Recycling of Polymerase Chain Reaction (PCR) Kits.

Polymerase chain reaction (PCR) kits have been used as common diagnosing tools during the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, with daily worldwide usage in the millions. It is well known that at the beginning of the pandemic, there was a shortage of PCR kits. So far, the ecosystem of a PCR kit is linear use; that is, kits are produced, used once, and disposed of as biolab waste. Here, we show that to mitigate the risk of future shortages, it is possible to envision recyclable PCR kits based on a more sustainable use of nucleic acid resources. A PCR kit is mainly composed of primers, nucleotides, and enzymes. In the case of a positive test, the free nucleotides are polymerized onto the primers to form longer DNA strands. Our approach depolymerizes such strands, keeping the primers and regenerating the nucleotides, i.e., returning the nucleic acid materials to the original state. The polymerized long DNA strands are hydrolyzed into nucleotide monophosphates that are then phosphorylated into triphosphates using a method that is developed from a recent publication. We used oligonucleotides with a 3'-terminal phosphorothioate (PS) backbone modification as nonhydrolyzable PCR primers, which are able to undergo the recycling process unchanged. The nuclease resistance of oligonucleotides with a ribose sugar modification was also evaluated, which showed worse recycling efficiency than PS-modified oligonucleotides. We successfully recycled both PCR primers and nucleotide monomers (∼75% yield). We demonstrate that the method allows for the direct reuse of PCR kits. We also show that the recycled primers can be isolated and then added to endpoint or quantitative PCR. This recycling approach provides a new path for circularly reusing nucleic acid materials in PCR kits.

Dynamics of Microbial Community and Potential Microbial Pollutants in Shopping Malls.

Shopping malls offer various niches for microbial populations, potentially serving as sources and reservoirs for the spread of microorganisms of public health concern. However, knowledge about the microbiome and the distribution of human pathogens in malls is largely unknown. Here, we examine the microbial community dynamics and genotypes of potential pathogens from floor and escalator surfaces in shopping malls and adjacent road dusts and greenbelt soils. The distribution pattern of microbial communities is driven primarily by habitats and seasons. A significant enrichment of human-associated microbiota in the indoor environment indicates that human interactions with surfaces might be another strong driver for mall microbiomes. Neutral community models suggest that the microbial community assembly is strongly driven by stochastic processes. Distinct performances of microbial taxonomic signatures for environmental classifications indicate the consistent differences of microbial communities of different seasons/habitats and the strong anthropogenic effect on homogenizing microbial communities of shopping malls. Indoor environments harbored higher concentrations of human pathogens than outdoor samples, also carrying a high proportion of antimicrobial resistance-associated multidrug efflux genes and virulence genes. These findings enhanced the understanding of the microbiome in the built environment and the interactions between humans and the built environment, providing a basis for tracking biothreats and communicable diseases and developing sophisticated early warning systems. IMPORTANCE Shopping malls are distinct microbial environments which can facilitate a constant transmission of microorganisms of public health concern between humans and the built environment or between human and human. Despite extensive investigation of the natural environmental microbiome, no comprehensive profile of microbial ecology has been reported in malls. Characterizing microbial distribution, potential pathogens, and antimicrobial resistance will enhance our understanding of how these microbial communities are formed, maintained, and transferred and help establish a baseline for biosurveillance of potential public health threats in malls.

Towards a global One Health index: a potential assessment tool for One Health performance.

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.

Evaluation of inactivated COVID-19 vaccine on semen parameters in reproductive-age males: a retrospective cohort study.

During the coronavirus disease (COVID-19) epidemic, there have been concerns about the impact of vaccines on people's fertility, including the fertility of those who are currently preparing for pregnancy and those who might become pregnant in future. However, there is still a lack of research on the effect of the COVID-19 vaccine on male fertility, and it is not surprising that couples and donors have concerns regarding vaccination. In this study, a retrospective cohort study was conducted to examine semen quality before and after receipt of the inactivated COVID-19 vaccine. There were no statistically significant changes in semen parameters (volume, sperm concentration, progressive motility, and total progressive motile count) after two doses of vaccine (all P > 0.05). In summary, our study updates the most recent studies on the effects of the COVID-19 vaccine on male fertility, and the information from this study could be used to guide fertility recommendations for assisted reproductive technology (ART) patients and donors.

Viral diversity and potential environmental risk in microplastic at watershed scale: Evidence from metagenomic analysis of plastisphere.

Microplastics (MPs) have been considered as a new vector for the long-distance transport of pathogens in aquatic ecosystems. However, the composition of viral communities attached on MPs and their environmental risk are largely unknown. Here, we profiled the viral diversity and potential risk in five different MPs collected from the Beilun River based on metagenomic analysis. Nearly 2863 million raw reads were produced and assembled, and annotation resulted in the identification of 1719 different species of viruses in MPs. Viruses in polypropylene (PP) displayed the highest diversity, with about 250 specific viruses detected. Source tracking of viruses in MPs by the fast expectation-maximization microbial source tracking method (FEAST) demonstrated that viruses in upstream and downstream MPs are two major sources of viruses in estuary. Furthermore, the MP-type-dependent potential environmental risk of viruses was significant based on both antibiotic resistance genes (ARGs) and virulence factors (VFs) detected in viral metagenomes, and PP was confirmed with the highest potential environmental risk. This study reveals the high diversity and potential environmental risk of viruses in different MPs, and provides an important guidance for future environmental monitoring and understanding the potential risks associated with both viral transmission and MPs pollution.

Discarded masks as hotspots of antibiotic resistance genes during COVID-19 pandemic.

The demand for facial masks remains high. However, little is known about discarded masks as a potential refuge for contaminants and to facilitate enrichment and spread of antibiotic resistance genes (ARG) in the environment. We address this issue by conducting an in-situ time-series experiment to investigate the dynamic changes of ARGs, bacteria and protozoa associated with discarded masks. Masks were incubated in an estuary for 30 days. The relative abundance of ARGs in masks increased after day 7 but levelled off after 14 days. The absolute abundance of ARGs at 30 days was 1.29 × 1012 and 1.07 × 1012 copies for carbon and surgical masks, respectively. According to normalized stochasticity ratio analysis, the assembly of bacterial and protistan communities was determined by stochastic (NST = 62%) and deterministic (NST = 40%) processes respectively. A network analysis highlighted potential interactions between bacteria and protozoa, which was further confirmed by culture-dependent assays, that showed masks shelter and enrich microbial communities. An antibiotic susceptibility test suggested that antibiotic resistant pathogens co-exist within protozoa. This study provides an insight into the spread of ARGs through discarded masks and highlights the importance of managing discarded masks with the potential ecological risk of mask contamination.

Co-distribution of Light At Night (LAN) and COVID-19 incidence in the United States.

BACKGROUND: Light at night (LAN) as a circadian disruption factor may affect the human immune system and consequently increase an individual's susceptibility to the severity of infectious diseases, such as COVID-19. COVID-19 infections spread differently in each state in the United States (US). The current analysis aimed to test whether there is an association between LAN and COVID-19 cases in 4 selected US states: Connecticut, New York, California, and Texas. METHODS: We analyzed clustering patterns of COVID-19 cases in ArcMap and performed a multiple linear regression model using data of LAN and COVID-19 incidence with adjustment for confounding variables including population density, percent below poverty, and racial factors. RESULTS: Hotspots of LAN and COVID-19 cases are located in large cities or metro-centers for all 4 states. LAN intensity is associated with cases/1 k for overall and lockdown durations in New York and Connecticut (P < 0.001), but not in Texas and California. The overall case rates are significantly associated with LAN in New York (P < 0.001) and Connecticut (P < 0.001). CONCLUSIONS: We observed a significant positive correlation between LAN intensity and COVID-19 cases-rate/1 k, suggesting that circadian disruption of ambient light may increase the COVID-19 infection rate possibly by affecting an individual's immune functions. Furthermore, differences in the demographic structure and lockdown policies in different states play an important role in COVID-19 infections.

Impact of socioeconomic status，population mobility and control measures on COVID-10 development in major cities of China.

:To evaluate the impact of socioeconomic status，population mobility，prevention and control measures on the early-stage coronavirus disease 2019 (COVID-19) development in major cities of China. : The rate of daily new confirmed COVID-19 cases in the 51 cities with the largest number of cumulative confirmed cases as of February 19，2020 (except those in Hubei province) were collected and analyzed using the time series cluster analysis. It was then assessed according to three aspects，that is, socioeconomic status，population mobility，and control measures for the pandemic. : According to the analysis on the 51 cities，4 development patterns of COVID-19 were obtained，including a high-incidence pattern (in Xinyu)，a late high-incidence pattern (in Ganzi)，a moderate incidence pattern (in Wenzhou and other 12 cities)，and a low and stable incidence pattern (in Hangzhou and other 35 cities). Cities with different types and within the same type both had different scores on the three aspects. : There were relatively large difference on the COVID-19 development among different cities in China，possibly affected by socioeconomic status，population mobility and prevention and control measures that were taken. Therefore，a timely public health emergency response and travel restriction measures inside the city can interfere the development of the pandemic. Population flow from high risk area can largely affect the number of cumulative confirmed cases.

High serum lactate dehydrogenase and dyspnea: Positive predictors of adverse outcome in critical COVID-19 patients in Yichang.

BACKGROUND: Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in China, constitutes a Public Health Emergency of International Concern. It is well known that COVID-19 patients may have increased serum lactate dehydrogenase (LDH) levels in the early stage. The clinical changes in LDH may have predictive value in disease evolution and prognosis in critically ill COVID-19 patients. AIM: To examine serum LDH and clinical characteristics in patients with COVID-19 and their predictive value for prognosis. METHODS: This retrospective study analyzed the clinical data of forty-seven critical COVID-19 patients in the intensive care unit of the Third People's Hospital of Yichang City from January 27 to March 25, 2020 and divided them into survivors and non-survivors. The patients were diagnosed according to the World Health Organization interim guidance and critical cases met any one of the following criteria: Respiratory failure and required mechanical ventilation, the occurrence of shock, and the combined failure of other organs that required intensive care unit monitoring and treatments, according to the diagnostic criteria of critical COVID-19. Clinical data including symptoms, detection of SARS-CoV-2, chest computed tomography (CT) images, changes in serum LDH in different clinical phases, and prognosis were collected. Statistical analysis of the data was performed. Continuous variables were expressed as median (interquartile range) and compared with the Mann-Whitney U test. Categorical variables were compared with the Chi-square test. Survival data were analyzed using Kaplan-Meier survival curves and log-rank tests. RESULTS: According to chest CT images, we observed the alveolitis and fibrosis stages in all critical patients in this study. Most non-survivors died in the fibrosis stage. Non-survivors had fewer days of hospitalization, shorter disease duration, shorter duration of alveolitis and fibrosis, and had dyspnea symptoms at disease onset (P = 0.05). Both first and lowest LDH values in the alveolitis stage were more pronounced in non-survivors than in survivors (449.0 U/L vs 288.0 U/L, P = 0.0243; 445.0 U/L vs 288.0 U/L, P = 0.0199, respectively), while the first, lowest and highest values of serum LDH in non-survivors were all significantly increased compared to survivors in the fibrosis phase (449.0 U/L vs 225.5 U/L, P = 0.0028; 432.0 U/L vs 191.0 U/L, P = 0.0007; 1303.0 U/L vs 263.5 U/L, P = 0.0001, respectively). The cut-off points of first LDH values in the alveolitis and fibrosis phase for distinction of non-survivors from survivors were 397.0 U/L and 263.0 U/L, respectively. In the fibrosis stage, non-survivors had more days with high LDH than survivors (7.0 d vs 0.0 d, P = 0.0002). Importantly, patients with high LDH had a significantly shorter median survival time than patients with low LDH in the alveolitis phase (22.0 d vs 36.5 d, P = 0.0002), while patients with high LDH also had a significantly shorter median survival time than patients with low LDH in the fibrosis phase (27.5 d vs 40.0 d, P = 0.0008). The proportion of non-survivors with detectable SARS-CoV-2 until death in the alveolitis stage was significantly increased compared with that in the fibrosis stage (100% vs 35.7%, P = 0.0220). CONCLUSION: High LDH and dyspnea symptoms were positive predictors of an adverse outcome in critical COVID-19. The rapid progressive fibrosis stage was more perilous than the alveolitis stage, even if SARS-CoV-2 is undetectable.

Meteorological impact on the COVID-19 pandemic: A study across eight severely affected regions in South America.

The role of meteorological factors in the transmission of the COVID-19 still needs to be determined. In this study, the daily new cases of the eight severely affected regions in four countries of South America and their corresponding meteorological data (average temperature, maximum temperature, minimum temperature, average wind speed, visibility, absolute humidity) were collected. Daily number of confirmed and incubative cases, as well as time-dependent reproductive number (Rt) was calculated to indicate the transmission of the diseases in the population. Spearman's correlation coefficients were assessed to show the correlation between meteorological factors and daily confirmed cases, daily incubative cases, as well as Rt. In particular, the results showed that there was a highly significant correlation between daily incubative cases and absolute humidity throughout the selected regions. Multiple linear regression model further confirmed the negative correlation between absolute humidity and incubative cases. The absolute humidity is predicted to show a decreasing trend in the coming months from the meteorological data of recent three years. Our results suggest the necessity of continuous controlling policy in these areas and some other complementary strategies to mitigate the contagious rate of the COVID-19.

Integrating Biomedical, Ecological, and Sustainability Sciences to Manage Emerging Infectious Diseases.

Globalization accelerates the mobilization of microorganisms via international trade and transport. Growth in population, increasing connectivity, and rapid urbanization all exacerbate the consequent risk of pandemics of zoonotic diseases. Global problems require global solutions, particularly the co-ordination of international research in biomedical sciences, global ecology, and sustainability.