Search

Weixing Zhang,1 Zhangzhi Li,2 Muhammad Safwan Akram,3 Muhammad Fayyaz Ur Rehman,4 Nazeer Hussain Khan,5,6 Dan Hu,7 Muhammad Mustaqeem,8 Yuanyuan Zeng,1 Fariha Kanwal9 1Department of Critical Care Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, People’s Republic of China; 2Department of Hematology, Taihe Hospital, Hubei University of Medicine, Hubei, 442000, People’s Republic of China; 3School of Health and Life Sciences, Teesside University, Middlesbrough, TS1 3BX, UK; 4Institute of Chemistry, University of Sargodha, Sargodha, 40100, Pakistan; 5Henan International Key Laboratory of Nuclear Protein, School of Life Sciences, Henan University Kaifeng, Henan, 475004, People’s Republic of China; 6Laboratory of Animal and Human Physiology, Department of Biological Sciences, Quaid I Azam University, Islamabad, 45320, Pakistan; 7Department of Neurology, The Central Hospital of Xiaogan, Hubei, 432100, People’s Republic of China; 8Department of Chemistry, University of Sargodha, Sub Campus Bhakkar, Bhakkar, 30000, Pakistan; 9Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaCorrespondence: Fariha Kanwal; Yuanyuan Zeng Email fariha@sjtu.edu.cn; yuanyuanzeng@aliyun.comObjective: To evaluate the Li’s and Japanese scoring methods scoring for screening early gastric cancer in a healthy population.Methods: During January 2016–December 2018, profiles of the healthy people participated in a physical examination in the first people’s Hospital of Shanghai were collected. A total of 342 volunteers, including 137 males and 205 females ageing 40– 74, were enrolled. After recording the basic information, all volunteers were scored using the Japan scoring method and the new gastric cancer screening score (ie, Li’s score). The subjects’ work characteristics (ROC curve) were drawn according to the patient’s endoscopic pathological examination to indicate early gastric cancer, to determine the best cut-off point for the diagnosis of early gastric cancer by Japanese scoring and Li’s scoring, respectively. The sensitivity and specificity of both scoring methods were calculated as well.Results: The area under the ROC curve of Japanese and Li’s score, in the diagnosis of early gastric cancer, was 0.763 and 0.837, respectively. Japanese and Li’s score ≥ 14 were considered as the best cut-off point. The sensitivity and specificity of Li’s scoring were 63.60% and 91.10%, respectively. The sensitivity and specificity of the Japanese score were 54.50% and 87.50%, respectively. The area under the ROC curve in Li’s scoring is more significant than that in Japanese scoring, and there was a substantial difference in the two methods (P< 0.05).Conclusion: Both Li’s scoring and Japanese scoring have shown good screening value for early gastric cancer in a healthy population, but Li’s scoring is more sensitive/specific than Japanese scoring.Keywords: Li’s scoring, Japanese scoring, early gastric cancer

Background and aimsThere are guidelines for the medical management of cirrhosis and associated quality indicators (QIs), but QIs focusing on standards for palliative aspects of care are needed.MethodsWe convened a 9-member, multidisciplinary expert panel and used RAND/UCLA modified Delphi methods to develop palliative care quality indicators for patients with cirrhosis. Experts were provided with a report based on a systematic review of the literature that contained evidence concerning the proposed candidate QIs. Panelists rated QIs prior to a planned meeting using a standard 9-point RAND appropriateness scale. These ratings guided discussion during a day-long phone conference meeting, and final ratings were then provided by panel members. Final QI scores were computed and QIs with a final median score of greater than or equal to 7, and no disagreement was included in the final set.ResultsAmong 28 candidate QIs, the panel rated 19 as valid measures of quality care. These 19 quality indicators cover care related to information and care planning (13) and supportive care (6).ConclusionsThese QIs are evidence-based process measures of care that may be useful to improve the quality of palliative care. Research is needed to better understand the quality of palliative care provided to patients with cirrhosis.

In situ monitoring of bone regeneration enables timely diagnosis and intervention by acquiring vital biological parameters. However, an existing gap exists in the availability of effective methodologies for continuous and dynamic monitoring of the bone tissue regeneration process, encompassing the concurrent visualization of bone formation and implant degradation. Here, we present an integrated scaffold designed to facilitate real-time monitoring of both bone formation and implant degradation during the repair of bone defects. Laponite (Lap), CyP-loaded mesoporous silica (CyP@MSNs) and ultrasmall superparamagnetic iron oxide nanoparticles (USPIO@SiO2) were incorporated into a bioink containing bone marrow mesenchymal stem cells (BMSCs) to fabricate functional scaffolds denoted as C@M/GLU using 3D bioprinting technology. In both in vivo and in vitro experiments, the composite scaffold has demonstrated a significant enhancement of bone regeneration through the controlled release of silicon (Si) and magnesium (Mg) ions. Employing near-infrared fluorescence (NIR-FL) imaging, the composite scaffold facilitates the monitoring of alkaline phosphate (ALP) expression, providing an accurate reflection of the scaffold's initial osteogenic activity. Meanwhile, the degradation of scaffolds was monitored by tracking the changes in the magnetic resonance (MR) signals at various time points. These findings indicate that the designed scaffold holds potential as an in situ bone implant for combined visualization of osteogenesis and implant degradation throughout the bone repair process.

Objective: The current study aimed to observe hypertension educational intervention's effect on general physicians (GPs) to improve blood pressure control and patient outcomes indirectly. Methods: This randomized control trial includes 42 GPs divided into 2 groups. GPs in group 1 receive face-to-face education with structured educational material on hypertension management strategies by a senior cardiologist. GPs in group 2 receive the print version of education material. The data was collected from six major cities in Pakistan. GPs with at least three years of experience in the broad primary care disciplines, with ages above 18 years, were included in the study. Results: A total of 42 physicians (21 from each group) completed questionnaires, while out of 420 hypertension patients, 105 newly diagnosed and already diagnosed patients enrolled under physicians of both groups. The educational material did just as well at informing clinicians as the face-to-face group intervention did and both the interventions had a significant effect on knowledge and BP control. Conclusion: After the 3-month follow-up, both interventions, including face-to-face and educational approaches, demonstrated significant effectiveness in improving knowledge and blood pressure control. Innovation: The study shows that hypertension educational intervention's effect on general physicians indirectly improves blood pressure control and patient outcomes. And emphasize for developing a hypertension educational program targeted at general physicians.

Skin cancer is a pervasive and potentially life-threatening disease. Early detection plays a crucial role in improving patient outcomes. Machine learning (ML) techniques, particularly when combined with pre-trained deep learning models, have shown promise in enhancing the accuracy of skin cancer detection. In this paper, we enhanced the VGG19 pre-trained model with max pooling and dense layer for the prediction of skin cancer. Moreover, we also explored the pre-trained models such as Visual Geometry Group 19 (VGG19), Residual Network 152 version 2 (ResNet152v2), Inception-Residual Network version 2 (InceptionResNetV2), Dense Convolutional Network 201 (DenseNet201), Residual Network 50 (ResNet50), Inception version 3 (InceptionV3), For training, skin lesions dataset is used with malignant and benign cases. The models extract features and divide skin lesions into two categories: malignant and benign. The features are then fed into machine learning methods, including Linear Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Decision Tree (DT), Logistic Regression (LR) and Support Vector Machine (SVM), our results demonstrate that combining E-VGG19 model with traditional classifiers significantly improves the overall classification accuracy for skin cancer detection and classification. Moreover, we have also compared the performance of baseline classifiers and pre-trained models with metrics (recall, F1 score, precision, sensitivity, and accuracy). The experiment results provide valuable insights into the effectiveness of various models and classifiers for accurate and efficient skin cancer detection. This research contributes to the ongoing efforts to create automated technologies for detecting skin cancer that can help healthcare professionals and individuals identify potential skin cancer cases at an early stage, ultimately leading to more timely and effective treatments.

The development of advanced Intelligent Transportation Systems has been made possible by the rapid expansion of autonomous vehicles (AVs) and networking technology (ITS). The in-vehicle users' increased data needs from AVs put the vehicle's trajectory data in danger and make it more susceptible to security threats. In this paper, Autonomous vehicles (AVs) transform the intelligent transportation system by exchanging real-time and seamless data with other AVs and the network (ITS). Transportation that is automated has many advantages for people. However, worries about safety, security, and privacy continue to grow. The AVs need to exchange sensory data with other AVs and with their own for navigation and trajectory planning. When an unreliable sensor-equipped AV or one that is malicious enters connectivity in such circumstances, the results could be disruptive. To effectively detect anomalies and mitigate cyberattacks in AVs, this study suggests the Efficient Anomaly Detection (EAD) method. The EAD technique finds and isolates rogue AVs using the Multi-Agent Reinforcement Learning (MARL) algorithm, which operates over the 6G network to thwart modern cyberattacks and provide a quick and accurate anomaly detection mechanism. The expected outcomes demonstrate the value of EAD and have an accuracy rate that is 8.01% greater than that of the current systems.

Abstract Multicenter studies in pediatric cardiovascular magnetic resonance (CMR) improve statistical power and generalizability. However, a structured process for identifying important research topics has not been developed. We aimed to (1) develop a list of high priority knowledge gaps, and (2) pilot the use of a wiki survey to collect a large group of responses. Knowledge gaps were defined as areas that have been either unexplored or under-explored in the research literature. High priority goals were: (1) feasible and answerable from a multicenter research study, and (2) had potential for high impact on the field of pediatric CMR. Seed ideas were contributed by a working group and imported into a pairwise wiki survey format which allows for new ideas to be uploaded and voted upon ( https://allourideas.org ). Knowledge gaps were classified into 2 categories: ‘Clinical CMR Practice’ (16 ideas) and ‘Disease Specific Research’ (22 ideas). Over a 2-month period, 3,658 votes were cast by 96 users, and 2 new ideas were introduced. The 3 highest scoring sub-topics were myocardial disorders (9 ideas), translating new technology & techniques into clinical practice (7 ideas), and normal reference values (5 ideas). The highest priority gaps reflected strengths of CMR (e.g., myocardial tissue characterization; implementation of technologic advances into clinical practice), and deficiencies in pediatrics (e.g., data on normal reference values). The wiki survey format was effective and easy to implement, and could be used for future surveys.

Objective: To determine the frequency of infections in cardiac implantable Electronic device patients, identify risk factors, and look for optimization in reducing Cardiac Implantable Electronic Device infections, with a resultant decrease in mortality and morbidity, decrease in hospital stay, and total expenditure. Study Design: Cross-sectional study. Place and Duration of Study: Electrophysiology Department of National Institute of Cardiovascular Diseases, Karachi Pakistan, from Jul 2019 to Jun 2020. Methodology: The study was conducted on the patients with cardiac implantable devices. Adult patients of either gender with cardiac implantable Electronic device and infection were included. Epicardial leads and surgical site infections within six weeks were excluded. Results: One thousand and forty-six (1046) patients were enrolled in the study. There were 596(57%) male patients. 385(36.8%) patients were implanted with single chamber pacemakers, 390(37.3%) with dual chamber pacemakers, 146(14%) single chamber ICD (implantable cardiac defibrillator), 67(6.4%) dual-chamber cardiac implantable Electronic device, 46(4.4%) CRT-D, 12(1.1%) TPM, 134(12.8%) Re-do, 114(10.9%), 114(10.9%) generator change, 20(1.9%) leads revision, 26(2.5%) patients had extraction. The rate of CIED infection was 34(2.1%). The association of the study parameters with infection rate revealed that type of device (p=0.002), extraction, suture type, and post-procedure hematoma (p

Computer viruses, malicious, and other hostile attacks can affect a computer network. Intrusion detection is a key component of network security as an active defence technology. Traditional intrusion detection systems struggle with issues like poor accuracy, ineffective detection, a high percentage of false positives, and an inability to handle new types of intrusions. To address these issues, we propose a deep learning-based novel method to detect cybersecurity vulnerabilities and breaches in cyber-physical systems. The proposed framework contrasts the unsupervised and deep learning-based discriminative approaches. This paper presents a generative adversarial network to detect cyber threats in IoT-driven IICs networks. The results demonstrate a performance increase of approximately 95% to 97% in terms of accuracy, reliability, and efficiency in detecting all types of attacks with a dropout value of 0.2 and an epoch value of 25. The output of well-known state-of-the-art DL classifiers achieved the highest true rate (TNR) and highest detection rate (HDR) when detecting the following attacks: (BruteForceXXS, BruteForceWEB, DoS_Hulk_Attack, and DOS_LOIC_HTTP_Attack) on the NSL-KDD, KDDCup99, and UNSW-NB15 datasets. It also maintained the confidentiality and integrity of users’ and systems’ sensitive information during the training and testing phases.

Objectives: Tricuspid valve (TV) surgery remains understudied and little data exist describing the surgical indications, outcomes, and prognostic factors for pediatric patients with non-Ebstein 2-ventricle congenital TV lesions. This study aims to describe early and late outcomes of pediatric patients with non-Ebstein congenital TV lesions undergoing isolated TV procedures at a single institution. Methods: All patients who underwent TV surgery for non-Ebstein congenital TV disease between 2006 and 2018 were included. Patients who had missing preoperative data, patients with single-ventricle physiology, congenitally corrected transposition of the great arteries, and patients undergoing TV intervention as part of repair of an atrioventricular canal defect were excluded. The primary end point was the occurrence of TV reintervention or TV regurgitation (TR) ≥ moderate. Results: A total of 85 patients were included. The tricuspid lesion was isolated TR in 80 (94.1%), isolated tricuspid stenosis in 3 (3.5%) and mixed disease in 2 (2.4%) patients. Median age at surgery was 33 years (interquartile range, 12-53 years). TV repair and TV replacement were performed in 66 (77.6%) and 19 (22.4%) patients, respectively. One (1.2%) patient underwent TV reoperation during the same admission. There was no in-hospital mortality. Median follow-up was 3.3 years (interquartile range, 0.1-4.7 years). The overall cumulative incidence of TV reintervention or TR deemed moderate or greater at 1, 3, and 5 years was 3% ± 2%, 11% ± 4%, and 20% ± 8%. In multivariable analysis, age younger than 12 years (P = .04) and mitral valve regurgitation deemed moderate or greater (P = .01) were independent risk factors for TV reintervention or recurrent TR deemed to be moderate or greater at last follow-up. Conclusions: TV surgery in patients with non-Ebstein congenital TV disease can be performed with good outcomes. TV reintervention or TR deemed moderate or greater occurred in 20% of patients on midterm follow-up. Patients younger than age 12 years are at higher risk for recurrent TR or TV reintervention, whereas preoperative MR deemed moderate or greater increases this risk, especially in patients older than age 12 years. There was no difference in outcomes between TV replacement and repair.

Background: To date, no optimal way of organizing and delivering care to hypertensive patients at the primary carer level has been identified, due to which a significant number of patients fail to meet the treatment goals. The current study aims to observe hypertension educational intervention's effect on general physicians (GPs) to indirectly improve blood pressure control and patient outcomes. Methodology: In this randomized control trial, GPs will be divided into 2 groups and both groups will be asked to fill hypertension awareness questionnaire at baseline and, after randomization. GPs of the group I will receive (1 day) face-to-face education with structured educational material on hypertension management strategies. GPs of group II will receive the print version of educational material (structured educational material) on strategies of structured hypertension management. Both groups of GPs will recruit 10 (5 newly diagnosed + 5 already diagnosed patients) from the study site. The patient will be asked to fill hypertension awareness questionnaire at baseline and share a 12-hour blood pressure measurement. GPs and patients will be reassessed after 3 months of intervention. Discussion: The purpose of designing this study is to observe the effect of hypertension educational intervention for general physicians to improve blood pressure control and patient outcomes indirectly. Results of this study may provide a basis for developing a hypertension educational program targeted at general physicians. Trial registration: The trial was registered with ClinicalTrials.gov NCT05038774.

Background: One of the most frequently observed valvular heart lesions is Mitral stenosis (MS), characterized by left ventricular inflow tract obstruction at the mitral valve level caused by different etiologies. Early detection of symptomatic mitral stenosis with a thrombus in LAA, not responding to anticoagulation in due course of time are sent for Mitral valve replacement rather than undergoing PTMC. The current study aims to see the anticoagulation response in different types of left atrial appendages so that non-responders can be referred for surgery on the first TEE and Cardiac CT. Methodology: The current study will observe the frequency of left atrial appendage (LAA) thrombus resolution after three months of anticoagulation in patients with severe MS. It will assess the response rate in different morphologies of LAA so that non-responders can be referred for surgery on the very first TEE and Cardiac CT. Consecutive MS patients with thrombus in LAA detected via transesophageal echocardiography will be included in the study. According to the standard procedure, TEE followed by Cardiac CT will be performed after obtaining informed consent from the patients. Discussion: Detecting the anticoagulation response using follow-up TEE in different types of left atrial appendages might be helpful for the non-responders that can be referred for surgery after TEE and Cardiac CT on first examination and TEE only at the end of three months. Trial registration number: The trial was registered on ClinicalTrials.gov (NCT05186649).

Higher education institutes have integratede-learning systems (ELS)in their educational infrastructure. The development and implementation of ELS needs continuous quality evaluation and assessment to attract more learners.A conceptual model consisting of system, service and information qualities was evaluated to measure the user satisfaction. Data was collected from 356 learners including Post Graduate (52%) and Graduate (48%)students of Virtual University, Pakistan. To investigate the research hypotheses, Structural Equation Modelling (SEM) was employed. The empirical analysis indicated that information quality (0.38, p<0.05), service quality (0.14, p<0.05)and system quality(0.48, p<0.01) were the positive and significant indicators for user satisfaction. The variance explained by the model is 71% that showed the significance of model. [ABSTRACT FROM AUTHOR]