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.

This article reviews the overview of dyadic coping, assessment tools, and the current application status of dyadic coping interventions in patients with gestational diabetes mellitus (GDM) and their spouses, aiming to provide a reference for related research.

Objective:To investigate the clinical features of patients with chronic obstructive pulmonary disease (COPD) and serum-positive specific IgE (SIgE).Methods:This study was a retrospective cohort study. A total of 105 stable COPD patients with allergic features and completed serum SIgE testing were included, and all of them were from Capital Medical University, Beijing Tong Ren Hospital from September 2022 to October 2023. Those with at least one positive result of SIgE testing were classified as positive SIgE COPD group, and those with negative SIgE were classified as negative SIgE COPD group. There were 32 cases (30.5%) in the positive SIgE COPD group and 73 cases (69.5%) in the negative SIgE COPD group. Differences in laboratory tests, pulmonary function, chronic obstructive pulmonary symptom scores, incidence of severe acute exacerbation events in the past year, and drug therapy were compared between the two groups. The risk factors for positive SIgE COPD were analyzed, and the best predictive value for the diagnosis of positive SIgE COPD was analyzed using the area under the curve (AUC) of receiver operating characteristic (ROC).Results:Compared with the negative SIgE COPD group, the percentage of positive SIgE COPD group with rhinitis, sinusitis, sinusitis with nasal polyps, eczema, and a history of drug or food allergy were higher (all P<0.05) and the percentage of those who had quit smoking were higher ( P<0.05); the percentage of IgE above normal thresholds, the level of IgE, the percentage of peripheral blood eosinophil (EOS%), the count of EOS, and fractional exhaled nitric oxide (FeNO) were higher (all P<0.05), and the percentage of those who had severe and above severe Global Strategy for the Diagnosis, Management, and Prevention of COPD (GOLD) pulmonary function classification were higher, while the percentage of forced expiratory volume in one second (FEV 1% predicted), 25% maximal expiratory flow (MEF 25%) and MEF 75/25% were lower, and FEV 1/FVC was higher (all P<0.05). The positive SIgE COPD group had higher modified British medical research council (mMRC) scores and COPD assessment test (CAT) scores, and a higher incidence of severe acute exacerbation events over the past year (all P<0.05), and the use of short-acting β 2 receptor agonists (SABA) or short-acting muscarinic antagonist (SAMA), inhaled corticosteroid (ICS), theophylline and oral hormone therapy were more frequent (all P<0.05). EOS% ( OR=1.252, 95% CI: 1.039-1.508) was a risk factor for SIgE positivity in COPD ( P<0.05), and having quit smoking ( OR=0.385, 95% CI: 0.197-0.751) was a protective factor ( P<0.05). The AUC value of the ROC curve of EOS%>2.5% for the diagnosis of SIgE positivity was 0.647 (95% CI: 0.543-0.752), with a sensitivity and specificity of 52.8% and 73.1%, respectively. Conclusions:Positive SIgE COPD has sever clinical symptoms, high risk of acute exacerbation and deficiencies in treatment. The elevate of EOS% is a risk factor for the development of positive SIgE in COPD patients; positive SIgE COPD meets the diagnostic criteria for allergic COPD phenotype, and EOS% over 2.5% is suggestive of the clinical detection of allergic COPD phenotype.

Objective:To compare the diagnostic efficacy of 22 G fine needle aspiration (FNA) needles and 22 G end-cutting fine needle biopsy (FNB) needles for solid pancreatic lesion using both cytological and histological examination.Methods:Clinical data of 116 patients who underwent endoscopic ultrasound-guided fine needle aspiration/biopsy (EUS-FNA/FNB) at the Digestive Endoscopy Center of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from June 2022 to March 2023 were retrospectively analyzed. Sixty-three patients sampled with 22 G FNA needles were the FNA group, and 53 sampled with 22 G FNB needles were the FNB group. The diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and cytological and histological diagnostic yield of FNA needles and FNB needles for solid pancreatic lesions were compared.Results:There were no significant differences in age, gender, lesion location, lesion size, or the number of passes between the FNA group and the FNB group ( P>0.05). There were no significant differences in the diagnostic accuracy [93.7% (59/63) VS 90.6% (48/53), P=0.730], sensitivity [93.0% (53/57) VS 90.2% (46/51), P=0.732], specificity [100.0% (6/6) VS 100.0% (2/2), P=1.000], positive predictive value [100.0% (53/53) VS 100.0% (46/46), P=1.000] and negative predictive value [60.0% (6/10) VS 28.6% (2/7), P=0.335] of combined cytology and histology in distinguishing benign and malignant lesions between the two groups. In the FNA group, the diagnostic accuracy of combined cytology and histology was higher than cytology alone [93.7% (59/63) VS 81.0% (51/63), P=0.008], and was higher than histology alone without statistical significance [93.7% (59/63) VS 87.3% (55/63), P=0.125]. In the FNB group, the diagnostic accuracy of combined cytology and histology was higher than cytology alone [90.6% (48/53) VS 69.8% (37/53), P=0.001], but not than histology alone [90.6% (48/53) VS 90.6% (48/53)， P=1.000]. For solid masses located in pancreatic body/tail, the diagnostic accuracy for malignancy by histology using FNB needles tended to be higher than that of FNA needles [100.0% (17/17) VS 81.3% (26/32), P=0.080]. Conclusion:Both FNA needles and FNB needles exhibit adequate diagnostic yield for solid pancreatic masses when combining cytology and histology. FNB needles may offer a higher histological diagnostic yield.