Universal adversarial attacks on deep neural networks for medical image classification

Deep neural networks (DNNs) are widely investigated in medical image classification to achieve automated support for clinical diagnosis. It is necessary to evaluate the robustness of medical DNN tasks against adversarial attacks, as high-stake decision-making will be made based on the diagnosis. Several previous studies have considered simple adversarial attacks. However, the vulnerability of DNNs to more realistic and higher risk attacks, such as universal adversarial perturbation (UAP), which is a single perturbation that can induce DNN failure in most classification tasks has not been evaluated yet

Natural images allow universal adversarial attacks on medical image classification using deep neural networks with transfer learning

Transfer learning from natural images is used in deep neural networks (DNNs) for medical image classification to achieve a computer-aided clinical diagnosis. Although the adversarial vulnerability of DNNs hinders practical applications owing to the high stakes of diagnosis, adversarial attacks are expected to be limited because training datasets (medical images), which are often required for adversarial attacks, are generally unavailable in terms of security and privacy preservation. Nevertheless, in this study, we demonstrated that adversarial attacks are also possible using natural images for medical DNN models with transfer learning, even if such medical images are unavailable; in particular, we showed that universal adversarial perturbations (UAPs) can also be generated from natural images. UAPs from natural images are useful for both non-targeted and targeted attacks. The performance of UAPs from natural images was significantly higher than that of random controls. The use of transfer learning causes a security hole, which decreases the reliability and safety of computer-based disease diagnosis. Model training from random initialization reduced the performance of UAPs from natural images; however, it did not completely avoid vulnerability to UAPs. The vulnerability of UAPs to natural images is expected to become a significant security threat

DOCK2 is involved in the host genetics and biology of severe COVID-19

「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target

Universal adversarial attacks on deep neural networks for medical image classification

Deep neural networks (DNNs) are widely investigated in medical image classification to achieve automated support for clinical diagnosis. It is necessary to evaluate the robustness of medical DNN tasks against adversarial attacks, as high-stake decision-making will be made based on the diagnosis. Several previous studies have considered simple adversarial attacks. However, the vulnerability of DNNs to more realistic and higher risk attacks, such as universal adversarial perturbation (UAP), which is a single perturbation that can induce DNN failure in most classification tasks has not been evaluated yet

Inhalation Administration of Valerena-4,7(11)-diene from Nardostachys chinensis Roots Ameliorates Restraint Stress-Induced Changes in Murine Behavior and Stress-Related Factors

Dried Nardostachys chinensis roots contain sesquiterpenoids that are widely used as herbal tranquilizers. We previously identified the highly sedative sesquiterpenoid valerena-4,7(11)-diene (VLD) from this plant. In the present study, we investigated stress reducing effects of VLD and the associated mechanisms of action. Application of 15-min restraint stresses induced excitatory behaviors in mice. Immobility times in the forced swim test and sleeping times in the pentobarbital sleep test were shortened in the stressed group by 47% and 43%, respectively, compared with the control group. Furthermore, restraint stress increased serum corticosterone levels by 75%, and cerebral serotonin (5-HT) and dopamine (DA) levels. Inhaled VLD (300 µg/cage) suppressed stress-induced excitatory behaviors and significantly reduced stress-induced blood corticosterone, cerebral 5-HT, and DA levels. These results suggest that VLD interacts with the hypothalamic–pituitary–adrenal axis and the sympathetic-adrenomedullary system. These interactions appear to involve GABAergic and D2 antagonist activities. Moreover, tests in anosmic and intravenously treated mice showed that the sedative effect of inhaled VLD was expressed via olfactory stimulation and pulmonary absorption. Although more studies are required to further elucidate the properties of this compound, our studies suggest that VLD may be an effective anti-stress aromatherapy for humans

Measurement of neutron spectra for photonuclear reaction with linearly polarized photons

Spectra of neutrons produced by a photonuclear reaction from a 197Au target were measured using 16.95 MeV linearly and circularly polarized photon beams at NewSUBARU-BL01 using a time-of-flight method. The difference in the neutron spectra between the cases of a linearly and circularly polarized photon was measured. The difference in the neutron yield increased with the neutron energy and was approximately threefold at the maximum neutron energy. In a direction perpendicular to that of the linear polarization, the neutron yields decreased as the neutron energy increased