Potential Function Research Articles

DOP87 Characterization of pathologic fibroblast and macrophage cell populations in colonic Crohn’s Disease with spatial transcriptomics

Abstract Background Single-cell transcriptomic data of the human intestine has shed new light on the cellular composition and heterogeneity present in healthy and diseased tissues. Nonetheless, little information is currently available on their spatial distribution within tissue structures and cellular neighborhoods, which is particularly relevant to infer the function of disease-specific cell types. Here, we apply spatial transcriptomics to healthy control (HC) and Crohn’s disease (CD) intestinal samples and provide a map of cell types across healthy and diseased colon. Methods Fresh frozen colonic sections from HC (n=1) and CD (n=3) patients were placed onto 10X Visium slides, which feature thousands of spatially barcoded spots, each capable of capturing RNA from 10-15 cells. To retrieve single-cell resolution, spots were deconvoluted according to the Cell2location approach using our previously generated human single cell RNA sequencing (scRNAseq) dataset1 as a reference. For validation and further analysis at single-cell resolution, a panel of 100 genes was measured using single molecule fluorescent in situ hybridization (Molecular Cartography) (Fig. 1A). Results Deconvolution analysis revealed the cellular composition of each spot across all four different tissue sections including epithelial, stromal and immune cell types. Here, we focused on studying the location and diversity of fibroblasts and macrophages given their plasticity during inflammation1,2. The most abundant fibroblast cell type in CD were the inflammation-associate (IAFs) and the GREM1+ subepithelial fibroblasts. These two subsets showed a distinct gene signature and location, suggesting different functions (Fig. 1B). Most GREM1+ fibroblasts co-expressed FGFR1 and were in proximity with endothelial cells (VWF+) expressing the VEGF receptor 2 KDR, highlighting a potential pro-angiogenic role of GREM1+ fibroblasts3 (Fig. 1C). Remarkably, GREM1 was abundantly expressed by CCL19+ fibroblastic reticular cells and TNC+ stromal cells, underlying the potential heterogeneity of GREM1+ fibroblasts. Regarding macrophages, we could identify an inflammation-specific population expressing PLA2G2D and PTGDS. These macrophages were mainly localized within granulomas surrounding M1 macrophages (Fig. 1D). While their function is unknown, their signature suggests they might be modulating inflammation through the production of anti-inflammatory lipid mediators4. Conclusion Using two different ST technologies, we resolved the tissue distribution of cell populations previously identified by scRNAseq and reveal their potential function based on their spatial location.

The Pathological Factors Involved in Current In Vitro Atherosclerotic Models.

Cardiovascular disease stemmed from atherosclerosis (AS) is well recognized to be the predominant cause of global death. To comprehensively clarify the pathogenesis of AS, exploit effective drugs, as well as develop therapeutic solutions, various atherosclerotic models were constructed in vitro and widely utilized by the scientific community. Compared with animal models, the in vitro atherosclerotic models play a prominent role not only in the targeted research of single pathological factor related to AS in the human derived system, but also in the combined study on multipathological factors leading to AS, thereby contributing tremendously to the in-depth elucidation of atherosclerotic pathological process. In the current review, a variety of pathological factors incorporated into the existing atherosclerotic models in vitro are broadly elaborated, including the pathological mechanism, in vitro simulation approaches, and the desired improvement perspectives for reproducing each pathological factor. In addition, this review also summarizes the advantages and disadvantages of current atherosclerotic models as well as their potential functionality. Finally, the promising aspects for future atherosclerotic models in vitro with potential advances are also discussed.

Integrating Machine Learning and Mendelian Randomization Determined a Functional Neurotrophin-Related Gene Signature in Patients with Lower-Grade Glioma.

Recent researches reported that neurotrophins can promote glioma growth/invasion but the relevant model for predicting patients' survival in Lower-Grade Gliomas (LGGs) lacked. In this study, we adopted univariate Cox analysis, LASSO regression, and multivariate Cox analysis to determine a signature including five neurotrophin-related genes (NTGs), CLIC1, SULF2, TGIF1, TTF2, and WEE1. Two-sample Mendelian Randomization (MR) further explored whether these prognostic-related genes were genetic variants that increase the risk of glioma. A total of 1306 patients have been included in this study, and the results obtained from the training set can be verified by four independent validation sets. The low-risk subgroup had longer overall survival in five datasets, and its AUC values all reached above 0.7. The risk groups divided by the NTGs signature exhibited a distinct difference in targeted therapies from the copy-number variation, somatic mutation, LGG's surrounding microenvironment, and drug response. MR corroborated that TGIF1 was a potential causal target for increasing the risk of glioma. Our study identified a five-NTGs signature that presented an excellent survival prediction and potential biological function, providing new insight for the selection of LGGs therapy.

Small Cajal Body-Specific RNA12 Promotes Carcinogenesis through Modulating Extracellular Matrix Signaling in Bladder Cancer

Background: Small Cajal body-specific RNAs (scaRNAs) are a specific subset of small nucleolar RNAs (snoRNAs) that have recently emerged as pivotal contributors in diverse physiological and pathological processes. However, their defined roles in carcinogenesis remain largely elusive. This study aims to explore the potential function and mechanism of SCARNA12 in bladder cancer (BLCA) and to provide a theoretical basis for further investigations into the biological functionalities of scaRNAs. Materials and Methods: TCGA, GEO and GTEx data sets were used to analyze the expression of SCARNA12 and its clinicopathological significance in BLCA. Quantitative real-time PCR (qPCR) and in situ hybridization were applied to validate the expression of SCARNA12 in both BLCA cell lines and tissues. RNA sequencing (RNA-seq) combined with bioinformatics analyses were conducted to reveal the changes in gene expression patterns and functional pathways in BLCA patients with different expressions of SCARNA12 and T24 cell lines upon SCARNA12 knockdown. Single-cell mass cytometry (CyTOF) was then used to evaluate the tumor-related cell cluster affected by SCARNA12. Moreover, SCARNA12 was stably knocked down in T24 and UMUC3 cell lines by lentivirus-mediated CRISPR/Cas9 approach. The biological effects of SCARNA12 on the proliferation, clonogenic, migration, invasion, cell apoptosis, cell cycle, and tumor growth were assessed by in vitro MTT, colony formation, wound healing, transwell, flow cytometry assays, and in vivo nude mice xenograft models, respectively. Finally, a chromatin isolation by RNA purification (ChIRP) experiment was further conducted to delineate the potential mechanisms of SCARNA12 in BLCA. Results: The expression of SCARNA12 was significantly up-regulated in both BLCA tissues and cell lines. RNA-seq data elucidated that SCARAN12 may play a potential role in cell adhesion and extracellular matrix (ECM) related signaling pathways. CyTOF results further showed that an ECM-related cell cluster with vimentin+, CD13+, CD44+, and CD47+ was enriched in BLCA patients with high SCARNA12 expression. Additionally, SCARNA12 knockdown significantly inhibited the proliferation, colony formation, migration, and invasion abilities in T24 and UMUC3 cell lines. SCARNA12 knockdown prompted cell arrest in the G0/G1 and G2/M phase and promoted apoptosis in T24 and UMUC3 cell lines. Furthermore, SCARNA12 knockdown could suppress the in vivo tumor growth in nude mice. A ChIRP experiment further suggested that SCARNA12 may combine transcription factors H2AFZ to modulate the transcription program and then affect BLCA progression. Conclusions: Our study is the first to propose aberrant alteration of SCARNA12 and elucidate its potential oncogenic roles in BLCA via the modulation of ECM signaling. The interaction of SCARNA12 with the transcriptional factor H2AFZ emerges as a key contributor to the carcinogenesis and progression of BLCA. These findings suggest SCARNA12 may serve as a diagnostic biomarker and potential therapeutic target for the treatment of BLCA.

Natural gradient ascent in evolutionary games

We consider evolutionary games with a continuous trait space where the replicator dynamics are restricted to the manifold of multivariate Gaussian distributions. We demonstrate that replicator dynamics are gradient flows with respect to the Fisher information metric. The potential function for these gradient flows is closely related to the mean fitness. Our findings extend previous results on natural gradient ascent in evolutionary games with a finite strategy set. Throughout the paper we pursue an information-geometric point of view on evolutionary games. This sheds a new light on the replicator dynamics as a learning process, realizing the compromise between maximization of the mean fitness and preservation of the diversity.

Transcriptome analysis of effects of Tecrl deficiency on cardiometabolic and calcium regulation in cardiac tissue.

Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a hereditary heart disease characterized by bidirectional or polymorphic ventricular tachycardia and an increased risk of sudden cardiac death. Although trans-2,3-enoyl-CoA reductase like (TECRL) is a newly reported pathogenic gene leading to CPVT that can influence intracellular calcium regulation, the unidentified mechanism underlying the pathogenesis of TECRL deficiency-mediated CPVT remains mainly elusive. In the present study, Tecrl knockout (KO) mice were established and the differentially expressed genes (DEGs) were investigated by RNA-sequencing from the heart tissues. In addition, 857 DEGs were identified in Tecrl KO mice. Subsequently, a weighted gene co-expression network analysis was conducted to discern the pivotal pathways implicated in the Tecrl-mediated regulatory network. Moreover, pathway mapping analyses demonstrated that essential metabolism-related pathways were significantly enriched, notably the fatty acid metabolic process and calcium regulation. Collectively, the data suggested a synergistic relationship between Tecrl deficiency and cardiometabolic and calcium regulation during the development of CPVT. Therefore, further studies on the potential function of TECRL in cardiac tissues would be beneficial to elucidate the pathogenesis of CPVT.

Unveiling the principles of stochastic resonance and complex potential functions for bearing fault diagnosis

This paper introduces a novel and complex Unsaturated Piecewise Linear Quad-Stable Stochastic Resonance System (UPLQSR) to address the issue of output saturation in the Classical Quad-Stable Stochastic Resonance (CQSR) system. By linearizing the structure of the potential function, the constraints imposed by high-order terms are effectively eliminated, allowing Brownian particles to move more freely. Numerical simulations demonstrate that UPLQSR achieves significantly higher output signal amplitudes compared to CQSR, highlighting its remarkable signal amplification capability. By analyzing the structure of the potential function, the relationship between the height of the potential barrier and the aggressiveness of the particles jumping is determined. Utilizing adiabatic approximation theory, the paper derives the Steady-state Probability Density (SPD), Mean First Passage Time (MFPT), and Spectral Amplification (SA), revealing the specific process of the particle jumping, as well as the influence of the parameters on the performance of the UPLQSR. After optimizing parameters using the Adaptive Genetic Algorithm (GA), UPLQSR is applied to the early fault diagnosis of various bearing models under Gaussian white noise, demonstrating superior fault detection capabilities. In summary, this study pioneered the theory of non-saturation of quad-stable systems, optimized the weak signal detection technique, and provided a more accurate means of signal identification and analysis, highlighting its great value of application in engineering.

The effects of silver particle size on bacterioplankton community and potential function in aquatic environment

Silver nanoparticles (AgNPs), known for their antimicrobial properties, are increasingly being recognized as a water pollutant, with their physicochemical properties varying based on particle size. However, there is a lack of research on whether presence of AgNPs and their particle size affect bacterial communities in water bodies. In this study, the water from Chaohu Lake was collected and spiked with AgNPS of different particle sizes of (5 nm, 50 nm, and 100 nm) to stimulate the microbial response. Our findings revealed that the presence of AgNPs could significantly disrupt bacterial community structure and strengthen the associations between certain bacteria, with significant impacts observed on nitrifying and denitrifying processes. Different particle sizes of AgNPs had various effects on bacterial community structure, with small-sized AgNPs affecting the bacterial community the most. Moreover, the presence of AgNPs and their varying particle sizes were observed to significantly affect the nitrogen cycle, carbon cycle, and respiration, thus imposing significant impacts on other ecological functions of aquatic ecosystems. This study provides a baseline study on the aquatic ecotoxicological effects of AgNPs.

VDTriplet: Vulnerability detection with graph semantics using triplet model

This study presents VDTriplet, a novel learning framework for building vulnerability detection models. VDTriplet is the first attempt using deep learning to avoid the potential known vulnerability function misjudgment due to the small difference between vulnerability and its fixed vulnerability function. Unlike prior work that treats the program as sequential tokens or randomly initialized graphs for supervised binary classification detection tasks, our model not only fuses rich syntactic and semantic information to obtain the most accurate program representation, but also utilizes the TripletNN model to reduce misjudgment of potential known vulnerabilities. VDTriplet first extracts the subgraphs that causes the vulnerability through the typical programming errors to reduce redundant code. Then, it uses the pre-trained model and unsupervised model for the graph encoding of subgraphs, thereby minimizing the influence of randomly initialized graph nodes and avoiding the need for supervised labeling. Finally, TripletNN model minimizes the distance between potential vulnerabilities and vulnerabilities with the same vulnerability type, and maximizes the distance between potential vulnerabilities and fixed vulnerabilities to reduce false positives. The results show that the performance of VDTriplet is significantly better than the studied baselines. Compared with the best performing model in the literature, our model achieves a total of 4.89%, 4.23%, 4.56% and 5.34% improvement in Accuracy, Precision, Recall and F1-Score in the test results respectively. Moreover, it exhibits well generalization in detecting new eight applications, demonstrating that it is potentially valuable in practical usage. Overall, this is indeed an outstanding improvement.

Prognostic and predictive value of super-enhancer-derived signatures for survival and lung metastasis in osteosarcoma

BackgroundRisk stratification and personalized care are crucial in managing osteosarcoma due to its complexity and heterogeneity. However, current prognostic prediction using clinical variables has limited accuracy. Thus, this study aimed to explore potential molecular biomarkers to improve prognostic assessment.MethodsHigh-throughput inhibitor screening of 150 compounds with broad targeting properties was performed and indicated a direction towards super-enhancers (SEs). Bulk RNA-seq, scRNA-seq, and immunohistochemistry (IHC) were used to investigate SE-associated gene expression profiles in osteosarcoma cells and patient tissue specimens. Data of 212 osteosarcoma patients who received standard treatment were collected and randomized into training and validation groups for retrospective analysis. Prognostic signatures and nomograms for overall survival (OS) and lung metastasis-free survival (LMFS) were developed using Cox regression analyses. The discriminatory power, calibration, and clinical value of nomograms were evaluated.ResultsHigh-throughput inhibitor screening showed that SEs significantly contribute to the oncogenic transcriptional output in osteosarcoma. Based on this finding, focus was given to 10 SE-associated genes with distinct characteristics and potential oncogenic function. With multi-omics approaches, the hyperexpression of these genes was observed in tumor cell subclusters of patient specimens, which were consistently correlated with poor outcomes and rapid metastasis, and the majority of these identified SE-associated genes were confirmed as independent risk factors for poor outcomes. Two molecular signatures were then developed to predict survival and occurrence of lung metastasis: the SE-derived OS-signature (comprising LACTB, CEP55, SRSF3, TCF7L2, and FOXP1) and the SE-derived LMFS-signature (comprising SRSF3, TCF7L2, FOXP1, and APOLD1). Both signatures significantly improved prognostic accuracy beyond conventional clinical factors.ConclusionsOncogenic transcription driven by SEs exhibit strong associations with osteosarcoma outcomes. The SE-derived signatures developed in this study hold promise as prognostic biomarkers for predicting OS and LMFS in patients undergoing standard treatments. Integrative prognostic models that combine conventional clinical factors with these SE-derived signatures demonstrate substantially improved accuracy, and have the potential to facilitate patient counseling and individualized management.

Chitosan surface-modified bovine serum albumin-oleic acid self-assembled complexes: Improving the thermal stability, controlled release and bioaccessibility of fucoxanthin

Fucoxanthin (FUCO) is a marine xanthophyll carotenoid with widespread potential physiological functions. However, poor water solubility and chemical instability limit FUCO's processing adaptability and bioavailability. In this study, chitosan surface-modified bovine serum albumin (BSA)-oleic acid (OA) self-assembled complexes were fabricated to improve the thermal stability as well as the controlled release and bioaccessibility of FUCO during gastrointestinal digestion. The results showed that glucose-grafted chitosan (GGC) could surface modify BSA-OA complexes by non-covalent affinity adhesion, resulting in a stable hydrophilic dispersion system with a polydispersity index <0.25 and a Zeta potential > −20 mV. Fourier transform infrared spectroscopy and transmission electron microscope observations revealed that GGC covered the surface of BSA-OA particles through hydrogen bonding, hydrophobic and electrostatic interactions. The GGC-BSA-OA delivery system captured FUCO with >88.00% encapsulation efficiency. Additionally, embedding FUCO in the GGC-modified BSA-OA complex improved its thermal stability. In vitro, gastrointestinal digestion simulations showed that the GGC-modified protein shell had a controlled-release effect on FUCO, which prevented acidic pH from destroying FUCO due to premature release during gastric digestion and released it during intestinal digestion. As expected, GGC-BSA-OA, an encapsulated carrier, dramatically improved the FUCO's digestive stability (retention rate >74.00%), bioaccessibility (>54.42%), and micellization rate (>70.00%) in simulated gastrointestinal digestion. These findings suggested that GGC-BSA-OA as a delivery vehicle could effectively improve FUCO's thermal processing stability and absorbability.

Graphullerene: A Fully Atomistic Analysis of the Tensile Characteristics Under Temperature Variation

Based on the molecular dynamics simulations, mechanical properties of the most recently synthesized covalent fullerene network, i.e., graphullerene sheet, under uniaxial tension, are determined. These properties include Young's modulus, ultimate stress, failure strain, tensile toughness, and Poisson's ratio. Due to the lack of existing data on mechanical properties of graphullerene, a comprehensive study is performed to get an insight into the effects of defect density, size, and temperature on all tensile characteristics. In the results, it is indicated that the tensile behavior of graphullerene structure is comparable with graphene allotropes. Moreover, it is observed that the presence of defect reduces stiffness, ultimate stress, and tensile toughness, while it has a negligible effect on the failure strain. It is further observed that unlike stiffness, increasing the temperature reduces other tensile characteristics. Interestingly, it is found that graphullerene exhibits auxetic behavior with negative Poisson's ratio which categorizes it as a unique auxetic material ever synthesized. At the end, three types of potential functions for hydrocarbons including adaptive intermolecular reactive empirical bond order, reactive empirical bond order, and Tersoff are considered to study the tensile behavior of graphullerene. This new auxetic nanosheet is a promising analogous to the existing 2D nanostructures with fascinating potential applications.

Roles of electrostatics and intermolecular electronic motions in the structural and spectroscopic features of hydrogen- and halogen-bonded systems

Abstract It is widely recognized that electrostatics plays a central role in the intermolecular interactions in condensed phases, as evidenced by the “electrostatics + Lennard-Jones” form of the potential functions that are commonly used in classical molecular dynamics simulations. Then, do we understand all about electrostatics in condensed phases? In this review, recent theoretical advances in relation to this topic will be discussed: (1) vibrational spectroscopic probing of the electrostatics in condensed phases, and (2) some phenomena affected by deviation from the scheme of isotropic fixed atomic partial charges, i.e., anisotropy and intermolecular transfer of electron distributions. A theoretical basis for better understanding on them and some theoretical models for practical calculations will be shown with some typical example cases of hydrogen- and halogen-bonded systems.

Effects of Early Mobilisation on Post Operative Pulmonary Complication in Patients with Open Abdominal Surgery

Background: Patients undergoing open abdominal surgery are the focus of this research, namely the effect of earlymobilisation on postoperative pulmonary problems. Early mobilization is proposed as a potential intervention toenhance respiratory function and reduce the risk of PPCs.Purpose: The purpose of this study is to evaluate the impact of pre-operative mobilisation on the incidence ofpulmonary complications in patients undergoing open abdominal surgery.Materials and Methods: This quasi-experimental study included 50 subjects who underwent open abdominalsurgery at Saveetha Medical Hospital, SIMTS. Convenient sampling was used to select the participants. Measuresof oxygen saturation (SPO2) and pulmonary function (FEV1) from a spirometer were employed as functionaloutcome indicators. After two weeks, participants were given a post-test to record their progress.Results: Data collected before and after early mobilisation exercise were analysed using a paired t-test. Theexperimental group showed significant improvements in SPO2, FIM, and FEV1 (P&lt;0.0001), indicating highervalues post-intervention. Post-test demonstrated higher statistical significance compared to pre-test.Conclusion: As a result, it was shown that early mobilisation Exercise is beneficial for reducing pulmonarycomplications after surgery.

The identification and functional characterization of the LcMCT gene from Liriodendron chinense reveals its potenatial role in carotenoids biosyanthesis

Terpenoids are not only important component of plant floral scent, but also indispensable elements in the formation of floral color. The petals of Liriodendron chinense are rich in tetraterpene carotenoids and release large amounts of volatile monoterpene and sesquiterpene compounds during full blooming stage. However, the mechanism of terpenoid synthesis is not clear in L. chinense. In this study, we identified a LcMCT gene and characterized its potential function in carotenoids biosynthesis. A total of 2947 up-regulated differentially expressed genes (DEGs) were discerned from the transcriptomic data of L. chinense petals, with a significant enrichment of DEGs related to plant hormone signal transduction and terpenoid backbone biosynthesis. After comprehensive analysis on these DEGs, the LcMCT gene was selected for subsequent function characterization. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) results showed that LcMCT was expressed at the highest level in the petals during full blooming stage, suggesting a possible role in carotenoids biosynthesis and volatile terpenoid biosynthesis. Subcellular localization showed that the LcMCT protein was localized in the chloroplast. Overexpression of LcMCT in Arabidopsis thaliana affected the expression levels of MEP pathway genes. Moreover, the MCT enzyme activity and carotenoids contents in transgenic A. thaliana were increased by 69.27% and 15.57%, respectively. These results suggest that LcMCT promotes the biosynthesis of terpenoid precursors via the MEP pathway. Our work lays a foundation for exploring the mechanism of terpenoid synthesis in L. chinense.

Genome-wide analysis and expression pattern of the ZoPP2C gene family in Zingiber officinale Roscoe

BackgroundProtein phosphatases type 2C (PP2C) are heavily involved in plant growth and development, hormone-related signaling pathways and the response of various biotic and abiotic stresses. However, a comprehensive report identifying the genome-scale of PP2C gene family in ginger is yet to be published.ResultsIn this study, 97 ZoPP2C genes were identified based on the ginger genome. These genes were classified into 15 branches (A-O) according to the phylogenetic analysis and distributed unevenly on 11 ginger chromosomes. The proteins mainly functioned in the nucleus. Similar motif patterns and exon/intron arrangement structures were identified in the same subfamily of ZoPP2Cs. Collinearity analysis indicated that ZoPP2Cs had 33 pairs of fragment duplicated events uniformly distributed on the corresponding chromosomes. Furthermore, ZoPP2Cs showed greater evolutionary proximity to banana’s PP2Cs. The forecast of cis-regulatory elements and transcription factor binding sites demonstrated that ZoPP2Cs participate in ginger growth, development, and responses to hormones and stresses. ZoERFs have plenty of binding sites of ZoPP2Cs, suggesting a potential synergistic contribution between ZoERFs and ZoPP2Cs towards regulating growth/development and adverse conditions. The protein–protein interaction network displayed that five ZoPP2Cs (9/23/26/49/92) proteins have robust interaction relationship and potential function as hub proteins. Furthermore, the RNA-Seq and qRT-PCR analyses have shown that ZoPP2Cs exhibit various expression patterns during ginger maturation and responses to environmental stresses such as chilling, drought, flooding, salt, and Fusarium solani. Notably, exogenous application of melatonin led to notable up-regulation of ZoPP2Cs (17/59/11/72/43) under chilling stress.ConclusionsTaken together, our investigation provides significant insights of the ginger PP2C gene family and establishes the groundwork for its functional validation and genetic engineering applications.

Identification of genomic diversity and selection signatures in Luxi cattle using whole-genome sequencing data.

The objective of this study was to investigate the genetic diversity, population structure and whole-genome selection signatures of Luxi cattle to reveal its genomic characteristics in terms of meat and carcass traits, skeletal muscle development, body size, and other traits. To further analyze the genomic characteristics of Luxi cattle, this study sequenced the whole-genome of 16 individuals from the core conservation farm in Shandong region, and collected 174 published genomes of cattle for conjoint analysis. Furthermore, three different statistics (pi, Fst, and XP-EHH) were used to detect potential positive selection signatures related to selection in Luxi cattle. Moreover, gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were performed to reveal the potential biological function of candidate genes harbored in selected regions. The results showed that Luxi cattle had high genomic diversity and low inbreeding levels. Using three complementary methods (pi, Fst, and XP-EHH) to detect the signatures of selection in the Luxi cattle genome, there were 2,941, 2,221 and 1,304 potentially selected genes identified, respectively. Furthermore, there were 45 genes annotated in common overlapping genomic regions covered 0.723 Mb, including PLAG1 zinc finger (PLAG1), dedicator of cytokinesis 3 (DOCK3), ephrin A2 (EFNA2), DAZ associated protein 1 (DAZAP1), Ral GTPase activating protein catalytic subunit alpha 1 (RALGAPA1), mediator complex subunit 13 (MED13), and decaprenyl diphosphate synthase subunit 2 (PDSS2), most of which were enriched in pathways related to muscle growth and differentiation and immunity. In this study, we provided a series of genes associated with important economic traits were found in positive selection regions, and a scientific basis for the scientific conservation and genetic improvement of Luxi cattle.

Feasibility of molecular dynamics simulation for process parameter guidance of silicon nitride thin films by PECVD

Due to the limitations of the characterization approaches and the relative complex and expensive characteristics of CVD method itself, experimental-based studies are limited, and simulation of SiNx deposition based on molecular dynamics (MD) simulation provides a more convenient and clear solution. In this work, Tersoff potential function containing the interatomic potential for two-body and three-body interactions was utilized to simulate of the deposition process for SiNx thin films by the PECVD. A quick and accurate method basing on Alpha-shapes was proposed to extract surface atoms and the surface roughness of the thin film samples at substrate temperatures of 353, 493, and 653 K were found to be 0.804, 0.794, and 0.721 nm respectively. By analyzing the radial distribution function, it can get that there are small changes in the Si-Si and Si-N bonds at three temperatures. We also found the diffusion phenomenon at the interface, and the atomic diffusion phenomenon at the substrate interface makes the phenomenon of elemental mutation at the interface less rapid. The simulation results confirm that the substrate temperature during deposition has an effect on the adsorption and atomic drift rate of the substrate, which in turn affects the surface morphology of the film.

Downregulation of Ambra1 by altered DNA methylation exacerbates dopaminergic neuron damage in a fenpropathrin-induced Parkinson-like mouse model

Fenpropathrin (Fen), a volatile pyrethroid insecticide, is used widely for agricultural applications and has been reported to increase the risk of Parkinson’s disease (PD). However, the molecular basis, underlying mechanisms, and pathophysiology of Fen-exposed Parkinsonism remain unknown. Recent studies have revealed epigenetic mechanisms underlying PD-related pathway regulation, including DNA methylation. Epigenetic mechanisms are potential targets for therapeutic intervention in neurodegenerative diseases. After whole-genome bisulfite sequencing (WGBS) of midbrain tissues from a Fen-exposed PD-like mouse model, we performed an association analysis of DNA methylation and gene expression. Then we successfully screened for the DNA methylation differential gene Ambra1, which is closely related to PD. The hypermethylation-low expression Ambra1 gene aggravated DA neuron damage in vitro and in vivo through the Ambra1/Parkin/LC3B-mediated mitophagy pathway. We administered 5-aza-2′-deoxycytidine (5-Aza-dC) to upregulate Ambra1 expression, thereby reducing Ambra1-mediated mitophagy and protecting DA neurons against Fen-induced damage. In conclusion, these findings elucidate the potential function of Ambra1 under the regulation of DNA methylation, suggesting that the inhibition of DNA methylation may alleviate Fen-exposed neuron damage.

Gene functions of the Ambystoma altamirani skin microbiome vary across space and time but potential antifungal genes are widespread and prevalent.

Amphibian skin microbiomes can play a critical role in host survival against emerging diseases by protecting their host against pathogens. While a plethora of biotic and abiotic factors have been shown to influence the taxonomic diversity of amphibian skin microbiomes it remains unclear whether functional genomic diversity varies in response to temporal and environmental factors. Here we applied a metagenomic approach to evaluate whether seasonality, distinct elevations/sites, and pathogen presence influenced the functional genomic diversity of the A. altamirani skin microbiome. We obtained a gene catalogue of 92 107 nonredundant annotated genes and a set of 50 unique metagenome assembled genomes (MAGs). Our analysis showed that genes linked to general and potential antifungal traits significantly differed across seasons and sampling locations at different elevations. Moreover, we found that the functional genomic diversity of A. altamirani skin microbiome differed between B. dendrobatidis infected and not infected axolotls only during winter, suggesting an interaction between seasonality and pathogen infection. In addition, we identified the presence of genes and biosynthetic gene clusters (BGCs) linked to potential antifungal functions such as biofilm formation, quorum sensing, secretion systems, secondary metabolite biosynthesis, and chitin degradation. Interestingly genes linked to these potential antifungal traits were mainly identified in Burkholderiales and Chitinophagales MAGs. Overall, our results identified functional traits linked to potential antifungal functions in the A. altamirani skin microbiome regardless of variation in the functional diversity across seasons, elevations/sites, and pathogen presence. Our findings suggest that potential antifungal traits found in Burkholderiales and Chitinophagales taxa could be related to the capacity of A. altamirani to survive in the presence of Bd, although further experimental analyses are required to test this hypothesis.