Deep bore well water level fluctuations in the Koyna region, India: the presence of a low order dynamical system in a seismically active environment

Water level fluctuations in deep bore wells in the vicinity of seismically active Koyna region in western India provides an opportunity to understand the causative mechanism underlying reservoir-triggered earthquakes. As the crustal porous rocks behave nonlinearly, their characteristics can be obtained by analysing water level fluctuations, which reflect an integrated response of the medium. A Fractal dimension is one such measure of nonlinear characteristics of porous rock as observed in water level data from the Koyna region. It is inferred in our study that a low nonlinear dynamical system with three variables can predict the water level fluctuations in bore wells

A report of a rare congenital malformation in a Nepalese child with congenital pouch colon: a case report

Congenital pouch colon is one of rare congenital anomalies. We report a 3-day-old male child with congenital pouch colon who underwent a window colostomy but died because of overwhelming sepsis. Due to its rarity, many surgeons in our part of the world may not be aware of it, hence increasing the potential to its mismanagement. However, with simple keen observations, we can safely come to its diagnosis. The aim of this report is to bring attention to congenital pouch colon associated with anorectal malformation in our country, with a brief emphasis on an approach to its diagnosis and initial management

Source of Previous Treatment for Re-Treatment TB Cases Registered under the National TB Control Programme, India, 2010

BACKGROUND: In 2009, nearly half (289,756) of global re-treatment TB notifications are from India; no nationally-representative data on the source of previous treatment was available to inform strategies for improvement of initial TB treatment outcome. OBJECTIVES: To assess the source of previous treatment for re-treatment TB patients registered under India's Revised National TB control Programme (RNTCP). METHODOLOGY: A nationally-representative cross sectional study was conducted in a sample of 36 randomly-selected districts. All consecutively registered retreatment TB patients during a defined 15-day period in these 36 districts were contacted and the information on the source of previous treatment sought. RESULTS: Data was collected from all 1712 retreatment TB patients registered in the identified districts during the study period. The data includes information on 595 'relapse' cases, 105 'failure' cases, 437 'treatment after default (TAD)' cases and 575 're-treatment others' cases. The source of most recent previous anti-tuberculosis therapy for 754 [44% (95% CI, 38.2%-49.9%)] of the re-treatment TB patients was from providers outside the TB control programme. A higher proportion of patients registered as TAD (64%) and 'retreatment others' (59%) were likely to be treated outside the National Programme, when compared to the proportion among 'relapse' (22%) or 'failure' (6%). Extrapolated to national registration, of the 292,972 re-treatment registrations in 2010, 128,907 patients would have been most recently treated outside the national programme. CONCLUSIONS: Nearly half of the re-treatment cases registered with the national programme were most recently treated outside the programme setting. Enhanced efforts towards extending treatment support and supervision to patients treated by private sector treatment providers are urgently required to improve the quality of treatment and reduce the numbers of patients with recurrent disease. In addition, reasons for the large number of recurrent TB cases from those already treated by the national programme require urgent detailed investigation

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID‐19: A Narrative Review

Background and Motivation: Parkinson’s disease (PD) is one of the most serious, non-curable, and expensive to treat. Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD patients. The presence of COVID‐19 causes the ML systems to be-come severely non‐linear and poses challenges in cardiovascular/stroke risk stratification. Further, due to comorbidity, sample size constraints, and poor scientific and clinical validation techniques, there have been no well‐explained ML paradigms. Deep neural networks are powerful learning machines that generalize non‐linear conditions. This study presents a novel investigation of deep learning (DL) solutions for CVD/stroke risk prediction in PD patients affected by the COVID‐19 framework. Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID‐19 framework. We study the hypothesis that PD in the presence of COVID‐19 can cause more harm to the heart and brain than in non‐ COVID‐19 conditions. COVID‐19 lung damage severity can be used as a covariate during DL training model designs. We, therefore, propose a DL model for the estimation of, (i) COVID‐19 lesions in computed tomography (CT) scans and (ii) combining the covariates of PD, COVID‐19 lesions, office and laboratory arterial atherosclerotic image‐based biomarkers, and medicine usage for the PD patients for the design of DL point‐based models for CVD/stroke risk stratification. Results: We validated the feasibility of CVD/stroke risk stratification in PD patients in the presence of a COVID‐ 19 environment and this was also verified. DL architectures like long short‐term memory (LSTM), and recurrent neural network (RNN) were studied for CVD/stroke risk stratification showing powerful designs. Lastly, we examined the artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients in the presence of COVID‐19. Conclusion: The DL is a very powerful tool for predicting CVD/stroke risk in PD patients affected by COVID‐19. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Anthropometric factors and breast cancer risk among urban and rural women in South India: a multicentric case–control study

Breast cancer (BC) incidence in India is approximately twice as high in urban women than in rural women, among whom we investigated the role of anthropometric factors and body size. The study was conducted at the Regional Cancer Centre, Trivandrum, and in three cancer hospitals in Chennai during 2002–2005. Histologically confirmed cases (n=1866) and age-matched controls (n=1873) were selected. Anthropometric factors were measured in standard ways. Information on body size at different periods of life was obtained using pictograms. Odds ratios (OR) of BC were estimated through logistic regression modelling. Proportion of women with body mass index (BMI)>25.0 kg/m2, waist size >85 cm and hip size >100 cm was significantly higher among urban than rural women. Risk was increased for waist size >85 cm (pre-menopausal: OR=1.24, 95% CI: 0.96–1.62; post-menopausal: 1.61, 95% CI: 1.22–2.12) and hip size >100 cm (pre-menopausal: OR=1.47, 95% CI: 1.05–2.06; post-menopausal 2.42, 95% CI: 1.72–3.41). Large body size at age 10 (OR=1.75, 95% CI: 1.01–3.03) and increased BMI (OR=1.33, 95% CI: 1.05–1.69 for 25.0–29.9 kg/m2 and OR=1.56, 95% CI: 1.03–2.35 for 30+ kg/m2) were associated with pre-menopausal BC risk. Our data support the hypotheses that increased anthropometric factors are risk factors of BC in India

A Phase II Randomized Double Blinded Trial Evaluating the Efficacy of Curcumin With Pre-operative Chemoradiation for Rectal Cancer

Background In vivo studies demonstrate that curcumin increases radioresponse of colorectal cancers. To demonstrate efficacy in humans, we performed a randomized double-blind study of locally advanced rectal cancer (LARC) patients receiving pre-operative chemoradiation therapy (CRT) ± curcumin. We used pathologic complete response (pCR) rate as a surrogate for clinical outcome. Methods From 2008–2010, LARC patients were randomized to placebo/curcumin in a 1:2 ratio. Patients received CRT [50.4 gray in 28 fractions; capecitabine (825 mg/m2 twice daily)] followed by surgery. Curcumin (4 grams orally, twice daily) or placebo was given throughout CRT and 6 weeks afterward. Toxicity was monitored weekly. Blood samples taken pre- and 1-hour post-ingestion and tissue biopsies (both collected at CRT week 2) were analyzed for pharmacokinetics. The primary outcome was surgical pCR rate. Results Of 22 enrolled patients, 15 received curcumin. Median age was 61 years and the majority were male (n=13; 59%). The median serum curcumin concentrations before (3.04 ng/mL; range, 1.24–18.88 ng/mL) and 1 hour after (3.32 ng/mL; range, 0.84–5.36 ng/mL) curcumin intake did not differ significantly (P=0.33). Serum curcumin concentrations both increased and decreased 1-hour post-administration (range as percentage of baseline: 8.8–258.1%). Twelve curcumin patient tissue biopsies had median curcumin concentration of 33.7 ng/mg tissue (range, 0.1–4,765.7 ng/mg). Two placebo and 1 curcumin patient achieved pCRs (P=0.18). One grade 3 toxicity (infection) was experienced. Conclusions The addition of curcumin to CRT did not increase pCR rates for LARC patients. The unpredictable bioavailability of curcumin contributes to continued uncertainties regarding curcumin efficacy

Dynamic Patterns of Circulating Seasonal and Pandemic A(H1N1)pdm09 Influenza Viruses From 2007–2010 in and around Delhi, India

Influenza surveillance was carried out in a subset of patients with influenza-like illness (ILI) presenting at an Employee Health Clinic (EHS) at All India Institute of Medical Sciences (AIIMS), New Delhi (urban) and pediatric out patients department of civil hospital at Ballabhgarh (peri-urban), under the Comprehensive Rural Health Services Project (CRHSP) of AIIMS, in Delhi region from January 2007 to December 2010. Of the 3264 samples tested, 541 (17%) were positive for influenza viruses, of which 221 (41%) were pandemic Influenza A(H1N1)pdm09, 168 (31%) were seasonal influenza A, and 152 (28%) were influenza B. While the Influenza viruses were detected year-round, their types/subtypes varied remarkably. While there was an equal distribution of seasonal A(H1N1) and influenza B in 2007, predominance of influenza B was observed in 2008. At the beginning of 2009, circulation of influenza A(H3N2) viruses was observed, followed later by emergence of Influenza A(H1N1)pdm09 with co-circulation of influenza B viruses. Influenza B was dominant subtype in early 2010, with second wave of Influenza A(H1N1)pdm09 in August-September, 2010. With the exception of pandemic H1N1 emergence in 2009, the peaks of influenza activity coincided primarily with monsoon season, followed by minor peak in winter at both urban and rural sites. Age group analysis of influenza positivity revealed that the percent positivity of Influenza A(H1N1)pdm09 influenza virus was highest in >5–18 years age groups (OR 2.5; CI = 1.2–5.0; p = 0.009) when compared to seasonal influenza. Phylogenetic analysis of Influenza A(H1N1)pdm09 from urban and rural sites did not reveal any major divergence from other Indian strains or viruses circulating worldwide. Continued surveillance globally will help define regional differences in influenza seasonality, as well as, to determine optimal periods to implement influenza vaccination programs among priority populations

First documented cure of a suggestive exogenous reinfection in polymyositis with same but multidrug resistant M. tuberculosis

BACKGROUND: MDR Mycobacterium tuberculosis is the major cause of treatment failure in tuberculosis patients, especially in immunosuppressed. We described a young polymyositis patient on immunosuppressive therapy who was started with antituberculosis therapy as a susceptible strain of M. tuberculosis was isolated from a single cutaneous abscess in his neck and from regional lymph nodes. CASE PRESENTATION: He had non-reactive miliary tuberculosis and multiple cutaneous abscesses 6 months later with the same strain, which was resistant this time to 9 antituberculosis drugs. We described clinical presentation, radiological and laboratory work-up, treatment and follow-up as the patient was cured after 1.5 years with 6 antituberculosis drugs. CONCLUSION: To our knowledge, this is the first reported case where an immunosuppressed patient with suggestive exogenous reinfection within 6 months with the same but MDR strain of M. tuberculosis was cured. Intense management and regular follow up were important since the patient was a potent source of MDR M. tuberculosis infection and there was limited choice for therapy

Yoga-Based Cardiac Rehabilitation After Acute Myocardial Infarction: A Randomized Trial

Background: Given the shortage of cardiac rehabilitation (CR) programs in India and poor uptake worldwide, there is an urgent need to find alternative models of CR that are inexpensive and may offer choice to subgroups with poor uptake (e.g., women and elderly). Objectives: This study sought to evaluate the effects of yoga-based CR (Yoga-CaRe) on major cardiovascular events and self-rated health in a multicenter randomized controlled trial. Methods: The trial was conducted in 24 medical centers across India. This study recruited 3,959 patients with acute myocardial infarction with a median and minimum follow-up of 22 and 6 months. Patients were individually randomized to receive either a Yoga-CaRe program (n = 1,970) or enhanced standard care involving educational advice (n = 1,989). The co-primary outcomes were: 1) first occurrence of major adverse cardiovascular events (MACE) (composite of all-cause mortality, myocardial infarction, stroke, or emergency cardiovascular hospitalization); and 2) self-rated health on the European Quality of Life–5 Dimensions–5 Level visual analogue scale at 12 weeks. Results: MACE occurred in 131 (6.7%) patients in the Yoga-CaRe group and 146 (7.4%) patients in the enhanced standard care group (hazard ratio with Yoga-CaRe: 0.90; 95% confidence interval [CI]: 0.71 to 1.15; p = 0.41). Self-rated health was 77 in Yoga-CaRe and 75.7 in the enhanced standard care group (baseline-adjusted mean difference in favor of Yoga-CaRe: 1.5; 95% CI: 0.5 to 2.5; p = 0.002). The Yoga-CaRe group had greater return to pre-infarct activities, but there was no difference in tobacco cessation or medication adherence between the treatment groups (secondary outcomes). Conclusions: Yoga-CaRe improved self-rated health and return to pre-infarct activities after acute myocardial infarction, but the trial lacked statistical power to show a difference in MACE. Yoga-CaRe may be an option when conventional CR is unavailable or unacceptable to individuals. (A study on effectiveness of YOGA based cardiac rehabilitation programme in India and United Kingdom; CTRI/2012/02/002408)

COVLIAS 1.0: Lung segmentation in COVID-19 computed tomography scans using hybrid deep learning artificial intelligence models

Background: COVID-19 lung segmentation using Computed Tomography (CT) scans is important for the diagnosis of lung severity. The process of automated lung segmentation is challenging due to (a) CT radiation dosage and (b) ground-glass opacities caused by COVID-19. The lung segmentation methodologies proposed in 2020 were semi-or automated but not reliable, accurate, and user-friendly. The proposed study presents a COVID Lung Image Analysis System (COVLIAS 1.0, AtheroPoint™, Roseville, CA, USA) consisting of hybrid deep learning (HDL) models for lung segmentation. Methodology: The COVLIAS 1.0 consists of three methods based on solo deep learning (SDL) or hybrid deep learning (HDL). SegNet is proposed in the SDL category while VGG-SegNet and ResNet-SegNet are designed under the HDL paradigm. The three proposed AI approaches were benchmarked against the National Institute of Health (NIH)-based conventional segmentation model using fuzzy-connectedness. A cross-validation protocol with a 40:60 ratio between training and testing was designed, with 10% validation data. The ground truth (GT) was manually traced by a radiologist trained personnel. For performance evaluation, nine different criteria were selected to perform the evaluation of SDL or HDL lung segmentation regions and lungs long axis against GT. Results: Using the database of 5000 chest CT images (from 72 patients), COVLIAS 1.0 yielded AUC of ~0.96, ~0.97, ~0.98, and ~0.96 (p-value < 0.001), respectively within 5% range of GT area, for SegNet, VGG-SegNet, ResNet-SegNet, and NIH. The mean Figure of Merit using four models (left and right lung) was above 94%. On benchmarking against the National Institute of Health (NIH) segmentation method, the proposed model demonstrated a 58% and 44% improvement in ResNet-SegNet, 52% and 36% improvement in VGG-SegNet for lung area, and lung long axis, respectively. The PE statistics performance was in the following order: ResNet-SegNet > VGG-SegNet > NIH > SegNet. The HDL runs in <1 s on test data per image. Conclusions: The COVLIAS 1.0 system can be applied in real-time for radiology-based clinical settings