Spindle and Giant Cell Type Undifferentiated Carcinoma of the Proximal Bile Duct

Undifferentiated spindle and giant cell carcinoma is an extremely rare malignant neoplasm arising in the extrahepatic bile duct. We herein present the case of a 67-year-old male who developed an undifferentiated spindle and giant cell carcinoma of the proximal bile duct. A nodular infiltrating tumor was located at the proximal bile duct, resulting in obstructive jaundice. Histologically, the tumor was composed of mainly spindle-shaped and giant cells and showed positive immunoreactivity for both cytokeratin and vimentin. Adjuvant chemotherapy was administered following extrahepatic bile duct resection, and he has been doing well for 16 months since the surgical treatment. The literature on this rare malignancy is also reviewed and discussed

ISR-DEPENDENT METABOLIC REGULATION

The eukaryotic translation initiation factor 2α (eIF2α) phosphorylation‐dependent integrated stress response (ISR), a component of the unfolded protein response, has long been known to regulate intermediary metabolism, but the details are poorly worked out. We report that profiling of mRNAs of transgenic mice harboring a ligand‐activated skeletal muscle–specific derivative of the eIF2α protein kinase R‐like ER kinase revealed the expected up‐regulation of genes involved in amino acid biosynthesis and transport but also uncovered the induced expression and secretion of a myokine, fibroblast growth factor 21 (FGF21), that stimulates energy consumption and prevents obesity. The link between the ISR and FGF21 expression was further reinforced by the identification of a small‐molecule ISR activator that promoted Fgf21 expression in cell‐based screens and by implication of the ISR‐inducible activating transcription factor 4 in the process. Our findings establish that eIF2α phosphorylation regulates not only cell‐autonomous proteostasis and amino acid metabolism, but also affects non‐cell‐autonomous metabolic regulation by induced expression of a potent myokine.—Miyake, M., Nomura, A., Ogura, A., Takehana, K., Kitahara, Y., Takahara, K., Tsugawa, K., Miyamoto, C., Miura, N., Sato, R., Kurahashi, K., Harding, H. P., Oyadomari, M., Ron, D., Oyadomari, S. Skeletal muscle‐specific eukaryotic translation initiation factor 2α phosphorylation controls amino acid metabolism and fibroblast growth factor 21‐mediated non‐cell‐autonomous energy metabolism

Machine Learning for Diagnosis of AD and Prediction of MCI Progression From Brain MRI Using Brain Anatomical Analysis Using Diffeomorphic Deformation.

Background:With the growing momentum for the adoption of machine learning (ML) in medical field, it is likely that reliance on ML for imaging will become routine over the next few years. We have developed a software named BAAD, which uses ML algorithms for the diagnosis of Alzheimer\u27s disease (AD) and prediction of mild cognitive impairment (MCI) progression.Methods:We constructed an algorithm by combining a support vector machine (SVM) to classify and a voxel-based morphometry (VBM) to reduce concerned variables. We grouped progressive MCI and AD as an AD spectrum and trained SVM according to this classification. We randomly selected half from the total 1,314 subjects of AD neuroimaging Initiative (ADNI) from North America for SVM training, and the remaining half were used for validation to fine-tune the model hyperparameters. We created two types of SVMs, one based solely on the brain structure (SVMst), and the other based on both the brain structure and Mini-Mental State Examination score (SVMcog). We compared the model performance with two expert neuroradiologists, and further evaluated it in test datasets involving 519, 592, 69, and 128 subjects from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL), Japanese ADNI, the Minimal Interval Resonance Imaging in AD (MIDIAD) and the Open Access Series of Imaging Studies (OASIS), respectively.Results:BAAD\u27s SVMs outperformed radiologists for AD diagnosis in a structural magnetic resonance imaging review. The accuracy of the two radiologists was 57.5 and 70.0%, respectively, whereas, that of the SVMst was 90.5%. The diagnostic accuracy of the SVMst and SVMcog in the test datasets ranged from 88.0 to 97.1% and 92.5 to 100%, respectively. The prediction accuracy for MCI progression was 83.0% in SVMst and 85.0% in SVMcog. In the AD spectrum classified by SVMst, 87.1% of the subjects were Aβ positive according to an AV-45 positron emission tomography. Similarly, among MCI patients classified for the AD spectrum, 89.5% of the subjects progressed to AD.Conclusion:Our ML has shown high performance in AD diagnosis and prediction of MCI progression. It outperformed expert radiologists, and is expected to provide support in clinical practice

Impact of Anatomical Resection for Hepatocellular Carcinoma With Microportal Invasion (vp1): A Multi-institutional Study by the Kyushu Study Group of Liver Surgery

Objective: The aim of the present study was to evaluate the value of anatomical resectionfor HCC with micro-portal vascular invasion (vp1) between 2000 and 2010. Summaryof Background: Vascular invasion has been reported as a prognostic factor of liverresection for hepatocellular carcinoma (HCC). Anatomical resection for HCC has resulted in optimum outcomes of eradicating intrahepatic micrometastases through the portal vein, but opposite results have also been reported. Methods: A clinical chart review was performed for 546 HCC patients with vp1. We retrospectively evaluated the recurrence-free survival (RFS) between anatomical (AR)and non-anatomical resection (NAR). The site of recurrence was also compared between these groups. The influence of AR on the overall survival (OS) and RFS rates was analyzed in patients selected by propensity score matching, and the prognostic factors were identified.Results: A total of 546 patients were enrolled, including 422 in the AR group and 124 in the NAR group. There was no difference in the 5-year OS and RFS rates between the two groups. Local recurrence was significantly more frequent in the NAR group than in the AR group. In a multivariate analysis, hepatitis C (HCV), PIVKAII ?380 mAU/ml, tumor diameter ?5 cm and ?70 years of age were significant predictors of a poor RFS after liverresection. There were no significant differences in the OS or RFS between the AR and NAR groups by a propensity score-matched analysis. Conclusion: Although local recurrence around the resection site was suppressed by AR, AR for HCC with vp1 did not influence the RFS or OS rates after hepatectomy in the modern era