On-Chip Nucleic Acid Purification Followed by ddPCR for SARS-CoV-2 Detection.

We developed a microfluidic chip integrated with nucleic acid purification and droplet-based digital polymerase chain reaction (ddPCR) modules to realize a 'sample-in, result-out' infectious virus diagnosis. The whole process involved pulling magnetic beads through drops in an oil-enclosed environment. The purified nucleic acids were dispensed into microdroplets by a concentric-ring, oil-water-mixing, flow-focusing droplets generator driven under negative pressure conditions. Microdroplets were generated with good uniformity (CV = 5.8%), adjustable diameters (50-200 µm), and controllable flow rates (0-0.3 µL/s). Further verification was provided by quantitative detection of plasmids. We observed a linear correlation of R2 = 0.9998 in the concentration range from 10 to 105 copies/µL. Finally, this chip was applied to quantify the nucleic acid concentrations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The measured nucleic acid recovery rate of 75 ± 8.8% and detection limit of 10 copies/µL proved its on-chip purification and accurate detection abilities. This chip can potentially be a valuable tool in point-of-care testing.

An integrated microfluidic chip for nucleic acid extraction and continued cdPCR detection of pathogens.

This paper introduces an enclosed microfluidic chip that integrates sample preparation and the chamber-based digital polymerase chain reaction (cdPCR). The sample preparation of the chip includes nucleic acid extraction and purification based on magnetic beads, which adsorb nucleic acids by moving around the reaction chambers to complete the reactions including lysis, washing, and elution. The cdPCR area of the chip consists of tens of thousands of regularly arranged microchambers. After the sample preparation processes are completed, the purified nucleic acid can be directly introduced into the microchambers for amplification and detection on the chip. The nucleic acid extraction performance and digital quantification performance of the system were examined using synthetic SARS-CoV-2 plasmid templates at concentrations ranging from 101-105 copies per µL. Further on, a simulated clinical sample was used to test the system, and the integrated chip was able to accurately detect SARS-CoV-2 virus particle samples doped with interference (saliva) with a detection limit of 10 copies per µL. This integrated system could provide a promising tool for point-of-care testing of pathogenic infections.

Relationship among Covid-19, stock price and green finance markets pragmatic evidence from volatility dynamics

This paper aims to map the effects of the rapid spread of coronavirus (COVID-19) on stock price dynamics and markets selections based on data from March 22, 2021, to September 20, 2021. Options markets from 2020 to 2021, multiple kinds of critical COVID-19 data. The proposed hypothetical modal considers investors' behavior and errors caused by the level of sentiment elicited for stock markets and green categories. This paper another element (1) Covid-19 (2) feeling, and (3) networking websites, for example, Covid-19 influence on the green size, green direction, and impact on securities prices. This paper used google search data work also creates a proxy for emotions dependent on five main categories of Data: (1) Covid-19, pandemic effect (2) markets, (3) lockdown, (4) banking and government aid. Moreover, this paper Use (a) VIX index sentiment, (b) S& The P 500 index is a measure of how well a sentiment (c) Sentiment in the S& amp;P 500 bank index. The Projected to empirical Finding follow First Level during the Covid-19, effect on jump volatility, and variability level in persistence on the green stock market exceeds that on the options market. VIX index green financial level increases with the COVID green financial level increase with the COVID-19 market index, index banking index and lockdown index. Therefore, it concluded the Share market statistic, COVID-19 benchmark, and long-run volatility. The fraction of the leap government assistance reduced. We find that the outbreak of the Pandemic of COVID-19 effects of the S&P 500 Index and S&P 500 Banks Index decrease with highest values (39%) but only after a surge in volatility covid-19 Pandemic. These results comply with our model's expectations.

Concurrent Rising of Dry Eye and Eye Strain Symptoms Among University Students During the COVID-19 Pandemic Era: A Cross-Sectional Study.

Purpose: Students spend extended hours using electronic devices due to online teaching. Digital eye strain (DES) and dry eye disease (DED) symptoms are both associated with prolonged screen exposure time and may co-occur. This study aimed to evaluate the correlation between DES and DED symptoms and determine the prevalence of DED according to the severity of DES. Patients and Methods: This cross-sectional study was conducted among international students in Chinese universities. The survey was built using Wenjuan Mini Program and distributed using the WeChat platform. The questionnaire assessed participants' screen exposure, the 20-20-20 rule, ED practices, and DED awareness. Computer Vision Syndrome Questionnaire (CVS-Q) and Dry Eye Questionnaire (DEQ-5) were used to diagnose DES and DED symptoms, respectively. Results: 498 students completed the survey, but 452 were considered for the study. Predictors of DES and DED symptoms were conjunctivitis, eye allergy, glares, tired eye, neck pain, back pain, PhD students, and daily spending > 9h on screen (P < 0.05 for all). We observed that an increase in DES scores also exponentially increases DED scores. Among students diagnosed with DES symptoms, 26.5% had mild to moderate DED symptoms, and 8.2% had severe DED symptoms. In contrast, only 8.4% and 0.9% of those with asymptomatic DES had mild to moderate and severe DED symptoms, respectively (P < 0.000). A strong and significant positive correlation (r = 0.695, P < 0.000) between DES and DED scores was found. Conclusion: We found an extremely high prevalence of DES and DED symptoms compared to the previous studies with a similar population group. We believe that the prevalence of DED may be underestimated in the young population. Training about proper ED practices is mandatory to prevent these deleterious ocular surface conditions.

Economic recovery through multisector management resources in small and medium businesses in China

In China, the idea of business continuity management (BCM) resources rapidly growing however few studies arranged on the subject and found insufficiently addressing the issue related to the natural resources. As a result, the current study attempts to seek to provide a deeper knowledge of existing Small and medium-sized Enterprises' BCM practices and provide focus on the need to help these businesses for economic recovery. Top executives from 150 Chinese small and medium-sized enterprises filled in an online survey over the period of 2015–2020. After it the findings have been formulated. Chinese SME disaster (particularly COVID-19) experiences have been revealed in the report, but a lack of business continuity planning is also evident along with an inability to construct a documented plan. Despite the fact that SMEs resources have varying BCM information and training requirements, the findings show that a company's assessed disaster management, BCM expertise and training requirements are linked to its size, operational duration disaster experiences and economic recovery. According to the report, it is thus critical to help small enterprises, especially those located in disaster-prone regions. Public and private sector involvement is equally vital in promoting BCM practices among small and medium-sized enterprises (SMEs). This study has provided recommendations for the betterment of business management side by side with futures' research.

Inhibition of Influenza Virus Replication by Oseltamivir Derivatives.

Characterized by the high morbidity and mortality and seasonal surge, the influenza virus (IV) remains a major public health challenge. Oseltamivir is commonly used as a first-line antiviral. As a neuraminidase inhibitor, it attenuates the penetration of viruses through the mucus on the respiratory tract and inhibits the release of virus progeny from infected cells. However, over the years, oseltamivir-resistant strains have been detected in the IV surveillance programs. Therefore, new antivirals that circumvent the resistant strains would be of great importance. In this study, two novel secondary amine derivatives of oseltamivir CUHK326 (6f) and CUHK392 (10i), which bear heteroaryl groups of M2-S31 proton channel inhibitors, were designed, synthesized and subjected to biological evaluation using plaque assay. Influenza A virus (A/Oklahoma/447/2008, H1N1), influenza B viruses (B/HongKong/CUHK33261/2012), an oseltamivir-resistant influenza A virus (A/HongKong/CUHK71923/2009, H1N1) and an oseltamivir-resistant influenza B virus (B/HongKong/CUHK33280/2012) were included in the antiviral effect assessment compared to oseltamivir carboxylate (OC). Both novel compounds significantly reduced the plaque size of seasonal IV A and B, and performed similarly to OC at their corresponding half-maximal inhibitory concentration (IC50). CUHK392 (10i) functioned more effectively than CUHK326 (6f). More importantly, these compounds showed an inhibitory effect on the oseltamivir-resistant strain under 10 nM with selective index (SI) of >200.

A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19.

Chest X-rays (CXR) and computed tomography (CT) are the main medical imaging modalities used against the increased worldwide spread of the 2019 coronavirus disease (COVID-19) epidemic. Machine learning (ML) and artificial intelligence (AI) technology, based on medical imaging fully extracting and utilizing the hidden information in massive medical imaging data, have been used in COVID-19 research of disease diagnosis and classification, treatment decision-making, efficacy evaluation, and prognosis prediction. This review article describes the extensive research of medical image-based ML and AI methods in preventing and controlling COVID-19, and summarizes their characteristics, differences, and significance in terms of application direction, image collection, and algorithm improvement, from the perspective of radiologists. The limitations and challenges faced by these systems and technologies, such as generalization and robustness, are discussed to indicate future research directions.

Correlation between early features and prognosis of symptomatic COVID-19 discharged patients in Hunan, China.

To determine the correlation between the clinical, laboratory, and radiological findings and the hospitalization days in Coronavirus Infectious Disease-19 (COVID-19) discharged patients. We retrospectively identified 172 discharged patients with COVID-19 pneumonia from January 10, 2020, to February 28, 2020, in Hunan province. The patients were categorized into group 1 (≤ 19 days) and group 2 (> 19 days) based on the time from symptom onset to discharge. Cough during admission occurred more commonly in group 2 (68.4%) than in group 1 (53.1%, p = 0.042). White blood cell (p = 0.045), neutrophil counts (p = 0.023), Alanine aminotransferase (p = 0.029), Aspartate aminotransferase (p = 0.027) and Lactate dehydrogenase (p = 0.021) that were above normal were more common in group 2. Patients with single lesions were observed more in group 1(17.7%, p = 0.018) and multiple lesions observed more in group 2(86.8%, p = 0.012). The number of lobes involved (p = 0.008) in the CT score (p = 0.001) for each patient was all differences between the two groups with a statistically significant difference. Mixed ground-glass opacity (GGO) and consolidation appearances were observed in most patients. GGO components > consolidation appearance was more common in group 1 (25.0%) than in group 2 (8.0%) with a significant difference (0.015), GGO < consolidation was more common in group 2(71.1%, p = 0.012). From the logistic regression analysis, the CT score (OR, 1.223; 95% CI, 1.004 to 1.491, p = 0.046) and the appearance of GGO > consolidation (OR, 0.150; 95% CI, 0.034 to 0.660, p = 0.012) were independently associated with the hospitalization days. Thus, special attention should be paid to the role of radiological features in monitoring the disease prognosis.

Analysis of influencing factors related to elevated serum troponin I level for COVID-19 patients in Yichang, China.

BACKGROUND: Cardiac injury is a common condition among hospitalized coronavirus disease 2019 (COVID-19) patients, and is associated with a higher risk of mortality. However, the mechanism of myocardial injury in COVID-19 remains unclear. In this retrospective study, we compared the clinical characteristics of COVID-19 patients with different troponin I (TnI) levels during hospitalization to provide a clinical reference for the identification of those at high-risk. METHODS: In total, 218 patients diagnosed with COVID-19 in Yichang Central People's Hospital and Yichang Third People's Hospital between January 23 and February 19, 2020 were initially included. Of these patients, 89 underwent TnI testing during hospitalization and were finally included in the study. The medical history, clinical signs and symptoms at the time of admission, and laboratory test results were recorded. The patients were assigned to the normal TnI group (TnI <0.01 µg/L; n=67) or the elevated TnI group (TnI >0.01 µg/L; n=22). RESULTS: The incidence of elevated TnI in our patient cohort was 24.7%. There were significant differences between the two groups in the following factors: history of coronary heart disease (CHD), age, lymphocyte count, prothrombin time (PT), activated partial thromboplastin time (APTT), and levels of interleukin (IL)-6, C-reactive protein (CRP), myoglobin (MYO), lactate dehydrogenase (LDH), and albumin (all P<0.05). Binary logistic analysis showed that a history of CHD, age, lymphocyte count, IL-6, APTT, and MYO were influencing factors of elevated serum TnI. CONCLUSIONS: A history of CHD, advanced age, decreased lymphocyte count, increased IL-6, increased MYO, and prolonged APTT were independent influencing factors of elevated TnI in COVID-19 patients. COVID-19 patients with these characteristics are prone to myocardial injury.

Clinical and radiological changes of hospitalised patients with COVID-19 pneumonia from disease onset to acute exacerbation: a multicentre paired cohort study.

OBJECTIVES: To analyse clinical and radiological changes from disease onset to exacerbation in coronavirus infectious disease-19 (COVID-19) patients. METHODS: We reviewed clinical histories of 276 patients with confirmed COVID-19 pneumonia and extracted data on patients who met the diagnostic criteria for COVID-19 severe/fatal pneumonia and had an acute exacerbation starting with mild or common pneumonia. RESULTS: Twenty-four patients were included. Of these, 8% were smokers, 54% had been to Wuhan, and 46% had comorbidities. Before acute exacerbation, elevated lactate dehydrogenase (232.9 ± 88.7) was present, and chest CT scans showed the number of involved lobes was 4 (2-5) and total CT score was 6 (2-8). Following acute exacerbation, patients were likely to have more clinical symptoms (p < 0.01) and abnormal laboratory changes (p < 0.01). The number of involved lobes and CT score after an exacerbation significantly increased to 5 (5-5) and 12 (9-14), respectively. Receiver operating characteristic (ROC) curve showed that, when the cutoff value of CT score was 5, the sensitivity and specificity for severe pneumonia were 90% and 70%, respectively. CT findings of ground glass opacity with consolidations (91.7%), bilateral distribution (100.0%), and multifocal lesion (100.0%) were features in found in patients after exacerbation. CONCLUSIONS: There are significant changes in clinical, laboratory, and CT findings in patients from disease onset to exacerbation. An increase in the number of involved lobes or an increased CT score from the baseline may predict poor clinical outcomes. Combining an assessment of CT changes with clinical and laboratory changes could help clinical teams evaluate the prognosis. KEY POINTS: • The common chest CT signs of COVID-19 pneumonia after exacerbation were ground glass opacity (GGO) with consolidation, bilateral distribution, and multifocal lesions. • An increase in number of involved lobes or an increased CT score from the baseline may predict a poor clinical outcome. • Worsened symptoms and abnormal laboratory results are also associated with poor prognosis.