Technology and Health Care最新文献

ObjectiveThis study aims to enhance cybersecurity by implementing a robust biometric-based authentication approach. A Multimodal Biometric System (MBS) is proposed, utilizing feature-level fusion of human facial (physiological) and speech (behavioral) features to improve security, accuracy, and user convenience. The system addresses the limitations of traditional authentication methods, including unimodal biometrics and password-based security.BackgroundIn the modern digital landscape, human-computer interaction and digital platforms play a crucial role in daily life. With billions of users engaging in social media, financial transactions, and e-commerce, the demand for secure authentication mechanisms has intensified. However, the increasing sophistication of cyber threats poses significant risks, undermining trust, security, and confidence in digital systems.Method: The proposed MBS incorporates improved proposed techniques for feature extraction, feature level fusion strategies and an ensemble classification model combining Bi-LSTM and DCNN. To optimize performance, the system is enhanced using an improved bio-inspired Manta Ray Foraging Optimization (MRFO) algorithm.ResultsThe system's performance was evaluated using two publicly available Voxceleb1 and VidTIMIT datasets, achieving accuracy rates of 98.23% and 97.92%, with Equal Error Rates (EERs) of 3.23% and 3.62%, respectively.ConclusionThe proposed approach outperforms conventional optimization techniques and existing state-of-the-art MBS. As a contactless and non-intrusive authentication system, it enables seamless data acquisition through devices equipped with cameras and microphones, such as smartphones, ensuring real-time processing of biometric modalities.Application: This contactless MBS presents a viable solution for secure and hygienic authentication in applications requiring high cyber resilience, including banking, e-commerce and other digital security domains.Precis/Table of Contents: This research enhances cybersecurity by proposing a Multimodal Biometric System (MBS) that integrates feature-level fusion of facial (physiological) and speech (behavioral) traits. The approach improves security, accuracy, and user convenience while addressing hygiene concerns. It overcomes the limitations of traditional authentication methods, including unimodal biometrics and password-based security vulnerabilities.

BackgroundTargeted regulation of drug-resistant gene expression through lncRNA has emerged as a novel research direction for overcoming immune resistance in osteosarcoma. However, the specific effects and regulatory mechanisms of lncRNA-TIL1H on immune resistance in osteosarcoma remain unclear.ObjectiveTo explore the mechanism by which lncRNA-TIL1H targets the regulation of the drug-resistant genes MDR1 and RAD21.MethodsClinical samples including osteosarcoma tissues and adjacent tissues were collected for qPCR and WB analysis of lncRNA-TIL1H expression as well as MDR1 and RAD21. Acquisition of drug-resistant osteosarcoma cells by cisplatin treatment MG-63/R. The cells were divided into four groups: MG-63, MG-63/R, si-NC-MG-63/R, and si-TIL1H-MG-63/R group. Cell proliferation and colony formation, and migration and invasion were detected by CCK-8, Transwell and scratch assays. In addition, the effects on osteosarcoma after interfering with lncRNA-TIL1H were further explored by the animal experiments, including HE staining and immunohistochemistry.ResultsThe expression of lncRNA-TIL1H and the drug-resistant genes MDR1 and RAD21 significantly increased in osteosarcoma. si-TIL1H effectively inhibited cell proliferation, invasion, migration and decreased the expression of drug-resistant genes in MG-63/R. Finally, the animal experiments revealed that si-lncRNA-TIL1H inhibited tumor proliferation.ConclusionThe expression of lncRNA-TIL1H in MG-63/R promotes the upregulation of drug-resistant genes MDR1 and RAD21, leading to the occurrence of immune resistance and accelerating osteosarcoma progression.

BackgroundRadiotherapy has become a fundamental treatment modality of head and neck (HN) malignancies, which provides a chance of long-term survival. However, radiation also amplifies the risk of developing radiation-induced sarcoma (RIS) in the irradiated tissue. Radiation-induced maxillary sinus sarcoma (RIMSS) is an extremely rare and highly lethal malignancy of the HN. RIS is mainly treated with surgery, but the anatomical district and the infiltrative nature of RIS make it challenging to achieve negative margins, resulting in high fatality rate with the mean survival time of approximately one year. Immunotherapy, as an effective treatment option is rapidly evolving for HN tumors. However, checkpoint Blockade Immunotherapy (CBI) combined with chemotherapy as maintenance therapy for RIS of HN is rarely reported.Case presentationThe study presents a 36-year-old female with numerous recurrences of RIMSS, who experienced a dramatic response to checkpoint blockade immunotherapy after rapidly progressing on involved-field radiotherapy and multiple surgeries. After using immunotherapy combined with chemotherapy, the patient had a nearly complete response (CR) and maintained with single-agent programmed cell death 1 (PD-1) inhibitors.ResultsThe patient achieved a durable response, with progression-free survival (PFS) lasting 18 months.ConclusionUsing CBI as maintenance therapy for RIMSS represents a novel treatment option, especially for unresectable patients. Further investigation is warranted to optimize a multimodal treatment and improve response.

BackgroundCow's milk protein allergy (CMPA) is a common food allergy in children, affecting growth, development, and quality of life. The pathogenesis involves immune dysregulation, particularly CD4+ T lymphocyte subsets, which play a key role in immune responses. The JAK2-STAT3 signaling pathway is critical for immune cell regulation, but its role in CMPA-associated immune changes remains unclear.MethodsA total of 103 CMPA patients and 100 healthy controls were enrolled. Peripheral blood samples were collected from patients before and after a 3-month CMPA avoidance diet. Flow cytometry, ELISA, western blotting, and qRT-PCR were used to analyze CD4+ T cell subsets (Th1, Th2, Th17), cytokine levels, and JAK2-STAT3 pathway activity.ResultsCMPA patients exhibited increased Th2 and Th17 proportions and reduced Th1 cells compared to controls. JAK2 and STAT3 phosphorylation levels were elevated, while SOCS1/SOCS3 expression was downregulated. After dietary avoidance, Th2 and Th17 proportions decreased, Th1 increased, and JAK2-STAT3 activation normalized. Pearson correlation analysis revealed positive associations between JAK2-STAT3 activation and Th2/Th17 proportions and a negative correlation with Th1.ConclusionsThe JAK2-STAT3 signaling pathway is abnormally activated in CMPA and correlates with CD4+ T lymphocyte subset imbalances. Targeting this pathway may offer therapeutic potential for CMPA management.

Background and ObjectiveBudd-Chiari syndrome (BCS) presents challenges in postoperative restenosis risk prediction due to unclear hemodynamic pathophysiology. Despite advances in interventional therapies, tools linking hemodynamic abnormalities to vascular remodeling are lacking. This study aimed to evaluate hemodynamic changes in BCS patients with inferior vena cava (IVC) stenosis using patient-specific MRI and computational fluid dynamics (CFD) to establish predictive biomarkers and optimize management.Methods3D IVC models were reconstructed from preoperative, postoperative, and healthy control MRI data. Dynamic hemodynamic parameters, including flow velocity, pressure gradients, wall shear stress (WSS), and vortex patterns, were analyzed via CFD simulations under physiologically accurate boundary conditions.ResultsPreoperative IVC stenosis caused severe disturbances. Post-intervention, parameters decreased (e.g., peak stenotic velocity from 1.91 m/s to 0.97 m/s; trans-stenotic pressure gradient from 3562 Pa to 1404 Pa) but remained higher than normal (peak velocity: 0.27 m/s; pressure fluctuation: Δ1225 Pa). Persistent vortices near stent edges and incomplete pressure normalization were observed, correlating with restenosis incidence. These findings highlight unresolved WSS (post-op peak WSS: 18.2 Pa vs normal: 6.18 Pa) and abnormal flow dynamics (e.g., prolonged vortex duration) as key recurrence risks.ConclusionThis study provides a hemodynamic framework for BCS, showing that intervention alleviates stenosis but doesn't restore normal flow. Residual stress emphasizes the need for adjunct therapies. The CFD approach offers predictive insights, advocating personalized monitoring for improved BCS outcomes.

BackgroundIn clinical diagnosis, determining the level of malignancy in tumors and differentiating between benign and malignant tumors are common classification challenges. Accurate and early diagnosis is essential for targeted treatment, and machine learning methods can assist in making these judgments.MethodsThis paper focuses on the classification of the lung tissue as benign or malignant and assessing the degree of aggressiveness in lung cancer. The study employed artificial neural network (ANN), logistic regression, and ridge penalized logistic regression, which are methods without built-in feature selection. Additionally, lasso penalized logistic regression, elastic-net penalized logistic regression, and sparse logistic regression with the hybrid L1/2 + 2 regularization (HLR), which are methods with built-in feature selection, were also utilized.ResultsIn the study on classifying benign and malignant lung tissue, ANN demonstrated the best predictive performance among the methods without built-in feature selection, achieving an average test accuracy of 91.82%. Among the methods with built-in feature selection, HLR outperformed the others with an average test accuracy of 96.67%. When determining the level of malignancy in lung tumors, ANN surpassed other methods without built-in feature selection, attaining an average test accuracy of 84.74%. In comparison, HLR exceeded the performance of other methods with built-in feature selection, reaching an average test accuracy of 93.33%.ConclusionsThe experimental results indicated that HLR with built-in feature selection and ANN without built-in feature selection exhibited strong competitiveness among the methods investigated in both classifying benign and malignant lung tissue and assessing the degree of aggressiveness in lung cancer.

BackgroundChemotherapy-induced nausea and vomiting (CINV) remains a prevalent and debilitating side effect of cancer treatment with limited therapeutic options. Dingxiang Shidi Decoction (DXSD), a classical Chinese herbal formula, has demonstrated clinical efficacy in CINV management. However, its active components and mechanism of action require systematic investigation.ObjectiveThis study aims to elucidate the pharmacologically active constituents of DXSD and their anti-CINV mechanisms.MethodsWe employed advanced analytical techniques including UPLC-MS/MS and GC-MS to analyze the chemical components of DXSD. Network pharmacology techniques were applied to explore its pharmacological mechanisms. And molecular docking simulation was conducted to further refine the drug-target interaction.ResultsA total of 292 chemical compounds were identified in DXSD, comprising 165 water-soluble components, 56 volatile components, and 84 network database entries. By integrating 564 drug targets with 888 CINV disease targets, we identified 143 potential therapeutic targets. Further protein-protein interaction (PPI) network analysis revealed 12 key active ingredients and 13 key therapeutic targets. Enrichment analysis suggested that DXSD may reduce inflammation, modulate neurotransmitter stimulation in the gastrointestinal tract, and regulate cellular proliferation and differentiation. Notably, key active ingredients, predominantly aromatic compounds such as sabinene, (-)-α-cubebene, α-copaene, β-caryophyllene, aromandendrene, γ-muurolene, (-)-α-muurolene, α-phellandrene, α-terpinene, γ-terpinene, (+)-δ-cadinene, and Gomisin B, demonstrated significant binding affinity with multiple targets, particularly AKT1, BCL2, EGFR, MTOR, and STAT3.ConclusionsThis study reveals the active components and therapeutic mechanisms of DXSD against CINV, supporting its clinical application and demonstrating the potential of aromatherapy as an effective treatment strategy.

BackgroundInsomnia is a prevalent global health issue that significantly impacts quality of life and poses a substantial economic burden. While conventional pharmacological and non-pharmacological treatments exist, they are often limited by side effects, dependency, or low clinical applicability. Guasha therapy, a traditional Chinese medicine nursing technique, shows promise for treating insomnia, but lacks standardized, evidence-based guidelines for its clinical application.ObjectiveTo analyze the regularity of meridian and acupoint selection in the treatment of insomnia with scraping therapy by using data mining technology.MethodsA computer-based search of PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform, Weipu Database(VIP), and Chinese Biomedical Literature Database (CBM) was conducted to retrieve the literature on scraping therapy for insomnia from the establishment of the database to March 15,2024.Excel was used to establish a database of acupoints for scraping therapy for insomnia, and the frequency of acupoints and meridians and the meridian tropism of acupoints were analyzed. SPSS 26.0 was used to cluster the high-frequency acupoints. The Apriori algorithm model provided by SPSS Modeler 18.0 was used to analyze the association rules of acupoint compatibility. Cytoscape 3.10.1 software was used to construct a complex network of meridian compatibility, and to analyze the core meridian of scraping in the treatment of insomnia.ResultsA total of 119 literatures were finally included, including 144 acupoints, with a total of 1121 frequencies. The most commonly used acupoints were Xinshu (BL15), Baihui (GV20), and Shenmen (HT7), and the commonly used compatibility acupoints were Xinshu-Pishu (BL20) and Xinshu-Pishu-Shenmen. The main meridians are Bladder meridian of foot-taiyang, Governor vessel, Gallbladder meridian of foot-shaoyang and Heart meridian of hand-shaoyin, which are the core meridian routes.ConclusionsData mining can effectively analyze the commonly used acupoints, acupoint compatibility rules and meridian rules of Gua Sha in the treatment of insomnia. The analysis results align with the traditional Chinese medicine principle of primarily following meridians, combining syndrome and root, enhancing the treatment effectiveness of insomnia, and providing a reference for clinical practice and research.

BackgroundUnderstanding patients' psychological, anatomical, and functional needs helps clinicians identify issues affecting smile aesthetics, improving orthodontic outcomes and quality of life.ObjectivesThis review examined laypeople's esthetic perceptions of malocclusion and orthodontic appliances via eye-tracking technology, considering gender and professional background influences.MethodsA systematic search was conducted in PubMed, Web of Science, Ovid MEDLINE, and ProQuest. Risk of bias (RoB) was assessed using the Joanna Briggs Institute tools. Data on eye fixation metrics and subjective ratings were descriptively synthesized.ResultsAmong 7009 studies, 27 met inclusion criteria (11 high, 10 moderate, and 6 low RoB) with variable methodologies. Ethnic and cultural factors were rarely considered. The eyes received the most attention in facial aesthetics. However, severe malocclusion and orthodontic appliances redirected gaze to the mouth, while attractive facial features mitigated this effect. Laypeople were more tolerant of malocclusion than dental professionals, who were more sensitive to malocclusion deviations. Facial esthetic perception revealed gender-related differences, where females focusing more on the eyes and males on the mouth and nose.ConclusionsMalocclusion and orthodontic appliances affect esthetic perception by altering gaze patterns. Integrating eye-tracking technology into orthodontic practice can improve patient satisfaction by aligning treatments with esthetic expectations.

BackgroundAtrial fibrillation (AF) is a common complication of acute myocardial infarction (AMI), significantly affecting patient prognosis by increasing the risk of heart failure, thromboembolic events, and mortality.ObjectiveTo explore the risk factors of AM combined with first-diagnosed AF.MethodsClinical data related to a total of 142 consecutive AMI patients admitted to Beijing Tongren Hospital from January 1, 2020 to May 1, 2020 were retrospectively analyzed, of whom 8 cases (5.6%) were divided into first-diagnosed AF group and the rest 134 cases were in non-first-diagnosed AF group according to the presence or absence of first-diagnosed AF. Clinical data, laboratory indexes, cardiac ultrasonography and coronary angiography results of the two groups were compared. Logistic regression method was used to analyze the possible risk factors offirst-diagnosed AF.ResultsComparing the various data between the two groups, the peak creatinine kinase myocardial band (CKMB), white blood cell count, left ventricular ejection fraction, and the proportion of patients with admission Killip grades 3-4 in the first-diagnosed AF group were significantly different from those in the non- first-diagnosed AF group (p < 0.05); the results of logistic multifactorial regression analysis showed that admission Killip grades 3-4 was an independent risk factor for first-diagnosed AF in patients with AMI (OR = 9.549, 95% CI: 1.697-53.737, p = 0.01).ConclusionPatients with AMI and Killip grade 3-4 face a heightened risk of developing atrial fibrillation. Close clinical observation, including ECG monitoring, is essential for early atrial fibrillation detection. Given the limitations of the current study, such as small sample size in single center, small number of AF events, the retrospective design, the validity and reliability of the research findings are constrained.