Diabetic retinopathy(DR)remains the leading cause of vision loss in patients with diabetes. Current anti-vascular endothelial growth factor(VEGF)therapies are limited by inadequate response in some patients and the necessity for repeated intravitreal injections, underscoring the urgent need for novel therapeutic targets. Angiopoietin-like protein 4(ANGPTL4), a multifunctional secreted protein, has emerged as a critical regulator in the pathogenesis and progression of DR, positioning it as a promising interventional target. This review systematically elaborates the biological characteristics of ANGPTL4, with a focus on its expression dynamics, molecular mechanisms, and regulatory networks rolesin the development of DR. Furthermore, the prospects of ANGPTL4-targeted therapeutic strategies are discussed, aiming to offer new insights and directions for understanding DR pathogenesis, advancing multi-target drug development, and improving clinical management.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Objective: To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students. Methods: From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model. Results: The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms. Conclusions The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.

ObjectiveTo observe the clinical efficacy and safety of Huatan Quyu formula in treating cerebral small vessel disease （CSVD） with phlegm and blood stasis blocking collateral pattern via randomized controlled trial， and explore its mechanism of improving CSVD by regulating glymphatic system （GS） circulation. MethodsSixty-eight CSVD patients with phlegm and blood stasis blocking collateral pattern in the Department of Encephalopathy， Affiliated Hospital of Shaanxi University of Chinese Medicine from April to December 2024 were selected and randomly divided into an experimental group （34 cases） and a control group， with 34 cases in each group. Both groups received basic Western medicine treatment， while the experimental group additionally received Huatan Quyu formula. After a course of 12 weeks， the following parameters were compared between the two groups before and after treatment. Clinical outcomes were assessed using the Tinetti performance-oriented mobility assessment （POMA）， Montreal Cognitive Assessment （MoCA）， Scales for Outcomes in Parkinson's Disease-Autonomic （SCOPA-AUT）， and traditional Chinese medicine （TCM） syndrome scores of phlegm and blood stasis blocking collateral pattern. Perivascular space （PVS） in the frontal lobe/basal ganglia and cerebrospinal fluid （CSF） flow parameters in the cerebral aqueduct were evaluated by 3.0T brain MRI， cerebrospinal fluid flow imaging， and phase-contrast magnetic resonance imaging （PC-MRI）. Then， safety indicators were monitored， and SPSS 25.0 was used for statistical analysis. ResultsSixty-four patients completed the study （32 in each group）. ①Baseline data： No statistically significant difference was found between the two group. ②Efficacy indicators： After treatment， the experimental group exhibited significantly improved total POMA， SCOPA-AUT， and TCM syndrome scores （P<0.01）， outperforming the control group （P<0.05）. No significant change was observed in MoCA scores between the two groups. ③Imaging indicators： The experimental group showed a reduced PVS area alongside significantly increased CSF flow parameters （including downward flow during the systolic period， and upward flow during the diastolic period） （P<0.01）， which were superior to the control group （P<0.01）. ④Safety： The laboratory indicators were normal in both groups， with no drug-related adverse reactions. ConclusionFor CSVD patients with phlegm and blood stasis blocking collateral pattern， Huatan Quyu formula can safely and effectively improve motor function， autonomic nerve function， and TCM syndromes， with potential mechanisms related to pulsatile CSF flow enhancement and GS circulation efficiency improvement.

Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

Lung transplantation is a definitive treatment for end-stage lung disease and can significantly improve patient prognosis. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury and chronic lung allograft dysfunction intertwine to form a complex pathological network, posing persistent challenges to long-term patient survival. In 2025, research teams worldwide have made systematic progress in the field of basic lung transplantation research. By integrating cutting-edge technologies including single-cell multi-omics, spatial transcriptomics and novel animal models, significant breakthroughs have been achieved in the evolutionary dynamics of drug-resistant infections, molecular mechanisms of immune regulation, programmed cell death, optimization of donor lung protection strategies and early warning of chronic lung allograft dysfunction. This article systematically reviews the representative advances in basic lung transplantation research worldwide in 2025, and deeply analyzes the implications of mechanistic breakthroughs for optimizing diagnosis and treatment strategies, aiming to anchor the direction for innovative breakthroughs and clinical translation in basic lung transplantation research.

ObjectiveTo explore the clinical efficacy of Juanbitang hot compress pack combined with intensive rehabilitation training in stroke patients with hemiplegia. MethodsA total of 80 stroke patients with hemiplegia were selected and assigned into a control group （40 cases） and an observation group （40 cases） according to the random number table method. The control group received conventional rehabilitation training and nursing intervention，while the observation group was additionally treated with Juanbitang hot compress pack. The two groups were compared in terms of the neurological function （national institute of health stroke scale score，NIHSS score），muscle strength，motor function （fugl-meyer assessment scale score，FMA score），daily living activity （modified barthel index，MBI），balance ability （berg balance scale score，BBS score），trunk control ability （Sheikh Trunk Control Test score，Sheikh TCT score），and homocysteine （Hcy） level before and after treatment. ResultsAfter treatment，the observation group had lower NIHSS score and Hcy level than the control group （P<0.05）. The total response rate of the observation group （97.50%） was higher than that of the control group （77.50%）. The scores of upper limb and lower limb FMA，MBI，BBS，and Sheikh TCT in the observation group were all higher than those in the control group （P<0.05）. ConclusionThe application of Juanbitang hot compress pack combined with rehabilitation training can effectively improve the neurological function，muscle strength，motor function，daily living ability，balance ability，and trunk control ability and reduce the Hcy level in stroke patients with hemiplegia，demonstrating enhanced clinical efficacy.

OBJECTIVE To optimize the preparation process of Pollen Typhae dripping pills.METHODS Using appearance morphology， roundness， tailing phenomenon， adhesion condition， friability， and total flavonoids content of Pollen Typhae as evaluation indicators， the analytic hierarchy process-entropy weight method （AHP-EWM） hybrid weighting method was employed to determine the weight coefficients of each indicator and calculate the comprehensive score as the response value. The effects of matrix type and ratio， drug-to-matrix ratio， and condensation temperature on the forming process of dripping pills were respectively investigated， through single-factor experiments and Box-Behnken response surface methodology and the optimal process was optimized and validated. The cumulative dissolution rate of Pollen Typhae dripping pills within 150 min was determined and compared with that of total flavonoid extract from Pollen Typhae .RESULTS The optimal preparation process for Pollen Typhae dripping pills was determined as follows： the ratio of PEG4000 to PEG6000 was 2∶1， the drug-to-matrix ratio was 1∶2， and the condensation temperature was 17.5 ℃. The measured average comprehensive score of dripping pills prepared under these conditions was 9.208 （RSD＝0.91%， n ＝3）， with a relative error of 0.83% compared to the predicted value of 9.285. The release mechanism of Pollen Typhae dripping pills was Fickian diffusion controlled deceleration release. The initial dissolution rate was fast， and the dissolution rate decreased in the middle and later stages. The total flavonoid extract from Pollen Typhae was released rapidly in the initial dissolution stage and quickly entered the plateau phase. Their maximum dissolution rates were 95.96% and 84.07%， respectively.CONCLUSIONS The optimized preparation process for Pollen Typhae dripping pills was stable and reliable. The dissolution rate of Pollen Typhae dripping pills prepared by optimized process was higher than that of the total flavonoid extract from Pollen Typhae .

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

This study identified 8 members including NjBIN2 of the GSK3 family in Nardostachys jatamansi by bioinformatics analysis. Moreover, the phylogenetic tree revealed that the GKS3 family members of N. jatamansi had a close relationship with those of Arabidopsis. RT-qPCR results showed that NjBIN2 presented a tissue-specific expression pattern with the highest expression in roots, suggesting that NjBIN2 played a role in root growth and development. In addition, the application of epibrassinolide or the brassinosteroid(BR) synthesis inhibitor(brassinazole) altered the expression pattern of NjBIN2 and influenced the photomorphogenesis(cotyledon opening) and root development of N. jatamansi, which provided direct evidence about the functions of NjBIN2. In conclusion, this study highlights the roles of BIN2 in regulating the growth and development of N. jatamansi by analyzing the expression pattern and biological function of NjBIN2. It not only enriches the understanding about the regulatory mechanism of the growth and development of N. jatamansi but also provides a theoretical basis and potential gene targets for molecular breeding of N. jatamansi with improved quality in the future.
Brassinosteroids/metabolism* ; Steroids, Heterocyclic/metabolism* ; Gene Expression Regulation, Plant/drug effects* ; Plant Proteins/metabolism* ; Phylogeny ; Nardostachys/metabolism* ; Plant Growth Regulators/pharmacology* ; Plant Roots/drug effects*