Full range of wettability through surface modification of single-wall carbon nanotubes by photo-initiated chemical vapour deposition

Single-wall carbon nanotubes (SWCNTs) have various remarkable properties, which make them a promising candidate for many applications. However, their inherent hydrophobicity has limited their commercial use in optical, biological, and electrical applications. Photo-initiated chemical vapour deposition (PICVD) using syngas is proposed as a novel, affordable, and versatile method to tailor SWCNT wettability through the addition of oxygen-containing functional groups. Following PICVD surface treatment, X-ray photoelectron spectroscopy, water contact angle measurements (CA), thermogravimetric analysis, Raman spectroscopy and transmission electron microscopy confirm controlled oxygenation of the SWCNT surface. Indeed, this novel approach allows to reproducibly make SWCNTs having surfaces properties ranging from superhydrophilic (CA 150°), including any intermediate values, by simply varying operational parameters such as molar ratio of the syngas precursor, photo-polymerization time and reactor pressure (about normal conditions)

Reaction kinetics and temperature effects in syngas photo-initiated chemical vapor deposition on single-walled carbon nanotubes

Photo-initiated chemical vapor deposition (PICVD) is a solvent-free process that can be used to produce thin films on a variety of substrates, with applications in fields ranging from biomedicine to optics and microelectronics. This study presents a kinetic analysis for this process using syngas (CO + H2) as a precursor for the surface treatment of single-walled carbon nanotubes (SWCNT) with average dimensions of 1.5 × 100 nm (diameter × length), and addresses the role of iron pentacarbonyl (Fe(CO)5), a photo-active contaminant found in CO. This work builds upon previously developed reaction schemes for PICVD, based mainly on surface characterizations, by coupling these analyses with gas-phase monitoring. This allows us to propose two separate reaction schemes for the gas and surface phase reactions and consider temperature effects. Online FTIR, offline GC-MS, and online GC characterized the gas phase, while for surface characterizations, XPS and TGA were used. Characterizations showed that a coating with a general formula of CnO3nFen was deposited, corresponding to 0.29 ± 0.04 mg carbon and 0.49 ± 0.03 mg iron on the SWCNT substrate over the course of treatment. The Fe(CO)5 was identified as the key reactant in syngas/PICVD reactions and was nearly completely consumed (94%). Mass balances derived from the gas phase characterization showed that Fe(CO)5 inputted to the plug flow reactor could potentially contribute all the amount of 0.49 ± 0.03 mg of Fe and 0.29 ± 0.04 mg of C to the coating on the SWCNT, indicating that syngas/PICVD can be optimized in the future to decrease gas throughput. Temperature did not show a significant effect in the case of PICVD. However, in the absence of ultraviolet light, its role becomes determinant, with rising temperatures causing more Fe deposition

18 F-MK-6240 tau-PET in genetic frontotemporal dementia

Tau is one of several proteins associated with frontotemporal dementia. While knowing which protein is causing a patient\u27s disease is crucial, no biomarker currently exists for identifying tau in vivo in frontotemporal dementia. The objective of this study was to investigate the potential for the promising 18F-MK-6240 PET tracer to bind to tau in vivo in genetic frontotemporal dementia. We enrolled subjects with genetic frontotemporal dementia, who constitute an ideal population for testing because their pathology is already known based on their mutation. Ten participants (three with symptomatic P301L and R406W MAPT mutations expected to show tau binding, three with presymptomatic MAPT mutations and four with non-tau mutations who acted as disease controls) underwent clinical characterization, tau-PET scanning with 18F-MK-6240, amyloid-PET imaging with 18F-NAV-4694 to rule out confounding Alzheimer\u27s pathology, and high-resolution structural MRI. Tau-PET scans of all three symptomatic MAPT carriers demonstrated at least mild 18F-MK-6240 binding in expected regions, with particularly strong binding in a subject with an R406W MAPT mutation (known to be associated with Alzheimer\u27s like neurofibrillary tangles). Two asymptomatic MAPT carriers estimated to be 5 years from disease onset both showed modest 18F-MK-6240 binding, while one ∼30 years from disease onset did not exhibit any binding. Additionally, four individuals with symptomatic frontotemporal dementia caused by a non-tau mutation were scanned (two C9orf72; one GRN; one VCP): 18F-MK-6240 scans were negative for three subjects, while one advanced C9orf72 case showed minimal regionally non-specific binding. All 10 amyloid-PET scans were negative. Furthermore, a general linear model contrasting genetic frontotemporal dementia subjects to a set of 83 age-matched controls showed significant binding only in the MAPT carriers in selected frontal, temporal and subcortical regions. In summary, our findings demonstrate mild but significant binding of MK-6240 in amyloid-negative P301L and R406W MAPT mutation subjects, with higher standardized uptake value ratio in the R406W mutation associated with the presence of NFTs, and little non-specific binding. These results highlight that a positive 18F-MK-6240 tau-PET does not necessarily imply a diagnosis of Alzheimer\u27s disease and point towards a potential use for 18F-MK-6240 as a biomarker in certain tauopathies beyond Alzheimer\u27s, although further patient recruitment and autopsy studies will be necessary to determine clinical applicability

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

Maine Won\u27t Wait One-Year Progress Report, 2021

This document, an “Maine Climate Science Update 2021”, is an interim communication to the Maine Climate Council and the public about the ongoing work of the scientific community and recent events associated with climate change. It is divided into three sections: (1) current events that reflect the acceleration of extreme weather events in Maine and elsewhere with possible connections to climate change; (2) noteworthy scientific reports with national and international scope released in 2021; and (3) examples of recent peer-reviewed publications from the ongoing work of the scientific community to understand climate change in Maine

The changing culture of silviculture

Changing climates are altering the structural and functional components of forest ecosystems at an unprecedented rate. Simultaneously, we are seeing a diversification of public expectations on the broader sustainable use of forest resources beyond timber production. As a result, the science and art of silviculture needs to adapt to these changing realities. In this piece, we argue that silviculturists are gradually shifting from the application of empirically derived silvicultural scenarios to new sets of approaches, methods and practices, a process that calls for broadening our conception of silviculture as a scientific discipline. We propose a holistic view of silviculture revolving around three key themes: observe, anticipate and adapt. In observe, we present how recent advances in remote sensing now enable silviculturists to observe forest structural, compositional and functional attributes in near-real-time, which in turn facilitates the deployment of efficient, targeted silvicultural measures in practice that are adapted to rapidly changing constraints. In anticipate, we highlight the importance of developing state-of-the-art models designed to take into account the effects of changing environmental conditions on forest growth and dynamics. In adapt, we discuss the need to provide spatially explicit guidance for the implementation of adaptive silvicultural actions that are efficient, cost-effective and socially acceptable. We conclude by presenting key steps towards the development of new tools and practical knowledge that will ensure meeting societal demands in rapidly changing environmental conditions. We classify these actions into three main categories: reexamining existing silvicultural trials to identify key stand attributes associated with the resistance and resilience of forests to multiple stressors, developing technological workflows and infrastructures to allow for continuous forest inventory updating frameworks, and implementing bold, innovative silvicultural trials in consultation with the relevant communities where a range of adaptive silvicultural strategies are tested. In this holistic perspective, silviculture can be defined as the science of observing forest condition and anticipating its development to apply tending and regeneration treatments adapted to a multiplicity of desired outcomes in rapidly changing realities

The changing culture of silviculture

Changing climates are altering the structural and functional components of forest ecosystems at an unprecedented rate. Simultaneously, we are seeing a diversification of public expectations on the broader sustainable use of forest resources beyond timber production. As a result, the science and art of silviculture needs to adapt to these changing realities. In this piece, we argue that silviculturists are gradually shifting from the application of empirically derived silvicultural scenarios to new sets of approaches, methods and practices, a process that calls for broadening our conception of silviculture as a scientific discipline. We propose a holistic view of silviculture revolving around three key themes: observe, anticipate and adapt. In observe, we present how recent advances in remote sensing now enable silviculturists to observe forest structural, compositional and functional attributes in near-real-time, which in turn facilitates the deployment of efficient, targeted silvicultural measures in practice that are adapted to rapidly changing constraints. In anticipate, we highlight the importance of developing state-of-the-art models designed to take into account the effects of changing environmental conditions on forest growth and dynamics. In adapt, we discuss the need to provide spatially explicit guidance for the implementation of adaptive silvicultural actions that are efficient, cost-effective and socially acceptable. We conclude by presenting key steps towards the development of new tools and practical knowledge that will ensure meeting societal demands in rapidly changing environmental conditions. We classify these actions into three main categories: re-examining existing silvicultural trials to identify key stand attributes associated with the resistance and resilience of forests to multiple stressors, developing technological workflows and infrastructures to allow for continuous forest inventory updating frameworks, and implementing bold, innovative silvicultural trials in consultation with the relevant communities where a range of adaptive silvicultural strategies are tested. In this holistic perspective, silviculture can be defined as the science of observing forest condition and anticipating its development to apply tending and regeneration treatments adapted to a multiplicity of desired outcomes in rapidly changing realities

A Computational Framework for Ultrastructural Mapping of Neural Circuitry

Circuitry mapping of metazoan neural systems is difficult because canonical neural regions (regions containing one or more copies of all components) are large, regional borders are uncertain, neuronal diversity is high, and potential network topologies so numerous that only anatomical ground truth can resolve them. Complete mapping of a specific network requires synaptic resolution, canonical region coverage, and robust neuronal classification. Though transmission electron microscopy (TEM) remains the optimal tool for network mapping, the process of building large serial section TEM (ssTEM) image volumes is rendered difficult by the need to precisely mosaic distorted image tiles and register distorted mosaics. Moreover, most molecular neuronal class markers are poorly compatible with optimal TEM imaging. Our objective was to build a complete framework for ultrastructural circuitry mapping. This framework combines strong TEM-compliant small molecule profiling with automated image tile mosaicking, automated slice-to-slice image registration, and gigabyte-scale image browsing for volume annotation. Specifically we show how ultrathin molecular profiling datasets and their resultant classification maps can be embedded into ssTEM datasets and how scripted acquisition tools (SerialEM), mosaicking and registration (ir-tools), and large slice viewers (MosaicBuilder, Viking) can be used to manage terabyte-scale volumes. These methods enable large-scale connectivity analyses of new and legacy data. In well-posed tasks (e.g., complete network mapping in retina), terabyte-scale image volumes that previously would require decades of assembly can now be completed in months. Perhaps more importantly, the fusion of molecular profiling, image acquisition by SerialEM, ir-tools volume assembly, and data viewers/annotators also allow ssTEM to be used as a prospective tool for discovery in nonneural systems and a practical screening methodology for neurogenetics. Finally, this framework provides a mechanism for parallelization of ssTEM imaging, volume assembly, and data analysis across an international user base, enhancing the productivity of a large cohort of electron microscopists