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Spinocerebellar ataxia (SCA) types 1, 2, 3, 6, and 7, associated with a (CAG)nrepeat expansion in coding sequences, are the most prevalent autosomal dominant ataxias worldwide (approximately 60% of the cases). In addition, the phenotype of SCA2 expansions has been now extended to Parkinson disease and amyotrophic lateral sclerosis. Their diagnosis is currently based on a PCR to identify small expanded alleles, followed by a second-level test whenever a false normal homozygous or a CAT interruption in SCA1 needs to be verified. Next-generation sequencing still does not allow efficient detection of these repeats. Here, we show the efficacy of a novel, rapid, and cost-effective method to identify and size pathogenic expansions in SCA1, 2, 3, 6, and 7 and recognize large alleles or interruptions without a second-level test. Twenty-five healthy controls and 33 expansion carriers were analyzed: alleles migrated consistently in different PCRs and capillary runs, and homozygous individuals were always distinguishable from heterozygous carriers of both common and large (>100 repeats) pathogenic CAG expansions. Repeat number could be calculated counting the number of peaks, except for the largest SCA2 and SCA7 alleles. Interruptions in SCA1 were always visible. Overall, our method allows a simpler, cost-effective, and sensibly faster SCA diagnostic protocol compared with the standard technique and to the still unadapted next-generation sequencing.

A Correction to this paper has been published: https://doi.org/10.1038/s41436-020-01064-y

Summary Glycosaminoglycans (GAGs) were isolated, separated by electrophoresis and quantified in 36 neurosurgical specimens of human gliomas and in 8 samples of normal white and gray matter. Gliomas of various degrees of malignancy exhibited different GAG patterns. Total GAG concentration was three times higher in low grade gliomas than in normal white matter. The mean percentage of single GAG classes was usually similar in both tissues, although in certain tumor samples a higher percentage of hyaluronate was found. GAG patterns in anaplastic astrocytomas, however, more closely resembled normal white and gray matter, both quantitatively and qualitatively. Glioblastomas, on the other hand, showed high GAG concentrations, in particular of heparan sulfate and dermatan sulfate. This finding could be secondary to the abundant vessels and mesodermal material associated with this oncotype. The hyaluronate/sulfated GAGs ratio was lower in oligodendrogliomas than in low grade astrocytomas. This biochemical feature may be correlated with the alcianophilia found in the honey-comb degeneration of oligodendrogliomas. The significance of these findings as they relate to tumor histology and biology have been discussed.

When a subject is at rest and meals have not been eaten for a relatively long time (e.g. during the night), presumably near-constant, zero-order glucose production occurs in the liver. Glucose elimination from the bloodstream may be proportional to glycemia, with an apparently first-order, linear elimination rate. Besides glycemia itself, unobserved factors (insulinemia, other hormones) may exert second and higher order effects. Random events (sleep pattern variations, hormonal cycles) may also affect glycemia. The time-course of transcutaneously, continuously measured glycemia (CGM) thus reflects the superposition of different orders of control, together with random system error. The problem may be formalized as a fractional random walk, or fractional Brownian motion. In the present work, the order of this fractional stochastic process is estimated on night-time CGM data from one subject. • We propose a novel order estimation method for fractional stochastic models (FSDE). • We apply the method to a FSDE glucose model fitted from real CGM data. • A scheme for the approximate FSDE integration via finite increments is proposed. • Stochastic correctness of our algorithm in terms of increment covariance is proved. • The accuracy is comparable to other fractional noise integration algorithms. [ABSTRACT FROM AUTHOR]