The Drosophila testis has been fundamental to understanding how stem cells interact with their endogenous microenvironment, or niche, to control organ growth in vivo. Here, we report the identification of two independent alleles for the highly conserved tumor suppressor gene, Retinoblastoma-family protein (Rbf), in a screen for testis phenotypes in X chromosome third-instar lethal alleles. Rbf mutant alleles exhibit overproliferation of spermatogonial cells, which is phenocopied by the molecularly characterized Rbf null allele. We demonstrate that Rbf promotes cell-cycle exit and differentiation of the somatic and germline stem cells of the testes. Intriguingly, depletion of Rbf specifically in the germline does not disrupt stem cell differentiation, rather Rbf loss of function in the somatic lineage drives overproliferation and differentiation defects in both lineages. Together our observations suggest that Rbf in the somatic lineage controls germline stem cell renewal and differentiation non-autonomously via essential roles in the microenvironment of the germline lineage.
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http://dx.doi.org/10.1016/j.stemcr.2016.11.007 | DOI Listing |
Clin Ophthalmol
December 2024
Department of Ophthalmology, Visual and Anatomical Sciences, Kresge Eye Institute/Wayne State University School of Medicine, Detroit, MI, USA.
Purpose: To evaluate the outcomes of scleral-fixated intraocular lenses (IOLs) implanted using either Yamane technique or Gore-Tex suture fixation, in comparison to intracapsular lens fixation, and to assess the efficacy of various lens formulas in achieving predicted refractive targets.
Patients And Methods: This study included 45 eyes from 44 patients with scleral-fixated IOLs, comprising 37 Yamane eyes and 8 Gore-Tex eyes. Preoperative refractive predictions from various formulae were compared with final postoperative refraction.
BMC Neurol
December 2024
Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, 02115, USA.
Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the world. Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high energy and have complex architecture. Considering these limitations, a time-varying synaptic efficacy function based leaky-integrate and fire neuron model, called SEFRON is used for the detection of PD.
View Article and Find Full Text PDFConventional control charts track changes in the process by using predefined process parameters. Conversely, during online monitoring, adaptive control charts modify the process parameters. To improve the process dispersion monitoring in various operational environments, this study presents an adaptive exponentially weighted moving average (AEWMA) control chart based on support vector regression (SVR).
View Article and Find Full Text PDFJ Hazard Mater
December 2024
Center for Water and Ecology, State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
Riverbank filtration (RBF) is an effective pretreatment technology for drinking water, removing organic micropollutants (OMPs) mainly through biodegradation. Despite documented improvements in OMP removal with extended adaptation time, the mechanisms remain poorly understood. This study assessed the removal of 128 OMPs over 82 d in a simulated RBF system, identified those with improved removal, and analyzed their properties.
View Article and Find Full Text PDFBiodegradation
December 2024
Department of Civil engineering, Islamic Azad university, Mashhad Branch, Iran.
The widespread use of pesticides, including diazinon, poses an increased risk of environmental pollution and detrimental effects on biodiversity, food security, and water resources. In this study, we investigated the impact of Potentially Toxic Elements (PTE) including Zn, Cd, V, and Mn on the degradation of diazinon in three different soils. We investigated the capability and performance of four machine learning models to predict residual pesticide concentration, including adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), radial basis function (RBF), and multi-layer perceptron (MLP).
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