Preliminary Verification Research Articles

Bioinformatics analysis of differentially expressed genes in diabetic foot ulcer and preliminary experimental verification.

Molecular changes are closely related to the pathogenesis and healing process of diabetic foot ulcers (DFUs), and are crucial for the early prediction and intervention of DFU. Bioinformatics analysis was performed in this study to identify the key differentially expressed genes (DEGs) in DFU, analyze their functions and function modes, and conduct preliminary experimental verification to determine the potential pivotal genes in the pathogenesis of DFU. Two datasets, GSE68183 and GSE80178, were obtained from the Gene Expression Omnibus (GEO). DEGs were obtained using GEO2R. Six co-expressed DEGs (co-DEGs) were obtained by R language analysis. The co-DEGs were constructed by using STRING and Cytoscape 3.7.2 to construct a protein-protein interaction (PPI) network, and two hub genes, NHLRC3 and BNIP3, were identified. The BNIP3 gene was selected for further analysis. Co-DEGs were used for Gene Ontology (GO) function analysis using the WebGestalt database, and BNIP3-related biological processes focused on mitochondrial protein decomposition. GO function analysis of the BNIP3 gene and its interacting genes was carried out using the cluster profile package and org.hs.eg. db package of the R language and its biological process was enriched in the cell response to external stimuli and autophagy. BNIP3 and its interacting genes were retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and KEGG pathway enrichment analysis was performed using the WebGestalt database. The results showed that BNIP3 was significantly correlated with mitochondrial autophagy and the FoxO signaling pathway. The miRDB and TargetScan databases were used to identify the relevant microRNAs (miRNAs) regulating the BNIP3 gene, and it was found that miRNA-182 may be involved in the targeted regulation of BNIP3. Western blot analysis was performed to determine the abnormal expression of BNIP3. Our study found that the BNIP3 gene may be a new biomarker and intervention target for DFU.

A method for high-precision time transfer between low earth orbit spacecraft and Beidou satellite and its preliminary test verification

A method for high-precision time transfer between low earth orbit spacecraft and Beidou satellite and its preliminary test verification

A Mixed Reality-enhanced Rapid Prototyping Approach for Industrial Articulated Products

The design of industrial articulated products is challenging due to the consideration of multiple poses, movements, and especially in-field constraints, such as the design of a personalized robot arm or the layout of articulated hoists. Traditionally, depicting 2D sketches from multiple perspectives and poses of the product is tedious. Meanwhile, on-site evaluation after fabricating the physical prototype is costly and time-consuming. In order to assist in context-aware decision-making at the early design stage, this research proposes a mixed reality-enhanced rapid prototyping approach for industrial articulated products. In a 3D mixed reality environment that incorporates the surroundings, designers can depict key joints and rough shapes through intuitive gesture-based interaction. After a quick prototype creation, the kinematics preview is provided to designers for preliminary functional verification. Finally, a user study shows that the proposed approach can help designers rapidly complete the MR prototype of articulated products at the early design stage, provide a better understanding of the product movement, assist in-field solution generation and facilitate communication. It is hoped this explorative study can offer insightful ideas with effective toolkits for assisting the new product design process more intuitively and interactively.

Research on a Regional Landslide Early-Warning Model Based on Machine Learning—A Case Study of Fujian Province, China

China’s landslide disasters are serious, and regional landslide disaster early-warning is one of the important means of disaster prevention and mitigation. The traditional regional landslide disaster early-warning model, however, is limited by the complex landslide induction mechanism, limited data accumulation, and insufficient big data analysis methods, and has problems such as limited early-warning accuracy and insufficient refinement. In this paper, a machine learning method was introduced into the field of regional landslide disaster warning. From the model construction process of training sample-set construction, sample learning and training, model parameter optimization, model preservation, warning output, and so on, a method for constructing a regional landslide early-warning model based on machine learning was systematically proposed. In the sample learning and training, 80% of the training sample-set was used as the training set, and 20% was used as the test set for five-fold cross validation. The Bayesian Optimization algorithm was used to optimize the model parameters, and the accuracy, ROC curve, and AUC value were used to verify the model accuracy and model generalization ability. With China’s Fujian province as an example, based on nine years of geological and meteorological data (2010–2018), geological environment factors, factors of hazard-affected bodies and historical disaster situations, and rainfall-induced factors in four categories, a total of 26 indicators were used as input characteristic parameters. Six machine learning algorithms were adopted to improve model training; the results showed that the Random Forest algorithm performed the best, giving an accuracy of 92.3%, and was the model with the best generalization ability (AUC was 0.955). The second best was the Artificial Neural Network model, with an accuracy of 0.937 and an AUC of 0.935. Next were the Nearest Neighbor model, the Logistic Regression model, and the Support Vector Machine; the poorest results were from the Decision Tree model. Finally, the typical rainfall-type landslide disaster process in Fujian Province was selected as an example to verify the Random Forest algorithm model. The results showed that compared with the early-warning results of the original explicit statistical model, the hit rate of the new model was 6 times, or equal to that of the original model, and the landslide density in the early-warning area of the new model was 1.6–1.7 times that of the original model. Preliminary verification showed that the new model based on the Random Forest method has obvious advantages, a higher hit rate and a smaller warning area, and can achieve more accurate warnings. The follow-up will continue to track the new landslide disaster situation in the study area and carry out model verification and correction.

Robot-assisted subretinal injection system: development and preliminary verification

BackgroundTo design and develop a surgical robot capable of assisting subretinal injection.MethodsA remote center of motion (RCM) mechanical design and a master-slave teleoperation were used to develop and manufacture the assisted subretinal surgery robot (RASR). Ten fresh isolated porcine eyes were divided into the Robot Manipulation (RM) group and Manual Manipulation (MM) group (5 eyes for each group), and subretinal injections were performed by the robot and manual manipulation methods, respectively. A preliminary verification of the robot was performed by comparing the advantages and disadvantages of the robot manipulation and manual manipulation by using optical coherent tomography (OCT), fundus photography, and video motion capture analysis after the surgery.ResultsBoth the robot and the manual manipulation were able to perform subretinal injections with a 100% success rate. The OCT results showed that the average subretinal area was 1.548 mm2 and 1.461 mm2 in the RM and MM groups, respectively (P > 0.05). Meanwhile the volume of subretinal fluid obtained using the retinal map mode built in OCT was not statistically different between the RM and MM groups (P > 0.05). By analyzing the surgical video using Kinovea, a motion capture and analysis software, the results suggest that the mean tremor amplitude of the RM group was 0.3681 pixels (x direction), which was significantly reduced compared to 18.8779 pixels (x direction) in the MM group (P < 0.0001).ConclusionRobot-assisted subretinal injection system (RASR) is able to finish subretinal injection surgery with better stability and less fatigue than manual manipulation.

Landmark-Based Scale Estimation and Correction of Visual Inertial Odometry for VTOL UAVs in a GPS-Denied Environment.

With the rapid development of technology, unmanned aerial vehicles (UAVs) have become more popular and are applied in many areas. However, there are some environments where the Global Positioning System (GPS) is unavailable or has the problem of GPS signal outages, such as indoor and bridge inspections. Visual inertial odometry (VIO) is a popular research solution for non-GPS navigation. However, VIO has problems of scale errors and long-term drift. This study proposes a method to correct the position errors of VIO without the help of GPS information for vertical takeoff and landing (VTOL) UAVs. In the initial process, artificial landmarks are utilized to improve the positioning results of VIO by the known landmark information. The position of the UAV is estimated by VIO. Then, the accurate position is estimated by the extended Kalman filter (EKF) with the known landmark, which is used to obtain the scale correction using the least squares method. The Inertial Measurement Unit (IMU) data are used for integration in the time-update process. The EKF can be updated with two measurements. One is the visual odometry (VO) estimated directly by a landmark. The other is the VIO with scale correction. When the landmark is detected during takeoff phase, or the UAV is returning to the takeoff location during landing phase, the trajectory estimated by the landmark is used to update the scale correction. At the beginning of the experiments, preliminary verification was conducted on the ground. A self-developed UAV equipped with a visual-inertial sensor to collect data and a high-precision real time kinematic (RTK) to verify trajectory are applied to flight tests. The experimental results show that the method proposed in this research effectively solves the problems of scale and the long-term drift of VIO.

Long‐Term High‐Resolution Gauge Adjusted Satellite Rainfall Product Over India

AbstractThis study aims to create a 21‐year, high spatiotemporal resolution Global Satellite Mapping of Precipitation (GSMaP) rainfall product adjusted by rain gauge measurements over the Indian mainland and highlighted the importance of the Indian Meteorological Department (IMD) daily gridded rainfall to generate gauge adjusted GSMaP rainfall products over Indian landmass. The targeted resolutions of the GSMaP are hourly and 0.1° × 0.1°. The National Oceanic and Atmospheric Administration Climate Prediction Center daily gauge analysis (0.5° × 0.5°) and IMD daily gridded rainfall (0.25° × 0.25°) were utilized to generate long‐term rainfall products, GSMaP_CPC and GSMaP_IMD rainfall, respectively. After preliminary verification of the GSMaP_CPC and GSMaP_IMD rainfalls with IMD gauges, these rainfall products are evaluated for the Indian Summer Monsoon periods of 2000–2020 with comparisons of other gauge adjusted rainfall products such as the Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement final‐run. The results suggest GSMaP_IMD has a smaller root‐mean‐square difference (RMSD) and higher correlation than GSMaP_CPC, evaluated against independent rainfall products. In the 3‐hour mean analysis with spaceborne precipitation radar data, it is found that the value of RMSD decreases in GSMaP_IMD with respect to GSMaP_CPC throughout the day. The statistics against the hourly dense gauge network suggests that the GSMaP_IMD is more effective in capturing large spatiotemporal rainfall variation. Thus, validation results with the independent sources suggest that GSMaP_IMD rainfall generally improved over GSMaP_CPC rainfall. These improvements are significant in orographic regions with high rainfall amounts, mainly the western Ghats and northeastern parts of India.

Analytical performance overview of the Lumipulse G pTau 181 Plasma RUO

AbstractBackgroundStudies have shown that changes in Alzheimer’s disease (AD) biomarker levels occur in blood at approximately the same time as in cerebrospinal fluid (CSF). Therefore, plasma‐based testing could be used as a simple, accessible, and scalable approach to help support the diagnosis of AD, avoiding the complexity of CSF sampling, and the high costs and limited availability of PET imaging. It was demonstrated that plasma pTau181 has the potential to be a good predictor of amyloid PET positivity, has proven to differentiate between AD and non‐AD neurodegenerative diseases, and is able to predict progression to AD. The aim of this study was to determine the preliminary analytical performance of the newly developed Lumipulse G pTau 181 Plasma RUO assay.MethodThe LUMIPULSE G System is a chemiluminescent enzyme immunoassay platform that allows fully automated processing of samples using ready‐to‐use immunoreaction cartridges. Time to result in these single use test cartridges takes about 30 minutes. The assay uses AT270 for capturing and HT7/BT2‐conjugate for detection in a 2‐step set‐up. Parameters analysed were precision, sensitivity, linearity, and potential impact of interfering substances. The studies included a series of buffer– and K2EDTA plasma samples at different concentration levels, each tested in several replicates sized to the different parameters tested.ResultThe total within‐lab variability of the assay was found to be &lt;5% CV for each of the samples tested, confirming the high precision of the LUMIPULSE G platform. Using low pTau181 concentrated plasma samples, the LoD was found to be &lt;0.20 pg/mL, and the LoQ &lt;0.50 pg/mL. The high sensitivity was confirmed by a formal concentration assignment to each tested samples of a cohort of healthy elderly subjects. Linearity was shown across the measurement range of the assay (0 – 60 pg/mL), and no significant impact of rheumatoid factor and human anti‐mouse antibodies was observed.ConclusionThis preliminary verification of the analytical performance of the Lumipulse G pTau 181 Plasma RUO indicated promising results in terms of low variability, good dilutional linearity, and high sensitivity. The assay is now ready for full analytical verification and clinical validation towards the identified contexts of use.

Preliminary verification of the anti-hypoxia mechanism of Gentiana straminea maxim based on UPLC-triple TOF MS/MS and network pharmacology

BackgroundAnoxia is characterized by changes in the morphology, metabolism, and function of tissues and organs due to insufficient oxygen supply or oxygen dysfunction. Gentiana straminea Maxim (G.s Maxim) is a traditional Tibetan medicine. Our previous work found that G.s Maxim mediates resistance to hypoxia, and we found that the ethyl acetate extract had the best effect. Nevertheless, the primary anti-hypoxia components and mechanisms of action remain unclear.MethodsCompounds from the ethyl acetate extraction of G.s Maxim were identified using UPLC-Triple TOF MS/MS. Then Traditional Chinese Medicine Systematic Pharmacology Database was used to filtrate them. Network pharmacology was used to forecast the mechanisms of these compounds. Male specific pathogen-free Sprague Dawley rats were randomly divided into six groups: (1) Control; (2) Model; (3) 228 mg/kg body weight Rhodiola capsules; (4) 6.66 g/kg body weight the G.s Maxim’s ethyl acetate extraction; (5) 3.33 g/kg body weight the G.s Maxim’s ethyl acetate extraction; (6) 1.67 g/kg body weight the G.s Maxim’s ethyl acetate extraction. After administering intragastric ally for 15 consecutive days, an anoxia model was established using a hypobaric oxygen chamber (7000 m, 24 h). Then Histology, enzyme-linked immunosorbent assays, and western blots were performed to determine these compounds’ anti-hypoxic effects and mechanisms. Finally, we performed a molecular docking test to test these compounds using Auto Dock.ResultsEight drug-like compounds in G.s Maxim were confirmed using UPLC-Triple TOF MS/MS and Lipinski’s rule. The tumor necrosis factor (TNF) signaling pathway, the hypoxia-inducible factor 1 (HIF-1) signaling pathway, and the nuclear factor kappa-B (NF-κB) signaling pathway was signaling pathways that G.s Maxim mediated anti-anoxia effects. The critical targets were TNF, Jun proto-oncogene (JUN), tumor protein p53 (TP53), and threonine kinase 1 (AKT1). Animal experiments showed that the ethyl acetate extraction of G.s Maxim ameliorated the hypoxia-induced damage of hippocampal nerve cells in the CA1 region and reversed elevated serum expression of TNF-α, IL-6, and NF-κ B in hypoxic rats. The compound also reduced the expression of HIF-1α and p65 and increased the Bcl-2/Bax ratio in brain tissue. These findings suggest that G.s Maxim significantly protects against brain tissue damage in hypoxic rats by suppressing hypoxia-induced apoptosis and inflammation. Ccorosolic acid, oleanolic acid, and ursolic acid had a strong affinity with core targets.ConclusionsThe ethyl acetate extraction of G.s Maxim mediates anti-hypoxic effects, possibly related to inhibiting apoptosis and inflammatory responses through the HIF-1/NF-κB pathway. The primary active components might be corosolic, oleanolic, and ursolic acids.

Advances in sequencing and key character analysis of mango (Mangifera indica L.).

Mango (Mangifera indica L.) is an important fruit crop in tropical and subtropical countries associated with many agronomic and horticultural problems, such as susceptibility to pathogens, including powdery mildew and anthracnose, poor yield and quality, and short shelf life. Conventional breeding techniques exhibit significant limitations in improving mango quality due to the characteristics of long ripening, self-incompatibility, and high genetic heterozygosity. In recent years, much emphasis has been placed on identification of key genes controlling a certain trait through genomic association analysis and directly breeding new varieties through transgene or genotype selection of offspring. This paper reviews the latest research progress on the genome and transcriptome sequencing of mango fruit. The rapid development of genome sequencing and bioinformatics provides effective strategies for identifying, labeling, cloning, and manipulating many genes related to economically important traits. Preliminary verification of the functions of mango genes has been conducted, including genes related to flowering regulation, fruit development, and polyphenol biosynthesis. Importantly, modern biotechnology can refine existing mango varieties to meet the market demand with high economic benefits.

Mechanism of Sijunzi Decoction in the treatment of colorectal cancer based on network pharmacology and experimental validation

Ethnopharmacological relevanceSijunzi Decoction（SJZD）, as a famous classical prescription for the treatment of colorectal cancer(CRC) in the traditional Chinese medicine (TCM), has achieved good curative effects in clinical practice. However, its specific ingredients and molecular mechanisms is still unclear. Aim of the studyTo analyze the effective ingredients and molecular mechanisms of SJZD in the treatment of CRC through network pharmacology technology and experimental validation. Materials and methodsFirst, the TCM Systems Pharmacology database and analysis platform database were searched to screen the effective chemical components of SJZD. Swiss Target Prediction was used to predict corresponding potential target genes of compounds. After that, we constructed a components and corresponding target network by Cytoscape. Simultaneously, 5 disease databases were used to search and filter CRC targets, and then we constructed a drug-disease target protein-protein interaction (PPI) network. Cytoscape 3.7 was used for visualization and cluster analysis, and Metascape database was used for GO and KEGG enrichment analysis. We drew the main pathway-target network diagram. Autodock vina1.5.6 was applied to molecular docking for the main compounds and target proteins. Subsequently, the potential mechanism of SJZD on colon cancer predicted by network pharmacological analysis was experimentally studied and verified in vivo and in vitro. Results144 effective active chemical components, 897 potential targets, and 2584 CRC target genes were screened out. The number of common targets between the SJZD and CRC was 414.3250 GO biological process items and 186 KEGG signal pathways were obtained after analysis. The main compounds and the target protein had a good binding ability in molecular docking. The results of cell and animal experiments showed that SJZD could promote apoptosis and autophagy of CRC cells through PI3K/Akt/mTOR pathway. ConclusionsSJZD can treat CRC through multiple components, multiple targets and multiple pathways. We initially revealed the effective components and molecular mechanisms of SJZD in the treatment of CRC, and we used molecular docking and experiment for preliminary verification.

Preliminary verification of multi-group cross-sections generation and locally heterogeneous transport calculation using OpenMC with CEFR start-up tests benchmark

The multi-group (MG) Monte-Carlo (MC) scheme is a hybrid method based on MC solvers and deterministic strategies. This paper focuses on the study of MG schemes for the analysis of fast reactors. The MG scheme in this paper is composed of two steps. In the cross-section generation step, the OpenMC continuous-energy (CE) mode is used with 2D or 3D high-fidelity cluster geometry. In the core calculation step, both homogeneous and locally heterogeneous core models are computed using OpenMC in multi-group mode. The MG schemes are applied and validated in the China Experimental Fast Reactor (CEFR) start-up tests and compared to the CE scheme. The results show an overprediction of core criticality. The locally heterogeneous scheme improves significantly the accuracy in predicting control rod worth. Moreover, synthesizing the results from deterministic code, the locally heterogeneous scheme exhibits a stable performance across different codes, core sizes, and control rod designs. The locally heterogeneous core model with cross-sections generated from the 3D cluster has a good ability in the prediction of feedback coefficients including the sodium void reactivity, temperature reactivity, and subassembly swap reactivity. The computation speed of the locally heterogeneous MG scheme is almost the same as the homogenous MG scheme and its core calculation uses only 7.2% computation time of the reference CE scheme.

Chemical constituents and anti-liver fibrosis mechanism of Meconopsis quintuplinervia based on UPLC-Q-Exactive-MS/MS and network pharmacology

In this study, UPLC-Q-Exactive-MS/MS was used to rapidly analyze the chemical constituents of Meconopsis quintupli-nervia, and the anti-liver fibrosis mechanism of M. quintuplinervia was preliminarily analyzed by network pharmacology, molecular docking, and cell experiments. The chemical constituents of M. quintuplinervia were identified according to the information of MS~1 and MS~2, as well as the data in the literature and databases. SwissTargetPrediction and TargetNet were used to predict the potential targets. The targets related to liver fibrosis were collected from GeneCards and OMIM. The protein-protein interaction(PPI) network was constructed by STRING. Cytoscape 3.6.1 was used to construct and analyze the &quot;constituent-target-disease&quot; network to obtain key targets and their corresponding constituents in the network. DAVID 6.8 was used for GO analysis and KEGG signaling pathway enrichment analysis. Finally, the preliminary verification was carried out by molecular docking and cell experiments. As a result, 106 chemical constituents were identified from M. quintuplinervia, including 66 flavonoids, 16 alkaloids, 18 phenolic acids, 1 anthocyanin, and 5 other constituents. Among them, 3 constituents were identified as potential new compounds, and 59 constituents were reported in M. quintuplinervia for the first time. Network pharmacology analysis showed that M. quintuplinervia presumably acted on AKT1, SRC, JUN, EGFR, STAT3, HSP90 AA1, MAPK3, and other core targets through luteolin, isorhamnetin, quercetin, apigenin, kaempferide, amurine, 2-methylflavinantine, allocryptopine, the multi and other active compounds, thereby regulating the PI3 K/AKT signaling pathway, pathways in cancer, proteoglycans in cancer, FoxO signaling pathway, and other pathways to exert anti-liver fibrosis effects. M. quintuplinervia extract(MQE) could significantly down-regulate PI3 K and AKT protein levels in the HSC-T6 cell model induced by TGF-β1, suggesting that MQE may have the ability to regulate the PI3 K/AKT signaling pathway. The findings of this study indicated that the anti-liver fibrosis effect of M. quintuplinervia had multi-constituent, multi-target, and multi-pathway characteristics, which may provide a scientific basis for the research on the pharmacodynamic materials, action mechanism, and quality markers of M. quintupli-nervia.

Preliminary Development and Verification of Divertor Module for CFETR System Safety Analysis Code

China Fusion Engineering Test Reactor (CFETR), the next-generation fusion device of China, is designed to bridge the gap between International Thermonuclear Experimental Reactor (ITER) and the commercial fusion power plant by solving the essential physical, engineering, and technical problems, including tritium self-sufficiency and high duty cycle of 0.3–0.5. Before the completion of the design and construction of CFETR, the thermal-hydraulic safety assessment is needed in order to ensure the safety of nuclear facilities and to get the national nuclear safety license. Up to now, there is no specialized code for the fusion reactor safety assessment. And the safety assessment work that had been done for the fusion device is completed by the system safety analysis code for pressurized water reactors, such as RELAP5, CHATHARE, and so on. For developing a simulation tool that can meet the safety assessment needs of the fusion reactor, some special models need to be established compared to the fission reactor. In this article, the development of a module for the divertor is presented. The thermal-hydraulic safety of the divertor with design basis accidents, and in-vessel loss of coolant (LOCA), is analyzed based on the developed code. Comparisons are performed to verify the reliability and feasibility of the developed code.

ER whorls triggered by GhCNX6 were discovered involved in drought stress on cotton

Drought stress is the main abiotic stress causing damage to cotton growth and severe yield loss. Under environmental stress conditions, the endoplasmic reticulum (ER) folding environment is disturbed, resulting in the accumulation of unfolded/misfolded proteins, causing ER stress and triggering the unfolded protein response (UPR). Analysis of drought RNA-sequencing data revealed a Gh_D09G2402.1 ( GhCNX ) gene involved in ER protein processing. Through the observation of the ultrastructure of the ER under drought stress in cotton, the characteristic structure of the endoplasmic reticulum whorl was found. Virus-induced gene silencing (VIGS) mediated GhCNX6 silenced cotton plants were found highly sensitive to drought stress. Arabidopsis thaliana plants overexpressing GhCNX6 showed stronger tolerance to drought stress, indicating that the GhCNX6 gene is involved in the action mechanism of cotton drought stress and enhances the tolerance to drought stress. Drought stress leads to ER stress response, and the resulting ER whorl and CNX gene play a role in the ER protein processing pathway, thereby regulating the mechanism of cotton response to drought stress. This study will help to further explore the mechanism of cotton drought resistance. • Endoplasmic reticulum whorls found in cotton under drought stress. • First preliminary verification of GhCNX6 positively responding to drought stress. • The regulatory mechanism of GhCNX6 and ER whorls under drought stress.

Identification of long non-coding RNA-microRNA-mRNA regulatory modules and their potential roles in drought stress response in wheat (Triticum aestivum L.)

Drought is one of the most severe abiotic stresses that influence wheat production across the globe. Understanding the molecular regulatory network of wheat in response to drought is of great importance in molecular breeding. Noncoding RNAs influence plant development and resistance to abiotic stresses by regulating gene expression. In this study, whole-transcriptome sequencing was performed on the seedlings of two wheat varieties with contrasting levels of drought tolerance under drought and control conditions to identify long noncoding RNAs (lncRNAs), micro RNAs (miRNAs), and mRNAs related to drought stress and explore the potential lncRNA-miRNA-mRNA regulatory modules in controlling wheat drought stress response. A total of 1515 differentially expressed lncRNAs (DELs), 209 differentially expressed miRNAs (DEMs), and 20462 differentially expressed genes (DEGs) were identified. Of the 20462 DEGs, 1025 were identified as potential wheat drought resistance-related DEGs. Based on the regulatory relationship and expression patterns of DELs, DEMs, and DEGs, 10 DEL-DEM-DEG regulatory modules related to wheat drought stress response were screened, and preliminary expression verification of two important candidate modules was performed. Our results revealed the possible roles of lncRNA-miRNA-mRNA modules in regulatory networks related to drought tolerance and provided useful information as valuable genomic resources in molecular breeding of wheat.

A test prototype of a novel flexible video laryngoscope and preliminary verification in a difficult airway management simulator

BackgroundTo verify a test prototype of a novel flexible video laryngoscope in a difficult airway management simulator and to compare the efficacy of the flexible video laryngoscope with that of a conventional video laryngoscope.MethodsFifteen clinical anesthesiologists performed endotracheal intubation with a flexible video laryngoscope and a conventional video laryngoscope in a difficult airway management simulator in the neutral position with intermediate and difficult mouth opening. The rate of intubation success, intubation time, and classification of glottic exposure were recorded. After endotracheal intubation, participants were asked to assess the difficulty of intubation of the two laryngoscopes.ResultsThe success rate of endotracheal intubation with flexible video laryngoscope was significantly higher than that with video laryngoscope in neutral positions with both intermediate (P = 0.025) and difficult (P = 0.005) mouth opening. The Cormack Lehane score of the flexible video laryngoscope was significantly lower than that of the video laryngoscope in the neutral position with intermediate mouth opening (P < 0.001) and difficult mouth opening (P < 0.001). There was no significant difference in intubation time in the neutral position with intermediate mouth opening (P = 0.460) or difficult mouth opening (P = 0.078). The difficulty score of endotracheal intubations with the flexible video laryngoscope was also significantly lower than that of the video laryngoscope in the neutral position with intermediate mouth opening (P = 0.001) and difficult mouth opening (P = 0.001).ConclusionsCompared with conventional video laryngoscopy, flexible video laryngoscopy can provide superior glottic exposure and improve the success rate of intubation in a difficult airway management simulator.

A system dynamics approach for dairy herd modeling considering fixed-term artificial insemination scenario

Objective: To design and develop a continuous simulation model based on System Dynamics to analyze reproductive parameters considering artificial insemination and reproductive policies aimed at sustainability in a dairy herd. Methodology: The procedure is classified into four stages: (I) Analysis of the behavior of the dairy herd and definition of the problem, (II) Description of processes and contextualization of a model, (III) Generation of the preliminary model, verification, validation and (IV) Analysis of results. Results: It was shown that using simulation tools it is possible to model the processes within the dairy herd. The effective detections of periods of heat constitute a determining factor in the application of policies of artificial insemination and in general in the sustainability of the herd. Therefore, using a reproductive biotechnology protocol, such as heat synchronization and fixed-term artificial insemination, are policies that mitigate the problems associated with reproductive problems. Conclusions: The use of system dynamics allowed us to have a holistic approach to the problem considering all the relevant variables to evaluate improvement policies. The model presented in the development of the research allowed evaluating different policies associated with animal management, meat exploitation in dry cows, and policies of continuous review on situations associated with the efficiency in the identification of cows in heat.

The diagnostic and prognostic value of pseudogene SIGLEC17P in lung adenocarcinoma and a preliminary functional study.

Among malignant tumors, lung adenocarcinoma (LUAD) is the leading cause of death worldwide. This study explored the diagnostic, prognostic value, and preliminary functional verification of sialic acid binding Ig like lectin 17, pseudogene (SIGLEC17P) in LUAD. Prognostic lncRNAsfor LUAD were identified by The Cancer Genome Atlasand quantitative real-time PCR (qRT-PCR) was used to detect the expression of SIGLEC17P in LUADand paracarcinoma tissues. Subsequently, lentiviral vectors were used to overexpress SIGLEC17P in A549 and H1299 cells. The effects of SIGLEC17P overexpression on the proliferation, migration, and invasiveness of LUADcells (A549 and H1299) were evaluated by Cell Counting Kit-8, wound healing, and transwell migration assays, respectively. Bioinformatics analyses were performed to reveal the potential pathways in which SIGLEC17P is involved in LUAD. qRT-PCRresults revealed low SIGLEC17P expression in LUADtissues and a significant association with the N stage, T stage, and tumor node metastasis stage. Furthermore, the receiver operating characteristiccurve demonstrated a reliable diagnostic value. The proliferation, migration, and invasion of LUADcells were inhibited by overexpression of SIGLEC17P. Bioinformatics analyses suggested that SIGLEC17P might exert antioncogenic effects in LUAD through the mir-20-3p/ADH1B or mir-4476-5p/DPYSL axis. In summary, our results revealed that SIGLEC17P acts as a prognostic biomarker, independent prognostic factor, and potential therapeutic target for patients with LUAD.

Identification and validation of an immunological microenvironment signature and prediction model for epstein-barr virus positive lymphoma: Implications for immunotherapy.

BackgroundEpstein-Barr virus (EBV) is considered a carcinogenic virus, which is associated with high risk for poor prognosis in lymphoma patients, and there has been especially no satisfying and effective treatment for EBV+ lymphoma. We aimed to identify the immunological microenvironment molecular signatures which lead to the poor prognosis of EBV+ lymphoma patients.MethodsDifferential genes were screened with microarray data from the GEO database (GSE38885, GSE34143 and GSE13996). The data of lymphoid neoplasm diffuse large B-cell lymphoma (DLBC) from the TCGA database and GSE4475 were used to identify the prognostic genes. The data of GSE38885, GSE34143, GSE132929, GSE58445 and GSE13996 were used to eluate the immune cell infiltration. Formalin-fixed, paraffin-embedded tissue was collected for Real Time Quantitative PCR from 30 clinical samples, including 15 EBV+ and 15 EBV- lymphoma patients.ResultsFour differential genes between EBV+ and EBV- lymphoma patients were screened out with the significance of the survival and prognosis of lymphoma, including CHIT1, SIGLEC15, PLA2G2D and TMEM163. Using CIBERSORT to evaluate immune cell infiltration, we found the infiltration level of macrophages was significantly different between EBV+ and EBV- groups and was closely related to different genes. Preliminary clinical specimen verification identified that the expression levels of CHIT1 and TMEM163 were different between EBV+ and EBV- groups.ConclusionsOur data suggest that differences in expression levels of CHIT1 and TMEM163 and macrophage infiltration levels may be important drivers of poor prognosis of EBV+ lymphoma patients. These hub genes may provide new insights into the prognosis and therapeutic target for EBV+ lymphoma.