Spectrum of clinical and biochemical profile and its importance in diabetic ketoacidosis: a tertiary care hospital experience in Gujarat

Background: Diabetes mellitus (DM) is a disorder of multiple etiologies, and diabetic ketoacidosis (DKA) is one of the life-threatening complications of DM. This study was aimed to study the clinical and biochemical profile of DKA patients. Methods: We conducted this retrospective study at a tertiary care hospital in Gujarat. We included total 100 patients above the age of 18 years having DM, presented with DKA. A detailed history, clinical examination and biochemical tests were carried out: random blood sugar, urinalysis, arterial blood gas analysis, serum ketone, HbA1c, serum creatinine, serum electrolytes- potassium and sodium and serum osmolality. The results were analysed using Microsoft excel. Results: Out of total 100 patients, 76 (76%) patients had type 1 DM and 24 (24%) had type 2 DM, 42 (42%) were in the age group of 18-30 years. The mean age was 39.75±12.14 years. There were 56 (56%) males and 44 (44%) females with male: female ratio of 1.3:1. Most common clinical features of DKA were nausea/vomiting (88%), breathlessness (43%) and fever (35%). The main biochemical parameters altered were blood sugar (>400 mg/dl in 41%) and serum ketones (≥5 in 84%) as well as majority of patients (64%) had their HbA1c level between 11-15% with the mean HbA1c value of 12.25±2.43%. Conclusions: DKA is a frequently observed emergency with high mortality rate. Education regarding symptoms of ketoacidosis, not missing insulin doses especially during illness, strict adherence to treatment and lifestyle modifications can greatly reduce DKA occurrence

Identifying Depressive Symptoms from Tweets: Figurative Language Enabled Multitask Learning Framework

Existing studies on using social media for deriving mental health status of users focus on the depression detection task. However, for case management and referral to psychiatrists, healthcare workers require practical and scalable depressive disorder screening and triage system. This study aims to design and evaluate a decision support system (DSS) to reliably determine the depressive triage level by capturing fine-grained depressive symptoms expressed in user tweets through the emulation of Patient Health Questionnaire-9 (PHQ-9) that is routinely used in clinical practice. The reliable detection of depressive symptoms from tweets is challenging because the 280-character limit on tweets incentivizes the use of creative artifacts in the utterances and figurative usage contributes to effective expression. We propose a novel BERT based robust multi-task learning framework to accurately identify the depressive symptoms using the auxiliary task of figurative usage detection. Specifically, our proposed novel task sharing mechanism, co-task aware attention, enables automatic selection of optimal information across the BERT layers and tasks by soft-sharing of parameters. Our results show that modeling figurative usage can demonstrably improve the model\u27s robustness and reliability for distinguishing the depression symptoms

Prevalence and Genotypes of Mycobacterium Avium Subspecies Paratuberculosis in Large Ruminants of Eastern Uttar Pradesh, North India

Uttar Pradesh is the fourth largest, most populous and leading milk and meat producing state in India. Despite the huge livestock population, information on the status of paratuberculosis homogeneity and heterogeneity of Mycobacterium avium subspecies paratuberculosis (MAP) isolates of eastern Uttar Pradesh is non-existent. Present study was aimed to estimate the presence of MAP in large ruminants (Cattle and Buffaloes) of eastern Uttar Pradesh. A total 108 fecal samples were collected from farmer's herds of large ruminants (cattle and buffaloes) from different geographical regions (Chandauli, Mughalsarai, Gazipur, and Naugarh) of eastern Uttar Pradesh and screened for the presence of MAP infection using microscopic examination, direct IS900 PCR and culture on Herrold egg yolk (HEY) medium. The isolates recovered on HEY medium were subjected to molecular identification and genotyping using IS900 PCR and IS1311 PCR-REA method, respectively. Of the 108 fecal samples, 25 (23.14%) and 11 (10.18%) samples were positive for the presence of acid-fast bacilli and growth on HEY medium, respectively. Species-wise, 17.5, 7.5% and 26.5, 11.7% fecal samples from cattle and buffaloes were found positive for the presence of acid-fast bacilli and growth on HEY medium, respectively. Isolates recovered on HEY medium with mycobactin J were positive for IS900 sequence and genotyped as Bison Type using IS1311 PCR-REA method. Present study is the first report on the presence of MAP infection and ‘Bison Type' genotype of MAP in eastern Uttar Pradesh. These findings will be useful for the intervention of effective control measures in order to reduce the prevalence of MAP infection in domestic livestock species and prevent its spread to the human population in the regions

Association of SUMOlation Pathway Genes With Stroke in a Genome-wide Association Study in India

OBJECTIVE: To undertake a genome-wide association study (GWAS) to identify genetic variants for stroke in an Indian population. METHODS: In a hospital-based case-control study, 8 teaching hospitals in India recruited 4,088 participants, including 1,609 stroke cases. Imputed genetic variants were tested for association with stroke subtypes using both single-marker and gene-based tests. Association with vascular risk factors was performed with logistic regression. Various databases were searched for replication, functional annotation, and association with related traits. Status of candidate genes previously reported in the Indian population was also checked. RESULTS: Associations of vascular risk factors with stroke were similar to previous reports and show modifiable risk factors such as hypertension, smoking, and alcohol consumption as having the highest effect. Single-marker–based association revealed 2 loci for cardioembolic stroke (1p21 and 16q24), 2 for small vessel disease stroke (3p26 and 16p13), and 4 for hemorrhagic stroke (3q24, 5q33, 6q13, and 19q13) at p < 5 × 10(−8). The index single nucleotide polymorphism of 1p21 is an expression quantitative trait locus (p(lowest) = 1.74 × 10(−58)) for RWDD3 involved in SUMOylation and is associated with platelet distribution width (1.15 × 10(−9)) and 18-carbon fatty acid metabolism (p = 7.36 × 10(−12)). In gene-based analysis, we identified 3 genes (SLC17A2, FAM73A, and OR52L1) at p < 2.7 × 10(−6). Eleven of 32 candidate gene loci studied in an Indian population replicated (p < 0.05), and 21 of 32 loci identified through previous GWAS replicated according to directionality of effect. CONCLUSIONS: This GWAS of stroke in an Indian population identified novel loci and replicated previously known loci. Genetic variants in the SUMOylation pathway, which has been implicated in brain ischemia, were identified for association with stroke

Association of acute toxic encephalopathy with litchi consumption in an outbreak in Muzaffarpur, India, 2014: a case-control study

Background Outbreaks of unexplained illness frequently remain under-investigated. In India, outbreaks of an acute neurological illness with high mortality among children occur annually in Muzaffarpur, the country’s largest litchi cultivation region. In 2014, we aimed to investigate the cause and risk factors for this illness. Methods In this hospital-based surveillance and nested age-matched case-control study, we did laboratory investigations to assess potential infectious and non-infectious causes of this acute neurological illness. Cases were children aged 15 years or younger who were admitted to two hospitals in Muzaffarpur with new-onset seizures or altered sensorium. Age-matched controls were residents of Muzaffarpur who were admitted to the same two hospitals for a non-neurologic illness within seven days of the date of admission of the case. Clinical specimens (blood, cerebrospinal fluid, and urine) and environmental specimens (litchis) were tested for evidence of infectious pathogens, pesticides, toxic metals, and other non-infectious causes, including presence of hypoglycin A or methylenecyclopropylglycine (MCPG), naturally-occurring fruit-based toxins that cause hypoglycaemia and metabolic derangement. Matched and unmatched (controlling for age) bivariate analyses were done and risk factors for illness were expressed as matched odds ratios and odds ratios (unmatched analyses). Findings Between May 26, and July 17, 2014, 390 patients meeting the case definition were admitted to the two referral hospitals in Muzaffarpur, of whom 122 (31%) died. On admission, 204 (62%) of 327 had blood glucose concentration of 70 mg/dL or less. 104 cases were compared with 104 age-matched hospital controls. Litchi consumption (matched odds ratio [mOR] 9·6 [95% CI 3·6 – 24]) and absence of an evening meal (2·2 [1·2–4·3]) in the 24 h preceding illness onset were associated with illness. The absence of an evening meal significantly modified the effect of eating litchis on illness (odds ratio [OR] 7·8 [95% CI 3·3–18·8], without evening meal; OR 3·6 [1·1–11·1] with an evening meal). Tests for infectious agents and pesticides were negative. Metabolites of hypoglycin A, MCPG, or both were detected in 48 [66%] of 73 urine specimens from case-patients and none from 15 controls; 72 (90%) of 80 case-patient specimens had abnormal plasma acylcarnitine profiles, consistent with severe disruption of fatty acid metabolism. In 36 litchi arils tested from Muzaffarpur, hypoglycin A concentrations ranged from 12·4 μg/g to 152·0 μg/g and MCPG ranged from 44·9 μg/g to 220·0 μg/g. Interpretation Our investigation suggests an outbreak of acute encephalopathy in Muzaffarpur associated with both hypoglycin A and MCPG toxicity. To prevent illness and reduce mortality in the region, we recommended minimising litchi consumption, ensuring receipt of an evening meal and implementing rapid glucose correction for suspected illness. A comprehensive investigative approach in Muzaffarpur led to timely public health recommendations, underscoring the importance of using systematic methods in other unexplained illness outbreaks

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17 : analysis for the Global Burden of Disease Study 2017

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1–65·8), 17·4% (7·7–28·4), and 59·5% (34·2–86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery