Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: We defined the root bacteria community (Fig. 1, step IV) and determined which bacteria isolates (from the reference stock, Fig. 5) corresponded to abundant OTUs on the roots under microcosm conditions (Additional file 1: Figure S8; Supplementary methods). See the Additional file 1: Supplementary results for a comparison between microcosm and soil-grown root communities (Additional file 1: Figure S9a, b; Supplementary methods and results). We then conducted microcosm experiments in which we inoculated Trifolium in the microcosms with bacteria strains isolated from its root microbiome. The goal was not to screen strains or to test specific functions but instead to combine all our tools (reference stock, microcosms, community sequencing, and soil extract information) and validate the overall experimental approach for future microbiota inoculation experiments. We assembled a simplified community, choosing strains from the reference stock that corresponded to abundant OTUs on the roots under microcosm conditions and belonged to well-represented bacterial genera in the collection (Additional file 1: Figure S9; strains per OTU were randomly chosen): a Flavobacterium (F; Bacteroidetes, #8 isolates for this genus in the reference stock; KHB002), a Pseudomonas (P; Proteobacteria, #83; KHB004), and a Janthinobacterium (J; Proteobacteria, #19, KHB023; Table 2). We also included a Microbacterium (M; Actinobacteria, #7; strain KHB073) because this genus was well-represented in the reference stock (numerous isolates could indicate that these bacteria were abundant on roots; Fig. 4b) and because we wanted the inoculated community to broadly reflect the abundant bacterial phyla of plant root microbiomes (Actinobacteria, Bacteroidetes, and Proteobacteria; [2, 25]). We inoculated these bacteria alone or in combination to the autoclaved microcosms (Fig. 1, step V) at densities of 106 cells mL−1 and planted surface-sterilized Trifolium seeds. We then monitored the community dynamics of the inoculated simplified community and scored effects of the bacteria inoculation on plant growth in three replicate experiments. [SEP] Justify:

Output: The text contrasts the claim by discussing the unique assembly of bacterial communities in the context of plant root microbiomes. It explains the experimental design of combining various bacterial strains that reflect the diversity of abundant bacterial phyla, suggesting that microbiomes are distinct to specific plants rather than identical among all individuals. For example, it notes that different genera like Flavobacterium, Pseudomonas, and Janthinobacterium were included based on their representation and abundance, indicating variability in microbiome composition.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: As it stands, therefore, the current 3-group type of comparison does not allow conclusions about associative learning. A second major weakness is apparent when considering the sketch in Figure 2g and the equation defining the response index (R. I. ) (line 480). The point is that the larvae that are located in the middle zone are not included in the denominator. This can inflate scores and is not appropriate. That is, suppose from a group of 30 animals (line 471) only 1 chooses the odour side and 29, bedazzled after 30-min quinine or sucrose exposure or otherwise confused by a given opto- or thermogenetic treatment, stay in the middle zone. . . a P. I. of 1. 0 would result. Unless experimentally demonstrated, claims that the thermogenetic effector shibire/ts reduces dopamine release from DANs are questionable. This is because firstly, there might be shibire/ts-insensitive ways of dopamine release, and secondly because shibire/ts may affect co-transmitter release from DANs. To implicate a role of dopamine in DANs, previous work used e. g. RNAi against the dopamine-synthesizing TH enzyme (Rohwedder et al, cited). It is not clear whether the genetic controls when using the Gal4/ UAS system are the homozygous, parental strains (XY-Gal4/ XY-Gal4 and UAS-effector/ UAS-effector), or as is standard in the field the heterozygous driver (XY-Gal4/ wildtype) and effector controls (UAS-effector/ wildtype) (in some cases effector controls appear to be missing, e. g. Figure 4d, Figure S4e, Figure S5c). As recently suggested by Yamada et al 2024, bioRxiv, high cAMP can lead to synaptic depression (sic). [SEP] Justify:

Output: The text is irrelevant to the claim as it primarily discusses issues regarding associative learning, experimental design flaws, and vaguely relates to dopamine release in the context of neuroscience experiments. It does not mention olfactory receptors or quantum effects at all, thus providing no support or contradiction to the claim.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: For all these patients, and in all these situations, subperiosteal implants may be an alternative, due to the digital revolution and the advent of modern digital technologies in dentistry [34,35,36,37, 46]. CBCT allows acquisition of 3D data of the patient’s residual bone volume, with considerable accuracy, and a low dose of radiation directed exclusively at the area of interest [27, 47]. The data acquired with the CBCT is then re-elaborated with appropriate reconstruction software, which allows generation of a virtual bone model of the area of interest [34,35,36,37]. Capturing an optical impression of the dentate arches allows modelling of a virtual diagnostic wax-up. Finally, the superimposition of bone and dental models, together with the virtual wax-up, makes it possible to design and model custom-made subperiosteal implants, designed and conceived specifically for the patient’s needs, both as a bone-supported structure and as a prosthetic emergency [34,35,36,37]. These 3D-printed implants represent a possible alternative solution for the rehabilitation of the atrophic posterior mandible of elderly patients who do not want or cannot undergo traditional regenerative techniques, preparatory to insertion of classical endosseous implants [34,35,36,37]. In particular, increasingly advanced DMLS techniques allow revisiting the old concept of subperiosteal implants. DMLS is a technique arose in the late 1990s in Germany, which has since been gaining importance in dentistry [29]. It is an additive manufacturing (AM) technique that uses a high-power laser to melt metallic powders together [29]. The procedure involves construction of a stratified 3D model, layer by layer. The CAD file is sliced into thin layers, creating a two-dimensional images series that, laced together, create the three-dimensionality of the product [29]. The powder of each layer is then selectively melted by the laser beam, and the process is continuously repeated layer by layer, until completion of the device. With DMLS, there is almost no limitation in the fabrication of complex objects, such as porous, hollow objects with interconnections, tunnels and crevices. [SEP] Justify:

Output: The text corroborates the claim by explaining that 3D printing techniques, such as DMLS, are used for designing and modeling custom-made subperiosteal implants specifically tailored to the needs of individual patients. It highlights that the use of 3D data allows for high accuracy in creating virtual bone models, which then leads to the design of implants that address the unique anatomical requirements of each patient.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Table 2 Bacterial strains used in the microcosm experimentsFull size table After 25 days, we harvested the experiments and counted ≥106 bacterial colony forming units of the inoculated strains on the roots (Table 2). This confirmed that the chosen strains are also able to successfully colonize roots under the artificial growth conditions in the microcosms. We noted a lower biomass in one experiment compared to the two others, and this experiment-to-experiment variation indicated to us that numerous replicates are also needed when highly controlled conditions are used. With regard to the effects of individual bacteria inoculation on the plants, we found that the Flavobacterium negatively affected the growth of Trifolium, while the other bacteria did not have an effect on shoot biomass production (Fig. 6a). The combined application of the bacteria (FJMP) also did not have an apparent effect on biomass production but alleviated the negative impact of the Flavobacterium when grown alone. We measured the composition of the simplified community upon inoculation and after 25 days on the roots (Additional file 1: Supplementary methods for details). could not be captured with the community quantification method, and we noted a small proportion of additional OTU sequences possibly representing sequencing errors or contamination, or in root samples, being derived from seed endophytes. Despite these limitations, the analysis revealed that the three other inoculated members retained similar proportions on the roots during 25 days of incubation as compared to when they were inoculated (Fig. 6b). This observation indicated that the alleviation of the negative impact of the Flavobacterium was not due to out-competition of this community member, but rather that its negative activities may have been “buffered” by the other bacteria in the simplified community. Fig. 6Functional analysis of a simplified Trifolium root microbiota in microcosms. a Trifolium growth in microcosms in the absence of inoculated bacteria (nbc no-bacteria control), with specific strains (F Flavobacterium KHB002, J Janthinobacterium KHB023, M Microbacterium strain KHB073, P Pseudomonas KHB004) or the simplified community (FJMP). The graph reports the mean shoot fresh weight (n = 12; ± s. e. m. ) and the individual data points from the three independent experiments with four replicates each. [SEP] Justify:

Output: The text contrasts the claim by discussing the variations in bacterial strains and their effects on plant growth. It mentions that despite some similarities in proportions of inoculated members on the roots over time, there is significant variation and complexity in the interactions of different bacterial strains, particularly noting how Flavobacterium negatively affected plant growth while other strains did not. This implies that microbiome compositions can differ greatly, contradicting the idea that they are identical across individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: That would call into question the interpretation of low-Dop2R leading to high-cAMP, leading to high-dopamine release, and thus the authors interpretation of the matching effects of low-Dop2R and driving DANs. response: Reviewer #1 (Public Review): Weakness #1: The authors claim to have identified drivers that label single DANs in Figure 1, but their confocal images in Figure S1 suggest that many of those drivers label additional neurons in the larval brain. It is also not clear why only some of the 57 drivers are displayed in Figure S1. As introduced in the results section, we screened 57 driver strains based on previous studies, either they were reported identifying a single (a pair of) dopaminergic neuron (DAN) in larvae or identifying only several DANs in the adult brain indicating the potential of identifying single dopaminergic neuron in larvae. 1, TH-GAL4 was used to cover all neurons in the DL1 cluster, while R58E02 and R30G08 were well known drivers for pPAM. Fly strains in Figure 1h, k, l, and m were reported as single DAN strains in larvae4, while strains in Figure 1e, f, g were reported identifying only several DANs in adult brains5,6. We examined these strains and only some of them labeled single DANs in 3rd instar larval brains (Figure 1f, g, h, l and m). Among them, only strains in Figure 1f and h labeled single DAN in the brain hemisphere, without labeling other non-DANs. Other strains labeled non-DANs in addition to single DANs (Figure 1g, l and m). Taking ventral nerve cord (VNC) into consideration, strain in Figure 1h also labeled neurons in VNC (Figure S1e), while strain in Figure 1f did not (Figure S1c). In summary, the strain in Figure 1f (R76F02AD;R55C10DBD, labeling DAN-c1) is a strain we screened labeling only a single DAN in the 3rd instar larval brains. [SEP] Justify:

Output: The text is irrelevant to the claim about quantum effects in olfactory receptors. It discusses weaknesses in studies identifying single dopaminergic neurons and does not provide any information about olfactory receptors or quantum mechanics.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: It is possible to manufacture titanium or titanium alloy implants, whether standard endosseous [29] or custom-made subperiosteal [34,35,36,37]. Surovas [35] demonstrated the feasibility and economic sustainability of the design and manufacture via DMLS of a custom-made subperiosteal implant in titanium alloy, able to adapt perfectly to the 3D-printed bone model. The steps for the design and fabrication of the custom-made implants were computerized tomography (CT) scan, CT data processing, 3D virtual model creation, modelling technique for custom implant, and data file preparation for 3D printing [35]. The custom-made subperiosteal implant was then fabricated in Ti6Al4V (a type 5 titanium alloy) using DMLS [35]. Cohen et al. [36] developed custom-made subperiosteal Ti6Al4V devices produced by AM and post-fabrication osteogenic micro- and nano-scale surface texture modification. The porous surface of these implants had the potential to stimulate human osteoblasts to produce osteogenic factors, and a high bone-to-implant contact was found for DMLS disks implanted in the rat calvaria and in the rabbit tibia [36]. When implanted in the human posterior mandible, three- and eight-month postoperative images showed new bone formation and osseointegration. The implants were stable and successful under function. These data are not surprising, given that the highly porous surface of titanium laser sintering implants has amply demonstrated in histological and histomorphometric human studies high levels of bone contact and osseointegration, with bone incorporation into the pores, in the posterior maxilla 2 months after insertion [48,49,50]. The possibility of obtaining a porous surface capable of stimulating bone formation represents one of the possible advantages of manufacturing subperiosteal implants with DMLS, and a major difference from traditional subperiosteal implants, which were fused and therefore presented a smooth surface. In a retrospective clinical study, Cerea et al. [34] presented an analogue–digital technique for fabricating custom-made subperiosteal implants, and reported on the survival and complication rates encountered when using these fixtures. [SEP] Justify:

Output: The text corroborates the claim by detailing the process of creating custom-made subperiosteal implants using 3D printing technology such as Direct Metal Laser Sintering (DMLS). It outlines the steps involved in the design and fabrication of these custom implants, highlighting their adaptability to individual 3D-printed bone models. Furthermore, it emphasizes the successful outcomes of these implants, which supports the efficacy and personalization of 3D printing in prosthetic and implant manufacturing.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: The letters indicate statistical significance at P < 0. 05 (Tukey’s HSD; analysis over the three experiments). Note, the Microbacterium (M, panel a) was not captured with the community quantification method. b Community composition of the simplified community (FJMP) at inoculation (input) and after 25 days on the roots. Sequences of other OTUs are indicated in gray Full size image DiscussionRoot microbiome compositionHere, we have characterized the bacterial communities on roots of T. pratense with respect to their composition and reported first steps towards experimentally testing their functions. Trifolium harbors a diverse root microbiome that differs qualitatively and quantitatively from that of the surrounding bulk soil (Fig. 2), confirming studies with other plant species [3–5, 26]. We found that OTU1, matching R. leguminosarum, accounted for a median 73. 5% of the root microbiome (Fig. 3b). We separately inspected root nodules and confirmed that Trifolium nodules were primarily inhabited by R. leguminosarum (Additional file 1: Figure S6) but also contained other bacteria taxa. This is in agreement with earlier work revealing within-nodule diversity in Trifolium repens and Trifolium fragiferum, which consisted of the dominant R. leguminosarum and the less-frequent rhizobia species Bradyrhizobium japonicum, Sinorhizobium sp. , and Mesorhizobium [27, 28]. For the purpose of the microcosm experiments, we described the root microbiome of Trifolium at a whole-root scale, sampling the entire root system including nodules. For a broader description of legume microbiomes, future work investigating the variation in multiple soil types and comparisons with non-legume plants is needed. Additionally, an in-depth spatial assessment of legume root microbiomes would be insightful, e. g. , by profiling the bacteria communities of root tissues with the nodules removed as well as inside the root nodules. The large number of DNA sequences allowed us to thoroughly characterize the Trifolium root microbiome beyond the dominant rhizobia members. [SEP] Justify:

Output: The text contrasts the claim by discussing the diversity of the root microbiome in Trifolium species, indicating that microbiome compositions differ qualitatively and quantitatively. It mentions that the Trifolium root microbiome is characterized by the presence of various bacterial taxa, and highlights the findings of earlier work that revealed within-nodule diversity. This suggests that microbiome compositions are not identical among different individuals or species.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Others (Figure 1g, h, l, and m) we still describe them as strains labeling single DANs, but they also label one to several non-DANs. 1, we mainly showed the strains labeling single DANs. The labeling patterns of other screened driver strains were summarized in Table1. Since all brain images of the rest 47 strains are available, we will state in Fig S1 that additional brain images can be provided upon request. Weakness #2: Critically, R76F02-AD; R55C10-DBD labels more than one neuron per hemisphere in Figure S1c, and the authors cite Xie et al. (2018) to note that this driver labels two DANs in adult brains. Therefore, the authors cannot argue that the experiments throughout their paper using this driver exclusively target DAN-c1. Figure S1c shows single DA neuron in each brain hemisphere. Additional GFP (+) signals were often observed, but not from cell bodies of DANs because they were not stained by a TH antibody. These additional GFP (+) signals were mainly neurites, including axonal terminals, but could be false positive signals or weakly stained non-neuronal cell bodies. This conclusion was based on analysis of a total of 22 larval brains. We will add this in the text or Fig S1 caption. Enlarged insert of GFP (+) signals will be added also to Figure S1c. Weakness #3: Missing from the screen of 57 drivers is the driver MB320C, which typically labels only PPL1-γ1pedc in the adult and should label DAN-c1 in the larva. If MB320C labels DAN-c1 exclusively in the larva, then the authors should repeat their key experiments with MB320C to provide more evidence for DAN-c1 involvement specifically. We thank the reviewer for the suggestion. MB320C mainly labels PPL1-y1pedc in the adult brain, with one or two other weakly labeled cells. It will be interesting to investigate the pattern of this driver in 3rd instar larval brains. If it only covers DAN-c1, we can try to knock-down D2R in this strain to check whether it can repeat our results. [SEP] Justify:

Output: The text does not address the claim regarding olfactory receptors and their potential quantum effects. It discusses various driver strains labeling neurons and the limitations of certain experimental observations without mentioning quantum effects or olfactory receptors.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: In total, 70 partially or completely edentulous patients were included in the study and treated with custom-made DMLS subperiosteal implants, in both the maxilla and the mandible [34]. These implants were designed in an analogue way by the surgeon, directly on 3D models, then digitally designed and fabricated via DMLS. At two-year follow-up, three implants were lost due to recurrent, untreatable infections; the implant survival rate was 95. 8% [34]. With regard to complications, four patients had pain, discomfort or swelling after implant placement, giving an incidence of immediate postoperative complications of 5. 7% [34]. During the follow-up period, one patient experienced recurrent infections, representing an incidence of biological complications of 1. 4% [34]. The rate of prosthetic complications amounted to 8. 9% [34]. The authors concluded that application of custom-made DMLS titanium subperiosteal implants can represent a successful strategy for the prosthetic restoration of patients with severe bone deficiencies, and an alternative to conventional bone regenerative techniques. The clinical study of Cerea et al. [34] has the highest number of enrolled patients and the longest follow-up, though it should be noted that the process for fabrication of the implants was hybrid (analogue–digital) and all implants underwent an electropolishing treatment, capable of transforming the porous surface of the laser-sintered implants into a smooth one. This can radically change the response of hard and soft tissues to the implant. Moreover, the study included different categories of patients (including completely edentulous), with different fixation screws and in the maxillary area. In our present study we have focused our attention only on partially edentulous patients, and in particular on the rehabilitation of the posterior mandible. Our case series showed positive clinical outcomes with the use of subperiosteal custom-made DMLS implants. First, the overall accuracy of the implants was excellent. Only two implants had an insufficient fit (with values of 4 and 5 rated by the surgeon), because of the presence of scattering from neighbouring crowns or teeth in the original CBCT that interfered with the thresholding process. However, these implants were adapted to the surgical sites during the interventions. In our present study, the whole fabrication processes (from the intraoral scans and CBCT to the surgery) took approximately 2–3 weeks. [SEP] Justify:

Output: The text corroborates the claim by detailing the use of custom-made DMLS (Direct Metal Laser Sintering) subperiosteal implants, which were specifically designed and fabricated using 3D printing techniques. It explicitly states that these implants were 'custom-made' and 'designed in an analogue way by the surgeon, directly on 3D models,' highlighting the tailored approach to individual patient needs. This aligns with the claim that 3D printing is utilized to provide customized prosthetics and implants.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: In addition to Rhizobium, Trifolium supports enriched OTUs from the genera Pantoea, Sphingomonas, Novosphingobium, and Pelomonas, among others, in its root microbiome (Additional file 1: Table S2). A review of relevant literature reveals that bacteria isolates of some of these genera have been found to be antagonistic to pathogens (Additional file 1: Table S2). This could possibly suggest a partitioning of complementary host services in the Trifolium root microbiome with “disease protection” and “nutrient provision” provided by the mentioned root-enriched genera and the nodule-inhabiting Rhizobia, respectively. However, because it is notoriously problematic to infer bacteria function from a taxonomy assignment [29], approaches other than 16S community sequencing are required for the functional understanding of the root microbiome. As a next step, such an indicative observation from cultivation independent microbiome analysis could be examined by testing reference stock bacteria belonging to these OTUs for their ability to suppress pathogens. Reference stocks and microcosms to study functions of the root microbiomeWith the isolation of root microbiome members (Fig. 5), setting up an experimental microcosm system (Additional file 1: Figure S1a–d) and testing for microbiota effects on plant growth (Fig. 6a), we delineate a possible approach to advance the functional understanding of the root microbiome. We built our reference stock (Fig. 4b) using one bacteria isolation medium, and at a sampling depth of 200 bacteria strains, we captured close to a quarter of the abundant members of the Trifolium root microbiome. Therefore, we believe that our work presents an encouraging example especially for smaller laboratories with limited resources. For future work, additional isolation media and growth conditions would likely permit us to broaden the reference stock and contribute to a targeted cultivation of “missing” Trifolium root microbiome members. Experimentation with inoculated plantsWe conducted multi-strain inoculation experiments with members of the Trifolium root microbiome to evaluate the suitability of microcosm growth system for plant-microbiota inoculation experiments. However, we first conducted the soil extract experiment (Additional file 1: Figure S7a, b, Figure S8; Supplementary methods and results) as a proof-of-concept to pre-screen microcosm-adapted bacteria strains. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexity and diversity of microbiome compositions. It mentions specific genera found in the Trifolium root microbiome and suggests that different strategies and findings from various microbiomes imply that composition can vary significantly among different organisms, which counters the notion that everyone's microbiome is identical.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: This will be an interesting fly strain to test, but we believe that it will not be necessary for our current manuscript as DAN-c1 driver is very specific (for details, refer to our response to Reviewer#3). However, this line will be very useful for future experiments. Weakness #4: The authors claim that the SS02160 driver used by Eschbach et al. (2020) labels other neurons in addition to DAN-c1. Could the authors use confocal imaging to show how many other neurons SS02160 labels? Given that both Eschbach et al. and Weber et al. (2023) found no evidence that DAN-c1 plays a role in larval aversive learning, it would be informative to see how SS02160 expression compares with the driver the authors use to label DAN-c1. We did not have our own images showing DANs in brains of SS02160 driver cross line. However, Figure 1 in the paper of Eschbach et al. (2020) shows strongly labeled four neurons on each brain hemisphere9, indicating that this driver is not a strain only labeling one neuron, DAN-c1. Weakness #5: The claim that DAN-c1 is both necessary and sufficient in larval aversive learning should be reworded. Such a claim would logically exclude any other neuron or even the training stimuli from being involved in aversive learning (see Yoshihara and Yoshihara (2018) for a detailed discussion of the logic), which is presumably not what the authors intended because they describe the possible roles of other DANs during aversive learning in the discussion. We agree that the words ‘necessary’ and ‘sufficient’ are too exclusive for other neurons. As mentioned in the Discussion part, we do think other dopaminergic neurons may also be involved in larval aversive learning. We are going to re-phrase these words by replacing them with more logically appropriate words, such as ‘important’, ‘essential’, or ‘mediating’. Weakness #6: Moreover, if DAN-c1 artificial activation conveyed an aversive teaching signal irrespective of the gustatory stimulus, then it should not impair aversive learning after quinine training (Figure 2k). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various weaknesses in a manuscript related to the role of specific neuronal drivers in aversive learning and does not mention olfactory receptors or any quantum effects. There is no information or evidence presented that connects to the claim regarding olfactory receptors functioning through quantum effects.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: The mean duration of the surgery was 44. 3 min. Notably, this result was influenced by the two aforementioned cases in which adaptation was not fully satisfactory (those cases required respectively 85 and 67 min, from anaesthesia to sutures). Finally, in our study, all implants survived at 1 year after placement. Immediate postoperative complications had a low incidence (10%), were minor in nature, and resolved in a few days with pain-relieving and antibiotic therapies. The low incidence of complications was a direct result of the perfect fit of the custom-made implants to the patient’s residual anatomy; the surgical procedures were simplified and sped up, inducing a more comfortable result. The main advantages of our fully digital technique, compared to the conventional analogue technique used in the past for fabrication of subperiosteal implants, relies on the accuracy of the implants. This increases considerably the correspondence between the implant structure and the underlying bone, eliminating the need for a surgical session to capture a physical impression of the bone, reducing non-fitting problems and distributing the load more evenly. The excellent accuracy speeds up and simplifies the surgery, reducing the risk of bacterial contamination or infection. In addition, compared to the previously published study of Cerea et al. [34], in our present study the design and fabrication of the implants was entirely digital, and the implants did not undergo electropolishing, so they had a porous surface. In fact, the manufacturing of implants by DMLS, together with the treatment with organic acids, determine the formation of a porous surface, with concavities that continue in a structure with interconnections between the pores [29, 48,49,50,51]. This porosity, although usually lower than that generated by other AM procedures such as the electron beam melting (EBM) [52] has the potential to stimulate bone ingrowth [29, 48, 49], as well as soft tissue adhesion [50, 51], for better healing and long-term tissue stability. Naturally, the present full digital technique has some problems. For the full digital design of these implants, experience and knowledge of CAD software is required. In particular, the thresholding is delicate for creating the 3D bone model on which the implant will be designed. In fact, if the thresholding is wrong, problems will inevitably arise in the fit and adaptation of the implant during the operation. [SEP] Justify:

Output: The text corroborates the claim by discussing the advantages of fully digital techniques in the creation of custom-made implants that fit the patient's anatomy perfectly. It mentions that the accuracy of the implants increases correspondence with the underlying bone structure, thereby simplifying the surgery and enhancing the comfort and safety of the procedure. This directly supports the idea of 3D printing being utilized to create tailored prosthetics and implants.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: We subsequently tested four bacteria strains, three of which were culturable members of the abundant root community (Fig. 5) and were also abundant members of the root microbiome in the soil extract experiment (Additional file 1: Figure S8). We chose to include a Microbacterium isolate because of its abundance in our reference stock (seven isolates, Fig. 4b) and its classification in the Actinobacteria, a phylum shown to be abundant in plant root microbiomes [25]. We confirmed that these strains successfully colonized plant roots as suggested by the higher abundances on roots compared to their initial inoculated density to the microcosms (Table 2). We could not capture the Microbacterium strain with the community quantification method (Fig. 6b), and similarly, none of the seven isolates from the reference stock clustered to any OTU in the entire dataset. A first possible explanation is that the Microbacterium is a rare but easily culturable microbiome member. Alternatively, the Microbacterium could be an abundant microbiome member, as indicated by the numerous isolates in the reference stock, but absent in the community profiles because of an observed mismatch in the priming site of the PCR primer 799F. A third possible explanation for the microcosms is that although the titer quantification revealed that the Microbacterium strain successfully colonized the plant roots in mono-associations, this strain was outcompeted in the simplified community by the other tested strains. Future experiments need to clarify these possibilities, but nevertheless, this is an example where cultivation and DNA-based approaches do not overlap, and a reminder that both methods have inherent limitations. While it is often discussed that PCR primers are biased towards certain bacterial taxa [30], the same is also true for isolation media, which have a specificity by favoring growth of certain bacterial groups [31]. We quantified the fresh weight of the shoot biomass in response to the bacteria in mono-associations or when the four bacteria were combined to a simplified community. We found that plants grew smaller when inoculated with the Flavobacterium strain in a mono-association, but that this negative plant growth response was alleviated when the Flavobacterium was inoculated in a community with the other strains (Fig. 6a). Since we measured that the Flavobacterium comprised roughly a third of the community (Fig. [SEP] Justify:

Output: The text contrasts the claim by discussing the variability in microbiome members and their abundances, suggesting that the composition is not identical. Specifically, it mentions that the Microbacterium strain could either be a rare or abundant microbiome member but is not consistently represented in community profiles. This indicates that different individuals may have different microbiome compositions, thus countering the idea that everyone has an identical microbiome.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: While the authors interpret Figure 2k (and Figure 5) to indicate that artificial activation causes excessive DAN-c1 dopamine release, an alternative explanation is that artificial activation compromises aversive learning by overriding DAN-c1 activity that could be evoked by quinine. This is a great point! Yes, we cannot rule out the possibility that artificial activation compromises aversive learning by overriding DAN-c1 activity that could be evoked by quinine. The experimental results with TRPA1 could be caused by depletion of dopamine, or DA inactivation due to prolonged depolarization or adaptation. However, we still think that our hypothesis on the over-excitation of DAN-c1 is more consistent with our experimental results and other published data. Our justification is as follows: (1) Associative learning occurs only when the CS and US are paired. In wild type larvae, a specific odor (conditioned stimulus, CS, such as pentyl acetate) depolarizes a subset of Kenyon cells in the mushroom body, while gustatory unconditioned stimulus (US, quinine) induces dopamine release from DAN-c1 to the lower peduncle (LP) compartment in the mushroom body (Figure 7a). Only when the CS and US are paired, calcium influx caused by CS and Gas activated by D1R binding to dopamine will turn on a mushroom body specific version of adenylyl cyclase, rutabaga, which is the co-incidence detector in associative learning (Figure 7d). (2) Rutabaga transforms ATP into cAMP, activating PKA signaling pathway and modifying the synaptic strength from mushroom body neurons (MBN, also called Kenyan cells) to the mushroom body output neurons (MBON, Figure 7d). This change in synaptic strength will lead to learned responses when the same odor appears again. (3) In our work, we found D2R is expressed in DAN-c1, and knockdown D2R in DAN-c1 impairs larval aversive learning. As D2R reduces cAMP level and neuronal excitability3, we hypothesized that knockdown of D2R in DAN-c1 would remove the inhibition of D2R auto-receptor, and lead to more dopamine (DA) release when US (quinine) was delivered compared to the wild type larvae. [SEP] Justify:

Output: The text is irrelevant to the claim regarding quantum effects in olfactory receptors. It discusses dopamine pathways and learning mechanisms in larvae, without addressing olfactory receptors or any quantum theories. Therefore, it neither supports nor rebuts the claim.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: It is therefore clear how, in the presence of CBCT with artefacts or substantial scattering in the area to be reconstructed, criticalities can emerge in the design of the implant, which in any case is not simple and requires adequate CAD knowledge. Some company services now offer help for the surgeon, at relatively low costs; these companies own the software and machines necessary for manufacturing the implants, and in this sense they represent the best solution for the clinician. In any case, surgery for placement of a subperiosteal implant is technically more complex than the classic positioning of endosseous implants ad modum Brånemark. The clinician’s surgical skills play a fundamental role in the insertion and in the management of any biological and technical complications. This study has limits. Firstly, it is just a case series; a larger sample of patient would be advisable to draw more specific conclusions about the reliability of these implants. Secondly, this study has a short follow-up of 1 year, and therefore does not report on the possible mid- or long-term complications that may affect these custom-made subperiosteal implants. For example, the progressive atrophy of the bone in elderly patients could determine the mobilization in the implant, in the medium or long period. Extending the follow-up is therefore mandatory, as it could lead to more solid conclusions. ConclusionsIn the past, subperiosteal implants represented a possible solution for prosthetic restoration of the atrophic posterior mandible. However, their use presented several technical and surgical issues (including the need for two surgical sessions, and often poor adaptation to the surgical site) that were in part responsible for the high percentage of complications in the short and long term. Today, each patient must be examined in their complexity, evaluating the best solution considering every aspect, physiological, pathological, aesthetic and economic. Digital technologies such as DMLS allow revisiting the old concept of subperiosteal implants in a modern way, for treatment of the posterior atrophic mandible of elderly patients who do not want to undergo to bone regenerative procedures. In the present study, ten elderly patients were treated with custom-made 3D-printed subperiosteal titanium implants. During surgery, the fit of the implants was satisfactory. Only two implants had insufficient fit, because of the presence of scattering in the CBCT; however, these were adapted to the surgical site during the intervention. [SEP] Justify:

Output: The text corroborates the claim by explicitly stating that ten elderly patients were treated with custom-made 3D-printed subperiosteal titanium implants. This indicates the application of 3D printing in creating tailored implants for individual patients, thus supporting the assertion made in the claim.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: 6b), we excluded the possibility that the loss of the negative growth effect was due to the bacterium being outcompeted by the other inoculated strains. Instead, the growth compromising activities of the Flavobacterium were possibly counteracted by one or more of the co-inoculated isolates, or alternatively, it did not reach a sufficient cell density in the simplified community treatment. The reference stock bacteria and microcosms present valuable resources for future microbiota manipulation experiments in which the contribution of the plant root microbiome to plant growth can be investigated. One next step would be to identify the functional traits, e. g. , related to bio-control or plant growth promotion, of the reference stock bacteria using bioassays and/or genome sequencing. We expect that different strains that mapping to the same OTU would interact differently with the host plant, and thus the testing of the functional range among bacteria within an OTU presents another next step. In summary, there are countless opportunities for microcosm experiments. For example, the microbiota of Trifolium can be manipulated with regard to its taxonomic or trait composition or with regard to its diversity and tested for effects on plant growth. Furthermore, the interplay among community members or the dynamics of community assembly can be examined in more detail. Finally, microbiota induced effects on plant growth under stress conditions such as high salinity, reduced nutrient availability, or pathogens can be investigated. ConclusionsWe have reported a multi-step approach (Fig. 1) combining cultivation-dependent and independent methods to describe and functionally examine the root microbiome of Trifolium. The need to experimentally manipulate a microbiota requires reference stocks of isolates, and we believe that reductionist plant-microbiota systems will permit a systematic examination of the root microbiome functions. Further studies employing targeted manipulations of the root microbiome can help in the development of new tools to increase the sustainability of other agricultural plant species [17] and investigate the relationship between microbiome diversity and plant performance [16]. MethodsPreparation of experimental soil, plant cultivation, and harvestExperimental soilAll experiments of this study were conducted with a natural experimental soil collected from the area outside the experimental plots of the long-term and Tillage (FAST) experiment (47° 26′ 20″ N 8° 31′ 40″ E). The experimental soil is a loamy sand with the following physicochemical characteristics: pH 6. [SEP] Justify:

Output: The text contrasts the claim by discussing the diversity and variability of microbiota, particularly in the context of different strains interacting with host plants and influencing plant growth. It mentions that testing among bacteria within an OTU and different strains highlighting variability suggests that microbiomes are not identical but rather diverse and context-dependent in their composition and functions.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: The elevated DA release along with calcium influx caused by CS increases the cAMP level in MBN, which leads to the learning deficit (over-excitation, Figure 7b). Mutant larvae with excessive cAMP, dunce, showed aversive learning deficiency, supporting our hypothesis2. (4) Our results of TRPA1 can be explained by this over-excitation hypothesis. When DAN-c1 is activated (34C) in distilled water group, the artificial activation mimicked the gustatory activation of quinine. The larvae showed the aversive learning responses towards the odor (Figure 2k DW group). When DAN-c1 is activated (34C) in sucrose group, the artificial activation mimicked the gustatory activation of quinine, so the larvae showed a learning response combining both appetitive and aversive learning (Figure 2k SUC group). (5) When DAN-c1 is activated (34C) in quinine group, the artificial activation and the gustatory activation of quinine lead to elevated DA release from DAN-c1. During training, this elevated DA caused over-excitation of MBN, leading to failure of aversive learning (Figure 2k QUI group), which had a similar phenotype compared to larvae with D2R knockdown in DAN-c1. (6) Similarly, optogenetic activation of DAN-c1 during aversive training, leads to elevated DA release from DAN-c1 (both gustatory activation of quinine and artificial activation). This would also cause over-excitation of MBN, and lead to failure of aversive learning. Artificial activation in other stages (resting or testing) won’t cause elevated DA release during training, so the aversive learning was not affected (Figure 5b). (7) However, when optogenetic activation was applied during training, we did not observe aversive learning responses in the distilled water group, or a reduction in the sucrose group (Figure 5c, Figure 5d). Our explanation is that the optogenetic stimulus we applied is too strong, DAN-c1 has already released elevated DA in both groups. So, the aversive learning in these groups has already been impaired, they just showed the corresponding learning responses to distilled water or sucrose. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on the relationship between elevated DA release, calcium influx, and learning deficits in larvae, without discussing olfactory receptors or quantum effects. Therefore, it does not support or contradict the claim.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: A digital workflow for modeling of custom dental implants Download PDF Download eeaccess Published: 06 June 2019 A digital workflow for modeling of custom dental implants : orcid. org/0000-0002-7822-81311 3D Printing in Medicine 1985. The first documented case of an orthopedic device made using 3D digital technology was a mandibular subperiosteal implant made by James RA [7]. At that time, direct metal printing was not available; therefore, CT data were used to create anatomical models of patients’ mandibles, which were then actualized as implants using traditional metal casting technology. After direc metal laser sintering (DMLS) technology became available from EOS (Krailling, Germany) in 1995 [6], it became possible to make three-dimensional objects in metal with virtually any complexity. This opened up possibilities for completely digital manufacturing processes—a route from patient anatomy virtualization to digital design and direct printing in biologically compatible metal or alloy (such as steel, CoCr (cobalt-chromium) alloy, Ti64 alloy, or pure titanium). Introduced into the dental field, these techniques expanded the ways in which custom subperiosteal implants could be made. With currently available technologies (as of 2018), it is possible to make subperiosteal dental implants using any of the following four methods: 1. Conventional: bone impression and lost wax casting metal 2. Transitional: CT, 3D jaw model printing, lost wax casting in metal 3. Digital: CT, modeling on virtual jaw model, printing in metal using DMLS or similar technology 4. Hybrid: bone impression, silicone impression or stone model optical scanning, modeling of implant on virtual jaw model, printing in metal using DMLS or similar technology The first method is the known classic, long-established approach that requires a second surgery for implant placement. During the first surgery, an impression is taken with silicone material. Then, the implant is modeled on a refractory model, cast in metal, and finished between surgeries—usually 2–3 weeks. The implant is put into place in a second surgical procedure. The second approach avoids the second surgery by using CT data obtained in advance and a refractory model for casting, duplicated from a 3D printed model. [SEP] Justify:

Output: The text corroborates the claim by detailing the use of 3D printing technologies in the creation of custom dental implants and prosthetics. It discusses how these devices can be tailored to individual patients through various methods of 3D modeling and printing, particularly mentioning the shift from traditional techniques to advanced digital methods and direct metal printing. The text illustrates the application of these technologies for custom subperiosteal implants using patient-specific anatomy data, aligning well with the claim about personalized prosthetic creation.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Conversely, the lower respiratory tract (LRT) comprises the syrinx, air sacs, bronchioles, and lungs [16]. Contrary to the prevailing microbial sterility dogma, there is now evidence for microbial colonization of the avian respiratory tracts [17, 18]. In view of this knowledge, the question of the origin of pioneer colonizers of the respiratory tract arises. Microbial colonization of the respiratory tract is a complex process influenced by host-related intrinsic factors and environmental extrinsic factors. Nonetheless, the pioneer colonizers of the poultry respiratory tract are hypothesized to be maternal-dependent. This hypothesis has been demonstrated in humans via a metagenomic neonatal study that showed differences in infant-mother gut microbiota resemblance based on delivery method [19]. Gantois et al. [20] exposition on the pathogenesis of Salmonella contamination in poultry support this hypothesis in poultry. It is reported that microbial seeding could occur via horizontal transmission during or after oviposition in the hen or vertically through the pores on eggshell membranes or eggshells. An association between maternal oviduct microbiota, yolk microbiota, and hatched chick microbiota has also been confirmed [21, 22]. Notwithstanding, well-designed longitudinal studies are needed to provide more insight on the maternal-origin hypothesis on microbial pioneer colonization in poultry, especially taking into cognizance modern poultry production systems that limit maternal hen-egg contact. et al. [23] made the first attempt to enumerate poultry respiratory bacterial communities, the findings of this study have limited practical use as a result of the limitations of the culture-dependent method that was employed. The study by Mulholland and colleagues [17] was the first study to adopt 16S rRNA amplicon sequencing methodology to provide a bacteria census of the poultry respiratory tract, specifically of the trachea at hatch. Data from this study affords the opportunity to speculate on the pioneer colonizers of the poultry respiratory tract. Accordingly, Fig. 1 presents information on the pioneer genera of the avian trachea. The avian trachea is seen to be predominantly (62%) dominated by the genera Pseudomonas, Brevibacterium, Streptococcus, Chryseobacterium, Bacillaceae, and Corynebacteriaceae at hatch. Using two- and seven-day-old chickens, Glendinning et al. [SEP] Justify:

Output: The text contrasts the claim by detailing the complexity of microbial colonization in poultry and humans, thereby implying variability in microbiome composition. It mentions that differences in infant-mother gut microbiota resemblance are influenced by delivery method, indicating that microbiome compositions can vary significantly based on specific factors.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: (8) We also applied this over-excitation to activate MBNs. As MBN takes over both appetitive and aversive learnings, over-excitation of MBNs led to deficit in both types of learning, which follows our hypothesis (Figure 6). In summary, we hypothesized that DAN-c1 restricts DA release via activation of D2R, which is important for larval aversive learning. D2R knockdown or artificial activation of DAN-c1 during training would induce elevated DA release, leading to over-excitation of MBNs and failure of aversive learning. Weakness #7: The authors should not necessarily expect that D2R enhancer driver strains would reflect D2R endogenous expression, since it is known that TH-GAL4 does not label p(PAM) dopaminergic neurons. Just like the example of TH-GAL4, it is possible that the D2R driver strains may partially reflect the expression pattern of endogenous D2R in larval brains. When we crossed the D2R driver strains with the GFP-tagged D2R strain, however, we observed co-localization in DM1 and DL2b dopaminergic neurons, as well as in mushroom body neurons (Figure S3 c to h). In addition, D2R knockdown with D2R-miR directly supported that the GFP-tagged D2R strain reflected the expression pattern of endogenous D2R (Figure 4b to d, signals were reduced in DM1). In summary, we think the D2R driver strains supported the expression pattern we observed from the GFP-tagged D2R strain, especially in DM1 DANs. Weakness #8: Their observations of GFP-tagged D2R expression could be strengthened with an anti-D2R antibody such as that used by Lam et al. , (1999) or Love et al. , (2023). Love et al. , (2023) used the antibody from Draper et al. 10. We have tried the same antibody, but we were not able to observe clear signals after staining. Maybe it is not specific for the neurons in the fly larval brain, or our staining protocol did not fit with this antibody. Unfortunately, we were not able to find Lam (1999) paper. [SEP] Justify:

Output: The text provided discusses the activation of MBNs, D2R functionality, and various experimental weaknesses associated with D2R expression studies. None of this content relates to the claim concerning olfactory receptors or quantum effects. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: 5Model preparation continued: a) virtual jaw models in occlusion; b) virtual teeth added; c) prospective abutments have been placed in places corresponding to future teeth; d) future abutments – sky blue abutments belong to subperiosteal implant and red one belongs to planned screw type implant; e) a cut-off tool placed in the area of tooth 24 (FDI), where abutment was planned to bury deeper into the bone; f) maxilla with cut-off and placed abutmentsFull size imageIn addition, consider the lateral component of jaw movements—create anatomical and mechanical means of implant fixation. When creating fixed cementable abutments, pay attention to parallelism of prospective abutments with current partnering abutments (teeth or implants) and the relation to opposing dentition (antagonists). The modeling process of a custom dental implant per se is the de novo creation process. This is in contrast to reconstructive surgery modeling, which often uses contra-lateral mirroring to obtain correct anatomical structures. Thus, new objects of intricate shape must be created, which in turn must closely adapt to current anatomical structures. This task requires suitable digital tools. Modeling for medical applications is still a new and emerging field of digital design. There is a range of software built for the dental prosthetic field and numerous programs for implant planning and surgical guide creation. Although some of these programs offer planing osteotomies and bone grafting, the majority are predominantly limited to use of standard screw type implants from different manufacturers. Consequently, they are not useful for modeling custom structures. Numerous software packages have been created for making fixed and removable dental prostheses via CAD/CAM. It appeared that the most straightforward route would be to use applications designed for modeling a partial removable dentures because of the similarity of subperiosteal implants and the framework of partial removable denture. However, after testing several software packages, this route proved to be unusable because the programs do not allow jaw model modification, are limited to preset structures, or require heavy customization to be useful. 3D modeling toolsDepending on software capabilities and designer approach, subperiosteal dental implants can be created using several different tools (techniques). The applicable techniques and corresponding programs are listed below:° Digital clay modeling. ▪ Sculpt clay with brush tool (Meshmixer, Blender, FreeForm). [SEP] Justify:

Output: The text corroborates the claim by discussing the modeling process for creating custom dental implants that adapt closely to current anatomical structures. It states that 'the modeling process of a custom dental implant per se is the de novo creation process,' indicating that 3D printing is employed to tailor implants to individual patient needs. Additionally, the text emphasizes the use of digital tools and software for designing specific dental prosthetics, which aligns with the purpose of 3D printing in medical applications.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: [24] and Ngunjiri et al. [25] have also reported that genera Pseudomonas, Staphylococcus, Actinobacillus, and Lactobacillus species (L. reuteri, L. gasseri, and L. crispatus) are initial colonizers of the chicken nasal, tracheal, and Broncho-(BAL) samples. At the phylum taxa, Mulholland et al. [17] report that the avian trachea is majorly colonized by four phyla at hatch, specifically Gram-positive bacteria Firmicutes (35%) and Actinobacteria (29%), Gram-negative bacteria (Proteobacteria (19%), and Bacteroidetes (9%). Although with varying order of abundance, the same bacterial phyla have been reported as pioneer colonizers of the avian gut [26, 27]. While the effects of the hatchery environment and contaminants on potential colonizers of the respiratory tract should be acknowledged, these results suggest that maternal influence plays a significant role in shaping the pioneer microbial community of the avian respiratory tract. Fig. 1Adapted from Glendinning et al. (2017) and Mulholland et al. (2021)Dynamics of microbiota colonization and succession in the avian trachea and lungs. At hatch, the avian trachea (representative of the upper respiratory tract-URT) was colonized predominantly by Pseudomonas (13%), Brevibacterium (9%), Brachybacterium (8%), Streptococcus (8%), Chryseobacterium (7%), Bacillaceae (6. 5%), and Corynebacteriaceae (6%). By week 3, the tracheal microbiota shifted, with reductions in Brevibacterium (6%), Bacillaceae (4. 2%), and Brachybacterium (5%). emerged dominantly, constituting 34. 1% of the trachea. In contrast, the lung microbiota (representative of the lower respiratory tract-LRT) displayed distinct colonization. Initially, Staphylococcus (25%), Pseudomonas (16%), Achromobacter (15%), and Lactobacillus (12%) were predominant at hatch. [SEP] Justify:

Output: The text contrasts the claim by detailing the variability in microbiome composition among avian species, indicating that different species and environmental factors contribute to unique microbial communities. It specifies that various bacterial genera and phyla colonize the avian respiratory tract, reflecting the diversity of microbiomes rather than indicating uniformity.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Weakness #9: Finally, the authors could consider the possibility other DANs may also mediate aversive learning via D2R. Knockdown of D2R in DAN-g1 appears to cause a defect in aversive quinine learning compared with its genetic control (Figure S4e). It is unclear why the same genetic control has unexpectedly poor aversive quinine learning after training with propionic acid (Figure S5a). The authors could comment on why RNAi knockdown of D2R in DAN-g1 does not similarly impair aversive quinine learning (Figure S5b). We also think that other DANs may be involved in aversive learning. We re-analyzed the learning assay data, seemingly D2R knockdown in DAN-g1 with miR partially affected aversive learning when trained with pentyl acetate (Figure S4e). We are going to build single statistic panels for DAN-g1 and DAN-d1. However, neither larvae with D2R knockdown in DAN-g1 using miR trained with propionic acid (Figure S5a), nor larvae with D2R knockdown in DAN-g1 using RNAi trained with pentyl acetate (Figure S5b) showing aversive learning deficit. We will add paragraphs about this in both Results and Discussion sections. Reviewer #2 (Public Review): Weakness#1: Is not completely clear how the system DAN-c1, MB neurons and Behavioral performance work. We can be quite sure that DAN-c1;Shits1 were reducing dopamine release and impairing aversive memory (Figure 2h). Similarly, DAN-c1;ChR2 were increasing dopamine release and also impaired aversive memory (Figure 5b). However, is not clear what is happening with DAN-c1;TrpA1 (Figure 2K). In this case the thermos-induction appears to impair the behavioral performance of all three conditions (QUI, DW and SUC) and the behavior is quite distinct from the increase and decrease of dopamine tone (Figure 2h and 5b). The study successfully examined the role of D2R in DAN-c1 and MB neurons in olfactory conditioning. [SEP] Justify:

Output: The text discusses specific experiments regarding D2R in DAN neurons and aversive learning, without mentioning olfactory receptors or any quantum effects. Therefore, it is irrelevant to the claim about olfactory receptors and quantum effects.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: ▪ Sculpt clay applying profile along surface curve (). ° Selected surface extrusion (Meshmixer, VRMesh). ° Curve fitting with pipe or tube (VRMesh, Freeform, Sculpt). In this case, modeling was conducted via the addition-subtraction method using the mesh brush sculpting technique. Two copies of a jaw model were used. The the first copy was used to model the implant itself by bulging virtual clay, which is similar to the manner in which a dental technician lays wax on the refractory model for partial production of a removable framework. The second copy was used for subtraction from first—to form the inner (bone facing) surface of the implant. Further detailsModels for the maxilla and mandible should be put as close as possible to centric relation, which makes abutment planning easier (Figs. 4b and c). Placing virtual teeth helps with the planning of future occlusion and abutments (Figs. 5b and c). Firstly, abutments are placed according to the current bone anatomy and future prosthetic plan. Bone quality and anatomic form must be considered while designing the implant. Load bearing and retentive elements should be planned only where at least 0. 8 mm of cortical bone is present. Retentive elements (loops, puds) were placed at specified locations and all above-mentioned elements were merged with one copy of the jaw models using a Boolean addition operation (Figs. 6b and c, Figs. 7a and d). Fig. 6modeling principle: a) original model of the jaw; b) pre-made structures (loops and abutments) added on to virtual model; c) pre-made structures and modelled (bulked) implant merged with original model; d) the 2nd copy of original model (yellow) recalled and matched with model onto which implant was modelled (orange); e) implant – result of Boolean operation, subtraction of yellow model form orange model; f) implant (resultant) model superimposed on the original jaw model. (Screenshots from Meshmixer program)Full size imageFig. [SEP] Justify:

Output: The text corroborates the claim by detailing a modeling process for creating implants, indicating customization suited to individual anatomical features. It discusses how modifications to a jaw model, including the placement of pre-made structures and adjustments based on the anatomy, reflect the tailoring aspect of 3D printed prosthetics and implants.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: By week 3, the composition shifted to Pseudomonas (35%), Lactobacillus (28%), and Staphylococcus (18%) as the dominant genera in the avian lungs. Full size imageIn terms of community structure, phyla Firmicutes, Proteobacteria, and Bacteroidetes—and to a lesser extent Actinobacteria and Tenericutes—are consistently reported as the major residents of the poultry respiratory tract [12, 25, 28]. and Bacteroidetes have also been reported as the predominant bacteria in the human colon [29], suggesting an evolutionary trend. phylum comprises more than 200 genera, including important probiotics like Lactobacillus, Bacillus, and Ruminicoccus. Conversely, the predominant genera in the phylum Bacteroidetes, including Bacteroides and Prevotella, are known pathobionts [30]. Of note, high Firmicutes to Bacteroidetes ratios are associated with increased inflammation, fat deposition and obesity in humans [31]. A reduction in the abundance of members of the Firmicutes phylum has also been linked with several pathologies in other animals including pigs, cattle, and horses [32]. At lower taxa, as many as 144 bacterial genera have been identified in the respiratory tract of turkeys including 25 shared genera between turkeys and chickens [9, 33], emphasizing the complexity of the poultry respiratory microbiota. A detailed summary of studies presenting the predominant genera in the poultry respiratory tract is presented in Table 1. The trachea and BAL samples are the most studied sections of the URT and LRT in poultry, respectively. The avian respiratory tract comprises more facultative anaerobes than obligate anaerobes, with genera Lactobacillus and Staphylococcus being ubiquitous residents of both the URT and LRT [17, 33]. Although the genus Lactobacillus predominates the poultry respiratory tract [34], its relative abundance varies depending on which part of the respiratory tract is being examined. genus is known to comprise gram-positive facultative anaerobic bacteria that degrade polysaccharides to yield lactic acid [35]. Lactobacillus species are often used in the poultry industry as probiotics as a result of their beneficial properties [36]. Notwithstanding, Johnson et al. [SEP] Justify:

Output: The text contrasts the claim by emphasizing the variability in microbiome composition, particularly highlighting that the composition of the avian lungs includes different dominant genera such as Pseudomonas, Lactobacillus, and Staphylococcus. Additionally, it discusses the complexity of the poultry respiratory microbiota and mentions the variability in the abundance of Lactobacillus based on the part of the respiratory tract being examined, indicating that microbiome compositions are not identical across individuals or species.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: The conclusions are well supported by the data, with the exception of the claim that dopamine release from DAN-c1 is sufficient for aversive learning in the absence of unconditional stimulus (Figure 2K). Alternatively, the authors need to provide a better explanation of this point. Please refer to our response to Weakness #6 of #1. Reviewer #3 (Public Review): Weakness #1: It is a strength of the paper that it analyses the function of dopamine neurons (DANs) at the level of single, identified neurons, and uses tools to address specific dopamine receptors (DopRs), exploiting the unique experimental possibilities available in larval Drosophila as a model system. Indeed, the result of their screening for transgenic drivers covering single or small groups of DANs and their histological characterization provides the community with a very valuable resource. In particular the transgenic driver to cover the DANc1 neuron might turn out useful. However, I wonder in which fraction of the preparations an expression pattern as in Figure 1f/ S1c is observed, and how many preparations the authors have analyzed. Also, given the function of DANs throughout the body, in addition to the expression pattern in the mushroom body region (Figure 1f) and in the central nervous system (Figure S1c) maybe attempts can be made to assess expression from this driver throughout the larval body (same for Dop2R distribution). We thank the reviewer for the positive comments and the suggestions. For the strain R76F02AD; R55C10DBD, we examined 22 third instar larval brains expressing GFP or Syt-GFP and Den-mCherry, all of them clearly labeled DAN-c1. Half of them only labeled DAN-c1, the rest have 1 to 5 weak labeled soma without neurites. Barely 1 or 2 strong labeled cells appear. These non-DAN-c1 neurons are seldom dopaminergic neurons. In VNC, 8 out of 12 do not label cells, 3 have 2-4 strong labeled cells. These data supported that R76F02AD;R55C10DBD exclusively labeled DAN-c1 in 3rd instar larval brains. [SEP] Justify:

Output: The text does not address the claim regarding olfactory receptors or their potential function through quantum effects. Instead, it discusses the function of dopamine neurons (DANs) and various methodologies used to analyze them, which is unrelated to the claim about olfactory receptors.


Input: Task: corroborate the claim using the given text. Claim: 3D printing is used to create custom prosthetics and implants tailored to individual patients. [SEP] Text: 7modeling in Meshmixer program: a) pre-made structures (loops and abutments) added on to original jaw model; b) implant modeling (bulking) by sculpt tool; c) pre-made structures and modelled (bulked) implant merged with original model; d) the 2nd copy of original model (dark grey) recalled and matched with model onto which implant was modelled (light grey); e) implant – result of Boolean operation (with lots of unwanted shells), f) implant (resultant) model superimposed on the original jaw modelFull size imageDuring the third step, interconnecting structures (straps) are modeled into saddle-like web connections using various brushes of the “” tool in Meshmixer (Figs. 7b and c). Abutments, retention loops, and peddles are connected by straps. The overall structure of the subperiosteal implant is usually designed to be 1. 5–1. 8 mm thick, which is an empirically defined value. During modeling, the implant is shaped slightly thicker by 0. 2–0. 3 mm to allow for later reduction and smoothing of its surface. Reduction is necessary because of the nature of the DMLS process, which results in printed parts with rough and oxidized surfaces. Supports also leave rough surface once removed; thus, extra thickness of metal must be included to enable reduction of the material. Boolean subtractionsubtraction operation is an essential part of custom implant additive modeling that results in a final product. The input for this computation consists of two models. The first model is an anatomical model of the bone and the second is the same anatomical model, but with modeled implant structure bulging from it. When the computer calculates the difference between these models - the resultant structure is the implant (Figs. 6, 7). Final stepsImplant contains small residual artifacts that have the appearance of small snowflake-like structures left behind after the Boolean operation. These small objects appear because of inconsistencies accumulated in virtual models during earlier manipulations. Such structures have to be removed manually and errors corrected using the above-mentioned software (Figs. 7e, 8a and b). Fig. [SEP] Justify:

Output: The text corroborates the claim as it details the process of creating an implant using software like Meshmixer, emphasizing the customization aspect through modeling and Boolean operations. It states that the implant is modeled based on an anatomical model of the bone, aligning with the idea of tailoring prosthetics and implants to individual patients.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: [34] have reported a negative correlation for increased Lactobacillus abundance in the cecum and ileum with weight of birds. This result emphasizes the need to be considerate of the type of Lactobacillus species, rather than the genus, when formulating probiotics applications. species in the poultry respiratory tract include Lactobacillus salivarius, Lactobacillus crispatus/acidophilus/gallinarum, Lactobacillus johnsonii/gasseri, Lactobacillus aviarius, and Lactobacillus reuteri [34]. Depending on the metabolic property and oxygen requirement of the bacteria, they can be classified as transient or colonizing species. For example, Lactobacillus aviaries is known as a transient species in the trachea because it is an obligate anaerobe found in relatively lower abundance [34, 37]. Experimental studies have demonstrated that Lactobacillus species exhibit immunostimulatory and antiviral properties [38,39,40]. Additionally, Lactobacillus acidophilus, Bifidobacterium bifidum, and Streptococcus faecalis species have been found to induce natural antibodies against various foreign antigens in chickens [41]. Table 1 A comprehensive summary of studies that present the most prevalent genera observed in the respiratory tract of poultryFull size tableIn addition to the complexity of the poultry respiratory microbiota, inconsistency exists regarding the microbial diversity within various sites in the poultry respiratory tract. One theory is that microbial diversity decreases posteriorly along poultry respiratory sites, from the nasal cavity to the lungs, which has been referred to as the island ecological model in human studies [42, 43]. This proposition is grounded in an ecological framework, suggesting that the nasal cavities serve as a microbiota mainland (source), with the highest richness and evenness of microbial species, acting as a source of microbial population for other respiratory sites (sink) [44]. Several poultry studies [18, 24, 45] are in conformation with this proposition. Interestingly, Abundo et al. [44] reported an exception to this model as BAL samples recorded significantly higher microbial diversity compared to the trachea. This exception is herein referred to as the spatial-anatomical model. [SEP] Justify:

Output: The text contrasts the claim by discussing the diversity of microbial species within the respiratory tract of poultry, indicating that microbial composition varies significantly within different sites, which suggests that microbiomes are not identical. It emphasizes that there are inconsistencies and variations in microbial diversity, reinforcing that microbiome composition is not uniform among individuals or species.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: For the question about the pattern of R76F02AD; R55C10DBD and the expression pattern of D2R in larval body, it is an interesting question. However, our main focus was on the central nervous system and the learning behaviors in fruit fly larvae, we may investigate this question in the future. Weakness #2: A first major weakness is that the main conclusion of the paper, which pertains to associative memory (last sentence of the abstract, and throughout the manuscript), is not justified by their evidence. Why so? Consider the paradigm in Figure 2g, and the data in Figure 2h (22 degrees, the control condition), where the assay and the experimental rationale used throughout the manuscript are introduced. Different groups of larvae are exposed, for 30min, to an odour paired with either i) quinine solution (red bar), ii) distilled water (yellow bar), or iii) sucrose solution (blue bar); in all cases this is followed by a choice test for the odour on one side and a distilled-water blank on the other side of a testing Petri dish. The authors observe that odour preference is low after odour-quinine pairing, intermediate after odour-water pairing and high after odour-sucrose pairing. The differences in odour preference relative to the odour-water case are interpreted as reflecting odour-quinine aversive associations and odour-sucrose appetitive associations, respectively. However, these differences could just as well reflect non-associative effects of the 30-min quinine or sucrose exposure per se (for a classical discussion of such types of issues see Rescorla 1988, Neurosci, or regarding 1988, Behav Genetics, or with some reference to the original paper by Honjo & Furukubo-Tokunaga 2005, J Neurosci that the authors reference, also Gerber & Stocker 2007, Chem Sens). As it stands, therefore, the current 3-group type of comparison does not allow conclusions about associative learning. We adopted this single odor larval learning paradigm from Honjo’s papers1,2. In these works, Honjo et al. first designed and performed this single odor paradigm for larval olfactory associative learning. [SEP] Justify:

Output: The text is irrelevant to the claim regarding olfactory receptors functioning through quantum effects. It primarily discusses issues related to associative memory and the experimental design of learning behaviors in fruit fly larvae without addressing any aspects of quantum mechanics or olfactory receptors.


Input: Task: corroborate the claim using the given text. Claim: 3D printing can create patient-specific surgical models for preoperative planning. [SEP] Text: Can 3D surgical planning and patient specific instrumentation reduce hip implant inventory? A prospective study Download PDF Download eeOpen access Published: 23 September 2020 Can 3D surgical planning and patient specific instrumentation reduce hip implant inventory? A prospective study : orcid. org/0000-0002-4212-37411,2, Johann Henckel1, Harry Hothi1,2 & …Alister Hart1,2 Show authors 3D Printing in Medicine 16. 020). The patientsWe recruited a consecutive series of 45 patients undergoing primary THA for osteoarthritis. In the initial group selected for the feasibility part of the study there were 14 males and 11 females (mean age 64. 36 years, range 39–81); in the experimental group of the pilot study there were 9 males and 11 females (mean age 71. 65 years, range 54–79). Table 1. Table 1 Patient demographicsFull size tableAccording to the literature, the accuracy for size component prediction with CT planning is around 90%, achieved with a minimum of 25 patients (alpha level 0. 05, power of 80%) [16, 17]. The number of patients in this study was chosen to provide a reasonable estimate of accuracy as well as reproducibility prior to starting a prospective study [19, 20]. CT scanning protocolAll patients underwent pre-operative CT-scanning of the hip region and the knee joint according to a standard protocol. The scanning protocol is specifically designed to minimize radiation dose, while ensuring a good spatial accuracy. Image acquisition consisted of two short spiral axial scans: one including the whole pelvis (starting at least 2 cm above the iliac crests and continue to at least 10 cm below the lesser trochanter) and the proximal femur; the second including the distal part of the femur in the affected side at least 2 cm above the posterior condyles and extend down to the distal condyles towards the tibia [21]. 3D surgical planning(and Communications in Medicine) data was transferred to the MyHip 3D reconstruction planning software to create a patient specific 3D model of the pelvis and femurs of the subject. The engineers at Medacta planned the position and size of the prosthesis according to the surgeon’s p1. Fig. 1MyHip planning software. [SEP] Justify:

Output: The text corroborates the claim by providing details on the use of 3D surgical planning to create patient-specific 3D models for preoperative purposes. It mentions that data from pre-operative CT scanning was used to create a patient-specific 3D model of the pelvis and femurs, which directly supports the assertion that 3D printing can be utilized for creating surgical models tailored to individual patients.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: This model is based on the concept that the unique anatomical and physiological functions of each distinct respiratory site dictate the richness and evenness of its microbial residents. This would imply that constant mucociliary clearance occurring in the trachea contributes to its reduced microbial richness in comparison to LRT sites, where microbial deposition contributes to its higher microbial diversity [46]. Indeed, further studies are needed to clarify whether poultry respiratory sites exhibit a source-sink or unique microbial diversity trend. Influencing factors on poultry respiratory microbiota community composition and diversityThe composition and diversity of the respiratory microbiota in poultry are influenced by various factors. These include intrinsic host-related factors such as bird type, breed, age, and genetics, as well as several extrinsic factors. Extrinsic factors include production system, sampling sites and methods, sequencing platforms, and methodologies (choice of PCR primers, regions to be sequenced, number of PCR cycles, DNA extraction protocols), as well as nutrition, antibiotics use, disease, and environmental stressors such as heat and litter quality. The interplay of these factors contributes to the complexity of the poultry respiratory microbiota. A synthesis of available information on the most decisive determinants of the poultry respiratory microbiota (presented in Fig. 2) are described below:Fig. 2Factors shaping community structure and diversity of poultry respiratory microbiota. The interplay between intrinsic factors (highlighted in orange) and extrinsic factors (highlighted in grey) significantly influences the community structure and diversity of the poultry respiratory microbiota. The respiratory site itself, shaped by distinct physiological functions, determines the microbial residents, resulting in unique bacterial communities across various respiratory sites. Additionally, avian species type governs microbiota composition, notably between chickens and turkeys. Age is a critical factor, with microbial colonization increasing until an age-independent plateau is reached. However, this process is impacted by diverse stressors, environmental conditions, and management practices. Factors such as ammonia pollution, heat stress, antibiotic usage, and pathogen presence, especially viruses, can disrupt microbiota balance, potentially leading to dysbiosis. Understanding these intricate relationships is crucial for a comprehensive comprehension of avian respiratory microbiota dynamicsFull size imageIntrinsic factorsAs highlighted in our description of the spatial-anatomical model of microbial diversity in the respiratory tract, the distinct physiological and adaptive functions of each respiratory site determine its specific microbial residents. [SEP] Justify:

Output: The text contrasts the claim by explaining that microbiome composition is influenced by various intrinsic and extrinsic factors, which lead to unique microbial communities across different respiratory sites. It elaborates on how factors such as bird type, breed, age, and genetics, along with production systems and environmental stressors, affect the diversity and composition of the microbiota, indicating that there is not an identical microbiome across individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: To address the reviewer’s question about the potential non-associative effects of the 30-min quinine or sucrose exposure, we would like to defend it primarily based on results from Honjo et al. (2005 and 2009). They applied the odorant to the larvae after training, only the ones had paired training with both odor and unconditioned stimulus (quinine or sucrose) showed learning responses. Larvae exposed 30 min in only odorant or unconditioned stimulus did not show different response to the odor compared to the naïve group1,2. To validate this paradigm induces associative learning responses, they also tested the paradigm from three aspects: (1) The odor responses are associative. Honjo et al. showed only when the odorant paired with unconditioned stimulus would induce corresponding attraction or repulsion of larvae to the odor. Neither odorant alone, unconditioned stimulus alone, nor temporal dissociation of odorant and unconditioned stimulus would induce learning responses. (2) The odor responses are odor specific. When applied a second odorant that was not used for training, larvae only showed learning responses to the unconditioned stimulus paired odor. This result ruled out the explanation of a general olfactory suppression and indicates larvae can discriminate and specifically alter the responses to the odor paired with unconditioned stimulus. Although the two-odor reciprocal training is not used, these results can show the association of unconditioned stimulus and the corresponding paired odor. (3) Well known learning deficit mutants did not show learned responses in this learning paradigm. Honjo et al. tested mutants (e. g. , rut and dnc) showing learning deficits in the adult stage with two odor reciprocal learning paradigm. These mutant larvae also failed to show learning responses tested with the single odor larval learning paradigm. (4) In our study, we used two distinct odorants (pentyl acetate and propionic acid), as well as two D2R knockdown strains (UAS-miR and UAS-RNAi for D2R). We obtained similar results for larvae with D2R knockdown in DAN-c1. In addition, our naïve olfactory, naïve gustatory, and locomotion data ruled out the possibilities that the responses were caused by impaired sensory or motor functions. Comparison with the control group (odor paired with distilled water) ruled out the potential effects if habituation existed. [SEP] Justify:

Output: The text is irrelevant to the claim because it discusses the associative learning responses of larvae in experiments involving odor and unconditioned stimulus but does not mention olfactory receptors or any potential quantum effects related to their function.


Input: Task: corroborate the claim using the given text. Claim: 3D printing can create patient-specific surgical models for preoperative planning. [SEP] Text: Examples of landmark selection a on the femur, b pelvis and c knee for the acquisition of the relevant anatomical and functional axes and planesFull size imageOnce the operator has selected all landmarks, he proceeds with adjusting the cut height. During the planning of the stem position and of the femoral head resection, all parameters related to the femoral resection in terms of cut height, cut angle and cut anteversion can be modified according to the surgeons’ planning philosophy. The stem is positioned in terms of AP (anterior/posterior) and ML (medial/lateral) offset from the default position, Fig. 2a. Fig. 2Examples of images from the MyHip software: a Preoperative planning of the femoral component, b anteversion view, c preoperative planning of the acetabular component positioned with 45° of inclination and 15° of anteversion (Lewinnek safe zone)Full size imageThe stem size is chosen to achieve a good fit in the intramedullary canal and head size is selected to adjust the femoral offset. Stem version (Fig. 2b), leg length adjustment, cup positioning can all be adjusted to achieve optimal alignment between the two legs (using the lesser trochanter as a reference). The surgeon defines the acetabular reaming depth and the acetabular angles (anteversion and inclination). Different spatial views are available, the operator can change the size of component among those available, while adjusting the level of fit-and-fill, Fig. 2. The result of the previous steps can be evaluated in the so-called global view and the leg length view. While the first one is focused on the affected side, the second one involves the contralateral side for comparison. This view is used to check the alignment between the two femurs, using the lesser trochanter as reference, Fig. 3. Fig. 3Example of (a) the global view and (b) leg length view after planning. While the first displays the affected side, the second one involves the contralateral side too. This view is used to check the alignment between the two femurs, using the lesser trochanter as reference. [SEP] Justify:

Output: The text corroborates the claim by detailing a process of preoperative planning that involves adjusting various parameters related to surgical models, such as stem position, femoral head resection, and acetabular angles. The mention of selecting anatomical landmarks and modifying parameters suggests a tailored approach to surgery, which is aligned with the use of patient-specific surgical models that can be created using 3D printing technology.


Input: Task: contrast the claim using the given text. Claim: Everyone's microbiome composition is identical. [SEP] Text: Hence, it is not surprising that the respiratory site under consideration is a factor that potentially influences microbiota composition and diversity. Several poultry studies have reported distinct bacterial communities across different respiratory sites [5, 24, 25, 34]. Sohail et al. [12] also reported distinct spatial bacterial ecology between the ceca and trachea using Polymerase chain reaction/denaturing gradient gel electrophoresis (PCR/DGGE) fingerprinting methodology. Tracheal samples were predominantly dominated by and Oscillospira whereas cecal samples had Aerococcus, Anaerococcus, Globicatella, Lactobacillus, Nosocomiicoccus and Staphylococcus as the prevailing genera in their study. In conformation with results from Sohail et al. [12] study, Kallapura et al. [47] also reported a higher rate of Salmonella recovery in the trachea compared to the ceca. This disparity could possibly be because of the two mucosa milieus, the trachea is the easiest route for microbe entry and colonization. Additionally, longer feed retention time, and lower pH afford the ceca its unique bacterial composition and diversity [48]. Taylor et al. [18] provided unique perspective on the peculiarity of the poultry respiratory tract microbiota, as they report unique microbiota compositions of the avian trachea and nasal cavity. It is speculated that the avian trachea harbors more transient species compared to the nasal cavity. Similar observations have been reported in the human respiratory tract [6, 49]. Furthermore, the type of poultry bird is another factor that reportedly dictates the composition and diversity of the poultry respiratory tract microbiota. Although some bacterial taxa overlap occur, distinct differences in the URT microbiota (trachea) of chickens and turkeys have been reported [9]. Kursa et al. [9] further showed that the chicken trachea harbors significantly greater bacterial diversity compared to the turkey trachea. This difference in respiratory microbiota composition and diversity is speculated to be confounded by the age of the flocks, as the average age of chickens and turkeys from which samples were obtained in the study was 30 and 25 weeks, respectively [9]. The impact of age on the composition and diversity of the microbial communities in the avian respiratory tract has received less attention compared to the gut. [SEP] Justify:

Output: The text contrasts the claim by explaining that there are distinct bacterial communities and differences in microbiota composition across various sites in poultry, as well as highlighting the unique bacterial diversity in the avian respiratory tract. It states that different poultry species and locations (like the trachea and ceca) have varied microbiota, indicating that microbial communities are not identical across all individuals.


Input: Task: pass the claim using the given text. Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: All these results supported this single odor learning paradigm is reliable to assess the learning abilities of Drosophila larvae. And the failure of reduction in R. I when larvae with D2R knockdown in DAN-c1 were trained in quinine paired with the odorant is caused by deficit in aversive learning ability. We will add a paragraph to address this in the Discussion part. Weakness #3: A second major weakness is apparent when considering the sketch in Figure 2g and the equation defining the response index (R. I. ) (line 480). The point is that the larvae that are located in the middle zone are not included in the denominator. This can inflate scores and is not appropriate. That is, suppose from a group of 30 animals (line 471) only 1 chooses the odor side and 29, bedazzled after 30-min quinine or sucrose exposure or otherwise confused by a given opto- or thermogenetic treatment, stay in the middle zone. . . a P. I. of 1. 0 would result. It is a good question. We gave 5 min during the testing stage to allow the larvae to wander in the testing plate. Under most conditions, more than half of larvae (>50%) will explore around, and the rest may stay in the middle zone (will not be calculated). We used 25-50 larvae in each learning assay, so finally around 10-30 larvae will locate in two semicircular areas. Indeed, based on our raw data, a R. I. of 1 seldom appears. Most of the R. I. s fall into a region from -0. 2 to 0. 8. We should admit that the calculation equation of R. I. is not linear, so it would be sharper (change steeply) when it approaching to -1 and 1. However, as most of the values fall into the region from -0. 2 to 0. 8, we think ‘border effects’ can be neglected if we have enough numbers of larvae in the calculation (10-30). Weakness #4: Unless experimentally demonstrated, claims that the thermogenetic effector shibire/ts reduces dopamine release from DANs are questionable. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses issues related to odor learning in Drosophila larvae and the methodological weaknesses of a study, rather than addressing olfactory receptors' potential quantum effects. There is no mention or implication of quantum effects or studies related to olfactory receptors, making it unrelated to the claim.


Input: Task: corroborate the claim using the given text. Claim: 3D printing can create patient-specific surgical models for preoperative planning. [SEP] Text: The red model (arrow) represents the pre-op position and the green is the post-op oneFull size imageA single, cementless implant system was used (Quadra-H System femoral components and acetabular components, Medacta, Switzerland). Surgical guides and anatomical models were produced by Sintering technology (SLS). PA 2200, a type of nylon that is a special moulding material developed by German EOS for their SLS rapid prototyping equipment, was used for 3D printing. (EOS, Munich, Germany). The components were sterilised either using gamma irradiation and delivered to our hospital or autoclaved at the hospital before intra-operative use. Intra-operative assessment and use of PSIFor each patient, the planned sizes of acetabular and femoral components were recorded and compared to the actual sizes used at surgery. Complications such as intra-operative femoral fracture was also recorded. During surgery, a patient-specific instrument guide was used to position the cup and cut the femoral neck, Fig. 4. Fig. 4The acetabular and femoral PSI guides. The acetabular guide is seated into the acetabulum, and two pins are inserted through attached drill sleeves. The guide is removed, leaving the two pins to act as either a constrained or unconstrained guide to reaming and component placement (a). The femoral guide has a contoured fit to the femoral neck/head and is kept in place for the neck cut by two intraosseous pins (b) [13]Full size imageThe acetabular guide was 3D printed to match the acetabular rim. Once seated into the acetabulum two pins were inserted through attached drill sleeves. The guide was then removed, leaving the two pins to act as either a constrained or unconstrained guide to reaming and component placement. The femoral PSI guide was 3D printed to fit the contours of the femoral head-neck junction (ie, no cartilage present at this junction). Once seated, it was secured with two threaded pins. The femoral neck cut was then completed using a standard method, with the saw blade flush on the cutting surface of the guide to deliver a femoral cut at the planned angle and location. [SEP] Justify:

Output: The text corroborates the claim by providing specific examples of how 3D printing technology was utilized to create patient-specific surgical guides and anatomical models for preoperative planning. It describes the use of patient-specific instrument (PSI) guides for positioning implants during surgery, indicating the capability of 3D printing to produce tailored models for individual patient anatomy, thus directly supporting the assertion in the claim.