Mining Indole Alkaloid Synthesis Gene Clusters from Genomes of 53 Claviceps Strains Revealed Redundant Gene Copies and an Approximate Evolutionary Hourglass Model

Ergot fungi (Claviceps spp.) are infamous for producing sclerotia containing a wide spectrum of ergot alkaloids (EA) toxic to humans and animals, making them nefarious villains in the agricultural and food industries, but also treasures for pharmaceuticals. In addition to three classes of EAs, several species also produce paspaline-derived indole diterpenes (IDT) that cause ataxia and staggers in livestock. Furthermore, two other types of alkaloids, i.e., loline (LOL) and peramine (PER), found in Epichloë spp., close relatives of Claviceps, have shown beneficial effects on host plants without evidence of toxicity to mammals. The gene clusters associated with the production of these alkaloids are known. We examined genomes of 53 strains of 19 Claviceps spp. to screen for these genes, aiming to understand the evolutionary patterns of these genes across the genus through phylogenetic and DNA polymorphism analyses. Our results showed (1) varied numbers of eas genes in C. sect. Claviceps and sect. Pusillae, none in sect. Citrinae, six idt/ltm genes in sect. Claviceps (except four in C. cyperi), zero to one partial (idtG) in sect. Pusillae, and four in sect. Citrinae, (2) two to three copies of dmaW, easE, easF, idt/ltmB, itd/ltmQ in sect. Claviceps, (3) frequent gene gains and losses, and (4) an evolutionary hourglass pattern in the intra-specific eas gene diversity and divergence in C. purpurea.

INDO-PAK HYDROPOLITICS: IMPLICATIONS FOR DISPUTED JAMMU AND KASHMIR

India and Pakistan have been fighting over Kashmir, a contested region that is claimed by both the countries. Competition over waterways and dependence over water assets of Kashmir remains a bone of contention between India and Pakistan. This Research paper discusses the dependence of India and Pakistan over water sources originating from Kashmir. Kashmir, besides emotional attachment also has strategic, economic and political benefits for India and Pakistan. In the twenty first century, traditional concepts of state security have been changed. We have moved from traditional security aspects to non-traditional security aspects. Water is included in one of the non-traditional security aspects. India having all cards in hands is showing its’ hegemonic by choking the loose points of Pakistan. Though Indus Water treaty was signed in 1960’s to resolve the water issues between the two countries, but still we have not found any direct solution that will resolve the water crisis and provide permanent peace in the region. There is no way forward which will provide a win win situation for India, Pakistan and Kashmir in Indus water treaty. The researcher accounted that Indus Water Treaty has proved successful as far as its’ theoretical approach is concerned, but has failed in implementation and practicality. The researcher has used Hourglass model to analyze the Indus Water Treaty and to suggest the way forward that will lead towards a conflict resolution. Mixed methods have been used in the research from secondary sources to analyze water dependence. The research also seeks to analyze Indus water treaty and to explore the prospects for equal division of water resources. The subject matter of the research is Indo-Pak water dependency over water of Kashmir with a focus on how it will contribute towards the socio-economic status of India and Pakistan in the region and also how much dependence on water would affect the regional peace and stability in Kashmir conflict. Keywords: Conflict resolution, Hourglass glass model, Kashmir conflict, India-Pakistan water dependency, Indus water Treaty, Composite Dialogue process.

The developmental hourglass model is applicable to the spinal cord

SummaryThe developmental hourglass model predict that embryonic morphology is most conserved at mid-embryonic stage and diverge at early and late stage. This model is generally considered by whole embryonic level. Here, we demonstrate that the hourglass model is also applicable to the more reduced element, the spinal cord. In the middle of the spinal cord development, dorsoventrally arrayed neuronal progenitor domains are established, which is conserved among vertebrates. We found that, by comparing the single-cell transcriptomes between mice and zebrafish, V3 interneurons, a subpopulation of the post-mitotic spinal neurons, display the divergent molecular profiles. We also found non-conservation of cis-regulatory elements located around the progenitor fate determinants, indicating the rewiring of the upstream gene regulatory network. These results demonstrate that, despite the conservation of the progenitor domains, processes before and after the progenitor domain specification has diverged. This study may help understand the molecular basis of the developmental hourglass model.

DL-inferencing for 3D Cephalometric Landmarks Regression task using OpenVINO

In this paper, we evaluate the performance of the Intel Distribution of OpenVINO toolkit in practical solving of the problem of automatic three-dimensional Cephalometric analysis using deep learning methods. This year, the authors proposed an approach to the detection of cephalometric landmarks from CT-tomography data, which is resistant to skull deformities and use convolutional neural networks (CNN). Resistance to deformations is due to the initial detection of 4 points that are basic for the parameterization of the skull shape. The approach was explored on CNN for three architectures. A record regression accuracy in comparison with analogs was obtained. This paper evaluates the perfor- mance of decision making for the trained CNN-models at the inference stage. For a comparative study, the computing environments PyTorch and Intel Distribution of OpenVINO were selected, and 2 of 3 CNN architectures: based on VGG for regression of cephalometric landmarks and an Hourglass-based model, with the RexNext backbone for the land- marks heatmap regression. The experimental dataset was consist of 20 CT of patients with acquired craniomaxillofacial deformities and was in- clude pre- and post-operative CT scans whose format is 800x800x496 with voxel spacing of 0.2x0.2x0.2 mm. Using OpenVINO showed a great increase in performance over the PyTorch, with inference speedup from 13 to 16 times for a Direct Regression model and from 3.5 to 3.8 times for a more complex and precise Hourglass model.