DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning

It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary structures first. However, experimental protocols for solving RNA structures are unavailable for large-scale investigation due to their high costs and time-consuming nature. Various computational tools were thus developed to predict the RNA secondary structures from sequences. Recently, deep networks have been investigated to help predict RNA structures directly from their sequences. However, existing deep-learning-based tools are more or less suffering from model overfitting due to their complicated problem formulation and defective model training processes, limiting their applications across sequences from different structural families. In this research, we designed a two-stage RNA structure prediction strategy called DEBFold (deep ensemble boosting and folding) based on convolution encoding/decoding and self-attention mechanisms to enhance the existing thermodynamic structure models. Moreover, the model training process followed rigorous steps to achieve an acceptable prediction generalization. On the family-wise reserved test sets and the PDB-derived test set, DEBFold achieves better structure prediction performance over traditional tools and existing deep-learning methods. In summary, we obtained a cutting-edge deep-learning-based structure prediction tool with supreme across-family generalization performance. The DEBFold tool can be accessed at https://cobis.bme.ncku.edu.tw/DEBFold/.

Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke

PURPOSE

Clinical risk scores are essential for predicting outcomes in stroke patients. The advancements in deep learning (DL) techniques provide opportunities to develop prediction applications using magnetic resonance (MR) images. We aimed to develop an MR-based DL imaging biomarker for predicting outcomes in acute ischemic stroke (AIS) and evaluate its additional benefit to current risk scores.

METHOD

This study included 3338 AIS patients. We trained a DL model using deep neural network architectures on MR images and radiomics to predict poor functional outcomes at three months post-stroke. The DL model generated a DL score, which served as the DL imaging biomarker. We compared the predictive performance of this biomarker to five risk scores on a holdout test set. Additionally, we assessed whether incorporating the imaging biomarker into the risk scores improved the predictive performance.

RESULTS

The DL imaging biomarker achieved an area under the receiver operating characteristic curve (AUC) of 0.788. The AUCs of the five studied risk scores were 0.789, 0.793, 0.804, 0.810, and 0.826, respectively. The imaging biomarker's predictive performance was comparable to four of the risk scores but inferior to one (p = 0.038). Adding the imaging biomarker to the risk scores improved the AUCs (p-values) to 0.831 (0.003), 0.825 (0.001), 0.834 (0.003), 0.836 (0.003), and 0.839 (0.177), respectively. The net reclassification improvement and integrated discrimination improvement indices also showed significant improvements (all p < 0.001).

CONCLUSIONS

Using DL techniques to create an MR-based imaging biomarker is feasible and enhances the predictive ability of current risk scores.

Identifying Human miRNA Target Sites via Learning the Interaction Patterns between miRNA and mRNA Segments

miRNAs (microRNAs) target specific mRNA (messenger RNA) sites to regulate their translation expression. Although miRNA targeting can rely on seed region base pairing, animal miRNAs, including human miRNAs, typically cooperate with several cofactors, leading to various noncanonical pairing rules. Therefore, identifying the binding sites of animal miRNAs remains challenging. Because experiments for mapping miRNA targets are costly, computational methods are preferred for extracting potential miRNA-mRNA fragment binding pairs first. However, existing prediction tools can have significant false positives due to the prevalent noncanonical miRNA binding behaviors and the information-biased training negative sets that were used while constructing these tools. To overcome these obstacles, we first prepared an information-balanced miRNA binding pair ground-truth data set. A miRNA-mRNA interaction-aware model was then designed to help identify miRNA binding events. On the test set, our model (auROC = 94.4%) outperformed existing models by at least 2.8% in auROC. Furthermore, we showed that this model can suggest potential binding patterns for miRNA-mRNA sequence interacting pairs. Finally, we made the prepared data sets and the designed model available at http://cosbi2.ee.ncku.edu.tw/mirna_binding/download.

RDDL: A systematic ensemble pipeline tool that streamlines balancing training schemes to reduce the effects of data imbalance in rare-disease-related deep-learning applications

Identifying lowly prevalent diseases, or rare diseases, in their early stages is key to disease treatment in the medical field. Deep learning techniques now provide promising tools for this purpose. Nevertheless, the low prevalence of rare diseases entangles the proper application of deep networks for disease identification due to the severe class-imbalance issue. In the past decades, some balancing methods have been studied to handle the data-imbalance issue. The bad news is that it is verified that none of these methods guarantees superior performance to others. This performance variation causes the need to formulate a systematic pipeline with a comprehensive software tool for enhancing deep-learning applications in rare disease identification. We reviewed the existing balancing schemes and summarized a systematic deep ensemble pipeline with a constructed tool called RDDL for handling the data imbalance issue. Through two real case studies, we showed that rare disease identification could be boosted with this systematic RDDL pipeline tool by lessening the data imbalance problem during model training. The RDDL pipeline tool is available at https://github.com/cobisLab/RDDL/.

Precisely Closed Reduction of Nasal Bone Fracture Assisted With Plain Film Measurements Under the Picture Archiving and Communication System

OBJECTIVES

To prevent aesthetic and functional deformities, precisely closed reduction is crucial in the management of nasal fractures. Plain film radiography (PF), ultrasonography (USG), and computed tomography can help confirm the diagnosis and classification of fractures and assist in performing closed reduction. However, no study in the literature reports on precisely closed reduction assisted with PF measurements under the picture archiving and communication system (PACS).

METHODS

We retrospectively evaluated 153 patients with nasal bone fracture between January 2013 and December 2017. Surgeons conducted precisely closed reduction assisted with PF measurement of the distance between the fracture site and nasal tip under PACS on 34 patients (group A). Another group on 119 patients were reduced under surgeon's experience (group B).

RESULTS

No significant differences in age, gender, Arbeitsgemeinschaft fur Osteosynthesefragen (AO) classification, and reduction outcome were observed between group A and group B (P > .05). The operative time of the group A was significantly lower (12.50 ± 4.64 minutes) compared to group B (23.78 ± 11.20 minutes; P < .001). After adjusted age, gender, and AO classification, patients in group A scored 10.46 minutes less on the operative time than those in group B (P < .001). In addition, the severity of nasal bone fracture (AO classification, β = 3.37, P = .002) was positive associated with the operative time.

CONCLUSIONS

In this study, closed reduction in nasal bone fracture assisted with PF measurements under PACS was performed precisely, thereby effectively decreasing operative time and the occurrence of complications. This procedure requires neither the use of new instruments or C-arm nor USG or navigation experience. Moreover, reduction can be easily performed using this method, and it requires short operative time, helps achieve great reduction, less radiation exposures, and is cost-effective.

Mechanical Behaviors of Microwave-Assisted Pyrolysis Recycled Carbon Fiber-Reinforced Concrete with Early-Strength Cement

This study aimed to investigate the mechanical performance of early-strength carbon fiber-reinforced concrete (ECFRC) by incorporating original carbon fiber (OCF), recycled carbon fiber (RCF), and sizing-removed carbon fiber (SCF). Compressive, flexural, and splitting tensile strength were tested under three fiber-to-cement weight ratios (5‱, 10‱, and 15‱). The RCF was produced from waste bicycle parts made of carbon fiber-reinforced polymer (CFRP) through microwave-assisted pyrolysis (MAP). The sizing-removed fiber was obtained through a heat-treatment method applied to the OCF. The results of scanning electron microscopy (SEM) analysis with energy dispersive X-ray spectrometry (EDS) indicated the successful removal of sizing and impurities from the surface of the RCF and SCF. The mechanical test results showed that ECFRC with a 10‱ fiber-to-cement weight ratio of carbon fiber had the greatest improvement in its mechanical strengths. Moreover, the ECFRC with 10‱ RCF exhibited higher compressive, flexural, and splitting tensile strength than that of benchmark specimen by 14.2%, 56.5%, and 22.5%, respectively. The ECFRC specimens with a 10‱ fiber-to-cement weight ratio were used to analyze their impact resistance under various impact energies in the impact test. At 50 joules of impact energy, the impact number of the ECFRC with SCF was over 23 times that of the benchmark specimen (early-strength concrete without fiber) and was also greater than that of ECFRC with OCF and RCF.

CFA: An explainable deep learning model for annotating the transcriptional roles of cis-regulatory modules based on epigenetic codes

Metazoa gene expression is controlled by modular DNA segments called cis-regulatory modules (CRMs). CRMs can convey promoter/enhancer/insulator roles, generating additional regulation layers in transcription. Experiments for understanding CRM roles are low-throughput and costly. Large-scale CRM function investigation still depends on computational methods. However, existing in silico tools only recognize enhancers or promoters exclusively, thus accumulating errors when considering CRM promoter/enhancer/insulator roles altogether. Currently, no algorithm can concurrently consider these CRM roles. In this research, we developed the CRM Function Annotator (CFA) model. CFA provides complete CRM transcriptional role labeling based on epigenetic profiling interpretation. We demonstrated that CFA achieves high performance (test macro auROC/auPRC = 94.1%/90.3%) and outperforms existing tools in promoter/enhancer/insulator identification. CFA is also inspected to recognize explainable epigenetic codes consistent with previous findings when labeling CRM roles. By considering the higher-order combinations of the epigenetic codes, CFA significantly reduces false-positive rates in CRM transcriptional role annotation. CFA is available at https://github.com/cobisLab/CFA/.

YMLA: A comparative platform to carry out functional enrichment analysis for multiple gene lists in yeast

Comparative analysis among multiple gene lists on their functional features is now a routine task due to the advancement of high-throughput experiments. Several enrichment analysis tools were developed in the past. However, these tools mainly focus on one gene list and contain only gene ontology or interaction features. What makes it worse, comparative investigation and customized feature set reanalysis are still unavailable. Therefore, we constructed the YMLA (Yeast Multiple List Analyzer) platform in this research. YMLA includes 39 yeast features and facilitates comparative analysis among multiple gene lists via tabular views, heatmaps, and network plots. Moreover, the customized feature set reanalysis function was implemented in YMLA to help form mechanism hypotheses based on a selected enriched feature subset. We demonstrated the biological applicability of YMLA via example lists consisting of genes with top/bottom translation efficiency values. The analysis results provided by YMLA reveal novel facts consistent with previous experiments. YMLA is available at https://cosbi7.ee.ncku.edu.tw/YMLA/.

SSRTool: a web tool for evaluating RNA secondary structure predictions based on species-specific functional interpretability

RNA secondary structures can carry out essential cellular functions alone or interact with one another to form the hierarchical tertiary structures. Experimental structure identification approa ches can show the in vitro structures of RNA molecules. However, they usually have limits in the resolution and are costly. In silico structure prediction tools are thus primarily relied on for pre-experiment analysis. Various structure prediction models have been developed over the decades. Since these tools are usually used before knowing the actual RNA structures, evaluating and ranking the pile of secondary structure predictions of a given sequence is essential in computational analysis. In this research, we implemented a web service called SSRTool (RNA Secondary Structure prediction Ranking Tool) to assist in the ranking and evaluation of the generated predicted structures of a given sequence. Based on the computed species-specific interpretability significance in four common RNA structure–function aspects, SSRTool provides three functions along with visualization interfaces: (1) Rank user-generated predictions. (2) Provide an automated streamline of structure prediction and ranking for a given sequence. (3) Infer the functional aspects of a given structure. We demonstrated the applicability of SSRTool via real case studies and reported the similar trends between computed species-specific rankings and the corresponding prediction F1 values. The SSRTool web service is available online at https://cobisHSS0.im.nuk.edu.tw/SSRTool/, http://cosbi3.ee.ncku.edu.tw/SSRTool/, or the redirecting site https://github.com/cobisLab/SSRTool/.

KDmarkers: A biomarker database for investigating epigenetic methylation and gene expression levels in Kawasaki disease

Kawasaki disease (KD) is a form of acute systemic vasculitis that primarily affects children and has become the most common cause of acquired heart disease. While the etiopathogenesis of KD remains unknown, the diagnostic criteria of KD have been well established. Nevertheless, the diagnosis of KD is currently based on subjective clinical symptoms, and no molecular biomarker is yet available. We have previously performed and combined methylation array (Illumina HumanMethylation450 BeadChip) and transcriptome array (Affymetrix GeneChip Human Transcriptome Array 2.0) to identify genes that are differentially methylated/expressed in KD patients compared with control subjects. We have found that decreased methylation levels combined with elevated gene expression can indicate genes (e.g., toll-like receptors and CD177) involved in the disease mechanisms of KD. In this study, we constructed a database called KDmarkers to allow researchers to access these valuable potential KD biomarkers identified via methylation array and transcriptome array. KDmarkers provides three search modes. First, users can search genes differentially methylated and/or differentially expressed in KD patients compared with control subjects. Second, users can check the KD patient groups in which a given gene is differentially methylated and/or differentially expressed. Third, users can explore the DNA methylation levels and gene expression levels in all samples (KD patients and controls) for a particular gene of interest. We further demonstrated that the results in KDmarkers are strongly associated with KD immune responses. All analysis results can be downloaded for downstream experimental designs. KDmarkers is available online at https://cosbi.ee.ncku.edu.tw/KDmarkers/.

regCNN: identifying Drosophila genome-wide cis-regulatory modules via integrating the local patterns in epigenetic marks and transcription factor binding motifs

Transcription regulation in metazoa is controlled by the binding events of transcription factors (TFs) or regulatory proteins on specific modular DNA regulatory sequences called cis-regulatory modules (CRMs). Understanding the distributions of CRMs on a genomic scale is essential for constructing the metazoan transcriptional regulatory networks that help diagnose genetic disorders. While traditional reporter-assay CRM identification approaches can provide an in-depth understanding of functions of some CRM, these methods are usually cost-inefficient and low-throughput. It is generally believed that by integrating diverse genomic data, reliable CRM predictions can be made. Hence, researchers often first resort to computational algorithms for genome-wide CRM screening before specific experiments. However, current existing in silico methods for searching potential CRMs were restricted by low sensitivity, poor prediction accuracy, or high computation time from TFBS composition combinatorial complexity. To overcome these obstacles, we designed a novel CRM identification pipeline called regCNN by considering the base-by-base local patterns in TF binding motifs and epigenetic profiles. On the test set, regCNN shows an accuracy/auROC of 84.5%/92.5% in CRM identification. And by further considering local patterns in epigenetic profiles and TF binding motifs, it can accomplish 4.7% (92.5%–87.8%) improvement in the auROC value over the average value-based pure multi-layer perceptron model. We also demonstrated that regCNN outperforms all currently available tools by at least 11.3% in auROC values. Finally, regCNN is verified to be robust against its resizing window hyperparameter in dealing with the variable lengths of CRMs. The model of regCNN can be downloaded athttp://cobisHSS0.im.nuk.edu.tw/regCNN/.

YTLR: Extracting yeast transcription factor-gene associations from the literature using automated literature readers

Cells adapt to environmental stresses mainly via transcription reprogramming. Correct transcription control is mediated by the interactions between transcription factors (TF) and their target genes. These TF-gene associations can be probed by chromatin immunoprecipitation techniques and knockout experiments, revealing TF binding (TFB) and regulatory (TFR) evidence, respectively. Nevertheless, most evidence is still fragmentary in the literature and requires tremendous human resources to curate. We developed the first pipeline called YTLR (Yeast Transcription-regulation Literature Reader) to automate TF-gene relation extraction from the literature. YTLR first identifies articles with TFB and TFR information. Then TF-gene binding pairs are extracted from the TFB articles, and TF-gene regulatory associations are recognized from the TFR papers. On gathered test sets, YTLR achieves an AUC value of 98.8% in identifying articles with TFB evidence and AUC = 83.4% in extracting the detailed TF-gene binding pairs. And similarly, YTLR also obtains an AUC value of 98.2% in identifying TFR articles and AUC = 80.4% in extracting the detailed TF-gene regulatory associations. Furthermore, YTLR outperforms previous methods in both tasks. To facilitate researchers in extracting TF-gene transcriptional relations from large-scale queried articles, an automated and easy-to-use software tool based on the YTLR pipeline is constructed. In summary, YTLR aims to provide easier literature pre-screening for curators and help researchers gather yeast TF-gene transcriptional relation conclusions from articles in a high-throughput fashion. The YTLR pipeline software tool can be downloaded at https://github.com/cobisLab/YTLR/.

An Aggregation Method to Identify the RNA Meta-Stable Secondary Structure and its Functionally Interpretable Structure Ensemble

RNA can provide vital cellular functions through its secondary or tertiary structure. Due to the low-throughput nature of experimental approaches, studies on RNA structures mainly resort to computational methods. However, current existing tools fail to consider RNA structure ensembles and do not provide ways to decipher functional hypotheses for the new predictions. In this research, a novel method was proposed to identify the functionally interpretable structure ensemble of a given RNA sequence and provide the meta-stable structure, or the most frequently observed functional RNA cellular conformation, based on the ensemble. In the prediction of meta-stable structures, the proposed method outperformed existing tools on a yeast test set. The inferred functional aspects were then manually checked and demonstrated a micro-averaging F1 value of 0.92. Further, a biological example of the yeast ASH1-E1 element was discussed to articulate that these functional aspects can also suggest testable hypotheses. Then the proposed method was verified to be well applicable to other species through a human test set. Finally, the proposed method was demonstrated to show resistance to sequence length-dependent performance deterioration.

Identifying piRNA targets on mRNAs in C. elegans using a deep multi-head attention network

Background

Piwi-interacting RNAs (piRNAs) are the small non-coding RNAs (ncRNAs) that silence genomic transposable elements. And researchers found out that piRNA also regulates various endogenous transcripts. However, there is no systematic understanding of the piRNA binding patterns and how piRNA targets genes. While various prediction methods have been developed for other similar ncRNAs (e.g., miRNAs), piRNA holds distinctive characteristics and requires its own computational model for binding target prediction.

Results

Recently, transcriptome-wide piRNA binding events in C. elegans were probed by PRG-1 CLASH experiments. Based on the probed piRNA-messenger RNAs (mRNAs) binding pairs, in this research, we devised the first deep learning architecture based on multi-head attention to computationally identify piRNA targeting mRNA sites. In the devised deep network, the given piRNA and mRNA segment sequences are first one-hot encoded and undergo a combined operation of convolution and squeezing-extraction to unravel motif patterns. And we incorporate a novel multi-head attention sub-network to extract the hidden piRNA binding rules that can simulate the biological piRNA target recognition process. Finally, the true piRNA–mRNA binding pairs are identified by a deep fully connected sub-network. Our model obtains a supreme discriminatory power of AUC \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=$$\end{document}= 93.3% on an independent test set and successfully extracts the verified binding pattern of a synthetic piRNA. These results demonstrated that the devised model achieves high prediction performance and suggests testable potential biological piRNA binding rules.

Conclusions

In this research, we developed the first deep learning method to identify piRNA targeting sites on C. elegans mRNAs. And the developed deep learning method is demonstrated to be of high accuracy and can provide biological insights into piRNA–mRNA binding patterns. The piRNA binding target identification network can be downloaded from http://cosbi2.ee.ncku.edu.tw/data_download/piRNA_mRNA_binding.

Cancer DEIso: An integrative analysis platform for investigating differentially expressed gene-level and isoform-level human cancer markers

Transcript isoforms regulated by alternative splicing can substantially impact carcinogenesis, leading to a need to obtain clues for both gene differential expression and malfunctions of isoform distributions in cancer studies. The Cancer Genome Atlas (TCGA) project was launched in 2008 to collect cancer-related genome mutation raw data from the population. While many repositories tried to add insights into the raw data in TCGA, no existing database provides both comprehensive gene-level and isoform-level cancer stage marker investigation and survival analysis. We constructed Cancer DEIso to facilitate in-depth analyses for both gene-level and isoform-level human cancer studies. Patient RNA-seq data, sample sheets, patient clinical data, and human genome datasets were collected and processed in Cancer DEIso. And four functions to search differentially expressed genes/isoforms between cancer stages were implemented: (i) Search potential gene/isoform markers for a specified cancer type and its two stages; (ii) Search potentially induced cancer types and stages for a gene/isoform; (iii) Expression survival analysis on a given gene/isoform for some cancer; (iv) Gene/isoform stage expression comparison visualization. As an example, we demonstrate that Cancer DEIso can indicate potential colorectal cancer isoform diagnostic markers that are not easily detected when only gene-level expressions are considered. Cancer DEIso is available at http://cosbi4.ee.ncku.edu.tw/DEIso/.

Role of the Inflammatory Response of RAW 264.7 Cells in the Metastasis of Novel Cancer Stem-Like Cells

Background and objectives: Tumor progression and the immune response are intricately linked. Additionally, the presence of macrophages in the microenvironment is essential for carcinogenesis, but regulation of the polarization of M1- and M2-like macrophages and their role in metastasis remain unclear. Based on previous studies, both reactive oxygen species (ROS) and the endoplasmic reticulum (ER) are emerging as key players in macrophage polarization. While it is known that cancers alter macrophage inflammatory responses to promote tumor progression, there is limited knowledge regarding how they affect the macrophage-dependent innate host defense. Materials and methods: We detected the levels of ROS, the ability of chemotaxis, the expressions of markers of M1-/M2-like macrophages in RAW264.7 in presence of T2- and T2C-conditioned medium. Results: The results of this study indicated that ROS levels were decreased in RAW 264.7 cells when cultured with T2C-conditioned medium, while there was an improvement in chemotaxis abilities. We also found that the M2-like macrophages were characterized by an elongated shape in RAW 264.7 cells cultured in T2C-conditioned medium, which had increased CD206 expression but decreased expression of CD86 and inducible nitric oxide synthase. Suppression of ER stress shifted polarized M1-like macrophages toward an M2-like phenotype in RAW 264.7 cells cultured in T2C-conditioned medium. Conclusions: Taken together, we conclude that the polarization of macrophages is associated with the alteration of cell shape, ROS accumulation, and ER stress.

Human IRES Atlas: an integrative platform for studying IRES-driven translational regulation in humans

It is now known that cap-independent translation initiation facilitated by internal ribosome entry sites (IRESs) is vital in selective cellular protein synthesis under stress and different physiological conditions. However, three problems make it hard to understand transcriptome-wide cellular IRES-mediated translation initiation mechanisms: (i) complex interplay between IRESs and other translation initiation–related information, (ii) reliability issue of in silico cellular IRES investigation and (iii) labor-intensive in vivo IRES identification. In this research, we constructed the Human IRES Atlas database for a comprehensive understanding of cellular IRESs in humans. First, currently available and suitable IRES prediction tools (IRESfinder, PatSearch and IRESpy) were used to obtain transcriptome-wide human IRESs. Then, we collected eight genres of translation initiation–related features to help study the potential molecular mechanisms of each of the putative IRESs. Three functional tests (conservation, structural RNA–protein scores and conditional translation efficiency) were devised to evaluate the functionality of the identified putative IRESs. Moreover, an easy-to-use interface and an IRES–translation initiation interaction map for each gene transcript were implemented to help understand the interactions between IRESs and translation initiation–related features. Researchers can easily search/browse an IRES of interest using the web interface and deduce testable mechanism hypotheses of human IRES-driven translation initiation based on the integrated results. In summary, Human IRES Atlas integrates putative IRES elements and translation initiation–related experiments for better usage of these data and deduction of mechanism hypotheses.

Database URL: http://cobishss0.im.nuk.edu.tw/Human_IRES_Atlas/

Transcription factor regulatory modules provide the molecular mechanisms for functional redundancy observed among transcription factors in yeast

BACKGROUND

Current technologies for understanding the transcriptional reprogramming in cells include the transcription factor (TF) chromatin immunoprecipitation (ChIP) experiments and the TF knockout experiments. The ChIP experiments show the binding targets of TFs against which the antibody directs while the knockout techniques find the regulatory gene targets of the knocked-out TFs. However, it was shown that these two complementary results contain few common targets. Researchers have used the concept of TF functional redundancy to explain the low overlap between these two techniques. But the detailed molecular mechanisms behind TF functional redundancy remain unknown. Without knowing the possible molecular mechanisms, it is hard for biologists to fully unravel the cause of TF functional redundancy.

RESULTS

To mine out the molecular mechanisms, a novel algorithm to extract TF regulatory modules that help explain the observed TF functional redundancy effect was devised and proposed in this research. The method first searched for candidate TF sets from the TF binding data. Then based on these candidate sets the method utilized the modified Steiner Tree construction algorithm to construct the possible TF regulatory modules from protein-protein interaction data and finally filtered out the noise-induced results by using confidence tests. The mined-out regulatory modules were shown to correlate to the concept of functional redundancy and provided testable hypotheses of the molecular mechanisms behind functional redundancy. And the biological significance of the mined-out results was demonstrated in three different biological aspects: ontology enrichment, protein interaction prevalence and expression coherence. About 23.5% of the mined-out TF regulatory modules were literature-verified. Finally, the biological applicability of the proposed method was shown in one detailed example of a verified TF regulatory module for pheromone response and filamentous growth in yeast.

CONCLUSION

In this research, a novel method that mined out the potential TF regulatory modules which elucidate the functional redundancy observed among TFs is proposed. The extracted TF regulatory modules not only correlate the molecular mechanisms to the observed functional redundancy among TFs, but also show biological significance in inferring TF functional binding target genes. The results provide testable hypotheses for biologists to further design subsequent research and experiments.

[An interlaboratory comparison study on the detection of RUNX1-RUNX1T1 fusion transcript levels and WT1 transcript levels]

Objective: To investigate the current status and real performance of the detection of RUNX1-RUNX1T1 fusion transcript levels and WT1 transcript levels in China through interlaboratory comparison. Methods: Peking University People's Hospital (PKUPH) prepared the samples for comparison. That is, the fresh RUNX1-RUNX1T1 positive (+) bone morrow nucleated cells were serially diluted with RUNX1-RUNX1T1 negative (-) nucleated cells from different patients. Totally 23 sets with 14 different samples per set were prepared. TRIzol reagent was added in each tube and thoroughly mixed with cells for homogenization. Each laboratory simultaneously tested RUNX1-RUNX1T1 and WT1 transcript levels of one set of samples by real-time quantitative PCR method. All transcript levels were reported as the percentage of RUNX1-RUNX1T1 or WT1 transcript copies/ABL copies. Spearman correlation coefficient between the reported transcript levels of each participated laboratory and those of PKUPH was calculated. Results: ①RUNX1-RUNX1T1 comparison: 9 samples were (+) and 5 were (-) , the false negative and positive rates of the 20 participated laboratories were 0 (0/180) and 5% (5/100) , respectively. The reported transcript levels of all 9 positive samples were different among laboratories. The median reported transcript levels of 9 positive samples were from 0.060% to 176.7%, which covered 3.5-log. The ratios of each sample's highest to the lowest reported transcript levels were from 5.5 to 12.3 (one result which obviously deviated from other laboratories' results was not included) , 85% (17/20) of the laboratories had correlation coefficient ≥0.98. ②WT1 comparison: The median reported transcript levels of all 14 samples were from 0.17% to 67.6%, which covered 2.6-log. The ratios of each sample's highest to the lowest reported transcript levels were from 5.3-13.7, 62% (13/21) of the laboratories had correlation coefficient ≥0.98. ③ The relative relationship of the reported RUNX1-RUNX1T1 transcript levels between the participants and PKUPH was not always consistent with that of WT1 transcript levels. Both RUNX1-RUNX1T1 and WT1 transcript levels from 2 and 7 laboratories were individually lower than and higher than those of PKUPH, whereas for the rest 11 laboratories, one transcript level was higher than and the other was lower than that of PKUPH. Conclusion: The reported RUNX1-RUNX1T1 and WT1 transcript levels were different among laboratories for the same sample. Most of the participated laboratories reported highly consistent result with that of PKUPH. The relationship between laboratories of the different transcript levels may not be the same.

A Novel Strengthening Method for Damaged Pipeline under High Temperature Using Inorganic Insulation Material and Carbon Fiber Reinforced Plastic Composite Material

In this paper, a strengthening method for the damaged high-temperature steel pipeline using inorganic insulation material which was confined by carbon fiber reinforcement plastic (CFRP) composite materials was proposed. Two inorganic insulation materials were composed of magnesium phosphate cement (MPC) mixing with perlite and vermiculite powders, respectively. The influences of insulation material composites with various ratios of the perlite or vermiculite powder were discussed, in terms of compressive strength and thermal conductivity coefficients of inorganic insulation materials. The insulation materials confined by carbon fiber reinforced polymer jackets for enhancing the mechanical behavior were also investigated. From the experimental results, the main finding of the work was that the inorganic insulation materials added to the perlite powder represented greater insulation capability than added vermiculite ones under the condition of the same compressive strength. Different ratios of perlite inorganic insulation material cylinders with the dimension of ϕ 10 cm × 20 cm were confined by one layer and two layers of CFRP composite material. The compressive strength of the specimens increased by 258%–927% after using 1-layer CFRP composite material and increased by 480%–1541% after applying 2-layer CFRP composite material. A peak strength prediction model of insulation materials confined by CFRP was proposed, and it was found that the proposed model accurately predicted the peak strength of the inorganic insulation material cylinder. Finally, a verification test of the strengthening method for damaged high-temperature pipeline was performed to prove that the proposed strengthening method is feasible.

Immunohistochemical localization of sex hormone receptors in two Raillietina tapeworms

Sex hormone receptors play critical roles in development and reproduction. However, it is not known whether they exist in Raillietina tapeworms, and if they do, whether they have a similar function to that in vertebrates. We examined the immunohistochemical distributions of androgen receptors (ARs), estrogen receptors (ERs), and progesterone receptors (PRs) in the tissues of two tapeworm species: Raillietina echinobothrida and Raillietina tetragona. Immunopositive ARs were found in the entire reproductive system of R. echinobothrida, including the testes, ovaries, and oocysts, and weakly immunopositive ERs and PRs were found in the testes, ovaries, and oocysts. Immunopositive ARs were also found throughout the entire reproductive system of R. tetragona, including the testes, ovaries, and oocysts, and weakly immunopositive ERs were in the testes and oocysts; the PRs were distributed in an immunonegative manner. The results show that androgens and their receptors play critical roles in reproductive system development in the two tapeworms. The immunoreactivity and tissue localizations of the sex hormone receptors suggest that, in both species, they have similar functions as in vertebrates, and modulate reproduction.

Spinal intraosseous epidural arteriovenous fistula with perimedullary drainage obliterated with Onyx embolization: case report

The authors report an extremely rare case of spinal intraosseous epidural arteriovenous fistula (AVF) with perimedullary vein reflux causing symptoms of myelopathy. The intraosseous fistula tracts were completely obliterated with Onyx embolic agent, resulting in a total resolution of symptoms. The unique features of this case include the rare location of the fistula in the vertebral body and the association of the fistula with a compressive fracture. Imaging studies confirmed these hemodynamic findings and provided clarity and direct evidence regarding the association of epidural AVF formation with the vertebral compressive fracture. The authors also propose a possible disease evolution based on the previously adduced reflux-impending mechanism.

The Yeast Nucleosome Atlas (YNA) database: an integrative gene mining platform for studying chromatin structure and its regulation in yeast

Background

Histone modification and remodeling play crucial roles in regulating gene transcription. These post-translational modifications of histones function in a combinatorial fashion and can be recognized by specific histone-binding proteins, thus regulating gene transcription. Therefore, understanding the combinatorial patterns of the histone code is vital to understanding the associated biological processes. However, most of the datasets regarding histone modification and chromatin regulation are scattered across various studies, and no comprehensive search and query tool has yet been made available to retrieve genes bearing specific histone modification patterns and regulatory proteins.

Description

For this reason, we developed the Yeast Nucleosome Atlas database, or the YNA database, which integrates the available experimental data on nucleosome occupancy, histone modifications, the binding occupancy of regulatory proteins, and gene expression data, and provides the genome-wide gene miner to retrieve genes with a specific combination of these chromatin-related datasets. Moreover, the biological significance analyzer, which analyzes the enrichments of histone modifications, binding occupancy, transcription rate, and functionality of the retrieved genes, was constructed to help researchers to gain insight into the correlation among chromatin regulation and transcription.

Conclusions

Compared to previously established genome browsing databases, YNA provides a powerful gene mining and retrieval interface, and is an investigation tool that can assist users to generate testable hypotheses for studying chromatin regulation during transcription. YNA is available online at http://cosbi3.ee.ncku.edu.tw/yna/.

iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation

Background

Comprehensive characterization of the phosphoproteome in living cells is critical in signal transduction research. But the low abundance of phosphopeptides among the total proteome in cells remains an obstacle in mass spectrometry-based proteomic analysis. To provide a solution, an alternative analytic strategy to confidently identify phosphorylated peptides by using the alkaline phosphatase (AP) treatment combined with high-resolution mass spectrometry was provided. While the process is applicable, the key integration along the pipeline was mostly done by tedious manual work.

Results

We developed a software toolkit, iPhos, to facilitate and streamline the work-flow of AP-assisted phosphoproteome characterization. The iPhos tookit includes one assister and three modules. The iPhos Peak Extraction Assister automates the batch mode peak extraction for multiple liquid chromatography mass spectrometry (LC-MS) runs. iPhos Module-1 can process the peak lists extracted from the LC-MS analyses derived from the original and dephosphorylated samples to mine out potential phosphorylated peptide signals based on mass shift caused by the loss of some multiples of phosphate groups. And iPhos Module-2 provides customized inclusion lists with peak retention time windows for subsequent targeted LC-MS/MS experiments. Finally, iPhos Module-3 facilitates to link the peptide identifications from protein search engines to the quantification results from pattern-based label-free quantification tools. We further demonstrated the utility of the iPhos toolkit on the data of human metastatic lung cancer cells (CL1-5).

Conclusions

In the comparison study of the control group of CL1-5 cell lysates and the treatment group of dasatinib-treated CL1-5 cell lysates, we demonstrated the applicability of the iPhos toolkit and reported the experimental results based on the iPhos-facilitated phosphoproteome investigation. And further, we also compared the strategy with pure DDA-based LC-MS/MS phosphoproteome investigation. The results of iPhos-facilitated targeted LC-MS/MS analysis convey more thorough and confident phosphopeptide identification than the results of pure DDA-based analysis.

cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila

BACKGROUND

Cis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs.

DESCRIPTION

It is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality.

CONCLUSIONS

cisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms of metazoan gene regulation. We believe that the information deposited in cisMEP will greatly facilitate the comparative usage of different CRM prediction tools and will help biologists to study the modular regulatory mechanisms between different TFs and their target genes.

YTRP: a repository for yeast transcriptional regulatory pathways

Regulatory targets of transcription factors (TFs) can be identified by the TF perturbation experiments, which reveal the expression changes owing to the perturbation (deletion or overexpression) of TFs. But the identified targets of a given TF consist of both direct and indirect regulatory targets. It has been shown that most of the TFPE-identified regulatory targets are indirect, indicating that TF-gene regulation is mainly through transcriptional regulatory pathways (TRPs) consisting of intermediate TFs. Without identification of these TRPs, it is not easy to understand how a TF regulates its indirect targets. Because there is no such database depositing the potential TRPs for Saccharomyces cerevisiae now, this motivates us to construct the YTRP (Yeast Transcriptional Regulatory Pathway) database. For each TF-gene regulatory pair under different experimental conditions, all possible TRPs in two underlying networks (constructed using experimentally verified TF-gene binding pairs and TF-gene regulatory pairs from the literature) for the specified experimental conditions were automatically enumerated by TRP mining procedures developed from the graph theory. The enumerated TRPs of a TF-gene regulatory pair provide experimentally testable hypotheses for the molecular mechanisms behind a TF and its regulatory target. YTRP is available online at http://cosbi3.ee.ncku.edu.tw/YTRP/. We believe that the TRPs deposited in this database will greatly improve the usefulness of TFPE data for yeast biologists to study the regulatory mechanisms between a TF and its knocked-out targets.

Database URL: http://cosbi3.ee.ncku.edu.tw/YTRP/

Inferring functional transcription factor-gene binding pairs by integrating transcription factor binding data with transcription factor knockout data

Background

Chromatin immunoprecipitation (ChIP) experiments are now the most comprehensive experimental approaches for mapping the binding of transcription factors (TFs) to their target genes. However, ChIP data alone is insufficient for identifying functional binding target genes of TFs for two reasons. First, there is an inherent high false positive/negative rate in ChIP-chip or ChIP-seq experiments. Second, binding signals in the ChIP data do not necessarily imply functionality.

Methods

It is known that ChIP-chip data and TF knockout (TFKO) data reveal complementary information on gene regulation. While ChIP-chip data can provide TF-gene binding pairs, TFKO data can provide TF-gene regulation pairs. Therefore, we propose a novel network approach for identifying functional TF-gene binding pairs by integrating the ChIP-chip data with the TFKO data. In our method, a TF-gene binding pair from the ChIP-chip data is regarded to be functional if it also has high confident curated TFKO TF-gene regulatory relation or deduced hypostatic TF-gene regulatory relation.

Results and conclusions

We first validated our method on a gathered ground truth set. Then we applied our method to the ChIP-chip data to identify functional TF-gene binding pairs. The biological significance of our identified functional TF-gene binding pairs was shown by assessing their functional enrichment, the prevalence of protein-protein interaction, and expression coherence. Our results outperformed the results of three existing methods across all measures. And our identified functional targets of TFs also showed statistical significance over the randomly assigned TF-gene pairs. We also showed that our method is dataset independent and can apply to ChIP-seq data and the E. coli genome. Finally, we provided an example showing the biological applicability of our notion.

Co-modulated behavior and effects of differentially expressed miRNA in colorectal cancer

Background

MicroRNAs (miRNAs) are short noncoding RNAs (approximately 22 nucleotides in length) that play important roles in colorectal cancer (CRC) progression through silencing gene expression. Numerous dysregulated miRNAs simultaneously participate in the process of colon cancer development. However, the detailed mechanisms and biological functions of co-expressed miRNA in colorectal carcinogenesis have yet to be fully elucidated.

Results

The objective of this study was to identify the dysfunctional miRNAs and their target mRNAs using a wet-lab experimental and dry-lab bioinformatics approach. The differentially expressed miRNA candidates were identified from 2 miRNA profiles, and were confirmed in CRC clinical samples using reported target genes of dysfunctional miRNAs to perform functional pathway enrichment analysis. Potential target gene candidates were predicted by an in silico search, and their expression levels between normal and colorectal tumor tissues were further analyzed using real-time polymerase chain reaction (RT-PCR).

We identified 5 miRNAs (miR-18a, miR-31, miR-96, miR-182, and miR-224) and 10 miRNAs (miR-1, miR-9, miR-10b, miR-133a, miR-143, miR-137, miR-147b, miR-196a/b, and miR-342) that were significantly upregulated and downregulated in colon tumors, respectively. Bioinformatics analysis showed that the known targets of these dysregulated miRNAs simultaneously participated in epithelial-to-mesenchymal transition (EMT), cell growth, cell adhesion, and cell cycles. In addition, we identified that several pivotal target gene candidates may be comodulated by dysfunctional miRNAs during colon cancer progression. Finally, 7 candidates were proven to be differentially expressed, and had an anti-correlationship with dysregulated miRNA in 48 CRC samples.

Conclusion

Fifteen dysfunctional miRNAs were engaged in metastasis-associated pathways through comodulating 7 target genes, which were identified by using a multi-step approach. The roles of these candidate genes are worth further exploration in the progression of colon cancer, and could potentially be targets in future therapy.

Complex coil assisted single coil embolization for small intracranial aneurysm

The purpose of the technical note is to introduce the complex coil assisted coil embolization method in the treatment of intracranial small aneurysm, in order to enhance the safety of the procedure. The first microcatheter was navigated into the aneurysm sac and the ultrasoft coil was used as the embolization coil. If the embolizations coil could not stay within the aneurysm sac smoothly, such as coil herniation into parent artery during the delivery process. The second microcatheter would be navigated to the aneurysm level in the parent artery. Another complex coil was delivered within the parent artery via the second microcatheter to provide the neck bridge effect in order to enhance the stability of embolization coil. Besides, the protection coil will not disturb the parent artery flow. While the embolization coil was put into the aneurysm sac smoothly under the help of complex protective coil, the protective coil was then withdrawn gently. We use the most magnified view, dual-plane approach simultaneously to observe the stability of embolization coil. The embolization coil would be detached without any evidence of coil motion or vibration. The new method could provide the physiological protective method, without leaving any protective device such as stent within the parent artery.

Auditory efferent dysfunction in normal-hearing chronic idiopathic tinnitus

OBJECTIVE

To investigate the function of the auditory efferent system in patients with chronic idiopathic tinnitus, but normal pure-tone audiograms.

METHODS

We studied 15 subjects with normal hearing that had experienced either unilateral or bilateral persistent tinnitus for at least 3 months. The ears of the 15 subjects were classified into tinnitus-positive-ear (TPE) and tinnitus-negative-ear (TNE) groups. The control-ear group (CE) comprised the ears of 15 subjects with normal hearing and no tinnitus. We measured different types of otoacoustic emissions (OAEs), including spontaneous (SOAEs), transient evoked (TEOAEs), and distortion product (DPOAEs). We also analyzed contralateral suppression of OAEs and auditory brainstem responses (ABRs). Data were compared among TPE, TNE, and CE groups.

RESULTS

The data associated with cochlear mechanics, including the prevalence of SOAEs, the number of SOAE peaks, and the overall TEOAE responses in the absence of a contralateral stimulus, were not significantly different among the TPE, TNE, and CE groups. In the TPE group, contralateral stimuli failed to significantly suppress overall TEOAEs, and contralateral suppression of DPOAEs was significantly reduced over a limited frequency range. Furthermore, the TPE group showed prolonged latencies in waves III and V of ABRs.

CONCLUSION

This study demonstrated that abnormal contralateral suppression of OAEs and ABRs indicated a dysfunction in the ipsilateral efferent medial olivocochlear system; this might play a role in normal-hearing tinnitus.

Identifying biologically interpretable transcription factor knockout targets by jointly analyzing the transcription factor knockout microarray and the ChIP-chip data

Background

Transcription factor knockout microarrays (TFKMs) provide useful information about gene regulation. By using statistical methods for detecting differentially expressed genes between the gene expression microarray data of the mutant and wild type strains, the TF knockout targets of the knocked-out TF can be identified. However, the identified TF knockout targets may contain a certain amount of false positives due to the experimental noises inherent in the high-throughput microarray technology. Even if the identified TF knockout targets are true, the molecular mechanisms of how a TF regulates its TF knockout targets remain unknown by this kind of statistical approaches.

Results

To solve these two problems, we developed a method to filter out the false positives in the original TF knockout targets (identified by statistical approaches) so that the biologically interpretable TF knockout targets can be extracted. Our method can further generate experimentally testable hypotheses of the molecular mechanisms of how a TF regulates its biologically interpretable TF knockout targets. The details of our method are as follows. First, a TF binding network was constructed using the ChIP-chip data deposited in the YEASTRACT database. Then for each original TF knockout target, it is said to be biologically interpretable if a path (in the TF binding network) from the knocked-out TF to this target could be identified by our path search algorithm. The identified path explains how the TF may regulate this target either directly by binding to its promoter or indirectly through intermediate TFs. After checking all the original TF knockout targets, the biologically interpretable ones could be extracted and the false positives could be filtered out. We validated the biological significance of our refined (i.e., biologically interpretable) TF knockout targets by assessing their functional enrichment, expression coherence, and the prevalence of protein-protein interactions. Our refined TF knockout targets outperform the original TF knockout targets across all measures.

Conclusions

By jointly analyzing the TFKM and ChIP-chip data, our method can extract the biologically interpretable TF knockout targets by identifying paths (in the TF binding network) from the knocked-out TF to these targets. The identified paths form experimentally testable hypotheses regarding the molecular mechanisms of how a TF may regulate its knockout targets. About seven hundred hypotheses generated by our methods have been experimentally validated in the literature. Our work demonstrates that integrating different data sources is a powerful approach to study complex biological systems.

Photoconduction mechanism of oxygen sensitization in InN nanowires

The photoconduction (PC) mechanism in indium nitride (InN) nanowires (NWs) has been investigated via environment-, temperature-, and power-dependent measurements. The adsorbed oxygen-induced modulation of the surface state is proposed to be the leading factor in the long lifetime or high gain transport and in sensitizing photocurrent generation in the InN NWs. The electron trapping effect by adsorbed oxygen can be verified by the increased activation energy from 33 ± 4 (in vacuum) to 58 ± 2 meV (in oxygen). The observed supralinear power dependence of photocurrent also suggests the presence of acceptor states that influence the carrier recombination behavior and compensate the thermal carriers in the InN NWs. The potential influence of native oxide on the molecule-sensitive PC in this nitride nanomaterial is also inferred.

Iatrogenic and fatal arterial air embolism during the CT scan

Systemic and fatal arterial air embolism during the computed tomography (CT) scan is rarely reported in English-based literature. Iatrogenic air embolism happening during the CT scan is often related to the injector, usually venous air embolism and asymptomatic. We report one fatal and extensive systemic arterial air embolism because of one error that happened during a brain CT scan. The mechanism is different from the reported cases in the literature. The possible mechanism and pathogenesis are well discussed to alert clinicians and prevent the recurrence of such complication.

Preoperative embolization of carotid body tumor by direct percutaneous intratumoral injection of N-butyl cyanoacrylate glue assisted with balloon protection technique

Substantial intraoperative bleeding during surgical removal of carotid body tumor may be a major problem in the management of these highly vascularized tumors. Traditional preoperative embolization via a transarterial access has proved effective but is often limited by complex vascular anatomy and small feeding vessels that is difficult to catheterize. We report two cases of carotid body tumor treated with direct puncture and intratumoral injection of N-butyl cyanoacrylate glue (NBCA) assisted with balloon protection technique for preoperative devascularization. The result was impressive and minimal bleeding loss during surgery was observed.

Model-based segmentation of flexor tendons from magnetic resonance images of finger joints

Trigger finger is a common hand disease, causing swelling, painful popping and clicking in moving the affected finger joint. To better evaluate patients with trigger finger, segmentation of flexor tendons from magnetic resonance (MR) images of finger joints, which can offer detailed structural information of tendons to clinicians, is essential. This paper presents a novel model-based method with three stages for automatically segmenting the flexor tendons. In the first stage, a set of tendon contour models (TCMs) is initialized from the most proximal cross-sectional image via two-step ellipse estimation. Each of the TCMs is then propagated to its distally adjacent image by affine registration. The propagation is sequentially performed along the proximal-distal direction until the most distal image is reached, as the second stage of segmentation. The TCMs on each cross-sectional image are refined in the last stage with the snake deformation. MR volumes of three subjects were used to validate the segmentation accuracy. Compared with the manual results, our method showed good accuracy with small average margins of errors (within 0.5 mm) and large overlapping ratio (dice similarity coefficient above 0.8). Overall, the proposed method has great potential for morphological change assessment of flexor tendons and pulley-tendon system modeling for image guided surgery.

Computational modeling of ultraviolet disinfection

The efficient design of ultraviolet light (UV) systems for water and wastewater treatment requires detailed knowledge of the patterns of fluid motion that occur in the disinfection channel. This knowledge is increasingly being obtained using Computational Fluid Dynamics (CFD) software packages that solve the equations governing turbulent fluid-flow motion. In this work, we present predictions of the patterns of flow and the extent of disinfection in a conventional reactor consisting of an open channel with an array of UV lamps placed with their axes perpendicular to the direction of flow. It is shown that the resulting flow is inherently unsteady due to the regular shedding of vortices from the submerged lamps. It is also shown that the accurate prediction of the hydraulic residence time and, consequently, the extent of disinfection is strongly dependent on the ability of the CFD method to capture the occurrence and strength of the vortex shedding, and its effects on the turbulent mixing processes.

Gastrointestinal stromal tumors: computed tomographic features and prediction of malignant risk from computed tomographic imaging

BACKGROUND

Gastrointestinal stromal tumors (GISTs) are specific, generally Kit (CD117)-positive, mesenchymal tumors of the gastrointestinal tract encompassing a majority of tumors previously considered gastrointestinal smooth muscle tumors. Our aim was to characterize the computed tomographic findings and predict malignant risk from computed tomography for the evaluation of GISTs.

METHODS

The computed tomographic images of 39 patients with pathologically and immunohistochemically proven GISTs were reviewed by 2 radiologists, and the final interpretations were reached by consensus. Images were assessed for the size, contour, growth pattern, boundary, degree of enhancement, and necrosis of the tumors. The presence of calcification within the lesions, abdominal lymphadenopathy, ascites, and bowel obstruction were also recorded. Categorical variables were compared using Fishers exact test. Univariate and multivariate logistic regression analyses were used for selection of significant predictors of high-risk malignancy. In addition, the relationships between computed tomographic features and tumor size were assessed by means of nonparametric univariate analysis with the MannWhitney U test and KruskalWallis test.

RESULTS

Both old age and larger tumor size (>or= 5 cm) were statistically significant in the univariate logistic analysis for high-risk malignant tumors (p < 0.25). However, in multivariate logistic regression, only larger tumor size (>or= 5 cm) was found to have final statistical significance for high-risk malignant GISTs (p < 0.05). In addition, more exophytic growth pattern (p < 0.01), more lobulated appearance (p < 0.01), good enhancement (p < 0.05),and more necrosis (p < 0.01) of masses were more often observed in larger GISTs than small ones on computed tomography.

CONCLUSION

Larger tumor size (>or= 5 cm) was found to have a predictive value with respect to high-risk malignant GISTs.

Neural correlates of antisaccade deficits in schizophrenia, an fMRI study

Schizophrenia patients were known to have oculomotor abnormalities for decades and several studies had found antisaccade impairment to be a biological marker of schizophrenia. In this study, we used functional magnetic resonance imaging (fMRI) to investigate the neural circuits responsible for antisaccade deficits in schizophrenia. Ten normal controls and 10 DSM-IV schizophrenia patients performed antisaccade tasks and control tasks during fMRI. Data were analyzed and task-specific activations were identified using Statistical Parametric Mapping (SPM-2). In normal subjects, antisaccade tasks activated bilateral frontal eye fields, supplementary eye fields, inferior frontal gyrus, superior parietal lobules, inferior parietal lobules, occipital visual cortex, cerebellum, thalamus, and lentiform nuclei (P<0.001). By contrast, schizophrenia patients failed to show activation in bilateral lentiform nucleus, bilateral thalamus, and left inferior frontal gyrus during antisaccade performance. Our findings suggest that schizophrenic antisaccade deficits are associated with dysfunction of fronto-striatal-thalamo-cortical circuits previously demonstrated to be responsible for suppression of the reflexive saccade. Left inferior frontal gyrus, which was known to be responsible for response inhibition on "go/no-go" testing, also plays an important role in schizophrenic antisaccade deficit.

An integrated healthcare enterprise information portal and healthcare information system framework

The paper presents an integrated, distributed Healthcare Enterprise Information Portal (HEIP) and Hospital Information Systems (HIS) framework over wireless/wired infrastructure at National Taiwan University Hospital (NTUH). A single sign-on solution for the hospital customer relationship management (CRM) in HEIP has been established. The outcomes of the newly developed Outpatient Information Systems (OIS) in HIS are discussed. The future HEIP blueprints with CRM oriented features: e-Learning, Remote Consultation and Diagnosis (RCD), as well as on-Line Vaccination Services are addressed. Finally, the integrated HEIP and HIS architectures based on the middleware technologies are proposed along with the feasible approaches. The preliminary performance of multi-media, time-based data exchanges over the wireless HEIP side is collected to evaluate the efficiency of the architecture.

Separation of gamma-globulins from porcine plasma by reversed micellar extraction

Factors affecting the separation of gamma-globulins from porcine plasma using reversed micelles were screened based on a fractional factorial design. The optimal processing conditions for obtaining the maximum yield of gamma-globulins under various constraints of product purity were determined using response surface methodology (RSM) and nonlinear programming. Results showed that the pH and sodium chloride concentration of the aqueous phase, and the concentration of surfactant (bis-(2-ethylhexyl) sulfosuccinate sodium salt, AOT) of the organic phase were the most important factors affecting the extraction performance. An eighty-five percent product purity and ninety-seven percent yield were obtained under the extraction conditions of 400 mM NaCl, 350 mM AOT, and pH 7.0. The extract exhibited immunological reactivity against anti-pig IgG.

Epstein-Barr virus-associated recurrent necrotic papulovesicles with repeated bacterial infections ending in sepsis and death: consideration of the relationship between Epstein-Barr virus infection and immune defect

The disease of Epstein-Barr virus (EBV) -associated recurrent necrotic papulovesicles is a distinct clinicopathologic entity different from classic hydroa vacciniforme (HV). A few patients have been reported as atypical HV with systemic involvement, development of lymphoma, and poor prognosis. We describe a patient with recurrent necrotic papulovesicles and multiple varioliform scars in both sun-exposed and covered areas. In contrast to cases of previously reported atypical HV, our patient suffered from repeated bacterial infections on various sites ending in sepsis and death, but without malignant transformation. EBV was detected in the lymphoid cells from the skin lesions by anti-latent membrane protein (LMP) antibody and in situ hybridization. We suggest that the repeated bacterial infections in this case raise the possibility of an association of EBV infection with increased susceptibility to bacterial infections.

Novel cell immobilization method utilizing centrifugal force to achieve high-density hepatocyte culture in porous scaffold

Cell seeding is one of the key procedures in the construction of tissue-engineered organs. In our previous efforts to create a bioartificial liver, high-density cultures of hepatocytes (>1 x 10(7) cells/1 cm(3)-substrate) and long-term maintenance of metabolic function were achieved with a packed-bed reactor utilizing porous poly(vinyl formal) (PVF) resin as a scaffold. However, a low seeding efficiency of about 30% remains a major obstacle to the scaleup of the reactor. In the present study, a new cell seeding method, centrifugal cell immobilization (CCI), which is based on alternating centrifugation and resuspension, was used to achieve high-density seeding and improve the seeding efficiency. Using the CCI method, the maximum density of the immobilized hepatocytes reached 3.8 x 10(7) cells/1 cm(3)-PVF, and the seeding efficiency was improved to about 43% after a relatively short immobilization process (about 15 min). Moreover, further improvement of the seeding efficiency was obtained by serial immobilization procedures. Thus, we concluded that this method is useful and effective for seeding cells into 3-dimensional scaffolds.

A specific molar ratio of stabilizer to protein is required for storage stability of a lyophilized monoclonal antibody

The selection of the appropriate excipient and the amount of excipient required to achieve a 2-year shelf-life is often done by using iso-osmotic concentrations of excipients such as sugars (e.g., 275 mM sucrose or trehalose) and salts. Excipients used for freeze-dried protein formulations are selected for their ability to prevent protein denaturation during the freeze-drying process as well as during storage. Using a model recombinant humanized monoclonal antibody (rhuMAb HER2), we assessed the impact of lyoprotectants, sucrose, and trehalose, alone or in combination with mannitol, on the storage stability at 40 degrees C. Molar ratios of sugar to protein were used, and the stability of the resulting lyophilized formulations was determined by measuring aggregation, deamidation, and oxidation of the reconstituted protein and by infrared (IR) spectroscopy (secondary structure) of the dried protein. A 360:1 molar ratio of lyoprotectant to protein was required for storage stability of the protein, and the sugar concentration was 3-4-fold below the iso-osmotic concentration typically used in formulations. Formulations with combinations of sucrose (20 mM) or trehalose (20 mM) and mannitol (40 mM) had comparable stability to those with sucrose or trehalose alone at 60 mM concentration. A formulation with 60 mM mannitol alone provided slightly less protection during storage than 60 mM sucrose or trehalose. The disaccharide/mannitol formulations also inhibited deamidation during storage to a greater extent than the lyoprotectant formulations alone. The reduction in aggregation and deamidation during storage correlated directly with inhibition of unfolding during lyophilization, as assessed by IR spectroscopy. Thus, it appears that the protein must be retained in its native-like state during freeze-drying to assure storage stability in the dried solid. Long-term studies (23-54 months) performed at 40 degrees C revealed that the appropriate molar ratio of sugar to protein stabilized against aggregation and deamidation for up to 33 months. Therefore, long-term storage at room temperature or above may be achieved by proper selection of the molar ratio and sugar mixture. Overall, a specific sugar/protein molar ratio was sufficient to provide storage stability of rhuMAb HER2.

Sweet's syndrome with abscess-like lesions in a patient with acute myelogenous leukemia

We describe a 49-year-old man with acute myelogenous leukemia associated with Sweet's syndrome and abscess-like lesions mimicking an infectious disease. Although blisters may be included in the clinical spectrum, frank non-infectious abscesses have not been reported as far as we know. Clinicians should be familiar with this clinical and histopathologic variant of Sweet's syndrome. It is mandatory to make every effort to find an infectious cause for abscesses before a diagnosis of Sweet's syndrome is made.

Effect of zinc binding and precipitation on structures of recombinant human growth hormone and nerve growth factor

Metal-induced precipitation of protein therapeutics is being used and further developed as a processing step in protein formulation and may have utility in protein purification and bulk storage. In such processes, it is imperative that native protein structure is maintained and the metal complexation is reversible. In the current study, we investigated the effects of zinc-induced precipitation on recombinant human growth hormone (rhGH) and recombinant human nerve growth factor (rhNGF). On the addition of ethylenediaminetetraacetic acid (EDTA), the precipitates were dissolved, yielding complete recovery of native protein in both cases. Both proteins have specific metal binding sites and require specific molar ratios of zinc to protein to initiate precipitation (zinc:rhGH > 2:1; zinc:rhNGF > 18:1). Furthermore, the secondary structures of both proteins were unperturbed in soluble zinc complexes and zinc-induced precipitates, as measured by infrared and circular dichroism spectroscopies. The soluble zinc complex of rhGH had minor tertiary structural alterations, whereas zinc binding did not alter the tertiary structure of rhNGF. These studies indicated that metal-induced precipitation provides a method to maintain proteins in their native state in precipitates, which may be useful for purification, storage, and formulation.