Deep Canonical Correlation Fusion Algorithm Based on Denoising Autoencoder for ASD Diagnosis and Pathogenic Brain Region Identification.

Autism Spectrum Disorder (ASD) is defined as a neurodevelopmental condition distinguished by unconventional neural activities. Early intervention is key to managing the progress of ASD, and current research primarily focuses on the use of structural magnetic resonance imaging (sMRI) or resting-state functional magnetic resonance imaging (rs-fMRI) for diagnosis. Moreover, the use of autoencoders for disease classification has not been sufficiently explored. In this study, we introduce a new framework based on autoencoder, the Deep Canonical Correlation Fusion algorithm based on Denoising Autoencoder (DCCF-DAE), which proves to be effective in handling high-dimensional data. This framework involves efficient feature extraction from different types of data with an advanced autoencoder, followed by the fusion of these features through the DCCF model. Then we utilize the fused features for disease classification. DCCF integrates functional and structural data to help accurately diagnose ASD and identify critical Regions of Interest (ROIs) in disease mechanisms. We compare the proposed framework with other methods by the Autism Brain Imaging Data Exchange (ABIDE) database and the results demonstrate its outstanding performance in ASD diagnosis. The superiority of DCCF-DAE highlights its potential as a crucial tool for early ASD diagnosis and monitoring.

Multi-kernel Learning Fusion Algorithm Based on RNN and GRU for ASD Diagnosis and Pathogenic Brain Region Extraction.

Autism spectrum disorder (ASD) is a complex, severe disorder related to brain development. It impairs patient language communication and social behaviors. In recent years, ASD researches have focused on a single-modal neuroimaging data, neglecting the complementarity between multi-modal data. This omission may lead to poor classification. Therefore, it is important to study multi-modal data of ASD for revealing its pathogenesis. Furthermore, recurrent neural network (RNN) and gated recurrent unit (GRU) are effective for sequence data processing. In this paper, we introduce a novel framework for a Multi-Kernel Learning Fusion algorithm based on RNN and GRU (MKLF-RAG). The framework utilizes RNN and GRU to provide feature selection for data of different modalities. Then these features are fused by MKLF algorithm to detect the pathological mechanisms of ASD and extract the most relevant the Regions of Interest (ROIs) for the disease. The MKLF-RAG proposed in this paper has been tested in a variety of experiments with the Autism Brain Imaging Data Exchange (ABIDE) database. Experimental findings indicate that our framework notably enhances the classification accuracy for ASD. Compared with other methods, MKLF-RAG demonstrates superior efficacy across multiple evaluation metrics and could provide valuable insights into the early diagnosis of ASD.

Metagenomic sequencing revealed the potential of banknotes as a repository of microbial genes.

BACKGROUND: Genetic resources are important natural assets. Discovery of new enzyme gene sequences has been an ongoing effort in biotechnology industry. In the genomic age, genomes of microorganisms from various environments have been deciphered. Increasingly, it has become more and more difficult to find novel enzyme genes. In this work, we attempted to use the easily accessible banknotes to search for novel microbial gene sequences. RESULTS: We used high-throughput genomic sequencing technology to comprehensively characterize the diversity of microorganisms on the US dollars and Chinese Renminbis (RMBs). In addition to finding a vast diversity of microbes, we found a significant number of novel gene sequences, including an unreported superoxide dismutase (SOD) gene, whose catalytic activity was further verified by experiments. CONCLUSIONS: We demonstrated that banknotes could be a good and convenient genetic resource for finding economically valuable biologicals.

Cas9 Protein Triggers Differential Expression of Inherent Genes Especially NGFR Expression in 293T Cells.

INTRODUCTION: CRISPR/CAS9 systems, which can be utilized in vitro biological experiments, have recently captured much attention for their important roles and benefits. However, full realization of the potential of CRISPR/CAS9 approaches requires addressing many challenges and side effects. The expression of genes and potential side effects of CRISPR/CAS9 in human cells remains to be elucidated. The aim of our study was to explore the effect of CRISPR/CAS9 on gene expression in 293T cells. METHODS: A Cas9-expressing PX458 plasmid and Cas9-deactivated PX458-T2A plasmid were used to study the role of CRISPR/CAS9 on regulating gene expression in 293T cells. Gene expression in 293T cells after transfection of the PX458 plasmid or PX458-T2A plasmid was detected by RNA sequencing and correlative statistical analysis. Differential gene expression in both PX458 transfected 293T cells and PX458-T2A transfected 293T cells compared with normal 293T cells was detected using quantitative reverse transcription polymerase chain reaction (RT qPCR). The mRNA and protein levels were measured using reverse transcription PCR and Western blot. Co-IP assay combined with shotgun LC-MS/MS were used to investigate the differences of NGFR-interaction proteins between PX458 transfected 293T cells and PX458-T2A transfected 293T cells. RESULTS: In this study, we observed that PX458 plasmid transfection and Cas9 expression can affect the expression of different genes, including FOSB (FBJ murine osteosarcoma viral oncogene homolog B), IL-11 (Interleukin-11), MMP1 (matrix metalloproteinase), CYP2D6 (CytochromeP4502D6), and NGFR (matrix metalloproteinase 1). Downregulation of NGFR after PX458 transfection was confirmed by RT qPCR and western blot analysis. NGFR expression was significantly lower in PX458 transfected 293T cells than in normal 293T cells and PX458-T2A transfected 293T cells. The co-IP dilutions analyzed by shotgun LC-MS/MS showed a total of 183 proteins interact with NGFR in PX458 transfected 293T cells while 221 proteins interact with NGFR were identified in PX458-T2A transfected 293T cells using the MASCOT engine. CONCLUSIONS: Cas9 expression by transfection of the PX458 plasmid was negatively correlated with the NGFR mRNA level and NGFR protein expression in 293T cells, while PX458-T2A, in which Cas9 is deactivated, did not affect NGFR expression. The decrease in NGFR expression also affects the amount of proteins that interact with NGFR. These results suggest that the effect of Cas9 on NGFR expression and the expression of other genes should be noticed when developing cell-based studies and therapies utilizing CRISPR/CAS9 systems.

Rapid detection of low-level HeLa cell contamination in cell culture using nested PCR.

HeLa cells are a commonly used cell line in many biological research areas. They are not picky for culture medium and proliferate rapidly. HeLa cells are a notorious source of cell cross-contamination and have been found to be able to contaminate a wide range of cell lines in cell culture. In this study, we reported a simple and efficient method for detecting the presence of HeLa cell contamination in cell culture. HPV-18 was used as a biomarker. The cell culture supernatant was used directly as the template for nested PCR without extracting nucleic acid. By PCR amplification of the cell culture supernatant with the designed primers, we were able to detect the presence of HeLa cells in the culture. The sensitivity of this method can reach 1%, which is 10-fold higher than Short tandem repeat sequence (STR) profiling. This simple, rapid, and "noninvasive" quality checking method should find applications in routine cell culture practice.

[Design of Smart Care Tele-Monitoring System for Mother and Fetus].

OBJECTIVE: To study and design a maternal and fetal monitoring system based on the cloud computing and internet of things, which can monitor and take smart care of the mother and fetus in 24 h. METHODS: Using a new kind of wireless fetal monitoring detector and a mobile phone, thus the doctor can keep touch with hospital through internet. The mobile terminal was developed on the Android system, which accepted the data of fetal heart rate and uterine contraction transmitted from the wireless detector, exchange information with the server and display the monitoring data and the doctor's advice in real-time. RESULTS: The mobile phone displayed the fetal heart rate line and uterine contraction line in real-time, recorded the fetus' grow process. It implemented the real-time communication between the doctor and the user, through wireless communication technology. CONCLUSIONS: The system removes the constraint of traditional telephone cable for users, while the users can get remote monitoring from the medical institutions at home or in the nearest community at any time, providing health and safety guarantee for mother and fetus.