ObjectiveTo elucidate the chemical composition of the reference sample of Jinshui Liujunjian and its distribution characteristics in blood and tissues of rats. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect the reference sample solution， plasma， and tissue samples of Jinshui Liujunjian under positive and negative ion modes， respectively. Qualitative Analysis 10.0 software and a self-constructed database were employed for primary mass spectrum matching.Compound identification was further validated by comparing retention times， secondary mass spectral fragments， reference standards， and literature data to deduce fragmentation pathways. ResultsA total of 122 compounds were identified in the reference sample of Jinshui Liujunjian， including 47 flavonoids， 5 amino acids， 13 iridoids， 16 triterpenoid saponins， etc.， of which 42 compounds were confirmed by comparison with reference substances. A total of 21 prototype components were identified in blood components； 50 prototype components were identified in different tissues， among which 13， 10， 7， 21， 11， 6， 14， and 40 prototype components were identified in the heart， liver， spleen， lung， kidney， brain， large intestine， and stomach， respectively. Among them， 7 compounds such as ferulic acid， glycyrrhizic acid， and nobiletin were exposed in the target organs of lung and kidney. ConclusionThis study elucidates the material basis of the reference samples of Jinshui Liujunjian， primarily composed of flavonoids and triterpenoid saponins， along with their in vivo distribution characteristics. These findings provide a scientific basis for establishing quality evaluation indicators and offer references for subsequent pharmacodynamic and pharmacokinetic investigations.

ObjectiveTo elucidate the chemical composition of the reference sample of Jinshui Liujunjian and its distribution characteristics in blood and tissues of rats. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect the reference sample solution， plasma， and tissue samples of Jinshui Liujunjian under positive and negative ion modes， respectively. Qualitative Analysis 10.0 software and a self-constructed database were employed for primary mass spectrum matching.Compound identification was further validated by comparing retention times， secondary mass spectral fragments， reference standards， and literature data to deduce fragmentation pathways. ResultsA total of 122 compounds were identified in the reference sample of Jinshui Liujunjian， including 47 flavonoids， 5 amino acids， 13 iridoids， 16 triterpenoid saponins， etc.， of which 42 compounds were confirmed by comparison with reference substances. A total of 21 prototype components were identified in blood components； 50 prototype components were identified in different tissues， among which 13， 10， 7， 21， 11， 6， 14， and 40 prototype components were identified in the heart， liver， spleen， lung， kidney， brain， large intestine， and stomach， respectively. Among them， 7 compounds such as ferulic acid， glycyrrhizic acid， and nobiletin were exposed in the target organs of lung and kidney. ConclusionThis study elucidates the material basis of the reference samples of Jinshui Liujunjian， primarily composed of flavonoids and triterpenoid saponins， along with their in vivo distribution characteristics. These findings provide a scientific basis for establishing quality evaluation indicators and offer references for subsequent pharmacodynamic and pharmacokinetic investigations.

ObjectiveTo analyze the comorbidity patterns of chronic metabolic diseases and their influencing factors among residents aged 35‒75 years old in Nantong City of Jiangsu Province, and to provide theoretical support for the prevention and control of comorbidities. MethodsThe permanent residents aged 35‒75 years from the Comprehensive Prevention and Control Project of Cardiovascular and Cerebrovascular Diseases in Nantong City from 2021 to 2024 were selected as the research subjects. Clustering analysis and association rule were used to investigate the comorbidity patterns of chronic metabolic diseases, and their influencing factors were identified through logistic regression analyses. ResultsThe prevalence of comorbidity of chronic metabolic diseases among residents aged 35‒75 years in Nantong City was 47.40%. Among comorbidity patterns based on disease counts, the prevalence of hypertension+dyslipidemia was highest in binary comorbidity patterns (6.25%), while that of hypertension+dyslipidemia+obesity was highest in ternary comorbidity patterns (4.01%). Association rules showed that in both binary and ternary comorbidity patterns, the confidence level was highest for obesity+hypertension (72.70%) and obesity+dyslipidemia+hypertension (74.54%). Renal insufficiency formed an independent cluster in cluster analyses. Logistic regression analyses revealed that, compared with the non-comorbidity group, males (OR=2.22, 95%CI: 1.69‒2.91), advanced age (45‒54 years, OR=1.38, 95%CI: 1.02‒1.88; 55‒64 years, OR=1.59, 95%CI: 1.14‒2.23; 65‒75 years, OR=2.34, 95%CI: 1.58‒3.47), and low physical activity (OR=1.26, 95%CI: 1.10‒1.65) were influencing factors for metabolic disease comorbidity. ConclusionIn the comorbidity patterns of chronic metabolic diseases among residents aged 35‒75 years in Nantong City, hypertension, diabetes mellitus, and dyslipidemia interact with each other. Individuals with obesity are more prone to diseases such as hypertension and dyslipidemia. Prevention and control of chronic metabolic diseases should be strengthened for males, individuals with low physical activity and advanced age.

ObjectiveThis study aimed to evaluate the effectiveness of various statistical methods based on the complementary sensitivity analysis framework recommended by the European Medicines Agency (EMA) in Alzheimer’s disease clinical trials, providing a reference for statistical practice that meets international regulatory standards for similar studies. MethodsBased on longitudinal data from a phase Ⅲ clinical trial for the treatment of Alzheimer’s disease, the change from baseline in Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) score from baseline at week 26 (with a decrease indicating cognitive improvement) was used as the primary outcome measure. This study employed a mixed-effects model with repeated measures (MMRM) under the assumption of missing at random (MAR) as the primary analysis, while using critical point analysis, rank-based analysis, and slope-based analysis for sensitivity verification. A systematic comparison of the efficacy estimation results from the four analytical methods was conducted to compare the consistency and robustness differences in research conclusions across different analytical strategies. ResultsThe primary analysis results from the MMRM showed that the improvement in ADAS-Cog score from baseline at week 26 in the treatment group was superior to that in the placebo group (LSMD=-3.22, 95%CI: -4.55 to -1.88, P<0.001). Both rank-based analyses and slope-based analyses indicated significant differences between groups (both P<0.001). Critical point analyses revealed that the treatment effect was negative under most reasonable missing hypothesis scenarios, with the effect value only potentially turning positive in extreme non-random missing scenarios. There was no overall reversal of the efficacy conclusion. ConclusionThe combination of MMRM, critical point analysis, rank-based analysis, and slope-based analysis can effectively address the challenge of missing data in clinical trials for progressive diseases. This strategy fully complies with international regulatory standards, verifies efficacy conclusions from multiple perspectives, and enhances the credibility and scientific validity of clinical trial results. It can provide a practical reference for statistical analysis of missing data in similar clinical trials for progressive diseases.

Objective To assess functional abnormalities in frontoparietal attention network of patients with traumatic brain injury(TBI),and to analyze neural mechanism of its attention disorders based on independent component analysis(ICA).Methods Totally 84 TBI patients were prospectively enrolled and divided into mild(n=33),moderate(n=27)and severe TBI groups(n=24)according to symptoms,non-contrast enhanced MRI findings,Glasgow coma scale(GCS)and Mayo craniocerebral trauma grading criteria.ICA was used to extract and analyze the optimal independent components(IC)of the dorsal attention network(DAN)and ventral attention network(VAN).Multiple linear regression analyses were performed to explore the correlations of functional connectivity(FC)of brain regions being significantly different among groups within attention network and the scores of trail making test A/B(TMT-A/B).Results Compared with control group and mild TBI group,spatial distribution of DAN(especially bilateral frontal eye field[FEF])in moderate and severe TBI groups were significantly smaller,the clusters tended to be discrete,and the intensity were significantly weakened.The right temporal parietal junction(TPJ)and right ventral frontal cortex(VFC)of VAN in control group,mild and moderate TBI groups were significantly affected,and VFC connection strength was the highest in severe TBI group.FC intensity in right VFC of TBI patients was positively correlated with TMT-A score(r=0.654,P＜0.001),which in left FEF was negatively correlated with TMT-B score(r=—0.383,P＜0.001).Conclusion FC of frontoparietal attention network was abnormal in TBI patients,which might be neural mechanism for its attention behavior disorders.

Objective A cross-sectional survey on the postoperative home care status and barriers was conducted among elderly patients with osteoporotic fractures nationwide,in order to provide a basis for promoting the improvement of standardized home care for elderly patients with osteoporotic fractures.Methods From October to November 2023,a survey on the current situation and barriers of home environment protection was conducted among elderly patients with osteoporotic fractures in the orthopedic wards of 594 hospitals across 31 provinces(autonomous regions/municipalities directly under the central government)using a convenience sampling method.Results A total of 14,349 questionnaires were distributed,and 12,496 valid questionnaires were collected,resulting in an effective response rate of 87.09％.Among the patients,5,502 cases(44.03％)had implemented home-based prevention and treatment of osteoporosis before the fracture.2 095(16.77％)of the patients experienced a subsequent fracture,of which 65.11％of the patients who experienced a subsequent fracture received medication intervention after the initial fracture,while 19.86％of the patients who experienced a subsequent fracture did not comply with the treatment for osteoporosis after the initial fracture.Additionally,77.66％(n=1 627/2 095)of the patients received community medical services after the initial fracture.Barriers to care factors in the home environment after fracture from the patient's perspective presented the complexity of the social-ecological system model in 6 dimensions at 2 levels:micro(basic personal situation,physiological factors,psychological factors,and behavioural factors),and meso(social support factors,and healthcare worker factors).Conclusion In the vast majority of elderly patients in China,before osteoporotic fracture,home-based measures to prevent osteoporosis have not been adequately implemented;after the initial osteoporotic fracture,the pathway of re-fracture prevention and management in the patient's home environment is not yet complete and its popularity needs to be improved;the barriers to home care faced by elderly patients with osteoporotic fracture are complex.It is recommended to promote effective linkages among hospitals,community health centres and families to strengthen the closed-loop management of re-fracture prevention and management.

BACKGROUND:Growth factor is the key effect molecule that plays a role in platelet-rich plasma in clinical treatment.There are differences in the concentration of growth factor after different activators activate platelet-rich plasma,which is an important factor affecting clinical efficacy. OBJECTIVE:To analyze the influence of different activators on the mass concentration of growth factors in platelet-rich plasma. METHODS:Totally 12 healthy volunteers were recruited to collect EDTA-K2 anticoagulant venous blood.Secondary centrifugation was used to prepare platelet-rich plasma.The difference in mass concentrations of growth factors was compared between venous blood and platelet-rich plasma.The platelet-rich plasma was mixed with four activators(normal saline,thrombin,calcium gluconate,calcium gluconate+thrombin)according to the volume ratio of 10:1,and incubated in a constant temperature water bath at 37 °C for 30 minutes.After centrifugation,the supernatant was extracted and the mass concentration of growth factor was detected.The bacterial growth in supernatant was measured by blood agar plate.Pearson correlation was used to analyze the correlation between different activators and the mass concentration of growth factor in platelet-rich plasma,and the correlation between the value of thrombocytometer and the mass concentration of growth factors in platelet-rich plasma. RESULTS AND CONCLUSION:(1)The mass concentrations of platelet-derived growth factor-BB,platelet-derived growth factor-AB,vascular endothelial growth factor,and epidermal growth factor in platelet-rich plasma were 8.7,22.2,2.3,and 2.8 times of those in venous blood,respectively(P<0.05).(2)Compared with normal saline group,the mass concentrations of platelet-derived growth factor BB,platelet-derived growth factor AB,vascular endothelial growth factor,and epidermal growth factor were increased in the thrombin group,calcium gluconate group,and calcium gluconate+thrombin group(P<0.05).The mass concentration of platelet-derived growth factor BB in the thrombin group and calcium gluconate group was higher than that in the calcium gluconate+thrombin group(P<0.05),and the mass concentration of platelet-derived growth factor AB in the thrombin group was higher than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).Epidermal growth factor mass concentration in the thrombin group was lower than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).(3)The results of blood agar plate test showed no bacterial growth in the supernatant of the four groups.(4)Pearson correlation analysis showed that the mass concentration of platelet-derived growth factor BB in platelet-rich plasma was strongly positively correlated with thrombin(r=0.683,P<0.05),and the mass concentration of vascular endothelial growth factor was strongly positively correlated with thrombin,calcium gluconate,calcium gluconate+thrombin stimulant(r=0.730,0.789,0.686,P<0.05).There was no correlation between the value of thrombocytometer and the mass concentration of four kinds of growth factors(P>0.05).(5)The results suggest that different activators have an impact on the concentration of growth factors in platelet-rich plasma.It is suggested to choose different activators to improve clinical efficacy according to different growth factor mass concentrations and treatment needs.

Extensive epigenetic reprogramming involves in memory CD8+ T-cell differentiation. The elaborate epigenetic rewiring underlying the heterogeneous functional states of CD8+ T cells remains hidden. Here, we profile single-cell chromatin accessibility and map enhancer-promoter interactomes to characterize the differentiation trajectory of memory CD8+ T cells. We reveal that under distinct epigenetic regulations, the early activated CD8+ T cells divergently originated for short-lived effector and memory precursor effector cells. We also uncover a defined epigenetic rewiring leading to the conversion from effector memory to central memory cells during memory formation. Additionally, we illustrate chromatin regulatory mechanisms underlying long-lasting versus transient transcription regulation during memory differentiation. Finally, we confirm the essential roles of Sox4 and Nrf2 in developing memory precursor effector and effector memory cells, respectively, and validate cell state-specific enhancers in regulating Il7r using CRISPR-Cas9. Our data pave the way for understanding the mechanism underlying epigenetic memory formation in CD8+ T-cell differentiation.
CD8-Positive T-Lymphocytes/metabolism* ; Cell Differentiation ; Chromatin/immunology* ; Animals ; Mice ; Immunologic Memory ; Epigenesis, Genetic ; SOXC Transcription Factors/immunology* ; NF-E2-Related Factor 2/immunology* ; Mice, Inbred C57BL ; Gene Regulatory Networks ; Enhancer Elements, Genetic

Chronic, unresolved inflammation correlates with persistent hepatic injury and fibrosis, ultimately progressing to hepatocellular carcinoma (HCC). Bisdemethoxycurcumin (BDMC) demonstrates therapeutic potential against HCC, yet its mechanism in preventing hepatic "inflammation-carcinoma transformation" remains incompletely understood. In the current research, clinical HCC specimens underwent analysis using hematoxylin-eosin (H&E) staining and immunohistochemistry (IHC) to evaluate the expression of fibrosis markers, M2 macrophage markers, and CXCL12. In vitro, transforming growth factor-β1 (TGF-β1)-induced LX-2 cells and a co-culture system of LX-2, THP-1, and HCC cells were established. Cell functions underwent assessment through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), flow cytometry, and Transwell assays. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blotting and immunofluorescence evaluated the differential expression of molecules. The interaction between β-catenin/TCF4 and CXCL12 was examined using co-immunoprecipitation (Co-IP), dual luciferase, and chromatin immunoprecipitation (ChIP) assays. A DEN-induced rat model was developed to investigate BDMC's role in liver fibrosis-associated HCC (LFAHCC) development in vivo. Our results showed that clinical HCC tissues exhibited elevated fibrosis and enriched M2 macrophages. BDMC delayed liver fibrosis progression to HCC in vivo. BDMC inhibited the inflammatory microenvironment induced by activated hepatic stellate cells (HSCs). Furthermore, BDMC suppressed M2 macrophage-induced fibrosis and HCC cell proliferation and metastasis. Mechanistically, BDMC repressed TCF4/β-catenin complex formation, thereby reducing CXCL12 transcription in LX-2 cells. Moreover, CXCL12 overexpression reversed BDMC's inhibitory effect on macrophage M2 polarization and its mediation of fibrosis, as well as HCC proliferation and metastasis. BDMC significantly suppressed LFAHCC development through CXCL12 in rats. In conclusion, BDMC inhibited LFAHCC progression by reducing M2 macrophage polarization through suppressing β-catenin/TCF4-mediated CXCL12 transcription.
Animals ; Liver Neoplasms/etiology* ; Humans ; Carcinoma, Hepatocellular/immunology* ; Liver Cirrhosis/complications* ; Macrophages/drug effects* ; Male ; Rats ; Chemokine CXCL12/genetics* ; Diarylheptanoids/pharmacology* ; Rats, Sprague-Dawley ; beta Catenin/genetics*

Objective To systematically evaluate the risk factors for new-onset atrial fibrillation (NOAF) after off-pump coronary bypass grafting (OPCABG). Methods PubMed, EMbase, Web of Science, The Cochrane Library, Wanfang data, CBM, VIP, and CNKI databases were systematically searched by computer to collect studies related to the risk factors for NOAF after OPCABG from the establishment of the database to July 2023. Literature screening and quality evaluation were conducted independently by two researchers. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature. RevMan 5.3 and Stata15.0 were used for meta-analysis. Results Finally, 19 case-control studies related to the risk factors for NOAF after OPCABG were included, all of which were high-quality literature with NOS score≥6 points, with a total of 7019 subjects. The results of meta-analysis showed that the following factors were associated with NOAF after OPCABG: (1) the patient’s own factors: age (MD=3.51, 95%CI 2.39 to 4.63, P<0.01); (2) preoperative factors: history of hypertension (OR=1.17, 95%CI 1.04 to 1.32, P=0.01), history of myocardial infarction (OR=1.21, 95%CI 1.06 to 1.38, P<0.01), history of percutaneous coronary intervention (OR=2.22, 95%CI 1.03 to 4.77, P=0.04), EuroSCOREⅡ score (MD=0.59, 95%CI 0.25 to 0.94, P<0.01), low-density lipoprotein (MD=0.11, 95%CI 0.02 to 0.20, P=0.02), left atrial diameter (MD=1.64, 95%CI 0.24 to 3.04, P=0.02); (3) postoperative and treatment factors: left ventricular end-diastolic diameter (MD=1.16, 95%CI 0.33 to 1.99, P<0.01), left ventricular ejection fraction (MD=0.90, 95%CI 0.07 to 1.73, P=0.03), mechanical ventilation time (MD=2.78, 95%CI 1.65 to 3.90, P<0.01), B-type natriuretic peptide (MD=219.67, 95%CI 27.46 to 411.88, P=0.03), ICU retention time (MD=7.07, 95%CI 5.64 to 8.50, P<0.01). Conclusion The existing evidence shows that age, history of hypertension, history of myocardial infarction, history of percutaneous coronary intervention, preoperative EuroSCOREⅡscore, preoperative low-density lipoprotein, preoperative left atrial diameter, postoperative left ventricular end-diastolic diameter, postoperative left ventricular ejection fraction, postoperative mechanical ventilation time, postoperative B-type natriuretic peptide, and postoperative ICU retention time are risk factors for NOAF after OPCABG. Clinical attention should be paid to the above factors to achieve early identification, thereby reducing the incidence of NOAF after OPCABG and improving the clinical prognosis of patients.