Search Results (123)

Adrenocortical carcinomas (ACCs) are rare, aggressive tumors often discovered incidentally. These malignancies may present with abnormal hormone secretion or, as in some cases, as non-functioning masses causing discomfort. We present a case of brain metastasis in a patient with a giant ACC. A 50-year-old man presented with headache and dizziness. A computed tomography (CT) scan showed an intracranial lesion within the parenchyma measuring 73*60*46 mm with left internal temporal involvement, abundant vasogenic edema and compressing the lateral left ventricle. Further imaging investigations identified a large necrotic tissue mass measuring 15 cm, located on both sides of the right diaphragmatic dome, in the middle posterior region. Hormonal workup was conducted and excluded a functional adrenal tumor. A CT-guided biopsy was performed, confirming ACC. Despite medical management, the patient’s condition deteriorated rapidly, with the cerebral metastasis proving fatal. This case underscores the challenges posed by advanced ACC, particularly when associated with atypical metastatic sites. Giant ACC, though rare, presents significant diagnostic and therapeutic challenges. Surgical excision with appropriate oncologic management can lead to favorable outcomes. This report contributes to the limited literature on cerebral metastases in ACC, aiming to enhance awareness among clinicians managing this rare entity. Full article

Background: The discovery of electroencephalogram (EEG) biomarkers of direct transmitter–receptor interactions in studies of neurotransmitter mechanisms underlying brain function remains relevant. Recently, EEG “signatures” of monoaminergic systems have been demonstrated using the “time-frequency clustering” approach. In the current study, the glutamic and cholinergic systems were under similar analysis with additional emphasis on their potential interaction. Methods: In non-anesthetized freely moving rats, we studied the EEG effects of agonists for glutamate receptors, injected into the cerebral lateral ventricles, and their modification after pretreatment with corresponding antagonists. The same protocol was used for acetylcholine receptors, activating and blocking substances that penetrate the blood–brain barrier (BBB) after subcutaneous injections. A clustering of significant time-dependent changes in tiny frequency subranges of the EEG spectra was performed. Results: After injections of agonists for glutamate receptors, two clusters with enhanced and suppressed activities around 2/4 and 10 Hz, respectively, were observed in the EEG spectra. These effects were reduced by pretreatment with corresponding receptor blockers. A cholinomimetic, physostigmine, decreased EEG activity around 2 and 10 Hz and increased near 5 and 22 Hz. Scopolamine, blocking muscarinic cholinoreceptors, weakened the effects of physostigmine. Intracerebral pretreatment with NMDA and AMPA receptor blockers differently modified the effects of physostigmine. The results demonstrate the EEG biomarkers of glutamatergic and cholinergic systems, as well as the specificity of interactions between them at the intracerebral level. Conclusions: The developed EEG time-frequency clustering is a potentially useful approach for the clinical evaluation of glutamatergic/cholinergic pathology and its correction by corresponding substances penetrating the BBB. Full article

Background: Common variable immunodeficiency is a heterogeneous disorder characterized by defects in antibody production and immune dysregulation, associated with infections and autoimmunity. Although structural and cognitive effects of CVID on the central nervous system have attracted attention in recent years, studies jointly addressing volumetric brain imaging and neurocognitive evaluation remain limited. Materials and Methods: In this retrospective cross-sectional study, 35 patients with common variable immunodeficiency and 40 age- and sex-matched healthy controls were evaluated. Cognitive performance was assessed in all participants using the Montreal Cognitive Assessment. High-resolution T1-weighted brain magnetic resonance imaging scans underwent automated segmentation using the volBrain platform, yielding quantitative volumetric measurements of cortical, subcortical, and cerebellar structures, as well as ventricles and cerebrospinal fluid. Intergroup comparisons were performed using independent t-tests and analysis of variance. Results: MoCA scores were significantly lower in patients with CVID. Volumetric analysis revealed prominent reductions in the volumes of total brain tissue, gray matter, cerebrum, cerebellum, limbic system, thalamus, and basal ganglia. Paralleling these findings, cerebrospinal fluid and lateral ventricle volumes were increased. Additional volume losses were detected in CVID patients with low MoCA scores. In CVID patients with autoimmunity, volume loss affected broader areas. Conclusions: CVID appears to be associated with structural brain changes and cognitive impairments. Chronic inflammation and immune dysregulation may contribute to these neurodegenerative processes. Regular neurocognitive monitoring and further prospective studies are warranted in patients with CVID. Full article

Fetal ventriculomegaly (VM) is a condition characterized by abnormal enlargement of the cerebral ventricles of the fetus brain that often causes developmental disorders in children. Manual segmentation and classification of ventricular structures from brain MRI scans are time-consuming and require clinical expertise. To address this challenge, we develop an automated pipeline for ventricle segmentation, ventricular width estimation, and VM severity classification using a publicly available dataset. An adaptive slice selection strategy converts 3D MRI volumes into the most informative 2D slices, which are then segmented to isolate the lateral ventricles and deep gray matter. Ventricular width is automatically estimated to assign severity levels based on clinical thresholds, generating labeled data for training a deep learning classifier. Finally, an explainability module using a large language model integrates the MRI slices, segmentation masks, and predicted severity to provide interpretable clinical reasoning. Experimental results demonstrate that the proposed decision support system delivers robust performance, achieving dice scores of 89% and 87.5% for the 2D and 3D segmentation models, respectively. Also, the classification network attains an accuracy of 86% and an F1-score of 0.84 in VM analysis. Full article

Background and Clinical Significance: Adults suffering from cerebellar metastases are often at high risk for rapid deterioration of their neurological status because the posterior fossa has limited compliance and the location of these metastases are close to the brain stem and important cerebrospinal fluid (CSF) pathways. In this paper, we present a longitudinal, patient-centered report on the history of an elderly individual who suffered from cognitive comorbidities and experienced a sudden loss of function in her cerebellum. Our goal in reporting this case is to provide a comparison between the patient’s pre-operative and post-operative neurological examinations; the imaging studies she had before and after surgery; the surgical techniques utilized during her operation; and the outcome of her post-operative course in a way that will be helpful to other patients who have experienced a similar situation. Case Presentation: We report the case of an 80-year-old woman who initially presented with progressive ipsilateral limb-trunk ataxia, impaired smooth pursuit eye movement, and rebound nystagmus, but preserved pyramidal and sensory functions. Her quantitative bedside assessments included some of the components of the Scale for the Assessment and Rating of Ataxia (SARA), and a National Institute of Health Stroke Scale (NIHSS) score of 3. These findings indicated dysfunction of the left neocerebellar hemisphere and possible dentate nucleus involvement. The patient’s magnetic resonance imaging (MRI) results demonstrated an expansive mass with surrounding vasogenic edema and marked compression and narrowing of the exits of the fourth ventricle which placed the patient’s CSF pathways at significant risk of occlusion, while the aqueduct and inlets were patent. She then underwent a left lateral suboccipital craniectomy with controlled arachnoidal CSF release, preservation of venous drainage routes, subpial corticotomy oriented along the lines of the folia, stepwise internal debulking, and careful protection of the cerebellar peduncles and dentate nucleus. Dural reconstruction utilized a watertight pericranial graft to restore the cisternal compartments. Her post-operative intensive care unit (ICU) management emphasized optimal venous outflow, normoventilation, and early mobilization. Histopathology confirmed the presence of metastatic carcinoma, and staging suggested that the most likely source of the primary tumor was the lungs. Immediately post-operation, computed tomography (CT) imaging revealed a smooth resection cavity with open foramina of Magendie and Luschka, intact contours of the brain stem, and no evidence of bleeding or hydrocephalus. The patient’s neurological deficits, including dysmetria, scanning dysarthria, and ataxic gait, improved gradually during the first 48 h post-operatively. Upon discharge, the patient demonstrated an improvement in her limb-kinetic subscore on the International Cooperative Ataxia Rating Scale (ICARS) and demonstrated independent ambulation. At two weeks post-operation, CT imaging revealed decreasing edema and stable cavity size, and the patient’s modified Rankin scale had improved from 3 upon admission to 1. There were no episodes of CSF leakage, wound complications, or new cranial nerve deficits. A transient post-operative psychotic episode that was likely secondary to her underlying Alzheimer’s disease was managed successfully with short-course pharmacotherapy. Conclusions: The current case study demonstrates the value of anatomy-based microsurgical planning, preservation of venous and CSF pathways, and targeted peri-operative management to facilitate rapid recovery of function in older adults who suffer from cerebellar metastasis and cognitive comorbidities. The case also demonstrates the importance of early multidisciplinary collaboration to allow for timely initiation of both adjuvant stereotactic radiosurgery and molecularly informed systemic therapy. Full article

Background: This study explored the correlation between lateral ventricle volume asymmetry and cerebral blood flow (CBF). Methods: A retrospective review of 94 patients who underwent CT perfusion (CTP) and standard brain imaging was conducted. Lateral ventricle volumes and CBF across 13 vascular-based regions of interest (ROIs) were measured. Cerebral artery stenosis was identified using magnetic resonance angiography (MRA) and digital subtraction angiography (DSA). Paired t-tests, Pearson’s correlation, logistic regression, and Cox models were used to assess the relationships between lateral ventricle asymmetry, CBF differences, and their associations with cerebral artery stenosis and the risk of stroke during follow-up. Results: 94 patients were included (mean age: 60.7 years). CBF was significantly lower on the side of the larger lateral ventricle in regions supplied by the anterior cerebral artery (ACA) (Mean relative value ± SD, % = 112.3 ± 32.5, p-value = 0.0016) and middle cerebral artery (MCA) (Mean relative value ± SD, % = 123.1 ± 57.8, p-value = 0.0004). A moderate correlation was observed between lateral ventricle volume asymmetry and CBF differences across the entire cohort. Significant associations were identified between CBF differences in specific ROIs and the presence of cerebral artery stenosis (MCA: aOR = 1.026, 95% CI: 1.004–1.048, p-value = 0.019). Conclusions: Lateral ventricle asymmetry is associated with reduced CBF in specific brain regions, particularly those supplied by the ACA. CBF differences in regions supplied by the PCA are linked to increased risk of subsequent stroke during follow-up. Full article

Background/Objectives: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective treatment for motor symptoms in Parkinson’s disease (PD), but concerns remain regarding its impact on cognitive function. Identifying neuroanatomical predictors of postoperative cognitive decline could improve patient selection and outcomes. This study aims to investigate the relationship between preoperative brain morphology and postoperative neuropsychological outcomes in PD patients undergoing bilateral STN-DBS. Methods: Thirty-eight PD patients underwent standardized neuropsychological testing and preoperative MRI before and 3–24 months after STN-DBS. Manual MRI morphometric measurements were obtained for 42 cortical, subcortical, and ventricular parameters. Changes in cognitive domains—including executive function, memory, language, visuospatial abilities, attention, and global cognition—were analyzed, and correlations between structural metrics and cognitive changes were assessed using Spearman’s coefficients. Results: Significant postoperative declines occurred selectively in language functions: verbal fluency (phonemic and semantic, d = −0.49 to −0.84) and confrontation naming (d = −0.47). Memory, executive functions, attention, and global cognition remained preserved. Enlarged lateral ventricles were consistently associated with poorer outcomes across multiple domains, while increased left precentral gyrus width correlated with executive and memory decline. Additionally, smaller midbrain and cingulate gyrus width were associated with greater executive impairment. Conclusions: STN-DBS in PD is associated with selective postoperative cognitive changes, most prominently in verbal fluency. Simple preoperative MRI morphometric measures, including ventricular size, limbic structure volumes, and specific cortical parameters, may serve as clinically feasible predictors of cognitive risk. Incorporating such measures into preoperative assessments could enhance patient selection, counseling, and individualized surgical planning. Full article

Background: During development, reelin sets the pace of neocortical neurogenesis, enabling newborn neurons to migrate. However, whether—and, if so, how—reelin signaling affects the adult neurogenic niches remains uncertain. Methods: In the present study, we use both loss- and gain-of-function genetic approaches, along with in vivo and ex vivo assays, to investigate this question. Results: We show that reelin signaling, resulting in Dab1 phosphorylation, occurs in the ependymal-subependymal zone (EZ/SEZ) of the lateral ventricles, where, along with its associated rostral migratory stream (RMS), the highest density of functional ApoER2 accumulates. Mice deficient in Reelin, ApoER2, or Dab1 exhibit enlarged ventricles and a dysplastic RMS. Moreover, while the conditional ablation of Dab1 in neural progenitor cells (NPCs) enlarges the ventricles and impairs neuroblast clearance from the SEZ, the transgenic misexpression of Reelin in NPCs of Reelin-deficient mice normalizes the ventricular lumen and the density of ependymal cilia, thereby ameliorating neuroblast migration. Consistently, intraventricular infusion of reelin reroutes neuroblasts. Conclusions: These results demonstrate that reelin signaling persists, sustaining the germinal niche of the lateral ventricles and influencing neuroblast migration in the adult brain. Full article

Introduction. Post-traumatic stress disorder (PTSD) remains one of the best-described yet also one of the most heterogeneous psychiatric disorders. Existing neuroimaging studies point to key changes in the hippocampus, amygdala, and prefrontal cortex, but the role of PTSD duration in modulating these changes has not been fully explained. Objectives. The aim of the study was to assess the impact of PTSD duration (≤5 years vs. >5 years) on volumetric and microstructural brain parameters, using multiple Magnetic Resonance Imaging (MRI) sequences (3D Ax BRAVO, Cube T2 FLAIR, Diffusion Tensor Imaging—DTI) and a set of macroscopic morphometric measurements. Methods. The study included 92 participants: 33 with PTSD of ≤5 years duration, 31 with PTSD > 5 years, and 28 healthy controls. Volume and diffusion parameters of six Regions of Interest (ROIs) (hippocampus, amygdala, prefrontal cortex—right and left) were evaluated, along with their associations with nine brain measurements (including width of the third ventricle, corpus callosum, and lateral fissures). Statistical analyses included the Kruskal–Wallis test with Compact Letter Display (CLD) correction and Spearman correlations. Results. (1) The volume of the right hippocampus was significantly greater in the PTSD > 5 years group compared to controls (p = 0.006), with intermediate values in the PTSD ≤ 5 years group. (2) In the left amygdala, an increase in Fractional Anisotropy (FA) and related anisotropy measures was observed in PTSD > 5 years (p ≈ 0.02), without volumetric changes. (3) In the left prefrontal cortex, diffusivity was reduced in PTSD ≤ 5 years (p = 0.035), partially normalizing after >5 years. (4) Correlation analysis revealed that chronic PTSD strengthens the negative associations between hippocampal microstructure and both the width of the amygdala and the interhemispheric fissure, indicating a progressive reorganization of fronto-limbic networks. Conclusions. PTSD induces region- and time-dependent brain changes: (a) adaptive/hypertrophic protection of the right hippocampus after many years of illness, (b) cumulative microstructural reorganization of the left amygdala, and (c) transient impairment of diffusion in the left prefrontal cortex in early PTSD. These findings highlight the necessity of considering the temporal dimension in planning therapeutic interventions and in the search for biomarkers of PTSD progression. Full article

Background/Objectives: Age-related structural changes in the human brain provide essential insights into cognitive aging and the onset of neurodegenerative diseases. This study aimed to comprehensively characterize age-related volumetric changes across multiple brain regions in a large, diverse, cognitively healthy cohort spanning adulthood (ages 21–90), integrating Korean, Information eXtraction from Images (IXI), and Alzheimer’s Disease Neuroimaging Initiative (ADNI) MRI datasets of cognitively healthy participants to characterize normative volumetric changes across adulthood using demographically diverse datasets. Methods: High resolution 3T T1-weighted MRI images from three distinct cohorts (totaling 1833 subjects) were processed through an optimized neuroimaging pipeline, combining advanced preprocessing with neural network-based segmentation. Volumetric data for 95 brain structures were segmented and analyzed across seven age bins (21–30 through 81–90). Pipeline reliability was validated against FreeSurfer using intraclass correlation coefficients (ICC) and coefficients of variation (CoV). Regression-based correction was used to correct for sex and cohort effects on brain region volume. Then, percentage change in each mean bilateral volumes of regions across the lifespan were computed to describe volumetric changes across life spans. Results: The segmentation pipeline demonstrated excellent agreement with FreeSurfer (mean ICC: 0.9965). Drastic volumetric expansions were observed in white matter hypointensities (122.6%), lateral ventricles (115.9%), and inferior lateral ventricles (116.8%). Moderate-to-notable shrinkage was found predominantly in the frontal lobe (pars triangularis: 21.5%), parietal lobe (inferior parietal: 20.4%), temporal lobe (transverse temporal: 21.6%), and cingulate cortex (caudal anterior cingulate: 16.1%). Minimal volume changes occurred in regions such as the insula (3.7%) and pallidum (2.6%). Conclusions: This study presents a comprehensive reference of normative regional brain volume changes across adulthood, highlighting substantial inter-regional variability. The findings can provide an essential foundation for differentiating normal aging patterns from early pathological alterations. Full article

Background/Objective: Neuronal intranuclear inclusion disease (NIID) is characterized by widespread deposition of eosinophilic intranuclear inclusions in multiple systems throughout the body. The aim of this study was to investigate the clinical and phenotypic features of NIID, with a focus on the potential association between the morphological features of fibrils formed by polyG (polyglycine) proteins and cognitive dysfunction in patients with NIID. Methods: This study involved a retrospective collection of clinical data from 15 patients with NIID harboring GGC repeat expansions in the NOTCH2NLC (Notch 2 N-Terminal Like C) gene (including symptoms, signs, biochemical markers, cranial MRI, MMSE, and MoCA cognitive scores). All patients underwent skin biopsy, with one additional autopsy of brain tissue. Some skin samples were stained with hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining with anti-p62 antibody. The remaining skin samples and brain tissue samples obtained from autopsies were analyzed using anti-p62 antibody immunofluorescence (IF) staining and transmission electron microscopy (TEM). The number of GGC repeats was quantified using repeat primer PCR (RP-PCR). Based on ultrastructural characteristics (morphology and diameter), inclusion fibers were classified into two subtypes, and differences in the severity of cognitive impairment between subtypes were compared. Results: The majority of patients in this cohort with NIID were female (73.3%), with an average age of onset of 61.06 ± 7.67 years. The core clinical manifestations were cognitive decline (93.3%) and autonomic dysfunction (93.3%). Cranial MRI revealed characteristic DWI “ribbon sign” in 93.3% of patients, accompanied by lateral ventricle enlargement (93.3%), cerebellar atrophy (86.6%), and high T2-FLAIR signal in the corpus callosum (93.3%). All patients were found to have pathogenic GGC amplification in the NOTCH2NLC gene (median 115, range 88–210). Skin/brain tissue pathology confirmed p62-positive nuclear inclusions, and transmission electron microscopy revealed two fiber subtypes for the first time: type A (Long, thin filamentous, 202.38 ± 42.35 nm) and type B (short rod-shaped, 73.08 ± 11.56 nm). Group analysis indicated that the diameter of fibers was significantly larger in the cognitive impairment group (p < 0.05), and the type B fiber group had lower cognitive levels (p < 0.05) and larger diameters (p < 0.05), suggesting a strong association between type B fibers and severe cognitive impairment and poor prognosis. Conclusions: The presence of two different forms of fibrils, type A and type B, in the inclusion bodies of NIID patients, and the poorer cognitive level of NIID patients in the type B group than that of type A suggest that type B fibrils can be used as a novel pathological marker of severe cognitive impairment and poor prognosis in NIID. Full article

Background: Multiple studies of the role of neurotransmitter systems in the effects of various substances on brain functions under normal conditions and at various brain disorders have demonstrated the relatively high usefulness of the electroencephalogram (EEG). However, little is known about EEG “fingerprints” of direct neurotransmitter–receptor interactions, in particular, for monoamine (MA) systems involved in the main brain functions. Methods: We looked at how the EEG effects of serotonin, dopamine, and norepinephrine receptors activating substances (quipazine, SKF-38393, and clonidine, respectively) injected into the brain’s lateral ventricles were affected by corresponding blockers (cyproheptadine, SCH-23390, and yohimbine) in freely moving rats. We introduced a method for clustering significant changes in the EEG spectra based on specific time intervals and narrow frequency subranges. Results: Stimulating serotonin and dopamine receptors caused specific suppression of EEG activity around 10 Hz and an increase near 18 Hz, respectively. The effects were reduced after pretreatment with the corresponding receptor blockers. Clonidine produced clusters of increased and decreased EEG activity around 6 Hz and 21 Hz, respectively, which were weakened by the blocker, yohimbine. These results demonstrate the “signatures” of different MA systems in EEG time–frequency clustering. Conclusions: We consider the developed approach as a potentially useful tool in clinics for evaluation of MA transmission pathology and its therapy with corresponding substances penetrating the blood–brain barrier. Full article

Bluetongue is a vector-borne viral infectious disease primarily affecting ruminants, transmitted by biting midges of the Culicoides species. The first bluetongue virus 3 (BTV-3) cases occurred in Hesse, Germany, in July 2024. From December 2024 onwards, field veterinarians observed calves born with neurological symptoms. A convenience sample of affected calves were admitted to the Veterinary Teaching Hospital at Justus-Liebig-University Giessen, Germany. A total of 13 calves from unvaccinated dams with pronounced neurological symptoms and positive PCR results for BTV-3 were studied. General and neurological examinations were performed and a blood sample was obtained for hematologic, blood biochemical and blood gas analysis. In 11 calves, magnetic resonance imaging (MRI) was performed. Due to the severe neurological lesions, all calves were euthanized and postmortem examinations were performed. The neurological examination of the calves revealed neurological indications consistent with diffuse forebrain disease. MRI revealed that all calves exhibited various stages of cortical parenchyma cell loss and secondary enlargement of the lateral ventricles. Postmortem examination revealed moderate to severe hydrocephalus internus or hydranencephaly. The results of clinical and neurological examinations, MRI, and postmortem examination, indicate severe impairment of brain development presumably associated with transplacental BTV-3 infection. Epidemiologic data and health records from the originating farms suggest that neurologic malformations developed after BTV-3 infection between 95 and 227 of the gestation period. Full article

Background and Objectives: The objective of this research is to make a comparative evaluation of the correlation between the volumetric examination of subcortical cerebral regions and white matter hyperintensities classified according to the Fazekas scoring system. Materials and Methods: A total of 236 cases with cranial MRI studies were retrospectively analyzed. This study included patients aged over 45 years who had white matter hyperintensities and who did not have a prior stroke diagnosis. White matter hyperintensities were evaluated in axial FLAIR images according to Fazekas’s grading scale. Patients with Fazekas 0 and 1 were grouped in group 1 and the patients with Fazekas 2 and 3 were grouped in group 2. MRI data processing and subcortical volumetric analyses were performed using the volBrain MRI brain volumetry system. Results: There were statistically significant differences between groups 1 and 2 in terms of cerebrospinal fluid total brain white and gray matter (p < 0.001), total brain white and gray matter (p = 0.009), total cerebrum (p < 0.001), accumbens (p < 0.001), thalamus (p < 0.001), frontal lobe (p < 0.001), parietal lobe (p < 0.001), and lateral ventricle (p < 0.001) volumes. Conclusions: Our study finds a strong link between white matter hyperintensity burden and brain atrophy. This includes volume reductions in total brain white and gray matter, frontal and parietal lobe atrophy, increased cerebrospinal fluid (CSF), and atrophy in specific brain regions such as the accumbens and thalamus. Full article

Background/Objectives: Artificial intelligence (AI) models for Alzheimer’s disease (AD) diagnosis often face the challenge of limited explainability, hindering their clinical adoption. Previous studies have relied on full-scale MRI, which increases unnecessary features, creating a “black-box” problem in current XAI models. Methods: This study proposes an explainable ensemble-based diagnostic framework trained on both clinical data and mid-slice axial MRI from the ADNI and OASIS datasets. The methodology involves training an ensemble model that integrates Random Forest, Support Vector Machine, XGBoost, and Gradient Boosting classifiers, with meta-logistic regression used for the final decision. The core contribution lies in the exclusive use of mid-slice MRI images, which highlight the lateral ventricles, thus improving the transparency and clinical relevance of the decision-making process. Our mid-slice approach minimizes unnecessary features and enhances model explainability by design. Results: We achieved state-of-the-art diagnostic accuracy: 99% on OASIS and 97.61% on ADNI using clinical data alone; 99.38% on OASIS and 98.62% on ADNI using only mid-slice MRI; and 99% accuracy when combining both modalities. The findings demonstrated significant progress in diagnostic transparency, as the algorithm consistently linked predictions to observed structural changes in the dilated lateral ventricles of the brain, which serve as a clinically reliable biomarker for AD and can be easily verified by medical professionals. Conclusions: This research presents a step toward more transparent AI-driven diagnostics, bridging the gap between accuracy and explainability in XAI. Full article