Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Reading the unique DNA methylation landscape of the brain: Non-CpG methylation,hydroxymethylation, and MeCP2

DNA methylation at CpG dinucleotides is an important epigenetic regulator common to virtually all mammalian cell types, but recent evidence indicates that during early postnatal development neuronal genomes also accumulate uniquely high levels of two alternative forms of methylation, non-CpG methylation and hydroxymethylation. Here we discuss the distinct landscape of DNA methylation in neurons, how it is established, and how it might affect the binding and function of protein readers of DNA methylation. We review studies of one critical reader of DNA methylation in the brain, the Rett syndrome protein methyl CpG-binding protein 2 (MeCP2), and discuss how differential binding affinity of MeCP2 for non-CpG and hydroxymethylation may affect the function of this methyl-binding protein in the nervous system.     

Treatment strategies for hypertension in patients with type 1 diabetes

ABSTRACT

Introduction

Type 1 diabetes mellitus (T1DM) is a chronic, autoimmune disease that is characterized by total absence of insulin production. Hypertension is a common comorbidity in T1DM with complex pathophysiology, while it is also a well-recognized risk factor for the development of cardiovascular disease (CVD), as well as other microvascular diabetic complications.     

Sudden Cardiac Death in Patients With Type 1 Versus Type 2 Diabetes

ObjectiveTo investigate the association between type 1 diabetes mellitus (T1D) and type 2 diabetes mellitus (T2D) with risk of sudden cardiac arrest (SCA).MethodsIn a prospective community-based study of SCA from February 1, 2002, through November 30, 2019, we ascertained 2771 cases age 18 years of age or older and matched them to 8313 controls based on geography, age, sex, and race/ethnicity. We used logistic regression to evaluate the independent association between diabetes, T1D, T2D, and SCA.ResultsPatients had a mean age of 64.5±15.9 years, were 33.3% female and 23.9% non-White race. Overall, 36.7% (n=1016) of cases and 23.8% (n=1981) of controls had diabetes. Among individuals with diabetes, the proportion of T1D was 6.5% (n=66) among cases and 2.0% among controls (n=40). Diabetes was associated with 1.5-times higher odds of SCA. Compared with those without diabetes, the odds ratio and 95% CI for SCA was 4.36 (95% CI, 2.81 to 6.75; P<.001) in T1D and 1.45 (95% CI, 1.30 to 1.63; P<.001) in T2D after multivariable adjustment. Among those with diabetes, the odds of having SCA were 2.41 times higher in T1D than in T2D (95% CI, 1.53 to 3.80; P<.001). Cases of SCA with T1D were more likely to have an unwitnessed arrest, less likely to receive resuscitation, and less likely to survive compared with those with T2D.ConclusionType 1 diabetes was more strongly associated with SCA compared with T2D and had less favorable outcomes following resuscitation. Diabetes type could influence the approach to risk stratification and prevention of SCA.     

A Very Long-term Longitudinal Study on the Evolution and Clinical Outcomes of Persistent Iatrogenic Atrial Septal Defect After Cryoballoon Ablation

Background

Persistent iatrogenic atrial septal defect (iASD) is a common but poorly characterized complication after cryoballoon (CB) pulmonary vein isolation (PVI) procedures. We therefore investigate its prevalence, evolution, risk factors, and clinical outcomes in a prospective longitudinal study.

Investigation of the mechanisms of Genkwa Flos hepatotoxicity by a cell metabolomics strategy combined with serum pharmacology in HL-7702 liver cells

1. To investigate Genkwa Flos hepatotoxicity, a cell metabolomics strategy combined with serum pharmacology was performed on human HL-7702 liver cells in this study.

2. Firstly, cell viability and biochemical indicators were determined and the cell morphology was observed to confirm the cell injury and develop a cell hepatotoxicity model. Then, with the help of cell metabolomics based on UPLC-MS, the Genkwa Flos group samples were completely separated from the blank group samples in the score plots and seven upregulated as well as two down-regulated putative biomarkers in the loading plot were identified and confirmed. Besides, two signal molecules and four enzymes involved in biosynthesis pathway of lysophosphatidylcholine and the sphingosine kinase/sphingosine-1-phosphate pathway were determined to investigate the relationship between Genkwa Flos hepatotoxicity and these two classic pathways. Finally, the metabolic pathways related to specific biomarkers and two classic metabolic pathways were analyzed to explain the possible mechanism of Genkwa Flos hepatotoxicity.

3. Based on the results, lipid peroxidation and oxidative stress, phospholipase A₂/lysophosphatidylcholine pathway, the disturbance of sphingosine-1-phosphate metabolic profile centered on sphingosine kinase/sphingosine-1-phosphate pathway and fatty acid metabolism might be critical participators in the progression of liver injury induced by Genkwa Flos.     

Combining CAPRA-S With Tumor IDC/C Features Improves the Prognostication of Biochemical Recurrence in Prostate Cancer Patients

Background: Intraductal carcinoma and cribriform (IDC/C) tumor features are well-established prognosticators of biochemical recurrence (BCR), metastasis, and prostate cancer (PCa)-specific mortality. However, approximately 70% of PCa patients undergoing a radical prostatectomy are IDC/C negative, yet up-to 20% of these patients progress and experience BCR. Thus, tumor histopathologic characteristics such as IDC/C alone are limited in their ability to predict disease progression. Conversely, several nomograms such as Cancer of the Prostate Risk Assessment-Surgery (CAPRA-S) have been developed to aid in the prognostication of BCR, but not yet widely applied in clinical settings. Materials and methods: In this study, we assessed the combined prognostic utility of IDC/C, and CAPRA-S for BCR in 3 PCa patient cohorts. Results: CAPRA-S+IDC/C improved the predictive accuracy of BCR in all 3 cohorts (P < .001). Specifically, among IDC/C negative cases, CAPRA-S improved the prognostication of BCR in low-risk (Cohort 1; P < .001, Cohort 2; P < .001, Cohort 3; P = .003), intermediate (Cohort 1; P < .001, Cohort 2; P = .006, Cohort 3; P = .03) and high-risk (Cohort 1-3; P < .001) patients. Conversely, IDC/C improved the prognostication of BCR among CAPRA-S low-risk (Cohorts 1; P < .001 and Cohort 3; P = .003) patients. Conclusion: Our results suggest the investigation of histopathological IDC/C features in CAPRA-S low-risk patients and conversely, nomogram CAPRA-S among IDC/C negative patients improves the identification of patients likely to experience BCR, which would otherwise be missed through current assessment regimens. These patients can be offered more intensive monitoring and adjuvant therapies upfront to circumvent the development of recurrent cancer or overtreatment at the time of surgery.