Food habits of tigers Panthera tigris and population attributes of prey species (population structure, density and biomass) were studied in the tropical dry deciduous forest of Pench National Park, Central India, from November 1998 to April 1999. Scat analysis and line transect method were used to estimate tiger food habits and density of major prey species, respectively. The 61.1 km 2 intensive study area was found to have very high ungulate density (90.3 animals km 72 ) with chital Axis axis being the most common species (80.7 animals km 72 ), followed by sambar Cervus unicolor (6.1 animals km 72 ). Common langur Presbytis entellus was the most abundant (77.2 animals km 72 ) primate species. When the density ®gures were multiplied by the average weight of each prey species, a high biomass density of 6013.25 kg km 72 was obtained for the intensive study area. Chital (47.3%) along with sambar (14.5%) and wild pig Sus scrofa (10.9%) constituted the major part of the tiger's diet. If there is food choice, tigers seem to kill medium-and large-sized species more often. Wild pig and sambar were consumed more than their availability, whereas chital were taken in proportion to their availability. Gaur Bos gaurus and nilgai Bosephalus tragocamelus were not represented in the tiger's diet. Common langur was consumed in lesser proportion by tigers than expected by estimates of its density. The average weight of animals consumed by tigers in the intensive study area was 82.1 kg. The analyses revealed that Pench harbours very high prey density and tigers are mostly dependent on the wild ungulates rather than on domestic livestock as is the case in many other areas in the Indian subcontinent. These two factors thus make Pench National Park a potential area for long-term conservation of tigers.

Food habits of tigers Panthera tigris in terms of prey abundance were studied in the semi-arid deciduous forests of Ranthambhore National Park, western India, between November 2000 and April 2001. Wild prey availability was assessed by line transects (n = 8) and prey selection by the tigers was determined from analysis of scats (n = 109). Compared to some other parts of the country, prey abundance was found to be high at 96.65 animals km − 2 . Chital Axis axis was the most abundant wild prey in the study area, followed by common langur Presbytis entellus, sambar Cervus unicolor, nilgai Boselaphus tragocamelus, wild pig Sus scrofa and chinkara Gazella bennetti. Chital (c. 31%) and sambar (c. 47%) constituted the bulk of the tigers' diet and were preferred prey. Nilgai and chinkara contributed minimally to the tigers' diet (c. 5-7% and < 1%, respectively) and were used less than their availability. Domestic livestock made up 10-12% of the tigers' diet. The average weight of an animal consumed was between 107 and 114 kg reflecting a preference for large prey. The analysis reveals that parts of Ranthambhore have high prey abundance, thus making it important for long-term tiger conservation. Despite the high prey abundance, tigers were still considerably dependent on domestic livestock, posing challenges for the park management to resolve potential areas of conflict.

Protein aggregation is a phenomenon that has attracted considerable attention within the pharmaceutical industry from both a developability standpoint (to ensure stability of protein formulations) and from a research perspective for neurodegenerative diseases. Experimental identification of aggregation behavior in proteins can be expensive; and hence, the development of accurate computational approaches is crucial. The existing methods for predicting protein aggregation rely mostly on the primary sequence and are typically trained on amyloid-like proteins. However, the training bias toward beta amyloid peptides may worsen prediction accuracy of such models when applied to larger protein systems. Here, we present a novel algorithm to identify aggregation-prone regions in proteins termed "AggScore" that is based entirely on three-dimensional structure input. The method uses the distribution of hydrophobic and electrostatic patches on the surface of the protein, factoring in the intensity and relative orientation of the respective surface patches into an aggregation propensity function that has been trained on a benchmark set of 31 adnectin proteins. AggScore can accurately identify aggregation-prone regions in several well-studied proteins and also reliably predict changes in aggregation behavior upon residue mutation. The method is agnostic to an amyloid-specific aggregation context and thus may be applied to globular proteins, small peptides and antibodies.

Spatio‐temporal partitioning is a viable mechanism for minimizing resource competition among sympatric species. The occurrence of sympatric large carnivores – tiger Panthera tigris, leopard Panthera pardus and dhole Cuon alpinus – in forests of the Indian subcontinent is complemented with high dietary overlap. We characterized temporal and spatial patterns of large carnivores with major prey species using photo‐captures from 50 camera trap stations in Mudumalai Tiger Reserve, Western Ghats during 2008–2010. We tested whether major prey species' activity and spatial use acted as drivers for coexistence among large carnivores. Tiger exhibited cathemeral activity in the night and is spatially correlated with sambar and gaur, supporting hypotheses related to large‐sized prey. Leopard was active throughout the day and is spatially correlated with almost all prey species with no active separation from tiger. Dhole exhibited diurnal activity and spatial use in relation to chital and avoided felids to a certain extent. Leopard exhibited spatial correlation with tiger and dhole, while tiger did not correlate with dhole. Leopard exhibited relatively broader temporal and spatial tolerance due to its generalist nature, which permits opportunistic exploitation of resources. This supports the hypothesis that predators actively used areas at the same time as their principal prey species depending upon their body size and morphological adaptation. We conclude that resource partitioning in large carnivores by activity and spatial use of their principal prey governs spatio‐temporal separation in large carnivores.

Density of tiger Panthera tigris and leopard Panthera pardus was estimated using photographic capturerecapture sampling in a tropical deciduous forest of Mudumalai Tiger Reserve, southern India, from November 2008 to February 2009. A total of 2,000 camera trap nights for 100 days yielded 19 tigers and 29 leopards within an intensive sampling area of 107 km 2 . Population size of tiger from closed population estimator model M b Zippin was 19 tigers (SE=±0.9) and for leopards M h Jackknife estimated 53 (SE=±11) individuals. Spatially explicit maximum likelihood and Bayesian model estimates were 8.31 (SE=±2.73) and 8.9 (SE=±2.56) per 100 km 2 for tigers and 13.17 (SE=±3.15) and 13.01 (SE=±2.31) per 100 km 2 for leopards, respectively. Tiger density for MMDM models ranged from 6.07 (SE=±1.74) to 9.72 (SE=±2.94) per 100 km 2 and leopard density ranged from 13.41 (SE=±2.67) to 28.91 (SE=±7.22) per 100 km 2 . Spatially explicit models were more appropriate as they handle information at capture locations in a more specific manner than some generalizations assumed in the classical approach. Results revealed high density of tiger and leopard in Mudumalai which is unusual for other high density tiger areas. The tiger population in Mudumalai is a part of the largest population at present in India and a source for the surrounding Reserved Forest.