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A Novel Technique Using Lyophilized Amniotic Membrane Patch (LAMPatch) as Primary Procedure in Patients with Myopic Traction Maculopathy with Macular Detachment

Abstract
Introduction: Maculopathy secondary to pathologic myopia (PM) is increasingly causing visual impairment and blindness worldwide. PM is associated with tractional maculopathy that ranges from macular foveoschisis to macular hole. These disorders are treated with different options that offer variable results, reflecting the need for new techniques that address myopic maculopathy with consistent outcomes.

Transcriptome profiling of macrophages persistently infected with human respiratory syncytial virus and effect of recombinant Taenia solium calreticulin on immune-related genes

Abstract
Introduction: Human respiratory syncytial virus (hRSV) is a main cause of bronchiolitis in infants and its persistence has been described in immunocompromised subjects. However, limited evidence has been reported on the gene expression triggered by the hRSV and the effect of recombinant Taenia solium-derived calreticulin (rTsCRT).

Simultaneous Parkinsonism and Dementia as Initial Presentation of Intracranial Dural Arteriovenous Fistulas: A Systematic Review

Abstract
Background: Intracranial dural arteriovenous fistulas (IDAVFs) are abnormal vascular connections between dural arteries and various venous structures within the brain. IDAVFs, rarely present with parkinsonism and dementia concurrently, making this a unique and underexplored clinical scenario. To the best of our knowledge, this is the first systematic review to comprehensively analyze cases of IDAVFs manifesting as both parkinsonism and dementia.

Performance of machine-learning approach for prediction of pre-eclampsia in a middle-income country

Abstract

Objective: Pre-eclampsia (PE) is a serious complication of pregnancy associated with maternal and fetal morbidity and mortality. As current prediction models have limitations and may not be applicable in resource-limited settings, we aimed to develop a machine-learning (ML) algorithm that offers a potential solution for developing accurate and efficient first-trimester prediction of PE.

Non-binary gender, vulnerable populations and mental health during the COVID-19 pandemic: Data from the COVID-19 MEntal health inTernational for the general population (COMET-G) study

Abstract
Background: The COVID-19 pandemic has brought significant mental health challenges, particularly for vulnerable populations, including non-binary gender individuals. The COMET international study aimed to investigate specific risk factors for clinical depression or distress during the pandemic, also in these special populations.

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