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Traditional systems for indoor pressure sensing and human activity recognition (HAR) rely on costly, high-resolution mats and computationally intensive neural network-based (NN-based) models that are prone to noise. In contrast, we design a cost-effective and noise-resilient pressure mat system for HAR, leveraging Velostat for intelligent pressure sensing and a novel hyperdimensional computing (HDC) classifier that is lightweight and highly noise resilient. To measure the performance of our system, we collected two datasets, capturing the static and continuous nature of human movements. Our HDC-based classification algorithm shows an accuracy of 93.19%, improving the accuracy by 9.47% over state-of-the-art CNNs, along with an 85% reduction in energy consumption. We propose a new HDC noise-resilient algorithm and analyze the performance of our proposed method in the presence of three different kinds of noise, including memory and communication, input, and sensor noise. Our system is more resilient across all three noise types. Specifically, in the presence of Gaussian noise, we achieve an accuracy of 92.15% (97.51% for static data), representing a 13.19% (8.77%) improvement compared to state-of-the-art CNNs.

Background: Adverse atherogenic lipid profile is associated with an increased risk of major adverse cardiac events in patients after acute coronary syndrome (ACS). Knowledge regarding the impact of statins on lipid profile remains limited. Methods: We retrospectively analysed multicenter, real-world data from the Chinese Cardiovascular Association Database-iHeart Project. Patients with a primary diagnosis of ACS from 2014 to 2021 during index hospitalisation and having at least one lipid panel record after discharge within 12 months were enrolled. We analysed target achievement of atherogenic lipid profile, including apolipoprotein B (< 80 mg/dL), low-density lipoprotein cholesterol (LDL-C) (< 1.8 mmol/L), lipoprotein(a) [Lp(a)] (< 30 mg/dL), triglycerides (< 1.7 mmol/L), remnant cholesterol (RC) (< 0.78 mmol/L), non-high-density lipoprotein cholesterol (< 2.6 mmol/L) at baseline and follow-up. Multivariate Cox regression models were employed to investigate the association between patient characteristics and target achievement. Results: Among 4861 patients, the mean age was 64.9 years. Only 7.8% of patients had all atherogenic lipids within the target range at follow-up. The proportion of target achievement was for LDL-C 42.7%, Lp(a) 73.3%, and RC 78.5%. Patients with female sex, younger age, myocardial infarction, hypertension, and hypercholesteremia were less likely to control LDL-C, Lp(a), and RC. An increase in the burden of comorbidities was negatively associated with LDL-C and Lp(a) achievements but not with RC. Conclusions: A substantial gap exists between lipid control and the targets recommended by contemporary guidelines. Novel therapeutics targeting the whole atherogenic lipid profile will be warranted to improve cardiovascular outcomes. What is known? 1. Long-term prognosis of ACS remains challenging, underlining the need for optimisation of secondary prevention in these patients. 2. In addition to LDL-C, the residual lipid risk attributed to other atherogenic lipids is associated with increased risk after ACS. What the study adds? 1. Only 7.8% of patients had all atherogenic lipids, including LDL-C, TG, ApoB, Lp(a), RC, and non-HDL-C, within the target range. 2. At follow-up, the proportions of the overall population and the very high-risk patients with LDL-C in the target range were 42.7% and 17.5%, respectively. 3. Patients with female sex, younger age, and comorbidities such as myocardial infarction, hypertension, and hypercholesterolemia were less likely to control their lipids. [ABSTRACT FROM AUTHOR]

Extended reality (XR) is an immersive technology widely applied in various fields. Due to the real-time interaction required between users and virtual environments, XR applications are highly sensitive to latency. Furthermore, handling computationally intensive tasks on wireless XR devices leads to energy consumption, which is a critical performance constraint for XR applications. It has been noted that the XR task can be decoupled to several subtasks with mixed serial–parallel relationships. Furthermore, the evaluation of XR application performance involves both subjective assessments from users and objective evaluations, such as of energy consumption. Therefore, in edge computing environments, ways to integrate task offloading for XR subtasks to meet users' demands for XR applications is a complex and challenging issue. To address this issue, this paper constructs a wireless XR system based on mobile edge computing (MEC) and conducts research on the joint optimization of multi-user communication channel access and task offloading. Specifically, we consider the migration of partitioned XR tasks to MEC servers and formulate a joint optimization problem for communication channel access and task offloading. The objective is to maximize the ratio of quality of experience (QoE) to energy consumption while meeting the user QoE requirements. Subsequently, we introduce a deep reinforcement learning-based algorithm to address this optimization problem. The simulation results demonstrate the effectiveness of this algorithm in meeting user QoE demands and improving energy conversion efficiency, regardless of the XR task partitioning strategies employed. [ABSTRACT FROM AUTHOR]

Simple Summary: The spur refers to the protrusion near the tarsometatarsus on both sides of the calves of chickens, and their length varies from individual to individual. By analyzing phenotypic measurement results, we found that there were significant variations in spur length in layers. After calculating heritability, we found that spur length had a high level of heritability in the population, which also proved that this quantitative trait was controlled by multiple genes. Subsequently, we utilized genomic sequencing to identify candidate genes associated with spur length. As is known to all, the genetic material passed from parents to all siblings is similar, but some gender-biased traits such as spurs and egg-laying only show in one gender. We also attempted to find a connection between these two traits in this article. Spurs, which mainly appear in roosters, are protrusions near the tarsometatarsus on both sides of the calves of chickens, and are connected to the tarsometatarsus by a bony core. As a male-biased morphological characteristic, the diameter and length of spurs vary significantly between different individuals, mainly related to genetics and age. As a specific behavior of hens, egg-laying also varies greatly between individuals in terms of traits such as age at first egg (AFE), egg weight (EW), and so on. At present, there are few studies on chicken spurs. In this study, we investigated the inheritance pattern of the spur trait in roosters with different phenotypes and the correlations between spur length, body weight at 18 weeks of age (BW18), shank length at 18 weeks of age (SL18), and the egg-laying trait in hens (both hens and roosters were from the same population and were grouped according to their family). These traits related to egg production included AFE, body weight at first egg (BWA), and first egg weight (FEW). We estimated genetic parameters based on pedigree and phenotype data, and used variance analysis to calculate broad-sense heritability for correcting the parameter estimation results. The results showed that the heritability of male left and right spurs ranged from 0.6 to 0.7. There were significant positive correlations between left and right spur length, BW18, SL18, and BWA, as well as between left and right spur length and AFE. We selected 35 males with the longest spurs and 35 males with the shortest spurs in the population, and pooled them into two sets to obtain the pooled genome sequencing data. After genome-wide association and genome divergency analysis by FST, allele frequency differences (AFDs), and XPEHH methods, we identified 7 overlapping genes (CENPE, FAT1, FAM149A, MANBA, NFKB1, SORBS2, UBE2D3) and 14 peak genes (SAMD12, TSPAN5, ENSGALG00000050071, ENSGALG00000053133, ENSGALG00000050348, CNTN5, TRPC6, ENSGALG00000047655,TMSB4X, LIX1, CKB, NEBL, PRTFDC1, MLLT10) related to left and right spur length through genome-wide selection signature analysis and a genome-wide association approach. Our results identified candidate genes associated with chicken spurs, which helps to understand the genetic mechanism of this trait and carry out subsequent research around it. [ABSTRACT FROM AUTHOR]

Induction of autophagy promotes cardiomyocyte survival and confers a cardioprotective effect on acute myocardial infarction (AMI). Our previous study showed that knockdown of long noncoding RNA (IncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) attenuated myocardial apoptosis in mouse AMI. Herein, this study further investigated whether the mechanisms by which MALAT1 enhanced cardiomyocyte apoptosis involved the autophagy regulation. To address this, cardiomyocytes were isolated from neonatal mice and then stimulated with hypoxia/reoxygenation (H/R) injury to mimic AMI. The cell apoptosis was evaluated using TUNEL staining and Western blot analysis of apoptosis-related proteins. The autophagy level was assessed using GFP-LC3 immunofluorescence and Western blot analysis of autophagy-related proteins. The results showed that H/R injury increased MALAT1 expression. Furthermore, MALAT1 overexpression significantly enhanced apoptosis and regulated autophagy of cardiomyocytes, whereas MALAT1 knockdown exerted the opposite effect. Moreover, rapamycin (an autophagy activator) effectively attenuated the MALATl-mediated enhancement of cardiomyocyte apoptosis. Overall, our findings demonstrated that the increased MALAT1 expression induced by H/R injury enhances cardiomyocyte apoptosis, at least in part, through autophagy modulation. Key words: MALAT1, cardiomyocyte apoptosis, autophagy, mTOR, hypoxia/reoxygenation injury. L'induction de l'autophagie favorise la survie des cardiomyocytes et confère un effet cardioprotecteur lors de l'infarctus aigu du myocarde (IAM). Les études antérieures réalisées par les auteurs ont montré que le knockdown de l'ARNnm long MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) atténuait l'apoptose des cellules du myocarde lors de l'IAM chez la souris. Ici, cette étude a davantage examiné si les mécanismes par lesquels MALAT1 augmentait l'apoptose des cardiomyocytes impliquaient la régulation de l'autophagie. Pour ce faire, des cardiomyocytes ont été isolés de souriceaux nouveau-nés et stimulés par un dommage d'hypoxie/réoxygénation (H/R) pour simuler un IAM. L'apoptose a été évaluée par la coloration TUNEL et l'analyse par buvardage Western des protéines liées à l'apoptose. Le niveau d'autophagie a été évalué par l'immunofluorescence de GFP-LC3 et l'analyse par buvardage Western des protéines liées à l'autophagie. Les résultats ont montré que le dommage d'H/R accroissait l'expression de MALAT1. Qui plus est, la surexpression de MALAT1 augmentait significativement l'apoptose et régulait l'autophagie des cardiomyocytes, alors que le knockdown de MALAT1 exerçait l'effet opposé. Par ailleurs, la rapamycine (un activateur de l'autophagie) atténuait efficacement l'augmentation de l'apoptose des cardiomyocytes médiée par MALAT1. Dans l'ensemble, ces résultats démontraient que l'expression accrue de MALAT1 induite par le dommage d'H/R augmente l'apoptose des cardiomyocytes par la modulation de l'autophagie, du moins en partie. [Traduit par la Rédaction] Mots-clés : MALAT1, apoptose des cardiomyocytes, autophagie, mTOR, dommage d'H/R., Introduction Acute myocardial infarction (AMI) is a most serious cardiovascular disease with high morbidity and mortality worldwide. It is characterized by myocardial necrosis caused by acute and persistent ischemia and [...]