Structural hierarchies define toughness and defect-tolerance despite simple and mechanically inferior brittle building blocks

Mineralized biological materials such as bone, sea sponges or diatoms provide load-bearing and armor functions and universally feature structural hierarchies from nano to macro. Here we report a systematic investigation of the effect of hierarchical structures on toughness and defect-tolerance based on a single and mechanically inferior brittle base material, silica, using a bottom-up approach rooted in atomistic modeling. Our analysis reveals drastic changes in the material crack-propagation resistance (R-curve) solely due to the introduction of hierarchical structures that also result in a vastly increased toughness and defect-tolerance, enabling stable crack propagation over an extensive range of crack sizes. Over a range of up to four hierarchy levels, we find an exponential increase in the defect-tolerance approaching hundred micrometers without introducing additional mechanisms or materials. This presents a significant departure from the defect-tolerance of the base material, silica, which is brittle and highly sensitive even to extremely small nanometer-scale defects

hTERT promoter activity and CpG methylation in HPV-induced carcinogenesis

<p>Abstract</p> <p>Background</p> <p>Activation of telomerase resulting from deregulated hTERT expression is a key event during high-risk human papillomavirus (hrHPV)-induced cervical carcinogenesis. In the present study we examined hTERT promoter activity and its relation to DNA methylation as one of the potential mechanisms underlying deregulated hTERT transcription in hrHPV-transformed cells.</p> <p>Methods</p> <p>Using luciferase reporter assays we analyzed hTERT promoter activity in primary keratinocytes, HPV16- and HPV18-immortalized keratinocyte cell lines and cervical cancer cell lines. In the same cells as well as cervical specimens we determined hTERT methylation by bisulfite sequencing analysis of the region spanning -442 to +566 (relative to the ATG) and quantitative methylation specific PCR (qMSP) analysis of two regions flanking the hTERT core promoter.</p> <p>Results</p> <p>We found that in most telomerase positive cells increased hTERT core promoter activity coincided with increased hTERT mRNA expression. On the other hand basal hTERT promoter activity was also detected in telomerase negative cells with no or strongly reduced hTERT mRNA expression levels. In both telomerase positive and negative cells regulatory sequences flanking both ends of the core promoter markedly repressed exogenous promoter activity.</p> <p>By extensive bisulfite sequencing a strong increase in CpG methylation was detected in hTERT positive cells compared to cells with no or strongly reduced hTERT expression. Subsequent qMSP analysis of a larger set of cervical tissue specimens revealed methylation of both regions analyzed in 100% of cervical carcinomas and 38% of the high-grade precursor lesions, compared to 9% of low grade precursor lesions and 5% of normal controls.</p> <p>Conclusions</p> <p>Methylation of transcriptionally repressive sequences in the hTERT promoter and proximal exonic sequences is correlated to deregulated hTERT transcription in HPV-immortalized cells and cervical cancer cells. The detection of DNA methylation at these repressive regions may provide an attractive biomarker for early detection of cervical cancer.</p

The Effects of Age on Inflammatory and Coagulation-Fibrinolysis Response in Patients Hospitalized for Pneumonia

Objective: To determine whether inflammatory and hemostasis response in patients hospitalized for pneumonia varies by age and whether these differences explain higher mortality in the elderly. Methods: In an observational cohort of subjects with community-acquired pneumonia (CAP) recruited from emergency departments (ED) in 28 hospitals, we divided subjects into 5 age groups (85% subjects, older subjects had modestly increased hemostasis markers and IL-6 levels (p,0.01). Conclusions: Modest age-related increases in coagulation response occur during hospitalization for CAP; however these differences do not explain the large differences in mortality. Despite clinical recovery, immune resolution may be delayed in older adults at discharge. © 2010 Kale et al

How to Appropriately Extrapolate Costs and Utilities in Cost-Effectiveness Analysis

Costs and utilities are key inputs into any cost-effectiveness analysis. Their estimates are typically derived from individual patient-level data collected as part of clinical studies the follow-up duration of which is often too short to allow a robust quantification of the likely costs and benefits a technology will yield over the patient’s entire lifetime. In the absence of long-term data, some form of temporal extrapolation—to project short-term evidence over a longer time horizon—is required. Temporal extrapolation inevitably involves assumptions regarding the behaviour of the quantities of interest beyond the time horizon supported by the clinical evidence. Unfortunately, the implications for decisions made on the basis of evidence derived following this practice and the degree of uncertainty surrounding the validity of any assumptions made are often not fully appreciated. The issue is compounded by the absence of methodological guidance concerning the extrapolation of non-time-to-event outcomes such as costs and utilities. This paper considers current approaches to predict long-term costs and utilities, highlights some of the challenges with the existing methods, and provides recommendations for future applications. It finds that, typically, economic evaluation models employ a simplistic approach to temporal extrapolation of costs and utilities. For instance, their parameters (e.g. mean) are typically assumed to be homogeneous with respect to both time and patients’ characteristics. Furthermore, costs and utilities have often been modelled to follow the dynamics of the associated time-to-event outcomes. However, cost and utility estimates may be more nuanced, and it is important to ensure extrapolation is carried out appropriately for these parameters

Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma

Correction to: Nature Communications; https://doi.org/10.1038/s41467-018-04989-w, published online 13 September 2018