Validation of an Electronic Health Record-Based Machine Learning Model Compared to Clinical Risk Scores for Gastrointestinal Bleeding.

BACKGROUND & AIMS: Guidelines recommend use of risk stratification scores for patients presenting with gastrointestinal bleeding (GIB) to identify very-low-risk patients eligible for discharge from emergency departments. Machine learning models may outperform existing scores and can be integrated within the electronic health record (EHR) to provide real-time risk assessment without manual data entry. We present the first EHR-based machine learning model for GIB. METHODS: The training cohort comprised 2,546 patients and internal validation of 850 patients presenting with overt GIB (hematemesis, melena, hematochezia) to emergency departments of 2 hospitals from 2014-2019. External validation was performed on 926 patients presenting to a different hospital with the same EHR from 2014-2019. The primary outcome was a composite of red-blood-cell transfusion, hemostatic intervention (endoscopic, interventional radiologic, or surgical), and 30-day all-cause mortality. We used structured data fields in the EHR available within 4 hours of presentation and compared performance of machine learning models to current guideline-recommended risk scores, Glasgow-Blatchford Score (GBS) and Oakland Score. Primary analysis was area under the receiver-operating-characteristic curve (AUC). Secondary analysis was specificity at 99% sensitivity to assess proportion of patients correctly identified as very-low-risk. RESULTS: The machine learning model outperformed the GBS (AUC=0.92 vs. 0.89;p<0.001) and Oakland score (AUC=0.92 vs. 0.89;p<0.001). At the very-low-risk threshold of 99% sensitivity, the machine learning model identified more very-low-risk patients: 37.9% vs. 18.5% for GBS and 11.7% for Oakland score (p<0.001 for both comparisons). CONCLUSIONS: An EHR-based machine learning model performs better than currently recommended clinical risk scores and identifies more very-low-risk patients eligible for discharge from the emergency department.

SERUM VITAMIN D AND SELECTED BIOMARKERS OF CALCIUM HOMEOSTASIS IN ASIAN ELEPHANTS (ELEPHAS MAXIMUS) MANAGED AT A LOW LATITUDE.

An understanding of species-specific vitamin D metabolism and its role in calcium homeostasis is essential for correct diet formulation and development of husbandry protocols for managed nondomestic species. This study documented serum vitamin D metabolites and other analytes involved in calcium homeostasis in Asian elephants (Elephas maximus) managed at a latitude similar to their wild natural habitat. Serum values for 33 elephants managed at a low latitude were measured in the peak of summer, revealing low vitamin D2 (25(OH)D2 2.3 ± 0.6 ng/ ml and 24,25(OH)2D2 2.17 ± 0.52 ng/ml) and nondetectable vitamin D3. Serum minerals (calcium, phosphorus, magnesium), ionized calcium, and parathyroid hormone were within normal reported ranges. In comparison with previously reported values in elephants managed at a high latitude, 25(OH)D2 (P < 0.001), 24,25(OH)2D2 (P = 0.001), and magnesium (P = 0.013) were significantly lower, and parathyroid hormone was significantly higher (P < 0.001). The lack of D3 production during ample sun exposure at a low latitude suggests that Asian elephants are incapable of cutaneous photobiosynthesis of vitamin D, and that low serum D2 is normal for this species.

Bacterial Sphingolipids Exacerbate Colitis by Inhibiting ILC3-derived IL-22 Production.

BACKGROUND & AIMS: Gut bacterial sphingolipids, primarily produced by Bacteroidetes, have dual roles as bacterial virulence factors and regulators of the host mucosal immune system, including regulatory T cells and invariant natural killer T cells. Patients with inflammatory bowel disease display altered sphingolipids profiles in fecal samples. However, how bacterial sphingolipids modulate mucosal homeostasis and regulate intestinal inflammation remains unclear. METHODS: We used dextran sodium sulfate (DSS)-induced colitis in mice monocolonized with Bacteroides fragilis strains expressing or lacking sphingolipids to assess the influence of bacterial sphingolipids on intestinal inflammation using transcriptional, protein, and cellular analyses. Colonic explant and organoid were used to study the function of bacterial sphingolipids. Host mucosal immune cells and cytokines were profiled and characterized using flow cytometry, enzyme-linked immunosorbent assay, and Western blot, and cytokine function in vivo was investigated by monoclonal antibody injection. RESULTS: B fragilis sphingolipids exacerbated intestinal inflammation. Mice monocolonized with B fragilis lacking sphingolipids exhibited less severe DSS-induced colitis. This amelioration of colitis was associated with increased production of interleukin (IL)-22 by ILC3. Mice colonized with B fragilis lacking sphingolipids following DSS treatment showed enhanced epithelial STAT3 activity, intestinal cell proliferation, and antimicrobial peptide production. Protection against DSS colitis associated with B fragilis lacking sphingolipids was reversed on IL22 blockade. Furthermore, bacterial sphingolipids restricted epithelial IL18 production following DSS treatment and interfered with IL22 production by a subset of ILC3 cells expressing both IL18R and major histocompatibility complex class II. CONCLUSIONS: B fragilis-derived sphingolipids exacerbate mucosal inflammation by impeding epithelial IL18 expression and concomitantly suppressing the production of IL22 by ILC3 cells.

Optimizing large language models in digestive disease: strategies and challenges to improve clinical outcomes.

Large Language Models (LLMs) are transformer-based neural networks with billions of parameters trained on very large text corpora from diverse sources. LLMs have the potential to improve healthcare due to their capability to parse complex concepts and generate context-based responses. The interest in LLMs has not spared digestive disease academics, who have mainly investigated foundational LLM accuracy, which ranges from 25% to 90% and is influenced by the lack of standardized rules to report methodologies and results for LLM-oriented research. In addition, a critical issue is the absence of a universally accepted definition of accuracy, varying from binary to scalar interpretations, often tied to grader expertise without reference to clinical guidelines. We address strategies and challenges to increase accuracy. In particular, LLMs can be infused with domain knowledge using Retrieval Augmented Generation (RAG) or Supervised Fine-Tuning (SFT) with reinforcement learning from human feedback (RLHF). RAG faces challenges with in-context window limits and accurate information retrieval from the provided context. SFT, a deeper adaptation method, is computationally demanding and requires specialized knowledge. LLMs may increase patient quality of care across the field of digestive diseases, where physicians are often engaged in screening, treatment and surveillance for a broad range of pathologies for which in-context learning or SFT with RLHF could improve clinical decision-making and patient outcomes. However, despite their potential, the safe deployment of LLMs in healthcare still needs to overcome hurdles in accuracy, suggesting a need for strategies that integrate human feedback with advanced model training.

Modulating Excited State Properties and Ligand Ejection Kinetics in Ruthenium Polypyridyl Complexes Designed to Mimic Photochemotherapeutics.

Ruthenium(II) polypyridyl complexes have gained significant interest as photochemotherapeutics (PCTs) due to their synthetic viability, strong light absorption, well understood excited state properties, and high phototoxicity indexes. Herein, we report the synthesis, characterization, electrochemical, spectrochemical, and preliminary cytotoxicity analyses of three series of ruthenium(II) polypyridyl complexes designed to mimic PCTs. The three series have the general structure of [Ru(bpy)2(N-N)]2+ (Series 1), [Ru(bpy)(dmb)(N-N)]2+ (Series 2), and [Ru(dmb)2(N-N)]2+ (Series 3, where N-N is a bidentate polypyridyl ligand, bpy = 2,2'-bipyridine, and dmb = 6,6'-dimethyl-2,2'-bipyridine). In the three series, the N-N ligand was systematically modified to incorporate increased conjugation and/or electronegative heteroatoms to increase dπ-π* backbonding, red-shifting the lowest energy metal-to-ligand charge transfer (MLCT) absorptions from λmax = 454 to λmax = 580 nm, nearing the therapeutic window for PCTs (600-1100 nm). In addition, steric bulk was systematically introduced through the series, distorting the Ru(II) octahedra, making the dissociative 3dd* state thermally accessible at room and body temperatures. This resulted in a 4 orders of magnitude increase in photoinduced ligand ejection kinetics, and demonstrates the ability to modulate both the MLCT* and dd* manifolds in the complexes, which is critical in PCT drug design. Preliminary cell viability assays suggest that the increased steric bulk to lower the 3dd* states may interfere with the cytotoxicity mechanism, limiting photoinitiated toxicity of the complexes. This work demonstrates the importance of understanding both the MLCT* and dd* manifolds and how they impact the ability of a complex to act as a PCT agent.

Predicting response to non-selective beta-blockers with liver-spleen stiffness and heart rate in patients with liver cirrhosis and high-risk varices.

INTRODUCTION: Non-selective beta-blockers (NSBB) are used for primary prophylaxis in patients with liver cirrhosis and high-risk varices (HRVs). Assessing therapeutic response is challenging due to the invasive nature of hepatic venous pressure gradient (HVPG) measurement. This study aims to define a noninvasive machine-learning based approach to determine response to NSBB in patients with liver cirrhosis and HRVs. METHODS: We conducted a prospective study on a cohort of cirrhotic patients with documented HRVs receiving NSBB treatment. Patients were followed-up with clinical and elastography appointments at 3, 6, and 12 months after NSBB treatment initiation. NSBB response was defined as stationary or downstaging variceal grading at the 12-month esophagogastroduodenoscopy (EGD). In contrast, non-response was defined as upstaging variceal grading at the 12-month EGD or at least one variceal hemorrhage episode during the 12-month follow-up. We chose cut-off values for univariate and multivariate model with 100% specificity. RESULTS: According to least absolute shrinkage and selection operator (LASSO) regression, spleen stiffness (SS) and liver stiffness (LS) percentual decrease, along with changes in heart rate (HR) at 3 months were the most significant predictors of NSBB response. A decrease > 11.5% in SS, > 16.8% in LS, and > 25.3% in HR was associated with better prediction of clinical response to NSBB. SS percentual decrease showed the highest accuracy (86.4%) with high sensitivity (78.8%) when compared to LS and HR. The multivariate model incorporating SS, LS, and HR showed the highest discrimination and calibration metrics (AUROC = 0.96), with the optimal cut-off of 0.90 (sensitivity 94.2%, specificity 100%, PPV 95.7%, NPV 100%, accuracy 97.5%).

Optimization of hepatological clinical guidelines interpretation by large language models: a retrieval augmented generation-based framework.

Large language models (LLMs) can potentially transform healthcare, particularly in providing the right information to the right provider at the right time in the hospital workflow. This study investigates the integration of LLMs into healthcare, specifically focusing on improving clinical decision support systems (CDSSs) through accurate interpretation of medical guidelines for chronic Hepatitis C Virus infection management. Utilizing OpenAI's GPT-4 Turbo model, we developed a customized LLM framework that incorporates retrieval augmented generation (RAG) and prompt engineering. Our framework involved guideline conversion into the best-structured format that can be efficiently processed by LLMs to provide the most accurate output. An ablation study was conducted to evaluate the impact of different formatting and learning strategies on the LLM's answer generation accuracy. The baseline GPT-4 Turbo model's performance was compared against five experimental setups with increasing levels of complexity: inclusion of in-context guidelines, guideline reformatting, and implementation of few-shot learning. Our primary outcome was the qualitative assessment of accuracy based on expert review, while secondary outcomes included the quantitative measurement of similarity of LLM-generated responses to expert-provided answers using text-similarity scores. The results showed a significant improvement in accuracy from 43 to 99% (p < 0.001), when guidelines were provided as context in a coherent corpus of text and non-text sources were converted into text. In addition, few-shot learning did not seem to improve overall accuracy. The study highlights that structured guideline reformatting and advanced prompt engineering (data quality vs. data quantity) can enhance the efficacy of LLM integrations to CDSSs for guideline delivery.

Review article: Upper gastrointestinal bleeding - review of current evidence and implications for management.

BACKGROUND: Acute upper gastrointestinal bleeding (UGIB) is a common emergency requiring hospital-based care. Advances in care across pre-endoscopic, endoscopic and post-endoscopic phases have led to improvements in clinical outcomes. AIMS: To provide a detailed, evidence-based update on major aspects of care across pre-endoscopic, endoscopic and post-endoscopic phases. METHODS: We performed a structured bibliographic database search for each topic. If a recent high-quality meta-analysis was not available, we performed a meta-analysis with random effects methods and odds ratios with 95% confidence intervals. RESULTS: Pre-endoscopic management of UGIB includes risk stratification, a restrictive red blood cell transfusion policy unless the patient has cardiovascular disease, and pharmacologic therapy with erythromycin and a proton pump inhibitor. Patients with cirrhosis should be treated with prophylactic antibiotics and vasoactive medications. Tranexamic acid should not be used. Endoscopic management of UGIB depends on the aetiology. For peptic ulcer disease (PUD) with high-risk stigmata, endoscopic therapy, including over-the-scope clips (OTSCs) and TC-325 powder spray, should be performed. For variceal bleeding, treatment should be customised by severity and anatomic location. Post-endoscopic management includes early enteral feeding for all UGIB patients. For high-risk PUD, PPI should be continued for 72 h, and rebleeding should initially be evaluated with a repeat endoscopy. For variceal bleeding, high-risk patients or those with further bleeding, a transjugular intrahepatic portosystemic shunt can be considered. CONCLUSIONS: Management of acute UGIB should include treatment plans for pre-endoscopic, endoscopic and post-endoscopic phases of care, and customise treatment decisions based on aetiology and severity of bleeding.

Bile acids modified by the intestinal microbiota promote colorectal cancer growth by suppressing CD8+ T cell effector functions.

Concentrations of the secondary bile acid, deoxycholic acid (DCA), are aberrantly elevated in colorectal cancer (CRC) patients, but the consequences remain poorly understood. Here, we screened a library of gut microbiota-derived metabolites and identified DCA as a negative regulator for CD8+ T cell effector function. Mechanistically, DCA suppressed CD8+ T cell responses by targeting plasma membrane Ca2+ ATPase (PMCA) to inhibit Ca2+-nuclear factor of activated T cells (NFAT)2 signaling. In CRC patients, CD8+ T cell effector function negatively correlated with both DCA concentration and expression of a bacterial DCA biosynthetic gene. Bacteria harboring DCA biosynthetic genes suppressed CD8+ T cells effector function and promoted tumor growth in mice. This effect was abolished by disrupting bile acid metabolism via bile acid chelation, genetic ablation of bacterial DCA biosynthetic pathway, or specific bacteriophage. Our study demonstrated causation between microbial DCA metabolism and anti-tumor CD8+ T cell response in CRC, suggesting potential directions for anti-tumor therapy.

Development of an MR-Guided Focused Ultrasound (MRgFUS) Lesioning Approach for the Fornix in the Rat Brain.

OBJECTIVE: High-intensity magnetic resonance-guided focused ultrasound (MRgFUS) is a non-invasive therapy to lesion brain tissue, used clinically in patients and pre-clinically in several animal models. Challenges with focused ablation in rodent brains can include skull and near-field heating and accurately targeting small and deep brain structures. We overcame these challenges by creating a novel method consisting of a craniectomy skull preparation, a high-frequency transducer (3 MHz) with a small ultrasound focal spot, a transducer positioning system with an added manual adjustment of ∼0.1 mm targeting accuracy, and MR acoustic radiation force imaging for confirmation of focal spot placement. METHODS: The study consisted of two main parts. First, two skull preparation approaches were compared. A skull thinning approach (n = 7 lesions) was compared to a craniectomy approach (n = 22 lesions), which confirmed a craniectomy was necessary to decrease skull and near-field heating. Second, the two transducer positioning systems were compared with the fornix chosen as a subcortical ablation target. We evaluated the accuracy of targeting using histologic methods from a high-frequency transducer with a small ultrasound focal spot and MR acoustic radiation force imaging. RESULTS: Comparing a motorized adjustment system (∼1 mm precision, n = 17 lesions) to the motorized system with an added micromanipulator (∼0.1 mm precision, n = 14 lesions), we saw an increase in the accuracy of targeting the fornix by 133%. CONCLUSIONS: The described work allows for repeatable and accurate targeting of small and deep structures in the rodent brain, such as the fornix, enabling the investigation of neurological disorders in chronic disease models.

Active transfer learning for audiogram estimation.

Computational audiology (CA) has grown over the last few years with the improvement of computing power and the growth of machine learning (ML) models. There are today several audiogram databases which have been used to improve the accuracy of CA models as well as reduce testing time and diagnostic complexity. However, these CA models have mainly been trained on single populations. This study integrated contextual and prior knowledge from audiogram databases of multiple populations as informative priors to estimate audiograms more precisely using two mechanisms: (1) a mapping function drawn from feature-based homogeneous Transfer Learning (TL) also known as Domain Adaptation (DA) and (2) Active Learning (Uncertainty Sampling) using a stream-based query mechanism. Simulations of the Active Transfer Learning (ATL) model were tested against a traditional adaptive staircase method akin to the Hughson-Westlake (HW) method for the left ear at frequencies ω=0.25,0.5,1,2,4,8 kHz, resulting in accuracy and reliability improvements. ATL improved HW tests from a mean of 41.3 sound stimuli presentations and reliability of ±9.02 dB down to 25.3±1.04 dB. Integrating multiple databases also resulted in classifying the audiograms into 18 phenotypes, which means that with increasing data-driven CA, higher precision is achievable, and a possible re-conceptualisation of the notion of phenotype classifications might be required. The study contributes to CA in identifying an ATL mechanism to leverage existing audiogram databases and CA models across different population groups. Further studies can be done for other psychophysical phenomena using ATL.

Unique Spatial Transcriptomic Profiling of the Murine Femoral Fracture Callus: A Preliminary Report.

Fracture callus formation is a dynamic stage of bone activity and repair with precise, spatially localized gene expression. Metastatic breast cancer impairs fracture healing by disrupting bone homeostasis and imparting an altered genomic profile. Previous sequencing techniques such as single-cell RNA and in situ hybridization are limited by missing spatial context and low throughput, respectively. We present a preliminary approach using the Visium CytAssist spatial transcriptomics platform to provide the first spatially intact characterization of genetic expression changes within an orthopedic model of impaired fracture healing. Tissue slides prepared from BALB/c mice with or without MDA-MB-231 metastatic breast cancer cells were used. Both unsupervised clustering and histology-based annotations were performed to identify the hard callus, soft callus, and interzone for differential gene expression between the wild-type and pathological fracture model. The spatial transcriptomics platform successfully localized validated genes of the hard (Dmp1, Sost) and soft callus (Acan, Col2a1). The fibrous interzone was identified as a region of extensive genomic heterogeneity. MDA-MB-231 samples demonstrated downregulation of the critical bone matrix and structural regulators that may explain the weakened bone structure of pathological fractures. Spatial transcriptomics may represent a valuable tool in orthopedic research by providing temporal and spatial context.

Factors Associated with Opting Out of an Unrelated Hematopoietic Stem Cell Donor Registry: Differences and Similarities across Five Key Groups of Young Race/Ethnically Diverse Potential Donors in the United States.

Young adults from underserved racial/ethnic groups are critically needed as unrelated hematopoietic stem cell (HSC) donors, yet they are more likely than other groups to opt out of donation after having matched a patient. Understanding which factors are most strongly associated with opting out among young underserved racial/ ethnic registered donors compared with their White counterparts will provide the basis for specific interventions to improve donor retention. We sought to determine the key, modifiable psychosocial, registry-related, and donation-related characteristics that are uniquely associated with opting out across 5 key racial/ethnic groups of young HSC donor registry members who had been contacted as a potential match for a patient. This study examines data from a large cross-sectional survey of young (age 18 to 30) registry members shortly after they preliminarily matched a patient (CT-stage) and continued toward or opted out of donation (CT-C and CT-NI), stratified by racial/ethnic group and sex. We assessed psychosocial, registry-related, and donation-related characteristics for all participants. We used chi-squared and F tests to assess differences between racial/ethnic groups. A separate logistic regression analysis for each racial/ethnic group was conducted to quantify adjusted associations between each variable and opting out. Then, we compared these associations across the racial/ethnic groups by evaluating the interaction effect between each variable and racial/ethnic group, with the same outcome (CT-C versus CT-NI) in question. Nine hundred thirty-five participants were surveyed, including 284 White, 165 Hispanic, 191 Black, 192 Asian/Pacific Islander, and 103 Multiracial/multiethnic participants. There were significant differences across racial/ethnic groups in values/goals, religious objections to donation, HSC-related medical mistrust, and parental involvement in donation decisions. Adjusted logistic regression subgroup analyses indicated that ambivalence was strongly associated with opting out across all racial/ethnic groups. Greater focus on intrinsic life goals (e.g., raising a family, becoming a community leader, influencing social values) was associated with opting out in the Multiracial/multiethnic, Hispanic, and Asian/Pacific Islander groups. Healthcare mistrust and insufficient registry contact was a significant factor for Hispanic participants. Protective factors against opting out included remembering joining the registry (Black participants), and parental support for donation decision (Asian/Pacific Islander participants). The performance of each logistic regression model was strong, with area-under-the curve ≥.88, CT-stage outcome classification accuracy ≥89%, and good fit between expected and observed opt-out probabilities. In the analysis across different racial/ethnic groups, the only significant interaction was race/ethnicity by whether more contact with the registry would have changed the decision at CT-stage; this variable was significant only for the Hispanic group. In the within-group analysis for Hispanic participants, the "more registry contact" variable was strongly associated with opting out (odds ratio 5.8, P = .03). Consistent with a growing body of HSC donor research, ambivalence was a key factor associated with opting-out for all racial/ethnic groups. Other key variables were differentially associated with opting-out depending on racial/ethnic group. Our study highlights key variables that registries should focus on as they develop targeted and tailored strategies to enhance commitment and reduce attrition of potential donors.

Improving Unrelated Donor Equity: Assessing Mismatched Donor Opportunities with Real-World Data in a Minority-Predominant Cohort.

Recent advances in graft-versus-host disease (GVHD) prophylaxis including post-transplant cyclophosphamide (PTCy) and abatacept have significantly improved outcomes following HLA-mismatched allogenic hematopoietic stem cell transplantation (allo-HSCT) and have tremendous potential for reducing racial disparities in donor availability. A recent small study employing bone marrow as the source of stem cells showed similar outcomes after 5/8 versus 7/8 matches and is currently being tested in a larger study using peripheral blood stem cells. In this study, we examine real-world alternative donor HSCT options for a minority-predominant cohort in the Bronx, NY, focusing on the availability of lesser-matched (5/8 to 7/8) donors. Records of patients who underwent HLA typing at Montefiore Medical Center (2019 to 2022) were reviewed. The National Marrow Donor Program registry was queried to evaluate the availability of donors with at least 99% likelihood of HLA match at various levels (5/8, 6/8, 7/8, 8/8). Two hundred forty-one patients were included, 70% were non-White. Although the availability of ≥7/8 donors was less common in non-White patients, 100% of patients from each group had at least one or more 5/8 and 6/8 HLA-matched donors and more than 80% of these patients had >100 potential 5/8 and 6/8 HLA-matched donors. There was no statistical difference by race or ethnicity in the mean number of donors at 5/8 and 6/8 HLA-match levels. We demonstrate through real-world data that patients from diverse ethnic and racial backgrounds have access to 5/8 and 6/8 HLA-matched donors for allo-HSCT, potentially eliminating disparities in donor availability and allowing prioritization of other donor selection characteristics such as donor age, sex, ABO, and B leader matching. Further work is needed to study whether the use of mismatched donors offers a more potent graft-versus malignancy effect and optimal GVHD prophylaxis.

MR-Guided Focused Ultrasound Thalamotomy in the Setting of Aneurysm Clip.

We report on a 75-year-old woman with a history of right MCA aneurysm clipping and medically refractive right-hand tremor. We successfully performed focused ultrasound thalamotomy of the left ventral intermediate nucleus under MR imaging-guidance at 3T. A thorough pretreatment evaluation of MR thermometry was critical to ensure that adequate precision could be achieved at the intended target. The tremor showed a 75% decrease at 24 hours postprocedure and a 50% decrease at a 3-month follow-up. There were no immediate adverse events.

Sponsorship of Clinical Trials Related to the Shoulder and Elbow: Trends Over Time and Comparative Analysis of Trial Characteristics by Sponsorship Type.

INTRODUCTION: Sponsorship trends have not been specifically evaluated for shoulder and elbow clinical trials, nor have trial characteristics been compared among shoulder and elbow trials sponsored by institutions, industries, and federal agencies. METHODS: ClinicalTrials.gov was queried for clinical trials using the terms 'shoulder' and 'elbow.' Trial characteristics were abstracted, including start year, intervention type, phase, randomization, and blinding. Univariate and multivariate analyses were performed to determine associations between sponsorship type and other trial characteristics. RESULTS: In total, 4,945 shoulder clinical trials and 1,517 elbow clinical trials were identified, of which 26 shoulder clinical trials and seven elbow clinical trials were excluded due to incomplete data. From 2000 to 2022, the number of shoulder and elbow trials initiated annually markedly increased driven by an increase in the number of institutional trials. Relative to trials with institutional sponsorship, industry sponsorship was independently associated with different intervention types, phase of study, lack of randomization, and blinding. DISCUSSION: From 2000 to 2022, the number of shoulder and elbow clinical trials initiated annually markedly increased, driven by an increase in institutionally sponsored trials. For clinical trials related to the shoulder, design characteristics were found to differ based on study sponsorship type. This suggests that the design characteristics of shoulder-related clinical trials are shifting over time.

Gut complement induced by the microbiota combats pathogens and spares commensals.

Canonically, the complement system is known for its rapid response to remove microbes in the bloodstream. However, relatively little is known about a functioning complement system on intestinal mucosal surfaces. Herein, we report the local synthesis of complement component 3 (C3) in the gut, primarily by stromal cells. C3 is expressed upon commensal colonization and is regulated by the composition of the microbiota in healthy humans and mice, leading to an individual host's specific luminal C3 levels. The absence of membrane attack complex (MAC) components in the gut ensures that C3 deposition does not result in the lysis of commensals. Pathogen infection triggers the immune system to recruit neutrophils to the infection site for pathogen clearance. Basal C3 levels directly correlate with protection against enteric infection. Our study reveals the gut complement system as an innate immune mechanism acting as a vigilant sentinel that combats pathogens and spares commensals.