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.

Background The prevalence of low back pain among workers using vibrating tools in the automobile manufacturing industry is high; however, research on associated risk factors remains limited. Objective To investigate the association between use of vibrating tools and low back pain among automobile manufacturing workers, and to estimate related population attributable risk percentage (PAR%). Methods A cross-sectional survey was conducted using the Chinese Musculoskeletal Disorders Questionnaire among workers with over one year of service in an automobile manufacturing enterprise. Workers were categorized into an exposed group (vibrating tool users) and a control group (non-users) based on their use of vibrating tools during work. The variables showing statistically significant differences between the two groups were selected as covariates for matching by 1∶2 nearest-neighbor propensity score. Chi-square test was used to compare the prevalence of low back pain between the matched exposed and control groups. Log-binomial regression model was employed to calculate the prevalence ratio (PR), and the PAR% of low back pain attributable to vibrating tool use was subsequently determined. Results A total of 6973 valid questionnaires were collected, comprising 5676 males and 1297 females, with an overall low back pain prevalence of 40.3% (2809/6973). The exposed group included 1255 workers (1134 males, 121 females), with a mean age of (44.2 ± 8.7) years and a mean tenure in the current position of (23.5 ± 9.9) years; the matching control group consisted of 2510 workers (2279 males, 231 females), with a mean age of (44.7 ± 8.6) years and a mean tenure in the current position of (24.0 ± 10.0) years. The prevalence of low back pain was 76.7% (963/1255) in the exposed group, significantly higher than the 29.9% (750/2510) in the control group (P<0.001). The log-binomial regression analysis showed a PR of 2.57 (95%CI: 2.28, 2.90) for the exposed group, with a PAR% of 22.03%. Conclusion The use of vibrating tools among automobile manufacturing workers is positively associated with reporting low back pain. Implementing effective measures to mitigate vibration hazards is crucial for reducing the burden of low back pain in this population.

Objective: To analyze the phylogenetic characteristics of VP1 gene of Coxsackievirus A10 (CVA10) isolates from 2004 to 2023, and to understand the genetic evolution and epidemic trends of CVA10, so as to provide references for the prevention and control of hand, foot, and mouth disease. Methods: The full-length sequences of the VP1 region of CVA10 isolates were retrieved from the BV-BRC database before December 15, 2024. Gene typing, sequence analysis, evolutionary analysis, and amino acid mutation site analysis were conducted using bioinformatics software. Results: A total of 1 253 CVA10 isolates VP1 region nucleotide full-length sequences from 2004 to 2023 were included, with 9 strains from 2004 to 2008, 338 strains from 2009 to 2012, and 906 strains from 2013 to 2023. China had the highest number of CVA10 isolates, with 1 143 strains accounting for 91.22%, and the predominant genotype was C3. Compared to the prototype strain, the nucleotide sequence homology of the VP1 region of CVA10 isolates ranged from 74.94% to 77.63%, while the amino acid sequence homology ranged from 88.59% to 93.62%. The third codon position preferred cytosine and thymine. The top three most abundant amino acids were threonine, alanine, and valine. The average relative synonymous codon usage of 30 amino acid codon groups was greater than 1. The average amino acid substitution entropy value was 0.04, with four amino acid mutation-prone sites identified, and the mutation-prone rate was 1.35%. Conclusions From 2004 to 2023, the majority of CVA10 isolates were primarily sourced from China, with genotype C3 being the predominant circulating strain in China. The nucleotide homology between the CVA10 isolates and the prototype strain was relatively low, and mutation-prone sites were identified, indicating that enhanced monitoring of viral variation is necessary.

The outer membrane composed predominantly of lipopolysaccharide (LPS) is an essential biological barrier for most Gram-negative (G^-) bacteria. Lipopolysaccharide transport protein (Lpt) complex LptDE is responsible for the critical final stage of LPS transport and outer membrane assembly. The structure and function of LptDE are highly conserved in most G^- bacteria but absent in mammalian cells, and thus LptDE complex is regarded as an attractive antibacterial target. In recent 10 years, the deciphering of the three-dimensional structure of LptDE protein facilities the drug discovery based on such "non-enzyme" proteins. Murepavadin, a peptidomimetic compound, was reported to be the first compound able to target LptD, enlightening a new class of antibacterial molecules with novel mechanisms of action. This article is devoted to summarize the molecular characteristics, structure-function of LptDE protein complex and review the development of murepavadin and related peptidomimetic compounds, in order to provide references for relevant researches.

Objective To make an epidemiological investigation on traditional Chinese medicine(TCM)dampness syndrome manifestations in the population at risk of cerebrovascular diseases in Guangdong area.Methods A cross-sectional study was conducted to analyze the clinical data related to the risk of cerebrovascular diseases in 330 Guangdong permanent residents.The diagnosis of dampness syndrome,quantitative scoring of dampness syndrome and rating of the risk of stroke were performed for the investigation of the distribution pattern of dampness syndrome and its influencing factors.Results(1)A total of 306(92.73%)study subjects were diagnosed as dampness syndrome.The percentage of dampness syndrome in the risk group was 93.82%(258/275),which was slightly higher than that of the healthy group(48/55,87.27%),but the difference was not statistically significant(χ2 = 2.91,P = 0.112).The quantitative score of dampness syndrome in the risk group was higher than that of the healthy group,and the difference was statistically significance(Z =-2.24,P = 0.025).(2)Among the study subjects at risk of cerebrovascular disease,evaluation time(χ2 = 26.11,P = 0.001),stroke risk grading(χ2= 8.85,P = 0.031),and history of stroke or transient ischemic attack(TIA)(χ2 = 9.28,P = 0.015)were the factors influencing the grading of dampness syndrome in the population at risk of cerebrovascular disease.Conclusion Dampness syndrome is the common TCM syndrome in the population of Guangdong area.The manifestations of dampness syndrome are more obvious in the population with risk factors of cerebrovascular disease,especially in the population at high risk of stroke,and in the population with a history of stroke or TIA.The assessment and intervention of dampness syndrome should be taken into account for future project of stroke prevention in Guangdong.

OBJECTIVE To explore the effects of different concentrations of aconitine on the ventricular electrophysiology of the rat heart when applied to the heart. METHODS By optical mapping technology, the effects of different concentrations of aconitine on ventricular action potential and calcium signal in rats before and 15 min after administration were observed by in vitro administration of aconitine 0.3, 1, 3 ng·mL−1. RESULTS Compared with the blank group, aconitine could be concentration-dependent to delay the conduction of action potentials under both spontaneous and 6 Hz stimulation rhythms, and there was a significant difference at a concentration of 3 ng·mL−1(P<0.05 or P<0.01). Compared with blank group, when the concentration of aconitine was 1 and 3 ng·mL−1, the action potential duration(APD) of the ventricle was significantly prolonged(P<0.01). Aconitine could also increase the dispersion of action potential conduction(P<0.05) and reduce the ratio of effective refractory period(ERP) to APD90(P<0.01). In addition, aconitine could also be concentration-dependent delay of calcium signal conduction, reduce the speed of calcium conduction(P<0.05 or P<0.01), increase the dispersion of calcium conduction and calcium transient duration(P<0.05 or P<0.01), and reduce the amplitude of calcium signal(P<0.01). CONCLUSION Using the optical labeling technique, it can be visualized that aconitine induces arrhythmia by concentration-dependent delay of ventricular action potential and calcium signaling in rats.To explore the effects of different concentrations of aconitine on the ventricular electrophysiology of the rat heart when applied to the heart. METHODS By optical mapping technology, the effects of different concentrations of aconitine on ventricular action potential and calcium signal in rats before and 15 min after administration were observed by in vitro administration of aconitine 0.3, 1, 3 ng·mL−1. RESULTS Compared with the blank group, aconitine could be concentration-dependent to delay the conduction of action potentials under both spontaneous and 6 Hz stimulation rhythms, and there was a significant difference at a concentration of 3 ng·mL−1(P<0.05 or P<0.01). Compared with blank group, when the concentration of aconitine was 1 and 3 ng·mL−1, the action potential duration(APD) of the ventricle was significantly prolonged(P<0.01). Aconitine could also increase the dispersion of action potential conduction(P<0.05) and reduce the ratio of effective refractory period(ERP) to APD90(P<0.01). In addition, aconitine could also be concentration-dependent delay of calcium signal conduction, reduce the speed of calcium conduction(P<0.05 or P<0.01), increase the dispersion of calcium conduction and calcium transient duration(P<0.05 or P<0.01), and reduce the amplitude of calcium signal(P<0.01). CONCLUSION Using the optical labeling technique, it can be visualized that aconitine induces arrhythmia by concentration-dependent delay of ventricular action potential and calcium signaling in rats.