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.

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.

Objective:To investigate the effects of differential torque of maxillary posterior teeth with clear aligner on anterior teeth 3D mechanics.Methods:4 maxillary models were designed for differential torque of posterior teeth on the basis of 3D me-chanical test model with first premolar extraction.The stereolithography models were made with the same size as the standard model by 3D printing.According to the torque of the 6 keys to normal occlusion of Andrews,the standard torque of Andrews was used in group A1.The posterior teeth with lingual-crown torque of 5° were used in groups A2,and those with buccal-crown torque of 5° and 10° were respecitvely used in group A3 and A4.4 sets of corresponding clear aligners were fabricated with a 0.75 mm thick thermoplastic material.Each group had 12 pairs of the same clear aligners.The anterior teeth underwent 0.25 mm activation for en-mass retraction.The six-axis force/torque transducer measurement system was used to measure the force applied by the clear align-ers on the anterior teeth in the 3D directions.Results:In buccolingual direction:in group A1,the 4 incisors received lingual force,in groups A2-A4,the anterior teeth received labial force,and the force on the central incisors was greater than that on later-al incisors.In mesiodistal direction:in group A1-A4,4 incisors received mesial force,and the force on lateral incisors was greater than that on central incisors;in group A1-A4,the canines received distal force;the force on canine in group A4 was greater than that in A2 or A3 groups(P＜0.05).The force in the vertical direction on the anterior teeth among the 4 groups(P＞0.05).Conclu-sion:When en-mass retraction of the anterior teeth with clear aligner,attention should be taken to the torque of the incisors and the tip of the canines.When the posterior teeth with standard torque,the activation of labial-crown overcorrection of the anterior teeth should be increased.When the posterior teeth with lingual-crown torque or buccal-crown torque,the activation of labial-crown over-correction of the anterior teeth should be appropriately reduced.Increasing the mesial overcorrection design of canines may avoid the extrusion of anterior teeth and the deepening of o-verbite due to the distal inclination of canines.

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*

In order to meet the need of autonomous control of patients with severe limb disorders, this paper designs a nursing bed control system based on motor imagery-brain computer interface (MI-BCI). In view of the low decoding performance of cross-subjects and the dynamic fluctuation of cognitive state in the existing MI-BCI technology, the neural network structure optimization and user interaction feedback enhancement are improved. Firstly, the optimized dual-branch graph convolution multi-scale neural network integrates dynamic graph convolution and multi-scale convolution. The average classification accuracy is higher than that of multi-scale attention temporal convolution network, Gram angle field combined with convolution long short term memory hybrid network, Transformer-based graph convolution network and other existing methods. Secondly, a dual visual feedback mechanism is constructed, in which electroencephalogram (EEG) topographic map feedback can improve the discrimination of spatial patterns, and attention state feedback can enhance the temporal stability of signals. Compared with the single EEG topographic map feedback and non-feedback system, the average classification accuracy of the proposed method is also greatly improved. Finally, in the four classification control task of nursing bed, the average control accuracy of the system is 90.84%, and the information transmission rate is 84.78 bits/min. In summary, this paper provides a reliable technical solution for improving the autonomous interaction ability of patients with severe limb disorders, which has important theoretical significance and application value.
Humans ; Brain-Computer Interfaces ; Deep Learning ; Electroencephalography ; Feedback, Sensory ; Neural Networks, Computer ; Beds

Objective To study the spatial distribution of the incidence of pulmonary tuberculosis in Hubei Province and its influencing factors, so as to improve the theoretical basis for scientific development of tuberculosis prevention and control measures in the future. Methods The data of reported incidence of tuberculosis and related influencing factors in various counties and districts of Hubei Province in 2020 were collected. Global Moran's I index, hotspot analysis and geographically weighted regression (GWR) model analysis were used to calculate the spatial autocorrelation of the incidence of tuberculosis, and to analyze the influencing factors affecting the incidence rate of tuberculosis. Results There were obvious regional differences in the space distribution of the incidence rate of tuberculosis. Hot spot analysis showed positive spatial correlation and obvious clustering. The GWR model (AICc=784.251) in this study had higher AICc value compared to the ordinary least squares regression (OLS) model (AICc=804.2585). The GWR model showed that the increase in the proportion of the population aged 65 and above and the proportion of the ethnic minority population had a significant promoting effect on the increase of the incidence rate of tuberculosis, and there was significant spatial heterogeneity. The effect of PM_2.5 concentration on the incidence rate of pulmonary tuberculosis varied in different regions, and the degree of effect was also different. Conclusion The proportion of people aged 65 and above and the proportion of ethnic minorities may significantly influence the incidence of pulmonary tuberculosis. The effect of PM_2.5 concentration varies in different regions, so targeted measures should be formulated according to the situation in different regions.