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Abstract Light-induced spin currents with the faster response is essential for the more efficient information transmission and processing. Herein, we systematically explore the effect of light illumination energy and direction on the light-induced spin currents in the W/Y3Fe5O12 heterojunction. Light-induced spin currents can be clearly categorized into two types. One is excited by the low light intensity, which mainly involves the photo-generated spin current from spin photovoltaic effect. The other is caused by the high light intensity, which is the light-thermally induced spin current and mainly excited by spin Seebeck effect. Under low light-intensity illumination, light-thermally induced temperature gradient is very small so that spin Seebeck effect can be neglected. Furthermore, the mechanism on spin photovoltaic effect is fully elucidated, where the photo-generated spin current in Y3Fe5O12 mainly originates from the process of spin precession induced by photons. These findings provide some deep insights into the origin of light-induced spin current.

Abstract Low-temperature germination (LTG) is an important agronomic trait for rice (Oryza sativa). Japonica rice generally has greater capacity for germination at low temperatures than the indica subpopulation. However, the genetic basis and molecular mechanisms underlying this complex trait are poorly understood. Here, we report that OsUBC12, encoding an E2 ubiquitin-conjugating enzyme, increases low-temperature germinability in japonica, owing to a transposon insertion in its promoter enhancing its expression. Natural variation analysis reveals that transposon insertion in the OsUBC12 promoter mainly occurs in the japonica lineage. The variation detected in eight representative two-line male sterile lines suggests the existence of this allele introgression by indica-japonica hybridization breeding, and varieties carrying the japonica OsUBC12 locus (transposon insertion) have higher low-temperature germinability than varieties without the locus. Further molecular analysis shows that OsUBC12 negatively regulate ABA signaling. OsUBC12-regulated seed germination and ABA signaling mainly depend on a conserved active site required for ubiquitin-conjugating enzyme activity. Furthermore, OsUBC12 directly associates with rice SUCROSE NON-FERMENTING 1-RELATED PROTEIN KINASE 1.1 (OsSnRK1.1), promoting its degradation. OsSnRK1.1 inhibits LTG by enhancing ABA signaling and acts downstream of OsUBC12. These findings shed light on the underlying mechanisms of UBC12 regulating LTG and provide genetic reference points for improving LTG in indica rice.

Societal Impact Statement Given the rapidly increasing drought and temperature stresses associated with climate change, innovative approaches for food security are imperative. One understudied opportunity is using feral crops—plants that have escaped and persisted without cultivation—as a source of genetic diversity, which could build resilience in domesticated conspecifics. In some cases, however, feral plants vigorously compete with crops as weeds, challenging food security. By bridging historically siloed ecological, agronomic, and evolutionary lines of inquiry into feral crops, there is the opportunity to improve food security and understand this relatively understudied anthropogenic phenomenon. Summary The phenomenon of feral crops, that is, free‐living populations that have established outside cultivation, is understudied. Some researchers focus on the negative consequences of domestication, whereas others assert that feral populations may serve as useful pools of genetic diversity for future crop improvement. Although research on feral crops and the process of feralization has advanced rapidly in the last two decades, generalizable insights have been limited by a lack of comparative research across crop species and other factors. To improve international coordination of research on this topic, we summarize the current state of feralization research and chart a course for future study by consolidating outstanding questions in the field. These questions, which emerged from the colloquium “Darwins' reversals: What we now know about Feralization and Crop Wild Relatives” at the BOTANY 2021 conference, fall into seven categories that span both basic and applied research: (1) definitions and drivers of ferality, (2) genetic architecture and pathway, (3) evolutionary history and biogeography, (4) agronomy and breeding, (5) fundamental and applied ecology, (6) collecting and conservation, and (7) taxonomy and best practices. These questions serve as a basis for ferality researchers to coordinate research in these areas, potentially resulting in major contributions to food security in the face of climate change.

Transportation electrification, involving large-scale integration of electric vehicles (EV) and fast charging stations (FCS), plays a critical role for global energy transition and decarbonization. In this context, coordination of EV routing and charging activities through suitably designed price signals constitutes an imperative step in secure and economic operation of the coupled power-transportation networks (CPTN). This work examines the non-cooperative pricing competition between self-interested EV charging service providers (CSP), taken into account the complex interactions between CSPs' pricing strategies, EV users' decisions and the operation of CPTN. The modeling of CPTN environment captures the prominent type of uncertainties stemming from the gasoline vehicle and EV origin-destination travel demands and their cost elasticity, EV initial state-of-charge and renewable energy sources (RES). An enhanced multi-agent proximal policy optimization method is developed to solve the pricing game, which incorporates an attention mechanism to selectively incorporate agents' representative information to mitigate the environmental non-stationarity without raising dimensionality challenge, while safeguarding the commercial confidentiality of CSP agents. To foster more efficient learning coordination in the highly uncertain CPTN environment, a sequential update scheme is also developed to achieve monotonic policy improvement for CSP agents. Case studies on an illustrative and a large-scale test system reveal that the proposed method facilitates sufficient competition among CSP agents and corroborates the core benefits in terms of reduced charging costs for EV users, enhancement of RES absorption and cost efficiency of the power distribution network. Results also validate the excellent generalization capability of the proposed method in coping with CPTN uncertainties. Finally, the rationale of the proposed attention mechanism is validated and the superior computational performance is highlighted against the state-of-the-art methods.

ABSTRACTIncreasing evidence reveals that the interaction between tumor cells and tumor-associated macrophages (TAMs) facilitates the progression of prostate cancer, but the related mechanisms remained unclear. This study determined how gankyrin, a component of the 19S regulatory complex of the 26S proteasome, regulates the progression and androgen deprivation therapy (ADT) resistance of prostate cancer through tumor cell–TAM interactions. In vitro functional experiments and in vivo subcutaneous tumor models were used to explore the biological role and molecular mechanisms of gankyrin in prostate cancer cell–TAM interactions. 234 prostate cancer patients were randomly divided into training and validation cohorts to examine the prognostic value of gankyrin through immunohistochemistry (IHC) and statistical analyses, and high gankyrin expression was correlated with poor prognosis. In addition, gankyrin facilitated the progression and ADT resistance of prostate cancer. Mechanistically, gankyrin recruited and upregulated non–POU-domain–containing octamer-binding protein (NONO) expression, resulting in increased androgen receptor (AR) expression. AR then bound to the high-mobility group box 1 (HMGB1) promoter to trigger HMGB1 transcription, expression, and secretion. Moreover, HMGB1 was found to promote the recruitment and activation of TAMs, which secrete IL-6 to reciprocally promote prostate cancer progression, ADT resistance and gankyrin expression via STAT3, resulting in formation of a gankyrin/NONO/AR/HMGB1/IL-6/STAT3 positive feedback loop. Furthermore, targeting the interaction between tumor cells and TAMs by blocking this loop inhibited ADT resistance in a tumor xenograft model. Taken together, the data show that gankyrin serves as a reliable prognostic indicator and therapeutic target for prostate cancer patients.

Abstract Background Renal cell carcinoma (RCC) is a hypermetabolic disease. Abnormal up-regulation of glycolytic signaling promotes tumor growth, and glycolytic metabolism is closely related to immunotherapy of renal cancer. The aim of the present study was to determine whether and how the glycolysis-related biomarker TCIRG1 affects aerobic glycolysis, the tumor microenvironment (TME) and malignant progression of clear cell renal cell carcinoma (ccRCC). Methods Based on The Cancer Genome Atlas (TCGA, n = 533) and the glycolysis-related gene set from MSigDB, we identified the glycolysis-related gene TCIRG1 by bioinformatics analysis, analyzed its immunological properties in ccRCC and observed how it affected the biological function and glycolytic metabolism using online databases such as TIMER 2.0, UALCAN, LinkedOmics and in vitro experiments. Results It was found that the expression of TCIRG1, was significantly increased in ccRCC tissue, and that high TCIRG1 expression was associated with poor overall survival (OS) and short progression-free interval (PFI). In addition, TCIRG1 expression was highly correlated with the infiltration immune cells, especially CD4+T cell Th1, CD8+T cell, NK cell, and M1 macrophage, and positively correlated with PDCD1, CTLA4 and other immunoinhibitors, CCL5, CXCR3 and other chemokines and chemokine receptors. More importantly, TCIRG1 may regulate aerobic glycolysis in ccRCC via the AKT/mTOR signaling pathway, thereby affecting the malignant progression of ccRCC cell lines. Conclusions Our results demonstrate that the glycolysis-related biomarker TCIRG1 is a tumor-promoting factor by affecting aerobic glycolysis and tumor immune microenvironment in ccRCC, and this finding may provide a new idea for the treatment of ccRCC by combination of metabolic intervention and immunotherapy.

Abstract Understanding the evolutionary forces in speciation is a central goal in evolutionary biology. Asian cultivated rice has two subspecies, indica and japonica, but the underlying mechanism of the partial reproductive isolation between them remains obscure. Here we show a presence-absence variation (PAV) at the Se locus functions as an indica-japonica reproductive barrier by causing hybrid sterility (HS) in indica-japonica crosses. The locus comprises two adjacent genes: ORF3 encodes a sporophytic pollen killer, whereas ORF4 protects pollen in a gametophytic manner. In F1 of indica-japonica crosses, pollen with the japonica haplotype, which lacks the sequence containing the protective ORF4, is aborted due to the pollen-killing effect of ORF3 from indica. Evolutionary analysis suggests ORF3 is a gene associated with the Asian cultivated rice species complex, and the PAV has contributed to the reproductive isolation between the two subspecies of Asian cultivated rice. Our analyses provide perspectives on rice inter-subspecies post-zygotic isolation, and will promote efforts to overcome reproductive barriers in indica-japonica hybrid rice breeding.

Multispectral thermometry is based on the law of blackbody radiation and is widely used in engineering practice today. Temperature values can be inferred from radiation intensity and multiple sets of wavelengths. Multispectral thermometry eliminates the requirements for single-spectral and spectral similarity, which are associated with two-colour thermometry. In the process of multispectral temperature inversion, the solution of spectral emissivity and multispectral data processing can be seen as the keys to accurate thermometry. At present, spectral emissivity is most commonly estimated using assumption models. When an assumption model closely matches an actual situation, the inversion of the temperature and the accuracy of spectral emissivity are both very high; however, when the two are not closely matched, the inversion result is very different from the actual situation. Assumption models of spectral emissivity exhibit drawbacks when used for thermometry of a complex material, or any material whose properties dynamically change during a combustion process. To address the above problems, in the present study, we developed a multispectral thermometry method based on optimisation ideas. This method involves analysing connections between measured temperatures of each channel in a multispectral temperature inversion process; it also makes use of correlations between multispectral signals at different temperatures. In short, we established a multivariate temperature difference correlation function based on the principles of multispectral radiometric thermometry, using information correlations between data for each channel in a temperature inversion process. We then established a high-precision thermometry model by optimising the correlation function and correcting any measurement errors. This method simplifies the modelling process so that it becomes an optimisation problem of the temperature difference function. This also removes the need to assume the relationships between spectral emissivity and other physical quantities, simplifying the process of multispectral thermometry. Finally, this involves correction of the spectral data so that any impact of measurement error on the thermometry is reduced. In order to verify the feasibility and reliability of the method, a simple eight-channel multispectral thermometry device was used for experimental validation, in which the temperature emitted from a blackbody furnace was identified as the standard value. In addition, spectral data from the 468–603 nm band were calibrated within a temperature range of 1923.15–2273.15 K, resulting in multispectral thermometry based on optimisation principles with an error rate of around 0.3% and a temperature calculation time of less than 3 s. The achieved level of inversion accuracy was better than that obtained using either a secondary measurement method (SMM) or a neural network method, and the calculation speed achieved was considerably faster than that obtained using the SMM method.

Abstract Background Despite all modern advances in medicine, an effective drug for treating sepsis has yet to be found. The discovery of CMPK2 spurred hopes for the treatment of sepsis. However, CMPK2‐untapped target inhibitors are still an enormous obstacle that has hindered the CMPK2‐centric treatment of sepsis. Methods Here, we found that the CMPK2 gene is highly expressed in the whole blood of sepsis patients by RNA‐Seq. First, recombinant CMPK2 was purified by a eukaryotic expression purification system, and the activity of recombinant CMPK2 was detected by the ADP‐GLO assay. Second, we developed an affinity MS strategy combined with quantitative lysine reactivity profiling to discover CMPK2 ligands from the active ingredients of Chinese herbs. In addition, the dissociation constant Kd of the ligand and the target protein CMPK2 was further detected by microscale thermophoresis technology. Third, we used this strategy to identify a naturally sourced small molecule, dracorhodin (DP). Using mass spectrometry‐based quantitative lysine reactivity profiling combined with a series of mutant tests, the results show that K265 acts as a bright hotspot of DP inhibition of CMPK2. Fourth, immune‐histochemical staining, ELISAs, RT‐qPCR, flow cytometry and immunoblotting were used to illustrate the potential function and related mechanism of DP in regulating sepsis injury. Results Our results suggest that DP exerts powerful anti‐inflammatory effects by regulating the NLRP3 inflammasome via the lipopolysaccharide (LPS)‐induced CMPK2 pathway. Strikingly, DP significantly attenuated LPS‐induced sepsis in a mouse model, but its effect was weakened in mice with myeloid‐specific Cmpk2 ablation. Conclusion We provide a new framework that provides more valuable information for new therapeutic approaches to sepsis, including the establishment of screening strategies and the development of target drugs to provide a theoretical basis for ultimately improving clinical outcomes for sepsis patients. Collectively, these findings reveal that DP is a promising CMPK2 inhibitor for the treatment of sepsis.

Abstract Chronic inflammation promotes the tumorigenesis and cell stemness maintenance of colorectal cancer (CRC). However, the bridge role of long noncoding RNA (lncRNA) in linking chronic inflammation to CRC development and progression needs better understanding. Here, we elucidated a novel function of lncRNA GMDS-AS1 in persistently activated signal transducer and transcription activator 3 (STAT3) and Wnt signaling and CRC tumorigenesis. Interleukin-6 (IL-6) and Wnt3a induced lncRNA GMDS-AS1 expression, which was highly expressed in the CRC tissues and plasma of CRC patients. GMDS-AS1 knockdown impaired the survival, proliferation and stem cell-like phenotype acquisition of CRC cells in vitro and in vivo. We performed RNA sequencing (RNA-seq) and mass spectrometry (MS) to probe target proteins and identify their contributions to the downstream signaling pathways of GMDS-AS1. In CRC cells, GMDS-AS1 physically interacted with the RNA-stabilizing protein HuR, thereby protecting the HuR protein from polyubiquitination- and proteasome-dependent degradation. HuR stabilized STAT3 mRNA and upregulated the levels of basal and phosphorylated STAT3 protein, persistently activating STAT3 signaling. Our research revealed that the lncRNA GMDS-AS1 and its direct target HuR constitutively activate STAT3/Wnt signaling and promote CRC tumorigenesis, the GMDS-AS1-HuR-STAT3/Wnt axis is a therapeutic, diagnostic and prognostic target in CRC.

As one of the essential nutrients for plants, nitrogen (N) has a major impact on the yield and quality of wheat worldwide. Due to chemical fertilizer pollution, it has become increasingly important to improve crop yield by increasing N use efficiency (NUE). Therefore, understanding the response mechanisms to low N (LN) stress is essential for the regulation of NUE in wheat. In this study, LN stress significantly accelerated wheat root growth, but inhibited shoot growth. Further transcriptome analysis showed that 8468 differentially expressed genes (DEGs) responded to LN stress. The roots and shoots displayed opposite response patterns, of which the majority of DEGs in roots were up-regulated (66.15%; 2955/4467), but the majority of DEGs in shoots were down-regulated (71.62%; 3274/4565). GO and KEGG analyses showed that nitrate reductase activity, nitrate assimilation, and N metabolism were significantly enriched in both the roots and shoots. Transcription factor (TF) and protein kinase analysis showed that genes such as MYB-related (38/38 genes) may function in a tissue-specific manner to respond to LN stress. Moreover, 20 out of 107 N signaling homologous genes were differentially expressed in wheat. A total of 47 transcriptome datasets were used for weighted gene co-expression network analysis (17,840 genes), and five TFs were identified as the potential hub regulatory genes involved in the response to LN stress in wheat. Our findings provide insight into the functional mechanisms in response to LN stress and five candidate regulatory genes in wheat. These results will provide a basis for further research on promoting NUE in wheat.

Due to the existence of bidirectional fault currents in active distribution networks (ADN), a key issue of its protection is how to identify the fault direction. In traditional power systems, the positive sequence fault component (PSFC) based protection schemes are widely used, since they have good performance under different types of fault. However, due to the diversity of voltage variants and the influence from low-voltage ride-through (LVRT) requirement, the PSFC impedance angle of an inverter-interfaced distributed generator (IIDG) is difficult to determine. To solve this problem, this paper proposed a solution based on the cooperative design of the IIDG fault control strategy. Within a few power cycles after the fault occurs, each IIDG is controlled to output a specific positive sequence current according to the voltage variant. In this way, the PSFC impedance angle of IIDG is fixed to a given value under any fault scenario, thereby ensuring the applicability of PSFC-based protection in ADN. On this basis, the fault direction identification method and trip logic for the protection device are proposed. The effectiveness of the proposed method is verified by Matlab simulation results. The PSFC impedance angle of IIDG stabilizes at the desired value, and the output current of IIDG is always limited within a safe range during the whole process. Based on the sampled signals in the second power cycle after the occurrence of a fault, the protection device can use the PSFC-based criterion to accurately determine the direction of the fault.

Wind-Energy systems based on permanent magnet synchronous generators (PMSG) offer attractive advantages due to the higher reliability and power density. Considering the uncertainty influence of wind speed, PMSG with the traditional control method has poor-dynamic performance. Therefore, the Maximum Wind-Energy Captured based on the Inverse-System (MWECIS) method is proposed to improve the control precision and speed tracking rapidity of PMSG. In this paper, the inverse system is illustrated according to the conventional PMSG systems, and two systems (inverse system and PMSG system) are cascaded to obtain a decoupled pseudo-linear system. The proposed MWECIS method contributes to present a linear control law for PMSG system. Compared with the tip–speed-ratio control based on proportional–integral​ (TSR-PI) method, the proposed MWECIS method shows the better dynamic performance such as quickly and stably speed tracking ability. The simulation and experimental results verify the effectiveness of the proposed method, which could achieve the maximum wind-energy capture.

Abstract Background Tumor-associated macrophages (TAMs) are closely related to unfavorable prognosis of patients with clear cell renal cell carcinoma (ccRCC). However, the important molecules in the interaction between ccRCC and TAMs are unclear. Methods TCGA-KIRC gene expression data of tumor tissues and normal tissues adjacent to tumor were compared to identify differentially expressed genes in ccRCC. TAMs related genes were discovered by analyzing the correlation between these differentially expressed genes and common macrophage biomarkers. Gene set enrichment analysis was performed to predict functions of TAMs related gene. The findings were further validated using RNA sequencing data obtained from the CheckMate 025 study and immunohistochemical analysis of samples from 350 patients with ccRCC. Kaplan–Meier survival curve, Cox regression analysis and Harrell’s concordance index analysis were used to determine the prognostic significance. Results In this study, we applied bioinformatic analysis to explore TAMs related differentially expressed genes in ccRCC and identified 5 genes strongly correlated with all selected macrophage biomarkers: STAC3, LGALS9, TREM2, FCER1G, and PILRA. Among them, FCER1G was abundantly expressed in tumor tissues and showed prognostic importance in patients with ccRCC who received treatment with Nivolumab; however, it did not exhibit prognostic value in those treated with Everolimus. We also discovered that high expression levels of FCER1G are related to T cell suppression. Moreover, combination of FCER1G and macrophage biomarker CD68 can improve the prognostic stratification of patients with ccRCC from TCGA-KIRC. Based on the immunohistochemical analysis of samples from patients with ccRCC, we further validated that FCER1G and CD68 are both highly expressed in tumor tissue and correlate with each other. Higher expression of CD68 or FCER1G in ccRCC tissue indicates shorter overall survival and progression-free survival; patients with high expression of both CD68 and FCER1G have the worst outcome. Combining CD68 and FCER1G facilitates the screening of patients with a worse prognosis from the same TNM stage group. Conclusions High expression of FCER1G in ccRCC is closely related to TAMs infiltration and suppression of T cell activation and proliferation. Combining the expression levels of FCER1G and macrophage biomarker CD68 may be a promising postoperative prognostic index for patients with ccRCC.

Sepsis-induced acute kidney injury (AKI) continues to be associated with poor outcomes in critical care patients. Previous research has revealed that tetrahydrocurcumin (THC) exerts renoprotective effects in multiple nephritic disorders by modulating inflammation and oxidative stress. However, the effects of THC on sepsis-induced AKI and the underlying mechanisms remain unclear. In this study, a mouse model of sepsis-induced AKI, generated by cecal ligation and puncture operation, was used to investigate the protective effects of THC and the role of SIRT1. Histological manifestation and TUNEL analysis were observed to determine the severity of kidney damage. Levels of BUN, SCr, KIM-1, and UAlb/Cr were calculated to assess the renal function. Expressions of IL-1β, IL-6, and TNF-α were measured to evaluate the inflammatory response. MDA content, SOD, GSH, CAT, and GPx activities and DHE staining were analyzed to estimate the degree of oxidative stress. Protein expressions of SIRT1, Ac-p65, and Ac-foxo1 were detected to explore the underlying mechanisms. We observed that THC not only increased the survival rate, improved the kidney function and ameliorated the renal histological damage of septic mice, but also inhibited inflammatory response, prohibited oxidative stress, and prevented cell apoptosis in renal tissues in septic mice. Mechanistically, THC remarkably increased the expression of SIRT1, accompanied by decreased expressions of downstream molecules Ac-p65 and Ac-foxo1. Meanwhile, the beneficial effects of THC were clearly abolished by the SIRT1-specific inhibitor EX527. These results delineate that THC prevents sepsis-induced AKI by suppressing inflammation and oxidative stress through activating the SIRT1 signaling. Abbreviation: Ac-p65: acetylated p65; Ac-foxo 1: acetylated forkhead box O1; AKI: acute kidney injury; BUN: blood urea nitrogen; CAT: catalase; DHE: dihydroethidium; GPx: glutathione peroxidase; GSH: reduced glutathione; IL-1β: Interleukin-1 beta; IL-6: Interleukin-6; KIM-1: kidney injury molecule 1; MDA: malondialdehyde; SCr: serum creatinine; SIRT1: silent information regulator 1; SOD: superoxide dismutase; THC: tetrahydrocurcumin; TNF-α: tumor necrosis factor-alpha; TUNEL: TdT-mediated dUTP Nick-End Labeling; UAlb/Cr: urine micro albumin/creatinine.

With the increasing penetration of the permanent-magnet direct-drive wind power system, the maximum wind-energy capture and the generation speed control are more and more important. In the literature, the dynamic performance of the generator speed is well documented by the inverse system method. However, conventional inverse system methods have parameter dependency that is not sufficient to meet the dynamic requirements for permanent magnet synchronous generator (PMSG) speed tracking. Therefore, this paper introduces a support vector regression machine (SVR) method, especially for the inverse system model, which could solve the inaccurate parameters problems. As the SVR has the nonlinear approximation ability to identify and adjust the parameters online, thus, the system robustness could be improved. Finally, the dynamic performance of generator speed is evaluated by using the SVR method. Proposed theoretical developments are verified by the Simulink Test and experimental test.

Based on the ArcGIS geostatistical analysis method, this study offers a visualization of the spatial distribution pattern and spatial trend of vegetable production in China. The research also examines the degree of spatial agglomeration patterns of vegetable production by using the standard deviation ellipse technique and exploratory spatial data analysis method. In addition, we employ the spatial regression model partial differential method to explore the driving factors leading to the changing layout of vegetable production. The findings unveil that vegetable production in China exhibit strong spatial non-equilibrium characteristics, with “high-high” and “low-low” types as the main agglomeration patterns. Furthermore, the location distribution shows a northeast–southwest orientation with the center of gravity of distribution gradually directed toward the southwest. Regarding driving factors, the results show that the effective irrigated area of natural factors had a facilitating effect on the layout of vegetable production, while the affected area had an inhibiting effect on it. Climate indicators such as temperature, precipitation and light show different degrees of influence on the layout of vegetable production. The level of urbanization and transportation conditions have a negative impact on the layout of production in the region. Market demand has a positive spillover effect on the layout of local vegetable production, while it has a negative spillover effect on other regions. Technological progress shows positive spillover effects on the layout of vegetable production in the region and other regions. Financial support policy also shows positive effects from an overall perspective.

Heterogeneity in gene expression and epigenetic states exists across individual cells. Here, the authors develop scCAT-seq, a technique for simultaneously performing ATAC-seq and RNA-seq within the same single cell.

Japonica rice can grow further north than wild or indica rice and is more tolerant of cold climates. Here, the authors show that bZIP73 likely underwent selection in the early phase of rice domestication to facilitate cold tolerance in japonica by modulating ABA and ROS homeostasis.

The microRNA (mir)-374a has been implicated in several types of human cancer; however, its role in diabetic nephropathy (DN) remains unclear. Monocyte chemoattractant protein (MCP)-1 is a chemokine that recruits macrophages to inflammatory sites and is important for the development and progression of DN. However, the relationship between miR-374a and MCP-1 in DN is unknown. We addressed this in the present study by examining the expression of these factors in kidney tissue samples from DN patients and through loss- and gain-of-function experiments using HK2 human renal tubular epithelial cells. We found that miR-374a was downregulated whereas MCP-1 was upregulated in DN tissue. A bioinformatics analysis revealed that MCP-1 is a putative target of miR-374a. To confirm this relationship, HK2 cells treated with normal glucose (5.6 mmol/l D-glucose), high glucose (HG) (30 mmol/l D-glucose), or high osmotic pressure solution (5.6 mmol/l D-glucose + 24.4 mmol/l D-mannitol) were transfected with miR-374a mimic or inhibitor. miR-374a mimic reduced MCP-1 mRNA expression and migration of co-cultured U937 cells, whereas miR-374a inhibition had the opposite effects. Additionally, interleukin-6 and -18 and tumor necrosis factor-α levels were downregulated by transfection of miR-374a mimic. On the other hand, MCP-1 overexpression reversed the inhibitory effects of miR-374a in HK2 cells. Thus, miR-374a suppresses the inflammatory response in DN through negative regulation of MCP-1 expression. These findings suggest that therapeutic strategies that target the miR-374a/MCP-1 axis can be an effective treatment for DN.

Demand response (DR) is widely accepted as a feasible and potential solution to improve the operation of the power system. In this paper, an economical and practical DR system architecture based on internet and Internet of things (IoT) communication technologies is discussed to achieve wide-area DR control without using an expensive metering infrastructure. Multi agents are introduced with respective control strategies to implement multi-time-scale control in a power system. In order to support quick DR strategies, a novel smart terminal design for the proposed DR system is described with functions of local parameter detection and action. The practicality of the proposed system was validated on a developed hardware-in-loop co-simulation platform.

SiteFinding-PCR is a method for isolating flanking sequence tags (FSTs) of T-DNA insertion lines, but the efficiency needs to be improved. Here we report a computation-assisted design for the random primers used in SiteFinding- PCR. A short sequence, GCATG, was screened from the rice genome and used as the 3′ end of the random primer. When applying the optimized primer for isolating FSTs from 168 transgenic rice lines, we obtained 107 specific products, including 64 FSTs. The efficiency of obtaining FSTs using the modified version of SiteFinding-PCR increased by 73.0% compared with the method previously reported (P < 0.01, µ test). We also provide computational results for several other plant species such as maize, sorghum, Arabidopsis, foxtail millet, and Brachypodium based on the available genome data, so that the modified method could be easily adapted to other species.