Identifying Glycemic Variability in Diabetes Patient Cohorts and Evaluating Disease Outcomes.

Glycemic variability (GV) is an obstacle to effective blood glucose control and an autonomous risk factor for diabetes complications. We, therefore, explored sample data of patients with diabetes mellitus who maintained better amplitude of glycemic fluctuations and compared their disease outcomes with groups having poor control. A retrospective study was conducted using electronic data of patients having hemoglobin A1C (HbA1c) values with five recent time points from Think Whole Person Healthcare (TWPH). The control variability grid analysis (CVGA) plot and coefficient of variability (CV) were used to identify and cluster glycemic fluctuation. We selected important variables using LASSO. Chi-Square, Fisher's exact test, Bonferroni chi-Square adjusted residual analysis, and multivariate Kruskal-Wallis tests were used to evaluate eventual disease outcomes. Patients with very high CV were strongly associated (p < 0.05) with disorders of lipoprotein (p = 0.0014), fluid, electrolyte, and acid-base balance (p = 0.0032), while those with low CV were statistically significant for factors influencing health status such as screening for other disorders (p = 0.0137), long-term (current) drug therapy (p = 0.0019), and screening for malignant neoplasms (p = 0.0072). Reducing glycemic variability may balance alterations in electrolytes and reduce differences in lipid profiles, which may assist in strategies for managing patients with diabetes mellitus.

Perspectives of Nurses Toward Telehealth Efficacy and Quality of Health Care: Pilot Study.

BACKGROUND: Telehealth nursing, or the delivery, management, and coordination of nursing care services provided via telecommunications technology, is one of the methods of delivering health care to patients in the United States. It is important to assess the service quality of the involved health professionals as well as the telehealth nursing process. The focus of this study is the innovative model of telehealth care delivery by nurses for managing patients with chronic disease while they are living in their own residence. OBJECTIVE: The primary objective of this pilot study was to examine whether telehealth technology impacts the perceived level of internal service quality delivered by nurses within a telehealth organization. To address this research goal, the notion of telehealth nursing service quality (TNSQ) is empirically tested and validated with a survey instrument. METHODS: Data were collected from nurses belonging to a home care agency based on interview questions inquiring about facilitators and inhibitors to TNSQ. A survey to measure TNSQ based on the SERVQUAL instrument was completed by adjusting descriptions of the original instrument to suit the context. Follow-up interviews were conducted to validate questions on the revised instrument. RESULTS: The findings of this survey research were positive, based on mean differences between expectations and perceptions of TNSQ. This indicates satisfaction with TNSQ and shows that the quality of the service is higher than what the respondents expect. The Wilcoxon signed-rank test using the P value for the test, which is .35, did not show a statistically significant change between the median differences of perception and expectation. The total number of respondents was 13. Results indicate that overall perceived service quality is a positive value (0.05332). This means the perceptions of the level of service are slightly higher than what they expect, indicating there is satisfaction with TNSQ. CONCLUSIONS: The responses to the interview questions and data gathered from the survey showed overall satisfaction with TNSQ. The SERVQUAL instrument was a good framework to assess TNSQ. In a nutshell, the study highlighted how the telehealth process provides daily monitoring of patient health, leading to the benefits of immediate feedback for patients, family, and caregivers as well as convenience of scheduling.

Link test--A statistical method for finding prostate cancer biomarkers.

We present a new method, link-test, to select prostate cancer biomarkers from SELDI mass spectrometry and microarray data sets. Biomarkers selected by link-test are supported by data sets from both mRNA and protein levels, and therefore results in improved robustness. Link-test determines the level of significance of the association between a microarray marker and a specific mass spectrum marker by constructing background mass spectra distributions estimated by all human protein sequences in the SWISS-PROT database. The data set consist of both microarray and mass spectrometry data from prostate cancer patients and healthy controls. A list of statistically justified prostate cancer biomarkers is reported by link-test. Cross-validation results show high prediction accuracy using the identified biomarker panel. We also employ a text-mining approach with OMIM database to validate the cancer biomarkers. The study with link-test represents one of the first cross-platform studies of cancer biomarkers.

Comprehension and Data-Sharing Behavior of Direct-To-Consumer Genetic Test Customers.

AIM: The aim of this study was to evaluate current direct-to-consumer (DTC) genetic customers' ability to interpret and comprehend test results and to determine if honest brokers are needed. METHOD: One hundred and twenty-two customers of the DTC genetic testing company 23andMe were polled in an online survey. The subjects were asked about their personal test results and to interpret the results of two mock test cases (type 2 diabetes and multiple sclerosis), where results were translated into disease probability for an individual compared to the public. RESULTS: When asked to evaluate the risk, 72.1% correctly assessed the first case and 77% were correct on the second case. Only 23.8% of those surveyed were able to interpret both cases correctly. x03C7;2 and logistic regression were used to interpret the results. Participants who took the time to read the DTC test-provided supplemental material were 3.93 times (p = 0.040) more likely to correctly interpret the test results than those who did not. The odds for correctly interpreting the test cases were 3.289 times (p = 0.011) higher for those who made more than USD 50,000 than those who made less. Survey results were compared to the Health Information National Trends Survey (HINTS) phase 4 cycle 3 data to evaluate national trends. CONCLUSIONS: Most of the subjects were able to correctly interpret the test cases, yet a majority did not share their results with a health-care professional. As the market for DTC genetic testing grows, test comprehension will become more critical. Involving more health professionals in this process may be necessary to ensure proper interpretations.

Forecasting the Spread of Mosquito-Borne Disease using Publicly Accessible Data: A Case Study in Chikungunya.

Mosquito-borne diseases account for multiple public health challenges in our modern world. The international health community has seen a number of mosquito-borne diseases come to the forefront in recent years, including West Nile virus, Chikungunya virus, and currently, Zika virus. Predicting the spread of mosquito-borne disease can aid early decision support for when and how to employ public health interventions within a community; however, accurate and fast predictions, months into the future, are difficult to achieve in urgent scenarios, particularly when little information is known about infection rates. New sources of information including social media have been proposed to accelerate the development of predictive models of disease progression. In this research, we adapted a previously described model for the spread of mosquito-borne disease using open intelligence sources. The novel implementation of a mixed-model for mosquito-borne disease was capable of being executed in minimal runtime. The results indicate that this model yields fast and relevant results with acceptable margins of error.

Contribution of bioinformatics prediction in microRNA-based cancer therapeutics.

Despite enormous efforts, cancer remains one of the most lethal diseases in the world. With the advancement of high throughput technologies massive amounts of cancer data can be accessed and analyzed. Bioinformatics provides a platform to assist biologists in developing minimally invasive biomarkers to detect cancer, and in designing effective personalized therapies to treat cancer patients. Still, the early diagnosis, prognosis, and treatment of cancer are an open challenge for the research community. MicroRNAs (miRNAs) are small non-coding RNAs that serve to regulate gene expression. The discovery of deregulated miRNAs in cancer cells and tissues has led many to investigate the use of miRNAs as potential biomarkers for early detection, and as a therapeutic agent to treat cancer. Here we describe advancements in computational approaches to predict miRNAs and their targets, and discuss the role of bioinformatics in studying miRNAs in the context of human cancer.

Ibudilast reverses the decrease in the synaptic signaling protein phosphatidylethanolamine-binding protein 1 (PEBP1) produced by chronic methamphetamine intake in rats.

BACKGROUND: Chronic methamphetamine intake has been shown to induce a neuroinflammatory state leading to significant changes in brain functioning including behavioral changes. These changes can persist for years after drug use is discontinued and likely contribute to the risk of relapse. A better understanding of inflammation responses associated with methamphetamine intake may help in designing novel and more efficacious treatment strategies. METHODS: Rats were trained to self-administer methamphetamine or saline on a variable ratio 3 schedule of reinforcement (25 days). This training was followed by 12 days of extinction (i.e., methamphetamine unavailable) during which rats received daily post-session administration of ibudilast (AV411; 2.5 or 7.5mg/kg) or saline. Following extinction, synaptosomes were isolated from the prefrontal cortex (PFC) and the differential pattern of synaptic proteins was assessed using mass spectrometry based proteomics. RESULTS: Treatment with ibudilast allowed for deeper extinction of active lever pressing. Quantitative mass spectrometry based proteomics on the PFC identified one potential hit; the synaptic signaling protein phosphatidylethanolamine-binding protein 1 (PEBP1). While methamphetamine intake was associated with reduced PEBP1 protein levels, treatment with ibudilast reversed this effect. Furthermore, decreased PEBP1 expression was correlated with subsequent activation of Raf-1, MEK, and ERK signaling components of the mitogen-activated protein kinase cascade (MAPK). Raf-1, MEK, and ERK expression levels were also attenuated by ibudilast treatment. CONCLUSION: PEBP1, given its synaptic localization and its role as a signaling molecule acting via the ERK/MAPK pathway, could be a potential therapeutic target mediating drug-seeking behaviors associated with neuroinflammation.

Transferrin-facilitated lipofection gene delivery strategy: characterization of the transfection complexes and intracellular trafficking.

We previously showed that mixing transferrin with a cationic liposome prior to the addition of DNA, greatly enhanced the lipofection efficiency. Here, we report characterization of the transfection complexes in formulations prepared with transferrin, lipofectin, and DNA (pCMVlacZ) in various formulations. DNA in all the formulations that contain lipofectin was resistant to DNase I treatment. Transfection experiments performed in Panc 1 cells showed that the standard formulation, which was prepared by adding DNA to a mixture of transferrin and lipofectin, yielded highest transfection efficiency. There was no apparent difference in zeta potential among these formulations, but the most efficient formulation contained complexes with a mean diameter of three to four times that of liposome and the complexes in other gene delivery formulations. Transmission electron microscopic examination of the standard transfection complexes formulated using gold-labeled transferrin showed extended circular DNA decorated with transferrin as compared to extensively condensed DNA found in lipofectin-DNA complexes and heterogeneous structures in other formulations. By confocal microscopy, DNA and transferrin were found to colocalize at the perinuclear space and in the nucleus, suggesting cotransportation intracellularly, including nuclear transport. We propose that transferrin enhances the transfection efficiency of the standard lipofection formulation by preventing DNA condensation, and facilitating endocytosis and nuclear targeting.

Optimisation of miRNA-mRNA relationship prediction using biological features.

MicroRNAs are small (approx. 22nt) non-coding RNAs that regulate the expression of genes by either degrading messenger-RNA (mRNA) that has already been transcribed or by repressing the translation of mRNA, thus inhibiting protein production. This mechanism of gene regulation by binding of the miRNA to 3-prime-untranslated region of target mRNAs has been recently discovered. This sequence-specific post-transcriptional gene regulation process affects large set of genes involved in number of biological pathways. Mapping of 7nt long miRNA seed sequence to the target gene has been a standard way of predicting miRNA targets. In this study, we develop a framework to enrich the human miRNA-mRNA relationship based on genomic and structural information.

Classification and identification of fungal sequences using characteristic restriction endonuclease cut order.

Restriction Fragment Length Polymorphism (RFLP) is a powerful molecular tool that is extensively used in the molecular fingerprinting and epidemiological studies of microorganisms. In a wet-lab setting, the DNA is cut with one or more restriction enzymes and subjected to gel electrophoresis to obtain signature fragment patterns, which is utilized in the classification and identification of organisms. This wet-lab approach may not be practical when the experimental data set includes a large number of genetic sequences and a wide pool of restriction enzymes to choose from. In this study, we introduce a novel concept of Enzyme Cut Order - a biological property-based characteristic of DNA sequences which can be defined and analyzed computationally without any alignment algorithm. In this alignment-free approach, a similarity matrix is developed based on the pairwise Longest Common Subsequences (LCS) of the Enzyme Cut Orders. The choice of an ideal set of restriction enzymes used for analysis is augmented by using genetic algorithms. The results obtained from this approach using internal transcribed spacer regions of rDNA from fungi as the target sequence show that the phylogenetically-related organisms form a single cluster and successful grouping of phylogenetically close or distant organisms is dependent on the choice of restriction enzymes used in the analysis. Additionally, comparison of trees obtained with this alignment-free and the legacy method revealed highly similar tree topologies. This novel alignment-free method, which utilizes the Enzyme Cut Order and restriction enzyme profile, is a reliable alternative to local or global alignment-based classification and identification of organisms.

Mucin biosynthesis: upregulation of core 2 beta 1,6 N-acetylglucosaminyltransferase by retinoic acid and Th2 cytokines in a human airway epithelial cell line.

Vitamin A and the T helper 2 cytokines IL-4 and IL-13 play important roles in the induction of mucin gene expression and mucus hypersecretion. However, the effects of these agents on enzymes responsible for mucin glycosylation have received little attention. Here, we report the upregulation of core 2 beta1,6 N-acetylglucosaminyltransferase (C2GnT) activity both by all-trans retinoic acid (RA) and by IL-4 and IL-13 in the H292 airway epithelial cell line. Northern blotting analysis showed that the M isoform of C2GnT, which is expressed in mucus-secreting tissues and can form all mucin glycan beta1,6-branched structures, including core 2, core 4, and blood group I antigen, was upregulated by both RA and IL-4/13. The L isoform, which forms only the core 2 structure, was moderately upregulated by IL-4/13 but not by RA. Enhancement of the M isoform of C2GnT by RA was abolished by an inhibitor of RA receptor alpha, implicating RA receptor alpha in the effect of RA. Likewise, an inhibitor of the Janus kinase 3 pathway blocked the enhancing effects of IL-4/13 on the L and M isoforms of C2GnT, suggesting a role of this pathway in the upregulation of these two C2GnTs by these cytokines. Taken together, the results suggest that IL-4/13 T helper 2 cytokines and RA can alter the activity of enzymes that synthesize branching mucin carbohydrate structure in airway epithelial cells, potentially leading to altered mucin carbohydrate structure and properties.

Computational approach involving use of the internal transcribed spacer 1 region for identification of Mycobacterium species.

The rapid and reliable identification of clinically significant Mycobacterium species is a challenge for diagnostic laboratories. This study evaluates a unique sequence-dependent identification algorithm called MycoAlign for the differential identification of Mycobacterium species. The MycoAlign system uses pan-Mycobacterium-specific primer amplification in combination with a customized database and algorithm. The results of testing were compared with conventional phenotypic assays and GenBank sequence comparisons using the 16S rRNA target. Discrepant results were retested and evaluated using a third independent database. The custom database was generated using the hypervariable sequences of the internal transcribed spacer 1 (ITS-1) region of the rRNA gene complex from characterized Mycobacterium species. An automated sequence-validation process was used to control quality and specificity of evaluated sequence. A total of 181 Mycobacterium strains (22 reference strains and 159 phenotypically identified clinical isolates) and seven nonmycobacterial clinical isolates were evaluated in a comparative study to validate the accuracy of the MycoAlign algorithm. MycoAlign correctly identified all referenced strains and matched species in 94% of the phenotypically identified Mycobacterium clinical isolates. The ITS-1 sequence target showed a higher degree of specificity in terms of Mycobacterium identification than the 16S rRNA sequence by use of GenBank BLAST. This study showed the MycoAlign algorithm to be a reliable and rapid approach for the identification of Mycobacterium species and confirmed the superiority of the ITS-1 region sequence over the 16S rRNA gene sequence as a target for sequence-based species identification.

Mucin biosynthesis: epidermal growth factor downregulates core 2 enzymes in a human airway adenocarcinoma cell line.

Enzymes which exhibit core 2 beta1,6 N-acetylglucosaminyltransferase (C2GnT) activity play important roles in physiologic processes including the inflammatory response and immune system function, and C2GnT activity is regulated during processes, such as T cell activation and cellular differentiation. In this study, we have examined the regulation of C2GnT activity in the H292 airway epithelial cell line by epidermal growth factor (EGF), which has been previously shown to upregulate expression of the airway mucin MUC5AC in this cell line. We found that EGF suppressed C2GnT activity in a time- and dose-dependent fashion, and also suppressed core 4 beta1,6 N-acetylglucosaminyltransferase (C4GnT) activity. Consistent with the suppression of C4GnT activity, Northern blotting results showed that EGF preferentially inhibited the M isoform of C2GnT, which forms core 2, core 4, and blood group I beta1,6 branched carbohydrate structures, while the L isoform, which forms only the core 2 structure, was only modestly affected. Furthermore, EGF treatment resulted in a shift in the carbohydrate structure of FLAG-tagged MUC1 expressed in the cells from core 2-based toward core 1-based structures, consistent with the inhibitory effects of EGF on C2GnT. Transforming growth factor alpha mimicked the effect of EGF on C2GnT, implicating the EGF receptor (EGF-R) in C2GnT suppression, and the EGF-R tyrosine kinase inhibitor AG1478 blocked C2GnT suppression, confirming the role of EGF-R in the inhibition of C2GnT expression. Also, PD98059, a specific inhibitor of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase (MEK)1/2 in the Ras-mitogen-activated protein kinase pathway, completely blocked the EGF suppressive effect, suggesting possible involvement of the Ras-mitogen-activated protein kinase pathway in EGF-mediated downregulation of C2GnT. The results of this study suggest that exposure of airway cells to EGF may result in remodeling of mucin carbohydrate structure, potentially altering the biological properties of the cells.

Downregulation of PTEN/MMAC/TEP1 expression in human prostate cancer cell line DU145 by growth stimuli.

Genetic alterations and/or deletion of the tumor suppressor gene PTEN/MMAC/TEP1 occur in many types of human cancer including prostate cancer. We describe the production of monoclonal antibody against recombinant human PTEN and the study of PTEN gene and protein expression in three commercially available human prostate cancer cell lines, PC-3, LNCaP, and DU 145. Northern blotting analyses showed that LNCaP and DU145 but not PC-3 cells expressed PTEN mRNA. However, Western blotting analyses using a monoclonal antibody against PTEN demonstrated the expression of PTEN protein in DU145 but not LNCaP cells. In DU 145 cells, PTEN expression at both the mRNA and protein levels inversely correlated with serum concentrations and levels of PKB/Akt phosphorylation. In addition, the basal activity of PKB/Akt as indicated by level of phosphorylation was higher in prostate cancer cells which do not express PTEN than that in the cells expressing wild type PTEN. Thus, PTEN may play a critical role in regulating cellular signaling in prostate cancer cells.

Temperature-mediated heteroduplex analysis for detection of pncA mutations associated with pyrazinamide resistance and differentiation between Mycobacterium tuberculosis and Mycobacterium bovis by denaturing high- performance liquid chromatography.

The goal of this study was to apply temperature-mediated heteroduplex analysis using denaturing high-performance liquid chromatography to identify pyrazinamide (PZA) resistance in Mycobacterium tuberculosis isolates and simultaneously differentiate between M. tuberculosis and Mycobacterium bovis. Features that contributed to an optimal assay included the use of two different reference probes for the pncA gene targets from wild-type M. tuberculosis and wild-type M. bovis, optimization of the column temperature, increasing the starting concentration of the elution buffer, and reducing the rate of elution buffer increase (slope). A total of 69 strains were studied, including 48 wild-type M. tuberculosis strains (13 were PZA-resistant strains) and 21 M. bovis strains (8 were BCG strains). In all isolates tested, wild-type M. tuberculosis generated a single-peak pattern when mixed with the M. tuberculosis probe and a double-peak pattern with the M. bovis probe. In contrast, all M. bovis isolates generated a double-peak pattern when mixed with the M. tuberculosis probe and a single-peak pattern with the M. bovis probe. PZA-resistant mutant M. tuberculosis isolates generated characteristic patterns that were easily distinguishable from both wild-type M. tuberculosis and M. bovis isolates. Chromatographic patterns generated by the two reference probes allowed the rapid detection of PZA resistance with the simultaneous ability to distinguish between M. tuberculosis and M. bovis. This approach may allow the detection of drug resistance-associated mutations, with potential application to clinical and epidemiological aspects of tuberculosis control.

Utilization of the relative complexity measure to construct a phylogenetic tree for fungi.

The relative complexity measure (RCM) is a new approach to evaluate relatedness of DNA sequences which eliminates the requirement to align sequences prior to analysis, a step required with standard reference methods. The value of the RCM approach to generate distance matrices for use in phylogenetic analysis of organisms has not been determined. This study compared RCM with the algorithmic and tree searching reference methods for phylogenetic analysis using fungal sequences. Sequences of the cytochrome b gene and the 18S rDNA gene were obtained from the GenBank database to determine feasibility of this method for phylogenetic relatedness. The RCM approach was also used to construct a phylogenetic tree using internal transcribed spacer (ITS) sequences from 23 medically relevant fungal species. The robustness of the RCM and reference approaches was determined by comparing the topology of seven medically relevant fungi within the phylogenetic trees generated after progressive removal of 10, 20, 30, 40 and 50% of the nucleotide bases from either the 5' or 3' end of the three genomic target sequences. The results demonstrated that the RCM method was equivalent to the reference methods for construction of phylogenetic trees from cytochrome b and 18S rDNA gene sequences. The phylogenetic tree constructed using the ITS sequence generated no contradictory topology. The RCM generated trees retained the appropriate topology after removal of up to 50% of the cytochrome b sequence, 40% of the ITS sequence, and 30% of the 18S gene target sequence. Comparatively, the reference methods failed to maintain topology after only a 10% sequence deletion for each genomic target. The results showed the RCM to be a reliable and robust computational approach for use in the construction of fungal phylogenetic trees without the requirement for prior sequence alignment.