Causes of variation in BCG vaccine efficacy: examining evidence from the BCG REVAC cluster randomized trial to explore the masking and the blocking hypotheses.

BCG protection varies and in some places (nearest the equator) is low or absent. Understanding this variation can inform the efforts to develop new vaccines against tuberculosis. Two main hypotheses are used to explain this variation: under masking, new vaccines are unlikely to increase protection; under blocking new vaccines have a greater potential to be effective when BCG is not. We conducted a cluster randomized trial to explored the masking and blocking hypotheses by studying BCG vaccine efficacy of neonatal vaccination and when administered for the first or a second (revaccination) time at school age in two sites (Manaus close and Salvador further south from the equator). Seven hundred and sixty three state schools were matched on socio economic characteristics of the neighborhood and 239,934 children were randomized to vaccine (BCG vaccination at school age) or control group. Protection by first BCG vaccination at school age was high in Salvador (34%, 95% CI 7-53%, p=0.017) but low in Manaus (8%, 95% CI t0 39-40%, p=0.686). For revaccination at school age, protection was modest in Salvador (19%, 95% CI 3-33%, p=0.022) and absent in Manaus (1%, 95% CI to 27-23%, p=0.932). Vaccine efficacy for neonatal vaccination was similar in Salvador (40%, 95% CI 22-54%, p<0.001) and Manaus (36%, 95% CI 11-53%, p=0.008). Variation in BCG efficacy was marked when vaccine was given at school age but absent at birth, which points towards blocking as the dominant mechanism. New tuberculosis vaccines that overcome or by pass this blocking effect could confer protection in situations where BCG is not protective

What if we decided to take care of everyone who needed treatment? Workforce planning in Mozambique using simulation of demand for HIV/AIDS care

Background: The growing AIDS epidemic in southern Africa is placing an increased strain on health systems, which are experiencing steadily rising patient loads. Health care systems are tackling the barriers to serving large populations in scaled-up operations. One of the most significant challenges in this effort is securing the health care workforce to deliver care in settings where the manpower is already in short supply. Methods: We have produced a demand-driven staffing model using simple spreadsheet technology, based on treatment protocols for HIV-positive patients that adhere to Mozambican guidelines. The model can be adjusted for the volumes of patients at differing stages of their disease, varying provider productivity, proportion who are pregnant, attrition rates, and other variables. Results: Our model projects the need for health workers using three different kinds of goals: 1) the number of patients to be placed on anti-retroviral therapy (ART), 2) the number of HIV-positive patients to be enrolled for treatment, and 3) the number of patients to be enrolled in a treatment facility per month. Conclusion: We propose three scenarios, depending on numbers of patients enrolled. In the first scenario, we start with 8000 patients on ART and increase that number to 58 000 at the end of three years (those were the goals for the country of Mozambique). This would require thirteen clinicians and just over ten nurses by the end of the first year, and 67 clinicians and 47 nurses at the end of the third year. In a second scenario, we start with 34 000 patients enrolled for care (not all of them on ART), and increase to 94 000 by the end of the third year, requiring a growth in clinician staff from 18 to 28. In a third scenario, we start a new clinic and enrol 200 new patients per month for three years, requiring 1.2 clinicians in year 1 and 2.2 by the end of year 3. Other clinician types in the model include nurses, social workers, pharmacists, phlebotomists, and peer counsellors. This planning tool could lead to more realistic and appropriate estimates of workforce levels required to provide high-quality HIV care in a low-resource settings

Expression of recombinant Araraquara Hantavirus nucleoprotein in insect cells and its use as an antigen for immunodetection compared to the same antigen expressed in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>Antigens for Hantavirus serological tests have been produced using DNA recombinant technology for more than twenty years. Several different strategies have been used for that purpose. All of them avoid the risks and difficulties involved in multiplying Hantavirus in the laboratory. In Brazil, the Araraquara virus is one of the main causes of Hantavirus Cardio-Pulmonary Syndrome (HCPS).</p> <p>Methods</p> <p>In this investigation, we report the expression of the N protein of the Araraquara Hantavirus in a Baculovirus Expression System, the use of this protein in IgM and IgG ELISA and comparison with the same antigen generated in <it>E. coli</it>.</p> <p>Results</p> <p>The protein obtained, and purified in a nickel column, was effectively recognized by antibodies from confirmed HCPS patients. Comparison of the baculovirus generated antigen with the N protein produced in <it>E. coli </it>showed that both were equally effective in terms of sensitivity and specificity.</p> <p>Conclusions</p> <p>Our results therefore indicate that either of these proteins can be used in serological tests in Brazil.</p

Identification of Dmrt2a downstream genes during zebrafish early development using a timely controlled approach

This research was supported by FCT (Portugal) grant (PTDC/SAU-BID/119627/2010) given to L.S. L.S. was supported by an IF contract from FCT (Portugal). R.A.P. was supported by a PhD fellowship (SFRH/BD/87607/2012) from FCT (Portugal). Publication was sponsored by LISBOA-01-0145-FEDER-007391, project co-funded by FEDER through POR Lisboa 2020 - Programa Operacional Regional de Lisboa, PORTUGAL 2020 and by Fundacao para a Ciencia e a Tecnologia.BACKGROUND: Dmrt2a is a zinc finger like transcription factor with several roles during zebrafish early development: left-right asymmetry, synchronisation of the somite clock genes and fast muscle differentiation. Despite the described functions, Dmrt2a mechanism of action is unknown. Therefore, with this work, we propose to identify Dmrt2a downstream genes during zebrafish early development. RESULTS: We generated and validated a heat-shock inducible transgenic line, to timely control dmrt2a overexpression, and dmrt2a mutant lines. We characterised dmrt2a overexpression phenotype and verified that it was very similar to the one described after knockdown of this gene, with left-right asymmetry defects and desynchronisation of somite clock genes. Additionally, we identified a new phenotype of somite border malformation. We generated several dmrt2a mutant lines, but we only detected a weak to negligible phenotype. As dmrt2a has a paralog gene, dmrt2b, with similar functions and expression pattern, we evaluated the possibility of redundancy. We found that dmrt2b does not seem to compensate the lack of dmrt2a. Furthermore, we took advantage of one of our mutant lines to confirm dmrt2a morpholino specificity, which was previously shown to be a robust knockdown tool in two independent studies. Using the described genetic tools to perform and validate a microarray, we were able to identify six genes downstream of Dmrt2a: foxj1b, pxdc1b, cxcl12b, etv2, foxc1b and cyp1a. CONCLUSIONS: In this work, we generated and validated several genetic tools for dmrt2a and identified six genes downstream of this transcription factor. The identified genes will be crucial to the future understanding of Dmrt2a mechanism of action in zebrafish.publishersversionpublishe

Characterisation of Human Embryonic Stem Cells Conditioning Media by 1H-Nuclear Magnetic Resonance Spectroscopy

BACKGROUND: Cell culture media conditioned by human foreskin fibroblasts (HFFs) provide a complex supplement of protein and metabolic factors that support in vitro proliferation of human embryonic stem cells (hESCs). However, the conditioning process is variable with different media batches often exhibiting differing capacities to maintain hESCs in culture. While recent studies have examined the protein complement of conditioned culture media, detailed information regarding the metabolic component of this media is lacking. METHODOLOGY/PRINCIPAL FINDINGS: Using a (1)H-Nuclear Magnetic Resonance ((1)H-NMR) metabonomics approach, 32 metabolites and small compounds were identified and quantified in media conditioned by passage 11 HFFs (CMp11). A number of metabolites were secreted by HFFs with significantly higher concentration of lactate, alanine, and formate detected in CMp11 compared to non-conditioned media. In contrast, levels of tryptophan, folate and niacinamide were depleted in CMp11 indicating the utilisation of these metabolites by HFFs. Multivariate statistical analysis of the (1)H-NMR data revealed marked age-related differences in the metabolic profile of CMp11 collected from HFFs every 24 h over 72 h. Additionally, the metabolic profile of CMp11 was altered following freezing at -20°C for 2 weeks. CM derived from passage 18 HFFs (CMp18) was found to be ineffective at supporting hESCs in an undifferentiated state beyond 5 days culture. Multivariate statistical comparison of CMp11 and CMp18 metabolic profiles enabled rapid and clear discrimination between the two media with CMp18 containing lower concentrations of lactate and alanine as well as higher concentrations of glucose and glutamine. CONCLUSIONS/SIGNIFICANCE: (1)H-NMR-based metabonomics offers a rapid and accurate method of characterising hESC conditioning media and is a valuable tool for monitoring, controlling and optimising hESC culture media preparation

Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5 years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24 h urine samples were obtained by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies