To develop and compare machine learning-based risk prediction models to identify patients at risk for short-term adverse outcomes (overnight admission, early complication, or readmission) after hip arthroscopy and to determine key predictive demographic and clinical factors.

Data from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database were used to develop and compare risk prediction models aiming to: (1) identify patients likely to experience short-term adverse outcomes including overnight admission, early complication, or readmission; and (2) determine the most predictive demographic and clinical factors contributing to adverse outcomes following hip arthroscopy. Predictive models were developed using support vector machine, random forest, logistic regression, gradient boosting, and extreme gradient boosting methods.

A total of 1478 eligible patients were included (56.4% female, mean age 40.0 ± 14.9 years), of whom 214 (14.5%) experienced a short-term adverse event. Compared to patients with an uncomplicated outpatient surgical course, those experiencing a short-term adverse event exhibited higher rates of diabetes mellitus, hypertension requiring medication, COPD, bleeding disorder, wound class ⩾2, ASA class ⩾3, lower preoperative haematocrit, and longer operative times. Logistic regression produced the optimal model for predicting short-term adverse events (AUC = 0.763), with operative time, preoperative haematocrit, ASA class, surgical procedure (CPT code), and age identified as the strongest predictive features.

These findings demonstrate the value of ML and may assist in predicting surgical outcomes, guiding clinical decision-making, and managing patient expectations regarding their postoperative course.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are fundamental in the management of type 2 diabetes mellitus (T2DM) and obesity. While early preclinical data raised concerns regarding direct pancreatic toxicity, contemporary human evidence from 2020 to 2025 has shifted the safety narrative. Meta-analyses of randomized controlled trials (RCTs) demonstrate no statistically significant independent association between GLP-1 RA use and acute pancreatitis (AP) (MH-OR 1.24 [0.94, 1.64]; P = .13).However, real-world data identifies a transient increase in risk during the first 6 months of treatment (HR 1.340; 95% CI, 1.239-1.449; P = .019). We propose that this 'pancreatic signal' is an indirect, biliary-mediated phenomenon driven by rapid weight loss and drug-induced gallbladder dysmotility via cholecystokinin (CCK) inhibition. Rather than restricting the indications of these cardioprotective therapies, clinical focus should pivot towards proactive biliary monitoring during the initial 24 weeks of therapy.

Type 2 diabetes mellitus (T2DM) poses a significant global health challenge, highlighting the urgent need for effective therapeutics. Heterophyllin B (HB), a cyclic peptide derived from Pseudostellaria Radix, has been proposed as a promising drug for T2DM. In this study, we systematically verified that HB could alleviate T2DM by modulating the hepatic IRS2/PI3K-Akt/FoxO1 signaling pathway, restoring bile acid and glycerophospholipid metabolism. However, the therapeutic potential of HB is hampered by its poor solubility, low oral bioavailability, and susceptibility to P-glycoprotein (P-gp) efflux. To overcome these limitations, we developed an oral delivery system in which a N-acetylgalactosamine (GalNAc)-modified pillar[6]arene (P6) designed for liver targeting encapsulates HB and then incorporated into a mucoadhesive interpolymer complex (IPC) micropatch, namely HB ⊂ P6-GalNAc/IPC. The formulation was encapsulated in enteric capsules for oral administration, which significantly enhanced intestinal absorption of HB and achieved a high oral bioavailability of 66.31%, approximately 3.3 times that of free HB. This improvement was attributed to multiple mechanisms, including reversible tight junction opening, inhibition of P-gp efflux, and activation of both clathrin- and caveolae-mediated endocytosis. In a high-fat diet/streptozotocin (HFD/STZ)-induced T2DM mouse model, HB ⊂ P6-GalNAc/IPC formulation outperformed metformin in improving glycemic control, insulin sensitivity, and lipid metabolism, while also ameliorating hepatic steatosis and providing notable pancreatic and renal protection. Collectively, this work not only clarifies the anti-diabetic mechanisms of HB but also offers a versatile strategy for the effective oral delivery of peptide-based therapeutics.

The glymphatic system (GS) is a brain-wide clearance pathway whose dysfunction has been implicated in cognitive decline. This study was designed to assess GS alterations in prediabetes (PDM) and type 2 diabetes mellitus (T2DM) using multiple MRI-derived metrics and to examine their associations with cognitive performance.

This cross-sectional study was conducted from October 2023 to June 2024 at Nanfang Hospital, a tertiary care center. A total of 147 participants were recruited, including 52 patients with T2DM, 44 with PDM, and 51 healthy controls (HC). All participants underwent brain MRI, laboratory examinations, and cognitive function assessments. GS function was evaluated using MRI-derived metrics, including CP volume, PVS volume, FW index, and DTI-ALPS index. Group differences were tested with general linear models adjusted for sex, age, and education, and associations with clinical variables were evaluated using partial correlations.

Compared with HC, PDM showed increased CP volume and FW index, without significant changes in DTI-ALPS index or PVS volume. T2DM showed reduced DTI-ALPS index, increased CP volume, and higher FW index, with unchanged PVS volume. In both groups, lower DTI-ALPS index and higher CP volume or FW index correlated with poorer cognitive performance.

PDM and T2DM exhibit GS alterations, including reduced DTI-ALPS index and increased CP volume and FW index, which are associated with poorer cognition. GS metrics may serve as potential neuroimaging biomarkers for cognitive impairment in this population.

Gestational diabetes mellitus (GDM) is a common pregnancy complication linked to adverse outcomes, highlighting the need for new diagnostic markers. This study aimed to identify oxidative stress-related genes as potential biomarkers for GDM using integrated bioinformatics and experimental validation.

The GSE70493 dataset was obtained from the Gene Expression Omnibus (GEO) database and analyzed using weighted gene co-expression network analysis (WGCNA), functional enrichment, and differential expression analysis. Reactive oxygen species (ROS) activity scores for each sample were calculated using single-sample gene set enrichment analysis (ssGSEA). ROS-associated differentially expressed genes (DEGs) were further screened using the least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and RandomForest algorithms to identify pivotal genes. A diagnostic radial-kernel support vector machine (SVM) classifier was constructed and rigorously evaluated through a 5 × 5 nested cross-validation framework on the training set, followed by validation in an independent external cohort (GSE249311). A transcription factor (TF)-gene regulatory network was established via the JASPAR database on the NetworkAnalyst 3.0 platform. The biological role of PRRG1 in GDM was also explored using cellular experiments.

WGCNA identified 7 co-expression modules, among which the green, pink, and black modules showed a strong positive correlation with ROS scores. Enrichment analysis showed that the module genes were mainly implicated in protein hydrolysis and processing, cell adhesion molecule binding, and various immune-related pathways. 765 DEGs, including 470 downregulated genes and 295 upregulated genes, were screened between GDM samples and control samples. Machine learning algorithm identified four hub genes (SH3BP5, ITGAM, PRRG1, and MIS12). When the four hub genes were combined, ROC curves showed that the hub genes exhibited strong diagnostic value for GDM. In GDM, SH3BP5, MIS12, and ITGAM were low-expressed, while PRRG1 was high-expressed. The TF-gene regulatory network showed that the hub genes could regulate multiple transcription factors separately. In vitro experiments demonstrated that PRRG1 knockdown significantly enhanced the viability, migration, and invasion of GDM cells.Table: Table [3, 4] was received; however, no citation was provided in the manuscript. Please provide the location of where to insert the citation in the main body of the text. Otherwise, kindly advise us on how to proceed. Please note that tables should be cited in ascending numerical order in the main body of the textDear editor, please consider removing the Tables 3 and 4 in the paper, since the data of molecular docking are absent in the current paper.

We provided four novel biomarkers targeting oxidative stress for the treatment of GDM.

Primary hyperparathyroidism (PHPT) is a prevalent endocrine disorder characterized by disrupted calcium-phosphorus homeostasis. Accurate biochemical assessment, including albumin-corrected calcium, and preoperative localization of parathyroid adenomas are essential for optimal management. This study aimed to evaluate temporal changes in imaging detectability, biochemical markers, and adenoma size, and to assess novel biochemical indices in patients with asymptomatic PHPT (aPHPT).In this multicenter retrospective study, 416 aPHPT patients underwent clinical, biochemical, and radiological evaluation at three time points. Biochemical parameters included albumin-corrected calcium, phosphorus, parathyroid hormone (PTH), 25-hydroxyvitamin D, alkaline phosphatase (ALP), and 24-hour urinary calcium. Novel indices-calcium/phosphorus (Ca/P), PTH/phosphorus (PTH/P), and calcium×chloride/phosphorus (Ca×Cl/P)-were calculated to evaluate diagnostic and predictive value. Imaging included high-resolution neck ultrasonography, 99mTc-sestamibi SPECT/CT, and four-dimensional CT to assess adenoma detectability and size changes. Statistical analyses included repeated-measures ANOVA or Friedman tests for temporal comparisons, correlation analyses, logistic regression for predictors of adenoma detection, and ROC curves to evaluate diagnostic accuracy. A p-value<0.05 was considered significant.Among 416 patients (87% female), ultrasound-detected adenomas decreased over time due to surgery of clearly visible lesions. CT and SPECT/CT initially improved localization, with later decline in CT but continued gains in SPECT/CT. Adenoma size increased, and the PTH/phosphorus ratio changed significantly. Baseline albumin-corrected calcium, phosphorus, and adenoma size predicted radiological detectability, with ROC AUCs of 0.78 for adenoma size and 0.72 for phosphorus. Surgically treated patients exhibited more pronounced biochemical abnormalities and superior CT-based localization.Following imaging and biochemical assessments, including albumin-corrected calcium, improve detection, monitoring, and management of aPHPT. Novel indices such as PTH/phosphorus and Ca/P ratios provide practical, low-cost tools for early disease identification and risk stratification. Integrating dynamic biochemical markers with imaging supports individualized, evidence-based clinical decision-making.

Breast cancer (BC) screening can detect BC early to reduce mortality. This study evaluated the impact of BC screening on the incidence of late-stage BC in a population-based setting in the Netherlands.

All Dutch women aged 50-74 years diagnosed with invasive BC or ductal carcinoma in situ (DCIS) between 2007 and 2016 (n = 108,253) were included from the Netherlands Cancer Registry. BC was classified as screen-related if diagnosed within 24 months the last screening attendance, and as screen-detected if diagnosed within 12 months after positive screening result. Late-stage BC was defined in two ways: advanced BC, including TNM stages T3, T4, or N2, N3, or M1, and metastatic BC, defined as M1 disease. Multivariable logistic regression adjusted for age and socioeconomical status was used to assess associations between screen-related and screen-detected BC and late-stage BC. Analyses were done overall and stratified by HR/HER2-defined subtypes.

BC incidence increased between 2007 and 2013 and decreased slightly thereafter. Advanced BC incidence decreased between 2007 and 2016, while metastatic BC rates remained stable. Non-screen-related BCs were significantly more likely to be present as late disease compared with screen-related (advanced BC: aOR = 3.24, 95%CI = 3.12-3.37; metastatic BC: aOR = 6.40, 95%CI = 5.98-6.85). Similarly, non-screen-detected BCs had substantial higher odds of being late than screen-detected BCs (advanced BC: aOR = 5.54, 95%CI = 5.31-5.78; metastatic BC: aOR = 12.66, 95% CI = 11.41-14.05) than screen-detected BCs. These associations were observed across all HR/HER2-defined subtypes.

Population-based screening is strongly associated with earlier-stage breast cancer at diagnosis, consistently across all immunohistochemistry subtypes.

Composite lymphoma (CL), composed of follicular lymphoma (FL) and nodal T-follicular helper cell lymphoma (nTFHL), is an uncommon and diagnostically challenging entity. We present a small series of such cases to characterize their clinicopathologic and diagnostic features.

We retrospectively analyzed 3 CL cases compared with 6 control cases of FL with expanded reactive T-follicular helper cells.

Histologically, all 3 CL cases demonstrated geographic zonation of the 2 neoplastic components, with the B-cell lymphoma residing in follicle centers (B-zones) and the T-cell neoplasm confined to perifollicular/interfollicular areas (T-zones), in contrast to a predominantly (83%) intrafollicular distribution of T-follicular helper cells in the control cases. In all CL cases, FL was suggested by histopathologic features, and the diagnosis was supported by flow cytometry. All 3 cases (100%) showed cytologic atypia and immunophenotypic aberrancy in the T-cell component, whereas none (0%) were observed in the control group. In 2 cases (66.7%), scattered Epstein-Barr virus-positive cells were seen in the T-zone, suggesting latent infection in bystander cells, again compared to none (0%) in the control. Genomic sequencing was performed in 2 cases, both (100%) showing pathogenic mutations associated with nTFHL, while none (0%) of the controls showed such mutations. Biclonality was confirmed by B-cell and T-cell receptor gene rearrangement analyses in all 3 CL cases. All patients with CL presented with an aggressive clinical course.

This series highlights the unique histopathologic characteristics of CL and underscores the importance of a multifaceted approach to diagnosis.

Eosinophilic lung diseases encompass a heterogeneous spectrum of disorders characterized by the accumulation of eosinophils within the lung parenchyma. Etiologies range from primary eosinophilic syndromes to secondary causes such as parasitic and fungal infections, hematologic malignancies, allergic conditions, and systemic autoimmune diseases. Given their overlapping clinical and radiologic presentations, accurate and timely diagnosis is critical for guiding appropriate management and avoiding both overtreatment and delays in therapy. This review synthesizes current evidence and expert perspectives on the differential diagnosis of eosinophilic lung diseases, drawing on clinical, laboratory, radiologic, and histopathologic approaches. Key emphasis is placed on distinguishing primary eosinophilic syndromes from secondary causes, the role of molecular and immunologic testing, and the integration of multidisciplinary expertise. A comprehensive diagnostic algorithm is presented to assist clinicians in routine practice, with particular emphasis on addressing unmet needs such as biomarker development and the establishment of standardized definitions for disease activity. By elucidating diagnostic processes and minimizing common errors, this article seeks to enhance the precision of differential diagnosis and improve clinical outcomes for patients with eosinophilic lung involvement.