LLM Performance Predictors are good initializers for Architecture Search

Large language models (LLMs) have become an integral component in solving a wide range of NLP tasks. In this work, we explore a novel use case of using LLMs to build performance predictors (PP): models that, given a specific deep neural network architecture, predict its performance on a downstream task. We design PP prompts for LLMs consisting of: (i) role: description of the role assigned to the LLM, (ii) instructions: set of instructions to be followed by the LLM to carry out performance prediction, (iii) hyperparameters: a definition of each architecture-specific hyperparameter and (iv) demonstrations: sample architectures along with their efficiency metrics and 'training from scratch' performance. For machine translation (MT) tasks, we discover that GPT-4 with our PP prompts (LLM-PP) can predict the performance of architecture with a mean absolute error matching the SOTA and a marginal degradation in rank correlation coefficient compared to SOTA performance predictors. Further, we show that the predictions from LLM-PP can be distilled to a small regression model (LLM-Distill-PP). LLM-Distill-PP models surprisingly retain the performance of LLM-PP largely and can be a cost-effective alternative for heavy use cases of performance estimation. Specifically, for neural architecture search (NAS), we propose a Hybrid-Search algorithm for NAS (HS-NAS), which uses LLM-Distill-PP for the initial part of search, resorting to the baseline predictor for rest of the search. We show that HS-NAS performs very similar to SOTA NAS across benchmarks, reduces search hours by 50% roughly, and in some cases, improves latency, GFLOPs, and model size

Leukocyte-specific protein 1 interacts with DC-SIGN and mediates transport of HIV to the proteasome in dendritic cells

Dendritic cells (DCs) capture and internalize human immunodeficiency virus (HIV)-1 through C-type lectins, including DC-SIGN. These cells mediate efficient infection of T cells by concentrating the delivery of virus through the infectious synapse, a process dependent on the cytoplasmic domain of DC-SIGN. Here, we identify a cellular protein that binds specifically to the cytoplasmic region of DC-SIGN and directs internalized virus to the proteasome. This cellular protein, leukocyte-specific protein 1 (LSP1), was defined biochemically by immunoprecipitation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. LSP1 is an F-actin binding protein involved in leukocyte motility and found on the cytoplasmic surface of the plasma membrane. LSP1 interacted specifically with DC-SIGN and other C-type lectins, but not the inactive mutant DC-SIGNΔ35, which lacks a cytoplasmic domain and shows altered virus transport in DCs. LSP1 diverts HIV-1 to the proteasome. Down-regulation of LSP1 with specific small interfering RNAs in human DCs enhanced HIV-1 transfer to T cells, and bone marrow DCs from lsp1−/− mice also showed an increase in transfer of HIV-1BaL to a human T cell line. Proteasome inhibitors increased retention of viral proteins in lsp1+/+ DCs, and substantial colocalization of virus to the proteasome was observed in wild-type compared with LSP1-deficient cells. Collectively, these data suggest that LSP1 protein facilitates virus transport into the proteasome after its interaction with DC-SIGN through its interaction with cytoskeletal proteins

Small Character Models Match Large Word Models for Autocomplete Under Memory Constraints

Autocomplete is a task where the user inputs a piece of text, termed prompt, which is conditioned by the model to generate semantically coherent continuation. Existing works for this task have primarily focused on datasets (e.g., email, chat) with high frequency user prompt patterns (or focused prompts) where word-based language models have been quite effective. In this work, we study the more challenging setting consisting of low frequency user prompt patterns (or broad prompts, e.g., prompt about 93rd academy awards) and demonstrate the effectiveness of character-based language models. We study this problem under memory-constrained settings (e.g., edge devices and smartphones), where character-based representation is effective in reducing the overall model size (in terms of parameters). We use WikiText-103 benchmark to simulate broad prompts and demonstrate that character models rival word models in exact match accuracy for the autocomplete task, when controlled for the model size. For instance, we show that a 20M parameter character model performs similar to an 80M parameter word model in the vanilla setting. We further propose novel methods to improve character models by incorporating inductive bias in the form of compositional information and representation transfer from large word models

A novel role for XIAP in copper homeostasis through regulation of MURR1

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102131/1/emboj7600031.pd

Allopurinol and blood pressure variability following ischemic stroke and transient ischemic attack:a secondary analysis of XILO-FIST

Blood Pressure Variability (BPV) is associated with cardiovascular risk and serum uric acid level. We investigated whether BPV was lowered by allopurinol and whether it was related to neuroimaging markers of cerebral small vessel disease (CSVD) and cognition. We used data from a randomised, double-blind, placebo-controlled trial of two years allopurinol treatment after recent ischemic stroke or transient ischemic attack. Visit-to-visit BPV was assessed using brachial blood pressure (BP) recordings. Short-term BPV was assessed using ambulatory BP monitoring (ABPM) performed at 4 weeks and 2 years. Brain MRI was performed at baseline and 2 years. BPV measures were compared between the allopurinol and placebo groups, and with CSVD and cognition. 409 participants (205 allopurinol; 204 placebo) were included in the visit-to-visit BPV analyses. There were no significant differences found between placebo and allopurinol groups for any measure of visit-to-visit BPV. 196 participants were included in analyses of short-term BPV at week 4. Two measures were reduced by allopurinol: the standard deviation (SD) of systolic BP (by 1.30 mmHg (95% confidence interval (CI) 0.18-2.42, p = 0.023)); and the average real variability (ARV) of systolic BP (by 1.31 mmHg (95% CI 0.31-2.32, p = 0.011)). There were no differences in other measures at week 4 or in any measure at 2 years, and BPV was not associated with CSVD or cognition. Allopurinol treatment did not affect visit-to-visit BPV in people with recent ischemic stroke or TIA. Two BPV measures were reduced at week 4 by allopurinol but not at 2 years.</p

Xanthine oxidase inhibition and white matter hyperintensity progression following ischaemic stroke and transient ischaemic attack (XILO-FIST): a multicentre, double-blinded, randomised, placebo-controlled trial

Background: People who experience an ischaemic stroke are at risk of recurrent vascular events, progression of cerebrovascular disease, and cognitive decline. We assessed whether allopurinol, a xanthine oxidase inhibitor, reduced white matter hyperintensity (WMH) progression and blood pressure (BP) following ischaemic stroke or transient ischaemic attack (TIA). Methods: In this multicentre, prospective, randomised, double-blinded, placebo-controlled trial conducted in 22 stroke units in the United Kingdom, we randomly assigned participants within 30-days of ischaemic stroke or TIA to receive oral allopurinol 300 mg twice daily or placebo for 104 weeks. All participants had brain MRI performed at baseline and week 104 and ambulatory blood pressure monitoring at baseline, week 4 and week 104. The primary outcome was the WMH Rotterdam Progression Score (RPS) at week 104. Analyses were by intention to treat. Participants who received at least one dose of allopurinol or placebo were included in the safety analysis. This trial is registered with ClinicalTrials.gov, NCT02122718. Findings: Between 25th May 2015 and the 29th November 2018, 464 participants were enrolled (232 per group). A total of 372 (189 with placebo and 183 with allopurinol) attended for week 104 MRI and were included in analysis of the primary outcome. The RPS at week 104 was 1.3 (SD 1.8) with allopurinol and 1.5 (SD 1.9) with placebo (between group difference −0.17, 95% CI −0.52 to 0.17, p = 0.33). Serious adverse events were reported in 73 (32%) participants with allopurinol and in 64 (28%) with placebo. There was one potentially treatment related death in the allopurinol group. Interpretation: Allopurinol use did not reduce WMH progression in people with recent ischaemic stroke or TIA and is unlikely to reduce the risk of stroke in unselected people. Funding: The British Heart Foundation and the UK Stroke Association

Aging and Immune System: An Overview

&nbsp;The world is seeing a quick segment move towards a more established populace, a pattern with significant clinical, social, monetary and political ramifications. Maturing is a multifaceted procedure, including various sub-atomic and cell components with regards to various organ frameworks. A urgent part of maturing is a lot of useful and auxiliary adjustments in the invulnerable framework that can show as a diminished capacity to battle contamination, lessened reaction to inoculation, increased incidence of cancer, higher prevalence of autoimmunity and constitutive low- grade inflammation, among others. In addition to cell-intrinsic changes in both innate and adaptive immune cells, alteration in the stromal microenvironment in primary and secondary lymphoid organs plays an important role in age-associated immune dysfunction. This review will provide a broad overview of these phenomena and point out some of their clinical and therapeutic implications. This review study setting, discussing the gradual aging immune system. Data for this study is collected from different search engines like PubMed, Google Scholar, MeSH, Semantic scholar, Cochrane, NCBI, Medline, core science. A total of 53 articles were selected. The aging of the immune system is associated with dramatic changes in the distribution and competence of immune cells. Anti-Aging therapy should aim at prolonging T cells’ survival while weakening inflammation prone to innate immunity