Human parvovirus B19 (B19V) is a small (22–24 nm) nonenveloped DNA virus belonging to the genus Erythrovirus (family Parvoviridae). Although it gener

Zika virus (ZIKV), a mosquito-borne flavivirus, belongs to the Flaviviridae family, genus Flavivirus. ZIKV was initially isolated in 1947 from a sentinel monkey in the Zika forest, Uganda. Little clinical importance was attributed to ZIKV, once only few symptomatic cases were reported in some African and Southeast Asiatic countries. This situation changed in 2007, when a large outbreak was registered on the Yap Island, Micronesia, caused by the Asian ZIKV lineage. Between 2013 and 2014, ZIKV spread explosively and caused many outbreaks in different islands of the Southern Pacific Ocean and in 2015 autochthonous transmission was reported in Brazil. Currently, Brazil is the country with the highest number of ZIKV-positive cases in Latin America. Moreover, for the first time after the discovery of ZIKV, the Brazilian scientists are studying the possibility for the virus to cause severe congenital infection related to microcephaly and serious birth defects due to the time-spatial coincidence of the alarming increase of newborns with microcephaly and the Brazilian ZIKV epidemic. The present review summarizes recent information for ZIKV epidemiology, clinical picture, transmission, diagnosis and the consequences of this emerging virus in Brazil.

The current COVID-19 pandemic demands massive testing by Real-time RT-PCR (Reverse Transcription Polymerase Chain Reaction), which is considered the gold standard diagnostic test for the detection of the SARS-CoV-2 virus. However, the virus continues to evolve with mutations that lead to phenotypic alterations as higher transmissibility, pathogenicity or vaccine evasion. Another big issue are mutations in the annealing sites of primers and probes of RT-PCR diagnostic kits leading to false-negative results. Therefore, here we identify mutations in the N (Nucleocapsid) gene that affects the use of the GeneFinder COVID-19 Plus RealAmp Kit. We sequenced SARS-CoV-2 genomes from 17 positive samples with no N gene detection but with RDRP (RNA-dependent RNA polymerase) and E (Envelope) genes detection, and observed a set of three different mutations affecting the N detection: a deletion of 18 nucleotides (Del28877-28894), a substitution of GGG to AAC (28881-28883) and a frameshift mutation caused by deletion (Del28877-28878). The last one cause a deletion of six AAs (amino acids) located in the central intrinsic disorder region at protein level. We also found this mutation in 99 of the 14,346 sequenced samples by the Sao Paulo state Network for Pandemic Alert of Emerging SARS-CoV-2 variants, demonstrating the circulation of the mutation in Sao Paulo, Brazil. Continuous monitoring and characterization of mutations affecting the annealing sites of primers and probes by genomic surveillance programs are necessary to maintain the effectiveness of the diagnosis of COVID-19.

Wolbachia-based mosquito control strategies have gained significant attention as a sustainable approach to reduce the transmission of vector-borne diseases such as dengue, Zika, and chikungunya. These endosymbiotic bacteria can limit the ability of mosquitoes to transmit pathogens, offering a promising alternative to traditional chemical-based interventions. With the growing impact of climate change on mosquito population dynamics and disease transmission, Wolbachia interventions represent an adaptable and resilient strategy for mitigating the public health burden of vector-borne diseases. Changes in temperature, humidity, and rainfall patterns can alter mosquito breeding habitats and extend the geographical range of disease vectors, increasing the urgency for effective control measures. This review highlights innovations in Wolbachia-based mosquito control and explores future directions in the context of climate change. It emphasizes the integration of Wolbachia with other biological approaches and the need for multidisciplinary efforts to address climate-amplified disease risks. As ecosystems shift, Wolbachia interventions could be crucial in reducing mosquito-borne diseases, especially in vulnerable regions. AI integration in Wolbachia research presents opportunities to enhance mosquito control strategies by modeling ecological data, predicting mosquito dynamics, and optimizing intervention outcomes. Key areas include refining release strategies, real-time monitoring, and scaling interventions. Future opportunities lie in advancing AI-driven approaches for integrating Wolbachia with other vector control measures, promoting adaptive, data-driven responses to climate-amplified disease transmission.