Isogenic human iPSC Parkinson's model shows nitrosative stress-induced dysfunction in MEF2-PGC1α transcription.

Parkinson's disease (PD) is characterized by loss of A9 dopaminergic (DA) neurons in the substantia nigra pars compacta (SNpc). An association has been reported between PD and exposure to mitochondrial toxins, including environmental pesticides paraquat, maneb, and rotenone. Here, using a robust, patient-derived stem cell model of PD allowing comparison of A53T α-synuclein (α-syn) mutant cells and isogenic mutation-corrected controls, we identify mitochondrial toxin-induced perturbations in A53T α-syn A9 DA neurons (hNs). We report a pathway whereby basal and toxin-induced nitrosative/oxidative stress results in S-nitrosylation of transcription factor MEF2C in A53T hNs compared to corrected controls. This redox reaction inhibits the MEF2C-PGC1α transcriptional network, contributing to mitochondrial dysfunction and apoptotic cell death. Our data provide mechanistic insight into gene-environmental interaction (GxE) in the pathogenesis of PD. Furthermore, using small-molecule high-throughput screening, we identify the MEF2C-PGC1α pathway as a therapeutic target to combat PD.

Development of Scaffold-Free Three-Dimensional Cholangiocyte Organoids to Study the Progression of Primary Sclerosing Cholangitis.

Organoids are novel in vitro models to study intercellular cross talk between the different types of cells in disease pathophysiology. To better understand the underlying mechanisms driving the progression of primary sclerosing cholangitis (PSC), scaffold-free multicellular three-dimensional cholangiocyte organoids (3D-CHOs) were developed using primary liver cells derived from normal subjects and patients with PSC. Human liver samples from healthy donors and patients with PSC were used to isolate primary cholangiocytes [epithelial cell adhesion molecule (EpCam)+/ cytokeratin-19+], liver endothelial cells (CD31+), and hepatic stellate cells (HSCs; CD31-/CD68-/desmin+/vitamin A+). 3D-CHOs were formed using cholangiocytes, HSCs, and liver endothelial cells, and kept viable for up to 1 month. Isolated primary cell lines and 3D-CHOs were further characterized by immunofluorescence, quantitative RT-PCR, and transmission electron microscopy. Transcription profiles for cholangiocytes (SOX9, CFTR, EpCAM, AE, SCT, and SCTR), fibrosis (ACTA2, COL1A1, DESMIN, and TGFß1), angiogenesis (PECAM, VEGF, CDH5, and vWF), and inflammation (IL-6 and TNF-α) confirmed PSC phenotypes of 3D-CHOs. Because cholangiocytes develop a neuroendocrine phenotype and express neuromodulators, confocal immunofluorescence was used to demonstrate localization of the neurokinin-1 receptor within cytokeratin-19+ cholangiocytes and desmin+ HSCs. Moreover, 3D-CHOs from patients with PSC confirmed PSC phenotypes with up-regulated neurokinin-1 receptor, tachykinin precursor 1, and down-regulated membrane metalloendopeptidase. Scaffold-free multicellular 3D-CHOs showed superiority as an in vitro model in mimicking PSC in vivo phenotypes compared with two-dimensional cell culture, which can be used in PSC disease-related research.

Disparities Associated With Electronic Behavioral Alerts for Safety and Violence Concerns in the Emergency Department.

STUDY OBJECTIVE: Although electronic behavioral alerts are placed as an alert flag in the electronic health record to notify staff of previous behavioral and/or violent incidents in emergency departments (EDs), they have the potential to reinforce negative perceptions of patients and contribute to bias. We provide characterization of ED electronic behavioral alerts using electronic health record data across a large, regional health care system. METHODS: We conducted a retrospective cross-sectional study of adult patients presenting to 10 adult EDs within a Northeastern United States health care system from 2013 to 2022. Electronic behavioral alerts were manually screened for safety concerns and then categorized by the type of concern. In our patient-level analyses, we included patient data at the time of the first ED visit where an electronic behavioral alert was triggered or, if a patient had no electronic behavioral alerts, the earliest visit in the study period. We performed a mixed-effects regression analysis to identify patient-level risk factors associated with safety-related electronic behavioral alert deployment. RESULTS: Of the 2,932,870 ED visits, 6,775 (0.2%) had associated electronic behavioral alerts across 789 unique patients and 1,364 unique electronic behavioral alerts. Of the encounters with electronic behavioral alerts, 5,945 (88%) were adjudicated as having a safety concern involving 653 patients. In our patient-level analysis, the median age for patients with safety-related electronic behavioral alerts was 44 years (interquartile range 33 to 55 years), 66% were men, and 37% were Black. Visits with safety-related electronic behavioral alerts had higher rates of discontinuance of care (7.8% vs 1.5% with no alert; P<.001) as defined by the patient-directed discharge, left-without-being-seen, or elopement-type dispositions. The most common topics in the electronic behavioral alerts were physical (41%) or verbal (36%) incidents with staff or other patients. In the mixed-effects logistic analysis, Black non-Hispanic patients (vs White non-Hispanic patients: adjusted odds ratio 2.60; 95% confidence interval [CI] 2.13 to 3.17), aged younger than 45 (vs aged 45-64 years: adjusted odds ratio 1.41; 95% CI 1.17 to 1.70), male (vs female: adjusted odds ratio 2.09; 95% CI 1.76 to 2.49), and publicly insured patients (Medicaid: adjusted odds ratio 6.18; 95% CI 4.58 to 8.36; Medicare: adjusted odds ratio 5.63; 95% CI 3.96 to 8.00 vs commercial) were associated with a higher risk of a patient having at least 1 safety-related electronic behavioral alert deployment during the study period. CONCLUSION: In our analysis, younger, Black non-Hispanic, publicly insured, and male patients were at a higher risk of having an ED electronic behavioral alert. Although our study is not designed to reflect causality, electronic behavioral alerts may disproportionately affect care delivery and medical decisions for historically marginalized populations presenting to the ED, contribute to structural racism, and perpetuate systemic inequities.

Development and Characterization of Human Primary Cholangiocarcinoma Cell Lines.

Cholangiocarcinoma (CCA) is the second most common primary liver tumor and is associated with late diagnosis, limited treatment options, and a 5-year survival rate of around 30%. CCA cell lines were first established in 1971, and since then, only 70 to 80 CCA cell lines have been established. These cell lines have been essential in basic and translational research to understand and identify novel mechanistic pathways, biomarkers, and disease-specific genes. Each CCA cell line has unique characteristics, reflecting a specific genotype, sex-related properties, and patient-related signatures, making them scientifically and commercially valuable. CCA cell lines are crucial in the use of novel technologies, such as three-dimensional organoid models, which help to model the tumor microenvironment and cell-to-cell crosstalk between tumor-neighboring cells. This review highlights crucial information on CCA cell lines, including: i) type of CCA (eg, intra- or extrahepatic), ii) isolation source (eg, primary tumor or xenograft), iii) chemical digestion method (eg, trypsin or collagenase), iv) cell-sorting method (colony isolation or removal of fibroblasts), v) maintenance-medium choice (eg, RPMI or Dulbecco's modified Eagle's medium), vi) cell morphology (eg, spindle or polygonal shape), and vii) doubling time of cells.

Deep learning prediction of hospital readmissions for asthma and COPD.

QUESTION: Severe asthma and COPD exacerbations requiring hospitalization are linked to increased disease morbidity and healthcare costs. We sought to identify Electronic Health Record (EHR) features of severe asthma and COPD exacerbations and evaluate the performance of four machine learning (ML) and one deep learning (DL) model in predicting readmissions using EHR data. STUDY DESIGN AND METHODS: Observational study between September 30, 2012, and December 31, 2017, of patients hospitalized with asthma and COPD exacerbations. RESULTS: This study included 5,794 patients, 1,893 with asthma and 3,901 with COPD. Patients with asthma were predominantly female (n = 1288 [68%]), 35% were Black (n = 669), and 25% (n = 479) were Hispanic. Black (44 vs. 33%, p = 0.01) and Hispanic patients (30 vs. 24%, p = 0.02) were more likely to be readmitted for asthma. Similarly, patients with COPD readmissions included a large percentage of Blacks (18 vs. 10%, p < 0.01) and Hispanics (8 vs. 5%, p < 0.01). To identify patients at high risk of readmission index hospitalization data of a subset of 2,682 patients, 777 with asthma and 1,905 with COPD, was analyzed with four ML models, and one DL model. We found that multilayer perceptron, the DL method, had the best sensitivity and specificity compared to the four ML methods implemented in the same dataset. INTERPRETATION: Multilayer perceptron, a deep learning method, had the best performance in predicting asthma and COPD readmissions, demonstrating that EHR and deep learning integration can improve high-risk patient detection.

Predicting relations between SOAP note sections: The value of incorporating a clinical information model.

Physician progress notes are frequently organized into Subjective, Objective, Assessment, and Plan (SOAP) sections. The Assessment section synthesizes information recorded in the Subjective and Objective sections, and the Plan section documents tests and treatments to narrow the differential diagnosis and manage symptoms. Classifying the relationship between the Assessment and Plan sections has been suggested to provide valuable insight into clinical reasoning. In this work, we use a novel human-in-the-loop pipeline to classify the relationships between the Assessment and Plan sections of SOAP notes as a part of the n2c2 2022 Track 3 Challenge. In particular, we use a clinical information model constructed from both the entailment logic expected from the aforementioned Challenge and the problem-oriented medical record. This information model is used to label named entities as primary and secondary problems/symptoms, events and complications in all four SOAP sections. We iteratively train separate Named Entity Recognition models and use them to annotate entities in all notes/sections. We fine-tune a downstream RoBERTa-large model to classify the Assessment-Plan relationship. We evaluate multiple language model architectures, preprocessing parameters, and methods of knowledge integration, achieving a maximum macro-F1 score of 82.31%. Our initial model achieves top-2 performance during the challenge (macro-F1: 81.52%, competitors' macro-F1 range: 74.54%-82.12%). We improved our model by incorporating post-challenge annotations (S&O sections), outperforming the top model from the Challenge. We also used Shapley additive explanations to investigate the extent of language model clinical logic, under the lens of our clinical information model. We find that the model often uses shallow heuristics and nonspecific attention when making predictions, suggesting language model knowledge integration requires further research.

Three-Dimensional Organoids as a Model to Study Nonalcoholic Fatty Liver Disease.

Despite the rising prevalence of nonalcoholic fatty liver disease (NAFLD), the underlying disease pathophysiology remains unclear. There is a great need for an efficient and reliable "human" in vitro model to study NAFLD and the progression to nonalcoholic steatohepatitis (NASH), which will soon become the leading indication for liver transplantation. Here, we review the recent developments in the use of three-dimensional (3D) liver organoids as a model to study NAFLD and NASH pathophysiology and possible treatments. Various techniques that are currently used to make liver organoids are discussed, such as the use of induced pluripotent stem cells versus primary cell lines and human versus murine cells. Moreover, methods for inducing lipid droplet accumulation and fibrosis to model NAFLD are explored. Finally, the limitations specific to the 3D organoid model for NAFLD/NASH are reviewed, highlighting the need for further development of multilineage models to include hepatic nonparenchymal cells and immune cells. The ultimate goal is to be able to accurately recapitulate the complex liver microenvironment in which NAFLD develops and progresses to NASH.

Nucleation and growth inhibition of biological minerals by cementum attachment protein-derived peptide (CAP-pi).

Biomineralization is a highly regulated process where proteins/peptides-crystal interactions contribute to the shaping, phasing and aggregation of minerals. We have identified and synthesized a cementum attachment protein-derived peptide (CAP-pi), which corresponds to amino acids 40-53 of the N-terminal CAP domain (MASSDEDGTNGGAS) and its phosphorylated variant (MASpSpDEDGTNGGASp) (CAP-pip). The peptide is composed of polar and negatively charged amino acids, which are disordered, according to in silico analysis. Our results show that CAP-pi inhibits hydroxyapatite (HA) formation and growth. However, it possesses low capacity to inhibit calcium oxalate crystal growth. CAP-pip showed a stronger inhibitory effect on the formation and growth of HA. As well as a high capacity to inhibit calcium oxalate monohydrate growth, mainly due to adsorption on specific growth faces. Small peptides have many advantages over the full-size protein, including low-cost production and modulation characteristics that allow for structural changes. Our findings suggest that CAP-pip-derived peptide could possess therapeutic potential to prevent or treat pathological calcifications such as renal stones and vascular calcification.

MEF2D haploinsufficiency downregulates the NRF2 pathway and renders photoreceptors susceptible to light-induced oxidative stress.

Gaining mechanistic insight into interaction between causative factors of complex multifactorial diseases involving photoreceptor damage might aid in devising effective therapies. Oxidative stress is one of the potential unifying mechanisms for interplay between genetic and environmental factors that contribute to photoreceptor pathology. Interestingly, the transcription factor myocyte enhancer factor 2d (MEF2D) is known to be important in photoreceptor survival, as knockout of this transcription factor results in loss of photoreceptors in mice. Here, using a mild light-induced retinal degeneration model, we show that the diminished MEF2D transcriptional activity in Mef2d+/- retina is further reduced under photostimulation-induced oxidative stress. Reactive oxygen species cause an aberrant redox modification on MEF2D, consequently inhibiting transcription of its downstream target, nuclear factor (erythroid-derived 2)-like 2 (NRF2). NRF2 is a master regulator of phase II antiinflammatory and antioxidant gene expression. In the Mef2d heterozygous mouse retina, NRF2 is not up-regulated to a normal degree in the face of light-induced oxidative stress, contributing to accelerated photoreceptor cell death. Furthermore, to combat this injury, we found that activation of the endogenous NRF2 pathway using proelectrophilic drugs rescues photoreceptors from photo-induced oxidative stress and may therefore represent a viable treatment for oxidative stress-induced photoreceptor degeneration, which is thought to contribute to some forms of retinitis pigmentosa and age-related macular degeneration.

Recurrent chimeric fusion RNAs in non-cancer tissues and cells.

Gene fusions and their products (RNA and protein) were once thought to be unique features to cancer. However, chimeric RNAs can also be found in normal cells. Here, we performed, curated and analyzed nearly 300 RNA-Seq libraries covering 30 different non-neoplastic human tissues and cells as well as 15 mouse tissues. A large number of fusion transcripts were found. Most fusions were detected only once, while 291 were seen in more than one sample. We focused on the recurrent fusions and performed RNA and protein level validations on a subset. We characterized these fusions based on various features of the fusions, and their parental genes. They tend to be expressed at higher levels relative to their parental genes than the non-recurrent ones. Over half of the recurrent fusions involve neighboring genes transcribing in the same direction. A few sequence motifs were found enriched close to the fusion junction sites. We performed functional analyses on a few widely expressed fusions, and found that silencing them resulted in dramatic reduction in normal cell growth and/or motility. Most chimeras use canonical splicing sites, thus are likely products of 'intergenic splicing'. We also explored the implications of these non-pathological fusions in cancer and in evolution.

Patient-Centered Decision Support: Formative Usability Evaluation of Integrated Clinical Decision Support With a Patient Decision Aid for Minor Head Injury in the Emergency Department.

BACKGROUND: The Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions. OBJECTIVE: Our objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns. METHODS: User-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage. RESULTS: The Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual clinician practice styles. The resultant tool includes a patient injury evaluator based on the Canadian CT Head Rule and provides patient specific risks using pictographs with natural frequencies and cues for discussion about patient concerns. CONCLUSIONS: This tool was designed to align evidence-based practices about CT in minor head injury patients. It establishes trust, empowers active participation, and addresses patient concerns and uncertainty about their condition. We hypothesize that, when implemented, the Concussion or Brain Bleed app will support-not hinder-the clinician-patient relationship, safely reduce CT use, and improve the patient experience of care.

Risk factors for readmission of patients with amputation to acute care from inpatient rehabilitation: A retrospective cohort study.

INTRODUCTION: Amputation is a major condition that requires inpatient rehabilitation. Some research has been conducted to explore the risk factors for readmission of patients from inpatient rehabilitation facilities to acute care hospitals. However, few studies have included patients with amputation in the study population. OBJECTIVE: To identify the risk factors for readmission of patients with amputation to acute care hospitals from an inpatient rehabilitation facility. DESIGN: Retrospective cohort study. SETTING: An acute rehabilitation hospital associated with a community-based tertiary medical center. PATIENTS: A retrospective review of 156 independent admissions of 145 patients from June 2019 to July 2022. MAIN OUTCOME MEASURE: The study outcome measure was readmission to acute care from an acute rehabilitation unit. RESULTS: Of the 156 independent admissions, the readmission rate was 19% (29/156). The most common cause of transfer was incision-site complications (9/29, 31%), including wound infection and wound dehiscence. Patients with amputation readmitted to acute care are more likely to be receiving dialysis (p < .001), have a longer length of stay in acute care before admission to the rehabilitation facility (p = .039), and have a lower Section GG score on admission (p < .001). Age, sex, ethnicity, amputation level, and history of diabetes mellitus were not associated with acute care hospital readmission. The logistic regression model revealed that patients being on dialysis was the only significant risk factor predictive of readmission to acute care (odds ratio [OR] 4.82, p = .006). CONCLUSIONS: This study showed that incision-site complications were the most common cause of disruption in inpatient rehabilitation via acute hospital readmission in patients with amputation. Being on dialysis was associated with a higher risk of readmission to acute care hospitals. Based on the results of this study, specific rehabilitation plans might be required for patients with amputation who carry certain risk factors to reduce rehospitalization to the acute care unit.

The role of rat prelimbic cortex in decision making.

The frontal cortex plays a critical role in decision-making. One specific frontal area, the anterior cingulate cortex, has been identified as crucial for setting a threshold for how much evidence is needed before a choice is made (Domenech & Dreher, 2010). Threshold is a key concept in drift diffusion models, a popular framework used to understand decision-making processes. Here, we investigated the role of the prelimbic cortex, part of the rodent cingulate cortex, in decision making. Male and female rats learned to choose between stimuli associated with high and low value rewards. Females learned faster, were more selective in their responses, and integrated information about the stimuli more quickly. By contrast, males learned more slowly and showed a decrease in their decision thresholds during choice learning. Inactivating the prelimbic cortex in female and male rats sped up decision making without affecting choice accuracy. Drift diffusion modeling found selective effects of prelimbic cortex inactivation on the decision threshold, which was reduced with increasing doses of the GABA-A agonist muscimol. Stimulating the prelimbic cortex through mu opioid receptors slowed the animals' choice latencies and increased the decision threshold. These findings provide the first causal evidence that the prelimbic cortex directly influences decision processes. Additionally, they suggest possible sex-based differences in early choice learning.

Tolerability of electrodiagnostic studies in patients: a prospective study.

Introduction: Nerve conduction study (NCS) and electromyography (EMG) are electrodiagnostic studies that are highly tolerated by patients despite their nature of causing pain and discomfort. However, few studies have focused on the true tolerability of these procedures in patients. This study aimed to determine the true tolerance rate of NCS and EMG in patient populations and the factors that might be associated with them. Methods: Participants scheduled for electrodiagnostic studies were prospectively recruited between March 2023 and September 2023. After completion of the study, the physicians completed a questionnaire on each patient's tolerance of the studies. Results: Of the 103 patients enrolled in the study, 98 were able to tolerate both tests, and 5 patients were intolerant to 1 or both tests. The overall tolerance rate of NCS and EMG was 95.1% (0.951, 95% CI 0.897 to 0.981). Age, sex, ethnicity, the type of NCS performed and the type of EMG performed were not associated with NCS or EMG intolerance. Conclusion: Most patients tolerated the NCS and EMG; however, a small percentage of patients were intolerant. Clinicians should recognise the intolerance of certain patients when introducing and performing electrodiagnostic tests.

Reconstitution of human PDAC using primary cells reveals oncogenic transcriptomic features at tumor onset.

Animal studies have demonstrated the ability of pancreatic acinar cells to transform into pancreatic ductal adenocarcinoma (PDAC). However, the tumorigenic potential of human pancreatic acinar cells remains under debate. To address this gap in knowledge, we expand sorted human acinar cells as 3D organoids and genetically modify them through introduction of common PDAC mutations. The acinar organoids undergo dramatic transcriptional alterations but maintain a recognizable DNA methylation signature. The transcriptomes of acinar organoids are similar to those of disease-specific cell populations. Oncogenic KRAS alone do not transform acinar organoids. However, acinar organoids can form PDAC in vivo after acquiring the four most common driver mutations of this disease. Similarly, sorted ductal cells carrying these genetic mutations can also form PDAC, thus experimentally proving that PDACs can originate from both human acinar and ductal cells. RNA-seq analysis reveal the transcriptional shift from normal acinar cells towards PDACs with enhanced proliferation, metabolic rewiring, down-regulation of MHC molecules, and alterations in the coagulation and complement cascade. By comparing PDAC-like cells with normal pancreas and PDAC samples, we identify a group of genes with elevated expression during early transformation which represent potential early diagnostic biomarkers.

Autonomy versus automation: perceptions of nonmydriatic camera choice for teleretinal screening in an urban safety net clinic.

OBJECTIVE: Teleretinal screening with nonmydriatic cameras has been presented as a means of increasing the number of patients assessed for diabetic retinopathy in urban safety net clinics. It has been hypothesized that automated nonmydriatic cameras may improve screening rates by reducing the learning curve for camera use. In this article, we examine the impact of introducing automated nonmydriatic cameras to urban safety net clinics whose photographers had previously used manual cameras. MATERIALS AND METHODS: We evaluated the impact of manual and automated digital nonmydriatic cameras on teleretinal screening using a quantitative analysis of readers' image quality ratings as well as a qualitative analysis, through in-depth interviews, of photographers' experiences. RESULTS: With the manual camera, 68% of images were rated "adequate" or better, including 24% rated "good" and 20% rated "excellent." With the automated camera, 61% were rated "adequate" or better, including 9% rated "good" and 0% rated "excellent." Photographers expressed frustration with their inability to control image-taking settings with the automated camera, which led to unexpected delays. CONCLUSIONS: For safety net clinics in which medical assistants are already trained to take photographs for diabetic retinopathy screening with a manual camera, the introduction of automated cameras may lead to frustration and paradoxically contribute to increased patient wait times. When photographers have achieved a high degree of aptitude with manual cameras and value the control they have over camera features, the introduction of automated cameras should be approached with caution and may require extensive training to increase user acceptability.

Mucinous Cystic Neoplasms of the Liver: Epidemiology, Diagnosis, and Management.

Mucinous cystic neoplasms (MCNs) are rare tumors of the liver, occasionally seen in the biliary tree. Epidemiologic data are limited by their indolence and recent changes to diagnostic criteria. They are considered premalignant lesions capable of invasive behavior. While their etiology remains unknown, their female predominance, age of onset, and hormonally responsive ovarian-type stroma suggest ectopic organogenesis during embryologic development. MCNs can typically be recognized on imaging; yet, invasiveness is often indeterminate, and percutaneous tissue biopsy has shown limited value. Therefore, complete excision is recommended for all lesions as focal malignant transformation and metastatic disease has been reported.

Predicting physician departure with machine learning on EHR use patterns: A longitudinal cohort from a large multi-specialty ambulatory practice.

Physician turnover places a heavy burden on the healthcare industry, patients, physicians, and their families. Having a mechanism in place to identify physicians at risk for departure could help target appropriate interventions that prevent departure. We have collected physician characteristics, electronic health record (EHR) use patterns, and clinical productivity data from a large ambulatory based practice of non-teaching physicians to build a predictive model. We use several techniques to identify possible intervenable variables. Specifically, we used gradient boosted trees to predict the probability of a physician departing within an interval of 6 months. Several variables significantly contributed to predicting physician departure including tenure (time since hiring date), panel complexity, physician demand, physician age, inbox, and documentation time. These variables were identified by training, validating, and testing the model followed by computing SHAP (SHapley Additive exPlanation) values to investigate which variables influence the model's prediction the most. We found these top variables to have large interactions with other variables indicating their importance. Since these variables may be predictive of physician departure, they could prove useful to identify at risk physicians such who would benefit from targeted interventions.

Exploring the Role of YAP1 and TAZ in Pancreatic Acinar Cells and the Therapeutic Potential of VT-104 in Pancreatic Inflammation.

Increasing evidences have linked the hippo pathway with the fibroinflammatory diseases. We generated a series of genetic knockout mice for targeting the key components of Hippo pathway to examine the individual effects of YAP1 and TAZ on pancreatic inflammation and evaluated the therapeutic potential of the YAP1/TAZ inhibitor VT-104. Mice with acinar-specific knockout of YAP1/TAZ did not exhibit any histological abnormalities in the pancreas. LATS1/2 deficiency induced acinar-to-ductal metaplasia, immune cell infiltration and fibroblast activation, which were rescued by the homozygous knockout YAP1, but not TAZ. Additionally, treatment with VT-104 also decreased pathological alterations induced by deletions of LATS1 and LATS2 in acinar cells. Our findings highlight the critical role of YAP1 in modulating pancreatic inflammation and demonstrate that VT-104 holds therapeutic potential to mitigate pancreatitis-associated pathological manifestations. Further exploration is necessary to unravel the underlying mechanisms and translate these insights into clinical applications.

Computational phenotypes for patients with opioid-related disorders presenting to the emergency department.

OBJECTIVE: We aimed to discover computationally-derived phenotypes of opioid-related patient presentations to the ED via clinical notes and structured electronic health record (EHR) data. METHODS: This was a retrospective study of ED visits from 2013-2020 across ten sites within a regional healthcare network. We derived phenotypes from visits for patients ≥18 years of age with at least one prior or current documentation of an opioid-related diagnosis. Natural language processing was used to extract clinical entities from notes, which were combined with structured data within the EHR to create a set of features. We performed latent dirichlet allocation to identify topics within these features. Groups of patient presentations with similar attributes were identified by cluster analysis. RESULTS: In total 82,577 ED visits met inclusion criteria. The 30 topics were discovered ranging from those related to substance use disorder, chronic conditions, mental health, and medical management. Clustering on these topics identified nine unique cohorts with one-year survivals ranging from 84.2-96.8%, rates of one-year ED returns from 9-34%, rates of one-year opioid event 10-17%, rates of medications for opioid use disorder from 17-43%, and a median Carlson comorbidity index of 2-8. Two cohorts of phenotypes were identified related to chronic substance use disorder, or acute overdose. CONCLUSIONS: Our results indicate distinct phenotypic clusters with varying patient-oriented outcomes which provide future targets better allocation of resources and therapeutics. This highlights the heterogeneity of the overall population, and the need to develop targeted interventions for each population.