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New paradigms have been recently proposed in the pathogenesis of both chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF), evidencing surprising similarities between these deadly diseases, despite their obvious clinical, radiological and pathologic differences. There is growing evidence supporting a \"double hit\" pathogenic model where in both COPD and IPF the cumulative action of an accelerated senescence of pulmonary parenchyma (determined by either telomere dysfunction and/or a variety of genetic predisposing factors), and the noxious activity of cigarette smoke-induced oxidative damage are able to severely compromise the regenerative potential of two pulmonary precursor cell compartments (alveolar epithelial precursors in IPF, mesenchymal precursor cells in COPD/emphysema). The consequent divergent derangement of signalling pathways involved in lung tissue renewal (mainly Wnt and Notch), can eventually lead to the distinct abnormal tissue remodelling and functional impairment that characterise the alveolar parenchyma in these diseases (irreversible fibrosis and bronchiolar honeycombing in IPF, emphysema and airway chronic inflammation in COPD).

Human induced pluripotent stem cells (iPSCs) have great potential in research, but pluripotency testing faces challenges due to non-standardized methods and ambiguous markers. Here, we use long-read nanopore transcriptome sequencing to discover 172 genes linked to cell states not covered by current guidelines. We validate 12 genes by qPCR as unique markers for specific cell fates: pluripotency ( CNMD , NANOG , SPP1 ), endoderm ( CER1 , EOMES , GATA6 ), mesoderm ( APLNR , HAND1 , HOXB7 ), and ectoderm ( HES5 , PAMR1 , PAX6 ). Using these genes, we develop a machine learning-based scoring system, “hiPSCore”, trained on 15 iPSC lines and validated on 10 more. hiPSCore accurately classifies pluripotent and differentiated cells and predicts their potential to become specialized 2D cells and 3D organoids. Our re-evaluation of cell fate marker genes identifies key targets for future studies on cell fate assessment. hiPSCore improves iPSC testing by reducing time, subjectivity, and resource use, thus enhancing iPSC quality for scientific and medical applications. Quality control, including pluripotency testing of human iPSCs lacks standardization. Here, authors identify and validate gene markers to develop the machine learning-based hiPSCore to streamline pluripotency testing and elevate iPSC quality.

Traders and investors are interested in accurately predicting cryptocurrency prices to increase returns and minimize risk. However, due to their uncertainty, volatility, and dynamism, forecasting crypto prices is a challenging time series analysis task. Researchers have proposed predictors based on statistical, machine learning (ML), and deep learning (DL) approaches, but the literature is limited. Indeed, it is narrow because it focuses on predicting only the prices of the few most famous cryptos. In addition, it is scattered because it compares different models on different cryptos inconsistently, and it lacks generality because solutions are overly complex and hard to reproduce in practice. The main goal of this paper is to provide a comparison framework that overcomes these limitations. We use this framework to run extensive experiments where we compare the performances of widely used statistical, ML, and DL approaches in the literature for predicting the price of five popular cryptocurrencies, i.e., XRP, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), and Monero (XMR). To the best of our knowledge, we are also the first to propose using the temporal fusion transformer (TFT) on this task. Moreover, we extend our investigation to hybrid models and ensembles to assess whether combining single models boosts prediction accuracy. Our evaluation shows that DL approaches are the best predictors, particularly the LSTM, and this is consistently true across all the cryptos examined. LSTM reaches an average RMSE of 0.0222 and MAE of 0.0173, respectively, 2.7% and 1.7% better than the second-best model. To ensure reproducibility and stimulate future research contribution, we share the dataset and the code of the experiments.

Genetic robustness, or the ability of an organism to maintain fitness in the presence of harmful mutations, can be achieved via protein feedback loops. Previous work has suggested that organisms may also respond to mutations by transcriptional adaptation, a process by which related gene(s) are upregulated independently of protein feedback loops. However, the prevalence of transcriptional adaptation and its underlying molecular mechanisms are unknown. Here, by analysing several models of transcriptional adaptation in zebrafish and mouse, we uncover a requirement for mutant mRNA degradation. Alleles that fail to transcribe the mutated gene do not exhibit transcriptional adaptation, and these alleles give rise to more severe phenotypes than alleles displaying mutant mRNA decay. Transcriptome analysis in alleles displaying mutant mRNA decay reveals the upregulation of a substantial proportion of the genes that exhibit sequence similarity with the mutated gene's mRNA, suggesting a sequence-dependent mechanism. These findings have implications for our understanding of disease-causing mutations, and will help in the design of mutant alleles with minimal transcriptional adaptation-derived compensation. Transcriptional adaptation, a genetic compensation process by which organisms respond to mutations by upregulating related genes, is triggered by mRNA decay and involves a sequence-dependent mechanism.

Arterial hypertension is strongly related to overweight and obesity. In obese subjects, several mechanisms may lead to hypertension such as insulin and leptin resistance, perivascular adipose tissue dysfunction, renal impairment, renin-angiotensin-aldosterone-system activation and sympathetic nervous system activity. Weight loss (WL) seems to have positive effects on blood pressure (BP). The aim of this review was to explain the mechanisms linking obesity and hypertension and to evaluate the main studies assessing the effect of WL on BP. We analysed studies published in the last 10 years (13 studies either interventional or observational) showing the effect of WL on BP. Different WL strategies were taken into account—diet and lifestyle modification, pharmacological intervention and bariatric surgery. Although a positive effect of WL could be identified in each study, the main difference seems to be the magnitude and the durability of BP reduction over time. Nevertheless, further follow-up data are needed: there is still a lack of evidence about long term effects of WL on hypertension. Hence, given the significant results obtained in several recent studies, weight management should always be pursued in obese patients with hypertension.

Gamma-ray bursts (GRBs) are divided into two populations 1 , 2 ; long GRBs that derive from the core collapse of massive stars (for example, ref.  3 ) and short GRBs that form in the merger of two compact objects 4 , 5 . Although it is common to divide the two populations at a gamma-ray duration of 2 s, classification based on duration does not always map to the progenitor. Notably, GRBs with short (≲2 s) spikes of prompt gamma-ray emission followed by prolonged, spectrally softer extended emission (EE-SGRBs) have been suggested to arise from compact object mergers 6 – 8 . Compact object mergers are of great astrophysical importance as the only confirmed site of rapid neutron capture ( r -process) nucleosynthesis, observed in the form of so-called kilonovae 9 – 14 . Here we report the discovery of a possible kilonova associated with the nearby (350 Mpc), minute-duration GRB 211211A. The kilonova implies that the progenitor is a compact object merger, suggesting that GRBs with long, complex light curves can be spawned from merger events. The kilonova of GRB 211211A has a similar luminosity, duration and colour to that which accompanied the gravitational wave (GW)-detected binary neutron star (BNS) merger GW170817 (ref.  4 ). Further searches for GW signals coincident with long GRBs are a promising route for future multi-messenger astronomy. A possible kilonova associated with a nearby, long-duration gamma-ray burst suggests that gamma-ray bursts with long and complex light curves can be spawned from the merger of two compact objects, contrary to the established gamma-ray burst paradigm.

Many of the most highly conserved elements in the human genome are “poison exons,” alternatively spliced exons that contain premature termination codons and permit post-transcriptional regulation of mRNA abundance through induction of nonsense-mediated mRNA decay (NMD). Poison exons are widely assumed to be highly conserved due to their presumed importance for organismal fitness, but this functional importance has never been tested in the context of a whole organism. Here, we report that a poison exon in Smndc1 is conserved across mammals and plants and plays a molecular autoregulatory function in both kingdoms. We generated mouse and A . thaliana models lacking this poison exon to find its loss leads to deregulation of SMNDC1 protein levels, pervasive alterations in mRNA processing, and organismal size restriction. Together, these models demonstrate the importance of poison exons for both molecular and organismal phenotypes that likely explain their extraordinary conservation.

Background/Objectives: Exercise and nutrition may be useful strategies in dynapenic and sarcopenic obesity management, but the identification of treatment modalities aimed at improving this condition is still lacking. We compared the effect of a five-month hypocaloric diet plus resistance training (RT) with and without essential amino acids (EAAs) on body composition, physical performance, and muscle strength among older adults with dynapenic obesity (DO). Methods: Older individuals (n = 48) with DO [(BMI ≥ 30 kg/m2 and/or high waist circumference and low handgrip strength (HGS)] were randomized into two double-blind groups (RT without EAAs vs. RT+EAAs). All participants followed a hypocaloric diet (1 g of proteins/kg spread over three meals) and RT for five months. Pre- and post-intervention assessments included the body composition (DXA), Short Physical Performance Battery (SPPB), HGS, one-repetition maximum (1-RM), and maximal isometric torque with an isokinetic dynamometer. Results: Both groups reduced body mass (RT: −4.66 kg; RT+EAAs: −4.02 kg), waist circumference (RT: −4.66 cm; RT+EAAs: −2.2 cm), total fat mass (RT: −3.81 kg; RT+EAAs: −3.72 kg), and compartmental fat mass with no between-group differences. Both groups improved 1-RM strength (33–47%), isometric torque for body mass (RT: 14.5%; RT+EAAs: 10.6%), and functional performance (chair stand (RT: −3.24 s; RT+EAAs: −1.5 s) and HGS (RT: −2.7 kg; RT+EAAs: 2.9 kg)) with no between-group differences. Conclusions: A moderate hypocaloric diet combined with RT improves body composition and physical function in DO participants, but EAA supplementation did not provide additional benefits.

In the present work a series of design rules are developed in order to tune the morphology of TiO 2 nanoparticles through hydrothermal process. Through a careful experimental design, the influence of relevant process parameters on the synthesis outcome are studied, reaching to the develop predictive models by using Machine Learning methods. The models, after the validation and training, are able to predict with high accuracy the synthesis outcome in terms of nanoparticle size, polydispersity and aspect ratio. Furthermore, they are implemented by reverse engineering approach to do the inverse process, i.e. obtain the optimal synthesis parameters given a specific product characteristic. For the first time, it is presented a synthesis method that allows continuous and precise control of NPs morphology with the possibility to tune the aspect ratio over a large range from 1.4 (perfect truncated bipyramids) to 6 (elongated nanoparticles) and the length from 20 to 140 nm.

Asthma is a common chronic disease characterized by episodic or persistent respiratory symptoms and airflow limitation. Asthma treatment is based on a stepwise and control-based approach that involves an iterative cycle of assessment, adjustment of the treatment and review of the response aimed to minimize symptom burden and risk of exacerbations. Anti-inflammatory treatment is the mainstay of asthma management. In this review we will discuss the rationale and barriers to the treatment of asthma that may result in poor outcomes. The benefits of currently available treatments and the possible strategies to overcome the barriers that limit the achievement of asthma control in real-life conditions and how these led to the GINA 2019 guidelines for asthma treatment and prevention will also be discussed.