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In seeking sustainable environmental strategies, microbial biophotoelectrochemistry (BPEC) systems represent a significant advancement. In this review, we underscore the shift from conventional bioenergy systems to sophisticated BPEC applications, emphasizing their utility in leveraging solar energy for essential biochemical conversions. Recent progress in BPEC technology has facilitated improved photoelectron transfer and system stability, resulting in substantial advancements in carbon and nitrogen fixation, degradation of pollutants, and energy recovery from wastewater. Advances in system design and synthetic biology have expanded the potential of BPEC for environmental clean-up and sustainable energy generation. We also highlight the challenges of environmental BPEC systems, ranging from performance improvement to future applications.
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TMEM16A, a member of the Transmembrane protein 16 family, serves as the molecular basis for calcium activated chloride channels (CaCCs). We use RT-PCR to demonstrate the expression of TMEM16A in the neurons of Helicoverpa armigera, and record the CaCCs current of acute isolated neurons of H. armigera for the first time using patch clamp technology. In order to screen effective inhibitors of calcium-activated chloride channels, the inhibitory effects of four chloride channel inhibitors, CaCCinh-A01, NPPB, DIDS, and SITS, on CaCCs were compared. The inhibitory effects of the four inhibitors on the outward current of CaCCs were CaCCinh-A01 (10 µM, 56.31 %), NPPB (200 µM, 43.69 %), SITS (1 mM, 12.41 %) and DIDS (1 mM, 13.29 %). Among these inhibitors, CaCCinh-A01 demonstrated the highest efficacy as a blocker. To further explore whether calcium channel proteins can serve as potential targets of pyrethroids, we compared the effects of (type I) tefluthrin and (type II) deltamethrin on CaCCs. 10 µM and 100 µM tefluthrin can stimulate a large tail current in CaCCs, prolonging their deactivation time by 10.44 ms and 31.49 ms, and the V0.5 shifted in the hyperpolarization by 2-8 mV. Then, deltamethrin had no obvious effect on the deactivation and activation of CaCCs. Therefore, CaCCs of H. armigera can be used as a potential target of pyrethroids, but type I and type II pyrethroids have different effects on CaCCs.
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Graph neural networks (GNNs) leveraging metapaths have garnered extensive utilization. Nevertheless, the escalating parameters and data corpus within graph pre-training models incur mounting training costs. Consequently, GNN models encounter hurdles including diminished generalization capacity and compromised performance amidst small sample datasets. Drawing inspiration from the efficacy demonstrated by self-supervised learning methodologies in natural language processing, we embark on an exploration. We endeavor to imbue graph data with augmentable, learnable prompt vectors targeting node representation enhancement to foster superior adaptability to downstream tasks. This paper proposes a novel approach, the Metapath Integrated Graph Prompt Neural Network (MIGP), which leverages learnable prompt vectors to enhance node representations within a pretrained model framework. By leveraging learnable prompt vectors, MIGP aims to address the limitations posed by mall sample datasets and improve GNNs' model generalization. In the pretraining stage, we split symmetric metapaths in heterogeneous graphs into short metapaths and explicitly propagate information along the metapaths to update node representations. In the prompt-tuning stage, the parameters of the pretrained model are fixed, a set of independent basis vectors is introduced, and an attention mechanism is employed to generate task-specific learnable prompt vectors for each node. Another notable contribution of our work is the introduction of three patent datasets, which is a pioneering application in related fields. We will make these three patent datasets publicly available to facilitate further research on large-scale patent data analysis. Through comprehensive experiments conducted on three patent datasets and three other public datasets, i.e., ACM, IMDB, and DBLP, we demonstrate the superior performance of the MIGP model in enhancing model applicability and performance across a variety of downstream datasets. The source code and datasets are available in the website.1.
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OBJECTIVE: We aimed to investigate the clinical findings of hospitalized paediatric COVID-19 patients by the end of 2022. METHOD: All confirmed children with COVID-19 infection admitted into Chaozhou Central Hospital during the COVID-19 outbreak from 19 December 2022 to 1 February 2023 were included. Detailed clinical data of those children were evaluated retrospectively. RESULTS: A total of 286 children, ranging in age from 1 month to 13 years old, were diagnosed with SARS-CoV-2 infection. Among these cases, 138 (48.3%) were categorized as mild, 126 (44.0%) as moderate and 22 (7.7%) as severe/critical. Symptoms varied among the children and included fever, upper respiratory tract symptoms, convulsions, sore throat, poor appetite, dyspnoea and gastrointestinal symptoms. Notably, febrile convulsions were observed in 96 (33.6%) patients, while acute laryngitis was documented in 50 (17.5%) cases. Among the severe/critical patients, eight developed multisystem inflammatory syndrome in children (MIS-C), and tragically, one patient's condition worsened and resulted in death. Furthermore, MRI scans revealed abnormal brain signals in six severe/critical patients. The severe/critical group also exhibited more pronounced laboratory abnormalities, including decreased haemoglobin and elevated ALT, AST, LDH and CK levels. CONCLUSIONS: Febrile convulsions and acute laryngitis are frequently observed in children diagnosed with SARS-CoV-2 Omicron infection. Moreover, MIS-C and abnormal neuroimaging appear to be relatively common phenomena in severe/critical cases.
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COVID-19 , SARS-CoV-2 , Humanos , COVID-19/epidemiologia , COVID-19/complicações , China/epidemiologia , Estudos Retrospectivos , Masculino , Pré-Escolar , Criança , Feminino , Lactente , Adolescente , Surtos de Doenças , Hospitalização/estatística & dados numéricos , Índice de Gravidade de DoençaRESUMO
Adiabatic demagnetization refrigeration (ADR) is a promising cooling technology with high efficiency and exceptional stability in achieving ultralow temperatures, playing an indispensable role at the forefront of fundamental and applied science. However, a significant challenge for ADR is that existing magnetic refrigerants struggle to concurrently achieve low magnetic ordering temperatures (T0) and substantial magnetic entropy changes (-ΔSm) at ultralow temperatures. In this work, we propose the combination of Gd3+ and Yb3+ to effectively regulate both -ΔSm and T0 in ultralow temperatures. Notably, the -ΔSm values for Gd0.1Yb0.9F3 (1) and Gd0.3Yb0.7F3 (2) in the 0.4-1.0 K range exceed those of all previously reported magnetic refrigerants within this temperature interval, positioning them as the most efficient magnetic refrigerants for the third stage to date. Although the -ΔSm values for Gd0.5Yb0.5F3 (3) in 1-4 K are less than those of the leading magnetic refrigerant Gd(OH)F2, the -ΔSm values for Gd0.7Yb0.3F3 (4) in 1-4 K at 2 T surpass those of all magnetic refrigerants previously documented within the same temperature range, making it the superior magnetic refrigerant for the fourth stage identified thus far.
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Open hollow dodecahedral cage clusters have long been a coveted target in synthetic chemistry, yet their creation poses immense challenges. Here we report two open hollow dodecahedral lanthanide-aluminum (Ln-Al) heterometallic cage clusters, namely, [Ln210Al140(µ2-OH)210(µ3-OH)540(OAc)180(H2O)156](ClO4)120·(MeCN)x·(H2O)y, (Ln = Dy and x = 27, y = 300 for 1; Ln = Y and x = 28, y = 420 for 2). Remarkably, the 350 metal atoms in 1 and 2 display a Keplerate-type four-shell structure of truncated icosidodecahedron@dodecahedron@dodecahedron@icosidodecahedron. The diameter of the cationic cluster in 1 is approximately 5.0 nm, with an inner cavity diameter of about 2.8 nm and a window diameter of roughly 0.66 nm. The cluster in 1 boasts an accessible inner void volume of up to 15,000 Å3. Notably, these cage clusters maintain stability in water, and the truncated icosidodecahedrons in 1 and 2 are the first of their kind synthesized to date. Given that the open hollow dodecahedral Ln-Al cage cluster has never been reported before, this work represents a member in the family of hollow open dodecahedral cages.
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BACKGROUND: Bletilla striata (Thunb.) Reichb.f. (B. striata) is a traditional Chinese medicinal herb. B. striata polysaccharides (BSP), stilbenes and 2-isobutyl malic acid glucosoxy-benzyl ester compounds are the main active ingredients in B. striata. However, there is limited report on the changes of medicinal components and their biosynthesis regulation mechanisms in the tubers of B. striata at different stages. METHOD: The tubers of B. striata were collected during the flowering period, fruiting period, and harvest period to determine the total polysaccharide content using the phenol sulfuric acid method. The changes in secondary metabolites in the tubers at these stages were analyzed by ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS), and transcriptomics was conducted for further exploration of their biosynthetic pathways. RESULT: The BSP content gradually increases from the flowering period to the fruiting period as the tubers develop, reaching its peak, but subsequently decreases at harvest time, which may be associated with the germination of B. striata buds in later stage. A total of 294 compounds were identified in this study. Among them, a majority of the compounds, such as 2-isobutyl malate gluconoxy-benzyl ester, exhibited high content during the fruit stage, while stilbenes like coelonin, 3'-O-methylbatatasin III, and blestriarene A accumulated during the harvesting period. The transcriptome data also revealed a substantial number of differentially expressed genes at various stages, providing a partial explanation for the complex changes in metabolites. We observed a correspondence between the expression pattern of GDP-Man biosynthesis-related enzyme genes and cumulative changes in BSP. And identified a positive correlation between 9 transcription factors and genes associated with polysaccharide biosynthesis, while 5 transcription factors were positively correlated with accumulation of 2-isobutyl malate gluconoxy-benzyl ester compounds and 5 transcription factors exhibited negative correlated with stilbene accumulation. CONCLUSION: It is imperative to determine the appropriate harvesting period based on the specific requirements of different active ingredients and the accumulation patterns of their metabolites. Considering the involvement of multiple transcription factors in the biosynthesis and accumulation of its active ingredients, a comprehensive investigation into the specific regulatory mechanisms that facilitate high-quality cultivation of B. striata is imperative.
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Metabolômica , Orchidaceae , Orchidaceae/metabolismo , Orchidaceae/crescimento & desenvolvimento , Orchidaceae/genética , Metabolômica/métodos , Regulação da Expressão Gênica de Plantas , Transcriptoma , Polissacarídeos/metabolismo , Perfilação da Expressão Gênica , Metabolismo Secundário/genética , Tubérculos/metabolismo , Tubérculos/crescimento & desenvolvimento , Tubérculos/genéticaRESUMO
Bioelectrochemical systems (BESs) exploit electroactive biofilms (EABs) for promising applications in biosensing, wastewater treatment, energy production, and chemical biosynthesis. However, during the operation of BESs, EABs inevitably decay. Seeking approaches to rejuvenate decayed EABs is critical for the sustainability and practical application of BESs. Prophage induction has been recognized as the primary reason for EAB decay. Herein, we report that introducing a competitive species of Geobacter uraniireducens suspended prophage induction in Geobacter sulfurreducens and thereby rejuvenated the decayed G. sulfurreducens EAB. The transcriptomic profile of G. sulfurreducens demonstrated that the addition of G. uraniireducens significantly affected the expression of metabolism- and stress response system-related genes and in particular suppressed the induction of phage-related genes. Mechanistic analyses revealed that interspecies ecological competition exerted by G. uraniireducens suppressed prophage induction. Our findings not only reveal a novel strategy to rejuvenate decayed EABs, which is significant for the sustainability of BESs, but also provide new knowledge for understanding phage-host interactions from an ecological perspective, with implications for developing therapies to defend against phage attack.
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Biofilmes , Geobacter , Prófagos , Biofilmes/crescimento & desenvolvimento , Geobacter/genética , Geobacter/fisiologia , Prófagos/genética , Prófagos/fisiologia , Fontes de Energia Bioelétrica/microbiologia , Interações Microbianas , TranscriptomaAssuntos
Leucemia Promielocítica Aguda , Sarcoma Mieloide , Humanos , Leucemia Promielocítica Aguda/genética , Leucemia Promielocítica Aguda/diagnóstico , Sarcoma Mieloide/genética , Sarcoma Mieloide/patologia , Sarcoma Mieloide/diagnóstico , Neoplasias da Coluna Vertebral/genética , Neoplasias da Coluna Vertebral/diagnóstico por imagem , Neoplasias da Coluna Vertebral/complicações , Masculino , Proteínas de Fusão Oncogênica/genética , Feminino , Pessoa de Meia-IdadeRESUMO
Keggin-Fe13 clusters are considered foundational building blocks or prenucleation precursors of ferrihydrite. Understanding the factors that influence the rotational configuration of these clusters, and their transformations in water, is vital for comprehending the formation mechanism of ferrihydrite. Here, we report syntheses and crystal structures of four lanthanide-iron-oxo clusters, namely, [Dy6Fe13(Gly)12(µ2-OH)6(µ3-OH)18(µ4-O)4(H2O)17]·13ClO4·19H2O (1), [Dy6Fe13(Gly)12(µ3-OH)24(µ4-O)4(H2O)18]·13ClO4·14H2O (2), [Pr8Fe34(Gly)24(µ3-OH)28(µ3-O)30(µ4-O)4(H2O)30]·6ClO4·20H2O (3), and [Pr6Fe13(Gly)12(µ3-OH)24(µ4-O)4(H2O)18]·13ClO4·22H2O (4, Gly = glycine). Single-crystal analyses reveal that 1 has a ß-Keggin-Fe13 cluster, marking the first documented instance of such a cluster to date. Conversely, both 2 and 4 contain an α-Keggin-Fe13 cluster, while 3 is characterized by four hexavacant ε-Keggin-Fe13 clusters. Magnetic property investigations of 1 and 2 show that 2 exhibits ferromagnetic interactions, while 1 exhibits antiferromagnetic interactions. An exploration of the synthetic conditions for 1 and 2 indicates that a higher pH promotes the formation of α-Keggin-Fe13 clusters, while a lower pH favors ß-Keggin-Fe13 clusters. A detailed analysis of the transition from 3 to 4 emphasizes that lacunary Keggin-Fe13 clusters can morph into Keggin-Fe13 clusters with a decrease in pH, accompanied by a significant change in their rotational configuration.
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Adiabatic demagnetization refrigeration is known to be the only cryogenic refrigeration technology that can achieve ultralow temperatures (âª1 K) at gravity-free conditions. The key indexes to evaluate the performance of magnetic refrigerants are their magnetic entropy changes (-ΔSm) and magnetic ordering temperature (T0). Although, based on the factors affecting the -ΔSm of magnetic refrigerants, one has been able to judge if a magnetic refrigerant has a large -ΔSm, how to accurately predict their T0 remains a huge challenge due to the fact that the T0 of magnetic refrigerants is related to not only magnetic exchange but also single-ion anisotropy and magnetic dipole interaction. Here, we, taking GdCO3F (1), Gd(HCOO)F2, Gd2(SO4)3·8H2O, GdF3, Gd(HCOO)3 and Gd(OH)3 as examples, demonstrate that the T0 of magnetic refrigerants with very weak magnetic interactions and small anisotropy can be accurately predicted by integrating mean-field approximation with quantum Monte Carlo simulations, providing an effective method for predicting the T0 of ultralow-temperature magnetic refrigerants. Thus, the present work lays a solid foundation for the rational design and preparation of ultralow-temperature magnetic refrigerants in the future.
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Objectives: This study aims to develop 7×7 machine-learning cross-combinatorial methods for selecting and classifying radiomic features used to construct Radiomics Score (RadScore) of predicting the mid-term efficacy and prognosis in high-risk patients with diffuse large B-cell lymphoma (DLBCL). Methods: Retrospectively, we recruited 177 high-risk DLBCL patients from two medical centers between October 2012 and September 2022 and randomly divided them into a training cohort (n=123) and a validation cohort (n=54). We finally extracted 110 radiomic features along with SUVmax, MTV, and TLG from the baseline PET. The 49 features selection-classification pairs were used to obtain the optimal LASSO-LASSO model with 11 key radiomic features for RadScore. Logistic regression was employed to identify independent RadScore, clinical and PET factors. These models were evaluated using receiver operating characteristic (ROC) curves and calibration curves. Decision curve analysis (DCA) was conducted to assess the predictive power of the models. The prognostic power of RadScore was assessed using cox regression (COX) and Kaplan-Meier plots (KM). Results: 177 patients (mean age, 63 ± 13 years,129 men) were evaluated. Multivariate analyses showed that gender (OR,2.760; 95%CI:1.196,6.368); p=0.017), B symptoms (OR,4.065; 95%CI:1.837,8.955; p=0.001), SUVmax (OR,2.619; 95%CI:1.107,6.194; p=0.028), and RadScore (OR,7.167; 95%CI:2.815,18.248; p<0.001) independently contributed to the risk factors for predicting mid-term outcome. The AUC values of the combined models in the training and validation groups were 0.846 and 0.724 respectively, outperformed the clinical model (0.714;0.556), PET based model (0.664; 0.589), NCCN-IPI model (0.523;0.406) and IPI model (0.510;0.412) in predicting mid-term treatment outcome. DCA showed that the combined model incorporating RadScore, clinical risk factors, and PET metabolic metrics has optimal net clinical benefit. COX indicated that the high RadScore group had worse prognosis and survival in progression-free survival (PFS) (HR, 2.1737,95%CI: 1.2983, 3.6392) and overall survival (OS) (HR,2.1356,95%CI: 1.2561, 3.6309) compared to the low RadScore group. KM survival analysis also showed the same prognosis prediction as Cox results. Conclusion: The combined model incorporating RadScore, sex, B symptoms and SUVmax demonstrates a significant enhancement in predicting medium-term efficacy and prognosis in high-risk DLBCL patients. RadScore using 7×7 machine learning cross-combinatorial methods for selection and classification holds promise as a potential method for evaluating medium-term treatment outcome and prognosis in high-risk DLBCL patients.
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Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in ancestry analysis. In this study, a self-developed panel consisting of 56 ancestry-informative InDels was used to investigate the genetic structures and genetic relationships between Chinese Inner Mongolia Manchu group and 26 reference populations. The Inner Mongolia Manchu group was closely related in genetic background to East Asian populations, especially the Han Chinese in Beijing. Moreover, populations from northern and southern East Asia displayed obvious variations in ancestral components, suggesting the potential value of this panel in distinguishing the populations from northern and southern East Asia. Subsequently, four machine learning models were performed based on the 56 AIM-InDel loci to evaluate the performance of this panel in ancestry prediction. The random forest model presented better performance in ancestry prediction, with 91.87% and 99.73% accuracy for the five and three continental populations, respectively. The individuals of the Inner Mongolia Manchu group were assigned to the East Asian populations by the random forest model, and they exhibited closer genetic affinities with northern East Asian populations. Furthermore, the random forest model distinguished 87.18% of the Inner Mongolia Manchus from the East Asian populations, suggesting that the random forest model based on the 56 ancestry-informative InDels could be a potential tool for ancestry analysis.
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Impressões Digitais de DNA , Etnicidade , Genética Populacional , Mutação INDEL , Aprendizado de Máquina , Humanos , China , Etnicidade/genética , Impressões Digitais de DNA/métodos , Povo Asiático/genética , Frequência do Gene , Polimorfismo GenéticoRESUMO
BACKGROUND: Bacterial fruit blotch (BFB), known as the 'cancer' of cucurbits, is a seed-borne disease of melons caused by Acidovorax citrulli. Traditional chemical treatments for BFB are ineffective and adversely affect the environment. Using dielectric barrier discharge (DBD) nanosecond-pulsed plasma technology, melon seeds were treated to promote germination and growth and to control BFB. RESULTS: Based on the evaluation parameters of seed germination, seedling growth, leaf yellowing and bacterial infection after seed plasma treatments, 9 min at 20 kV was selected as the optimal plasma discharge parameter. In this study, seedling growth was significantly improved after treating melon seeds carrying A. citrulli using this discharge parameter. The number of first true leaves measured on the eighth day was 2.3 times higher and the disease index was reduced by 60.5% compared to the control group. Attenuated total reflectance-Fourier transform infrared measurements show that plasma treatments penetrate the seed coat and denature polysaccharides and proteins in the seed kernel, affecting their growth and sterilization properties. CONCLUSION: Pre-sowing treatment of melon seeds carrying A. citrulli using nanosecond-pulsed plasma technology can effectively control seedling BFB disease and promote melon seedling growth by optimizing DBD parameters. © 2024 Society of Chemical Industry.
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Multiview attributed graph clustering is an important approach to partition multiview data based on the attribute characteristics and adjacent matrices from different views. Some attempts have been made in using graph neural network (GNN), which have achieved promising clustering performance. Despite this, few of them pay attention to the inherent specific information embedded in multiple views. Meanwhile, they are incapable of recovering the latent high-level representation from the low-level ones, greatly limiting the downstream clustering performance. To fill these gaps, a novel dual information enhanced multiview attributed graph clustering (DIAGC) method is proposed in this article. Specifically, the proposed method introduces the specific information reconstruction (SIR) module to disentangle the explorations of the consensus and specific information from multiple views, which enables graph convolutional network (GCN) to capture the more essential low-level representations. Besides, the contrastive learning (CL) module maximizes the agreement between the latent high-level representation and low-level ones and enables the high-level representation to satisfy the desired clustering structure with the help of the self-supervised clustering (SC) module. Extensive experiments on several real-world benchmarks demonstrate the effectiveness of the proposed DIAGC method compared with the state-of-the-art baselines.
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BACKGROUND: Understanding the association of peripheral inflammation and post-stroke depressive symptomology (PSDS) might provide further insights into the complex etiological mechanism of organic depression. However, studies focusing on the longitudinal patterns of PSDS were limited and it remained unclear whether peripheral inflammation influences the occurrence and development of PSDS. METHODS: A total of 427 prospectively enrolled and followed ischemic stroke patients were included in the analytical sample. Depressive symptomology was assessed on four occasions during 1 year after ischemic stroke. Peripheral inflammatory proteins on admission and repeated measures of peripheral immune markers in three stages were collected. Latent class growth analysis (LCGA) was employed to delineate group-based trajectories of peripheral immune markers and PSDS. Multinomial regression was performed to investigate the association of peripheral inflammation with PSDS trajectories. RESULTS: Four distinct trajectories of PSDS were identified: stable-low (n = 237, 55.5 %), high-remitting (n = 120, 28.1 %), late-onset (n = 44, 10.3 %), and high-persistent (n = 26, 6.1 %) PSDS trajectories. The elevation of peripheral fibrinogen on admission increased the risk of high-persistent PSDS in patients with early high PSDS. Additionally, chronic elevation of innate immune levels might not only increase the risk of high-persistent PSDS in patients with early high PSDS but also increase the risk of late-onset PSDS in patients without early high PSDS. The elevation of adaptive immune levels in the convalescence of ischemic stroke may contribute to the remission of early high PSDS. CONCLUSIONS: Peripheral immunity could influence the development of PSDS, and this influence might have temporal heterogeneity. These results might provide vital clues for the inflammation hypothesis of PSD.
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Depressão , Inflamação , AVC Isquêmico , Humanos , Masculino , Feminino , AVC Isquêmico/imunologia , AVC Isquêmico/complicações , Estudos Prospectivos , Inflamação/sangue , Inflamação/imunologia , Pessoa de Meia-Idade , Idoso , Depressão/imunologia , Depressão/sangue , Fibrinogênio/análise , Fibrinogênio/metabolismo , Biomarcadores/sangueRESUMO
Karst rocky desertification refers to the process of land degradation caused by various factors such as climate change and human activities including deforestation and agriculture on a fragile karst substrate. Nutrient limitation is common in karst areas. Moss crust grows widely in karst areas. The microorganisms associated with bryophytes are vital to maintaining ecological functions, including climate regulation and nutrient circulation. The synergistic effect of moss crusts and microorganisms may hold great potential for restoring degraded karst ecosystems. However, our understanding of the responses of microbial communities, especially abundant and rare taxa, to nutrient limitations and acquisition in the presence of moss crusts is limited. Different moss habitats exhibit varying patterns of nutrient availability, which also affect microbial diversity and composition. Therefore, in this study, we investigated three habitats of mosses: autochthonal bryophytes under forest, lithophytic bryophytes under forest and on cliff rock. We measured soil physicochemical properties and enzymatic activities. We conducted high-throughput sequencing and analysis of soil microorganisms. Our finding revealed that autochthonal moss crusts under forest had higher nutrient availability and a higher proportion of copiotrophic microbial communities compared to lithophytic moss crusts under forest or on cliff rock. However, enzyme activities were lower in autochthonal moss crusts under forest. Additionally, rare taxa exhibited distinct structures in all three habitats. Analysis of co-occurrence network showed that rare taxa had a relatively high proportion in the main modules. Furthermore, we found that both abundant and rare taxa were primarily assembled by stochastic processes. Soil properties significantly affected the community assembly of the rare taxa, indirectly affecting microbial diversity and complexity and finally nutrient acquisition. These findings highlight the importance of rare taxa under moss crusts for nutrient acquisition. Addressing this knowledge gap is essential for guiding ongoing ecological restoration projects in karst rocky desertification regions.
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BACKGROUND: Bletilla striata (Thunb.) Reichb. f. (B. striata) is a perennial herbaceous plant in the Orchidaceae family known for its diverse pharmacological activities, such as promoting wound healing, hemostasis, anti-inflammatory effects, antioxidant properties, and immune regulation. Nevertheless, the microbe-plant-metabolite regulation patterns for B. striata remain largely undetermined, especially in the field of rhizosphere microbes. To elucidate the interrelationships between soil physics and chemistry and rhizosphere microbes and metabolites, a comprehensive approach combining metagenome analysis and targeted metabolomics was employed to investigate the rhizosphere soil and tubers from four provinces and eight production areas in China. RESULTS: Our study reveals that the core rhizosphere microbiome of B. striata is predominantly comprised of Paraburkholderia, Methylibium, Bradyrhizobium, Chitinophaga, and Mycobacterium. These microbial species are recognized as potentially beneficial for plants health. Comprehensive analysis revealed a significant association between the accumulation of metabolites, such as militarine and polysaccharides in B. striata and the composition of rhizosphere microbes at the genus level. Furthermore, we found that the soil environment indirectly influenced the metabolite profile of B. striata by affecting the composition of rhizosphere microbes. Notably, our research identifies soil organic carbon as a primary driving factor influencing metabolite accumulation in B. striata. CONCLUSION: Our fndings contribute to an enhanced understanding of the comprehensive regulatory mechanism involving microbe-plant-metabolite interactions. This research provides a theoretical basis for the cultivation of high-quality traditional Chinese medicine B. striata.
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Microbiota , Orchidaceae , Rizosfera , Microbiologia do Solo , Orchidaceae/microbiologia , Orchidaceae/metabolismo , China , Tubérculos/microbiologia , Tubérculos/metabolismoRESUMO
Pyroptosis is closely related to the development and treatment of various cancers; thus, comprehensive studies of the correlations between pyroptosis and its inductive or inhibitive factors can provide new ideas for the intervention and diagnosis of tumors. The dysfunction of mitochondria may induce pyroptosis in cancer cells, which can be reflected by the fluctuations of the microenvironmental parameters in mitochondria as well as the changes of mitochondrial DNA level and morphology, etc. To precisely track and assess the mitochondria-associated pyroptosis process, simultaneous visualization of changes in multiphysiological parameters in mitochondria is highly desirable. In this work, we reported a nonreaction-based, multifunctional small-molecule fluorescent probe Mito-DK with the capability of crosstalk-free response to polarity and mtDNA as well as mitochondrial morphology. Accurate assessment of mitochondria-associated pyroptosis induced by palmitic acid/H2O2 was achieved through monitoring changes in mitochondrial multiple parameters with the help of Mito-DK. In particular, the pyroptosis-inducing ability of an antibiotic doxorubicin and the pyroptosis-inhibiting capacity of an anticancer agent puerarin were evaluated by Mito-DK. These results provide new perspectives for visualizing mitochondria-associated pyroptosis and offer new approaches for screening pyroptosis-related anticancer agents.