Large language models surpass human experts in predicting neuroscience results.

Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts.

Smart laser Sintering: Deep Learning-Powered powder bed fusion 3D printing in precision medicine.

Medicines remain ineffective for over 50% of patients due to conventional mass production methods with fixed drug dosages. Three-dimensional (3D) printing, specifically selective laser sintering (SLS), offers a potential solution to this challenge, allowing the manufacturing of small, personalized batches of medication. Despite its simplicity and suitability for upscaling to large-scale production, SLS was not designed for pharmaceutical manufacturing and necessitates a time-consuming, trial-and-error adaptation process.

Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs.

Due to the huge success and rapid development of convolutional neural networks (CNNs), there is a growing demand for hardware accelerators that accommodate a variety of CNNs to improve their inference latency and energy efficiency, in order to enable their deployment in real-time applications. Among popular platforms, field-programmable gate arrays (FPGAs) have been widely adopted for CNN acceleration because of their capability to provide superior energy efficiency and low-latency processing, while supporting high reconfigurability, making them favorable for accelerating rapidly evolving CNN algorithms. This article introduces a highly customized streaming hardware architecture that focuses on improving the compute efficiency for streaming applications by providing full-stack acceleration of CNNs on FPGAs.

Whole-exome sequencing identifies susceptibility genes and pathways for idiopathic pulmonary fibrosis in the Chinese population.

Genetic factors play a role in the risk of idiopathic pulmonary fibrosis (IPF). Specifically, MUC5B rs35705950 non-risk alleles and immunologic aberrations were associated with the IPF's progression. However, rare genetic variants have not been systematically investigated in Chinese IPF patients.

Relation between sex hormones and leucocyte telomere length in men with idiopathic pulmonary fibrosis.

Background And Objective: IPF is an ageing-related lung disorder featuring progressive lung scarring. IPF patients are frequently identified with short telomeres but coding mutations in telomerase can only explain a minority of cases. Sex hormones regulate telomerase activity in vitro and levels of sex hormones are related to LTL.

Real-world experiences: Efficacy and tolerability of pirfenidone in clinical practice.

Background: The safety of pirfenidone on pulmonary fibrosis patients with other kinds of interstitial lung diseases (ILDs) in addition to idiopathic pulmonary fibrosis (IPF) is unknown. Furthermore, its effectiveness-related factors on IPF patients are not quite explored.

Methods: A retrospective study, on patients prescribed pirfenidone for pulmonary fibrosis, was conducted to assess effectiveness on IPF patients and tolerability of all patients with lung fibrosis.