Deep Canonical Correlation Fusion Algorithm Based on Denoising Autoencoder for ASD Diagnosis and Pathogenic Brain Region Identification

Autism Spectrum Disorder (ASD) is defined as a neurodevelopmental condition distinguished by unconventional neural activities. Early intervention is key to managing the progress of ASD, and current research primarily focuses on the use of structural magnetic resonance imaging (sMRI) or resting-state functional magnetic resonance imaging (rs-fMRI) for diagnosis. Moreover, the use of autoencoders for disease classification has not been sufficiently explored. In this study, we introduce a new framework based on autoencoder, the Deep Canonical Correlation Fusion algorithm based on Denoising Autoencoder (DCCF-DAE), which proves to be effective in handling high-dimensional data. This framework involves efficient feature extraction from different types of data with an advanced autoencoder, followed by the fusion of these features through the DCCF model. Then we utilize the fused features for disease classification. DCCF integrates functional and structural data to help accurately diagnose ASD and identify critical Regions of Interest (ROIs) in disease mechanisms. We compare the proposed framework with other methods by the Autism Brain Imaging Data Exchange (ABIDE) database and the results demonstrate its outstanding performance in ASD diagnosis. The superiority of DCCF-DAE highlights its potential as a crucial tool for early ASD diagnosis and monitoring.

Identification of superior and rare haplotypes to optimize branch number in soybean

KEY MESSAGE

Using the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean. Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.

Dual Function of the Third Component in Ternary Organic Solar Cells: Broaden the Spectrum and Optimize the Morphology

Ternary organic solar cells (T-OSCs) have attracted significant attention as high-performance devices. In recent years, T-OSCs have achieved remarkable progress with power conversion efficiency (PCE) exceeding 19%. However, the introduction of the third component complicates the intermolecular interaction compared to the binary blend, resulting in poor controllability of active layer and limiting performance improvement. To address these issues, dual-functional third components have been developed that not only broaden the spectral range but also optimize morphology. In this review, the effect of the third component on expanding the absorption range of T-OSCs is first discussed. Second, the extra functions of the third component are introduced, including adjusting the crystallinity and molecular stack in active layer, regulating phase separation and purity, altering molecular orientation of the donor or acceptor. Finally, a summary of the current research progress is provided, followed by a discussion of future research directions.

α-Synuclein reduces acetylserotonin O-methyltransferase mediated melatonin biosynthesis by microtubule-associated protein 1 light chain 3 beta-related degradation pathway

Previous studies have demonstrated that α-synuclein (α-SYN) is closely associated with rapid eye movement sleep behavior disorder (RBD) related to several neurodegenerative disorders. However, the exact molecular mechanisms are still rarely investigated. In the present study, we found that in the α-SYNA53T induced RBD-like behavior mouse model, the melatonin level in the plasma and pineal gland were significantly decreased. To elucidate the underlying mechanism of α-SYN-induced melatonin reduction, we investigated the effect of α-SYN in melatonin biosynthesis. Our findings showed that α-SYN reduced the level and activity of melatonin synthesis enzyme acetylserotonin O-methyltransferase (ASMT) in the pineal gland and in the cell cultures. In addition, we found that microtubule-associated protein 1 light chain 3 beta (LC3B) as an important autophagy adapter is involved in the degradation of ASMT. Immunoprecipitation assays revealed that α-SYN increases the binding between LC3B and ASMT, leading to ASMT degradation and a consequent reduction in melatonin biosynthesis. Collectively, our results demonstrate the molecular mechanisms of α-SYN in melatonin biosynthesis, indicating that melatonin is an important molecule involved in the α-SYN-associated RBD-like behaviors, which may provide a potential therapeutic target for RBD of Parkinson's disease.

Synergistic Role of Water and Oxygen Leads to Degradation in Formamidinium-Based Halide Perovskites

Mixed-cation metal halide perovskites have shown remarkable progress in photovoltaic applications with high power conversion efficiencies. However, to achieve large-scale deployment of this technology, efficiencies must be complemented by long-term durability. The latter is limited by external factors, such as exposure to humidity and air, which lead to the rapid degradation of the perovskite materials and devices. In this work, we study the mechanisms causing Cs and formamidinium (FA)-based halide perovskite phase transformations and stabilization during moisture and air exposure. We use in situ X-ray scattering, X-ray photoelectron spectroscopy, and first-principles calculations to study these chemical interactions and their effects on structure. We unravel a surface reaction pathway involving the dissolution of FAI by water and iodide oxidation by oxygen, driving the Cs/FA ratio into thermodynamically unstable regions, leading to undesirable phase transformations. This work demonstrates the interplay of bulk phase transformations with surface chemical reactions, providing a detailed understanding of the degradation mechanism and strategies for designing durable and efficient perovskite materials.

A limited overlap of interactions between the bacterial community of water and sediment in wetland ecosystem of the Yellow River floodplain

Introduction

Aquatic ecosystems in floodplains provide homes for a variety of active bacterial populations. However, the coexistence pattern of bacterial communities of water and sediment in these ecosystems is unclear.

Methods

In the present study, Illumina Mi-Seq sequencing were to assess bacteria's co-occurrence patterns in the water and sediment of different time dynamics and plant communities of the Yellow River floodplain ecosystem.

Results and discussion

The results showed that compared to water, the α-diversity of the bacterial community was way greater in sediment. The bacterial community structure significantly differed between water and sediment, and there was a limited overlap of interactions between the bacterial community of water and sediment. In addition, bacteria in water and sediment coexisting show different temporal shifts and community assembly patterns. The water was selected for specific groups of microorganisms that assemble over time in a non-reproducible and non-random way, whereas the sediment environment was relatively stable, and the bacterial communities were gathered randomly. The depth and plant cover significantly influenced the structure of a bacterial community in the sediment. The bacterial community in sediment formed a more robust network than those in water to cope with external changes. These findings improved our comprehension of the ecological trends of water and sediment bacterium colonies coexisting enhanced the biological barrier function, and the capacity of floodplain ecosystems to provide services and offered support for doing so.

China is implementing the national nutrition plan of action

With the transformation of Chinese economic and social structure, the social determinants of nutrition have undergone significant changes, which have a great influence on the dietary patterns and nutrition status of its population. The transition in the structure of nutrition intake in China can be characterized by a rapid trend in food accessibility, affordability, and diversity. However, challenges, such as the triple burden of malnutrition (undernourishment, micronutrient deficiencies, and obesity), still seriously threaten the population's health. To approach the targets for the “Healthy China 2030,” the General Office of the State Council of the People's Republic of China issued the National Nutrition Plan of Action (2017–2030), which specifies multi-sectoral transdisciplinary measures to improve population nutrition status. In our study, we recognized the role of the National Nutrition Plan of China in responding to the call for the Sustainable Development Goals (SDGs). Under the global- and country-level targets, this paper presented six primary intervention measures specified in the National Nutrition Plan of Action in China, highlighting the importance of collaborative actions for participants in all sectors.

The Potential Role of Vitamin D in the Development of Tuberculosis in Chinese Han Population: One Case-Control Study

Background and aims:

Spinal serum 25-hydroxyvitamin D [25[OH]D] status plays an important role in mediating innate immune responses by acting as a cofactor for induction of antimycobacterial activity and is thus involved in the development of Tuberculosis (TB). Results reported regarding the association of vitamin D with TB remained controversial. We aimed to identify any common association between 25[OH]D status and TB in the Chinese Han population.

Methods

280 subjects (70 TB patients and 210 matched controls) were recruited. TB cases were diagnosed based on the presence of acid-fast bacilli on smears from sputum and MTB isolation. Healthy controls were randomly selected from four local community-based populations. 25[OH]D was detected by electrochemiluminescence immunoassay (ECLIA) on Roche Elecsys before the initial treatment. Multivariable logistic regression analysis was used to examine the association of Vitamin D with TB.

Results

There was no significant difference in the serum vitamin D level between total cases and controls, but we found a strong tendency toward a higher serum vitamin D level in male population (P < 0.05) with TB but not in females. High serum vitamin D increased the risk of TB in the Chinese Han population (OR = 1.035, 95%CI: 1.001–1.070, P < 0.05). The serum vitamin D level was significantly decreased with age increasing in cases and controls (all P < 0.001).

Conclusions

High serum vitamin D may be an independent risk factor for TB in the Chinese Han population.

Three new pyrrole alkaloids from the endophytic fungus Albifimbria viridis

Three new pyrrole alkaloids albifipyrrols A-C (1-3), were isolated from the endophytic fungus Albifimbria viridis collected from the Chinese medicinal plant. Their structures were elucidated by extensive NMR and HRESIMS spectrometric analyses. All compounds were evaluated for immunosuppressive activity. Fortunately, compound 2 exhibits certain inhibition specifically against the LPS-induced proliferation of B lymphocyte cells with IC₅₀ value 16.16 μM.

iTRAQ Proteomic Analysis of Wheat (Triticum aestivum L.) Genotypes Differing in Waterlogging Tolerance

Transient and chronic waterlogging constrains crop production in many regions of the world. Here, we invoke a novel iTRAQ-based proteomic strategy to elicit protein synthesis and regulation responses to waterlogging in tolerant (XM 55) and sensitive genotypes (YM 158). Of the 7,710 proteins identified, 16 were distinct between the two genotypes under waterlogging, partially defining a proteomic basis for waterlogging tolerance (and sensitivity). We found that 11 proteins were up-regulated and 5 proteins were down-regulated; the former included an Fe-S cluster assembly factor, heat shock cognate 70, GTP-binding protein SAR1A-like and CBS domain-containing protein. Down-regulated proteins contained photosystem II reaction center protein H, carotenoid 9, 10 (9', 10')-cleavage dioxygenase-like, psbP-like protein 1 and mitochondrial ATPase inhibitor. We showed that nine proteins responded to waterlogging with non-cultivar specificity: these included 3-isopropylmalate dehydratase large subunit, solanesyl-diphosphate synthase 2, DEAD-box ATP-dependent RNA helicase 3, and 3 predicted or uncharacterized proteins. Sixteen of the 28 selected proteins showed consistent expression patterns between mRNA and protein levels. We conclude that waterlogging stress may redirect protein synthesis, reduce chlorophyll synthesis and enzyme abundance involved in photorespiration, thus influencing synthesis of other metabolic enzymes. Collectively, these factors accelerate the accumulation of harmful metabolites in leaves in waterlogging-susceptible genotypes. The differentially expressed proteins enumerated here could be used as biological markers for enhancing waterlogging tolerance as part of future crop breeding programs.

Antiviral RNA interference in disease vector (Asian longhorned) ticks

Disease vectors such as mosquitoes and ticks play a major role in the emergence and re-emergence of human and animal viral pathogens. Compared to mosquitoes, however, much less is known about the antiviral responses of ticks. Here we showed that Asian longhorned ticks (Haemaphysalis longicornis) produced predominantly 22-nucleotide virus-derived siRNAs (vsiRNAs) in response to severe fever with thrombocytopenia syndrome virus (SFTSV, an emerging tick-borne virus), Nodamura virus (NoV), or Sindbis virus (SINV) acquired by blood feeding. Notably, experimental acquisition of NoV and SINV by intrathoracic injection also initiated viral replication and triggered the production of vsiRNAs in H. longicornis. We demonstrated that a mutant NoV deficient in expressing its viral suppressor of RNAi (VSR) replicated to significantly lower levels than wildtype NoV in H. longicornis, but accumulated to higher levels after knockdown of the tick Dicer2-like protein identified by phylogeny comparison. Moreover, the expression of a panel of known animal VSRs in cis from the genome of SINV drastically enhanced the accumulation of the recombinant viruses. This study establishes a novel model for virus-vector-mouse experiments with longhorned ticks and provides the first in vivo evidence for an antiviral function of the RNAi response in ticks. Interestingly, comparing the accumulation levels of SINV recombinants expressing green fluorescent protein or SFTSV proteins identified the viral non-structural protein as a putative VSR. Elucidating the function of ticks’ antiviral RNAi pathway in vivo is critical to understand the virus-host interaction and the control of tick-borne viral pathogens.

Tick-borne diseases (TBDs) are the most common illnesses transmitted by ticks, and the annual number of reported TBD cases continues to increase. The Asian longhorned tick, a vector associated with at least 30 human pathogens, is native to eastern Asia and recently reached the USA as an emerging disease threat. Newly identified tick-transmitted pathogens continue to be reported, raising concerns about how TBDs occur. Interestingly, tick can harbor pathogens without being affected themselves. For viral infections, ticks have their own immune systems that protect them from infection. Meanwhile, tick-borne viruses have evolved to avoid these defenses as they establish themselves within the vector. Here, we show in detail that infecting longhorned ticks with distinct arthropod-borne RNA viruses through two approaches natural blood feeding and injection, all induce the production of vsiRNAs. Dicer2-like homolog plays a role in regulating antiviral RNAi responses as knocking down of this gene enhanced viral replication. Furthermore, we demonstrate that tick antiviral RNAi responses are inhibited through expression heterologous VSR proteins in recombinant SINV. We identify both the virus and tick factors are critical components to understanding TBDs. Importantly, our study introduces a novel, in vivo virus-vector-mouse model system for exploring TBDs in the future.

TLGP: a flexible transfer learning algorithm for gene prioritization based on heterogeneous source domain

BACKGROUND

Gene prioritization (gene ranking) aims to obtain the centrality of genes, which is critical for cancer diagnosis and therapy since keys genes correspond to the biomarkers or targets of drugs. Great efforts have been devoted to the gene ranking problem by exploring the similarity between candidate and known disease-causing genes. However, when the number of disease-causing genes is limited, they are not applicable largely due to the low accuracy. Actually, the number of disease-causing genes for cancers, particularly for these rare cancers, are really limited. Therefore, there is a critical needed to design effective and efficient algorithms for gene ranking with limited prior disease-causing genes.

RESULTS

In this study, we propose a transfer learning based algorithm for gene prioritization (called TLGP) in the cancer (target domain) without disease-causing genes by transferring knowledge from other cancers (source domain). The underlying assumption is that knowledge shared by similar cancers improves the accuracy of gene prioritization. Specifically, TLGP first quantifies the similarity between the target and source domain by calculating the affinity matrix for genes. Then, TLGP automatically learns a fusion network for the target cancer by fusing affinity matrix, pathogenic genes and genomic data of source cancers. Finally, genes in the target cancer are prioritized. The experimental results indicate that the learnt fusion network is more reliable than gene co-expression network, implying that transferring knowledge from other cancers improves the accuracy of network construction. Moreover, TLGP outperforms state-of-the-art approaches in terms of accuracy, improving at least 5%.

CONCLUSION

The proposed model and method provide an effective and efficient strategy for gene ranking by integrating genomic data from various cancers.

Fine mapping epitope on Glycoprotein-Gn from Severe Fever with Thrombocytopenia Syndrome Virus

Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) was recently identified as a tick-borne pathogen that threat to human health. Since 2010, many countries including China, South Korea, and Japan have reported Human SFTS caused by SFTSV infection. The glycoprotein encoded by the SFTSV M gene is the major antigenic component on the viral surface, and responsible for the viral entry, which makes it an important viral antigen and a clinical diagnostic target. The present study aimed to map linear B cell epitopes (BCEs) on the N-terminal glycoprotein (Gn) from SFTSV strain WCH/97/HN/China/2011 using the modified biosynthetic peptide method. Five fine epitopes (E1, 196FSQSEFPD203; E2, 232GHSHKII238; E3, 256VCYKEGTGPC265; E4, 285FCKVAG290, and E5, 316SYGGM320) were identified using the rabbit antisera. Western blot analysis showed that all the five epitopes interacted with the positive serum of sheep that had been naturally infected with SFTSV. Three-dimensional structural modeling analysis showed that all identified BCEs were located on the surface of the SFTSV-Gn and contained flexible loops. The sequence alignment revealed high conservation of the identified BCEs among 13 SFTSV strains from different lineage. These mapped epitopes will escalate the understanding of the epitope distribution and pathogenic mechanism of SFTSV, and could provide a basis for the development of a SFTSV multi-epitope detection antigen.

Facile Synthesis of Water-Soluble Fullerene (C60) Nanoparticles via Mussel-Inspired Chemistry as Efficient Antioxidants

Rational design and modification of the all-carbon fullerene cages to meliorate their nature of hydrophobicity is critical for biomedical applications. The outstanding electron affinity of fullerenes enables them to effectively eliminate reactive oxygen species (ROS), the excess of which may lead to health hazards or biological dysfunction. Herein reported is a facile, mild, and green approach to synthesizing the favorable water-soluble C60 nanoparticles capable of ROS-scavenging by combining the mussel-inspired chemistry with the Michael addition reaction. Various characterization techniques, including Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectra (XPS), thermogravimetric analysis (TGA), transmission electron cryomicroscopy (Cryo-TEM), and dynamic laser scattering (DLS) were carried out to confirm the satisfactory preparation of the hybrid C60-PDA-GSH nanoparticles, which exhibited apparent scavenging capacity of DPPH and hydroxyl radicals in vitro. Additionally, the biocompatible C60-PDA-GSH nanoparticles entered into cells and displayed a universal cytoprotective effect against oxidative press induced by H2O2 in four kinds of human cells at a low concentration of 2 μg/mL. The ease and versatility of the strategy present in this work will not only trigger more fullerene-based materials by the immobilization of diverse functional molecules, but will also extend their possible applications.

Optimization of robustness of interdependent network controllability by redundant design

Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks. Then, the structural controllability of interdependent networks is measured by the minimum driver nodes. Furthermore, we propose a parameter which can be obtained by the structure and minimum driver set of interdependent networks under different proportions of node attacks and analyze the robustness for interdependent network controllability. Finally, we optimize the robustness of interdependent network controllability by redundant design including node backup and redundancy edge backup and improve the redundant design by proposing different strategies according to their cost. Comparative strategies of redundant design are conducted to find the best strategy. Results shows that node backup and redundancy edge backup can indeed decrease those nodes suffering from failure and improve the robustness of controllability. Considering the cost of redundant design, we should choose BBS (betweenness-based strategy) or DBS (degree based strategy) for node backup and HDF(high degree first) for redundancy edge backup. Above all, our proposed strategies are feasible and effective at improving the robustness of interdependent network controllability.

Low probability of intercept-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems

In this paper, we investigate the problem of low probability of intercept (LPI)-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems, where the radar system optimizes the transmitted waveform such that the interference caused to the cellular communication systems is strictly controlled. Assuming that the precise knowledge of the target spectra, the power spectral densities (PSDs) of signal-dependent clutters, the propagation losses of corresponding channels and the communication signals is known by the radar, three different LPI based criteria for radar waveform optimization are proposed to minimize the total transmitted power of the radar system by optimizing the multicarrier radar waveform with a predefined signal-to-interference-plus-noise ratio (SINR) constraint and a minimum required capacity for the cellular communication systems. These criteria differ in the way the communication signals scattered off the target are considered in the radar waveform design: (1) as useful energy, (2) as interference or (3) ignored altogether. The resulting problems are solved analytically and their solutions represent the optimum power allocation for each subcarrier in the multicarrier radar waveform. We show with numerical results that the LPI performance of the radar system can be significantly improved by exploiting the scattered echoes off the target due to cellular communication signals received at the radar receiver.