31 resultados para R. Thomas George
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
BACKGROUND There is an urgent need for preclinical models of prostate cancer; however, clinically relevant patient-derived prostate cancer xenografts (PDXs) are demanding to establish. METHODS Sixty-seven patients who were undergoing palliative transurethral surgery or radical prostatectomy for histologically confirmed, clinically relevant prostate cancer were included in the study. Fresh prostate cancer tissue was identified by frozen analysis in 48 patients. The cancer tissue was transplanted subcutaneously and under the renal capsule of NSG and NOG mice supplemented with human testosterone. All growing PDXs were evaluated by histology and immunohistochemistry. RESULTS Early assessment of the animals at least three months after transplantation included 27/48 (56.3%) eligible PDX cohorts. PDX growth was detected in 10/27 (37%) mouse cohorts. Eight of the ten PDXs were identified as human donor derived lymphomas, including seven Epstein Barr virus (EBV)-positive diffuse large B-cell lymphomas and one EBV-negative peripheral T-cell lymphoma. One sample consisted of benign prostatic tissue, and one sample comprised a benign epithelial cyst. Prostate cancer was not detected in any of the samples. CONCLUSIONS Tumors that arise within the first three months after prostate cancer xenografting may represent patient-derived EBV-positive lymphomas in up to 80% of the early growing PDXs when using triple knockout NSG immunocompromised mice. Therefore, lymphoma should be excluded in prostate cancer xenografts that do not resemble typical prostatic adenocarcinoma. Prostate 9999: XX-XX, 2014. © 2015 Wiley Periodicals, Inc.
Resumo:
OBJECTIVES To report on trends of tuberculosis ascertainment among HIV patients in a rural HIV cohort in Tanzania, and assessing the impact of a bundle of services implemented in December 2012, consisting of three components:(i)integration of HIV and tuberculosis services; (ii)GeneXpert for tuberculosis diagnosis; and (iii)electronic data collection. DESIGN Retrospective cohort study of patients enrolled in the Kilombero Ulanga Antiretroviral Cohort (KIULARCO), Tanzania.). METHODS HIV patients without prior history of tuberculosis enrolled in the KIULARCO cohort between 2005 and 2013 were included.Cox proportional hazard models were used to estimate rates and predictors of tuberculosis ascertainment. RESULTS Of 7114 HIV positive patients enrolled, 5123(72%) had no history of tuberculosis. Of these, 66% were female, median age was 38 years, median baseline CD4+ cell count was 243 cells/µl, and 43% had WHO clinical stage 3 or 4. During follow-up, 421 incident tuberculosis cases were notified with an estimated incidence of 3.6 per 100 person-years(p-y)[95% confidence interval(CI)3.26-3.97]. The incidence rate varied over time and increased significantly from 2.96 to 43.98 cases per 100 p-y after the introduction of the bundle of services in December 2012. Four independent predictors of tuberculosis ascertainment were identified:poor clinical condition at baseline (Hazard Ratio (HR) 3.89, 95% CI 2.87-5.28), WHO clinical stage 3 or 4 (HR 2.48, 95% CI 1.88-3.26), being antiretroviralnaïve (HR 2.97, 95% CI 2.25-3.94), and registration in 2013(HR 6.07, 95% CI 4.39-8.38). CONCLUSION The integration of tuberculosis and HIV services together with comprehensive electronic data collection and use of GeneXpert increased dramatically the ascertainment of tuberculosis in this rural African HIV cohort.
Resumo:
Leopard Complex spotting occurs in several breeds of horses and is caused by an incompletely dominant allele (LP). Homozygosity for LP is also associated with congenital stationary night blindness (CSNB) in Appaloosa horses. Previously, LP was mapped to a 6 cm region on ECA1 containing the candidate gene TRPM1 (Transient Receptor Potential Cation Channel, Subfamily M, Member 1) and decreased expression of this gene, measured by qRT-PCR, was identified as the likely cause of both spotting and ocular phenotypes. This study describes investigations for a mutation causing or associated with the Leopard Complex and CSNB phenotype in horses. Re-sequencing of the gene and associated splice sites within the 105 624 bp genomic region of TRPM1 led to the discovery of 18 SNPs. Most of the SNPs did not have a predictive value for the presence of LP. However, one SNP (ECA1:108,249,293 C>T) found within intron 11 had a strong (P < 0.0005), but not complete, association with LP and CSNB and thus is a good marker but unlikely to be causative. To further localize the association, 70 SNPs spanning over two Mb including the TRPM1 gene were genotyped in 192 horses from three different breeds segregating for LP. A single 173 kb haplotype associated with LP and CSNB (ECA1: 108,197,355- 108,370,150) was identified. Illumina sequencing of 300 kb surrounding this haplotype revealed 57 SNP variants. Based on their localization within expressed sequences or regions of high sequence conservation across mammals, six of these SNPs were considered to be the most likely candidate mutations. While the precise function of TRPM1 remains to be elucidated, this work solidifies its functional role in both pigmentation and night vision. Further, this work has identified several potential regulatory elements of the TRPM1 gene that should be investigated further in this and other species.
Resumo:
The Janzen–Connell hypothesis proposes that specialized herbivores maintain high numbers of tree species in tropical forests by restricting adult recruitment so that host populations remain at low densities. We tested this prediction for the large timber tree species, Swietenia macrophylla, whose seeds and seedlings are preyed upon by small mammals and a host-specific moth caterpillar Steniscadia poliophaea, respectively. At a primary forest site, experimental seed additions to gaps – canopy-disturbed areas that enhance seedling growth into saplings – over three years revealed lower survival and seedling recruitment closer to conspecific trees and in higher basal area neighborhoods, as well as reduced subsequent seedling survival and height growth. When we included these Janzen–Connell effects in a spatially explicit individual-based population model, the caterpillar's impact was critical to limiting Swietenia's adult tree density, with a > 10-fold reduction estimated at 300 years. Our research demonstrates the crucial but oft-ignored linkage between Janzen–Connell effects on offspring and population-level consequences for a long-lived, potentially dominant tree species.
Resumo:
OBJECTIVE To illustrate an approach to compare CD4 cell count and HIV-RNA monitoring strategies in HIV-positive individuals on antiretroviral therapy (ART). DESIGN Prospective studies of HIV-positive individuals in Europe and the USA in the HIV-CAUSAL Collaboration and The Center for AIDS Research Network of Integrated Clinical Systems. METHODS Antiretroviral-naive individuals who initiated ART and became virologically suppressed within 12 months were followed from the date of suppression. We compared 3 CD4 cell count and HIV-RNA monitoring strategies: once every (1) 3 ± 1 months, (2) 6 ± 1 months, and (3) 9-12 ± 1 months. We used inverse-probability weighted models to compare these strategies with respect to clinical, immunologic, and virologic outcomes. RESULTS In 39,029 eligible individuals, there were 265 deaths and 690 AIDS-defining illnesses or deaths. Compared with the 3-month strategy, the mortality hazard ratios (95% CIs) were 0.86 (0.42 to 1.78) for the 6 months and 0.82 (0.46 to 1.47) for the 9-12 month strategy. The respective 18-month risk ratios (95% CIs) of virologic failure (RNA >200) were 0.74 (0.46 to 1.19) and 2.35 (1.56 to 3.54) and 18-month mean CD4 differences (95% CIs) were -5.3 (-18.6 to 7.9) and -31.7 (-52.0 to -11.3). The estimates for the 2-year risk of AIDS-defining illness or death were similar across strategies. CONCLUSIONS Our findings suggest that monitoring frequency of virologically suppressed individuals can be decreased from every 3 months to every 6, 9, or 12 months with respect to clinical outcomes. Because effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.