bluuebunny/crossref_metadata_2025_split huggingface dataset:
The three steps method for uniportal video-assisted thoracoscopic right upper lobectomy
Authors: Liu Caiyang , Ran Ran , Luo Lei , Li Xiaoliang , Liu Gaohua , Shao Hong , Li Ji 
Published: July 2022

Abstract
Background: The uniportal video-assisted thoracoscopic right upper lobectomy (UVATRUL), as a common procedure for thoracic surgeons, has some inherent challenges. We introduced a three steps method for UVATRUL and investigated the feasibility of the three steps method on the patients of right upper lung cancer.Methods: Forty-eight patients with right upper lobe lung cancer who underwent the three steps method UVATRUL in our hospital from January 2020 to May 2022 were selected as the three steps method group. Forty-seven patients who underwent the traditional UVATRUL were selected as the traditional method group. The intraoperative condition and postoperative condition of the two groups were retrospectively analysed. Results: All patients had successfully completed their surgeries. There was no significant difference between the two groups in respect of intraoperative blood loss, rate of conversion, day one thoracic drainage volume, chest tube indwelling time, incidence of postoperative complications, and postoperative hospital stay (P>0.05). The operative time of the three steps method group was significantly shorter than the traditional method group (P<0.001), and the number of reloads used was also significantly less than the traditional method group (P=0.014).Conclusion: Compared with traditional UVATRUL, the three steps method trims the surgery procedures, shortens operative time, and reduces the use of reloads which makes it a decent surgical modality.
Hourly electricity consumption estimation methodology based on the metaheuristic algorithms
Authors: ağır tuba tanyıldızı 
Published: July 2022

Abstract
Estimation of electricity consumption is very difficult as it depends on meteorological factors such as temperature, pressure and wind. Accurate estimation of electricity consumption is very important in terms of cost, time, energy savings, energy management and storage. In this study, Extreme learning machine (ELM) and Artificial Neural Network (ANN) are used to estimate the hourly electricity consumption of a city. ELM and ANN algorithms were simulated for 10 different neurons and 5 different activation functions. For the results of ELM and ANN algorithms, the significance test of the correlation coefficient was performed using statistical methods. In addition, the effects of the changes in the number of neurons and activation functions of ELM and ANN algorithms on performance were examined. It showed that the MSE, RMSE, R and R^2 values in the best performance of the ELM algorithm were 4.476e-06,0.0021,0.9999 and 0.9998. The ANN algorithm is MSE, RMSE, R and R^2 of values 5.22e-06,0.0023,0.9993 and 0.9986 respectively. While the correlation limits of the ELM algorithm at the 95% confidence interval are 0.9946 < ρ < 1.0052, the correlation limits at the 95% confidence interval of the ANN algorithm are 0.9921 < ρ < 1.0027. Neuron selection in ELM and ANN algorithms affected the performance by 1.49% and 0.34%, respectively. The activation function selection in the ELM and ANN algorithms affected the performance by 1.33% and 2.36%, respectively. The results showed that the ELM algorithm was successful in predicting energy consumption, short training time, low iteration number, good correlation limits, and significant activation selection.
High triglyceride-glucose index in young adulthood is associated with incident cardiovascular disease and mortality in later life: insight from the CARDIA Study
Authors: Xu Xinghao , Huang Rihua , Lin Yifen , Guo Yue , Xiong Zhenyu , Zhong Xiangbin , Ye Xiaomin , Li Miaohong , Zhuang Xiaodong , Liao Xinxue 
Published: July 2022

Abstract
Background
This study aimed to investigate the associations between the triglyceride-glucose (TyG) index in young adulthood with incident cardiovascular disease (CVD) and mortality.
Methods
We included 4,854 participants from the Coronary Artery Risk Development in Young Adults study at baseline. The TyG index was calculated as ln (fasting triglyceride [mg/dl] ⋅ fasting glucose [mg/dl]/2), and the TyG index trajectories were identified by using the latent class growth mixture model. CVD events and all-cause mortality were adjudicated over 25 years of follow-up. We evaluated the association between the baseline and trajectories of the TyG index with incident CVD events and all-cause mortality using Cox proportional hazards regression analysis.
Results
Among 4,854 participants (mean age 24.76 years, 45.6% male, 51.0% black), there were 161 incident CVD events and 250 all-cause mortality during a median 25 years follow-up. After adjusting for multiple confounding variables, each one-unit increase in the TyG index was associated with a 93% higher CVD risk (hazard ratio [HR] 1.93, 95% confidence interval [CI] 1.40–2.65) and a 69% higher all-cause mortality risk (HR 1.69, 95% CI 1.31–2.18). Similar results were observed when participants were categorized by TyG index quartiles, with a greater risk of CVD events (HR 2.54, 95% CI 1.44–4.49) and all-cause mortality (HR 1.91, 95% CI 1.27–2.89) for those participants in the highest quartile as compared with the lowest quartile. Three distinct trajectories of the TyG index along the follow-up duration were identified: low (43.5%), moderate (45.6%), and high (10.8%). Compared with those participants in the low TyG index trajectory group, those in the high TyG index trajectory group had a greater risk of CVD events (HR 2.17, 95% CI 1.25–3.76) and all-cause mortality (HR 2.63, 95% CI 1.57–4.39).
Conclusions
Higher baseline TyG index levels and higher long-term trajectory of TyG index during young adulthood were significantly associated with a high risk of incident CVD events and all-cause mortality in later life.
Adverse health and environmental outcomes of sewage treatment plant on surrounding groundwater with emphasis on some mitigation recommendations
Authors: Kandil A. T. , Hagagg K. , Gamal A. A. , El-Nasser M. G. Abd , Mostafa W. M. 
Published: July 2022

Abstract
Water quality deterioration hinders economic and social development in developing countries that are facing freshwater security and shortages. This study based on the collection of 29 water samples and focused on the relationship between sewage treatment plant and groundwater system surrounding it using multidisciplinary approach that combines the characterization of groundwater system and its connection with surrounding canal and drains; using chemical and isotopic characterization revealing that there is a direct relation between the surface water system and surrounding groundwater system. About 58% of the groundwater samples and all surface water samples in the investigated area are threatened by high concentrations of trace elements. The multivariate statistical analysis elucidates that anthropogenic effect, fertilizers sewage contamination are the main causes of groundwater pollution. Nearly; 31% and 11.5% of groundwater samples posing oral chronic non carcinogenic health risk and dermal chronic risk for adult, respectively. While all surface water samples were posing oral chronic non carcinogenic health risk, with no dermal hazard. Visual MINTAQ geochemical modeling program was used for determining the groundwater aqueous species distribution to indicate their effect on the distribution of trace element in groundwater, revealing that Ba, Mn, Zn, and Sr existed as free radical ion in the hazardous samples; revealing that those elements would be available for further sorption process and can be mitigated through sorption processes. The uncharged species of Fe and Al are expected to be more mobile in groundwater because they would not be attracted to the surface charge of minerals. Inorganic ligands (HCO3−, SO42−, Cl−, and NO3−) act as nucleation centers that were linked with those trace elements creating new species with higher solubility degree in water that are transported away randomly for long distances in the water path.
Accurate prediction of posterior corneal astigmatism in a multi-center study for predictive, preventive and personalised medicine
Authors: Xu Guihua , Peng Qingsheng , Liu Baoyi , Zhu Shanqing , Guo Yunxiang , Yu Honghua , Hu Yijun 
Published: July 2022

Abstract
Aims
To predict posterior corneal astigmatism (PCA) magnitude and flat axis using other corneal parameters.
Methods
In this multicenter cross-sectional study, sex, age, eye laterality, and eight selected corneal parameters were input, and PCA magnitude and flat axis were output of the ridge regression (RR) models. Data from two centers were used for RR models construction and internal validation, and data from the other three centers were for external validation. Mean absolute error (MAE), root mean square error (RMSE) and area under the receiver operating characteristic curve (AUC) were used to evaluate the prediction accuracy.
Results
A total of 10448 subjects (17538 eyes) were included (5943 males and 4505 females, mean age: 24.84 ± 5.38 years). An RR equation was generated for prediction of PCA magnitude in all eyes (R2 = 0.501) with an MAE and an RMSE of 0.065-0.080D and 0.083-0.102D in external validation, respectively. Another RR equation was generated for prediction of PCA flat axis in all eyes (R2 = 0.157) with an MAE and an RMSE of 6.254–8.518° and 9.052–12.612° in external validation, respectively. Binary prediction of eyes with a PCA ≥ 0.50D was performed with a mean AUC of 0.900-0.928 in external validation. For eyes with a PCA ≥ 0.50D, in external validation an MAE of 0.049-0.059D and an RMSE of 0.058-0.076D were achieved in prediction of PCA magnitude, with an MAE of 2.863–4.010° and an RMSE of 3.755–5.263° in prediction of PCA flat axis.
Conclusions
Accurate prediction of PCA magnitude and flat axis based on other corneal parameters can be achieved by RR models. The RR models may be useful in refractive surgery to improve personalized astigmatism correction and prevent residual astigmatism.
Inhibitory effect of oroxylin A on atopic dermatitis-like symptoms in mice
Authors: Lee Ye-Ji , Im Dong-Soon 
Published: July 2022

Abstract
Scutellaria baicalensis has long been used in Asian traditional medicine to prevent and treat suppurative dermatitis, allergic diseases, inflammation, hyperlipemia, and arteriosclerosis. Oroxylin A is a flavone present in Scutellaria baicalensis. Because the root extracts of Scutellaria baicalensis have been shown to have anti-dermatitis effects, the authors investigated the effects of oroxylin A on chemically-induced atopic dermatitis (AD) in an in vivo AD model induced by 1-chloro-2,4-dinitrobenzene (CDNB) in BALB/c mice. CDNB-induced skin hypertrophy and accumulation of mast cells in the epidermis and dermis were significantly ameliorated by oroxylin A. Increased serum levels of immunoglobulin E, as well as pro-inflammatory chemokines and cytokines in the skin and lymph nodes were significantly ameliorated by oroxylin A. Suppression of immune responses in the skin and lymph nodes by oroxylin A decreased the symptoms of AD. Thus, these results proved that oroxylin A is an effective component of Scutellaria baicalensis for treating the symptoms of AD.
Two-Timescale Design for Reconfigurable Intelligent Surface-aided Full-Duplex Massive MIMO Systems
Authors: ZHU Feng , Dai Jianxin 
Published: July 2022

Abstract
In this paper, we aim to investigate a full-duplex reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple- output (mMIMO) system. Different from the existing contributions, we consider the two-timescale design scheme. Specifically, the phase shift at the RIS is designed based on the statistical channel state information (CSI), while the beamforming at the base station (BS) is designed based on the instantaneous effective CSI. We derive the closed-form expression of the uplink (UL) and downlink (DL) achievable rate, analyse the system performance and use genetic algorithm

(GA) to maximize UL, DL and full-duplex achievable sum rate.
Analysis of Intracell Spectrum Handoff under General Traffic Parameters Distribution in Cognitive Radio Networks
Authors: Hoque Shanidul , Sriv A 
Published: July 2022

Abstract
Cognitive Radio (CR) technology solves the spectrum scarcity and spectrum shortcoming issues through dynamic spectrum access with a central point of contention spectrum handoff (SHO). SHO is an essential operation of secondary users (SUs) which is accountable for seamless and reliable services to ensuring better performance of a CR network. In this paper, we analyse the performance of intracell SHO of a non-stationary SU under various traffic parameters distribution in CR networks. We model the analytical formula of probability of intracell SHO and expected number of SHO of an SU in both source cell and destination cell considering lognormal service time distribution and Erlang-3, 23 residual time distribution of spectrum holes in a CR network. This paper also investigates the effect of departure rates of spectrum holes (λ), SUs (µ), and cell crossing rate (η) of SUs on probability of intracell SHO and expected number of SHO in a CR network. The proposed model with lognormal service time distribution and erlang-3, 23 residual time distribution offers higher probability of no intracell SHO and lower probabilities of intracell SHO (1st, 2nd, 3rd, and so on) and therefore, provides fewer number of expected number of SHO under the impact of λ, µ, and η.
Spatial-Temporal Fusion Graph Framework for Trajectory Similarity Computation
Authors: Zhou Silin , Han Peng , Yao Di , Chen Lisi , Zhang Xiangliang 
Published: July 2022

Abstract
Trajectory similarity computation is an essential operation in many applications of spatial data analysis. In this paper, we study the problem of trajectory similarity computation over spatial network, where the real distances between objects are reflected by the network distance. Unlike previous studies which learn the representation of trajectories in Euclidean space, it requires to capture not only the sequence information of the trajectory but also the structure of spatial network. To this end, we propose GTS, a brand new framework that can jointly learn both factors so as to accurately compute the similarity. It first learns the representation of each point-of-interest (POI) in the road network along with the trajectory information. This is realized by incorporating the distances between POIs and trajectory in the random walk over the spatial network as well as the loss function. Then the trajectory representation is learned by a Graph Neural Network model to identify neighboring POIs within the same trajectory, together with an LSTM model to capture the sequence information in the trajectory. On the basis of it, we also develop the GTS+ extension to support similarity metrics that involve both spatial and temporal information. We conduct comprehensive evaluation on several real world datasets. The experimental results demonstrate that our model substantially outperforms all existing approaches.
Traumatic blunt thoracic aortic injury: a 10-year single-center retrospective analysis
Authors: Sun Jingwei , Ren Kai , Zhang Liyun , Xue Chao , Duan Weixun , Liu Jincheng 
Published: July 2022

Abstract
Background: Approximately 80% of patients with blunt thoracic aortic injury (BTAI) die before reaching the hospital. Most people who survive the initial injury eventually die without appropriate treatment. This study analyzed and reported the treatment strategy of a single center for BTAI in the last 10 years and the early and middle clinical results.Methods: This retrospective study included patients diagnosed with BTAI at Xijing Hospital from 2013 to 2022. All inpatients with BTAI aged ≥18 years were included in this study. The clinical data, imaging findings, and follow-up results were retrospectively collected and analyzed. The Kaplan–Meier curve and multivariate logistic regression were used to compare survivors and nonsurvivors.Results: A total of 72 patients (57% men) were diagnosed with BTAI, with a mean age of 54.2 ± 9.1 years. The injury severity score (ISS) was 24.3 ± 18, with Grade I BTAI1 (1.4%), Grade II 17 (23.6%), Grade III 52 (72.2%), and Grade IV 2 (2.8%) aortic injuries. Traffic accidents were the main cause of BTAI in 32 patients (44.4%). Most patients had trauma, 37 had rib fractures (51.4%), Sixty patients (83.3%) underwent thoracic endovascular aortic repair (TEVAR) surgery, eight (11.1%) underwent conservative treatment, and only four (5.6%) underwent open surgery.The overall hospitalization mortality was 12.5%. In multivariate logistic regression, elevated creatinine levels (P = 0.041) and high Glasgow coma scale (GCS) score (P = 0.004) were the predictors of hospital mortality. The median follow-up period was 57 (28–87) months. During the follow-up period, all-cause mortality was 5.6% and no aortic-related deaths were reported. Three patients (4.2%) needed secondary surgery and two of them underwent endovascular repair.Conclusion: Although TEVAR surgery may be associated with intra- or postoperative dissection rupture or serious complications in the treatment of Grade III BTAI, the incidence rate was only 8.9%. Nevertheless, TEVAR surgery remains a safe and feasible approach for the treatment of Grade II or III BTAI, and surgical treatment should be considered first,. A high GCS score and elevated creatinine levels in the emergency department were closely associated with hospital mortality. Younger patients need long-term follow-up after TEVAR.
TCR extracellular domain genetically linked to CD28, 2B4/41BB and DAP10/CD3ζ-engineered NK cells mediates antitumor effects
Authors: Li Shance , Zhang Chaoting , Shen Luyan , Teng Xia , Xiao Yefei , Lu Zheming 
Published: July 2022

Abstract
NK cells, especially FDA-approved NK-92 cells, could be used for TCR engineering owing to their specialized cytotoxicity against tumors, safety profile and potential use as an off-the-shelf cellular therapy. The TCR complex requires assembly of TCR-α/β chains with CD3 molecules (CD3δ, CD3γ, CD3ε, CD3ζ) to be correctly expressed at the cell membrane, and yet NK cells lack expression of these CD3 subunits besides CD3ζ. Since transmembrane regions of TCR α and β chains are involved in TCR complex assembly, transmembrane regions of TCR replaced by CD28 transmembrane domain could result in the expression of TCR independent of its companion CD3 subunits. However, since the absence of CD3 signaling components can influence the transmission of TCR signals to NK cells, it is necessary to add the signaling molecules of NK cells followed by CD28 transmembrane domain. Both CD3ζ and DAP10 play an important role in the activation and cytotoxicity of NK cells; moreover, 2B4 and 4-1BB are the main costimulatory molecules in NK cells. Therefore, we designed a chimeric TCR that consisted of the extracellular domains of the TCR α and β chains specific for NYESO-1 fused to the CD28 transmembrane domain followed by the 41BB and CD3ζ signaling domains as well as the 2B4 and DAP10 signaling domain, respectively. The chimeric TCR genetically engineered NK-92 cells exhibit antigen-specific recognition and lysis of tumor cells both in vitro and in vivo. The overall encouraging data highlight the value of NK-92 cells engineered to express therapeutic chimeric TCR for adoptive immunotherapies.
Using near-infrared reflectance and biomass allocation patterns of maize plants (Zea mays L.) to characterize soil fertility and productivity response dynamics
Authors: Awiti Alex O. 
Published: July 2022

Abstract
This paper characterizes the variation in soil quality along a forest to cropland conversation chronosequence using (i) VIS/NIR spectral characteristics of leaf samples from maize plants grown on soils from a forest-cropland chronosequence and, (ii) evaluates root: shoot biomass partitioning patterns of maize plants along a chronosequence soil quality gradient. Five hundred and forty-two topsoil samples were retrieved from a forest to cropland conversation chronosequence comprising primary and secondary forest, recently converted and historically converted farmlands. About 200 grams of each of the 542 samples were used in a bioassay in which hybrid maize seeds were planted in plastic pots under controlled conditions. Plants were harvested after 14 days. Shoots and roots were separated, dried and weighed. Discriminant analysis was used to evaluate the underlying spectral differences among the dried, ground shoot samples. Root: shoot biomass allocation patterns were assessed relative to soil spectral condition classes. The difference in reflectance of leaf samples was significant (Wilk’s Lambda = 0.006; F= 18.27; p>0.0001). The reflectance of leaf samples from maize plants grown in nutrient-poor exhibited a right shift in the 0.68-0.74 µm region (red edge position); a phenomenon diagnostic of nutrient stress. Maize plants exhibited plasticity in biomass partitioning patterns consistent with the soil quality gradient defined by fertility classes. Log-transformed root-shoot ratios revealed that maize plants grown in high nutrient soils had a low root/shoot ratio. High root: shoot ratio was observed among maize plants grown in soils classified as low in nutrients.
Analysis of the value and possible mechanisms of miRNA in cirrhosis based on bioinformatics approach
Authors: Kuang Xiao , Li Jinyu , Xu Yiheng , Yang Lihong , Liu Xiaoxiao , Yang Jinhui , Tai Wenlin 
Published: July 2022

Abstract
Aim: Cirrhosis is the ultimate fate of several liver diseases, but the mechanisms regarding the development of cirrhosis remain unclear. In this study, we performed a screening of differentially expressed miRNAs in cirrhosis using public databases and explored their functions and pathways associated with cirrhosis.Methods: We screened differentially expressed miRNAs in cirrhosis using the GEO dataset and bioinformatics methods. in addition, we explored their possible biological pathways using analysis of differentially expressed miRNAs and their predicted target genes and gene ontology (GO) terms. The screened miRNAs were also validated.Results: In total, we screened out 129 differentially expressed miRNAs. The differentially expressed miRANs and their target genes are concentrated in the nucleus and cytoplasm, while their functions and pathways are closely related to the activities of transcription factors or related enzymes. We found that the main upstream transcription factors regulating differential miRNAs are SP1, SP4, KLF7, EGR1, POU2F1, and RREB1. Then, we combined two factors, top ranking and high repetition frequency, to derive the top three most important genes (CTNNB1, RHOA, RAC1). Finally, we also performed a ROC curve analysis of the diagnostic efficacy of has-miR-199a/b-3p for cirrhosis (Area under the curve=0.7531, Sensitivity=55.56% Specificity=100%).Conclusions: We screened for differentially expressed miRNAs in cirrhosis and analyzed their associated transcription factors and target genes. The differentially expressed miRNAs functioned in close correlation with the associated transcription factor activity. And, we identified the top three pivotal genes (CTNNB1, RHOA, RAC1) among the target genes. Finally, has-miR-199a/b-3p was analyzed and concluded that it can be used as a non-invasive diagnostic biomarker for liver cirrhosis. The differential miRNAs and their target genes identified in this study not only reveal new insights into the pathogenesis of cirrhosis, but also provide many potential targets for the treatment of cirrhosis.