LSP Framework: A Compensatory Model for Defeating Trigger Reverse Engineering via Label Smoothing Poisoning

Deep neural networks are vulnerable to backdoor attacks. Among the existing backdoor defense methods, trigger reverse engineering based approaches, which reconstruct the backdoor triggers via optimizations, are the most versatile and effective ones compared to other types of methods. In this paper, we summarize and construct a generic paradigm for the typical trigger reverse engineering process. Based on this paradigm, we propose a new perspective to defeat trigger reverse engineering by manipulating the classification confidence of backdoor samples. To determine the specific modifications of classification confidence, we propose a compensatory model to compute the lower bound of the modification. With proper modifications, the backdoor attack can easily bypass the trigger reverse engineering based methods. To achieve this objective, we propose a Label Smoothing Poisoning (LSP) framework, which leverages label smoothing to specifically manipulate the classification confidences of backdoor samples. Extensive experiments demonstrate that the proposed work can defeat the state-of-the-art trigger reverse engineering based methods, and possess good compatibility with a variety of existing backdoor attacks

Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

Local features at neighboring spatial positions in feature maps have high correlation since their receptive fields are often overlapped. Self-attention usually uses the weighted sum (or other functions) with internal elements of each local feature to obtain its weight score, which ignores interactions among local features. To address this, we propose an effective interaction-aware self-attention model inspired by PCA to learn attention maps. Furthermore, since different layers in a deep network capture feature maps of different scales, we use these feature maps to construct a spatial pyramid and then utilize multi-scale information to obtain more accurate attention scores, which are used to weight the local features in all spatial positions of feature maps to calculate attention maps. Moreover, our spatial pyramid attention is unrestricted to the number of its input feature maps so it is easily extended to a spatio-temporal version. Finally, our model is embedded in general CNNs to form end-to-end attention networks for action classification. Experimental results show that our method achieves the state-of-the-art results on the UCF101, HMDB51 and untrimmed Charades.Comment: Accepted by ECCV201

Learning from Easy to Complex: Adaptive Multi-curricula Learning for Neural Dialogue Generation

Current state-of-the-art neural dialogue systems are mainly data-driven and are trained on human-generated responses. However, due to the subjectivity and open-ended nature of human conversations, the complexity of training dialogues varies greatly. The noise and uneven complexity of query-response pairs impede the learning efficiency and effects of the neural dialogue generation models. What is more, so far, there are no unified dialogue complexity measurements, and the dialogue complexity embodies multiple aspects of attributes---specificity, repetitiveness, relevance, etc. Inspired by human behaviors of learning to converse, where children learn from easy dialogues to complex ones and dynamically adjust their learning progress, in this paper, we first analyze five dialogue attributes to measure the dialogue complexity in multiple perspectives on three publicly available corpora. Then, we propose an adaptive multi-curricula learning framework to schedule a committee of the organized curricula. The framework is established upon the reinforcement learning paradigm, which automatically chooses different curricula at the evolving learning process according to the learning status of the neural dialogue generation model. Extensive experiments conducted on five state-of-the-art models demonstrate its learning efficiency and effectiveness with respect to 13 automatic evaluation metrics and human judgments.Comment: Accepted to AAAI 202

CRISPR-Cas13 in malaria parasite: Diagnosis and prospective gene function identification

Malaria caused by Plasmodium is still a serious public health problem. Genomic editing is essential to understand parasite biology, elucidate mechanical pathways, uncover gene functions, identify novel therapeutic targets, and develop clinical diagnostic tools. Recent advances have seen the development of genomic diagnostic technologies and the emergence of genetic manipulation toolbox comprising a host of several systems for editing the genome of Plasmodium at the DNA, RNA, and protein level. Genomic manipulation at the RNA level is critical as it allows for the functional characterization of several transcripts. Of notice, some developed artificial RNA genome editing tools hinge on the endogenous RNA interference system of Plasmodium. However, Plasmodium lacks a robust RNAi machinery, hampering the progress of these editing tools. CRISPR-Cas13, which belongs to the VI type of the CRISPR system, can specifically bind and cut RNA under the guidance of crRNA, with no or minimal permanent genetic scar on genes. This review summarizes CRISPR-Cas13 system from its discovery, classification, principle of action, and diagnostic platforms. Further, it discusses the application prospects of Cas13-based systems in Plasmodium and highlights its advantages and drawbacks

Association between weekend catch-up sleep and glycemic control among individuals with diabetes: a population-based study

ObjectivesWeekend catch-up sleep (WCUS), a compensation for insufficient sleep during weekdays, was associated with desirable metabolic effects. However, its relationship with glycemic control among adults with diabetes was not fully established.MethodsParticipants from the 2017-2018 cycle of the National Health and Nutrition Examination Survey were included for analysis. WCUS was defined as a difference in sleep duration between weekends and weekdays of more than one hour. Glycemic control was assessed by hemoglobin A1C (HbA1c) and fasting plasma glucose levels. Poor glycemic control was defined as an HbA1c level exceeding 10.0%.ResultsThe final analysis included 571 participants (weighted number: 38,714,135), and 24.90% of them practicing WCUS. No significant association was found between glycemic control and the presence of WCUS. However, significant negative associations were noted between WCUS with a duration of 1-2 hours and HbA1c level [β= -0.82, 95% CI: (-1.34, -0.30), P=0.004] and fasting glucose level [β= -1.67, 95% CI: (-2.51, -0.82), P<0.001] when compared with participants with no WCUS, which remained consistent across different subgroups. In addition, it was also associated with a reduced risk of developing poor glycemic control (OR=0.10, 95% CI: (0.01, 0.60), P=0.015). With WCUS duration of ≥ 2 hours, such associations became not significant.ConclusionsWCUS for 1-2 hours was associated with lower levels of HbA1c and fasting glucose and reduced risk of developing poor glycemic control, while a duration of ≥ 2 hours was not. Further research is needed to determine the optimal duration of WCUS

The regulation of trophoblastic p53 homeostasis by the p38-WIP1 feedback loop is disturbed in placentas from pregnancies complicated by preeclampsia

Background/Aims: Excessive apoptosis of trophoblasts, induced by sustained hypoxia, leads to abnormal placentation and is strongly linked to pregnancy complications such as preeclampsia (PE). Wild-type p53-induced phosphatase (Wip1) positively regulates cellular survival in tumor cells through the p38 and p53 pathways, but its expression pattern and effects in trophoblasts have yet to be reported. This study clarified the effect of Wip1 on the regulatory mechanism of p53-dependent apoptosis in trophoblasts, and thus increases understanding of the etiology of PE. Methods: In normal and PE placentas, Wip1 mRNA and protein levels were determined by RT-qPCR and Western blotting respectively, while localization of Wip1 in placental tissues and in HTR8/SVneo cells was determined by immunohistochemistry and immunofluorescence. Two in vitro trophoblastic PE models were established by subjecting HTR8/SVneo cells to either hypoxia intervention in incubator (HII) or simulated ischemic buffer (SIB). Wip1 was suppressed in the aforementioned PE models by specific inhibitor or shRNA, and apoptosis was then assessed by flow cytometry, while further validation was done by measurement of cleaved-caspase 9 expression by Western blotting. The p38 inhibitor SB202190, Mdm2 inhibitor NVP-CGM097, and proteasome inhibitor MG- 132 were administered in PE models, either in combination or alone, to determine the regulatory order of the component signal molecules of the feedback loop. The impact of Wip1 on p53-Mdm2 interaction was examined by coimmunoprecipitation. Lastly, the upregulation of the p38-Wip1 loop was confirmed in human placentas from pregnancies complicated by PE, using Western blotting. Results: Wip1 expression was significantly elevated in human PE placentas and in vitro trophoblastic PE models; this is opposite to the pattern observed in tumor cells. Inhibition of Wip1 rescued hypoxia-induced p38 activation, cleavage of caspase 9 and apoptosis but significantly compromised p53-Mdm2 binding, while p-p53Ser15 was increased. Inhibition of Mdm2 degradation resulted in p53 destabilization and p38-Wip1 loop down-regulation, while degradation of the p53-Mdm2 complex resulted in p53 accumulation and p38-Wip1 loop hyperactivation. However, the p53-Mdm2 interaction was found to be more important in the regulation of the p38-Wip1 loop than Mdm2 stability. Conclusion: Trophoblastic p53 homeostasis is maintained by the p38-Wip1 feedback regulatory loop in response to hypoxic stress, which is dysregulated in the placentas of pregnancies complicated by PE, and thereby leads to excessive apoptosis

AMPK regulates homeostasis of invasion and viability in trophoblasts by redirecting glucose metabolism: Implications for pre-eclampsia

Pre-eclampsia (PE) is deemed an ischemia-induced metabolic disorder of the placenta due to defective invasion of trophoblasts during placentation; thus, the driving role of metabolism in PE pathogenesis is largely ignored. Since trophoblasts undergo substantial glycolysis, this study aimed to investigate its function and regulatory mechanism by AMPK in PE development. Metabolomics analysis of PE placentas was performed by gas chromatography–mass spectrometry (GC–MS). Trophoblast-specific AMPKα1-deficient mouse placentas were generated to assess morphology. A mouse PE model was established by Reduced Uterine Perfusion Pressure, and placental AMPK was modulated by nanoparticle-delivered A769662. Trophoblast glucose uptake was measured by 2-NBDG and 2-deoxy-d-[3H] glucose uptake assays. Cellular metabolism was investigated by the Seahorse assay and GC–MS.PE complicated trophoblasts are associated with AMPK hyperactivation due not to energy deficiency. Thereafter, AMPK activation during placentation exacerbated PE manifestations but alleviated cell death in the placenta. AMPK activation in trophoblasts contributed to GLUT3 translocation and subsequent glucose metabolism, which were redirected into gluconeogenesis, resulting in deposition of glycogen and accumulation of phosphoenolpyruvate; the latter enhanced viability but compromised trophoblast invasion. However, ablation of AMPK in the mouse placenta resulted in decreased glycogen deposition and structural malformation. These data reveal a novel homeostasis between invasiveness and viability in trophoblasts, which is mechanistically relevant for switching between the ‘go’ and ‘grow’ cellular programs