195 research outputs found
Shape-centered Representation Learning for Visible-Infrared Person Re-identification
Current Visible-Infrared Person Re-Identification (VI-ReID) methods
prioritize extracting distinguishing appearance features, ignoring the natural
resistance of body shape against modality changes. Initially, we gauged the
discriminative potential of shapes by a straightforward concatenation of shape
and appearance features. However, two unresolved issues persist in the
utilization of shape features. One pertains to the dependence on auxiliary
models for shape feature extraction in the inference phase, along with the
errors in generated infrared shapes due to the intrinsic modality disparity.
The other issue involves the inadequately explored correlation between shape
and appearance features. To tackle the aforementioned challenges, we propose
the Shape-centered Representation Learning framework (ScRL), which focuses on
learning shape features and appearance features associated with shapes.
Specifically, we devise the Shape Feature Propagation (SFP), facilitating
direct extraction of shape features from original images with minimal
complexity costs during inference. To restitute inaccuracies in infrared body
shapes at the feature level, we present the Infrared Shape Restitution (ISR).
Furthermore, to acquire appearance features related to shape, we design the
Appearance Feature Enhancement (AFE), which accentuates identity-related
features while suppressing identity-unrelated features guided by shape
features. Extensive experiments are conducted to validate the effectiveness of
the proposed ScRL. Achieving remarkable results, the Rank-1 (mAP) accuracy
attains 76.1%, 71.2%, 92.4% (72.6%, 52.9%, 86.7%) on the SYSU-MM01, HITSZ-VCM,
RegDB datasets respectively, outperforming existing state-of-the-art methods
Container CT scanner: a solution for modular emergency radiology department during the COVID-19 pandemic
During the coronavirus disease 2019 (COVID-19) pandemic period, container computed tomography (CT) scanners were developed and used for the first time in China to perform CT examinations for patients with clinically mild to moderate COVID-19 who did not need to be hospitalized for comprehensive treatment, but needed to be isolated in Fangcang shelter hospitals (also known as makeshift hospitals) to receive some supportive treatment. The container CT is a multidetector CT scanner installed within a radiation-protected stand-alone container (a detachable lead shielding room) that is deployed outside the makeshift hospital buildings. The container CT approach provided various medical institutions with the solution not only for rapid CT installation and high adaptability to site environments, but also for significantly minimizing the risk of cross-infection between radiological personnel and patients during CT examination in the pandemic. In this article, we described the typical setup of a container CT and how it worked for chest CT examinations in Wuhan city, the epicenter of COVID-19 outbreak
One-year weight losses in the Tianjin Gestational Diabetes Mellitus Prevention Programme : A randomized clinical trial
Aims: To report the weight loss findings after the first year of a lifestyle intervention trial among women with gestational diabetes mellitus (GDM). Methods: A total of 1180 women with GDM were randomly assigned (1: 1) to receive a 4-year lifestyle intervention (intervention group, n = 586) or standard care (control group, n = 594) between August 2009 and July 2011. Major elements of the intervention included 6 face-to-face sessions with study dieticians and two telephone calls in the first year, and two individual sessions and two telephone calls in each subsequent year. Results: Among 79% of participants who completed the year 1 trial, mean weight loss was 0.82 kg (1.12% of initial weight) in the intervention group and 0.09 kg (0.03% of initial weight) in the control group (P=.001). In a prespecified subgroup analysis of people who completed the trial, weight loss was more pronounced in women who were overweight (body mass index = 24 kg/m(2)) at baseline: mean weight loss 2.01 kg (2.87% of initial weight) in the intervention group and 0.44 kg (0.52% of initial weight) in the control group (P Conclusion: The 1-year lifestyle intervention led to significant weight losses after delivery in women who had GDM, and the effect was more pronounced in women who were overweight at baseline.Peer reviewe
Effects of obesity and a history of gestational diabetes on the risk of postpartum diabetes and hyperglycemia in Chinese Women: Obesity, GDM and diabetes risk
Objective: To evaluate the independent or combined effects of gestational diabetes (GDM) and pre-pregnancy and postpartum BMI on the odds of postpartum diabetes and hyperglycemia. Methods: The study samples included 1263 women with prior GDM and 705 women without GDM. Postpartum 1-7 years diabetes was diagnosed by the standard oral glucose tolerance test. Results: The multivariable-adjusted odds ratios among women with prior GDM, compared with those without it, were 7.52 for diabetes and 2.27 for hyperglycemia. The multivariable-adjusted odds ratios at different postpartum BMI levels (= 28 kg/m(2)) were 1.00, 2.80, and 8.08 for diabetes (P-trend = 31.9%) or abdominal obesity (>= 85 cm) had a 2.7-6.9-fold higher odds ratio for diabetes or hyperglycemia. Women with both obesity and prior GDM had the highest risk of diabetes or hyperglycemia compared with non-obese women without GDM. Non-obese women with prior GDM had the same risk of diabetes and hyperglycemia as non-GDM women with obesity. When using Cox regression models, the results were very close to those using logistic regression models. Conclusions: Maternal prior GDM and pre-pregnancy or postpartum obesity contribute equally to postpartum diabetes and hyperglycemia risk. (C) 2019 Elsevier B.V. All rights reserved.Peer reviewe
High risk of metabolic syndrome after delivery in pregnancies complicated by gestational diabetes
Aims: To investigate the risk of postpartum metabolic syndrome in women with GDM compared with those without GDM in a Chinese population. Methods: Tianjin GDM observational study included 1263 women with a history of GDM and 705 women without GDM. Multivariate logistic regression was used to assess risks of postpartum metabolic syndrome between women with and without GDM. Postpartum metabolic syndrome was diagnosed by two commonly used criteria. Results: During a mean 3.53 years of follow up, 256 cases of metabolic syndrome were identified by using the NCEPATPIII criteria and 244 cases by using the IDF criteria. Multivariable-adjusted odds ratios of metabolic syndrome in women with GDM compared with those without GDM were 3.66 (95% confidence interval [CI] 2.02-6.63) for NCEP ATPIII criteria and 3.90 (95% CI 2.13-7.14) for IDF criteria. Women with GDM had higher multivariable-adjusted odds ratios of central obesity, hypertriglyceridemia, and high blood pressure than women without GDM. The multivariable-adjusted odds ratios of low HDL cholesterol and hyperglycemia were not significant between women with and without GDM, however, the multivariable-adjusted odds ratio of hyperglycemia became significant when we used the modified criteria. Conclusions: The present study indicated that women with prior GDM had significantly higher risks for postpartum metabolic syndrome, as well as its individual components. (C) 2019 Elsevier B.V. All rights reserved.Peer reviewe
Differential regulation of cell motility and invasion by FAK
Cell migration and invasion are fundamental components of tumor cell metastasis. Increased focal adhesion kinase (FAK) expression and tyrosine phosphorylation are connected with elevated tumorigenesis. Null mutation of FAK results in embryonic lethality, and FAK−/− fibroblasts exhibit cell migration defects in culture. Here we show that viral Src (v-Src) transformation of FAK−/− cells promotes integrin-stimulated motility equal to stable FAK reexpression. However, FAK−/− v-Src cells were not invasive, and FAK reexpression, Tyr-397 phosphorylation, and FAK kinase activity were required for the generation of an invasive cell phenotype. Cell invasion was linked to transient FAK accumulation at lamellipodia, formation of a FAK–Src-p130Cas–Dock180 signaling complex, elevated Rac and c-Jun NH2-terminal kinase activation, and increased matrix metalloproteinase expression and activity. Our studies support a dual role for FAK in promoting cell motility and invasion through the activation of distinct signaling pathways
Applying hybrid clustering in pulsar candidate sifting with multi-modality for FAST survey
Pulsar search is always the basis of pulsar navigation, gravitational wave
detection and other research topics. Currently, the volume of pulsar candidates
collected by Five-hundred-meter Aperture Spherical radio Telescope (FAST) shows
an explosive growth rate that has brought challenges for its pulsar candidate
filtering System. Particularly, the multi-view heterogeneous data and class
imbalance between true pulsars and non-pulsar candidates have negative effects
on traditional single-modal supervised classification methods. In this study, a
multi-modal and semi-supervised learning based pulsar candidate sifting
algorithm is presented, which adopts a hybrid ensemble clustering scheme of
density-based and partition-based methods combined with a feature-level fusion
strategy for input data and a data partition strategy for parallelization.
Experiments on both HTRU (The High Time Resolution Universe Survey) 2 and FAST
actual observation data demonstrate that the proposed algorithm could
excellently identify the pulsars: On HTRU2, the precision and recall rates of
its parallel mode reach 0.981 and 0.988. On FAST data, those of its parallel
mode reach 0.891 and 0.961, meanwhile, the running time also significantly
decrease with the increment of parallel nodes within limits. So, we can get the
conclusion that our algorithm could be a feasible idea for large scale pulsar
candidate sifting of FAST drift scan observation
Identifying optimal ranges of weight gain at the end of the second trimester result from a population-based cohort study
Abstract
Objective:
To identify the optimal weight gain at the end of the second trimester.
Design:
This was a population-based cohort study from the antenatal care system in Tianjin, China. We calculated gestational weight gain (GWG) based on the weight measured in the first trimester and the end of the second trimester. Restricted cubic spline analysis was performed to model the possible non-linear relationships between GWG and adverse outcomes. The optimal GWG was defined as the value of the lowest risk. Non-inferiority margins and the shape of the spline curves identified the recommended ranges in Chinese-specific BMI categories.
Setting:
Tianjin Maternal and Child Health Cohort.
Participants:
Singleton pregnant women aged 18–45 years.
Results:
In total, 69 859 pregnant women were included. Adverse outcome (including stillbirth, preterm birth, hypertensive disorders of pregnancy, gestational diabetes mellitus, small and large for gestational age) was significantly associated with GWG at the end of the second trimester. The risk score was non-linearly correlated with GWG in the underweight, normal weight and overweight groups. GWG at the end of the second trimester should not be 0 kg) in the first and second trimesters.
Conclusions:
According to the comprehensive adverse maternal and infant outcomes, we recommend the optimal GWG at the end of the second trimester. This study may provide a considerable reference for weight management
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The MC4R genotype is associated with postpartum weight reduction and glycemic changes among women with prior gestational diabetes: longitudinal analysis
The genetic variants near the Melanocortin-4 receptor gene (MC4R), a key protein regulating energy balance and adiposity, have been related to obesity and glucose metabolism. We aimed to assess whether the MC4R genotype affected longitudinal changes in body weight and glucose metabolism biomarkers among women with prior gestational diabetes mellitus (GDM). The MC4R genotype, postpartum weight reduction, and glycemic changes between after delivery and pregnancy were assessed in a cohort of 1208 Chinese women who had experienced GDM. The adiposity-increasing allele (C) of the MC4R variant rs6567160 was associated with greater postpartum increase of HbA1c (β = 0.08%; P = 0.03) and 2-hour OGTT glucose concentrations (β = 0.25 mmol/L; P = 0.02). In addition, we found an interaction between the MC4R genotype and postpartum weight reduction on changes in fasting plasma glucose (P-interaction = 0.03). We found that the MC4R genotype was associated with postpartum glycemic changes; and the association with fasting glucose were significantly modified by postpartum weight reduction in women who had experienced GDM
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Maternal Glucose during Pregnancy and after Delivery in Women with Gestational Diabetes Mellitus on Overweight Status of Their Children
Objective:. To examine the association of maternal glycemia during pregnancy and after delivery with anthropometry in the offspring of mothers with gestational diabetes mellitus (GDM). Methods:. A total of 1,263 GDM mothers and their children finished the health survey at 1–5 years after delivery. Results:. Offspring of GDM mothers who were diagnosed with diabetes during pregnancy had higher prevalence of overweight, higher mean weight for height Z scores, and higher mean BMI for age Z scores at 1–5 years old than the offspring of GDM mothers who were diagnosed with impaired glucose tolerance (IGT) during pregnancy. Offspring of GDM mothers who developed diabetes 1–5 years after delivery had higher mean values of Z scores for weight for height and BMI for age at 1–5 years old than the offspring of GDM mothers who had normal glucose or prediabetes after delivery. Conclusions:. Offspring of GDM mothers who were diagnosed with diabetes during pregnancy or after delivery had an increased risk of childhood overweight or weight gain at 1–5 years old compared with children of GDM mothers with IGT during pregnancy or with normal glucose or prediabetes after delivery
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