Genomic survey, expression profile and co-expression network analysis of OsWD40 family in rice

<p>Abstract</p> <p>Background</p> <p>WD40 proteins represent a large family in eukaryotes, which have been involved in a broad spectrum of crucial functions. Systematic characterization and co-expression analysis of <it>OsWD40 </it>genes enable us to understand the networks of the WD40 proteins and their biological processes and gene functions in rice.</p> <p>Results</p> <p>In this study, we identify and analyze 200 potential <it>OsWD40 </it>genes in rice, describing their gene structures, genome localizations, and evolutionary relationship of each member. Expression profiles covering the whole life cycle in rice has revealed that transcripts of <it>OsWD40 </it>were accumulated differentially during vegetative and reproductive development and preferentially up or down-regulated in different tissues. Under phytohormone treatments, 25 <it>OsWD40 </it>genes were differentially expressed with treatments of one or more of the phytohormone NAA, KT, or GA3 in rice seedlings. We also used a combined analysis of expression correlation and Gene Ontology annotation to infer the biological role of the <it>OsWD40 </it>genes in rice. The results suggested that <it>OsWD40 </it>genes may perform their diverse functions by complex network, thus were predictive for understanding their biological pathways. The analysis also revealed that <it>OsWD40 </it>genes might interact with each other to take part in metabolic pathways, suggesting a more complex feedback network.</p> <p>Conclusions</p> <p>All of these analyses suggest that the functions of <it>OsWD40 </it>genes are diversified, which provide useful references for selecting candidate genes for further functional studies.</p

The Influence of Neighbourhood Environment on Airbnb: a Geographically Weighed Regression Analysis

Sharing accommodation has emerged recently as a new business model in the accommodation sector. Due to the potential gentrification Airbnb might bring to an area, it is critical to understand the spatial patterns of sharing economy and its possible determinants. The neighbourhood environment has proven to be an important factor in the traditional hotel business, and whether it is the same for sharing accommodation is worth investigating. In this study, location data of 29,780 houses/apartments on Airbnb.com in London was collected. Using Ordinal Least Square and Geography Weighed Regression analysis, the spatial distribution features of Airbnb and its relationship with neighbourhood environment in London were explored. The results show that sharing accommodation is mainly located in the city centre and around tourist attractions. Neighbourhood elements such as Water, Vegetation Coverage, Art & Human Landscape, Travel & Transport, University, Nightlife Spot emerged as important factors influencing Airbnb. In addition, the distribution of Airbnb in London is spatially non-stationary, in some areas high Airbnb is associated with higher transportation accessibility, in other areas, high Airbnb is associated with more attractions or nightlife spots, suggesting that the role of different factors varies in different regions, proving Tobler’s first law of geography

Acute Systemic Infection-Associated Russell Body Gastroesophagitis: A Case Report and Literature Review

Russell body esophagitis/gastritis (RBG) is a rare gastrointestinal inflammatory condition characterized by accumulation of plasma cells containing dense eosinophilic cytoplasmic inclusions, i.e., Russell bodies. Herein, we report a case of RBG in a patient with a systemic inflammation background. A 61-year-old female presented with oral infection. Upper gastrointestinal endoscopy revealed patchy salmon-colored esophageal mucosa proximally to the gastroesophageal junction, suggestive of “Barrett’s esophagus”. Histologic examination of the biopsy tissue from the lower esophagus showed diffuse lymphoplasmacytic infiltration with abundant admixed enlarged plasma cells (Mott cells) containing bright eosinophilic, round, dense, homogenous inclusions (Russell bodies) in cytoplasm. Immunohistochemical study demonstrated membranous staining of CD138 in the Mott cells, while immunoglobulin light chain in situ hybridization revealed positivity of only kappa light chain, indicating kappa light chain restriction and clonality. A proton-pump inhibitor therapy was initiated, but the patient passed away due to generalized infection. Our case suggests that Russell body esophagitis/gastritis (RBG) can be a gastrointestinal presentation associated with acute systemic infection

A Tumor Mitochondria Vaccine Protects against Experimental Renal Cell Carcinoma

Mitochondria provide energy for cells via oxidative phosphorylation. Reactive oxygen species, a byproduct of this mitochondrial respiration, can damage mitochondrial DNA (mtDNA), and somatic mtDNA mutations have been found in all colorectal, ovarian, breast, urinary bladder, kidney, lung, and pancreatic tumors studied. The resulting altered mitochondrial proteins or tumor-associated mitochondrial Ags (TAMAs) are potentially immunogenic, suggesting that they may be targetable Ags for cancer immunotherapy. In this article, we show that the RENCA tumor cell line harbors TAMAs that can drive an antitumor immune response. We generated a cellular tumor vaccine by pulsing dendritic cells with enriched mitochondrial proteins from RENCA cells. Our dendritic cell-based RENCA mitochondrial lysate vaccine elicited a cytotoxic T cell response in vivo and conferred durable protection against challenge with RENCA cells when used in a prophylactic or therapeutic setting. By sequencing mtDNA from RENCA cells, we identified two mutated molecules: COX1 and ND5. Peptide vaccines generated from mitochondrial-encoded COX1 but not from ND5 had therapeutic properties similar to RENCA mitochondrial protein preparation. Thus, TAMAs can elicit effective antitumor immune responses, potentially providing a new immunotherapeutic strategy to treat cancer

Up-regulation of interferon-a/APOBEC3G signal pathway potently inactivates HIV-1 infectivity in resting CD4-T cells

Poster Presentation

Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study

Background Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children. Methods and findings Real-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ −6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered. Conclusions To our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.This study was funded by the National Key R&D Program of China (2018YFC0116500), the National Natural Science Foundation of China (91546101, 81822010), the Guangdong Science and Technology Innovation Leading Talents (2017TX04R031), and Youth Pearl River Scholar in Guangdong (2016)

Fucoxanthin, a Marine Carotenoid, Attenuates β

Alzheimer’s disease (AD), the most common neurodegenerative disorder, is characterized by neurofibrillary tangles, synaptic impairments, and loss of neurons. Oligomers of β-amyloid (Aβ) are widely accepted as the main neurotoxins to induce oxidative stress and neuronal loss in AD. In this study, we discovered that fucoxanthin, a marine carotenoid with antioxidative stress properties, concentration dependently prevented Aβ oligomer-induced increase of neuronal apoptosis and intracellular reactive oxygen species in SH-SY5Y cells. Aβ oligomers inhibited the prosurvival phosphoinositide 3-kinase (PI3K)/Akt cascade and activated the proapoptotic extracellular signal-regulated kinase (ERK) pathway. Moreover, inhibitors of glycogen synthase kinase 3β (GSK3β) and mitogen-activated protein kinase (MEK) synergistically prevented Aβ oligomer-induced neuronal death, suggesting that the PI3K/Akt and ERK pathways might be involved in Aβ oligomer-induced neurotoxicity. Pretreatment with fucoxanthin significantly prevented Aβ oligomer-induced alteration of the PI3K/Akt and ERK pathways. Furthermore, LY294002 and wortmannin, two PI3K inhibitors, abolished the neuroprotective effects of fucoxanthin against Aβ oligomer-induced neurotoxicity. These results suggested that fucoxanthin might prevent Aβ oligomer-induced neuronal loss and oxidative stress via the activation of the PI3K/Akt cascade as well as inhibition of the ERK pathway, indicating that further studies of fucoxanthin and related compounds might lead to a useful treatment of AD

Dietary L-Tryptophan Consumption Determines the Number of Colonic Regulatory T cells and Susceptibility to Colitis via GPR15

Environmental factors are the major contributor to the onset of immunological disorders such as ulcerative colitis. However, their identities remain unclear. Here, we discover that the amount of consumed L-Tryptophan (L-Trp), a ubiquitous dietary component, determines the transcription level of the colonic T cell homing receptor, GPR15, hence affecting the number of colonic FOXP3+ regulatory T (Treg) cells and local immune homeostasis. Ingested L-Trp is converted by host IDO1/2 enzymes, but not by gut microbiota, to compounds that induce GPR15 transcription preferentially in Treg cells via the aryl hydrocarbon receptor. Consequently, two weeks of dietary L-Trp supplementation nearly double the colonic GPR15+ Treg cells via GPR15-mediated homing and substantially reduce the future risk of colitis. In addition, humans consume 3–4 times less L-Trp per kilogram of body weight and have fewer colonic GPR15+ Treg cells than mice. Thus, we uncover a microbiota-independent mechanism linking dietary L-Trp and colonic Treg cells, that may have therapeutic potential