Showing papers by "University of Erlangen-Nuremberg published in 2021"

Plasma Hsp90 levels in patients with systemic sclerosis and relation to lung and skin involvement: a cross-sectional and longitudinal study.

Abstract: Our previous study demonstrated increased expression of Heat shock protein (Hsp) 90 in the skin of patients with systemic sclerosis (SSc). We aimed to evaluate plasma Hsp90 in SSc and characterize its association with SSc-related features. Ninety-two SSc patients and 92 age-/sex-matched healthy controls were recruited for the cross-sectional analysis. The longitudinal analysis comprised 30 patients with SSc associated interstitial lung disease (ILD) routinely treated with cyclophosphamide. Hsp90 was increased in SSc compared to healthy controls. Hsp90 correlated positively with C-reactive protein and negatively with pulmonary function tests: forced vital capacity and diffusing capacity for carbon monoxide (DLCO). In patients with diffuse cutaneous (dc) SSc, Hsp90 positively correlated with the modified Rodnan skin score. In SSc-ILD patients treated with cyclophosphamide, no differences in Hsp90 were found between baseline and after 1, 6, or 12 months of therapy. However, baseline Hsp90 predicts the 12-month change in DLCO. This study shows that Hsp90 plasma levels are increased in SSc patients compared to age-/sex-matched healthy controls. Elevated Hsp90 in SSc is associated with increased inflammatory activity, worse lung functions, and in dcSSc, with the extent of skin involvement. Baseline plasma Hsp90 predicts the 12-month change in DLCO in SSc-ILD patients treated with cyclophosphamide.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Extracellular vesicles as a next-generation drug delivery platform.

Abstract: Extracellular-vesicle-based cell-to-cell communication is conserved across all kingdoms of life. There is compelling evidence that extracellular vesicles are involved in major (patho)physiological processes, including cellular homoeostasis, infection propagation, cancer development and cardiovascular diseases. Various studies suggest that extracellular vesicles have several advantages over conventional synthetic carriers, opening new frontiers for modern drug delivery. Despite extensive research, clinical translation of extracellular-vesicle-based therapies remains challenging. Here, we discuss the uniqueness of extracellular vesicles along with critical design and development steps required to utilize their full potential as drug carriers, including loading methods, in-depth characterization and large-scale manufacturing. We compare the prospects of extracellular vesicles with those of the well established liposomes and provide guidelines to direct the process of developing vesicle-based drug delivery systems. In this Review the authors discuss the biological role of extracellular vesicles and how they can be applied as drug carriers, focusing on the current state of their manufacturing and existing challenges.

Quantum approximate optimization of non-planar graph problems on a planar superconducting processor

Abstract: Faster algorithms for combinatorial optimization could prove transformative for diverse areas such as logistics, finance and machine learning. Accordingly, the possibility of quantum enhanced optimization has driven much interest in quantum technologies. Here we demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA). Like past QAOA experiments, we study performance for problems defined on the planar connectivity graph native to our hardware; however, we also apply the QAOA to the Sherrington–Kirkpatrick model and MaxCut, non-native problems that require extensive compilation to implement. For hardware-native problems, which are classically efficient to solve on average, we obtain an approximation ratio that is independent of problem size and observe that performance increases with circuit depth. For problems requiring compilation, performance decreases with problem size. Circuits involving several thousand gates still present an advantage over random guessing but not over some efficient classical algorithms. Our results suggest that it will be challenging to scale near-term implementations of the QAOA for problems on non-native graphs. As these graphs are closer to real-world instances, we suggest more emphasis should be placed on such problems when using the QAOA to benchmark quantum processors. It is hoped that quantum computers may be faster than classical ones at solving optimization problems. Here the authors implement a quantum optimization algorithm over 23 qubits but find more limited performance when an optimization problem structure does not match the underlying hardware.

Machine learning and deep learning

Abstract: Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. Deep learning is a machine learning concept based on artificial neural networks. For many applications, deep learning models outperform shallow machine learning models and traditional data analysis approaches. In this article, we summarize the fundamentals of machine learning and deep learning to generate a broader understanding of the methodical underpinning of current intelligent systems. In particular, we provide a conceptual distinction between relevant terms and concepts, explain the process of automated analytical model building through machine learning and deep learning, and discuss the challenges that arise when implementing such intelligent systems in the field of electronic markets and networked business. These naturally go beyond technological aspects and highlight issues in human-machine interaction and artificial intelligence servitization.

The eROSITA X-ray telescope on SRG

Abstract: eROSITA (extended ROentgen Survey with an Imaging Telescope Array) is the primary instrument on the Spectrum-Roentgen-Gamma (SRG) mission, which was successfully launched on July 13, 2019, from the Baikonour cosmodrome. After the commissioning of the instrument and a subsequent calibration and performance verification phase, eROSITA started a survey of the entire sky on December 13, 2019. By the end of 2023, eight complete scans of the celestial sphere will have been performed, each lasting six months. At the end of this program, the eROSITA all-sky survey in the soft X-ray band (0.2–2.3 keV) will be about 25 times more sensitive than the ROSAT All-Sky Survey, while in the hard band (2.3–8 keV) it will provide the first ever true imaging survey of the sky. The eROSITA design driving science is the detection of large samples of galaxy clusters up to redshifts z > 1 in order to study the large-scale structure of the universe and test cosmological models including Dark Energy. In addition, eROSITA is expected to yield a sample of a few million AGNs, including obscured objects, revolutionizing our view of the evolution of supermassive black holes. The survey will also provide new insights into a wide range of astrophysical phenomena, including X-ray binaries, active stars, and diffuse emission within the Galaxy. Results from early observations, some of which are presented here, confirm that the performance of the instrument is able to fulfil its scientific promise. With this paper, we aim to give a concise description of the instrument, its performance as measured on ground, its operation in space, and also the first results from in-orbit measurements.

Massive Access for 5G and Beyond

Abstract: Massive access, also known as massive connectivity or massive machine-type communication (mMTC), is one of the main use cases of the fifth-generation (5G) and beyond 5G (B5G) wireless networks. A typical application of massive access is the cellular Internet of Things (IoT). Different from conventional human-type communication, massive access aims at realizing efficient and reliable communications for a massive number of IoT devices. Hence, the main characteristics of massive access include low power, massive connectivity, and broad coverage, which require new concepts, theories, and paradigms for the design of next-generation cellular networks. This paper presents a comprehensive survey of massive access design for B5G wireless networks. Specifically, we provide a detailed review of massive access from the perspectives of theory, protocols, techniques, coverage, energy, and security. Furthermore, several future research directions and challenges are identified.

Internet-Based Cognitive Behavioral Therapy for Depression: A Systematic Review and Individual Patient Data Network Meta-analysis.

Abstract: Importance Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them. Objective To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information. Data Sources We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019. Study Selection Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization. Data Extraction and Synthesis We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression. Main Outcomes and Measures Patient Health Questionnaire–9 (PHQ-9) scores. Results Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, −0.8; 95% CI, −1.4 to −0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9. Conclusions and Relevance In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.

Acknowledging the use of human cadaveric tissues in research papers: Recommendations from anatomical journal editors.

Abstract: Research within the anatomical sciences often relies on human cadaveric tissues. Without the good will of these donors who allow us to use their bodies to push forward our anatomical knowledge, most human anatomical research would come to a standstill. However, many research papers omit an acknowledgement to the donor cadavers or, as no current standardized versions exist, use language that is extremely varied. To remedy this problem, 20 editors-in-chiefs from 17 anatomical journals joined together to put together official recommendations that can be used by authors when acknowledging the donor cadavers used in their studies. The goal of these recommendations is to standardize the writing approach by which donors are acknowledged in anatomical studies that use human cadaveric tissues. Such sections in anatomical papers will not only rightfully thank those who made the donation but might also encourage, motivate, and inspire future individuals to make such gifts for the betterment of the anatomical sciences and patient care.

Simultaneously Transmitting And Reflecting (STAR) RIS Aided Wireless Communications

Abstract: The novel concept of simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RISs) is investigated, where the incident wireless signal is divided into transmitted and reflected signals passing into both sides of the space surrounding the surface, thus facilitating a full-space manipulation of signal propagation. Based on the introduced basic signal model of ‘STAR’, three practical operating protocols for STAR-RISs are proposed, namely energy splitting (ES), mode switching (MS), and time switching (TS). Moreover, a STAR-RIS aided downlink communication system is considered for both unicast and multicast transmission, where a multi-antenna base station (BS) sends information to two users, i.e., one on each side of the STAR-RIS. A power consumption minimization problem for the joint optimization of the active beamforming at the BS and the passive transmission and reflection beamforming at the STAR-RIS is formulated for each of the proposed operating protocols, subject to communication rate constraints of the users. For ES, the resulting highly-coupled non-convex optimization problem is solved by an iterative algorithm, which exploits the penalty method and successive convex approximation. Then, the proposed penalty-based iterative algorithm is extended to solve the mixed-integer non-convex optimization problem for MS. For TS, the optimization problem is decomposed into two subproblems, which can be consecutively solved using state-of-the-art algorithms and convex optimization techniques. Finally, our numerical results reveal that: 1) the TS and ES operating protocols are generally preferable for unicast and multicast transmission, respectively; and 2) the required power consumption for both scenarios is significantly reduced by employing the proposed STAR-RIS instead of conventional reflecting/transmiting-only RISs.

Methotrexate hampers immunogenicity to BNT162b2 mRNA COVID-19 vaccine in immune-mediated inflammatory disease.

Abstract: Objective To investigate the humoral and cellular immune response to messenger RNA (mRNA) COVID-19 vaccines in patients with immune-mediated inflammatory diseases (IMIDs) on immunomodulatory treatment. Methods Established patients at New York University Langone Health with IMID (n=51) receiving the BNT162b2 mRNA vaccination were assessed at baseline and after second immunisation. Healthy subjects served as controls (n=26). IgG antibody responses to the spike protein were analysed for humoral response. Cellular immune response to SARS-CoV-2 was further analysed using high-parameter spectral flow cytometry. A second independent, validation cohort of controls (n=182) and patients with IMID (n=31) from Erlangen, Germany, were also analysed for humoral immune response. Results Although healthy subjects (n=208) and patients with IMID on biologic treatments (mostly on tumour necrosis factor blockers, n=37) demonstrate robust antibody responses (over 90%), those patients with IMID on background methotrexate (n=45) achieve an adequate response in only 62.2% of cases. Similarly, patients with IMID on methotrexate do not demonstrate an increase in CD8+ T-cell activation after vaccination. Conclusions In two independent cohorts of patients with IMID, methotrexate, a widely used immunomodulator for the treatment of several IMIDs, adversely affected humoral and cellular immune response to COVID-19 mRNA vaccines. Although precise cut-offs for immunogenicity that correlate with vaccine efficacy are yet to be established, our findings suggest that different strategies may need to be explored in patients with IMID taking methotrexate to increase the chances of immunisation efficacy against SARS-CoV-2 as has been demonstrated for augmenting immunogenicity to other viral vaccines.

IceCube-Gen2: the window to the extreme Universe

Abstract: The observation of electromagnetic radiation from radio to γ-ray wavelengths has provided a wealth of information about the Universe. However, at PeV (1015 eV) energies and above, most of the Universe is impenetrable to photons. New messengers, namely cosmic neutrinos, are needed to explore the most extreme environments of the Universe where black holes, neutron stars, and stellar explosions transform gravitational energy into non-thermal cosmic rays. These energetic particles havemillions of times higher energies than those produced in the most powerful particle accelerators on Earth. As neutrinos can escape from regions otherwise opaque to radiation, they allow an unique view deep into exploding stars and the vicinity of the event horizons of black holes. The discovery of cosmic neutrinos with IceCube has opened this new window on the Universe. IceCube has been successful in finding first evidence for cosmic particle acceleration in the jet of an active galactic nucleus. Yet, ultimately, its sensitivity is too limited to detect even the brightest neutrino sources with high significance, or to detect populations of less luminous sources. In thiswhite paper, we present an overview of a next-generation instrument, IceCube-Gen2, which will sharpen our understanding of the processes and environments that govern the Universe at the highest energies. IceCube-Gen2 is designed to: (a) Resolve the high-energy neutrino sky from TeV to EeV energies (b) Investigate cosmic particle acceleration through multi-messenger observations (c) Reveal the sources and propagation of the highest energy particles in the Universe (d) Probe fundamental physics with high-energy neutrinos IceCube-Gen2 will enhance the existing IceCube detector at the South Pole. It will increase the annual rate of observed cosmic neutrinos by a factor of ten compared to IceCube, and will be able to detect sources five times fainter than its predecessor. Furthermore, through the addition of a radio array, IceCube- Gen2 will extend the energy range by several orders of magnitude compared to IceCube. Construction will take 8 years and cost about $350M. The goal is to have IceCube-Gen2 fully operational by 2033. IceCube-Gen2 will play an essential role in shaping the new era of multimessenger astronomy, fundamentally advancing our knowledge of the highenergy Universe. This challenging mission can be fully addressed only through the combination of the information from the neutrino, electromagnetic, and gravitational wave emission of high-energy sources, in concert with the new survey instruments across the electromagnetic spectrum and gravitational wave detectors which will be available in the coming years.

Efficacy of Margetuximab vs Trastuzumab in Patients With Pretreated ERBB2-Positive Advanced Breast Cancer: A Phase 3 Randomized Clinical Trial.

Abstract: Importance ERRB2 (formerly HER2)–positive advanced breast cancer (ABC) remains typically incurable with optimal treatment undefined in later lines of therapy. The chimeric antibody margetuximab shares ERBB2 specificity with trastuzumab but incorporates an engineered Fc region to increase immune activation. Objective To compare the clinical efficacy of margetuximab vs trastuzumab, each with chemotherapy, in patients with pretreated ERBB2-positive ABC. Design, Setting, and Participants The SOPHIA phase 3 randomized open-label trial of margetuximab plus chemotherapy vs trastuzumab plus chemotherapy enrolled 536 patients from August 26, 2015, to October 10, 2018, at 166 sites in 17 countries. Eligible patients had disease progression on 2 or more prior anti-ERBB2 therapies and 1 to 3 lines of therapy for metastatic disease. Data were analyzed from February 2019 to October 2019. Interventions Investigators selected chemotherapy before 1:1 randomization to margetuximab, 15 mg/kg, or trastuzumab, 6 mg/kg (loading dose, 8 mg/kg), each in 3-week cycles. Stratification factors were metastatic sites (≤2, >2), lines of therapy (≤2, >2), and chemotherapy choice. Main Outcomes and Measures Sequential primary end points were progression-free survival (PFS) by central blinded analysis and overall survival (OS). All α was allocated to PFS, followed by OS. Secondary end points were investigator-assessed PFS and objective response rate by central blinded analysis. Results A total of 536 patients were randomized to receive margetuximab (n = 266) or trastuzumab (n = 270). The median age was 56 (27-86) years; 266 (100%) women were in the margetuximab group, while 267 (98.9%) women were in the trastuzumab group. Groups were balanced. All but 1 patient had received prior pertuzumab, and 489 (91.2%) had received prior ado-trastuzumab emtansine. Margetuximab improved primary PFS over trastuzumab with 24% relative risk reduction (hazard ratio [HR], 0.76; 95% CI, 0.59-0.98;P = .03; median, 5.8 [95% CI, 5.5-7.0] months vs 4.9 [95% CI, 4.2-5.6] months; October 10, 2018). After the second planned interim analysis of 270 deaths, median OS was 21.6 months with margetuximab vs 19.8 months with trastuzumab (HR, 0.89; 95% CI, 0.69-1.13;P = .33; September 10, 2019), and investigator-assessed PFS showed 29% relative risk reduction favoring margetuximab (HR, 0.71; 95% CI, 0.58-0.86;P Conclusions and Relevance In this phase 3 randomized clinical trial, margetuximab plus chemotherapy had acceptable safety and a statistically significant improvement in PFS compared with trastuzumab plus chemotherapy in ERBB2-positive ABC after progression on 2 or more prior anti-ERBB2 therapies. Final OS analysis is expected in 2021. Trial Registration ClinicalTrials.gov Identifier:NCT02492711

Physics-Based Modeling and Scalable Optimization of Large Intelligent Reflecting Surfaces

Abstract: Intelligent reflecting surfaces (IRSs) have the potential to transform wireless communication channels into smart reconfigurable propagation environments. To realize this new paradigm, the passive IRSs have to be large, especially for communication in far-field scenarios, so that they can compensate for the large end-to-end path-loss, which is caused by the multiplication of the individual path-losses of the transmitter-to-IRS and IRS-to-receiver channels. However, optimizing a large number of sub-wavelength IRS elements imposes a significant challenge for online transmission. To address this issue, in this article, we develop a physics-based model and a scalable optimization framework for large IRSs. The basic idea is to partition the IRS unit cells into several subsets, referred to as tiles, model the impact of each tile on the wireless channel, and then optimize each tile in two stages, namely an offline design stage and an online optimization stage. For physics-based modeling, we borrow concepts from the radar literature, model each tile as an anomalous reflector, and derive its impact on the wireless channel for a given phase shift by solving the corresponding integral equations for the electric and magnetic vector fields. In the offline design stage, the IRS unit cells of each tile are jointly designed for the support of different transmission modes, where each transmission mode effectively corresponds to a given configuration of the phase shifts that the unit cells of the tile apply to an impinging electromagnetic wave. In the online optimization stage, the best transmission mode of each tile is selected such that a desired quality-of-service (QoS) criterion is maximized. We consider an exemplary downlink system and study the minimization of the base station (BS) transmit power subject to QoS constraints for the users. Since the resulting mixed-integer programming problem for joint optimization of the BS beamforming vectors and the tile transmission modes is non-convex, we derive two efficient suboptimal solutions, which are based on alternating optimization and a greedy approach, respectively. We show that the proposed modeling and optimization framework can be used to efficiently optimize large IRSs comprising thousands of unit cells.

Clinical and molecular characteristics of HER2-low-positive breast cancer: pooled analysis of individual patient data from four prospective, neoadjuvant clinical trials.

Abstract: Summary Background The development of anti-HER2 antibody–drug conjugates opens new therapeutic options for patients with breast cancer, including patients with low expression of HER2. To characterise this new breast cancer subtype, we have compared the clinical and molecular characteristics of HER2-low-positive and HER2-zero breast cancer, including response to neoadjuvant chemotherapy and prognosis. Methods In this pooled analysis of individual patient data, we evaluated a cohort of 2310 patients with HER2-non-amplified primary breast cancer that were treated with neoadjuvant combination chemotherapy in four prospective neoadjuvant clinical trials (GeparSepto, NCT01583426 ; GeparOcto, NCT02125344 ; GeparX, NCT02682693 ; Gain-2 neoadjuvant, NCT01690702 ) between July 30, 2012, and March 20, 2019. Central HER2 testing was done prospectively before random assignment of participants in all trials. HER2-low-positive status was defined as immunohistochemistry (IHC) 1+ or IHC2+/in-situ hybridisation negative and HER2-zero was defined as IHC0, based on the American Society of Clinical Oncology/College of American Pathologists guidelines. Disease-free survival and overall survival data were available for 1694 patients (from all trials except GeparX) with a median follow-up of 46·6 months (IQR 35·0–52·3). Bivariable and multivariable logistic regression models and Cox-proportional hazards models were performed based on a predefined statistical analysis plan for analysis of the endpoints pathological complete response, disease-free survival, and overall survival. Findings A total of 1098 (47·5%) of 2310 tumours were HER2-low-positive and 1212 (52·5%) were HER2-zero. 703 (64·0%) of 1098 patients with HER2-low-positive tumours were hormone receptor positive, compared with 445 (36·7%) of 1212 patients with HER2-zero tumours (p Interpretation Our results show that HER2-low-positive tumours can be identified as new subgroup of breast cancer by standardised IHC, distinct from HER2-zero tumours. HER2-low-positive tumours have a specific biology and show differences in response to therapy and prognosis, which is particularly relevant in therapy-resistant, hormone receptor-negative tumours. Our results provide a basis for a better understanding of the biology of breast cancer subtypes and the refinement of future diagnostic and therapeutic strategies. Funding German Cancer Aid (Deutsche Krebshilfe).

Dynamic EMT: a multi-tool for tumor progression.

Abstract: The process of epithelial-mesenchymal transition (EMT) is fundamental for embryonic morphogenesis. Cells undergoing it lose epithelial characteristics and integrity, acquire mesenchymal features, and become motile. In cancer, this program is hijacked to confer essential changes in morphology and motility that fuel invasion. In addition, EMT is increasingly understood to orchestrate a large variety of complementary cancer features, such as tumor cell stemness, tumorigenicity, resistance to therapy and adaptation to changes in the microenvironment. In this review, we summarize recent findings related to these various classical and non-classical functions, and introduce EMT as a true tumorigenic multi-tool, involved in many aspects of cancer. We suggest that therapeutic targeting of the EMT process will-if acknowledging these complexities-be a possibility to concurrently interfere with tumor progression on many levels.

Highly Sensitive Ultrathin Flexible Thermoplastic Polyurethane/Carbon Black Fibrous Film Strain Sensor with Adjustable Scaffold Networks.

Abstract: In recently years, high-performance wearable strain sensors have attracted great attention in academic and industrial. Herein, a conductive polymer composite of electrospun thermoplastic polyurethane (TPU) fibrous film matrix-embedded carbon black (CB) particles with adjustable scaffold network was fabricated for high-sensitive strain sensor. This work indicated the influence of stereoscopic scaffold network structure built under various rotating speeds of collection device in electrospinning process on the electrical response of TPU/CB strain sensor. This structure makes the sensor exhibit combined characters of high sensitivity under stretching strain (gauge factor of 8962.7 at 155% strain), fast response time (60 ms), outstanding stability and durability (> 10,000 cycles) and a widely workable stretching range (0–160%). This high-performance, wearable, flexible strain sensor has a broad vision of application such as intelligent terminals, electrical skins, voice measurement and human motion monitoring. Moreover, a theoretical approach was used to analyze mechanical property and a model based on tunneling theory was modified to describe the relative change of resistance upon the applied strain. Meanwhile, two equations based from this model were first proposed and offered an effective but simple approach to analyze the change of number of conductive paths and distance of adjacent conductive particles.

Patients with COVID-19: in the dark-NETs of neutrophils.

Abstract: SARS-CoV-2 infection poses a major threat to the lungs and multiple other organs, occasionally causing death. Until effective vaccines are developed to curb the pandemic, it is paramount to define the mechanisms and develop protective therapies to prevent organ dysfunction in patients with COVID-19. Individuals that develop severe manifestations have signs of dysregulated innate and adaptive immune responses. Emerging evidence implicates neutrophils and the disbalance between neutrophil extracellular trap (NET) formation and degradation plays a central role in the pathophysiology of inflammation, coagulopathy, organ damage, and immunothrombosis that characterize severe cases of COVID-19. Here, we discuss the evidence supporting a role for NETs in COVID-19 manifestations and present putative mechanisms, by which NETs promote tissue injury and immunothrombosis. We present therapeutic strategies, which have been successful in the treatment of immunο-inflammatory disorders and which target dysregulated NET formation or degradation, as potential approaches that may benefit patients with severe COVID-19.

SARS-CoV-2 vaccination responses in untreated, conventionally treated and anticytokine-treated patients with immune-mediated inflammatory diseases.

Abstract: Objectives To better understand the factors that influence the humoral immune response to vaccination against SARS-CoV-2 in patients with immune-mediated inflammatory diseases (IMIDs). Methods Patients and controls from a large COVID-19 study, with (1) no previous history of COVID-19, (2) negative baseline anti-SARS-CoV-2 IgG test and (3) SARS-CoV-2 vaccination at least 10 days before serum collection were measured for anti-SARS-CoV-2 IgG. Demographic, disease-specific and vaccination-specific data were recorded. Results Vaccination responses from 84 patients with IMID and 182 controls were analysed. While all controls developed anti-SARS-CoV-2 IgG, five patients with IMID failed to develop a response (p=0.003). Moreover, 99.5% of controls but only 90.5% of patients with IMID developed neutralising antibody activity (p=0.0008). Overall responses were delayed and reduced in patients (mean (SD): 6.47 (3.14)) compared with controls (9.36 (1.85); p Conclusions Immune responses against the SARS-CoV-2 are delayed and reduced in patients with IMID. This effect is based on the disease itself rather than concomitant treatment.

Functional autoantibodies against G-protein coupled receptors in patients with persistent Long-COVID-19 symptoms

Abstract: Impairment of health after overcoming the acute phase of COVID-19 is being observed more and more frequently. Here different symptoms of neurological and/or cardiological origin have been reported. With symptoms, which are very similar to the ones reported but are not caused by SARS-CoV-2, the occurrence of functionally active autoantibodies (fAABs) targeting G-protein coupled receptors (GPCR-fAABs) has been discussed to be involved. We, therefore investigated, whether GPCR-fAABs are detectable in 31 patients suffering from different Long-COVID-19 symptoms after recovery from the acute phase of the disease. The spectrum of symptoms was mostly of neurological origin (29/31 patients), including post-COVID-19 fatigue, alopecia, attention deficit, tremor and others. Combined neurological and cardiovascular disorders were reported in 17 of the 31 patients. Two recovered COVID-19 patients were free of follow-up symptoms. All 31 former COVID-19 patients had between 2 and 7 different GPCR-fAABs that acted as receptor agonists. Some of those GPCR-fAABs activate their target receptors which cause a positive chronotropic effect in neonatal rat cardiomyocytes, the read-out in the test system for their detection (bioassay for GPCR-fAAB detection). Other GPCR-fAABs, in opposite, cause a negative chronotropic effect on those cells. The positive chronotropic GPCR-fAABs identified in the blood of Long-COVID patients targeted the β2-adrenoceptor (β2-fAAB), the α1-adrenoceptor (α1-fAAB), the angiotensin II AT1-receptor (AT1-fAAB), and the nociceptin-like opioid receptor (NOC-fAAB). The negative chronotropic GPCR-fAABs identified targeted the muscarinic M2-receptor (M2-fAAB), the MAS-receptor (MAS-fAAB), and the ETA-receptor (ETA-fAAB). It was analysed which of the extracellular receptor loops was targeted by the autoantibodies.

A Comprehensive Overview on 5G-and-Beyond Networks With UAVs: From Communications to Sensing and Intelligence

Abstract: Due to the advancements in cellular technologies and the dense deployment of cellular infrastructure, integrating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and beyond cellular networks is a promising solution to achieve safe UAV operation as well as enabling diversified applications with mission-specific payload data delivery. In particular, 5G networks need to support three typical usage scenarios, namely, enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). On the one hand, UAVs can be leveraged as cost-effective aerial platforms to provide ground users with enhanced communication services by exploiting their high cruising altitude and controllable maneuverability in three-dimensional (3D) space. On the other hand, providing such communication services simultaneously for both UAV and ground users poses new challenges due to the need for ubiquitous 3D signal coverage as well as the strong air-ground network interference. Besides the requirement of high-performance wireless communications, the ability to support effective and efficient sensing as well as network intelligence is also essential for 5G-and-beyond 3D heterogeneous wireless networks with coexisting aerial and ground users. In this paper, we provide a comprehensive overview of the latest research efforts on integrating UAVs into cellular networks, with an emphasis on how to exploit advanced techniques (e.g., intelligent reflecting surface, short packet transmission, energy harvesting, joint communication and radar sensing, and edge intelligence) to meet the diversified service requirements of next-generation wireless systems. Moreover, we highlight important directions for further investigation in future work.

Robust and Secure Sum-Rate Maximization for Multiuser MISO Downlink Systems With Self-Sustainable IRS

Abstract: This paper investigates robust and secure multiuser multiple-input single-output (MISO) downlink communications assisted by a self-sustainable intelligent reflection surface (IRS), which can simultaneously reflect and harvest energy from the received signals. We study the joint design of beamformers at an access point (AP) and the phase shifts as well as the energy harvesting schedule at the IRS for maximizing the system sum-rate. The design is formulated as a non-convex optimization problem taking into account the wireless energy harvesting capability of IRS elements, secure communications, and the robustness against the impact of channel state information (CSI) imperfection. Subsequently, we propose a computationally-efficient iterative algorithm to obtain a suboptimal solution to the design problem. In each iteration, $\mathcal {S}$ -procedure and the successive convex approximation are adopted to handle the intermediate optimization problem. Our simulation results unveil that: 1) there is a non-trivial trade-off between the system sum-rate and the self-sustainability of the IRS; 2) the performance gain achieved by the proposed scheme is saturated with a large number of energy harvesting IRS elements; 3) an IRS equipped with small bit-resolution discrete phase shifters is sufficient to achieve a considerable system sum-rate of the ideal case with continuous phase shifts.