Association between fibrinogen-to-albumin ratio and bone metabolism markers (β-CTX and P1NP) in Chinese individuals with osteoporotic fracture: a cross-sectional investigation.

Objective: Research on the link between inflammatory indicators and markers of bone metabolism is currently lacking, especially the interaction between Procollagen type 1 N-terminal propeptide (P1NP), the β-C-terminal telopeptide of type 1 collagen (β-CTX), and the fibrinogen-to-albumin ratio (FAR). This study intends to fill that knowledge gap by investigating the possible link between inflammatory indicators and bone metabolism.

Methods: This observational study included 718 individuals diagnosed with osteoporotic fractures from Kunshan Hospital Affiliated to Jiangsu University between January 2017 and July 2022.

Association of apolipoprotein A1 levels with lumbar bone mineral density and β-CTX in osteoporotic fracture individuals: a cross-sectional investigation.

Background: The relationship between the levels of high-density lipoprotein (HDL) and bone mineral density (BMD) is controversial. Furthermore, the specific role of apolipoprotein A1 (APOA1), a primary HDL component, in regulating BMD remains unclear. This study aimed to elucidate the correlation between APOA1 levels and lumbar BMD in patients with osteoporotic fracture (OPF) for novel insights into potential therapeutic strategies against osteoporosis.

Zero-Shot Image Classification Method Based on Attention Mechanism and Semantic Information Fusion.

The zero-shot image classification (ZSIC) is designed to solve the classification problem when the sample is very small, or the category is missing. A common method is to use attribute or word vectors as a priori category features (auxiliary information) and complete the domain transfer from training of seen classes to recognition of unseen classes by building a mapping between image features and a priori category features. However, feature extraction of the whole image lacks discrimination, and the amount of information of single attribute features or word vector features of categories is insufficient, which makes the matching degree between image features and prior class features not high and affects the accuracy of the ZSIC model.