1.Eficacy and safety of washed red blood cells and white suspended red blood cells in the treatment of autoimmune hemolytic anemia: a meta-analysis
Wenda FU ; Hua WEI ; Dan LI ; Longfei YANG
Chinese Journal of Blood Transfusion 2025;38(2):284-290
[Objective] To systematically evaluate the therapeutic effect of washed red blood cells and white suspended red blood cells on patients with autoimmune hemolytic anemia, and to provide reference for their clinical treatment. [Methods] CNKI, Wanfang, VIP, PubMed, Embase, Cochrane Library and other databases from the establishment of the database to August 2024 were searched, including the randomized controlled trials of washed red blood cells and white suspended red blood cells in the treatment of autoimmune hemolytic anemia that met the requirements. After literature screening, data extraction and quality evaluation, meta-analysis was performed using Review manager 5.3 software and Stata 15.1 software to analyze the therapeutic effect of blood transfusion in the primary outcome, hematological indicators (Hb, Ret, RBC, and TBIL) of the two groups after blood transfusion and the occurrence of adverse blood transfusion reactions. [Results] After screening, 10 literatures meeting the criteria were retrieved, and a total of 753 patients with autoimmune hemolytic anemia were treated with washed red blood cell infusion in the observation group and white suspended red blood cell infusion in the control group. Meta-analysis suggested that there was no significant difference in the therapeutic effect of transfusion between patients who received washed red cells and those received white suspended red cells[SMD=1.16, 95%CI (0.87, 1.54), P>0.05]. The hematological indexes of the two groups after transfusion (Hb [SMD=0.04, 95%CI (-0.14, 0.22), P>0.05]、Ret[SMD=-0.15, 95%CI (-0.34, 0.03), P>0.05]、RBC[SMD=0.08, 95%CI (-0.10, 0.26), P>0.05] and TBIL [SMD=-0.02, 95%CI (-0.18, 0.15), P>0.05]) and the incidence of transfusion adverse reactions[SMD=0.8, 95%CI (0.47, 1.39), P>0.05] were not significantly different. [Conclusion] Based on the current study, the efficacy and safety of infusion of washed red blood cells and white suspended red blood cells are comparable in patients with autoimmune hemolytic anemia. However, considering the simple preparation process of washed red blood cells and the low price, infusion of washed red blood cells is recommended for patients with autoimmune hemolytic anemia.
2.Acute Inflammatory Pain Induces Sex-different Brain Alpha Activity in Anesthetized Rats Through Optically Pumped Magnetometer Magnetoencephalography
Meng-Meng MIAO ; Yu-Xuan REN ; Wen-Wei WU ; Yu ZHANG ; Chen PAN ; Xiang-Hong LIN ; Hui-Dan LIN ; Xiao-Wei CHEN
Progress in Biochemistry and Biophysics 2025;52(1):244-257
ObjectiveMagnetoencephalography (MEG), a non-invasive neuroimaging technique, meticulously captures the magnetic fields emanating from brain electrical activity. Compared with MEG based on superconducting quantum interference devices (SQUID), MEG based on optically pump magnetometer (OPM) has the advantages of higher sensitivity, better spatial resolution and lower cost. However, most of the current studies are clinical studies, and there is a lack of animal studies on MEG based on OPM technology. Pain, a multifaceted sensory and emotional phenomenon, induces intricate alterations in brain activity, exhibiting notable sex differences. Despite clinical revelations of pain-related neuronal activity through MEG, specific properties remain elusive, and comprehensive laboratory studies on pain-associated brain activity alterations are lacking. The aim of this study was to investigate the effects of inflammatory pain (induced by Complete Freund’s Adjuvant (CFA)) on brain activity in a rat model using the MEG technique, to analysis changes in brain activity during pain perception, and to explore sex differences in pain-related MEG signaling. MethodsThis study utilized adult male and female Sprague-Dawley rats. Inflammatory pain was induced via intraplantar injection of CFA (100 μl, 50% in saline) in the left hind paw, with control groups receiving saline. Pain behavior was assessed using von Frey filaments at baseline and 1 h post-injection. For MEG recording, anesthetized rats had an OPM positioned on their head within a magnetic shield, undergoing two 15-minute sessions: a 5-minute baseline followed by a 10-minute mechanical stimulation phase. Data analysis included artifact removal and time-frequency analysis of spontaneous brain activity using accumulated spectrograms, generating spectrograms focused on the 4-30 Hz frequency range. ResultsMEG recordings in anesthetized rats during resting states and hind paw mechanical stimulation were compared, before and after saline/CFA injections. Mechanical stimulation elevated alpha activity in both male and female rats pre- and post-saline/CFA injections. Saline/CFA injections augmented average power in both sexes compared to pre-injection states. Remarkably, female rats exhibited higher average spectral power 1 h after CFA injection than after saline injection during resting states. Furthermore, despite comparable pain thresholds measured by classical pain behavioral tests post-CFA treatment, female rats displayed higher average power than males in the resting state after CFA injection. ConclusionThese results imply an enhanced perception of inflammatory pain in female rats compared to their male counterparts. Our study exhibits sex differences in alpha activities following CFA injection, highlighting heightened brain alpha activity in female rats during acute inflammatory pain in the resting state. Our study provides a method for OPM-based MEG recordings to be used to study brain activity in anaesthetized animals. In addition, the findings of this study contribute to a deeper understanding of pain-related neural activity and pain sex differences.
3.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.
4.Correlation between the serum levels of aminotransferases and liver inflammation activity in pediatric chronic hepatitis B patients: An analysis of 1 267 cases
Dan ZHAO ; Lina JIANG ; Shuhong LIU ; Haiyan WEI ; Chunmei BAO ; Jingmin ZHAO
Journal of Clinical Hepatology 2025;41(6):1062-1067
ObjectiveTo investigate the correlation of the serum levels of aminotransferases and their ratios with liver inflammation activity in pediatric chronic hepatitis B (pCHB) patients, and to provide a basis for selecting the dominant population for treatment. MethodsThis study was conducted among 1 267 pCHB patients who were admitted to The Fifth Medical Center of Chinese PLA General Hospital from January 2010 to August 2022 and these patients did not receive antiviral therapy. The patients were analyzed in terms of demographic features, blood routine, blood biochemistry, HBV serological markers, and liver biopsy data. According to liver inflammation activity based on liver biopsy, the patients were divided into no or mild inflammation activity (G0 — G1) group and significant inflammation activity (G2 — G4) group. The serum levels of aminotransferases and their ratios were compared between groups, and their correlation with liver inflammation activity in pCHB patients was analyzed. Additionally, the patients were stratified by the age, and the relationship between serum aminotransferase levels and liver inflammation activity was analyzed in each age group. For comparison of continuous data between two groups, the independent samples t-test was used when the data were normally distributed, while the Mann-Whitney U test was used when the data were not normally distributed; the chi-square test was employed for comparison of categorical data between two groups. A Spearman’s correlation analysis was performed for correlation assessment. ResultsAmong the 1 267 pCHB patients, there were 468 (36.9%) in the G0 — G1 group and 799 (63.1%) in the G2 — G4 group, and there were significant differences between the two groups in the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), AST/ALT ratio, gamma-glutamyl transpeptidase (GGT), total bilirubin, direct bilirubin, HBeAg quantification, low-density lipoprotein, and platelet count (PLT) (all P<0.05). The correlation analysis showed that liver inflammation activity was negatively correlated with PLT and low-density lipoprotein (both P<0.05) and was positively correlated with GGT, total bilirubin, direct bilirubin, and HBeAg titer (all P<0.05), while it was not significantly correlated with ALT, AST, and AST/ALT ratio (all P>0.05). In the 0 — 12 years group, the 13 — 18 years male group, and the 13 — 18 years female group, liver inflammation activity aggravated with the increases in the serum levels of ALT and AST, and there were significant differences between groups (all P<0.05). In the 0 — 12 years group, there was a significant difference in significant liver inflammation activity between the AST/ALT ratio >1 group and the AST/ALT ratio ≤1 group (P<0.001). Among the 1 267 patients, 447 (35.28%) had an ALT level of <2×upper limit of normal (ULN), among whom 196 (43.85%) had G≥2 liver inflammation, accounting for 15.47% of all children enrolled. ConclusionLiver inflammation activity is not significantly correlated with ALT, AST, and AST/ALT ratio in pCHB patients, suggesting that the serum levels of aminotransferases cannot truly reflect liver inflammation activity in pCHB patients with an aminotransferase level of <2×ULN. In clinical practice, liver biopsy should be performed for children with an aminotransferase level of <2×ULN to clarify whether antiviral therapy should be performed.
5.Application value of gene-modified mesenchymal stem cells in liver diseases
Tingting ZHAO ; Junfeng LI ; Dan ZHOU ; Xiaoqin GAO ; Wei YUE ; Ruqin WANG ; Liting ZHANG
Journal of Clinical Hepatology 2025;41(6):1220-1226
The immunomodulatory, repair, and regeneration-promoting functions of mesenchymal stem cells make them one of the potential treatment methods for liver diseases. At present, viral and non-viral delivery methods have been developed to genetically modify mesenchymal stem cells, and gene modification can promote the survival, homing, and cytokine secretion of mesenchymal stem cells, thereby enhancing the ability of mesenchymal stem cells to treat liver diseases. This article mainly summarizes the research advances in gene-modified mesenchymal stem cells in the treatment of liver diseases, in order to provide new insights and strategies for the clinical treatment of liver diseases.
6.Targeting PPARα for The Treatment of Cardiovascular Diseases
Tong-Tong ZHANG ; Hao-Zhuo ZHANG ; Li HE ; Jia-Wei LIU ; Jia-Zhen WU ; Wen-Hua SU ; Ju-Hua DAN
Progress in Biochemistry and Biophysics 2025;52(9):2295-2313
Cardiovascular disease (CVD) remains one of the leading causes of mortality among adults globally, with continuously rising morbidity and mortality rates. Metabolic disorders are closely linked to various cardiovascular diseases and play a critical role in their pathogenesis and progression, involving multifaceted mechanisms such as altered substrate utilization, mitochondrial structural and functional dysfunction, and impaired ATP synthesis and transport. In recent years, the potential role of peroxisome proliferator-activated receptors (PPARs) in cardiovascular diseases has garnered significant attention, particularly peroxisome proliferator-activated receptor alpha (PPARα), which is recognized as a highly promising therapeutic target for CVD. PPARα regulates cardiovascular physiological and pathological processes through fatty acid metabolism. As a ligand-activated receptor within the nuclear hormone receptor family, PPARα is highly expressed in multiple organs, including skeletal muscle, liver, intestine, kidney, and heart, where it governs the metabolism of diverse substrates. Functioning as a key transcription factor in maintaining metabolic homeostasis and catalyzing or regulating biochemical reactions, PPARα exerts its cardioprotective effects through multiple pathways: modulating lipid metabolism, participating in cardiac energy metabolism, enhancing insulin sensitivity, suppressing inflammatory responses, improving vascular endothelial function, and inhibiting smooth muscle cell proliferation and migration. These mechanisms collectively reduce the risk of cardiovascular disease development. Thus, PPARα plays a pivotal role in various pathological processes via mechanisms such as lipid metabolism regulation, anti-inflammatory actions, and anti-apoptotic effects. PPARα is activated by binding to natural or synthetic lipophilic ligands, including endogenous fatty acids and their derivatives (e.g., linoleic acid, oleic acid, and arachidonic acid) as well as synthetic peroxisome proliferators. Upon ligand binding, PPARα activates the nuclear receptor retinoid X receptor (RXR), forming a PPARα-RXR heterodimer. This heterodimer, in conjunction with coactivators, undergoes further activation and subsequently binds to peroxisome proliferator response elements (PPREs), thereby regulating the transcription of target genes critical for lipid and glucose homeostasis. Key genes include fatty acid translocase (FAT/CD36), diacylglycerol acyltransferase (DGAT), carnitine palmitoyltransferase I (CPT1), and glucose transporter (GLUT), which are primarily involved in fatty acid uptake, storage, oxidation, and glucose utilization processes. Advancing research on PPARα as a therapeutic target for cardiovascular diseases has underscored its growing clinical significance. Currently, PPARα activators/agonists, such as fibrates (e.g., fenofibrate and bezafibrate) and thiazolidinediones, have been extensively studied in clinical trials for CVD prevention. Traditional PPARα agonists, including fenofibrate and bezafibrate, are widely used in clinical practice to treat hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) levels. These fibrates enhance fatty acid metabolism in the liver and skeletal muscle by activating PPARα, and their cardioprotective effects have been validated in numerous clinical studies. Recent research highlights that fibrates improve insulin resistance, regulate lipid metabolism, correct energy metabolism imbalances, and inhibit the proliferation and migration of vascular smooth muscle and endothelial cells, thereby ameliorating pathological remodeling of the cardiovascular system and reducing blood pressure. Given the substantial attention to PPARα-targeted interventions in both basic research and clinical applications, activating PPARα may serve as a key therapeutic strategy for managing cardiovascular conditions such as myocardial hypertrophy, atherosclerosis, ischemic cardiomyopathy, myocardial infarction, diabetic cardiomyopathy, and heart failure. This review comprehensively examines the regulatory roles of PPARα in cardiovascular diseases and evaluates its clinical application value, aiming to provide a theoretical foundation for further development and utilization of PPARα-related therapies in CVD treatment.
7.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.
8.Effect and mechanism of Jingangteng capsules in the treatment of non-alcoholic fatty liver disease based on gut microbiota and metabolomics
Shiyuan CHENG ; Yue XIONG ; Dandan ZHANG ; Jing LI ; Zhiying SUN ; Jiaying TIAN ; Li SHEN ; Yue SHEN ; Dan LIU ; Qiong WEI ; Xiaochuan YE
China Pharmacy 2025;36(11):1340-1347
OBJECTIVE To investigate the effect and mechanism of Jingangteng capsules in the treatment of non-alcoholic fatty liver disease (NAFLD). METHODS Thirty-two SD rats were randomly divided into normal group and modeling group. The modeling group was fed a high-fat diet to establish a NAFLD model. The successfully modeled rats were then randomly divided into model group, atorvastatin group[positive control, 2 mg/(kg·d)], and Jingangteng capsules low- and high-dose groups [0.63 and 2.52 mg/(kg·d)], with 6 rats in each group. The pathological changes of the liver were observed by hematoxylin-eosin staining and oil red O staining. Enzyme-linked immunosorbent assay was performed to determine the serum levels of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), alanine transaminase (ALT), aspartate transaminase (AST), tumour necrosis factor-α (TNF-α), interleukin-1β (IL-1β), IL-6, IL-18. 16S rDNA amplicon sequencing and metabolomics techniques were applied to explore the effects of Jingangteng capsules on gut microbiota and metabolisms in NAFLD rats. Based on the E-mail:591146765@qq.com metabolomics results, Western blot analysis was performed to detect proteins related to the nuclear factor kappa-B (NF-κB)/NOD-like receptor family protein 3 (NLRP3) signaling pathway in the livers of NAFLD rats. RESULTS The experimental results showed that Jingangteng capsules could significantly reduce the serum levels of TG, TC, LDL-C, AST, ALT, TNF-α, IL-1β, IL-6, IL-18, while increased the level of HDL-C, and alleviated the hepatic cellular steatosis and inflammatory infiltration in NAFLD rats. They could regulate the gut microbiota disorders in NAFLD rats, significantly increased the relative abundance of Romboutsia and Oscillospira, and significantly decreased the relative abundance of Blautia (P<0.05). They also regulated metabolic disorders primarily by affecting secondary bile acid biosynthesis, fatty acid degradation, O-antigen nucleotide sugar biosynthesis, etc. Results of Western blot assay showed that they significantly reduced the phosphorylation levels of NF-κB p65 and NF-κB inhibitor α, and the protein expression levels of NLRP3, caspase-1 and ASC (P<0.05 or P<0.01). CONCLUSIONS Jingangteng capsules could improve inflammation, lipid accumulation and liver injury in NAFLD rats, regulate the disorders of gut microbiota and metabolisms, and inhibit NF-κB/NLRP3 signaling pathway. Their therapeutic effects against NAFLD are mediated through the inhibition of the NF-κB/NLRP3 signaling pathway.
9.An analysis of risk factors for mortality in patients with bloodstream infections caused by carbapenem-resistant Klebsiella pneumoniae
Qiuli ZHU ; Miaomiao GENG ; Ju WEI ; Yun SHEN ; Dan HU ; Chunxia CHEN ; Haiwei CHEN ; Zhe SUN
Shanghai Journal of Preventive Medicine 2025;37(4):296-300
ObjectiveTo explore the clinical characteristics and risk factors for 30-day mortality in hospitalized patients with bloodstream infections (BSI) caused by carbapenem-resistant Klebsiella pneumoniae (CRKP). MethodsData were obtained retrospectively from the electronic medical records of inpatients at a tertiary A-grade hospital in Shanghai from January 2016 to December 2023. The collected variables included age, gender, department, surgical treatment, empirical antibiotic therapy, Pitt Bacteremia score (PBS), Charlson comorbidity index (CCI), INCREMENT-CPE score (ICS), length of hospital stay, the time from CRKP-BSI to discharge and, etc. The follow-up period ended upon discharge, with the follow-up outcomes defined as in-hospital mortality or discharge. The endpoint was defined as death within 30 days (including day 30) caused by CRKP-BSI or infection-related complications. Patients who survived within 30 days after CRKP-BSI were classified into the survival group, while those who died within 30 days were classified into the death group. Independent risk factors for 30-day mortality in patients with CRKP-BSI were analyzed using univariate and multivariate Cox regression analysis. ResultsA total of 71 hospitalized patients with CRKP-BSI, comprising 51 males and 20 females, with an average age of (65.12±18.25) years, were included during the study period. The M (P25, P75) of hospital stay were 37.00 (24.00, 56.00) days, and M (P25, P75) of the duration from CRKP-BSI to discharge or death were 18.00 (7.00, 35.00) days. There were 20 deaths (28.17%) in the death group and 51 survivors (71.83%) in the survival group. The results of multivariate Cox regression analysis showed that the ICS as an independent risk factor for 30-day mortality in CRKP-BSI patients (HR=1.379, 95%CI: 1.137‒1.671, P=0.001). Each 1-point increase in the ICS was associated with a 37.9% increase in the risk of mortality. ConclusionThe ICS is found to be a risk factor for 30-day mortality in patients with CRKP-BSI, which may facilitate the prediction for the risk of 30-day mortality and thereby support clinical decision-making for patients with CRKP-BSI.
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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