Astrocytic endothelin-1 overexpression impairs learning and memory ability in ischemic stroke via altered hippocampal neurogenesis and lipid metabolism

Vascular etiology is the second most prevalent cause of cognitive impairment globally.Endothelin-1,which is produced and secreted by endothelial cells and astrocytes,is implicated in the pathogenesis of stroke.However,the way in which changes in astrocytic endothelin-1 lead to poststroke cognitive deficits following transient middle cerebral artery occlusion is not well understood.Here,using mice in which astrocytic endothelin-1 was overexpressed,we found that the selective overexpression of endothelin-1 by astrocytic cells led to ischemic stroke-related dementia(1 hour of ischemia;7 days,28 days,or 3 months of reperfusion).We also revealed that astrocytic endothelin-1 overexpression contributed to the role of neural stem cell proliferation but impaired neurogenesis in the dentate gyrus of the hippocampus after middle cerebral artery occlusion.Comprehensive proteome profiles and western blot analysis confirmed that levels of glial fibrillary acidic protein and peroxiredoxin 6,which were differentially expressed in the brain,were significantly increased in mice with astrocytic endothelin-1 overexpression in comparison with wild-type mice 28 days after ischemic stroke.Moreover,the levels of the enriched differentially expressed proteins were closely related to lipid metabolism,as indicated by Kyoto Encyclopedia of Genes and Genomes pathway analysis.Liquid chromatography-mass spectrometry nontargeted metabolite profiling of brain tissues showed that astrocytic endothelin-1 overexpression altered lipid metabolism products such as glycerol phosphatidylcholine,sphingomyelin,and phosphatidic acid.Overall,this study demonstrates that astrocytic endothelin-1 overexpression can impair hippocampal neurogenesis and that it is correlated with lipid metabolism in poststroke cognitive dysfunction.

Decoding Retinoblastoma: Differential Gene Expression

Background: Retinoblastoma, the most common intraocular pediatric cancer, presents complexities in its genetic landscape that necessitate a deeper understanding for improved therapeutic interventions. This study leverages computational tools to dissect the differential gene expression profiles in retinoblastoma. Methods: Employing an in silico approach, we analyzed gene expression data from public repositories by applying rigorous statistical models, including limma and de seq 2, for identifying differentially expressed genes DEGs. Our findings were validated through cross-referencing with independent datasets and existing literature. We further employed functional annotation and pathway analysis to elucidate the biological significance of these DEGs. Results: Our computational analysis confirmed the dysregulation of key retinoblastoma-associated genes. In comparison to normal retinal tissue, RB1 exhibited a 2.5-fold increase in expression (adjusted p Conclusions: Our analysis reinforces the critical genetic alterations known in retinoblastoma and unveils new avenues for research into the disease’s molecular basis. The discovery of chemoresistance markers and immune-related genes opens potential pathways for personalized treatment strategies. The study’s outcomes emphasize the power of in silico analyses in unraveling complex cancer genomics.

Effects of pyraclostrobin on growth,oxidative stress,and gene expression in relation to stress and ATP-binding cassette transporters in Tetrahymena thermophila

Pyraclostrobin(PYR),a widely used fungicide,has negative effects on fish and algae,but its toxicity in protozoa remains unclear.In this study,the effects of PYR on the growth,oxidative stress,and gene expression related to stress and ATP-binding cassette(ABC)transporters in Tetrahymena thermophila were investigated.The result showed that the 96-h IC_(50)of PYR against T.thermophila was 17.2 mg/L.Moreover,PYR inhibited the growth of T.thermophila in concentration-or time-dependent manner.A morphological study revealed that the shape and size of T.thermophila changed,and damage of cell membrane surface was observed by scanning electron microscopy after 96 h of PYR exposure.The activities of superoxide dismutase(SOD)and catalase(CAT)increased throughout the experiment.In contrast,the glutathione(GSH)content was increased at 24 h and 48 h of exposure and decreased at 96 h.Moreover,a significant increase in malondialdehyde(MDA)level was observed in T.thermophila after96 h of exposure.Furthermore,PYR upregulated the HSP703,HSP705,GPx2,and ABAC15 gene expression in the 0.1–5-mg/L groups and downregulated the HSP704,HSP90,TGR,and ABCC52 mRNA levels at 96 h of exposure.These results suggest that PYR may exert adverse effects on T.thermophila by inducing oxidative stress and changing the gene expression related to ABC transporters and stress,which may enrich the understanding of the toxicity mechanism of PYR in aquatic organisms and provide reference data for aquatic ecological risk assessments.

Genome-wide identification and expression profiling of photosystem II(PsbX)gene family in upland cotton(Gossypium hirsutum L.)

Background Photosystem II(PSII)constitutes an intricate assembly of protein pigments,featuring extrinsic and intrinsic polypeptides within the photosynthetic membrane.The low-molecular-weight transmembrane protein PsbX has been identified in PSII,which is associated with the oxygen-evolving complex.The expression of PsbX gene protein is regulated by light.PsbX’s central role involves the regulation of PSII,facilitating the binding of quinone molecules to the Qb(PsbA)site,and it additionally plays a crucial role in optimizing the efficiency of photosynthesis.Despite these insights,a comprehensive understanding of the PsbX gene’s functions has remained elusive.Results In this study,we identified ten PsbX genes in Gossypium hirsutum L.The phylogenetic analysis results showed that 40 genes from nine species were classified into one clade.The resulting sequence logos exhibited substantial conservation across the N and C terminals at multiple sites among all Gossypium species.Furthermore,the ortholo-gous/paralogous,Ka/Ks ratio revealed that cotton PsbX genes subjected to positive as well as purifying selection pressure might lead to limited divergence,which resulted in the whole genome and segmental duplication.The expression patterns of GhPsbX genes exhibited variations across specific tissues,as indicated by the analysis.Moreover,the expression of GhPsbX genes could potentially be regulated in response to salt,intense light,and drought stresses.Therefore,GhPsbX genes may play a significant role in the modulation of photosynthesis under adverse abiotic conditions.Conclusion We examined the structure and function of PsbX gene family very first by using comparative genom-ics and systems biology approaches in cotton.It seems that PsbX gene family plays a vital role during the growth and development of cotton under stress conditions.Collectively,the results of this study provide basic information to unveil the molecular and physiological function of PsbX genes of cotton plants.

Expression Recognition Method Based on Convolutional Neural Network and Capsule Neural Network

Convolutional neural networks struggle to accurately handle changes in angles and twists in the direction of images,which affects their ability to recognize patterns based on internal feature levels. In contrast, CapsNet overcomesthese limitations by vectorizing information through increased directionality and magnitude, ensuring that spatialinformation is not overlooked. Therefore, this study proposes a novel expression recognition technique calledCAPSULE-VGG, which combines the strengths of CapsNet and convolutional neural networks. By refining andintegrating features extracted by a convolutional neural network before introducing theminto CapsNet, ourmodelenhances facial recognition capabilities. Compared to traditional neural network models, our approach offersfaster training pace, improved convergence speed, and higher accuracy rates approaching stability. Experimentalresults demonstrate that our method achieves recognition rates of 74.14% for the FER2013 expression dataset and99.85% for the CK+ expression dataset. By contrasting these findings with those obtained using conventionalexpression recognition techniques and incorporating CapsNet’s advantages, we effectively address issues associatedwith convolutional neural networks while increasing expression identification accuracy.

E2E-MFERC:AMulti-Face Expression Recognition Model for Group Emotion Assessment

In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assessstudents’ group emotions can provide educators with more comprehensive and intuitive classroom effect analysis,thereby continuouslypromotingthe improvementof teaching quality.However,most existingmulti-face expressionrecognition methods adopt a multi-stage approach, with an overall complex process, poor real-time performance,and insufficient generalization ability. In addition, the existing facial expression datasets are mostly single faceimages, which are of low quality and lack specificity, also restricting the development of this research. This paperaims to propose an end-to-end high-performance multi-face expression recognition algorithm model suitable forsmart classrooms, construct a high-quality multi-face expression dataset to support algorithm research, and applythe model to group emotion assessment to expand its application value. To this end, we propose an end-to-endmulti-face expression recognition algorithm model for smart classrooms (E2E-MFERC). In order to provide highqualityand highly targeted data support for model research, we constructed a multi-face expression dataset inreal classrooms (MFED), containing 2,385 images and a total of 18,712 expression labels, collected from smartclassrooms. In constructing E2E-MFERC, by introducing Re-parameterization visual geometry group (RepVGG)block and symmetric positive definite convolution (SPD-Conv) modules to enhance representational capability;combined with the cross stage partial network fusion module optimized by attention mechanism (C2f_Attention),it strengthens the ability to extract key information;adopts asymptotic feature pyramid network (AFPN) featurefusion tailored to classroomscenes and optimizes the head prediction output size;achieves high-performance endto-end multi-face expression detection. Finally, we apply the model to smart classroom group emotion assessmentand provide design references for classroom effect analysis evaluation metrics. Experiments based on MFED showthat the mAP and F1-score of E2E-MFERC on classroom evaluation data reach 83.6% and 0.77, respectively,improving the mAP of same-scale You Only Look Once version 5 (YOLOv5) and You Only Look Once version8 (YOLOv8) by 6.8% and 2.5%, respectively, and the F1-score by 0.06 and 0.04, respectively. E2E-MFERC modelhas obvious advantages in both detection speed and accuracy, which can meet the practical needs of real-timemulti-face expression analysis in classrooms, and serve the application of teaching effect assessment very well.

A Novel Deep Learning-Based Model for Classification of Wheat Gene Expression

Deep learning(DL)plays a critical role in processing and converting data into knowledge and decisions.DL technologies have been applied in a variety of applications,including image,video,and genome sequence analysis.In deep learning the most widely utilized architecture is Convolutional Neural Networks(CNN)are taught discriminatory traits in a supervised environment.In comparison to other classic neural networks,CNN makes use of a limited number of artificial neurons,therefore it is ideal for the recognition and processing of wheat gene sequences.Wheat is an essential crop of cereals for people around the world.Wheat Genotypes identification has an impact on the possible development of many countries in the agricultural sector.In quantitative genetics prediction of genetic values is a central issue.Wheat is an allohexaploid(AABBDD)with three distinct genomes.The sizes of the wheat genome are quite large compared to many other kinds and the availability of a diversity of genetic knowledge and normal structure at breeding lines of wheat,Therefore,genome sequence approaches based on techniques of Artificial Intelligence(AI)are necessary.This paper focuses on using the Wheat genome sequence will assist wheat producers in making better use of their genetic resources and managing genetic variation in their breeding program,as well as propose a novel model based on deep learning for offering a fundamental overview of genomic prediction theory and current constraints.In this paper,the hyperparameters of the network are optimized in the CNN to decrease the requirement for manual search and enhance network performance using a new proposed model built on an optimization algorithm and Convolutional Neural Networks(CNN).

Expression of cyclin-dependent kinase 9 is positively correlated with the autophagy level in colon cancer

BACKGROUND Cyclin-dependent kinase 9(CDK9)expression and autophagy in colorectal cancer(CRC)tissues has not been widely studied.CDK9,a key regulator of transcription,may influence the occurrence and progression of CRC.The expression of auto-phagy-related genes BECN1 and drug resistance factor ABCG2 may also play a role in CRC.Under normal physiological conditions,autophagy can inhibit tumorigenesis,but once a tumor forms,autophagy may promote tumor growth.Therefore,understanding the relationship between autophagy and cancer,partic-ularly how autophagy promotes tumor growth after its formation,is a key motivation for this research.AIM To investigate the relationship between CDK9 expression and autophagy in CRC,assess differences in autophagy between left and right colon cancer,and analyze the associations of autophagy-related genes with clinical features and prognosis.METHODS We collected tumor tissues and paracarcinoma tissues from colon cancer patients with liver metastasis to observe the level of autophagy in tissues with high levels of CDK9 and low levels of CDK9.We also collected primary tissue from left and right colon cancer patients with liver metastasis to compare the autophagy levels and the expression of BECN1 and ABCG2 in the tumor and paracarcinoma tissues.RESULTS The incidence of autophagy and the expression of BECN1 and ABCG2 were different in left and right colon cancer,and autophagy might be involved in the occurrence of chemotherapy resistance.Further analysis of the rela-tionship between the expression of autophagy-related genes CDK9,ABCG2,and BECN1 and the clinical features and prognosis of colorectal cancer showed that the high expression of CDK9 indicated a poor prognosis in colorectal cancer.CONCLUSION This study laid the foundation for further research on the combination of CDK9 inhibitors and autophagy inhibitors in the treatment of patients with CRC.

The Influence of Aerial Exposure on Sea Anemones Aulactinia veratra Mucin Genes Expression Using the RNA Sequencing

Mucin genes are the main component of mucus. The sea anemone species, Aulactinia veratra (Phylum Cnidaria) contains different types of mucin genes. In the intertidal zone, A. veratra is found to be exposed to air during the low tide and produces large quantities of mucus as an external covering. The relation between low tide and mucus secretion is still unclear, and what is the role of mucin during arial exposure is not yet investigated. This study hypothesised that the mucin genes in A. veratra would have significantly high expression in response to aerial exposure. Therefore, the aim of current study was to examine and analyses the response of A. veratra mucins in response to an experiment involving three hours of aerial exposure. To achieve this, aim the RNA-sequencing and bioinformatics analyses were used to examine the expression profile of A. veratra mucin genes in response to aerial exposure. The generated results have shown that, Mucin4-like and mucin5B-like were up-regulated in response to the three hours of aerial exposure in A. veratra. This finding shows a significant role of mucin5B-like and mucin4-like genes in response to air stress at low tide. The data generated from this study could be used in conjunction with future mucin gene studies of sea anemones and other cnidarians to compare A. veratra mucin gene expression results across time, and to extend our understanding of mucin stress response in this phylum.

High patatin like phospholipase domain containing 8 expression as a biomarker for poor prognosis of colorectal cancer

BACKGROUND Patatin like phospholipase domain containing 8(PNPLA8)has been shown to play a significant role in various cancer entities.Previous studies have focused on its roles as an antioxidant and in lipid peroxidation.However,the role of PNPLA8 in colorectal cancer(CRC)progression is unclear.AIM To explore the prognostic effects of PNPLA8 expression in CRC.METHODS A retrospective cohort containing 751 consecutive CRC patients was enrolled.PNPLA8 expression in tumor samples was evaluated by immunohistochemistry staining and semi-quantitated with immunoreactive scores.CRC patients were divided into high and low PNPLA8 expression groups based on the cut-off va-lues,which were calculated by X-tile software.The prognostic value of PNPLA8 was identified using univariate and multivariate Cox regression analysis.The over-all survival(OS)rates of CRC patients in the study cohort were compared with Kaplan-Meier analysis and Log-rank test.RESULTS PNPLA8 expression was significantly associated with distant metastases in our cohort(P=0.048).CRC patients with high PNPLA8 expression indicated poor OS(median OS=35.3,P=0.005).CRC patients with a higher PNPLA8 expression at either stage I and II or stage III and IV had statistically significant shorter OS.For patients with left-sided colon and rectal cancer,the survival curves of two PN-PLA8-expression groups showed statistically significant differences.Multivariate analysis also confirmed that high PNPLA8 expression was an independent prog-nostic factor for overall survival(hazard ratio HR=1.328,95%CI:1.016-1.734,P=0.038).

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway

BACKGROUND The ubiquitin-proteasome pathway(UPP)has been proven to play important roles in cancer.AIM To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes.METHODS In this study,UPP-related E1,E2,E3,deubiquitylating enzyme,and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes(KEGG)database,aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based RESULTS Five genes(including autophagy related 10,proteasome 20S subunit alpha 8,proteasome 20S subunit beta 2,ubiquitin specific peptidase 17 like family member 2,and ubiquitin specific peptidase 8)were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer.Among training,validation,and Gene Expression Omnibus sets,the overall survival differed significantly between the high-risk and low-risk groups.The expression of the five genes was significantly associated with immunocyte infiltration,tumor stage,and postoperative recurrence.A total of 111 differentially expressed genes(DEGs)were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways.Cell division cycle 20,Kelch repeat and BTB domain containing 11,and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival.CONCLUSION We have constructed a prognosis predictive model in patients with liver cancer,which contains five genes that associate with immunocyte infiltration,tumor stage,and postoperative recurrence.

Influence of Angiotensin II on α1-Adrenergic Receptors Function in Rat Aorta and Expression in Vascular Smooth Muscle Cells

Angiotensin II (Ang II) is the main mediator of the Renin-Angiotensin-System acting on AT1 and other AT receptors. It is regarded as a pleiotropic agent that induces many actions, including functioning as a growth factor, and as a contractile hormone, among others. The aim of this work was to examine the impact of Ang II on the expression and function of α1-adrenergic receptors (α1-ARs) in cultured rat aorta, and aorta-derived smooth muscle cells. Isolated Wistar rat aorta was incubated for 24 h in DMEM at 37˚C, then subjected to isometric tension and to the action of added norepinephrine, in concentration-response curves. Ang II was added (1 × 10−5 M), and in some experiments, 5-Methylurapidil (α1A-AR antagonist), AH11110A (α1B-AR antagonist), or BMY-7378 (α1D-AR antagonist), were used to identify the α1-AR involved in the response. Desensitization of the contractile response to norepinephrine was observed due to incubation time, and by the Ang II action. α1D-AR was protected from desensitization by BMY-7378;while RS-100329 and prazosin partially mitigated desensitization. In another set of experiments, isolated aorta-derived smooth muscle cells were exposed to Ang II and α1-ARs proteins were evaluated. α1D-AR increased at 30 and 60 min post Ang II exposure, the α1A-AR diminished from 1 to 4 h, while α1B-AR remained unchanged over 24 h of Ang II exposure. Ang II induced an increase of α1D-AR at short times, and BMY-7378 protected α1D-AR from desensitization.

Color Expression and Mood Creation in Imagery Oil Painting

Oil painting is a traditional Western painting form.With the introduction of China and the influence of China’s traditional painting and aesthetics,the painting style became more distinctive,expanding a new development direction of oil painting,and thus imagery oil painting came into being.Color,as the most important element in imagery oil painting,mainly plays the role of mood creation and emotional expression.Many creators are good at injecting their thoughts and emotions into the paintings through color matching,so as to enhance the artistic expression of the paintings.This paper analyzes the color expression characteristics of imagery oil painting and explores the color expression techniques in imagery oil painting and mood creation of imagery oil painting from several aspects.

Identification,evolution,expression and protein interaction analysis of genes encoding B-box zinc-finger proteins in maize

The B-box(BBX)family of proteins consists of zinc-finger transcription factors with one or two highly conserved B-box motifs at their N-termini.BBX proteins play crucial roles in various aspects of plant growth and development,including seedling photomorphogenesis,shade avoidance,flowering time,and biotic and abiotic stress responses.Previous studies have identified many different BBXs from several plant species,although the BBX family members in maize are largely unknown.Genome-wide identification and comprehensive analysis of maize BBX(ZmBBX)expression and interaction networks would therefore provide valuable information for understanding their functions.In this study,36 maize BBXs in three major clades were identified.The ZmBBXs within a given clade were found to share similar domains,motifs,and genomic structures.Gene duplication analyses revealed that the expansion of BBX proteins in maize has mainly occurred by segmental duplication.The expression levels of ZmBBXs were analyzed in various organs and tissues,and under different abiotic stress conditions.Protein–protein interaction networks of ZmBBXs were established using bioinformatic tools and verified by bimolecular fluorescence complementation(BiFC)assays.Our findings can facilitate a greater understanding of the complexity of the ZmBBX family and provide novel clues for unravelling ZmBBX protein functions.

Probing the processing of facial expressions in monkeys via time perception and eye tracking

Accurately recognizing facial expressions is essential for effective social interactions.Non-human primates(NHPs)are widely used in the study of the neural mechanisms underpinning facial expression processing,yet it remains unclear how well monkeys can recognize the facial expressions of other species such as humans.In this study,we systematically investigated how monkeys process the facial expressions of conspecifics and humans using eye-tracking technology and sophisticated behavioral tasks,namely the temporal discrimination task(TDT)and face scan task(FST).We found that monkeys showed prolonged subjective time perception in response to Negative facial expressions in monkeys while showing longer reaction time to Negative facial expressions in humans.Monkey faces also reliably induced divergent pupil contraction in response to different expressions,while human faces and scrambled monkey faces did not.Furthermore,viewing patterns in the FST indicated that monkeys only showed bias toward emotional expressions upon observing monkey faces.Finally,masking the eye region marginally decreased the viewing duration for monkey faces but not for human faces.By probing facial expression processing in monkeys,our study demonstrates that monkeys are more sensitive to the facial expressions of conspecifics than those of humans,thus shedding new light on inter-species communication through facial expressions between NHPs and humans.

Metabolomics and gene expression levels reveal the positive effects of teaseed oil on lifespan and aging process in Caenorhabditis elegans

As an irreplaceable dietary constituent,lipids play a vital important role in health,but their effects on aging process and longevity are still not well known yet.In this paper,the metabolic profiling and gene expression levels of Caenorhabditis elegans were investigated to explore the effects of different edible oils on senescence and lifespan.The results showed that teaseed oil(TO)could prolong the life expectancy and slow down the aging process of C.elegans.Compared to the control group,the intake of lard oil(LO)and TO increased the expression levels of genes related to inhibition of protein aggregation(akt-1,daf-16,hsf-1,hsp-16.2)and lipid metabolism(daf-7,daf-1,mdt-15,lipl-4,fat-5,fat-6,fat-7),with a more significant alteration in TO group.Metabolomics revealed that palm oil can upregulated plenty of fatty acids(palmitic acid,stearic acid,tetracosanoic acid),together with some amino acids(tryptophan,L-aspartate,L-valine)and carbohydrate(D-glucose),while the trend was opposite in TO group.Besides,moderate-to-strong correlations were found between differential metabolites and changed genes.In general,this paper claimed that TO could prolong lifespan and slow down aging process via regulating the lipids,amino acids and carbohydrates metabolism.

Genome-wide identification of TPS genes in sesame and analysis of their expression in response to abiotic stresses

Trehalose and its precursor,trehalose-6-phosphate,play critical roles in plant metabolism and response to abiotic stresses.Trehalose-6-phosphate synthase(TPS)is a key enzyme in the trehalose synthesis pathway.Hence this study identified TPS genes in sesame(SiTPSs)and examined their expression patterns under various abiotic stresses.Totally,ten SiTPSs were identified and comprehensively characterized.SiTPSs were found to be unevenly distributed on five out of 13 sesame chromosomes and were predicted to be localized in chloroplasts and vacuoles of cells.Phylogenetic analysis classified SiTPS proteins into two groups(I and II),which was supported by gene structure and conserved motif analyses.Analysis of cis-acting elements in promoter regions of SiTPSs revealed that they might primarily involve developmental and environmental responses.SiTPSs exhibited different expression patterns in different tissues and under different abiotic stresses.Most group II SiTPS genes(SiTPS4-SiTPS10)were strongly induced by drought,salt,waterlogging,and osmotic stress.Particularly,SiTPS10 was the most significantly up-regulated under various abiotic stresses,indicating it is a candidate gene for improving sesame tolerance to multiple abiotic stresses.Our results provide insight into the TPS gene family in sesame and fundamental resources for genomics studies towards dissecting SiTPS genes’functions.

Robust identification of regulatory variants(eQTLs)using a differential expression framework developed for RNA‑sequencing

Background A gap currently exists between genetic variants and the underlying cell and tissue biology of a trait,and expression quantitative trait loci(eQTL)studies provide important information to help close that gap.However,two concerns that arise with eQTL analyses using RNA-sequencing data are normalization of data across samples and the data not following a normal distribution.Multiple pipelines have been suggested to address this.For instance,the most recent analysis of the human and farm Genotype-Tissue Expression(GTEx)project proposes using trimmed means of M-values(TMM)to normalize the data followed by an inverse normal transformation.Results In this study,we reasoned that eQTL analysis could be carried out using the same framework used for dif-ferential gene expression(DGE),which uses a negative binomial model,a statistical test feasible for count data.Using the GTEx framework,we identified 35 significant eQTLs(P<5×10^(–8))following the ANOVA model and 39 significant eQTLs(P<5×10^(–8))following the additive model.Using a differential gene expression framework,we identified 930 and six significant eQTLs(P<5×10^(–8))following an analytical framework equivalent to the ANOVA and additive model,respectively.When we compared the two approaches,there was no overlap of significant eQTLs between the two frameworks.Because we defined specific contrasts,we identified trans eQTLs that more closely resembled what we expect from genetic variants showing complete dominance between alleles.Yet,these were not identified by the GTEx framework.Conclusions Our results show that transforming RNA-sequencing data to fit a normal distribution prior to eQTL analysis is not required when the DGE framework is employed.Our proposed approach detected biologically relevant variants that otherwise would not have been identified due to data transformation to fit a normal distribution.

Role of FOXP3 in Immunohistochemical Expression in Preeclampsia

Background: FoxP3 gene variants have been linked to endometriosis, infertility, and autoimmune illnesses, according to numerous researches. Maternal sensitivity to the PE gene and the genetic variations of FoxP3 has not been thoroughly investigated. Objective: Investigation of the immune-histochemical expression of FoxP3 in placental tissue of PE patients. Methods: A total of 26 pre-eclamptic women as a case and 26 ethnically matched healthy pregnant women as a control group aged between 18 and 40 years old of different gravidity and parity referred to the labor ward for delivery either by vaginal delivery or cesarean section was enrolled to investigate the immunohistochemical expression of FOXP3 in placental tissue of PE patients. Results: Lower expression of FOXP3 IHC was statistically significant and noted in the group of preeclampsia compared to the healthy control group. Lower gestational age at delivery and a higher percentage of cesarean section were statistically significant and noted in the group of preeclampsia compared to the healthy control group. Conclusion: In comparison to the healthy control group, preeclampsia patients had statistically significantly lower FOXP3 IHC expression, and FOXP3 polymorphism was associated with the development of PE. Our findings can serve as a guide for statistical analyses and functional investigations that are more in-depth.

MdAIL5 overexpression promotes apple adventitious shoot regeneration by regulating hormone signaling and activating the expression of shoot development-related genes

Adventitious shoot(AS)regeneration is a significant factor in the genetic transformation of horticultural plants.It is also a noteworthy approach to their vegetative propagation.AS regeneration remains highly dependent on the genotype or maturity of explants.We here found that the AS regeneration abilities of apple leaves were positively correlated with MdAIL5 expression.MdAIL5 overexpression dramatically increased AS regeneration efficiency.Notably,MdAIL5 overexpression could restore the AS formation ability of explants to a certain extent,which was lost with an increase in maturity.Endogenous hormone detection revealed that MdAIL5 overexpression changed the contents of auxin,cytokinin(CK),and other hormones in apple leaves.Transcriptome analysis revealed that many genes related to auxin,CK,and brassinolide signaling pathways were significantly and differentially expressed between MdAIL5-overexpressing transgenic apple and wild-type apple plants.Yeast one-hybrid assays,the electrophoretic mobility shift assay,and the dual-luciferase reporter assay revealed that MdAIL5 directly binds to MdARF9 and MdHB14 promoters and positively affects their expression.We here established a model of MdAIL5 regulating AS formation,which acts as a theoretical basis for facilitating genotype-or explant maturity-independent AS regeneration in the future.