Search

The complexity of fMRI signals quantifies temporal dynamics of spontaneous neural activity, which has been increasingly recognized as providing important insights into cognitive functions and psychiatric disorders. However, its heritability and structural underpinnings are not well understood. Here, we utilize multi-scale sample entropy to extract resting-state fMRI complexity in a large healthy adult sample from the Human Connectome Project. We show that fMRI complexity at multiple time scales is heritable in broad brain regions. Heritability estimates are modest and regionally variable. We relate fMRI complexity to brain structure including surface area, cortical myelination, cortical thickness, subcortical volumes, and total brain volume. We find that surface area is negatively correlated with fine-scale complexity and positively correlated with coarse-scale complexity in most cortical regions, especially the association cortex. Most of these correlations are related to common genetic and environmental effects. We also find positive correlations between cortical myelination and fMRI complexity at fine scales and negative correlations at coarse scales in the prefrontal cortex, lateral temporal lobe, precuneus, lateral parietal cortex, and cingulate cortex, with these correlations mainly attributed to common environmental effects. We detect few significant associations between fMRI complexity and cortical thickness. Despite the non-significant association with total brain volume, fMRI complexity exhibits significant correlations with subcortical volumes in the hippocampus, cerebellum, putamen, and pallidum at certain scales. Collectively, our work establishes the genetic basis and structural correlates of resting-state fMRI complexity across multiple scales, supporting its potential application as an endophenotype for psychiatric disorders., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Menaquinone-7 (MK-7), a subtype of vitamin K 2 (VK 2 ), assumes crucial roles in coagulation function, calcium homeostasis, and respiratory chain transmission. The production of MK-7 via microbial fermentation boasts mild technological conditions and high biocompatibility. Nevertheless, the redox activity of MK-7 imposes constraints on its excessive accumulation in microorganisms. To address this predicament, an adaptive laboratory evolution (ALE) protocol was implemented in Bacillus subtilis BS011, utilizing vitamin K 3 (VK 3 ) as a structural analog of MK-7. The resulting strain, BS012, exhibited heightened tolerance to high VK 3 concentrations and demonstrated substantial enhancements in biofilm formation and total antioxidant capacity (T-AOC) when compared to BS011. Furthermore, MK-7 production in BS012 exceeded that of BS011 by 76% and 22% under static and shaking cultivation conditions, respectively. The molecular basis underlying the superior performance of BS012 was elucidated through genome and transcriptome analyses, encompassing observations of alterations in cell morphology, variations in central carbon and nitrogen metabolism, spore formation, and antioxidant systems. In summation, ALE technology can notably enhance the tolerance of B. subtilis to VK and increase MK-7 production, thus offering a theoretical framework for the microbial fermentation production of other VK 2 subtypes. Additionally, the evolved strain BS012 can be developed for integration into probiotic formulations within the food industry to maintain intestinal flora homeostasis, mitigate osteoporosis risk, and reduce the incidence of cardiovascular disease. KEY POINTS: • Bacillus subtilis was evolved for improved vitamin K tolerance and menaquinone-7 (MK-7) production • Evolved strains formed wrinkled biofilms and elongated almost twofold in length • Evolved strains induced sporulation to improve tolerance when carbon was limited., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: Low-grade gliomas (LGG) are common brain tumors with high mortality rates. Cancer cell invasion is a significant factor in tumor metastasis. Novel biomarkers are urgently needed to predict LGG prognosis effectively., Methods: The data for LGG were obtained from the Bioinformatics database. A consensus clustering analysis was performed to identify molecular subtypes linked with invasion in LGG. Differential expression analysis was performed to identify differentially expressed genes (DEGs) between the identified clusters. Enrichment analyses were then conducted to explore the function for DEGs. Prognostic signatures were placed, and their predictive power was assessed. Furthermore, the invasion-related prognostic signature was validated using the CGGA dataset. Subsequently, clinical specimens were procured in order to validate the expression levels of the distinct genes examined in this research, and to further explore the impact of these genes on the glioma cell line LN229 and HS-683., Results: Two invasion-related molecular subtypes of LGG were identified, and we sifted 163 DEGs between them. The enrichment analyses indicated that DEGs are mainly related to pattern specification process. Subsequently, 10 signature genes ( IGF2BP2, SRY, CHI3L1, IGF2BP3, MEOX2, ABCC3, HOXC4, OTP, METTL7B , and EMILIN3 ) were sifted out to construct a risk model. Besides, the survival (OS) in the high-risk group was lower. The performance of the risk model was verified. Furthermore, a highly reliable nomogram was generated. Cellular experiments revealed the ability to promote cell viability, value-addedness, migratory ability, invasive ability, and colony-forming ability of the glioma cell line LN229 and HS-683. The qRT-PCR analysis of clinical glioma samples showed that these 10 genes were expressed at higher levels in high-grade gliomas than in low-grade gliomas, suggesting that these genes are associated with poor prognosis of gliomas., Conclusion: Our study sifted out ten invasion-related biomarkers of LGG, providing a reference for treatments and prognostic prediction in LGG., Competing Interests: The authors declare that there is no conflicts of interest., (© 2024 Wang et al.)

An extremely hazardous heavy metal called cadmium (Cd) is frequently released into the soil, causing a considerable reduction in plant productivity and safety. In an effort to reduce the toxicity of Cd, silicon dioxide nanoparticles were chosen because of their capability to react with metallic substances and decrease their adsorption. This study examines the processes that underlie the stress caused by Cd and how SiO 2 NPs may be able to lessen it through modifying antioxidant defense, oxidative stress, and photosynthesis. A 100 μM concentration of Cd stress was applied to the hydroponically grown wild rice line, and 50 μM of silicon dioxide nanoparticles (SiO 2 NPs) was given. The study depicted that when 50 μM SiO 2 NPs was applied, there was a significant decrease in Cd uptake in both roots and shoots by 30.2% and 15.8% under 100 μM Cd stress, respectively. The results illustrated that Cd had a detrimental effect on carotenoid and chlorophyll levels and other growth-related traits. Additionally, it increased the levels of ROS in plants, which reduced the antioxidant capability by 18.8% (SOD), 39.2% (POD), 32.6% (CAT), and 25.01% (GR) in wild rice. Nevertheless, the addition of silicon dioxide nanoparticles reduced oxidative damage and the overall amount of Cd uptake, which lessened the toxicity caused by Cd. Reduced formation of reactive oxygen species (ROS), including MDA and H 2 O 2 , and an increased defense system of antioxidants in the plants provided evidence for this. Moreover, SiO 2 NPs enhanced the Cd resistance, upregulated the genes related to antioxidants and silicon, and reduced metal transporters' expression levels.

This research combined Whole-Genome sequencing, intraspecific comparative genomics and transposon mutagenesis to investigate the menaquinone-7 (MK-7) synthesis potential in Bacillus subtilis natto. First, Whole-Genome sequencing showed that Bacillus subtilis natto BN-P15-11-1 contains one single circular chromosome in size of 3,982,436 bp with a GC content of 43.85 %, harboring 4,053 predicted coding genes. Next, the comparative genomics analysis among strain BN-P15-11-1 with model Bacillus subtilis 168 and four typical Bacillus subtilis natto strains proves that the closer evolutionary relationship Bacillus subtilis natto BN-P15-11-1 and Bacillus subtilis 168 both exhibit strong biosynthetic potential. To further dig for MK-7 biosynthesis latent capacity of BN-P15-11-1, we constructed a mutant library using transposons and a high throughput screening method using microplates. We obtained a YqgQ deficient high MK-7 yield strain F4 with a yield 3.02 times that of the parent strain. Experiments also showed that the high yield mutants had defects in different transcription and translation regulatory factor genes, indicating that regulatory factor defects may affect the biosynthesis and accumulation of MK-7 by altering the overall metabolic level. The findings of this study will provide more novel insights on the precise identification and rational utilization of the Bacillus subtilis subspecies for biosynthesis latent capacity., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: Major depressive disorder (MDD) is a debilitating disease involving sensory and higher-order cognitive dysfunction. Previous work has shown altered asymmetry in MDD, including abnormal lateralized activation and disrupted hemispheric connectivity. However, it remains unclear whether and how MDD affects functional asymmetries in the context of intrinsic hierarchical organization., Methods: Here, we evaluate intra- and inter-hemispheric asymmetries of the first three functional gradients, characterizing unimodal-transmodal, visual-somatosensory, and somatomotor/default mode-multiple demand hierarchies, to study MDD-related alterations in overarching system-level architecture., Results: We find that, relative to the healthy controls, MDD patients exhibit alterations in both primary sensory regions (e.g., visual areas) and transmodal association regions (e.g., default mode areas). We further find these abnormalities are woven in heterogeneous alterations along multiple functional gradients, associated with cognitive terms involving mind, memory, and visual processing. Moreover, through an elastic net model, we observe that both intra- and inter-asymmetric features are predictive of depressive traits measured by BDI-II scores., Discussion: Altogether, these findings highlight a broad and mixed effect of MDD on functional gradient asymmetry, contributing to a richer understanding of the neurobiological underpinnings in MDD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yang, Zhen, Wang, Liu, Zheng, Zheng, Zheng and Tang.)

Network modeling characterizes the underlying principles of structural properties and is of vital significance for simulating dynamical processes in real world. However, bridging structure and dynamics is always challenging due to the multiple complexities in real systems. Here, through introducing the individual's activity rate and the possibility of group interaction, we propose a probabilistic activity-driven (PAD) model that could generate temporal higher-order networks with both power-law and high-clustering characteristics, which successfully links the two most critical structural features and a basic dynamical pattern in extensive complex systems. Surprisingly, the power-law exponents and the clustering coefficients of the aggregated PAD network could be tuned in a wide range by altering a set of model parameters. We further provide an approximation algorithm to select the proper parameters that can generate networks with given structural properties, the effectiveness of which is verified by fitting various real-world networks. Finally, we construct the co-evolution framework of the PAD model and higher-order contagion dynamics and derive the critical conditions for phase transition and bistable phenomenon using theoretical and numerical methods. Results show that tendency of participating in higher-order interactions can promote the emergence of bistability but delay the outbreak under heterogeneous activity rates. Our model provides a basic tool to reproduce complex structural properties and to study the widespread higher-order dynamics, which has great potential for applications across fields., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

While brain function is supported and constrained by the underlying structure, the connectome-based link estimated by current approaches is either relatively moderate or accompanied by high model complexity, with the essential principles underlying structure-function coupling remaining elusive. Here, by proposing a mapping method based on network eigendecomposition, we present a concise and strong correspondence between structure and function. We show that the explanation of functional connectivity can be significantly improved by incorporating interactions between different structural eigenmodes. We also demonstrate the pronounced advantage of the present mapping in capturing individual-specific information with simple implementation. Applying our methodology to the human lifespan, we find that functional diversity decreases with age, with functional interactions increasingly dominated by the leading functional mode. We also find that structure-function liberality weakens with age, which is driven by the decreases in functional components that are less constrained by anatomy, while the magnitude of structure-aligned components is preserved. Overall, our work enhances the understanding of structure-function coupling from a collective, connectome-oriented perspective and promotes a more refined identification of functional portions relevant to human aging, holding great potential for mechanistic insights into individual differences associated with cognition, development, and neurological disorders., (© 2023. The Author(s).)

Molecular fingerprints are significant cheminformatics tools to map molecules into vectorial space according to their characteristics in diverse functional groups, atom sequences, and other topological structures. In this paper, we investigate a novel molecular fingerprint Anonymous-FP that possesses abundant perception about the underlying interactions shaped in small, medium, and large-scale atom chains. In detail, the possible atom chains from each molecule are sampled and extended as anonymous atom chains using an anonymous encoding manner. After that, the molecular fingerprint Anonymous-FP is embedded into vectorial space in virtue of the Natural Language Processing technique PV-DBOW. Anonymous-FP is studied on molecular property identification via molecule classification experiments on a series of molecule databases and has shown valuable advantages such as less dependence on prior knowledge, rich information content, full structural significance, and high experimental performance. During the experimental verification, the scale of the atom chain or its anonymous pattern is found significant to the overall representation ability of Anonymous-FP. Generally, the typical scale r = 8 could enhance the molecule classification performance, and specifically, Anonymous-FP gains the classification accuracy to above 93% on all NCI datasets.

Arbuscular mycorrhizal fungi (AMF) are obligate plant symbionts of most land plants. In these organisms, thousands of nuclei that are either genetically similar (homokaryotic) or derived from two distinct parents (dikaryotic) co-exist in a large syncytium. Here, we investigated the impact of these two nuclear organizations on the mycorrhizal response of potatoes (Solanum tuberosum) by inoculating four potato cultivars with eight Rhizophagus irregularis strains individually (four homokaryotic and four dikaryotic). By evaluating plant and fungal fitness-related traits four months post inoculation, we found that AMF genetic organization significantly affects the mycorrhizal response of host plants. Specifically, homokaryotic strains lead to higher total, shoot, and tuber biomass and a higher number of tubers, compared to dikaryotic strains. However, fungal fitness-related traits showed no clear differences between homokaryotic and dikaryotic strains. Nucleotype content analysis of single spores confirmed that the nucleotype ratio of AMF heterokaryon spores can shift depending on host identity. Together, these findings continue to highlight significant ecological differences derived from the two distinct genetic organizations in AMF., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

While the link between brain structure and function remains an ongoing challenge, the prevailing hypothesis is that the structure-function relationship may itself be gradually decoupling from unimodal to transmodal cortex. However, this hypothesis is constrained by the underlying models which may neglect requisite information. Here we relate structural and functional connectivity derived from diffusion and functional MRI through orthogonal eigenmodes governing frequency-specific diffusion patterns. We find that low-frequency eigenmodes contribute little to functional interactions in transmodal cortex, resulting in divergent structure-function relationships. Conversely, high-frequency eigenmodes predominantly support neuronal coactivation patterns in these areas, inducing structure-function convergence along a unimodal-transmodal hierarchy. High-frequency information, although weak and scattered, could enhance the structure-function tethering, especially in transmodal association cortices. Our findings suggest that the structure-function decoupling may not be an intrinsic property of brain organization, but can be narrowed through multiplexed and regionally specialized spatiotemporal propagation regimes., (© 2023. Springer Nature Limited.)

The present study aimed to investigate the role of miR-149-3p/chromobox 2 (CBX2)/Wnt/β-catenin pathway in the proliferation and metastasis of glioma cells. The expression and clinical significance of miR-149-3p and CBX2 were analyzed using data from public databases. Cell Counting Kit-8 and colony formation assays were performed to measure cell proliferation. Transwell assays were used to assess cell invasion. The results showed that miR-149-3p was downregulated and CBX2 was upregulated in glioma, and that the downregulated expression of miR-149-3p promoted the proliferation and invasion of glioma cells. In addition, downregulated expression of CBX2 suppressed the proliferation and invasion of glioma cells. Dual-luciferase assay indicated that CBX2 is a target gene of miR149-3p. The possible molecular mechanism of CBX2 was probed by western blotting, which showed that it may further affect the Wnt/β-catenin pathway. These present findings demonstrated that miR-149-3p may function as a tumor suppressor miRNA by directly regulating CBX2 and serve important roles in the malignancy of glioma., Competing Interests: The authors declare that they have no competing interests., (Copyright: © Wang et al.)

Environmental changes play a critical role in determining the evolution of social dilemmas in many natural or social systems. Generally, the environmental changes include two prominent aspects: the global time-dependent fluctuations and the local strategy-dependent feedbacks. However, the impacts of these two types of environmental changes have only been studied separately, a complete picture of the environmental effects exerted by the combination of these two aspects remains unclear. Here we develop a theoretical framework that integrates group strategic behaviors with their general dynamic environments, where the global environmental fluctuations are associated with a nonlinear factor in public goods game and the local environmental feedbacks are described by the 'eco-evolutionary game'. We show how the coupled dynamics of local game-environment evolution differ in static and dynamic global environments. In particular, we find the emergence of cyclic evolution of group cooperation and local environment, which forms an interior irregular loop in the phase plane, depending on the relative changing speed of both global and local environments compared to the strategic change. Further, we observe that this cyclic evolution disappears and transforms into an interior stable equilibrium when the global environment is frequency-dependent. Our results provide important insights into how diverse evolutionary outcomes could emerge from the nonlinear interactions between strategies and the changing environments., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The relationship between strain and elastic energy is simplified by introducing a stress state parameter based on the generalised Hooke's law. It is assumed that the micro-element strengths satisfy the Weibull distribution and a new model for the non-linear evolution of energy is developed by introducing the concept of rock micro-element strengths. A sensitivity analysis of the model parameters is carried out on this basis. The results show that the model agrees well with the experimental data. The model is close to the deformation and damage laws of the rock and is able to reflect the relationship between the elastic energy and strain of the rock. By comparing with other model curves, the model of this paper is more suitable for the experimental curve. They show that the improved model could better describe the stress-strain relationship of rock. Finally, according to the analysis of the influence of the distribution parameter on the variation pattern of the elastic energy of the rock, the magnitude of the distribution parameter can directly reflect the peak energy of the rock., (© 2023. The Author(s).)

Stimulation to local areas remarkably affects brain activity patterns, which can be exploited to investigate neural bases of cognitive function and modify pathological brain statuses. There has been growing interest in exploring the fundamental action mechanisms of local stimulation. Nevertheless, how noise amplitude, an essential element in neural dynamics, influences stimulation-induced brain states remains unknown. Here, we systematically examine the effects of local stimulation by using a large-scale biophysical model under different combinations of noise amplitudes and stimulation sites. We demonstrate that noise amplitude nonlinearly and heterogeneously tunes the stimulation effects from both regional and network perspectives. Furthermore, by incorporating the role of the anatomical network, we show that the peak frequencies of unstimulated areas at different stimulation sites averaged across noise amplitudes are highly positively related to structural connectivity. Crucially, the association between the overall changes in functional connectivity as well as the alterations in the constraints imposed by structural connectivity with the structural degree of stimulation sites is nonmonotonically influenced by the noise amplitude, with the association increasing in specific noise amplitude ranges. Moreover, the impacts of local stimulation of cognitive systems depend on the complex interplay between the noise amplitude and average structural degree. Overall, this work provides theoretical insights into how noise amplitude and network structure jointly modulate brain dynamics during stimulation and introduces possibilities for better predicting and controlling stimulation outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Vitamin K 2 plays an important role in electron transport, blood coagulation, and calcium homeostasis, and researchers have been trying to use microbes to produce it. Although our previous studies have shown that gradient radiation, breeding, and culture acclimation can improve vitamin K 2 production in Elizabethkingia meningoseptica, the mechanism is still unclear. This study is the first which performs genome sequencing of E. meningoseptica sp. F2 as a basis for subsequent experiments and further comparative analyses with other strains. Comparative metabolic pathway analysis of E. meningoseptica sp. F2, E. coli, Bacillus subtilis, and other vitamin K 2 product strains revealed that the mevalonate pathway of E. meningoseptica sp. F2 is different in bacteria at the system level. The expressions of menA, menD, menH, and menI in the menaquinone pathway and idi, hmgR, and ggpps in the mevalonate pathway were higher than those in the original strain. A total of 67 differentially expressed proteins involved in the oxidative phosphorylation metabolic pathway and citric acid cycle (TCA cycle) were identified. Our results reveal that combined gradient radiation breeding and culture acclimation can promote vitamin K 2 accumulation probably by regulating the vitamin K 2 pathway, oxidative phosphorylation metabolism pathway, and the citrate cycle (TCA cycle)., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Different stress creep tests are conducted on the sandstone in this study to better describe the creep properties of rocks under different stress states. A model that describes the rock creep process is established. The various stages of creep can be described by combining the creep properties of the creep elements of the model. A new method for determining creep parameters is proposed by using the special point on the creep curve and the definition of creep deformation. The relationship between the creep parameters, stress, and time is analyzed. An improved creep model that considers the effects of stress state and time on the creep parameters is developed. This model is verified using experimental data and calculation results. Results shows that the improved creep model better describes the creep properties of rocks and provides a new method for determining future model parameters. The shear modulus of elastic model controls the instantaneous deformation. The shear modulus of viscoelastic model governs the limit of viscoelastic deformation. The shear viscoelastic coefficient of viscoelastic model increases with the increase in stress. The coefficient of viscoplastic model controls the viscoplastic creep rate. The coefficient of a nonlinear Newtonian dashpot mainly controls the accelerated creep deformation of rock. The calculation results of the proposed model agree well with the experimental data under the action of different stress levels. This model accurately reflects the creep characteristics of the primary and steady-state creep stages, and overcomes the shortcomings of the traditional Nishihara model in describing accelerated creep., (© 2023. The Author(s).)

Background: Isocitrate dehydrogenase (IDH) mutation status is an important biomarker for the treatment strategy selection and prognosis evaluation of glioma. The purpose of this study is to predict the IDH mutation status of gliomas based on multicenter magnetic resonance (MR) images using radiomic models, which were composed from the selected radiomics features and logistic regression (LR), support vector machine (SVM), and LR least absolute shrinkage and selection operator (LASSO) classifiers., Methods: We retrospectively reviewed the medical records of 205 patients with gliomas. We enrolled 78 patients from Shandong Provincial Hospital from January 2018 to December 2019 as testing sets and 127 patients from The Cancer Genome Atlas (TCGA) as training sets. Preoperative MR images were stratified according to their IDH status, and the participants formed a consecutive and random series. Four MR modalities, including T1C, T2, T1 fluid-attenuated inversion recovery (FLAIR), and T2 FLAIR, were used for analysis. Five-fold cross-validation was adopted to train the models, and the models' performances were verified through the testing set. Tumor volumes of interest (VOI) were delineated on the 4 MR modalities. A total of 428 radiomics features were extracted. Two feature selection algorithms, Pearson correlation coefficient (PCC) and recursive feature elimination (RFE), were used to select radiomics features. These features were fed into 3 machine learning classifiers, which were LR, SVM, and LR LASSO, to construct prediction models. The accuracy (ACC), sensitivity (SEN), specificity (SPEC), and area under the curve (AUC) were applied to measure the predictive performance of the radiomics models., Results: The LR (SVM and LR LASSO) classifier predicted IDH mutation status with an average testing set ACC of 80.77% (80.64% and 80.41%), a SEN of 73.68% (84.21% and 89.47%), a SPEC of 87.50% (67.50% and 62.50%), and an AUC of 0.8572 (0.8217 and 0.8164)., Conclusions: The radiomics models based on MR modalities demonstrated the potential to be used as tools across different data sets for the noninvasive prediction of the IDH mutation status in glioma., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-836/coif). The authors have no conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

The Internet of Things (IoT) and blockchain, the hottest frontier technologies in recent years, are expected to lead the next technological revolution. Blockchain promises to solve the current challenges encountered by the IoT. However, most of the proposed blockchain-based IoT architectures, which are based on discrete logarithm or large integer factorization problems, are susceptible to quantum attacks. Several quantum-resistant blockchain schemes have recently been proposed. However, the efficiency of their construction or the equipment required is not satisfactory. In this paper, to construct a more efficient postquantum blockchain infrastructure, we propose blockchain architecture for the IoT over the NTRU lattice and provide a cryptographic security proof of the scheme. Attributed to the more efficient underlying lattice structure, our scheme has excellent performance when compared to the existing quantum-resistant blockchain scheme, and we reduce the transaction size from hundreds of megabytes to several kilobytes. To further improve the blockchain's performance, we present the general framework of segregated witnesses and aggregate signatures over the NTRU lattice. Our scheme promises a blockchain solution for resource-constrained environments., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yuan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The biosynthesis of citric acid (CA) using Aspergillus niger as a carrier is influenced by mycelium morphology, which is determined by the expression level of morphology-related genes. As a key component of the fungal cell wall, chitin content has an important effect on morphogenesis, and to investigate the effects of this on fermentation performance, we used RNA interference to knockdown chitin synthase C (CHSC) and chitin synthase activator (CHS3) to obtain the single-gene mutant strains A. niger chs3 and chsC and the double mutant A. niger chs3C. We found that the CA fermentation performance of the two single mutants was significantly better than that of the double mutant. The mutant A. niger chs3-4 exhibited CA production potential compared to that of the parent strain in scale-up fermentation; we determined certain characteristics of CA high-yielding strain fermentation pellets. In addition, when chsC alone was silenced, there was very little change in chs3 mRNA levels, whereas those of chsC were significantly reduced when only chs3 was silenced. As this may be because of a synergistic effect between chsC and chs3, and we speculated that the latent activation target of CHS3 is CHSC, our results confirmed this hypothesis. This study is the first application of a separation and combination silence strategy of chitin synthase and chitin synthase activator in the morphology of A. niger CA fermentation. Furthermore, it provides new insights into the method for the morphological study of A. niger fermentation and the interaction of homologous genes. KEY POINTS: • The function of chitin synthase C (chsC) and chitin synthase activator (chs3) is tightly interrelated. • Mycelial morphology was optimized by knockdown of CHS3, resulting in the overproduction of citric acid. • The separation and combination silence strategies are promising tools for the interaction of homologous housekeeping genes., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Identifying the most influential spreaders in online social networks plays a prominent role in affecting information dissemination and public opinions. Researchers propose many effective identification methods, such as k-shell. However, these methods are usually validated by simulating propagation models, such as epidemic-like models, which rarely consider the Push-Republish mechanism with attenuation characteristic, the unique and widely-existing spreading mechanism in online social media. To address this issue, we first adopt the Push-Republish (PR) model as the underlying spreading process to check the performance of identification methods. Then, we find that the performance of classical identification methods significantly decreases in the PR model compared to epidemic-like models, especially when identifying the top 10% of superspreaders. Furthermore, inspired by the local tree-like structure caused by the PR model, we propose a new identification method, namely the Local-Forest (LF) method, and conduct extensive experiments in four real large networks to evaluate it. Results highlight that the Local-Forest method has the best performance in accurately identifying superspreaders compared with the classical methods.

While inequalities in science are common, most efforts to understand them treat scientists as isolated individuals, ignoring the network effects of collaboration. Here, we develop models that untangle the network effects of productivity defined as paper counts, and prominence referring to high-impact publications, of individual scientists from their collaboration networks. We find that gendered differences in the productivity and prominence of mid-career researchers can be largely explained by differences in their coauthorship networks. Hence, collaboration networks act as a form of social capital, and we find evidence of their transferability from senior to junior collaborators, with benefits that decay as researchers age. Collaboration network effects can also explain a large proportion of the productivity and prominence advantages held by researchers at prestigious institutions. These results highlight a substantial role of social networks in driving inequalities in science, and suggest that collaboration networks represent an important form of unequally distributed social capital that shapes who makes what scientific discoveries., (© 2022. The Author(s).)

Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model called HTNet for diagnosis of HT by training on 106,513 thyroid ultrasound images from 17,934 patients and test its performance on 5051 patients from 2 datasets of static images and 1 dataset of video data. HTNet achieves an area under the receiver operating curve (AUC) of 0.905 (95% CI: 0.894 to 0.915), 0.888 (0.836-0.939) and 0.895 (0.862-0.927). HTNet exceeds radiologists' performance on accuracy (83.2% versus 79.8%; binomial test, p < 0.001) and sensitivity (82.6% versus 68.1%; p < 0.001). By integrating serologic markers with imaging data, the performance of HTNet was significantly and marginally improved on the video (AUC, 0.949 versus 0.888; DeLong's test, p = 0.004) and static-image (AUC, 0.914 versus 0.901; p = 0.08) testing sets, respectively. HTNet may be helpful as a tool for the management of HT., (© 2022. The Author(s).)

Nutritional food supplements and pharmaceutical products produced with vitamin K 2 as raw materials a very promising market in the global scope. The main production method of vitamin K 2 is microbial fermentation, but approximately 50% of vitamin K 2 synthesized by the main production strain Bacillus subtilis natto exists in extracellular form, which is not easy to separate and extract. In order to solve this problem, in this study, we synthesized a novel cellulose flocculant, MCC-g-LMA, by grafting reaction using microcrystalline cellulose (MCC) and lauryl methacrylate (LMA) as monomers, and ammonium persulfate as an initiator to flocculate VK 2 from the fermentation supernatant. The flocculant was characterized by Fourier transform infrared spectroscopy (FTIR), elemental analysis, and scanning electron microscopy (SEM), and the grafting reaction was successful. When the flocculant dosage was 48.0 mg/L and pH was 5.0, the flocculation rate of the MCC-g-LMA on the fermentation supernatant reached 85.3%, and the enrichment rate of VK 2 reached 90.0%. Furthermore, we explored the flocculation mechanism of VK 2 by the MCC-g-LMA and speculated that the flocculation mechanism mainly included adsorption bridging, hydrophobic association and net trapping and sweep effect. In this study, the extraction method for trace high-value biological products in the fermentation supernatant was improved, which provided a method and theoretical basis for the efficient separation and purification of VK 2 and other terpenoids.

Public goods games are widely used to model social dilemmas involving multiple agents. Though defection is the only rational choice for an individual in a public goods game, cooperative behavior is observed in a variety of social dilemmas, which is the subject of our research. Punishing defectors has been shown to be an effective mechanism for promoting cooperation, but it relies on the third-party umpire being fair. In this article, an umpire intervention model with corruption is proposed to explore the impact of corruption on punishment mechanisms. In our model, players and umpires operate in a multilayer network. The players play public goods games, which are overseen by umpires. Fair umpires punish defectors, whereas corrupt umpires take bribes from defectors rather than meting out a punishment. We separately explore the effects of the fraction of fair umpires ρ , the spatial distribution, and the fine cost α and bribe cost β. Our Monte Carlo simulation shows that the above factors have a significant impact on cooperation. Intervention by an umpire always improves social efficiency, even for an entirely corrupt system. Moreover, relatively developed systems can resist corruption. Staggered and centralized distributions always have opposite effects on cooperative behavior, and these effects depend on ρ and r. We also find that whether cooperators fully occupy the player layer depends only on whether β reaches a certain threshold.

Background: Menaquinone-7 (MK-7), which is associated with complex and tightly regulated pathways and redox imbalances, is produced at low titres in Bacillus subtilis. Synthetic biology provides a rational engineering principle for the transcriptional optimisation of key enzymes and the artificial creation of cofactor regeneration systems without regulatory interference. This holds great promise for alleviating pathway bottlenecks and improving the efficiency of carbon and energy utilisation., Results: We used a bottom-up synthetic biology approach for the synthetic redesign of central carbon and to improve the adaptability between material and energy metabolism in MK-7 synthesis pathways. First, the rate-limiting enzymes, 1-deoxyxylulose-5-phosphate synthase (DXS), isopentenyl-diphosphate delta-isomerase (Fni), 1-deoxyxylulose-5-phosphate reductase (DXR), isochorismate synthase (MenF), and 3-deoxy-7-phosphoheptulonate synthase (AroA) in the MK-7 pathway were sequentially overexpressed. Promoter engineering and fusion tags were used to overexpress the key enzyme MenA, and the titre of MK-7 was 39.01 mg/L. Finally, after stoichiometric calculation and optimisation of the cofactor regeneration pathway, we constructed two NADPH regeneration systems, enhanced the endogenous cofactor regeneration pathway, and introduced a heterologous NADH kinase (Pos5P) to increase the availability of NADPH for MK-7 biosynthesis. The strain expressing pos5P was more efficient in converting NADH to NADPH and had excellent MK-7 synthesis ability. Following three Design-Build-Test-Learn cycles, the titre of MK-7 after flask fermentation reached 53.07 mg/L, which was 4.52 times that of B. subtilis 168. Additionally, the artificially constructed cofactor regeneration system reduced the amount of NADH-dependent by-product lactate in the fermentation broth by 9.15%. This resulted in decreased energy loss and improved carbon conversion., Conclusions: In summary, a "high-efficiency, low-carbon, cofactor-recycling" MK-7 synthetic strain was constructed, and the strategy used in this study can be generally applied for constructing high-efficiency synthesis platforms for other terpenoids, laying the foundation for the large-scale production of high-value MK-7 as well as terpenoids., (© 2022. The Author(s).)

Brain health is an important research direction of neuroscience. In addition to the effects of diseases, we cannot ignore the negative effect of aging on brain health. There have been many studies on brain aging, but only a few have used dynamic models to analyze differences in micro brain characteristics in healthy people. In this article, we use the relaxed mean-field model (rMFM) to study the effects of normal aging. Two main parameters of this model are the recurrent connection strength and subcortical input strength. The sensitivity of the rMFM to the initial values of the parameters has not been fully discussed in previous research. We examine this issue through repeated numerical experiments and obtain a reasonable initial parameter range for this model. Differences in recurrent connection strength and subcortical input strength due to aging have also not been studied previously. We use statistical methods to find the regions of interest (ROIs) exhibiting significant differences between young and old groups. Further, we carry out a difference analysis on the process of change of these ROIs on a more detailed timescale. We find that even with the same final results, the trends of change in these ROIs are different. This shows that to develop possible methods to prevent or delay brain damage due to aging, more attention needs to be paid to the trends of change of different ROIs, not just the final results., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhan, Zheng, Yang, Zhen, Tang and Zheng.)

Vitamin K2, a natural fat-soluble vitamin, is a potent neuroprotective molecule, owing to its antioxidant effect, but its mechanism has not been fully elucidated. Therefore, we stimulated SH-SY5Y cells with 6-hydroxydopamine (6-OHDA) in a proper dose-dependent manner, followed by a treatment of vitamin K2. In the presence of 6-OHDA, cell viability was reduced, the mitochondrial membrane potential was decreased, and the accumulation of reactive oxygen species (ROS) was increased. Moreover, the treatment of 6-OHDA promoted mitochondria-mediated apoptosis and abnormal mitochondrial fission and fusion. However, vitamin K2 significantly suppressed 6-OHDA-induced changes. Vitamin K2 played a significant part in apoptosis by upregulating and downregulating Bcl-2 and Bax protein expressions, respectively, which inhibited mitochondrial depolarization, and ROS accumulation to maintain mitochondrial structure and functional stabilities. Additionally, vitamin K2 significantly inhibited the 6-OHDA-induced downregulation of the MFN1/2 level and upregulation of the DRP1 level, respectively, and this enabled cells to maintain the dynamic balance of mitochondrial fusion and fission. Furthermore, vitamin K2 treatments downregulated the expression level of p62 and upregulated the expression level of LC3A in 6-OHDA-treated cells via the PINK1/Parkin signaling pathway, thereby promoting mitophagy. Moreover, it induced mitochondrial biogenesis in 6-OHDA damaged cells by promoting the expression of PGC-1α, NRF1, and TFAM. These indicated that vitamin K2 can release mitochondrial damage, and that this effect is related to the participation of vitamin K2 in the regulation of the mitochondrial quality-control loop, through the maintenance of the mitochondrial quality-control system, and repair mitochondrial dysfunction, thereby alleviating neuronal cell death mediated by mitochondrial damage.

Background: The study and application of microbial consortia are topics of interest in the fields of metabolic engineering and synthetic biology. In this study, we report the design and optimisation of Elizabethkingia meningoseptica and Escherichia coli co-culture, which bypass certain limitations found during the molecular modification of E. meningoseptica, such as resistance to many antibiotics and fewer available molecular tools., Results: The octaprenyl pyrophosphate synthase from E. meningoseptica sp. F2 (EmOPPS) was expressed, purified, and identified in the present study. Then, owing to the low vitamin K2 production by E. coli or E. meningoseptica sp. F2 monoculture, we introduced the E. meningoseptica and E. coli co-culture strategy to improve vitamin K2 biosynthesis. We achieved production titres of 32 mg/L by introducing vitamin K2 synthesis-related genes from E. meningoseptica sp. F2 into E. coli, which were approximately three-fold more than the titre achieved with E. meningoseptica sp. F2 monoculture. This study establishes a foundation for further engineering of MK-n (n = 4, 5, 6, 7, 8) in a co-cultivation system of E. meningoseptica and E. coli. Finally, we analysed the surface morphology, esterase activity, and membrane permeability of these microbial consortia using scanning electron microscopy, confocal laser scanning microscopy, and flow cytometry, respectively. The results showed that the co-cultured bacteria were closely linked and that lipase activity and membrane permeability improved, which may be conducive to the exchange of substances between bacteria., Conclusions: Our results demonstrated that co-culture engineering can be a useful method in the broad field of metabolic engineering of strains with restricted molecular modifications., (© 2022. The Author(s).)

To date, there is no functional characterization of EmGGPPS (from Elizabethkingia meningoseptica sp.F2) as enzymes catalyzing GGPP. In this research, maltose-binding protein (MBP), disulfide bond A (DbsA), disulfide bond C (DbsC), and two other small protein tags, GB1 (Protein G B1 domain) and ZZ (Protein A IgG ZZ repeat domain), were used as fusion partners to construct an EmGGPPS fusion expression system. The results indicated that the expression of MBP-EmGGPPS was higher than that of the other four fusion proteins in E. coli BL21 (DE3). Additionally, using EmGGPPS as a catalyst for the production of GGPP was verified using a color complementation assay in Escherichia coli. In parallel with it, the enzyme activity experiment in vitro showed that the EmGGPPS protein could produce GGPP, GPP and FPP. Finally, we successfully demonstrated MK-4 production in engineered E. coli by overexpression of EmGGPPS., (Copyright © 2021. Published by Elsevier Inc.)

Despite the high specific capacity of silicon as a promising anode material for the next-generation high-capacity Li-ion batteries (LIBs), its practical applications are impeded by the rapid capacity decay during cycling. To tackle the issue, herein, a binder-grafting strategy is proposed to construct a covalently cross-linked binder [carboxymethyl cellulose/phytic acid (CMC/PA)], which builds a robust branched network with more contact points, allowing stronger bonds with Si nanoparticles by hydrogen bonding. Benefitting from the enhanced mechanical reliability, the resulting Si-CMC/PA electrodes exhibit a high reversible capacity with improved long-term cycling stability. Moreover, an assembled full cell consisting of the as-obtained Si-CMC/PA anode and commercial LiFePO 4 cathode also exhibits excellent cycling performance (120.4 mA h g -1 at 1 C for over 100 cycles with 88.4% capacity retention). In situ transmission electron microscopy was employed to visualize the binding effect of CMC/PA, which, unlike the conventional CMC binder, can effectively prevent the lithiated Si anodes from cracking. Furthermore, the combined ex situ microscopy and X-ray photoelectron spectroscopy analysis unveils the origin of the superior Li-ion storage performance of the Si-CMC/PA electrode, which arises from its excellent structural integrity and the stabilized solid-electrolyte interphase films during cycling. This work presents a facile and efficient binder-engineering strategy for significantly improving the performance of Si anodes for next-generation LIBs.

Cross-modal retrieval has become a topic of popularity, since multi-data is heterogeneous and the similarities between different forms of information are worthy of attention. Traditional single-modal methods reconstruct the original information and lack of considering the semantic similarity between different data. In this work, a cross-modal semantic autoencoder with embedding consensus (CSAEC) is proposed, mapping the original data to a low-dimensional shared space to retain semantic information. Considering the similarity between the modalities, an automatic encoder is utilized to associate the feature projection to the semantic code vector. In addition, regularization and sparse constraints are applied to low-dimensional matrices to balance reconstruction errors. The high dimensional data is transformed into semantic code vector. Different models are constrained by parameters to achieve denoising. The experiments on four multi-modal data sets show that the query results are improved and effective cross-modal retrieval is achieved. Further, CSAEC can also be applied to fields related to computer and network such as deep and subspace learning. The model breaks through the obstacles in traditional methods, using deep learning methods innovatively to convert multi-modal data into abstract expression, which can get better accuracy and achieve better results in recognition., (© 2021. The Author(s).)

Objective: Large volume radiological text data have been accumulated since the incorporation of electronic health record (EHR) systems in clinical practice. We aimed to determine whether deep natural language processing algorithms could aid radiologists in improving thyroid cancer diagnosis., Methods: Sonographic EHR data were obtained from the EHR database. Pathological reports were used as the gold standard for diagnosing thyroid cancer. We developed thyroid cancer diagnosis based on natural language processing (THCaDxNLP) to interpret unstructured sonographic text reports for thyroid cancer diagnosis. We used the area under the receiver operating characteristic curve (AUROC) as the primary metric to measure the performance of the THCaDxNLP. We compared the performance of thyroid ultrasound radiologists aided with THCaDxNLP vs. those without THCaDxNLP using 5 independent test sets., Results: We obtained a total number of 788,129 sonographic radiological reports. The number of thyroid sonographic data points was 132,277, 18,400 of which were thyroid cancer patients. Among the 5 test sets, the numbers of patients per set were 439, 186, 82, 343, and 171. THCaDxNLP achieved high performance in identifying thyroid cancer patients (the AUROC ranged from 0.857-0.932). Thyroid ultrasound radiologists aided with THCaDxNLP achieved significantly higher performances than those without THCaDxNLP in terms of accuracy (93.8% vs. 87.2%; one-sided t -test, adjusted P = 0.003), precision (92.5% vs. 86.0%; P = 0.018), and F1 metric (94.2% vs. 86.4%; P = 0.007)., Conclusions: THCaDxNLP achieved a high AUROC for the identification of thyroid cancer, and improved the accuracy, sensitivity, and precision of thyroid ultrasound radiologists. This warrants further investigation of THCaDxNLP in prospective clinical trials., Competing Interests: No potential conflicts of interest are disclosed., (Copyright © 2021 Cancer Biology & Medicine.)

Lattice-based non-interactive zero-knowledge proof has been widely used in one-way communication and can be effectively applied to resist quantum attacks. However, lattice-based non-interactive zero-knowledge proof schemes have long faced and paid more attention to some efficiency issues, such as proof size and verification time. In this paper, we propose the non-interactive zero-knowledge proof schemes from RLWE-based key exchange by making use of the Hash function and public-key encryption. We then show how to apply the proposed schemes to achieve the fixed proof size and rapid public verification. Compared with previous approaches, our schemes can realize better effectiveness in proof size and verification time. In addition, the proposed schemes are secure from completeness, soundness, and zero-knowledge., Competing Interests: The authors have declared that no competing interests exist.

Structures of genetic regulatory networks are not fixed. These structural perturbations can cause changes to the reachability of systems' state spaces. As system structures are related to genotypes and state spaces are related to phenotypes, it is important to study the relationship between structures and state spaces. However, there is still no method can quantitively describe the reachability differences of two state spaces caused by structural perturbations. Therefore, Difference in Reachability between State Spaces (DReSS) is proposed. DReSS index family can quantitively describe differences of reachability, attractor sets between two state spaces and can help find the key structure in a system, which may influence system's state space significantly. First, basic properties of DReSS including non-negativity, symmetry and subadditivity are proved. Then, typical examples are shown to explain the meaning of DReSS and the differences between DReSS and traditional graph distance. Finally, differences of DReSS distribution between real biological regulatory networks and random networks are compared. Results show most structural perturbations in biological networks tend to affect reachability inside and between attractor basins rather than to affect attractor set itself when compared with random networks, which illustrates that most genotype differences tend to influence the proportion of different phenotypes and only a few ones can create new phenotypes. DReSS can provide researchers with a new insight to study the relation between genotypes and phenotypes., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

By comparing the survival rate and positive mutation rate of the primary mutagenic strain and progeny mutagenic strain under different radiation doses, the results showed that the tolerance of the mutagenic strain to radiation dose increased with the increase of the mutagenic generations. We adopted an improved gradient radiation breeding strategy to improve the breeding efficiency. The strains were treated with radiation in four stages. The first stage was low energy N + ion implantation (ion energy 15 keV, dose 80 × 2.6 × 10 13  cm -2 ). In the second stage, the energy and dose of N + ion reached to 20 keV, 90 × 2.6 × 10 13  cm -2 . In the third stage, 60 Co-γ radiation (dose of 1.56 kGy) was used. In the fourth stage, the radiation dose of 60 Co-γ increased to 1.82 kGy. After each stage of radiation, the MK (Menaquinone) precursor 1, 4-dihydroxy-2-naphthalate (DHNA) was used as the stress factor to domesticate the mutant strains. By gradually increasing the concentration of DHNA in the culture medium, the substrate tolerance of Flavobacterium sp. was effectively improved. By measuring SOD (superoxide dismutase) activity and malondialdehyde, it showed that the cell damage caused by radiation mutagenesis to the offspring mutant was less than that of the primary mutant. Changes in membrane permeability and membrane potential of the mutant strains were reflected in changes in fluorescence intensity of luciferin diacetate and rhodamine 123, which could explain the enhanced substrate tolerance of strain F-2. After gradient radiation breeding and culture acclimation, the biomass of mutant Strain F-2 was 6.59 g/L, and the MK yield was 9.59 mg/L.

Menaquinone-7 is involved in bone metabolism and can be used to prevent and treat osteoporosis. However, as a fat-soluble vitamin, menaquinone-7 has poor water solubility. As a surfactant, hydrophobins can change the affinity/hydrophobicity of the covered interface. In this study, menaquinone-7 was modified by hydrophobins, and the different addition ratios were explored. Moreover, Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS), and water contact angle (WCA) measurements indicated that hydrophobins effectively bind to menaquinone-7 and greatly increase the hydrophilicity of the surface of menaquinone-7. Studies on the metabolism of MC3T3-E1 cells showed that compared with native menaquinone-7, HGFI-modified menaquinone-7 can significantly promote osteoblast differentiation but inhibit osteoclast differentiation. Besides, the Mito-Tracker Green experiments show that HGFI-modified menaquinone-7 can significantly promote the activity of mitochondria in cells. These findings indicate that hydrophobins can be used as an effective biomaterial to modify menaquinone-7, promote the formation of osteoblasts, and better to bone balance.

Prisoner's dilemma game is the most commonly used model of spatial evolutionary game which is considered as a paradigm to portray competition among selfish individuals. In recent years, Win-Stay-Lose-Learn, a strategy updating rule base on aspiration, has been proved to be an effective model to promote cooperation in spatial prisoner's dilemma game, which leads aspiration to receive lots of attention. In this paper, according to Expected Value Theory and Achievement Motivation Theory, we propose a dynamic aspiration model based on Win-Stay-Lose-Learn rule in which individual's aspiration is inspired by its payoff. It is found that dynamic aspiration has a significant impact on the evolution process, and different initial aspirations lead to different results, which are called Stable Coexistence under Low Aspiration, Dependent Coexistence under Moderate aspiration and Defection Explosion under High Aspiration respectively. Furthermore, a deep analysis is performed on the local structures which cause defectors' re-expansion, the concept of END- and EXP-periods are used to justify the mechanism of network reciprocity in view of time-evolution, typical feature nodes for defectors' re-expansion called Infectors, Infected nodes and High-risk cooperators respectively are found. Compared to fixed aspiration model, dynamic aspiration introduces a more satisfactory explanation on population evolution laws and can promote deeper comprehension for the principle of prisoner's dilemma., Competing Interests: The authors have declared that no competing interests exist.

Background: Classification of diseases based on genetic information is of great significance as the basis for precision medicine, increasing the understanding of disease etiology and revolutionizing personalized medicine. Much effort has been directed at understanding disease associations by constructing disease networks, and classifying patient samples according to gene expression data. Integrating human gene networks overcomes limited coverage of genes. Incorporating pathway information into disease classification procedure addresses the challenge of cellular heterogeneity across patients., Results: In this work, we propose a disease classification model LAMP, which concentrates on the layered assessment on modules and pathways. Directed human gene interactions are the foundation of constructing the human gene network, where the significant roles of disease and pathway genes are recognized. The fast unfolding algorithm identifies 11 modules in the largest connected component. Then layered networks are introduced to distinguish positions of genes in propagating information from sources to targets. After gene screening, hierarchical clustering and refined process, 1726 diseases from KEGG are classified into 18 categories. Also, it is expounded that diseases with overlapping genes may not belong to the same category in LAMP. Within each category, entropy is applied to measure the compositional complexity, and to evaluate the prospects for combination diagnosis and gene-targeted therapy for diseases., Conclusion: In this work, by collecting data from BioGRID and KEGG, we develop a disease classification model LAMP, to support people to view diseases from the perspective of commonalities in etiology and pathology. Comprehensive research on existing diseases can help meet the challenges of unknown diseases. The results provide suggestions for combination diagnosis and gene-targeted therapy, which motivates clinicians and researchers to reposition the understanding of diseases and explore diagnosis and therapy strategies.

Conversion-type transition-metal phosphide anode materials with high theoretical capacity usually suffer from low-rate capability and severe capacity decay, which are mainly caused by their inferior electronic conductivities and large volumetric variations together with the poor reversibility of discharge product (Li 3 P), impeding their practical applications. Herein, guided by density functional theory calculations, these obstacles are simultaneously mitigated by confining amorphous FeP nanoparticles into ultrathin 3D interconnected P-doped porous carbon nanosheets (denoted as FeP@CNs) via a facile approach, forming an intriguing 3D flake-CNs-like configuration. As an anode for lithium-ion batteries (LIBs), the resulting FeP@CNs electrode not only reaches a high reversible capacity (837 mA h g -1 after 300 cycles at 0.2 A g -1 ) and an exceptional rate capability (403 mA h g -1 at 16 A g -1 ) but also exhibits extraordinary durability (2500 cycles, 563 mA h g -1 at 4 A g -1 , 98% capacity retention). By combining DFT calculations, in situ transmission electron microscopy, and a suite of ex situ microscopic and spectroscopic techniques, we show that the superior performances of FeP@CNs anode originate from its prominent structural and compositional merits, which render fast electron/ion-transport kinetics and abundant active sites (amorphous FeP nanoparticles and structural defects in P-doped CNs) for charge storage, promote the reversibility of conversion reactions, and buffer the volume variations while preventing pulverization/aggregation of FeP during cycling, thus enabling a high rate and highly durable lithium storage. Furthermore, a full cell composed of the prelithiated FeP@CNs anode and commercial LiFePO 4 cathode exhibits impressive rate performance while maintaining superior cycling stability. This work fundamentally and experimentally presents a facile and effective structural engineering strategy for markedly improving the performance of conversion-type anodes for advanced LIBs.

BACKGROUND Thyroid nodules are extremely common and typically diagnosed with ultrasound whether benign or malignant. Imaging diagnosis assisted by Artificial Intelligence has attracted much attention in recent years. The aim of our study was to build an ensemble deep learning classification model to accurately differentiate benign and malignant thyroid nodules. MATERIAL AND METHODS Based on current advanced methods of image segmentation and classification algorithms, we proposed an ensemble deep learning classification model for thyroid nodules (EDLC-TN) after precise localization. We compared diagnostic performance with four other state-of-the-art deep learning algorithms and three ultrasound radiologists according to ACR TI-RADS criteria. Finally, we demonstrated the general applicability of EDLC-TN for diagnosing thyroid cancer using ultrasound images from multi medical centers. RESULTS The method proposed in this paper has been trained and tested on a thyroid ultrasound image dataset containing 26 541 images and the accuracy of this method could reach 98.51%. EDLC-TN demonstrated the highest value for area under the curve, sensitivity, specificity, and accuracy among five state-of-the-art algorithms. Combining EDLC-TN with models and radiologists could improve diagnostic accuracy. EDLC-TN achieved excellent diagnostic performance when applied to ultrasound images from another independent hospital. CONCLUSIONS Based on ensemble deep learning, the proposed approach in this paper is superior to other similar existing methods of thyroid classification, as well as ultrasound radiologists. Moreover, our network represents a generalized platform that potentially can be applied to medical images from multiple medical centers.

Prenyltransferase NovQ immobilized carboxymethyl cellulose magnetic nanoparticles (NCMNs) were successfully synthesized via a valuable approach integrated from nanocomposite preparation, and applied for the production of vitamin K 2 using menadione hydroquinol and dimethylallyl diphosphate (DMAPP) as substrates. To investigate the interaction between nanoparticles and NovQ, we characterized the nanocomposite, and revealed that carboxymethyl cellulose (CMC) and Fe 3 O 4 formed a core-shell structure to absorb NovQ in the reaction systems, resulting from the high affinity of immobilized materials. Meanwhile, NCMNs with excellent pH and temperature tolerance, enhanced prenylated activity, and improved stability were found. Molecular docking analysis was also conducted to justify the contribution of multiple amino acids and effect of nanoparticles on catalytic properties of NovQ. Taken together, our study introduces a promising strategy to prepare magnetic nanoparticles and improve the performance of catalyst, which aims for opening new orientations for synthesis of magnetic nanoparticles used for prenyltransferase immobilization., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Prenyltransferase NovQ is a vital class involved in the biosynthesis of secondary metabolites such as clorobiocin and novobiocin. To investigate the relationship between structure and catalytic properties of NovQ, here, we have analyzed the substrate-binding site, namely PT barrel, and revealed that menadione hydroquinol formed intermolecular interactions with the residue Glu281 near the center of the active pocket. In this study, Glu281 was substituted with 9 diverse amino acids and catalytic properties of mutants were observed in vitro. Among them, E281Q showed 2.05-fold activities towards the aromatic substrate and prenyl donor, while others obtained catalytic efficiency between 8.4 and 88.6% of that of wild-type NovQ. Furthermore, the effects of catalytic conditions and substrate status on the activity of NovQ and its mutants were considered to obtain the optimized prenylated reaction. When the evolutionary NovQ variant E281Q was overexpressed in the host constructed to synthesize dimethylallyl diphosphate through the engineered mevalonate (MVA) pathway, we harvested up to 4.7 mg/L prenylated menadione at C-3 position by exogenously supplying the aromatic substrate. The construction of the microbial platform based on NovQ opens a new orientation to further biosynthesize various vitamin K 2 with other ABBA prenyltransferases in E. coli.

The published online version contains some errors.

Background: The newly developed sugarcorn is conceived for dual-purpose use as a potential biofuel feedstock and a high-energy silage crop. Its agronomic traits are, however, not fully appraised under the umbrella of nitrogen (N) management and with canopy reflectance indicator. A 3-year field study was conducted to examine the responses of silage biomass, stalk sugar concentration, sugar and juice yields to various N applications; and determine the quantitative relationships between canopy reflectance, expressed as the normalized difference vegetation index (NDVI), and stalk sucrose or other sugar measures in a dual-purpose sugarcorn (cv. 'CO384xC103'), in comparison with a commercial leafy silage-specific hybrid (cv. 'Pride A5892G3 EDF')., Results: The moderate N rate, 125 kg ha -1 , produced similar stalk sucrose, silage and grain yields, compared to the high rate (250 kg N ha -1 ), regardless of application methods. The NDVI signatures measured at the V8-V10 stage exhibited significant (P < 0.01) and exponential relationships with stalk sucrose concentrations, sucrose and juice yields at the R3 stage, and with silage yield at approximately 65% whole-plant moisture, the optimum silage-harvest window., Conclusion: The results indicate that the moderate N rate, 125 kg ha -1 , which is recommended for conventional grain corn production in the region, was likely close to the economic optimum N rate for leafy silage-specific and sugarcorn. Canopy reflectance, measured at the early growth stages, can be used as a potential indicator of sugar and silage production, and this quantitative relationship necessitates further evaluation with more genotypes and under wide environmental conditions. © 2019 Her Majesty the Queen in Right of Canada Journal of The Science of Food and Agriculture © 2019 Society of Chemical Industry., (© 2019 Her Majesty the Queen in Right of Canada Journal of The Science of Food and Agriculture © 2019 Society of Chemical Industry.)

Feedback loops between population dynamics of individuals and their ecological environment are ubiquitously found in nature and have shown profound effects on the resulting eco-evolutionary dynamics. By incorporating linear environmental feedback law into the replicator dynamics of two-player games, recent theoretical studies have shed light on understanding the oscillating dynamics of the social dilemma. However, the detailed effects of more general nonlinear feedback loops in multi-player games, which are more common especially in microbial systems, remain unclear. Here, we focus on ecological public goods games with environmental feedbacks driven by a nonlinear selection gradient. Unlike previous models, multiple segments of stable and unstable equilibrium manifolds can emerge from the population dynamical systems. We find that a larger relative asymmetrical feedback speed for group interactions centred on cooperators not only accelerates the convergence of stable manifolds but also increases the attraction basin of these stable manifolds. Furthermore, our work offers an innovative manifold control approach: by designing appropriate switching control laws, we are able to steer the eco-evolutionary dynamics to any desired population state. Our mathematical framework is an important generalization and complement to coevolutionary game dynamics, and also fills the theoretical gap in guiding the widespread problem of population state control in microbial experiments., Competing Interests: We declare we have no competing interests., (© 2020 The Authors.)

Increasing evidence shows that static magnetic fields (SMFs) can affect microbial growth metabolism, but the specific mechanism is still unclear. In this study, we have investigated the effect of moderate-strength SMFs on growth and vitamin K 2 biosynthesis of Flavobacterium sp. m1-14. First, we designed a series of different moderate-strength magnetic field intensities (0, 50, 100, 150, 190 mT) and exposure times (0, 24, 48, 72, 120 h). With the optimization of static magnetic field intensity and exposure time, biomass and vitamin K 2 production significantly increased compared to control. The maximum vitamin K 2 concentration and biomass were achieved when exposed to 100 mT SMF for 48 h; compared with the control group, they increased by 71.3% and 86.8%, respectively. Interestingly, it was found that both the cell viability and morphology changed significantly after SMF treatment. Second, the adenosine triphosphate (ATP) and glucose-6-phosphate dehydrogenase (G6PDH) metabolism is more vigorous after exposed to 100 mT SMF. This change affects the cell energy metabolism and fermentation behavior, and may partially explain the changes in bacterial biomass and vitamin K 2 production. The results show that moderate-strength SMFs may be a promising method to promote bacterial growth and secondary metabolite synthesis.