Analysis of the immunohistochemical and genetic expression pattern of kisspeptin in endometrial polyps.

Objective: Endometrial polyp (EP) is a type of pathology that is quite common in clinical practice. Although its exact etiology is not fully known, there is evidence to support that it is sensitive to hormonal stimuli. We aimed to investigate the relationship between kisspeptin (KP) and EP by comparing the genetic (tissue-blood) and immunohistochemical (IHC) expression of KP in EP lesions in patients with normal endometrial findings.

TOR2 plays the central role in rapamycin-induced lifespan extension in budding yeast.

The target of rapamycin (TOR) protein, renowned for its highly conserved nature across species, plays a pivotal role in modulating signaling pathways via its multiprotein complexes, TORC1 and TORC2. The relationship between TOR and its inhibitor, rapamycin, especially in the context of lifespan extension, has earned significant attention. Unlike mammals, which have a single TOR gene, the budding yeast Saccharomyces cerevisiae features two TOR paralogs: TOR1 and TOR2.

variants cause a phenotypic spectrum from early-onset Parkinson's disease to perinatal lethality by disrupting mitochondrial pathways.

Dissecting biological pathways highlighted by Mendelian gene discovery has provided critical insights into the pathogenesis of Parkinson's disease (PD) and neurodegeneration. This approach ultimately catalyzes the identification of potential biomarkers and therapeutic targets. Here, we identify as a new gene implicated in PD and childhood neurodegeneration.

Validity and Reliability of the Turkish Version of the Patient-Reported Impact of Spasticity Measure in Multiple Sclerosis.

Background: We aimed to evaluate the validity and reliability of the Turkish version of the Patient-Reported Impact of Spasticity Measure (PRISM-TR).

Methods: Expert opinions and the forward-back translation method were used for linguistic validation. Cronbach α and test-retest analysis were performed for reliability analysis.

A machine learning approach to determine the risk factors for fall in multiple sclerosis.

Background: Falls in multiple sclerosis can result in numerous problems, including injuries and functional loss. Therefore, determining the factors contributing to falls in people with Multiple Sclerosis (PwMS) is crucial. This study aims to investigate the contributing factors to falls in multiple sclerosis using a machine learning approach.