CSF sphingolipids are correlated with neuroinflammatory cytokines and differentiate neuromyelitis optica spectrum disorder from multiple sclerosis.

BACKGROUND: There is a need for biomarkers of disease progression and therapeutic response in multiple sclerosis (MS). This study aimed to identify cerebrospinal fluid (CSF) lipids that differentiate MS from other neuroinflammatory conditions and correlate with Expanded Disability Status Scale (EDSS) scores, gadolinium-enhancing lesions or inflammatory mediators. METHODS: Lipids and inflammatory cytokines/chemokines were quantified with liquid chromatography-tandem mass spectrometry and multiplex ELISA, respectively, in CSF from people with untreated MS, neuromyelitis optica spectrum disorder (NMOSD), other inflammatory neurological diseases and non-inflammatory neurological diseases (NIND). Analytes were compared between groups using analysis of variance, and correlations were assessed with Pearson's analysis. RESULTS: Twenty-five sphingolipids and four lysophosphatidylcholines were significantly higher in NMOSD compared with MS and NIND cases, whereas no lipids differed significantly between MS and NIND. A combination of three sphingolipids differentiated NMOSD from MS with the area under the curve of 0.92 in random forest models. Ninety-four lipids, including those that differentiated NMOSD from MS, were positively correlated with macrophage migration inhibitory factor (MIF) and 37 lipids were positively correlated with CSF protein in two independent MS cohorts. EDSS was inversely correlated with cholesterol ester CE(16:0) in both MS cohorts. In contrast, MIF and soluble triggering receptor expressed on myeloid cells 2 were positively associated with EDSS. CONCLUSIONS: CSF sphingolipids are positively correlated with markers of neuroinflammation and differentiate NMOSD from MS. The inverse correlation between EDSS and CE(16:0) levels may reflect poor clearance of cholesterol released during myelin break-down and warrants further investigation as a biomarker of therapeutic response.

Functional outcomes of diets in multiple sclerosis (FOOD for MS): Protocol for a parallel arm randomized feeding trial for low glycemic load and calorie restriction.

BACKGROUND: Pilot trials indicate that both a low glycemic load (GL) diet and calorie restriction (CR) can be implemented successfully in people with multiple sclerosis (pMS) and may improve MS symptoms and physical function, but large randomized clinical trials (RCTs) have not yet been conducted. The purpose of this study is to test these interventions alone and in combination to determine their efficacy for improving clinical and patient reported outcomes (PROs) in pMS. METHODS: This 32-week, two-arm, RCT at two centers will randomly assign 100 adults with relapsing-remitting or secondary progressive MS to a low GL diet (n = 50) or a standard GL diet (n = 50). Both diet groups will complete two study phases: a eucaloric phase (16 weeks) and a CR phase (16 weeks). Groceries for the study meal plans will be delivered to participants' homes weekly. The primary outcome is physical function, measured by timed 25-ft walk test. Secondary outcomes are pain, fatigue, mood, and anxiety. DISCUSSION: This will be the most rigorous intervention trial to date of a low GL diet and CR in adults with MS, and among the first to assess the impact of intentional weight loss on MS symptoms. Results will provide valuable insight for recommending dietary change, weight loss, or both to adults with MS. These non-drug interventions pose few risks and have potential to yield significant improvements in MS symptoms. TRIAL REGISTRATION ID: NCT05327322.

A Review of Geophysical Modeling Based on Particle Swarm Optimization.

This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical fields are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth's subsurface and then to undertake a critical evaluation of their benefits and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle different data sets without conflicting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the benefit of PSO practitioners or inexperienced researchers.

SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence.

We applied a generalized SEIR epidemiological model to the recent SARS-CoV-2 outbreak in the world, with a focus on Italy and its Lombardy, Piedmont, and Veneto regions. We focused on the application of a stochastic approach in fitting the model parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We analyzed the official data and the predicted evolution of the epidemic in the Italian regions, and we compared the results with the data and predictions of Spain and South Korea. We linked the model equations to the changes in people's mobility, with reference to Google's COVID-19 Community Mobility Reports. We discussed the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.

A new case of induced helical chirality in a bichromophoric system: absolute configuration of transparent and flexible diols from the analysis of the electronic circular dichroism spectra of the corresponding di(1-naphthyl)ketals.

Di(1-naphthyl)ketals of 1, n-diols show couplet effects allied to the (1)B naphthalene transition in their CD spectra. This means that they assume a conformation with a prevailing sense of twist of the naphthalene rings, imposed by the absolute configuration (AC) of the starting diols and by the nature of the R 1 groups. A positive couplet for aliphatic diols is a probe of ( R, R), AC while the opposite sign is found for ( R, R) aromatic diols.