OBJECTIVE To evaluate the efficacy， safety and cost-effectiveness of deucravacitinib in the treatment of moderate- to-severe plaque psoriasis. METHODS Rapid health technology assessment （HTA） reports， systematic reviews （SR）/meta- analyses， and pharmacoeconomic studies on deucravacitinib for the treatment of moderate-to-severe plaque psoriasis were identified by searching PubMed， Web of Science， Embase， CNKI， Wanfang data and official HTA websites. The search time frame spanned from database inception to July 2025. After literature screening， data extraction， and quality assessment， the study results were subjected to descriptive analysis and synthesis. RESULTS A total of 14 articles were finally included， consisting of 1 HTA report， 10 SR/meta-analyses， and 3 pharmacoeconomic studies. Regarding efficacy， deucravacitinib demonstrated superior efficacy to both placebo and apremilast， with significantly higher response rates for Psoriasis Area and Severity Index 50/75/90/100， Static Physician’ s Global Assessment 0/1， and Dermatology Life Quality Index 0/1， as well as greater reduction in Psoriasis Symptoms and Signs Diary Score （P＜0.05）. Regarding safety， deucravacitinib was well-tolerated. Although the overall incidence of adverse events （AEs） was higher than placebo， it was not significantly different from apremilast. Moreover， the incidence of serious AEs and the rate of discontinuation due to AEs did not differ significantly from placebo （P＞0.05）. Regarding cost-effectiveness， deucravacitinib proved to be more cost-effective than apremilast across multiple healthcare system perspectives， including those of the United States， Japan， and China. CONCLUSIONS Deucravacitinib exhibits favorable efficacy， safety， and cost-effectiveness in the treatment of moderate-to-severe plaque psoriasis. Additional real-world studies are warranted to further refine its evaluation.

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Objective:To explore the research status and hotspots of TCM syndrome differentiation and treatment for headache using bibliometrics.Methods:Literature about TCM syndrome differentiation and treatment for headache was retrieved from CNKI, VIP, Wanfang Data, and CBM from the establishment of the databases to July 18, 2024. Excel 2023 was used to extract information such as publication time, author, unit and keywords of the literature. The authors' affiliation and keywords were preprocessed. VOSviewer software was used for keyword co-occurrence analysis and clustering analysis, and a keyword temporal overlay network was constructed.Results:Totally 1 513 articles were finally included. The journal with the largest number of publications was Henan Traditional Chinese Medicine. 346 authors were involved, initially forming research teams represented with Cao Kegang, Zhou Jianwei, Ni Jinjun, etc., mainly from Beijing University of Chinese Medicine, Henan University of Chinese Medicine, Shandong University of Traditional Chinese Medicine, etc.; the included literature included a total of 2 153 keywords, which the frequency of 5 931 times in total. The top three keywords in frequency were acupuncture and moxibustion therapy, clinical efficacy, and experience of famous doctors. Current research hotspots included data mining, network pharmacology, literature research, syndrome elements, medication law, venturing and bloodletting therapy, calcitonin gene-related peptide, classic prescriptions, nitric oxide, etc. Conclusions:At present, research on TCM syndrome differentiation and treatment for headache mainly focuses on three major sections: acupuncture, moxibustion and massage, clinical efficacy of TCM syndrome differentiation and treatment, and experience of famous doctors. Future research mainly focuses on data mining, medication law, network pharmacology, syndrome elements, and pathogenesis.

Objective:To assess the predictive value of acute liver failure (ALF) for sepsis-free survival (SFS) in burn patients and to identify associated risk factors.Methods:A retrospective cohort study was conducted on burn patients meeting inclusion criteria from the 2014 Kunshan aluminum dust explosion disaster (August 2, 2014 - April 13, 2015). Eligible patients were stratified into ALF and non-ALF groups based on the development of ALF. Demographic characteristics, total burn surface area, organ dysfunction, time to sepsis onset, and clinical outcomes were collected and compared between groups. Kaplan-Meier survival analysis and multivariate Cox regression were performed to assess the impact of ALF on SFS. A nomogram model was constructed for individualized risk prediction.Results:Among 185 enrolled patients (ALF group:21, non-ALF group:164), ALF incidence was 11.35%. The ALF group demonstrated higher mortality (85.71% vs. 34.15%, P<0.001) and SFS failure rates (100.00% vs. 61.59%, P<0.001) compared to non-ALF patients. Multivariate Cox analysis identified ALF as an independent sepsis predictor ( HR=1.68, 95% CI: 1.00-2.80, P<0.05). Time-dependent ROC analysis showed AUCs of 0.626, 0.714, 0.703, and 0.706 for SFS prediction at 2, 4, 8, and 12 weeks respectively. The nomogram model demonstrated that ALF combined with other parameters effectively predicted sepsis risk within 2-12 weeks post-injury. ALF development showed significant associations with concurrent organ dysfunction including acute kidney injury, acute heart failure, and acute respiratory distress syndrome (all P<0.001). A higher proportion of ALF patients received hemodialysis ( P<0.001) and pre-hospital central venous catheterization ( P=0.017). Conclusions:ALF independently predicts SFS failure and correlates strongly with poor prognosis in burn patients. Early ALF recognition and targeted interventions may facilitate sepsis risk stratification and precision prevention strategies.

This paper analyzed the "non-standardization" phenomenon of syndrome differentiation in traditional Chinese medicine （TCM） from the diagnosis process. It is proposed that the symptoms and signs collected by the four examinations of inspection， listening/smelling， inquiry， and palpation naturally have a certain "ambiguity"， which can be reduced by the comparison and comprehensive condensation （comprehensive analysis of the four examinations） of a large amount of multi-dimensional clinical data， thereby realizing the sublimation of TCM diagnosis from "ambiguity" of four examinations to "accuracy" of diagnostic conclusion. Based on the above assumptions， this paper further proposed that a research idea of intelligent syndrome differentiation in TCM， that is， by taking the clinical thinking ability of TCM physicians as the core， adopting artificial intelligence technology based on knowledge graph visualization， integrating the complex network association and reasoning method of "symptom-pathogenesis-syndrome" linked by pathogenesis， and through the automatic analysis and reasoning process of a large amount of multi-dimensional and ambiguous clinical data， the intelligent TCM diagnosis based on syndrome differentiation can be realized.

Objective:Differences between randomized controlled trial (RCT) results and real world study (RWS) results may not represent a true efficacy-effectiveness gap because efficacy-effectiveness gap estimates may be biased when RWS and RCT differ significantly in study design or when there is bias in RWS result estimation. Secondly, when there is an efficacy- effectiveness gap, it should not treat every patient the same way but assess the real-world factors influencing the intervention's effectiveness and identify the subgroup likely to achieve the desired effect.Methods:Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31 st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results:Ten articles were included to discuss how to use the RCT research protocol as a template to develop the corresponding RWS research protocol. Moreover, based on correctly estimating the efficacy-effectiveness gap, evaluate the intervention effect in the patient subgroup to confirm the subgroup that can achieve the expected benefit-risk ratio to bridge the efficacy-effectiveness gap.Conclusion:Using real-world data to simulate key features of randomized controlled clinical trial study design can improve the authenticity and effectiveness of study results and bridge the efficacy-effectiveness gap.

Objective:Randomized controlled trials (RCT) usually have strict implementation criteria. The included subjects' characteristics of the conditions for the intervention implementation are quite different from the actual clinical environment, resulting in discrepancies between the risk-benefit of interventions in actual clinical use and the risk-benefit shown in RCT. Therefore, some methods are needed to enhance the extrapolation of RCT results to evaluate the real effects of drugs in real people and clinical practice settings.Methods:Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31 st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results:A total of 12 articles were included. Three methods in the included literature focused on: ①improving the design of traditional RCT to increase population representation; ②combining RCT Data with real-world data (RWD) for analysis;③calibrating RCT results according to real-world patient characteristics.Conclusions:Improving the design of RCT to enhance the population representation can improve the extrapolation of the results of RCT. Combining RCT data with RWD can give full play to the advantages of data from different sources; the results of the RCT were calibrated against real-world population characteristics so that the effects of interventions in real-world patient populations can be predicted.

The clinical demand for occlusal reconstruction increases rapidly with increasing number of patients who have lost their normal occlusion because of tooth wear and dentition defects.Occlusal reconstruction is a special type of restoration defined as a comprehensive restoration of the function of the stomatognathic system by reestablishing a uni-form and stable occlusal relationship between the upper and lower dentitions.Occlusal function analysis is an important part of occlusal reconstruction to achieve accurate restora-tion design and adjustment.Digital occlusal function analysis was conducted to monitor the movement of the mandible and obtain related data for the parameter design of occlusal reconstruction.Preoperative design,intraoper-ative adjustment,and postoperative verification were achieved,thereby improving the efficiency and accuracy of occlusal reconstruction.

Objective:To establish an ultrasound radiomics model by integrating clinical, pathological, and conventional ultrasound features with radiomics characteristics, and to explore its clinical value in predicting endocrine resistance in hormone receptor(HR)-positive breast cancer.Methods:A retrospective analysis was performed on 478 patients with HR-positive breast cancer from January 2017 to December 2021 in the Second Affiliated Hospital of Harbin Medical University, of which 430 were resistant and 48 were sensitive. The clinical, pathological and immunohistochemical data and ultrasound images were collected.Firstly, the propensity score was used to process and match the data. Secondly, Logistic regression was used to screen clinical, pathological, and conventional ultrasound features associated with endocrine resistance. Then, PyRadiomics was used to extract the radiomic features of grayscale ultrasound images, and a series of methods such as Lasso regression were used to screen the radiomic features related to endocrine resistance. Seven machine learning methods such as random forest were used to build a radiomics model. Finally, clinical, pathological and ultrasound features were added to establish a clinical pathological model, a clinical pathological ultrasound model, a clinical pathological radiomics model and a combined model of the four features, and the model effectiveness was evaluated.Results:①Propensity score matching: 96 patients were matched, including 48 patients in the drug-resistant group and 48 patients in the sensitive group. ②Screening clinical pathological conventional ultrasound features related to endocrine resistance: lymph node metastasis, tumor diameter, posterior echo attenuation, and growth orientation were independent predictors of endocrine resistance (all P<0.05). ③Screening radiomics features related to endocrine resistance: 18 features such as Dependence Entropy. ④Establishing radiomics model: the machine learning model of random forest method (AUC=0.80) performed best. ⑤Radiomics model integrating clinical, pathological and conventional ultrasound features: the AUC of the clinical pathological model was 0.70, the AUC of the clinical pathological ultrasound model was 0.78, the AUC of the clinical pathological radiomics model was 0.82, and the AUC of the combined model was 0.86. Conclusions:The radiomics model established by the random forest method performs best in predicting endocrine resistance in HR-positive breast cancer. The model that integrates multiple features performs best in assessing endocrine resistance.which is expected to provide an objective basis for clinicians to predict endocrine resistance in HR-positive breast cancer.

BACKGROUND:Exercise has a regulatory effect on intestinal flora dysbiosis,which can effectively protect the beneficial flora and improve the intestinal environment.However,the effect of treadmill exercise on the structure and diversity of intestinal microbial community in Parkinson's disease and the specific mechanism are not clear. OBJECTIVE:Using 16S rDNA technique to analyze the effect of treadmill exercise on the structure and diversity of the intestinal flora of rats with Parkinson's disease,and to investigate the mechanism of non-pharmacological treadmill exercise to improve Parkinson's disease. METHODS:Twelve of the 18 Sprague-Dawley rats were randomly selected to make animal models of Parkinson's disease using unilateral 2-point nigrostriatal injection of 6-hydroxydopamine.The remaining six rats were used as sham-operation group,which were injected with the same dose of saline containing 0.2%ascorbic acid using the same positioning and injection method.After successful modeling,12 rats with Parkinson's disease were randomly divided into model group and treadmill exercise group(n=6 per group).The treadmill exercise group was subjected to a middle and low intensity tread mill exercise,10 m/min,30 minutes per day,5 days per week for 4 weeks.Fresh feces were collected and stored in liquid nitrogen 24 hour after the last exercise session,and the changes in fecal flora were analyzed by 16S rDNA sequencing technique. RESULTS AND CONCLUSION:Treadmill exercise significantly improved behavior and nigrostriatal tyrosine hydroxylase-positive cell expression in rats with Parkinson's disease model and alleviated changes in the structure and diversity of the gut microbial community caused by Parkinson's disease,increased the number of operational taxonomic units and modulated Alpha and Beta diversity in rats.At the phylum and genus levels,the abundance ratio of Firmicutes/Bacteroidetes in the model group decreased compared with the sham-operated group,while beneficial bacteria such as Prevotella,Bacteroides,and Clostridium_XlV increased significantly after treadmill exercise.To conclude,treadmill exercise has a significant modulating effect on behavioral abnormalities,toxic damage to dopaminergic neurons and gut microbial imbalance caused by Parkinson's disease,alleviates the symptoms of flora-related diseases,and has a positive effect on the improvement of Parkinson's disease.