Abstract: Background and Clinical Significance: Plexiform fibromyxoma (PFM) is a rare benign gastric mesenchymal neoplasm characterized by multinodular plexiform growth of bland spindle cells in a myxoid or fibromyxoid stroma. We report a case of the cellular form of PFM with limited myxoid stroma and aberrant KIT expression, resulting in diagnostic difficulty by biopsy. Case presentation: A 59-year-old woman presented with a slowly enlarging 15-mm gastric antral submucosal tumor. A resected specimen by laparoscopic and endoscopic cooperative surgery revealed spindle cell proliferation forming plexiform nodules with a myxoid background in limited areas. Positive immunoreactivity of a subset of spindle cells for KIT suggested a diagnosis of gastrointestinal stromal tumor (GIST), although DOG1 was negative. In addition, diffuse staining for CD10, smooth muscle actin, and D2-40 were confusing. MALAT1::GLI1 fusion was detected by next-generation sequencing analysis. Consequently, a diagnosis of PFM was established. Conclusions: This case expands the morphologic and immunophenotypic spectrum of PFM and indicates the possible diagnostic utility and biological significance of D2-40 expression. Although molecular confirmation of MALAT1::GLI1 fusion is definitive for diagnosis of PFM, the findings of present case may aid diagnosis in challenging cases that mimic GIST.

Abstract: Background: Artificial intelligence (AI) shows promising results in lymphoma detection, prediction, and classification. However, translating these findings into practice requires a rigorous assessment of potential biases, clinical utility, and further validation of research models. Objective: The goal of this study was to summarize existing studies on artifi- cial intelligence models for the histopathological detection of lymphoma. Design: This study adhered to the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines. A systematic search was conducted across three major databases (Scopus, PubMed, Web of Science) for English-language articles and reviews published between 2016 and 2025. Seven precise search queries were applied to identify relevant publications, accounting for variations in study modality, algorithmic architectures, and disease-specific terminology. Results: The search identified 615 records, of which 36 articles met the inclusion criteria. These studies presented 36 AI models, comprising 30 diagnostic and 6 prognostic applica- tions, with Convolutional Neural Networks (CNNs) being the predominant architecture. Regarding data sources, 83% (30/36) of datasets utilized Hematoxylin and Eosin (H&E) stained images, while the remainder relied on diverse modalities, including IHC stained slides, bone marrow smears, and other tissue preparations. Studies predominantly utilized retrospective, private cohorts with sample sizes typically ranging from 50 to 400 patients; only a minority leveraged open-access repositories (e.g., Kaggle, TCGA). The primary appli- cation was slide-level multi-class classification, distinguishing between specific lymphoma subtypes and non-neoplastic controls. Beyond diagnosis, a subset of studies explored advanced prognostic tasks, such as predicting chemotherapy response and disease progres- sion (e.g., in CLL), as well as automated biomarker quantification (c-MYC, BCL2, PD-L1). Reported diagnostic performance was generally high, with accuracy ranging from 60% to 100% (clustering around 90%) and AUC values spanning 0.70 to 0.99 (predominantly >0.90). Conclusions: While AI models demonstrate high diagnostic accuracy, their translation into practice is limited by unstandardized protocols, morphological complexity, and the "black box" nature of algorithms. Critical issues regarding data provenance, image noise, and lack of representativeness raise risks of systematic bias, hence the need for rigorous validation in diverse clinical environments.

Abstract: Mesonephric-like adenocarcinoma is a rare uterine neoplasm recognized in the fifth edition of the World Health Organization Classification of Female Genital Tumors and poses diagnostic challenges due to its morphologic and immunophenotypic overlap with other endometrial carcinomas. We retrospectively reviewed three cases diagnosed at our institution, evaluating clinical presentation, histologic features, immunohistochemical profile, and available molecular findings, and performed a literature review of approximately 200 reported cases with emphasis on comorbidities and potential predisposing factors. All three patients presented with abnormal uterine bleeding and had hypothyroidism, and one patient had Down syndrome, representing the first reported case in this population. Tumors consistently expressed thyroid transcription factor 1, showed variable GATA3 expression, and demonstrated limited or absent hormone receptor expression. Literature review revealed frequent association with Müllerian-type lesions and recurrent KRAS mutations, while thyroid disease was not identified as a consistent comorbidity. These findings support a Müllerian origin for mesonephric-like adenocarcinoma and suggest that hypothyroidism is unlikely to represent a defining association. The occurrence in a patient with Down syndrome raises the possibility of an underlying genetic susceptibility that warrants further investigation.

Abstract: Diffuse large B-cell lymphoma (DLBCL) is one of the most frequent subtypes of non-Hodgkin lymphoma (NHL). In approximately 40% of the patients, the prognosis and clinical evolution is unfavorable. This study is a proof-of-concept computer vision exercise to support the feasibility of predicting the prognosis of DLBCL using only hematoxylin and eosin (H&E) histological images and deep learning. A conventional series of DLBCL of 114 cases was split into two prognostic groups according to the overall survival (curve fitting and slope analysis): patients who died before the first 2 years (“Dead 2-years”, b1 = -0.054), and the others (b1 = -0.003). Twenty different convolutional neural networks (CNN) were used, and explainable artificial intelligence (XAI) was used to identify the areas of the images that the network used for classification. The final model based on DarkNet-19 predicted prognosis groups with high performance (test set accuracy = 96.26%). The other performance parameters were precision (94.46%), recall (95.02%), false positive rate (3.07%), specificity (96.93%), and F1 score (94.74%). XAI, including grad-CAM, occlusion sensitivity, and image-LIME confirmed that the CNN was focusing on the correct areas. Correlation with the clinicopathological characteristics found that the Dead < 2-years group was correlated with stage III-IV, International Prognostic Index (IPI) High + High/intermediate, progressive disease, non-GCB cell-of-origin, CD10-, BCL2+, and EBER+. Analysis of the immune microenvironment, cell cycle, and germinal center markers showed that Dead < 2-years had higher IL10, PD-L1, and CD163, and lower E2F1 protein expressions. In conclusion, the overall survival of DLBCL can be predicted using H&E histological images and deep learning. The trained CNN could be used as pre-trained CNN model for transfer learning in the future.

Abstract: Backgraund/Objectives: Transient receptor potential melastatin 7 (TRPM7), a unıque ion channel protein, has important effects for the proliferation of many cancer cell lines and tumor progression in various cancers. This study aimed to investigate whether TRPM7 expression has an effect on the prognosis of patients with colorectal cancer (CRC). Methods: TRPM7 expression was evaluated in paraffin-embedded tu-mor tissues of 259 CRC patients, immunohistochemically. In addition, the ratio of CD4+/CD8+ lymphocytes in the tumor microenvironment was determined semi-quantitatively. Results: According to our data, tumor size was clearly higher in cases with high TRPM7 expression than those with low expression. TRPM7 overex-pression was closely related to high depth of tumor invasion, increased lymph node metastasis and high distant metastasis rate. These findings exposed that high TRPM7 expression is effective in the progression and aggressiveness of CRC. While there was a negative correlation between TRPM7 overexpression and the density of CD8+ TILs, a positive correlation was revealed between TRPM7 expression and the CD4+/CD8+ TILs ratio. This result aroused curiosity for further studies on what kind of connection is between the TRPM7 channel protein and TILs. Also, high TRPM7 expression was closely associated with low overall (OS) and disease-free survival (DFS) times. Fur-thermore, multivariate analyses revealed TRPM7 overexpression was independently related with short OS and DFS. Conclusions: In conclusion, the high TRPM7 expres-sion and CD4+/CD8+ TILs ratio are independent poor prognostic indicators in CRC. In the future, TRPM7 may be a promising biomolecule for new targeted treatment options for CRC.

Abstract: The dichotomous outcomes of chronic lung inflammation, represented by either pulmonary emphysema or interstitial fibrosis, involve poorly understood overlapping mechanisms. Recent insights from network theory suggest that percolation phenomena, coupled with the dynamics of extracellular matrix crosslinking, play an important role in determining these divergent pathological trajectories. This review examines how critical percolation thresholds at which local damage or repair transitions to system-wide structural failure or rigidification determine the changes in lung tissue during chronic inflammation. We examine the mechanisms of collagen and elastin crosslinking, the feedback loops that amplify initial perturbations, and the threshold behaviors that push inflamed lung tissue toward either emphysematous destruction or fibrotic consolidation. Understanding these percolation-dependent transitions provides new insights into why similar inflammatory insults can produce opposite structural outcomes and suggests novel therapeutic strategies targeting the crosslinking mechanisms that underlie these critical transitions.

Abstract: Cutaneous melanoma is one of the most aggressive skin cancers known. Over the years, multiple studies have focused on researching novel treatment options. For this purpose, numerous areas have been analyzed, and the focus has shifted toward the mechanisms by which immune-modulating molecules act within the microenviron-ment. Among these, ATP-binding cassette transporters and stem-associated pathways have been shown to influence drug response and immune escape. ABCB5 is a gene with multiple isoforms that significantly influences the immune response. In melano-ma, the ABCB5α isoform is predominantly expressed, primarily in tumor stem-like cells. Thus, it can alter the effects of medications by promoting chemoresistance via ac-tive drug efflux. The gene also regulates pathways PI3K/Akt, BCL-2, and miR-145, leading to overexpression. ABCB5 positive cells create an immunosuppressive micro-environment via cytokines (IL-8, IL-6, TGF-β) and death ligands (PD-L1), favoring tumor progression, thus correlating with poor prognosis. This review integrates cur-rent data on the molecular and microenvironmental mechanisms, underlying mela-noma progression and therapy resistance, highlighting ABCB5 as one of the several emerging biomarkers with potential prognostic and therapeutic relevance.

Abstract: Small molecules either derived from cell metabolic reactions or produced by gut bacterial flora have shown the potential of affecting gene expression, which suggests the possibility of interactions able to modulate cellular functions. In this context, the reported experi-ments were aimed at verifying a possible interplay between lactate and butyrate in modu-lating the efficacy of antineoplastic drugs. Butyrate is a product of gut bacterial flora, shown to be endowed with anticancer properties; conversely, increased lactate levels in cancer cells were found to be associated with higher proliferation and drug resistance. For the reported experiments, we adopted two cell cultures from clinically relevant, but dif-ferent cancer forms: pancreatic and triple-negative mammary adenocarcinomas. In spite of their different tissue origin, the two cell cultures appeared to similarly respond to the effects of the two metabolites, which were found to modulate in opposite ways the expres-sion of key genes involved in DNA repair by homologous recombination. As a conse-quence, changed efficacy of this repair pathway and modified response to PARP inhibi-tors were observed. Notably, our results also suggest that the counteracting effect between these two metabolites may be leveraged to address additional challenges limiting the suc-cess of anticancer therapies.

Abstract: Thrombocytopenia is a frequent complication of patients presenting emergently across the world for a wide array of etiologies. From patients who develop thrombocytopenia due to invasive neoplastic disease affecting the bone marrow to patients who developed immune-complications secondary to formation of auto-antibody responses that drive patients’ platelets counts lower or even infection, stress the clearest need of prompt tests to discern the more likely thrombocytopenic-inducing cause. It is in this setting that looking at other platelet variables easily obtainable from modern hematology analyzers have gained traction. One of these elements found in extended platelet profiles are immature platelets (youngest and newly released platelets) also known as reticulated platelets depending upon the platform performing the measurement. Among the advantages of obtaining these counts is that it represents the immediate responses by the bone marrow to the thrombocytopenia and depending on etiology inducing the thrombocytopenia it also provides information of the marrow response to therapeutic approaches. It is in this context that this review will present information of how these relatively novel platelet parameters can be used in clinical practice and how they can be a rapid gauge of the body’s response to disease processes leading to thrombocytopenia. Thrombocytopenias resulting from infection (sepsis), autoantibody formation (immune thrombocytopenia and immune-mediated thrombotic thrombocytopenic purpura), immune dysregulation (systemic lupus erythematosus), and iatrogenic (drug-induced) will be discussed and be used to explain how these young platelet measurements can provide valuable clinical information.

Abstract: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating multi-system illness with heterogeneity that complicates identifying the pathophysiology, biomarkers, and therapeutic targets. Evidence indicates the importance of immune dysregulation, including the complement system, in ME/CFS. This study investigates the contribution of genetic drivers to potential dysregulation of the complement pathway in ME/CFS. We used protein quantitative trait loci (pQTL) analyses, adjusted for covariates using linear and logistic regression, to identify genetic variants significantly associated with plasma complement protein levels in a study sample identified from the general population (50 ME/CFS and 121 non-fatigued). ME/CFS patients carrying certain pQTLs exhibited dysregulation of the alternative complement pathway, which defined an inflammatory subgroup with a high C3/low Bb profile and established a genetic link to dysregulation of the alternative complement pathway. Six of the significant pQTLs were also found associated with fatigue-related phenotypes in the UK biobank, 4 of which were complement-associated, providing some validation in an independent population. Our findings highlight a mechanism by which risk alleles contribute to ME/CFS heterogeneity, providing evidence of a genetic basis for complement dysregulation in a subgroup. This approach could identify pathway-focused subgroups in ME/CFS and similar illnesses to inform personalized approaches to diagnosis and treatments.

Abstract: Background: Mammary ductal hyperplasia represents a spectrum of benign proliferative breast lesions, some of which pose elevated risks for malignant transformation into ductal carcinoma in situ and invasive breast cancer. This narrative review explores why only specific types, particularly those with atypia, exhibit higher progression potential, synthesizing epidemiologic, histopathologic, molecular, and environmental insights. Methods: We reviewed key literature from databases, including PubMed, focusing on classification, risk stratification, genetic/epigenetic mechanisms, tumor microenvironment dynamics, and modifiable factors influencing progression. Results: Benign breast lesions are categorized into non-proliferative, proliferative without atypia, and proliferative with atypia, such as atypical ductal hyperplasia and atypical lobular hyperplasia. Atypia represents a morpho-logic continuum toward low-grade ductal carcinoma in situ, driven by genetic alterations, epigenetic reprogramming, and changes in the tumor microenvironment, including stromal remodeling, immune infiltration, hypoxia-induced angiogenesis, and extracellular matrix degradation. Dietary factors, such as high-fat intake and obesity, exacerbate progression through inflammation, insulin resistance, and adipokine imbalance, while environmental toxins, including endocrine disruptors, pesticides, and ionizing radiation, amplify genomic instability. Conclusions: Understanding differential risks and mechanisms underscores the need for stratified surveillance, biomarker-driven interventions, and lifestyle modifications to mitigate progression. Future research should prioritize molecular profiling for personalized prevention in high-risk hyperplasia.

Abstract: Traumatic brain injury (TBI) and malignancies, despite their distinct nature, are characterized by similar immune responses, including the development of local and systemic inflammation and T-cell exhaustion. This article compares the role of immune checkpoints in the development of immune dysfunction in cancer and TBI, examines the contribution of the sympathetic nervous system to these changes, and discusses the relationship between local and systemic inflammation in these two conditions. Particular attention is paid to approaches to pharmacological modulation of inflammation and the impact on exhausted T-cells in these conditions. Comparison of inflammation and T-cell exhaustion in cancer and TBI highlights existing gaps in our understanding of immune regulation in TBI and points to areas requiring further investigation. Clarification of the immune mechanisms underlying the pathogenesis of TBI may facilitate the search for new diagnostic markers and lay the groundwork for the development of new therapeutic approaches for TBI treatment.

Abstract: Background: Plasmablastic lymphoma (PBL) is a rare and highly aggressive B-cell neoplasm most often associated with immunodeficiency. Transformation of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) into PBL is exceptionally uncommon, particularly in immunocompetent individuals. This paper describes a rare synchronous SLL-to-PBL transformation and summarizes current knowledge on synchronous and metachronous cases reported in the literature. Methods: A 46-year-old immunocompetent woman presented with generalized lymphadenopathy and lumbar pain. Concurrent biopsies of an axillary lymph node and a retroperitoneal mass were obtained. Diagnostic evaluation included immunohistochemistry, fluorescent in situ hybridization (FISH), PCR-based assessment of IGH, IGK, and IGL loci, and next-generation sequencing (NGS) of IGHV to assess clonal relatedness. The patient was treated with six cycles of Dara-CHOP, followed by autologous stem cell transplantation and maintenance therapy with daratumumab and ibrutinib. Results: The axillary node showed SLL (CD20+, CD5+, CD23+), while the retroperitoneal mass demonstrated classic features of PBL (CD138+, MUM1+, MYC+, Ki-67 ~100%, CD20–). FISH detected MYC rearrangement in the PBL component. PCR and NGS confirmed identical IGHV1-69 rearrangements, establishing clonal relatedness and Richter transformation. Review of published cases shows that both synchronous and metachronous CLL/SLL-to-PBL transformations are exceedingly rare. The patient achieved partial metabolic remission after treatment and remains in sustained metabolic response 24 months after diagnosis. Conclusions: This case highlights a rare example of synchronous CLL/SLL-to-PBL transformation in an immunocompetent patient. Integration of detailed molecular diagnostics enabled early recognition and guided a personalized treatment approach incorporating CD38-targeted therapy and BTK inhibition, resulting in an excellent long-term clinical outcome.

Abstract: Background/Objectives: Variations in staining styles—arising from differences in tissue preparation, scanners, and laboratory protocols—severely compromise the robustness of automated cell segmentation algorithms in digital pathology. Moreover, manual nucleus annotation is extremely labor-intensive, leading to a scarcity of large-scale, fully anno-tated datasets for supervised nucleus segmentation. This study proposes a novel framework that simultaneously mitigates staining variability and achieves high-accuracy nucleus segmentation using only minimal annotations. Methods: We present 3SGAN, a multitask dual-branch generative adversarial network (GAN) that jointly performs stain normalization and nucleus segmentation in a semi-supervised manner. The framework adopts a teacher-student paradigm: a lightweight teacher model (AttCycle) equipped with attention gates generates reliable pseudo-labels, while a high-capacity student model (TransCycle) leveraging a hybrid CNN-Transformer architecture further refines performance. 3SGAN was trained and evaluated on a large dataset of 1,408 Whole-Slide Images (WSIs) from two medical institutions, encompassing 101 distinct staining styles, with nucleus-level annotations required for only 5% of the data. Results: 3SGAN sig-nificantly outperformed state-of-the-art methods, achieving substantial improvements in stain normalization quality (RMSE, PSNR, SSIM) and marked gains in nucleus seg-mentation performance (F1 score, mean IoU, and AJI). External validation on independent MoNuSeg and PanNuke datasets, as well as on previously untested tumor-rich non-ROI regions from our in-house WSIs, confirmed strong generalizability with excellent stain normalization and top-tier segmentation accuracy across diverse staining protocols, tissue types, and pathological patterns. Conclusions: The proposed 3SGAN framework demonstrates that high-performance nucleus segmentation and stain normalization can be achieved with minimal annotation requirements, offering a practical and scalable solution for digital pathology applications across diverse clinical settings and staining protocols.

Abstract: This review article attempts to provide a unifying hypothesis to explain the myriad of symptoms and predispositions underlying the development of PASC (Postacute Sequelae of COVID), often referred to as Long COVID. The hypothesis described here proposes that Long COVID is best understood as a disorder of persistent immune dysregulation, with chronic macrophage activation representing the fundamental underlying pathophysiology. Unlike transient post-viral syndromes, long COVID involves a sustained innate immune response, particularly within monocyte-derived macrophages, driven by persistent spike protein (peripherally in MAIT cells and centrally in Microglial cells), epigenetic imprinting, and gut-related viral reservoirs. These macrophages are not merely activated temporarily, but become epigenetically “trained” into a prolonged inflammatory state, as demonstrated by enduring histone acetylation markers such as H3K27acDNA Reprogramming. It is proposed that recognizing macrophage activation as the central axis of Long COVID pathology offers a framework for personalized risk assessment, targeted intervention, and therapeutic recalibration.

Abstract: Human papillomavirus (HPV) plays a crucial role in the pathogenesis of oropharyngeal squamous cell carcinomas (OPSCC). Accurate HPV status classification is essential for therapeutic stratification. While p16 immunohistochemistry (IHC) is the clinical surrogate marker, it has limited specificity. In this study, we implemented a weakly supervised deep learning approach using the Clustering-constrained Attention Multiple Instance Learning (CLAM) framework to directly predict HPV status from hematoxylin and eosin (H&amp;E)-stained whole-slide images (WSIs) of OPSCC. A total of 123 WSIs from two cohorts (TCGA and OPSCC-UNINA) were used. Attention heatmaps revealed that the model predominantly focused on tumor-rich regions. Errors were primarily observed in slides with conflicting p16/ISH status or suboptimal quality. Morphological analysis of high-attention patches confirmed that cellular features extracted from correctly classified slides align with HPV status, with a Random Forest classifier achieving 83% accuracy at the cell level. This work supports the feasibility of deep learning-based HPV prediction from routine H&amp;E slides, with potential clinical implications for streamlined, cost-effective diagnostics.

Abstract: Background: Histologic healing is increasingly recognized as a sensitive marker of disease remission in ulcerative colitis (UC). However, the dynamics of mucosal T lymphocytes and pro-inflammatory cytokines during healing remain incompletely understood. Methods: In this observational, cross-sectional study, paired colonic biopsies from 20 adult UC patients were analyzed during active inflammation and subsequent histologic healing. Immunohistochemistry was performed for CD3, CD4, CD8, and IL-6. Lymphocyte densities were quantified in intraepithelial and lamina propria compartments, while IL-6 expression was scored semi-quantitatively. Histologic activity was assessed using the Geboes score. Results: Intraepithelial CD4⁺ T cells significantly decreased during histologic healing (mean 6.8 → 3.75 cells/HPF, p < 0.05), whereas lamina propria CD4⁺ cells remained variably persistent, suggesting ongoing immune regulation. Intraepithelial CD8⁺ cells increased during remission, indicating a potential reparative or surveillance role. IL-6 expression markedly declined in epithelial and stromal compartments during healing, reflecting resolution of mucosal inflammation. Correlation analyses revealed enhanced coordination between CD4⁺ and CD8⁺ cells in the healing phase, consistent with immune homeostasis. Conclusions: Histologic healing in UC involves compartment-specific shifts in T lymphocyte populations and a marked reduction of IL-6 expression, reflecting coordinated immune regulation beyond clinical remission. These findings highlight the potential of combined cellular and cytokine biomarkers to monitor mucosal healing and guide immunomodulatory therapies.

Abstract: To contrast the COVID-19 pandemic brought by the corona virus SARS-CoV-2, two mRNA-based anti-COVID-19 vaccines (by Pfizer-BioNTech and Moderna) were rela-tively soon made available and deployed worldwide based on an emergency approval. Being considered vulnerable and at risk of infection, cancer patients have been priori-tized for COVID-19 vaccination and vaccinated repeatedly because of the short-time protection provided by these vaccines. During the pandemic, because of the large number of infected patients requiring assistance, many hospitals opted for giving pri-ority to these patients while postponing the specialist treatment for other pathologies, including cancer. Recently, a surge in the incidence and rapid progression of cancers has been observed in many countries, which could (at least partially) represent those cancers undiagnosed or untreated during the pandemic. It has also been suggested that the SARS-CoV-2 itself or even the anti-COVID-19 mRNA vaccines could have contrib-uted to the recurrence and worse clinical outcome in cancer patients, given the high incidence of COVID-19 in hospitalized patients and that these patients have been vac-cinated with priority several times and in a short period. Although it appears ex-tremely unlikely that SARS-CoV-2 and anti-COVID-19 mRNA vaccines elicit genotoxic events and cause neo-cancerogenesis in a short time, they could still cause non-genotoxic pro-carcinogenic effects by triggering an exaggerated inflammatory re-action, compromising immune homeostasis, stimulating cell proliferation, and nega-tively affecting cellular stress response and damage repair machinery. This could re-sult in the promotion of regrowth of dormant micrometastases or relapse of stable minimal residual disease. Such a harmful outcome may likely result from a synergy between the virus and the vaccine, especially in multi-vaccinated and multi-infected individuals. Here, I bring the cell pathologist's point of view and discuss the multiple possible mechanisms by which the virus and the anti-COVID-19 mRNA vaccine might favor tumorigenesis. While a causal link cannot be established at this stage, knowledge of potential carcinogenic risks could help doctors and health policymakers take the best actions to protect vulnerable patients and convince the vaccine developer to de-sign a vaccine free from such harm.

Abstract:

Background and Objectives: Differentiating between subtypes of renal cell carcinoma (RCC) can be challenging due to overlapping immunohistochemical and histomorphological features. Furthermore, despite the evaluation of numerous histopathologic parameters, predicting metastasis and prognosis remains unclear. In this study, we aimed to evaluate the potential of microRNA (miRNA) expression levels in establishing definitive diagnoses, assessing metastatic potential, and determining patient prognosis. Materials and Methods: A total of 35 clear cell RCC (cc-RCC), 11 chromophobe RCC (ch-RCC), 9 papillary RCC (p-RCC) cases, and 9 cc-RCC metastases were retrospectively analyzed. MiRNA-21 and miRNA-210 expression profiles were assessed using non-parametric tests, receiver operating characteristic (ROC) analysis, and Cox regression models. Results: The expression levels of both miRNA-21 and miRNA-210 were significantly elevated in cc-RCC and p-RCC cases. In contrast, miRNA-210 expression levels were significantly reduced in all ch-RCC cases, whereas miRNA-21 expression showed no significant change. Although miRNA-21 expression levels were higher in metastases compared to primary cc-RCC tumors, the difference was not statistically significant (p=0.053). No significant difference was observed in miRNA-210 expression between metastatic and primary cc-RCC tumors (p=0.237). Regardless of histological subtype, an increase in miRNA-210 expression was associated with a significant reduction in overall survival (p=0.03, HR=1.729, 95% CI: 1.043-2.864). Conclusion: The findings suggest that miRNA-21 and miRNA-210 expression levels can help distinguish ch-RCC from cc-RCC and p-RCC. Additionally, miRNA-210, but not miRNA-21, may differentiate cc-RCC from p-RCC. Higher miRNA-210 expression levels were associated with worse overall survival in RCC patients. While miRNA-21 levels were increased in cc-RCC metastases, further studies with larger sample sizes are needed to establish its role in predicting metastasis.

Abstract: Parkinson’s disease (PD) is a multisystem disorder, with early changes extending beyond basal ganglia circuitries and involving non-dopaminergic pathways, including cerebellar networks. Whether cerebellar dysfunction reflects a compensatory mechanism or an intrinsic hallmark of disease progression remains unresolved. In this cross-sectional study, we examined how cerebellar γ-aminobutyric acid (GABA) and glutamate/glutamine (Glx) systems, as well as their excitatory/inhibitory (E/I) balance, are modulated along the disease course. As to ascertain how these mechanisms contribute to motor and non-motor features in the premotor and early stages of PD, 18 individuals with isolated REM sleep behaviour disorder (iRBD) 20 de novo, drug-naïve PD (dnPD), and 18 matched healthy controls underwent clinical, cognitive, and neuropsychiatric assessments alongside cerebellar magnetic resonance spectroscopy (MRS, MEGA-PRESS, 3T). While cerebellar neurotransmitter levels did not differ significantly across groups, dnPD patients exhibited a shift toward hyperexcitability in the E/I ratio, without correlation to clinical or cognitive measures. In contrast, in iRBD an inverse relationship between heightened GABAergic activity and neuropsychiatric symptoms emerged. These findings suggest an early, dynamic cerebellar involvement, potentially reflecting compensatory modulation of altered basal ganglia output. Our results support cerebellar GABA MRS as a promising biomarker and open perspectives for targeting non-dopaminergic pathways in PD.