Search

Abstract The Ideal Plant Architecture 1 (IPA1) transcription factor promotes rice yield and immunity through phosphorylation at its amino acid residue Ser163 as a switch. Although phosphorylated IPA1 mimic, IPA1(S163D), directly targets the promoter of immune response gene WRKY45, it cannot activate its expression. Here, we identified a co-activator of IPA1(S163D), a RING-finger E3 ligase IPA1 interactor 7 (IPI7), which fine-tunes the transcriptional activity of IPA1 to timely promote plant immunity and simultaneously maintain growth for yield. IPI7 interacts with IPA1 and promotes K29-polyubiquitination of IPA1 in vitro and in vivo. However, the stability of IPA1 protein is not affected by IPI7-mediated ubiquitination. The IPI7-promoted K29-polyubiquitination of IPA1 is induced by Magnaporthe oryzae infection and required for phosphorylated IPA1 to transactivate WRKY45 expression for immune response but not for plain IPA1 to transactivate DENSE AND ERECT PANICLES 1 (DEP1) expression for panicle development. IPI7 knockout impairs IPA1-mediated immunity but not yield. Our study reveals that plants utilize non-proteolytic K29-ubiquitination as a response to pathogen infection to fine-tune IPA1 transactivation activity for promoting immunity.

Urban vegetation in China has changed substantially in recent decades due to rapid urbanization and dramatic climate change. Nevertheless, the spatial differentiation of greenness among major cities of China and its evolution process and drivers are still poorly understood. This study examined the spatial patterns of vegetation greenness across 289 cities in China in 2000, 2005, 2010, 2015, and 2018 by using spatial autocorrelation analysis on the Normalized Difference Vegetation Index (NDVI); then, the influencing factors were analyzed by using the optimal parameters-based geographical detector (OPGD) model and 18 natural and anthropogenic indicators. The findings demonstrated a noticeable rise in the overall greenness of the selected cities during 2000–2018. The cities in northwest China and east China exhibited the rapidest and slowest greening, respectively, among the six sub-regions. A significant positive spatial correlation was detected between the greenness of the 289 cities in different periods, but the correlation strength weakened over time. The hot and very hot spots in southern and eastern China gradually shifted to the southwest. While the spatial pattern of urban greenness in China is primarily influenced by wind speed (WS) and precipitation (PRE), the interaction between PRE and gross domestic product (GDP) has the highest explanatory power. The explanatory power of most natural factors decreased and, conversely, the influence of anthropogenic factors generally increased. These findings emphasize the variations in the influence strength of multiple factors on urban greenness pattern, which should be taken into account to understand and adapt to the changing urban ecosystem.

Abstract Background The effects of blue light on photosynthetic organs have been studied. However, its effects on non-photosynthetic organs, in particular, on the early stages of rice caryopsis development, are unclear. Thus, we aimed to determine the metabolic characteristics of caryopsis development under blue light to improve the metabolic quality of crop kernels. Results We conducted a multi-omics analysis of each of the three periods from the beginning of cellular differentiation to the end of morphogenesis in post-pollination seeds of a japonica rice variety to explore the effect of blue light on metabolic levels during these metabolic changes and its genetic basis. It was found that blue light caused a gradual decrease in auxin content, a significant increase in the accumulation of JA and flavonoids, and a downregulation of the expression of many starch-related genes and proteins, leads to reduced starch synthesis and smaller starch granules. In addition, the gene co-expression network identified three transcription factors that may regulate starch and two that may regulate flavonoids. Conclusions It was found through multi-omics testing that hormones such as jasmonic acid and auxins, and metabolites including alkaloids, flavonoids, lipids, organic acids, phenolic acids, and terpenoids altered significantly. Transcriptome and proteome analyses showed that blue light affected the seed nutrient repository activity. Specifically, starch- and gluten-related genes and proteins were significantly downregulated. Co- and WGCNA analyses identified several transcription factors that were regulated under blue light and identified key regulators of starch. Our study provides an understanding of the effects of blue light on post-flowering development in Gramineae and provides a framework for blue light-induced synthesis of secondary metabolites. Graphical Abstract

Abstract Background As an emerging food crop with high nutritional value, quinoa has been favored by consumers in recent years; however, flooding, as an abiotic stress, seriously affects its growth and development. Currently, reports on the molecular mechanisms related to quinoa waterlogging stress responses are lacking; accordingly, the core genes related to these processes were explored via Weighted Gene Co-expression Network Analysis (WGCNA). Results Based on the transcriptome data, WGCNA was used to construct a co-expression network of weighted genes associated with flooding resistance-associated physiological traits and metabolites. Here, 16 closely related co-expression modules were obtained, and 10 core genes with the highest association with the target traits were mined from the two modules. Functional annotations revealed the biological processes and metabolic pathways involved in waterlogging stress, and four candidates related to flooding resistance, specifically AP2/ERF, MYB, bHLH, and WRKY-family TFs, were also identified. Conclusions These results provide clues to the identification of core genes for quinoa underlying quinoa waterlogging stress responses. This could ultimately provide a theoretical foundation for breeding new quinoa varieties with flooding tolerance.

Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China. In this study, we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives. The results from Local Indicators of Spatial Association (LISA) uncover notable spatial disparities in aging population rates, with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland. The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures, but negatively correlated with economic development, social consumption, and medical facilities. From a local perspective, a Geographically Weighted (GW) correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors. The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging, but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.

Abstract Stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most important diseases of wheat worldwide. Identification of new and elite Pst-resistance loci or genes has the potential to enhance overall resistance to this pathogen. Here, we conducted an integrated genome-wide association study (GWAS) and transcriptomic analysis to screen for loci associated with resistance to stripe rust in 335 accessions from Yunnan, including 311 landraces and 24 cultivars. Based on the environmental phenotype, we identified 113 protein kinases significantly associated with Pst resistance using mixed linear model (MLM) and generalized linear model (GLM) models. Transcriptomic analysis revealed that 52 of 113 protein kinases identified by GWAS were up and down regulated in response to Pst infection. Among these genes, a total of 15 receptor kinase genes were identified associated with Pst resistance. 11 candidate genes were newly discovered in Yunnan wheat germplasm. Our results revealed that resistance alleles to stripe rust were accumulated in Yunnan wheat germplasm, implying direct or indirect selection for improving stripe rust resistance in elite wheat breeding programs.

Ethnopharmacological relevance: Aster tataricus L.f., an extensively used herb in traditional Chinese medicine for more than 2000 years, is known as “Zi wan” or “Fan huncao”. Its dried root and rhizome hold great promise in the treatment of cough, asthma, tumor, inflammation, etc.Aim of the study: This literature review summarizes the morphology characteristics, ethnopharmacological use, phytochemical properties, pharmacological effects, and potential applications of Aster tataricus. Furthermore, this review will discuss the future research trends and development prospects of this plant. Materials and methods: Using “Aster tataricus L.f.”, “Traditional medicinal usage”, “Phytochemistry”, “Pharmacological effects” as the keywords and gathered relevant data on Aster tataricus L.f. using electronic databases (Elsevier, PubMed, ACS, CNKI, Google Scholar, Baidu Scholar, Web of Science), relevant books, and classic literature about Chinese herb. Result: A total of 186 compounds have been isolated and identified from Aster tataricus, including terpenes, organic acids, peptides, and flavonoids. And Aster tataricus has been widely used as a natural cough suppressant and has anti-oxidative, anti-inflammatory, anti-depressive, and anti-tumor effects. In addition, Aster tataricus has also been reported to have damaging effects on the liver as well as other toxicities were discussed in this review. Conclusions: Aster tataricus is an ancient herbal medicine with a broad spectrum of pharmaco logical activities that has been used for thousands of years in China, and has shown remarkable effectiveness in the treatment of various diseases, especially cough, asthma, inflammation. Although its rich chemical constituents have various pharmacological activities, the underlying mechanisms, as well as its toxicity and safety, remains unclear and warrant further investigation.

Background: The aim of this study was to explore the association between lactate/albumin ratio and the prognosis of sepsis patients. Methods: A computerized search was performed in Pubmed, EMbase, Ovid, Medline, and Google Scholar to collate relevant studies. The results were compared using standardized mean differences (SMD)/odds ratio (OR) and 95% confidence intervals (CI). Prospective and retrospective cohort studies were both included in this study. Results: A total of nine studies involving 3039 participants were included. Pooled analysis revealed that survivors had substantially lower lactate/albumin ratio than non-survivors (SMD=-2.02, 95% CI: -2.76 to -1.28, I2=97.4%). Further, our results also indicated that elevated lactate/albumin ratio is an independent risk factor for mortality (OR=2.16, 95% CI: 1.58 to 2.95, I2=76.2%) and multiple organ dysfunction syndrome (MODS) (OR=3.41, 95% CI: 1.78 to 6.50, I2=0.0%) in septic patients. Moreover, according to the area under curve (AUC) results, the lactate/albumin ratio also presented good discriminatory power to predict mortality (AUC=0.75, 95% CI: 0.68 to 0.84, I2=92.9%) and MODS (AUC=0.78, 95% CI: 0.68 to 0.91, I2= 65.1%) in septic patients. Begg's and Egger's tests suggested no publication bias in the included studies. Conclusion: Our results highlighted that the lactate/albumin ratio is an important prognostic factor for MODS and mortality in sepsis patients, having good capabilities in identifying MODS and mortality. Elevated lactate/albumin ratio is an independent risk factor for mortality and multiple organ dysfunction syndrome (MODS) in septic patients. The lactate/albumin ratio also presented good discriminatory power to predict mortality and MODS in septic patients.

In graph modeling, scarcity of labeled data is a challenging issue. To address this issue, state-of-the-art graph models learn the representation of graph data via contrastive learning. Those models usually use data augmentation techniques to generate positive pairs for contrastive learning, which aims to maximize the similarity of positive data pairs while minimizing the similarity of negative data pairs. However, samples with the same labels may be separately mapped in the feature space. To solve this problem, we introduce a novel model called Clustering Contrastive Graph Neural Network (CC-GNN), which develops a new kind of grouped contrastive learning that maximizes the similarity of positive data groups and minimizes the similarity of negative groups. That is, contrastive learning is defined on a group level rather than on an instant level. We assert that parameters learned by this kind of contrastive learning will lead to better performance of graph neural networks for downstream classification tasks. We combined the clustering contrastive learning technique with three baseline GNN models for graph classification. We found that the performance of these models was significantly improved, which strongly supports our assertion. We also testified the models for node classification on three popular citation networks. Finally, we conducted an ablation study to analyze how the clustering contrastive learning influence the performance of a graph model.

Online teacher professional development is widely regarded as a promising way to improve the quality of teachers and the effect of teaching. Micro-learning, which has the potential to fit the learner's personalized learning needs through a variety of small educational resources and flexible learning opportunities, could be an efficient way for the online teacher professional development. However, the scattered knowledge points and fragmented learning time in micro-learning may limit the learner's comprehension and the construction of knowledge. In this study, a knowledge map-based online micro-learning system was developed to solve this problem. To verify the effectiveness of the proposed system, a quasi-experiment was conducted during a three-week online course for teachers' professional development. A total of 42 in-service Mandarin teachers participated in the course, and were divided into two equal groups. An experimental group learned by using a knowledge map tool while a control group learned the same contents in the form of the conventional list type. The results indicate that the experimental group outperformed the control group in terms of learning engagement, and showed a clearer and more complete knowledge structure. Furthermore, micro-learning coupled with knowledge maps was found to improve the teachers' learning performance.

The antibiotics are generally regarded as the first choice approach to treat dairy mastitis, targeting the public health problems associated with the food safety and the emergence of antibioticresistant bacteria. The objective of the study was to evaluate the antibacterial efficacy of ursolic acid (UA) when used to treat Staphylococcus aureus and other isolates associated with bovine mastitis and to clarify the mechanistic basis for these effects. The bacteriostatic properties of UA extracted from Rosmarinus officinalis L. at four different purity levels were assessed by calculating minimum inhibitory concentration (MIC) values, while the synergistic effects of combining 98% UA with antibiotics were evaluated by measuring the fractional inhibitory concentration index (FICI). Changes in biofilm formation and the growth curves of the clinical isolates were assessed to clarify the bacteriostatic effect of UA. Furthermore, the cell wall integrity, protein synthesis, and reactive oxygen species (ROS) production were assessed to determine the antibacterial mechanism of UA treatment. Ultimately, UA was revealed to exhibit robust activity against Gram-positive bacteria including S. aureus (ATCC 25923), Streptococcus dysgalactiae (ATCC27957), Streptococcus agalactiae (ATCC13813), Enterococcus faecalis (ATCC29212), and Streptococcus mutans (ATCC25175). However, it did not affect Escherichia coli (ATCC 25922). The MIC values of UA preparations that were 98, 50, 30, and 10% pure against S. aureus were 39, 312, 625, and 625 μg/mL, respectively, whereas the corresponding MIC for E. coli was >5,000 μg/mL. The minimum bactericidal concentrations of 98% UA when used to treat three clinical S. aureus isolates (S4, S5, and S6) were 78, 78, and 156 μg/mL, respectively. Levels of biofilm formation for clinical S. aureus isolates decreased with increasing 98% UA concentrations. Above the MIC dose, UA treatment resulted in the dissolution of bacterial cell walls and membranes, with cells becoming irregularly shaped and exhibiting markedly impaired intracellular protein synthesis. S. aureus treated with 98% UA was able to rapidly promote intracellular ROS biogenesis. Together, these data highlight the promising utility of UA as a compound that can be used together with other antibiotics for the treatment of infections caused by S. aureus.

Abstract Background Although the concept of declined immune function associated with cancer has been accepted extensively, real-world clinical studies focusing on analysis of the peripheral blood immune changes underlying ageing, immunity and cancer are scarce. Methods In this case-control study, we retrospectively analysed 1375 cancer patients and enrolled 275 age and gender matched healthy individuals. Flow cytometry was conducted to assess the immune changes. Further analysis was examined by SPSS 17.0 and GraphPad Prism 9 software. Results Cancer patients showed obviously decreased CD3+ T, CD3+CD4+ Th, CD3+CD8+ CTL, CD19+ B, CD16+CD56+ NK cell counts and lower percentage of PD-1 (programmed cell death protein-1, PD-1) positive cells than healthy control (P

In order to meet the increasing requirements of speed and distance, an advanced digital signal processing (DSP) algorithm is preferred without changing the system structure in intensity modulation and the direct detection (IM/DD) system. As the transmission distance increases, the power fading induced by dispersion must be mitigated. In addition, linear and nonlinear inter symbol interference (ISI) introduced by bandwidth limitation and device imperfections becomes an obstacle to achieving higher capacity. The Gerchberg–Saxton (GS) algorithm was recently used to compensate for dispersion. In this paper, GS-based pre- and post-compensation schemes in the IM/DD system with nonlinearity were investigated. We investigated and compared the performance of the GS-based pre- and post-compensation algorithm in a 28 GB aud four-level pulse amplitude modulation (PAM-4) transmission over 40 km standard single-mode fiber (SSMF). The bit error rate (BER) achieved a threshold of 3.8 × 10−3 using look-up-table (LUT), FFE, and the GS-based pre-compensation algorithm without iterations. Turning to the GS-based post-compensation scheme, 80 iterations are needed. However, the demand for FFE is reduced. The algorithm selection depends on the tolerance of the transmitter or receiver complexity in specific scenarios. The joint LUT and GS-based pre-compensation algorithm may be a preferable approach in scenarios where a low-complexity receiver is desired.

Settlement prediction based on monitoring data holds significant importance for engineering maintenance of seawalls. In practical engineering, the volume of the collected monitoring data is often limited due to the restrictions of devices and engineering budgets. Previous studies have applied the fractional-order grey model to time series prediction under the situation of limited data volume. However, the performance of the fractional-order grey model is easily affected by the inappropriate settings of fractional order. Also, the model cannot make dynamic predictions due to the characteristic of fixed step size. To solve the above problems, in this paper, the genetic algorithm with enhanced search capabilities was employed to solve the premature convergence problem. Additionally, to solve the problem of the fractional-order grey model associated with fixed step size, the real-time tracing algorithm was introduced to conduct equal-dimensionally recursive calculation. The proposed model was validated using monitoring data of four monitoring points at Haiyan seawall in Zhejiang province, China. The prediction performance of the proposed model was then compared with those of the fractional-order GM(1,1), integer-order GM(1,1), and fractal theory model. Results indicate that the proposed model significantly improves the prediction performance compared to other models.

The use of the subharmonic signal from microbubbles exposed to ultrasound is a promising safe and cost-effective approach for the non-invasive measurement of blood pressure. Achieving a high sensitivity of the subharmonic amplitude to the ambient overpressure is crucial for clinical applications. However, currently used microbubbles have a wide size distribution and diverse shell properties. This causes uncertainty in the response of the subharmonic amplitude to changes in ambient pressure, which limits the sensitivity. The aim of this study was to use monodisperse microbubbles to improve the sensitivity of subharmonic-based pressure measurements. With the same shell materials and gas core, we used a flow-focusing microfluidic chip and a mechanical agitation method to fabricate monodisperse (∼2.45-µm mean radius and 4.7 % polydisperse index) and polydisperse microbubbles (∼1.51-µm mean radius and 48.4 % polydisperse index), respectively. We varied the ultrasound parameters (i.e., the frequency, peak negative pressure (PNP) and pulse length), and found that there was an optimal excitation frequency (2.8 MHz) for achieving maximal subharmonic emission for monodisperse microbubbles, but not for polydisperse microbubbles. Three distinct regimes (occurrence, growth, and saturation) were identified in the response of the subharmonic amplitude to increasing PNP for both monodisperse and polydisperse microbubbles. For the polydisperse microbubbles, the subharmonic amplitude decreased either monotonically or non-monotonically with ambient overpressure, depending on the PNP. By contrast, for the monodisperse microbubbles, there was only a monotonic decrease at all PNPs. The maximum sensitivity (1.18 dB/kPa, R2 = 0.97) of the subharmonic amplitude to ambient overpressure for the monodisperse microbubbles was ∼6.5 times higher than that for the polydisperse microbubbles (0.18 dB/kPa, R2 = 0.88). These results show that monodisperse microbubbles can achieve a more consistent response of the subharmonic signal to changes in ambient overpressure and greatly improve the measurement sensitivity.

This study investigates the impact of oil market uncertainty on the volatility of Chinese sector indexes. We utilize commonly used realized volatility of WTI and Brent oil price along with the CBOE crude oil volatility index (OVX) to embody the oil market uncertainty. Based on the sample span from Mar 16, 2011 to Dec 31, 2019, this study utilizes vector autoregression (VAR) model to derive the impacts of the three different uncertainty indicators on Chinese stock volatilities. The empirical results show, for all sectors, the impact of OVX on sectors volatilities are more economically and statistically significant than that of realized volatility of both WTI and Brent oil prices, especially after the Chinese refined oil pricing reform of March 27, 2013. That implies OVX is more informative than traditional WTI and Brent oil prices with respect to volatility spillover from oil market to Chinese stock market. This study could provide some important implications for the participants in Chinese stock market.

Abstract Background Quinoa is a highly nutritious and novel crop that is resistant to various abiotic stresses. However, its growth and development is restricted due to its limited utilization of soil phosphorus. Studies on the levels of phosphorus in quinoa seedlings are limited; therefore, we analyzed transcriptome data from quinoa seedlings treated with different concentrations of phosphorus. Results To identify core genes involved in responding to various phosphorus levels, the weighted gene co-expression network analysis method was applied. From the 12,085 expressed genes, an analysis of the gene co-expression network was done. dividing the expressed genes into a total of twenty-five different modules out of which two modules were strongly correlated with phosphorus levels. Subsequently we identified five core genes that correlated strongly either positively or negatively with the phosphorus levels. Gene ontology and assessments of the Kyoto Encyclopedia of Genes and Genomes have uncovered important biological processes and metabolic pathways that are involved in the phosphorus level response. Conclusions We discovered crucial new core genes that encode proteins from various transcription factor families, such as MYB, WRKY, and ERF, which are crucial for abiotic stress resistance. This new library of candidate genes associated with the phosphorus level responses in quinoa seedlings will help in breeding varieties that are tolerant to phosphorus levels.

Quinoa is a nutritious crop that is tolerant to extreme environmental conditions; however, low-temperature stress can affect quinoa growth, development, and quality. Considering the lack of molecular research on quinoa seedlings under low-temperature stress, we utilized a Weighted Gene Co-Expression Network Analysis to construct weighted gene co-expression networks associated with physiological indices and metabolites related to low-temperature stress resistance based on transcriptomic data. We screened 11 co-expression modules closely related to low-temperature stress resistance and selected 12 core genes from the two modules that showed the highest associations with the target traits. Following the functional annotation of these genes to determine the key biological processes and metabolic pathways involved in low-temperature stress, we identified four important transcription factors involved in resistance to low-temperature stress: gene-LOC110731664, gene-LOC110736639, gene-LOC110684437, and gene-LOC110720903. These results provide insights into the molecular genetic mechanism of quinoa under low-temperature stress and can be used to breed lines with tolerance to low-temperature stress.

Rice blast, caused by the fungus Magnaporthe oryzae, and brown planthopper (BPH) infestation are two of the most destructive problems of rice production in China. The development of multi-resistant varieties is widely recognized as the most efficient and environmentally friendly approach to controlling crop diseases and pests. Functional molecular markers (FMMs) have been developed from functional variants in the genic region associated with trait variation, greatly enhancing the efficiency of identifying and pyramiding valuable genes in crop breeding. In this study, two FMMs and a multiplex PCR amplification system were developed for two major broad-spectrum BPH resistance genes, Bph6 and Bph9. With the assistance of FMMs in the multi-resistant rice restorer-line development pipeline, two lines (Huahui7713 and Huahui3006) with blast and BPH resistance were developed by pyramiding three resistance genes Pigm, Bph6 and Bph9. Two new hybrid rice varieties, Weiliangyou7713 and Xuanliangyou3006, derived from Huahui7713 and Huahui3006, have been developed and commercialized in China. Weiliangyou7713 and Xuanliangyou3006 exhibit enhanced resistance to both blast and BPH, while maintaining optimal yield and grain quality. The adoption of Weiliangyou7713 continues to expand, now being cultivated on a large scale, which is promising for its future role in reducing the dependence on chemical fungicides and pesticides in rice production. This suggests that the implementation of Huahui7713 and Huahui3006 in targeted breeding programs could be highly beneficial for developing rice varieties with strong resistance to blast and BPH.

Abstract As a member of Xenes family, germanene has excellent nonlinear saturable absorption characteristics. In this work, we prepared germanene nanosheets by liquid phase exfoliation and measured their saturation intensity as 0.6 GW/cm2 with a modulation depth of 8%. Then, conventional solitons with a pulse width of 946 fs and high-energy noise-like pulses with a pulse width of 784 fs were obtained by using germanene nanosheet as a saturable absorber for a mode-locked Erbium-doped fiber laser. The characteristics of the two types of pulses were investigated experimentally. The results reveal that germanene has great potential for modulation devices in ultrafast lasers and can be used as a material for creation of excellent nonlinear optical devices to explore richer applications in ultrafast photonics. Graphical Abstract

Abstract Background Quinoa (Chenopodium quinoa Willd.) originates in high altitude areas, such as the Andes, and has some inherent characteristics of cold, drought, and salinity tolerance, but is sensitive to high temperature. Results To gain insight into the response mechanism of quinoa to high temperature stress, we conducted an extensive targeted metabolomic study of two cultivars, Dianli-3101 and Dianli-3051, along with a combined transcriptome analysis. A total of 794 metabolites and 54,200 genes were detected, in which the genes related to photosynthesis were found down-regulated at high temperatures, and two metabolites, lipids and flavonoids, showed the largest changes in differential accumulation. Further analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and transcription factors revealed that quinoa inhibits photosynthesis at high temperatures, and the possible strategies being used for high temperature stress management are regulation of heat stress transcription factors (HSFs) to obtain heat tolerance, and regulation of purine metabolism to enhance stress signals for rapid response to high temperature stress. The tolerant genotype could have an enhanced response through lower purine levels. The induction of the stress response could be mediated by HSF transcription factors. The results of this study may provide theoretical references for understanding the response mechanism of quinoa to high temperature stress, and for screening potential high temperature tolerant target genes and high temperature tolerant strains. Conclusions These findings reveal the regulation of the transcription factor family HSF and the purinergic pathway in response to high temperature stress to improve quinoa varieties with high temperature tolerance.

The microwave treatment is commonly applied to flaxseed to release nutrients, inactivate enzymes, remove cyanogens, and intensify flavors. The current study aimed to explore the influences of microwave exposure on the antioxidant and interfacial properties of flaxseed protein isolates (FPI), focusing on the altering composition and molecular structure. The results showed that after microwave exposure (700 W, 1–5 min), more compact assembly of storage proteins and subsequent permeation by membrane fragments of oil bodies occurred for cold-pressing flaxseed flours. Moreover, the particle sizes of FPI was progressively reduced with the decrement ranged from 37.84 to 60.66% (P

Abstract Thiosulfate oxidation by microbes has a major impact on global sulfur cycling. Here, we provide evidence that bacteria within various Roseobacter lineages are important for thiosulfate oxidation in marine biofilms. We isolate and sequence the genomes of 54 biofilm-associated Roseobacter strains, finding conserved sox gene clusters for thiosulfate oxidation and plasmids, pointing to a niche-specific lifestyle. Analysis of global ocean metagenomic data suggests that Roseobacter strains are abundant in biofilms and mats on various substrates, including stones, artificial surfaces, plant roots, and hydrothermal vent chimneys. Metatranscriptomic analysis indicates that the majority of active sox genes in biofilms belong to Roseobacter strains. Furthermore, we show that Roseobacter strains can grow and oxidize thiosulfate to sulfate under both aerobic and anaerobic conditions. Transcriptomic and membrane proteomic analyses of biofilms formed by a representative strain indicate that thiosulfate induces sox gene expression and alterations in cell membrane protein composition, and promotes biofilm formation and anaerobic respiration. We propose that bacteria of the Roseobacter group are major thiosulfate-oxidizers in marine biofilms, where anaerobic thiosulfate metabolism is preferred.

Atrial fibrillation (AF) is the most common clinical arrhythmia disorder. It can easily lead to complications such as thromboembolism, palpitations, dizziness, angina, heart failure, and stroke. The disability and mortality rates associated with AF are extremely high, significantly affecting the quality of life and work of patients. With the deepening of research into the brain-heart connection, the link between AF and stroke has become increasingly evident. AF is now categorized as either Known Atrial Fibrillation (KAF) or Atrial Fibrillation Detected After Stroke (AFDAS), with stroke as the baseline. This article, through a literature review, briefly summarizes the current pathogenesis of KAF and AFDAS, as well as the status of their clinical pharmacological and non-pharmacological treatments. It has been found that the existing treatments for KAF and AFDAS have limited efficacy and are often associated with significant adverse reactions and a risk of recurrence. Moreover, most drugs and treatment methods tend to focus on a single mechanism pathway. For example, drugs targeting ion channels primarily modulate ion channels and have relatively limited impact on other pathways. This limitation underscores the need to break away from the “one disease, one target, one drug/measurement” dogma for the development of innovative treatments, promoting both drug and non-drug therapies and significantly improving the quality of clinical treatment. With the increasing refinement of the overall mechanisms of KAF and AFDAS, a deeper exploration of physiological pathology, and comprehensive research on the brain-heart relationship, it is imperative to shift from long-term symptom management to more precise and optimized treatment methods that are effective for almost all patients. We anticipate that drugs or non-drug therapies targeting the central nervous system and upstream pathways can guide the simultaneous treatment of multiple downstream pathways in AF, thereby becoming a new breakthrough in AF treatment research.

Ursolic acid (UA) is a plant-derived pentacyclic triterpenoid with 30 carbon atoms. UA has anti-inflammatory, antioxidative, antimicrobial, hepato-protective, anticancer, and other biological activities. Most studies on the biological functions of UA have been performed in mammalian cell (in vitro) and rodent (in vivo) models. UA is used in animal husbandry as an anti-inflammatory and antiviral agent, as well as for enhancing the integrity of the intestinal barrier. Although UA has been shown to have significant in vitro bacteriostatic effects, it is rarely used in animal nutrition. The use of UA as a substitute for oral antibiotics or as a novel feed additive in animal husbandry should be considered. This review summarizes the available data on the biological functions of UA and its applications in animal husbandry.

Abstract The unambiguous detection and classification of volatile organic compounds (VOCs) are crucial in many fields. For using VOC‐sensing to explore the alteration and spoilage of food, very inexpensive sensors are desired. Simple colorimetric sensors seem highly attractive for these applications. Here, a label‐free, colorimetric sensor array made of metal‐organic‐framework‐based (MOF‐based) Fabry‐Pérot (FP) films is presented where the signal read‐out is performed either by their optical spectra or by pictures taken with a smartphone camera. Exposing the FP‐MOF‐films to various VOCs causes a reversible shift of the photonic pattern, where the magnitude of the shift depends on the VOC type, its concentration, and the MOF structure. The application of machine‐ learning‐ algorithms on the sensor data allows to identify the VOCs with a high classification accuracy (92% at 100 ppm). It is shown that the sensor array read‐out can also be performed with a common smartphone camera, also precisely classifying the VOC analytes. Moreover, fresh and spoiled food, like milk and meat, is distinguished by its head space. Thus, the study presents a very inexpensive platform of small colorimetric sensors that allow determining the quality, alteration, and spoilage of food, and it may contribute to realizing smart labels and intelligent packaging.

Establishing wildlife corridors to link detached habitat patches is a widely advocated conservation strategy to reduce the adverse impacts of habitat fragmentation. Given the scarcity of conservation resources, designing an efficient corridor system calls for an optimization approach. The optimal configuration of a wildlife corridor system involving multiple habitat patches poses significant challenges, both methodologically and computationally. This study proposes a two-stage procedure for that purpose. In the first stage, we determine a best-quality corridor between each pair of habitat patches using the method described in Wang et al. (2022). In the second stage, we select a subset of those corridors to assemble a least-cost corridor system using a mixed integer linear programming model presented in this paper. We use an illustrative example to demonstrate the workings of the two-stage method, and then apply it to a real dataset for an area in Cumberland County, Nova Scotia, Canada, involving 1039 irregular land parcels. Results show that an efficient corridor system where each habitat patch is connected to some neighboring habitat patches through a specified minimum number of corridors can be identified conveniently in terms of both data processing and computational effort.