Unique sequence features of the Human Adenovirus 31 complete genomic sequence are conserved in clinical isolates

<p>Abstract</p> <p>Background</p> <p>Human adenoviruses (HAdV) are causing a broad spectrum of diseases. One of the most severe forms of adenovirus infection is a disseminated disease resulting in significant morbidity and mortality. Several reports in recent years have identified HAdV-31 from species A (HAdV-A31) as a cause of disseminated disease in children following haematopoetic stem cell transplantation (hSCT) and liver transplantation. We sequenced and analyzed the complete genome of the HAdV-A31 prototype strain to uncover unique sequence motifs associated with its high virulence. Moreover, we sequenced coding regions known to be essential for tropism and virulence (early transcription units E1A, E3, E4, the fiber knob and the penton base) of HAdV-A31 clinical isolates from patients with disseminated disease.</p> <p>Results</p> <p>The genome size of HAdV-A31 is 33763 base pairs (bp) in length with a GC content of 46.36%. Nucleotide alignment to the closely related HAdV-A12 revealed an overall homology of 84.2%. The genome organization into early, intermediate and late regions is similar to HAdV-A12. Sequence analysis of the prototype strain showed unique sequence features such as an immunoglobulin-like domain in the species A specific gene product E3 CR1 beta and a potentially integrin binding RGD motif in the C-terminal region of the protein IX. These features were conserved in all analyzed clinical isolates. Overall, amino acid sequences of clinical isolates were highly conserved compared to the prototype (99.2 to 100%), but a synonymous/non synonymous ratio (S/N) of 2.36 in E3 CR1 beta suggested positive selection.</p> <p>Conclusion</p> <p>Unique sequence features of HAdV-A31 may enhance its ability to escape the host's immune surveillance and may facilitate a promiscuous tropism for various tissues. Moderate evolution of clinical isolates did not indicate the emergence of new HAdV-A31 subtypes in the recent years.</p

Herbicide-Resistant Field Crops

This chapter reviews information about how crop plants resist herbicides and how resistance is selected for in plants and surveys specific herbicide-resistant crops by chemical family. The discussion in the chapter includes HRCs derived from both traditional and biotechnological selection methodologies. Plants avoid the effects of herbicides they encounter by several different mechanisms. These mechanisms can be grouped into two categories: those that exclude the herbicide molecule from the site in the plant where they induce the toxic response and those that render the specific site of herbicide action resistant to the chemical. The chapter presents herbicide-resistant crops by the herbicide chemical family—such as, triazine, acetolactate synthatase, acetyl-CoA carboxylase, glyphosate, bromoxynil, phenoxycarboxylic acids, and glufosinate. Resistant crops are listed in the chapter regardless of whether they have been commercialized or were developed for experimental purposes only, and are provided regardless of their “success” as resistant plants

Tripeptidyl Peptidase II Is Required for c-MYC–Induced Centriole Overduplication and a Novel Therapeutic Target in c-MYC–Associated Neoplasms

Centrosome aberrations are frequently detected in c-MYC–associated human malignancies. Here, we show that c-MYC–induced centrosome and centriole overduplication critically depend on the protease tripeptidyl peptidase II (TPPII). We found that TPPII localizes to centrosomes and that overexpression of TPPII, similar to c-MYC, can disrupt centriole duplication control and cause centriole multiplication, a process during which maternal centrioles nucleate the formation of more than a single daughter centriole. We report that inactivation of TPPII using chemical inhibitors or siRNA-mediated protein knockdown effectively reduced c-MYC–induced centriole overduplication. Remarkably, the potent and selective TPPII inhibitor butabindide not only potently suppressed centriole aberrations but also caused significant cell death and growth suppression in aggressive human Burkitt lymphoma cells with c-MYC overexpression. Taken together, these results highlight the role of TPPII in c-MYC–induced centriole overduplication and encourage further studies to explore TPPII as a novel antineoplastic drug target

Variation across operating sites in urinary and sexual outcomes after radical prostatectomy in localized and locally advanced prostate cancer

Purpose The extent of variation in urinary and sexual functional outcomes after radical prostatectomy (RPE) between prostate cancer (PC) operating sites remains unknown. Therefore, this analysis aims to compare casemix-adjusted functional outcomes (EPIC-26 scores incontinence, irritative/obstructive function and sexual function) between operating sites 12 months after RPE. Materials and methods Analysis of a cohort of 7065 men treated with RPE at 88 operating sites (prostate cancer centers, PCCs) between 2016 and 2019. Patients completed EPIC-26 and sociodemographic information surveys at baseline and 12 months after RPE. Survey data were linked to clinical data. EPIC-26 domain scores at 12 months after RPE were adjusted for relevant confounders (including baseline domain score, clinical and sociodemographic information) using regression analysis. Differences between sites were described using minimal important differences (MIDs) and interquartile ranges (IQR). The effects of casemix adjustment on the score results were described using Cohen's d and MIDs. Results Adjusted domain scores at 12 months varied between sites, with IQRs of 66-78 (incontinence), 89-92 (irritative/obstructive function), and 20-29 (sexual function). Changes in domain scores after casemix adjustment for sites >= 1 MID were noted for the incontinence domain (six sites). Cohen's d ranged between - 0.07 (incontinence) and - 0.2 (sexual function), indicating a small to medium effect of casemix adjustment. Conclusions Variation between sites was greatest in the incontinence and sexual function domains for RPE patients. Future research will need to identify the factors contributing to this variation

Optimal Investment in Learning-Curve Technologies

We study optimal investment in technologies characterized by the learning curve. There are two investment patterns depending on the shape of the learning curve. If the learning process is slow, firms invest relatively late and on a larger scale. If the curve is steep, firms invest earlier and on a smaller scale. We further demonstrate that learning investment differs greatly from investment in technologies without learning effects. Learning investments generate substantial initial losses and are very sensitive to downside risk. We show that the most susceptible to losses and risk are technologies with intermediate speed of learning