Outcome modeling techniques for prostate cancer radiotherapy: Data,models, and validation

Prostate cancer is a frequently diagnosed malignancy worldwide and radiation therapy is a first-line approach in treating localized as well as locally advanced cases. The limiting factor in modern radiotherapy regimens is dose to normal structures, an excess of which can lead to aberrant radiation-induced toxicities. Conversely, dose reduction to spare adjacent normal structures risks underdosing target volumes and compromising local control. As a result, efforts aimed at predicting the effects of radiotherapy could invaluably optimize patient treatments by mitigating such toxicities and simultaneously maximizing biochemical control. In this work, we review the types of data, frameworks and techniques used for prostate radiotherapy outcome modeling. Consideration is given to clinical and dose-volume metrics, such as those amassed by the QUANTEC initiative, and also to newer methods for the integration of biological and genetic factors to improve prediction performance. We furthermore highlight trends in machine learning that may help to elucidate the complex pathophysiological mechanisms of tumor control and radiation-induced normal tissue side effects.     

Proteins in Tumor-Derived Plasma Extracellular Vesicles Indicate Tumor Origin

Cancer-derived extracellular vesicles (EVs) promote tumorigenesis, premetastatic niche formation, and metastasis via their protein cargo. However, the proteins packaged by patient tumors into EVs cannot be determined in vivo because of the presence of EVs derived from other tissues. We therefore developed a cross-species proteomic method to quantify the human tumor-derived proteome of plasma EVs produced by patient-derived xenografts of four cancer types. Proteomic profiling revealed individualized packaging of novel protein cargo, and machine learning accurately classified the type of the underlying tumor.     

基于F3Net显著性目标检测的蝴蝶图像前背景自动分割

[目的]具有复杂背景的蝴蝶图像前背景分割难度大.本研究旨在探索基于深度学习显著性目标检测的蝴蝶图像自动分割方法.[方法]应用DUTS-TR数据集训练F3Net显著性目标检测算法构建前背景预测模型,然后将模型用于具有复杂背景的蝴蝶图像数据集实现蝴蝶前背景自动分割.在此基础上,采用迁移学习方法,保持ResNet骨架不变,利...     

The influence of prior ovipositional experience on host selection in four species of aphidiid wasps (Hymenoptera: Aphidiidae)

We evaluated the influence of prior ovipositional experience on host selection in four solitary parasitoids, Aphidius erviHaliday, A. pisivorusSmith, A. smithiSharma & Subba Rao, and Praon pequodorumViereck (Hymenoptera: Aphidiidae). When provided simultaneously with equal numbers of two species of aphids, Acyrthosiphon pisum(Harris) and Macrosiphum creeliiDavis (Homoptera: Aphididae), all four parasitoids showed a moderate to strong preference for A. pisum.This preference did not increase after sampling, except in P. pequodorum.Learning did not alter host selection behavior in A. erviand P. pequodorum.However, females of A. pisivorusconditioned on A. pisumselected fewer M. creeliithan unconditioned wasps and wasps conditioned on M. creelii.It is suggested that prior ovipositional experience influences a parasitoid's expectations of the kinds of hosts available, but it does not alter the (innate) rank order of hosts.     

Food selection by locusts: The rôle of learning in rejection behaviour

The food selection behaviour of male fifth instar nymphs of Locusta migratoria was monitored on the host plant wheat and on the non-host plants Senecio vulgaris, S. jacobaea and Brassica oleracea. The non-hosts were rejected, but the mode of rejection altered with time in a way which suggested associative learning. This hypothesis was tested and the results discussed in relation to classical theories of learning.

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La sélection des aliments chez les criquets: Le rôle de l'apprentissage dans le comportement de rejet

Résumé Des larves mâles de cinquième stade de Locusta migratoria ont été placées dans des cages avec des végétaux qui pouvaient être changées sans troubler les insectes. Le contact avec des pieds de blé entraînait généralement une palpation suivie de morsures et alors d'alimentation continue. Les plantes non-hôtes Senecio vulgaris, S. jacobaea et Brassica oleracea étaient rejetées, d'abord après morsures suivant la palpation, mais ultérieurement par palpation seule. Nous avons vérifié l'hypothèse que la sensation obtenue par palpation était initialement inadéquate pour provoquer le rejet, ce qui était assuré par les morsures ultérieures mais qu'avec l'expérience l'insecte apprenait à lier la sensation de palpation avec celle de morsures et progressivement rejetait après palpation seule. Ainsi les 8 premiers contacts avec des aliments désagréables ont été observés, soit quant S. vulgaris était présenté continuellement, soit quand S. vulgaris était remplacé par une autre plante désagréable après 4 contacts. Une analyse mathématique des résultats révèle une tendance au rejet par palpation seule à travers les contacts successifs, et que cette tendance est interrompue et se restaure quand l'espace végétal est changé. Ces résultats sond discutés dans le contexte des théories de l'apprentissage et on en a conclu que le phénomène observé est le résultat d'un apprentissage associatif.

     

Stimulation of dopamine D1 receptor improves learning capacity in cooperating cleaner fish

Accurate contextual decision-making strategies are important in social environments. Specific areas in the brain are tasked to process these complex interactions and generate correct follow-up responses. The dorsolateral and dorsomedial parts of the telencephalon in the teleost fish brain are neural substrates modulated by the neurotransmitter dopamine (DA), and are part of an important neural circuitry that drives animal behaviour from the most basic actions such as learning to search for food, to properly choosing partners and managing decisions based on context. The Indo-Pacific cleaner wrasse Labroides dimidiatus is a highly social teleost fish species with a complex network of interactions with its ‘client’ reef fish. We asked if changes in DA signalling would affect individual learning ability by presenting cleaner fish two ecologically different tasks that simulated a natural situation requiring accurate decision-making. We demonstrate that there is an involvement of the DA system and D₁ receptor pathways on cleaners'' natural abilities to learn both tasks. Our results add significantly to the growing literature on the physiological mechanisms that underlie and facilitate the expression of cooperative abilities.     

Fostering Industrial Symbiosis With Agent-Based Simulation and Participatory Modeling

The sciences of industrial ecology, complex systems, and adaptive management are intimately related, since they deal with flows and dynamic interdependencies between system elements of various kinds. As such, the tool kit of complex systems science could enrich our understanding of how industrial ecosystems might evolve over time. In this article, I illustrate how an important tool of complex systems science— agent-based simulation —can help to identify those potential elements of an industrial ecosystem that could work together to achieve more eco-efficient outcomes. For example, I show how agent-based simulation can generate cost-efficient energy futures in which groups of firms behave more eco-efficiently by introducing strategically located clusters of renewable, low-emissions, distributed generation. I then explain how role-playing games and participatory modeling can build trust and reduce conflict about the sharing of common-pool resources such as water and energy among small clusters of evolving agents. Collective learning can encourage potential industrial partners to gradually cooperate by exchanging by-products and/or sharing common infrastructure by dint of their close proximity. This kind of coevolutionary learning, aided by participatory modeling, could help to bring about industrial symbiosis.     

Cue use affects resource subdivision among three coexisting hummingbird species

Competition for food can influence the coexistence of speciesvia habitat selection, and learned behavior can influence foragingdecisions. I investigated whether learned behavior and competitionact together to influence species interactions between threecoexisting hummingbird species: black-chinned (Archilochusalexandri), blue-throated (Lampornis clemenciae), and magnificent(Eugenes fulgens) hummingbirds. I found that color cue useby individuals affects not only their foraging choices butalso population-level responses to competition. I presented hummingbirds two types of habitats (rich and poor feeders).All birds shared a preference for the rich feeders, but shiftedpreference toward poor feeders in response to competition.I used color cues to manipulate the amount of information availableto birds and examined the effects of two information states(complete or incomplete) on their foraging choices. I examined hummingbirds' preferences for the rich feeders when both competitordensities and information varied. To relate foraging choicesto energetic intake, I also analyzed energy gained during asingle foraging bout. Males of all species exhibited strongpreferences for rich feeders when they foraged with complete information and low competitor densities. Without complete information,the two subordinate species (black-chinned and magnificent)shifted preference away from rich feeders in response to highdensities of the dominant species (blue-throated). Each subordinatespecies shifted in a unique way: black-chinned hummingbirdsreduced foraging efficiency, while magnificent hummingbirdsreduced foraging time. Birds foraging with complete information remained selective on rich feeders even at high competitor densities.Thus, learned information affected competitive interactions(for rich feeders) among these species.     

Brain insulin system dysfunction in streptozotocin intracerebroventricularly treated rats generates hyperphosphorylated tau protein

The intracerebroventricular (icv) application of streptozotocin (STZ) in low dosage was used in 3-month-old rats to explore brain insulin system dysfunction. Three months following STZ icv treatment, the expression of insulin-1 and -2 mRNA was significantly reduced to 11% in hippocampus and to 28% in frontoparietal cerebral cortex, respectively. Insulin receptor (IR) mRNA expression decreased significantly in frontoparietal cerebral cortex and hippocampus (16% and 33% of control). At the protein/activity level, different abnormalities of protein tyrosine kinase activity (increase in hippocampus), total IR beta-subunit (decrease in hypothalamus) and phosphorylated IR tyrosine residues (increase) became apparent. The STZ-induced disturbance in learning and memory capacities was not abolished by icv application of glucose transport inhibitors known to prevent STZ-induced diabetes mellitus. The discrepancy between reduced IR gene expression and increase in both phosphorylated IR tyrosine residues/protein tyrosine kinase activity may indicate imbalance between phosphorylation/dephosphorylation of the IR beta-subunit causing its dysfunction. These abnormalities may point to a complex brain insulin system dysfunction after STZ icv application, which may lead to an increase in hyperphosphorylated tau-protein concentration. Brain insulin system dysfunction is discussed as possible pathological core in the generation of hyperphosphorylated tau protein as a morphological marker of sporadic Alzheimer's disease.