Morphological, Chemical, and Physical-Mechanical Properties of a Clumping Bamboo (Thyrsostachys oliveri) for Construction Applications.

In view of the long-term utilization history as a building and furniture making material in southeast Asian countries, Thyrsostachys oliveri is considered to have great utilization potential. However, little is known about the quantitative morphological characteristics and comprehensive material properties of its culm. In this study, we systematically investigated the morphological characteristics, the chemical components, and the physical-mechanical properties of the three-year-old culm of T. oliveri. The morphological analysis result showed that the internode length, the diameter of internodes and the wall thickness changed with the culm height. The volume of the culm wall of a single internode increased before the 10th internode, and then it decreased to a significant level at the 20th internode. The basic chemical compositions (cellulose, hemicellulose, lignin and silicon content) of the culm wall were 346.19 mg/g, 95.32 mg/g, 33.17%, and 3.39 mg/g, respectively. These component contents were relatively stable in the bottom and middle part of the culm, but changed significantly in the upper part of the culm. The moisture content and the base density of the culm wall were 73.01% and 0.64 g/cm3, respectively. The culm wall shrinkage rate in the radial, tangential direction as well as the volumetric shrinkage reached the minimum value in the middle part of the culm. The average compressive strength, modulus of rupture and modulus of elasticity of the culm wall were 67.03 MPa, 143.74 MPa, and 7.99 GPa, respectively. These results provide valuable reference data for more rational use of this bamboo resources.

Decrease in ambient volatile organic compounds during the COVID-19 lockdown period in the Pearl River Delta region, south China.

During the COVID-19 lockdown, ambient ozone levels are widely reported to show much smaller decreases or even dramatical increases under substantially reduced precursor NOx levels, yet changes in ambient precursor volatile organic compounds (VOCs) have been scarcely reported during the COVID-19 lockdown, which is an opportunity to examine the impacts of dramatically changing anthropogenic emissions on ambient VOC levels in megacities where ozone formation is largely VOC-limited. In this study, ambient VOCs were monitored online at an urban site in Guangzhou in the Pearl River Delta region before, during, and after the COVID-19 lockdown. The average total mixing ratios of VOCs became 19.1% lower during the lockdown than before, and those of alkanes, alkenes and aromatics decreased by 19.0%, 24.8% and 38.2%, respectively. The levels of light alkanes (C < 6) decreased by only 13.0%, while those of higher alkanes (C ≥ 6) decreased by 67.8% during the lockdown. Disappeared peak VOC levels in morning rush hours and the drop in toluene to benzene ratios during the lockdown suggested significant reductions in vehicle exhaust and industrial solvent emissions. Source apportioning by positive matrix factorization model revealed that reductions in industrial emissions, diesel exhaust (on-road diesel vehicles and off-road diesel engines) and gasoline-related emissions could account for 48.9%, 42.2% and 8.8%, respectively, of the decreased VOC levels during the lockdown. Moreover, the reduction in industrial emissions could explain 56.0% and 70.0% of the reductions in ambient levels of reactive alkenes and aromatics, respectively. An average increase in O3-1 h by 17% and a decrease in the daily maximum 8-h average ozone by 11% under an average decrease in NOx by 57.0% and a decrease in VOCs by 19.1% during the lockdown demonstrated that controlling emissions of precursors VOCs and NOx to prevent ambient O3 pollution in megacities such as Guangzhou remains a highly challenging task.

The COVID-19 Pandemic Changes the Nudging Effect of Social Information on Individuals' Blood Donation Intention.

The positive effect of social information on nudging prosocial behavior is context dependent. Understanding how sensitive intervention outcomes are to changes in the choice context is essential for policy design, especially in times of great uncertainty, such as the current COVID-19 pandemic. The present paper explores the effectiveness of social information in changing voluntary blood donation intention in two contexts: before and after the peak of the COVID-19 pandemic in China. In addition to the dimension of context, information content and its source are also important. Using a survey administered to 1,116 participants, we conducted an intertemporal randomized-controlled experiment to systematically analyze how information can effectively nudge the intention to donate blood. Compared with content featuring blood donors' commendation information, blood users' demand information is found to have a stronger nudging effect. An official information source has a greater influence on participants' donation intention than an unofficial source. Furthermore, our analysis of two waves of experimental data (i.e., before and after the peak of the COVID-19 pandemic) shows that the COVID-19 pandemic has further enhanced the nudging effect of blood users' demand information and official information sources. These findings provide a theoretical basis and policy recommendations for relevant institutions to develop effective blood donation campaign strategies.

Distinguishing Coronavirus Disease 2019 Patients From General Surgery Emergency Patients With the CIAAD Scale: Development and Validation of a Prediction Model Based on 822 Cases in China.

Background: During the epidemic, surgeons cannot identify infectious acute abdomen patients with suspected coronavirus disease 2019 (COVID-19) immediately using the current widely applied methods, such as double nucleic acid detection. We aimed to develop and validate a prediction model, presented as a nomogram and scale, to identify infectious acute abdomen patients with suspected COVID-19 more effectively and efficiently. Methods: A total of 584 COVID-19 patients and 238 infectious acute abdomen patients were enrolled. The least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analyses were conducted to develop the prediction model. The performance of the nomogram was evaluated through calibration curves, Receiver Operating Characteristic (ROC) curves, decision curve analysis (DCA), and clinical impact curves in the training and validation cohorts. A simplified screening scale and a management algorithm were generated based on the nomogram. Results: Five potential COVID-19 prediction variables, fever, chest CT, WBC, CRP, and PCT, were selected, all independent predictors of multivariable logistic regression analysis, and the nomogram, named the COVID-19 Infectious Acute Abdomen Distinguishment (CIAAD) nomogram, was generated. The CIAAD nomogram showed good discrimination and calibration, and it was validated in the validation cohort. Decision curve analysis revealed that the CIAAD nomogram was clinically useful. The nomogram was further simplified as the CIAAD scale. Conclusion: We established an easy and effective screening model and scale for surgeons in the emergency department to use to distinguish COVID-19 patients. The algorithm based on the CIAAD scale will help surgeons more efficiently manage infectious acute abdomen patients suspected of having COVID-19.

Short Communication - Characteristics of healthcare workers who died during the fight against COVID-19 in China

ABSTRACT Coronavirus disease 2019(COVID-19), first reported in December 2019 in Wuhan, China, has progressed to a pandemic associated with substantial morbidity and mortality. Little is known about the healthcare workers who died fighting the disease in China. This paper analyzed the data of 78 Chinese healthcare workers who died in the fight against COVID-19 between 23 January and 2 June, 2020, and revealed the following characteristics. First, compared to the number of deaths directly attributable to COVID-19, more healthcare workers died from pre-existing disease attack induced by excessive fatigue or died from accidents. Second, the median age of the healthcare workers who died directly from COVID-19 was younger than that of the Wuhan non-healthcare workers who died of COVID 19. Third, although more women than men were involved in fighting the pandemic, more men died. Fourth, more healthcare workers died in Hubei than in other provinces. Fifth, most of the healthcare workers who died directly from COVID-19 were non-professionals.

Association of Early-Phase In-Hospital Glycemic Fluctuation With Mortality in Adult Patients With Coronavirus Disease 2019.

OBJECTIVE: To investigate the association of in-hospital early-phase glycemic control with adverse outcomes among inpatients with coronavirus disease 2019 (COVID-19) in Wuhan, China. RESEARCH DESIGN AND METHODS: The study is a large case series, and data were obtained regarding consecutive patients hospitalized with COVID-19 in the Central Hospital of Wuhan between 2 January and 15 February 2020. All patients with definite outcomes (death or discharge) were included. Demographic, clinical, treatment, and laboratory information were extracted from electronic medical records. We collected daily fasting glucose data from standard morning fasting blood biochemistry to determine glycemic status and fluctuation (calculated as the square root of the variance of daily fasting glucose levels) during the 1st week of hospitalization. RESULTS: A total of 548 patients were included in the study (median age 57 years; 298 [54%] were women, and n = 99 had diabetes [18%]), 215 suffered acute respiratory distress syndrome (ARDS), 489 survived, and 59 died. Patients who had higher mean levels of glucose during their 1st week of hospitalization were older and more likely to have a comorbidity and abnormal laboratory markers, prolonged hospital stays, increased expenses, and greater risks of severe pneumonia, ARDS, and death. Compared with patients with the lowest quartile of glycemic fluctuation, those who had the highest quartile of fluctuation magnitude had an increased risk of ARDS (risk ratio 1.97 [95% CI 1.01, 4.04]) and mortality (hazard ratio 2.73 [95% CI 1.06, 7.73]). CONCLUSIONS: These results may have implications for optimizing glycemic control strategies in COVID-19 patients during the early phase of hospitalization.

Characteristics of healthcare workers who died during the fight against COVID-19 in China.

Coronavirus disease 2019 (COVID-19), first reported in December 2019 in Wuhan, China, has progressed to a pandemic associated with substantial morbidity and mortality. Little is known about the healthcare workers who died fighting the disease in China. This paper analyzed the data of 78 Chinese healthcare workers who died in the fight against COVID-19 between 23 January and 2 June, 2020, and revealed the following characteristics. First, compared to the number of deaths directly attributable to COVID-19, more healthcare workers died from pre-existing disease attack induced by excessive fatigue or died from accidents. Second, the median age of the healthcare workers who died directly from COVID-19 was younger than that of the Wuhan non- healthcare workers who died of COVID 19. Third, although more women than men were involved in fighting the pandemic, more men died. Fourth, more healthcare workers died in Hubei than in other provinces. Fifth, most of the healthcare workers who died directly from COVID-19 were non-professionals.

A cohort study of 676 patients indicates D-dimer is a critical risk factor for the mortality of COVID-19.

Coronavirus Disease 2019 (COVID-19) has recently become a public emergency and a worldwide pandemic. However, the information on the risk factors associated with the mortality of COVID-19 and of their prognostic potential is limited. In this retrospective study, the clinical characteristics, treatment and outcome data were collected and analyzed from 676 COVID-19 patients stratified into 140 non-survivors and 536 survivors. We found that the levels of Dimerized plasmin fragment D (D-dimer), C-reactive protein (CRP), lactate dehydrogenase (LDH), procalcitonin (PCT) were significantly higher in non-survivals on admission (non-survivors vs. survivors: D-Dimer ≥ 0.5 mg/L, 83.2% vs. 44.9%, P<0.01; CRP ≥10 mg/L, 50.4% vs. 6.0%, P<0.01; LDH ≥ 250 U/L, 73.8% vs. 20.1%, P<0.01; PCT ≥ 0.5 ng/ml, 27.7% vs. 1.8%, P<0.01). Moreover, dynamic tracking showed D-dimer kept increasing in non-survivors, while CRP, LDH and PCT remained relatively stable after admission. D-dimer has the highest C-index to predict in-hospital mortality, and patients with D-dimer levels ≥0.5 mg/L had a higher incidence of mortality (Hazard Ratio: 4.39, P<0.01). Our study suggested D-dimer could be a potent marker to predict the mortality of COVID-19, which may be helpful for the management of patients.

High aspartate aminotransferase to alanine aminotransferase ratio on admission as risk factor for poor prognosis in COVID-19 patients.

This study aimed to analyze aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio in COVID-19 patients. After exclusion, 567 inpatients were included in this study and separated into two groups according to their AST/ALT ratio on admission. Death was regarded as poor prognosis in this study. Of 567 patients, 200 (35.3%) had AST/ALT ≥ 1.38. Of the 200 patients, older age (median age 60 years), myalgia (64 [32%] cases), fatigue (91 [45.5%] cases), some comorbidities and outcomes were significantly different from patients with AST/ALT < 1.38. They also had worse chest computed tomography (CT) findings, laboratory results and severity scores. Levels of platelet count (OR 0.995, 95% CI [0.992-0.998]) and hemoglobin (OR 0.984, 95% CI [0.972-0.995]) were independently associated with AST/ALT ≥ 1.38 on admission. Furthermore, a high AST/ALT ratio on admission was an independent risk factor for poor prognosis (OR 99.9, 95% CI [2.1-4280.5]). In subsequent monitoring, both survivors and non-survivors showed decreased AST/ALT ratio during hospitalization. In conclusion, high AST/ALT ratio might be the indication of worse status and outcomes in COVID-19 patients.

Clinical Course and Mortality of Stroke Patients With Coronavirus Disease 2019 in Wuhan, China.

BACKGROUND AND PURPOSE: No studies have reported the effect of the coronavirus disease 2019 (COVID-19) epidemic on patients with preexisting stroke. We aim to study the clinical course of COVID-19 patients with preexisting stroke and to investigate death-related risk factors. METHODS: We consecutively included 651 adult inpatients with COVID-19 from the Central Hospital of Wuhan between January 2 and February 15, 2020. Data on the demography, comorbidities, clinical manifestations, laboratory findings, treatments, complications, and outcomes (ie, discharged or death) of the participants were extracted from electronic medical records and compared between patients with and without preexisting stroke. The association between risk factors and mortality was estimated using a Cox proportional hazards regression model for stroke patients infected with severe acute respiratory syndrome coronavirus 2. RESULTS: Of the 651 patients with COVID-19, 49 with preexisting stroke tended to be elderly, male, had more underlying comorbidities and greater severity of illness, prolonged length of hospital stay, and greater hospitalization expenses than those without preexisting stroke. Cox regression analysis indicated that the patients with stroke had a higher risk of developing critical pneumonia (adjusted hazard ratio, 2.01 [95% CI, 1.27-3.16]) and subsequent mortality (adjusted hazard ratio, 1.73 [95% CI, 1.00-2.98]) than the patients without stroke. Among the 49 stroke patients, older age and higher score of Glasgow Coma Scale or Sequential Organ Failure Assessment were independent risk factors associated with in-hospital mortality. CONCLUSIONS: Preexisting stroke patients infected with severe acute respiratory syndrome coronavirus 2 were readily predisposed to death, providing an important message to individuals and health care workers that preventive measures must be implemented to protect and reduce transmission in stroke patients in this COVID-19 crisis.