Investigation of the effects and mechanism of Total Glycosides of paeony against Radiation-Induced brain injury through network Pharmacology, molecular docking and experimental Verification.

Background: Total glucosides of paeony (TGP), derived from the dried root of Paeonia, is a popular treatment for immune diseases. Radiation induced brain injury (RBI) is a common side effect of brain radiation therapy, but the efficacy of TGP in treating RBI remains uncertain.

Purpose: To evaluate the protective effects of TGP against RBI and elucidate its underlying mechanisms using pharmacological network analysis, molecular docking, and experimental validation.

Enhancement of oil dispersion and marine oil snow formation by surface-active biomasses from diatom.

Following the Deepwater Horizon oil spill event, the formation of marine oil snow (MOS) has attracted much attention from marine environmental scientists. This study investigates the crude oil dispersion as well as the MOS formation in the presence of Phaeodactylum tricornutum and Chaetoceros sp. through laboratory experiments.

Variation in cancer risk between organs can not be explained by the degree of somatic clonal expansion.

Somatic clonal expansion refers to the proliferation and expansion of a cell clone within a multicellular organism. Since cancer also results from the uncontrolled proliferation of few cell clones, it is generally believed that aging-associated somatic clonal expansion observed in normal tissues represents a precancerous condition. For instance, hematological malignancy is often preceded by clonal hematopoiesis.

Carbon Dioxide Sensing Based on Off-Axis Integrated Cavity Absorption Spectroscopy Combined with the Informer and Multilayer Perceptron Models.

Off-axis integrated cavity output spectroscopy (OA-ICOS) allows the laser to be reflected multiple times inside the cavity, increasing the effective absorption path length and thus improving sensitivity. However, OA-ICOS systems are affected by various types of noise, and traditional filtering methods offer low processing efficiency and perform limited feature extraction. Deep learning models enable us to extract important features from large-scale, complex spectral data and analyze them efficiently and accurately.

Predictive value of lymphocyte-associated inflammation index in post-stroke cognitive impairment: a systematic review and meta-analysis.

Background: The predictive role of the lymphocyte-associated inflammation index in post-stroke cognitive impairment (PSCI) remains controversial. Therefore, we performed an updated meta-analysis to update the evidence.

Methods: This meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.