Liaquat University of Medical & Health Sciences

BACKGROUND: There are approximately 4 million neonatal deaths and half a million maternal deaths worldwide each year. There is limited evidence from clinical trials to guide the development of effective maternity services in developing countries. METHODS: We performed a cluster-randomized, controlled trial involving seven subdistricts (talukas) of a rural district in Pakistan. In three talukas randomly assigned to the intervention group, traditional birth attendants were trained and issued disposable delivery kits; Lady Health Workers linked traditional birth attendants with established services and documented processes and outcomes; and obstetrical teams provided outreach clinics for antenatal care. Women in the four control talukas received usual care. The primary outcome measures were perinatal and maternal mortality. RESULTS: Of the estimated number of eligible women in the seven talukas, 10,114 (84.3 percent) were recruited in the three intervention talukas, and 9443 (78.7 percent) in the four control talukas. In the intervention group, 9184 women (90.8 percent) received antenatal care by trained traditional birth attendants, 1634 women (16.2 percent) were seen antenatally at least once by the obstetrical teams, and 8172 safe-delivery kits were used. As compared with the control talukas, the intervention talukas had a cluster-adjusted odds ratio for perinatal death of 0.70 (95 percent confidence interval, 0.59 to 0.82) and for maternal mortality of 0.74 (95 percent confidence interval, 0.45 to 1.23). CONCLUSIONS: Training traditional birth attendants and integrating them into an improved health care system were achievable and effective in reducing perinatal mortality. This model could result in large improvements in perinatal and maternal health in developing countries.

BACKGROUND: Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. METHODS: GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. FINDINGS: The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. INTERPRETATION: We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. FUNDING: Gates Foundation.

Diabetes mellitus poses a substantial global health challenge, necessitating innovative approaches to improve patient outcomes. Conventional one-size-fits-all treatment strategies have shown limitations in addressing the diverse nature of the disease. In recent years, personalized medicine has emerged as a transformative solution, tailoring treatment plans based on individual genetic makeup, lifestyle factors, and health characteristics. This review highlights the role of genetic screening in predicting diabetes susceptibility and response to treatment, as well as the potential of pharmacogenomics in optimizing medication choices. Moreover, it discusses the incorporation of lifestyle modifications and behavioral interventions to empower patients in their health journey. Telemedicine and remote patient monitoring are also examined for their role in enhancing accessibility and adherence. Ethical considerations and challenges in implementing personalized medicine are addressed. The review envisions a future where personalized medicine becomes a cornerstone in diabetes management, ensuring improved patient outcomes and fostering more effective and patient-centric care on a global scale.

OBJECTIVES: To determine the frequency, risk factors and pattern of urinary complaints during pregnancy. METHODS: A descriptive study was conducted in the Obstetric and Gynaecology Department of Isra University Hospital, Hyderabad from 1st January to 30th August 2008. Total 232 women were selected to ascertain the frequency and pattern of urinary symptoms as well as the risk factors of urinary tract infection (UTI) such as age, parity, education, past history of UTI and haemoglobin among women attending an antenatal clinic. All pregnant women irrespective of age, parity and gestational age were included, while women with known underlying renal pathology, chronic renal disease, renal transplant, diabetes or taking immunosuppressant therapy were excluded. Informed consent was taken and data collected on a self designed proforma. All the women underwent complete examination of urine. Dipstick test was performed on midstream urine and urine was cultured incase of positive dipstick test and women with urinary symptoms. Data was analyzed on SPSS version 11. Odds ratio and 95% confidence interval were calculated among the categorical parameters by applying the Fisher's exact test. RESULTS: Out of 232 women, 108(46.5%) reported urinary symptoms which were due to pregnancy induced changes on urinary system as no growth was obtained on urine culture, while 10 (4.3%) were due to underlying UTI. Most common urinary symptom in these women was abnormal voiding pattern 85 (40.3%) followed by irritative symptoms and voiding difficulties. Illiteracy, history of sexual activity, low socioeconomic (monthly income < Rs. 10,000 / month) group, past history of UTI and multiparity were found to be risk factors for UTI in these women. On complete urine examination, 222 (95.6%) patients either did not reveal any pus cells or had less than 5 WBC/HPF. Out of 108 cultures, only 10 (4.3%) specimens showed growth. E-coli was the most commonly detected organism 7 (3%) followed by S-aureus in 3 (1.3%). CONCLUSION: The common urinary symptoms encountered in the studied women were abnormal voiding pattern followed by irritative symptoms. Majority of urinary symptoms were due to pregnancy related changes in the urinary system. Past history of UTI, sexual activity, lower socioeconomic group and multi parity were significant risk factors for UTI.

Heart Disease has become one of the most serious diseases that has a significant impact on human life. It has emerged as one of the leading causes of mortality among the people across the globe during the last decade. In order to prevent patients from further damage, an accurate diagnosis of heart disease on time is an essential factor. Recently we have seen the usage of non-invasive medical procedures, such as artificial intelligence-based techniques in the field of medical. Specially machine learning employs several algorithms and techniques that are widely used and are highly useful in accurately diagnosing the heart disease with less amount of time. However, the prediction of heart disease is not an easy task. The increasing size of medical datasets has made it a complicated task for practitioners to understand the complex feature relations and make disease predictions. Accordingly, the aim of this research is to identify the most important risk-factors from a highly dimensional dataset which helps in the accurate classification of heart disease with less complications. For a broader analysis, we have used two heart disease datasets with various medical features. Firstly, we performed the correlation and inter-dependence of different medical features in the context of heart disease. Secondly, we applied a filter-based feature selection technique on both datasets to select most relevant features (an optimal reduced feature subset) for detecting the heart disease. Finally, various machine learning classification models were investigated using complete and reduced features subset as inputs for experimentation analysis. The trained classifiers were evaluated based on Accuracy, Receiver Operating Characteristics (ROC) curve, and F1-Score. The classification results of the models proved that there is a high impact of relevant features on the classification accuracy . Even with a reduced number of features, the performance of the classification models improved significantly with a reduced training time as compared with models trained on full feature set.

Background: Quercetin, a well-known naturally occurring polyphenol, has recently been shown by molecular docking, in vitro and in vivo studies to be a possible anti-COVID-19 candidate. Quercetin has strong antioxidant, anti-inflammatory, immunomodulatory, and antiviral properties, and it is characterized by a very high safety profile, exerted in animals and in humans. Like most other polyphenols, quercetin shows a very low rate of oral absorption and its clinical use is considered by most of modest utility. Quercetin in a delivery-food grade system with sunflower phospholipids (Quercetin Phytosome ® , QP) increases its oral absorption up to 20-fold. Methods: In the present prospective, randomized, controlled, and open-label study, a daily dose of 1000 mg of QP was investigated for 30 days in 152 COVID-19 outpatients to disclose its adjuvant effect in treating the early symptoms and in preventing the severe outcomes of the disease. Results: The results revealed a reduction in frequency and length of hospitalization, in need of non-invasive oxygen therapy, in progression to intensive care units and in number of deaths. The results also confirmed the very high safety profile of quercetin and suggested possible anti-fatigue and pro-appetite properties. Conclusion: QP is a safe agent and in combination with standard care, when used in early stage of viral infection, could aid in improving the early symptoms and help in preventing the severity of COVID-19 disease. It is suggested that a double-blind, placebo-controlled study should be urgently carried out to confirm the results of our study. Keywords: SARS-CoV-2, infectious diseases, coronavirus, pneumonia, botanicals, Phytosome ®

AnkyrinG, encoded by the ANK3 gene, is involved in neuronal development and signaling. It has previously been implicated in bipolar disorder and schizophrenia by association studies. Most recently, de novo missense mutations in this gene were identified in autistic patients. However, the causative nature of these mutations remained controversial. Here, we report inactivating mutations in the Ankyrin 3 (ANK3) gene in patients with severe cognitive deficits. In a patient with a borderline intelligence, severe attention deficit hyperactivity disorder (ADHD), autism and sleeping problems, all isoforms of the ANK3 gene, were disrupted by a balanced translocation. Furthermore, in a consanguineous family with moderate intellectual disability (ID), an ADHD-like phenotype and behavioral problems, we identified a homozygous truncating frameshift mutation in the longest isoform of the same gene, which represents the first reported familial mutation in the ANK3 gene. The causality of ANK3 mutations in the two families and the role of the gene in cognitive function were supported by memory defects in a Drosophila knockdown model. Thus we demonstrated that ANK3 plays a role in intellectual functioning. In addition, our findings support the suggested association of ANK3 with various neuropsychiatric disorders and illustrate the genetic and molecular relation between a wide range of neurodevelopmental disorders.

BACKGROUND: Chronic kidney disease (CKD) is common and ranks among the leading causes of mortality and morbidity. This analysis aimed to present global CKD estimates using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 to inform evidence-based policies for CKD identification and treatment. METHODS: This analysis focused on adults aged 20 years and older over the period 1990 to 2023, from 204 countries and territories. Data sources used were published literature, vital registration systems, kidney failure treatment registries, and household surveys. Estimates of CKD burden, including deaths, incidence, prevalence, and disability-adjusted life-years (DALYs), were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool. A comparative risk assessment approach estimated the proportion of cardiovascular deaths attributable to impaired kidney function and estimated risk factors for CKD. FINDINGS: Globally, in 2023, 788 million (95% uncertainty interval 743-843) people aged 20 years and older were estimated to have CKD, up from 378 million (354-407) in 1990. The global age-standardised prevalence of CKD in adults was 14·2% (13·4-15·2), a relative rise of 3·5% (2·7-4·1) from 1990. The region with the highest age-standardised prevalence was north Africa and the Middle East (18·0%; 16·9-19·4). Most people had stage 1-3 CKD, with a combined prevalence of 13·9% (13·1-15·0). In 2023, CKD was the ninth leading cause of death globally, accounting for 1·48 million (1·30-1·65) deaths, and the 12th leading cause of DALYs, with an age-standardised DALY rate of 769·2 (691·8-857·4) per 100 000. Impaired kidney function as a risk factor accounted for 11·5% (8·4-14·5) of cardiovascular deaths. High fasting plasma glucose, body-mass index, and systolic blood pressure were all leading risk factors for CKD DALYs. INTERPRETATION: CKD is a major global health issue, with rising prevalence and increasing importance as a cause of death and as a risk factor for cardiovascular death. A better understating of aetiology, appropriate screening, and implementation programmes are needed to translate advances in CKD treatment into improved patient outcomes. FUNDING: Gates Foundation, Wellcome, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.

Environment pollution is a wide-reaching problem and it is likely to influence the health of human populations is great. This paper provides the insight view about the affects of environment pollution in the perspective of air pollution, water and land/ soil waste pollution on human by diseases and problems, animals and trees/ plants. Study finds that these kinds of pollutions are not only seriously affecting the human by diseases and problems but also the animals and trees/ plants. According to author, still time left in the hands of global institutions, governments and local bodies to use the advance resources to balance the environment for living and initiates the breathed intellectuals to live friendly with environment. As effective reply to contamination is largely base on human appraisal of the problem from every age group and contamination control program evolves as a nationwide fixed cost-sharing effort relying upon voluntary participation (Sharp & Bromley, 1979).

The objective of this study was to evaluate the association between trace and toxic elements zinc (Zn), cadmium (Cd), nickel (Ni) and lead (Pb) in biological samples (scalp hair, blood and urine) of smoker and nonsmoker hypertensive patients (n=457), residents of Hyderabad, Pakistan. For the purpose of comparison, the biological samples of age-matched healthy controls were selected as referents. The concentrations of trace and toxic elements were measured by atomic absorption spectrophotometer prior to microwave-assisted acid digestion. The validity and accuracy of the methodology were checked using certified reference materials and by the conventional wet acid digestion method on the same certified reference materials and real samples. The recovery of all the studied elements was found to be in the range of 97.8-99.3% in certified reference materials. The results of this study showed that the mean values of Cd, Ni and Pb were significantly higher in scalp hair, blood and urine samples of both smoker and nonsmoker patients than in referents (P<0.001), whereas the concentration of Zn was lower in the scalp hair and blood, but higher in the urine samples of hypertensive patients. The deficiency of Zn and the high exposure of toxic metals as a result of tobacco smoking may be synergistic with risk factors associated with hypertension.

Introduction As a result of the ongoing COVID-19 pandemic, health care professionals (HDPs) are facing immense strain due to the heavy load of cases. In many cases, they work increasingly long hours, often with limited resources and a dubious infrastructure. Thus, it is important to check on the mental health of caregivers. Methods and materials This cross-sectional study was conducted in May 2020, at various hospitals in Karachi, Pakistan. All HCPs posted in the COVID-19 isolation wards were invited to participate and a total of 112 completed this study. A carefully structured form was created, which included the Depression Anxiety Stress Scale-21 (DASS-21). Results The overall mean score of anxiety was 19.01 ± 9.2, depression was 18.12 ± 10, and stress was 20.12 ± 12.0. There were 81 (72.3%) participants who suffered from moderate to extremely severe depression, 96 ( 85.7%) participants who suffered from moderate to extremely severe anxiety, and 101 (90.1%) participants who reported moderate to extreme stress levels Conclusions It is evident that there are a high number of healthcare workers affected by various psychological ailments such as anxiety, stress, and depression. It is important that the government take steps to ensure that HCPs' mental health is regularly checked and that efforts are made to reduce their burdens.

Background: Senescent cells (SCs) are involved in proliferative disorders, but their role in pulmonary hypertension remains undefined. We investigated SCs in patients with pulmonary arterial hypertension and the role of SCs in animal pulmonary hypertension models. Methods: We investigated senescence (p16, p21) and DNA damage (γ-H2AX, 53BP1) markers in patients with pulmonary arterial hypertension and murine models. We monitored p16 activation by luminescence imaging in p16-luciferase (p16 LUC/+ ) knock-in mice. SC clearance was obtained by a suicide gene (p16 promoter–driven killer gene construct in p16-ATTAC mice), senolytic drugs (ABT263 and cell-permeable FOXO4-p53 interfering peptide [FOXO4-DRI]), and p16 inactivation in p16 LUC/LUC mice. We investigated pulmonary hypertension in mice exposed to normoxia, chronic hypoxia, or hypoxia+Sugen, mice overexpressing the serotonin transporter (SM22-5-HTT + ), and rats given monocrotaline. Results: Patients with pulmonary arterial hypertension compared with controls exhibited high lung p16, p21, and γ-H2AX protein levels, with abundant vascular cells costained for p16, γ-H2AX, and 53BP1. Hypoxia increased thoracic bioluminescence in p16 LUC/+ mice. In wild-type mice, hypoxia increased lung levels of senescence and DNA-damage markers, senescence-associated secretory phenotype components, and p16 staining of pulmonary endothelial cells (P-ECs, 30% of lung SCs in normoxia), and pulmonary artery smooth muscle cells. SC elimination by suicide gene or ABT263 increased the right ventricular systolic pressure and hypertrophy index, increased vessel remodeling (higher dividing proliferating cell nuclear antigen–stained vascular cell counts during both normoxia and hypoxia), and markedly decreased lung P-ECs. Pulmonary hemodynamic alterations and lung P-EC loss occurred in older p16 LUC/LUC mice, wild-type mice exposed to Sugen or hypoxia+Sugen, and SM22-5-HTT + mice given either ABT263 or FOXO4-DRI, compared with relevant controls. The severity of monocrotaline-induced pulmonary hypertension in rats was decreased slightly by ABT263 for 1 week but was aggravated at 3 weeks, with loss of P-ECs. Conclusions: Elimination of senescent P-ECs by senolytic interventions may worsen pulmonary hemodynamics. These results invite consideration of the potential impact on pulmonary vessels of strategies aimed at controlling cell senescence in various contexts.

The determination of toxic elements in the biological samples of human beings is an important clinical screening procedure. The aim of this work was to determine total content of toxic elements-aluminum (Al), cadmium (Cd), and lead (Pb)-in whole blood and urine samples of male chronic renal failure patients (CRFPs) on maintenance hemodialysis from 2006 to 2007. The study included 100 CRFPs, plus 150 healthy volunteers in the control group. The concentration of toxic elements (TEs) were determined in blood sample before and after hemodialysis, while urine sample was determined once, before dialysis. Toxic elements were analyzed by electrothermal atomic absorption spectrometer, prior to microwave-induced acid digestion. The accuracy of the total Al, Cd, and Pb measurements was tested by simultaneously analyzing certified reference materials. No significant differences were established between the analytical results and the certified values (paired t-test at p > 0.05). The levels of TEs in blood samples of patients before dialysis were found to be higher than blood samples after dialysis session. In the control group, the blood levels of Al, Cd, and Pb were significantly lower than the chronic renal failure patients. Moreover, the study shows that analyzing levels of Al, Cd, and Pb may be useful in hemodialysis patients in evaluating TEs status.

Heart failure is a substantial and escalating global health challenge, affecting millions worldwide. This complex syndrome arises from diverse etiologies, encompassing ischemic heart disease, hypertension, valvular abnormalities, and cardiomyopathies. Heart failure is characterized by the heart's inability to pump blood efficiently to meet the body's metabolic demands, leading to debilitating symptoms, frequent hospitalizations, and high mortality rates. Traditionally, the management of Heart failure has focused on alleviating symptoms, reducing fluid retention, and enhancing cardiac contractility. These goals have been achieved through a combination of pharmacological therapies such as angiotensin-converting enzyme inhibitors, beta-blockers, and diuretics, often complemented by device-based interventions like implantable cardioverter-defibrillators and cardiac resynchronization therapy. However, despite these advances, the relentless progression of heart failure remains a significant clinical challenge. Neurohormonal activation, cardiac fibrosis, and cellular remodeling are just a few of the intricate processes contributing to the disease's progression. In recent years, researchers and clinicians have embarked on a quest to identify novel therapeutic approaches that address these underlying mechanisms. One such avenue of exploration involves the revolutionary field of gene therapy, with promising gene-editing techniques, such as CRISPR-Cas9, offering potential routes for correcting genetic mutations that contribute to heart failure. Additionally, regenerative medicine approaches, including stem cell therapy and tissue engineering, hold significant promise for repairing damaged cardiac tissue and restoring function. Furthermore, precision medicine initiatives have gained traction, aiming to tailor heart failure therapies to individual patient profiles, taking into account genetics, biomarkers, and comorbidities. Integrating artificial intelligence and machine learning in heart failure management has also enabled the development of predictive models for early intervention, risk stratification, and personalized treatment recommendations. This narrative review navigates the intricate landscape of emerging therapies for heart failure, emphasizing their potential to revolutionize the field by targeting the disease's fundamental mechanisms. By exploring these innovative approaches, we aspire to provide a comprehensive perspective on the evolving paradigm of heart failure management, fostering a hopeful outlook for patients and clinicians alike.

BACKGROUND: Salmonella enterica serotype Typhi (S Typhi) is a major public health problem in low-income and middle-income countries. We aimed to investigate the effectiveness and impact of the typhoid conjugate vaccine Typbar-TCV against S Typhi among children in an outbreak setting of extensively drug-resistant (XDR) S Typhi in Pakistan. METHODS: This cohort study was done from Feb 21, 2018, to Dec 31, 2019. A census survey of all households located in the Qasimabad and Latifabad subdistricts of Hyderabad, Pakistan, was done at baseline, and 174 005 households were registered in the census. The Typbar-TCV immunisation campaign was initiated at temporary vaccination centres and 207 000 children aged 6 months to 10 years were vaccinated from Feb 21, 2018, to Dec 31, 2018. Social mobilisers informed parents about the vaccination process. Vaccination records were maintained electronically and linked with the household census surveys. Active surveillance for suspected and blood-culture-confirmed S Typhi was established in hospitals, clinics, and laboratories to assess the following outcomes: cases of suspected typhoid fever, culture-confirmed S Typhi, and antimicrobial resistance. An age-stratified cohort of 1100 vaccinated children was randomly selected from the vaccination registry, tested for Vi-IgG antibodies (data not reported), and followed up fortnightly (via telephone calls or household visits) until Dec 31, 2019, for ascertainment of outcomes during the study period. 20 847 vaccinated and unvaccinated children were randomly selected from the census registry as a quality control cohort and followed up from Oct 1 to Dec 31, 2019, for ascertainment of outcomes. Vaccine effectiveness against suspected, culture-confirmed, and XDR S Typhi was calculated. FINDINGS: 23 407 children from the census registry and surveillance system were included in the vaccine effectiveness analysis. 13 436 (57·4%) children were vaccinated, 12 214 (52·2%) were male, and 10 168 (43·4%) were aged 6-59 months. 5378 (23·0%) of 23 407 children had suspected S Typhi, among whom 775 (14·4%) had culture-confirmed S Typhi and 361 (68·6%) of 526 had XDR S Typhi. Vaccine effectiveness was 55% (95% CI 52-57) against suspected S Typhi (regardless of culture confirmation), 95% (93-96) against culture-confirmed S Typhi, and 97% (95-98) against XDR S Typhi. INTERPRETATION: Typbar-TCV is effective in protecting children against S Typhi infection in an outbreak setting, and was able, with moderate deployment, to curtail a major XDR S Typhi outbreak in a densely populated setting. The vaccine shows efficacy against S Typhi irrespective of antimicrobial resistance. FUNDING: Bill & Melinda Gates Foundation.

Introduction The overall environment of the medical school is often considered very stressful. It projects negative effects not only on the academic performances of medical students but also deteriorate their physical health and psychosocial wellbeing. The aim of this study was to determine the frequency of depression, stress, and anxiety among final year medical students. Methods This observational study was conducted in public and private medical colleges in February 2019. The instrument utilized in this study was Depression, Anxiety, and Stress Scale (DASS-21). Factors predisposing to depression, stress, and anxiety were also recorded. Data were entered and analyzed using SPSS v. 21. Results The mean scores of depression, anxiety, and stress were 18.00 ± 11.5, 19.15 ± 11.2, and 20.92 ± 11.2, respectively. The mean score of anxiety and stress was higher in private college students, while that of depression was higher in public college students. Overall, 57.6% of the students suffered from moderate to extremely severe depression, 74% of the students suffered from moderate to extremely severe anxiety, and 57.7% students had moderate to extremely severe stress. The common reasons to high stress and anxiety included the pressure of passing exams, the pressure of living up to family's expectations, fear of stepping into the real world of medicine, and dissatisfaction with the administration. Conclusion The incidence of psychological illnesses including anxiety, stress, and depression is high among the medical students of Pakistan. Reasons predisposing the students to these illnesses must be efficiently tackled.

As an analytic tool in medicine, particularly in radiology, deep learning is gaining much attention and opening a new way for disease diagnosis. Nonetheless, it is rather challenging to acquire large‐scale detailed labelled datasets in the field of medical imaging. In fact, transfer learning provides a possible way to resolve this issue to a certain extent such that the parameter learning of a neural network starts with its pre‐trained weights learned from a large‐scale dataset of certain similar task, and fine‐tunes on a small comprehensively annotated dataset for the particular target task. The main aim of this study is to apply the deep learning model to detect the synovial fluid of human knee joint from magnetic resonance images. A specialized convolutional neural network architecture is proposed for automated detection of human knee joint's synovial fluid. Two independent datasets are used in the training, development, and evaluation of the proposed model. It is demonstrated by the experimental results that the proposed model obtains high sensitivity, specificity, precision, and accuracy to the detection of human knee joint's synovial fluid. As a result, this proposed approach provides a novel and feasible way for automating and expediting the synovial fluid analysis.

The coronaviruses (CoVs) belongs to the subgroup Orthocoronavirinae in the family Coronaviridae, Order Nidovirales.1 During 2002, the China reports first outbreak of SARS quickly spread worldwide, leads to approximately 11% fatality rate while during 2012;2 Middle East Respiratory Syndrome (MERS) originates in Saudi Arabia followed by its spread worldwide with 37% mortality.3 During December 2019, an pneumonia of unknown etiology has been detected in vast majority of patients resides in Wuhan City, Central China and Hubei Province.4 The Genomic research has been identified that this pneumonia considered as coronavirus disease 2019 caused by novel corona virus (CoV) labeled as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), formerly called as 2019-novel coronavirus (2019-nCoV).5 The screening and management strategies are not sufficient to end the battled against COVID-19.6 The survivors face various long terms symptoms produced by COVID-19 which are still the matter of debate.7 The literature reported 50-90% individuals have persistent symptoms and considered as long-haulers but due to confounders as gender, age, race, duration and severity of infection, short term study period and follow ups the results are hampered and limited.8

century. However, regrettably, a potential decline in life expectancy has been proposed for these nations in the 21st century due to a rapid upsurge in the prevalence of fatal degenerative diseases like cardiovascular diseases (CVD), cancer and diabetes. Collectively, these three diseases accounted for 65% of all deaths in urbanized societies and were considered as a dynamic issue for shortening the genetically determined lifespan through increased mortalities, morbidities, disabilities, immense sufferings, and premature aging. These fatal degenerative diseases and premature aging are closely associated with oxidative stress produced by the free radicals in the body. In epidemiologic studies, flavonoid-rich foods (FRF) like fruits, vegetables, and beverages have been associated as protective agents against these diseases. These also have been observed for their geroprotective effects and help in preventing premature aging and deterioration of brain function, which is related to Alzheimer's disease and dementia. In this review, we presented a comprehensive overview of the FRF for their potential role against lifespan-shortening complications, i.e., CVD, cancer, and diabetes. We also have drawn the future perspective and dietary guidelines to reduce the fatal disease burden in urban populations.

Background The coronavirus disease (COVID-19) pandemic has put an excessive strain on healthcare systems across the globe, causing a shortage of personal protective equipment (PPE). PPE is a precious commodity for health personnel to protect them against infections. We investigated the availability of PPE among doctors in the United States (US) and Pakistan. Methods A cross-sectional study, including doctors from the US and Pakistan, was carried out from April 8 to May 5, 2020. An online self-administered questionnaire was distributed to doctors working in hospitals in the US and Pakistan after a small pilot study. All analysis was done using Statistical Package for Social Science (SPSS) version 23.0 (IBM Corp., Armonk, NY). Results After informed consent, 574 doctors (60.6% from Pakistan and 39.4% from the US) were included in the analysis. The majority of the participants were females (53.3%), and the mean age of the participants was 35.3 ± 10.3 years. Most doctors (47.7%) were from medicine and allied fields. Among the participants, 87.6% of doctors from the US reported having access to masks/N95 respirators, 79.6% to gloves, 77.9% to face-shields or goggles, and 50.4% to full-suit/gown. Whereas, doctors in Pakistan reported to have poor availability of PPE with only 37.4% having access to masks/N95 respirator, 34.5% to gloves, 13.8% to face-shields or goggles, and 12.9% to full-suit/gown. The reuse of PPE was reported by 80.5% and 60.3% physicians from the US and Pakistan, respectively. More doctors from Pakistan (50.6%) reported that they had been forced to work without PPE compared to doctors in the US (7.1%). Conclusion There is a lack of different forms of PPE in the US and Pakistan. Doctors from both countries reported that they had been forced to work without PPE. Compared to the US, more doctors from Pakistan reported having faced discrimination in receiving PPE.