TYPE I INTERFERON SCORE IS ASSOCIATED WITH THE SEVERITY AND POOR PROGNOSIS IN ANTI-MDA5 ANTIBODY-POSITIVE DERMATOMYOSITIS PATIENTS

BackgroundAnti-MDA5 antibody-positive dermatomyositis (anti-MDA5+DM) is a rare autoimmune disease associated with a high mortality rate due to rapid-progressive interstitial lung disease (RP-ILD), particularly in East Asia[1]. MDA5, acts as a cytoplasmic sensor of viral RNA, thus activating antiviral responses including the type I interferon (IFN) signaling pathway[2]. The involvement of type 1 IFN in the pathogenesis of MDA5+DM has been proposed based on the significantly elevated expression of its downstream stimulated genes(ISG) in muscle, skin, lung, and peripheral blood[3;4]. Janus kinase inhibitor, which targets the IFN pathway, combined with glucocorticoid could improve the survival of early-stage MDA5+DM-ILD patients[5]. In clinical practice, there is still an urgent demand for sensitive biomarkers to facilitate clinical risk assessment and precise treatment.ObjectivesThis study aimed to investigate the clinical significance of interferon score, especially IFN-I score, in patients with anti-MDA5+DM.MethodsDifferent subtypes of idiopathic inflammatory myopathy, including anti-MDA5+DM(n=61), anti-MDA5-DM(n=20), antisynthetase syndrome(ASS,n=22),polymyositis(PM,n=6) and immune-mediated necrotizing myopathy(IMNM,n=9), and 58 healthy controls were enrolled.. A multiplex quantitative real-time PCR(RT-qPCR) assay using four TaqMan probes was utilized to evaluate two type I ISGs (IFI44, MX1, which are used for IFN-I score), one type II ISG (IRF1), and one housekeeping gene (HRPT1). Clinical features and disease activity index were compared between high and low IFN-I score groups in 61 anti-MDA5+DM patients. The association between laboratory findings and the predictive value of baseline IFN-I score level for mortality was analyzed.ResultsThe IFN scores were significantly higher in patients with anti-MDA5+DM than in HC (Figure 1A). The IFN-I score correlated positively with serum IFN α(r = 0.335, P =0.008), ferritin (r = 0.302, P = 0.018), and Myositis Disease Activity Assessment Visual Analogue Scale (MYOACT) score(r=0.426, P=0.001). Compared with patients with low IFN-I scores, patients with high IFN-I scores showed increased MYOACT score, CRP, AST, ferritin, and the percentages of plasma cells (PC%) but decreased lymphocyte count, natural killer cell count, and monocyte count. The 3-month survival rate was significantly lower in patients with IFN-I score > 4.9 than in those with IFN-I score ≤ 4.9(72.9% vs. 100%, P=0.044)(Figure 1B).ConclusionIFN score, especially IFN-I score, detected by multiplex RT-qPCR, can be a valuable biomarker for monitoring disease activity and predicting mortality in anti-MDA5+DM patients.References[1]I.E. Lundberg, M. Fujimoto, J. Vencovsky, R. Aggarwal, M. Holmqvist, L. Christopher-Stine, A.L. Mammen, and F.W. Miller, Idiopathic inflammatory myopathies. Nat Rev Dis Primers 7 (2021) 86.[2]G. Liu, J.H. Lee, Z.M. Parker, D. Acharya, J.J. Chiang, M. van Gent, W. Riedl, M.E. Davis-Gardner, E. Wies, C. Chiang, and M.U. Gack, ISG15-dependent activation of the sensor MDA5 is antagonized by the SARS-CoV-2 papain-like protease to evade host innate immunity. Nat Microbiol 6 (2021) 467-478.[3]G.M. Moneta, D. Pires Marafon, E. Marasco, S. Rosina, M. Verardo, C. Fiorillo, C. Minetti, L. Bracci-Laudiero, A. Ravelli, F. De Benedetti, and R. Nicolai, Muscle Expression of Type I and Type II Interferons Is Increased in Juvenile Dermatomyositis and Related to Clinical and Histologic Features. Arthritis Rheumatol 71 (2019) 1011-1021.[4]Y. Ye, Z. Chen, S. Jiang, F. Jia, T. Li, X. Lu, J. Xue, X. Lian, J. Ma, P. Hao, L. Lu, S. Ye, N. Shen, C. Bao, Q. Fu, and X. Zhang, Single-cell profiling reveals distinct adaptive immune hallmarks in MDA5+ dermatomyositis with therapeutic implications. Nat Commun 13 (2022) 6458.[5]Z. Chen, X. Wang, and S. Ye, Tofacitinib in Amyopathic Dermatomyositis–Associated Interstitial Lung Disease. New England Journal of Medicine 381 (2019) 291-293.AcknowledgementsThis work was supported by the National Natural Science Foundation of China [81974251], and Shanghai Hospital Develop ent Center, Joint Research of New Advanced Technology Project [SHDC12018106]Disclosure of InterestsNone Declared.

Electrical Detection Assay Based on Programmable Nucleic Acid Probe for Efficient Single-Nucleotide Polymorphism Identification.

The large-scale pandemic and fast evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have triggered an urgent need for an efficient and sensitive on-site nucleic acid testing method with single-nucleotide polymorphism (SNP) identification capability. Here, we report a multiplexed electrical detection assay based on a paperclip-shaped nucleic acid probe (PNprobe) functionalized field-effect transistor (FET) biosensor for highly sensitive and specific detection and discrimination of SARS-CoV-2 variants. The three-stem structure of the PNprobe significantly amplifies the thermodynamic stability difference between variant RNAs that differ in a single-nucleotide mutation. With the assistance of combinatorial FET detection channels, the assay realizes simultaneously the detection and identification of key mutations of seven SARS-CoV-2 variants, including nucleotide substitutions and deletions at single-nucleotide resolution within 15 min. For 70 simulated throat swab samples, the multiplexed electrical detection assay shows an identification accuracy of 97.1% for the discrimination of SARS-CoV-2 variants. Our designed multiplexed electrical detection assay with SNP identification capability provides an efficient tool to achieve scalable pandemic screening.

Design Probes in a Pandemic: Two Tales of Hybrid Radical Placemaking from Ireland and Australia

Design probes, an essential research tool during the COVID-19 pandemic, are ancillary "personal"data gathering tools that enable researchers to enter the private world of research participants. This paper compares two case studies of design probes used during the pandemic for radical placemaking in hybrid digital-physical environments: Digital Art Summer School in Northrock, Ireland, with eleven participants, and Chatty Bench Project in Brisbane, Australia, with sixteen participants. The paper further expands on the design methodology of the probes and their deployment during the online radical placemaking projects. From the participant responses to the probes' activities and interviews, both studies demonstrated that the probes fostered placemaking in digital environments during the pandemic. The paper concludes with three lessons on the potential of probes as a critical research instrument to enable creativity, build social capital and create bonds between people and places during uncertain and turbulent times. © 2022 Owner/Author.

Characterizing the VPN Ecosystem in the Wild

With the increase of remote working during and after the COVID-19 pandemic, the use of Virtual Private Networks (VPNs) around the world has nearly doubled. Therefore, measuring the traffic and security aspects of the VPN ecosystem is more important now than ever. VPN users rely on the security of VPN solutions, to protect private and corporate communication. Thus a good understanding of the security state of VPN servers is crucial. Moreover, properly detecting and characterizing VPN traffic remains challenging, since some VPN protocols use the same port number as web traffic and port-based traffic classification will not help. In this paper, we aim at detecting and characterizing VPN servers in the wild, which facilitates detecting the VPN traffic. To this end, we perform Internet-wide active measurements to find VPN servers in the wild, and analyze their cryptographic certificates, vulnerabilities, locations, and fingerprints. We find 9.8M VPN servers distributed around the world using OpenVPN, SSTP, PPTP, and IPsec, and analyze their vulnerability. We find SSTP to be the most vulnerable protocol with more than 90% of detected servers being vulnerable to TLS downgrade attacks. Out of all the servers that respond to our VPN probes, 2% also respond to HTTP probes and therefore are classified as Web servers. Finally, we use our list of VPN servers to identify VPN traffic in a large European ISP and observe that 2.6% of all traffic is related to these VPN servers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Augmented Spaces: Introducing a Technology-Supported Home Environment to Improve our Mental Health during "Work from Home” Isolation

During the COVID-19 pandemic many restrictions were implemented to prevent the spread of the disease. These restrictions included working from home (WFH) and self-isolation. However, this situation had a negative impact on our mental health, causing depression and anxiety in many employees around the world. In this context, we hypothesized that our home spaces could become a catalyst of positive emotions through the use of technology-supported home environments, which use cyber-physical systems to reduce mental health symptoms during the lockdown. We used a qualitative approach, through interviews and cultural probes, to understand the experience of people who were forced to work from home during the lockdown. Additionally, we used a design science approach to explore technology-supported solutions that could enhance our home spaces. The result is a system that mixes analog and digital elements to create interactive rooms, which have a positive impact on people's well-being. © 2022 IEEE Computer Society. All rights reserved.

Technologies for Direct Detection of Covalent Protein-Drug Adducts.

In the past two decades, drug candidates with a covalent binding mode have gained the interest of medicinal chemists, as several covalent anticancer drugs have successfully reached the clinic. As a covalent binding mode changes the relevant parameters to rank inhibitor potency and investigate structure-activity relationship (SAR), it is important to gather experimental evidence on the existence of a covalent protein-drug adduct. In this work, we review established methods and technologies for the direct detection of a covalent protein-drug adduct, illustrated with examples from (recent) drug development endeavors. These technologies include subjecting covalent drug candidates to mass spectrometric (MS) analysis, protein crystallography, or monitoring intrinsic spectroscopic properties of the ligand upon covalent adduct formation. Alternatively, chemical modification of the covalent ligand is required to detect covalent adducts by NMR analysis or activity-based protein profiling (ABPP). Some techniques are more informative than others and can also elucidate the modified amino acid residue or bond layout. We will discuss the compatibility of these techniques with reversible covalent binding modes and the possibilities to evaluate reversibility or obtain kinetic parameters. Finally, we expand upon current challenges and future applications. Overall, these analytical techniques present an integral part of covalent drug development in this exciting new era of drug discovery.

Combining Cultural Probes and Interviews with Caregivers to Co-Design a Social Mobile Robotic Solution

Objectives: The objective of our research is to study the social organization within institutions welcoming dependent older adults and the potential impact of introducing a social robot. Material(s) and Method(s): In a co-design approach with professionals, the observation of behaviors, regulated by social rules and norms, will allow, in a way coherent with our empirical approach, to question the conditions necessary for the design of an acceptable human-robot interaction. The ethnographic observations, which were cancelled due to the Covid crisis, led us to use the "cultural probes" method combined with interviews, to understand the daily work of health professionals better. Result(s): The analysis of the collected data allows us to identify 5 recurrent themes - Time and personnel, the health situation,1 Communication/Attention, Guiding, Activities - for which we have listed, in this article, the issues encountered, the questions raised and ideas of potential solutions with the use of a social robot. Conclusion(s): The Cultural Probes approach may seem time-consuming and requires a significant investment, but it has allowed us to maintain regular contact during the pandemic. In addition, the qualitative data collected proved to be a good discussion tool.Copyright © 2022 AGBM

Characterizing the VPN Ecosystem in the Wild

With the increase of remote working during and after the COVID-19 pandemic, the use of Virtual Private Networks (VPNs) around the world has nearly doubled. Therefore, measuring the traffic and security aspects of the VPN ecosystem is more important now than ever. VPN users rely on the security of VPN solutions, to protect private and corporate communication. Thus a good understanding of the security state of VPN servers is crucial. Moreover, properly detecting and characterizing VPN traffic remains challenging, since some VPN protocols use the same port number as web traffic and port-based traffic classification will not help. In this paper, we aim at detecting and characterizing VPN servers in the wild, which facilitates detecting the VPN traffic. To this end, we perform Internet-wide active measurements to find VPN servers in the wild, and analyze their cryptographic certificates, vulnerabilities, locations, and fingerprints. We find 9.8M VPN servers distributed around the world using OpenVPN, SSTP, PPTP, and IPsec, and analyze their vulnerability. We find SSTP to be the most vulnerable protocol with more than 90% of detected servers being vulnerable to TLS downgrade attacks. Out of all the servers that respond to our VPN probes, 2% also respond to HTTP probes and therefore are classified as Web servers. Finally, we use our list of VPN servers to identify VPN traffic in a large European ISP and observe that 2.6% of all traffic is related to these VPN servers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Multiplex and Ultrasensitive Detection of Severe Acute Respiratory Syndrome Coronavirus 2 and Influenza A/B Nucleocapsid Proteins Based on Nanometer-Sized Core-Shell Superparamagnetic Antifouling Probes

Infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A (Flu A), and influenza B (Flu B) show similar clinical symptoms, such as cough, fever, and dyspnea, but patients infected by these viruses should be treated differently. The rapid and accurate diagnosis of infections caused by SARS-CoV-2, Flu A or Flu B is critical during the influenza season. Herein, we synthesized core-shell magnetic particles (MNPs) with excellent antifouling properties and applied them in the MNP-based immunochromatographic test (MICT) for simultaneous detection of SARS-CoV-2, Flu A, and Flu B nucleocapsid(N) proteins in 20 min. Two kinds of carboxyl-modified MNPs, MNP@pMBAA and MNP@Si-SA, were prepared and evaluated as probes in the MICT. Among them, the MNP@pMBAA showed lower nonspecific adsorption of proteins and low background noise in the application in MICTs. Particularly, the MNP@pMBAA50 bead-based MICT strip exhibited the highest signal-to-noise ratio for SARS-CoV-2 N protein detection with a limit of detection (LOD) of 0.072 ng/mL. Moreover, the proposed MICT strip demonstrated a minimal cross-reactivity and a broad linear dynamic detection range under a magnetic assay reader in the simultaneous detection of SARS-CoV-2, Flu A, and Flu B N proteins with relative LOD values of 0.0086, 0.012, and 0.018 ng/mL, respectively. The results demonstrated that the synthesized MNPs showed great potential for use as MICT probes for sensitive and multiplex detection of biomarkers in the development of point-of-care testing systems. © 2023 American Chemical Society.

Addressing loneliness in the workplace through human-robot interaction: Development and evaluation of a social office robot concept

New work has been a topic for a few years now and the COVID-19 pandemic has brought this trend more into focus, i.e., working remotely became more popular. However, besides various advantages, there is the risk of loneliness in employees, which can negatively affect their work performance and mental health. Research in different domains suggests that social robots could reduce loneliness. Since we were interested in whether and how such findings are transferable to the office context, we developed and tested a concept for a social office robot. More specifically, we first conducted a cultural probes study with white-collar workers to gain information about workplace loneliness and its drivers. Second, we explored design possibilities for a social office robot in a focus group. Based on the results, we created a concrete concept, Luca, which we finally evaluated and optimized with the help of interviews with participants from various industries. The present work contributes to HRI research and practice, e.g., by providing design recommendations for the implementation of a social office robot. Future research could investigate the effectiveness of a social office robot intervention in field studies. Next to implications for research and practice, potential limitations are discussed. © 2023 the author(s), published by De Gruyter, Berlin/Boston 2023.

Fast one-pot microwave-assisted green synthesis of highly fluorescent plant-inspired S,N-self-doped carbon quantum dots as a sensitive probe for the antiviral drug nitazoxanide and hemoglobin

In this study, we report a one-pot, green, cost-efficient, and fast synthesis of plant-based sulfur and nitrogen self-co-doped carbon quantum dots (S,N-CQDs). By 4-min microwave treatment of onion and cabbage juices as renewable, cheap, and green carbon sources and self-passivation agents, blue emissive S,N-CQDs have been synthesized (λex/λem of 340/418 nm) with a fluorescence quantum yield of 15.2%. A full characterization of the natural biomass-derived quantum dots proved the self-doping with nitrogen and sulfur. The S,N-CQDs showed high efficiency as a fluorescence probe for sensitive determination of nitazoxanide (NTZ), that recently found wide applicability as a repurposed drug for COVID-19, over the concentration range of 0.25–50.0 μM with LOD of 0.07 μM. The nanoprobe has been successfully applied for NTZ determination in pharmaceutical samples with excellent % recovery of 98.14 ± 0.42. Furthermore, the S,N-CQDs proved excellent performance as a sensitive fluorescence nanoprobe for determination of hemoglobin (Hb) over the concentration range of 36.3–907.5 nM with a minimum detectability of 10.30 nM. The probe has been applied for the determination of Hb in blood samples showing excellent agreement with the results documented by a medical laboratory. The greenness of the developed probe has been positively investigated by different greenness metrics and software. The green character of the proposed analytical methods originates from the synthesis of S,N-CQDs from sustainable, widely available, and cheap plants via low energy/low cost microwave-assisted technique. Omission of organic solvents and harsh chemicals beside dependence on mix-and-read analytical approach corroborate the method greenness. The obtained results demonstrated the substantial potential of the synthesized green, safe, cheap, and sustainable S,N-CQDs for pharmaceutical and biological applications. © 2022 Elsevier B.V.

COVIDGuardian: A Machine Learning approach for detecting the Three Cs

On January 30, 2020, WHO officially declared the outbreak of COVID-19 a Public Health Emergency of International Concern. Japan announced the state of emergency and implemented safety protocols the "Three Cs", a warning guideline addressing to voluntarily avoid potentially COVID-19 hazardous situations such as confined and closed spaces, crowded places and close-contact settings that lead to occurrence of serious clusters. The primary goal of this research is to identify the factors which help to estimate whether the user is in the Three Cs. We propose COVIDGuardian, a system that detects the Three Cs based on data such as CO2, temperature, humidity, and wireless packet log. The results show that estimation of closed space had the highest accuracy followed by close-contact settings and crowded places. The ensemble Random Forest (RF) classifier demonstrates the highest accuracy and F score in detecting closed spaces and crowded spaces. The findings indicated that integrated loudness value, average CO2, average humidity, probe request log, and average RSSI are of critical importance. In addition, when the probe request logs were filtered at three RSSI cutoff points (1m, 3m, and 5m), 1m cut-off points had the highest accuracy and F Score among the Three C models. © 2022 Copyright held by the owner/author(s).

Feeling our way: methodological explorations on researching touch through uncertainty

This paper argues that methodological uncertainty, such as that experienced by the social research community through the COVID-19 pandemic (2020–2022) is, and has always been, a vital part of the research landscape. Whilst recognising the many damaging effects of the uncertainties of the pandemic on research and researchers, we home in on the potential of the challenges raised by uncertainty as a force for methodological innovation. We introduce three InTouch project research studies conducted during Lockdown and reflect on the methodological challenges raised by the change and uncertainty of the pandemic. We describe our use, adaptation and reorientation of creative, sensory, and speculative methods to overcome these challenges. We reflect on how we mobilised the uncertain methodological terrain of digital touch and social research in the pandemic as a resource for methodological innovation. [ FROM AUTHOR]

In silico evaluation of the impact of Omicron variant of concern sublineage BA.4 and BA.5 on the sensitivity of RT-qPCR assays for SARS-CoV-2 detection using whole genome sequencing.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern (VoC) Omicron (B.1.1.529) has rapidly spread around the world, presenting a new threat to global public human health. Due to the large number of mutations accumulated by SARS-CoV-2 Omicron, concerns have emerged over potentially reduced diagnostic accuracy of reverse-transcription polymerase chain reaction (RT-qPCR), the gold standard diagnostic test for diagnosing coronavirus disease 2019 (COVID-19). Thus, we aimed to assess the impact of the currently endemic Omicron sublineages BA.4 and BA.5 on the integrity and sensitivity of RT-qPCR assays used for coronavirus disease 2019 (COVID-19) diagnosis via in silico analysis. We employed whole genome sequencing data and evaluated the potential for false negatives or test failure due to mismatches between primers/probes and the Omicron VoC viral genome. METHODS: In silico sensitivity of 12 RT-qPCR tests (containing 30 primers and probe sets) developed for detection of SARS-CoV-2 reported by the World Health Organization (WHO) or available in the literature, was assessed for specifically detecting SARS-CoV-2 Omicron BA.4 and BA.5 sublineages, obtained after removing redundancy from publicly available genomes from National Center for Biotechnology Information (NCBI) and Global Initiative on Sharing Avian Influenza Data (GISAID) databases. Mismatches between amplicon regions of SARS-CoV-2 Omicron VoC and primers and probe sets were evaluated, and clustering analysis of corresponding amplicon sequences was carried out. RESULTS: From the 1164 representative SARS-CoV-2 Omicron VoC BA.4 sublineage genomes analyzed, a substitution in the first five nucleotides (C to T) of the amplicon's 3'-end was observed in all samples resulting in 0% sensitivity for assays HKUnivRdRp/Hel (mismatch in reverse primer) and CoremCharite N (mismatch in both forward and reverse primers). Due to a mismatch in the forward primer's 5'-end (3-nucleotide substitution, GGG to AAC), the sensitivity of the ChinaCDC N assay was at 0.69%. The 10 nucleotide mismatches in the reverse primer resulted in 0.09% sensitivity for Omicron sublineage BA.4 for Thai N assay. Of the 1926 BA.5 sublineage genomes, HKUnivRdRp/Hel assay also had 0% sensitivity. A sensitivity of 3.06% was observed for the ChinaCDC N assay because of a mismatch in the forward primer's 5'-end (3-nucleotide substitution, GGG to AAC). Similarly, due to the 10 nucleotide mismatches in the reverse primer, the Thai N assay's sensitivity was low at 0.21% for sublineage BA.5. Further, eight assays for BA.4 sublineage retained high sensitivity (more than 97%) and 9 assays for BA.5 sublineage retained more than 99% sensitivity. CONCLUSION: We observed four assays (HKUnivRdRp/Hel, ChinaCDC N, Thai N, CoremCharite N) that could potentially result in false negative results for SARS-CoV-2 Omicron VoCs BA.4 and BA.5 sublineages. Interestingly, CoremCharite N had 0% sensitivity for Omicron Voc BA.4 but 99.53% sensitivity for BA.5. In addition, 66.67% of the assays for BA.4 sublineage and 75% of the assays for BA.5 sublineage retained high sensitivity. Further, amplicon clustering and additional substitution analysis along with sensitivity analysis could be used for the modification and development of RT-qPCR assays for detecting SARS-CoV-2 Omicron VoC sublineages.

COVIDGuardian: A Machine Learning approach for detecting the Three Cs

On January 30, 2020, WHO officially declared the outbreak of COVID-19 a Public Health Emergency of International Concern. Japan announced the state of emergency and implemented safety protocols the "Three Cs", a warning guideline addressing to voluntarily avoid potentially COVID-19 hazardous situations such as confined and closed spaces, crowded places and close-contact settings that lead to occurrence of serious clusters. The primary goal of this research is to identify the factors which help to estimate whether the user is in the Three Cs. We propose COVIDGuardian, a system that detects the Three Cs based on data such as CO2, temperature, humidity, and wireless packet log. The results show that estimation of closed space had the highest accuracy followed by close-contact settings and crowded places. The ensemble Random Forest (RF) classifier demonstrates the highest accuracy and F score in detecting closed spaces and crowded spaces. The findings indicated that integrated loudness value, average CO2, average humidity, probe request log, and average RSSI are of critical importance. In addition, when the probe request logs were filtered at three RSSI cutoff points (1m, 3m, and 5m), 1m cut-off points had the highest accuracy and F Score among the Three C models. © 2022 Copyright held by the owner/author(s).

Palpation Robot System - Reproduction Method by Deep Neural Network of Skin Palpation Judgment Focusing on Softness Classification

In recent years, the spread of infectious diseases, such as COVID-19, has increased the need for medical examinations to avoid contact between doctors and patients. Most treatments, especially dermatology, require palpation, and its impact is significant. In this study, we aimed to reproduce the judgment of the softness and surface textures of diseased parts, which is important to dermatologists for determining the condition, using a simple robot device. Five levels of softness and three types of surface textures labeled with 14 types of materials were obtained from interviews with dermatologists. To acquire a haptic response from materials during pushing, 1) a single-rod probe with a haptic sensor using a linear actuator and 2) a dual-rod type configuration to obtain vibration propagation was constructed. Frequency-analyzed images were produced from the obtained waveforms of force and acceleration. A total of 343 images from 13 materials were used for transfer learning and were classified using AlexNet. The classification accuracy of the single-rod probe was 93.0%, and that of the dual-probe configuration was 95.2%. The classification accuracy was improved using the dual probe configuration than the single one;the softness classification accuracy was improved from 93.8% (single-rod) to 95.7% (dual-rod configuration). The surface texture classification accuracy was improved from 91.9% (single-rod) to 92.8% (dual-rod configuration), respectively. Therefore, the proposed method enables the reproduction of the judgment of five-level softness and three types of surface texture judgment by dermatologists. © 2022 IEEE.

Multi-modal lung ultrasound image classification by fusing image-based features and probe information

Lung ultrasound is a widely used portable, cheap, and non-invasive medical imaging technology that can be used to identify various lung pathologies. In this work, we propose a multi-modal approach for lung ultrasound image classification that combines image-based features with information about the type of ultrasound probe used to acquire the input image. Experiments on a large lung ultrasound image dataset that contains images acquired with a linear or a convex ultrasound probe demonstrated the superiority of the proposed approach for the task of classifying lung ultrasound images as "COVID-19”, "Normal”, "Pneumonia”, or "Other”, when compared to simply using image-based features. Classification accuracy reached 99.98% using the proposed combination of the Xception pre-trained CNN model with the ultrasound probe information, as opposed to 96.81% when only the pre-trained EfficientNetB4 CNN model was used. Furthermore, the experimental results demonstrated a consistent improvement in classification performance when combining the examined base CNN models with probe information, indicating the efficiency of the proposed approach. © 2022 IEEE.

Gaining resolution when creating imagery of aging.

In seeking to support healthy aging, designers have struggled to reduce their assumptions and biases toward older adults, been seen to interpret the worlds of later life through unfiltered imagery, as well as engage with stigmas, ultimately diminishing the technologies they construct. This article seeks to critically analyse this state-of-the-art from a design research perspective while engaging with the growing interdisciplinary study of aging and technologies. Toward this, we proposition "resolution" as a concept indicative of the level of detail that seeks to characterize the fidelity that representations of later life have. This concept is explored through a cultural probe study that investigated the sentiments of several older Australians regarding the inequities and social isolation brought on by the COVID-19 pandemic. Providing a diary alongside photovoice and mapping tasks, the study captured perceptions of social technology, practices, networks, and wellbeing, offering a diverse and complex picture of aging and technology. Through reflexive thematic analyses of some of these materials, this case study offers designers pathways to understanding and including older adults in their work. In determining the resolution of these images of aging, we discuss how transparency about the limitations and qualities of such participatory methods through incorporating reflexivity can influence the degree of detail such imagery gains. Ultimately this concept builds on the notion of participation configuration, supporting designers to realize better images of aging and representations of later life.

Characterization of the Ubiquitin and ISG15 Deconjugase Activity of SARS-CoV-1 and SARS-CoV-2 Papain-Like Protease.

Both severe acute respiratory syndrome coronavirus 1 and 2 (SARS-CoV-1 and SARS-CoV-2) encode a papain-like protease (PLpro), which plays a vital role in viral propagation. PLpro accomplishes this function by processing the viral polyproteins essential for viral replication and removing the small proteins, ubiquitin and ISG15 from the host's key immune signaling proteins, thereby preventing the host's innate immune response. Although PLpro from both SARS-CoV-1 and SARS-CoV-2 are structurally highly similar (83% sequence identity), they exhibit functional variability. Hence, to further elucidate the mechanism and aid in drug discovery efforts, the biochemical and kinetic characterization of PLpro is needed. This chapter describes step-by-step experimental procedures for evaluating PLpro activity in vitro using activity-based probes (ABPs) along with fluorescence-based substrates. Herein we describe a step-by-step experimental procedure to assess the activity of PLpro in vitro using a suite of activity-based probes (ABPs) and fluorescent substrates and how they can be applied as fast and yet sensitive methods to calculate kinetic parameters.

Editorial to the Special Issue: “High-Energy Gamma-Ray Astronomy: Results on Fundamental Questions after 30 Years of Ground-Based Observations”

In the presence of other particles, photons or magnetic fields, cosmic rays lose energy by emitting gamma rays and other carriers of astrophysical information, such as neutrinos. The combined observation of these probes, whose origin is closely linked, make up the multi-messenger astronomy framework, of which gamma-rays are the key ingredient. Since the discovery of the first TeV-emitting source a little over 30 years ago, ground-based gamma-ray astronomy, and in particular the imaging air-Cherenkov technique (IACT), has been a major actor in the many revolutions witnessed in the field of astro-particle physics. Cosmology and cosmic ray physics are discussed by L. Tibaldo, D. Gaggero and P. Martin in “Gamma Rays as Probes of Cosmic-Ray Propagation and Interactions in Galaxies” [8], by A. Franceschini in “Photon–Photon Interactions and the Opacity of the Universe in Gamma Rays” [9] and by R. Alves Batista and A. Saveliev in “The Gamma-ray Window to Intergalactic Magnetism” [10], reporting on the limits obtained with gamma-rays in the intergalactic magnetic field. [...]IACTs have proven to be great probes of fundamental physics topics, specially dark matter (DM) searches.