Nursing cooperation related to thoracoscopic surgery in children

Objective:To explore the nursing cooperation of pediatric cardiac surgery by thoracoscopy.Methods:30 patients undergoing thoracoscopy in a third-grade hospital in Yantai were observed and their nursing process was recorded and analyzed.Results:The good cooperation of operating room nurses and equipment nurses can relax the children and increase the success rate of surgery and reduce the occurrence of complications.Conclusion:Full preoperative preparation,close intraoperative cooperation,strict instrument maintenance,and cleaning and disinfection are the guaranteeof pediatric thoracic surgery.

Meplazumab in hospitalized adults with severe COVID-19(DEFLECT):a multicenter,seamless phase 2/3,randomized,third-party double-blind clinical trial

Meplazumab,a humanized CD147 antibody,has shown favourable safety and efficacy in our previous clinical studies.In DEFLECT(NCT04586153),167 patients with severe COVID-19 were enroled and randomized to receive three dosages of meplazumab and a placebo.Meplazumab at 0.12 mg/kg,compared to the placebo group,showed clinical benefits in significantly reducing mortality by 83.6%(2.4%vs.14.6%,p=0.0150),increasing the proportion of patients alive and discharged without supplemental oxygen(82.9%vs.70.7%,p=0.0337)and increasing the proportion of patients who achieved sustained clinical improvement(41.5%vs.31.7%).The response rate in the 0.2 mg/kg group was relatively increased by 16.0%compared with the placebo group(53.7%vs.46.3%).Meplazumab also reduced the viral loads and multiple cytokine levels.Compare with the placebo group,the 0.3 mg/kg significantly increased the virus negative rate by 40.6%(p=0.0363)and reduced IL-8 level(p=0.0460);the 0.2 mg/kg increased the negative conversion rate by 36.9%,and reduced IL-4(p=0.0365)and IL-8 levels(p=0.0484).In this study,the adverse events occurred at a comparable rate across the four groups,with no unexpected safety findings observed.In conclusion,meplazumab promoted COVID-19 convalescence and reduced mortality,viral load,and cytokine levels in severe COVID-19 population with good safety profile.

Geotextile protection of glacier:Observed and simulated impacts on energy and mass balance

The detailed physical processes involved in slowing glacier ablation by material cover remain poorly understood so far.In the present study,using the snow cover model SNOWPACK,the effect of geotextile cover on the energy and mass balance at the tongue of the Urumqi Glacier No.1(Chinese Tien Shan)was simulated between July 12,2022 and August 31,2022.The mass changes and the energy fluxes with and without material cover were compared.The results indicated that the geotextile covering reduced glacier ablation by approximately 68%compared to the ablation in the uncovered regions.The high solar reflectivity of the geotextile reduced the net short-wave radiation energy available for the melt by 45%.Thermal insulation of the geotextile reduced the sensible heat flux by 15%.In addition,the wet geotextile exerted a cooling effect through long-wave radiation and negative latent heat flux.This cooling effect reduced the energy available for ablation by 20%.Consequently,only 37%of the energy was used for melting compared to that used in the uncovered regions(67%).Sensitivity experiments revealed that the geotextile cover used at a thickness range of 0.045-0.090 m reduced the ice loss by approximately 68%-72%,and a further increase in the thickness of the geotextile cover led to little improvements.A higher temperature and greater wind speed increased glacier ablation,although their effects were small.When the precipitation was set to zero,it led to a significantly increased melt.Overall,the geotextile effectively protected the glacier tongue from rapid melting,and the observed results have provided inspiration for developing an effective and sustainable approach to protect the glaciers using geotextile cover.

A phytochemical study on Dichocarpum auriculatum, an endangered medicinal plant peculiar to China

Objective:Dichocarpum auriculatum,an endangered perennial herb,is endemic to China and has been used as folk medicines for the treatment of cough,hepatitis,scrofula,and epilepsy.However,there is no phytochemical report on this herbal so far.For the resource development and protective importance of this endangered medicinal plant,a phytochemical study was undertaken.Methods:The chemical constituents were purified by silica gel column,Sephadex LH-20 column,and semi-preparative reversed phase HPLC.NMR and MS spectra were used for structural identification.Results:Thirteen compounds were isolated from D.auriculatum.Their structures were characterized as jatrorrhizine(1),berberine(2),steponine(3),magnoflorine(4),coclauril(5),menisdaurin(6),menisdaurilide(7),aquilegiolide(8),(6 R,9 S)-3-oxo-α-ionol-β-D-glucopyranoside(9),blumenol C glucoside(10),palmitic acid(11),dibutylphthalate(12),and auriculatum A(13).Conclusion:Compound 13 is a new diester terephthalate derivative.All the compounds are obtained from the genus Dichocarpum for the first time,and compounds 9 and 10 have potential chemotaxonomic significance to the genus Dichocarpum.

N-Fluorinated phenyl-N'-pyrimidyl urea derivatives: Synthesis,biological evaluation and 3D-QSAR study

With the increase of herbicide-resistant weeds, novel, more selective and even more potent herbicides to control weeds are needed. In this paper, a series of N-fluorinated phenyl-N＇-pyrimidyl urea derivatives were synthesized and screened for their herbicidal activities against Amaranthus retroflexus （AR） and Setaria viridis （ SV）. Compound 2S （N-（3-trifluoromethylphenyl）-N＇-（2-amino-4-chloro-6-methylpyr- imidyl） urea） exhibited marked herbicidal activity against SV（IC50 =11.67 mg/L） and is more potent than bensulfuron （IC50= 27.45 mg/L）, a commercially available herbicide. A statistically significant CoMFA model with high prediction abilities （q2 = 0.869, r2 = 0.989） was obtained.

Safety and efficacy of meplazumab in healthy volunteers and COVID-19 patients: a randomized phase 1 and an exploratory phase 2 trial

Recent evidence suggests that CD147 serves as a novel receptor for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.Blocking CD147 via anti-CD147 antibody could suppress the in vitro SARS-CoV-2 replication.Meplazumab is a humanized anti-CD147 IgG_(2) monoclonal antibody,which may effectively prevent SARS-CoV-2 infection in coronavirus disease 2019(COVID-19)patients.Here,we conducted a randomized,double-blinded,placebo-controlled phase 1 trial to evaluate the safety,tolerability,and pharmacokinetics of meplazumab in healthy subjects,and an open-labeled,concurrent controlled add-on exploratory phase 2 study to determine the efficacy in COVID-19 patients.In phase 1 study,59 subjects were enrolled and assigned to eight cohorts,and no serious treatment-emergent adverse event(TEAE)or TEAE grade≥3 was observed.The serum and peripheral blood Cmax and area under the curve showed non-linear pharmacokinetic characteristics.No obvious relation between the incidence or titer of positive anti-drug antibody and dosage was observed in each cohort.The biodistribution study indicated that meplazumab reached lung tissue and maintained>14 days stable with the lung tissue/cardiac blood-pool ratio ranging from 0.41 to 0.32.In the exploratory phase 2 study,17 COVID-19 patients were enrolled,and 11 hospitalized patients were involved as concurrent control.The meplazumab treatment significantly improved the discharged(P=0.005)and case severity(P=0.021),and reduced the time to virus negative(P=0.045)in comparison to the control group.These results show a sound safety and tolerance of meplazumab in healthy volunteers and suggest that meplazumab could accelerate the recovery of patients from COVID-19 pneumonia with a favorable safety profile.

Research on Quality Markers of Moutan Cortex: Quality Evaluation and Quality Standards of Moutan Cortex

Objective To identify the quality markers of Moutan Cortex（MC） and establish the quality evaluation methods for multi-component assay and fingerprinting of MC. Methods The chemical constituents in MC were identified by HPLC-QTOF-MS. UPLC was employed for the multi-component assay and fingerprinting of MC. Furthermore, text mining was carried out to review the biosynthesis pathways and pharmacological and pharmacokinetic studies related to MC, and in silico target fishing was conducted to construct compound-target networks for MC. Results Sixteen compounds were clearly identified in MC and their structures were confirmed through comparison with literature data. In addition, the biosynthetic pathways and component specificities of the identified compounds were summarized and confirmed by text mining.Pharmacological activities, including traditional usage and modern pharmacological studies were summarized. A total of 282 targets from Homo sapiens were fished for 13 compounds. In addition, pharmacokinetic studies of different compounds were synopsized. Finally, multi-component assay and fingerprint of MC were established. Conclusion Eight major components are selected as quality markers of MC, such as oxypaeoniflorin, apiopaeonoside, albiflorin, paeonolide, paeoniflorin, 1,2,3,4,6-penta-O-galloyl-β-D-glucose, mudanpioside C and paeonol. These eight quality markers are successfully applied to the quality evaluation of MC, and could be useful in improving the current quality standards of MC.

Self-adaptive scale pedestrian detection algorithm based on deep residual network

Purpose–The conventional pedestrian detection algorithms lack in scale sensitivity.The purpose of this paper is to propose a novel algorithm of self-adaptive scale pedestrian detection,based on deep residual network(DRN),to address such lacks.Design/methodology/approach–First,the“Edge boxes”algorithm is introduced to extract region of interestsfrompedestrian images.Then,the extracted boundingboxesare incorporatedto differentDRNs,one is a large-scale DRN and the other one is the small-scale DRN.The height of the bounding boxes is used to classify the results of pedestrians and to regress the bounding boxes to the entity of the pedestrian.At last,a weighted self-adaptive scale function,which combines the large-scale results and small-scale results,is designed for the final pedestrian detection.Findings–Tovalidatetheeffectivenessandfeasibilityoftheproposedalgorithm,somecomparisonexperiments have been done on the common pedestrian detection data sets:Caltech,INRIA,ETH and KITTI.Experimental resultsshowthattheproposedalgorithmisadaptedforthevariousscalesofthepedestrians.Fortheharddetected small-scale pedestrians,the proposed algorithm has improved the accuracy and robustness of detections.Originality/value–By applying different models to deal with different scales of pedestrians,the proposed algorithm with the weighted calculation function has improved the accuracy and robustness for different scales of pedestrians.