MiR-92a-2-5p suppresses esophageal squamous cell carcinoma cell proliferation and invasion by targeting PRDX2.

MicroRNAs (miRNAs) can function as negative regulators of gene expression by binding to the 3'-untranslated region (3'-UTR) of target genes. The aberrant expression of miRNAs in neoplasm is extensively associated with tumorigenesis and cancer progression, including esophageal squamous cell carcinoma (ESCC). Our previous investigation has identified the oncogenic roles of Peroxiredoxin2 (PRDX2) in ESCC progression; however, its upstream regulatory mechanism remains to be elucidated. By merging the prediction results from miRWalk2.0 and miRNA differential expression analysis results based on The Cancer Genome Atlas Esophageal Carcinoma (TCGA-ESCA) database, eight miRNA candidates were predicted to be the potential regulatory miRNAs of PRDX2, followed by further identification of miR-92a-2-5p as the putative miRNA of PRDX2. Subsequent functional studies demonstrated that miR-92a-2-5p can suppress ESCC cell proliferation and migration, as well as tumor growth in subcutaneous tumor xenograft models, which might be mediated by the suppression of AKT/mTOR and Wnt3a/ß-catenin signaling pathways upon miR-92a-2-5p mimic transfection condition. These data revealed the tumor suppressive functions of miR-92a-2-5p in ESCC by targeting PRDX2.

The sequence kernel association test for multicategorical outcomes.

Disease heterogeneity is ubiquitous in biomedical and clinical studies. In genetic studies, researchers are increasingly interested in understanding the distinct genetic underpinning of subtypes of diseases. However, existing set-based analysis methods for genome-wide association studies are either inadequate or inefficient to handle such multicategorical outcomes. In this paper, we proposed a novel set-based association analysis method, sequence kernel association test (SKAT)-MC, the sequence kernel association test for multicategorical outcomes (nominal or ordinal), which jointly evaluates the relationship between a set of variants (common and rare) and disease subtypes. Through comprehensive simulation studies, we showed that SKAT-MC effectively preserves the nominal type I error rate while substantially increases the statistical power compared to existing methods under various scenarios. We applied SKAT-MC to the Polish breast cancer study (PBCS), and identified gene FGFR2 was significantly associated with estrogen receptor (ER)+ and ER- breast cancer subtypes. We also investigated educational attainment using UK Biobank data ( N = 127 , 127 $N=127,127$ ) with SKAT-MC, and identified 21 significant genes in the genome. Consequently, SKAT-MC is a powerful and efficient analysis tool for genetic association studies with multicategorical outcomes. A freely distributed R package SKAT-MC can be accessed at https://github.com/Zhiwen-Owen-Jiang/SKATMC.

Performance of [18F]FDG PET/CT versus FAPI PET/CT for lung cancer assessment: a systematic review and meta-analysis.

PURPOSE: This article aims to compare the diagnostic performance of 18-fluorodeoxyglucose ([18F]FDG) PET/CT and fibroblast activating protein inhibitor (FAPI) PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer patients. METHODS: A systematic search was conducted on the Cochrane Library, Embase, and PubMed/MEDLINE databases from inception until November 1, 2022. Included studies assessed the use of FAPI PET/CT and [18F]FDG PET/CT in patients with lung cancer. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to evaluate the risk of bias. A random variable model was used to analyze the diagnostic tests of the two imaging modalities. RESULTS: The sensitivity of FAPI PET/CT in detecting primary lung cancer lesions was 0.98 (95% CI: 0.88-1.00), while the sensitivity of [18F]FDG PET/CT was 0.99 (95% CI: 0.74-1.00). For the detection of metastatic lesions (lymph node metastases and distant metastases), FAPI PET/CT had a sensitivity of 0.99 (95% CI: 0.90-1.00), while the sensitivity of [18F]FDG PET/CT was 0.77 (95% CI: 0.66-0.85). However, the specificity of the two imaging modalities could not be assessed due to the lack of sufficient information on pertinent true negatives. CONCLUSION: In the diagnosis of metastatic lung cancer lesions, FAPI PET/CT demonstrated a higher sensitivity compared to [18F]FDG PET/CT. Therefore, FAPI PET/CT may be considered an alternative imaging modality for the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases. CLINICAL RELEVANCE STATEMENT: FAPI may be an alternative to [18F]FDG in the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases, which plays a very important role in treatment. KEY POINTS: • This article is to compare the performance of [18F]FDG PET/CT with FAPI PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer. • However, FAPI PET/CT has a higher sensitivity for the diagnostic assessment of metastatic lung cancer lesions.

Leveraging a disulfidptosis-related signature to predict the prognosis and immunotherapy effectiveness of cutaneous melanoma based on machine learning.

BACKGROUND: Disulfidptosis is a recently discovered programmed cell death pathway. However, the exact molecular mechanism of disulfidptosis in cutaneous melanoma remains unclear. METHODS: In this study, clustering analysis was performed using data from public databases to construct a prognostic model, which was subsequently externally validated. The biological functions of the model genes were then investigated through various experimental techniques, including qRT-PCR, Western blotting, CCK-8 assay, wound healing assay, and Transwell assay. RESULTS: We constructed a signature using cutaneous melanoma (CM) data, which accurately predicts the overall survival (OS) of patients. The predictive value of this signature for prognosis and immune therapy response was validated using multiple external datasets. High-risk CM subgroups may exhibit decreased survival rates, alterations in the tumor microenvironment (TME), and increased tumor mutation burden. We initially verified the expression levels of five optimum disulfidptosis-related genes (ODRGs) in normal tissues and CM. The expression levels of these genes were further confirmed in HaCaT cells and three melanoma cell lines using qPCR and protein blotting analysis. HLA-DQA1 emerged as the gene with the highest regression coefficient in our risk model, highlighting its role in CM. Mechanistically, HLA-DQA1 demonstrated the ability to suppress CM cell growth, proliferation, and migration. CONCLUSION: In this study, a novel signature related to disulfidptosis was constructed, which accurately predicts the survival rate and treatment sensitivity of CM patients. Additionally, HLA-DQA1 is expected to be a feasible therapeutic target for effective clinical treatment of CM.

Testing microbiome association using integrated quantile regression models.

MOTIVATION: Most existing microbiome association analyses focus on the association between microbiome and conditional mean of health or disease-related outcomes, and within this vein, vast computational tools and methods have been devised for standard binary or continuous outcomes. However, these methods tend to be limited either when the underlying microbiome-outcome association occurs somewhere other than the mean level, or when distribution of the outcome variable is irregular (e.g. zero-inflated or mixtures) such that conditional outcome mean is less meaningful. We address this gap by investigating association analysis between microbiome compositions and conditional outcome quantiles. RESULTS: We introduce a new association analysis tool named MiRKAT-IQ within the Microbiome Regression-based Kernel Association Test framework using Integrated Quantile regression models to examine the association between microbiome and the distribution of outcome. For an individual quantile, we utilize the existing kernel machine regression framework to examine the association between that conditional outcome quantile and a group of microbial features (e.g. microbiome community compositions). Then, the goal of examining microbiome association with the whole outcome distribution is achieved by integrating all outcome conditional quantiles over a process, and thus our new MiRKAT-IQ test is robust to both the location of association signals (e.g. mean, variance, median) and the heterogeneous distribution of the outcome. Extensive numerical simulation studies have been conducted to show the validity of the new MiRKAT-IQ test. We demonstrate the potential usefulness of MiRKAT-IQ with applications to actual biological data collected from a previous microbiome study. AVAILABILITY AND IMPLEMENTATION: R codes to implement the proposed methodology is provided in the MiRKAT package, which is available on CRAN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Generalized Quantum Measurements on a Higher-Dimensional System via Quantum Walks.

Quantum measurements play a fundamental role in quantum mechanics. Especially, generalized quantum measurements provide a powerful and versatile tool to extract information from quantum systems. However, how to realize them on an arbitrary higher-dimensional quantum system remains a challenging task. Here we propose a simple recipe for the implementation of a general positive-operator valued measurement (POVM) on a higher-dimensional quantum system via a one-dimensional discrete-time quantum walk with a two-dimensional coin. Furthermore, using single photons and linear optics, we realize experimentally a symmetric, informationally complete (SIC) POVM on a three-dimensional system with high fidelity. As an application, we realize a qutrit state tomography with SIC-POVM and confirm that the infidelity scaling achieved by the qutrit SIC-POVM is as good as that based on mutually unbiased bases. Our study paves the way to explore physics and information in higher-dimensional quantum systems and finds applications in various quantum information processing tasks that rely on generalized quantum measurements.

Treatment response to isotretinoin correlates with specific shifts in Cutibacterium acnes strain composition within the follicular microbiome.

There are no drugs as effective as isotretinoin for acne. Deciphering the changes in the microbiome induced by isotretinoin in the pilosebaceous follicle of successfully treated patients can pave the way to identify novel therapeutic alternatives. We determined how the follicular microbiome changes with isotretinoin and identified which alterations correlate with a successful treatment response. Whole genome sequencing was done on casts from facial follicles of acne patients sampled before, during and after isotretinoin treatment. Alterations in the microbiome were assessed and correlated with treatment response at 20 weeks as defined as a 2-grade improvement in global assessment score. We investigated the α-diversity, ß-diversity, relative abundance of individual taxa, Cutibacterium acnes strain composition and bacterial metabolic profiles with a computational approach. We found that increased ß-diversity of the microbiome coincides with a successful treatment response to isotretinoin at 20 weeks. Isotretinoin selectively altered C. acnes strain diversity in SLST A and D clusters, with increased diversity in D1 strains correlating with a successful clinical response. Isotretinoin significantly decreased the prevalence of KEGG Ontology (KO) terms associated with four distinct metabolic pathways inferring that follicular microbes may have limited capacity for growth or survival following treatment. Importantly, these alterations in microbial composition or metabolic profiles were not observed in patients that failed to achieve a successful response at 20 weeks. Alternative approaches to recapitulate this shift in the balance of C. acnes strains and microbiome metabolic function within the follicle may be beneficial in the future treatment of acne.

The value of contrast-enhanced harmonic endoscopic ultrasound in differential diagnosis and evaluation of malignant risk of gastrointestinal stromal tumors (<50mm).

OBJECTIVES: Contrast-enhanced harmonic endoscopic ultrasound (CEH-EUS) has been used in the differential diagnosis of benign and malignant tumors by visualization of tumor microcirculation and perfusion. However, its diagnostic role in submucosal tumors (SMTs), especially leiomyomas and gastric submucosal tumors (GISTs) was rarely studied. The aim of this study was to analyze the diagnostic role of CEH-EUS for SMTs (<50 mm) and the value of assessing the malignant potential of GISTs. MATERIALS AND METHODS: We retrospectively included patients with tumors <50 mm in diameter who underwent preoperative EUS and CEH-EUS examination and had pathologically confirmed as leiomyomas and GISTs. To analyze the imaging features of CEH-EUS with pathological diagnosis as the gold standard and evaluate its diagnostic value. RESULTS: This study included 10 cases of leiomyomas and 38 cases of GISTs. Under CEH-EUS detection, 86.9% of GISTs showed hyper-enhancement, 89.5% showed diffuse enhancement, 39.5% showed non-enhancing spots, and 97.4% showed obvious capsule enhancement. In contrast, the leiomyoma cases mostly showed hypo-enhancement (50.0%) or non-enhancement (30.0%) (p < 0.05). Then, the value of CEH-EUS in the differential diagnosis of benign and malignant tumors based on blood flow is significantly higher than that of B-EUS. Signal appearance time was significantly faster in the intermediate-high risk GISTs than in the very low-low risk group (5.1 s versus 15.5 s, p < 0.05), and the AUROC values predicted the risk at this time to be 0.903 (0.763-0.975). Heterogeneous perfusion and non-enhancing spots were also more common in the intermediate-high risk group. Univariate and multivariate analysis revealed that intratumoral irregularitie was an independent predictor of moderate to high risk (OR 3.99, 95%CI 1.04-90.95), with sensitivity, specificity and accuracy of 73.33%, 91.30% and 84.21%, respectively. CONCLUSIONS: Through this study, CEH-EUS has a good differential diagnostic ability for leiomyomas and GISTs, and has a high value in predicting the risk of GISTs.

Dual-waveguide stacked graphene light modulator based on an MZI structure.

In order to solve the defects of the high driving voltage and a large volume of the existing electro-optical modulators, a double-waveguide stacked graphene optical modulator based on a Mach-Zehnder Interferometer structure is designed in this paper. First, the modulator size of traditional planar structure is effectively reduced by stacking two modulators vertically. Secondly, by changing the relative position of the electrode and the waveguide, the coupling effect of the electrode and the waveguide is enhanced, and the driving voltage is reduced. Finally, the performance of the designed electro-optic modulator is verified by the finite element method. The half-wave voltage of 0.55 V · cm and the modulation bandwidth of 58.8 GHz are realized on the basis of the length of 1.14 mm. The insertion loss is 1.15 dB, and the return loss is -44.8d B.

Evolution of the facial skin microbiome during puberty in normal and acne skin.

BACKGROUND: The composition of the skin microbiome varies from infancy to adulthood and becomes most stable in adulthood. Adult acne patients harbour an 'acne microbiome' dominated by specific strains of Cutibacterium acnes. However, the precise timing of skin microbiome evolution, the development of the acne microbiome, and the shift to virulent C. acnes strain composition during puberty is unknown. OBJECTIVES: We performed a cross-sectional pilot study in a paediatric population to understand how and when the skin microbiome composition transitions during puberty and whether a distinct 'acne microbiome' emerges in paediatric subjects. METHODS: Forty-eight volunteers including males and females, ages 7-17 years, with and without acne were enrolled and evaluated for pubertal development using the Tanner staging criteria. Sebum levels were measured, and skin microbiota were collected by sterile swab on the subject's forehead. DNA was sequenced by whole genome shotgun sequencing. RESULTS: A significant shift in microbial diversity emerged between early (T1-T2) and late (T3-T5) stages of puberty, coinciding with increased sebum production on the face. The overall relative abundance of C. acnes in both normal and acne skin increased during puberty and individual C. acnes strains were uniquely affected by pubertal stage and the presence of acne. Further, an acne microbiome signature associated with unique C. acnes strain composition and metabolic activity emerges in late puberty in those with acne. This unique C. acnes strain composition is predicted to have increased porphyrin production, which may contribute to skin inflammation. CONCLUSIONS: Our data suggest that the stage of pubertal development influences skin microbiome composition. As children mature, a distinct acne microbiome composition emerges in those with acne. Understanding how both puberty and acne influence the microbiome may support novel therapeutic strategies to combat acne in the paediatric population.

Variant-set association test for generalized linear mixed model.

Advances in high-throughput biotechnologies have culminated in a wide range of omics (such as genomics, epigenomics, transcriptomics, metabolomics, and metagenomics) studies, and increasing evidence in these studies indicates that the biological architecture of complex traits involves a large number of omics variants each with minor effects but collectively accounting for the full phenotypic variability. Thus, a major challenge in many "ome-wide" association analyses is to achieve adequate statistical power to identify multiple variants of small effect sizes, which is notoriously difficult for studies with relatively small-sample sizes. A small-sample adjustment incorporated in the kernel machine regression framework was proposed to solve this for association studies under various settings. However, such an adjustment in the generalized linear mixed model (GLMM) framework, which accounts for both sample relatedness and non-Gaussian outcomes, has not yet been attempted. In this study, we fill this gap by extending small-sample adjustment in kernel machine association test to GLMM. We propose a new Variant-Set Association Test (VSAT), a powerful and efficient analysis tool in GLMM, to examine the association between a set of omics variants and correlated phenotypes. The usefulness of VSAT is demonstrated using both numerical simulation studies and applications to data collected from multiple association studies. The software for implementing the proposed method in R is available at https://www.github.com/jchen1981/SSKAT.

Rapid Point-of-Care Assay by SERS Detection of SARS-CoV-2 Virus and Its Variants.

Addressing the spread of coronavirus disease 2019 (COVID-19) has highlighted the need for rapid, accurate, and low-cost diagnostic methods that detect specific antigens for SARS-CoV-2 infection. Tests for COVID-19 are based on reverse transcription PCR (RT-PCR), which requires laboratory services and is time-consuming. Here, by targeting the SARS-CoV-2 spike protein, we present a point-of-care SERS detection platform that specifically detects SARS-CoV-2 antigen in one step by captureing substrates and detection probes based on aptamer-specific recognition. Using the pseudovirus, without any pretreatment, the SARS-CoV-2 virus and its variants were detected by a handheld Raman spectrometer within 5 min. The limit of detection (LoD) for the pseudovirus was 124 TU µL-1 (18 fM spike protein), with a linear range of 250-10,000 TU µL-1. Moreover, this assay can specifically recognize the SARS-CoV-2 antigen without cross reacting with specific antigens of other coronaviruses or influenza A. Therefore, the platform has great potential for application in rapid point-of-care diagnostic assays for SARS-CoV-2.

MiRKAT: kernel machine regression-based global association tests for the microbiome.

SUMMARY: Distance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and high-dimensional outcomes. Omnibus tests allow simultaneous consideration of multiple distance and dissimilarity measures, providing higher power across a range of simulation scenarios. Two measures of effect size, a modified R-squared coefficient and a kernel RV coefficient, are incorporated to allow comparison of effect sizes across multiple kernels. AVAILABILITY AND IMPLEMENTATION: MiRKAT is available on CRAN as an R package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptome alterations in zebrafish gill after exposure to different sizes of microplastics.

Most studies on microplastics (MPs) focused on gut, liver, and brain, and MPs toxicity was size-dependent, but less has been reported on gill. Here, zebrafish were exposed to three sizes of MPs (45-53 µm, 90-106 µm, and 250-300 µm). Next, comparative transcriptome analysis and determination of physiological indices were performed in zebrafish gills to elucidate the size-associated toxicity of MPs to fish gills. Compared with the control, 60, 344, and 802 differentially expressed genes (DEGs) were identified after exposure to 45-53 µm, 90-106 µm, and 250-300 µm MPs for 5 days, respectively. More DEGs in treatment with bigger MPs suggested that bigger MPs might induce more changes in zebrafish gills than smaller ones. These DEGs were significantly enriched in the FoxO signaling, cellular senescence, circadian rhythm and p53 signaling pathways. Besides, 90-106 µm and 250-300 µm MPs treatments inhibited the cell cycle and prevented the apoptosis. The GSH content significantly increased after MPs exposure, suggesting the induction of oxidative stress. AChE and Na+/K+-ATPase activities were significantly lowered in all MPs treatments than in the control, suggesting the inhibition of neurotransmission and ion regulation. These changes might negatively influence the normal functioning of gills, such as osmoregulation, ion regulation, and respiration.

Prioritizing genetic variants in GWAS with lasso using permutation-assisted tuning.

MOTIVATION: Large scale genome-wide association studies (GWAS) have resulted in the identification of a wide range of genetic variants related to a host of complex traits and disorders. Despite their success, the individual single-nucleotide polymorphism (SNP) analysis approach adopted in most current GWAS can be limited in that it is usually biologically simple to elucidate a comprehensive genetic architecture of phenotypes and statistically underpowered due to heavy multiple-testing correction burden. On the other hand, multiple-SNP analyses (e.g. gene-based or region-based SNP-set analysis) are usually more powerful to examine the joint effects of a set of SNPs on the phenotype of interest. However, current multiple-SNP approaches can only draw an overall conclusion at the SNP-set level and does not directly inform which SNPs in the SNP-set are driving the overall genotype-phenotype association. RESULTS: In this article, we propose a new permutation-assisted tuning procedure in lasso (plasso) to identify phenotype-associated SNPs in a joint multiple-SNP regression model in GWAS. The tuning parameter of lasso determines the amount of shrinkage and is essential to the performance of variable selection. In the proposed plasso procedure, we first generate permutations as pseudo-SNPs that are not associated with the phenotype. Then, the lasso tuning parameter is delicately chosen to separate true signal SNPs and non-informative pseudo-SNPs. We illustrate plasso using simulations to demonstrate its superior performance over existing methods, and application of plasso to a real GWAS dataset gains new additional insights into the genetic control of complex traits. AVAILABILITY AND IMPLEMENTATION: R codes to implement the proposed methodology is available at https://github.com/xyz5074/plasso. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Experimental demonstration of strong unitary uncertainty relations.

Uncertainty relations are one of the most important foundations of quantum physics. In the textbook literatures, uncertainty relations usually refer to the preparation uncertainty. Its original formulation based on variances of two observables limits on the ability to prepare an ensemble of quantum systems for which non-commuting observables will have arbitrary uncertainty. The preparation uncertainty relation has been widely investigated. On the other hand, a unitary operator is a fundamental tenet of quantum theory. Every evolution of a closed quantum system is governed by acting unitary operators on the state of the system and the evolution of an open system can be represented by acting unitary operators on an enlarged system consisting of the quantum system as a subsystem. Therefore, naturally, to understand and quantitatively capture the essence of uncertainty relations for unitary operators is important and timely. Here we report an experimental investigation of a set of uncertainty relations for two unitary operators, which are theoretically derived by using a sequence of fine-grained inequalities. We test these uncertainty relations with single photons and interferometric networks. The unitary uncertainty relation is saturated by any pure qubit state. For higher-dimensional states, it is stronger than the best known bound introduced in the previous literatures. The lower bounds of the unitary uncertainty relations can be even further strengthened by the symmetry of permutation. The experimental findings agree with the predictions of quantum theory and respect the new uncertainty relations.

Maternal nicotine exposure aggravates metabolic associated fatty liver disease via PI3K/Akt signaling in adult offspring mice.

AIM: The aim of this study is to investigate the effect of maternal nicotine exposure (MNE) on the development of metabolic associated fatty liver disease (MAFLD) in adulthood offspring and the underlying mechanism. METHODS: Pregnant mice (n = 22) were subcutaneously injected with either saline vehicle (n = 11) or nicotine (n = 11) twice a day on gestational days 11-21. Offspring mice (n = 176) from both groups were weaned at postnatal day 21, and for 6 months after postnatal day 21, 96 mice were fed either a standard chow diet (n = 48) or a high-fat diet (n = 48). Serum lipid indicators, liver function indicators, insulin, and liver mitochondrial respiration were analyzed. The expression levels of fibrosis-related proteins, phosphorylated PI3K, phosphorylated Akt, sterol regulatory element-binding transcription factor 1 (SREBP1c), and peroxisome proliferator-activated receptor alpha (PPAR-α) were detected in the liver by immunohistochemistry and Western blotting. RESULTS: MNE significantly decreased the weight of both maternal and offspring mice (~30%) and inhibited organ growth in offspring mice (P < .05). MNE also significantly increased serum levels of total bile acid, triglycerides, total cholesterol, glucose, alanine aminotransferase, aspartate aminotransferase, low-density lipoprotein, and insulin while decreasing serum high-density lipoprotein levels and mitochondrial respiration activity in mice fed either the normal diet or high-fat diet (all P < .05). These effects of MNE on lipid metabolism and insulin resistance were mediated via PI3K and Akt phosphorylation and down-regulation of SREBP1c and PPAR-α. CONCLUSION: Our data indicate MNE induces lipid metabolism disorder and insulin resistance to promote MAFLD progression in adult offspring through activation of PI3K/Akt signaling and suppression of SREBP1c and PPARα protein expression.

Compositional knockoff filter for high-dimensional regression analysis of microbiome data.

A critical task in microbiome data analysis is to explore the association between a scalar response of interest and a large number of microbial taxa that are summarized as compositional data at different taxonomic levels. Motivated by fine-mapping of the microbiome, we propose a two-step compositional knockoff filter to provide the effective finite-sample false discovery rate (FDR) control in high-dimensional linear log-contrast regression analysis of microbiome compositional data. In the first step, we propose a new compositional screening procedure to remove insignificant microbial taxa while retaining the essential sum-to-zero constraint. In the second step, we extend the knockoff filter to identify the significant microbial taxa in the sparse regression model for compositional data. Thereby, a subset of the microbes is selected from the high-dimensional microbial taxa as related to the response under a prespecified FDR threshold. We study the theoretical properties of the proposed two-step procedure, including both sure screening and effective false discovery control. We demonstrate these properties in numerical simulation studies to compare our methods to some existing ones and show power gain of the new method while controlling the nominal FDR. The potential usefulness of the proposed method is also illustrated with application to an inflammatory bowel disease data set to identify microbial taxa that influence host gene expressions.

The time-dependent variations of zebrafish intestine and gill after polyethylene microplastics exposure.

Microplastics (MPs) are common environmental contaminants that present a growing health concern due to their increasing presence in aquatic and human systems. However, the mechanisms behind MP effects on organisms are unclear. In this study, zebrafish (Danio rerio) were used as an in vivo model to investigate the potential risks and molecular mechanisms of the toxic effects of polyethylene MPs (45-53 µm). In the zebrafish intestine, 6, 5, and 186 genes showed differential expression after MP treatment for 1, 5, and 10 days, respectively. In the gills, 318, 92, and 484 genes showed differential expression after MP treatment for 1, 5, and 10 days, respectively. In both the intestine and the gills, Gene Ontology (GO) annotation showed that the main enriched terms were biological regulation, cellular process, metabolic process, cellular anatomical entity, and binding. KEGG enrichment analysis on DEGs revealed that the dominant pathways were carbohydrate metabolism and lipid metabolism, which were strongly influenced by MPs in the intestine. The dominant pathways in the gills were immune and lipid metabolism. The respiratory rate of gills, the activity of SOD and GSH in the intestine significantly increased after exposure to MPs compared with the control (p < 0.05), while the activity of SOD did not change in the gills. GSH activity was only significantly increased after MP exposure for 5 days. Also, the MDA content was not changed in the intestine but was significantly decreased in the gills after MP exposure. The activity of AChE significantly decreased only after MPs exposure for 5 days. Overall, these results indicated that MPs pollution significantly induced oxidative stress and neurotoxicity, increased respiratory rate, disturbed energy metabolism and stimulated immune function in fish, displaying an environmental risk of MPs to aquatic ecosystems.

Trilobolide-6-O-isobutyrate suppresses hepatocellular carcinoma tumorigenesis through inhibition of IL-6/STAT3 signaling pathway.

Currently available therapies for hepatocellular carcinoma (HCC), with a high morbidity and high mortality, are only marginally effective and with sharp adverse side effects, which makes it compulsory to explore novel and more effective anticancer molecules. Chinese medicinal herbs exhibited prominent anticancer effects and were applied to supplement clinical cancer treatment. Here, we reported a compound, trilobolide-6-O-isobutyrate (TBB), isolated from the flowers of Wedelia trilobata with a markedly cytotoxic effect on HCC cells. We found that TBB time- and dose-dependently inhibited HCC cells' growth and colony formation in vitro. Moreover, TBB induced cell cycle arrest at the G2/M phase, mitochondrial caspase-dependent apoptosis, and suppressed migration and invasion, as well as the glycolysis of HCC cells. Mechanistically, our data indicated that TBB inhibited the STAT3 pathway activation by directly interacting with the TYR 640/657 sites of the STAT3 protein and decreasing the level of p-STAT3. TBB also regulated the expression of PCNA, Ki67, Cyclin B1, Cyclin E, Bax, Bcl2, MMP2/9, and PGK1 through the inhibition of the IL-6/STAT3 signaling pathway. Lastly, we confirmed that TBB effectively eliminated tumor growth without causing overt toxicity to healthy tissues in the xenograft tumor model. The exploration of anticancer activity and the underlying mechanism of TBB suggested its usage as a promising chemotherapeutic agent for HCC.