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iTRAQ-based quantitative proteomic analysis of herbicide stress in Avena ludoviciana Durieu
Spectral optimization of supercontinuum shaping using metaheuristic algorithms, a comparative study
AbstractSupercontinuum generation in optical fiber involves complex nonlinear dynamics, making optimization challenging, and typically relying on trial-and-error or extensive numerical simulations. Machine learning and metaheuristic algorithms offer more efficient optimization approaches. We report here an experimental study of supercontinuum spectral shaping by tuning the phase of the input pulses, different optimization approaches including a genetic algorithm, particle swarm optimizer, and simulated annealing. We find that the genetic algorithm and particle swarm optimizer are more robust and perform better, with the particle swarm optimizer converging faster. Our study provides valuable insights for the systematic optimization of supercontinuum and other optical sources.
Association between systemic immune inflammation index and cataract incidence from 2005 to 2008
Abstract The objective of this study is to investigate the association between the Systemic Immune-Inflammation Index (SII) and cataracts. This cross-sectional study analyzed data from the 2005–2008 NHANES to examine the relationship between the SII and cataract prevalence. Covariates included age, race/ethnicity, gender, education level, marital status, Body Mass Index (BMI), smoking, alcohol consumption, hypertension, hyperlipidemia, and diabetes. Multivariable logistic regression was used to assess the association, while spline curve fitting explored potential non-linear relationships. Threshold analysis identified critical inflection points. To address age-related bias, Propensity Score Matching (PSM) was performed, aligning cataract patients with comparable non-cataract individuals for further evaluation. Our study included 3,623 participants, of whom 730 (20.15%) were diagnosed with cataracts. After adjusting for all covariates, multivariable logistic regression analysis demonstrated that elevated levels of the SII were significantly associated with increased odds of cataracts (Model1: OR = 1.56; 95%CI [1.33–1.85]; Model2: OR = 1.55; 95%CI [1.32–1.84]; Model3: OR = 1.57; 95%CI [1.33–1.86]). In the spline curve fitting model, the relationship between ln-SII and cataract prevalence was non-linear (P < 0.001), with a critical inflection point identified at an SII of 428.38. SII levels remained significantly associated with cataract prevalence following PSM adjustments (Model 1: OR = 1.48; 95% CI [1.21–1.80]; Model 2: OR = 1.48; 95% CI [1.21–1.80]; Model 3: OR = 1.46; 95% CI [1.20–1.78]). Elevated SII levels are associated with a higher prevalence of cataracts, underscoring the pivotal role of systemic inflammation in cataract development. These findings indicate that SII could serve as a valuable biomarker for assessing cataract risk, further emphasizing the significance of managing systemic inflammation as a potential strategy for cataract prevention.