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Amid the rapid advancement of electronic information technology, the need for cable eccentricity measurement in the industry is increasing both in China and across the globe. Current detection methods have several flaws, including high costs, insufficient accuracy, and instability. In this paper, we introduce a magnetic field-based detection method for cable eccentricity that provides high precision and cost-effectiveness. We position three pairs of magnetic field-collection modules in a circular array to gather magnetic flux density information induced by the electrified cable. We apply the law of electromagnetic induction to calculate the cable eccentricity. Our method is non-contact, preserving the cable’s integrity. Our method outperforms traditional detection methods, not only in achieving greater accuracy and stability but also in significantly lowering the detection cost. Simulations and experiments show that our method’s error rate under specified conditions is 0~4%, with a maximum standard deviation of 0.11, confirming its precision and stability in detecting cable eccentricity. The effectiveness of our method is influenced by two factors: lift-off value and loading current intensity. Our method presents a novel concept and a dependable strategy for the progress of cable eccentricity-detection technology.

Lubricants are of key importance for mechanical processing, and exist in nearly every mechanical system. When the equipment is in operation, debris particles will be generated in mechanical lubricants. The detection of debris particles can indicate the wear degree of machinery components, and provide prognosis warning for the system before the fault occurs. In this work, a novel type of inductive debris sensor consisting of two excitation coils and two sensing coils is proposed for online debris monitoring. The developed sensor was proven to be of high sensitivity through experimental verification. The testing results show that, using the designed sensor, ferrous metal debris with a size of 115 μm and nonferrous metal debris with a size of 313 μm in a pipe with an inner diameter of 12.7 mm can be effectively detected. Moreover, the proposed inductive debris sensor structure has better sensitivity at higher throughput and its design provides a useful insight into the development of high-quality sensors with superior performances.

Intravenous infusion is an important clinical medical intervention, and its safety is critical to patient recovery. To mitigate the elevated risk of complications (e.g., air embolism) arising from delayed response to infusion endpoints, this paper designs a flexible double pole capacitive (FPB) sensor, which includes a main pole plate, an adaptive pole plate, and a back shielding electrode. The sensor establishes a mapping between residual liquid volume in the infusion bottle and its equivalent capacitance, enabling a non-contact adaptive monitoring system. The system enables precise quantification of residual liquid levels, suppressing baseline drift induced by environmental temperature/humidity fluctuations and container variations via an adaptive algorithm, without requiring manual calibration, and overcomes the limitations of traditional rigid sensors when adapting to curved containers. Experimental results showed that the system achieved an overall sensitivity of 753.5 fF/mm, main pole plate linearity of 1.99%, and adaptive pole plate linearity of 0.53% across different test subjects, linearity of 0.53% across different test subjects, with liquid level resolution accuracy reaching 1 mm. These results validate the system’s ultra-high resolution (1 mm) and robust adaptability.

Lung adenocarcinoma (LUAD) is one of the most widespread and fatal types of lung cancer. Oxidative stress, resulting from an imbalance in the production and accumulation of reactive oxygen species (ROS), is considered a promising therapeutic target for cancer treatment. Currently, immune checkpoint blockade (ICB) therapy is being explored as a potentially effective treatment for early-stage LUAD. In this research, we aim to identify distinct subtypes of LUAD patients by investigating genes associated with oxidative stress and immunotherapy. Additionally, we aim to propose subtype-specific therapeutic strategies. We conducted a thorough search of the Gene Expression Omnibus (GEO) datasets. From this search, we pinpointed datasets that contained both expression data and survival information. We selected genes associated with oxidative stress and immunotherapy using keyword searches on GeneCards. We then combined expression data of LUAD samples from both The Cancer Genome Atlas (TCGA) and 11 GEO datasets, forming a unified dataset. This dataset was subsequently divided into two subsets, Dataset_Training and Dataset_Testing, using a random bifurcation method, with each subset containing 50% of the data. We applied consensus clustering (CC) analysis to identify distinct LUAD subtypes within the Dataset_Training. Molecular variances associated with oxidative stress levels, the tumor microenvironment (TME), and immune checkpoint genes (ICGs) were then investigated among these subtypes. Employing feature selection combined with machine learning techniques, we constructed models that achieved the highest accuracy levels. We validated the identified subtypes and models from Dataset_Training using Dataset_Testing. A hub gene with the highest importance values in the machine learning model was identified. We then utilized virtual screening to discover potential compounds targeting this hub gene. In the unified dataset, we integrated 2,154 LUAD samples from TCGA-LUAD and 11 GEO datasets. We specifically selected 1,311 genes associated with immune and oxidative stress processes. The expression data of these genes were then employed for subtype identification through CC analysis. Within Dataset_Training, two distinct subtypes emerged, each marked by different levels of immune and oxidative stress pathway values. Consequently, we named these as the OX + and IM + subtypes. Notably, the OX + subtype showed increased oxidative stress levels, correlating with a worse prognosis than the IM + subtype. Conversely, the IM + subtype demonstrated enhanced levels of immune pathways, immune cells, and ICGs compared to the OX + subtype. We reconfirmed these findings in Dataset_Testing. Through gene selection, we identified an optimal combination of 12 genes for predicting LUAD subtypes: ACP1, AURKA, BIRC5, CYC1, GSTP1, HSPD1, HSPE1, MDH2, MRPL13, NDUFS1, SNRPD1, and SORD. Out of the four machine learning models we tested, the support vector machine (SVM) stood out, achieving the highest area under the curve (AUC) of 0.86 and an accuracy of 0.78 on Dataset_Testing. We focused on HSPE1, which was designated as the hub gene due to its paramount importance in the SVM model, and computed the docking structures for four compounds: ZINC3978005 (Dihydroergotamine), ZINC52955754 (Ergotamine), ZINC150588351 (Elbasvir), and ZINC242548690 (Digoxin). Our study identified two subtypes of LUAD patients based on oxidative stress and immunotherapy-related genes. Our findings provided subtype-specific therapeutic strategies.

Family caregiver self-efficacy plays an important role in improving the health and quality of life of patients in the early post-coronary artery bypass grafting (CABG). However, there is a lack of targeted self-efficacy assessment tool for caregivers of patients. Thus, the purpose of this study was to develop a Family Caregiver Self-Efficacy Scale for patients in the early post-CABG (FCSES-EPCABG) and to test its reliability and validity. Based on self-efficacy theory, the initial scale was formed by the literature review, semi-structured interviews, Delphi expert consultation, and pre-survey. Through the convenience sampling method, 133 caregivers who met the selection criteria were chosen for the questionnaire survey at Wuhan Asian Heart Hospital from January 2024 to May 2024. The aim was to test the reliability and validity of the scale. The final scale contained five dimensions of wound care, medication management, cardiac rehabilitation management, social support, and self-care, with a total of 22 items. The item-level content validity index ranged from 0.889 to 1.000, the scale-level content validity index/average was 0.985, and the content validity ratio ranged from 0.778 to 1.000. The exploratory factor analysis showed that the cumulative variance contribution rate of the five dimensions was 69.433%. In the criterion-related validity analysis, the total score of the FCSES-EPCABG was positively correlated with the total score of the General Self-Efficacy Scale (r = 0.762, P<0.001). The Cronbach's alpha coefficient of the scale was 0.919, the half reliability was 0.779, and the test-retest reliability was 0.936. The FCSES-EPCABG has satisfactory reliability and validity, which is suitable for evaluating the self-efficacy of family caregivers of patients in the early post-CABG.

IntroductionEndoscopic sinus surgery is an effective treatment for olfactory dysfunction related to chronic rhinosinusitis (CRS). However, recent studies have shown that most patients with CRS experience a return of olfactory function to preoperative levels within months to a year after surgery. Clinically, olfactory training after sinonasal surgery has been proven beneficial for olfactory recovery. The study aims to explore the effectiveness of olfactory training in treating postoperative olfactory dysfunction in patients with CRS after surgery. Additionally, conventional olfactory training (COT) devices have the drawback of insufficient deposition rates of odourants in the olfactory cleft, leading to poor treatment outcomes. This experiment employs a modified olfactory training (MOT) device based on respiratory pressure and compares its therapeutic effects with the COT device.Methods and analysisThis will be a randomised controlled trial. The aim is to investigate the effectiveness of olfactory training in treating postoperative olfactory dysfunction in patients with CRS and to compare the effects of MOT with COT. Participants will be randomly allocated in a 1:1:1 ratio to the MOT group, the COT group and the control group for 12 months. The primary outcome will be the change in the odour threshold, odour discrimination, odour identification and the total threshold, detection and identification score after 12 months of olfactory training. The secondary outcomes will include objective olfactory cleft assessment, the volumes of grey matter, white matter and cerebrospinal fluid, the volume and shape of the olfactory bulb, and the subjective olfactory assessment.Ethics and disseminationThis study protocol has been registered with ClinicalTrials.gov and has received approval from the Peking University Third Hospital Medical Science Research Ethics Committee. The results will be published in scientific peer-reviewed journals.Trial registration numberNCT06837051.

Background Gestational diabetes mellitus (GDM) is the most common medical complication associated with pregnancy, which may impose risks on both mother and fetus. Micro RNAs (miRNAs) and long noncoding RNAs (lncRNAs) are implied as vital regulators in GDM. A recent paper revealed dysregulation of miR-33a-5p in placental tissues of GDM patients. However, the biological function of miR-33a-5p in GDM remains elusive. This study focused on exploring the function and underlying mechanisms of miR-33a-5p in GDM. Methods 12 GDM pregnancies and 12 healthy pregnancies were enrolled in the study. INS-1 cell line was applied in in vitro experiments. The expression levels of miR-33a-5p, lnc-DANCR (Differentiation Antagonizing Non-Protein Coding RNA), and ABCA1 (ATP-binding cassette transporter 1) mRNA were determined by RT-qPCR assay. Glucose and insulin levels were measured by ELISA assay. Luciferase reporter assay and western blot assay were applied to validate the target of miR-33a-5p. Results miR-33a-5p was upregulated in the blood samples from GDM, and was positively correlated with blood glucose ( p  < 0.0001). Overexpression or inhibition of miR-33a-5p significantly inhibited or promoted cell growth and insulin production of INS-1 cells ( p  < 0.01). Furthermore, ABCA1 is a direct target of miR-33a-5p, and lnc-DANCR functions as a sponge for miR-33a-5p to antagonize the function of miR-33a-5p in INS-1 cells. Conclusion Our study demonstrated that lnc-DANCR-miR-33a-5p-ABCA1 signaling cascade plays a crucial role in the regulation of the cellular function of INS-1 cells.

Background During interprofessional clinical practice, compared to understanding of one’s own professional role and function, it might be more difficult to clarify the roles and contributions of the other health-care team members because of the inter-professional barrier. In order to provide students the opportunity for real experience with other professions in team environments and enhance their perceptions of other professions’ roles, this study developed a comprehensive and multi-dimension extracurricular interprofessional education (IPE) model through designing and integrating a profession-role exchange component, that was medical students as pharmacists or nurses, pharmacy students as physicians or nurses, and nursing students as physicians or pharmacists in the interprofessional health-care student team, into the service learning experience in a real community setting. Methods In this pre/post-intervention study, the effect of integrated profession-role exchange experiences on the students’ attitudes towards interprofessional collaboration and their role clarification was evaluated among 60 student volunteers (20 medical students, 20 pharmacy students and 20 nursing students). All involved students were divided into the profession-role exchange intervention group and the control group. Subjects in the control group did not participate the profession-role exchange experiences, the other IPE procedures were the same for both groups. Three survey instruments for attitudes toward interprofessional clinical collaboration were respectively used to measure the students’ attitudes toward physician-pharmacist, physician-nurse and nurse-pharmacist collaborations. “Roles and responsibilities” subscale of Readiness for Interprofessional Learning Scale was used to evaluate the overall role clarification during IPE. Results Compared to the control IPE activity, the addition of profession-role exchange component resulted in the significant increase in students’ positive attitudes towards interprofessional collaboration, and the enhancement of students’ role awareness. Conclusions The profession-role exchange might be more effective and better initiate students to the practice of interprofessional collaboration, and could be used as an effective IPE tool for improving the role awareness of health-care students.

Diabetic cardiomyopathy (DCM) is a condition characterized by myocardial dysfunction that occurs in individuals with diabetes, in the absence of coronary artery disease, valve disease, and other conventional cardiovascular risk factors such as hypertension and dyslipidemia. It is considered a significant and consequential complication of diabetes in the field of cardiovascular medicine. The primary pathological manifestations include myocardial hypertrophy, myocardial fibrosis, and impaired ventricular function, which can lead to widespread myocardial necrosis. Ultimately, this can progress to the development of heart failure, arrhythmias, and cardiogenic shock, with severe cases even resulting in sudden cardiac death. Despite several decades of both fundamental and clinical research conducted globally, there are currently no specific targeted therapies available for DCM in clinical practice, and the incidence and mortality rates of heart failure remain persistently high. Thus, this article provides an overview of the current treatment modalities and novel techniques pertaining to DCM, aiming to offer valuable insights and support to researchers dedicated to investigating this complex condition. Summary of treatment methods for diabetic cardiomyopathy.

Background To investigate whether clinically assessed mouth-breathing severity is independently associated with polysomnography–defined obstructive sleep apnea severity in children with adenoidal hypertrophy and/or tonsillar hypertrophy, and to evaluate its potential as a non-invasive predictor of moderate-to-severe obstructive sleep apnea. Methods We retrospectively analyzed pediatric inpatients admitted for planned adenotonsillectomy at Shanghai Sixth People’s Hospital. Based on a mouth-breathing score (range 1–7), patients were categorized into mild (scores 1–3) or severe (scores 4–7) mouth-breathing groups. Obstructive sleep apnea severity was classified as non-to-mild [obstructive apnea–hypopnea index ≤ 5 events/h] or moderate-to-severe (obstructive apnea–hypopnea index > 5 events/h). Demographic, clinical, and polysomnography parameters were compared. Correlation and logistic regression analyses were performed to identify independent predictors of moderate-to-severe condition, and the diagnostic performance of the predictive model was evaluated. Results Compared with mild mouth-breathing group, the severe group demonstrated significantly higher apnea–hypopnea index, obstructive apnea–hypopnea index, percentage of total sleep time with oxygen saturation < 90%, and lower mean oxygen saturation (all P  < 0.05). Mouth-breathing scores positively correlated with apnea–hypopnea index and obstructive apnea–hypopnea index (rho = 0.2173, 0.2102, P  < 0.0001). Multivariate analysis identified severe mouth-breathing scores (OR = 2.357; 95% CI, 1.354–4.101; P  = 0.002), female sex (OR = 0.602; 95% CI, 0.377–0.961; P  = 0.034), and tonsillar grade > II (OR = 1.820; 95% CI, 1.147–2.886; P  = 0.011) as independent predictors of moderate-to-severe diseases. The multivariable model yielded an AUC of 0.658. At the optimal cutoff defined by the Youden index (0.228), it demonstrated a sensitivity of 73.1%, a specificity of 49.6%, a positive predictive value (PPV) of 35.7%, and a negative predictive value (NPV) of 82.8%. In comparison, using a mouth-breathing score ≥ 4 as a standalone diagnostic criterion produced an AUC of 0.636, with corresponding sensitivity, specificity, PPV, and NPV of 82.4%, 35.5%, 32.8%, and 84.0%, respectively. Conclusions Mouth-breathing score was independently associated with the severity of obstructive sleep apnea in children with adenoidal hypertrophy and/or tonsillar hypertrophy. These findings indicate that structured mouth-breathing assessment may serve as a simple, non-invasive adjunct to clinical risk stratification for pediatric obstructive sleep apnea.