Institution
Wuhan University
Education•Wuhan, China•
About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Computer science & Population. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.
Topics: Computer science, Population, Catalysis, Feature extraction, Apoptosis
Papers published on a yearly basis
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TL;DR: Under the optimal conditions, a rapid and effective determination of SAs in environmental water samples was achieved and good reproducibility was obtained.
240 citations
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TL;DR: Older males with comorbidities are more likely to develop severe disease, even die from SARS-CoV-2 infection, but either virus itself or cytokine release storm mediated damage to other organ including cardiac, renal, hepatic, and hemorrhage should be taken seriously as well.
Abstract: Background A recently developing pneumonia caused by SARS-CoV-2 was originated in Wuhan, China, and has quickly spread across the world. We reported the clinical characteristics of 82 death cases with COVID-19 in a single center. Methods Clinical data on 82 death cases laboratory-confirmed as SARS-CoV-2 infection were obtained from a Wuhan local hospital’s electronic medical records according to previously designed standardized data collection forms. Results All patients were local residents of Wuhan, and the great proportion of them were diagnosed as severe illness when admitted. Most of the death cases were male (65.9%). More than half of dead patients were older than 60 years (80.5%) and the median age was 72.5 years. The bulk of death cases had comorbidity (76.8%), including hypertension (56.1%), heart disease (20.7%), diabetes (18.3%), cerebrovascular disease (12.2%), and cancer (7.3%). Respiratory failure remained the leading cause of death (69.5%), following by sepsis syndrome/MOF (28.0%), cardiac failure (14.6%), hemorrhage (6.1%), and renal failure (3.7%). Furthermore, respiratory, cardiac, hemorrhage, hepatic, and renal damage were found in 100%, 89%, 80.5%, 78.0%, and 31.7% of patients, respectively. On the admission, lymphopenia (89.2%), neutrophilia (74.3%), and thrombocytopenia (24.3%) were usually observed. Most patients had a high neutrophil-to-lymphocyte ratio of >5 (94.5%), high systemic immune-inflammation index of >500 (89.2%), increased C-reactive protein level (100%), lactate dehydrogenase (93.2%), and D-dimer (97.1%). A high level of IL-6 (>10 pg/ml) was observed in all detected patients. Median time from initial symptom to death was 15 days (IQR 11-20), and a significant association between aspartate aminotransferase (p=0.002), alanine aminotransferase (p=0.037) and time from initial symptom to death were interestingly observed. Conclusion Older males with comorbidities are more likely to develop severe disease, even die from SARS-CoV-2 infection. Respiratory failure is the main cause of COVID-19, but either virus itself or cytokine release storm mediated damage to other organ including cardiac, renal, hepatic, and hemorrhage should be taken seriously as well. Funding No founding. Research in context Evidence before this study As the seventh member of enveloped RNA coronavirus, severe acute respiratory syndrome coronavirus (SARS-CoV)-2 causes a cluster of severe respiratory disease which is similar to another two fatal coronavirus infection caused by SARS-CoV and Middle Eastern respiratory syndrome coronavirus (MERS-CoV). Through searching PubMed and the China National knowledge infrastructure databases up to February 20, 2020, no published article focusing on hospitalized dead patients was identified. Added value of this study We conducted a single-center investigation involving 82 hospitalized death patients with COVID-19 and focused on their epidemiological and clinical characteristics. 66 of 82 (80.5%) of patients were older than 60 years and the median age was 72.5 years. The bulk of death cases had comorbidity (76.8%). Respiratory failure remained the leading cause of death, following by sepsis syndrome/MOF, cardiac failure, hemorrhage, and renal failure. Most patients had a high neutrophil-to-lymphocyte ratio, high systemic immune-inflammation index, and increased levels of proinflammatory cytokines. Implications of all the available evidence SARS-CoV-2 causes a cluster of severe respiratory illness which is similar to another two fatal coronavirus infection caused by SARS-CoV and MERS-CoV. Death is more likely to occur in older male patients with comorbidity. Infected patients might develop acute respiratory distress and respiratory failure which was the leading cause of death, but damages of other organs and systems, including cardiac, hemorrhage, hepatic, and renal also contribute to the death. These damages might be attributable to indirect cytokines storm initiated by immune system and direct attack from SARS-CoV-2 itself.
240 citations
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TL;DR: Values of R = sigma(e(+e(-)-->hadrons)/sigma( e(+)e (-)-->mu(+)mu(-)) for 85 center-of-mass energies between 2 and 5 GeV measured with the upgraded Beijing Spectrometer at the Beijing Electron-Positron Collider are reported.
Abstract: We report values of $R\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}\ensuremath{\sigma}({e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}\mathrm{hadrons})/\ensuremath{\sigma}({e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\mu}}^{+}{\ensuremath{\mu}}^{\ensuremath{-}})$ for 85 center-of-mass energies between 2 and $5\mathrm{GeV}$ measured with the upgraded Beijing Spectrometer at the Beijing Electron-Positron Collider.
239 citations
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TL;DR: The results suggest that boron plays an important role in enhancing osteoblast proliferation in B-MBG scaffold system and DEX-loaded B- MBG scaffolds show great potential as a release system to enhance osteogenic property for bone tissue engineering application.
239 citations
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TL;DR: In this article, the influence of coagulation solution composition on the spinning performance was discussed and the intermolecular interactions of blend fibers were studied by infrared analysis (IR), X-ray diffraction (XRD), and scanning electron micrograph (SEM) and by measurements of mechanical properties and water-retention properties.
Abstract: Chitosan and poly(vinyl alcohol) blend fibers were prepared by spinning their solution through a viscose-type spinneret at 25°C into a coagulating bath containing aqueous NaOH and ethanol. The influence of coagulation solution composition on the spinning performance was discussed, and the intermolecular interactions of blend fibers were studied by infrared analysis (IR), X-ray diffraction (XRD), and scanning electron micrograph (SEM) and by measurements of mechanical properties and water-retention properties. The results demonstrated that the water-retention properties and mechanical properties of the blend fibers increase due to the presence of PVA in the chitosan substract, and the mechanical strength of the blends is also related to PVA content and the degree of deacetylation of chitosan. The best mechanical strength values of the blend fibers, 1.82 cN/d (dry state) and 0.81 cN/d (wet state), were obtained when PVA content was 20 wt % and the degree of deacetylation of chitosan was 90.2%. The strength of the blend fibers, especially wet tenacity could be improved further by crosslinking with glutaraldehyde. The water-retention values (WRV) of the blend fibers were between 170 and 241%, obviously higher than pure chitosan fiber (120%). The structure analysis indicated that there are strong interaction and good miscibility between chitosan and poly(vinyl alcohol) molecular resulted from intermolecular hydrogen bonds. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 80: 2558–2565, 2001
239 citations
Authors
Showing all 93441 results
Name | H-index | Papers | Citations |
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Jing Wang | 184 | 4046 | 202769 |
Jiaguo Yu | 178 | 730 | 113300 |
Lei Jiang | 170 | 2244 | 135205 |
Gang Chen | 167 | 3372 | 149819 |
Omar M. Yaghi | 165 | 459 | 163918 |
Xiang Zhang | 154 | 1733 | 117576 |
Yi Yang | 143 | 2456 | 92268 |
Thomas P. Russell | 141 | 1012 | 80055 |
Jun Chen | 136 | 1856 | 77368 |
Lei Zhang | 135 | 2240 | 99365 |
Chuan He | 130 | 584 | 66438 |
Han Zhang | 130 | 970 | 58863 |
Lei Zhang | 130 | 2312 | 86950 |
Zhen Li | 127 | 1712 | 71351 |
Chao Zhang | 127 | 3119 | 84711 |