A model of multiple tumor marker for lymph node metastasis assessment in colorectal cancer: a retrospective study.

Background: Assessment of colorectal cancer (CRC) lymph node metastasis (LNM) is critical to the decision of surgery, prognosis, and therapy strategy. In this study, we aimed to develop and validate a multiple tumor marker nomogram for predicting LNM in CRC patients. Methods: A total of 674 patients who met the inclusion criteria were collected and randomly divided into primary cohort and internal test cohort at a ratio of 7:3. An external test cohort enrolled 178 CRC patients from the West China Hospital. Clinicopathologic variables were obtained from electronic medical records. The least absolute shrinkage and selection operator (LASSO) and interquartile range analysis were carried out for variable dimensionality reduction and feature selection. Multivariate logistic regression analysis was conducted to develop predictive models of LNM. The performance of the established models was evaluated by the receiver operating characteristic (ROC) curve, calibration belt, and clinical usefulness. Results: Based on minimum criteria, 18 potential features were reduced to six predictors by LASSO and interquartile range in the primary cohort. The model demonstrated good discrimination and ROC curve (AUC = 0.721 in the internal test cohort, AUC = 0.758 in the external test cohort) in LNM assessment. Good calibration was shown for the probability of CRC LNM in the internal and external test cohorts. Decision curve analysis illustrated that multi-tumor markers nomogram was clinically useful. Conclusions: The study proposed a reliable nomogram that could be efficiently and conveniently utilized to facilitate the assessment of individually-tailored LNM in patients with CRC, complementing imaging and biopsy tests.

Deep learning radiomics model related with genomics phenotypes for lymph node metastasis prediction in colorectal cancer.

BACKGROUND AND PURPOSE: The preoperative lymph node (LN) status is important for the treatment of colorectal cancer (CRC). Here, we established and validated a deep learning (DPL) model for predicting lymph node metastasis (LNM) in CRC. MATERIALS AND METHODS: A total of 423 CRC patients were divided into cohort 1 (training set, n = 238, testing set, n = 101) and cohort 2 (validation set, n = 84). Among them, 84 patients' tumour tissues were collected for RNA sequencing. The DPL features were extracted from enhanced venous-phase computed tomography of CRC using an autoencoder. A DPL model was constructed with the least absolute shrinkage and selection operator algorithm. Carcinoembryonic antigen and carbohydrate antigen 19-9 were incorporated into the DPL model to construct a combined model. The model performance was assessed by receiver operating characteristic curves, calibration curves and decision curves. The correlations between DPL features, which have been selected, and genes were analysed by Spearman' correlation, and the genes correlated with DPL features were used to transcriptomic analysis. RESULTS: The DPL model, integrated with 20 DPL features, showed a good discrimination performance in predicting the LNM, with areas under the curves (AUCs) of 0.79, 0.73 and 0.70 in the training set, testing set and validation set, respectively. The combined model had a better performance, with AUCs of 0.81, 0.77 and 0.73 in the three sets, respectively. Decision curve analysis confirmed the clinical application value of the DPL model and combined model. Furthermore, catabolic processes and immune-related pathways were identified and related with the selected DPL features. CONCLUSION: This study presented a DPL model and a combined model for LNM prediction. We explored the potential genomic phenotypes related with DPL features. In addition, the model could potentially be utilized to facilitate the individualized prediction of LNM in CRC.

Individualized Prediction of Colorectal Cancer Metastasis Using a Radiogenomics Approach.

Objectives: To evaluate whether incorporating the radiomics, genomics, and clinical features allows prediction of metastasis in colorectal cancer (CRC) and to develop a preoperative nomogram for predicting metastasis. Methods: We retrospectively analyzed radiomics features of computed tomography (CT) images in 134 patients (62 in the primary cohort, 28 in the validation cohort, and 44 in the independent-test cohort) clinicopathologically diagnosed with CRC at Dazhou Central Hospital from February 2018 to October 2019. Tumor tissues were collected from all patients for RNA sequencing, and clinical data were obtained from medical records. A total of 854 radiomics features were extracted from enhanced venous-phase CT of CRC. Least absolute shrinkage and selection operator regression analysis was utilized for data dimension reduction, feature screen, and radiomics signature development. Multivariable logistic regression analysis was performed to build a multiscale predicting model incorporating the radiomics, genomics, and clinical features. The receiver operating characteristic curve, calibration curve, and decision curve were conducted to evaluate the performance of the nomogram. Results: The radiomics signature based on 16 selected radiomics features showed good performance in metastasis assessment in both primary [area under the curve (AUC) = 0.945, 95% confidence interval (CI) 0.892-0.998] and validation cohorts (AUC = 0.754, 95% CI 0.570-0.938). The multiscale nomogram model contained radiomics features signatures, four-gene expression related to cell cycle pathway, and CA 19-9 level. The multiscale model showed good discrimination performance in the primary cohort (AUC = 0.981, 95% CI 0.953-1.000), the validation cohort (AUC = 0.822, 95% CI 0.635-1.000), and the independent-test cohort (AUC = 0.752, 95% CI 0.608-0.896) and good calibration. Decision curve analysis confirmed the clinical application value of the multiscale model. Conclusion: This study presented a multiscale model that incorporated the radiological eigenvalues, genomics features, and CA 19-9, which could be conveniently utilized to facilitate the individualized preoperatively assessing metastasis in CRC patients.

Hepatitis A virus-induced hsa-miR-146a-5p attenuates IFN-ß signaling by targeting adaptor protein TRAF6.

Hepatitis A virus (HAV), a unique hepatotropic human picornavirus, is the causative agent of acute hepatitis A in humans. Some studies have shown that HAV antagonizes the innate immune response by disrupting interferon-beta (IFN-ß) signaling by viral proteins. However, whether microRNAs (miRNAs), a class of non-coding RNAs, are involved in the antagonism of IFN-ß induction upon HAV infection is still unclear. In this study, we investigated the effects and mechanisms by which HAV-induced miRNAs antagonize IFN-ß signaling. A variety of analytical methods, including miRNA microarray, RT-qPCR, dual-luciferase reporter assay, and Western blotting, were performed using HAV-infected cells. The results indicated that HAV infection upregulates the expression of hsa-miR-146a-5p, which in turn partially suppresses the induction of IFN-ß synthesis, thereby promoting viral replication. Mechanistically, TRAF6 (TNF receptor-associated factor 6), a key adaptor protein in the RIG-I/MDA5-mediated IFN-I signaling pathway, is targeted and degraded by hsa-miR-146a-5p. As TRAF6 is necessary for IFN-ß induction, inhibition of this protein attenuates IFN-ß signaling. Taken together, the results from this study indicated that HAV disrupts RIG-I/MDA5-mediated IFN-I signaling partially through the cleavage of the essential adaptor molecule TRAF6 via hsa-miR-146a-5p.

A Novel Model Based on CXCL8-Derived Radiomics for Prognosis Prediction in Colorectal Cancer.

Introduction: Prognosis prediction is essential to improve therapeutic strategies and to achieve better clinical outcomes in colorectal cancer (CRC) patients. Radiomics based on high-throughput mining of quantitative medical imaging is an emerging field in recent years. However, the relationship among prognosis, radiomics features, and gene expression remains unknown. Methods: We retrospectively analyzed 141 patients (from study 1) diagnosed with CRC from February 2018 to October 2019 and randomly divided them into training (N = 99) and testing (N = 42) cohorts. Radiomics features in venous phase image were extracted from preoperative computed tomography (CT) images. Gene expression was detected by RNA-sequencing on tumor tissues. The least absolute shrinkage and selection operator (LASSO) regression model was used for selecting imaging features and building the radiomics model. A total of 45 CRC patients (study 2) with immunohistochemical (IHC) staining of CXCL8 diagnosed with CRC from January 2014 to October 2018 were included in the independent testing cohort. A clinical model was validated for prognosis prediction in prognostic testing cohort (163 CRC patients from 2014 to 2018, study 3). We performed a combined radiomics model that was composed of radiomics score, tumor stage, and CXCL8-derived radiomics model to make comparison with the clinical model. Results: In our study, we identified the CXCL8 as a hub gene in affecting prognosis, which is mainly through regulating cytokine-cytokine receptor interaction and neutrophil migration pathway. The radiomics model incorporated 12 radiomics features screened by LASSO according to CXCL8 expression in the training cohort and showed good performance in testing and IHC testing cohorts. Finally, the CXCL8-derived radiomics model combined with tumor stage performed high ability in predicting the prognosis of CRC patients in the prognostic testing cohort, with an area under the curve (AUC) of 0.774 [95% confidence interval (CI): 0.674-0.874]. Kaplan-Meier analysis of the overall survival probability in CRC patients stratified by combined model revealed that high-risk patients have a poor prognosis compared with low-risk patients (Log-rank P < 0.0001). Conclusion: We demonstrated that the radiomics model reflected by CXCL8 combined with tumor stage information is a reliable approach to predict the prognosis in CRC patients and has a potential ability in assisting clinical decision-making.

A Software-Defined Radio Receiver for Wireless Recording From Freely Behaving Animals.

To eliminate tethering effects on the small animals' behavior during electrophysiology experiments, such as neural interfacing, a robust and wideband wireless data link is needed for communicating with the implanted sensing elements without blind spots. We present a software-defined radio (SDR) based scalable data acquisition system, which can be programmed to provide coverage over standard-sized or customized experimental arenas. The incoming RF signal with the highest power among SDRs is selected in real-time to prevent data loss in the presence of spatial and angular misalignments between the transmitter (Tx) and receiver (Rx) antennas. A 32-channel wireless neural recording system-on-a-chip (SoC), known as WINeRS-8, is embedded in a headstage and transmits digitalized raw neural signals, which are sampled at 25 kHz/ch, at 9 Mbps via on-off keying (OOK) of a 434 MHz RF carrier. Measurement results show that the dual-SDR Rx system reduces the packet loss down to 0.12%, on average, by eliminating the blind spots caused by the moving Tx directionality. The system operation is verified in vivo on a freely behaving rat and compared with a commercial hardwired system.

An Inductively-Powered Wireless Neural Recording and Stimulation System for Freely-Behaving Animals.

An inductively-powered wireless integrated neural recording and stimulation (WINeRS-8) system-on-a-chip (SoC) that is compatible with the EnerCage-HC2 for wireless/battery-less operation has been presented for neuroscience experiments on freely behaving animals. WINeRS-8 includes a 32-ch recording analog front end, a 4-ch current-controlled stimulator, and a 434 MHz on - off keying data link to an external software- defined radio wideband receiver (Rx). The headstage also has a bluetooth low energy link for controlling the SoC. WINeRS-8/EnerCage-HC2 systems form a bidirectional wireless and battery-less neural interface within a standard homecage, which can support longitudinal experiments in an enriched environment. Both systems were verified in vivo on rat animal model, and the recorded signals were compared with hardwired and battery-powered recording results. Realtime stimulation and recording verified the system's potential for bidirectional neural interfacing within the homecage, while continuously delivering 35 mW to the hybrid WINeRS-8 headstage over an unlimited period.

Full-length genome and molecular characterization of dengue virus serotype 2 isolated from an imported patient from Myanmar.

BACKGROUND: Dengue is the most common mosquito-borne infection worldwide and a serious threat to global public health. Sporadic dengue virus serotype 2 (DENV-2) imported cases from Myanmar have been documented almost every year in Yunnan Province of China since 2005. However, the complete genome sequences of DENV-2 isolates imported from Myanmar are not available. METHODS: The full-length genome of the DENV-2 strain (YNPE2), isolated from an imported case from Myanmar in 2013, was identified by the next-generation sequencing. The extreme ends of the viral genome were validated by 5'/3' RACE and Sanger sequencing. Furthermore, phylogenetic, recombination and selection pressure analyses were conducted for the molecular characterization of YNPE2 strain. RESULTS: Whole-genome sequencing revealed that the full-length sequence of YNPE2 strain was 10,724 bases, with an open reading frame encoding for 3391 amino acids. The YNPE2 strain had 99.0% nucleotide identity and 99.8% amino acid identity with two closely related strains, ThD2_0078_01 strain (DQ181797) and DENV-2/TH/BID-V2157/200 strain (FJ639832). The phylogenetic analysis suggested that the YNPE2 strain belonged to Asian I genotype and was likely derived from Thailand strain (DQ181797). Moreover, selection pressure analysis revealed two amino acid sites of the NS4B and NS5 proteins, with important evidence of positive selection. CONCLUSION: This study revealed the first complete genome sequence and molecular characterization of a DENV-2 strain (YNPE2) isolated from an imported case from Myanmar, thus providing a valuable reference genome source for future surveillance, epidemiology and vaccine development of DENV-2 virus in Yunnan, China.

Complete Genome Sequence Analysis of an Imported Dengue Virus Serotype 1 Strain from Myanmar.

It has been determined that recent dengue virus epidemics in Yunnan, China, originated from Southeast Asian strains. Here, we report the first complete genome sequence and molecular characterization of the imported dengue virus serotype 1 strain YNPE1. Phylogenetic analysis revealed that strain YNPE1 belonged to genotype I.

Molecular characterization and phylogenetic analysis of a dengue virus serotype 3 isolated from a Chinese traveler returned from Laos.

BACKGROUND: Dengue virus (DENV) infection caused by international visitors has become a public health concern in China. Although sporadic imported cases of DENV have been documented in Yunnan, China since 2000, a complete genome sequence of dengue virus serotype 3 (DENV-3) imported from Laos is still not available. Here, we report the first complete genome sequence and genomic characterization of a DENV-3 strain (YNPE3) isolated from a patient returned from Laos. METHODS: Viral isolation from the patient's serum was performed using mosquitoes C6/36 cells. Reverse transcriptase polymerase chain reaction (RT-PCR) was used for identification and serotyping of the virus. The complete sequence was determined by Sanger dideoxy sequencing. Homology analysis was implemented by NCBI-BLAST. Multiple sequence alignment was performed using MegAlign module of the Lasergene 7 software package DNASTAR. MFOLD software was used to predict the RNA secondary structure of 5' untranslated region (UTR) and 3' UTR. Phylogenetic analysis, which was based on envelope gene and complete coding sequence, was performed by Maximum-Likelihood method. RESULTS: RT-PCR analysis confirmed that the virus belonged to dengue virus serotype 3, which was named YNPE3 strain. The full-length genome of the YNPE3 strain was 10,627 nucleotides (nts) with an open reading frame (ORF) encoding 3390 amino acids. Strain YNPE3 shared 98.6-98.8% nucleotide identity with the closely related strains isolated in India (JQ922556, KU216209, KU216208). We observed the deletion of about 40 nts in the 5' UTR and 3' UTR of strain YNPE3, and 11 nts (ACGCAGGAAGT) insertion that was present in the 3' UTR of YNPE3. Compared with prototype strain H87, abundant amino acid substitutions in the YNPE3 strain were observed. Phylogenetic analysis revealed that the YNPE3 strain belonged to genotype III of DENV-3, and that it might be closely related with genotype III strains isolated in Laos and India. CONCLUSIONS: This is the first report of the complete genome sequence and molecular characterization of a DENV-3 isolate imported from Laos. The presented results can further promote disease surveillance, and epidemiological and evolutionary studies of the DENV-3 in Yunnan province of China.

Deep RNA Sequencing Reveals a Repertoire of Human Fibroblast Circular RNAs Associated with Cellular Responses to Herpes Simplex Virus 1 Infection.

BACKGROUND/AIMS: Circular RNAs (circRNAs), a new class of regulators of gene expression, are involved in diverse physiological and pathogenic processes. However, their role in cellular responses to virus infection is yet unclear. METHODS: A human lung fibroblast cell line was infected or mock infected by herpes simplex virus 1 (HSV-1). Deep RNA sequencing was used to profile the global changes in circRNAs, genes, and miRNAs following HSV-1 infection. Altered circRNAs, genes, and miRNAs were validated using quantitative reverse transcription polymerase chain reaction (RT-qPCR). An integration analysis of circRNAs, genes, and miRNAs was applied to investigate the putative function of the dysregulated circRNAs. RESULTS: A total of 536 circRNAs, 3,885 genes, and 207 miRNAs were significantly dysregulated after HSV-1 infection. An integration analysis of circRNAs, genes, and miRNAs revealed the alleged involvement of dysregulated circRNAs in cellular responses to HSV-1 infection via the circRNA-miRNA-gene regulatory axis. These genes regulated by circRNAs were enriched to NOD-like receptor/JAK-STAT signaling pathway, and pathways of apoptosis, cell cycle progression, and cell death, all of which may be implicated in the viral pathogenesis and cellular immunity. CONCLUSIONS: These data present a comprehensive view for circRNAs induced by HSV-1 and their interplay with miRNAs and genes during HSV-1 infection, thus offering new insights into the mechanisms of interactions between HSV-1 and the host.

Molecular characterization of an imported dengue virus serotype 4 isolate from Thailand.

The epidemic of dengue virus infections has spread markedly in Yunnan province of China in recent years due to an increase in the number of imported dengue cases. To the best of our knowledge, the present study is the first to report a whole genome sequence and molecular characterization of an imported DENV-4 isolate from Thailand. The current strain, 2013JH285, has an RNA genome of 10,772 nucleotides that shares 99.0% nucleotide and 99.7% amino acid sequence identity with the 2013 Thailand strain CTI2-13. Phylogenetic analysis of the whole genome sequence revealed that the 2013JH285 strain belongs to genotype I of DENV-4. Recombination analysis suggested that the 2013JH285 strain originated from inter-genotypic recombination of DENV-4 strains. The new complete DENV-4 genome sequence reported here might contribute to further understanding of the molecular epidemiology and disease surveillance of DENV-4 in China.

Molecular cloning and functional characterization of cathepsin B from Nile tilapia (Oreochromis niloticus).

Cathepsin B (CatB) has been widely known for its hydrolytic ability and involvement in the innate immunity. However, the mechanism of CatB from teleosts participating in immunoregulation remains poorly understood; and the sequence of CatB from Nile tilapia (NtCatB) has not been cloned and characterized. In this study, the coding sequence of NtCatB was cloned, and then characterized by bioinformatic analysis and heterologous expression. The deduced amino acid sequence (330-aa) of NtCatB contains the representative features of CatB. Quantitative real-time PCR revealed the extensive mRNA expression of NtCatB in six tissues of healthy Nile tilapia, and its transcription level was significantly up-regulated after Streptococcus agalactiae challenge. NtCatB may interact with some immunological function proteins and take part in the regulatory pathway. These results suggest that NtCatB is likely to be involved in the immune reaction. The mature region (residues 79-328, mNtCatB) of NtCatB was cloned and transferred to pET-28a for expressing the recombinant protein. The purified recombinant mNtCatB was verified with the activity of 992.34 U mg-1 min-1 under the optimal condition using a substrate hydrolyzing assay. The recombinant cystatin-A1-like can effectively inhibit the activity of the recombinant mNtCatB, and their binding form was predicted by molecular docking. Our results contribute to elucidating the immunological functions of NtCatB.

Influence of androgen on myocardial apoptosis and expression of myocardial IR and IRS­1 in chronic heart failure rat models.

The present study aimed to investigate the effect of androgens on chronic heart failure (CHF) in a rat model. A total of 120 Sprague Dawley male rats were randomly divided into the following groups: (A) sham operation group, (B) castrated group, (C) heart failure (HF) group, (D) castrated + HF group, and (E) castrated + HF + testosterone (T) replacement therapy group. There were 20 rats in group A, and 25 rats in the other groups. Surgical castration was performed on groups B, D and E, and T replacement therapy was administered to group E. Groups C, D and E were treated with doxorubicin hydrochloride to prepare the CHF animal model. The insulin sensitivity index (ISI) was calculated from fasting blood glucose and fasting insulin levels. Echocardiography was performed. Venous blood was collected for plasma T level test. Myocardial tissue was used for apoptosis index analysis. The expression levels of myocardial insulin receptor (IR) and insulin receptor substrate­1 (IRS­1) were measured by reverse transcription semi­quantitative polymerase chain reaction. Compared with group A, the T level and ISI decreased, whereas the expression level of IR and IRS­1 were increased in the CHF group (P<0.05). Following castration, the T level and ISI were significantly decreased, and the expression of IR and IRS­1 were increased compared with the uncastrated CHF rats (P<0.01). Following androgen administration, the ISI increased, expression of IR and IRS­1 decreased, and the myocardial apoptosis index decreased (P<0.05). Taken together, these results demonstrated that androgen supplementation could improve insulin resistance and affect the expression of IR and IRS­1 in CHF, thereby reducing myocardial apoptosis and improving cardiac function.

Unique expression signatures of circular RNAs in response to DNA tumor virus SV40 infection.

Circular RNAs (circRNAs), identified as a class of widely expressed endogenous regulatory RNAs, are involved in diverse physiological and pathological processes. However, their role in viral pathogenesis and cellular antiviral response remains unexplored. In this study, a potent DNA tumor virus, simian virus 40 (SV40), was used as a model to investigate the viral influences on cellular circRNA transcriptome. Using RNA-seq, 15,241 putative circRNAs were identified de novo from 5,057 parental genes in monkey kidney-derived Vero cells. The expression of selected circRNAs was confirmed by reverse transcription-polymerase chain reaction and Sanger sequencing. Further analysis showed that most circRNAs comprised multiple exons, and most parental genes produced multiple circRNA isoforms. A total of 134 significantly dysregulated circRNAs, including 103 upregulated and 31 downregulated circRNAs, were found after SV40 infection. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that various cancer-related pathways, including p53 and Wnt pathway, could be affected by SV40 infection via the alteration of the circRNA hosting genes. Moreover, diverse cellular immune pathways, including Toll-like receptor pathway and Janus kinase-signal transducer and activator of transcription pathway, could also be affected by SV40 infection. An integrated circRNA-miRNA-gene analysis suggested the putative function of circRNAs as cellular and viral miRNA decoys to indirectly regulate the gene expression during SV40 infection. This study presented the first comprehensive expression and functional profile of circRNAs in response to SV40 infection, thus providing new insights into the mechanisms of viral pathogenesis and cellular immune response.