The SEQanswers wiki: a wiki database of tools for high-throughput sequencing analysis

Recent advances in sequencing technology have created unprecedented opportunities for biological research. However, the increasing throughput of these technologies has created many challenges for data management and analysis. As the demand for sophisticated analyses increases, the development time of software and algorithms is outpacing the speed of traditional publication. As technologies continue to be developed, methods change rapidly, making publications less relevant for users. The SEQanswers wiki (SEQwiki) is a wiki database that is actively edited and updated by the members of the SEQanswers community (http://SEQanswers.com/). The wiki provides an extensive catalogue of tools, technologies and tutorials for high-throughput sequencing (HTS), including information about HTS service providers. It has been implemented in MediaWiki with the Semantic MediaWiki and Semantic Forms extensions to collect structured data, providing powerful navigation and reporting features. Within 2 years, the community has created pages for over 500 tools, with approximately 400 literature references and 600 web links. This collaborative effort has made SEQwiki the most comprehensive database of HTS tools anywhere on the web. The wiki includes task-focused mini-reviews of commonly used tools, and a growing collection of more than 100 HTS service providers. SEQwiki is available at: http://wiki.SEQanswers.com/

Photo-designed terahertz devices

Technologies are being developed to manipulate electromagnetic waves using artificially structured materials such as photonic crystals and metamaterials, with the goal of creating primary optical devices. For example, artificial metallic periodic structures show potential for the construction of devices operating in the terahertz frequency regime. Here we demonstrate the fabrication of photo-designed terahertz devices that enable the real-time, wide-range frequency modulation of terahertz electromagnetic waves. These devices are comprised of a photo-induced, planar periodic-conductive structure formed by the irradiation of a silicon surface using a spatially modulated, femtosecond optical pulsed laser. We also show that the modulation frequency can be tuned by the structural periodicity, but is hardly affected by the excitation power of the optical pump pulse. We expect that our findings will pave the way for the construction of all-optical compact operating devices, such as optical integrated circuits, thereby eliminating the need for materials fabrication processes

Thermal Impact on Spiking Properties in Hodgkin-Huxley Neuron with Synaptic Stimulus

The effect of environmental temperature on neuronal spiking behaviors is investigated by numerically simulating the temperature dependence of spiking threshold of the Hodgkin-Huxley neuron subject to synaptic stimulus. We find that the spiking threshold exhibits a global minimum in a "comfortable temperature" range where spike initiation needs weakest synaptic strength, indicating the occurrence of optimal use of synaptic transmission in neural system. We further explore the biophysical origin of this phenomenon in ion channel gating kinetics and also discuss its possible biological relevance in information processing in neural systems.Comment: 10 pages, 4 figure

Expression analysis of mammaglobin A (SCGB2A2) and lipophilin B (SCGB1D2) in more than 300 human tumors and matching normal tissues reveals their co-expression in gynecologic malignancies

BACKGROUND: Mammaglobin A (SCGB2A2) and lipophilin B (SCGB1D2), two members of the secretoglobin superfamily, are known to be co-expressed in breast cancer, where their proteins form a covalent complex. Based on the relatively high tissue-specific expression pattern, it has been proposed that the mammaglobin A protein and/or its complex with lipophilin B could be used in breast cancer diagnosis and treatment. In view of these clinical implications, the aim of the present study was to analyze the expression of both genes in a large panel of human solid tumors (n = 309), corresponding normal tissues (n = 309) and cell lines (n = 11), in order to evaluate their tissue specific expression and co-expression pattern. METHODS: For gene and protein expression analyses, northern blot, dot blot hybridization of matched tumor/normal arrays (cancer profiling arrays), quantitative RT-PCR, non-radioisotopic RNA in situ hybridization and immunohistochemistry were used. RESULTS: Cancer profiling array data demonstrated that mammaglobin A and lipophilin B expression is not restricted to normal and malignant breast tissue. Both genes were abundantly expressed in tumors of the female genital tract, i.e. endometrial, ovarian and cervical cancer. In these four tissues the expression pattern of mammaglobin A and lipophilin B was highly concordant, with both genes being down-, up- or not regulated in the same tissue samples. In breast tissue, mammaglobin A expression was down-regulated in 49% and up-regulated in 12% of breast tumor specimens compared with matching normal tissues, while lipophilin B was down-regulated in 59% and up-regulated in 3% of cases. In endometrial tissue, expression of mammaglobin A and lipophilin B was clearly up-regulated in tumors (47% and 49% respectively). Both genes exhibited down-regulation in 22% of endometrial tumors. The only exceptions to this concordance of mammaglobin A/lipophilin B expression were normal and malignant tissues of prostate and kidney, where only lipophilin B was abundantly expressed and mammaglobin A was entirely absent. RNA in situ hybridization and immunohistochemistry confirmed expression of mammaglobin A on a cellular level in endometrial and cervical cancer and their corresponding normal tissues. CONCLUSION: Altogether, these data suggest that expression of mammaglobin A and lipophilin B might be controlled in different tissues by the same regulatory transcriptional mechanisms. Diagnostic assays based on mammaglobin A expression and/or the mammaglobin A/lipophilin B complex appear to be less specific for breast cancer, but with a broader spectrum of potential applications, which includes gynecologic malignancies

Reduction of the Body Burden of PCBs and DDE by Dietary Intervention in a Randomized Trial

Serum polychlorinated biphenyls (PCBs) in Anniston, AL, residents have been associated with hypertension and diabetes. There have been no systematic interventions to reduce PCB body burdens in Anniston or other populations. Our objective was to determine the efficacy of 15 g/day of dietary olestra to reduce PCBs in Anniston residents. Blood PCBs and 1,1-bis-(4-chlorophenyl)-2,2-dichloroethene were measured at baseline and 4-month intervals in a double-blind, placebo-controlled, 1-year trial. Participants with elevated serum PCBs were randomized into two groups of 14 and received potato crisps made with olestra or vegetable oil (VO). Elimination rates during the study period were compared with 5-year prestudy rates. Eleven participants in the olestra group and 12 in the VO group completed the study. Except for one participant in the VO group, reasons for dropout were unrelated to treatments. The elimination rate of 37 noncoplanar PCB congeners during the 1-year trial was faster during olestra consumption compared to the pretrial period (−0.0829±0.0357 and −0.00864±0.0116 year−1, respectively; P=.04), but not during VO consumption (−0.0413±0.0408 and −0.0283±0.0096 year−1, respectively; P=.27). The concentration of PCBs in two olestra group participants decreased by 27% and 25% during the trial. There was no significant time by group interaction in change from baseline. However, group main effects for total PCBs and PCB 153 were of borderline significance. This pilot study has demonstrated that olestra can safely reduce body burdens of PCBs and supports a larger intervention trial that may also determine whether reduction in PCBs will reduce the risk of hypertension and diabetes

Longitudinal association of biomarkers of pesticide exposure with cardiovascular disease risk factors in youth with diabetes

Background: Cardiovascular disease (CVD) is the leading cause of death among individuals with diabetes, but little is known about the role of exposures to environmental chemicals such as pesticides in the early development of CVD risk in this population. Objectives: To describe changes over time in concentrations of pesticide biomarkers among youth with diabetes in the United States and to estimate the longitudinal association between these concentrations and established risk factors for CVD. Methods: Pesticide biomarkers were quantified in urine and serum samples from 87 youth with diabetes participating in the multi-center SEARCH cohort study. Samples were obtained around the time of diagnosis (baseline visit, between 2006 and 2010) and, on average, 5.4 years later (follow-up visit, between 2012 and 2015). We calculated geometric mean (95% CI) pesticide biomarker concentrations. Eight CVD risk factors were measured at these two time points: body mass index (BMI) z-score, HbA1c, insulin sensitivity, fasting C-peptide (FCP), LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides. Linear regression models were used to estimate the associations between each pesticide biomarker at baseline and each CVD risk factor at follow-up, adjusting for baseline health outcome, elapsed time between baseline and follow up, sex, age, race/ethnicity, and diabetes type. Results: Participants were, on average, 14.2 years old at their baseline visit, and most were diagnosed with type 1 diabetes (57.5%). 4-nitrophenol, 3-phenoxybenzoic acid, 2,4-dichlorophenoxyacetic acid (2,4-D), 3,5,6-trichloro-2-pyridinol, 2,2-bis(4-chlorophenyl)-1,1-dichloroethene, and hexachlorobenzene were detected in a majority of participants at both time points. Participants in the highest quartile of 2,4-D and 4-nitrophenol at baseline had HbA1c levels at follow-up that were 1.05 percentage points (95% CI: −0.40, 2.51) and 1.27 percentage points (0.22, 2.75) higher, respectively, than participants in the lowest quartile of these pesticide biomarkers at baseline. These participants also had lower log FCP levels (indicating reduced beta-cell function) compared to participants in the lowest quartile at baseline: beta (95% CI) for log FCP of −0.64 (−1.17, −0.11) for 2,4-D and −0.39 (−0.96, 0.18) for 4-nitrophenol. In other words, participants in the highest quartile of 2,4-D had a 47.3% lower FCP level compared to participants in the lowest quartile, and those in the highest quartile of 4-nitrophenol had a 32.3% lower FCP level than those in the lowest quartile. Participants with trans-nonachlor concentrations in the highest quartile at baseline had HbA1c levels that were 1.45 percentage points (−0.11, 3.01) higher and log FCP levels that were −0.28 (−0.84, 0.28) lower than participants in the lowest quartile at baseline, that is to say, participants in the highest quartile of trans-nonachlor had a 24.4% lower FCP level than those in the lowest quartile. While not all of these results were statistically significant, potentially due to the small same size, clinically, there appears to be quantitative differences. No associations were observed between any pesticide biomarker at baseline with BMI z-score or insulin sensitivity at follow-up. Conclusions: Exposure to select pesticides may be associated with impaired beta-cell function and poorer glycemic control among youth with diabetes

Bridging the gap: Using reservoir ecology and human serosurveys to estimate Lassa virus spillover in West Africa

Forecasting the risk of pathogen spillover from reservoir populations of wild or domestic animals is essential for the effective deployment of interventions such as wildlife vaccination or culling. Due to the sporadic nature of spillover events and limited availability of data, developing and validating robust, spatially explicit, predictions is challenging. Recent efforts have begun to make progress in this direction by capitalizing on machine learning methodologies. An important weakness of existing approaches, however, is that they generally rely on combining human and reservoir infection data during the training process and thus conflate risk attributable to the prevalence of the pathogen in the reservoir population with the risk attributed to the realized rate of spillover into the human population. Because effective planning of interventions requires that these components of risk be disentangled, we developed a multi-layer machine learning framework that separates these processes. Our approach begins by training models to predict the geographic range of the primary reservoir and the subset of this range in which the pathogen occurs. The spillover risk predicted by the product of these reservoir specific models is then fit to data on realized patterns of historical spillover into the human population. The result is a geographically specific spillover risk forecast that can be easily decomposed and used to guide effective intervention. Applying our method to Lassa virus, a zoonotic pathogen that regularly spills over into the human population across West Africa, results in a model that explains a modest but statistically significant portion of geographic variation in historical patterns of spillover. When combined with a mechanistic mathematical model of infection dynamics, our spillover risk model predicts that 897,700 humans are infected by Lassa virus each year across West Africa, with Nigeria accounting for more than half of these human infections.</jats:p

Assessment of xenoestrogenic exposure by a biomarker approach: application of the E-Screen bioassay to determine estrogenic response of serum extracts

BACKGROUND: Epidemiological documentation of endocrine disruption is complicated by imprecise exposure assessment, especially when exposures are mixed. Even if the estrogenic activity of all compounds were known, the combined effect of possible additive and/or inhibiting interaction of xenoestrogens in a biological sample may be difficult to predict from chemical analysis of single compounds alone. Thus, analysis of mixtures allows evaluation of combined effects of chemicals each present at low concentrations. METHODS: We have developed an optimized in vitro E-Screen test to assess the combined functional estrogenic response of human serum. The xenoestrogens in serum were separated from endogenous steroids and pharmaceuticals by solid-phase extraction followed by fractionation by high-performance liquid chromatography. After dissolution of the isolated fraction in ethanol-DMSO, the reconstituted extract was added with estrogen-depleted fetal calf serum to MCF-7 cells, the growth of which is stimulated by estrogen. After a 6-day incubation on a microwell plate, cell proliferation was assessed and compared with the effect of a 17-beta-estradiol standard. RESULTS AND CONCLUSIONS: To determine the applicability of this approach, we assessed the estrogenicity of serum samples from 30 pregnant and 60 non-pregnant Danish women thought to be exposed only to low levels of endocrine disruptors. We also studied 211 serum samples from pregnant Faroese women, whose marine diet included whale blubber that contain a high concentration of persistent halogenated pollutants. The estrogenicity of the serum from Danish controls exceeded the background in 22.7 % of the cases, while the same was true for 68.1 % of the Faroese samples. The increased estrogenicity response did not correlate with the lipid-based concentrations of individual suspected endocrine disruptors in the Faroese samples. When added along with the estradiol standard, an indication of an enhanced estrogenic response was found in most cases. Thus, the in vitro estrogenicity response offers a promising and feasible approach for an aggregated exposure assessment for xenoestrogens in serum

Gender differences in the physiological responses and kinematic behaviour of elite sprint cross-country skiers

Gender differences in performance by elite endurance athletes, including runners, track cyclists and speed skaters, have been shown to be approximately 12%. The present study was designed to examine gender differences in physiological responses and kinematics associated with sprint cross-country skiing. Eight male and eight female elite sprint cross-country skiers, matched for performance, carried out a submaximal test, a test of maximal aerobic capacity (VO2max) and a shorter test of maximal treadmill speed (Vmax) during treadmill roller skiing utilizing the G3 skating technique. The men attained 17% higher speeds during both the VO2max and the Vmax tests (P < 0.05 in both cases), differences that were reduced to 9% upon normalization for fat-free body mass. Furthermore, the men exhibited 14 and 7% higher VO2max relative to total and fat-free body mass, respectively (P < 0.05 in both cases). The gross efficiency was similar for both gender groups. At the same absolute speed, men employed 11% longer cycles at lower rates, and at peak speed, 21% longer cycle lengths (P < 0.05 in all cases). The current study documents approximately 5% larger gender differences in performance and VO2max than those reported for comparable endurance sports. These differences reflect primarily the higher VO2max and lower percentage of body fat in men, since no gender differences in the ability to convert metabolic rate into work rate and speed were observed. With regards to kinematics, the gender difference in performance was explained by cycle length, not by cycle rate