Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Because of the correspondence established in D, these virtual labels are tied to the physical objects in real space. Figure 2 with 1 supplement Download asset Open asset Spatial memory task. (A) Five objects are arranged on a half-circle; the subject explores the scene, then reports the recalled object identities and locations. (B) Recall performance during blocks 1 (left) and 2 (right). Recalled target angle potted against true angle. Shaded bar along the diagonal shows the 30 deg width of each object; data points within the bar indicate perfect recall. Dotted lines are linear regressions. (C) Slope and (D) correlation coefficient for the regressions in panel (B). Figure 2—figure supplement 1 Download asset Open asset Mental imagery task supplementary data. Spatial memory data (Figure 2) from blocks 1 (left) and 2 (right) by subject. Shaded areas indicate the true azimuthal extent of each object. Markers indicate recalled location. Most recalled locations overlap with the true extent of the object. Subjects 8–10 were normally sighted and performed the exploration phase using vision. Figure 3 with 2 supplements Download asset Open asset Direct navigation task. (A) For each trial, a target chair is randomly placed at one of four locations. The subject begins in the starting zone (red shaded circle), follows the voice of the chair, and navigates to the target zone (green shaded circle). (B) All raw trajectories from one subject (#6) including 1 s time markers. Oscillations from head movement are filtered out in subsequent analysis. (C) Filtered and aligned trajectories from all trials of 3 subjects (#3, 4, 7). Arrow highlights a trial where the subject started in the wrong direction. (D) Trajectories of subjects performing the task with only a cane and no HoloLens. (E) Deviation index, namely the excess length of the walking trajectory relative to the shortest distance between start and target. Note logarithmic axis and dramatic difference between HoloLens and Cane conditions. (F) Speed of each subject normalized to the free-walking speed. Figure 3—figure supplement 1 Download asset Open asset Direct navigation task extended data. Trial distance (A) and trial duration (B) for the first 20 trials of all subjects. A modest effect of practice on task duration can be observed across all subjects (B).

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Results and discussionStart version of ArkMAP is now the default tool used to display maps in the ArkDB web application, replacing applet drawing code. This not only allows more flexible configuration options for the user, but also allows connection to third party data resources which was not possible from within a sandboxed applet. When accessed from is automatically preloaded with the user’s selected maps, otherwise maps are downloaded via the drop down ‘File’ menu: local XML files may be opened, new maps created with a text editor, or the user may download maps from one of the configured data sources (and Ensembl Bacteria). By selecting a data source the user can browse and select maps for available species, analyses or Ensembl releases. The same File menu allows screenshots of the canvas to be saved at any time as or PNG graphics files, or printed locally. The ArkMAP user interface is dominated by the drawing canvas upon which maps can be freely positioned and resized. The canvas is scrollable and automatically expands as new maps are added. Maps are sensitive to mouse actions, and on mouse entry the rectangular bounds of a map are drawn in grey; selecting a map by clicking within this area changes the border to green; grey stretch bars at the bottom allow the map to be resized by mouse dragging (see Figures 1 and 2). Maps may be dragged around the canvas and because maps are transparent they may overlap each other, allowing the user fine control of image composition. Maps may be stacked or even overlapped in ‘columns’, and because inter-marker relationships are only drawn between maps in adjacent ‘columns’ the user can sensitively control what information is visible (in Figure 3 maps 3 & 4, and maps 5 & 6 are in adjacent columns). Figure 1Screen shot of ArkMAP showing three gene maps uploaded from Ensembl. Map 1 (highlighted) of Cow chromosome 20 was retrieved from Ensembl release 63. Map 2 was retrieved by searching for human regions of conserved synteny to map 1. Map 3 was retrieved by fetching the more recent release version 70 for the region displayed in map 1. The upper configuration panel allows the selected map to be hidden or deleted, and the tabbed panels below allow rescaling, resizing, reorienting of the axis; changing the map title; choosing font types and sizes and selecting which markers to display.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Nakamura LK1981Lactobacillus amylovorus, a new starch-hydrolyzing species from cattle waste-corn fermentations. Syst Bacteriol: 31566318. ChatterjeeM. . R. K. 1997Production of lactic acid by direct fermentation of starchy wastes by an amylase-producing Lactobacillus. Biotechnol Lett: 19873419. GiraudE. ChampaillerA. RaimbaultM. 1994Degradation of raw starch by a wild amylolytic strain of Lactobacillus plantarum. Microbiol 6043192320. VishnuC. SeenayyaG. ReddyG. Direct fermentation of various pure and crude starchy substrates to L(+) lactic acid using Lactobacillus amylophilus GV6. 2002184293321. NaveenaB. J. MdAltafBhadrayya. K. MadhavendraS. S. ReddyG. 2005Direct fermentation of starch to L(+) lactic acid in SSF by Lactobacillus amylophilus GV6 using wheat bran as support and substrate-medium optimization using RSM. 406819022. AnuradhaR. SureshA. K. VenkateshK. V. 1999Simultaneous saccharification and fermentation of starch to lactic acid. 353677523. ZhangD. X. CheryanM. 1994Starch to lactic acid in a continuous membrane reactor. 291455024. NaveenaB. J. VishnuC. MdAltafReddy. G. 2003Wheat bran an inexpensive substrate for production of lactic acid in solid state fermentation by L actobacillus amylophilus GV6-optimization of fermentation conditions. J Res62453625. Goel MK. Biotechnology: an overview;1994 AltafM. VenkateshwarM. SrijanaM. ReddyG. 2007An economic approach for L-(+) lactic acid fermentation by Lactobacillus amylophilus GV6 using inexpensive carbon and nitrogen sources. J Appl Microbiol;1033728027. PandeyA. SoccolC. R.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: “Essential reading for anyone who wants to understand why systems meant to save our lives end up killing us instead. ” — author of Ambulance: Choreographing the End of Life in Thailand “A richly detailed and theoretically innovative ethnography that illuminates how neoliberal health care systems can undermine a legally guaranteed right to health care. ” — author of State of Health: Pleasure and Politics in Care under Chávez “This book has much to offer to anthropologists, clinicians, bioethicists, philosophers, and policymakers who want to understand how inequities are remade and reframed by market-based health care reforms. ” — CÉSAR E. ABADÍA-author of Health in Ruins: Destruction of at a Sanz is of Anthropology at the University of de& reboots, franchises, and songs that remake old songs—does it feel like everything new in popular culture is just derivative of something old? Contrary to popular belief, the reason is not audiences or marketing, but Wall Street. In this book, Andrew deWaard shows how the financial sector is dismantling the creative capacity of cultural industries by upwardly redistributing wealth, consolidating corporate media, harming creative labor, and restricting our collective media culture. Moreover, financialization is transforming the very character of our mediascapes for branded transactions. Our media are increasingly shaped by the profit-extraction techniques of hedge funds, asset managers, venture capitalists, private equity firms, and derivatives traders. Illustrated with examples drawn from popular culture, offers readers the critical financial literacy necessary to understand the destructive financialization of film, television, and popular music—and provides a plan to reverse this dire threat to culture. “The thoughtful and thought-provoking 1524. The current movements in Cotzal, rooted in a long history of resistance, counter dominant narratives of that often portray them as “conquered. ” Egyptian Things: to the deaths of Antony and Cleopatra, Rome finally took control of Egypt. This occupation simultaneously facilitated and circumscribed the exchange of goods, people, and ideas along the paths carved by Rome’s burgeoning empire. In this book, sets out to recapture one of these systems of exchange: the vibrant literary tradition known as Aegyptiaca—or “Egyptian Things”—in which culturally mixed authors wrote about Egypt for a Greek and Roman audience.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Colour key: purple: identity, sky-blue: synonymy, black: one-to-one orthology, vermilion: apparent one-to-one orthology, orange: one-to-many orthology, blue-green: many-to-many orthology, blue: possible orthology, yellow: paralogy. ▲ forward transcribed gene; ▽reverse transcribed gene. Full size imageFigure 2Composite screen shot of ArkMAP illustrating various interactive options. Map 1 has been zoomed to show bases 1-40M of a chicken ePCR map from ArkDB, the selected (green highlighted) region of this map has been used to retrieve the cognate gene-annotated assembly from (map 2). As the mouse cursor is moved over the canvas it changes to reflect available actions for the underlying map object. Three versions of the cursor are shown here: cross hairs used to select regions on the axes, a double arrow used to stretch the selected map (2) and the open hand indicating that the map can be moved by mouse dragging. In addition the (hand) cursor has triggered display of a pop-up box displaying the coordinates of the blue-highlighted marker. Mouse clicking this selected marker would display a more detailed pop-up with further information and interaction options. The gene mappings from Ensembl include orientation information: ▲ forward or ▽ reverse transcribed gene. Alternate ‘Context Menus’ are shown for selected regions of each map. In both cases the user may zoom or project (duplicate) the selected map region. In the case of the ArkDB ePCR map the user may choose to import the cognate Ensembl chromosome (performed here), whilst for the Ensembl assembly map the user may import alternate release versions of the annotated assembly, import dbSNP variation maps (where available), search for regions of conserved synteny in a specified target species or choose to perform threshold filtering on any homology relationships for genes on this map. Full size imageFigure 3Composite screen shot of ArkMAP detailing a mapping analysis of low quality Salmon data. Map 1 is a private (and obfuscated) salmon QTL linkage map (Houston RD, Gonen S: per. comm. ) which uses SNP markers shared on published linkage map of salmon chromosome 26 (map 2 [25]).

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Rodriguez-LeonJ. A. NigamP. 2001Solid state fermentation in biotechnology: fundamentals and applications. New Delhi: Asiatech Publishers28. MercierP. YerushalamiL. RouleauD. DochaniaD. 1992Kinetics of lactic acid fermentations on glucose and corn by Lactobacillus amylophilus. J Biotechnol 551112129. ChengP. MullerR. E. JaegerS. BajpaiR. JannottiE. L. 1991Lactic acid production from enzyme thinned cornstarch using Lactobacillus amylovorus. J 72734 30. KurusavaH. IshikawaH. TanakaH. L-lactic acid production from starch by co-immobilized mixed culture system of Aspergilus awamori and Streptococcus lactis. 198831183731. KristoficovaL. RosenbergM. VlnovaA. SajbidorJ. CetrikM. Selection of Rhizopus strains for L (+) lactic acid and gammalinolenic acid production. 199136451532. 1979Lactobacillus amylophilus, a new starch hydrolyzing species from swine waste-corn fermentation. Microbiol 205314033. Prasana VA2005Amylases and their applications. Afr. J Biotechnol 4131525152934. SivaramakrishnanS. GangadharanD. MadhavanK. 2006Amylase from microbial sources-An overview on recent developments. Food technol. Biotechnol. 44217318435. GhorbelR. E. MaktoufS. MassoudE. B. BejarS. ChaabouniS. E. 2009Amylase from Bacillus cohnii US147 with a Broad pH Applicability. Appl. Biochem. Biotechnol. 157506036. 1998Production and properties of a raw starch degrading amylase from thermophilic and alkaliphilic Bacillus sp TS-23. Biochem, 281616837. GiraudE. CunnyG.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: Close navigation menu in Comorbidity of Mental and Edited by N. Sartorius; N. for other works by this author on: PubMed 10. 1159/isbn. 978-3-318-02604-7 Status: Available ISBN electronic: 978-3-318-02604-7 ISBN print: 978-3-318-02603-0 Subject Area: and Gerontology Oncology Psychiatry and Psychology Book Series: in Publication date: 2014 This publication presents evidence about the magnitude and severe consequences of comorbidity of mental and physical illnesses from a personal and societal perspective. Leading experts address the huge burden of co-morbidity to the affected individual as well as the public health aspects, the costs to society and interaction with factors stemming from the context of socioeconomic developments. The authors discuss the clinical challenge of managing cardiovascular illnesses, cancer, infectious diseases and other physical illness when they occur with a range of mental and behavioral disorders, including substance abuse, eating disorders and anxiety. Also covered are the organization of health services, the training of different categories of health personnel and the multidisciplinary engagement necessary to prevent and manage comorbidity effectively. The book is essential reading for general practitioners, internists, public health specialists, psychiatrists, cardiologists, oncologists, medical educationalists and other health care professionals. ‹ › 10. 1159/000365941 Published: 2014 Subject Area: and Gerontology Oncology Psychiatry and Psychology Book Series: in Split-2014. "the Costs: Impact of Comorbidity", Comorbidity of Mental and Physical Disorders, N. Sartorius, R. I. G. Holt, M. citation file: Ris (Zotero) toolbar search search input Search input auto suggest filter your search © 2015 S. Karger AG, Basel2014License DisclaimerThis 4. 0 (CC BY-NC-ND). Usage and distribution for commercial purposes as well as any distribution of modified material requires written permission. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The best BlastX hits for sequences flanking the salmon SNPS were mapped as ‘orthologous sequences’ on the stickleback (map 3) and medaka (map 4) genome assemblies. These maps were then projected onto the gene annotated assemblies downloaded from Ensembl (maps 5 and 6). The figure is a composite screenshot from ArkMAP showing ‘Identity’ relationships in purple and ‘Synonymy’ relationships in blue (key as in Figure 1). Full size imageWhen a map is selected various (collapsible) configuration panels are displayed (see Figure 1). In the upper panel maps may be hidden (using the ‘eye’ icon) or permanently removed. Separate tabbed control panes allow rescaling, resizing, reorienting of the axis; changing the map title; choosing font types and sizes and selecting which markers to display. Maps are drawn vertically as a scaled red axis, with labelled markers positioned as points or ranges; where available marker orientation is shown (see Figures 1 and 2). The user can select a sub-region of a map by mouse dragging along the labelled side of the axis, causing a context-dependent menu to be displayed beside the highlighted selection (see Figure 2). As described above, in addition to facilitating zooming or duplication (projection) of the region, various further options are presented according to type of map. Figure 1 illustrates an ArkMAP workflow that compared bovine genome builds between Ensembl releases, which was informed by querying a map for regions of conserved synteny in a better characterized model species (human). The gene-annotated map of bovine chromosome 20 (map 1) was loaded from Ensembl release 63 which used assembly version Btau_4. 1. This map has been zoomed to show the first 4. 5 MB, and the majority of marker labels have been hidden using the configuration panel. This region was selected, and searched via the ‘Context Menu’ for regions of conserved synteny with the annotated human genome. Conservation queries are performed by the JEnsembl API, which successively searches the data source for human homologues to each bovine gene located on the selected region. It should be noted that as the search time is proportional to the number of genes selected, searching large chromosomal regions may cause ArkMAP to become non-responsive.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: 1997Molecular characterization of the α-amylase genes of Lactobacillus plantarum A6 and Lactobacillus amylovorus reveals an unusual 3’ end structure with direct tandem repeats and suggest a common evolutionnary origin. Gene 198149157 38. TalamondP. DesseauxV. MoreauY. SantimoneM. Marchis-mourenG. 2002Isolation, characterization and inhibition by acarbose of the α-amylase from Lactobacillus fermentum : comparison with Lb. manihotivorans and Lb. plantarum. Comparative Biochem. and Physiol. 13335136039. Qui and Yao2007Lactic acid production, rice straw. Bioresources 2341942940. Sawadogo-LinganiH. DiawaraB. ASTraoréJakobsen. M. 2008Technological properties of Lactobacillus fermentum involved in the processing of dolo and pito, sorghum beers, for the selection of starter cultures. J. Appl Microbiol, 104387388241. ChampagneC. 1998La production des ferments dans l’industrie laitière Ed. Agriculture et Agroalimentaire, Canada,32145 42. EdelmanS. Westerlund-WikströmB. LeskeläS. KettunenH. RautonenN. ApajalahtiJ. KorhonenT. K. 2002In vitro adhesion specificity of indigenous lactobacilli within the avian intestinal tract. Microbiol 685155515943. HofvendahlK. Hahn-HagerdalB. 1997L-lactic acid production from whole wheat flour hydrolysate using strains of Lactobacilli and Lactococci. Technol 20301307 44. . MoonS. H. FrankJ. R. 1993Technological and economic potential of polylactic acid and lactic acid derivatives. International congress on chemicals from biotechnology, Hannover, Germany 1845. 2006Biotechnological production of lactic acid and its recent applications. Biotechnol 441637246. SenthuranA. SenthuranV. MattiassonB. KaulR.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product 4. 0. 2008. Mean healthcare costs were significantly higher in the schizophrenia group; a key driver of greater healthcare costs was the significantly higher rate of physical health problems, including congestive heart failure (45. 1 vs. 38. 8%), chronic obstructive pulmonary disease (52. 7 vs. 41. 4%), hypothyroidism (36. 7 vs. 26. 7%) and dementia (64. 5 vs. 32. 1%) [7]. Turning to bipolar disorder, in the USA the medical records (spanning 1 year) of more than 28,000 people with bipolar disorder were compared with matched controls without any mental health problems [8]. Those with bipolar disorder had a significantly higher prevalence of metabolic comorbidities than the general population (37 vs. 30%). Annual healthcare costs for metabolic conditions were twice those of controls (USD 531 vs. 233). The bipolar cohort also had significantly higher overall medical service and prescription drug costs than those of the control cohort (USD 12,764 vs. 3,140). Prescription medication costs for metabolic conditions were also higher, with bipolar cohort per-patient costs of USD 571 versus 301 for the control cohort. Analysis of data on 67,000 members of a health insurance fund in seven US states also suggests that 67% of total healthcare costs of bipolar disorder were related to the treatment of comorbid physical health conditions [9]. Comorbid depression or anxiety disorders and physical health problems have also been associated with higher levels of cost to healthcare systems. One US study reported that the costs of 11 chronic health problems are significantly greater when an individual has comorbid depression. Costs related to diabetes, coronary artery disease and congestive heart failure were approximately twice the costs of individuals without depression [10].

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: This map is aligned (by marker identity) with a published salmon linkage map [25] (map 2), downloaded from a private ArkDB data source. The salmon SNP markers were analysed by BlastX in order to map orthologous sequence markers on the genome assemblies of stickleback and Japanese medaka. Chromosome regions sharing markers (by synonymy) with the QTL region of interest were downloaded, zoomed and aligned with the salmon linkage map (maps 3 and 4). Using the ‘Context Menu’ these regions of the physical maps were used to retrieve the cognate regions of the stickleback and medaka genome assemblies from Ensembl (transferring the ‘salmon orthologue’ markers across to the gene-annotated maps; shown in red, maps 5 and 6). The gene maps for the better characterized model fish species are therefore now aligned with a potential region of conserved synteny in the poorly characterized salmon QTL region. The user could extend the analysis by aligning synonymous markers on the medaka and stickleback maps, querying for regions of conserved synteny between various fish genomes, and drilling down to get details and homologies for individual genes on the maps. It is worth noting here that care should be taken when considering the significance of synonymy relationships. Sharing a name does not necessarily imply that the markers are the same, use an identical detection technique or are orthologous between species. Conversely if markers on different maps have the same ArkDB accession ID or Ensembl stable identifier, there is greater confidence that they represent the same object on each map (e. g. for ArkDB a marker typically represents a particular detection protocol, whereas Ensembl IDs represent a stable curated gene model). In the analysis shown in Figure 3, the markers present on the ArkDB stickleback and medaka maps are Blast analysis target hits, which have been named identically to the source salmon sequences, so we can be reasonably confident in the significance of the ‘synonymy’ relationships between the salmon, stickleback and medaka maps. Figure 4 illustrates the integration of public mapping data across the ArkDB and Ensembl sources. In this case a legacy bovine linkage map (1) is aligned by marker identity with an ePCR map of the marker set on the bovine genome (2).

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: We also acknowledge that EET could involve other as-yet unidentified respiratory components (lines 478-485 and 504-5) and that we cannot exclude ATP generation by oxidative phosphorylation (lines 482-485). Reviewer #1 (Recommendations for the authors): 1) The only weakness: The methods and results of metabolite analyses are not sufficiently described. This requires explanation if conclusions are to be made about yield, fermentation, and physiology. The paper provides strong evidence that electron diversion to external acceptors is an electron sink. However, while quantitative conclusions are made about fermentation, only ~30% of the mannitol can be accounted for in the EET condition that is the focus of this paper. Put another way, the paper is about where electrons go, but the majority of the electrons are missing. Clarify if this strain can excrete products such as sugar polymers, sugars, pyruvate, formate, glycerol, acetoin, or butanediol. State if standards for these were included in the product analysis (an RI detector can pick up nearly all of these). Explain why formate isn't present (was it not measured? ), as this would allow determination of flux through PFL vs. a pyruvate excretion, a carbon sink of acetoin, or butanediol. Could missing carbon be due to excretion of a partially oxidized sugar like fructose (which would also show up on an RI detector), or accumulation of storage polysaccharide? We thank the Reviewer for the Reviewer’s strong endorsement of our manuscript and clear recommendations for improvements. In the revised manuscript, we provide additional data showing where ~80% of the carbon goes under EET conditions (1) and where the majority of the carbon goes under open circuit conditions. With this more complete information, our balances account for between 77-96% of the electrons (see Supplement file 1). These new data more completely support our conclusion that EET increases fermentation product yield, metabolic flux, and environmental acidification. A) Address these questions in the section around line 299; where fermentation products are mentioned as being present or absent. What was looked for, but not found (lactate yes, succinate no), vs which were not looked for, (pyruvate? Formate? Acetoin, etc). This makes it clear that carbon is not missing, just that the methods were unable to detect it.

Output: pass


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: Two reviews, one with 27 [11] and the other with 41 largely US-set studies [12], looked at the impact on healthcare resource utilisation of comorbid diabetes and depression. Both reviews consistently showed increased healthcare resource use to manage diabetes in people with depression. For example, in one study of more than 400,000 adults with diabetes in the USA, the costs of depression increased mean annual healthcare costs from USD 11,000 to 19,000 [13], while in Australia, health service use by people with comorbid diabetes and depression was 49% higher compared to those with diabetes alone [14]. In another US study, the healthcare costs of managing diabetes over a 6-month period were found to be between 50 and 75% higher in people with major depression than in people with diabetes alone [15]. Furthermore, this study observed a significant difference in the costs of managing one or more complications of diabetes in people with major depression compared to those with sub-clinical thresholds of depression. Other studies also point to higher costs of managing complications. In the USA, the costs of managing complications of diabetes, such as diabetic neuropathy, in people with comorbid depression have also been shown to be significantly greater than in those without depression [16]. Another US study looked at the healthcare costs of more than 14,000 people with depression, congestive heart failure, or both [17]. People who also had depression had significantly higher total annual healthcare costs than those without: USD 20,046 versus 11,956. Costs increased with the severity of comorbidity, but mental healthcare costs accounted for less than 1% of total healthcare costs. Outside of the USA, significantly increased costs to healthcare systems have also been observed when comorbidity involved depression. English data from more than 86,000 patients in the were used to assess whether comorbidity increases the costs of managing patients in primary care [18]. The study found that 20% of all patients had more than one chronic health problem and that all instances of comorbidity increased the costs of primary healthcare compared to the costs of managing these conditions separately. Depression was found to be the most important cost-increasing condition, significantly increasing costs in adult patients of all ages when comorbid with a wide range of conditions.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: SetupTesting platform The experiments have been performed on the Cloud infrastructure. In particular, a 8-node Spark 2. 1. 0 cluster has been deployed into HDInsight, Microsoft’s cloud distribution of the Hadoop ecosystem (Hadoop 2. 7. 3), based on the Platform. Two cluster nodes act as head nodes, and are equipped with an 8-core 2. 4 GXeon E5-2673 v3 processor and 28GB of RAM each. Furthermore, the cluster has other six worker nodes, each with two 8-core 4. 78 GXeon E5-2673 v3 processors for a total of 16 cores, 112GB of RAM and a 800GB local SSD disk, and an overall disk capacity of 4. 8TB. jobs have been configured to use 2 cores per executor, the number of executors, instead, varies according to the specific experiment performed. the experimental validation, we have used the metagenomic dataset described in [50]. In particular, the SRR094926 run of the SRP004875 SRA study (available on the NCBI short read archive) has been considered, for a total space occupation of about 125GB (FASTA format). Furthermore, another dataset containing only the first 32GB of this run has also been considered. 1 for summary information. Table 1 Number of distinct and total k-mers for our datasetsFull size table Experimental evaluationThis section presents an experimental study of different configurations and parameters, as well as of their main implications on the performances of FastKmer. Values ofk. For all experiments, we examine the running time performance of the k-mer statistics collection task on our datasets for two different reference values of k: 28 and 55. Following the choice of [35], these two values have been chosen as examples that reflect both the case where each k-mer can be stored using a single Long variable, as well as the case where it requires more variables. Signature length. Preliminary experiments have been performed in order to tune the signature length parameter m (data not shown but available upon request). The result is that small values of m increase the probability that consecutive k-mers share the same minimizer and thus reduces the I/O cost at the end of the first stage. However, if too small, it might render the distribution of partition sizes skewed and the largest partition might not fit in memory.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: c) Lack of DHNA is always used as a reliable negative control in the other experiments, provide any data that shows if the addition of DHNA is essential for the mV drop in this assay, so we know it is also an assay of EET. Lacking better evidence/controls, this is one of the weaker bits of data in the main body, especially next to the more robust Fe/current data. Appropriate for supplements, but not conclusive as is. We now provide background and justification for our use of ORP experiments (lines 213-217). Extracellular redox potential is also referred to as oxidation-reduction potential (ORP), which is the ratio of all oxidative to reductive components in the environment (Killeen et al. , 2018 – Am. J. Enol. Vitic. ). Redox reactions are prevalent in food fermentations (see Hansen, 2018 – Curr. Op. Food. Sci. for a comprehensive list) and ORP directly influences the outcome of fermentations with lactic acid bacteria (Brasca et al. , 2007 – J. App. Micro. , Olsen and Pérez-Díaz 2009 – J. Food Sci. ). A) Already after one hour incubation in mMRS there was a significant difference in ORP between the wild-type and ndh2 deletion mutant. This change was also observable for the pplA deletion mutant after three hours incubation. ORP differences between the wild-type and the two mutant strains persisted for the duration of the experiment. Additionally, we note that other factors besides EET will affect ORP. Although our new data show that DHNA, and therefore EET capacity, is a major driver of ORP reduction, L. plantarum and related bacteria (e. g. L. lactis) possess NADH oxidase and therefore are able to reduce O2, thereby also contributing to ORP reduction (Tachon et al. , 2010 – App. and Env. Micro). Hence, although we expect that iron was reduced by the wild-type L. plantarum strain, it was not the only redox active compound. We revised the text (lines 219-228) and Figure 3B to clarify these distinctions. B) pH values along with the experimental data collected in response to comment C (below), have been added to a new Figure 3 – supplement figure 1.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: For instance, the costs of managing comorbid depression and asthma or diabetes were greater for patients of all ages, whilst depression and comorbid cancer were associated with significantly higher costs in people aged 40-59 years. Depression and comorbid obesity, heart failure or epilepsy were associated with significantly higher primary care costs in patients aged over 60 years. Increases in cost ranged from GBP 269 for people aged 40-59 years with depression and cancer to GBP 2,817 in people with comorbid depression and obesity aged 40-59 years. In younger adults, mean additional costs related to asthma and comorbid depression were GBP 1,257, while comorbid diabetes and depression increased costs by GBP 2,133 in people aged over 60 years. Other examples of additional costs from around the world can be identified. In Singapore, adults attending a specialist diabetes centre over a 1-year period who also had depression had a 30% chance of hospitalisation compared to 10% in the diabetes-alone group. They were four times more likely to be hospitalised for non-psychiatric conditions and three times more likely to be hospitalised for complications of diabetes [19]. In Hungary, a survey of more than 12,000 people looking at their use of health services over a 12-month period found that those with comorbid diabetes and depression had a 2. 6 times greater risk of a lengthy period of hospitalisation and had almost double the risk of multiple hospital admissions compared to people with diabetes alone [20]. Another study looked at the impacts of physical comorbidity on healthcare costs for 65,000 people receiving primary care in Spain in 2004. Individuals with a depressive disorder had a significantly greater number of comorbid conditions or risk factors, including obesity, dyslipidaemia and smoking per year compared to other primary care service users (7. 4 conditions vs. 4. 3). Overall the annual costs of care were EUR 1,084 and 684 per patient in the comorbid and control populations, respectively [21]. In the UK, the economic impacts of smoking in people with mental disorders have been estimated to cost primary and secondary care service providers GBP 720 million per annum in treating smoking-related disease. The study also estimated that about a third of all cigarettes smoked in England are smoked by people with a mental disorder. This could mean that there are 2. 6 million avoidable hospital admissions, 3.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: On the other hand, a large value of m will make the distribution of partition sizes more balanced at the cost of a higher redundancy (with no compression for m→k). The assignment which empirically yields, on average, the best performance on the considered datasets is m=10. This is in line with the results in [35, 46] on datasets of comparable characteristics. Number of bins. The number of bins B used for the signatures binning scheme is considered. At the starting of the second stage, each partition contains a number of bins to be processed. Having few bins decreases the overall memory management overhead to be paid at the beginning and at the end of the processing of each bin. As a downside, having few, very large bins might require an amount of memory exceeding the one available to a worker process. On the other hand, a larger number of bins allows for a better granularity of the distributed execution and reduce memory requirements for each worker process, as each bin can be processed independently. However, in such a case, there is an increased memory management overhead for each worker process. Spark parallelism. A Spark-specific parameter which may have an impact on the running time and cluster usage, is the Spark parallelism level (p). This parameter corresponds to the number of tasks that are spawned by Spark (as well as the number of partitions). Its choice has a side effect on the number of bins mapped to partitions: if bin numbers are uniformly spread, each task will receive a number of bins that tends to B/p. On large bins. As previously stated, when using the minimizer-based approach, the distribution of superkmers associated to signatures can be very uneven, with particularly frequent signatures tending to have a very large fraction of superkmers. This is mainly driven by the minimizer-based scheme: the distribution of superkmers associated to signatures can be very uneven, with low lexicographic signatures, tending to have a very large fraction of superkmers, compared to the rest. This is partly mitigated by the choice of signatures within a suitably filtered sets of canonical minimizers that do not start with common prefixes, and by the hash-based mapping of signatures to bins. Nevertheless, since the scheme is data-oblivious, it might still produce large bins.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Lacking good carbon or electron recovery, neither can be ruled out, though the non-respiratory reductive pathway is most logical. While the Reviewer’s reasoning is sound, L. plantarum, like other lactic acid bacteria, only possesses the reductive branch of the TCA cycle; it does not possess an oxidative branch (Tsuji et al. , 2013 – Technol). Thus, we can rule out the possibility of TCA cycle oxidation, leaving the reductive branch as the only way to produce succinate. In agreement with the prior literature, we detected only trace amounts of succinate amongst the many TCA cycle metabolites we looked for: succinate, fumarate, oxaloacetate, citrate, malate. Thus, we are confident that the metabolic flux through the reductive branch of the TCA cycle was marginal, if present. In the revised manuscript, we now explain that L. plantarum does not possess an oxidative branch of the TCA cycle and that our measurements were sensitive to, but did not detect, these other TCA cycle intermediates (lines 308-310 and 312-314). 6) Table 1/line 403-: The low YATP in cells using EET is a possible 'different energy conversion strategy'. (Side note- an energy spilling/Russell mechanism would be an 'ATP-dissipating', not -accumulating). I'd suggest uncoupling of acid production from growth by low pH seems likely. In most strains, simple glycolytic pathway functions at low external pH, but complex protein synthesis and replication processes become inhibited, ATP from substrate turnover is needed to maintain pmf and internal pH, and high internal organic acids become toxic. Citable yield/pH data can be hard to locate as it comes from the 80's in the age of calling every lactic acid bacterium a Streptococcus, but since the non-EET cultures at neutral pH got close to the Bauchop and Elsden YATP, and EET cultures at pH 4 were a fraction of this, these data look like common behaviour of many lactic acid bacteria. In future comparisons, pH control could help estimate energy yields from EET. The first paper I found in a quick search to illustrate pH effects was: Russell and Dombrowski, DOI: 10. 1128/aem. 39. 3.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: 1 million avoidable primary care consultations and 18. 8 million prescriptions that can be avoided each year [22]. In Germany, analysis at one teaching hospital over a 2-year period again reported that the average total costs of hospitalisation for people with cardiovascular disease alone compared to those with psychiatric comorbidity (largely depression and anxiety disorders) differed significantly (EUR 5,142 vs. 7,663). The average length of stay for patients with comorbidity was 13. 2 days compared to 8. 9 for patients with cardiovascular disease only [23]. Furthermore, this paper highlighted that the funding system in that hospital did not fully cover the costs of comorbidity, which means that patients might not receive appropriate levels of care. There is also some limited information looking at the association between healthcare costs and comorbid asthma and mental disorders. One systematic review found 20 studies, largely focused on depression or anxiety disorders and asthma. It reported increased rates of hospitalisation, emergency department visits and visits to primary care practitioners in people with asthma and a mental disorder [24]. In the USA, a telephone survey of adolescents (aged 11-17 years) with asthma found that those assessed to have depressive disorders as well had on average 51% higher healthcare costs [25]. Most of these additional costs were related to non-asthma and non-mental health-related healthcare costs. Impacts beyond There appear to be fewer estimates of the impacts of comorbidity beyond the healthcare system. Published estimates concentrate on indirect costs - mainly productivity losses from employment due to absenteeism, with much less discussion of poor performance at work (presenteeism); there does not appear to be much information on the intangible costs of comorbidity. One review looked at the impact on participation in employment of people with coronary artery disease and mental disorders [26]. Only 13 studies were identified, 10 of which focused on comorbid depression. The review concluded that people with comorbid depression had a reduced likelihood of returning to work following the onset of illness (odds ratio 0. 37) compared to people with coronary artery disease alone. A systematic review on comorbid diabetes and depression identified 11 studies that looked at the impacts on productivity, but only two of these studies assigned a monetary value to productivity losses and none included losses from premature mortality or informal care [12].

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: In our distributed setting, this is particularly relevant because they can introduce bottlenecks where the running time is impacted by a few number of workers that take more time than the others, thus leading to a non-optimal utilization of the cluster. Experimental results. Figure 3 shows the running time of FastKmer when run with 16 executors, (for a total of 32 workers), using various values of B corresponding to powers of two between 512 and 16. 384, and a parallelism levels ranging from 32 to 512 (corresponding, respectively, to 1 and 16 average tasks per core). As per the number of bins, performances improve consistently for values of B up to 8192, after which we have no improvement (also for higher values of B, not plotted for legibility). The x-axis shows the parallelism p: again, for both values of k, we see a performance increase when we raise p up to 320 tasks. No improvement, if not a slight deterioration, is noticeable for higher values of p. This is expected: while higher parallelism tends to better spread large bins across many partitions, conversely, more tasks determine more scheduling overhead for their start and finalization. Spark tuning guidelines, [51], suggest setting a parallelism level that is in the range of 2−3 tasks per core: this choice of p leads to 10 tasks per core in our test instance (32 workers), suggesting a possible heavy scheduling-related overhead. Fig. 3Algorithm execution times on the 32GB dataset with k=28,55 and an increasing number of bins (B) and parallelism level. Best combination shown in boldFull size image Intuitively, increasing both values of B and p mitigates the big bins problem, since: (i) mapping signatures to more bins means potentially big signatures to be spread over a larger number of bins, (ii) increasing parallelism allows to split big bins as they are more granular and distributed across more tasks. This does not fully remedy the fact that bins can have very different sizes. A further inspection of the distribution of the single task running times for low values of B and p shows that some tasks take much longer than others (peaking at as much as 50% of cluster underutilization, for some configurations).

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: “Fermentation” refers to the pathways that restore the NAD+/NADH ratio and allow growth with substrate-level phosphorylation as the sole mechanism of ATP generation. Per the Reviewer’s helpful suggestion, the Introduction text has been revised to define substrate-level phosphorylation and fermentation (lines 50-54). Lines 50-51 and 373-374: Some organic compounds can also be respired (for example fumarate). is correct here. The introduction (lines 41-49) includes a broad definition of anaerobic respiration, which includes using both organic and inorganic compounds. We acknowledge that the original text (lines 373-374) may lead the reader to think that respiration is only associated with the use of inorganic electron acceptors. To avoid this confusion, we now state that another major difference in fermentation and anaerobic respiration is the use of the endogenous versus external organic electron acceptors (lines 377-378). Lines 51-52 should say “Fermentative bacteria produce ATP solely via substrate-level phosphorylation” because substrate-level phosphorylation also occurs when bacteria are growing by respiration (i. e. , in glycolysis). We have revised this sentence (lines 50-52). Instead of using the word ‘solely’, we prefer to employ the word ‘mainly’ since ATP can also be generated via respiration in some primarily fermentative bacteria, like lactic acid bacteria, under specific conditions. Lines 71-73: It is unclear how the property of being “exergonic” or “endergonic” is relevant in the context here. We agree with the Reviewer that providing these details is not relevant and have removed them. Lines 85-86: “…EET is associated with non-fermentative respiratory organisms…” Does this refer specifically to endogenous EET (i. e. , without an added mediator? ). This should be clarified because there is a long history of research on fermentation+EET in the presence of added mediators (see next comment). makes a good point, and we revised the sentence to clarify that we are describing that endogenous EET is mainly associated with respiratory species.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: Data from a cross-sectional survey of 78,000 workers in Australia [27] show higher relative risks of both absenteeism and poor functioning while at work in individuals with comorbid psychological distress and physical health problems compared to those with physical health problems only. For instance, compared to people with no health problems, the risk of absenteeism from work was 33% higher for people who were experiencing psychological distress alongside obesity, and 27% higher for those who had high levels of cholesterol. Rates of presenteeism were between 2. 5 and 5 times greater in populations with comorbid asthma, obesity, arthritis, diabetes and high cholesterol compared with the reference population. Data from the 2007 Survey of and Wellbeing (n = 8,841) have also been used to compare work functioning and absenteeism rates in people with depression, cardiovascular disease, or both conditions, with a disease-free population [28]. As table 3 shows, compared to a population with neither condition, and adjusted for various social and demographic characteristics, the odds ratio for people with comorbid depression and cardiovascular disease participating in work was significantly lower at just 0. 4. This compared with odds ratios for work participation of 0. 8 for depression or cardiovascular disease only. The comorbid group were also 10 times more likely to experience poor work functioning compared to the healthy workforce, 9 times greater than for people with cardiovascular disease alone and 2. 5 times greater than for people with depression alone. Rates of absenteeism were also significantly higher for the comorbid group. Table 3Work participation, work functioning and disease group in Australia [28] View largeData from a large Canadian survey of more than 130,000 people found (even after adjusting for socio-demographic characteristics, alcohol dependence and chronic physical illness burden), that the presence of comorbid major depressive disorders was associated with twice the likelihood of healthcare utilisation, and increased functional disability and work absence compared to the presence of a chronic physical illness without comorbid depression [29]. Significant increases in resource use and productivity losses have also been reported in a population survey of more than 12,000 adults in Hungary [20]. People with comorbid diabetes and depression were more than twice as likely to have lengthier stays in hospital (>20 days) and to have more hospital admissions. They were also more than 3 times as likely to have a prolonged absence (>10 days) from paid work and to be unemployed.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: In this setting, jobs correspond to bins, and their processing time is estimated as the number of k-mers contained in the corresponding bin (later, referred to as bin size), and the number of machines is assumed to be the number of partitions. From the FastKmer viewpoint, the integration of this scheduling algorithm requires two main modifications to the original pipeline. At the beginning of the computation, a new preliminary stage is run to derive an estimation of bin sizes by examining a sample of the input data (whose size can be specified, defaulting to 1%). This estimation is then used to compute a schedule using LPT. In turn, the resulting schedule is used by a custom partitioner replacing the original one available with Spark for mapping bins to partitions at the end of the first stage. Granularity of working units. In order to further mitigate the “big bins problem”, we also take into consideration a variant of the partitioning scheme, that instead of bins, uses the signature value itself to implement the binning process. In our multiprocessor scheduling analogy, the set of superkmers belonging to a signature represents a job. This choice achieves two major benefits: (i) it allows the removal of a parameter (B) which should be, otherwise, optimized, (ii) it allows for the finest granularity of work units for the second phase of the task, that will prove to be particularly convenient for our custom-partitioner based implementation, as shown in the following experimental section. Custom partitioning results. Figure 4 reports a running time comparison between an implementation of FastKmer using the default Spark partitioner (left), and another one implementing our custom multiprocessor scheduling-based partitioning scheme (right) run on our 32GB dataset. As for our custom partitioner, it further compares two different granularities for the work units: bins and signatures (solid vs dashed lines). For the bins granularity (B=8192, resulting from the previous analysis), the impact of the custom partitioner is moderate. For the signatures choice, instead, the improvement of the custom partitioner has a consistently higher margin, suggesting an important impact of the imbalanced signatures distribution. On a related note, it can be noticed that the improvement is starting at the lowest level of parallelism (1 task per CPU core), and increases up to 128 total tasks (4 tasks per CPU core).

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: This finding made us realize that even well-studied phenomena, such as glucose repression in yeast, are observed differently between pure culture and mixed culture. Hereafter, the “specialist” mode is defined as the state in which yeast obtains energy predominantly from glucose due to glucose repression, and the “generalist” mode is defined as the state in which yeast utilizes various carbon sources through bypassing glucose suppression. These reports greatly stimulated us to investigate whether sake yeast exhibits the same phenomenon during sake making. Rice components are converted into sake by the metabolic capacity of koji fungus and sake yeast; lactic acid bacteria are also essential especially in the traditional sake making represented by the kimoto method, (Kitagaki and Kitamoto 2013; Bokulich et al. 2014; Takahashi et al. 2021; Ito et al. 2023). As a preliminary step to sake fermentation, the shubo yeast starter is produced to cultivate a large amount of viable yeast. In traditional methods, lactic acid bacteria that originate from ingredients or environments spontaneously grow from the mixture of rice, koji, and water, resulting in an increase of the lactic acid concentration and a decrease of the pH. Sake yeast has a higher tolerance to lactic acid than the other microorganisms, allowing it to grow dominantly. Therefore, the state of sake yeast in a traditional yeast starter is far from pure culture, and it begins to grow surrounded by an overwhelming number of lactic acid bacteria. As the ethanol concentration increases, the lactic acid bacteria die off, and a yeast starter consisting almost exclusively of viable sake yeast is completed. If lactic acid bacteria may alter the carbon metabolic mode of sake yeast, we should pay more careful attention to such microbial interactions during sake making. We found that kimoto lactic acid bacteria, such as Leuconostoc mesenteroides and Latilactobacillus sakei, switch the carbon metabolic mode of sake yeast from a glucose utilization “specialist” to a “generalist” (Figure 1) (Watanabe et al. 2018; Watanabe and Takagi 2019). The “specialist” and “generalist” modes can be distinguished by the growth on the agar plate containing glycerol as a carbon source in the presence of a non-metabolizable glucose analog, glucosamine (a. k. a.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: In Finland, analysis of certified sickness absence in 33,000 public sector employees reported that non-cardiovascular comorbid conditions for employees with diabetes, including depression, accounted for over 50% of excess risk of sickness absence [30]. A US study of a manufacturing company with 15,000 employees reported 13. 5 sick days per annum on average due to depression and physical comorbidity (diabetes, heart disease, hypertension or back problems) compared to 6. 6 and 8. 8 days for those with a physical condition or depression alone. Total mean costs, including healthcare and disability, per employee with comorbidity were USD 7,906. This is conservative as the costs of poor performance (presenteeism) at work were not included [31]. Data from the UK Survey also indicate that over a year individuals with diabetes and depression were 7. 7 and 5. 3 times more likely to take sick days and have their work and other activities impaired by poor health compared to people with diabetes alone [32]. The number of working days lost was also found to be significantly higher in people with comorbid diabetes and depression compared to diabetes alone in Singapore - 1. 9 versus 1. 4 working days lost over a 3-month period [19]. Strengthening the Case for Mental and 1. : Long-. of Co-Morbidities. London, The King's Fund, 2012. 2. : The size and burden of mental disorders and other disorders of the brain in Europe 2010. 2011;21:655-679. 3. : Outcomes of Nordic mental health systems: life expectancy of patients with mental disorders. Psychiatry 2011;199:453-458. 4. McDaid D, Park A-L, Currie C, Zanotti C: Investing in the wellbeing of young people: making the economic case; in (eds): Wellbeing: A Guide. of Wellbeing. Oxford, John Wiley, 2014, vol 5. 5. : The impact of obesity on health care costs among persons with schizophrenia. Psychiatry 2009;31:1-7. 6. : Healthcare spending among community-dwelling adults with schizophrenia. 2005; 11(8 suppl):S242-S247. 7. : Health outcomes and cost of care among older adults with schizophrenia: a 10-year study using medical records across the continuum of care. 2014;22:427-436. 8.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: We now turn to the case of KCH. We recall that this system has been developed to only support values of k smaller than 32. As for the case of k=28, we notice that FastKmer is about 20% faster than KCH when processing the 32GB dataset. This difference becomes even more significant when considering the 125GB dataset. Here, FastKmer is about two times faster than KCH. To explain this, consider that KCH aggregates k-mers in bins at a much coarser level and that it lacks a scheduling strategy able to ensure an even distribution of the workload among the nodes of the underlying distributed system. Scalability analysisIn this section, we present a scalability analysis, with respect to cluster scale and dataset sizes. After the preliminary analysis among the distributed framework, performed in the previous sections, we selected the best performing ones: FastKmer and KCH. Figure 5 shows the running time comparison of the two systems for various values of k (except for KCH, that supports only values up to k=31). From Fig. 5 we see that FastKmer outperforms KCH in terms of running time, for all number of workers. Fig. 5Running time comparison of FK and other k-mer counting algorithms for various values of k and an increasing number of workersFull size image For completeness, we also compared the performance of FastKmer and KCH to those of the fastest multi-threaded k-mers counting system, KMC3 [54], by running the latter on a single node using an increasing number of processing cores (up to 16 cores, the maximum available on a single nodes). From the results depicted in Fig. 5, KMC3 is the fastest system when using a small number of cores, whereas its execution time remains approximately the same for increasing number of workers. This is in line with the literature, as it has already been observed [16] that the performance of this system does not improve when considering a large number of cores. Overall, FastKmer outperforms previous approaches in terms of running time, showing to scale better for an increasing number of workers on both datasets and values of k. Profiling SparkTo conclude, we deepen the analysis on Spark performance overheads, reporting a breakdown of the execution times of FastKmer when run on the 32GB dataset using an increasing number of workers.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: , YPGly + GlcN agar plate). Intrinsic “specialist” yeast cells did not grow on this plate because of glucosamine-induced glucose repression, while “generalist” cells, utilizing glycerol, were observed around the paper disks containing kimoto lactic acid bacteria. Thus, lactic acid bacteria in the traditional sake making process play a role not only in the production of lactic acid to inhibit the growth of unwanted microorganisms, but also in the control of carbon metabolism of sake yeast. We also found that the effect varies in intensity depending on the type of yeast and lactic acid bacteria. Km67, which was isolated from a kimoto sake manufacturer (Takao et al. 2018), was more strongly affected by the lactic acid bacteria than Kyokai no. 701 (K701), a representative strain in modern sake making. Lentilactobacillus hilgardii, which is involved in sake spoilage and not considered a kimoto lactic acid bacteria, induced little carbon metabolic alteration in both K701 and Km67. These results suggest that the switching from the “specialist” to “generalist” mode is a microbial interaction specifically among the microorganisms coexisting in the kimoto-type sake making process. Figure 1. Carbon metabolic alteration of sake yeast by kimoto lactic acid bacteria. Sake yeast cells (upper, K701; lower, Km67) were spread on YPGly + GlcN agar plates, where only the “generalist” can form colonies. The growth phenotype was changed around the filter papers containing different strains of lactic acid bacteria. Open in new tabDownload slide Significance of cross-kingdom microbial interaction in sake making What is the biological significance of the mysterious cross-kingdom microbial interaction? This phenomenon was originally discovered in a growth environment in which glucose and non-glucose carbon sources are mixed (Jarosz et al. 2014a,b). Conventional microbiology often uses a simplified experimental condition in which glucose is the sole carbon source in culture media. In fact, however, such glucose-rich environments are rarely found in nature. In natural growth environments containing glucose and non-glucose carbon sources, the “specialist” yeast S. cerevisiae preferentially uses glucose.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: : Health and economic burden of metabolic comorbidity among individuals with bipolar disorder. J 2009;29:595-600. 9. : Treatment costs and health care utilization for patients with bipolar disorder in a large managed care population. 2008;11:416-423. 10. : Depression and costs of health care. Psychosomatics 2009;50:392-401. 11. : Healthcare costs in patients with diabetes mellitus and comorbid mental disorders - a systematic review. Diabetologia 2010;53:2470-2479. 12. : Economic aspects of the association between diabetes and depression: a systematic review. J 2012;142(suppl):S42-S55. 13. -: Treatment patterns and resource use among patients with comorbid diabetes mellitus and major depressive disorder. J 2011;14:440-447. 14. : Trends in health-related quality of life and health service use associated with comorbid diabetes and major depression in South Australia, 1998-2008. 2012;47:871-877. 15. : Diabetes complications and depression as predictors of health service costs. Psychiatry 2005;27:344-351. 16. : Impact of comorbid depression or anxiety on patterns of treatment and economic outcomes among patients with diabetic peripheral neuropathic pain. 2009;25:1763-1773. 17. : Healthcare costs associated with depression in medically Ill fee-for-service Medicare participants. J Soc 2009;57:506-510. 18. : Implications of comorbidity for primary care costs in the UK: a retrospective observational study. 2013;63:e274-e282. 19. : Comorbid depression and increased health care utilisation in individuals with diabetes. Psychiatry 2009;31:220-224. 20. : Comorbid depression is associated with increased healthcare utilization and lost productivity in persons with diabetes: a large nationally representative Hungarian population survey. 2009;71:501-507. 21. : Patterns of health services use and costs in patients with mental disorders in primary care (in Spanish). 2007;21:306-313. 22. of Physicians, of Psychiatrists: Smoking and Mental Health. London, of Physicians, 2013. 23. ünger J, Herzog W, Löwe B: Psychiatric comorbidity in cardiovascular inpatients: costs, net gain, and length of hospitalization.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The execution time of a Spark task can be broken down into (optional), Executor Runtime, Time (optional), Time and Time [55]. This information has been collected out of FastKmer runs by collecting the performance metrics readable from Logs (except for the Scheduler Delay, which has been calculated from other available metrics, following Spark UI code)Tables 3 and 4 contain task performance metrics for the two main stages of FastKmer (Fig. 1): the k-mers extraction phase (Stage 1) and the k-mer counting phase (Stage 2). The preliminary stages that implement the multiprocessor scheduling partitioning schemes have been omitted, as their compute time is negligible with respect to the overall processing, accounting only for a few seconds. Table 3 Running time breakdown, in seconds, of the two FastKmer stages on the 32GB dataset with k fixed to 28 and a decreasing number of executorsFull size tableTable 4 Running time breakdown, in seconds, of the two FastKmer stages on the 32GB dataset with k fixed to 55 and a decreasing number of executorsFull size table The metrics report, for each stage, the sum of average values for all tasks in groups of (#executors × #executor cores), over each round, up to the parallelism level. Unfortunately, the Time obtainable by the performance metrics is actually only the blocking time during the shuffle reads (also called Time), i. e. , the time a thread has to wait for another read to finish to acquire the lock on a shuffled block. The time to actually fetch the block from the shuffle source executor is included in the Time (which may be from disk, if the shuffle block cache spilled). No metric exists for the read time of a remote block during a shuffle read. For this reason, to give a sense of the overhead, we have also reported the local and remote size (in MB). For completeness, we have included the size as well. As can be clearly seen by the two tables, the performance metrics scale linearly with the number of workers. ConclusionsIt is worth to remark that the advantages of technologies like Hadoop or Spark for the analysis of big data come at a cost. A naive usage of these technologies may bring to solutions that, although being able to run on big data, are inefficient.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: The reduction of ethanol stress is a benefit to both yeast and the other coexisting microorganisms. Bacteria coexisting with yeast may promote symbiosis of the microbial ecosystem via delaying yeast alcohol fermentation. Figure 2. Fermentation tests using sake yeast “specialist” and “generalist” strains. (a), (b) Yeast strains were subjected to the fermentation tests using YPD20 medium. Carbon dioxide emission during alcoholic fermentation (a) and the percentages of dead cells after completion of alcoholic fermentation (b) were measured. (c) Possible significance of switching the carbon metabolic mode of sake yeast by kimoto lactic acid bacteria. Open in new tabDownload slideIn the traditional sake making process, lactic acid bacteria only exist in the early stage of the shubo yeast starter; they are killed by ethanol produced by yeast afterward. Thus, the “generalist” carbon metabolism of yeast may occur specifically in the yeast starter. In the subsequent fermentation of sake mash, where live lactic acid bacteria do not exist, the yeast can reverse into the “specialist” state. Here, it should be noted that the purposes of the shubo yeast starter and the sake mash are quite different despite the similar production process using rice, koji, and water. In the yeast starter, it is important to cultivate a large amount of yeast in a living state, and ethanol production is not the goal. Suppressing alcoholic fermentation by the “generalist” yeast through the action of lactic acid bacteria is beneficial to prevent the yeast cell death. In contrast, the key in sake mash is the efficiency of alcoholic fermentation. Since yeast is not used repeatedly in sake making, dead yeast cells after the end of fermentation are removed as part of the sake lees. The absence of viable lactic acid bacteria in sake mash provides benefits via returning yeast to the “specialist” mode. In the long history of sake making, mankind has optimized the two different steps to maximize the abilities of yeast and lactic acid bacteria. The shubo yeast starter provides the opportunity for microbial symbiosis between yeast and lactic acid bacteria, while the sake mash is the stage where yeast can reach the full potential of alcoholic fermentation. Thus, we have clarified why traditional sake making requires lactic acid bacteria from the viewpoint of microbial interactions.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: J 2011;70:135-139. 24. : Health care costs in persons with asthma and comorbid mental disorders: a systematic review. Psychiatry 2011;33:443-453. 25. : The effect of comorbid anxiety and depressive disorders on health care utilization and costs among adolescents with asthma. Psychiatry 2008;30:398-406. 26. : Indirect costs in patients with coronary artery disease and mental disorders: a systematic review and meta-analysis. 2012;25:319-329. 27. : Health-related productivity losses increase when the health condition is co-morbid with psychological distress: findings from a large cross-sectional sample of working Australians. BMC 2011;11:417. 28. O': Co-morbid depression is associated with poor work outcomes in persons with cardiovascular disease (CVD): a large, nationally representative survey in the Australian population. BMC 2012;12:47. 29. : Does co-morbid depressive illness magnify the impact of chronic physical illness? A population-based perspective. 2006;36:587-596. 30. Kivimäki : Increased sickness absence in diabetic employees: what is the role of co-morbid conditions? 2007;24:1043-1048. 31. : Health and disability costs of depressive illness in a major U. S. corporation. Psychiatry 2000;157:1274-1278. 32. Das-: Diabetes, common mental disorders, and disability: findings from the. 2007;69:543-550. 33. : Cost-effectiveness of a multicondition collaborative care intervention: a randomized controlled trial. Psychiatry 2012;69:506-514. 34. : Cost-effectiveness analysis of collaborative care management of major depression among low income, predominantly Hispanics with diabetes. 2012;15:249-254. 35. : Collaborative care for depression in individuals with type II diabetes; in (eds): Promotion and Prevention: Case. London, Department of Health, 2011. 36. : Examining the cost effectiveness of interventions to promote the physical health of people with mental health problems: a systematic review. BMC 2013;13:787. 37. McDaid D: Economic modelling for global mental health; in Thornicroft G, (eds): Health Trials. Oxford, Press, 2014. 38.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Berkeley: : 2011. p. 22. 2. 91. 2014. Preprint at Accessed 28 Nov 2018. -Grabysz A. KMC 2: fast and resource-frugal k-mer counting. Bioinformatics. 2015; 31(10):1569–76. 61. 2001. Laboratory LBN. kmernator. 2012. Accessed 28 Nov 2018. . Kmerind: A Library for K-mer Indexing of on Systems. New York: ACM; 2016. 33. . BioPig: a Hadoop-based analytic toolkit for large-scale sequence data. Bioinformatics. 2013; 29:3014–9. 2013. UCB/EECS-2013-207. . Reducing storage requirements for biological sequence comparison. Bioinformatics. 2004; 20(18):3363–9. 1576. 2016. Accessed 28 Nov 2018. . file format for sequences with quality scores, and the Solexa/variants. Res. 2010; 38(6):1767–71. 6. Saratoga: VLDB Endowment: 2013. p. 169–80. 0000. 2015; 31(10):1569–1576. 2004. . FASTdoop: a versatile and efficient library for the input of FASTA and FASTQ files for Mapbioinformatics applications. Bioinformatics. 2017; 33(10):1575–7. PubMed 7. 2018. Accessed 28 Nov 2018. Johnson DS. The NP-completeness column: an ongoing guide. J Algoritm. 1985; 6(3):434–51. 29. 61. CAS 15. Berkeley: : 2015. p. 293–307. 4. Author informationAuthor notesPetrillo and contributed equally to this work.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: It contributes directly to taste and flavour by the formation of peptides and free amino acids as well as by liberation of substrates for further catabolic changes and thereby formation of volatile flavour compounds. Besides sensory quality aspects of proteolysis, formation of bioactive peptides as a result of proteolysis during cheese ripening has been reported. Cheese contains phosphopeptides as natural constituents [16, 17], and secondary proteolysis during cheese ripening leads to the formation of other bioactive peptides, such as those with ACEI activity. The findings by Meisel et al. [18] showed that inhibitory activity increased as proteolysis developed, however, the bioactivity decreased when proteolysis during ripening exceeded a certain level. Another link between potential antihypertensive peptides and proteolysis was found in Parmesan cheese [19]. A bioactive peptide derived from αs1-casein was isolated from 6-month old cheese, but it was degraded further during maturation and was not detectable after 15 month of ripening. ACEI peptide fractions having different potencies have been isolated from various Italian cheeses, e. g. Crescenza (37% inhibition), mozzarella (59% inhibition), Gorgonzola (80% inhibition) and Italico (82% inhibition) [20]. ACEI peptides have also been found in enzyme-modified cheeses [21], in a low-fat cheese made in Finland [22] and Manchego cheeses manufactured with different starter cultures [23]. cheese manufactured with Enterococcus faecium or a L. lactis ssp. lactis-Enterococcus faecium mixture showed the largest number of fractions with ACEI activity among tested lactic acid strains [24]. Pripp et al. [25] investigated the relationship between proteolysis and ACE inhibition in and Kesam. The traditional Norwegian cheese Gamalost had per unit cheese weight higher ACE inhibition potential than Brie, Roquefort and Gouda-type cheese. However, ACE inhibition expressed as IC50 per unit peptide concentration from ethanol soluble fraction assessed by the OPA-assay was highest for Kesam, a Quark-type cheese with a low degree of proteolysis.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: Despite a 3- to 4-fold increase in the use of antidepressant medications, the prevalence of depression and anxiety disorders in Australia, Canada, the United Kingdom, and the has remained unchanged over the past 20 years. 1 In the absence of compelling evidence that the incidence of these disorders is on the rise, a natural conclusion is that depressed or anxious patients who could benefit from treatment are still not identified and treated, or that the duration of illness has remained unchanged in those who are treated. This is a striking and troubling finding, considering the known efficacy of antidepressants and psychotherapies. It emphasizes both a well-delineated treatment gap, whereby many patients with depression or anxiety do not receive treatment, and a quality gap whereby those who are treated either do not need to be treated or do not receive effective treatment. 2–7Several factors contribute to these gaps. Even knowledgeable and well-intentioned physicians face competing demands, including the need to concurrently address medical comorbidities and social determinants of health, making identification and management of common mental disorders challenging. ‘Usual care’ for these disorders requires both a patient-initiated encounter and the clinician’s subjective impression of the presence of a treatment-responsive condition, leading to delays in the initiation and titration of treatments,8,9 high treatment dropout rates, and low recovery rates. 5,10,11A better integration of the care provided by primary care providers and specialists has been advanced as one solution to improve access to care and the quality of the care delivered. 12–14 Integrated care encompasses models ranging from colocation (mental health providers delivering care within the primary care setting), to shared care (with increased coordination of care through provider-to-provider communication and shared health records), to the collaborative care model (CCM) (also known as ‘chronic care model’). 12,15–18 The CCM is a well-established and effective approach to both mental and physical disease management that includes several key elements: 1) team-based care that includes patients as active member of the treatment team and establishes patient-centred goals and care plans; 2) measurement-based care where patient-reported outcomes are monitored using rating scales and treatments are regularly adjusted to reach predefined targets (e. g.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Genomic data sampling and its effect on classification performance assessment 0. 01). The smallest numbers of train-test experiments allow the generation of the highest or most optimistic accuracy estimates. This method produced the lowest (most conservative) cross-validation accuracy estimates. Figure 2 shows that more than 1000 train-test runs are required to significantly reduce the variance of this cross-validation estimate. Again, the smallest numbers of train-test experiments generated the most optimistic accuracy estimates. The 95%–5% cross-validation method (Figure 3) requires more than 5000 train-test runs to reduce the variance of these estimates. This method produced the most optimistic cross-validation accuracy estimates. The leave-one-out method estimated the highest prediction accuracy for this classification problem (0. 81). The results generated by the bootstrap method are depicted in Figure 4. It indicates that more than 1000 train-test runs were required to achieve a confidence interval size equal to 0. 01. The bootstrap result originating from 1000 train-test runs is not significantly different than that produced by the 50%–50% cross-validation technique based on 1000 train-test runs. These results suggest that the estimation of high accuracy values may be associated with an increase of the size of the training datasets. Figure 1 Accuracy estimation for leukaemia data classifier (I) Cross-validation method based on a 50%–50% splitting. Prediction accuracy values and the confidence intervals for the means (95% confidence) are depicted for a number of train-test runs. A: 10 train-test runs, B: 25 train-test runs, C: 50 train-test runs, D: 100 train-test runs, E: 500 train-test runs, F: 1000 train-test runs, G: 2000 train-test runs, H: 3000 train-test runs, I: 4000 train-test runs, J: 5000 train-test runs. Full size image Figure 2 Accuracy estimation for leukaemia data classifier (II) Cross-validation method based on a 75%–25% splitting. Prediction accuracy values and the confidence intervals for the means (95% confidence) are depicted for a number of train-test runs.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: 123Cheddar (with probiotics)αs1-cn f(1-9)αs1-cn f(1-7)αs1-cn f(1-6)αs1-cn f(24-32)β-cn f(193-209)30Swiss cheese varietiesβ-cn, f(84–86)β-cn, f(74–76) and κ-cn, f(108–110)9531-34Fresco cheeseαs1-cn f(1-15)αs1-cn f(1-22)αs1-cn f(14-23)αs1-cn f(24-34)β-cn f(193-205)β-cn f(193-207)β-cn f(193-209)24Table 1. Examples of identified bioactive peptides in different cheese varieties2. 2. Fermented milkDuring fermentation process, lactic acid bacteria hydrolyze milk proteins, mainly caseins, into peptides and amino acids which are used as nitrogen sources necessary for their growth. Hence, bioactive peptides can be generated by starter and non-starter bacteria used in the manufacture of fermented dairy products (Table 2). Proteolytic system of Lb. helveticus, Lb. delbrueckii ssp bulgaricus, L. lactis ssp. diacetylactis, L. lactis ssp. cremoris, and Streptococcus (Str. ) salivarius ssp. thermophilus strains have demonstrated to hydrolyze milk proteins and release ACEI peptides. Among lactic acid bacteria, Lb. helveticus has high extracellular proteinase activity and the ability to release large amount of peptides in fermented milk. As a result, among various kinds of fermented milk, antihypertensive effect related to ACEI peptides were found in milk produced by Lb. helveticus. Two ACEI peptides have been purified from sour milk and identified as VPP and IPP [34]. OrganismsACE-inhibition Identified peptidesDoseResponse (Δ SBP mmHg)Ref. IC50 mg/mlSequenceIC50 µMLb. helveticus and Str.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: , a specific depression score corresponding to remission); 3) treatment selection and adjustments based on evidence (encapsulated in algorithms or care pathways) or, in the absence of evidence, expert opinion; and 4) population-based care whereby patients with a target condition are identified via systematic screening, tracked in a clinical registry, and reached proactively if they are disengaging from treatment. 19–21In primary care, where most common mental disorders are treated,14,22,23 more than 80 randomized controlled trials (RCTs) have shown that collaborative care is more effective than usual care to improve quality of care processes, clinical outcomes, patient and provider experience, health disparities, and cost-effectiveness. 24–27 A recent commentary on collaborative care suggested that further RCTs on collaborative care were unnecessary and possibly unethical given the existing body of evidence supporting its implementation. 28In this issue, 2 systematic reviews assess the evidence for integrated care in pediatric and geriatric patients. 29,30 Campo and colleagues29 highlight the early onset of many mental illnesses and the substantial quality gap in care for children and adolescents, which may portend poor outcomes, including suicide. They describe a wide array of pediatric mental health integrated care initiatives, including telephone consultations, education, colocation, and the CCM. They conclude that, in the pediatric population, integrated care approaches are more effective than usual care for depression, anxiety, and disruptive behaviour disorders but not substance use disorders. These approaches improve key clinical processes (such as treatment initiation or completion), clinical outcomes (such as response and remission), and patient and provider experience. Among the various integration initiatives reviewed, the CCM yields more robust and positive outcomes. The advent of the Patient’s Medical Home, a primary care reform initiative that provides comprehensive and accessible team-based primary care, amplifies opportunities for integration. Fortunately, the CCM ‘has powerfully influenced the conceptualization of the medical home’,29 emphasizing proactive and longitudinal care and the ‘incremental steps that produce sustained progress’. 31At the other end of the life span, Bruce and Sirey30 review integrated care interventions for older depressed patients. They point out the magnitude of the disease burden, as well as its impacts on caregivers, comorbid medical conditions, and mortality.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: A: 10 train-test runs, B: 25 train-test runs, C: 50 train-test runs, D: 100 train-test runs, E: 500 train-test runs, F: 1000 train-test runs, G: 2000 train-test runs, H: 3000 train-test runs, I: 4000 train-test runs, J: 5000 train-test runs. Full size image Figure 3 Accuracy estimation for leukaemia data classifier (III) Cross-validation method based on a 95%–5% splitting. Prediction accuracy values and the confidence intervals for the means (95% confidence) are depicted for a number of train-test runs. A: 10 train-test runs, B: 25 train-test runs, C: 50 train-test runs, D: 100 train-test runs, E: 500 train-test runs, F: 1000 train-test runs, G: 2000 train-test runs, H: 3000 train-test runs, I: 4000 train-test runs, J: 5000 train-test runs. Full size image Figure 4 Accuracy estimation for leukaemia data classifier (IV) Bootstrap method. Prediction accuracy values and the confidence intervals for the means (95% confidence) are depicted for a number of train-test runs. A: 100 train-test runs, B: 200 train-test runs, C: 300 train-test runs, D: 400 train-test runs, E: 500 train-test runs, F: 600 train-test runs, G: 700 train-test runs, H: 800 train-test runs, I: 900 train-test runs, J: 1000 train-test runs. Full size image Classification of expression patterns in data consisted of 88 cases categorised into four classes: Ewing family of tumors (EWS), rhabdomyosarcoma (RMS), Burkitt lymphomas (BL) and neuroblastomas (NB), which were represented by the expression values of 2308 genes with suspected roles in processes relevant to these tumors. and RMS contained 30, 11, 19 and 28 cases respectively. Principal component analysis was applied to reduce the dimensionality of the cases. As indicated in [6], the 10 dominant components per case were used to train the networks. The original datasets, experimental protocols and further analyses can be found in [6]. All of the networks were trained and tested using the same learning parameters.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: lactis ssp. cremoris, after fermentation of milk separately with each strain for 72 hours [36]. The most inhibitory fractions of the fermented milk mainly contained β-casein-derived peptides with inhibitory concentration (IC50) values ranging from 8. 0 to 11. 2 μg/ml. Fuglsang et al. [37] tested a total of 26 strains of wild-type lactic acid bacteria, mainly belonging to L. lactis and Lb. helveticus, for their ability to produce a milk fermentate with ACEI activity. All tested strains produced ACEI substances in varying amounts, and two of the strains exhibited high ACE inhibition and a high OPA index, which correlates well with peptide formation. In another study 25 lactic acid strains of Lactobacillus, Lactococccus and Leuconsotoc were used [38]. The strains were tested alone or in combination and the highest activities were observed in Lb. jensenii, Lb. acidophilus and Leuc. mesenteroides strains and all strains showed correlation between ACE inhibition and degree of proteolysis. In a recent study, milk was fermented to defined pH values with 13 strains of lactic acid bacteria. The highest ACEI activity was obtained with two highly proteolytic strains of Lb. helveticus and with the Lactococcus strains. Fermentation from pH 4. 6 to 4. 3 with these strains slightly increased the ACEI activity, whilst fermentation to pH 3. 5 with Lb. helveticus reduced the ACEI activity [39]. Moreover, four different Enterococcus faecalis strains, isolated from raw milk, produced fermented milk with potent ACEI activity [40]. In a recent research it was found that L. lactis strains isolated from artisanal dairy starters or commercial starter cultures are potential for the production of fermented dairy products with ACEI properties. Especially, a strain isolated from artisanal cheese presented the lowest IC50 (13µg/ml) [41]. Bioactive peptides isolated from skim milk and whey fermented using a range of organisms are summarized in Table 2. The majority of identified peptides are casein-derived ACEI peptides having IC50 values ranging from 5 to 500 µM.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: The high prevalence of geriatric depression in primary care, older patients’ preference for being treated by their primary care provider, and the shortage of geriatric psychiatrists are critical drivers for integration of depression care for older adults. The authors methodically lay out the varying evidence for different types of integration. -E study of colocated care included reduced wait times and structured communication between specialists and primary care providers, as well as showed improved acceptance of treatment but no difference in clinical outcomes. By contrast, the trial was a seminal collaborative care intervention, operationalized as a care manager offering brief psychological interventions, pharmacotherapy, and proactive patient monitoring using measurement-based care and a clinical registry, as well as on-site psychiatric expert input to guide stepwise depression care to target remission. intervention patients were more likely than usual-care patients to receive and continue treatment, achieve response and remission, and be satisfied with their care. Similarly, the collaborative care trial showed improved depression care and outcomes, including reduced suicidal ideation and long-term mortality. These and other studies of collaborative care have shown its impact not only on depressive symptoms but also on other outcomes important to patients, including physical health functioning, self-efficacy, and quality of life. Subsequent studies have also demonstrated the value of CCM for older patients with anxiety or Alzheimer disease or for those who are homebound. Greater effect sizes are observed with interventions in patients with more severe depression or with comorbid chronic physical illness, as well as in populations that commonly experience health disparities such as those with low socioeconomic status. Colocation of specialists in primary care is becoming more common in Canada, but colocation by itself is not enough to achieve improved outcomes. Despite 20 years of evidence supporting the effectiveness of the CCM, it has rarely been adopted in clinical settings. Both reviews discuss how this problem is perpetuated by knowledge gaps regarding what adaptations of the model may be less resource intensive and more scalable, as well as what supports and structures are needed to successfully implement collaborative care in the ‘real world’. Answering these questions will require study designs beyond RCTs: realist reviews, pragmatic trials, quasi-experimental or mixed-methods program evaluations, and rigorously evaluated quality improvement interventions. There are other barriers and challenges to implementation in Canada. Access and the Role of ReformPrimary care reform toward team-based models of care (e. g.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The BP-ANN architectures comprised 10 input nodes, 8 hidden nodes and 4 output nodes. Each output node encodes one of the tumor classes. Figures 5, 6 and 7 illustrate the prediction accuracy mean values and their confidence intervals (95% confidence) obtained for each cross-validation technique respectively. Figure 5 indicates that more than 500 train-test runs are required to achieve a confidence interval size equal to 0. 01 for this splitting method. The smallest numbers of train-test experiments allow the generation of the most optimistic accuracy estimates. However, in general this method produced the most conservative cross-validation accuracy estimates. Figure 6 shows that more than 1000 train-test runs are required to significantly reduce the variance of this cross-validation estimate. The 95%–5% cross-validation method (Figure 7) requires more than 5000 train-test runs to achieve the same. This method produced the most optimistic cross-validation accuracy estimates. The leave-one-out method produced the highest accuracy estimate for this dataset (0. 79). Figure 8 illustrates the results generated by the bootstrap method. In this situation more than 900 train-test runs were required to achieve a confidence interval size equal to 0. 01. These results also suggest that the estimation of high accuracy values may be linked to an increase of the size of the training datasets. Figure 5 Accuracy estimation for the SRBCT classifier (I) Cross-validation method based on a 50%–50% splitting. Prediction accuracy values and the confidence intervals for the means (95% confidence) are depicted for a number of train-test runs. A: 10 train-test runs, B: 25 train-test runs, C: 50 train-test runs, D: 100 train-test runs, E: 500 train-test runs, F: 1000 train-test runs, G: 2000 train-test runs, H: 3000 train-test runs, I: 4000 train-test runs, J: 5000 train-test runs. Full size image Figure 6 Accuracy estimation for the SRBCT classifier (II) Cross-validation method based on a 75%–25% splitting. Prediction accuracy values and the confidence intervals for the means (95% confidence) are depicted for a number of train-test runs.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: [44] identified two peptides in fermented milk with Enterococcus faecalis that corresponded to β -casein fragments Lys-His-Leu-Pro-Leu-Pro and Lys-Val-Tyr-Pro-Phe-Pro-Gly-Pro-Ile-Pro-ASn-Ser-Leu-Pro-Gln-Asn-Ile-Pro-Pro, with potent ACEI activity. Many kinds of proteolytic enzymes have been reported from lactic acid bacteria, and have been reviewed extensively [6, 45]. The components of the proteolytic systems of lactic acid bacteria are divided into three groups, including the extracellular proteinase that catalyzes casein breakdown to peptides, peptidases that hydrolyze peptides to amino acids and a peptide transport system. The extracellular proteinase activity was almost correlated with ACEI activity in the fermented milk, suggesting that the proteolysis of casein by the extracellular proteinase is the most important parameter in the processing of active components [46]. The importance of the proteinase was also supported by the fact that a proteinase negative mutant was not able to generate antihypertensive peptides in the fermented milk, whereas the wild-type strain had the ability to release strong antihypertensive peptides in the fermented milk [47]. The enzymatic process generating the antihypertensive peptides VPP and IPP in Lb. helveticus has been elucidated. By the proteolytic action of the extracellular proteinase long peptide with amino acid residue including VPP and IPP sequences were generated. Next the long peptide would be hydrolyzed to shorter peptides by intracellular peptidases. A key enzyme that can catalyze C-terminal processing of Val-Pro-Pro-Phe-Leu and Ile-Pro-Pro-Leu-Thr to VPP and IPP has been purified from Lb. helveticus CM4. The endopeptidase has sequence homology in amino terminal sequence to a previously reported pepO-gene product [48]. Kilpi et al. [49] found out higher ACE inhibition in milk fermentation using peptidase-deletion mutants compared to the wild-type of Lb. helveticus strain.

Output: corroborate


Input: Claim: Neuroscience can cure all mental health disorders. [SEP] Text: , the Patient’s Medical Home) is in variable but overall limited stages of progress. In Ontario, where primary care reform is relatively more advanced, Teams (FHTs) and Centres could provide expanded access, interdisciplinary care, and quality improvement. However, they care for less than a third of the provincial population, and their fidelity to the CCM components is highly variable. 32 Moreover, owing at least in part to financial disincentives, people with mental illness and addictions are underrepresented in FHTs, although they are among those who could benefit the most. 33,34 To better support CCM implementation, primary care reform will need to include appropriate adjustment of capitation funding models for case complexity and ensure that mental health is on the primary care quality improvement agenda. Finally, across the country, access to empirically supported psychotherapies remains poor. The promised federal investments in mental health care should consider the strategies that have been adopted in other countries such as England or Australia. 35Culture and the Need for ChampionsThese news ways of practicing require changes to the culture of health care delivery, roles, workflows, and competencies. 36–39 study (Across Minnesota—Directions) was the largest effort to scale collaborative care across an entire population. 40 failed to improve depression outcomes, but we can learn from the analysis of its implementation and of those who benefitted from it. The high referral rate to the study was attributable to several factors: strong clinical and managerial leadership support; perceptions of care manager abilities and ‘fit’; well-defined care manager role with adequate time, space, and support; care manager visibility and accessibility on site; and a strong primary care provider champion. 41 These findings resonate with our own experience with the implementation of the trial of telephone-based collaborative care for depression, anxiety, and alcohol use disorders. 42 They are echoed in Atul Gawande’s 1. Has increased provision of treatment reduced the prevalence of common mental disorders? Review of the evidence from four countries. World Psychiatry. 2017;16(1):90–99. CrossrefPubMed2. Jorm AF. The quality gap in mental health treatment in Australia. Z J Psychiatry. 2015;49(10):934–935. CrossrefPubMedWeb of Science3. Low-intensity treatment of depression in primary care: is it problematic? Psychiatry. 2000;22(2):78–83.

Output: contrast