Instruction-responsive programmable assemblies with DNA origami block pieces.

DNA nanotechnology has created a wide variety of nanostructures that provide a reliable platform for nanofabrication and DNA computing. However, constructing programmable finite arrays that allow for easy pre-functionalization remains challenge. We aim to create more standardized and controllable DNA origami components, which could be assembled into finite-scale and more diverse superstructures driven by instruction sets.

Multitask Level-Based Learning Swarm Optimizer.

Evolutionary multitasking optimization (EMTO) is currently one of the hottest research topics that aims to utilize the correlation between tasks to optimize them simultaneously. Although many evolutionary multitask algorithms (EMTAs) based on traditional differential evolution (DE) and the genetic algorithm (GA) have been proposed, there are relatively few EMTAs based on particle swarm optimization (PSO). Compared with DE and GA, PSO has a faster convergence speed, especially during the later state of the evolutionary process.

Adaptive Bi-Operator Evolution for Multitasking Optimization Problems.

The field of evolutionary multitasking optimization (EMTO) has been a highly anticipated research topic in recent years. EMTO aims to utilize evolutionary algorithms to concurrently solve complex problems involving multiple tasks. Despite considerable advancements in this field, numerous evolutionary multitasking algorithms continue to use a single evolutionary search operator (ESO) throughout the evolution process.

Scalable DNA recognition circuits based on DNA strand displacement.

DNA is a kind of nano-molecule considered to be computable on the molecular level, and the precise Watson-Crick principle of base pairing has made it possible for DNA to be a novel computer material. The DNA strand displacement technology has greatly facilitated the development of DNA computing in both logical and intelligent computation. In this paper, we proposed and implemented a molecular recognition circuit based on DNA strand displacement, which can achieve recognition and summation functions.

A stochastic approach for co-evolution process of virus and human immune system.

Infectious diseases have long been a shaping force in human history, necessitating a comprehensive understanding of their dynamics. This study introduces a co-evolution model that integrates both epidemiological and evolutionary dynamics. Utilizing a system of differential equations, the model represents the interactions among susceptible, infected, and recovered populations for both ancestral and evolved viral strains.

Towards Chinese text and DNA shift encoding scheme based on biomass plasmid storage.

DNA, as the storage medium in organisms, can address the shortcomings of existing electromagnetic storage media, such as low information density, high maintenance power consumption, and short storage time. Current research on DNA storage mainly focuses on designing corresponding encoders to convert binary data into DNA base data that meets biological constraints. We have created a new Chinese character code table that enables exceptionally high information storage density for storing Chinese characters (compared to traditional UTF-8 encoding).

Mesenchymal Stem Cells Pretreated with Collagen Promote Skin Wound-Healing.

The existing treatment modalities for skin injuries mainly include dressings, negative-pressure wound treatment, autologous skin grafting, and high-pressure wound treatment. All of these therapies have limitations such as high time cost, the inability to remove inactivated tissue in a timely manner, surgical debridement, and oxygen toxicity. Mesenchymal stem cells have a unique self-renewal ability and wide differentiation potential, and they are one of the most promising stem cell types in cell therapy and have great application prospects in the field of regenerative medicine.

Using amino acid features to identify the pathogenicity of influenza B virus.

Background: Influenza B virus can cause epidemics with high pathogenicity, so it poses a serious threat to public health. A feature representation algorithm is proposed in this paper to identify the pathogenicity phenotype of influenza B virus.

Methods: The dataset included all 11 influenza virus proteins encoded in eight genome segments of 1724 strains.

Research on the Spatial Agglomeration Characteristics and Influencing Factors of Express Delivery Station Based on DNN.

In this paper, the POI data of 736 Cainiao stations in Nanjing is taken as the research sample. With the help of ArcGIS software, the standard deviation ellipse, spatial autocorrelation, average nearest neighbor, cold and hot spot analysis, nuclear density estimation, and other spatial analysis models are used to quantitatively characterize its business mode, spatial distribution characteristics, and equilibrium. Based on DNN, the spatial agglomeration characteristics and distribution directions of the Cainiao station in Nanjing were sorted out, the cold spots and hot spots of the spatial layout were identified, and the spatial differentiation rules and agglomeration patterns were revealed.

Melatonin treatment improves human umbilical cord mesenchymal stem cell therapy in a mouse model of type II diabetes mellitus via the PI3K/AKT signaling pathway.

Background: Mesenchymal stem cells (MSCs) are promising candidates for tissue regeneration and disease treatment. However, long-term in vitro passaging leads to stemness loss of MSCs, resulting in failure of MSC therapy. This study investigated whether the combination of melatonin and human umbilical cord mesenchymal stem cells (hUC-MSCs) was superior to hUC-MSCs alone in ameliorating high-fat diet and streptozocin (STZ)-induced type II diabetes mellitus (T2DM) in a mouse model.

Corrigendum: Melatonin Promotes the Therapeutic Effect of Mesenchymal Stem Cells on Type 2 Diabetes Mellitus by Regulating TGF-β Pathway.

[This corrects the article DOI: 10.3389/fcell.2021.

Melatonin Promotes the Therapeutic Effect of Mesenchymal Stem Cells on Type 2 Diabetes Mellitus by Regulating TGF-β Pathway.

Abundant evidence proves the therapeutic effect of adipose-derived mesenchymal stem cells (ADMSCs) in the treatment of diabetes mellitus. However, the problems have not been solved that viability of ADMSCs were inconsistent and the cells quickly undergo senescence after cell culture. In addition, the therapeutic effect of ADMSCs is still not satisfactory.

Prediction of pandemic risk for animal-origin coronavirus using a deep learning method.

Background: Coronaviruses can be isolated from bats, civets, pangolins, birds and other wild animals. As an animal-origin pathogen, coronavirus can cross species barrier and cause pandemic in humans. In this study, a deep learning model for early prediction of pandemic risk was proposed based on the sequences of viral genomes.

Predicting Cross-Species Infection of Swine Influenza Virus with Representation Learning of Amino Acid Features.

Swine influenza viruses (SIVs) can unforeseeably cross the species barriers and directly infect humans, which pose huge challenges for public health and trigger pandemic risk at irregular intervals. Computational tools are needed to predict infection phenotype and early pandemic risk of SIVs. For this purpose, we propose a feature representation algorithm to predict cross-species infection of SIVs.

Bin-based genome-wide association studies reveal superior alleles for improvement of appearance quality using a 4-way MAGIC population in rice.

Introduction: The multiparental population provides us the chance to identify superior alleles controlling a trait for genetic improvement. Genome wide association studies at bin level (bin-GWAS) are expected to be more power in QTL mapping than GWAS at SNP level (SNP-GWAS).

Objectives: This study is to estimate genetic effects of QTL conferring grain appearance quality in rice by SNP-GWAS and bin-GWAS, compare their power in QTL mapping and identify the superior alleles of all detected QTL from 4 parents for genetic improvement.

A systematic study of critical miRNAs on cells proliferation and apoptosis by the shortest path.

Background: MicroRNAs are a class of important small noncoding RNAs, which have been reported to be involved in the processes of tumorigenesis and development by targeting a few genes. Existing studies show that the imbalance between cell proliferation and apoptosis is closely related to the initiation and development of cancers. However, the impact of miRNAs on this imbalance has not been studied systematically.

A Systematic Way to Infer the Regulation Relations of miRNAs on Target Genes and Critical miRNAs in Cancers.

MicroRNAs (miRNAs) are a class of important non-coding RNAs, which play important roles in tumorigenesis and development by targeting oncogenes or tumor suppressor genes. One miRNA can regulate multiple genes, and one gene can be regulated by multiple miRNAs. To promote the clinical application of miRNAs, two fundamental questions should be answered: what's the regulatory mechanism of a miRNA to a gene, and which miRNAs are important for a specific type of cancer.

Using the spike protein feature to predict infection risk and monitor the evolutionary dynamic of coronavirus.

Background: Coronavirus can cross the species barrier and infect humans with a severe respiratory syndrome. SARS-CoV-2 with potential origin of bat is still circulating in China. In this study, a prediction model is proposed to evaluate the infection risk of non-human-origin coronavirus for early warning.

Efficient Gaussian sample specific network marker discovery and drug enrichment analysis validation.

Identifying stable gene markers at an individual level can help to understand the genetic mechanisms of each individual patient and accomplish personalized medicine. In this paper, we propose an efficient framework to identify sample-specific markers. Gene expression data first is transformed to a corresponding likelihood matrix to alleviate inherent noise besides adding population information to each sample.

Scoring amino acid mutation to predict pandemic risk of avian influenza virus.

Background: Avian influenza virus can directly cross species barriers and infect humans with high fatality. As antigen novelty for human host, the public health is being challenged seriously. The pandemic risk of avian influenza viruses should be analyzed and a prediction model should be constructed for virology applications.

Predicting interspecies transmission of avian influenza virus based on wavelet packet decomposition.

Using wavelet packet decomposition, the energy coefficients in the fifth level of viral protein sequences were achieved to predict interspecies transmission. Since avian-origin influenza viruses could have high sequence similarities with human-origin avian influenza virus and could have the phenotype of interspecies transmission, viral data should be filtered to prevent the misconduct of feature selection and false performance of predicting models. Considering the balance of data size, the empirical cut-off value 97% was used to screen avian-origin influenza virus with high sequence similarity.

Scoring Amino Acid Mutations to Predict Avian-to-Human Transmission of Avian Influenza Viruses.

Avian influenza virus (AIV) can directly cross species barriers and infect humans with high fatality. Using machine learning methods, the present paper scores the amino acid mutations and predicts interspecies transmission. Initially, 183 signature positions in 11 viral proteins were screened by the scores of five amino acid factors and their random forest rankings.

[Recent Advances in Vaccines and Drugs Against the Ebola Virus].

The Ebola virus belongs to the Filovirus family, which causes Ebola hemorrhagic fever (mortality, 25%-90%). An outbreak of infection by the Ebola virus is sweeping across West Africa, leading to high mortality and worldwide panic. The Ebola virus has caused a serious threat to public health, so intensive scientific studies have been carried out.

The Complete Genome of a New Betabaculovirus from Clostera anastomosis.

Clostera anastomosis (Lepidoptera: Notodontidae) is a defoliating forest insect pest. Clostera anastomosis granulovirus-B (ClasGV-B) belonging to the genus Betabaculovirus of family Baculoviridae has been used for biological control of the pest. Here we reported the full genome sequence of ClasGV-B and compared it to other previously sequenced baculoviruses.