The role of wind gusts in upper ocean diurnal variability

Upper ocean processes play a key role in air-sea coupling, with variability on both short and long time scales. The diurnal cycle associated with diurnal solar insolation and nighttime cooling, may act, along with stochastic wind variability, on upper ocean temperatures and stratification resulting in a diurnal warm layer and a nonlinear rectified effect on longer time scales. This study describes diurnal changes in upper ocean temperature for a location in the equatorial Indian Ocean, using observations from the Dynamics of the Madden-Julian Oscillation field campaign, a high vertical resolution 1-D process model, and a diurnal cycling scheme. Solar forcing is the main driver of diurnal variability in upper ocean temperature and stratification. Yet except during nighttime convection, winds with variability on the order of hours (here referred to as “wind gusts”) regulate how fast surface water is mixed to greater depths when daily mean winds are weak. Wind gusts are much stronger than diurnal winds. Even using stochastic wind gusts but no diurnal winds as input in a 1-D process model yields an estimate of diurnal temperature that compares well with observations. A new version of the Large and Caron (2015) scheme (LC2015) provides an estimate of upper ocean diurnal temperature that is consistent with observations. LC2015 has the advantage of being suitable for implementation in a climate model, with the goal to improve SST estimates, hence the simulated heat flux at the air-sea interface. Yet LC2015 is not very sensitive to the inclusion or omission of the high-frequency component of the wind

A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India.

BACKGROUND: The elimination programme for visceral leishmaniasis (VL) in India has seen great progress, with total cases decreasing by over 80% since 2010 and many blocks now reporting zero cases from year to year. Prompt diagnosis and treatment is critical to continue progress and avoid epidemics in the increasingly susceptible population. Short-term forecasts could be used to highlight anomalies in incidence and support health service logistics. The model which best fits the data is not necessarily most useful for prediction, yet little empirical work has been done to investigate the balance between fit and predictive performance. METHODOLOGY/PRINCIPAL FINDINGS: We developed statistical models of monthly VL case counts at block level. By evaluating a set of randomly-generated models, we found that fit and one-month-ahead prediction were strongly correlated and that rolling updates to model parameters as data accrued were not crucial for accurate prediction. The final model incorporated auto-regression over four months, spatial correlation between neighbouring blocks, and seasonality. Ninety-four percent of 10-90% prediction intervals from this model captured the observed count during a 24-month test period. Comparison of one-, three- and four-month-ahead predictions from the final model fit demonstrated that a longer time horizon yielded only a small sacrifice in predictive power for the vast majority of blocks. CONCLUSIONS/SIGNIFICANCE: The model developed is informed by routinely-collected surveillance data as it accumulates, and predictions are sufficiently accurate and precise to be useful. Such forecasts could, for example, be used to guide stock requirements for rapid diagnostic tests and drugs. More comprehensive data on factors thought to influence geographic variation in VL burden could be incorporated, and might better explain the heterogeneity between blocks and improve uniformity of predictive performance. Integration of the approach in the management of the VL programme would be an important step to ensuring continued successful control

A mobile telehealth intervention for adults with insulin-requiring diabetes: early results of a mixed-methods randomized controlled trial

BACKGROUND: The role of technology in health care delivery has grown rapidly in the last decade. The potential of mobile telehealth (MTH) to support patient self-management is a key area of research. Providing patients with technological tools that allow for the recording and transmission of health parameters to health care professionals (HCPs) may promote behavior changes that result in improved health outcomes. Although for some conditions the evidence of the effectiveness of MTH is clear, to date the findings on the effects of MTH on diabetes management remain inconsistent. OBJECTIVE: This study aims to evaluate an MTH intervention among insulin-requiring adults with diabetes to establish whether supplementing standard care with MTH results in improved health outcomes-glycated hemoglobin (HbA1c), blood pressure (BP), health-related quality of life (HRQoL), diabetes self-management behaviors, diabetes health care utilization, and diabetes self-efficacy and illness beliefs. An additional objective was to explore the acceptability of MTH and patients' perceptions of, and experience, using it. METHODS: A mixed-method design consisting of a 9-month, two-arm, parallel randomized controlled trial (RCT) was used in combination with exit qualitative interviews. Quantitative data was collected at baseline, 3 months, and 9 months. Additional intervention fidelity data, such as participants' MTH transmissions and contacts with the MTH nurse during the study, were also recorded. RESULTS: Data collection for both the quantitative and qualitative components of this study has ended and data analysis is ongoing. A total of 86 participants were enrolled into the study. Out of 86 participants, 45 (52%) were randomized to the intervention group and 36 (42%) to the control group. Preliminary data on MTH training sessions and MTH usage by intervention participants are presented in this paper. We expect to publish complete study results in 2015. CONCLUSIONS: The range of data collected in this study will allow for a comprehensive evaluation of processes and outcomes. The early results presented suggest that MTH usage decreases over time and that MTH participants would benefit from attending more than one training session. TRIAL REGISTRATION: ClinicalTrials.gov NCT00922376; http://clinicaltrials.gov/ct2/show/NCT00922376 (Archived by WebCite at http://www.webcitation.org/6Vu4nhLI6)

Surveillance of testicular microlithiasis?: Results of an UK based national questionnaire survey

BACKGROUND: The association of testicular microlithiasis with testicular tumour and the need for follow-up remain largely unclear. METHODS: We conducted a national questionnaire survey involving consultant BAUS members (BAUS is the official national organisation (like the AUA in USA) of the practising urologists in the UK and Ireland), to provide a snapshot of current attitudes towards investigation and surveillance of patients with testicular microlithiasis. RESULTS: Of the 464 questionnaires sent to the BAUS membership, 263(57%) were returned. 251 returns (12 were incomplete) were analysed, of whom 173(69%) do and 78(31%) do not follow-up testicular microlithiasis. Of the 173 who do follow-up, 119(69%) follow-up all patients while 54(31%) follow-up only a selected group of patients. 172 of 173 use ultra sound scan while 27(16%) check tumour makers. 10(6%) arrange ultrasound scan every six months, 151(88%) annually while 10(6%) at longer intervals. 66(38%) intend to follow-up these patients for life while, 80(47%) until 55 years of age and 26(15%) for up to 5 years. 173(68.9%) believe testicular microlithiasis is associated with CIS in < 1%, 53(21%) think it is between 1&10% while 7(3%) believe it is > 10%. 109(43%) believe those patients who develop a tumour, will have survival benefit with follow-up while 142(57%) do not. Interestingly, 66(38%) who follow-up these patients do not think there is a survival benefit. CONCLUSION: There is significant variability in how patients with testicular microlithiasis are followed-up. However a majority of consultant urologists nationally, believe surveillance of this patient group confers no survival benefit. There is a clear need to clarify this issue in order to recommend a coherent surveillance policy

New approaches to measuring anthelminthic drug efficacy: parasitological responses of childhood schistosome infections to treatment with praziquantel

By 2020, the global health community aims to control and eliminate human helminthiases, including schistosomiasis in selected African countries, principally by preventive chemotherapy (PCT) through mass drug administration (MDA) of anthelminthics. Quantitative monitoring of anthelminthic responses is crucial for promptly detecting changes in efficacy, potentially indicative of emerging drug resistance. Statistical models offer a powerful means to delineate and compare efficacy among individuals, among groups of individuals and among populations.; We illustrate a variety of statistical frameworks that offer different levels of inference by analysing data from nine previous studies on egg counts collected from African children before and after administration of praziquantel.; We quantify responses to praziquantel as egg reduction rates (ERRs), using different frameworks to estimate ERRs among population strata, as average responses, and within strata, as individual responses. We compare our model-based average ERRs to corresponding model-free estimates, using as reference the World Health Organization (WHO) 90 % threshold of optimal efficacy. We estimate distributions of individual responses and summarize the variation among these responses as the fraction of ERRs falling below the WHO threshold.; Generic models for evaluating responses to anthelminthics deepen our understanding of variation among populations, sub-populations and individuals. We discuss the future application of statistical modelling approaches for monitoring and evaluation of PCT programmes targeting human helminthiases in the context of the WHO 2020 control and elimination goals

Design, Synthesis and Characterization of a Highly Effective Inhibitor for Analog-Sensitive (as) Kinases

Highly selective, cell-permeable and fast-acting inhibitors of individual kinases are sought-after as tools for studying the cellular function of kinases in real time. A combination of small molecule synthesis and protein mutagenesis, identified a highly potent inhibitor (1-Isopropyl-3-(phenylethynyl)-1H-pyrazolo[3,4-d]pyrimidin-4-amine) of a rationally engineered Hog1 serine/threonine kinase (Hog1T100G). This inhibitor has been successfully used to study various aspects of Hog1 signaling, including a transient cell cycle arrest and gene expression changes mediated by Hog1 in response to stress. This study also underscores that the general applicability of this approach depends, in part, on the selectivity of the designed the inhibitor with respect to activity versus the engineered and wild type kinases. To explore this specificity in detail, we used a validated chemogenetic assay to assess the effect of this inhibitor on all gene products in yeast in parallel. The results from this screen emphasize the need for caution and for case-by-case assessment when using the Analog-Sensitive Kinase Allele technology to assess the physiological roles of kinases

Identifying Tightly Regulated and Variably Expressed Networks by Differential Rank Conservation (DIRAC)

A powerful way to separate signal from noise in biology is to convert the molecular data from individual genes or proteins into an analysis of comparative biological network behaviors. One of the limitations of previous network analyses is that they do not take into account the combinatorial nature of gene interactions within the network. We report here a new technique, Differential Rank Conservation (DIRAC), which permits one to assess these combinatorial interactions to quantify various biological pathways or networks in a comparative sense, and to determine how they change in different individuals experiencing the same disease process. This approach is based on the relative expression values of participating genes—i.e., the ordering of expression within network profiles. DIRAC provides quantitative measures of how network rankings differ either among networks for a selected phenotype or among phenotypes for a selected network. We examined disease phenotypes including cancer subtypes and neurological disorders and identified networks that are tightly regulated, as defined by high conservation of transcript ordering. Interestingly, we observed a strong trend to looser network regulation in more malignant phenotypes and later stages of disease. At a sample level, DIRAC can detect a change in ranking between phenotypes for any selected network. Variably expressed networks represent statistically robust differences between disease states and serve as signatures for accurate molecular classification, validating the information about expression patterns captured by DIRAC. Importantly, DIRAC can be applied not only to transcriptomic data, but to any ordinal data type

Hybrid Models Identified a 12-Gene Signature for Lung Cancer Prognosis and Chemoresponse Prediction

Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35-50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs

Pd Nanoparticles and Thin Films for Room Temperature Hydrogen Sensor

We report the application of palladium nanoparticles and thin films for hydrogen sensor. Electrochemically grown palladium particles with spherical shapes deposited on Si substrate and sputter deposited Pd thin films were used to detect hydrogen at room temperature. Grain size dependence of H2sensing behavior has been discussed for both types of Pd films. The electrochemically grown Pd nanoparticles were observed to show better hydrogen sensing response than the sputtered palladium thin films. The demonstration of size dependent room temperature H2sensing paves the ways to fabricate the room temperature metallic and metal–metal oxide semiconductor sensor by tuning the size of metal catalyst in mixed systems. H2sensing by the Pd nanostructures is attributed to the chemical and electronic sensitization mechanisms

E2F1 Mediated Apoptosis Induced by the DNA Damage Response Is Blocked by EBV Nuclear Antigen 3C in Lymphoblastoid Cells

EBV latent antigen EBNA3C is indispensible for in vitro B-cell immortalization resulting in continuously proliferating lymphoblastoid cell lines (LCLs). EBNA3C was previously shown to target pRb for ubiquitin-proteasome mediated degradation, which facilitates G1 to S transition controlled by the major transcriptional activator E2F1. E2F1 also plays a pivotal role in regulating DNA damage induced apoptosis through both p53-dependent and -independent pathways. In this study, we demonstrate that in response to DNA damage LCLs knocked down for EBNA3C undergo a drastic induction of apoptosis, as a possible consequence of both p53- and E2F1-mediated activities. Importantly, EBNA3C was previously shown to suppress p53-induced apoptosis. Now, we also show that EBNA3C efficiently blocks E2F1-mediated apoptosis, as well as its anti-proliferative effects in a p53-independent manner, in response to DNA damage. The N- and C-terminal domains of EBNA3C form a stable pRb independent complex with the N-terminal DNA-binding region of E2F1 responsible for inducing apoptosis. Mechanistically, we show that EBNA3C represses E2F1 transcriptional activity via blocking its DNA-binding activity at the responsive promoters of p73 and Apaf-1 apoptosis induced genes, and also facilitates E2F1 degradation in an ubiquitin-proteasome dependent fashion. Moreover, in response to DNA damage, E2F1 knockdown LCLs exhibited a significant reduction in apoptosis with higher cell-viability. In the presence of normal mitogenic stimuli the growth rate of LCLs knockdown for E2F1 was markedly impaired; indicating that E2F1 plays a dual role in EBV positive cells and that active engagement of the EBNA3C-E2F1 complex is crucial for inhibition of DNA damage induced E2F1-mediated apoptosis. This study offers novel insights into our current understanding of EBV biology and enhances the potential for development of effective therapies against EBV associated B-cell lymphomas