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Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors globally, significantly affecting liver functions, thus necessitating the identification of biomarkers and effective therapeutics to improve HCC-based disabilities. This study aimed to identify prognostic biomarkers, signaling cascades, and candidate drugs for the treatment of HCC through integrated bioinformatics approaches such as functional enrichment analysis, survival analysis, molecular docking, and simulation. Differential expression and functional enrichment analyses revealed 176 common differentially expressed genes from two microarray datasets, GSE29721 and GSE49515, significantly involved in HCC development and progression. Topological analyses revealed 12 hub genes exhibiting elevated expression in patients with higher tumor stages and grades. Survival analyses indicated that 11 hub genes (CCNB1, AURKA, RACGAP1, CEP55, SMC4, RRM2, PRC1, CKAP2, SMC2, UHRF1, and FANCI) and three transcription factors (E2F1, CREB1, and NFYA) are strongly linked to poor patient survival. Finally, molecular docking and simulation identified seven candidate drugs with stable complexes to their target proteins: tozasertib (-9.8 kcal/mol), tamatinib (-9.6 kcal/mol), ilorasertib (-9.5 kcal/mol), hesperidin (-9.5 kcal/mol), PF-562271 (-9.3 kcal/mol), coumestrol (-8.4 kcal/mol), and clofarabine (-7.7 kcal/mol). These findings suggest that the identified hub genes and TFs could serve as valuable prognostic biomarkers and therapeutic targets for HCC-based disabilities.

The infection control team (ICT) ensures the implementation of infection control guidelines in healthcare facilities. This systematic review aims to evaluate the effectiveness of ICT, with or without an infection control link nurse (ICLN) system, in reducing healthcare-associated infections (HCAIs). We searched four databases to identify randomised controlled trials (RCTs) in inpatient, outpatient and long-term care facilities. We judged the quality of the studies, conducted meta-analyses whenever interventions and outcome measures were comparable in at least two studies, and assessed the certainty of evidence. Nine RCTs were included; all were rated as being low quality. Overall, ICT, with or without an ICLN system, did not reduce the incidence rate of HCAIs [risk ratio (RR) = 0.65, 95% confidence interval (CI): 0.45-1.07], death due to HCAIs (RR = 0.32, 95% CI: 0.04-2.69) and length of hospital stay (42 days vs. 45 days, p = 0.52). However, ICT with an ICLN system improved nurses' compliance with infection control practices (RR = 1.17, 95% CI: 1.00-1.38). Due to the high level of bias, inconsistency and imprecision, these findings should be considered with caution. High-quality studies using similar outcome measures are needed to demonstrate the effectiveness and cost-effectiveness of ICT.

The m.3243A>G mutation in mitochondrial tRNA-Leu(UUR) is one of the most common pathogenic mitochondrial DNA mutations in humans. The clinical manifestations are highly heterogenous and the causes for the drastic clinical variability are unknown. Approximately one third of patients suffer from cardiac disease, which often increases mortality. Why only some patients develop cardiomyopathy is unknown. Here, we studied the molecular effects of a high m.3243A>G mutation load on cardiomyocyte functionality, using cells derived from induced pluripotent stem cells (iPSC-CM) of two different m.3243A>G patients, only one of them suffering from severe cardiomyopathy. While high mutation load impaired mitochondrial respiration in both patients' iPSC-CMs, the downstream consequences varied. mtDNA mutant cells from a patient with no clinical heart disease showed increased glucose metabolism and retained cellular ATP levels, whereas cells from the cardiac disease patient showed reduced ATP levels. In this patient, the mutations also affected intracellular calcium signaling, while this was not true in the other patient's cells. Our results reflect the clinical variability in mitochondrial disease patients and show that iPSC-CMs retain tissue specific features seen in patients.

In collaborative body sensor networks, namely wireless body area networks (WBANs), each of the physical sensor applications is used to collaboratively monitor the health status of the human body. The applications of WBANs comprise diverse and dynamic traffic loads such as very low-rate periodic monitoring (i.e., observation) data and high-rate traffic including event-triggered bursts. Therefore, in designing a medium access control (MAC) protocol for WBANs, energy conservation should be the primary concern during low-traffic periods, whereas a balance between satisfying high-throughput demand and efficient energy usage is necessary during high-traffic times. In this paper, we design a traffic load-aware innovative MAC solution for WBANs, called ATLAS. The design exploits the superframe structure of the IEEE 802.15.4 standard, and it adaptively uses the contention access period (CAP), contention free period (CFP) and inactive period (IP) of the superframe based on estimated traffic load, by applying a dynamic "wh" (whenever which is required) approach. Unlike earlier work, the proposed MAC design includes load estimation for network load-status awareness and a multi-hop communication pattern in order to prevent energy loss associated with long range transmission. Finally, ATLAS is evaluated through extensive simulations in ns-2 and the results demonstrate the effectiveness of the protocol.

Energy conservation is one of the striking research issues now-a-days for power constrained wireless sensor networks (WSNs) and hence, several duty-cycle based MAC protocols have been devised for WSNs in the last few years. However, assimilation of diverse applications with different QoS requirements (i.e., delay and reliability) within the same network also necessitates in devising a generic duty-cycle based MAC protocol that can achieve both the delay and reliability guarantee, termed as multi-constrained QoS, while preserving the energy efficiency. To address this, in this paper, we propose a Multi-constrained QoS-aware duty-cycle MAC for heterogeneous traffic in WSNs (MQ-MAC). MQ-MAC classifies the traffic based on their multi-constrained QoS demands. Through extensive simulation using ns-2 we evaluate the performance of MQ-MAC. MQ-MAC provides the desired delay and reliability guarantee according to the nature of the traffic classes as well as achieves energy efficiency.