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.

     

Nonthermal Plasma‐Induced Degradation of Morin and Enhancement of Biological Activities

In the present study, non‐thermal dielectric barrier discharge (DBD) plasma of induced structural changes of morin resulted in the isolation of one previously undescribed benzofuranone derivative, along with two known compounds. The chemical structures of these degradation products were elucidated by UV, NMR and FAB‐MS spectroscopic analyses. The isolated three compounds showed potent antioxidative activities in two different tests, with IC₅₀ values in the range of 12.9–41.8 μm in the 2,2′‐azino‐bis (3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS⁺) radical scavenging activity, 19.0–71.9 μm for hydroxyl radical scavenging activity test. Furthermore, the new methoxylated benzofuranone exhibited enhancement of inhibitory effects against pancreatic lipase with an IC₅₀ value of 90.7±1.6 μm , when compared to the parent morin. These results suggested that the degradation products isolated from plasma exposed morin might be beneficial for prevention of obesity and related diseases.     

Sex Differences in the Steepness of Dominance Hierarchies in Captive Bonobo Groups

Bonobos have a reputation as a female-dominated and egalitarian species. We examined the 2 aspects of dominance in 6 captive bonobo groups. Females do not consistently evoke submission from all males in all contexts. Though females occupy the highest-ranking positions in the dominance hierarchy, there are in each group males that obtain rather high ranks and are able to dominate ≥1 female. Thus female dominance is not complete and hierarchies can be better described as nonexclusive female dominance. We studied egalitarianism by measuring linearity and steepness of dominance hierarchies. The hierarchies of all groups are highly linear. Hierarchies among males are steeper than among females. On average, male bonobos are more despotic than females, but females too can have despotic relations, both with other females and with males. Hence one can call bonobos in captivity semidespotic rather than egalitarian.     

Long noncoding RNA PTENP1 affects the recovery of spinal cord injury by regulating the expression of miR-19b and miR-21

Exosomes derived from differentiated P12 cells and MSCs were proved to suppress apoptosis of neuron cells, and phosphatase and tensin homolog pseudogene 1 (PTENP1) was reported to inhibit cell proliferation. In this study, we aimed to investigate the role of PTENP1 in the process of post-spinal cord injury (SCI) recovery, so as to evaluate the therapeutic effects of exosomes derived from MSCs transfected with PTENP1 short hairpin RNA (shRNA), as a type of novel biomarkers in the treatment of SCI. Electron microscopy was used to observe the morphology of different exosomes. Real-time polymerase chain reaction and western blot, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays, flow cytometry, Nissl staining, immunohistochemistry assay, and terminal deoxynucleotidyl transferase dUTP nick end labeling assay were conducted to investigate and validate the underlying molecular signaling pathway. PTENP1-shRNA downregulated PTENP1 and PTEN while upregulating miR-21 and miR-19b. PTENP1-shRNA also accelerated cell apoptosis and reduced cell viability. In addition, PTENP1 reduced the miR-21 and miR-19b expression by directly targeting miR-21 and miR-19b. Meanwhile, both miR-21 and miR-19b reduced the expression of PTEN by directly targeting the 3′-untranslated region of PTEN. Furthermore, PTEN level and apoptosis index of neuron cells was the highest in the SCI group, while the treatment with exosomes+PTENP1-shRNA reduced the PTEN expression to a level similar to that in the sham group. Finally, PTENP1 inhibited miR-21 and miR-19b expression but upregulated PTEN expression. The upregulation of miR-21/miR-19b also suppressed the apoptosis of neuron cells by downregulating the PTEN expression. PTENP1 is involved in the recovery of SCI by regulating the expression of miR-19b and miR-21, and exosomes from PTENP1-shRNA-transfected cells may be used as a novel biomarker in SCI treatment.     

Soil Properties,Nutrient Dynamics,and Soil Enzyme Activities Associated with Garlic Stalk Decomposition under Various Conditions

The garlic stalk is a byproduct of garlic production and normally abandoned or burned, both of which cause environmental pollution. It is therefore appropriate to determine the conditions of efficient decomposition, and equally appropriate to determine the impact of this decomposition on soil properties. In this study, the soil properties, enzyme activities and nutrient dynamics associated with the decomposition of garlic stalk at different temperatures, concentrations and durations were investigated. Stalk decomposition significantly increased the values of soil pH and electrical conductivity. In addition, total nitrogen and organic carbon concentration were significantly increased by decomposing stalks at 40°C, with a 5∶100 ratio and for 10 or 60 days. The highest activities of sucrase, urease and alkaline phosphatase in soil were detected when stalk decomposition was performed at the lowest temperature (10°C), highest concentration (5∶100), and shortest duration (10 or 20 days). The evidence presented here suggests that garlic stalk decomposition improves the quality of soil by altering the value of soil pH and electrical conductivity and by changing nutrient dynamics and soil enzyme activity, compared to the soil decomposition without garlic stalks.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.