Light-responsive antibacterial dissolving microneedles loaded with 5-aminolevulinic acid and silver nanoparticles for the treatment of acne.

Acne is a chronic inflammatory disease of pilosebaceous unit, which can be aggravated by hyperkeratosis of the pilosebaceous unit, excessive secretion of sebum and the proliferation of Propionibacterium acnes (P. acnes). Traditional drug treatment methods commonly exhibit drawbacks, including bacterial resistance and poor transdermal permeability, resulting in suboptimal efficacy and recurrent infections.

Global level of methylation in the sea lamprey (jawless vertebrate) genome is intermediate between invertebrate and jawed vertebrate genomes.

In eukaryotes, cytosine methylation is a primary heritable epigenetic modification of the genome that regulates many cellular processes. In invertebrate, methylated cytosine generally located on specific genomic elements (e.g.

Anciently duplicated genes continuously recruited to heart expression in vertebrate evolution are associated with heart chamber increase.

Although gene/genome duplications in the early stage of vertebrates have been thought to provide major resources of raw genetic materials for evolutionary innovations, it is unclear whether they continuously contribute to the evolution of morphological complexity during the course of vertebrate evolution, such as the evolution from two heart chambers (fishes) to four heart chambers (mammals and birds). We addressed this issue by our heart RNA-Seq experiments combined with published data, using 13 vertebrates and one invertebrate (sea squirt, as an outgroup). Our evolutionary transcriptome analysis showed that number of ancient paralogous genes expressed in heart tends to increase with the increase of heart chamber number along the vertebrate phylogeny, in spite that most of them were duplicated at the time near to the origin of vertebrates or even more ancient.

Co-delivery of drugs by adhesive transdermal patches equipped with dissolving microneedles for the treatment of rheumatoid arthritis.

In this study, a dosage form consisting of dissolving (D) microneedles (M) and an adhesive (A) transdermal patch (P; DMAP) was designed and pre-clinically evaluated for the treatment of rheumatoid arthritis (RA). The tip of the dissolving microneedles (DMNs) was loaded with the macromolecular drug melittin (Mel@DMNs), this to treat joint inflammation and bone damage, while the adhesive transdermal patches contained the low molecular weight drug diclofenac sodium (DS; DS@AP) for pain relief. Mel@DMNs and DS@AP were ingeniously connected through an isolation layer for compounding Mel-DS@DMAP for the simultaneous delivery of the drugs.

Simvastatin nanocrystals-based dissolving microneedles for wound healing.

Currently, one of the main problems encountered in wound healing therapy is related to inefficient drug delivery. However, dissolving microneedles (DMNs) can be administered percutaneously to effectively deliver a drug to a deep wound area. Simvastatin (SIM) can promote wound healing, albeit its insolubility in water limits its application.

Synthesis of multifunctional amorphous metallic shell on crystalline metallic nanoparticles.

Colloidal nanoparticles can be coated with a conformal shell to form multifunctional nanoparticles. For instance, plasmonic, magnetic, and catalytic properties, chemical stability and biocompatibility can be mixed and matched. Here, a facile synthesis for depositing metal boride amorphous coatings on colloidal metallic nanocrystals is introduced.

Genome distance and phylogenetic inference accommodating gene duplication, loss and new gene input.

With the rapid growth of entire genome data, phylogenomics focuses on analyzing evolutionary histories and relationships of species, i.e., the tree of life.

MATTE: a pipeline of transcriptome module alignment for anti-noise phenotype-gene-related analysis.

A phenotype may be associated with multiple genes that interact with each other in the form of a gene module or network. How to identify these relationships is one important aspect of comparative transcriptomics. However, it is still a challenge to align gene modules associated with different phenotypes.

Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools.

Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate.

5-aminolevulinic acid-loaded dissolving microneedle array for photodynamic therapy of rheumatoid arthritis on rats.

Photodynamic therapy (PDT) is a noninvasive technique that can be used to treat rheumatoid arthritis (RA) by irradiating photosensitizers with specific wavelengths of light to generate reactive oxygen species (ROS), thus leading to targeted cell necrosis. However, efficient delivery of photosensitizers with low side effects is a key issue. We developed a 5-aminolevulinic acid-loaded dissolving microneedle array (5-ALA@DMNA) that can locally and efficiently deliver photosensitizers for RA treatment by PDT.

TSNAdb v2.0: The Updated Version of Tumor-specific Neoantigen Database.

In recent years, neoantigens have been recognized as ideal targets for tumor immunotherapy. With the development of neoantigen-based tumor immunotherapy, comprehensive neoantigen databases are urgently needed to meet the growing demand for clinical studies. We have built the tumor-specific neoantigen database (TSNAdb) previously, which has attracted much attention.

MODIG: integrating multi-omics and multi-dimensional gene network for cancer driver gene identification based on graph attention network model.

Motivation: Identifying genes that play a causal role in cancer evolution remains one of the biggest challenges in cancer biology. With the accumulation of high-throughput multi-omics data over decades, it becomes a great challenge to effectively integrate these data into the identification of cancer driver genes.

Results: Here, we propose MODIG, a graph attention network (GAT)-based framework to identify cancer driver genes by combining multi-omics pan-cancer data (mutations, copy number variants, gene expression and methylation levels) with multi-dimensional gene networks.

Celecoxib nanocrystal-loaded dissolving microneedles with highly efficient for osteoarthritis treatment.

Osteoarthritis (OA) is a prevalent degenerative disease that has a significant impact on patients' lives. Celecoxib (CXB) is now primarily used to treat OA with oral dosing. CXB's limited water solubility, on the other hand, restricts its therapeutic application.

d/d-H, a New Test to Distinguish Different Selection Modes in Protein Evolution and Cancer Evolution.

One of the most popular measures in the analysis of protein sequence evolution is the ratio of nonsynonymous distance (d) to synonymous distance (d). Under the assumption that synonymous substitutions in the coding region are selectively neutral, the d/d ratio can be used to statistically detect the adaptive evolution (or purifying selection) if d/d > 1 (or d/d < 1) significantly. However, due to strong structural constraints and/or variable functional constraints imposed on amino acid sites, most encoding genes in most species have demonstrated d/d < 1.

A Simple Evolutionary Model of Genetic Robustness After Gene Duplication.

When a dispensable gene is duplicated (referred to the ancestral dispensability denoted by O), genetic buffering and duplicate compensation together maintain the duplicate redundancy, whereas duplicate compensation is the only mechanism when an essential gene is duplicated (referred to the ancestral essentiality denoted by O). To investigate these evolutionary scenarios of genetic robustness, I formulated a simple mixture model for analyzing duplicate pairs with one of the following states: double dispensable (DD), semi-dispensable (one dispensable one essential, DE), or double essential (EE). This model was applied to the yeast duplicate pairs from a whole-genome duplication (WGD) occurred about 100 million years ago (mya), and the mouse duplicate pairs from a WGD occurred about more than 500 mya.

Assembly of 97 Novel Bacterial Genomes in the Microbial Community Affiliated with Polyvinyl Alcohol in Soil of Northern China.

Background: Undeveloped ecosystems belong to rich source of microbial population, of which resources remain unearthed. A kind of polymeric compound system with high polyvinyl alcohol (PVA) content has been reported and named . Marker gene amplification showed that harbored little-explored microbial communities.

TSNAD v2.0: A one-stop software solution for tumor-specific neoantigen detection.

TSNAD is a one-stop software solution for predicting neoantigens from the whole genome/exome sequencing data of tumor-normal pairs. Here we present TSNAD v2.0 which provides several new features such as the function of RNA-Seq analysis including gene expression and gene fusion analysis, the support of different versions of the reference genome.

Random Penetrance of Mutations Among Individuals: A New Type of Genetic Drift in Molecular Evolution.

The determinative view of mutation penetrance is a fundamental assumption for the building of molecular evolutionary theory: individuals in the population with the same genotype have the same fitness effect. Since this view has been constantly challenged by experimental evidence, it is desirable to examine to what extent violation of this view could affect our understanding of molecular evolution. To this end, the author formulated a new theory of molecular evolution under a random model of penetrance: for any individual with the same mutational genotype, the coefficient of selection is a random variable.

Robust Adaptive Control for a Small Unmanned Helicopter Using Reinforcement Learning.

This article presents a novel adaptive controller for a small-size unmanned helicopter using the reinforcement learning (RL) control methodology. The helicopter is subject to system uncertainties and unknown external disturbances. The dynamic unmodeling uncertainties of the system are estimated online by the actor network, and the tracking performance function is optimized via the critic network.

Evolution and functional divergence of the ERBB receptor family.

The ERBB gene family plays an important role in cell proliferation and differentiation, and aberrant activations could result in tumorigenesis, which makes this gene family an attractive drug target in the area of precision oncology. Functional divergence analysis and conservation analysis were performed using ClustalW, MEGA7 and DIVERGE3 software. One hundred and forty five functional divergence residues sites, 94 totally conserved sites and averagely 345 conserved sites of individual gene member were obtained.

CanDriS: posterior profiling of cancer-driving sites based on two-component evolutionary model.

Current cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored. Due to the over-excess mutations unrelated to cancer, the great challenge is to identify somatic mutations that are cancer-driven. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model: while the ground component corresponds to passenger mutations, the rapidly evolving component corresponds to driver mutations.

The Impact of DNA Methylation Dynamics on the Mutation Rate During Human Germline Development.

DNA methylation is a dynamic epigenetic modification found in most eukaryotic genomes. It is known to lead to a high CpG to TpG mutation rate. However, the relationship between the methylation dynamics in germline development and the germline mutation rate remains unexplored.

DeepHLApan: A Deep Learning Approach for Neoantigen Prediction Considering Both HLA-Peptide Binding and Immunogenicity.

Neoantigens play important roles in cancer immunotherapy. Current methods used for neoantigen prediction focus on the binding between human leukocyte antigens (HLAs) and peptides, which is insufficient for high-confidence neoantigen prediction. In this study, we apply deep learning techniques to predict neoantigens considering both the possibility of HLA-peptide binding (binding model) and the potential immunogenicity (immunogenicity model) of the peptide-HLA complex (pHLA).