Validation of Gait Measurements on Short-Distance Walkways Using Azure Kinect DK in Patients Receiving Chronic Hemodialysis

Muscle dysfunction, skeletal muscle fibrosis, and disability are associated with weakness in patients with end-stage renal disease. The main purpose of this study was to validate the effectiveness of a proposed system for gait monitoring on short-distance 1.5 m walkways in a dialysis center. Gaits with reduced speed and stride length, long sit-to-stand time (SST), two forward angles, and two unbalanced gait regions are defined in the proposed Kinect v3 gait measurement and analysis system (K3S) and have been considered clinical features in end-stage renal disease (ESRD) associated with poor dialysis outcomes. The stride and pace calibrations of the Kinect v3 system are based on the Zeno Walkway. Its single rating intraclass correlation (ICC) for the stride is 0.990, and its single rating ICC for the pace is 0.920. The SST calibration of Kinect v3 is based on a pressure insole; its single rating ICC for the SST is 0.871. A total of 75 patients on chronic dialysis underwent gait measurement and analysis during walking and weighing actions. After dialysis, patients demonstrated a smaller stride (p < 0.001) and longer SST (p < 0.001). The results demonstrate that patients' physical fitness was greatly reduced after dialysis. This study ensures patients' adequate physical gait strength to cope with the dialysis-associated physical exhaustion risk by tracing gait outliers. As decreased stride and pace are associated with an increased risk of falls, further studies are warranted to evaluate the clinical benefits of monitoring gait with the proposed reliable and valid system in order to reduce fall risk in hemodialysis patients.

Association between hyperlipidemia and trigger finger: A nationwide population-based cohort study

The cause of trigger fingers remains uncertain. High lipid levels in the blood may reduce blood supply to the distal fingers and promote inflammation. We aimed to explore the association between hyperlipidemia and trigger finger. A nationwide population-based cohort study using longitudinal data from 2000 to 2013, 41,421 patients were included in the hyperlipidemia cohort and 82,842 age- and sex-matched patients were included in the control cohort. The mean age was 49.90 ± 14.73 years in the hyperlipidemia cohort and 49.79 ± 14.71 years in the control cohort. After adjusting for possible comorbidities, the hazard ratio of trigger finger in the hyperlipidemia cohort was 4.03 (95% confidence interval [CI], 3.57-4.55), with values of 4.59 (95% CI, 3.67-5.73) and 3.77 (95% CI, 3.26-4.36) among male and female patients, respectively. This large-scale population-based study demonstrated that hyperlipidemia is correlated to trigger finger.

Long-term ambient hydrocarbon exposure and incidence of urinary bladder cancer

Particulate matter and volatile organic compounds, including total hydrocarbons (THCs), are major ambient air pollutants. Primary nonmethane hydrocarbons (NMHCs) originate from vehicle emissions. The association between air pollution and urinary bladder cancer (UBC) is debatable. We investigated whether long-term exposure to ambient hydrocarbons increases UBC risk among people aged ≥ 20 years in Taiwan. Linkage dataset research with longitudinal design was conducted among 589,135 initially cancer-free individuals during 2000-2013; 12 airborne pollutants were identified. Several Cox models considering potential confounders were employed. The study outcomes were invasive or in situ UBC incidence over time. The targeted pollutant concentration was divided into three tertiles: T1/T2/T3. The mean age of individuals at risk was 42.5 (SD 15.7), and 50.5% of the individuals were men. The mean daily average over 10 years of airborne THC concentration was 2.25 ppm (SD 0.13), and NMHC was 0.29 ppm (SD 0.09). Both pollutants show long-term monotonic downward trend over time using the Mann-Kendall test. There was a dose-dependent increase in UBC at follow-up. UBC incidence per 100,000 enrollees according to T1/T2/T3 exposure to THC was 60.9, 221.2, and 651.8, respectively; it was 170.0/349.5/426.7 per 100,000 enrollees, corresponding to T1/T2/T3 exposure to NMHC, respectively. Without controlling for confounding air pollutants, the adjusted hazard ratio (adj.HR) was 1.83 (95% CI 1.75-1.91) per 0.13-ppm increase in THC; after controlling for PM_2.5, adj.HR was even higher at 2.09 (95% CI 1.99-2.19). The adj.HR was 1.37 (95% CI 1.32-1.43) per 0.09-ppm increase in ambient NMHC concentration. After controlling for SO₂ and CH₄, the adj.HR was 1.10 (95% CI 1.06-1.15). Sensitivity analyses showed that UBC development risk was not sex-specific or influenced by diabetes status. Long-term exposure to THC and NMHC may be a risk factor for UBC development. Acknowledging pollutant sources can inform risk management strategies.

Re-engineering a Clinical Trial Management System Using Blockchain Technology: System Design, Development, and Case Studies

Background

A clinical trial management system (CTMS) is a suite of specialized productivity tools that manage clinical trial processes from study planning to closeout. Using CTMSs has shown remarkable benefits in delivering efficient, auditable, and visualizable clinical trials. However, the current CTMS market is fragmented, and most CTMSs fail to meet expectations because of their inability to support key functions, such as inconsistencies in data captured across multiple sites. Blockchain technology, an emerging distributed ledger technology, is considered to potentially provide a holistic solution to current CTMS challenges by using its unique features, such as transparency, traceability, immutability, and security.

Objective

This study aimed to re-engineer the traditional CTMS by leveraging the unique properties of blockchain technology to create a secure, auditable, efficient, and generalizable CTMS.

Methods

A comprehensive, blockchain-based CTMS that spans all stages of clinical trials, including a sharable trial master file system; a fast recruitment and simplified enrollment system; a timely, secure, and consistent electronic data capture system; a reproducible data analytics system; and an efficient, traceable payment and reimbursement system, was designed and implemented using the Quorum blockchain. Compared with traditional blockchain technologies, such as Ethereum, Quorum blockchain offers higher transaction throughput and lowers transaction latency. Case studies on each application of the CTMS were conducted to assess the feasibility, scalability, stability, and efficiency of the proposed blockchain-based CTMS.

Results

A total of 21.6 million electronic data capture transactions were generated and successfully processed through blockchain, with an average of 335.4 transactions per second. Of the 6000 patients, 1145 were matched in 1.39 seconds using 10 recruitment criteria with an automated matching mechanism implemented by the smart contract. Key features, such as immutability, traceability, and stability, were also tested and empirically proven through case studies.

Conclusions

This study proposed a comprehensive blockchain-based CTMS that covers all stages of the clinical trial process. Compared with our previous research, the proposed system showed an overall better performance. Our system design, implementation, and case studies demonstrated the potential of blockchain technology as a potential solution to CTMS challenges and its ability to perform more health care tasks.

Enhanced Risk of Osteoporotic Fracture in Patients with Sarcopenia: A National Population-Based Study in Taiwan

Sarcopenia is a progressive and generalized skeletal muscle disorder associated with poor health outcomes in older adults. However, its association with the risk of fracture risk is yet to be clarified. Therefore, this study aimed to assess the incidence and consequence of osteoporosis-related fractures among patients with sarcopenia in Taiwan. A retrospective, population-based study on 616 patients with sarcopenia, aged >40 years, and 1232 individuals without sarcopenia was conducted to evaluate claims data from Taiwan’s National Health Insurance Research Database collected in the period January 2000−December 2013. The incidence rate of osteoporosis-related fracture was 18.13 and 14.61 per 1000 person years in the patients with sarcopenia and comparison cohort, respectively. Patients with sarcopenia had a greater osteoporotic fracture risk (adjusted hazard ratio [HR] 2.11; 95% confidence interval [CI] 1.47−3.04) after correcting for possible confounding. Additionally, females showed statistically significant correlations of sarcopenia with osteoporosis-related fracture risk (HR 1.53; CI 0.83−2.8 for males and HR 2.40, CI 1.51−3.81 for females). During this retrospective study on the fracture risk in Taiwan, an adverse impact of sarcopenia was observed, which substantiates the need to work toward sarcopenia prevention and interventions to reverse fracture susceptibility in patients with sarcopenia.

A Clinical Kidney Intelligence Platform Based on Big Data, Artificial Intelligence, and Blockchain Technology

The high prevalence and incidence of end-stage rental disease (ESRD) and the difficulty in the early predicting the acute kidney injury (AKI) event highlights the limits of existing kidney care model, particularly the fragmented care and fractured data. The era of medical big data and artificial intelligence (AI) opens an opportunity to fill these knowledge and practice gaps. To obtain multi-dimensional view of the profiles of patients receiving dialysis, we propose to provide coherent care services and to actively collect patients’ multi-faceted information from home and hospital (e.g., photos of diets, sleep duration, or dermatologic manifestations). Furthermore, by introducing the blockchain in the infrastructure to enable the trustable medical exchange and effectively creates a large set of distributed medical data lake from various participated hospitals. We will introduce the medical coin, a virtual token, to vitalize digital service within the blockchain and create common interests among data generators, data vendors, and data users.We aim to create business models on top of its therapeutic effectiveness and unlock the academic and commercial value of medical data ecosystem.

Ethanolic extract of Puhuang (Pollen Typhae) modulates lipopolysaccharide-induced inflammatory response through inducible nitric oxide synthase / cyclooxygenase-2 signaling in RAW 264.7 macrophage

OBJECTIVE

To evaluate the immune modulatory response of Puhuang (Pollen Typhae), ethanolic extract of dried pollens (TP-E) and charcoal activated pollens (CTP-E) were used for their phytochemical evaluation and their modulatory response against lipopolysaccharide (LPS) induced inflammatory activity on RAW264.7 macrophage cells.

METHODS

Biochemical assays were carried out to quantify the 1,1-Diphenyl-2-picrylhydrazyl Radical Scavenging Activity, Reducing Power, Ferrous ion chelating ability and total polyphenol content and flavonoids. Non-toxic dose of the extract (TP-E and CTP-E) was chosen based on 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Effect of TP-E and CTP-E on lipopolysaccharides-induced inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expression was measured by Western blot and quantitative PCR (qRT-PCR). Expression of inflammatory cytokines, such as interleukins (IL-1β and IL-6) and tumor necrosis factor α (TNF-α), was quantified using qRT-PCR. Mitogen-activated protein kinase pathway was analyzed using Western blot.

RESULTS

Phytochemical analysis revealed that both TP-E and CTP-E have strong antioxidant activities and high flavonoid and phenolic contents. TP-E and CTP-E effectively inhibit the expression of iNOS and COX-2, thereby inhibiting its downstream proinflammatory regulators, the extracellular signal-related kinase-1/2, that decreases the expression of IL-1β, IL-6 and TNF-α.

CONCLUSION

Phytochemical constituents present in Typha angustifolia Linn could be used for treating inflammation-related diseases.

LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

A novel miRNA-based classification model of risks and stages for clear cell renal cell carcinoma patients

Background

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma and patients at advanced stage showed poor survival rate. Despite microRNAs (miRNAs) are used as potential biomarkers in many cancers, miRNA biomarkers for predicting the tumor stage of ccRCC are still limitedly identified. Therefore, we proposed a new integrated machine learning (ML) strategy to identify a novel miRNA signature related to tumor stage and prognosis of ccRCC patients using miRNA expression profiles. A multivariate Cox regression model with three hybrid penalties including Least absolute shrinkage and selection operator (Lasso), Adaptive lasso and Elastic net algorithms was used to screen relevant prognostic related miRNAs. The best subset regression (BSR) model was used to identify optimal prognostic model. Five ML algorithms were used to develop stage classification models. The biological significance of the miRNA signature was analyzed by utilizing DIANA-mirPath.

Results

A four-miRNA signature associated with survival was identified and the expression of this signature was strongly correlated with high risk patients. The high risk patients had unfavorable overall survival compared with the low risk group (HR = 4.523, P-value = 2.86e−08). Univariate and multivariate analyses confirmed independent and translational value of this predictive model. A combined ML algorithm identified six miRNA signatures for cancer staging prediction. After using the data balancing algorithm SMOTE, the Support Vector Machine (SVM) algorithm achieved the best classification performance (accuracy = 0.923, sensitivity = 0.927, specificity = 0.919, MCC = 0.843) when compared with other classifiers. Furthermore, enrichment analysis indicated that the identified miRNA signature involved in cancer-associated pathways.

Conclusions

A novel miRNA classification model using the identified prognostic and tumor stage associated miRNA signature will be useful for risk and stage stratification for clinical practice, and the identified miRNA signature can provide promising insight to understand the progression mechanism of ccRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04189-2.

Development of A Blockchain Framework for Virtual Clinical Trials

Clinical trials are essential for discovering new treatments, but there are multiple challenges to patient recruitment, patient engagement, and cost containment. Virtual clinical trials (VCT) are an innovative approach that provides potential solutions by conducting home-based, rather than site-based, clinical trials. Virtual clinical trials are still the exception rather than general practice due to technical barriers. "Blockchain," a distributed ledger technology, is a perfect match for virtual clinical trials. Its peer-to-peer design, security settings, and data transparency meet the needs of many healthcare applications. The programmable "Smart Contract" feature makes blockchain more suitable and feasible for VCT by solving computational issues. Our previous work has shown the power of applying blockchain to clinical trial recruitment. This work develops a comprehensive blockchain framework, with simulations and case studies, including patient recruitment, patient engagement, and persistent monitoring modules.

Dissecting molecular network structures using a network subgraph approach

Biological processes are based on molecular networks, which exhibit biological functions through interactions of genetic elements or proteins. This study presents a graph-based method to characterize molecular networks by decomposing the networks into directed multigraphs: network subgraphs. Spectral graph theory, reciprocity and complexity measures were used to quantify the network subgraphs. Graph energy, reciprocity and cyclomatic complexity can optimally specify network subgraphs with some degree of degeneracy. Seventy-one molecular networks were analyzed from three network types: cancer networks, signal transduction networks, and cellular processes. Molecular networks are built from a finite number of subgraph patterns and subgraphs with large graph energies are not present, which implies a graph energy cutoff. In addition, certain subgraph patterns are absent from the three network types. Thus, the Shannon entropy of the subgraph frequency distribution is not maximal. Furthermore, frequently-observed subgraphs are irreducible graphs. These novel findings warrant further investigation and may lead to important applications. Finally, we observed that cancer-related cellular processes are enriched with subgraph-associated driver genes. Our study provides a systematic approach for dissecting biological networks and supports the conclusion that there are organizational principles underlying molecular networks.

Identification of most influential co-occurring gene suites for gastrointestinal cancer using biomedical literature mining and graph-based influence maximization

Background

Gastrointestinal (GI) cancer including colorectal cancer, gastric cancer, pancreatic cancer, etc., are among the most frequent malignancies diagnosed annually and represent a major public health problem worldwide.

Methods

This paper reports an aided curation pipeline to identify potential influential genes for gastrointestinal cancer. The curation pipeline integrates biomedical literature to identify named entities by Bi-LSTM-CNN-CRF methods. The entities and their associations can be used to construct a graph, and from which we can compute the sets of co-occurring genes that are the most influential based on an influence maximization algorithm.

Results

The sets of co-occurring genes that are the most influential that we discover include RARA - CRBP1, CASP3 - BCL2, BCL2 - CASP3 – CRBP1, RARA - CASP3 – CRBP1, FOXJ1 - RASSF3 - ESR1, FOXJ1 - RASSF1A - ESR1, FOXJ1 - RASSF1A - TNFAIP8 - ESR1. With TCGA and functional and pathway enrichment analysis, we prove the proposed approach works well in the context of gastrointestinal cancer.

Conclusions

Our pipeline that uses text mining to identify objects and relationships to construct a graph and uses graph-based influence maximization to discover the most influential co-occurring genes presents a viable direction to assist knowledge discovery for clinical applications.

Text mining in a literature review of urothelial cancer using topic model

Background

Urothelial cancer (UC) includes carcinomas of the bladder, ureters, and renal pelvis. New treatments and biomarkers of UC emerged in this decade. To identify the key information in a vast amount of literature can be challenging. In this study, we use text mining to explore UC publications to identify important information that may lead to new research directions.

Method

We used topic modeling to analyze the titles and abstracts of 29,883 articles of UC from Pubmed, Web of Science, and Embase in Mar 2020. We applied latent Dirichlet allocation modeling to extract 15 topics and conducted trend analysis. Gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to identify UC related pathways.

Results

There was a growing trend regarding UC treatment especially immune checkpoint therapy but not the staging of UC. The risk factors of UC carried in different countries such as cigarette smoking in the United State and aristolochic acid in Taiwan and China. GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC.

Conclusions

The risk factors of UC may be dependent on the countries and GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC. These findings may provide further UC research directions.

Identification of Hub Genes Associated With Development of Head and Neck Squamous Cell Carcinoma by Integrated Bioinformatics Analysis

Improved insight into the molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify significant genes associated with HNSCC and to further analyze its prognostic significance. In our study, the cancer genome atlas (TCGA) HNSCC database and the gene expression profiles of GSE6631 from the Gene Expression Omnibus (GEO) were used to explore the differential co-expression genes in HNSCC compared with normal tissues. A total of 29 differential co-expression genes were screened out by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. As suggested in functional annotation analysis using the R clusterProfiler package, these genes were mainly enriched in epidermis development and differentiation (biological process), apical plasma membrane and cell-cell junction (cellular component), and enzyme inhibitor activity (molecular function). Furthermore, in a protein-protein interaction (PPI) network containing 21 nodes and 25 edges, the ten hub genes (S100A8, S100A9, IL1RN, CSTA, ANXA1, KRT4, TGM3, SCEL, PPL, and PSCA) were identified using the CytoHubba plugin of Cytoscape. The expression of the ten hub genes were all downregulated in HNSCC tissues compared with normal tissues. Based on survival analysis, the lower expression of CSTA was associated with worse overall survival (OS) in patients with HNSCC. Finally, the protein level of CSTA, which was validated by the Human Protein Atlas (HPA) database, was down-regulated consistently with mRNA levels in head and neck cancer samples. In summary, our study demonstrated that a survival-related gene is highly correlated with head and neck cancer development. Thus, CSTA may play important roles in the progression of head and neck cancer and serve as a potential biomarker for future diagnosis and treatment.

A Patient-Centric Health Information Exchange Framework Using Blockchain Technology

Health Information Exchange (HIE) exhibits remarkable benefits for patient care such as improving healthcare quality and expediting coordinated care. The Office of the National Coordinator (ONC) for Health Information Technology is seeking patient-centric HIE designs that shift data ownership from providers to patients. There are multiple barriers to patient-centric HIE in the current system, such as security and privacy concerns, data inconsistency, timely access to the right records across multiple healthcare facilities. After investigating the current workflow of HIE, this paper provides a feasible solution to these challenges by utilizing the unique features of blockchain, a distributed ledger technology which is considered "unhackable". Utilizing the smart contract feature, which is a programmable self-executing protocol running on a blockchain, we developed a blockchain model to protect data security and patients' privacy, ensure data provenance, and provide patients full control of their health records. By personalizing data segmentation and an "allowed list" for clinicians to access their data, this design achieves patient-centric HIE. We conducted a large-scale simulation of this patient-centric HIE process and quantitatively evaluated the model's feasibility, stability, security, and robustness.

Applying Blockchain Technology to Enhance Clinical Trial Recruitment

Patient recruitment for clinical trials is known to be a challenging aspect of clinical research. There are multiple competing concerns from the sponsor, patient and principal investigator's perspectives resulting in most clinical trials not meeting recruitment requirements on time. Conducting under-enrolled clinical trials affects the power of conclusive results or causes premature trial termination. The Blockchain is a distributed ledger technology originally applied in the financial sector. Its features as a peer-to-peer system with publicly audited transactions, data security, and patient privacy are a good fit for the needs of clinical trials recruitment. The "Smart Contract" is a programmable self-executing protocol that regulates the blockchain transactions. Given current recruitment challenges, we have proposed a blockchain model containing multiple trial-based contracts for trial management and patient engagement and a master smart contract for automated subject matching, patient recruitment, and trial-based contracts management.

Usefulness of Therapeutic Hypothermia to Improve Survival in Out-of-Hospital Cardiac Arrest

Background

In recent years, therapeutic hypothermia (TH) has been used to improve outcomes in patients with out-of-hospital cardiac arrest (OHCA). Despite these recommendations, many centers are still hesitant to implement such hypothermia protocols. In this study, we assessed the effects of TH for OHCA patients.

Methods

A total of 58 OHCA patients who had return of spontaneous circulation after OHCA presumed to be due to cardiac causes were enrolled. Twenty-three patients underwent TH, which was performed using a large volume of ice crystalloid fluid infusions in the emergency room and conventional cooling blankets in the ICU to maintain a body temperature of 32-34 °C for 24 hours using a tympanic thermometer. Patients in the control group received standard supportive care without TH. Hospital survival and neurologic outcomes were compared.

Results

There were no significant differences between the groups in patient characteristics, underlying etiologies and disease severity. In the 23 patients who received TH, 17 were alive at hospital discharge. In the 35 patients who received supportive care, only 11 were alive at hospital discharge (73.91% vs. 31.43%, p = 0.0015). Approximately 52% of the patients in the TH group had good neurologic outcomes (12 of 23) compared with the 20% (7 of 35) of the patients in the supportive group (p = 0.01).

Conclusions

TH can improve the outcomes of OHCA patients. Further large-scale studies are needed to verify our results.

Identification of Prognostic Candidate Genes in Breast Cancer by Integrated Bioinformatic Analysis

Breast cancer is one of the most common malignancies. However, the molecular mechanisms underlying its pathogenesis remain to be elucidated. The present study aimed to identify the potential prognostic marker genes associated with the progression of breast cancer. Weighted gene coexpression network analysis was used to construct free-scale gene coexpression networks, evaluate the associations between the gene sets and clinical features, and identify candidate biomarkers. The gene expression profiles of GSE48213 were selected from the Gene Expression Omnibus database. RNA-seq data and clinical information on breast cancer from The Cancer Genome Atlas were used for validation. Four modules were identified from the gene coexpression network, one of which was found to be significantly associated with patient survival time. The expression status of 28 genes formed the black module (basal); 18 genes, dark red module (claudin-low); nine genes, brown module (luminal), and seven genes, midnight blue module (nonmalignant). These modules were clustered into two groups according to significant difference in survival time between the groups. Therefore, based on betweenness centrality, we identified TXN and ANXA2 in the nonmalignant module, TPM4 and LOXL2 in the luminal module, TPRN and ADCY6 in the claudin-low module, and TUBA1C and CMIP in the basal module as the genes with the highest betweenness, suggesting that they play a central role in information transfer in the network. In the present study, eight candidate biomarkers were identified for further basic and advanced understanding of the molecular pathogenesis of breast cancer by using co-expression network analysis.

Applying Blockchain Technology for Health Information Exchange and Persistent Monitoring for Clinical Trials

"Blockchain" is a distributed ledger technology originally applied in the financial sector. This technology ensures the integrity of transactions without third-party validation. Its functions of decentralized transaction validation, data provenance, data sharing, and data integration are a good fit for the needs of health information exchange and clinical trials. We investigated the current workflow of Health Information Exchange and clinical trials; conducted design thinking processes with clinicians, trial managers, informaticians, and blockchain professionals; and implemented a private blockchain model to tackle known issues. We used coded Smart Contract regulations to simulate several scenarios in healthcare processes. This proof-of-concept work provides a feasible simulation for potential solutions to monitor clinical trials across different census regions persistently. Various levels of data access privileges have been designed to utilize a suite of customized Smart Contract settings. These settings emulate the workflow protocols for the monitoring entities, trial sponsors, clinical sponsors and participating subjects. Keywords: Blockchain, Smart Contract, Health Information Exchange, Clinical Trial, Persistent Monitoring.

The Combination of Computational and Biosensing Technologies for Selecting Aptamer against Prostate Specific Antigen

Herein, we report a method of combining bioinformatics and biosensing technologies to select aptamers against prostate specific antigen (PSA). The main objective of this study is to select DNA aptamers with higher binding affinity for PSA by using the proposed method. Based on the five known sequences of PSA-binding aptamers, we adopted the functions of reproduction and crossover in the genetic algorithm to produce next-generation sequences for the computational and experimental analysis. RNAfold web server was utilized to analyze the secondary structures, and the 3-dimensional molecular models of aptamer sequences were generated by using RNAComposer web server. ZRANK scoring function was used to rerank the docking predictions from ZDOCK. The biosensors, the quartz crystal microbalance (QCM) and a surface plasmon resonance (SPR) instrument, were used to verify the binding ability of selected aptamer for PSA. By carrying out the simulations and experiments after two generations, we obtain one aptamer that can have the highest binding affinity with PSA, which generates almost 2-fold and 3-fold greater measured signals than the responses produced by the best known DNA sequence in the QCM and SPR experiments, respectively.

Drug repurposing and therapeutic anti-microRNA predictions for inhibition of oxidized low-density lipoprotein-induced vascular smooth muscle cell-associated diseases

Drug repurposing is a new method for disease treatments, which accelerates the identification of new uses for existing drugs with minimal side effects for patients. MicroRNA-based therapeutics are a class of drugs that have been used in gene therapy following the FDA's approval of the first anti-sense therapy. This study examines the effects of oxLDL on vascular smooth muscle cells (VSMCs) and identifies potential drugs and antimiRs for treating VSMC-associated diseases. The Connectivity Map (cMap) database is utilized to identify potential new uses of existing drugs. The success of the identifications was supported by MTT assay, clonogenic assay and clinical trial data. Specifically, 37 drugs, some of which are undergoing clinical trials, were identified. Three of the identified drugs exhibit IC50 activities. Among the 37 drugs' targets, three differentially expressed genes (DEGs) are identified as drug targets by using both the DrugBank and the NCBI PubChem Compound databases. Also, one DEG, DNMT1, which is regulated by 17 miRNAs, where these miRNAs are potential targets for developing antimiR-based miRNA therapy, is found.

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Identify potential drugs for cardiovascular diseases caused by stress-induced genes in vascular smooth muscle cells

BACKGROUND

Abnormal proliferation of vascular smooth muscle cells (VSMC) is a major cause of cardiovascular diseases (CVDs). Many studies suggest that vascular injury triggers VSMC dedifferentiation, which results in VSMC changes from a contractile to a synthetic phenotype; however, the underlying molecular mechanisms are still unclear.

METHODS

In this study, we examined how VSMC responds under mechanical stress by using time-course microarray data. A three-phase study was proposed to investigate the stress-induced differentially expressed genes (DEGs) in VSMC. First, DEGs were identified by using the moderated t-statistics test. Second, more DEGs were inferred by using the Gaussian Graphical Model (GGM). Finally, the topological parameters-based method and cluster analysis approach were employed to predict the last batch of DEGs. To identify the potential drugs for vascular diseases involve VSMC proliferation, the drug-gene interaction database, Connectivity Map (cMap) was employed. Success of the predictions were determined using in-vitro data, i.e. MTT and clonogenic assay.

RESULTS

Based on the differential expression calculation, at least 23 DEGs were found, and the findings were qualified by previous studies on VSMC. The results of gene set enrichment analysis indicated that the most often found enriched biological processes are cell-cycle-related processes. Furthermore, more stress-induced genes, well supported by literature, were found by applying graph theory to the gene association network (GAN). Finally, we showed that by processing the cMap input queries with a cluster algorithm, we achieved a substantial increase in the number of potential drugs with experimental IC50 measurements. With this novel approach, we have not only successfully identified the DEGs, but also improved the DEGs prediction by performing the topological and cluster analysis. Moreover, the findings are remarkably validated and in line with the literature. Furthermore, the cMap and DrugBank resources were used to identify potential drugs and targeted genes for vascular diseases involve VSMC proliferation. Our findings are supported by in-vitro experimental IC50, binding activity data and clinical trials.

CONCLUSION

This study provides a systematic strategy to discover potential drugs and target genes, by which we hope to shed light on the treatments of VSMC proliferation associated diseases.

Towards Semantic Biomedical Problem Solving

Biological and medical intelligence (BMI) has been studied in solos, lacking a systematic methodology. In this paper, we describe how Semantic Computing can enhance biological and medical intelligence. Specifically, we show how Structured Natural Language (SNL) can express many problems in BMI with a finite number of sentence patterns, and show how biological tools, OLAP, data mining tools and statistical analysis tools may be linked to solve problems related to biomedical data.

FARE-CAFE: a database of functional and regulatory elements of cancer-associated fusion events

Chromosomal translocation (CT) is of enormous clinical interest because this disorder is associated with various major solid tumors and leukemia. A tumor-specific fusion gene event may occur when a translocation joins two separate genes. Currently, various CT databases provide information about fusion genes and their genomic elements. However, no database of the roles of fusion genes, in terms of essential functional and regulatory elements in oncogenesis, is available. FARE-CAFE is a unique combination of CTs, fusion proteins, protein domains, domain–domain interactions, protein–protein interactions, transcription factors and microRNAs, with subsequent experimental information, which cannot be found in any other CT database. Genomic DNA information including, for example, manually collected exact locations of the first and second break points, sequences and karyotypes of fusion genes are included. FARE-CAFE will substantially facilitate the cancer biologist’s mission of elucidating the pathogenesis of various types of cancer. This database will ultimately help to develop ‘novel’ therapeutic approaches.

Database URL:http://ppi.bioinfo.asia.edu.tw/FARE-CAFE

Cancer risk in patients aged 30 years and above with type 2 diabetes receiving antidiabetic monotherapy: a cohort study using metformin as the comparator

INTRODUCTION

Accumulating evidence suggests that metformin reduces incident cancer development. Few cohort studies have evaluated the risk of subsequent cancer development in diabetic cohorts receiving antidiabetic monotherapy. We conducted a population-based study in patients with new-onset type 2 diabetes treated with antidiabetic monotherapy.

METHODS

We identified a cohort of patients with type 2 diabetics aged ≥30 years receiving hypoglycemic monotherapy (n=7,325) from the 1998-2007 Longitudinal Health Insurance Dataset. Patients were grouped according to the antidiabetic therapy they received into metformin (n=2,223), sulfonylurea (n=3,965), glitazone (n=53), meglitinide (n=128), acarbose (n=150), and insulin (n=806) groups. Patients with preexisting cancer were excluded. All patients were followed up until cancer development, dropout, death, or until December 31, 2008. Cox's model was used to estimate multivariable hazard ratios (HRs) adjusted for age, sex, Charlson comorbidity index, smoking-related comorbidities, alcohol use disorders, morbid obesity, pancreatitis, hypertension, monthly income, and urbanization level. The log-rank test was used to compare cumulative cancer incidence. Two-sided P-values <0.05 were required to reject the null hypothesis.

RESULTS

The overall median follow-up duration was 2.5 years (interquartile range, 3.6 years). Totally, 367 and 124 cancers developed in the sulfonylurea and metformin groups, respectively, representing an adjusted HR of 1.36 (95% confidence interval [CI], 1.11-1.67; P<0.005). No significant differences were observed between other groups. Increased adjusted HRs were observed for colorectal cancer (adjusted HR, 1.94; 95% CI, 1.15-3.27; P<0.05) and lung cancer (adjusted HR, 1.76; 95% CI, 1.00-3.07; P<0.05).

CONCLUSION

Metformin monotherapy may be associated with a reduction in the risk for cancer development compared with sulfonylurea monotherapy. Moreover, the use of an average defined daily dose of >0.25 of metformin when compared to lower dose will contribute to a reduction of 80% risk.

A model comparison study of the flowering time regulatory network in Arabidopsis

Background

Several dynamic models of a gene regulatory network of the light-induced floral transition process in Arabidopsis have been developed to capture the behavior of gene transcription and infer predictions based on experimental observations. It has been proven that the models can make accurate and novel predictions, which generate testable hypotheses.

Two major issues were addressed in this study. First, construction of dynamic models for gene regulatory networks requires the use of mathematic modeling that comprises equations of a large number of parameters. Second, the binding mechanism of the transcription factor with DNA is another factor that requires detailed modeling. The first issue was tackled by adopting an optimization algorithm, and the second was addressed by comparing the performance of three alternative modeling approaches, namely the S-system, the Michaelis-Menten model and the Mass-action model. The efficiencies of parameter estimation and modeling performance were calculated based on least square error (O(p)), mean relative error (MRE) and Akaike Information Criterion (AIC).

Results

We compared three models to describe gene regulation of the flowering transition process in Arabidopsis. The Mass-action model is the simplest and has the least parameters. It is therefore less computation-intensive with the smallest AIC value. The disadvantage, however, is that it assumes the system is simply a second order reaction which is not the case in our study. The Michaelis-Menten model also assumes the system is homogeneous and ignores the intracellular protein transport process. The S-system model has the best performance and it does describe the diffusion effects. A disadvantage of the S-system is that it involves the most parameters. The largest AIC value also implies an over-fitting may occur in parameter estimation.

Conclusions

Three dynamic models were adopted to describe the dynamics of the gene regulatory network of the flowering transition process in Arabidopsis. Based on MRE, the least square error and global sensitivity analysis, the S-system has the best performance. However, the fact that it has the highest AIC suggests an over-fitting may occur in parameter estimation. The result of this study may need to be applied carefully when modeling complex gene regulatory networks.

Prediction of microRNA-regulated protein interaction pathways in Arabidopsis using machine learning algorithms

MicroRNAs are small, endogenous RNAs found in many different species and are known to have an influence on diverse biological phenomena. They also play crucial roles in plant biological processes, such as metabolism, leaf sidedness and flower development. However, the functional roles of most microRNAs are still unknown. The identification of closely related microRNAs and target genes can be an essential first step towards the discovery of their combinatorial effects on different cellular states. A lot of research has tried to discover microRNAs and target gene interactions by implementing machine learning classifiers with target prediction algorithms. However, high rates of false positives have been reported as a result of undetermined factors which will affect recognition. Therefore, integrating diverse techniques could improve the prediction. In this paper we propose identifying microRNAs target of Arabidopsis thaliana by integrating prediction scores from PITA, miRanda and RNAHybrid algorithms used as a feature vector of microRNA-target interactions, and then implementing SVM, random forest tree and neural network machine learning algorithms to make final predictions by majority voting. Furthermore, microRNA target genes are linked with their protein-protein interaction (PPI) partners. We focus on plant resistance genes and transcription factor information to provide new insights into plant pathogen interaction networks. Downstream pathways are characterized by the Jaccard coefficient, which is implemented based on Gene Ontology. The database is freely accessible at http://ppi.bioinfo.asia.edu.tw/At_miRNA/.

Clinical implications of deregulated CDK4 and Cyclin D1 expression in patients with human hepatocellular carcinoma

Deregulated cell cycle can contribute to the unscheduled proliferation in cancer cells. Overexpression of cell cycle regulators CDK4 and Cyclin D1 has been reported in many cancers. The aim of this study is to determine the clinical implications of CDK4 and Cyclin D1 in hepatocellular carcinoma (HCC). The levels of mRNA and protein were analyzed by quantitative real-time RT-PCR and immunohistochemistry, respectively, in 59 paired HCC and the neighboring noncancer tissues. The relationship between CDK4 and Cyclin D1 expression, clinicopathological parameters, and prognosis was investigated. Our data demonstrated that the mRNA level of CDK4 was up-regulated (p = 0.019), while that of Cyclin D1 was down-regulated (p = 0.002), in HCC. Immunohistochemical data confirmed that CDK4 protein was increased in 73 % and Cyclin D1 protein was decreased in 66 % of HCC samples. Overexpression of CDK4 was correlated with HBV (p = 0.054, borderline significant), tumor size (p = 0.014), and stage (p = 0.010). The Kaplan-Meier survival curves showed that high CDK4 was correlated with a poor survival rate (I vs. II, p < 0.001; I vs. III, p < 0.001). Univariate analysis showed that tumor size (p = 0.002), stage (p = 0.021), and high CDK4 score (I vs. II-III, p < 0.001) were significant prognostic factors. Multivariate analysis showed that tumor size (p = 0.007) and high CDK4 score (I vs. II-III, p < 0.001) were independent factors for overall survival of HCC. The expression of Cyclin D1 was not correlated with CDK4 expression, tumor grades, survival rate, and any clinicopathological parameters. CDK4 could provide a clinical prognostic marker for HCC progression.

Overexpression of Thy1/CD90 in human hepatocellular carcinoma is associated with HBV infection and poor prognosis

Thy1/CD90 is an important marker of many types of stem cells. It functions as a tumor suppressor in ovarian cancer and in nasopharyngeal carcinoma. In this study, the expression status of Thy1 in clinical hepatocellular carcinoma (HCC) tissue samples was investigated. Relationships of Thy1 expression with clinical parameters and patient survival rate were analyzed. The quantities of Thy1 mRNA were statistically higher in tumor tissues than those in the adjacent non-tumor tissues (p<0.001). Immunohistochemical data confirmed that Thy1 protein was increased in 73% of HCC samples. Thy1 expression was not influenced by chronic alcohol exposure or cirrhosis. Overexpression in Thy1 was correlated with age (p=0.006), hepatitis B virus (HBV) infection (p=0.044), and histological grade (p=0.014). Patients with the highest level of Thy1 expression showed the poorest prognosis (p=0.040). In conclusion, overexpression of Thy1 may not suppress the development of HCC. Thy1 could provide a clinical prognostic marker for HCC.

Decreased expression of p39 is associated with a poor prognosis in human hepatocellular carcinoma

The aims of this study are to investigate the relationship between p39 expression and clinicopathological parameters of hepatocellular carcinoma (HCC) and to evaluate the prognostic value of p39 for HCC patients. Real-time quantitative PCR and immunohistochemistry was used to measure p39 expression in tumor and adjacent nontumor samples. Relationships of p39 expression with clinical parameters and patient survival were analyzed. Real-time quantitative RT-PCR showed that the quantity of p39 mRNA in cancerous tissue was significantly lower than that in nontumor tissue (P < 0.001). Immunohistochemistry data confirmed that p39 protein was reduced in 64% of HCC. p39 expression was not influenced by chronic alcohol exposure or cirrhosis. Reduction in p39 was correlated with the HBV (P = 0.039), HCV (P = 0.011), and histological grade (P < 0.001). HCC patients with lower p39 expression had poorer overall survival rate than that with high expression (HR, 2.868; 95% CI, 1.451-5.670; P = 0.002). Together with other results, these results reveal that p39 expression was reduced in HCC tissue. p39 could be a useful clinical prognostic marker for hepatocellular carcinoma patients.

An Automatically Tuning Intrusion Detection System

An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

The association of -627 interleukin-10 promoter polymorphism in Chinese patients with systemic lupus erythematosus

The objective of the study is to examine whether interleukin-10 (IL-10) promoter polymorphism is a marker of susceptibility of systemic lupus erythematosus (SLE) in Chinese patients in Taiwan. The study included 119 Chinese patients with SLE. One hundred unrelated healthy individuals living in central Taiwan served as control subjects. Each polymorphism was detected as a result of a polymerase chain reaction (PCR)-based restriction analysis. The PCR product length was determined to be 412 bp (CC) whereas two fragments of 236 and 176 bp were determined to be excisable lengths (AA). The relationship between the IL-10 gene polymorphism and clinical manifestations of SLE was evaluated. For the genotype and allelic frequency, there were statistically significant differences between the SLE patients and the normal control subjects (p=0.007 and 0.003, respectively). But we did not detect any association of carriage rate of the IL-10 polymorphism and the normal control subjects (p=0.077). Furthermore, we did not detect any association of IL-10 genotype with antinuclear antibody, malar rash, photosensitivity, discoid lupus, mucosal ulcer, arthritis, serositis, hematology, immunology, involvement of central nervous system, and renal disease involvement in the SLE patients. The significant relation of -627 IL-10 genotype and allelic frequency with SLE implies that the IL-10 gene polymorphism can serve as a candidate gene marker for further study in patients with SLE in Taiwan.

Increased prevalence of interleukin-1 receptor antagonist gene polymorphism in patients with chronic rhinosinusitis

OBJECTIVE

To assess the association of the interleukin (IL)-1beta and the IL-1 receptor antagonist (IL-1Ra) gene polymorphisms with chronic rhinosinusitis (CRS).

DESIGN

Genotyping of the 2 IL-1beta gene (IL1B) polymorphisms (promoter and exon) and the IL-1Ra gene (IL1RN) polymorphism (intron 2) was performed using polymerase chain reaction and restriction length fragment polymorphism analyses.

SETTING

Prospective study, tertiary medical center.

PATIENTS

The study population comprised 88 consecutive adult Taiwan-Chinese patients who met stringent criteria for CRS and received endoscopic sinus surgery and 103 healthy volunteers of the same ethnicity and similar age range. Of the 88 patients, 61 had CRS with nasal polyps, while the other 27 had CRS without nasal polyps.

RESULTS

There were significant differences in the distribution of the IL1RN polymorphism between the control subjects and patients with CRS (P<.05). The II allele of IL1RN occurred more frequently in the CRS patient group, and the odds ratio for subjects with I/II genotype was 3.39 (95% confidence interval, 1.25-9.18). In the case of CRS without nasal polyps, the odds ratio for subjects with I/II genotype was further increased to 4.75 (1.39-16.25). There was no association between the other 2 polymorphisms of IL1B and CRS.

CONCLUSION

Increased prevalence of IL1RN polymorphism in patients with CRS suggests that this polymorphism, or a polymorphism in linkage disequilibrium with it, may be involved in the development of CRS.

Amino acid concentrations in cerebrospinal fluid in children with acute lymphoblastic leukemia undergoing chemotherapy

Cerebrospinal fluid (CSF) amino acid concentrations were measured in 45 children with acute lymphoblastic leukemia (ALL). Central nervous system (CNS) disease was absent in 34 and present in 11 (Groups L and M, respectively) at diagnosis. Thirty-two otherwise healthy children with febrile convulsions were studied for comparison. Results from this study show that glutamine levels at Day 0 were significantly higher in patients than in controls. Patients in Group M had elevated glutamine levels compared to Group L. In comparison, at Day 14, concentrations of glutamine and asparagine decreased, while glutamic acid amounts increased significantly in Group L. Glutamine levels fell at Day 42 in Group M, which may have resulted from more intensive treatment. From this study we hypothesise that higher baseline glutamine levels are indicative of a greater risk for CNS leukemia. Large-scale prospective trials are required to confirm increased baseline CSF glutamine levels in ALL patients, to identify glutamine as a marker for CNS disease and to clarify underlying mechanisms regulating glutamine in ALL.

Glutathione S-transferase T1 deletion is a risk factor for developing end-stage renal disease in diabetic patients

Reactive oxygen metabolites may contribute to the development of end-stage renal disease (ESRD) in diabetic and hypertensive patients. In this study, we used multiplex polymerase chain reaction (PCR) to analyze polymorphisms of two endogenous antioxidant genes, glutathione S-transferase M1 (GSTM1) and glutathione S-transferase T1 (GSTT1), and to determine their role in the development of ESRD in diabetic and hypertensive patients. Our results showed that homozygous deletion of the GSTT1 gene is a risk factor for developing ESRD in diabetic patients (p=0.004, OR=2.18, 95% confidence interval (CI) =1.29-3.70), but not in hypertensive patients. No association between homozygous deletion of GSTM1 and the development of ESRD was found in either diabetic patients or hypertensive patients. These results indicate that genetic variations in enzymes involved in free radical metabolism are associated with the development of ESRD in diabetes mellitus (DM) patients, and may permit the targeting of preventive and early intervention strategies to high-risk individuals.

Usefulness of thallium-201 muscle scan to investigate perfusion reserve in the lower limbs of patients with systemic lupus erythematusus

Patients with systemic lupus erythematosus (SLE) may develop premature atherosclerosis, notably peripheral vascular disease presenting with intermittent claudication or gangrene. This study evaluates the usefulness of thallium-201 muscle perfusion scan (Tl-201 muscle scan) for investigating perfusion reserve in the lower limbs of 25 asymptomatic, female SLE patients without peripheral ischemia findings. The patients showed no evidence of peripheral arterial disease in history, physical examination, or Doppler ultrasonography. A control group consisted of 24 healthy, age-matched women. Each subject flexed her right foot maximally both dorsally and plantarly 60 times. In the middle of this exercise, 2 mCi of Tl-201 was injected intravenously. Three minutes after the injection, a posterior image of both calves was obtained using a gamma camera. Rectangular regions of interest were symmetrically drawn over both calves. The total count in the resting calf was subtracted from the total count in the exercising calf, and the percentage of increase, termed the perfusion reserve, was determined. A significant difference was found between the perfusion reserves of the SLE patients and control groups (75.3+/-8.9% and 99.6+/-9.0%, respectively, P <0.05). In conclusion, perfusion reserve in the lower limb muscles of SLE patients may be measured by Tl-201 muscle perfusion scan.

Usefulness of technetium-99m hexamethylpropylene amine oxime lung scan to detect inhalation lung injury of patients with pulmonary symptoms/signs but negative chest radiograph and pulmonary function test findings after a fire accident--a preliminary report

OBJECTIVE

In this study, we employed technetium-99m hexamethylpropylene amine oxime (99mTc HMPAO) lung scan to detect inhalation lung injury of patients after a fire accident.

METHODS

Ten healthy men for controls and 10 male patients with pulmonary symptoms/signs from a fire accident were enrolled in this study for comparison. 99mTc HMPAO lung scan was performed in each control and patient, as well as the degree of pulmonary vascular endothelium damage was represented as lung/liver uptake ratios (L/L ratio). All of the controls and patients had no smoking histories. None of the controls and patients had positive findings of plain chest radiograph (CXR) and pulmonary function test (PFT).

RESULTS

The results showed that significantly higher L/L ratio in the 10 patients (0.53 +/- 0.07) than in the 10 controls (0.30 +/- 0.07) (the p value < 0.05). Using a cut-off value of 0.40, all of the 10 patients had abnormally increased L/L ratios.

CONCLUSIONS

We conclude that 99mTc HMPAO lung scan has the potential to be a sensitive, objective and noninvasive method to detect inhalation lung injury of patients with pulmonary symptoms/signs but negative CXR and PFT findings after a fire accident.

A pilot trial of quantitative Tc-99m HMPAO and Ga-67 citrate lung scans to detect pulmonary vascular endothelial damage and lung inflammation in patients of collagen vascular diseases with active diffuse infiltrative lung disease

Diffuse infiltrative lung disease (ILD) includes a heterogeneous group of disorders predominantly affecting lung parenchyma and sparing the airway. To assess the degree of pulmonary vascular endothelial damage in active ILD, lung/liver uptake ratios (L/L ratio) on technetium-99m hexamethylpropylene amine oxime (Tc-99m HMPAO) lung scan were determined in 30 patients with active ILD. Meanwhile, the gallium-67 citrate (Ga-67) uptake index (GUI) on Ga-67 lung scan was used to evaluate the severity of lung inflammation in active ILD. In this study, high-resolution CT (HRCT) was used to evaluate disease activity in ILD. The results show statistically significant differences between normal controls and patients with active ILD as shown in L/L ratios and GUI. However, when the patients were divided into two groups of 15 patients with normal chest X-ray findings and 15 with abnormal X-ray findings, there was no significant difference in those parameters. In addition, there was no statistically significant difference between the groups in HRCT scoring. No good correlation between the degree of pulmonary vascular endothelial damage and the severity of lung inflammation was found. In addition, there were no good correlations between HRCT scoring vs GUI and HRCT vs L/L ratio in different study subgroups. In conclusion, L/L ratios on Tc-99m HMPAO and GUI on Ga-67 lung scans differ from chest X-ray findings and have the potential to detect the degree of pulmonary vascular endothelial damage and severity of lung inflammation in active IDL. However, the relationships between HRCT scoring, GUI, and L/L ratio in patients with collagen vascular diseases and active ILD are not significant.

Association between urokinase gene 3'-UTR T/C polymorphism and Chinese patients with rheumatoid arthritis in Taiwan

OBJECTIVES

The purpose of this study was to investigate whether the urokinase gene 3'-UTR C/T polymorphism is a marker of susceptibility to or severity of rheumatoid arthritis (RA) in Chinese patients.

METHODS

A total of 145 RA patients and 134 healthy control subjects were enrolled in this study. We identified the C/T polymorphism of the urokinase gene, which is mapped on the 3'-untranslated region (3'-UTR) on chromosome 10 by polymerase chain reaction (PCR).

RESULTS

There were significant differences in the distribution of the urokinase gene 3'-UTR C/T polymorphism frequency between RA patients and subjects in the control group. However, we did not detect an, association between the urokinase gene 3'-UTR C/T polymorphism and rheumatoid factor (RF), extraarticular involvement or bone erosion in RA patients.

CONCLUSION

The urokinase gene 3'-UTR "T" allele was associated with RA in Chinese patients in Taiwan.

The effects of one-week fluticasone propionate inhalation therapy for Tc-99m DTPA radioaerosol distribution in asthma of children: a preliminary report

This study evaluated the effects of fluticasone propionate inhalation therapy for the distribution pattern of Tc-99m DTPA radioaerosols in 10 children with asthma. The homogeneous degree of depositing Tc-99m DTPA radioaerosol was evaluated using a modified standard score system over the bilateral lungs. The baseline scores were calculated from Tc-99m DTPA radioaerosol inhalation lung scintigraphy before inhalation therapy (100 microg fluticasone propionate two times daily for one week), and the scores were recalculated after inhalation therapy to evaluate the effects of one-week of fluticasone propionate inhalation therapy for Tc-99m DTPA radioaerosol distribution patterns. After one week of fluticasone propionate inhalation therapy, the scores were decreased in all of the 10 children, which may mean that the bronchial constriction degree due to asthma is decreased. In addition, there was a significantly statistical difference in the scores before and after one-week fluticasone propionate inhalation therapy (p < 0.05). In conclusion, one-week fluticasone propionate inhalation therapy could significantly improve the bronchial constriction due to asthma in children based on the evidence of Tc-99m DTPA radioaerosol inhalation lung scintigraphic findings.

Using 99mTc HMPAO brain SPECT to evaluate the effects of anticoagulant therapy on regional cerebral blood flow in primary antiphospholipid antibody syndrome patients with brain involvement-a preliminary report

Technetium-99m hexamethylpropylene amine oxime ((99m)Tc HMPAO) brain single photon emission computed tomography (SPECT) was used to evaluate the effects of anticoagulant therapy (ACT) on regional cerebral blood flow (rCBF) in patients with primary antiphospholipid antibody syndrome (PAPS). Sixteen female PAPS patients with neuropsychiatric manifestations and hypoperfusion lesions demonstrated on initial (99m)Tc HMPAO brain SPECT images were enrolled in this study. Follow-up (99m)Tc HMPAO brain SPECT images were performed 1 month after ACT. Meanwhile, serum anticardiolipin antibodies (ACA) were measured before and after ACT. Before ACT, 14 (87.5%) patients had positive ACA. After ACT, all 16 PAPS patients showed decreased serologic findings, and their neuropsychiatric manifestations subsided. After ACT, 11 (68.8%) patients showed complete recovery of regional cerebral blood flow (rCBF) and five (31.2%) patients showed partial recovery in the follow-up (99m)Tc HMPAO brain SPECT images. This type of imaging is a logical and objective tool for measuring the effects of ACT in PAPS patients with brain involvement by determining changes in rCBF.

Association of the neuronal nicotinic acetylcholine receptor subunit alpha4 polymorphisms with febrile convulsions

PURPOSE

The alpha4-subunit gene of the neuronal nicotinic acetylcholine receptor (CHRNA4) has been identified as the first gene underlying an idiopathic partial epilepsy syndrome in human autosomal-dominant nocturnal frontal lobe epilepsy. Studies provided evidence that the protein coded by CHRNA4 is one of the most abundant subunits of the neuronal nicotinic acetylcholine receptors in mammalian brains, and mutations of CHRNA4 seem to cause neuronal excitation. The CHRNA4 gene may have a role in the development of febrile convulsions (FCs), the majority of childhood seizures. This study assessed the distribution of genotypes of CHRNA4 in patients with FCs.

METHODS

A total of 102 children with FCs and 80 normal control subjects were included in the study. Polymerase chain reaction was used to identify the C/T polymorphism of the CHRNA4 gene. Genotypes and allelic frequencies for the CHRNA4 gene polymorphisms in both groups were compared.

RESULTS

The number of individuals with heterozygous CHRNA4 (Ser543Ser)-C/T genotype was significantly greater (60.8% vs. 32.5%; p = 0.001), and the CHRNA4 (Ser543Ser)-T allele frequency was significantly higher (p = 0.001), in patients with FCs compared with healthy controls. The odds ratio for developing FCs in individuals with the CHRNA4 (Ser543Ser)-CT genotype was 3.77 compared with individuals with two copies of the CHRNA4 (Ser543Ser)-C allele.

CONCLUSIONS

This study demonstrated an association between the CHRNA4 gene and FCs. Individuals with the T allele had a higher incidence of FCs. These data suggest that the CHRNA4 gene or a closely linked gene might be one of the susceptibility factors for FCs.

Association analysis of gamma 2 subunit of gamma- aminobutyric acid type A receptor polymorphisms with febrile seizures

An alternation of gamma-aminobutyric acid (GABA)-ergic neurotransmission has been implicated as an etiologic factor in epileptogenesis. Missense mutations in the GABRG2 gene, which encodes the gamma2 subunit of central nervous GABAA receptors, have recently been described in one family with childhood absence epilepsy and febrile seizures (FSs). FSs represent the majority of childhood seizures and have a genetic predisposition. It is not known, however, whether polymorphisms in those genes involved in familial epilepsies also contribute to the pathogenesis of FSs. By performing an association study, we used single-nucleotide polymorphisms to investigate the distribution of genotypes of GABRG2 in patients with FSs. A total of 104 children with FSs and 83 normal control subjects were included in the study. PCR was used to identify the C/T and A/G polymorphisms of the GABRG2 gene on chromosome 5q33. Genotypes and allelic frequencies for the GABRG2 gene polymorphisms in both groups were compared. The GABRG2 (nucleotide position 3145 in intron G-->A) gene in both groups was not significantly different. In contrast, the number of individuals with the GABRG2 (SNP211037)-C/C genotype in patients with FSs was significantly greater compared with that in healthy control subjects (p = 0.017), and the GABRG2 (SNP211037)-C allele frequency in patients with FSs was significantly higher than that in healthy control subjects (p = 0.009). The odds ratio for developing FSs in individuals with the GABRG2 (SNP211037)-C/C genotype was 2.56 compared with individuals with the GABRG2 (SNP211037)-T/T genotype. These data suggest that the GABRG2 gene might be one of the susceptibility factors for FSs.

Evaluating the changes in alveolar permeability and lung ventilation in patients with chronic renal failure after haemodialysis using 99mTc-DTPA radioaerosol inhalation lung scan

Hypoxaemia occurring in patients with chronic renal failure (CRF) during haemodialysis (HD) has long been known. Several mechanisms of pathogenesis have been proposed. Before and after regular HD, lung ventilation (LV) and alveolar permeability (AP) were measured in 24 male patients with CRF (age, 61-75 years). LV and AP were determined by 99mTc-diethylenetriaminepentaacetic acid (99mTc-DTPA) radioaerosol inhalation lung scan (99mTc-DTPA lung scan). The LV images were visually interpreted according to established criteria, including the presence or absence of an inhomogeneous distribution, inverted base to apex gradient and segmental hypoventilation. The degree of AP in the total right lung was presented as the clearance rate (K; %.min-1) of the time-activity curve from dynamic total right lung images. Ten male normal controls (age, 62-76 years) were enrolled in the study for comparison. Ten of 24 (42%) cases showed an inhomogeneous distribution and eight of 24 (33%) cases showed hypoventilation on equilibrium LV images. After regular HD for 5 h, no significant changes in the LV images were found. Before HD, the CRF patient group (K=1.14+/-0.36%.min-1) had a significantly faster clearance rate than that of normal controls (0.75+/-0.14%.min-1, P<0.05). Moreover, the clearance rate after HD was significantly slower (0.87+/-0.15%.min-1, P<0.05) than that before HD. CRF can predispose patients to LV change and AP damage. After HD, the damage to AP is significantly improved. However, after HD, the change in LV is not significant.

Polymorphisms of the interleukin-4 gene in chinese patients with systemic lupus erythematosus in Taiwan

We aimed to evaluate the relationship between two polymorphisms of the IL4 gene (-590T/C and intron 3) and systemic lupus erythematosus in Chinese patients in Taiwan. This study included 91 patients with systemic lupus erythematosus (SLE) and 163 unrelated, age matched healthy controls living in the same area. The typing of -590T/C and intron 3 VNTR (variable number of tandem repeats) polymorphisms were performed by PCR-RFLP and PCR, respectively. Allelic frequencies and carriage rates between SLE patients and controls were compared, and the relationship between allelic frequencies and clinical manifestations of SLE was evaluated. The genotype frequencies of IL-4 intron 3 were found to differ significantly between SLE patients with and without discoid rash (chi-square test, P = 0.03 5). The allelic frequency of intron 3 RP1 was significant different in the patients with discoid rash when compared to patients without this clinical feature (OR = 3.70, 95% CI 2.04-6.72, chi2 test, P = 0.029). The RP1/RP1 homozygous carriage was significantly associated with patients with discoid rash when compared to patients without this clinical feature (OR = 6.04, 95% CI 2.81-12.95, P = 0.01). The allelic frequency of -590T was significant different in the patients with discoid rash when compared to patients without this clinical feature (OR = 3.44, 95% CI 1.88-6.31, chi-square test, P=0.04). The T/T homozygous carriage was significantly associated with patients with discoid rash when compared to patients without this clinical feature (OR = 5.41, 95% CI 2.50-11.68, P = 0.02). We describe a novel association between RPI/RPI and T/T homozygous carriage and patients with discoid rash. The role of the intron 3 polymorphism of the IL4 gene in SLE remains unclear and further substantiation based on larger patient samples is needed.