Chemical Recycling of Polyethylene by Tandem Catalytic Conversion to Propylene.

Although polyethylene (PE) and polypropylene (PP) are by far the world's largest volume plastics, only a tiny fraction of these energy-rich polyolefins are currently recycled. Depolymerization of PE to its constituent monomer, ethylene, is highly endothermic and conventionally accessible only through unselective, high-temperature pyrolysis. Here, we provide experimental demonstrations of our recently proposed tandem catalysis strategy, which uses ethylene to convert PE to propylene, the commodity monomer used to make PP. The approach combines rapid olefin metathesis with rate-limiting isomerization. Monounsaturated PE is progressively disassembled at modest temperatures via many consecutive ethenolysis events, resulting selectively in propylene. Fully saturated PE can be converted to unsaturated PE starting with a single transfer dehydrogenation to ethylene, which produces a small amount of ethane (1 equiv per dehydrogenation event). These principles are demonstrated using both homogeneous and heterogeneous catalysts. While selectivity under batch conditions is limited at high conversion by the formation of an equilibrium mixture of olefins, high selectivity to propylene (≥94%) is achieved in a semicontinuous process due to the continuous removal of propylene from the reaction mixture.

Automated Measurements of Muscle Mass Using Deep Learning Can Predict Clinical Outcomes in Patients With Liver Disease.

INTRODUCTION: There is increasing recognition of the central role of muscle mass in predicting clinical outcomes in patients with liver disease. Muscle size can be extracted from computed tomography (CT) scans, but clinical implementation will require increased automation. We hypothesize that we can achieve this by using artificial intelligence. METHODS: Using deep convolutional neural networks, we trained an algorithm on the Reference Analytic Morphomics Population (n = 5,268) and validated the automated methodology in an external cohort of adult kidney donors with a noncontrast CT scan (n = 1,655). To test the clinical usefulness, we examined its ability to predict clinical outcomes in a prospectively followed cohort of patients with clinically diagnosed cirrhosis (n = 254). RESULTS: Between the manual and automated methodologies, we found excellent inter-rater agreement with an intraclass correlation coefficient of 0.957 (confidence interval 0.953-0.961, P < 0.0001) in the adult kidney donor cohort. The calculated dice similarity coefficient was 0.932 ± 0.042, suggesting excellent spatial overlap between manual and automated methodologies. To assess the clinical usefulness, we examined its ability to predict clinical outcomes in a cirrhosis cohort and found that automated psoas muscle index was independently associated with mortality after adjusting for age, gender, and child's classification (P < 0.001). DISCUSSION: We demonstrated that deep learning techniques can allow for automation of muscle measurements on clinical CT scans in a diseased cohort. These automated psoas size measurements were predictive of mortality in patients with cirrhosis showing proof of principal that this methodology may allow for wider implementation in the clinical arena.

Genomic landscape of ductal carcinoma in situ and association with progression.

PURPOSE: The detection rate of breast ductal carcinoma in situ (DCIS) has increased significantly, raising the concern that DCIS is overdiagnosed and overtreated. Therefore, there is an unmet clinical need to better predict the risk of progression among DCIS patients. Our hypothesis is that by combining molecular signatures with clinicopathologic features, we can elucidate the biology of breast cancer progression, and risk-stratify patients with DCIS. METHODS: Targeted exon sequencing with a custom panel of 223 genes/regions was performed for 125 DCIS cases. Among them, 60 were from cases having concurrent or subsequent invasive breast cancer (IBC) (DCIS + IBC group), and 65 from cases with no IBC development over a median follow-up of 13 years (DCIS-only group). Copy number alterations in chromosome 1q32, 8q24, and 11q13 were analyzed using fluorescence in situ hybridization (FISH). Multivariable logistic regression models were fit to the outcome of DCIS progression to IBC as functions of demographic and clinical features. RESULTS: We observed recurrent variants of known IBC-related mutations, and the most commonly mutated genes in DCIS were PIK3CA (34.4%) and TP53 (18.4%). There was an inverse association between PIK3CA kinase domain mutations and progression (Odds Ratio [OR] 10.2, p < 0.05). Copy number variations in 1q32 and 8q24 were associated with progression (OR 9.3 and 46, respectively; both p < 0.05). CONCLUSIONS: PIK3CA kinase domain mutations and the absence of copy number gains in DCIS are protective against progression to IBC. These results may guide efforts to distinguish low-risk from high-risk DCIS.

FOXA1 overexpression mediates endocrine resistance by altering the ER transcriptome and IL-8 expression in ER-positive breast cancer.

Forkhead box protein A1 (FOXA1) is a pioneer factor of estrogen receptor α (ER)-chromatin binding and function, yet its aberration in endocrine-resistant (Endo-R) breast cancer is unknown. Here, we report preclinical evidence for a role of FOXA1 in Endo-R breast cancer as well as evidence for its clinical significance. FOXA1 is gene-amplified and/or overexpressed in Endo-R derivatives of several breast cancer cell line models. Induced FOXA1 triggers oncogenic gene signatures and proteomic profiles highly associated with endocrine resistance. Integrated omics data reveal IL8 as one of the most perturbed genes regulated by FOXA1 and ER transcriptional reprogramming in Endo-R cells. IL-8 knockdown inhibits tamoxifen-resistant cell growth and invasion and partially attenuates the effect of overexpressed FOXA1. Our study highlights a role of FOXA1 via IL-8 signaling as a potential therapeutic target in FOXA1-overexpressing ER-positive tumors.

Phylogenetic analyses of melanoma reveal complex patterns of metastatic dissemination.

Melanoma is difficult to treat once it becomes metastatic. However, the precise ancestral relationship between primary tumors and their metastases is not well understood. We performed whole-exome sequencing of primary melanomas and multiple matched metastases from eight patients to elucidate their phylogenetic relationships. In six of eight patients, we found that genetically distinct cell populations in the primary tumor metastasized in parallel to different anatomic sites, rather than sequentially from one site to the next. In five of these six patients, the metastasizing cells had themselves arisen from a common parental subpopulation in the primary, indicating that the ability to establish metastases is a late-evolving trait. Interestingly, we discovered that individual metastases were sometimes founded by multiple cell populations of the primary that were genetically distinct. Such establishment of metastases by multiple tumor subpopulations could help explain why identical resistance variants are identified in different sites after initial response to systemic therapy. One primary tumor harbored two subclones with different oncogenic mutations in CTNNB1, which were both propagated to the same metastasis, raising the possibility that activation of wingless-type mouse mammary tumor virus integration site (WNT) signaling may be involved, as has been suggested by experimental models.

Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer.

BACKGROUND: High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors. METHODS: We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA). RESULTS: High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup. CONCLUSIONS: We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

Molecular Simulations of Fatty-Acid Methyl Esters and Representative Biodiesel Mixtures.

Despite the importance of fatty-acid methyl esters (FAMEs) as key components of various green solvents, detergents, plasticizers, and biodiesels, our understanding of these systems at the molecular level is limited. An enhanced molecular-level perspective of FAMEs will enable a detailed analysis of the polymorph and crystallization phenomena that adversely impact flow properties at low temperatures. Presented here, is the parameterization and validation of a charge-modified generalized amber force field (GAFF) for eight common FAMEs and two representative biodiesel mixtures. Our simulations accurately reproduce available experimental data (e.g. densities and self-diffusivity coefficients) and their trends, with respect to temperature and degree of unsaturation. Structural analyses from our simulations provide a more detailed picture of liquid-phase molecular ordering in FAMEs and confirm recent experimental hypotheses. This study provides a firm foundation to initiate further studies into the mechanisms that drive crystallization phenomena at the molecular level.

Subtype and pathway specific responses to anticancer compounds in breast cancer.

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response.

Loss-of-function mutations in Notch receptors in cutaneous and lung squamous cell carcinoma.

Squamous cell carcinomas (SCCs) are one of the most frequent forms of human malignancy, but, other than TP53 mutations, few causative somatic aberrations have been identified. We identified NOTCH1 or NOTCH2 mutations in ~75% of cutaneous SCCs and in a lesser fraction of lung SCCs, defining a spectrum for the most prevalent tumor suppressor specific to these epithelial malignancies. Notch receptors normally transduce signals in response to ligands on neighboring cells, regulating metazoan lineage selection and developmental patterning. Our findings therefore illustrate a central role for disruption of microenvironmental communication in cancer progression. NOTCH aberrations include frameshift and nonsense mutations leading to receptor truncations as well as point substitutions in key functional domains that abrogate signaling in cell-based assays. Oncogenic gain-of-function mutations in NOTCH1 commonly occur in human T-cell lymphoblastic leukemia/lymphoma and B-cell chronic lymphocytic leukemia. The bifunctional role of Notch in human cancer thus emphasizes the context dependency of signaling outcomes and suggests that targeted inhibition of the Notch pathway may induce squamous epithelial malignancies.

Low-parameter supervised learning models can discriminate pseudoprogression and true progression in non-perfusion-based MRI.

Discrimination of pseudoprogression and true progression is one challenge to the treatment of malignant gliomas. Although some techniques such as circulating tumor DNA (ctDNA) and perfusion-weighted imaging (PWI) demonstrate promise in distinguishing PsP from TP, we investigate robust and replicable alternatives to distinguish the two entities based on more widely-available media. In this study, we use low-parametric supervised learning techniques based on geographically-weighted regression (GWR) to investigate the utility of both conventional MRI sequences as well as a diffusion-weighted sequence (apparent diffusion coefficient or ADC) in the discrimination of PsP v TP. GWR applied to MRI modality pairs is a unique approach for small sample sizes and is a novel approach in this arena. From our analysis, all modality pairs involving ADC maps, and those involving post-contrast T1 regressed onto T2 showed potential promise. This work on ADC data adds to a growing body of research suggesting the predictive benefits of ADC, and suggests further research on the relationships between post-contrast T1 and T2.Clinical relevance- Few studies have investigated predictive potential of conventional MRI and ADC to detect PsP. Our study adds to the growing research on the topic and presents a new perspective to research by exploiting the utility of ADC in PsP v TP distinction. In addition, our GWR methodology for low-parametric supervised computer vision models demonstrates a unique approach for image processing of small sample sizes.

Genomic DNA activates the AIM2 inflammasome and STING pathways to induce inflammation in lacrimal gland myoepithelial cells.

PURPOSE: Primary Sjögren's syndrome (pSS) is an autoimmune disease that mainly attacks the lacrimal glands causing severe aqueous-deficient dry eye. Clinical evidence indicates the DNA sensing mechanism in the pathogenesis of pSS. The purpose of the present study is to determine the pro-inflammatory effect of self-genomic DNA (gDNA) on myoepithelial cells (MECs), which along with acinar and ductal cells is a major cell type of the lacrimal gland. METHOD: MECs primary culture was acquired from female C57BL6J mice. Genomic DNA was extracted from the spleen of the same animal. The MECs were challenged with self-gDNA. The cytokine secretion was detected using supernatant by enzyme-linked immunosorbent assay (ELISA). The activation of inflammasomes was determined using FAM-FLICA. Cryosections of NOD.B10.H2b mouse model of pSS were obtained for immunofluorescence microscopy (IF), with Balb/C as control. RESULT: Treatment with gDNA activated AIM2 inflammasome assembly and function, leading to secretion of interleukin (IL)-1ß and IL-18 in MECs. The stimulation of IL-1ß secretion by gDNA appeared to be solely at the post-translational level, whereas IL-18 secretion was a combination of increased protein synthesis and post-translational modification. Genomic DNA also induced the activation of STimulators of INterferon Genes (STING), which correlated to the activation of STING in the lacrimal gland from the NOD.B10.H2b mouse. STING activation led to the secretion of IFN-ß via Nuclear Factor-κB (NF-κB). The IFN-ß further enhances the secretion of IL-1ß. The contractility of MECs was disabled by treatment with gDNA or poly AnT, independent of the level of intracellular [Ca2+]. CONCLUSION: Self-gDNA induces a proinflammatory response in lacrimal gland MECs by activating both the AIM2 inflammasome and STING and thus may contribute to the pathogenesis of pSS.

Xenografts faithfully recapitulate breast cancer-specific gene expression patterns of parent primary breast tumors.

Though xenografts are used extensively for drug development in breast cancer, how well xenografts reflect the breadth of primary breast tumor subtypes has not been well characterized. Moreover, few studies have compared the gene expression of xenograft tumors to the primary tumors from which they were derived. Here we investigate whether the ability of human breast tumors (n = 20) to create xenografts in immune-deficient mice is associated with breast cancer immunohistochemical (IHC) and intrinsic subtype. We also characterize how precisely the gene expression of xenografts reprises that of parent breast tumors, using hierarchical clustering and other correlation-based techniques applied to Agilent 44K gene expression data from 16 samples including four matched primary tumor-xenograft pairs. Of the breast tumors studied, 25 % (5/20) generated xenografts. Receptor and intrinsic subtype were significant predictors of xenograft success, with all (4/4) triple-negative (TN) tumors and no (0/12) HR+Her2- tumors forming xenografts (P = 0.0005). Tumor cell expression of ALDH1, a stem cell marker, trended toward successful engraftment (P = 0.14), though CDK5/6, a basal marker, did not. Though hierarchical clustering across the 500 most variable genes segregated human breast tumors from xenograft tumors, when clustering was performed over the PAM50 gene set the primary tumor-xenograft pairs clustered together, with all IHC subtypes clustered in distinct groups. Greater similarity between primary tumor-xenograft pairs relative to random pairings was confirmed by calculation of the within-pair between-pair scatter ratio (WPBPSR) distribution (P = 0.0269), though there was a shift in the xenografts toward more aggressive features including higher proliferation scores relative to the primary. Triple-negative breast tumors demonstrate superior ability to create xenografts compared to HR+ tumors, which may reflect higher proliferation or relatively stroma-independent growth of this subtype. Xenograft tumors' gene expression faithfully resembles that of their parent tumors, yet also demonstrates a shift toward more aggressive molecular features.

Cross-platform pathway-based analysis identifies markers of response to the PARP inhibitor olaparib.

Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. PARP inhibitors can act as chemosensitizers, or operate on the principle of synthetic lethality when used as single agent. Clinical trials have shown drugs in this class to be promising for BRCA mutation carriers. We postulated that inability to demonstrate response in non-BRCA carriers in which BRCA is inactivated by other mechanisms or with deficiency in homologous recombination for DNA repair is due to lack of molecular markers that define a responding subpopulation. We identified candidate markers for this purpose for olaparib (AstraZeneca) by measuring inhibitory effects of nine concentrations of olaparib in 22 breast cancer cell lines and identifying features in transcriptional and genome copy number profiles that were significantly correlated with response. We emphasized in this discovery process genes involved in DNA repair. We found that the cell lines that were sensitive to olaparib had a significant lower copy number of BRCA1 compared to the resistant cell lines (p value 0.012). In addition, we discovered seven genes from DNA repair pathways whose transcriptional levels were associated with response. These included five genes (BRCA1, MRE11A, NBS1, TDG, and XPA) whose transcript levels were associated with resistance and two genes (CHEK2 and MK2) whose transcript levels were associated with sensitivity. We developed an algorithm to predict response using the seven-gene transcription levels and applied it to 1,846 invasive breast cancer samples from 8 U133A/plus 2 (Affymetrix) data sets and found that 8-21 % of patients would be predicted to be responsive to olaparib. A similar response frequency was predicted in 536 samples analyzed on an Agilent platform. Importantly, tumors predicted to respond were enriched in basal subtype tumors. Our studies support clinical evaluation of the utility of our seven-gene signature as a predictor of response to olaparib.

Simulated MRI Artifacts: Testing Machine Learning Failure Modes.

Objective. Seven types of MRI artifacts, including acquisition and preprocessing errors, were simulated to test a machine learning brain tumor segmentation model for potential failure modes. Introduction. Real-world medical deployments of machine learning algorithms are less common than the number of medical research papers using machine learning. Part of the gap between the performance of models in research and deployment comes from a lack of hard test cases in the data used to train a model. Methods. These failure modes were simulated for a pretrained brain tumor segmentation model that utilizes standard MRI and used to evaluate the performance of the model under duress. These simulated MRI artifacts consisted of motion, susceptibility induced signal loss, aliasing, field inhomogeneity, sequence mislabeling, sequence misalignment, and skull stripping failures. Results. The artifact with the largest effect was the simplest, sequence mislabeling, though motion, field inhomogeneity, and sequence misalignment also caused significant performance decreases. The model was most susceptible to artifacts affecting the FLAIR (fluid attenuation inversion recovery) sequence. Conclusion. Overall, these simulated artifacts could be used to test other brain MRI models, but this approach could be used across medical imaging applications.

Healthy US population reference values for CT visceral fat measurements and the impact of IV contrast, HU range, and spinal levels.

Measurements of visceral adipose tissue cross-sectional area and radiation attenuation from computed tomography (CT) scans provide useful information about risk and mortality. However, scan protocols vary, encompassing differing vertebra levels and utilizing differing phases of contrast enhancement. Furthermore, fat measurements have been extracted from CT using different Hounsfield Unit (HU) ranges. To our knowledge, there have been no large studies of healthy cohorts that reported reference values for visceral fat area and radiation attenuation at multiple vertebra levels, for different contrast phases, and using different fat HU ranges. Two-phase CT scans from 1,677 healthy, adult kidney donors (age 18-65) between 1999 and 2017, previously studied to determine healthy reference values for skeletal muscle measures, were utilized. Visceral adipose tissue cross-sectional area (VFA) and radiation attenuation (VFRA) measures were quantified using axial slices at T10 through L4 vertebra levels. T-tests were used to compare males and females, while paired t-tests were conducted to determine the effect (magnitude and direction) of (a) contrast enhancement and (b) different fat HU ranges on each fat measure at each vertebra level. We report the means, standard deviations, and effect sizes of contrast enhancement and fat HU range. Male and female VFA and VFRA were significantly different at all vertebra levels in both contrast and non-contrast scans. Peak VFA was observed at L4 in females and L2 in males, while peak VFRA was observed at L1 in both females and males. In general, non-contrast scans showed significantly greater VFA and VFRA compared to contrast scans. The average paired difference due to contrast ranged from 1.6 to - 8% (VFA) and 3.2 to - 3.0% (VFRA) of the non-contrast value. HU range showed much greater differences in VFA and VFRA than contrast. The average paired differences due to HU range ranged from - 5.3 to 22.2% (VFA) and - 5.9 to 13.6% (VFRA) in non-contrast scans, and - 4.4 to 20.2% (VFA) and - 4.1 to 12.6% (VFRA) in contrast scans. The - 190 to - 30 HU range showed the largest differences in both VFA (10.8% to 22.2%) and VFRA (7.6% to 13.6%) compared to the reference range (- 205 to - 51 HU). Incidentally, we found that differences in lung inflation result in very large differences in visceral fat measures, particularly in the thoracic region. We assessed the independent effects of contrast presence and fat HU ranges on visceral fat cross-sectional area and mean radiation attenuation, finding significant differences particularly between different fat HU ranges. These results demonstrate that CT measurements of visceral fat area and radiation attenuation are strongly dependent upon contrast presence, fat HU range, sex, breath cycle, and vertebra level of measurement. We quantified contrast and non-contrast reference values separately for males and females, using different fat HU ranges, for lumbar and thoracic CT visceral fat measures at multiple vertebra levels in a healthy adult US population.

Sex-based differences in conjunctival goblet cell responses to pro-inflammatory and pro-resolving mediators.

Many conjunctival inflammatory diseases differ between the sexes and altered conjunctival goblet cells (CGCs) response is often involved. Inflammation is initiated by the release of pro-inflammatory mediators and terminated by the biosynthesis of specialized pro-resolution mediators (SPMs). Herein, we determined the sex-based difference in the responses of CGCs to inflammatory stimuli or pro-resolving lipid SPMs and their interaction with sex hormones. GCs were cultured from pieces of human conjunctiva in RPMI media. CGCs were transferred 24 h before the start of experiments to phenol red-free and FBS-free media to minimize exogenous hormones. RT-PCR, immunofluorescence microscopy (IF), and Western Blot (WB) were performed to determine the presence of sex hormone receptors. Cellular response to pro-inflammatory stimuli or SPMs was studied by measuring the increase in intracellular [Ca2+] ([Ca2+]i) using fura 2/AM microscopy. Use of RT-PCR demonstrated estrogen receptor (ER) α in 4/5 males and 3/3 females; ERß in 2/4 males and 2/3 females; and androgen receptors (AR) in 3/3 male and 3/3 female CGCs. Positive immunoreactivity by IF and protein expression by WB was detected using antibodies for the ERα and ERß in 3/3 males and 3/3 females, while AR were only present in males. Significantly different Ca2+ responses between sexes were found with carbachol only at 10-3 M, but not with histamine or leukotriene (LT) B4 at any concentration used. Incubation with dihydrotestosterone (DHT), estrone (E1), or estradiol (E2) at 10-7 M for 30 min significantly inhibited the LTB4-stimulated [Ca2+]i increase in male and female CGCs. Incubation with DHT, E1, and E2 overnight significantly inhibited the LTB4 response in females, while DHT and E2 significantly inhibited the LTB4 response in males. The SPM lipoxin A4 (LXA4) (10-9-10-8 M), but not the resolvins D1 or D2, induced an [Ca2+]i increase that was significantly higher in males compared to females. We conclude that male and female CGCs showed differences in the expression of sex hormone receptors. Treatment with sex hormones altered pro-inflammatory mediator LTB4-induced response. Males compared to females have a higher response to the ω-6-fatty acid derived SPM LXA4, indicating males may terminate inflammation in conjunctival goblet cells faster than females.

Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas.

ABSTRACT: Advanced imaging techniques provide a powerful tool to assess the intratumoral and intertumoral heterogeneity of gliomas. Advances in the molecular understanding of glioma subgroups may allow improved diagnostic assessment combining imaging and molecular tumor features, with enhanced prognostic utility and implications for patient treatment. In this article, a comprehensive overview of the physiologic basis for conventional and advanced imaging techniques is presented, and clinical applications before and after treatment are discussed. An introduction to the principles of radiomics and the advanced integration of imaging, clinical outcomes, and genomic data highlights the future potential for this field of research to better stratify and select patients for standard as well as investigational therapies.