Systemic endopolyploidy in Spathoglottis plicata (Orchidaceae) development

BACKGROUND: Endopolyploidy is developmentally regulated. Presence of endopolyploidy as a result of endoreduplication has been characterized in insects, mammals and plants. The family Orchidaceae is the largest among the flowering plants. Many of the members of the orchid family are commercially micropropagated. Very little has been done to characterize the ploidy variation in different tissues of the orchid plants during development. RESULTS: The DNA contents and ploidy level of nuclei extracted from various tissues of a tropical terrestrial orchid Spathoglottis plicata were examined by flow cytometry. Sepals, petals and ovary tissues were found to have only a 2C (C, DNA content of the unreplicated haploid chromosome complement) peak. Columns, floral pedicels of newly open flowers and growing flower stems were observed to have an endopolyploid 8C peak in addition to 2C and 4C peaks. In developing floral pedicels, four peaks were observed for 2C, 4C, 8C and 16C. In root tips, there were 2C, 4C and 8C peaks. But in the root tissues at the region with root hairs, only a 2C peak was observed. Nuclei extracted from young leaves shown three peaks for 2C, 4C and 8C. A similar pattern was found in the vegetative tissues of both greenhouse-grown plants and tissue-cultured plantlets. In mature leaves, a different pattern of ploidy level was found at different parts of the leaves. In the leaf tips and middle parts, there were 2C and 4C peaks. Only at the basal part of the leaves, there were three peaks for 2C, 4C and 8C. CONCLUSIONS: Systemic variation of cellular endopolyploidy in different tissues during growth and development of Spathoglottis plicata from field-grown plants and in vitro cultures was identified. The implication of the findings was discussed

Genome-wide microarray analysis of TGFβ signaling in the Drosophila brain

BACKGROUND: Members of TGFβ superfamily are found to play important roles in many cellular processes, such as proliferation, differentiation, development, apoptosis, and cancer. In Drosophila, there are seven ligands that function through combinations of three type I receptors and two type II receptors. These signals can be roughly grouped into two major TGFβ pathways, the dpp/BMP and activin pathways, which signal primarily through thick veins (tkv) and baboon (babo). Few downstream targets are known for either pathway, especially targets expressed in the Drosophila brain. RESULTS: tkv and babo both affect the growth of tissues, but have varying effects on patterning. We have identified targets for the tkv and babo pathways by employing microarray techniques using activated forms of the receptors expressed in the brain. In these experiments, we compare the similarities of target genes of these two pathways in the brain. About 500 of 13,500 examined genes changed expression at 95% confidence level (P < 0.05). Twenty-seven genes are co-regulated 1.5 fold by both the tkv and babo pathways. These regulated genes cluster into various functional groups such as DNA/RNA binding, signal transducers, enzymes, transcription regulators, and neuronal regulators. RNAi knockdown experiments of homologs of several of these genes show abnormal growth regulation, suggesting these genes may execute the growth properties of TGFβ. CONCLUSIONS: Our genomic-wide microarray analysis has revealed common targets for the tkv and babo pathways and provided new insights into downstream effectors of two distinct TGFβ like pathways. Many of these genes are novel and several genes are implicated in growth control. Among the genes regulated by both pathways is ultraspiracle, which further connects TGFβ with neuronal remodeling

An Empirical Study on Environmental Efficiency Assessment in Urban Industrial Concentration Areas

Many urban industrial concentration areas are becoming mixtures of intensive industrial and residential land use. While they play important roles in urban economy and employment, the energy consumption and pollution discharge in the process of industrial production bring mang negative effects on surrounding people and environments. In this paper, a tool is proposed to evaluate the environmental efficiency (EE) of the industrial concentration areas in order to coordinate the functioning of economic activities and environmental protection. Based upon discussion on the principal and significance of EE assessment in urban industrial concentration areas, an empirical study is conducted in Fengtai district, Beijing, to elaborate the idea from three aspects: socio-economic contribution, environmental load, and environmental risk. The study area was divided into 1379 grids of 500 m*500 m as the basic spatial unit while the spatial size effect and its rationality of the environmental functions have been testified. As the result, it turned out that the amount of the low EE grids account for 71.15% of the total districts while the rather high environmental load grids 20.18%. In the meantime, we found out that the area of low EE value grids have the tendency to aggregate towards the central urban areas, along urban express ring roads and around wholesale markets. These results shed light to implementing the refined environmental spatial management and control

Short-chain Fatty Acids Regulate the Immune Responses via G Protein Coupled Receptor 41 in Bovine Rumen Epithelial Cells

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Establishment and evaluation of a predictive model for length of hospital stay after total knee arthroplasty: A single-center retrospective study in China

BackgroundTotal knee arthroplasty (TKA) is the ultimate option for end-stage osteoarthritis, and the demand of this procedure are increasing every year. The length of hospital stay (LOS) greatly affects the overall cost of joint arthroplasty. The purpose of this study was to develop and validate a predictive model using perioperative data to estimate the risk of prolonged LOS in patients undergoing TKA.MethodsData for 694 patients after TKA collected retrospectively in our department were analyzed by logistic regression models. Multi-variable logistic regression modeling with forward stepwise elimination was used to determine reduced parameters and establish a prediction model. The discrimination efficacy, calibration efficacy, and clinical utility of the prediction model were evaluated.ResultsEight independent predictors were identified: non-medical insurance payment, Charlson Comorbidity Index (CCI) ≥ 3, body mass index (BMI) &gt; 25.2, surgery on Monday, age &gt; 67.5, postoperative complications, blood transfusion, and operation time &gt; 120.5 min had a higher probability of hospitalization for ≥6 days. The model had good discrimination [area under the curve (AUC), 0.802 95% CI, 0.754–0.850]] and good calibration (p = 0.929). A decision curve analysis proved that the nomogram was clinically effective.ConclusionThis study identified risk factors for prolonged hospital stay in patients after TKA. It is important to recognize all the factors that affect hospital LOS to try to maximize the use of medical resources, optimize hospital LOS and ultimately optimize the care of our patients

Cloning, Expression and Characterization of an Esterase Gene in a Metagenomic Library of Traditional Fermented Food

Esterase is an industrial enzyme that is widely used in food, medicine, fine chemicals. The total genomic DNA was extracted from traditional fermented food in China to construct a metagenomic library that included a novel esterase gene (est_115). Sequence homology analysis showed that the highest homology with the carboxylester hydrolase from Pseudomonas lutea was 38%, indicating that esterase belongs to a new class of esterases. Then, an est_115 gene recombinant expression vector was constructed and expressed. The Est_115 had higher catalytic activity to p-nitrophenol ester, with a short acyl-carbon chain. The enzyme can maintain high catalytic activity and salt tolerance in 10%–18% NaCl, suggesting that this novel esterase can be used in processing food using high osmotic pressure

Social network inference and privacy preserving trajectory publishing in mobile phone data

Mobile phone data are collected communication logs between human beings. There are two interesting aspects and applications of the data: finding social structures and mobility patterns. The data could not only offer insights about how people make friends with each other but also shed light on how people move around in cities. These questions could help potential applications in security control and smart city planning. One interesting problem in social networks is Social Network Inference problem. Given the original raw communication data, how to accurately infer the relevant social network from the raw data? Are there noisy actors to affect the legitimacy of the social network? We consider the noise removal process as an important issue in Social Network Inference process. In this work, the noise removal problem is formulated and studied. Effective noise removing techniques are proposed to tackle the problem. Another important application of the data is about the whereabouts of human beings. However, the privacy issue is prohibiting the sharing and study of the data. Recent study shows that more than 50% of the population in the United States could be uniquely identified if a similar mobile phone data as ours is published even with an anonymization on the IDs. We formulate the top location attack and prove that it is an NP-Complete problem to prevent such attack. Then, we propose our novel privacy preserving technique to modify the original data with minimal distortion

Automated Scoring of Translations with BERT Models: Chinese and English Language Case Study

With the wide application of artificial intelligence represented by deep learning in natural language-processing tasks, the automated scoring of translations has also advanced and improved. This study aims to determine if the BERT-assist system can reliably assess translation quality and identify high-quality translations for potential recognition. It takes the Han Suyin International Translation Contest as a case study, which is a large-scale and influential translation contest in China, with a history of over 30 years. The experimental results show that the BERT-assist system is a reliable second rater for massive translations in terms of translation quality, as it can effectively sift out high-quality translations with a reliability of r = 0.9 or higher. Thus, the automated translation scoring system based on BERT can satisfactorily predict the ranking of translations according to translation quality and sift out high-quality translations potentially shortlisted for prizes