Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs.

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

Single-cell sequencing of the substantia nigra reveals microglial activation in a model of MPTP.

Background: N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on the cells and genes of PD has not been fully elucidated. Methods: Single-nucleus RNA sequencing was performed in the Substantia Nigra (SN) of MPTP mice. UMAP analysis was used for the dimensionality reduction visualization of the SN in the MPTP mice. Known marker genes highly expressed genes in each cluster were used to annotate most clusters. Specific Differentially Expressed Genes (DEGs) and PD risk genes analysis were used to find MPTP-associated cells. GO, KEGG, PPI network, GSEA and CellChat analysis were used to reveal cell type-specific functional alterations and disruption of cell-cell communication networks. Subset reconstruction and pseudotime analysis were used to reveal the activation status of the cells, and to find the transcription factors with trajectory characterized. Results: Initially, we observed specific DEGs and PD risk genes enrichment in microglia. Next, We obtained the functional phenotype changes in microglia and found that IGF, AGRN and PTN pathways were reduced in MPTP mice. Finally, we analyzed the activation state of microglia and revealed a pro-inflammatory trajectory characterized by transcription factors Nfe2l2 and Runx1. Conclusion: Our work revealed alterations in microglia function, signaling pathways and key genes in the SN of MPTP mice.

The Peer Review Process: Past, Present, and Future.

The peer review process is a fundamental aspect of modern scientific paper publishing, underpinning essential quality control. First conceptualised in the 1700s, it is an iterative process that aims to elevate scientific literature to the highest standards whilst preventing publication of scientifically unsound, potentially misleading, and even plagiarised information. It is widely accepted that the peer review of scientific papers is an irreplaceable and fundamental aspect of the research process. However, the rapid growth of research and technology has led to a huge increase in the number of publications. This has led to increased pressure on the peer review system. There are several established peer review methodologies, ranging from single and double blind to open and transparent review, but their implementation across journals and research fields varies greatly. Some journals are testing entirely novel approaches (such as collaborative reviews), whilst others are piloting changes to established methods. Given the unprecedented growth in publication numbers, and the ensuing burden on journals, editors, and reviewers, it is imperative to improve the quality and efficiency of the peer review process. Herein we evaluate the peer review process, from its historical origins to current practice and future directions.

Candidate tumor-specific CD8+ T cell subsets identified in the malignant pleural effusion of advanced lung cancer patients by single-cell analysis.

Isolation of tumor-specific T cells and their antigen receptors (TCRs) from malignant pleural effusions (MPE) may facilitate the development of TCR-transduced adoptive cellular immunotherapy products for advanced lung cancer patients. However, the characteristics and markers of tumor-specific T-cells in MPE are largely undefined. To this end, to establish the phenotypes and antigen specificities of CD8+ T cells, we performed single-cell RNA and TCR sequencing of samples from three advanced lung cancer patients. Dimensionality reduction on a total of 4,983 CD8+ T cells revealed 10 clusters including naïve, memory, and exhausted phenotypes. We focused particularly on exhausted T cell clusters and tested their TCR reactivity against neoantigens predicted from autologous cancer cell lines. Four different TCRs specific for the same neoantigen and one orphan TCR specific for the autologous cell line were identified from one of the patients. Differential gene expression analysis in tumor-specific T cells relative to the other T cells identified CXCL13, as a candidate gene expressed by tumor-specific T cells. In addition to expressing CXCL13, tumor-specific T cells were present in a higher proportion of T cells co-expressing PDCD1(PD-1)/TNFRSF9(4-1BB). Furthermore, flow cytometric analyses in advanced lung cancer patients with MPE documented that those with high PD-1/4-1BB expression have a better prognosis in the subset of 57 adenocarcinoma patients (p = .039). These data suggest that PD-1/4-1BB co-expression might identify tumor-specific CD8+ T cells in MPE, which are associated with patients' prognosis. (233 words).

Predictive genetic panel for adult asthma using machine learning methods.

Background: Asthma is a chronic inflammatory disease of the airways that is heterogeneous and multifactorial, making its accurate characterization a complex process. Therefore, identifying the genetic variations associated with asthma and discovering the molecular interactions between the omics that confer risk of developing this disease will help us to unravel the biological pathways involved in its pathogenesis. Objective: We sought to develop a predictive genetic panel for asthma using machine learning methods. Methods: We tested 3 variable selection methods: Boruta's algorithm, the top 200 genome-wide association study markers according to their respective P values, and an elastic net regression. Ten different algorithms were chosen for the classification tests. A predictive panel was built on the basis of joint scores between the classification algorithms. Results: Two variable selection methods, Boruta and genome-wide association studies, were statistically similar in terms of the average accuracies generated, whereas elastic net had the worst overall performance. The predictive genetic panel was completed with 155 single-nucleotide variants, with 91.18% accuracy, 92.75% sensitivity, and 89.55% specificity using the support vector machine algorithm. The markers used range from known single-nucleotide variants to those not previously described in the literature. Our study shows potential in creating genetic prediction panels with tailored penalties per marker, aiding in the identification of optimal machine learning methods for intricate results. Conclusions: This method is able to classify asthma and nonasthma effectively, proving its potential utility in clinical prediction and diagnosis.

Functional variation among mesenchymal stem cells derived from different tissue sources.

Background: Mesenchymal stem cells (MSCs) are increasingly recognized for their regenerative potential. However, their clinical application is hindered by their inherent variability, which is influenced by various factors, such as the tissue source, culture conditions, and passage number. Methods: MSCs were sourced from clinically relevant tissues, including adipose tissue-derived MSCs (ADMSCs, n = 2), chorionic villi-derived MSCs (CMMSCs, n = 2), amniotic membrane-derived MSCs (AMMSCs, n = 3), and umbilical cord-derived MSCs (UCMSCs, n = 3). Passages included the umbilical cord at P0 (UCMSCP0, n = 2), P3 (UCMSCP3, n = 2), and P5 (UCMSCP5, n = 2) as well as the umbilical cord at P5 cultured under low-oxygen conditions (UCMSCP5L, n = 2). Results: We observed that MSCs from different tissue origins clustered into six distinct functional subpopulations, each with varying proportions. Notably, ADMSCs exhibited a higher proportion of subpopulations associated with vascular regeneration, suggesting that they are beneficial for applications in vascular regeneration. Additionally, CMMSCs had a high proportion of subpopulations associated with reproductive processes. UCMSCP5 and UCMSCP5L had higher proportions of subpopulations related to female reproductive function than those for earlier passages. Furthermore, UCMSCP5L, cultured under low-oxygen (hypoxic) conditions, had a high proportion of subpopulations associated with pro-angiogenic characteristics, with implications for optimizing vascular regeneration. Conclusions: This study revealed variation in the distribution of MSC subpopulations among different tissue sources, passages, and culture conditions, including differences in functions related to vascular and reproductive system regeneration. These findings hold promise for personalized regenerative medicine and may lead to more effective clinical treatments across a spectrum of medical conditions.

Optimizing Integrated-Loss Capacities via Asymmetric Electronic Environments for Highly Efficient Electromagnetic Wave Absorption.

Asymmetric electronic environments based on microscopic-scale perspective have injected infinite vitality in understanding the intrinsic mechanism of polarization loss for electromagnetic (EM) wave absorption, but still exists a significant challenge. Herein, Zn single-atoms (SAs), structural defects, and Co nanoclusters are simultaneously implanted into bimetallic metal-organic framework derivatives via the two-step dual coordination-pyrolysis process. Theoretical simulations and experimental results reveal that the electronic coupling interactions between Zn SAs and structural defects delocalize the symmetric electronic environments and generate additional dipole polarization without sacrificing conduction loss owing to the compensation of carbon nanotubes. Moreover, Co nanoclusters with large nanocurvatures induce a strong interfacial electric field, activate the superiority of heterointerfaces and promote interfacial polarization. Benefiting from the aforementioned merits, the resultant derivatives deliver an optimal reflection loss of -58.9 dB and the effective absorption bandwidth is 5.2 GHz. These findings provide an innovative insight into clarifying the microscopic loss mechanism from the asymmetric electron environments viewpoint and inspire the generalized electronic modulation engineering in optimizing EM wave absorption.

Design of Atomically Dispersed CoN4 Sites and Co Clusters for Synergistically Enhanced Oxygen Reduction Electrocatalysis.

Constructing dual-site catalysts consisting of atomically dispersed metal single atoms and metal atomic clusters (MACs) is a promising approach to further boost the catalytic activity for oxygen reduction reaction (ORR). Herein, a porous CoSA-AC@SNC featuring the coexistence of Co single-atom sites (CoN4) and S-coordinated Co atomic clusters (SCo6) in S, N co-doped carbon substrate is successfully synthesized by using porphyrinic metal-organic framework (Co-TPyP MOF) as the precursor. The introduction of the sulfur source creates abundant microstructural defects to anchor Co metal clusters, thus modulating the electronic structure of its surrounding carbon substrate. The synergistic effect between the two types of active sites and structural advantages, in turn, results in high ORR performance of CoSA-AC@SNC with half-wave potential (E1/2) of 0.86 V and Tafel slope of 50.17 mV dec-1. Density functional theory (DFT) calculations also support the synergistic effect between CoN4 and SCo6 by detailing the catalytic mechanism for the improved ORR performance. The as-fabricated Zn-air battery (ZAB) using CoSA-AC@SNC demonstrates impressive peak power density of 174.1 mW cm-2 and charge/discharge durability for 148 h. This work provides a facile synthesis route for dual-site catalysts and can be extended to the development of other efficient atomically dispersed metal-based electrocatalysts.

Spatial heterogeneity and functional zonation of living tissues and organs in situ.

In most organs, resources such as nutrients, oxygen, and physiologically active substances are unevenly supplied within the tissue spaces. Consequently, different tissue functions are exhibited in each space. This spatial heterogeneity of tissue environments arises depending on the spatial arrangement of nutrient vessels and functional vessels, leading to continuous changes in the metabolic states and functions of various cell types from regions proximal to these vessels to distant regions. This phenomenon is referred to as "zonation". Traditional analytical methods have made it difficult to investigate this zonation in detail. However, recent advancements in intravital imaging, spatial transcriptomics, and single-cell transcriptomics technologies have facilitated the discovery of "zones" in various organs and elucidated their physiological roles. Here, we outline the spatial differences in the immune system within each zone of organs. This information provides a deeper understanding of organs' immune systems.

Long-term retention and survival of cemented implant-supported zirconia and metal-ceramic single crowns: A retrospective study.

OBJECTIVES: To evaluate the effect of different cement types on the incidence of failure and loss of retention of zirconia and metal-ceramic single crowns (SCs) cemented on implant abutments. METHODS: We placed 567 implant-supported SCs in 358 patients and retrospectively evaluated long-term retention for up to 12.8 years. The frameworks were made from metal alloy (n = 307) or zirconia (n = 260). SCs were cemented with permanent (glass-ionomer cement; n = 376) or semipermanent cement (zinc oxide non-eugenol cement; n = 191) on standardized (n = 446) or customized (n = 121) abutments. Kaplan-Meier curves were used to calculate the incidence of decementation. Differences between survival curves were assessed with log-rank tests. Cox-regression analysis was performed to evaluate multiple risk factors. RESULTS: Of the 567 SCs, 22 failed because of technical complications and four because of implant loss. Loss of retention was observed in 50 SCs. Analysis revealed a 7% probability of loss of retention for zirconia and 16% for metal-ceramic SCs after 10 years (p = .011). After 5 years, loss of retention was higher for standardized abutments than for customized abutments (p = .014). The probability of loss of retention was higher with semipermanent than with permanent cement (p = .001). Cox-regression analysis revealed semipermanent cement as the only significant risk factor for SC failure (p = .026). CONCLUSIONS: In contrast to semipermanent cement, permanent cement provides acceptable long-term retention of cemented implant-supported SCs. These possible positive effects of customized abutments have to be controlled with larger sample sizes.

Organolanthanide Single-Molecule Magnets with Heterocyclic Ligands.

Lanthanide (Ln) based mononuclear single-molecule magnets (SMMs) provide probably the finest ligand regulation model for magnetic property. Recently, the development of such SMMs has witnessed a fast transition from coordination to organometallic complexes because the latter provides a fertile, yet not fully excavated soil for the development of SMMs. Especially those SMMs with heterocyclic ligands have shown the potential to reach higher blocking temperature. In this minireview, we give an overview of the design principle of SMMs and highlight those "shining stars" of heterocyclic organolanthanide SMMs based on the ring sizes of ligands, analysing how the electronic structures of those ligands and the stiffness of subsequently formed molecules affect the dynamic magnetism of SMMs. Finally, we envisaged the future development of heterocyclic Ln-SMMs.

A Comparison of Ductal Stenting and Surgical Shunts for Infants with Duct-Dependent Pulmonary Blood Flow: The Impact of Single Versus Biventricular Repair Pathways on Outcomes.

Ductal stenting (DS) is an alternative to the Blalock-Taussig-Thomas Shunt (BTTS) as initial palliation for congenital heart disease with duct-dependent pulmonary blood flow (DDBPF). We sought to analyze the impact of intended single ventricle (SV) and biventricular (BiV) repair pathways on the outcome of DS and BTTS in infants with DDPBF. A single-center, retrospective comparison of infants with DDPBF who underwent either DS (2012-2022) or BTTS procedures (2013-2017). Primary outcomes included all-cause mortality and risk of unplanned re-intervention. Participants were divided into four groups: 1.SV with DS, 2.SV with BTTS, 3.BiV with DS, and 4.BiV with BTTS. Fifty-one DS (SV 45%) and 86 BTTS (SV 49%) procedures were undertaken. For those who had DS, mortality was lower in the BiV compared to SV patients (BiV: 0/28, versus SV: 4/23, p = 0.04). Compared to BiV DS, BiV BTTS had a higher risk of combined death or unplanned re-intervention (HR 4.28; CI 1.25-14.60; p = 0.02). In SV participants, there was no difference for either primary outcome based on procedure type. DS was associated with shorter intensive care length of stay for SV participants (mean difference 5 days, p = 0.01) and shorter intensive care and hospital stay for BiV participants (mean difference 11 days for both outcomes, p = 0.001). There is a survival benefit for DS in BiV participants compared with DS in SV and BTTS in BiV participants. Ductal stenting is associated with a shorter intensive care and hospital length of stay.

The heterogeneity of erythroid cells: insight at the single-cell transcriptome level.

Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.

Single Cell Transcriptome Analysis During Development in Dictyostelium.

Dictyostelium represents a stripped-down model for understanding how cells make decisions during development. The complete life cycle takes around a day and the fully differentiated structure is composed of only two major cell types. With this apparent reduction in "complexity," single cell transcriptomics has proven to be a valuable tool in defining the features of developmental transitions and cell fate separation events, even providing causal information on how mechanisms of gene expression can feed into cell decision-making. These scientific outputs have been strongly facilitated by the ease of non-disruptive single cell isolation-allowing access to more physiological measures of transcript levels. In addition, the limited number of cell states during development allows the use of more straightforward analysis tools for handling the ensuing large datasets, which provides enhanced confidence in inferences made from the data. In this chapter, we will outline the approaches we have used for handling Dictyostelium single cell transcriptomic data, illustrating how these approaches have contributed to our understanding of cell decision-making during development.

A Novel Detection Method for High-Order SNP Epistatic Interactions Based on Explicit-Encoding-Based Multitasking Harmony Search.

To elucidate the genetic basis of complex diseases, it is crucial to discover the single-nucleotide polymorphisms (SNPs) contributing to disease susceptibility. This is particularly challenging for high-order SNP epistatic interactions (HEIs), which exhibit small individual effects but potentially large joint effects. These interactions are difficult to detect due to the vast search space, encompassing billions of possible combinations, and the computational complexity of evaluating them. This study proposes a novel explicit-encoding-based multitasking harmony search algorithm (MTHS-EE-DHEI) specifically designed to address this challenge. The algorithm operates in three stages. First, a harmony search algorithm is employed, utilizing four lightweight evaluation functions, such as Bayesian network and entropy, to efficiently explore potential SNP combinations related to disease status. Second, a G-test statistical method is applied to filter out insignificant SNP combinations. Finally, two machine learning-based methods, multifactor dimensionality reduction (MDR) as well as random forest (RF), are employed to validate the classification performance of the remaining significant SNP combinations. This research aims to demonstrate the effectiveness of MTHS-EE-DHEI in identifying HEIs compared to existing methods, potentially providing valuable insights into the genetic architecture of complex diseases. The performance of MTHS-EE-DHEI was evaluated on twenty simulated disease datasets and three real-world datasets encompassing age-related macular degeneration (AMD), rheumatoid arthritis (RA), and breast cancer (BC). The results demonstrably indicate that MTHS-EE-DHEI outperforms four state-of-the-art algorithms in terms of both detection power and computational efficiency. The source code is available at https://github.com/shouhengtuo/MTHS-EE-DHEI.git .

In Vivo Exposure Pathways of Ambient Magnetite Nanoparticles Revealed by Machine Learning-Aided Single-Particle Mass Spectrometry.

Nanosized ultrafine particles (UFPs) from natural and anthropogenic sources are widespread and pose serious health risks when inhaled by humans. However, tracing the inhaled UFPs in vivo is extremely difficult, and the distribution, translocation, and metabolism of UFPs remain unclear. Here, we report a label-free, machine learning-aided single-particle inductively coupled plasma mass spectrometry (spICP-MS) approach for tracing the exposure pathways of airborne magnetite nanoparticles (MNPs), including external emission sources, and distribution and translocation in vivo using a mouse model. Our results provide quantitative analysis of different metabolic pathways in mice exposed to MNPs, revealing that the spleen serves as the primary site for MNP metabolism (84.4%), followed by the liver (11.4%). The translocation of inhaled UFPs across different organs alters their particle size. This work provides novel insights into the in vivo fate of UFPs as well as a versatile and powerful platform for nanotoxicology and risk assessment.

Association of polymorphisms within P2RX4 with type 2 diabetes mellitus: a preliminary case-control study.

OBJECTIVE: Type 2 diabetes mellitus (T2DM) is a complex heterogenic metabolic with a wide range of etiology. Purinergic receptors have pivotal roles in different processes and are hypothesized to have roles in the pathogenesis of T2DM. MATERIALS AND METHODS: Three hundred subjects affected by T2DM and 300 healthy subjects were genotyped by amplification refractory mutation system polymerase chain reaction (ARMS-PCR). SPSS V16.0 was recruited for statistical analysis. RESULTS: The findings showed that the G allele of rs25644A > G increases the risk of T2DM in our population statistically (OR = 1.51, 95% CI = 1.14-1.99, p = 0.003). This allele in some genotype models, including the dominant model, caused an increase in the risk of T2DM. The interaction of genotypes between studied variants in the P2XR4 gene increased the risk of T2DM. Haplotype analysis showed that Ars1169727/Grs25644 haplotype caused an increase in the risk of T2DM. CONCLUSIONS: The findings suggest that rs25644A > G plays a role in our population's increased risk of T2DM.

Investigation of structural, optical and mechanical behaviour of pure and Cr doped L-asparagine monohydrate single crystals.

Pure and chromium (Cr) doped L-asparagine monohydrate (LAM) single crystals were grown by using evaporation controlled solution growth technique. XRD analysis confirmed the orthorhombic crystal system with space group P212121 of grown crystals. Cr-incorporation decreased the cell parameters and unit cell volume of the crystals. Intermolecular interactions were analysed through Hirshfeld and fingerprint studies. SEM analysis showed the appearance of pits on the smooth surface of pure crystal due to Cr-addition. UV-Vis analysis showed high transparency, low cut-off and direct band gap of 5.42 eV and 5.51 eV for pure and Cr doped crystals, respectively. Fundamental functional groups were identified by FTIR and Raman spectroscopy. The thermal stability and melting point of the crystals were investigated using TGA/DSC analysis. The dielectric constant for doped LAM was increased to 44 as compare to dielectric constant of pure crystal which was 32. Both crystals showed low dielectric loss, having values 0.04 and 0.006 for pure LAM and doped crystals, respectively. In Vickers microhardness test, Cr doping was found to change the nature of pure LAM crystal from 'soft' to 'hard' as Meyer's index changed from 2.48 to 1.24.

Mapping and spectroscopy of telecom quantum emitters with confocal laser scanning microscopy.

Efficiently coupling single-photon emitters in the telecommunication C-band that are not deterministically positioned to photonic structures requires both spatial and spectral mapping. This study introduces the photoluminescence mapping of telecom C-band self-assembled quantum dots (QDs) by confocal laser scanning microscopy, a technique previously unexplored in this wavelength range which fulfills these two requirements. We consider the effects of distortions inherent to any imaging system but largely disregarded in prior works to derive accurate coordinates from photoluminescence maps. We obtain a position uncertainty below 11 nm for 10\% of the QDs when assuming no distortions, highlighting the potential of the scanning approach. After distortion correction, we found that the previously determined positions are on average shifted by 428 nm from the corrected positions, demonstrating the necessity of this correction for accurate positioning. Then, through error propagation, the position uncertainty for 10\% of the QDs increases to 110 nm.

Quantitative risk assessment for the introduction of bluetongue virus into mainland Europe by long-distance wind dispersal of Culicoides spp.: A case study from Sardinia.

Europe faces regular introductions and reintroductions of bluetongue virus (BTV) serotypes, most recently exemplified by the incursion of serotype 3 in the Netherlands. Although the long-distance wind dispersal of the disease vector, Culicoides spp., is recognized as a virus introduction pathway, it remains understudied in risk assessments. A Quantitative Risk Assessment framework was developed to estimate the risk of BTV-3 incursion into mainland Europe from Sardinia, where the virus has been present since 2018. We used an atmospheric transport model (HYbrid Single-Particle Lagrangian Integrated Trajectory) to infer the probability of airborne dispersion of the insect vector. Epidemiological disease parameters quantified the virus prevalence in vector population in Sardinia and its potential first transmission after introduction in a new area. When assuming a 24h maximal flight duration, the risk of BTV introduction from Sardinia is limited to the Mediterranean Basin, mainly affecting the southwestern area of the Italian Peninsula, Sicily, Malta, and Corsica. The risk extends to the northern and central parts of Italy, Balearic archipelago, and mainland France and Spain, mostly when maximal flight duration is longer than 24h. Additional knowledge on vector flight conditions and Obsoletus complex-specific parameters could improve the robustness of the model. Providing both spatial and temporal insights into BTV introduction risks, our framework is a key tool to guide global surveillance and preparedness against epizootics.