Zwitterionic carboxybetaine polymers extend the shelf-life of human platelets.

The shelf-life of human platelets preserved in vitro for therapeutic transfusion is limited because of bacterial contamination and platelet storage lesion (PSL). The PSL is the predominant factor and limiting unfavorable interactions between the platelets and the non-biocompatible storage bag surfaces is the key to alleviate PSL. Here we describe a surface modification method for biocompatible platelet storage bags that dramatically extends platelet shelf-life beyond the current US Food and Drug Administration (FDA) standards of 5 days. The surface coating of the bags can be achieved through a simple yet effective dip-coating and light-irradiation method using a biocompatible polymer. The biocompatible polymers with tunable functional groups can be routinely fabricated at any scale and impart super-hydrophilicity and non-fouling capability on commercial hydrophobic platelet storage bags. As critical parameters reflecting the platelets quality, the activation level and binding affinity with von Willebrand factor (VWF) of the platelets stored in the biocompatible platelet bags at 8 days are comparable with those in the commercial bags at 5 days. This technique also demonstrates promise for a wide range of medical and engineering applications requiring biocompatible surfaces. STATEMENT OF SIGNIFICANCE: Current standard platelet preservation techniques agitate platelets at room temperature (20-24 °C) inside a hydrophobic (e.g., polyvinyl chloride (PVC)) storage bag, thereby allowing preservation of platelets only for 5 days. A key factor leading to quality loss is the unfavorable interaction between the platelets and the non-biocompatible storage bag surfaces. Here, a surface modification method for biocompatible platelet storage bags has been created to dramatically extend platelet shelf-life beyond the current FDA standards of 5 days. The surface coating of the bags can be achieved via a simple yet effective dip-coating and light-irradiation method using a carboxybetaine polymer. This technique is also applicable to many other applications requiring biocompatible surfaces.

sRIS: A Small RNA Illustration System for Plant Next-Generation Sequencing Data Analysis.

Small RNA (sRNA), such as microRNA (miRNA) and short interfering RNA, are well-known to control gene expression based on degradation of target mRNA in plants. A considerable amount of research has applied next-generation sequencing (NGS) to reveal the regulatory pathways of plant sRNAs. Consequently, numerous bioinformatics tools have been developed for the purpose of analyzing sRNA NGS data. However, most methods focus on the study of sRNA expression profiles or novel miRNAs predictions. The analysis of sRNA target genes is usually not integrated into their pipelines. As a result, there is still no means available for identifying the interaction mechanisms between host and virus or the synergistic effects between two viruses. For the present study, a comprehensive system, called the Small RNA Illustration System (sRIS), has been developed. This system contains two main components. The first is for sRNA overview analysis and can be used not only to identify miRNA but also to investigate virus-derived small interfering RNA. The second component is for sRNA target prediction, and it employs both bioinformatics calculations and degradome sequencing data to enhance the accuracy of target prediction. In addition, this system has been designed so that figures and tables for the outputs of each analysis can be easily retrieved and accessed, making it easier for users to quickly identify and quantify their results. sRIS is available at http://sris.itps.ncku.edu.tw/.

Delineation of condition specific Cis- and Trans-acting elements in plant promoters under various Endo- and exogenous stimuli.

BACKGROUND: Transcription factors (TFs) play essential roles during plant development and response to environmental stresses. However, the relationships among transcription factors, cis-acting elements and target gene expression under endo- and exogenous stimuli have not been systematically characterized. RESULTS: Here, we developed a series of bioinformatics analysis methods to infer transcriptional regulation by using numerous gene expression data from abiotic stresses and hormones treatments. After filtering the expression profiles of TF-encoding genes, 291 condition specific transcription factors (CsTFs) were obtained. Differentially expressed genes were then classified into various co-expressed gene groups based on each CsTFs. In the case studies of heat stress and ABA treatment, several known and novel cis-acting elements were identified following our bioinformatics approach. Significantly, a palindromic sequence of heat-responsive elements is recognized, and also obtained from a 3D protein structure of heat-shock protein-DNA complex. Notably, overrepresented 3- and 4-mer motifs in an enriched 8-mer motif could be a core cis-element for a CsTF. In addition, the results suggest DNA binding preferences of the same CsTFs are different according to various conditions. CONCLUSIONS: The overall results illustrate this study may be useful in identifying condition specific cis- and trans- regulatory elements and facilitate our understanding of the relationships among TFs, cis-acting elements and target gene expression.

Paddy-upland rotation for sustainable agriculture with regards to diverse soil microbial community.

Diverse soil microbial community is determinant for sustainable agriculture. Rich microbial diversity has presumably improved soil health for economic crops to grow. In this work, the benefits of paddy-upland rotation on soil microbial diversity and specific microbes are thus intensively explored. The microbiome from multiple factor experiment (three fertilizations coupled with two rotation systems) were investigated by novel enrichment and co-occurrence analysis in a field well maintained for 25 years. Using next-generation sequencing technique, we firstly present explicit evidence that different rotation systems rather than fertilizations mightily governed the soil microbiome. Paddy-upland rotation (R1) obviously increase more microbial diversity than upland rotation (R2) whether organic (OF), chemical (CF) or integrated fertilizers (IF) were concomitantly applied. Besides, the specific bacterial composition dominated in OF soil is more similar to that of R1 than to CF, suggesting that paddy-upland rotation might be the best option for sustainable agriculture if chemical fertilizer is still required. Interestingly, the pot bioassay verified clearly the novel analysis prediction, illustrating that greater microbial diversity and specific microbial composition correlated significantly with disease resistance. This finding highlights the eminence of paddy-upland rotation in promoting microbial diversity and specific microbial compositions, preserving soil health for sustainable agriculture.

microRPM: a microRNA prediction model based only on plant small RNA sequencing data.

Motivation: MicroRNAs (miRNAs) are endogenous non-coding small RNAs (of about 22 nucleotides), which play an important role in the post-transcriptional regulation of gene expression via either mRNA cleavage or translation inhibition. Several machine learning-based approaches have been developed to identify novel miRNAs from next generation sequencing (NGS) data. Typically, precursor/genomic sequences are required as references for most methods. However, the non-availability of genomic sequences is often a limitation in miRNA discovery in non-model plants. A systematic approach to determine novel miRNAs without reference sequences is thus necessary. Results: In this study, an effective method was developed to identify miRNAs from non-model plants based only on NGS datasets. The miRNA prediction model was trained with several duplex structure-related features of mature miRNAs and their passenger strands using a support vector machine algorithm. The accuracy of the independent test reached 96.61% and 93.04% for dicots (Arabidopsis) and monocots (rice), respectively. Furthermore, true small RNA sequencing data from orchids was tested in this study. Twenty-one predicted orchid miRNAs were selected and experimentally validated. Significantly, 18 of them were confirmed in the qRT-PCR experiment. This novel approach was also compiled as a user-friendly program called microRPM (miRNA Prediction Model). Availability and implementation: This resource is freely available at http://microRPM.itps.ncku.edu.tw. Contact: nslin@sinica.edu.tw or sarah321@mail.ncku.edu.tw. Supplementary information: Supplementary data are available at Bioinformatics online.

Impedance feedback control of microfluidic valves for reliable post processing combinatorial droplet injection.

Droplet microfluidics has found use in many biological assay applications as a means of high-throughput sample processing. One of the challenges of the technology, however, is the ability to control and merge droplets on-demand as they flow through the microdevices. It is in the interest of developing lab-on-chip devices to be able to combinatorically program additive mixing steps for more complex multistep and multiplex assays. Existing technologies to merge droplets are either passive in nature or require highly predictable droplet movement for feedforward control, making them vulnerable to errors during high throughput operation. In this paper, we describe and demonstrate a microfluidic valve-based device for the purpose of combinatorial droplet injection at any stage in a multistep assay. Microfluidic valves are used to robustly control fluid flow, droplet generation, and droplet mixing in the device on-demand, while on-chip impedance measurements taken in real time are used as feedback to accurately time the droplet injections. The presented system is contrasted to attempts without feedback, and is shown to be 100% reliable over long durations. Additionally, content detection and discretionary injections are explored and successfully executed.

PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants.

Transcription factors (TFs) are sequence-specific DNA-binding proteins acting as critical regulators of gene expression. The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN2.itps.ncku.edu.tw) provides an informative resource for detecting transcription factor binding sites (TFBSs), corresponding TFs, and other important regulatory elements (CpG islands and tandem repeats) in a promoter or a set of plant promoters. Additionally, TFBSs, CpG islands, and tandem repeats in the conserve regions between similar gene promoters are also identified. The current PlantPAN release (version 2.0) contains 16 960 TFs and 1143 TF binding site matrices among 76 plant species. In addition to updating of the annotation information, adding experimentally verified TF matrices, and making improvements in the visualization of transcriptional regulatory networks, several new features and functions are incorporated. These features include: (i) comprehensive curation of TF information (response conditions, target genes, and sequence logos of binding motifs, etc.), (ii) co-expression profiles of TFs and their target genes under various conditions, (iii) protein-protein interactions among TFs and their co-factors, (iv) TF-target networks, and (v) downstream promoter elements. Furthermore, a dynamic transcriptional regulatory network under various conditions is provided in PlantPAN 2.0. The PlantPAN 2.0 is a systematic platform for plant promoter analysis and reconstructing transcriptional regulatory networks.

Risk factors of late-onset neonatal sepsis in Taiwan: A matched case-control study.

BACKGROUND: Infants in a neonatal intensive care unit (NICU) have a higher incidence of bloodstream infections (BSIs) than any other pediatric or adult population. The predisposing factors have not been comprehensively evaluated in this population in Taiwan. METHODS: A retrospective matched case-control study was conducted in the NICUs of a teaching hospital in Taiwan. The case patients were identified from a staff-maintained electronic database containing the records of BSIs from July 2003 to June 2006. The case patients and the control patients (who did not develop BSI during their NICU stay) were 1:1 matched by birth weight, gestational age, gender, Apgar score, and date of birth. RESULTS: A total of 164 infants with culture-proven BSI were identified. Of these, 74 (45.1%) infants were female. The mean gestational age and birth weight were 30.7 ± 0.7 weeks and 1512 ± 804 g, respectively. The common etiologic pathogens included coagulase-negative staphylococci (28.7%), Staphylococcus aureus (16.5%), and Klebsiella pneumoniae (14.6%). Candida spp. accounted for 11 (6.7%) episodes. Two independent factors associated with BSIs in the neonates, as identified by multivariate analysis using conditional logistic regression, were the use of parenteral nutrition (matched odds ratio [mOR], 6.07; 95% confidence interval [CI], 1.14-32.32; p = 0.034) and intraventricular hemorrhage (mOR, 2.68; 95% CI, 1.20-5.99; p = 0.017). CONCLUSION: Parenteral nutrition was a significant and independent risk of late-onset neonatal sepsis. This risk should be considered when implementing early parenteral nutrition in NICUs.

AtmiRNET: a web-based resource for reconstructing regulatory networks of Arabidopsis microRNAs.

Compared with animal microRNAs (miRNAs), our limited knowledge of how miRNAs involve in significant biological processes in plants is still unclear. AtmiRNET is a novel resource geared toward plant scientists for reconstructing regulatory networks of Arabidopsis miRNAs. By means of highlighted miRNA studies in target recognition, functional enrichment of target genes, promoter identification and detection of cis- and trans-elements, AtmiRNET allows users to explore mechanisms of transcriptional regulation and miRNA functions in Arabidopsis thaliana, which are rarely investigated so far. High-throughput next-generation sequencing datasets from transcriptional start sites (TSSs)-relevant experiments as well as five core promoter elements were collected to establish the support vector machine-based prediction model for Arabidopsis miRNA TSSs. Then, high-confidence transcription factors participate in transcriptional regulation of Arabidopsis miRNAs are provided based on statistical approach. Furthermore, both experimentally verified and putative miRNA-target interactions, whose validity was supported by the correlations between the expression levels of miRNAs and their targets, are elucidated for functional enrichment analysis. The inferred regulatory networks give users an intuitive insight into the pivotal roles of Arabidopsis miRNAs through the crosstalk between miRNA transcriptional regulation (upstream) and miRNA-mediate (downstream) gene circuits. The valuable information that is visually oriented in AtmiRNET recruits the scant understanding of plant miRNAs and will be useful (e.g. ABA-miR167c-auxin signaling pathway) for further research. Database URL: http://AtmiRNET.itps.ncku.edu.tw/

EXPath: a database of comparative expression analysis inferring metabolic pathways for plants.

BACKGROUND: In general, the expression of gene alters conditionally to catalyze a specific metabolic pathway. Microarray-based datasets have been massively produced to monitor gene expression levels in parallel with numerous experimental treatments. Although several studies facilitated the linkage of gene expression data and metabolic pathways, none of them are amassed for plants. Moreover, advanced analysis such as pathways enrichment or how genes express under different conditions is not rendered. DESCRIPTION: Therefore, EXPath was developed to not only comprehensively congregate the public microarray expression data from over 1000 samples in biotic stress, abiotic stress, and hormone secretion but also allow the usage of this abundant resource for coexpression analysis and differentially expression genes (DEGs) identification, finally inferring the enriched KEGG pathways and gene ontology (GO) terms of three model plants: Arabidopsis thaliana, Oryza sativa, and Zea mays. Users can access the gene expression patterns of interest under various conditions via five main functions (Gene Search, Pathway Search, DEGs Search, Pathways/GO Enrichment, and Coexpression analysis) in EXPath, which are presented by a user-friendly interface and valuable for further research. CONCLUSIONS: In conclusion, EXPath, freely available at http://expath.itps.ncku.edu.tw, is a database resource that collects and utilizes gene expression profiles derived from microarray platforms under various conditions to infer metabolic pathways for plants.

Large-scale investigation of human TF-miRNA relations based on coexpression profiles.

Noncoding, endogenous microRNAs (miRNAs) are fairly well known for regulating gene expression rather than protein coding. Dysregulation of miRNA gene, either upregulated or downregulated, may lead to severe diseases or oncogenesis, especially when the miRNA disorder involves significant bioreactions or pathways. Thus, how miRNA genes are transcriptionally regulated has been highlighted as well as target recognition in recent years. In this study, a large-scale investigation of novel cis- and trans-elements was undertaken to further determine TF-miRNA regulatory relations, which are necessary to unravel the transcriptional regulation of miRNA genes. Based on miRNA and annotated gene expression profiles, the term "coTFBS" was introduced to detect common transcription factors and the corresponding binding sites within the promoter regions of each miRNA and its coexpressed annotated genes. The computational pipeline was successfully established to filter redundancy due to short sequence motifs for TFBS pattern search. Eventually, we identified more convinced TF-miRNA regulatory relations for 225 human miRNAs. This valuable information is helpful in understanding miRNA functions and provides knowledge to evaluate the therapeutic potential in clinical research. Once most expression profiles of miRNAs in the latest database are completed, TF candidates of more miRNAs can be explored by this filtering approach in the future.

AlgaePath: comprehensive analysis of metabolic pathways using transcript abundance data from next-generation sequencing in green algae.

BACKGROUND: Algae are important non-vascular plants that have many research applications, including high species diversity, biofuel sources, and adsorption of heavy metals and, following processing, are used as ingredients in health supplements. The increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes has made the development of an integrated resource for retrieving gene expression data and metabolic pathway essential for functional analysis and systems biology. In a currently available resource, gene expression profiles and biological pathways are displayed separately, making it impossible to easily search current databases to identify the cellular response mechanisms. Therefore, in this work the novel AlgaePath database was developed to retrieve transcript abundance profiles efficiently under various conditions in numerous metabolic pathways. DESCRIPTION: AlgaePath is a web-based database that integrates gene information, biological pathways, and NGS datasets for the green algae Chlamydomonas reinhardtii and Neodesmus sp. UTEX 2219-4. Users can search this database to identify transcript abundance profiles and pathway information using five query pages (Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-expression Analysis). The transcript abundance data of 45 and four samples from C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively, can be obtained directly on pathway maps. Genes that are differentially expressed between two conditions can be identified using Folds Search. The Gene Group Analysis page includes a pathway enrichment analysis, and can be used to easily compare the transcript abundance profiles of functionally related genes on a map. Finally, the Co-expression Analysis page can be used to search for co-expressed transcripts of a target gene. The results of the searches will provide a valuable reference for designing further experiments and for elucidating critical mechanisms from high-throughput data. CONCLUSIONS: AlgaePath is an effective interface that can be used to clarify the transcript response mechanisms in different metabolic pathways under various conditions. Importantly, AlgaePath can be mined to identify critical mechanisms based on high-throughput sequencing. To our knowledge, AlgaePath is the most comprehensive resource for integrating numerous databases and analysis tools in algae. The system can be accessed freely online at http://algaepath.itps.ncku.edu.tw.

A Lego®-like swappable fluidic module for bio-chem applications.

A Lego®-like swappable fluidic module (SFM) is proposed in this research. We designed and fabricated selected modular fluidic components, including functional and auxiliary types that can be effortlessly swapped and integrated into a variety of modular devices to rapidly assemble a fully-portable, disposable fluidic system. In practice, an integrated SFM uses finger-operated, electricity-free pumps to deliver fluids. Using a swirling mechanism, the vortex mixer can rapidly mix two liquids in a one-shot mixing event. We demonstrate the successful application of this SFM in several microfluidic applications, such as the synthesis of gold nanoparticles (AuNPs) from chloroauric acid (HAuCl4), and nucleic acid amplification from the Hepatitis B virus (HBV) with a capillary convective polymerase chain reaction (ccPCR).

A real-time convective PCR machine in a capillary tube instrumented with a CCD-based fluorometer.

This research reports the design, analysis, integration, and test of a prototype of a real-time convective polymerase chain reaction (RT-cPCR) machine that uses a color charged coupled device (CCD) for detecting the emission of fluorescence intensity from an RT-cPCR mix in a microliter volume glass capillary. Because of its simple mechanism, DNA amplification involves employing the cPCR technique with no need for thermocycling control. The flow pattern and temperature distribution can greatly affect the cPCR process in the capillary tube, a computational fluid dynamics (CFD) simulation was conducted in this study for the first time to estimate the required period of an RT-cPCR cycle. This study also tested the PCR mix containing hepatitis B virus (HBV) plasmid samples by using SYBR Green I fluorescence labeling dye to assess the prototype performance. The measured results from the image-processing scheme indicate that the RT-cPCR prototype with a CCD-based fluorometer can achieve similar DNA quantification reproducibility compared to commercial machines, even when the initial DNA concentration in the test PCR mix is reduced to 10 copies/µL.