Insomnia and intestinal microbiota: a narrative review.

Purpose: The intestinal microbiota and insomnia interact through the microbiota-gut-brain axis. The purpose of this review is to summarize and analyze the changes of intestinal microbiota in insomnia, the interaction mechanisms between intestinal microbiota and insomnia and the treatment methods based on the role of microbiota regulation in insomnia, in order to reveal the feasibility of artificial intervention of intestinal microbiota to improve insomnia.

Methods: Pubmed/ Embase were searched through March 2024 to explore the relevant studies, which included the gut microbiota characteristics of insomnia patients, the mechanisms of interaction between insomnia and gut microbiota, and the relationship between gut microbiota and insomnia treatment.

Insomnia among coronavirus disease 2019 survivors: A single-center cross-sectional study.

Since the coronavirus disease 2019 (COVID-19) epidemic, insomnia has become one of the longer COVID-19 symptoms. This study aimed to investigate insomnia among COVID-19 survivors and explore the occurrence and influencing factors of insomnia. A cross-sectional study was performed from December 2022 to February 2023 through an online questionnaire star survey with 8 questions.

Precipitate Evolution in 22Cr25NiWCuCo(Nb) Austenitic Heat-Resistant Stainless Steel during Heat Treatment at 1200 °C.

In this study, 22Cr25NiWCuCo(Nb) heat-resistant steel specimens with high Cr and Ni contents were adopted to investigate the effect of Nb content on thermal and precipitation behavior. Differential scanning calorimetry profiles revealed that the melting point of the 22Cr25NiWCuCo(Nb) steel specimens decreased slightly with the Nb content. After heat treatment at 1200 °C for 2 h, the precipitates dissolved in a Nb-free steel matrix.

[Baseline correction method for Raman spectroscopy based on B-spline fitting].

Baseline drift is a widespread phenomenon in modern spectroscopy instrumentation, which would bring a very negative impact to the feature extraction of spectrum signal, and the baseline correction method is an important means to solve the problem, which is also the important part of Raman signal preprocessing. The general principle of baseline drift elimination is using the fitting method to the fit the baseline. The traditional fitting method is polynomial fitting, but this method is prone to over-fitting and under-fitting, and the fitting order is difficult to be determined.