On a Dhole trail: examining ecological and anthropogenic correlates of Dhole habitat occupancy in the Western Ghats of India

Although they play a critical role in shaping ecological communities, many threatened predator species are data-deficient. The Dhole Cuon alpinus is one such rare canid with a global population thought to be < 2500 wild individuals. We assessed habitat occupancy patterns of dholes in the Western Ghats of Karnataka, India, to understand ecological and anthropogenic determinants of their distribution and habitat-use. We conducted spatially replicated detection/non-detection surveys of dhole signs along forest trails at two appropriate scales: the entire landscape and a single wildlife reserve. Landscape-scale habitat occupancy was assessed across 38,728 km2 surveying 206 grid cells of 188-km2 each. Finer scale habitat-use within 935 km2 Bandipur Reserve was studied surveying 92 grid cells of 13-km2 km each. We analyzed the resulting data of dhole signs using likelihood-based habitat occupancy models. The models explicitly addressed the problematic issue of imperfect detection of dhole signs during field surveys as well as potential spatial auto-correlation between sign detections made on adjacent trail segments. We show that traditional ‘presence versus absence’ analyses underestimated dhole habitat occupancy by 60% or 8682 km2 [naïve  =  0.27; ≏ ψL (SE) =  0.68 (0.08)] in the landscape. Addressing imperfect sign detections by estimating detection probabilities [ˆpt(L) (SE)  =  0.12 (0.11)] was critical for reliable estimation. Similar underestimation occurred while estimating habitat-use probability at reserve-scale [naïve  =  0.39; ˆψs (SE) =  0.71 (0.06)]. At landscape scale, relative abundance of principal ungulate prey primarily influenced dhole habitat occupancy. Habitat-use within a reserve, however, was predominantly and negatively influenced by anthropogenic disturbance. Our results are the first rigorous assessment of dhole occupancy at multiple spatial scales with potential conservation value. The approach used in this study has potential utility for cost-effectively assessing spatial distribution and habitat-use in other species, landscapes and reserves

Disrupting myeloid-specific LXRα phosphorylation promotes FoxM1 expression and modulates atherosclerosis by inducing macrophage proliferation

Macrophages are key immune cells for the initiation and development of atherosclerotic lesions. However, the macrophage regulatory nodes that determine how lesions progress in response to dietary challenges are not fully understood. Liver X receptors (LXRs) are sterol-regulated transcription factors which play a central role in atherosclerosis by integrating cholesterol homeostasis and immunity. LXR pharmacological activation elicits a robust anti-atherosclerotic transcriptional program in macrophages that can be affected by LXRα S196 phosphorylation in vitro. To investigate the impact of these transcriptional changes in atherosclerosis development, we have generated mice carrying a Ser-to-Ala mutation in myeloid cells in the LDLR-deficient atherosclerotic background (M-S196ALdlr-KO). M-S196ALdlr-KO mice fed a high fat diet exhibit increased atherosclerotic plaque burden and lesions with smaller necrotic cores and thinner fibrous caps. These diet-induced phenotypic changes are consistent with a reprogramed macrophage transcriptome promoted by LXRα-S196A during atherosclerosis development. Remarkably, expression of several proliferation-promoting factors including the proto-oncogene FoxM1 and its targets are induced by LXRα-S196A. This is consistent with increased proliferation of plaque-resident cells in M-S196ALdlr-KO mice. Moreover, disrupted LXRα phosphorylation increases expression of phagocytic molecules resulting in increased apoptotic cell removal by macrophages, explaining the reduced necrotic cores. Finally, the macrophage transcriptome promoted by LXRα-S196A under dietary perturbation is markedly distinct from that revealed by LXR ligand activation, highlighting the singularity of this post-translational modification. Overall, our findings demonstrate that LXRα phosphorylation at S196 is an important determinant of atherosclerotic plaque development through selective changes in gene transcription that affect multiple pathways

Awareness and Utilization of Health Insurance Among Selected Population of State of Sikkim, India

On an average, 10% Indians are covered under different types of health insurance schemes, mostly inadequate. This low coverage might be because of lack of awareness about health insurance or might be because of lack of financial literacy. The aim of the present study was to investigate the awareness, and utilization of health insurance in the selected population of State of Sikkim. A cross-sectional descriptive study was carried out in northeastern region (NER) of India, which is considered as one of the backward regions of the country. Sample unit was revisiting Central Referral Hospital Manipal, Gangtok Sikkim. The study was conducted among 1500 Out-patients revisiting the various outpatient departments of the hospital. Finding was significant for awareness of health insurance; enrolment for the scheme; reason for non- enrolment. 49.9% of the non-enrollees were not aware of the health insurance schemes. 25.1% of the participants have utilized the services more than five times in a year. An important finding of the current study is that education and economic class seldom influence peoples’ enrollment in health insurance schemes. The study supports this statement as 89.6% of literates were from non-enrollees group and 77.7% were from lower middle class and upper lower income groups. This indicates the need for financial education for people and their families to take up better financial investment decision and increase their health security. Enhancing the financial literacy and to create awareness and benefits of health insurance among the people of the selected region is important. It is suggested that the issues related financial literacy can be taken up by insurance companies or the organizers by conducting more and more awareness programs in identified regions of low and moderate enrolment across the country

Quality of life among nurses working in different health care setting in the state of Karnataka, India

Context: Nurses reactions on stressors can be physiological, psychological and behavioral leading to stress related to mental and physical diseases that decrease well-being, satisfaction and quality of life. Aim: To investigate the quality of life (QOL) among nurses working in different healthcare settings in hospitals of Karnataka State, India. Settings and Design: This is a cross-sectional study carried out in two regions of Karnataka State, India with a total sample size of 501. Subjects and Methods: WHO evaluation instrument on Quality of Life World Health Organization Quality of Life-Brief Version (WHOQOL-BREF) is the tool used for collecting and analysing data. It composed of four domains: Physical health, psychological health, social relationships and the environmental domain. Statistical Analysis Used: The mean score of items within each domain is used to calculate the domain score. Transformed scores were estimated using the tables for standardizing scores from 0-100. SPSS 16.0 Version is used for statistical analysis. Results: For overall physical health status of nurses was "ill" in both the hospitals (34%; 23%) with significance at 0.01 levels. The mean score for psychological domain was least (41.83). Overall perception of QOL result showed significance at 0.01 level for all domains except for psychological domain. Conclusions: Hospital authorities and health managers of any type of health care setting need to plan for enhancing better quality of life for nurses by planning for better working environment by providing facilities for coping mental demands, software systems and work-rest schedules to reduce the jobs physical demands. Thus, enhance QOL of nurses resulting in better healthcare services to the community

Measuring Indian giant squirrel (Ratufa indica) abundance in southern India using distance sampling

A large body of work on the ecology of sciurids is based on comparing patterns of abundance across either space or time. However, in most cases investigators choose to use surrogate measures of abundance, such as indices based on species or sign encounter rates, or trapping rates. This requires the assumption that detection probabilities are equal at all sites (or time periods) sampled, an assumption that is difficult to meet under field conditions. We demonstrate the application of line transect-based distance sampling, a technique that explicitly models and accounts for detection probability, to estimate ecological densities of Indian giant squirrels in forested habitats. Line transect surveys were carried out at several sites and the number of detections included: 86 (Bandipur), 152 (Nalkeri), 110 (Sunkadakatte), 304 (Muthodi) and 236 (Lakkavalli). The encounter rates ranged from 0.179/km in Bandipur through 0.296/km (Nalkeri), 0.368/km (Sunkadakatte), and 0.625/km (Lakkavalli), to 0.779/km in Muthodi, while the estimated probabilities of detection were 0.517 (Bandipur), 0.532 (Nalkeri), 0.531 (Sunkadakatte) 0.548 (Lakkavalli) and 0.604 (Muthodi). The estimated mean squirrel densities (± standard error of the density) ranged from 2.37 (0.33) squirrels/km2 in Bandipur through 4.55 (0.44) squirrels/km2 in Nalkeri, 4.86 (0.62) squirrels/km2 in Sunkadakatte, to 10.20 (0.82) squirrels/km2 and 12.26 (1.10) squirrels/km2 in Muthodi and Lakkavalli respectively. We discuss design, field survey and data analytic considerations for rigorously estimating squirrel density and abundance

Implementation of International Classification of Diseases 10: Preparedness for E-medical records and health reporting

Context: International Statistical Classification of Diseases and Related Health Problems (ICD 10) define the universe of diseases that exist, and classify them according to specified criteria. World Health Organization (WHO) has mandated ICD 10 for health reporting by its member states. In India, few of the hospitals in the state are following the standard coding and reporting system. Ministry of Health and Family Welfare (MOHFW), India, have notified the electronic medical records standards to be followed by health care providers in August, 2013 and recommended ICD 10 as reporting standard for both mortality and morbidity. The current study was carried out to promote standard reporting practices and implementation of ICD 10 coding system as per WHO/MOHFW reporting norms in a 150 bedded mission hospital in Udupi District of Karnataka State and successfully implemented with VI phase project. The phases included awareness and knowledge interviews, orientation, training, implementation, and testing. Although the standards and notification have been put up in government MOHFW web pages, it is suggested that the authorized bodies to mandate standard reporting of disease by all types of healthcare providers and upgrading/training programs to be extended to private healthcare sectors as well

State space and movement specification in open population spatial capture-recapture models.

With continued global changes, such as climate change, biodiversity loss, and habitat fragmentation, the need for assessment of long-term population dynamics and population monitoring of threatened species is growing. One powerful way to estimate population size and dynamics is through capture-recapture methods. Spatial capture (SCR) models for open populations make efficient use of capture-recapture data, while being robust to design changes. Relatively few studies have implemented open SCR models, and to date, very few have explored potential issues in defining these models. We develop a series of simulation studies to examine the effects of the state-space definition and between-primary-period movement models on demographic parameter estimation. We demonstrate the implications on a 10-year camera-trap study of tigers in India. The results of our simulation study show that movement biases survival estimates in open SCR models when little is known about between-primary-period movements of animals. The size of the state-space delineation can also bias the estimates of survival in certain cases.We found that both the state-space definition and the between-primary-period movement specification affected survival estimates in the analysis of the tiger dataset (posterior mean estimates of survival ranged from 0.71 to 0.89). In general, we suggest that open SCR models can provide an efficient and flexible framework for long-term monitoring of populations; however, in many cases, realistic modeling of between-primary-period movements is crucial for unbiased estimates of survival and density

Study area map of Bandipur Tiger Reserve.

<p>Study area and survey design for Bandipur Tiger Reserve, India (2012) showing protected area boundary, forest road sign-survey routes and 13-km²-grid array. Inset: location of the study area and adjoining protected areas.</p

The Nottingham Ischaemic Cardiovascular Magnetic Resonance resource (NotIs CMR): a prospective paired clinical and imaging scar database—protocol

Introduction Research utilising artificial intelligence (AI) and cardiovascular magnetic resonance (CMR) is rapidly evolving with various objectives, however AI model development, generalisation and performance may be hindered by availability of robust training datasets including contrast enhanced images. Methods NotIs CMR is a large UK, prospective, multicentre, observational cohort study to guide the development of a biventricular AI scar model. Patients with ischaemic heart disease undergoing clinically indicated contrast-enhanced cardiac magnetic resonance imaging will be recruited at Nottingham University Hospitals NHS Trust and Mid-Yorkshire Hospital NHS Trust. Baseline assessment will include cardiac magnetic resonance imaging, demographic data, medical history, electrocardiographic and serum biomarkers. Participants will undergo monitoring for a minimum of 5 years to document any major cardiovascular adverse events. The main objectives include (1) AI training, validation and testing to improve the performance, applicability and adaptability of an AI biventricular scar segmentation model being developed by the authors and (2) develop a curated, disease-specific imaging database to support future research and collaborations and, (3) to explore associations in clinical outcome for future risk prediction modelling studies. Conclusion NotIs CMR will collect and curate disease-specific, paired imaging and clinical datasets to develop an AI biventricular scar model whilst providing a database to support future research and collaboration in Artificial Intelligence and ischaemic heart disease

Patterns and Determinants of Habitat Occupancy by the Asian Elephant in the Western Ghats of Karnataka, India

<div><p>Understanding species distribution patterns has direct ramifications for the conservation of endangered species, such as the Asian elephant <i>Elephas maximus</i>. However, reliable assessment of elephant distribution is handicapped by factors such as the large spatial scales of field studies, survey expertise required, the paucity of analytical approaches that explicitly account for confounding observation processes such as imperfect and variable detectability, unequal sampling probability and spatial dependence among animal detections. We addressed these problems by carrying out ‘detection—non-detection’ surveys of elephant signs across a <i>c</i>. 38,000-km² landscape in the Western Ghats of Karnataka, India. We analyzed the resulting sign encounter data using a recently developed modeling approach that explicitly addresses variable detectability across space and spatially dependent non-closure of occupancy, across sampling replicates. We estimated overall occupancy, a parameter useful to monitoring elephant populations, and examined key ecological and anthropogenic drivers of elephant presence. Our results showed elephants occupied 13,483 km² (<i>SE</i> = 847 km²) corresponding to 64% of the available 21,167 km² of elephant habitat in the study landscape, a useful baseline to monitor future changes. Replicate-level detection probability ranged between 0.56 and 0.88, and ignoring it would have underestimated elephant distribution by 2116 km² or 16%. We found that anthropogenic factors predominated over natural habitat attributes in determining elephant occupancy, underscoring the conservation need to regulate them. Human disturbances affected elephant habitat occupancy as well as site-level detectability. Rainfall is not an important limiting factor in this relatively humid bioclimate. Finally, we discuss cost-effective monitoring of Asian elephant populations and the specific spatial scales at which different population parameters can be estimated. We emphasize the need to model the observation and sampling processes that often obscure the ecological process of interest, in this case relationship between elephants to their habitat.</p></div