Comparative Analysis of Gelatin/Polylactic Acid and Commercial PLA Membranes for Guided Bone Regeneration: A Randomized Clinical Trial.

BACKGROUND This study included 32 patients with single missing teeth and alveolar bone defects and aimed to compare outcomes from guided bone regeneration with a gelatin/polylactic acid (GT/PLA) barrier membrane and a Guidor® bioresorbable matrix barrier dental membrane. MATERIAL AND METHODS A total of 32 participants were recruited in the clinical study, with single missing teeth and alveolar bone defects, requiring guided bone regeneration (32 missing teeth in total). They were randomly divided into the GT/PLA membrane group (experimental) and Guidor® membrane group (control) by the envelope method (n=16).

Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer.

Colorectal cancer (CRC) is a prevalent malignant tumor worldwide, with a high mortality rate due to its complex etiology and limited early screening techniques. This study aimed to identify potential biomarkers for early detection of CRC utilizing targeted metabolite profiling of platelet-rich plasma (PRP). Based on multiple reaction monitoring (MRM) mode, liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis identified metabolites in PRP collected from patients with CRC (n = 70) and healthy controls (n = 30).

Regulation of desiccation-immersion cycle on the rate and fate of dissolved organic carbon release by Ulva pertusa.

Macroalgae widely distribute in intertidal zones, one of blue carbon organisms. However, the regulatory mechanisms of tide on the carbon sequestration of macroalgae are still unclear. This study explored the effects of desiccation-rewetting cycles induced by tide on dissolved organic carbon (DOC) release from Ulva pertusa, which is prevalent from high to low tidal zones.

Flood risk in mountainous settlements: A new framework based on an interpretable NSGA-II-GB from a point-area duality perspective.

Global climate change has significantly increased the frequency and intensity of extreme precipitation events, thereby heightening flood risks for mountainous settlements. However, due to geographical and socio-economic constraints in these regions, flood-related sample data are generally scarce. This study introduces a Mean Filter (MF) grounded in the point-area duality perspective, combined with a feature selection approach utilizing multi-objective optimization algorithms.