Design-time detection of physical-unit changes in product lines

Software product lines evolve over time, both as new products are added to the product line and as existing products are updated. This evolution creates unintended as well as planned changes to Systems. A persistent problem is that unintended changes are hard to detect. Often they are not discovered until testing or operations. Late discovery is a problem especially in safety-critical, cyberphysical product lines such as avionics, pacemakers, and smart-braking systems, where unintended changes may lead to accidents. This thesis proposes an approach and a prototype tool to detect unintended changes earlier in development of a new product in the product line. The capability to detect potentially risky, unintended changes at the design stage is beneficial because repair is easier, less costly, and safer in design than when detection is delayed to testing or operations. The Product Line Change Detector (PLCD) introduced here analyzes products’ SysML block and parametric diagrams, which are typical project artifacts for cyber-physical systems, in order to detect problematic, unintended changes. The PLCD software automatically detects potential change-related issues, ranks them in terms of severity using the products’ safety-analysis artifacts, and reports them to developers in a graphical format. Developers select and fix the reported issues with the assistance of the tool’s displays, with the tool recording the fixes and updating the SysML diagrams accordingly. The evaluation of PLCD’s performance and capabilities uses three product lines, extended from cyber-physical systems in the literature: NASA astronaut jetpack, vehicle dynamics, and low-earth satellite. The evaluation focuses on unintended changes that cause physical unit inconsistencies, such as between meters and feet, since those may lead to accidents in cyber-physical product lines. The evaluation results show that PLCD successfully detects such unintended changes both in a single product and between products in a software product line

Design-time detection of physical-unit changes in product lines

Software product lines evolve over time, both as new products are added to the product line and as existing products are updated. This evolution creates unintended as well as planned changes to Systems. A persistent problem is that unintended changes are hard to detect. Often they are not discovered until testing or operations. Late discovery is a problem especially in safety-critical, cyberphysical product lines such as avionics, pacemakers, and smart-braking systems, where unintended changes may lead to accidents. This thesis proposes an approach and a prototype tool to detect unintended changes earlier in development of a new product in the product line. The capability to detect potentially risky, unintended changes at the design stage is beneficial because repair is easier, less costly, and safer in design than when detection is delayed to testing or operations. The Product Line Change Detector (PLCD) introduced here analyzes products’ SysML block and parametric diagrams, which are typical project artifacts for cyber-physical systems, in order to detect problematic, unintended changes. The PLCD software automatically detects potential change-related issues, ranks them in terms of severity using the products’ safety-analysis artifacts, and reports them to developers in a graphical format. Developers select and fix the reported issues with the assistance of the tool’s displays, with the tool recording the fixes and updating the SysML diagrams accordingly. The evaluation of PLCD’s performance and capabilities uses three product lines, extended from cyber-physical systems in the literature: NASA astronaut jetpack, vehicle dynamics, and low-earth satellite. The evaluation focuses on unintended changes that cause physical unit inconsistencies, such as between meters and feet, since those may lead to accidents in cyber-physical product lines. The evaluation results show that PLCD successfully detects such unintended changes both in a single product and between products in a software product line.</p

Non-coding RNAs expression in SARS-CoV-2 infection: pathogenesis, clinical significance, and therapeutic targets

Abstract The coronavirus disease 2019 (COVID-19) pandemic has been looming globally for three years, yet the diagnostic and treatment methods for COVID-19 are still undergoing extensive exploration, which holds paramount importance in mitigating future epidemics. Host non-coding RNAs (ncRNAs) display aberrations in the context of COVID-19. Specifically, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) exhibit a close association with viral infection and disease progression. In this comprehensive review, an overview was presented of the expression profiles of host ncRNAs following SARS-CoV-2 invasion and of the potential functions in COVID-19 development, encompassing viral invasion, replication, immune response, and multiorgan deficits which include respiratory system, cardiac system, central nervous system, peripheral nervous system as well as long COVID. Furthermore, we provide an overview of several promising host ncRNA biomarkers for diverse clinical scenarios related to COVID-19, such as stratification biomarkers, prognostic biomarkers, and predictive biomarkers for treatment response. In addition, we also discuss the therapeutic potential of ncRNAs for COVID-19, presenting ncRNA-based strategies to facilitate the development of novel treatments. Through an in-depth analysis of the interplay between ncRNA and COVID-19 combined with our bioinformatic analysis, we hope to offer valuable insights into the stratification, prognosis, and treatment of COVID-19

DL0410 Ameliorates Memory and Cognitive Impairments Induced by Scopolamine via Increasing Cholinergic Neurotransmission in Mice

Deficiency of the cholinergic system is thought to play a vital role in cognitive impairment of dementia. DL0410 was discovered as a dual inhibitor of acetylcholinesterase (AChE) and butyrylcholinestease (BuChE), with potent efficiency in in-vitro experiments, but its in vivo effect on the cholinergic model has not been evaluated, and its action mechanism has also not been illustrated. In the present study, the capability of DL0410 in ameliorating the amnesia induced by scopolamine was investigated, and its effect on the cholinergic system in the hippocampus and its binding mode in the active site of AChE was also explored. Mice were administrated DL0410 (3 mg/kg, 10 mg/kg, and 30 mg/kg), and mice treated with donepezil were used as a positive control. The Morris water maze, escape learning task, and passive avoidance task were used as behavioral tests. The test results indicated that DL0410 could significantly improve the learning and memory impairments induced by scopolamine, with 10 mg/kg performing best. Further, DL0410 inhibited the AChE activity and increased acetylcholine (ACh) levels in a dose-dependent manner, and interacted with the active site of AChE in a similar manner as donepezil. However, no difference in the activity of BuChE was found in this study. All of the evidence indicated that its AChE inhibition is an important mechanism in the anti-amnesia effect. In conclusion, DL0410 could be an effective therapeutic drug for the treatment of dementia, especially Alzheimer’s disease

CircGRIA1 shows an age-related increase in male macaque brain and regulates synaptic plasticity and synaptogenesis

Circular RNAs are expressed in the brain and show age-dependent expression patterns. Here the authors show the circGRIA1 is expressed in an age-dependent manner in the male macaque brain and serves a functional role in synaptic plasticity