Objective: To evaluate the effect of community comprehensive management model intervention among patients with dyslipidemia, so as to provide the reference for optimizing community management strategies and improving the target achievement rate for blood lipids among this population. Methods: From May to June 2023, a multi-stage stratified random sampling method was employed to select patients with dyslipidemia from primary healthcare institutions in Jiaxing City, Zhejiang Province. Eligible participants were randomly assigned to either a control group or an intervention group. The control group received routine management, while the intervention group was subjected to a community comprehensive management model in addition to the routine care. Both groups were followed up for 24 months. Data on demographic characteristics, lifestyle behaviors, physical examination indices, and blood biochemical indicators were collected at baseline and after the intervention through questionnaires, physical examinations, and laboratory tests. Changes in obesity rate, central obesity rate, target achievement rates for blood lipids, blood pressure, and blood glucose, as well as lifestyle modifications, were analyzed. Differences between the two groups before and after the intervention were assessed using generalized estimating equations (GEE). Results: The control group consisted of 560 patients, including 303 females (54.11%) and 430 individuals aged ≥65 years (76.79%). The intervention group also included 560 patients, with 300 females (53.57%) and 431 individuals aged ≥65 years (76.96%). Before the intervention, no statistically significant differences were observed between the two groups in terms of gender, age, educational level, history of chronic diseases, and atherosclerotic cardiovascular disease risk stratification (all P>0.05). After 24 months of intervention, interaction effects between group and time were observed for obesity rate, central obesity rate, target achievement rate for blood lipids, target achievement rate for blood glucose, composite target achievement rate, physical activity rate, and medication adherence (all P<0.05). Specifically, the intervention group demonstrated lower rates of obesity and central obesity, and higher target achievement rate of blood lipids, target achievement rate of blood glucose, composite target achievement rate, physical activity rate, and medication adherence compared to the control group. Conclusion The community comprehensive management model contributed to improvements in multiple metabolic parameters (including body weight, waist circumference, blood lipids, and blood glucose) among patients with dyslipidemia, and was associated with increased physical activity rate and medication adherence.

ObjectiveThis paper aims to clarify the material basis of Gualou Niubangtang and establish a quantitative analysis method for its main constituents， providing a reference for the overall quality control of this preparation. MethodsThe constituents in the formula were systematically characterized based on ultra-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry （UPLC-Q-TOF-MS/MS）. Identification was performed by matching with the UNIFI 9.6 software and utilizing database platforms such as PubChem， ChemicalBook， and ChemSpider， combined with relevant literature reports. A quantitative analysis method for the seven main constituents in Gualou Niubangtang was established by using high performance liquid chromatography （HPLC）. ResultsUPLC-Q-TOF-MS/MS analysis identified 155 constituents， including 69 flavonoids， 36 terpenoids， 23 phenylpropanoids， 8 phenylethanoid glycosides， and 19 other types of constituents. In the established quantitative analysis method， the seven main constituents showed good linearity within their respective linear ranges. The precision， repeatability， stability， and spike recovery all met the required standards. The results showed that the content ranges of geniposide， liquiritin， hesperidin， arctiin， baicalin， oroxylin A-7-O-β-D-glucuronide， and wogonoside in 15 batches of Gualou Niubangtang were 13.67-21.25， 1.20-7.64， 5.45-7.45， 22.97-33.51， 29.95-39.07， 2.58-4.80， and 6.56-9.31 mg·g^-1， respectively. ConclusionThis study successfully characterizes and attributes multi-category constituents in Gualou Niubangtang， clarifying that its material basis is primarily composed of flavonoids， terpenoids， phenylethanoid glycosides， and phenylpropanoids. Furthermore， it enables the quantification of seven constituents within the formula. This work lays a foundation for research on the quality control， action mechanism， and clinical application of this formula.

Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

ObjectiveTo analyze the infection status of main respiratory pathogens in influenza-like illness (ILI) cases in Anji County, Huzhou City, Zhejiang Province, and to provide a reference for the prevention, diagnosis, and treatment of respiratory infections. MethodsThroat swab samples were collected from 520 ILI cases in an influenza sentinel surveillance hospital in Anji County of Zhejiang Province from December 2023 to November 2024. Multiplex real-time fluorescence quantitative polymerase chain reaction (mRT-PCR) was used to detect 18 pathogens and their subtypes, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (Flu A), influenza A (H1N1) virus, influenza A (H3N2) virus, influenza B virus (Flu B), influenza B virus Victoria lineage (BV), influenza B virus Yamagata lineage (BY), coronavirus (CoV), human parainfluenza virus (HPIV), respiratory syncytial virus (RSV), human metapneumovirus (HMPV), adenovirus (ADV), human bocavirus (HBoV), enterovirus (EV), rhinovirus (RV), Mycoplasma pneumoniae (MP), Chlamydia pneumoniae (CP), and Streptococcus pneumoniae (SP). ResultsThe overall positivity rate of pathogens in 520 samples was 33.65%, among which the detection rates of Flu (9.14%), ADV (7.50%), SARS-CoV-2 (6.15%), and EV (3.65%) were relatively high. There were statistically significant differences in the overall positivity rate of pathogens by age and season (all P<0.05). The highest overall positivity rate was observed in the 5‒14 years old group (42.77%), and the overall positivity rate in winter (53.08%) was significantly higher than that in other seasons. ConclusionFrom 2023 to 2024, the main respiratory pathogens detected in ILI cases in Anji County were Flu, ADV, SARS-CoV-2, and EV. The epidemic characteristics showed age and seasonal specificity, so it is necessary to strengthen prevention and control for high-risk populations and epidemic seasons in a targeted manner.

OBJECTIVE To investigate the risk factors for sodium valproate （VPA）-induced hyperammonemia in neurocritical patients， and to construct a risk prediction model. METHODS Clinical data were retrospectively collected from 172 neurocritical patients who received VPA treatment in the Department of Critical Care Medicine， the Fourth Affiliated Hospital of Soochow University from January 2022 to June 2025. Patients were divided into the hyperammonemia group （73 cases） and the normal group （99 cases） based on their blood ammonia levels. Univariate analysis and LASSO regression analysis were used to screen for predictive variables. Independent factors were identified through multivariate Logistic regression analysis， and a nomogram was constructed accordingly. The performance of the model was evaluated using receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis （DCA）. RESULTS Combination of univariate analysis and LASSO regression analysis screened out seven predictive variables： body mass index （BMI）≥24.0 kg/m 2 ， concomitant use of benzodiazepines， VPA blood concentration， hemoglobin， serum urea， average daily VPA dose， and albumin. Multivariate Logistic regression analysis showed that concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， VPA blood concentration， albumin and serum urea level （with odds ratios of 1.615， 1.538， 1.623， 1.942 and 0.637， respectively； 95% confidence intervals of 1.128-2.359， 1.059-2.251， 1.112-2.431， 1.106-3.598 and 0.402-0.980， respectively） were all significantly associated with VPA-induced hyperammonemia in neurocritical patients （ P ＜0.05）. The nomogram prediction model constructed based on these variables was evaluated， showing that the area under the ROC curve was 0.810 for the test set and 0.844 for the validation set. The calibration curves closely approximated t he actual curves， and the application of this model could improve the clinical net benefit. CONCLUSIONS Concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， high VPA blood concentration and high albumin level are independent risk factors for VPA-induced hyperammonemia in neurocritical patients， while high serum urea level is an independent protective factor. The risk prediction model constructed based on these factors exhibits good discrimination， consistency， and clinical applicability， making it applicable for predicting the risk of VPA-induced hyperammonemia in neurocritical patients.

ObjectiveTo investigate the effect of neuromuscular electrical stimulation (NMES) on quadriceps muscle strength and walking for patients after anterior cruciate ligament reconstruction (ACLR). MethodsThirty-four patients after ACLR were selected at Beijing Rehabilitation Hospital of Capital Medical University from July, 2022 to October, 2023, and randomly divided into control group (n = 17) and experimental group (n = 17). Both groups received routine rehabilitation and functional training, and the experimental group received NMES during the functional training, while the control group received sham NMES, for eight weeks. Quadriceps peak torque-to-weight ratio, single-leg support phase and plantar impulses during walking were measured before and after intervention. ResultsTwo cases in the control group and three in the experimental group dropped down. Quadriceps peak torque-to-weight ratio improved in both groups after intervention (|t| > 17.578, P < 0.001), and improved more in the experimental group than in the control group (t = 4.714, P < 0.001); while the affected single-leg support phase and the affected/unaffected single-leg support phase ratio improved in both groups (|t| > 16.882, P < 0.001), and improved more in the experimental group than in the control group (t > 3.234, P < 0.01); and plantar impulses of all zones optimized in both groups (t > 9.221, P < 0.001), and were better in the experimental group than in the control group(|t| > 2.852, P < 0.01). ConclusionNMES may further improve quadriceps muscle strength, plantar pressure distribution during walking and single-leg support in patients after ACLR.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

With the transformation in modern medical models and the increasingly diversified needs of patients， building a harmonious and mutually trusting doctor-patient community relationship has become the key to improving the quality of medical services， enhancing patients’ sense of access to medical care， and promoting medical effects. Medical social worker is an indispensable member of the medical team， whose interdisciplinary background knowledge and professional skills provide unique advantages for building a harmonious doctor-patient community relationship. However， the current subjects of research on the doctor-patient community are still limited to the medical staff and patients， and there is a lack of relevant research that uses interdisciplinary thinking and tools to explore the path of building a doctor-patient community. Therefore， under the guidance of the spiral research idea of action research method， by sorting out the action paths of medical social workers in carrying out pediatric neurosurgery specialist services in the past five years， three analytical tools from management， namely the strategic decision-making process model， the organization- stakeholder fit model， and the value proposition canvas， were used to solve the problems and dilemmas in the different stages of building a doctor-patient community. On these foundations， practical knowledge was produced， providing valuable experience and methods for medical social workers to build a doctor-patient community.

Background: and Purpose Guillain–Barré syndrome (GBS) is an autoimmune-mediated disorder characterized by demyelinating or axonal injury of the peripheral nerve. Our aim is to determine whether serum amyloid A (SAA) is a biomarker of demyelinating injury and disease severity in patients with GBS. Methods: This study retrospectively enrolled 40 patients with either the demyelinating or axonal GBS and sex- and age-matched controls with other neurological diseases as well as healthy subjects. The demographic and clinical features at entry were collected. The serum levels of the SAA isoforms SAA1, SAA2, and SAA4 were determined in the patients with GBS and the controls using the enzyme-linked immunosorbent assay and analyzed for the associations between levels of different SAA isoforms and the clinical features of the patients. Results: The levels of SAA2 and SAA4 were significantly higher in patients with GBS than in both the other neurological disease controls and the healthy subjects (p<0.05 for all). The level of SAA1 did not differ between patients with GBS and the controls. The level of SAA2 was considerably higher in GBS patients with antecedent infection than in those without infection (p=0.020). The levels of different SAA isoforms were not associated with the disease severity or other clinical features of patients with GBS (p>0.05 for all). Conclusions Increased levels of SAA2 and SAA4 may only represent the acute inflammatory status and so cannot be utilized as biomarkers of the disease severity or demyelinating injury in patients with GBS.

Background: and Purpose Guillain–Barré syndrome (GBS) is an autoimmune-mediated disorder characterized by demyelinating or axonal injury of the peripheral nerve. Our aim is to determine whether serum amyloid A (SAA) is a biomarker of demyelinating injury and disease severity in patients with GBS. Methods: This study retrospectively enrolled 40 patients with either the demyelinating or axonal GBS and sex- and age-matched controls with other neurological diseases as well as healthy subjects. The demographic and clinical features at entry were collected. The serum levels of the SAA isoforms SAA1, SAA2, and SAA4 were determined in the patients with GBS and the controls using the enzyme-linked immunosorbent assay and analyzed for the associations between levels of different SAA isoforms and the clinical features of the patients. Results: The levels of SAA2 and SAA4 were significantly higher in patients with GBS than in both the other neurological disease controls and the healthy subjects (p<0.05 for all). The level of SAA1 did not differ between patients with GBS and the controls. The level of SAA2 was considerably higher in GBS patients with antecedent infection than in those without infection (p=0.020). The levels of different SAA isoforms were not associated with the disease severity or other clinical features of patients with GBS (p>0.05 for all). Conclusions Increased levels of SAA2 and SAA4 may only represent the acute inflammatory status and so cannot be utilized as biomarkers of the disease severity or demyelinating injury in patients with GBS.