Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions.

Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters is essential for elucidating complex protein interactions and for the targeted screening of peptide- or protein-based drugs. We introduce MCGLPPI++, a meta-learning framework designed to improve the adaptability of pretrained geometric models in such scenarios. To effectively boost the meta-learning optimization by injecting prior intersample distribution knowledge, three specially designed training sample cluster splitting patterns based on protein interaction interfaces are introduced.

Expert-guided protein language models enable accurate and blazingly fast fitness prediction.

Motivation: Exhaustive experimental annotation of the effect of all known protein variants remains daunting and expensive, stressing the need for scalable effect predictions. We introduce VespaG, a blazingly fast missense amino acid variant effect predictor, leveraging protein language model (pLM) embeddings as input to a minimal deep learning model.

Results: To overcome the sparsity of experimental training data, we created a dataset of 39 million single amino acid variants from the human proteome applying the multiple sequence alignment-based effect predictor GEMME as a pseudo standard-of-truth.

Efficacy of BAFF inhibition and B-cell depletion in non-obese diabetic mice as a spontaneous model for Sjögren's disease.

Introduction: The therapeutic interest of targeting B-cell activating factor (BAFF) in Sjögren's disease (SjD) can be suspected from the results of two phase II clinical trials but has not been evaluated in an animal model of the disease. We aimed to evaluate the therapeutic efficacy of this strategy on dryness and salivary gland (SG) infiltrates in the NOD mouse model of SjD.

Material And Methods: Female NOD mice between ages 10 and 18 weeks were treated with a BAFF-blocking monoclonal antibody, Sandy-2 or an isotype control.

Critical assessment of missense variant effect predictors on disease-relevant variant data.

Regular, systematic, and independent assessment of computational tools used to predict the pathogenicity of missense variants is necessary to evaluate their clinical and research utility and suggest directions for future improvement. Here, as part of the sixth edition of the Critical Assessment of Genome Interpretation (CAGI) challenge, we assess missense variant effect predictors (or variant impact predictors) on an evaluation dataset of rare missense variants from disease-relevant databases. Our assessment evaluates predictors submitted to the CAGI6 Annotate-All-Missense challenge, predictors commonly used by the clinical genetics community, and recently developed deep learning methods for variant effect prediction.

Protein embeddings predict binding residues in disordered regions.

The identification of protein binding residues helps to understand their biological processes as protein function is often defined through ligand binding, such as to other proteins, small molecules, ions, or nucleotides. Methods predicting binding residues often err for intrinsically disordered proteins or regions (IDPs/IDPRs), often also referred to as molecular recognition features (MoRFs). Here, we presented a novel machine learning (ML) model trained to specifically predict binding regions in IDPRs.

Alignment-based Protein Mutational Landscape Prediction: Doing More with Less.

The wealth of genomic data has boosted the development of computational methods predicting the phenotypic outcomes of missense variants. The most accurate ones exploit multiple sequence alignments, which can be costly to generate. Recent efforts for democratizing protein structure prediction have overcome this bottleneck by leveraging the fast homology search of MMseqs2.

Resolving the Scales of the Quark-Gluon Plasma with Energy Correlators.

Jets provide us with ideal probes of the quark-gluon plasma (QGP) produced in heavy-ion collisions, since its dynamics at its different scales is imprinted into the multiscale substructure of the final state jets. We present a new approach to jet substructure in heavy-ion collisions based on the study of correlation functions of energy flow operators. By analyzing the two-point correlator of an in-medium quark jet, we demonstrate that the spectra of correlation functions robustly identify the scales defined by the properties of the QGP, particularly those associated with the onset of color coherence.

LambdaPP: Fast and accessible protein-specific phenotype predictions.

The availability of accurate and fast artificial intelligence (AI) solutions predicting aspects of proteins are revolutionizing experimental and computational molecular biology. The webserver LambdaPP aspires to supersede PredictProtein, the first internet server making AI protein predictions available in 1992. Given a protein sequence as input, LambdaPP provides easily accessible visualizations of protein 3D structure, along with predictions at the protein level (GeneOntology, subcellular location), and the residue level (binding to metal ions, small molecules, and nucleotides; conservation; intrinsic disorder; secondary structure; alpha-helical and beta-barrel transmembrane segments; signal-peptides; variant effect) in seconds.

Modulation of autoimmune diabetes by N-ethyl-N-nitrosourea- induced mutations in non-obese diabetic mice.

Genetic association studies of type 1 diabetes (T1D) in humans, and in congenic non-obese diabetic (NOD) mice harboring DNA segments from T1D-resistant mice, face the challenge of assigning causation to specific gene variants among many within loci that affect disease risk. Here, we created random germline mutations in NOD/NckH mice and used automated meiotic mapping to identify mutations modifying T1D incidence and age of onset. In contrast with association studies in humans or congenic NOD mice, we analyzed a relatively small number of genetic changes in each pedigree, permitting implication of specific mutations as causative.

Embeddings from protein language models predict conservation and variant effects.

The emergence of SARS-CoV-2 variants stressed the demand for tools allowing to interpret the effect of single amino acid variants (SAVs) on protein function. While Deep Mutational Scanning (DMS) sets continue to expand our understanding of the mutational landscape of single proteins, the results continue to challenge analyses. Protein Language Models (pLMs) use the latest deep learning (DL) algorithms to leverage growing databases of protein sequences.

De novo germline mutation in the dual specificity phosphatase 10 gene accelerates autoimmune diabetes.

Insulin-dependent or type 1 diabetes (T1D) is a polygenic autoimmune disease. In humans, more than 60 loci carrying common variants that confer disease susceptibility have been identified by genome-wide association studies, with a low individual risk contribution for most variants excepting those of the major histocompatibility complex (MHC) region (40 to 50% of risk); hence the importance of missing heritability due in part to rare variants. Nonobese diabetic (NOD) mice recapitulate major features of the human disease including genetic aspects with a key role for the MHC haplotype and a series of loci.

Elliptic Flow of Heavy Quarkonia in pA Collisions.

Using the dilute-dense factorization in the color glass condensate framework, we investigate the azimuthal angular correlation between a heavy quarkonium and a charged light hadron in proton-nucleus collisions. We extract the second harmonic v_{2}, commonly known as the elliptic flow, with the light hadron as the reference. This particular azimuthal angular correlation between a heavy meson and a light hadron was first measured at the LHC recently.

Search for Neutrinoless Quadruple-β Decay of ^{150}Nd with the NEMO-3 Detector.

We report the results of a first experimental search for lepton number violation by four units in the neutrinoless quadruple-β decay of ^{150}Nd using a total exposure of 0.19 kg yr recorded with the NEMO-3 detector at the Modane Underground Laboratory. We find no evidence of this decay and set lower limits on the half-life in the range T_{1/2}>(1.

The BiPo-3 detector.

The BiPo-3 detector is a low radioactive detector dedicated to measuring ultra-low natural contaminations of Tl and Bi in thin materials, initially developed to measure the radiopurity of the double β decay source foils of the SuperNEMO experiment at the μBq/kg level. The BiPo-3 technique consists in installing the foil of interest between two thin ultra-radiopure scintillators coupled to low radioactive photomultipliers. The design and performances of the detector are presented.

Regulatory mechanisms of immune tolerance in type 1 diabetes and their failures.

In this brief review we propose to discuss salient data showing the importance of immune regulatory mechanisms, and in particular of Treg, for the control of pathogenic anti-β-cell response in autoimmune diabetes. Disease progression that culminates with the massive destruction of insulin-secreting β-cells and advent of hyperglycemia and glycosuria tightly correlates with a functional deficit in immune regulation. Better dissection of the cellular and molecular mechanisms through which the immune system normally sustains tolerance to "self", and which become defective when autoimmune aggression is overt, is the only direct and robust way to learn how to harness these effectively, so as to restore immune tolerance in patients with insulin-dependent type 1 diabetes.

Control of Immune Response to Allogeneic Embryonic Stem Cells by CD3 Antibody-Mediated Operational Tolerance Induction.

Implantation of embryonic stem cells (ESCs) and their differentiated derivatives into allogeneic hosts triggers an immune response that represents a hurdle to clinical application. We established in autoimmunity and in transplantation that CD3 antibody therapy induces a state of immune tolerance. Promising results have been obtained with CD3 antibodies in the clinic.

Antibiotics in early life alter the gut microbiome and increase disease incidence in a spontaneous mouse model of autoimmune insulin-dependent diabetes.

Insulin-dependent or type 1 diabetes is a prototypic autoimmune disease whose incidence steadily increased over the past decades in industrialized countries. Recent evidence suggests the importance of the gut microbiota to explain this trend. Here, non-obese diabetic (NOD) mice that spontaneously develop autoimmune type 1 diabetes were treated with different antibiotics to explore the influence of a targeted intestinal dysbiosis in the progression of the disease.

Evidence of 131I and (134,137)Cs activities in Bordeaux, France due to the Fukushima nuclear accident.

Following the Fukushima nuclear accident, low-background gamma spectrometry measurements were performed with HPGe detectors at the PRISNA platform located at the CENBG laboratory in Bordeaux, France. Different kinds of samples were collected and measured between March 26 and May 14, 2011. The first fission product observed was (131)I with maximum activity values of 2.

Combating employee theft in the healthcare industry.

The healthcare industry is especially susceptible to internal fraud and employee theft, the author's research has found. He presents details of 14 costly healthcare embezzlements that took place in three months and gives insight into schemes employed on the most common types of embezzlement. He also describes proactive steps which can be taken to prevent, detect and respond to this phenomenon as well as providing a primer on conducting an internal theft investigation.

Measurement of the ββ decay half-life of 130Te with the NEMO-3 detector.

We report results from the NEMO-3 experiment based on an exposure of 1275 days with 661 g of (130)Te in the form of enriched and natural tellurium foils. The ββ decay rate of (130)Te is found to be greater than zero with a significance of 7.7 standard deviations and the half-life is measured to be T(½)(2ν) = [7.

Azimuthal correlations of forward dihadrons in d + Au collisions at RHIC in the color glass condensate.

We present a good description of recent experimental data on forward dihadron azimuthal correlations measured in deuteron-gold collisions at the BNL Relativistic Heavy Ion Collider (RHIC), where monojet production has been observed. Our approach is based on the color glass condensate theory for the small-x degrees of freedom of the nuclear wave function, including the use of nonlinear evolution equations with running QCD coupling. Our analysis provides further evidence for the presence of saturation effects in RHIC data.

First results of the search for neutrinoless double-beta decay with the NEMO 3 detector.

The NEMO 3 detector, which has been operating in the Fréjus underground laboratory since February 2003, is devoted to the search for neutrinoless double-beta decay (beta beta 0v). The half-lives of the two neutrino double-beta decay (beta beta 2v) have been measured for 100Mo and 82Se. After 389 effective days of data collection from February 2003 until September 2004 (phase I), no evidence for neutrinoless double-beta decay was found from approximately 7 kg of 100Mo and approximately 1 kg of 82Se.

Rectified motion of colloids in asymmetrically structured channels.

We set micron size particles into macroscopic motion by submitting them to a low frequency electric field (of zero mean value) in a microfabricated channel exhibiting a topological ratchet-like local polarity. Rectification is induced by the coupling between electrophoresis, electroosmosis, and dielectrophoresis. The macroscopic velocities of the particles are functions of the electric field and of the geometry of the channel; they strongly depend on their size which opens the way to potential separations.