Objective To explore an artificial intelligence (AI)-based method for automated hand hygiene monitoring and to compare the effectiveness of three algorithms (UniFormerV2, TDN, C3D) in recognizing hand hygiene steps in surgical settings, thereby aiding hospital infection control. Methods From April to October 2024, we non-invasively collected 641 video recordings of healthcare staff performing hand hygiene at four-bay scrub sinks in two tertiary hospitals using overhead HD cameras. The dataset was annotated by five trained experts for model training and validation. Results Following training on 385 samples, internal validation (n=119) showed the C3D model achieved 81% accuracy, 87% recall, and an 83% F1-score. The TDN model achieved 93%, 91%, and 92% for the same metrics. The UniFormerV2 model outperformed both, with an accuracy, recall, and F1-score of 93%—an improvement of over 10 percentage points compared to traditional CNNs (TDN, C3D). It also achieved an 84% accuracy in external validation, demonstrating strong generalization. Conclusion The UniFormerV2 model is more accurate than CNN-based models for hand hygiene step recognition and shows robust performance in external validation. It presents a viable tool for healthcare facilities to enhance hand hygiene management, ultimately improving medical quality and patient safety.

To improve the targeted therapeutic effect of magnolol (Mag) on neuroblastoma, Mag-loaded mitochondria-targeting immunoliposomes modified by datuximab (aGD2) and triphenylphosphine (TPP) (Mag/aGD2-T-ILN) were prepared, and their physicochemical properties, targeting characteristics and anti-tumor activity were evaluated. Physico-chemical properties showed that the surface of Mag/aGD2-T-ILN was smooth and spherical, with good dispersibility. The particle sizes, PDI and Zeta potentials of Mag/aGD2-T-ILN were measured to be (136.5 ± 5.1) nm, 0.184 ± 0.010 and (27.5 ± 3.6) mV, respectively. Mag/aGD2-T-ILN could release the drug continuously and slowly, and maintain good stability at 4 ℃. Cytotoxicity test exhibited that the IC50 of 2-ME/aGD2-T-ILN was (4.07 ± 0.48) µmol/L, and compared with free Mag, the toxicity of Mag/aGD2-T-ILN to SH-SY5Y cells increased by 6.4 times. Cellular binding and uptake assays suggested that Rho-aGD2-T-ILN could specifically target GD2-positive tumor cells and then further reach their mitochondria. Therapeutic efficacy indicated that Mag/aGD2-T-ILN could better suppress the growth of SH-SY5Y tumor cells in the body with lower toxicity and less side-effects. The results demonstrated that the Mag/aGD2-T-ILN nanoparticles system could achieve intracellular endocytosis through specific binding of antibodies and antigens between the carrier and the surface of tumor cells and electrostatic interaction, then effectively delivered and released the drugs into mitochondria by crossing the mitochondrial phospholipid membrane through TPP, and thus achieving mitochondria-targeting therapy of Mag/aGD2-T-ILN. Through the construction of this active targeting delivery system, the clinical application value of datuximab and Mag is improved, providing a novel approach for the clinical treatment of neuroblastoma.

ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

ObjectiveTo investigate the effects of modified Xiaoyaosan （JJXYS） on behavioral abnormalities and hippocampal mitochondrial quality control （MQC） in the rat model of post-myocardial infarction depression （PMD） and preliminarily explore its potential mechanism. MethodsA rat model of PMD was established by left anterior descending coronary artery ligation combined with chronic unpredictable mild stress （CUMS）. Rats were randomized into a control group， a model group， a fluoxetine （FLX， 10 mg·kg^-1） group， and low-， medium-， and high-dose JJXYS （JJXYS-L/M/H， 1.12， 2.24， 4.48 g·kg^-1， respectively） groups. Depressive-like behaviors were evaluated by body weight monitoring， sucrose preference test， open field test， and forced swimming test. Hematoxylin-eosin staining and Nissl staining were used to observe hippocampal histomorphology and neuronal changes. Enzyme-linked immunosorbent assay was conducted to determine the serum levels of 5-hydroxytryptamine （5-HT）， dopamine （DA）， interleukin-1 beta （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α）. The mRNA levels of MQC-related genes including peroxisome proliferator-activated receptor-gamma coactivator-1 alpha （PGC-1α）， nuclear respiratory factor 1 （Nrf1）， and transcription factor A， mitochondrial （TFAM） in the hippocampal tissue were measured by real-time PCR. The expression of proteins related to the dynamin-related protein 1 （Drp1）/PTEN-induced putative kinase 1 （PINK1）/Parkin signaling pathway was determined by Western blot. ResultsCompared with the control group， the model group showed restricted body weight gain， aggravated depressive-like behaviors， declined serum 5-HT and DA levels， evident hippocampal neuronal damage and reduced Nissl bodies， as well as downregulated expression of MQC-related genes and proteins （P<0.05）. Compared with the model group， both FLX and JJXYS alleviated the above changes to varying degrees. Moreover， the JJXYS-M and JJXYS-H groups showed more pronounced effects， improving behavioral performance， restoring 5-HT and DA levels， alleviating hippocampal pathological injury， and upregulating the expression of PGC-1α/Nrf1/TFAM mRNA and Drp1/PINK1/Parkin signaling pathway-related proteins （P<0.05）. ConclusionJJXYS can significantly alleviate depressive-like behaviors and neurotransmitter imbalance in the rat model of PMD by regulating hippocampal MQC and upregulating the Drp1/PINK1/Parkin-related pathway. This study provides experimental evidence for the intervention of PMD with JJXYS.

Background As a traditional labor-intensive industry, the wooden furniture manufacturing sector has been facing significant occupational health hazards, notably noise exposure. Objective To understand the current status of occupational health management and workplace noise monitoring in the wooden furniture manufacturing industry in Foshan City of Guangzhou Province over the past five years (2020−2024), to clarify the exposure level of occupational noise hazards in this industry, the implementation of prevention and control measures, and their dynamic changing trends, and to provid a reference basis for formulating and optimizing targeted occupational health supervision strategies. Methods By judgment sampling method, 381 wooden furniture manufacturing enterprises in Foshan City from 2020 to 2024 were selected. Through document review, on-site investigation, and on-site testing, the basic information of the enterprise, key indicators of occupational health management (declaration of projects with occupational disease hazards, occupational health training, the setting and effect of occupational disease prevention facilities, the allocation and use of personal protective equipment, occupational health examinations, etc.) and monitoring data of noise intensity in the workplace were systematically collected. Descriptive statistical analysis was adopted to present the characteristics of enterprises and various indicators, and trend tests were used for dynamic changes of occupational health management indicators and noise intensity monitoring results between each year. Results Among the 381 enterprises, small and micro enterprises accounted for 94.0% (358/381), the overall occupational hazard exposure rate of workers was 56.7% (15199/26798), and the noise exposure rate was 45.6% (12221/26798). The report rate of projects with occupational disease hazards was 100%, the occupational health training rate of exposed workers was 69.6%, the setting rate and effectiveness rate of noise prevention facilities were 24.9% and 95.8% respectively, the distribution rate and effective wearing rate of noise protection earplugs/earmuffs were 77.6% and 87.1% respectively, and the rate of occupational health examinations for noise-exposed workers and the abnormal rate were 55.4% and 2.5% respectively. The trend analysis results showed that the rates of occupational health training, setting and effectiveness of noise prevention facilities, distribution and effective wearing of noise protection earplugs/earmuffs, occupational health examinations for noise-exposed workers, and abnormal health examination results all showed an overall upward trend (P values were all<0.05). The proportion of workplace noise intensity greater than 85 dB(A) and the rate of noise exceeding standards at work positions both showed an overall upward trend (P values were both<0.01). Conclusion During the period from 2020 to 2024, the occupational health management in the wooden furniture manufacturing industry in Foshan City has achieved certain positive progress, particularly in areas such as the installation of protective facilities, the use of personal protective equipment, and the implementation of occupational health examinations. However, workplace noise hazards have not been effectively controlled. Moving forward, regulatory efforts must consolidate existing management achievements while strengthening mandatory requirements and support for the technical transformation of high-noise processes and the widespread adoption of noise reduction facilities. This approach is essential to fundamentally curb occupational noise hazards.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective To explore the risk factors for portal vein thrombosis(PVT)in patients with cirrhosis in the decompensated stage and construct a risk prediction model for PVT so as to improve the early diagnosis rate of decompensated liver cirrhosis PVT.Methods The clinical data of patients with cirrhosis in the decompensated stage admitted to Department of Gastroenterology,The First Affiliated Hospital of Xi'an Jiaotong University between June 2018 and June 2023 were collected and divided into cirrhosis PVT group(n=135)and cirrhosis non-PVT group(n=225)according to whether or not portal vein thrombosis was formed.We made a univariate analysis of the general data,laboratory indexes,liver function scores and imaging findings of the patients in the two groups,and indexes with statistically significant differences were included in binary Logistic regression for multifactorial analysis to screen out independent risk factors.A predictive model of binary Logistic regression was established based on the independent risk factors.The clinical data of the validation set were incorporated into the model,the accuracy of the prediction model was evaluated by receiver operating curve(ROC),and the practicability of the model was evaluated by consistency curve to complete the validation and evaluation of the constructed prediction model.Internal stability of the model was verified with Bootstrap method.Finally,R software(4.3.1)was used to draw a nomogram of the prediction model to visualize the model.Results Univariate analysis revealed statistically significant differences between patients in the PVT and non-PVT groups in the following five aspects:history of splenectomy,history of endoscopic varicose vein treatment,portal vein diameter,and neutrophil-to-lymphocyte ratio(P＜0.05).Binary Logistics regression analysis showed that a history of splenectomy(P=0.002,OR=3.012,95％CI:1.500-6.047),a history of endoscopic varicose vein treatment(P=0.001,OR=2.276,95％CI:1.400-3.698),widening of portal vein diameter(P=0.007,OR=1.942,95％CI:1.202-3.136),increased neutrophil-to-lymphocyte ratio(P=0.009,OR=1.886,95％CI:1.170-3.041),and elevated D-dimer(P＜0.001,OR=3.725,95％CI:2.149-6.485)were independent risk factors for the formation of portal vein thrombosis in patients with cirrhosis in the decompensated stage of cirrhosis chemically presented(P＜0.05).The area under the ROC curve of the predictive model and the model after internal validation was 0.760 and 0.7494,respectively.The model still had good prediction ability and accuracy in the verification set.Conclusion A history of splenectomy,history of endoscopic varicose vein treatment,widening of portal vein diameter,increased neutrophil-to-lymphocyte ratio,and elevated D-dimer concentration are independent risk factors for the formation of portal vein thrombosis in patients with decompensated cirrhosis.The Logistic prediction model and visual nomogram constructed based on the above independent risk factors have a good ability to predict the occurrence of PVT in patients with decompensated cirrhosis and have important clinical guiding significance for early screening patients with PVT in decompensated cirrhosis.

Objective To construct an XGBoost predictive model using clinical characteristic data from patients with chronic obstructive pulmonary disease(COPD)and evaluate the efficacy of the predictive model in early risk prediction of lung cancer occurrence in COPD patients.Methods In this retrospective cross-sectional study,cluster sampling was used.We selected clinically diagnosed COPD patients admitted to The Second Affiliated Hospital of Xi'an Jiaotong University from January 1,2018,to December 31,2022.A total of 4 008 patients with complete data were included.First,the baseline of each characteristic was analyzed,and then XGBoost was used to construct the lung cancer risk prediction model for COPD patients,and SHAP(SHapley Additive exPlanation)value was used to quantify and attribute the importance of each characteristic.DC A curve was used to evaluate the clinical application value.Results After constructing a lung cancer risk model for COPD patients using 28 variables,eight variables were selected according to the importance of the variables and clinical experience,and the prediction model was reconstructed.The model efficacy in the training set and the test set was 0.948(0.938,0.958)and 0.797(0.738,0.856),respectively.SHAP diagram showed that elevated CEA,CA125,FIB,eosinophils,PLT and D-dimer and reduced TT all contributed to an increased risk of lung cancer in COPD patients.DCA curve showed that the prediction model had clinical application value,which could help doctors make more accurate prognosis prediction and treatment decisions.Conclusion The successful establishment of an XGBoost predictive model,utilizing a subset of features,enables early prediction of lung cancer occurrence in COPD patients.