Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards

In this paper, we study the problem of (finite horizon tabular) Markov decision processes (MDPs) with heavy-tailed rewards under the constraint of differential privacy (DP). Compared with the previous studies for private reinforcement learning that typically assume rewards are sampled from some bounded or sub-Gaussian distributions to ensure DP, we consider the setting where reward distributions have only finite $(1+v)$-th moments with some $v \in (0,1]$. By resorting to robust mean estimators for rewards, we first propose two frameworks for heavy-tailed MDPs, i.e., one is for value iteration and another is for policy optimization. Under each framework, we consider both joint differential privacy (JDP) and local differential privacy (LDP) models. Based on our frameworks, we provide regret upper bounds for both JDP and LDP cases and show that the moment of distribution and privacy budget both have significant impacts on regrets. Finally, we establish a lower bound of regret minimization for heavy-tailed MDPs in JDP model by reducing it to the instance-independent lower bound of heavy-tailed multi-armed bandits in DP model. We also show the lower bound for the problem in LDP by adopting some private minimax methods. Our results reveal that there are fundamental differences between the problem of private RL with sub-Gaussian and that with heavy-tailed rewards.Comment: ICML 2023. arXiv admin note: text overlap with arXiv:2009.09052 by other author

The Analysis of Vertical Transaction Behavior and Performance Based on Automobile Brand Trust in Supply Chain

The nontrust behaviors among the automobile supply chain members lead to a trust crisis situation. Under such circumstances, this paper studies the mutual influences of trust, enterprise behavior, and transaction performance on the independent brand automobile supply chain. The business behavior concept which consists of information sharing, joint action, and specific asset investment is proposed. Then, the paper tests the reliability and validity of the collected data through Structural Equation Modeling (SEM). Through empirical test and analysis on mutual relationship among vertical transaction enterprise behaviors, trust, and transaction performance, the vertical transaction enterprise behaviors can be regulated, so as to improve the efficiency of independent brand automobile supply chain

Pathologic complete response of hepatoid adenocarcinoma of the stomach after chemo-immunotherapy: A rare case report and literature review

BackgroundHepatoid adenocarcinoma of the stomach (HAS) is a highly malignant subtype of gastric carcinoma with specific clinicopathological features and extremely poor prognosis. We present an exceedingly rare case of complete response after chemo-immunotherapy.Case DescriptionA 48-year-old woman with highly elevated serum alpha-fetoprotein (AFP) level was found to have HAS verified by pathological examination based on gastroscopy. Computed tomography scan was done and TNM staging of the tumor was T4aN3aMx. Programmed cell death ligand-1 (PD-L1) immunohistochemistry was performed, revealing a negative PD-L1 expression. Chemo-immunotherapy including oxaliplatin plus S-1 and PD-1 inhibitor terelizumab was given to this patient for 2 months until the serum AFP level decreased from 748.5 to 12.9 ng/mL and the tumor shrank. D2 radical gastrectomy was then performed and histopathology of the resected specimen revealed that the cancerous cells had disappeared. Pathologic complete response (pCR) was achieved and no evidence of recurrence has been found after 1 year of follow-up.ConclusionsWe, for the first time, reported an HAS patient with negative PD-L1 expression who achieved pCR from the combined chemotherapy and immunotherapy. Although no consensus has been reached regarding the therapy, it might provide a potential effective management strategy for HAS patient

Differences in Physicochemical and Nutritional Properties of Breast and Thigh Meat from Crossbred Chickens, Commercial Broilers, and Spent Hens

The objective of this study was to compare the physicochemical and nutritional properties of breast and thigh meat from commercial Chinese crossbred chickens (817 Crossbred chicken, 817C), imported commercial broilers (Arbor Acres broiler, AAB), and commercial spent hens (Hyline Brown, HLB). The crossbred chickens, commercial broilers and spent hens were slaughtered at their typical market ages of 45 d, 40 d, and 560 d, respectively. The results revealed that several different characteristic features for the three breeds. The meat of the 817C was darker than that of the other two genotypes. The 817C were also characterized by higher protein, lower intramuscular fat, and better texture attributes (cooking loss, pressing loss and Warner-Bratzler shear force [WBSF]) compared with AAB and HLB. The meat of the spent hens (i.e. HLB) was higher in WBSF and total collagen content than meat of the crossbred chickens and imported broilers. Furthermore, correlation analysis and principal component analysis revealed that there was a clear relationship among physicochemical properties of chicken meats. With regard to nutritional properties, it was found that 817C and HLB exhibited higher contents of essential amino acids and essential/non-essential amino acid ratios. In addition, 817C were noted to have highest content of microelements whereas AAB have highest content of potassium. Besides, 817C birds had particularly higher proportions of desirable fatty acids, essential fatty acids, polyunsaturated/saturated and (18:0+18:1)/16:0 ratios. The present study also revealed that there were significant differences on breast meat and thigh meat for the physicochemical and nutritional properties, regardless of chicken breeds. In conclusion, meat of crossbred chickens has some unique features and exhibited more advantages over commercial broilers and spent hens. Therefore, the current investigation would provide valuable information for the chicken meat product processing, and influence the consumption of different chicken meat

Wip1-dependent modulation of macrophage migration and phagocytosis

Macrophage accumulation within the vascular wall is a hallmark of atherosclerosis. Controlling macrophage conversion into foam cells remains a major challenge for treatment of atherosclerotic diseases. Here, we show that Wip1, a member of the PP2C family of Ser/Thr protein phosphatases, modulates macrophage migration and phagocytosis associated with atherosclerotic plaque formation. Wip1 deficiency increases migratory and phagocytic activities of the macrophage under stress conditions. Enhanced migration of Wip1-/- macrophages is mediated by Rac1-GTPase and PI3K/AKT signalling pathways. Elevated phagocytic ability of Wip1-/- macrophages is linked to CD36 plasma membrane recruitment that is regulated by AMPK activity. Our study identifies Wip1 as an intrinsic negative regulator of macrophage chemotaxis. We propose that Wip1-dependent control of macrophage function may provide avenues for preventing or eliminating plaque formation in atherosclerosis

Construction and validation of a risk prediction model for aromatase inhibitor-associated bone loss

PurposeTo establish a high-risk prediction model for aromatase inhibitor-associated bone loss (AIBL) in patients with hormone receptor-positive breast cancer.MethodsThe study included breast cancer patients who received aromatase inhibitor (AI) treatment. Univariate analysis was performed to identify risk factors associated with AIBL. The dataset was randomly divided into a training set (70%) and a test set (30%). The identified risk factors were used to construct a prediction model using the eXtreme gradient boosting (XGBoost) machine learning method. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression methods were used for comparison. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the model in the test dataset.ResultsA total of 113 subjects were included in the study. Duration of breast cancer, duration of aromatase inhibitor therapy, hip fracture index, major osteoporotic fracture index, prolactin (PRL), and osteocalcin (OC) were found to be independent risk factors for AIBL (p < 0.05). The XGBoost model had a higher AUC compared to the logistic model and LASSO model (0.761 vs. 0.716, 0.691).ConclusionThe XGBoost model outperformed the logistic and LASSO models in predicting the occurrence of AIBL in patients with hormone receptor-positive breast cancer receiving aromatase inhibitors

A novel dilated contextual attention module for breast cancer mitosis cell detection

Background and object: Mitotic count (MC) is a critical histological parameter for accurately assessing the degree of invasiveness in breast cancer, holding significant clinical value for cancer treatment and prognosis. However, accurately identifying mitotic cells poses a challenge due to their morphological and size diversity.Objective: We propose a novel end-to-end deep-learning method for identifying mitotic cells in breast cancer pathological images, with the aim of enhancing the performance of recognizing mitotic cells.Methods: We introduced the Dilated Cascading Network (DilCasNet) composed of detection and classification stages. To enhance the model’s ability to capture distant feature dependencies in mitotic cells, we devised a novel Dilated Contextual Attention Module (DiCoA) that utilizes sparse global attention during the detection. For reclassifying mitotic cell areas localized in the detection stage, we integrate the EfficientNet-B7 and VGG16 pre-trained models (InPreMo) in the classification step.Results: Based on the canine mammary carcinoma (CMC) mitosis dataset, DilCasNet demonstrates superior overall performance compared to the benchmark model. The specific metrics of the model’s performance are as follows: F1 score of 82.9%, Precision of 82.6%, and Recall of 83.2%. With the incorporation of the DiCoA attention module, the model exhibited an improvement of over 3.5% in the F1 during the detection stage.Conclusion: The DilCasNet achieved a favorable detection performance of mitotic cells in breast cancer and provides a solution for detecting mitotic cells in pathological images of other cancers

Crystal Structure of the Caenorhabditis elegans Apoptosome Reveals an Octameric Assembly of CED-4

SummaryThe CED-4 homo-oligomer or apoptosome is required for initiation of programmed cell death in Caenorhabditis elegans by facilitating autocatalytic activation of the CED-3 caspase zymogen. How the CED-4 apoptosome assembles and activates CED-3 remains enigmatic. Here we report the crystal structure of the complete CED-4 apoptosome and show that it consists of eight CED-4 molecules, organized as a tetramer of an asymmetric dimer via a previously unreported interface among AAA+ ATPases. These eight CED-4 molecules form a funnel-shaped structure. The mature CED-3 protease is monomeric in solution and forms an active holoenzyme with the CED-4 apoptosome, within which the protease activity of CED-3 is markedly stimulated. Unexpectedly, the octameric CED-4 apoptosome appears to bind only two, not eight, molecules of mature CED-3. The structure of the CED-4 apoptosome reveals shared principles for the NB-ARC family of AAA+ ATPases and suggests a mechanism for the activation of CED-3