Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-2906983/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Published03 Nov, 2023Read the published version in BMC Psychiatry →Version 1posted 9You are reading this latest preprint versionAbstractBackground: Patient-reported outcome measures (PROM) provide clinicians with information about patients’ perceptions of distress. When linked with treatment and diagnostic registers, new information may be obtained, such as associations with prevalence and service use. This study aimed to examine psychological symptoms among psychiatric outpatients and to investigate treatment-relevant characteristics of symptom-homogeneous classes. Methods: In a cohort study of 2473 (63% female) outpatients, factor mixture modelling (FMM) was used to analyse self-reported symptoms of anxiety and depression before treatment, and the classes association with functional impairment, the prevalence of common mental health disorders (CMHD) and the number of assessments and psychotherapy appointments one year after treatment start. Results: Overall, 22% of patients with a CMHD had an additional comorbid mood/anxiety disorder. This comorbid group reported higher symptoms of anxiety and depression compared to patients with non-comorbid anxiety disorders. FMM revealed three classes: “anxiety and somatic depression” (33%), “mixed depression and anxiety” (40%), and “cognitive depression” (27%). The anxiety and somatic depression class was associated with older age, being single and on sick leave, higher probability of depressive-, anxiety-, and comorbid disorders, having more appointments and higher functional impairment. Although the cognitive depression class had less somatic distress than the mixed depression and anxiety class, they reported more functional impairment and had higher service use. Conclusions: The results demonstrate the clinical relevance of applying FMM to PROM data of depression, anxiety, and functional impairment when linked with treatment registers. Three patient groups emerged, with different symptom patterns. Higher symptom severity did not necessarily imply more functional impairment and service use when subdimensions and latent patient groups were accounted for. Patient-reported outcome measuresLatent class analysisFactor mixture modelsCommon mental disordersComorbidityFiguresFigure 1IntroductionPatient-reported outcome measures (PROM) have been increasingly applied to encourage patient involvement (1). [SEP] Justify:

Output: The text corroborates the claim by discussing the prevalence of common mental health disorders (CMHD), specifically stating that 22% of patients with a CMHD had additional comorbid mood/anxiety disorders. This highlights that depression and anxiety are not only prevalent but also often occur together, supporting the assertion that these disorders are among the most common globally.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Each group selects a reporter who will report out each group's findings. While the students sort the pasta, the instructor will write the early form of the on the board that is described in Table 3A. The instructor will then use the student's reports to fill in the blanks. The final version of the Table is described in Table 3B. Mimic antibiotic treatment (5 minutes). The antibiotic treatment that was first described by Estes (14) will take no more than 5 minutes. Since broad spectrum antibiotics typically get rid of more bacteria than just the targeted pathogen, long and curved pasta will be removed from those of the bags that contain these types of pasta. This reflects how an antibiotic can impact multiple types of bacteria. Students who received the dairy diet resembling bag of pasta will now have an empty bag and students who received the omnivore diet resembling pasta bag will still have a reasonably full bag of pasta (Figure 2). The instructor should guide discussion so students notice that some bags are emptier than others and that the number of different types of pasta has decreased in all bags except the meat diet resembling bag. These observations simulate a decrease in the biodiversity of the gut microbiome after antibiotic treatment, accompanied by empty niches in which new bacteria can colonize. Students then fill up these empty spaces in the pasta bags with the beans that simulate the environmental bacteria (Figure 2). Upon close inspection, some student groups will notice the presence of yellow or green lentils in their pasta bags, resembling infection with C. difficile. Note that only student groups who received green lentils which are indicative of toxin-producing C. difficile will 'develop symptoms. ' Figure 2. An example of the antibiotic treatment. On the left side, students received a pasta bag that resembles an omnivore diet and contains seven different types of past. On the right side, the pasta bag is representative of a dairy diet and contains only long pasta. The first row is the original pasta bag that students received. The second row shows the respective pasta bags after long and curved pasta were removed in the simulation of antibiotic treatment that reduces different types of bacteria, but not all types. In the third row, students filled up the now empty spaces with beans from the bean bag. Beans resemble environmental bacteria that move into niches in the gut that the antibiotic treatment cleared out. A small number of these beans are lentils which represent C. difficile. [SEP] Justify:

Output: The text contrasts the claim by demonstrating that different dietary conditions can lead to varying outcomes in the gut microbiome's biodiversity. It discusses how students' pasta bags, representing different diets, have differing levels of bacteria post-simulation, suggesting that diet indeed influences microbiome composition. For example, the dairy diet resulted in an emptier bag with reduced diversity compared to the omnivore diet, illustrating direct dietary impacts on bacterial populations.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Although we leave a more complete treatment to future studies, Figure S2 in 2 shows that in the presence of deleterious mutations, intermediate rates of sex can be maintained even when a substantial number of loci are segregating for sexually antagonistic variation (it also shows that extrapolation from the two-locus model generally still provides correct quantitative predictions). In the next section, we suggest possible experimental tests of the overall direction and strength of selection for sex arising from differences in selection between the sexes. this 0. 01 when the haploid mutation rate U is around 2, the strength of selection against mutations in females is and selection is about five or six times stronger in males. As shown in this 2. Given that sex differences in selection are likely to give rise to polymorphisms involving both deleterious mutations and sexually antagonistic alleles, is the net effect likely to favor or disfavor sex? The answer to this question is largely an empirical issue, depending on the relative frequencies of such mutations and their effects (note that sexually antagonistic variation is likely to be less important when the baseline rate of sex is low, as it is more difficult to maintain such variation—see 1. Experimental evidence that sexual selection helps to purge the female mutation load remains scarce. A few studies have measured the effect of specific mutations on male and female fitness (see 2001. Sexual selection and the maintenance of sexual reproduction. Nature 411:692–695. 2009. Spatial heterogeneity and the evolution of sex in diploids. Am. Nat. 174:S54–S70. . H. 1995. A general model for the evolution of recombination. Genet. Res. 65:123–144. 2005. Evolution of recombination due to random drift. Genetics 169:2353–2370. 1991. Natural and sexual selection on many loci. Genetics 127:229–255. 2010. Higher rates of sex evolve in spatially heterogeneous environments. Nature 468:89–93. 1982. The masterpiece of nature. Univ. of California Press, Berkeley, CA. 2001. Negative genetic correlation for adult fitness between sexes reveals ontogenetic conflict in Drosophila. Proc. Natl. Acad. Sci. USA 98:1671–1675. 1930. The genetical theory of natural selection. Oxford Univ. Press, Oxford, U. K. 2007. [SEP] Justify:

Output: The text does not directly support or contradict the claim about natural selection driving evolution through differential survival. Instead, it discusses the complexity of sexual reproduction and selection, including the maintenance of intermediate rates of sex in the presence of deleterious mutations, without clearly addressing the specific mechanisms of natural selection or its role in the evolution of species.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: PROM can be helpful in the diagnostic process of common mental health disorders (CMHD) (2) and is often implemented to facilitate service planning (3). Since accessible quality indicators about patients’ needs often are rudimentary and lack diagnostic and symptomatic information (4), PROM data could help providers to facilitate person-centred services (1,2). Although linking PROM with register data is underutilized, important knowledge about patients may be obtained by connecting these sources of information (3). One potential outcome of combining PROM- and register data is to increase the knowledge about specific groups of patients, such as those with comorbid disorders. Compared to patients with non-comorbid CMHD, patients with comorbidity have been associated with higher service utilization, higher symptom severity, and higher levels of functional impairment (5). One PROM study which examined comorbidity in outpatient treatment showed that 45% of patients with an anxiety disorder had comorbid depression, 64% with post-traumatic stress disorder (PTSD) had a depressive disorder, and that comorbid depression was associated with higher symptom severity both before and after treatment (6). Studies like these demonstrate the additive value of PROM data linked with diagnostic registers of CMHD. Thus, collecting and combining PROM data on depression and anxiety with diagnostic information could add accumulated knowledge and improve person-centred services. Another potential of PROM data is the possibility offered to analyse symptom severity across the whole sample, capturing symptom heterogeneity beyond diagnoses. Mixture model analysis has become a frequently applied statistical framework to aggregate symptom heterogeneity into a smaller set of homogeneous groups. One model specification, latent class analysis (LCA), has been used to analyse symptoms of depression and anxiety simultaneously, and class indicators have identified important sub-samples in non-clinical adult populations (7–14) and clinical adult populations (15,16). In the latter two studies, three class solutions were identified, labelled by a gradient of symptom severity, where the higher severity classes were more strongly associated with CMHD, and with a decreased association with mild and low severity classes. LCA, however, has been criticized when applied to detect homogeneous subgroups of CMHD (17) because of the strict methodological requirements of local independence: class indicators should only depend on the latent classes and not correlate. This is an unrealistic requirement for symptoms of depression and anxiety due to their frequent co-occurrence. [SEP] Justify:

Output: The text corroborates the claim by discussing comorbid disorders related to depression and anxiety, particularly noting that a significant percentage of patients with anxiety also experience depression. It highlights that 45% of patients with an anxiety disorder concurrently have comorbid depression, demonstrating the prevalence of these disorders. Furthermore, the references to higher service utilization and symptom severity in patients with comorbid conditions indicate the commonality of depression and anxiety in mental health diagnoses.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Mapping the in class simulation to research on the gut microbiome (35 minutes). The advanced part of the exercise will be to identify specific microbes, as well as their metabolic products in dependence on the diet. Students will perform seven tasks, each of which should take approximately 5 minutes. The first task is to use the Nature paper on the Project (1) to identify the nine phyla of bacteria that contribute to the gut microbiome. These are and Verrucomicrobia. Among these, Firmicutes and Bacteroides are predominant. Second, students will determine the predominant bacteria in the gut microbiome of a person who lives on a dairy diet. Typically, newborn babies live on a diet that consists exclusively of milk. Students will be referred to Koenig and coworkers (16) who investigated the changes in the growing infant's gut microbiome that accompany the transition from a dairy diet to adult food. The information that is pertinent to this pasta simulation can be found in the first paragraph of the introduction. While the gut of the newborn baby is almost sterile, the vaginal microbiome of the mother serves as the first source of bacteria, mainly of the genus Bifidobacteria. The growth of these bacteria is further supported by the milk diet, as Bifidobacteria metabolize and degrade oligosaccharides that are provided with the milk and cannot be degraded by the human intestine. Bacteroidetes are also found in breast milk and help the baby transition to the adult gut microbiome and a more diverse diet. Students will report Bifidobacteria as an indicator of a dairy diet and the instructor will include this information in the Table (Table 3) on the board in column 8 (Bacteria). Students will note the Koenig reference in column 9 (Reference). For the student's information, Bifidobacteria belong to the phylum Actinobacteria. The third task is to find information in the Portune paper (15) on the predominant bacteria in adult humans who live on a diet that consists predominantly of meat. According to Table 1 of this paper (15), people with this diet have a gut microbiome that includes bacteria of the genera Alistipes, Bilophila, and Bacteriodes (24). Students will find these in the Table and the instructor will add the bacteria to Table 3 on the board, column 8. Task 4 is to identify the bacteria that are predominant in people on a plant diet. [SEP] Justify:

Output: The text contrasts the claim by detailing how different diets result in varying microbiome compositions. It specifically discusses how the gut microbiome of a newborn baby develops from a sterile state to a more diverse one as the diet changes from exclusively milk to adult food. The reference to the study by Koenig highlights the changes that occur in the microbiome due to dietary transitions, indicating that diet has a significant impact on microbiome composition.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: The evolution of sex and recombination in response to abiotic or coevolutionary fluctuations in epistasis. Genetics 175:1835–1863. 2007. Sexual selection and the evolution of obligatory sex. BMC Evol. Biol. 7:245. 1980. Sex versus non-sex versus parasite. Oikos 35:282–290. 2010. The role of advantageous mutations in enhancing the evolution of a recombination modifier. Genetics 184:1153–1164. 2003. Recombination can evolve in large finite populations given selection on sufficient loci. Genetics 165:2249–2258. 2006. Interference among deleterious mutations favours sex and recombination in finite populations. Nature 443:89–92. 1977. Regions of stable equilibria for models of differential selection in the two sexes under random mating. Genetics 85:171–183. 2002. General models of multilocus evolution. Genetics 161:1727–1750. 1987. Anisogamy, sexual selection, and the evolution and maintenance of sex. Evol. Ecol. 1:95–105. 2000. The evolution of recombination in a heterogeneous environment. Genetics 156:423–438. 1998. Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland, MA. 2011. Inbreeding reveals stronger net selection on Drosophila melanogaster males: implications for mutation load and the fitness of sexual females. Heredity 106:994–1002. 1984. Males and the advantage of sex. J. Theor. Biol. 108:215–220. 1971. The origin and maintenance of sex. 1932. Some genetic aspects of sex. Am. Nat. 66:118–138. 1993. The evolution of multilocus systems under weak selection. Genetics 134:627–647. 2003. The advantages of segregation and the evolution of sex. Genetics 164:1099–1118. 2009. The evolutionary enigma of sex. Am. Nat. 174:S1–S14. . P. , and N. H. Barton. 1997. The evolution of recombination: removing the limits to natural selection. Genetics 147:879–906. 2001. Selection for recombination in small populations. Evolution 55:1921–1931. . P. , and D. Bourguet. [SEP] Justify:

Output: The text provides a comprehensive list of references and topics related to evolutionary biology, encompassing subjects such as sexual selection and recombination, but does not specifically address or support the claim regarding natural selection and differential survival. As a result, the information appears irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: The advantage of factor mixture modelling (FMM) over LCA is that FMM does not assume conditional independence of latent classes (18) and therefore has been suggested to be more suitable in psychiatric research (19). Applying FMM with class indicators of depression and anxiety has been conducted within general adult populations (20), and for people with a lifetime episode of depression (21), but rarely within a clinical mental health setting. The scope of the current study is two-folded: first, to examine the one-year prevalence of CMHD in a diagnostic register and their association with patient-reported symptom severity in a large cross-sectional heterogeneous psychiatric outpatient sample. In accordance with previous research, we hypothesize comorbid mood and anxiety disorders to be frequently occurring, associated with higher symptom severity, and higher service use. Second, to identify homogeneous subgroups based on self-reported symptoms of depression and anxiety and analyse their association with clinician-assessed mental disorders and other clinically relevant covariates. Due to the exploratory nature of FMM, the numbers of identified classes are not hypothesized a priori. Methodspatients requiring non-urgent specialized mental health treatment are typically referred by their general practitioners to district psychiatric outpatient clinics for treatment. At one such clinic, electronic PROM data was collected between February 2020 and February 2022. All patients with a first assessment were invited to participate. Groups of patients with a primary diagnosis of obsessive-compulsive disorder (OCD), schizophrenia, substance abuse, and elderly patients, were treated at other specialized units. Out of 2519 patients who consented to participate, patients with missing information on all self-report questionnaires were excluded (n = 46). The final sample consisted of 2473 outpatients (79% of the invited participants; see Table 1). Out of the participating patients, 97% also had available register data with diagnostic and treatment information. information was extracted for age, gender, self-reported relationship status, and work status. Diagnostic information in accordance with the ICD-10 (Organization, 2016) and the number of appointments was collected until one year after the self-reported symptom assessment (extraction date in March 2023). Diagnoses were manually clustered into bipolar, depressive, anxiety, PTSD, somatization, and comorbid mood/anxiety disorder. [SEP] Justify:

Output: The text corroborates the claim by discussing the prevalence of mood and anxiety disorders within a psychiatric outpatient sample, specifically mentioning 'comorbid mood and anxiety disorders to be frequently occurring.' This aligns directly with the assertion that depression and anxiety are common mental health disorders.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: These too are listed in Table 1 (15) and include Roseburia, Eubacterium rectale, and Ruminoccus bromii, all from the phylum Firmicutes. These bacteria will go in Table 3, column 8. By this time, the students will have assigned specific bacteria to the different types of pasta in their snack bags and the instructor will have constructed Table 3B, on the board. There should be about 15 min left of class time. The remaining three tasks focus on how changes in the diet to high fat, high fiber, or high protein impact the gut microbiome and specific bacterial metabolic pathways that will lead to the respective metabolic products excreted into the human intestine. This is the next step in the signal transduction pathway from the diet to the ultimate impact on human health and will transition students for the follow up homework assignment. The relevant information is listed in Tables 1, 2, and 3 of the Portune paper. To complete the in class part of the exercise, students will need to identify metabolic products that the bacteria secrete and that contribute to human health. As one example, high fiber diet leads to an increase in Bifidobacteria and Lactobacilli, which are considered probiotics and produce short chain fatty acids including acetate, propionate, and butyrate (27). While it is not fully understood which metabolic products these bacteria produce, long chain fatty acids themselves can reduce short chain fatty acids in the gut, which favors a pro-inflammatory environment (28). Diseases that result from this include obesity, type 2 diabetes, and colon cancer. active learning activity will conclude with a follow up homework assignment. So far, students have studied the composition of the gut microbiome in response to the respective diets and identified metabolic byproducts that some of these bacteria produce and excrete into the host intestine. During the three days following the in class time, students will get together in their group and concentrate on the part of the Portune paper (15) that focuses on the link between changes in the gut microbiome/bacterial metabolic products and the resulting diseases, as well as the molecular response in the host intestinal cells that contributes to chronic inflammation. To limit the scope of the paper, students will focus on a high fat diet (section 2). Students will summarize their findings in a short paper of 1-2 pages of text including a figure. [SEP] Justify:

Output: The text contrasts the claim by discussing how dietary changes, such as high fat, high fiber, or high protein diets, impact the gut microbiome and bacterial metabolic pathways. It specifically mentions that a high fiber diet leads to an increase in beneficial bacteria like Bifidobacteria and Lactobacilli, which produce short chain fatty acids. This indicates that changes in diet can indeed alter the composition of the microbiome, directly contradicting the claim.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: 1999. Balanced polymorphisms and the evolution of dominance. Am. Nat. 153:561–574. 1999. The red queen and fluctuating epistasis: a population genetic analysis of antagonistic coevolution. Am. Nat. 154:393–405. 2006. Intralocus sexual conflict diminishes the benefits of sexual selection. PLoS Biol. 4:e356. 2007. An evolutionary cost of separate genders revealed by male-limited evolution. Am. Nat. 169:29–37. 1992. Sexually antagonistic genes: experimental evidence. Science 256:1436–1439. 2001. Intersexual ontogenetic conflict. J. Evol. Biol. 14:685–693. 2006. The Hill-Robertson effect and the evolution of recombination. Genetics 173:1793–1811. 2010. Deleterious mutations and selection for sex in finite, diploid populations. Genetics 184:1095–1112. 2009. On the causes of selection for recombination underlying the hypothesis. Am. Nat. 174:S31–S42. 2008. Mating density and the strength of sexual selection against deleterious alleles in Drosophila melanogaster. Evolution 62:857–867. 2001. Sexual selection and the maintenance of sex. Nature 411:689–692. 1990. Allele-frequency change in a class-structured population. Am. Nat. 135:95–106. 1976. Sexual selection and resource-accruing abilities in Anolis garmani. Evolution 30:253–269. 2000. Fixation of new alleles and the extinction of small populations: drift load, beneficial alleles, and sexual selection. Evolution 54:1851–1861. 2009. Purging the genome with sexual selection: reducing mutation load through selection on males. Evolution 63:569–582. 4. [SEP] Justify:

Output: The text does not directly address the claim regarding natural selection and differential survival. Instead, it lists various studies and topics related to evolutionary biology, but does not provide any evidence or argument about natural selection driving evolution. Therefore, it is deemed irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: ResultsOverall, 63% (n = 1524) of the patients were diagnosed with a CMHD (bipolar, depressive, PTSD, anxiety, or somatization disorder). Further, 2% (n = 55) were registered with a mixed anxiety depressive disorder without a comorbid CMHD. Other frequent prevalent diagnoses for patients with no CMHD were attention deficit hyperactivity disorder (10%, n = 245) and personality disorders (4%, n = 106), and symptoms and signs involving emotional state (R45, 21%, n = 496). One year’s prevalence of comorbid CMHD was the following: for patients diagnosed with bipolar disorder (n = 125), 25% also had a depressive disorder, 8% had PTSD, 17% had an anxiety disorder, and 6% had somatization disorder. Out of patients diagnosed with a depressive disorder (n = 865), 4% were also diagnosed with bipolar disorder, 6% with PTSD, 28% with anxiety disorder, and 3% with somatization disorder. Regarding PTSD (n = 245), 4% were diagnosed with bipolar disorder, 23% with depressive disorder, 9% with anxiety disorder, and 2% a somatization disorder. Regarding anxiety disorders (n = 613), 3% had bipolar disorder, 39% had depressive disorder, 3% had PTSD, and 5% had somatization disorder. Of patients with somatization disorder (n = 92), 8% had bipolar disorder, 30% had a depressive disorder, 7% had PTSD, and 32% had an anxiety disorder. Overall, 22% of patients diagnosed with a CMHD had a comorbid mood and anxiety disorder. Correspondingly, 14% of all patients with diagnostic data had a comorbid mood and anxiety disorder. Patients with comorbid disorders scored higher symptom severity of depression and anxiety than patients diagnosed with non-comorbid disorders, with the only exception of symptoms of anxiety for somatization disorders (Table 1). 1 here Patients with bipolar disorders had a mean of 4. 37 (SD = 3. 65) assessments, and 11. 23 (SD = 9. 71) psychotherapy appointments. For depressive disorders, these numbers were 3. 86 (SD = 4. 10), and 11. 60 (SD = 8. 78) respectively. Patients with anxiety disorders had 3. 72 (SD = 3. 91) assessments and 10. 64 (SD = 8. [SEP] Justify:

Output: The text corroborates the claim by providing statistical data showing that a significant percentage of patients are diagnosed with common mental health disorders (CMHD), including depressive and anxiety disorders. Specifically, it notes that 63% of patients were diagnosed with a CMHD, indicating a high prevalence of these disorders. It further highlights the comorbidity of mood and anxiety disorders in patients with other diagnoses, supporting the assertion that depression and anxiety are widespread mental health issues.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Assignment instructions to be given to the students are provided as S1. The microbe/host response to a change towards a high fat diet includes an increase in the lipopolysaccharide (LPS) production by the bacteria (e. g. Firmicutes) and an increase in the permeability of the intestinal barrier by the host. The latter may be due to a decreased integrity of tight junction proteins (29). Students are given the assignment to summarize the effect of the high fat diet through the bacterial responses on the host system. Students will use 3. Students are free to select any three molecules that contribute to the signal transduction of their choice and go into the details of their function. 20 points are dedicated to this assignment by the author of this manuscript on a scale of 350 to 400 points for the course. activity engages students to explore the role of diet on the gut microbiome, the differences in bacterial metabolism, the molecular response in the human intestinal cells, and the resulting impact on human health. Students typically have no difficulty identifying the nine phyla that contribute to the gut microbiome. The expectation is not that they will remember all nine. However, phyla such as Firmicutes or Bacteroidetes have been discussed in the lectures that preceded this exercise. Students are expected to recognize and remember these two predominant phyla. The most effective part of the pasta exercise may be the short demonstration of an infection by C. difficile in response to antibiotic treatment. The empty pasta bags that now contain a smaller number of different pasta types are an effective simulation. When students 'fill up' their gut with new bacteria, some of which may not be beneficial to human health, students often experience a light-bulb moment. This response is consistent with the student responses that were described by Estes (14). Junior and senior Microbiology students, as well as graduate students should have heard of C. difficile infection during previous classes. Likewise, they should have knowledge about chronic inflammatory diseases. However, this exercise is very practical and provides a real life scenario, which makes it more interesting for the students. It is likely that this activity makes ideas and knowledge more tangible for the learner and promotes long-term retention of the content. Although all students participated in the group discussions, to promote inclusiveness, I would advise instructors to have different students report from the groups throughout the class. This lesson can be scaled to accommodate differently sized classes. [SEP] Justify:

Output: The text contrasts the claim by detailing how a change in diet, specifically a high fat diet, leads to measurable changes in the microbiome. It mentions an increase in lipopolysaccharide (LPS) production by bacteria such as Firmicutes and changes in the permeability of the intestinal barrier due to changes in the microbiome. This indicates that dietary changes can indeed affect microbiome composition.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: The frequency of genotype j in the male gamete pool is given by πj, with A5Finally, genotype frequencies among juvenile males of the next generation are given by A6 (where δij= 1 if i=j and 0 otherwise), whereas genotype frequencies among juvenile females are given by A7 where T=∑i, j≥i[(1 −σij)xmutij+ωtot y′ij/c], and σij is the rate of sex of females carrying genotype ij. 0. From equations (11) and (13) we have B3 B4 This gives us a recursion for ∇M. Solving at equilibrium gives an expression for ∇M at QLE: B5 Plugging this expression into equations (B3) and (B4) gives B6 Expressions for ∇A, and to the first order in when δσ= 0 are given by equations (26) and (27). Putting everything together, one obtains B7 Recursions for and can be derived similarly. One obtains B8 B9 B10 1. Although polymorphism cannot be maintained when with weak selection (C5), it can with stronger selection (C1–C4). Higher fitness in heterozygous individuals favors the maintenance of polymorphism. Most importantly, these equations show that as the rate of sex evolves, different loci subject to sexually antagonistic selection are likely to be polymorphic. With infrequent sex, only alleles with weak effects in females ( low) will satisfy these conditions, whereas with frequent sex larger is necessary. Author notes Data Archived: Dryad: doi:10. 5061/dryad. 1m104© 2012, Society for the Study of EvolutionThis 1. Equilibrium rate of sex σ as a function of the deleterious mutation rate U. - pdf file EVO_1459_sm_supp2Figure S2. Top: Equilibrium rate of sex σ as a function of the cost of sex c with loci subject to both sexually antagonistic selection and mutation-selection balance. Bottom: Amount of genetic variance maintained at equilibrium at loci under deleterious mutation (higher values) and at loci under sexually antagonistic selection (lower values). - pdf file Advertisement 2023. . [SEP] Justify:

Output: The text does not address the claim directly as it focuses on mathematical expressions and models related to genotype frequencies and the dynamics of sex and selection. It contains technical content that does not explicitly mention natural selection or its role in species evolution, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: The LMR test, aLMR test, and BLRT in the three-factor, 5-Class FMM-2 model solution all had p values greater than. 05, which indicates that this model solution should be rejected despite lower criterion indices. Therefore, we then considered a three-factor, 3-Class FMM-2 model which had the second lowest criterion indices. Although the LMR and the aLMR tests did not show univocally support for this model solution, the BLRT had a p-value <. 001, indicating that this model solution significantly fit the data. The entropy value for this model solution was also high, indicating that there is a clear separation between distinguishable classes. Furthermore, the three-factor, 3-Class FMM-2 model replicates the combined results from the CFA and LCA analyses. 2 here Selecting the three-factor, 3-Class FMM-2 model implies that the underlying symptoms are conceptualized equivalently and normally distributed within classes. In other words, the three classes are represented by normally distributed patterns of symptoms of depression and anxiety such that individuals within classes can have quantitatively different ranges of symptom severity. The criterion indices for the FMM-1 solution were much higher and therefore unsuitable for model selection. Additionally, the assumptions of the FMM-1 imply that all patients within a class are having the same levels of distress and that there is no within-class heterogeneity in symptoms of depression and anxiety. This is unlikely to be correct as symptom variation exists as well as the range of severity, consistent with our FMM-2 model solution. Since we assumed variations in symptoms of depression and anxiety as well as the range of severity, the three-factor, 3-Class FMM-2 model was chosen. Interpretation of classes from the factor mixture model The three distress classes were labelled according to differences in factor means (see Figure 1). The reference Class two comprising 40% of the sample, was labelled “mixed depression and anxiety” whereas patients in Class one (33%), in comparison to the mixed depression and anxiety class reported lower levels of cognitive depression, but higher levels of somatic depression and anxiety symptoms and was thus labelled “anxiety and somatic depression”. Patients in Class three (27%) on the other hand reported lower somatic depression than mixed depression and anxiety class and Class three was thus labelled “cognitive depression”. [SEP] Justify:

Output: The text corroborates the claim by discussing symptoms of depression and anxiety within various classes in a factor mixture model, indicating their prevalence and differing severities among patients. It highlights the existence of separate classes of symptoms that demonstrate the commonality of depression and anxiety in mental health diagnoses.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: The activity was designed for six groups of three to five students. If the class size is smaller, the number of students per group can simply be reduced. It is critical to have different diets and gut microbiomes, which makes it essential to have at least six bags. If the class size is larger, some of the pasta bags can be duplicated, rather than increasing the number of students per group; larger groups may result in a smaller percentage of students participating. The exercise can be adjusted for lower academic levels, such as for precollege students, by going back to the original Estes exercise (14) and doing the pasta/bean work without asking students to relate information on actual bacteria to the pasta and beans. Stressing the antibiotic mimicry by providing students with additional information on C. difficile and other antibiotic related infections will increase the practical relevance of this aspect of the exercise and make it suitable for 100 or 200 level classes. Finally, the module may be applied for a course in health-related professional programs (e. g. medicine, pharmacy) by asking students to predict whether people with a variety of diets would be more or less susceptible to different diseases based upon their diet dependent gut microbiome. Students would have to do their own literature search to determine if evidence exists to support hypotheses that they themselves formulate. This task could either be an in class activity for a second class period or an additional assignment. 1. Impact of Diet and Antibiotics - Assignment instructions that instructors will give to students for the follow up assignment. S2. Impact of Diet and Antibiotics - Sample follow up assignment for instructors. S3. Impact of Diet and Antibiotics - Grading rubric for the follow up assignment. 2012. Structure, function and diversity of the healthy human microbiome. Nature 486:207-214. Ercolini D, Fogliano V. 2018. Food design to feed the human gut microbiota. J Chem 66:3754-3758. den van. 2014. The short-chain fatty acid uptake fluxes by mice on a guar gum supplemented diet associate with amelioration of major biomarkers of the metabolic syndrome. PLoS One 9:e107392. . ,. 2012. Butyrate and propionate protect against diet-induced obesity and regulate gut hormones via free fatty acid receptor 3-independent mechanisms. PLoS One 7:e35240. de. 2009. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that different diets and gut microbiomes are critical, suggesting that dietary changes can indeed impact the microbiome composition. It implies that diets are associated with variations in gut microbiomes and mentions research that supports hypotheses regarding the connection between diet and gut health.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Sign in through your institution Filter EvolutionThis issue Biological SciencesEvolutionary BiologyScience and search term Advance 10. 1111/j. 1558-5646. 2011. 01352. x Published: 01 October 2011 10. 1111/j. 1558-5646. 2011. 01352. x Select format. ris (Mendeley, Papers, Zotero). enw (EndNote). bibtex (BibTex). txt (Medlars, RefWorks) Download citation issue Biological SciencesEvolutionary BiologyScience and search term issue Biological SciencesEvolutionary BiologyScience and search term for mates has resulted in sophisticated mechanisms of male control over female reproduction. Antiaphrodisiacs are pheromones transferred from males to females during mating that reduce attractiveness of females to subsequent courting males. Antiaphrodisiacs generally help unreceptive females reduce male harassment. However, lack of control over pheromone release by females and male control over the amount transferred provides males an opportunity to use antiaphrodisiacs to delay remating by females that have returned to a receptive state. We propose a model for the evolution of antiaphrodisiacs under the influence of intrasexual selection, and determine whether changes in this signal in 11 species of Heliconius butterflies are consistent with two predictions of the model. First, we find that as predicted, male‐contributed chemical mixtures are complex and highly variable across species, with limited phylogenetic signal. Second, differences in rates of evolution in pheromone composition between two major clades of Heliconius are as expected: the clade with a greater potential for male–male competition (polyandrous) shows a faster rate of divergence than the one with typically monoandrous mating system. Taken together, our results provide evidence that for females, antiaphrodisiacs can be both honest signals of receptivity (helping reduce harassment) and chastity belts (a male‐imposed reduction in remating). Female mating receptivity, Heliconius, male‐male competition, male control on female reproduction, sexual conflict, signal evolutionMale control over female mating frequency is common in nature and involves remarkable morphological, behavioral, and physiological adaptations aimed at manipulating female receptivity or discouraging advances by other males (e. g. , Parker 1970, Simmons 2001). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses male control over female reproduction and the concepts of antiaphrodisiacs in Heliconius butterflies, without mentioning natural selection or differential survival specifically.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: The factor variances within the classes were all significant, which agrees with the interpretation that there are variations in diagnostic class membership and the range of severity of the patient’s self-reported symptoms of depression and anxiety. 1 here Predictors of class membership 3 for predictors of class membership. There were no findings of gender predicting any class membership. Older age predicted a higher probability of membership to the anxiety and somatic depression class, compared to both the mixed depression and anxiety and the cognitive depression classes. Being single predicted a higher probability of membership in the anxiety and somatic depression class compared to the mixed depression and anxiety class, and the cognitive depression class compared to the mixed depression and anxiety class. 3 here Differences in relevant outcome variables Patients with a high probability of membership in the anxiety and somatic depression class were to a larger degree associated with being on sick leave and being diagnosed with depression, anxiety and comorbid mood/anxiety disorder compared to the other classes. Patients with a high probability of belonging to the cognitive depression class were to a larger degree associated with being on sick leave and being diagnosed with depression, and comorbid mood/anxiety disorder, compared to the mixed depression and anxiety class. They also had a higher probability of being diagnosed with mixed anxiety and depressive disorder, compared to the anxiety and somatic depression class. Regarding the mixed depression and anxiety class, they had a higher probability of being diagnosed with somatization disorder compared to the cognitive depression class. Regarding functional impairment and service use, the anxiety and somatic depression class had more assessment and psychotherapy appointments and reported the highest degree of impairment compared to the other classes. The cognitive depression class reported more psychotherapy appointments and functional impairment than the mixed depression and anxiety class. Outcomes across classes are presented in Table 4. 4 here DiscussionThis study shows that linking PROM with register data on CMHD can provide supplemental information on the service needs of routine mental health outpatients. Patients with comorbid mood and anxiety disorders differed from non-comorbid patients as a group characterized by higher symptom severity, and higher service use. Since analyses of patients diagnosed with CMHD did not consider the full sample, in this case excluding 35% of the sample, we also examined FMM-aggregated PROM data. Three classes distinguished themselves regarding levels of cognitive depression, somatic depression, and anxiety, together with clinically relevant covariates. [SEP] Justify:

Output: The text corroborates the claim by discussing variations in diagnostic class membership and symptom severity in patients with depression and anxiety, indicating these issues are prevalent and significant enough to be classified and studied. It mentions that patients with comorbid mood and anxiety disorders showcase higher symptom severity and service use, which aligns with the notion that depression and anxiety are common mental health disorders. The mention of various classes such as 'anxiety and somatic depression' and 'cognitive depression' confirms the widespread nature of these conditions.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Changes in gut microbiota control inflammation in obese mice through a mechanism involving GLP-2-driven improvement of gut permeability. Gut 58:1091-1103. Kiefer J, Beyer-Sehlmeyer G, Pool-Zobel BL. 2006. Mixtures of SCFA, composed according to physiologically available concentrations in the gut lumen, modulate histone acetylation in human HT29 colon cancer cells. Nutr 96:803-810. . 2017. Gut microbiome and inflammation: a study of diabetic inflammasome-knockout mice. J 2017:6519785. . 2018. The gut microbiome and elevated cardiovascular risk in obesity and autoimmunity. Atherosclerosis 271:203-213. . 2018. Dysbiosis of gut microbiota in promoting the development of colorectal cancer. (Oxf) 6:1-12. . 2018. Gut microbiota-immune system crosstalk and pancreatic disorders. 2018:7946431. . 1978. Antibiotic-associated pseudomembranous colitis due to toxin-producing clostridia. N Med 298:531-534. . 2012. Risk of Clostridium difficile infection with acid suppressing drugs and antibiotics: meta-analysis. Gastroenterol 107:1011-1019. . 2017. Fecal microbiota transplantation for recurrent Clostridium difficile infection reduces recurrent urinary tract infection frequency. Dis 65:1745-1747. Estes AM. 2015. Modeling the dynamic digestive system microbiome. J Educ 16:271-273. Portune KJ, Benitez-. 2017. Gut microbiota, diet, and obesity-related disorders-the good, the bad, and the future challenges. 61:1600252. . 2011. Succession of microbial consortia in the developing infant gut microbiome. 108:4578-4585. Kuh GD. 2008. High-impact educational practices. Association of and Universities. Sweat JJ, G. ; Han, S. ; Wolfgram, S. M. 2013. How does high impact practice predict student engagement? A comparison of white and minority students. Learn 7:17. Prince M. 2013. Does active learning work? A review of the research. J 93:223-231. Froyd JE. 2007. [SEP] Justify:

Output: The text contrasts the claim by providing evidence that changes in gut microbiota, which can be influenced by diet, control inflammation in various models of disease such as obesity and diabetes. The mention of 'gut microbiota, diet, and obesity-related disorders' further implies that dietary changes can indeed affect microbiome composition.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Common mechanisms include the transfer of seminal fluid proteins, donation of nuptial gifts, formation of mating plugs, and mate guarding (Thornhill and Alcock 1983; Simmons 2001). The evolution of such strategies is the result of selection on males to reduce sperm competition when females mate repeatedly within a breeding period. Females often obtain direct benefits from multiple matings (Arnqvist and Nilsson 2000). Thus a conflict can arise if male traits reduce female remating below what is optimal for the latter leading to male–female antagonistic coevolution (Arnqvist and Rowe 2005). Antiaphrodisiacs are chemical signals transferred during mating by males to females that temporarily reduce female attractiveness to subsequent courting males. Described first in the beetle Tenebrio molitor (Happ 1969), they have since been found in a wide range of taxa, including Drosophila melanogaster, garter snakes, and several species of bees and butterflies (Gilbert 1976; Ross and Crews 1977; Scott 1986; Andersson et al. 2000; Ayasse et al. 2001). Some authors have regarded these male‐donated pheromones as nuptial gifts because they help unreceptive females repel unwanted males (Thornhill and Alcock 1983). The notion that these pheromones have little role in controlling remating has largely arisen because decreased attractiveness appears to be synchronized with inherently low female sexual receptivity. The assumption that reduced receptivity follows mating is based mainly on a few taxa where females themselves produce additional chemicals to repel males, or are physically incapable of remating immediately (Scott 1986; Ayasse et al. 2001). Recent studies have challenged the view that donor males and mated females always have a common interest in the repelling of courting males. Antiaphrodisiacs are typically emitted passively during courtship displays. Such apparent lack of female control over the release of this pheromone, as well as the male's ability to modify the amount transferred according to the potential for sperm competition, suggests that the presence of antiaphrodisiacs in a mated female may not always be a honest signal of her receptivity to mate, and can in fact become an instrument of male control over female remating (Andersson et al. 2000; 2003; 2004). In this 0. 25 mm, 0. 25‐μm‐thick film). [SEP] Justify:

Output: The text does not directly address or support the claim about how natural selection drives evolution through differential survival. Instead, it discusses specific mating strategies and chemical signals in various species, which are not explicitly linked to the overarching concept of natural selection or differential survival. Hence, the text is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: It is therefore possible that this class, equal to one-third of the sample, was characterized by patients with persistent psychological problems of high complexity across a broad range of areas. The elevated levels of somatic problems and anxiety reported by this class could therefore reflect a group of patients with a chronic course of depression. A longitudinal study on patients with depression showed higher cortisol levels and c-reactive proteins amongst patients with persistent problems, and these biomarkers had a considerably stronger relationship to somatic-, rather than cognitive symptoms of depression (37). Thus, higher somatic symptoms of depression could indicate the chronicity of the disorder. Levels of somatic symptoms of depression also separated the other two classes. The mixed depression and anxiety- were the largest class, compromising 40% of the patients. They were more often in a relationship and younger compared to patients in the other classes. Their levels of cognitive symptoms of depression and anxiety were similar to the class labelled cognitive depression class. Their higher levels of somatic symptoms of depression were unexpected since they also had less service use, reported a lower degree of functional impairment and lower levels of sickness absence. At the same time, they also had the highest probability of a somatization disorder. A possible explanation is that patients in the mixed depression and anxiety class are highly distressed but still able to work or study, which means that they are more exposed to daily stressors. These patients may express more somatic depressive complaints as a result of trying to cope with difficult everyday challenges. Correspondingly, patients in the cognitive depression class may be less exposed to work or study-related daily stressors, and at the same time report more severe functional impairment, and higher treatment needs. The relationship between symptoms and functioning is complex, and many times weaker than expected. In a review, McKnight and Kashdan (38) argued that the dimensionality of the instruments, and sample properties could obscure the relationship. Thus, when these are accounted for, new information may be obtained. Results show the accumulated value of conjoining clinician-rated and self-reported information, as this provides new perspectives of the patient population that is not readily available from each source of information alone. The clinical implication of these findings is gained knowledge of latent patient groups, showing that higher symptom severity does not necessarily imply more service use and higher functional impairment. This underlines the need for evaluations that combine the perspective of patients, clinicians, and the organisation. [SEP] Justify:

Output: The text corroborates the claim by highlighting that approximately 40% of the patient sample was identified as having mixed depression and anxiety. This substantial portion indicates that depression and anxiety are prevalent among the studied population, thus supporting the assertion that these are common mental health disorders globally.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Diet may influence the oral microbiome composition in cats access Published: 09 June 2016 Diet may influence the oral microbiome composition in cats Christina J. Adler1,2, Richard Malik3, Gina V. Browne1,2 & …Jacqueline M. Norris4 Show authors Microbiome 0. 001). Amongst this higher diversity, cats on dry-food diets had a higher abundance of Porphyromonas spp. (p < 0. 01) and Treponema spp. (p < 0. 01). ConclusionsWhile we observed differences in the oral microbiome between cats on the two diets assessed, the relationship between these differences and gingival health was unclear. Our preliminary results indicate that further analysis of the influence of dietary constituents and texture on the feline oral microbiome is required to reveal the relationship between diet, the oral microbiome and gingival health in cats. BackgroundThe microbiome of the gingival cleft is of great interest in human dentistry because the two most important diseases of the teeth and periodontium in human patients, dental caries and periodontitis [1], are related to changes in the relative contribution of various potentially pathogenic bacteria in the complex biofilm referred to as dental plaque [2]. As a result, there is considerable information on the oral microbiome of human patients, how this is associated with different disease conditions, and how this is influenced by diet [3, 4]. This includes studies using ancient deoxyribonucleic acid (DNA) which have shown that systematic changes in the microbiome are correlated with changes in diet, in both a contemporary and an evolutionary sense [5]. Cats, like humans, are very commonly affected by periodontal disease, with a consensus that it is the most common disease of feline patients in developed nations [6]. While periodontal disease is seen in cats of all ages, it is generally considered to progress with age, although its extent and severity are impacted on by such factors as diet and co-morbid disease (especially kidney disease and infection with feline immunodeficiency virus and/or feline calicivirus). Indeed, some feline diets are specifically formulated to prevent and/or ameliorate the severity of feline periodontal disease. [SEP] Justify:

Output: The text contrasts the claim by presenting evidence that diet influences the oral microbiome composition in cats, indicating that systematic changes in the microbiome are correlated with changes in diet. Specifically, it notes that cats on different types of diets show differences in their oral microbiome, suggesting that dietary changes can indeed impact microbiome composition.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Injection was in splitless mode (250°C injector temperature) with helium as the carrier gas (constant flow of 1 mL/min). The temperature program started at 50°C, was held for 1 min, and then rose to 320°C with a heating rate of 5°C/min. Compounds were identified by comparison of the mass spectra and retention times with those of authentic reference samples as well as analyses of mass spectral fragmentation patterns. Further details of the identification of Heliconius gland constituents can be found in Yildizhan (2009). Males transfer most of the compounds from their abdominal glands into females during mating (Schulz et al. 2008). However, the chemical content of females’ glands varied substantially, probably due the time elapsed since mating, and the use of the pheromone while adopting the rejection posture (Andersson et al. 2004). Thus, data from females were used only to test whether chemical transference happened in the same way as described for H. melpomene (Schulz et al. 2008). Analysis of the interspecific variation in gland content was performed based only on data from males. Some intraspecific variation in such composition, particularly in minor compounds, also occurred among males. Thus, compounds used in the analysis were restricted to those that appeared in more than one individual male or mated female of the species, and were not found in the surrounding tissue of the gland, or in virgin females. Components were scored as present or absent in the 11 species of Heliconius. Analysis of of Two indices were used to estimate the degree of phylogenetic signal in the evolution of abdominal pheromone blends and their individual components (Symonds and Elgar 2004; Symonds and Wertheim 2005): the consistency CI=m/s (Kluge and Farris 1969), and the retention index RI= (g − s) (g − m) (Farris 1989), where s is the number of character state changes along the phylogeny (steps) based on parsimony, m the minimum possible steps (no homoplasy), and g the maximum possible number of changes in any tree (maximum homoplasy). Both indices range between zero and one with values closer to one indicating higher degrees of fit of characters to the phylogeny. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses a method for analyzing chemical compounds in Heliconius species without addressing natural selection or the evolution of species. It focuses on technical details of a scientific process rather than evolutionary concepts.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-1182206/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Under ReviewVersion 1posted 10You are reading this latest preprint versionAbstractBackground:Approximately one in five women who have recently gave birth suffer from some form of common mental disorder (CMD) particularly depression and/or anxiety. Most available CMD screening tools in most lowand middle income countries do not screen for more than one mental health problem. Having a screening tool that is free to use, short in assessment time and used to screen for more than one CMD is appealing in a resource constrained setting. This study aimed at assessing the reliability and validity of the Depression, Anxiety, and Stress Scale-21 items (DASS-21) for screeningCMDsexperienced by women who have recently given birth in Malawi. Method: We used the gold-standard design for scale validation of comparing the responses to the Chichewa translated and adapted DASS-21 instrument with an independently administered Interview for DSM-IV (SCID). Internal reliability was reported using Cronbach’s alpha coefficient. The ability of DASS-21 and (EPDS) to discriminate cases from non-cases was assessed by receiver operating characteristics (ROC) analysis and its curve was used to select cut-off points for DASS-21 and EPDS that maximise both sensitivity and specificity. Results: The overall Cronbach’s alpha for DASS-21 scale was 0. 74. The internal consistency for DASS-21 depression subscale, anxiety subscale and stress subscale were 0. 66, 0. 29 and 0. 52 respectively. The area under the ROC curve was 0. 76 (95% CI: 0. 6086; 0. 9102) for DASS-21 depression subscale (DASS-D) and 0. 65 for DASS-21 anxiety subscale (DASS-A). At a cut-off point of one or more, the sensitivity and specificity for DASS-D was 69. 2% and 75. 5% whilst DASS-A was 52. 9% and 75. 5% respectively. Pearson correlation coefficient for the association between DASS-D and EPDS was r = 0. 61, p<0. 001. [SEP] Justify:

Output: The text corroborates the claim by stating that approximately one in five women who have recently given birth suffer from common mental disorders (CMD), particularly depression and/or anxiety. This indicates that depression and anxiety are prevalent mental health issues, aligning with the claim that they are among the most common mental health disorders globally.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: To date, there have only been a handful of in-depth genetic studies of the feline oral microbiome [14–16], and these have not considered the contribution of diet to the observed findings. The present work evaluates the composition of the feline oral microbiome using next-generation sequencing (NGS) and, in a preliminary fashion, the contribution of diet to the composition of the microbiome. The two mutually exclusive dietary categories fed to cats for months to years were (i) dry extruded kibbles (highly refined, cereal-based, dehydrated rations) and (ii) wet (canned [any type] and/or fresh meat [uncooked chicken, or lamb or beef; off or on the bone] combinations, high in water content, protein and fat, but low in carbohydrate). Our findings are in agreement with recent published work on the composition of the feline oral microbiome [14–18] and show a tangible effect of diet on the overall diversity and relative frequency of occurrence of known periodontal pathogens. ResultsWe used in-depth genetic sequencing to analyse the composition of the oral microbiome in 10 owned cats. The phylogenetically informative 16S gene (hypervariable region V1-V3) was amplified from supragingival dental plaque samples from cats in the study cohort. Illumina sequencing of the 16S PCR products produced a total of 2,421,096 sequences with an average of 186,238 sequences per sample, post-quality filtering. These sequences had an average length of 487 base pairs. Feline oral microbiome compositionThe cat oral microbiome contained a diverse array of bacteria from 14 phyla (Fig. 1). For each cat and diet group, the relative frequency of operational taxonomic units (OTUs) is presented in Additional file 1. Irrespective of diet, three phyla accounted for 76 % of sequences. These included Bacteriodetes (31 %), Firmicutes (24 %) and Proteobacteria (21 %). Amongst the phyla, we found a total of 411 bacterial OTUs across all the cats (Fig. 2). The majority (67 %) of these OTUs belonged to genera that occurred at abundances below 1 %. The remaining 33 % of OTUs had abundances above 1 % and accounted for the majority (76 %) of sequences. The most dominant OTUs across all the cats belonged to the Porphyromonas genus (14. [SEP] Justify:

Output: The text contrasts the claim by showing evidence that diet significantly affects the composition of the feline oral microbiome. It states that the study evaluates the contribution of diet to the microbiome composition and presents findings that indicate a tangible effect of diet on the diversity and frequency of periodontal pathogens in the microbiome. This directly contradicts the claim that changing one's diet has no impact on microbiome composition.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Compounds present in only one species (autapomorphies) were excluded from both analyses as they by default have minimum number of steps (s) and tend to inflate the CI of the blend (Sanderson and Donoghue 1989). Both indices were calculated using PAUP* 4. 0b10 (Swofford 2002). A randomization test was also used to estimate whether CI and RI differed from measurements obtained from a random distribution of characters (Maddison and Slatkin 1991). (Package, reshuffle states within characters) by Maddison and Maddison (2008), null distributions of CI and RI were calculated from 2000 matrices created by shuffling data of presence/absence of chemical compounds while keeping the phylogeny constant. Two‐tailed Z‐tests were then used to compare the null distribution with values inferred from our data. The characters were mapped in a phylogeny inferred by mitochondrial (Co and 16S) and nuclear data (Ef1α, dpp, ap and wg) (Beltrán et al. 2007) pruned to contain only the species studied (Fig. 2, Supporting information). If antiaphrodisiac evolution has been mainly driven by intrasexual selection, we expect lower values of CI and RI, particularly for analysis including only species in the nonpupal mating clade. Phylogenetic analysis with chemicals as characters was used to determine in which clades abdominal blends have evolved congruently with a molecular phylogeny of the group. Bootstrap analysis on trees constructed by maximum parsimony (MP) using heuristic search with TBR swapping algorithm were performed with 2000 replicates and confidence level of 50 using PAUP* 4. 0b10 (Swofford 2002). Bootstrap values of the resulting consensus tree were then mapped on the molecular phylogeny to compare species associations found in both trees. If the chemical composition of abdominal glands changed gradually through time, suggesting little pressure for changes in the signal, finding consensus trees that closely resemble the inferred phylogeny of the group with high branch supports is expected. In contrast, if male–male competition has accelerated the evolution of the chemical blend, a poor match of trees is expected. With MP two species either sharing or lacking particular compounds could be clustered together if either gains or losses of compounds happened in their closest common ancestor. This analysis can indicate whether the overall evolution of the blend mirrors the phylogenetic history of the species. [SEP] Justify:

Output: The text does not address the claim regarding natural selection and its role in species evolution. Instead, it focuses on the methodologies for analyzing phylogenetic relationships and chemical compounds among species, without providing evidence or arguments related to natural selection acting through differential survival.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: Conclusion: DASS-21 as an overall item has good internal reliability but none of its subscales (DASS-D, DASS-A, DASS-S) have satisfactory internal reliability. AnxietyDepressioninternal reliabilityreceiver operating curvesensitivityspecificityFiguresFigure 11. 0 BackgroundMaternal mental health problems remain a global public health challenge. Approximately 13% of women who have given birthin high income countries suffer from some form of common mental disorder (CMD), primarily depression and/oranxiety. [1] The situation is worse in low and lower-middle income countries (LMICs) where one in five (19. 8%) womenwho have recently given birth experience a CMD. [1] Untreated CMDs reduce maternal level of functioning,[2] and may consequently impair mother-infant interaction[3] and infant cognitive development. [4] The current low detection and treatment rate of CMDs in LMICs is very concerning. There are several reasons for this. First, perinatal mental health for women living in LMICs is only an emerging area of interestfor researchers and policy makers, asthe international agenda has moved beyond survival to understand what is needed to enable women (and infants) to thrive. [1]Second, it has been thought that women living in LMICs are protected from experiencing postpartum mental disorders by social and traditional cultural practices during the postpartum period, a notion which has not been substantiated. [1]Third, low detection and treatment rate of CMDs in LMICs might be attributed to lack ofculturally sensitive screening tools that are simple to use. Lastly but important,in most LMICs perinatal mental health screening and treatmentareyet to be integrated into a routine healthcare package of mother-child dyadic interventionsoffered when a mother attends well-baby clinics. [5] Several perinatal CMD screening tools such as (EPDS),[6] WHO Self-Reporting Questionnaire,[7] Questionnaire-9,[8]and Post-Scale[9]have been validated for screening perinatal mental disorders in Malawi. However, these individual tools are not designed to screen formultiple separate common mental disorders (e. g. depression, anxiety, PTSD). [SEP] Justify:

Output: The text corroborates the claim by stating that approximately 13% of women who have given birth in high income countries suffer from common mental disorders (CMD), primarily depression and/or anxiety, and that the situation is worse in low and lower-middle income countries (LMICs), where one in five women experience a CMD. This indicates that both depression and anxiety are indeed prevalent mental health disorders globally.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: 9 %) followed by the Treponema (5. 1 %) and Fusibacter (4. 5 %) genera. Fig. 1Relative abundance of phyla in the oral microbiome of cats on dry- and wet-food diets. The abundance of phyla was calculated from sequences classified as bacteria. These sequences were taxonomically assigned using the Greengenes database following operational taxonomic unit (OTU) classification with uclust (QIIME version 1. 8. 0). Relative abundances were calculated using normalised sequence data to account for varying sequence depth between samples (Phyloseq version 1. 10. 0)Full size image Fig. 2Phylogeny of sequences in the oral microbiome of cats on dry and wet diets. The phylogeny was generated using maximum likelihood (RAxML version 730) from representative sequences of the operational taxonomic units (OTUs) and graphically displayed in the of Life (version 2. 1). Sequences with less than 0. 2 patristic distance between OTUs were collapsed (Phyloseq version 1. 10. 0). The abundance of genera in the dry- and wet-food diet groups displayed around the phylogeny was calculated from normalised OTU counts (Phyloseq version 1. 10. 0). Abbreviation: NA non-assignedFull size image Impact of diet on the feline oral microbiomeThe overall oral bacterial diversity was estimated for each cat (see Additional file 2). We used the alpha (α) diversity metric, Estimator (ACE), to assess species richness and the to assess species evenness. We assessed whether the overall bacterial diversity differed between cats eating highly refined dry (higher carbohydrate content [both on a dry matter, total energy and absolute percentage basis], dehydrated, lower percentage of protein and fat on a percentage basis as fed) versus wet (lower carbohydrate content, high in water [approx. 70 %], variably higher in protein and fat) diets (see Additional file 3). Many of the dry extruded kibbles are sprayed with phosphoric acid to improve palatability, and such diets were the ones that tended to be fed to cats in the dry-food cohort. An analysis of covariance () was conducted to determine if there was a statistically significant effect of diet on the cat’s oral microbiome ACE and values, when controlling for age of the cats. [SEP] Justify:

Output: The text contrasts the claim by discussing a study that evaluates the impact of different diets (dry and wet) on the oral microbiome of cats. It specifically mentions assessing bacterial diversity using metrics which indicate the effect of diet on microbiome composition. This suggests that changing one's diet does in fact influence the microbiome composition, thus directly opposing the claim that diet has no impact.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: However, as compounds in a blend produce a scent, it is reasonable to assume that the more compounds are shared between two blends the more similar they are when perceived by a receiver. Divergence of abdominal chemical composition among the 11 species was also calculated using the Jaccard‐Tanimoto similarity coefficient (J) (Willett et al. 1998). This coefficient is calculated as a proportion of compounds shared between chemical blends of the two species relative to the total number of compounds in both blends. Similarity was then converted to distance (1 −J), and the resulting matrix correlated with a matrix of patristic distances calculated from the branch length of the molecular‐based phylogeny using (Fourment and Gibbs 2006). We used the Pearson's correlation and a Mantel test with 2000 permutations to calculate the significance levels of the correlation. Mantel tests were performed using R 2. 7. 1. (Vegan package 1. 15–1, R Team, 2008). Results (not shown) of similar analysis using squared Euclidian Distance, another commonly used measure of chemical differences among species, were comparable to those obtained with the Jaccard coefficient. Separate analyses were performed for all chemical compounds and for different sets of data based on the degree of volatility. Two divisions of the whole dataset were performed. In the first (A), all chemicals were divided into two groups (high/low volatility A), classifying compounds with molecular weights below 300 g/mol as volatiles (Bradbury and Vehrencamp 1998). In the second division (high/low volatility B), we classified as volatiles those chemicals with lower molecular weight than weight of compounds dominating virgin female glands, which are odorless for us (ca. 270 g/mol). We expected that if the evolution of this pheromone has been targeted toward reduction of the threshold amount needed to repel subsequent males (Fig. 1A), then only volatile components of the blend would show evidence of male–male competition (e. g. , poor phylogenetic signal). By contrast, such poor phylogenetic signal found in the less‐volatile portion of the mixture (matrix), considered responsible for controlling volatile component evaporation rates, provides evidence for evolution to increase the number of rejection displays before repellant effects of the antiaphrodisiac is lost (Fig. 1B). [SEP] Justify:

Output: The text does not provide any information related to natural selection or the evolution of species due to differential survival. Instead, it discusses chemical composition, similarity analyses, and methods like the Jaccard-Tanimoto coefficient, which are unrelated to the claim about natural selection.


Input: Task: pass the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: Positive likelihood ratio (LR+) tells us how much to increase the probability of the disease if the test is positive while Negative likelihood ratio (LR-) tells us how much to decrease the probability of the disease if the test is negative. The larger the LR+ (≥5), the greater the likelihood of the disease and the smaller the LR- (<5), the lesser the likelihood of a disease. ( The ability of DASS-21 and EPDS to discriminate cases from non-cases was assessed by receiver operating characteristics (ROC) analysis and its curve was used to select cut-off points for DASS-21 and EPDS. The area under the ROC curve (AUC) is the best parameter for summarizinga screening tool’s overall discriminative value. A value of ≥0. 70, 0. 80 up to 0. 90 and >0. 90 is interpreted as reasonable, good and excellent, respectively. [23]Comparisons were made between the AUCs for the DASS-D and EPDS. The criteria to choose an optimal cut-off value was to maximise both sensitivity and specificity, and to set sensitivity value higher than specificity in order to detect all potential cases. For a test to be useful, the sensitivity + specificity should be atleast 1. 5. Data analysis was conducted using 15. 1 (of America, 2017). 2. 6 This study was nested within the trial, which was approved by the College of Malawi (P. 02/18/2357) and the Walter and Institute of Ethics Committee,Australia(18/02). All participants were given information about the study and either signed a consent form or printed their thumbprint (as witnessed by impartial observer) for those who could not write. Assessments were done in closed rooms to maintain privacy. Participants were given unique identifying numbers and forms containing their names were kept separately from their files. Participants identified as needing further assessment and management were referred to local Ministry of Health psychiatric services. 3. 0 Results3. 1 Descriptive analysis Overall, 115/120 (95. 8%) of the required sample provided complete responses to all the three questionnaires (-21 and EPDS) administered. The mean age of the included participants was 24 (standard deviation: 6. 8) years. Approximately 82% of the participants were either married or living together with their husband and 68. [SEP] Justify:

Output: The text discusses statistical methods for assessing screening tools for mental health disorders but does not address the prevalence of depression and anxiety or corroborate the claim regarding their commonality. Therefore, it is considered irrelevant to the claim.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: We controlled for age because OTU diversity has previously been found to rise with increasing age [19]. We observed a significant effect of diet when controlling for age on species richness (ACE), F(2, 7) = 39. 26, p = 0. 0002 (Fig. 3), and evenness (Simpsons Index), F(2, 7) = 85. 67, p = 0. 00001. Cats on a dry-food compared to a wet-food diet had a higher diversity of OTUs in their oral microbiomes (ACE p = 0. 0001, Simpsons p = 0. 0001). Additionally, the overall bacterial diversity increased with increasing age (ACE p = 0. 0002, Simpsons p = 0. 0001). Fig. 3Analysis of covariance on the effect of diet type and age on the feline oral microbiome’s α diversity. Analysis of covariance () was used to test the effect of dry and wet diets on α diversity, while controlling for age of the cats in R (version 3. 1. 2). Alpha diversity was calculated using the Abundance-based (ACE) metric, from operational taxonomic unit (OTU) abundance data (Phyloseq version 1. 10. 0). was performed on the log of ACEFull size image To determine what was causing the higher bacterial diversity in cats consuming dry food, we assessed the effect of diet on the abundance of specific bacteria. A differential abundance test, DESeq2 [20, 21], was used to compare the OTUs present in dental plaque samples from cats on dry-food to those on a wet-food diet. Of the 411 OTUs identified in the cat’s oral microbiomes, 23 were differentially abundant between the two diets (Fig. 4). Of these 23, 65 % of OTUs were significantly more abundant in plaque from cat’s consuming a dry diet. The most enriched bacteria in cats eating dry diets exclusively included OTUs from the following genera: Actinobacillus (p = 1. 74 × 10−8), Acholeplasma (p = 0. 0002), Treponema (p = 0. 0087) and Porphyromonas (p = 0. 0028). The remaining 35 % of OTUs were significantly more abundant in dental plaque from cats consuming a wet diet. [SEP] Justify:

Output: The text contrasts the claim by providing clear evidence that diet significantly affects the microbiome composition. It describes experimental results showing that cats' oral microbiomes exhibit differences in OTU diversity based on whether they were fed dry or wet food, with specific genera being more abundant in one type of diet. This demonstrates that changing the diet can lead to notable changes in microbiome composition, directly opposing the claim.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Several chemicals present in abdominal glands are biosynthetically related, and thus their joint occurrence in a single blend may not represent independent traits. Bias would occur in our analysis if a family of chemicals appears in two species that have independently acquired a new compound of that family (Schulz et al. 1993; Symonds and Elgar 2004). In an attempt to correct for this effect, compounds were also combined in chemical classes and biosynthetically related groups, and the new data of presence and absence of these groups analyzed as explained above. Groups of known or assumed biosynthetic relationships are given in Supporting information. content of abdominal glands from Heliconius males varied considerably among species, both in composition and number of compounds (Fig. 2, Supporting information). We identified a total 211 compounds, more than 50% being found exclusively in one species. Blend composition ranged from a few compounds, as in H. ismenius (6) to over 75 compounds as in H. cydno and H. pachinus. The chemical mixture of the species studied included esters (41%), lactones (26%), and terpenes (15%), the remainder being alcohols, ketones, and aromatic compounds. With the exception of H. ismenius, which lacks heavy esters and lactones, male secretions had a similar broad composition across species, consisting of few major volatile compounds imbedded in a less‐volatile matrix made up mainly of esters of common fatty acids. A complete antiaphrodisiac composition for each species is given in the Supporting information. Both indices used to estimate whether blends have evolved in congruence with the phylogeny indicate that the phylogenetic signal in antiaphrodisiac blends was higher than expected by chance (all Z‐tests, df = 1999, P < 0. 001) (Table 1a). However, the correspondence is not very strong as CI and RI are near 0. 5, half the maximum possible value. Similar results were obtained when chemical data were divided according to volatility that suggests that similar modes of evolution probably govern signal and matrix compounds. Grouping compounds according to their biosynthetic relationships only slightly decreased the phylogenetic signal of abdominal blends, indicating that the interdependence of chemical data did not bias our analyses of the entire dataset toward any particular result (Table 1a). [SEP] Justify:

Output: The text discusses the chemical compositions of abdominal glands in various species and their phylogenetic signals, but it does not address natural selection or differential survival as mechanisms driving evolution. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: Log in or new issue alertsGet alerts Submit a your Email address: Subscribe to e2022. | DOI: 10. 4103/amh. amh_177_21 is high prevalence of psychological distress in patients diagnosed with neurological disorders. A cross-sectional study was done among inpatients from the department of neurology in a tertiary care centre in to assess prevalence of anxiety, depression, and barriers to mental health-care utilization. Anxiety and depression were estimated using the (HADS). There is a high prevalence of psychological distress among the study participants. Proactive inquiry and screening of distress by the treating team may help identify psychological distress. Patients are more conforming and open to treating doctor. Barriers to mental health-care utilization included stigma, patient perception regarding treating doctor's attitude, patients' perception regarding distress, and doctor's perception regarding patient distress. There is a need for measures to alleviate stigma. general estimate in patients seeking neurological treatment is that 40% of neurology outpatients and 34% of neurology inpatients have psychiatric disorders. [1] Recognition and treatment of comorbid psychiatric disorders significantly improve the treatment outcome, overall health status, and rehabilitation. [2] Primary treating physicians may have difficulty to recognize the symptoms of depression and anxiety more than 50% of the time. [3] Hence, psychiatric comorbidities may not be adequately addressed in primary neurological facility. [4] Many other factors additionally influence mental health-care utilization among patients of neurology. [5] Studies in developed nations showed that majority of surveyed patients reported felt need for mental health intervention. However, almost half of those needing help were not formally referred to mental health professionals (MHPs) and one-third of them remained untreated. [3] The most commonly found barriers to utilization of mental health services in developed countries are inadequate screening and detection of psychiatric complications by medical care providers, availability of services, accessibility of services, and acceptability of mental health-care treatment. [3] To the best of our knowledge, this is the first Indian study that assessed barriers to utilization of mental health services in patients who are receiving treatment at a neurological setting. followed a cross-sectional design. Participants were adults with a primary neurological condition admitted under the Department of. They were recruited over a period of 3 months. Patients with severe cognitive impairment were excluded from the study. [SEP] Justify:

Output: The text corroborates the claim by highlighting a high prevalence of anxiety and depression among patients with neurological disorders. It states that '40% of neurology outpatients and 34% of neurology inpatients have psychiatric disorders,' indicating that depression and anxiety are prevalent in this population, thus supporting the claim of these conditions being common mental health disorders globally.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: These bacteria were primarily Proteobacteria, from the Neisseriaceae family (38 %), including Conchiformibius kuhniae (p = 0. 0002). The differential abundance test indicated that diet alters the abundance of specific bacteria in the feline oral microbiome. Fig. 4Differentially abundant genera between the oral microbiomes of cats on dry and wet diets. DESeq was used to test for the presence of differentially abundant operational taxonomic units (OTUs) in the oral microbiome of the cats on a dry- compared to wet-food diet (Phyloseq version 1. 10. 0). The DESeq test was applied to OTUs that had been filtered to remove singletons and species with an abundance below 0. 005 %. The figure presents those OTUs that were found to be significantly different (p < 0. 01) between the two diets. Positive log2-fold change values indicate enriched OTUs in the dry diet, and negative log2-fold change values indicate enriched OTUs in the cats eating a wet diet. Abbreviation: NA non-assignedFull size image DiscussionOur analysis of the oral microbiome is only the fourth NGS study in cats [14–16] and for the first time highlights the potential impact of diet on bacterial composition. Cats consuming dry kibble (dehydrated, highly refined, cereal-based, sprayed with oil and phosphoric acid) compared to a higher protein/lower carbohydrate wet diet (approx. 70 % water by weight) have a more diverse oral microbiome, with an enrichment of bacteria associated with both gingival health and periodontal disease. Our findings indicate that diets commonly fed to domestic cats in Australia [22] influence the feline oral microbiome make-up, although exactly how these composition changes relate to gingival health requires resolution. Current understanding of the feline oral microbiome and what impacts its composition is limited by a lack of culture-independent studies. At a broad scale, we found a similar bacterial profile to published NGS [14–16] and Sanger sequencing [17, 18] studies of the feline oral microbiome, in terms of abundance of phyla and detection of genera. [SEP] Justify:

Output: The text contrasts the claim by demonstrating that diet alters the abundance of specific bacteria in the feline oral microbiome. It presents evidence that cats on different diets (dry vs. wet) show significant differences in microbial composition, indicating that dietary changes do indeed have an impact on microbiome composition.


Input: Task: pass the claim using the given text. Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Small letters represent clades marked in the pruned molecular‐based phylogeny of the group (Fig. 2), with bootstrap values higher than 5%. A dash represents a value lower than 5%. All compoundsHigh volatilityHigh volatilityLow volatilityLow volatilityChemical groups(93)A(67)B(55)A(26)B(38)(34)ACI 0. 567 0. 573 0. 534 0. 553 0. 623 0. 486 0. 397±0. 007 0. 405±0. 008 0. 399±0. 009 0. 378±0. 013 0. 396±0. 011 0. 348±0. 011RI 0. 567 0. 558 0. 5 0. 588 0. 662 0. 542 0. 139±0. 026 0. 129±0. 03 0. 138±0. 034 0. 16±0. 047 0. 144±0. 001 0. 186±0. 041Ba1001009998. 710099. 3b 67. 5 12. 3 6. 373. 5 74. 384. 7c 45. 9 55. 753. 5 − − 9. 1d 80. 2 59. 258. 558 56. 872. 3e − 13. 911. 2 − − −All compoundsHigh volatilityHigh volatilityLow volatilityLow volatilityChemical groups(93)A(67)B(55)A(26)B(38)(34)ACI 0. 567 0. 573 0. 534 0. 553 0. 623 0. 486 0. 397±0. 007 0. 405±0. 008 0. 399±0. 009 0. 378±0. 013 0. 396±0. 011 0. 348±0. 011RI 0. 567 0. 558 0. 5 0. 588 0. 662 0. 542 0. 139±0. 026 0. 129±0. 03 0. 138±0. 034 0. 16±0. 047 0. 144±0. 001 0. 186±0. 041Ba1001009998. 710099. 3b 67. 5 12. 3 6. 373. 5 74. 384. 7c 45. 9 55. 753. 5 − − 9. 1d 80. 2 59. 258. 558 56. 872. 3e − 13. 911. [SEP] Justify:

Output: The text is irrelevant to the claim about natural selection as it discusses molecular-based phylogeny and chemical groups without addressing evolutionary processes or natural selection. There is no mention of differential survival or species evolution.


Input: Task: corroborate the claim using the given text. Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: Psychological profile Based on the HADS scoring, the mean anxiety score was 6. 6 ± 4. 4 and mean depression score was 6. 0 ± 4. 1. Ten (33. 3%) of the patients had screened positive for anxiety score and ten (33. 3%) screened positive for depression. The prevalence of psychological distress (either anxiety or depression) was 50. 0% (n = 15). Among the participants, eight (26. 7%) reported suicidal ideas and one (3. 3%) had a history of suicidal attempt. More than half (n = 17, 56. 7%) reported to have or were described to have anxious personality traits. Four participants (13. 3%) were already taking psychotropics and they all had HADS anxiety/depression score above cut off. Eleven participants (36. 7%) reported perceived stress. The details on barriers are provided in Table 1. Table 1: Psychological profile of the study participantsBarriers in mental health-care utilization The following results are based on those who had subjectively felt anxious, depressed, or tense (n = 19). Among those 19 participants, help-seeking was seen in 13 (68. 4%). Twelve (63. 2%) of them informed about their distress to either their neurologist or when they consulted a mental health professional. Among those 12 who informed treating doctor, 11 (92. 3%) participants reported that the treating doctor took action on their concern (viz. , listened with empathy, prescribed medicine, and referred to psychiatrist). All patients referred by the treating doctor to MHP complied with the referral, and all of them reported benefit with the treatment offered by the MHP. However, 50% of them (n = 4) stopped treatment from MHP later on. The details on barriers are provided in Table 2. Table 2: Barriers to mental health utilization among the study participantsFactors associated with mixed anxiety-depression Those with anxious trait, perceived stress, and medical comorbidity were found to have greater prevalence of mixed anxiety depression when compared to those without those risk factors. However, the associations were not statistically significant on Chi-square analysis. Other factors could not be analyzed for the association since the sample was too small to provide a meaningful result. study revealed a higher prevalence of psychological distress. Half of the patient population had objective distress. As noted in other studies, mixed anxiety depression is one of the common presentations among nonpsychiatric population. [SEP] Justify:

Output: The text corroborates the claim by providing data supporting the prevalence of anxiety and depression among the study participants. It notes that the prevalence of psychological distress, which includes anxiety and depression, was 50.0%, indicating that these disorders are indeed common in the population studied. Additionally, it mentions that mixed anxiety-depression is a common presentation among nonpsychiatric populations, further reinforcing the claim about the global commonality of these mental health disorders.


Input: Task: contrast the claim using the given text. Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Our findings were most similar to Harris and colleagues’ study [14], which also found the dominant phyla to be Firmicutes (30 %), Bacteriodetes (22 %) and Proteobacteria (17 %). The present investigation and Harris et al. ’s study [14] recovered a similar number of OTUs, 411 and 267, respectively, which was lower than the 10,177 OTUs recovered from NGS analysis of the feline oral microbiome by Sturgeon and colleagues [15]. This variation in bacterial diversity between studies is potentially attributable to the region of the 16S gene amplified. In both ours and Harris et al. ’s study [14], the V1-V3 region of the 16S gene was sequenced, which is longer than the V4 region sequenced in Sturgeon and colleagues’ study [15]. At a fine scale, there was a variation in the abundance of OTUs recovered between the studies. For example, while we found Porphyromonas at an abundance of 15 %, Sturgeon et al. [15] found it at a frequency of 2 %, which may reflect variation in the gingival health between the cats assessed. The variation in the abundance of genera could also reflect differences between the studies in terms of OTU classification methods and reference databases used for species classification. Overall, while broad similarities in the feline oral microbiome were found between our and past NGS studies, the fine-scale differences highlight the extent of unknown information about what influences the composition of the cat oral microbial community. We examined in a preliminary fashion one of the key factors thought to influence the composition of the human and feline oral microbiome, namely diet. While we detected differences in the abundance and diversity of bacteria between cats fed two broad categories of diets (dehydrated kibble versus well-hydrated meat-based or fresh meat rations), what these results mean for feline oral health is less clear. Cats consuming dry kibble exclusively, a popular choice in and to a lesser extent in Australia (13. [SEP] Justify:

Output: The text contrasts the claim by indicating that differences in diet lead to variations in bacterial abundance and diversity in the microbiome of cats. It states, 'we detected differences in the abundance and diversity of bacteria between cats fed two broad categories of diets,' suggesting that dietary changes have a direct influence on microbiome composition.