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ABSTRACT Dispersal, environmental filtering, and biotic interactions define the species inventory of local communities. Along successional gradients, these assembly processes are predicted to sequentially vary in their relative importance with dispersal as the dominating process early in succession, followed by environmental filtering and biotic interactions at later stages. While observational data from field studies supported this prediction, controlled experiments confirming a sequence of successional processes are still lacking. We designed miniature ecosystems to explicitly test these assumptions under controlled laboratory conditions. Our “Ecosystems on a Plate” (EsoaP) are 3D-printed customized microplates with 24 connected wells allowing us to track dispersal, niche filtering, and biotic interactions among bacteria and plants in time and space. Within EsoaPs, we created heterogeneous habitat landscapes by well-specific nutrient levels or by providing plant seedlings as mutualistic partners in a checkerboard pattern. Bacteria of a single strain were released in one well and subsequently distributed themselves within the plates. We measured the spatial distribution of bacterial abundances at two time points as a function of abiotic or biotic heterogeneity. Bacterial abundance distribution confirmed a shift from initial dispersal-dominated processes to later niche filtering and biotic interactions as more important processes. Our approach follows the principles of open science as the affordable availability of 3D printers as well as shared STL files makes EsoaPs disseminatable and accessible to all levels of society, facilitating future experimental research.IMPORTANCEHypotheses regarding the underlying processes of ecological successions have primarily emerged from and have been tested in observational studies, lacking substantial support through controlled experiments. The design of such experiments should focus on testing contemporary ecological theories at the intersection of community assembly and successional research. To achieve this, we developed and employed 3D-printed “Ecosystems on a Plate” (EsoaP) within controlled laboratory settings. EsoaPs surmount several limitations of nanoscale instruments that had hindered their application in ecologically meaningful research. By sharing 3D printing designs, experimental protocols, and data openly, we facilitate reproducibility of our experiments by researchers across diverse ecological disciplines. Moreover, our approach facilitates cost-effective replication of experiments, democratizing access to tools for ecological research, and thus holds the potential to serve as a model for future studies and educational purposes.

Abstract Phytoalexin sakuranetin functions in resistance against rice blast. However, the mechanisms underlying the effects of sakuranetin remains elusive. Here, we report that rice lines expressing resistance (R) genes were found to contain high levels of sakuranetin, which correlates with attenuated endocytic trafficking of plasma membrane (PM) proteins. Exogenous and endogenous sakuranetin attenuates the endocytosis of various PM proteins and the fungal effector PWL2. Moreover, accumulation of the avirulence protein AvrCO39, resulting from uptake into rice cells by Magnaporthe oryzae, was reduced following treatment with sakuranetin. Pharmacological manipulation of clathrin-mediated endocytic (CME) suggests that this pathway is targeted by sakuranetin. Indeed, attenuation of CME by sakuranetin is sufficient to convey resistance against rice blast. Our data reveals a mechanism of rice against M. oryzae by increasing sakuranetin levels and repressing the CME of pathogen effectors, which is distinct from the action of many R genes that mainly function by modulating transcription.

Abstract Link prediction algorithms are indispensable tools in many scientific applications by speeding up network data collection and imputing missing connections. However, in many systems, links change over time and it remains unclear how to optimally exploit such temporal information for link predictions in such networks. Here, we show that many temporal topological features, in addition to having high computational cost, are less accurate in temporal link prediction than sequentially stacked static network features. This sequential stacking link prediction method uses 41 static network features that avoid detailed feature engineering choices and is capable of learning a highly accurate predictive distribution of future connections from historical data. We demonstrate that this algorithm works well for both partially observed and completely unobserved target layers, and on two temporal stochastic block models achieves near-oracle-level performance when combined with other single predictor methods as an ensemble learning method. Finally, we empirically illustrate that stacking multiple predictive methods together further improves performance on 19 real-world temporal networks from different domains.

With the widespread application of power electronic devices in industrial and residential settings, the performance of three-phase inverters under nonlinear loads has garnered significant attention. Nonlinear loads pose significant challenges due to their complex behavior, which can adversely affect power quality and system stability. This paper aims to propose a dual closed-loop control strategy for three-phase inverters under nonlinear loads to enhance stability, dynamic response, and robustness. The control strategy employs model-compensated Active Disturbance Rejection Control (ADRC) as the outer loop and traditional Proportional-Integral (PI) control as the inner loop. Theoretical derivations and simulation tests were conducted in the dq coordinate system to validate the effectiveness of the approach. Simulation results demonstrate that the designed controller successfully combines the advantages of both ADRC and PI control, offering improved stability, rapid dynamic response, and excellent robustness. The proposed controller design method can be extended to grid-tie applications due to its reliable performance under various operational conditions.

Objective To analyze the clinical features of children with tracheobronchomalacia （TBM） complicated with pulmonary infection，and to explore the significance of fiberoptic bronchoscopy in the diagnosis and treatment of this disease. Methods Clinical data of 236 children admitted to our hospital due to recurrent pulmonary infection were collected. Among them， 37 children were diagnosed with TBM by fiberoptic bronchoscopy. Clinical features of TBM and fiberoptic bronchoscopy results were analyzed. The differences between TBM and non-TBM children were statistically compared. Results The proportion of TBM children aged 0.05）. Fiberoptic bronchoscopy found mild and moderate TBM at a single site in TBM children， and favorable outcomes were obtained. Conclusion TBM is one of the important factors of recurrent pulmonary infection and wheezing in young children. It is challenging to identify the symptoms of TBM. Bronchoscopy is beneficial to timely diagnosis and treatment.

Abstract Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where chaperones service hundreds of clients, forming chaperone-client interaction networks. How network structure affects its robustness to chaperone targeting is key to developing cancer-specific drug therapy. However, few studies have assessed how structure and robustness vary across different cancer tissues. Here, using ecological network analysis, we reveal a non-random, hierarchical pattern whereby the cancer type modulates the chaperones’ ability to realize their potential client interactions. Despite the low similarity between the chaperone-client interaction networks, we highly accurately predict links in one cancer type based on another. Moreover, we identify groups of chaperones that interact with similar clients. Simulations of network robustness show that this group structure affects cancer-specific response to chaperone removal. Our results open the door for new hypotheses regarding the ecology and evolution of chaperone-client interaction networks and can inform cancer-specific drug development strategies.

Real-world network datasets are typically obtained in ways that fail to capture all edges. The patterns of missing data are often non-uniform as they reflect biases and other shortcomings of different data collection methods. Nevertheless, uniform missing data is a common assumption made when no additional information is available about the underlying missing-edge pattern, and link prediction methods are frequently tested against uniformly missing edges. To investigate the impact of different missing-edge patterns on link prediction accuracy, we employ 9 link prediction algorithms from 4 different families to analyze 20 different missing-edge patterns that we categorize into 5 groups. Our comparative simulation study, spanning 250 real-world network datasets from 6 different domains, provides a detailed picture of the significant variations in the performance of different link prediction algorithms in these different settings. With this study, we aim to provide a guide for future researchers to help them select a link prediction algorithm that is well suited to their sampled network data, considering the data collection process and application domain.

ObjectiveThe previously established 38-plex InDel system was optimized and its performance was validated according to the Scientific Working Group on DNA Analysis Method （SWGDAM） application guidelines. The ancestry inference accuracy of individuals from East Asian， European， African and mixed populations was verified.MethodsDNA standard sample 9947A was used as the template to establish the optimal amplification conditions by adjusting primer balance， Mg2+ final concentration and optimizing PCR thermal cycle parameters and amplification volume. The allelic dropout， nonspecific amplification and whether the origin of the inferred samples matched the known information were compared to evaluate the performance of this system.ResultsThe optimal dosage of this system was 0.125-2 ng DNA template. The results of InDel typing were accurate， the amplification equilibrium was good， and the species specificity was good. This system showed certain tolerance to DNA samples including the inhibitor such as hemoglobin （≤80 μmol/L）， indigo （≤40 mmol/L）， calcium ion （≤1.0 mmol/L）， and humic acid （≤90 ng/μL）. The system enabled the direct amplification of DNA from saliva and blood on filter paper， and the results of ethnic inference were accurate. The system successfully detected the mixed DNA sample from two individuals. The test results of the system for common biological materials in practical cases were accurate.ConclusionThe results of the 38-plex InDel system are accurate and reliable， and the performance of the system meets the requirement of the SWGDAM guidelines. This system can accurately differentiate the ancestry origins of individuals from African， European， East Asian， and Eurasian populations and can be implemented in forensic practice.

Over the past few decades, researchers have put their effort and paid significant attention to the authorship attribution field, as it plays an important role in software forensics analysis, plagiarism detection, security attack detection, and protection of trade secrets, patent claims, copyright infringement, or cases of software theft. It helps new researchers understand the state-of-the-art works on authorship attribution methods, identify and examine the emerging methods for authorship attribution, and discuss their key concepts, associated challenges, and potential future work that could help newcomers in this field. This paper comprehensively surveys authorship attribution methods and their key classifications, used feature types, available datasets, model evaluation criteria and metrics, and challenges and limitations. In addition, we discuss the potential future research directions of the authorship attribution field based on the insights and lessons learned from this survey work.

A multidiversity analysis of plant, microbial, and invertebrate communities in a glacier forefield suggests that stochastic, dispersal-driven processes are replaced by deterministic processes after passing a threshold during ecological succession.

IntroductionEvidence suggests that negative cognitive processing bias (NCPB) is a significant risk factor for depression. The microbiota–gut–brain axis has been proven to be a contributing factor to cognitive health and disease. However, the connection between microbiota and NCPB remains unknown. This study mainly sought to explore the key microbiota involved in NCPB and the possible pathways through which NCPB affects depressive symptoms.MethodsData in our studies were collected from 735 Chinese young adults through a cross-sectional survey. Fecal samples were collected from 35 young adults with different levels of NCPB (18 individuals were recruited as the high-status NCPB group, and another 17 individuals were matched as the low-status NCPB group) and 60 with different degrees of depressive symptoms (27 individuals were recruited into the depressive symptom group, as D group, and 33 individuals were matched into the control group, as C group) and analyzed by the 16S ribosomal RNA sequencing technique.ResultsAs a result, the level of NCPB correlated with the degree of depressive symptoms as well as anxiety symptoms and sleep quality (p < 0.01). The β-diversity of microbiota in young adults was proven to be significantly different between the high-status NCPB and the low-status NCPB groups. There were several significantly increased bacteria taxa, including Dorea, Christensenellaceae, Christe -senellaceae_R_7_group, Ruminococcaceae_NK4A214_group, Eggerthellaceae, Family-XIII, Family_XIII_AD3011_group, Faecalibaculum, and Oscillibacter. They were mainly involved in pathways including short-chain fatty acid (SCFA) metabolism. Among these variable bacteria taxa, Faecalibaculum was found associated with both NCPB and depressive symptoms. Furthermore, five pathways turned out to be significantly altered in both the high-status NCPB group and the depressive symptom group, including butanoate metabolism, glyoxylate and dicarboxylate metabolism, propanoate metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, valine, leucine, and isoleucine degradation. These pathways were related to SCFA metabolism.DiscussionFecal microbiota is altered in Chinese young male adults with high status NCPB and may be involved in the biochemical progress that influences depressive symptoms.

Receding glaciers create virtually uninhabited substrates waiting for initial colonization of bacteria, fungi and plants. These glacier forefields serve as an ideal ecosystem for studying transformations in community composition and diversity over time and the interactions between taxonomic groups in a dynamic landscape. In this study, we investigated the relationships between the composition and diversity of bacteria, fungi, and plant communities as well as environmental factors along a successional gradient. We used random forest analysis assessing how well the composition and diversity of taxonomic groups and environmental factors mutually predict each other. We did not identify a single best indicator for all taxonomic and environmental properties, but found specific predictors to be most accurate for each taxon and environmental factor. The accuracy of prediction varied considerably along the successional gradient, highlighting the dynamic environmental conditions along the successional gradient that may also affect biotic interactions across taxa. This was also reflected by the high accuracy of predictions of plot age by all taxa. Next to plot age, our results indicate a strong importance of pH and temperature in structuring microbial and plant community composition. In addition, taxonomic groups predicted the community composition of each other more accurately than environmental factors, which may either suggest that these groups similarly respond to other not measured environmental factors or that direct interactions between taxa shape the composition of their communities. In contrast, diversity of taxa was not well predicted, suggesting that community composition of one taxonomic group is not a strong driver of the diversity of another group. Our study provides insights into the successional development of multidiverse communities shaped by complex interactions between taxonomic groups and the environment.

Root system architecture (RSA) and tiller are important agronomic traits. However, the mechanisms of the IGT family genes regulate RSA and tiller development in different rice varieties remain unclear. In this study, we demonstrated that 38 rice varieties obtained from Yuanyang Hani’s terraced fields with different RSA and could be classified into six groups based on the ratio of root length and width. We found a positive correlation between RSA (including root width, length, and area) and tiller number in most of rice varieties. Furthermore, the IGT family genes Deeper Rooting 1 (DRO1), LAZY1, TAC1, and qSOR1 showed different expression patterns when rice grown under irrigation and drought conditions. Moreover, the qSOR1 gene had higher levels in the roots and tillers, and accompanied with higher levels of PIN1b gene in roots when rice grown under drought environmental condition. DRO1 gene had two single nucleotide polymorphisms (SNPs) in the exon 3 sequences and showed different expression patterns in the roots and tillers of the 38 rice varieties. Overexpression of DRO1 with a deletion of exon 5 caused shorter root length, less lateral roots and lower levels of LAZY1, TAC1, and qSOR1. Further protein interaction network, microRNA targeting and co-expression analysis showed that DRO1 plays a critical role in the root and tiller development associated with auxin transport. These data suggest that the RSA and tiller development are regulated by the IGT family genes in an intricate network way, which is tightly related to rice genetic background in rice adapting to different environmental conditions.

A rotating magnet-based mechanical antenna (RMBMA) is a new promising paradigm which can significantly reduce both the size and the power consumption of the super-low frequency electromagnetic transmitter. To further reveal the effects of the rotational motion on transmission, this paper investigates the performance analysis of MSK (Minimum Shift Keying)-based RMBMA for the first time. Initially, based on the framework of MSK-based RMBMA, both the information loading of RMBMA and the control strategies of the motor are proposed, such that the impacts of the step response induced by the motor on the information loading are characterized. Then, the transmission capacity of the MSK-based RMBMA is derived in the closed form. The results indicate that increasing output torque or decreasing inertia load can enhance the transmission capacity. Finally, numerical simulations using a realistic system model demonstrate the validity of the proposed performance analysis. The simulation results show that when the inertia is less than 0.0128 kg∙m2 and the symbol rate is less than 4 bit/s, the bit error rate is less than 10%, thereby improving the transmission capacity. The proposed comprehensive design principles of RMBMA provide guidance for system design and practical implementation.

Global warming increases the vulnerability of plants, especially alpine herbaceous species, to local extinction. In this study, we collected species distribution information from herbarium specimens for ten selected Cyananthus and Primula alpine species endemic to the Himalaya-Hengduan Mountains (HHM). Combined with climate data from WorldClim, we used Maximum Entropy Modeling (MaxEnt) to project distributional changes from the current time period to 2070. Our predictions indicate that, under a wide range of climate change scenarios, the distributions of all species will shift upward in elevation and northward in latitude; furthermore, under these scenarios, species will expand the size of their range. For the majority of the species in this study, habitats are available to mitigate upward and northward shifts that are projected to be induced by changing climate. If current climate projections, however, increase in magnitude or continue to increase past our projection dates, suitable habitat for future occupation by alpine species will be limited as we predict range contraction or less range expansion for some of the species under more intensified climate scenarios. Our study not only underscores the value of herbarium source information for future climate model projections but also suggests that future studies on the effects of climate change on alpine species should include additional biotic and abiotic factors to provide greater resolution of the local dynamics associated with species persistence under a warming climate. Keywords: Global warming, MaxEnt, Range expansion, Alpine species, Himalaya-Hengduan Mountains

Using a fresh empirical approach to time-frequency domain frameworks, this study analyzes the return and volatility spillovers from fossil fuel markets (coal, natural gas, and crude oil) to electricity spot and futures markets in Europe. In the time domain, by an approach developed by Diebold and Yilmaz (2012) which can analyze the directional spillover effect across different markets, we find natural gas has the highest return spillover effect on electricity markets followed by coal and oil. We also find that return spillovers increase with the length of the delivery period of electricity futures. In the frequency domain, using the methodology proposed by Barunik and Krehlik (2018) that can decompose the spillover effect into different frequency bands, we find most of the return spillovers from fossil fuels to electricity are produced in the short term while most of the volatility spillovers are generated in the long term. Additionally, dynamic return spillovers have patterns corresponding to the use of natural gas for electricity generation, while volatility spillovers are sensitive to extreme financial events.

Our study analyzes the return and volatility spillover among the natural gas, crude oil, and electricity utility stock indices in North America and Europe from 4 August 2009 to 16 August 2019. First, in time domain, both total return and volatility spillover are stronger in Europe than in North America. Furthermore, compared to natural gas, crude oil has a greater volatility spillover on the electricity utility stock indices in North America and Europe. Second, in frequency domain, most of the return spillover occurs in the short-term, while most of the volatility spillover occurs over a longer period. Third, the rolling analyses indicate that the return and volatility from 2009 to late 2013 remained stable in North America and Europe, which may be a result of the 2008 global financial crisis, and started to fluctuate after late 2013 due to some extreme events, indicating that extreme events can significantly influence spillover effects. Moreover, investors should monitor current events to diversify their portfolios properly and hedge their risks.

Sinomenine (SIN) is a bioactive alkaloid extracted from the Chinese medicinal plant Sinomenium acutum, which is widely used in the clinical treatment of rheumatoid arthritis (RA). However, its role in acute lung injury (ALI) is unclear. In this study, we investigate the role of SIN in lipopolysaccharide (LPS)-induced ALI in mice. After ALI, lung water content and histological signs of pulmonary injury were attenuated, whereas the PaO2/FIO2 (P/F) ratios were elevated significantly in the mice pretreated with SIN. Additionally, SIN markedly inhibited inflammatory cytokine TNF-α and IL-1β expression levels as well as neutrophil infiltration in the lung tissues of the mice. Microarray analysis and real-time PCR showed that SIN treatment upregulated adenosine A(2A) receptor (A(2A)R) expression, and the protective effect of SIN was abolished in A(2A)R knockout mice. Further investigation in isolated mouse neutrophils confirmed the upregulation of A(2A)R by SIN and showed that A(2A)R-cAMP-PKA signaling was involved in the anti-inflammatory effect of SIN. Taken together, these findings demonstrate an A(2A)R-associated anti-inflammatory effect and the protective role of SIN in ALI, which suggests a potential novel approach to treat ALI.