12 research outputs found

    Resolution of the type material of the Asian elephant, Elephas maximus Linnaeus, 1758 (Proboscidea, Elephantidae)

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    The understanding of Earth’s biodiversity depends critically on the accurate identification and nomenclature of species. Many species were described centuries ago, and in a surprising number of cases their nomenclature or type material remain unclear or inconsistent. A prime example is provided by Elephas maximus, one of the most iconic and well-known mammalian species, described and named by Linnaeus (1758) and today designating the Asian elephant. We used morphological, ancient DNA (aDNA), and high-throughput ancient proteomic analyses to demonstrate that a widely discussed syntype specimen of E. maximus, a complete foetus preserved in ethanol, is actually an African elephant, genus Loxodonta. We further discovered that an additional E. maximus syntype, mentioned in a description by John Ray (1693) cited by Linnaeus, has been preserved as an almost complete skeleton at the Natural History Museum of the University of Florence. Having confirmed its identity as an Asian elephant through both morphological and ancient DNA analyses, we designate this specimen as the lectotype of E. maximus

    Proteomic Biomarkers for Acute Interstitial Lung Disease in Gefitinib-Treated Japanese Lung Cancer Patients

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    Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan. We generated ∼7 million tandem mass spectrometry (MS/MS) measurements with extensive quality control and validation, producing one of the largest proteomic lung cancer datasets to date, incorporating rigorous study design, phenotype definition, and evaluation of sample processing. After alignment, scaling, and measurement batch adjustment, we identified 41 peptide peaks representing 29 proteins best predicting ILD. Multivariate peptide, protein, and pathway modeling achieved ILD prediction comparable to previously identified clinical variables; combining the two provided some improvement. The acute phase response pathway was strongly represented (17 of 29 proteins, p = 1.0×10−25), suggesting a key role with potential utility as a marker for increased risk of acute ILD events. Validation by Western blotting showed correlation for identified proteins, confirming that robust results can be generated from an MS/MS platform implementing strict quality control

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    An Experimental Investigation of Thermal Runaway and Gas Release of NMC Lithium-Ion Pouch Batteries Depending on the State of Charge Level

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    In this study, 19 experiments were conducted with 25 pouch cells of NMC cathode to investigate thermal runaway and the release of gases from lithium-ion batteries (LIBs). Single cells, double cells, and a four-cell battery stack were forced to undergo thermal runaway inside an air-tight reactor vessel with a volume of 100 dm3. The study involved two series of tests with two types of ignition sources. In the Series 1 tests, a heating plug was used to initiate thermal runaway in LIBs in the ranges of 80–89% and 90–100% SOC. In the Series 2 tests, a heating plate was used to trigger thermal runaway in LIBs in the ranges of 30–50%, 80–89%, and 90–100% SOC. Thermal runaway started at an onset temperature of 344 ± 5 K and 345 K for the Series 1 tests and from 393 ± 36 K to 487 ± 10 K for the Series 2 tests. Peak reaction temperatures ranged between 642 K and 1184 K, while the maximum pressures observed were between 1.2 bar and 7.28 bar. Thermal runaway induced explosion of the cells and lead to a rate of temperature increase greater than 10 K/s. The amounts of gases released from the LIBs were calculated from pressures and temperatures measured in the reactor. Then, the gas composition was analyzed using a Fourier transform infrared (FTIR) spectrometer. The highest gaseous production was achieved at a range of 90–100% SOC and higher battery capacities 72 L, 1.8 L/Ah (Series 1, battery stack) and 103 L, 3.2 L/Ah (Series 2, 32 Ah cell)). Among the gases analyzed, the concentration of gaseous emissions such as C2H4, CH4, and C2H6 increased at a higher cell capacity in both series of tests. The study results revealed characteristic variations of thermal behavior with respect to the type of ignition source used

    Composition and Explosibility of Gas Emissions from Lithium-Ion Batteries Undergoing Thermal Runaway

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    Lithium-based batteries have the potential to undergo thermal runaway (TR), during which mixtures of gases are released. The purpose of this study was to assess the explosibility of the gaseous emission from LIBs of an NMC-based cathode during thermal runaway. In the current project, a series of pouch lithium-based battery cells was exposed to abuse conditions (thermal) to study the total amount of gases released and the composition of the gas mixture. First, the battery cells were placed in a closed vessel, and the pressure and temperature rise inside the vessel were measured. In a second step, the composition of gases was analysed using a Fourier transform Infrared (FTIR) spectrometer. We found that the amount of released gases was up to 102 ± 4 L, with a clear dependence on the battery capacity. This study showed that the concentration of gaseous emissions such as carbon monoxide (CO), methane (CH4), ethylene (C2H4), ethane (C2H6), and hydrogen cyanide (HCN) increased with higher cell capacity. Of the five studied flammable gases, the maximum concentrations of carbon monoxide (16.85 vol%), methane (7.6 vol%), and ethylene (7.86 vol%) were identified to be within their explosible range. Applying Le Chatelier’s law, a calculated lower explosion limit (LEL) of 7% in volume fraction was obtained for the gas mixture. The upper explosion limit (UEL) of the gas mixture was also found to be 31% in volume. A filter comprising pyrobubbles was used for the removal of the studied gas components released during the thermal abuse. The investigation revealed that the pyrobubbles filter was highly effect in the removal of HCN (up to 94% removal) and CO2 (up to 100% removal). Herein, we report the dependency of the method of thermal runaway trigger on the measured maximum temperature
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