Hemoglobin status in pregnant women for diagnosis of anemia, assessment of severity and its socio-demographic determinants in rural area of Kanpur district, Uttar Pradesh, India

Background: Anaemia is one of the most common nutritional deficiency disorders affecting the pregnant women in the developing countries. In India anaemia in pregnancy is a major health issue with adverse maternal and foetal outcome. Nutritional anaemia in pregnant women continues to be a cause of concern despite the fact that this problem is largely preventable and easily treatable. Objectives was to determine the prevalence and severity of anaemia in the pregnant women.Methods: Around 350 pregnant women in different trimesters of pregnancy were enrolled coming for the 1st time in outpatient department of Obstetrics and Gynaecology, in Rama Medical College Hospital and Research Centre, Kanpur from Janurary 2016 to December 2016. Information regarding age, age at marriage, age at 1st pregnancy, parity, Interval between previous and index pregnancy, no of abortions, educational status, dietary habits, Type of family, Socioeconomic status was collected in pre-designed structured schedule after taking written consent from pregnant women attending out-patient department. Haemoglobin estimation was done by auto analyser and anaemia was graded according to WHO criterion. Statistical analysis was done by percentages and proportions.Results: A high prevalence of anaemia, (87.71%) was observed in pregnant women. The current study shows (24.7%) cases of mild anaemia, (54.5%) cases of moderate anaemia, and (7.9%) of severe anaemia.Conclusions: A very high prevalence of anaemia in pregnancy needs awareness about late marriage, birth spacing, one or two child norm, antenatal care, green leafy vegetable in diet, mandatory regular supply of iron folic acid (IFA) tablets to adolescent and pregnant women along with correction of other nutritional deficiencies

The New ID Proof: A Case Report of Denture Labeling

Denture labeling is not a new concept in either prosthetic or forensic dentistry and its routine practice has been urged by forensic dentists internationally for many years. Prosthodontistsare playing very important role in forensic dentistry as they are concerned with fabrication of various prostheses which can serve as an important tool for identification. The main objective of this article is to discuss the various methods available for denture marking along with a case report

Improving the Optical and Thermoelectric Properties of Cs2InAgCl6 with Substitutional Doping: A DFT Insight

New generation Indium based lead-free Cs2InAgCl6 is a promising halide material in photovoltaic applications due to its good air stability and non-toxic behavior. But its wide band gap (>3 eV) is not suitable for solar spectrum and hence reducing the photoelectronic efficiency for device applications. Here we report a significant band gap reduction from 3.3 eV to 0.6 eV by substitutional doping and its effect on opto-electronic and opto-thermoelectric properties from first-principles study. The results predict that Sn/Pb and Ga & Cu co-doping enhance the density of states significantly near the valence band maximum (VBM) and thus reduce the band gap by shifting the VBM upward while the alkali-metals (K/Rb) slightly increase the band gap. A strong absorption peak near Shockley-Queisser limit is observed in co-doped case while in Sn/Pb-doped case, we notice a peak in the middle of the visible region of solar spectrum. The nature of band gap is indirect with Cu-Ga/Pb/Sn doping with a significant reduction in the band gap. We observe a significant increase in the power factor (PF) (2.03 mW/mK2) for n-type carrier in Pb-dpoing, which is ~3.5 times higher than the pristine case (0.6 mW/mK2) at 500 K

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed. This critical gap may be addressed through the development of "Lifelong Learning" systems that are capable of 1) Continuous Learning, 2) Transfer and Adaptation, and 3) Scalability. Unfortunately, efforts to improve these capabilities are typically treated as distinct areas of research that are assessed independently, without regard to the impact of each separate capability on other aspects of the system. We instead propose a holistic approach, using a suite of metrics and an evaluation framework to assess Lifelong Learning in a principled way that is agnostic to specific domains or system techniques. Through five case studies, we show that this suite of metrics can inform the development of varied and complex Lifelong Learning systems. We highlight how the proposed suite of metrics quantifies performance trade-offs present during Lifelong Learning system development - both the widely discussed Stability-Plasticity dilemma and the newly proposed relationship between Sample Efficient and Robust Learning. Further, we make recommendations for the formulation and use of metrics to guide the continuing development of Lifelong Learning systems and assess their progress in the future.Comment: To appear in Neural Network

Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India.

BACKGROUND: Neurodevelopmental disorders (NDDs) compromise the development and attainment of full social and economic potential at individual, family, community, and country levels. Paucity of data on NDDs slows down policy and programmatic action in most developing countries despite perceived high burden. METHODS AND FINDINGS: We assessed 3,964 children (with almost equal number of boys and girls distributed in 2-<6 and 6-9 year age categories) identified from five geographically diverse populations in India using cluster sampling technique (probability proportionate to population size). These were from the North-Central, i.e., Palwal (N = 998; all rural, 16.4% non-Hindu, 25.3% from scheduled caste/tribe [SC-ST] [these are considered underserved communities who are eligible for affirmative action]); North, i.e., Kangra (N = 997; 91.6% rural, 3.7% non-Hindu, 25.3% SC-ST); East, i.e., Dhenkanal (N = 981; 89.8% rural, 1.2% non-Hindu, 38.0% SC-ST); South, i.e., Hyderabad (N = 495; all urban, 25.7% non-Hindu, 27.3% SC-ST) and West, i.e., North Goa (N = 493; 68.0% rural, 11.4% non-Hindu, 18.5% SC-ST). All children were assessed for vision impairment (VI), epilepsy (Epi), neuromotor impairments including cerebral palsy (NMI-CP), hearing impairment (HI), speech and language disorders, autism spectrum disorders (ASDs), and intellectual disability (ID). Furthermore, 6-9-year-old children were also assessed for attention deficit hyperactivity disorder (ADHD) and learning disorders (LDs). We standardized sample characteristics as per Census of India 2011 to arrive at district level and all-sites-pooled estimates. Site-specific prevalence of any of seven NDDs in 2-<6 year olds ranged from 2.9% (95% CI 1.6-5.5) to 18.7% (95% CI 14.7-23.6), and for any of nine NDDs in the 6-9-year-old children, from 6.5% (95% CI 4.6-9.1) to 18.5% (95% CI 15.3-22.3). Two or more NDDs were present in 0.4% (95% CI 0.1-1.7) to 4.3% (95% CI 2.2-8.2) in the younger age category and 0.7% (95% CI 0.2-2.0) to 5.3% (95% CI 3.3-8.2) in the older age category. All-site-pooled estimates for NDDs were 9.2% (95% CI 7.5-11.2) and 13.6% (95% CI 11.3-16.2) in children of 2-<6 and 6-9 year age categories, respectively, without significant difference according to gender, rural/urban residence, or religion; almost one-fifth of these children had more than one NDD. The pooled estimates for prevalence increased by up to three percentage points when these were adjusted for national rates of stunting or low birth weight (LBW). HI, ID, speech and language disorders, Epi, and LDs were the common NDDs across sites. Upon risk modelling, noninstitutional delivery, history of perinatal asphyxia, neonatal illness, postnatal neurological/brain infections, stunting, LBW/prematurity, and older age category (6-9 year) were significantly associated with NDDs. The study sample was underrepresentative of stunting and LBW and had a 15.6% refusal. These factors could be contributing to underestimation of the true NDD burden in our population. CONCLUSIONS: The study identifies NDDs in children aged 2-9 years as a significant public health burden for India. HI was higher than and ASD prevalence comparable to the published global literature. Most risk factors of NDDs were modifiable and amenable to public health interventions

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Antimicrobial susceptibility pattern of colistin resistance Klebsiella pneumoniae from clinical Isolates

Background: There is very little information available in India about the prevalence of colistin-resistant Klebsiella pneumonia in patients and their susceptibility pattern. The increased use of colistin to treat infections are caused by multidrug-resistant Gram-negative bacteria has resulted in an increase of colistin resistance in Klebsiella pneumoniae in numerous countries. Materials and Methods: These isolates were collected from distinct clinical specimens and analyzed using the broth micro-dilution technique to establish their colistin minimal inhibitory concentration (mic). Result: Of 116 Klebsiella species, Klebsiella pneumonia was 96.55% while Klebsiella oxytoca was 3.45%. Among isolates, 09 (7.76%) were colistin resistant Klebsiella pneumonia by broth-micro dilution. In total, 09 case-patients were identified, 62.93% males and 37.07% females. The mean±SD of the age was 45.93±18.15. Carbapenem, Piperacillin-tazobactam and tigecycline were the most effective drug used for combine therapy to colistin resistance gram negative infections. Conclusion: This is the first study to look at the incidence of colistin-resistant Klebsiella pneumoniae in individuals in Jaipur. &nbsp;Infection caused by Klebsiella pneumonia highly resistant to many drugs.&nbsp; However, various colistin-based combined strategies have indeed been proven to be effective in curing these problems. To minimise colistin use and avoid misuse, a comprehensive antibiotic stewardship policy must be implemented

A methodological approach to identify communities at risk: Trajectory dispersion models to trace air pollutants during colour festival

In this study, we observe the health effects experienced by the people living in that respective study area by analyzing the hospital admission data. A limited study on the association between air pollutants and the number of hospital admissions is available. The proposed research is an extended version of a previously published article, performed in the year 2019 during the color festival - ''Holi”, the colors used are widespread throughout the festival. Fine particles were monitored and their ion concentrations were analyzed by ion chromatograph. The significant anions (sulphate, nitrate, and chloride) and cations (sodium, potassium, and magnesium) were obtained in fine particles which were higher than the permissible limits. The collected data shows a 0.7% of the increase in hospital admissions after Holi. Dispersion modeling and trajectory analysis have been introduced to understand the dispersion of air pollutants during pre-holi, holi and post-holi. Thus, it is evident that the Holi festival potentially contributes to air pollution, which leads to serious health hazards