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.

Objective To establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. Methods Patients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. Results A total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. Conclusion For patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.

ObjectiveTo evaluate the clinical efficacy and safety of Huaban Jiedu Formulation （化斑解毒方， HJF） in treating psoriasis vulgaris with blood-heat syndrome. MethodsA randomized， double-blind， placebo-controlled study was conducted with 60 patients diagnosed with psoriasis vulgaris of blood-heat syndrome. Patients were randomly assigned to either a treatment group or a control group， with 30 cases in each. The treatment group received HJF granules orally， one dose a day， combined with topical Qingshi Zhiyang Ointment （青石止痒软膏）， while the control group received placebo granules， one dose a day， combined with the same topical ointment. Both groups were topically treated twice daily of 28 days treatment cours. Psoriasis area and severity index （PASI）， visual analogue scale for pruritus （VAS）， traditional Chinese medicine （TCM） syndrome scores， dermatology life quality index （DLQI）， and psoriasis life stress inventory （PLSI） were assessed before treatment and on day 14 and day 28. Response rates for PASI 50 （≥50% reduction） and PASI 75 （≥75% reduction）， as well as overall clinical efficacy， were compared between groups. Serum levels of interleukin-6 （IL-6） and interleukin-17 （IL-17） were measured before and after 28 days of treatment. Adverse reactions during treatment were recorded. ResultsAfter 28 days of treatment， both groups showed significant reductions in PASI total score， lesion area score， erythema， scaling， and infiltration scores， pruritus VAS score， TCM syndrome score， DLQI， PLSI， and serum IL-6 and IL-17 levels （P＜0.05）. Compared to the control group， the treatment group had significantly greater improvements in PASI total score and erythema score， TCM syndrome score， serum IL-6 and IL-17 levels， and PASI 50 response rate after 28 days （P＜0.05）. Between-group comparisons of score differences before and after 28-day treatment revealed that the treatment group showed significantly better improvements in PASI total， lesion area score， erythema score， TCM syndrome score， DLQI， PLSI， and inflammatory markers （P＜0.05 or P＜0.01）. The total effective rate on day 14 and day 28 was 40.00% （12/30） and 83.33% （25/30） in the treatment group， versus 6.90% （2/29） and 41.38% （12/29） in the control group， respectively. The clinical efficacy in the treatment group was significantly superior to that in the control group （P＜0.05）. Mild gastric discomfort occurred in 3 patients in the treatment group and 1 in the control group. ConclusionHJF can effectively improve skin lesions and TCM symptoms relieve pruritus， enhance quality of life， and reduce inflammatory markers IL-6 and IL-17， in patients with blood-heat syndrome of psoriasis vulgaris， with a good safety profile.

Background::In the clinic, practitioners encounter many patients with an abnormal pattern of dense punctate magnetic resonance imaging (MRI) signal in the basal ganglia, a phenomenon known as "cheese sign". This sign is reported as common in cerebrovascular diseases, dementia, and old age. Recently, cheese sign has been speculated to consist of dense perivascular space (PVS). This study aimed to assess the lesion types of cheese sign and analyze the correlation between this sign and vascular disease risk factors.Methods::A total of 812 patients from Peking Union Medical College Hospital (PUMCH) dementia cohort were enrolled. We analyzed the relationship between cheese sign and vascular risk. For assessing cheese sign and defining its degree, the abnormal punctate signals were classified into basal ganglia hyperintensity (BGH), PVS, lacunae/infarctions and microbleeds, and counted separately. Each type of lesion was rated on a four-level scale, and then the sum was calculated; this total was defined as the cheese sign score. Fazekas and Age-Related White Matter Changes (ARWMC) scores were used to evaluate the paraventricular, deep, and subcortical gray/white matter hyperintensities.Results::A total of 118 patients (14.5%) in this dementia cohort were found to have cheese sign. Age (odds ratio [OR]: 1.090, 95% confidence interval [CI]: 1.064-1.120, P <0.001), hypertension (OR: 1.828, 95% CI: 1.123-2.983, P = 0.014), and stroke (OR: 1.901, 95% CI: 1.092-3.259, P = 0.025) were risk factors for cheese sign. There was no significant relationship between diabetes, hyperlipidemia, and cheese sign. The main components of cheese sign were BGH, PVS, and lacunae/infarction. The proportion of PVS increased with cheese sign severity. Conclusions::The risk factors for cheese sign were hypertension, age, and stroke. Cheese sign consists of BGH, PVS, and lacunae/infarction.

Exosomes represent a class of nanoscale extracellular vesicles that facilitate the exchange of genetic information among various cells.Alzheimer's disease(AD)stands as a progressive neurodegenerative disorder characterized by its subtle and advan-cing onset,representing the foremost form of dementia lacking effective therapeutic interventions.Notably,investigations have illuminated the involvement of exosomes in the pathogenesis of AD,attributing diagnostic and therapeutic significance to their role,particularly concerning exosomal microRNAs(miRNA).The miRNAs carried by exosomes serve as potential biomarkers for AD,while also exhibiting potential benefits in ameliorating cognitive dysfunction in individuals afflicted by AD.This article aims to comprehensively review the origins of exosomes(encom-passing both mesenchymal cell-derived exosomes and brain-de-rived exosomes)and their potential as therapeutic agents targe-ting AD.

Cervical cancer is one of the most common gynecological malignant tumors,the five-year survival rate decreased significantly in the case of lymph node metastasis and distant metasta-sis,so the development of new anti-cervical cancer drugs is of great significance for the treatment of cervical cancer.Molecular docking technology is one of the most commonly used research methods in computer aided drug design,which is widely used in screening the effective components of drugs,finding the targets of drugs acting on tumors and exploring the mechanism of antineoplastic drugs.This paper reviews the molecular docking technology in the screening of anti-cervical cancer drugs,the determination of anti-tumor targets and the mechanism of anti-cervical cancer,in order to provide more sufficient theoretical basis for the screening of anti-cervical cancer drugs and new drug research and development.

Clostridium perfringens is a common Gram-positive anaerobic conditioned pathogen,widely existing in nature,which can cause diarrhea,gas gangrene,and other diseases.Antibiotics are used in the clinical treatment of Clostridium perfringens infection,but the bacteria will devel-op resistance through mutation,drug-resistant plasmid transmission,and other ways,so that Clos-tridium perfringens can survive under the environmental pressure of antibiotics.Therefore,it is very important to find and develop new preparations to replace antibiotics or as feed additives to target the removal of Clostridium perfringens from the body or to prevent infection.In this study,a virulent Clostridium perfringens phage vB_CPP_AT was isolated from sewage by double plate method.The morphology of the bacteriophage was observed by transmission electron microscope.The biological characteristics of the bacteriophage were analyzed by lytic spectrum,MOI,pH,and temperature tolerance.The results showed that the vB_CPP_AT belongs to the Podoviridae.It would grow explosively at 60 min with an optimal MOI of 0.1.The vB_CPP_AT only lyse Clos-tridium perfringens and the lytic rate was 40％(8/20).No cleavage reaction occurred with other bacteria tested.The phage had good thermal stability and acid-base tolerance.Genomic analysis re-vealed that the phage had double-stranded DNA with a total length of 16 790 bp,and 20 open read-ing frames.Genomic analysis of vBCPPAT showed that it was a new virulent phage of Clostridi-um perfringens.The results laid a foundation for the clinical treatment of Clostridium perfringens with phage.

In order to investigate the regulatory effect of Codonopsis saponins on the immunosup-pression caused by H9N2 subtype avian influenza virus(AIV)infection,rat pulmonary microvas-cular endothelial cells(RPMECs)were incubated with different concentrations of Codonopsis sap-onins(5,10 and 20 mg/L).The expression level of PD-L1 was detected by RT-PCR and flow cy-tometry,and the contents of TNF-α,IFN-y and IL-10 in supernatant were detected by ELISA kit.The titer of H9N2 AIV in supernatant was detected by plaque method.Then,a co-culture system of RPMECs and T cells was established using a Transwell plate with an aperture of 8 μm to mimic the migration of circulating T cells across microvessels to the site of viral infection.RPMECs were cultured in the upper chamber of Transwell,inoculated with H9N2 AIV,supplemented with 20 mg/L Codonopsis saponins 1 h later,and T cells 36 h later.After 8 h of treatment,T cells in the lower compartment were collected and the proportions of CD4+T cells and CD8+T cells were detected by flow cytometry,the expression levels of IL-2,IFN-y and granzyme B in the superna-tant were detected by ELISA,and the proportions of perforin-1 positive T cells were detected by flow cytometry.The proliferation activity of T cells was detected with the MTT cell proliferation and cytotoxicity assay kit,and the percentage of apoptotic cells was detected by flow cytometry af-ter staining of T cells with Annexin V-FITC/PI.The experimental results showed that Codonopsis saponins could significantly reduce the expression level of PD-L1,IL-10 and TNF-α in RPMECs in-duced by H9N2 AIV infection,and reduce the apoptosis rate of T cells.However,the expression levels of IL-2,IFN-y,perforin-1 and granzyme B in transendothelial migration T cells and the pro-liferation activity of T cells were significantly increased.In this study,Codonopsis saponins can sig-nificantly inhibit the expression of H9N2 AIV-induced PD-L1 in RPMECs,enhance the antiviral function of T cells migrating across the endothelial layer,and enhance the resistance of host to H9N2 AIV.

Objective: Self-determination theory (SDT) deems that people have three causality orientations: autonomy orientation, control orientation, and impersonal orientation. Previous studies suggested that lower autonomy orientation or higher control and impersonal orientations may be associated with more addictive behaviors. Our study aimed to investigate if these associations exist in Internet gaming disorder (IGD), and if sensation seeking, anxiety, and depression could influence the associations between causality orientations and IGD symptoms. Methods: A total of 1,400 college students completed the Internet Gaming Disorder Scale, General Causality Orientation Scale, Brief Sensation Seeking Scale, Generalized Anxiety Disorder Scale, and Patient Health Questionnaire. Correlation, multiple linear regressions, structural equation model (SEM) analyses, and moderation analyses were conducted to explore the associations. Results: The control and impersonal orientations were positively associated with IGD symptoms, while the autonomy orientation was negatively associated with them. Moreover, SEM analyses showed that the autonomy-IGD relationship was totally mediated by anxiety and depression, the impersonal-IGD relationship was partially mediated by anxiety, and the control-IGD relationship was partially mediated by depression. Finally, the effects of causality orientations on IGD were moderated by sensation seeking. Conclusion Overall, autonomy orientation is linked to fewer gaming problems, whereas control and impersonal orientations are associated with more gaming problems. Moreover, the relationships between causality orientations and IGD symptoms are mediated by anxiety and depression and moderated by sensation seeking. Our findings inform theory on the motivations of gaming behaviors and may shed light on the prevention and intervention of IGD from the perspective of SDT.

Objective:To investigate the impact of ionizing radiation(IR)on the structure and function of the testis and pro-vide some strategies for the prevention and treatment of IR-induced damage(IRD).Methods:Using radiation dose simulation,se-men analysis,hormone testing,electron microscopy and single-cell transcriptome sequencing,we assessed and analyzed a case of IRD.We established a mouse model of IRD to validate the results of single-cell sequencing,and investigated the specific biological mecha-nisms of IRD and potential strategies for its intervention.Results:IR at 1-2 Gy significantly reduced sperm concentration and mo-tility,which gradually recovered after 12 months but the percentage of morphologically normal sperm remained low.It also caused im-balanced levels of various steroid hormones,decreased testosterone and dehydroepiandrosterone sulfate,increased progesterone,prolac-tin,luteinizing hormone,and follicle-stimulating hormone.Electron microscopy revealed damages to the testis structure,including loss of germ cells,atrophy of the seminiferous tubules,nuclear membrane depression of the spermatocytes,mitochondrial atrophy and de-formation,and reduction of mitochondrial cristae.Single-cell sequencing indicated significant changes in the function of the Leydig cells and macrophages and disrupted lipid-related metabolic pathways after IRD.Administration of L-carnitine to the mouse model im-proved lipid metabolism disorders and partially alleviated IRD to the germ cells.Conclusion:Ionizing radiation can cause disorders of testicular spermatogenesis and sexual hormones and inhibit lipid metabolism pathways in Leydig cells and macrophages.Improving lipid metabolism can alleviate IRD to germ cells.