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| 2. |
- Jin, Ying-Hui, et al.
(författare)
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Chemoprophylaxis, diagnosis, treatments, and discharge management of COVID-19 : An evidence-based clinical practice guideline (updated version)
- 2020
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Ingår i: Military Medical Research. - : Springer Science and Business Media LLC. - 2054-9369. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, coronavirus disease 2019 (COVID-19), affecting more than seventeen million people around the world. Diagnosis and treatment guidelines for clinicians caring for patients are needed. In the early stage, we have issued "A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version)"; now there are many direct evidences emerged and may change some of previous recommendations and it is ripe for develop an evidence-based guideline. We formed a working group of clinical experts and methodologists. The steering group members proposed 29 questions that are relevant to the management of COVID-19 covering the following areas: chemoprophylaxis, diagnosis, treatments, and discharge management. We searched the literature for direct evidence on the management of COVID-19, and assessed its certainty generated recommendations using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Recommendations were either strong or weak, or in the form of ungraded consensus-based statement. Finally, we issued 34 statements. Among them, 6 were strong recommendations for, 14 were weak recommendations for, 3 were weak recommendations against and 11 were ungraded consensus-based statement. They covered topics of chemoprophylaxis (including agents and Traditional Chinese Medicine (TCM) agents), diagnosis (including clinical manifestations, reverse transcription-polymerase chain reaction (RT-PCR), respiratory tract specimens, IgM and IgG antibody tests, chest computed tomography, chest x-ray, and CT features of asymptomatic infections), treatments (including lopinavir-ritonavir, umifenovir, favipiravir, interferon, remdesivir, combination of antiviral drugs, hydroxychloroquine/chloroquine, interleukin-6 inhibitors, interleukin-1 inhibitors, glucocorticoid, qingfei paidu decoction, lianhua qingwen granules/capsules, convalescent plasma, lung transplantation, invasive or noninvasive ventilation, and extracorporeal membrane oxygenation (ECMO)), and discharge management (including discharge criteria and management plan in patients whose RT-PCR retesting shows SARS-CoV-2 positive after discharge). We also created two figures of these recommendations for the implementation purpose. We hope these recommendations can help support healthcare workers caring for COVID-19 patients.
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| 3. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 5. |
- Pramukti, Iqbal, et al.
(författare)
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Problematic Use of Internet Among Indonesia University Students : Psychometric Evaluation of Bergen Social Media Addiction Scale and Internet Gaming Disorder Scale-Short Form
- 2023
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Ingår i: Psychiatry Investigation. - : Korean Neuropsychiatric Association. - 1738-3684 .- 1976-3026. ; 20:12, s. 1103-1111
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Social media addiction and internet gaming disorder may cause mental health problems among a minority of university students. The Bergen Social Media Addiction Scale (BSMAS) and the 9-item Internet Gaming Disorder Scale-Short Form (IGDS9-SF) are commonly used worldwide. However, they have not been translated or validated into Indonesian. The present study aimed to translate and validate the BSMAS and IGDS9-SF in an Indonesian context among young adults.Methods: A multi-center, web-based cross-sectional study was conducted among 458 university students (74% female; mean age 22.5 years) in Indonesia from June to December 2021. The BSMAS and IGDS9-SF were translated into Indonesian. Internal consistency (using Cronbach’s α and McDonald’s ω) and factor structure (using confirmatory factor analysis) of the two instruments were examined. Concurrent validity of BSMAS and IGDS9-SF was examined using their correlations with two external concepts: nomophobia and psychological distress.Results: Internal consistency of the Indonesian BSMAS and IGDS9-SF were both acceptable (Cronbach’s α=0.80 and 0.90; McDonald’s ω=0.86 and 0.92). Both instruments were unidimensional with good factor loadings (0.54–0.78 for BSMAS; 0.63–0.79 for IGDS9-SF). Moreover, BSMAS and IGDS9-SF had stronger associations with nomophobia (r=0.58 and 0.12; p<0.001) than with psychological distress (r=0.43 and 0.15; p<0.001).Conclusion: The Indonesian versions of the BSMAS and IGDS9-SF had good psychometric properties in terms of linguistic validity, unidimensionality, and reliability. The findings indicate the tools are appropriate for assessing the risk of social media addiction and in-ternet gaming disorder among university students in Indonesia.
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| 6. |
- Song, Yanling, et al.
(författare)
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Growth of winter wheat adapting to climate warming may face more low-temperature damage
- 2023
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Ingår i: International Journal of Climatology. - : Wiley. - 0899-8418 .- 1097-0088. ; 43:4, s. 1970-9
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Tidskriftsartikel (refereegranskat)abstract
- China's surface air temperature is increasing due to global warming, so it is interesting that how low temperatures would be changed during the growth period of winter wheat in future. We focused on the low temperatures of winter wheat from 2021 to 2050, using temperatures under the high emission scenario Representative Concentration Pathway 8.5 (RCP8.5) projected by the RegCM4.4 regional climate model. The results showed that the annual mean temperature was projected to increase by 0.42°C⋅decade−1 in the northern and by 0.35°C⋅decade−1 in the southern winter wheat region. Furthermore, the temperature was expected to increase rapidly in spring, which could advance the dates of flowering and the start of the grain-filling period. Using the genetic parameters determined by the calibration and validation of WOFOST and bias-corrected projected meteorological data, simulations of winter wheat growth were performed over the winter wheat region for 2021–2050. The simulated number of days to the flowering period of winter wheat for 2041–2050 was on average 6.5 days less than in 2021–2030, due to the spring warming. Because of the earlier start of the growing season, winter wheat could face negative effects by being subjected to low temperatures. Indeed, the number of low-temperature days was projected to increase by 110% from 2041 to 2050 compared to 2021–2030, and the number of killing degree days (KDDs) is projected to increase by 120% at the same time. If the number of days to flowering did not change, the number of low-temperature days and KDDs only changed slightly, showing that the negative influence of low temperature was mainly caused by the advancement of the flowering date. The effect of low temperature on growth was underestimated when the response of winter wheat growth to global warming was not considered.
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| 7. |
- Yu, Wenjin, et al.
(författare)
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Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid
- 2022
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Ingår i: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 12, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.
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| 8. |
- Zhang, Huai, et al.
(författare)
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A global survey on the use of the international classification of diseases codes for metabolic dysfunction-associated fatty liver disease.
- 2024
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Ingår i: Hepatology international. - 1936-0541.
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Tidskriftsartikel (refereegranskat)abstract
- With the implementation of the 11th edition of the International Classification of Diseases (ICD-11) and the publication of the metabolic dysfunction-associated fatty liver disease (MAFLD) nomenclature in 2020, it is important to establish consensus for the coding of MAFLD in ICD-11. This will inform subsequent revisions of ICD-11.Using the Qualtrics XM and WJX platforms, questionnaires were sent online to MAFLD-ICD-11 coding collaborators, authors of papers, and relevant association members.A total of 890 international experts in various fields from 61 countries responded to the survey. We also achieved full coverage of provincial-level administrative regions in China. 77.1% of respondents agreed that MAFLD should be represented in ICD-11 by updating NAFLD, with no significant regional differences (77.3% in Asia and 76.6% in non-Asia, p=0.819). Over 80% of respondents agreed or somewhat agreed with the need to assign specific codes for progressive stages of MAFLD (i.e. steatohepatitis) (92.2%), MAFLD combined with comorbidities (84.1%), or MAFLD subtypes (i.e., lean, overweight/obese, and diabetic) (86.1%).This global survey by a collaborative panel of clinical, coding, health management and policy experts, indicates agreement that MAFLD should be coded in ICD-11. The data serves as a foundation for corresponding adjustments in the ICD-11 revision.
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| 9. |
- Boström, Hanna L. B., et al.
(författare)
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How Reproducible is the Synthesis of Zr-Porphyrin Metal-Organic Frameworks? An Interlaboratory Study
- 2024
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Ingår i: Advanced Materials. - 0935-9648 .- 1521-4095. ; 36:15
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Tidskriftsartikel (refereegranskat)abstract
- Metal-organic frameworks (MOFs) are a rapidly growing class of materials that offer great promise in various applications. However, the synthesis remains challenging: for example, a range of crystal structures can often be accessed from the same building blocks, which complicates the phase selectivity. Likewise, the high sensitivity to slight changes in synthesis conditions may cause reproducibility issues. This is crucial, as it hampers the research and commercialization of affected MOFs. Here, it presents the first-ever interlaboratory study of the synthetic reproducibility of two Zr-porphyrin MOFs, PCN-222 and PCN-224, to investigate the scope of this problem. For PCN-222, only one sample out of ten was phase pure and of the correct symmetry, while for PCN-224, three are phase pure, although none of these show the spatial linker order characteristic of PCN-224. Instead, these samples resemble dPCN-224 (disordered PCN-224), which has recently been reported. The variability in thermal behavior, defect content, and surface area of the synthesised samples are also studied. The results have important ramifications for field of metal-organic frameworks and their crystallization, by highlighting the synthetic challenges associated with a multi-variable synthesis space and flat energy landscapes characteristic of MOFs. It performed an interlaboratory study of the synthesis of the metal-organic frameworks (MOFs) PCN-222 and PCN-224. Ten participants independently synthesized the two MOFs and the products are analyzed, primarily by X-ray diffraction. The success rates are low (one-three samples corresponding to a pure sample of the correct phase), thus highlighting the problems with irreproducibility in MOF synthesis. image
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| 10. |
- Cai, Jing, et al.
(författare)
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Size-segregated particle number and mass concentrations from different emission sources in urban Beijing
- 2020
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 20:21, s. 12721-12740
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Tidskriftsartikel (refereegranskat)abstract
- Although secondary particulate matter is reported to be the main contributor of PM2.5 during haze in Chinese megacities, primary particle emissions also affect particle concentrations. In order to improve estimates of the contribution of primary sources to the particle number and mass concentrations, we performed source apportionment analyses using both chemical fingerprints and particle size distributions measured at the same site in urban Beijing from April to July 2018. Both methods resolved factors related to primary emissions, including vehicular emissions and cooking emissions, which together make up 76% and 24% of total particle number and organic aerosol (OA) mass, respectively. Similar source types, including particles related to vehicular emissions (1.6 +/- 1.1 mu gm(-3); 2.4 +/- 1.8 x 10(3) cm(-3) and 5.5 +/- 2.8 x 10(3) cm(-3) for two traffic-related components), cooking emissions (2.6 +/- 1.9 mu gm(-3) and 5.5 +/- 3.3 x 10(3) cm(-3)) and secondary aerosols (51 +/- 41 mu gm(-3) and 4.2 +/- 3.0 x 10(3) cm(-3)), were resolved by both methods. Converted mass concentrations from particle size distributions components were comparable with those from chemical fingerprints. Size distribution source apportionment separated vehicular emissions into a component with a mode diameter of 20 nm (traffic-ultrafine) and a component with a mode diameter of 100 nm (traffic-fine). Consistent with similar day- and nighttime diesel vehicle PM2.5 emissions estimated for the Beijing area, traffic-fine particles, hydrocarbon-like OA (HOA, traffic-related factor resulting from source apportionment using chemical fingerprints) and black carbon (BC) showed similar diurnal patterns, with higher concentrations during the night and morning than during the afternoon when the boundary layer is higher. Traffic-ultrafine particles showed the highest concentrations during the rush-hour period, suggesting a prominent role of local gasoline vehicle emissions. In the absence of new particle formation, our re-sults show that vehicular-related emissions (14% and 30% for ultrafine and fine particles, respectively) and cooking-activity-related emissions (32 %) dominate the particle number concentration, while secondary particulate matter (over 80 %) governs PM2.5 mass during the non-heating season in Beijing.
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