1.Exploring Chemical Constituent Distribution in Blood/Brain(Hippocampus) and Emotional Regulatory Effect of Raw and Vinegar-processed Products of Citri Reticulatae Pericarpium Viride
Yi BAO ; Yonggui SONG ; Qianmin LI ; Zhifu AI ; Genhua ZHU ; Ming YANG ; Huanhua XU ; Qin ZHENG ; Yiting HUANG ; Zihan GAO ; Dan SU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(2):189-197
ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride(CRPV), and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS) was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts, as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards, databases, and relevant literature were utilized for compound annotation, with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups, including the blank group, model group, diazepam group(2.5 mg·kg-1), raw CRPV low/high dose groups(0.6, 1.2 g·kg-1), and vinegar-processed CRPV low/high dose groups(0.6, 1.2 g·kg-1), with 10 mice per group. Except for the blank group, all other groups underwent chronic restraint stress(2 h·d-1) for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling, with a total treatment duration of 10 d. Following model-based drug administration, mice underwent open-field, forced swimming, and elevated plus maze tests. After anesthesia with isoflurane, whole brains were collected from each group of mice, and hippocampi were dissected. Reactive oxygen species(ROS) level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay(ELISA). Hematoxylin-eosin(HE) staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei(NeuN) and peroxisome proliferator-activated receptor alpha(PPARα) expressions in hippocampal tissue. Then, pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders, exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV, with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds, including 20 flavonoids, 20 flavonoid glycosides, 3 triterpenes, 3 phenolic acids, 1 alkaloid, and 6 other compounds. Twenty-one components were detected in blood(15 methoxyflavones, 4 flavonoid glycosides, and 2 phenolic acids), with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues(all common to both forms). In regulating emotional disorders, Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology, particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS(P<0.05). ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing, but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway, thereby negatively regulating ROS generation in the hippocampus, reducing oxidative stress, and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards, pharmacodynamic material research, and active drug development of raw and vinegar-processed CRPV.
2.Mechanism of KLF4 in regulating ferroptosis in diabetic nephropathy
Huanzhen ZHANG ; Zhangyong DAN ; Xiaorui SHI ; Rumeng ZHU ; Yi WANG ; Huaqing ZHU
Acta Universitatis Medicinalis Anhui 2026;61(3):509-517
ObjectiveTo investigate the role of Krüppel-like factor 4 (KLF4) in type 1 diabetic nephropathy (DN) and to elucidate its underlying mechanisms. MethodsSixteen male Sprague-Dawley (SD) rats were selected and randomly divided into control group and model group, with 8 rats in each group. Rats in model group were intraperitoneally injected with a single dose of 55 mg/kg streptozotocin (STZ) to establish a diabetic nephropathy (DN) model, while those in control group were injected with an equal volume of sodium citrate buffer at the same time. After successful model establishment, the serum levels of blood urea nitrogen (BUN) and serum creatinine (SCR) were determined. Hematoxylin-eosin (HE) staining was performed on renal tissues to observe pathological changes, and immunofluorescence staining was conducted to detect the expression of KLF4 in renal tissues. Lipid peroxidation levels were evaluated by measuring malondialdehyde (MDA), Fe²⁺, and lipid peroxidation products in rat kidneys. A high glucose (HG)-induced cell injury model was established in HK-2 cells, with mitochondrial membrane potential assessed using 5,5',6,6'-tetrachloro-1,1',3,3'- tetraethylbenzimidazolylcarbocyanine iodide (JC-1) staining. Lipid peroxidation levels (MDA, Fe²⁺, and lipid peroxides) were measured in HK-2 cells.KLF4-overexpressing HK-2 cells were then constructed, followed by repeated JC-1, MDA, Fe²⁺, and lipid peroxidation assays. Western blot was performed to evaluate the expression of ferroptosis-related proteins including glutathione peroxidase 4 (GPX4), nuclear factor erythroid 2-related factor 2 (NRF2), and Kelch-like ECH-associated protein 1 (Keap1), in renal tissues, HK-2 cells, and KLF4-overexpressing HK-2 cells. ResultsCompared with the control group, DN rats exhibited elevated serum BUN and SCR levels, glomerular hypertrophy, renal interstitial fibrosis, and decreased KLF4 expression. Additionally, MDA, Fe²⁺, and lipid peroxidation levels increased, indicating enhanced ferroptosis in renal tissues, accompanied by reduced GPX4 and NRF2 expression and elevated Keap1 levels. Similarly, HG-treated HK-2 cells showed decreased KLF4 expression, increased MDA, Fe²⁺ and lipid peroxidation, elevated ferroptosis, and dysregulated GPX4/NRF2/Keap1 expression. However, KLF4 overexpression reversed these alterations induced by high glucose treatment. ConclusionIn the renal tissues of type 1 diabetic rats, the expression of KLF4 decreases the level of ferroptosis increases, and KLF4 overexpression could alleviate HG-induced HK-2 cell injury.
3.Inverse Association Between Alcohol Consumption and Parkinson’s Disease Risk and Identification of RIT2 as a Linked Biomarker
Wei LU ; Xiu-Li CHENG ; Xiao-Yun PAN ; Dan-Dan YANG ; Hui-Ling ZOU ; Li-Guo DONG ; Yi-Liang WEI ; Gui-Yun CUI
Progress in Biochemistry and Biophysics 2026;53(6):1723-1733
ObjectiveAs a common lifestyle habit, alcohol consumption has a controversial association with the onset of Parkinson’s disease (PD). To demonstrate the correlation between alcohol consumption and PD and to identify associated genes, we integrated findings from clinical surveys, genomics, transcriptomics, and animal experiments. MethodsWe investigated the alcohol consumption rates (including both before and after disease onset) among 244 PD patients in China and 177 PD patients from the U.S. NHANES database. Mendelian randomization (MR) analysis was performed using genome-wide association study (GWAS) data for three alcohol-related traits and seven PD-related datasets from the MRC IEU OpenGWAS database. Transcriptomic data from the substantia nigra of PD patients were obtained from three GEO datasets (GSE7621, GSE20141, and GSE49036) to analyze RIT2 gene transcription. Finally, three groups of animal experiments (water/20% ethanol/20% liquor, with 4 C57BL/6J mice per group) were conducted to examine changes in brain RIT2 gene expression and transcriptomic profiles following alcohol consumption. ResultsThe alcohol consumption rates among PD patients in China and the U.S. (9%-18.87%) were significantly lower than the general population rates of 15%-45% in their respective regions (P<0.001), suggesting a possible negative association between alcohol consumption and PD. Subsequently, in 21 bidirectional MR analyses using 3 alcohol-related GWAS datasets and 7 PD-related GWAS datasets, the forward MR analyses (alcohol intake as exposure, PD as outcome) yielded 12 negative associations (ORIVW<1) and 9 positive associations (ORIVW>1). Among these, only two negative associations reached statistical significance: alcohol intake frequency (ORIVW=0.75, 95% CI: 0.60-0.93, P=0.010) and alcohol consumption (ORIVW=0.20, 95% CI: 0.05-0.83, P=0.026). The forward MR analysis (alcohol intake→PD) identified 235 SNPs, annotated to 316 genes, while the reverse MR analyses (PD→alcohol intake) identified 37 SNPs, annotated to 53 genes. Notably, only the RIT2 gene appeared in both the forward and reverse MR analyses (alcohol intake→PD: rs28597806, rs8083110; PD→alcohol intake: rs4588066). RIT2 is selectively expressed in the human brain (FPKM: 5.259±2.103), with low or no expression in peripheral tissues (FPKM: <1). Analysis of three human substantia nigra transcriptomic datasets revealed a decreasing trend in RIT2 gene expression in PD patients (GSE20141 array signal: 3.49±1.23 vs. 2.33±0.87, P=0.044). Animal experiments demonstrated that administration of 20% ethanol or 20% liquor (approximately 8% ethanol) stimulated a >2-fold upregulation of RIT2 gene expression in the mouse brain. Furthermore, transcriptomic sequencing revealed that the two alcohol-treated groups exhibited 96 (20% ethanol vs. water control) and 4 (20% liquor vs. water control) differentially expressed genes, respectively, indicating that low-dose alcohol consumption can achieve RIT2 upregulation while minimizing impact on other brain genes. In addition to its anti-infective effects, low-dose alcohol consumption primarily influences signaling pathways related to neurodegenerative diseases such as PD and Prion diseases. ConclusionAlcohol consumption is generally considered as a harmful lifestyle habit. However, some studies have also shown a lower risk of mortality among individuals who consume low doses of alcohol (100 g/week of ethanol) or drink occasionally. Currently, one of the research focuses on alcohol consumption is whether the human body can benefit from low-dose alcohol intake. This study provides new evidence supporting a negative association between alcohol consumption and PD, and for the first time, through MR analysis, identifies the RIT2 gene as a potential mediator of the effect of alcohol consumption on PD. RIT2 is selectively expressed in the human brain. Building upon existing evidence indicating downregulated RIT2 gene expression in PD pathogenesis, our experiments confirm that low-dose alcohol consumption can upregulate RIT2 expression in the brain. In brief, alcohol consumption may suppress the pathogenesis of PD by upregulating RIT2 expression in the substantia nigra. China is facing a serious problem of population aging. This study offers important insights for long-term PD prevention and treatment strategies, with the aim of benefiting more potential PD patients through lifestyle modifications, thereby improving the quality of life of the aging population and reducing the economic burden on healthcare.
4.Analysis of soil-borne nematode infection status among rural communities in Yubei, Chongqing
Dan JIANG ; Yong-dong HAO ; Sen-ping YANG ; Xiao-yuan SU ; Hua-jun BAI ; Bo LYU ; Ya-ling RAN ; He-yi GUAN ; Ling HU
Acta Parasitologica et Medica Entomologica Sinica 2026;33(2):85-89
Objective To analyze the infection status and epidemic trends of soil-borne nematode infections in Yubei, Chongqing City, in 2010,2021, and 2022. Methods The local populations from four survey sites of four towns in 2010 and five sites of five towns in 2021 and 2022 were surveyed regarding their basic information using a unified form. Fecal samples of the participants were collected and tested for soil-borne nematode infections using the modified Kato-Katz thick smear method. Results In 2010, 2 049 participants were surveyed, followed by 1 000 participants in 2021 and 2022. The overall prevalence of parasitic infections declined significantly from 3.86% to 0.20%. In 2010, soil-transmitted nematode included hookworms(3.81%) and roundworms(0.29%). In 2021, the infection rates of roundworms and hookworms were 1.70% and 0.10% respectively. Notably, only Ascaris was identified in 2022(0.20%). The≥60 age group consistently exhibited the highest infection rates across all surveys, followed by the 40-59 age group. The infection rates of males in the three surveys were 3.31%,1.92%, and 0.20% respectively, and those of females were 4.37%, 1.46%, and 0.20% respectively. There was no statistically significant difference in the infection rates between males and females. Educational attainment was inversely associated with infection; in 2010, the highest prevalence was observed among those with primary education or below, whereas in 2021, illiterate or semi-literate individuals showed the highest susceptibility. The occupational distribution of infections in 2010 indicated that retirees (8.33%), farmers(4.86%), and homemakers or unemployed individuals(3.45%)were the most affected. However, in 2021 and 2022, farmers emerged as the predominant occupational group with soil-transmitted nematode infections. Conclusions The infection rate of soil-borne nematodes showed a decreasing trend in Yubei, and the infection species changed from hookworms in 2010 to Ascaris in 2022. Farmers, the elderly, and people with low education levels should continue to be the focus of preventive and control efforts.
5.Mechanisms of Exercise Intervention in Cancer Bone Metastasis
Si-Tong YAN ; Feng-Zhi YU ; Bo-Yi ZONG ; Meng-Lu HE ; Dan-Dan JIA
Progress in Biochemistry and Biophysics 2026;53(8):2104-2122
Bone metastases are a common and serious complication of solid tumors such as breast cancer, prostate cancer, lung cancer, and kidney cancer, and occur at a high rate in patients with advanced cancer. This pathological process not only frequently leads to skeletal-related events such as severe bone pain, pathological fractures, spinal cord compression, and hypercalcemia—conditions that severely impact patients’ quality of life—but may also significantly increase the risk of death. Cancer bone metastasis is a complex, multistage cascade involving key steps such as the detachment of tumor cells from the primary tumor, their invasion and entry into the bloodstream, and their colonization, dormancy, and reactivation within the bone microenvironment. In recent years, exercise—as a safe and easily implementable non-pharmacological intervention—has demonstrated significant potential in inhibiting bone metastasis, improving the bone microenvironment, and alleviating related clinical symptoms. Its mechanisms of action may involve multiple levels. First, at the mechanical load level, mechanical signals generated by exercise can directly act on bone cells, inhibiting tumor cell infiltration and colonization by regulating endothelial cell permeability and osteoclast activity. Second, at the endocrine and paracrine levels, exercise can alter the expression profiles of microRNAs (such as miR-486 and miR-34b) carried by extracellular vesicles and particles (EVPs) in the circulation, thereby inhibiting tumor cell proliferation and migration by targeting cell cycle-related genes. Furthermore, exercise can remodel the immune microenvironment, enhance the cytotoxic activity of antitumor immune cells, and improve oxygen supply to tumor tissues, thereby alleviating hypoxia-induced immunosuppression. Finally, at the metabolic intervention level, exercise can induce systemic metabolic reprogramming, increasing the nutritional demands of normal tissues, thereby competing with tumor cells for nutrients and forming a “metabolic barrier” in distal organs such as bones. This article reviews the pathogenesis and classification of bone metastases, including osteolytic, osteogenic, and mixed types, and elaborates in detail on the complex processes by which tumor cells undergo colonization, dormancy, and reactivation within the bone microenvironment. Furthermore, based on a comprehensive analysis of human and animal studies on exercise interventions for bone metastases, this paper highlights the mechanisms by which exercise inhibits tumor formation, growth, and spread through the regulation of mechanical loading, extracellular vesicles and granules, as well as via immune and metabolic pathways, thereby interfering with bone metastasis. However, the array of exercise modalities and intensities available for patients grappling with the challenges of cancer-related bone metastases remains markedly constrained, and the formulation of tailored exercise prescriptions continues to be devoid of robust, evidence-based medical backing. This review aims to explore the effects of exercise on bone health in patients with bone metastases, analyze the factors and considerations that should be taken into account in exercise prescriptions, and provide new theoretical support and insights for developing personalized exercise programs for these patients and further advancing relevant clinical research. Future research directions should include the development of evidence-based, personalized exercise prescriptions and further clarification of the safety boundaries and best practice standards for exercise interventions, thereby promoting the advancement of relevant clinical research and ultimately improving patients’ clinical outcomes and quality of life.
6.Terms Related to The Study of Biomacromolecular Condensates
Ke RUAN ; Xiao-Feng FANG ; Dan LI ; Pi-Long LI ; Yi LIN ; Zheng WANG ; Yun-Yu SHI ; Ming-Jie ZHANG ; Hong ZHANG ; Cong LIU
Progress in Biochemistry and Biophysics 2025;52(4):1027-1035
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.
7.Novel outpatient infusion model of blinatumomab: case studies of two patients
Guijun LI ; Xuemei JIANG ; Xin WANG ; Qiuxia XU ; Jianhui LI ; Susi DAI ; Ying HE ; Hai YI ; Dan CHEN
Chinese Journal of Blood Transfusion 2025;38(4):557-561
[Objective] To evaluate the feasibility of a novel outpatient infusion model for blinatumomab in two acute lymphoblastic leukemia (ALL) patients, aiming to address challenges of poor treatment tolerance, high healthcare costs, and compromised quality of life, thereby providing clinical insights for broader adoption of this approach. [Methods] Two post-allogeneic hematopoietic stem cell transplantation (allo-HSCT) patients undergoing blinatumomab maintenance therapy were selected to evaluate the efficacy of the outpatient infusion model. Patient selection criteria, nursing protocols, standardized workflows, and advancements in infusion practices were systematically analyzed combined with a review of global developments in this field. [Results] Both patients completed outpatient blinatumomab infusion without severe adverse events, demonstrating preliminary feasibility and safety of this model. The novel approach enhanced treatment convenience, reduced hospitalization costs, and improved quality of life. [Conclusion] Despite the limited sample size, this pilot study highlights the potential of outpatient blinatumomab administration as a viable alternative to traditional inpatient regimens.
8.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.
9.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.
10.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.


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