GSDME-mediated keratinocyte pyroptosis participates in the pathogenesis of psoriasis by promoting skin inflammation.

OBJECTIVE: Psoriasis is a common, chronic inflammatory disease with unclear etiology. Keratinocytes in psoriasis are susceptible to exogenous triggers that induce inflammatory cell death. This study investigated whether GSDME-mediated pyroptosis in keratinocytes contributes to the pathogenesis of psoriasis. METHODS: Skin samples from patients with psoriasis and healthy controls were collected to evaluate the expression of GSDME, cleaved-caspase-3, and inflammatory factors. We then analyzed the data series, GSE41662, to further compare the expression of GSDME between lesional and non-lesional skin samples in those with psoriasis. In vivo, caspase-3 inhibitor and GSDME deficiency mice (Gsdme-/-) were applied to block caspase-3/GSDME activation in the imiquimod-induced psoriasis model. Skin inflammation, disease severity, and pyroptosis-related proteins were analyzed. In vitro, tumor necrosis factor-α (TNF-α)-induced caspase-3/GSDME-mediated pyroptosis in the HACAT cell line was explored. RESULTS: Our analysis of the GSE41662 data series found that GSDME were upregulated in psoriasis lesions, compared to normal skin. High levels of inflammatory cytokines such as IL-1ß, IL-6, and TNF-α were also found in psoriasis lesions. In mice of Gsdme-/- and caspase-3 inhibitor groups, the severity of skin inflammation was attenuated, and GSDME and C-caspase-3 levels decreased after imiquimod treatment. Similarly, IL-1ß, IL-6, and TNF-α were decreased in Gsdme-/- and caspase-3 inhibitor groups. In vitro, TNF-α induced HACAT cell pyroptosis through caspase-3/GSDME pathway activation, which was suppressed by blocking caspase-3 or silencing GSDME. CONCLUSION: Our study provides a novel explanation that TNF-α/caspase-3/GSDME-mediated keratinocyte pyroptosis is highly responsible for the initiation and acceleration of skin inflammation and progression of psoriasis.

Nuclear and mitochondrial genomes of Polylopha cassiicola: the first assembly in Chlidanotinae (Tortricidae).

Tortricidae is one of the largest families in Lepidoptera, including subfamilies of Tortricinae, Olethreutinae, and Chlidanotinae. Here, we assembled the gap-free genome for the subfamily Chlidanotinae using Illumina, Nanopore, and Hi-C sequencing from Polylopha cassiicola, a pest of camphor trees in southern China. The nuclear genome is 302.03 Mb in size, with 36.82% of repeats and 98.4% of BUCSO completeness. The karyotype is 2n = 44 for males. We identified 15412 protein-coding genes, 1052 tRNAs, and 67 rRNAs. We also determined the mitochondrial genome of this species and annotated 13 protein-coding genes, 22 tRNAs, and one rRNA. These high-quality genomes provide valuable information for studying phylogeny, karyotypic evolution, and adaptive evolution of tortricid moths.

A hybrid feature selection algorithm combining information gain and grouping particle swarm optimization for cancer diagnosis.

BACKGROUND: Cancer diagnosis based on machine learning has become a popular application direction. Support vector machine (SVM), as a classical machine learning algorithm, has been widely used in cancer diagnosis because of its advantages in high-dimensional and small sample data. However, due to the high-dimensional feature space and high feature redundancy of gene expression data, SVM faces the problem of poor classification effect when dealing with such data. METHODS: Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). The algorithm firstly calculates the information gain values of the features and ranks them in descending order according to the value. Then, ranked features are grouped according to the information index, so that the features in the group are close, and the features outside the group are sparse. Finally, grouped features are searched using grouping PSO and evaluated according to in-group and out-group. RESULTS: Experimental results show that the average accuracy (ACC) of the SVM on the feature subset selected by the IG-GPSO is 98.50%, which is significantly better than the traditional feature selection algorithm. Compared with KNN, the classification effect of the feature subset selected by the IG-GPSO is still optimal. In addition, the results of multiple comparison tests show that the feature selection effect of the IG-GPSO is significantly better than that of traditional feature selection algorithms. CONCLUSION: The feature subset selected by IG-GPSO not only has the best classification effect, but also has the least feature scale (FS). More importantly, the IG-GPSO significantly improves the ACC of SVM in cancer diagnostic.

Rapid and Repeated Climate Adaptation Involving Chromosome Inversions following Invasion of an Insect.

Following invasion, insects can become adapted to conditions experienced in their invasive range, but there are few studies on the speed of adaptation and its genomic basis. Here, we examine a small insect pest, Thrips palmi, following its contemporary range expansion across a sharp climate gradient from the subtropics to temperate areas. We first found a geographically associated population genetic structure and inferred a stepping-stone dispersal pattern in this pest from the open fields of southern China to greenhouse environments of northern regions, with limited gene flow after colonization. In common garden experiments, both the field and greenhouse groups exhibited clinal patterns in thermal tolerance as measured by critical thermal maximum (CTmax) closely linked with latitude and temperature variables. A selection experiment reinforced the evolutionary potential of CTmax with an estimated h2 of 6.8% for the trait. We identified 3 inversions in the genome that were closely associated with CTmax, accounting for 49.9%, 19.6%, and 8.6% of the variance in CTmax among populations. Other genomic variations in CTmax outside the inversion region were specific to certain populations but functionally conserved. These findings highlight rapid adaptation to CTmax in both open field and greenhouse populations and reiterate the importance of inversions behaving as large-effect alleles in climate adaptation.

Energy Gap of the Even-Denominator Fractional Quantum Hall State in Bilayer Graphene.

Bernal bilayer graphene hosts even-denominator fractional quantum Hall states thought to be described by a Pfaffian wave function with non-Abelian quasiparticle excitations. Here, we report the quantitative determination of fractional quantum Hall energy gaps in bilayer graphene using both thermally activated transport and by direct measurement of the chemical potential. We find a transport activation gap of 5.1 K at B=12 T for a half filled N=1 Landau level, consistent with density matrix renormalization group calculations for the Pfaffian state. However, the measured thermodynamic gap of 11.6 K is smaller than theoretical expectations for the clean limit by approximately a factor of 2. We analyze the chemical potential data near fractional filling within a simplified model of a Wigner crystal of fractional quasiparticles with long-wavelength disorder, explaining this discrepancy. Our results quantitatively establish bilayer graphene as a robust platform for probing the non-Abelian anyons expected to arise as the elementary excitations of the even-denominator state.

Chromosome-level genome assembly of the Japanese sawyer beetle Monochamus alternatus.

The Japanese sawyer beetle Monochamus alternatus (Coleoptera: Cerambycidae) is a pest in pine forests and acts as a vector for the pine wood nematode Bursaphelenchus xylophilus, which causes the pine wilt disease. We assembled a high-quality genome of M. alternatus at the chromosomal level using Illumina, Nanopore, and Hi-C sequencing technologies. The assembled genome is 767.12 Mb, with a scaffold N50 of 82.0 Mb. All contigs were assembled into ten pseudo-chromosomes. The genome contains 63.95% repeat sequences. We identify 16, 284 protein-coding genes in the genome, of which 11,244 were functionally annotated. The high-quality genome of M. alternatus provides an invaluable resource for the biological, ecological, and genetic study of this beetle and opens new avenues for understanding the transmission of pine wood nematode by insect vectors.

Berberine Metabolites Stimulate GLP-1 Secretion by Alleviating Oxidative Stress and Mitochondrial Dysfunction.

Berberine (BBR) is a principal component of Rhizoma coptidis known for its therapeutic potential in treating diseases such as type 2 diabetes mellitus (T2DM) and obesity. Despite the trace levels of BBR in plasma, it's believed that its metabolites play a pivotal role in its biological activities. While BBR is recognized to promote GLP-1 production in intestinal L cells, the cytoprotective effects of its metabolites on these cells are yet to be explored. The present study investigates the effects of BBR metabolites on GLP-1 secretion and the underlying mechanisms. Our results revealed that, out of six BBR metabolites, berberrubine (BBB) and palmatine (PMT) significantly increased the production and glucose-stimulated secretion of GLP-1 in GLUTag cells. Notably, both BBB and PMT could facilitate GLP-1 and insulin secretion and enhance glucose tolerance in standard mice. Moreover, a single dose of PMT could markedly increase plasma GLP-1 and improve glucose tolerance in mice with obesity induced by a high-fat diet. In palmitic acid or TNF[Formula: see text]-treated GLUTag cells, BBB and PMT alleviated cell death, oxidative stress, and mitochondrial dysfunction. Furthermore, they could effectively reverse inflammation-induced inhibition of the Akt signaling pathway. In general, these insights suggest that the beneficial effects of orally administered BBR on GLP-1 secretion are largely attributed to the pharmacological activity of BBB and PMT by their above cytoprotective effects on L cells, which provide important ideas for stimulating GLP-1 secretion and the treatment of T2DM.

Autoimmune congenital heart block: a case report and review of the literature related to pathogenesis and pregnancy management.

Autoimmune congenital heart block (ACHB) is a passively acquired immune-mediated disease characterized by the presence of maternal antibodies against components of the Ro/SSA and La/SSB ribonucleoprotein complex that mainly affects the cardiac conducting system. ACHB occurs in 2% of women with positive anti-Ro/SSA and anti-La/SSB antibodies and causes a high risk of intrauterine fetal death, neonatal mortality, and long-term sequelae. In this review, we first describe a case of ACHB to provide preliminary knowledge. Then, we discuss the possible pathogenic mechanisms of ACHB; summarize the pregnancy management of patients with positive anti-Ro/SSA and anti-La/SSB antibodies and/or rheumatic diseases, the prevention of ACHB, and the treatment of ACHB fetuses; and propose routine screening of these antibodies for the general population. Careful follow-up, which consists of monitoring the fetal heart rate, is feasible and reassuring for pregnant women with positive anti-Ro/SSA and/or anti-La/SSB antibodies to lower the risk of ACHB in fetuses. Moreover, maternal administration of hydroxychloroquine may be useful in preventing ACHB in pregnant women with anti-Ro/SSA and/or anti-La/SSB antibodies.

Cascade of Multielectron Bubble Phases in Monolayer Graphene at High Landau Level Filling.

The phase diagram of an interacting two-dimensional electron system in a high magnetic field is enriched by the varying form of the effective Coulomb interaction, which depends strongly on the Landau level index. While the fractional quantum Hall states that dominate in the lower-energy Landau levels have been explored experimentally in a variety of two-dimensional systems, much less work has been done to explore electron solids owing to their subtle transport signatures and extreme sensitivity to disorder. Here, we use chemical potential measurements to map the phase diagram of electron solid states in N=2, N=3, and N=4 Landau levels in monolayer graphene. Direct comparison between our data and theoretical calculations reveals a cascade of density-tuned phase transitions between electron bubble phases up to two, three, or four electrons per bubble in the N=2, 3, and 4 Landau levels, respectively. Finite-temperature measurements are consistent with melting of the solids for T≈1 K.

Testing for adaptive changes linked to range expansion following a single introduction of the fall webworm.

Adaptive evolution following colonization can affect the impact of invasive species. The fall webworm (FWW) invaded China 40 years ago through a single introduction event involving a severe bottleneck and subsequently diverged into two genetic groups. The well-recorded invasion history of FWW, coupled with a clear pattern of genetic divergence, provides an opportunity to investigate whether there is any sign of adaptive evolution following the invasion. Based on genome-wide SNPs, we identified genetically separated western and eastern groups of FWW and correlated spatial variation in SNPs with geographical and climatic factors. Geographical factors explained a similar proportion of the genetic variation across all populations compared with climatic factors. However, when the two population groups were analysed separately, environmental factors explained more variation than geographical factors. SNP outliers in populations of the western group had relatively stronger response to precipitation than temperature-related variables. Functional annotation of SNP outliers identified genes associated with insect cuticle protein potentially related to desiccation adaptation in the western group and genes associated with lipase biosynthesis potentially related to temperature adaptation in the eastern group. Our study suggests that invasive species may maintain the evolutionary potential to adapt to heterogeneous environments despite a single invasion event. The molecular data suggest that quantitative trait comparisons across environments would be worthwhile.

Cyclophosphamide induced intestinal injury is alleviated by blocking the TLR9/caspase3/GSDME mediated intestinal epithelium pyroptosis.

OBJECTIVES: Cyclophosphamide (CYC) was commonly used to treat autoimmune disorders, and it could also cause side effects such as intestinal damage. This study aimed to explore the mechanism of CYC-induced intestinal cytotoxicity and provide evidence for protecting from intestinal damage by blocking TLR9/caspase3/GSDME mediated pyroptosis. METHODS: Intestinal epithelial cells (IEC-6) were treated with 4-hydroxycyclophosphamide (4HC), a key active metabolite of CYC. The pyroptotic rate of IEC-6 cells was detected by Annexin V/PI-Flow cytometry, microscopy imaging, and PI staining. The expression and activation of TLR9, caspase3 and GSDME in IEC-6 cells were detected by western blot and immunofluorescence staining. In addition, hydroxychloroquine (HCQ) and ODN2088 were used to inhibit TLR9 to investigate the role of TLR9 on caspase3/GSDME-mediated pyroptosis. Finally, mice lacking Gsdme or TLR9 or pretreating with HCQ were injected intraperitoneally with CYC, and the incidence and severity of intestinal damage were assessed. RESULTS: CYC induced lytic cell death in IEC-6 cells and increased the expression of TLR9, activated caspase3, and GSDME-N. Besides, both ODN2088 and HCQ could inhibit CYC-induced pyroptosis in IEC-6 cells. In vivo, CYC-induced intestinal injury was characterized by a large amount of intestinal villi abscission and structural disordered. Gsdme or TLR9 deficiency, or pretreatment of HCQ effectively attenuated intestinal damage in CYC-induced model mice. CONCLUSIONS: These results indicate an alternative mechanism for CYC-induced intestinal damage, which actives TLR9/caspase3/GSDME signaling pathway, leading to pyroptosis of intestinal epithelial cells. And targeting pyroptosis might be a potential therapeutic approach for CYC-induced intestinal damage.

[Spatial-temporal Variation in Groundwater Quality and the Contamination Source Analysis in Shihezi-Changji Area].

To analyze spatial-temporal variation in groundwater quality and contamination sources in the Shihezi-Changji area in Xinjiang, a Bayesian water quality evaluation model based on Shannon entropy, Spearman rank correlation coefficient, principal component analysis, and an absolute principal component scores-multiple linear regression receptor model (APCS-MLR) were comprehensively used in this study. Groundwater samples in 23 in-situ wells were collected from 2016 to 2021 for quality analysis. The results showed that ① groundwater quality was generally good, with most samples having a phreatic water quality of Class Ⅰ and Class Ⅱ and most confined groundwater quality being of Class Ⅰ. ② Temporally, 2016 and 2017 were the key time nodes of water quality variation in phreatic water and confined groundwater, respectively. Class Ⅳ and Class Ⅴ groundwater was observed only before the key time nodes, whereas after those time nodes the groundwater quality fluctuated within Class Ⅰ to Class Ⅲ. ③ Spatially, the order of phreatic water quality in descending order was Shihezi City, Hutubi county, Manas county, and Changji City, whereas that of confined groundwater quality was:Shihezi City and Changji City, Hutubi county, and Manas county. ④ The spatial-temporal variations in groundwater quality and that in major related indices were basically similar and highly heterogeneous. ⑤ Phreatic water quality was mainly affected by leaching (67.30%), leaching-migration (10.89%), and agricultural-domestic pollution (9.44%); by contrast, unconfined groundwater quality was mainly affected by leaching-enrichment (52.08%), agricultural-domestic pollution (16.06%), and ion exchange under an alkaline environment (12.64%). Although groundwater quality was improved over the years, more attention should be paid to groundwater salinization in the 149 Regiment in northern Manas County.

Identification and Risk Assessment of Priority Control Organic Pollutants in Groundwater in the Junggar Basin in Xinjiang, P.R. China.

The Junggar Basin in Xinjiang is located in the hinterland of Eurasia, where the groundwater is a significant resource and has important ecological functions. The introduction of harmful organic pollutants into groundwater from increasing human activities and rapid socioeconomic development may lead to groundwater pollution at various levels. Therefore, to develop an effective regulatory framework, establishing a list of priority control organic pollutants (PCOPs) is in urgent need. In this study, a method of ranking the priority of pollutants based on their prevalence (Pv), occurrence (O) and persistent bioaccumulative toxicity (PBT) has been developed. PvOPBT in the environment was applied in the screening of PCOPs among 34 organic pollutants and the risk assessment of screened PCOPs in groundwater in the Junggar Basin. The results show that the PCOPs in groundwater were benzo[a]pyrene, 1,2-dichloroethane, trichloromethane and DDT. Among the pollutants, benzo[a]pyrene, 1,2-dichloroethane and DDT showed high potential ecological risk, whilst trichloromethane represented low potential ecological risk. With the exception of benzo[a]pyrene, which had high potential health risks, the other screened PCOPs had low potential health risks. Unlike the scatter distribution of groundwater benzo[a]pyrene, the 1,2-dichloroethane and trichloromethane in groundwater were mainly concentrated in the central part of the southern margin and the northern margin of the Junggar Basin, while the DDT in groundwater was only distributed in Jinghe County (in the southwest) and Beitun City (in the north). Industrial and agricultural activities were the main controlling factors that affected the distribution of PCOPs.

Genetic Diversity and Fine-Scale Genetic Structure of Spodoptera litura Fabricius (Lepidoptera: Noctuidae) in Southern China Based on Microsatellite Markers.

Population genetic structure is strongly affected by dispersal events, especially for migratory species. The investigation of population structure is therefore conducive to increasing our understanding of species dispersal. Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) is an important tobacco pest in China causing serious damage to multiple crops. In this study, we explore its dispersal dynamics by clarifying the fine-scale population genetics using 545 S. litura samples collected from tobacco plantations at 24 locations (mainly in Baise, Hechi, and Hezhou, Southern China). We analyzed the genetic diversity, genetic structure, and gene flow of these populations using seven microsatellite loci. Our results revealed high genetic diversity and low population genetic structure among S. litura. The genetic distance was uncorrelated with geographical distance, indicating the complete randomness of dispersal among the local populations. Our results suggest that the movement scope of contemporary S. litura might be much higher than the local-level spatial scale, which will provide a theoretical basis for pest management.

An ultra-high vacuum system for fabricating clean two-dimensional material devices.

High mobility electron gases confined at material interfaces have been a venue for major discoveries in condensed matter physics. Ultra-high vacuum (UHV) technologies played a key role in creating such high-quality interfaces. The advent of two-dimensional (2D) materials brought new opportunities to explore exotic physics in flat lands. UHV technologies may once again revolutionize research in low dimensions by facilitating the construction of ultra-clean interfaces with a wide variety of 2D materials. Here, we describe the design and operation of a UHV 2D material device fabrication system, in which the entire fabrication process is performed under pressure lower than 5 × 10-10 mbar. Specifically, the UHV system enables the exfoliation of atomically clean 2D materials. Subsequent in situ assembly of van der Waals heterostructures produces high-quality interfaces that are free of contamination. We demonstrate functionalities of this system through exemplary fabrication of various 2D materials and their heterostructures.

Three Novel Adenylate Cyclase Genes Show Significant Biological Functions in Plant.

Adenylate cyclase is the key enzyme solely synthesizing cAMP which participates in cell metabolism regulations and functions as an intracellular second messenger. However, the biological functions of plant ACs have not been elucidated clearly for their poor conservative sequences and low detectable cAMP. We performed a systematic study of plant ACs by using Chinese jujube, whose fruit exhibits the highest cAMP content among plants. Three novel ACs were identified from Chinese jujube, and two types of methods including in vitro and in vivo were used to certificate ZjAC1-3 which can catalyze the conversion of ATP into cAMP. The biological functions of significant accelerations of seed germination, root growth, and flowering were found via overexpression of these AC genes in Arabidopsis, and these functions of ACs were further demonstrated by treating the AC-overexpressing transgenic lines and wild type Arabidopsis with bithionol and dibutyryl-cAMP. At last, transcriptome data revealed that the underlying mechanism of the biological functions of ACs might be regulation of the key genes involved in the circadian rhythm pathway and the hormone signal transduction pathway. This research established a foundation for further investigating plant AC genes and provided strong evidence for cAMP serving as a signaling molecule in plants.

Removal of As(V) from aqueous solution using modified Fe3O4 nanoparticles.

The removal of arsenic contamination from the aqueous environment is of great importance in the conservation of the Earth's water resources, and surfactants are a promising material used to modify magnetic nanoparticles to improve adsorption properties. Therefore, it is important to develop efficient and selective adsorbents for arsenic. Surface modification of Fe3O4 was carried out using anionic, cationic and zwitterionic surfactants to obtain composite Fe3O4@SDS, Fe3O4@CTAB, Fe3O4@SNC 16 and Fe3O4@NPC 16 (collectively referred to as Fe3O4@surfactants). The synthesized composite Fe3O4@surfactants magnetic nanoparticles were characterized by XRD, TEM and FTIR. The As(V) removal characteristics of the composite magnetic nanoparticles from the aqueous solution were evaluated by adsorption batch experiments which indicated the possibility of effective application of the surfactant-modified Fe3O4 magnetic nanoparticles for the removal of As(V) from aqueous solution. The adsorption equilibrium of the composites was reached in 30 min and the kinetic data followed the pseudo-second-order model. Langmuir equation could represent the adsorption isotherm data very well. Moreover, under the identical conditions, Fe3O4@CTAB showed maximum capacity of adsorption for As(V) (55.671 mg g-1), with its removal efficiency being much higher than that of the other composites. In addition, the Fe3O4@surfactants composite magnetic nanoparticles retained 93.5% of its initial arsenic removal efficiency even after re-using it five times. The mechanism of arsenic adsorption by Fe3O4@surfactants composite magnetic nanoparticles was proved to be complexation via electrostatic attraction, which was mainly innersphere in nature.

CGUFS: A clustering-guided unsupervised feature selection algorithm for gene expression data.

Aim: Gene expression data is typically high dimensional with a limited number of samples and contain many features that are unrelated to the disease of interest. Existing unsupervised feature selection algorithms primarily focus on the significance of features in maintaining the data structure while not taking into account the redundancy among features. Determining the appropriate number of significant features is another challenge. Method: In this paper, we propose a clustering-guided unsupervised feature selection (CGUFS) algorithm for gene expression data that addresses these problems. Our proposed algorithm introduces three improvements over existing algorithms. For the problem that existing clustering algorithms require artificially specifying the number of clusters, we propose an adaptive k-value strategy to assign appropriate pseudo-labels to each sample by iteratively updating a change function. For the problem that existing algorithms fail to consider the redundancy among features, we propose a feature grouping strategy to group highly redundant features. For the problem that the existing algorithms cannot filter the redundant features, we propose an adaptive filtering strategy to determine the feature combinations to be retained by calculating the potentially effective features and potentially redundant features of each feature group. Result: Experimental results show that the average accuracy (ACC) and matthews correlation coefficient (MCC) indexes of the C4.5 classifier on the optimal features selected by the CGUFS algorithm reach 74.37% and 63.84%, respectively, significantly superior to the existing algorithms. Conclusion: Similarly, the average ACC and MCC indexes of the Adaboost classifier on the optimal features selected by the CGUFS algorithm are significantly superior to the existing algorithms. In addition, statistical experiment results show significant differences between the CGUFS algorithm and the existing algorithms.

A hybrid sampling algorithm combining synthetic minority over-sampling technique and edited nearest neighbor for missed abortion diagnosis.

BACKGROUND: Clinical diagnosis based on machine learning usually uses case samples as training samples, and uses machine learning to construct disease prediction models characterized by descriptive texts of clinical manifestations. However, the problem of sample imbalance often exists in the medical field, which leads to a decrease in classification performance of the machine learning. METHODS: To solve the problem of sample imbalance in medical dataset, we propose a hybrid sampling algorithm combining synthetic minority over-sampling technique (SMOTE) and edited nearest neighbor (ENN). Firstly, the SMOTE is used to over-sampling missed abortion and diabetes datasets, so that the number of samples of the two classes is balanced. Then, ENN is used to under-sampling the over-sampled dataset to delete the "noisy sample" in the majority. Finally, Random forest is used to model and predict the sampled missed abortion and diabetes datasets to achieve an accurate clinical diagnosis. RESULTS: Experimental results show that Random forest has the best classification performance on missed abortion and diabetes datasets after SMOTE-ENN sampled, and the MCC index is 95.6% and 90.0%, respectively. In addition, the results of pairwise comparison and multiple comparisons show that the SMOTE-ENN is significantly better than other sampling algorithms. CONCLUSION: Random forest has significantly improved all indexes on the missed abortion dataset after SMOTE-ENN sampled.

MiR-95-3p acts as a prognostic marker and promotes cervical cancer progression by targeting VCAM1.

Background: Cervical cancer patients have a high risk of metastasis and a poor prognosis with shorter disease-free survival. Thus, novel biomarkers and feasible therapies urgently need to be discovered. Previous studies have shown that miR-95-3p plays crucial roles in several cancer types. However, the roles of miR-95-3p in cervical cancer remain unknown. Methods: The micro ribonucleic acid (miRNA) expression data and clinical characteristics of cervical cancer samples were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to identify the prognostic-related miRNAs. The potential target genes of miR-95-3p were predicted by the TargetScan database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to explore the target gene of miR-95-3p. The effects of miR-95-3p inhibition and overexpression on cell proliferation were inspected by cell counting kit-8 (CCK-8) assays and cell colony formation assays. Wound-healing assays and transwell assays were also used to examine cell migration ability in HeLa and SiHa cells. Results: MiR-95-3p was the only miRNA significantly associated with the poor prognosis of cervical squamous cell carcinoma. A further analysis suggested that vascular cell adhesion molecule 1 (VCAM1) is a target gene of miR-95-3p in cervical cancer, and miR-95-3p promotes the malignant behavior of cervical cancer cells by inhibiting the expression of VCAM1. The CCK-8 and cell colony assays showed that miR-95-3p downregulation significantly suppressed cell proliferation in the HeLa and SiHa cells. The transwell and wound-healing assays showed that miR-95-3p inhibition suppressed cell migration in the HeLa and SiHa cells. Further the Western blot analysis and the quantitative real-time-polymerase chain reaction (qRT-PCR) showed that the knockdown of miR-95-3p in HeLa cells resulted in increased VCAM1 expression. And VCAM1 was highly expressed in the paired adjacent normal cervical epithelium tissue samples, but lowly expressed in the cervical tumor tissue samples. Conclusions: Our study was the first to show that miR-95-3p could serve as a prognostic biomarker of cervical cancer. Mechanistically, we discovered that miR-95-3p inhibited the expression of the cell adhesion molecule VCAM1 and thus promoted further tumor progression.