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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Floral architecture plays a pivotal role in developmental processes under genetic regulation and is also influenced by environmental cues. This affects the plant silique phenotype in Arabidopsis and grain yield in crops. Despite the relatively small number of family members of zinc finger homeodomain (ZF-HD) transcription factors (TFs) in plants, their biological role needs to be investigated to understand the molecular mechanisms associated with plant developmental processes. Therefore, we generated HB31SRDX and HB21SRDX repressor mutant lines to understand the functional role of ZF-HD TFs. The mutant lines showed severe defects in plant architecture, including increased branching number, reduced plant height, distorted floral phenotype, and short silique. We found that HB31 and HB21 are paralogs in Arabidopsis, and both positively regulate cell size-related genes, cell wall modification factor-related genes, and M-type MADS-box TF families. In addition, HB31 and HB21 are negatively associated with abiotic stress-related genes, vegetative-to-reproductive phase transition of meristem-related genes, and TCP and RAV TFs. microRNA164 (miR164), miR822, miR396, miR2934, and miR172 were downregulated, whereas miR169, miR398, miR399, and miR157 were upregulated in the two repressor lines. Phenotypic and molecular analyses demonstrated that the miR396/GRF modules regulated by HB31 and HB21 are involved in the plan floral architecture of Arabidopsis. The findings of this study will help elucidate the role of ZF-HD TFs in maintaining the floral architecture. [ABSTRACT FROM AUTHOR]

Background: Poor functional status is a key marker of morbidity, yet is not routinely captured in clinical encounters. We developed and evaluated the accuracy of a machine learning algorithm that leveraged electronic health record (EHR) data to provide a scalable process for identification of functional impairment. Methods: We identified a cohort of patients with an electronically captured screening measure of functional status (Older Americans Resources and Services ADL/IADL) between 2018 and 2020 (N = 6484). Patients were classified using unsupervised learning K means and t‐distributed Stochastic Neighbor Embedding into normal function (NF), mild to moderate functional impairment (MFI), and severe functional impairment (SFI) states. Using 11 EHR clinical variable domains (832 variable input features), we trained an Extreme Gradient Boosting supervised machine learning algorithm to distinguish functional status states, and measured prediction accuracies. Data were randomly split into training (80%) and test (20%) sets. The SHapley Additive Explanations (SHAP) feature importance analysis was used to list the EHR features in rank order of their contribution to the outcome. Results: Median age was 75.3 years, 62% female, 60% White. Patients were classified as 53% NF (n = 3453), 30% MFI (n = 1947), and 17% SFI (n = 1084). Summary of model performance for identifying functional status state (NF, MFI, SFI) was AUROC (area under the receiving operating characteristic curve) 0.92, 0.89, and 0.87, respectively. Age, falls, hospitalization, home health use, labs (e.g., albumin), comorbidities (e.g., dementia, heart failure, chronic kidney disease, chronic pain), and social determinants of health (e.g., alcohol use) were highly ranked features in predicting functional status states. Conclusion: A machine learning algorithm run on EHR clinical data has potential utility for differentiating functional status in the clinical setting. Through further validation and refinement, such algorithms can complement traditional screening methods and result in a population‐based strategy for identifying patients with poor functional status who need additional health resources. [ABSTRACT FROM AUTHOR]

Complex diseases have multifactorial etiologies making actionable diagnostic biomarkers difficult to identify. Diagnostic research must expand beyond single or a handful of genetic or epigenetic targets for complex disease and explore a broader system of biological pathways. With the objective to develop a diagnostic tool designed to analyze a comprehensive network of epigenetic profiles in complex diseases, we used publicly available DNA methylation data from over 2,400 samples representing 20 cell types and various diseases. This tool, rather than detecting differentially methylated regions at specific genes, measures the intra-individual methylation variability within gene promoters to identify global shifts away from healthy regulatory states. To assess this new approach, we explored three distinct questions: 1) Are profiles of epigenetic variability tissuespecific? 2) Do diseased tissues exhibit altered epigenetic variability compared to normal tissue? 3) Can epigenetic variability be detected in complex disease? Unsupervised clustering established that global epigenetic variability in promoter regions is tissue-specific and promoter regions that are the most epigenetically stable in a specific tissue are associated with genes known to be essential for its function. Furthermore, analysis of epigenetic variability in these most stable regions distinguishes between diseased and normal tissue in multiple complex diseases. Finally, we demonstrate the clinical utility of this new tool in the assessment of a multifactorial condition, male infertility. We show that epigenetic variability in purified sperm is correlated with live birth outcomes in couples undergoing intrauterine insemination (IUI), a common fertility procedure. Men with the least epigenetically variable promoters were almost twice as likely to father a child than men with the greatest number of epigenetically variable promoters. Interestingly, no such difference was identified in men undergoing in vitro fertilization (IVF), another common fertility procedure, suggesting this as a treatment to overcome higher levels of epigenetic variability when trying to conceive. [ABSTRACT FROM AUTHOR]

To understand the relationship between stressful work environments and patient care by assessing work conditions, burnout, and elements of the diagnostic process. Notes and transcripts of audiotaped encounters were assessed for verbal and written documentation related to psychosocial data, differential diagnosis, acknowledgement of uncertainty, and other diagnosis-relevant contextual elements using 5-point Likert scales in seven primary care physicians (PCPs) and 28 patients in urgent care settings. Encounter time spent vs time needed (time pressure) was collected from time stamps and clinician surveys. Study physicians completed surveys on stress, burnout, and work conditions using the Mini-Z survey. Physicians with high stress or burnout were less likely to record psychosocial information in transcripts and notes (psychosocial information noted in 0% of encounters in 4 high stress/burned-out physicians), whereas low stress physicians (n=3) recorded psychosocial information consistently in 67% of encounters. Burned-out physicians discussed a differential diagnosis in only 31% of encounters (low counts concentrated in two physicians) vs. in 73% of non-burned-out doctors' encounters. Burned-out and non-burned-out doctors spent comparable amounts of time with patients (about 25 min). Key diagnostic elements were seen less often in encounter transcripts and notes in burned-out urgent care physicians. [ABSTRACT FROM AUTHOR]

Individual neurons or muscle cells express many G-protein-coupled receptors (GPCRs) for neurotransmitters and neuropeptides, yet it remains unclear how cells integrate multiple GPCR signals that all must activate the same few G-proteins. We analyzed this issue in the Caenorhabditis elegans egg-laying system, where multiple GPCRs on muscle cells promote contraction and egg laying. We genetically manipulated individual GPCRs and G-proteins specifically in these muscle cells within intact animals and then measured egg laying and muscle calcium activity. Two serotonin GPCRs on the muscle cells, Gaq-coupled SER-1 and Gas-coupled SER-7, together promote egg laying in response to serotonin. We found that signals produced by either SER-1/Gaq or SER-7/Gas alone have little effect, but these two subthreshold signals combine to activate egg laying. We then transgenically expressed natural or designer GPCRs in the muscle cells and found that their subthreshold signals can also combine to induce muscle activity. However, artificially inducing strong signaling through just one of these GPCRs can be sufficient to induce egg laying. Knocking down Gaq and Gas in the egg-laying muscle cells induced egg-laying defects that were stronger than those of a SER-1/SER-7 double knockout, indicating that additional endogenous GPCRs also activate the muscle cells. These results show that in the egg-laying muscles multiple GPCRs for serotonin and other signals each produce weak effects that individually do not result in strong behavioral outcomes. However, they combine to produce sufficient levels of Gaq and Gas signaling to promote muscle activity and egg laying. [ABSTRACT FROM AUTHOR]

Diagnostic performance is uniquely challenging to measure, and providing feedback on diagnostic performance to catalyze diagnostic recalibration remains the exception to the rule in healthcare. Diagnostic accuracy, timeliness, and explanation to the patient are essential dimensions of diagnostic performance that each intersect with a variety of technical, contextual, cultural, and policy barriers. Setting aside assumptions about current constraints, we explore the future of diagnostic performance feedback by describing the "minimum viable products" and the "ideal state" solutions that can be envisioned for each of several important barriers. Only through deliberate and iterative approaches to breaking down these barriers can we improve recalibration and continuously drive the healthcare ecosystem towards diagnostic excellence. [ABSTRACT FROM AUTHOR]

The environment in which clinicians provide care and think about their patients is a crucial and undervalued component of the diagnostic process. In this paper, we propose a new conceptual model that links work conditions to clinician responses such as stress and burnout, which in turn impacts the quality of the diagnostic process and finally patient diagnostic outcomes. The mechanism for these interactions critically depends on the relationship between working memory (WM) and long-term memory (LTM), and ways WM and LTM interactions are affected by working conditions. We propose a conceptual model to guide interventions to improve work conditions, clinician reactions and ultimately diagnostic process, accuracy and outcomes. Improving diagnosis can be accomplished if we are able to understand, measure and increase our knowledge of the context of care. [ABSTRACT FROM AUTHOR]

Introduction: Sorghum (Sorghum bicolor (L.) Moench) is an agriculturally and economically important staple crop that has immense potential as a bioenergy feedstock due to its relatively high productivity on marginal lands. To capitalize on and further improve sorghum as a potential source of sustainable biofuel, it is essential to understand the genomic mechanisms underlying complex traits related to yield, composition, and environmental adaptations. Methods: Expanding on a recently developedmapping population, we generated de novo genome assemblies for 10 parental genotypes from this population and identified a comprehensive set of over 24 thousand large structural variants (SVs) and over 10.5 million single nucleotide polymorphisms (SNPs). Results: We show that SVs and nonsynonymous SNPs are enriched in different gene categories, emphasizing the need for long read sequencing in crop species to identify novel variation. Furthermore, we highlight SVs and SNPs occurring in genes and pathways with known associations to critical bioenergy-related phenotypes and characterize the landscape of genetic differences between sweet and cellulosic genotypes. Discussion: These resources can be integrated into both ongoing and future mapping and trait discovery for sorghum and its myriad uses including food, feed, bioenergy, and increasingly as a carbon dioxide removal mechanism. [ABSTRACT FROM AUTHOR]

Uncertainty is ubiquitous in medicine. Studies link intolerance of uncertainty to burnout, ineffective communication, cognitive bias, and inappropriate resource use. Little is known about how uncertainty manifests in the clinical learning environment. We aimed to explore the perceptions and experiences of uncertainty among residents and attendings. We conducted a mixed-methods study including a survey, semi-structured interviews, and ethnographic observations during rounds with residents and attendings at an academic medical center. The survey included three validated instruments: Physicians' Reaction to Uncertainty Scale; Maslach Burnout Inventory 2-item; and Educational Climate Inventory. 35/60 (58%) of eligible residents and 14/21 (67%) attendings completed the survey. Residents reported higher anxiety due to uncertainty than attendings, higher concern about bad outcomes, and greater reluctance to disclose uncertainty to patients. Residents reported increased symptoms of burnout (p <.05). Perceiving the learning environment as more competitive correlated with reluctance to disclose uncertainty (r = −0.44; p <.01). Qualitative themes included: recognizing and facing uncertainty, and consequences for the learning environment. Observations revealed senior clinicians have greater comfort acknowledging uncertainty. Medical curricula should be developed to promote recognition and acknowledgement of uncertainty. Greater acknowledgement of uncertainty, specifically by attendings and senior residents, may positively impact the clinical learning environment. [ABSTRACT FROM AUTHOR]

The plant‐sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2‐pyrone synthase gene from Gerbera hybrida (GhPS) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl‐CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP‐citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl‐CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12‐ACL1‐ACC1 using fed‐batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl‐CoA‐derived polyketides from low‐cost carbon sources. [ABSTRACT FROM AUTHOR]

In plants, vegetative and reproductive development are associated with agronomically important traits that contribute to grain yield and biomass. Zinc finger homeodomain (ZF-HD) transcription factors (TFs) constitute a relatively small gene family that has been studied in several model plants, including Arabidopsis thaliana L. and Oryza sativa L. The ZF-HD family members play important roles in plant growth and development, but their contribution to the regulation of plant architecture remains largely unknown due to their functional redundancy. To understand the gene regulatory network controlled by ZF-HD TFs, we analyzed multiple loss-of-function mutants of ZF-HD TFs in Arabidopsis that exhibited morphological abnormalities in branching and flowering architecture. We found that ZF-HD TFs, especially HB34, negatively regulate the expression of miR157 and positively regulate SQUAMOSA PROMOTER BINDING–LIKE 10 (SPL10), a target of miR157. Genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq) analysis revealed that miR157D and SPL10 are direct targets of HB34, creating a feed-forward loop that constitutes a robust miRNA regulatory module. Network motif analysis contains overrepresented coherent type IV feedforward motifs in the amiR zf-HD and hbq mutant background. This finding indicates that miRNA-mediated ZF-HD feedforward modules modify branching and inflorescence architecture in Arabidopsis. Taken together, these findings reveal a guiding role of ZF-HD TFs in the regulatory network module and demonstrate its role in plant architecture in Arabidopsis. [ABSTRACT FROM AUTHOR]

Background: Studies consider the clinical encounter as linear, comprising six phases (opening, problem presentation, history-taking, physical examination, diagnosis, treatment and closing). This study utilizes formal conversation analysis to explore patient-physician interactions and understanding diagnostic utterances during these phases. Methods: This study is a qualitative sub-analysis that explores how the diagnosis process, along with diagnostic uncertainty, are addressed during 28 urgent care visits. We analyzed physicians' hypothesis-generation process by focusing on: location of diagnostic utterances during the encounter; whether certain/uncertain diagnostic utterances were revised throughout the encounter; and how physicians tested their hypothesis-generation and managed uncertainty. We recruited 7 primary care physicians (PCPs) and their 28 patients from Brigham and Women's Hospital (BWH) in 3 urgent care settings. Encounters were audiotaped, transcribed, and coded using NVivo12 qualitative data analysis software. Data were analyzed inductively and deductively, using formal content and conversation analysis. Results: We identified 62 diagnostic communication utterances in 12 different clinical situations. In most (24/28, 86%) encounters, the diagnosis process was initiated before the diagnosis phase (57% during history taking and 64% during physical examination). In 17 encounters (61%), a distinct diagnosis phase was not observed. Findings show that the diagnosis process is nonlinear in two ways. First, nonlinearity was observed when diagnostic utterances occurred throughout the encounter, with the six encounter phases overlapping, integrating elements of one phase with another. Second, nonlinearity was noted with respect to the resolution of diagnostic uncertainty, with physicians acknowledging uncertainty when explaining their diagnostic reasoning, even during brief encounters. Conclusions: Diagnosis is often more interactive and nonlinear, and expressions of diagnostic assessments can occur at any point during an encounter, allowing more flexible and potentially more patient-centered communication. These findings are relevant for physicians' training programs and helping clinicians improve their communication skills in managing uncertain diagnoses. [ABSTRACT FROM AUTHOR]

Pharmacy Several publications have made the case for improving diagnosis-related education in schools of pharmacy; and courses on clinical reasoning, physical examination, and other aspects of diagnosis are now appearing (see Supplementary Appendix B) [[25]], [[26]], [[27]]. Current diagnosis education is inadequate Achieving competency in diagnosis is a primary focus in many health professions; however, the focus is relatively narrow, aimed primarily at conveying facts to students without ensuring expertise in the diagnostic process itself. Keywords: competence; competency; diagnosis; diagnostic error; health professions education; medical education; nursing education; pharmacy education EN competence competency diagnosis diagnostic error health professions education medical education nursing education pharmacy education 166 175 10 05/12/22 20220501 NES 220501 Introduction "Education is the most powerful weapon which you can use to change the world."-Nelson Mandela Improving diagnosis education represents a critically important approach to reduce harm related to diagnostic error in practice [[1]]. [Extracted from the article]

There is debate regarding whether most articulatory planning occurs offline (rather than online) and whether the products of off-line processing are stored in a separate articulatory buffer until a large enough chunk is ready for production. This hypothesis predicts that delayed naming conditions should reduce not only onset RTs but also word durations because articulatory plans will be buffered and kept ready. We have tested this hypothesis with young control speakers, an aphasic speaker , and an age and education-matched speaker, using repetition, reading and picture-naming tasks. Contrary to the off-line hypothesis, delayed conditions strongly reduced onset RTs, but had no benefit for word durations. In fact, we found small effects in the opposite direction. Moreover, frequency and imageability affected word durations even in delayed conditions, consistent with articulatory processing continuing on-line. The same pattern of results was found in CS and in control participants, strengthening confidence in our results. There is debate regarding whether most articulatory planning occurs offline (rather than online) and whether the results of off-line processing are stored in a separate articulatory buffer until a large enough chunk is ready for production. This hypothesis predicts that delayed naming conditions should reduce not only onset RTs but also word durations because articulatory plans will be buffered and kept ready. We have tested young control speakers, an aphasic speaker, and an age and education matched speaker, using repetition, reading and picture naming tasks. Contrary to the off-line hypothesis, delayed conditions strongly reduced onset RTs, but had no benefit for word durations. In fact, we found small effects in the opposite direction. Moreover, frequency and imageability affected word durations even in delayed conditions, consistent with articulatory processing continuing on-line. The same pattern of results was found in CS and in control participants, strengthening confidence in our results. [ABSTRACT FROM AUTHOR]

The future of diagnosis - where are we going? The field of diagnosis and our understanding of the diagnostic process have significantly evolved over the last several decades. Building on the use of technology in diagnosis feedback, Schmidt and colleagues propose a novel use for digital decision support (DDS) modeled on deliberate practice and aligned with our understanding of the diagnostic process [[14]]. [Extracted from the article]

Background: The U.S. military conflicts in Iraq and Afghanistan had the most casualties since Vietnam with more than 53,000 wounded in action. Novel injury mechanisms, such as improvised explosive devices, and higher rates of survivability compared with previous wars led to a new pattern of combat injuries. The purpose of the present study was to use latent class analysis (LCA) to identify combat injury profiles among U.S. military personnel who survived serious wounds. Methods: A total of 5,227 combat casualty events with an Injury Severity Score (ISS) of 9 or greater that occurred in Iraq and Afghanistan from December 2002 to July 2019 were identified from the Expeditionary Medical Encounter Database for analysis. The Barell Injury Diagnosis Matrix was used to classify injuries into binary variables by site and type of injury. LCA was employed to identify injury profiles that accounted for co-occurring injuries. Injury profiles were described and compared by demographic, operational, and injury-specific variables. Results: Seven injury profiles were identified and defined as: (1) open wounds (18.8%), (2) Type 1 traumatic brain injury (TBI)/facial injuries (14.2%), (3) disseminated injuries (6.8%), (4) Type 2 TBI (15.4%), (5) lower extremity injuries (19.8%), (6) burns (7.4%), and (7) chest and/or abdominal injuries (17.7%). Profiles differed by service branch, combat location, year of injury, injury mechanism, combat posture at the time of injury, and ISS. Conclusion: LCA identified seven distinct and interpretable injury profiles among U.S. military personnel who survived serious combat injuries in Iraq or Afghanistan. These findings may be of interest to military medical planners as resource needs are evaluated and projected for future conflicts, and medical professionals involved in the rehabilitation of wounded service members. [ABSTRACT FROM AUTHOR]

Main conclusion: SorghumBase provides a community portal that integrates genetic, genomic, and breeding resources for sorghum germplasm improvement. Public research and development in agriculture rely on proper data and resource sharing within stakeholder communities. For plant breeders, agronomists, molecular biologists, geneticists, and bioinformaticians, centralizing desirable data into a user-friendly hub for crop systems is essential for successful collaborations and breakthroughs in germplasm development. Here, we present the SorghumBase web portal (), a resource for the sorghum research community. SorghumBase hosts a wide range of sorghum genomic information in a modular framework, built with open-source software, to provide a sustainable platform. This initial release of SorghumBase includes: (1) five sorghum reference genome assemblies in a pan-genome browser; (2) genetic variant information for natural diversity panels and ethyl methanesulfonate (EMS)-induced mutant populations; (3) search interface and integrated views of various data types; (4) links supporting interconnectivity with other repositories including genebank, QTL, and gene expression databases; and (5) a content management system to support access to community news and training materials. SorghumBase offers sorghum investigators improved data collation and access that will facilitate the growth of a robust research community to support genomics-assisted breeding. [ABSTRACT FROM AUTHOR]

Background: Internal Medicine (IM) programs offer elective subspecialty rotations in which residents may enroll to supplement the experience and knowledge obtained during general inpatient and outpatient rotations. Objective evidence that these rotations provide enhanced subspecialty specific knowledge is lacking. The purpose of this study was to determine whether exposure to an endocrinology subspecialty rotation enhanced a resident's endocrinology-specific knowledge beyond that otherwise acquired during IM residency. Methods: Data were collected on internal medicine resident scores on the American College of Physicians Internal Medicine In-Training Examinations (IM-ITE) for calendar years 2012 through 2018 along with enrollment data as to whether residents had completed an endocrinology subspecialty rotation prior to sitting for a given IM-ITE. Three hundred and six internal medicine residents in the University of Minnesota Internal Medicine residency program with 664 scores total on the IM-ITE for calendar years 2012 through 2018. Percentage of correct answers on the overall and endocrine subspecialty content areas on the IM-ITE for each exam were determined and the association between prior exposure to an endocrinology subspecialty rotation and percentage of correct answers in the endocrinology content area was analyzed using generalized linear mixed-effects models. Results: Two hundred and thirty-three residents (76%) completed an endocrinology subspecialty rotation at some point during their residency; 121 (40%) residents had at least one IM-ITE both before and after exposure to an endocrine subspecialty rotation. Exposure to an endocrinology subspecialty rotation exhibited a positive association with the expected IM-ITE percent correct on the endocrinology content area (5.5% predicted absolute increase). Advancing year of residency was associated with a predicted increase in overall IM-ITE score but did not improve the predictive model for endocrine subspecialty score. Conclusions: Completion of an endocrinology subspecialty elective was associated with an increase in resident endocrine specific knowledge as assessed by the IM-ITE. These findings support the value of subspecialty rotations in enhancing a resident's subspecialty specific medical knowledge. [ABSTRACT FROM AUTHOR]

Summary Genome sequencing projects annotate protein-coding gene models with multiple transcripts, aiming to represent all of the available transcript evidence. However, downstream analyses often operate on only one representative transcript per gene locus, sometimes known as the canonical transcript. To choose canonical transcripts, Transcript Ranking and Canonical Election (TRaCE) holds an 'election' in which a set of RNA-seq samples rank transcripts by annotation edit distance. These sample-specific votes are tallied along with other criteria such as protein length and InterPro domain coverage. The winner is selected as the canonical transcript, but the election proceeds through multiple rounds of voting to order all the transcripts by relevance. Based on the set of expression data provided, TRaCE can identify the most common isoforms from a broad expression atlas or prioritize alternative transcripts expressed in specific contexts. Availability and implementation Transcript ranking code can be found on GitHub at {{ https://github.com/warelab/TRaCE }}. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Background Errors in reasoning are a common cause of diagnostic error. However, it is difficult to improve performance partly because providers receive little feedback on diagnostic performance. Examining means of providing consistent feedback and enabling continuous improvement may provide novel insights for diagnostic performance. Methods We developed a model for improving diagnostic performance through feedback using a six-step qualitative research process, including a review of existing models from within and outside of medicine, a survey, semistructured interviews with individuals working in and outside of medicine, the development of the new model, an interdisciplinary consensus meeting, and a refinement of the model. Results We applied theory and knowledge from other fields to help us conceptualise learning and comparison and translate that knowledge into an applied diagnostic context. This helped us develop a model, the Diagnosis Learning Cycle, which illustrates the need for clinicians to be given feedback about both their confidence and reasoning in a diagnosis and to be able to seamlessly compare diagnostic hypotheses and outcomes. This information would be stored in a repository to allow accessibility. Such a process would standardise diagnostic feedback and help providers learn from their practice and improve diagnostic performance. This model adds to existing models in diagnosis by including a detailed picture of diagnostic reasoning and the elements required to improve outcomes and calibration. Conclusion A consistent, standard programme of feedback that includes representations of clinicians' confidence and reasoning is a common element in non-medical fields that could be applied to medicine. Adapting this approach to diagnosis in healthcare is a promising next step. This information must be stored reliably and accessed consistently. The next steps include testing the Diagnosis Learning Cycle in clinical settings. [ABSTRACT FROM AUTHOR]

Background and Objectives: The Rural Physician Associate Program (RPAP) at the University of Minnesota Medical School (UMMS) is a 9-month rural longitudinal integrated clerkship (LIC) for third-year medical students built on a foundation of family medicine. The purpose of this study was to examine the relationships between participation in the RPAP program and the desired workforce outcomes of practice in Minnesota, primary care specialty (particularly family medicine), and rural practice.Methods: We analyzed workforce outcomes for UMMS graduates who completed postgraduate training between 1975 and 2017, comparing RPAP participants (n=1,217) to noparticipants (n=7,928). We identified graduates through internal UMMS databases linked to the American Medical Association (AMA) Physician Masterfile and the National Provider Identifier (NPI) registry. We identified workforce outcomes of rural practice, practice in Minnesota, primary care specialty, and family medicine specialty based on practice specialty and practice location data available through the AMA and NPI data sets.Results: Proportionally, more RPAP graduates practice in state (65.7% vs 54.4%, P<.01), in primary care (69.0% vs 33.4%, P<.01), in family medicine (61.1% vs 17.3%, P<.01), and rurally (41.2% vs 13.9%, P<.01) than non-RPAP graduates.Conclusions: We demonstrate a significant association between participation in RPAP and a career in family medicine, rural practice, and primary care, all outcomes that promote meeting urgent rural workforce needs. [ABSTRACT FROM AUTHOR]

Sepsis carries a high mortality in the United States. Hospitals across the country are working to find new ways to recognize, treat, and streamline care for patients with sepsis. At an academic medical center in the Midwest, a quality improvement project was developed using a sepsis rapid response team with physician associates/assistants (PAs) and NPs. This improved hospital adherence to sepsis evaluation and order set use from 48% to 86%. The added evaluation of the patient by a PA or NP, along with ensuring adherence to the sepsis order set, made an effective first step to improve care of patients with sepsis in this hospital. [ABSTRACT FROM AUTHOR]

We describe the case of Jessica Barnett, an adolescent girl whose repeated episodes of syncope and near-syncope were ascribed to a seizure or anxiety disorder. The correct diagnoses (congenital long QT syndrome; arrythmogenic right ventricular cardiomyopathy) were established by autopsy and genetic studies only after her death at age 17. The perspective of the family is presented, along with an analysis of what went right and what went wrong in Jessica’s diagnostic journey. Key lessons in this case include the value of family as engaged members of the diagnostic team, that a ‘hyperventilation test’ should not be used to exclude cardiac origins of syncope or pre-syncope, and the inherent challenges in the diagnosis of the long QT syndrome. [ABSTRACT FROM AUTHOR]

Background: Regular physical activity and exercise provide many health benefits. These health benefits are mediated in large part through cardiorespiratory fitness and muscular strength. As most individuals have not had an assessment of their personal cardiorespiratory fitness or muscular strength we investigated if measurements of cardiorespiratory fitness and muscular strength would influence an individual's subsequent self-reported exercise and physical activity. Methods: Volunteer subjects at a State Fair were randomized in 1:1 parallel fashion to control and intervention groups. The baseline Exercise Vital Sign (EVS) and type of physical activity were obtained from all subjects. The intervention group received estimated maximum oxygen uptake (VO2max) using a step test and muscular strength using a hand grip dynamometer along with age-specific norms for both measurements. All subjects were provided exercise recommendations. Follow up surveys were conducted at 3, 6 and 12 months regarding their EVS and physical activity. Results: One thousand three hundred fifteen individuals (656 intervention, 659 control) were randomized with 1 year follow up data obtained from 823 subjects (62.5%). Baseline mean EVS was 213 min/week. No change in EVS was found in either group at follow-up (p = 0.99). Subjects who were less active at baseline (EVS < 150) did show an increase in EVS (86 to 146) at 6 months (p < 0.05). At 3 months the intervention group increased resistance training (29.1 to 42.8%) compared to controls (26.3 to 31.4%) (p < 0.05). Lifestyle physical activity increased in the intervention group at 3 months (27.7 to 29.1%) and 6 months (25%) whereas it declined in the control group at 3 months (24.4 to 20.1%) and 6 months (18.7%) (p < 0.05). Conclusion: Providing VO2max estimates and grip strength did not produce an increase in overall physical activity. The EVS and exercise recommendations did however produce an increase in physical activity in less active individuals. In a very active population the VO2max estimate and measured grip strength did increase lifestyle activity and resistance training. Wider adoption of these measures could be effective in promoting physical activity and resistance training. Trial registration: clinicaltrials.gov NCT03518931 Registered 05/08/2018 -retrospectively registered. [ABSTRACT FROM AUTHOR]