Mutation of Arabidopsis HY1 causes UV-C hypersensitivity by impairing carotenoid and flavonoid biosynthesis and the down-regulation of antioxidant defence

Previous pharmacological results confirmed that haem oxygenase-1 (HO-1) is involved in protection of cells against ultraviolet (UV)-induced oxidative damage in soybean [Glycine max (L.) Merr.] seedlings, but there remains a lack of genetic evidence. In this study, the link between Arabidopsis thaliana HO-1 (HY1) and UV-C tolerance was investigated at the genetic and molecular levels. The maximum inducible expression of HY1 in wild-type Arabidopsis was observed following UV-C irradiation. UV-C sensitivity was not observed in ho2, ho3, and ho4 single and double mutants. However, the HY1 mutant exhibited UV-C hypersensitivity, consistent with the observed decreases in chlorophyll content, and carotenoid and flavonoid metabolism, as well as the down-regulation of antioxidant defences, thereby resulting in severe oxidative damage. The addition of the carbon monoxide donor carbon monoxide-releasing molecule-2 (CORM-2), in particular, and bilirubin (BR), two catalytic by-products of HY1, partially rescued the UV-C hypersensitivity, and other responses appeared in the hy1 mutant. Transcription factors involved in the synthesis of flavonoid or UV responses were induced by UV-C, but reduced in the hy1 mutant. Overall, the findings showed that mutation of HY1 triggered UV-C hypersensitivity, by impairing carotenoid and flavonoid synthesis and antioxidant defences

De novo mutations in ARID1B associated with both syndromic and non-syndromic short stature

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Initializing Models with Larger Ones

Weight initialization plays an important role in neural network training. Widely used initialization methods are proposed and evaluated for networks that are trained from scratch. However, the growing number of pretrained models now offers new opportunities for tackling this classical problem of weight initialization. In this work, we introduce weight selection, a method for initializing smaller models by selecting a subset of weights from a pretrained larger model. This enables the transfer of knowledge from pretrained weights to smaller models. Our experiments demonstrate that weight selection can significantly enhance the performance of small models and reduce their training time. Notably, it can also be used together with knowledge distillation. Weight selection offers a new approach to leverage the power of pretrained models in resource-constrained settings, and we hope it can be a useful tool for training small models in the large-model era. Code is available at https://github.com/OscarXZQ/weight-selection

Sources and formation of nucleation mode particles in remote tropical marine atmospheres over the South China Sea and the Northwest Paci fic Ocean

Peer reviewe

Long non-coding RNA ATB promotes malignancy of esophageal squamous cell carcinoma by regulating miR-200b/Kindlin-2 axis

Esophageal squamous cell carcinoma (ESCC) is one of the leading causes of cancer-related death, especially in China. In addition, the prognosis of late stage patients is extremely poor. However, the biological significance of the long non-coding RNA lnc-ATB and its potential role in ESCC remain to be documented. In this study, we investigated the role of lnc-ATB and the underlying mechanism promoting its oncogenic activity in ESCC. Expression of lnc-ATB was higher in ESCC tissues and cell lines than that in normal counterparts. Upregulated lnc-ATB served as an independent prognosis predictor of ESCC patients. Moreover, loss-of-function assays in ESCC cells showed that knockdown of lnc-ATB inhibited cell proliferation and migration both in vitroand in vivo. Mechanistic investigation indicated that lnc-ATB exerted oncogenic activities via regulating Kindlin-2, as the anti-migration role of lnc-ATB silence was attenuated by ectopic expression of Kindlin-2. Further analysis showed that lnc-ATB functions as a molecular sponge for miR-200b and Kindlin-2. Dysregulated miR-200b/Kindlin-2 signaling mediated the oncogenic activity of lnc-ATB in ESCC. Our results suggest that lnc-ATB predicts poor prognosis and may serve as a potential therapeutic target for ESCC patients

Systematic Theoretical Analysis of Dual-Parameters R

This paper systematically studied the simultaneous measurement of two parameters by a LC-type passive sensor from the theoretical perspective. Based on the lumped circuit model of the typical LC-type passive dual-parameter sensor system, the influencing factors of the signal strength of the sensor as well as the influencing factors of signal crosstalk were both analyzed. It is found that the influencing factors of the RF readout signal strength of the sensor are mainly quality factors (Q factors) of the LC tanks, coupling coefficients, and the resonant frequency interval of the two LC tanks. And the influencing factors of the signal crosstalk are mainly coupling coefficient between the sensor inductance coils and the resonant frequency interval of the two LC tanks. The specific influence behavior of corresponding influencing factors on the signal strength and crosstalk is illustrated by a series of curves from numerical results simulated by using MATLAB software. Additionally, a decoupling scheme for solving the crosstalk problem algorithmically was proposed and a corresponding function was derived out. Overall, the theoretical analysis conducted in this work can provide design guidelines for making the dual-parameter LC-type passive sensor useful in practical applications