A decision rule algorithm for the detection of patients with hypertension using claims data.

Objectives: Claims data covers a large population and can be utilized for various epidemiological and economic purposes. However, the diagnosis of prescriptions is not determined in the claims data of many countries. This study aimed to develop a decision rule algorithm using prescriptions to detect patients with hypertension in claims data.

Exploring autoimmune endocrine diseases induced by monoclonal antibodies used as multiple sclerosis pharmacotherapy: a systematic review.

Multiple sclerosis (MS) is an autoimmune neurodegenerative disease that targets myelin, leading to inflammation and neuron death. Monoclonal antibodies (MAb) have long been used to control the progression and exacerbations of this disorder, which may induce secondary autoimmune disease as a rare adverse event. This systematic review aimed to gather data of case reports around this subject and to explain the mechanism behind their occurrence.

Inhibition of histone methyltransferase promotes cognition and mitochondrial function in vascular dementia model.

Vascular dementia (VD) is one of the most common forms of dementia worldwide, characterized by problems with reasoning, planning, judgment, and memory. This study investigated the effect of a histone methyltransferase inhibitor on cognition and mitochondrial function in a rat model of VD, as well as its impact on HO-induced neurotoxicity in hippocampal neuronal cultures. In the in vivo experiments, VD was induced by bilateral occlusion of the common carotid artery (CCA) for one month.

AmiR-P3: An AI-based microRNA prediction pipeline in plants.

Background: MicroRNAs (miRNAs) are small noncoding RNAs that play important post-transcriptional regulatory roles in animals and plants. Despite the importance of plant miRNAs, the inherent complexity of miRNA biogenesis in plants hampers the application of standard miRNA prediction tools, which are often optimized for animal sequences. Therefore, computational approaches to predict putative miRNAs (merely) from genomic sequences, regardless of their expression levels or tissue specificity, are of great interest.