Analysis of quantitative trait loci and candidate gene exploration associated with cold tolerance in rice ( L.) during the seedling stage.

Cold stress during the seedling stage significantly threatens rice ( L.) production, specifically in temperate climates. This study aimed to identify quantitative trait loci (QTLs) associated with cold tolerance at the seedling stage.

Effect of intracameral air injection during Ahmed glaucoma valve implantation on hypertensive phase.

The purpose of this study was to evaluate the difference in the incidence of the hypertensive phase (HP) between Ahmed glaucoma valve (AGV) patients who received intracameral air injection and those who did not. A total of 78 patients who underwent AGV surgery between January 1, 2016 and June 30, 2023 were included in this retrospective study. HP was defined as intraocular pressure (IOP) greater than 21 mmHg within the first 6 postoperative months.

Situating the salience and parietal memory networks in the context of multiple parallel distributed networks using precision functional mapping.

Brain networks serving higher cognitive functions are widely distributed across frontal and posterior association zones. Two exceptions have been the parietal memory network (PMN) and salience network (SAL), which are typically restricted to posterior (e.g.

Surgical Management of Fibrosing Mediastinitis Presenting as Superior Vena Cava Syndrome.

Fibrosing mediastinitis is a rare chronic inflammatory condition characterized by excessive fibrotic process in the mediastinum. Although various infectious processes are more common causes, it can also be related to several malignancies. We report a case of a 28-year-old woman with fibrosing mediastinitis related to an aggressive primary gray-zone lymphoma causing complete occlusion of the superior vena cava (SVC) and the innominate veins.

Machine learning to predict periprosthetic joint infections following primary total hip arthroplasty using a national database.

Introduction: Periprosthetic joint infection (PJI) following total hip arthroplasty (THA) remains a devastating complication for patients and surgeons. Given the implications of these infections and the current paucity of risk calculators utilizing machine learning (ML), this study aimed to develop an ML algorithm that could accurately identify risk factors for developing a PJI following primary THA using a national database.

Materials And Methods: A total of 51,053 patients who underwent primary THA between 2013 and 2020 were identified using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database.