OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Human non-histone lysine crotonylation plays crucial roles in biological activities.However,traditional wet-lab experiments are time-consuming and labor-intensive,making computational prediction methods increasingly popular in recent years.Despite the biological importance of lysine crotonylation,there are relatively few studies on human non-histone proteins.In this study,we developed an ensemble deep learning predictor named iHNHC-RsFPN by constructing a Residual Pyramid Network(RsFPN).First,three feature extraction methods were employed to encode sequence samples.Next,weak classifi-ers based on RsFPN were individually trained for different feature types.Finally,these weak classifiers were integrated to build a robust final predictor.Independent test results demonstrated that iHNHC-RsF-PN achieved outstanding performance across four key metrics:sensitivity(Sn=0.8580),specificity(Sp=0.7463),accuracy(Acc=0.7798),and Matthews correlation coefficient(MCC=0.5586).Comparative experiments revealed that iHNHC-RsFPN significantly improved prediction accuracy for hu-man non-histone crotonylation sites over existing methods.Additionally,we established a user-friendly web server(http://www.lzzzlab.top/ihnc/)that provides straightforward prediction services without complex calculations,facilitating further research for experts in related fields.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the impact of the two-way referral model on compliance and prognosis in patients with heart failure.Methods:This bidirectional cohort study enrolled chronic heart failure (CHF) patients treated at Qilu Hospital of Shandong University or designated primary hospitals between March 2018 and March 2022. Patients were categorized into two groups based on referral status: two-way referral group (participating in the referral model with≥1 follow-up visit at primary hospitals) and the core hospital group (receiving treatment and follow-up exclusively at Qilu Hospital). Baseline clinical characteristics were collected and compared between groups. Patients underwent followed-up, with primary endpoints including follow-up rate, drug (β-blockers, angiotension converting enzyme inhibitor (ACEI)/angiotensin Ⅱ receptor blockers (ARB)/angiotensin receptor-neprilysin inhibitor (ARNI), sodium-glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists) utilization rate and target dose achievement rate. Secondary endpoints encompassed changes from baseline in left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), and N-terminal pro-brain natriuretic peptide (NT-proBNP), plus cardiovascular mortality and heart failure rehospitalization. Generalized linear mixed models analyzed longitudinal trends in LVEF, LVEDd, and NT-proBNP levels. Kaplan-Meier curves and Cox regression evaluated LVEF recovery rates, supplemented by subgroup analyses. Multivariate logistic regression was used to identify factors influencing target dose achievement rate for β-blockers and ACEI/ARB/ARNI therapies in CHF patients.Results:A total of 357 patients were enrolled, aged 53 (41, 63) years, including 256 males (71.7%). 157 patients were in the two-way referral group and 200 patients in the core hospital-treated group. Compared with the core hospital-treated group, the two-way referral group had lower baseline LVEF (28 (22, 34)% vs. 31 (23, 36)%, P=0.021) and systolic blood pressure (116 (104, 125) mmHg vs. 121 (109, 134) mmHg (1 mmHg=0.133 kPa), P=0.010). The 12-month follow-up rate of the two-way referral group was higher than the core hospital-treated group (73.8% vs. 56.0%, P=0.004). No significant between-group differences were observed in drug utilization rate of β-blockers, ACEI/ARB/ARNI, or sodium-glucose cotransporter 2 inhibitors during follow-up (all P>0.05), while mineralocorticoid receptor antagonists use showed a declining trend in both groups. Although the core hospital-treated group had higher target dose achievement rates for β-blockers (65.4% vs. 49.3%, P=0.042) and ACEI/ARB/ARNI (79.8% vs. 65.8%, P=0.046) than the two-way referral group, multivariate logistic regression indicated that the two-way referral model was not a negative predictor for these outcomes (all P>0.05). Both groups showed improved NT-proBNP, LVEDd, and LVEF from baseline (all P<0.001) with no significant difference in trends between groups (all P>0.05). There was no significant difference in the composite incidence (7.6% vs. 6.5%, P=0.674) and cumulative incidence (log-rank P=0.684) of cardiovascular death and heart failure rehospitalization at 12 months between two groups. Conclusion:The two-way referral model demonstrates advantages in improving medication adherence, drug utilization rates, and targetdoseachievement rates among CHF patients. This model not only promotes cardiac functional recovery but also reduces risks of cardiovascular mortality and heart failure rehospitalization, achieving comparable therapeutic and management outcomes to those observed in core hospital-treated patients.

Objective:To evaluate the efficacy and safety of combining third-generation epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKI) with brain radiotherapy in patients with newly diagnosed EGFR mutation-positive non-small cell lung cancer (NSCLC) with brain metastases. Methods:A retrospective analysis was performed on the clinical data of patients with newly diagnosed EGFR-mutant NSCLC with brain metastases who received first-line treatment with third-generation EGFR-TKI with or without brain radiotherapy at the Fourth Affiliated Hospital of Guangxi Medical University between January 2018 and December 2022. Patients treated with EGFR-TKI plus brain radiotherapy were assigned to the combination group, while those treated with EGFR-TKI alone were assigned to the monotherapy group. Intracranial progression-free survival (iPFS), progression-free survival (PFS), overall survival (OS), intracranial disease control rate (iDCR), intracranial objective response rate (iORR), and adverse events were compared between groups. Subgroup analyses were performed according to EGFR exon 19 deletion (19del) and exon 21L858R mutation status. Survival was estimated using the Kaplan-Meier method, with the log-rank test applied for group comparisons and univariate analysis, while multivariate analysis was conducted using Cox proportional hazards regression model. Results:A total of 107 patients were included: 57 (53%) in the monotherapy group and 50 (47%) in the combination group. The combination therapy significantly improved iORR (80% vs. 60%, P=0.023), prolonged median OS (37.7 vs. 31.6 months, P=0.004), and extended median iPFS (21.8 vs. 16.7 months, P=0.018). The iDCR was 100% in both groups, and the difference in median PFS was not statistically significant (18.6 vs. 15.2 months, P=0.086). In the 19del subgroup ( n=53), patients in the combination group had longer OS ( P=0.028) and iPFS ( P=0.028). In the 21L858R subgroup ( n=54), the median OS was also longer in the combination group ( P=0.050). Multivariate analysis identified TKI monotherapy and an Eastern Cooperative Oncology Group (ECOG) performance status score=2 as independent adverse prognostic factors for iPFS, while TKI monotherapy, age ≥65 years, ECOG score=2, and >3 brain metastases were the independent adverse prognostic factors for OS. The incidence of adverse events did not differ significantly between groups (all P>0.05). Conclusions:First-line combination therapy with third-generation EGFR-TKI and cranial radiotherapy provides superior efficacy and acceptable safety compared with EGFR-TKI monotherapy in patients with EGFR-mutant lung adenocarcinoma and brain metastases. Both EGFR 19del and 21L858R mutation subgroups benefit from the combined treatment approach.

This paper summarizes the progress of theoretical research and practice of One Health in China,and discusses the paradigm of One Health governance to improve the prevention and control of infectious diseases in China and the world,and provide an example for the improvement of the public health system.In particular,China has long history to apply the concept of One Health in the national schistosomiasis control programmes and patriotic health campaigns,which were not only focusing on human health,but also emphasizing the sustainable development of animal health and ecological environment.At the same time,the application of tools such as system dynamics model,eDNA technology,One Health economic assessment and global One Health index(GOHI)in the field of disease control and environmental health provides technical support for the concept of One Health.Despite the challenges of practical application of these tools,the One Health concept will play a greater role in providing sustainable solutions for human-animal-environmental health by strengthening interdisciplinary collaboration,improving standardization protocols and promoting inter-national cooperation.

Objective To conduct a bibliometric analysis of relevant literature on liver failure caused by viral hepatitis from the past five years,and to help researchers understand the current status and hotspots in this field,and to provide insights into future research trends.Methods Based on the Science Citation Index Expanded(SCI-Expanded)data from Web of Science Core Collection,visualization analysis and mapping were conducted through VOSviewer and CiteSpace software to generate visual representations of international research collaboration networks,keyword co-occurrence clustering,and keyword bursts.Results From 2019 to 2023,a total of 873 relevant literature were included,with a total citation frequency of 7 364 and an average citation frequency of 8.44.Among them,China had the highest number of publications(458 articles,52.46%)and had the most cooperation with the United States.The research hotspots of viral hepatitis induced liver failure were mainly divided into three categories:basic and clinical research on liver failure caused by non-hepatitis B virus(HBV),the pathogenesis of HBV related liver failure,and treatment and prediction models of liver failure.The keyword time overlay map and burst map showed that the research hotspots had gradually shifted from the prevention and control of new infections to the treatment and prognosis assessment of patients with chronic infection.Conclusion China is a major international research entity in liver failure caused by viral hepatitis and actively participates in international scientific collaborations.The research hotspots on liver failure caused by viral hepatitis have gradually shifted from preventing viral hepatitis infections and expanding treatment options to the treatment of chronic infection patients and prognostic prediction.

Aim To explore the in vitro anti-human triple-negative breast cancer(TNBC)effect and mech-anism of Austocystin R.Methods MTT assay was used to evaluate the anti-tumor potential of Austocystin R for various human tumor cells and normal cells.Flow cytometry was employed to evaluate the influence on cell cycle progression.mRFP-GFP-LC3 adenovirus transfection was used to evaluate the autophagic flux process.Western blot assay was used to verify the effect of Austocystin R on the expression of related pro-teins.Results The results showed that Austocystin R significantly inhibited the proliferation of multiple tumor cells in a dose-dependent manner,especially for the MDA-MB-231 cells with an IC50 of 1.45μmol·L-1.In addition,Austocystin R increased the protein expression of PTEN,p53,p-p53,p27,p21,and down-regulated the expression of p-PI3K,p-AKT and p-mTOR.Austocystin R can significantly increase the proportion of S-phase MDA-MB-231 cells,inhibit the expression of Cyclin D1,CDK4,CDK6,Rb,Cyclin B1 and CDK1,and promote the expression of Cyclin E1 and CDK2.Austocystin R can promote the autophagic flux process of MDA-MB-231 cells,promote the expres-sion of LC3 Ⅰ/Ⅱ,p-Beclin-1,p-ULK1,HMGB-1 and Atg 14 proteins,and inhibit the expression of Beclin-1,ULK1,p62,ATG 3,ATG 4B,ATG 5,ATG 7,ATG 12,ATG 13 and ATG 16L1 proteins.Conclusion Austo-cystin R can exhibit its anti-TNBC activity by inhibi-ting the PI3K/AKT/mTOR signaling pathway,blocking the cell cycle at the S phase and inducing autophagic cell death.

Human non-histone lysine crotonylation plays crucial roles in biological activities.However,traditional wet-lab experiments are time-consuming and labor-intensive,making computational prediction methods increasingly popular in recent years.Despite the biological importance of lysine crotonylation,there are relatively few studies on human non-histone proteins.In this study,we developed an ensemble deep learning predictor named iHNHC-RsFPN by constructing a Residual Pyramid Network(RsFPN).First,three feature extraction methods were employed to encode sequence samples.Next,weak classifi-ers based on RsFPN were individually trained for different feature types.Finally,these weak classifiers were integrated to build a robust final predictor.Independent test results demonstrated that iHNHC-RsF-PN achieved outstanding performance across four key metrics:sensitivity(Sn=0.8580),specificity(Sp=0.7463),accuracy(Acc=0.7798),and Matthews correlation coefficient(MCC=0.5586).Comparative experiments revealed that iHNHC-RsFPN significantly improved prediction accuracy for hu-man non-histone crotonylation sites over existing methods.Additionally,we established a user-friendly web server(http://www.lzzzlab.top/ihnc/)that provides straightforward prediction services without complex calculations,facilitating further research for experts in related fields.