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Phosphodiesterase type 5 (PDE5) inhibitors, including sildenafil, tadalafil, and vardenafil, are primarily prescribed for erectile dysfunction and pulmonary hypertension. Emerging evidence suggests they may also modulate inflammatory pathways and improve vascular function, but their effects on inflammatory biomarkers in humans remain incompletely defined. A systematic review and meta-analysis were conducted to evaluate the impact of PDE5 inhibitors on inflammatory and endothelial markers in adult humans. Randomized controlled trials comparing PDE5 inhibition to placebo were identified through electronic database searches. Outcomes included pro-inflammatory markers (TNF-α, IL-6, IL-8, CRP, VCAM-1, ICAM-1, P-selectin) and anti-inflammatory or signalling markers (IL-10, NO, cGMP), assessed at short-term (≤1 week), intermediate-term (4–6 weeks), or long-term (≥12 weeks) follow-up. Risk of bias was assessed using the Cochrane RoB 2 tool. A total of 20 studies comprising 1549 participants were included. Meta-analyses showed no significant short-term effects of PDE5 inhibition on TNF-α, IL-6, or CRP. Long-term treatment was associated with reduced IL-6 (SMD = −0.64, p = 0.002) and P-selectin (SMD = −0.57, p = 0.02), and increased cGMP (SMD = 0.87, p = 0.0003). Effects on IL-10 and nitric oxide were inconsistent across studies. Most trials had low risk of bias. PDE5 inhibitors may exert anti-inflammatory effects in long-term use by reducing vascular inflammation and enhancing cGMP signalling. These findings support further investigation of PDE5 in chronic inflammatory conditions.

Calcium ions are versatile messengers, helping to control many body functions including blood pressure. How they do this becomes clearer from a study of their interactions with ion channels in blood vessels.

As software systems increasingly interact with humans in application domains such as transportation and healthcare, they raise concerns related to the social, legal, ethical, empathetic, and cultural (SLEEC) norms and values of their stakeholders. Normative non-functional requirements (N-NFRs) are used to capture these concerns by setting SLEEC-relevant boundaries for system behavior. Since N-NFRs need to be specified by multiple stakeholders with widely different, non-technical expertise (ethicists, lawyers, regulators, end users, etc.), N-NFR elicitation is very challenging. To address this challenge, we introduce N-Check, a novel tool-supported formal approach to N-NFR analysis and debugging. N-Check employs satisfiability checking to identify a broad spectrum of N-NFR well-formedness issues (WFI), such as conflicts, redundancy, restrictiveness, insufficiency, yielding diagnostics which pinpoint their causes in a user-friendly way that enables non-technical stakeholders to understand and fix them. We show the effectiveness and usability of our approach through nine case studies in which teams of ethicists, lawyers, philosophers, psychologists, safety analysts, and engineers used N-Check to analyse and debug 233 N-NFRs comprising 62 issues for the software underpinning the operation of systems ranging from assistive-care robots and tree-disease detection drones to manufacturing collaborative robots.

Normative non-functional requirements specify constraints that a system must observe in order to avoid violations of social, legal, ethical, empathetic, and cultural norms. As these requirements are typically defined by non-technical system stakeholders with different expertise and priorities (ethicists, lawyers, social scientists, etc.), ensuring their well-formedness and consistency is very challenging. Recent research has tackled this challenge using a domain-specific language to specify normative requirements as rules whose consistency can then be analysed with formal methods. In this paper, we propose a complementary approach that uses Large Language Models to extract semantic relationships between abstract representations of system capabilities. These relations, which are often assumed implicitly by non-technical stakeholders (e.g., based on common sense or domain knowledge), are then used to enrich the automated reasoning techniques for eliciting and analyzing the consistency of normative requirements. We show the effectiveness of our approach to normative requirements elicitation and operationalization through a range of real-world case studies.