Enhancement of microbial community dynamics and metabolism in compost through ammonifying cultures inoculation.

The efficient use of livestock and poultry manure waste has become a global challenge, with microorganisms playing an important role. To investigate the impact of novel ammonifying microorganism cultures (NAMC) on microbial community dynamics and carbon and nitrogen metabolism, five treatments [5% (v/w) sterilized distilled water, Amm-1, Amm-2, Amm-3, and Amm-4] were applied to cow manure compost. Inoculation with NAMC improved the structure of bacterial and fungal communities, enriched the populations of the functional microorganisms, enhanced the role of specific microorganisms, and promoted the formation of tight modularity within the microbial network. Further functional predictions indicated a significant increase in both carbon metabolism (CMB) and nitrogen metabolism (NMB). During the thermophilic phase, inoculated NAMC treatments boosted carbon metabolism annotation by 10.55%-33.87% and nitrogen metabolism annotation by 26.69%-63.11. Structural equation modeling supported the NAMC-mediated enhancement of NMB and CMB. In conclusion, NAMC inoculation, particularly with Amm-4, enhanced the synergistic interaction between bacteria and fungi. This collaboration promoted enzymatic catabolic and synthetic processes, resultng in positive feedback loops with the endogenous microbial community. Understanding these mechanisms not only unravels how ammonifying microorganisms influence microbial communities but also paves the way for the development of the composting industry and global waste management practices.

A randomized, controlled clinical trial of acupoint catgut embedding as an effective control of functional anorectal pain.

BACKGROUND: Patients with functional anorectal pain (FAP) usually feel pain in the anal region, foreign body sensation, and defecation disorders. The pain may radiate to the perineum, thighs, and waist. Conventional biofeedback, local nerve block and surgical treatment have certain limitations. Thread-embedding acupuncture (TEA) is a complementary and alternative therapy, which is widely used in the clinical practice of traditional Chinese medicine to treat functional anorectal pain. This study evaluated the efficacy and safety of the catgut-embedding acupuncture in patients with FAP. METHODS: FAP patients were enrolled and randomly divided into a thread-embedding acupuncture group (n = 35) and a sham-embedding acupuncture control group (n = 36). Patients underwent treatment twice monthly for 2 months and were assessed before and after treatments for visual analogue scales (VAS) of anorectal pain, VAS of lumbar pain or soreness, VAS of abdominal distension or pain, anal incontinence index, and SF-36 quality of life. The SF-36 quality of life score included assessment of physical functioning, role-physical, bodily-pain, general health, role-emotional, social functioning, vitality, and mental health. RESULT: The total effective rate was 85.71% for the treatment group versus 8.33% of the controls after 2 months (P < .001). The patients' anal rectum VAS score was significantly higher after treatment versus pretreatment (P < .01), while the physical functioning, role-physical, bodily-pain, role-emotional, and mental health in the experimental group and the role-emotional, and mental health in the control group were all significantly improved versus pretreatment (P < .05). The anorectal VAS score, anal incontinence index, and the SF-36 scores of the physical functioning, role-physical, bodily-pain, role-emotional, and mental health were better in the treatment group compared to the control group (P < .05). Most importantly, there were no adverse reactions observed in either group during the treatment. CONCLUSION: The thread-embedding acupuncture treatment effectively and safely improved the emotional anxiety and quality of life in FAP patients.

[Electroacupuncture at acupoints of yangming meridians for sarcopenia: a randomized controlled trial].

OBJECTIVE: To observe the clinical effect of electroacupuncture at acupoints of yangming meridians for sarcopenia. METHODS: A total of 60 patients with sarcopenia were randomized into an observation group and a control group, 30 cases in each group. In the control group, conventional nutrition intervention for sarcopenia was adopted. In the observation group, on the basis of the treatment in the control group, acupuncture was applied at bilateral Binao (LI 14), Quchi (LI 11), Zusanli (ST 36), Yanglingquan (GB 34), etc.,ipsilateral Quchi (LI 11) and Zusanli (ST 36) were connected to electroacupuncture, with discontinuous wave, 2 Hz in frequency, 1-10 mA in intensity, 2 times a week, with a interval of 3 days. A total of 12-week treatment was required in the two groups. Before and after treatment, the appendicular skeletal muscle mass index (ASMI), grip strength, 6 m-walking time, body fat percentage and body moisture percentage were observed in the two groups. RESULTS: Compared with those before treatment, after treatment, ASMI and grip strength were increased while 6 m-walking time was shortened in the two groups (P<0.05); body fat percentage was decreased while body moisture percentage was increased in the observation group (P<0.05). After treatment, in the observation group, ASMI, grip strength and body moisture percentage were increased (P<0.05), 6 m-walking time was shortened and body fat percentage was decreased (P<0.05) compared with those in the control group. CONCLUSION: Electroacupuncture at acupoints of yangming meridians can effectively improve the skeletal muscle mass, muscle function, body fat percentage and body moisture percentage in patients with sarcopenia, and make the distribution of muscle and fat more reasonable.

Projective Synchronization of Delayed Uncertain Coupled Memristive Neural Networks and Their Application.

In this article, the authors analyzed the nonlinear effects of projective synchronization between coupled memristive neural networks (MNNs) and their applications. Since the complete signal transmission is difficult under parameter mismatch and different projective factors, the delays, which are time-varying, and uncertainties have been taken to realize the projective synchronization of MNNs with multi-links under the nonlinear control method. Through the extended comparison principle and a new approach to dealing with the mismatched parameters, sufficient criteria have been determined under different types of projective factors and the framework of the Lyapunov-Krasovskii functional (LKF) for projective convergence of the coupled MNNs. Instead of the classical treatment for secure communication, the concept of error of synchronization between the drive and response systems has been applied to solve the signal encryption/decryption problem. Finally, the simulations in numerical form have been demonstrated graphically to confirm the adaptability of the theoretical results.

Mapping of the Cladosporium fulvum resistance gene Cf-16, a major gene involved in leaf mold disease in tomato.

Tomato (Solanum lycopersicum) is widely cultivated and consumed worldwide. Tomato leaf mold, caused by Cladosporium fulvum, is one of the most devastating diseases in tomato production. At present, some tomato leaf mold resistance (Cf series) genes used in production gradually lose resistance due to the continuous and rapid differentiation of C. fulvum physiological races. The Cf-16 gene derived from the "Ontario7816" tomato cultivar has shown effective resistance in field trials for many years, but few studies have reported on the mapping of the Cf-16 gene, which has not been cloned, limiting its utilization in tomato breeding. Here, we mapped Cf-16 using a novel comprehensive strategy including bulk segregation analysis (BSA), genome resequencing and SSR molecular markers. A genetic analysis revealed that Cf-16 resistance in "Ontario7816" is controlled by one major dominant locus. The Cf-16 gene was mapped in a region of 2.6 cM at chromosome 6 between two markers, namely, TGS447 and TES312, by using an F2 population from a cross between the resistant cultivar "Ontario7816" and susceptible line "Moneymaker." Two nucleotide-binding-site-leucine-rich repeat (NBS-LRR) resistance genes, namely, XM_004240667.3 and XM_010323727.1, were identified in this interval. They are strong candidates for the Cf-16 gene. The mapping of Cf-16 may speed up its utilization for breeding resistant tomato varieties and represents an important step forward in our understanding of the mechanism underlying resistance to tomato leaf mold.

Association of ATG4A single nucleotide polymorphism rs807185 on risk of microscopic polyangiitis in Chinese population.

BACKGROUND: Microscopic polyangiitis is a type of antineutrophil cytoplasmic antibody-associated vasculitis, characterized by a systemic, pauci-immune, necrotizing, small-vessel vasculitis without clinical or pathological evidence of necrotizing granulomatous inflammation. Many studies have linked autophagy-related gene polymorphisms to the development of immune diseases. However, the association between autophagy-related genes and microscopic polyangiitis remains unclear. OBJECTIVE: We investigated the association between microscopic polyangiitis and the single nucleotide polymorphism rs807185 in autophagy-associated gene 4A (ATG4A) in the Chinese population. METHODS: ATG4A single nucleotide polymorphism rs807185 frequency was identified using multiplex polymerase chain reaction and high-throughput sequencing in a cohort with microscopic polyangiitis (n = 181) and a healthy control group (n = 209). RESULTS: We found that the control cohort had a higher prevalence of allele A of rs807185 compared to the microscopic polyangiitis cohort. The rs807185A allele was therefore linked to a lower risk of microscopic polyangiitis. CONCLUSION: The single nucleotide polymorphism rs807185 allele A in ATG4A may have a protective effect against microscopic polyangiitis in the Chinese population, but the molecular mechanisms remain unclear.

Non-negative matrix factorization for overlapping community detection in directed weighted networks with sparse constraints.

Detecting overlapping communities is essential for analyzing the structure and function of complex networks. However, most existing approaches only consider network topology and overlook the benefits of attribute information. In this paper, we propose a novel attribute-information non-negative matrix factorization approach that integrates sparse constraints and optimizes an objective function for detecting communities in directed weighted networks. Our algorithm updates the basic non-negative matrix adaptively, incorporating both network topology and attribute information. We also add a sparsity constraint term of graph regularization to maintain the intrinsic geometric structure between nodes. Importantly, we provide strict proof of convergence for the multiplication update rule used in our algorithm. We apply our proposed algorithm to various artificial and real-world networks and show that it is more effective for detecting overlapping communities. Furthermore, our study uncovers the intricate iterative process of system evolution toward convergence and investigates the impact of various variables on network detection. These findings provide insights into building more robust and operable complex systems.

Fast Markov Clustering Algorithm Based on Belief Dynamics.

Graph clustering is one of the most significant, challenging, and valuable topic in the analysis of real complex networks. To detect the cluster configuration accurately and efficiently, we propose a new Markov clustering algorithm based on the limit state of the belief dynamics model. First, we present a new belief dynamics model, which focuses beliefs of multicontent and randomly broadcasting information. A strict proof is provided for the convergence of nodes' normalized beliefs in complex networks. Second, we introduce a new Markov clustering algorithm (denoted as BMCL) by employing a belief dynamics model, which guarantees the ideal cluster configuration. Following the trajectory of the belief convergence, each node is mapped into the corresponding cluster repeatedly. The proposed BMCL algorithm is highly efficient: the convergence speed of the proposed algorithm researches O(TN) in sparse networks. Last, we implement several experiments to evaluate the performance of the proposed methods.

Protective effects of fowl-origin cadmium-tolerant lactobacillus against sub-chronic cadmium-induced toxicity in chickens.

Cadmium (Cd) directly endangers poultry health and indirectly causes harm to human health by food chain. Numerous studies have focused on removing Cd using lactic acid bacteria (LAB). However, there is still a lack of in vivo studies to validate whether Cd can be absorbed successfully by LAB to alleviate Cd toxicity. Here, we aimed to isolated and screened poultry-derived Cd-tolerant LAB with the strongest adsorption capacity in vitro and investigate the protective effect of which on sub-chronic Cd toxicity in chickens. First, nine Cd-tolerant LAB strains were selected preliminarily by isolating, screening, and identifying from poultry farms. Next, four strains with the strongest adsorption capacity were used to explore the influence of different physical and chemical factors on the ability of LAB to adsorb Cd as well as its probiotic properties in terms of acid tolerance, bile salt tolerance, drug resistance, and antibacterial effects. Resultantly, the CLF9-1 strain with the best comprehensive ability was selected for further animal protection test. The Cd-tolerant LAB treatment promoted the growth performance of chickens and reduced the Cd-elevated liver and kidney coefficients. Moreover, Cd-induced liver, kidney, and duodenum injuries were alleviated significantly by high-dose LAB treatment. Furthermore, LAB treatment also increased the elimination of Cd in feces and markedly reduced the Cd buildup in the liver and kidney. In summary, these findings determine that screened Cd-tolerant LAB strain exerts a protective effect on chickens against sub-chronic cadmium poisoning, thus providing an essential guideline for the public health and safety of livestock and poultry.

CRISPR-Cas9-mediated mutagenesis of the SlSRM1-like gene leads to abnormal leaf development in tomatoes.

BACKGROUND: Leaves, which are the most important organs of plants, can not only fix carbon sources through photosynthesis, but also absorb nutrients through transpiration. Leaf development directly determines the growth, flowering and fruiting of plants. There are many factors that affect leaf development, such as the growth environment, gene expression, and hormone synthesis. In this study, tomatoes were used to study the role of the transcription factor Solanum lycopersicum salt-related MYB1-like (SlSRM1-like) in the development of tomato leaves. RESULTS: Loss-of-function of the SlSRM1-like gene mediated by clustered, regularly interspaced, short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) resulted in abnormal tomato leaf morphology, including thinner leaves, wrinkled edges, raised veins, disordered edge veins, and left and right asymmetry. An analysis of the transcription levels of genes related to leaf development revealed that the expression of these genes was significantly altered in the SlSRM1-like mutants (SlSRM1-like-Ms). Moreover, the SlSRM1-like gene was expressed at higher transcription levels in young tissues than in old tissues, and its expression was also induced in response to auxin. In addition, the transcription levels of genes related to the auxin pathway, which regulates tomato growth and development, were severely affected in the SlSRM1-like-Ms. Therefore, it is hypothesized that the SlSRM1-like gene functions in the regulation of tomato leaf development through the auxin-related pathway. CONCLUSIONS: In this study, we successfully knocked out the SlSRM1-like gene in the tomato variety Ailsa Craig using CRISPR technology and found that knockout of the SlSRM1-like gene resulted in abnormal development of tomato leaves. Further research indicated that SlSRM1-like regulated tomato leaf development through auxin-related pathways. The results provide an important reference for the functional study of other SRM1-like genes in plants and provide new insights into the regulation of leaf development in tomato and other plants.

Difference and Cluster Analysis on the Carbon Dioxide Emissions in China During COVID-19 Lockdown via a Complex Network Model.

The continuous increase of carbon emissions is a serious challenge all over the world, and many countries are striving to solve this problem. Since 2020, a widespread lockdown in the country to prevent the spread of COVID-19 escalated, severely restricting the movement of people and unnecessary economic activities, which unexpectedly reduced carbon emissions. This paper aims to analyze the carbon emissions data of 30 provinces in the 2020 and provide references for reducing emissions with epidemic lockdown measures. Based on the method of time series visualization, we transform the time series data into complex networks to find out the hidden information in these data. We found that the lockdown would bring about a short-term decrease in carbon emissions, and most provinces have a short time point of impact, which is closely related to the level of economic development and industrial structure. The current results provide some insights into the evolution of carbon emissions under COVID-19 blockade measures and valuable insights into energy conservation and response to the energy crisis in the post-epidemic era.

Comparative transcriptome analysis reveals the response mechanism of Cf-16-mediated resistance to Cladosporium fulvum infection in tomato.

BACKGROUND: Leaf mold disease caused by Cladosporium fulvum is a serious threat affecting the global production of tomato. Cf genes are associated with leaf mold resistance, including Cf-16, which confers effective resistance to leaf mold in tomato. However, the molecular mechanism of the Cf-16-mediated resistance response is largely unknown. RESULTS: We performed a comparative transcriptome analysis of C. fulvum-resistant (cv. Ontario7816) and C. fulvum-susceptible (cv. Moneymaker) tomato cultivars to identify differentially expressed genes (DEGs) at 4 and 8 days post inoculation (dpi) with C. fulvum. In total, 1588 and 939 more DEGs were found in Cf-16 tomato than in Moneymaker at 4 and 8 dpi, respectively. Additionally, 1350 DEGs were shared between the 4- and 8-dpi Cf-16 groups, suggesting the existence of common core DEGs in response to C. fulvum infection. The up-regulated DEGs in Cf-16 tomato were primarily associated with defense processes and phytohormone signaling, including salicylic acid (SA) and jasmonic acid (JA). Moreover, SA and JA levels were significantly increased in Cf-16 tomato at the early stages of C. fulvum infection. Contrary to the previous study, the number of up-regulated genes in Cf-16 compared to Cf-10 and Cf-12 tomatoes was significantly higher at the early stages of C. fulvum infection. CONCLUSION: Our results provide new insight into the Cf-mediated mechanism of resistance to C. fulvum, especially the unique characteristics of Cf-16 tomato in response to this fungus.

Hierarchical structure in the world's largest high-speed rail network.

Presently, China has the largest high-speed rail (HSR) system in the world. However, our understanding of the network structure of the world's largest HSR system remains largely incomplete due to the limited data available. In this study, a publicly available data source, namely, information from a ticketing website, was used to collect an exhaustive dataset on the stations and routes within the Chinese HSR system. The dataset included all 704 HSR stations that had been built as of June, 2016. A classical set of frequently used metrics based on complex network theory were analyzed, including degree centrality, betweenness centrality, and closeness centrality. The frequency distributions of all three metrics demonstrated highly consistent bimodal-like patterns, suggesting that the Chinese HSR network consists of two distinct regimes. The results indicate that the Chinese HSR system has a hierarchical structure, rather than a scale-free structure as has been commonly observed. To the best of our knowledge, such a network structure has not been found in other railway systems, or in transportation systems in general. Follow-up studies are needed to reveal the formation mechanisms of this hierarchical network structure.

Dynamic Cluster Formation Game for Attributed Graph Clustering.

Besides the topological structure, there are additional information, i.e., node attributes, on top of the plain graphs. Usually, these systems can be well modeled by attributed graphs, where nodes represent component actors, a set of attributes describe users' portraits and edges indicate their connections. An elusive question associated with attributed graphs is to study how clusters with common internal properties form and evolve in real-world networked systems with great individual diversity, which leads to the so-called problem of attributed graph clustering (AGC). In this paper, we comprehended AGC naturally as a dynamic cluster formation game (DCFG), where each node's feasible action set can be constrained by every cluster in a discrete-time dynamical system. Specifically, we carried out a deep research on a special case of finite dynamic games, named dynamic social game (DSG), the convergence of the finite Nash equilibrium sequence in a DSG was also proved strictly. By carefully defining the feasible action set and the utility function associated with each node, the proposed DCFG can be well related to a DSG; and we showed that a balanced solution of AGC could be found by solving a finite set of coupled static Nash equilibrium problems in the related DCFG. We, finally, proposed a self-learning algorithm, which can start from any arbitrary initial cluster configuration, and, finally, find the corresponding balanced solution of AGC, where all nodes and clusters are satisfied with the final cluster configuration. Extensive experiments were applied on real-world social networks to demonstrate both effectiveness and scalability of the proposed approach by comparing with the state-of-the-art graph clustering methods in the literature.

Global vs local modularity for network community detection.

Community structures are ubiquitous in various complex networks, implying that the networks commonly be composed of groups of nodes with more internal links and less external links. As an important topic in network theory, community detection is of importance for understanding the structure and function of the networks. Optimizing statistical measures for community structures is one of most popular strategies for community detection in complex networks. In the paper, by using a type of self-loop rescaling strategy, we introduced a set of global modularity functions and a set of local modularity functions for community detection in networks, which are optimized by a kind of the self-consistent method. We carefully compared and analyzed the behaviors of the modularity-based methods in community detection, and confirmed the superiority of the local modularity for detecting community structures on large-size and heterogeneous networks. The local modularity can more quickly eliminate the first-type limit of modularity, and can eliminate or alleviate the second-type limit of modularity in networks, because of the use of the local information in networks. Moreover, we tested the methods in real networks. Finally, we expect the research can provide useful insight into the problem of community detection in complex networks.

Critical analysis of (Quasi-)Surprise for community detection in complex networks.

Module or community structures widely exist in complex networks, and optimizing statistical measures is one of the most popular approaches for revealing and identifying such structures in real-world applications. In this paper, we focus on critical behaviors of (Quasi-)Surprise, a type of statistical measure of interest for community structure, accompanied by a series of comparisons with other measures. Specially, the effect of various network parameters on the measures is thoroughly investigated. The critical number of dense subgraphs in partition transition is derived, and a kind of phase diagrams is provided to display and compare the phase transitions of the measures. The effect of "potential well" for (Quasi-)Surprise is revealed, which may be difficult to get across by general greedy (agglomerative or divisive) algorithms. Finally, an extension of Quasi-Surprise is introduced for the study of multi-scale structures. Experimental results are of help for understanding the critical behaviors of (Quasi-)Surprise, and may provide useful insight for the design of effective tools for community detection.

Punishment diminishes the benefits of network reciprocity in social dilemma experiments.

Network reciprocity has been widely advertised in theoretical studies as one of the basic cooperation-promoting mechanisms, but experimental evidence favoring this type of reciprocity was published only recently. When organized in an unchanging network of social contacts, human subjects cooperate provided the following strict condition is satisfied: The benefit of cooperation must outweigh the total cost of cooperating with all neighbors. In an attempt to relax this condition, we perform social dilemma experiments wherein network reciprocity is aided with another theoretically hypothesized cooperation-promoting mechanism-costly punishment. The results reveal how networks promote and stabilize cooperation. This stabilizing effect is stronger in a smaller-size neighborhood, as expected from theory and experiments. Contrary to expectations, punishment diminishes the benefits of network reciprocity by lowering assortment, payoff per round, and award for cooperative behavior. This diminishing effect is stronger in a larger-size neighborhood. An immediate implication is that the psychological effects of enduring punishment override the rational response anticipated in quantitative models of cooperation in networks.