Background:Data dashboards are popular tools for supporting routine monitoring and decision-making in public health. Two dashboards were developed in Côte d'Ivoire to visualize laboratory data on HIV viral load (VL) and early infant diagnosis (EID) testing. Objective:This study assessed the attitudes and experiences regarding data-driven decision-making and the VL and EID dashboards among existing and potential dashboard users in Côte d'Ivoire. Methods:We conducted a qualitative study including 2 focus group discussions (FGDs) and 12 in-depth interviews (IDIs). The conceptual framework for the use of health data in decision-making guided the FGDs, and the Consolidated Framework for Implementation Research informed the IDIs. We used deductive and inductive approaches to analyze the interview data. Results:The 26 participants were from 17 organizations; 11 (42.3%) were female. The participants reported a supportive data culture that valued data-driven decision-making and external pressure from the United States President's Emergency Plan for AIDS Relief (PEPFAR) that motivated data use. The dashboards were considered useful for monitoring performances and making decisions for service delivery and laboratory operations. Existing users used the dashboards regularly. Potential users expressed interest in the speed and ability to track progress. The participants considered the dashboards simple and straightforward compared to other analytical tools but suggested updating the dashboards more frequently and visualizing more data. Conclusions:The study highlighted the importance of supportive data culture and the potential of dashboards to promote data use. However, challenges such as limited access to the internet and equipment for potential users need to be addressed.

Epigenetic ‘clocks’ based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock ( R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.

Background The Ministry of Health in Côte d'Ivoire and the International Training and Education Center for Health at the University of Washington, funded by the United States President’s Emergency Plan for AIDS Relief, have been collaborating to develop and implement the Open-Source Enterprise-Level Laboratory Information System (OpenELIS). The system is designed to improve HIV-related laboratory data management and strengthen quality management and capacity at clinical laboratories across the nation. Objective This evaluation aimed to quantify the effects of implementing OpenELIS on data quality for laboratory tests related to HIV care and treatment. Methods This evaluation used a quasi-experimental design to perform an interrupted time-series analysis to estimate the changes in the level and slope of 3 data quality indicators (timeliness, completeness, and validity) after OpenELIS implementation. We collected paper and electronic records on clusters of differentiation 4 (CD4) testing for 48 weeks before OpenELIS adoption until 72 weeks after. Data collection took place at 21 laboratories in 13 health regions that started using OpenELIS between 2014 and 2020. We analyzed the data at the laboratory level. We estimated odds ratios (ORs) by comparing the observed outcomes with modeled counterfactual ones when the laboratories did not adopt OpenELIS. Results There was an immediate 5-fold increase in timeliness (OR 5.27, 95% CI 4.33-6.41; P<.001) and an immediate 3.6-fold increase in completeness (OR 3.59, 95% CI 2.40-5.37; P<.001). These immediate improvements were observed starting after OpenELIS installation and then maintained until 72 weeks after OpenELIS adoption. The weekly improvement in the postimplementation trend of completeness was significant (OR 1.03, 95% CI 1.02-1.05; P<.001). The improvement in validity was not statistically significant (OR 1.34, 95% CI 0.69-2.60; P=.38), but validity did not fall below pre-OpenELIS levels. Conclusions These results demonstrate the value of electronic laboratory information systems in improving laboratory data quality and supporting evidence-based decision-making in health care. These findings highlight the importance of OpenELIS in Côte d'Ivoire and the potential for adoption in other low- and middle-income countries with similar health systems.

Background Few investigations have assessed contributions of both vaginal bacteria and proinflammatory immune mediators to human immunodeficiency virus (HIV) acquisition risk in a prospective cohort. Methods We conducted a nested case-control study of African women who participated in a randomized placebo-controlled trial of daily oral versus vaginal tenofovir-based preexposure prophylaxis for HIV infection. Vaginal concentrations of 23 bacterial taxa and 16 immune mediators were measured. Relationships between individual bacterial concentrations or immune mediators and HIV risk were analyzed using generalized estimating equations in a multivariable model. Factor analysis assessed relationships between combinations of bacterial taxa, immune mediators, and HIV acquisition risk. Results We identified 177 HIV pre-seroconversion visits from 150 women who acquired HIV and 531 visits from 436 women who remained HIV uninfected. Fourteen bacterial taxa and 6 proinflammatory cytokines and chemokines were individually associated with greater HIV risk after adjusting for confounders. Women with all 14 taxa versus <14 taxa (adjusted odds ratio [aOR], 4.45 [95% confidence interval {CI}, 2.20-8.98]; P < .001) or all 6 immune mediators versus <6 mediators (aOR, 1.77 [95% CI, 1.24-2.52]; P < .001) had greater risk for HIV acquisition. Factor analysis demonstrated that a bacterial factor comprised of 14 high-risk bacterial taxa (aOR, 1.57 [95% CI, 1.27-1.93]; P < 0.001) and the interferon gamma-induced protein 10 (highest quartile: aOR, 3.19 [95% CI, 1.32-7.72]; P = 0.002) contributed to the highest HIV risk. Conclusions Bacterial and host biomarkers for predicting HIV acquisition risk identify women at greatest risk for HIV infection and can focus prevention efforts.

Purpose:The goal of this preliminary study is to describe the vaginal microbiome of transgender and gender nonbinary (TGNB) individuals using nonculture-based techniques. TGNB individuals may undergo gender-affirming surgical procedures, which can include the creation of a neovagina. Little is known about microbial species that comprise this environment in states of health or disease. Methods:In this pilot study, vaginal swabs were self-collected from 15 healthy self-identified TGNB participants (age 26-69 years) and 8 cisgender comparator participants (age 27-50 years) between 2017 and 2018. Next-generation 16S ribosomal RNA sequencing was used to profile individual bacterial communities from all study samples. Results:The TGNB cohort demonstrated significantly higher intraindividual (alpha) diversity than the cisgender group (p=0.0003). Microbial species commensal to the gut and skin were identified only in specimens from TGNB participants. Although Lactobacillus species were dominant in all cisgender comparator samples, they were found at low relative abundance (≤3%) in TGNB samples. Conclusion:In this study, specimens collected from neovaginas showed increased alpha diversity and substantially different composition compared with natal vaginas. In contrast to natal vaginas, neovaginas were not dominated by Lactobacillus, but were hosts to many microbial species. Studies that help to improve our understanding of the neovaginal microbiome may enable clinicians to differentiate between healthy and diseased neovaginal states.

Background Sexual behavior may influence the composition of the male urethral microbiota, but this hypothesis has not been tested in longitudinal studies of men who have sex with men (MSM). Methods From December 2014 to July 2018, we enrolled MSM with nongonococcal urethritis (NGU) attending a sexual health clinic. Men attended 5 in-clinic visits at 3-week intervals, collected weekly urine specimens at home, and reported daily antibiotics and sexual activity on weekly diaries. We applied broad-range 16S rRNA gene sequencing to urine. We used generalized estimating equations to estimate the association between urethral sexual exposures in the prior 7 days (insertive oral sex [IOS] only, condomless insertive anal intercourse [CIAI] only, IOS with CIAI [IOS + CIAI], or none) and Shannon index, number of species (observed, oral indicator, and rectal indicator), and specific taxa, adjusting for recent antibiotics, age, race/ethnicity, HIV, and preexposure prophylaxis. Results Ninety-six of 108 MSM with NGU attended ≥1 follow-up visit. They contributed 1140 person-weeks of behavioral data and 1006 urine specimens. Compared with those with no urethral sexual exposures, those with IOS only had higher Shannon index ( P = 0.03 ) but similar number of species and presence of specific taxa considered, adjusting for confounders; the exception was an association with Haemophilus parainfluenzae . CIAI only was not associated with measured aspects of the urethral microbiota. IOS + CIAI was only associated with presence of H. parainfluenzae and Haemophilus . Conclusions Among MSM after NGU, IOS and CIAI did not seem to have a substantial influence on measured aspects of the composition of the urethral microbiota.

For studies using microbiome data, the ability to robustly combine data from technically and biologically distinct microbiome studies is a crucial means of supporting more robust and clinically relevant inferences. Formidable technical challenges arise when attempting to combine data from technically diverse 16S rRNA gene variable region amplicon sequencing (16S) studies. Closed operational taxonomic units and taxonomy are criticized as being heavily dependent upon reference sets and with limited precision relative to the underlying biology. Phylogenetic placement has been demonstrated to be a promising taxonomy-free manner of harmonizing microbiome data, but it has lacked a validated count-based feature suitable for use in machine learning and association studies. Here we introduce a phylogenetic-placement-based, taxonomy-independent, compositional feature of microbiota: phylotypes. Phylotypes were predictive of clinical outcomes such as obesity or pre-term birth on technically diverse independent validation sets harmonized post hoc. Thus, phylotypes enable the rigorous cross-validation of 16S-based clinical prognostic models and associative microbiome studies.

Identification and analysis of clinically relevant strains of bacteria increasingly relies on whole-genome sequencing. The downstream bioinformatics steps necessary for calling variants from short-read sequences are well-established but seldom validated against haploid genomes. We devised an in silico workflow to introduce single nucleotide polymorphisms (SNP) and indels into bacterial reference genomes, and computationally generate sequencing reads based on the mutated genomes. We then applied the method to Mycobacterium tuberculosis H37Rv, Staphylococcus aureus NCTC 8325, and Klebsiella pneumoniae HS11286, and used the synthetic reads as truth sets for evaluating several popular variant callers. Insertions proved especially challenging for most variant callers to correctly identify, relative to deletions and single nucleotide polymorphisms. With adequate read depth, however, variant callers that use high quality soft-clipped reads and base mismatches to perform local realignment consistently had the highest precision and recall in identifying insertions and deletions ranging from1 to 50 bp. The remaining variant callers had lower recall values associated with identification of insertions greater than 20 bp. Identification and analysis of clinically relevant strains of bacteria increasingly relies on whole-genome sequencing. The downstream bioinformatics steps necessary for calling variants from short-read sequences are well-established but seldom validated against haploid genomes.

In this paper, we consider the current and potential role of the latest generation of Large Language Models (LLMs) in medical informatics, particularly within the realms of clinical and anatomic pathology. We aim to provide a thorough understanding of the considerations that arise when employing LLMs in healthcare settings, such as determining appropriate use cases and evaluating the advantages and limitations of these models. Furthermore, this paper will consider the infrastructural and organizational requirements necessary for the successful implementation and utilization of LLMs in healthcare environments. We will discuss the importance of addressing education, security, bias, and privacy concerns associated with LLMs in clinical informatics, as well as the need for a robust framework to overcome regulatory, compliance, and legal challenges.

Acute graft-versus-host disease (aGVHD) remains a major limitation of allogeneic stem cell transplantation (SCT), and severe intestinal manifestation is the major cause of early mortality. Intestinal microbiota control MHC class II (MHC-II) expression by ileal intestinal epithelial cells (IECs) that promote GVHD. Here, we demonstrated that genetically identical mice of differing vendor origins had markedly different intestinal mi-crobiota and ileal MHC-II expression, resulting in discordant GVHD severity. We utilized cohousing and anti-biotic treatment to characterize the bacterial taxa positively and negatively associated with MHC-II expres-sion. A large proportion of bacterial MHC-II inducers were vancomycin sensitive, and peri-transplant oral vancomycin administration attenuated CD4+ T cell-mediated GVHD. We identified a similar relationship be-tween pre-transplant microbes, HLA class II expression, and both GVHD and mortality in a large clinical SCT cohort. These data highlight therapeutically tractable mechanisms by which pre-transplant microbial taxa contribute to GVHD independently of genetic disparity.

Abstract Displaying the cost of laboratory tests and medications in the electronic health record (EHR) at the time of order may influence ordering practices. Our organization’s EHR was configured to display a semi-quantitative value adjacent to laboratory orders: “$” tests imply relatively little cost and “$$$$” tests imply resource intensive tests. Cost display is associated with charges from hospital or clinic fee schedules by default but can also be configured to reflect direct laboratory costs. To understand our system’s configuration and potentially improve the information being provided to our clinicians upon ordering, all the test ordering data was compiled and analyzed for all individual “orderable” tests within the year of 2021 (Jan 1st 2021 – Dec 31st 2021). Variables analyzed included frequency of test ordering, average test turnaround time, and each of the various possible measures of “cost”: direct costs based on labor and reagents/supplies (when available), reimbursement from the Clinical Laboratory Fee Schedule, and pricing from the fee schedule of the largest hospital in our organization (chargemaster). Results showed an extensive rightward skew in each of the “cost” variables, with most routine tests, like the complete blood count (CBC) or complete metabolic panel (CMP), falling in the lower price range and a number of outlier tests with much higher costs (newer forms of molecular testing). There was minimal linearity in correlations between the various price variables. Correlation between chargemaster price by quintile and actual dollar signs displayed in the EHR showed that the two often disagree. No definitive discernable logic was thus identified for the number of dollar signs shown in the EHR based on the possible “cost” variables analyzed here. Between the lab’s best estimate for direct costs and chargemaster pricing, a rough correlation with slope greater than 1 was identified, suggesting that chargemaster pricing is systematically higher than the cost of running each test. Between the cost of running each test and reimbursement via the Clinical Laboratory Fee Schedule, a rough correlation with slope less than 1 was identified, suggesting that lab costs are systematically higher than reimbursement. The current lack of strong correlations between these various “cost” variables is helpful as a first step in examining how to improve our organization’s EHR system, assessing our laboratory’s cost effectiveness, and discussing potential future considerations for hospital chargemaster pricing as well as the US system of reimbursement. Further work is needed to clarify the relationship between cost displays in EHR and physician ordering practices.

Background:Reflexive laboratory testing workflows can improve the assessment of patients receiving pain medications chronically, but complex workflows requiring pathologist input and interpretation may not be well-supported by traditional laboratory information systems. In this work, we describe the development of a web application that improves the efficiency of pathologists and laboratory staff in delivering actionable toxicology results. Method:Before designing the application, we set out to understand the entire workflow including the laboratory workflow and pathologist review. Additionally, we gathered requirements and specifications from stakeholders. Finally, to assess the performance of the implementation of the application, we surveyed stakeholders and documented the approximate amount of time that is required in each step of the workflow. Results:A web-based application was chosen for the ease of access for users. Relevant clinical data was routinely received and displayed in the application. The workflows in the laboratory and during the interpretation process served as the basis of the user interface. With the addition of auto-filing software, the return on investment was significant. The laboratory saved the equivalent of one full-time employee in time by automating file management and result entry. Discussion:Implementation of a purpose-built application to support reflex and interpretation workflows in a clinical pathology practice has led to a significant improvement in laboratory efficiency. Custom- and purpose-built applications can help reduce staff burnout, reduce transcription errors, and allow staff to focus on more critical issues around quality.

Microbiome science is difficult to translate back to patients due to an inability to harmonize 16S rRNA gene-based microbiome data, as differences in the technique will result in different amplicon sequence variants (ASV) from the same microbe. Here we demonstrate that placement of ASV onto a common phylogenetic tree of full-length 16S rRNA alleles can harmonize microbiome studies. Using in silico data approximating 100 healthy human stool microbiomes we demonstrated that phylogenetic placement of ASV can recapitulate the true relationships between communities as compared closed-OTU based approaches (Spearman R 0.8 vs 0.2). Using real data from thousands of human gut and vaginal microbiota, we demonstrate phylogenetic placement, but not closed OTUs, were able to group communities by origin (stool vs vaginal) without being confounded by technique and integrate new data into existing ordination/clustering models for precision medicine. This enables meta-analysis of microbiome studies and the microbiome as a biomarker. ### Competing Interest Statement The authors have declared no competing interest.

s exponential and increased contagiousness to evasion of humoral memory due to altered spike protein antigens 3), to what viral load has contributed to its dominance 5). Here, we examine whether symptomatic individuals and asymptomatic carriers infected with Omicron demonstrate differences in viral load by examining the reverse transcriptase PCR (RT-PCR) cycle thresholds ( C T ) in sequence-con fi rmed cases, compared with prior infections with the Alpha and Delta variants of SARS-CoV-2.

Identification of clinically relevant strains of bacteria increasingly relies on whole genome sequencing. The downstream bioinformatics steps necessary for calling variants from short read sequences are well-established but seldom validated against haploid genomes. We devised an in silico workflow to introduce single nucleotide polymorphisms (SNP) and indels into bacterial reference genomes, and computationally generate sequencing reads based on the mutated genomes. We then applied the method to Mycobacterium tuberculosis H37Rv and used the synthetic reads as truth sets for evaluating several popular variant callers. Insertions proved especially challenging for most variant callers to correctly identify, relative to deletions and single nucleotide polymorphisms. With adequate read depth, however, variant callers that use high quality soft-clipped reads and base mismatches to perform local realignment consistently had the highest precision and recall in identifying medium-length insertions and deletions.

Pig-tailed macaques (Macaca nemestrina) may help advance our understanding of how the genital microbiota influences sexually transmitted infections. We characterized the vaginal microbiota and evaluated the effect of streptomycin (STR) treatment on GC colonization to aid the development of a macaque model of genital gonococcal infection.

BackgroundBacterial colonization and associations with bacterial vaginosis (BV) signs and symptoms (Amsel criteria) may vary between populations. We assessed relationships between vaginal bacteria and Amsel criteria among two populations. MethodsKenyan participants from the placebo arm of the Preventing Vaginal Infections (PVI) trial and participants from a Seattle-based cross-sectional BV study were included. Amsel criteria were recorded at study visits, and the vaginal microbiota was characterized using 16S rRNA gene sequencing. Logistic regression models, accounting for repeat visits as appropriate, were fit to evaluate associations between bacterial relative abundance and each Amsel criterion. ResultsAmong 84 PVI participants (496 observations) and 220 Seattle participants, the prevalence of amine odor was 25% and 40%, clue cells 16% and 37%, vaginal discharge 10% and 52%, elevated vaginal pH 69% and 67%, and BV 13% and 44%, respectively. BV-associated bacterium 1 (BVAB1) was positively associated with all Amsel criteria in both populations. Eggerthella type 1, Fannyhessea (Atopobium) vaginae, Gardnerella spp., Sneathia amnii, and Sneathia sanguinegens were positively associated with all Amsel criteria in the Seattle study, and all but discharge in the PVI trial. ConclusionsCore vaginal bacteria are consistently associated with BV signs and symptoms across two distinct populations of women.