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 comprehensively excavate and analyze the research status,research hotspots and future trends of the literature related to the field of acupoint catgut embedding therapy for pain treatment in the CNKI database.Methods We searched the CNKI database from its establishment to June 2022,and scientifically analyzed the authors,keywords,and institutions of the included literature of acupoint catgut embedding therapy for pain treatment through specific algorithms of Citespace to generate a visual knowledge map.Results A total of 319 documents were included for statistical analysis,the number of publications in the field of acupoint catgut embedding therapy for the treatment of pain was generally on the rise,the number of publications by various authors was on the low side,and there was a lack of co-operation between the research teams,with the main institutions being the Guang'anmen Hospital,Chinese Academy of Chinese Medical Sciences,Affiliated Hospital of Youjiang Medical Universities of Nationalities and the Guangzhou University of Chinese Medicine,forming a 10-keyword clustering,and the hotspots of diseases under study were mainly mixed haemorrhoids,postoperative pain,low back and leg pain and dysmenorrhoea,etc..The main interventions were pure acupoint catgut embedding therapy and the combination of acupoint catgut embedding therapy and other acupuncture therapies,and the main research method was clinical research.Conclusion Acupoint catgut embedding therapy for the treatment of pain has a good development prospect,the future needs to deepen the clinical research,strengthen the mechanism research,pay attention to the joint use of acupoint catgut embedding therapy and other traditional Chinese medicine methods,and pay attention to the research of different thread materials.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

Viral myocarditis(VMC)is the leading cause of dilated cardiomyopathy,which can lead to heart failure and sudden cardiac death.With the development of high-throughput sequencing technology,non-coding RNA(ncRNA)plays an important role in the occurrence and development of VMC.ncRNA promotes the occurrence and development of VMC by regulating viral replication,immune cell function,myocardial cell death,myocardial interstitial fibrosis,and other pathological processes.This article reviews the research progress of ncRNA in VMC and provides new ideas for the pathogenesis,diagnosis,and treatment of VMC.

The compound (E)-1-(4-(3-(5-chloro-6-oxo-3,6-dihydropyridin-1(2H)-yl)-3-oxo-propyl-1-ene-1-yl) phenyl)-3-(4-fluorophenyl) urea (C12), a novel derivative of piperlongumine previously synthesized by our research group, was investigated in this study to examine its effects on human non-small cell lung cancer cell line H1299 in vitro and elucidate its potential mechanism of action. The impact of C12 on the proliferation, migration, and invasion abilities of H1299 cells were assessed using methyl thiazolyl tetrazolium (MTT) assay, wound healing assay, cloning formation assay, and Transwell assay. Flow cytometry was employed to evaluate the influence of C12 on cell cycle progression, reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP), and apoptosis induction in H1299 cells. Western blot analysis was conducted to investigate the expression levels of p21, Cyclin B1, CDK1, Bax, Bcl-2, JNK, p-JNK, Erk1/2, p-Erk1/2, p38 and p-p38 proteins for exploring the anti-tumor mechanism underlying C12's actions. The results demonstrated that C12 exerted inhibitory effects on the proliferation, migration, and invasion capacities of H1299 cells in a time-dependent and concentration-dependent manner. Moreover, C12 induced G2/M phase arrest in the cell cycle, reduced MMP levels, elevated ROS production, and triggered apoptotic processes. Flow cytometry analysis revealed that C12 downregulated Cyclin B1 and CDK1 protein expressions, resulting in G2/M phase arrest. C12 also upregulated Bax/Bcl-2 ratio, promoting apoptosis. Furthermore, C12 activated MAPK signaling pathway by enhancing phosphorylation levels of JNK, Erk1/2, and p38 proteins. In conclusion, C12 significantly suppressed proliferation, migration, and invasion capabilities while inducing cell cycle arrest and apoptosis in H1299 cells. These effects may be attributed to activation of the MAPK signaling pathway.

With the widespread use of carbapenem antibiotics,the clinical detection rate of carbapenem-resistant Gram-negative bacilli has shown a significant increase.Carbapenem-resistant Gram-negative bacilli isolates are often extensively or fully resistant,resulting in limited antimicrobial treatment options and high morbidity and mortality rates,posing a serious public health threat.The clinical treatment of carbapenem-resistant Gram-negative bacilli includes the use of single or combination antimicrobials such as polymyxin,tigecycline,and fosfomycin.A number of new antimicrobials and therapeutic approaches are under development.The clinical management of carbapenem-resistant Gram-negative infections is severely challenged by the limited choice of antimicrobial agents.Therefore,this article reviews the current status and progress of antimicrobial treatment for carbapenem-resistant Gram-negative bacilli to providing clinical reference.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Huocao(a traditional Chinese herbal medicine) moxibustion is a characteristic technology in Yi medicine suitable for cold-dampness diseases. Huocao, as the moxibustion material, is confusedly used in clinical practice and little is known about its quality control. In this study, UPLC method was used to establish the chemical fingerprint of non-volatile components in Huocao, and the contents of eight phenolic acids such as chlorogenic acid were determined. Multivariate statistical analysis was performed to obtain the indicator components of Huocao for quality evaluation, and thus a comprehensive evaluation system for the quality of Huocao was built. The UPLC fingerprints of 49 batches of Huocao were established, and there were 20 common peaks, of which eight phenolic acids including neochlorogenic acid and chlorogenic acid were identified. Except for three batches of Huocao, the similarity of the other 46 batches was higher than 0.89, suggesting that the established fingerprint method could be used for quality control of the medicinal herb. The correlation coefficient between entropy weight score of the eight phenolic acids and comprehensive fingerprint score in Huocao was 0.875(P<0.01), which indicated that the eight phenolic acids could be used as indicator components for the quality evaluation of Huocao. Furthermore, in multivariate statistical analysis on the common peaks of fingerprint and the contents of the eight phenolic acids, chlorogenic acid, isochlorogenic acid A and isochlorogenic acid C were screened to be the indicator components. The results revealed that the proposed method achieved a simple and accurate quality control of Huocao based on UPLC fingerprint and multi-component content determination, which provided useful data for establishing the quality standard of Huocao.
Chlorogenic Acid ; Entropy ; Hydroxybenzoates ; Quality Control

Chirality is one of the fundamental properties of nature, and most of the important molecules in living organisms contain chiral structures. The efficacy and safety of drugs are often closely related to the chiral structure of compounds, however, there are relatively more studies on synthetic characterization, pharmacology, and toxicology of chiral small molecule chemical drugs, but relatively less studies on chiral compounds contained in natural drugs such as traditional Chinese medicines. Chiral separation, as the basis of chiral research, has a pivotal position in the study of chiral compounds. In this paper, we systematically describe the separation methods of chiral compounds from the classification of chiral splitting methods based on chromatographic and non-chromatographic methods, as well as chromatographic packing materials, chiral additives and chiral derivatization, and review the chiral compounds in natural drugs such as traditional Chinese medicines reported in the past ten years, in order to provide references for the splitting and evaluating the activity of chiral compounds, and the improvement of quality standards of traditional Chinese medicines.