ObjectiveTo understand the epidemiological distribution and gene evolutionary variation of influenza A (H3N2) viruses in Fengxian District, Shanghai, in the surveillance year of 2023, and to provide a reference basis for influenza prevention and control. MethodsThe prevalence of influenza virus in Fengxian District in the 2023 influenza surveillance year (April 2023‒March 2024) was analyzed. The hemagglutinin (HA) gene, neuraminidase (NA) gene, and amino acid sequences of 75 strains of H3N2 influenza viruses were compared with the vaccine reference strain for similarity matching and phylogenetic evolutionary analysis, in addition to an analysis of gene characterization and variation. ResultsIn Fengxian District, there was a mixed epidemic of H3N2 and H1N1 in the spring of 2023, with H3N2 being the predominant subtype in the second half of the year, and Victoria B becoming the predominant subtype in the spring of 2024. A total of 75 influenza strains of H3N2 with HA and NA genes were distributed in the 3C.2a1b.2a.2a.2a.3a.1 and B.4 branches, with overall similarity to the reference strain of the 2024 vaccine higher than that of the reference strain of the 2022 and 2023 vaccine. Compared with the 2023 vaccine reference strain, three antigenic sites and one receptor binding site were changed in HA, with three glycosylation sites reduced and two glycosylation sites added; where as in NA seven antigenic sites and the 222nd resistance site changed with two glycosylation sites reduced. ConclusionThe risk of antigenic variation and drug resistance of H3N2 in this region is high, and it is necessary to strengthen the publicity and education on the 2024 influenza vaccine and long-term monitoring of influenza virus prevalence and variation levels.

BACKGROUND: In the interim analysis of MONARCH plus, adding abemaciclib to endocrine therapy (ET) improved progression-free survival (PFS) and objective response rate (ORR) in predominantly Chinese postmenopausal women with HR+/HER2- advanced breast cancer (ABC). This study presents the final pre-planned PFS analysis. METHODS: In the phase III MONARCH plus study, postmenopausal women in China, India, Brazil, and South Africa with HR+/HER2- ABC without prior systemic therapy in an advanced setting (cohort A) or progression on prior ET (cohort B) were randomized (2:1) to abemaciclib (150 mg twice daily [BID]) or placebo plus: anastrozole (1.0 mg/day) or letrozole (2.5 mg/day) (cohort A) or fulvestrant (500 mg on days 1 and 15 of cycle 1 and then on day 1 of each subsequent cycle) (cohort B). The primary endpoint was PFS of cohort A. Secondary endpoints included cohort B PFS (key secondary endpoint), ORR, overall survival (OS), safety, and health-related quality of life (HRQoL). RESULTS: In cohort A (abemaciclib: n  = 207; placebo: n  = 99), abemaciclib plus a non-steroidal aromatase inhibitor improved median PFS vs . placebo (28.27 months vs . 14.73 months, hazard ratio [HR]: 0.476; 95% confidence interval [95% CI]: 0.348-0.649). In cohort B (abemaciclib: n  = 104; placebo: n  = 53), abemaciclib plus fulvestrant improved median PFS vs . placebo (11.41 months vs . 5.59 months, HR: 0.480; 95% CI: 0.322-0.715). Abemaciclib numerically improved ORR. Although immature, a trend toward OS benefit with abemaciclib was observed (cohort A: HR: 0.893, 95% CI: 0.553-1.443; cohort B: HR: 0.512, 95% CI: 0.281-0.931). The most frequent grade ≥3 adverse events in the abemaciclib arms were neutropenia, leukopenia, anemia (both cohorts), and lymphocytopenia (cohort B). Abemaciclib did not cause clinically meaningful changes in patient-reported global health, functioning, or most symptoms vs . placebo. CONCLUSIONS: Abemaciclib plus ET led to improvements in PFS and ORR, a manageable safety profile, and sustained HRQoL, providing clinical benefit without a high toxicity burden or reduced quality of life. TRIAL REGISTRATION ClinicalTrials.gov (NCT02763566).
Humans ; Female ; Fulvestrant/therapeutic use* ; Breast Neoplasms/metabolism* ; Aminopyridines/therapeutic use* ; Benzimidazoles/therapeutic use* ; Middle Aged ; Aromatase Inhibitors/therapeutic use* ; Aged ; Receptor, ErbB-2/metabolism* ; Adult ; Letrozole/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Anastrozole/therapeutic use*

Transarterial radioembolization (TARE) is a widely utilized therapeutic approach for hepatocellular carcinoma (HCC), however, the clinical implementation is constrained by the stringent preparation conditions of radioembolization agents. Herein, we incorporated the superstable homogeneous iodinated formulation technology (SHIFT), simultaneously utilizing an enhanced solvent form in a carbon dioxide supercritical fluid environment, to encapsulate radionuclides (such as ¹³¹I,¹⁷⁷Lu, or ¹⁸F) with lipiodol for the preparation of radiolipiodol. The resulting radiolipiodol exhibited exceptional stability and ultra-high labeling efficiency (≥99%) and displayed notable intratumoral radionuclide retention and in vivo stability more than 2 weeks following locoregional injection in subcutaneous tumors in mice and orthotopic liver tumors in rats and rabbits. Given these encouraging findings, ¹⁸F was authorized as a radiotracer in radiolipiodol for clinical trials in HCC patients, and showed a favorable tumor accumulation, with a tumor-to-liver uptake ratio of ≥50 and minimal radionuclide leakage, confirming the feasibility of SHIFT for TARE applications. In the context of transforming from preclinical to clinical screening, the preparation of radiolipiodol by SHIFT represents an innovative physical strategy for radionuclide encapsulation. Hence, this work offers a reliable and efficient approach for TARE in HCC, showing considerable promise for clinical application (ChiCTR2400087731).

OBJECTIVES: We propose a multi-feature fusion model based on manually extracted features and deep learning features from endoscopic images for grading rebleeding risk of peptic ulcers. METHODS: Based on the endoscopic appearance of peptic ulcers, color features were extracted to distinguish active bleeding (Forrest I) from non-bleeding ulcers (Forrest II and III). The edge and texture features were used to describe the morphology and appearance of the ulcers in different grades. By integrating deep features extracted from a deep learning network with manually extracted visual features, a multi-feature representation of endoscopic images was created to predict the risk of rebleeding of peptic ulcers. RESULTS: In a dataset consisting of 3573 images from 708 patients with Forrest classification, the proposed multi-feature fusion model achieved an accuracy of 74.94% in the 6-level rebleeding risk classification task, outperforming the experienced physicians who had a classification accuracy of 59.9% (P<0.05). The F1 scores of the model for identifying Forrest Ib, IIa, and III ulcers were 90.16%, 75.44%, and 77.13%, respectively, demonstrating particularly good performance of the model for Forrest Ib ulcers. Compared with the first model for peptic ulcer rebleeding classification, the proposed model had improved F1 scores by 5.8%. In the simplified 3-level risk (high-risk, low-risk, and non-endoscopic treatment) classification task, the model achieved F1 scores of 93.74%, 81.30%, and 73.59%, respectively. CONCLUSIONS The proposed multi-feature fusion model integrating deep features from CNNs with manually extracted visual features effectively improves the accuracy of rebleeding risk classification for peptic ulcers, thus providing an efficient diagnostic tool for clinical assessment of rebleeding risks of peptic ulcers.
Humans ; Deep Learning ; Peptic Ulcer ; Risk Assessment ; Peptic Ulcer Hemorrhage ; Recurrence

Approximately 20% to 30% of the global workforce is engaged in shift work. As a significant cause of circadian disruption, shift work is closely associated with an increased risk for periodontitis. Nevertheless, how shift work-related circadian disruption functions in periodontitis remains unknown. Herein, we employed a simulated shift work model constructed by controlling the environmental light-dark cycles and revealed that shift work-related circadian disruption exacerbated the progression of experimental periodontitis. RNA sequencing and in vitro experiments indicated that downregulation of the core circadian protein brain and muscle ARNT-like protein 1 (BMAL1) and activation of the Gasdermin D (GSDMD)-mediated pyroptosis were involved in the pathogenesis of that. Mechanically, BMAL1 regulated GSDMD-mediated pyroptosis by suppressing NOD-like receptor protein 3 (NLRP3) inflammasome signaling through modulating nuclear receptor subfamily 1 group D member 1 (NR1D1), and inhibiting Gsdmd transcription via directly binding to the E-box elements in its promoter. GSDMD-mediated pyroptosis accelerated periodontitis progression, whereas downregulated BMAL1 under circadian disruption further aggravated periodontal destruction by increasing GSDMD activity. And restoring the level of BMAL1 by circadian recovery and SR8278 injection alleviated simulated shift work-exacerbated periodontitis via lessening GSDMD-mediated pyroptosis. These findings provide new evidence and potential interventional targets for circadian disruption-accelerated periodontitis.
Pyroptosis/physiology* ; ARNTL Transcription Factors/metabolism* ; Animals ; Periodontitis/etiology* ; Mice ; Phosphate-Binding Proteins/metabolism* ; Shift Work Schedule/adverse effects* ; Intracellular Signaling Peptides and Proteins/metabolism* ; Mice, Inbred C57BL ; Male ; Disease Models, Animal ; Gasdermins

Drug development remains a critical issue in the field of biomedicine. With the rapid advancement of information technologies such as artificial intelligence (AI) and the advent of the big data era, AI-assisted drug development has become a new trend, particularly in predicting drug-target associations. To address the challenge of drug-target prediction, AI-driven models have emerged as powerful tools, offering innovative solutions by effectively extracting features from complex biological data, accurately modeling molecular interactions, and precisely predicting potential drug-target outcomes. Traditional machine learning (ML), network-based, and advanced deep learning architectures such as convolutional neural networks (CNNs), graph convolutional networks (GCNs), and transformers play a pivotal role. This review systematically compiles and evaluates AI algorithms for drug- and drug combination-target predictions, highlighting their theoretical frameworks, strengths, and limitations. CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions. GCNs provide deep insights into molecular interactions via relational data, whereas transformers increase prediction accuracy by capturing complex dependencies within biological sequences. Network-based models offer a systematic perspective by integrating diverse data sources, and traditional ML efficiently handles large datasets to improve overall predictive accuracy. Collectively, these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy. This review summarizes the application of AI in drug development, particularly in drug-target prediction, and offers recommendations on models and algorithms for researchers engaged in biomedical research. It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.

Objective To explore the potential role and underlying mechanism of the functionally uncharacterized gene Gm49394 on regulating β-cell apoptosis under diabetic conditions.Methods The expression and translational activity of Gm49394 in pancreatic β-cell lines and non-β-cell lines were validated using RNA fluorescence in situ hybridization(RNA-FISH),quantitative real-time PCR(qPCR),Western blotting,and immunofluorescence(IF)assay.The β-cell lines(NIT-1/Min6)with Gm49394 overexpression or knockdown were constructed.The proliferation,apoptosis,mitochondrial function,as well as oxidative stress and endoplasmic reticulum stress markers in these β-cell lines under physiological homeostasis or pathological stress conditions,such as high glucose(30 mmol/L),inflammation(10 ng/mL IFN-γ alone or combined with 10 ng/mL IL-6),and hydrogen peroxide(100 μmol/L H2O2)were detected by flow cytometry and Western blotting.Results RNA-FISH and qPCR indicated that Gm49394 was specifically expressed in pancreatic β-cell lines and up-regulated under high glucose or inflammatory stimulation.IF assay and Western blotting showed that Gm49394 had protein-coding activity.Flow cytometry and Western blotting identified that Gm49394 overexpression did not affect β-cell proliferation,but promoted β-cell apoptosis and increased reactive oxygen species(ROS)and mitochondrial superoxide(MitoSOX)levels in β cells under physiological homeostasis or pathological stress conditions(P<0.05).Under physiological conditions,Gm49394 knockdown failed to induce significant alterations on β-cell apoptosis,ROS,or MitoSOX levels.Under pathological stress conditions,Gm49394 knockdown significantly suppressed β-cell proliferation,apoptosis,as well as oxidative and endoplasmic reticulum stress(P<0.05).Conclusion Gm49394 may promote β-cell apoptosis via oxidative stress and endoplasmic reticulum stress.

The reform of medical insurance payment is a critical part of deepening the medical reform.It plays an important role in guiding the behavior of healthcare providers.The latest progress in the reform of health insurance payment in the US.is the imple-mentation of value-based payment models.The literature research method is applied to review the development of value-based pay-ment practices in the US.It finds the main value-based payment models in the United States are targeted hospitals and physicians as the incentive object,with the characteristics of the combination of reward and punishment,the combination of horizontal and ver-tical evaluation,the continuous improvement of evaluation system,and the full use of information means.On this basis,combined with the national conditions of China,it puts forward four suggestions on establishing effective incentive mechanism,formulating scientific evaluation system,insisting on continuous improvement mechanism and strengthening medical information construction for future reform of medical insurance.

ObjectiveTo systematically evaluate the efficacy and safety of omental wrapping technique for pancreaticojejunal anastomosis in preventing complications after pancreaticoduodenectomy. MethodsThis study was conducted according to the PRISMA guideline. English and Chinese databases including CNKI， Wanfang Data， VIP， CBM， the Cochrane Library， PubMed， Embase， and Web of Science were searched for clinical studies on omental wrapping technique for pancreaticojejunal anastomosis in preventing complications after pancreaticoduodenectomy published up to November 2022， and Stata 16 and Review Manager 5.4 were used to perform the meta-analysis. ResultsA total of 15 studies with 1 830 patients were included in this study. The meta-analysis showed that the omental wrapping group had a significantly lower overall incidence rate of postoperative pancreatic fistula （POPF） than the non-omental wrapping group （odds ratio ［OR］=0.30， 95% confidence interval ［CI］： 0.22‍ ‍—‍ ‍0.41， P<0.001）， and the subgroup analysis showed that the omental wrapping group had a significantly lower incidence rate of grade B/C POPF than the non-omental wrapping group （OR=0.29， 95%CI： 0.21‍ ‍—‍ ‍0.39， P<0.001）. Compared with the non-omental wrapping group， the omental wrapping group had significantly lower incidence rates of postoperative bile leakage （OR=0.30， 95%CI： 0.16‍ ‍—‍ ‍0.56， P<0.001）， postoperative hemorrhage （OR=0.35， 95%CI： 0.24‍ ‍—‍ ‍0.53， P<0.001）， delayed gastric emptying （OR=0.45， 95%CI： 0.31‍ ‍—‍ ‍0.64， P<0.001）， abdominal infection （OR=0.55， 95%CI： 0.40‍ ‍—‍ ‍0.75， P<0.001）， reoperation （OR=0.31， 95%CI： 0.18‍ ‍—‍ ‍0.54， P<0.001）， and death within 30 days after surgery （OR=0.42， 95%CI： 0.22‍ ‍—‍ ‍0.80， P=0.009）， a significantly earlier time to diet （mean difference ［MD］=-0.98， 95%CI： -1.84 to -0.11， P=0.03）， and a significantly shorter length of postoperative hospital stay （MD=-2.44， 95%CI： -4.10 to -0.77， P=0.004）. There were no significant differences between the two groups in the time of operation （MD=-13.68， 95%CI： -28.31 to -0.95， P=0.07） and intraoperative blood loss （MD=-17.26， 95%CI： -57.55 to -23.03， P=0.40）. ConclusionOmental wrapping can reduce the incidence rates of postoperative complications such as pancreatic fistula， bile leakage， postoperative hemorrhage， abdominal infection， and delayed gastric emptying， improve the prognosis of patients， and shorten the length of hospital stay， without increasing surgical difficulty or time of operation.