The present study aimed at furthering the understanding of the potential effects of e-learner characteristics on e-learner satisfaction in an EFL context. Specifically, it examined the collective impact of computer anxiety, computer-mediated communication (CMC) apprehension, metacognitive self-regulation strategy use, mastery goal orientation, and performance goal orientation on EFL e-learner satisfaction. Multiple regression analyses revealed that not all university EFL students are satisfied with e-learning English courses; only students with high levels of metacognitive self-regulation strategy use, high levels of mastery goal orientation, and a low degree of CMC apprehension are satisfied with e-learning English courses. Results imply that on-line English instructors need to find ways to help students develop these characteristics.
In this study, we have developed a platform for the rapid screening of the SARS-CoV-2 virus in saliva. Electrical double layer (EDL) gated field-effect transistors (FET) biosensor is applied in this research to detect the electrical signals in the sample. Nucleocapsid protein is used as the target protein since it is expressed abundantly during infection. The sensor illustrates a lower detection limit compared to recent methods, which shows the potential of our sensor to make a diagnosis in the early stages of the disease. Besides, additional pre-pretreatment is not needed. The sensor is a robust diagnostic tool for rapid screening of COVID-19. Introduction The coronavirus pandemic, also known as COVID-19, is caused by SARS-CoV-2 virus. COVID-19 causes severe acute respiratory syndrome and poses a significant threat to health internationally. The World Health Organization (WHO) declared this as a global pandemic. Symptom-based screening cannot be an effective strategy to identify individuals. The symptoms of mild patients are similar to influenza, which may easily lead to false negative confirmation of disease. Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) is the most well-known method employed for the clinical diagnosis of COVID-19. But, this method is costly and needs a long time to get the result. Hence, a rapid and low-cost diagnosis method is urgently required. Experimental Sensor array fabrication The disposable sensor array chip consists of two gold electrodes. One electrode is connected to the gate voltage supply, defined as the reference electrode. The other one is connected to the gate metal, and considered as the sensing electrode. Functionalization of sensor surface Antibody against SARS-CoV-2 nucleocapsid protein is used as receptor in this study, which is immobilized on the gold gate electrode. Traut’s Reagent (Thermo Scientific, (26101)) introduces sulfhydryl (-SH) groups to the primary amines of antibody. The modified antibody can then covalently bind to Au gate electrode by Au-S Bond. The antibody(1.5mg/mL) and Traut’s reagent (14 mM) are mixed and incubated at room temperature for 1 hour. The mixture is then dropped on the sensor surface and incubated in 4 °C refrigerator for 12 hours. Electrical measurement The sensor array chip is inserted into a portable prototype device with FET LND150. 2V DC bias as the drain-source voltage and a short duration gate pulse are steadily provided. The difference between the two current drains is defined as current gain, which is used as the index in data analysis. Fluorescence experiment After the electrical measurement, the secondary antibody, anti-mouse IgG (DyLight® 594), is added to the sensor to conjugate with the primary antibody. The sensor array chip is incubated for 1 hour at room temperature, and the unbound molecule is washed away by 1X PBS. Fluorescence microscope, (LEICA DM2500 LED) is used to capture the fluorescence image with 100 ms exposure time and quantitative analysis is performed using imageJ software. Result and conclusion When infected with SARS-CoV-2, the body produces antibodies that bind specific to nucleocapsid proteins and other surface antigens to help eliminate the virus. SARS-CoV-2 virus nucleocapsid protein is abundantly expressed during infection and is one of the highly immunogenic proteins. Hence, nucleocapsid protein is used as the target protein in this study. We immobilized antibody for nucleocapsid protein on the sensor. Electrical signal changed as the concentration of nucleocapsid protein increased from 0 to 400 ng/mL. The limit of detection for N protein was established at 0.4ng/mL. Tests that can distinguish between IgM and IgG can provide information about the stage of infection, indicating how long the person has been infected with SARS-CoV-2. In this study, we developed a platform that can help to confirm the infection in patients quickly in saliva. N-protein testing can potentially help us track the spread of the disease and accurately detect the infected individuals so as to control further spreading of the disease. Figure 1
In this work, we develop a portable measurement system to detect the critical UV dose for cells, and we can make precautions to prevent people from skin cancer. In this research, we have developed a rapid and highly selective array using field-effect-transistor-based biosensor to monitor the real time electrical signal change of cell membranes. According to the difference of the electrical response, it is possible to predict when cells are undergoing apoptosis dynamically. All in all, our sensor can detect the signal change of cells when they are stimulated by outside environment.
Studies utilizing biosensors are being extensively used in the field of biomedicine, drug testing and environmental sensing in recent years. Various types of biosensors are being developed to employ in different ways with different sets of advantages. Field -effect transistor (FET) based sensor system is one such sensor which has the unique advantages of rapid detection, low manufacturing cost, ease of use and high sensitivity. In this study, an EDL-FET sensor array has been used to detect a fragment of COVID-19 viral RNA in saliva without performing complex pre-treatment procedures on the sample. The results of this study demonstrate a promising screening tool that can potentially be used for rapid detection of COVID-19. The portability of the device adds an additional advantage that it can be used even in the places with poor healthcare facilities for accurate detection of the pathogen. Introduction Covid19 is one of the deadliest pandemic till date, which is challenge for the complete health care system all over the world. Rapid disease diagnosis and proper patient isolation have been proven as better way in epidemic handling and control. Due to the present unavailability of vaccines and standardized treatment protocol, rapid diagnosis and treatment is in very high mandate. Multiple diagnosing platforms have been developed for the diagnosis of COVID-19 effectively. At present, many platforms such as Lateral flow immune chromatography, serology testing and Antigen detection have been authorized by WHO for the SARS-CoV-2 detection. Real time RT-PCR is considered as the gold standard for disease diagnosis and it is the most viable method to perceive viral RNA from nasopharyngeal swab samples. However, false negative signal is also commonly seen in this PCR method. The long analysis time and large sample collection to result challenges the consistent SARS-CoV-2 detection in PCR analysis method. The quality of testing and realistic data processing also plays a critical role in success of treatment. For nasopharyngeal sampling, the swab sample is invasively collected from nasal duct and it can make the patient very uncomfortable. This may result in reduced viral content in the test sample and resulting in the rise of false negative results. Testing for viral RNA in the patient’s saliva is suggested to be an alternative source for COVID-19 detection. Taking this idea to account, our sensor array was specially fabricated for the diagnosis of viral RNA in the saliva from patient. Artificial ssDNA probes that specifically match with viral RNA, were designed and immobilized over the sensor surface. The functionalized sensor surface was exposed to the saliva sample, which was collected from the suspected patient sample. The specified viral RNA binds with the pre-immobilised ssDNA probes over the FET sensor surface. The corresponding signal changes of EDL-FET sensor for different concentration of complimentary DNA strands and an artificial Covid viral RNA (S-gene RNA) has been analysed. Sensor fabrication An extended gate chip was employed in the sensor array. Electrode surface was cleaned and to ensure proper cleaning of surface, fluorescent images were taken. 10μM ssDNA probe was prepared with TE buffer, followed by adding 1mM TCEP (tris (2-carboxyethyl) phosphine) buffer. The probe solution was then dropped on the cleaned chip and allowed to react for 30 minutes at room temperature. TCEP was used as a reducing agent which helps in the formation of dithiol bonds (SS), making the attachment of the probe easier. Probe- TTT TTT TGG CAA TGT TGT TCC TTG AGG AAGT- FAM Complementary DNA: GCTACAACTTCCTCAAGGAACAACATTGCCAAAAGGCTTCTACGCAGAAG Electrical measurement After the DNA probe was immobilized over the sensor surface, baseline measurement was carried out. The drain current was measured at different voltage bias (Vg=0V and 1V, at Vd=2V). Throughout the measurement, drain current change was taken as sensing signal. Drain current change ( ) is defined as the difference in drain current at Vg=0V and 1V, at Vd=2V. All were performed using identical test solution composition and every measurement was carried out for 20 minutes. Conclusion We successfully immobilized the probe over the sensor area and the corresponding signals were measured with different concentrations of complimentary DNA and viral RNA. Responses to artificial-SARS-CoV-2 viral RNA on functionalized EDL-FET sensor array were effectively monitored. The detection limit of DNA in saliva sample is found to be approximately 1fM, which indicates the feasibility to direct viral RNA without PCR. Due to the ease of usage and sample collection from the patients and fast test results, the EDL-FET platform has significant promise for point of care diagnosis and high potential to be implemented in remote sensing. Figure 1
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.