Molecular Simulation of Covalent Adaptable Networks and Vitrimers: A Review.

Covalent adaptable networks and vitrimers are novel polymers with dynamic reversible bond exchange reactions for crosslinks, enabling them to modulate their properties between those of thermoplastics and thermosets. They have been gathering interest as materials for their recycling and self-healing properties. In this review, we discuss different molecular simulation efforts that have been used over the last decade to investigate and understand the nanoscale and molecular behaviors of covalent adaptable networks and vitrimers. In particular, molecular dynamics, Monte Carlo, and a hybrid of molecular dynamics and Monte Carlo approaches have been used to model the dynamic bond exchange reaction, which is the main mechanism of interest since it controls both the mechanical and rheological behaviors. The molecular simulation techniques presented yield sufficient results to investigate the structure and dynamics as well as the mechanical and rheological responses of such dynamic networks. The benefits of each method have been highlighted. The use of other tools such as theoretical models and machine learning has been included. We noticed, amongst the most prominent results, that stress relaxes as the bond exchange reaction happens, and that at temperatures higher than the glass transition temperature, the self-healing properties are better since more bond BERs are observed. The lifetime of dynamic covalent crosslinks follows, at moderate to high temperatures, an Arrhenius-like temperature dependence. We note the modeling of certain properties like the melt viscosity with glass transition temperature and the topology freezing transition temperature according to a behavior ruled by either the Williams-Landel-Ferry equation or the Arrhenius equation. Discrepancies between the behavior in dissociative and associative covalent adaptable networks are discussed. We conclude by stating which material parameters and atomistic factors, at the nanoscale, have not yet been taken into account and are lacking in the current literature.

Unique Method for Facile Postsynthetic Modification of Nonisocyanate Polyurethanes.

Nonisocyanate polyurethanes (NIPUs) are broadly investigated as a potential replacement for conventional polyurethanes (PUs) to eliminate the use of toxic isocyanates and reduce occupational hazards. One of the most popular approaches to NIPU synthesis is the polyaddition of cyclic bis(carbonate)s and diamines to form poly(hydroxyurethane)s (PHUs). However, such PHUs are highly hydrophilic due to the presence of two hydroxyl groups per repeat unit, and the resulting moisture absorption significantly degrades their thermomechanical performance and physical stability upon exposure to humidity, thus limiting their utility. Here, we introduce a simple and scalable approach for the modification of PHUs to increase hydrophobicity and adjust their properties. The proposed reaction between aldehydes and appropriately spaced hydroxyl groups in the polymer backbone resulted in high degrees of modification (up to 84%) and up to 3-fold reductions in water uptake at 85% RH. Furthermore, the use of aromatic aldehydes in particular enabled the retention of mechanical properties over a wide range of humidity levels, resulting in performance comparable to conventional PUs. Finally, we note that this approach is not limited to reducing moisture sensitivity alone and provides ample opportunities for imparting a broad range of novel properties to PHUs through an appropriate selection of functional aldehydes.

Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies.

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures.

BACKGROUND: Cirrus is an automated risk predictor for breast cancer that comprises texture-based mammographic features and is mostly independent of mammographic density. We investigated genetic and environmental variance of variation in Cirrus. METHODS: We measured Cirrus for 3,195 breast cancer-free participants, including 527 pairs of monozygotic (MZ) twins, 271 pairs of dizygotic (DZ) twins, and 1,599 siblings of twins. Multivariate normal models were used to estimate the variance and familial correlations of age-adjusted Cirrus as a function of age. The classic twin model was expanded to allow the shared environment effects to differ by zygosity. The SNP-based heritability was estimated for a subset of 2,356 participants. RESULTS: There was no evidence that the variance or familial correlations depended on age. The familial correlations were 0.52 (SE, 0.03) for MZ pairs and 0.16(SE, 0.03) for DZ and non-twin sister pairs combined. Shared environmental factors specific to MZ pairs accounted for 20% of the variance. Additive genetic factors accounted for 32% (SE = 5%) of the variance, consistent with the SNP-based heritability of 36% (SE = 16%). CONCLUSION: Cirrus is substantially familial due to genetic factors and an influence of shared environmental factors that was evident for MZ twin pairs only. The latter could be due to nongenetic factors operating in utero or in early life that are shared by MZ twins. IMPACT: Early-life factors, shared more by MZ pairs than DZ/non-twin sister pairs, could play a role in the variation in Cirrus, consistent with early life being recognized as a critical window of vulnerability to breast carcinogens.

Does the 11-year solar cycle affect lake and river ice phenology?

Records of ice-on and ice-off dates are available for lakes and rivers across the Northern Hemisphere spanning decades and in some cases centuries. This data provides an opportunity to investigate the climatic processes that may control ice phenology. Previous studies have reported a trend toward shorter ice-covered seasons with global warming, as well as links between ice phenology and several modes of natural climate variability such as the North Atlantic Oscillation, the Pacific-North American Pattern, the El Niño-Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation. The 11-year sunspot cycle has also been proposed as a driver of ice phenology, which is somewhat surprising given that this cycle's strongest impacts are in the stratosphere. In this study, we use a large data set of lakes and rivers across the Northern Hemisphere to test this potential link. We find little or no connection between the sunspot cycle and either ice-on or ice-off dates. We conclude that while many well-known climate cycles do impact ice phenology, we are able to rule out any strong impact of the solar cycle.

Causal relationships between breast cancer risk factors based on mammographic features.

BACKGROUND: Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. METHODS: We used digitised mammograms for 371 monozygotic twin pairs, aged 40-70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. RESULTS: The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22-0.81; all P < 0.005). We estimated that 28-92% of the associations between the risk scores could be attributed to causal relationships between the scores, with the rest attributed to familial confounders shared by the scores. There was consistent evidence for positive causal effects: of Cirrus, light areas, and bright areas on the brightest areas (accounting for 34%, 55%, and 85% of the associations, respectively); and of light areas and bright areas on Cirrus (accounting for 37% and 28%, respectively). CONCLUSIONS: In a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas, including through a causal pathway via textural features. These causal relationships help us gain insight into the relative aetiological importance of different mammographic features in breast cancer. For example our findings are consistent with the brightest areas being more aetiologically important than lighter areas for screen-detected breast cancer; conversely, light areas being more aetiologically important for interval breast cancer. Additionally, specific textural features capture aetiologically independent breast cancer risk information from dense areas. These findings highlight the utility of ICE FALCON and family data in decomposing the associations between intercorrelated disease biomarkers into distinct biological pathways.

Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks.

BACKGROUND: The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered. DEVELOPMENT: We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID's building block is variance in risk, Δ2, where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ2). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher's classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors. APPLICATION: For female breast cancer, VALID quantified how much variance in risk is explained-at different ages-by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors. CONCLUSION: VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk.

A New Method to Prepare Stable Polyaniline Dispersions for Highly Loaded Cathodes of All-Polymer Li-Ion Batteries.

A new method for the preparation of polyaniline (PANI) films that have a 2D structure and can record high active mass loading (up to 30 mg cm-2) via acid-assisted polymerization in the presence of concentrated formic acid was developed. This new approach represents a simple reaction pathway that proceeds quickly at room temperature in quantitative isolated yield with the absence of any byproducts and leads to the formation of a stable suspension that can be stored for a prolonged time without sedimentation. The observed stability was explained by two factors: (a) the small size of the obtained rod-like particles (50 nm) and (b) the change of the surface of colloidal PANI particles to a positively charged form by protonation with concentrated formic acid. The films cast from the concentrated suspension were composed of amorphous PANI chains assembled into 2D structures with nanofibrillar morphology. Such PANI films demonstrated fast and efficient diffusion of the ions in liquid electrolyte and showed a pair of revisable oxidation and reduction peaks in cyclic voltammetry. Furthermore, owing to the high mass loading, specific morphology, and porosity, the synthesized polyaniline film was impregnated by a single-ion conducting polyelectrolyte-poly(LiMn-r-PEGMm) and characterized as a novel lightweight all-polymeric cathode material for solid-state Li batteries by cyclic voltammetry and electrochemical impedance spectroscopy techniques.

Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci.

BACKGROUND: DEPendency of association on the number of Top Hits (DEPTH) is an approach to identify candidate susceptibility regions by considering the risk signals from overlapping groups of sequential variants across the genome. METHODS: We applied a DEPTH analysis using a sliding window of 200 SNPs to colorectal cancer data from the Colon Cancer Family Registry (CCFR; 5,735 cases and 3,688 controls), and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO; 8,865 cases and 10,285 controls) studies. A DEPTH score > 1 was used to identify candidate susceptibility regions common to both analyses. We compared DEPTH results against those from conventional genome-wide association study (GWAS) analyses of these two studies as well as against 132 published susceptibility regions. RESULTS: Initial DEPTH analysis revealed 2,622 (CCFR) and 3,686 (GECCO) candidate susceptibility regions, of which 569 were common to both studies. Bootstrapping revealed 40 and 49 candidate susceptibility regions in the CCFR and GECCO data sets, respectively. Notably, DEPTH identified at least 82 regions that would not be detected using conventional GWAS methods, nor had they been identified by previous colorectal cancer GWASs. We found four reproducible candidate susceptibility regions (2q22.2, 2q33.1, 6p21.32, 13q14.3). The highest DEPTH scores were in the human leukocyte antigen locus at 6p21 where the strongest associated SNPs were rs762216297, rs149490268, rs114741460, and rs199707618 for the CCFR data, and rs9270761 for the GECCO data. CONCLUSIONS: DEPTH can identify candidate susceptibility regions for colorectal cancer not identified using conventional analyses of larger datasets. IMPACT: DEPTH has potential as a powerful complementary tool to conventional GWAS analyses for discovering susceptibility regions within the genome.

Mechanically Robust Poly(ionic liquid) Block Copolymers as Self-Assembling Gating Materials for Single-Walled Carbon-Nanotube-Based Thin-Film Transistors.

The proliferation of high-performance thin-film electronics depends on the development of highly conductive solid-state polymeric materials. We report on the synthesis and properties investigation of well-defined cationic and anionic poly(ionic liquid) AB-C type block copolymers, where the AB block was formed by random copolymerization of highly conductive anionic or cationic monomers with poly(ethylene glycol) methyl ether methacrylate, while the C block was obtained by post-polymerization of 2-phenylethyl methacrylate. The resulting ionic block copolymers were found to self-assemble into a lamellar morphology, exhibiting high ionic conductivity (up to 3.6 × 10-6 S cm-1 at 25 °C) and sufficient electrochemical stability (up to 3.4 V vs Ag+/Ag at 25 °C) as well as enhanced viscoelastic (mechanical) performance (storage modulus up to 3.8 × 105 Pa). The polymers were then tested as separators in two all-solid-state electrochemical devices: parallel plate metal-insulator-metal (MIM) capacitors and thin-film transistors (TFTs). The laboratory-scale truly solid-state MIM capacitors showed the start of electrical double-layer (EDL) formation at ∼103 Hz and high areal capacitance (up to 17.2 µF cm-2). For solid-state TFTs, low hysteresis was observed at 10 Hz due to the completion of EDL formation and the devices were found to have low threshold voltages of -0.3 and 1.1 V for p-type and n-type operations, respectively.

ADMANI: Annotated Digital Mammograms and Associated Non-Image Datasets.

Supplemental material is available for this article. Keywords: Mammography, Screening, Convolutional Neural Network (CNN) Published under a CC BY 4.0 license. See also the commentary by Cadrin-Chênevert in this issue.

Improved Neurophysiological Process Imaging Through Optimization of Kalman Filter Initial Conditions.

Recent work presented a framework for space-time-resolved neurophysiological process imaging that augments existing electromagnetic source imaging techniques. In particular, a nonlinear Analytic Kalman filter (AKF) has been developed to efficiently infer the states and parameters of neural mass models believed to underlie the generation of electromagnetic source currents. Unfortunately, as the initialization determines the performance of the Kalman filter, and the ground truth is typically unavailable for initialization, this framework might produce suboptimal results unless significant effort is spent on tuning the initialization. Notably, the relation between the initialization and overall filter performance is only given implicitly and is expensive to evaluate; implying that conventional optimization techniques, e.g. gradient or sampling based, are inapplicable. To address this problem, a novel efficient framework based on blackbox optimization has been developed to find the optimal initialization by reducing the signal prediction error. Multiple state-of-the-art optimization methods were compared and distinctively, Gaussian process optimization decreased the objective function by 82.1% and parameter estimation error by 62.5% on average with the simulation data compared to no optimization applied. The framework took only 1.6[Formula: see text]h and reduced the objective function by an average of 13.2% on 3.75[Formula: see text]min 4714-source channel magnetoencephalography data. This yields an improved method of neurophysiological process imaging that can be used to uncover complex underpinnings of brain dynamics.

4D Printing of Electroactive Triple-Shape Composites.

Triple-shape polymers can memorize two independent shapes during a controlled recovery process. This work reports the 4D printing of electro-active triple-shape composites based on thermoplastic blends. Composite blends comprising polyester urethane (PEU), polylactic acid (PLA), and multiwall carbon nanotubes (MWCNTs) as conductive fillers were prepared by conventional melt processing methods. Morphological analysis of the composites revealed a phase separated morphology with aggregates of MWCNTs uniformly dispersed in the blend. Thermal analysis showed two different transition temperatures based on the melting point of the crystallizable switching domain of the PEU (Tm~50 ± 1 °C) and the glass transition temperature of amorphous PLA (Tg~61 ± 1 °C). The composites were suitable for 3D printing by fused filament fabrication (FFF). 3D models based on single or multiple materials were printed to demonstrate and quantify the triple-shape effect. The resulting parts were subjected to resistive heating by passing electric current at different voltages. The printed demonstrators were programmed by a thermo-mechanical programming procedure and the triple-shape effect was realized by increasing the voltage in a stepwise fashion. The 3D printing of such electroactive composites paves the way for more complex shapes with defined geometries and novel methods for triggering shape memory, with potential applications in space, robotics, and actuation technologies.

Solvents drive self-assembly mechanisms and inherent properties of Kraft lignin nanoparticles (<50 nm).

HYPOTHESIS: Strikingly, Kraft lignin nanoparticles (KLNPs) can substitute polluting nanoparticles in diverse applications. An attractive method for synthesizing KLNPs is Solvent shifting. We hypothesized that by a detailed understanding of the solvent properties and influence of the process parameters, one could derive new fundamental and technical information about the lignin nanoparticle formation process. EXPERIMENTS: DMSO and THF were chosen best solvents based on the Hansen solubility parameter of lignin. The four synthesis parameters such as lignin concentration, (anti-solvent) water volume, temperature, and stirring speed were used to investigate the size, polydispersity index (PDI), morphology as well as the thermal, mechanical and optical properties of KLNPsDMSO & KLNPsTHF. FINDINGS: KLNPsTHF follows the well-known nucleation and growth (NG) mechanism, resulting in spherical KLNPs (43 ± 12 nm: 0.20 PDI). Surprisingly, KLNPsDMSO follows a unique mechanism resembling spinodal decomposition (SD), which generates rare bicontinuous-to-spherical KLNPs (17 ± 8 nm: 0.20 PDI). Remarkably, we show that the difference in the KLNPs mechanism modulates their intrinsic properties, such as glass transition temperature (Tg), specific surface area (SSA), elastic modulus (EM) and optical properties. Beyond the new mechanism, our synthesis resulted in reproducible ultra-small KLNPs with an excellent % yield. Such findings have vast implications in high-performance nanocomposites.

Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?

Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene-environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10-14), ~0.6% (P = 2 × 10-7), and ~8.7% (P = 7 × 10-87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P < 0.05) were found at 61, 14, and 7 CpGs for smoking, alcohol consumption, and BMI, respectively. There was strong evidence that all lifestyle-related phenotypes were positively associated with PhenoAge and GrimAge, except for alcohol consumption with PhenoAge. There was weak evidence that the association of smoking with GrimAge was attenuated in participants genetically predisposed to smoking (interaction term: -0.022, standard error [SE] = 0.012, P = 0.058) and that the association of alcohol consumption with PhenoAge was attenuated in those genetically predisposed to drink alcohol (interaction term: -0.030, SE = 0.015, P = 0.041). In conclusion, genetic susceptibility to unhealthy lifestyles did not strongly modify the association between observed lifestyle behaviour and blood DNA methylation. Potential associations were observed for epigenetic ageing measures, which should be replicated in additional studies.

Ionic poly(dimethylsiloxane)-silica nanocomposites: Dispersion and self-healing.

Abstract: Poly(dimethylsiloxane) (PDMS)-based nanocomposites have attracted increasing attention due to their inherent outstanding properties. Nevertheless, the realization of high levels of dispersion of nanosilicas in PDMS represents a challenge arising from the poor compatibility between the two components. Herein, we explore the use of ionic interactions located at the interface between silica and a PDMS matrix by combining anionic sulfonate-functionalized silica and cationic ammonium-functionalized PDMS. A library of ionic PDMS nanocomposites was synthesized and characterized to highlight the impact of charge location, density, and molecular weight of ionic PDMS polymers on the dispersion of nanosilicas and the resulting mechanical reinforcement. The use of reversible ionic interactions at the interface of nanoparticles-polymer matrix enables the healing of scratches applied to the surface of the nanocomposites. Molecular dynamics simulations were used to estimate the survival probability of ionic cross-links between nanoparticles and the polymer matrix, revealing a dependence on polymer charge density. Impact statement: Poly(dimethylsiloxane) (PDMS) has been widely used in diverse applications due to its inherent attractive and multifunctional properties including optical transparency, high flexibility, and biocompatibility. The combination of such properties in a single polymer matrix has paved the way toward a wide range of applications in sensors, electronics, and biomedical devices. As a liquid at room temperature, the cross-linking of the PDMS turns the system into a mechanically stable elastomer for several applications. Nanofillers have served as a reinforcing agent to design PDMS nanocomposites. However, due to significant incompatibility between silica and the PDMS matrix, the dispersion of nanosilica fillers has been challenging. One of the existing strategies to improve nanoparticle dispersion consists of grafting oppositely charged ionic functional groups to the nanoparticle surface and the polymer matrix, respectively, creating nanoparticle ionic materials. Here, this approach has been explored further to improve the dispersion of nanosilicas in a PDMS matrix. The designed ionic PDMS nanocomposites exhibit self-healing properties due to the reversible nature of ionic interactions. The developed synthetic approach can be transferred to other kinds of inorganic nanoparticles dispersed in a PDMS matrix, where dispersion at the nanometer scale is a prerequisite for specific applications such as encapsulants for light-emitting diodes (LEDs). Supplementary information: The online version contains supplementary material available at 10.1557/s43577-022-00346-x.

Smoking Methylation Marks for Prediction of Urothelial Cancer Risk.

BACKGROUND: Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction. METHODS: Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case-control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC). RESULTS: The meta-analysis identified associations (P < 4.7 × 10-5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00-1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91-1.30). CONCLUSIONS: Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets. IMPACT: DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.

Reinforcement of Styrene Butadiene Rubber Employing Poly(isobornyl methacrylate) (PIBOMA) as High Tg Thermoplastic Polymer.

A set of poly(isobornyl methacrylate)s (PIBOMA) having molar mass in the range of 26,000-283,000 g mol-1 was prepared either via RAFT process or using free radical polymerization. These linear polymers demonstrated high glass transition temperatures (Tg up to 201 °C) and thermal stability (Tonset up to 230 °C). They were further applied as reinforcing agents in the preparation of the vulcanized rubber compositions based on poly(styrene butadiene rubber) (SBR). The influence of the PIBOMA content and molar mass on the cure characteristics, rheological and mechanical properties of rubber compounds were studied in detail. Moving die rheometry revealed that all rubber compounds filled with PIBOMA demonstrated higher torque increase values ΔS in comparison with rubber compositions without filler, independent of PIBOMA content or molar mass, thus confirming its reinforcing effect. Reinforcement via PIBOMA addition was also observed for vulcanized rubbers in the viscoelastic region and the rubbery plateau, i.e. from -20 to 180 °C, by dynamic mechanical thermal analysis. Notably, while at temperatures above ~125 °C, ultra-high-molecular-weight polyethylene (UHMWPE) rapidly loses its ability to provide reinforcement due to softening/melting, all PIBOMA resins maintained their ability to reinforce rubber matrix up to 180 °C. For rubber compositions containing 20 phr of PIBOMA, both tensile strength and elongation at break decreased with increasing PIBOMA molecular weight. In summary, PIBOMA, with its outstanding high Tg among known poly(methacrylates), may be used in the preparation of advanced high-stiffness rubber compositions, where it provides reinforcement above 120 °C and gives properties appropriate for a range of applications.

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study.

Background: We previously investigated the association between 5 "first-generation" measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods: We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results: We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions: The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

Rheological characterization, compression, and injection molding of hydroxyapatite-silk fibroin composites.

Traditional bone fixation devices made from inert metal alloys provide structural strength for bone repair but are limited in their ability to actively promote bone healing. Although several naturally derived bioactive materials have been developed to promote ossification in bone defects, it is difficult to translate small-scale benchtop fabrication of these materials to high-output manufacturing. Standard industrial molding processes, such as injection and compression molding, have typically been limited to use with synthetic polymers since most biopolymers cannot withstand the harsh processing conditions involved in these techniques. Here we demonstrate injection and compression molding of a bioceramic composite comprised of hydroxyapatite (HA) and silk fibroin (SF) from Bombyx mori silkworm cocoons. Both the molding behavior of the HA-SF slurry and final scaffold mechanics can be controlled by modulating SF protein molecular weight, SF content, and powder-to-liquid ratio. HA-SF composites with up to 20 weight percent SF were successfully molded into stable three-dimensional structures using high pressure molding techniques. The unique durability of silk fibroin enables application of common molding techniques to fabricate composite silk-ceramic scaffolds. This work demonstrates the potential to move bone tissue engineering one step closer to large-scale manufacturing of natural protein-based resorbable bone grafts and fixation devices.