ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Continuous manufacturing, as an innovative pharmaceutical production model, offers advantages such as high production efficiency and ease of control compared to traditional batch production, aligning with the future trend of drug production moving toward greater efficiency and intelligence. However, the development of continuous manufacturing technology in wet granulation has been slow. On one hand, this is closely related to its high technical complexity, substantial equipment investment costs, and stringent process control requirements. On the other hand, the long-term use of the traditional batch production model has created strong path dependence, and the lack of mature standardized processes further increases the difficulty of technological transformation. To promote the deep integration of wet granulation technology with continuous manufacturing, this review systematically outlines the current application of wet granulation in continuous manufacturing. It focuses on the development of key technologies such as online detection, process modeling, and process scale-up, with the aim of providing a reference for process innovation and application in wet granulation.
Drug Compounding/instrumentation* ; Technology, Pharmaceutical/methods* ; Drugs, Chinese Herbal/chemistry* ; Models, Theoretical

OBJECTIVE: To explore clinical effect of autologous osteochondral transplantation (AOT) in the treatment of recurrent anterior dislocation of the shoulder joint with glenoid cartilage defect in rabbits by establishing a model of recurrent anterior dislocation of the shoulder joint with < 20% glenoid cartilage defect in rabbits. METHODS: Twenty-four male New Zealand white rabbits, aged 6-month-old, weighed (2.69±0.17) kg were selected. The labrum of shoulder joint of rabbits was artificially destroyed to establish a model of recurrent anterior dislocation of shoulder joint with cartilage defect. They were divided into AOT surgery group and simple suture group, with 12 rabbits in each group. AOT group were underwent AOT surgery, while simple suture group was treated with simple Bankart suture for recurrent shoulder joint dislocation. At 6 and 12 weeks after operation, 6 rabbits between two groups were sacrificed for sampling. The dietary conditions, activity conditions, mental states of rabbits and healing conditions of grafts in the specimens were observed and compared between two groups. HE staining was used to observe cell creep, cell morphology, inflammatory cell infiltration, fibrochondrocytes and their arrangement. Masson staining was used to observe the formation and arrangement of collagen fibers; Safrane-green staining was used to observe the regeneration of articular cartilage, subchondral bone and bone tissue. Bone mineral density (BMD), bone volume (BV) and trabecular thickness (Tb.Th) between two groups were measured by Micro-CT to evaluate the remodeling of shoulder glenoid bone defects by autologous osteochondral cartilage. RESULTS: After different surgical interventions were carried out in both groups of rabbits, at 6 weeks after the operation, the abduction, extension, internal rotation and external rotation of the shoulder joint on the operated side showed limited range of motion compared with the contralateral side, while adduction and forward flexion showed no obvious abnormalities compared with the contralateral side. At 12 weeks after operation, the range motion of tshoulder joints in both groups of rabbits had returned to the state before modeling. The effects of HE staining, Masson staining and safrane-green staining at 12 weeks after operation in both groups were stronger than the staining results at 6 weeks after operation. Moreover, the results of HE staining, Masson staining and safranin fixation green staining in AOT group at 6 and 12 weeks after operation were all higher than those in simple suture group. Micro-CT scan results at 6 and 12 weeks after operation showed that BMD (0.427±0.014), (0.466±0.032) g·cm-3, BV(116.171±3.527), (159.327±3.500) mm3, and Tb.Th (0.230±0.006), (0.285±0.009) mm in AOT group, which were higher than those of simple suture group in BMD(0.358±0.011), (0.384±0.096) g·cm-3, BV(72.657±3.903), (118.713±3.860) mm3, and Tb.Th(0.204±0.009), (0.243±0.007) mm;and the differences were statistically significant (P<0.05). CONCLUSION AOT procedure could effectively promote osteogenesis and fibrocartilage regeneration in the cartilage defect area of the shoulder glenoid <20%, which is conducive to reshaping the structure of the shoulder glenoid.
Animals ; Rabbits ; Male ; Transplantation, Autologous ; Cartilage, Articular/injuries* ; Shoulder Dislocation/physiopathology* ; Bone Transplantation ; Shoulder Joint/surgery*

OBJECTIVE: To explore the immunophenotypic characteristics of bone marrow granulocytes (G) and their clinical significance in patients with multiple myeloma (MM). METHODS: The granulocyte immunophenotypes of bone marrow in 70 MM patients (MM group) and 40 anemia patients (control group) were detected by flow cytometry, and its correlation with clinical characteristics was further analyzed. Univariate and multivariate regression analysis were used to screen factors that affected prognosis. RESULTS: The CD56⁺G%, CD13⁺G%, CD22⁺G% and CD117⁺G% in MM group were higher than those in the control group (all P <0.05). CD56⁺G% and CD117⁺G% in CR⁺VGPR group were significantly lower than those in PR+MR+PD group (both P <0.05). The CD10⁺G% in RISS Ⅲ stage and Ca²⁺ ≥2.65 mmol/L groups were increased (both P <0.05). The CD56⁺G% in elevated lactate dehydrogenase, β₂-microglobulin≥5.5 mg/L and hemoglobin <85 g/L groups were increased (all P <0.05), while the CD117⁺G% in high-risk cytogenetic positive group was decreased (P <0.05). The expression rate of CD molecules on granulocytes was divided into low (L) and high (H) groups according to the median value. The overall survival (OS) of the LCD56⁺G%, LCD13⁺G% and LCD22⁺G% groups was significantly prolonged (all P <0.05). CD13⁺G% and CD22⁺G% were independent risk factors for OS in MM patients (HR=0.443, 0.410, both P <0.05). CONCLUSION The CD56⁺G%, CD10⁺G% and CD117⁺G% are closely correlated with clinical features in MM patients, while CD13⁺G% and CD22⁺G% are closely correlated with prognosis. Detection of CD molecules expression on granulocytes may be used to evaluate prognosis and guide treatment.
Humans ; Multiple Myeloma/immunology* ; Granulocytes/immunology* ; Prognosis ; Immunophenotyping ; Male ; Bone Marrow ; Female ; Flow Cytometry ; Middle Aged ; Aged ; Clinical Relevance

OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

Dark plum can be used to treat symptoms such as consumptive thirst due to deficiency-heat and chronic cough due to lung deficiency.Its active ingredients have auxiliary effects on lowering blood glucose,antibacterial and anti-inflammatory activities.Insulin resistance is mainly characterized by the weakening of the physiological effects of insulin in the body,with a relatively complex mechanism that can lead to various metabolic-related diseases and seriously affect health.The active ingredients of dark plum can improve insulin resistance by regulating insulin signaling pathways,endoplasmic reticulum stress,antioxidant stress,inflammatory signaling pathways,levels of related inflammatory mediators,and free fatty acid levels.By reviewing the relevant literature on the improvement of insulin resistance by the active ingredients of dark plum,this article summarizes and analyzes its mechanism of action,aiming to provide new ideas and scientific evidence for in-depth research on insulin resistance and the development and application of drugs.

Objective:To investigate the predictive value of color Doppler ultrasound combined with electrocardio-gram for right heart dys function in patients with pulmonary heart disease(PHD).Methods:A total of 100 PHD patients admitted in Dongcheng Branch of First Affiliated Hospital of Anhui Medical University between January 2020 and December 2023 were retrospectively analyzed.According to results of 6min walking test(6MWT),pa-tients were divided into good right heart function group(n=64,≥350m)and right heart dysfunction group(n=36,＜350m).The indexes of cardiac color ultrasound[isovolumic relaxation time(IVRT),isovolumetric contraction time(IVCT)and right ventricular Tei index],ECG[24h mean R-R interval standard deviation(SDNN),normal R-R interval standard deviation per 5min(SDANN)and the ratio of low frequency components to high frequency components(LF/HF)]were compared between two groups.Receiver operating characteristic(ROC)curve was drawn to analyze the diagnostic value of color Doppler ultrasound,ECG and their combination for right heart dys-function in PHD patients.Spearman correlation coefficient was used to analyze the association of color Doppler ul-trasound,ECG and their combination with right heart dysfunction in PHD patients.Results:Compared with those in good right heart function group,patients in right heart dysfunction group had significant higher IVRT[(120.64±14.08)ms vs.(97.87±10.93)ms],IVCT[(84.28±12.33)ms vs.(71.92±10.61)ms]and Tei index[(0.85±0.11)vs.(0.63±0.07)](P＜0.001 all),and significant lower SDNN[(75.52±12.58)ms vs.(85.58±11.75)ms],SDANN[(63.86±10.92)ms vs.(76.75±11.71)ms]and LF/HF[(1.33±0.19)vs.(1.84±0.27)](P＜0.001 all).ROC curve indicated that the AUC of color Doppler ultrasound combined ECG in diagnosing right heart dysfunction in PHD patients was 0.911(95％CI 0.838～0.959),which was significantly higher than those of color Doppler ultrasound[0.775(95％CI 0.681～0.853),Z=2.404,P=0.016]and ECG[0.688(95％CI 0.588～0.777),Z=3.968,P=0.001]alone.Spearman correlation analysis indicated that there was a significant positive correlation of color Doppler ultrasound(r=0.547),ECG(r=0.375)and their combination(r=0.810)with right heart dysfunction in PHD patients(P＜0.001 all),and the correlation between combined detection and right heart dysfunction in PHD patients was significantly higher.Conclusion:Color Doppler ultrasound combined with ECG possesses high diagnostic performance for right heart dysfunction in PHD patients.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.