Data_Sheet_1_Decitabine improves MMS-induced retinal photoreceptor cell damage by targeting DNMT3A and DNMT3B.PDF

IntroductionRetinitis pigmentosa (RP) is a group of neurodegenerative retinopathies causing blindness due to progressive and irreversible photoreceptor cell death. The alkylating agent methyl methanesulfonate (MMS) can induce selective photoreceptor cell death, which is used to establish RP animal models. MMS induces DNA base damage by adding alkyl groups to DNA, and epigenetic modifications influence DNA damage response. Here, we aimed to explore the relationship between DNA methylation and DNA damage response in dying photoreceptors of RP.MethodsThe mouse RP model was established by a single intraperitoneal injection of MMS. The retinal structure and function were assessed by H&E, OCT, TUNEL, and ERG at several time points. The expression of DNA methylation regulators was assessed by qPCR and Western blot. DNMT inhibitor 5-aza-dC was applied to inhibit the activity of DNA methyltransferases and improve the retinal photoreceptor damage.ResultsThe outer nuclear layer (ONL) and IS/OS layer were significantly thinner and the retinal function was impaired after MMS treatment. The cell death was mainly located in the ONL. The retinal damage induced by MMS was accompanied by hyperexpression of DNMT3A/3B. The application of DNMT inhibitor 5-aza-dC could suppress the expression level of DNMT3A/3B, resulting in the remission of MMS-induced photoreceptor cell damage. The ONL and IS/OS layers were thicker than that of the control group, and the retinal function was partially restored. This protective effect of 5-aza-dC was associated with the down-regulated expression of DNMT3A/3B.ConclusionThese findings identified a functional role of DNMT3A/3B in MMS-induced photoreceptor cell damage and provided novel evidence to support DNMTs as potential therapeutic targets in retinal degenerative diseases.Graphical Abstrac

DataSheet_1_Machine learning-based CT texture analysis in the differentiation of testicular masses.xlsx

PurposeTo evaluate the ability of texture features for distinguishing between benign and malignant testicular masses, and furthermore, for identifying primary testicular lymphoma in malignant tumors and identifying seminoma in testicular germ cell tumors, respectively.MethodsWe retrospectively collected 77 patients with an abdominal and pelvic enhanced computed tomography (CT) examination and a histopathologically confirmed testicular mass from a single center. The ROI of each mass was split into two parts by the largest cross-sectional slice and deemed to be two samples. After all processing steps, three-dimensional texture features were extracted from unenhanced and contrast-enhanced CT images. Excellent reproducibility of texture features was defined as intra-class correlation coefficient ≥0.8 (ICC ≥0.8). All the groups were balanced via the synthetic minority over-sampling technique (SMOTE) method. Dimension reduction was based on pearson correlation coefficient (PCC). Before model building, minimum-redundancy maximum-relevance (mRMR) selection and recursive feature elimination (RFE) were used for further feature selection. At last, three ML classifiers with the highest cross validation with 5-fold were selected: autoencoder (AE), support vector machine(SVM), linear discriminant analysis (LAD). Logistics regression (LR) and LR-LASSO were also constructed to compare with the ML classifiers.Results985 texture features with ICC ≥0.8 were extracted for further feature selection process. With the highest AUC of 0.946 (P ConclusionUntil now, this is the first study that applied CT texture analysis (CTTA) to assess the heterogeneity of testicular tumors. LR model based on CTTA might be a promising non-invasive tool for the diagnosis and differentiation of testicular masses. The accurate diagnosis of testicular masses would assist urologists in correct preoperative and perioperative decision making.</p

Additional file 1 of The practical clinical role of machine learning models with different algorithms in predicting prostate cancer local recurrence after radical prostatectomy

Supplementary Material

LD plot of the 20 SNPs in four genes in the control (left) and case (right) groups.

(a) LD plot of the 4 SNPs of the FAT3 gene in the control (left) and case (right) groups. (b) LD plot of the 4 SNPs of DLG2 gene in the control (left) and case (right) groups. (c) LD plot of the 6 SNPs of the KTN1 gene in the control (left) and case (right) groups. (d) LD plot of the 6 SNPs of the DCC gene in control (left) and case (right) groups. The values in squares are the D’ calculated using pair-wise analyses. Empty squares indicate D’ = 1 (i.e. complete LD between a pair of SNPs).</p

The frequencies of haplotypes in the four genes and their associations with the risk of heroin addiction.

The frequencies of haplotypes in the four genes and their associations with the risk of heroin addiction.</p

A Population-Based Study of Four Genes Associated with Heroin Addiction in Han Chinese

<div><p>Recent studies have shown that variants in FAT atypical cadherin 3 (<i>FAT3</i>), kinectin 1 (<i>KTN1</i>), discs large homolog2 (<i>DLG2</i>) and deleted in colorectal cancer (<i>DCC</i>) genes influence the structure of the human mesolimbic reward system. We conducted a systematic analysis of the potential functional single nucleotide polymorphisms (SNPs) in these genes associated with heroin addiction. We scanned the functional regions of these genes and identified 20 SNPs for genotyping by using the SNaPshot method. A total of 1080 samples, comprising 523 cases and 557 controls, were analyzed. We observed that <i>DCC</i> rs16956878, rs12607853, and rs2292043 were associated with heroin addiction. The T alleles of rs16956878 (<i>p</i> = 0.0004) and rs12607853 (<i>p</i> = 0.002) were significantly enriched in the case group compared with the controls. A lower incidence of the C allele of rs2292043 (<i>p</i> = 0.002) was observed in the case group. In block 2 of DCC (rs2292043-rs12607853-rs16956878), the frequency of the T-T-T haplotype was significantly higher in the case group than in the control group (<i>p</i> = 0.024), and fewer C-C-C haplotypes (<i>p</i> = 0.006) were detected in the case group. <i>DCC</i> may be an important candidate gene in heroin addiction, and rs16956878, rs12607853, and rs2292043 may be risk factors, thereby providing a basis for further genetic and biological research.</p></div

The results of gene-gene interactions using MDR.

<p>The results of gene-gene interactions using MDR.</p

Demographic and addiction characteristics of <i>DCC</i> SNP rs16956878.

<p>Demographic and addiction characteristics of <i>DCC</i> SNP rs16956878.</p

Demographic and addiction characteristics of <i>DCC</i> SNP rs16956878.

Demographic and addiction characteristics of DCC SNP rs16956878.</p

Genotypic and allelic frequencies of gene polymorphisms in the control and case group and statistical results.

<p>Genotypic and allelic frequencies of gene polymorphisms in the control and case group and statistical results.</p