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Brain : a Journal of Neurology Nov 2023Moyamoya disease is an uncommon cerebrovascular disorder characterized by steno-occlusive changes in the circle of Willis and abnormal vascular network development. Ring...
Moyamoya disease is an uncommon cerebrovascular disorder characterized by steno-occlusive changes in the circle of Willis and abnormal vascular network development. Ring finger protein 213 (RNF213) has been identified as an important susceptibility gene for Asian patients, but researchers have not completely elucidated whether RNF213 mutations affect the pathogenesis of moyamoya disease. Using donor superficial temporal artery samples, whole-genome sequencing was performed to identify RNF213 mutation types in patients with moyamoya disease, and histopathology was performed to compare morphological differences between patients with moyamoya disease and intracranial aneurysm. The vascular phenotype of RNF213-deficient mice and zebrafish was explored in vivo, and RNF213 knockdown in human brain microvascular endothelial cells was employed to analyse cell proliferation, migration and tube formation abilities in vitro. After bioinformatics analysis of both cell and bulk RNA-seq data, potential signalling pathways were measured in RNF213-knockdown or RNF213-knockout endothelial cells. We found that patients with moyamoya disease carried pathogenic mutations of RNF213 that were positively associated with moyamoya disease histopathology. RNF213 deletion exacerbated pathological angiogenesis in the cortex and retina. Reduced RNF213 expression led to increased endothelial cell proliferation, migration and tube formation. Endothelial knockdown of RNF213 activated the Hippo pathway effector Yes-associated protein (YAP)/tafazzin (TAZ) and promoted the overexpression of the downstream effector VEGFR2. Additionally, inhibition of YAP/TAZ resulted in altered cellular VEGFR2 distribution due to defects in trafficking from the Golgi apparatus to the plasma membrane and reversed RNF213 knockdown-induced angiogenesis. All these key molecules were validated in ECs isolated from RNF213-deficient animals. Our findings may suggest that loss-of-function of RNF213 mediates the pathogenesis of moyamoya disease via the Hippo pathway.
Topics: Humans; Animals; Mice; Moyamoya Disease; Endothelial Cells; Hippo Signaling Pathway; Zebrafish; Neovascularization, Pathologic; Genetic Predisposition to Disease; Adenosine Triphosphatases; Ubiquitin-Protein Ligases
PubMed: 37399508
DOI: 10.1093/brain/awad225 -
Ugeskrift For Laeger Jan 2024Mesothelioma of the tunica vaginalis testis (MTVT) is a rare tumour and a cause of hydrocele. This case report concerns a 26-year-old male with hydrocele treated with...
Mesothelioma of the tunica vaginalis testis (MTVT) is a rare tumour and a cause of hydrocele. This case report concerns a 26-year-old male with hydrocele treated with left hydrocelectomy. Histopathology revealed MTVT, and left radical orchiectomy was performed followed by chemotherapy. Fluorescence in situ hybridization, DNA and RNA next-generation sequencing showed no mesothelioma-associated tumour suppressor gene mutations, but deletion of CDKN2A and a rare TFG-ADGRG7 fusion both reported in pleural mesotheliomas, were detected. Clinicians should consider malignancy in case of discrepancy between symptoms and objective findings in scrotal conditions.
Topics: Male; Humans; Adult; Testis; In Situ Hybridization, Fluorescence; Testicular Neoplasms; Mesothelioma; Mesothelioma, Malignant; Testicular Hydrocele
PubMed: 38305267
DOI: 10.61409/V07230476 -
Le Infezioni in Medicina 2024Following the introduction of RNA-based vaccines, COVID-19 vaccine-associated clinical lymphadenopathy (C19-LAP) has been reported as a side effect. Moreover,... (Review)
Review
Following the introduction of RNA-based vaccines, COVID-19 vaccine-associated clinical lymphadenopathy (C19-LAP) has been reported as a side effect. Moreover, subclinical lymphadenopathy detected on imaging (SLDI) has also been observed, mainly as incidental findings while performing screening tests on oncological patients. In these cases, surgical lymphadenectomy, fine-needle aspiration cytology (FNAC) and core needle biopsy (CNB) have been used as a valuable diagnostic tool for SLDI and C19-LAP. In this review the clinical, histologic and cytologic features of SLDI and C19-LAP have been investigated. A search for studies that reported on C19-LAP and SLDI histopathology and cytopathology was performed on PubMed and Google Scholar, on 11 January 2023. Thirty-one reports on SLDI and C19-LAP were retrieved and included in a pooled analysis. In total, we included 54 patients with a median age of 47 years. In our research, surgical excision, CNB and/or FNAC of C19-LAP or SLDI enlarged lymph nodes have been performed in 54 cases. Of all cases, only two metastases were diagnosed and one case was diagnosed as reactive hyperplasia with atypical follicles. The remaining cases were reactive lymphadenopathy (28 cases), follicular hyperplasia (13 cases), Kikuchi-Fujimoto disease (6 cases), granulomatous lymphadenitis (2 cases), eosinophilic lymph node abscesses (1 case), Langherans cell histiocytosis (1 case), Rosai-Dorfman disease (1 case). SLDI and C19-LAP have represented a diagnostic dilemma, especially in oncologic patients. The role of different diagnostic tools for SLDI and C19-LAP has been discussed.
PubMed: 38827838
DOI: 10.53854/liim-3202-1 -
Journal of Korean Medical Science Nov 2023The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis... (Review)
Review
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.
Topics: Humans; DNA Methylation; Brain Neoplasms; Prognosis; Databases, Factual
PubMed: 37935168
DOI: 10.3346/jkms.2023.38.e356 -
Nature Communications Oct 2023Current diagnosis of glioma types requires combining both histological features and molecular characteristics, which is an expensive and time-consuming procedure....
Current diagnosis of glioma types requires combining both histological features and molecular characteristics, which is an expensive and time-consuming procedure. Determining the tumor types directly from whole-slide images (WSIs) is of great value for glioma diagnosis. This study presents an integrated diagnosis model for automatic classification of diffuse gliomas from annotation-free standard WSIs. Our model is developed on a training cohort (n = 1362) and a validation cohort (n = 340), and tested on an internal testing cohort (n = 289) and two external cohorts (n = 305 and 328, respectively). The model can learn imaging features containing both pathological morphology and underlying biological clues to achieve the integrated diagnosis. Our model achieves high performance with area under receiver operator curve all above 0.90 in classifying major tumor types, in identifying tumor grades within type, and especially in distinguishing tumor genotypes with shared histological features. This integrated diagnosis model has the potential to be used in clinical scenarios for automated and unbiased classification of adult-type diffuse gliomas.
Topics: Adult; Humans; Brain Neoplasms; Deep Learning; Neuropathology; Glioma
PubMed: 37821431
DOI: 10.1038/s41467-023-41195-9 -
Journal of Translational Medicine Nov 2023Idiopathic pulmonary fibrosis (IPF) is the most common idiopathic interstitial lung disease. Clinical models to accurately evaluate the prognosis of IPF are currently...
BACKGROUND
Idiopathic pulmonary fibrosis (IPF) is the most common idiopathic interstitial lung disease. Clinical models to accurately evaluate the prognosis of IPF are currently lacking. This study aimed to construct an easy-to-use and robust prediction model for transplant-free survival (TFS) of IPF based on clinical and radiological information.
METHODS
A multicenter prognostic study was conducted involving 166 IPF patients who were followed up for 3 years. The end point of follow-up was death or lung transplantation. Clinical information, lung function tests, and chest computed tomography (CT) scans were collected. Body composition quantification on CT was performed using 3D Slicer software. Risk factors in blood routine examination-radiology-pulmonary function (BRP) were identified by Cox regression and utilized to construct the "BRP Prognosis Model". The performance of the BRP model and the gender-age-physiology variables (GAP) model was compared using time-ROC curves, calibration curves, and decision curve analysis (DCA). Furthermore, histopathology fibrosis scores in clinical specimens were compared between the different risk stratifications identified by the BRP model. The correlations among body composition, lung function, serum inflammatory factors, and profibrotic factors were analyzed.
RESULTS
Neutrophil percentage > 68.3%, pericardial adipose tissue (PAT) > 94.91 cm, pectoralis muscle radiodensity (PMD) ≤ 36.24 HU, diffusing capacity of the lung for carbon monoxide/alveolar ventilation (DLCO/VA) ≤ 56.03%, and maximum vital capacity (VCmax) < 90.5% were identified as independent risk factors for poor TFS among patients with IPF. We constructed a BRP model, which showed superior accuracy, discrimination, and clinical practicability to the GAP model. Median TFS differed significantly among patients at different risk levels identified by the BRP model (low risk: TFS > 3 years; intermediate risk: TFS = 2-3 years; high risk: TFS ≈ 1 year). Patients with a high-risk stratification according to the BRP model had a higher fibrosis score on histopathology. Additionally, serum proinflammatory markers were positively correlated with visceral fat volume and infiltration.
CONCLUSIONS
In this study, the BRP prognostic model of IPF was successfully constructed and validated. Compared with the commonly used GAP model, the BRP model had better performance and generalization with easily obtainable indicators. The BRP model is suitable for clinical promotion.
Topics: Humans; Idiopathic Pulmonary Fibrosis; Lung; Prognosis; Vital Capacity; Biomarkers; Fibrosis; Retrospective Studies
PubMed: 37951977
DOI: 10.1186/s12967-023-04668-5 -
Turk Patoloji Dergisi 2024This review which aims to examine the recent and current status of pathology education in medical schools, and covers the publications related to undergraduate pathology... (Review)
Review
OBJECTIVE
This review which aims to examine the recent and current status of pathology education in medical schools, and covers the publications related to undergraduate pathology education published between 2010 January and June 2023.
MATERIAL AND METHOD
A search was performed through PubMed, Google Scholar, Semantic Scholar, and Ulakbim search engines for the Science Citation Index, Science Citation Index Expanded, Emerging Sources Citation Index, Directory of Open Access Journals, Scopus, PubMed as well as TR Dizin indexed articles. The findings are categorized into two periods as 2010 January - 2020 April (pre-COVID-19 pandemic) and May 2020 - 2023 June. A total of 24 reviews/editorials/letters to the editor and 63 research articles in the pre-pandemic period and 11 reviews/ editorials/ letters to the editor and 35 research articles between 2020 May and 2023 June are included in the analysis.
RESULTS
Currently, medical education generally depends on core education programs with defined learning objectives and outcomes. Moreover, problem-based, case-based, and team-based interactive learning are being used along with traditional didactic courses. Additionally, digital/ web-based/remote education methods have gained prominence after the COVID-19 pandemic. The virtual or augmented reality and 3D drawing applications are offered as a solution for the autopsy and macroscopy courses. A scarce number of publications are found on measuring and evaluating the effectiveness of learning.
CONCLUSION
Artificial intelligence in pathology education is a topic that looks likely to become important in the near future. National and international comprehensive standardization is a necessity. A joint effort and collective intelligence are needed to achieve the desired goals in undergraduate pathology education.
Topics: Humans; COVID-19; Education, Medical, Undergraduate; Pathology; Pandemics; SARS-CoV-2; Coronavirus Infections; Pneumonia, Viral; Curriculum; Betacoronavirus
PubMed: 38265100
DOI: 10.5146/tjpath.2023.13048 -
Kidney360 Nov 2023Veterinary nephrology is a specialized field of veterinary medicine providing a high level of care for animals with all types of kidney disease. Veterinarians complete...
Veterinary nephrology is a specialized field of veterinary medicine providing a high level of care for animals with all types of kidney disease. Veterinarians complete extensive training to become board-certified in veterinary nephrology-urology. Companion animal nephrology is the most advanced field; however, all species are afflicted by a variety of renal disorders. Most naturally occurring animal kidney diseases have similar disorders found in people; where veterinary research is lacking, clinical management is often modified from standard of care in people. Veterinarians have become adept at scaling down procedures to safely perform them on dogs and cats weighing only a few kilograms. Advanced diagnostics (renal biopsy, cystoscopy, fluoroscopic studies, etc. ) and therapeutics (renal replacement therapy, interventional endourology, etc. ) are commonly performed within the practice of veterinary nephrology-urology. Collaboration between veterinary and human nephrologists may advance both disciplines and improve care for people and animals alike.
Topics: Animals; Cats; Dogs; Humans; Nephrology; Cat Diseases; Dog Diseases; Kidney; Kidney Diseases; Animal Diseases
PubMed: 37840194
DOI: 10.34067/KID.0000000000000273 -
Diagnostics (Basel, Switzerland) Aug 2023Deep learning (DL), often called artificial intelligence (AI), has been increasingly used in Pathology thanks to the use of scanners to digitize slides which allow us to... (Review)
Review
Deep learning (DL), often called artificial intelligence (AI), has been increasingly used in Pathology thanks to the use of scanners to digitize slides which allow us to visualize them on monitors and process them with AI algorithms. Many articles have focused on DL applied to prostate cancer (PCa). This systematic review explains the DL applications and their performances for PCa in digital pathology. Article research was performed using PubMed and Embase to collect relevant articles. A Risk of Bias (RoB) was assessed with an adaptation of the QUADAS-2 tool. Out of the 77 included studies, eight focused on pre-processing tasks such as quality assessment or staining normalization. Most articles ( = 53) focused on diagnosis tasks like cancer detection or Gleason grading. Fifteen articles focused on prediction tasks, such as recurrence prediction or genomic correlations. Best performances were reached for cancer detection with an Area Under the Curve (AUC) up to 0.99 with algorithms already available for routine diagnosis. A few biases outlined by the RoB analysis are often found in these articles, such as the lack of external validation. This review was registered on PROSPERO under CRD42023418661.
PubMed: 37627935
DOI: 10.3390/diagnostics13162676