Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.

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.

Objective To investigate the cross-sectional associations between different fatty liver classifications and cardiac structure and function in people undergo health examination. Methods A total of 6 545 adults who underwent health examinations at the Health Management Center of Zhongshan Hospital, Fudan University between January 1 and December 31, 2017, were retrospectively included. Demographic characteristics and laboratory data were collected. The hepatic steatosis was graded by ultrasonography. And patients with fatty liver were further stratified according to alanine aminotransferase (ALT) or aspartate aminotransferase (AST) levels, as well as the degree of liver fibrosis. Cardiac morphology and function were assessed by transthoracic echocardiography, and left ventricular geometric patterns were classified accordingly. Multivariate logistic regression analysis was performed to evaluate the associations between fatty liver classifications and cardiac abnormalities. Results There were 2 795 patients (42.7%) with fatty liver, of whom 832 (29.8%) had significant cardiac structural alterations and 1 500 (53.7%) had diastolic dysfunction. Severe fatty liver was risk factor for concentric remodeling and increased relative wall thickness (RWT), with odds ratios (ORs) of 1.27 (P＝0.012) and 1.27 (P＝0.009), respectively. Fatty liver accompanied by elevated ALT or AST was risk factor for concentric remodeling (OR＝1.45,1.56; P＝0.001, 0.001), increased RWT (OR＝1.48,1.57; P＜0.001, ＜0.001), and diastolic dysfunction (OR＝1.27, 1.32; P＝0.035, 0.040), respectively. Fatty liver with liver fibrosis was risk factor for concentric remodeling (OR＝1.83, P＝0.046) and diastolic dysfunction (OR＝2.64, P＝0.034). Conclusions Advanced fatty liver, including severe hepatic steatosis, accompanied by elevated liver enzymes or liver fibrosis, could increase risks of cardiac remodeling and diastolic dysfunction, while systolic function is preserved. For patients with fatty liver, it is recommended to undergo regular ultrasonography examination.

Background: Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes mellitus that significantly impairs patients’ quality of life. Traditional Chinese medicine (TCM), as a major component of complementary and alternative medicine, has accumulated numerous effective formulas for the clinical management of DPN. However, systematic approaches for optimizing TCM formulas remain limited. Objective: To establish a pathway-oriented approach for TCM formula optimization and to evaluate the efficacy and mechanisms of the optimized formula in DPN. Methods: We developed 2 formula optimization algorithms that defined pathway-oriented herbal correlation (HC) and herbal contribution (HO) to screen and construct a new herbal formula, Qihongtongbi (QHTB), for treating Qi deficiency and blood stasis syndrome complicated with DPN. An animal experiment was subsequently conducted to evaluate the therapeutic effectiveness of QHTB. A total of 32 specific-pathogen-free male ob/ob mice (18–20 g) were randomly divided into 4 groups: model, Mudan Granules (MDG), QHTB low- and high-dose groups (n = 8). Ten male C57BL/6J mice (18–20 g) served as the control group. Metabolomics analysis was further employed to elucidate the biological mechanisms underlying the effects of QHTB. Results: Based on our previous study on TCM medication patterns for treating DPN, 22 candidate herbs were selected for formula optimization. The top 5 candidate herbs (total HC = 25.24 × 10 ) exhibited HC values comparable to those of MDG (total HC = 26.1 × 10 ). These herbs were Carthamus tinctorius L. (HC = 5.40 × 10 ), Astragalus mongholicus Bunge (HC = 5.23 × 10 ), Salvia miltiorrhiza Bunge (HC = 5.15 × 10 ), Commiphora myrrha (T. Nees) Engl. (HC = 5.02 × 10 ), and Glycyrrhiza glabra L. (HC = 4.44 × 10 ). HO analysis showed that the cumulative HO of these 5 herbs exceeded 50%. In vivo experiments demonstrated that, compared with the model group, QHTB significantly lowered blood glucose (P < 0.05), enhanced nerve conduction velocity (P < 0.01), improved nociceptive hypersensitivity (P < 0.01), and ameliorated sciatic nerve morphology, with efficacy comparable to MDG. Serum and fecal metabolomics further revealed that QHTB exerted multipathway regulatory effects, among which nicotinate and nicotinamide metabolism represented a key mechanism. Conclusion: In summary, this study provides a methodological reference for the systematic optimization of TCM formulas.

ObjectiveTo establish a castrated male mouse model and to preliminarily investigate the effects of testosterone replacement therapy （TRT） on behavior， serum indices， and histopathological changes in castrated mice， as well as to explore the role of androgens in cognitive function. MethodsForty 6-month-old male C57/BL6J mice were randomly divided into sham operation group， castration group， testosterone propionate （0.5，1.0 mg/kg） treated group， with 10 mice in each group. Following castration and subcutaneous administration of testosterone propionate at different doses （0.5 and 1.0 mg/kg） for TRT， learning and memory abilities were assessed using the Morris water maze （MWM） test and the passive avoidance test. Serum testosterone and serum brain-derived neurotrophic factor （BDNF） levels were measured by ELISA， and histopathological changes in the hippocampus were examined using hematoxylin-eosin （HE） staining. ResultsRoutine observations： there were no statistically significant differences in body weight among groups at any time point. MWM test： compared with castration group， sham operation group and testosterone propionate-treated groups （0.5， 1.0 mg/kg） showed significantly reduced escape latency on days 4 and 5 （P0.05）， while the number of platform crossings and the time spent in the target quadrant significantly increased （P0.05）. Passive avoidance test： the number of passive avoidance errors significantly decreased in sham operation group and testosterone propionate （1.0 mg/kg）-treated group （P0.05）， and the passive avoidance latency was significantly prolonged in sham-operated group and testosterone propionate-treated groups （0.5， 1.0 mg/kg） （P0.05）. Serum testosterone and serum BDNF assays： serum testosterone levels and serum BDNF concentrations significantly increased in sham operation group and testosterone propionate-treated groups （0.5， 1.0 mg/kg） （P0.01）. HE staining： compared with sham operation group， neuronal density in all hippocampal subregions was slightly reduced in castration group； in the testosterone propionate （0.5 mg/kg）-treated group， neuronal arrangement in the CA1 and CA3 regions was improved and apoptotic cells were reduced compared with castration group； in testosterone propionate （1.0 mg/kg）-treated group， the pyramidal cell layer in the CA3 region was more compactly arranged， with fewer apoptotic cells than in castration group. ConclusionTRT improves learning and memory performance in castration male mice， potentially through modulation of hippocampal BDNF signaling pathways.

ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

The crystalline lens of the eye is recognized as one of the most radiosensitive tissues in the human body. While the International Commission on Radiological Protection (ICRP) has classified ionizing radiation (IR)-induced cataracts as a tissue reaction (deterministic effect) and subsequently reduced the occupational equivalent dose limit for the lens, significant uncertainties remain regarding the precise dose threshold and the complex biological pathways driving lens opacification. This review provides a comprehensive synthesis of current knowledge concerning radiation-induced lens damage, integrating epidemiological exposure characteristics with dose-response modeling and mechanistic molecular insights. First, we analyze exposure characteristics through four epidemiological dimensions: dose, time, space, and population. Clinical evidence suggests that radiation cataracts—particularly posterior subcapsular opacities—exhibit a distinct latency period that is inversely correlated with dose. We highlight that risk is not confined to acute high-dose scenarios (such as in atomic bomb survivors) but is increasingly relevant in chronic low-dose occupational settings (e.g., interventional radiology) and medical diagnostics (e.g., CT scans). Crucially, individual susceptibility is modified by genetic background, age, and environmental co-factors, complicating risk assessment. Second, we critically examine the dose-effect relationship. Although the ICRP suggests a threshold of 0.5 Gy, emerging data challenge the traditional threshold model, with some studies advocating for a linear non-threshold (LNT) relationship. We further discuss the critical roles of radiation quality and dose rate. High linear energy transfer (LET) radiation demonstrates a significantly higher relative biological effectiveness (RBE) for cataractogenesis compared to low-LET radiation. Paradoxically, and unlike many other tissues, the lens may exhibit an “inverse dose-rate effect,” where fractionated or protracted exposures potentially enhance biological damage—a finding that challenges classical radiobiological paradigms. Third, drawing upon the “cataractogenic load” hypothesis and the unique physiological constraints of the lens, this review elucidates the multidimensional molecular mechanisms driving radiation-induced opacification. Key mechanisms include four aspects. (1) DNA damage and repair: IR induces DNA double-strand breaks (DSBs) that, due to the lens’ limited repair capacity (modulated by genes such as ATM, Ptch1, and Ercc2), lead to the accumulation of damage. (2) Antioxidant defense system: dysfunction of the Nrf2/HO-1 antioxidant axis results in redox imbalances, triggering NF-κB-mediated inflammation and protein aggregation. (3) Cell proliferation and senescence: IR disrupts cell cycle regulation, causing a dichotomy of effects—driving premature senescence in some cell populations (evidenced by ATM nuclear foci) while inducing aberrant proliferation via growth factor upregulation (FGF2, TGFβ) in others. (4) Cell migration and adhesion: activation of the Wnt/β‑catenin pathway and alterations in the E-cadherin complex promote the abnormal migration of epithelial cells to the posterior capsule, a hallmark of radiation-induced cataracts. In conclusion, radiation-induced cataractogenesis is a multifactorial process in which genetic susceptibility and environmental stressors converge to overwhelm the lens’ homeostatic thresholds. Future research must prioritize longitudinal cohort studies to refine dose thresholds and employ multi-omics approaches to map the crosstalk between DNA damage responses and matrix remodeling. Establishing a robust mechanistic model is essential for developing targeted radioprotective strategies and optimizing radiation protection standards for occupational and medical safety.

Primary biliary cholangitis （PBC） is an autoimmune liver disease characterized by intrahepatic cholestasis， while fatigue is a common symptom of PBC that significantly affects the quality of life of patients. The pathogenesis of fatigue is complex and may be associated with the factors such as cholestasis-induced inflammation， gut microbiota dysbiosis， brain structural and functional abnormalities， and mitochondrial dysfunction. At present， first-line therapies and liver transplantation have a limited effect in alleviating fatigue， and there is still a lack of standardized comprehensive assessment system. Emerging drugs and non-pharmaceutical interventions， including lifestyle modifications， have shown potential application prospects. This article systematically reviews the research advances in the clinical manifestations， pathogenesis， clinical assessment， and intervention of fatigue in PBC patients， in order to provide a reference for optimizing treatment strategies and promoting the research and development of new therapies.

This paper summarizes professor WANG Qingguo's experience in treatment of headache based on the "achieving harmony by unblocking and balancing" concept. It is considered that although the pathogenesis of headache is generally attributed to "pain arises from obstruction" and "pain arises from malnourishment"， clinical presentations often involve a complex mixture of deficiency and excess， as well as cold and heat patterns. Professor WANG proposes the diagnostic and therapeutic theory of "achieving harmony by unblocking and balancing"， advocating for equal emphasis on "freeing the flow of qi and blood" and "regulating the balance of yin and yang". He has summarized eight treatment methods for common headache patterns. For wind-cold attacking the collaterals， treatment should focus on dispersing and unblocking through modified Gegen Decoction （葛根汤）. For wind-dampness binding， it is recommended to unblock and drain， using modified Qingshang Juantong Decoction （清上蠲痛汤）. For damp-heat congestion， unblocking and clearing is the method， using modified Toufeng Shen Formula （头风神方）. For liver-gallbladder qi constraint， unblocking and soothing is the treatment principle， and modified Sanpian Decoction （散偏汤） is suggested. For insufficiency of center qi， even supplementation method is recommended， and modified Yiqi Congming Decoction （益气聪明汤） can be used. For liver yang hyperactivity， unblocking and subduing are combined， using modified Xunlong Decoction （驯龙汤）. For deficiency-cold in the liver and stomach， warming， harmonizing， unblocking， and descending are applied， using modified Wuzhuyu Decoction （吴茱萸汤）. For blood deficiency with cold congelation， unblocking and nourishing are undertaken together， using modified Danggui Sini Decoction （当归四逆汤）. The ultimate goal is to restore the dynamic balance of yin， yang， qi， and blood in the body， thereby allevia-ting pain by restoring clarity and function to the head orifices.