This paper summarizes Professor DING Ying's clinical experience in the treatment of systemic lupus erythematosus （SLE） through differentiation of three states， yin fire， latent fire， and fire toxin. It is proposed that fire pathogenic factors constitute a key pathological element running throughout the entire disease course of SLE. The evolution of its pathogenesis centers on these three states， spleen-kidney deficiency with the initial emergence of yin fire as the onset of disease， damage to yin by medicinal toxicity with internal blazing of latent fire as the driver of disease progression， and the interlocking of blood stasis and heat with intense scorching by fire toxin as the critical factor leading to severe and life-threatening conditions. Corresponding to these three stages， targeted prescriptions are formulated， Jiuwei Yishen Formulation （九味益肾方） to tonify the spleen and kidney， raise yang， and disperse fire； Ziyin Xiehuo Decoction （滋阴泄火汤） to nourish yin and fluids while clearing latent fire； and Santeng Changluo Jiedu Decoction （三藤畅络解毒汤） to dispel blood stasis， unblock the collaterals， detoxify， and restrain fire. This staged and integrated therapeutic strategy aims to address both root and branch and to achieve overall regulation， providing valuable guidance for the clinical differentiation and treatment of SLE.

Objective:To assess the relationship between basophil levels and mortality in patients with intra-abdominal infection.Methods:Information on patients with intraperitoneal infection admitted to the intensive care unit were extracted from the MIMIC database.A time-dependent Cox regression model was used to adjust for confounders associated with 28-day mortality.Propensity score matching(PSM)was used to balance the baseline differences be-tween groups with different basophil levels,and a restricted cube chart(RCS)was used to show the relationship between basophil count and 28-day mortality in patients with intra-abdominal infection.Results:A total of 4403 patients with intra-abdominal infection were enrolled in the MIMIC database.Patients with high basophil levels have lower mortality than those with low basophil levels.There was an L-shaped curve between basophil level and 28-day mortality,with a cut-off value of 0.47×109/L.Cox regression analysis showed that basophil levels were an independent protective factor for mortal-ity in patients with intra-abdominal infection after adjusting for potential confounders(HR=0.586,95%CI:0.443-0.769).Protective factors for death at basophil levels remained after PSM adjusted for potential confounders(HR=0.628,95%CI:0.470-0.832).Conclusion:Basophil level is an independent protective factor for mortality in patients with intra-abdominal infection,and basophil levels should be dynamically monitored to better evaluate the prognosis of patients.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Complete dentures can be fabricated by cutting and grinding the resin in one step.It is worth trying to manufacture removable partial dentures through simulating this approach to minimize manual fabrication as much as possible.This article reports on a case where a digitally designed and milled removable partial denture was made from a cuttable resin.After a two-month postoperative follow-up,there was no significant pain or discomfort in the soft or hard tissues.This preliminary study suggests that this digital restoration plan could a-chieve good restoration results and can be further clinically promoted.

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.

Objective:To investigate the factors influencing the persistence of prostate specific antigen(PSA) following radical prostatectomy, and to develop and validate a predictive model for PSA persistence.Methods:Clinical data from 1 828 patients who underwent radical prostatectomy at Shanghai Changhai Hospital between January 2015 and December 2023 were retrospectively analyzed. Of these, 1 295 patients from January 2015 to April 2021 comprised the modeling group, while 533 patients from May 2021 to December 2023 formed the validation group. Additionally, 109 patients who underwent radical surgery at the Third Affiliated Hospital of Naval Medical University between March and December 2023 were included as an external validation group. Patients with incomplete clinical information, serum PSA levels exceeding 100 ng/ml, or those who received preoperative neoadjuvant therapy were excluded. Ultimately, 1 003, 369, and 86 patients were included in the modeling, validation, and external validation groups, respectively. The modeling group had serum PSA of 19.29 (8.43, 23.73) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 191, 673, 123, and 16 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 460, 466, and 77 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 363, 486, and 154 patients, respectively. The validation group had serum PSA of 12.80 (6.82, 14.40) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 40, 289, 37, and 3 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 218, 145, and 6 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 140, 184, and 45 patients, respectively. The external validation group had serum PSA of 12.84 (7.11, 12.97) ng/ml; the clinical stages were distributed as T 1, T 2 and T 3 in 9, 68, and 9 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 58, 27, and 1 patient, respectively; and the secondary Gleason scores were 3, 4, and 5 in 28, 50, and 8 patients, respectively. Logistic regression analysis was used to identify independent risk factors for PSA persistence after radical prostatectomy in the modeling group and a prediction model was constructed. The predictive performance of the model was analyzed using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve, the calibration curve, and the clinical decision curve. The predictive performance of the model was verified by the ROC curve in the validation group and the external validation group. Results:The incidence of persistent PSA after surgery in the modeling group, validation group, and external validation group was 8.97% (90/1 003), 7.32% (27/369), and 17.4% (15/86), respectively. In the modeling group, univariate and multivariate logistic regression analysis revealed that serum PSA, percentage of positive needle cores, primary Gleason score on biopsy, and secondary Gleason score on biopsy were independent risk factors for PSA persistence ( P<0.05), and a prediction model was constructed based on these factors. The AUC value of this model was 0.790 (95% CI 0.745-0.835). Calibration curve and clinical decision curve analyses showed that the model's predicted probabilities aligned well with actual risks within the 0-40% prediction interval, providing clinical benefit. The AUC values of the ROC curves in the validation group and external validation group were 0.808 (95% CI 0.719-0.897) and 0.822 (95% CI 0.714-0.929), respectively, indicating that the model had good predictive performance. Conclusions:The predictive model for PSA persistence, constructed based on serum PSA, percentage of positive needle cores, primary and secondary Gleason score on biopsy, demonstrated good clinical predictive performance, exhibiting high accuracy in both internal and cross-center validation.

Objective:To investigate disease characteristics of patients with psoriatic arthritis (PsA) based on the PsA cohort in West China Hospital, so as to provide a reference for clinicians in its diagnosis, treatment, and evaluation strategy formulation.Methods:A cross-sectional study was carried out, and a descriptive analysis was conducted on clinical data from PsA patients who were treated at the Department of Dermatology, West China Hospital, Sichuan University between April 2, 2020, and January 21, 2025. Demographic characteristics, clinical manifestations, laboratory and imaging findings, and treatment modalities were analyzed.Results:A total of 530 PsA patients were included, of whom 332 (62.6%) were males and 198 (37.4%) were females, with ages of 44.1 ± 12.4 years. Skin lesions preceded joint symptoms in 452 patients (85.3%), with time intervals ( M [ Q1, Q3]) of 8.0 (3.0, 15.0) years. Overweight or obesity was observed in 319 patients (60.2%), and 188 (35.5%) had comorbid fatty liver. Peripheral joint involvement was common (485 cases, 91.5%), with the proximal interphalangeal joints being most frequently affected by tenderness (172 cases, 35.5%) and swelling (119 cases, 24.5%) ; the number of enthesitis cases identified by ultrasonography (116 cases, 23.9%) was significantly higher than that by clinical examination (82 cases, 15.5%) ; axial joint involvement was observed in 258 patients (48.7%), with the sacroiliac joints most commonly affected (201 cases, 77.9%). Regarding treatment, conventional systemic drugs were predominant in the treatment of psoriasis prior to the diagnosis of PsA; after the diagnosis of PsA, the number of patients receiving targeted therapies increased to 334 (63.0%), with interleukin-17 inhibitors being the most common (140 cases, 26.4%), followed by tumor necrosis factor-α inhibitors (106 cases, 20.0%) and Janus kinase inhibitors (39 cases, 7.4%) . Conclusions:PsA predominantly affects males over 40 years old and is characterized by preceding skin lesions, delayed diagnosis, and multiple comorbidities. High-frequency ultrasound has advantages in the early detection of peripheral enthesitis. Further attention is needed for managing comorbidities such as fatty liver and obesity-related metabolic conditions.

Complete dentures can be fabricated by cutting and grinding the resin in one step.It is worth trying to manufacture removable partial dentures through simulating this approach to minimize manual fabrication as much as possible.This article reports on a case where a digitally designed and milled removable partial denture was made from a cuttable resin.After a two-month postoperative follow-up,there was no significant pain or discomfort in the soft or hard tissues.This preliminary study suggests that this digital restoration plan could a-chieve good restoration results and can be further clinically promoted.

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Objective:To investigate the factors influencing the persistence of prostate specific antigen(PSA) following radical prostatectomy, and to develop and validate a predictive model for PSA persistence.Methods:Clinical data from 1 828 patients who underwent radical prostatectomy at Shanghai Changhai Hospital between January 2015 and December 2023 were retrospectively analyzed. Of these, 1 295 patients from January 2015 to April 2021 comprised the modeling group, while 533 patients from May 2021 to December 2023 formed the validation group. Additionally, 109 patients who underwent radical surgery at the Third Affiliated Hospital of Naval Medical University between March and December 2023 were included as an external validation group. Patients with incomplete clinical information, serum PSA levels exceeding 100 ng/ml, or those who received preoperative neoadjuvant therapy were excluded. Ultimately, 1 003, 369, and 86 patients were included in the modeling, validation, and external validation groups, respectively. The modeling group had serum PSA of 19.29 (8.43, 23.73) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 191, 673, 123, and 16 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 460, 466, and 77 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 363, 486, and 154 patients, respectively. The validation group had serum PSA of 12.80 (6.82, 14.40) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 40, 289, 37, and 3 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 218, 145, and 6 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 140, 184, and 45 patients, respectively. The external validation group had serum PSA of 12.84 (7.11, 12.97) ng/ml; the clinical stages were distributed as T 1, T 2 and T 3 in 9, 68, and 9 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 58, 27, and 1 patient, respectively; and the secondary Gleason scores were 3, 4, and 5 in 28, 50, and 8 patients, respectively. Logistic regression analysis was used to identify independent risk factors for PSA persistence after radical prostatectomy in the modeling group and a prediction model was constructed. The predictive performance of the model was analyzed using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve, the calibration curve, and the clinical decision curve. The predictive performance of the model was verified by the ROC curve in the validation group and the external validation group. Results:The incidence of persistent PSA after surgery in the modeling group, validation group, and external validation group was 8.97% (90/1 003), 7.32% (27/369), and 17.4% (15/86), respectively. In the modeling group, univariate and multivariate logistic regression analysis revealed that serum PSA, percentage of positive needle cores, primary Gleason score on biopsy, and secondary Gleason score on biopsy were independent risk factors for PSA persistence ( P<0.05), and a prediction model was constructed based on these factors. The AUC value of this model was 0.790 (95% CI 0.745-0.835). Calibration curve and clinical decision curve analyses showed that the model's predicted probabilities aligned well with actual risks within the 0-40% prediction interval, providing clinical benefit. The AUC values of the ROC curves in the validation group and external validation group were 0.808 (95% CI 0.719-0.897) and 0.822 (95% CI 0.714-0.929), respectively, indicating that the model had good predictive performance. Conclusions:The predictive model for PSA persistence, constructed based on serum PSA, percentage of positive needle cores, primary and secondary Gleason score on biopsy, demonstrated good clinical predictive performance, exhibiting high accuracy in both internal and cross-center validation.