Mapping knowledge structure and research of the biologic treatment of asthma: A bibliometric study.

Background: Bronchial asthma (asthma) is a chronic inflammatory disease of the airways, involving a variety of cells and cellular components, that manifests clinically as recurrent episodes of wheezing, shortness of breath, with or without chest tightness or cough, airway hyperresponsiveness, and variable airflow limitation. The number of people with asthma has reached 358 million worldwide and asthma causes huge economic loss. However, there is a subset of patients who are not sensitive to existing drugs and the existing drugs have many adverse effects. Therefore, it's important to find new drugs for asthma patients. Methods: Publications related to biologics in asthma published from 2000 to 2022 were retrieved from Web of Science Core Collection. The search strategies were as follows: topic: TS=(biologic* OR "biologic* product*" OR "biologic* therap*" OR biotherapy* OR "biologic* agent*" OR Benralizumab OR "MEDI-563" OR Fasenra OR "BIW-8405" OR Dupilumab OR SAR231893 OR "SAR-231893" OR Dupixent OR REGN668 OR "REGN-668" OR Mepolizumab OR Bosatria OR "SB-240563" OR SB240563 OR Nucala OR Omalizumab OR Xolair OR Reslizumab OR "SCH-55700" OR SCH55700 OR "CEP-38072" OR CEP38072 OR Cinqair OR "DCP-835" OR DCP835 OR Tezspire OR "tezepelumab-ekko" OR "AMG-157" OR tezspire OR "MEDI-9929" OR "MEDI-19929" OR MEDI9929 OR Itepekimab OR "REGN-3500"OR REGN3500 OR "SAR-440340"OR SAR440340 OR Tralokinumab OR "CAT-354" OR Anrukinzumab OR "IMA-638" OR Lebrikizumab OR "RO-5490255"OR "RG-3637"OR "TNX-650"OR "MILR1444A"OR "MILR-1444A"OR"PRO301444"OR "PRO-301444"OR Pitrakinra OR altrakincept OR "AMG-317"OR"AMG317" OR Etokimab OR Pascolizumab OR "IMA-026"OR Enokizumab OR "MEDI-528"OR "7F3COM-2H2" OR 7F3COM2H2 OR Brodalumab OR "KHK-4827" OR "KHK4827"OR "AMG-827"OR Siliq OR Ligelizumab OR "QGE-031" OR QGE031 OR Quilizumab OR Talizumab OR "TNX-901" OR TNX901 OR Infliximab OR Etanercept OR "PRS-060") AND TS=asthma*. The document type was set to articles and review articles and the language restriction was set to English. Three different analysis tools including one online platform, VOS viewer1.6.18, and CiteSpace V 6.1.R1 software were used to conduct this bibliometric study. Results: This bibliometric study included 1,267 English papers published in 244 journals from 2,012 institutions in 69 countries/regions. Omalizumab, benralizumab, mepolizumab, and tezepelumab in relation to asthma were the research hotspots in the field. Conclusion: This study systematically uncovers a holistic picture of existing literature related to the biologic treatment of asthma over the past 20 years. We consulted scholars in order to understand key information in this field from the perspective of bibliometrics, which we believe may greatly facilitate future research in this field.

Deep Neural Network with Joint Distribution Matching for Cross-Subject Motor Imagery Brain-Computer Interfaces.

Motor imagery brain-computer interfaces (BCIs) have demonstrated great potential and attract world-spread attentions. Due to the nonstationary character of the motor imagery signals, costly and boring calibration sessions must be proceeded before use. This prevents them from going into our realistic life. In this paper, the source subject's data are explored to perform calibration for target subjects. Model trained on source subjects is transferred to work for target subjects, in which the critical problem to handle is the distribution shift. It is found that the performance of classification would be bad when only the marginal distributions of source and target are made closer, since the discriminative directions of the source and target domains may still be much different. In order to solve the problem, our idea comes that joint distribution adaptation is indispensable. It makes the classifier trained in the source domain perform well in the target domain. Specifically, a measure for joint distribution discrepancy (JDD) between the source and target is proposed. Experiments demonstrate that it can align source and target data according to the class they belong to. It has a direct relationship with classification accuracy and works well for transferring. Secondly, a deep neural network with joint distribution matching for zero-training motor imagery BCI is proposed. It explores both marginal and joint distribution adaptation to alleviate distribution discrepancy across subjects and obtain effective and generalized features in an aligned common space. Visualizations of intermediate layers illustrate how and why the network works well. Experiments on the two datasets prove the effectiveness and strength compared to outstanding counterparts.

[Metabolic profiling analysis of amino metabolites in plant extract based on pre-column derivatization-ultra high performance liquid chromatography-mass spectrometry].

Amino metabolites are important compounds that play a key role in plant growth and development. A metabolic profiling analysis method of amino metabolites in plant extract was developed based on pre-column derivatization-ultra high performance liquid chromatography- mass spectrometry. Using the tobacco leaf as an example, a total of 87 amino metabolites, including amino acids, amines, peptides, alkaloids etc. were detected. The repeatability of the method was good with RSDs of 85 amino metabolites between 1. 5% and 18. 8%. Forty-three amino metabolites validated by standard samples showed good linearity with the correlation coefficients of 0.993-0.999, covered linear range of four orders of magnitude. The limits of detection were 0.03-6.58 ng/mL. The intra-day and inter-day precisions were 0.7%-15.6% and 0.8%-22.9%, respectively. The recoveries were 74.4%-122.7%. The influence of topping on metabolic profiling of amino metabolites in fresh tobacco was investigated using the developed method. The results showed that the amino metabolites in the upper tobacco leaves were most affected than those in the middle and lower leaves. Metabolism of amino metabolites in the upper leaves after topping was mainly towards the alkaloid synthesis. The method integrated the advantages of triple quadrupole mass spectrometry and high resolution quadrupole-time of flight mass spectrometry. It can be used for metabolic profiling analysis of amino metabolites in plant extract with high sensitivity and selectivity.

Further Study on Chemical Constituents of Parnassia wightiana Wall: Four New Dihydro-ß-agarofuran Sesquiterpene Polyesters.

Four new (1-4), along with six known (5-10) dihydro-ß-agarofuran sesquiterpene polyesters were isolated from the whole plants of Parnassia wightiana. The new compounds were structurally elucidated through spectroscopic analysis including UV (Ultraviolet Spectrum), IR (Infrared Spectrum), ¹H-NMR (¹Hydrogen-Nuclear Magnetic Resonance), ¹³C-NMR (¹³Carbon-Nuclear Magnetic Resonance), DEPT (Distortionless Enhancement by Polarization Transfer), ¹H-¹H COSY (¹H-¹H Correlation Spectroscopy), HSQC (Heteronuclear Single Quantum Coherence), HMBC (Heteronuclear Multiple Bond Correlation), NOESY (Nuclear Overhauser Enhancement Spectroscopy) and HR-MS (High Resolution Mass Specttrum) and their absolute configurations were proposed by comparison of NOESY spectra and specific optical rotations with those of known compounds and biosynthesis grounds. Compound 2 is the first sesquiterpene alkaloid isolated from this plant. New compounds 1-4 exhibited some cytotoxic activities against NB4, MKN-45 and MCF-7 cells at 20 µM and of which 4 showed the highest activity against NB4 and MKN-45 cells with inhibition rates of 85.6% and 30.5%, respectively.

Metabolomics study of cured tobacco using liquid chromatography with mass spectrometry: method development and its application in investigating the chemical differences of tobacco from three growing regions.

Cured tobacco is an important plant material. Component studies are a big challenge for its significantly diverse chemical properties and vastly different concentrations. In this work, liquid chromatography with quadrupole time-of-flight mass spectrometry was used to perform a metabolomics study of cured tobacco owing to its efficient separation and detection of semipolar metabolites. A solvent of methanol/water (8:2, v/v) and 30 min of ultrasound time were found to be optimal to perform extraction. 95, 92, and 93% of metabolite features had within 20% of coefficient of variation for repeatability, intraday and interday precision analysis, respectively, indicating a good stability of the method developed. 113 metabolites were identified in cured tobacco based on accurate mass, retention time, and MS/MS fragments. The developed method was applied to a metabolomics study of cured tobacco from three growing regions. Forty three metabolites were found to be contributed to the classification. It is shown that the developed method can be applied to metabolomics analysis of plant materials.

Microbial communities in long-term, water-flooded petroleum reservoirs with different in situ temperatures in the Huabei Oilfield, China.

The distribution of microbial communities in the Menggulin (MGL) and Ba19 blocks in the Huabei Oilfield, China, were studied based on 16S rRNA gene analysis. The dominant microbes showed obvious block-specific characteristics, and the two blocks had substantially different bacterial and archaeal communities. In the moderate-temperature MGL block, the bacteria were mainly Epsilonproteobacteria and Alphaproteobacteria, and the archaea were methanogens belonging to Methanolinea, Methanothermobacter, Methanosaeta, and Methanocella. However, in the high-temperature Ba19 block, the predominant bacteria were Gammaproteobacteria, and the predominant archaea were Methanothermobacter and Methanosaeta. In spite of shared taxa in the blocks, differences among wells in the same block were obvious, especially for bacterial communities in the MGL block. Compared to the bacterial communities, the archaeal communities were much more conserved within blocks and were not affected by the variation in the bacterial communities.