Pathophysiology and Treatment of Lipid Abnormalities in Cerebrotendinous Xanthomatosis: An Integrative Review.

Cerebrotendinous xanthomatosis (CTX) is an autosomal recessive disorder caused by pathogenic variants in CYP27A1, leading to a deficiency in sterol 27-hydroxylase. This defect results in the accumulation of cholestanol and bile alcohols in various tissues, including the brain, tendons and peripheral nerves. We conducted this review to evaluate lipid profile abnormalities in patients with CTX. A search was conducted in PubMed, Embase and the Virtual Health Library in January 2023 to evaluate studies reporting the lipid profiles of CTX patients, including the levels of cholestanol, cholesterol and other lipids. Elevated levels of cholestanol were consistently observed. Most patients presented normal or low serum cholesterol levels. A decrease in chenodeoxycholic acid (CDCA) leads to increased synthesis of cholesterol metabolites, such as bile alcohols 23S-pentol and 25-tetrol 3-glucuronide, which may serve as surrogate follow-up markers in patients with CTX. Lipid abnormalities in CTX have clinical implications. Cholestanol deposition in tissues contributes to clinical manifestations, including neurological symptoms and tendon xanthomas. Dyslipidemia and abnormal cholesterol metabolism may also contribute to the increased risk of atherosclerosis and cardiovascular complications observed in some CTX patients.

Submesoscale dispersion in the vicinity of the Deepwater Horizon spill.

Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society, and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity field at the submesoscales (100 m to tens of kilometers, hours to days) remain unresolved due to a lack of synoptic measurements at these scales. Using high-frequency position data provided by the near-simultaneous release of hundreds of accurately tracked surface drifters, we study the structure of submesoscale surface velocity fluctuations in the Northern Gulf of Mexico. Observed two-point statistics confirm the accuracy of classic turbulence scaling laws at 200-m to 50-km scales and clearly indicate that dispersion at the submesoscales is local, driven predominantly by energetic submesoscale fluctuations. The results demonstrate the feasibility and utility of deploying large clusters of drifting instruments to provide synoptic observations of spatial variability of the ocean surface velocity field. Our findings allow quantification of the submesoscale-driven dispersion missing in current operational circulation models and satellite altimeter-derived velocity fields.

Environmental inversion using high-resolution matched-field processing.

This paper considers the inversion of experimental field data collected with light receiving systems designed to meet operational requirements. Such operational requirements include system deployment in free drifting configurations and a limited number of acoustic receivers. A well-known consequence of a reduced spatial coverage is a poor sampling of the vertical structure of the acoustic field, leading to a severe ill-conditioning of the inverse problem and data to model cost function with a massive sidelobe structure having many local extrema. This causes difficulties to meta-heuristic global search methods, such as genetic algorithms, to converge to the true model parameters. In order to cope with this difficulty, broadband high-resolution processors are proposed for their ability to significantly attenuate sidelobes, as a contribution for improving convergence. A comparative study on simulated data shows that high-resolution methods did not outperform the conventional Bartlett processor for pinpointing the true environmental parameter when using exhaustive search. However, when a meta-heuristic technique is applied for exploring a large multidimensional search space, high-resolution methods clearly improved convergence, therefore reducing the inherent uncertainty on the final estimate. These findings are supported by the results obtained on experimental field data obtained during the Maritime Rapid Environmental Assessment 2003 sea trial.