Phosphorylation of the Arp2 subunit relieves auto-inhibitory interactions for Arp2/3 complex activation.

Actin filament assembly by the actin-related protein (Arp) 2/3 complex is necessary to build many cellular structures, including lamellipodia at the leading edge of motile cells and phagocytic cups, and to move endosomes and intracellular pathogens. The crucial role of the Arp2/3 complex in cellular processes requires precise spatiotemporal regulation of its activity. While binding of nucleation-promoting factors (NPFs) has long been considered essential to Arp2/3 complex activity, we recently showed that phosphorylation of the Arp2 subunit is also necessary for Arp2/3 complex activation. Using molecular dynamics simulations and biochemical assays with recombinant Arp2/3 complex, we now show how phosphorylation of Arp2 induces conformational changes permitting activation. The simulations suggest that phosphorylation causes reorientation of Arp2 relative to Arp3 by destabilizing a network of salt-bridge interactions at the interface of the Arp2, Arp3, and ARPC4 subunits. Simulations also suggest a gain-of-function ARPC4 mutant that we show experimentally to have substantial activity in the absence of NPFs. We propose a model in which a network of auto-inhibitory salt-bridge interactions holds the Arp2 subunit in an inactive orientation. These auto-inhibitory interactions are destabilized upon phosphorylation of Arp2, allowing Arp2 to reorient to an activation-competent state

Learning topological operations on meshes with application to block decomposition of polygons

We present a learning based framework for mesh quality improvement on unstructured triangular and quadrilateral meshes. Our model learns to improve mesh quality according to a prescribed objective function purely via self-play reinforcement learning with no prior heuristics. The actions performed on the mesh are standard local and global element operations. The goal is to minimize the deviation of the node degrees from their ideal values, which in the case of interior vertices leads to a minimization of irregular nodes.Comment: Submitted to Computer-Aided Design Journal. Presented at 17th US National Conference on Computational Mechanics, Albuquerque, N

RecXplainer: Post-Hoc Attribute-Based Explanations for Recommender Systems

Recommender systems are ubiquitous in most of our interactions in the current digital world. Whether shopping for clothes, scrolling YouTube for exciting videos, or searching for restaurants in a new city, the recommender systems at the back-end power these services. Most large-scale recommender systems are huge models trained on extensive datasets and are black-boxes to both their developers and end-users. Prior research has shown that providing recommendations along with their reason enhances trust, scrutability, and persuasiveness of the recommender systems. Recent literature in explainability has been inundated with works proposing several algorithms to this end. Most of these works provide item-style explanations, i.e., `We recommend item A because you bought item B.' We propose a novel approach, RecXplainer, to generate more fine-grained explanations based on the user's preference over the attributes of the recommended items. We perform experiments using real-world datasets and demonstrate the efficacy of RecXplainer in capturing users' preferences and using them to explain recommendations. We also propose ten new evaluation metrics and compare RecXplainer to six baseline methods.Comment: Awarded the Best Student Paper at TEA Workshop at NeurIPS 2022. 13 page

Face Recognition for Fast Information Retrieval and Record Lookup

This publication describes systems and techniques directed to taking a red, green and blue (RGB) image of a customer’s face, identifying landmarks on the face, creating a face box region, thumbnailing the face box region, sending the thumbnail to a face recognition model where face data is embedded into a vector, and using the vector in a multi-dimensional tree searching algorithm to quickly look up or retrieve information or a record relating to the customer in a database. The face image capture may be performed using standard RGB camera technology to enable broad, cost-effective business adoption. Two-factor authentication may be employed to address potential RGB image spoofing. Embedding the vector may be implemented on local technology to minimize network data transmissions of face images and increase lookup speed

PHYSICOCHEMICAL CHARACTERISTICS OF RASAMANIKYA-AN AYURVEDIC ARSENICAL FORMULATION

Objective: The objective of this study was standardization and Chemical characterization of rasamanikya prepared as per standard operating procedures (SOP) mentioned in the classical text. Methods: Rasamanikya was prepared by putting churnodaka shodhita haratala (Orpiment-As2S3) between two abhraka (white mica) sheets which are heated for a while to obtain a red colored finished product. The Ayurvedic specifications for the analysis of rasamanikya were performed through qualitative and quantitative analysis. Physicochemical analysis, assay of elements by atomic absorption spectrometer (AAS) and inductively coupled plasma-atomic emission spectrometry (ICP-AES) were carried out and some other tests such as x-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS) and energy dispersive x-ray analyzer (EDAX) were also performed to ensure the quality of the drug. Results: In the finished drug Arsenic and Sulphur are present in the form of As4S4, As2S3, As2S5. On the basis of XPS survey scans, scanning electron microscopy-energy dispersive x-ray analyzer (SEM-EDAX) and carbon, hydrogen, nitrogen, sulphur (CHNS) analysis the Arsenic to Sulphur (As to S) ratio is thus standardized as 39-47: 53-61. In addition to this powder, XRD shows a major conversion into an amorphous phase. Conclusion: The results could be used to lay down a new set of pharmacopoeial standards for the preparation of rasamanikya for getting optimal efficacy of medicine. Therefore, the information will help the Scientists and Researchers to build comprehensive standards, to screen the compounds responsible for different bioactivities, and to elucidate the molecular mechanism of action

Magnetotransport properties of individual InAs nanowires

We probe the magnetotransport properties of individual InAs nanowires in a field effect transistor geometry. In the low magnetic field regime we observe magnetoresistance that is well described by the weak localization (WL) description in diffusive conductors. The weak localization correction is modified to weak anti-localization (WAL) as the gate voltage is increased. We show that the gate voltage can be used to tune the phase coherence length ($l_\phi$) and spin-orbit length ($l_{so}$) by a factor of $\sim$ 2. In the high field and low temperature regime we observe the mobility of devices can be modified significantly as a function of magnetic field. We argue that the role of skipping orbits and the nature of surface scattering is essential in understanding high field magnetotransport in nanowires

A first order phase transition mechanism underlies protein aggregation in mammalian cells

The formation of misfolded protein aggregates is a hallmark of neurodegenerative diseases. The aggregate formation process exhibits an initial lag phase when precursor clusters spontaneously assemble. However, most experimental assays are blind to this lag phase. We develop a quantitative assay based on super-resolution imaging in fixed cells and light sheet imaging of living cells to study the early steps of aggregation in mammalian cells. We find that even under normal growth conditions mammalian cells have precursor clusters. The cluster size distribution is precisely that expected for a so-called super-saturated system in first order phase transition. This means there exists a nucleation barrier, and a critical size above which clusters grow and mature. Homeostasis is maintained through a Szilard model entailing the preferential clearance of super-critical clusters. We uncover a role for a putative chaperone (RuvBL) in this disassembly of large clusters. The results indicate early aggregates behave like condensates