Evaluation in mice of the immunogenicity and protective efficacy of a tetravalent subunit vaccine candidate against dengue virus

A dengue vaccine must induce protective immunity against the four serotypes of the virus. Our group has developed chimeric proteins consisting of the protein P64k from Neisseria meningitidis and the domain III from the four viral envelope proteins. In this study, the immunogenicity of a tetravalent vaccine formulation using aluminum hydroxide as adjuvant was evaluated in mice. After three doses, neutralizing antibody titers were detected against the four viral serotypes, the lowest seroconversion rate being against dengue virus serotype 4. One month after the last dose, immunized animals were challenged with infective virus, and partial but statistically significant protection was found to have been achieved. Based on these results, further studies in mice and non‐human primates using this tetravalent formulation in a prime‐boost strategy with attenuated viruses are strongly recommended.     

Evaluation of purified recombinant spike fragments for assessment of the presence of serum neutralizing antibodies against a variant strain of porcine epidemic diarrhea virus

Since 2010, variant strains of porcine epidemic diarrhea virus(PEDV) have caused disasters in the pork industry. The spike(S) protein, as the major immunity-eliciting antigen, has previously been used for serological testing and has been found to correlate significantly with the results of the serum neutralization(SN) test. However, further evaluation of this method is needed as new epidemic strains of PEDV emerge. Hence, the main objective of this study was to assess sow sera and determine the correlation between enzyme-linked immunosorbent assay(ELISA) results(involving a newly isolated GDS01 virus-based ELISA and ELISAs based on seven recombinant fragments comprising overlapping S1 and partial S2 sequences) and SN titers. Furthermore, we determined the reliability of the ELISAs based on receiver operating characteristics(ROC) curve analyses. For the most promising ELISA, i.e., the SP4 ELISA, the correlation coefficient(r) and the area under curve(AUC) were determined to be 0.6113 and 0.8538, respectively. In addition, we analyzed the homology of the SP4 sequences obtained from different strains(including vaccine strains) and found that various strains showed a high degree of homology in this region. Thus, we conclude that SP4 is a promising serological testing protein for use in the field.     

Transition phase in the production of recombinant proteins in yeast under the ADH2 promoter: an important step for reproducible manufacturing of a malaria transmission blocking vaccine candidate

TBV25H, a malaria transmission blocking vaccine candidate, has been cloned in Saccharomyces cerevisiae under the control of the glucose repressed ADH2 promoter. Available fermentation procedures for production of this protein have been unsatisfactory, mainly because of irreproducibility. This work presents an efficient and reproducible method for the production of this vaccine candidate by implementing a three-stage fermentation process. During the first (glucose fed-batch) phase, the promoter is repressed and the culture is allowed to grow exponentially. In the second stage, the glucose supply is provided at a slower constant rate. In the third (ethanol consumption) stage, accumulated ethanol is first allowed to be consumed and an external ethanol supplement is then added as required. The promoter is fully derepressed in this phase, and TBV25H is synthesized. The period of glucose limitation was concluded to be essential for reproducibility. It is presumed that during this period, the culture moves gradually from glucose to ethanol utilization, derepressing the promoter, activating recombinant protein biosynthesis and consequently resuming metabolism without the typical diauxic phase of batch cultures. Received 21 October 1997/ Accepted in revised form 15 January 1998     

Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.