This research work presents a comparative performance of geographic information system (GIS)-based statistical models for landslide susceptibility mapping (LSM) of the Himalayan watershed in India. A ...total of 190 landslide locations covering an area of 14.63 km
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were identified in the watershed, using high-resolution linear imaging self-scanning (LISS IV) data. The causative factors used for LSM of the study area are slope, aspect, lithology, curvature, lineament density, land cover and drainage buffer. The spatial database has been prepared using remote sensing data along with ancillary data like geological maps. LSMs were prepared using information value (InV), frequency ratio (FR) and analytical hierarchy process (AHP) models. The validation results using the prediction rate curve technique show 89.61%, 87.12% and 88.26% area under curve values for FR, AHP and InV models, respectively. Therefore, the frequency ratio (FR) model could be used for LSM in other parts of this hilly terrain.
The transcytosis of antigens across the gut epithelium by microfold cells (M cells) is important for the induction of efficient immune responses to some mucosal antigens in Peyer's patches. Recently, ...substantial progress has been made in our understanding of the factors that influence the development and function of M cells. This review highlights these important advances, with particular emphasis on: the host genes which control the functional maturation of M cells; how this knowledge has led to the rapid advance in our understanding of M-cell biology in the steady state and during aging; molecules expressed on M cells which appear to be used as "immunosurveillance" receptors to sample pathogenic microorganisms in the gut; how certain pathogens appear to exploit M cells to infect the host; and finally how this knowledge has been used to specifically target antigens to M cells to attempt to improve the efficacy of mucosal vaccines.
The present era has seen a surge in artificial intelligence-related research in oncology, mainly using deep learning, because of powerful computer hardware, improved algorithms and the availability ...of large amounts of data from open-source domains and the use of transfer learning. Here we discuss the multifaceted role of deep learning in cancer care, ranging from risk stratification, the screening and diagnosis of cancer, to the prediction of genomic mutations, treatment response and survival outcome prediction, through the use of convolutional neural networks. Another role of artificial intelligence is in the generation of automated radiology reports, which is a boon in high-volume centres to minimise report turnaround time. Although a validated and deployable deep-learning model for clinical use is still in its infancy, there is ongoing research to overcome the barriers for its universal implementation and we also delve into this aspect. We also briefly describe the role of radiomics in oncoimaging. Artificial intelligence can provide answers pertaining to cancer management at baseline imaging, saving cost and time. Imaging biobanks, which are repositories of anonymised images, are also briefly described. We also discuss the commercialisation and ethical issues pertaining to artificial intelligence. The latest generation generalist artificial intelligence model is also briefly described at the end of the article. We believe this article will not only enrich knowledge, but also promote research acumen in the minds of readers to take oncoimaging to another level using artificial intelligence and also work towards clinical translation of such research.
•Risk prediction using artificial intelligence can triage patients for cancer screening.•Artificial intelligence-based diagnosis and molecular mutation prediction can save cost and time.•Artificial intelligence-based treatment response and toxicity prediction can guide management decisions.•Artificial intelligence-based survival outcome and recurrence prediction can aid in prognostication.•Researchers to focus on clinical translation of the developed mathematical algorithm.
A mobile ad hoc network (MANET) is a self-configurable network connected by wireless links. This type of network is only suitable for provisional communication links as it is infrastructure-less and ...there is no centralized control. Providing QoS and security aware routing is a challenging task in this type of network due to dynamic topology and limited resources. The main purpose of secure and trust based on-demand multipath routing is to find trust based secure route from source to destination which will satisfy two or more end to end QoS constraints. In this paper, the standard ad hoc on-demand multi-path distance vector protocol is extended as the base routing protocol to evaluate this model. The proposed mesh based multipath routing scheme to discover all possible secure paths using secure adjacent position trust verification protocol and better link optimal path find by the Dolphin Echolocation Algorithm for efficient communication in MANET. The performance analysis and numerical results show that our proposed routing protocol produces better packet delivery ratio, reduced packet delay, reduced overheads and provide security against vulnerabilities and attacks.
The study indicates the viability of geographic information system and remote sensing data for the analysis as well as estimation of the stage and the rate of erosional processes in a Himalayan ...watershed for improved planning and management. The Gaj watershed lies in the outer Himalayan region of Himachal Pradesh, India, which has been characterized in to nine sub-watersheds for studying the geomorphological evolution of each separately for comparative assessment irrespective of any scale issue. The method involves the use of 30 m Cartosat (digital elevation model) for operative and time-saving data extraction of morphometric and hypsometric parameters. The estimated hypsometric integral values and the shape of the hypsometric curves reveal varying degree of erosional stages of the sub-watersheds demanding attention over the denudation activities. The results have helped in the qualitative discussions and prioritizing the sub-watershed for sustainable soil–water conservation and management, which can be useful for controlling the erosional activities at right locations in the study area.
Signal transduction through the transforming growth factor-beta 1 (TGF-β1) pathway affects epithelial to mesenchymal transition (EMT), partly by modulation of E-Cadherin expression. The concurrent ...impact of extracellular matrix driven regulation of integrin signaling on EMT has not been well characterized. We assessed the cumulative effect and molecular mechanisms of TGF-β1 and integrin signal transduction on E-Cadherin in a renal cell cancer (RCC) model. Stimulation of RCC cells with TGF-β1 demonstrated a three-fold increased expression of integrin αv. A ligand of integrin αv-β3, (cyclopentapeptide containing Arginyl-Glycyl-Aspartic acid motif, RGD), was used to mimic integrin signaling. Treatment of cells with RGD and TGF-β1 demonstrated significantly greater E-cadherin depletion than either ligand alone. This cooperative action on E-Cadherin expression is regulated by transcription factor Snai1 and is followed on a cellular level by increased cellular mobility as evidenced in a wound healing assay. Subsequent silencing of potential downstream mediators of the cumulative action of RGD and TGF-β1 was carried out by small interfering RNA transfection and confirmed by Western blotting and/or RT-PCR. SiRNA mediated silencing of FAK and PINCH1 independently abrogated the cumulative effect of RGD and TGF-β1 on E-Cadherin expression.
We have identified a novel mechanism through which extracellular matrix event transduction by integrins further augments TGF-β1 related effects on EMT. Molecular machinery involved in the integrin αv-TGF-β1 interplay may represent a therapeutic target in RCC.
•In a renal cell carcinoma model, integrin signaling with RGD was synergistic with TGF-β1 in causing e-cadherin depletion.•Silencing of downstream mediators FAK and PINCH1 prevented this synergism.•These proteins may represent therapeutically-targetable steps in the pathogenesis of renal cell carcinoma.
Gliomas are the commonest malignant central nervous system tumours in adults and imaging is the cornerstone of diagnosis, treatment, and post-treatment follow-up of these patients. With the ...ever-evolving treatment strategies post-treatment imaging and interpretation in glioma remains challenging, more so with the advent of anti-angiogenic drugs and immunotherapy, which can significantly alter the appearance in this setting, thus making interpretation of routine imaging findings such as contrast enhancement, oedema, and mass effect difficult to interpret. This review details the various methods of management of glioma including the upcoming novel therapies and their impact on imaging findings, with a comprehensive description of the imaging findings in conventional and advanced imaging techniques. A systematic appraisal for the existing and emerging techniques of imaging in these settings and their clinical application including various response assessment guidelines and artificial intelligence based response assessment will also be discussed.
•Post treatment imaging of glioma remains a challenging area for radiologists.•Multiparametric MRI is occasionally needed as a problem-solving tool.•Response assessment criteria are available to help standardize interpretation.•AI has shown promising results in assessing treatment response in glioblastoma.
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