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We investigate Lyα, [O iii] λ5007, Hα, and [C ii] 158 μm emission from 1124 galaxies at z = 4.9-7.0. Our sample is composed of 1092 Lyα emitters (LAEs) at z = 4.9, 5.7, 6.6, and 7.0 identified by Subaru/Hyper-Suprime-Cam (HSC) narrowband surveys covered by Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH) and 34 galaxies at z = 5.148-7.508 with deep ALMA [C ii] 158 μm data in the literature. Fluxes of strong rest-frame optical lines of [O iii] and Hα (Hβ) are constrained by significant excesses found in the SPLASH 3.6 and 4.5 μm photometry. At z = 4.9, we find that the rest-frame Hα equivalent width and the Lyα escape fraction f Lyα positively correlate with the rest-frame Lyα equivalent width fLyα positively correlate with the rest-frame Lyα equivalent width EWLyα0 . The correlation is similarly found at z ∼ 0-2, suggesting no evolution of the correlation over z ≃ 0-5. The typical ionizing photon production efficiency of LAEs is log(ξ ion/[Hz erg-1]) ≃ 25.5, significantly (60%-100%) higher than those of LBGs at a given UV magnitude. At z = 5.7-7.0, there exists an interesting turnover trend that the [O iii]/Hα flux ratio increases in and then decreases out to . We also identify an anticorrelation between a ratio of [C ii] luminosity to star formation rate (L [C ii]/SFR) and at the >99% confidence level.. We carefully investigate physical origins of the correlations with stellar-synthesis and photoionization models and find that a simple anticorrelation between and metallicity explains self-consistently all of the correlations of Lyα, Hα, [O iii]/Hα, and [C ii] identified in our study, indicating detections of metal-poor (∼0.03 Z o) galaxies with .

Most stars in today's Universe reside within spheroids, which are bulges of spiral galaxies and elliptical galaxies 1,2 . Their formation is still an unsolved problem 3-5 . Infrared/submillimetre-bright galaxies at high redshifts 6 have long been suspected to be related to spheroid formation 7-12 . Proving this connection has been hampered so far by heavy dust obscuration when focusing on their stellar emission 13-15 or by methodologies and limited signal-to-noise ratios when looking at submillimetre wavelengths 16,17 . Here we show that spheroids are directly generated by star formation within the cores of highly luminous starburst galaxies in the distant Universe. This follows from the ALMA submillimetre surface brightness profiles, which deviate substantially from those of exponential disks, and from the skewed-high axis-ratio distribution. Most of these galaxies are fully triaxial rather than flat disks: the ratio of the shortest to the longest of their three axes is half, on average, and increases with spatial compactness. These observations, supported by simulations, reveal a cosmologically relevant pathway for in situ spheroid formation through starbursts that is probably preferentially triggered by interactions (and mergers) acting on galaxies fed by non-coplanar gas accretion streams., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: A central goal of modern evidence-based medicine is the development of simple and easy to use tools that help clinicians integrate quantitative information into medical decision-making. The Bayesian Pre-test/Post-test Probability (BPP) framework is arguably the most well known of such tools and provides a formal approach to quantify diagnostic uncertainty given the result of a medical test or the presence of a clinical sign. Yet, clinical decision-making goes beyond quantifying diagnostic uncertainty and requires that that uncertainty be balanced against the various costs and benefits associated with each possible decision. Despite increasing attention in recent years, simple and flexible approaches to quantitative clinical decision-making have remained elusive., Methods: We extend the BPP framework using concepts of Bayesian Decision Theory. By integrating cost, we can expand the BPP framework to allow for clinical decision-making., Results: We develop a simple quantitative framework for binary clinical decisions (e.g., action/inaction, treat/no-treat, test/no-test). Let p be the pre-test or post-test probability that a patient has disease. We show that r ∗ = ( 1 - p ) / p represents a critical value called a decision boundary. In terms of the relative cost of under- to over-acting, r ∗ represents the critical value at which action and inaction are equally optimal. We demonstrate how this decision boundary can be used at the bedside through case studies and as a research tool through a reanalysis of a recent study which found widespread misestimation of pre-test and post-test probabilities among clinicians., Conclusions: Our approach is so simple that it should be thought of as a core, yet previously overlooked, part of the BPP framework. Unlike prior approaches to quantitative clinical decision-making, our approach requires little more than a hand-held calculator, is applicable in almost any setting where the BPP framework can be used, and excels in situations where the costs and benefits associated with a particular decision are patient-specific and difficult to quantify., (© 2024. The Author(s).)

The human gut teems with a diverse ecosystem of microbes, yet non-bacterial portions of that community are overlooked in studies of metabolic diseases firmly linked to gut bacteria. Type 2 diabetes mellitus (T2D) is associated with compositional shifts in the gut bacterial microbiome and the mycobiome, the fungal portion of the microbiome. However, whether T2D and/or metformin treatment underpins fungal community changes is unresolved. To differentiate these effects, we curated a gut mycobiome cohort spanning 1,000 human samples across five countries and validated our findings in a murine experimental model. We use Bayesian multinomial logistic normal models to show that T2D and metformin both associate with shifts in the relative abundance of distinct gut fungi. T2D is associated with shifts in the Saccharomycetes and Sordariomycetes fungal classes, while the genera Fusarium and Tetrapisipora most consistently associate with metformin treatment. We confirmed the impact of metformin on individual gut fungi by administering metformin to healthy mice. Thus, metformin and T2D account for subtle, but significant and distinct variation in the gut mycobiome across human populations. This work highlights for the first time that metformin can confound associations of gut fungi with T2D and warrants the need to consider pharmaceutical interventions in investigations of linkages between metabolic diseases and gut microbial inhabitants., Importance: This is the largest to-date multi-country cohort characterizing the human gut mycobiome, and the first to investigate potential perturbations in gut fungi from oral pharmaceutical treatment. We demonstrate the reproducible effects of metformin treatment on the human and murine gut mycobiome and highlight a need to consider metformin as a confounding factor in investigations between type 2 diabetes mellitus and the gut microbial ecosystem., Competing Interests: The authors declare no conflict of interest.

The prevalence of chronic, non-communicable diseases has risen sharply in recent decades, especially in industrialized countries. While several studies implicate the microbiome in this trend, few have examined the evolutionary history of industrialized microbiomes. Here we sampled 235 ancient dental calculus samples from individuals living in Great Britain (∼2200 BCE to 1853 CE), including 127 well-contextualized London adults. We reconstructed their microbial history spanning the transition to industrialization. After controlling for oral geography and technical biases, we identified multiple oral microbial communities that coexisted in Britain for millennia, including a community associated with Methanobrevibacter, an anaerobic Archaea not commonly prevalent in the oral microbiome of modern industrialized societies. Calculus analysis suggests that oral hygiene contributed to oral microbiome composition, while microbial functions reflected past differences in diet, specifically in dairy and carbohydrate consumption. In London samples, Methanobrevibacter-associated microbial communities are linked with skeletal markers of systemic diseases (for example, periostitis and joint pathologies), and their disappearance is consistent with temporal shifts, including the arrival of the Second Plague Pandemic. This suggests pre-industrialized microbiomes were more diverse than previously recognized, enhancing our understanding of chronic, non-communicable disease origins in industrialized populations., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

By applying Differential Set Analysis (DSA) to sequence count data, researchers can determine whether groups of microbes or genes are differentially enriched. Yet sequence count data suffer from a scale limitation: these data lack information about the scale (i.e., size) of the biological system under study, leading some authors to call these data compositional (i.e., proportional). In this article, we show that commonly used DSA methods that rely on normalization make strong, implicit assumptions about the unmeasured system scale. We show that even small errors in these scale assumptions can lead to positive predictive values as low as 9%. To address this problem, we take three novel approaches. First, we introduce a sensitivity analysis framework to identify when modeling results are robust to such errors and when they are suspect. Unlike standard benchmarking studies, this framework does not require ground-truth knowledge and can therefore be applied to both simulated and real data. Second, we introduce a statistical test that provably controls Type-I error at a nominal rate despite errors in scale assumptions. Finally, we discuss how the impact of scale limitations depends on a researcher's scientific goals and provide tools that researchers can use to evaluate whether their goals are at risk from erroneous scale assumptions. Overall, the goal of this article is to catalyze future research into the impact of scale limitations in analyses of sequence count data; to illustrate that scale limitations can lead to inferential errors in practice; yet to also show that rigorous and reproducible scale reliant inference is possible if done carefully., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 McGovern et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The detection of starlight from the host galaxies of quasars during the reionization epoch (z > 6) has been elusive, even with deep Hubble Space Telescope observations 1,2 . The current highest redshift quasar host detected 3 , at z = 4.5, required the magnifying effect of a foreground lensing galaxy. Low-luminosity quasars 4-6 from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) 7 mitigate the challenge of detecting their underlying, previously undetected host galaxies. Here we report rest-frame optical images and spectroscopy of two HSC-SSP quasars at z > 6 with the JWST. Using near-infrared camera imaging at 3.6 and 1.5 μm and subtracting the light from the unresolved quasars, we find that the host galaxies are massive (stellar masses of 13 × and 3.4 × 10 10  M ☉ , respectively), compact and disc-like. Near-infrared spectroscopy at medium resolution shows stellar absorption lines in the more massive quasar, confirming the detection of the host. Velocity-broadened gas in the vicinity of these quasars enables measurements of their black hole masses (1.4 × 10 9 and 2.0 × 10 8  M ☉ , respectively). Their location in the black hole mass-stellar mass plane is consistent with the distribution at low redshift, suggesting that the relation between black holes and their host galaxies was already in place less than a billion years after the Big Bang., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

G protein-coupled receptor (GPCR)-biased agonism, selective activation of certain signaling pathways relative to others, is thought to be directed by differential GPCR phosphorylation "barcodes." At chemokine receptors, endogenous chemokines can act as "biased agonists", which may contribute to the limited success when pharmacologically targeting these receptors. Here, mass spectrometry-based global phosphoproteomics revealed that CXCR3 chemokines generate different phosphorylation barcodes associated with differential transducer activation. Chemokine stimulation resulted in distinct changes throughout the kinome in global phosphoproteomics studies. Mutation of CXCR3 phosphosites altered β-arrestin 2 conformation in cellular assays and was consistent with conformational changes observed in molecular dynamics simulations. T cells expressing phosphorylation-deficient CXCR3 mutants resulted in agonist- and receptor-specific chemotactic profiles. Our results demonstrate that CXCR3 chemokines are non-redundant and act as biased agonists through differential encoding of phosphorylation barcodes, leading to distinct physiological processes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

We derive a simple asymptotic approximation for the long-run case fatality rate of COVID-19 (alpha and delta variants) and show that these estimations are highly correlated to the interaction between US State median age and projected US unemployment rate (Adj. r2 = 60%). We contrast this to the high level of correlation between point (instantaneous) estimates of per state case fatality rates and the interaction of median age, population density and current unemployment rates (Adj. r2 = 50.2%). To determine whether this is caused by a "race effect," we then analyze unemployment, race, median age and population density across US states and show that adding the interaction of African American population and unemployment explains 53.5% of the variance in COVID case fatality rates for the alpha and delta variants when considering instantaneous case fatality rate. Interestingly, when the asymptotic case fatality rate is used, the dependence on the African American population disappears, which is consistent with the fact that in the long-run COVID does not discriminate on race, but may discriminate on access to medical care which is highly correlated to employment in the US. The results provide further evidence of the impact inequality can have on case fatality rates in COVID-19 and the impact complex social, health and economic factors can have on patient survival., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Griffin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Broiler breeder hens, the parent stock of commercial broiler chickens, are genetically selected for rapid growth. Due to a longer production period and the focus of genetic selection on superior carcass traits in their progeny, these hens have the propensity to gain excess adipose tissue and exhibit severe ovarian dysfunction, a phenotype that is similar to human polycystic ovary syndrome (PCOS). Metformin is an antihyperglycemic drug approved for type 2 diabetes that is prescribed off-label for PCOS with benefits on metabolic and reproductive health. An additional effect of metformin treatments in humans is modulation of gut microbiome composition, hypothesized to benefit glucose sensitivity and systemic inflammation. The effects of dietary metformin supplementation in broiler breeder hens have not been investigated, thus we hypothesized that dietary metformin supplementation would alter the gut microbiome of broiler breeder hens. Broiler breeder hens were supplemented with metformin at four different levels (0, 25, 50, and 75 mg/kg body weight) from 25 to 65 weeks of age, and a subset of hens ( n = 8-10 per treatment group) was randomly selected to undergo longitudinal microbiome profiling with 16S rRNA sequencing. Metformin impacted the microbial community composition in 75 mg/kg metformin compared to controls (adjusted PERMANOVA p = 0.0006) and an additional dose-dependent difference was observed between 25 mg/kg and 75 mg/kg (adjusted PERMANOVA p = 0.001) and between 50 mg/kg and 75 mg/kg (adjusted PERMANOVA p = 0.001) but not between 25 mg/kg and 50 mg/kg (adjusted PERMANOVA p = 0.863). There were few differences in the microbiome attributed to hen age, and metformin supplementation did not alter alpha diversity. Bacteria that were identified as differentially relatively abundant between 75 mg/kg metformin treatment and the control, and between metformin doses, included Ruminococcus and members of the Clostridia family that have been previously identified in human trials of PCOS. These results demonstrate that metformin impacts the microbiome of broiler breeder hens in a dose-dependent manner and several findings were consistent with PCOS in humans and with metformin treatment in type 2 diabetes. Metformin supplementation is a potentially promising option to improve gut health and reproductive efficiency in broiler breeder hens., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Van Syoc, Weaver, Rogers, Silverman, Ramachandran and Ganda.)

Sensory processing in olfactory systems is organized across olfactory bulb glomeruli, wherein axons of peripheral sensory neurons expressing the same olfactory receptor co-terminate to transmit receptor-specific activity to central neurons. Understanding how receptors map to glomeruli is therefore critical to understanding olfaction. High-throughput spatial transcriptomics is a rapidly advancing field, but low-abundance olfactory receptor expression within glomeruli has previously precluded high-throughput mapping of receptors to glomeruli in the mouse. Here we combined sequential sectioning along the anteroposterior, dorsoventral, and mediolateral axes with target capture enrichment sequencing to overcome low-abundance target expression. This strategy allowed us to spatially map 86% of olfactory receptors across the olfactory bulb and uncover a relationship between OR sequence and glomerular position., (© 2022. The Author(s).)

Background: Short-chain fatty acids (SCFAs) derived from gut bacteria are associated with protective roles in diseases ranging from obesity to colorectal cancers. Intake of microbially accessible dietary fibers (prebiotics) lead to varying effects on SCFA production in human studies, and gut microbial responses to nutritional interventions vary by individual. It is therefore possible that prebiotic therapies will require customizing to individuals., Results: Here, we explored prebiotic personalization by conducting a three-way crossover study of three prebiotic treatments in healthy adults. We found that within individuals, metabolic responses were correlated across the three prebiotics. Individual identity, rather than prebiotic choice, was also the major determinant of SCFA response. Across individuals, prebiotic response was inversely related to basal fecal SCFA concentration, which, in turn, was associated with habitual fiber intake. Experimental measures of gut microbial SCFA production for each participant also negatively correlated with fiber consumption, supporting a model in which individuals' gut microbiota are limited in their overall capacity to produce fecal SCFAs from fiber., Conclusions: Our findings support developing personalized prebiotic regimens that focus on selecting individuals who stand to benefit, and that such individuals are likely to be deficient in fiber intake. Video Abstract., (© 2022. The Author(s).)

Background: Spinal cord injury (SCI) has a significant impact on motor control and active force generation. Quantifying muscle activation following SCI may help indicate the degree of motor impairment and predict the efficacy of rehabilitative interventions. In healthy persons, muscle activation is typically quantified by electromyographic (EMG) signal amplitude measures. However, in SCI, these measures may not reflect voluntary effort, and therefore other nonamplitude-based features should be considered. Objectives: The purpose of this study was to assess the correlation of time-domain EMG features with the exerted joint torque (validity) and their test-retest repeatability (reliability), which may contribute to characterizing muscle activation following SCI. Methods: Surface EMG (SEMG) and torque were measured while nine uninjured participants and four participants with SCI performed isometric contractions of tibialis anterior (TA) and soleus (SOL). Data collection was repeated at a subsequent session for comparison across days. Validity and test-retest reliability of features were assessed by Spearman and intraclass correlation (ICC) of linear regression coefficients. Results: In healthy participants, SEMG features correlated well with torque (TA: ρ > 0.92; SOL: ρ > 0.94) and showed high reliability (ICC mean = 0.90; range, 0.72-0.99). In an SCI case series, SEMG features also correlated well with torque (TA: ρ > 0.86; SOL: ρ > 0.86), and time-domain features appeared no less repeatable than amplitude-based measures. Conclusion: Time-domain SEMG features are valid and reliable measures of lower extremity muscle activity in healthy participants and may be valid measures of sublesional muscle activity following SCI. These features could be used to gauge motor impairment and progression of rehabilitative interventions or in controlling assistive technologies., Competing Interests: Conflicts of Interest The authors report no conflicts of interest., (© 2021 American Spinal Injury Association.)

PCR amplification plays an integral role in the measurement of mixed microbial communities via high-throughput DNA sequencing of the 16S ribosomal RNA (rRNA) gene. Yet PCR is also known to introduce multiple forms of bias in 16S rRNA studies. Here we present a paired modeling and experimental approach to characterize and mitigate PCR NPM-bias (PCR bias from non-primer-mismatch sources) in microbiota surveys. We use experimental data from mock bacterial communities to validate our approach and human gut microbiota samples to characterize PCR NPM-bias under real-world conditions. Our results suggest that PCR NPM-bias can skew estimates of microbial relative abundances by a factor of 4 or more, but that this bias can be mitigated using log-ratio linear models., Competing Interests: The authors have declared that no competing interests exist.

Untargeted sequencing of nucleic acids present in food can inform the detection of food safety and origin, as well as product tampering and mislabeling issues. The application of such technologies to food analysis may reveal valuable insights that are simply unobtainable by targeted testing, leading to the efforts of applying such technologies in the food industry. However, before these approaches can be applied, it is imperative to verify that the most appropriate methods are used at every step of the process: gathering of primary material, laboratory methods, data analysis, and interpretation. The focus of this study is on gathering the primary material, in this case, DNA. We used bovine milk as a model to (i) evaluate commercially available kits for their ability to extract nucleic acids from inoculated bovine milk, (ii) evaluate host DNA depletion methods for use with milk, and (iii) develop and evaluate a selective lysis-propidium monoazide (PMA)-based protocol for host DNA depletion in milk. Our results suggest that magnetically based nucleic acid extraction methods are best for nucleic acid isolation of bovine milk. Removal of host DNA remains a challenge for untargeted sequencing of milk, highlighting the finding that the individual matrix characteristics should always be considered in food testing. Some reported methods introduce bias against specific types of microbes, which may be particularly problematic in food safety, where the detection of Gram-negative pathogens and hygiene indicators is essential. Continuous efforts are needed to develop and validate new approaches for untargeted metagenomics in samples with large amounts of DNA from a single host. IMPORTANCE Tracking the bacterial communities present in our food has the potential to inform food safety and product origin. To do so, the entire genetic material present in a sample is extracted using chemical methods or commercially available kits and sequenced using next-generation platforms to provide a snapshot of the microbial composition. Because the genetic material of higher organisms present in food (e.g., cow in milk or beef, wheat in flour) is around 1,000 times larger than the bacterial content, challenges exist in gathering the information of interest. Additionally, specific bacterial characteristics can make them easier or harder to detect, adding another layer of complexity to this issue. In this study, we demonstrate the impact of using different methods for the ability to detect specific bacteria and highlight the need to ensure that the most appropriate methods are being used for each particular sample.

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in September 2020 and is rapidly spreading toward fixation. Using a variety of statistical and dynamic modeling approaches, we estimate that this variant has a 43 to 90% (range of 95% credible intervals, 38 to 130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine rollout, COVID-19 hospitalizations and deaths across England in the first 6 months of 2021 were projected to exceed those in 2020. VOC 202012/01 has spread globally and exhibits a similar transmission increase (59 to 74%) in Denmark, Switzerland, and the United States., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Genomic studies feature multivariate count data from high-throughput DNA sequencing experiments, which often contain many zero values. These zeros can cause artifacts for statistical analyses and multiple modeling approaches have been developed in response. Here, we apply different zero-handling models to gene-expression and microbiome datasets and show models can disagree substantially in terms of identifying the most differentially expressed sequences. Next, to rationally examine how different zero handling models behave, we developed a conceptual framework outlining four types of processes that may give rise to zero values in sequence count data. Last, we performed simulations to test how zero handling models behave in the presence of these different zero generating processes. Our simulations showed that simple count models are sufficient across multiple processes, even when the true underlying process is unknown. On the other hand, a common zero handling technique known as "zero-inflation" was only suitable under a zero generating process associated with an unlikely set of biological and experimental conditions. In concert, our work here suggests several specific guidelines for developing and choosing state-of-the-art models for analyzing sparse sequence count data., (© 2020 The Author(s).)

Pediatric obesity remains a public health burden and continues to increase in prevalence. The gut microbiota plays a causal role in obesity and is a promising therapeutic target. Specifically, the microbial production of short-chain fatty acids (SCFA) from the fermentation of otherwise indigestible dietary carbohydrates may protect against pediatric obesity and metabolic syndrome. Still, it has not been demonstrated that therapies involving microbiota-targeting carbohydrates, known as prebiotics, will enhance gut bacterial SCFA production in children and adolescents with obesity (age, 10 to 18 years old). Here, we used an in vitro system to examine the SCFA production by fecal microbiota from 17 children with obesity when exposed to five different commercially available over-the-counter (OTC) prebiotic supplements. We found microbiota from all 17 patients actively metabolized most prebiotics. Still, supplements varied in their acidogenic potential. Significant interdonor variation also existed in SCFA production, which 16S rRNA sequencing supported as being associated with differences in the host microbiota composition. Last, we found that neither fecal SCFA concentration, microbiota SCFA production capacity, nor markers of obesity positively correlated with one another. Together, these in vitro findings suggest the hypothesis that OTC prebiotic supplements may be unequal in their ability to stimulate SCFA production in children and adolescents with obesity and that the most acidogenic prebiotic may differ across individuals. IMPORTANCE Pediatric obesity remains a major public health problem in the United States, where 17% of children and adolescents are obese, and rates of pediatric "severe obesity" are increasing. Children and adolescents with obesity face higher health risks, and noninvasive therapies for pediatric obesity often have limited success. The human gut microbiome has been implicated in adult obesity, and microbiota-directed therapies can aid weight loss in adults with obesity. However, less is known about the microbiome in pediatric obesity, and microbiota-directed therapies are understudied in children and adolescents. Our research has two important findings: (i) dietary prebiotics (fiber) result in the microbiota from adolescents with obesity producing more SCFA, and (ii) the effectiveness of each prebiotic is donor dependent. Together, these findings suggest that prebiotic supplements could help children and adolescents with obesity, but that these therapies may not be "one size fits all.", (Copyright © 2020 Holmes et al.)

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections to date has relied heavily on reverse transcription polymerase chain reaction testing. However, limited test availability, high false-negative rates, and the existence of asymptomatic or subclinical infections have resulted in an undercounting of the true prevalence of SARS-CoV-2. Here, we show how influenza-like illness (ILI) outpatient surveillance data can be used to estimate the prevalence of SARS-CoV-2. We found a surge of non-influenza ILI above the seasonal average in March 2020 and showed that this surge correlated with coronavirus disease 2019 (COVID-19) case counts across states. If one-third of patients infected with SARS-CoV-2 in the United States sought care, this ILI surge would have corresponded to more than 8.7 million new SARS-CoV-2 infections across the United States during the 3-week period from 8 to 28 March 2020. Combining excess ILI counts with the date of onset of community transmission in the United States, we also show that the early epidemic in the United States was unlikely to have been doubling slower than every 4 days. Together, these results suggest a conceptual model for the COVID-19 epidemic in the United States characterized by rapid spread across the United States with more than 80% infected individuals remaining undetected. We emphasize the importance of testing these findings with seroprevalence data and discuss the broader potential to use syndromic surveillance for early detection and understanding of emerging infectious diseases., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).)

Culture and screening of gut bacteria enable testing of microbial function and therapeutic potential. However, the diversity of human gut microbial communities (microbiota) impedes comprehensive experimental studies of individual bacterial taxa. Here, we combine advances in droplet microfluidics and high-throughput DNA sequencing to develop a platform for separating and assaying growth of microbiota members in picoliter droplets (MicDrop). MicDrop enabled us to cultivate 2.8 times more bacterial taxa than typical batch culture methods. We then used MicDrop to test whether individuals possess similar abundances of carbohydrate-degrading gut bacteria, using an approach which had previously not been possible due to throughput limitations of traditional bacterial culture techniques. Single MicDrop experiments allowed us to characterize carbohydrate utilization among dozens of gut bacterial taxa from distinct human stool samples. Our aggregate data across nine healthy stool donors revealed that all of the individuals harbored gut bacterial species capable of degrading common dietary polysaccharides. However, the levels of richness and abundance of polysaccharide-degrading species relative to monosaccharide-consuming taxa differed by up to 2.6-fold and 24.7-fold, respectively. Additionally, our unique dataset suggested that gut bacterial taxa may be broadly categorized by whether they can grow on single or multiple polysaccharides, and we found that this lifestyle trait is correlated with how broadly bacterial taxa can be found across individuals. This demonstration shows that it is feasible to measure the function of hundreds of bacterial taxa across multiple fecal samples from different people, which should in turn enable future efforts to design microbiota-directed therapies and yield new insights into microbiota ecology and evolution. IMPORTANCE Bacterial culture and assay are components of basic microbiological research, drug development, and diagnostic screening. However, community diversity can make it challenging to comprehensively perform experiments involving individual microbiota members. Here, we present a new microfluidic culture platform that makes it feasible to measure the growth and function of microbiota constituents in a single set of experiments. As a proof of concept, we demonstrate how the platform can be used to measure how hundreds of gut bacterial taxa drawn from different people metabolize dietary carbohydrates. Going forward, we expect this microfluidic technique to be adaptable to a range of other microbial assay needs., (Copyright © 2020 Villa et al.)

Given the highly dynamic and complex nature of the human gut microbial community, the ability to identify and predict time-dependent compositional patterns of microbes is crucial to our understanding of the structure and functions of this ecosystem. One factor that could affect such time-dependent patterns is microbial interactions, wherein community composition at a given time point affects the microbial composition at a later time point. However, the field has not yet settled on the degree of this effect. Specifically, it has been recently suggested that only a minority of taxa depend on the microbial composition in earlier times. To address the issue of identifying and predicting temporal microbial patterns we developed a new model, MTV-LMM (Microbial Temporal Variability Linear Mixed Model), a linear mixed model for the prediction of microbial community temporal dynamics. MTV-LMM can identify time-dependent microbes (i.e., microbes whose abundance can be predicted based on the previous microbial composition) in longitudinal studies, which can then be used to analyze the trajectory of the microbiome over time. We evaluated the performance of MTV-LMM on real and synthetic time series datasets, and found that MTV-LMM outperforms commonly used methods for microbiome time series modeling. Particularly, we demonstrate that the effect of the microbial composition in previous time points on the abundance of taxa at later time points is underestimated by a factor of at least 10 when applying previous approaches. Using MTV-LMM, we demonstrate that a considerable portion of the human gut microbiome, both in infants and adults, has a significant time-dependent component that can be predicted based on microbiome composition in earlier time points. This suggests that microbiome composition at a given time point is a major factor in defining future microbiome composition and that this phenomenon is considerably more common than previously reported for the human gut microbiome., Competing Interests: The authors have declared that no competing interests exist.

AbstractFollowing publication of the original article [1], the authors noticed an error in the presentation of equations in the PDF version.

Background: Artificial gut models provide unique opportunities to study human-associated microbiota. Outstanding questions for these models' fundamental biology include the timescales on which microbiota vary and the factors that drive such change. Answering these questions though requires overcoming analytical obstacles like estimating the effects of technical variation on observed microbiota dynamics, as well as the lack of appropriate benchmark datasets., Results: To address these obstacles, we created a modeling framework based on multinomial logistic-normal dynamic linear models (MALLARDs) and performed dense longitudinal sampling of four replicate artificial human guts over the course of 1 month. The resulting analyses revealed how the ratio of biological variation to technical variation from sample processing depends on sampling frequency. In particular, we find that at hourly sampling frequencies, 76% of observed variation could be ascribed to technical sources, which could also skew the observed covariation between taxa. We also found that the artificial guts demonstrated replicable trajectories even after a recovery from a transient feed disruption. Additionally, we observed irregular sub-daily oscillatory dynamics associated with the bacterial family Enterobacteriaceae within all four replicate vessels., Conclusions: Our analyses suggest that, beyond variation due to sequence counting, technical variation from sample processing can obscure temporal variation from biological sources in artificial gut studies. Our analyses also supported hypotheses that human gut microbiota fluctuates on sub-daily timescales in the absence of a host and that microbiota can follow replicable trajectories in the presence of environmental driving forces. Finally, multiple aspects of our approach are generalizable and could ultimately be used to facilitate the design and analysis of longitudinal microbiota studies in vivo.

Background: Cholera is a public health problem worldwide, and the risk factors for infection are only partially understood., Methods: We prospectively studied household contacts of patients with cholera to compare those who were infected to those who were not. We constructed predictive machine learning models of susceptibility, using baseline gut microbiota data. We identified bacterial taxa associated with susceptibility to Vibrio cholerae infection and tested these taxa for interactions with V. cholerae in vitro., Results: We found that machine learning models based on gut microbiota, as well as models based on known clinical and epidemiological risk factors, predicted V. cholerae infection. A predictive gut microbiota of roughly 100 bacterial taxa discriminated between contacts who developed infection and those who did not. Susceptibility to cholera was associated with depleted levels of microbes from the phylum Bacteroidetes. By contrast, a microbe associated with cholera by our modeling framework, Paracoccus aminovorans, promoted the in vitro growth of V. cholerae. Gut microbiota structure, clinical outcome, and age were also linked., Conclusion: These findings support the hypothesis that abnormal gut microbial communities are a host factor related to V. cholerae susceptibility.

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

Marker gene sequencing of microbial communities has generated big datasets of microbial relative abundances varying across environmental conditions, sample sites and treatments. These data often come with putative phylogenies, providing unique opportunities to investigate how shared evolutionary history affects microbial abundance patterns. Here, we present a method to identify the phylogenetic factors driving patterns in microbial community composition. We use the method, "phylofactorization," to re-analyze datasets from the human body and soil microbial communities, demonstrating how phylofactorization is a dimensionality-reducing tool, an ordination-visualization tool, and an inferential tool for identifying edges in the phylogeny along which putative functional ecological traits may have arisen., Competing Interests: The authors declare there are no competing interests.

Objective: Pedestrian and cyclist collisions comprise a significant proportion of preventable injury. In urban settings, collision rates have been linked to various socio-demographic factors. We sought to determine whether neighbourhood marginalization affects pedestrian and cyclist collisions in the Greater Toronto Area., Methods: For 114 intersections, pedestrian and cyclist collisions were extracted from the Toronto Traffic Data Centre database. We used a geographic information system approach to determine census Dissemination Areas and an associated Ontario Marginalization Index (ON-Marg) for each intersection. We performed a logistic regression to examine the associations between the four ON-Marg dimensions (residential instability, material deprivation, dependency, ethnic concentration) and pedestrian and cyclist collisions., Results: The odds of sustaining a collision were independently associated with residential instability for both pedestrians (OR 1.84, 95% CI 1.21-2.84, p=0.006) and cyclists (OR 2.04, 95% CI 1.34-3.16, p=0.001). Higher overall collision rates (both pedestrian and cyclist) were associated with both ethnic concentration (OR 1.56, 95% CI 1.05-2.37, p=0.033) and residential instability (OR 2.16, 95% CI 1.43-3.38, p=0.001). Material deprivation and dependency were not significant risk factors for intersection collisions in this model., Conclusions: Collisions involving pedestrians and cyclists are more common in areas of increased residential instability and ethnic concentration in Toronto. Intersections in neighbourhoods with these characteristics could be targeted for strategies to reduce pedestrian and cyclist injury risk in urban settings.

Objective: To determine the utility of a novel Paediatric Consultation Assessment Tool (PCAT)., Design: Developed to measure clinicians' communication behaviour with children and their parents/guardian, PCAT was designed according to consensus guidelines and refined at a number of stages. Volunteer clinicians provided videotaped real consultations. Assessors were trained to score communication skills using PCAT, a novel rating scale., Setting: Eight UK paediatric units., Participants: 19 paediatricians collected video-recorded material; a second cohort of 17 clinicians rated the videos., Main Outcome Measures: Itemised and aggregated scores were analysed (means and 95% confidence intervals) to determine measurement characteristics and relationship to patient, consultation, clinician and assessor attributes; generalisability coefficient of aggregate score; factor analysis of items; comparison of scores between groups of patients, consultations, clinicians and assessors., Results: 188 complete consultations were analysed (median per doctor = 10). 3 videos marked by any trained assessor are needed to reliably (r > 0.8) assess a doctor's triadic consultation skills using PCAT, 4 to assess communication with just children or parents. Performance maps to two factors - "clinical skills" and "communication behaviour"; clinicians score more highly on the former (mean (SD) 95% CI 0.52 (0.075)). There were significant differences in scores for the same skills applied to parent and child, especially between the ages of 2 and 10 years, and for information-sharing rather than relationship building skills (2-tailed significance < 0.001). Conclusions The PCAT appears to be reliable, valid and feasible for the assessment of triadic consultation skills by direct observation.

Objective: To determine the utility of a novel Paediatric Consultation Assessment Tool (PCAT)., Design: Developed to measure clinicians' communication behaviour with children and their parents/guardian, PCAT was designed according to consensus guidelines and refined at a number of stages. Volunteer clinicians provided videotaped real consultations. Assessors were trained to score communication skills using PCAT, a novel rating scale., Setting: Eight UK paediatric units., Participants: 19 paediatricians collected video-recorded material; a second cohort of 17 clinicians rated the videos., Main Outcome Measures: Itemised and aggregated scores were analysed (means and 95% confidence intervals) to determine measurement characteristics and relationship to patient, consultation, clinician and assessor attributes; generalisability coefficient of aggregate score; factor analysis of items; comparison of scores between groups of patients, consultations, clinicians and assessors., Results: 188 complete consultations were analysed (median per doctor = 10). 3 videos marked by any trained assessor are needed to reliably (r>0.8) assess a doctor's triadic consultation skills using PCAT, 4 to assess communication with just children or parents. Performance maps to two factors--"clinical skills" and "communication behaviour"; clinicians score more highly on the former (mean (SD) 95% CI 0.52 (0.075)). There were significant differences in scores for the same skills applied to parent and child, especially between the ages of 2 and 10 years, and for information-sharing rather than relationship-building skills (2-tailed significance <0.001)., Conclusions: The PCAT appears to be reliable, valid and feasible for the assessment of triadic consultation skills by direct observation.

Low-dose imaging protocols in chest CT are important in the screening and surveillance of suspicious and indeterminate lung nodules. Techniques that maintain nodule detectability yet permit dose reduction, particularly for large body habitus, were investigated. The objective of this study was to determine the extent to which radiation dose can be minimized while maintaining diagnostic performance through knowledgeable selection of reconstruction techniques. A 320-slice volumetric CT scanner (Aquilion ONE, Toshiba Medical Systems) was used to scan an anthropomorphic phantom at doses ranging from approximately 0.1 mGy up to that typical of low-dose CT (LDCT, approximately 5 mGy) and diagnostic CT (approximately 10 mGy). Radiation dose was measured via Farmer chamber and MOSFET dosimetry. The phantom presented simulated nodules of varying size and contrast within a heterogeneous background, and chest thickness was varied through addition of tissue-equivalent bolus about the chest. Detectability of a small solid lung nodule (3.2 mm diameter, -37 HU, typically the smallest nodule of clinical significance in screening and surveillance) was evaluated as a function of dose, patient size, reconstruction filter, and slice thickness by means of nine-alternative forced-choice (9AFC) observer tests to quantify nodule detectability. For a given reconstruction filter, nodule detectability decreased sharply below a threshold dose level due to increased image noise, especially for large body size. However, nodule detectability could be maintained at lower doses through knowledgeable selection of (smoother) reconstruction filters. For large body habitus, optimal filter selection reduced the dose required for nodule detection by up to a factor of approximately 3 (from approximately 3.3 mGy for sharp filters to approximately 1.0 mGy for the optimal filter). The results indicate that radiation dose can be reduced below the current low-dose (5 mGy) and ultralow-dose (1 mGy) levels with knowledgeable selection of reconstruction parameters. Image noise, not spatial resolution, was found to be the limiting factor in detection of small lung nodules. Therefore, the use of smoother reconstruction filters may permit lower-dose protocols without trade-off in diagnostic performance.

Effective consultations with patients and their families are important for patient satisfaction, adherence to treatment, and recovery from illness. Communication problems among health professionals are common. Fortunately, the skills of effective communication can be taught and learned. This paper highlights evidence based approaches to teaching these skills with minimal resources.

The mitotic spindle has long been recognized to play an essential role in determining the position of the cleavage furrow during cell division, however little is known about the mechanisms involved in this process. One attractive hypothesis is that signals from the spindle may function to induce reorganization of cortical structures and transport of actin filaments to the equator during cytokinesis. While an important idea, few experiments have directly tested this model. In the present study, we have used a variety of experimental approaches to identify microtubule-dependent effects on key cortical events during normal cell cleavage, including cortical flow, reorientation of actin filaments, and formation of the contractile apparatus. Single-particle tracking experiments showed that the microtubule disrupting drug nocodazole induces an inhibition of the movements of cell surface receptors following anaphase onset, while the microtubule stabilizing drug taxol causes profound changes in the overall pattern of receptor movements. These effects were accompanied by a related set of changes in the organization of the actin cytoskeleton. In nocodazole-treated cells, the three-dimensional organization of cortical actin filaments appeared less ordered than in controls. Measurements with fluorescence-detected linear dichroism indicated a decrease in the alignment of filaments along the spindle axis. In contrast, actin filaments in taxol-treated cells showed an increased alignment along the equator on both the ventral and dorsal cortical surfaces, mirroring the redistribution pattern of surface receptors. Together, these experiments show that spindle microtubules are involved in directing bipolar flow of surface receptors and reorganization of actin filaments during cell division, thus acting as a stimulus for positioning cortical cytoskeletal components and organizing the contractile apparatus of dividing tissue culture cells.

Effective communication between doctor and patient is a core clinical skill. It is increasingly recognized that it should and can be taught with the same rigour as other basic medical sciences. To validate this teaching, it is important to define the content of communication training programmes by stating clearly what is to be learnt. We therefore describe a practical teaching tool, the Calgary-Cambridge Referenced Observation Guides, that delineates and structures the skills which aid doctor-patient communication. We provide detailed references to substantiate the research and theoretical basis of these individual skills. The guides form the foundation of a sound communication curriculum and are offered as a starting point for programme directors, facilitators and learners at all levels. We describe how these guides can also be used on an everyday basis to help facilitators teach and students learn within the experiential methodology that has been shown to be central to communication training. The learner-centred and opportunistic approach used in communication teaching makes it difficult for learners to piece together their evolving understanding of communication. The guides give practical help in countering this problem by providing: an easily accessible aide-mémoire; a recording instrument that makes feedback more systematic; and an overall conceptual framework within which to organize the numerous skills that are discovered one by one as the communication curriculum unfolds.

We have used fluorescent latex beads to label membrane receptors on cultured NRK cells. Movement of individual beads during cell division was recorded with digital imaging techniques. Surface-bound beads showed no organized movement during metaphase but started to migrate toward the equator approximately 1 min after anaphase onset, when chromosomes moved out of the equatorial region to create the interzone. The movement was most active in the central region of the cell near separating chromosomes, while beads located near the poles of the cell underwent primarily random motion. Most beads showed a surge in speed upon the passage of chromosomes, suggesting a possible link between chromosome separation and cortical reorganization. Furthermore, treatment of anaphase cells with cytochalasin D induced a rapid, simultaneous collapse of beads and cortical actin filaments into aggregates, indicating that the movement of beads was closely related to the reorganization of the actin cortex. In contrast to normal directional movement, cytochalasin-induced movement occurred in random directions and caused some beads in the equatorial region to move toward poles. Our results indicate that cytokinesis involves contractile activities, not only along the equator, but over a wide area of the actin-containing cortex. In addition, organized cortical activities appear to be temporally activated at anaphase onset, and spatially modulated by the spindle interzone or separating chromosomes.