Neuropeptide and serotonin co-transmission sets the activity pattern in the C. elegans egg-laying circuit.

Neurons typically release both a neurotransmitter and one or more neuropeptides, but how these signals are integrated within neural circuits to generate and tune behaviors remains poorly understood. We studied how the two hermaphrodite-specific neurons (HSNs) activate the egg-laying circuit of Caenorhabditis elegans by releasing both the neurotransmitter serotonin and NLP-3 neuropeptides. Egg laying occurs in a temporal pattern with approximately 2-min active phases, during which eggs are laid, separated by approximately 20-min inactive phases, during which no eggs are laid. To understand how serotonin and NLP-3 neuropeptides together help produce this behavior pattern, we identified the G-protein-coupled receptor neuropeptide receptor 36 (NPR-36) as an NLP-3 neuropeptide receptor using genetic and molecular experiments. We found that NPR-36 is expressed in, and promotes egg laying within, the egg-laying muscle cells, the same cells where two serotonin receptors also promote egg laying. During the active phase, when HSN activity is high, we found that serotonin and NLP-3 neuropeptides each have a different effect on the timing of egg laying. During the inactive phase, HSN activity is low, which may result in release of only serotonin, yet mutants lacking either serotonin or nlp-3 signaling have longer inactive phases. This suggests that NLP-3 peptide signaling may persist through the inactive phase to help serotonin signaling terminate the inactive phase. We propose a model for neural circuit function in which multiple signals with short- and long-lasting effects compete to generate and terminate persistent internal states, thus patterning a behavior over tens of minutes.

Digital supervision in the clinical learning environment: Characterizing teamwork in the electronic health record.

BACKGROUND: Attending physicians in academic hospitals work in supervisory team structures with medical residents to provide patient care. How attendings utilize the electronic health record (EHR) to support learning through supervision is not well understood. OBJECTIVE: To compare EHR behavior on teaching versus direct care, including evidence of supervisory calibration to learners. METHODS: Cross-sectional study analysis of EHR metadata from 1721 shifts of hospital medicine faculty at a large, urban academic medical center, January to June 2022. Measures included total EHR time per shift, EHR time outside shift, and time spent on: note-writing, note review/attestation, order entry, and other clinical review. We assessed within physician differences across these service types and used multilevel modeling to determine whether these behaviors varied with resident physicians' experience, accounting for physician-specific signature behavior patterns. RESULTS: Attendings spent substantially less time in the EHR while on teaching service than on direct service (129 vs. 240 min; p < .001) and apportioned their work differently throughout the day. Physicians were less behaviorally consistent and varied more than their peers when on teaching service. Attendings calibrated their supervision to learners. Attendings logged 12.7% less EHR time when paired with more senior residents than postgraduate year 2 (PGY2) residents (137 vs. 120 min, p = .002). PGY1 presence was also associated with reduced EHR time, suggesting some delegation of supervision to senior trainees. CONCLUSION: EHR behaviors on teaching service are highly variable and differ substantially from direct care; a lack of consistency suggests important opportunities to establish best practices for EHR-based supervision and create an effective clinical learning environment.

Empowering Third-Year Medical Students to Detect Bias and Medical Misinformation Online via Experiential Learning of "Lateral Reading," A Fact-Checker's Technique.

Problem: Misleading health information is detrimental to public health. Even physicians can be misled by biased health information; however, medical students and physicians are not taught some of the most effective techniques for identifying bias and misinformation online. Intervention: Using the stages of Kolb's experiential learning cycle as a framework, we aimed to teach 117 third-year students at a United States medical school to apply a fact-checking technique for identifying bias and misinformation called "lateral reading" through a 50-minute learning cycle in a 90-minute class. Each student's concrete experience was to independently read a biased article and rate its credibility, demonstrating their baseline skills at identifying bias. Students were given structured opportunities for reflective observation through individual and large group discussion. Students were guided through abstract conceptualization to determine techniques and frameworks utilized by fact checkers, specifically "lateral reading"-utilizing the internet to research the background of the author, organization, and citations using independent sources before exploring the article itself in depth. Students' active experimentation included re-rating the credibility of the same article and discussing further implications with classmates and instructors. Context: In January 2020, sessions were offered to third-year medical students during their required, longitudinal transition-to-residency course. Impact: Compared to baseline, when using lateral reading, students deemed the article less credible. Students' active experimentation changed whether they identified the organization and sources behind the article as credible. Notably, 86% (53/62) of students who viewed the organization positively pre-intervention did not describe the organization positively post intervention. Similarly, 66% (36/55) of students who cited the sources as positive pre-exercise changed their assessment after the exercise. While three students mentioned the author negatively pre-intervention, none of the 21 students who described the author in a negative fashion post-intervention described the author negatively pre-intervention. Positively describing the organization, author, or sources pre-intervention correlated with differences in credibility rating after the intervention. These findings indicate that teaching students to read laterally may increase their ability to detect bias in online medical information. Lessons Learned: Further research is needed to determine whether students who learned lateral reading via experiential learning will apply this skill in their education and career. Additionally, research should assess whether this skill helps future physicians counter bias and misinformation in ways that improve health.

Gender differences in factors associated with rural health care practice in Minnesota.

PURPOSE: To understand gender differences in factors affecting rural health care workforce to inform the development of effective policies and recruitment strategies to address rural health care workforce shortages. METHODS: A cross-sectional survey of health care professionals (including Advanced practice registered nurses (APRNs), physicians, physician assistants (PAs), and registered nurses (RNs)) in Minnesota was administered by the Minnesota Department of Health from October 18, 2021, to July 25, 2022, during their professional license renewal. The main outcome was whether or not the respondent was practicing in a rural area. The effects of factors associated with rural practice were estimated using binary logistic regression models, and subsequently subgroup analysis was conducted by gender across the four health care professions. FINDINGS: Results show that although there were significant gender differences in some factors (growing up in a rural area and family considerations were more likely to influence women's decisions than men's, whereas men were more likely to be influenced by the prospect of having autonomy and broad scope of practice than women), these differences became insignificant when the four health care professionals were analyzed separately suggesting that overall gender differences observed were almost entirely explained by profession differences. CONCLUSIONS: Gender differences do not significantly influence the factors impacting rural practice. However, being raised in a rural environment emerges as the most influential predictor of rural practice underscoring the importance of involving rural residents of all genders in health care practice.

Lessons in clinical reasoning - pitfalls, myths, and pearls: a case of persistent dysphagia and patient partnership.

OBJECTIVES: Diagnostic excellence underscores the patient-centered diagnosis and patient engagement in the diagnostic process. In contrast to a patient-centered diagnosis, a doctor-centered diagnosis with a lack of patient engagement may inhibit the diagnostic process due to the lack of responsibility, disrupted information, and increased effect of cognitive biases, particularly in a situation where multiple physicians are involved. In this paper, we suggest a promising idea to enhance patient engagement in the diagnostic process by using written information by a patient about their perspective and experience, which can fill the gaps needed for diagnosis that doctors cannot find alone. CASE PRESENTATION: A 38-year-old woman developed chest pain, which gradually worsened during the following two years. For two years, she was evaluated in multiple departments; however, no definitive diagnosis was made, and her condition did not improve. During this evaluation, she searched her symptoms and image findings online. She reached a possible diagnosis of 'esophageal achalasia.' Still, she could not tell her concerns to any physicians because she felt that her concerns were not correctly recognized, although she showed her notes that her symptoms were recorded. She finally consulted the department of internal medicine, where her notes and previous test results were thoroughly reviewed. The final diagnosis of esophageal achalasia was confirmed. CONCLUSIONS: Doctors must organize an environment where patients can freely express their thoughts, emotions, and ideas regarding their diagnosis. Cogenerating visit notes using patient input through written communication can be a promising idea to facilitate patient engagement in the diagnostic process.

High-quality chromosome scale genome assemblies of two important Sorghum inbred lines, Tx2783 and RTx436.

Sorghum bicolor (L.) Moench is a significant grass crop globally, known for its genetic diversity. High quality genome sequences are needed to capture the diversity. We constructed high-quality, chromosome-level genome assemblies for two vital sorghum inbred lines, Tx2783 and RTx436. Through advanced single-molecule techniques, long-read sequencing and optical maps, we improved average sequence continuity 19-fold and 11-fold higher compared to existing Btx623 v3.0 reference genome and obtained 19 and 18 scaffolds (N50 of 25.6 and 14.4) for Tx2783 and RTx436, respectively. Our gene annotation efforts resulted in 29 612 protein-coding genes for the Tx2783 genome and 29 265 protein-coding genes for the RTx436 genome. Comparative analyses with 26 plant genomes which included 18 sorghum genomes and 8 outgroup species identified around 31 210 protein-coding gene families, with about 13 956 specific to sorghum. Using representative models from gene trees across the 18 sorghum genomes, a total of 72 579 pan-genes were identified, with 14% core, 60% softcore and 26% shell genes. We identified 99 genes in Tx2783 and 107 genes in RTx436 that showed functional enrichment specifically in binding and metabolic processes, as revealed by the GO enrichment Pearson Chi-Square test. We detected 36 potential large inversions in the comparison between the BTx623 Bionano map and the BTx623 v3.1 reference sequence. Strikingly, these inversions were notably absent when comparing Tx2783 or RTx436 with the BTx623 Bionano map. These inversion were mostly in the pericentromeric region which is known to have low complexity regions and harder to assemble and suggests the presence of potential artifacts in the public BTx623 reference assembly. Furthermore, in comparison to Tx2783, RTx436 exhibited 324 883 additional Single Nucleotide Polymorphisms (SNPs) and 16 506 more Insertions/Deletions (INDELs) when using BTx623 as the reference genome. We also characterized approximately 348 nucleotide-binding leucine-rich repeat (NLR) disease resistance genes in the two genomes. These high-quality genomes serve as valuable resources for discovering agronomic traits and structural variation studies.

Large Language Model Influence on Management Reasoning: A Randomized Controlled Trial.

Importance: Large language model (LLM) artificial intelligence (AI) systems have shown promise in diagnostic reasoning, but their utility in management reasoning with no clear right answers is unknown. Objective: To determine whether LLM assistance improves physician performance on open-ended management reasoning tasks compared to conventional resources. Design: Prospective, randomized controlled trial conducted from 30 November 2023 to 21 April 2024. Setting: Multi-institutional study from Stanford University, Beth Israel Deaconess Medical Center, and the University of Virginia involving physicians from across the United States. Participants: 92 practicing attending physicians and residents with training in internal medicine, family medicine, or emergency medicine. Intervention: Five expert-developed clinical case vignettes were presented with multiple open-ended management questions and scoring rubrics created through a Delphi process. Physicians were randomized to use either GPT-4 via ChatGPT Plus in addition to conventional resources (e.g., UpToDate, Google), or conventional resources alone. Main Outcomes and Measures: The primary outcome was difference in total score between groups on expert-developed scoring rubrics. Secondary outcomes included domain-specific scores and time spent per case. Results: Physicians using the LLM scored higher compared to those using conventional resources (mean difference 6.5 %, 95% CI 2.7-10.2, p<0.001). Significant improvements were seen in management decisions (6.1%, 95% CI 2.5-9.7, p=0.001), diagnostic decisions (12.1%, 95% CI 3.1-21.0, p=0.009), and case-specific (6.2%, 95% CI 2.4-9.9, p=0.002) domains. GPT-4 users spent more time per case (mean difference 119.3 seconds, 95% CI 17.4-221.2, p=0.02). There was no significant difference between GPT-4-augmented physicians and GPT-4 alone (-0.9%, 95% CI -9.0 to 7.2, p=0.8). Conclusions and Relevance: LLM assistance improved physician management reasoning compared to conventional resources, with particular gains in contextual and patient-specific decision-making. These findings indicate that LLMs can augment management decision-making in complex cases. Trial registration: ClinicalTrials.gov Identifier: NCT06208423; https://classic.clinicaltrials.gov/ct2/show/NCT06208423.

Decisions to Practice in Rural Areas Among Mental Health Care Professionals.

This survey study assesses factors associated with mental health care professionals choosing to practice in rural locations.

Beyond thinking fast and slow: Implications of a transtheoretical model of clinical reasoning and error on teaching, assessment, and research.

From dual process to a family of theories known collectively as situativity, both micro and macro theories of cognition inform our current understanding of clinical reasoning (CR) and error. CR is a complex process that occurs in a complex environment, and a nuanced, expansive, integrated model of these theories is necessary to fully understand how CR is performed in the present day and in the future. In this perspective, we present these individual theories along with figures and descriptive cases for purposes of comparison before exploring the implications of a transtheoretical model of these theories for teaching, assessment, and research in CR and error.

Homophily and social mixing in a small community: Implications for infectious disease transmission.

Community mixing patterns by sociodemographic traits can inform the risk of epidemic spread among groups, and the balance of in- and out-group mixing affects epidemic potential. Understanding mixing patterns can provide insight about potential transmission pathways throughout a community. We used a snowball sampling design to enroll people recently diagnosed with SARS-CoV-2 in an ethnically and racially diverse county and asked them to describe their close contacts and recruit some contacts to enroll in the study. We constructed egocentric networks of the participants and their contacts and assessed age-mixing, ethnic/racial homophily, and gender homophily. The total size of the egocentric networks was 2,544 people (n = 384 index cases + n = 2,160 recruited peers or other contacts). We observed high rates of in-group mixing among ethnic/racial groups compared to the ethnic/racial proportions of the background population. Black or African-American respondents interacted with a wider range of ages than other ethnic/racial groups, largely due to familial relationships. The egocentric networks of non-binary contacts had little age diversity. Black or African-American respondents in particular reported mixing with older or younger family members, which could increase the risk of transmission to vulnerable age groups. Understanding community mixing patterns can inform infectious disease risk, support analyses to predict epidemic size, or be used to design campaigns such as vaccination strategies so that community members who have vulnerable contacts are prioritized.

Influence of a Large Language Model on Diagnostic Reasoning: A Randomized Clinical Vignette Study.

Importance: Diagnostic errors are common and cause significant morbidity. Large language models (LLMs) have shown promise in their performance on both multiple-choice and open-ended medical reasoning examinations, but it remains unknown whether the use of such tools improves diagnostic reasoning. Objective: To assess the impact of the GPT-4 LLM on physicians' diagnostic reasoning compared to conventional resources. Design: Multi-center, randomized clinical vignette study. Setting: The study was conducted using remote video conferencing with physicians across the country and in-person participation across multiple academic medical institutions. Participants: Resident and attending physicians with training in family medicine, internal medicine, or emergency medicine. Interventions: Participants were randomized to access GPT-4 in addition to conventional diagnostic resources or to just conventional resources. They were allocated 60 minutes to review up to six clinical vignettes adapted from established diagnostic reasoning exams. Main Outcomes and Measures: The primary outcome was diagnostic performance based on differential diagnosis accuracy, appropriateness of supporting and opposing factors, and next diagnostic evaluation steps. Secondary outcomes included time spent per case and final diagnosis. Results: 50 physicians (26 attendings, 24 residents) participated, with an average of 5.2 cases completed per participant. The median diagnostic reasoning score per case was 76.3 percent (IQR 65.8 to 86.8) for the GPT-4 group and 73.7 percent (IQR 63.2 to 84.2) for the conventional resources group, with an adjusted difference of 1.6 percentage points (95% CI -4.4 to 7.6; p=0.60). The median time spent on cases for the GPT-4 group was 519 seconds (IQR 371 to 668 seconds), compared to 565 seconds (IQR 456 to 788 seconds) for the conventional resources group, with a time difference of -82 seconds (95% CI -195 to 31; p=0.20). GPT-4 alone scored 15.5 percentage points (95% CI 1.5 to 29, p=0.03) higher than the conventional resources group. Conclusions and Relevance: In a clinical vignette-based study, the availability of GPT-4 to physicians as a diagnostic aid did not significantly improve clinical reasoning compared to conventional resources, although it may improve components of clinical reasoning such as efficiency. GPT-4 alone demonstrated higher performance than both physician groups, suggesting opportunities for further improvement in physician-AI collaboration in clinical practice.

Characteristics differentiating problem representation synthesis between novices and experts.

BACKGROUND: Formulating a thoughtful problem representation (PR) is fundamental to sound clinical reasoning and an essential component of medical education. Aside from basic structural recommendations, little consensus exists on what characterizes high-quality PRs. OBJECTIVES: To elucidate characteristics that distinguish PRs created by experts and novices. METHODS: Early internal medicine residents (novices) and inpatient teaching faculty (experts) from two academic medical centers were given two written clinical vignettes and were instructed to write a PR and three-item differential diagnosis for each. Deductive content analysis described the characteristics comprising PRs. An initial codebook of characteristics was refined iteratively. The primary outcome was differences in characteristic frequencies between groups. The secondary outcome was characteristics correlating with diagnostic accuracy. Mixed-effects regression with random effects modeling compared case-level outcomes by group. RESULTS: Overall, 167 PRs were analyzed from 30 novices and 54 experts. Experts included 0.8 fewer comorbidities (p < .01) and 0.6 more examination findings (p = .01) than novices on average. Experts were less likely to include irrelevant comorbidities (odds ratio [OR] = 0.4, 95% confidence interval [CI] = 0.2-0.8) or a diagnosis (OR = 0.3, 95% CI = 0.1-0.8) compared with novices. Experts encapsulated clinical data into higher-order terms (e.g., sepsis) than novices (p < .01) while including similar numbers of semantic qualifiers (SQs). Regardless of expertise level, PRs following a three-part structure (e.g., demographics, temporal course, and clinical syndrome) and including temporal SQs were associated with diagnostic accuracy (p < .01). CONCLUSIONS: Compared with novices, expert PRs include less irrelevant data and synthesize information into higher-order concepts. Future studies should determine whether targeted educational interventions for PRs improve diagnostic accuracy.

Consensus-Derived Recommended Skills for Transition to Residency Courses.

PURPOSE: Transition to residency (TTR) courses facilitate the medical student-residency transition and are an integral part of senior medical student training. The authors established a common set of skills for TTR courses, and an expected level of entrustment students should demonstrate in each skill on TTR course completion. METHOD: A modified Delphi approach was used with 3 survey iterations between 2020 and 2022 to establish skills to be included in a TTR course. Nine TTR experts suggested general candidate skills and conducted a literature search to ensure no vital skills were missed. A stakeholder panel was solicited from email lists of TTR educators, residency program directors, and residents at the panelists' institutions. Consensus was defined as more than 75% of participants selecting a positive inclusion response. An entrustment questionnaire asked panelists to assign a level of expected entrustment to each skill, with 1 indicating observation only and 6 indicating perform independently. RESULTS: The stakeholder panel initially consisted of 118 respondents with representation across educational contexts and clinical specialties. Response rates were 54% in iteration 2, 42% in iteration 3, and 33% on the entrustment questionnaire. After 3 iterations, 54 skills met consensus and were consolidated into 37 final skills categorized into 18 clinical skills (e.g., assessment and management of inpatient concerns), 14 communication skills (e.g., delivering serious news or having difficult conversations), 4 personal and professional skills (e.g., prioritization of clinical tasks), and 1 procedural skill (mask ventilation). Median entrustment levels were reported for all skills, with 19 skills having a level of expected entrustment of 4 (perform independently and have all findings double-checked). CONCLUSIONS: These consensus skills can serve as the foundation of a standardized national TTR curriculum framework. Entrustment guidance may help educational leaders optimize training and allocation of resources for TTR curriculum development and implementation.

Phonological impairments in Hindi aphasics: Error analyses and cross-linguistic comparisons.

We assessed phonological and apraxic impairments in Hindi persons with aphasia (PwA) and compared them to Italian PwA reported in previous studies. Overall, we found strong similarities. Phonological errors were present across production tasks (repetition, reading and naming), most errors were non-lexical and, among those, a majority involved individual phonemes. There were significant effects of length, but not frequency. Hindi PwA, like the Italian PwA, showed strong effects of syllabic structure, with most errors occurring on consonants and weak syllabic positions, preserving syllable structure and simplifying phonemes or syllabic templates. These similarities were modulated by some language-specific patterns. Vowel insertions were more common in Hindi, possibly due to the presence of a central vowel, and segmental simplifications concentrated on marked aspiration and retroflection features. We hope our study will encourage further research in Hindi and other Indian languages. This will improve clinical diagnosis and our understanding of cross-linguistic differences.

The inseparability of context and clinical reasoning.

Early descriptions of clinical reasoning have described a dual process model that relies on analytical or nonanalytical approaches to develop a working diagnosis. In this classic research, clinical reasoning is portrayed as an individual-driven cognitive process based on gathering information from the patient encounter, forming mental representations that rely on previous experience and engaging developed patterns to drive working diagnoses and management plans. Indeed, approaches to patient safety, as well as teaching and assessing clinical reasoning focus on the individual clinician, often ignoring the complexity of the system surrounding the diagnostic process. More recent theories and evidence portray clinical reasoning as a dynamic collection of processes that takes place among and between persons across clinical settings. Yet, clinical reasoning, taken as both an individual and a system process, is insufficiently supported by theories of cognition based on individual clinicals and lacks the specificity needed to describe the phenomenology of clinical reasoning. In this review, we reinforce that the modern healthcare ecosystem - with its people, processes and technology - is the context in which health care encounters and clinical reasoning take place.

Exploring Competency-Based Medical Education Through the Lens of the UME-GME Transition: A Qualitative Study.

PURPOSE: Competency-based medical education (CBME) represents a shift to a paradigm with shared definitions, explicit outcomes, and assessments of competence. The groundwork has been laid to ensure all learners achieve the desired outcomes along the medical education continuum using the principles of CBME. However, this continuum spans the major transition from undergraduate medical education (UME) to graduate medical education (GME) that is also evolving. This study explores the experiences of medical educators working to use CBME assessments in the context of the UME-GME transition and their perspectives on the existing challenges. METHOD: This study used a constructivist-oriented qualitative methodology. In-depth, semistructured interviews of UME and GME leaders in CBME were performed between February 2019 and January 2020 via Zoom. When possible, each interviewee was interviewed by 2 team members, one with UME and one with GME experience, which allowed follow-up questions to be pursued that reflected the perspectives of both UME and GME educators more fully. A multistep iterative process of thematic analysis was used to analyze the transcripts and identify patterns across interviews. RESULTS: The 9 interviewees represented a broad swath of UME and GME leadership positions, though most had an internal medicine training background. Analysis identified 4 overarching themes: mistrust (a trust chasm exists between UME and GME); misaligned goals (the residency selection process is antithetical to CBME); inadequate communication (communication regarding competence is infrequent, often unidirectional, and lacks a shared language); and inflexible timeframes (current training timeframes do not account for individual learners' competency trajectories). CONCLUSIONS: Despite the mutual desire and commitment to move to CBME across the continuum, mistrust, misaligned goals, inadequate communication, and inflexible timeframes confound such efforts of individual schools and programs. If current efforts to improve the UME-GME transition address the themes identified, educators may be more successful implementing CBME along the continuum.