Emerging biomedical tools for biomarkers detection and diagnostics in schistosomiasis.

Schistosomiasis is a neglected disease that strikes many people from tropical and subtropical countries where there are not satisfactory sanitation and wide access to clean water. Schistosoma spp., the causative agents of schistosomiasis, exhibit a quite complex life cycle that involves two hosts (humans and snails, respectively, the definitive and the intermediate), and five evolutive forms: cercariae (human infective form), schistosomula, adult worms, eggs, and miracidia. The techniques to diagnose schistosomiasis still have various limitations, mainly regarding low-intensity infections. Although various mechanisms associated with schistosomiasis have already been evidenced, there is still a need to fulfill the comprehension of this disease, especially to prospect for novel biomarkers to improve its diagnosis. Developing methods with more sensitivity and portability to detect the infection is valuable to reach schistosomiasis control. In this context, this review has gathered information not only on schistosomiasis biomarkers but also on emerging optical and electrochemical tools proposed in selected studies from about the last ten years. Aspects of the assays regarding the sensibility, specificity, and time needed for detecting diverse biomarkers are described. We hope this review can guide future developments in the field of schistosomiasis, contributing to improving its diagnosis and eradication.

An evaluation of relational and NoSQL distributed databases on a low-power cluster.

The constant growth of social media, unconventional web technologies, mobile applications, and Internet of Things (IoT) devices create challenges for cloud data systems in order to support huge datasets and very high request rates. NoSQL databases, such as Cassandra and HBase, and relational SQL databases with replication, such as Citus/PostgreSQL, have been used to increase horizontal scalability and high availability of data store systems. In this paper, we evaluated three distributed databases on a low-power low-cost cluster of commodity Single-Board Computers (SBC): relational Citus/PostgreSQL and NoSQL databases Cassandra and HBase. The cluster has 15 Raspberry Pi 3 nodes with Docker Swarm orchestration tool for service deployment and ingress load balancing over SBCs. We believe that a low-cost SBC cluster can support cloud serving goals such as scale-out, elasticity, and high availability. Experimental results clearly demonstrated that there is a trade-off between performance and replication, which provides availability and partition tolerance. Besides, both properties are essential in the context of distributed systems with low-power boards. Cassandra attained better results with its consistency levels specified by the client. Both Citus and HBase enable consistency but it penalizes performance as the number of replicas increases.

Generalized statistics: Applications to data inverse problems with outlier-resistance.

The conventional approach to data-driven inversion framework is based on Gaussian statistics that presents serious difficulties, especially in the presence of outliers in the measurements. In this work, we present maximum likelihood estimators associated with generalized Gaussian distributions in the context of Rényi, Tsallis and Kaniadakis statistics. In this regard, we analytically analyze the outlier-resistance of each proposal through the so-called influence function. In this way, we formulate inverse problems by constructing objective functions linked to the maximum likelihood estimators. To demonstrate the robustness of the generalized methodologies, we consider an important geophysical inverse problem with high noisy data with spikes. The results reveal that the best data inversion performance occurs when the entropic index from each generalized statistic is associated with objective functions proportional to the inverse of the error amplitude. We argue that in such a limit the three approaches are resistant to outliers and are also equivalent, which suggests a lower computational cost for the inversion process due to the reduction of numerical simulations to be performed and the fast convergence of the optimization process.

Effects of 10-valent pneumococcal conjugate (PCV10) vaccination on the nasopharyngeal microbiome.

Pathogenic bacteria, such as Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae and Moraxella catarrhalis, are important vaccine targets. The 10-valent pneumococcal conjugate vaccine (PCV10) acts on 10 differents S. pneumoniae serovars. However, this vaccine could also act on other bacteria genera, leading to dysbiosis. Moreover, the vaccination has also been associated with imbalances in the ratio between commensal and potentially pathogenic bacteria. Despite the wealth of studies assessing the influence of the microbiome on vaccine effects, how vaccination can influence the microbiome remains poorly understood. Herein, we assessed the effects of PCV10 on infant nasopharyngeal microbiome composition. Nasopharyngeal aspirates were collected from children with acute respiratory infection (ARI) aged 6-23 months. Two groups were composed of 48 vaccinated and 36 unvaccinated subjects. 16S ribosomal RNA sequencing was performed to assess bacterial composition and results were analyzed with QIIME. Similar bacterial compositions were observed in the unvaccinated and vaccinated samples. Principal component analysis also indicated a similar bacterial composition between the groups. In addition, bacterial diversity was not different between the vaccinated and unvaccinated samples. Accordingly, our results suggest that PCV10 vaccination promotes a specific response against its targets, thereby preserving the nosocomial microbiome. Although not statistically significant, Streptococcus and Haemophilus genera were increased in the vaccinated group, while Moraxella was decreased. Increases in Streptococcus may be associated with vaccine-target taxa replacement by non-pathogenic species. In sum, we observed that PCV10 vaccination acts by promoting a target-specific action against pathogenic bacteria and also induces commensal bacteria colonization without substantially changing the nasopharyngeal microbiome.