Low serum level of citrullinated histone H3 in patients with dermatomyositis.

OBJECTIVES: We aimed at analyzing the serum levels of citrullinated histone H3 (CitH3) in patients with dermatomyositis (DM) and their association with disease activity. METHODS: Serum CitH3 levels were measured using enzyme-linked immunosorbent assays in serum samples obtained from 93 DM patients and 56 healthy controls (HCs). Receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminant capacity of CitH3 and other disease variables. The association between CitH3 and disease variables was analyzed using Pearson's rank correlation. RESULTS: Serum CitH3 level was significantly lower in DM patients than in HCs (p < 0.001). The ROC curve analysis revealed that CitH3 strongly discriminated DM patients from HCs (area under the curve [AUC], 0.86), and a combination of CitH3 and the ratio of neutrophil to lymphocyte counts (NLR) showed a greater diagnostic value (AUC, 0.92). Serum CitH3 levels were markedly lower in DM patients with normal muscle enzyme levels than in HCs (all p < 0.001), and when compared to an elevated group, the CitH3 levels were comparable (all p > 0.05). The CitH3 levels showed no difference between DM in active and remission groups. However, in a paired test with 18 hospitalized DM patients, the CitH3 levels were higher in remission state than in active state. Moreover, the CitH3 levels showed no correlation with disease variables that were associated with the disease activity of DM. CONCLUSIONS: Serum CitH3 level may serve as a useful biochemical marker for screening patients with DM from HCs, while its role in monitoring DM disease activity requires further research.

Impact of Novel Coronavirus Pneumonia on Agricultural Products Prices: A Case Study of Chengdu

Ensuring the basic stability of supply and prices of agricultural products bears on people's wellbeing and contributes to social development and stability. However, the outbreak of COVID-19 and a series of rules and regulations confining socialization adopted to deal with the epidemic have led to the prominent contradiction between supply and demand in the agricultural market, and the sharp fluctuations in the prices of agricultural products. In this paper, the price data of agricultural products in the main urban area of Chengdu in the 10 weeks before and 20 weeks after the Spring Festival from 2018 to 2020 were used to empirically study the impact of COVID-19 on local agricultural product prices by generalized multiple difference method (DID). The empirical results show that, first, compared with the Spring Festival of 2018 and 2019, the COVID-19 epidemic in the Spring Festival of 2020 led to an average increase of 105.02% in the retail prices of agricultural products in Chengdu, among which the increase of livestock and poultry, fruits and vegetables, and aquatic products was the most obvious, while the change of grain and oil prices was not significant. Second, compared with the demand side, the COVID-19 pandemic has a major impact on agricultural prices from the supply side. Third, the impact of COVID-19 on the retail prices of agricultural products is more obvious in areas where the primary industry is relatively small and industrialization is fast. Fourth, in the short term, the government's policy of suppressing prices does not restrain all agricultural prices. The above research findings provide a reference for understanding the adjustment mechanism of agricultural prices under the impact of the epidemic, and for effectively formulating relevant policies to stabilize the price of agricultural products, ensure supply, and alleviate the pressure on people's livelihood.

Performance evaluation of a non-invasive one-step multiplex RT-qPCR assay for detection of SARS-CoV-2 direct from saliva.

Polymerase chain reaction (PCR) has proven to be the gold-standard for SARS-CoV-2 detection in clinical settings. The most common approaches rely on nasopharyngeal specimens obtained from swabs, followed by RNA extraction, reverse transcription and quantitative PCR. Although swab-based PCR is sensitive, swabbing is invasive and unpleasant to administer, reducing patient compliance for regular testing and resulting in an increased risk of improper sampling. To overcome these obstacles, we developed a non-invasive one-step RT-qPCR assay performed directly on saliva specimens. The University of Nottingham Asymptomatic Testing Service protocol simplifies sample collection and bypasses the need for RNA extraction, or additives, thus helping to encourage more regular testing and reducing processing time and costs. We have evaluated the assay against the performance criteria specified by the UK regulatory bodies and attained accreditation (BS EN ISO/IEC 17,025:2017) for SARS-CoV-2 diagnostic testing by the United Kingdom Accreditation Service. We observed a sensitivity of 1 viral copy per microlitre of saliva, and demonstrated a concordance of > 99.4% between our results and those of other accredited testing facilities. We concluded that saliva is a stable medium that allows for a highly precise, repeatable, and robust testing method.

Direct RT-qPCR Assay for the Detection of SARS-CoV-2 in Saliva Samples.

Since mid-2020 there have been complexities and difficulties in the standardisation and administration of nasopharyngeal swabs. Coupled with the variable and/or poor accuracy of lateral flow devices, this has led to increased societal 'testing fatigue' and reduced confidence in test results. Consequently, asymptomatic individuals have developed reluctance towards repeat testing, which remains the best way to monitor COVID-19 cases in the wider population. On the other hand, saliva-based PCR, a non-invasive, highly sensitive, and accurate test suitable for everyone, is gaining momentum as a straightforward and reliable means of detecting SARS-CoV-2 in symptomatic and asymptomatic individuals. Here, we provide an itemised list of the equipment and reagents involved in the process of sample submission, inactivation and analysis, as well as a detailed description of how each of these steps is performed.

Predicting the Incident Cases of Emerging Infectious Disease Using a Bayesian Probability Model - China, February 2020.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: The exact number of incident cases of emerging infectious diseases on a daily basis is of great importance to the disease control and prevention, but it is not directly available from the current surveillance system in time. WHAT IS ADDED BY THIS REPORT?: In this study, a Bayesian statistical method was proposed to estimate the posterior parameters of the gamma probability distribution of the lag time between the onset date and the reporting time based on the surveillance data. And then the posterior parameters and corresponding cumulative gamma probability distribution were used to predict the actual number of new incident cases and the number of unreported cases per day. The proposed method was used for predicting COVID-19 incident cases from February 5 to February 26, 2020. The final results show that Bayesian probability model predictions based on data reported by February 28, 2020 are very close to those actually reported a month later. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: This research provides a Bayesian statistical approach for early estimation of the actual number of cases of incidence based on surveillance data, which is of great value in the prevention and control practice of epidemics.