MiR-431 promotes cardiomyocyte proliferation by targeting FBXO32 expression.

BACKGROUND: The induction of cardiomyocyte (CM) proliferation is a promising approach for cardiac regeneration following myocardial injury. MicroRNAs (miRNAs) have been reported to regulate CM proliferation. In particular, miR-431 expression decreases during cardiac development, according to Gene Expression Omnibus (GEO) microarray data. However, whether miR-431 regulates CM proliferation has not been thoroughly investigated. METHODS: We used integrated bioinformatics analysis of GEO datasets to identify the most significantly differentially expressed miRNAs. Real-time quantitative PCR and fluorescence in situ hybridization were performed to determine the miRNA expression patterns in hearts. Gain- and loss-of-function assays were conducted to detect the role of miRNA in CM proliferation. Additionally, we detected whether miR-431 affected CM proliferation in a myocardial infarction model. The TargetScan, miRDB and miRWalk online databases were used to predict the potential target genes of miRNAs. Luciferase reporter assays were used to study miRNA interactions with the targeting mRNA. RESULTS: First, we found a significant reduction in miR-431 levels during cardiac development. Then, by overexpression and inhibition of miR-431, we demonstrated that miR-431 promotes CM proliferation in vitro and in vivo, as determined by immunofluorescence assays of 5-ethynyl-2'-deoxyuridine (EdU), pH3, Aurora B and CM count, whereas miR-431 inhibition suppresses CM proliferation. Then, we found that miR-431 improved cardiac function post-myocardial infarction. In addition, we identified FBXO32 as a direct target gene of miR-431, with FBXO32 mRNA and protein expression being suppressed by miR-431. FBXO32 inhibited CM proliferation. Overexpression of FBXO32 blocks the enhanced effect of miR-431 on CM proliferation, suggesting that FBXO32 is a functional target of miR-431 during CM proliferation. CONCLUSION: In summary, miR-431 promotes CM proliferation by targeting FBXO32, providing a potential molecular target for preventing myocardial injury.

lncRNA ZNRD1-AS1 promotes malignant lung cell proliferation, migration, and angiogenesis via the miR-942/TNS1 axis and is positively regulated by the m6A reader YTHDC2.

RATIONALE: Lung cancer is the most prevalent form of cancer and has a high mortality rate, making it a global public health concern. The N6-methyladenosine (m6A) modification is a highly dynamic and reversible process that is involved in a variety of essential biological processes. Using in vitro, in vivo, and multi-omics bioinformatics, the present study aims to determine the function and regulatory mechanisms of the long non-coding (lnc)RNA zinc ribbon domain-containing 1-antisense 1 (ZNRD1-AS1). METHODS: The RNAs that were bound to the m6A 'reader' were identified using YTH domain-containing 2 (YTHDC2) RNA immunoprecipitation (RIP)-sequencing. Utilizing methylated RIP PCR/quantitative PCR, pull-down, and RNA stability assays, m6A modification and ZNRD1-AS1 regulation were analyzed. Using bioinformatics, the expression levels and clinical significance of ZNRD1-AS1 in lung cancer were evaluated. Using fluorescent in situ hybridization and quantitative PCR assays, the subcellular location of ZNRD1-AS1 was determined. Using cell migration, proliferation, and angiogenesis assays, the biological function of ZNRD1-AS1 in lung cancer was determined. In addition, the tumor suppressor effect of ZNRD1-AS1 in vivo was validated using a xenograft animal model. Through bioinformatics analysis and in vitro assays, the downstream microRNAs (miRs) and competing endogenous RNAs were also predicted and validated. RESULTS: This study provided evidence that m6A modification mediates YTHDC2-mediated downregulation of ZNRD1-AS1 in lung cancer and cigarette smoke-exposed cells. Low levels of ZNRD1-AS1 expression were linked to adverse clinicopathological characteristics, immune infiltration, and prognosis. ZNRD1-AS1 overexpression was shown to suppress lung cancer cell proliferation, migration, and angiogenesis in vitro and in vivo, and to reduce tumor growth in nude mice. ZNRD1-AS1 expression was shown to be controlled by treatment of cells with either the methylation inhibitor 3-Deazaadenosine or the demethylation inhibitor Meclofenamic. Furthermore, the miR-942/tensin 1 (TNS1) axis was demonstrated to be the downstream regulatory signaling pathway of ZNRD1-AS1. CONCLUSIONS: ZNRD1-AS1 serves an important function and has clinical relevance in lung cancer. In addition, the findings suggested that m6A modification could mediate the regulation of the ZNRD1-AS1/miR-942/TNS1 axis via the m6A reader YTHDC2.

Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis.

BACKGROUND: Lung cancer is one of the most common carcinomas in the world, and lung adenocarcinoma (LUAD) is the most lethal and most common subtype of lung cancer. Cigarette smoking is the most leading risk factor of lung cancer, but it is still unclear how normal lung cells become cancerous in cigarette smokers. This study aims to identify potential smoking-related biomarkers associated with the progression and prognosis of LUAD, as well as their regulation mechanism using an in vitro carcinogenesis model and bioinformatics analysis. RESULTS: Based on the integration analysis of four Gene Expression Omnibus (GEO) datasets and our mRNA sequencing analysis, 2 up-regulated and 11 down-regulated genes were identified in both S30 cells and LUAD. By analyzing the LUAD dataset in The Cancer Gene Analysis (TCGA) database, 3 of the 13 genes, viz., glycophorin C (GYPC), NME/NM23 nucleoside diphosphate kinase 1 (NME1) and slit guidance ligand 2 (SLIT2), were found to be significantly correlated with LUAD patients' smoking history. The expression levels of GYPC, NME1 and SLIT2 in S30 cells and lung cancer cell lines were validated by quantitative PCR, immunofluorescence, and western blot assays. Besides, these three genes are associated with tumor invasion depth, and elevated expression of NME1 was correlated with lymph node metastasis. The enrichment analysis suggested that these genes were highly correlated to tumorigenesis and metastasis-related biological processes and pathways. Moreover, the increased expression levels of GYPC and SLIT2, as well as decreased expression of NME1 were associated with a favorable prognosis in LUAD patients. Furthermore, based on the multi-omics data in the TCGA database, these genes were found to be regulated by DNA methylation. CONCLUSION: In conclusion, our observations indicated that the differential expression of GYPC, NME1 and SLIT2 may be regulated by DNA methylation, and they are associated with cigarette smoke-induced LUAD, as well as serve as prognostic factors in LUAD patients.

Targeting Myeloid-Derived Suppressor Cells Is a Novel Strategy for Anti-Psoriasis Therapy.

Psoriasis is a common immune-mediated, chronic inflammatory genetic-related disease that affects patients' quality of life. Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of progenitor and immature myeloid cells which are expanded in psoriatic skin lesions and peripheral blood. However, the role of MDSCs in the pathogenesis of psoriasis remains unclear. Here, we confirmed that the accumulation of human MDSCs is remarkably increased in skin lesions of psoriasis patients by flow cytometry. Depleting MDSCs by Gemcitabine significantly suppresses IMQ-induced psoriatic inflammation and epidermal thickening as well as Th17 and Treg cell accumulation. Moreover, through the RNA-Seq technique, we validated some differentially expressed genes on CD4+ T-cells of IMQ-induced-MDSC-depleted mice such as IL-21 and Timd2, which are involved in Th17-cell differentiation or T-cell activation. Interestingly, neutralizing IL-21R by antibody reduces IMQ-induced epidermal thickening through downregulating the infiltration of MDSCs and Th17 cells. Our data suggest that targeting myeloid-derived suppressor cells is a novel strategy for antipsoriasis therapy. IL-21 may be a potential therapeutic target in psoriasis.

Resistant silkworm strain block viral infection independent of melanization.

Melanization mediated by the prophenoloxidase-activating system (proPO) is an important immune response in invertebrates. However, the role of melanization on viral infection has not been wildly revealed in Bombyx mori (B. mori), silkworm. Here, we investigated the extent of melanization of susceptible (871) and resistant (near-isogenic line 871C) B. mori strains. The result showed that the extent of melanization was significantly higher in the susceptible strain than in the resistant strain. A majority of Serpins were up-regulated in the resistant strain through iTRAQ-based quantitative proteomics, comparing with susceptible strain. Our data further identified that Serpin-5, Serpin-9 and Serpin-19 reduced PO activity, indicating that the menlanization pathway was inhibited in the resistant strain. Moreover, our results indicated that the hemolymph of 871 reduced viral infection in the presence of PTU, indicating that melanization of 871 strain hemolymph blocked viral infection. However, viral infection was significantly suppressed in the hemolymph of 871C strain regardless of the presence of PTU or not, which implied that the resistant strain inhibited viral infection independent of the melanization pathway. Taken together, our findings indicated that the melanization pathway was inhibited in resistant strain. These results expend the analysis of melanization pathway in insects and provide insights into understanding the antiviral mechanism.

The Akkermansia muciniphila is a gut microbiota signature in psoriasis.

Psoriasis is an immune-mediated chronic inflammatory skin disease. Although its pathogenesis is not fully understood, Th17 cells and the cytokines they produce, such as IL-17, IL-22 and IL-23, play critical roles in the pathogenesis of psoriasis. Evidence has demonstrated that psoriasis has some common features, including immune responses (due to Th17 cells) and inflammatory cytokine profiles, with systematic diseases including inflammatory bowel diseases (IBDs) and obesity. Recently, studies have demonstrated that the gut microbiota plays a crucial role in host homoeostasis and immune response, particular in Th17 cells, but the role of the gut microbiota in psoriasis remains unclear. To study the relationship between gut microbiota and psoriasis, we analysed microbiota profiles in psoriasis using a 16S rDNA sequencing platform, and we found that the abundance of Akkermansia muciniphila was significantly reduced in patients with psoriasis. A. muciniphila is believed to have an important function in the pathogenesis of IBD and obesity; therefore, A. muciniphila, which is an indicator of health status, may be a key node for psoriasis as well as IBD and obesity. Taken together, our study identified that gut microbiota signature and function are significantly altered in the gut of patients with psoriasis, which provides a novel angle to understanding the pathogenesis of psoriasis.

fMRI as a Preimplant Objective Tool to Predict Postimplant Oral Language Outcomes in Children with Cochlear Implants.

OBJECTIVES: Despite the positive effects of cochlear implantation, postimplant variability in speech perception and oral language outcomes is still difficult to predict. The aim of this study was to identify neuroimaging biomarkers of postimplant speech perception and oral language performance in children with hearing loss who receive a cochlear implant. The authors hypothesized positive correlations between blood oxygen level-dependent functional magnetic resonance imaging (fMRI) activation in brain regions related to auditory language processing and attention and scores on the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2) and the Early Speech Perception Test for Profoundly Hearing-Impaired Children (ESP), in children with congenital hearing loss. DESIGN: Eleven children with congenital hearing loss were recruited for the present study based on referral for clinical MRI and other inclusion criteria. All participants were <24 months at fMRI scanning and <36 months at first implantation. A silent background fMRI acquisition method was performed to acquire fMRI during auditory stimulation. A voxel-based analysis technique was utilized to generate z maps showing significant contrast in brain activation between auditory stimulation conditions (spoken narratives and narrow band noise). CELF-P2 and ESP were administered 2 years after implantation. Because most participants reached a ceiling on ESP, a voxel-wise regression analysis was performed between preimplant fMRI activation and postimplant CELF-P2 scores alone. Age at implantation and preimplant hearing thresholds were controlled in this regression analysis. RESULTS: Four brain regions were found to be significantly correlated with CELF-P2 scores. These clusters of positive correlation encompassed the temporo-parieto-occipital junction, areas in the prefrontal cortex and the cingulate gyrus. For the story versus silence contrast, CELF-P2 core language score demonstrated significant positive correlation with activation in the right angular gyrus (r = 0.95), left medial frontal gyrus (r = 0.94), and left cingulate gyrus (r = 0.96). For the narrow band noise versus silence contrast, the CELF-P2 core language score exhibited significant positive correlation with activation in the left angular gyrus (r = 0.89; for all clusters, corrected p < 0.05). CONCLUSIONS: Four brain regions related to language function and attention were identified that correlated with CELF-P2. Children with better oral language performance postimplant displayed greater activation in these regions preimplant. The results suggest that despite auditory deprivation, these regions are more receptive to gains in oral language development performance of children with hearing loss who receive early intervention via cochlear implantation. The present study suggests that oral language outcome following cochlear implant may be predicted by preimplant fMRI with auditory stimulation using natural speech.

Proteomic diversity of high density lipoproteins: our emerging understanding of its importance in lipid transport and beyond.

Recent applications of mass spectrometry technology have dramatically increased our understanding of the proteomic diversity of high density lipoproteins (HDL). Depending on the method of HDL isolation, upwards of 85 proteins have been identified, and the list continues to grow. In addition to proteins consistent with traditionally accepted roles in lipid transport, HDL carries surprising constituents, such as members of the complement pathway, protease inhibitors involved in hemostasis, acute-phase response proteins, immune function mediators, and even metal-binding proteins. This compositional diversity fits well with hundreds of studies demonstrating a wide functional pleiotrophy, including roles in lipid transport, oxidation, inflammation, hemostasis, and immunity. This review summarizes the progression of our understanding of HDL proteomic complexity and points out key experimental observations that reinforce the functional diversity of HDL. The possibility of specific HDL subspecies with distinct functions, the evidence supporting this concept, and some of the best examples of experimentally defined HDL subspecies are also discussed. Finally, key challenges facing the field are highlighted, particularly the need to identify and define the function of HDL subspecies to better inform attempts to pharmacologically manipulate HDL for the benefit of cardiovascular disease and possibly other maladies.

Kinetics and mechanism study of competitive inhibition of jack-bean urease by baicalin.

Baicalin (BA) is the principal component of Radix Scutellariae responsible for its pharmacological activity. In this study, kinetics and mechanism of inhibition by BA against jack-bean urease were investigated for its therapeutic potential. It was revealed that the IC50 of BA against jack-bean urease was 2.74 ± 0.51 mM, which was proved to be a competitive and concentration-dependent inhibition with slow-binding progress curves. The rapid formation of initial BA-urease complex with an inhibition constant of K(i) = 3.89 × 10⁻³ mM was followed by a slow isomerization into the final complex with an overall inhibition constant of K(i)* = 1.47 × 10⁻4 mM. High effectiveness of thiol protectors against BA inhibition indicated that the strategic role of the active-site sulfhydryl group of the urease was involved in the blocking process. Moreover, the inhibition of BA was proved to be reversible due to the fact that urease could be reactivated by dithiothreitol but not reactant dilution. Molecular docking assay suggested that BA made contacts with the important activating sulfhydryl group Cys-592 residues and restricted the mobility of the active-site flap. Taken together, it could be deduced that BA was a competitive inhibitor targeting thiol groups of urease in a slow-binding manner both reversibly and concentration-dependently, serving as a promising urease inhibitor for treatments on urease-related diseases.

GAPDH: A common housekeeping gene with an oncogenic role in pan-cancer.

Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is one of the most prominent housekeeping proteins and is widely used as an internal control in some semi-quantitative assays. In addition to glycolysis, GAPDH is involved in several cancer-related biological processes and has been reported to be commonly dysregulated in multiple cancer types. Therefore, its role in the physiological process of cancer needs to be urgently elucidated. Pan-cancer analysis indicated that GAPDH is ubiquitously highly expressed in most cancer types, and that patients with a high GAPDH expression of in tumor tissues have a poor prognosis. The concordance of GAPDH expression in tumors with the infiltration of immune cells and immune checkpoints implies a certain association between GAPDH and the tumor microenvironment as well as tumor development. Gene Set Enrichment Analysis revealed that GAPDH may contribute to multiple important cancer-related pathways and biological processes. Multi-omics analysis and in vitro cell experiments revealed that GAPDH overexpression is regulated by DNA copy number amplification and promoter methylation modification. Importantly, a transcription factor, forkhead box M1 (FOXM1), which is capable of regulating GAPDH expression, was also identified and was confirmed to be an oncogene and ubiquitously highly expressed in multiple cancer types. Semi-quantitative chromatin immunoprecipitation, quantitative PCR, and dual-luciferase assays showed that FOXM1 mainly binds to the promoter region of GAPDH in two cancer cell lines. The present findings revealed the implication of GAPDH in tumor development, thus bringing attention to this important molecule and casting doubts on its role as an internal reference gene in cancer studies.

Postchronic Single-Walled Carbon Nanotube Exposure Causes Irreversible Malignant Transformation of Human Bronchial Epithelial Cells through DNA Methylation Changes.

As environmental pollutants and possible carcinogens, carbon nanotubes (CNTs) have recently been found to induce carcinogenesis and tumor metastasis after long-term pulmonary exposure. However, whether CNT-induced carcinogenesis can be inherited and last for generations remains unclear. Herein, postchronic single-walled carbon nanotubes (SWCNTs) exposed human lung cell model (BEAS-2B cells) are established to investigate SWCNT-induced carcinogenesis. At a tolerated sublethal dose level, postchronic SWCNT exposure significantly increases the migration and invasion abilities of BEAS-2B cells, leading to malignant cell transformation. Notably, the malignant transformation of BEAS-2B cells is irreversible within a 60 day recovery period after SWCNT exposure, and the malignant transformation activities of cells gradually increase during the recovery period. Moreover, these transformed cells promote carcinogenesis in vivo, accompanied by a raised level of biomarkers of lung adenocarcinoma. Further mechanism analyses reveal that postchronic exposure to SWCNTs causes substantial DNA methylation and transcriptome dysregulation of BEAS-2B cells. Subsequent enrichment and clinical database analyses reveal that differentially expressed/methylated genes of BEAS-2B cells are enriched in cancer-related biological pathways. These results not only demonstrate that postchronic SWCNT-exposure-induced carcinogenesis is heritable but also uncover a mechanism from the perspective of DNA methylation.

miR­200b upregulation promotes migration of BEAS­2B cells following long­term exposure to cigarette smoke by targeting ETS1.

Cigarette smoking is the leading cause of all histological types of lung cancer, and the role that microRNAs (miRNAs) serve in its pathogenesis is being increasingly recognized. The aim of the present study was to investigate the role of miR­200b on migration in cigarette smoke­induced malignant transformed cells. In the present study, miR­200b expression was found to be increased in cigarette smoke (CS)­exposed BEAS­2B cells, lung cancer cell lines and tumor tissue samples. Using wound healing and Transwell migration assays, the migratory ability was shown to be increased in miR­200b­overexpressing cells, whereas miR­200b knockdown resulted in reduced migration. Additionally, the expression of E­Cadherin was downregulated, whereas that of N­Cadherin was upregulated in miR­200b mimic­transfected cells, suggesting an increase in epithelial­mesenchymal transition. Downstream, using four target gene prediction tools, six target genes of miR­200b were predicted, amongst which, ETS proto­oncogene 1 transcription factor (ETS1) was shown to be significantly associated with tumor invasion depth and negatively associated with miR­200b expression. The interaction between miR­200b and ETS1 was confirmed using a dual­luciferase reporter assay. Using rescue experiments, the increased migratory ability of the miR­200b­overexpressing cells was reversed by ETS1 overexpression. In summary, this study showed that miR­200b overexpression serves a carcinogenic role and promotes the migration of BEAS­2B cells following long­term exposure to CS by targeting ETS1.

Downregulation of m6A Reader YTHDC2 Promotes the Proliferation and Migration of Malignant Lung Cells via CYLD/NF-κB Pathway.

Lung cancer is one of the most common types of carcinoma worldwide. Cigarette smoking is considered the leading cause of lung cancer. Aberrant expression of several YT521-B homology (YTH) family proteins has been reported to be closely associated with multiple cancer types. The present study aims to evaluate the function and regulatory mechanisms of the N6-methyladenosine (m6A) reader protein YTH domain containing 2 (YTHDC2) by in vitro, in vivo and bioinformatics analyses. The results revealed that YTHDC2 was reduced in lung cancer and cigarette smoke-exposed cells. Notably, bioinformatics and tissue arrays analysis demonstrated that decreased YTHDC2 was highly associated with smoking history, pathological stage, invasion depth, lymph node metastasis and poor outcomes. The in vivo and in vitro studies revealed that YTHDC2 overexpression inhibited the proliferation and migration of lung cancer cells as well as tumor growth in nude mice. Furthermore, YTHDC2 decreased expression was modulated by copy number deletion in lung cancer. Importantly, the cylindromatosis (CYLD)/NF-κB pathways were confirmed as the downstream signaling of YTHDC2, and this axis was mediated by m6A modification. The present results indicated that smoking-related downregulation of YTHDC2 was associated with enhanced proliferation and migration in lung cancer cells, and appeared to be regulated by DNA copy number variation. Importantly, YTHDC2 functions as a tumor suppressor through the CYLD/NF-κB signaling pathway, which is mediated by m6A modification.

Scutellarin regulates osteoarthritis in vitro by inhibiting the PI3K/AKT/mTOR signaling pathway.

Osteoarthritis (OA) is a highly prevalent disease worldwide that causes disability and diminishes the quality of life of affected individuals. The disease is characterized by cartilage destruction, increased inflammatory responses and cholesterol metabolic disorder. Scutellarin is the major active ingredient extracted from Erigeron breviscapus, and it has been demonstrated to possess various pharmacological functions in the treatment of the disease. However, its effects on OA are complex. The present study investigated whether scutellarin can mediate the release of inflammatory cytokines, the expression of collagen- and cholesterol-related proteins, and regulate the phosphoinositide 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) signaling pathway in a cell model of OA. Interleukin (IL)-1ß was used to stimulate OA in SW1353 cells in vitro. The primary methods used were ELISA and western blotting, which were carried out to examine the effects of scutellarin on the cell model of OA. It was found that scutellarin increased the expression of collagen II and SRY-box 9, whereas it suppressed the expression of matrix metalloproteinase 13. In addition, scutellarin downregulated the expression levels of cholesterol 25-hydroxylase and cytochrome P450 family 7 subfamily B polypeptide 1, but upregulated the expression of apolipoprotein A-1 and adenosine triphosphate-binding cassette transporter A1. The IL-1ß-induced increase in the expression of IL-6 was decreased by treatment with scutellarin; however, scutellarin did not alter the expression of C-reactive protein and tumor necrosis factor-α. The protein expression levels of AKT, phosphorylated (p)-AKT, mTOR and p-mTOR in the PI3K/AKT/mTOR signaling pathway were decreased in the IL-1ß-induced SW1353 cells following scutellarin treatment. Overall, the findings of the present study demonstrated that scutellarin regulated OA in vitro by inhibiting the PI3K/AKT/mTOR signaling pathway.

fMRI as a Preimplant Objective Tool to Predict Children's Postimplant Auditory and Language Outcomes as Measured by Parental Observations.

BACKGROUND: The trends in cochlear implantation candidacy and benefit have changed rapidly in the last two decades. It is now widely accepted that early implantation leads to better postimplant outcomes. Although some generalizations can be made about postimplant auditory and language performance, neural mechanisms need to be studied to predict individual prognosis. PURPOSE: The aim of this study was to use functional magnetic resonance imaging (fMRI) to identify preimplant neuroimaging biomarkers that predict children's postimplant auditory and language outcomes as measured by parental observation/reports. RESEARCH DESIGN: This is a pre-post correlational measures study. STUDY SAMPLE: Twelve possible cochlear implant candidates with bilateral severe to profound hearing loss were recruited via referrals for a clinical magnetic resonance imaging to ensure structural integrity of the auditory nerve for implantation. INTERVENTION: Participants underwent cochlear implantation at a mean age of 19.4 mo. All children used the advanced combination encoder strategy (ACE, Cochlear Corporation™, Nucleus® Freedom cochlear implants). Three participants received an implant in the right ear; one in the left ear whereas eight participants received bilateral implants. Participants' preimplant neuronal activation in response to two auditory stimuli was studied using an event-related fMRI method. DATA COLLECTION AND ANALYSIS: Blood oxygen level dependent contrast maps were calculated for speech and noise stimuli. The general linear model was used to create z-maps. The Auditory Skills Checklist (ASC) and the SKI-HI Language Development Scale (SKI-HI LDS) were administered to the parents 2 yr after implantation. A nonparametric correlation analysis was implemented between preimplant fMRI activation and postimplant auditory and language outcomes based on ASC and SKI-HI LDS. Statistical Parametric Mapping software was used to create regression maps between fMRI activation and scores on the aforementioned tests. Regression maps were overlaid on the Imaging Research Center infant template and visualized in MRIcro. RESULTS: Regression maps revealed two clusters of brain activation for the speech versus silence contrast and five clusters for the noise versus silence contrast that were significantly correlated with the parental reports. These clusters included auditory and extra-auditory regions such as the middle temporal gyrus, supramarginal gyrus, precuneus, cingulate gyrus, middle frontal gyrus, subgyral, and middle occipital gyrus. Both positive and negative correlations were observed. Correlation values for the different clusters ranged from -0.90 to 0.95 and were significant at a corrected p value of <0.05. Correlations suggest that postimplant performance may be predicted by activation in specific brain regions. CONCLUSIONS: The results of the present study suggest that (1) fMRI can be used to identify neuroimaging biomarkers of auditory and language performance before implantation and (2) activation in certain brain regions may be predictive of postimplant auditory and language performance as measured by parental observation/reports.

C-lysozyme contributes to antiviral immunity in Bombyx mori against nucleopolyhedrovirus infection.

Lysozymes is a ubiquitous immune effector that is widely distributed in both vertebrates and invertebrates. Previous reports have shown that lysozymes significantly inhibit viral infections in vertebrates. However, the antiviral effects of lysozymes in invertebrates remain unclear. Here, we investigated the role of lysozymes in Bombyx mori (B. mori) response to viral infection by overexpressing B. mori C-lysozyme (BmC-LZM) in larvae and cells. We found that BmC-LZM was up-regulated in cells in response to viral infection. Indeed, the overexpressing of BmC-LZM significantly inhibited viral replication in cells during late-stage infection. However, this effect was reversed by BmC-LZM mRNA. BmC-LZM was successfully overexpressed in B. mori strain 871 using Baculovirus Expression Vector System (BEVS). This overexpression markedly reduced viral proliferation and increased larval survival percentage. Thus, BmC-LZM inhibited viral replication both in vivo and in vitro, indicating that BmC-LZM is involved in the insect immune response to viral infection. Our results provide a basis for further applications of lysozymes.

A Computational Model for the Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Based on Functional Brain Volume.

In this paper, we investigated the problem of computer-aided diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) using machine learning techniques. With the ADHD-200 dataset, we developed a Support Vector Machine (SVM) model to classify ADHD patients from typically developing controls (TDCs), using the regional brain volumes as predictors. Conventionally, the volume of a brain region was considered to be an anatomical feature and quantified using structural magnetic resonance images. One major contribution of the present study was that we had initially proposed to measure the regional brain volumes using fMRI images. Brain volumes measured from fMRI images were denoted as functional volumes, which quantified the volumes of brain regions that were actually functioning during fMRI imaging. We compared the predictive power of functional volumes with that of regional brain volumes measured from anatomical images, which were denoted as anatomical volumes. The former demonstrated higher discriminative power than the latter for the classification of ADHD patients vs. TDCs. Combined with our two-step feature selection approach which integrated prior knowledge with the recursive feature elimination (RFE) algorithm, our SVM classification model combining functional volumes and demographic characteristics achieved a balanced accuracy of 67.7%, which was 16.1% higher than that of a relevant model published previously in the work of Sato et al. Furthermore, our classifier highlighted 10 brain regions that were most discriminative in distinguishing between ADHD patients and TDCs. These 10 regions were mainly located in occipital lobe, cerebellum posterior lobe, parietal lobe, frontal lobe, and temporal lobe. Our present study using functional images will likely provide new perspectives about the brain regions affected by ADHD.

A semi-supervised Support Vector Machine model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging.

INTRODUCTION: We developed a machine learning model to predict whether or not a cochlear implant (CI) candidate will develop effective language skills within 2 years after the CI surgery by using the pre-implant brain fMRI data from the candidate. METHODS: The language performance was measured 2 years after the CI surgery by the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2). Based on the CELF-P2 scores, the CI recipients were designated as either effective or ineffective CI users. For feature extraction from the fMRI data, we constructed contrast maps using the general linear model, and then utilized the Bag-of-Words (BoW) approach that we previously published to convert the contrast maps into feature vectors. We trained both supervised models and semi-supervised models to classify CI users as effective or ineffective. RESULTS: Compared with the conventional feature extraction approach, which used each single voxel as a feature, our BoW approach gave rise to much better performance for the classification of effective versus ineffective CI users. The semi-supervised model with the feature set extracted by the BoW approach from the contrast of speech versus silence achieved a leave-one-out cross-validation AUC as high as 0.97. Recursive feature elimination unexpectedly revealed that two features were sufficient to provide highly accurate classification of effective versus ineffective CI users based on our current dataset. CONCLUSION: We have validated the hypothesis that pre-implant cortical activation patterns revealed by fMRI during infancy correlate with language performance 2 years after cochlear implantation. The two brain regions highlighted by our classifier are potential biomarkers for the prediction of CI outcomes. Our study also demonstrated the superiority of the semi-supervised model over the supervised model. It is always worthwhile to try a semi-supervised model when unlabeled data are available.

Detecting brain structural changes as biomarker from magnetic resonance images using a local feature based SVM approach.

Detecting brain structural changes from magnetic resonance (MR) images can facilitate early diagnosis and treatment of neurological and psychiatric diseases. Many existing methods require an accurate deformation registration, which is difficult to achieve and therefore prevents them from obtaining high accuracy. We develop a novel local feature based support vector machine (SVM) approach to detect brain structural changes as potential biomarkers. This approach does not require deformation registration and thus is less influenced by artifacts such as image distortion. We represent the anatomical structures based on scale invariant feature transform (SIFT). Likelihood scores calculated using feature-based morphometry is used as the criterion to categorize image features into three classes (healthy, patient and noise). Regional SVMs are trained to classify the three types of image features in different brain regions. Only healthy and patient features are used to predict the disease status of new brain images. An ensemble classifier is built from the regional SVMs to obtain better prediction accuracy. We apply this approach to 3D MR images of Alzheimer's disease, Parkinson's disease and bipolar disorder. The classification accuracy ranges between 70% and 87%. The highly predictive disease-related regions, which represent significant anatomical differences between the healthy and diseased, are shown in heat maps. The common and disease-specific brain regions are identified by comparing the highly predictive regions in each disease. All of the top-ranked regions are supported by literature. Thus, this approach will be a promising tool for assisting automatic diagnosis and advancing mechanism studies of neurological and psychiatric diseases.

Combined analysis of sMRI and fMRI imaging data provides accurate disease markers for hearing impairment.

In this research, we developed a robust two-layer classifier that can accurately classify normal hearing (NH) from hearing impaired (HI) infants with congenital sensori-neural hearing loss (SNHL) based on their Magnetic Resonance (MR) images. Unlike traditional methods that examine the intensity of each single voxel, we extracted high-level features to characterize the structural MR images (sMRI) and functional MR images (fMRI). The Scale Invariant Feature Transform (SIFT) algorithm was employed to detect and describe the local features in sMRI. For fMRI, we constructed contrast maps and detected the most activated/de-activated regions in each individual. Based on those salient regions occurring across individuals, the bag-of-words strategy was introduced to vectorize the contrast maps. We then used a two-layer model to integrate these two types of features together. With the leave-one-out cross-validation approach, this integrated model achieved an AUC score of 0.90. Additionally, our algorithm highlighted several important brain regions that differentiated between NH and HI children. Some of these regions, e.g. planum temporale and angular gyrus, were well known auditory and visual language association regions. Others, e.g. the anterior cingulate cortex (ACC), were not necessarily expected to play a role in differentiating HI from NH children and provided a new understanding of brain function and of the disorder itself. These important brain regions provided clues about neuroimaging markers that may be relevant to the future use of functional neuroimaging to guide predictions about speech and language outcomes in HI infants who receive a cochlear implant. This type of prognostic information could be extremely useful and is currently not available to clinicians by any other means.