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.

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 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.

ObjectiveTo explore the impact of overtime work on work-related musculoskeletal disorders in male employees in the automobile manufacturing industry. Methods A total of 1 731 male employees with more than one year of working experience from an automobile manufacturing industry were selected as the research subjects using judgment sampling method. The Musculoskeletal Disorder Questionnaire was used to investigate the prevalence of musculoskeletal disorder. Employees were divided into control group and overtime group, and a 1∶1 matching was performed using propensity score matching method, and 573 pairs were successfully matched. The prevalence of WMSDs in various body parts was compared between the two groups. Results The overtime working rate of the research subjects was 34.2%, and the prevalence of WMSDs was 57.1%. Overtime work increased the risk of WMSDs in the neck, shoulders, upper back, lower back, ankle/feet, and overall body of the workers (all P<0.05), with the odd ratio and 95% confidence interval of 1.43 (1.10-1.85), 1.38 (1.06-1.80), 1.42 (1.07-1.89), 1.28 (1.01-1.62), 1.37 (1.01-1.87), and 1.49 (1.17-1.89), respectively. However, there was no association between overtime work and the risk of WMSDs in the elbows, hands/wrists, hips, and knees of the subjects (all P>0.05). Conclusion Overtime work increases the risk of WMSDs in the neck, shoulders, upper back, lower back, ankles/feet, and overall body of male employees in the automobile manufacturing industry. Enterprises should improve labor organization, reduce overtime work, and protect the health of workers.

Objective: To investigate the expression of the Y chromosome gene lysine-specific demethylase 5D(KDM5D) in male bladder cancer and its effects on cancer progression, thereby explaining gender-related prognostic differences in bladder cancer. Methods: Bioinformatics analysis was conducted to identifyKDM5Das a differentially expressed Y chromosome gene with prognostic significance in bladder cancer based on data from the TCGA database. The expression ofKDM5Din bladder cancer cell lines, collected clinical bladder cancer tissues, and adjacent normal epithelial tissues were examined using quantitative Real-time PCR(qPCR), Western blot, immunofluorescence, tumor microenvironment analysis, and bioinformatics pathway analysis. The effects ofKDM5Don bladder cancer cell proliferation and migration were validated through cell experiments followingKDM5Dknockdown and overexpression. Additionally, clinical data onKDM5Dexpression in bladder cancer tissue arrays were statistically analyzed in relation to metastasis and recurrence. Results: KDM5Dwas generally downregulated in male bladder cancer but exhibited variable expression in different bladder cancer cell lines and between recurrent and non-recurrent bladder cancers. Overexpression ofKDM5Dinhibited tumor cell proliferation and migration, and lowerKDM5Dexpression was associated with higher recurrence and metastasis rates. Bioinformatics analysis suggested thatKDM5Dmight influence tumor metastasis or recurrence by affecting immune cell aggregation and epithelial-mesenchymal transition. Conclusion KDM5Dis a protective gene specific to male bladder cancer and may be associated with the generally better prognosis observed in male compared to female bladder cancer patients.