Self-adaptive integration of photothermal and radiative cooling for continuous energy harvesting from the sun and outer space.

The sun (∼6,000 K) and outer space (∼3 K) are two significant renewable thermodynamic resources for human beings on Earth. The solar thermal conversion by photothermal (PT) and harvesting the coldness of outer space by radiative cooling (RC) have already attracted tremendous interest. However, most of the PT and RC approaches are static and monofunctional, which can only provide heating or cooling respectively under sunlight or darkness. Herein, a spectrally self-adaptive absorber/emitter (SSA/E) with strong solar absorption and switchable emissivity within the atmospheric window (i.e., 8 to 13 µm) was developed for the dynamic combination of PT and RC, corresponding to continuously efficient energy harvesting from the sun and rejecting energy to the universe. The as-fabricated SSA/E not only can be heated to ∼170 °C above ambient temperature under sunshine but also be cooled to 20 °C below ambient temperature, and thermal modeling captures the high energy harvesting efficiency of the SSA/E, enabling new technological capabilities.

Electrically Tunable, Rapid Spin-Orbit Torque Induced Modulation of Colossal Magnetoresistance in Mn3Si2Te6 Nanoflakes.

As a quasi-layered ferrimagnetic material, Mn3Si2Te6 nanoflakes exhibit magnetoresistance behavior that is fundamentally different from their bulk crystal counterparts. They offer three key properties crucial for spintronics. First, at least 106 times faster response compared to that exhibited by bulk crystals has been observed in current-controlled resistance and magnetoresistance. Second, ultralow current density is required for resistance modulation (∼5 A/cm2). Third, electrically gate-tunable magnetoresistance has been realized. Theoretical calculations reveal that the unique magnetoresistance behavior in the Mn3Si2Te6 nanoflakes arises from a magnetic field induced band gap shift across the Fermi level. The rapid current induced resistance variation is attributed to spin-orbit torque, an intrinsically ultrafast process (∼nanoseconds). This study suggests promising avenues for spintronic applications. In addition, it highlights Mn3Si2Te6 nanoflakes as a suitable platform for investigating the intriguing physics underlying chiral orbital moments, magnetic field induced band variation, and spin torque.

Room-Temperature Magnetic Phase Transition in an Electrically Tuned van der Waals Ferromagnet.

Finding tunable van der Waals (vdW) ferromagnets that operate at above room temperature is an important research focus in physics and materials science. Most vdW magnets are only intrinsically magnetic far below room temperature and magnetism with square-shaped hysteresis at room temperature has yet to be observed. Here, we report magnetism in a quasi-2D magnet Cr_{1.2}Te_{2} observed at room temperature (290 K). This magnetism was tuned via a protonic gate with an electron doping concentration up to 3.8×10^{21} cm^{-3}. We observed nonmonotonic evolutions in both coercivity and anomalous Hall resistivity. Under increased electron doping, the coercivities and anomalous Hall effects (AHEs) vanished, indicating a doping-induced magnetic phase transition. This occurred up to room temperature. DFT calculations showed the formation of an antiferromagnetic (AFM) phase caused by the intercalation of protons which induced significant electron doping in the Cr_{1.2}Te_{2}. The tunability of the magnetic properties and phase in room temperature magnetic vdW Cr_{1.2}Te_{2} is a significant step towards practical spintronic devices.

A Robust Fire Detection Model via Convolution Neural Networks for Intelligent Robot Vision Sensing.

Accurate fire identification can help to control fires. Traditional fire detection methods are mainly based on temperature or smoke detectors. These detectors are susceptible to damage or interference from the outside environment. Meanwhile, most of the current deep learning methods are less discriminative with respect to dynamic fire and have lower detection precision when a fire changes. Therefore, we propose a dynamic convolution YOLOv5 fire detection method using a video sequence. Our method first uses the K-mean++ algorithm to optimize anchor box clustering; this significantly reduces the rate of classification error. Then, the dynamic convolution is introduced into the convolution layer of YOLOv5. Finally, pruning of the network heads of YOLOv5's neck and head is carried out to improve the detection speed. Experimental results verify that the proposed dynamic convolution YOLOv5 fire detection method demonstrates better performance than the YOLOv5 method in recall, precision and F1-score. In particular, compared with three other deep learning methods, the precision of the proposed algorithm is improved by 13.7%, 10.8% and 6.1%, respectively, while the F1-score is improved by 15.8%, 12% and 3.8%, respectively. The method described in this paper is applicable not only to short-range indoor fire identification but also to long-range outdoor fire detection.

LSU rDNA D5 region: the DNA barcode for molecular classification and identification of Demodex.

Whether ribosomal genes can be used as DNA barcodes for molecular identification of Demodex (Acariformes: Demodicidae) is unclear. To examine this, Demodex folliculorum, D. brevis, D. canis, and D. caprae were collected for DNA extraction, rDNA fragments amplification, sequencing, and analysis. The V2 and V4 regions of SSU rDNA; D5, D6, and D8 regions of LSU rDNA; and ITS region were obtained from the four morphospecies. BLAST analysis showed that the obtained sequences matched those of Demodex or Aplonobia (Acariformes: Tetranychidae) in Raphignathae. Phylogenetic trees derived from V2, V4, D5, D6, and D8 regions, but not from ITS region, showed that the four species of Demodex clustered independently. Sequence divergence analysis further demonstrated that D5, D6, and D8 regions had obvious barcoding gap between intraspecific and interspecific divergences, with the gap of D5 (16.91%) larger than that of D6 (11.82%) and D8 (4.66%). The V2 and V4 regions did not have a barcoding gap, as the intraspecific and interspecific divergences partially overlapped. For the ITS region, intraspecific and interspecific divergences completely overlapped. These results suggest that the D5, D6, and D8 regions of LSU rDNA, especially D5, are suitable DNA barcodes for Demodex.

DNA barcoding for molecular identification of Demodex based on mitochondrial genes.

There has been no widely accepted DNA barcode for species identification of Demodex. In this study, we attempted to solve this issue. First, mitochondrial cox1-5' and 12S gene fragments of Demodex folloculorum, D. brevis, D. canis, and D. caprae were amplified, cloned, and sequenced for the first time; intra/interspecific divergences were computed and phylogenetic trees were reconstructed. Then, divergence frequency distribution plots of those two gene fragments were drawn together with mtDNA cox1-middle region and 16S obtained in previous studies. Finally, their identification efficiency was evaluated by comparing barcoding gap. Results indicated that 12S had the higher identification efficiency. Specifically, for cox1-5' region of the four Demodex species, intraspecific divergences were less than 2.0%, and interspecific divergences were 21.1-31.0%; for 12S, intraspecific divergences were less than 1.4%, and interspecific divergences were 20.8-26.9%. The phylogenetic trees demonstrated that the four Demodex species clustered separately, and divergence frequency distribution plot showed that the largest intraspecific divergence of 12S (1.4%) was less than cox1-5' region (2.0%), cox1-middle region (3.1%), and 16S (2.8%). The barcoding gap of 12S was 19.4%, larger than cox1-5' region (19.1%), cox1-middle region (11.3%), and 16S (13.0%); the interspecific divergence span of 12S was 6.2%, smaller than cox1-5' region (10.0%), cox1-middle region (14.1%), and 16S (11.4%). Moreover, 12S has a moderate length (517 bp) for sequencing at once. Therefore, we proposed mtDNA 12S was more suitable than cox1 and 16S to be a DNA barcode for classification and identification of Demodex at lower category level.

De novo RNA-Seq and functional annotation of Sarcoptes scabiei canis.

The transcriptomic data of Sarcoptes is still lacking in the public database due to the difficulty in extracting high-quality RNA from tiny mites with thick chitin. In this study, total RNA was extracted from live Sarcoptes mites for quality assessment, RNA-Seq, functional annotation, and coding region (CD) prediction and verification. The results showed that the sample JMQ-lngm was qualified for cDNA library construction. Firstly, Agilent 2100 detection showed that the RNA baseline was smooth and the 18S peak was single. Second, the Illumina platform generated 65.78M clean reads and 20,826 unigenes with 35.43M were assembled, occupying 62.98 % of the 56.26M genome. In total, 15,034 unigenes were annotated in seven functional databases. Finally, 13,122 CDs were detected in the 20,826 unigenes, of which 70 complete CDs were matched with Sarcoptes manually in non-redundant nucleotide (NT). Three CDs with indels ≥10 bp were verified. Those results indicated that peritrophin sequences of JMQ-lngm missed 35 bp during the assembly; the pressure-sensitive sodium channel sequences of all the six Sarcoptes scabiei canis isolates were confirmed to be 90 bp shorter than that of a Sarcoptes scabiei hominis isolate; three introns remained in PH chlorine ion channel gating sequences of JMQ-lngm. Moreover, the allergen gene prediction for JMQ-lngm indicated that 61 unigenes were matched with 19 allergen genes of Dermatophagoides, of which Der 1, Der 3, Der 8, and Der 10 had been confirmed in NT. In conclusion, this study successfully completed the RNA-Seq and functional annotation of S. s. canis for the first time, which provides molecular data for future studies on the identification and pathogenic genes of Sarcoptidae.

Constructing and detecting a cDNA library for mites.

RNA extraction and construction of complementary DNA (cDNA) library for mites have been quite challenging due to difficulties in acquiring tiny living mites and breaking their hard chitin. The present study is to explore a better method to construct cDNA library for mites that will lay the foundation on transcriptome and molecular pathogenesis research. We selected Psoroptes cuniculi as an experimental subject and took the following steps to construct and verify cDNA library. First, we combined liquid nitrogen grinding with TRIzol for total RNA extraction. Then, switching mechanism at 5' end of the RNA transcript (SMART) technique was used to construct full-length cDNA library. To evaluate the quality of cDNA library, the library titer and recombination rate were calculated. The reliability of cDNA library was detected by sequencing and analyzing positive clones and genes amplified by specific primers. The results showed that the RNA concentration was 836 ng/µl and the absorbance ratio at 260/280 nm was 1.82. The library titer was 5.31 × 10(5) plaque-forming unit (PFU)/ml and the recombination rate was 98.21%, indicating that the library was of good quality. In the 33 expressed sequence tags (ESTs) of P. cuniculi, two clones of 1656 and 1658 bp were almost identical with only three variable sites detected, which had an identity of 99.63% with that of Psoroptes ovis, indicating that the cDNA library was reliable. Further detection by specific primers demonstrated that the 553-bp Pso c II gene sequences of P. cuniculi had an identity of 98.56% with those of P. ovis, confirming that the cDNA library was not only reliable but also feasible.

Population identification of Sarcoptes hominis and Sarcoptes canis in China using DNA sequences.

There has been no consistent conclusion on whether Sarcoptes mites parasitizing in humans and animals are the same species. To identify Sarcoptes (S.) hominis and S. canis in China, gDNA was extracted from individual mites (five from patients with scabies and five from dogs with mange) for amplification of rDNA ITS2, mtDNA 16S, and cox1 fragment sequences. Then, the sequences obtained were aligned with those from different hosts and geographical locations retrieved from GenBank and sequence analyses were conducted. Phylogenetic trees based on 317-bp mtDNA cox1 showed five distinctive branches (species) of Sarcoptes mites, four for S. hominis (S. hominis Chinese, S. nr. hominis Chinese, S. hominis Australian, and S. hominis Panamanian) and one for S. animal (S. animal). S. animal included mites from nine animal species, with S. canis China, S. canis Australia, and S. canis USA clustering as a subbranch. Further sequence divergence analysis revealed no overlap between intraspecific (≤ 2.6 %) and interspecific (2.6-10.5 %) divergences in 317-bp mtDNA cox1. However, overlap was detected between intra- and interspecific divergences in 311-bp rDNA ITS2 or 275-bp mtDNA 16S when the divergences exceeded 1.0 %, which resulted in failure in identification of Sarcoptes. The results showed that the 317-bp mtDNA cox1 could be used as a DNA barcode for molecular identification of Sarcoptes mites. In addition, geographical isolation was observed between S. hominis Chinese, S. hominis Australian, and S. hominis Panamanian, but not between all S. canis. S. canis and the other S. animal belonged to the same species.

Hybrid parameters for fluid identification using an enhanced quantum neural network in a tight reservoir.

This paper proposes a fluid classifier for a tight reservoir using a quantum neural network (QNN). It is difficult to identify the fluid in tight reservoirs, and the manual interpretation of logging data, which is an important means to identify the fluid properties, has the disadvantages of a low recognition rate and non-intelligence, and an intelligent algorithm can better identify the fluid. For tight reservoirs, the logging response characteristics of different fluid properties and the sensitivity and relevance of well log parameter and rock physics parameters to fluid identification are analyzed, and different sets of input parameters for fluid identification are constructed. On the basis of quantum neural networks, a new method for combining sample quantum state descriptions, sensitivity analysis of input parameters, and wavelet activation functions for optimization is proposed. The results of identifying the dry layer, gas layer, and gas-water co-layer in the tight reservoir in the Sichuan Basin of China show that different input parameters and activation functions affect recognition performance. The proposed quantum neural network based on hybrid parameters and a wavelet activation function has higher fluid identification accuracy than the original quantum neural network model, indicating that this method is effective and warrants promotion and application.

A comparative analysis of small RNA sequencing data in tubers of purple potato and its red mutant reveals small RNA regulation in anthocyanin biosynthesis.

Anthocyanins are a group of natural pigments acting as stress protectants induced by biotic/abiotic stress in plants. Although the metabolic pathway of anthocyanin has been studied in potato, the roles of miRNAs on the metabolic pathway remain unclear. In this study, a purple tetraploid potato of SD92 and its red mutant of SD140 were selected to explore the regulation mechanism of miRNA in anthocyanin biosynthesis. A comparative analysis of small RNAs between SD92 and SD140 revealed that there were 179 differentially expressed miRNAs, including 65 up- and 114 down-regulated miRNAs. Furthermore, 31 differentially expressed miRNAs were predicted to potentially regulate 305 target genes. KEGG pathway enrichment analysis for these target genes showed that plant hormone signal transduction pathway and plant-pathogen interaction pathway were significantly enriched. The correlation analysis of miRNA sequencing data and transcriptome data showed that there were 140 negative regulatory miRNA-mRNA pairs. The miRNAs included miR171 family, miR172 family, miR530b_4 and novel_mir170. The mRNAs encoded transcription factors, hormone response factors and protein kinases. All these results indicated that miRNAs might regulate anthocyanin biosynthesis through transcription factors, hormone response factors and protein kinase.

Bruceine D and afatinib combination inhibits ovarian cancer cells proliferation and migration through DNA damage repair and EGFR pathway.

Owing to the high rates of relapse and migration, ovarian cancer (OC) has been recognized as the most lethal gynecological malignancy worldwide. The activity of the epidermal growth factor receptor (EGFR) signaling pathway is frequently associated with OC cell proliferation and migration. Despite this knowledge, inhibition of EGFR signaling in OC patients failed to achieve satisfactory therapeutic effects. In this study, we identified that bruceine D (BD) and EGFR inhibitor, afatinib, combination resulted in synergistic anti-OC effects. The results indicated that compared with one of both drugs alone, the combination of BD and afatinib slowed the DNA replication rate, inhibition of cell viability, and proliferation and clone formation. This resulted in cell cycle arrest and cell apoptosis. In addition, the combination of BD and afatinib possessed a stronger ability to inhibit the OC cell adhesion and migration than treatment with BD or afatinib alone. Mechanistically, the combined treatment triggered intense DNA damage, suppressed DNA damage repair, and enhanced the inhibition of the EGFR pathway. These results demonstrated that compared with each pathway inhibition, combined blocking of both DNA damage repair and the EGFR pathway appears to more effective against OC treatment. The results support the potential of BD and afatinib combination as a therapeutic strategy for OC patients.

Ferroelectrically Modulated and Enhanced Photoresponse in a Self-Powered α-In2Se3/Si Heterojunction Photodetector.

Photodetectors have been applied to pivotal optoelectronic components of modern optical communication, sensing, and imaging systems. As a room-temperature ferroelectric van der Waals semiconductor, 2D α-In2Se3 is a promising candidate for a next-generation optoelectronic material because of its thickness-dependent direct bandgap and excellent optoelectronic performance. Previous studies of photodetectors based on α-In2Se3 have been rarely focused on the modulated relationship between the α-In2Se3 intrinsic ferroelectricity and photoresponsivity. Herein, a simple integrated process and high-performance photodetector based on an α-In2Se3/Si vertical hybrid-dimensional heterojunction was constructed. Our photodetector in the ferroelectric polarization up state accomplishes a self-powered, highly sensitive photoresponse with an on/off ratio of 4.5 × 105 and detectivity of 1.6 × 1013 Jones, and it also shows a fast response time with 43 µs. The depolarization field generated by the remanent polarization of ferroelectrics in α-In2Se3 provides a strategy for enhancement and modulation of photodetection. The negative correlation was discovered because the enhancement photoresponsivity factor of ferroelectric modulation competes with the photovoltaic behavior within the α-In2Se3/Si heterojunction. Our research highlights the great potential of the high-efficiency heterojunction photodetector for future object recognition and photoelectric imaging.

Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China.

Improving energy efficiency is an important way to achieve low-carbon economic development, a common goal of most nations. Based on the comprehensive survey data of enterprises above a designated size in Guangdong Province, this paper studies the impact of artificial intelligence on the energy efficiency of manufacturing enterprises. The results show that: (1) artificial intelligence, as measured by the use of industrial robots, has significantly improved the energy efficiency of manufacturing enterprises. This conclusion is still robust after introducing data on industrial robots in the United States over the same time period as the instrumental variable for the endogeneity test. (2) The mechanism test shows that artificial intelligence mainly promotes the improvement in energy efficiency by promoting technological progress; the impact of artificial intelligence on the technological efficiency of enterprises is not significant. (3) Heterogeneity analysis shows that the age of the manufacturing enterprises inhibits a promoting effect of artificial intelligence on energy efficiency; manufacturing enterprises' performance can enhance the promoting effect of artificial intelligence on energy efficiency, but this promoting effect can only be shown when the enterprise performance is positive. The paper clarifies both the impact of artificial intelligence on the energy efficiency of manufacturing enterprises and its mechanism of action; this will help provide a reference for future decision-making designed to improve manufacturing enterprises' energy efficiency.

An automatic method to generate voxel-based absorbed doses from radioactivity distributions for nuclear medicine using generative adversarial networks: a feasibility study.

An approach to autogenerate voxel-based absorbed dose for nuclear medicine is proposed using generative adversarial networks. The method is based on image-to-image transformation and promises to achieve real-time visualization of the absorbed dose and optimization of therapeutic strategies. The activity-density superimposed image is input to generator (G) as a reference image to generate a pseudoabsorbed dose image (DI), which is then mixed with ground truth (GT) DI and recognized by discriminator (D). If the pseudoimage is recognized, the information is fed back, and G regenerates a pseudodose image until D drops to obtain a lifelike DI. As a feasibility study, we used the dose distribution of segmented human anatomy from different sources and activities as training and test datasets. The activity source was assumed to be 1, 2, 3, 4, or 7 subsource blocks. The 3-subsource model was used as the test dataset, and the others were used as the training dataset. The activity distribution in the subsource was assumed to be uniform or heterogeneous (i.e., Gaussian diffusion with sigma 0.0, 0.3, or 0.6). Differences were assessed by Gamma analysis. Results showed that the same or quasi-inhomogeneity model can well predict the dose distribution of different activity-inhomogeneity. Although the 1-source model was trained with very few datasets, it showed an optimal balance between accuracy and training efficiency. There were offsets in the mean absorbed dose between the predicted and GT, but they all showed a higher Gamma-pass-rate (> 93%) and ~ 10% std.

Systematic Construction and Validation of a Novel Ferroptosis-Related Gene Model for Predicting Prognosis in Cervical Cancer.

Methods: Datasets containing RNA sequencing and corresponding clinical data of cervical cancer patients were obtained from searching publicly accessible databases. The "NMF" R package was conducted to calculate the matrix of the screened prognosis gene expression. Ferroptosis-related differential genes in cervical cancer were detected using the "limma" R function and WGCNA. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis were conducted to develop a novel prognostic signature. The prediction model was verified by the nomogram integrating clinical characteristics; the GSE44001 dataset was used as an external verification. Then, the immune status and tumor mutation load were explored. Finally, immunohistochemistry as well as quantitative polymerase chain reaction (RT-qPCR) was utilized to ascertain the expression of FRGs. Results: Two molecular subgroups (cluster 1 and cluster 2) with different FRG expression patterns were recognized. A ferroptosis-related model based on 4 genes (VEGFA, CA9, DERL3, and RNF130) was developed through TCGA database to identify the unfavorable prognosis cases. Patients in cluster 1 showed significantly decreased overall survival in contrast with those in cluster 2 (P < 0.05). The LASSO technique and Cox regression analysis were both utilized to establish the independence of the prognostic model. The validity of nomogram prognostic predictions has been well demonstrated for 3- and 5-year survival in both internal and external data validation cohorts. These two subgroups showed striking differences in tumor-infiltrating leukocytes and tumor mutation burden. The low-risk subgroup showed a longer overall survival time with a higher immune cell score and higher tumor mutation rate. Gene functional enrichment analyses revealed predominant enrichment in various tumor-associated signaling pathways. Finally, the expression of each gene was confirmed by immunohistochemistry and RT-qPCR. Conclusion: A novel and comprehensive ferroptosis-related gene model was proposed for cervical cancer which was capable of distinguishing the patients independently with high risk for poor survival, and targeting ferroptosis may represent a promising approach for the treatment of CC.

Efficacy of umbilical cord mesenchymal stem cell transfusion for the treatment of severe AKI: a protocol for a randomised controlled trial.

INTRODUCTION: Acute kidney injury (AKI) is a common and severe clinical problem that is associated with high mortality, a long hospital stays and high healthcare resource consumption. Approximately a quarter of AKI survivors will develop chronic kidney disease. Mesenchymal stem cells (MSCs) are multipotent stem cells with antiapoptotic, immunomodulatory, antioxidative and proangiogenic properties. Therefore, MSCs have been considered as a potential new therapy for the treatment of AKI. Several clinical trials have been performed, but the results have been inconsistent. This trial investigated whether MSCs can improve renal recovery and mortality in patients with severe AKI. METHODS AND ANALYSIS: One hundred subjects suffering from severe AKI will participate in this patient-blinded, randomised, placebo-controlled, parallel design clinical trial. Participants will be randomly assigned to receive two doses of MSCs or placebo (saline) on days 0 and 7. Urinary biomarkers of renal injury and repair will be measured using commercially available ELISA kits. The main outcome measures are changes in renal function levels within the first 28 days following MSC infusion. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of the Chinese PLA General Hospital. The findings of the study will be disseminated through public and scientific channels. TRIAL REGISTRATION NUMBER: NCT04194671.

Ultrasound enhances the therapeutic potential of mesenchymal stem cells wrapped in greater omentum for aristolochic acid nephropathy.

BACKGROUND: Mesenchymal stem cells (MSCs) have been reported to promote regeneration in both subjects with acute kidney injury (AKI) and chronic kidney disease (CKD), but their efficacy remains limited, probably because most of the cells accumulate in the lungs, liver, and spleen after an intravenous infusion. Therefore, ultrasound-guided administration of MSCs represents a possible approach to solve this problem. The greater omentum is used to promote cell survival due to its rich vasculature. We hypothesized that ultrasound-guided administration of MSCs combined with greater omentum might be more curative than currently available approaches. METHODS: In this study, we established an aristolochic acid nephropathy (AAN) model by intraperitoneally administering aristolochic acid I sodium salt (AA-I) at a dose of 5 mg/kg body weight on alternate days for 4 weeks. Subsequently, a laparotomy was performed, and the left kidney from which the capsule had been removed was wrapped with the greater omentum. A dose of 2 × 107 MSCs was injected into the space between the greater omentum and the left kidney. Equal amounts of MSCs were administered under ultrasound guidance every second week for a total of 4 treatments. Mice were sacrificed 4 weeks after surgery. Serum creatinine and blood urea levels were measured to assess renal function. qPCR, Western blot, and histological analyses were conducted to further investigate the therapeutic mechanism of MSCs. RESULTS: Ultrasound-guided injection of MSCs into the greater omentum that surrounds the kidney enriched cells in the kidney region for up to 5 days. Renal function tests indicated that MSCs improved renal function to a great extent, as reflected by decreased blood urea nitrogen and serum creatinine levels. In addition, histological analyses showed that MSCs noticeably attenuated kidney injury, as evidenced by the amelioration of tubular necrosis and peritubular interstitial fibrosis. Mitigation of renal interstitial fibrosis was further confirmed by immunohistochemistry, qPCR, and western blotting after MSC treatment. Moreover, immunofluorescence staining revealed that MSCs alleviated inflammatory responses by increasing the counts of CD206+ cells and decreasing the counts of CD68+ cells. MSC migration was initiated in response to AA-I-treated renal epithelial cells in an in vitro migration assay. CONCLUSIONS: These findings suggested that administration of MSCs into the cavity formed by the injured kidney and the greater omentum under ultrasound guidance improved renal function, attenuated kidney injury, and mitigated renal interstitial fibrosis and inflammatory responses. Thus, this approach might be a safe and effective therapy for CKD.

Electric-field-assisted non-volatile magnetic switching in a magnetoelectronic hybrid structure.

Electric-field (E-field) control of magnetic switching provides an energy-efficient means to toggle the magnetic states in spintronic devices. The angular tunneling magnetoresistance (TMR) of an magnetic tunnel junction (MTJ)/PMN-PT magnetoelectronic hybrid indicates that the angle-dependent switching fields of the free layer can decrease significantly subject to the application of an E-field. In particular, the switching field along the major axis is reduced by 59% from 28.0 to 11.5 Oe as the E-field increases from 0 to 6 kV/cm, while the TMR ratio remains intact. The switching boundary angle decreases (increases) for the parallel (antiparallel) to antiparallel (parallel) state switch, resulting in a shrunk switching window size. The non-volatile and reversible 180° magnetization switching is demonstrated by using E-fields with a smaller magnetic field bias as low as 11.5 Oe. The angular magnetic switching originates from competition among the E-field-induced magnetoelastic anisotropy, magnetic shape anisotropy, and Zeeman energy, which is confirmed by micromagnetic simulations.

Comparison of defense responses of transgenic potato lines expressing three different Rpi genes to specific Phytophthora infestans races based on transcriptome profiling.

Potato late blight, one of the most devastating diseases in potato, is caused by the oomycete Phytophthora infestans. Over 20 resistance genes have been cloned including R1, R3a, and R3b. The distinctions between defense response mechanisms mediated by different resistance genes are still unclear. Here we performed transcriptome profiling in three transgenic lines, R1, R3a, and R3b, and wild-type Desiree under inoculation with two P. infestans isolates, 89148 (race 0) and CN152 (super race), using RNA-seq. Compared with wild type, specific differentially expressed genes (DEGs) were identified in the three transgenic lines. The highest number of DEGs occurred in transgenic R3b, with 779 DEGs in response to isolate 89148 and 864 DEGs in response to infection by CN152, followed by transgenic R1 lines with 408 DEGs for isolate 89148 and 267 DEGs for CN152. Based on gene ontology, the most common GO terms (15 for 89148 and 20 for CN152) were enriched in transgenic R3a and R3b lines. This indicates that the defense pathways mediated by R3a and R3b are more similar than those mediated by R1. Further separate GO analysis of up- or down-regulated DEGs showed that the down-regulated DEGs mainly functioned in mediating the resistance of potato to P. infestans 89148 by response to stress biological process and to CN152 by oxidation reduction biological process. KEGG pathways of DNA replication, plant-pathogen interaction and pentose and glucuronate interconversions are unique for transgenic R1, R3a, and R3b lines in incompatible interactions. Quantitative real-time PCR experimental validation confirmed the induced expression of DEGs in the late blight resistance signaling pathway. Our results will lay a solid foundation for further understanding the mechanisms of plant-pathogen interactions, and provide a theoretical reference for durable resistance in potato.