Comprehensive Evaluation of Quality and Differences in Franch from Different Origins Based on UPLC-ZENO-Q-TOF-MS/MS Compounds Analysis and Antioxidant Capacity.

Franch is mainly produced in southwest China. The region has a vast area and rich climate, which has an impact on the quality of the plants due to the differences in distribution between the origins. There is a lack of systematic research on its chemical compounds in the existing literature, and fewer studies have been reported for the active compounds of this plant.

Spatial multi-omics at subcellular resolution via high-throughput in situ pairwise sequencing.

Technology for spatial multi-omics aids the discovery of new insights into cellular functions and disease mechanisms. Here we report the development and applicability of multi-omics in situ pairwise sequencing (MiP-seq), a method for the simultaneous detection of DNAs, RNAs, proteins and biomolecules at subcellular resolution. Compared with other in situ sequencing methods, MiP-seq enhances decoding capacity and reduces sequencing and imaging costs while maintaining the efficacy of detection of gene mutations, allele-specific expression and RNA modifications.

MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing.

Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification.

Deep learning for detecting visually impaired cataracts using fundus images.

To develop a visual function-based deep learning system (DLS) using fundus images to screen for visually impaired cataracts. A total of 8,395 fundus images (5,245 subjects) with corresponding visual function parameters collected from three clinical centers were used to develop and evaluate a DLS for classifying non-cataracts, mild cataracts, and visually impaired cataracts. Three deep learning algorithms (DenseNet121, Inception V3, and ResNet50) were leveraged to train models to obtain the best one for the system.

Decoding the spatial chromatin organization and dynamic epigenetic landscapes of macrophage cells during differentiation and immune activation.

Immunocytes dynamically reprogram their gene expression profiles during differentiation and immunoresponse. However, the underlying mechanism remains elusive. Here, we develop a single-cell Hi-C method and systematically delineate the 3D genome and dynamic epigenetic atlas of macrophages during these processes.

Infection Analysis (iSFA) Identified Coronavirus Infection and Potential Transmission Risk in Mammals.

Coronaviruses are a great source of threat to public health which could infect various species and cause diverse diseases. However, the epidemic's spreading among different species remains elusive. This study proposed an infection analysis (iSFA) system that includes pathogen genome or transcript mining in transcriptome data of the potential host and performed a comprehensive analysis about the infection of 38 coronaviruses in wild animals, based on 2,257 transcriptome datasets from 89 mammals' lung and intestine, and revealed multiple potential coronavirus infections including porcine epidemic diarrhea virus (PEDV) infection in .

Neuron-derived neuropeptide Y fine-tunes the splenic immune responses.

The nervous and immune systems are closely entwined to maintain the immune balance in health and disease. Here, we showed that LPS can activate suprarenal and celiac ganglia (SrG-CG) neurons and upregulate NPY expression in rats. Single-cell sequencing analysis revealed that knockdown of the NPY gene in SrG-CG altered the proliferation and activation of splenic lymphocytes.

Reprogramming Mycobacterium tuberculosis CRISPR System for Gene Editing and Genome-wide RNA Interference Screening.

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), which is still the leading cause of mortality from a single infectious disease worldwide. The development of novel anti-TB drugs and vaccines is severely hampered by the complicated and time-consuming genetic manipulation techniques for M. tuberculosis.

Improved Prediction of Regulatory Element Using Hybrid Abelian Complexity Features with DNA Sequences.

: Deciphering the code of -regulatory element (CRE) is one of the core issues of current biology. As an important category of CRE, enhancers play crucial roles in gene transcriptional regulations in a distant manner. Further, the disruption of an enhancer can cause abnormal transcription and, thus, trigger human diseases, which means that its accurate identification is currently of broad interest.

A directed learning strategy integrating multiple omic data improves genomic prediction.

Genomic prediction (GP) aims to construct a statistical model for predicting phenotypes using genome-wide markers and is a promising strategy for accelerating molecular plant breeding. However, current progress of phenotype prediction using genomic data alone has reached a bottleneck, and previous studies on transcriptomic and metabolomic predictions ignored genomic information. Here, we designed a novel strategy of GP called multilayered least absolute shrinkage and selection operator (MLLASSO) by integrating multiple omic data into a single model that iteratively learns three layers of genetic features (GFs) supervised by observed transcriptome and metabolome.

Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in Human.

DNA methylation plays a significant role in transcriptional regulation by repressing activity. Change of the DNA methylation level is an important factor affecting the expression of target genes and downstream phenotypes. Because current experimental technologies can only assay a small proportion of CpG sites in the human genome, it is urgent to develop reliable computational models for predicting genome-wide DNA methylation.

Accumulation of urinary 2-thiothiazolidine-4-carboxylic acid (TTCA) among workers occupationally exposed to carbon disulfide for 1 week.

Objectives: To investigate if carbon disulfide (CS(2)) accumulates after a 1-week exposure period, and how the work-shift duration and exposure magnitude affects this accumulation for the workers in viscose rayon industry.

Methods: Six 8-h and seven 12-h workers in the spinning department historically known to be exposed to high air CS(2) were recruited as the exposed groups. Seven workers from other non-CS(2)-exposed departments were recruited as non-exposure controls.