26 research outputs found

    āŠŪāŠūāŠ§āŦāŠŊāŠŪāŠŋāŠ• āŠķāŠūāŠģāŠūāŠĻāŠū āŠķāŠŋāŠ•āŦāŠ·āŠ•āŦ‹āŠĻāŠū āŠŪāŦ‚āŠēāŦāŠŊāŦ‹, āŠļāŠŋāŠĶāŦāŠ§āŠŋāŠŠāŦāŠ°āŦ‡āŠ°āŠĢāŠū āŠ…āŠĻāŦ‡ āŠķāŦ€āŠ–āŠĩāŠĩāŠū āŠŠāŦāŠ°āŠĪāŦāŠŊāŦ‡āŠĻāŠū āŠĩāŠēāŠĢāŠĻāŦ‹ āŠ…āŠ­āŦāŠŊāŠūāŠļ

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    “āŠˆāŠĻāŦāŠĄāŠŋāŠŊāŠū-āŦĻāŦĶāŦĻāŦĶ āŠĻāŠĩāŦ€ āŠļāŠđāŠļāŦāŠĪāŦāŠ°āŠūāŠŽāŦāŠĶāŦ€āŠĻāŦāŠ‚ āŠļāŦāŠĩāŠŠāŦāŠĻ”āŠŪāŠūāŠ‚ āŠĄāŦ‰. āŠ. āŠŠāŦ€. āŠœāŦ‡. āŠ…āŠŽāŦāŠĶāŦāŠē āŠ•āŠēāŠūāŠŪ āŠēāŠ–āŦ‡ āŠ›āŦ‡ āŠ•āŦ‡ “āŠ•āŦ‹āŠˆāŠŠāŠĢ āŠđāŦ‡āŠļāŠŋāŠŊāŠĪāŠŪāŠūāŠ‚ āŠŠāŠĢ āŠĪāŠŪāŦ‡ āŠœāŦ‹ āŠķāŠŋāŠ•āŦāŠ·āŠ• āŠ›āŦ‹ āŠĪāŦ‹ āŠĪāŠŪāŠūāŠ°āŦ‡ āŠāŠ• āŠĩāŠŋāŠķāŦ‡āŠ· āŠ­āŦ‚āŠŪāŠŋāŠ•āŠū āŠ­āŠœāŠĩāŠĩāŠūāŠĻāŦ€ āŠ›āŦ‡ āŠŠāŠĢ āŠŽāŦ€āŠœāŦ€ āŠ•āŦ‹āŠˆāŠŠāŠĢ āŠĩāŦāŠŊāŠ•āŦāŠĪāŠŋ āŠ•āŠ°āŠĪāŠūāŠ‚ āŠĩāŠ§āŦ āŠĪāŠŪāŦ‡ āŠŠāŦ‡āŠĒāŦ€āŠ“āŠĻāŦ‡ āŠ†āŠ•āŠūāŠ° āŠ†āŠŠāŦ€ āŠ°āŠđāŦāŠŊāŠū āŠ›āŦ‹. āŠ† āŠĶāŦ‡āŠķāŠŪāŠūāŠ‚ āŠāŠ• āŠœāŠŪāŠūāŠĻāŦ‹ āŠđāŠĪāŦ‹ āŠœāŦāŠŊāŠūāŠ°āŦ‡ āŠķāŠŋāŠ•āŦāŠ·āŠ•āŦ‹āŠĻāŦ‹ āŠ—āŦāŠ°āŦāŠ“ āŠĪāŠ°āŦ€āŠ•āŦ‡ āŠ†āŠĶāŠ° āŠĨāŠĪāŦ‹. āŠ†āŠœāŦ‡ āŠœāŦ‹āŠ•āŦ‡, āŠķāŠŋāŠ•āŦāŠ·āŠ•āŠĻāŦ‡ āŠ–āŦ‚āŠĢāŠūāŠŪāŠūāŠ‚ āŠŦāŦ‡āŠ‚āŠ•āŦ€ āŠĶāŦ‡āŠĩāŠūāŠŪāŠūāŠ‚ āŠ†āŠĩāŦāŠŊāŠū āŠ›āŦ‡. āŠ˜āŠĢāŠū āŠķāŠŋāŠ•āŦāŠ·āŠ•āŦ‹ āŠ…āŠĪāŦāŠŊāŠ‚āŠĪ āŠ•āŠ‚āŠ—āŠūāŠģ āŠŠāŠ°āŠŋāŠļāŦāŠĨāŠŋāŠĪāŠŋāŠ“āŠŪāŠūāŠ‚ āŠ•āŠūāŠŪ āŠ•āŠ°āŦ‡ āŠ›āŦ‡. āŠĪāŦ‡āŠŪāŠĻāŦ€ āŠŠāŦāŠ°āŠķāŦāŠ°āŦāŠĻāŦ‹ āŠ‰āŠ•āŦ‡āŠēāŠĩāŠūāŠĻāŦ€ āŠœāŠ°āŦ‚āŠ° āŠ…āŠ‚āŠ—āŦ‡ āŠ…āŠŪāŦ‡ āŠĩāŠūāŠ•āŦ‡āŠŦ āŠ›āŦ€āŠ. āŠ›āŠĪāŠūāŠ‚āŠŊ āŠ…āŠŪāŦ‡ āŠķāŠŋāŠ•āŦāŠ·āŠ•āŦ‹āŠĻāŦ‡ āŠ•āŠūāŠŪ āŠ•āŠ°āŠĩāŠūāŠĻāŦ€ āŠĩāŠŋāŠĻāŠ‚āŠĪāŦ€ āŠ•āŠ°āŦ€āŠ āŠ›āŦ€āŠ.” āŠĄāŦ‰. āŠ•āŠēāŠūāŠŪāŠĻāŠūāŠ‚ āŠļāŦāŠĩāŠŠāŦāŠĻāŠĻāŦāŠ‚ āŠ­āŠūāŠ°āŠĪ āŠĻāŠŋāŠ°āŦāŠŪāŠūāŠĢ āŠ•āŠ°āŠĩāŠūāŠŪāŠūāŠ‚ āŠķāŠŋāŠ•āŦāŠ·āŠ•āŦ‹ āŠ–āŦ‚āŠŽ āŠœ āŠŪāŠđāŠĪāŦāŠĪāŦāŠĩāŠĻāŦ€ āŠ­āŦ‚āŠŪāŠŋāŠ•āŠū āŠ­āŠœāŠĩāŦ€ āŠ°āŠđāŦāŠŊāŠū āŠ›āŦ‡. āŠļāŠŪāŠūāŠœ āŠ…āŠĻāŦ‡ āŠ°āŠūāŠ·āŦāŠŸāŦāŠ°āŠĻāŠū āŠ­āŠūāŠĩāŠŋ āŠĻāŠūāŠ—āŠ°āŠŋāŠ•āŦ‹āŠĻāŦ‹ āŠŪāŠđāŠĪāŦāŠĪāŦāŠĩāŠĻāŦ‹ āŠĩāŠŋāŠ•āŠūāŠļ āŠķāŠūāŠģāŠūāŠ“āŠŪāŠūāŠ‚ āŠĨāŠūāŠŊ āŠ›āŦ‡. āŠŪāŠĻāŦ‹āŠĩāŦˆāŠœāŦāŠžāŠūāŠĻāŠŋāŠ•āŦ‹āŠĻāŦ‹ āŠŪāŠĪāŦ‡ āŠŽāŠūāŠģāŠ•āŠĻāŠū āŠĪāŠ°āŦāŠĢāŠūāŠĩāŠļāŦāŠĨāŠūāŠĻāŠū āŠķāŠ°āŦ‚āŠ†āŠĪāŠĻāŠū āŠĩāŠ°āŦāŠ·āŦ‹ āŠĪāŦ‡āŠĻāŠū āŠĩāŠŋāŠ•āŠūāŠļ āŠŪāŠūāŠŸāŦ‡ āŠ–āŦ‚āŠŽ āŠœ āŠ…āŠ—āŠĪāŦāŠŊāŠĻāŠū āŠ›āŦ‡ āŠ…āŠĻāŦ‡ āŠ† āŠŽāŠūāŠģāŠĩāŠŋāŠ•āŠūāŠļāŠĻāŠū āŠķāŦāŠ°āŦ‡āŠ·āŦāŠ  āŠĪāŠŽāŠ•āŦāŠ•āŠūāŠŪāŠūāŠ‚ āŠķāŠŋāŠ•āŦāŠ·āŠ• āŠĩāŠŋāŠĩāŠŋāŠ§ āŠŠāŦāŠ°āŠ•āŠūāŠ°āŠĻāŦ€ āŠ­āŦ‚āŠŪāŠŋāŠ•āŠū āŠ­āŠœāŠĩāŦ‡ āŠ›āŦ‡. āŠŠāŦāŠ°āŠĩāŠ°āŦāŠĪāŠŪāŠūāŠĻ āŠķāŠŋāŠ•āŦāŠ·āŠĢāŠŪāŠūāŠ‚ āŠ†āŠœāŦ‡ āŠļāŠ‚āŠŠāŦ‚āŠ°āŦāŠĢ āŠ—āŦāŠĢāŠĩāŠĪāŦāŠĪāŠū āŠĩāŦāŠŊāŠĩāŠļāŦāŠĨāŠūāŠŠāŠĻ (TQM)āŠĻāŦ‹ āŠĩāŠŋāŠšāŠūāŠ° āŠ°āŠūāŠ·āŦāŠŸāŦāŠ° āŠ•āŠ•āŦāŠ·āŠūāŠ āŠ…āŠŪāŠēāŠŪāŠūāŠ‚ āŠŪāŦ‚āŠ•āŠūāŠŊ āŠ°āŠđāŦāŠŊāŦ‹ āŠ›āŦ‡. āŠĪāŦ‡āŠĻāŠū āŠœ āŠ­āŠūāŠ— āŠ°āŦ‚āŠŠāŦ‡ āŠđāŠūāŠē āŠĩāŠ°āŦāŠ· āŦĻāŦĶāŦĶāŦĻāŠĨāŦ€ āŠ—āŦāŠœāŠ°āŠūāŠĪ āŠļāŠ°āŠ•āŠūāŠ° āŠĶāŦāŠĩāŠūāŠ°āŠū āŠ•āŠ°āŦāŠŪāŠŊāŦ‹āŠ—āŦ€ āŠŊāŦ‹āŠœāŠĻāŠū āŠđāŦ‡āŠ āŠģ āŠķāŠŋāŠ•āŦāŠ·āŠĢ āŠļāŠūāŠĨāŦ‡ āŠļāŠ‚āŠ•āŠģāŠūāŠŊāŦ‡āŠēāŠūāŠ‚ āŠĪāŠŪāŠūāŠŪ āŠēāŦ‹āŠ•āŦ‹āŠĻāŦ‡ āŠ—āŦāŠĢāŠĩāŠĪāŦāŠĪāŠū-āŠļāŠ­āŠ° āŠĪāŠūāŠēāŦ€āŠŪ āŠ…āŠŠāŠūāŠˆ āŠ°āŠđāŦ€ āŠ›āŦ‡. āŠļāŠ‚āŠķāŦ‹āŠ§āŠ•āŠĻāŦ‡ āŠ† āŠĪāŠūāŠēāŦ€āŠŪ āŠŊāŦ‹āŠœāŠĻāŠū āŠ…āŠ‚āŠĪāŠ°āŦāŠ—āŠĪ āŠ°āŠūāŠœāŠŊ āŠ•āŠ•āŦāŠ·āŠūāŠĻāŠū āŠĪāŠœāŠœāŦāŠž āŠĪāŠ°āŦ€āŠ•āŦ‡ āŠ•āŠūāŠŪāŠ—āŦ€āŠ°āŦ€ āŠ•āŠ°āŠĩāŠūāŠĻāŦ‹ āŠ…āŠĩāŠļāŠ° āŠŠāŦāŠ°āŠūāŠŠāŦāŠĪ āŠĨāŠŊāŦ‹ āŠđāŠĪāŦ‹. āŠ† āŠĪāŠūāŠēāŦ€āŠŪ āŠĶāŠ°āŠŪāŦāŠŊāŠūāŠĻ āŠĶāŠŋāŠĩāŠļāŦ‹ āŠļāŦāŠ§āŦ€ āŠķāŠŋāŠ•āŦāŠ·āŠ•āŦ‹ āŠļāŠūāŠĨāŦ‡ āŠ†āŠ‚āŠĪāŠ° āŠŠāŦāŠ°āŠ•āŦāŠ°āŠŋāŠŊāŠū, āŠœāŦ‚āŠĨ āŠšāŠ°āŦāŠšāŠū āŠ…āŠĻāŦ‡ āŠĩāŠŋāŠšāŠūāŠ° āŠĩāŠŋāŠĻāŠŋāŠŪāŠŊ āŠĶāŦāŠĩāŠūāŠ°āŠū āŠāŠĩāŦ€ āŠ…āŠĻāŦāŠ­āŦ‚āŠĪāŠŋ āŠĨāŠˆ āŠ•āŦ‡ āŠķāŠŋāŠ•āŦāŠ·āŠ•āŦ‹āŠĻāŠū āŠĩāŠŋāŠĩāŠŋāŠ§ āŠŪāŦ‚āŠēāŦāŠŊāŦ‹, āŠļāŠŋāŠ§āŦāŠ§āŠŋāŠŠāŦāŠ°āŦ‡āŠ°āŠĢāŠū āŠ…āŠĻāŦ‡ āŠĪāŦ‡āŠŪāŠĻāŦ‡ āŠķāŦ€āŠ–āŠĩāŠĩāŠū āŠŠāŦāŠ°āŠĪāŦāŠŊāŦ‡āŠĻāŠū āŠĩāŠēāŠĢāŠĻāŦāŠ‚ āŠļāŦāŠĪāŠ° āŠœāŠūāŠĢāŦ€ āŠķāŠŋāŠ•āŦāŠ·āŠĢāŠŪāŠūāŠ‚ āŠļāŠ‚āŠŠāŦ‚āŠ°āŦāŠĢ āŠ—āŦāŠĢāŠĩāŠĪāŦāŠĪāŠū āŠļāŦāŠ§āŠūāŠ°āŠĢāŠū āŠ…āŠ­āŠŋāŠŊāŠūāŠĻāŠĻāŠū āŠ† āŠŪāŠđāŠūāŠŊāŠœāŦāŠžāŠŪāŠūāŠ‚ āŠ•āŦ‡āŠĩāŦ€ āŠ°āŦ€āŠĪāŦ‡ āŠ‰āŠŠāŠŊāŦ‹āŠ—āŦ€ āŠĨāŠˆ āŠķāŠ•āŠūāŠŊ ? āŠĪāŦ‡āŠĩāŠū āŠĩāŠŋāŠšāŠūāŠ°āŠŽāŦ€āŠœ āŠļāŠ‚āŠķāŦ‹āŠ§āŠ•āŠĻāŦ‡ āŠļāŠĪāŠĪ āŠĒāŠ‚āŠĒāŦ‹āŠģāŠĪāŠū āŠđāŠĪāŠūāŠ‚ āŠĪāŦ‡āŠĻāŠūāŠ‚ āŠŠāŠ°āŠŋāŠŠāŠūāŠ•āŠ°āŦ‚āŠŠāŦ‡ āŠŠāŦāŠ°āŠļāŦāŠĪāŦāŠĪ āŠļāŠŪāŠļāŦāŠŊāŠūāŠĻāŦ‹ āŠ‰āŠĶāŦāŠ­āŠĩ āŠĨāŠŊāŦ‹ āŠđāŠĪāŦ‹. āŠ…āŠ‚āŠĪāŦ‡ āŠĶāŦ‡āŠĩāŠĪāŦāŠĪāŦāŠĩāŠĻāŦ‡ āŠŠāŦ‹āŠ·āŠĩāŠūāŠĻāŠū āŠ‰āŠŪāŠĶāŠū āŠ•āŦāŠ·āŦ‡āŠĪāŦāŠ°āŠŪāŠūāŠ‚ āŠ•āŠūāŠ°āŦāŠŊ āŠ•āŠ°āŦ€ āŠ°āŠđāŦ‡āŠēāŠūāŠ‚ āŠ† āŠķāŠŋāŠ•āŦāŠ·āŠ• āŠļāŠŪāŠūāŠœ āŠŪāŠūāŠŸāŦ‡ āŠ•āŠ‚āŠˆāŠ• āŠķāŦāŠ°āŦ‡āŠ·āŦāŠ  āŠ•āŠ°āŦ€ āŠ›āŦāŠŸāŠĩāŠūāŠĻāŠū āŠŠāŦāŠ°āŠŊāŠūāŠļāŠŪāŠūāŠ‚āŠĨāŦ€ āŠāŠ• āŠķāŠŋāŠ•āŦāŠ·āŠ• āŠ•āŦ‡āŠŪ āŠ…āŠēāŠŋāŠŠāŦāŠĪ āŠ°āŠđāŦ€ āŠķāŠ•āŦ‡

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

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    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

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    Engineered polyallylamine nanoparticles for efficient in vitro transfection

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    Purpose: Cationic polymers (i.e. polyallylamine, poly-L-lysine) having primary amino groups are poor transfection agents and possess high cytotoxicity index when used without any chemical modification and usually entail specific receptor mediated endocytosis or lysosomotropic agents to execute efficient gene delivery. In this report, primary amino groups of polyallylamine (PAA, 17 kDa) were substituted with imidazolyl functions, which are presumed to enhance endosomal release, and thus enhance its gene delivery efficiency and eliminate the requirement of external lysosomotropic agents. Further, systems were cross-linked with polyethylene glycol (PEG) to prepare PAA-IAA-PEG (PIP) nanoparticles and evaluated them in various model cell lines. Materials and Methods: The efficacy of PIP nanoparticles in delivering a plasmid encoding enhanced green fluorescent protein (EGFP) gene was assessed in COS-1, N2a and HEK293 cell lines, while their cytotoxicity was investigated in COS-1 and HEK293 cell lines. The PAA was chemically modified using imidazolyl moieties and ionically cross-linked with PEG to engineer nanoparticles. The extent of substitution was determined by ninhydrin method. The PIP nanoparticles were further characterized by measuring the particle size (dynamic light scattering and transmission electron microscopy), surface charge (zeta potential), DNA accessibility and buffering capacity. The cytotoxicity was examined using the MTT method. Results: In vitro transfection efficiency of synthesized nanoparticles is increased up to several folds compared to native polymer even in the presence of serum, while maintaining the cell viability over 100% in COS-1 cells. Nanoparticles possess positive zeta potential between 5.6-13 mV and size range of 185-230 nm in water. The accessibility experiment demonstrated that nanoparticles with higher degree of imidazolyl substitution formed relatively loose complexes with DNA. An acid-base titration showed enhanced buffering capacity of modified PAA. Conclusions: The PIP nanoparticles reveal tremendous potential as novel delivery system for achieving improved transfection efficiency, while keeping the cells at ease

    Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

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    India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study

    Multicenter Case–Control Study of COVID-19–Associated Mucormycosis Outbreak, India

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    We performed a case–control study across 25 hospitals in India for the period of January–June 2021 to evaluate the reasons for an COVID-19–associated mucormycosis (CAM) outbreak. We investigated whether COVID-19 treatment practices (glucocorticoids, zinc, tocilizumab, and others) were associated with CAM. We included 1,733 cases of CAM and 3,911 age-matched COVID-19 controls. We found cumulative glucocorticoid dose (odds ratio [OR] 1.006, 95% CI 1.004–1.007) and zinc supplementation (OR 2.76, 95% CI 2.24–3.40), along with elevated C-reactive protein (OR 1.004, 95% CI 1.002–1.006), host factors (renal transplantation [OR 7.58, 95% CI 3.31–17.40], diabetes mellitus [OR 6.72, 95% CI 5.45–8.28], diabetic ketoacidosis during COVID-19 [OR 4.41, 95% CI 2.03–9.60]), and rural residence (OR 2.88, 95% CI 2.12–3.79), significantly associated with CAM. Mortality rate at 12 weeks was 32.2% (473/1,471). We emphasize the judicious use of COVID-19 therapies and optimal glycemic control to prevent CAM
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