Sarcopenia is a clinical syndrome characterized by a decrease in skeletal muscle strength and quality， often accompanied by adverse outcomes such as falls， loss of function and weakness. The pathogenesis of sarcopenia is complex， and studies have shown that dysfunction due to impaired mitochondrial quality control is an important pathological factor in the occurrence and development. Traditional Chinese medicine（TCM） has been widely favoured for regulating mitochondrial homeostasis and preventing sarcopenia by virtue of its multi-target and multi-pathway advantages. They can play a role in the prevention and treatment of sarcopenia by regulating the mitochondrial quality control system to inhibit the occurrence of mitochondrial oxidative stress， regulate the balance of mitochondrial dynamics， inhibit mitochondrial autophagy， promote mitochondrial biosynthesis， resist the occurrence of mitochondrial apoptosis， and maintain the mitochondrial calcium and protein homeostasis. Based on this， the paper reviewed the relationship between mitochondrial quality control and sarcopenia， as well as the mechanism of TCM in intervening the mitochondrial quality control system to treat sarcopenia， in order to provide a new idea for the prevention and treatment of sarcopenia by TCM and to a theoretical basis for the clinical research on TCM intervention in sarcopenia.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Neuronal reprogramming is an innovative technique for converting non-neuronal somatic cells into neurons that can be used to replace lost or damaged neurons, providing a potential effective therapeutic strategy for central nervous system (CNS) injuries or diseases. Transcription factors have been used to induce neuronal reprogramming, while their reprogramming efficiency is relatively low, and the introduction of exogenous genes may result in host gene instability or induce gene mutation. Therefore, their future clinical application may be hindered by these safety concerns. Compared with transcription factors, small-molecule compounds have unique advantages in the field of neuronal reprogramming, which can overcome many limitations of traditional transcription factor-induced neuronal reprogramming. Here, we review the recent progress in the research of small-molecule compound-mediated neuronal reprogramming and its application in CNS regeneration and repair.
Humans ; Cellular Reprogramming/drug effects* ; Neurons/cytology* ; Animals ; Transcription Factors ; Small Molecule Libraries/pharmacology* ; Nerve Regeneration

Analyzing the spatial distribution pattern and formation factors of medicinal plant resources can provide a scientific basis for the protection and development of traditional Chinese medicine(TCM) resources. This study is based on the survey data of medicinal plant resources in 104 county-level administrative regions of Anhui province in the Fourth National Survey of TCM Resources. The global spatial autocorrelation analysis, trend surface analysis, local spatial autocorrelation analysis, hotspot analysis, and a geodetector were employed to analyze the spatial distribution pattern of medicinal plant richness, and its relationship with natural factors was explored. The results can provide a basis for the formulation of development strategies such as the protection and utilization of TCM resources, as well as offer a scientific foundation for the establishment of regional planning schemes for TCM resources in Anhui province. The results indicated that the richness of medicinal plant resources in Anhui province had significant spatial heterogeneity, exhibiting highly clustered distribution characteristics. Cold spots and hot spots presented clustered distribution patterns, with cold spots mostly located north of the Huaihe River and hot spots south of the Yangtze River. Overall, the distribution of medicinal plant resources in Anhui province showed an overall trend of high in the south and low in the north, which was consistent with the overall geomorphic trend of this province. In addition, natural factors such as altitude, precipitation, and vegetation type played an important role in the diversity and spatial distribution pattern formation of medicinal plant resources. The extraction and analysis of the spatial distribution characteristics of natural factors in cold and hot spot regions discovered that the heterogeneity of eco-environments constituted a fundamental condition for the formation of species diversity.
Plants, Medicinal/classification* ; China ; Spatial Analysis ; Conservation of Natural Resources ; Biodiversity

To improve the quality evaluation system of Hibisci Mutabilis Folium, this study established high performance liquid chromatography(HPLC) fingerprints of Hibisci Mutabilis Folium and evaluated the quality differences of medicinal materials from different places of production by chemometrics. Furthermore, a content measurement method of differential components was established based on quantitative analysis of multi-components by single-marker(QAMS). The fingerprints of 17 batches of Hibisci Mutabilis Folium from different places of production were constructed, with a total of 19 common peaks marked and seven components confirmed. The similarity between the sample fingerprints and the reference fingerprints ranged from 0.890 to 0.974. By utilizing principal component analysis(PCA), hierarchical cluster analysis(HCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA), the chemical patterns of fingerprints were identified. Five components that could be used to evaluate the quality differences of Hibisci Mutabilis Folium were screened, namely peak 6(quercetin 3-O-β-robinobioside), peak 7(rutin), peak 9(kaempferol-3-O-β-robinobioside), peak 10(kaempferol-3-O-rutinoside), and peak 14(tiliroside). The relative correction factors of isoquercitrin, kaempferol-3-O-β-robinobioside, kaempferol-3-O-rutinoside, kaempferol-3-O-β-D-glucoside, and tiliroside were measured with rutin as the internal reference. The QAMS method was established for the content measurement of six flavonoids, and the results showed there was no significant difference compared to the results obtained by an external standard method. In summary, the HPLC fingerprints and QAMS method established in the study, demonstrating stability and accuracy, can provide a reference for the overall quality evaluation of Hibisci Mutabilis Folium.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Principal Component Analysis