Molecular analysis of VP4, VP7, and NSP4 genes of P[6]G2 rotavirus genotype strains recovered from neonates admitted to hospital in Belém, Brazil

This investigation describes the molecular characterization of P[6]G2 rotavirus strains from hospitalized neonates with community-acquired diarrhea (CAD), nosocomial diarrhea (ND), and asymptomatic nosocomial infection (ANI) in Belém, Brazil. Twenty-six rotavirus strains with P[6]G2 genotype were sequenced to genes coding for VP4, VP7, and NSP4 proteins. Phylogenetic analysis of the VP4 gene, including prototype strains RV3, ST3, M37, and U1205, showed that local P[6]G2 strains clustered forming a distinct lineage (bootstrap of 99%). Brazilian P[6]G2 strains had the highest homology (ranging from 96.0%-98.3%) with the African strain GR1107, G4P[6]. Phylogenetic tree for VP7 gene was constructed including old and new G2 African strains SA3958GR/97, SA356PT/96, SA514GR/87, SA4476PT/97, BF3676/99, GH1803/99, and representative strains of G1, G3, G4, G5, G8, and G9 genotypes. The Brazilian P[6]G2 samples fell into a distinct group (bootstrap value of 97%) and showed homology rates ranging from 92.1% to 93.5% with P[6]G2 African strains BF3676/99, GH1803/99, and SA3958GR/97. Nucleotide sequence analysis of the NSP4 gene, including human prototype strains S2, KUN, DS-1, RV5, RV3 and ST3, and animal prototype OSU, showed that all neonatal isolates fell into genotype A and clustered with a bootstrap value of 100%, with in-group similarities ranging from 99.3% to 100%. In this study no significant differences in nucleotide sequences of the VP4, VP7, and NSP4 genes could be observed when comparing diarrheic (CAD and ND) and non-diarrheic (ANI) babies. Monitoring of rotavirus strains in hospital environments is of particular importance, since it is claimed currently that an efficacious rotavirus vaccine, when available for routine use, will determine an impact on hospital-acquired rotavirus disease.     

Different regions of the class P-III snake venom metalloproteinase jararhagin are involved in binding to α2β1 integrin and collagen

SVMPs are multi-domain proteolytic enzymes in which disintegrin-like and cysteine-rich domains bind to cell receptors, plasma or ECM proteins. We have recently reported that jararhagin, a P-III class SVMP, binds to collagen with high affinity through an epitope located within the Da-disintegrin sub-domain. In this study, we evaluated the binding of jararhagin to α₂β₁ integrin (collagen receptor) using monoclonal antibodies and recombinant jararhagin fragments. In solid phase assays, binding of jararhagin to α₂β₁ integrin was detectable from concentrations of 20 nM. Using recombinant fragments of jararhagin, only fragment JC76 (residues 344-421), showed a significant binding to recombinant α₂β₁ integrin. The anti-jararhagin monoclonal antibody MAJar 3 efficiently neutralised binding of jararhagin to collagen, but not to recombinant α₂β₁ integrin nor to cell-surface-exposed α₂β₁ integrin (α₂-K562 transfected cells and platelets). The same antibody neutralised collagen-induced platelet aggregation. Our data suggest that jararhagin binding to collagen and α₂β₁ integrin occurs by two independent motifs, which are located on disintegrin-like and cysteine-rich domains, respectively. Moreover, toxin binding to collagen appears to be sufficient to inhibit collagen-induced platelet aggregation.     

Auriculo-condylar syndrome: mapping of a first locus and evidence for genetic heterogeneity

Auriculo-condylar syndrome (ACS), an autosomal dominant disorder of first and second pharyngeal arches, is characterized by malformed ears ('question mark ears'), prominent cheeks, microstomia, abnormal temporomandibular joint, and mandibular condyle hypoplasia. Penetrance seems to be complete, but there is high inter- and intra-familial phenotypic variation, with no evidence of genetic heterogeneity. We herein describe a new multigeneration family with 11 affected individuals (F1), in whom we confirm intra-familial clinical variability. Facial asymmetry, a clinical feature not highlighted in other ACS reports, was highly prevalent among the patients reported here. The gene responsible for ACS is still unknown and its identification will certainly contribute to the understanding of human craniofacial development. No chromosomal rearrangements have been associated with ACS, thus mapping and positional cloning is the best approach to identify this disease gene. To map the ACS gene, we conducted linkage analysis in two large ACS families, F1 and F2 (F2; reported elsewhere). Through segregation analysis, we first excluded three known loci associated with disorders of first and second pharyngeal arches (Treacher Collins syndrome, oculo-auriculo-vertebral spectrum, and Townes-Brocks syndrome). Next, we performed a wide genome search and we observed evidence of linkage to 1p21.1-q23.3 in F2 (LOD max 3.01 at theta=0). Interestingly, this locus was not linked to the phenotype segregating in F1. Therefore, our results led to the mapping of a first locus of ACS (ACS1) and also showed evidence for genetic heterogeneity, suggesting that there are at least two loci responsible for this phenotype.     

Effects of THBS3, SPARC and SPP1 expression on biological behavior and survival in patients with osteosarcoma

Background  

Osteosarcoma is a very aggressive tumor with a propensity to metastasize and invade surrounding tissue. Identification of the molecular determinants of invasion and metastatic potential may guide the development of a rational strategy for devising specific therapies that target the pathways leading to osteosarcoma.     

Novel 6p rearrangements and recurrent translocation breakpoints in retinoblastoma cell lines identified by spectral karyotyping and mBAND analyses

Gain of the short arm of chromosome 6, usually through isochromosome 6p formation, is present in approximately 50% of retinoblastoma tumors. The minimal region of gain maps to chromosome band 6p22. Two genes, DEK and E2F3, are implicated as candidate oncogenes. However, chromosomal translocations have been overlooked as a potential mechanism of activation of oncogenes at 6p22 in retinoblastoma. Here, we report combined spectral karyotyping), 4',6-diamidino-2-phenylindole banding, mBAND, and locus-specific fluorescence in situ hybridization analyses of four retinoblastoma cell lines, RB1021, RB247c, RB383, and Y79. In RB1021 and RB247c, 6p undergoes structural rearrangements involving a common translocation breakpoint at 6p22. These data imply that 6p translocations may represent another mechanism of activation of 6p oncogene(s) in a subset of retinoblastomas, besides the copy number increase. In addition to 6p22, other recurrent translocation breakpoints identified in this study are 4p16, 11p15, 17q21.3, and 20q13. Common regions of gain map to chromosomal arms 1q, 2p, 6p, 17q, and 21q.     

Immune-inflammatory,coagulation, adhesion,and imaging biomarkers combined in machine learning models improve the prediction of death 1 year after ischemic stroke

Some clinical, imaging, and laboratory biomarkers have been identified as predictors of prognosis of acute ischemic stroke (IS). The aim of this study was to evaluate the prognostic validity of a combination of clinical, imaging, and laboratory biomarkers in predicting 1-year mortality of IS. We evaluated 103 patients with IS within 24 h of their hospital admission and assessed demographic data, IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT), and degree of stenosis, as well as laboratory variables including immune-inflammatory, coagulation, and endothelial dysfunction biomarkers. The IS patients were categorized as survivors and non-survivors 1 year after admission. Non-survivors showed higher NIHSS and cIMT values, lower antithrombin, Protein C, platelet counts, and albumin, and higher Factor VIII, von Willebrand Factor (vWF), white blood cells, tumor necrosis factor (TNF)-α, interleukin (IL)-10, high-sensitivity C-reactive protein (hsCRP), and vascular cellular adhesion molecule 1 (VCAM-1) than survivors. Neural network models separated non-survivors from survivors using NIHSS, cIMT, age, IL-6, TNF-α, hsCRP, Protein C, Protein S, vWF, and platelet endothelial cell adhesion molecule 1 (PECAM-1) with an area under the receiving operating characteristics curve (AUC/ROC) of 0.975, cross-validated accuracy of 93.3%, sensitivity of 100% and specificity of 85.7%. In conclusion, imaging, immune-inflammatory, and coagulation biomarkers add predictive information to the NIHSS clinical score and these biomarkers in combination may act as predictors of 1-year mortality after IS. An early prediction of IS outcome is important for personalized therapeutic strategies that may improve the outcome of IS.

     

Signal pathway involved in the development of hypoxic preconditioning in rat hepatocytes

Ischemic preconditioning improves liver resistance to hypoxia and reduces reperfusion injury following transplantation. However, the intracellular signals that mediate the development of liver hypoxic preconditioning are largely unknown. We have investigated the signal pathway leading to preconditioning in freshly isolated rat hepatocytes. Hepatocytes were preconditioned by 10-minute incubation under hypoxic conditions followed by 10 minutes of reoxygenation and subsequently exposed to 90 minutes of hypoxia. Preconditioning reduced hepatocyte killing by hypoxia by about 35%. A similar protection was also obtained by preincubation with chloro-adenosine or with A(2A)-adenosine receptor agonist CGS21680, whereas A(1)-adenosine receptor agonist N-phenyl-isopropyladenosine (R-PIA) was inactive. Conversely, the development of preconditioning was blocked by A(2)-receptor antagonist 3,7-dimethyl-1-propargylxanthine (DMPX), but not by A(1)-receptor antagonist 8-cyclopenthyl-1, 3-dipropylxanthine (DPCPX). In either preconditioned or CGS21680-treated hepatocytes a selective activation of delta and epsilon protein kinase C (PKC) isoforms was also evident. Inhibition of heterotrimeric G(i) protein or of phospholypase C by, respectively, pertussis toxin or U73122, prevented PKC activation as well as the development of preconditioning. MEK inhibitor PD98509 did not interfere with preconditioning that was instead blocked by p38 MAP kinase inhibitor SB203580. The direct activation of p38 MAPK by anisomycin A mimicked the protection against hypoxic injury given by preconditioning. Consistently, an increased phosphorylation of p38 MAPK was observed in preconditioned or CGS21680-treated hepatocytes, and this effect was abolished by PKC-blocker, chelerythrine. We propose that a signal pathway involving A(2A)-adenosine receptors, G(i)-proteins, phospholypase C, delta- and epsilon-PKCs, and p38 MAPK, is responsible for the development of liver ischemic preconditioning.     

Rasch Model of the COVID-19 Symptom Checklist—A Psychometric Validation Study

While self-reported Coronavirus Disease 2019 (COVID-19) symptom checklists have been extensively used during the pandemic, they have not been sufficiently validated from a psychometric perspective. We, therefore, used advanced psychometric modelling to explore the construct validity and internal consistency of an online self-reported COVID-19 symptom checklist and suggested adaptations where necessary. Fit to the Rasch model was examined in a sample of 1638 Austrian citizens who completed the checklist on up to 20 days during a lockdown. The items’ fatigue’, ‘headache’ and ‘sneezing’ had the highest likelihood to be affirmed. The longitudinal application of the symptom checklist increased the fit to the Rasch model. The item ‘cough’ showed a significant misfit to the fundamental measurement model and an additional dependency to ‘dry cough/no sputum production’. Several personal factors, such as gender, age group, educational status, COVID-19 test status, comorbidities, immunosuppressive medication, pregnancy and pollen allergy led to systematic differences in the patterns of how symptoms were affirmed. Raw scores’ adjustments ranged from ±0.01 to ±0.25 on the metric scales (0 to 10). Except for some basic adaptations that increases the scale’s construct validity and internal consistency, the present analysis supports the combination of items. More accurate item wordings co-created with laypersons would lead to a common understanding of what is meant by a specific symptom. Adjustments for personal factors and comorbidities would allow for better clinical interpretations of self-reported symptom data.