Hepatic ultrastructural features distinguish paediatric Wilson disease from NAFLD and autoimmune hepatitis.

BACKGROUND AND AIMS: Wilson disease (WD) has diverse presentations that frequently mimic other liver diseases. Distinguishing WD from non-alcoholic fatty liver disease (NAFLD) and autoimmune hepatitis (AIH), can be difficult and has critical implications for medical management. This study aimed to examine the utility of histological features of WD in children compared to those with NAFLD and AIH. METHODS: A review of liver biopsy slides was performed in children with a clinical and/or genetic diagnosis of WD, seen at the Hospital for Sick Children between 1981 and 2019 and compared to controls with NAFLD and AIH. 37 children with WD and 37 disease controls (20 NAFLD; 17 AIH) were included. Three pathologists, blind to clinical details and diagnosis, reviewed all liver biopsies to reach consensus. Clinical and histopathologic features were compared between groups. RESULTS: Most WD cases displayed steatosis or steatohepatitis on histology (34/37), active AIH-pattern in 1 and inactive cirrhosis in 2 cases. Electron microscopy (EM) findings of mitochondrial abnormalities including dilated tips of cristae, pleomorphism, membrane duplication and dense matrix were more frequent in the WD group as compared to disease controls (p < 0.0001). In WD, dilated tips of mitochondrial cristae had a sensitivity of 91% and specificity of 86%, best among EM features. CONCLUSIONS: Light microscopic findings display considerable overlap among children with WD, NAFLD and AIH. Ultrastructural findings of mitochondrial abnormalities are important to distinguish WD from NAFLD and AIH. EM examination should be considered essential in the diagnostic work-up of paediatric liver biopsies.

Liver transplantation for Gaucher disease presenting as neonatal cholestasis: Case report and literature review.

BACKGROUND: We present a rare case of neonatal cholestasis in a female infant with Gaucher Disease (GD), who received liver transplantation. We review the relevant literature on similar disease presentations. METHODS: A chart review of the index case was performed. PubMed and Medline databases were searched to identify other cases. RESULTS: A 4-day-old female was referred with conjugated hyperbilirubinemia. Physical examination revealed icterus with hepatosplenomegaly and normal neurologic examination. The diagnosis of GD was confirmed through liver biopsy, low glucocerebrosidase enzyme activity, and two pathogenic mutations in GBA gene. Despite early initiation of ERT, the patient had worsening of her liver failure and underwent a left lateral segment liver transplant from a living donor at 7 months of age. She experienced improvement of her liver enzymes and coagulation, but passed away at 8 months due to the late onset of neurologic involvement. Nine other cases of GD presenting with neonatal cholestasis have been reported. Forty-four percent (4/9) of cases received ERT and none were considered for transplant. Overall, the literature suggests a poor prognosis with death reported in 77% (7/9) cases. CONCLUSIONS: Neonatal presentation of GD represents a poor prognosis despite early initiation of treatment. Diagnosis remains a challenge as the presentation is rare and multiple tests such as BM biopsy, liver biopsy with both light and electron microscopy, enzymology, and genetic testing may need to be completed to reach a diagnosis. Neurological sequelae may manifest later making the decision to proceed with liver transplantation a difficult one.

Artificial Intelligence-Powered Mammography: Navigating the Landscape of Deep Learning for Breast Cancer Detection.

Worldwide, breast cancer (BC) is one of the most commonly diagnosed malignancies in women. Early detection is key to improving survival rates and health outcomes. This literature review focuses on how artificial intelligence (AI), especially deep learning (DL), can enhance the ability of mammography, a key tool in BC detection, to yield more accurate results. Artificial intelligence has shown promise in reducing diagnostic errors and increasing early cancer detection chances. Nevertheless, significant challenges exist, including the requirement for large amounts of high-quality data and concerns over data privacy. Despite these hurdles, AI and DL are advancing the field of radiology, offering better ways to diagnose, detect, and treat diseases. The U.S. Food and Drug Administration (FDA) has approved several AI diagnostic tools. Yet, the full potential of these technologies, especially for more advanced screening methods like digital breast tomosynthesis (DBT), depends on further clinical studies and the development of larger databases. In summary, this review highlights the exciting potential of AI in BC screening. It calls for more research and validation to fully employ the power of AI in clinical practice, ensuring that these technologies can help save lives by improving diagnosis accuracy and efficiency.

Using Deep Learning to Automate Eosinophil Counting in Pediatric Ulcerative Colitis Histopathological Images.

Background: Accurate identification of inflammatory cells from mucosal histopathology images is important in diagnosing ulcerative colitis. The identification of eosinophils in the colonic mucosa has been associated with disease course. Cell counting is not only time-consuming but can also be subjective to human biases. In this study we developed an automatic eosinophilic cell counting tool from mucosal histopathology images, using deep learning. Method: Four pediatric IBD pathologists from two North American pediatric hospitals annotated 530 crops from 143 standard-of-care hematoxylin and eosin (H & E) rectal mucosal biopsies. A 305/75 split was used for training/validation to develop and optimize a U-Net based deep learning model, and 150 crops were used as a test set. The U-Net model was then compared to SAU-Net, a state-of-the-art U-Net variant. We undertook post-processing steps, namely, (1) the pixel-level probability threshold, (2) the minimum number of clustered pixels to designate a cell, and (3) the connectivity. Experiments were run to optimize model parameters using AUROC and cross-entropy loss as the performance metrics. Results: The F1-score was 0.86 (95%CI:0.79-0.91) (Precision: 0.77 (95%CI:0.70-0.83), Recall: 0.96 (95%CI:0.93-0.99)) to identify eosinophils as compared to an F1-score of 0.2 (95%CI:0.13-0.26) for SAU-Net (Precision: 0.38 (95%CI:0.31-0.46), Recall: 0.13 (95%CI:0.08-0.19)). The inter-rater reliability was 0.96 (95%CI:0.93-0.97). The correlation between two pathologists and the algorithm was 0.89 (95%CI:0.82-0.94) and 0.88 (95%CI:0.80-0.94) respectively. Conclusion: Our results indicate that deep learning-based automated eosinophilic cell counting can obtain a robust level of accuracy with a high degree of concordance with manual expert annotations.

NOXA expression is downregulated in human breast cancer undergoing incomplete pathological response and senescence after neoadjuvant chemotherapy.

Neoadjuvant chemotherapy (NAC) is a frequently utilized approach to treat locally advanced breast cancer, but, unfortunately, a subset of tumors fails to undergo complete pathological response. Apoptosis and therapy-induced senescence (TIS) are both cell stress mechanisms but their exact role in mediating the pathological response to NAC is not fully elucidated. We investigated the change in expression of PAMIP1, the gene encoding for the pro-apoptotic protein, NOXA, following NAC in two breast cancer gene datasets, and the change in NOXA protein expression in response to NAC in 55 matched patient samples (pre- and post-NAC). PAMIP1 expression significantly declined in post-NAC in the two sets, and in our cohort, 75% of the samples exhibited a downregulation in NOXA post-NAC. Matched samples that showed a decline in NOXA post-NAC were examined for TIS based on a signature of downregulated expression of Lamin-B1 and Ki-67 and increased p16INK4a, and the majority exhibited a decrease in Lamin B1 (66%) and Ki-67 (80%), and increased p16INK4a (49%). Since our cohort consisted of patients that did not develop complete pathological response, such findings have clinical implications on the role of TIS and NOXA downregulation in mediating suboptimal responses to the currently established NAC.

Comparing MitoQ10 and heat therapy: Evaluating mechanisms and therapeutic potential for polycystic ovary syndrome induced by circadian rhythm disruption.

Environmental factors, such as sleep restriction, contribute to polycystic ovary syndrome (PCOS) by causing hyperinsulinemia, hyperandrogenism, insulin resistance, and oligo- or anovulation. This study aimed to evaluate the effects of circadian rhythm disruption on reproductive and metabolic functions and investigate the potential therapeutic benefits of MitoQ10 and hot tub therapy (HTT). Sixty female rats were divided into six groups: control, MitoQ10, HTT, and three groups with PCOS induced by continuous light exposure(L/L). The reproductive, endocrine, and structural manifestations ofL/L-induced PCOS were confirmed by serum biochemical measurements, ultrasound evaluation of ovarian size, and vaginal smear examination at week 14. Subsequently, the rats were divided into the L/L (untreated), L/L+MitoQ10-treated, andL/L+HTT-treated groups. At the end of week 22, all rats were sacrificed. Treatmentwith MitoQ10 or HTT partially reversed the reproductive, endocrine, and structural features of PCOS, leading to a decreased amplitude of isolated uterine contractions, ovarian cystic changes and size, and endometrial thickness. Furthermore, both interventions improved the elevated serum levels of anti-Mullerian hormone (AMH), kisspeptin, Fibulin-1, A disintegrin and metalloproteinase with thrombospondin motifs 19 (ADAMTS-19), lipid profile, homeostatic model assessment for insulin resistance (HOMA-IR), oxidative stress markers, androgen receptors (AR) and their transcription target genes, FKBP52 immunostaining in ovarian tissues, and uterine estrogen receptor alpha (ER-α) and PRimmunostaining. In conclusion, MitoQ10 supplementation and HTT demonstrated the potential for ameliorating metabolic, reproductive, and structural perturbations associated with PCOS induced by circadian rhythm disruption. These findings suggest a potential therapeutic role for these interventions in managing PCOS in women.

Upper gastrointestinal tract involvement of pediatric inflammatory bowel disease: A pathological review.

Upper gastrointestinal (UGI) tract involvement of inflammatory bowel disease (IBD) is commonly seen in pediatric patients. Upper endoscopy is included in the routine workup of children with suspected IBD to enhance the diagnosis and management of these patients. Currently, childhood IBD is classified into ulcerative colitis (UC), atypical UC, Crohn's disease (CD) and IBD unclassified. Histologic confirmation of UGI tract involvement, in particular the presence of epithelioid (non-caseating) granulomas, is helpful in confirming the diagnosis of IBD and its classification. Herein, we reviewed selected IBD-associated UGI tract manifestations in children. Lymphocytic esophagitis, seen predominantly in CD, is histologically characterized by increased intraepithelial lymphocytes (> 20 in one high-power field) in a background of mucosal injury with absence of granulocytes. Focally enhanced gastritis is a form of gastric inflammation in pediatric IBD marked by a focal lymphohistiocytic pit inflammation with or without granulocytes and plasma cells in a relatively normal background gastric mucosa. Duodenal inflammation seen in children with IBD includes cryptitis, villous flattening, increased intraepithelial lymphocytes, and lamina propria eosinophilia. Finally, epithelioid granulomas not associated with ruptured gland/crypt are a diagnostic feature of CD. The clinicopathologic correlation and differential diagnosis of each microscopic finding are discussed. Clinicians and pathologists should be cognizant of the utility and limitations of these histologic features.