Citations

Abstract With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and diverse applications. This survey aims to address this need by providing a thorough review of BioLMs, focusing on their evolution, classification, and distinguishing features, alongside a detailed examination of training methodologies, datasets, and evaluation frameworks. We explore the wide‐ranging applications of BioLMs in critical areas such as disease diagnosis, drug discovery, and vaccine development, highlighting their impact and transformative potential in bioinformatics. We identify key challenges and limitations inherent in BioLMs, including data privacy and security concerns, interpretability issues, biases in training data and model outputs, and domain adaptation complexities. Finally, we highlight emerging trends and future directions, offering valuable insights to guide researchers and clinicians toward advancing BioLMs for increasingly sophisticated biological and clinical applications.

Background/Objectives: Coronavirus disease 2019 (COVID-19) is associated with gastrointestinal (GI) symptoms. Small intestinal bacterial overgrowth (SIBO) is emerging as a significant GI sequela post-COVID-19 infection. This study aimed to evaluate the prevalence and incidence of SIBO post-COVID-19 infection across different age groups and to identify associated risk factors in a global cohort. Methods: A retrospective study utilized the TriNetX database and included adult patients (≥18 years) diagnosed with SIBO following COVID-19 infection (1 January 2022–30 May 2024). A propensity score matching (1:1) was used to adjust for demographics and SIBO risk factors. Kaplan–Meier survival analysis assessed the SIBO incidence within 12 months. Results: Among 1,660,092 COVID-19 patients and 42,322,017 controls, SIBO was diagnosed in 353 COVID-19 patients without hydrogen breath tests (BT) and 78 with BT, compared to 3368 controls without BT and 871 with BT. Age-specific analysis demonstrated a clear, progressive increase in the SIBO incidence, becoming distinctly significant by 6 months and highest at 12 months post-infection. The highest risks were noted in ages 60–69 (0.011% vs. 0.004%, OR 2.6, p = 0.0003) and 70–79 (0.011% vs. 0.005%, OR 2.0, p = 0.0004), with younger age groups (30–49 years) also showing significantly increased risks. The medication analysis revealed strong associations with chronic opioid, proton pump inhibitor, and antidiarrheal medication. Conclusions: COVID-19 significantly increased the risk of SIBO, particularly within the first 12 months post-infection, across various age groups and, notably, in association with certain chronic medications. Clinical vigilance and targeted management strategies are recommended to mitigate long-term GI consequences.

ABSTRACT Premature infants often require supplemental oxygen therapy, however, exposure to supraphysiological oxygen (hyperoxia) can disrupt normal lung development and contribute to bronchopulmonary dysplasia (BPD). Mitochondrial dysfunction is increasingly recognized as a contributor to hyperoxia-induced BPD. However, the effects of hyperoxia on mitochondrial function and mucociliary differentiation in the developing upper airway epithelium remain poorly understood. This study tested the hypothesis that hyperoxia impairs neonatal airway mucociliary differentiation by disrupting mitochondrial bioenergetic function. Neonatal tracheal airway epithelial cells (nTAECs) from term infants (n=5) were cultured in a 3D air-liquid interface (ALI) model and exposed to 60% O₂ during the mid-phase of differentiation (ALI day 7-14). Cellular phenotype was assessed using immunofluorescence staining and gene expression analyses. Mitochondrial function was evaluated through Seahorse metabolic flux analysis, and global protein changes were characterized by quantitative proteomics. Hyperoxia exposure significantly impaired terminal epithelial differentiation, characterized by reductions in ciliated and goblet cells. Seahorse assay revealed a decrease in baseline oxygen consumption and mitochondrial ATP production, accompanied by a compensatory increase in glycolytic ATP production. Quantitative proteomics identified disruption of mitochondrial Complex I as a central feature of the hyperoxic response. Downstream proteomic pathway analyses further confirmed the metabolic shift from mitochondrial to glycolytic ATP production and demonstrated altered epithelial differentiation pathways, including NOTCH and TGF-β signaling. These findings reveal that moderate hyperoxia impairs mitochondrial bioenergetics and alters metabolic programming, leading to disrupted mucociliary differentiation. Future in vivo studies should evaluate mitochondrial oxidative fitness as a therapeutic target in neonatal lung disease. NEW & NOTEWORTHY We report that moderate hyperoxia during a critical window of mucociliary differentiation disrupts terminal maturation in neonatal airway epithelial cells cultured in a 3D model. Hyperoxia induced mitochondrial bioenergetic dysfunction and metabolic reprogramming, with proteomic analysis identifying Complex I disruption as a key driver of impaired differentiation. Overall, these findings reveal a previously underrecognized link between mitochondrial bioenergetics and airway epithelial development, positioning metabolic dysfunction as an early trigger of hyperoxia-induced neonatal airway injury.

Black patients with metastatic prostate cancer have higher mortality rates compared to non-Hispanic White patients. There are no data on outcomes with [177Lu]Lu-PSMA-617 (LuPSMA) across racial groups. We evaluated the association between race and outcomes with LuPSMA in a multi-institutional cohort of consecutive patients with mCRPC treated with LuPSMA. The primary outcomes were PSA-50 rate, PSA-progression-free survival (PSA-PFS), and overall survival (OS). Statistical models were adjusted for age, number of prior therapies, sites of metastases, and baseline PSA. A total of 654 patients were included; 593 (91%) were White, 45 (7%) were Black and 16 (2%) were another non-Black minority (NBM). There were no statistically significant differences in PSA-50 rates, PSA-PFS and OS between the groups. Black and White patients treated with LuPSMA had similar clinical outcomes; efforts are needed to ensure Black and NBM patients have equal access to life prolonging therapies to narrow disparities in outcomes.

Importance Nontraumatic subarachnoid hemorrhage (SAH) represents the third most common stroke type with unique etiologies, risk factors, diagnostics, and treatments. Nevertheless, epidemiological studies often cluster SAH with other stroke types leaving its distinct burden estimates obscure. Objective To estimate the worldwide burden of SAH. Design, Setting, and Participants Based on the repeated cross-sectional Global Burden of Disease (GBD) 2021 study, the global burden of SAH in 1990 to 2021 was estimated. Moreover, the SAH burden was compared with other diseases, and its associations with 14 individual risk factors were investigated with available data in the GBD 2021 study. The GBD study included the burden estimates of nontraumatic SAH among all ages in 204 countries and territories between 1990 and 2021. Exposures SAH and 14 modifiable risk factors. Main Outcomes and Measures Absolute numbers and age-standardized rates with 95% uncertainty intervals (UIs) of SAH incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) as well as risk factor–specific population attributable fractions (PAFs). Results In 2021, the global age-standardized SAH incidence was 8.3 (95% UI, 7.3-9.5), prevalence was 92.2 (95% UI, 84.1-100.6), mortality was 4.2 (95% UI, 3.7-4.8), and DALY rate was 125.2 (95% UI, 110.5-142.6) per 100 000 people. The highest burden estimates were found in Latin America, the Caribbean, Oceania, and high-income Asia Pacific. Although the absolute number of SAH cases increased, especially in regions with a low sociodemographic index, all age-standardized burden rates decreased between 1990 and 2021: the incidence by 28.8% (95% UI, 25.7%-31.6%), prevalence by 16.1% (95% UI, 14.8%-17.7%), mortality by 56.1% (95% UI, 40.7%-64.3%), and DALY rate by 54.6% (95% UI, 42.8%-61.9%). Of 300 diseases, SAH ranked as the 36th most common cause of death and 59th most common cause of DALY in the world. Of all worldwide SAH-related DALYs, 71.6% (95% UI, 63.8%-78.6%) were associated with the 14 modeled risk factors of which high systolic blood pressure (population attributable fraction [PAF] = 51.6%; 95% UI, 38.0%-62.6%) and smoking (PAF = 14.4%; 95% UI, 12.4%-16.5%) had the highest attribution. Conclusions and Relevance Although the global age-standardized burden rates of SAH more than halved over the last 3 decades, SAH remained one of the most common cardiovascular and neurological causes of death and disabilities in the world, with increasing absolute case numbers. These findings suggest evidence for the potential health benefits of proactive public health planning and resource allocation toward the prevention of SAH.

Purpose Automating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. Manual QA is tedious, time-consuming, and prone to subjective experiences. Automatic segmentation reduces physician workload and improves consistency. However, an effective QA process for these automatic contours remains an unmet need in clinical practice. Materials and Methods The patient data used in this study was derived from the AAPM Thoracic Auto-Segmentation Challenge dataset, including left and right lungs, heart, esophagus, and spinal cord. Two groups of organ-at-risk (OAR) were generated. A ResNet-152 network was used as a feature extractor, and a one-class support vector machine (OC-SVM) was employed to classify contours as ‘high’ or ‘low’ quality. To evaluate the generalizability, we generated low-quality contours using translation and resizing techniques and assessed correlations between detection limits and metrics such as volume, Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD). Results The proposed OC-SVM model outperformed binary classifiers n metrics such as balanced accuracy and area under the receiver operating characteristic curve (AUC) . It demonstrated superior performance in detecting various types of contour errors while maintaining high interpretability. Strong correlations were observed between detection limits and contour metrics. Conclusion Our proposed model integrates an attention mechanism with a one-class classification framework to automate QA for OAR delineations. This approach effectively detects diverse types of contour errors with high accuracy, significantly reducing the burden on physicians during radiotherapy planning.

ABSTRACTBackgroundDeep learning (DL) models for accurate renal tumor characterization may benefit from multi‐center datasets for improved generalizability; however, data‐sharing constraints necessitate privacy‐preserving solutions like federated learning (FL).PurposeTo assess the performance and reliability of FL for renal tumor segmentation and classification in multi‐institutional MRI datasets.Study TypeRetrospective multi‐center study.PopulationA total of 987 patients (403 female) from six hospitals were included for analysis. 73% (723/987) had malignant renal tumors, primarily clear cell carcinoma (n = 509). Patients were split into training (n = 785), validation (n = 104), and test (n = 99) sets, stratified across three simulated institutions.Field Strength/SequenceMRI was performed at 1.5 T and 3 T using T2‐weighted imaging (T2WI) and contrast‐enhanced T1‐weighted imaging (CE‐T1WI) sequences.AssessmentFL and non‐FL approaches used nnU‐Net for tumor segmentation and ResNet for its classification. FL‐trained models across three simulated institutional clients with central weight aggregation, while the non‐FL approach used centralized training on the full dataset.Statistical TestsSegmentation was evaluated using Dice coefficients, and classification between malignant and benign lesions was assessed using accuracy, sensitivity, specificity, and area under the curves (AUCs). FL and non‐FL performance was compared using the Wilcoxon test for segmentation Dice and Delong's test for AUC (p < 0.05).ResultsNo significant difference was observed between FL and non‐FL models in segmentation (Dice: 0.43 vs. 0.45, p = 0.202) or classification (AUC: 0.69 vs. 0.64, p = 0.959) on the test set. For classification, no significant difference was observed between the models in accuracy (p = 0.912), sensitivity (p = 0.862), or specificity (p = 0.847) on the test set.Data ConclusionFL demonstrated comparable performance to non‐FL approaches in renal tumor segmentation and classification, supporting its potential as a privacy‐preserving alternative for multi‐institutional DL models.Evidence Level4.Technical EfficacyStage 2.

Abstract Molecular mechanisms underlying disruptions in brain glucose uptake and metabolism, linked with cognitive decline in Alzheimer’s disease (AD) patients, are only partially understood. This study investigated how soluble amyloid beta (sAβ) peptides affect glucose transport at the blood-brain barrier (BBB), the primary portal for glucose entry into the brain. We demonstrated that [ 18 F]-fluorodeoxyglucose ( 18 FDG) uptake is reduced in sAβ overproducing APP,PS1 transgenic mice compared to wild-type mice. Moreover, the influx rate of 18 FDG decreased in sAβ40 or sAβ42 pre-infused mice, highlighting the inhibitory effect of sAβ peptides on glucose transport at the BBB. Consistently, the expression of GLUT1, the primary glucose transporter at the BBB, is reduced in polarized human cerebral microvascular endothelial cell (hCMEC/D3) monolayers upon exposure to sAβ peptides and in Aβ-laden cerebral vasculature in vivo. The study further examined the influence of sAβ on the insulin-AKT pathway, known to regulate glucose uptake through modulation of thioredoxin-interacting protein (TXNIP) expression. Results showed that sAβ peptides suppress AKT phosphorylation and reduce GLUT1 expression by upregulating TXNIP levels in hCMEC/D3 monolayers. Co-incubation of resveratrol with sAβ peptides reduced TXNIP expression and rectified reductions in GLUT1 expression. In summary, toxic sAβ impairs BBB glucose transport by disrupting the insulin/AKT/TXNIP axis.