J-shaped association between dietary zinc intake and new-onset hypertension: a nationwide cohort study in China / 医学前沿

We aimed to investigate the relationship of dietary zinc intake with new-onset hypertension among Chinese adults. A total of 12,177 participants who were free of hypertension at baseline from the China Health and Nutrition Survey were included. Dietary intake was assessed by three consecutive 24-h dietary recalls combined with a household food inventory. Participants with systolic blood pressure ≽ 140 mmHg or diastolic blood pressure ≽ 90 mmHg or diagnosed by a physician or under antihypertensive treatment during the follow-up were defined as having new-onset hypertension. During a median follow-up duration of 6.1 years, 4269 participants developed new-onset hypertension. Overall, the association between dietary zinc intake and new-onset hypertension followed a J-shape (P for non-linearity < 0.001). The risk of new-onset hypertension significantly decreased with the increment of dietary zinc intake (per mg/day: hazard ratio (HR) 0.93; 95% confidence interval (CI) 0.88-0.98) in participants with zinc intake < 10.9 mg/day, and increased with the increment of zinc intake (per mg/day: HR 1.14; 95% CI 1.11-1.16) in participants with zinc intake ≽ 10.9 mg/day. In conclusion, there was a J-shaped association between dietary zinc intake and new-onset hypertension in general Chinese adults, with an inflection point at about 10.9 mg/day.

The review of ionizing radiation model studies using Caenorhabditis elegans / 中华放射医学与防护杂志

With the increasing prominence of radiotherapy in the treatment of tumors,how to reduce the side effects of radiotherapy has become a hot research topic gradually.Caenorhabditis elegans (C.elegans) has become a good model for studying ionizing radiation due to its unique advantages.In recent years,there's increasing study on ionizing radiation by using nematode model.In this paper,the effects of ionizing radiation on nematode and underlying mechanisms are reviewed briefly.

Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression Recognition.

Facial expression is a temporally dynamic event which can be decomposed into a set of muscle motions occurring in different facial regions over various time intervals. For dynamic expression recognition, two key issues, temporal alignment and semantics-aware dynamic representation, must be taken into account. In this paper, we attempt to solve both problems via manifold modeling of videos based on a novel mid-level representation, i.e., expressionlet. Specifically, our method contains three key stages: 1) each expression video clip is characterized as a spatial-temporal manifold (STM) formed by dense low-level features; 2) a universal manifold model (UMM) is learned over all low-level features and represented as a set of local modes to statistically unify all the STMs; and 3) the local modes on each STM can be instantiated by fitting to the UMM, and the corresponding expressionlet is constructed by modeling the variations in each local mode. With the above strategy, expression videos are naturally aligned both spatially and temporally. To enhance the discriminative power, the expressionlet-based STM representation is further processed with discriminant embedding. Our method is evaluated on four public expression databases, CK+, MMI, Oulu-CASIA, and FERA. In all cases, our method outperforms the known state of the art by a large margin.