ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

Objective To explore the effectiveness of the generative large language model MedGo in nursing decision-making for elderly patients with multimorbidity. Methods A quasi-randomized controlled trial study was conducted involving 6 junior nurses, 6 senior nurses and the MedGo model from January 1, 2025 to March 31, 2025 at the Emergency Internal Medicine Ward of Shanghai East Hospital Affiliated to Tongji University. Clinical data of 120 elderly patients with multimorbidity were analyzed to compare the performance of the three groups in four tasks (nursing diagnosis assessment, nursing intervention formulation, complication identification, and complication prevention) from three evaluation dimensions: decision-making time consumption, decision accuracy, and decision-making quality. Results In terms of decision-making time, the senior nurse group completed all four tasks faster than the junior nurse group (P＜0.01), and the MedGo group completed all four tasks faster than the junior nurse group (P＜0.001) and the senior nurse group (P＜0.001). In terms of decision-making accuracy, senior nurse group scored higher than junior nurse group in all four tasks (P＜0.001), while the MedGo group outperformed the senior nurse group only in complication identification (P＜0.001). In terms of decision-making quality, the MedGo group scored higher than junior nurse group (P＜0.001) and senior nurse group (P＜0.001) in all four tasks. Conclusions The MedGo model demonstrates advantages of high efficiency, accuracy, and quality in nursing decision-making for elderly patients with multimorbidity; senior nurses outperform junior nurses in decision-making, providing diverse references for clinical nursing decision-making.

Periodontitis is a chronic inflammatory disease. The heterotopic colonization of periodontal pathogens results in the development of several systemic diseases. Porphyromonas gingivalis (P. gingivalis), a key pathogen for periodontitis, has been linked to the development of various cancers, such as oral squamous cell carcinoma (OSCC), lung cancer, esophageal cancer, pancreatic cancer, colorectal cancer, cervical cancer, and prostate cancer. P. gingivalis promote the progression of tumor through various mechanisms, P. gingivalis regulates proteins targeting cell cycle and apoptosis to promote proliferation of tumor cells directly, enhances tumor stemness by upregulating the expression of cluster of differentiation 44 (CD44) and cluster of differentiation 133 (CD133), activates inflammasome and p38/c-Jun N-terminal kinase 1(JNK) pathways, regulates tumor-associated neutrophil (TAN) polarization to remodel the tumor microenvironment, regulates epithelial-mesenchymal transition (EMT) to promote tumor metastasis, remodel macrophage function to evade host immune response, and regulates multi-communicating with symbiotic bacteria. In addition, P. gingivalis accelerates the progression of esophageal cancer, pancreatic cancer, colorectal cancer, and prostate cancer by promoting cell proliferation, inhibiting apoptosis, inducing chronic inflammation, and escaping immunity. However, the oral microbiome is a complex system, whether the interactions between oral bacteria affect tumor progression needs to be further investigated.

Background Benzothiazoles and benzotriazoles are ubiquitously detected in drinking water, posing potential health risks. Developing a reliable and sensitive analytical method is critical for assessing their exposure levels and associated risks. Objective To establish an automated solid-phase extraction (SPE) coupled with liquid chromatography-tandem mass spectrometry method for the simultaneous determination of benzothiazole, 2-aminobenzothiazole, benzotriazole, and 5-chlorobenzotriazole in drinking water. Methods Key parameters were systematically optimized. Three mobile phase systems were compared to evaluate their effects on chromatographic peak shape and separation; three SPE cartridges were tested for extraction efficiency; the influences of water pH on extraction recoveries and matrix effects were investigated; the contributions of pretreatment steps to benzothiazole blank were analyzed, and control measures were established; nitrogen evaporation temperatures were tested to ensure analyte stability. The optimized parameters were used to develop the method, validate its performance, and analyze drinking water samples. Results Drinking water samples were first adjusted to pH 6.0 with formic acid, and then extracted using HLB cartridges. After elution with 6 mL methanol, the eluate was concentrated under nitrogen evaporation at 45 °C, followed by separation on a C18 column using a gradient elution of acetonitrile-0.1% formic acid solution, and tandem mass spectrometry detection. Avoiding nitrogen blow-drying during SPE and eliminating the use of polypropylene materials during nitrogen evaporation can effectively minimize benzothiazole contamination. Good calibration linearity was obtained for the target analytes in the concentration range of 5.0-250 μg·L⁻¹, with a correlation coefficient of r > 0.995. The method detection limits were in the range of 1.0-5.0 ng·L⁻¹. The recoveries of the target analytes in pure water and tap water were 80.2%-119.5% and 72.2%-115.6%, respectively, with relative standard deviations of were 3.2%-12.8% and 2.3%-11.6%, respectively. When applying this method to actual water samples, benzotriazole was detected in 100% of treated and tap water samples, with median concentrations of 79.4 ng·L⁻¹ and 114 ng·L⁻¹, respectively. Benzothiazole was detected in 83.3% of treated water samples and 100% of tap water samples, with median concentrations of 48.3 ng·L⁻¹ and 65.4 ng·L⁻¹, respectively. In addition, 5-chloro-benzotriazole exhibited low detection rates and concentrations, while 2-amino-benzothiazole was undetected. Conclusion The developed method demonstrates high accuracy, reliability, and sensitivity, making it suitable for the analysis of trace levels of benzothiazoles and benzotriazoles in drinking water.

Vaccines are highly effective, but rare or delayed adverse events following immunization (AEFIs) require post-licensure surveillance beyond clinical trials. Korea lacks a comprehensive, active, database-based framework, yet key assets exist: nationwide claims databases (National Health Insurance Service/Health Insurance Review and Assessment Service), the national immunization registry (Korea Disease Control and Prevention Agency’s Immunization Registry Information System) for National Immunization Program (NIP) and non-NIP vaccines, and increasingly standardized hospital electronic health records.We propose a federated, code to data architecture with data linkages between these data.Implementation should adopt a common data model (CDM), standardized case definitions, latency accounting, and transparent public reporting under strong privacy governance. Major challenges include multi step administrative approvals for data linkage, incomplete capture of adult non-NIP vaccinations, heterogeneous hospital data structures, and strict data protection constraints. Strategic priorities are to streamline statutory and administrative processes for public health use, mandate or enable claims-based capture of adult vaccinations, enhance CDM based interoperability, and develop secure hubs for aggregated outputs. With these measures, Korea will be well positioned to establish a scalable active surveillance system capable of detecting rare AEFIs, supporting transparent and evidence-based communication, and ensuring equitable injury compensation grounded in domestic data.

Objective: This study aimed to develop a reliable and valid Mixed State Severity Index (MSSI) to assess mood instability in patients with mood disorders and determine cutoff scores. Methods: Twenty-one items were selected based on Koukopoulos’ criteria for mixed depressive episode, historically referred to as agitated depression, and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision mixed features criteria. The MSSI was administered to 242 patients (major depressive disorder [n=92], bipolar disorder [BD] I [n=78], and BD II [n=72]) and 726 controls. Results: The MSSI demonstrated high internal consistency (α=0.78–0.90). Exploratory factor analysis revealed a stable four-factor structure. Based on receiver operating characteristic analysis, optimal cutoff scores were identified to distinguish mood disorder groups from controls, ranging from 19.5 to 27.5 depending on diagnosis. Conclusion The MSSI is a reliable and valid instrument for assessing the severity of mixed features in patients with mood disorders. The established cutoff scores enhance its clinical utility, providing robust diagnosis and treatment planning support.

To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.