Promotion of apoplastic oxidative burst by artificially selected GhCBSX3A enhances Verticillium dahliae resistance in upland cotton.

Verticillium wilt (VW) is a devasting disease affecting various plants, including upland cotton, a crucial fiber crop. Despite its impact, the genetic basis underlying cotton's susceptibility or defense against VW remains unclear. Here, we conducted a genome-wide association study on VW phenotyping in upland cotton and identified a locus on A13 that is significantly associated with VW resistance. We then identified a cystathionine ß-synthase domain gene at A13 locus, GhCBSX3A, which was induced by Verticillium dahliae. Functional analysis, including expression silencing in cotton and overexpression in Arabidopsis thaliana, confirmed that GhCBSX3A is a causal gene at the A13 locus, enhancing SAR-RBOHs-mediated apoplastic oxidative burst. We found allelic variation on the TATA-box of GhCBSX3A promoter attenuated its expression in upland cotton, thereby weakening VW resistance. Interestingly, we discovered that altered artificial selection of GhCBSX3A_R (an elite allele for VW) under different VW pressures during domestication and other improved processes allows specific human needs to be met. Our findings underscore the importance of GhCBSX3A in response to VW, and we propose a model for defense-associated genes being selected depending on the pathogen's pressure. The identified locus and gene serve as promising targets for VW resistance enhancement in cotton through genetic engineering.

A Visual Pathway into Central Complex for High-Frequency Motion-Defined Bars in Drosophila.

Relative motion breaks a camouflaged target from a same-textured background, thus eliciting discrimination of a motion-defined object. Ring (R) neurons are critical components in the Drosophila central complex, which has been implicated in multiple visually guided behaviors. Using two-photon calcium imaging with female flies, we demonstrated that a specific population of R neurons that innervate the superior domain of bulb neuropil, termed superior R neurons, encoded a motion-defined bar with high spatial frequency contents. Upstream superior tuberculo-bulbar (TuBu) neurons transmitted visual signals by releasing acetylcholine within synapses connected with superior R neurons. Blocking TuBu or R neurons impaired tracking performance of the bar, which reveals their importance in motion-defined feature encoding. Additionally, the presentation of a low spatial frequency luminance-defined bar evoked consistent excitation in R neurons of the superior bulb, whereas either excited or inhibited responses were evoked in the inferior bulb. The distinct properties of the responses to the two bar stimuli indicate there is a functional division between the bulb subdomains. Moreover, physiological and behavioral tests with restricted lines suggest that R4d neurons play a vital role in tracking motion-defined bars. We conclude that the central complex receives the motion-defined features via a visual pathway from superior TuBu to R neurons and might encode different visual features via distinct response patterns at the population level, thereby driving visually guided behaviors.SIGNIFICANCE STATEMENT Animals could discriminate a motion-defined object that is indistinguishable with a same-textured background until it moves, but little is known about the underlying neural mechanisms. In this study, we identified that R neurons and their upstream partners, TuBu neurons, innervating the superior bulb of Drosophila central brain are involved in the discrimination of high-frequency motion-defined bars. Our study provides new evidence that R neurons receive multiple visual inputs from distinct upstream neurons, indicating a population coding mechanism for the fly central brain to discriminate diverse visual features. These results build progress in unraveling neural substrates for visually guided behaviors.

A potassium-chloride co-transporter with altered genome architecture functions as a suppressor in glioma.

Gliomas, the most lethal tumours in brain, have a poor prognosis despite accepting standard treatment. Limited benefits from current therapies can be attributed to genetic, epigenetic and microenvironmental cues that affect cell programming and drive tumour heterogeneity. Through the analysis of Hi-C data, we identified a potassium-chloride co-transporter SLC12A5 associated with disrupted topologically associating domain which was downregulated in tumour tissues. Multiple independent glioma cohorts were included to analyse the characterization of SLC12A5 and found it was significantly associated with pathological features, prognostic value, genomic alterations, transcriptional landscape and drug response. We constructed two SLC12A5 overexpression cell lines to verify the function of SLC12A5 that suppressed tumour cell proliferation and migration in vitro. In addition, SLC12A5 was also positively associated with GABAA receptor activity and negatively associated with pro-tumour immune signatures and immunotherapy response. Collectively, our study provides a comprehensive characterization of SLC12A5 in glioma and supports SLC12A5 as a potential suppressor of disease progression.

Acetylation of GhCaM7 enhances cotton resistance to Verticillium dahliae.

Protein lysine acetylation is an important post-translational modification mechanism involved in cellular regulation in eukaryotes. Calmodulin (CaM) is a ubiquitous Ca2+ sensor in eukaryotes and is crucial for plant immunity, but it is so far unclear whether acetylation is involved in CaM-mediated plant immunity. Here, we found that GhCaM7 is acetylated upon Verticillium dahliae (V. dahliae) infection and a positive regulator of V. dahliae resistance. Overexpressing GhCaM7 in cotton and Arabidopsis enhances V. dahliae resistance and knocking-down GhCaM7 makes cotton more susceptible to V. dahliae. Transgenic Arabidopsis plants overexpressing GhCaM7 with mutation at the acetylation site are more susceptible to V. dahliae than transgenics overexpressing the wild-type GhCaM7, implying the importance of the acetylated GhCaM7 in response to V. dahliae infection. Yeast two-hybrid, bimolecular fluorescent complementation, luciferase complementation imaging, and coimmunoprecipitation assays demonstrated interaction between GhCaM7 and an osmotin protein GhOSM34 that was shown to have a positive role in V. dahliae resistance. GhCaM7 and GhOSM34 are co-localized in the cell membrane. Upon V. dahliae infection, the Ca2+ content reduces almost instantly in plants with downregulated GhCaM7 or GhOSM34. Down regulating GhOSM34 enhances accumulation of Na+ and increases cell osmotic pressure. Comparative transcriptomic analyses between cotton plants with an increased or reduced expression level of GhCaM7 and wild-type plants indicate the involvement of jasmonic acid signaling pathways and reactive oxygen species in GhCaM7-enabled disease resistance. Together, these results demonstrate the involvement of CaM protein in the interaction between cotton and V. dahliae, and more importantly, the involvement of the acetylated CaM in the interaction.

Comparative chloroplast-specific SNP and nSCoT markers analysis and population structure study in kiwifruit plants.

BACKGROUND: Kiwifruit (Actinidiaceae family) is an economically important fruit tree in China and New Zealand. It is a typical dioecious plant that has undergone frequent natural hybridization, along with chromosomal ploidy diversity within the genus Actinidia, resulting in higher genetic differences and horticultural diversity between interspecific and intraspecific traits. This diversity provides a rich genetic base for breeding. China is not only the original center of speciation for the Actinidia genus but also its distribution center, housing the most domesticated species: A. chinensis var. chinensis, A. chinensis var. deliciosa, A. arguta, and A. polygama. However, there have been relatively few studies on the application of DNA markers and the genetic basis of kiwifruit plants. By combining information from chloroplast-specific SNPs and nuclear SCoT (nSCoT) markers, we can uncover complementary aspects of genetic variation, population structure, and evolutionary relationships. In this study, one chloroplast DNA (cpDNA) marker pair was selected out of nine cpDNA candidate pairs. Twenty nSCoT markers were selected and used to assess the population structure and chloroplast-specific DNA haplotype diversity in 55 kiwifruit plants (Actinidia), including 20 samples of A. chinensis var. chinensis, 22 samples of A. chinensis var. deliciosa, 11 samples of A. arguta, and two samples of A. polygama, based on morphological observations collected from China. RESULTS: The average genetic distance among the 55 samples was 0.26 with chloroplast-specific SNP markers and 0.57 with nSCoT markers. The Mantel test revealed a very small correlation (r = 0.21). The 55 samples were categorized into different sub-populations using Bayesian analysis, the Unweighted Pair Group Method with the Arithmetic Mean (UPGMA), and the Principal Component Analysis (PCA) method, respectively. Based on the analysis of 205 variable sites, a total of 15 chloroplast-specific DNA haplotypes were observed, contributing to a higher level of polymorphism with an Hd of 0.78. Most of the chloroplast-specific DNA haplotype diversity was distributed among populations, but significant diversity was also observed within populations. H1 was shared by 24 samples, including 12 of A. chinensis var. chinensis and 12 of A. chinensis var. deliciosa, indicating that H1 is an ancient and dominant haplotype among the 55 chloroplast-specific sequences. H2 may not have evolved further.The remaining haplotypes were rare and unique, with some appearing to be exclusive to a particular variety and often detected in single individuals. For example, the H15 haplotype was found exclusively in A. polygama. CONCLUSION: The population genetic variation explained by chloroplast-specific SNP markers has greater power than that explained by nSCoTs, with chloroplast-specific DNA haplotypes being the most efficient. Gene flow appears to be more evident between A. chinensis var. chinensis and A. chinensis var. deliciosa, as they share chloroplast-specific DNA haplotypes, In contrast, A.arguta and A. polygama possess their own characteristic haplotypes, derived from the haplotype of A. chinensis var. chinensis. Compared with A. chinensis, the A.arguta and A. polygama showed better grouping. It also seems crucial to screen out, for each type of molecular marker, especially haplotypes, the core markers of the Actinidia genus.

Artificial Intelligence-Based Microfluidic Platform for Detecting Contaminants in Water: A Review.

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed.

Enrichment of Trypsin Inhibitor from Soybean Whey Wastewater Using Different Precipitating Agents and Analysis of Their Properties.

Recovering valuable active substances from the by-products of agricultural processing is a crucial concern for scientific researchers. This paper focuses on the enrichment of soybean trypsin inhibitor (STI) from soybean whey wastewater using either ammonium sulfate salting or ethanol precipitation, and discusses their physicochemical properties. The results show that at a 60% ethanol content, the yield of STI was 3.983 mg/mL, whereas the yield was 3.833 mg/mL at 60% ammonium sulfate saturation. The inhibitory activity of STI obtained by ammonium sulfate salting out (A-STI) was higher than that obtained by ethanol precipitation (E-STI). A-STI exhibited better solubility than E-STI at specific temperatures and pH levels, as confirmed by turbidity and surface hydrophobicity measurements. Thermal characterization revealed that both A-STI and E-STI showed thermal transition temperatures above 90 °C. Scanning electron microscopy demonstrated that A-STI had a smooth surface with fewer pores, while E-STI had a rough surface with more pores. In conclusion, there was no significant difference in the yield of A-STI and E-STI (p < 0.05); however, the physicochemical properties of A-STI were superior to those of E-STI, making it more suitable for further processing and utilization. This study provides a theoretical reference for the enrichment of STI from soybean whey wastewater.

[BMP]+[BF4]--Modified CsPbI1.2Br1.8 Solar Cells with Improved Efficiency and Suppressed Photoinduced Phase Segregation.

With the rapid progress in a power conversion efficiency reaching up to 26.1%, which is among the highest efficiency for single-junction solar cells, organic-inorganic hybrid perovskite solar cells have become a research focus in photovoltaic technology all over the world, while the instability of these perovskite solar cells, due to the decomposition of its unstable organic components, has restricted the development of all-inorganic perovskite solar cells. In recent years, Br-mixed halogen all-inorganic perovskites (CsPbI3-xBrx) have aroused great interests due to their ability to balance the band gap and phase stability of pure CsPbX3. However, the photoinduced phase segregation in lead mixed halide perovskites is still a big burden on their practical industrial production and commercialization. Here, we demonstrate inhibited photoinduced phase segregation all-inorganic CsPbI1.2Br1.8 films and their corresponding perovskite solar cells by incorporating a 1-butyl-1-methylpiperidinium tetrafluoroborate ([BMP]+[BF4]-) compound into the CsPbI1.2Br1.8 films. Then, its effect on the perovskite films and the corresponding hole transport layer-free CsPbI1.2Br1.8 solar cells with carbon electrodes under light is investigated. With a prolonged time added to the reduced phase segregation terminal, this additive shows an inhibitory effect on the photoinduced phase segregation phenomenon for perovskite films and devices with enhanced cell efficiency. Our study reveals an efficient and simple route that suppresses photoinduced phase segregation in cesium lead mixed halide perovskite solar cells with enhanced efficiency.

Discovery of Alloy Catalysts Beyond Pd for Selective Hydrogenation of Reformate via First-Principle Screening with Consideration of H-Coverage.

The highly selective hydrogenation to remove olefins is a significant refining approach for the reformate. Herein, a library of transition metal for reformate hydrogenation is tested experimentally to validate the predictive level of catalytic activity from our theoretical framework, which combines ab initio calculations and microkinetic modeling, with consideration of surface H-coverage effect on hydrogenation kinetics. The favorable H coverage of specific alloy surface under relevant hydrogenation condition, is found to be determined by its corresponding alloy composition. Besides, olefin hydrogenation rate is determined as a function of two descriptors, i.e. H coverage and binding energies of atomic hydrogen, paving the way to computationally screen on metal component in the periodic table. Evaluation of 172 bimetallic alloys based on the activity volcano map, as well as benzene hydrogenation rate, identifies prospective superior candidates and experimentally confirms that Zn3Ir1 outperforms pure Pd catalysts for the selective hydrogenation refining of reformate. The insights into H-coverage-related microkinetic modelling have enabled us to both theoretically understand experimental findings and identify novel catalysts, thus, bridging the gap between first-principle simulations and industrial applications. This work provides useful guidance for experimental catalyst design, which can be easily extended to other hydrogenation reaction.

Integration of single-cell regulon atlas and multi-omics data for prognostic stratification and personalized treatment prediction in human lung adenocarcinoma.

Transcriptional programs are often dysregulated in cancers. A comprehensive investigation of potential regulons is critical to the understanding of tumorigeneses. We first constructed the regulatory networks from single-cell RNA sequencing data in human lung adenocarcinoma (LUAD). We next introduce LPRI (Lung Cancer Prognostic Regulon Index), a precision oncology framework to identify new biomarkers associated with prognosis by leveraging the single cell regulon atlas and bulk RNA sequencing or microarray datasets. We confirmed that LPRI could be a robust biomarker to guide prognosis stratification across lung adenocarcinoma cohorts. Finally, a multi-omics data analysis to characterize molecular alterations associated with LPRI was performed from The Cancer Genome Atlas (TCGA) dataset. Our study provides a comprehensive chart of regulons in LUAD. Additionally, LPRI will be used to help prognostic prediction and developing personalized treatment for future studies.

Uncovering genomic and transcriptional variations facilitates utilization of wild resources in cotton disease resistance improvement.

BACKGROUND: Upland cotton wild/landraces represent a valuable resource for disease resistance alleles. Genetic differentiation between genotypes, as well as variation in Verticillium wilt (VW) resistance, has been poorly characterized for upland cotton accessions on the domestication spectrum (from wild/landraces to elite lines). RESULTS: To illustrate the effects of modern breeding on VW resistance in upland cotton, 37 wild/landraces were resequenced and phenotyped for VW resistance. Genomic patterns of differentiation were identified between wild/landraces and improved upland cotton, and a significant decline in VW resistance was observed in association with improvement. Four genotypes representing different degrees of improvement were used in a full-length transcriptome analysis to study the genetic basis of VW resistance. ROS signaling was highly conserved at the transcriptional level, likely providing the basis for VW resistance in upland cotton. ASN biosynthesis and HSP90-mediated resistance moderated the response to VW in wild/landraces, and loss of induction activity of these genes resulted in VW susceptibility. The observed genomic differentiation contributed to the loss of induction of some important VW resistance genes such as HSP90.4 and PR16. CONCLUSIONS: Besides providing new insights into the evolution of upland cotton VW resistance, this study also identifies important resistance pathways and genes for both fundamental research and cotton breeding.

RNA-targeted small-molecule drug discoveries: a machine-learning perspective.

In the past two decades, machine learning (ML) has been extensively adopted in protein-targeted small molecule (SM) discovery. Once trained, ML models could exert their predicting abilities on large volumes of molecules within a short time. However, applying ML approaches to discover RNA-targeted SMs is still in its early stages. This is primarily because of the intrinsic structural instability of RNA molecules that impede the structure-based screening or designing of RNA-targeted SMs. Recently, with more studies revealing RNA structures and a growing number of RNA-targeted ligands being identified, it resulted in an increased interest in the field of drugging RNA. Undeniably, intracellular RNA is much more abundant than protein and, if successfully targeted, will be a major alternative target for therapeutics. Therefore, in this context, as well as under the premise of having RNA-related research data, ML-based methods can get involved in improving the speed of traditional experimental processes. [Figure: see text].

Paired dCas9 design as a nucleic acid detection platform for pathogenic strains.

The wide application of molecular beacon probes in specific DNA detection, especially in the fast prototyping of pathogen DNA detection kits in point-of-care diagnostics, has been hindered by the nonflexible choice of target sequences and the unstable fluorophore output. We developed an in vitro DNA detection system consisting of a pair of dCas9 proteins linked to split halves of luciferase, named the Paired dCas9 (PC) reporter. Co-localization of the reporter pair to a ~46 bp target sequence defined by two single guide RNAs (sgRNAs) activated luciferase which subsequently generated highly intensified luminescent signals. Combined with an array design and statistical analyses, the PC reporter system could be programmed to access sequence information across the entire genome of the pathogenic Mycobacterium tuberculosis H37Rv strain. These findings suggest great potential for the PC reporter in effective and affordable in vitro nucleic acid detection technologies. In this article we highlighted the systems design from our previous researchworkon the PC reporter (Zhang et al, 2015)with a focuson methodology.

Functional divergence of GLP genes between G. barbadense and G. hirsutum in response to Verticillium dahliae infection.

Germin-like proteins (GLPs) play important roles in plant disease resistance but are rarely reported in cotton. We compared the expression of GLPs in Verticillium dahliae inoculate G. hirsutum (susceptible) and G. barbadense (resistant) and enriched 11 differentially expressed GLPs. 2741 GLP proteins identified from 53 species determined that GLP probably originated from algae and could be classified into 7 clades according to phylogenetic analysis, among which Clade I is likely the most ancient. Cotton GLP (two allopolyploids and two diploids) genes within a shared clade were highly conserved. Intriguingly, clade VII genes were mainly located in gene clusters that derived from the expansion of LTR transposons. Clade VII members expressed mainly in root which is the first battle against Verticillium dahlia and could be induced more intensely in G. barbadense than G. hirsutum. The GLP genes are resistant to Verticillium dahliae, which can be further investigated against Verticillium wilt.

The Performance Characterization and Optimization of Fiber-Optic Acoustic Pressure Sensors Based on the MOEMS Sensitized Structure.

In order to investigate the factors affecting the acoustic performance of the extrinsic Fabry-Perot interferometer (EFPI) fiber-optic acoustic pressure sensor and to effectively improve its detection capability, this paper enhances the sensor's detection sensitivity by adding more sensitized rings to its acoustic pressure-sensitive film. Furthermore, a novel real-time coupled acoustic test method is proposed to simultaneously monitor the changes in the spectral and acoustic metrics of the sensor to characterize its overall performance. Finally, an EFPI-type fiber-optic acoustic pressure sensor was developed based on the Micro-Optical Electro-Mechanical System (MOEMS). The acoustic tests indicate that the optimized fiber-optic acoustic pressure sensor has a sensitivity as high as 2253.2 mV/Pa, and the acoustic overload point (AOP) and signal-to-noise ratios (SNRs) can reach 108.85 dB SPL and 79.22 dB, respectively. These results show that the sensor produced through performance characterization experiments and subsequent optimization has a very high acoustic performance index, which provides a scientific theoretical basis for improving the overall performance of the sensor and will have broad application prospects in the field of acoustic detection.

Circular RNA CircCDKN2B-AS_006 Promotes the Tumor-like Growth and Metastasis of Rheumatoid Arthritis Synovial Fibroblasts by Targeting the miR-1258/RUNX1 Axis.

Rheumatoid arthritis (RA) is an autoimmune polyarthritis in which synovial fibroblasts (SFs) play a major role in cartilage and bone destruction through tumor-like proliferation, migration, and invasion. Circular RNAs (circRNAs) have emerged as vital regulators for tumor progression. However, the regulatory role, clinical significance, and underlying mechanisms of circRNAs in RASF tumor-like growth and metastasis remain largely unknown. Differentially expressed circRNAs in synovium samples from patients with RA and patients with joint trauma were identified via RNA sequencing. Subsequently, in vitro and in vivo experiments were performed to investigate the functional roles of circCDKN2B-AS_006 in RASF proliferation, migration, and invasion. CircCDKN2B-AS_006 was upregulated in synovium samples from patients with RA and promoted the tumor-like proliferation, migration, and invasion of RASFs. Mechanistically, circCDKN2B-AS_006 was shown to regulate the expression of runt-related transcription factor 1 (RUNX1) by sponging miR-1258, influencing the Wnt/ß-catenin signaling pathway, and promoting the epithelial-to-mesenchymal transition (EMT) in RASFs. Moreover, in the collagen-induced arthritis (CIA) mouse model, intra-articular injection of lentivirus-shcircCDKN2B-AS_006 was capable of alleviating the severity of arthritis and inhibiting the aggressive behaviors of SFs. Furthermore, the correlation analysis results revealed that the circCDKN2B-AS_006/miR-1258/RUNX1 axis in the synovium was correlated with the clinical indicators of RA patients. CircCDKN2B-AS_006 promoted the proliferation, migration, and invasion of RASFs by modulating the miR-1258/RUNX1 axis.

Tracking groundwater pollution plumes at landfill sites using borehole hydrochemical and hydrodynamic profile (BHHP) method.

Groundwater pollution at landfill sites poses a significant risk to human health and ecological security. However, efficiently tracking pollution plumes in a polluted aquifer with variable pollutants remains challenging. In order to track groundwater pollution plumes at landfill sites, an in-situ borehole hydrochemical and hydrodynamic profile (BHHP) method was developed. Total dissolved solids (TDS), oxidation-reduction potential (ORP), and ammonia nitrogen were selected as the hydrochemical indicators. Meanwhile, the hydrodynamic indicators included flow direction and flow velocity of groundwater. Among the three hydrochemical indicators, TDS and ORP were analyzed to be the prior alternative ones for the BHHP application. The BHHP method was successfully applied to track groundwater pollution plumes at a typical valley-type landfill site and its neighboring downstream zone. Consequently, four groundwater pollution plumes of different types and different scales were identified in both horizontal and vertical directions within the depth of 0-50 m, and the various pollution sources for the detected pollution plumes were revealed. Furthermore, the BHHP method was validated using sampling test results of groundwater chloride and chemical oxygen demand at the surveyed landfill site.

Recent progression and future perspectives in cotton genomic breeding.

Upland cotton is an important global cash crop for its long seed fibers and high edible oil and protein content. Progress in cotton genomics promotes the advancement of cotton genetics, evolutionary studies, functional genetics, and breeding, and has ushered cotton research and breeding into a new era. Here, we summarize high-impact genomics studies for cotton from the last 10 years. The diploid Gossypium arboreum and allotetraploid Gossypium hirsutum are the main focus of most genetic and genomic studies. We next review recent progress in cotton molecular biology and genetics, which builds on cotton genome sequencing efforts, population studies, and functional genomics, to provide insights into the mechanisms shaping abiotic and biotic stress tolerance, plant architecture, seed oil content, and fiber development. We also suggest the application of novel technologies and strategies to facilitate genome-based crop breeding. Explosive growth in the amount of novel genomic data, identified genes, gene modules, and pathways is now enabling researchers to utilize multidisciplinary genomics-enabled breeding strategies to cultivate "super cotton", synergistically improving multiple traits. These strategies must rise to meet urgent demands for a sustainable cotton industry.

Endophytic fungi of Lycium barbarum: isolation, determination, bioactivity and separation of compounds.

Lycium barbarum is widely distributed in China and used as a traditional Chinese medicine herb to treat dizziness, abdominal pain, dry cough, headache and fatigue. Several studies have examined the endophytes of L. barbarum from northwest China; however, few have focused on that from eastern China. The objective of this study was to isolate and determine the endophytic fungi of L. barbarum from Shandong province, as well as to obtain and identify active secondary metabolites from the endophytes. In this study, 17 endophytic fungi were isolated from L. barbarum and denoted as GQ-1 to GQ-17, respectively. These fungi were further classified into ten genera based on the morphological and ITS identification. The crude extracts of these fungi were obtained by using liquid fermentation and EtOAc extraction, and their antibacterial, cytotoxic, and antioxidant activities were evaluated. The results showed that GQ-6 and GQ-16 exhibited high inhibitory activity; GQ-6 and GQ-9 showed high cytotoxic activity and GQ-5 exhibited high scavenging capability for DPPH free radicals. Additionally, Cladosporium sp. GQ-6 was used to investigate the secondary metabolites. The crude extracts were purified by using column chromatography, reverse column, and liquid chromatography, and four monomeric compounds were identified, including two known compounds (α-acetylorcinol (1) and cladosporester B (2)) and two new compounds (cladosporacid F (3) and cladosporester D (4)). The anti-fungal and antibacterial activities of these compounds were confirmed, but no cytotoxic activity was observed. In conclusion, endophytic fungi of L. barbarum from eastern China can serve as a potential source of active natural products with antibacterial and antioxidant properties.

Estrogen antagonizes ASIC1a-induced chondrocyte mitochondrial stress in rheumatoid arthritis.

BACKGROUND: Destruction of articular cartilage and bone is the main cause of joint dysfunction in rheumatoid arthritis (RA). Acid-sensing ion channel 1a (ASIC1a) is a key molecule that mediates the destruction of RA articular cartilage. Estrogen has been proven to have a protective effect against articular cartilage damage, however, the underlying mechanisms remain unclear. METHODS: We treated rat articular chondrocytes with an acidic environment, analyzed the expression levels of mitochondrial stress protein HSP10, ClpP, LONP1 by q-PCR and immunofluorescence staining. Transmission electron microscopy was used to analyze the mitochondrial morphological changes. Laser confocal microscopy was used to analyze the Ca2+, mitochondrial membrane potential (Δψm) and reactive oxygen species (ROS) level. Moreover, ASIC1a specific inhibitor Psalmotoxin 1 (Pctx-1) and Ethylene Glycol Tetraacetic Acid (EGTA) were used to observe whether acid stimulation damage mitochondrial function through Ca2+ influx mediated by ASIC1a and whether pretreatment with estrogen could counteract these phenomena. Furthermore, the ovariectomized (OVX) adjuvant arthritis (AA) rat model was treated with estrogen to explore the effect of estrogen on disease progression. RESULTS: Our results indicated that HSP10, ClpP, LONP1 protein and mRNA expression and mitochondrial ROS level were elevated in acid-stimulated chondrocytes. Moreover, acid stimulation decreased mitochondrial membrane potential and damaged mitochondrial structure of chondrocytes. Furthermore, ASIC1a specific inhibitor PcTx-1 and EGTA inhibited acid-induced mitochondrial abnormalities. In addition, estrogen could protect acid-stimulated induced mitochondrial stress by regulating the activity of ASIC1a in rat chondrocytes and protects cartilage damage in OVX AA rat. CONCLUSIONS: Extracellular acidification induces mitochondrial stress by activating ASIC1a, leading to the damage of rat articular chondrocytes. Estrogen antagonizes acidosis-induced joint damage by inhibiting ASIC1a activity. Our study provides new insights into the protective effect and mechanism of action of estrogen in RA.