Few-Shot Keypoint Detection as Task Adaptation via Latent Embeddings

Dense object tracking, the ability to localize specific object points with pixel-level accuracy, is an important computer vision task with numerous downstream applications in robotics. Existing approaches either compute dense keypoint embeddings in a single forward pass, meaning the model is trained to track everything at once, or allocate their full capacity to a sparse predefined set of points, trading generality for accuracy. In this paper we explore a middle ground based on the observation that the number of relevant points at a given time are typically relatively few, e.g. grasp points on a target object. Our main contribution is a novel architecture, inspired by few-shot task adaptation, which allows a sparse-style network to condition on a keypoint embedding that indicates which point to track. Our central finding is that this approach provides the generality of dense-embedding models, while offering accuracy significantly closer to sparse-keypoint approaches. We present results illustrating this capacity vs. accuracy trade-off, and demonstrate the ability to zero-shot transfer to new object instances (within-class) using a real-robot pick-and-place task

Vector-based navigation using grid-like representations in artificial agents

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go. Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex. Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space and is critical for integrating self-motion (path integration) and planning direct trajectories to goals (vector-based navigation). Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types12. We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments—optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation, demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments

Treating Brain Tumor with Microbeam Radiation Generated by a Compact Carbon-Nanotube-Based Irradiator: Initial Radiation Efficacy Study

Microbeam radiation treatment (MRT) using synchrotron radiation has shown great promise in the treatment of brain tumors, with a demonstrated ability to eradicate the tumor while sparing normal tissue in small animal models. With the goal of expediting the advancement of MRT research beyond the limited number of synchrotron facilities in the world, we recently developed a compact laboratory-scale microbeam irradiator using carbon nanotube (CNT) field emission-based X-ray source array technology. The focus of this study is to evaluate the effects of the microbeam radiation generated by this compact irradiator in terms of tumor control and normal tissue damage in a mouse brain tumor model. Mice with U87MG human glioblastoma were treated with sham irradiation, low-dose MRT, high-dose MRT or 10 Gy broad-beam radiation treatment (BRT). The microbeams were 280 µm wide and spaced at 900 µm center-to-center with peak dose at either 48 Gy (low-dose MRT) or 72 Gy (high-dose MRT). Survival studies showed that the mice treated with both MRT protocols had a significantly extended life span compared to the untreated control group (31.4 and 48.5% of life extension for low- and high-dose MRT, respectively) and had similar survival to the BRT group. Immunostaining on MRT mice demonstrated much higher DNA damage and apoptosis level in tumor tissue compared to the normal brain tissue. Apoptosis in normal tissue was significantly lower in the low-dose MRT group compared to that in the BRT group at 48 h postirradiation. Interestingly, there was a significantly higher level of cell proliferation in the MRT-treated normal tissue compared to that in the BRT-treated mice, indicating rapid normal tissue repairing process after MRT. Microbeam radiation exposure on normal brain tissue causes little apoptosis and no macrophage infiltration at 30 days after exposure. This study is the first biological assessment on MRT effects using the compact CNT-based irradiator. It provides an alternative technology that can enable widespread MRT research on mechanistic studies using a preclinical model, as well as further translational research towards clinical applications

Overcoming catastrophic forgetting in neural networks

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks that they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on a hand-written digit dataset and by learning several Atari 2600 games sequentially

Image-guided microbeam irradiation to brain tumour bearing mice using a carbon nanotube x-ray source array

Microbeam radiation therapy (MRT) is a promising experimental and preclinical radiotherapy method for cancer treatment. Synchrotron based MRT experiments have shown that spatially fractionated microbeam radiation has the unique capability of preferentially eradicating tumour cells while sparing normal tissue in brain tumour bearing animal models. We recently demonstrated the feasibility of generating orthovoltage microbeam radiation with an adjustable microbeam width using a carbon nanotube based X-ray source array. Here we report the preliminary results from our efforts in developing an image guidance procedure for the targeted delivery of the narrow microbeams to the small tumour region in the mouse brain. Magnetic resonance imaging was used for tumour identification, and on-board X-ray radiography was used for imaging of landmarks without contrast agents. The two images were aligned using 2D rigid body image registration to determine the relative position of the tumour with respect to a landmark. The targeting accuracy and consistency were evaluated by first irradiating a group of mice inoculated with U87 human glioma brain tumours using the present protocol and then determining the locations of the microbeam radiation tracks using γ-H2AX immunofluorescence staining. The histology results showed that among 14 mice irradiated, 11 received the prescribed number of microbeams on the targeted tumour, with an average localization accuracy of 454 μm measured directly from the histology (537 μm if measured from the registered histological images). Two mice received one of the three prescribed microbeams on the tumour site. One mouse was excluded from the analysis due to tissue staining errors

Mammary Involution and Breast Cancer Risk: Transgenic Models and Clinical Studies

Postlactational involution is the process following weaning during which the mammary gland undergoes massive cell death and tissue remodeling as it returns to the pre-pregnant state. Lobular involution is the process by which the breast epithelial tissue is gradually lost with aging of the mammary gland. While postlactational involution and lobular involution are distinct processes, recent studies have indicated that both are related to breast cancer development. Experiments using a variety of rodent models, as well as observations in human populations, suggest that deregulation of postlactational involution may act to facilitate tumor formation. By contrast, new human studies show that completion of lobular involution protects against subsequent breast cancer incidence

Insulin-like growth factor (IGF)-I obliterates the pregnancy-associated protection against mammary carcinogenesis in rats: evidence that IGF-I enhances cancer progression through estrogen receptor-α activation via the mitogen-activated protein kinase pathway

INTRODUCTION: Pregnancy protects against breast cancer development in humans and rats. Parous rats have persistently reduced circulating levels of growth hormone, which may affect the activity of the growth hormone/insulin-like growth factor (IGF)-I axis. We investigated the effects of IGF-I on parity-associated protection against mammary cancer. METHODS: Three groups of rats were evaluated in the present study: IGF-I-treated parous rats; parous rats that did not receive IGF-I treatment; and age-matched virgin animals, which also did not receive IGF-I treatment. Approximately 60 days after N-methyl-N-nitrosourea injection, IGF-I treatment was discontinued and all of the animal groups were implanted with a silastic capsule containing 17β-estradiol and progesterone. The 17β-estradiol plus progesterone treatment continued for 135 days, after which the animals were killed. RESULTS: IGF-I treatment of parous rats increased mammary tumor incidence to 83%, as compared with 16% in parous rats treated with 17β-estradiol plus progesterone only. Tumor incidence and average number of tumors per animal did not differ between IGF-I-treated parous rats and age-matched virgin rats. At the time of N-methyl-N-nitrosourea exposure, DNA content was lowest but the α-lactalbumin concentration highest in the mammary glands of untreated parous rats in comparison with age-matched virgin and IGF-I-treated parous rats. The protein levels of estrogen receptor-α in the mammary gland was significantly higher in the age-matched virgin animals than in untreated parous and IGF-I-treated parous rats. Phosphorylation (activation) of the extracellular signal-regulated kinase-1/2 (ERK1/2) and expression of the progesterone receptor were both increased in IGF-I-treated parous rats, as compared with those in untreated parous and age-matched virgin rats. Expressions of cyclin D(1 )and transforming growth factor-β(3 )in the mammary gland were lower in the age-matched virgin rats than in the untreated parous and IGF-I-treated parous rats. CONCLUSION: We argue that tumor initiation (transformation and fixation of mutations) may be similar in parous and age-matched virgin animals, suggesting that the main differences in tumor formation lie in differences in tumor progression caused by the altered hormonal environment associated with parity. Furthermore, we provide evidence supporting the notion that tumor growth promotion seen in IGF-I-treated parous rats is caused by activation of estrogen receptor-α via the Raf/Ras/mitogen-activated protein kinase cascade

Favorable prognostic value of SOCS2 and IGF-I in breast cancer

<p>Abstract</p> <p>Background</p> <p>Suppressor of cytokine signaling (SOCS) proteins comprise a protein family, which has initially been described as STAT induced inhibitors of the Jak/Stat pathway. Recent in vivo and in vitro studies suggest that SOCS proteins are also implicated in cancer. The STAT5 induced IGF-I acts as an endocrine and para/autocrine growth and differentiation factor in mammary gland development. Whereas high levels of circulating IGF-I have been associated with increased cancer risk, the role of autocrine acting IGF-I is less clear. The present study is aimed to elucidate the clinicopathological features associated with SOCS1, SOCS2, SOCS3, CIS and IGF-I expression in breast cancer.</p> <p>Methods</p> <p>We determined the mRNA expression levels of SOCS1, SOCS2, SOCS3, CIS and IGF-I in 89 primary breast cancers by reverse transcriptase PCR. SOCS2 protein expression was further evaluated by immuno-blot and immunohistochemistry.</p> <p>Results</p> <p>SOCS2 expression inversely correlated with histopathological grade and ER positive tumors exhibited higher SOCS2 levels. Patients with high SOCS2 expression lived significantly longer (108.7 vs. 77.7 months; P = 0.015) and high SOCS2 expression proved to be an independent predictor for good prognosis (HR = 0.45, 95% CI 0.23 – 0.91, P = 0.026). In analogy to SOCS2, high IGF-I expression was an independent predictor for good prognosis in the entire patient cohort. In the subgroup of patients with lymph-node negative disease, high IGF-I was a strong predictor for favorable outcome in terms of overall survival and relapse free survival (HR = 0.075, 95% CI 0.014 – 0.388, P = 0.002).</p> <p>Conclusion</p> <p>This is the first report on the favorable prognostic value of high SOCS2 expression in primary mammary carcinomas. Furthermore a strong association of high IGF-I expression levels with good prognosis was observed especially in lymph-node negative patients. Our results suggest that high expression of the STAT5 target genes SOCS2 and IGF-I is a feature of differentiated and less malignant tumors.</p

Knockout and transgenic mice of Trp53: what have we learned about p53 in breast cancer?

The human p53 tumor suppressor gene TP53 is mutated at a high frequency in sporadic breast cancer, and Li-Fraumeni syndrome patients who carry germline mutations in one TP53 allele have a high incidence of breast cancer. In the 10 years since the first knockout of the mouse p53 tumor suppressor gene (designated Trp53) was published, much has been learned about the contribution of p53 to biology and tumor suppression in the breast through the use of p53 transgenic and knockout mice. The original mice deficient in p53 showed no mammary gland phenotype. However, studies using BALB/c-Trp53-deficient mice have demonstrated a delayed involution phenotype and a mammary tumor phenotype. Together with other studies of mutant p53 transgenes and p53 bitransgenics, a greater understanding has been gained of the role of p53 in involution, of the regulation of p53 activity by hormones, of the effect of mouse strain and modifier genes on tumor phenotype, and of the cooperation between p53 and other oncogenic pathways, chemical carcinogens and hormonal stimulation in mammary tumorigenesis. Both p53 transgenic and knockout mice are important in vivo tools for understanding breast cancer, and are yet to be exploited for developing therapeutic strategies in breast cancer