The reliability and integrity of overall survival data based on follow-up records only and potential solutions to the challenges

Overall survival (OS) is considered the standard clinical endpoint to support effectiveness claims in new drug applications globally, particularly for lethal conditions such as cancer. However, the source and reliability of OS in the setting of clinical trials have seldom been doubted and discussed. This study first raised the common issue that data integrity and reliability are doubtful when we collect OS information or other time-to-event endpoints based solely on simple follow-up records by investigators without supporting material, especially since the 2019 COVID-19 pandemic. Then, two rounds of discussions with 30 Chinese experts were held and 12 potential source scenarios of three methods for obtaining the time of death of participants, including death certificate, death record and follow-up record, were sorted out and analysed. With a comprehensive assessment of the 12 scenarios by legitimacy, data reliability, data acquisition efficiency, difficulty of data acquisition, and coverage of participants, both short-term and long-term recommended sources, overall strategies and detailed measures for improving the integrity and reliability of death date are presented. In the short term, we suggest integrated sources such as public security systems made available to drug inspection centres appropriately as soon as possible to strengthen supervision. Death certificates provided by participants' family members and detailed standard follow-up records are recommended to investigators as the two channels of mutual compensation, and the acquisition of supporting materials is encouraged as long as it is not prohibited legally. Moreover, we expect that the sharing of electronic medical records and the legal disclosure of death records in established health registries can be realized with the joint efforts of the whole industry in the long-term. The above proposed solutions are mainly based on the context of China and can also provide reference for other countries in the world. © 2022 The Authors

Common Adverse Events Following COVID-19 Vaccination in Patients with Type 2 Diabetes

In the COVID-19 pandemic, vaccines have emerged as the most effective tool to protect people from COVID-19. However, there is a limited study of adverse events (AEs) for COVID-19 vaccines among people with type 2 diabetes. The purpose of this study is to report the common adverse events following the COVID-19 vaccines, mRNA-1273, BNT162b2, and JNJ-78436735 in diabetic patients. We collected data for common adverse events to the COVID-19 vaccines using Vaccine Adverse Event Reporting System (VAERS). To identify the people with and without diabetes, we used the Natural language processing algorithms. After a 1:3 propensity score matching, we used 6,829 people with type 2 diabetes and 20,487 healthy control groups. Multiple logistic regression analysis was performed to obtain the odds ratio for 25 common AEs in order of high frequency. The most common AEs were pain (17.9%), headache (16.6%), pyrexia (13.4%), chills (12.4%), fatigue (12.0%), dizziness (11.0%). In particular, AEs of the dysmenorrhea in women were rare (0.14%), but a 15-fold higher frequency was observed in patients with diabetes (0.45% versus 0.03%) than in those with controls. The risk of all common AEs following both mRNA vaccines was significantly lower (OR = 0.87, 95% CI = 0.77–0.97, P = 0.015) than that after one viral vector vaccine, as well as the risk among males (OR = 0.56, 95% CI = 0.53–0.59, P < 0.001) was lower than among females. In conclusion, the risk of common adverse events among people with type 2 diabetes was low after both mRNA vaccines and in males. These findings might have implications for safe vaccine use. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The role of Socio-Economic Development after COVID-19 and Energy-Growth-Environment in ASEAN Economies

The present study assesses the energy-growth-environment nexus by including the effects of socio-economic development in ASEAN economies – a literature vacuum that needs to be filled. For this objective, panel data of 8 ASEAN nations throughout the 2000-2020 timeframe is obtained to examine the effect of human development, urbanization, and industrialization on energy-growth-environment interaction. Empirical estimation is carried out by adopting the second generation Cross Sectionally Augmented Autoregressive Distributed Lag Model (CS-ARDL) as the data's cross-sectional dependence and slope heterogeneity are present. It is observed that human development has a considerable negative influence on the environment and a significant positive impact on economic growth but has minimal effect on energy consumption. Urbanization and industrialization are the primary drivers of CO2 emission and energy consumption. However, urbanization does not affect economic growth considerably in ASEAN countries. Based on the findings, chosen countries are encouraged to invest more in human development measures, the transition towards zero-emission industrial variety, energy transition, and energy-efficient production technology. © 2022 asociación Cuadernos de economía.

Adaptation to Remote Teaching during Spring 2020 Amidst COVID-19: Perspectives of Advanced Placement Statistics Teachers

During the Spring 2020 semester, K-12 teachers throughout many parts of the world adapted from face-to-face to online teaching. To better understand these experiences, seven advanced placement (AP) Statistics high school teachers were interviewed following a semi-structured protocol. A collaborative and consensus-driven analysis of transcripts revealed 12 distinct themes. The three most extensively discussed themes appeared to be assessment (19.11%), communication methods (12.23%), and use of online instructional approaches (11.90%). Teachers from schools that did not provide devices to students (i.e., not “one-to-one”) tended to report concerns around digital access more frequently (6.87%) and tended to express a more negative sentiment (Sentiment Mean = –.09) than teachers at schools that provided devices (5.69%;Sentiment Mean = 1.35, p <.01). These findings highlight issues facing teachers during the transition to remote and online instruction and suggest a need for supporting teachers in developing familiarity with online and remote assessment resources and strategies. © 2022 Taylor & Francis Group, LLC.

Will Oil Price Volatility Cause Market Panic?

It is generally known that violent oil price volatility will cause market panic;however, the extent to which is worthy of empirical test. Firstly, this paper employs the TVP-VAR model to analyze the time-varying impacts of oil price volatility on the panic index using monthly data from January 1990 to November 2021. Then, after using the SVAR model to decompose the oil price volatility, this paper uses the PDL model to analyze the heterogeneous impacts of oil price volatility from different sources. Finally, based on the results of oil decomposition, this paper uses the TARCH model to analyze the asymmetric impacts of oil price volatility in different directions. The results show that: (1) oil price volatility can indeed cause market panic, and these impacts exhibit time-varying characteristics;(2) oil price volatility from different sources has different impacts on the panic index, and the order from high to low is oil-specific demand shocks, supply shocks, and aggregate demand shocks;and (3) oil price volatility has asymmetric impacts on the panic index, and positive shocks have greater impacts than negative.

MMFC: MULTI-MODAL FUSION CASCADE FRAMEWORK FOR COVID-19 DISEASE COURSE CLASSIFICATION

Many deep learning methods have been proposed for the diagnosis of COVID-19 since the global pandemic. However, few studies have focused on the disease course classification of COVID-19, which is crucial for radiologists to determine treatment plans. This paper proposes a Multi-Modal Fusion Cascade (MMFC) framework for this task, which can make the most of multi-modal information, including CT image and bio-information (laboratory examination, clinical characterization, etc.). The proposed framework consists of two parts: Bio-Visual Feature Learning Module (BFL) and Joint Decision Module (JD). Firstly, BFL learns the discriminative visual features from the mediastinal window with the assistance of bio-information. According to the official Treatment Protocol of China, the bio-information is chosen and helps the BFL better extract the images’ bio-visual features and then obtained a disease course classification result based on CT images. Secondly, JD uses bio-information again and fuses the confidence of BFL’s result to make the joint decision. Experimental results show that our framework significantly improves accuracy and sensitivity compared to the baseline. © 2021 IEEE

The RNA helicase DHX16 recognizes specific viral RNA to trigger RIG-I-dependent innate antiviral immunity.

Type I interferons (IFN-I) are essential to establish antiviral innate immunity. Unanchored (or free) polyubiquitin (poly-Ub) has been shown to regulate IFN-I responses. However, few unanchored poly-Ub interactors are known. To identify factors regulated by unanchored poly-Ub in a physiological setting, we developed an approach to isolate unanchored poly-Ub from lung tissue. We identified the RNA helicase DHX16 as a potential pattern recognition receptor (PRR). Silencing of DHX16 in cells and in vivo diminished IFN-I responses against influenza virus. These effects extended to members of other virus families, including Zika and SARS-CoV-2. DHX16-dependent IFN-I production requires RIG-I and unanchored K48-poly-Ub synthesized by the E3-Ub ligase TRIM6. DHX16 recognizes a signal in influenza RNA segments that undergo splicing and requires its RNA helicase motif for direct, high-affinity interactions with specific viral RNAs. Our study establishes DHX16 as a PRR that partners with RIG-I for optimal activation of antiviral immunity requiring unanchored poly-Ub.

Performance evaluation of a Sars-CoV-2 rapid test and two automated immunoassays

Due to urgency and demand of a response to the Covid-19 pandemic, numerous Sars-CoV-2 immunoassays have been rapidly developed. Objective: This study aimed at assessing the performance of rapid Sars-CoV-2 antibody test in comparison to high-throughput serological assays. Methods: A total of 86 serum samples were evaluated in the three assays: a lateral flow immunoassay - Wondfo Sars-CoV-2 Antibody Test (WRT) - and two chemiluminescence immunoassays: Elecsys Anti-Sars-CoV-2 (ECLIA), and Sars-CoV-2 IgG (CMIA-IgG). Results: The estimated diagnostic sensitivities of serological tests in the evaluation of serum samples from the epidemiological survey were: WRT 59% [95% confidence interval (CI) 43.4%-72.9%], ECLIA 66.7% (51%-79.4%), and CMIA-IgG 61.5% (47.1%-73%). Meanwhile, the estimated diagnostic specificity was for WRT 78.7% (95% CI 65.1%-88%), ECLIA 72.3% (58.2%-83.1%), and CMIA-IgG 76.6% (74%-95.5%). The sensitivity and specificity values were lower than manufacturers' claimed. Although 16.2% (14/86) of serological results were discordant among the three Sars-CoV-2 serological assays, the degree of agreement by the kappa index was adequate: WRT/CMIA-IgG [0.757 (95% CI 0.615-0.899)], WRT/ECLIA [0.715 (0.565-0.864)], and ECLIA/CMIA-IgG [0.858 (0.748-0.968)]. Conclusion: The serological testing may be a useful diagnostic tool, which reinforces its careful evaluation, and, as well as the correct time to use it. © 2021 Sociedade Brasileira de Pneumologia e Tisiologia. All rights reserved.

Clustering and multiple-spreading events of nosocomial severe acute respiratory syndrome coronavirus 2 infection.

BACKGROUND: There is growing evidence that super-spreading events (SSEs) and multiple-spreading events (MSEs) are a characteristic feature of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, data regarding the possibility of SSEs or MSEs in healthcare settings are limited. METHODS: This study was performed at a tertiary-care hospital in Korea. We analysed the nosocomial COVID-19 cases that occurred in healthcare workers and inpatients and their caregivers between January and 20th December 2020. Cases with two to four secondary cases were defined as MSEs and those with five or more secondary cases as SSEs. FINDINGS: We identified 21 nosocomial events (single-case events, N = 12 (57%); MSE + SSE, N = 9 (43%)) involving 65 individuals with COVID-19. Of these 65 individuals, 21 (32%) were infectors. The infectors tended to have a longer duration between symptom onset and diagnostic confirmation than did the non-infectors (median two days vs zero days, P=0.08). Importantly, 12 (18%) individuals were responsible for MSEs and one (2%) for an SSE, which collectively generated 35 (54%) secondary cases. CONCLUSION: In a hospital with thorough infection-control measures, approximately 70% of the nosocomial cases of COVID-19 did not generate secondary cases, and one-fifth of the infectors were responsible for SSEs and MSEs, which accounted for approximately half of the total cases. Early case identification, isolation, and extensive contact tracing are important for the prevention of transmission and SSEs.

Estimation of the impact of comprehensive covid-19 testing in South Korea: A cost-benefit analysis using the extended seir model

Comprehensive COVID-19 diagnostic testing is regarded as a critical in preventing the spread of the virus, but only a few studies thus far have sought to assess the net benefits that sustained testing might offer, despite the importance accorded by researchers to evidence-based policy making. We performed a cost-benefit analysis using the extended SEIR model to assess whether maintaining the current level of COVID-19 testing is an economically rational choice compared with counterfactual scenarios. Our results suggest that the relationship between the net benefits and the level of testing assumes an inverted-U shape, which means that comprehensive diagnostic testing is effective in flattening the infection curve, but it is a financial burden to society. This study provides evidence that comprehensive diagnostic testing would not be a good strategy for countries with scant financial and medical resources, considering the costs. Furthermore, undertaking comprehensive diagnostic testing without implementing other strategies is a limited approach to preventing the spread of infectious diseases. Therefore, this study suggests that policy makers should find ways to improve the effectiveness of tests, not just increase the level of tests. © 2020 by the GSPA, Seoul National University.

Preliminary Analysis of the Therapeutic Mechanism of Feiluoning in Convalescent Patients With COVID-19

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), is often accompanied by injury to pulmonary function and pulmonary fibrosis. Feiluoning (FLN) is a new Chinese medicine prescription which is available for the treatment of severe and critical convalescence of COVID-19 patients. FLN also has a positive effect on pulmonary function injury and pulmonary fibrosis. We explored the potential mechanism of FLN’s effect on the convalescent treatment of COVID-19. According to the pharmacodynamic activity parameters, we screened the active chemical constituents of FLN by comparing the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The Uniprot database was used to querying the corresponding target genes, and Cytoscape 3.6.1 was used to construct a herb-compound-target network. Protein interaction analysis, target gene function enrichment analysis, and signal pathway analysis were performed using the STRING, DAVID, and Kyoto Encyclopedia of Genes and Genomes pathway databases. Molecular docking was used to predict the binding capacity of the core compound with COVID-19 hydrolase 3 Cl and angiotensin-converting enzyme 2 (ACE2). The herb-compound-target network was successfully constructed and key targets identified, including prostaglandin G/H synthase 2, estrogen receptor 1, heat shock protein HSP 90, and androgen receptor. The major affected metabolic pathways were pathways in cancer, pancreatic cancer, nonsmall cell lung cancer, and toll-like receptor signaling. The core compounds of FLN, including quercetin, luteolin, kaempferol, and stigmasterol, could strongly bind to COVID-19 3 Cl hydrolase, and other compounds, including 7-O-methylisomucronulatol and medicocarpin, could strongly bind to ACE2. Thus, it is predicted that FLN has the characteristics of a multicomponent, multitarget, and multichannel overall control compound. FLN’s mechanism of action in the treatment of COVID-19 may be associated with the regulation of inflammation and immune-related signaling pathways, and the influence of COVID-19 3 Cl hydrolase binding ability.

Inhibition of SARS-CoV-2 in Vero cell cultures by peptide-conjugated morpholino oligomers.

BACKGROUND: As the causative agent of COVID-19, SARS-CoV-2 is a pathogen of immense importance to global public health. Development of innovative direct-acting antiviral agents is sorely needed to address this virus. Peptide-conjugated morpholino oligomers (PPMO) are antisense compounds composed of a phosphorodiamidate morpholino oligomer covalently conjugated to a cell-penetrating peptide. PPMO require no delivery assistance to enter cells and are able to reduce expression of targeted RNA through sequence-specific steric blocking. METHODS: Five PPMO designed against sequences of genomic RNA in the SARS-CoV-2 5'-untranslated region and a negative control PPMO of random sequence were synthesized. Each PPMO was evaluated for its effect on the viability of uninfected cells and its inhibitory effect on the replication of SARS-CoV-2 in Vero-E6 cell cultures. Cell viability was evaluated with an ATP-based method using a 48 h PPMO treatment time. Viral growth was measured with quantitative RT-PCR and TCID50 infectivity assays from experiments where cells received a 5 h PPMO treatment time. RESULTS: PPMO designed to base-pair with sequence in the 5' terminal region or the leader transcription regulatory sequence region of SARS-CoV-2 genomic RNA were highly efficacious, reducing viral titres by up to 4-6 log10 in cell cultures at 48-72 h post-infection, in a non-toxic and dose-responsive manner. CONCLUSIONS: The data indicate that PPMO have the ability to potently and specifically suppress SARS-CoV-2 growth and are promising candidates for further preclinical development.

Inhibition of SARS-CoV-2 in Vero cell cultures by peptide-conjugated morpholino-oligomers.

BACKGROUND: SARS-CoV-2 is the causative agent of COVID-19 and a pathogen of immense global public health importance. Development of innovative direct-acting antiviral agents is sorely needed to address this virus. Peptide-conjugated morpholino oligomers (PPMO) are antisense agents composed of a phosphordiamidate morpholino oligomer covalently conjugated to a cell-penetrating peptide. PPMO require no delivery assistance to enter cells and are able to reduce expression of targeted RNA through sequence-specific steric blocking. OBJECTIVES AND METHODS: Five PPMO designed against sequences of genomic RNA in the SARS-CoV-2 5'-untranslated region and a negative control PPMO of random sequence were synthesized. Each PPMO was evaluated for its effect on the viability of uninfected cells and its inhibitory effect on the replication of SARS-CoV-2 in Vero-E6 cell cultures. Cell viability was evaluated with an ATP-based method and viral growth was measured with quantitative RT-PCR and TCID 50 infectivity assays. RESULTS: PPMO designed to base-pair with sequence in the 5'-terminal region or the leader transcription regulatory sequence-region of SARS-CoV-2 genomic RNA were highly efficacious, reducing viral titers by up to 4-6 log10 in cell cultures at 48-72 hours post-infection, in a non-toxic and dose-responsive manner. CONCLUSION: The data indicate that PPMO have the ability to potently and specifically suppress SARS-CoV-2 growth and are promising candidates for further pre-clinical development.