A Multiscale Framework for the Characterization of Damage in Textile Composites Under Thermomechanical Loads

This work examines composite failure at multiple scales. The first scale that is examined is the fiber-matrix scale, where fibers and matrix are discretely modeled. A model is developed at this scale which includes randomness in the fiber positions. This randomness is found to significantly influence the stress field and resulting failure that occurs under thermo mechanical loads as compared to fiber-matrix microstructures with regular arrays of fibers. The fiber-matrix model is utilized to characterize variability and temperature dependence of the composite strength arising from microstructural randomness and the presence of thermally induced stresses. The second scale that is examined is that of a textile unit cell. Failure initiation behavior is examined for a variety of thermo mechanical loadings at this scale, and it is found that failure tends to initiate in a limited number of ways for a wide variety of loadings. A new progressive failure model is then examined for the textile unit cell. This model utilizes cohesive interface elements in the tows, neat matrix pockets, and tow and matrix interfaces to account for crack opening in the textile, as well as a continuum damage model to account for diffuse damage in the tows. Variability and temperature dependence of the transverse tow strength is introduced by specifying varying cohesive strengths in the intra-tow cohesive zones using a Weibull distribution characterized using the random fiber-matrix model. Progressive failure analyses are then performed for the textile unit cell under a variety of thermomechanical loads, and the resulting behaviors are compared to identify characteristic modes of damage development and their effect on the textile response. A continuum damage model for the textile material, which can be applied to engineering structures, is developed based on the characteristic damage modes observed in the textile unit cell analyses. This model tracks the evolution of each characteristic mode of damage based on the structural-scale stress and predicts the degradation in the textile response as a result of this damage. The ability of this model to predict the textile’s response under various damage-inducing loads is then compared to the response obtained from textile unit cell progressive failure analysis, and both models are found to be in good agreement for most loadings

Prediction of Damage Zone Growth in Composites Using Continuum Damage Mechanics

The continuum damage mechanics (CDM) approach is widely used to model damage in polymer matrix composite materials which are represented using the homogenized properties of the fiber and matrix constituents. CDM simplifies the problem of accounting for a large number of defects in a material by considering the homogenized effect of the defects as a change in constitutive properties of the material. However, recent investigations of textile composites have shown that CDM inaccurately predicts the direction of damage zone growth for some composite architectures which fail under shear load, tending to predict failure transverse to the fibers. This behavior is fundamentally attributable to the fact that shear failure in textiles results in large (tow-scale) matrix cracks, while CDM is intended to model distributed micro-cracks. It is shown that when CDM is used to model shear failure in anisotropic continua, material anisotropy tends to cause CDM to predict failure contrary to what is expected for these structures. An approach is presented that may allow CDM to better predict damage growth for shear failure in composites by encouraging the creation of an intial damage zone with sufficient directional bias to overcome the effect of material anisotropy

Ocular Biomarkers of Disease: Employing Routine Eye Exams to Promote Better Health Surveillance

America’s burden of vision impairment, Alzheimer’s disease and related dementias (ADRD), and cardiovascular disease will continue to rise over the next 40 years. The burden of these diseases will be greater for women, Hispanics, African-Americans, and those from lower socio-economic regions. A key challenge is to develop strategies to deny the organization of the pathologies that eventually lead to the manifestation of the disease. An important feature within this battle is the development of appropriate tools and biomarkers for early reconnaissance of the enemy. Recent advances in Optical Coherence Tomography Angiography (OCTA) present a unique opportunity to examine physiological features of the eyes that overlap with structures within the brain and heart. Specifically, tracking of the vessel density and thickness of the nerve fiber layers of the eye may provide valuable information regarding an individual’s path towards visual impairment, ADRD, and cardiovascular disease. Thus, OCTA can extend eye care beyond capturing those who are at risk for vision loss, and include examination of biomarkers which provide information concerning trajectories of cognitive and cardiovascular health. Given loss of vision is perceived as ‘the worst ailment that could happen to person’ across all ethnic and racial groups, Ophthalmologists and Optometrists can not only provide a path toward improved eye health, but also serve as an innovative access point for early detection of individuals at risk for ADRD and Cardiovascular disease

Reducing unscheduled hospital care for adults with diabetes following a hypoglycaemic event: which community-based interventions are most effective? A systematic review

AIM: To determine which community-based interventions are most effective at reducing unscheduled hospital care for hypoglycaemic events in adults with diabetes. METHODS: Medline Ovid, CINAHL Plus and ProQuest Health and Medical Collection were searched using both key search terms and medical subject heading terms (MeSH) to identify potentially relevant studies. Eligible studies were those that involved a community-based intervention to reduce unscheduled admissions in adults with diabetes. Papers were initially screened by the primary researcher and then a secondary reviewer. Relevant data were then extracted from papers that met the inclusion criteria. RESULTS: The search produced 2226 results, with 1360 duplicates. Of the remaining 866 papers, 198 were deemed appropriate based on titles, 90 were excluded following abstract review. A total of 108 full papers were screened with 19 full papers included in the review. The sample size of the 19 papers ranged from n = 25 to n = 104,000. The average ages within the studies ranged from 41 to 74 years with females comprising 57% of the participants. The following community-based interventions were identified that explored reducing unscheduled hospital care in people with diabetes; telemedicine, education, integrated care pathways, enhanced primary care and care management teams. CONCLUSIONS: This systematic review shows that a range of community-based interventions, requiring different levels of infrastructure, are effective in reducing unscheduled hospital care for hypoglycaemia in people with diabetes. Investment in effective community-based interventions such as integrated care and patient education must be a priority to shift the balance of care from secondary to primary care, thereby reducing hospital admissions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40200-021-00817-z

Direct measurements of intramolecular electron transfer rates between cytochrome c and cytochrome c peroxidase: effects of exothermicity and primary sequence on rate.

Rapid mixing of ferrocytochrome c peroxidase [cyt c peroxidase(II)] and ferricytochrome c [cyt c(III)] results in the reduction of cyt c(III) by cyt c peroxidase(II). In 10 mM phosphate, pH 7.0, the rate of decay of cyt c peroxidase(II) and the rate of accumulation of cyt c(II) give equal first-order rate constants: k = 0.23 +/- 0.02 s-1. Equivalent results are obtained by pulse radiolysis using isopropanol radical as the reducing agent. This rate is independent of the initial cyt c(III):cyt c peroxidase(II) ratios. These results are consistent with unimolecular electron transfer occurring within a cyt c(III)-cyt c peroxidase(II) complex. When cyt c is replaced by porphyrin cyt c (iron-free cyt c), a complex still forms with cyt c peroxidase. On radiolysis, using e-aq as the reducing agent, intracomplex electron transfer occurs from the porphyrin cyt c anion radical to cyt c peroxidase(III) with k = 150 s-1. This large rate increase with increasing delta G degrees suggests that the barrier for intracomplex electron transfer is large. Finally, we have briefly investigated how the cyt c peroxidase(II)----cyt c(III) rate depends on the primary structure of cyt c(III). We find the reactivity order to be as follows: yeast (k = 3.4 s-1) greater than horse (k = 0.3 s-1) greater than tuna (k = 0.2 s-1). These results mirror a report [Ho, P. S., Sutoris, C., Liang, N., Margoliash, E. & Hoffman, B. M. (1985) J. Am. Chem. Soc. 107, 1070-1071] on excited state reactions of the cyt c/cyt c peroxidase couple

Recombinant Adeno-Associated Virus Utilizes Cell-Specific Infectious Entry Mechanisms

Understanding the entry and trafficking mechanism(s) of recombinant adeno-associated virus (rAAV) into host cells can lead to evolution in capsid and vector design and delivery methods, resulting in enhanced transduction and therapeutic gene expression. Variability of findings regarding the early entry pathway of rAAV supports the possibility that rAAV, like other viruses, can utilize more than one infectious entry pathway. We tested whether inhibition of macropinocytosis impacted rAAV transduction of HeLa cells compared to hepatocellular carcinoma cell lines. We found that macropinocytosis inhibitor cytochalasin D blocked rAAV transduction of HeLa cells (>2-fold) but enhanced (10-fold) transduction in HepG2 and Huh7 lines. Similar results were obtained with another macropinocytosis inhibitor, 5-(N-ethyl-N-isopropyl) amiloride (EIPA). The augmented transduction was due to neither viral binding nor promoter activity, affected multiple rAAV serotypes (rAAV2, rAAV2-R585E, and rAAV8), and influenced single-stranded and self-complementary virions to comparable extents. Follow-up studies using CDC42 inhibitor ML141 and p21-activated kinase 1 (PAK1) siRNA knockdown also resulted in enhanced HepG2 transduction. Microscopy revealed that macropinocytosis inhibition correlated with expedited nuclear entry of the rAAV virions into HepG2 cells. Enhancement of hepatocellular rAAV transduction extended to the mouse liver in vivo (4-fold enhancement) but inversely blocked heart tissue transduction (13-fold). This evidence of host cell-specific rAAV entry pathways confers a potent means for controlling and enhancing vector delivery and could help unify the divergent accounts of rAAV cellular entry mechanisms

Relationships among plutonium contents of soil, vegetation, and animals collected on and adjacent to an integrated nuclear complex in the humid southeastern United States

Twenty-three representative sampling locations in and adjacent to the Savannah River Plant (SRP) site were selected to obtain information on Pu movement in the food chain under southeastern U. S. environmental conditions. Soil, a resuspendible fraction of the soil, honeysuckle (Lonicera japonica), and camphor weed (Heterotheca subaxillaris) were collected at each location. Grasshoppers and cotton rats (Sigmodon hispidus) were collected at some locations. The soil concentrations at the selected locations ranged from 1.5 fCi/g to 171 fCi/g, and alpha percentages of $sup 238$Pu ranged from 2 to 66. The concentration of plutonium in the vegetation and on the leaves ranged from 0.17 to 76.1 fCi/g, and the alpha percentages of $sup 238$Pu, from 3 to 61. The concentration of plutonium in cotton rats and grasshoppers ranged from 0.07 to 3.58 fCi/g, and the alpha percentages of $sup 238$Pu ranged from 22 to 80. Comparisons among the Pu values of the vegetation, soil, and resuspendible fractions suggest the use of a proposed resuspendible measurement technique as a monitoring method to indicate subtle changes in the Pu concentration of the soil surface that are not detectable by routine soil sampling. Although the $sup 238$Pu data in the various ecosystem components were not conclusive, they support evidence that there is an apparent increase in the biological availability of $sup 238$Pu relative to the $sup 239$' $sub 240$ in the environment. The Pu concentrations of ecosystem components decreased as the distance from the reprocessing plants increased. (auth

COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer

COSMIC (http://www.sanger.ac.uk/cosmic) curates comprehensive information on somatic mutations in human cancer. Release v48 (July 2010) describes over 136 000 coding mutations in almost 542 000 tumour samples; of the 18 490 genes documented, 4803 (26%) have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs (19 new cancer genes and 30 new fusion pairs this year) and this number is continually increasing. Key amongst these is TP53, now available through a collaboration with the IARC p53 database. In addition to data from the Cancer Genome Project (CGP) at the Sanger Institute, UK, and The Cancer Genome Atlas project (TCGA), large systematic screens are also now curated. Major website upgrades now make these data much more mineable, with many new selection filters and graphics. A Biomart is now available allowing more automated data mining and integration with other biological databases. Annotation of genomic features has become a significant focus; COSMIC has begun curating full-genome resequencing experiments, developing new web pages, export formats and graphics styles. With all genomic information recently updated to GRCh37, COSMIC integrates many diverse types of mutation information and is making much closer links with Ensembl and other data resources

I-TRAP: A method to identify transcriptional regulator activated promoters

BACKGROUND: The differential expression of virulence genes is often used by microbial pathogens in adapting to the environment of their host. The differential expression of such sets of genes can be regulated by RNA polymerase sigma factors. Some sigma factors are differentially expressed, which can provide a means to identifying other differentially expressed genes such as those whose expression are controlled by the sigma factor. METHODS: To identify sigma factor-regulated genes, we developed a method, termed I-TRAP, for the identification of transcriptional regulator activated promoters. The I-TRAP method is based on the fact that some genes will be differentially expressed in the presence and absence of a transcriptional regulator. I-TRAP uses a DNA library in a promoter-trap vector that contains two reporter genes, one to allow the selection of active promoters in the presence of the transcriptional regulator and a second to allow screening for promoter activity in the absence of the transcriptional regulator. RESULTS: To illustrate the development and use of the I-TRAP approach, the construction of the vectors, host strains, and library necessary to identify SigmaE-regulated genes of Mycobacterium tuberculosis is described. CONCLUSION: The I-TRAP method should be a versatile and useful method for identifying and characterizing promoter activity under a variety of conditions and in response to various regulatory proteins. In our study, we isolated 360 clones that may contain plasmids carrying SigmaE-regulated promoters genes of M. tuberculosis

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types