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Simultaneous stresses of salinity and drought often coincide during rice-growing seasons in saline lands, primarily due to insufficient water resources and inadequate irrigation facilities. Consequently, combined salinity-drought stress poses a major threat to rice production. In this study, two salinity levels (NS, non-salinity; HS, high salinity) along with three drought treatments (CC, control condition; DJ, drought stress imposed at jointing; DH, drought stress imposed at heading) were performed to investigate their combined influences on leaf photosynthetic characteristics, biomass accumulation, and rice yield formation. Salinity, drought, and their combination led to a shortened growth period from heading to maturity, resulting in a reduced overall growth duration. Grain yield was reduced under both salinity and drought stress, with a more substantial reduction under the combined salinity-drought stress. The combined stress imposed at heading caused greater yield losses in rice compared with the stress imposed at jointing. Additionally, the combined salinity-drought stress induced greater decreases in shoot biomass accumulation from heading to maturity, as well as in shoot biomass and nonstructural carbohydrate (NSC) content in the stem at heading and maturity. However, it increased the harvest index and NSC remobilization reserve. Salinity and drought reduced the leaf area index and SPAD value of flag leaves and weakened the leaf photosynthetic characteristics as indicated by lower photosynthetic rates, transpiration rates, and stomatal conductance. These reductions were more pronounced under the combined stress. Salinity, drought, and especially their combination, decreased the activities of ascorbate peroxidase, catalase, and superoxide dismutase, while increasing the contents of malondialdehyde, hydrogen peroxide, and superoxide radical. Our results indicated a more significant yield loss in rice when subjected to combined salinity-drought stress. The individual and combined stresses of salinity and drought diminished antioxidant enzyme activities, inhibited leaf photosynthetic functions, accelerated leaf senescence, and subsequently lowered assimilate accumulation and grain yield.

Detection of biomarkers was extremely important for the early diagnosis, prognosis, and therapy optimization of diseases. The purpose of this study was to investigate the differences in serum metabolites between patients with heart failure (HF) and healthy control (HC) and to diagnose HF qualitatively. In this study, serum samples from 83 patients with HF and 35 HCs were used as the research subjects for untargeted metabolomic analysis using ultraperformance liquid chromatography combined with quadrupole‐time of flight mass spectrometry (UPLC‐QTOF/MS) technology. Potential biomarkers were screened and validated using the orthogonal partial least squares discriminant analysis (OPLS‐DA), random forest (RF), binary logistic regression (BLR), and receiver operating characteristic (ROC) analysis. The results indicated that a total of 43 metabolites were considered as differentially expressed metabolites (DEMs). Among these DEMs, glycodeoxycholate was identified as a specific biomarker of HF. A ROC curve analysis for HC versus HF discrimination showed an area under the ROC curve (AUC) of 0.9853 (95% CI: 0.9859–1.0000), a sensitivity of 95%, and a specificity of 100%. Hence, glycodeoxycholate might serve as a potential biomarker for HF. Furthermore, the amino acid metabolism was screened as the most significantly altered pathway in patients with HF. By identifying serum biomarkers and analyzing metabolic pathways, our study provided opportunities to enhance the understanding of the pathogenesis and early diagnosis of HF. [ABSTRACT FROM AUTHOR]

Rotational speed measurement is important for many applications. Here, a noncontact rotational speed test method based on the detection of the periodically perturbed near-field microwave of an open-ended waveguide is proposed. Both simulations and experiments were conducted to verify the near-field microwave rotational speed sensor. The constructed rotation speed sensing system was composed of a standard open-ended WR-42 waveguide (in our measurements, a waveguide-to-coaxial adapter was used to represent an open-ended waveguide) working at ~18 GHz, a radio frequency (RF) circulator, a signal generator, a, RF detector and an oscilloscope. A rotating fan to be measured was placed close to the waveguide's mouth and, thus, the waveguide's reflection coefficient was periodically modulated by the rotating fan blades. Then, the RF detector converted this varying reflection coefficient into a direct current (DC) voltage, namely, a periodical waveform. Finally, the rotational speed of the fan could be extracted from this waveform. Measurements using both the proposed near-field microwave method and conventional optical transmission/reflection methods were conducted for verification. The effect of the rotating fan's location relative to the waveguide's mouth was also studied. The results show the following: 1. The proposed method works well with a rotational speed of up to ~5000 RPM (rounds per minute), and an accuracy of 1.7% can be achieved. 2. Metallic or non-metallic fan blades are all suitable for this method. Compared with the existing radar method, the proposed method may be advantageous for rotation detection in a constrained space. [ABSTRACT FROM AUTHOR]

Monitoring winter wheat Soil–Plant Analysis Development (SPAD) values using Unmanned Aerial Vehicles (UAVs) is an effective and non-destructive method. However, predicting SPAD values during the booting stage is less accurate than other growth stages. Existing research on UAV-based SPAD value prediction has mainly focused on low-altitude flights of 10–30 m, neglecting the potential benefits of higher-altitude flights. The study evaluates predictions of winter wheat SPAD values during the booting stage using Vegetation Indices (VIs) from UAV images at five different altitudes (i.e., 20, 40, 60, 80, 100, and 120 m, respectively, using a DJI P4-Multispectral UAV as an example, with a resolution from 1.06 to 6.35 cm/pixel). Additionally, we compare the predictive performance using various predictor variables (VIs, Texture Indices (TIs), Discrete Wavelet Transform (DWT)) individually and in combination. Four machine learning algorithms (Ridge, Random Forest, Support Vector Regression, and Back Propagation Neural Network) are employed. The results demonstrate a comparable prediction performance between using UAV images at 120 m (with a resolution of 6.35 cm/pixel) and using the images at 20 m (with a resolution of 1.06 cm/pixel). This finding significantly improves the efficiency of UAV monitoring since flying UAVs at higher altitudes results in greater coverage, thus reducing the time needed for scouting when using the same heading overlap and side overlap rates. The overall trend in prediction accuracy is as follows: VIs + TIs + DWT > VIs + TIs > VIs + DWT > TIs + DWT > TIs > VIs > DWT. The VIs + TIs + DWT set obtains frequency information (DWT), compensating for the limitations of the VIs + TIs set. This study enhances the effectiveness of using UAVs in agricultural research and practices. [ABSTRACT FROM AUTHOR]

Drought stress is one of the most severe natural disasters in terms of its frequency, length, impact intensity, and associated losses, making it a significant threat to agricultural productivity. Sorghum (Sorghum bicolor), a C4 plant, shows a wide range of morphological, physiological, and biochemical adaptations in response to drought stress, paving the way for it to endure harsh environments. In arid environments, sorghum exhibits enhanced water uptake and reduced dissipation through its morphological activity, allowing it to withstand drought stress. Sorghum exhibits physiological and biochemical resistance to drought, primarily by adjusting its osmotic potential, scavenging reactive oxygen species, and changing the activities of its antioxidant enzymes. In addition, certain sorghum genes exhibit downregulation capabilities in response to drought stress. Therefore, in the current review, we explore drought tolerance in sorghum, encompassing its morphological characteristics and physiological mechanisms and the identification and selection of its functional genes. The use of modern biotechnological and molecular biological approaches to improving sorghum resistance is critical for selecting and breeding drought-tolerant sorghum varieties. [ABSTRACT FROM AUTHOR]

Background: Glutamine synthetase (GS), glutamate synthase (GOGAT), and nitrate reductase (NR) are key enzymes involved in nitrogen assimilation and metabolism in plants. However, the systematic analysis of these gene families lacked reports in soybean (Glycine max (L.) Merr.), one of the most important crops worldwide. Methods: In this study, we performed genome-wide identification and characterization of GS, GOGAT, and NR genes in soybean under abiotic and nitrogen stress conditions. Results: We identified a total of 10 GS genes, six GOGAT genes, and four NR genes in the soybean genome. Phylogenetic analysis revealed the presence of multiple isoforms for each gene family, indicating their functional diversification. The distribution of these genes on soybean chromosomes was uneven, with segmental duplication events contributing to their expansion. Within the nitrogen assimilation genes (NAGs) group, there was uniformity in the exon-intron structure and the presence of conserved motifs in NAGs. Furthermore, analysis of cis-elements in NAG promoters indicated complex regulation of their expression. RT-qPCR analysis of seven soybean NAGs under various abiotic stresses, including nitrogen deficiency, drought-nitrogen, and salinity, revealed distinct regulatory patterns. Most NAGs exhibited up-regulation under nitrogen stress, while diverse expression patterns were observed under salt and drought-nitrogen stress, indicating their crucial role in nitrogen assimilation and abiotic stress tolerance. These findings offer valuable insights into the genomic organization and expression profiles of GS, GOGAT, and NR genes in soybean under nitrogen and abiotic stress conditions. The results have potential applications in the development of stress-resistant soybean varieties through genetic engineering and breeding. [ABSTRACT FROM AUTHOR]

Somatostatin (SST) is a regulatory peptide and acts as an endogenous inhibitory regulator of the secretory and proliferative responses of target cells. SST's actions are mediated by a family of seven transmembrane domain G protein-coupled receptors that comprise five distinct subtypes (SSTR1-5). SSTR5 is one of the major SSTRs in the islets of Langerhans. Homeodomain-containing transcription factor pancreatic and duodenal homeobox-1 (PDX-1) is essential for pancreatic development, β cell differentiation, maintenance of normal β cell functions in adults and tumorigenesis. Recent studies show that SSTR5 acts as a negative regulator for PDX-1 expression and that SSTR5 mediates somatostatin's inhibitory effect on cell proliferation and insulin expression/excretion through down-regulating PDX-1 expression. SSTR5 exerts its inhibitory effect on PDX-1 expression at both the transcriptional level by down-regulating PDX-1 mRNA and the post-translational level by enhancing PDX-1 ubiquitination. Identification of PDX-1 as a transcriptional target for SSTR5 may help in guiding the choice of therapeutic cancer treatments.

Salinity is one of the major constraints to crop production. Rice is a main staple food and is highly sensitive to salinity. This study aimed to elucidate the effects of salt stress on physiological and agronomic traits of rice genotypes with contrasting salt tolerance. Six contrasting rice genotypes (DJWJ, JFX, NSIC, HKN, XD2H and HHZ), including three salt-tolerant and three salt-sensitive rice genotypes, were grown under two different salt concentrations (0 and 100 mmol L−1 NaCl solution). The results showed that growth, physiological and yield-related traits of both salt-sensitive and salt-tolerant rice were significantly affected by salt stress. In general, plant height, tiller number, dry weight and relative growth rate showed 15.7%, 11.2%, 25.2% and 24.6% more reduction in salt-sensitive rice than in salt-tolerant rice, respectively. On the contrary, antioxidant enzyme activity (superoxide dismutase, peroxidase, catalase), osmotic adjustment substances (proline, soluble protein, malondialdehyde (MDA)) and Na+ content were significantly increased under salt stress, and the increase was far higher in salt-tolerant rice except for MDA. Furthermore, grain yield and yield components significantly decreased under salt stress. Overall, the salt-sensitive rice genotypes showed a 15.3% greater reduction in grain yield, 5.1% reduction in spikelets per panicle, 7.4% reduction in grain-filling percentage and 6.1% reduction in grain weight compared to salt-tolerant genotypes under salt stress. However, a modest gap showed a decline in panicles (22.2% vs. 22.8%) and total spikelets (45.4% vs. 42.1%) between salt-sensitive and salt-tolerant rice under salinity conditions. This study revealed that the yield advantage of salt-tolerant rice was partially caused by more biomass accumulation, growth rate, strong antioxidant capacity and osmotic adjustment ability under salt stress, which contributed to more spikelets per panicle, high grain-filling percentage and grain weight. The results of this study could be helpful in understanding the physiological mechanism of contrasting rice genotypes' responses to salt stress and to the breeding of salt-tolerant rice. [ABSTRACT FROM AUTHOR]