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. The objective of this study was to explore whether sex hormones were associated with LTL, whether they interacted with genetic variants in telomerase and whether polymorphisms in the exon of androgen metabolism genes were associated with plasma testosterone concentrations in male IPF patients. METHODS: A case-control study was performed on 101 male IPF subjects and 51 age-matched healthy controls. Early morning plasma sex hormones were quantified, and whole-exome sequencing was used to identify rare protein-altering variants of telomerase and SNP in the exon of androgen metabolism genes. LTL was analysed by PCR and expressed as a T/S ratio. RESULTS: LTL, testosterone and DHT were decreased significantly in the IPF group. After adjustments for age and variant status in telomerase-related genes, only testosterone was positively associated with LTL (P = 0.001). No significant interaction (P = 0.661) was observed between rare protein-altering variants of telomerase and testosterone. No coding SNP in androgen metabolism genes were significantly associated with testosterone concentrations. CONCLUSION: Plasma testosterone is associated with LTL independent of age or rare protein-altering variants of telomerase. No genetic variations of androgen-related pathway genes are associated with androgen concentrations. Further studies are warranted to examine whether hormonal interventions might retard telomere loss in male IPF patients.

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. In response, this study introduces a deep learning model trained on a variety of features to identify the best feature set to represent drugs and polymeric materials for the prediction of the printability of drug-loaded formulations using SLS. The proposed model demonstrates success by achieving 90% accuracy in predicting printability. Furthermore, explainability analysis unveils materials that facilitate SLS printability, offering invaluable insights for scientists to optimize SLS formulations, which can be expanded to other disciplines. This represents the first study in the field to develop an interpretable, uncertainty-optimized deep learning model for predicting the printability of drug-loaded formulations. This paves the way for accelerating formulation development, propelling us into a future of personalized medicine with unprecedented manufacturing precision.

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. The proposed accelerator maps most computational functions, that is, convolutional and deconvolutional layers into a singular unified module, and implements the residual and concatenative connections between the functions with high efficiency, to support the inference of mainstream CNNs with different topologies. This architecture is further optimized through exploiting different levels of parallelism, layer fusion, and fully leveraging digital signal processing blocks (DSPs). The proposed accelerator has been implemented on Intel's Arria 10 GX1150 hardware and evaluated with a wide range of benchmark models. The results demonstrate a high performance of over 1.3 TOP/s of throughput, up to 97% of compute [multiply-accumulate (MAC)] efficiency, which outperforms the state-of-the-art FPGA accelerators.

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. In this study, we aimed to improve understanding of the genetic architecture of IPF in the Chinese population and to assess whether rare protein-coding variants in the immunity pathway genes are enriched in the IPF patients with non-risk alleles at rs35705950. A case-control exome-wide study including 110 IPF patients and 60 matched healthy controls was conducted. rs35705950 was genotyped by Sanger sequencing. To identify genes enriched in IPF, gene-based association analyses were performed. Identified genes were included for further pathway analyses using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Associations between rs35705950 and genes enriched in the immunity pathway were also tested. 226 genes that were enriched with deleterious variants were identified in IPF patients. Out of them, 36 genes were significantly enriched in GO and KEGG pathways in the IPF. Pathway analyses implicated that these genes were involved in the immune response and cell adhesion. Rare protein-altering variants in genes related to the immunity pathway did not significantly differ between patients with a MUC5B risk allele and individuals without risk allele. We drafted a comprehensive mutational landscape of rare protein-coding variants in the Chinese IPF and identified genes related to immune response and cell adhesion. These results partially explain changes in gene expression involved in the immunity/inflammatory pathways in IPF patients.

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. The effectiveness of pirfenidone was tested on 110 IPF subjects receiving treatment for ≥3 months by high-resolution computed tomography (HRCT). Response-linked factors and progression-free survival (PFS) were also analyzed. The data about safety outcomes and drug dose adjustments were collected from all included subjects. RESULTS: A total of 176 subjects were included: 117 were IPF, 19 connective tissue disease-associated interstitial lung disease (CTD-ILD), and 40 unclassifiable ILD. Out of the 110 IPF subjects, 89 subjects were assessed as stable and 21 as progressive, out of which 10 died of acute exacerbation and 11 progressed. The effectiveness was significantly related to their baseline body mass index (BMI). IPF subjects with BMI>25kg/m2 or diffusion capacity of carbon monoxide (DLco)>30% had higher PFS rate. The most common adverse events were skin-related and gastrointestinal-related. Drug discontinuation owing to adverse events occurred similarly in these three groups. CONCLUSION: Pirfenidone was well tolerated in most of the lung fibrosis patients besides IPF, with a similar pattern of adverse events. Nearly 80% of IPF subjects were assessed as stable. More benefits were seen in IPF patients with higher BMI or mild-to-moderate disease.