Animal experimentation constitutes a critical link between basic research and clinical application, making its research quality and translational efficiency paramount. Although considerable progress has been made in standardizing operational procedures and ethical guidelines, the standardization of outcome evaluation systems has significantly lagged, creating a key bottleneck that constrains the quality of biomedical research and evidence synthesis. This deficiency is manifested by pronounced heterogeneity in outcome selection across similar studies, incomplete methodological reporting, and disparate criteria for result interpretation, which severely impairs the comparability of findings and the evidence integration. To cope with this challenge, this paper systematically introduces a mature methodological tool from clinical research–the core outcome set (COS)–and explores its construction strategies and application potential in the field of animal experimentation. Given the extensive diversity of animal experiments, a pragmatic strategy of "focusing on key areas, implementing phased pilots, and promoting gradual expansion" should be adopted. This approach prioritizes the development of domain-specific COS for disease areas characterized by high research volume, urgent translational needs, and well-established animal models. A multi-source integration pathway for COS development is detailed, comprising systematic literature searches, methodological appraisals, and expert consensus, with the feasibility of leveraging artificial intelligence (AI) to enhance efficiency also being examined. The development and promotion of such COS are not intended to restrict scientific exploration; rather, they aim to establish a new, tiered evaluation paradigm consisting of "core outcomes" (mandatory), "recommended outcomes" (encouraged), and "exploratory outcomes" (optional). This framework is expected not only to enhance research quality through standardization and to adhere to the "3R" principles but also to accelerate the accumulation of high-quality evidence. This, in turn, provides a solid foundation for higher-level evidence synthesis, ultimately facilitating the effective translation of basic research findings into clinical practice and providing an essential methodological framework for scientific advancement in relevant disciplines.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Diabetic Peripheral Neuropathy （DPN） is one of the most common and harmful complications of type 2 diabetes. DPN's pathogenesis include high blood sugar-induced oxidative stress， inflammation， and mitochondrial dysfunction. These factors are combined to damage nerve fibers， leading to sensory issues， pain， and numbness. Through a coordinated effect， these factors trigger nerve fiber damage and lead to sensory abnormalities， pain and numbness in limbs， and other symptoms， seriously restricting patients' activities of daily living and mobility. Recent research highlights that cellular senescence plays a critical role in DPN. Cellular senescence is manifested by the loss of cell proliferation ability， and further aggravates nerve damage via oxidative stress， mitochondrial dysfunction， autophagy impairment， inflammatory reaction， and other mechanisms， accelerating DPN occurrence and progression. In terms of medical treatment， current methods focus on blood sugar control， pain relief medicine， and microcirculation improvement， while no therapy has been developed based on cellular senescence. In contrast， traditional Chinese medicine （TCM） shows a unique advantage in DPN prevention and treatment via cellular senescence modulation. TCM emphasizes a holistic approach， as well as syndrome differentiation and treatment， effective in anti-aging and nerve damage repair. Recent studies show that TCM active ingredients， including puerarin， ginsenosides， and berberine， can reduce inflammation， oxidative stress， and apoptosis via signaling pathway regulation， thereby slowing cellular senescence to alleviate nerve damage. Furthermore， TCM compounds such as Buyang Huanwutang， Taohong Siwutang， and Huangqi Guizhi Wuwutang exert synergistic effects on cellular senescence-related pathways to improve nerve health and reduce DPN clinical symptoms. Therefore， this paper reviews the literature related to the interaction between cellular senescence and DPN from the perspective of cellular senescence， summarizing the mechanism of DPN and TCM intervention strategies.

Objective: To understand the prevalence and related factors of depressive symptoms among primary and secondary school students in the in depth monitoring counties of China s Rural Compulsory Education Nutrition Improvement Program, so as to provide a basis for prevention and psychological intervention of depressive symptoms among children and adolescents in rural areas. Methods: In November 2022, a stratified random sampling method was adopted to collect height and weight data, basic personal and family information of 7 949 primary and secondary school students from grade three to grade nine through physical measurements and questionnaires in 56 key monitoring schools implementing the Student Nutrition Improvement Program in 7 in depth monitoring counties (Jalaid Banner in Inner Mongolia, Jinzhai County in Anhui, Mao Xian in Sichuan, Tiandeng County in Guangxi, Mian County in Shaanxi, Zhaozhou County in Heilongjiang and Youxi County in Fujian), and to obtain the information related to their depressive symptoms through the self assessment questionnaire on depression. Multivariate Logistic regression analysis was conducted to analyze the prevalence of depressive symptoms among primary and secondary school students, as well as their related factors. Results: The detection rate of depressive symptoms among primary and secondary school students in the in depth monitored counties was 23.5%. Logistic regression analysis showed that the probability of detecting depressive symptoms was higher among female students, middle school students, students whose video screen duration per day was >2 h, and students whose parents marital status was divorced or widowed ( OR =1.40, 1.64, 1.60, 1.24), and students whose sleep duration reached the recommended standard, whose parents usually accompanied them daily for time was 60-<120 min and ≥120 min, and students whose mothers literacy level was middle school graduation had lower probability of detecting depressive symptoms ( OR =0.85, 0.84, 0.71, 0.76) ( P < 0.05 ). Conclusion The detection rate of depressive symptoms among students in the in depth monitoring area is high, and targeted interventions need to be developed for students to reduce the risk of mental health problems.

ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4⁺ T lymphocytes. Additionally, spleen CD4⁺ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4⁺ and CD8⁺ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4⁺ and CD8⁺ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4⁺ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4⁺ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.

Objective To investigate the health literacy of naval officers and soldiers,so as to provide a reference for the development of health education and health promotion policies and measures for this population.Methods The health literacy of naval officers and soldiers was measured using the Chinese residents'health literacy questionnaire(2018).Results The health literacy level of naval officers and soldiers has met the target set by the Healthy China 2030 development plan.The order of health literacy compliance rate in 3 aspects from high to low was"healthy lifestyle and behaviors","basic health knowledge and concepts",and"essential health skills".The 6 types of problems of health literacy from high to low was"safety and first aid","scientific health perspectives","infectious disease prevention","health information","basic medical care",and"chronic disease prevention".Conclusion The overall health literacy level of naval officers and soldiers is good;the"safety and first aid"literacy has obvious advantages.It is recommended to implement continuous dynamic monitoring of health literacy,develop a targeted curriculum system to enhance health management capabilities,improve the health management ability of officers and soldiers,and further enhance the combat effectiveness.

Objective To construct and validate a nomogram-based prediction model of vascular plaque stability in patients with progressive cerebral infarction based on serum monocyte chemotactic protein-1(MCP-1),monocyte chemotactic protein-1 inducible protein 1(MCPIP1)combined with inflammatory factors.Methods A retrospective cohort study was conducted on 200 patients with progressive cerebral infarction admitted to our department from January to December 2023.All of them were assigned into a modeling group,and were divided into a stable plaque subgroup and the unstable plaque subgroup according to results of carotid multilayer spiral CT angiography.Their general data,results of laboratory tests,and other clinical indicators were collected to identify the influencing factors for vascular plaque instability with single-factor and multifactor analyses.Then a nomogram model for predicting vascular plaque stability was constructed for patients with progressive cerebral infarction.Receiver operating characteristics(ROC)curve was plotted to evaluate the predictive performance of the nomogram model.Subsequently,in a ratio of 7∶3 between the cases in the modeling group and the validation group,another 86 patients with progressive cerebral infarction admitted to our department from January to June 2024 were enrolled and served as the validation group.Their clinical data were collected for external validation of the model.Results In the modeling group,there were 68 patients(34.00％)in the stable plaque subgroup and 132 patients(66.00％)in the unstable plaque subgroup.Univariate analysis showed that there were significant differences between the 2 subgroups in terms of age(65.31±6.74 vs 67.52±7.14 years,t=2.113),comorbid diabetes mellitus[35(48.53％)vs 80(60.61％)cases,Chi-square=7.182],MCP-1(570.67±104.23 vs 693.94±128.45 pg/mL,t=6.836),MCPIP1(2.93±0.58 vs 4.08±0.75 ng/mL,t=11.051),homocysteine(Hcy,10.56±2.38 vs 16.04±3.54 μmol/L,t=11.491),C-reactive protein(CRP,6.16±2.03 vs 8.05±2.67 mg/L,t=5.122)and TNF-α(1.31±0.29 vs 1.79±0.47 ng/mL,t=7.696)(all P＜0.05).Multivariate analysis indicated that age(β=0.103,OR=1.109,95％CI=1.012～1.215),comorbid diabetes(β=2.135,OR=8.461,95％CI=1.866～38.353),Hcy(β=0.706,OR=2.026,95％CI=1.550～2.650),MCP-1(β=0.011,OR=1.011,95％CI=1.004～1.018),MCPIP1(β=1.928,OR=6.875,95％CI=2.765～17.094),CRP(β=0.327,OR=1.387,95％CI=1.022～1.883)and TNF-α(β=1.491,OR=4.443,95％CI=1.389～14.212)were independent influencing factors for vascular plaque instability in the patients with progressive cerebral infarction(all P＜0.05).The modeling formula based on these factors was Logit(P)=0.103×(age)+2.135×(combined diabetes)+0.706×(Hcy)+0.01 1×(MCP-1)+1.928×(MCPIP1)+0.327×(CRP)+1.491×(TNF-α)-34.684.ROC curve analysis revealed that the area under curve(AUC)of the model in the modeling group was 0.956(95％CI:0.931～0.981,P＜0.001),with a sensitivity of 0.841 and a specificity of 0.926,and the AUC value in validation group was 0.960(95％CI=0.925～0.996,P＜0.001).Conclusion Our nomogram prediction model has a good predictive performance for vascular plaque instability in patients with progressive stroke,and it can be used to identify high-risk patients for vascular plaque instability in clinical practice.

Objective To comparatively evaluate the diagnostic value of metagenomic next-generation sequencing(mNGS)versus conventional microbial culture in spinal infections.Methods A cross-section design was conducted on 82 consecutive patients with suspected spinal infections treated between February 2022 and January 2024 at Jiangbei Branch of First Affiliated Hospital of Army Medical University(Third Military Medical University).Microbiological culture,histopathological examination,and mNGS results from infected specimens were analyzed.Clinical diagnosis,primarily based on clinical manifestations,laboratory tests and radiologic features combined with medical history,was defined as the gold standard,and then the diagnostic performance,including sensitivity and specificity,were compared between mNGS and microbial culture.Results Among the 82 patients,definitive microbiological evidence was identified in 70 cases,and mNGS demonstrated a significantly higher detection rate than microbial culture(64 vs 36 cases,78.05％vs 43.9％,P<0.05).mNGS also obtained obviously higher sensitivity,accuracy,and negative predictive value(NPV),and notably lower positive predictive value(PPV)when compared to conventional microbial culture(all P<0.05).When stratified by infection type,mNGS obtained significantly higher sensitivity and accuracy compared to microbial culture in tuberculous spinal infections(P<0.05).For non-tuberculous spinal infections,mNGS also showed superior sensitivity to microbial culture(P<0.05).Conclusion In patients with spinal infections,mNGS demonstrates a significantly higher pathogen detection rate than conventional microbial culture.This technique can provide early and broad-spectrum pathogenic microbiological evidence for spinal infection.

Bismuth iodide(BiOI)with different crystal plane ratios of(110)to(001)was synthesized,and typeⅡheterojunction formed between(001)and(110)crystal planes of BiOI was used to improve the separation efficiency of photogenerated electrons and holes.Then the BiOI(001)/(110)was composited with nitrogen-doped graphene quantum dots(N-GQDs)to prepare a ternary composites,which could enhance the range and intensity of light absorption,and prolonged the lifetime of photogenerated electrons due to the formation of Z-scheme heterojunctions between BiOI and N-GQDs,thereby leading to the excellent photoelectric performance of the BiOI/N-GQDs for generating sensitive photoelectric response signals.A photoelectrochemical sensor for sensitive detection of chlorpyrifos(CPF)was designed with BiOI/N-GQDs-modified FTO electrode as a photocathode.The S and N atoms contained in CPF were coordinated with Bi(Ⅲ)on the surface of BiOI,which reduced the photocurrent of BiOI/N-GQDs.The photocurrent change was linear with logarithm of concentration of CPF in the range of 1.5×10-12-5.0×10-9 mol/L,and the detection limit was 1.5×10-12 mol/L.The sensor was highly sensitive,selective and stable,and could be used for determination of trace CPF in environmental and food samples.