Correlation analysis between language gene polymorphism and geography/society parameter from twenty-six countries

Human language diversity, as a biological phenotype, shall be genetically linked with language gene polymorphism. Meanwhile, this phenotype is historically shaped by local geographical/social factors. But how many language gene polymorphisms have direct correlations with some geography/society characteristics during the long-run evolution of human languages is an interesting question and largely remains uninvestigated. This study selected a series of geography/society factors (including 13 geographical factors and 21 social factors) from 26 countries and 111 single nucleotide polymorphisms (SNPs) randomly selected from 13 language genes. Principal component analysis (PCA) was performed to explore their potential correlations. Preliminary but interesting results were obtained as follow. (1) Most geographical parameters are concentrated into one cluster in the PCA diagram. The cluster contains 12 parameters that are positively correlated with each other; (2) PCA diagrams divide social parameters into four clusters, among which exist positive and negative correlations; (3) The strongest positive correlations were observed at one of ATP2C2 gene SNPs (ATP-1: rs78371901); the strongest negative correlations were found at one of NFXL1 gene SNPs (NFX-6: rs1440228); and the least correlations with language gene SNPs were observed at four geography/society factors: aash (Annual average rainfall), fore (Forest coverage), pden (Population density of the country) and rway (Runway traffic mode).

PhenClust, a standalone tool for identifying trends within sets of biological phenotypes using semantic similarity and the Unified Medical Language System metathesaurus

Objectives We sought to cluster biological phenotypes using semantic similarity and create an easy-to-install, stable, and reproducible tool. Materials and Methods We generated Phenotype Clustering (PhenClust)—a novel application of semantic similarity for interpreting biological phenotype associations—using the Unified Medical Language System (UMLS) metathesaurus, demonstrated the tool’s application, and developed Docker containers with stable installations of two UMLS versions. Results PhenClust identified disease clusters for drug network-associated phenotypes and a meta-analysis of drug target candidates. The Dockerized containers eliminated the requirement that the user install the UMLS metathesaurus. Discussion Clustering phenotypes summarized all phenotypes associated with a drug network and two drug candidates. Docker containers can support dissemination and reproducibility of tools that are otherwise limited due to insufficient software support. Conclusion PhenClust can improve interpretation of high-throughput biological analyses where many phenotypes are associated with a query and the Dockerized PhenClust achieved our objective of decreasing installation complexity.

Changing biological behaviour of NETs during the evolution of the disease: progress on progression

Following improvements in the management and outcome of neuroendocrine neoplasms (NENs) in recent years, we see a subset, particularly of pancreatic NENs, which become more aggressive during the course of the disease. This is reflected by an increase in the Ki-67 labelling index, as a marker of proliferation, which may lead to an occasion of increase in grading, but generally does not appear to be correlated with histologically confirmed dedifferentiation. A systematic review of the literature was performed in PubMed, Cochrane Library, and Embase until May 2020 to identify cases that have behaved in such a manner. We screened 244 articles: only seven studies included cases in their cohort, or in a subset of the cohort studied, with a proven increase in the Ki-67 during follow-up through additional biopsy. In addition to these studies, we have also tried to identify possible pathophysiological mechanisms implicated in advanced NENs, although currently no studies appear to have addressed the mechanisms implicated in the switch to a more aggressive biological phenotype over the course of the disease. Such progression of the disease course may demand a change in the management. Summarising the overall evidence, we suggest that future studies should concentrate on changes in the molecular pathways during disease progression with sequential biopsies in order to shed light on the mechanisms that render a neoplasm more aggressive than its initial phenotype or genotype.

Insights Into Exosomal Non-Coding RNAs Sorting Mechanism and Clinical Application

Exosomes are natural nanoscale bilayer phospholipid vesicles that can be secreted by almost all types of cells and are detected in almost all types of body fluids. Exosomes are effective mediators of cell–cell signaling communication because of their ability to carry and transfer a variety of bioactive molecules, including non-coding RNAs. Non-coding RNAs have also been found to exert strong effects on a variety of biological processes, including tumorigenesis. Many researchers have established that exosomes encapsulate bioactive non-coding RNAs that alter the biological phenotype of specific target cells in an autocrine or a paracrine manner. However, the mechanism by which the producer cells package non-coding RNAs into exosomes is not well understood. This review focuses on the current research on exosomal non-coding RNAs, including the biogenesis of exosomes, the possible mechanism of sorting non-coding RNAs, their biological functions, and their potential for clinical application in the future.

Confinement discerns swarmers from planktonic bacteria

Powered by flagella, many bacterial species exhibit collective motion on a solid surface commonly known as swarming. As a natural example of active matter, swarming is also an essential biological phenotype associated with virulence, chemotaxis, and host pathogenesis. Physical changes like cell elongation and hyper flagellation have been shown to accompany the swarming phenotype. Less studied, however, are the contrasts of collective motion between the swarming cells and their counterpart planktonic cells of comparable cell density. Here, we show that confining bacterial movement in circular microwells allows distinguishing bacterial swarming from collective swimming. On a soft agar plate, a novel bacterial strain Enterobacter sp. SM3 in swarming and planktonic states exhibited different motion patterns when confined to circular microwells of a specific range of sizes. When the confinement diameter was between 40 μm and 90 μm, swarming SM3 formed a single swirl motion pattern in the microwells whereas planktonic SM3 formed multiple swirls. Similar differential behavior is observed across several other species of gram-negative bacteria. We also observed 'rafting behavior' of swarming bacteria upon dilution. We hypothesize that the rafting behavior might account for the motion pattern difference. We were able to predict these experimental features via numerical simulations where swarming cells are modeled with stronger cell-cell alignment interaction. Our experimental design using PDMS microchip disk arrays enabled us to observe bacterial swarming on murine intestinal surface suggesting a new method for characterizing bacterial swarming under complex environments, such as in polymicrobial niches, and for in vivo swarming exploration.

Evaluation of the effects of human dental pulp stem cells on the biological phenotype of hypertrophic keloid fibroblasts

Background Despite numerous existing treatments for keloids, the responses in the clinic have been disappointing due to either low efficacy or side effects. Numerous studies dealing with preclinical and clinical trials have been published about effective therapies for fibrotic diseases using mesenchymal stem cells, However, no research has yet been reported to scientifically investigate the effect of HDPSCs on the treatment of keloids.The objective is to provide an experimental basis to provide a novel proposal for the application of stem cells in the treatment of keloids.Methods HNFs and HKFs were cultured alone and in combination with DPSCs using a trans-well cell-contact-independent cell culture system. The effects of DPSCs on HKFs were tested using CCK-8 assay, Live/dead staining assay, quantitative polymerase chain reaction, Western blot．Result DPSCs don’t inhibited HKFs and HNFs proliferation and induce apoptosis, but inhibited migration. Furthermore, DPSCs significantly decreased expression of profibrotic genes, transforming growth factor-β 1，and transforming growth factor-β 2. DPSCs suppressed the ECM synthesis in HKFs, as indicated by decreased expression of collagen I and fibronectin and low levels of hydroxyproline in cell culture supernatant． Conclusions 1) Co-culture of DPSCs inhibits the migration of HKFs but does not affect the proliferation and apoptosis of HKFs.2) DPSCs co-culture inhibits the expression of pro-fibrotic genes and promotes the expression of anti-fibrotic genes in HKFs.3) DPSCs co-culture inhibits the synthesis of extracellular matrix by HKFs.

High-throughput analysis of B3GLCT regulation predicts phenotype of Peters' Plus Syndrome in line with the miRNA Proxy Hypothesis

MicroRNAs (miRNAs, miRs) finely tune protein expression and target networks of 100s-1000s of genes that control specific biological processes. They are critical regulators of glycosylation, one of the most diverse and abundant posttranslational modifications. In recent work, miRs have been shown to predict the biological functions of glycosylation enzymes, leading to the miRNA proxy hypothesis which states, if a miR drives a specific biological phenotype, the targets of that miR will drive the same biological phenotype. Testing of this powerful hypothesis is hampered by our lack of knowledge about miR targets. Target prediction suffers from low accuracy and a high false prediction rate. Herein, we develop a high-throughput experimental platform to analyze miR:target interactions, miRFluR. We utilize this system to analyze the interactions of the entire human miRome with beta-3-glucosyltransferase (B3GLCT), a glycosylation enzyme whose loss underpins the congenital disorder Peters Plus Syndrome. Although this enzyme is predicted by multiple algorithms to be highly targeted by miRs, we identify only 27 miRs that downregulate B3GLCT, a >96% false positive rate for prediction. Functional enrichment analysis of these validated miRs predict phenotypes associated with Peters Plus Syndrome, although B3GLCT is not in their known target network. Thus, biological phenotypes driven by B3GLCT may be driven by the target networks of miRs that regulate this enzyme, providing additional evidence for the miRNA Proxy Hypothesis.

Evaluation of the effects of human dental pulp stem cells on the biological phenotype of hypertrophic keloid fibroblasts

Background Despite numerous existing treatments for keloids, the responses in the clinic have been disappointing due to either low efficacy or side effects. Numerous studies dealing with preclinical and clinical trials have been published about effective therapies for fibrotic diseases using mesenchymal stem cells, However, no research has yet been reported to scientifically investigate the effect of HDPSCs on the treatment of keloids.The objective is to provide an experimental basis to provide a novel proposal for the application of stem cells in the treatment of keloids.Methods HNFs and HKFs were cultured alone and in combination with DPSCs using a trans-well cell-contact-independent cell culture system. The effects of DPSCs on HKFs were tested using CCK-8 assay, Live/dead staining assay, quantitative polymerase chain reaction, Western blot．Results DPSCs don’t inhibited HKFs and HNFs proliferation and induce apoptosis, but inhibited migration. Furthermore, DPSCs significantly decreased expression of profibrotic genes, transforming growth factor-β 1，and transforming growth factor-β 2. DPSCs suppressed the ECM synthesis in HKFs, as indicated by decreased expression of collagen I and fibronectin and low levels of hydroxyproline in cell culture supernatant． Conclusions 1) Co-culture of DPSCs inhibits the migration of HKFs but does not affect the proliferation and apoptosis of HKFs.2) DPSCs co-culture inhibits the expression of pro-fibrotic genes and promotes the expression of anti-fibrotic genes in HKFs.3) DPSCs co-culture inhibits the synthesis of extracellular matrix by HKFs.