Parkinson's disease (PD) is a neurodegenerative disease characterized by the selective loss of dopaminergic neurons in the substantia nigra (SN). In a previous study, the authors demonstrated that ferritin heavy chain 1 (FTH1) inhibited ferroptosis in a model of 6‑hydroxydopamine (6‑OHDA)‑induced PD. However, whether and how microRNAs (miRNAs/miRs) modulate FTH1 in PD ferroptosis is not yet well understood. In the present study, in vivo and in vitro models of PD induced by 6‑OHDA were established. The results in vivo and in vitro revealed that the levels of the ferroptosis marker protein, glutathione peroxidase 4 (GPX4), and the PD marker protein, tyrosine hydroxylase (TH), were decreased in the model group, associated with a decreased FTH1 expression and the upregulation of miR‑335. In both the in vivo and in vitro models, miR‑335 mimic led to a lower FTH1 expression, exacerbated ferroptosis and an enhanced PD pathology. The luciferase 3'‑untranslated region reporter results identified FTH1 as the direct target of miR‑335. The silencing of FTH1 in 6‑OHDA‑stimulated cells enhanced the effects of miR‑335 on ferroptosis and promoted PD pathology. Mechanistically, miR‑335 enhanced ferroptosis through the degradation of FTH1 to increase iron release, lipid peroxidation and reactive oxygen species (ROS) accumulation, and to decrease mitochondrial membrane potential (MMP). On the whole, the findings of the present study reveal that miR‑335 promotes ferroptosis by targeting FTH1 in in vitro and in vivo models of PD, providing a potential therapeutic target for the treatment of PD.
Deep neural networks (DNN) have become a common sensing modality in autonomous systems as they allow for semantically perceiving the ambient environment given input images. Nevertheless, DNN models have proven to be vulnerable to adversarial digital and physical attacks. To mitigate this issue, several detection frameworks have been proposed to detect whether a single input image has been manipulated by adversarial digital noise or not. In our prior work, we proposed a real-time detector, called VisionGuard (VG), for adversarial physical attacks against single input images to DNN models. Building upon that work, we propose VisionGuard* (VG), which couples VG with majority-vote methods, to detect adversarial physical attacks in time-series image data, e.g., videos. This is motivated by autonomous systems applications where images are collected over time using onboard sensors for decision-making purposes. We emphasize that majority-vote mechanisms are quite common in autonomous system applications (among many other applications), as e.g., in autonomous driving stacks for object detection. In this paper, we investigate, both theoretically and experimentally, how this widely used mechanism can be leveraged to enhance the performance of adversarial detectors. We have evaluated VG* on videos of both clean and physically attacked traffic signs generated by a state-of-the-art robust physical attack. We provide extensive comparative experiments against detectors that have been designed originally for out-of-distribution data and digitally attacked images.
Abstract The emergence and development of artemisinin resistance threaten global malaria control and elimination goals, thereby prompting research on the mechanisms of malaria parasite resistance. The mutation of Plasmodium falciparum Kelch 13 ( PfK13) protein is associated with artemisinin resistance, but the unique or common mechanism by which it leads to this resistance is unclear. By analyzing the different effects of PfK13 mutation on the P. falciparum transcriptome and proteome at the different stages, we found that PfK13 mutation did not significantly change glycolysis, TCA, pentose phosphate pathway (PPP) and oxidative phosphorylation but reduced the expression of reproduction- and DNA synthesis-related genes. Moreover, the reduced number of the merozoite, decreased amount of hemozoin, and slowed growth of P. falciparum 3D7C580Y were consistent with the changes, suggesting that the PfK13 mutation reduces hemoglobin ingestion, leading to artemisinin resistance, likely by decreasing the parasites' need for haem and iron. This study helps elucidate the mechanism of artemisinin resistance caused by the PfK13 mutation.
Abstract Babesia spp. are intraerythrocytic apicomplexan organisms digesting hemoglobin similar to intraerythrocytic Plasmodium spp. However, unlike Plasmodium spp., Babesia spp. are not sensitive to artemisinin, The difference between Babesia genomes and Plasmodium genomes revealed that smaller Babesia genomes lack numerous genes, especially haem synthesis-related genes. Single-cell sequencing analysis showed that different groups of B. microti with expressed pentose phosphate pathway (PPP)-related, DNA replication-related, antioxidation-related, glycolysis-related, and glutathione-related genes were not as sensitive to artemether as P. yoelii 17XNL . Especially, PPP-related, DNA replication-related, and glutathione-related genes were inactively expressed compared with P. yoelii 17XNL . Adding iron supply in vivo can promote the reproduction of B. microti . These results suggest that Babesia spp. lack a similar mechanism to that in malaria parasites, by which haem or iron in hemoglobin is utilized, but it likely leads to their insensitivity to artemisinin in turn. Author summary Babesia and Plasmodium are similar in many ways, from morphology to life history. In particular, both ingest and break down hemoglobin. However, compared with Plasmodium , Babesia cannot form hemozoin with less pathogenicity and insensitivity to artemisinin. Recent studies suggest that artemisinin can kill malaria parasites through free-radical and iron-capture effects, indicating that iron and haem play a key role in the sensitivity of malaria parasites to artemisinin. The Babesia genome is smaller and does not contain haem synthesis-related genes, indicating low requirements and utilization of haem and iron (HI). Moreover, we found that the expression of PPP-related and DNA replication-related genes is not active, distinctly different from malaria parasites. However, adding iron supply in vivo can increase the infection rate of B. microti . Therefore, we hypothesized that Babesia lacks mechanisms for the efficient utilization of HI, resulting in low requirements for HI, and therefore insensitivity to artemisinin.
Deep learning models have shown extreme vulnerability to distribution shifts such as synthetic perturbations and spatial transformations. In this work, we explore whether we can adopt the characteristics of adversarial attack methods to help improve robustness of object detection to distribution shifts such as synthetic perturbations and spatial transformations. We study a class of realistic object detection settings wherein the target objects have control over their appearance. To this end, we propose a reversed Fast Gradient Sign Method (FGSM) to obtain these angelic patches that significantly increase the detection probability, even without pre-knowledge of the perturbations. In detail, we apply the patch to each object instance simultaneously, strengthening not only classification, but also bounding box accuracy. Experiments demonstrate the efficacy of the partial-covering patch in solving the complex bounding box problem. More importantly, the performance is also transferable to different detection models even under severe affine transformations and deformable shapes. To the best of our knowledge, we are the first object detection patch that achieves both cross-model efficacy and multiple patches. We observed average accuracy improvements of 30% in the real-world experiments. Our code is available at: https://github.com/averysi224/angelic_patches.
The FH/DS hybrid spread spectrum technology integrates the advantages of direct sequence spread spectrum and frequency hopping spread spectrum technologies in terms of resistance to multipath interference, anti-tracking interference, and interception. At the same time, it overcomes significant near-far effect and poor concealment performance. It is widely used in military communication systems worldwide. However, the unique structure of FH/DS signals directly increases the difficulty of synchronization scheme design and implementation. In this paper, taking the context of inter-ballistic, inter-satellite, and ground-to-ballistic networking as a background, a new frequency hopping signal capture algorithm is proposed using the sync header method and combined with the slow scanning strategy. The algorithm adopts a new strategy of extending the slow scanning time during the frequency hopping demodulation process to expand the number of effectively accumulated frequency points, thus achieving energy accumulation under low signal-to-noise ratio conditions. In the phase search part, a half-hop is used as the search step for signal detection, maximizing the utilizttion of synchronization hop resources. Overall, this algorithm saves more than 50% of the synchronization resources and reduces the capture time to half of that of the original sync header method, thereby improving the survival probability of the communication system.
The combination of frequency diverse array (FDA) with range-angle-time dependent beampattern and waveform diversity in multiple input multiple output (MIMO) radar, namely, FDA-MIMO radar, offers additional degrees-of-freedom to enhance the overall system performance. The existing parameter estimation algorithms for FDA-MIMO radar are difficult to achieve effective target estimation when there is amplitude-phase error in the array antenna. In this paper, the proposed method can achieve the calibration and estimation for FDA-MIMO radar with random amplitude and phase errors. First, the signal model for FDA-MIMO radar signal model with random amplitude and phase errors is established. Second, the angle and range estimation is obtained by the spectral peak search method with reduced dimension. Then, the amplitude and phase error of each array element are estimated by the singular value decomposition and eigenvalue decomposition. Finally, the multiple simulation experiments show that in the presence of amplitude and phase errors, the existing algorithms have completely failed, but the proposed algorithm still has the ability to estimate the target with high precision.
Abstract Background The emergence and spread of artemisinin resistance threaten global malaria control and elimination goals, and encourage research on the mechanisms of drug resistance in malaria parasites. Mutations in Plasmodium falciparum Kelch 13 ( Pf K13) protein are associated with artemisinin resistance, but the unique or common mechanism which results in this resistance is unclear. Methods We analyzed the effects of the Pf K13 mutation on the transcriptome and proteome of P. falciparum at different developmental stages. Additionally, the number of merozoites, hemozoin amount, and growth of P. falciparum 3D7 C580Y and P. falciparum 3D7 WT were compared. The impact of iron supplementation on the number of merozoites of P. falciparum 3D7 C580Y was also examined. Results We found that the Pf K13 mutation did not significantly change glycolysis, TCA, pentose phosphate pathway, or oxidative phosphorylation, but did reduce the expression of reproduction- and DNA synthesis-related genes. The reduced number of merozoites, decreased level of hemozoin, and slowed growth of P. falciparum 3D7 C580Y were consistent with these changes. Furthermore, adding iron supply could increase the number of the merozoites of P. falciparum 3D7 C580Y . Conclusions These results revealed that the Pf K13 mutation reduced hemoglobin ingestion, leading to artemisinin resistance, likely by decreasing the parasites' requirement for haem and iron. This study helps elucidate the mechanism of artemisinin resistance due to Pf K13 mutations. Graphical Abstract
AbstractBackground Depression is a psychiatric disorder which affects many aspects of social life of patients; however, the molecular biological mechanisms underlying its development are not fully understood. Atypical phase separation is a mechanism contributing to the occurrence of neurological disorders. The interaction between autophagy and iron metabolism have been implicated in the pathogenesis of neurological diseases.Methods To explore the pathogenesis of depression, we analyzed super-enhancers (SEs) in the prefrontal cortex of depression model rats using chromatin immunoprecipitation sequencing (ChIP-seq). The role of the upstream protein Bromodomain Containing 2 (BRD2) in super-enhancers (SEs) was investigated by synthesizing liquid-liquid phase separation proteins in vitro which were examined through Fluorescence recovery after photobleaching (FRAP) analysis. Moreover, the markers of ferritinophagy in cortisol-stimulated primary cortical neuron cells and PC12 cell models were explored to the occurrence of ferritinophagy in depression models.Results Rats exposed to chronic mild stress (CMS) exhibited decreased activation of autophagy-related 7 (ATG7) mediated by SEs. In rats subjected to CMS and in cellular models of depression, ferritinophagy was detected. Arid5a stimulated ATG7 activation via SEs and was influenced by the BET family and liquid-liquid phase separation. Ferritinophagy dysfunction in cellular models of depression was dependent on ATG7. BRD2 exhibited aberrant phase separation in CMS rats. The BET inhibitor JQ1 alleviated depressive behavior in rats subjected to CMS.Conclusions The ATG7 genes are activated by SEs in cellular and animal models of depression. The increased transcriptional activity of ATG7 can increase the risk of ferritinophagy. Moreover, the phase separation of BRD2 promotes ATG7 expression via SEs.
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