Resonant dipolar collisions of ultracold molecules induced by microwave dressing

We demonstrate microwave dressing on ultracold, fermionic ${}^{23}$Na${}^{40}$K ground-state molecules and observe resonant dipolar collisions with cross sections exceeding three times the $s$-wave unitarity limit. The origin of these collisions is the resonant alignment of the approaching molecules' dipoles along the intermolecular axis, which leads to strong attraction. We explain our observations with a conceptually simple two-state picture based on the Condon approximation. Furthermore, we perform coupled-channels calculations that agree well with the experimentally observed collision rates. While collisions are observed here as laser-induced loss, microwave dressing on chemically stable molecules trapped in box potentials may enable the creation of strongly interacting dipolar gases of molecules.Comment: 6 pages, 4 figure

Amelioration of systemic inflammation via the display of two different decoy protein receptors on extracellular vesicles

Extracellular vesicles (EVs) can be functionalized to display specific protein receptors on their surface. However, surface-display technology typically labels only a small fraction of the EV population. Here, we show that the joint display of two different therapeutically relevant protein receptors on EVs can be optimized by systematically screening EV-loading protein moieties. We used cytokine-binding domains derived from tumour necrosis factor receptor 1 (TNFR1) and interleukin-6 signal transducer (IL-6ST), which can act as decoy receptors for the pro-inflammatory cytokines tumour necrosis factor alpha (TNF-α) and IL-6, respectively. We found that the genetic engineering of EV-producing cells to express oligomerized exosomal sorting domains and the N-terminal fragment of syntenin (a cytosolic adaptor of the single transmembrane domain protein syndecan) increased the display efficiency and inhibitory activity of TNFR1 and IL-6ST and facilitated their joint display on EVs. In mouse models of systemic inflammation, neuroinflammation and intestinal inflammation, EVs displaying the cytokine decoys ameliorated the disease phenotypes with higher efficacy as compared with clinically approved biopharmaceutical agents targeting the TNF-α and IL-6 pathways.International Society for Advancement of Cytometry Marylou Ingram Scholar 2019-2023H2020 EXPERTSwedish foundation of Strategic Research (SSF-IRC; FormulaEx)ERC CoG (DELIVER)Swedish Medical Research CouncilAccepte

Microbial carbon use efficiency promotes global soil carbon storage

Funding Information: We thank H. Yang, M. Schrumpf, T. Wutzler, R. Zheng and H. Ma for their comments and suggestions on this study. This work was supported by the National Natural Science Foundation of China (42125503) and the National Key Research and Development Program of China (2020YFA0608000, 2020YFA0607900 and 2021YFC3101600). F.T. was financially supported by China Scholarship Council during his visit at Food and Agricultural Organization of the United Nations (201906210489) and the Max-Planck Institute for Biogeochemistry (202006210289). The contributions of Y.L. were supported through US National Science Foundation DEB 1655499 and 2242034, subcontract CW39470 from Oak Ridge National Laboratory (ORNL) to Cornell University, DOE De-SC0023514, and the USDA National Institute of Food and Agriculture. S.M. has received funding from the ERC under the European Union’s H2020 Research and Innovation Programme (101001608). The contributions of U.M. were supported through a US Department of Energy grant to the Sandia National Laboratories, which is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. We thank the WoSIS database ( https://www.isric.org/explore/wosis ) for providing the publicly available global-scale SOC database used in this study. Publisher Copyright: © 2023, The Author(s).Peer reviewedPublisher PD

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

This study was supported by the NSF China Programs (Grant No. 31300539 and 31570629) and the Public Welfare Technology Application Research Program of Zhejiang province (Grant No. 2015C31004).Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.Yeshttp://www.plosone.org/static/editorial#pee

A case of unexplained duodenal ulcer and massive gastrointestinal bleed

A 73-year-old man was displaying symptoms of massive gastrointestinal (GI) bleed. Surgical actions were performed to control the bleed caused by an erosive duodenal ulcer with duodenal perforation. When investigating the culprit of this case, the pain medications prescribed two weeks prior by a traditional Chinese medicine doctor raised attention. The patient's admission serum sample and the pain medications from unknown sources were analyzed using a clinically validated liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method. The NSAIDs diclofenac, piroxicam, and indomethacin were identified, as well as some other synthetic drugs and natural products. The patient's concurrent exposure to multiple NSAIDs significantly increased the risk of upper GI complications. It is reasonable to argue that the high-dose use of the NSAIDs was a major cause of the duodenal ulcer and GI bleed. In addition, the identified natural products such as atropine and ephedrine have well-documented toxicities. It is important to increase the visibility of unregulated medications, and the capability to perform untargeted mass spectrometry analysis provides a unique diagnostic advantage in cases where exposure to toxic substances is possible