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Weil, A.

Publications and source records attributed to Weil, A..

6 recordsLinked to original sources

Precision mapping and molecular contextualization of surgical outcome epicenters in temporal lobe epilepsy

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy is the most common drug-resistant epilepsy, with surgical resection offering the primary path to seizure freedom. Despite standardized approaches, a substantial proportion of patients experience seizure recurrence, and the neurobiological substrates underlying these divergent outcomes remain unclear. We applied an individualized normative modeling framework to multimodal preoperative MRI data in a group that subsequently underwent surgical resection, to characterize patient-specific structural deviations and identify disease epicenters. Patients who became seizure-free exhibited spatially coherent abnormalities localized to the hippocampus and ipsilateral association regions, anchored in agranular limbic territories and enriched for genes linked to calcium-dependent signaling. Non-seizure-free patients, on the other hand, showed a more heterogeneous and distributed pattern of deviations, consistent with a "temporal-plus" network organization, and broader neuromodulatory dysregulation. Crucially, overlap between resected tissue and network-defined epicenters was closely associated with seizure freedom, independent of total resection volume. These findings provide a multiscale framework for precision surgical planning, shifting the focus from standardized tissue removal to targeted disconnection of patient-specific pathological hubs.

neuroscience↗

The use of Artificial Intelligence in Magnetic Resonance Imaging of Epilepsy: A Systematic Review and Meta-Analysis

BackgroundThe application of artificial intelligence (AI)/machine learning (ML) to MRI can be a powerful tool to streamline clinical decision-making, yet variability amongst MRI sequences and algorithms have hindered appropriate assessment of reliability and generalizability. MethodsWe conducted a systematic review and meta-analysis of the ability of current AI/ML models operating on MRI data for: 1) epilepsy diagnosis, 2) temporal lobe epilepsy lateralization, 3) lesion localization, and 4) post-surgical outcome prediction. Searches were conducted across PubMed, Medline, and Embase databases from inception until January 1, 2025. We selected studies that employed AI/ML models trained on any MRI modality to classify at least ten patients across the four main objectives for qualitative assessment, and further included in the meta-analysis if they reported an accuracy rate. The primary outcome of the meta-analysis was the overall accuracy of AI/ML models trained on MRI data. The secondary outcome was the concomitant risk of bias evaluation using PROBAST. FindingsWe identified 158 studies for qualitative evaluation and 127 studies for inclusion in the meta-analysis. AI/ML on multimodal MRI could accurately distinguish epilepsy patients from healthy controls (overall accuracy: 88% [85-90]), lateralize temporal lobe epilepsy (90% [87-93]), localize epileptogenic lesions (82% [74-88]), and predict post-surgical seizure-freedom (83% [78-87]). Overall, a high risk of bias remains in the literature; participant bias remained high across all outcomes (64-87%), as well as predictor (88-100%) and analysis (83-100%) bias. Outcome bias was low only for AI/ML studies predicting post-surgical outcomes. InterpretationOur results support promising accuracy of AI/ML models in epilepsy diagnostics and prognostics but remain highly susceptible to bias in participants, predictors, outcome, and analysis domains which limits current translation to routine clinical practice. We encourage closer interdisciplinary collaboration between clinical and scientific groups to improve validation studies based on thorough study design, analysis, and reporting.

neuroscience↗

Differential reorganization of episodic and semantic memory systems in epilepsy-related mesiotemporal pathology

Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, while semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE), as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE as well as 60 age and sex-matched healthy controls and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, both in the MTL and in neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. In the neocortex, alterations were characterized by reduced functional differentiation in patients in lateral temporal and midline parietal cortices in both hemispheres. In the MTL, on the other hand, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, while hippocampal functional topographies were unaffected. Leveraging MRI proxies of MTL pathology, we furthermore observed alterations in hippocampal microstructure and morphology are associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic, but again not semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, while episodic processes are supported by a network involving both the hippocampus and neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.

neuroscience↗

CRISPR/Cas9 generated MeSWEET10a mutants show reduced susceptibility to cassava bacterial blight and produce viable seed

Bacteria from the genus Xanthomonas are prolific phytopathogens that elicit disease in over 400 plant species. Xanthomonads carry a repertoire of specialized proteins called transcription activator-like (TAL) effectors that promote disease and pathogen virulence by inducing expression of host susceptibility (S) genes. Xanthomonas phaseoli pv. manihotis (Xpm) causes bacterial blight on the staple food crop, cassava. The Xpm effector, TAL20, induces ectopic expression of the S gene, MeSWEET10a, a sugar transporter that contributes to cassava bacterial blight susceptibility. We used CRISPR/Cas9 to generate multiple cassava lines with edits to the MeSWEET10a TAL20 effector binding site and/or coding sequence. In several of the regenerated lines, MeSWEET10a expression was no longer induced by Xpm and in these cases, we observed reduced cassava bacterial blight disease symptoms post Xpm infection. MeSWEET10a is expressed in cassava flowers. Therefore, we investigated flower development and reproductive function in an MeSWEET10a mutant line. We found that the MeSWEET10a mutant produced phenotypically wildtype cassava flowers and viable F1 seed. Thus, blocking MeSWEET10a induction is a viable strategy for decreasing cassava susceptibility to CBB.

plant biology↗

Recurrence of cancer cell states across diverse tumors and their interactions with the microenvironment

While genetic tumor heterogeneity has long been recognized, recent work has revealed significant variation among cancer cells at the epigenetic and transcriptional levels. Profiling tumors at the single-cell level in individual cancer types has shown that transcriptional heterogeneity is organized into cancer cell states, implying that diverse cell states may represent stable and functional units with complementary roles in tumor maintenance and progression. However, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Furthermore, the role of cancer cell states in tumor progression and their specific interactions with cells of the tumor microenvironment remain to be elucidated. Here, we perform a pan-cancer single-cell RNA-Seq analysis across 15 cancer types and identify a catalog of 16 gene modules whose expression defines recurrent cancer cell states, including stress, interferon response, epithelial-mesenchymal transition, metal response, basal and ciliated. Using mouse models, we find that induction of the interferon response module varies by tumor location and is diminished upon elimination of lymphocytes. Moreover, spatial transcriptomic analysis further links the interferon response in cancer cells to T cells and macrophages in the tumor microenvironment. Our work provides a framework for studying how cancer cell states interact with the tumor microenvironment to form organized systems capable of immune evasion, drug resistance, and metastasis.

cancer biology↗

A new in vitro assay measuring direct interaction of nonsense suppressors with the eukaryotic protein synthesis machinery

Nonsense suppressors (NonSups) induce \"readthrough\", i.e., the selection of near cognate tRNAs at premature termination codons and insertion of the corresponding amino acid into nascent polypeptide. Prior readthrough measurements utilized contexts in which NonSups can promote readthrough directly, by binding to one or more of the components of the protein synthesis machinery, or indirectly, by several other mechanisms. Here we utilize a new, highly-purified in vitro assay to measure exclusively direct nonsense suppressor-induced readthrough. Of 16 NonSups tested, 12 display direct readthrough, with results suggesting that such NonSups act by at least two different mechanisms. In preliminary work we demonstrate the potential of single molecule fluorescence energy transfer measurements to elucidate mechanisms of NonSup-induced direct readthrough, which will aid efforts to identify NonSups having improved clinical efficacy.\n\nTable of Contents artwork\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC=\"FIGDIR/small/330506_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (18K):\norg.highwire.dtl.DTLVardef@a548dborg.highwire.dtl.DTLVardef@15237bcorg.highwire.dtl.DTLVardef@c93d3forg.highwire.dtl.DTLVardef@1d40e2c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗