Preoperative function-specific connectome analysis predicts surgery-related aphasia after glioma resection.

Glioma resection within language-eloquent regions poses a high risk of surgery-related aphasia (SRA). Preoperative functional mapping by navigated transcranial magnetic stimulation (nTMS) combined with diffusion tensor imaging (DTI) is increasingly used to localize cortical and subcortical language-eloquent areas. This study enrolled 60 nonaphasic patients with left hemispheric perisylvian gliomas to investigate the prediction of SRA based on function-specific connectome network properties under different fractional anisotropy (FA) thresholds. Moreover, we applied a machine learning model for training and cross-validation to predict SRA based on preoperative connectome parameters. Preoperative connectome analysis helps predict SRA development with an accuracy of 73.3% and sensitivity of 78.3%. The current study provides a new perspective of combining nTMS and function-specific connectome analysis applied in a machine learning model to investigate language in neurooncological patients and promises to advance our understanding of the intricate networks.

Elucidating the structural-functional connectome of language in glioma-induced aphasia using nTMS and DTI.

Glioma-induced aphasia (GIA) is frequently observed in patients with newly diagnosed gliomas. Previous studies showed an impact of gliomas not only on local brain regions but also on the functionality and structure of brain networks. The current study used navigated transcranial magnetic stimulation (nTMS) to localize language-related regions and to explore language function at the network level in combination with connectome analysis. Thirty glioma patients without aphasia (NA) and 30 patients with GIA were prospectively enrolled. Tumors were located in the vicinity of arcuate fasciculus-related cortical and subcortical regions. The visualized ratio (VR) of each tract was calculated based on their respective fractional anisotropy (FA) and maximal FA. Using a thresholding method of each tract at 25% VR and 50% VR, DTI-based tractography was performed to construct structural brain networks for graph-based connectome analysis, containing functional data acquired by nTMS. The average degree of left hemispheric networks (Mleft ) was higher in the NA group than in the GIA group for both VR thresholds. Differences of global and local efficiency between 25% and 50% VR thresholds were significantly lower in the NA group than in the GIA group. Aphasia levels correlated with connectome properties in Mleft and networks based on positive nTMS mapping regions (Mpos ). A more substantial relation to language performance was found in Mpos and Mleft compared to the network of negative mapping regions (Mneg ). Gliomas causing deterioration of language are related to various cerebral networks. In NA patients, mainly Mneg was impacted, while Mpos was impacted in GIA patients.

Task-based memory systems in contextual-cueing of visual search and explicit recognition.

Visual search is facilitated when observers encounter targets in repeated display arrangements. This 'contextual-cueing' (CC) effect is attributed to incidental learning of spatial distractor-target relations. Prior work has typically used only one recognition measure (administered after the search task) to establish whether CC is based on implicit or explicit memory of repeated displays, with the outcome depending on the diagnostic accuracy of the test. The present study compared two explicit memory tests to tackle this issue: yes/no recognition of a given search display as repeated versus generation of the quadrant in which the target (which was replaced by a distractor) had been located during the search task, thus closely matching the processes involved in performing the search. While repeated displays elicited a CC effect in the search task, both tests revealed above-chance knowledge of repeated displays, though explicit-memory accuracy and its correlation with contextual facilitation in the search task were more pronounced for the generation task. These findings argue in favor of a one-system, explicit-memory account of CC. Further, they demonstrate the superiority of the generation task for revealing the explicitness of CC, likely because both the search and the memory task involve overlapping processes (in line with 'transfer-appropriate processing').

TRIM25 promotes Capicua degradation independently of ERK in the absence of ATXN1L.

BACKGROUND: Aberrations in Capicua (CIC) have recently been implicated as a negative prognostic factor in a multitude of cancer types through the derepression of targets downstream of the mitogen-activated protein kinase (MAPK) signaling cascade, such as oncogenic E26 transformation-specific (ETS) transcription factors. The Ataxin-family protein ATXN1L has previously been reported to interact with CIC in both developmental and disease contexts to facilitate the repression of CIC target genes and promote the post-translational stability of CIC. However, little is known about the mechanisms at the base of ATXN1L-mediated CIC post-translational stability. RESULTS: Functional in vitro studies utilizing ATXN1LKO human cell lines revealed that loss of ATXN1L leads to the accumulation of polyubiquitinated CIC protein, promoting its degradation through the proteasome. Although transcriptomic signatures of ATXN1LKO cell lines indicated upregulation of the mitogen-activated protein kinase pathway, ERK activity was found to contribute to CIC function but not stability. Degradation of CIC protein following loss of ATXN1L was instead observed to be mediated by the E3 ubiquitin ligase TRIM25 which was further validated using glioma-derived cell lines and the TCGA breast carcinoma and liver hepatocellular carcinoma cohorts. CONCLUSIONS: The post-translational regulation of CIC through ATXN1L and TRIM25 independent of ERK activity suggests that the regulation of CIC stability and function is more intricate than previously appreciated and involves several independent pathways. As CIC status has become a prognostic factor in several cancer types, further knowledge into the mechanisms which govern CIC stability and function may prove useful for future therapeutic approaches.