Component-specific modeling

Accomplishments are described for a 3 year program to develop methodology for component-specific modeling of aircraft hot section components (turbine blades, turbine vanes, and burner liners). These accomplishments include: (1) engine thermodynamic and mission models, (2) geometry model generators, (3) remeshing, (4) specialty three-dimensional inelastic structural analysis, (5) computationally efficient solvers, (6) adaptive solution strategies, (7) engine performance parameters/component response variables decomposition and synthesis, (8) integrated software architecture and development, and (9) validation cases for software developed

Tumor suppressors in chronic lymphocytic leukemia: From lost partners to active targets

Tumor suppressors play an important role in cancer pathogenesis and in the modulation of resistance to treatments. Loss of function of the proteins encoded by tumor suppressors, through genomic inactivation of the gene, disable all the controls that balance growth, survival, and apoptosis, promoting cancer transformation. Parallel to genetic impairments, tumor suppressor products may also be functionally inactivated in the absence of mutations/deletions upon post-transcriptional and post-translational modifications. Because restoring tumor suppressor functions remains the most effective and selective approach to induce apoptosis in cancer, the dissection of mechanisms of tumor suppressor inactivation is advisable in order to further augment targeted strategies. This review will summarize the role of tumor suppressors in chronic lymphocytic leukemia and attempt to describe how tumor suppressors can represent new hopes in our arsenal against chronic lymphocytic leukemia (CLL)

CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region

The first case of Coronavirus Disease 2019 in Italy was detected on February the 20th in Lombardy region. Since that date, Lombardy has been the most affected Italian region by the epidemic, and its healthcare system underwent a severe overload during the outbreak. From a public health point of view, therefore, it is fundamental to provide healthcare services with tools that can reveal possible new health system stress periods with a certain time anticipation, which is the main aim of the present study. Moreover, the sequence of law decrees to face the epidemic and the large amount of news generated in the population feelings of anxiety and suspicion. Considering this whole complex context, it is easily understandable how people "overcrowded"social media with messages dealing with the pandemic, and emergency numbers were overwhelmed by the calls. Thus, in order to find potential predictors of possible new health system overloads, we analysed data both from Twitter and emergency services comparing them to the daily infected time series at a regional level. Particularly, we performed a wavelet analysis in the time-frequency plane, to finely discriminate over time the anticipation capability of the considered potential predictors. In addition, a cross-correlation analysis has been performed to find a synthetic indicator of the time delay between the predictor and the infected time series. Our results show that Twitter data are more related to social and political dynamics, while the emergency calls trends can be further evaluated as a powerful tool to potentially forecast new stress periods. Since we analysed aggregated regional data, and taking into account also the huge geographical heterogeneity of the epidemic spread, a future perspective would be to conduct the same analysis on a more local basis. Copyright

The Long Island Breast Cancer Study Project: description of a multi-institutional collaboration to identify environmental risk factors for breast cancer

The Long Island Breast Cancer Study Project is a federally mandated, population-based case-control study to determine whether breast cancer risk among women in the counties of Nassau and Suffolk, NY, is associated with selected environmental exposures, assessed by blood samples, self-reports, and environmental home samples. This report describes the collaborative project’s background, rationale, methods, participation rates, and distributions of known risk factors for breast cancer by case-control status, by blood donation, and by availability of environmental home samples. Interview response rates among eligible cases and controls were 82.1% (n=1,508) and 62.8% (n=1,556), respectively. Among case and control respondents who completed the interviewer-administered questionnaire, 98.2 and 97.6% self-completed the food frequency questionnaire; 73.0 and 73.3% donated a blood sample; and 93.0 and 83.3% donated a urine sample. Among a random sample of case and control respondents who are long-term residents, samples of dust (83.6 and 83.0%); soil (93.5 and 89.7%); and water (94.3 and 93.9%) were collected. Established risk factors for breast cancer that were found to increase risk among Long Island women include lower parity, late age at first birth, little or no breast feeding, and family history of breast cancer. Factors that were found to be associated with a decreased likelihood that a respondent would donate blood include increasing age and past smoking; factors associated with an increased probability include white or other race, alcohol use, ever breastfed, ever use of hormone replacement therapy, ever use of oral contraceptives, and ever had a mammogram. Long-term residents (defined as 15+ years in the interview home) with environmental home samples did not differ from other long-term residents, although there were a number of differences in risk factor distributions between long-term residents and other participants, as anticipated

Bilayer-spanning DNA nanopores with voltage-switching between open and closed state.

Membrane-spanning nanopores from folded DNA are a recent example of biomimetic man-made nanostructures that can open up applications in biosensing, drug delivery, and nanofluidics. In this report, we generate a DNA nanopore based on the archetypal six-helix-bundle architecture and systematically characterize it via single-channel current recordings to address several fundamental scientific questions in this emerging field. We establish that the DNA pores exhibit two voltage-dependent conductance states. Low transmembrane voltages favor a stable high-conductance level, which corresponds to an unobstructed DNA pore. The expected inner width of the open channel is confirmed by measuring the conductance change as a function of poly(ethylene glycol) (PEG) size, whereby smaller PEGs are assumed to enter the pore. PEG sizing also clarifies that the main ion-conducting path runs through the membrane-spanning channel lumen as opposed to any proposed gap between the outer pore wall and the lipid bilayer. At higher voltages, the channel shows a main low-conductance state probably caused by electric-field-induced changes of the DNA pore in its conformation or orientation. This voltage-dependent switching between the open and closed states is observed with planar lipid bilayers as well as bilayers mounted on glass nanopipettes. These findings settle a discrepancy between two previously published conductances. By systematically exploring a large space of parameters and answering key questions, our report supports the development of DNA nanopores for nanobiotechnology.The SH lab is supported by the Leverhulme Trust (RPG-170), UCL Chemistry, EPSRC (Institutional Sponsorship Award), the National Physical Laboratory, and Oxford Nanopore Technologies. KG acknowledges funding from the Winton Program of Physics for Sustainability, Gates Cambridge and the Oppenheimer Trust. UFK was supported by an ERC starting grant #261101.This is the final version of the article. It was first published by ACS under the ACS AuthorChoice license at http://dx.doi.org/10.1021/nn5039433 This permits copying and redistribution of the article or any adaptations for non-commercial purposes

Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused an ongoing pandemic of a pathology termed Coronavirus Disease 19 (COVID-19). Several studies reported that both COVID-19 and RTEL1 variants are associated with shorter telomere length, but a direct association between the two is not generally acknowledged. Here we demonstrate that up to 8.6% of severe COVID-19 patients bear RTEL1 ultra-rare variants, and show how this subgroup can be recognized. Methods: A cohort of 2246 SARS-CoV-2-positive subjects, collected within the GEN-COVID Multicenter study, was used in this work. Whole exome sequencing analysis was performed using the NovaSeq6000 System, and machine learning methods were used for candidate gene selection of severity. A nested study, comparing severely affected patients bearing or not variants in the selected gene, was used for the characterisation of specific clinical features connected to variants in both acute and post-acute phases. Results: Our GEN-COVID cohort revealed a total of 151 patients carrying at least one RTEL1 ultra-rare variant, which was selected as a specific acute severity feature. From a clinical point of view, these patients showed higher liver function indices, as well as increased CRP and inflammatory markers, such as IL-6. Moreover, compared to control subjects, they present autoimmune disorders more frequently. Finally, their decreased diffusion lung capacity for carbon monoxide after six months of COVID-19 suggests that RTEL1 variants can contribute to the development of SARS-CoV-2-elicited lung fibrosis. Conclusion: RTEL1 ultra-rare variants can be considered as a predictive marker of COVID-19 severity, as well as a marker of pathological evolution in pulmonary fibrosis in the post-COVID phase. This notion can be used for a rapid screening in hospitalized infected people, for vaccine prioritization, and appropriate follow-up assessment for subjects at risk. Trial Registration NCT04549831 (www.clinicaltrial.org

Mechanism of KMT5B haploinsufficiency in neurodevelopment in humans and mice.

Pathogenic variants in KMT5B, a lysine methyltransferase, are associated with global developmental delay, macrocephaly, autism, and congenital anomalies (OMIM# 617788). Given the relatively recent discovery of this disorder, it has not been fully characterized. Deep phenotyping of the largest (n = 43) patient cohort to date identified that hypotonia and congenital heart defects are prominent features that were previously not associated with this syndrome. Both missense variants and putative loss-of-function variants resulted in slow growth in patient-derived cell lines. KMT5B homozygous knockout mice were smaller in size than their wild-type littermates but did not have significantly smaller brains, suggesting relative macrocephaly, also noted as a prominent clinical feature. RNA sequencing of patient lymphoblasts and Kmt5b haploinsufficient mouse brains identified differentially expressed pathways associated with nervous system development and function including axon guidance signaling. Overall, we identified additional pathogenic variants and clinical features in KMT5B-related neurodevelopmental disorder and provide insights into the molecular mechanisms of the disorder using multiple model systems