Alzheimer’s And Parkinson’s Disease Classification Using Deep Learning Based On MRI: A Review

Neurodegenerative disorders present a current challenge for accurate diagnosis and for providing precise prognostic information. Alzheimer’s disease (AD) and Parkinson's disease (PD), may take several years to obtain a definitive diagnosis. Due to the increased aging population in developed countries, neurodegenerative diseases such as AD and PD have become more prevalent and thus new technologies and more accurate tests are needed to improve and accelerate the diagnostic procedure in the early stages of these diseases. Deep learning has shown significant promise in computer-assisted AD and PD diagnosis based on MRI with the widespread use of artificial intelligence in the medical domain. This article analyses and evaluates the effectiveness of existing Deep learning (DL)-based approaches to identify neurological illnesses using MRI data obtained using various modalities, including functional and structural MRI. Several current research issues are identified toward the conclusion, along with several potential future study directions

A Tale of Two Transients: GW 170104 and GRB 170105A

We present multi-wavelength follow-up campaigns by the AstroSat CZTI and GROWTH collaborations in search of an electromagnetic counterpart to the gravitational wave event GW 170104. At the time of the GW 170104 trigger, the AstroSat CZTI field of view covered 50.3% of the sky localization. We do not detect any hard X-ray (>100 keV) signal at this time, and place an upper limit of $\approx 4.5\times {10}^{-7}\,\mathrm{erg}\,{\mathrm{cm}}^{-2}\,{{\rm{s}}}^{-1}$, for a 1 s timescale. Separately, the ATLAS survey reported a rapidly fading optical source dubbed ATLAS17aeu in the error circle of GW 170104. Our panchromatic investigation of ATLAS17aeu shows that it is the afterglow of an unrelated long, soft GRB 170105A, with only a fortuitous spatial coincidence with GW 170104. We then discuss the properties of this transient in the context of standard long GRB afterglow models

Development and comparative evaluation of two antigen detection tests for Visceral Leishmaniasis

Background: Visceral leishmaniasis (VL) can be fatal without timely diagnosis and treatment. Treatment efficacies vary due to drug resistance, drug toxicity and co-morbidities. It is important to monitor treatment responsiveness to confirm cure and curtail relapse. Currently, microscopy of spleen, bone marrow or lymph node biopsies is the only definitive method to evaluate cure. A less invasive test for treatment success is a high priority for VL management. Methods: In this study, we describe the development of a capture ELISA based on detecting Leishmania donovani antigens in urine samples and comparison with the Leishmania Antigen ELISA, also developed for the same purpose. Both were developed as prototype kits and tested on patient urine samples from Sudan, Ethiopia, Bangladesh and Brazil, along with appropriate control samples from endemic and non-endemic regions. Sensitivity and specificity were assessed based on accurate detection of patients compared to control samples. One- Way ANOVA was used to assess the discrimination capacity of the tests and Cohen’s kappa was used to assess their correlation. Results: The Leishmania Antigen Detect™ ELISA demonstrated >90 % sensitivity on VL patient samples from Sudan, Bangladesh and Ethiopia and 88 % on samples from Brazil. The Leishmania Antigen ELISA was comparable in performance except for lower sensitivity on Sudanese samples. Both were highly specific. To confirm utility in monitoring treatment, urine samples were collected from VL patients at days 0, 30 and 180 post- treatment. For the Leishmania Antigen Detect™ ELISA, positivity was high at day 0 at 95 %, falling to 21 % at day 30. At day 180, all samples were negative, corresponding well with clinical cure. A similar trend was also seen for the Leishmania Antigen ELISA albeit; with lower positivity of 91 % at Day 0 and more patients, remaining positive at Days 30 and 180. Discussion: The Leishmania Antigen Detect™ and the Leishmania Antigen ELISAs are standardized, user- friendly, quantitative and direct tests to detect Leishmania during acute VL as well as to monitor parasite clearance during treatment. They are a clear improvement over existing options. Conclusion: The ELISAs provide a non-invasive method to detect parasite antigens during acute infection and monitor its clearance upon cure, filling an unmet need in VL management. Further refinement of the tests with more samples from endemic regions will define their utility in monitoring treatment