Evolutionary Strategies Enable Systematic and Reliable Uncertainty Quantification: A Proof-of-Concept Pilot Study on Resting-State Functional MRI Language Lateralization.

Reliable and trustworthy artificial intelligence (AI), particularly in high-stake medical diagnoses, necessitates effective uncertainty quantification (UQ). Existing UQ methods using model ensembles often introduce invalid variability or computational complexity, rendering them impractical and ineffective in clinical workflow. We propose a UQ approach based on deep neuroevolution (DNE), a data-efficient optimization strategy. Our goal is to replicate trends observed in expert-based UQ. We focused on language lateralization maps from resting-state functional MRI (rs-fMRI). Fifty rs-fMRI maps were divided into training/testing (30:20) sets, representing two labels: "left-dominant" and "co-dominant." DNE facilitated acquiring an ensemble of 100 models with high training and testing set accuracy. Model uncertainty was derived from distribution entropies over the 100 model predictions. Expert reviewers provided user-based uncertainties for comparison. Model (epistemic) and user-based (aleatoric) uncertainties were consistent in the independently and identically distributed (IID) testing set, mainly indicating low uncertainty. In a mostly out-of-distribution (OOD) holdout set, both model and user-based entropies correlated but displayed a bimodal distribution, with one peak representing low and another high uncertainty. We also found a statistically significant positive correlation between epistemic and aleatoric uncertainties. DNE-based UQ effectively mirrored user-based uncertainties, particularly highlighting increased uncertainty in OOD images. We conclude that DNE-based UQ correlates with expert assessments, making it reliable for our use case and potentially for other radiology applications.

Fibration symmetry-breaking supports functional transitions in a brain network engaged in language.

In his book 'A Beautiful Question' 1, physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures 1-4. While symmetry is a cornerstone of physics, it has not yet been found widespread applicability to describe biological systems 5, particularly the human brain. In this context, we study the human brain network engaged in language and explore the relationship between the structural connectivity (connectome or structural network) and the emergent synchronization of the mesoscopic regions of interest (functional network). We explain this relationship through a different kind of symmetry than physical symmetry, derived from the categorical notion of Grothendieck fibrations 6. This introduces a new understanding of the human brain by proposing a local symmetry theory of the connectome, which accounts for how the structure of the brain's network determines its coherent activity. Among the allowed patterns of structural connectivity, synchronization elicits different symmetry subsets according to the functional engagement of the brain. We show that the resting state is a particular realization of the cerebral synchronization pattern characterized by a fibration symmetry that is broken 7 in the transition from rest to language. Our findings suggest that the brain's network symmetry at the local level determines its coherent function, and we can understand this relationship from theoretical principles.

Tumors Affect the Metabolic Connectivity of the Human Brain Measured by 18 F-FDG PET.

PURPOSE: 18 F-FDG PET captures the relationship between glucose metabolism and synaptic activity, allowing for modeling brain function through metabolic connectivity. We investigated tumor-induced modifications of brain metabolic connectivity. PATIENTS AND METHODS: Forty-three patients with left hemispheric tumors and 18 F-FDG PET/MRI were retrospectively recruited. We included 37 healthy controls (HCs) from the database CERMEP-IDB-MRXFDG. We analyzed the whole brain and right versus left hemispheres connectivity in patients and HC, frontal versus temporal tumors, active tumors versus radiation necrosis, and patients with high Karnofsky performance score (KPS = 100) versus low KPS (KPS < 70). Results were compared with 2-sided t test ( P < 0.05). RESULTS: Twenty high-grade glioma, 4 low-grade glioma, and 19 metastases were included. The patients' whole-brain network displayed lower connectivity metrics compared with HC ( P < 0.001), except assortativity and betweenness centrality ( P = 0.001). The patients' left hemispheres showed decreased similarity, and lower connectivity metrics compared with the right ( P < 0.01), with the exception of betweenness centrality ( P = 0.002). HC did not show significant hemispheric differences. Frontal tumors showed higher connectivity metrics ( P < 0.001) than temporal tumors, but lower betweenness centrality ( P = 4.5 -7 ). Patients with high KPS showed higher distance local efficiency ( P = 0.01), rich club coefficient ( P = 0.0048), clustering coefficient ( P = 0.00032), betweenness centrality ( P = 0.008), and similarity ( P = 0.0027) compared with low KPS. Patients with active tumor(s) (14/43) demonstrated significantly lower connectivity metrics compared with necroses. CONCLUSIONS: Tumors cause reorganization of metabolic brain networks, characterized by formation of new connections and decreased centrality. Patients with frontal tumors retained a more efficient, centralized, and segregated network than patients with temporal tumors. Stronger metabolic connectivity was associated with higher KPS.

Operando double-edge high-resolution X-ray absorption spectroscopy study of BiVO4 photoanodes.

High energy resolution fluorescence detected X-ray absorption spectroscopy is a powerful method for probing the electronic structure of functional materials. The X-ray penetration depth and photon-in/photon-out nature of the method allow operando experiments to be performed, in particular in electrochemical cells. Here, operando high-resolution X-ray absorption measurements of a BiVO4 photoanode are reported, simultaneously probing the local electronic states of both cations. Small but significant variations of the spectral lineshapes induced by the applied potential were observed and an explanation in terms of the occupation of electronic states at or near the band edges is proposed.

Congenital Malformations of the Eye: A Pictorial Review and Clinico-Radiological Correlations.

Congenital malformations of the eye represent a wide and heterogeneous spectrum of abnormalities that may be part of a complex syndrome or be isolated. Ocular malformation severity depends on the timing of the causative event during eye formation, ranging from the complete absence of the eye if injury occurs during the first weeks of gestation, to subtle abnormalities if the cause occurs later on. Knowledge of ocular malformations is crucial to performing a tailored imaging protocol and correctly reporting imaging findings. Together with the ophthalmologic evaluation, imaging may help frame ocular malformations and identify underlying genetic conditions. The purpose of this pictorial review is to describe the imaging features of the main ocular malformations and the related ophthalmologic findings in order to provide a clinico-radiological overview of these abnormalities to the clinical radiologist. Sight is a crucial sense for children to explore the world and relate with their parents from birth. Vision impairment or even blindness secondary to ocular malformations deeply affects children's growth and quality of life.

AC-73 and Syrosingopine Inhibit SARS-CoV-2 Entry into Megakaryocytes by Targeting CD147 and MCT4.

Coagulation disorders are described in COVID-19 and long COVID patients. In particular, SARS-CoV-2 infection in megakaryocytes, which are precursors of platelets involved in thrombotic events in COVID-19, long COVID and, in rare cases, in vaccinated individuals, requires further investigation, particularly with the emergence of new SARS-CoV-2 variants. CD147, involved in the regulation of inflammation and required to fight virus infection, can facilitate SARS-CoV-2 entry into megakaryocytes. MCT4, a co-binding protein of CD147 and a key player in the glycolytic metabolism, could also play a role in SARS-CoV-2 infection. Here, we investigated the susceptibility of megakaryocytes to SARS-CoV-2 infection via CD147 and MCT4. We performed infection of Dami cells and human CD34+ hematopoietic progenitor cells induced to megakaryocytic differentiation with SARS-CoV-2 pseudovirus in the presence of AC-73 and syrosingopine, respective inhibitors of CD147 and MCT4 and inducers of autophagy, a process essential in megakaryocyte differentiation. Both AC-73 and syrosingopine enhance autophagy during differentiation but only AC-73 enhances megakaryocytic maturation. Importantly, we found that AC-73 or syrosingopine significantly inhibits SARS-CoV-2 infection of megakaryocytes. Altogether, our data indicate AC-73 and syrosingopine as inhibitors of SARS-CoV-2 infection via CD147 and MCT4 that can be used to prevent SARS-CoV-2 binding and entry into megakaryocytes, which are precursors of platelets involved in COVID-19-associated coagulopathy.

Robust Molecular Anodes for Electrocatalytic Water Oxidation Based on Electropolymerized Molecular Cu Complexes.

A multistep synthesis of a new tetra-amidate macrocyclic ligand functionalized with alkyl-thiophene moieties, 15,15-bis(6-(thiophen-3-yl)hexyl)-8,13-dihydro-5H-dibenzo[b,h][1,4,7,10]tetraazacyclotridecine-6,7,14,16(15H,17H)-tetraone, H4 L, is reported. The reaction of the deprotonated ligand, L4- , and Cu(II) generates the complex [LCu]2- , that can be further oxidized to Cu(III) with iodine to generate [LCu]- . The H4 L ligand and their Cu complexes have been thoroughly characterized by analytic and spectroscopic techniques (including X-ray Absorption Spectroscopy, XAS). Under oxidative conditions, the thiophene group of [LCu]2- complex polymerizes on the surface of graphitic electrodes (glassy carbon disks (GC), glassy carbon plates (GCp ), carbon nanotubes (CNT), or graphite felts (GF)) generating highly stable thin films. With CNTs deposited on a GC by drop casting, hybrid molecular materials labeled as GC/CNT@p-[LCu]2- are obtained. The latter are characterized by electrochemical techniques that show their capacity to electrocatalytically oxidize water to dioxygen at neutral pH. These new molecular anodes achieve current densities in the range of 0.4 mA cm-2 at 1.30 V versus NHE with an onset overpotential at ≈250 mV. Bulk electrolysis experiments show an excellent stability achieving TONs in the range of 7600 during 24 h with no apparent loss of catalytic activity and maintaining the molecular catalyst integrity, as evidenced by electrochemical techniques and XAS spectroscopy.

MiR126-targeted-nanoparticles combined with PI3K/AKT inhibitor as a new strategy to overcome melanoma resistance.

Metastatic melanoma poses significant challenges as a highly lethal disease. Despite the success of molecular targeting using BRAFV600E inhibitors (BRAFis) and immunotherapy, the emergence of early recurrence remains an issue and there is the need for novel therapeutic approaches. This study aimed at creating a targeted delivery system for the oncosuppressor microRNA 126 (miR126) and testing its effectiveness in combination with a phosphatidylinositol 3-kinase (PI3K)/ protein kinase B (AKT) inhibitor for treating metastatic melanoma resistant to BRAFis. To achieve this, we synthesized chitosan nanoparticles containing a chemically modified miR126 sequence. These nanoparticles were further functionalized with an antibody specific to the chondroitin sulfate proteoglycan 4 (CSPG4) melanoma marker. After evaluation in vitro, the efficacy of this treatment was evaluated through an in vivo experiment using mice bearing resistant human melanoma. The co-administration of miR126 and the PI3K/AKT inhibitor in these experiments significantly reduced tumor growth and inhibited the formation of liver and lung metastases. These results provide evidence for a strategy to target an oncosuppressive nucleic acid sequence to tumor cells while simultaneously protecting it from plasma degradation. The system described in this study exhibits encouraging potential for the effective treatment of therapy-resistant metastatic melanoma while also presenting a prospective approach for other forms of cancer.

Ex Vivo Anti-Leukemic Effect of Exosome-like Grapefruit-Derived Nanovesicles from Organic Farming-The Potential Role of Ascorbic Acid.

Citrus fruits are a natural source of ascorbic acid, and exosome-like nanovesicles obtained from these fruits contain measurable levels of ascorbic acid. We tested the ability of grapefruit-derived extracellular vesicles (EVs) to inhibit the growth of human leukemic cells and leukemic patient-derived bone marrow blasts. Transmission electron microscopy and nanoparticle tracking analysis (NTA) showed that the obtained EVs were homogeneous exosomes, defined as exosome-like plant-derived nanovesicles (ELPDNVs). The analysis of their content has shown measurable amounts of several molecules with potent antioxidant activity. ELPDNVs showed a time-dependent antiproliferative effect in both U937 and K562 leukemic cell lines, comparable with the effect of high-dosage ascorbic acid (2 mM). This result was confirmed by a clear decrease in the number of AML blasts induced by ELPDNVs, which did not affect the number of normal cells. ELPDNVs increased the ROS levels in both AML blast cells and U937 without affecting ROS storage in normal cells, and this effect was comparable to ascorbic acid (2 mM). With our study, we propose ELPDNVs from grapefruits as a combination/supporting therapy for human leukemias with the aim to improve the effectiveness of the current therapies.

Magnetic resonance imaging based neurosurgical planning on hololens 2: A feasibility study in a paediatric hospital.

Objective: The goal of this work is to show how to implement a mixed reality application (app) for neurosurgery planning based on neuroimaging data, highlighting the strengths and weaknesses of its design. Methods: Our workflow explains how to handle neuroimaging data, including how to load morphological, functional and diffusion tensor imaging data into a mixed reality environment, thus creating a first guide of this kind. Brain magnetic resonance imaging data from a paediatric patient were acquired using a 3 T Siemens Magnetom Skyra scanner. Initially, this raw data underwent specific software pre-processing and were subsequently transformed to ensure seamless integration with the mixed reality app. After that, we created three-dimensional models of brain structures and the mixed reality environment using Unity™ engine together with Microsoft® HoloLens 2™ device. To get an evaluation of the app we submitted a questionnaire to four neurosurgeons. To collect data concerning the performance of a user session we used Unity Performance Profiler. Results: The use of the interactive features, such as rotating, scaling and moving models and browsing through menus, provided by the app had high scores in the questionnaire, and their use can still be improved as suggested by the performance data collected. The questionnaire's average scores were high, so the overall experiences of using our mixed reality app were positive. Conclusion: We have successfully created a valuable and easy-to-use neuroimaging data mixed reality app, laying the foundation for more future clinical uses, as more models and data derived from various biomedical images can be imported.

Developing the next generation of renewable energy technologies: an overview of low-TRL EU-funded research projects.

A cluster of eleven research and innovation projects, funded under the same call of the EU's H2020 programme, are developing breakthrough and game-changing renewable energy technologies that will form the backbone of the energy system by 2030 and 2050 are, at present, at an early stage of development. These projects have joined forces at a collaborative workshop, entitled ' Low-TRL Renewable Energy Technologies', at the 10th Sustainable Places Conference (SP2022), to share their insights, present their projects' progress and achievements to date, and expose their approach for exploitation and market uptake of their solutions.

Functional MRI in Neuro-Oncology: State of the Art and Future Directions.

Since its discovery in the early 1990s, functional MRI (fMRI) has been used to study human brain function. One well-established application of fMRI in the clinical setting is the neurosurgical planning of patients with brain tumors near eloquent cortical areas. Clinical fMRI aims to preoperatively identify eloquent cortices that serve essential functions in daily life, such as hand movement and language. The primary goal of neurosurgery is to maximize tumor resection while sparing eloquent cortices adjacent to the tumor. When a lesion presents in the vicinity of an eloquent cortex, surgeons may use fMRI to plan their best surgical approach by determining the proximity of the lesion to regions of activation, providing guidance for awake brain surgery and intraoperative brain mapping. The acquisition of fMRI requires patient preparation prior to imaging, determination of functional paradigms, monitoring of patient performance, and both processing and analysis of images. Interpretation of fMRI maps requires a strong understanding of functional neuroanatomy and familiarity with the technical limitations frequently present in brain tumor imaging, including neurovascular uncoupling, patient compliance, and data analysis. This review discusses clinical fMRI in neuro-oncology, relevant ongoing research topics, and prospective future developments in this exciting discipline.

Electrodeposited Ionomer Protection Layer for Negative Electrodes in Zinc-Air Batteries.

The protection of zinc anodes in zinc-air batteries (ZABs) is an efficient way to reduce corrosion and Zn dendrite formation and improve cyclability and battery efficiency. Anion-conducting poly(N-vinylbenzyl N,N,N-trimethylammonium)chloride (PVBTMA) thin films were electrodeposited directly on zinc metal using cyclic voltammetry. This deposition process presents a combination of advantages, including selective anion transport in PVBTMA reducing zinc crossover, high interface quality by electrodeposition improving the corrosion protection of zinc and high ionomer stiffness opposing zinc dendrite perforation. The PVBTMA layer was observed by optical and electron microscopy, and the wettability of the ionomer-coated surface was investigated by contact angle measurements. ZABs with PVBTMA-coated Zn showed an appreciable and stable open-circuit voltage both in alkaline electrolyte (1.55 V with a Pt cathode) and in miniaturized batteries (1.31 V with a carbon paper cathode). Cycling tests at 0.5 mA/cm2 within voltage limits of 2.1 and 0.8 V gave a stable discharge capacity for nearly 100 cycles with a liquid electrolyte and more than 20 cycles in miniaturized batteries. The faster degradation of the latter ZAB was attributed to the clogging of the carbon air cathode and drying or carbonation of the electrolyte sorbed in a Whatman paper.

The autophagic protein FYCO1 controls TNFRSF10/TRAIL receptor induced apoptosis and is inactivated by CASP8 (caspase 8).

Apoptosis is a tightly controlled cell death program executed by proteases, the so-called caspases. It plays an important role in tissue homeostasis and is often dysregulated in cancer. Here, we identified FYCO1, a protein that promotes microtubule plus end-directed transport of autophagic and endosomal vesicles as a molecular interaction partner of activated CASP8 (caspase 8). The absence of FYCO1 sensitized cells to basal and TNFSF10/TRAIL-induced apoptosis by receptor accumulation and stabilization of the Death Inducing Signaling Complex (DISC). Loss of FYCO1 resulted in impaired transport of TNFRSF10B/TRAIL-R2/DR5 (TNF receptor superfamily member 10b) to the lysosomes in TNFSF10/TRAIL-stimulated cells. More in detail, we show that FYCO1 interacted via its C-terminal GOLD domain with the CCZ1-MON1A complex, which is necessary for RAB7A activation and for the fusion of autophagosomal/endosomal vesicles with lysosomes. We demonstrated that FYCO1 is a novel and specific CASP8 substrate. The cleavage at aspartate 1306 resulted in the release of the C-terminal GOLD domain, inactivating FYCO1 function, and allowing for the progression of apoptosis. Furthermore, the lack of FYCO1 resulted in a stronger and prolonged formation of the TNFRSF1A/TNF-R1 signaling complex. Thus, FYCO1 limits the ligand-induced and steady-state signaling of TNFR-superfamily members, providing a control mechanism that fine-tunes both apoptotic and inflammatory answers.Abbreviations: AP: affinity purification; CHX: cycloheximide; co-IP: co-immunoprecipitation; CRISPR: clustered regularly interspaced short palindromic repeats; DISC: death-inducing signaling complex; DR: death receptors; doxy: doxycycline; GEF: guanine nucleotide exchange factor; ind: inducible; KD: knockdown; KO: knockout; MS: mass spectrometry; shRNA: short hairpin RNA; siRNA: small interfering RNA; TIP: two-step co-immunoprecipitation; WB: western blot.

Association of Lack of Speech Arrest During Cortical Stimulation With Interhemispheric Reorganization of the Functional Language Network in Patients With Brain Tumors.

BACKGROUND. Brain tumors induce language reorganization, which may influence the extent of resection in surgical planning. Direct cortical stimulation (DCS) allows definitive language mapping during awake surgery by locating areas of speech arrest (SA) surrounding the tumor. Although functional MRI (fMRI) combined with graph theory analysis can illustrate whole-brain network reorganization, few studies have corroborated these findings with DCS intraoperative mapping and clinical language performance. OBJECTIVE. We evaluated whether patients with low-grade gliomas (LGGs) without SA during DCS show increased right-hemispheric connections and better speech performance compared with patients with SA. METHODS. We retrospectively recruited 44 consecutive patients with left perisylvian LGG, preoperative language task-based fMRI, speech performance evaluation, and awake surgery with DCS. We generated language networks from ROIs corresponding to known language areas (i.e., language core) on fMRI using optimal percolation. Language core connectivity in the left and right hemispheres was quantified as fMRI laterality index (LI) and connectivity LI on the basis of fMRI activation maps and connectivity matrices. We compared fMRI LI and connectivity LI between patients with SA and without SA and used multivariable logistic regression (p < .05) to assess associations between DCS and connectivity LI, fMRI LI, tumor location, Broca area and Wernicke area involvement, prior treatments, age, handedness, sex, tumor size, and speech deficit before surgery, within 1 week after surgery, and 3-6 months after surgery. RESULTS. Patients with SA showed left-dominant connectivity; patients without SA lateralized more to the right hemisphere (p < .001). Between patients with SA and those without, fMRI LI was not significantly different. Patients without SA showed right-greater-than-left connectivity of Broca area and premotor area compared with patients with SA. Regression analysis showed significant association between no SA and right-lateralized connectivity LI (p < .001) and fewer speech deficits before (p < .001) and 1 week after (p = .02) surgery. CONCLUSION. Patients without SA had increased right-hemispheric connections and right translocation of the language core, suggesting language reorganization. Lack of interoperative SA was associated with fewer speech deficits both before and immediately after surgery. CLINICAL IMPACT. These findings support tumor-induced language plasticity as a compensatory mechanism, which may lead to fewer postsurgical deficits and allow extended resection.

Distribution of Relaxation Times Based on Lasso Regression: A Tool for High-Resolution Analysis of IMPS Data in Photoelectrochemical Systems.

Intensity-modulated photocurrent spectroscopy (IMPS) has been largely employed in semiconductor characterization for solar energy conversion devices to probe the operando behavior with widely available facilities. However, the implementation of IMPS data analysis to complex structures, whether based on the physical rate constant model (RCM) or the assumption-free distribution of relaxation times (DRT), is generally limited to a semi-quantitative description of the charge carrier kinetics of the system. In this study, a new algorithm for the analysis of IMPS data is developed, providing unprecedented time resolution to the investigation of µs to s charge carrier dynamics in semiconductor-based systems used in photoelectrochemistry and photovoltaics. The algorithm, based on the previously developed DRT analysis, is herein modified with a Lasso regression method and available to the reader free of charge. A validation of this new algorithm is performed on a α-Fe2O3 photoanode for photoelectrochemical water splitting, identified as a standard platform in the field, highlighting multiple potential-dependent charge transfer paths, otherwise hidden in the conventional IMPS data analysis.

Numerical and Experimental Study of Gas Phase Nanoparticle Synthesis Using NanoDOME.

Nowadays, with the rocketing of computational power, advanced numerical tools, and parallel computing, multi-scale simulations are becoming applied more and more to complex multi-physics industrial processes. One of the several challenging processes to be numerically modelled is gas phase nanoparticle synthesis. In an applied industrial scenario, the possibility to correctly estimate the geometric properties of the mesoscopic entities population (e.g., their size distribution) and to more precisely control the results is a crucial step to improve the quality and efficiency of the production. The "NanoDOME" project (2015-2018) aims to be an efficient and functional computational service to be applied in such processes. NanoDOME has also been refactored and upscaled during the H2020 Project "SimDOME". To prove its reliability, we present here an integrated study between experimental data and NanoDOME's predictions. The main goal is to finely investigate the effect of a reactor's thermodynamic conditions on the thermophysical history of mesoscopic entities along the computational domain. To achieve this goal, the production of silver nanoparticles has been assessed for five cases with different experimental operative conditions of the reactor. The time evolution and final size distribution of nanoparticles have been simulated with NanoDOME by exploiting the method of moments and population balance model. The validation is performed by comparing NanoDOME's calculations with the experimental data.

Effect of tumor genetics, pathology, and location on fMRI of language reorganization in brain tumor patients.

OBJECTIVES: Language reorganization may follow tumor invasion of the dominant hemisphere. Tumor location, grade, and genetics influence the communication between eloquent areas and tumor growth dynamics, which are drivers of language plasticity. We evaluated tumor-induced language reorganization studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness). METHODS: The study was retrospective cross-sectional. We included patients with left-hemispheric tumors (study group) and right-hemispheric tumors (controls). We calculated five fMRI laterality indexes (LI): hemispheric, temporal lobe, frontal lobe, Broca's area (BA), Wernicke's area (WA). We defined LI ≥ 0.2 as left-lateralized (LL) and LI < 0.2 as atypical lateralized (AL). Chi-square test (p < 0.05) was employed to identify the relationship between LI and tumor/patient variables in the study group. For those variables having significant results, confounding factors were evaluated in a multinomial logistic regression model. RESULTS: We included 405 patients (235 M, mean age: 51 years old) and 49 controls (36 M, mean age: 51 years old). Contralateral language reorganization was more common in patients than controls. The statistical analysis demonstrated significant association between BA LI and patient sex (p = 0.005); frontal LI, BA LI, and tumor location in BA (p < 0.001); hemispheric LI and fibroblast growth factor receptor (FGFR) mutation (p = 0.019); WA LI and O6-methylguanine-DNA methyltransferase promoter (MGMT) methylation in high-grade gliomas (p = 0.016). CONCLUSIONS: Tumor genetics, pathology, and location influence language laterality, possibly due to cortical plasticity. Increased fMRI activation in the right hemisphere was seen in patients with tumors in the frontal lobe, BA and WA, FGFR mutation, and MGMT promoter methylation. KEY POINTS: • Patients harboring left-hemispheric tumors present with contralateral translocation of language function. Influential variables for this phenomenon included frontal tumor location, BA location, WA location, sex, MGMT promoter methylation, and FGFR mutation. • Tumor location, grade, and genetics may influence language plasticity, thereby affecting both communication between eloquent areas and tumor growth dynamics. • In this retrospective cross-sectional study, we evaluated language reorganization in 405 brain tumor patients by studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness).

Functional MRI during tongue strength tasks before and after partial glossectomy: Insights into the cortical activation of tongue motor function.

AIM: Because the tongue is a midline structure, studies on the neural correlates of lateralized tongue function are challenging and remain limited. Patients with tongue cancer who undergo unilateral partial glossectomy may be a unique cohort to study tongue-associated cortical activation, particularly regarding brain hemispheric lateralization. This longitudinal functional magnetic resonance imaging (fMRI) study investigated cortical activation changes for three tongue tasks before and after left-sided partial glossectomy in patients with squamous cell carcinoma of the tongue. METHODS: Seven patients with squamous cell carcinoma involving the left tongue who underwent fMRI before and 6 months after unilateral partial glossectomy were studied. Post-surgical changes in laterality index (LI) values for tongue-associated precentral and postcentral gyri fMRI activation were calculated for the dry swallow, tongue press, and saliva sucking tasks. Group analysis fMRI activation maps were generated for each of the three tasks. RESULTS: There were significant differences in changes in LI values post-surgery between the tongue press (p < 0.005; median: +0.24), saliva sucking (-0.10), and dry swallow tasks (-0.16). Decreased contralateral activation (change in LI ≥+0.20) was observed post-surgery during tongue press in six of seven patients, but only in two patients during saliva sucking and one patient during dry swallow (p < 0.05). There was also increased activation in the supplementary motor area following surgery. CONCLUSION: Post-surgical fMRI changes following left-sided partial glossectomy may suggest task-specific sensitivities to cortical activation changes following unilateral tongue deficits that may reflect the impacts of surgery and adaptive responses to tongue impairment.

The promise of metabolic imaging in diffuse midline glioma.

Recent insights into histopathological and molecular subgroups of glioma have revolutionized the field of neuro-oncology by refining diagnostic categories. An emblematic example in pediatric neuro-oncology is the newly defined diffuse midline glioma (DMG), H3 K27-altered. DMG represents a rare tumor with a dismal prognosis. The diagnosis of DMG is largely based on clinical presentation and characteristic features on conventional magnetic resonance imaging (MRI), with biopsy limited by its delicate neuroanatomic location. Standard MRI remains limited in its ability to characterize tumor biology. Advanced MRI and positron emission tomography (PET) imaging offer additional value as they enable non-invasive evaluation of molecular and metabolic features of brain tumors. These techniques have been widely used for tumor detection, metabolic characterization and treatment response monitoring of brain tumors. However, their role in the realm of pediatric DMG is nascent. By summarizing DMG metabolic pathways in conjunction with their imaging surrogates, we aim to elucidate the untapped potential of such imaging techniques in this devastating disease.