Targeting microRNAs to Regulate the Integrity of the Blood–Brain Barrier

The blood–brain barrier (BBB) is a highly specialized neurovascular unit that protects the brain from potentially harmful substances. In addition, the BBB also engages in the exchange of essential nutrients between the vasculature and brain parenchyma, which is critical for brain homeostasis. Brain diseases, including neurological disorders and cerebrovascular diseases, are often associated with disrupted BBB integrity, evidenced by increased permeability. Therefore, defining the mechanisms underlying the regulation of BBB integrity is crucial for the development of novel therapeutics targeting brain diseases. MicroRNAs (miRNA), a type of small non-coding RNAs, are emerging as an important regulator of BBB integrity. Here we review recent developments related to the role of miRNAs in regulating BBB integrity

p21-activated kinase is involved in the sporulation, pathogenicity, and stress response of Arthrobotrys oligospora under the indirect regulation of Rho GTPase-activating protein

The p21-GTPase-activated protein kinases (PAKs) participate in signal transduction downstream of Rho GTPases, which are regulated by Rho GTPase-activating proteins (Rho-GAP). Herein, we characterized two orthologous Rho-GAPs (AoRga1 and AoRga2) and two PAKs (AoPak1 and AoPak2) through bioinformatics analysis and reverse genetics in Arthrobotrys oligospora, a typical nematode-trapping (NT) fungus. The transcription analyses performed at different development stages suggested that Aopaks and Aorga1 play a crucial role during sporulation and trap formation, respectively. In addition, we successfully deleted Aopak1 and Aorga1 via the homologous recombination method. The disruption of Aopak1 and Aorga1 caused a remarkable reduction in spore yield and the number of nuclei per cell, but did not affect mycelial growth. In ∆Aopak1 mutants, the trap number was decreased at 48 h after the introduction of nematodes, but nematode predatory efficiency was not affected because the extracellular proteolytic activity was increased. On the contrary, the number of traps in ∆Aorga1 mutants was significantly increased at 36 h and 48 h. In addition, Aopak1 and Aorga1 had different effects on the sensitivity to cell-wall-disturbing reagent and oxidant. A yeast two-hybrid assay revealed that AoPak1 and AoRga1 both interacted with AoRac, and AoPak1 also interacted with AoCdc42. Furthermore, the Aopaks were up-regulated in ∆Aorga1 mutants, and Aorga1 was down-regulated in ∆Aopak1 mutants. These results reveal that AoRga1 indirectly regulated AoPAKs by regulating small GTPases

Nano-additive manufacturing of multilevel strengthened aluminum matrix composites

Nanostructured materials are being actively developed, while it remains an open question how to rapidly scale them up to bulk engineering materials for broad industrial applications. This study propose an industrial approach to rapidly fabricate high-strength large-size nanostructured metal matrix composites and attempts to investigate and optimize the deposition process and strengthening mechanism. Here, advanced nanocrystalline aluminum matrix composites (nanoAMCs) were assembled for the first time by a novel nano-additive manufacturing method that was guided by numerical simulations (i.e. the in-flight particle model and the porefree deposition model). The present nanoAMC with a mean grain size <50 nm in matrix exhibited hardness eight times higher than the bulk aluminum and shows the highest hardness among all Al–Al2O3 composites reported to date in the literature, which are the outcome of controlling multiscale strengthening mechanisms from tailoring solution atoms, dislocations, grain boundaries, precipitates, and externally introduced reinforcing particles. The present high-throughput strategy and method can be extended to design and architect advanced coatings or bulk materials in a highly efficient (synthesizing a nanostructured bulk with dimensions of 50 × 20 × 4 mm3 in 9 min) and highly flexible (regulating the gradient microstructures in bulk) way, which is conducive to industrial production and application

Impact of cytotoxic T lymphocytes immunotherapy on prognosis of colorectal cancer patients

BackgroundExpansion and activation of cytotoxic T lymphocytes (CTLs) in vitro represents a promising immunotherapeutic strategy, and CTLs can be primed by dendritic cells (DCs) loaded with tumor-associated antigens (TAAs) transformed by recombinant adeno-associated virus (rAAV). This study aimed to explore the impact of rAAV-DC-induced CTLs on prognosis of CRC and to explore factors associated with prognosis.MethodsThis prospective observational study included patients operated for CRC at Yan’an Hospital Affiliated to Kunming Medical University between 2016 and 2019. The primary outcome was progression-free survival (PFS), secondary outcomes were overall survival (OS) and adverse events. Totally 49 cases were included, with 29 and 20 administered rAAV-DC-induced CTL and chemotherapy, respectively.ResultsAfter 37-69 months of follow-up (median, 54 months), OS (P=0.0596) and PFS (P=0.0788) were comparable between two groups. Mild fever occurred in 2 (6.9%) patients administered CTL infusion. All the chemotherapy group experienced mild-to-moderate adverse effects, including vasculitis (n=20, 100%), vomiting (n=5, 25%), nausea (n=17, 85%) and fatigue (n=17, 85%).ConclusionsLymphatic metastasis (hazard ratio [HR]=4.498, 95% confidence interval [CI]: 1.290-15.676; P=0.018) and lower HLA-I expression (HR=0.294, 95%CI: 0.089-0.965; P=0.044) were associated with poor OS in the CTL group. CTLs induced by rAAV-DCs might achieve comparable effectiveness in CRC patients compare to chemotherapy, cases with high tumor-associated HLA-I expression and no lymphatic metastasis were more likely to benefit from CTLs

New Measles Virus Genotype Associated with Outbreak, China

Better understanding of transmission patterns will enhance control and elimination programs

Direct and indirect effects of climate on richness drive the latitudinal diversity gradient in forest trees

Data accessibility statement: Full census data are available upon reasonable request from the ForestGEO data portal, http://ctfs.si.edu/datarequest/ We thank Margie Mayfield, three anonymous reviewers and Jacob Weiner for constructive comments on the manuscript. This study was financially supported by the National Key R&D Program of China (2017YFC0506100), the National Natural Science Foundation of China (31622014 and 31570426), and the Fundamental Research Funds for the Central Universities (17lgzd24) to CC. XW was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB3103). DS was supported by the Czech Science Foundation (grant no. 16-26369S). Yves Rosseel provided us valuable suggestions on using the lavaan package conducting SEM analyses. Funding and citation information for each forest plot is available in the Supplementary Information Text 1.Peer reviewedPostprin

Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001

Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001.Peer reviewe

Research of New Machining Method of Skew Bevel Gears Based on Generation Line

According to generating principle of spiral bevel gear and space meshing theory, formation theory of generation line of tooth surface about skew bevel gears is studied. A new processing method of tooth surface with the generation line as chord of face circular cutters is put forward. Moving process model of milling processing with skew bevel gears is built, and profile of the gears can be machined using three axes linkage method based on the model. Machining test of the gears is carried out on experiment platform designed. Furthermore, 3D points cloud model of tooth surface are calculated in light of mathematical model of the tooth surface which has been established, and datum of mesh nodes on actual tooth surface are collected. Then surface errors is evaluated by normal vector equation of the tooth surface which has been developed. Finally, this method is proved to be effective and feasible

Response of soil extracellular enzyme activity to experimental precipitation in a shrub-encroached grassland in Inner Mongolia

Shrub encroachment has caused a vegetation shift in arid and semiarid grassland ecosystems around the world, leading to marked changes in ecosystem structures and functions. Soil extracellular enzyme activity (EEA) is an informative indicator of microbial decomposition and plays an important role in soil biogeochemical cycles, but it is unclear how shrub encroachment affects soil EEA, especially in the future precipitation pattern under climate change. In this study, we measured soil EEAs in a shrub-encroached grassland in Inner Mongolia, China, after four years of in situ experimental precipitation manipulation. Soil samples were collected from grass patches and shrub patches in four precipitation manipulation treatments (-30%, control, +30%, and +50%). Four soil enzymes involved in carbon cycling (alpha-glucosidase, AG; beta-1,4-glucosidase, BG; beta-D-cellobiosidase, CB; and beta-xylosidase, XS), two nitrogen-acquiring enzymes (beta-1,4-N-acetylglucosaminidase, NAG; and leucine amino peptidase, LAP), and one phosphorus-acquiring enzyme (acid phosphatase, AP) were investigated. The results showed that BG, XS, and LAP activities were significantly enhanced in shrub patches than grass patches (p < 0.05). BG, LAP, and AP were significantly different in precipitation treatments (p < 0.05) and were highest in +30% and shrub patches. Shrub encroachment and increased precipitation (+30%) interactively enhanced LAP (p < 0.05). Our study also showed that soil temperature and soil moisture were major factors for the variations in EEA under different precipitation treatments in the grass patches, while soil temperature, NH4+-N and NO3-N were major causes for those in the shrub patches. Overall, our study highlights that shrub encroachment and altered precipitation can influence soil EEA, which in turn may have consequential effects on nutrients availability and biochemical cycling. (c) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)