Romosozumab adverse event profile: a pharmacovigilance analysis based on the FDA Adverse Event Reporting System (FAERS) from 2019 to 2023.

Objective: This study aims to analyze adverse drug events (ADE) related to romosozumab from the second quarter of 2019 to the third quarter of 2023 from FAERS database.

Methods: The ADE data related to romosozumab from 2019 Q2 to 2023 Q3 were collected. After data normalization, four signal strength quantification algorithms were used: ROR (Reporting Odds Ratios), PRR (Proportional Reporting Ratios), BCPNN (Bayesian Confidence Propagation Neural Network), and EBGM (Empirical Bayesian Geometric Mean).

Deficiency of myeloid discoidin domain receptor 2 aggravates melanoma lung and bone metastasis.

Melanoma, one of the most prevalent cancers worldwide, frequently metastasizes to the lung and bones. Tumor-associated macrophages play essential roles in melanoma metastasis but the underlying mechanism remains obscure. We previously demonstrated that specific knockout of Ddr2, a receptor tyrosine kinase, exacerbates systemic inflammation via modulating macrophage repolarization.

Secreted protein TNA: a promising biomarker for understanding the adipose-bone axis and its impact on bone metabolism.

Background: Osteoporosis (OP) is a systemic bone disease characterized by reduced bone mass and deterioration of bone microstructure, leading to increased bone fragility. Platelets can take up and release cytokines, and a high platelet count has been associated with low bone density. Obesity is strongly associated with OP, and adipose tissue can influence platelet function by secreting adipokines.

Mediating oxidative stress through the Palbociclib/miR-141-3p/STAT4 axis in osteoporosis: a bioinformatics and experimental validation study.

Osteoporosis is a common bone disease characterized by loss of bone mass, reduced bone strength, and deterioration of bone microstructure. ROS-induced oxidative stress plays an important role in osteoporosis. However, the biomarkers and molecular mechanisms of oxidative stress are still unclear.

Baseline Pydiflumetofen Sensitivity of Isolates Collected from Henan, China, and Potential Resistance Mechanisms.

Fusarium crown rot (FCR), caused by , is one of the most important diseases impacting wheat production in the Huanghuai region, the most important wheat-growing region of China. The current study found that the SDHI fungicide pydiflumetofen, which was recently developed by Syngenta Crop Protection, provided effective control of 67 wild-type isolates in potato dextrose agar, with an average EC value of 0.060 ± 0.

Progranulin from different gliocytes in the nucleus accumbens exerts distinct roles in FTD- and neuroinflammation-induced depression-like behaviors.

Background: Neuroinflammation in the nucleus accumbens (NAc) is well known to influence the progression of depression. However, the molecular mechanisms triggering NAc neuroinflammation in depression have not been fully elucidated. Progranulin (PGRN) is a multifunctional growth factor that is linked to the innate immune response and inflammation, and PGRN plays a key role in neurodegenerative diseases such as frontotemporal dementia (FTD).

Catalytic synthesis of 2,5-bis(hydroxymethyl)furan from 5-hydroxymethylfurfual by recombinant Saccharomyces cerevisiae.

2,5-Bis(hydroxymethyl)furan (BHMF) is a versatile building block in the synthesis of polymers, fuels, and macrocycle polyethers. In this work, alcohol dehydrogenases (ADHs) were identified from Meyerozyma guilliermondii SC1103 and were heterologously expressed in Saccharomyces cerevisiae for the synthesis of BHMF from 5-hydroxymethylfurfural (HMF). Of recombinant strains constructed, S.

DeeReCT-PolyA: a robust and generic deep learning method for PAS identification.

Motivation: Polyadenylation is a critical step for gene expression regulation during the maturation of mRNA. An accurate and robust method for poly(A) signals (PASs) identification is not only desired for the purpose of better transcripts' end annotation, but can also help us gain a deeper insight of the underlying regulatory mechanism. Although many methods have been proposed for PAS recognition, most of them are PAS motif- and human-specific, which leads to high risks of overfitting, low generalization power, and inability to reveal the connections between the underlying mechanisms of different mammals.

Efficient and accurate inversion of multiple scattering with deep learning.

Image reconstruction under multiple light scattering is crucial in a number of applications such as diffraction tomography. The reconstruction problem is often formulated as a nonconvex optimization, where a nonlinear measurement model is used to account for multiple scattering and regularization is used to enforce prior constraints on the object. In this paper, we propose a powerful alternative to this optimization-based view of image reconstruction by designing and training a deep convolutional neural network that can invert multiple scattered measurements to produce a high-quality image of the refractive index.