Enhancing the quality of reporting of orthodontic clinical research

Research reports need to provide complete, accurate, and transparent information to allow readers to easily understand and critically assess the study results. Poor reporting makes studies unable to be synthesized in systematic reviews, fail to inform clinical practice, and compromise evidence-based clinical decision making. Evidence suggested the reporting quality of orthodontic clinical studies was poor, which caused a large amount of avoidable research waste. Reporting guidelines (RGs) are developed to guide and standardize the reporting of specific study types and improve their reporting quality. This article introduces the commonly used RGs in orthodontic clinical studies and illustrates the relationship between the existing RGs and their extensions. The majority of extensions are those to the CONSORT and PRISMA guidelines. The EQUATOR Network is an online library of RGs and education resources, and authors can use it to find appropriate RGs. Although a large number of RGs and extensions have been published, involving various study types, the reporting quality of orthodontic clinical studies still needs to be improved. Active strategies to strengthen the implementation of RGs are necessary to fill the gaps between RG publication and the quality improvement of studies. Other issues including selective reporting and spin, structure format of abstracts, and artificial intelligence in reporting are also discussed. Language models such as ChatGPT have largely changed scientific research and reporting in the era of artificial intelligence. Authors are strongly recommended to always be transparent in reporting and responsible for the content of their studies.<br/

Estimation of NO2_{2} emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

Nitrogen dioxide (NO$_{2}$) air pollution provides valuable information for quantifying NOx (NOx = NO +NO$_{2}$) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO$_{2}$emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s−1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s−1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory. Weekly variations in NO$_{2}$emission are highly related to anthropogenic activities, such as the transport sector. The NO$_{2}$emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO$_{2}$emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO$_{2}$emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO$_{2}$decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx (NOx = NO + NO2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s−1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s−1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory.We wish to acknowledge the Joint R&D and Talents Program project, funded by the Qingdao Sino-German Institute of Intelligent Technologies (grant no. kh0100020213319); the Deutsche Forschungsgemeinschaft; and the Open Access Publishing Fund of the Karlsruhe Institute of Technology for their support

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from three-year (April 2018 – March 2021) TROPOMI observations by combining a wind-assigned anomaly approach and a Machine Learning (ML) method, the so-called Gradient Descent. This combined approach is firstly applied to the Saudi Arabian capital city Riyadh, as a test site, and yields a total emission rate of 1.04×1026 molec./s. The ML-trained anomalies fit very well with the wind-assigned anomalies with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites where the cement plant and power plants are located and over areas along the highways. Using the same approach, an emission rate of 1.80×1025 molec./s is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable to the CAMS inventory.We also acknowledge the project of Joint R&D and Talents Program funded by the Qingdao Sino-German Institute of Intelligent Technologies (kh0100020213319) and the project of Transnational Interoperability Rules and Solution Patterns in Collaborative Production Networks based on IDS and GAIA-X funded by Ministry of Science and Technology, PRC (SQ2021YFE010470)

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Search for direct stau production in events with two hadronic tau-leptons in root s=13 TeV pp collisions with the ATLAS detector

A search for the direct production of the supersymmetric partners ofτ-leptons (staus) in final stateswith two hadronically decayingτ-leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of139fb−1, recorded with the ATLAS detector at the LargeHadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected StandardModel background is observed. Limits are derived in scenarios of direct production of stau pairs with eachstau decaying into the stable lightest neutralino and oneτ-lepton in simplified models where the two staumass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidencelevel for a massless lightest neutralino

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Current trends in drug metabolism and pharmacokinetics.

Pharmacokinetics (PK) is the study of the absorption, distribution, metabolism, and excretion (ADME) processes of a drug. Understanding PK properties is essential for drug development and precision medication. In this review we provided an overview of recent research on PK with focus on the following aspects: (1) an update on drug-metabolizing enzymes and transporters in the determination of PK, as well as advances in xenobiotic receptors and noncoding RNAs (ncRNAs) in the modulation of PK, providing new understanding of the transcriptional and posttranscriptional regulatory mechanisms that result in inter-individual variations in pharmacotherapy; (2) current status and trends in assessing drug-drug interactions, especially interactions between drugs and herbs, between drugs and therapeutic biologics, and microbiota-mediated interactions; (3) advances in understanding the effects of diseases on PK, particularly changes in metabolizing enzymes and transporters with disease progression; (4) trends in mathematical modeling including physiologically-based PK modeling and novel animal models such as CRISPR/Cas9-based animal models for DMPK studies; (5) emerging non-classical xenobiotic metabolic pathways and the involvement of novel metabolic enzymes, especially non-P450s. Existing challenges and perspectives on future directions are discussed, and may stimulate the development of new research models, technologies, and strategies towards the development of better drugs and improved clinical practice

A randomized double-blinded study assessing the dose-response of ropivacaine with dexmedetomidine for maintenance of labor with epidural analgesia in nulliparous parturients

Background: The combination of ropivacaine and dexmedetomidine has been used as an epidural analgesic for inducing labor. However, there is limited data regarding the administration of epidural analgesia for labor maintenance, hence, this study aimed to determine the optimum concentration through dose-response curves of ropivacaine plus dexmedetomidine, which could be used along with the Programmed Intermittent Epidural Bolus (PIEB) technique.Methods: One hundred parturients were randomized into 4 groups who were administered four different doses of ropivacaine (dexmedetomidine at 0.4 μg mL−1): 0.04%, 0.06%, 0.08%, and 0.1%. The primary outcome that was determined included the proportion of patients experiencing breakthrough pain during their 1st stage of labor. Breakthrough pain was described as a visual analog scale [VAS] score of &gt;30 mm, requiring supplemental epidural analgesia after the administration of at least one patient-controlled bolus. The effective concentration of analgesia that was used for labor maintenance in 50% (EC50) and 90% (EC90) of patients were calculated with the help of probit regression. Secondary outcomes included epidural block characteristics, side effects, neonatal outcomes, and patient satisfaction.Results: The results indicated that the proportion of patients without breakthrough pain was 45% (10/22), 55% (12/22), 67% (16/24), and 87% (20/23) for 0.04%, 0.06%, 0.08%, and 0.10% doses of the analgesic that were administered, respectively. The EC50 value was 0.051% (95% confidence interval [CI], 0.011%–0.065%) while the EC90 value was recorded to be 0.117% (95% CI, 0.094%–0.212%). Side effects were similar among groups.Conclusion: A ropivacaine dose of 0.117% can be used as epidural analgesia for maintaining the 1st stage of labor when it was combined with dexmedetomidine (0.4 μg mL−1) and the PIEB technique.Clinical Trial Register:https://www.chictr.org.cn/index.aspx, identifier ChiCTR220005955