Chloroplast development and genomes uncoupled signaling are independent of the RNA-directed DNA methylation pathway

The Arabidopsis genome is methylated in CG and non-CG (CHG, and CHH in which H stands for A, T, or C) sequence contexts. DNA methylation has been suggested to be critical for seed development, and CHH methylation patterns change during stratification and germination. In plants, CHH methylation occurs mainly through the RNA-directed DNA methylation (RdDM) pathway. To test for an involvement of the RdDM pathway in chloroplast development, we analyzed seedling greening and the maximum quantum yield of photosystem II (F-v/F-m) in Arabidopsis thaliana seedlings perturbed in components of that pathway. Neither seedling greening nor F-v/F-m in seedlings and adult plants were affected in this comprehensive set of mutants, indicating that alterations in the RdDM pathway do not affect chloroplast development. Application of inhibitors like lincomycin or norflurazon inhibits greening of seedlings and represses the expression of photosynthesis-related genes including LIGHT HARVESTING CHLOROPHYLL A/B BINDING PROTEIN1.2 (LHCB1.2) in the nucleus. Our results indicate that the LHCB1.2 promoter is poorly methylated under both control conditions and after inhibitor treatment. Therefore no correlation between LHCB1.2 mRNA transcription and methylation changes of the LHCB1.2 promoter could be established. Moreover, we conclude that perturbations in the RdDM pathway do not interfere with gun signaling

Organellar Gene Expression and Acclimation of Plants to Environmental Stress

Organelles produce ATP and a variety of vital metabolites, and are indispensable for plant development. While most of their original gene complements have been transferred to the nucleus in the course of evolution, they retain their own genomes and gene-expression machineries. Hence, organellar function requires tight coordination between organellar gene expression (OGE) and nuclear gene expression (NGE). OGE requires various nucleus-encoded proteins that regulate transcription, splicing, trimming, editing, and translation of organellar RNAs, which necessitates nucleus-to-organelle (anterograde) communication. Conversely, changes in OGE trigger retrograde signaling that modulates NGE in accordance with the current status of the organelle. Changes in OGE occur naturally in response to developmental and environmental changes, and can be artificially induced by inhibitors such as lincomycin or mutations that perturb OGE. Focusing on the model plant Arabidopsis thaliana and its plastids, we review here recent findings which suggest that perturbations of OGE homeostasis regularly result in the activation of acclimation and tolerance responses, presumably via retrograde signaling

Precomputed Multiple Scattering for Rapid Light Simulation in Participating Media

International audienceRendering translucent materials is costly: light transport algorithms need to simulate a large number of scattering events inside the material before reaching convergence. The cost is especially high for materials with a large albedo or a small mean-free-path, where higher-order scattering effects dominate. We present a new method for fast computation of global illumination with participating media. Our method uses precomputed multiple scattering effects, stored in two compact tables. These precomputed multiple scattering tables are easy to integrate with any illumination simulation algorithm. We give examples for virtual ray lights (VRL), photon mapping with beams and paths (UPBP), Metropolis Light Transport with Manifold Exploration (MEMLT). The original algorithms are in charge of low-order scattering, combined with multiple scattering computed using our table. Our results show significant improvements in convergence speed and memory costs, with negligible impact on accuracy

Gonadal tumor risk in pediatric and adolescent phenotypic females with disorders of sex development and Y chromosomal constitution with different genetic etiologies

ObjectivesThis retrospective study sought to investigate the risk and proportion of gonadal neoplasms in phenotypic female pediatric patients with DSD and the presence of the Y chromosome and different genetic backgrounds in a single Chinese center.Materials and MethodsFrom January 2012 to December 2020, pediatric and adolescent patients with DSD and the presence of the Y chromosome who had unambiguous female genitalia and underwent bilateral gonadectomy or gonadal biopsy were included in this study. Patients’ demographics, karyotype, laboratory test results, gross pathology, and histology of gonadal tissue were all collected. The patients were divided into three groups based on their different genetic backgrounds, and the percentage of gonadal tumors was calculated to assess the risk of gonadal tumor and malignancy by etiology.ResultsA total of 22 patients with DSD and an unambiguous female phenotype with a Y chromosome were recruited. The mean age was 10.91 ± 4.99 years (9 months to 19 years). Gonadal neoplasia was confirmed in six (27.3%) cases by pathological examination of surgical gonadal tissue samples. Among 44 gonadal samples from these 22 patients, the following were identified: five gonadoblastomas, three dysgerminomas, and two Leydig cell tumors. The youngest patient with a tumor was a 2-year-old girl with 46,XY complete gonadal dysgenesis (46,XY CGD or Swyer syndrome) and bilateral gonadoblastoma. Patients with 46,XY complete gonadal dysgenesis (4/6; 66.7%) had the highest tumor occurrence rate. Among 10 patients with Turner syndrome with the presence of the Y chromosome, only one patient was diagnosed with a gonadal tumor. Leydig cell tumor was diagnosed in only one of six patients with 46,XY androgen synthesis/action disorders.ConclusionPediatric patients with 46,XY complete gonadal dysgenesis had a significantly increased risk of developing gonadal tumors and underwent prophylactic gonadectomy as soon as the diagnosis was confirmed, whereas those with Turner syndrome with Y chromosome and 46,XY androgen synthesis/action disorders had a relatively low risk. In view of the limited number of patients, a large multicenter study with close follow-ups is needed to support these conclusions

The effect of the social support on PTSD and PTG about university student volunteers in the prevention and controlling of coronavirus: with coping style as the intermediary

To investigate the relationship among post-traumatic stress disorder (PTSD), posttraumatic growth (PTG), social support, and coping style of university student volunteers in the prevention and control of the coronavirus in 2020, a total of 2,990 university student volunteers (students who are enrolled in a university and involved in volunteer activities) from 20 universities in Sichuan Province participated in the prevention and control of the epidemic were investigated when March 20–31, 2020 when the coronavirus first occurred using the post-traumatic stress disorder questionnaire, posttraumatic growth questionnaire, university student social support questionnaire and coping style questionnaire. The results showed that (1) 7.06% of university student volunteers had some degree of PTSD symptoms (the total PCL-C score was 38–49), and 2.88% had obvious PTSD symptoms, (2) PTSD level of university student volunteers was significantly positively correlated with negative coping style, and significantly negatively correlated with social support and positive coping style; on the contrary, the PTG level is significantly positively correlated with social support and positive coping styles, and (3) Positive coping style plays a partial mediating role in the influence of social support on PTG; in the influence of social support on PTSD, the mediating effect of positive or negative coping style was not significant. These results show that in the prevention and control of the coronavirus, the positive coping style and social support of university student volunteers can positively predict the PTG level of them, while the negative coping style can positively predict the severity of their PTSD symptoms. Among them, a positive coping style plays a partial mediating role in the influence of social support on the PTG level

Trajectory Series Analysis based Event Rule Induction for Visual Surveillance

In this paper, a generic rule induction framework based on trajectory series analysis is proposed to learn the event rules. First the trajectories acquired by a tracking system are mapped into a set of primitive events that represent some basic motion patterns of moving object. Then a min-imum description length (MDL) principle based grammar induction algorithm is adopted to infer the meaningful rules from the primitive event series. Compared with previous grammar rule based work on event recognition where the rules are all defined manually, our work aims to learn the event rules automatically. Experiments in a traffic cross-road have demonstrated the effectiveness of our methods. Shown in the experimental results, most of the grammar rules obtained by our algorithm are consistent with the ac-tual traffic events in the crossroad. Furthermore the traffic lights rule in the crossroad can also be leaned correctly with the help of eliminating the irrelevant trajectories. 1

A road quality classification technique based on vehicle system responses with experimental validation

Aiming at estimating the road surface condition with improvement of the accuracy in spatial, this paper proposes a new method to classify road surface condition by considering identification interval based on vehicle system responses. First, the response signals in different vehicle speeds are decomposed by using both Wavelet Transform (WT) and Empirical Mode Decomposition (EMD) techniques. Then characteristics of the signals in both the time and decomposed frequency domain are subsequently extracted. An Improved Distance Evaluation Technique (IDET) is used to select superior features from the characteristics. Finally, a Support Vector Machine (SVM) classifier is applied to determine the road classification. The influences of identification intervals in spatial accuracy are discussed, and an adaptive classification interval was proposed to improve accuracy. The algorithm is validated by using both simulation and experimental results