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In 2020, Science, Technology, Engineering and Math (STEM) faculty within a United Kingdom university implemented an online personal tutoring model. This model aimed to deliver a consistent experience to ~1000 students, supporting learning and fostering a sense of belonging during a global pandemic. Here we describe and evaluate a Curriculum Integrated personal tutor model, designed to provide a structured and dialogic student experience. We provide details on the timetabled activities, aligned to student development needs, and reflect on the model's effectiveness in supporting student learning, building belonging, and providing accessible delivery. We highlight strengths and explore weaknesses, providing recommendations for implementation of this type of model at other institutions.

We summarize national-scale data for Ph.D. earners in engineering or computer science from 2015 to 2019 whose post-graduate school employment is known, highlighting outcomes for biological/biomedical/biosystems engineering students. We use NSF's Survey of Earned Doctorates (SED), which has collected information from Ph.D. recipients in the USA since 1957. The data are collected at the time of degree completion and constitute a greater than 90% response rate. Compared to all engineering and computer science disciplines, biological/biomedical/biosystems engineering has a higher proportion going to 4yr/med/research institutions (52% vs. 33%) and non-profit (3.6% vs. 2.9%) and lower proportion going to industry (33% vs. 48%), government (4.3% vs. 8.4%), and is similar for non-US positions (6.1% vs. 5.7%). Compared to 2010--2014 biological/biomedical/biosystems engineering Ph.D. recipients, more 2015--2019 recipients are going to industry (25% to 33%) and fewer to 4yr/med/research institutions (59% to 52%) and government (5.3% to 4.3%). Across all engineering and computer science disciplines, a smaller proportion of females entered industry (43%) compared to males (49%), while a larger proportion of females entered 4yr/med/research institutions (37%) compared to males (32%). Over half of Asian doctoral recipients entered industry, as compared to 38% of Hispanic doctoral recipients. In contrast, a higher proportion of Hispanic individuals (37%) entered 4yr/med/research institutions after their doctoral programs, as compared to 31% of Asian doctoral recipients. Black doctoral recipients had the highest proportion enter positions in government (14%) and non-profit (4%) sectors. Our results are situated in the broader literature focused on postdoctoral career, training, and employment sectors and trends in STEM. We discuss implications for graduate programs, policymakers, and researchers.

Whether doctoral students are funded primarily by fellowships, research assistantships, or teaching assistantships impacts their degree completion, time to degree, learning outcomes, and short- and long-term career outcomes. Variations in funding patterns have been studied at the broad field level but not comparing engineering sub-disciplines. We addressed two research questions: How do PhD student funding mechanisms vary across engineering sub-disciplines? And how does variation in funding mechanisms across engineering sub-disciplines map onto the larger STEM disciplinary landscape? We analyzed 103,373 engineering and computing responses to the U.S. Survey of Earned Doctorates collected between 2007 and 2016. We conducted analysis of variance with Bonferroni post hoc comparisons to examine variation in funding across sub-disciplines. Then, we conducted a k-means cluster analysis on percentage variables for fellowship, research, and teaching assistantship funding mechanism with STEM sub-discipline as the unit of analysis. A statistically significantly greater percentage of biomedical/biological engineering doctoral students were funded via a fellowship, compared to every other engineering sub-discipline. Consequently, biomedical/biological engineering had significantly lower proportions of students supported via research and teaching assistantships than nearly all other engineering sub-disciplines. We identified five clusters. The majority of engineering sub-disciplines grouped together into a cluster with high research assistantships and low teaching assistantships. Biomedical/biological engineering clustered in the high fellowships grouping with most other biological sciences but no other engineering sub-disciplines. Biomedical/biological engineering behaves much more like biological and life sciences in utilizing fellowships to fund graduate students, far more than other engineering sub-disciplines. Our study provides further evidence of the prevalence of fellowships in life sciences and how it stretches into biomedical/biological engineering. The majority of engineering sub-disciplines relied more on research assistantships to fund graduate study. The lack of uniformity provides an opportunity to diversify student experiences during their graduate programs but also necessitates an awareness to the advantages and disadvantages that different funding portfolios can bestow on students.

To understand the roles of acute-phase viral dynamics and host immune responses in post-acute sequelae of SARS-CoV-2 infection (PASC), we enrolled 136 participants within 5 days of their first positive SARS-CoV-2 real-time PCR test. Participants self-collected up to 21 nasal specimens within the first 28 days post-symptom onset; interviewer-administered questionnaires and blood samples were collected at enrollment, days 9, 14, 21, 28, and month 4 and 8 post-symptom onset. Defining PASC as the presence of any COVID-associated symptom at their 4-month visit, we compared viral markers (quantity and duration of nasal viral RNA load, infectious viral load, and plasma N-antigen level) and host immune markers (IL-6, IL-10, TNF-α, IFN-α, IFN-γ, MCP, IP-10, and Spike IgG) over the acute period. Compared to those who fully recovered, those reporting PASC demonstrated significantly higher maximum levels of SARS-CoV-2 RNA and N-antigen, burden of RNA and infectious viral shedding, and lower Spike-specific IgG levels within 9 days post-illness onset. No significant differences were identified among a panel of host immune markers. Our results suggest early viral dynamics and the associated host immune responses play a role in the pathogenesis of PASC, highlighting the importance of understanding early biological markers in the natural history of PASC.

UNLABELLED: Gastrointestinal diseases are the most frequently reported clinical problems in captive common marmosets (Callithrix jacchus), often affecting the health and welfare of the animal and ultimately their use as a research subject. The microbiome has been shown to be intimately connected to diet and gastrointestinal health. Here, we use shotgun metagenomics and untargeted metabolomics in fecal samples of common marmosets collected before, during, and after a dietary transition from a biscuit to a gel diet. The overall health of marmosets, measured as weight recovery and reproductive outcome, improved after the diet transition. Moreover, each marmoset pair had significant shifts in the microbiome and metabolome after the diet transition. In general, we saw a decrease in Escherichia coli and Prevotella species and an increase in Bifidobacterium species. Untargeted metabolic profiles indicated that polyamine levels, specifically cadaverine and putrescine, were high after diet transition, suggesting either an increase in excretion or a decrease in intestinal reabsorption at the intestinal level. In conclusion, our data suggest that Bifidobacterium species could potentially be useful as probiotic supplements to the laboratory marmoset diet. Future studies with a larger sample size will be beneficial to show that this is consistent with the diet change. IMPORTANCE: Appropriate diet and health of the common marmoset in captivity are essential both for the welfare of the animal and to improve experimental outcomes. Our study shows that a gel diet compared to a biscuit diet improves the health of a marmoset colony, is linked to increases in Bifidobacterium species, and increases the removal of molecules associated with disease. The diet transition had an influence on the molecular changes at both the pair and time point group levels, but only at the pair level for the microbial changes. It appears to be more important which genes and functions present changed rather than specific microbes. Further studies are needed to identify specific components that should be considered when choosing an appropriate diet and additional supplementary foods, as well as to validate the benefits of providing probiotics. Probiotics containing Bifidobacterium species appear to be useful as probiotic supplements to the laboratory marmoset diet, but additional work is needed to validate these findings.

The gut microbiota (GM) can regulate bone mass, but its association with incident fractures is unknown. We used Cox regression models to determine whether the GM composition is associated with incident fractures in the large FINRISK 2002 cohort (n = 7043, 1092 incident fracture cases, median follow-up time 18 years) with information on GM composition and functionality from shotgun metagenome sequencing. Higher alpha diversity was associated with decreased fracture risk (hazard ratio [HR] 0.92 per standard deviation increase in Shannon index, 95% confidence interval 0.87-0.96). For beta diversity, the first principal component was associated with fracture risk (Aitchison distance, HR 0.90, 0.85-0.96). In predefined phyla analyses, we observed that the relative abundance of Proteobacteria was associated with increased fracture risk (HR 1.14, 1.07-1.20), while the relative abundance of Tenericutes was associated with decreased fracture risk (HR 0.90, 0.85-0.96). Explorative sub-analyses within the Proteobacteria phylum showed that higher relative abundance of Gammaproteobacteria was associated with increased fracture risk. Functionality analyses showed that pathways related to amino acid metabolism and lipopolysaccharide biosynthesis associated with fracture risk. The relative abundance of Proteobacteria correlated with pathways for amino acid metabolism, while the relative abundance of Tenericutes correlated with pathways for butyrate synthesis. In conclusion, the overall GM composition was associated with incident fractures. The relative abundance of Proteobacteria, especially Gammaproteobacteria, was associated with increased fracture risk, while the relative abundance of Tenericutes was associated with decreased fracture risk. Functionality analyses demonstrated that pathways known to regulate bone health may underlie these associations.

Bacteroides fragilis is a Gram-negative commensal bacterium commonly found in the human colon, which differentiates into two genomospecies termed divisions I and II. Through a comprehensive collection of 694 B. fragilis whole genome sequences, we identify novel features distinguishing these divisions. Our study reveals a distinct geographic distribution with division I strains predominantly found in North America and division II strains in Asia. Additionally, division II strains are more frequently associated with bloodstream infections, suggesting a distinct pathogenic potential. We report differences between the two divisions in gene abundance related to metabolism, virulence, stress response, and colonization strategies. Notably, division II strains harbor more antimicrobial resistance (AMR) genes than division I strains. These findings offer new insights into the functional roles of division I and II strains, indicating specialized niches within the intestine and potential pathogenic roles in extraintestinal sites.ImportanceUnderstanding the distinct functions of microbial species in the gut microbiome is crucial for deciphering their impact on human health. Classifying division II strains as Bacteroides fragilis can lead to erroneous associations, as researchers may mistakenly attribute characteristics observed in division II strains to the more extensively studied division I B. fragilis. Our findings underscore the necessity of recognizing these divisions as separate species with distinct functions. We unveil new findings of differential gene prevalence between division I and II strains in genes associated with intestinal colonization and survival strategies, potentially influencing their role as gut commensals and their pathogenicity in extraintestinal sites. Despite the significant niche overlap and colonization patterns between these groups, our study highlights the complex dynamics that govern strain distribution and behavior, emphasizing the need for a nuanced understanding of these microorganisms.

BACKGROUND: Chronic exposure to microorganisms inside homes can impact respiratory health. Few studies have used advanced sequencing methods to examine adult respiratory outcomes, especially continuous measures. We aimed to identify metagenomic profiles in house dust related to the quantitative traits of pulmonary function and airway inflammation in adults. Microbial communities, 1264 species (389 genera), in vacuumed bedroom dust from 779 homes in a US cohort were characterized by whole metagenome shotgun sequencing. We examined two overall microbial diversity measures: richness (the number of individual microbial species) and Shannon index (reflecting both richness and relative abundance). To identify specific differentially abundant genera, we applied the Lasso estimator with high-dimensional inference methods, a novel framework for analyzing microbiome data in relation to continuous traits after accounting for all taxa examined together. RESULTS: Pulmonary function measures (forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio) were not associated with overall dust microbial diversity. However, many individual microbial genera were differentially abundant (p-value < 0.05 controlling for all other microbial taxa examined) in relation to FEV1, FVC, or FEV1/FVC. Similarly, fractional exhaled nitric oxide (FeNO), a marker of airway inflammation, was unrelated to overall microbial diversity but associated with differential abundance for many individual genera. Several genera, including Limosilactobacillus, were associated with a pulmonary function measure and FeNO, while others, including Moraxella to FEV1/FVC and Stenotrophomonas to FeNO, were associated with a single trait. CONCLUSIONS: Using state-of-the-art metagenomic sequencing, we identified specific microorganisms in indoor dust related to pulmonary function and airway inflammation. Some were previously associated with respiratory conditions; others were novel, suggesting specific environmental microbial components contribute to various respiratory outcomes. The methods used are applicable to studying microbiome in relation to other continuous outcomes. Video Abstract.

Homelessness is a public health concern in California and throughout the United States. Intimate partner violence (IPV) is a risk factor for experiencing homelessness. Few studies have examined the interplay between IPV, homelessness, and housing. Qualitative methods can provide a greater understanding of the lived experience of IPV and homelessness to identify potential solutions. We purposefully sampled 104 adults who reported experiencing IPV in the California Statewide Study of People Experiencing Homelessness (CASPEH), a representative, mixed-methods study. We administered semi-structured interviews focusing on IPV and six other topic areas pertaining to homelessness from October 2021 to May 2022. We created and applied a codebook with a multidisciplinary team using a hybrid of deductive and inductive logic. Our analysis included all participants who discussed IPV and homelessness across the seven studies. We conducted a thematic analysis using an interpretivist approach and informed by grounded theory. We found that violence within a partnership was multidimensional (physical, sexual, emotional, and financial) and bidirectional. We identified six themes: (1) IPV precipitated and prolonged homelessness; (2) Need for housing, financial stability, and material resources influenced staying in abusive relationships; (3) Alcohol and illicit substance use exacerbated violence between partners; (4) Participants struggled to find resources in domestic violence (DV) shelters; (5) The healthcare system did not provide substantial support; and (6) discrimination and stigma influenced equitable access to housing and DV resources. Experiencing IPV contributed to homelessness and impeded returns to housing. Limitations in current IPV resources impede care. We propose equitable expansion of survivor-centered services that improve access to long-term subsidized housing, prevent IPV and homelessness with flexible funding options, and facilitate rapid exits from homelessness through trauma-informed, non-congregate shelter that transitions to permanent housing.

There has been an increase in volume as well as an improvement in overall survival (OS) after hematopoietic cell transplantation (HCT) for hematologic disorders. It is unknown if these changes have affected racial/ethnic minorities equally. In this observational study from the Center for International Blood and Marrow Transplant Research of 79 904 autologous (auto) and 65 662 allogeneic (allo) HCTs, we examined the volume and rates of change of autoHCT and alloHCT over time and trends in OS in 4 racial/ethnic groups: non-Hispanic Whites (NHWs), non-Hispanic African Americans (NHAAs), and Hispanics across 5 2-year cohorts from 2009 to 2018. Rates of change were compared using Poisson model. Adjusted and unadjusted Cox proportional hazards models examined trends in mortality in the 4 racial/ethnic groups over 5 study time periods. The rates of increase in volume were significantly higher for Hispanics and NHAAs vs NHW for both autoHCT and alloHCT. Adjusted overall mortality after autoHCT was comparable across all racial/ethnic groups. NHAA adults (hazard ratio [HR] 1.13; 95% confidence interval [CI] 1.04-1.22; P = .004) and pediatric patients (HR 1.62; 95% CI 1.3-2.03; P < .001) had a higher risk of mortality after alloHCT than NHWs. Improvement in OS over time was seen in all 4 groups after both autoHCT and alloHCT. Our study shows the rate of change for the use of autoHCT and alloHCT is higher in NHAAs and Hispanics than in NHWs. Survival after autoHCT and alloHCT improved over time; however, NHAAs have worse OS after alloHCT, which has persisted. Continued efforts are needed to mitigate disparities for patients requiring alloHCT.

As the microbiome field moves from descriptive and associative research to mechanistic and interventional studies, being able to account for all confounding variables in the experimental design, which includes the maternal effect1, cage effect2, facility differences3, as well as laboratory and sample handling protocols4, is critical for interpretability of results. Despite significant procedural and bioinformatic improvements, unexplained variability and lack of replicability still occur. One underexplored factor is that the microbiome is dynamic and exhibits diurnal oscillations that can change microbiome composition5-7. In this retrospective analysis of 16S amplicon sequencing studies in male mice, we show that sample collection time affects the conclusions drawn from microbiome studies and its effect size is larger than those of a daily experimental intervention or dietary changes. The timing of divergence of the microbiome composition between experimental and control groups is unique to each experiment. Sample collection times as short as only 4 hours apart can lead to vastly different conclusions. Lack of consistency in the time of sample collection may explain poor cross-study replicability in microbiome research. The impact of diurnal rhythms on the outcomes and study design of other fields is unknown but likely significant.

OBJECTIVE: Integrating clinical research into routine clinical care workflows within electronic health record systems (EHRs) can be challenging, expensive, and labor-intensive. This case study presents a large-scale clinical research project conducted entirely within a commercial EHR during the COVID-19 pandemic. CASE REPORT: The UCSD and UCSDH COVID-19 NeutraliZing Antibody Project (ZAP) aimed to evaluate antibody levels to SARS-CoV-2 virus in a large population at an academic medical center and examine the association between antibody levels and subsequent infection diagnosis. RESULTS: The project rapidly and successfully enrolled and consented over 2000 participants, integrating the research trial with standing COVID-19 testing operations, staff, lab, and mobile applications. EHR-integration increased enrollment, ease of scheduling, survey distribution, and return of research results at a low cost by utilizing existing resources. CONCLUSION: The case study highlights the potential benefits of EHR-integrated clinical research, expanding their reach across multiple health systems and facilitating rapid learning during a global health crisis.

Purpose: The purpose of this investigation was to evaluate language development and disorders course titles across communication sciences and disorders (CSD) graduate programs in an effort to determine whether adolescents were specifically being recognized via inclusive language or dedicated courses. The findings can be used to propel important discussions about the need for inclusive course titles, inform initial directions for improvements in preprofessional education, and guide broader changes in the discipline, especially for the adolescent population. Method: A review of accredited CSD graduate programs across the United States was conducted using the American Speech-Language-Hearing Association EdFind database. A total of 298 master's-level CSD programs were used for this study. CSD course titles located in each of the university's graduate catalogs were documented, categorized, and reviewed by the research team. Results: Of the 298 CSD graduate programs reviewed, one in eight specifically included the word "adolescent(s)" or "adolescence" in the titles of their language development and disorders courses. Remarkably, only four adolescent-focused courses, two of which were listed as electives, were offered across all reviewed programs. A post hoc analysis of the language used in course titling revealed that 42 titles used inclusive terminology. Conclusions: Adolescents are developmentally distinct from children, yet a majority of CSD graduate programs used ambiguous or exclusive words in the titles of their language development and disorders courses. The unintentional failure to recognize this important difference in course titles may be contributing to the ongoing neglect of adolescents within the field. Reframing collective thinking is required for change. Reasons and suggestions for including adolescents in course titles and separate offerings are provided to assist CSD graduate programs in leading the way toward improving equity for adolescents.

This review aimed to synthesize the group design literature to identify the evidence-based reading comprehension interventions for children with ASD. The primary aim was to identify which reading comprehension interventions had demonstrated positive effects for students with ASD in group design studies. This review was initiated using both PsychInfo and ERIC in October 2019 with a second review completed in April 2020. For studies to be included, they had to include pre-/post-data on a reading comprehension intervention and include students with ASD as well as to be (1) peer-reviewed, (2) written in English, and (3) published between 2000 and 2019. The decision to review articles from 2000 forward was based on the publication of the National Reading Panel report (2000) and the wealth of research on the Big Five areas of reading. Five studies were found that met criteria, with a total of 141 students and 87% of the intervention group meeting criteria for ASD. Results showed effectiveness for reading comprehension interventions using anaphoric questions, direct instruction, and comprehension training strategies. These instructional strategies are consistent with single-case design study findings showing efficacy for these strategies with individual students and are important in supporting the variability of executive functioning skills needed for integrating passage information with whole group instruction as well.

Spoken language in schools, now often branded as oracy, is seeing something of a resurgence of interest. This is well-founded and to be welcomed. Nevertheless, the policy-level coopting of oracy, as a concept open to various interpretations, raises questions concerning the desirable degree of prescription and conformity to be promoted in pupils' spoken language. Though often encompassing talk as pedagogy, oracy is strongly associated with developing the skills of spoken language. Such skills rest on a number of assumptions and norms around participation in talk that merit examination. This article explores common classroom orthodoxies in terms of who speaks, when they may speak and how they must speak. As a way of examining these orthodoxies, the article proposes a greater acknowledgement of "orality" alongside, and as a precursor to, oracy. Using an illustration from a real lesson, it argues that raising the profile of orality is a reminder of the importance of understanding and appreciating specific and diverse oral traditions before bringing to bear the generalities and possible standardisation of oracy.

South Africa has low literacy levels and teachers face multiple challenges in their endeavours to elevate levels of literacy. This is especially prevalent in rural and township schools where teachers face the additional challenges of isolation, limited resources and access to professional development. This article reports on the findings and learning from a preliminary research study which piloted a handheld mobile phone App. This collaborative project, between a university in KwaZulu-Natal and one in England, aimed to support in-service and preservice teachers in rural and township settings to use the App to assess and match books to learners' (aged 9-12) stage of reading development in order to facilitate their independent reading and provide teachers with a range of strategies for teaching comprehension that could supplement other professional development available. In-service teachers (n = 120) and preservice teachers (n = 93) took part in this mixed-methods study. The main finding from the study was that whilst participants were positive about the App, many did not access the App independently. This article discusses the broader issues, including participants' foundational knowledge and literacy research participation considerations, that may have underpinned this finding in this collaborative Global North and South research.

Background: Engineering curricula are built around faculty and accreditors' perceptions of what knowledge, skills, and abilities graduates will need in engineering careers. However, the people making these decisions may not be fully aware of what industry employers require for engineering graduates. Purpose/Hypothesis: The purpose of this study is to determine how industry employer-sought professional and technical skills vary among engineering disciplines and levels of education. Design/Method: Using a large sample (n = 26,103) of mined job advertisements, we use the O*NET skills database to determine the frequencies of different professional and technical skills for biomedical, civil, chemical, electrical, environmental, and mechanical engineers with bachelor's, master's, and PhD degrees. Results: The most frequently sought professional skill is problem-solving; the most frequently sought technical skills across disciplines are Microsoft Office software and computer-aided design software. Although not the most frequently requested skills, job advertisements including the Python and MATLAB programming languages paid significantly higher salaries than those without. Conclusions: The findings of this study have important implications for engineering program leaders and curriculum designers choosing which skills to teach students so that they are best prepared to get and excel in engineering jobs. The results also show which skills students can prioritize investing their time in so that they receive the largest financial return on their investment.

The biology education literature includes compelling assertions that unfamiliar problems are especially useful for revealing students' true understanding of biology. However, there is only limited evidence that such novel problems have different cognitive requirements than more familiar problems. Here, we sought additional evidence by using chatbots based on large language models as models of biology students. For human physiology and cell biology, we developed sets of realistic and hypothetical problems matched to the same lesson learning objectives (LLOs). Problems were considered hypothetical if (i) known biological entities (molecules and organs) were given atypical or counterfactual properties (redefinition) or (ii) fictitious biological entities were introduced (invention). Several chatbots scored significantly worse on hypothetical problems than on realistic problems, with scores declining by an average of 13%. Among hypothetical questions, redefinition questions appeared especially difficult, with many chatbots scoring as if guessing randomly. These results suggest that, for a given LLO, hypothetical problems may have different cognitive demands than realistic problems and may more accurately reveal students' ability to apply biology core concepts to diverse contexts. The Test Question Templates (TQT) framework, which explicitly connects LLOs with examples of assessment questions, can help educators generate problems that are challenging (due to their novelty), yet fair (due to their alignment with pre-specified LLOs). Finally, ChatGPT's rapid improvement toward expert-level answers suggests that future educators cannot reasonably expect to ignore or outwit chatbots but must do what we can to make assessments fair and equitable.

Despite substantial evidence supporting the efficacy of prebiotics for promoting host health and stress resilience, few experiments present evidence documenting the dynamic changes in microbial ecology and fecal microbially modified metabolites over time. Furthermore, the literature reports a lack of reproducible effects of prebiotics on specific bacteria and bacterial-modified metabolites. The current experiments examined whether consumption of diets enriched in prebiotics (galactooligosaccharides (GOS) and polydextrose (PDX)), compared to a control diet, would consistently impact the gut microbiome and microbially modified bile acids over time and between two research sites. Male Sprague Dawley rats were fed control or prebiotic diets for several weeks, and their gut microbiomes and metabolomes were examined using 16S rRNA gene sequencing and untargeted LC-MS/MS analysis. Dietary prebiotics altered the beta diversity, relative abundance of bacterial genera, and microbially modified bile acids over time. PICRUSt2 analyses identified four inferred functional metabolic pathways modified by the prebiotic diet. Correlational network analyses between inferred metabolic pathways and microbially modified bile acids revealed deoxycholic acid as a potential network hub. All these reported effects were consistent between the two research sites, supporting the conclusion that dietary prebiotics robustly changed the gut microbial ecosystem. Consistent with our previous work demonstrating that GOS/PDX reduces the negative impacts of stressor exposure, we propose that ingesting a diet enriched in prebiotics facilitates the development of a health-promoting gut microbial ecosystem.

MOTIVATION: Phylogenetic placement of a query sequence on a backbone tree is increasingly used across biomedical sciences to identify the content of a sample from its DNA content. The accuracy of such analyses depends on the density of the backbone tree, making it crucial that placement methods scale to very large trees. Moreover, a new paradigm has been recently proposed to place sequences on the species tree using single-gene data. The goal is to better characterize the samples and to enable combined analyses of marker-gene (e.g., 16S rRNA gene amplicon) and genome-wide data. The recent method DEPP enables performing such analyses using metric learning. However, metric learning is hampered by a need to compute and save a quadratically growing matrix of pairwise distances during training. Thus, the training phase of DEPP does not scale to more than roughly 10 000 backbone species, a problem that we faced when trying to use our recently released Greengenes2 (GG2) reference tree containing 331 270 species. RESULTS: This paper explores divide-and-conquer for training ensembles of DEPP models, culminating in a method called C-DEPP. While divide-and-conquer has been extensively used in phylogenetics, applying divide-and-conquer to data-hungry machine-learning methods needs nuance. C-DEPP uses carefully crafted techniques to enable quasi-linear scaling while maintaining accuracy. C-DEPP enables placing 20 million 16S fragments on the GG2 reference tree in 41 h of computation. AVAILABILITY AND IMPLEMENTATION: The dataset and C-DEPP software are freely available at https://github.com/yueyujiang/dataset_cdepp/.

In South Africa, alcohol use during pregnancy is prevalent and associated with increased HIV risk. Developing locally sensitive and contextually appropriate evidence-based interventions to address alcohol use among pregnant and breastfeeding women in South Africa requires comprehensive understanding of the context of perinatal alcohol use and how relationships and lived environments may serve as barriers or supports for alcohol reduction. We conducted twenty in-depth qualitative interviews with isiXhosa speaking women who reported alcohol use during their recent pregnancy and/or recent intimate partner violence in Cape Town, South Africa between September and November 2022. We describe patterns and drivers of ongoing alcohol use during pregnancy and map them onto levels of the socioecological model. Data were analyzed utilizing the interpretivist paradigm and interpretive thematic analysis. Eight women reported alcohol use during pregnancy, sixteen reported experiencing recent IPV, and four women reported both alcohol use during pregnancy and recent IPV. In interviews, commonly cited reasons for continued alcohol use in pregnancy included stress (e.g., due to financial concerns), peer pressure, the central role of alcohol use in socialization and the persistence of misconceptions regarding the safety of alcohol use in pregnancy. Still, despite women reporting social norms that supported continued alcohol use in pregnancy, many altered who they drank with due to fear of judgement from close friends and family, leaving them isolated from their social support system. Interventions aimed at increasing interpersonal support, such as the use of peer mentors, could prove beneficial. Although the clinic provides messaging around the harms of alcohol use in pregnancy, these messages conflict with messaging received from their peers, limiting their impact on behavior. Locally sensitive tailored, relevant programming that intervenes on barriers to reducing alcohol use in pregnancy at multiple levels of the socioeconomic model are vital to effectively addressing this public health issue.

BackgroundInfection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2.MethodsWe performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs.ResultsAmong 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001).ConclusionsIP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. By inserting sequences into a whole-genome phylogeny, we show that 16S rRNA and shotgun metagenomic data generated from the same samples agree in principal coordinates space, taxonomy and phenotype effect size when analyzed with the same tree.

Phylogenetic trees provide a framework for organizing evolutionary histories across the tree of life and aid downstream comparative analyses such as metagenomic identification. Methods that rely on single-marker genes such as 16S rRNA have produced trees of limited accuracy with hundreds of thousands of organisms, whereas methods that use genome-wide data are not scalable to large numbers of genomes. We introduce updating trees using divide-and-conquer (uDance), a method that enables updatable genome-wide inference using a divide-and-conquer strategy that refines different parts of the tree independently and can build off of existing trees, with high accuracy and scalability. With uDance, we infer a species tree of roughly 200,000 genomes using 387 marker genes, totaling 42.5 billion amino acid residues.