Urban Cholera transmission hotspots and their implications for Reactive Vaccination: evidence from Bissau city, Guinea Bissau

Use of cholera vaccines in response to epidemics (reactive vaccination) may provide an effective supplement to traditional control measures. In Haiti, reactive vaccination was considered but, until recently, rejected in part due to limited global supply of vaccine. Using Bissau City, Guinea-Bissau as a case study, we explore neighborhood-level transmission dynamics to understand if, with limited vaccine and likely delays, reactive vaccination can significantly change the course of a cholera epidemic

Prevalence and tick loads in Nguni cattle reared in different environmental conditions across four provinces of South Africa

BACKGROUND AND AIM: In tropical and subtropical countries, ixodid ticks are among livestock’s most economically important ectoparasites. Although Nguni cattle from South Africa have adapted to harsh environments, it is unknown whether they will be resistant to ticks, and the diseases carried by ticks under various climatic conditions. Therefore, this study aimed to compare tick load and estimate the prevalence of different tick species among Nguni cattle under different environmental conditions. MATERIALS AND METHODS: Tick counts were conducted monthly under natural challenges over 2 years on 586 Nguni cattle located at ARC-Roodeplaat and Loskop farms (warmer climate), Mukhuthali Nguni Community and the University of Fort Hare farms (cooler climate). The generalized linear model procedure of the Statistical Analysis System was used to analyze the data. It fitted the location (farm), sex, year, month or season, and animal age as covariates. RESULTS: The tick species (relative prevalence) observed were as follows: Amblyomma hebraeum (42%), Rhipicephalus evertsi (22%), Rhipicephalus (Boophilus) spp. (16%), Rhipicephalus appendiculatus (11%), Hyalomma marginatum (5%), and Rhipicephalus simus (4%). Tick infestation was significantly affected by location, season, year, month of the tick counting and age of the animal. Loskop farm had the highest tick count (m = 30.69) and showed the largest variation in tick count. Compared to the other seasons, higher tick counts were seen during the hot-dry (September–November) and hot-wet (December–February) seasons. A. hebraeum was the dominant tick species across all four farms, followed by R. evertsi. The perianal region (under the tail head), the perineum and the belly body locations were the most preferred tick attachment sites. CONCLUSION: These results provide useful information for developing appropriate control strategies for ticks and tick-borne diseases in these provinces of South Africa. Further work must investigate the feasibility of genetic improvement for tick resistance

Association between Antibodies to the MR 67,000 Isoform of Glutamate Decarboxylase (GAD) and Type 1 (Insulin-Dependent) Diabetes Mellitus with Coexisting Autoimmune Polyendocrine Syndrome Type II

By using an immunoprecipitation assay, we analysed reactivity of autoantibodies to human recombinant GAD65 and GAD67 in sera from patients with autoimmune polyendocrine syndrome Type II (APS II) with and without Type 1 (insulin-dependent) diabetes mellitus (IDDM) compared to patients with organ-specific autoimmunity. Overall antibodies to GAD65 were correlated with IDDM in all study groups, whereas GAD67 antibodies were associated with IDDM when APS II coexists. Antibodies to GAD65 and GAD67 were detected in 13 (44.8%) and 7 (24.1%) out of 29 APS II patients with IDDM, but in only 4 (13.8%) and 2 (6.9%) out of 29 APS II patients without IDDM, respectively (p < 0.05). In short-standing IDDM (< 1 year), antibodies to GAD67 were significantly more frequent in patients with APS II (5 of 9 [55.6%] subjects) compared to matched diabetic patients without coexisting polyendocrinopathy (1 of 18 [5.6%] subjects) (p < 0.02). The levels of GAD65 (142 ± 90 AU) and GAD67 antibodies (178 ± 95 AU) were significantly higher in patients with polyglandular disease than in patients with isolated IDDM (91 ± 85 AU and 93 ± 57 AU) (p < 0.02). Interestingly, all 11 GAD67 antibody positive subjects also had GAD65 antibodies (p < 0.0001), and in 10 of 11 anti-GAD67 positive sera the GAD67 antibodies could be blocked by either GAD67 or GAD65, suggesting the presence of cross-reactive autoantibodies. No correlation was observed between GAD antibodies and age, sex or any particular associated autoimmune disease, besides IDDM. GAD antibodies were present in only 1 of 6 (16.7%) patients with APS Type I, in 1 of 26 (3.9%) patients with autoimmune thyroid disease but in none of the patients with Addison's disease (n = 16), pernicious anaemia (n = 7) or normal controls (n = 50). Our data suggest distinct antibody specificities reactive to GAD isoforms in APS II and IDDM, which might reflect different mechanisms of autoimmune response in IDDM with coexisting autoimmune polyendocrine autoimmunity

Detection of autoantibodies against reactive oxygen species modified glutamic acid decarboxylase-65 in type 1 diabetes associated complications

<p>Abstract</p> <p>Background</p> <p>Autoantibodies against glutamate decarboxylase-65 (GAD₆₅Abs) are thought to be a major immunological tool involved in pathogenic autoimmunity development in various diseases. GAD₆₅Abs are a sensitive and specific marker for type 1 diabetes (T1D). These autoantibodies can also be found in 6-10% of patients classified with type 2 diabetes (T2D), as well as in 1-2% of the healthy population. The latter individuals are at low risk of developing T1D because the prevalence rate of GAD₆₅Abs is only about 0.3%. It has, therefore, been suggested that the antibody binding to GAD₆₅in these three different GAD₆₅Ab-positive phenotypes differ with respect to epitope specificity. The specificity of reactive oxygen species modified GAD₆₅(ROS-GAD₆₅) is already well established in the T1D. However, its association in secondary complications of T1D has not yet been ascertained. Hence this study focuses on identification of autoantibodies against ROS-GAD₆₅(ROS-GAD₆₅Abs) and quantitative assays in T1D associated complications.</p> <p>Results</p> <p>From the cohort of samples, serum autoantibodies from T1D retinopathic and nephropathic patients showed high recognition of ROS-GAD₆₅as compared to native GAD₆₅(N-GAD₆₅). Uncomplicated T1D subjects also exhibited reactivity towards ROS-GAD₆₅. However, this was found to be less as compared to the binding recorded from complicated subjects. These results were further proven by competitive ELISA estimations. The apparent association constants (AAC) indicate greater affinity of IgG from retinopathic T1D patients (1.90 × 10^-6M) followed by nephropathic (1.81 × 10^-6M) and uncomplicated (3.11 × 10^-7M) T1D patients for ROS-GAD₆₅compared to N-GAD₆₅.</p> <p>Conclusion</p> <p>Increased oxidative stress and blood glucose levels with extended duration of disease in complicated T1D could be responsible for the gradual formation and/or exposing cryptic epitopes on GAD₆₅that induce increased production of ROS-GAD₆₅Abs. Hence regulation of ROS-GAD₆₅Abs could offer novel tools for analysing and possibly treating T1D complications.</p

Safety and Feasibility of Thoracic Malignancy Surgery During the COVID-19 Pandemic

Background: The coronavirus disease 2019 (COVID-19) pandemic has decreased surgical activity, particularly in the field of oncology, because of the suspicion of a higher risk of COVID-19–related severe events. This study aimed to investigate the feasibility and safety of thoracic cancer surgery in the most severely affected European and Canadian regions during the COVID-19 pandemic. Methods: The study investigators prospectively collected data on surgical procedures for malignant thoracic diseases from January 1 to April 30, 2020. The study included patients from 6 high-volume thoracic surgery departments: Nancy and Strasbourg (France), Freiburg (Germany), Milan and Turin (Italy), and Montreal (Canada). The centers involved in this research are all located in the most severely affected regions of those countries. An assessment of COVID-19–related symptoms, polymerase chain reaction (PCR)–confirmed COVID-19 infection, rates of hospital and intensive care unit admissions, and death was performed for each patient. Every deceased patient was tested for COVID-19 by PCR. Results: In the study period, 731 patients who underwent 734 surgical procedures were included. In the whole cohort, 9 cases (1.2%) of COVID-19 were confirmed by PCR, including 5 in-hospital contaminants. Four patients (0.5%) needed readmission for oxygen requirements. In this subgroup, 2 patients (0.3%) needed intensive care unit and mechanical ventilatory support. The total number of deaths in the whole cohort was 22 (3%). A single death was related to COVID-19 (0.14%). Conclusions: Maintaining surgical oncologic activity in the era of the COVID-19 pandemic seems safe and feasible, with very low postoperative morbidity or mortality. To continue to offer the best care to patients who do not have COVID-19, reports on other diseases are urgently needed

A cloud-based enhanced differential evolution algorithm for parameter estimation problems in computational systems biology

This is a post-peer-review, pre-copyedit version of an article published in Cluster Computing. The final authenticated version is available online at: https://doi.org/10.1007/s10586-017-0860-1[Abstract] Metaheuristics are gaining increasing recognition in many research areas, computational systems biology among them. Recent advances in metaheuristics can be helpful in locating the vicinity of the global solution in reasonable computation times, with Differential Evolution (DE) being one of the most popular methods. However, for most realistic applications, DE still requires excessive computation times. With the advent of Cloud Computing effortless access to large number of distributed resources has become more feasible, and new distributed frameworks, like Spark, have been developed to deal with large scale computations on commodity clusters and cloud resources. In this paper we propose a parallel implementation of an enhanced DE using Spark. The proposal drastically reduces the execution time, by means of including a selected local search and exploiting the available distributed resources. The performance of the proposal has been thoroughly assessed using challenging parameter estimation problems from the domain of computational systems biology. Two different platforms have been used for the evaluation, a local cluster and the Microsoft Azure public cloud. Additionally, it has been also compared with other parallel approaches, another cloud-based solution (a MapReduce implementation) and a traditional HPC solution (a MPI implementation)Ministerio de Economía y Competitividad; DPI2014-55276-C5-2-RMinisterio de Economía y Competitividad; TIN2013-42148-PMinisterio de Economía y Competitividad; TIN2016-75845-PXunta de Galicia ; R2016/045Xunta de Galicia; GRC2013/05

An iterative identification procedure for dynamic modeling of biochemical networks

<p>Abstract</p> <p>Background</p> <p>Mathematical models provide abstract representations of the information gained from experimental observations on the structure and function of a particular biological system. Conferring a predictive character on a given mathematical formulation often relies on determining a number of non-measurable parameters that largely condition the model's response. These parameters can be identified by fitting the model to experimental data. However, this fit can only be accomplished when identifiability can be guaranteed.</p> <p>Results</p> <p>We propose a novel iterative identification procedure for detecting and dealing with the lack of identifiability. The procedure involves the following steps: 1) performing a structural identifiability analysis to detect identifiable parameters; 2) globally ranking the parameters to assist in the selection of the most relevant parameters; 3) calibrating the model using global optimization methods; 4) conducting a practical identifiability analysis consisting of two (<it>a priori </it>and <it>a posteriori</it>) phases aimed at evaluating the quality of given experimental designs and of the parameter estimates, respectively and 5) optimal experimental design so as to compute the scheme of experiments that maximizes the quality and quantity of information for fitting the model.</p> <p>Conclusions</p> <p>The presented procedure was used to iteratively identify a mathematical model that describes the NF-<it>κ</it>B regulatory module involving several unknown parameters. We demonstrated the lack of identifiability of the model under typical experimental conditions and computed optimal dynamic experiments that largely improved identifiability properties.</p

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

Signaling pathways play a key role in complex diseases such as cancer, for which the development of novel therapies is a difficult, expensive and laborious task. Computational models that can predict the effect of a new combination of drugs without having to test it experimentally can help in accelerating this process. In particular, network-based dynamic models of these pathways hold promise to both understand and predict the effect of therapeutics. However, their use is currently hampered by limitations in our knowledge of the underlying biochemistry, as well as in the experimental and computational technologies used for calibrating the models. Thus, the results from such models need to be carefully interpreted and used in order to avoid biased predictions. Here we present a procedure that deals with this uncertainty by using experimental data to build an ensemble of dynamic models. The method incorporates steps to reduce overfitting and maximize predictive capability. We find that by combining the outputs of individual models in an ensemble it is possible to obtain a more robust prediction. We report results obtained with this method, which we call SELDOM (enSEmbLe of Dynamic lOgic-based Models), showing that it improves the predictions previously reported for several challenging problems.JRB and DH acknowledge funding from the EU FP7 project NICHE (ITN Grant number 289384). JRB acknowledges funding from the Spanish MINECO project SYNBIOFACTORY (grant number DPI2014-55276-C5-2-R). AFV acknowledges funding from the Galician government (Xunta de Galiza) through the I2C postdoctoral fellowship ED481B2014/133-0. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Efficacy and Safety of Lacosamide in Painful Diabetic Neuropathy

OBJECTIVE: To evaluate efficacy and safety of lacosamide compared with placebo in painful diabetic polyneuropathy. RESEARCH DESIGN AND METHODS: Diabetic patients with at least moderate neuropathic pain were randomized to placebo or lacosamide 400 (in a slow or standard titration) or 600 mg/day over 6-week titration and 12-week maintenance periods. Primary efficacy criterion was intra-individual change in average daily Numeric Pain Rating Scale score from baseline to the last 4 weeks. RESULTS: For the primary end point, pain reduction was numerically but not statistically greater with lacosamide compared with placebo (400 mg/day, P = 0.12; 600 mg/day, P = 0.18). Both doses were significantly more effective compared with placebo over the titration (P = 0.03, P = 0.006), maintenance (P = 0.01, P = 0.005), and entire treatment periods (P = 0.03, P = 0.02). Safety profiles between titration schemes were similar. CONCLUSIONS: Lacosamide reduced neuropathic pain and was well tolerated in diabetic patients, but the primary efficacy criterion was not met, possibly due to an increased placebo response over the last 4 weeks.status: publishe