With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

The assessment of adverse drug events is an important basis for clinical safety evaluation and post-marketing risk control of drugs,and its causality assessment is gaining increasing attention.The existing methods for assessing the causal relationship between drugs and the occurrence of adverse reactions can be broadly classified into three categories:global introspective methods,standardized methods,and probabilistic methods.At present,there is no systematic introduction of the operational details of the various methods in the domestic literature.This paper compares representative causality assessment methods in terms of definition and concept,methodological steps,industry evaluation and advantages and disadvantages,clarifies the basic process of determining the causality of adverse drug reactions,and discusses how to further improve the adverse drug reaction monitoring and evaluation system,with a view to providing a reference for drug development and pharmacovigilance work in China.

Bilastine,a new second-generation histamine H1 receptor antagonist,is used in the treatment of urticaria,in psoriasis,eczema,atopic dermatitis,prurigo,pruritus,eosinophilic dermatitis and many other skin diseases are also widely used.This article reviews the pharmacology,pharmacokinetics,safety and efficacy of bilastine,its application in skin diseases and adverse drug reactions for clinical reference.

The rare-earth-elements-doped upconversion nanoparticles NaYF4:Yb3+,Er3+were synthesized by solvothermal method,and NaYF4:Yb3+,Er3+@SiO2 were prepared by coating SiO2 on the surface of NaYF4:Yb3+,Er3+by inverse microemulsion method in this work.Based on the fluorescence quenching principle between NaYF4∶Yb3+,Er3+@SiO2 and SQA-Fe3+,a NaYF4∶Yb3+,Er3+@SiO2-SQA-Fe3+fluorescence nanosensor was constructed for detection of trace hydrogen peroxide(H2O2).Under optimal conditions,the linear range of this method for detecting H2O2 was 1.8?84.0 μmol/L,with detection limit(3σ)of 0.47 μmol/L.The recoveries of H2O2 spiked in milk were 98.4%?99.7%.This method could be used for detection of H2O2 residue in milk samples,with advantages such as low detection limit,good stability and strong anti-interference ability.

Parabacteroides distasonis is a gram-negative bacterium initially isolated from a clinical specimen in the 1930s. The strain was re-classified to form the new genus Parabacteroides in 2006. P. distasonis can regulate intestinal barrier function and plays a key role in immune response and metabolic regulation of bodies. Traditional Chinese medicine(TCM) is closely related to the intestinal microbiota. Polysaccharides, saponins, and other ingredients of TCM can treat diseases by interacting with P. distasonis, but the specific mechanisms underlying these processes are still unclear, requiring further exploration. This study reviewed the roles and related mechanisms of P. distasonis in inflammatory-immune diseases, metabolic diseases, cardiovascular disease, neuropsychiatric diseases, cancer, and other diseases and summarized the relevant research results of TCM to prevent and treat diseases by regulating P. distasonis. This study provides a reference for subsequent exploration of P. distasonis and research on the interaction between TCM and intestinal microbiota.
Humans ; Gastrointestinal Microbiome/drug effects* ; Medicine, Chinese Traditional ; Animals ; Bacteroidetes ; Drugs, Chinese Herbal/pharmacology*

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
Humans ; Nomograms ; Retrospective Studies ; Carcinoma, Renal Cell/pathology* ; Prognosis ; Risk Factors ; Nephrectomy ; Kidney Neoplasms/pathology* ; Necrosis

Objective: To report the long-term survival of renal cell carcinoma (RCC) patients treated with radical nephrectomy in Sun Yat-sen University Cancer Center. Methods: We retrospectively analyzed the clinical, pathological and follow-up records of 1 367 non-metastatic RCC patients treated with radical nephrectomy from 1999 to 2020 in this center. The primary endpoint of this study was overall survival rate. Survival curves were estimated using the Kaplan-Meier method, and group differences were compared through Log-rank test. Univariate and multivariate Cox analysis were fit to determine the clinical and pathological features associated with overall survival rate. Results: A total of 1 367 patients treated with radical nephrectomy with complete follow-up data were included in the study. The median follow-up time was 52.6 months, and 1 100 patients survived and 267 died, with the median time to overall survival not yet reached. The 5-year and 10-year overall survival rates were 82.8% and 74.9%, respectively. The 5-year and 10-year overall survival rates of Leibovich low-risk patients were 93.3% and 88.2%, respectively; of Leibovich intermediate-risk patients were 82.2% and 72.3%, respectively; and of Leibovich high-risk patients were 50.5% and 30.2%, respectively. There were significant differences in the long-term survival among the three groups (P<0.001). The 10-year overall survival rates for patients with pT1, pT2, pT3 and pT4 RCC were 83.2%, 73.6%, 55.0% and 31.4%, respectively. There were significant differences among pT1, pT2, pT3 and pT4 patients(P<0.001). The 5-year and 10-year overall survival rates of patients with lymph node metastasis were 48.5% and 35.6%, respectively, and those of patients without lymph node metastasis were 85.1% and 77.5%, respectively. There was significant difference in the long-term survival between patients with lymph node metastasis and without lymph node metastasis. The 10-year overall survival rate was 96.2% for nuclear Grade 1, 81.6% for nuclear Grade 2, 60.5% for nuclear Grade 3, and 43.4% for nuclear Grade 4 patients. The difference was statistically significant. There was no significant difference in the long-term survival between patients with localized renal cancer (pT1-2N0M0) who underwent open surgery and minimally invasive surgery (10-year overall survival rate 80.5% vs 85.6%, P=0.160). Multivariate Cox analysis showed that age≥55 years (HR=2.11, 95% CI: 1.50-2.96, P<0.001), T stage(T3+ T4 vs T1a: HR=2.37, 95% CI: 1.26-4.46, P=0.008), local lymph node metastasis (HR=3.04, 95%CI: 1.81-5.09, P<0.001), nuclear grade (G3-G4 vs G1: HR=4.21, 95%CI: 1.51-11.75, P=0.006), tumor necrosis (HR=1.66, 95% CI: 1.17-2.37, P=0.005), sarcomatoid differentiation (HR=2.39, 95% CI: 1.31-4.35, P=0.005) and BMI≥24kg/m(2) (HR=0.56, 95%CI: 0.39-0.80, P=0.001) were independent factors affecting long-term survival after radical nephrectomy. Conclusions: The long-term survival of radical nephrectomy in patients with renal cell carcinoma is satisfactory. Advanced age, higher pathological stage and grade, tumor necrosis and sarcomatoid differentiation were the main adverse factors affecting the prognosis of patients. Higher body mass index was a protective factor for the prognosis of patients.
Humans ; Middle Aged ; Carcinoma, Renal Cell/secondary* ; Lymphatic Metastasis ; Retrospective Studies ; Neoplasm Staging ; Kidney Neoplasms/pathology* ; Prognosis ; Nephrectomy ; Survival Analysis ; Necrosis/surgery* ; Survival Rate

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
Humans ; Nomograms ; Retrospective Studies ; Carcinoma, Renal Cell/pathology* ; Prognosis ; Risk Factors ; Nephrectomy ; Kidney Neoplasms/pathology* ; Necrosis

Objective: To report the long-term survival of renal cell carcinoma (RCC) patients treated with radical nephrectomy in Sun Yat-sen University Cancer Center. Methods: We retrospectively analyzed the clinical, pathological and follow-up records of 1 367 non-metastatic RCC patients treated with radical nephrectomy from 1999 to 2020 in this center. The primary endpoint of this study was overall survival rate. Survival curves were estimated using the Kaplan-Meier method, and group differences were compared through Log-rank test. Univariate and multivariate Cox analysis were fit to determine the clinical and pathological features associated with overall survival rate. Results: A total of 1 367 patients treated with radical nephrectomy with complete follow-up data were included in the study. The median follow-up time was 52.6 months, and 1 100 patients survived and 267 died, with the median time to overall survival not yet reached. The 5-year and 10-year overall survival rates were 82.8% and 74.9%, respectively. The 5-year and 10-year overall survival rates of Leibovich low-risk patients were 93.3% and 88.2%, respectively; of Leibovich intermediate-risk patients were 82.2% and 72.3%, respectively; and of Leibovich high-risk patients were 50.5% and 30.2%, respectively. There were significant differences in the long-term survival among the three groups (P<0.001). The 10-year overall survival rates for patients with pT1, pT2, pT3 and pT4 RCC were 83.2%, 73.6%, 55.0% and 31.4%, respectively. There were significant differences among pT1, pT2, pT3 and pT4 patients(P<0.001). The 5-year and 10-year overall survival rates of patients with lymph node metastasis were 48.5% and 35.6%, respectively, and those of patients without lymph node metastasis were 85.1% and 77.5%, respectively. There was significant difference in the long-term survival between patients with lymph node metastasis and without lymph node metastasis. The 10-year overall survival rate was 96.2% for nuclear Grade 1, 81.6% for nuclear Grade 2, 60.5% for nuclear Grade 3, and 43.4% for nuclear Grade 4 patients. The difference was statistically significant. There was no significant difference in the long-term survival between patients with localized renal cancer (pT1-2N0M0) who underwent open surgery and minimally invasive surgery (10-year overall survival rate 80.5% vs 85.6%, P=0.160). Multivariate Cox analysis showed that age≥55 years (HR=2.11, 95% CI: 1.50-2.96, P<0.001), T stage(T3+ T4 vs T1a: HR=2.37, 95% CI: 1.26-4.46, P=0.008), local lymph node metastasis (HR=3.04, 95%CI: 1.81-5.09, P<0.001), nuclear grade (G3-G4 vs G1: HR=4.21, 95%CI: 1.51-11.75, P=0.006), tumor necrosis (HR=1.66, 95% CI: 1.17-2.37, P=0.005), sarcomatoid differentiation (HR=2.39, 95% CI: 1.31-4.35, P=0.005) and BMI≥24kg/m(2) (HR=0.56, 95%CI: 0.39-0.80, P=0.001) were independent factors affecting long-term survival after radical nephrectomy. Conclusions: The long-term survival of radical nephrectomy in patients with renal cell carcinoma is satisfactory. Advanced age, higher pathological stage and grade, tumor necrosis and sarcomatoid differentiation were the main adverse factors affecting the prognosis of patients. Higher body mass index was a protective factor for the prognosis of patients.
Humans ; Middle Aged ; Carcinoma, Renal Cell/secondary* ; Lymphatic Metastasis ; Retrospective Studies ; Neoplasm Staging ; Kidney Neoplasms/pathology* ; Prognosis ; Nephrectomy ; Survival Analysis ; Necrosis/surgery* ; Survival Rate