CARLA: Adjusted common average referencing for cortico-cortical evoked potential data.

Human brain connectivity can be mapped by single pulse electrical stimulation during intracranial EEG measurements. The raw cortico-cortical evoked potentials (CCEP) are often contaminated by noise. Common average referencing (CAR) removes common noise and preserves response shapes but can introduce bias from responsive channels. We address this issue with an adjusted, adaptive CAR algorithm termed "CAR by Least Anticorrelation (CARLA)". CARLA was tested on simulated CCEP data and real CCEP data collected from four human participants. In CARLA, the channels are ordered by increasing mean cross-trial covariance, and iteratively added to the common average until anticorrelation between any single channel and all re-referenced channels reaches a minimum, as a measure of shared noise. We simulated CCEP data with true responses in 0-45 of 50 total channels. We quantified CARLA's error and found that it erroneously included 0 (median) truly responsive channels in the common average with ≤42 responsive channels, and erroneously excluded ≤2.5 (median) unresponsive channels at all responsiveness levels. On real CCEP data, signal quality was quantified with the mean R2 between all pairs of channels, which represents inter-channel dependency and is low for well-referenced data. CARLA re-referencing produced significantly lower mean R2 than standard CAR, CAR using a fixed bottom quartile of channels by covariance, and no re-referencing. CARLA minimizes bias in re-referenced CCEP data by adaptively selecting the optimal subset of non-responsive channels. It showed high specificity and sensitivity on simulated CCEP data and lowered inter-channel dependency compared to CAR on real CCEP data.

Research note: Expert opinions of feather sucking and licking behavior in meat chicken breeder birds.

Feather sucking, or feather licking, has been reported anecdotally by employees in the Australian meat chicken breeder industry, but scarcely in the scientific literature. Consequently, the causes and implications of this behavior in meat chicken breeding chickens is relatively unknown. We surveyed 17 industry experts to generate hypotheses about feather sucking behavior. We aimed to understand the frequency and when it occurs, and attempted to understand what may cause an "outbreak". The recruitment of participants was intentionally biased towards Australian perspectives; only 5 of the 17 participants were international. All participants, except 1, had seen feather sucking/licking behavior (94.1%) and most participants (80%) suggested that the behavior was most frequently observed during rearing. Participants presented varying concerns about this behavior, ranging from the perspective that it was "normal" and had no impact on welfare, to concerns about mating injuries due to damaged feathers, increased risk of feather pecking and cannibalism, and psychological stress indicated by expression of repetitive (seemingly) functionless behavior. "Feather licking," "feather sucking," "feather eating," and "feather pecking" were terms used interchangeably, leading to confusion by participants about the cause and implications of the target behavior. The most common factors reported as the cause were boredom (52.9%), nutritional deficiencies (47.1%), and feed restriction (41.2%) and more than 80% of respondents agreed that stress contributes to feather sucking. The outputs from this study reflect only a small, but expert, number of opinions on feather sucking/licking behaviors in the Australian meat chicken breeder industry. A systematic understanding of this behavior is needed to provide insight into causation and the implications for welfare.

A fast comparative genome browser for diverse bacteria and archaea.

Genome sequencing has revealed an incredible diversity of bacteria and archaea, but there are no fast and convenient tools for browsing across these genomes. It is cumbersome to view the prevalence of homologs for a protein of interest, or the gene neighborhoods of those homologs, across the diversity of the prokaryotes. We developed a web-based tool, fast.genomics, that uses two strategies to support fast browsing across the diversity of prokaryotes. First, the database of genomes is split up. The main database contains one representative from each of the 6,377 genera that have a high-quality genome, and additional databases for each taxonomic order contain up to 10 representatives of each species. Second, homologs of proteins of interest are identified quickly by using accelerated searches, usually in a few seconds. Once homologs are identified, fast.genomics can quickly show their prevalence across taxa, view their neighboring genes, or compare the prevalence of two different proteins. Fast.genomics is available at https://fast.genomics.lbl.gov.

Osteopetrosis in the pediatric patient: what the radiologist needs to know.

Osteopetrosis describes several types of rare sclerosing bone dysplasias of varying clinical and radiographic severity. The classic autosomal dominant subtype emerges most often in adolescence but can present from infancy through adulthood. The autosomal recessive osteopetrosis, or "malignant infantile osteopetrosis," presents in infancy with a grimmer prognosis, though the autosomal dominant forms (often mislabeled as "benign") actually can have life-threatening consequences as well. Often osteopetrosis is detected due to skeletal findings on radiographs performed to evaluate injury or as an incidental finding during evaluation for illness. Given the varied phenotypic severity and presentations at different ages, radiologists play an integral role in the care of these patients both in diagnosis and in clinical evaluation and monitoring. A deeper understanding of the underlying genetic basis of the disease can aid in the radiologist in diagnosis and in anticipation of unique complications. An overview of current clinical management is also discussed.

What's in a Name? Experimental Evidence of Gender Bias in Recommendation Letters Generated by ChatGPT.

BACKGROUND: Artificial intelligence chatbots such as ChatGPT (OpenAI) have garnered excitement about their potential for delegating writing tasks ordinarily performed by humans. Many of these tasks (eg, writing recommendation letters) have social and professional ramifications, making the potential social biases in ChatGPT's underlying language model a serious concern. OBJECTIVE: Three preregistered studies used the text analysis program Linguistic Inquiry and Word Count to investigate gender bias in recommendation letters written by ChatGPT in human-use sessions (N=1400 total letters). METHODS: We conducted analyses using 22 existing Linguistic Inquiry and Word Count dictionaries, as well as 6 newly created dictionaries based on systematic reviews of gender bias in recommendation letters, to compare recommendation letters generated for the 200 most historically popular "male" and "female" names in the United States. Study 1 used 3 different letter-writing prompts intended to accentuate professional accomplishments associated with male stereotypes, female stereotypes, or neither. Study 2 examined whether lengthening each of the 3 prompts while holding the between-prompt word count constant modified the extent of bias. Study 3 examined the variability within letters generated for the same name and prompts. We hypothesized that when prompted with gender-stereotyped professional accomplishments, ChatGPT would evidence gender-based language differences replicating those found in systematic reviews of human-written recommendation letters (eg, more affiliative, social, and communal language for female names; more agentic and skill-based language for male names). RESULTS: Significant differences in language between letters generated for female versus male names were observed across all prompts, including the prompt hypothesized to be neutral, and across nearly all language categories tested. Historically female names received significantly more social referents (5/6, 83% of prompts), communal or doubt-raising language (4/6, 67% of prompts), personal pronouns (4/6, 67% of prompts), and clout language (5/6, 83% of prompts). Contradicting the study hypotheses, some gender differences (eg, achievement language and agentic language) were significant in both the hypothesized and nonhypothesized directions, depending on the prompt. Heteroscedasticity between male and female names was observed in multiple linguistic categories, with greater variance for historically female names than for historically male names. CONCLUSIONS: ChatGPT reproduces many gender-based language biases that have been reliably identified in investigations of human-written reference letters, although these differences vary across prompts and language categories. Caution should be taken when using ChatGPT for tasks that have social consequences, such as reference letter writing. The methods developed in this study may be useful for ongoing bias testing among progressive generations of chatbots across a range of real-world scenarios. TRIAL REGISTRATION: OSF Registries osf.io/ztv96; https://osf.io/ztv96.

Engaging Cancer Care Physicians in Off-Label Drug Clinical Trials: Human-Centered Design Approach.

BACKGROUND: Using a human-centered design (HCD) approach can provide clinical trial design teams with a better understanding of the needs, preferences, and attitudes of clinical trial stakeholders. It can also be used to understand the challenges and barriers physician stakeholders face in initiating and completing clinical trials, especially for using off-label drugs (OLDs) to treat unmet clinical needs in cancer treatment. However, the HCD approach is not commonly taught in the context of clinical trial design, and few step-by-step guides similar to this study are available to demonstrate its application. OBJECTIVE: This study aims to demonstrate the feasibility and process of applying an HCD approach to creating clinical trial support resources for physician stakeholders to overcome barriers to pursuing clinical trials for OLDs to treat cancer. METHODS: An HCD approach was used to develop OLD clinical trial support concepts. In total, 45 cancer care physicians were contacted, of which 15 participated in semistructured interviews to identify barriers to prescribing OLDs or participating in cancer OLD clinical trials. Design research is qualitative-it seeks to answer "why" and "how" questions; thus, a sample size of 15 was sufficient to provide insight saturation to address the design problem. The team used affinity mapping and thematic analysis of qualitative data gathered from the interviews to inform subsequent web-based co-design sessions, which included creative matrix exercises and voting to refine and prioritize the ideas used in the final 3 recommended concepts. RESULTS: The findings demonstrate the potential of HCD methods to uncover important insights into the barriers physicians face in participating in OLD clinical trials or prescribing OLDs, such as recruitment challenges, low willingness to prescribe without clinical data, and stigma. Notably, only palliative care participants self-identified as "frequent prescribers" of OLDs, despite high national OLD prescription rates among patients with cancer. Participants found the HCD approach engaging, with 60% (9/15) completing this study; scheduling conflicts caused most of the dropouts. Over 150 ideas were generated in 3 co-design sessions, with the groups voting on 15 priority ideas that the design team then refined into 3 final recommendations, especially focused on increasing the participation of physicians in OLD clinical trials. CONCLUSIONS: Using participatory HCD methods, we delivered 3 concepts for clinical trial support resources to help physician stakeholders overcome barriers to pursuing clinical trials for OLDs to treat cancer. Overall, integrating the HCD approach can aid in identifying important stakeholders, such as prescribing physicians; facilitating their engagement; and incorporating their perspectives and needs into the solution design process. This paper highlights the process, methods, and potential of HCD to improve cancer clinical trial design. Future work is needed to train clinical trial designers in the HCD approach and encourage adoption in the field.

Multistate nontyphoidal Salmonella and Shiga toxin-producing Escherichia coli outbreaks linked to international travel-United States, 2017-2020.

Enteric bacterial infections are common among people who travel internationally. During 2017-2020, the Centers for Disease Control and Prevention investigated 41 multistate outbreaks of nontyphoidal Salmonella and Shiga toxin-producing Escherichia coli linked to international travel. Resistance to one or more antimicrobial agents was detected in at least 10% of isolates in 16 of 30 (53%) nontyphoidal Salmonella outbreaks and 8 of 11 (73%) Shiga toxin-producing E. coli outbreaks evaluated by the National Antimicrobial Resistance Monitoring System. At least 10% of the isolates in 14 nontyphoidal Salmonella outbreaks conferred resistance to one or more of the clinically significant antimicrobials used in human medicine. This report describes the epidemiology and antimicrobial resistance patterns of these travel-associated multistate outbreaks. Investigating illnesses among returned travellers and collaboration with international partners could result in the implementation of public health interventions to improve hygiene practices and food safety standards and to prevent illness and spread of multidrug-resistant organisms domestically and internationally.

Flagella are required to coordinately activate competition and host colonization factors in response to a mechanical signal.

Bacteria employ antagonistic strategies to eliminate competitors of an ecological niche. Contact-dependent mechanisms, such as the type VI secretion system (T6SS), are prevalent in host-associated bacteria, yet we know relatively little about how T6SS+ strains make contact with competitors in highly viscous environments, such as host mucus. To better understand how cells respond to and contact one another in such environments, we performed a genome-wide transposon mutant screen of the T6SS-wielding beneficial bacterial symbiont, Vibrio fischeri, and identified two sets of genes that are conditionally required for killing. LPS/capsule and flagellar-associated genes do not affect T6SS directly and are therefore not required for interbacterial killing when cell contact is forced yet are necessary for killing in high-viscosity liquid (hydrogel) where cell-cell contact must be biologically mediated. Quantitative transcriptomics revealed that V. fischeri significantly increases expression of both T6SS genes and cell surface modification factors upon transition from low- to high-viscosity media. Consistent with coincubation and fluorescence microscopy data, flagella are not required for T6SS expression in hydrogel. However, flagella play a key role in responding to the physical environment by promoting expression of the surface modification genes identified in our screen, as well as additional functional pathways important for host colonization including uptake of host-relevant iron and carbon sources, and nitric oxide detoxification enzymes. Our findings suggest that flagella may act as a mechanosensor for V. fischeri to coordinately activate competitive strategies and host colonization factors, underscoring the significance of the physical environment in directing complex bacterial behaviors.

Using classification trees to identify psychotherapy patients at risk for poor treatment adherence.

To determine the relative importance of a wide variety of personality and psychopathology variables in influencing patients' adherence to psychotherapy treatment.Two classification trees were trained to predict patients' (1) treatment utilization (i.e., their likelihood of missing a given appointment) and (2) termination status (i.e., their likelihood of dropping out of therapy prematurely). Each tree was then validated in an external dataset to examine performance accuracy.Patients' social detachment was most influential in predicting their treatment utilization, followed by affective instability and activity/energy levels. Patients' interpersonal warmth was most influential in predicting their termination status, followed by levels of disordered thought and resentment. The overall accuracy rating for the tree for termination status was 71.4%, while the tree for treatment utilization had a 38.7% accuracy rating.Classification trees are a practical tool for clinicians to determine patients at risk of premature termination. More research is needed to develop trees that predict treatment utilization with high accuracy across different types of patients and settings.

Belowground insect herbivory induces systemic volatile emissions that strengthen neighbouring plant resistance aboveground.

Plants transmit ecologically relevant messages to neighbouring plants through chemical cues. For instance, insect herbivory triggers the production of herbivore-induced plant volatiles (HIPVs), which can enhance neighbouring plant defences. HIPVs are emitted from directly damaged plant tissues and from systemic, nondamaged tissues. Although volatile-mediated interplant interactions have been observed both above- and belowground, it remains unknown whether belowground herbivory induces systemic HIPVs aboveground that influence neighbouring plants. To explore how belowground herbivory affects interplant interactions aboveground, we characterised systemic HIPVs from squash induced by belowground striped cucumber beetle (Acalymma vittatum) larval herbivory. We exposed squash 'receiver plants' to systemic HIPVs or volatiles from nondamaged plants. We then measured herbivore resistance by challenging 'receiver plants' with aboveground-feeding herbivores: adult beetles (A. vittatum) or squash bugs (Anasa tristis). We discovered belowground-damaged plants emitted more (E)-ß-ocimene, a key volatile from the systemic HIPV blend, than nondamaged controls, and that exposure to systemic HIPVs enhanced neighbouring plant resistance to aboveground squash bugs, but not adult beetles. Further investigations into the mechanism of interplant interaction revealed ß-ocimene alone can elicit plant resistance against squash bugs. Overall, our findings reveal a novel form of volatile-mediated interactions between plants spanning across aboveground-belowground plant systems.

Holo-analysis of the effects of xylo-oligosaccharides on broiler chicken performance.

1. Xylo-oligosaccharides (XOS) stimulate proliferation of beneficial bacteria in the gastrointestinal tract of broiler chickens. This results in enhanced utilisation of dietary non-starch polysaccharides and increased production of valuable short-chain fatty acids. However, these positive effects do not always translate into improved bird productive performance, with inconsistent performance responses observed between bird trials.2. A holo-analysis was conducted to determine the effects of supplementing XOS into broiler diets on bird feed intake, body weight gain, feed conversion and mortality. This was done by comparing the XOS supplemented treatment to the control treatment. A total of 53 studies which met the criteria for inclusion were used in the analysis.3. The results showed that XOS had a notable positive impact on bird mortality; XOS reduced mortality by 0.69% for every 1% increment in the control group. XOS supplementation induced a positive effect on the feed conversion ratio (FCR). However, the efficacy of XOS at improving FCR was dependent on the efficiency of the control group (performance of the flock), and the concentration of total arabinoxylan, protein and phytase in the diet. There were insufficient data points to predict the effect of XOS on body weight and feed intake.4. In conclusion, the holo-analysis revealed that supplementing XOS to broiler chicken diets reduces bird mortality. XOS can also improve FCR, but the scale of response is dependent on the diet composition and control flock performance. Additional studies are required to confirm the effects of XOS on body weight and feed intake.

Initial Results from a New College Substance Use Prevention Program Targeting Externalizing and Internalizing Traits.

Objective: College students engage in high rates of risky substance use. Standard college prevention strategies focus on providing feedback about current substance use behaviors and harm reduction strategies but do not address the underlying genetically-influenced risk factors impacting these behaviors. We created an online Personalized Feedback Program (PFP) for college students that targets genetically-influenced externalizing and internalizing risk pathways and provides personalized recommendations and campus resources. College students received personalized feedback on four risk domains (Sensation Seeking, Impulsivity, Extraversion, and Neuroticism). Methods: An open trial (n = 300) was conducted at a large public university in spring of 2021 to assess initial responses to the PFP and evaluate intentions related to future substance use and campus resource use. Results: 81% of students in the open trial reported they enjoyed the Personalized Feedback Program. Participants reported intending to use significantly more campus resources after completing the PFP. Among participants that drank, 39% reported they intended to decrease their alcohol consumption and 41% reported they intended to decrease the number of times they get drunk after completing the PFP; these intentions to reduce use after completing the PFP are higher than rates found in previous studies. Conclusion: Preliminary data indicate that the Personalized Feedback Program may be a complementary method to enhance current college substance use prevention programs.

Epidemiology of Intensive Care Patients Classified as a Third Sex in Australia and New Zealand.

BACKGROUND: Patient sex affects treatment and outcomes in critical illness. Previous studies of sex differences in critical illness compared female and male patients. In this study, we describe the group of patients classified as a third sex admitted to ICUs in Australia and New Zealand. RESEARCH QUESTION: What are the admission characteristics and outcomes of ICU patients classified as belonging to a third sex group compared with patients classified as female or male? STUDY DESIGN AND METHODS: Retrospective observational study of admissions to 200 ICUs, recorded in the Australian and New Zealand Intensive Care Society's Adult Patient Database from 2018 to 2022. We undertook mixed effect logistic regression to compare hospital mortality across the sex groups, adjusted for illness severity, diagnosis, treatment limitation, year, and hospital. RESULTS: We examined 892,161 admissions, of whom 525 (0.06%) were classified as third sex. Patients classified as third sex were represented across all diagnostic categories, jurisdictions, and hospital types. On average, they were younger than the groups classified as female (59.2 ± 20.0 vs 61.3 ± 18.4 years; P = .02) or male (63.2 ± 16.7 years; P < .001), respectively. Patients classified as third sex were more likely to be admitted after orthopedic surgery (10.1% third sex admissions [95% CI, 7.7%-13.0%]; 6.2% female [95% CI, 6.1%-6.3%]; 4.8% male [95% CI, 4.7%-4.9%]) and drug overdose (8.8% third sex admissions [95% CI, 6.5%-11.5%]; 4.2% female [95% CI, 4.1%-4.2%]; 3.1% male [95% CI, 3.0%-3.1%]). There was no difference in the adjusted hospital mortality of patients classified as third sex compared with the other groups. INTERPRETATION: Patients classified as third sex composed a small minority group of adult ICU patients. This group had a different diagnostic case mix but similar outcomes to the groups classified as female or male. Further characterizing a third sex group will require improved processes for recording sex and gender in health records.

Taxonomic and environmental distribution of bacterial amino acid auxotrophies.

Many microorganisms are auxotrophic-unable to synthesize the compounds they require for growth. With this work, we quantify the prevalence of amino acid auxotrophies across a broad diversity of bacteria and habitats. We predicted the amino acid biosynthetic capabilities of 26,277 unique bacterial genomes spanning 12 phyla using a metabolic pathway model validated with empirical data. Amino acid auxotrophy is widespread across bacterial phyla, but we conservatively estimate that the majority of taxa (78.4%) are able to synthesize all amino acids. Our estimates indicate that amino acid auxotrophies are more prevalent among obligate intracellular parasites and in free-living taxa with genomic attributes characteristic of 'streamlined' life history strategies. We predicted the amino acid biosynthetic capabilities of bacterial communities found in 12 unique habitats to investigate environmental associations with auxotrophy, using data compiled from 3813 samples spanning major aquatic, terrestrial, and engineered environments. Auxotrophic taxa were more abundant in host-associated environments (including the human oral cavity and gut) and in fermented food products, with auxotrophic taxa being relatively rare in soil and aquatic systems. Overall, this work contributes to a more complete understanding of amino acid auxotrophy across the bacterial tree of life and the ecological contexts in which auxotrophy can be a successful strategy.

Rib detection using pitch-catch ultrasound and classification algorithms for a novel ultrasound therapy device.

BACKGROUND: Noninvasive ultrasound (US) has been used therapeutically for decades, with applications in tissue ablation, lithotripsy, and physical therapy. There is increasing evidence that low intensity US stimulation of organs can alter physiological and clinical outcomes for treatment of health disorders including rheumatoid arthritis and diabetes. One major translational challenge is designing portable and reliable US devices that can be used by patients in their homes, with automated features to detect rib location and aid in efficient transmission of energy to organs of interest. This feasibility study aimed to assess efficacy in rib bone detection without conventional imaging, using a single channel US pitch-catch technique integrated into an US therapy device to detect pulsed US reflections from ribs. METHODS: In 20 healthy volunteers, the location of the ribs and spleen were identified using a diagnostic US imaging system. Reflected ultrasound signals were recorded at five positions over the spleen and adjacent ribs using the therapy device. Signals were classified as between ribs (intercostal), partially over a rib, or fully over a rib using four models: threshold-based time domain classification, threshold-based frequency domain classification, logistic regression, and support vector machine (SVM). RESULTS: SVM performed best overall on the All Participants cohort with accuracy up to 96.25%. All models' accuracies were improved by separating participants into two cohorts based on Body Mass Index (BMI) and re-fitting each model. After separation into Low BMI and High BMI cohorts, a simple time-thresholding approach achieved accuracies up to 100% and 93.75%, respectively. CONCLUSION: These results demonstrate that US reflection signal classification can accurately provide low complexity, real-time automated onboard rib detection and user feedback to advance at-home therapeutic US delivery.

Measurement of Healthy and Injured Triceps Surae Morphology.

Achilles tendon injuries occur throughout the lifespan and can negatively affect quality of life and overall health. Achilles tendinopathy is generally classified as an overuse injury associated with fusiform tendon thickening, neovascularization, and interstitial tendon degeneration. Current literature suggests these structural changes are associated with symptoms and lower physical activity levels, as well as symptoms and lower extremity function in the long term. Surgically and non-surgically managed Achilles tendon ruptures result in increased tendon cross-sectional area (CSA) and a lengthened Achilles tendon. Both structural outcomes have clinical implications, as larger CSA positively predicts function, whereas increased tendon lengthening predicts reduced function after Achilles tendon rupture. Given the relationship between structural changes associated with Achilles tendon injuries for both injury severity and injury recovery, it is critical to be able to quantify Achilles tendon structure reliably and accurately. Silbernagel's group has established a valid and reliable method for efficiently evaluating triceps surae muscle and tendon structure. In this protocol, B-mode musculoskeletal ultrasound imaging is used to measure triceps surae structure, including Achilles tendon thickness and CSA, soleus thickness, and the presence of additional findings (calcifications and bursitis). B-mode extended field-of-view is used to measure Achilles tendon length and gastrocnemius anatomical CSA. Finally, power Doppler is used to identify intratendinous neovascularization. Quantification of triceps surae structure allows for comparison between limbs as well as longitudinal changes in response to exercise and treatment for healthy individuals and those with Achilles tendon injuries. This protocol has been used in many research studies to date and proves valuable in understanding the relationship between tendon structure and injury development, severity, and recovery. As ultrasound devices are becoming more affordable and portable, this protocol proves promising as a clinical tool, given its quick and efficient methods.

The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease.

BACKGROUND: Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical procedures, therapies, and interventions. METHODS: MAxO incorporates logical structures that link MAxO terms to numerous other ontologies within the OBO Foundry. Term development involves a blend of manual and semi-automated processes. Additionally, we have generated annotations detailing diagnostic modalities for specific phenotypic abnormalities defined by the Human Phenotype Ontology (HPO). We introduce a web application, POET, that facilitates MAxO annotations for specific medical actions for diseases using the Mondo Disease Ontology. FINDINGS: MAxO encompasses 1,757 terms spanning a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. These terms annotate phenotypic features associated with specific disease (using HPO and Mondo). Presently, there are over 16,000 MAxO diagnostic annotations that target HPO terms. Through POET, we have created 413 MAxO annotations specifying treatments for 189 rare diseases. CONCLUSIONS: MAxO offers a computational representation of treatments and other actions taken for the clinical management of patients. Its development is closely coupled to Mondo and HPO, broadening the scope of our computational modeling of diseases and phenotypic features. We invite the community to contribute disease annotations using POET (https://poet.jax.org/). MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO). FUNDING: NHGRI 1U24HG011449-01A1 and NHGRI 5RM1HG010860-04.

Evaluating E. coli genome-scale metabolic model accuracy with high-throughput mutant fitness data.

The Escherichia coli genome-scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision-recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene-protein-reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high-throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

A Web-Based Intervention to Address Risk Factors for Maternal Morbidity and Mortality (MAMA LOVE): Development and Evaluation Study.

Background: Maternal mortality in the United States is a public health crisis and national emergency. Missed or delayed recognition of preventable life-threatening symptoms and untimely treatment of preventable high-risk medical conditions have been cited as key contributors to the nation's worsening mortality rates. Effective strategies are urgently needed to address this maternal health crisis, particularly for Black birthing populations. Morbidity and Mortality Assessment: Lifting Outcomes Via Education (MAMA LOVE) is a web-based platform that focuses on the identification of maternal morbidity and mortality risk factors. Objective: The purpose of this paper is to present the conceptualization, development, heuristics, and utility evaluation of the web-based maternal mortality risk assessment and educational tool MAMA LOVE. Methods: A user-centered design approach was used to gain feedback from clinical experts and potential end users to ensure that the tool would be effective among groups most at risk for maternal morbidity and mortality. A heuristic evaluation was conducted to evaluate usability and need within the current market. Algorithms describing key clinical, mental health, and social conditions were designed using digital canvas software (Miro) and incorporated into the final wireframes of the revised prototype. The completed version of MAMA LOVE was designed in Figma and built with the SurveyJS platform. Results: The creation of the MAMA LOVE tool followed three distinct phases: (1) the content development and creation of an initial prototype; (2) the feedback gathering and usability assessment of the prototype; and (3) the design, development, and testing of the final tool. The tool determines the corresponding course of action using the algorithm developed by the authors. A total of 38 issues were found in the heuristic evaluation of the web tool's initial prototype. Conclusions: Maternal morbidity and mortality is a public health crisis needing immediate effective interventions. In the current market, there are few digital resources available that focus specifically on the identification of dangerous symptoms and risk factors. MAMA LOVE is a tool that can address that need by increasing knowledge and providing resources and information that can be shared with health care professionals.