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PurposeThe current study proposes a moderated mediation model to predict work-from-home engagement during an emergency such as the coronavirus disease 2019 (COVID-19) pandemic based on the integration of well-known concepts, including inclusive leadership, organizational support and perceived risk theory.Design/methodology/approachAn online questionnaire on the Google Forms platform was designed and distributed to Vietnamese employees using a convenience sampling method. A total of 794 valid questionnaires were used for data analysis. Partial least squares structural equation modeling (PLS-SEM) was employed to test the proposed model and hypotheses. The instrument's validity and reliability were tested and ensured.FindingsThe study found that inclusive leadership has direct and indirect effects on work-from-home engagement through the separate and serial mediating roles of perceived organizational support and employee motivation. The present study also revealed that the effects of perceived organizational support and employee motivation on work-from-home engagement are strengthened by employee risk perception. Moreover, the study showed that perceived organizational support and employee motivation performed the lowest of the four elements that were considered, while the importance of these two factors was the highest.Practical implicationsThese findings suggest that in an emergency such as COVID-19, contextual factors should be given more attention. Based on these findings, several theoretical and practical implications for human resource management are highlighted.Originality/valueBy integrating inclusive leadership, organizational support and perceived risk theory to explore employees' engagement in working from home during an emergency, the present study demonstrated that in addition to traditional factors, leadership and contextual factors should be considered for studies on working from home in an emergency such as the COVID-19 pandemic. The present study established that these factors might encourage employees' work-from-home engagement.
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Purpose: The present study integrates inclusive leadership and protection motivation theory to propose a new model predicting employees' intention to work from home during an emergency situation such as the COVID-19 pandemic. Design/methodology/approach: A questionnaire was developed to collect data from 939 Taiwanese and Vietnamese office employees using a non-probability convenience sampling method. A total of 887 valid questionnaires were used for further analysis. The data were analysed following a two-stage structural equation modelling using SPSS 22 and AMOS 20 software. The validity and reliability of the instrument were tested and ensured. Findings: The results revealed that inclusive leadership and factors related to protection motivation theory– including perceived severity and perceived vulnerability – have positive direct and indirect effects on employees' work-from-home intentions through the mediating role of employees' work-from-home-related attitudes. Protection motivation theory factors were found to have a stronger effect on employees' work-from-home intention than inclusive leadership. Differences in the relationship between perceived vulnerability, perceived severity and employees' intentions towards working from home were also discovered among participants from the two studied countries. Practical implications: The integration of inclusive leadership and protection motivation theory brings into light what will drive employees' intention to work from home during an emergency situation. The present study has several theoretical and practical implications for scholars, governments, managers and policymakers that can help them improve management policies for working from home in the future. Originality/value: Based on integrating inclusive leadership and protection motivation theory to explore employees' intention to work from home during an emergency situation, the present study demonstrated that inclusive leadership and protection motivation theory should be considered for studies on working from home in a pandemic setting. © 2023, Emerald Publishing Limited.
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Background and Objective: Under the impact of the global Covid-19 pandemic, in-hospital training for radiologic technologist students meets several difficulties. The specificity of radiography sciences requires numerous practical exercises. We conducted a tutorial lesson for radiologic technologist students using X-ray simulation software to learn how to operate X-ray machines. The study aimed to evaluate students' satisfaction with the teaching method based on simulation software in radiological sciences. Method: 57 third-year radiologic technologist students were enrolled. All the students joined practical classes onsite from May to August 2021. The main training topic was routine X-ray radiography with in-house X-ray simulation software that was built by Hue University in collaboration with Duy Tan University. The satisfaction of students was evaluated following Likert 5 scale with 14 specific items. Descriptive statistics and a one-sample t-test were performed with SPSS Version 20 (IBM, USA). Result: The findings show that 68% of students were satisfied with the hypothetical clinical situation given in the simulation-based training class. One-sample t-test suggests that the average score of all the criteria is greater than 3, from 3.49 to 4.07. Most of the students wanted to participate further in a similar simulation-based training class in the future (91.23%). Simulation-based training software improves students' experience, radiograph creation ability, and image quality evaluation. Conclusion: Simulation-based training improves clinical skills, enhances visual thinking ability, and clinical practice ability of radiologic technologist students. This teaching method seems to be the appropriate solution for medical imaging technology training in the Covid-19 pandemic. However, further studies with a larger population are needed to comprehensively evaluate the effectiveness of the computer-based simulation teaching approach compared to conventional methods. © 2022 by authors.
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Background: COVID-19 is known to induce a wide range of symptoms, most likely as a result of fast respiratory deterioration, which leads to rapid decompensation of the patient's clinical condition. Surprisingly, some patients have both the novel virus and a secondary bacterial infection, which makes disease management even more difficult. Case report: We reported a case of a patient with a positive polymerase chain reaction (PCR) test for SARS-CoV-2 presenting a rapidly worsening dinical course due to superimposed pneumonia diagnosed by laboratory markers and radiologic findings. The first Chest X-ray revealed a voluminous dense homogenous mass located in the middle lobe of the right lung and scattered alveolar opacities in the left lung field. Non-enhanced chest computed tomography (CT) scanner showed nonspecific imaging features of COVID-19 pneumonia by consolidation with multifocal, diffuse, perihilar ground-glass opacities. Repeated chest X-ray showed this mass on the right is larger and more prominent of the alveolar opacities scattered across the two lung fields. Conclusion: CT findings are critical in assisting radiologists in quickly recognizing the characteristics of pulmonary lesions and their consequences. One of the imaging findings consistent with lung super infection consequences is the advancement of consolidation and multifocal nodular opacities, which presents the clinical symptom and laboratory testing required in these individuals.
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Human adenovirus serotype 26 (Ad26) is used as a gene-based vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and HIV-1. However, its primary receptor portfolio remains controversial, potentially including sialic acid, coxsackie and adenovirus receptor (CAR), integrins, and CD46. We and others have shown that Ad26 can use CD46, but these observations were questioned on the basis of the inability to cocrystallize Ad26 fiber with CD46. Recent work demonstrated that Ad26 binds CD46 with its hexon protein rather than its fiber. We examined the functional consequences of Ad26 for infection in vitro and in vivo. Ectopic expression of human CD46 on Chinese hamster ovary cells increased Ad26 infection significantly. Deletion of the complement control protein domain CCP1 or CCP2 or the serine-threonine-proline (STP) region of CD46 reduced infection. Comparing wild-type and sialic acid-deficient CHO cells, we show that the usage of CD46 is independent of its sialylation status. Ad26 transduction was increased in CD46 transgenic mice after intramuscular (i.m.) injection but not after intranasal (i.n.) administration. Ad26 transduction was 10-fold lower than Ad5 transduction after intratumoral (i.t.) injection of CD46expressing tumors. Ad26 transduction of liver was 1,000-fold lower than that ofAd5 after intravenous (i.v.) injection. These data demonstrate the use of CD46 by Ad26 in certain situations but also show that the receptor has little consequence by other routes of administration. Finally, i.v. injection of high doses of Ad26 into CD46 mice induced release of liver enzymes into the bloodstream and reduced white blood cell counts but did not induce thrombocytopenia. This suggests that Ad26 virions do not induce direct clotting side effects seen during coronavirus disease 2019 (COVID-19) vaccination with this serotype of adenovirus. IMPORTANCE The human species D Ad26 is being investigated as a low-seroprevalence vector for oncolytic virotherapy and gene-based vaccination against HIV-1 and SARS-CoV-2. However, there is debate in the literature about its tropism and receptor utilization, which directly influence its efficiency for certain applications. This work was aimed at determining which receptor(s) this virus uses for infection and its role in virus biology, vaccine efficacy, and, importantly, vaccine safety.
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Introduction: Despite recent advances, MM remains incurable and new therapeutic options are needed, particularly for pts with RRMM. IBER is a novel, potent oral cereblon E3 ligase modulator (CELMoD ®) compound with enhanced tumoricidal and immune-stimulatory effects compared with immunomodulatory (IMiD ®) agents. Preclinically, IBER demonstrated marked synergy with DEX and with other standard myeloma treatments. CC-220-MM-001 (NCT02773030) is an ongoing phase 1/2 study evaluating IBER with different treatment combinations in independent cohorts of pts with RRMM;in phase 1, the recommended phase 2 dose of IBER, when given in combination with DEX, was determined at 1.6 mg (Lonial S, et al. Blood 2019;134[suppl 1]:3119). Here we report results from the dose expansion of IBER + DEX in pts with heavily pretreated, triple-class exposed (including ≥ 1 IMiD agent, ≥ 1 proteasome inhibitor [PI], and ≥ 1 anti-CD38 monoclonal antibody [mAb]) RRMM. Methods: Eligible pts had RRMM;had received ≥ 3 prior lines of therapy, including lenalidomide (LEN), pomalidomide (POM), a PI, a glucocorticoid, and an anti-CD38 mAb;had experienced disease progression within 60 days of last myeloma therapy;and were refractory to an IMiD agent, a PI, a glucocorticoid, and an anti-CD38 mAb. Pts with central nervous system involvement were not eligible. Pts who had received prior anti-BCMA therapy were excluded, but included in a supportive cohort for safety and preliminary efficacy assessment. IBER (1.6 mg) was given orally on days (D) 1-21, in combination with DEX (40 mg;20 mg if > 75 years of age) on D1, 8, 15, and 22 of each 28-day cycle. Thrombo-embolism prophylaxis was mandatory for all pts. Primary objective was to determine efficacy expressed as overall response rate (ORR). Secondary endpoints included additional efficacy and safety assessments. Exploratory endpoints included evaluation of health-related quality of life (HRQoL). Results: As of June 2, 2021, 107 pts had received IBER + DEX. Median age was 64 (44-83) years;median time since initial diagnosis was 6.9 (1.6-24.5) years. Extramedullary plasmacytomas were present in 25.2% of pts;29.9% of pts had high-risk cytogenetics. Median number of prior regimens was 6 (3-23). All pts were triple-class exposed;prior therapies included autologous stem cell transplantation (78.5%), PIs (100%), IMiD agents (LEN [100%] and POM [100%]), and anti-CD38 mAbs (100%);99.1% of pts were refractory to last myeloma regimen and 97.2% of pts were triple-class refractory. Median follow-up was 7.69 (0.5-17.5) months, with a median number of 4 (1-17) cycles received and 13 (12.1%) pts continuing treatment. Main reason for discontinuation was progressive disease (69.2%). ORR was 26.2%, with 1 (0.9%) stringent complete response, 8 (7.5%) very good partial responses, and 19 (17.8%) partial responses (Table);the clinical benefit rate (≥ minimal response) was 36.4% and disease control rate (≥ stable disease) was 79.4%. Median duration of response was 7.0 (4.5-11.3) months (Table), median progression-free survival was 3.0 (2.8-3.7) months, and median overall survival was 11.2 (9.0-not reached) months. Similar response rates were observed among a cohort of pts also exposed to BCMA therapies (N = 24, Table). Grade (Gr) 3-4 treatment-emergent adverse events (TEAEs) were reported in 88 (82.2%) pts. Most frequent (≥ 20% pts) hematologic Gr 3-4 TEAEs were neutropenia (44.9%;and 4.7% febrile neutropenia), anemia (28.0%), thrombocytopenia (21.5%), and leukopenia (20.6%). Gr 3-4 infections were reported in 27.1% of pts;Gr 3-4 pneumonia and COVID-19 occurred in 10.3% and 4.7% of pts, respectively. Occurrence of other Gr 3-4 non-hematologic TEAEs was generally low, including gastrointestinal disorders (5.6%), fatigue (2.8%), rash (1.9%). Fifty-six (52.3%) pts and 20 (18.7%) had IBER dose interruptions and reductions due to TEAEs, respectively. Five (4.7%) pts discontinued due to TEAEs. No pt discontinued IBER due to neutropenia. Overall, HRQoL was maintained in these pts. Conclusions: IBER + DEX demonst ated promising efficacy in pts with heavily pretreated, triple-class exposed and refractory RRMM, as well as in pts who had previously received anti-BCMA therapy;this combination was generally well tolerated and TEAEs were manageable with dose reductions and interruptions. These results support the further development of IBER in MM, including phase 3 trials in combination regimens. [Formula presented] Disclosures: Lonial: Abbvie: Consultancy, Honoraria;AMGEN: Consultancy, Honoraria;Takeda: Consultancy, Honoraria, Research Funding;GlaxoSmithKline: Consultancy, Honoraria, Research Funding;TG Therapeutics: Membership on an entity's Board of Directors or advisory committees;Merck: Honoraria;BMS/Celgene: Consultancy, Honoraria, Research Funding;Janssen: Consultancy, Honoraria, Research Funding. Popat: GlaxoSmithKline: Consultancy, Honoraria, Research Funding;Abbvie, Takeda, Janssen, and Celgene: Consultancy;Takeda: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES;AbbVie, BMS, Janssen, Oncopeptides, and Amgen: Honoraria;Janssen and BMS: Other: travel expenses. Hulin: Sanofi: Honoraria;Celgene/BMS: Honoraria;Janssen: Honoraria;Takeda: Honoraria;abbvie: Honoraria. Jagannath: Legend Biotech: Consultancy;Bristol Myers Squibb: Consultancy;Karyopharm Therapeutics: Consultancy;Janssen Pharmaceuticals: Consultancy;Sanofi: Consultancy;Takeda: Consultancy. Oriol: Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees;Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees;BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Richardson: Karyopharm: Consultancy, Research Funding;Regeneron: Consultancy;AbbVie: Consultancy;Celgene/BMS: Consultancy, Research Funding;Oncopeptides: Consultancy, Research Funding;GlaxoSmithKline: Consultancy;Protocol Intelligence: Consultancy;Janssen: Consultancy;Secura Bio: Consultancy;Takeda: Consultancy, Research Funding;Sanofi: Consultancy;AstraZeneca: Consultancy;Jazz Pharmaceuticals: Consultancy, Research Funding. Weisel: Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;Roche: Honoraria;Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding;Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding;Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding;GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees;Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding;Bristol Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding;Abbvie: Consultancy;Novartis: Honoraria;Pfizer: Honoraria. Minnema: Cilag: Consultancy;Janssen: Consultancy;Alnylam: Consultancy;Celgene: Other: Travel expenses;Kite/Gilead: Consultancy;BMS: Consultancy. Badros: J&J: Research Funding;Janssen: Research Funding;BMS: Research Funding;GlaxoSmithKline: Research Funding. Knop: BMS/Celgene: Consultancy, Honoraria, Research Funding;Amgen: Research Funding;Janssen: Consultancy;Oncopeptides: Consultancy;Pfizer: Consultancy;Sanofi: Consultanc . Stadtmauer: Janssen: Consultancy, Honoraria;Takeda: Consultancy, Honoraria;Abbvie: Consultancy, Honoraria;Amgen: Consultancy, Honoraria;Bristol Myers Squibb: Consultancy, Honoraria, Research Funding. Chen: Bristol Myers Squibb: Current Employment. Nguyen: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Amin: Bristol Myers Squibb: Current Employment. Kueenburg: Celgene a BMS company: Current Employment. Peluso: Celgene, a Bristol-Myers Squibb Company: Current Employment. van de Donk: BMS/Celgene: Consultancy, Honoraria;Janssen: Consultancy, Research Funding;Amgen: Consultancy, Research Funding;Cellectis: Research Funding;Takeda: Consultancy;Roche: Consultancy;Novartis /bayer/servier: Consultancy.
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This paper reports on a band-aid type sensor that can simultaneously measure multiple physiological parameters with only one sensing element. The proposed sensor consists of a MEMS-based piezoresistive cantilever, a thin silicone tube whose inner pressure is measured by the cantilever. The whole sensor device is attached to a surgical tape, which allows the band-aid like attachment of the sensor to human skin to measure the vibration caused by the physiological parameters such as pulse wave, heart sound and respiration. Using the fabricated sensor device, we demonstrate two applications: the simultaneous measurements of pulse wave and respiration when attaching the sensor to the user's nose and the simultaneous measurements of heart sound and respiration using when attaching the sensor to the user's chest. We show that these the physiological parameters can be independently extracted from the cantilever output using low pass and high pass filters. The proposed sensor is useful for continuous health monitoring, which has become a great demand in the with/post COVID-19 era.
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This paper addresses the plant disease detection and classification using Deep Learning approach. In particular, we propose a novel model using the Triplet Loss together with the fine-tuned pre-trained MobileNet model to extract good features, classify, and detect diseases of plants from the open-source PlantVillage dataset. Using our proposed model, the achievable results are 99.92%, which outperforms the existing models using the same dataset. Furthermore, our proposed model can support the large-scale agricultural sector, which plays an important role in ensuring food security during the current COVID-19 crisis.
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From late 2019 to early 2020, the coronavirus outbreak affected 213 countries and territories around the world. This respiratory virus seriously affects human lung functionality. One way to diagnose this illness and find out if the lungs are infected is to evaluate chest X-ray. The evaluation of X-rays is challenging because corona has minor effects on the lungs in the early stages, and other diseases can have a similar effect. In this condition, Computer-Aided Diagnosis (CAD) can make a huge contribution and help decision support for healthcare professionals. Deep learning has obtained great results in data analysis recently, but the requirement for a large amount of training data prevents the use deep learning in medical data analysis since it is difficult to obtain a large amount of data from the medical field. This paper proposes an effective deep transfer learning-based model that improves current state-of-the-art systems in COVID-19 detection in chest radiographs. The weights of the DesneNet121 and ResNet50 on the Imagenet have transferred as initial weights, and then the two models have been fine-tuned with a deep classifier with data augmentation to detect three classes of COVID-19, Viral Pneumonia and normal radiographs. The proposed models obtained 97.83% accuracy with minimal false-negative results on the only public available COVID-19 radiography dataset. The Image-Level Accuracy (ILA) of the results outperform the results of previous studies, together with sensitivity and recall performance. Moreover, the proposed methods are scalable, and can be expanded to cover the detection of other types of diseases in the future and be integrated with more CNNs to increase their generalization capabilities. © 2020 IEEE.