Adenocarcinoma Arising in a Duplication of the Cecum

Intestinal duplications are rare developmental abnormalities that may occur anywhere in the gastrointestinal tract. The possibility of a malignant change occurring in these duplications is very low. We present a case of adenocarcinoma arising in a duplication of the cecum. A 41-year-old male patient was admitted because of a palpable abdominal mass. Abdominal computed tomography revealed a 6-cm, peripheral wall-enhanced, round, cystic mass in the cecal area. Excision of the mesenteric mass and a right hemicolectomy was performed. Upon histologic examination, the patient was diagnosed with adenocarcinoma arising in a duplication of the cecum

EC-18, a Synthetic Monoacetyldiacylglyceride, Inhibits Hematogenous Metastasis of KIGB-5 Biliary Cancer Cell in Hamster Model

EC-18 (monoacetyldiacylglyceride) stimulates T cell production of IL-2, IL-4, IL-12, IFN-γ, and GM-CSF in vitro. To study the effects of these cytokines stimulated by EC-18 on cancer cells, we applied hamster biliary cancer model, a difficult cancer to treat. Cancer (KIGB-5) cells were given intravenously to produce hematogenous metastatic lung lesions which were treated with EC-18 at 10, 25, and 50 mg/kg/day respectively. The fourth group was untreated control. At 4th, 8th, and 12th week the lungs were examined. EC-18 treated groups showed only a few microscopic lung lesions and no evidence of metastatic lesion with highest dose whereas widespread gross lung lesions were observed in untreated control. To investigate whether the anti-tumor effect of EC-18 is associated with suppression of tumor cell Toll-like receptor 4 (TLR-4) expression in addition to stimulation of the immune cells, KIGB-5 cells were exposed to LPS with or without EC-18. TLR-4 mRNA and protein expression, measured by reverse transcriptase PCR (RT-PCR), real-time quantitative PCR and western blot analysis, showed suppression of TLR-4 expression in KIGB-5 cells treated with EC-18 compared with control. In conclusion, EC-18 has a significant anti-tumor effect in this experimental model of biliary cancer suggesting potential for clinical application to this difficult cancer

Impact of diabetes mellitus on mortality in patients with acute heart failure: a prospective cohort study

Although more than one-third of the patients with acute heart failure (AHF) have diabetes mellitus (DM), it is unclear if DM has an adverse impact on clinical outcomes. This study compared the outcomes in patients hospitalized for AHF stratified by DM and left ventricular ejection fraction (LVEF). The Korean Acute Heart Failure registry prospectively enrolled and followed 5625 patients from March 2011 to February 2019. The primary endpoints were in-hospital and overall all-cause mortality. We evaluated the impact of DM on these endpoints according to HF subtypes and glycemic control. During a median follow-up of 3.5years, there were 235 (4.4%) in-hospital mortalities and 2500 (46.3%) overall mortalities. DM was significantly associated with increased overall mortality after adjusting for potential confounders (adjusted hazard ratio [HR] 1.11, 95% confidence interval [CI] 1.03–1.22). In the subgroup analysis, DM was associated with higher a risk of overall mortality in heart failure with reduced ejection fraction (HFrEF) only (adjusted HR 1.14, 95% CI 1.02–1.27). Inadequate glycemic control (HbA1c ≥ 7.0% within 1year after discharge) was significantly associated with a higher risk of overall mortality compared with adequate glycemic control (HbA1c < 7.0%) (44.0% vs. 36.8%, log-rank p = 0.016). DM is associated with a higher risk of overall mortality in AHF, especially HFrEF. Well-controlled diabetes (HbA1c < 7.0%) is associated with a lower risk of overall mortality compared to uncontrolled diabetes. Trial registration ClinicalTrial.gov, NCT01389843. Registered July 6, 2011. https://clinicaltrials.gov/ct2/show/NCT01389843This study was supported by Research of Korea Centers for Disease Control and Prevention (2010-E63003-00, 2011-E63002-00, 2012-E63005-00, 2013E63003-00, 2013-E63003-01, 2013-E63003-02, and 2016-ER6303-00)

PAIP 2019: Liver cancer segmentation challenge

Pathology Artificial Intelligence Platform (PAIP) is a free research platform in support of pathological artificial intelligence (AI). The main goal of the platform is to construct a high-quality pathology learning data set that will allow greater accessibility. The PAIP Liver Cancer Segmentation Challenge, organized in conjunction with the Medical Image Computing and Computer Assisted Intervention Society (MICCAI 2019), is the first image analysis challenge to apply PAIP datasets. The goal of the challenge was to evaluate new and existing algorithms for automated detection of liver cancer in whole-slide images (WSIs). Additionally, the PAIP of this year attempted to address potential future problems of AI applicability in clinical settings. In the challenge, participants were asked to use analytical data and statistical metrics to evaluate the performance of automated algorithms in two different tasks. The participants were given the two different tasks: Task 1 involved investigating Liver Cancer Segmentation and Task 2 involved investigating Viable Tumor Burden Estimation. There was a strong correlation between high performance of teams on both tasks, in which teams that performed well on Task 1 also performed well on Task 2. After evaluation, we summarized the top 11 team&apos;s algorithms. We then gave pathological implications on the easily predicted images for cancer segmentation and the challenging images for viable tumor burden estimation. Out of the 231 participants of the PAIP challenge datasets, a total of 64 were submitted from 28 team participants. The submitted algorithms predicted the automatic segmentation on the liver cancer with WSIs to an accuracy of a score estimation of 0.78. The PAIP challenge was created in an effort to combat the lack of research that has been done to address Liver cancer using digital pathology. It remains unclear of how the applicability of AI algorithms created during the challenge can affect clinical diagnoses. However, the results of this dataset and evaluation metric provided has the potential to aid the development and benchmarking of cancer diagnosis and segmentation. (C) 2020 The Authors. Published by Elsevier B.V

Mesostructured Block Copolymer Nanoparticles: Versatile Templates for Hybrid Inorganic/Organic Nanostructures

We present a versatile strategy to prepare a range of nanostructured poly(styrene)-block-poly(2-vinyl pyridine) copolymer particles with tunable interior morphology and controlled size by a simple solvent exchange procedure. A key feature of this strategy is the use of functional block copolymers incorporating reactive pyridyl moieties which allow the absorption of metal salts and other inorganic precursors to be directed. Upon reduction of the metal salts, well-defined hybrid metal nanoparticle arrays could be prepared, whereas the use of oxide precursors followed by calcination permits the synthesis of silica and titania particles. In both cases, ordered morphologies templated by the original block copolymer domains were obtained

Annuitization and Asset Allocation with Borrowing Constraint

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