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    [–] Suicide molecules kill any cancer cell - Cancer cells treated with the RNA molecules never become resistant to them because they simultaneously eliminate multiple genes that cancer cells need for survival. mvea 1 points ago in Health

    Journal reference:

    Induction of DISE in ovarian cancer cells in vivo

    Andrea E. Murmann1, Kaylin M. McMahon3,6, Ashley Haluck-Kangas1, Nandini Ravindran1, Monal Patel1, Calvin Y. Law1, Sonia Brockway1, Jian-Jun Wei4, C. Shad Thaxton3,5,6,7 and Marcus E. Peter

    Oncotarget. 2017; 8:84643-84658.

    Published: October 04, 2017

    DOI: https://doi.org/10.18632/oncotarget.21471

    Link: http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path[]=21471&path[]=68236

    Abstract:

    The death receptor CD95/Fas can be activated by immune cells to kill cancer cells. shRNAs and siRNAs derived from CD95 or CD95 ligand (CD95L) are highly toxic to most cancer cells. We recently found that these sh/siRNAs kill cancer cells in the absence of the target by targeting the 3’UTRs of critical survival genes through canonical RNAi. We have named this unique form of off-target effect DISE (for death induced by survival gene elimination). DISE preferentially kills transformed cells and cancer stem cells. We demonstrate that DISE induction occurs in cancer cells in vivo after introducing a lentiviral CD95L derived shRNA (shL3) into HeyA8 ovarian cancer cells grown as i.p. xenografts in mice, when compared to a scrambled shRNA. To demonstrate the possibility of therapeutically inducing DISE, we coupled siRNAs to templated lipoprotein nanoparticles (TLP). In vitro, TLPs loaded with a CD95L derived siRNA (siL3) selectively silenced a biosensor comprised of Venus and CD95L ORF and killed ovarian cancer cells. In vivo, two siRNA-TLPs (siL2-TLP and siL3-TLP) reduced tumor growth similarly as observed for cells expressing the shL3 vector. These data suggest that it is possible to kill ovarian cancer cells in vivo via DISE induction using siRNA-TLPs.

    [–] Suicide molecules kill any cancer cell - Cancer cells treated with the RNA molecules never become resistant to them because they simultaneously eliminate multiple genes that cancer cells need for survival. mvea 13 points ago in Futurology

    Journal reference:

    Induction of DISE in ovarian cancer cells in vivo

    Andrea E. Murmann1, Kaylin M. McMahon3,6, Ashley Haluck-Kangas1, Nandini Ravindran1, Monal Patel1, Calvin Y. Law1, Sonia Brockway1, Jian-Jun Wei4, C. Shad Thaxton3,5,6,7 and Marcus E. Peter

    Oncotarget. 2017; 8:84643-84658.

    Published: October 04, 2017

    DOI: https://doi.org/10.18632/oncotarget.21471

    Link: http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path[]=21471&path[]=68236

    Abstract:

    The death receptor CD95/Fas can be activated by immune cells to kill cancer cells. shRNAs and siRNAs derived from CD95 or CD95 ligand (CD95L) are highly toxic to most cancer cells. We recently found that these sh/siRNAs kill cancer cells in the absence of the target by targeting the 3’UTRs of critical survival genes through canonical RNAi. We have named this unique form of off-target effect DISE (for death induced by survival gene elimination). DISE preferentially kills transformed cells and cancer stem cells. We demonstrate that DISE induction occurs in cancer cells in vivo after introducing a lentiviral CD95L derived shRNA (shL3) into HeyA8 ovarian cancer cells grown as i.p. xenografts in mice, when compared to a scrambled shRNA. To demonstrate the possibility of therapeutically inducing DISE, we coupled siRNAs to templated lipoprotein nanoparticles (TLP). In vitro, TLPs loaded with a CD95L derived siRNA (siL3) selectively silenced a biosensor comprised of Venus and CD95L ORF and killed ovarian cancer cells. In vivo, two siRNA-TLPs (siL2-TLP and siL3-TLP) reduced tumor growth similarly as observed for cells expressing the shL3 vector. These data suggest that it is possible to kill ovarian cancer cells in vivo via DISE induction using siRNA-TLPs.

    [–] Prozac in ocean water a possible threat to sea life - Oregon shore crabs exhibit risky behavior when they’re exposed to the antidepressant Prozac, making it easier for predators to catch them, according to a new study. mvea 3 points ago in science

    Journal Reference:

    Joseph R. Peters, Elise F. Granek, Catherine E. de Rivera, Matthew Rollins.

    Prozac in the water: Chronic fluoxetine exposure and predation risk interact to shape behaviors in an estuarine crab.

    Ecology and Evolution, 2017;

    DOI: 10.1002/ece3.3453

    Link: http://onlinelibrary.wiley.com/doi/10.1002/ece3.3453/abstract

    Abstract

    Predators exert considerable top-down pressure on ecosystems by directly consuming prey or indirectly influencing their foraging behaviors and habitat use. Prey is, therefore, forced to balance predation risk with resource reward. A growing list of anthropogenic stressors such as rising temperatures and ocean acidification has been shown to influence prey risk behaviors and subsequently alter important ecosystem processes. Yet, limited attention has been paid to the effects of chronic pharmaceutical exposure on risk behavior or as an ecological stressor, despite widespread detection and persistence of these contaminants in aquatic environments. In the laboratory, we simulated estuarine conditions of the shore crab, Hemigrapsus oregonensis, and investigated whether chronic exposure (60 days) to field-detected concentrations (0, 3, and 30 ng/L) of the antidepressant fluoxetine affected diurnal and nocturnal risk behaviors in the presence of a predator, Cancer productus. We found that exposure to fluoxetine influenced both diurnal and nocturnal prey risk behaviors by increasing foraging and locomotor activity in the presence of predators, particularly during the day when these crabs normally stay hidden. Crabs exposed to fluoxetine were also more aggressive, with a higher frequency of agonistic interactions and increased mortality due to conflicts with conspecifics. These results suggest that exposure to field-detected concentrations of fluoxetine may alter the trade-off between resource acquisition and predation risk among crabs in estuaries. This fills an important data gap, highlighting how intra- and interspecific behaviors are altered by exposure to field concentrations of pharmaceuticals; such data more explicitly identify potential ecological impacts of emerging contaminants on aquatic ecosystems and can aid water quality management.

    [–] Prozac in ocean water a possible threat to sea life - Oregon shore crabs exhibit risky behavior when they’re exposed to the antidepressant Prozac, making it easier for predators to catch them, according to a new study. mvea 2 points ago in environment

    Journal Reference:

    Joseph R. Peters, Elise F. Granek, Catherine E. de Rivera, Matthew Rollins.

    Prozac in the water: Chronic fluoxetine exposure and predation risk interact to shape behaviors in an estuarine crab.

    Ecology and Evolution, 2017;

    DOI: 10.1002/ece3.3453

    Link: http://onlinelibrary.wiley.com/doi/10.1002/ece3.3453/abstract

    Abstract

    Predators exert considerable top-down pressure on ecosystems by directly consuming prey or indirectly influencing their foraging behaviors and habitat use. Prey is, therefore, forced to balance predation risk with resource reward. A growing list of anthropogenic stressors such as rising temperatures and ocean acidification has been shown to influence prey risk behaviors and subsequently alter important ecosystem processes. Yet, limited attention has been paid to the effects of chronic pharmaceutical exposure on risk behavior or as an ecological stressor, despite widespread detection and persistence of these contaminants in aquatic environments. In the laboratory, we simulated estuarine conditions of the shore crab, Hemigrapsus oregonensis, and investigated whether chronic exposure (60 days) to field-detected concentrations (0, 3, and 30 ng/L) of the antidepressant fluoxetine affected diurnal and nocturnal risk behaviors in the presence of a predator, Cancer productus. We found that exposure to fluoxetine influenced both diurnal and nocturnal prey risk behaviors by increasing foraging and locomotor activity in the presence of predators, particularly during the day when these crabs normally stay hidden. Crabs exposed to fluoxetine were also more aggressive, with a higher frequency of agonistic interactions and increased mortality due to conflicts with conspecifics. These results suggest that exposure to field-detected concentrations of fluoxetine may alter the trade-off between resource acquisition and predation risk among crabs in estuaries. This fills an important data gap, highlighting how intra- and interspecific behaviors are altered by exposure to field concentrations of pharmaceuticals; such data more explicitly identify potential ecological impacts of emerging contaminants on aquatic ecosystems and can aid water quality management.

    [–] A significant number of childhood cancer survivors are worried about keeping their health insurance, to the point of letting it affect their career decisions, finds national cancer survey published in JAMA Oncology. mvea 11 points ago in science

    Journal Reference:

    Anne C. Kirchhoff, Ryan Nipp, Echo L. Warner, Karen Kuhlthau, Wendy M. Leisenring, Karen Donelan, Julia Rabin, Giselle K. Perez, Kevin C. Oeffinger, Paul C. Nathan, Leslie L. Robison, Gregory T. Armstrong, Elyse R. Park.

    “Job Lock” Among Long-term Survivors of Childhood Cancer.

    JAMA Oncology, 2017;

    DOI: 10.1001/jamaoncol.2017.3372

    Link: https://jamanetwork.com/journals/jamaoncology/article-abstract/2657668

    Key Points

    Question What are the associations between “job lock” and a history of childhood cancer?

    Findings In this cross-sectional survey study, almost 1 in 4 of the 394 full-time employed survivors of childhood cancer reported a history of “job lock” (staying at a job to keep work-related health insurance). Job lock was associated with factors including female sex, history of health insurance denial, problems paying medical bills, and a severe, disabling, or life-threatening chronic health condition.

    Meaning The need for insurance coverage may limit childhood cancer survivors’ employment trajectory.

    Abstract

    Importance Childhood cancer survivors may be reluctant to make changes in their employment because of access to health insurance.

    Objective To examine the prevalence of “job lock” (staying at a job to keep work-related health insurance) in a sample drawn from an established, multi-institutional cohort of full-time employed childhood cancer survivors compared with a random sample of siblings and to explore factors associated with job lock among cancer survivors.

    Design, Setting, and Participants Cross-sectional survey of full-time employed adult survivors of childhood cancer and a random sample of siblings derived from a cohort of 25 US pediatric oncology centers.

    Exposures Data collection included sociodemographic factors, insurance coverage, chronic medical conditions, and treatment.

    Main Outcomes and Measures Self-report of job lock and factors associated with job lock.

    Results Among the 522 participants, 394 were cancer survivors (54.5% male) and 128 were siblings (51.5% male). Job lock was reported by 23.2% (95% CI, 18.9%-28.1%) of survivors, compared with 16.9% (95% CI, 11.1%-25.0%) of siblings (P = .16). Job lock was more common among survivors reporting previous health insurance denial (relative risk [RR], 1.60; 95% CI, 1.03-2.52) and problems paying medical bills (RR, 2.43; 95% CI, 1.56-3.80). Among survivors, being female (RR, 1.70; 95% CI, 1.11-2.59; P = .01) and having a severe, disabling, or life-threatening health condition (RR, 1.72; 95% CI, 1.09-2.69; P = .02) were associated with job lock.

    Conclusions and Relevance Job lock is common among long-term childhood cancer survivors who are employed full-time. A survivor’s decision to remain employed at a job in order to maintain health insurance coverage may affect career trajectory, diminish potential earning power, and ultimately impact quality of life.

    [–] A significant number of childhood cancer survivors are worried about keeping their health insurance, to the point of letting it affect their career decisions, finds national cancer survey published in JAMA Oncology. mvea 1 points ago in Health

    Journal Reference:

    Anne C. Kirchhoff, Ryan Nipp, Echo L. Warner, Karen Kuhlthau, Wendy M. Leisenring, Karen Donelan, Julia Rabin, Giselle K. Perez, Kevin C. Oeffinger, Paul C. Nathan, Leslie L. Robison, Gregory T. Armstrong, Elyse R. Park.

    “Job Lock” Among Long-term Survivors of Childhood Cancer.

    JAMA Oncology, 2017;

    DOI: 10.1001/jamaoncol.2017.3372

    Link: https://jamanetwork.com/journals/jamaoncology/article-abstract/2657668

    Key Points

    Question What are the associations between “job lock” and a history of childhood cancer?

    Findings In this cross-sectional survey study, almost 1 in 4 of the 394 full-time employed survivors of childhood cancer reported a history of “job lock” (staying at a job to keep work-related health insurance). Job lock was associated with factors including female sex, history of health insurance denial, problems paying medical bills, and a severe, disabling, or life-threatening chronic health condition.

    Meaning The need for insurance coverage may limit childhood cancer survivors’ employment trajectory.

    Abstract

    Importance Childhood cancer survivors may be reluctant to make changes in their employment because of access to health insurance.

    Objective To examine the prevalence of “job lock” (staying at a job to keep work-related health insurance) in a sample drawn from an established, multi-institutional cohort of full-time employed childhood cancer survivors compared with a random sample of siblings and to explore factors associated with job lock among cancer survivors.

    Design, Setting, and Participants Cross-sectional survey of full-time employed adult survivors of childhood cancer and a random sample of siblings derived from a cohort of 25 US pediatric oncology centers.

    Exposures Data collection included sociodemographic factors, insurance coverage, chronic medical conditions, and treatment.

    Main Outcomes and Measures Self-report of job lock and factors associated with job lock.

    Results Among the 522 participants, 394 were cancer survivors (54.5% male) and 128 were siblings (51.5% male). Job lock was reported by 23.2% (95% CI, 18.9%-28.1%) of survivors, compared with 16.9% (95% CI, 11.1%-25.0%) of siblings (P = .16). Job lock was more common among survivors reporting previous health insurance denial (relative risk [RR], 1.60; 95% CI, 1.03-2.52) and problems paying medical bills (RR, 2.43; 95% CI, 1.56-3.80). Among survivors, being female (RR, 1.70; 95% CI, 1.11-2.59; P = .01) and having a severe, disabling, or life-threatening health condition (RR, 1.72; 95% CI, 1.09-2.69; P = .02) were associated with job lock.

    Conclusions and Relevance Job lock is common among long-term childhood cancer survivors who are employed full-time. A survivor’s decision to remain employed at a job in order to maintain health insurance coverage may affect career trajectory, diminish potential earning power, and ultimately impact quality of life.

    [–] Physics Boosts AI Methods - Researchers report the first application of quantum computing to a physics problem. By employing quantum-compatible machine learning techniques, they developed a method of extracting a rare Higgs boson signal from copious noise data, as reported in Nature. mvea 3 points ago in science

    Journal Reference:

    Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel Lidar, Maria Spiropulu.

    Solving a Higgs optimization problem with quantum annealing for machine learning.

    Nature, 2017; 550 (7676): 375

    DOI: 10.1038/nature24047

    Link: https://www.nature.com/nature/journal/v550/n7676/full/nature24047.html

    Abstract:

    The discovery of Higgs-boson decays in a background of standard-model processes was assisted by machine learning methods1, 2. The classifiers used to separate signals such as these from background are trained using highly unerring but not completely perfect simulations of the physical processes involved, often resulting in incorrect labelling of background processes or signals (label noise) and systematic errors. Here we use quantum3, 4, 5, 6 and classical7, 8 annealing (probabilistic techniques for approximating the global maximum or minimum of a given function) to solve a Higgs-signal-versus-background machine learning optimization problem, mapped to a problem of finding the ground state of a corresponding Ising spin model. We build a set of weak classifiers based on the kinematic observables of the Higgs decay photons, which we then use to construct a strong classifier. This strong classifier is highly resilient against overtraining and against errors in the correlations of the physical observables in the training data. We show that the resulting quantum and classical annealing-based classifier systems perform comparably to the state-of-the-art machine learning methods that are currently used in particle physics9, 10. However, in contrast to these methods, the annealing-based classifiers are simple functions of directly interpretable experimental parameters with clear physical meaning. The annealer-trained classifiers use the excited states in the vicinity of the ground state and demonstrate some advantage over traditional machine learning methods for small training datasets. Given the relative simplicity of the algorithm and its robustness to error, this technique may find application in other areas of experimental particle physics, such as real-time decision making in event-selection problems and classification in neutrino physics.

    I

    [–] Physics Boosts AI Methods - Researchers report the first application of quantum computing to a physics problem. By employing quantum-compatible machine learning techniques, they developed a method of extracting a rare Higgs boson signal from copious noise data, as reported in Nature. mvea 4 points ago in Futurology

    Journal Reference:

    Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel Lidar, Maria Spiropulu.

    Solving a Higgs optimization problem with quantum annealing for machine learning.

    Nature, 2017; 550 (7676): 375

    DOI: 10.1038/nature24047

    Link: https://www.nature.com/nature/journal/v550/n7676/full/nature24047.html

    Abstract:

    The discovery of Higgs-boson decays in a background of standard-model processes was assisted by machine learning methods1, 2. The classifiers used to separate signals such as these from background are trained using highly unerring but not completely perfect simulations of the physical processes involved, often resulting in incorrect labelling of background processes or signals (label noise) and systematic errors. Here we use quantum3, 4, 5, 6 and classical7, 8 annealing (probabilistic techniques for approximating the global maximum or minimum of a given function) to solve a Higgs-signal-versus-background machine learning optimization problem, mapped to a problem of finding the ground state of a corresponding Ising spin model. We build a set of weak classifiers based on the kinematic observables of the Higgs decay photons, which we then use to construct a strong classifier. This strong classifier is highly resilient against overtraining and against errors in the correlations of the physical observables in the training data. We show that the resulting quantum and classical annealing-based classifier systems perform comparably to the state-of-the-art machine learning methods that are currently used in particle physics9, 10. However, in contrast to these methods, the annealing-based classifiers are simple functions of directly interpretable experimental parameters with clear physical meaning. The annealer-trained classifiers use the excited states in the vicinity of the ground state and demonstrate some advantage over traditional machine learning methods for small training datasets. Given the relative simplicity of the algorithm and its robustness to error, this technique may find application in other areas of experimental particle physics, such as real-time decision making in event-selection problems and classification in neutrino physics.

    I

    [–] Scientists pinpoint jealousy in the monogamous brain: The first neurobiology study of jealousy in a monogamous primate species sheds light on the emotion that keeps couples together — but also tears them apart mvea 2 points ago in science

    Journal Reference:

    Nicole Maninger, Sally P. Mendoza, Donald R. Williams, William A. Mason, Simon R. Cherry, Douglas J. Rowland, Thomas Schaefer, Karen L. Bales.

    Imaging, Behavior and Endocrine Analysis of “Jealousy” in a Monogamous Primate.

    Frontiers in Ecology and Evolution, 2017; 5

    DOI: 10.3389/fevo.2017.00119

    Link: https://www.frontiersin.org/articles/10.3389/fevo.2017.00119/full

    Abstract:

    Understanding the neurobiology of social bonding in non-human primates is a critical step in understanding the evolution of monogamy, as well as understanding the neural substrates for emotion and behavior. Coppery titi monkeys (Callicebus cupreus) form strong pair bonds, characterized by selective preference for their pair mate, mate-guarding, physiological and behavioral agitation upon separation, and social buffering. Mate-guarding, or the “maintenance” phase of pair bonding, is relatively under-studied in primates. In the current study, we used functional imaging to examine how male titi monkeys viewing their pair mate in close proximity to a stranger male would change regional cerebral glucose metabolism. We predicted that this situation would challenge the pair bond and induce “jealousy” in the males. Animals were injected with [18F]-fluorodeoxyglucose (FDG), returned to their cage for 30 min of conscious uptake, placed under anesthesia, and then scanned for 1 h on a microPET P4 scanner. During the FDG uptake, males (n = 8) had a view of either their female pair mate next to a stranger male (“jealousy” condition) or a stranger female next to a stranger male (control condition). Blood and cerebrospinal fluid samples were collected and assayed for testosterone, cortisol, oxytocin, and vasopressin. Positron emission tomography (PET) was co-registered with structural magnetic resonance imaging (MRI), and region of interest analysis was carried out. Bayesian multivariate multilevel analyses found that the right lateral septum (Pr(b > 0) = 93%), left posterior cingulate cortex (Pr(b > 0) = 99%), and left anterior cingulate (Pr(b > 0) = 96%) showed higher FDG uptake in the jealousy condition compared to the control condition, while the right medial amygdala (Pr(b > 0) = 85%) showed lower FDG uptake. Plasma testosterone and cortisol concentrations were higher during the jealousy condition. During the jealousy condition, duration of time spent looking across at the pair mate next to a stranger male was associated with higher plasma cortisol concentrations. The lateral septum has been shown to be involved in mate-guarding and mating-induced aggression in monogamous rodents, while the cingulate cortex has been linked to territoriality. These neural and physiological changes may underpin the emotion of jealousy, which can act in a monogamous species to preserve the long-term integrity of the pair.