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Abstract Background There is dearth of literature addressing early outcomes of acute coronary syndrome (ACS) among young patients, particularly South Asians descent who are predisposed to premature coronary artery disease (CAD). Therefore, we compared presentation, management, and early outcomes of young vs. old ACS patients and explored predictors of in-hospital mortality. Methods We extracted data of 23,560 ACS patients who presented at Tabba Heart Institute, Karachi, Pakistan, from July 2012-June 2020, from the Chest pain-MI-Registry™. We categorized data into young ≤ 45 and old ACS patients > 45 years. Chi-sq/Fischer exact tests were used to assess the difference between presentation, disease management, and in-hospital mortality between both groups. Logistic regression was used to determine odds ratio along with 95% confidence interval of factors associated with early mortality. Results The younger patients were 12.2% and women 23.5%. The prevalence of dyslipidemia (34.5% vs. 22.4%), diabetes (52.1% vs. 27.4%), and hypertension (68.3% vs. 42.9%) was higher in older patients. Family history of premature CAD (18.1% vs. 32.7%), smoking (40.0% vs. 22.9%), and smokeless tobacco use (6.5% vs. 8.4%) were lower in older patients compared to younger ones. Younger patients were more likely to present with STEMI (33.2% vs. 45%). The median symptom-to-door time was 125 min longer (p-value

Background: Out-of-hospital cardiac arrest (OHCA) is a major cause of morbidity and mortality globally, with survival outcomes remaining poor particularly in many low- and middle-income countries. We aimed to establish a pilot OHCA registry in Karachi, Pakistan to provide insights into OHCA patient demographics, pre-hospital and in-hospital care, and outcomes. Methods: A multicenter longitudinal study was conducted from August 2015-October 2019 across 11 Karachi hospitals, using a standardized Utstein-based survey form. Data was retrospectively obtained from medical records, patients, and next-of-kin interviews at hospitals with accessible medical records, while hospitals without medical records system used on-site data collectors. Demographics, arrest characteristics, prehospital events, and survival outcomes were collected. Survivors underwent follow-up at 1 month, 6 months, 1 year, and 5 years. Results: In total, 1068 OHCA patients were included. Mean age was 55 years, 61.1 % (n = 653) male. Witnessed arrests accounted for 94.9 % of the cases (n = 1013), whereas 89.4 % of the cases (n = 955) were transported via non-EMS. Bystander CPR was performed in 10.3 % (n = 110) cases whereas pre-hospital defibrillation performed in 0.4 % (n = 4). In-hospital defibrillation was performed in 9.9 % (n = 106) cases despite

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.

BackgroundElectronic health records (EHRs) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHRs in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes. ObjectiveThis study reviews advanced spatial analyses that used individual-level health data from EHRs within the United States to characterize patient phenotypes. MethodsWe systematically evaluated English-language, peer-reviewed studies from the PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on study design or specific health domains. ResultsA substantial proportion of studies (>85%) were limited to geocoding or basic mapping without implementing advanced spatial statistical analysis, leaving only 49 studies that met the eligibility criteria. These studies used diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were less common. A noteworthy surge (n=42, 86%) in publications was observed after 2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were limited. ConclusionsThis review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. We suggest that future research should focus on addressing these gaps and harnessing spatial analysis to enhance individual patient contexts and clinical decision support.

Purpose – The purpose of this study was to explore how transport companies in Uganda execute strategies in a turbulent business environment. Design/methodology/approach – The study adopted an exploratory qualitative methodology using the data collected through an open-ended instrument. Utilizing the qualitative data analysis software QSR NVivo9, the data were analyzed following the Gioia's methodology. Verbatim texts were used to explain the emergent themes. Findings – The study's findings show that to successfully execute strategies, companies in Uganda communicate, coordinate and put control systems in their operations. The activities undertaken include customer care, timely settlement of complaints, comfortable seats, playing local music, partnerships with reliable fuel stations, setting up strategic offices, cost management, use of experienced drivers, sub-renting vehicles and inspections. Originality/value – The study produces a pioneering result of how transport companies execute strategies in a turbulent business environment, an aspect that has not been adequately highlighted in previous studies.

In the field of real-time systems, component-based models for mixed criticality systems (MCS) on multicore platform are gaining significant attention of the researchers from the recent past. The concept of mixed-criticality is firstly applied on single core systems but after gaining attention, it evolved to multicore platform. Initially, the tasks of MCS executes in low mode however if a task having high criticality does not its scheduling requirements complete its low mode, then the system switch to high mode. In high mode, only high critical tasks executes its high mode scheduling requirements, while all low tasks are discarded from further execution. In the realm of MCS, the component-based model have high importance and has been used in large and complex real-time systems. In component-based model, the component of a system is splatted into multiple components. In this study, a new component-based scheduling approach is proposed for multicore MCS. In the multicore mixed-criticality compositional framework, special emphasis is given on deriving the supply bound function, which represents available core supply, and the demand bound function, which indicates the requirements of resources for scheduling. A mixed-criticality multicore compositional framework (MMCF) is introduced for component-based MCS having tightened deadline. For the proposed strategy, a schedulability analysis is conducted, ensuring that the system can be scheduled only if the supply bound function is equal to or less than the demand bound function. On a 4-core platform, the scheduleability for the three scheduling strategies i.e. MMCF, MC-Partition, and Global are shown at different utilization levels of resource. 100% schedulability is shown by the proposed MMCF, MC-Partition, and global techniques for target utilizations of 0.7, 0.5, and 0.4, respectively. For a given utilization U=0.6, the proposed MMCF approach shows 100 % schedulability, while the MC-partition and global approaches show 90% and 20% schedulabilities respectively. It shows that the proposed MMCF approach schedules 10% and 80% more task sets than the MC-partition and global approaches respectively. The experimental results reveal that the proposed MMCF approach offers better schedulability than the other two approaches.

Real-time systems mostly interact with the external world and each input operation must meet predetermined deadlines to be useful. However, in many real-time applications, a partial result is also acceptable. We developed a reward-based mixed criticality system based on the resource reservation approach to address the problem of ensuring the effective execution of low- and high-criticality tasks in both low- and high modes, even under heavy workloads. Using dedicated servers with pessimistic resource allocation for each high criticality task ensured their execution in both modes unaffected by low criticality tasks. The surplus resources are reclaimed and assigned to low critical tasks’ server by utilizing a greedy reclamation of unused bandwidth (GRUB) algorithm. Three strategies were suggested for server allocation to low criticality tasks: a dedicated server for all low criticality tasks, a single server for each low criticality task, and two servers (mandatory and optional) for each low criticality task. Our analysis revealed efficiency of the first approach by achieving 100% schedulability at a 1.1 target utilization, scheduling 20% and 50% more task sets than the second and third approaches, respectively. Moreover, the effectiveness of the proposed approach over existing imprecise mixed criticality approaches were demonstrated through comprehensive experimentation.

Abstract Background There has been an increase in Acute Coronary Syndrome (ACS) patients without standard modifiable risk factors i.e. hypertension, diabetes, dyslipidemia, and tobacco use (SMuRFless) compared to the patients with ≥ 1 SMuRF but this has not been studied in South Asia despite them being a high-risk population. We conducted a comparative analysis of first episodes of ACS cases admitted to a tertiary cardiac center in Pakistan between SMuRFless and ≥ 1 SMuRF patients for clinical presentation, management, in-hospital, and 5-year mortality. Methods We undertook a retrospective study and data of 15,051 patients admitted at Tabba Heart Institute (THI) with the first episode of ACS was extracted from Chest Pain-MI™, and the CathPCI Registry® registry affiliated with the National Cardiovascular Data Registry (NCDR®), USA. Logistic regression and Cox proportional algorithm yielded odds ratio (OR) and hazard ratios (HR) with 95% confidence interval (CI) for associated factors of in-patient and 5-year mortality. Results There were 15% SMuRFless cases and in-hospital mortality was 4.1% in SMuRFless vs. 3.9% in the ≥ 1 SMuRF group (p-0.59), the difference remained insignificant after adjusting for age, gender, Killip class, multivessel disease, type of ACS, percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) (Adjusted OR:1.1 [0.8, 1.3]. Unadjusted 5-year mortality was 40% lower in the SMuRFless group but the difference was insignificant after adjusting for age, gender, disease at presentation, its severity, and management (Adjusted HR 0.7 95% CI[0.5, 1.0]). STEMI, NSTEMI, Killip class, and multivessel disease increased the risk of overall 5-year mortality. Conclusion In-hospital and 5-year mortality was not different between the SMuRFless and ≥ 1 SMuRF group, there is a need to understand mediators of immediate and long-term mortality risk in SMuRFless patients.

Viral pathogens are major concern nowadays. Bacterial CRISPR/Cas systems help in defending the host body against different pathogens including viruses too. This system contains restriction enzymes that introduce dsDNA breaks on target site to make the virus non-functional by damaging its genes. Coronavirus, HIV and Herpes viruses are causing mortality all around the world. To control the spread of disease, early detection and treatment is required. CRISPR system due to its high efficiency provides a platform to restrict the viral entry into host cell, viral genome editing and eliminate the latent infections. In this review, the CRISPR strategies against three major viral diseases are put under consideration: Coronavirus, Acquired Immunodeficiency Syndrome and Herpesvirus associated diseases. Three CRISPR/Cas systems have been discussed including CRISPR/Cas12, CRISPR/Cas9 and CRISPR/Cas13 that are used against the above listed viruses.

Introduction Atherosclerotic cardiovascular disease (ASCVD) is a major cause of morbidity, mortality and health expenditures worldwide. Despite having higher ASCVD in the Pakistani population, data on subclinical coronary atherosclerosis in young Pakistanis remain scarce. The PAKistan Study of prEmature coronary atHerosclerosis in young AdulTs (PAK-SEHAT) aims to assess the prevalence, severity and determinants of subclinical coronary atherosclerosis among Pakistani men (35–60 years) and women (35–65 years) free of clinically symptomatic ASCVD and will assess 5-year rates of ASCVD events.Methods and analysis PAK-SEHAT is an ongoing prospective cohort study with 2000 participants from all provinces of Pakistan who will be interviewed at the baseline along with phlebotomy, measurement of carotid intima-media thickness (CIMT) and coronary CT angiography (CCTA). Phlebotomy will be repeated at 2.5 years, whereas CIMT and CCTA will be repeated at 5 years. We will report the frequency of maximal coronary stenosis ≥50% and ≥70%, number of coronary vessels with plaque and the number of coronary segments affected per participant on CCTA. We will use Cox proportional hazards regression models to evaluate the association between baseline characteristics and incident ASCVD events during follow-up. These associations will be presented as HRs with 95% CIs.Ethics and dissemination The study protocol was approved by the Tabba Heart Institute Institutional Review Board (THI/IRB/FQ/22-09-2021/016). All study procedures are consistent with the principles of the Declaration of Helsinki. Findings of the study will be disseminated via peer-reviewed publications and conference presentations.Trial registration number NCT05156736.

Facial expression is a type of communication and is useful in many areas of computer vision, including intelligent visual surveillance, human-robot interaction and human behavior analysis. A deep learning approach is presented to classify happy, sad, angry, fearful, contemptuous, surprised and disgusted expressions. Accurate detection and classification of human facial expression is a critical task in image processing due to the inconsistencies amid the complexity, including change in illumination, occlusion, noise and the over-fitting problem. A stacked sparse auto-encoder for facial expression recognition (SSAE-FER) is used for unsupervised pre-training and supervised fine-tuning. SSAE-FER automatically extracts features from input images, and the softmax classifier is used to classify the expressions. Our method achieved an accuracy of 92.50% on the JAFFE dataset and 99.30% on the CK+ dataset. SSAE-FER performs well compared to the other comparative methods in the same domain.

Abstract Background In many contexts, including fragile settings like Afghanistan, the coverage of basic health services is low. To address these challenges there has been considerable interest in working with NGOs and examining the effect of financial incentives on service providers. The Government of Afghanistan has used contracting with NGOs for more than 15 years and in 2019 introduced pay-for-performance (P4P) into the contracts. This study examines the impact of P4P on health service delivery in Afghanistan. Methods We conducted an interrupted time series (ITS) analysis with a non-randomized comparison group that employed segmented regression models and used independently verified health management information system (HMIS) data from 2015 to 2021. We compared 31 provinces with P4P contracts to 3 provinces where the Ministry of Public Health (MOPH) continued to deliver services without P4P. We used data from annual health facility surveys to assess the quality of care. Findings Independent verification of the HMIS data found that consistency and accuracy was greater than 90% in the contracted provinces. The introduction of P4P increased the 10 P4P-compensated service delivery outcomes by a median of 22.1 percentage points (range 10.2 to 43.8) for the two-arm analysis and 19.9 percentage points (range: - 8.3 to 56.1) for the one-arm analysis. There was a small decrease in quality of care initially, but it was short-lived. We found few other unintended consequences. Interpretation P4P contracts with NGOs led to a substantial improvement in service delivery at lower cost despite a very difficult security situation. The promising results from this large-scale experience warrant more extensive application of P4P contracts in other fragile settings or wherever coverage remains low.

The cluster-based technique is gaining focus for scheduling tasks of mixed-criticality (MC) real-time multicore systems. In this technique, the cores of the MC system are distributed in groups known as clusters. When all cores are distributed in clusters, the tasks are partitioned into clusters, which are scheduled on the cores within each cluster using a global approach. In this study, a cluster-based technique is adopted for scheduling tasks of real-time mixed-criticality systems (MCS). The Decreasing Criticality Decreasing Utilization with the worst-fit (DCDU-WF) technique is used for partitioning of tasks to clusters, whereas a novel mixed-criticality cluster-based boundary fair (MC-Bfair) scheduling approach is used for scheduling tasks on cores within clusters. The MC-Bfair scheduling algorithm reduces the number context switches and migration of tasks, which minimizes the overhead of mixed-criticality tasks. The migration and context switch overhead time is added at the time of each migration and context switch respectively for a task. In low critical mode, the low mode context switch and migration overhead time is added to task execution time, while the high mode overhead time of migration and context switch is added to the execution time of a task in high critical mode. The results obtained from experiments show the better schedulablity performance of proposed cluster-based technique as compared to cluster-based fixed priority (CB-FP), MC-EKG-VD-1, global and partitioned scheduling techniques e.g., for target utilization U=0.6, the proposed technique schedule 66.7% task sets while MC-EKG-VD-1, CB-FP, partitioned and global techniques schedule 50%, 33.3%, 16.7% and 0% task sets respectively.

Lie symmetry analysis (LSA) is one of the most common, effective, and estimation-free methods to find the symmetries and solutions of the differential equations (DEs) by following an algorithm. This analysis leads to reduce the order of partial differential equations (PDEs). Many physical problems are converted into non-linear DEs and these DEs or system of DEs are then solved with several methods such as similarity methods, Lie Bäcklund transformation, and Lie group of transformations. LSA is suitable for providing the conservation laws corresponding to Lie point symmetries or Lie Bäcklund symmetries. Short pulse equation (SPE) is a non-linear PDE, used in optical fibers, computer graphics, and physical systems and has been generalized in many directions. We will find the symmetries and a class of solutions depending on one-parameter (ε) obtained from Lie symmetry groups. Then we will construct the optimal system for the Lie algebra and invariant solutions (called similarity solutions) from Lie subalgebras of generalized SPE.

Therapeutic Area: ASCVD/CVD Risk Factors Background: There is a scarcity of literature exploring early outcomes of young acute-coronary-syndrome patients, predominantly in South Asians, who are considered to be at most risk of developing premature coronary artery disease. Therefore, we compared presentation, management, and early outcomes of young vs. old ACS patients and explored predictors of in-hospital mortality. Methods: We extracted data of 23,560 ACS patients presented at Tabba Heart Institute, Karachi, Pakistan, from July 2012-June 2020, from the Chest pain-MI Registry™. Young patients: ≤45 years. Chi-sq/Fischer exact tests assessed the difference between variables in younger vs. older patients. Logistic regression was used to determine predictors of early mortality, and odds ratios along with 95% confidence intervals were reported. Results: The mean age was 59.0±11.4 years, women: 23.5%, and younger patients: 12.3%. Dyslipidemia (34.5% vs. 22.4%), diabetes (52.1% vs. 27.4%) and hypertension (68.3% vs. 42.9%) were higher in older adults. In contrast, Family history of premature coronary artery disease (32.7% vs. 18.1%) and smokeless-tobacco (8.4% vs. 6.5%) was higher in young adults. Younger adults were more likely to present with STEMI (45% vs. 33.2%) and be asymptomatic on presentation (40.8% vs. 36.1%). Median symptom-to-door-time was higher in younger patients (760(192, 3140) vs. 635(186,2735) minutes). Coronary angiography and CABG were higher in older patients; however, PCI was higher in young adults. The use of all medications in first 24 hours except IV anticoagulant and angiotensin receptor blockers was higher in younger adults. In-hospital mortality (4.3% vs. 1.7%) and complications including cardiac arrest (1.9% vs. 0.7%), cardiogenic shock (1.9% vs. 0.9%) and heart failure (1% vs. 0.6%) were more common in older patients. After adjusting for risk factors, older age (2.4, 1.5-3.7) was a significant predictor of early mortality. Other predictors included: STEMI (OR:3.2, 95% CI:1.9-5.5), women (1.4, 1,1-1.8), Killip III/IV (3, 2.4-3.8), cardiac arrest (3.2, 2.2-4.5) and heart failure (1.8, 1.4-2.3) at presentation, Left ventricular ejection fraction (0.9, 0.93-0.95) and PCI (1.3, 1.1-1.7) and CABG (3, 2.3-3.9) at index hospitalization. Conclusion: Younger patients presented differently from their older counterparts as they were likely to be asymptomatic and have STEMI. They had favorable clinical outcomes, which might be explained by the aggressive treatment.

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.

This paper presents an active slip control system (ASCS) for a four-wheel drive electric vehicle (EV) using an active suspension of the vehicle. The integrated control mechanism is designed using a combination of a fuzzy controller and a nonlinear back-stepping controller to control the slip of the individual wheels with the help of the active suspension of the vehicle. In this research, the presented control mechanism is implemented in two steps. In the first step, based on the friction coefficient calculated from a nonlinear tire model, the fuzzy controller will generate the vehicle roll and pitch angles required to reduce the slipping of the individual wheels by changing the vertical load of the individual wheel. In the second step, a nonlinear back-stepping controller is used to track the required roll and pitch angles using the active suspension of the vehicle. A linear seven degree of freedom (DOF) vertical mathematical model is used for the design of the nonlinear back-stepping controller, while the rules of the fuzzy controller are interpreted from the friction coefficients of the tyre model. The performance of the presented control mechanism is verified using a 14-DOF nonlinear model with nonlinear tyre dynamics. The simulations using a nonlinear vehicle model show that the presented controller can successfully improve vehicle stability by reducing the slipping of the individual wheel.

We have previously reported a multipurpose silicone elastomer vaginal ring providing sustained release of dapivirine (an antiretroviral) and levonorgestrel (a progestin) for HIV prevention and hormonal contraception. During initial development, issues arose due to reaction between the ethynyl group in the levonorgestrel molecule and the hydride-functionalised polydimethylsiloxane components in the silicone elastomer formulation. This unwanted reaction occurred both during and to a lesser extent after ring manufacture, impacting the curing process, the mechanical properties of the ring, and the in vitro release of levonorgestrel. Recently, we reported custom silicone elastomer grades that minimise this reaction. In this follow-on study, we describe the manufacture, in vitro drug release, mechanical, and pharmaceutical stability testing of ring formulations prepared from a custom silicone elastomer and containing 200 mg dapivirine and 80, 160, 240 or 320 mg levonorgestrel. The rings showed mechanical properties similar to marketed ring products, sustained in vitro release of both drugs over 30 days in quantities deemed clinically relevant, offered acceptable assay values, and provided good product stability over 15 weeks at 40 °C and 75% relative humidity.

The prime objective of the cloud data storage process is to make the service, irrespective of being infinitely extensible, a more reliable storage and low-cost model that also encourages different data storage types. Owing to the storage process, it must satisfy the cloud users’ prerequisites. Nevertheless, storing massive amounts of data becomes critical as this affectsthe data quality or integrity. Hence, this poses various challenges for existing methodologies. An efficient, reliable cloud storage model is proposed using a hybrid heuristic approach to overcome the challenges. The prime intention of the proposed system is to store the data effectively in the cloud environment by resolving two constraints, which are general and specific (structural). The cloud data were initially gathered and used to analyze the storage performance. Since the data were extensive, different datasets and storage devices were considered. Every piece of data was specified by its corresponding features, whereas the devices were characterized by the hardware or software components. Subsequently, the objective function was formulated using the network’s structural and general constraints. The structural constraints were determined by the interactions between the devices and data instances in the cloud. Then, the general constraints regarding the data allocation rules and device capacity were defined. To mitigate the constraints, the components were optimized using the Hybrid Pelican–Billiards Optimization Algorithm (HP-BOA) to store the cloud data. Finally, the performance was validated, and the results were analyzed and compared against existing approaches. Thus, the proposed model exhibited the desired results for storing cloud data appropriately.

Autonomous path following has gained tremendous popularity during the last few decades. Numerous researchers have contributed to the development of highly automated navigation systems using different types of sensors and their combination. However, their proposed approaches do not provide a cost-efficient solution because of the deployment of exorbitant and sophisticated sensors, which remains a challenging problem for customized vehicles used in academic research. To overcome this issue, this study presents an economically efficient sensorless steering angle approach that employs a single camera for steering control and quick response (QR) based localization of a vehicle. Moreover, we used SONAR for object detection in a defined route to avoid possible collisions. The proposed technique combines a Probablistic Hough Transfrom for lane detection and QR codes, which helps the vehicle stay in its lane for stabilized control. To prove the efficiency of our approach, we tested it on our developed prototype vehicle named EMO. To validate the proposed approach through in-field testing, we designed a customized test track within the campus. The experimental results show the benefit of our proposed approach compared to existing methods available in the literature.

Objectives: To assess immediate outcome and complications of Amplatzer septal occluder percutaneous device for closure of secundum atrial septal defect in adults, and to determine regression in right ventricular size, reduced pulmonary arterial systolic pressure and incidence of device embolization at follow-up. Methods: The single-cohort, ambi-directional, observational study was conducted at the Tabba Heart Institute, Karachi, from January 2013 to July 2018, and comprised patients admitted consecutively for percutaneous atrial septal defect closure. Pre-closure trans-oesophageal echocardiogram was performed in all cases to ensure adequacy of defect margins necessary for device stability. Immediate procedure success and complications were determined by trans-oesophageal echocardiogram, while transthoracic echo was done on follow-up. Data was analysed using SPSS 21. Results: Of the 64 patients, 41(71.9%) were females. The overall mean age was 36.6±14 years. Median size of atrial septal defect was 21mm (interquartile range: 17-26mm). Immediate success was observed in 59(92.2%) patients, and there were 5(8%) acute device embolization events. Small residual atrial septal defect was found in 4(6.3%) cases. On 20-month follow-up, 54(84.4%) patients showed improved symptoms. Repeat transthoracic echo was performed in 39(60.1%) cases, and there were no late embolic events or residual atrial septal defect. Right ventricular size normalized in 34(89.5%) cases, mean pulmonary arterial systolic pressure reduced significantly compared to pre-closure measurement (p

Introduction Provisional stenting using drug-eluting stent is effective for simple coronary bifurcation lesions. Kissing balloon inflation using conventional non-compliant balloon is the primary treatment of side branch (SB) after main vessel (MV) stenting. Drug-coating balloon (DCB) is reported to be associated with less frequent clinical events in in-stent restenosis and small vessel disease. The importance of DCB in bifurcation treatment is understudied. Accordingly, this trial is designed to investigate the superiority of DCB to non-compliant balloon angioplasty for SB after provisional stenting in patients with true coronary bifurcation lesions.Methods and analysis The DCB-BIF trial is a prospective, multicentre, randomised, superiority trial including 784 patients with true coronary bifurcation lesions. Patients will be randomised in a 1:1 fashion to receive either DCB or non-compliant balloon angioplasty if SB diameter stenosis >70% after MV stenting. The primary endpoint is the composite of major adverse cardiac event at the 1-year follow-up, including cardiac death, myocardial infarction (MI) or clinically driven target lesion revascularisation. The major secondary endpoints include all-cause death, periprocedural MI, spontaneous MI, clinically driven target vessel revascularisation, in-stent restenosis, stroke and individual component of the primary endpoint. The safety endpoint is the risk of stent thrombosis.Ethics and dissemination The study protocol and informed consent have been reviewed and approved by the Institutional Review Board of all participating centres. The written informed consent for participation in the trial will be obtained from all participants. The results of this study will be published in a peer-reviewed journal and disseminated at conferences.Trial registration number NCT04242134.

A dapivirine-releasing silicone elastomer vaginal ring for reducing women's risk of HIV acquisition has recently been approved. A next-generation multipurpose vaginal ring releasing dapivirine and levonorgestrel is currently in development, offering hormonal contraception and HIV prevention from a single device. Previously, we reported challenges with incorporating levonorgestrel into rings manufactured from addition-cure silicone elastomers due to an irreversible chemical reaction between the levonorgestrel molecule and the hydride-functionalised crosslinker component of the silicone elastomer formulation, leading to low drug content assay, cure inhibition, and reduced ring mechanical properties (which may account for the increased incidence of ring expulsion in vivo). Here, we report on the development and testing of various custom silicone elastomer materials specifically formulated to circumvent these issues. After extensive testing of the custom silicones and subsequent manufacture and testing (Shore M hardness, pot life, content assay, oscillatory rheology, mechanical testing) of rings containing both dapivirine and levonorgestrel, a lead candidate formulation was selected that was amenable to practical ring manufacture via injection molding, exhibited no substantial levonorgestrel binding, and offered suitable mechanical properties.

Objective: The Asian American population in the U.S. comprises various, ethnically diverse subgroups. Traditionally, this population has been studied as a single, aggregated group, potentially masking differences in risk among subgroups. Analyses using disaggregated data can help better characterize the health needs of different Asian subpopulations and inform targeted, effective public health interventions. We assessed the prevalence of cardiovascular disease (CVD) risk factors and atherosclerotic CVD (ASCVD) and their associations with socioeconomic factors among Chinese, Asian Indian, Filipino and Other Asian subjects, compared with non-Hispanic White (NHW) subjects in the U.S. Methods: : Cross-sectional study using data from 298,286 adults from the National Health Interview Survey (NHIS) from 2007 to 2018. We utilized chi-squared tests to compare characteristics across subgroups. Weighted proportions and unadjusted and adjusted logistic regression models were utilized to examine the associations between Asian subgroups, self-reported CVD risk factors and self-reported ASCVD, as well as between socioeconomic factors within each Asian subgroup. Results: : Asian Indian subjects had the highest prevalence of diabetes (12.5%), while Filipino subjects had the highest prevalence of hyperlipidemia (27.7%), hypertension (29.8%) and obesity (19.8%). Despite this, the prevalence of self-reported ASCVD was lower in all Asian groups compared with NHWs. Chinese subjects had the lowest odds of having each of the CVD risk factors assessed. Conclusion: : We found considerable heterogeneity in the distribution of risk factors as well as ASCVD among Asian subgroups in the US. Compared with health system or community-based reports, the prevalence of risk factors and ASCVD may be underestimated in some Asian NHIS subgroups. There is an urgent need for efforts to improve recruitment of Asian participants of heterogeneous socioeconomic backgrounds in national surveys, as well as to perform a thorough assessment of risk factors and disease in this population, not relying solely on self-report.

Pseudo thrombocytopenia is the estimation of low platelet counts by a Hematology analyzer in spite of lack of shortage in platelets. EDTA-induced pseudo thrombocytopenia, commonly seen in clinical practice, occurs mainly due to anti platelet antibodies. Pseudo thrombocytopenia is seen in normal healthy individuals as well as in other disorders like cardiovascular, liver, autoimmune diseases and malignancy. We are presenting a case of multi coagulant resistant dependent thrombocytopenia. The purpose of the case report is to review approaches to pseudo thrombocytopenia. The case has coagulant resistant dependent thrombocytopenia in association with Anasarca and was a known case of cardiomyopathy with severely dilated left atrium, left ventricle &right atrium. Keywords: Pseudo platelet aggregation, multicoagulant resistant thrombocytopenia, pseudo thrombocytopenia. Continuous...

Using a combination of field visits, laboratory experiments and analyses, this study examined the impacts of illegal artisanal crude oil refineries on the environment. Total Hydrocarbons (THC) and heavy metals in the soil and water bodies as well as pr were determined and compared with both national international standards. The study found THC and heavy metals such as Iron and Manganese to be significantly high in both soil and water samples. It was found that the artisanal crude oil refining activities in the Niger Delta Area of Nigeria generate and discharge environmental safety hazards that are far beyond the statutory and intentional acceptable limits.

Abstract Background Community-wide analyses provide an essential means for evaluation of the effect of interventions or design variables on the composition of the microbiome. Applications of these analyses are omnipresent in microbiome literature, yet some of their statistical properties have not been tested for robustness towards common features of microbiome data. Recently, it has been reported that PERMANOVA can yield wrong results in the presence of heteroscedasticity and unbalanced sample sizes. Findings We develop a method for multivariate analysis of variance, Wd∗ $W_{d}^{*}$, based on Welch MANOVA that is robust to heteroscedasticity in the data. We do so by extending a previously reported method that does the same for two-level independent factor variables. Our approach can accommodate multi-level factors, stratification, and multiple post hoc testing scenarios. An R language implementation of the method is available at https://github.com/alekseyenko/WdStar. Conclusion Our method resolves potential for confounding of location and dispersion effects in multivariate analyses by explicitly accounting for the differences in multivariate dispersion in the data tested. The methods based on Wd∗ $W_{d}^{*}$ have general applicability in microbiome and other ‘omics data analyses.

Fresh properties of concrete are closely related to operation and construction, such as transporting, placing, compacting, etc.; and they also have a great impact on the lifetime performance of concrete. In this paper, the influence of Diatomaceous Earth (DE) as a natural pozzolan on fresh properties of cement pastes has been investigated. Cement pastes with different water-to-binder ratios (w/b=0.4, 0.5 and 0.6) and 0%, 2%, 6% and 10% replacement levels of DE by weight of cement were studied. Viscosity, yield stress, flow diameter, bleeding, setting times, and the heat evolution of all cement pastes were measured. Results showed that DE has a significant impact on fresh properties of cement pastes. Increasing DE content in cement pastes resulted in higher viscosity and lower flow diameters. Pastes with higher DE replacement levels showed lower bleeding rate and shorter initial and final setting times. The isothermal calorimetry test also showed that, as a pozzolanic material, DE lowered the heat of hydration, however, it advanced the appearance of the heat evolution peaks which was in agreement with the results from setting time tests.

In step with rapid advancements in computer vision, vehicle classification demonstrates a considerable potential to reshape intelligent transportation systems. In the last couple of decades, image processing and pattern recognition-based vehicle classification systems have been used to improve the effectiveness of automated highway toll collection and traffic monitoring systems. However, these methods are trained on limited handcrafted features extracted from small datasets, which do not cater the real-time road traffic conditions. Deep learning-based classification systems have been proposed to incorporate the above-mentioned issues in traditional methods. However, convolutional neural networks require piles of data including noise, weather, and illumination factors to ensure robustness in real-time applications. Moreover, there is no generalized dataset available to validate the efficacy of vehicle classification systems. To overcome these issues, we propose a convolutional neural network-based vehicle classification system to improve robustness of vehicle classification in real-time applications. We present a vehicle dataset comprising of 10,000 images categorized into six-common vehicle classes considering adverse illuminous conditions to achieve robustness in real-time vehicle classification systems. Initially, pretrained AlexNet, GoogleNet, Inception-v3, VGG, and ResNet are fine-tuned on self-constructed vehicle dataset to evaluate their performance in terms of accuracy and convergence. Based on better performance, ResNet architecture is further improved by adding a new classification block in the network. To ensure generalization, we fine-tuned the network on the public VeRi dataset containing 50,000 images, which have been categorized into six vehicle classes. Finally, a comparison study has been carried out between the proposed and existing vehicle classification methods to evaluate the effectiveness of the proposed vehicle classification system. Consequently, our proposed system achieved 99.68%, 99.65%, and 99.56% accuracy, precision, and F1-score on our self-constructed dataset.

Context. Social media platforms such as Facebook and Twitter carry a big load of people’s opinions about politics and leaders, which makes them a good source of information for researchers to exploit different tasks that include election predictions. Objective. Identify, categorize, and present a comprehensive overview of the approaches, techniques, and tools used in election predictions on Twitter. Method. Conducted a systematic mapping study (SMS) on election predictions on Twitter and provided empirical evidence for the work published between January 2010 and January 2021. Results. This research identified 787 studies related to election predictions on Twitter. 98 primary studies were selected after defining and implementing several inclusion/exclusion criteria. The results show that most of the studies implemented sentiment analysis (SA) followed by volume-based and social network analysis (SNA) approaches. The majority of the studies employed supervised learning techniques, subsequently, lexicon-based approach SA, volume-based, and unsupervised learning. Besides this, 18 types of dictionaries were identified. Elections of 28 countries were analyzed, mainly USA (28%) and Indian (25%) elections. Furthermore, the results revealed that 50% of the primary studies used English tweets. The demographic data showed that academic organizations and conference venues are the most active. Conclusion. The evolution of the work published in the past 11 years shows that most of the studies employed SA. The implementation of SNA techniques is lower as compared to SA. Appropriate political labelled datasets are not available, especially in languages other than English. Deep learning needs to be employed in this domain to get better predictions.

The use of slang, abusive, and offensive language has become common practice on social media. Even though social media companies have censorship polices for slang, abusive, vulgar, and offensive language, due to limited resources and research in the automatic detection of abusive language mechanisms other than English, this condemnable act is still practiced. This study proposes USAD (Urdu Slang and Abusive words Detection), a lexicon-based intelligent framework to detect abusive and slang words in Perso-Arabic-scripted Urdu Tweets. Furthermore, due to the nonavailability of the standard dataset, we also design and annotate a dataset of abusive, offensive, and slang word Perso-Arabic-scripted Urdu as our second significant contribution for future research. The results show that our proposed USAD model can identify 72.6% correctly as abusive or nonabusive Tweet. Additionally, we have also identified some key factors that can help the researchers improve their abusive language detection models.

Software defects prediction at the initial period of the software development life cycle remains a critical and important assignment. Defect prediction and correctness leads to the assurance of the quality of software systems and has remained integral to study in the previous years. The quick forecast of imperfect or defective modules in software development can serve the development squad to use the existing assets competently and effectively to provide remarkable software products in a given short timeline. Hitherto, several researchers have industrialized defect prediction models by utilizing statistical and machine learning techniques that are operative and effective approaches to pinpoint the defective modules. Tree family machine learning techniques are well-thought-out to be one of the finest and ordinarily used supervised learning methods. In this study, different tree family machine learning techniques are employed for software defect prediction using ten benchmark datasets. These techniques include Credal Decision Tree (CDT), Cost-Sensitive Decision Forest (CS-Forest), Decision Stump (DS), Forest by Penalizing Attributes (Forest-PA), Hoeffding Tree (HT), Decision Tree (J48), Logistic Model Tree (LMT), Random Forest (RF), Random Tree (RT), and REP-Tree (REP-T). Performance of each technique is evaluated using different measures, i.e., mean absolute error (MAE), relative absolute error (RAE), root mean squared error (RMSE), root relative squared error (RRSE), specificity, precision, recall, F-measure (FM), G-measure (GM), Matthew’s correlation coefficient (MCC), and accuracy. The overall outcomes of this paper suggested RF technique by producing best results in terms of reducing error rates as well as increasing accuracy on five datasets, i.e., AR3, PC1, PC2, PC3, and PC4. The average accuracy achieved by RF is 90.2238%. The comprehensive outcomes of this study can be used as a reference point for other researchers. Any assertion concerning the enhancement in prediction through any new model, technique, or framework can be benchmarked and verified.

Mining social network data and developing user profile from unstructured and informal data are a challenging task. The proposed research builds user profile using Twitter data which is later helpful to provide the user with personalized recommendations. Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets. Semantic and syntactic analysis on tweets is performed to minimize information loss during the process of tweets classification. After precise classification and sentiment analysis, the system builds user interest-based profile by analyzing user’s post on Twitter to know about user interests. The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately.

Background: The main language of instruction for teaching medicine in most of the Arabic-speaking countries is English then French to a lesser extent. To our knowledge, Syria is the only Arab country that uses Arabic as the language of instruction in its medical colleges. Objective: This study explored the perspectives of decision-makers on the choice of English language for medical instruction in Saudi Arabia, in addition to, the academic, economic and social impact of this choice.This paper also explores their awareness of the languages used currently and in the past for teaching medicine and what obstacles are expected if Arabic language is adopted as the language of instruction in medicine. Methods: This was a qualitative study that purposively interviewed eight decision-makers at the university, regulatory, and ministerial levels on the choice of English language for medical instruction in Saudi Arabia. The semi-structured interviews were developed and conducted by the investigators. Each interview was audio taped and transcribed verbatim. Key themes were identified by the research team, with each theme representing an idea or a position. Results: All decision-makers expressed a positive attitude towards the choice of English for medical instruction, but there was also an overall support for a future Arabic curriculum, once obstacles are overcome. The availability of medical resources was the main factor which decision-makers agreed upon for the choice of language. There was also a consensus on the need to introduce Arabic in teaching communication skills. Conclusion: There is an overwhelming preference of choice for the English language over Arabic language for medical instruction. The adaptation of Arabic language was seen to have major obstacles but could be overcome through a given nationwide initiative. It is recommended to have future studies in assessing periodic changes in the perspective of choice of language in medicine. Keywords: Education, Teaching, Decision makers, Language of instruction, Qualitative

BACKGROUND: Platelet dysfunction may be one of the pathophysiologic complications in beta-thalassemia patients. However, the results obtained from the platelet aggregation vary in different types of β-thalassemia and among patients. OBJECTIVE: We evaluated the platelet function to determine risk of thrombosis in two groups': beta-thalassemia major (TM) and intermedia (TI). MATERIALS AND METHODS: In a cross-sectional study, platelets of 82 adult patients with beta-thalassemia (46 β-TM and 36 β-TI) who had undergone splenectomy and 85 normal healthy individuals as control were induced by collagen 10 μ g/ml, adenosine diphosphate (ADP) 20 μ M/l, arachidonic acid 500 μ M/l, and ristocetin 1500 μ g/ml. Independent t-test was used to compare the mean values using SPSS 16. P < 0.05 was taken to indicate statistical significance. RESULTS: Although a significant increase was observed in the platelet aggregation by collagen, ADP, and arachidonic acid in β-TM patients as compared with healthy controls, the β-TI patients showed no difference (P < 0.05). There was no significant alteration in response to ristocetin in β-TM but it reduced in β-TI. CONCLUSIONS: The platelet aggregation in β-TM patients is more than β-TI, both of whom splenectomized. The platelet aggregation in beta-thalassemia might be impressed by transfusion. Given these changes, thrombotic risk should be considered in beta-thalassemia patients.

The health industry is one of the most auspicious domains for the application of Internet of Things (IoT) based technologies. Lots of studies have been carried out in the health industry field to minimize the use of resources and increase the efficiency. The use of IoT combined with other technologies has brought quality advancement in the health sector at minimum expense. One such technology is the use of wireless body area networks (WBANs), which will help patients incredibly in the future and will make them more productive because there will be no need for staying at home or a hospital for a long time. WBANs and IoT have an integrated future as WBANs, like any IoT application, are a collection of heterogeneous sensor-based devices. For the better amalgamation of the IoT and WBANs, several hindrances blocking their integration need to be addressed. One such problem is the efficient routing of data in limited resource sensor nodes (SNs) in WBANs. To solve this and other problems, such as transmission of duplicate sensed data, limited network lifetime, etc., energy harvested and cooperative-enabled efficient routing protocol (EHCRP) for IoT-WBANs is proposed. The proposed protocol considers multiple parameters of WBANs for efficient routing such as residual energy of SNs, number of hops towards the sink, node congestion levels, signal-to-noise ratio (SNR) and available network bandwidth. A path cost estimation function is calculated to select forwarder node using these parameters. Due to the efficient use of the path-cost estimation process, the proposed mechanism achieves efficient and effective multi-hop routing of data and improves the reliability and efficiency of data transmission over the network. After extensive simulations, the achieved results of the proposed protocol are compared with state-of-the-art techniques, i.e., E-HARP, EB-MADM, PCRP and EERP. The results show significant improvement in network lifetime, network throughout, and end-to-end delay.

Nowadays, there is a growing trend in smart cities. Therefore, Terrestrial and Internet of Things (IoT) enabled Underwater Wireless Sensor Networks (TWSNs and IoT-UWSNs) are mostly used for observing and communicating via smart technologies. For the sake of collecting the desired information from the underwater environment, multiple acoustic sensors are deployed with limited resources, such as memory, battery, processing power, transmission range, etc. The replacement of resources for a particular node is not feasible due to the harsh underwater environment. Thus, the resources held by the node needs to be used efficiently to improve the lifetime of a network. In this paper, to support smart city vision, a terrestrial based “Away Cluster Head with Adaptive Clustering Habit” (ACH) 2 is examined in the specified three dimensional (3-D) region inside the water. Three different cases are considered, which are: single sink at the water surface, multiple sinks at water surface,, and sinks at both water surface and inside water. “Underwater (ACH) 2 ” (U-(ACH) 2 ) is evaluated in each case. We have used depth in our proposed U-(ACH) 2 to examine the performance of (ACH) 2 in the ocean environment. Moreover, a comparative analysis is performed with state of the art routing protocols, including: Depth-based Routing (DBR) and Energy Efficient Depth-based Routing (EEDBR) protocol. Among all of the scenarios followed by case 1 and case 3, the number of packets sent and received at sink node are maximum using DEEC-(ACH) 2 protocol. The packets drop ratio using TEEN-(ACH) 2 protocol is less when compared to other algorithms in all scenarios. Whereas, for dead nodes DEEC-(ACH) 2 , LEACH-(ACH) 2 , and SEP-(ACH) 2 protocols’ performance is different for every considered scenario. The simulation results shows that the proposed protocols outperform the existing ones.

مقدمه: به منظور غربال‌گری و انتخاب اهداكنندگان سالم، چگونگی برخورد با داوطلبین دارای عوامل خطر و این كه كدام‌یك و با چه عامل خطری، از اهدای خون معاف شود، از اهمیت خاصی برخوردار است. روش‌ها: در یك مطالعه‌ی هم‌گروهی در فاصله‌ی سال‌های 1390-1384 نقش عوامل خطر كوچك (Minor) برای انتقال عفونت‌های HBV (Hepatitis B virus)، HCV (Hepatitis C virus) و HIV (Human immunodeficiency virus) در بین اهداكنندگان خون در استان تهران مورد ارزیابی قرار گرفت. مواجهه با عوامل خطر متوسط و بزرگ به عنوان معیار خروج از مطالعه در نظر گرفته شد. داده‌های مربوط به مطالعه، از بانك اطلاعاتی MAK-SYSTEM International Group استخراج گردید. نسبت شانس و میزان بروز در دو گروه بدون مواجهه و دارای مواجهه محاسبه شد. به منظور محاسبه‌ی میزان بروز در اهداكنندگان با اهدای تكراری، تعداد اهداكنندگان Seroconverter بر تعداد كل شخص- سال در معرض خطر تقسیم شد. یافته‌ها: از 19044 نفر داوطلب اهدای خون وارد شده به مطالعه در سال 1384، 10696 نفر در گروه بدون مواجهه (بدون عامل خطر) و 8348 نفر در گروه دارای مواجهه با عامل خطر كوچك تا سال 1390 پی‌گیری شدند. نسبت شانس برای اهداكنندگان دارای مواجهه 7/2 و در زیرگروه‌های حجامت 9/2، دندان‌پزشكی 4/1، آندوسكوپی و بیوپسی 5/1 و تماس خانگی 8/7 به دست آمد. خطر نسبی محاسبه شده برای HBV در گروه دارای مواجهه و زیرگروه عامل خطر حجامت، به ترتیب 9/6 و 9/9 محاسبه شد. نتیجه‌گیری: نتایج این مطالعه نشان می‌دهد که اعمال معافیت در خصوص موارد مواجهه با عوامل خطر كوچك، به خصوص در مورد حجامت، امری ضروری است و هر گونه تغییر سیاست در پذیرش اهداكنندگان در كشورمان، تا زمان كاربرد روش‌های غربال‌گری دقیق‌تری همچون Nucleic acid-based tests (NAT) یا Polymerase chain reaction (PCR) و اعلام نتایج پژوهش‌های بعد از آن، شتاب‌زده خواهد بود.

Objective: In some medical circumstances, pediatric patients may need premedication for transferring to the operating room. In these situations, using intravenous premedication is preferred. We assessed the efficacy and safety of intravenous midazolam, intravenous ketamine, and combination of both to reduce the anxiety and improve behavior in children undergoing general anesthesia. Methods: In a double-blind randomized clinical trial, 90 pediatric patients aged 6 months to 6 years with American Society of Anesthesiologist grade I or II were enrolled. Before anesthesia, children were randomly divided into three groups to receive intravenous midazolam 0.1 mg/kg, or intravenous ketamine 1 mg/kg, or combination of half doses of both. Behavior types and sedation scores were recorded before premedication, after premedication, before anesthesia, and after anesthesia in the postanesthesia care unit. Anesthesia time, recovery duration, blood pressure, and heart rate were also recorded. For comparing distribution of behavior types and sedation scores among three groups, we used Kruskal–Wallis test, and for comparing mean and standard deviation of blood pressure and heart rates, we used analysis of variance. Findings: After premedication, children's behavior was significantly better in the combination group (P < 0.001). After anesthesia, behavior type was same among three groups (P = 0.421). Sedation scores among three groups were also different after premedication and the combination group was significantly more sedated than the other two groups (P < 0.001). Conclusion: Combination of 0.05 mg/kg of intravenous midazolam and 0.5 mg/kg of intravenous ketamine as premedication produced more deep sedation and more desirable behavior in children compared with each midazolam 0.1 mg/kg or ketamine 1 mg/kg.

Background: To assess the proportion of Pakistani patients achieving blood pressure goal while on existing antihypertensive therapy and reasons for not achieving BP goal. Methods: This descriptive study was conducted in 60 centers across 10 cities of Pakistan by simple random sampling. It was a national, multi-centre, noninterventional, cross-sectional, epidemiological disease registry. Patients, who were ≥15 years of age, on antihypertensive medications for ≥4 weeks and had taken a dose on the day of visit, were included. Investigators were randomly selected from a list of physicians within a given geographical territory (Urban) in major cities of Pakistan. Approximately 58% of the physicians were general practitioners and 42% were specialist such as medical internist and cardiologist. Reasons for not achieving BP goal was determined by assessing different variables. Changes made in BP management in patients not at BP goal and therapeutic regimens prescribed to patients at BP goal were also documented. Differences in the profile of patients according to the attainment of BP goal were analyzed using bi-variate analysis. A p

ntroduction:Leishmaniasis is one of the six important tropical diseases, different aspects of which are required to be studied, as recommended by World Health Organization. This study investigated the status of Antroponotic cutaneous leishmaniasis (ACL) in Larestan.Material and Methods:This was a cross-sectional descriptive study. Data were gathered through the epidemiological survey forms of the patients including questions on age, sex, the number of sores, location of the lesion, place of residence, and the type of construction. The data were analyzed by SPSS, version 15.Results:From776 patients, 327 (42.1%) were male and 449 (57.9%) female. The highest prevalence was in the age group of 0-9 years (43.9%) and the lowest was in 60+, 33 (4.3%). The mean of age and its standard deviation were 18.27 and 17.8, respectively with the range of 1-84. Of the patients, 575 (74.1%) were villagers and 201(25.9%) of them were residents of the urban areas. More than 484 (62.4%) patients had more than one sore. 406 (52.3%) of them were living in newly-built houses and 47.7 were living in old house. The high risk parts of the body were the hands; 301(58.4%) patients had sores on their hands.Conclusion:This study showed that the sex pattern of the disease differs from that in other areas and children under 10 years of age are mostly at risk. Also, leishmaniasis was mostly seen in rural areas; therefore, prevention measures must be taken together with education for groups at risk.

BACKGROUND: Using two logistic regression models, we determined the associates of poor physical and mental health related quality of life (HRQoL) among beta thalassemia patients.METHODS: In this cross-sectional study which was conducted during 2006 and 2007 in outpatient adult thalassemia clinic, Blood Transfusion Organization, Tehran, Iran, Short Form 36 (SF-36) was used for measuring HRQoL in 179 patients with beta thalassemia (major/intermedia). We determined scores higher than third quartiles of obtained PCS and MCS scores as the cutoff points of good HRQoL. Poor HRQoL was defined scores lower than first quartiles of obtained PCS and MCS scores. Two distinct logistic regression models were used to derive associated variables including demographic, clinical, and psychological factors.RESULTS: The regression models suggested that poor physical HRQoL was positively associated with somatic comorbidities (OR = 1.472, CI = 1.021-2.197, p = 0.048) and depression score (OR = 8.568, CI = 2.325-31.573, p = 0.001). The variables that were associated with poor mental HRQoL were anxiety score (OR = 9.409, CI = 1.022-89.194, p = 0.049) and depression score (OR = 20.813, CI = 4.320-100.266, p < 0.001).CONCLUSIONS: Depression is associated with both poor physical and mental HRQoL among patients with major/intermedia beta thalassemia, however somatic comorbidities and anxiety are associated with poor physical and mental HRQoL, respectively.KEYWORDS: Thalassemia, Health Related Quality of Life, Anxiety, Depression, Somatic Comorbidities.

Mannose-binding lectin (MBL) is a Ca⁺² -dependent collagenous lectin, that is produced by liver and mediates innate immune responses by opsonization of pathogens. The serum level of MBL varies widely among healthy individuals, ranging from 0.05 µg/ml (or lower) to over 5 µg/ml, mainly depending on genetic variation. This study has examined promoter and exon 1 of mbl2 genotype among 117 Iranian healthy blood donors. MBL Single Nucleotide Polymorphisms (SNPs) were genotyped using polymerase chain reaction (PCR), and serum levels of MBL were quantified using a double-antibody enzyme linked immunosorbent assay (ELISA). Results of this study showed that there are two promoter polymorphisms at -550 (H/L variants) and -221 (Y/X variants) positions, and three polymorphisms in exon 1 at codon 52 (D Allele), 54 (B Allele), and 57 (C Allele) in this population. B allele was significantly correlated with the lowest serum MBL level. Our results also showed that the most frequent genotype was HYA/LXA, and the genotype that associated with the highest serum level of MBL was HYA/HYA. The genotype that causes lowest MBL production in Iranian population was LYB/LXA. These results showed some differences compared to that of the other populations. To verify the originality of these differences we may need to extend the study to a larger samples of respective populations; meanwhile the importance of a new mutation, nucleotide 101 of MBL2 exon1, reported in the current study should be taken in considerations in terms of its possible pathobiological effects in following studies.

A middle aged female presented in emergency department with chest discomfort. Her old electrocardiogram(EKG) showed left bundle branch block (LBBB) signs. EKG performed in the emergency room revealedleft bundle branch block with 4-6 mm discordant ST segment elevation in leads V1-V3 and 1mm concordantST segment elevation in lead V4. Diagnosis o f acute anterior wall STEMI was made based on Sgarbossacriteria. She underwent angiography which showed total occlusion o f proximal left anterior descendingartery which was stented. She had uneventful post-stenting course in hospital and was discharged. The casehighlights the significance of Sgarbossa criteria which can be applied to diagnose acute myocardial infarctionin the presence o f LBBB so th at prompt thrombolytic or primary angioplasty can be preformed.

Limited literature exists on men's experiences with intimate partner violence (IPV) during the COVID-19 lockdown, especially in resource-constrained settings like Nigeria. We investigated the prevalence, risk factors, and lifetime experiences of IPV among men in Nigeria, during COVID-19 restrictions. Using a mixed methods design, we interviewed 420 married men with a structured questionnaire and conducted 20 in-depth interviews. Logistic regression and a framework approach were used for data analysis. Approximately 86.4% of respondents (n=363) experienced IPV at some point in their lifetime. The prevalence of IPV during the COVID-19 restrictions was 76.2% (n=320). Over a lifetime, verbal (67.4%), physical (78.1%), and sexual coercion (81.0%) were the most common forms of IPV. During the COVID-19 lockdown, the corresponding proportions were 48.6%, 69.5%, and 57.4%, respectively. Male- and female-perpetrated IPV over a lifetime (88.3% vs 87.6%) and during COVID-19 restrictions (88.3% vs 81.4%) were similar (p>0.05). Older age, non-Muslim religion, longer marital duration, partner's profession, and no formal education were associated with higher IPV risk. Home confinement, financial stress, childbirth, disrespect towards spouse's parents, emotional detachment, disputes about child discipline, and suspected infidelity contributed to IPV. Men's active involvement in family life, improved communication, and increased transparency emerged as protective factors. Our findings highlight the high rates of IPV during the pandemic, with men as both perpetrators and victims. Future epidemic preparedness plans should prioritize IPV prevention strategies that enhance partner communication, promote male involvement in family life, address the gender education gap, and provide support services., Competing Interests: Disclosure Statement: All authors declare no conflicts of interest.

HIV self-testing (HIVST) holds promise for accessing hard-to-reach populations by overcoming sociocultural and structural barriers to awareness of HIV status. This phenomenological qualitative study explored the experiences and perspectives of married men in Kano, northern Nigeria, regarding HIV testing and counseling (HTC) and HIVST. Twenty married men from diverse socioeconomic backgrounds participated in in-depth interviews conducted in the local language. Thematic analysis was employed to analyze the data, yielding key themes related to prior test experiences, knowledge of self-testing, and perceived ease of use, in addition to motivation for self-testing and concerns about reliability and counseling support. The findings shed light on the impact of facility-based HIV testing experiences on the perspectives of participants. Concerns related to delays, overcrowding, discomfort, fear, and unsupportive attitudes from healthcare providers influenced their perceptions. Among persons with previous self-testing experience, initial uneasiness was overcome with repeated use, highlighting the ease of use associated with HIVST. Motivations for self-testing included privacy, convenience, personal empowerment, improved infection detection, and efficiency. Concerns were raised regarding the reliability of self-testing results compared to hospital-based testing, and the absence of counseling support during self-testing. Our findings underscore the need to address infrastructural limitations, enhance counseling support, and promote awareness and knowledge of HIVST., Competing Interests: The authors declare that they have no conflicts of interest regarding the publication of this paper., (Copyright © 2024 Zubairu Iliyasu et al.)