Topological Semantic Graph Memory for Image-Goal Navigation

A novel framework is proposed to incrementally collect landmark-based graph memory and use the collected memory for image goal navigation. Given a target image to search, an embodied robot utilizes semantic memory to find the target in an unknown environment. % The semantic graph memory is collected from a panoramic observation of an RGB-D camera without knowing the robot's pose. In this paper, we present a topological semantic graph memory (TSGM), which consists of (1) a graph builder that takes the observed RGB-D image to construct a topological semantic graph, (2) a cross graph mixer module that takes the collected nodes to get contextual information, and (3) a memory decoder that takes the contextual memory as an input to find an action to the target. On the task of image goal navigation, TSGM significantly outperforms competitive baselines by +5.0-9.0% on the success rate and +7.0-23.5% on SPL, which means that the TSGM finds efficient paths. Additionally, we demonstrate our method on a mobile robot in real-world image goal scenarios

Visually Grounding Instruction for History-Dependent Manipulation

This paper emphasizes the importance of robot's ability to refer its task history, when it executes a series of pick-and-place manipulations by following text instructions given one by one. The advantage of referring the manipulation history can be categorized into two folds: (1) the instructions omitting details or using co-referential expressions can be interpreted, and (2) the visual information of objects occluded by previous manipulations can be inferred. For this challenge, we introduce the task of history-dependent manipulation which is to visually ground a series of text instructions for proper manipulations depending on the task history. We also suggest a relevant dataset and a methodology based on the deep neural network, and show that our network trained with a synthetic dataset can be applied to the real world based on images transferred into synthetic-style based on the CycleGAN.Comment: 8 pages, 6 figure

Visually Grounding Language Instruction for History-Dependent Manipulation

This paper emphasizes the importance of a robot's ability to refer to its task history, especially when it executes a series of pick-and-place manipulations by following language instructions given one by one. The advantage of referring to the manipulation history can be categorized into two folds: (1) the language instructions omitting details but using expressions referring to the past can be interpreted, and (2) the visual information of objects occluded by previous manipulations can be inferred. For this, we introduce a history-dependent manipulation task which objective is to visually ground a series of language instructions for proper pick-and-place manipulations by referring to the past. We also suggest a relevant dataset and model which can be a baseline, and show that our model trained with the proposed dataset can also be applied to the real world based on the CycleGAN. Our dataset and code are publicly available on the project website: https://sites.google.com/view/history-dependent-manipulation

Sex-specific bi-directional association between osteoporosis and depression from the national representative data of South Korea

Both osteoporosis and depression are major health threats, but their interrelationship is not clear. This study elucidated the associations between osteoporosis and depression while considering the temporal sequence of the diagnoses. In this cross-sectional study, data were extracted from the Korean National Health and Nutrition Examination Surveys (2007-2009 and 2015-2019, n = 29,045). Osteoporosis and depression were defined by diagnoses thereof. The odds ratio (OR) of the incident osteoporosis among depression patients without a history of osteoporosis was calculated by multivariable logistic regression adjusted for potential confounders. A reverse association was also assessed. Participants were additionally stratified by their sex and age. As a result, male depression patients aged under 50 years showed higher ORs for osteoporosis than those without depression (OR 9.16, 95% CI 1.78-47.18). Female osteoporosis patients showed lower ORs for depression than those without osteoporosis (OR 0.71, 95% CI 0.58-0.88), especially in women aged 50 years and older. In the sensitivity analysis, the same results were obtained in women by their menopause status. Depression has a strong positive association with the occurrence of osteoporosis in young male adults, and osteoporosis has a negative association with the occurrence of depression in female adults.N

Effects of Intermittent Fasting on the Circulating Levels and Circadian Rhythms of Hormones

Intermittent fasting has become an increasingly popular strategy in losing weight and associated reduction in obesity-related medical complications. Overwhelming studies support metabolic improvements from intermittent fasting in blood glucose levels, cardiac and brain function, and other health benefits, in addition to weight loss. However, concerns have also been raised on side effects including muscle loss, ketosis, and electrolyte imbalance. Of particular concern, the effect of intermittent fasting on hormonal circadian rhythms has received little attention. Given the known importance of circadian hormonal changes to normal physiology, potential detrimental effects by dysregulation of hormonal changes deserve careful discussions. In this review, we describe the changes in circadian rhythms of hormones caused by intermittent fasting. We covered major hormones commonly pathophysiologically involved in clinical endocrinology, including insulin, thyroid hormones, and glucocorticoids. Given that intermittent fasting could alter both the level and frequency of hormone secretion, decisions on practicing intermittent fasting should take more considerations on potential detrimental consequences versus beneficial effects pertaining to individual health conditions. © 2021 Korean Endocrine Society. All rights reserved.1

Mouse Model of Small for Gestational Age Offspring with Catch-up Growth Failure and Dysregulated Glucose Metabolism in Adulthood

Background: We aimed to build mouse models of small for gestational age (SGA), recapitulating failure of catch-up growth and dysregulated metabolic outcomes in adulthood. Methods: Pregnant CS7BU6 mice were given a protein-restricted diet (PRD; 6% kcal from protein) during pregnancy without (model 1) or with cross-fostering (model 2). Model 3 extended the PRD to the end of the lactation period. Model 4 changed to a 93'o PRD without cross-fostering. Results: Model 1 yielded a reduced size of offspring with a poor survival rate. Model 2 improved survival but offspring showed early catch-up growth. Model 3 maintained a reduced size of offspring after weaning with a higher body mass index and blood glucose levels in adult stages. Model 4 increased the survival of the offspring while maintaining a reduced size and dysregulated glucose metabolism. Conclusion: Models 3 and 4 are suitable for studying SGA accompanying adulthood short stature and metabolic disorders.N

Visually Grounding Language Instruction for History-Dependent Manipulation

his paper emphasizes the importance of a robot's ability to refer to its task history, especially when it executes a series of pick-and-place manipulations by following language instructions given one by one. The advantage of referring to the manipulation history can be categorized into two folds: (1) the language instructions omitting details but using expressions referring to the past can be interpreted, and (2) the visual information of objects occluded by previous manipulations can be inferred. For this, we introduce a history-dependent manipulation task which objective is to visually ground a series of language instructions for proper pick-and-place manipulations by referring to the past. We also suggest a relevant dataset and model which can be a baseline, and show that our model trained with the proposed dataset can also be applied to the real world based on the CycleGAN

The Effect of DPP-4 Inhibitors on Metabolic Parameters in Patients with Type 2 Diabetes

BackgroundWe evaluated the effects of two dipeptidyl peptidase-4 (DPP-4) inhibitors, sitagliptin and vildagliptin, on metabolic parameters in patients with type 2 diabetes mellitus.MethodsA total of 170 type 2 diabetes patients treated with sitagliptin or vildagliptin for more than 24 weeks were selected. The patients were separated into two groups, sitagliptin (100 mg once daily, n=93) and vildagliptin (50 mg twice daily, n=77). We compared the effect of each DPP-4 inhibitor on metabolic parameters, including the fasting plasma glucose (FPG), postprandial glucose (PPG), glycated hemoglobin (HbA1c), and glycated albumin (GA) levels, and lipid parameters at baseline and after 24 weeks of treatment.ResultsThe HbA1c, FPG, and GA levels were similar between the two groups at baseline, but the sitagliptin group displayed a higher PPG level (P=0.03). After 24 weeks of treatment, all of the glucose-related parameters were significantly decreased in both groups (P=0.001). The levels of total cholesterol and triglycerides were only reduced in the vildagliptin group (P=0.001), although the sitagliptin group received a larger quantity of statins than the vildagliptin group (P=0.002).The mean change in the glucose- and lipid-related parameters after 24 weeks of treatment were not significantly different between the two groups (P=not significant). Neither sitagliptin nor vildagliptin treatment was associated with a reduction in the high sensitive C-reactive protein level (P=0.714).ConclusionVildagliptin and sitagliptin exert a similar effect on metabolic parameters, but vildagliptin exerts a more potent beneficial effect on lipid parameters

Augmentation of the RNA m6A reader signature is associated with poor survival by enhancing cell proliferation and EMT across cancer types

Cancer: The role of modifications to RNA Studying the effects of a chemical modification of messenger RNA molecules (mRNA), which carry genetic information from DNA to the cell's protein-making machinery, reveals new insights into the role of these modifications in cancer, suggesting potential therapeutic approaches. Researchers in Seoul, South Korea, led by Joon-Yong An at Korea University and Sung-Yup Cho at Seoul National University investigated the most common modifications of mRNA involving methyl groups (CH3): addition ('writing'), having a regulatory effect on the cell ('reading') or removal ('erasing'). The molecular activities involved in reading the modifications were increased in all 11 types of cancer in cancer-sampling databases and their own patient cohort. Changes in writing and erasing of the modifications varied with cancer type. The proteins that mediate the reading responses to RNA methylation are possible targets for new anti-cancer drugs. N-6-Methyladenosine (m6A) RNA modification plays a critical role in the posttranscriptional regulation of gene expression. Alterations in cellular m6A levels and m6A-related genes have been reported in many cancers, but whether they play oncogenic or tumor-suppressive roles is inconsistent across cancer types. We investigated common features of alterations in m6A modification and m6A-related genes during carcinogenesis by analyzing transcriptome data of 11 solid tumors from The Cancer Genome Atlas database and our in-house gastric cancer cohort. We calculated m6A writer (W), eraser (E), and reader (R) signatures based on corresponding gene expression. Alterations in the W and E signatures varied according to the cancer type, with a strong positive correlation between the W and E signatures in all types. When the patients were divided according to m6A levels estimated by the ratio of the W and E signatures, the prognostic effect of m6A was inconsistent according to the cancer type. The R and especially the R2 signatures (based on the expression of IGF2BPs) were upregulated in all cancers. Patients with a high R2 signature exhibited poor prognosis across types, which was attributed to enrichment of cell cycle- and epithelial-mesenchymal transition-related pathways. Our study demonstrates common features of m6A alterations across cancer types and suggests that targeting m6A R proteins is a promising strategy for cancer treatment.N