Role of Amyloidogenic and Non-Amyloidogenic Protein Spaces in Neurodegenerative Diseases and their Mitigation Using Theranostic Agents.

Neurodegenerative diseases (NDDs) refer to a complex heterogeneous group of diseases which are associated with the accumulation of amyloid fibrils or plaques in the brain leading to progressive loss of neuronal functions. Alzheimer's disease is one of the major NDD responsible for 60-80 % of all dementia cases. Currently, there are no curative or disease-reversing/modifying molecules for many of the NDDs except a few such as donepezil, rivastigmine, galantamine, carbidopa and levodopa which treat the disease-associated symptoms. Similarly, there are very few FDA-approved tracers such as flortaucipir (Tauvid) for tau fibril imaging and florbetaben (Neuraceq), flutemetamol (Vizamyl), and florbetapir (Amyvid) for amyloid imaging available for diagnosis. Recent advances in the cryogenic electron microscopy reported distinctly different microstructures for tau fibrils associated with different tauopathies highlighting the possibility to develop tauopathy-specific imaging agents and therapeutics. In addition, it is important to identify the proteins that are associated with disease development and progression to know about their 3D structure to develop various diagnostics, therapeutics and theranostic agents. The current article discusses in detail the disease-associated amyloid and non-amyloid proteins along with their structural insights. We comprehensively discussed various novel proteins associated with NDDs and their implications in disease pathology. In addition, we document various emerging chemical compounds developed for diagnosis and therapy of different NDDs with special emphasis on theranostic agents for better management of NDDs.

Gate-Tunable Anomalous Hall Effect in a 3D Topological Insulator/2D Magnet van der Waals Heterostructure.

We demonstrate advantages of samples made by mechanical stacking of exfoliated van der Waals materials for controlling the topological surface state of a three-dimensional topological insulator (TI) via interaction with an adjacent magnet layer. We assemble bilayers with pristine interfaces using exfoliated flakes of the TI BiSbTeSe2 and the magnet Cr2Ge2Te6, thereby avoiding problems caused by interdiffusion that can affect interfaces made by top-down deposition methods. The samples exhibit an anomalous Hall effect (AHE) with abrupt hysteretic switching. For the first time in samples composed of a TI and a separate ferromagnetic layer, we demonstrate that the amplitude of the AHE can be tuned via gate voltage with a strong peak near the Dirac point. This is the signature expected for the AHE due to Berry curvature associated with an exchange gap induced by interaction between the topological surface state and an out-of-plane-oriented magnet.

Manipulation of the van der Waals Magnet Cr2Ge2Te6 by Spin-Orbit Torques.

We report measurements of current-induced thermoelectric and spin-orbit torque effects within devices in which multilayers of the semiconducting two-dimensional van der Waals magnet Cr2Ge2Te6 (CGT) are integrated with Pt and Ta metal overlayers. We show that the magnetic orientation of the CGT can be detected accurately either electrically (using an anomalous Hall effect) or optically (using magnetic circular dichroism) with good consistency. The samples exhibit large thermoelectric effects, but nevertheless, the spin-orbit torque can be measured quantitatively using the angle-dependent second harmonic Hall technique. For CGT/Pt, we measure the spin-orbit torque efficiency to be similar to conventional metallic-ferromagnet/Pt devices with the same Pt resistivity. The interfacial transparency for spin currents is therefore similar in both classes of devices. Our results demonstrate the promise of incorporating semiconducting 2D magnets within spin-orbitronic and magneto-thermal devices.

Sequential one-pot synthesis of bis(indolyl)glyoxylamides: Evaluation of antibacterial and anticancer activities.

A series of bis(indolyl)glyoxylamides 10a-n has been designed and synthesized. In situ generated indole-3-glyoxalylchloride from the reaction of readily available indole 9 with oxalyl chloride was treated with tryptamine to produce bis(indolyl)glyoxylamides 10a-n in 82-93% yields. All the synthesized bis(indolyl)glyoxylamides were well characterized and tested for their antibacterial activity against Gram-positive and Gram-negative bacterial strains. Compounds 10d, 10g and 10i were found to display potent antibacterial activity against Gram-negative strain. Further, the cytotoxicity of bis(indolyl)glyoxylamides 10a-n were evaluated against a panel of human cancer cell lines. Of the screened analogues, compound 10f (IC50=22.34µM; HeLa, 24.05µM; PC-3, 21.13µM; MDA-MB-231 and 29.94µM; BxPC-3) was identified as the most potent analogue of the series. Exposure of PC-3 cells to either 10a or 10f resulted in increased levels of cleaved PARP1, indicating that bis(indolyl)glyoxylamides induce apoptosis in PC-3 cells. Most importantly, compounds 10d, 10g and 10i were completely ineffective in mammalian cells, suggesting that they target bacterial-specific targets and thus will not display any toxicity in host cells.

Reflection and transmission of plane waves from a fluid-porous piezoelectric solid interface.

The reflection and transmission of plane waves from a fluid-porous piezoelectric solid interface is studied. The porous piezoelectric solid, having 6 mm symmetry, is supposed to be filled with viscous fluid. The expressions for amplitude ratios and energy ratios corresponding to reflected wave and transmitted waves are derived analytically. The Christoffel equation of a leaky wave propagating along the surface of a porous piezoelectric solid is derived. The effects of the angle of incidence, frequency, porosity, piezoelectric interaction, and anisotropy on the reflected and transmitted energy ratios are studied numerically for a particular model BaTiO(3). The porous piezoelectric solid half space is assumed to be loaded with water. The effects of porosity and frequency on the leaky wave velocity are also studied.

Development and Assessment of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices.

Importance: Most dermatologic cases are initially evaluated by nondermatologists such as primary care physicians (PCPs) or nurse practitioners (NPs). Objective: To evaluate an artificial intelligence (AI)-based tool that assists with diagnoses of dermatologic conditions. Design, Setting, and Participants: This multiple-reader, multiple-case diagnostic study developed an AI-based tool and evaluated its utility. Primary care physicians and NPs retrospectively reviewed an enriched set of cases representing 120 different skin conditions. Randomization was used to ensure each clinician reviewed each case either with or without AI assistance; each clinician alternated between batches of 50 cases in each modality. The reviews occurred from February 21 to April 28, 2020. Data were analyzed from May 26, 2020, to January 27, 2021. Exposures: An AI-based assistive tool for interpreting clinical images and associated medical history. Main Outcomes and Measures: The primary analysis evaluated agreement with reference diagnoses provided by a panel of 3 dermatologists for PCPs and NPs. Secondary analyses included diagnostic accuracy for biopsy-confirmed cases, biopsy and referral rates, review time, and diagnostic confidence. Results: Forty board-certified clinicians, including 20 PCPs (14 women [70.0%]; mean experience, 11.3 [range, 2-32] years) and 20 NPs (18 women [90.0%]; mean experience, 13.1 [range, 2-34] years) reviewed 1048 retrospective cases (672 female [64.2%]; median age, 43 [interquartile range, 30-56] years; 41 920 total reviews) from a teledermatology practice serving 11 sites and provided 0 to 5 differential diagnoses per case (mean [SD], 1.6 [0.7]). The PCPs were located across 12 states, and the NPs practiced in primary care without physician supervision across 9 states. The NPs had a mean of 13.1 (range, 2-34) years of experience and practiced in primary care without physician supervision across 9 states. Artificial intelligence assistance was significantly associated with higher agreement with reference diagnoses. For PCPs, the increase in diagnostic agreement was 10% (95% CI, 8%-11%; P < .001), from 48% to 58%; for NPs, the increase was 12% (95% CI, 10%-14%; P < .001), from 46% to 58%. In secondary analyses, agreement with biopsy-obtained diagnosis categories of maglignant, precancerous, or benign increased by 3% (95% CI, -1% to 7%) for PCPs and by 8% (95% CI, 3%-13%) for NPs. Rates of desire for biopsies decreased by 1% (95% CI, 0-3%) for PCPs and 2% (95% CI, 1%-3%) for NPs; the rate of desire for referrals decreased by 3% (95% CI, 1%-4%) for PCPs and NPs. Diagnostic agreement on cases not indicated for a dermatologist referral increased by 10% (95% CI, 8%-12%) for PCPs and 12% (95% CI, 10%-14%) for NPs, and median review time increased slightly by 5 (95% CI, 0-8) seconds for PCPs and 7 (95% CI, 5-10) seconds for NPs per case. Conclusions and Relevance: Artificial intelligence assistance was associated with improved diagnoses by PCPs and NPs for 1 in every 8 to 10 cases, indicating potential for improving the quality of dermatologic care.

A deep learning system for differential diagnosis of skin diseases.

Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of skin conditions using 16,114 de-identified cases (photographs and clinical data) from a teledermatology practice serving 17 sites. The DLS distinguishes between 26 common skin conditions, representing 80% of cases seen in primary care, while also providing a secondary prediction covering 419 skin conditions. On 963 validation cases, where a rotating panel of three board-certified dermatologists defined the reference standard, the DLS was non-inferior to six other dermatologists and superior to six primary care physicians (PCPs) and six nurse practitioners (NPs) (top-1 accuracy: 0.66 DLS, 0.63 dermatologists, 0.44 PCPs and 0.40 NPs). These results highlight the potential of the DLS to assist general practitioners in diagnosing skin conditions.

Ultrasonic wave's interaction at fluid-porous piezoelectric layered interface.

The complete description of acoustic propagation in a multilayered system is of great interest in a variety of applications such as non-destructive evaluation and acoustic design and there is need for a flexible model that can describe the reflection and transmission of ultrasonic waves in these media. The reflection and transmission of ultrasonic waves from a fluid loaded porous piezoelectric layered structure is studied analytically. The layered structure is considered to be consisting of n number of layers of porous piezoelectric materials. Transfer matrix technique is used to study the layered materials. The analytical expressions for the reflected, transmitted, interaction energy ratios and surface impedance are obtained. The effects of frequency, porosity, angle of incidence, layer thickness and number of layers on the energy ratios and surface impedance are studied for different configurations of the layered materials. The results obtained are deduced for the poro-elastic and fluid loaded porous piezoelectric half space case, which are in agreement with earlier established results. A comparison of the results, obtained by alternate numerical techniques, is made.