Oral solid dosage forms require processes such as disintegration and dissolution to release the drug before it can be absorbed and utilized by the body. In this manuscript, imaging technology was used to continuously visualize and characterize the in vitro static drug release process of gliclazide modified release tablets from 15 manufacturers, combined with the traditional method of in vitro dissolution testing, to determine the release profile of gliclazide modified release tablets, to evaluate the similarity of the release profiles by using the similarity factor (f₂) method and based on the analysis of the release profiles fitted with a variety of mathematical models. The results indicate that the gliclazide modified release tablets produced by 14 companies are hydrophilic gel matrix tablets. Compared to the reference listed drug, the release profiles of formulations from 11 companies show high similarity (f₂ > 50) to the reference. Among these, formulations with visual characteristics similar to the reference exhibit similar release curves. This study provides an alternative method for the in vitro consistency evaluation of gliclazide modified release tablets, aiming to assess the in vitro release behaviour of generic formulations more accurately and comprehensively.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Objective To investigate the relationship between single nucleotide polymorphisms(SNPs)in the eNOS gene and genetic susceptibility to systemic lupus erythematosus(SLE)in Hainan.Methods Blood samples were collected from SLE patients(SLE group,n=214)and healthy controls(control group,n=214)from January 2020 to December 2022 at the First Affiliated Hospital of Hainan Medical College and Hainan Provincial People's Hospital.The bases of eNOS gene rs3918188,rs1799983 and rs1007311 loci in each group were detected by SNaPshot sequencing technology.Logistic regression was used to analyze the correlation between genotypes,alleles and gene models(dominant model,recessive model,and overdominant model)of the above 3 target loci of the eNOS gene and genetic susceptibility to SLE.Haplotype analysis was conducted using HaploView 4.2 software to investigate the relationship between haploid and genetic susceptibility to SLE at each site.Results The results of logistic regression analysis revealed that the CC genotype and the C allele at rs3918188 locus were risk factors for genetic susceptibility to SLE(CC vs.AA:OR=2.449,P<0.05;C vs.A:OR=2.133,P<0.001).In recessive model at rs3918188 locus,CC genotype carriers had an increased risk of SLE development compared with AA+AC genotype carriers(OR=2.774,P<0.001).In contrast,in overdominant model at this locus,AC genotype carriers had a decreased risk of SLE occurrence compared with AA+CC genotype carriers(OR=0.385,P<0.001).In addition,polymorphisms of rs1799983 and rs1007311 were not associated with susceptibility to SLE in genotype,allele type and the 3 genetic models(P>0.05).Haplotype analysis revealed a strong linkage disequilibrium between the rs1007311 and rs1799983 loci of the eNOS gene,but no significant correlation was found between haplotype and genetic susceptibility to SLE(P>0.05).Conclusion The CC genotype and C allele at rs3918188 locus of eNOS gene may be risk factors for SLE in Hainan,while the risk of SLE occurrence is reduced in carriers of AC genotype under the overdominant model.

Objective:This study aimed to assess the effects of Peer Balint-style group on the empathy ability of third-year long-term medical students and to provide a theoretical and practical reference for effectively improving their humanistic quality.Methods:Ninety third-year Chinese long-term medicine students participated. Volunteers received either ten sessions of 1.5-h Peer Balint-style group which were led by specially trained peers from June 2019 to August 2019. The College Students' Empathy Ability Questionnaire was used before the experiment and the second day after the experiment. The total score of the scale from the pre-test and post-test and the scores of each dimension conformed to a normal distribution, with equal variance, describing in the form of ( x± s). Paired t-tests were performed to compare the total score and each dimension score before and after the intervention, using SPSS 22.0. Semi-structured interviews were conducted with 7 peer-group leaders and group members after the clinical practice period. The interview materials were analyzed by traditional content analysis. The content of the qualitative research was open-coded to obtain 10 categories, suggesting the role and inadequacy of Peer Balint-style groups. Results:A total of 63 valid samples were obtained. There was no significant difference of ( t=-0.44, P=0.661, P>0.05) between the total score of the post-test (118.00±11.98) and the total score of the pre-test (117.38±12.36). In each dimension, the reverse comprehension score of post-test (9.06±1.97) was significantly different ( t=-2.08, P=0.041, P>0.05) from the pre-test's (8.57±2.15), which increased compared to the pre-test score. Conclusions:Peer Balint-style group had a positive effect on improving empathy among medical students. Compared with the traditional Balint group, it has wider coverage, higher affinity and greater mobility. However, the design of the Peer Balint-style group still needs to be further improved.

Hypertension is a common chronic disease,and its incidence is increasing year by year worldwide.Its pathological mechanism is complex,involving genetics,environment,lifestyle and other factors.In recent years,the role of immune-inflammatory mechanism in the pathogenesis of hypertension has gradually attracted attention.Especially T helper cell 17(Th17)and regulatory T cells(Treg),as important components of the immune system,the effect of their balance on hypertension has become a research hotspot.This article reviews the research progress of the correlation between Th17/Treg and hypertension,in order to provide new ideas and methods for the immunotherapy and prevention of hypertension.

After entering the body from the drug delivery site, antitumor nanomedicines need to cross a series of physiopathological barriers to reach the target site of action to effectively exert antitumor therapeutic effects. The ligand modification strategy is a classic method to enhance the efficiency of nanomedicine delivery in vivo, but the contradiction between the single ligand modification strategy, which is characterized by unity and stage, and the in vivo delivery process, which is characterized by versatility and whole-process characteristics, determines that nanomedicines modified by a single ligand alone cannot satisfy the target efficacy requirements. Therefore, the use of multiligand combinatorial modification strategies by virtue of nanomedicine surface area advantages is key to advancing the next generation of smart nanomedicines. In this paper, on the basis of summarizing and classifying the commonly used functional ligands for in vivo delivery, the advantages and research progress of multiligand combination modification of antitumor nanomedicines are discussed with special focus, and the multiligand combination modification is classified as synergistic and complementary according to the combination of the ligands, which is of great significance to ensure that antitumor nanomedicines can overcome the multiple physiopathological barriers to achieve precise delivery.