Microglia at sites of atrophy restrict the progression of retinal degeneration via galectin-3 and Trem2

Outer retinal degenerations, including age-related macular degeneration (AMD), are characterized by photoreceptor and retinal pigment epithelium (RPE) atrophy. In these blinding diseases, macrophages accumulate at atrophic sites, but their ontogeny and niche specialization remain poorly understood, especially in humans. We uncovered a unique profile of microglia, marked by galectin-3 upregulation, at atrophic sites in mouse models of retinal degeneration and human AMD. In disease models, conditional deletion of galectin-3 in microglia led to phagocytosis defects and consequent augmented photoreceptor death, RPE damage, and vision loss, indicating protective roles. Mechanistically, Trem2 signaling orchestrated microglial migration to atrophic sites and induced galectin-3 expression. Moreover, pharmacologic Trem2 agonization led to heightened protection but in a galectin-3-dependent manner. In elderly human subjects, we identified this highly conserved microglial population that expressed galectin-3 and Trem2. This population was significantly enriched in the macular RPE-choroid of AMD subjects. Collectively, our findings reveal a neuroprotective population of microglia and a potential therapeutic target for mitigating retinal degeneration

Zeeman slowing of a Group III atom

We realize the first Zeeman slower of an atom in the Main Group III of the periodic table, otherwise known as the "triel elements". Despite that our atom of choice (namely indium) does not have a ground state cycling transition suitable for laser cooling, slowing is achieved by driving the transition $\lvert 5P_{3/2},F=6 \rangle \rightarrow \lvert 5D_{5/2},F=7 \rangle$, where the lower-energy state is metastable. Using a slower based on permanent magnets in a transverse-field configuration, we observe a bright slowed atomic beam at our design goal velocity of 70 m/s. The techniques presented here can straightforwardly extend to other triel atoms such as thallium, aluminum, and gallium. Furthermore, this work opens the possibility of cooling Group III atoms to ultracold temperatures.Comment: 8 pages, 9 figures. Final published versio

Heat-induced oxidation and proteomic changes to yak milk protein

Yak milk is a dietary source of high-quality protein in the plateau region of China but as yet uncharacterized oxidative changes occur during heat treatment. Therefore, oxidation of and proteomic changes to milk proteins from plateau pasture-fed yaks after at different temperatures were investigated. Content of carbonyl groups, surface hydrophobicity increased, and total sulfhydryl, disulfide bond content decreased. Endogenous fluorescence intensity decreased after at increasing temperatures, indicating increased particle size, and absolute values of the zeta potential decreased. Analysis by Fourier transform infrared spectroscopy showed changes of the secondary structure, with relative content of α-helices increasing and then decreasing, β-sheet showed a trend of decreasing and then increasing while the relative content of random curl did not change. The close range of the β-turn gradually decreased, breaking the protein microstructure, and folding stacking occurred. Proteomics analyses showed a temperature dependent effect. Sixty-two proteins were suppressed and 49 elevated with 4 pathways up-regulated and 7 down-regulated at 65 °C. Thirty-one proteins were suppressed and 37 elevated with 5 pathways up-regulated and 4 down-regulated at 90 °C. The most extensive changes were observed at 120 °C, when 327 proteins were suppressed and 308 elevated with 11 pathways up-regulated and 33 down-regulated

AceGPT, Localizing Large Language Models in Arabic

This paper explores the imperative need and methodology for developing a localized Large Language Model (LLM) tailored for Arabic, a language with unique cultural characteristics that are not adequately addressed by current mainstream models like ChatGPT. Key concerns additionally arise when considering cultural sensitivity and local values. To this end, the paper outlines a packaged solution, including further pre-training with Arabic texts, supervised fine-tuning (SFT) using native Arabic instructions and GPT-4 responses in Arabic, and reinforcement learning with AI feedback (RLAIF) using a reward model that is sensitive to local culture and values. The objective is to train culturally aware and value-aligned Arabic LLMs that can serve the diverse application-specific needs of Arabic-speaking communities. Extensive evaluations demonstrated that the resulting LLM called `AceGPT' is the SOTA open Arabic LLM in various benchmarks, including instruction-following benchmark (i.e., Arabic Vicuna-80 and Arabic AlpacaEval), knowledge benchmark (i.e., Arabic MMLU and EXAMs), as well as the newly-proposed Arabic cultural \& value alignment benchmark. Notably, AceGPT outperforms ChatGPT in the popular Vicuna-80 benchmark when evaluated with GPT-4, despite the benchmark's limited scale. % Natural Language Understanding (NLU) benchmark (i.e., ALUE) Codes, data, and models are in https://github.com/FreedomIntelligence/AceGPT.Comment: https://github.com/FreedomIntelligence/AceGP

XLF and APLF bind Ku80 at two remote sites to ensure DNA repair by non-homologous end joining

International audienceThe Ku70-Ku80 (Ku) heterodimer binds rapidly and tightly to the ends of DNA double-strand breaks and recruits factors of the non-homologous end-joining (NHEJ) repair pathway through molecular interactions that remain unclear. We have determined crystal structures of the Ku-binding motifs (KBM) of the NHEJ proteins APLF (A-KBM) and XLF (X-KBM) bound to a Ku-DNA complex. The two KBM motifs bind remote sites of the Ku80 alpha/beta domain. The X-KBM occupies an internal pocket formed by an unprecedented large outward rotation of the Ku80 alpha/beta domain. We observe independent recruitment of the APLF-interacting protein XRCC4 and of XLF to laser-irradiated sites via binding of A- and X-KBMs, respectively, to Ku80. Finally, we show that mutation of the X-KBM and A-KBM binding sites in Ku80 compromises both the efficiency and accuracy of end joining and cellular radiosensitivity. A- and X-KBMs may represent two initial anchor points to build the intricate interaction network required for NHEJ

methodology development and applications of protein-protein interaction prediction

Les interactions protéine-protéine (IPP) jouent un rôle essentiel dans le vivant. Mon travail de thèse s’est concentré sur développement de méthodes bio-informatiques pour la prédiction et la modélisation structurale des IPP. Mon objectif était d'améliorer le pouvoir prédictif des méthodes permettant de prédire les structures d’assemblages macromoléculaires (docking) et d'aborder les problèmes rencontrés par les biologistes sur des cas réels d’interactions.Pour obtenir des modèles de protéines isolées de meilleure qualité, j’ai tout d’abord développé le serveur HHalign-Kbest basé sur des algorithmes d’alignements sous-optimaux. Ensuite, dans le domaine du « docking », j’ai élaboré le serveur InterEvDock qui prend en compte les informations de coévolution entre protéines. Les validations en aveugle montrent que ce serveur atteint de meilleures performances que d’autres serveurs de référence lorsque l’information évolutive est disponible.Afin de tester plus à fond nos méthodes, nous avons participé au concours CAPRI - un concours international pour la prédiction des interactions protéiques. Sur les sessions couvrant la période 2013-2016, notre groupe s’est classé 1er. Enfin, j'ai développé un jeu de données d’apprentissage et de test, PPI4DOCK. Il contient un très grand nombre de cibles de complexes (plus de 1000) et permettra d'améliorer les méthodes de docking à partir des structures expérimentales ou de modèles.En termes d'applications, je me investis dans différents projets collaboratifs, qui touchent des domaines aussi variés que, la recherche de partenaires pour le chaperon d’histone Asf1; la prédiction des modes d’interaction entre CENP-F et Nup133 dans le contexte de la mitose et de Exo70 et Abi dans celui de la régulation de la mobilité cellulaire; la simulation des modes de liaison entre le complexe Ku et ses partenaires peptidiques, dans les voies de réparation de l'ADN.Protein-protein interactions (PPIs) play essential roles in life. My PhD work aimed at developing advanced bioinformatics methods in the field of PPI prediction at the structural scale. My goal was to improve the predictive power of methods which model the structures of macromolecular assemblies (docking) and to tackle real-life problems faced by biologists.First, I developed HHalign-Kbest server using algorithms for the search of suboptimal solutions to gain better-quality models. Second, in the field of protein docking, I built InterEvDock server which can take co-evolutionary information into account. It yields better performance than other state-of-the-art servers. In order to further test our methods, we participated in CAPRI – an international challenge for prediction of protein interactions. Over years 2013-2016, our group ranked 1st at the 6th CAPRI evaluation meeting. At last, I developed a realistic benchmark dataset PPI4DOCK, largest dataset so far, in order to improve docking methods for the scientific community.In terms of applications, I was involved in a variety of collaborative projects with different labs. As representative examples, I searched for binding partners of the histone chaperone Asf1; I studied the CENP-F/Nup133 interaction in the context of mitosis and the Exo70/Abi interaction related to cell mobility regulation; I also simulated the binding modes of multiple peptides, partners of Ku complex involved in DNA repair pathway