M3FPolypSegNet: Segmentation Network with Multi-frequency Feature Fusion for Polyp Localization in Colonoscopy Images

Polyp segmentation is crucial for preventing colorectal cancer a common type of cancer. Deep learning has been used to segment polyps automatically, which reduces the risk of misdiagnosis. Localizing small polyps in colonoscopy images is challenging because of its complex characteristics, such as color, occlusion, and various shapes of polyps. To address this challenge, a novel frequency-based fully convolutional neural network, Multi-Frequency Feature Fusion Polyp Segmentation Network (M3FPolypSegNet) was proposed to decompose the input image into low/high/full-frequency components to use the characteristics of each component. We used three independent multi-frequency encoders to map multiple input images into a high-dimensional feature space. In the Frequency-ASPP Scalable Attention Module (F-ASPP SAM), ASPP was applied between each frequency component to preserve scale information. Subsequently, scalable attention was applied to emphasize polyp regions in a high-dimensional feature space. Finally, we designed three multi-task learning (i.e., region, edge, and distance) in four decoder blocks to learn the structural characteristics of the region. The proposed model outperformed various segmentation models with performance gains of 6.92% and 7.52% on average for all metrics on CVC-ClinicDB and BKAI-IGH-NeoPolyp, respectively.Comment: 5pages. 2023 IEEE International Conference on Image Processing (ICIP). IEEE, 202

Chemokine Lkn-1/CCL15 enhances matrix metalloproteinase-9 release from human macrophages and macrophage-derived foam cells

Atherosclerosis is characterized by a chronic inflammatory disease, and chemokines play an important role in both initiation and progression of atherosclerosis development. Leukotactin-1 (Lkn-1/CCL15), a new member of the human CC chemokine family, is a potent chemoattractant for leukocytes. Our previous study has demonstrated that Lkn-1/CCL15 plays a role in the initiation of atherosclerosis, however, little is currently known whether Lkn-1/CCL15 is associated with the progression of atherosclerosis. Matrix metalloproteinases (MMPs) in human coronary atherosclerotic lesions play a crucial role in the progression of atherosclerosis by altering the vulnerability of plaque rupture. In the present study, we examined whether Lkn-1/CCL15 modulates MMP-9 release, which is a prevalent form expressed by activated macrophages and foam cells. Human THP-1 monocytic cells and/or human peripheral blood monocytes (PBMC) were treated with phorbol myristate acetate to induce their differentiation into macrophages. Foam cells were prepared by the treatment of THP-1 macrophages with human oxidized LDL. The macrophages and foam cells were treated with Lkn-1/CCL15, and the levels of MMP-9 release were measured by Gelatin Zymography. Lkn-1/CCL15 significantly enhanced the levels of MMP-9 protein secretion from THP-1 monocytic cells-derived macrophages, human PBMC-derived macrophages, as well as macrophage-derived foam cell in a dose dependent manner. Our data suggest that the action of Lkn-1/CCL15 on macrophages and foam cells to release MMP-9 may contribute to plaque destabilization in the progression of atherosclerosis

Clinical MetaData ontology: a simple classification scheme for data elements of clinical data based on semantics

Background The increasing use of common data elements (CDEs) in numerous research projects and clinical applications has made it imperative to create an effective classification scheme for the efficient management of these data elements. We applied high-level integrative modeling of entire clinical documents from real-world practice to create the Clinical MetaData Ontology (CMDO) for the appropriate classification and integration of CDEs that are in practical use in current clinical documents. Methods CMDO was developed using the General Formal Ontology method with a manual iterative process comprising five steps: (1) defining the scope of CMDO by conceptualizing its first-level terms based on an analysis of clinical-practice procedures, (2) identifying CMDO concepts for representing clinical data of general CDEs by examining how and what clinical data are generated with flows of clinical care practices, (3) assigning hierarchical relationships for CMDO concepts, (4) developing CMDO properties (e.g., synonyms, preferred terms, and definitions) for each CMDO concept, and (5) evaluating the utility of CMDO. Results We created CMDO comprising 189 concepts under the 4 first-level classes of Description, Event, Finding, and Procedure. CMDO has 256 definitions that cover the 189 CMDO concepts, with 459 synonyms for 139 (74.0%) of the concepts. All of the CDEs extracted from 6 HL7 templates, 25 clinical documents of 5 teaching hospitals, and 1 personal health record specification were successfully annotated by 41 (21.9%), 89 (47.6%), and 13 (7.0%) of the CMDO concepts, respectively. We created a CMDO Browser to facilitate navigation of the CMDO concept hierarchy and a CMDO-enabled CDE Browser for displaying the relationships between CMDO concepts and the CDEs extracted from the clinical documents that are used in current practice. Conclusions CMDO is an ontology and classification scheme for CDEs used in clinical documents. Given the increasing use of CDEs in many studies and real-world clinical documentation, CMDO will be a useful tool for integrating numerous CDEs from different research projects and clinical documents. The CMDO Browser and CMDO-enabled CDE Browser make it easy to search, share, and reuse CDEs, and also effectively integrate and manage CDEs from different studies and clinical documents.This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number:HI18C2386). KHIDI had no participation in the study design or data collection and analysis process. KHIDI did not participate in the writing of the manuscript

Three Cases of Non-Surgical Treatment of Stent Loss During Percutaneous Coronary Intervention

Percutaneous coronary intervention with stenting is widely used for ischemic heart disease. Because stent loss, which occurs rarely during the procedure, might have dire consequences, such as bleeding, stent embolism, acute myocardial infarction, emergency coronary artery bypass graft, and death, appropriate treatment is needed as soon as stent loss occurs. We report three cases of stent loss which were successfully treated with three different non-surgical methods

Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study

Background Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). Methods This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. Results A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P  0.05 between expected and observed values). Conclusions This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.This work was funded by Doosan Yonkang Foundation (Grant No. 30–2016-0240), Liver Research Foundation of Korea as part of Bio Future Strategies Research Project, and Ewha Womans University research grant (2016). The funding bodies had no role in the design of the study, collection, analysis, and interpretation of data and in writing of the manuscript

Corrigendum: Behavioral and Neuroimaging Evidence for Facial Emotion Recognition in Elderly Korean Adults with Mild Cognitive Impairment, Alzheimer's Disease, and Frontotemporal Dementia

Background: Facial emotion recognition (FER) is impaired in individuals with frontotemporal dementia (FTD) and Alzheimer’s disease (AD) when compared to healthy older adults. Since deficits in emotion recognition are closely related to caregiver burden or social interactions, researchers have fundamental interest in FER performance in patients with dementia.Purpose: The purpose of this study was to identify the performance profiles of six facial emotions (i.e., fear, anger, disgust, sadness, surprise, and happiness) and neutral faces measured among Korean healthy control (HCs), and those with mild cognitive impairment (MCI), AD, and FTD. Additionally, the neuroanatomical correlates of facial emotions were investigated.Methods: A total of 110 (33 HC, 32 MCI, 32 AD, 13 FTD) older adult participants were recruited from two different medical centers in metropolitan areas of South Korea. These individuals underwent an FER test that was used to assess the recognition of emotions or absence of emotion (neutral) in 35 facial stimuli. Repeated measures two-way analyses of variance were used to examine the distinct profiles of emotional recognition among the four groups. We also performed brain imaging and voxel-based morphometry (VBM) on the participants to examine the associations between FER scores and gray matter volume.Results: The mean score of negative emotion recognition (i.e., fear, anger, disgust, and sadness) clearly discriminated FTD participants from individuals with MCI and AD and HC [F(3,106) = 10.829, p 2 = 0.235], whereas the mean score of positive emotion recognition (i.e., surprise and happiness) did not. A VBM analysis showed negative emotions were correlated with gray matter volume of anterior temporal regions, whereas positive emotions were related to gray matter volume of fronto-parietal regions.Conclusion: Impairment of negative FER in patients with FTD is cross-cultural. The discrete neural correlates of FER indicate that emotional recognition processing is a multi-modal system in the brain. Focusing on the negative emotion recognition is a more effective way to discriminate healthy aging, MCI, and AD from FTD in older Korean adults.</p

Analysis of significant protein abundance from multiple reaction-monitoring data

Background Discovering reliable protein biomarkers is one of the most important issues in biomedical research. The ELISA is a traditional technique for accurate quantitation of well-known proteins. Recently, the multiple reaction-monitoring (MRM) mass spectrometry has been proposed for quantifying newly discovered protein and has become a popular alternative to ELISA. For the MRM data analysis, linear mixed modeling (LMM) has been used to analyze MRM data. MSstats is one of the most widely used tools for MRM data analysis that is based on the LMMs. However, LMMs often provide various significance results, depending on model specification. Sometimes it would be difficult to specify a correct LMM method for the analysis of MRM data. Here, we propose a new logistic regression-based method for Significance Analysis of Multiple Reaction Monitoring (LR-SAM). Results Through simulation studies, we demonstrate that LMM methods may not preserve type I error, thus yielding high false- positive errors, depending on how random effects are specified. Our simulation study also shows that the LR-SAM approach performs similarly well as LMM approaches, in most cases. However, LR-SAM performs better than the LMMs, particularly when the effects sizes of peptides from the same protein are heterogeneous. Our proposed method was applied to MRM data for identification of proteins associated with clinical responses of treatment of 115 hepatocellular carcinoma (HCC) patients with the tyrosine kinase inhibitor sorafenib. Of 124 candidate proteins, LMM approaches provided 6 results varying in significance, while LR-SAM, by contrast, yielded 18 significant results that were quite reproducibly consistent. Conclusion As exemplified by an application to HCC data set, LR-SAM more effectively identified proteins associated with clinical responses of treatment than LMM did.This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C2037, HI15C2165). Publication of this article was sponsored by HI16C2037 grant

Genetic, management, and nutritional factors affecting intramuscular fat deposition in beef cattle — A review

Intramuscular fat (IMF) content in skeletal muscle including the longissimus dorsi muscle (LM), also known as marbling fat, is one of the most important factors determining beef quality in several countries including Korea, Japan, Australia, and the United States. Genetics and breed, management, and nutrition affect IMF deposition. Japanese Black cattle breed has the highest IMF content in the world, and Korean cattle (also called Hanwoo) the second highest. Here, we review results of research on genetic factors (breed and sex differences and heritability) that affect IMF deposition. Cattle management factors are also important for IMF deposition. Castration of bulls increases IMF deposition in most cattle breeds. The effects of several management factors, including weaning age, castration, slaughter weight and age, and environmental conditions on IMF deposition are also reviewed. Nutritional factors, including fat metabolism, digestion and absorption of feed, glucose/starch availability, and vitamin A, D, and C levels are important for IMF deposition. Manipulating IMF deposition through developmental programming via metabolic imprinting is a recently proposed nutritional method to change potential IMF deposition during the fetal and neonatal periods in rodents and domestic animals. Application of fetal nutritional programming to increase IMF deposition of progeny in later life is reviewed. The coordination of several factors affects IMF deposition. Thus, a combination of several strategies may be needed to manipulate IMF deposition, depending on the consumer’s beef preference. In particular, stage-specific feeding programs with concentrate-based diets developed by Japan and Korea are described in this article

Paricalcitol Pretreatment Attenuates Renal Ischemia-Reperfusion Injury via Prostaglandin E 2

The protective mechanism of paricalcitol remains unclear in renal ischemia-reperfusion (IR) injury. We investigated the renoprotective effects of paricalcitol in IR injury through the prostaglandin E2 (PGE2) receptor EP4. Paricalcitol was injected into IR-exposed HK-2 cells and mice subjected to bilateral kidney ischemia for 23 min and reperfusion for 24 hr. Paricalcitol prevented IR-induced cell death and EP4 antagonist cotreatment offset these protective effects. Paricalcitol increased phosphorylation of Akt and cyclic AMP responsive element binding protein (CREB) and suppressed nuclear factor-κB (NF-κB) in IR-exposed cells and cotreatment of EP4 antagonist or EP4 small interfering RNA blunted these signals. In vivo studies showed that paricalcitol improved renal dysfunction and tubular necrosis after IR injury and cotreatment with EP4 antagonist inhibited the protective effects of paricalcitol. Phosphorylation of Akt was increased and nuclear translocation of p65 NF-κB was decreased in paricalcitol-treated mice with IR injury, which was reversed by EP4 blockade. Paricalcitol decreased oxidative stress and apoptosis in renal IR injury. Paricalcitol also attenuated the infiltration of inflammatory cells and production of proinflammatory cytokines after IR injury. EP4 antagonist abolished these antioxidant, anti-inflammatory, and antiapoptotic effects. The EP4 plays a pivotal role in the protective effects of paricalcitol in renal IR injury