ObjectiveTo investigate somatization symptoms in adolescents during frequent earthquakes in Hefei， and to explore their correlation with earthquake experiences. MethodsA cross-sectional survey was used to select 324 adolescents in Hefei as the survey objects. The self-rating scale of somatization symptoms （SSS） and the fatigue intensity scale （FIS） were used to evaluate the somatization symptoms and fatigue degree of middle school students， and multivariate Logistic regression analysis was used to explore the related factors of somatization symptoms and fatigue among middle school students. ResultsA total of 324 adolescents were included， and the overall detection rate of somatization symptoms was 6.5%， and the detection rate of moderate or above fatigue was 20.1%. The results of regression analysis showed that adolescents who were concerned about the earthquake for a longer time （≥1 h） had a higher risk of somatization symptoms （OR=5.430， 95%CI： 1.547-19.058）， and adolescents who received pre-earthquake training had a lower degree of fatigue （OR=0.535， 95%CI： 0.292-0.981） （P<0.05）. ConclusionDuring the frequent earthquakes， adolescents have more somatization symptoms and fatigue. Therefore， it is crucial to enhance health education， reduce the emphasis on event-related reports， and implement earthquake prevention and disaster reduction training to improve the physical and mental health of adolescents.

This study aimed to investigate the mechanism of compound Agrimonia pilosula enteritis capsules (CAPEC) on ulcerative colitis (UC) in mice with dampness-heat syndrome. The mice were randomly divided into five groups: the control group, the model group, the positive drug (5-aminosalicylic acid, 5-ASA) group, the low-dose CAPEC (CAPEC-L) group and the high-dose CAPEC (CAPEC-H) group. The mice models were established by using high-fat high-sucrose diet, feeding with distilled spirit and dextran sulfate sodium (DSS). The effects of CAPEC on bile acids (BAs) metabolic profiles in bile and the FXR-SREBP-1 signaling pathway were investigated in the model of UC in mice with dampness-heat syndrome by ELISA, qRT-PCR, UHPLC-QQQ/MS, and histopathological analysis. The results showed that, compared with the model group, the CAPEC-L group and the CAPEC-H group significantly reduced the disease activity index (DAI), and proinflammatory cytokine levels (including IL-6, IL-1β, and TNF-α) in both serum and colon tissues. Additionally, CAPEC markedly ameliorated intestinal inflammation, hepatic lipid accumulation, and pathological alterations in tongue tissue. The CAPEC-H group significantly attenuated the abnormal elevation of BAs profiles in bile, and up-regulated hepatic mRNA levels of Cyp7a1, Cyp7b1, Cyp27a1, Bsep, Fxr, and Shp, while down-regulating Srebp-1 and Cyp8b1 expression. The experimental results suggest that CAPEC alleviates UC with dampness-heat syndrome by ameliorating BAs metabolic disorders, hepatic lipid accumulation, and intestinal inflammation. These findings provide mechanistic insights into CAPEC’s traditional effects of clearing heat and drying dampness, and strengthening the spleen to relieve diarrhea.

BACKGROUND:Previous studies by our research group discovered that Jiawei Xiaoyao San has a significant anti-liver cancer effect,but the specific mechanism of action was unclear. OBJECTIVE:To investigate the regulatory effects of the traditional Chinese medicine formula Jiawei Xiaoyao San on the levels of miRNAs in plasma exosomes of rats with diethylnitrosamine chronically induced primary liver cancer,based on high-throughput sequencing combined with bioinformatics. METHODS:SD rats were randomly divided into a blank control group,a liver cancer model group,and a Jiawei Xiaoyao San treatment group.Liver cancer models were induced by continuous administration of diethylnitrosamine for 12 weeks.Starting from the 17th week,rats in the Jiawei Xiaoyao San treatment group were administered Jiawei Xiaoyao San once daily until the end of the 20th week,while rats in the blank control and liver cancer model groups were given an equivalent volume of saline.Anti-hepatocellular carcinoma effects were validated by assessing the morphological structure of rat liver tissues,along with the expression of the hepatocellular carcinoma markers,Glypican-3 protein and serum alpha-fetoprotein.Plasma exosomes from each group of rats were isolated using ultracentrifugation.High-throughput sequencing technology was used to screen for differentially expressed miRNAs in rat plasma exosomes.Bioinformatics was used to predict the potential biomarkers through which Jiawei Xiaoyao San exerts its anti-liver cancer effects via liver cancer-derived exosomal miRNAs,followed by functional analysis. RESULTS AND CONCLUSION:(1)Jiawei Xiaoyao San significantly improved the morphological structure of liver tissues in a rat model of liver cancer.Compared with the liver cancer model group,the expression of liver cancer markers Glypican-3 protein and serum alpha-fetoprotein was significantly reduced in the Jiawei Xiaoyao San treatment group.(2)Bioinformatics analysis showed that in the Jiawei Xiaoyao San group,upregulated miR-223-3p in the liver cancer model group had target binding sites with genes E2F1 and NCOA1,which were closely related to liver cancer survival and prognosis.Therefore,Jiawei Xiaoyao San has a therapeutic effect on liver cancer,possibly by targeting negative regulation of NCOA1/E2F1 through liver cancer plasma-derived exosomal miR-223-3p,thereby playing anti-liver cancer effect.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

ObjectiveTo analyze the clinical treatment plan and traditional Chinese medicine （TCM） medication rule of children with primary nephrotic syndrome （PNS） in the First Affiliated Hospital of Henan University of Chinese Medicine. MethodsThe gender and age of children firstly diagnosed with nephrotic syndrome in the pediatric nephrology department of the First Affiliated Hospital of Henan University of Chinese Medicine from November 2019 to December 2022 were collected， and the use of immunosuppressive agents and related frequencies were counted. According to the inclusion and exclusion criteria， an independent TCM prescription database for children with nephrotic syndrome was established. Excel was used to analyze the relevant information of the literature. The frequency counting， association rule analysis， and cluster analysis were carried out on TCM in the prescription， and the high-frequent drugs were analyzed. Results（1） General information： A total of 711 children were included， consisting of 522 males （73.42%） and 189 females （26.58%）. The ratio of male to female was about 2.76∶1. The disease mainly occurred in infants and preschool age， and the average age of onset was （4.74 ± 3.48） years old. （2） Clinical treatment plan and use of immunosuppressive agents： Of the 711 children with PNS， 237 were treated with hormone alone （32.33%）， and 474 （66.67%） received immunosuppressive agents combined with hormones. In the initial treatment， hormone combined with Tacrolimus （TAC） was the preferred treatment （32.91%）. For children with refractory PNS who exhibited poor clinical efficacy， Rituximab （RTX） was mostly used for treatment， with a ratio of up to 23.63%. （3） TCM syndrome and medication rule： In PNS syndrome differentiation， Qi and Yin deficiency was identified as the main syndrome. This involved a total of 477 cases， accounting for 67.09%. Yang deficiency of spleen and kidney was observed in 118 cases， accounting for 16.60%. A total of 711 children were included， of which 706 children were treated with TCM. This involved a total of 706 prescriptions， 226 TCM， and 9 793 frequencies. There were 30 herbs used more than 95 times. The top five TCM were Radix et Rhizoma Glycyrrhizae （81.16%）， Radix Astragali （71.81%）， Poria （68.84%）， Rhizoma Atractylodis Macrocephalae （63.60%）， and Fructus Corni （57.37%）. The drug association rules and network diagram showed that the combination of ''Radix Astragali-Rhizoma Atractylodis Macrocephalae-Poria'' was the closest， and five types of combinations were obtained by cluster analysis. ConclusionIn the diagnosis and treatment of PNS in children， TAC combined with hormones shows good clinical efficacy and high safety. For children with refractory PNS， RTX combined with hormones can be used. TCM medication for PNS should follow the basic principles of strengthening the body and vital Qi and make good use of drugs such as Radix Astragali， Poria， Rhizoma Atractylodis Macrocephalae， and cornus to regulate the Yin and Yang balance and achieve better clinical efficacy.

ObjectiveTo analyze the clinical treatment plan and traditional Chinese medicine （TCM） medication rule of children with primary nephrotic syndrome （PNS） in the First Affiliated Hospital of Henan University of Chinese Medicine. MethodsThe gender and age of children firstly diagnosed with nephrotic syndrome in the pediatric nephrology department of the First Affiliated Hospital of Henan University of Chinese Medicine from November 2019 to December 2022 were collected， and the use of immunosuppressive agents and related frequencies were counted. According to the inclusion and exclusion criteria， an independent TCM prescription database for children with nephrotic syndrome was established. Excel was used to analyze the relevant information of the literature. The frequency counting， association rule analysis， and cluster analysis were carried out on TCM in the prescription， and the high-frequent drugs were analyzed. Results（1） General information： A total of 711 children were included， consisting of 522 males （73.42%） and 189 females （26.58%）. The ratio of male to female was about 2.76∶1. The disease mainly occurred in infants and preschool age， and the average age of onset was （4.74 ± 3.48） years old. （2） Clinical treatment plan and use of immunosuppressive agents： Of the 711 children with PNS， 237 were treated with hormone alone （32.33%）， and 474 （66.67%） received immunosuppressive agents combined with hormones. In the initial treatment， hormone combined with Tacrolimus （TAC） was the preferred treatment （32.91%）. For children with refractory PNS who exhibited poor clinical efficacy， Rituximab （RTX） was mostly used for treatment， with a ratio of up to 23.63%. （3） TCM syndrome and medication rule： In PNS syndrome differentiation， Qi and Yin deficiency was identified as the main syndrome. This involved a total of 477 cases， accounting for 67.09%. Yang deficiency of spleen and kidney was observed in 118 cases， accounting for 16.60%. A total of 711 children were included， of which 706 children were treated with TCM. This involved a total of 706 prescriptions， 226 TCM， and 9 793 frequencies. There were 30 herbs used more than 95 times. The top five TCM were Radix et Rhizoma Glycyrrhizae （81.16%）， Radix Astragali （71.81%）， Poria （68.84%）， Rhizoma Atractylodis Macrocephalae （63.60%）， and Fructus Corni （57.37%）. The drug association rules and network diagram showed that the combination of ''Radix Astragali-Rhizoma Atractylodis Macrocephalae-Poria'' was the closest， and five types of combinations were obtained by cluster analysis. ConclusionIn the diagnosis and treatment of PNS in children， TAC combined with hormones shows good clinical efficacy and high safety. For children with refractory PNS， RTX combined with hormones can be used. TCM medication for PNS should follow the basic principles of strengthening the body and vital Qi and make good use of drugs such as Radix Astragali， Poria， Rhizoma Atractylodis Macrocephalae， and cornus to regulate the Yin and Yang balance and achieve better clinical efficacy.

Objective:To explore the neurophysiological features of the prefrontal-limbic-striatal circuit in patients with early-stage bipolar disorder without manic or hypomanic episodes, and its role in identifying early-stage bipolar disorder.Methods:From 2009 to 2019, a total of 155 hospitalized patients with major depressive disorder (MDD) from Nanjing Brain Hospital were selected after at least 5 years of follow-up, 31 patients with depression transitioned to bipolar disorder(ctBD group) and 76 patients remained the diagnosis of MDD(MDD group) were recruited.Sixty-two healthy controls matched for age, gender, and education years were selected as control group(HC group). Resting-state magnetoencephalography (MEG) data in eyes-open state of all subjects were collected.Data were analyzed based on the fieldtrip toolkit on the MATLAB platform. The key brain area of the prefrontal-limbic-striatal circuit were selected. Inter-group statistical analysis were conducted on the spectral energy and power-correlated functional connectivity at the theta, alpha, beta, and gamma frequency bands in the brain area of interest. In addition, the prediction model was constructed to early recognize bipolar disorder.Results:(1)There were statistically significant differences in the spectral energy of theta and alpha frequency bands in the prefrontal-limbic-striatal circuit among the 3 groups (cluster- F=120.50, 112.39, both P<0.05). The spectral energy of theta and alpha frequency bands in interest brain regions of prefrontal-limbic-striatal circuit in MDD group was lower than that in HC group (cluster- t=89.52, P<0.05). The spectral energy of theta band in prefrontal-limbic-striatal circuit in ctBD group was lower than that in HC group(cluster- t=105.82, P<0.05), and the spectral energy of alpha band in inferior frontal gyrus, orbitofrontal gyrus and caudate nucleus was lower than that in HC group (cluster- t=75.78, P<0.05), while there was no significant difference between the MDD group and the ctBD group ( P>0.05).(2)After FDR correction, there were statistically significant differences in functional connectivity between the left orbitofrontal gyrus and the right ventral striatum among the three groups (0.26 (0.13, 0.34), 0.12 (0.09, 0.24), 0.27 (0.20, 0.37), H=13.51, P<0.05, FDR correction). The strength of functional connectivity between the left orbitofrontal gyrus and the right ventral striatum in the MDD group was weaker than that in the HC group and the ctBD group (all P<0.05).(3)Binary Logistic regression analysis showed that the functional connectivity of beta frequency band between the left orbitofrontal gyrus and the right ventral striatum ( B=1.50, OR=4.50, 95% CI=1.73-11.70), the functional connectivity between the right orbitofrontal gyrus and the right amygdala( B=0.98, OR=2.68, 95% CI=1.18-6.13), the total HAMD score ( B=0.80, OR=2.28, 95% CI=1.36-3.67), the body weight factor score ( B=-1.99, OR=0.14, 95% CI=0.04-0.45), the anxiety factor score ( B=-0.99, OR=0.37, 95% CI=0.19-0.71), and sleep factor score( B=-1.14, OR=0.32, 95% CI=0.16-0.65)were the influencing factors for depression transitioned to bipolar disorder. Conclusion:The decreased resting low-frequency energy in the prefrontal-limbic-striatal circuit may be the common neural basis for the onset of unipolar and bipolar depression, and enhanced functional connectivity may be a potential neural circuit mechanism for depression transitioned to bipolar disorder. Functional connectivity combined with clinical manifestations is helpful for early recognition of bipolar disorder.

Objective:To analyze the predictive factors associated with late-onset sepsis(LOS) in very low birth weight infants,and to develop a risk prediction score scale applicable to these infants three days postnatal.This will provide valuable insights for early diagnosis and timely intervention.Methods:Very low birth weight infants admitted to the Children's Hospital of Fudan University from January 1,2022,to June 30,2024,were selected as research subjects.These infants were categorized into two groups:the LOS group and the non-LOS group,based on whether they developed LOS.LASSO regression analysis,alongside univariate and multivariate regression analyses,was employed to identify predictive factors for LOS in this population.A Logistic model was constructed using the optimal combination of predictive variables,and a risk assessment scale was subsequently developed.The prediction performance of the model was evaluated using the Hosmer-Lemeshow chi-square test and the receiver operating characteristic curve.Results:A total of 444 cases of very low birth weight infants were included,of which 185 had LOS and 259 did not.After screening the variables,seven independent factors were included into the model:birth weight,gestational age,tracheal intubation,abnormal skin color,abdominal distension,elevated C-reactive protein levels,and right hand perfusion index.A predictive scoring scale was developed based on the regression coefficients of each variable,with corresponding risk scores assigned as follows:1,4,3,2,1,1,and 2; a score of ≥3.5 indicated high-risk groups.The Hosmer-Lemeshow test results demonstrated that χ2 = 7.602( P = 0.473).The area under the receiver operating characteristic curve was 0.792 ( P<0.001),with a sensitivity of 73.5% and specificity of 71.0%. Conclusion:The risk score scale developed in this study exhibits significant predictive capability,providing valuable insights for clinical medical personnel to assess the risk of LOS in very low birth weight infants during the early postnatal period.

Objective To develop a hypoxia endurance testing system for aviation physiological training of pilots.Methods The hypoxia endurance testing system comprised a low-oxygen mixed gas generator,a pressurization system for low-oxygen mixed gas and a personal breathing apparatus.The low-oxygen mixed gas generator consisted of a main unit composed of an air compressor,a filter,a buffer tank,polymer membrane,a control module,sensors and regulators,wire cables,supporting hoses,etc.;the pressurization system for low-oxygen mixed gas was made up of a protective box,a cooling fan,a motor and a driver,a control module,a solenoid valve,a convergence block,a pressure gauge,etc.;the personal breating apparatus was composed of a gas cylinder,a pressure reducer,an oxygen supply regulator,etc.Forty-eight subjects were selected for hypoxia exposure tests to verify the effectiveness of the system.Results The system developed had the functions of low-oxygen gas preparation,pressurized filling and hypoxia experiment,and the experimental results indicated the acute hypoxia exposure by the system significantly caused signs and symptoms of hypoxia and weakened physiological functions.Conclusion The system developed gains advantages in high accuracy of gas volume fraction control,safety and remarkable effect of simulated hypoxia,and can be an effective tool for acute high-altitude hypoxia testing and training of pilots.[Chinese Medical Equipment Journal,2025,46(10):23-28]