Electrospray-on-Electrospun Breathable, Biodegradable, and Robust Nanofibrous Membranes with Photocatalytic Bactericidal Activity

The increasing emergence of infectious diseases like COVID-19 has created an urgent need for filtration/purification materials coupled with multifunctional features such as mechanical integrity, excellent airflow/filtration, and antibacterial/antimicrobial properties. Polymer membranes and metal-organic frameworks (MOFs) have demonstrated high effectiveness in air filtration and purification. MOF nanoparticles have been introduced into electrospun polymer nanofibrous membranes through embedding or postsolution growth. However, the derived hybrids are still facing the issue of (1) limited MOF exposure, which leads to low efficacy;and (2) uncontrollable growth, which leads to pore blocking and low breathability. In this work, we customized an electrospray-on-electrospinning in situ process to dynamically integrate MOF nanoparticles into a robust and elastic continuous nanofibrous membrane for advanced properties including high mechanical strength and flexibility, excellent breathability, particle filtration, and good antimicrobial performance. Biodegradable polylactic acid was reinforced by the poly(hydroxybutyrate)-di-poly(DLA-CL)x copolymer (PHBR) and used as an electrospinning matrix, while MOF nanoparticles were simultaneously electrically sprayed onto the nanofibers with easily controllable MOF loading. The MOF nanoparticles were homogeneously deposited onto nanofibers without clogging the pores in the membrane. The collision of PLA and MOF under the wet status during electrospinning and the hydrogen bonding through C=O and N-H bonds strengthen the affinity between PLA nanofibers and MOF nanoparticles. Because of these factors, the MOF-incorporated PLA/PHBR nanofibrous membrane achieved over 95% particle filtration efficiency with enhanced mechanical properties while maintaining high breathability. Meanwhile, it exhibits excellent photocatalytic antibacterial performance, which is necessary to kill microbes. The electrospray-on-electrospinning in situ process provides an efficient and straightforward way to hybridize one-dimensional (1D) or two-dimensional (2D) nanomaterials into a continuous nanofibrous membrane with strong interaction and controllable loading. Upon integrating proper functionalities from the materials, the obtained hybrids are able to achieve multifunctionalities for various applications.

Religious beliefs and food waste prevention practices: mechanisms of divine and environmental awareness

Under the crisis of food and energy shortage caused by the COVID-19 pandemic, it is emergently important to emphasize food waste prevention in the tourism and hospitality industry because people around the world have started traveling in the post-pandemic era. Based on norm activation model and individualism-collectivism, this study proposes a perspective of religious beliefs to conceptualize divine awareness (i.e. divine retribution and divine rewards) and environmental awareness (i.e. resource scarcity and eco-friendly) on the formation of food waste prevention practices. A total of 571 samples from Taiwan and 483 samples from the United States was collected. Both countries showed that religious beliefs improved divine retribution, divine rewards, and religious food waste prevention practices. Divine rewards enhanced tourists' awareness of resource scarcity and eco-friendly, and resource scarcity led to religious food waste prevention practices. Interestingly, the effects of divine retribution on resource scarcity and eco-friendly were significant only in Taiwan. © 2023 Taylor & Francis Group, LLC.

Electrospray-on-Electrospun Breathable, Biodegradable, and Robust Nanofibrous Membranes with Photocatalytic Bactericidal Activity

The increasing emergence of infectious diseases like COVID-19 has created an urgent need for filtration/purification materials coupled with multifunctional features such as mechanical integrity, excellent airflow/filtration, and antibacterial/antimicrobial properties. Polymer membranes and metal-organic frameworks (MOFs) have demonstrated high effectiveness in air filtration and purification. MOF nanoparticles have been introduced into electrospun polymer nanofibrous membranes through embedding or postsolution growth. However, the derived hybrids are still facing the issue of (1) limited MOF exposure, which leads to low efficacy;and (2) uncontrollable growth, which leads to pore blocking and low breathability. In this work, we customized an electrospray-on-electrospinning in situ process to dynamically integrate MOF nanoparticles into a robust and elastic continuous nanofibrous membrane for advanced properties including high mechanical strength and flexibility, excellent breathability, particle filtration, and good antimicrobial performance. Biodegradable polylactic acid was reinforced by the poly(hydroxybutyrate)-di-poly(DLA-CL)x copolymer (PHBR) and used as an electrospinning matrix, while MOF nanoparticles were simultaneously electrically sprayed onto the nanofibers with easily controllable MOF loading. The MOF nanoparticles were homogeneously deposited onto nanofibers without clogging the pores in the membrane. The collision of PLA and MOF under the wet status during electrospinning and the hydrogen bonding through C═O and N-H bonds strengthen the affinity between PLA nanofibers and MOF nanoparticles. Because of these factors, the MOF-incorporated PLA/PHBR nanofibrous membrane achieved over 95% particle filtration efficiency with enhanced mechanical properties while maintaining high breathability. Meanwhile, it exhibits excellent photocatalytic antibacterial performance, which is necessary to kill microbes. The electrospray-on-electrospinning in situ process provides an efficient and straightforward way to hybridize one-dimensional (1D) or two-dimensional (2D) nanomaterials into a continuous nanofibrous membrane with strong interaction and controllable loading. Upon integrating proper functionalities from the materials, the obtained hybrids are able to achieve multifunctionalities for various applications. © 2023 American Chemical Society.

Online Purchase Over Pandemic Covid-19: Its Growth and Future in Malaysia

Ever since Malaysian Government imposed movement control order (MCO) due to covid-19, there is a surge in online purchase. Covid-19 pandemic has affected shopping and purchasing behavior of consumers. It is in the view that shifting consumer habits are changing Malaysia’s future for retail. Such scenario brought forth by covid-19 pandemic to online purchase, its growth and future. Consumers’ buying behavior has been the interest in this research. This research intends to determine the factors of online purchase during the pandemic. It is to identify the common problems encountered by online consumers. It also intends to find out whether it is a temporary behavioral change of the consumer because of the benefits of online shopping during this covid-19 pandemic. Technology acceptance model and the theory of planned behavior used are to study the factors of online purchase and consumers’ behavior while adopting online purchase during covid-19 pandemic period and in the future. The subjects for this research are 150 volunteering adults, aged between 20 and 30 years old with at least one-time experience of online purchase during covid-19 pandemic. Google Form has been used, and snowballing is used to reach the subjects. This research has concluded that online purchase is resulting in a positive way. Online sales and promotion are the main reason for the surge of online purchase. Besides, consumers also want to avoid crowds during covid-19. More importantly is that most respondents will continue to purchase online even after the pandemic despite problems encountered in the process. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Identification of two distinct phenotypes among hospitalized covid-19 patients using latent class analysis

Introduction: COVID-19 pneumonia is a heterogeneous disorder with a complex pathogenesis. Underlying subgroups may exist among patients who are admitted to the hospital with COVID-19 infection. Methods: We reviewed the charts of adult patients who were hospitalized primarily for COVID-19 at Greenwich Hospital. We performed latent class analysis using variables based on patient demographics (age, sex, race, and body mass index), comorbidities (hypertension, diabetes, coronary artery disease, chronic heart failure, chronic kidney disease, neurological disease, and pre-existing respiratory disease), laboratory results, and treatment information (medications received during hospitalization, hospital length of stay, maximized oxygen requirement, and requirement for intubation). Results: Two phenotypes were identified: C1 and C2. C1 (n=193) included older individuals with a higher mortality rate (25.4% vs 8.97%, p<0.001) and more comorbidities such as hypertension (88.6% vs 22.8%, p<0.001), coronary artery disease (32.1% vs 0.0%, p<0.001), chronic heart failure (20.7% vs 0%, p<0.001), diabetes mellitus (38.3% vs 17.6%, p<0.001), chronic kidney disease (25.4% vs 2.8%, p<0.001), pre-existing respiratory disease (24.9% vs 11.0%, p=0.004), and preexisting neurological disease (32.1% vs 3.5%, p<0.001). C2 (n=290) consisted of individuals who were younger (53.7 years vs 79.5 years, p<0.001), more likely to be obese (40.3% vs. 28.0%, p=0.007), mostly male (70.3% vs 52.3%, p<0.001), and mostly non-white (69.7% vs. 28.5%, p<0.001), with higher levels of inflammatory markers such as C-reactive protein (18.3±43.4 vs. 10.7±13.7 mg/L, p=0.006) and alanine aminotransferase (209±512 vs. 96.2±204 U/L, p=0.001). Conclusions: Using latent class analysis, we identified two clinical phenotypes of patients who were admitted to the hospital for COVID-19. Our findings may reflect different pathophysiologic processes that lead to moderate to severe COVID-19 and may be useful in the identification of treatment targets and the selection of patients with severe COVID-19 disease for future clinical trials.

Design and Implementation of a Low Cost, Open Access Digital Stethoscope for Social Distanced Medical Care and Tele Auscultation: Stethogram

As quality and availability of information and communication technologies infrastructure improved in urban and rural areas across the world, telemedicine is gaining more attention and momentum to improve healthcare delivery. However, tele auscultation, an essential part of clinical diagnosis, remains challenging due to several factors, including access to an affordable quality digital stethoscope for patients receiving care remotely. The COVID-19 pandemic has exhibited a similar challenge highlighting the need for a low-cost digital stethoscope used while donning personal protective equipment. Motivated by healthcare providers struggle to protect themselves and the patient during the COVID-19 pandemic and to address the challenges of caring for a patient remotely, we designed a low-cost digital stethoscope suitable for both the COVID-19 challenges and tele auscultation based on standard smartphone, off-the-shelf components, open-source 3D-printed parts and tool-free assembly. We present the result of a fully functional digital stethoscope smartphone attachment successfully developed at the cost of approximately $20 and evaluated by participating clinicians. © 2021 ACM.

IDENTIFICATION OF PHENOTYPES AMONG COVID-19 DEATH USING LATENT CLASS ANALYSIS

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: Certain risk factors and prognostic indicators have been identified in patients with coronavirus disease 2019 (COVID-19). However, no study has addressed the risk factor distribution pattern among patients who die from COVID-19. In this study, we used latent class analysis (LCA) to identify phenotypes and risk factor distribution patterns in hospitalized patients who died from COVID-19. METHODS: We reviewed the charts of patients who died from COVID-19 at Greenwich Hospital from February 1 to May 30, 2020. We performed LCA based on well-documented prognostic factors of COVID-19. We also compared the in-hospital laboratory results, and treatment information among the different clusters identified by LCA. To validate of the clustering results, we conducted a robust LCA of the entire COVID-19 cohort. RESULTS: 483 patients who were admitted for COVID-19 infection from February 1 to May 30, 2020, 81 patients died. Using latent cluster analysis, we identified two risk factor clusters among COVID-19 death: C1 (n=58) and C2 (n=23). In C1, patients were older (p<0.001) with a higher proportion of comorbidities such as hypertension (82.8% vs. 39.1%, p<0.001), CAD (43.1% vs. 0%, p<0.001), CHF (22.4% vs. 0%, p=0.015), and pre-existing respiratory disease (32.8% vs. 0%, p=0.004) than in C2. In C2, patients were significantly younger and were more likely to be obese (BMI ≥30 kg/m2;56.5% vs. 24.1%, p=0.012), male (87.0% vs. 58.6%, p=0.018), and non-white (60.9% vs. 15.8%, p<0.001) than in C1. Compared with patients in C1, patients in C2 showed a pattern of increased expression of inflammatory and hypercoagulable markers, including C-reactive protein (84.4±117 vs. 12.7±10.7 mg/L, p=0.008) and D-dimer (17.8±13.6 vs. 8.0±9.9 mg/L, p=0.004). The robust-test by using the entire cohort of patients hospitalized with COVID-19 had identified two clusters of risk factor patterns similar to those identified in the cohort of patients who died from COVID-19. CONCLUSIONS: Our study suggests that there are two patterns of risk factors that contributed to death in patients with COVID-19. These results indicate that different pathophysiologic processes lead to COVID-19 death and may be useful in identifying treatment targets and selecting patients with severe COVID-19 disease for future clinical trials. CLINICAL IMPLICATIONS: The results indicate that each phenotype of patients who died from COVID-19 has its distinct feature and underlying pathophysiology. Research focused on targeted therapy for each phenotype may help decrease the mortality rate among patients with severe COVID-19. DISCLOSURES: No relevant relationships by Deepa Jansen, source=Web Response No relevant relationships by Pengyang Li, source=Web Response No relevant relationships by Catherine Teng, source=Web Response