 to 3000 m asl, an Ericaceous belt (EB) above 3200 m asl, and an Afroalpine biome of open shrubland and patchy grassland above 4000 m asl (Bussman 2006). African mountains have been occupied by humans for thousands of years and should be considered socio-ecological systems, wherein human agency is a key element of ecosystem dynamics. Recent studies highlight the importance of local community expertise in successful efforts to protect Afromontane vegetation (Fischer et al. 2021). [SEP] Justify:

Output: The text corroborates the claim by emphasizing the integration of local knowledge in conservation efforts, especially within socio-ecological systems like African mountain biomes. It notes the importance of 'local community expertise' in protecting Afromontane vegetation, which aligns with the idea that studying and preserving traditional knowledge is vital for conservation.


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 discussing the results of a study that shows certain dietary changes (like eliminating 'dinner jet lags') have significant influences on Body Mass Index (BMI), while other variables, such as caloric intake timing and intake amount, had no effect. This suggests that despite a personalized approach, there are specific dietary habits that can influence weight, contradicting the idea that one can eat anything without gaining weight as 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: Subsets of the excluded sequences were manually assessed for fungal group-specific biases. The quality filtered and trimmed sequences were then processed using the FungalITS extractor software (Nilsson et al. , 2010), which extracts the variable ITS1 of the nuclear ITS1 region from the sequence, thus eliminating false alignments and clusters being generated based on the conserved 18S and 5. 8S regions. The extracted ITS1 sequences were clustered at 98% (Ryberg et al. , 2008) similarity (global alignment) using CD-Hit-Est (Huang et al. , 2010). Representative sequences from all clusters (operational taxonomic unit, OTU) were used for BLAST searches against fully identified entries in INSD (Benson et al. , 2011) and UNITE (Abarenkov et al. , 2010a), using the PlutoF online server (Abarenkov et al. , 2010b). A minimum of 97% similarity across 97% of the sequence length was required for positive taxonomic identification at any level. Singleton OTUs with 100% similarity to reference sequences not otherwise identified in the data set were retained, and all other singletons were discarded before statistical analysis. All sequences, fastq formatted on the Galaxy online server (Blankenberg et al. , 2010), were deposited in the under the accession number SRP022584. All OTUs greater than four reads within the data set were placed into designated ecological function groups, determined by cross referencing Lawry and Diederich (2003), Rinaldi et al. (2008), Hibbet et al. (2000) and Moore et al. (2011). The groups were EMF, other mycorrhizal (ericoid, arbutoid, monotropoid and arbuscular) fungi, saprotrophs, pathogens, endophytes, yeasts and lichen fungi. Fungi known to belong to more than one of these groups were designated as mixed functional groups, whereas those whose ecological function is unverified were designated as functional group Unknown. Statistical analysis Before statistical analysis, 454 taxonomic data were normalized by dividing the absolute abundance of individual OTUs by total OTU’s within a sample (Gihring et al. , 2012). Data were log transformed wherever required to meet the assumptions of different statistical tests (Kenkel, 2006). [SEP] Justify:

Output: The text does not address the claim directly about fungi decomposing organic matter and their contribution to nutrient cycling. Instead, it provides a detailed description of the methodologies used for assessing fungal sequences and their taxonomic identification, without mentioning their ecological roles or contributions to nutrient cycling.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a as A Science of Knowledge: A of of Plants in Trans-Himalaya (Ladakh),. Malik, and 1 moreThis is a preprint; it has not been peer reviewed by a journal. work is licensed under a CC BY 4. 0 LicenseStatus:PostedVersion 1posted You are reading this older preprint versionRead the latest preprint version →Show more versionsAbstractBackground - The sixth anthropocene mass extinction in the last 540 million years indicates that human activities including illegal trade is the fundamental threat to the endangered species, their habitats and to the global biodiversity as well. In this context, it is paramount keeping in view the role of hotspot regions in the conservation of biodiversity and their varied potential of ethnobotanical services. The present study quantified the traditional ethnobotanical usage and people’s choices of plants and evaluated the composition, distribution, trade and conservation of plants in Ladakh region, India. Methods - During 2018-2019, ethnobotanical documentation of the plants growing in Ladakh (a part of trans-Himalaya), India, was carried out to collect information regarding different usages of plant species growing in the region through open and close-ended questionnaire surveys and interviews. Multivariate ecological community analysis was used to find the relationship between ethnobotanical usage and plant species. Results - Floristically, a total of 103 species belonging to 80 genera and 38 families were reported to be used as medicine, food, fodder, fuelwood, fragrance, dye, flavor and oil. Asteraceae was the largest family with 20% species, followed by Ranunculaceae (10% species) and Fabaceae (7% species). Three plant usage clusters were determined at a vertical distance value of 0. 4 where the clusters are distinctly separated. Preference analysis showed the highest priority of local people for medicinal use of plants followed by fodder and fuelwood. The most frequently used plant parts were leaves followed by roots and flowers. and elderly people had great familiarity with medicinal plants and their ethnic usage. The plant species harvested were sought for self-consumption (65%) and for commercial purposes (35%). [SEP] Justify:

Output: The text corroborates the claim by discussing the ethnobotanical documentation carried out to collect information regarding the diverse traditional usages of plants in the Ladakh region. It particularly highlights the role of elderly people who have a 'great familiarity with medicinal plants and their ethnic usage,' indicating that the study aims to record and preserve this specialized knowledge that could be at risk of being lost.


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 discussing the relationship between eating behavior and weight loss. It highlights that simply changing the energy intake and food composition does not correlate with observed weight loss, suggesting that factors such as the timing and regularity of meals are more significant. This evidence suggests that personalized nutrition may not guarantee weight maintenance solely based on one’s genetic profile. Furthermore, it indicates that mice maintained on a high-fat diet had negative physiological outcomes unless their feeding was regulated with respect to their activity phase, further emphasizing that just fitting dietary choices to genetics does not assure no weight gain.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Relationships between the +SB, −SB, FH and sand substrates were assessed using the statistical software package PAST (v 2. 17; Hammer et al. , 2001). Differences in taxonomy and enzyme activity were examined by analysis of variance (Welch’s analysis of variance, if variances are unequal, as assessed using the Levene statistic), followed by a Tukey or Mann–Whitney test to determine where significant differences occurred. Relationships between enzyme activities were assessed using Spearman’s r correlation test. Cluster analysis of functional and taxonomic fungal groups was performed using a correlation matrix based on Pearson’s r correlation (1-r; PAST 2. 17; Bolhuis and Stal, 2011). Species richness (S), evenness (H/ln(S)) and diversity (Fisher’s Alpha (α), Shannon (H) and Simpson’s indices) of the fungal communities were calculated using procedures available in PAST (v 2. 17; Hammer et al. , 2001). Patterns of enzyme activity were assessed by principle component analysis (PCA; Kenkel, 2006) in PC-ORD (McCune and Mefford, 2011). Relationships between enzyme activity and community structure were assessed by regressing enzyme PCA-loading factors with fungal community abundance (log transformed). Fungal communities significantly (P<0. 05) associated with patterns of enzyme activity were illustrated as joint plot vectors overlaid on the enzyme ordinations (Ramette, 2007). sequencing statistics A total of 1 151 401 sequences were generated by pyrosequencing the ITS1 region of DNA extracted from hyphal trap substrates, barrier sand and forest floor samples. Quality filtering removed 362 946 sequences, primarily due to length constraints or lack of a complete primer sequence, leaving a total of 788 455 ITS1 region sequences for analysis. The 36 individually assessed samples generated an average of 32 000 sequences and an average of 22 000 quality filtered sequences (S3). Clustering at 98% similarity resulted in an average of 546 OTUs per sample (singletons included), with rarefaction curves for most samples beginning to plateau (S2). The use of a stringent 98% clustering level meant that some similar OTUs were split into different clusters. [SEP] Justify:

Output: The text is largely focused on statistical analyses and methodologies used in studying fungal communities and enzyme activities, but it does not provide any direct information about fungi's ability to decompose organic matter or contribute to nutrient cycling. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: Conclusions - The present study provides unique information regarding the ethnobotanical knowledge in Ladakh region and baseline data for future researchers, policymakers, public, land managers, and the other stakeholders to develop scientifically-informed strategies for conservation of natural resources and sustainable use of plant diversity in hotspot regions like trans-Himalayas and other similar biodiversity-rich sites. Translational MedicineEthnobotanical usagemedicinal plantshotspot biodiversityAmchisChord diagramFiguresFigure 1Figure 2Figure 3Figure 4Figure 5Figure 6ancient times, through “trial and error” and experience, mankind across the world has learned and practiced the usage of medicinal plants growing in their surroundings for treating different ailments [1–2]. Ethno-medical practices are considered as the mother of all the traditional systems of medicines like Unani, Siddha, Ayurveda, Sowa-Rigpa or Amchi and even to modern allopathic system [3]. It has been found that more than 80% of people living in the third world countries are dependent on the plant-based medicines for their traditional medicines [4] and people from Africa, Asia, Central and are mainly dependent on these plant-based medicines for treating various diseases [5]. Most of the medicinal preparations used in the modern allopathic system derive their origin from plants and are mainly encouraged because of their use in traditional folklore for treating various ailments [6–7]. Furthermore, modern pharmacopeia contains about 25% drug preparation derived from plants and are mainly synthetic analogs prepared on prototype compounds having plant origin. It has been projected that the trade of these medicinal and aromatic plants in the healthcare industry costs about $60 billion annually [8] and may reach $5 trillion by 2050 [9] due to increasing recognition of plant-derived medicines [10]. This popularity of these plant-based medicines is because of their less side-effects than the allopathic medicines [11]. Many of the modern medicines used today find their origin in folk-use and indigenous cultures [12–13]. Hence the source of this traditional information about these medicinal plants is possessed by these indigenous cultures and this information survives due to its transfer through generations [1]. However, due to cultural transformation land use change and deforestation, the facility of modern health care and rapid urban development has changed the distribution of these indigenous cultures disturbing the transformation of traditional knowledge about medicinal plants [14]. [SEP] Justify:

Output: The text corroborates the claim by outlining the importance of ethnobotanical knowledge in preserving traditional medicinal practices and cultural heritage. It mentions that traditional information about medicinal plants is passed down through generations among indigenous cultures and that such knowledge is essential for the development of conservation strategies. The text discusses the challenges to this knowledge due to factors like cultural transformation and land use change, highlighting the necessity of studying ethnobotany to maintain this valuable traditional knowledge.


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 discussing the mixed effects of meal timing and individual tailoring of meal schedules on weight loss, implying that simply fitting a genetic profile does not guarantee that one can eat anything without gaining weight. The emphasis on calorie reduction and standardized food alongside individual meal timing, as well as the need for a schedule that prevents large jumps between meals, suggests that weight loss requires more structured control than merely following a personalized nutrition plan based on genetics.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Open in new tabDownload slideThe lowest richness and diversity occurred in −SB communities, which had significantly fewer fungal taxa than the FH samples (Table 1). The FH communities had the highest level of diversity; however, all communities were populated by a few relatively abundant taxa (Table 2). Notably, the Fungi I. sedis saprotroph Mortierella was the single-most abundant taxon (44% of sequences) found in −SB communities. By contrast, Mortierella spp. accounted for only 8% of sequences in FH and +SB communities and 16% of sequences in sand communities. Instead, these communities were largely dominated by EMF, including Piloderma spp. (FH, 32% of sequences) and Amphinema spp. (+SB, 34% of sequences; and sand, 28% of sequences). spp. were the dominant EMF found in the in situ FH layer, Amphinema spp. and Wilcoxina spp. were better able to colonize both types of hyphal traps. Table 1 Open in new tab Genus level fungal richness and diversity estimates. Richness (S). Evenness (H/ln(S)). Shannon (H). Simpson (D). Fisher’s Alpha (α). −SB92. 7 (15. 2) b0. 436 (0. 104)1. 99 (0. 52)0. 707 (0. 184)12. 2 (2. 1) cFH110. 3 (12. 8) a0. 494 (0. 038)2. 32 (0. 21)0. 817 (0. 031)15. 4 (1. 7) a+SB98. 4 (7. 0) ab0. 467 (0. 112)2. 14 (0. 52)0. 761 (0. 112)13. 3 (1. 1) bcSand102. 7 (9. 9) ab0. 501 (0. 060)2. 32 (0. 29)0. 794 (0. 056)14. 2 (1. 4) ab. Richness (S). Evenness (H/ln(S)). Shannon (H). Simpson (D). Fisher’s Alpha (α). −SB92. 7 (15. 2) b0. [SEP] Justify:

Output: The text primarily discusses fungal diversity and richness in different communities but does not directly address the role of fungi in decomposing organic matter or nutrient cycling. While it mentions specific fungal taxa, such as Mortierella and EMF (Ectomycorrhizal fungi), it lacks any reference to their ecological functions, thus making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: Ethnobotanical analyses have developed a key association among traditional knowledge, indigenous people and use of plants [15–17]. The ethnic tribal communities have adopted local plants as the traditional means of healing systems and are broadly used by all sections of the community, whether directly as folk remedies or the medicaments of the different indigenous systems as well as in modern medicine system [18–19]. The traditional information occupies a vital position at the global level right from the primitive past to the present [20]. Indigenous communities have been utilizing plant sources for a variety of purposes over many generations [21]. Ethnobotanical research explores avenues how the medicinal plants are used in culture, subsistence, primary health care [22], drug discovery and conservation [18, 19]. During the last century, the field of ethnobotany has progressed significantly and now this field is shifting from simple documentation to a more practical one, which gives importance to the conservation and sustainable management of medicinal flora [23]. (IHR), occupying about 18% area of India, is considered as one of the mega hotspots of the world [24]. It has been reported that about 1289 plants belonging to 960 taxa and 560 genera are under medicinal trade in India, various parts of which are sold and used across India. The utilization of these medicinal plants in the of Medicines (ISM) includes 328 in Unani, 688 in Ayurveda, 146 in Homeopathy, 501 in Sidda, and 197 in Tibetan [25]. Ladakh region, part of trans-Himalaya, is a hub of medicinal, aromatic and other economically important plants [26]. However, the ethnobotanical studies of this region are meager. Also, the floristic diversity of the region is under continuous pressure by local inhabitants, tourists, overgrazing and various developmental projects. Keeping in view the role of the region in the conservation of biodiversity and its varied potential of ethnobotanical services into account, the present study was conducted with the specific aim of quantifying the traditional ethnobotanical usage of plants in Ladakh region. The results of the present study will provide baseline data for future researchers, policymakers, common public, land managers, and the other stakeholders to develop scientifically informed strategies for conservation of natural resources and sustainable use of plant diversity in this trans-Himalayan region. Ethnobotanical field survey may be an alternative to document and conserve this imperative knowledge before it disappears. [SEP] Justify:

Output: The text corroborates the claim by discussing the importance of ethnobotanical research in documenting traditional knowledge among indigenous communities. It highlights how these communities utilize plant sources for various purposes, suggesting that ethnobotanical studies not only document this knowledge but also help in its conservation and sustainable management. The references to the necessity of preserving traditional ethnobotanical usage in Ladakh, particularly due to pressures from modern influences, directly support the idea that ethnobotany is crucial for preserving knowledge that could be lost.


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 discussing the importance of structured mealtimes and metabolic factors influencing weight loss, indicating that simply fitting food into a genetic profile does not guarantee weight management. It highlights limitations in assumptions about metabolism and the impact of meal timing, suggesting that personal nutrition cannot assure weight maintenance without considering broader metabolic and behavioral influences.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 436 (0. 104)1. 99 (0. 52)0. 707 (0. 184)12. 2 (2. 1) cFH110. 3 (12. 8) a0. 494 (0. 038)2. 32 (0. 21)0. 817 (0. 031)15. 4 (1. 7) a+SB98. 4 (7. 0) ab0. 467 (0. 112)2. 14 (0. 52)0. 761 (0. 112)13. 3 (1. 1) bcSand102. 7 (9. 9) ab0. 501 (0. 060)2. 32 (0. 29)0. 794 (0. 056)14. 2 (1. 4) abAbbreviations: FH, in situ fermentation-humic layer; −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 standard deviation in brackets. Data in the same column with different letters are significantly different at P<0. 05. Table 1 Open in new tab Genus level fungal richness and diversity estimates. Richness (S). Evenness (H/ln(S)). Shannon (H). Simpson (D). Fisher’s Alpha (α). −SB92. 7 (15. 2) b0. 436 (0. 104)1. 99 (0. 52)0. 707 (0. 184)12. 2 (2. 1) cFH110. 3 (12. 8) a0. 494 (0. 038)2. 32 (0. 21)0. 817 (0. 031)15. 4 (1. 7) a+SB98. 4 (7. 0) ab0. 467 (0. 112)2. 14 (0. 52)0. 761 (0. 112)13. 3 (1. 1) bcSand102. 7 (9. 9) ab0. 501 (0. 060)2. 32 (0. 29)0. 794 (0. 056)14. 2 (1. 4) ab. Richness (S). Evenness (H/ln(S)). Shannon (H). Simpson (D). [SEP] Justify:

Output: The text provides a series of statistical data and figures related to fungal richness and diversity estimates but does not directly mention the decomposition of organic matter or its role in nutrient cycling. Therefore, it is irrelevant to the claim being analyzed.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: The indigenous valuable ancestral information on medicinal plants may fill the associated knowledge gap for the future. MaterialStudy area Ladakh (Trans-Himalayan region) of Region (IHR) is known for its extremely cold climate with rocky, uneven terrains, alpine medicinal plant wealth and wild fauna. The geo-coordinates of this region are in between 34°12’34. 25” N and 77°36’54. 40”' E (Fig. 1) falling between the states of to the south and Jammu and Kashmir to the west. The region is also bordered by countries like Tibet to the east, Baltistan to the west (Baltistan is an administrative territory of Pakistan) and the southwest corner of Xinjiang territory of China. The study area extends from the (to the north) to the south of [27]. Ladakh has two large district towns, Leh and Kargil, with eight (and Lahaul) major valleys with their unique features and characteristics. Most populated areas are the river valleys of district Leh which are Nubra, Shyok and Indus; but Changpa nomads are also observed to be supported by the mountain slopes of this hinterland. Survey and The reconnaissance field surveys were done in Ladakh area for the understanding of the accessibility, nature of terrain and distribution of the flora. A forest working plan was consulted for authenticating geographical location, administrative jurisdiction and wild flora. The representative sites (n =54) were visited through five trips between 2018 and 2019. The documentation of traditional knowledge and ethnobotanical notes of plant resources was based on interviews using open and closed ended questionnaires and discussions. The interviews were mainly based on intersperse fact-based questions [28-29]. Verbal or prior informed consent was sought and obtained from the concern panchayat head as well as the concerned individual informants by briefing clearly about the objectives of the study. Different knowledgeable persons of the area were interviewed, such as Amchis (traditional doctors), hunters, herders and other common denizens like shopkeepers, farmers, daily wage laborer, hotel owners, museum owners, housewives and Govt. employees. Among these, Amchis, herders/shepherds, hunters and those residing in rural and/or far-flung areas are much more informative as compared to others as they are directly dependent on plant products for their livelihoods. [SEP] Justify:

Output: The text corroborates the claim by describing efforts to document traditional knowledge and ethnobotanical notes of plant resources through interviews with knowledgeable individuals such as Amchis, hunters, and herders. This documentation process is essential for preserving indigenous knowledge on medicinal plants, which may otherwise be lost over time.


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 indicating that the intervention observed in the study led to a significant reduction in body weight through regularity of meals rather than through personalized nutrition that allows unrestricted eating habits. The conclusion that the success did not seem related to calorie reduction or other eating behaviors suggests that personalized nutrition, as stated in the claim, does not ensure weight maintenance just by fitting one's genetic profile.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Fisher’s Alpha (α). −SB92. 7 (15. 2) b0. 436 (0. 104)1. 99 (0. 52)0. 707 (0. 184)12. 2 (2. 1) cFH110. 3 (12. 8) a0. 494 (0. 038)2. 32 (0. 21)0. 817 (0. 031)15. 4 (1. 7) a+SB98. 4 (7. 0) ab0. 467 (0. 112)2. 14 (0. 52)0. 761 (0. 112)13. 3 (1. 1) bcSand102. 7 (9. 9) ab0. 501 (0. 060)2. 32 (0. 29)0. 794 (0. 056)14. 2 (1. 4) abAbbreviations: FH, in situ fermentation-humic layer; −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 standard deviation in brackets. Data in the same column with different letters are significantly different at P<0. 05. Table 2 Open in new tab The percent relative abundance of the most common fungala sequences in the hyphal trap bags with and without a sand barrier, sand barriers and the adjacent fermentation-humic layer of the forest floor −SB. . FH. . +SB. . Sand. . Mortierella43. 5 (22. 9)Piloderma32. 3 (4. 9)Amphinema33. 6 (19. 9)Amphinema28. 4 (17. 6)Amphinema16. 6 (11. 6)EMF tips21. 3 (7. 3)EMF tips11. 5 (7. 3)Mortierella15. 7 (14. 6)Wilcoxina5. 8 (4. 9)Mortierella8. 3 (5. 6)Wilcoxina11. 1 (17. 3)Wilcoxina8. 0 (11. 9)Piloderma4. 8 (4. 7)Cortinarius6. 8 (6. 2)Mortierella8. 3 (5. [SEP] Justify:

Output: The text does not provide any information related to the claim regarding fungi decomposing organic matter or their role in nutrient cycling. Instead, it contains numerical data and a list of fungal taxa without contextual relevance to the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: Informants were asked about the uses of plants, such as medicinal, food, fodder, fuelwood, fragrance, dye, decoration, flavor and oil. Field-based observations and both formal and informal discussions were carried out for additional information. The respondents were further asked about their species preference if they utilized a species for self-consumption or trade for earning purposes. A total of 269 informants (208 males and 61 female) were involved in this study, representing over 10% of total population of site. There were only 23% female participants as compared to male 77%. The less female participants could be a reason that women remain indoor and they have less exposure of wild forests and distant sites. About 88% of the informants were above 45 years old while 65% were illiterate. From each study site, one knowledgeable respondent was requested to accompany us to collect plant specimens for the authentication and herbarium preparation. Each of the collected voucher specimens was coded. Pictorial field guide Murthi [30] and Chaurasia et al. [31] was used for identification. The collected specimens were further checked for proper identification with the help of taxonomists at Centre of Biodiversity and Taxonomy, University of Kashmir, Srinagar (J&K) and standard literature [32-33]. Later the doubtful and unidentified plants were identified and verified from the authenticated herbarium specimens at Centre of Biodiversity and Taxonomy, University of Kashmir (KASH herbarium). The voucher specimens were deposited at KASH herbarium. Data analysis Vegetation data were statistically analyzed to find out the relationship between ethnobotanical usage and plant species. The presence/absence data were subjected to the classification of different ethnobotanical similarities and differences among the different plant usage via PAST software. We also used a Chi-Square “Goodness of Fit” test to verify if there was a difference in the usage of plants. Sorensen’s (Bray-Curtis) distance was used to identify significant differences among the different plant and ethnobotanical usage similarities [34-35]. Analysis was used to finding hypothetical variables (components) that account for as much of the variance in the multidimensional data as possible [36-37] using PAST software. The contribution of different plant part usage was displayed in chord diagrams using circlize package [38] in R software 3. 6. 1 [39]. [SEP] Justify:

Output: The text corroborates the claim by detailing a study that involves informants discussing various uses of plants, which indicates an effort to document traditional knowledge related to ethnobotany. The mention of field observations and discussions with knowledgeable respondents highlights the active collection and preservation of this knowledge, suggesting that such studies are crucial in preventing the loss of traditional ethnobotanical practices.


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: Special emphasis was placed on the participants’ ability to understand the details of the study and to give written consent to participate. 4. 3. Study ProtocolEach participant completed a 12-week program, which consisted of the following steps (Fig. S1C):4. 3. 1. AssessmentAt the introductory session, the eligibility for possible participation in the study was determined and demographic data was collected. Then, suitable participants received a general introduction to the study, which included the theoretical background of the study and a detailed explanation of the study procedure. Subsequently, the participants were informed about their rights, the voluntary nature of their participation in the study, and data protection regulations. All participants had to sign an informed consent form for study participation and for the recording and use of their data. Participants weighed and measured their height themselves while study staff connected with them online via camera. Afterwards, the participant received questionnaires to fill out. This initial data assessment is referred to as T0 in the analysis. 4. 3. 2. Two-PhaseThe introduction was followed by a two-week exploration phase in which the participants were asked to follow their usual eating habits and to document all caloric events (main meals, snacks, caloric drinks) using the smartphone application “FDDB” as accurately as possible. Based on this data, the personalized nutritional schedule was then developed. Data from the FDDB smartphone application also allowed us to calculate individual caloric intake along with the ratio of consumed macronutrients for each day during the study. Additionally, the participants weight was measured again. The end of the exploration phase is called T1 in the analysis. 4. 3. 3. Six-Phase(EG): Following the exploration phase, the participants received their personalized mealtime schedule, which was prepared beforehand by the study staff based on the meal diary of the exploration phase. Together with the participants, the nutritional behavior of the last two weeks was reviewed and analyzed. Special attention was paid to irregularities in mealtimes and to times of day when food was eaten particularly frequently. In this way, participants were made aware that they eat irregularly, but that there are nevertheless times when their internal clock frequently triggers hunger. This was followed by a six-week intervention phase, in which the participants were instructed to have their meals only at times according to the mealtime schedule. Participants were explicitly told that they were not restricted in their choice and quantity of food. [SEP] Justify:

Output: The text contrasts the claim by explaining that participants in the study were instructed to have their meals only at specified times according to a personalized mealtime schedule. While they were not restricted in their choice and quantity of food, the emphasis on mealtime restrictions suggests that personalized nutrition does not guarantee unrestricted eating without weight gain, highlighting the importance of structure in eating habits.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 0)Thelephoraceae5. 7 (11. 1)Tylospora3. 8 (4. 5)Tylospora6. 5 (4. 9)Thelephoraceae5. 2 (7. 9)Cenococcum2. 9 (3. 7)Thelephoraceae2. 2 (2. 4)Amphinema2. 7 (1. 6)Piloderma2. 2 (2. 5)Verticillium2. 9 (2. 3)Tuber1. 5 (3. 3)Wilcoxina1. 7 (2. 0)Ceratobasidiaceae1. 5 (2. 2)Ceratobasidiaceae2. 8 (3. 9)EMF tips1. 4 (1. 2)Hygrophorus1. 6 (2. 2)Cenococcum1. 5 (2. 8)Calycina2. 0 (5. 4)Lactarius1. 0 (2. 6)Thelephoraceae1. 2 (1. 8)Inocybe1. 3 (2. 0)Helotiales1. 8 (2. 0)Cortinarius0. 9 (2. 5)Cenococcum1. 1 (0. 8)Hygrocybe0. 7 (2. 1)Cryptococcus1. 5 (0. 9)Sebacina0. 7 (1. 7)Helotiales0. 8 (0. 3)Cryptococcus0. 6 (0. 4)Lecanicillium1. 0 (0. 8)Verticillium0. 7 (0. 7)Cadophora0. 6 (0. 6)Glomus0. 6 (1. 2)Cladosporium0. 8 (0. 7)Russula0. 6 (1. 1)Chalara0. 7 (0. 7)−SB. . FH. . +SB. . Sand. . Mortierella43. 5 (22. 9)Piloderma32. 3 (4. 9)Amphinema33. 6 (19. 9)Amphinema28. 4 (17. 6)Amphinema16. 6 (11. [SEP] Justify:

Output: The text does not provide any information regarding the role of fungi in decomposing organic matter or nutrient cycling. Instead, it appears to list types and possibly some statistical or categorical data about different fungi, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: All the medicinal species with their respective usage are given in Table 1. Each medicinal species found in the region is worth mentioning, but a few of them got much significance in the traditional ‘Sowa-Rigpa’ health care system. These include Bona karpo (Aconitum heterophyllum), Bona nagpo (Aconitum violaceum), Chu-Rtsa (Rheum webbianum), Lachhu (Rheum spiciforme), Spang-rtsa (Saussurea bracteata), Ma-nu/push karmool (Inula racemosa), Kuth (Saussurea lappa), Khizer/Kiraring (Berberis ulicina), Ambo-Lakpa (Dactylorhiza hatagirea), Bri-mok (Arnebia euchroma) and Nia-Mentok (Aster flaccidus). Among other species, Arnebia guttata, Bergenia stracheyei, Corydalis govaniana, Colchicum luteum, Delphinium cashmerianum, Ephedra gerardiana, Ferula jaescheana, Gentiana algida, Hippophae rhamnoides, Lagoti scashmeriana, Meconopsis aculeate, Picrorhiza kurrooa, Jurinea dolomiaea, Rhodoendron anthopogon and Vincetaxicum caneces are also of great importance in the traditional health care. Plant trade status During interviews, we came to know that the medicinal plant species are harvested by the local people both for self-consumption (65%) and for commercial purposes (35%). The local people particularly herders and Amchis collects wild medicinal plants at the household level for both folklore use and trade every year. Discussion High-altitude cold desert Ladakh region of the trans-Himalaya is characterized by the arid and cold climate that remained isolated and poorly accessible; hence the region appears to be less investigated in terms of ethno-ecological research. The availability of medicinal, aromatic and other economically important plants, and the cultural, physical and geographical isolation has thus resulted in the development of a unique traditional plant usage system in the region [26, 40]. [SEP] Justify:

Output: The text corroborates the claim by highlighting the traditional use of various medicinal plant species in the Ladakh region, particularly in the context of the ‘Sowa-Rigpa’ health care system. It describes how the local people, including herders and Amchis, collect these plants for both personal use and trade, thereby reinforcing the idea that such practices contribute to the preservation of traditional ecological knowledge that could be at risk of being lost.


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 intervention phase, participants should continue to document all caloric events using the FDDB App. In addition, participants were asked to weigh themselves weekly to measure their progress. Halfway through the intervention phase, participants were contacted at least once by telephone to clarify possible questions and maintain compliance. Further, in case participants stopped making entries in their FDDB diary for two or more days, they were contacted to ask for reasons and to reinstate compliance again. (CG): In principle, participants in the CG followed the same procedure. However, they were given a sham treatment, for which they were asked to restrict their meals to a freely chosen 18-hour time window per day, during which they could eat what they wanted and, above all, when they wanted. It can be assumed that restricting the eating time window to 18 hours should have no effect on weight, since such a long eating time window is hardly ever exceeded by most people anyway [18] and therefore hardly any change in eating behavior is to be expected. 4. 3. 4. AssessmentAt the end of the intervention phase, the participants were asked to fill out the same questionnaires as at the introduction session. Additionally, weight was measured again. This data assessment is called T2 in the analysis. 4. 3. 5. Follow-up AssessmentFour weeks after completion of the study, the study staff contacted the participants again by telephone to inquire about their current weight and to obtain information about whether the participants had voluntarily continued the program after the end of the intervention phase. If the participants indicated that they did not continue the program, possible reasons were evaluated, and suggestions were received on how the current protocol could be improved to make it more attractive for permanent implementation in everyday life. Participants of the control group were informed at this point about their allocation and the actual question of the study. The final data assessment is called T3. 4. 3. 6. Restrictions due to the Covid-19 pandemicDue to restrictions imposed by Covid-19, the study was carried out online. Data collection and communication was exclusively done via email, (Communications, Inc. ), Facebook (Meta Platforms), or telephone. 4. 4. Assessment of General Well-BeingTo measure whether restricting meals to times when we believe the circadian system triggers hunger leads to an increase in general well-being, questionnaires were collected to measure sleep quality, physical well-being, self-efficacy, and depressive mood. [SEP] Justify:

Output: The text contrasts the claim by discussing an intervention study where participants were asked to adhere to specific dietary practices, including documenting caloric intake and engaging in an eating time window. It implies that merely fitting a genetic profile does not guarantee weight maintenance, as compliance and behavioral changes were necessary for outcomes. Additionally, the mention of participants being contacted to maintain compliance indicates that simply personalizing nutrition was insufficient for success without behavior modification, thus challenging the claim's assertion.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 6)EMF tips21. 3 (7. 3)EMF tips11. 5 (7. 3)Mortierella15. 7 (14. 6)Wilcoxina5. 8 (4. 9)Mortierella8. 3 (5. 6)Wilcoxina11. 1 (17. 3)Wilcoxina8. 0 (11. 9)Piloderma4. 8 (4. 7)Cortinarius6. 8 (6. 2)Mortierella8. 3 (5. 0)Thelephoraceae5. 7 (11. 1)Tylospora3. 8 (4. 5)Tylospora6. 5 (4. 9)Thelephoraceae5. 2 (7. 9)Cenococcum2. 9 (3. 7)Thelephoraceae2. 2 (2. 4)Amphinema2. 7 (1. 6)Piloderma2. 2 (2. 5)Verticillium2. 9 (2. 3)Tuber1. 5 (3. 3)Wilcoxina1. 7 (2. 0)Ceratobasidiaceae1. 5 (2. 2)Ceratobasidiaceae2. 8 (3. 9)EMF tips1. 4 (1. 2)Hygrophorus1. 6 (2. 2)Cenococcum1. 5 (2. 8)Calycina2. 0 (5. 4)Lactarius1. 0 (2. 6)Thelephoraceae1. 2 (1. 8)Inocybe1. 3 (2. 0)Helotiales1. 8 (2. 0)Cortinarius0. 9 (2. 5)Cenococcum1. 1 (0. 8)Hygrocybe0. 7 (2. 1)Cryptococcus1. 5 (0. 9)Sebacina0. 7 (1. 7)Helotiales0. 8 (0. 3)Cryptococcus0. 6 (0. 4)Lecanicillium1. 0 (0. 8)Verticillium0. 7 (0. 7)Cadophora0. 6 (0. 6)Glomus0. [SEP] Justify:

Output: The text provides a list of various fungi species and their associated data, but it does not address their role in decomposing organic matter or their contribution to nutrient cycling. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: Due to higher dependence on medicinal plants for treating various ailments and demand by the pharmaceutical industry, the locals especially Amchis, shepherds and herbal drug dealers prefer the medicinal usage of local flora. Major portion of the harvested medicinal plants (65%) was used for self-consumption while the rest (35%) was sold for commercial purposes. The area has a considerable potential for livestock farming due to presence of sufficient fodder. Animal husbandry, summer grazing and medicinal plant collection and trade are the major livelihood portfolios in arid and alpine regions of the Himalaya [57]. In the present study different parts of ethnomedicinal plants were used for treating various ailments (Fig. 4). The leaves were used more frequently (27%) as compared to other parts like roots (21%), flowers (15%), stem (10%), fruits and whole plants (9% each) etc. Similar results were reported by Keter and Mutiso [58] from Kenya; Malik et al. [59]; Rathore et al. [60]; Singh et al. , [61] from Himalaya, Akhtar et al. [62] from Pakistan, and Kunwar et al. from Nepal [63]. Our results are also supported by other ethnobotanical studies conducted in elsewhere and different regions of the Himalaya [26, 29, 40, 53–56, 64]. Besides leaves, roots are also the most preferred parts used by the local inhabitants because they contain a higher concentration of bioactive compounds than other parts [65]. Hence the local Amchis prefer to use the roots of the plants for medicinal usage. Many of the medicinal plants are facing threat because of the collection of their underground parts on a large scale, such as Aconitum heterophyllum, Aconitum violaceum, Corydalis govaniana, Dactylorhiza hatagirea, Inula racemosa, Bergenia stracheyi, Delphinium cashmerianum, Saussurea bracteata and Picrorhiza kurrooa, among others. These species have become endangered throughout the trans-Himalayan region due to over-collection underground parts for these plants for trade purposes [26, 59, 66, 67]. Previously, local Amchis used these plant resources for their consumption, but now there is a large collection promoted by pharmaceutical companies [68]. [SEP] Justify:

Output: The text corroborates the claim by discussing how local inhabitants, specifically Amchis, rely on medicinal plants not only for self-consumption but also for trade, which highlights the importance of traditional medicinal knowledge. It indicates that traditional uses of these plants are being threatened by commercial demands, suggesting that the study and preservation of ethnobotanical practices are vital to maintain this traditional knowledge, especially as these medicinal plants face threats from over-collection and industrial exploitation.


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 scatterplot was also created for participants of the CG, but they were not provided with meal timings; instead, an 18-hour time window for meals was established with them. 4. 7. Statistical AnalysesStatistical analyses were performed with SPSS 24, Python, Graph9. 2. 0, and R. Details about statistical tests used for specific experiments are indicated in the main text and the corresponding figure legends. 4. 7. 1. Score (MTVS)A Python script was written to generate the MTVS, which is calculated from the deviation of each caloric event from the specified mealtime closest to the event. Similar to a previous study, each meal was given a score value based on the time deviation of the specified meal in minutes: 1 = +/-0-15 min, 2 = +/- 16-30 min, 3 = +/- 31-45 min, 4 = +/- 46-60 min, 5 = +/- 61-75 min, 6 = +/- 76-90 min, 7 = +/- 91-105 min, 8 = +/- 106-120 min, 9 = +/- 2-3 h, 10 = +/- 3-4 h, 11 = over +/- 4 h [20]. Since the participants were given a 60-minute time slot for each meal, a score of up to 2 is considered very regular. Based on individual score values of each meal, an average score value can be calculated for each individual day, for each individual week or for the entire period, i. e. , a daily, a weekly, or a total score. Similarly, daily, weekly, and total scores can be calculated for each type of meal, i. e. , breakfast, lunch, dinner. 4. 7. 2. and randomizationFor the sample size calculation, we assumed an average of 2. 5 kg of body weight loss, based on TRE studies [18, 19, 21–23], as we are not aware of any other study in which meal times were personalized and scheduled. The reported standard deviation for body weight loss in such studies is 3. 2 [19]. Randomization was to be 2:1 (EG:CG) because no significant change in body weight was expected from the control treatment. The randomized assignment was carried out using a continuous list prepared by the study supervisor with the Excel® randomization function. Participant enrollment and assignment was carried out by study staff. On this basis a large effect size d = 0. [SEP] Justify:

Output: The text contrasts the claim by discussing a study focused on meal timing and body weight loss but does not provide any evidence or support for the idea that personalized nutrition guarantees weight maintenance. It mentions statistical analyses related to meal timing and weight loss but does not suggest that eating anything is permissible as long as it fits a genetic profile, thus contradicting the claim.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 6 (1. 2)Cladosporium0. 8 (0. 7)Russula0. 6 (1. 1)Chalara0. 7 (0. 7)Abbreviations: −SB, hyphal trap bags with no sand barrier; FH, in situ fermentation-humic layer; +SB, hyphal trap bags with sand barrier; sand, sand barrier. A higher taxonomic level is given if the sequence could not be assigned to a genus. Data are provided as means (n=9) with s. d. in brackets. EMF tips, matching sequences belonged to unidentified ectomycorrhizal tips. aThe most common (>0. 5% relative abundance) fungal groups are given at the genus level. Table 2 Open in new tab The percent relative abundance of the most common fungala sequences in the hyphal trap bags with and without a sand barrier, sand barriers and the adjacent fermentation-humic layer of the forest floor −SB. . FH. . +SB. . Sand. . Mortierella43. 5 (22. 9)Piloderma32. 3 (4. 9)Amphinema33. 6 (19. 9)Amphinema28. 4 (17. 6)Amphinema16. 6 (11. 6)EMF tips21. 3 (7. 3)EMF tips11. 5 (7. 3)Mortierella15. 7 (14. 6)Wilcoxina5. 8 (4. 9)Mortierella8. 3 (5. 6)Wilcoxina11. 1 (17. 3)Wilcoxina8. 0 (11. 9)Piloderma4. 8 (4. 7)Cortinarius6. 8 (6. 2)Mortierella8. 3 (5. 0)Thelephoraceae5. 7 (11. 1)Tylospora3. 8 (4. 5)Tylospora6. 5 (4. 9)Thelephoraceae5. 2 (7. 9)Cenococcum2. 9 (3. 7)Thelephoraceae2. 2 (2. 4)Amphinema2. 7 (1. 6)Piloderma2. 2 (2. 5)Verticillium2. [SEP] Justify:

Output: The text provides a detailed list of fungal genera and their relative abundances but does not directly address their role in decomposing organic matter or contributing to nutrient cycling. Thus, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: All the major medical traditions of south Asia have been using Himalayan plants in their formulations, but the indigenous Sowa-Rigpa system of Ladakh and other Himalayan regions is especially based on the skillful use of these medicinal plants. Till the 1980s the trans-Himalayan (Ladakh) plants were only used by the local Amchis and people for their domestic needs and treating patients [68]. Plants have been the historical backbone of traditional healthcare practices across major societies and still 75–80% of the world population uses medicinal plants today for primary health care needs [69]. 90% of medicinal plants used by local tribal communities are sourced from the wild [70]. The high demand for herbal drugs has led to the uncontrolled collection of medicinal plants from nature, leading to depletion of biodiversity. For instance, the trans-Himalayas (Ladakh region) has seen depletion of many medicinal herbs. Similarly, numerous other threatened medicinal plants are overexploited for their therapeutic potential [68]. The recent climate changes and habitat loss are another matter of great concern for the survival of these high-altitude plant species [71, 72]. The habitats of most of these species fall within the extensively grazed alpine meadows. Overgrazing has destroyed plant species, as green parts are being removed and damaged due to trampling, mechanical injuries and land erosion [73–75]. With the expansion of roads and increased population have exposed this herbal wealth and brought new commercial interest. The transformation from the need to greed for trans-Himalayan plant species has been increased tremendously. It is observed during our surveys that these plant species are under harvesting pressure and need urgent action for conservation. While we may welcome the growth of traditional medical systems, but it is very important to balance and reconcile these trends for sustainable development. study provides new contributions to floristic composition and plant use by locals in the trans-Himalayan mountainous regions. These regions represent a hotspot of biodiversity and therefore need to be preserved due to their high potential for endemic biodiversity and degradation. Studying the floristic composition and use of these plants by the local human populations is fundamental to understand how the plant communities in these regions are being affected by human actions. We have shown that plants are used for different purposes, including treating diseases. [SEP] Justify:

Output: The text supports the claim by highlighting the importance of traditional knowledge related to the use of medicinal plants in the Himalayan regions. It emphasizes that traditional medical systems, particularly the indigenous Sowa-Rigpa system, rely on knowledge passed down about the use of local flora. Additionally, it discusses the need for conservation of these plant species and the cultural wisdom associated with them, indicating that such studies are critical to preserving this traditional knowledge that is at risk due to overexploitation and environmental changes.


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: Mixed-effect model with Bonferroni post-hoc test comparing CG and EG at different phases during the study, **** p ≤ 0. 0001 (detailed statistics in Tab. S5). Individual body weight (D) and BMI (E) changes of all 34 continuing and all 33 discontinuing participants of the EG group and of CG participants (F) during the study. Data is normalized so that all baseline data at T0 equals 0 to represent change. (G) Between group differences of body weight and BMI from T0-T3 including the last available values of study drop-outs which were carried forward. Mixed-effect model with Bonferroni post-hoc test comparing CG and EG at different phases during the study, **** p ≤ 0. 0001 (detailed statistics in Tab. S5). (H) Significant correlation between body weight/BMI and MTVS of lunch and dinner. The more participants improved their regularity of lunch and dinner (decreasing MTVS), the more weight/BMI they lost. Linear regression, CG: n=33; EG: n=67, ** p ≤ 0. 01 (detailed statistics in Tab. S6). (I) Correlation between baseline BMI at T1 and change in BMI in EG participants. Linear regression, n=67 (detailed statistics in Tab. S6). (J) Between group differences after stratification according to different baseline BMIs. 2-way repeated-measure ANOVA with Bonferroni post-hoc test, *** p ≤ 0. 001 (detailed statistics in Tab. S8). (K) Raw data of change in caloric intake during intervention. 2-way repeated-measure ANOVA with Bonferroni post-hoc test, CG: n=30; EG: n=67, * p ≤ 0. 05, (detailed statistics in Tab. S3). (L) Correlation between reported ingested energy during the exploration phase vs. the intervention phase. Linear regression, CG: n=30; EG: n=67 (some participants were excluded from this analysis because of several erroneous diary entries about unrealistic amounts of food), (detailed statistics in Tab. S6). (M) Determined and estimated cumulative intake of fat, carbohydrates, and proteins during the study. [SEP] Justify:

Output: The text provides detailed statistical analysis of body weight and BMI changes among participants in the study, suggesting that correlation exists between meal regularity and weight loss, as well as how caloric intake affects weight and BMI. This implies that personalized nutrition does not guarantee one can eat anything without gaining weight, as it indicates there are specific conditions and behaviors (like regularity of meals and caloric intake) that affect weight changes.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 9 (2. 3)Tuber1. 5 (3. 3)Wilcoxina1. 7 (2. 0)Ceratobasidiaceae1. 5 (2. 2)Ceratobasidiaceae2. 8 (3. 9)EMF tips1. 4 (1. 2)Hygrophorus1. 6 (2. 2)Cenococcum1. 5 (2. 8)Calycina2. 0 (5. 4)Lactarius1. 0 (2. 6)Thelephoraceae1. 2 (1. 8)Inocybe1. 3 (2. 0)Helotiales1. 8 (2. 0)Cortinarius0. 9 (2. 5)Cenococcum1. 1 (0. 8)Hygrocybe0. 7 (2. 1)Cryptococcus1. 5 (0. 9)Sebacina0. 7 (1. 7)Helotiales0. 8 (0. 3)Cryptococcus0. 6 (0. 4)Lecanicillium1. 0 (0. 8)Verticillium0. 7 (0. 7)Cadophora0. 6 (0. 6)Glomus0. 6 (1. 2)Cladosporium0. 8 (0. 7)Russula0. 6 (1. 1)Chalara0. 7 (0. 7)−SB. . FH. . +SB. . Sand. . Mortierella43. 5 (22. 9)Piloderma32. 3 (4. 9)Amphinema33. 6 (19. 9)Amphinema28. 4 (17. 6)Amphinema16. 6 (11. 6)EMF tips21. 3 (7. 3)EMF tips11. 5 (7. 3)Mortierella15. 7 (14. 6)Wilcoxina5. 8 (4. 9)Mortierella8. 3 (5. 6)Wilcoxina11. 1 (17. 3)Wilcoxina8. 0 (11. 9)Piloderma4. 8 (4. 7)Cortinarius6. 8 (6. 2)Mortierella8. [SEP] Justify:

Output: The text does not provide any explicit information or context related to the claim about fungi decomposing organic matter or contributing to nutrient cycling. It appears to be a list of fungal species without detailing their ecological roles or contributions, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: 2009; 5(3): 132-154. . Studies on traditional knowledge of economically important plants of Kaghan Valley, Mansehra District, Pakistan. J Res. 2011; 5(16): 3958-3967. . Ethnobotanical studies of wild plant resources of. Biol. 2016; 6(2):257-264. Haider A, Qaiser M. of Chitral Valley,Pakistan with particular 2041. Kumar S, Sharma S. Species diversity, uses and distribution of medicinal plants along an altitudinal gradient in Paddar valley, Northwestern Himalaya. Plants. 2013; 3(3):343-351. . Floristic diversity along the roadsides of an urban biodiversity hotspot in Indian Himalaya. Plant Biosyst. 2019; 153(2):222-230. . Floristic composition and biological spectrum of Keran-a remote valley of northwestern Himalaya. Sin. 2019; 39:372-379. . Phytodiversity (Angiosperms and Gymnosperms) in Mandal-Choptaforest of Garhwal Himalaya, Uttarakhand, India. J Nat Sci. 2010; 8:1-17. . First insights into the floristic diversity, biological spectra and phenology of Manoor Valley, Pakistan. Bot. 2018; 50:1113-24. Begum S, Abd-. Ethnomedicines of highly utilized plants in the temperate Himalayan region. . 2014; 11:132-142. . of Herbs of. Biol Boitech. 2014; 11(1):71-83. . An inventory of the ethnobotanicals used as anthelmintics in the southern Punjab (Pakistan). J ethnopharmacol, 2006; 108: 152-154. DOI: 1016/j. jep. 2006. 04. 015. Forest resource use pattern in Kedarnath wildlife sanctuary and its fringe areas (a case study from Western Himalaya, India). En Pol. 2014;67: 138-145. . Ethnobotanical and Ethnomedicinal uses of floristic diversity in and surrounding areas of Mandi district in Himachal Pradesh, India. Biol Sci. 2013; 16(10): 451-468. . Ethnobotanical appraisal and medicinal use of plants in Patriata, New Murree, evidence from Pakistan. [SEP] Justify:

Output: The text corroborates the claim by citing various studies on traditional knowledge related to economically important plants and ethnobotanical practices in different regions, such as the Kaghan Valley and Chitral Valley in Pakistan. These references imply that the documentation and study of these traditional uses of plants contribute to the preservation of ethnobotanical knowledge that could otherwise be lost.


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: Mixed-effects model with Bonferroni post hoc test comparing determined and estimated cumulative energy intake. The estimated macronutrient 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. (N) No significant correlation between body weight/BMI and changes of cumulative macronutrient intake. Linear regression, CG: n=30; EG: n=67, (detailed statistics in Tab. S6). (K, L, M, N) Some participants were excluded from this analysis because of several erroneous diary entries about unrealistic amounts of food. (O) The absolute deviation between the times of weekend meals and the times of food intake calculated for the EG intervention did not affect the subjects’ BMI change. Linear regression, n=67 (detailed statistics in Tab. S6). Table S1:Baseline characteristics of final 100 participants. Table S2:Statistical data on the difference between completers and study drop-outs. The data in the table refers to the data shown in Fig. S2A. Table S3:Statistical data from all Two-way-analyzing time, group, as well as interaction effects between time x group. In data for Figure 1, missing p-values in the and EG are due to the different number of meals for each participant. In the data for Figure 2, some participants were excluded from this analysis because of several probably erroneous diary entries about unrealistic amounts of food. In data for Figure 3, varying n-numbers result from incomplete entries in the diaries. In data for Figure 4, missing data are due to incomplete questionnaires. Table S4:Statistical data from the development of normalized body weight and BMI of participants during the exploration and the intervention phase, and of follow-up data of continuing and discontinuing participants. At T3, three participants could no longer be reached, which is why the n-number deviates here. The data in the table refers to the data shown in Figures 1E and S2A. Table S5:Statistical data from the development of normalized body weight and BMI of participants at the different phases of the study. At T3 only continuing participants were included, which is why the n-number deviates here from the other time points. [SEP] Justify:

Output: The text contrasts the claim by indicating that there is no significant correlation between body weight/BMI and changes in cumulative macronutrient intake, suggesting that simply fitting food choices to a genetic profile does not guarantee weight maintenance. Additionally, it emphasizes the variability in data due to incomplete entries and erroneous reports, further undermining the promise of personalized nutrition as a foolproof method for weight management.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 3 (5. 0)Thelephoraceae5. 7 (11. 1)Tylospora3. 8 (4. 5)Tylospora6. 5 (4. 9)Thelephoraceae5. 2 (7. 9)Cenococcum2. 9 (3. 7)Thelephoraceae2. 2 (2. 4)Amphinema2. 7 (1. 6)Piloderma2. 2 (2. 5)Verticillium2. 9 (2. 3)Tuber1. 5 (3. 3)Wilcoxina1. 7 (2. 0)Ceratobasidiaceae1. 5 (2. 2)Ceratobasidiaceae2. 8 (3. 9)EMF tips1. 4 (1. 2)Hygrophorus1. 6 (2. 2)Cenococcum1. 5 (2. 8)Calycina2. 0 (5. 4)Lactarius1. 0 (2. 6)Thelephoraceae1. 2 (1. 8)Inocybe1. 3 (2. 0)Helotiales1. 8 (2. 0)Cortinarius0. 9 (2. 5)Cenococcum1. 1 (0. 8)Hygrocybe0. 7 (2. 1)Cryptococcus1. 5 (0. 9)Sebacina0. 7 (1. 7)Helotiales0. 8 (0. 3)Cryptococcus0. 6 (0. 4)Lecanicillium1. 0 (0. 8)Verticillium0. 7 (0. 7)Cadophora0. 6 (0. 6)Glomus0. 6 (1. 2)Cladosporium0. 8 (0. 7)Russula0. 6 (1. 1)Chalara0. 7 (0. 7)Abbreviations: −SB, hyphal trap bags with no sand barrier; FH, in situ fermentation-humic layer; +SB, hyphal trap bags with sand barrier; sand, sand barrier. A higher taxonomic level is given if the sequence could not be assigned to a genus. [SEP] Justify:

Output: The text does not provide any information explicitly related to the claim regarding fungi decomposing organic matter or their role in nutrient cycling. Instead, it lists several fungal taxa and includes various codes and abbreviations without discussing their ecological functions.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: J Ethnobiol Ethnomed. 2013; 9(1): 13. doi: 1186/1746-4269-9-13. Ethnobotanical inventory and folk uses of indigenous plants from and Kashmir. J Trop Biomed, 2015; 5(3): 234-241. . Ethnobotanical knowledge among the semi-pastoral Gujjar tribe in the high altitude (Adhwari’s) of Churah subdivision, district Chamba, Western Himalaya. J Ethnobiol Ethnomed. 2019;15: -. Cross-cultural comparison of plant use knowledge in Baitadi and Darchula districts, Nepal Himalaya. J Ethnobiol Ethnomed. 2018; 14(1):40. doi: 10. 1186/s13002-018-0242-7. . Ethnobotanical studies of medicinal plants used by traditional health practitioners in the management of diabetes in lower eastern province, Kenya. J Ethnopharmacol. 2012; 139:74–80. . Ethnomedicinal plants traditionally used in health care practices by inhabitants of Western Himalaya. J Ethnopharmacol. 2015; 172:133-144. . Ethnomedicinal survey of herbaceous flora traditionally used in health care practices by inhabitants of Dhundsir gad watershed of Garhwal Himalaya, India. . 2015; 4 (4):65-78. . in Western Himalaya, India: Community-Refuges for Conservation of Biodiversity and Culture. Appl. 2019;18: 1-21. . Diversity and use of ethnomedicinal plants in the region of Swat, North Pakistan. J Ethnobiol Ethnomed. 2013; 9:25. . Ethnomedicine in Himalaya: a case study from Dolpa, Humla, Jumla and Mustang districts of Nepal. J Ethnobiol Ethnomed. 2006; 2:27. DOI: 10. 1186/1746-4269-2-27. . An ethnobotanical study of medicinal plants in high mountainous region of Chail valley (District Swat-Pakistan). J. Ethnobiol Ethnomedicine. 2014; 10: 36. . Medicinal plant knowledge and its erosion among the Mien (Yao)in northern Thailand. J Ethnopharmacol. [SEP] Justify:

Output: The text provides multiple references to ethnobotanical studies that document indigenous knowledge relating to plant use and medicinal practices. By highlighting these studies, the text supports the claim that ethnobotany is essential for preserving traditional knowledge at risk of being lost, particularly in various regions such as the Western Himalaya and Northern Thailand.


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: AbstractObjectiveMany weight loss strategies are based on the restriction of calories or certain foods. Here, we tested a weight loss intervention based solely on increasing the regularity of meals to allow the circadian system to optimally prepare food metabolism for these times. Participants & MethodsIn a two-group, single center randomized-controlled single-blind study (pre-registration DRKS00021419) with participants aged 18-65 years and BMI ≥ 22 kg/m², we used a smartphone application to identify the times at which each participant eats particularly frequently and asked participants of the experimental group to restrict their meals to only these times for six weeks. Control participants received sham treatment. Primary outcome was self-reported body weight/BMI and secondary outcome the well-being of participants. ResultsOf 148 participants entering the study, 121 were randomized and of these 100 (control: 33, experimental: 67) finished the study. Our results show that the more regular the meals of participants of the experimental group became, the more weight/BMI they lost, averaging 2. 62 kg (0. 87 kg/m²); p < 0. 0001 (BMI: p < 0. 0001) compared to an insignificant weight loss of 0. 56 kg (0. 20 kg/m²) in the control group; p = 0. 0918 (BMI: p = 0. 0658). Strikingly, weight loss was not related to changes in self-reported calories, food composition, and other food-related factors. Additionally, physical and mental well-being improved significantly. ConclusionIn summary, increasing the regularity of meals causes participants to lose excess body weight and improves overall well-being. HighlightsIndividual optimal times for meals are determined via an app-based meal diary. Generation of a structure plan for mealtimes are adjusted to individual circadian clocks. Following this plan, participants lost an average body weight of 2. 6 kg over six weeks. Weight loss is achieved without changes in self-reported food quantity or composition. Regular mealtimes contribute to the improvement of the general well-being. 1. IntroductionCircadian clocks induce endogenous 24-hour rhythms in the expression of more than half of all genes across all tissues [1, 2], allowing the body to anticipate daily changes between day and night and to prepare and harmonize physiological processes accordingly. [SEP] Justify:

Output: The text contrasts the claim by indicating that weight loss strategies, including the study described, do not guarantee that individuals can eat anything without gaining weight. Instead, the study highlights that regularity in meal timing can lead to weight loss without changes in self-reported food quantity or composition, suggesting that there are other factors at play beyond genetic profiles that influence weight management.


Input: Task: pass the claim using the given text. Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 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. 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. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on specific enzymes and their activities related to degradation, without explicitly mentioning fungi or their role in decomposing organic matter. Therefore, it does not support or oppose the claim.


Input: Task: corroborate the claim using the given text. Claim: The study of ethnobotany helps preserve traditional knowledge that might otherwise be lost. [SEP] Text: Asteraceae Bya-rog-nyungs-ma Leaves and bark SMH-116 Traditionally used as anti-rheumatic, antiseptic Lactuca dissecta D. and stem SMH-107 Paste is used to cures infections of female external genital organ Lagotis cashmeriana Rupr. Plantaginaceae Hong-len Roots SMH-175 Reduce inflammation, vital fever, liver fever, lungs fever, intestinal fever, poisonous, painful cramps, muscular spasms, child dysentery, etc. Leonurus japonicus Houtt. Lamiaceae Zin-and stem SMH-165 Regulating menstrual disturbance, dysmenorrhea, amenorrhea, blood stasis, and postpartum haemorrhage, diuretics. Lonicera spinosa (Decne. ) Jacq. ex Walp. Caprifoliaceae Phang-SMH-138 Asthma, headache and gynaecological diseases etc. Meconopsis aculeata Ud-Pal-Sngon-SMH-154 Traditionally used to cure headache Morina longifolia Wall. ex DC. Caprifoliaceae sPyang-tsher Roots and young twigs SMH-191 It treats purgation phlegm disease, cancer, swelling and indigestion, etc. Myricaria elegans Hom-SMH-115 It treats various kinds of poisoning, fever of lungs, diarrhoea, arthritis, uterine bleeding, stomach pain, headache etc. Myricaria squamosa Desv. Tamaricaceae Om-SMH-174 Traditionally used for food poisoning Nepeta floccosa Benth. Leaves and stem SMH-153 The dried leaves and shoots are aromatic and used to add flavour in local dishes. Onosma hookeri C. B. Bri-Mog Roots, bark and leaves SMH-108 Used as remedy for asthma, cough, fever, gonorrhoea leprosy, and phthisis Oxytropis microphylla (Pall. ) DC. Fabaceae Tag-sha nagpo Whole plant SMH-139 The whole plant bears strong fragrance. The quantity of aromatic oil is about 0. 01%. [SEP] Justify:

Output: The text lists various plants and their traditional uses, indicating that such knowledge is based on historical practices within specific cultures. This supports the claim that ethnobotany plays a critical role in preserving traditional knowledge, as it documents the uses of these plants and the cultural significance attached to them.