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The brain of a 69-year-old man exhibited extensive granulomatous inflammation in the walls of arteries in the leptomeninges, associated with amyloid deposition in the media of the involved arteries. The extracranial arteries exhibited neither granulomatous inflammation nor amyloid deposition in their walls.

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Background Intra-articular (IA) injection of hyaluronic acid (HA) (IA-HA) is a well-recognized treatment option for pain associated with symptomatic knee osteoarthritis (OA). IA-HA products differ in their HA content, molecular weight, cross-linking, and source of HA. These differences are assumed to affect the biocompatibility of the IA-HA products once injected inside the knee joint. Methods In the present study, we investigated the biocompatibility of three multiple-injection IA-HA products available in the global market. These included SUPARTZ FX™, a medium range molecular weight HA derived from rooster comb (Avian-HA); ORTHOVISC®, a high range molecular weight HA obtained through biological fermentation (Bio-HA); and SYNVISC®, a high molecular weight cross-linked hyaluronan derived from rooster comb (Avian-CL-HA). Rabbit knee joint tissues were histologically and biochemically examined after IA injection of the products. Furthermore, we compared the amounts of impurities in the IA-HA products. Results IA injection of Avian-CL-HA into rabbit knee joints induced the aggregation of inflammatory cells, infiltration of eosinophils, and an increase in the number of cells in the synovial fluid. However, these effects were not seen in the Avian-HA and Bio-HA groups. The residual protein content and the contaminant levels of bacterial endotoxins were below the limit of quantitation in all HA products. Avian-CL-HA contained relatively a large amount of (1 → 3)-β-D-glucan, but this was below the lower limit of quantification in the other HA products. Conclusions The present results clearly demonstrate that the biocompatibility of Avian-HA is comparable to that of Bio-HA, and they were both considered to have a favorable safety profile for the treatment of symptomatic OA of the knee. However, immunostimulatory activity was observed after injection of Avian-CL-HA: this might be a result of its unique cross-linking structure and/or the considerable amount of (1 → 3)-β-D-glucan impurity present in the formulation.

Bioreduction with immobilized bakers' yeast proceeded smoothly in hexane by using alcohols, such as methanol, ethanol, and propan-2-01, instead of glucose, as an energy source; ethyl 3-oxobutanoate and ethyl benzoylformate were each reduced to the corresponding chiral hydroxy esters with a high enantiomeric purity.

Accumulating evidence indicates that alterations of gut microbiota are associated with colorectal cancer (CRC). Therefore, the use of gut microbiota for the diagnosis of CRC has received attention. Recently, several studies have been conducted to detect the differences in the gut microbiota between healthy individuals and CRC patients using machine learning‐based gut bacterial DNA meta‐sequencing analysis, and to use this information for the development of CRC diagnostic model. However, to date, most studies had small sample sizes and/or only cross‐validated using the training dataset that was used to create the diagnostic model, rather than validated using an independent test dataset. Since machine learning‐based diagnostic models cause overfitting if the sample size is small and/or an independent test dataset is not used for validation, the reliability of these diagnostic models needs to be interpreted with caution. To circumvent these problems, here we have established a new machine learning‐based CRC diagnostic model using the gut microbiota as an indicator. Validation using independent test datasets showed that the true positive rate of our CRC diagnostic model increased substantially as CRC progressed from Stage I to more than 60% for CRC patients more advanced than Stage II when the false positive rate was set around 8%. Moreover, there was no statistically significant difference in the true positive rate between samples collected in different cities or in any part of the colorectum. These results reveal the possibility of the practical application of gut microbiota‐based CRC screening tests.

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