Predicting ozone formation in petrochemical industrialized Lanzhou city by interpretable ensemble machine learning.

Ground-level ozone (O3) formation depends on meteorology, precursor emissions, and atmospheric chemistry. Understanding the key drivers behind the O3 formation and developing an accurate and efficient method for timely assessing the O3-VOCs-NOx relationships applicable in different O3 pollution events are essential. Here, we developed a novel machine learning ensemble model coupled with a Shapley additive explanation algorithm to predict the O3 formation regime and derive O3 formation sensitivity curves. The algorithm was tested for O3 events during the COVID-19 lockdown, a sandstorm event, and a heavy O3 pollution episode (maximum hourly O3 concentration >200 µg/m3) from 2019 to 2021. We show that increasing O3 concentrations during the COVID-19 lockdown and the heavy O3 pollution event were mainly caused by the photochemistry subject to local air quality and meteorological conditions. Influenced by the sandstorm weather, low O3 levels were mainly attributable to weak sunlight and low precursor levels. O3 formation sensitivity curves demonstrate that O3 formation in the study area was in a VOCs-sensitive regime. The VOCs-specific O3 sensitivity curves can also help make hybrid and timely strategies for O3 abatement. The results demonstrate that machine learning driven by observational data has the potential to be a very useful tool in predicting and interpreting O3 formation.

3- to 24-month Follow-up on COVID-19 with Pulmonary Tuberculosis Survivors after Discharge: Results from a Prospective, Multicenter Study.

Objective: Coronavirus disease 2019 (COVID-19) and tuberculosis (TB) are major public health and social issues worldwide. The long-term follow-up of COVID-19 with pulmonary TB (PTB) survivors after discharge is unclear. This study aimed to comprehensively describe clinical outcomes, including sequela and recurrence at 3, 12, and 24 months after discharge, among COVID-19 with PTB survivors. Methods: From January 22, 2020 to May 6, 2022, with a follow-up by August 26, 2022, a prospective, multicenter follow-up study was conducted on COVID-19 with PTB survivors after discharge in 13 hospitals from four provinces in China. Clinical outcomes, including sequela, recurrence of COVID-19, and PTB survivors, were collected via telephone and face-to-face interviews at 3, 12, and 24 months after discharge. Results: Thirty-two COVID-19 with PTB survivors were included. The median age was 52 (45, 59) years, and 23 (71.9%) were men. Among them, nearly two-thirds (62.5%) of the survivors were moderate, three (9.4%) were severe, and more than half (59.4%) had at least one comorbidity (PTB excluded). The proportion of COVID-19 survivors with at least one sequela symptom decreased from 40.6% at 3 months to 15.8% at 24 months, with anxiety having a higher proportion over a follow-up. Cough and amnesia recovered at the 12-month follow-up, while anxiety, fatigue, and trouble sleeping remained after 24 months. Additionally, one (3.1%) case presented two recurrences of PTB and no re-positive COVID-19 during the follow-up period. Conclusion: The proportion of long symptoms in COVID-19 with PTB survivors decreased over time, while nearly one in six still experience persistent symptoms with a higher proportion of anxiety. The recurrence of PTB and the psychological support of COVID-19 with PTB after discharge require more attention.

Optimization of potential non-covalent inhibitors for the SARS-CoV-2 main protease inspected by a descriptor of the subpocket occupancy.

The main protease is regarded as an essential drug target for treating Coronavirus Disease 2019. In the present study, 13 marketed drugs were investigated to explore the possible binding mechanism, utilizing molecular docking, molecular dynamics simulation, and MM-PB(GB)SA binding energy calculations. Our results suggest that fusidic acid, polydatin, SEN-1269, AZD6482, and UNC-2327 have high binding affinities of more than 23 kcal mol-1. A descriptor was defined for the energetic occupancy of the subpocket, and it was found that S4 had a low occupancy of less than 10% on average. The molecular optimization of ADZ6482 via reinforcement learning algorithms was carried out to screen out three lead compounds, in which slight structural changes give more considerable binding energies and an occupancy of the S4 subpocket of up to 43%. The energetic occupancy could be a useful descriptor for evaluating the local binding affinity for drug design.

Industry herding in crypto assets

The aim of this paper is to investigate if herd behaviour is present in crypto assets at industry level. Using price information extracted from coinmarketcap.com between 29 April 2013 and 9 May 2022, we find evidence of herding and reverse herding in the crypto assets market. Concentrated periods of herding and reverse herding are particularly evident in the January 2020–April 2022 Covid period. At industry level, herding is more profound in large sectors with higher volatility. In smaller sectors where ventures are backed by ‘real assets’, very short periods of herding with marginal significance are detected. Reverse herding is present in all industries except Real Estate between June 2021 and May 2022, implying that strategies such as excessive ‘flight to quality’ or/and token picking are at play during the recent crypto crash. We also detect varying asymmetric herding at industry level. This paper further examines the factors that drive such industry herding and reverse herding in the crypto assets market, and our results show that industry concentration and investor sentiments contribute to the probability of herding/reverse herding. Our study provides further insights to the forces that drive the dispersion in crypto assets prices and contribute to the behavioural studies of the crypto market.

Histones released by NETosis enhance the infectivity of SARS-CoV-2 by bridging the spike protein subunit 2 and sialic acid on host cells.

Neutrophil extracellular traps (NETs) can capture and kill viruses, such as influenza viruses, human immunodeficiency virus (HIV), and respiratory syncytial virus (RSV), thus contributing to host defense. Contrary to our expectation, we show here that the histones released by NETosis enhance the infectivity of SARS-CoV-2, as found by using live SARS-CoV-2 and two pseudovirus systems as well as a mouse model. The histone H3 or H4 selectively binds to subunit 2 of the spike (S) protein, as shown by a biochemical binding assay, surface plasmon resonance and binding energy calculation as well as the construction of a mutant S protein by replacing four acidic amino acids. Sialic acid on the host cell surface is the key molecule to which histones bridge subunit 2 of the S protein. Moreover, histones enhance cell-cell fusion. Finally, treatment with an inhibitor of NETosis, histone H3 or H4, or sialic acid notably affected the levels of sgRNA copies and the number of apoptotic cells in a mouse model. These findings suggest that SARS-CoV-2 could hijack histones from neutrophil NETosis to promote its host cell attachment and entry process and may be important in exploring pathogenesis and possible strategies to develop new effective therapies for COVID-19.

Three doses of prototypic SARS-CoV-2 inactivated vaccine induce cross-protection against its variants of concern.

Variants are globally emerging very quickly following pandemic prototypic SARS-CoV-2. To evaluate the cross-protection of prototypic SARS-CoV-2 vaccine against its variants, we vaccinated rhesus monkeys with three doses of prototypic SARS-CoV-2 inactivated vaccine, followed by challenging with emerging SARS-CoV-2 variants of concern (VOCs). These vaccinated animals produced neutralizing antibodies against Alpha, Beta, Delta, and Omicron variants, although there were certain declinations of geometric mean titer (GMT) as compared with prototypic SARS-CoV-2. Of note, in vivo this prototypic vaccine not only reduced the viral loads in nasal, throat and anal swabs, pulmonary tissues, but also improved the pathological changes in the lung infected by variants of Alpha, Beta, and Delta. In summary, the prototypic SARS-CoV-2 inactivated vaccine in this study protected against VOCs to certain extension, which is of great significance for prevention and control of COVID-19.

Practice and experience of regional medical center entrance linkage and closed-loop management under the wartime situation of the COVID-19 in China

On 28 July 2021, the first indigenous case of novel coronavirus pneumonia (COVID-19) emerged in Yangzhou, marking the beginning of a public health crisis caused by the new coronavirus pneumonia. It is a significant challenge for hospitals to carry out prevention and control measures to ensure the safety of medical professionals and patients when facing the changes in an epidemic situation. Subei People’s Hospital, as one of the first group of “Grade III-class A” hospitals in Jiangsu Province and the Yangzhou Regional Medical Centre, responded quickly and scientifically to prevent and control the disease. A closed-loop management system was implemented at the hospital entrance (consisting of the outpatient clinic, emergency clinic, fever clinic, and buffer ward) and an epidemic prevention and control group was established with the assistance of multiple departments. This group optimized the pre-screening and triage system, standardized the fever clinic consultation process, and improved the construction of an information-based prevention and control network so that patients were detected, diagnosed, isolated, and treated early. The emergency management capability was improved to achieve zero missed consultations of patients attending for COVID-19 and to effectively maintain medical order during this critical period. This current report systematically summarizes the operational practices and the effectiveness achieved by implementation of the entrance closed-loop management in the hospital and analyzed the key operational issues for future reference by medical institutions and management departments.

Machine learning and algorithmic fairness in public and population health

Until now, much of the work on machine learning and health has focused on processes inside the hospital or clinic. However, this represents only a narrow set of tasks and challenges related to health;there is greater potential for impact by leveraging machine learning in health tasks more broadly. In this Perspective we aim to highlight potential opportunities and challenges for machine learning within a holistic view of health and its influences. To do so, we build on research in population and public health that focuses on the mechanisms between different cultural, social and environmental factors and their effect on the health of individuals and communities. We present a brief introduction to research in these fields, data sources and types of tasks, and use these to identify settings where machine learning is relevant and can contribute to new knowledge. Given the key foci of health equity and disparities within public and population health, we juxtapose these topics with the machine learning subfield of algorithmic fairness to highlight specific opportunities where machine learning, public and population health may synergize to achieve health equity.Algorithmic solutions to improve treatment are starting to transform health care. Mhasawade and colleagues discuss in this Perspective how machine learning applications in population and public health can extend beyond clinical practice. While working with general health data comes with its own challenges, most notably ensuring algorithmic fairness in the face of existing health disparities, the area provides new kinds of data and questions for the machine learning community.

Can situations awaken emotions? The compilation and evaluation of the Emotional Situation Sentence System (ESSS).

We aimed to establish and evaluate a standardized emotional situation sentence system (ESSS) relevant to the lives of college students to supplement prior literature and adapt to the needs of emotional research. Two studies were designed for this research; study 1 examined the effect of words in the ESSS and study 2 involved the use of pictures. For Study 1, 778 items were selected by 607 college students and 15 experts. We then tested the scale with 80 undergraduate participants. The ESSS sentences were rated on their degree of valence, arousal, and dominance using a 9-point scale. Cronbach's α (greater than 0.986) of the overall score as well as each sub-score in the three components confirmed the scale's reliability. As seen on a scatter plot, the results suggest that negative emotions (fear, disgust, anger, sadness, anxiety) are convergent and different from the distribution of positive (happiness) and neutral emotions. Study 2 included 30 participants to compare the difference in valence and arousal between the ESSS and emotional pictures. The results indicate that the ESSS is a standardized, situational, and ecological emotional contextual text system, well-suited to invoke emotion in college students. The ESSS has significantly better arousal and potency than pictures; moreover, it can be applied to experimental studies of anxiety-related emotions. However, emotion pictures have shorter response times, and wider application ranges, and they can include more cross-cultural characteristics compared to words.

Unsupervised PM2.5 anomalies in China induced by the COVID-19 epidemic.

To stop the spread of COVID-19 (2019 novel coronavirus), China placed lockdown on social activities across China since mid-January 2020. The government actions significantly affected emissions of atmospheric pollutants and unintentionally created a nationwide emission reduction scenario. In order to assess the impacts of COVID-19 on fine particular matter (PM2.5) levels, we developed a "conditional variational autoencoder" (CVAE) algorithm based on the deep learning to discern unsupervised PM2.5 anomalies in Chines cities during the COVID-19 epidemic. We show that the timeline of changes in number of cities with unsupervised PM2.5 anomalies is consistent with the timeline of WHO's response to COVID-19. Using unsupervised PM2.5 anomaly as a time node, we examine changes in PM2.5 before and after the time node to assess the response of PM2.5 to the COVID-19 lockdown. The rate of decrease of PM2.5 around the time node in northern China is 3.5 times faster than southern China, and decreasing PM2.5 levels in southern China is 3.5 times of that in northern China. Results were also compared with anomalous PM2.5 occurring in Chinese's Spring Festival from 2017 to 2019, PM2.5 anomalies during around Chinese New Year in 2020 differ significantly from 2017 to 2019. We demonstrate that this method could be used to detect the response of air quality to sudden changes in social activities.

The olfactory route is a potential way for SARS-CoV-2 to invade the central nervous system of rhesus monkeys.

Neurological manifestations are frequently reported in the COVID-19 patients. Neuromechanism of SARS-CoV-2 remains to be elucidated. In this study, we explored the mechanisms of SARS-CoV-2 neurotropism via our established non-human primate model of COVID-19. In rhesus monkey, SARS-CoV-2 invades the CNS primarily via the olfactory bulb. Thereafter, viruses rapidly spread to functional areas of the central nervous system, such as hippocampus, thalamus, and medulla oblongata. The infection of SARS-CoV-2 induces the inflammation possibly by targeting neurons, microglia, and astrocytes in the CNS. Consistently, SARS-CoV-2 infects neuro-derived SK-N-SH, glial-derived U251, and brain microvascular endothelial cells in vitro. To our knowledge, this is the first experimental evidence of SARS-CoV-2 neuroinvasion in the NHP model, which provides important insights into the CNS-related pathogenesis of SARS-CoV-2.

Telemedicine and healthcare disparities: a cohort study in a large healthcare system in New York City during COVID-19.

OBJECTIVE: Through the coronavirus disease 2019 (COVID-19) pandemic, telemedicine became a necessary entry point into the process of diagnosis, triage, and treatment. Racial and ethnic disparities in healthcare have been well documented in COVID-19 with respect to risk of infection and in-hospital outcomes once admitted, and here we assess disparities in those who access healthcare via telemedicine for COVID-19. MATERIALS AND METHODS: Electronic health record data of patients at New York University Langone Health between March 19th and April 30, 2020 were used to conduct descriptive and multilevel regression analyses with respect to visit type (telemedicine or in-person), suspected COVID diagnosis, and COVID test results. RESULTS: Controlling for individual and community-level attributes, Black patients had 0.6 times the adjusted odds (95% CI: 0.58-0.63) of accessing care through telemedicine compared to white patients, though they are increasingly accessing telemedicine for urgent care, driven by a younger and female population. COVID diagnoses were significantly more likely for Black versus white telemedicine patients. DISCUSSION: There are disparities for Black patients accessing telemedicine, however increased uptake by young, female Black patients. Mean income and decreased mean household size of a zip code were also significantly related to telemedicine use. CONCLUSION: Telemedicine access disparities reflect those in in-person healthcare access. Roots of disparate use are complex and reflect individual, community, and structural factors, including their intersection-many of which are due to systemic racism. Evidence regarding disparities that manifest through telemedicine can be used to inform tool design and systemic efforts to promote digital health equity.

The Gastrointestinal Tract Is an Alternative Route for SARS-CoV-2 Infection in a Nonhuman Primate Model.

BACKGROUND & AIMS: Gastrointestinal (GI) manifestations have been increasingly reported in patients with coronavirus disease 2019 (COVID-19). However, the roles of the GI tract in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are not fully understood. We investigated how the GI tract is involved in SARS-CoV-2 infection to elucidate the pathogenesis of COVID-19. METHODS: Our previously established nonhuman primate (NHP) model of COVID-19 was modified in this study to test our hypothesis. Rhesus monkeys were infected with an intragastric or intranasal challenge with SARS-CoV-2. Clinical signs were recorded after infection. Viral genomic RNA was quantified by quantitative reverse transcription polymerase chain reaction. Host responses to SARS-CoV-2 infection were evaluated by examining inflammatory cytokines, macrophages, histopathology, and mucin barrier integrity. RESULTS: Intranasal inoculation with SARS-CoV-2 led to infections and pathologic changes not only in respiratory tissues but also in digestive tissues. Expectedly, intragastric inoculation with SARS-CoV-2 resulted in the productive infection of digestive tissues and inflammation in both the lung and digestive tissues. Inflammatory cytokines were induced by both types of inoculation with SARS-CoV-2, consistent with the increased expression of CD68. Immunohistochemistry and Alcian blue/periodic acid-Schiff staining showed decreased Ki67, increased cleaved caspase 3, and decreased numbers of mucin-containing goblet cells, suggesting that the inflammation induced by these 2 types of inoculation with SARS-CoV-2 impaired the GI barrier and caused severe infections. CONCLUSIONS: Both intranasal and intragastric inoculation with SARS-CoV-2 caused pneumonia and GI dysfunction in our rhesus monkey model. Inflammatory cytokines are possible connections for the pathogenesis of SARS-CoV-2 between the respiratory and digestive systems.

Impacts of the COVID-19 pandemic on the dairy industry: Lessons from China and the United States and policy implications

The purposes of this study are to assess the COVID-19 pandemic's impacts on the dairy industries in China and the United States and to derive policy recommendations for enhancing the diary industries' resilience to pandemics and other market shocks. Specifically, data from the two nations are used to analyze and compare the mechanisms through which the pandemic has affected their dairy industries and to discuss potential lessons from their experiences. The findings suggest that this pandemic has heavily affected the dairy industries in both China and the United States through similar mechanisms, such as decreased farmgate milk prices, disruption and difficulties of moving milk within the supply chains, worker shortages, increased production costs, and lack of operating capital. There were also significant differences in the affecting mechanisms between the two nations, including transportation difficulties from widespread road closures and significant reduction in holiday sales of dairy products in China, and the shutdown of many dairy processors in the United States due to the closing of schools, restaurants, and hotels. While government financial reliefs are highly needed to help many dairy farms and processors survive this pandemic in the short term, the dairy industries and governments need to work together to develop long-term strategies and policies to balance the industries' efficiency and flexibility, product specialization and diversification, supply chain integration and local food systems, and market mechanisms and policy regulations and interventions.

Susceptibility of tree shrew to SARS-CoV-2 infection.

Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a pandemic event in the world, it has not only caused huge economic losses, but also a serious threat to global public health. Many scientific questions about SARS-CoV-2 and Coronavirus disease (COVID-19) were raised and urgently need to be answered, including the susceptibility of animals to SARS-CoV-2 infection. Here we tested whether tree shrew, an emerging experimental animal domesticated from wild animal, is susceptible to SARS-CoV-2 infection. No clinical signs were observed in SARS-CoV-2 inoculated tree shrews during this experiment except the increasing body temperature particularly in female animals. Low levels of virus shedding and replication in tissues occurred in all three age groups. Notably, young tree shrews (6 months to 12 months) showed virus shedding at the earlier stage of infection than adult (2 years to 4 years) and old (5 years to 7 years) animals that had longer duration of virus shedding comparatively. Histopathological examine revealed that pulmonary abnormalities were the main changes but mild although slight lesions were also observed in other tissues. In summary, tree shrew is less susceptible to SARS-CoV-2 infection compared with the reported animal models and may not be a suitable animal for COVID-19 related researches. However, tree shrew may be a potential intermediate host of SARS-CoV-2 as an asymptomatic carrier.

Serologic Detection of SARS-CoV-2 Infections in Hemodialysis Centers: A Multicenter Retrospective Study in Wuhan, China.

RATIONALE & OBJECTIVE: Patients receiving maintenance hemodialysis (MHD) are highly vulnerable to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The current study was designed to evaluate the prevalence of SARS-CoV-2 infection based on both nucleic acid testing (NAT) and antibody testing in Chinese patients receiving MHD. STUDY DESIGN: Cross-sectional study. SETTING & PARTICIPANTS: From December 1, 2019, to March 31, 2020, a total of 1,027 MHD patients in 5 large hemodialysis centers in Wuhan, China, were enrolled. Patients were screened for SARS-CoV-2 infection by symptoms and initial computed tomography (CT) of the chest. If patients developed symptoms after the initial screening was negative, repeat CT was performed. Patients suspected of being infected with SARS-CoV-2 were tested with 2 consecutive throat swabs for viral RNA. In mid-March 2020, antibody testing for SARS-CoV-2 was obtained for all MHD patients. EXPOSURE: NAT and antibody testing results for SARS-CoV-2. OUTCOMES: Morbidity, clinical features, and laboratory and radiologic findings. ANALYTICAL APPROACH: Differences between groups were examined using t test or Mann-Whitney U test, comparing those not infected with those infected and comparing those with infection detected using NAT with those with infection detected by positive serology test results. RESULTS: Among 1,027 patients receiving MHD, 99 were identified as having SARS-CoV-2 infection, for a prevalence of 9.6%. Among the 99 cases, 52 (53%) were initially diagnosed with SARS-CoV-2 infection by positive NAT; 47 (47%) were identified later by positive immunoglobulin G (IgG) or IgM antibodies against SARS-CoV-2. There was a spectrum of antibody profiles in these 47 patients: IgM antibodies in 5 (11%), IgG antibodies in 35 (74%), and both IgM and IgG antibodies in 7 (15%). Of the 99 cases, 51% were asymptomatic during the epidemic; 61% had ground-glass or patchy opacities on CT of the chest compared with 11.6% among uninfected patients (P<0.001). Patients with hypertensive kidney disease were more often found to have SARS-CoV-2 infection and were more likely to be symptomatic than patients with another primary cause of kidney failure. LIMITATIONS: Possible false-positive and false-negative results for both NAT and antibody testing; possible lack of generalizability to other dialysis populations. CONCLUSIONS: Half the SARS-CoV-2 infections in patients receiving MHD were subclinical and were not identified by universal CT of the chest and selective NAT. Serologic testing may help evaluate the overall prevalence and understand the diversity of clinical courses among patients receiving MHD who are infected with SARS-CoV-2.

Comparison of nonhuman primates identified the suitable model for COVID-19.

Identification of a suitable nonhuman primate (NHP) model of COVID-19 remains challenging. Here, we characterized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in three NHP species: Old World monkeys Macaca mulatta (M. mulatta) and Macaca fascicularis (M. fascicularis) and New World monkey Callithrix jacchus (C. jacchus). Infected M. mulatta and M. fascicularis showed abnormal chest radiographs, an increased body temperature and a decreased body weight. Viral genomes were detected in swab and blood samples from all animals. Viral load was detected in the pulmonary tissues of M. mulatta and M. fascicularis but not C. jacchus. Furthermore, among the three animal species, M. mulatta showed the strongest response to SARS-CoV-2, including increased inflammatory cytokine expression and pathological changes in the pulmonary tissues. Collectively, these data revealed the different susceptibilities of Old World and New World monkeys to SARS-CoV-2 and identified M. mulatta as the most suitable for modeling COVID-19.