A Category of Genes

Understanding how genes interact and relate to each other is a fundamental question in biology. However, current practices for describing these relationships, such as drawing diagrams or graphs in a somewhat arbitrary manner, limit our ability to integrate various aspects of the gene functions and view the genome holistically. To overcome these limitations, we need a more appropriate way to describe the intricate relationships between genes. Interestingly, category theory, an abstract field of mathematics seemingly unrelated to biology, has emerged as a powerful language for describing relations in general. We propose that category theory could provide a framework for unifying our knowledge of genes and their relationships. As a starting point, we construct a category of genes, with its morphisms abstracting various aspects of the relationships betweens genes. These relationships include, but not limited to, the order of genes on the chromosomes, the physical or genetic interactions, the signalling pathways, the gene ontology causal activity models (GO-CAM) and gene groups. Previously, they were encoded by miscellaneous networks or graphs, while our work unifies them in a consistent manner as a category. By doing so, we hope to view the relationships between genes systematically. In the long run, this paves a promising way for us to understand the fundamental principles that govern gene regulation and function.Comment: 13 pages, 6 figures, 1 tabl

Mechanism design and kinematics analysis of multifunctional waist rehabilitation bed

A multifunctional waist rehabilitation bed is designed for the traction therapy of human spine and gait rehabilitation training. The rehabilitation bed has four degrees of freedom, the rotation in the x, y, and z axis, and the movement in the z axis, which realizes traction treatment of lumbar spine rotation around coronal axis, vertical axis, sagittal axis and gait rehabilitation training. Considering the stability and safety during the rehabilitation process, the kinematic model of coronal-axis-rotation part, vertical-axis-rotation part and rehabilitation bed are established. Using MATLAB, the model and numerical simulation were carried out to obtain the curve of joint change when the waist rehabilitation bed was used for different functions, which verifies the effectiveness of the mechanism

AMD-DBSCAN: An Adaptive Multi-density DBSCAN for datasets of extremely variable density

DBSCAN has been widely used in density-based clustering algorithms. However, with the increasing demand for Multi-density clustering, previous traditional DSBCAN can not have good clustering results on Multi-density datasets. In order to address this problem, an adaptive Multi-density DBSCAN algorithm (AMD-DBSCAN) is proposed in this paper. An improved parameter adaptation method is proposed in AMD-DBSCAN to search for multiple parameter pairs (i.e., Eps and MinPts), which are the key parameters to determine the clustering results and performance, therefore allowing the model to be applied to Multi-density datasets. Moreover, only one hyperparameter is required for AMD-DBSCAN to avoid the complicated repetitive initialization operations. Furthermore, the variance of the number of neighbors (VNN) is proposed to measure the difference in density between each cluster. The experimental results show that our AMD-DBSCAN reduces execution time by an average of 75% due to lower algorithm complexity compared with the traditional adaptive algorithm. In addition, AMD-DBSCAN improves accuracy by 24.7% on average over the state-of-the-art design on Multi-density datasets of extremely variable density, while having no performance loss in Single-density scenarios. Our code and datasets are available at https://github.com/AlexandreWANG915/AMD-DBSCAN.Comment: Accepted at DSAA202

Suppressed N fixation and diazotrophs after four decades of fertilization

Background: N fixation is one of the most important microbially driven ecosystem processes on Earth, allowing N to enter the soil from the atmosphere, and regulating plant productivity. A question that remains to be answered is whether such a fundamental process would still be that important in an over-fertilized world, as the long-term effects of fertilization on N fixation and associated diazotrophic communities remain to be tested. Here, we used a 35-year fertilization experiment, and investigated the changes in N fixation rates and the diazotrophic community in response to long-term inorganic and organic fertilization. Results: It was found that N fixation was drastically reduced (dropped by 50%) after almost four decades of fertilization. Our results further indicated that functionality losses were associated with reductions in the relative abundance of keystone and phylogenetically clustered N fixers such as Geobacter spp. Conclusions: Our work suggests that long-term fertilization might have selected against N fixation and specific groups of N fixers. Our study provides solid evidence that N fixation and certain groups of diazotrophic taxa will be largely suppressed in a more and more fertilized world, with implications for soil biodiversity and ecosystem functions

Analysis of single-cell RNAseq identifies transitional states of T cells associated with hepatocellular carcinoma

BACKGROUND: Exhausted T cells and regulatory T cells (Tregs) comprise diverse subsets of tumor immunosuppressive microenvironment that play key roles in tumor progress. Understanding subset diversity in T cells is a critical question for developing cancer immunotherapy. METHODS: A total of 235 specimens from surgical resections of hepatocellular carcinoma (HCC) patients were examined for infiltration of exhausted T cell (Tex) in tumor and adjacent tissue. We conducted deep single-cell targeted immune profiling on CD3 RESULTS: We observed transitional differentiation of exhausted CD8 CONCLUSIONS: T cell exhaustion is a progressive process, and the gene-expression profiling displayed T cell exhaustion and anergy are different. Accordingly, it is possible that functional exhaustion is caused by the combination effects of passive defects and overactivation in stress response. The results help to understand the dynamic framework of T cells function in cancer which is important for designing rational cancer immunotherapies

CMTr cap-adjacent 2′-O-ribose mRNA methyltransferases are required for reward learning and mRNA localization to synapses

Cap-adjacent nucleotides of animal, protist and viral mRNAs can be O-methylated at the 2‘ position of the ribose (cOMe). The functions of cOMe in animals, however, remain largely unknown. Here we show that the two cap methyltransferases (CMTr1 and CMTr2) of Drosophila can methylate the ribose of the first nucleotide in mRNA. Double-mutant flies lack cOMe but are viable. Consistent with prominent neuronal expression, they have a reward learning defect that can be rescued by conditional expression in mushroom body neurons before training. Among CMTr targets are cell adhesion and signaling molecules. Many are relevant for learning, and are also targets of Fragile X Mental Retardation Protein (FMRP). Like FMRP, cOMe is required for localization of untranslated mRNAs to synapses and enhances binding of the cap binding complex in the nucleus. Hence, our study reveals a mechanism to co-transcriptionally prime mRNAs by cOMe for localized protein synthesis at synapses