Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya

Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator–prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy‐deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate‐only model shows that only 11.64% (17,190 km²) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km² (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate‐only model. It is predicted that future climate may alter the predator–prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards – a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future.     

IL-10- and TGFβ-mediated Th9 Responses in a Human Helminth Infection

Background

Th9 cells are a subset of CD4⁺ T cells that express the protoypical cytokine, IL-9. Th9 cells are known to effect protective immunity in animal models of intestinal helminth infections. However, the role of Th9 cells in human intestinal helminth infections has never been examined.

Methodology

To examine the role of Th9 cells in Strongyloidis stercoralis (Ss), a common intestinal helminth infection, we compared the frequency of Th9 expressing IL-9 either singly (mono-functional) or co-expressing IL-4 or IL-10 (dual-functional) in Ss-infected individuals (INF) to frequencies in uninfected (UN) individuals.

Principal Findings

INF individuals exhibited a significant increase in the spontaneously expressed and/or antigen specific frequencies of both mono- and dual-functional Th9 cells as well as Th2 cells expressing IL-9 compared to UN. The differences in Th9 induction between INF and UN individuals was predominantly antigen-specific as the differences were no longer seen following control antigen or mitogen stimulation. In addition, the increased frequency of Th9 cells in response to parasite antigens was dependent on IL-10 and TGFx since neutralization of either of these cytokines resulted in diminished Th9 frequencies. Finally, following successful treatment of Ss infection, the frequencies of antigen-specific Th9 cells diminished in INF individuals, suggesting a role for the Th9 response in active Ss infection. Moreover, IL-9 levels in whole blood culture supernatants following Ss antigen stimulation were higher in INF compared to UN individuals.

Conclusion

Thus, Ss infection is characterized by an IL-10- and TGFβ dependent expansion of Th9 cells, an expansion found to reversible by anti-helmintic treatment.     

Endophytes of opium poppy differentially modulate host plant productivity and genes for the biosynthetic pathway of benzylisoquinoline alkaloids

Planta - Endophytes reside in different parts of the poppy plant and perform the tissue-specific functions. Most leaf endophytes modulate photosynthetic efficiency, plant growth, and productivity...     

Baseline susceptibility of Asian corn borer (Ostrinia furnacalis (Guenée)) populations in Vietnam to Cry1Ab insecticidal protein

Susceptibility of Asian corn borer (ACB), Ostrinia furnacalis (Guenée) to Bacillus thuringiensis (Bt) Cry1Ab protein was studied between 2015 and 2016 with 11 ACB populations, collected from various geographical regions in Vietnam. A concentration range of Cry1Ab from 0.20 to 26.10 ng/cm² of diet was evaluated against F₁ ACB neonates using diet surface-overlay bioassays. Mortality data was recorded daily until seven days after infestation. Growth inhibition was recorded at the end of seven days. The median lethal concentration (LC₅₀) varied ≈3-fold among the different populations, ranging from 0.58 to 1.83 ng/cm² of diet with an overall mean of 0.86 ng/cm² of diet. Even the lowest concentration of 0.20 ng/cm² caused 73.53% growth inhibition. >90% growth inhibition was achieved at 0.82 ng/cm² or higher concentrations. The results reflect natural variation in Bt susceptibility among ACB populations rather than variation caused by prior exposure to selection pressures. LC₉₉ value (17.26 ng/cm²) was generated by pooling mortality data across different populations. The upper fiducial limit of LC₉₉ (24.38 ng/cm²) could be a potential diagnostic dose for future resistance monitoring programs. The findings from this study suggest that ACB populations in Vietnam are highly susceptible to Cry1Ab protein. This is the first report of Cry1Ab susceptibility of different ACB populations in Vietnam and will serve as a baseline for future resistance monitoring work.     

Dissecting protein‐protein interactions in proteasome assembly: Implication to its self‐assembly

The 26S proteasome is a multi‐catalytic ATP‐dependent protease complex that recognizes and cleaves damaged or misfolded proteins to maintain cellular homeostasis. The 26S subunit consists of 20S core and 19S regulatory particles. 20S core particle consists of a stack of heptameric alpha and beta subunits. To elucidate the structure‐function relationship, we have dissected protein‐protein interfaces of 20S core particle and analyzed structural and physiochemical properties of intra‐alpha, intra‐beta, inter‐beta, and alpha‐beta interfaces. Furthermore, we have studied the evolutionary conservation of 20S core particle. We find the size of intra‐alpha interfaces is significantly larger and is more hydrophobic compared with other interfaces. Inter‐beta interfaces are well packed, more polar, and have higher salt‐bridge density than other interfaces. In proteasome assembly, residues in beta subunits are better conserved than alpha subunits, while multi‐interface residues are the most conserved. Among all the residues at the interfaces of both alpha and beta subunits, Gly is highly conserved. The largest size of intra‐alpha interfaces complies with the hypothesis that large interfaces form first during the 20S assembly. The tight packing of inter‐beta interfaces makes the core particle impenetrable from outer wall of the cylinder. Comparing the three domains, eukaryotes have large and well‐packed interfaces followed by archaea and bacteria. Our findings provide a structural basis of assembly of 20S core particle in all the three domains of life.     

Twelve polymorphic microsatellite loci from the Asian citrus psyllid,Diaphorina citri Kuwayama,the vector for citrus greening disease,huanglongbing

Twelve polymorphic microsatellite markers were developed from microsatellite‐enriched DNA libraries and mined from an expressed sequence tags library of Diaphorina citri, the vector of the citrus greening disease (huanglongbing). Analysis of 288 individuals from Florida, Texas, and Brazil showed that allelic diversity ranged from three to eight alleles per locus and observed and expected heterozygosities ranged from 0.014 to 0.569 and from 0.052 to 0.653, respectively. These variable microsatellite loci can provide means for assessing overall genetic variation and migration patterns for this agriculturally important pest species. This information can be used to aid in developing successful management strategies.     

Single feature polymorphism discovery in rice

The discovery of nucleotide diversity captured as single feature polymorphism (SFP) by using the expression array is a high-throughput and effective method in detecting genome-wide polymorphism. The efficacy of such method was tested in rice, and the results presented in the paper indicate high sensitivity in predicting SFP. The sensitivity of polymorphism detection was further demonstrated by the fact that no biasness was observed in detecting SFP with either single or multiple nucleotide polymorphisms. The high density SFP data that can be generated quite effectively by the current method has promise for high resolution genetic mapping studies, as physical location of features are well-defined on rice genome.     

Survival of boll weevil （Coleoptera： Curculionidae） adults after feeding on pollens from various sources

The survival of overwintering boll weevil, Anthonomus grandis grandis （Boheman）, adults on non-cotton hosts in the Lower Rio Grande Valley （LRGV） of Texas was examined from 2001 to 2006. The success of the Boll Weevil Eradication Program, which was reintroduced into the LRGV in 2005, depends on controlling overwintering boll weevil populations. Laboratory studies were conducted using boll weevil adults that were captured in pheromone traps from September through March. The number of adults captured per trap declined significantly in the field from fall to the beginning of spring （3.5-7.0-fold）. The proportion of trapped males and females did not differ significantly. The mean weight of boll weevil adults captured in September was 13.3 mg, while those of captured adults from November to February were significantly lower and ranged from 6.7 to 7.8 mg. Our results show that boll weevil adults can feed on different plant pollens. The highest longevity occurred when adults were fed almond pollen or mixed pollens （72.6 days and 69.2 days, respectively） and the lowest when they fed on citrus pollen or a non-food source （9.7 days or 7.4 days, respectively）. The highest adult survival occurred on almond and mixed pollens [88.0%-97. 6% after 1st feeding period （10 days）, 78.0%-90.8% after 3rd feeding period （10 days）, 55. 0%-83.6% after 5th feeding period （10 days）, and 15.2%-32.4% after lOth feeding period （10 days）]. The lowest adult survival occurred on citrus pollen [52.0%-56.0% after 1st feeding period （10 days）, 13.3% after 3rd and 5th feeding periods （10 days）, and 0 after 6th feeding period （10 days）]. Pollen feeding is not a behavior restricted to adult boll weevils of a specific sex or physiological state. Understanding how boll weevil adults survive in the absence of cotton is important to ensure ultimate success of eradicating this pest in the subtropics.     

Classification of Leukemia and Leukemoid Using VGG-16 Convolutional Neural Network Architecture

Leukemoid reaction like leukemia indicates noticeable increased count of WBCs (White Blood Cells) but the cause of it is due to severe inflammation or infections in other body regions. In automatic diagnosis in classifying leukemia and leukemoid reactions, ALL IDB2 (Acute Lymphoblastic Leukemia-Image Data Base) dataset has been used which comprises 110 training images of blast cells and healthy cells. This paper aimed at an automatic process to distinguish leukemia and leukemoid reactions from blood smear images using Machine Learning. Initially, automatic detection and counting of WBC is done to identify leukocytosis and then an automatic detection of WBC blasts is performed to support classification of leukemia and leukemoid reactions. Leukocytosis is commonly observed both in leukemia and leukemoid hence physicians may have chance of wrong diagnosis of malignant leukemia for the patients with leukemoid reactions. BCCD (blood cell count detection) Dataset has been used which has 364 blood smear images of which 349 are of single WBC type. The Image segmentation algorithm of Hue Saturation Value color based on watershed has been applied. VGG16 (Visual Geometric Group) CNN (Convolution Neural Network) architecture based deep learning technique is being incorporated for classification and counting WBC type from segmented images. The VGG16 architecture based CNN used for classification and segmented images obtained from first part were tested to identify WBC blasts.