Biallelic Variants in EPHA2 Identified in Three Large Inbred Families with Early-Onset Cataract.

Hereditary congenital cataract (HCC) is clinically and genetically heterogeneous. We investigated HCC that segregates in three inbred families (LUCC03, LUCC16, and LUCC24). Ophthalmological examinations revealed cataracts with variability related to the age of onset segregating in a recessive manner in these families. Exome sequencing of probands identified a novel homozygous c.2710delG;p.(Val904Cysfs*36) EPHA2 variant in LUCC03 and a known homozygous c.2353G>A;p.(Ala785Thr) EPHA2 variant in the other two recessive families. EPHA2 encodes a transmembrane tyrosine kinase receptor, which is primarily involved in membrane-transport, cell-cell adhesion, and repulsion signaling processes. Computational structural modeling predicts that substitution of a threonine for an alanine p.(Ala785Thr) results in the formation of three new hydrogen bonds with the neighboring residues, which causes misfolding of EPHA2 in both scenarios. Insights from our study will facilitate counseling regarding the molecular and phenotypic landscape of EPHA2-related HCC.

Serologic Evidence of Severe Fever with Thrombocytopenia Syndrome Virus and Related Viruses in Pakistan.

We describe the seroprevalence of severe fever with thrombocytopenia syndrome virus (SFTSV) and the association of antibody occurrence with location, sex, and age among the human population in Pakistan. Our results indicate substantial activity of SFTSV and SFTSV-related viruses in this country.

Study of Vitamin D deficiency and contributing factors in the population of Hyderabad, Pakistan.

The study of vitamin D (25-OHD) deficiency was intended to analyse the incidence and some contributing factors amid healthy individuals of different living standards in general population of Hyderabad and its adjacent areas. A total of 1244 healthy individuals (1-84 year of age) (females 725 (58.2%) and males 519 (41.8%)) were selected in this study and the concentration of Serum vitamin D (25-OHD), phosphorus, alkaline phosphatase and calcium was analysed. The prevalence of vitamin D (25-OHD) deficiency was 78.3%. The values <10ng/mL were noted as severe deficiency, 10-20ng/ml moderate and 21-29.9ng/ml as mild deficiency or insufficiency. The degrees of vitamin D (25-OHD) deficiency amongst the healthy individuals were severe (17.2%), mild (18.8%) and moderate (42.3%). Vitamin D (25-OHD) was positively correlated with blood calcium profile whereas alkaline phosphatase and phosphorus correlated negatively. The study showed that vitamin D (25-OHD) deficiency has a high prevalence in healthy subjects.

Beyond the In-Practice CBC: The Research CBC Parameters-Driven Machine Learning Predictive Modeling for Early Differentiation among Leukemias.

A targeted and timely treatment can be a beneficial tool for patients with hematological emergencies (particularly acute leukemias). The key challenges in the early diagnosis of leukemias and related hematological disorders are their symptom-sharing nature and prolonged turnaround time as well as the expertise needed in reporting confirmatory tests. The present study made use of the potential morphological and immature fraction-related parameters (research items or cell population data) generated during complete blood cell count (CBC), through artificial intelligence (AI)/machine learning (ML) predictive modeling for early (at the pre-microscopic level) differentiation of various types of leukemias: acute from chronic as well as myeloid from lymphoid. The routine CBC parameters along with research CBC items from a hematology analyzer in the diagnosis of 1577 study subjects with hematological neoplasms were collected. The statistical and data visualization tools, including heat-map and principal component analysis (PCA,) helped in the evaluation of the predictive capacity of research CBC items. Next, research CBC parameter-driven artificial neural network (ANN) predictive modeling was developed to use the hidden trend (disease's signature) by increasing the auguring accuracy of these potential morphometric parameters in differentiation of leukemias. The classical statistics for routine and research CBC parameters showed that as a whole, all study items are significantly deviated among various types of leukemias (study groups). The CPD parameter-driven heat-map gave clustering (separation) of myeloid from lymphoid leukemias, followed by the segregation (nodding) of the acute from the chronic class of that particular lineage. Furthermore, acute promyelocytic leukemia (APML) was also well individuated from other types of acute myeloid leukemia (AML). The PCA plot guided by research CBC items at notable variance vindicated the aforementioned findings of the CPD-driven heat-map. Through training of ANN predictive modeling, the CPD parameters successfully differentiate the chronic myeloid leukemia (CML), AML, APML, acute lymphoid leukemia (ALL), chronic lymphoid leukemia (CLL), and other related hematological neoplasms with AUC values of 0.937, 0.905, 0.805, 0.829, 0.870, and 0.789, respectively, at an agreeably significant (10.6%) false prediction rate. Overall practical results of using our ANN model were found quite satisfactory with values of 83.1% and 89.4.7% for training and testing datasets, respectively. We proposed that research CBC parameters could potentially be used for early differentiation of leukemias in the hematology-oncology unit. The CPD-driven ANN modeling is a novel practice that substantially strengthens the predictive potential of CPD items, allowing the clinicians to be confident about the typical trend of the "disease fingerprint" shown by these automated potential morphometric items.

Field evaluation of typhoid conjugate vaccine in a catch-up campaign among children aged 9 months to 15 years in Sindh, Pakistan.

BACKGROUND: Typhoid conjugate vaccine (TCV) has recently been introduced in the expanded program for immunization (EPI) in Pakistan. Before its introduction in routine immunization, a onetime catchup campaign among children 9 months to 15 years old was conducted in November 2019. We performed field evaluation of TCV against culture confirmed Salmonella Typhi (S. Typhi) among 9 months to 15 years old children during the catch up campaign in Karachi and Hyderabad. METHODS: A rapid assessment of blood culture confirmed S. Typhi was performed. Age eligible cases of culture confirmed S. Typhi were identified from the laboratory networks of Aga Khan University Hospital Karachi and Hyderabad, Kharadar General Hospital Karachi, and Liaqat University of Medical & Health Sciences (LUMHS) Hyderabad. Information on sociodemographic, typhoid vaccination history and antimicrobial resistance was collected using a structured questionnaire. Patient medical records and lab reports were also reviewed to collect information on diagnosis and antimicrobial susceptibility information. Information about the population vaccination coverage during catch-up campaign was obtained from the provincial EPI office. Field performance of TCV in catchup campaign was measured by calculating the effectiveness using rapid screening method which is less resource-intensive technique of calculating vaccine effectiveness (VE). RESULTS: Overall, 968 culture confirmed typhoid cases were enrolled. Among them, 82% (793/968) were from Karachi and 18% (175/968) from Hyderabad. The average age of the participants was 5.68 years, and 54% (523/968) were male. 6% (62/968) of the culture confirmed S. Typhi cases were multidrug resistant (MDR), and 61% (586/968) were extensively drug resistant (XDR). The VE using the TCV coverage data provided by EPI was 98%. CONCLUSION: TCV is effective against culture confirmed S. Typhi among children aged 9 months to 15 years in the catch-up campaign setting. While typhoid vaccination can significantly decrease the burden of typhoid disease, improvements in sanitation and hygiene are necessary for the prevention of spread of enteric fever. Longer term follow up will be needed to assess the duration of protection and requirement for booster doses of TCV.

Effectiveness of typhoid conjugate vaccine against culture-confirmed Salmonella enterica serotype Typhi in an extensively drug-resistant outbreak setting of Hyderabad, Pakistan: a cohort study.

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.

Cell Population Data-Driven Acute Promyelocytic Leukemia Flagging Through Artificial Neural Network Predictive Modeling.

A targeted and timely offered treatment can be a benefitting tool for patients with acute promyelocytic leukemia (APML). Current round of study made use of potential morphological and immature fraction-related parameters (cell population data) generated during complete blood cell count (CBC), through artificial neural network (ANN) predictive modeling for early flagging of APML cases. We collected classical CBC items along with cell population data (CPD) from hematology analyzer at diagnosis of 1067 study subjects with hematological neoplasms. For morphological assessment, peripheral blood films were examined. Statistical and machine learning tools including principal component analysis (PCA) helped in the evaluation of predictive capacity of routine and CPD items. Then selected CBC item-driven ANN predictive modeling was developed to smartly use the hidden trend by increasing the auguring accuracy of these parameters in differentiation of APML cases. We found a characteristic triad based on lower (53.73) platelet count (PLT) with decreased/normal (4.72) immature fraction of platelet (IPF) with addition of significantly higher value (65.5) of DNA/RNA content-related neutrophil (NE-SFL) parameter in patients with APML against other hematological neoplasm's groups. On PCA, APML showed exceptionally significant variance for PLT, IPF, and NE-SFL. Through training of ANN predictive modeling, our selected CBC items successfully classify the APML group from non-APML groups at highly significant (0.894) AUC value with lower (2.3 percent) false prediction rate. Practical results of using our ANN model were found acceptable with value of 95.7% and 97.7% for training and testing data sets, respectively. We proposed that PLT, IPF, and NE-SFL could potentially be used for early flagging of APML cases in the hematology-oncology unit. CBC item-driven ANN modeling is a novel approach that substantially strengthen the predictive potential of CBC items, allowing the clinicians to be confident by the typical trend raised by these studied parameters.