Zirconium-Based Metal-Organic Frameworks as Reusable Antibacterial Peroxide Carriers for Protective Textiles

Countries around the world have sought efficient protective coverings, including masks, gowns, and fabrics, for air purification to protect people against infectious diseases. However, the demand for significant quantities of disposable protective textiles poses a global challenge, especially when the production of protective gear is suspended due to COVID-19 outbreaks in factories and along supply lines. Therefore, the development of reusable, self-decontaminating protective masks and coverings loaded with disinfectants, such as antibacterial peroxide species, presents an attractive strategy to fight against bacteria risks. In this work, we incorporated persulfate ions, which serve as stable active peroxide precursors, into two porous zirconium-based metal-organic frameworks (Zr-MOFs), enabling these materials to act as regenerable reservoirs for the slow release of biocidal hydrogen peroxide upon hydrolysis by contact with humid air. Single-crystal X-ray diffraction studies reveal the two different coordination motifs for the persulfate ions, which can either bridge between two adjacent nodes or coordinate to a single node depending on both the node connectivity and the distances between open metal sites. The active peroxide precursors within the porous Zr-MOF carriers are stable during storage and easily regenerated once consumed. Importantly, these persulfate-loaded Zr-MOFs can be integrated onto textiles using a facile aqueous in-situ growth procedure, and these composites demonstrate potent and reusable biocidal activity against both Gram-negative bacteria and Gram-positive bacteria. Overall, this approach presents a viable strategy to develop robust protective textiles capable of rapidly deactivating pathogens.

CAPRL Scoring System for Prediction of 30-day Mortality in 949 Patients with Coronavirus Disease 2019 in Wuhan, China: A Retrospective, Observational Study

Background:Coronavirus disease 2019 (COVID-19) is a serious and even lethal respiratory illness. The mortality of critically ill patients with COVID-19, especially short term mortality, is considerable. It is crucial and urgent to develop risk models that can predict the mortality risks of patients with COVID-19 at an early stage, which is helpful to guide clinicians in making appropriate decisions and optimizing the allocation of hospital resoureces.Methods:In this retrospective observational study, we enrolled 949 adult patients with laboratory-confirmed COVID-19 admitted to Tongji Hospital in Wuhan between January 28 and February 12, 2020. Demographic, clinical and laboratory data were collected and analyzed. A multivariable Cox proportional hazard regression analysis was performed to calculate hazard ratios and 95% confidence interval for assessing the risk factors for 30-day mortality.Results:The 30-day mortality was 11.8% (112 of 949 patients). Forty-nine point nine percent (474) patients had one or more comorbidities, with hypertension being the most common (359 [37.8%] patients), followed by diabetes (169 [17.8%] patients) and coronary heart disease (89 [9.4%] patients). Age above 50 years, respiratory rate above 30 beats per minute, white blood cell count of more than10 × 109/L, neutrophil count of more than 7 × 109/L, lymphocyte count of less than 0.8 × 109/L, platelet count of less than 100 × 109/L, lactate dehydrogenase of more than 400 U/L and high-sensitivity C-reactive protein of more than 50 mg/L were independent risk factors associated with 30-day mortality in patients with COVID-19. A predictive CAPRL score was proposed integrating independent risk factors. The 30-day mortality were 0% (0 of 156), 1.8% (8 of 434), 12.9% (26 of 201), 43.0% (55 of 128), and 76.7% (23 of 30) for patients with 0, 1, 2, 3, ≥4 points, respectively.Conclusions:We designed an easy-to-use clinically predictive tool for assessing 30-day mortality risk of COVID-19. It can accurately stratify hospitalized patients with COVID-19 into relevant risk categories and could provide guidance to make further clinical decisions. © 2021 The Chinese Medical Association, Published by Wolters Kluwer Health, Inc.

Walvis Ridge Hotspot: drilling Walvis Ridge, Southeast Atlantic Ocean, to test models of ridge-hotspot interaction, isotopic zonation, and the hotspot reference frame

Hotspot tracks (quasilinear chains of seamounts, ridges, and other volcanic structures) provide important records of plate motions, as well as mantle geodynamics, magma flux, and mantle source compositions. The Tristan-Gough-Walvis Ridge (TGW) hotspot track, extending from the active volcanic islands of Tristan da Cunha and Gough through a province of guyots and then along Walvis Ridge to the Etendeka flood basalt province, forms one of the most prominent and complex global hotspot tracks. The TGW hotspot track displays a tight linear age progression in which ages increase from the islands to the flood basalts (covering ~135 My). Unlike Pacific tracks, which are simple chains of seamounts that are often compared to chains of pearls, the TGW track is alternately a steep-sided narrow ridge, an oceanic plateau, subparallel linear ridges and chains of seamounts, and areas of what appear to be randomly dispersed seamounts. The track displays isotopic zonation over the last ~70 My. The zonation appears near the middle of the track just before it splits into two to three chains of ridge- and guyot-type seamounts. The older ridge is also overprinted with age-progressive late-stage volcanism, which was emplaced ~30–40 My after the initial eruptions and has a distinct isotopic composition. The plan for Expedition 391 was to drill at six sites, three along Walvis Ridge and three in the seamount (guyot) province, to gather igneous rocks to better understand the formation of track edifices, the temporal and geochemical evolution of the hotspot, and the variation in paleolatitudes at which the volcanic edifices formed. After a delay of 18 days to address a shipboard outbreak of the coronavirus disease 2019 (COVID-19) virus, Expedition 391 proceeded to drill at four of the proposed sites: three sites on the eastern Walvis Ridge around Valdivia Bank, an ocean plateau within the ridge, and one site on the lower flank of a guyot in the Center track, a ridge located between the Tristan subtrack (which extends from the end of Walvis Ridge to the island of Tristan da Cunha) and the Gough subtrack (which extends from Walvis Ridge to the island of Gough). One hole was drilled at Site U1575, located on a low portion of the northeastern Walvis Ridge north of Valdivia Bank. At this location, 209.9 m of sediments and 122.4 m of igneous basement were cored. The latter comprised 10 submarine lava units consisting of pillow, lobate, sheet, and massive lava flows, the thickest of which was ~21 m. Most lavas are tholeiitic, but some alkalic basalts were recovered. A portion of the igneous succession consists of low-Ti basalts, which are unusual because they appear in the Etendeka flood basalts but have not been previously found on Walvis Ridge. Two holes were drilled at Site U1576 on the west flank of Valdivia Bank. The first hole was terminated because a bit jammed shortly after penetrating igneous basement. Hole U1576A recovered a remarkable ~380 m thick sedimentary section consisting mostly of chalk covering a nearly complete sequence from Paleocene to Late Cretaceous (Campanian). These sediments display short and long cyclic color changes that imply astronomically forced and longer term paleoenvironmental changes. The igneous basement yielded 11 submarine lava units ranging from pillows to massive flows, which have compositions varying from tholeiitic basalt to basaltic andesite, the first occurrence of this composition recovered from the TGW track. These units are separated by seven sedimentary chalk units that range in thickness from 0.1 to 11.6 m, implying a long-term interplay of sedimentation and lava eruptions. Coring at Site U1577, on the extreme eastern flank of Valdivia Bank, penetrated a 154 m thick sedimentary section, the bottom ~108 m of which is Maastrichtian–Campanian (possibly Santonian) chalk with vitric tephra layers. Igneous basement coring progressed only 39.1 m below the sediment-basalt contact, recovering three massive submarine tholeiite basalt lava flows that are 4.1, 15.5, and >19.1 m thick, respectively. Paleomag etic data from Sites U1577 and U1576 indicate that their volcanic basements formed just before the end of the Cretaceous Normal Superchron and during Chron 33r, shortly afterward, respectively. Biostratigraphic and paleomagnetic data suggest an east–west age progression across Valdivia Bank, becoming younger westward. Site U1578, located on a Center track guyot, provided a long and varied igneous section. After coring through 184.3 m of pelagic carbonate sediments mainly consisting of Eocene and Paleocene chalk, Hole U1578A cored 302.1 m of igneous basement. Basement lavas are largely pillows but are interspersed with sheet and massive flows. Lava compositions are mostly alkalic basalts with some hawaiite. Several intervals contain abundant olivine, and some of the pillow stacks consist of basalt with remarkably high Ti content. The igneous sequence is interrupted by 10 sedimentary interbeds consisting of chalk and volcaniclastics and ranging in thickness from 0.46 to 10.19 m. Paleomagnetic data display a change in basement magnetic polarity ~100 m above the base of the hole. Combining magnetic stratigraphy with biostratigraphic data, the igneous section is inferred to span >1 My. Abundant glass from pillow lava margins was recovered at Sites U1575, U1576, and U1578. Although the igneous penetration was only two-thirds of the planned amount, drilling during Expedition 391 obtained samples that clearly will lead to a deeper understanding of the evolution of the Tristan-Gough hotspot and its track. Relatively fresh basalts with good recovery will provide ample samples for geochemical, geochronologic, and paleomagnetic studies. Good recovery of Late Cretaceous and early Cenozoic chalk successions provides samples for paleoenvironmental study. © 2022 Authors. All rights reserved.

Analysis of air pollution characteristics, transport pathways and potential source areas identification in Beijing before, during and after the COVID-19 outbreak

A series of lockdown measures in response to the Corona Virus Disease 2019 (COVID-19) outbreak resulted in a drop in anthropogenic emissions and changes in concentrations of PM2.5 and O-3. Backward trajectories analysis, cluster analysis, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) technologies were conducted to reveal the characteristics and potential source areas of pollutants in Beijing before the COVID-19 outbreak (BCO period), during the outbreak (COB period) and after the outbreak (ACO period), as well as the contemporaneous period in 2019 (CCO period), which is critical for exploring the efficient control measures and making policy. The results indicated that despite the significant reduction in anthropogenic emissions during the epidemic, the PM2.5 concentrations increased by 1.0% caused by unfavorable meteorological conditions. O-3 concentrations increased by 174.8% compared to that during the BCO period due to the increased temperature and inappropriate precursor reduction ratios. A considerable decrease of NO3- in PM2.5 was observed under the influence of significant reductions in vehicle emissions during the lockdown. The cluster analysis revealed that short-range transport played a significant role in the accumulation of local PM2.5 pollution, while long-range northwest airflows contributed more to O-3 accumulation, and weakened as the season changed. The PSCF and CWT analysis demonstrated that potential source areas of PM2.5 were mostly located in the central and southern Hebei, the southwestern Shandong in the CCO period, and expanded to central Inner Mongolia and northern Shanxi in the COB period. These areas were highly compatible with the high emission areas of the emission inventory statistics. After the outbreak, the source areas of O-3 were centered in the Beijing-Tianjin-Hebei region and Shandong province, with a radial dispersion in all directions, while they were distributed in the central Mongolia and Inner Mongolia during the other periods.

A review: The phytochemistry, pharmacology, and pharmacokinetics of Curcumae Longae Rhizoma (Turmeric)

Curcumae Longae Rhizoma (CLR) is the rhizome of Curcuma longa L. Pharmacological studies show that CLR can be used to treat cervical cancer, lung cancer, lupus nephritis, and other conditions. In this paper, we review botany, traditional application, phytochemistry, pharmacological activity, and pharmacokinetics of CLR. The literature from 1981 to date was entirely collected from online databases, such as Web of Science, Google Scholar, China Academic Journals full-text database (CNKI), Wiley, Springer, PubMed, and ScienceDirect. The data were also obtained from ancient books, theses and dissertations, and Flora Reipublicae Popularis Sinicae. There are a total of 275 compounds that have been isolated from CLR, including phenolic compounds, volatile oils, and others. The therapeutic effect of turmeric has been expanded from breaking blood and activating qi in the traditional sense to antitumor, anti-inflammatory, antioxidation, neuroprotection, antibacterial, hypolipidemic effects, and other benefits. However, the active ingredients and mechanisms of action related to relieving disease remain ill defined, which requires more in-depth research and verification at a clinical level.

Evolution of donations on scale-free networks during a COVID-19 breakout

Having a large number of timely donations during the early stages of a COVID-19 breakout would normally be considered rare. Donation is a special public goods game with zero yield for donors, and it has the characteristics of the prisoners' dilemma. This paper discusses why timely donations in the early stages of COVID-19 occurred. Based on the idea that donation is a strategy adopted by players during interconnection on account of their understanding of the environment, donation-related populations are placed on social networks and the inter-correlation structures in the population are described by scale-free networks. Players in donation-related populations are of four types: donors, illegal beneficiaries, legal beneficiaries, and inactive people. We model the evolutionary game of donation on a scale-free network. Donors, illegal beneficiaries and inactive people learn and update strategies under the Fermi update rule, whereas the conversion between legal beneficiaries and the other three types is determined by the environment surrounding the players. We study the evolution of cooperative action when the agglomeration coefficient, the parameters of the utility function, the noise intensity, the utility coefficient, the donation coefficient and the initial states of the population on the scale-free network change. For population sizes of 50, 100, 150, and 200, we give the utility functions and the agglomeration coefficients for promoting cooperation and study the corresponding steady states and structural characteristics of the population. We identify the best ranges of the noise intensity K, the donation coefficient alpha and the utility coefficient beta for promoting cooperation at different population sizes. Furthermore, with the increase of the population size, the donor traps are found. At the same time, it is discovered that the initial states of the population have a great impact on the steady states;thus the upper and lower triangle phenomena are proposed. We also find that the population size itself is also an important factor for promoting donation, pointing out the direction of efforts to further promote donation and achieve better social homeostasis under the donation model.

Evaluating the Impact of Positive Implicit Followership towards Employees' Feedback-Seeking: Based on the Social Information Processing Perspective

Amid the growth of COVID-19 pandemic, SMEs are facing greater uncertainties and pressures to survive because even though they are efficiently managed, their human resource organizations lack a large number of resources and a well-developed training system to foster the sustainable development of employees. Employees are important assets of the company, and their continuous growth and development are keys to the survival of the company. In this context, the individual worker's assessment of his or her job role and how the assessments drive the employee to exhibit an appropriate proactive work behavior are particularly important. Previous research has typically focused on how organizations and leaders perceive employees but has rarely explored employees' own implicit followership cognitive states. This study integrates the traits of positive implicit followership of employees, namely, industry trait, enthusiasm trait, and good citizen trait, with perceived supervisor support (PSS) and feedback-seeking behavior (FSB) into one research framework. In this study, 207 valid questionnaires were collected by using offline convenience sampling, and structural equation modeling (SEM) analysis was conducted. The results show that employees' industry traits directly and positively influence FSB, while enthusiasm traits and good citizen traits have no direct effect on promoting FSB. In addition, industry trait, enthusiasm trait, and good citizen trait significantly and positively influence PSS, with good citizen trait having the greatest positive effect on PSS. Furthermore, PSS has a significant positive effect on FSB. Finally, PSS was found to mediate between industry traits and FSB. Corresponding to the results of the study, the actions shaping employees' positive implicit followership cognition and forming a good supportive atmosphere to promote employees' performance of more feedback-seeking behaviors are recommended.

5G-Enabled UAV-to-Community Offloading: Joint Trajectory Design and Task Scheduling

Due to line-of-sight communication links and distributed deployment, Unmanned Aerial Vehicles (UAVs) have attracted substantial interest in agile Mobile Edge Computing (MEC) service provision. In this paper, by clustering multiple users into independent communities based on their geographic locations, we design a 5G-enabled UAV-to-community offloading system. A system throughput maximization problem is formulated, subjected to the transmission rate, atomicity of tasks and speed of UAVs. By relaxing the transmission rate constraint, the mixed integer non-linear program is transformed into two subproblems. We first develop an average throughput maximization-based auction algorithm to determine the trajectory of UAVs, where a community-based latency approximation algorithm is developed to regulate the designed auction bidding. Then, a dynamic task admission algorithm is proposed to solve the task scheduling subproblem within one community. Performance analyses demonstrate that our designed auction bidding can guarantee user truthfulness, and can be fulfilled in polynomial time. Extensive simulations based on real-world data in health monitoring and online YouTube video services show that our proposed algorithm is able to maximize the system throughput while guaranteeing the fraction of served users.

Markov Decision Model of Emergency Medical Supply Scheduling in Public Health Emergencies of Infectious Diseases

In this paper, a Markov decision process (MDP) model was established to study emergency medical material scheduling strategies for public health emergencies such as COVID-19.Within the constraints of dispatchable supplies, the priority of each medical node complicates the problem of deciding which hospital node supplies to respond to. The model assumes that the probability of events in the initial time period is in line with the Poisson distribution and that the location and priority of each hospital node is known when the material demand is initiated. The priority of hospital nodes is divided into four categories: critical, urgent, priority, and routine. There are several patients with different priorities in a hospital node: critical illness, severe illness, and mild illness. The priority of the hospital node is determined by the overall situation of the hospital patients. The MDP model established in this paper gives how to dispatch limited emergency medical supplies in the dispatching center to make the service rate of the whole system the best. The efficiency of the dispatching center in responding to the material needs of the hospital node depends on the constraints of the number and response time of different priority patients at the node. The maximum effect iterative dynamic model was simulated by simulation experiment and compared with the simulation effect under general conditions, so as to observe whether the model improved the system service rate. (C) 2021 The Authors. Published by Atlantis Press B.V.

Antiviral properties of traditional chinese medicine against coronavirus: Research clues for coronavirus disease-2019

The objective of this study was to provide research clues for the prevention and treatment of coronavirus disease-2019 (COVID-19) and coronavirus (CoV) infection using Traditional Chinese Medicine (TCM). A review on research and clinical trials that using TCM extracts and active ingredients against CoV was performed, and a table of TCM agents and their effects on CoV were summarized. Relevant analysis was performed and visual expression of the data included summarizing the types of TCM and treatment methods for COVID-19. TCM fighting against CoV is mainly used in the lung and heart channels, and its medicinal properties are mainly cold and mild, while its taste is mainly bitter and sweet. The majority of research focused on treatments that clear away heat and toxic materials and those that strengthen body resistance and tonify deficiencies. TCM has unique advantages to fight against CoV. The development of new anti-CoV therapy using TCM is of great significance for the prevention and treatment of COVID-19 pneumonia and various viral infectious diseases.

[Clinical characteristics and death risk factors of severe COVID-19].

Objective: To analyze the clinical features and death-related risk factors of COVID-19. Methods: We enrolled 891 COVID-19 patients admitted to the Affiliated Hospital of Jianghan University from December 2019 to February 2020, including 427 men and 464 women. Of the 891 cases, 582 were severe or critical, including 423(73%)severe and 159 (27%) critical cases. We compared the demographics, laboratory findings, clinical characteristics, treatments and prognosis data of the 582 severe patients. Univariate and multivariate logistic regression analysis was conducted to explore the risk factors associated with death in COVID-19 patients. Results: The 582 severe patients included 293 males and 289 females, with a median age of 64(range 24 to 106). Sixty-three patients died, including 45 males and 18 females, with a median age of 71(range 37 to 90). The average onset time of the 582 patients was 8 days, of whom 461 (79%) had fever, 358 (62%) dry cough, 274 (47%) fatigue. There were 206 cases with shortness of breath (35%), 155 cases with expectoration (27%), 83 cases with muscle pain or joint pain (14%), 71 cases with diarrhea (12%), and 29 cases with headache (4%). Underlying diseases were present in 267 (46%) patients, most commonly hypertension (194, 33%), followed by diabetes (69, 12%), coronary atherosclerotic heart disease (37, 6%), tumor (18, 3%), and chronic obstructive pulmonary disease (5, 1%). Chest CT showed bilateral lung involvement in 505 patients (87%). Upon admission, the median lymphocyte count of the 582 patients was 0.8(IQR, 0.6-1.1)×10(9)/L, the median D-dimer was 0.5 (IQR, 0.4- 0.8) mg/L, the median N-terminal brain natriuretic peptide precursor (NT-proBNP) was 433 (IQR, 141- 806) pg/L, and the median creatinine was 70.3 (IQR, 56.9-87.9) µmol/L. The death group had a median lymphocyte count of 0.5 (0.4-0.8)×10(9)/L, D-dimer 1.1 (0.7-10.0)mg/L, N-terminal brain natriuretic peptide precursor 1479(893-5 087) pg/ml, and creatinine 89.9(67.1-125.3) µmol/L. Multivariate logistic analysis showed that increased D-dimer (OR: 1.095, 95% CI: 1.045-1.148, P<0.001), increased NT-proBNP (OR: 4.759, 95% CI: 2.437-9.291, P<0.001), and decreased lymphocyte count (OR: 0.180, 95% CI: 0.059-0.550, P=0.003) were the risk factors of death in COVID-19 patients. Conclusions: The average onset time of severe COVID-19 was 8 days, and the most common symptoms were fever, dry cough and fatigue. Comorbidities such as hypertension were common and mostly accompanied by impaired organ functions on admission. Higher D-dimer, higher NT-proBNP, and lower lymphocyte count were the independent risk factors of death in COVID-19 patients.

Predicting the trend of the COVID-19 outbreak and timely grading the current risk level of epidemic based on moving average prediction limits

Objective : To establish a practical data-driven method that helps predict the evolutionary trend of the coronavirus disease 2019 (COVID-19) epidemic, track and prejudge the current risk classification of the epidemic area, and provide a quantitative evidence for precision prevention and control strategies. Methods ¡¤ A moving average prediction limit (MAPL) method was established based on the moving average method. The previous severe acute respiratory syndrome (SARS) epidemic data was used to verify the practicability of the MAPL method for predicting epidemic trends and quantitative risk. By tracking the COVID-19 outbreak epidemic data publicly reported since January 16, 2020, the MAPL method was used for timely epidemic trend prediction and the risk classification. Results ¡¤ According to the MAPL analysis, the na-tional epidemic of COVID-19 peaked in early February 2020. After active prevention and control in early stages, the overall epidemic situation in the country showed a downward trend from mid-February to mid-March. Compared with Hubei Province, the number of new cases in non-Hubei region declined rapidly in mid-February, but then increased slightly. The analysis of imported cases since March showed that there was a medium to high level of epidemic import risk in the near future. It is recommended to take corresponding prevention and control measures to prevent the epidemic from spreading again. Conclusion ¡¤ The MAPL method can assist in judging the epidemic trend of emerging infectious diseases and predicting the risk levels in a timely manner. Each epidemic district may implement a differentiated precision prevention and control strategies according to the local classification of epidemic risk. Since March, attention should be paid to the prevention and control of imported risks.

[Clinical characteristics of 30 medical workers infected with new coronavirus pneumonia].

Objective: To investigate the clinical characteristics of medical staff with novel coronavirus pneumonia(NCP). Methods: 30 patients infected with novel coronavirus referred to jianghan university hospital between January 11, 2020 and January 3, 2020 were studied. The data reviewed included those of clinical manifestations, laboratory investigation and Radiographic features. Results: The patients consisted of 10 men and 20 women, including 22 doctors and 8 nurses,aged 21~59 years(mean 35±8 years).They were divided to 26 common type and 4 severe cases, all of whom had close(within 1m) contact with patients infected of novel coronavirus pneumonia. The average contact times were 12 (7,16) and the average cumulative contact time was 2 (1.5,2.7) h.Clinical symptoms of these patients were fever in 23 patients (76.67%) , headache in 16 petients (53.33%) , fatigue or myalgia in 21patients (70%) , nausea, vomiting or diarrhea in 9 petients (30%) , cough in 25 petients (83.33%) , and dyspnea in 14 petients (46.67%) .Routine blood test revealed WBC <4.0×10(9)/L in 8 petients (26.67%) , (4-10) ×10(9)/L in 22 petients (73.33%) , and WBC>4.0×10(9)/L in 4 petients (13.33%) during the disease.Lymphocyte count <1.0×10(9)/L occurred in 12 petients (40%),abnormal liver function in 7 petients (23.33%) ,myocardial damage in 5 petients(16.67%), elevated D-dimer (>0.5mg/l) in 5 patients (16.67%). Compared with normal patients, the average exposure times, cumulative exposure time, BMI, Fever time, white blood cell count, liver enzyme, LDH, myoenzyme and D-dimer were significantly increased in severe patients, while the lymphocyte count and albumin levels in peripheral blood were significantly decreased.Chest CT mainly showed patchy shadows and interstitial changes.According to imaging examination, 11 patients (36.67%) showed Unilateral pneumonia and 19 patients (63.33%) showed bilateral pneumonia,4 patients (13.33%) showed bilateral multiple mottling and ground-glass opacity.Compared with the patients infected in the protected period, the proportion of severe infection and bilateral pneumonia were both increased in the patients infected in unprotected period. Conclusion: Medical staffs are at higher risk of infection.Infection rates are associated with contact time, the amount of suction virus. Severe patients had BMI increased, heating time prolonged , white blood cell count, lymphocyte count, D-dimer and albumin level significantly changed and were prone to be complicated with liver damage and myocardial damage.Strict protection measures is important to prevent infection for medical workers.