Attention-Based Fault-Tolerant Approach for Multi-Agent Reinforcement Learning Systems

The aim of multi-agent reinforcement learning systems is to provide interacting agents with the ability to collaboratively learn and adapt to the behavior of other agents. Typically, an agent receives its private observations providing a partial view of the true state of the environment. However, in realistic settings, the harsh environment might cause one or more agents to show arbitrarily faulty or malicious behavior, which may suffice to allow the current coordination mechanisms fail. In this paper, we study a practical scenario of multi-agent reinforcement learning systems considering the security issues in the presence of agents with arbitrarily faulty or malicious behavior. The previous state-of-the-art work that coped with extremely noisy environments was designed on the basis that the noise intensity in the environment was known in advance. However, when the noise intensity changes, the existing method has to adjust the configuration of the model to learn in new environments, which limits the practical applications. To overcome these difficulties, we present an Attention-based Fault-Tolerant (FT-Attn) model, which can select not only correct, but also relevant information for each agent at every time step in noisy environments. The multihead attention mechanism enables the agents to learn effective communication policies through experience concurrent with the action policies. Empirical results showed that FT-Attn beats previous state-of-the-art methods in some extremely noisy environments in both cooperative and competitive scenarios, much closer to the upper-bound performance. Furthermore, FT-Attn maintains a more general fault tolerance ability and does not rely on the prior knowledge about the noise intensity of the environment

Plasma‐based microRNA signatures in early diagnosis of breast cancer

Abstract Background MicroRNAs (miRNAs) play an important role in the development and progression of breast cancer (BC). The purpose of the present study was to identify plasma miRNAs enabling early diagnosis of BC. Materials and Methods Expression levels of seven plasma miRNAs (miR‐23a‐3p, miR‐29b‐2‐5p, miR‐130a‐5p, miR‐144‐3p, miR‐148a‐3p, miR‐152‐3p, and miR‐182‐5p) in 106 patients with newly diagnosed BC and 96 healthy participants were analyzed by qRT‐PCR. We also evaluated the relationship between the expression levels of these miRNAs and clinicopathological features of patients with BC. Results Compared with healthy controls, we found that miR‐23a‐3p (p = .025), miR‐130a‐5p (p = .006), miR‐144‐3p (p = .040), miR‐148a‐3p (p = .023), and miR‐152‐3p (p = .019) were downregulated in the plasma of patients with BC. MiR‐130a‐5p, miR‐144‐3p, and miR‐152‐3p were downexpressed in BC tissues as well as plasma. The expression of the miR‐23a‐3p, miR‐144‐3p, and miR‐152‐3p was related to ER positive and PR positive. Besides, miR‐23a‐3p, miR‐144‐3p, and miR‐152‐3p did show the significant difference in the staging compromised to the control, especially in stage I‐II. Moreover, we also found that miR‐144‐3p and miR‐148a‐3p were associated with lymph node invasion. Conclusions The expression levels of the miR‐23a‐3p, miR‐130a‐5p, miR‐144‐3p, miR‐148a‐3p, and miR‐152‐3p were lower in patients with BC compared to healthy controls and were associated with ex hormone receptor, clinical stage, and lymph node metastasis, indicating the diagnostic potential of these miRNAs in BC

Association between ACYP2

Abstract Background Kidney cancer is the predominant form of malignancy of the kidney and accounts for approximately 3%–4% of all cancers. Renal cell cancer (RCC) represents more than 85% of kidney cancer. It has been reported that genetic factors may predispose individuals to RCC. This study evaluated the association between Acylphosphatase 2 (ACYP2) gene polymorphisms and RCC risk in the Han Chinese population. Methods Twelve single‐nucleotide polymorphisms (SNPs) in ACYP2 were genotyped using the Agena MassARRAY platform from 293 RCC patients and 495 controls. The Chi‐squared test, genetic models, haplotype, and stratification analyses were used to evaluate the association between SNPs and the risk of RCC. The relative risk was estimated using the odds ratio (OR) and 95% confidence interval (CI). Results We observed that the rs6713088 allele G (OR = 1.26, 95% CI: 1.03–1.53, p = .023) and rs843711 allele T (OR = 1.29, 95% CI: 1.06–1.57, p = .010) were associated with increased RCC risk. Genetic model analyses found that rs843711 was significantly associated with an increased RCC risk under the recessive model and log‐additive model after adjusting for age and gender. Haplotype analysis showed that the haplotype “TTCTCGCC” (OR = 0.67, 95% CI: 0.48–0.94, p = .021) was associated with a decreased risk of RCC in the Han Chinese population. Stratification analysis also found that rs6713088 and rs843711 were significantly associated with increased RCC risk. Conclusion In summary, the results suggested that ACYP2 polymorphisms could be used as a genetic marker for RCC. Additional functional and association studies are required to validate our results

Image-guided dendritic cell-based vaccine immunotherapy in murine carcinoma models.

In recent decades, immunotherapy has undergone extensive developments for oncologic therapy applications. Dendritic cells (DCs) plays a fundamental role in cell-based vaccination immunotherapy against various types of cancer. It involves stimulating innate and adaptive immunity, in particular cytotoxic T-cell mediated antitumor effects, against targeted tumors and has been studied in both preclinical and clinical settings. Nevertheless, clinical outcomes have been unsatisfying. The antitumor response requires sufficient migration of viable DCs from primary administration site to targeted tumors through related lymphatics. The dynamics and mechanisms of the DCs migration still need further investigation. Here, we briefly introduce the current clinically applicable methods for manufacturing DC-based cancer vaccines and their most commonly used non-invasive, real-time tracking approaches. Furthermore, we propose a hypothesis that intraperitoneal injection may improve the efficiency of DC-based cancer vaccine

18F-FDG PET Biomarkers Help Detect Early Metabolic Response to Irreversible Electroporation and Predict Therapeutic Outcomes in a Rat Liver Tumor Model.

Purpose To test the hypothesis that biomarkers of fluorine 18 (18F) fluorodeoxyglucose (FDG) positron emission tomography (PET) can be used for the early detection of therapeutic response to irreversible electroporation (IRE) of liver tumor in a rodent liver tumor model. Materials and Methods The institutional animal care and use committee approved this study. Rats were inoculated with McA-RH7777 liver tumor cells in the left median and left lateral lobes. Tumors were allowed to grow for 7 days to reach a size typically at least 5 mm in longest diameter, as verified with magnetic resonance (MR) imaging. IRE electrodes were inserted, and eight 100-μsec, 2000-V pulses were applied to ablate the tumor tissue in the left median lobe. Tumor in the left lateral lobe served as a control in each animal. PET/computed tomography (CT) and MR imaging measurements were performed at baseline and 3 days after IRE for each animal. Additional MR imaging measurements were obtained 14 days after IRE. After 14-day follow-up MR imaging, rats were euthanized and tumors harvested for hematoxylin-eosin, CD34, and caspase-3 staining. Change in the maximum standardized uptake value (ΔSUVmax) was calculated 3 days after IRE. The maximum lesion diameter change (ΔDmax) was measured 14 days after IRE by using axial T2-weighted imaging. ΔSUVmax and ΔDmax were compared. The apoptosis index was calculated by using caspase-3-stained slices of apoptotic tumor cells. Pearson correlation coefficients were calculated to assess the relationship between ΔSUVmax at 3 days and ΔDmax (or apoptosis index) at 14 days after IRE treatment. Results ΔSUVmax, ΔDmax, and apoptosis index significantly differed between treated and untreated tumors (P < .001 for all). In treated tumors, there was a strong correlation between ΔSUVmax 3 days after IRE and ΔDmax 14 days after IRE (R = 0.66, P = .01) and between ΔSUVmax 3 days after IRE and apoptosis index 14 days after IRE (R = 0.57, P = .04). Conclusion 18F-FDG PET imaging biomarkers can be used for the early detection of therapeutic response to IRE treatment of liver tumors in a rodent model. © RSNA, 2017