Sense and antisense OsDof12 transcripts in rice

<p>Abstract</p> <p>Background</p> <p>Antisense transcription is a widespread phenomenon in plants and mammals. Our previous data on rice gene expression analysis by microarray indicated that the sense and antisense transcripts at the <it>OsDof12 </it>locus were co-expressed in leaves. In current study, we analyzed the expression patterns in detail and looked for the possible mechanism related to their expression patterns.</p> <p>Results</p> <p><it>OsDof12</it>, being a single copy gene located on rice chromosome 3, encodes a predicted Dof protein of 440 amino acids with one intron of 945 bp. The antisense transcript, <it>OsDofl2os</it>, overlaps with both the exonic and intronic regions of <it>OsDof12 </it>and encodes a functionally unknown protein of 104 amino acids with no intron. The sense-antisense <it>OsDof12 </it>transcripts were co-expressed within the same tissues, and their expressions were not tissue-specific in general. At different developmental stages in rice, the <it>OsDof12 </it>and <it>OsDof12os </it>transcripts exhibited reciprocal expression patterns. Interestingly, the expression of both genes was significantly induced under drought treatment, and inhibited by dark treatment. In the <it>Pro</it>_{<it>OsDof</it>12}<it>-GUS </it>and <it>Pro</it>_{<it>OsDof</it>12<it>os</it>}-<it>GUS </it>transgenic rice plants, the expression profiles of GUS were consistent with those of the <it>OsDof12 </it>and <it>OsDof12os </it>transcripts, respectively. In addition, the analysis of cis-regulatory elements indicated that either of the two promoters contained 74 classes of cis-regulatory elements predicted, of which the two promoter regions shared 53 classes.</p> <p>Conclusion</p> <p>Based on the expression profiles of <it>OsDof12 </it>and <it>OsDof12os</it>, the expression patterns of GUS in the <it>Pro</it>_{<it>OsDof</it>12}<it>-GUS </it>and <it>Pro</it>_{<it>OsDof</it>12<it>os</it>}-<it>GUS </it>transgenic rice plants and the predicted common cis-regulatory elements shared by the two promoters, we suggest that the co-expression patterns of <it>OsDof12 </it>and <it>OsDof12os </it>might be attributed to the basically common nature of the two promoters.</p

Boundary-semantic collaborative guidance network with dual-stream feedback mechanism for salient object detection in optical remote sensing imagery

With the increasing application of deep learning in various domains, salient object detection in optical remote sensing images (ORSI-SOD) has attracted significant attention. However, most existing ORSI-SOD methods predominantly rely on local information from low-level features to infer salient boundary cues and supervise them using boundary ground truth, but fail to sufficiently optimize and protect the local information, and almost all approaches ignore the potential advantages offered by the last layer of the decoder to maintain the integrity of saliency maps. To address these issues, we propose a novel method named boundary-semantic collaborative guidance network (BSCGNet) with dual-stream feedback mechanism. First, we propose a boundary protection calibration (BPC) module, which effectively reduces the loss of edge position information during forward propagation and suppresses noise in low-level features without relying on boundary ground truth. Second, based on the BPC module, a dual feature feedback complementary (DFFC) module is proposed, which aggregates boundary-semantic dual features and provides effective feedback to coordinate features across different layers, thereby enhancing cross-scale knowledge communication. Finally, to obtain more complete saliency maps, we consider the uniqueness of the last layer of the decoder for the first time and propose the adaptive feedback refinement (AFR) module, which further refines feature representation and eliminates differences between features through a unique feedback mechanism. Extensive experiments on three benchmark datasets demonstrate that BSCGNet exhibits distinct advantages in challenging scenarios and outperforms the 17 state-of-the-art (SOTA) approaches proposed in recent years. Codes and results have been released on GitHub: https://github.com/YUHsss/BSCGNet.Comment: Accepted by TGR

Contribution of infrastructure to the township's sustainable development in Southwest China

Townships in Southwest China are usually located in mountainous regions, which are abundant in natural and cultural landscape resources. There are additional requirements for the township’s sustainable development in these areas. However, insufficient infrastructures, due to limited resources, constrain the sustainable development of these townships. Sustainable contribution of infrastructure (SCOI) in this study is defined as the performance of infrastructure as a contribution to the coordinated development among economic, social, and environmental dimensions of township’s sustainable development. It is necessary to assess these infrastructures according to SCOI and provide choices for investment to maximize resource utilization. Therefore, an assessing model of SCOI with 26 general indicators was developed, which covers five most urgently needed infrastructures of these townships in Southwest China, including road transport, sewage treatment, waste disposal, water supply, and gas. In this model, quantitative and qualitative methods are combined to acquire different SCOI of each infrastructure. The result of the SCOI would be an important reference for infrastructure investment. A case study of Jiansheng Town, that is located in the Dadukou district of Chongqing, demonstrates the applicability of the model. It shows the assessing model of SCOI is efficient to identify the most valuable infrastructure that is appropriate for investment with the goal of township’s sustainable development. This study can provide insights for infrastructure investment and management in townships or areas

Mesoporous TiO

Mesoporous anatase TiO2 micro-nanometer composite structure was synthesized by solvothermal method at 180°C, followed by calcination at 400°C for 2 h. The as-prepared TiO2 was characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), and Fourier transform infrared spectrum (FT-IR). The specific surface area and pore size distribution were obtained from N2 adsorption-desorption isotherm, and the optoelectric property of the mesoporous TiO2 was studied by UV-Vis absorption spectrum and surface photovoltage spectra (SPS). The photocatalytic activity was evaluated by photodegradation of sole rhodamine B (RhB) and sole phenol aqueous solutions under simulated sunlight irradiation and compared with that of Degussa P-25 (P25) under the same conditions. The photodegradation preference of this mesoporous TiO2 was also investigated for an RhB-phenol mixed solution. The results show that the TiO2 composite structure consists of microspheres (∼0.5–2 μm in diameter) and irregular aggregates (several hundred nanometers) with rough surfaces and the average primary particle size is 10.2 nm. The photodegradation activities of this mesoporous TiO2 on both RhB and phenol solutions are higher than those of P25. Moreover, this as-prepared TiO2 exhibits photodegradation preference on RhB in the RhB-phenol mixture solution

Establishment and evaluation of a predictive model for length of hospital stay after total knee arthroplasty: A single-center retrospective study in China

BackgroundTotal knee arthroplasty (TKA) is the ultimate option for end-stage osteoarthritis, and the demand of this procedure are increasing every year. The length of hospital stay (LOS) greatly affects the overall cost of joint arthroplasty. The purpose of this study was to develop and validate a predictive model using perioperative data to estimate the risk of prolonged LOS in patients undergoing TKA.MethodsData for 694 patients after TKA collected retrospectively in our department were analyzed by logistic regression models. Multi-variable logistic regression modeling with forward stepwise elimination was used to determine reduced parameters and establish a prediction model. The discrimination efficacy, calibration efficacy, and clinical utility of the prediction model were evaluated.ResultsEight independent predictors were identified: non-medical insurance payment, Charlson Comorbidity Index (CCI) ≥ 3, body mass index (BMI) &gt; 25.2, surgery on Monday, age &gt; 67.5, postoperative complications, blood transfusion, and operation time &gt; 120.5 min had a higher probability of hospitalization for ≥6 days. The model had good discrimination [area under the curve (AUC), 0.802 95% CI, 0.754–0.850]] and good calibration (p = 0.929). A decision curve analysis proved that the nomogram was clinically effective.ConclusionThis study identified risk factors for prolonged hospital stay in patients after TKA. It is important to recognize all the factors that affect hospital LOS to try to maximize the use of medical resources, optimize hospital LOS and ultimately optimize the care of our patients

Emissions of NO and NH3 from a Typical Vegetable-Land Soil after the Application of Chemical N Fertilizers in the Pearl River Delta

Conceived and designed the experiments: DL. Performed the experiments: DL. Analyzed the data: DL. Contributed reagents/materials/analysis tools: DL. Wrote the paper: DL.Cropland soil is an important source of atmospheric nitric oxide (NO) and ammonia (NH3). Chinese croplands are characterized by intensive management, but limited information is available with regard to NO emissions from croplands in China and NH3 emissions in south China. In this study, a mesocosm experiment was conducted to measure NO and NH3 emissions from a typical vegetable-land soil in the Pearl River Delta following the applications of 150 kg N ha−1 as urea, ammonium nitrate (AN) and ammonium bicarbonate (ABC), respectively. Over the sampling period after fertilization (72 days for NO and 39 days for NH3), mean NO fluxes (± standard error of three replicates) in the control and urea, AN and ABC fertilized mesocosms were 10.9±0.9, 73.1±2.9, 63.9±1.8 and 66.0±4.0 ng N m−2 s−1, respectively; mean NH3 fluxes were 8.9±0.2, 493.6±4.4, 144.8±0.1 and 684.7±8.4 ng N m−2 s−1, respectively. The fertilizer-induced NO emission factors for urea, AN and ABC were 2.6±0.1%, 2.2±0.1% and 2.3±0.2%, respectively. The fertilizer-induced NH3 emission factors for the three fertilizers were 10.9±0.2%, 3.1±0.1% and 15.2±0.4%, respectively. From the perspective of air quality protection, it would be better to increase the proportion of AN application due to its lower emission factors for both NO and NH3.Yeshttp://www.plosone.org/static/editorial#pee

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Stochastic mSQG equations with multiplicative transport noises: White noise solutions and scaling limit

Luo D, Zhu R. Stochastic mSQG equations with multiplicative transport noises: White noise solutions and scaling limit. Stochastic Processes and their Applications. 2021;140:236-286.We consider the modified Surface Quasi-Geostrophic (mSQG) equation on the 2D torus T-2, perturbed by multiplicative transport noise. The equation admits the white noise measure on T-2 as the invariant measure. We first prove the existence of white noise solutions to the stochastic equation via the method of point vortex approximation, then, under a suitable scaling limit of the noise, we show that the solutions converge weakly to the unique stationary solution of the dissipative mSQG equation driven by spacetime white noise. The weak uniqueness of the latter equation is also proved by following Gubinelli and Perkowski's approach in Gubinelli and Perkowski (2020). (C) 2021 Elsevier B.V. All rights reserved