Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

BackgroundMany studies have shown that patients with depressive disorder show impairments in prospective memory， while it is deemed necessary for facilitating their social reintegration， and the current research findings are inconsistent regarding the factors affecting prospective memory of patients with depressive disorder. ObjectiveTo explore the impact of target characteristics （emotional valence and salience） on prospective memory in patients with depressive disorder， so as to provide references for the training and recovery of prospective memory function in these patients. MethodsFrom January to December 2022， 53 patients with depressive disorder were recruited from the outpatient department of Inner Mongolia Autonomous Mental Health Center. Meanwhile， 45 healthy individuals were concurrently recruited from surrounding communities as control group. An experiment with a 2 （participant type： depressive disorder， healthy control） ×2 （target salience： salient， non-salient） ×3 （emotional valence： positive， neutral， negative） factorial design was conducted. The positive/neutral/negative emotional pictures from Chinese Affective Picture System （CAPS） were used for emotional stimulation. A dual-task experimental paradigm was adopted， and the response time and accuracy in prospective memory task and ongoing task were recorded for participants with different target characteristics. Results①In the prospective memory task， the main effect of participant type was statistically significant， with the depressive group showing lower accuracy （F=14.892， P<0.01） and longer response time （F=10.642， P=0.002） compared with control group. ② The main effect of target emotional valence on accuracy （F=7.575， P=0.001） and response time （F=3.196， P=0.044） in the prospective memory task was statistically significant. Simple effect analysis revealed that depressive group yielded a shorter response time and higher accuracy rate under negative conditions compared with positive and neutral conditions （P<0.05 or 0.01）. ③ The main effect of target salience on accuracy （F=6.659， P=0.012） and response time （F=10.106， P=0.002） in the prospective memory task was also statistically significant， with higher accuracy and shorter response time for salient targets compared with non-salient targets. ConclusionPatients with depressive disorder demonstrate preferential attention to and processing of negative stimuli in prospective memory tasks， while increasing target salience may facilitate spontaneous processing of prospective memory task in patients with depressive disorder. ［Funded by Inner Mongolia Health Commission Medical Health Science and Technology Project （number， 202202104）］

As a chronic and lifelong disease， diabetes mellitus occurs across all age groups and gender groups. Since the disease requires lifelong treatment， it seriously affects the quality of life of patients. With the rising incidence on a global scale， diabetes mellitus has become a global problem that seriously affects public health. Moreover， the complications of this disease have aroused concern from the global medical research community， the World Health Organization， and the public. In the past， Western medicine was used in the clinical treatment of diabetes mellitus， which， however， had drug dependence， unsatisfactory efficacy， and side effects. Long-term oral administration of antidiabetics may cause liver and kidney function damage， hypoglycemia and other adverse symptoms. The treatment of diabetes mellitus has been faced with challenges such as limited efficacy and obvious side effects. Therefore， exploring more effective treatment means， especially tapping the potential of traditional Chinese medicine （TCM） in the treatment of diabetes mellitus， is a major issue to be solved. TCM has shown a great application value and a broad prospect in the treatment of diabetes mellitus because of multi-target regulation， a holistic view， synergistic effects， and high safety. TCM has a history of thousands of years in the prevention and treatment of diabetes mellitus， with rich experience accumulated and remarkable results achieved. Particularly， TCM demonstrates definite therapeutic effects on the complications. The application of TCM in the treatment of complications has been recognized and accepted by patients because of the definite therapeutic effect. In recent years， great progress has been achieved in the treatment of diabetes mellitus by the combination of Chinese and western medicine， which has made important contributions to the control of diabetes mellitus. This paper reviews the articles about the treatment of diabetes mellitus with TCM classic prescriptions， summarizes the treatment of clinical cases regarding the indications of these prescriptions， and provides an overview of the treatment mechanisms， aiming to offer fresh insights and strategies for the clinical diagnosis and treatment of diabetes mellitus.

OBJECTIVE To design and synthesize mono-carbonyl curcumin analogues（MCACs） and investigate the activities of them against breast cancer. METHODS The analogues F1， F2， and F3 were obtained by aldol condensation reaction， and their antitumor activities（including the activities of human breast cancer cell MCF-7 and human lung cancer cell A549） were detected by MTT assay [evaluated with half inhibitory concentration（IC50）]. The results of MTT assay were compared with those of curcumin. Bioinformatics methods were used to collect the core targets of analogues F1， F2 and F3 acting on breast cancer， and then molecular docking verification was carried out. The cell experiments were conducted to investigate the effects of high， medium and low concentrations （16， 8， 4 μmol/L） of F1， F2 and F3 on the expression of the first core target protein as well as the effects of medium concentration of F1， F2 and F3 on the expression of cleaved-caspase-3. RESULTS Compared with curcumin， IC50 of analogues F1， F2 and F3 to A549 and MCF-7 cells（except for IC50 of analogue F2 to A549 cells） were decreased significantly（P＜ 0.05 or P＜0.01）； among them， IC50 of analogue F2 to MCF-7 cell was the lowest， being（9.67±1.27） μmol/L. Bioinformatics analysis showed that index of affinity of analogues F1， F2 and F3 with the first core target epidermal growth factor receptor （EGFR）， protein kinase B （AKT） and AKT were 5.909 2， 8.402 5 and 6.486 6， respectively； high concentration of F1 could significantly reduce the phosphorylation level of EGFR protein in MCF-7 cells（P＜0.01）， while low， medium， and high concentrations of F2 and high concentration of F3 could significantly reduce the phosphorylation level of AKT protein in MCF-7 cells（P＜0.05 or P＜0.01）. Medium concentration of F1， F2， and F3 could significantly increase the expression level of cleaved- caspase-3 protein in MCF-7 cells（P＜0.01）. CONCLUSIONS Designed and synthesized MCACs F1， F2 and F3 all have good anti- breast cancer activity， and F2 has better anti-breast cancer activity.

BACKGROUND:The biomechanical analysis of scoliosis cases is limited,with only independent analysis focusing on the spine or lower limbs,thus lacking a comprehensive evaluation of the multidimensional body.As a result,it becomes challenging to reflect the movement relationship between the trunk and lower limbs during daily activities,which hinders comprehensive clinical treatment guidance. OBJECTIVE:To explore the relationship between different segments of the spine and the kinematics/kinetics of the lower limbs during gait activities by measuring spinal kinematics in scoliosis patients,to provide a comprehensive and multi-level assessment of the biomechanical differences between scoliosis patients and the normal population,consequently offering evidence-based guidance for the prevention and treatment of scoliosis. METHODS:A cross-sectional study was conducted from July 2020 to June 2021 at the Rehabilitation Hospital Affiliated to Fujian University of Traditional Chinese Medicine in Fuzhou University City.A total of 28 scoliosis patients and 28 normal individuals in the same age group were included.Three-dimensional motion capture system was used to capture gait kinematic data at a sampling frequency of 100 Hz.Two force plates(AMTI 400600,sampling frequency 1 500 Hz)were embedded in a 10-meter-long 2.4-meter-wide level ground walkway(with an effective data collection length of 4 m)to collect kinetic data.The differences in spatial-temporal parameters,kinematics,and kinetics of gait between the two groups were compared.Immediately after inclusion,all subjects underwent full spinal X-ray measurements to compare the differences between the scoliosis and normal groups. RESULTS AND CONCLUSION:(1)Patients with scoliosis exhibited reduced relative rotational range of motion between the shoulder and trunk,as well as between the thorax and pelvis,compared to the normal group(P<0.05).However,the rotational range of motion in the pelvis was larger in patients with scoliosis compared to the normal group(P<0.05).(2)Patients with scoliosis showed decreased range of motion in the hip and knee joints,as well as reduced peak torque in hip joint flexion and extension,and lower peak values of ground reaction forces in the concave and convex directions,in comparison to the normal group(P<0.05).(3)Patients with scoliosis demonstrated greater asymmetry indices in knee joint range of motion,relative rotational range of motion between the shoulder and trunk,and between the thorax and pelvis,when compared to the normal group(P<0.05).(4)These findings illustrate a rigid movement pattern among the shoulder,thorax,and pelvis in patients with scoliosis during level walking.There is a reduction in range of motion in the hip and knee joints,as well as decreased peak torque values in hip joint flexion and extension,and ground reaction forces in the concave and convex directions.These characteristics can serve as foundational elements for assessing rehabilitation and developing treatment plans.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Background/Aims: Reflux symptoms frequently present in patients diagnosed with functional dyspepsia (FD). This investigation sought to elucidate the contribution of gastroesophageal reflux in the overlap relationship. Methods: Consecutive patients presenting with reflux symptoms and/or FD symptoms were prospectively included. Comprehensive assessments, including symptoms evaluation, endoscopy, esophageal functional examinations (high-resolution manometry and reflux monitoring), and proton pump inhibitor (PPI) treatment efficacy evaluation, were conducted in these patients. Results: The study enrolled 315 patients, 43.2% of which had concurrent FD symptoms and overlapping reflux symptoms. Notably, a mere 28.7% of patients in the overlap symptoms group had objective gastroesophageal reflux disease evidences (the grade of esophagitis≥ B or the acid exposure time ≥ 4.2%). Functional heartburn was demonstrated to be the main cause of overlapping reflux symptoms(55.1%). Reflux parameters analysis revealed that the reflux burden in the overlap symptoms group paralleled that of the FD symptoms group, with both registering lower levels than the reflux symptoms group (P < 0.05). Furthermore, PPI response rates were notably diminished in the overlap symptoms group (P < 0.001), even for those with objective gastroesophageal reflux disease evidences. Conclusions The study illuminated that overlapping reflux symptoms in FD was common. Strikingly, these symptoms primarily diverged from reflux etiology and exhibited suboptimal responses to PPI intervention. These findings challenge prevailing paradigms and accentuate the imperative for nuanced therapeutic approaches tailored to the distinctive characteristics of overlapping reflux symptoms in the context of FD.

ObjectiveTo determine the optimal combination of the effective monomer components "quercetin-kaempferol-abietic acid-boswellic acid" in Fujin Shengjisan for promoting diabetic ulcer （DU） wound healing through uniform design， thereby achieving the modern application of the ancient formula. MethodsFollowing the principle of "uniform design-pharmacodynamic experiment-mathematical modeling and model verification"， the U₁₄（14⁵） uniform design table was adopted.The four monomer components of Chinese medicine were considered as the independent variables， and the proliferation rate of human umbilical vein endothelial cells （HUVECs） induced by glucose was used as the pharmacodynamic indicator. A mathematical model was constructed using DPS software to correlate the effective monomer components with the pharmacodynamic indicator. The results of uniform design were verified through CCK-8 assay， cell scratch healing， tube formation， Western blot， and Real-time PCR. ResultsAmong the 14 compatibility groups， compared with the high-glucose model group， compound compatibility group 6 showed the strongest proliferation effect and statistical significance （P<0.05）. Four quadratic polynomial regression equations （Y₁-Y₄） were obtained through DPS modeling. Considering the model's fit， stability， and practical application， equations Y₁-Y₃ were selected for the follow-up verification. To ensure experiment reproducibility， group 6 was used for validation. Group 6 and equations Y₁-Y₃ were renamed as compound prescription ① to compound prescription④， respectively， to represent the modern application of the ancient FJSJ Powder through compatibility of monomer components. Verification experiments showed that in the CCK-8， scratch healing， and tube formation assays， the cell viability， wound healing rate， and tube formation number of HUVECs stimulated with 50 mmol·L^-1 glucose were significantly reduced compared with the blank group. Moreover， the expression levels of angiogenesis-related cytokines， vascular endothelial growth factor （VEGF） and fibroblast growth factor 2 （FGF2）， and CD31 secretion were significantly down-regulated. However， after intervention with compound prescriptions ① to ④， compound prescriptions ① and ③ significantly improved the biological functions of HUVECs induced by 50 mmol·L^-1 glucose. Further analysis of the regression coefficients of compound prescriptions ① and ③， and the relative dose ratios of each monomer component， indicated that abietic acid， quercetin， and boswellic acid promoted angiogenesis of HUVECs in the high glucose environment， with a major effect （positive partial correlation coefficients， all > 0.9）. Abietic acid and boswellic acid， as well as kaempferol and boswellic acid， promoted angiogenesis in HUVECs through interaction （positive partial correlation coefficients）. ConclusionCompound prescriptions ① and ③ are the optimal combinations. They can reverse the inhibitory effects of high glucose， stimulate the proliferation， migration， and tube formation abilities of HUVECs in a high glucose environment， and promote the expression of vascular endothelial growth factorA（VEGFA）， FGF2， and CD31， thereby promoting angiogenesis and facilitating DU wound healing. This finding not only confirms the good reproducibility and feasibility of compound prescriptions ① and ③ but also provides new insights and methods for the rational construction of mathematical models to further study the compatibility theory of Chinese medicine.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.