TaNAC2, a NAC-type wheat transcription factor conferring enhanced multiple abiotic stress tolerances in Arabidopsis

Environmental stresses such as drought, salinity, and cold are major factors that significantly limit agricultural productivity. NAC transcription factors play essential roles in response to various abiotic stresses. However, the paucity of wheat NAC members functionally characterized to date does not match the importance of this plant as a world staple crop. Here, the function of TaNAC2 was characterized in Arabidopsis thaliana. A fragment of TaNAC2 was obtained from suppression subtractive cDNA libraries of wheat treated with polyethylene glycol, and its full-length cDNA was obtained by searching a full-length wheat cDNA library. Gene expression profiles indicated that TaNAC2 was involved in response to drought, salt, cold, and abscisic acid treatment. To test its function, transgenic Arabidopsis lines overexpressing TaNAC2–GFP controlled by the cauliflower mosaic virus 35S promoter were generated. Overexpression of TaNAC2 resulted in enhanced tolerances to drought, salt, and freezing stresses in Arabidopsis, which were simultaneously demonstrated by enhanced expression of abiotic stress-response genes and several physiological indices. Therefore, TaNAC2 has potential for utilization in transgenic breeding to improve abiotic stress tolerances in crops

Regional Disparities in Emissions of Rural Household Energy Consumption: A Case Study of Northwest China

The purpose of this paper is to present the emissions status of multiple rural areas from the perspective of a field survey and make up for the defects of the traditional emission cognition of single type of area. The basic data in the lower reaches of the Weihe River of Northwest China were collected through household questionnaire surveys, and emissions from rural household energy consumption were calculated in the paper. In addition, the grey relational analysis method was used to identify influential factors of emission disparities. The results show that the total emissions of the plain, loess tableland, and Qinling piedmont areas are 1863.20, 1850.43, and 2556.68 kg, respectively. Regional disparities in emissions of rural household energy consumption vary greatly. CO2 emissions are highest in the Qinling piedmont area, followed by the loess tableland area. For other emissions, there is no fixed order of the three areas, which suggests that disparities in emissions are connected with the dominant type of energy consumption. Diversification of energy use might not necessarily produce higher emissions, but the traditional biomass energy pattern does generate more emissions. The regional supply capacity of household energy is the original influence factor of disparities in emissions, and factors that influence these disparities are directly related to differences among farmers, followed by the age structure, educational background, income level, occupation, and so on

Breast cancer screening and early diagnosis in China: a systematic review and meta-analysis on 10.72 million women

Abstract Background The incidence of breast cancer among Chinese women has gradually increased in recent years. This study aims to analyze the situation of breast cancer screening programs in China and compare the cancer detection rates (CDRs), early-stage cancer detection rates (ECDRs), and the proportions of early-stage cancer among different programs. Methods We conducted a systematic review and meta-analysis of studies in multiple literature databases. Studies that were published between January 1, 2010 and June 30, 2023 were retrieved. A random effects model was employed to pool the single group rate, and subgroup analyses were carried out based on screening model, time, process, age, population, and follow-up method. Results A total of 35 studies, including 47 databases, satisfied the inclusion criteria. Compared with opportunistic screening, the CDR (1.32‰, 95% CI: 1.10‰–1.56‰) and the ECDR (0.82‰, 95% CI: 0.66‰–0.99‰) were lower for population screening, but the proportion of early-stage breast cancer (80.17%, 95% CI: 71.40%–87.83%) was higher. In subgroup analysis, the CDR of population screening was higher in the urban group (2.28‰, 95% CI: 1.70‰–2.94‰), in the breast ultrasonography (BUS) in parallel with mammography (MAM) group (3.29‰, 95% CI: 2.48‰–4.21‰), and in the second screening follow-up group (2.47‰, 95% CI: 1.64‰–3.47‰), and the proportion of early-stage breast cancer was 85.70% (95% CI: 68.73%–97.29%), 88.18% (95% CI: 84.53%–91.46%), and 90.05% (95% CI: 84.07%–94.95%), respectively. Conclusion There were significant differences between opportunistic and population screening programs. The results of these population screening studies were influenced by the screening process, age, population, and follow-up method. In the future, China should carry out more high-quality and systematic population-based screening programs to improve screening coverage and service

Can magmatic zircon be distinguished from hydrothermal zircon by trace element composition? The effect of mineral inclusions on zircon trace element composition

Mineral inclusions, e.g., apatite, titanite, monazite, K-feldspar, are common in magmatic zircons. Although many studies mention that light rare earth element (LREE) contents of zircons could be compromised by an analytical artefact of the accidental sampling of mineral inclusions, how and to what degree these inclusions influence analysis of zircon composition is still not well constrained. Here we report U–Pb ages and trace element abundances for zircon crystals, where apatite and K-feldspar inclusions are observed, from diorite porphyry in the Weibao deposit, East Kunlun Mountains, Northern Tibetan Plateau. Although zircon morphological and chronological evidence consistently advocates a magmatic origin without undergoing significant hydrothermal alteration, 7 of 15 analytical spots show LREE-enriched patterns and low Ce/Ce* ratios which are comparable to those for published “hydrothermal” zircon. Quantitative modelling in this study manifests that these LREE-enriched patterns and low Ce/Ce* ratios can be achieved with only 0.1 to 2 vol% contamination from sub-micrometer apatite inclusions, which in practice are hard to monitor under the LA–ICP–MS (normally with large pit diameter and depth) and conventional microscopes. Titanite, monazite, xenotime, and allanite have similar roles to apatite, and LREE contents of zircon can be significantly elevated with only 0.05 vol% contamination from these inclusions. We therefore suggest that the widely used geochemical discrimination criteria for magmatic and hydrothermal zircon, e.g., (Sm/La)N vs. La and Ce/Ce* vs. (Sm/La)N diagrams and the degree of Ce anomalies, are ambiguous since they are extremely susceptible to contamination by mineral inclusions, and that within single samples only Ce4+/Ce3+ values calculated from zircons of low LREE values probably represent the oxidation state of magmas

Knockdown of Long Non-Coding RNA UCA1 Increases the Tamoxifen Sensitivity of Breast Cancer Cells through Inhibition of Wnt/β-Catenin Pathway.

Acquired resistance to tamoxifen remains a major obstacle in breast cancer (BC) treatment, since the underlying mechanism has not been fully elucidated. The long non-coding RNA (lncRNA) urothelial carcinoma-associated 1 (UCA1) has been recently shown to be dysregulated and plays important roles in progression of breast cancer. In the present study, we aimed to investigate the biological role and clinical significance of UCA1 in BC drug resistance. Hence, we used quantitative PCR assay to evaluate the UCA1 expression in tissues from patients with BC as well as established tamoxifen-resistant BC cell lines in vitro. We tested the viability, invasive ability and apoptosis rate in MCF-7 and T47D cells using MTT assay, transwell assay and flow cytometry assay, respectively. The influence of UCA1 on tumorigenesis was monitored by in vivo mice xenograft model. The activation of Wnt/β-catenin signaling pathway was evaluated by immunofluorescence assay, western blot assay and luciferase reporter assay, respectively. We found that the expression of UCA1 positively correlated with the pathological grade and mortality of breast cancer patients, moreover, expressions of UCA1 was increased significantly in the tamoxifen-resistant cell lines compared with the wild type parental cells. Ectopic expression of UCA1 promoted cell survival and resistance to tamoxifen treatment, whereas inhibition of UCA1 enhanced tamoxifen sensitivity of BC cells and induced more apoptotic cells. In addition, tamoxifen-resistant cells exhibited increased Wnt signaling activation as measured by the TOP/FOP Wnt luciferase reporter assay and β-catenin protein level compared with parental MCF-7 and T47D cells, respectively. In line with these data, UCA1 depletion attenuated the activity of Wnt/β-catenin pathway activation and the tumorigenicity of the tamoxifen-resistant BC cells. Taken together, our data highlights the pivotal role of UCA1-Wnt/β-catenin signaling pathway in the tamoxifen resistance in breast cancer, which could be targeted to improve the effectiveness and efficacy of tamoxifen treatment in breast cancer

A fault-tolerant sensor scheduling approach for target tracking in wireless sensor networks

Target tracking is a critical application in wireless sensor networks (WSNs). Existing target tracking algorithms basically perform node scheduling based on trajectory prediction. Once the target is lost due to prediction errors, the target recovery mechanism performs a search to find the target, which may require the system to activate a large number of nodes and cause additional energy consumption. Moreover, the target data may be lost due to the time consuming of target recovery. To solve this problem, we propose a fault-tolerant sensor scheduling (FTSS) approach to reduce the target loss probability as much as possible. Furthermore, we design a low-power scheduling mechanism in FTSS to reduce energy consumption. In FTSS, we first design a fault-tolerant domain to expand the scheduling range of candidate nodes. Then, we consider remaining energy, sensing coverage, and overlapping coverage to activate as few sensors as possible to cover the fault-tolerant domain. Moreover, we employ an improved binary Grey Wolf Optimizer (bGWO) in the optimization process to speed up the convergence. Numeric evaluations indicate that, compared to DPT, HCTT, GBRHA, and E2DR-MCS, our method achieves 11%, 2.3%, 7.8%, 4.6% reduction in target loss probability, and improves network lifetime by 138%, 49%, 31%, 19%, respectively

Preparation and Degradation of Seedling Containers Made from Straw and Hydrolyzed Soy Protein Isolate Modified Urea-Formaldehyde Resins

Straw powders were blended with hydrolyzed soy protein isolate (HSPI) modified urea-formaldehyde (UF) resins to produce biodegradable seedling containers. The tensile strength and the degradability of the seedling containers were characterized. Moreover, the degradation behavior of modified UF resins was investigated using 15N isotopic tracing, dynamic mechanical analysis, 13C CP/MAS NMR spectroscopy, and a scanning electron microscope-energy dispersive spectrometer. The results showed that the best tensile strength of the seedling containers made from HSPI-modified UF resins was improved by 6% compared with the seedling containers made from UF resins. The degradability of the seedling containers made from modified UF resins was improved 8.8 times more than that of unmodified UF resins. HSPI can lower the cross-linking degree of UF resins. The HSPI and urea-formaldehyde molecular chains in the resins were decomposed simultaneously in the soil. After degradation, nodular particles that appeared to be coalesced by small globular particles remained. In the process of degradation, modified UF resins can provide a nitrogen source for crops

Physical, Chemical, and Rheological Properties of Rice Husks Treated by Composting Process

A composting treatment was employed in an effort to improve the processability of rice husks. Changes in the chemical composition, physical structure, and rheological properties of modified rice husks were analyzed. The results indicated that the average diameter of compost-treated samples was significantly higher than that of the untreated samples because they were able to adhere to each other by the bacterial protein. Scanning electron microscopy images showed that the epidermis became rugged and lumpy because the composition of rice husks (cellulose, hemicellulose, lignin, and pectin) was partially decomposed, an effect confirmed by the chemical composition and FTIR analysis. Thermogravimetric analysis showed that the composted samples had better thermal stability than the untreated ones. Stress-strain curves showed that the treated samples displayed a moderately significant change of slope at about 0 to 10% strain, and they had better mechanical properties than untreated samples. Juxtaposing the rheological properties of both untreated and treated samples determined that the latter had higher apparent viscosity as a result of degradation and bacterial protein effects. All results indicated that the composting treatment changed the physical, chemical, and rheological properties of the rice husks, which are beneficial for its utilization and processability

An Improved Q-Learning-Based Sensor-Scheduling Algorithm for Multi-Target Tracking

Target tracking is an essential issue in wireless sensor networks (WSNs). Compared with single-target tracking, how to guarantee the performance of multi-target tracking is more challenging because the system needs to balance the tracking resource for each target according to different target properties and network status. However, the balance of tracking task allocation is rarely considered in those prior sensor-scheduling algorithms, which may result in the degradation of tracking accuracy for some targets and additional system energy consumption. To address this issue, we propose in this paper an improved Q-learning-based sensor-scheduling algorithm for multi-target tracking (MTT-SS). First, we devise an entropy weight method (EWM)-based strategy to evaluate the priority of targets being tracked according to target properties and network status. Moreover, we develop a Q-learning-based task allocation mechanism to obtain a balanced resource scheduling result in multi-target-tracking scenarios. Simulation results demonstrate that our proposed algorithm can obtain a significant enhancement in terms of tracking accuracy and energy efficiency compared with the existing sensor-scheduling algorithms

A detection probability guaranteed energy-efficient scheduling mechanism in large-scale WSN

In intrusion detection wireless sensor network (WSN), ensuring detection performance and prolonging network lifetime are two equally important but contradictory pursuits. In this paper, we propose a node scheduling scheme jointly considering the detection probability, energy consumption, and energy balance to ensure the detection performance and maximize the network lifetime. We mathematically transform the scheduling process into an optimization problem and further propose a novel mechanism called greedy-like step-by-step trimming heuristic algorithm (GLSTA) to obtain the optimal task nodes set. By gradually trimming unnecessary nodes, GLSTA intelligently eliminates redundancy and obtains a task set that can save energy and balance the residual energy of nodes. Moreover, we propose a dual cluster head (OCH-DCH, organization cluster head-data cluster head) scheme to realize the smooth update of the cluster due to the target movement. Simulation results show that the rounds of half nodes death of GLSTA are extended by at least 28.6% compared with existing mechanisms