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Autoimmune encephalitis (AIE) is a type of immunoreactive encephalitic disorder and is recognized as the most prevalent noninfectious encephalitis. Nevertheless, the rarity of definitive AIE diagnosis through biopsy or autopsy represents a significant hurdle to understanding and managing the disease. In this article, we present the pathological findings of AIE and review the literature based on a distinct case of AIE presenting as CD8+ T-lymphocyte predominant encephalitis. We describe the clinical progression, diagnostic imaging, laboratory data, and autopsy findings of an 80-year-old deceased male patient. The patient was diagnosed with pulmonary tuberculosis 6 months before death and received appropriate medications. A week before admission to the hospital, the patient manifested symptoms such as a tendency to sleep, decreased appetite, and confusion.Although the patient temporally improved with medication including correction of hyponatremia, the patient progressed rapidly and died in 6 weeks. The brain tissue revealed lymphocytic infiltration in the gray and white matter, leptomeninges, and perivascular infiltration with a predominance of CD8+ T lymphocytes, suggesting a case of AIE. There was no detectable evidence of viral infection or underlying neoplasm. The autopsy revealed that this patient also had Alzheimer’s disease, atherosclerosis, arteriolosclerosis, and aging-related tau astrogliopathy. This report emphasizes the pivotal role of pathological examination in the diagnosis of AIE, especially when serological autoantibody testing is not available or when a patient is suspected of having multiple diseases.
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BACKGROUND@#Mesenchymal stem cells (MSCs) have been highlighted as a potent therapeutic option for conditions with excessive osteoclast activity such as systemic and local bone loss in rheumatic disease. In addition to their immunomodulatory functions, MSCs also directly suppress osteoclast differentiation and activation by secreting osteoprotegerin (OPG) and IL-10 but the underlying mechanisms are still to be clarified. Tumor necrosis factor-stimulated gene-6 (TSG-6) is a potent anti-inflammatory molecule that inhibits osteoclast activation and has been shown to mediate MSC’s immunomodulatory functions. In this study, we aimed to determine whether adipose tissue-derived MSC (ADMSC) inhibits the differentiation from osteoclast precursors to mature osteoclasts through TSG-6. @*METHODS@#Human ADMSCs were co-cultured with bone marrow-derived monocyte/macrophage (BMMs) from DBA/ 1J or B6 mouse in the presence of osteoclastogenic condition (M-CSF 10 ng/mL and RANKL 10 ng/mL). In some coculture groups, ADMSCs were transfected with siRNA targeting TSG-6 or OPG to determine their role in osteoclastogenesis. Tartrate-resistant acid phosphatase (TRAP) activity in culture supernatant and mRNA expression of osteoclast markers were investigated. TRAP+ multinucleated cells and F-actin ring formation were counted. @*RESULTS@#ADMSCs significantly inhibited osteoclast differentiation under osteoclastogenic conditions. Suppression of TSG-6 significantly reversed the inhibition of osteoclast differentiation in a degree similar to that of OPG based on TRAP activity, mRNA expression of osteoclast markers, and numbers of TRAP+ multinucleated cell and F-actin ring formation. @*CONCLUSION@#This study demonstrated that ADMSCs inhibit osteoclast differentiation through TSG-6 under osteoclastogenic conditions.
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The aim of this study is to investigate the genetic profiles and methylation-based classifications of Embryonal tumor with multilayered rosettes (ETMR), with a specific focus on differentiating between C19MC amplified and C19MC-not amplified groups, including cases with DICER1 mutations. To achieve this, next-generation sequencing using a targeted gene panel for brain tumors and methylation class studies using the Epic850K microarray were performed to identify tumor subclasses and their clinicopathological characteristics. The study cohort consisted of four patients, including 3 children (a 4-months/F, a 9-months/M, and a 2 y/F), and one adult (a 30 y/Male). All three tumors in the pediatric patients originated in the posterior fossa and exhibited TTYH1:C19MC fusion and C19MC amplification. The fourth case in the adult patient involved the cerebellopontine angle with biallelic DICER1 mutation. Histopathological examination revealed typical embryonal features characterized by multilayered rosettes and abundant neuropils in all cases, while the DICER1-mutant ETMR also displayed cartilage islands in addition to the classic ETMR pathology. All four tumors showed positive staining for LIN28A. The t-SNE clustering analysis demonstrated that the first three cases clustered with known subtypes of ETMR, specifically C19MC amplified, while the fourth case clustered separately to non-C19MC amplified subclass. During the follow-up period of 6~12 months, leptomeningeal dissemination of the tumor occurred in all patients. Considering the older age of onset in DICER1-mutant ETMR, genetic counseling should be recommended due to the association of DICER1 mutations with germline and second-hit somatic mutations in cancer.
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The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis is the first step for healthcare professionals to predict tumor prognosis and establish personalized treatment plans for patients. The methylation classifier can be used to perform classification on tumor samples with diagnostic difficulties due to ambiguous histology or mismatch between histopathology and molecular signatures, i.e., not otherwise specified (NOS) cases or not elsewhere classified (NEC) cases, aiding in pathological decision-making. Here, the authors elucidate upon the application of a methylation classifier as a tool to mitigate the inherent complexities associated with the pathological evaluation of brain tumors, even when pathologists are experts in histopathological diagnosis and have access to enough molecular genetic information. Also, it should be emphasized that methylome cannot classify all types of brain tumors, and it often produces erroneous matches even with high matching scores, so, excessive trust is prohibited. The primary issue is the considerable difficulty in obtaining reference data regarding the methylation profile of each type of brain tumor. This challenge is further amplified when dealing with recently identified novel types or subtypes of brain tumors, as such data are not readily accessible through open databases or authors of publications. An additional obstacle arises from the fact that methylation classifiers are primarily research-based, leading to the unavailability of charging patients. It is important to note that the application of methylation classifiers may require specialized laboratory techniques and expertise in DNA methylation analysis.