Unveiling Microbial Nitrogen Metabolism in Rivers using a Machine Learning Approach.

Microbial nitrogen metabolism is a complicated and key process in mediating environmental pollution and greenhouse gas emissions in rivers. However, the interactive drivers of microbial nitrogen metabolism in rivers have not been identified. Here, we analyze the microbial nitrogen metabolism patterns in 105 rivers in China driven by 26 environmental and socioeconomic factors using an interpretable causal machine learning (ICML) framework. ICML better recognizes the complex relationships between factors and microbial nitrogen metabolism than traditional linear regression models. Furthermore, tipping points and concentration windows were proposed to precisely regulate microbial nitrogen metabolism. For example, concentrations of dissolved organic carbon (DOC) below tipping points of 6.2 and 4.2 mg/L easily reduce bacterial denitrification and nitrification, respectively. The concentration windows for NO3--N (15.9-18.0 mg/L) and DOC (9.1-10.8 mg/L) enabled the highest abundance of denitrifying bacteria on a national scale. The integration of ICML models and field data clarifies the important drivers of microbial nitrogen metabolism, supporting the precise regulation of nitrogen pollution and river ecological management.

Identification of ADAM23 as a Potential Signature for Psoriasis Using Integrative Machine-Learning and Experimental Verification.

Background: Psoriasis is a common chronic, recurrent, and inflammatory skin disease. Identifying novel and potential biomarkers is valuable in the treatment and diagnosis of psoriasis. The goal of this study was to identify novel key biomarkers of psoriasis and analyze the potential underlying mechanisms. Methods: Psoriasis-related datasets were downloaded from the Gene Expression Omnibus database to screen differential genes in the datasets. Functional and pathway enrichment analyses were performed on the differentially expressed genes (DEGs). Candidate biomarkers for psoriasis were identified from the GSE30999 and GSE6710 datasets using four machine learning algorithms, namely, random forest (RF), least absolute shrinkage and selection operator (LASSO) logistic regression, weighted gene co-expression network analysis (WGCNA), and support vector machine recursive feature elimination (SVM-RFE), and were validated using the GSE41662 dataset. Next, we used CIBERSORT and single-cell RNA analysis to explore the relationship between ADAM23 and immune cells. Finally, we validated the expression of the identified biomarkers expressions in human and mouse experiments. Results: A total of 709 overlapping DEGs were identified, including 426 upregulated and 283 downregulated genes. Enhanced by enrichment analysis, the differentially expressed genes (DEGs) were spatially arranged in relation to immune cell involvement, immune-activating processes, and inflammatory signals. Based on the enrichment analysis, the DEGs were mapped to immune cell involvement, immune-activating processes, and inflammatory signals. Four machine learning strategies and single-cell RNA sequencing analysis showed that ADAM23, a disintegrin and metalloprotease, may be a unique, critical biomarker with high diagnostic accuracy for psoriasis. Based on CIBERSORT analysis, ADAM23 was found to be associated with a variety of immune cells, such as macrophages and mast cells, and it was upregulated in the macrophages of psoriatic lesions in patients and mice. Conclusion: ADAM23 may be a potential biomarker in the diagnosis of psoriasis and may contribute to the pathogenesis by regulating immunological activity in psoriatic lesions.

Subthreshold Depression: A Systematic Review and Network Meta-Analysis of Non-Pharmacological Interventions.

Background: Subthreshold depression (StD) is considered to be the "precursor" stage of major depressive disorder (MDD), which could cause higher risk of suicide, disease burden and functional impairment. There have been various non-pharmacological interventions for StD. However, the comparison of their effectiveness still lacks sufficient evidence. We performed a systematic review and network meta-analysis to evaluate and rank the efficacy of multiple non-pharmacological interventions targeting StD. Methods: We conducted a thorough search across various databases including PubMed, Medline, Embase, Web of Science and PsycINFO from inception to December 2022. All included studies were randomized controlled trials (RCTs) of non-pharmacological interventions for patients with StD compared with control group (CG). Several universal scales for measuring depression severity were used as efficacy outcomes. The surface under the cumulative ranking curve (SUCRA) was used to separately rank each intervention using the "Stata 17.0" software. Results: A total of thirty-six trials were included, involving twenty-eight interventions and 7417 participants. The research found that most non-pharmacological interventions were superior to controls for StD. In each outcome evaluation by different scales for measuring depression, psychotherapy always ranked first in terms of treatment effectiveness, especially Problem-solving Therapy (PST), Behavioral Activation Therapy (BAT), Cognitive Behavioral Therapy (CBT)/Internet-based CBT (I-CBT)/Telephone-based CBT (T-CBT). Since different groups could not be directly compared, the total optimal intervention could not be determined. Conclusion: Here, we show that psychotherapy may be the better choice for the treatment of StD. This study provides some evidence on StD management selection for clinical workers. However, to establish its intervention effect more conclusively, the content, format and operators of psychotherapy still require extensive exploration to conduct more effective, convenient and cost-effective implementation in primary healthcare. Notably, further research is also urgently needed to find the biological and neural mechanisms of StD by examining whether psychotherapy alters neuroplasticity in patients with StD.

CircPTPN22 modulates T-cell activation by sponging miR-4689 to regulate S1PR1 expression in patients with systemic lupus erythematosus.

BACKGROUND: Circular RNAs are involved in autoimmune disease pathogenesis. Our previous study indicated that circPTPN22 is involved in autoimmune diseases, such as systemic lupus erythematosus (SLE) and rheumatoid arthritis, but the underlying mechanisms remain unclear. METHODS: First, the expression of circPTPN22 was detected by real-time PCR and western blotting. After overexpression or knockdown of circPTPN22, the proliferation of Jurkat cells was detected by the CCK-8 assay, and the apoptosis of Jurkat cells was detected by flow cytometry. In addition, the relationship between circPTPN22-miR-4689-S1PR1 was confirmed by bioinformatic analyses, fluorescence in situ hybridization assays, RNA-binding protein immunoprecipitation, and dual luciferase reporter assays. RESULTS: We found that circPTPN22 expression was downregulated in the PBMCs of SLE patients compared to those of healthy controls. Overexpression of circPTPN22 increased proliferation and inhibited apoptosis of Jurkat T cells, whereas knockdown of circPTPN22 exerted the opposite effects. CircPTPN22 acts as a miR-4689 sponge, and S1PR1 is a direct target of miR-4689. Importantly, the circPTPN22/miR-4689/S1PR1 axis inhibited the secretion of TNF-α and IL-6 in Jurkat T cells. CONCLUSIONS: CircPTPN22 acts as a miR-4689 sponge to regulate T-cell activation by targeting S1PR1, providing a novel mechanism for the pathogenesis of SLE.

Featured immune characteristics of COVID-19 and systemic lupus erythematosus revealed by multidimensional integrated analyses.

BACKGROUND: Coronavirus disease 2019 (COVID-19) shares similar immune characteristics with autoimmune diseases like systemic lupus erythematosus (SLE). However, such associations have not yet been investigated at the single-cell level. METHODS: We integrated and analyzed RNA sequencing results from different patients and normal controls from the GEO database and identified subsets of immune cells that might involve in the pathogenesis of SLE and COVID- 19. We also disentangled the characteristic alterations in cell and molecular subset proportions as well as gene expression patterns in SLE patients compared with COVID-19 patients. RESULTS: Key immune characteristic genes (such as CXCL10 and RACK1) and multiple immune-related pathways (such as the coronavirus disease-COVID-19, T-cell receptor signaling, and MIF-related signaling pathways) were identified. We also highlighted the differences in peripheral blood mononuclear cells (PBMCs) between SLE and COVID-19 patients. Moreover, we provided an opportunity to comprehensively probe underlying B-cell‒cell communication with multiple ligand-receptor pairs (MIF-CD74+CXCR4, MIF-CD74+CD44) and the differentiation trajectory of B-cell clusters that is deemed to promote cell state transitions in COVID-19 and SLE. CONCLUSIONS: Our results demonstrate the immune response differences and immune characteristic similarities, such as the cytokine storm, between COVID-19 and SLE, which might pivotally function in the pathogenesis of the two diseases and provide potential intervention targets for both diseases.

Highly active complexes of pyrite and organic matter regulate arsenic fate.

Arsenic (As) presents high toxicity and strong carcinogenicity, and its health risks are regulated by its oxidation state and speciation. As can form complexes with the surface of minerals or organic matter through adsorption, affecting its toxicity and bioavailability. However, the regulation effect of the interaction of coexisting minerals and organic matter on As fate remains largely unknown. Here, we discovered that minerals (e.g., pyrite) and organic matter (e.g., alanyl glutamine, AG) can form pyrite-AG complexes, promoting As(III) oxidation under simulated solar irradiation. The formation of pyrite-AG was explored in terms of the interaction of surface oxygen atoms, electron transfer and crystal surface changes. From the perspective of atoms and molecules, pyrite-AG showed more oxygen vacancies, stronger reactive oxygen species (ROS) and a higher electron transport capacity than pyrite alone. Compared with pyrite, pyrite-AG effectively promoted the conversion of highly toxic As(III) to less toxic As(V) due to the enhanced photochemical properties. Moreover, quantification and capture of ROS confirmed that hydroxyl radicals (•OH) played an important role in As(III) oxidation in the pyrite-AG and As(III) system. Our results provide previously unidentified perspectives on the effects and chemical mechanisms of highly active complexes of mineral and organic matter on As fate and provide new insights into the risk assessment and control of As pollution.

Development potential of nanoenabled agriculture projected using machine learning.

The controllability and targeting of nanoparticles (NPs) offer solutions for precise and sustainable agriculture. However, the development potential of nanoenabled agriculture remains unknown. Here, we build an NP-plant database containing 1,174 datasets and predict (R2 higher than 0.8 for 13 random forest models) the response and uptake/transport of various NPs by plants using a machine learning approach. Multiway feature importance analysis quantitatively shows that plant responses are driven by the total NP exposure dose and duration and plant age at exposure, as well as the NP size and zeta potential. Feature interaction and covariance analysis further improve the interpretability of the model and reveal hidden interaction factors (e.g., NP size and zeta potential). Integration of the model, laboratory, and field data suggests that Fe2O3 NP application may inhibit bean growth in Europe due to low night temperatures. In contrast, the risks of oxidative stress are low in Africa because of high night temperatures. According to the prediction, Africa is a suitable area for nanoenabled agriculture. The regional differences and temperature changes make nanoenabled agriculture complicated. In the future, the temperature increase may reduce the oxidative stress in African bean and European maize induced by NPs. This study projects the development potential of nanoenabled agriculture using machine learning, although many more field studies are needed to address the differences at the country and continental scales.

Cu/Au nanoclusters with peroxidase-like activity for chemiluminescence detection of α-amylase.

Herein, a novel chemiluminescence method was developed for efficient and sensitive detection of α-amylase activity. α-Amylase is closely related to our life, and α-amylase concentration is a marker for the diagnosis of acute pancreatitis. In this paper, Cu/Au nanoclusters with peroxidase-like activity were prepared using starch as a stabilizer. Cu/Au nanoclusters can catalyze H2O2 to generate reactive oxygen species and increase the CL signal. The addition of α-amylase makes the starch decompose and causes the nanoclusters to aggregate. The aggregation of the nanoclusters caused them to increase in size and decrease in the peroxidase-like activity, resulting in a decrease in the CL signal. α-Amylase was detected by the CL method of signal changes caused by dispersion-aggregation in the range of 0.05-8 U mL-1 with a low detection limit of 0.006 U mL-1. The chemiluminescence scheme based on the luminol-H2O2-Cu/Au NC system is of great significance for the sensitive and selective determination of α-amylase in real samples, and the detection time is short. This work provides new ideas for the detection of α-amylase based on the chemiluminescence method and the signal lasts for a long time, which can realize timely detection.

Exosomes containing miR-122-5p secreted by LPS-induced neutrophils regulate the apoptosis and permeability of brain microvascular endothelial cells by targeting OCLN.

OBJECTIVE: To explore the effect of exosomes containing miR-122-5p secreted by lipopolysaccharide (LPS)-induced neutrophils on the apoptosis and permeability of brain microvascular endothelial cells (BMECs). METHODS: Neutrophils in blood were isolated, purified and identified. LPS-induced neutrophils were co-cultured with BMECs. Untreated or LPS-induced neutrophil exosomes were isolated and identified with a transmission electron microscope. miR-122-5p expressions in the exosomes were detected by real-time quantitative polymerase chain reaction, and then the exosomes were co-cultured with BMECs. Bioinformatics analysis was performed to predict the downstream target gene of miR-122-5p, and OCLN was selected as the subject. Dual luciferase reporter assay was carried out to verify the interactive relationship between OCLN and miR-122-5p. LPS and miR-122-5p were used to treat neutrophils, and then exosomes were collected. Exosome or OCLN was embedded in BMECs. The proliferation, colony forming ability and apoptosis of BMECs were detected by cholecystokinin octopeptide, clone formation assay and flow cytometry, respectively. Corresponding kits were used to detect the activities of reactive oxygen species, superoxide dismutase, malondialdehyde and catalase. Vascular endothelial growth factor and tight junction proteins (ZO-1 and Claudin-5) expressions were measured by Western blot for cell permeability evaluation. RESULTS: miR-122-5p had an increased expression in LPS-induced neutrophil exosomes and could promote oxidative stress, apoptosis and permeability increase of BMECs and the inhibition of BMECs proliferation and colony formation (P<0.05). miR-122-5p targeted the binding with OCLN and down-regulated OCLN expression. OCLN overexpression partly decreased the malignant effect of miR-122-5p on BMECs (P<0.05). CONCLUSION: LPS can induce neutrophils to secrete exosomes containing miR-122-5p. The down-regulation of OLCN expression can aggravate BMECs injury.

MicroRNA miR-126 attenuates brain injury in septic rats via NF-κB signaling pathway.

The purpose of this study was to investigate the impact and mechanism of microRNA miR-126 on brain injury induced by blood-brain barrier (BBB) damage in septic rats. We used cecal ligation and perforation (CLP) to create a rat model of sepsis. The experimental rats were randomly divided into Control group, CLP group, CLP + miR-NC group, CLP + miR-126 group and CLP + miR-126 + NF-κB pathway agonist (PMA) group. MiR-126 expressed in the brain tissue of CLP rats was down-regulated by qRT-PCR. Upregulation of miR-126 in CLP rats could improve brain injury and BBB marker protein level, reduce brain water content, Evans blue extravasation, inflammation, and excessive oxidative stress. This could also result in an inhibition of NF-κB signaling pathway activity. In conclusion, miR-126 overexpression can prevent brain injury caused by BBB damage via the inhibition of NF-κB signaling pathway activity.

Comparison of Soybean Transformation Efficiency and Plant Factors Affecting Transformation during the Agrobacterium Infection Process.

The susceptibility of soybean genotype to Agrobacterium infection is a key factor for the high level of genetic transformation efficiency. The objective of this study is to evaluate the plant factors related to transformation in cotyledonary nodes during the Agrobacterium infection process. This study selected three genotypes (Williams 82, Shennong 9 and Bert) with high transformation efficiency, which presented better susceptibility to Agrobacterium infection, and three low transformation efficiency genotypes (General, Liaodou 16 and Kottman), which showed a relatively weak susceptibility. Gibberellin (GA) levels and soybean GA20ox2 and CYP707A2 transcripts of high-efficiency genotypes increased and were higher than those of low-efficiency genotypes; however, the opposite performance was shown in abscisic acid (ABA). Higher zeatin riboside (ZR) content and DNA quantity, and relatively higher expression of soybean IPT5, CYCD3 and CYCA3 were obtained in high-efficiency genotypes. High-efficiency genotypes had low methyl jasmonate (MeJA) content, polyphenol oxidase (PPO) and peroxidase (POD) activity, and relatively lower expression of soybean OPR3, PPO1 and PRX71. GA and ZR were positive plant factors for Agrobacterium-mediated soybean transformation by facilitating germination and growth, and increasing the number of cells in DNA synthesis cycle, respectively; MeJA, PPO, POD and ABA were negative plant factors by inducing defence reactions and repressing germination and growth, respectively.

Crucial role of anions on arrangement of Cu2S nanocrystal superstructures.

Both of the arrays of Cu2S nanowires and the superlattices of Cu2S nanoparticles are obtained by the solventless thermolysis of copper thiolate in the presence of laurate. For the first time, the types of anions in the reaction system, which are generally neglected in previous studies, are found to determine the structure of the final assembly products. Furthermore, experimental results shows in the presence of Cl⁻ ions, Cl⁻ ions participate in the self-assembly process and promote the formation of Cu2S nanowire arrays. Finally, the content of Cl⁻ ions is gradually decreased with assembly reaction proceeding. Therefore, duiring the process, Cl⁻ ions play a role of 'catassembly' in the formation of Cu2S nanocrystal superstructures.

Covalently stabilized Pd clusters in microporous polyphenylene: an efficient catalyst for Suzuki reactions under aerobic conditions.

A novel catalyst composed of a microporous polyphenylene network and covalently stabilized Pd clusters (Pd/MPP) for highly efficient Suzuki-Miyaura coupling is synthesized with an in-situ one-pot chemical approach, through the catalytic trimerization of 1,3,5-triethynylbenzene. The unique Pd/MPP cluster exhibits very high catalytic activity for a broad scope of Suzuki-Miyaura reactions with short reaction time, good yield, and high turnover number and turnover frequency values, even in aqueous media under aerobic conditions. The strong covalent interaction between Pd and MPP network prevents the agglomeration or leaching of Pd clusters and enables the catalyst to remain highly active, even after a number of cycles.

Enhanced transparent conductive properties of graphene/carbon nano-composite films.

Transparent conductive graphene/carbon nano-composite films are produced based on graphene oxide (GO) sheets and phenolic resins that are layer-by-layer deposited on a quartz substrate using a spin coating technique. The graphene/carbon nano-composite films with high graphitization degree and high crystallization exhibit exceptionally high electrical conductivity and transparency after thermal reduction. A remarkable sheet resistance of 1.98 komega/square at 81.3% transparency in the wavelength of 550 nm is obtained, which significantly outperforms that (3.29 komega/square at 81.7% transparency) of the film produced from pure GO sheets after thermal reduction.

One-dimensional/two-dimensional hybridization for self-supported binder-free silicon-based lithium ion battery anodes.

A unique silicon-based anode for lithium ion batteries is developed via the facile hybridization of one-dimensional silicon nanowires and two-dimensional graphene sheets. The resulting paper-like film holds advantages highly desirable for not only accommodating the volume change of silicon, but also facilitating the fast transport of electron and lithium ions.

Renewing functionalized graphene as electrodes for high-performance supercapacitors.

An acid-assisted ultrarapid thermal strategy is developed for constructing specifically functionalized graphene. The electrochemical performance of functionalized graphene can be boosted via elaborate coupling between the pseudocapacitance and the electronic double layer capacitance through rationally tailoring the structure of graphene sheets. This presents an opportunity for developing further high-performance graphene-based electrodes to bridge the performance gap between traditional capacitors and batteries.

Graphene-confined Sn nanosheets with enhanced lithium storage capability.

Novel graphene-confined tin nanosheets (G/Sn/G) are constructed using an elaborately designed glucose-assisted chemical protocol. The as-synthesized G/Sn/G are featured with significantly enhanced lithium storage properties when compared with other graphene-based 0D/2D composite nanostructures, disclosing the merits of the 2D/2D composite featured with a surface-to-surface integration formula between graphene and the second 2D phase.

Transcriptional responses to drought stress in root and leaf of chickpea seedling.

Chickpea (Cicer arietinum L.) is an important pulse crop grown mainly in the arid and semi-arid regions of the world. Due to its taxonomic proximity with the model legume Medicago truncatula and its ability to grow in arid soil, chickpea has its unique advantage to understand how plant responds to drought stress. In this study, an oligonucleotide microarray was used for analyzing the transcriptomic profiles of unigenes in leaf and root of chickpea seedling under drought stress, respectively. Microarray data showed that 4,815 differentially expressed unigenes were either ≥ 2-fold up- or ≤ 0.5-fold down-regulated in at least one of the five time points during drought stress. 2,623 and 3,969 unigenes were time-dependent differentially expressed in root and leaf, respectively. 110 pathways in two tissues were found to respond to drought stress. Compared to control, 88 and 52 unigenes were expressed only in drought-stressed root and leaf, respectively, while nine unigenes were expressed in both the tissues. 1,922 function-unknown unigenes were found to be remarkably regulated by drought stress. The expression profiles of these time-dependent differentially expressed unigenes were useful in furthering our knowledge of molecular mechanism of plant in response to drought stress.

One-pot synthesis of Bi-Ni nanowire and nanocable arrays by coelectrodeposition approach.

A novel and convenient one-pot electrodeposition approach has been developed for precisely controlled fabrication of large-scale Bi-Ni nanowire and nanocable arrays. Using porous anodic aluminum oxide as a shape-directing template, by simply changing the electrochemical deposition mode, desired Bi-Ni hybrid nanowires and Bi-Ni core-shell nanocables have been obtained in the CV and CC modes, respectively. The structure, morphology, and composition of the as-prepared samples were characterized using X-ray powder diffraction, transmission electron microscopy, elemental mapping, and energy-dispersive X-ray spectrometry.