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236 result(s) for "The Barne"
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Vitebsk Nazis Battle On in City's Streets
LONDON, June 26 (Monday).-- The Red Army drive to liberate White Russia has now widened over a 250-mile front encircling five Nazi divisions in the fortress city of Vitebsk and liberating hundreds of smaller village in the gaps between the remaining...
Commons Gets Plan to Assure Post -War Jobs
LONDON, June 21.-- The maintenance of a high and stable level of employment in Britain after the war as a primary responsibility of the government was submitted to the House of Commons today by Ernest Bevin, Minister of Labor and National Service, for a record...
Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
The accumulation and extrusion of Ca 2+ in the pre- and postsynaptic compartments play a critical role in initiating plastic changes in biological synapses. To emulate this fundamental process in electronic devices, we developed diffusive Ag-in-oxide memristors with a temporal response during and after stimulation similar to that of the synaptic Ca 2+ dynamics. In situ high-resolution transmission electron microscopy and nanoparticle dynamics simulations both demonstrate that Ag atoms disperse under electrical bias and regroup spontaneously under zero bias because of interfacial energy minimization, closely resembling synaptic influx and extrusion of Ca 2+ , respectively. The diffusive memristor and its dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses, representing an advance in hardware implementation of neuromorphic functionalities. Calcium ions play a vital role in enabling synaptic plasticity in biological systems. The dynamic behaviour of these ions has now been emulated in a metal atom diffusion-based memristor.
COPD awareness in the urban slums and rural areas around Pune city in India
COPD is the second leading cause of death and disability adjusted life years (DALYs) in India, yet, it remains poorly recognized. We aimed to study the level of awareness of COPD in urban slums of Pune city in India and its neighboring rural areas. All male and female subjects above the age of 30 years residing in 13 randomly selected slums of Pune city (total population of 3000) and 7 randomly selected neighboring rural villages (total population of 3000) were invited to participate in this cross-sectional community survey. After obtaining written informed consent, 13 trained community health workers (CHWs) administered a questionnaire that captured their level of awareness of COPD. Of the 6000 subjects approached, 5420 residents (mean age ± SD = 48.0 ± 13.5 years; 38% males) consented and answered all questions. The number of people who had ever heard the word COPD was 49/5420 [0.9% (0.6–1.1%); 0.7% (0.5–1.3%) of the urban slum dwellers and 1.15% (0.5–1.3%) of rural residents]. Among those who had never heard the word COPD (n = 5371), when asked what was the name of the disease caused by long-term tobacco smoking, 38% said cancer, 16.7% said asthma, and 4.4% said TB. Among those who had heard the word COPD (n = 49), 6.1% said it was a disease of the heart, and 61% attributed COPD to smoke and dust pollution and 20% to tobacco smoking. The level of awareness of COPD in the Indian community is extremely low, highlighting the need to have nationwide mass awareness programs in India.
Comparison of a portable, pneumotach flow-sensor–based spirometer (Spirofy™) with the vitalograph alpha Touch™ spirometer in evaluating lung function in healthy individuals, asthmatics, and COPD patients—a randomized, crossover study
Background Spirofy™ is India’s first portable, pneumotach flow-sensor-based digital spirometer developed to diagnose asthma and chronic obstructive pulmonary disease (COPD). In this study, we compared the performance of the Spirofy™ device with that of the Vitalograph Alpha Touch™ spirometer in measuring the lung capacities of healthy individuals, asthmatics, and COPD patients. We also assessed the inter-device variability between two Spirofy™ devices. Methods In a randomized, three-way crossover, open-label study, we measured the differences in forced expiratory volume in the first second (FEV 1 ) and forced vital capacity (FVC) between the Spirofy™ and Vitalograph Alpha Touch™ spirometers. A proportion of the FEV 1 /FVC ratio distribution of < 0.7 was used to compare the diagnostic accuracies of the Spirofy™ with Vitalograph™ Alpha Touch™ spirometers. Results Ninety subjects participated in this study. The mean ± SD FVC values obtained from the Spirofy™ 1, Spirofy™ 2, and Vitalograph Alpha Touch™ devices were 2.60 ± 1.05 L, 2.64 ± 1.04 L, and 2.67 ± 1.04 L, respectively. The mean ± SD FEV 1 values obtained from the Spirofy™ 1, Spirofy™ 2, and Vitalograph Alpha Touch™ devices were 1.87 ± 0.92 (L), 1.88 ± 0.92 (L), and 1.93 ± 0.93 (L), respectively. A significant positive correlation was found between the FVC and FEV 1 values recorded by Vitalograph Alpha Touch™, Spirofy™ 1, and Spirofy™ 2. As compared to Vitalograph Alpha Touch™, the Spirofy™ device showed good sensitivity (97%), specificity (90%), and overall accuracy (93.3%) at an FEV 1 /FVC ratio < 0.7. No inter-device variability was observed between the two Spirofy™ devices. Conclusion Spirofy™ is a portable and easy-to-use device and is as accurate as the standard Vitalograph Alpha Touch™ spirometer for the diagnosis of COPD and asthma. Trial registration CTRI/2021/09/036492 (Clinical Trials Registry - India)
Two microbiota subtypes identified in irritable bowel syndrome with distinct responses to the low FODMAP diet
ObjectiveReducing FODMAPs (fermentable oligosaccharides, disaccharides, monosaccharides and polyols) can be clinically beneficial in IBS but the mechanism is incompletely understood. We aimed to detect microbial signatures that might predict response to the low FODMAP diet and assess whether microbiota compositional and functional shifts could provide insights into its mode of action.DesignWe used metagenomics to determine high-resolution taxonomic and functional profiles of the stool microbiota from IBS cases and household controls (n=56 pairs) on their usual diet. Clinical response and microbiota changes were studied in 41 pairs after 4 weeks on a low FODMAP diet.ResultsUnsupervised analysis of baseline IBS cases pre-diet identified two distinct microbiota profiles, which we refer to as IBSP (pathogenic-like) and IBSH (health-like) subtypes. IBSP microbiomes were enriched in Firmicutes and genes for amino acid and carbohydrate metabolism, but depleted in Bacteroidetes species. IBSH microbiomes were similar to controls. On the low FODMAP diet, IBSH and control microbiota were unaffected, but the IBSP signature shifted towards a health-associated microbiome with an increase in Bacteroidetes (p=0.009), a decrease in Firmicutes species (p=0.004) and normalisation of primary metabolic genes. The clinical response to the low FODMAP diet was greater in IBSP subjects compared with IBSH (p=0.02).Conclusion50% of IBS cases manifested a ‘pathogenic’ gut microbial signature. This shifted towards the healthy profile on the low FODMAP diet; and IBSP cases showed an enhanced clinical responsiveness to the dietary therapy. The effectiveness of FODMAP reduction in IBSP may result from the alterations in gut microbiota and metabolites produced. Microbiota signatures could be useful as biomarkers to guide IBS treatment; and investigating IBSP species and metabolic pathways might yield insights regarding IBS pathogenic mechanisms.
Is underuse of Inhaled Corticosteroids for Asthma in India contributing to 42% of global asthma deaths?
Background: According to the 2019 Global Burden of Disease (GBD) report, India contributes to an estimated 12.9% of global asthma cases (34.3 million) but a disproportionate 42.3% of all global asthma deaths. Also, asthma causes 4.83 million disability-adjusted life years (DALYs) annually in India, four times more than China, which ranks second. Hypothesis: We hypothesised that this disproportionate increase in asthma deaths and suffering in India could be due to the under-use of inhaled corticosteroids. Methods: Using the estimated number of asthma cases in each state and union territory in India (34.3 million) from the 2019 GBD data, we calculated the expected sales of inhaled corticosteroids (ICS) for asthmatics in India. We assumed that 10% of asthmatics have mild intermitted disease and thus need only 4 units of ICS pMDI per year. The remaining 90% should ideally use 12 units of ICS pMDI or equivalent DPI. We also assumed that 30% of ICS sales in India would be accounted for by the 38 million COPD patients. State-wise actual sales of ICS in India were obtained from IQVIA. Results: The total amount of ICS sales in India for asthma obtained from IQVIA was 26.4 million versus the 384.16 million expected sales, which is only 6.8% of the required estimated sales. Moreover, when we correlated state-wise actual sales of ICS in India versus asthma mortality and DALYs (per 100,000 population), we found a significant negative correlation (R = −0.56; P < 0.001 for asthma deaths and R = −0.61; P < 0.001 for asthma DALYs). Impact and Future Direction: Policy-makers, health care providers, public health researchers, asthma sufferers and the people at large need to take cognizance of our findings and undertake appropriate measures, such as creating awareness and ensuring availability and regular use of ICS by asthmatics in India.
An AI-driven framework for predicting sleep quality and delivering personalized recommendations using digital wellbeing and lifestyle data
Sleep is essential for maintaining mental clarity, emotional stability, and physical health, as supported by extensive research in sleep science. However, modern lifestyles characterized by excessive screen exposure, irregular routines, and heightened stress levels have led to a noticeable decline in sleep quality. Existing AI and digital health tools for sleep monitoring remain expensive or heavily reliant on wearable devices, creating a gap in accessible and non-intrusive sleep assessment methods. To address this issue, the present study proposes a low-cost, software-based AI system that predicts sleep quality without specialized hardware. The system integrates behavioral factors such as exercise duration, caffeine intake, and stress levels with digital wellbeing metrics including screen time, app usage patterns, and nighttime device activity, all of which have been shown to influence sleep patterns. After preprocessing, machine learning models such as Random Forest and XGBoost classify sleep quality into Good, Average, or Poor, aligning with prior research utilizing behavioral and physiological indicators for sleep prediction. A user-friendly dashboard visualizes trends and provides personalized recommendations, such as reducing nighttime screen exposure to improve sleep hygiene. This AI-driven approach offers an accessible and actionable framework for improving sleep health.