High Degree Of Connectivity Research Articles

Hydrocarbon potential assessment of the lacustrine fan delta reservoirs in the Lower Cretaceous syn-rift Xing’anling Formation in the Beier Sag, Hailar Basin, Northeast China

Efficient exploration and development of oil and gas resources in complex geological environments continue to pose significant challenges for the energy industry. The localization and extraction of reservoirs in basins with complex structures, developed faults, and scattered sedimentary sand bodies are topics of international interest. One such basin, the Hailar Basin in northeastern China, represents a complex geological environment with heterogeneous distributions of oil and gas reserves, along with variable reservoir conditions, leading to challenges in hydrocarbon exploration and extraction. The Sudeert oil field, situated within this basin, is known for its high productivity; nevertheless, the underlying factors responsible for its success are not yet fully comprehended. Based on seismic, logging, and core data from the Sudeert oil field, as well as previous research, this study comprehensively analyzed the sedimentary environment, sedimentary facies characteristics, sand body distribution patterns, vertical stacking relationships of sand bodies, and hydrocarbon accumulation potential of the oil reservoirs in the Lower Cretaceous Xing’anling Formation in the Sudeert oil field. The Xing’anling Formation I and II oil reservoirs are deposited in a fan-delta front sedimentary environment, and the sedimentary microfacies that are conducive to the development of reservoir sand bodies include underwater distributary channels, underwater natural levees, estuary dams, front silt beds, and turbidite sands. Among them, the underwater distributary channel microfacies is the main depositional facies for the development of reservoir sand bodies. Three major depositional patterns of fan lobes can be identified within this depositional system: 1) isolated, 2) contact, and 3) superimposed lobes. Different combinations of lobes developed in different blocks and resulted in different sand body depositional patterns. The isolated lobes mainly developed in the western oil-producing (B28 block) due to the scarcity of sand and slowly increasing accommodation space. The contact lobes mainly developed in the central oil-producing block (B14 block) due to sufficient sediment supply and steadily increasing accommodation space across a wide area. The superimposed lobes mainly developed in the southeast oil-producing block (B16 block) due to sufficient sediment input and steadily increasing accommodation space within a restricted area. In the whole study area, the superimposed lobe pattern is the most favorable depositional pattern and forms the highest-quality reservoirs because of the high degree of sand body connectivity. These results also highlight the utility of sedimentary patterns and sand body assemblage studies for the oil exploration and development of similar rifted basins.

Integrated bioinformatics analysis to identify key genes and pathways involved in the endometria of patients with recurrent implantation failure undergoing in vitro fertilization and embryo transfer

Objectives: Recurrent implantation failure (RIF) is a challenging clinical problem that occurs in approximately 10% of patients undergoing in vitro fertilization and embryo transfer. Because of the varied criteria for RIF, as well as differences in the time and methods of endometrial biopsy, previous studies have not reached an agreement regarding the key genes and pathways of RIF. In this study, bioinformatic analyses were performed in a homogeneous population with consistent biopsy conditions to explore the molecular mechanisms and identify key RIF-associated genes and pathways in the endometrium. Methods: Seven datasets from the Gene Expression Omnibus database were reviewed in detail, and GSE111974, GSE103465, and GSE26787 were included for further analysis. Common differentially expressed genes (DEGs) were identified using the GEO2R online tool. Gene Ontology and pathway enrichment analyses were performed and a protein–protein interaction (PPI) network was constructed. The RNA and protein expression files of the hub genes were obtained. Results: A total of 402 common DEGs were identified between patients with RIF and controls. The enrichment of these DEGs was mainly associated with tube morphogenesis, vasculature development, and positive regulation of cell migration. Pathway enrichment indicated that pathways involved in cancer, the vascular endothelial growth factor A-vascular endothelial growth factor receptor 2 signaling pathway, and cell cycle pathways were mainly involved. Moreover, a PPI network was constructed, and the three most significant submodules were mainly involved in rRNA processing and the regulation of proteolysis. The following ten DEGs with high degrees of connectivity were identified as hub genes: CDC42, VEGFA, MAP2K1, APP, CYCS, UBE2I, PLEK, LMNA, SMAD2, and ATRX. Conclusion: Key genes and pathways identified in this study could improve our understanding of the underlying molecular events in RIF and be used as potential biomarkers and therapeutic targets. Further studies are required to confirm these results and explore the functions of hub genes in the endometrium during the implantation window in patients with RIF.

Using the Concept of Accessibility and Linear Programming to Measure and Select the Most Prominent Logistics Cities in Iraq

In this research, we will address the importance of geographical location in relation to the supply chain and the process of choosing a location, relying on basic factors, and building a mathematical model using linear programming to choose the most important cities that have a high degree of connectivity (Accessibility) in Iraq from being economical or service distribution centers, either subsidiary or It has a high response speed and contributes to building a logistical transportation model in Iraq. The sports model, after the solution, has reached the selection of the best cities in terms of logistics.

Evaluating thermal expansion in fluorides and oxides: Machine learning predictions with connectivity descriptors

Open framework structures (e.g., ScF3, Sc2W3O12, etc.) exhibit significant potential for thermal expansion tailoring owing to their high atomic vibrational degrees of freedom and diverse connectivity between polyhedral units, displaying positive/negative thermal expansion (PTE/NTE) coefficients at a certain temperature. Despite the proposal of several physical mechanisms to explain the origin of NTE, an accurate mapping relationship between the structural–compositional properties and thermal expansion behavior is still lacking. This deficiency impedes the rapid evaluation of thermal expansion properties and hinders the design and development of such materials. We developed an algorithm for identifying and characterizing the connection patterns of structural units in open-framework structures and constructed a descriptor set for the thermal expansion properties of this system, which is composed of connectivity and elemental information. Our developed descriptor, aided by machine learning (ML) algorithms, can effectively learn the thermal expansion behavior in small sample datasets collected from literature-reported experimental data (246 samples). The trained model can accurately distinguish the thermal expansion behavior (PTE/NTE), achieving an accuracy of 92%. Additionally, our model predicted six new thermodynamically stable NTE materials, which were validated through first-principles calculations. Our results demonstrate that developing effective descriptors closely related to thermal expansion properties enables ML models to make accurate predictions even on small sample datasets, providing a new perspective for understanding the relationship between connectivity and thermal expansion properties in the open framework structure. The datasets that were used to support these results are available on Science Data Bank, accessible via the link https://doi.org/10.57760/sciencedb.j00113.00100.

Uncovering Potential Novel Biomarkers in Immunoglobulin-Resistant Kawasaki Disease Using Bioinformatics Analysis

Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD) is a complicated disorder, which can induce multiple-system damage. The pathogenic factor inducing KD remains unclear. The present study focused on identifying potential novel biomarkers for IVIG-resistant KD using integrated analyses. Eight IVIG-resistant KD samples and twelve IVIG-sensitive KD samples were included in the GSE18606 dataset. A Linear Model for Microarray Data (LIMMA) identified 504 differentially expressed genes (DEGs), An IVIG-resistant KD sample was compared with an IVIG-sensitive KD sample to identify 17 modules through weighted gene co-expression network analysis (WGCNA). A common gene (CG) is the intersection of DEGs and genes in the most significant module. Analysis of functional enrichment revealed that CGs were mainly enriched in TNF signaling pathways and NF-kappa B signaling pathways. Ten of these genes were selected as hub genes because of their high degree of connectivity (KLF1, AHSP, HBQ1, HBA2, HBA1, EPB42, GYPB, UBB, KRT1 and BPIFB2).

Analysis of Department of Home Economics Education Curriculum of College of Education through Keyword Network Analysis

본 연구는 우리나라 사범대학의 가정교육과 교육과정과 382개의 교수요목에 포함된 내용을 키워드 네트워크 방식을 통해 특성을 파악하고 세부 분야별 상관성을 분석하였다. 총 11개 대학의 가정교육과 교육과정과 382개의 교수요목을 분석하기 위해 Krword 프로그램을 활용하여 키워드 출현 빈도를 분석하고, 키워드 간의 연결 정도와 다양한 중심성 척도를 시각화하여 분석한 결과는 다음과 같다. 첫째, 전체 교수요목을 분석한 결과는 가족, 중등학교, 의복, 식품, 소비자, 디자인 등 다양한 분야를 나타내는 키워드들이 골고루 나타났으며 ‘방법’, ‘실제’, ‘변화’, ‘원리’ 등과 같은 교수법 및 수업 방식에 관한 키워드가 높은 연결 정도와 중심성 지표를 나타냈다. 둘째, 세부 분야별 분석에서 영역별 핵심키워드가 나타났으며, 키워드들의 주제는 학문기반의 핵심키워드를 반영하고 있었다. 본 연구는 가정교육과 교육과정에서 미래지향적이고 융합적인 교육내용을 다룰 수 있는 교육과정으로 전환하는 것에 기여하는데 의의가 있다.The purpose of this study was to identify the characteristics of the contents included in the curriculum and 382 syllabi of the department of home economics education of College of Education in Korea and analyze the correlation by detailed area through the keyword network method. In order to analyze the home economics education curriculum and 382 syllabuses of a total of 11 universities, the frequency of keyword occurrence was analyzed using the KrKwic program, also the degree of connection between keywords and various centrality scales were calculated and visualized. The results of this study were as follows. First, as a result of analyzing the entire syllabi, keywords representing various fields such as family, secondary school, clothing, food, consumer, and design appeared evenly, and keywords related to teaching methods such as ‘method’, ‘practice’, ‘change’, and ‘principle’ were appeared. Those keywords showed high degree of connection and centrality. Second, in the detailed sectoral analysis, core keywords for each area appeared, and each subject were found to reflect the core keywords of the academic base. This study contributes to the conversion of curriculum of the department of home economics education to future-oriented and convergent curriculum.

Humpback whale song variations in La Reunion Island from 2016 to 2018 and in Madagascar in 2018

AbstractMale Megaptera novaeangliae produce complex and structured songs which are shared at the population level. Song patterns are culturally transmitted and evolve progressively through time, both over the breeding season and among years. The songs also undergo periods of relatively rapid change, termed “revolutions.” Acoustic monitoring was conducted from 2016 to 2018 in Reunion and throughout 2018 in Madagascar to assess spatiotemporal variation in song structures and population connectivity. A total of 46 high‐quality song samples were selected, representing 2,760 min of recordings in Reunion. In Madagascar, 12 samples representing 240 min of recordings were analyzed. Analysis of songs revealed 11 phrases and their variants. Low levels of temporal variations were observed over the breeding season. Songs recorded in June were very similar to those recorded in September. Greater variation was observed between years, and some phrases identified in 2018 may have evolved from phrases recorded in 2017. More variants were described for each phrase type in 2018 compared to 2016. All themes recorded in Reunion were shared with Madagascar, suggesting a high degree of population connectivity during the breeding season.

Integrative network-based analysis on multiple Gene Expression Omnibus datasets identifies novel immune molecular markers implicated in non-alcoholic steatohepatitis.

Non-alcoholic steatohepatitis (NASH), an advanced subtype of non-alcoholic fatty liver disease (NAFLD), has becoming the most important aetiology for end-stage liver disease, such as cirrhosis and hepatocellular carcinoma. This study were designed to explore novel genes associated with NASH. Here, five independent Gene Expression Omnibus (GEO) datasets were combined into a single cohort and analyzed using network biology approaches. 11 modules identified by weighted gene co-expression network analysis (WGCNA) showed significant association with the status of NASH. Further characterization of four gene modules of interest demonstrated that molecular pathology of NASH involves the upregulation of hub genes related to immune response, cholesterol and lipid metabolic process, extracellular matrix organization, and the downregulation of hub genes related to cellular amino acid catabolic, respectively. After DEGs enrichment analysis and module preservation analysis, the Turquoise module associated with immune response displayed a remarkably correlation with NASH status. Hub genes with high degree of connectivity in the module, including CD53, LCP1, LAPTM5, NCKAP1L, C3AR1, PLEK, FCER1G, HLA-DRA and SRGN were further verified in clinical samples and mouse model of NASH. Moreover, single-cell RNA-seq analysis showed that those key genes were expressed by distinct immune cells such as microphages, natural killer, dendritic, T and B cells. Finally, the potential transcription factors of Turquoise module were characterized, including NFKB1, STAT3, RFX5, ILF3, ELF1, SPI1, ETS1 and CEBPA, the expression of which increased with NASH progression. In conclusion, our integrative analysis will contribute to the understanding of NASH and may enable the development of potential biomarkers for NASH therapy.

A Zeolite-Like Metal-Organic Framework Based Membrane for Reverse Selective Hydrogen Separation and Butane Isomer Sieving.

Here, the fabrication of a defect-free membrane that is based on a zeolite-like metal-organic framework (ZMOF) with the underlying ana topology is reported. The unique ana-ZMOF structure provides high degree of pore connectivity, which is reflected by the fast transport of gases. Prominently, it offers an optimum pore-aperture size, affording notable sieving selectivity for butane/isobutane, and optimal pore energetics for reverse CO2 /H2 separation. This emphasize the potential for the application of pure MOF membranes, paving the way to more sustainability of energy resources.

A Zeolite‐Like Metal–Organic Framework Based Membrane for Reverse Selective Hydrogen Separation and Butane Isomer Sieving

AbstractHere, the fabrication of a defect‐free membrane that is based on a zeolite‐like metal‐organic framework (ZMOF) with the underlying ana topology is reported. The unique ana‐ZMOF structure provides high degree of pore connectivity, which is reflected by the fast transport of gases. Prominently, it offers an optimum pore‐aperture size, affording notable sieving selectivity for butane/isobutane, and optimal pore energetics for reverse CO2/H2 separation. This emphasize the potential for the application of pure MOF membranes, paving the way to more sustainability of energy resources.

Evaluation of the Genes and Molecular Pathways Involved in Skin Lesions in Patients with COVID-19: Systems Biology and Bioinformatics Analysis Approach

Background: Coronavirus disease 2019 (COVID-19) was first identified in 2019 in Wuhan, China. Initially, although the number of COVID-19-infected individuals was very low, the infected cases increased as the virus spread worldwide. Skin manifestation is one of the symptoms observed in COVID-19 patients. Objectives: This study investigated the critical genes and molecular pathways involved in skin manifestations in COVID-19 patients through a biological system approach. Methods: In this study, the microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database and analyzed for identifying differentially expressed genes (DEGs). The enrichment analysis of DEGs was evaluated using the DAVID database. Afterward, protein-protein interaction (PPI) networks were constructed via the STRING database and visualized using Cytoscape software. The hub genes were recognized using the cytoHubba. The interaction of the microRNA (miRNA)-hub genes, transcription factor (TF)-hub genes, and drug-hub genes was also evaluated in this study. Results: After analysis, some genes with the highest degree of connectivity, which were involved in the pathogenesis of HELLP syndrome were identified, and they were known as hub genes. These genes are as follows: IFN-γ, CXCL1, CCL2, CCL3, TLR2, IL-1B, CXCL6, IL-6, CCL4, and CXCL2. has-mir-34a-5p, has-mir-20a-5p, and has-mir-27a-3p as miRNA, as well as RELA as TF had the most interaction with the hub genes. Conclusion: Finally, IL-6 and CXCL10 that were compared to the other hub genes had the highest interaction with other genes; therefore, their role in Shamgir's pathogenesis is significant. Targeting the cited genes would be a strategy to prevent symptom manifestation and better patient management.

Spatio-temporal connectivity of the aquatic microbiome associated with cyanobacterial blooms along a Great Lake riverine-lacustrine continuum.

Lake Erie is subject to recurring events of cyanobacterial harmful algal blooms (cHABs), but measures of nutrients and total phytoplankton biomass seem to be poor predictors of cHABs when taken individually. A more integrated approach at the watershed scale may improve our understanding of the conditions that lead to bloom formation, such as assessing the physico-chemical and biological factors that influence the lake microbial community, as well as identifying the linkages between Lake Erie and the surrounding watershed. Within the scope of the Government of Canada's Genomics Research and Development Initiative (GRDI) Ecobiomics project, we used high-throughput sequencing of the 16S rRNA gene to characterize the spatio-temporal variability of the aquatic microbiome in the Thames River-Lake St. Clair-Detroit River-Lake Erie aquatic corridor. We found that the aquatic microbiome was structured along the flow path and influenced mainly by higher nutrient concentrations in the Thames River, and higher temperature and pH downstream in Lake St. Clair and Lake Erie. The same dominant bacterial phyla were detected along the water continuum, changing only in relative abundance. At finer taxonomical level, however, there was a clear shift in the cyanobacterial community, with Planktothrix dominating in the Thames River and Microcystis and Synechococcus in Lake St. Clair and Lake Erie. Mantel correlations highlighted the importance of geographic distance in shaping the microbial community structure. The fact that a high proportion of microbial sequences found in the Western Basin of Lake Erie were also identified in the Thames River, indicated a high degree of connectivity and dispersal within the system, where mass effect induced by passive transport play an important role in microbial community assembly. Nevertheless, some cyanobacterial amplicon sequence variants (ASVs) related to Microcystis, representing less than 0.1% of relative abundance in the upstream Thames River, became dominant in Lake St. Clair and Erie, suggesting selection of those ASVs based on the lake conditions. Their extremely low relative abundances in the Thames suggest additional sources are likely to contribute to the rapid development of summer and fall blooms in the Western Basin of Lake Erie. Collectively, these results, which can be applied to other watersheds, improve our understanding of the factors influencing aquatic microbial community assembly and provide new perspectives on how to better understand the occurrence of cHABs in Lake Erie and elsewhere.

Nucleus pulposus related lncRNA and mRNA expression profiles in intervertebral disc degeneration

In the present study, we aimed to have a comprehensive understanding of nucleus pulposus related long noncoding RNA (lncRNA) and mRNA expression profiles in intervertebral disc degeneration (IDD). In total, 2418 mRNAs and 528 lncRNAs were found to be differentially expressed in the IDD group compared with the Control group. Combining microarray datasets and sequencing data, 5 overlapping DEMs and 7 overlapping DELs were identified. NF-κB signaling pathway, PI3K-Akt signaling pathway and Wnt/β-catenin signaling pathway were strongly linked with enriched GO terms and KEGG pathways. The ceRNA network suggested that lnc-TMEM44-AS1-hsa-miR-206-HDAC4 may be one crucial axis in IDD. PPI network analysis was constructed with 309 nodes and 129 edges. And the highest connectivity degrees were ALB, APOB and CCL2. This study suggested that specific lncRNAs and ceRNA axes may be crucial in the development of IDD. It provides a new perspective for delaying IDD process and enhancing intervertebral disc repair.

Magnetic susceptibility of inclined soils and its relationship with some agronomic indicators

The modern agricultural complex requires the use of new methods for determining soil characteristics for adequate information support of the latest technologies, which is often impossible to provide using conventional methods. The purpose of the study is to identify the informative value of magnetometric methods in determining slope processes that regulate the use of certain measures to increase soil fertility and protect soils from erosion. The study was conducted on inclined agricultural landscapes of the Kharkiv region. This study used a KLY-2 Kappabridge (Czech Republic) and an Ohaus 403 laboratory scale to determine magnetic susceptibility. The selected soil samples, in accordance with the accepted methods, were brought to an air-dry state under normal conditions. Soil sampling was conducted from a layer of 0-20 cm. Visualisation of the study results and determination of potential soil losses (USLE model) was performed in the QGis programme. The correlation of magnetic susceptibility on simple and complex slopes was analysed. It was established that on simple slopes, the value of the magnetic susceptibility of the soil has a high value of this indicator with the content of physical clay and organic carbon. Therewith, there is a high degree of connection of this indicator with the results of mathematical modelling of erosion processes (USLE). For complex sections of slopes, the method is correct only for transeluvial landscapes, while for accumulative landscapes, the mentioned connection disappears. The correlation coefficient in the humus content – magnetic susceptibility pair also decreases. This is due to the alternation of washout–accumulation zones and exits of soil-forming rocks in runoff basins, the existence of which is not provided for by the procedure for applying the USLE model of potential soil losses. The use of soil MS data has a high potential for the localisation of soil inhomogeneities associated with the differentiation of humus content and granulometric composition

Effects of Three Different Tillage Patterns on Ground and Below-Ground Dwelling Insect Assemblage

Tillage could significantly change the biodiversity in farmlands. As a prominent component of farmland ecology, crops play a key role in regulating biological communities. To explore the effects of tillage patterns and planting modes, including high-disturbance tillage practices and different plant compositions, on the abundance of soil insects, we tested the responses of soil insects to no-tillage (NT), ridge tillage (RT), and fall plow (FP) treatments with different planting modes. The results illustrated that planting modes significantly changed the distributions of ground-dwelling insect species and disturbed interactions on the farmland. Soil-dwelling insect assemblages were mainly influenced by tillage patterns, which reflected that soil physicochemical properties, especially pH, had the highest contribution to the determination of community composition. The no-tillage system supported the highest predator species richness and lower herbivore richness with higher abundance. In the no-tillage system, most of the insects on the farmland have established relationships, forming a relatively high degree of connection between different insects. The network was more specialized and nested in the field with fall ploughing. In conclusion, the effects of tillage patterns and planting modes on insect assemblage can be divided into two spatial dimensions: the success of soil-ground insect maintenance determined by plants and below-ground depended on tillage.

Bioinformatic identification of potential biomarkers and therapeutic targets in carotid atherosclerosis and vascular dementia.

Vascular disease is the second most common cause of dementia. The prevalence of vascular dementia (VaD) has increased over the past decade. However, there are no licensed treatments for this disease. Carotid atherosclerosis (CAS) is highly prevalent and is the main cause of ischemic stroke and VaD. We studied co-expressed genes to understand the relationships between CAS and VaD and further reveal the potential biomarkers and therapeutic targets of CAS and VaD. CAS and VaD differentially expressed genes (DEGs) were identified through bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE43292 and GSE122063, respectively. Furthermore, a variety of target prediction methods and network analysis approaches were used to assess the protein-protein interaction (PPI) networks, the Gene Ontology (GO) terms, and the pathway enrichment for DEGs, and the top 7 hub genes, coupled with corresponding predicted miRNAs involved in CAS and VaD, were assessed as well. A total of 60 upregulated DEGs and 159 downregulated DEGs were identified, of which the top 7 hub genes with a high degree of connectivity were selected. Overexpression of these hub genes was associated with CAS and VaD. Finally, the top 7 hub genes were coupled with corresponding predicted miRNAs. hsa-miR-567 and hsa-miR-4652-5p may be significantly associated with CAS and VaD.

Analysis of crises in related economies on the example of Latin American countries

This article provides an analysis of the key macroeconomic and financial indicators of Latin American countries in 2020–2022. The objective is to periodize the behavior of economic indicators in the connected economies of developing countries. The relevance of the study lies in the need to understand the mechanisms of behavior of economic entities in crisis situations. Latin American countries were chosen as a model for the study because they are characterized by a high degree of connectivity, as they all fall into the category of developing countries and differ significantly in the behavior of regulators in crisis conditions. Based on the objective, the analyzed period for the region under consideration was conditionally divided into four stages: the initial panic of 2020, the period of the beginning of recovery at the end of 2020, the recovery of economies against the background of rising inflation in 2021, and a decrease in recovery growth due to instability in 2022. The methodology shows general trends and characteristic deviations caused by general and specific factors. General trends describe the behavior of economic indicators in the selected four stages of the crisis. The deviations show how related economies react to general external shocks in specific conditions. For example, the size of the economy and domestic economic policy have shown themselves as specific factors. The results show that Brazil’s larger economy was more affected by the inflationary shock and took tougher measures with regard to the central bank rate. Throughout the crisis and the subsequent period, Mexico demonstrated a lower unemployment rate and a lower level of government budget losses.

Comparative analysis of changes in whey proteins of goat milk throughout the lactation cycle using quantitative proteomics.

The composition and content of goat milk proteins are affected by many factors and have been extensively studied. However, variation in whey protein composition in goat milk throughout the lactation cycle has not been clarified. In the current study, 15 dairy goats were selected, and milk samples were collected at 1, 3, 30, 90, 150, and 240 d after delivery. Whey proteins were separated and digested and then identified using data-independent acquisition (DIA) and data-dependent acquisition proteomics approaches. Protein profiles identified using DIA were consistent with those of the data-dependent acquisition proteomics approach according to clustering and principal component analyses. Significant differences in the abundance of 238 proteins around the lactation cycle were identified using the DIA approach. Developmental changes of the whey proteome corresponding to lactation stage were revealed: plasminogen, α-2-macroglobulin, and fibronectin levels decreased from d 1 to 240, whereas polymeric immunoglobulin receptor, nucleobindin 2, fatty acid-binding protein 3, and lactoperoxidase increased from d 1 to 240. Protein-protein interaction analysis showed that fibronectin with a higher degree of connectivity is a central node. The findings are of great significance to better understanding the potential role of specific proteins and the mechanism of protein biosynthesis or intercellular transport in the mammary glands related to the physiological changes of dairy goats.

Weighted gene correlation network analysis identifies the critical long non-coding RNAs participate in the progression of osteosarcoma.

This study aimed to identify more biomarkers associated with osteosarcoma progression via lncRNA-mRNA co-expression network. Dataset GSE99671 was downloaded from GEO database. The mRNAs and lncRNAs that were differentially expressed between tumor and normal samples were screened out. Functional enrichment analysis of differentially expressed mRNAs was carried out, followed by weighted gene correlation network analysis (WGCNA). Based on the lncRNAs and mRNAs, a lncRNA-mRNA co-expression network was constructed. Total 703 mRNAs and 7 lncRNAs were differentially expressed between tumor and normal tissues. The mRNAs were significantly enriched in functions associated with inflammatory response as well as autoimmune thyroid disease and ribosome pathways. WGCNA revealed that ME2 module had a high correlation with tumor, and ST3GAL4, UCK2, PSAT1 etc. had higher connectivity degrees in this module. lncRNA-mRNA co-expression network showed that 12 mRNAs, such as PEMT, COL10A1 and GSTA1, were synergistically expressed with lncRNA TTTY14. Inflammatory response and ribosome synthesis may play important role in osteosarcoma progression. lncRNA TTTY14 may affect the development of osteosarcoma by cooperative expression with PEMT, COL10A1, GSTA1, etc. ST3GAL4, UCK2, PSAT1 as well as TTTY14 may serve as key biomarkers in osteosarcoma.

Establishing connectivity patterns of eastern oysters (Crassostrea virginica) on regional oceanographic scales

AbstractLocalized depletion of marine and estuarine populations often results from large‐scale natural and anthropogenic disturbances (e.g., hurricanes, oil spills) as well as overharvest of fisheries resources. Understanding how such localized depletions may affect populations at larger regional scales requires knowledge of connectivity among local populations within the larger regional landscape or metapopulation. Efforts to restore populations following such decreases require similar knowledge. During the 2010 Deepwater Horizon oil spill, dramatic declines of oysters occurred throughout estuaries west and east of the Mississippi River. We examined trajectories of particles, which were parameterized to mimic oyster larvae, using the ADvanced CIRCulation (ADCIRC; https://adcirc.org) model to evaluate potential connectivity within and among embayments from Western Louisiana to Alabama. Patterns of larval settlement, which we defined as the intersection of a larval particle with known or expected oyster habitat at any point 13–21 days post‐release, reflected much greater local contributions, with 50%–90% of settled particles originating within the same subdivision of embayments. Exchange among subdivision was much less (0%–40%) and settlement originating from outside the embayment of release was trivial under most scenarios (0%–14%). Connectivity between adjacent basins was greatest for larvae released in the southern portions of the embayment, whereas connectivity among nonadjacent basins was not predicted under the scenarios modeled. Because most local populations are relatively isolated on ecological timescales, areas suffering from extensive local depletion are likely to require extensive time to recover due to the lack of larval subsidy from the overall regional population. Restoration would require building stepping‐stone populations or reefs within and among basin to restore a high degree of connectivity.