Habitat preference in the critically endangered yellow‐tailed woolly monkey (Lagothrix flavicauda) at La Esperanza,Peru

Habitat loss is one of the main threats to wildlife. Therefore, knowledge of habitat use and preference is essential for the design of conservation strategies and identification of priority sites for the protection of endangered species. The yellow‐tailed woolly monkey (Lagothrix flavicauda Humboldt, 1812), categorized as Critically Endangered on the IUCN Red List, is endemic to montane forests in northern Peru where its habitat is greatly threatened. We assessed how habitat use and preference in L. flavicauda are linked to forest structure and composition. The study took place near La Esperanza, in the Amazonas region, Peru. Our objective was to identify characteristics of habitat most utilized by L. flavicauda to provide information that will be useful for the selection of priority sites for conservation measures. Using presence records collected from May 2013 to February 2014 for one group of L. flavicauda, we classified the study site into three different use zones: low‐use, medium‐use, and high‐use. We assessed forest structure and composition for all use zones using 0.1 ha Gentry vegetation transects. Results show high levels of variation in plant species composition across the three use zones. Plants used as food resources had considerably greater density, dominance, and ecological importance in high‐use zones. High‐use zones presented similar structure to medium‐ and low‐use zones; thus it remains difficult to assess the influence of forest structure on habitat preference. We recommend focusing conservation efforts on areas with a similar floristic composition to the high‐use zones recorded in this study and suggest utilizing key alimentation species for reforestation efforts.     

The cucumber mosaic virus 1a protein regulates interactions between the 2b protein and ARGONAUTE 1 while maintaining the silencing suppressor activity of the 2b protein

The cucumber mosaic virus (CMV) 2b viral suppressor of RNA silencing (VSR) is a potent counter-defense and pathogenicity factor that inhibits antiviral silencing by titration of short double-stranded RNAs. It also disrupts microRNA-mediated regulation of host gene expression by binding ARGONAUTE 1 (AGO1). But in Arabidopsis thaliana complete inhibition of AGO1 is counterproductive to CMV since this triggers another layer of antiviral silencing mediated by AGO2, de-represses strong resistance against aphids (the insect vectors of CMV), and exacerbates symptoms. Using confocal laser scanning microscopy, bimolecular fluorescence complementation, and co-immunoprecipitation assays we found that the CMV 1a protein, a component of the viral replicase complex, regulates the 2b-AGO1 interaction. By binding 2b protein molecules and sequestering them in P-bodies, the 1a protein limits the proportion of 2b protein molecules available to bind AGO1, which ameliorates 2b-induced disease symptoms, and moderates induction of resistance to CMV and to its aphid vector. However, the 1a protein-2b protein interaction does not inhibit the ability of the 2b protein to inhibit silencing of reporter gene expression in agroinfiltration assays. The interaction between the CMV 1a and 2b proteins represents a novel regulatory system in which specific functions of a VSR are selectively modulated by another viral protein. The finding also provides a mechanism that explains how CMV, and possibly other viruses, modulates symptom induction and manipulates host-vector interactions.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.     

Bayesian Nonparametric Modeling for Comparison of Single-Neuron Firing Intensities

Summary .  We propose a fully inferential model-based approach to the problem of comparing the firing patterns of a neuron recorded under two distinct experimental conditions. The methodology is based on nonhomogeneous Poisson process models for the firing times of each condition with flexible nonparametric mixture prior models for the corresponding intensity functions. We demonstrate posterior inferences from a global analysis, which may be used to compare the two conditions over the entire experimental time window, as well as from a pointwise analysis at selected time points to detect local deviations of firing patterns from one condition to another. We apply our method on two neurons recorded from the primary motor cortex area of a monkey's brain while performing a sequence of reaching tasks.     

Recruitment of Nox4 to a Plasma Membrane Scaffold Is Required for Localized Reactive Oxygen Species Generation and Sustained Src Activation in Response to Insulin-like Growth Factor-I

Nox4-derived ROS is increased in response to hyperglycemia and is required for IGF-I-stimulated Src activation. This study was undertaken to determine the mechanism by which Nox4 mediates sustained Src activation. IGF-I stimulated sustained Src activation, which occurred primarily on the SHPS-1 scaffold protein. In vitro oxidation experiments indicated that Nox4-derived ROS was able to oxidize Src when they are in close proximity, and Src oxidation leads to its activation. Therefore we hypothesized that Nox4 recruitment to the plasma membrane scaffold SHPS-1 allowed localized ROS generation to mediate sustained Src oxidation and activation. To determine the mechanism of Nox4 recruitment, we analyzed the role of Grb2, a component of the SHPS-1 signaling complex. We determined that Nox4 Tyr-491 was phosphorylated after IGF-I stimulation and was responsible for Nox4 binding to the SH2 domain of Grb2. Overexpression of a Nox4 mutant, Y491F, prevented Nox4/Grb2 association. Importantly, it also prevented Nox4 recruitment to SHPS-1. The role of Grb2 was confirmed using a Pyk2 Y881F mutant, which blocked Grb2 recruitment to SHPS-1. Cells expressing this mutant had impaired Nox4 recruitment to SHPS-1. IGF-I-stimulated downstream signaling and biological actions were also significantly impaired in Nox4 Y491F-overexpressing cells. Disruption of Nox4 recruitment to SHPS-1 in aorta from diabetic mice inhibited IGF-I-stimulated Src oxidation and activation as well as cell proliferation. These findings provide insight into the mechanism by which localized Nox4-derived ROS regulates the sustained activity of a tyrosine kinase that is critical for mediating signal transduction and biological actions.     

Diagnosis of abdominal masses with percutaneous biopsy guided by ultrasound.

OBJECTIVE--To assess the accuracy and safety of percutaneous biopsy of abdominal masses guided by ultrasound. DESIGN--Prospective study. SETTING--Combined gastroenterology service, Scarborough Hospital. PATIENTS--108 Consecutive patients identified as having a discrete mass on diagnostic ultrasound examination of the abdomen. INTERVENTION--A sample of tissue was obtained with an aseptic technique under local anaesthesia: an 18 steel wire gauge needle (Tru-Cut) was mounted in a spring loaded firing device (Biopty gun) that was advanced under simultaneous ultrasound scanning, permitting precise localisation of the target organ. MAIN OUTCOME MEASURE--Results of histological examination of tissue specimens. RESULTS--Biopsy failed in four patients. Adequate histological specimens were obtained in 104 patients with masses in the liver (31), pancreas (37), kidney (10), and adrenal glands (six) and in 20 undiagnosed abdominal and retroperitoneal masses. Follow up was until death or confirmation of the diagnosis. Three complications but no deaths occurred. Malignancy was suspected in 84 patients before biopsy. This was confirmed in 70 patients, in 26 of whom confirmation of dissemination obviated the need for further investigation. In 10 patients biopsy indicated a previously unsuspected primary tumour, and in 12 it showed only a benign lesion. Among 24 patients considered to have benign disease biopsy showed an unsuspected neoplasm in seven. Use of biopsy thus had a major effect on clinical management in 55 patients. Four false negative but no false positive diagnoses resulted from the procedure. CONCLUSION--Percutaneous biopsy of abdominal and retroperitoneal masses under ultrasound guidance is a safe and accurate method of obtaining a histological diagnosis. The results obtained have a considerable effect on clinical management.