Enzyme Immobilization Technologies and Industrial Applications.

Enzymes play vital roles in diverse industrial sectors and are essential components of many industrial products. Immobilized enzymes possess higher resistance to environmental changes and can be recovered/recycled easily when compared to the free forms. The primary benefit of immobilization is protecting the enzymes from the harsh environmental conditions (e.g., elevated temperatures, extreme pH values, etc.). The immobilized enzymes can be utilized in various large-scale industries, e.g., medical, food, detergent, textile, and pharmaceutical industries, besides being used in water treatment plants. According to the required application, a suitable enzyme immobilization technique and suitable carrier materials are chosen. Enzyme immobilization techniques involve covalent binding, encapsulation, entrapment, adsorption, etc. This review mainly covers enzyme immobilization by various techniques and their usage in different industrial applications starting from 1992 until 2022. It also focuses on the multiscale operation of immobilized enzymes to maximize yields of certain products. Lastly, the severe consequence of the COVID-19 pandemic on global enzyme production is briefly discussed.

Changes in breast cancer staging trends among Egyptian women after COVID-19: A retrospective single-center study.

OBJECTIVES: Since being declared a global pandemic, the SARS-CoV-2 virus had a significant impact on the entire globe. The pandemic has placed a heavy burden on healthcare systems worldwide, and cancer patients are particularly prone. Despite the fact that initial international reports suggest delays in breast cancer (BC) diagnosis and screening programs, the Egyptian context requires additional research on this topic. To examine whether COVID-19 has changed the pattern of disease presentation before and after the pandemic, focusing on the tumor, node, and metastasis (TNM) staging of the disease at the initial presentation. METHODS: This single-center, retrospective study of female BC patients initially diagnosed at Baheya Foundation was conducted during the following time frames: from Jan 2019 to Jan 2020 (Pre COVID-19 cohort) and from Mar 2020 to Mar 2021 (post-COVID-19 cohort). We compared the two cohorts in terms of clinical characteristics, tumor characteristics, and the number of days from presentation to treatment. Our primary endpoint was the difference in the TNM stage of BC at the initial presentation. RESULTS: This analysis included 710 BC patients, 350 from the pre-COVID cohort and 360 from the post-COVID group. We detected a 27.9% increase in late-stage BC (stages III-IV) in the post-pandemic cohort compared to the pre-pandemic (60.1% vs. 47%, p < 0.001). The time from diagnosis to commencement of treatment was significantly longer (28.34 ± 18.845 vs 36.04 ± 23.641 days, p < 0.001) in the post-COVID cohort (mean difference = 7.702, 95% CI 4.54-10.85, p < 0.001). A higher percentage of patients in the post-pandemic cohort received systemic neoadjuvant therapy (p-value for Exact's test for all treatment options = 0.001). CONCLUSIONS: The number of patients requiring systemic neoadjuvant chemotherapy increased dramatically in the post-pandemic group with advanced stages of BC at presentation. This study highlights the need for proper management of cancer patients during any future pandemic.

Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser

Cloud computing has been a dominant computing paradigm for many years. It provides applications with computing, storage, and networking capabilities. Furthermore, it enhances the scalability and quality of service (QoS) of applications and offers the better utilization of resources. Recently, these advantages of cloud computing have deteriorated in quality. Cloud services have been affected in terms of latency and QoS due to the high streams of data produced by many Internet of Things (IoT) devices, smart machines, and other computing devices joining the network, which in turn affects network capabilities. Content delivery networks (CDNs) previously provided a partial solution for content retrieval, availability, and resource download time. CDNs rely on the geographic distribution of cloud servers to provide better content reachability. CDNs are perceived as a network layer near cloud data centers. Recently, CDNs began to perceive the same degradations of QoS due to the same factors. Fog computing fills the gap between cloud services and consumers by bringing cloud capabilities close to end devices. Fog computing is perceived as another network layer near end devices. The adoption of the CDN model in fog computing is a promising approach to providing better QoS and latency for cloud services. Therefore, a fog-based CDN framework capable of reducing the load time of web services was proposed in this paper. To evaluate our proposed framework and provide a complete set of tools for its use, a fog-based browser was developed. We showed that our proposed fog-based CDN framework improved the load time of web pages compared to the results attained through the use of the traditional CDN. Different experiments were conducted with a simple network topology against six websites with different content sizes along with a different number of fog nodes at different network distances. The results of these experiments show that with a fog-based CDN framework offloading autonomy, latency can be reduced by 85% and enhance the user experience of websites.