ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba（TPAGH）， and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group， recombinant human epidermal growth factor（rhEGF） group（4 mg·kg^-1）， and low， medium， and high dose groups of TPAGH（3.5， 7， 14 mg·kg^-1）， with 24 mice in each group. A full-thickness skin excision model was constructed， and each administration group was coated with the drug at the wound site， and the model group was treated with an equal volume of normal saline， the treatment was continued for 30 days， during which 8 mice from each group were sacrificed on days 6， 12， and 30. The healing of the wounds in the mice was observed， and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin（HE）， Masson， and Sirius red staining， and enzyme-linked immunosorbent assay（ELISA） was used to dynamically measure the contents of interleukin-6（IL-6）， tumor necrosis factor-α（TNF-α）， vascular endothelial growth factor A（VEGFA）， matrix metalloproteinase（MMP）-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH， and molecular docking of key components and targets was performed. Gene Ontology（GO） biological process analysis and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis were carried out for the related targets， so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH， including 28 phenylpropanoids， 31 tannins， 23 triterpenes， 49 flavonoids， and 15 others， and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that， compared with the model group， the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate（P<0.05）， and the number of new capillaries， number of fibroblasts， number of new skin appendages， epidermal regeneration rate， collagen deposition ratio， and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved（P<0.05， 0.01）， the levels of IL-6， TNF-α， MMP-3 and MMP-9 in the skin tissues were reduced to different degrees， while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets， including tumor protein 53（TP53）， sarcoma receptor coactivator（SRC）， protein kinase B（Akt）1， signal transducer and activator of transcription 3（STAT3）， epidermal growth factor receptor（EGFR） and so on， participating in 75 signaling pathways such as advanced glycation end-products（AGE）-receptor for AGE（AGE/RAGE） signaling pathway， phosphatidylinositol 3-kinase（PI3K）/Akt signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway. Molecular docking confirmed that the key components genistein， geraniin， and casuariin had good binding ability to TP53， SRC， Akt1， STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction， thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology， the study explores how key components may bind to targets such as TP53， Akt1 and EGFR， exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.

ObjectiveBased on analytic hierarchy process（AHP）-criteria importance through intercriteria correlation（CRITIC） hybrid weighting method， grey relational analysis and backpropagation artificial neural network（BP-ANN）， to optimize the water extraction process of Qizhi prescription， so as to provide an experimental basis for optimization of the preparation process of this prescription and the establishment of quality standards. MethodsL₉（3⁴） orthogonal test was employed， and the AHP-CRITIC hybrid weighting method was utilized to determine the weight coefficients of the quality fractions of various components， including astragaloside Ⅳ， polygalaxanthone Ⅲ， calycosin-7-O-β-D-glucoside， tenuifolin， and 3，6′-disinapoylsucrose， as well as the dry extract yield. The comprehensive score of each factor level combination in the orthogonal test were calculated as evaluation indicator to select the optimal extraction process parameters. The effects of extraction times， extraction time， and solvent dosage on the aqueous extraction process of the formula were investigated through intuitive analysis， variance analysis， and grey relational analysis. Meanwhile， a BP-ANN model was established to reverse-predict the optimal extraction process parameters of Qizhi prescription， and the optimized process parameters were validated. ResultsThe weight coefficients of the five index components（astragaloside Ⅳ， tenuifolin， calycosin-7-O-β-D-glucoside， polygalaxanthone Ⅲ， and 3，6′-disinapoylsucrose） and dry extract yield were 25.7%， 20.82%， 16.41%， 12.45%， 15.96% and 8.67%， respectively. The optimized extraction process parameters were extracted 3 times with 8， 6， 6 times the amount of water， each time for 1 h. The network prediction results of BP-ANN test samples were consistent with the orthogonal test results， and the mean square error（MSE） of the predicted and measured values of the network was <1%. The water extraction process of Qizhi prescription analyzed and predicted by relevant mathematical models was stable and feasible， which could effectively improve the extraction efficiency of the active ingredients of Astragali Radix and Polygalae Radix， and the average comprehensive score of the validation test was 90.85 with the relative standard deviation（RSD） of 1.55%. ConclusionThis study establishes a water extraction process for compound Qizhi granules， and the optimized extraction process can effectively improve the extraction efficiency of active ingredients， which provides useful references for the optimization of preparation process and the establishment of quality standards for other clinical experience formulas.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

OBJECTIVE To assess the scientific rigor， clarity and feasibility of the recommendations of the Guidelines for Evidence-based Use of Biological Agents for the Clinical Treatment of Osteoporosis （hereinafter referred to as the Guideline） through external review， in order to further revise and improve the Guideline recommendations. METHODS This study employed a cross-sectional survey research design， a convenience sampling method was adopted to select frontline medical workers in the field of osteoporosis （including clinical doctors， clinical pharmacists， and nurses） as well as patients or their family members. External review was conducted through a combination of closed-ended and open-ended electronic questionnaires to get feedback from them on the appreciation，clarity and feasibility of the 32 preliminary recommendations in the Guideline. RESULTS A total of 90 external review subjects from 15 hospitals were collected， including 45 clinical doctors， 15 clinical pharmacists， 15 nurses and 15 patients or their family members. The overall appreciation degree of recommendations was 99.38%， the overall clarity degree of recommendations was 98.92%， and the overall feasibility degree of recommendations was 99.65%. At the same time， 111 subjective suggestions were collected， which provided an important reference for the further improvement of the Guideline recommendations. Based on the above feedback， the Guideline steering committee and core expert group revised the wording of 12 draft recommendations without deletion， and finally determined 32 recommendations. CONCLUSIONS The external review provides an important basis for the final formation of the Guideline， further improves the scientific rigor， clarity and feasibility of the recommendations， and ensures the standardization， practicality and implementability of the Guideline.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

ObjectiveTo investigate the current status of emergency management for severe mental disorders in Shanghai, and to provide countermeasures and suggestions for the establishment of a sound emergency management system for severe mental disorders and the enhancement of emergency management capability. MethodsA questionnaire survey and qualitative interviews were used to conduct an investigation into the emergency management in 17 district-level mental illness prevention and control institutions in Shanghai, which includes the basic situation of emergency management for severe mental disorders, the construction of emergency response teams and personnel, emergency preparedness drills and training, emergency management plans and rules and regulations, and problems encountered in emergency management. ResultsIn terms of emergency management mechanism and basic situation, resources such as personnel allocation, security funds and green channel were well equipped in each district-level mental illness prevention and control institution in Shanghai. However, the equipment of some hardware facilities was still insufficient to some extent. Therefore, further improvement on the emergency management mechanism for severe mental disorders was needed. With regard to the construction of emergency team and personnel allocation, the majority were those aged between 35‒<45 years old, with a bachelor’s degree, and more than 10 years of working experience. For example, 90.27% staff in district-level mental illness prevention and control institution had a bachelor’s degree or above, which was higher than that among the staff in community-level (73.60%); staff majored in clinical medicine in district-level institution accounted for the proportion at 52.71%, higher than that among the staff in community-level (28.86%); 57.24% staff in district-level institution had an intermediate professional title, higher than that among the staff in community-level (42.28%); and 69.90% staff in district-level institution had more than 10 years of working experience, higher than that among the staff in community-level (43.62%). In the aspect of emergency drills and training, all district-level mental illness prevention and control institutions in Shanghai had a high demand for emergency training, and the weak aspects mainly focused on lack of emergency service protocols, skills of addressing technical challenges, and construction of effectiveness evaluation system. Moreover, the teaching methods were primarily centered on case analysis, simulation drills, interactive discussions, and so forth. Concerning emergency management plans and rules and regulations, all districts in Shanghai had relatively established well-developed systems for emergency response plans, emergency response leadership groups, and emergency response operational task forces for severe mental disorders. About half of the institutions had established other rules and regulations related to emergency management of severe mental disorders in addition to emergency plans. ConclusionShanghai has initially established an emergency management system for severe mental disorders, but it is still fragile in specialized training for emergency management of severe mental disorders, construction of emergency management mechanisms, and the building-up of grassroots emergency teams. Further priorities should include strengthening emergency management training, enhancing the construction of emergency management personnel teams, and gradually establishing a more comprehensive and integrated emergency management mechanism for severe mental disorders.

Objective To explore the longitudinal associations of body roundness index (BRI), visceral adiposity index (VAI), and metabolic score for visceral fat (METS-VF) with the risk of new-onset atrial fibrillation (AF). Methods This study included participants from the UK Biobank who were free of AF or pregnancy at baseline and completed the first and second assessments of BRI, VAI, and METS-VF. The changes in BRI, VAI, and METS-VF were classified using K-means clustering analyses, and the cumulative adiposity indices were also calculated. The primary outcome was new-onset AF. Three Cox regression models were employed to investigate the longitudinal associations of the BRI, VAI, and METS-VF changes with the risk of incident new-onset AF. The results were presented as hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). Restricted cubic spline analyses were performed to explore potential non-linear associations between baseline or cumulative adiposity indices and the risk of new-onset AF. C-index analyses were conducted to evaluate the predictive value of BRI, VAI, and METS-VF for new-onset AF. Subgroup analyses were performed according to age, gender, race, smoking status, alcohol consumption, and physical activity. Polygenic risk scores were applied to account for genetic susceptibility and investigate potential interactions between adiposity indices and genetic risk. Univariate linear regression analyses were performed to evaluate the relationships of cumulative adiposity indices and magnetic resonance imaging and dual X-ray absorptiometry parameters, including visceral adipose tissue (VAT) volume, VAT mass, trunk fat volume, and trunk fat mass. We further applied the eXtreme Gradient Boosting (XGBoost) algorithm, with the feature importance being measured to evaluate the predictive value of each adiposity index for imaging parameters. Mendelian randomization analysis was further conducted to investigate the potential causal relationship between trunk fat mass and AF. Results A total of 12 776 participants were included. Over a median follow-up of 9.60 years, 761 (5.96%) new-onset AF events were recorded. Participants were divided into four classes based on the changes in adiposity indices. In the fully adjusted model, compared to participants in Class 1 of BRI, those in Class 3 (HR＝1.30, 95%CI 1.04-1.63, P＝0.023) and Class 4 (HR＝2.17, 95%CI 1.61-2.93, P＜0.001) were associated with significantly higher risks of new-onset AF. Regarding METS-VF, participants in Class 4 of METS-VF also demonstrated a significantly higher risk of new-onset AF compared to those in Class 1 (HR＝1.66, 95%CI 1.15-2.39, P＝0.007). However, no significant association was observed between different classes of VAI and the risk of new-onset AF. For every 1 standard deviation increase in cumulative BRI, VAI, and METS-VF, the fully adjusted HRs of new-onset AF were 1.23 (95%CI 1.13-1.35), 1.02 (95%CI 0.94-1.10), and 1.23 (95%CI 1.12-1.35), respectively. Cumulative adiposity indices (BRI, VAI, and METS-VF) were divided into quartiles. Using the first quartile as reference, participants in the highest quartiles of BRI (HR＝1.40, 95%CI 1.10-1.79, P＝0.007) and METS-VF (HR＝1.44, 95%CI 1.13-1.83, P＝0.003) both exerted a significantly higher risk of new-onset AF. Regarding VAI, no significant association was observed (HR＝1.00, 95%CI 0.81-1.23, P＝0.988). Restricted cubic spline analyses revealed non-linear relationships between cumulative BRI, baseline/cumulative VAI, and baseline/cumulative METS-VF with new-onset AF risk (all P_overall＜0.05, P_non-linear＜0.05). In the C-index analysis, BRI demonstrated the highest predictive performance for new-onset AF, followed by METS-VF and VAI. Subgroup analysis indicated a stronger association between METS-VF and the risk of new-onset AF amongst participants younger than 60 years (P_interaction＝0.008). Polygenic risk score analysis stratified by genetic risk demonstrated a synergistic effect between BRI and genetic risk with new-onset AF, with the overall risk of new-onset AF increasing as both BRI and genetic risk increased. Linear regression analysis revealed a positive correlation between cumulative BRI with VAT volume, VAT mass, trunk fat volume, and trunk fat mass. The feature importance plot derived from the XGBoost algorithm indicated that cumulative BRI had the greatest predictive value on VAT volume, VAT mass, trunk fat volume, and trunk fat mass. Mendelian randomization analysis confirmed a significant causal relationship between trunk fat mass and AF. Conclusions There are significant non-linear associations between BRI, METS-VF, and VAI with new-onset AF. Higher BRI and METS-VF are significantly associated with a higher risk of new-onset AF, whereas no significant association is observed for the VAI. BRI exhibits a positive correlation with VAT and trunk fat, and demonstrates superior performance in predicting new-onset AF compared to VAI and METS-VF. Monitoring and managing BRI may be important in the early detection and intervention of AF.

BACKGROUND: Pulmonary arterial hypertension (PAH) presents a significant health burden in Asia and remains a critical challenge. This study aims to delineate the PAH burden in Asia from 1990 to 2021. METHODS: Using the latest data from the Global Burden of Disease 2021, we evaluated and analyzed the distributions and patterns of PAH disease burden among various age groups, sexes, regions, and countries in Asia. Additionally, we examined the associations between PAH disease burden and key health system indicators, including the socio-demographic index (SDI) and the universal health coverage (UHC) index. RESULTS: In 2021, there were 25,989 new PAH cases, 103,382 existing cases, 13,909 PAH-associated deaths, and 385,755 DALYs attributed to PAH in Asia, which accounted for approximately 60% of global PAH cases. The age-standardized rates (ASRs) for prevalence and deaths were 2.05 (95% uncertainty interval [UI]: 1.66-2.52) per 100,000 population and 0.31 (95% UI: 0.23-0.38) per 100,000 population, respectively. From 1990 to 2021, Asia reported the lowest ASRs for PAH prevalence but the highest ASRs for deaths compared to other continents. While the ASRs for prevalence increased slightly, ASRs for mortality and DALYs decreased over time. This increasing burden of PAH was primarily driven by population growth and aging. The burden was especially pronounced among individuals aged ≥60 years and <9 years, who collectively accounted for the majority of deaths and DALYs. Moreover, higher SDI and UHC levels were linked to reduced incidence, but higher prevalence rates. CONCLUSIONS Although progress has been made in reducing PAH-related mortality and DALYs, the disease continues to impose a substantial burden in Asia, particularly among older adults and young children. Region-specific health policies should focus on improving early diagnosis, expanding access to treatment, and effectively addressing the growing PAH burden in the region.
Humans ; Global Burden of Disease ; Male ; Female ; Middle Aged ; Adult ; Asia/epidemiology* ; Prevalence ; Aged ; Pulmonary Arterial Hypertension/mortality* ; Adolescent ; Young Adult ; Child ; Child, Preschool ; Infant ; Hypertension, Pulmonary/epidemiology*

BACKGROUND: Treatment with chimeric antigen receptor-T (CAR-T) cells has shown promising effectiveness in patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL), although the process of preparing for this therapy usually takes a long time. We have recently created CD19 Fast-CAR-T (F-CAR-T) cells, which can be produced within a single day. The objective of this study was to evaluate and contrast the effectiveness and safety of CD19 F-CAR-T cells with those of CD19 conventional CAR-T cells in the management of R/R B-ALL. METHODS: A multicenter, retrospective analysis of the clinical data of 44 patients with R/R B-ALL was conducted. Overall, 23 patients were administered with innovative CD19 F-CAR-T cells (F-CAR-T group), whereas 21 patients were given CD19 conventional CAR-T cells (C-CAR-T group). We compared the rates of complete remission (CR), minimal residual disease (MRD)-negative CR, leukemia-free survival (LFS), overall survival (OS), and the incidence of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) between the two groups. RESULTS: Compared with the C-CAR-T group, the F-CAR-T group had significantly higher CR and MRD-negative rates (95.7% and 91.3%, respectively; 71.4% and 66.7%, respectively; P = 0.036 and P = 0.044). No significant differences were observed in the 1-year or 2-year LFS or OS rates between the two groups: the 1-year and 2-year LFS for the F-CAR-T group vs.C-CAR-T group were 47.8% and 43.5% vs. 38.1% and 23.8% (P = 0.384 and P = 0.216), while the 1-year and 2-year OS rates were 65.2% and 56.5% vs. 52.4% and 47.6% (P = 0.395 and P = 0.540). Additionally, among CR patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) following CAR-T-cell therapy, there were no significant differences in the 1-year or 2-year LFS or OS rates: 57.1% and 50.0% vs. 47.8% and 34.8% (P = 0.506 and P = 0.356), 64.3% and 57.1% vs. 65.2% and 56.5% (P = 0.985 and P = 0.883), respectively. The incidence of CRS was greater in the F-CAR-T group (91.3%) than in the C-CAR-T group (66.7%) (P = 0.044). The incidence of ICANS was also greater in the F-CAR-T group (30.4%) than in the C-CAR-T group (9.5%) (P = 0.085), but no treatment-related deaths occurred in the two groups. CONCLUSION Compared with C-CAR-T-cell therapy, F-CAR-T-cell therapy has a superior remission rate but also leads to a tolerably increased incidence of CRS/ICANS. Further research is needed to explore the function of allo-HSCT as an intermediary therapy after CAR-T-cell therapy.

Eucommiae Cortex, the dried bark of Eucommia ulmoides( Eucommiaceae), has both medicinal and edible values.Modern research has shown that Eucommiae Cortex contains various components such as flavonoids, lignans, iridoids, phenolic acids,terpenoids, and steroids, which have anti-osteoporosis, antioxidant, anti-inflammatory, blood glucose-lowering, and gastrointestinal tract-protecting effects. Eucommiae Cortex has applications in multiple fields such as healthcare, industry, and animal husbandry,demonstrating broad development prospects. This article reviews the chemical constituents, pharmacological effects, and quality control status of Eucommiae Cortex. Furthermore, according to the concept of quality marker(Q-marker), this article predicts the Q-markers of Eucommiae Cortex from traditional medicinal properties, traditional medicinal effects, new medicinal effects, measurability of chemical components, compatibility, harvesting periods, and geographical origins. The components such as pinoresinol diglucoside,chlorogenic acid, caffeic acid, quercetin, baicalein, baicalin, olivil, coniferyl ferulate, and kaempferol can be used as Q-markers for Eucommiae Cortex, which provide reference for establishing a systematic quality control system for Eucommiae Cortex.
Eucommiaceae/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Quality Control ; Humans ; Animals