A Report of a Rare Case of BCOR (B-cell Line 6 Corepressor)-Altered Sarcoma of the Lung in a Child.

Ewing sarcoma is one of the small round blue cell tumors of childhood that typically affects bone. Recently, a subgroup of undifferentiated round-cell sarcomas has been genetically identified as BCOR (B-cell Line 6 Corepressor)-altered sarcomas (BAS). We present a case of a six-year-old male child who presented with a chief complaint of shortness of breath and tachypnea and was found to have a large mediastinal mass concerning sarcoma. Preliminary biopsy results were positive for small round blue cells, possibly Ewing sarcoma. After six cycles of chemotherapy, with subsequent shrinkage of mediastinal mass, the patient was able to undergo wedge resection and excision of the mass with en bloc resection of the fifth and sixth rib, preserving his right lung. Final tissue pathology was positive for BAS. There have been only four reported cases of BAS of the chest wall and zero reported cases of primary tumor presentation of the lung, making this a rare presentation of the disease.

Loss to Follow up in Patients with Proliferative Diabetic Retinopathy Treated with Anti-VEGF Therapy and/or Panretinal Photocoagulation in the United States.

PURPOSE: To determine the rate of loss to follow up (LTFU) in patients with proliferative diabetic retinopathy (PDR) treated with anti-VEGF therapy and/or panretinal photocoagulation (PRP) in the United States. DESIGN: Retrospective cohort study using the national IRIS® (Intelligent Research in Sight) Registry data. SUBJECTS: A total of 73 595 eyes of 56 590 patients with PDR diagnosed between 2013 and 2015 and treated between 2013 and 2018. METHODS: Multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). MAIN OUTCOME MEASURES: Loss to follow up was no follow up within 12 months from last treatment. RESULTS: For patient eyes treated for PDR, 11.7% (95% CI, 11.5-12.0) were LTFU. Among patients with PDR treated with anti-VEGF therapy alone, PRP alone, and anti-VEGF and PRP, the rates of LTFU were 12.3% (95% CI, 11.8-12.7), 12.6% (95% CI, 12.1-13.0), and 10.8% (95% CI, 10.4-11.1), respectively. Risk factors for LTFU include Black or African American race/ethnicity (odds ratio [OR], 1.26; 95% CI, 1.13-1.41; P < 0.001), Hispanic ethnicity (OR, 1.28; 95% CI, 1.16-1.42; P < 0.001), Native American/Alaska Native or Native Hawaiian/Other Pacific Islander race/ethnicity (OR, 2.69; 95% CI, 2.14-3.38; P < 0.001), and unilateral disease (OR, 2.05; CI, 1.88-2.23; P < 0.001). Odds for LTFU were higher with patients with baseline vision of 20/50 to 20/200 (OR, 1.25; 95% CI, 1.15-1.36; P < 0.001) and with vision worse than 20/200 (OR, 1.22; 95% CI, 1.05-1.42; P = 0.01) than for patient eyes with a baseline visual acuity of 20/40 or better. Odds for LTFU were lower for Medicare Fee-for-Service (OR, 0.71; 95% CI, 0.64-0.79; P < 0.001) and Medicare Managed (OR, 0.66; 95% CI, 0.56-0.78; P < 0.001) compared with private insurance. Odds for LTFU were lower for patients treated in the Midwest (OR, 0.72; 95% CI, 0.64-0.81; P < 0.001) and West (OR, 0.83; 95% CI, 0.74-0.94; P = 0.003) compared with in the South region. CONCLUSIONS: The rate of LTFU is between 10% and 12% among patients with PDR who were treated with anti-VEGF injections and/or PRP. Risk factors include Black or African American race/ethnicity, Hispanic ethnicity, baseline vision worse than 20/40, private insurance, South region, and unilateral disease. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Integrating single-cell RNA-seq to identify fibroblast-based molecular subtypes for predicting prognosis and therapeutic response in bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is a highly aggressive and heterogeneous disease, posing challenges for diagnosis and treatment. Cancer immunotherapy has recently emerged as a promising option for patients with advanced and drug-resistant cancers. Fibroblasts, a significant component of the tumor microenvironment, play a crucial role in tumor progression, but their precise function in BLCA remains uncertain. METHODS: Single-cell RNA sequencing (scRNA-seq) data for BLCA were obtained from the Gene Expression Omnibus database. The R package "Seurat" was used for processing scRNA-seq data, with uniform manifold approximation and projection (UMAP) for downscaling and cluster identification. The FindAllMarkers function identified marker genes for each cluster. Differentially expressed genes influencing overall survival (OS) of BLCA patients were identified using the limma package. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between high- and low-risk groups were investigated. RT-qPCR and immunohistochemistry validated the expression of prognostic genes. RESULTS: Fibroblast marker genes identified three molecular subtypes in the testing set. A prognostic signature comprising ten genes stratified BLCA patients into high- and low-score groups. This signature was validated in one internal and two external validation sets. High-score patients exhibited increased immune cell infiltration, elevated chemokine expression, and enhanced immune checkpoint expression but had poorer OS and a reduced response to immunotherapy. Six sensitive anti-tumor drugs were identified for the high-score group. RT-qPCR and immunohistochemistry showed that CERCAM, TM4SF1, FN1, ANXA1, and LOX were highly expressed, while EMP1, HEYL, FBN1, and SLC2A3 were downregulated in BLCA. CONCLUSION: A novel fibroblast marker gene-based signature was established, providing robust predictions of survival and immunotherapeutic response in BLCA patients.

In vitro and genomic mining studies of anti-Clostridium perfringens Compounds Derived from Bacillus amyloliquefaciens.

Clostridium perfringens is an important opportunistic microorganism in commercial poultry production that is implicated in necrotic enteritis (NE) outbreaks. This disease poses a severe financial burden on the global poultry industry, causing estimated annual losses of $6 billion globally. The ban on in-feed antibiotic growth promoters has spurred investigations into approaches of alternatives to antibiotics, among which Bacillus probiotics have demonstrated varying degrees of effectiveness against NE. However, the precise mechanisms underlying Bacillus-mediated beneficial effects on host responses in NE remain to be further elucidated. In this manuscript, we conducted in vitro and genomic mining analysis to investigate anti-C. perfringens activity observed in the supernatants derived from 2 Bacillus amyloliquefaciens strains (FS1092 and BaD747). Both strains demonstrated potent anti-C. perfringens activities in in vitro studies. An analysis of genomes from 15 B. amyloliquefaciens, 11 B. velezensis, and 2 B. subtilis strains has revealed an intriguing clustering pattern among strains known to possess anti-C. perfringens activities. Furthermore, our investigation has identified 7 potential antimicrobial compounds, predicted as secondary metabolites through antiSMASH genomic mining within the published genomes of B. amyloliquefaciens species. Based on in vitro analysis, BaD747 may have the potential as a probiotic in the control of NE. These findings not only enhance our understanding of B. amyloliquefaciens's action against C. perfringens but also provide a scientific rationale for the development of novel antimicrobial therapeutic agents against NE.

AI Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Recently, AI tools have been deployed with increasing speed in educational and clinical settings. However, the use of AI by trainees across different levels of experience has not been well studied. This study investigates the impact of AI assistance on diagnostic accuracy for intracranial hemorrhage (ICH) and large vessel occlusion (LVO) by medical students (MS) and resident trainees (RT). MATERIALS AND METHODS: This prospective study was conducted between March 2023 and October 2023. MS and RT were asked to identify ICH and LVO in 100 non-contrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating AI for ICH only (n = 26), the other for LVO only (n = 28). Primary outcomes included accuracy, sensitivity, and specificity for ICH / LVO detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with chi-square; differences in continuous variables were assessed with ANOVA. RESULTS: 48 participants completed the study, generating 10,779 ICH or LVO interpretations. With diagnostic aid, MS accuracy improved 11.0 points (P < .001) and RT accuracy showed no significant change. ICH interpretation time increased with diagnostic aid for both groups (P < .001) while LVO interpretation time decreased for MS (P < .001). Despite worse performance in detection of the smallest vs. the largest hemorrhages at baseline, MS were not more likely to accept a true positive AI result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the AI or when supplied with an incorrect AI result. CONCLUSIONS: This study demonstrated greater improvement in diagnostic accuracy with AI for MS compared to RT. However, MS were less likely than RT to overrule incorrect AI interpretations and were less accurate, even with diagnostic aid, than the AI was by itself. ABBREVIATIONS: ICH = intracranial hemorrhage; LVO = large vessel occlusion; MS = medical students; RT = resident trainees.

Shifts in ophthalmic care utilization during the COVID-19 pandemic in the US.

BACKGROUND: Healthcare restrictions during the COVID-19 pandemic, particularly in ophthalmology, led to a differential underutilization of care. An analytic approach is needed to characterize pandemic health services usage across many conditions. METHODS: A common analytical framework identified pandemic care utilization patterns across 261 ophthalmic diagnoses. Using a United States eye care registry, predictions of utilization expected without the pandemic were established for each diagnosis via models trained on pre-pandemic data. Pandemic effects on utilization were estimated by calculating deviations between observed and expected patient volumes from January 2020 to December 2021, with two sub-periods of focus: the hiatus (March-May 2020) and post-hiatus (June 2020-December 2021). Deviation patterns were analyzed using cluster analyses, data visualizations, and hypothesis testing. RESULTS: Records from 44.62 million patients and 2455 practices show lasting reductions in ophthalmic care utilization, including visits for leading causes of visual impairment (age-related macular degeneration, diabetic retinopathy, cataract, glaucoma). Mean deviations among all diagnoses are 67% below expectation during the hiatus peak, and 13% post-hiatus. Less severe conditions experience greater utilization reductions, with heterogeneities across diagnosis categories and pandemic phases. Intense post-hiatus reductions occur among non-vision-threatening conditions or asymptomatic precursors of vision-threatening diseases. Many conditions with above-average post-hiatus utilization pose a risk for irreversible morbidity, such as emergent pediatric, retinal, or uveitic diseases. CONCLUSIONS: We derive high-resolution insights on pandemic care utilization in the US from high-dimensional data using an analytical framework that can be applied to study healthcare disruptions in other settings and inform efforts to pinpoint unmet clinical needs.

The COVID-19 pandemic disrupted healthcare services globally, including eye care in the United States. Using a US eye disease database, we measured how the pandemic impacted patient visits for 261 eye diagnoses by comparing actual visit volumes for each diagnosis with what would have been expected without the pandemic. We identified groups of conditions with similar changes in visit levels and examined whether these shifts were related to characteristics of the diagnoses studied. We found extended decreases in patient presentations for most eye conditions, with greater reductions for less severe diagnoses, and with anomalies and differences in this trend across diagnosis categories and pandemic sub-periods. This highlights areas of potentially unmet need in vision care arising from the pandemic.