Predicting the environmental suitability and population at risk of podoconiosis in Africa

Podoconiosis is a type of tropical lymphedema that causes massive swelling of the lower limbs. The disease is associated with both economic insecurity, due to long-term morbidity-related loss of productivity, and intense social stigma. The geographical distribution and burden of podoconiosis in Africa are uncertain. We applied statistical modelling to the most comprehensive database compiled to date to predict the environmental suitability of podoconiosis in the African continent. By combining climate and environmental data and overlaying population figures, we predicted the environmental suitability and human population at risk of podoconiosis in Africa. Environmental suitability for podoconiosis was predicted in 29 African countries. In the year 2020, the total population in areas suitable for podoconiosis is estimated at 114.5 million people, (95% uncertainty interval: 109.4–123.9) with 16.9 million in areas suitable for both lymphatic filariasis and podoconiosis. Of the total 5,712 implementation units (typically second administrative-level units, such as districts) defined by the World Health Organization in Africa, 1,655 (29.0%) were found to be environmentally suitable for podoconiosis. The majority of implementation units with high environmental suitability are located in Angola (80, 4.8%), Cameroon (170, 10.3%), the DRC (244, 14.7%), Ethiopia (495, 29.9%), Kenya (217, 13.1%), Uganda (116, 7.0%) and Tanzania (112, 6.8%). Of the 1,655 environmentally suitable implementation units, 960 (58.0%) require more detailed community-level mapping. Our estimates provide key evidence of the population at risk and geographical extent of podoconiosis in Africa, which will help decision-makers to better plan more integrated intervention programmes

Cross-Species Analyses Identify the BNIP-2 and Cdc42GAP Homology (BCH) Domain as a Distinct Functional Subclass of the CRAL_TRIO/Sec14 Superfamily

The CRAL_TRIO protein domain, which is unique to the Sec14 protein superfamily, binds to a diverse set of small lipophilic ligands. Similar domains are found in a range of different proteins including neurofibromatosis type-1, a Ras GTPase-activating Protein (RasGAP) and Rho guanine nucleotide exchange factors (RhoGEFs). Proteins containing this structural protein domain exhibit a low sequence similarity and ligand specificity while maintaining an overall characteristic three-dimensional structure. We have previously demonstrated that the BNIP-2 and Cdc42GAP Homology (BCH) protein domain, which shares a low sequence homology with the CRAL_TRIO domain, can serve as a regulatory scaffold that binds to Rho, RhoGEFs and RhoGAPs to control various cell signalling processes. In this work, we investigate 175 BCH domain-containing proteins from a wide range of different organisms. A phylogenetic analysis with ∼100 CRAL_TRIO and similar domains from eight representative species indicates a clear distinction of BCH-containing proteins as a novel subclass within the CRAL_TRIO/Sec14 superfamily. BCH-containing proteins contain a hallmark sequence motif R(R/K)h(R/K)(R/K)NL(R/K)xhhhhHPs (‘h’ is large and hydrophobic residue and ‘s’ is small and weekly polar residue) and can be further subdivided into three unique subtypes associated with BNIP-2-N, macro- and RhoGAP-type protein domains. A previously unknown group of genes encoding ‘BCH-only’ domains is also identified in plants and arthropod species. Based on an analysis of their gene-structure and their protein domain context we hypothesize that BCH domain-containing genes evolved through gene duplication, intron insertions and domain swapping events. Furthermore, we explore the point of divergence between BCH and CRAL-TRIO proteins in relation to their ability to bind small GTPases, GAPs and GEFs and lipid ligands. Our study suggests a need for a more extensive analysis of previously uncharacterized BCH, ‘BCH-like’ and CRAL_TRIO-containing proteins and their significance in regulating signaling events involving small GTPases

Enhanced Longevity by Ibuprofen, Conserved in Multiple Species, Occurs in Yeast through Inhibition of Tryptophan Import

The common non-steroidal anti-inflammatory drug ibuprofen has been associated with a reduced risk of some age-related pathologies. However, a general pro-longevity role for ibuprofen and its mechanistic basis remains unclear. Here we show that ibuprofen increased the lifespan of Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster, indicative of conserved eukaryotic longevity effects. Studies in yeast indicate that ibuprofen destabilizes the Tat2p permease and inhibits tryptophan uptake. Loss of Tat2p increased replicative lifespan (RLS), but ibuprofen did not increase RLS when Tat2p was stabilized or in an already long-lived strain background impaired for aromatic amino acid uptake. Concomitant with lifespan extension, ibuprofen moderately reduced cell size at birth, leading to a delay in the G1 phase of the cell cycle. Similar changes in cell cycle progression were evident in a large dataset of replicatively long-lived yeast deletion strains. These results point to fundamental cell cycle signatures linked with longevity, implicate aromatic amino acid import in aging and identify a largely safe drug that extends lifespan across different kingdoms of life.The open access fee for this work was funded through the Texas A&M University Open Access to Knowledge (OAK) Fund

silx-kit/pyFAI: pyFAI-2024.01

<ul> <li>Possibility to define the detector orientation:<ul> <li>It is the position of the origin of the detector at any of the 4 corner of the image</li> <li>Uses the EXIF nomenclature where pyFAI's (default) orientation is tagged 3</li> <li>Offers compatibility with calibration made by Diotas (where orientation=2 since images are flipped)</li> <li>Expose the feature in the calib2 GUI for custom detectors.</li> <li>Tutorial on the usage</li> <li>New sub-version of the PoniFile API (2.1) for this feature</li> </ul> </li> <li>Expose the number of corners of a detector pixel (feature unused for now)</li> <li>Refactor pyFAI-benchmark tool with better looking reults (Thanks Edgar)</li> <li>Possibility to integrate in 2D with any second dimension unit:<ul> <li>No more limited to the azimuthal angle chi</li> <li>Several new units have been added</li> <li>Offers the qx/qy integration as example</li> </ul> </li> <li>Support for Detris Pilatus4 detector both with Si and CdTe sensors (thanks to Max Burian)</li> <li>Support XRDML formt (compatibility with MAUD software)</li> <li>Multigeometry gains a reset() method to free some memory with optimized garbage collection.</li> <li>Support pathlib when reading-PONI files</li> <li>Change in the build system:<ul> <li>Drop of setup.py the build system based on distutils/numpy.distutils/setuptools</li> <li>Enforce the use of meson-python</li> <li>Move the sources of the code into src directory</li> <li>Support for Python 3.7-3.12 (requires silx v2 for 3.12) + Provide debian packages for debian12 but ubuntu 20.04 is too old and lack meson-python</li> </ul> </li> <li>Facts and figures:<ul> <li>600+ commits; 120 pull-requests *with the contribution of: Edgar Gutierrez Fernandez Jérôme Kieffer.</li> </ul> </li> </ul&gt

PITPs as targets for selectively interfering with phosphoinositide signaling in cells

Sec14-like phosphatidylinositol transfer proteins (PITPs) integrate diverse territories of intracellular lipid metabolism with stimulated phosphatidylinositol-4-phosphate production and are discriminating portals for interrogating phosphoinositide signaling. Yet, neither Sec14-like PITPs nor PITPs in general have been exploited as targets for chemical inhibition for such purposes. Herein, we validate what is to our knowledge the first small-molecule inhibitors (SMIs) of the yeast PITP Sec14. These SMIs are nitrophenyl(4-(2-methoxyphenyl)piperazin-1-yl)methanones (NPPMs) and are effective inhibitors in vitro and in vivo. We further establish that Sec14 is the sole essential NPPM target in yeast and that NPPMs exhibit exquisite targeting specificities for Sec14 (relative to related Sec14-like PITPs), propose a mechanism for how NPPMs exert their inhibitory effects and demonstrate that NPPMs exhibit exquisite pathway selectivity in inhibiting phosphoinositide signaling in cells. These data deliver proof of concept that PITP-directed SMIs offer new and generally applicable avenues for intervening with phosphoinositide signaling pathways with selectivities superior to those afforded by contemporary lipid kinase–directed strategies