Despite the increasing evidence of human papillomavirus (HPV) vertical transmission, this route is regarded as less clinically important because of the detections of transient HPV DNA. However, recent studies have provided clear evidence of papillomavirus productive infection in lymphocytes, placenta, and bovine fetal tissue. Furthermore, a model of papillomavirus latency has been recently proposed that could explain the failure or transience in HPV detection observed in some infected infants. This new evidence of hematogeneous and vertical spread of HPV suggests that these modes of transmission should be investigated in greater detail to obtain a better understanding of the infection and a fuller awareness of the preventive measures that can be taken against HPV-related diseases.

The aim of this study was to evaluate the presence of different types of Bovine papillomavirus (BPV) in cattle skin lesions and to identify new viral types in Brazil. A total of 72 skin lesions were analysed from 66 different bovines by PCR using degenerate and specific primers, and subsequent sequencing. Sequencing quality was determined using Staden package with Phred 30. Similarity analysis was performed with BioEdit and BLAST programs to verify the identity with known BPV types. Phylogenetic analysis was carried out using Maximum Likelihood method with TIM3 + G as nucleotide substitution model in PAUP*, and 1000 non-parametric bootstrap replicates. Analyses revealed the presence of ten different types of BPV in the samples, with the exception of BPV7. The presence of co-infections was very high as almost all samples (89%) were co-infected. A putative new BPV11 subtype was also found in lesions from different animals. These results add significant knowledge about the prevalence and diversity of BPV infection in Brazilian cattle, which could be used in future studies aiming at the development of more specific treatment and diagnostic methods.

This paper examines the predictability of COVID-19 worldwide lethality considering 43 countries. Based on the values inherent to Permutation entropy (Hs) and Fisher information measure (Fs), we apply the Shannon-Fisher causality plane (SFCP), which allows us to quantify the disorder an evaluate randomness present in the time series of daily death cases related to COVID-19 in each country. We also use Hs and Fs to rank the COVID-19 lethality in these countries based on the complexity hierarchy. Our results suggest that the most proactive countries implemented measures such as facemasks, social distancing, quarantine, massive population testing, and hygienic (sanitary) orientations to limit the impacts of COVID-19, which implied lower entropy (higher predictability) to the COVID-19 lethality. In contrast, the most reactive countries implementing these measures depicted higher entropy (lower predictability) to the COVID-19 lethality. Given this, our findings shed light that these preventive measures are efficient to combat the COVID-19 lethality.