There is ongoing discussion about whether preoperative obesity is negatively associated with inpatient outcomes of total hip arthroplasty (THA). The aim was to investigate the interaction between obesity and muscle strength and the association with postoperative inpatient recovery after THA. Preoperative obesity (body mass index (BMI)>30 kg/m2) and muscle weakness (hand grip strength <20 kg for woman and <30 kg for men) were measured about 6 weeks before THA. Patients with a BMI<18.5 kg/m2 were excluded. Outcomes were delayed inpatient recovery of activities (>2 days to reach independence of walking) and prolonged length of hospital stay (LOS, >4 days and/or discharge to extended rehabilitation). Univariate and multivariable regression analyses with the independent variables muscle weakness and obesity, and the interaction between obesity and muscle weakness, were performed and corrected for possible confounders.
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Skeletal muscle-related symptoms are common in both acute coronavirus disease (Covid)-19 and post-acute sequelae of Covid-19 (PASC). In this narrative review, we discuss cellular and molecular pathways that are affected and consider these in regard to skeletal muscle involvement in other conditions, such as acute respiratory distress syndrome, critical illness myopathy, and post-viral fatigue syndrome. Patients with severe Covid-19 and PASC suffer from skeletal muscle weakness and exercise intolerance. Histological sections present muscle fibre atrophy, metabolic alterations, and immune cell infiltration. Contributing factors to weakness and fatigue in patients with severe Covid-19 include systemic inflammation, disuse, hypoxaemia, and malnutrition. These factors also contribute to post-intensive care unit (ICU) syndrome and ICU-acquired weakness and likely explain a substantial part of Covid-19-acquired weakness. The skeletal muscle weakness and exercise intolerance associated with PASC are more obscure. Direct severe acute respiratory syndrome coronavirus (SARS-CoV)-2 viral infiltration into skeletal muscle or an aberrant immune system likely contribute. Similarities between skeletal muscle alterations in PASC and chronic fatigue syndrome deserve further study. Both SARS-CoV-2-specific factors and generic consequences of acute disease likely underlie the observed skeletal muscle alterations in both acute Covid-19 and PASC.
Many lithographically created optical components, such as photonic crystals, require the creation of periodically repeated structures [1]. The optical properties depend critically on the consistency of the shape and periodicity of the repeated structure. At the same time, the structure and its period may be similar to, or substantially below that of the optical diffraction limit, making inspection with optical microscopy difficult. Inspection tools must be able to scan an entire wafer (300 mm diameter), and identify wafers that fail to meet specifications rapidly. However, high resolution, and high throughput are often difficult to achieve simultaneously, and a compromise must be made. TeraNova is developing an optical inspection tool that can rapidly image features on wafers. Their product relies on (a) knowledge of what the features should be, and (b) a detailed and accurate model of light diffraction from the wafer surface. This combination allows deviations from features to be identified by modifying the model of the surface features until the calculated diffraction pattern matches the observed pattern. This form of microscopy—known as Fourier microscopy—has the potential to be very rapid and highly accurate. However, the solver, which calculates the wafer features from the diffraction pattern, must be very rapid and precise. To achieve this, a hardware solver will be implemented. The hardware solver must be combined with mechatronic tracking of the absolute wafer position, requiring the automatic identification of fiduciary markers. Finally, the problem of computer obsolescence in instrumentation (resulting in security weaknesses) will also be addressed by combining the digital hardware and software into a system-on-a-chip (SoC) to provide a powerful, yet secure operating environment for the microscope software.
Today, embedded devices such as banking/transportation cards, car keys, and mobile phones use cryptographic techniques to protect personal information and communication. Such devices are increasingly becoming the targets of attacks trying to capture the underlying secret information, e.g., cryptographic keys. Attacks not targeting the cryptographic algorithm but its implementation are especially devastating and the best-known examples are so-called side-channel and fault injection attacks. Such attacks, often jointly coined as physical (implementation) attacks, are difficult to preclude and if the key (or other data) is recovered the device is useless. To mitigate such attacks, security evaluators use the same techniques as attackers and look for possible weaknesses in order to “fix” them before deployment. Unfortunately, the attackers’ resourcefulness on the one hand and usually a short amount of time the security evaluators have (and human errors factor) on the other hand, makes this not a fair race. Consequently, researchers are looking into possible ways of making security evaluations more reliable and faster. To that end, machine learning techniques showed to be a viable candidate although the challenge is far from solved. Our project aims at the development of automatic frameworks able to assess various potential side-channel and fault injection threats coming from diverse sources. Such systems will enable security evaluators, and above all companies producing chips for security applications, an option to find the potential weaknesses early and to assess the trade-off between making the product more secure versus making the product more implementation-friendly. To this end, we plan to use machine learning techniques coupled with novel techniques not explored before for side-channel and fault analysis. In addition, we will design new techniques specially tailored to improve the performance of this evaluation process. Our research fills the gap between what is known in academia on physical attacks and what is needed in the industry to prevent such attacks. In the end, once our frameworks become operational, they could be also a useful tool for mitigating other types of threats like ransomware or rootkits.
The global market for the industrial manufacturing of recombinant proteins (RPS) is steadily increasing and demand will keep rising in years to come. Currently, RPs are already an integral part of disease therapeutics, agriculture and the chemical industry and RP manufacturing methods rely heavily on host systems such as prokaryotes and, to a lesser extent, mammalian, yeast and plant cells. When comparing these host systems, all have their specific strengths and weaknesses and numerous challenges remain to improve protein manufacturing on an industrial scale. In this project, GLO Biotics proposes an innovative plant-based RP expression platform with the potential of significantly reducing costs and process requirements compared to the current state-of-the-art systems. Specifically, this novel concept is based on the use of coconut water as a natural, cell-free ‘protein production factory’. Coconut water in nuts aged 4-6 months is composed of free-floating cell nuclei devoid of cell walls, and it has been demonstrated these nuclei can express foreign proteins. Compared to existing platforms, the relative ease of delivering foreign protein-coding genes into this system, as well as the ease of recovery of the produced protein, potentially offers an innovative platform with great commercial attractiveness. In summary, the aim of this project is to provide a proof-of-concept for coconut water as a novel and competitive RP production platform by demonstrating the production and recovery of several commercially available RPs. To this end, GLO Biotics intends to collaborate with Zuyd University of Applied Sciences (Zuyd) and the Aachen Maastricht Institute for Biobased Materials (AMIBM) in demonstrating the potential of the ‘GLO-Conuts’ expression system. As a consortium, Zuyd and GLO Biotics will utilize their shared experience in molecular engineering and DNA vector technology and AMIBM will bring their expertise in plant-based RP production and recovery.
