Clinical features and outcomes in kidney transplant recipients with COVID-19 pneumonia: a single center retrospective cohort study (preprint)

Objective This retrospective cohort study aimed to assess the clinical characteristics, treatment outcomes, and short-term prognosis of kidney transplant recipients (KTRs) with concurrent coronavirus disease 2019 (COVID-19) pneumonia.Methods KTRs with COVID-19 pneumonia who were admitted to our hospital from December 28, 2022, to March 28, 2023 were included in the study, and their clinical symptoms, response to antiviral medications, and short-term prognosis were analyzed.Results A total of 64 KTRs with initial diagnosis of COVID-19 pneumonia were included in this study. The primary symptoms were fever, cough, and myalgia, with an incidence of 79.7%, 89.1%, and 46.9%, respectively. The administration of antiviral drugs (paxlovid or molnupiravir) within 1–5 days and for over 5 days demonstrated a statistically significant reduction in viral shedding time compared to the group without antiviral medication (P = 0.002). Both the paxlovid and molnupiravir treatment groups exhibited a significantly shorter duration of viral shedding time in comparison to the group without antiviral drugs (P = 0.002). After 6 months of recovery, there was no significantly negative impact on transplant kidney function (P = 0.294).Conclusion Fever, cough, and myalgia remain common initial symptoms of concurrent COVID-19 pneumonia in KTRs. The earlier use of antiviral drugs (the paxlovid or molnupiravir) is associated with better therapeutic outcomes. severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had limited impact on short-term renal function of the KTRs with concurrent moderate or severe COVID-19 pneumonia.

Relocalization evaluation of arbidol in the treatment of COVID-19 (preprint)

Background: The spread of COVID-19 continues, the mutation of SARS-COV-2 is still difficult to control, and the need for antiviral drugs to treat COVID-19 remains urgent. The use of arbidol in the treatment of COVID-19 is limited and controversial. Methods To clarify the efficacy of arbidol on COVID-19, we collected 25 cases and 178 related studies. We analyzed the treatment information of arbidol based on the obtained cases, expanded the scope of the study, and collected current studies on the treatment of COVID-19 in various databases for in-depth analysis. Results History analysis showed that arbidol was effective (76% cure rate) compared with other drugs. However, compared with other antiviral drugs or standard therapy, the arbidol group had no significant advantage in reducing the time to negative virus transformation, length of hospital stays, or improvement in CT (MD=0.22, 95%CI -0.29-0.73; MD = 0.61, 95% CI 1.46 to 2.67; RR=1.15, 95%CI 0.88-1.50); Analysis of adverse events showed no significant difference between the arbidol group and the other groups (RR=0.82, 95%CI 0.25-2.71). Conclusion Our study showed that arbidol had no significant effect on COVID-19, but showed a slight advantage in CT improvement and adverse events. Our study objectively evaluated the efficacy of arbidol in the treatment of COVID-19 and provided some guidance for arbidol in the treatment of COVID-19.

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At the end of 2022, the World Health Organization reported an increase in group A Streptococcus (GAS) infections, such as scarlet fever, in multiple countries. The outbreak primarily affected children under 10 years old, and the number of deaths was higher than anticipated, causing international concern. This paper reviews the current state of the GAS disease outbreak, its causes, and response measures. The authors aim to draw attention from clinical workers in China and increase their awareness and vigilance regarding this epidemic. Healthcare workers should be aware of the potential epidemiological changes in infectious diseases that may arise after the optimization of control measures for coronavirus disease 2019 to ensure children's health.

The dynamic change of serotype distribution and antimicrobial resistance of pneumococcal isolates since PCV13 administration and COVID-19 control in Urumqi, China.

Objective: This study aims to analyze the serotype distribution and drug resistance of Streptococcus pneumoniae isolated from children aged 8 days to 7 years in Urumqi, China, between 2014 to 2021, during which PCV13 was introduced in the private sector's immunization program and COVID-19 control was administrated in the last 2 years. Methods: Serotypes of S. pneumoniae isolates were determined by Quellung reaction, and their susceptibility against 14 antimicrobials were tested. According to the start year of PCV13 administration (2017) and COVID-19 control (2020), the study period was divided into three stages: 2014-2015, 2018-2019, and 2020-2021. Results: A total of 317 isolates were involved in this study. The most common serotypes were type 19F (34.4%), followed by 19A (15.8%), 23F (11.7%), 6B (11.4%), and 6A(5.0%). The coverage rate of both PCV13 and PCV15 was 83.0%. The coverage of PCV20 was a little higher at 85.2%. The resistance rate against penicillin was 28.6% according to the breakpoints of oral penicillin, which would reach up to 91.8% based on the breakpoints of parenteral penicillin for meningitis. The resistance rates to erythromycin, clindamycin, tetracycline, and sulfamethoxazole-trimethoprim were 95.9%, 90.2%, 88.9%, and 78.8%, respectively. The PCV13 isolate was more resistant to penicillin than the non-PCV13 ones. There was not any significant change found in the serotype distribution since the PCV13 introduction and the COVID-19 control. The resistance rate against oral penicillin slightly elevated to 34.5% in 2018-2019 from 30.7% in 2014-2015 and then decreased significantly to 18.1% in 2020-2021 (χ 2 = 7.716, P < 0.05), while the resistance rate to ceftriaxone (non-meningitis) continuously declined from 16.0% in 2014-2015 to 1.4% in 2018-2019 and 0% in 2020-2021 (Fisher = 24.463, P < 0.01). Conclusion: The common serotypes of S. pneumoniae isolated from children in Urumqi were types 19F, 19A, 23F, 6B, and 6A, which we found to have no marked change since the PCV13 introduction and the COVID-19 control However, the resistance rate to oral penicillin and ceftriaxone significantly declined in the COVID-19 control stage.

Surface ozone changes during the COVID-19 outbreak in China: An insight into the pollution characteristics and formation regimes of ozone in the cold season.

The countrywide lockdown in China during the COVID-19 pandemic provided a natural experiment to study the characteristics of surface ozone (O3). Based on statistical analysis of air quality across China before and during the lockdown, the tempo-spatial variations and site-specific formation regimes of wintertime O3 were analyzed. The results showed that the O3 pollution with concentrations higher than air quality standards could occur widely in winter, which had been aggravated by the emission reduction during the lockdown. On the national scale of China, with the significant decrease (54.03%) in NO2 level from pre-lockdown to COVID-19 lockdown, the maximum daily 8-h average concentration of O3 (MDA8h O3) increased by 39.43% from 49.05 to 64.22 µg/m3. This increase was comprehensively contributed by attenuated NOx suppression and favorable meteorological changes on O3 formation during the lockdown. As to the pollution states of different monitoring stations, surface O3 responded oppositely to the consistent decreased NO2 across China. The O3 levels were found to increase in the northern and central regions, but decrease in the southern region, where the changes in both meteorology (e.g. temperature drops) and precursors (reduced emissions) during the lockdown had diminished local O3 production. The spatial differences in NOx levels generally dictate the site-specific O3 formation regimes in winter, with NOx-titration/VOCs-sensitive regimes being dominant in northern and central China, while VOCs-sensitive/transition regimes being dominant in southern China. These findings highlight the influence of NOx saturation levels on winter O3 formation and the necessity of VOCs emission reductions on O3 pollution controls.

Decline of onset-to-diagnosis interval and its impacts on clinical outcome of COVID-19 in China: a nation-wide observational study.

BACKGROUND: To quantitatively assess the impact of the onset-to-diagnosis interval (ODI) on severity and death for coronavirus disease 2019 (COVID-19) patients. METHODS: This retrospective study was conducted based on the data on COVID-19 cases of China over the age of 40 years reported through China's National Notifiable Infectious Disease Surveillance System from February 5, 2020 to October 8, 2020. The impacts of ODI on severe rate (SR) and case fatality rate (CFR) were evaluated at individual and population levels, which was further disaggregated by sex, age and geographic origin. RESULTS: As the rapid decline of ODI from around 40 days in early January to < 3 days in early March, both CFR and SR of COVID-19 largely dropped below 5% in China. After adjusting for age, sex, and region, an effect of ODI on SR was observed with the highest OR of 2.95 (95% CI 2.37‒3.66) at Day 10-11 and attributable fraction (AF) of 29.1% (95% CI 22.2‒36.1%) at Day 8-9. However, little effect of ODI on CFR was observed. Moreover, discrepancy of effect magnitude was found, showing a greater effect from ODI on SR among patients of male sex, younger age, and those cases in Wuhan. CONCLUSION: The ODI was significantly associated with the severity of COVID-19, highlighting the importance of timely diagnosis, especially for patients who were confirmed to gain increased benefit from early diagnosis to some extent.

Quality of online video resources concerning patient education for neck pain: A YouTube-based quality-control study.

Background: More than 70 percent of the world's population is tortured with neck pain more than once in their vast life, of which 50-85% recur within 1-5 years of the initial episode. With medical resources affected by the epidemic, more and more people seek health-related knowledge via YouTube. This article aims to assess the quality and reliability of the medical information shared on YouTube regarding neck pain. Methods: We searched on YouTube using the keyword "neck pain" to include the top 50 videos by relevance, then divided them into five and seven categories based on their content and source. Each video was quantitatively assessed using the Journal of American Medical Association (JAMA), DISCERN, Global Quality Score (GQS), Neck Pain-Specific Score (NPSS), and video power index (VPI). Spearman correlation analysis was used to evaluate the correlation between JAMA, GQS, DISCERN, NPSS and VPI. A multiple linear regression analysis was applied to identify video features affecting JAMA, GQS, DISCERN, and NPSS. Results: The videos had a mean JAMA score of 2.56 (SD = 0.43), DISCERN of 2.55 (SD = 0.44), GQS of 2.86 (SD = 0.72), and NPSS of 2.90 (SD = 2.23). Classification by video upload source, non-physician videos had the greatest share at 38%, and sorted by video content, exercise training comprised 40% of the videos. Significant differences between the uploading sources were observed for VPI (P = 0.012), JAMA (P < 0.001), DISCERN (P < 0.001), GQS (P = 0.001), and NPSS (P = 0.007). Spearman correlation analysis showed that JAMA, DISCERN, GQS, and NPSS significantly correlated with each other (JAMA vs. DISCERN, p < 0.001, JAMA vs. GQS, p < 0.001, JAMA vs. NPSS, p < 0.001, DISCERN vs. GQS, p < 0.001, DISCERN vs. NPSS, p < 0.001, GQS vs. NPSS, p < 0.001). Multiple linear regression analysis suggested that a higher JAMA score, DISCERN, or GQS score were closely related to a higher probability of an academic, physician, non-physician or medical upload source (P < 0.005), and a higher NPSS score was associated with a higher probability of an academic source (P = 0.001) than of an individual upload source. Conclusions: YouTube videos pertaining to neck pain contain low quality, low reliability, and incomplete information. Patients may be put at risk for health complications due to inaccurate, and incomplete information, particularly during the COVID-19 crisis. Academic groups should be committed to high-quality video production and promotion to YouTube users.

Predicting CO2 Emission Footprint Using AI through Machine Learning

Adequate CO2 is essential for vegetation, but industrial chimneys and land, space and oceanic vehicles exert tons of excessive CO2 and are mostly responsible for the greenhouse effect, global warming and climate change. Due to COVID-19, CO2 emission was in 2020 at its lowest level compared to prior decades. However, it is unknown how long it will take to reduce CO2 emission to a tolerable point. Furthermore, it is also unknown to what extent it can increase or change in the future. Accurate forecasting of CO2 emissions has real significance for choosing the optimum ways of reducing CO2 emissions. Although some existing models have noticeable CO2 emission forecasting accuracy, the models implemented in this work have more efficacy in prediction due to incorporating COVID-19's effect on CO2 emission. This paper implements four prediction models using SARIMA (SARIMAX) based on ARIMA. The four models are based on the time period of the surge of the COVID-19 pandemic. The main objective of this work is to compare these four models to suggest an effective model to predict the total CO2 emissions for the future. The study forecasts global total CO2 emission from 2022 to 2027 for near future prediction, 2022 to 2054 for future prediction and 2022 to 2072 for far future prediction. Among the various error measures, mean absolute percentage error (MAPE) is chosen for accuracy comparison. The calculation yields different accuracy for the four SARIMAX models. The MAPEs for the four methods are: pre-COV (MAPE: 0.32), start-COV (MAPE: 0.28), trans-COV (MAPE: 0.19), post-COV (MAPE: 0.09). The MAPE value is relatively low for post-COV (MAPE: 0.09). Hence, it can be inferred that post-COV are suitable models to forecast the global total CO2 emission for the future. The post-COV predictions for the global total CO2 emission for the years 2022 to 2027 are: 36,218.59, 36,733.69, 37,238.29, 37,260.88, 37,674.01 and 37,921.47 million tons (MT). This study successfully predicts CO2 emission either for the COVID-19 period or the post-COVID-19 normal periods. The Machine Learning (ML) method used in this study has shown good agreement with the IPCC model in predicting the past emissions, the current emissions due to COVID-19 and the emissions of the upcoming future. These prediction results can be an asset for the decision support system to develop a suitable policy for global CO2 emission reduction. For future research, a number of other external influence variables responsible for CO2 emission can be added for finer forecasts. This research is an original work in predicting COVID-19-affected CO2 emission using AI through the ML methodology.

Targeting epigenetic regulators for inflammation: Mechanisms and intervention therapy.

Emerging evidence indicates that resolution of inflammation is a critical and dynamic endogenous process for host tissues defending against external invasive pathogens or internal tissue injury. It has long been known that autoimmune diseases and chronic inflammatory disorders are characterized by dysregulated immune responses, leading to excessive and uncontrol tissue inflammation. The dysregulation of epigenetic alterations including DNA methylation, posttranslational modifications to histone proteins, and noncoding RNA expression has been implicated in a host of inflammatory disorders and the immune system. The inflammatory response is considered as a critical trigger of epigenetic alterations that in turn intercede inflammatory actions. Thus, understanding the molecular mechanism that dictates the outcome of targeting epigenetic regulators for inflammatory disease is required for inflammation resolution. In this article, we elucidate the critical role of the nuclear factor-κB signaling pathway, JAK/STAT signaling pathway, and the NLRP3 inflammasome in chronic inflammatory diseases. And we formulate the relationship between inflammation, coronavirus disease 2019, and human cancers. Additionally, we review the mechanism of epigenetic modifications involved in inflammation and innate immune cells. All that matters is that we propose and discuss the rejuvenation potential of interventions that target epigenetic regulators and regulatory mechanisms for chronic inflammation-associated diseases to improve therapeutic outcomes.

Genetic screening for hypertension and COVID-19 reveals functional variant of SPEG associated with severe COVID-19 in female (preprint)

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 6.4 million deaths worldwide and is still spreading among global populations. The prevalent comorbidity between hypertension and severe COVID-19 suggests common genetic factors may affect the outcome of both diseases. As both hypertension and severe COVID-19 demonstrate sex-specific prevalence, common genetic factors among the two diseases may display gender-based differential associations. By evaluating COVID-19 association signals of 172-candidate hypertension single nucleotide polymorphisms derived from more than one million European individuals in two severe COVID-19 genome-wide association studies from UK BioBank with European ancestry, we revealed one functional cis expression quantitative trait locus of SPEG (rs12474050) associating with both hypertension and severe COVID-19 in female. The risk allele of rs12474050*T is correlated with lower SPEG expression in muscle-skeletal, heart-atrial appendage, and heart-left ventricle; among these tissues the SPEG expression is higher in female than in male COVID-19 patients. Further analysis revealed SPEG is mainly expressed in cardiomyocytes in heart and is upregulated upon SARS-CoV-2 infection, with significantly higher folder change of SPEG expression observed in female compared to male COVID-19 patients. Taken together, our analyses strongly suggest the involvement of SPEG in both hypertension and severe COVID-19 in female, which provides new insights for sex-specific effect of severe COVID-19 in female.

Does It Matter to Establish a Strategic Partnership for COVID-19 Prevention and Control? The Perspective of Multiple Distances in Emerging Economies

The rapid spread of the COVID-19 pandemic in early 2020 has impacted the politics, economy and society of countries around the world. The public health diplomacy system through which developed countries in Europe and America used to provide vertical one-way assistance to developing countries faces huge challenges. How emerging economies can cooperate to fight the pandemic on the basis of mutual trust and mutual benefit has become an urgent issue. In this paper, we examine the impact of political mutual trust on the effectiveness of pandemic prevention and control from the perspective of establishing strategic partnerships between emerging economies. Furthermore, taking into account the huge differences between emerging economies, this paper explores institutional distance, cultural distance, and geographical distance—the adjustment effect of the control effect. Studies have shown that the improvement of political mutual trust is conducive to the formation of a community of shared futures between countries and has a positive effect on curbing the spread of the pandemic. The increase of the three-dimensional distance of institutions, culture, and geography will weaken the effect of establishing strategic partners for pandemic prevention and control. This paper explores a new model of horizontal international cooperation among emerging economies, and provides a reference for emerging economies to deal with common globalization issues in the future.

Comparative miRNA transcriptomics of macaques and mice reveals MYOC is an inhibitor for Cryptococcus neoformans invasion into the brain.

Cryptococcal meningoencephalitis (CM) is emerging as an infection in HIV/AIDS patients shifted from primarily ART-naive to ART-experienced individuals, as well as patients with COVID-19 and immunocompetent hosts. This fungal infection is mainly caused by the opportunistic human pathogen Cryptococcus neoformans. Brain or central nervous system (CNS) dissemination is the deadliest process for this disease; however, mechanisms underlying this process have yet to be elucidated. Moreover, illustrations of clinically relevant responses in cryptococcosis are currently limited due to the low availability of clinical samples. In this study, to explore the clinically relevant responses during C. neoformans infection, macaque and mouse infection models were employed and miRNA-mRNA transcriptomes were performed and combined, which revealed cytoskeleton, a major feature of HIV/AIDS patients, was a centric pathway regulated in both infection models. Notably, assays of clinical immune cells confirmed an enhanced macrophage "Trojan Horse" in patients with HIV/AIDS, which could be shut down by cytoskeleton inhibitors. Furthermore, myocilin, encoded by MYOC, was found to be a novel enhancer for the macrophage "Trojan Horse," and an enhanced fungal burden was achieved in the brains of MYOC-transgenic mice. Taken together, the findings from this study reveal fundamental roles of the cytoskeleton and MYOC in fungal CNS dissemination, which not only helps to understand the high prevalence of CM in HIV/AIDS but also facilitates the development of novel therapeutics for meningoencephalitis caused by C. neoformans and other pathogenic microorganisms.

Efficacy and Safety Evaluation of Arbidol in Patients with COVID-19 (preprint)

Background The spread of COVID-19 continues, the mutation of SARS-COV-2 is still difficult to control, and the need for antiviral drugs to treat COVID-19 remains urgent. The use of arbidol in the treatment of COVID-19 is limited and controversial. Methods To clarify the efficacy of arbidol on COVID-19, we collected 25 cases and 178 related studies. We analyzed the treatment information of arbidol based on the obtained cases, expanded the scope of the study, and collected current studies on the treatment of COVID-19 in various databases for in-depth analysis. Results History analysis showed that arbidol was effective (76% cure rate) compared with other drugs. However, compared with other antiviral drugs or standard therapy, the arbidol group had no significant advantage in reducing the time to negative virus transformation, length of hospital stays, or improvement in CT (MD=0.22, 95%CI -0.29-0.73; MD = 0.61, 95% CI 1.46 to 2.67; RR=1.15, 95%CI 0.88-1.50); Analysis of adverse events showed no significant difference between the arbidol group and the other groups (RR=0.82, 95%CI 0.25-2.71). Conclusion Our study showed that arbidol had no significant effect on COVID-19, but showed a slight advantage in CT improvement and adverse events. Our study objectively evaluated the efficacy of arbidol in the treatment of COVID-19 and provided some guidance for arbidol in the treatment of COVID-19.

Swarm Robots Cooperative and Persistent Distribution Modeling and Optimization Based on the Smart Community Logistics Service Framework

The high efficiency, flexibility, and low cost of robots provide huge opportunities for the application and development of intelligent logistics. Especially during the COVID-19 pandemic, the non-contact nature of robots effectively helped with preventing the spread of the epidemic. Task allocation and path planning according to actual problems is one of the most important problems faced by robots in intelligent logistics. In the distribution, the robots have the fundamental characteristics of battery capacity limitation, limited load capacity, and load affecting transportation capacity. So, a smart community logistics service framework is proposed based on control system, automatic replenishment platform, network communication method, and coordinated distribution optimization technology, and a Mixed Integer Linear Programming (MILP) model is developed for the collaborative and persistent delivery of a multiple-depot vehicle routing problem with time window (MDVRPTW) of swarm robots. In order to solve this problem, a hybrid algorithm of genetically improved set-based particle swarm optimization (S-GAIPSO) is designed and tested with numerical cases. Experimental results show that, Compared to CPLEX, S-GAIPSO has achieved gaps of 0.157%, 1.097%, and 2.077% on average, respectively, when there are 5, 10, and 20 tasks. S-GAIPSO can obtain the optimal or near-optimal solution in less than 0.35 s, and the required CPU time slowly increases as the scale increases. Thus, it provides utility for real-time use by handling a large-scale problem in a short time.

Self-distillation contrastive learning enables clustering-free signature extraction and mapping to multimodal single-cell atlas of multimillion scale (preprint)

Massively generated single-cell multi-omics datasets are revolutionizing biological studies of heterogenous tissues and organisms, which necessitate powerful computational methods to unleash the full potential of these tremendous data. Here, we present Concerto, stands for self-distillation contrastive learning of cell representations, a self-supervised representation learning framework optimized with asymmetric teacher-student configuration to analyze single-cell multi-omics datasets with scalability up to building 10 million-cell reference within 1.5 hour and querying 10k cells within 8 seconds. Concerto leverages dropout layer as minimal data augmentation to learn meaningful cell representations in a contrastive manner. The teacher module uses attention mechanism to aggregate contextualized gene embeddings within cellular context, while the student module uses simpler dense structure with discreate input. The learned task-agnostic representations can be adapted to a broad range of single-cell computation tasks. 1) Via supervised fine-tuning, Concerto enables automatic cell classification as well as novel cell-type discovery; 2) Attention weights provide model interpretability via automatically extracting specific molecular signatures at single-cell resolution without the needs of clustering; 3) Via source-aware training, Concerto supports efficient data integration by projecting all cells across multiple batches into a joint embedding space. 4) Via batch-aware inference or unsupervised fine-tuning, Concerto enables mapping query cells onto reference and accurately transferring annotations. Concerto can flexibly extend to multi-omics datasets simply through cross-modality summation operation to obtain unified cell embeddings. Using examples from human peripheral blood, human thymus, human pancreas, and mouse tissue atlas, Concerto shows superior performance benchmarking against other top-performing methods. We also demonstrate Concerto recapitulates detailed COVID-19 disease variation through query-to-reference mapping. Concerto can operate on all genes and represents a fully data-driven approach with minimum prior distribution assumptions, eliminating the needs of PCA-like or autoencoder-like dimensionality reduction, which significantly reforms the current best practice. Concerto is a simple, straightforward, robust, and scalable framework, offering a brand new perspective to derive cell representations and can effectively satisfy the emerging paradigm of query-to-reference mapping in the era of atlas-level single-cell multimodal analysis.

Etiological and epidemiological features of acute respiratory infections in China.

Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children <5 years old and school-age children have the highest viral positivity rate (46.9%) and bacterial positivity rate (30.9%). Influenza virus, respiratory syncytial virus and human rhinovirus are the three leading viral pathogens with proportions of 28.5%, 16.8% and 16.7%, and Streptococcus pneumoniae, Mycoplasma pneumoniae and Klebsiella pneumoniae are the three leading bacterial pathogens (29.9%, 18.6% and 15.8%). Negative interactions between viruses and positive interactions between viral and bacterial pathogens are common. A Join-Point analysis reveals the age-specific positivity rate and how this varied for individual pathogens. These data indicate that differential priorities for diagnosis, prevention and control should be highlighted in terms of acute respiratory tract infection patients' demography, geographic locations and season of illness in China.

Remote Chemistry Teacher Professional Development Delivery: Enduring Lessons for Programmatic Redesign

COVID-19 has thrust educators into a period of uncertainty, complicating conventional ways of teaching and learning. We suspect that the pandemic has magnified the challenges that some high school teachers already experience, particularly when they are the sole chemistry teacher at their school. The pandemic has likely inhibited collegial interactions and access to professional development (PD). Our reflections from redesigning a face-to-face PD program to one that is remotely delivered provide recommendations that advance PD accessibility and interactivity to mitigate isolation and other longstanding challenges teachers may face. In this article, we discuss how the cognitive learning model informed emergent teaching practices that guided the transformation of the PD's implementation for 20 high school chemistry teachers. Our reflections on the PD's strengths, areas for improvement, and insights alongside participant feedback provide enduring guidelines for fellow teacher educators. Specifically, we forward the importance of conceptualizing theory-informed design principles first, and then modifying the delivery with appropriate tools and technologies. As PD facilitators, we also draw attention to the necessity for flexibility. Remaining open to adaptation during implementation is crucial to advance teacher learning and engagement. We hope our process for how and why our PD program was redesigned will inspire future teacher educators to explore new, postpandemic ways of maximizing high-quality PD experiences.

Biomimetic Design and Mass Production of Sustainable Multiscale Cellulose Fibers‐Based Hierarchical Filter Materials for Protective Clothing

As a core part of personal protective equipment (PPE), filter materials play a key role in individual protection, especially in the fight against the COVID‐19. Here, a high‐performance multiscale cellulose fibers‐based filter material is introduced for protective clothing, which overcomes the limitation of mutual exclusion of filtration and permeability in cellulose‐based filter materials. With the hierarchical biomimetic structure design and the active surface of multiscale cellulose fibers, high PM2.5 removal efficiency of ≈92% is achieved with the high moisture transmission rate of 8 kg m−2 d−1. Through a simple and effective dip‐coating and roll‐to‐roll process, the hierarchical filter materials can be made on a large scale and further fabricated into high‐quality protective clothing by industrial production equipment. [ABSTRACT FROM AUTHOR] Copyright of Advanced Materials Technologies is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The impact of intervention to the incidence of natural focus diseases during the outbreak of COVID-19 in Jiangsu Province, China (preprint)

Doxorubicin (DOX) is a well-known chemotherapeutic drug for most malgnencies including breast cancer and leukemia whilst the usage of DOX is limited owing to its cardiotoxicity. The present study analyzed the effects of crocin on doxorubicin’s cardiotoxic efect in rat myocardium and searched their mechanistic interaction in the pathogenesis of DOX-induced myocardial toxicity. Forty rats were divided into four groups; (a) control (received normal saline as a dose of 1 ml/kg by ip for 15 days), (b) Crocin (received crocin as a dose of 40 mg/kg/24h by ip for 15 days), (c) DOX (received DOX as a dose of 2 mg/kg/48h by ip in six injection, cumulative dose 12 mg/kg), and (d) DOX+Crocin (received DOX as a dose of 2 mg/kg/48h by ip in six injection and crocin as a dose of 40 mg/kg/24h ip for 15 days). According to the present study, DOX administration caused significant increases in lipid indices (triglyseride, low-dencity lipoproteins and very low-dencity lipoproteins) as well as cardiac markers (Creatine kinase-muscle/brain and Cardiac Troponin I). Morever, DOX caused significant increases in oxidative stress parameters (malondialdehyde and total oxidant status) as well as decreases in antioxidant defense systems (glutathione, superoxide dismutase, catalase and total antioxidant status). The present study also demonstrated that co-administration of crocin with DOX significantly ameliorated the lipid profile and biochemical parameters in rats receiving DOX. The results were supported by histopathological and immunohistochemical evaluations. Taken together, our results reveal that crocin might be a cardioprotective agent in DOX treated patients for cancer.

The clinical course of critically ill COVID-19 patients receiving invasive mechanical ventilation with subsequent terminal weaning: Primary data from 11 cases.

ABSTRACT: The coronavirus disease (COVID-19) outbreak was first reported in December 2019 in Wuhan, China. Specific information about critically ill COVID-19 patients receiving invasive mechanical ventilation (IMV) is rare.To describe the clinical course and complications of critically ill patients with COVID-19 who received IMV and were successfully weaned from it.This retrospective study included patients admitted to 3 intensive care units (ICUs) and 1 sub-ICU of Renmin Hospital of Wuhan University and Wuhan Jin Yin-tan Hospital between December 24, 2019, and March 12, 2020. Eleven patients who had been diagnosed with critically ill COVID-19 according to the World Health Organization interim guidance, received invasive ventilation, and were finally successfully weaned from it, were enrolled in our study. Their presenting symptoms, comorbidity conditions, laboratory values, ICU course, ventilator parameters, treatments, and relative complications were recorded.Of 108 critically ill COVID-19 patients who received invasive ventilation, 11 patients who underwent tracheal extubation or terminal weaning were included. The mean age of the 11 patients was 52.8 years (range, 38-70 years), 8 (72.7%) were male, and 2 were health care workers. The median time from onset of symptoms to dyspnea was 6.6 days (range, 3-13 days), and the median duration of IMV was 15.7 days (range, 6-29 days). All 11 patients presented with acute severe hypoxemic respiratory failure and received IMV, and 1 patient switched to extracorporeal membrane oxygenation assistance. A lung-protective strategy with lower tidal volume ventilation and proper driving pressure is the main strategy of IMV. All patients had extrapulmonary manifestations, including acute kidney injury, hepatic dysfunction, myocardial damage, and/or lymphopenia. Hospital-acquired infections occurred in 7 (63.6%) patients.Critical COVID-19 illness is characterized by acute hypoxemic respiratory failure and subsequent dysfunction of other organs with a high mortality rate. Correct ventilation strategies and other clinical strategies to improve oxygenation based on the skilled trained group and the availability of equipment are the key methods to rescue lives.