Search Results (63)

The germin-like protein (GLP) family plays vital roles for plant growth, stress adaptation, and defense; however, its evolutionary dynamics and functional diversity in halophytes remain poorly characterized. Here, we present the genome-wide analysis of the GLP family in the halophytic forage alkaligrass (Puccinellia tenuiflora), which identified 54 PutGLPs with a significant expansion compared to other plant species. Phylogenetic analysis revealed monocot-specific clustering, with 41.5% of PutGLPs densely localized to chromosome 7, suggesting tandem duplication as a key driver of family expansion. Collinearity analysis confirmed evolutionary conservation with monocot GLPs. Integrated gene structure and motif analysis revealed conserved cupin domains (BoxB and BoxC). Promoter cis-acting elements analysis revealed stress-responsive architectures dominated by ABRE, STRE, and G-box motifs. Tissue-/organ-specific expression profiling identified root- and flower-enriched PutGLPs, implying specialized roles in stress adaptation. Dynamic expression patterns under salt-dominated stresses revealed distinct regulatory pathways governing ionic and alkaline stress responses. Functional characterization of PutGLP37 demonstrated its cell wall localization, dual superoxide dismutase (SOD) and oxalate oxidase (OXO) enzymatic activities, and salt stress tolerance in Escherichia coli, yeast (Saccharomyces cerevisiae INVSc1), and transgenic Arabidopsis. This study provides critical insights into the evolutionary innovation and stress adaptive roles of GLPs in halophytes. Full article

Human induced pluripotent stem cells (iPSCs) offer immense potential as a source for cell therapy in spinal cord injury (SCI) and other diseases. The development of hypoimmunogenic, universal cells that could be transplanted to any recipient without requiring a matching donor could significantly enhance their therapeutic potential and accelerate clinical translation. To create off-the-shelf hypoimmunogenic cells, we used CRISPR-Cas9 to delete B2M (HLA class I) and CIITA (master regulator of HLA class II). Double-knockout (DKO) iPSC-derived neural progenitor cells (NPCs) evaded T-cell-mediated immune rejection in vitro and after grafting into the injured spinal cord of athymic rats and humanized mice. However, loss of HLA class I heightened susceptibility to host natural killer (NK) cell attack, limiting graft survival. To counter this negative effect, we engineered DKO NPCs to overexpress macrophage migration inhibitory factor (MIF), an NK cell checkpoint ligand. MIF expression markedly reduced NK cell-mediated cytotoxicity and improved long-term engraftment and integration of NPCs in the animal models for spinal cord injury. These findings demonstrate that MIF overexpression, combined with concurrent B2M and CIITA deletion, generates hiPSC neural derivatives that escape both T- and NK-cell surveillance. This strategy provides a scalable route to universal donor cells for regenerative therapies in SCI and potentially other disorders. Full article

Herbivorous protistan grazers are ubiquitous and abundant in marine and temperate freshwater environments. However, little is known about the algivorous ciliates and their feeding habits in outdoor mass algal cultures. In this study, we report on one hypotrich ciliate, identified as Sterkiella histriomuscorum, from the outdoor mass culture of Scenedesmus in Arizona, USA. A long-term field survey revealed that this species often occurs in Scenedesmus culture in spring and summer, and can graze very heavily on Scenedesmus cells. By isolating Sterkiella cells and then observing them via light microscopy and electron microscopy, detailed information about the morphology, ultrastructure, excystment process, and feeding characteristics of the ciliate was obtained. Specifically, it seems that S. histriomuscorum has a range of different strategies for excystment, and the sharp change in the ion concentration in the environment around the cyst results in osmotic shock, which likely facilitates the excystment. Feeding experiments revealed that S. histriomuscorum preferred to graze on chlorophytes as well as the diatom Phaeodactylum tricornutum and had no interaction with chrysophytes or cyanobacteria. Molecular phylogenetic analysis based on the SSU rRNA gene sequence indicated that both the genus Sterkiella and the species S. histriomuscorum are non-monophyletic. The information obtained from this study will help advance our understanding of the biodiversity and ecological function of S. histriomuscorum, and will also be very useful in the development of early warning systems and control measures for preventing or treating this contaminant in microalgal mass cultures. Full article

This study investigated the optimal strategies for improving sugar biosynthesis in mango fruits. Randomized block design was used for experimental treatments. The mango cultivar “Renong-1” was sprayed with five green plant growth regulators, including solutions of SBP (sucrose-based polymers, a new highly efficient and eco-friendly plant growth regulator), SPM (sucrose + potassium dihydrogen phosphate + microelement fertilizer), TPM (taurine + potassium dihydrogen phosphate + microelement fertilize), PFA (potassium fulvic acid), and SOP (seaweed oligosaccharide peptide) at different fruit development stages. Indicators, such as soluble solid content, soluble sugar and starch contents, and activities of 11 enzymes associated with sugar metabolism in physiologically mature and in full ripening fruits were evaluated. The results showed that SBP solution diluted 100-fold exerted the strongest effect on the soluble sugar content and sweetness value of “Renong-1” mango fruits. Based on the linear regression analysis, a significant negative correlation was observed between the activity of acid invertase and the perceived sweetness of physiologically mature fruits, while the activities of other enzymes were significantly negatively correlated with the perceived sweetness of full ripening fruits. According to multiple regression (by lars function in R) and other comprehensive analysis, A1B3 (spraying SBP solution one time in the young fruit stage) was selected as the optimal treatment combination for enhancing “Renong-1” mango perceived sweetness, followed by A1B2 (spraying SBP solution for the first time in the young fruit stage and the second time at medium maturity) as the alternative treatment combination. Full article

Light reflected from satellite surfaces is polarized light, which plays a crucial role in space target identification and remote sensing. To deepen our understanding of the polarized reflectance property for satellite material surface, we present the experiments of polarimetric laboratory measurements from two typical satellite materials in the wavelength range of 400–1000 nm by using a goniometer instrument. The bidirectional polarized reflectance factor (BPRF) is used to describe the polarization characteristics of our samples. The polarized spectral reflectance and distribution of BPRF for our datasets are analyzed. Furthermore, five semi-empirical polarized bidirectional reflectance distribution functions (pBRDFs) models for polarized reflectance of typical satellite material surfaces (Preist–Germer model, Maxwell–Beard model, three-component model, Cook–Torrance model, and Kubelka–Munk model) are quantitatively intercompared using the measured BPRFs. The results suggest that the measured BPRFs of our samples are spectrally irrelevant, and the hemispherical distribution of BPRFs is obviously anisotropic. Except for the Preist–Germer model, the other semi-empirical models are in good agreement with the measured BPRF at the selected wavelengths, indicating that we can accurately simulate the polarized reflectance property of the satellite surface by using the existing polarimetric models. The Kubelka–Munk pBRDF model best fits the silver polyimide film and white coating surfaces with RMSE equal to 3.25% and 2.03%, and the correlation coefficient is 0.994 and 0.984, respectively. This study can be applied to provide an accurate pBRDF model for space object scene simulation and has great potential for polarization remote sensing. Full article

Mango (Mangifera indica L.) (2n = 40) is an important perennial fruit tree in tropical and subtropical regions. The lack of information on genetic diversity at the molecular level hinders efforts in mango genetic improvement and molecular marker-assisted breeding. In this study, a genome-wide screening was conducted to develop simple sequence repeat (SSR) markers using the Alphonso reference genome. A total of 187 SSR primer pairs were designed based on SSR loci with consisting of tri- to hexa-nucleotide motifs, and 34 highly polymorphic primer pairs were selected to analyze the diversity of 231 germplasm resources. These primers amplified 219 alleles (Na) across 231 accessions, averaging of 6.441 alleles for per marker. The polymorphic information content (PIC) values ranged from 0.509 to 0.757 with a mean of 0.620. Genetic diversity varied among populations, with Southeast Asia showing the highest diversity, and Australia the lowest. Population structure analysis, divided the accessions into two groups, Group I (India) and Group II (Southeast Asia), containing 104 and 127 accessions, respectively, consistent with results from phylogenetic analysis and principal component analysis (PCA). Sixteen SSR primer pairs capable of distinguishing all tested accessions, were selected as core primers for constructing fingerprints of 229 mango accessions. These findings offer valuable resources for enhancing the utilization of mango germplasm in breeding programs. Full article

Calcium silicate hydrate (CSH) gel is an important hydration product of cement, significantly influencing the coagulation and hardening processes, as well as the mechanical properties, volume stability, and durability of cement. Moreover, it plays a crucial role in the adsorption of harmful ions. In this study, CSH gel was synthesized through the precipitation of calcium acetate and sodium silicate and was subsequently used to adsorb chloride ions. The results indicated that when the calcium-to-silicon ratio was 1.2, the CSH gel exhibited excellent adsorption performance for chloride ions introduced via CaCl₂ and NaCl, with adsorption capacities of 17.45 mg·g⁻¹ and 8.06 mg·g⁻¹, respectively. The adsorption of chloride ions in CSH gel primarily occurs due to the physical adsorption of chloride ions on the surface and within the internal pores of the CSH gel, accompanied by a displacement reaction between hydroxide ion and chloride ions. Full article

Anthocyanins are important secondary metabolites contributing to the red coloration of fruits, the biosynthesis of which is significantly affected by light. Glutathione S-transferases (GSTs) play critical roles in the transport of anthocyanins from the cytosol to the vacuole. Despite their importance, GST genes in mango have not been extensively characterized. In this study, 62 mango GST genes were identified and further divided into six subfamilies. MiGSTs displayed high similarity in their exon/intron structure and motif and domain composition within the same subfamilies. The mango genome harbored eleven pairs of segmental gene duplications and ten sets of tandemly duplicated genes. Orthologous analysis identified twenty-nine, seven, thirty-four, and nineteen pairs of orthologous genes among mango MiGST genes and their counterparts in Arabidopsis, rice, citrus, and bayberry, respectively. Tissue-specific expression profiling highlighted tissue-specific expression patterns for MiGST genes. RNA-seq and qPCR analyses revealed elevated expression levels of seven MiGSTs including MiDHAR1, MiGSTU7, MiGSTU13, MiGSTU21, MiGSTF3, MiGSTF8, and MiGSTF9 during light-induced anthocyanin accumulation in mango. This study establishes a comprehensive genetic framework of MiGSTs in mango fruit and their potential roles in regulating anthocyanin accumulation, which is helpful in developing GST-derived molecular markers and speeding up the process of breeding new red-colored mango cultivars. Full article

Change detection based on optical image processing plays a crucial role in the field of damage assessment. Although existing damage scene change detection methods have achieved some good results, they are faced with challenges, such as low accuracy and slow speed in optical image change detection. To solve these problems, an image change detection approach that combines infrared polarization imaging with a fast principal component analysis network (Fast-PCANet) is proposed. Firstly, the acquired infrared polarization images are analyzed, and pixel image blocks are extracted and filtered to obtain the candidate change points. Then, the Fast-PCANet network framework is established, and the candidate pixel image blocks are sent to the network to detect the change pixel points. Finally, the false-detection points predicted by the Fast-PCANet are further corrected by region filling and filtering to obtain the final binary change map of the damage scene. Comparisons with typical PCANet-based change detection algorithms are made on a dataset of infrared-polarized images. The experimental results show that the proposed Fast-PCANet method improves the PCC and the Kappa coefficient of infrared polarization images over infrared intensity images by 6.77% and 13.67%, respectively. Meanwhile, the inference speed can be more than seven times faster. The results verify that the proposed approach is effective and efficient for the change detection task with infrared polarization imaging. The study can be applied to the damage assessment field and has great potential for object recognition, material classification, and polarization remote sensing. Full article

This research addresses the critical issue of major fishing vessel accidents, which traditionally suffer from a lack of focused analysis due to their rarity and the subjective nature of their classification. We propose an innovative methodology of Peaks Over Threshold to overcome subjectivity in accident classification. This approach ensures a more representative and accurate analysis of major accidents, distinguishing them from more common, less severe incidents. Employing a Bayesian network model, we further explore the most influential factors contributing to these major accidents. The key innovation lies in our novel approach to data handling and analysis, enabling us to uncover hidden patterns and causal relationships that traditional methods often overlook. The results show that the approach proposed in this study can effectively capture the key factors of major fishing vessel accidents. This study identifies accident type, vessel-related factors, and accident location as the key influential factors leading to major accidents. The findings from our research are intended to inform sustainable fisheries management practices, promoting interventions that aim to decrease the occurrence and impact of severe maritime accidents while balancing economic, safety, and sustainable development considerations. Full article

Data transmission is one of the critical factors in the future of the Internet of Things (IoT). The techniques of a reconfigurable intelligent surface (RIS) and backscatter communication (BackCom) are in need of a solution of realizing low-power sustainable transmission, which shows great potential in wireless communication. Hence, this paper introduces an RIS-based BackCom system, where the RIS receives energy from a base station (BS) and sends information by backscattering the signals from the BS. To maximize the sum rate of all IoT devices (IoTDs), we jointly optimized the time allocation, the RIS-reflecting phase shifts and the transmit power of the BS by exploiting an alternative optimization algorithm. The simulation results illustrate the effectiveness and the feasibility of the proposed wireless communication scheme and the proposed algorithm in IoT networks. Full article

Quinoa (Chenopodium quinoa Willd.) is gaining recognition as a pseudocereal due to its nutritional attributes and adaptability to challenging conditions and marginal soils. However, understanding the optimal fertilization for quinoa growth remains a challenge. This study investigates the effects of nitrogen fertilization (0, 90, 120, and 150 kg using urea) on quinoa phenology, growth, and photosynthesis in the Loess Plateau region of China, a critical area facing soil erosion and ecological degradation. The results showed that nitrogen fertilization significantly influenced quinoa phenology, prompting early flowering and shorter growth at an optimum rate of 120 kg ha⁻¹. Nitrogen application enhanced growth traits such as plant height, stem diameter, and chlorophyll content, particularly at the heading and flowering stages. Photosynthesis-related parameters, including net photosynthesis rate, transpiration rate, stomatal conductance, and intercellular CO₂ concentration, were affected by nitrogen application, with higher values observed at 120 kg ha⁻¹. Non-photochemical quenching was significantly increased by nitrogen application, indicating the efficient dissipation of excess energy. The study demonstrated a positive correlation between grain yield and growth traits, photosynthesis-related traits, and chlorophyll content. In conclusion, quinoa yield could be significantly improved at the Loess Plateau region under rainfed conditions by an optimal nitrogen fertilizer rate of 120 kg ha⁻¹, which reduces the growth duration while increasing photosynthesis traits. Full article

The recent dominance of Adelphocoris suturalis Jakovlev as the primary cotton field pest in Bt-cotton-cultivated areas has generated significant interest in cotton pest control research. This study addresses the limited understanding of cotton defense mechanisms triggered by A. suturalis feeding. Utilizing LC-QTOF-MS, we analyzed cotton metabolomic changes induced by A. suturalis, and identified 496 differential positive ions (374 upregulated, 122 downregulated) across 11 categories, such as terpenoids, alkaloids, phenylpropanoids, flavonoids, isoflavones, etc. Subsequent iTRAQ-LC-MS/MS analysis of the cotton proteome revealed 1569 differential proteins enriched in 35 metabolic pathways. Integrated metabolome and proteome analysis highlighted significant upregulation of 17 (89%) proteases in the α-linolenic acid (ALA) metabolism pathway, concomitant with a significant increase in 14 (88%) associated metabolites. Conversely, 19 (73%) proteases in the fructose and mannose biosynthesis pathway were downregulated, with 7 (27%) upregulated proteases corresponding to the downregulation of 8 pathway-associated metabolites. Expression analysis of key regulators in the ALA pathway, including allene oxidase synthase (AOS), phospholipase A (PLA), allene oxidative cyclase (AOC), and 12-oxophytodienoate reductase3 (OPR3), demonstrated significant responses to A. suturalis feeding. Finally, this study pioneers the exploration of molecular mechanisms in the plant–insect relationship, thereby offering insights into potential novel control strategies against this cotton pest. Full article

Stalk rot is a prevalent disease of maize (Zea mays L.) that severely affects maize yield and quality worldwide. The ascomycete fungus Fusarium spp. is the most common pathogen of maize stalk rot. At present, the molecular mechanism of Fusarium proliferation during the maize stalk infection that causes maize stalk rot has rarely been reported. In this study, we investigated the response of maize to F. proliferatum infestation by analyzing the phenotypic, transcriptomic, and metabolomic data of inbred lines ZC17 (resistant) and CH72 (susceptible) with different levels of resistance to stalk rot. Physiological and phenotypic results showed that the infection CH72 was significantly more severe than ZC17 after inoculation. Transcriptome analysis showed that after inoculation, the number of differentially expressed genes (DEGs) was higher in CH72 than in ZC17. Nearly half of these DEGs showed the same expression trend in the two inbred lines. Functional annotation and enrichment analyses indicated that the major pathways enriched for DEGs and DEMs included the biosynthesis of plant secondary metabolites, phenylalanine metabolism, biosynthesis of plant hormones, and plant–pathogen interactions. The comprehensive analysis of transcriptome and metabolome data indicated that phenylalanine metabolism and the phenylalanine, tyrosine, and tryptophan biosynthesis pathways played a crucial role in maize resistance to F. proliferatum infection. In addition, a transcription factor (TF) analysis of the DEGs showed that several TF families, including MYB, bHLH, NAC, and WRKY, were significantly activated after inoculation, suggesting that these TFs play important roles in the molecular regulatory network of maize disease resistance. The findings of this study provide valuable insights into the molecular basis of the response of maize to Fusarium proliferatum infection and highlight the importance of combining multiple approaches, such as phenotyping, transcriptomics, and metabolomics, to gain a comprehensive understanding of plant–pathogen interactions. Full article

The Ångström–Prescott formula is commonly used in climatological calculation methods of solar radiation simulation. Aiming at the characteristics of a vast area, few meteorological stations, and uneven distribution in the tropical regions of China, in order to obtain the optimal parameters of the global solar radiation calculation model, this study proposes a suitable monthly global solar radiation model based on the single-station approach and the between-groups linkage of the A–P model, which utilizes monthly measured meteorological data from 80 meteorological stations spanning the period from 1996 to 2016 in the tropical zone of China, considering the similarity in changes of monthly sunshine percentage between stations. The applicability and accuracy of the correction parameters (a and b coefficients) were tested and evaluated, and then the modified parameters were extended to conventional meteorological stations through Thiessen polygons. Finally, the spatial distribution of solar radiation in the tropical region of China was simulated by kriging, IDW, and spline interpolation techniques. The results show the following: (1) The single-station model exhibited the highest accuracy in simulating the average annual global solar radiation, followed by the model based on the between-groups linkage. After optimizing the a and b coefficients, the simulation accuracy of the average annual global solar radiation increased by 5.3%, 8.1%, and 4.4% for the whole year, dry season, and wet season, respectively. (2) Through cross-validation, the most suitable spatial interpolation methods for the whole year, dry season, and wet season in the tropical zone of China were IDW, Kriging, and Spline, respectively. This research has positive implications for improving the accuracy of solar radiation prediction and guiding regional agricultural production. Full article