To systematically analyzed the reporting status of core elements in publicly available clinical practice guideline(hereafter referred to as "guideline") protocols published domestically and internationally over the past decade, identified existing problems, and provided evidence to inform the standardized writing and publication of future guideline protocols.

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.

ObjectiveTo establish a tumor prognostic risk assessment model related to target genes of the miR-34 family. MethodsTarget genes of the miR-34 family were screened， and the scores of miR-34 target genes were assessed in 16 tumor types. Univariate Cox regression analysis was used to identify the tumor type with the strongest correlation between miR-34 target gene scores and overall survival （OS）. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed to elucidate the functional roles and signaling pathways of miR-34 target genes. A prognostic risk model based on the miR-34 target genes was constructed using univariate Cox and LASSO regression analyses. Quantitative real-time PCR （qPCR） and dual-luciferase reporter assays were conducted to validate whether the target genes bind to miR-34 and measure their RNA expression levels in the relevant tumors. Additionally， the risk score was integrated with other clinical indicators to develop a nomogram prediction model for patient survival. ResultsA total of 65 target genes of the miR-34 family were screened. The cancer type exhibiting stronger correlation between the target gene scores and OS was lung adenocarcinoma （P = 0.003， HR= 5.150）. Furthermore， miR-34 target genes were predominantly enriched in oxidative stress pathways and various tumor-related processes. Three genes， LDHA， GALNT7， and SATB2， were identified as core components of the prognostic analysis model for lung adenocarcinoma. Additionally， the constructed nomogram model demonstrated robust predictive performance. ConclusionThe risk model and prognosis model of lung adenocarcinoma constructed based on the key target genes of miR-34 have good predictive performance.

Narrative medicine focuses on empathy， relevance， and emotion， precisely aligning with the elements of “clown doctor” such as compassion， interaction， and pain relief. From the perspective of narrative medicine， the practice of “clown doctors” not only focuses on the emotional changes of patients but also enhances their sense of belonging by recreating their experiences. The key element for the success of “clown doctors” lies in establishing a multi-dimensional trust relationship among medical workers， patients， colleagues， and society， while ensuring their practice adheres to medical ethics norms. “Clown doctors” should concentrate on dimensions such as concept dissemination， clinical application， social recognition， and ethical practice of narrative medicine. They should also constantly optimize narrative techniques， deepen the understanding of patients’ stories， and intervene in the medical process in a more delicate and comprehensive way， thereby fostering in-depth communication and understanding between doctors and patients.

Objective To compare the dosimetric and radiobiological differences of helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) in craniospinal irradiation. Methods The CT images of 15 patients who received craniospinal irradiation in our hospital were selected. The target volumes and organs at risk (OARs) were contoured, and HT and VMAT plans were designed. The dosimetric parameters of the two plans were compared. A Matlab program based on equivalent uniform dose was developed to calculate the normal tissue complication probability (NTCP). The NTCP values of the two plans were compared. Results The homogeneity index of the target volume in the HT group was better than that in the VMAT group, with values of 0.06 ± 0.01 and 0.08 ± 0.24, respectively, and the difference was statistically significant (P=0.03). However, there was no significant difference in the conformity index of the target volume (P>0.05). There were significant differences in key indicators (D_mean, V₅, D_max) of the lungs, liver, lens, and eyeballs between the two groups (P<0.05). Regarding OARs, the NTCP values of the lens, optic chiasm, lungs, and liver in the HT and VMAT groups were as follows: 0.04 ± 0.03 vs. 0.1 ± 0.06 in the left lens, 0.04 ± 0.06 vs. 0.1 ± 0.07 in the right lens, 0.16 (0.14-0.17) vs. 0.21 (0.18-0.24) in the optic chiasm, 3.89 × 10⁻⁴ (2.45 × 10⁻⁴-7.3 × 10⁻⁴) vs. 8.95 × 10⁻⁴ (5.19 × 10⁻⁴-1.75 × 10⁻³) in the lungs, and 3.45 × 10⁻⁸ (6.0 × 10⁻⁹-1.036 × 10⁻⁷) vs. 9.54 × 10⁻⁸ (1.70 × 10⁻⁸-2.056 × 10⁻⁷) in the liver; the HT group was superior to the VMAT group, and all differences were statistically significant (P<0.05). The NTCP values of the heart in the two groups were 1.35 × 10⁻⁸ (6.34 × 10⁻⁹-2.06 × 10⁻⁹) vs. 5.06 × 10⁻⁹ (2.29 × 10⁻⁹-7.9 × 10⁻⁹), significantly lower in the VMAT group than in the HT group (P<0.05). Conclusion HT has high homogeneity and consistency. The two plans have their own advantages in OAR protection. For OARs with no significant differences in physical dosimetry, NTCP results can be used as a reference. Therefore, comparing the dosimetric parameters and OAR NTCP of HT and VMAT plans can help select the optimal clinical treatment strategy.

ObjectiveTo investigate the mechanisms by which Liuwei Buqi prescription （LWBQ） regulates alveolar macrophage efferocytosis and improves inflammatory responses in rats with chronic obstructive pulmonary disease （COPD） characterized by lung-kidney Qi deficiency based on the nuclear factor erythroid 2-related factor 2 （Nrf2）/macrophage receptor with collagenous structure （MARCO） pathway. MethodsSuccessfully modeled rats were randomly divided into a model group， low-dose LWBQ group （LWBQ-L， 2.25 g·kg^-1·d^-1）， medium-dose LWBQ group （LWBQ-M， 4.5 g·kg^-1·d^-1）， high-dose LWBQ group （LWBQ-H， 9 g·kg^-1·d^-1）， and aminophylline group （AMIN， 50 mg·kg^-1·d^-1）， with 8 rats in each group. Another 8 healthy rats were included as the blank group. Except for the blank group， rats in the remaining groups were subjected to smoke exposure combined with forced swimming， intratracheal lipopolysaccharide （LPS） instillation， and subcutaneous hydrocortisone injection to establish a COPD model with lung-kidney Qi deficiency. After successful modeling， rats were administered different doses of LWBQ or AMIN by gavage. Body weight， fur condition， and oral secretions were observed. Pulmonary function was measured using an animal lung function analyzer. Enzyme-linked immunosorbent assay （ELISA） was used to detect the expression levels of interferon-γ （IFN-γ）， interleukin-6 （IL-6）， interleukin-1 （IL-1）， and tumor necrosis factor-α （TNF-α） in bronchoalveolar lavage fluid （BALF） and serum （SER）. Hematoxylin-eosin （HE） staining was used to examine pathological changes in lung tissue. Giemsa staining was performed to detect eosinophils， basophils， and neutrophils in BALF. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL） was used to detect apoptosis in lung tissue. Western blot and real-time polymerase chain reaction （Real-time PCR） were employed to determine the protein and mRNA expression levels of efferocytosis-related proteins growth arrest-specific gene 6 （GAS6）， milk fat globule-epidermal growth factor 8 （MFG-E8）， and pathway-related proteins Nrf2 and MARCO in lung tissue. ResultsCompared with the blank group， the model group showed reduced food intake， nasal and oral secretions with sputum， and decreased body weight （P<0.01）， decreased peak expiratory flow （PEF） （P<0.01）， increased forced vital capacity （FVC） （P<0.01）， and decreased forced expiratory volume in 0.3 s/forced vital capacity ［FEV0.3/FVC （%）］ （P<0.01）. The expression levels of IFN-γ， IL-6， IL-1， and TNF-α in BALF and SER were increased （P<0.01）. Lung tissue exhibited structural destruction， hyperplasia， inflammatory exudation， increased apoptotic cells， and increased mean optical density （P<0.01）. The protein and mRNA expression levels of GAS6， MFG-E8， and MARCO， as well as Nrf2 mRNA expression， were increased （P<0.01）. Compared with the model group， the LWBQ groups showed increased food intake， reduced nasal and oral secretions with sputum， and increased body weight （P<0.05， P<0.01）. PEF was increased （P<0.01）. FVC was increased in rats treated with low- and medium-dose LWBQ （P<0.01）， and FEV0.3/FVC （%） was increased in rats treated with medium- and high-dose LWBQ （P<0.05， P<0.01）. The expression levels of IFN-γ， IL-6， IL-1， and TNF-α in BALF and SER were decreased （P<0.01）. Lung tissue structure was relatively intact， with improvement in hyperplasia and inflammatory exudation. The number of apoptotic cells in lung tissue was reduced， and mean optical density was decreased （P<0.05， P<0.01）. The protein and mRNA expression levels of efferocytosis-related proteins GAS6 and MFG-E8 and pathway-related proteins Nrf2 and MARCO were increased （P<0.01）. ConclusionLWBQ can alleviate pulmonary and systemic inflammation， improve lung function， and reduce lung tissue damage in rats with COPD characterized by lung-kidney Qi deficiency. The mechanism may be related to enhancement of alveolar macrophage efferocytosis through regulation of the Nrf2/MARCO pathway.

Diabetic nephropathy （DKD）， as a common microvascular complication of diabetes mellitus （DM）， is a major cause of end-stage renal disease （ESRD）. Its clinical manifestations include increased urinary protein excretion， thickening of the glomerular basement membrane， and renal tubulointerstitial fibrosis. The pathogenesis of DKD is complex and involves multiple factors， including disordered glucose metabolism， hemodynamic alterations， and oxidative stress. Although modern medical approaches can alleviate certain symptoms， they still have limitations such as insufficient therapeutic targeting and prominent adverse effects. The transforming growth factor-β/Smad （TGF-β/Smad） signaling pathway is not only a tissue fibrosis pathway that has attracted considerable attention in recent years， but also regulates multiple protein molecules， including the glomerular podocyte slit diaphragm protein Podocin， interleukin-1β （IL-1β）， and superoxide dismutase （SOD）， thereby participating in various pathological processes and ultimately mediating renal injury. Flavonoid compounds， owing to their sustained pharmacological effects， broad spectrum of action， and high safety profile， have become ideal candidates for targeted therapy research in DKD. Existing studies have shown that these compounds can exert inhibitory effects on renal fibrosis， alleviate inflammatory responses， protect podocytes， and reduce oxidative stress by regulating the interactions between the TGF-β/Smad signaling pathway and the aforementioned protein molecules， thereby maintaining renal structure and function， reducing proteinuria， and significantly improving DKD lesions. This review briefly outlines the composition and functions of the TGF-β/Smad signaling pathway， elucidates the mechanisms by which this pathway regulates DKD， and focuses on summarizing major studies from the past decade on flavonoid-based interventions in DKD through targeted inhibition of the TGF-β/Smad signaling pathway. Furthermore， it discusses the considerable therapeutic potential of flavonoids in the treatment of this disease， aiming to provide a scientific basis for future clinical prevention and treatment of DKD and to promote the development of targeted drugs.

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.

Objective: To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents. Methods: A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model. Results: The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05). Conclusion The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.