Physicochemical and Structural Characterisation of Human Il-1α and Il-2 Proteins with Insilco Tools

Inflammation is a physiological reaction that occurs as a result of several types of injuries, including those caused by physical, chemical, or biological sources. Interleukins, which belong to the wider category of cytokines, modify cellular function in the context of inflammation. Interleukins are used in animal experiments to explore aspects linked to healthcare. The interleukin-1α and interleukin-2 families are particularly associated with harmful inflammatory processes, even more so than any other kind of cytokine. The objective of the current work was to analyze the physiochemical characteristics, secondary structures, and tertiary structures of IL-1α and IL-2 utilizing bioinformatic techniques. The amino acid sequences of IL-1α and IL-2 were obtained from the UniProt protein database. The physicochemical characterisation of IL-1α and IL-2 proteins showed that they are made up of 271 and 153 amino acids, with molecular weights of 30606.61 and 17627.1 Da, respectively. The predicted isoelectric (pI) values for the IL-1α and IL-2 peptides were determined to be 5.04 and 7.67, respectively. In their secondary structures, the IL-1α and IL-2 proteins display a higher proportion of extended strands and alpha helices respectively. The predicted 3D structure of IL-1α and IL-2 from humans demonstrates that P01583.1.A and P60568.1.A are the most appropriate templates. The QMEAN values for the predicted models of IL-1α and IL-2 were 0.51±0.05 and 0.73±0.07, respectively. The Ramachandran plot showed that most of the amino acid phi-psi distributions are in line with a right-handed helix. These results confirm that the expected model is stable and reliable

Temperature-dependent structural properties, phase transition behavior, and dynamic properties of a benzene derivative in the solid state

We report the solid-state structural properties and phase transition behavior of 1,4-dibromo-2,3,5,6-tetramethylbenzene, demonstrating that this material undergoes an order–disorder phase transition below ambient temperature (at ca. 154 K on cooling and ca. 160 K on heating). In both the high-temperature and low-temperature phases, the crystal structure is based on π-stacking of the molecules. In the crystal structure of the high-temperature phase, the bromine occupancy in each substituent site is ca. 1/3 and the methyl group occupancy in each substituent site is ca. 2/3, consistent with statistical orientational disorder of the molecule between six distinct orientations. Natural-abundance solid-state 2H NMR spectroscopy confirms that, at ambient temperature, this disorder is dynamic via rapid molecular reorientation about an axis perpendicular to the aromatic ring. In the low-temperature phase, the bromine and methyl substituents occupy preferred sites within the crystal structure, with the distribution of site occupancies becoming progressively more ordered on decreasing temperature

Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial

Aims  The third Universal Definition of Myocardial Infarction (MI) Task Force classified MIs into five types: Type 1, spontaneous; Type 2, related to oxygen supply/demand imbalance; Type 3, fatal without ascertainment of cardiac biomarkers; Type 4, related to percutaneous coronary intervention; and Type 5, related to coronary artery bypass surgery. Low-density lipoprotein cholesterol (LDL-C) reduction with statins and proprotein convertase subtilisin–kexin Type 9 (PCSK9) inhibitors reduces risk of MI, but less is known about effects on types of MI. ODYSSEY OUTCOMES compared the PCSK9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome (ACS) and elevated LDL-C (≥1.8 mmol/L) despite intensive statin therapy. In a pre-specified analysis, we assessed the effects of alirocumab on types of MI. Methods and results  Median follow-up was 2.8 years. Myocardial infarction types were prospectively adjudicated and classified. Of 1860 total MIs, 1223 (65.8%) were adjudicated as Type 1, 386 (20.8%) as Type 2, and 244 (13.1%) as Type 4. Few events were Type 3 (n = 2) or Type 5 (n = 5). Alirocumab reduced first MIs [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77–0.95; P = 0.003], with reductions in both Type 1 (HR 0.87, 95% CI 0.77–0.99; P = 0.032) and Type 2 (0.77, 0.61–0.97; P = 0.025), but not Type 4 MI. Conclusion  After ACS, alirocumab added to intensive statin therapy favourably impacted on Type 1 and 2 MIs. The data indicate for the first time that a lipid-lowering therapy can attenuate the risk of Type 2 MI. Low-density lipoprotein cholesterol reduction below levels achievable with statins is an effective preventive strategy for both MI types.For complete list of authors see http://dx.doi.org/10.1093/eurheartj/ehz299</p

Effect of alirocumab on mortality after acute coronary syndromes. An analysis of the ODYSSEY OUTCOMES randomized clinical trial

Background: Previous trials of PCSK9 (proprotein convertase subtilisin-kexin type 9) inhibitors demonstrated reductions in major adverse cardiovascular events, but not death. We assessed the effects of alirocumab on death after index acute coronary syndrome. Methods: ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) was a double-blind, randomized comparison of alirocumab or placebo in 18 924 patients who had an ACS 1 to 12 months previously and elevated atherogenic lipoproteins despite intensive statin therapy. Alirocumab dose was blindly titrated to target achieved low-density lipoprotein cholesterol (LDL-C) between 25 and 50 mg/dL. We examined the effects of treatment on all-cause death and its components, cardiovascular and noncardiovascular death, with log-rank testing. Joint semiparametric models tested associations between nonfatal cardiovascular events and cardiovascular or noncardiovascular death. Results: Median follow-up was 2.8 years. Death occurred in 334 (3.5%) and 392 (4.1%) patients, respectively, in the alirocumab and placebo groups (hazard ratio [HR], 0.85; 95% CI, 0.73 to 0.98; P=0.03, nominal P value). This resulted from nonsignificantly fewer cardiovascular (240 [2.5%] vs 271 [2.9%]; HR, 0.88; 95% CI, 0.74 to 1.05; P=0.15) and noncardiovascular (94 [1.0%] vs 121 [1.3%]; HR, 0.77; 95% CI, 0.59 to 1.01; P=0.06) deaths with alirocumab. In a prespecified analysis of 8242 patients eligible for ≥3 years follow-up, alirocumab reduced death (HR, 0.78; 95% CI, 0.65 to 0.94; P=0.01). Patients with nonfatal cardiovascular events were at increased risk for cardiovascular and noncardiovascular deaths (P<0.0001 for the associations). Alirocumab reduced total nonfatal cardiovascular events (P<0.001) and thereby may have attenuated the number of cardiovascular and noncardiovascular deaths. A post hoc analysis found that, compared to patients with lower LDL-C, patients with baseline LDL-C ≥100 mg/dL (2.59 mmol/L) had a greater absolute risk of death and a larger mortality benefit from alirocumab (HR, 0.71; 95% CI, 0.56 to 0.90; Pinteraction=0.007). In the alirocumab group, all-cause death declined wit h achieved LDL-C at 4 months of treatment, to a level of approximately 30 mg/dL (adjusted P=0.017 for linear trend). Conclusions: Alirocumab added to intensive statin therapy has the potential to reduce death after acute coronary syndrome, particularly if treatment is maintained for ≥3 years, if baseline LDL-C is ≥100 mg/dL, or if achieved LDL-C is low. Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01663402

Role of Artificial Intelligence in Veterinary Preventive Medicine: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis aims to comprehensively evaluate the current role and effectiveness of artificial intelligence (AI) applications in veterinary preventive medicine across different animal species. The review will focus on original research articles that report the use of AI technologies such as machine learning, deep learning, expert systems, and computer vision in disease prediction, surveillance, early diagnosis, and foodborne disease monitoring in animals including cattle, poultry, swine, sheep, goats, and companion animals (e.g., dogs). Veterinary preventive medicine is a rapidly evolving field that emphasizes proactive measures to ensure animal health, minimize disease transmission, and enhance food safety. With growing interest in AI technologies globally, the veterinary sector is beginning to embrace data-driven solutions to optimize preventive strategies. However, evidence remains fragmented and lacks a unified synthesis of outcomes, methodologies, and species-specific applications. This systematic review addresses this gap by assessing the diagnostic accuracy, surveillance efficiency, and overall effectiveness of AI tools used in preventive veterinary practice. This review will be conducted following PRISMA 2020 guidelines. Articles will be screened based on PECO eligibility criteria: Population – any animal species; Exposure – use of AI models for preventive purposes; Comparison – not mandatory but may include traditional methods; Outcome – diagnostic performance (accuracy, sensitivity), and surveillance effectiveness. Only peer-reviewed original research articles published between January 2021 and May 10, 2025 will be included. Reviews, conference proceedings, and non-peer-reviewed literature will be excluded. There will be no language restrictions. Electronic databases including Google Scholar, PubMed, Elsevier, and Wiley will be searched. Data will be managed using Zotero, and risk of bias will be assessed using QUADAS-2. A meta-analysis will be conducted where data allow; otherwise, a narrative synthesis will be presented. This protocol has been registered to ensure transparency and minimize bias. The review is expected to be completed within 6 months. No funding was received, and the authors declare no conflicts of interest