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BACKGROUND With the continuous accumulation of data resources around the world, the application of data visualization has become more urgent, and the methods of data visualization have also shown diversified characteristics. Data visualization is a scientific and technical research on the visual representation of data, which studies how to display relatively obscure data visually in a real and accurate way, to vividly and intuitively express the information and rules contained in the data. Literature is an important carrier of knowledge dissemination, with systematic characteristics, continuity, a large quantity and fast update, and is an important source of information. The visualization research of literature is of great significance to the dissemination of knowledge. At present, the visualization research of document data is mostly combined with the bibliometric analysis method, which visualizes the relationship between documents in the form of a scientific knowledge map. The application of this technology and method has played an important role in mining the information and rules contained in document data, but it is slightly insufficient in the spatial attribute mining of document data, which requires in-depth research in this field. OBJECTIVES To provide new solutions for expanding the application of literature data in the field of spatial visualization, thereby further enhancing the usable value of literature data. METHODS GIS technology was used to carry out the research on the spatial visualization method of document data, excavate the common content features and spatial features of document data, and gather the structured document data of a certain volume of spatial feature information to lay the data foundation for the visualization research. At the same time, the combination point between GIS technology and document data was studied, and the strategy and technical route for information mining and spatial visualization of document data were formed. Taking the data of more than 140 Re-Os isotope dating documents published since 2015 to 2020 as an example, the application test of this technical method was carried out. A Re-Os isotope data visualization service system with a five-tier architecture including layers of support, data, service, application and user has been developed, to realize the spatial visualization application of Re-Os isotope dating document data results. RESULTS The results show that: (1) The study area contains more than 140 ore producing areas that carried out Re-Os isotope dating research from 2015 to 2020, covering the eastern, central, and western regions of China. (2) There are 19 main minerals in the study area, mainly copper (29.0%), molybdenum (28.3%), tungsten (12.4%) and gold (11.0%). (3) There are 12 kinds of detection objects, and the proportion of molybdenite as the detection object is 80.7%, which indicates that molybdenite is still the preferred research object of the Re-Os isotope dating method, which is inseparable from the high Re/Os value of molybdenite. (4) The detection age falls in the lower age range of 0-200Ma, accounting for 62.1% of the ore-producing areas, which are mainly distributed in the northeast and southeast regions of China, indicating that the Re-Os isotope ages in the eastern region are concentrated in the Mesozoic era, which is consistent with the existence of large-scale Mesozoic mineralization events in the eastern region of China. The ore-producing area in the age range above 200Ma accounts for 37.9%, which is mainly distributed in the central and western regions of China, indicating that the Re-Os isotope ages in the central and western regions are concentrated before the Mesozoic era and have the characteristics of multiple mineralization. CONCLUSIONS The research shows that the document data visualization technology and method proposed in this paper can be used to excavate the spatial characteristics of the document data, expand the application of the document data in the field of spatial visualization, and solve the problems of how to analyze and extract the common information of the document data, locate the spatial feature information, and realize the spatial visualization technology. In terms of revealing important target areas, key research minerals and main application technologies, it can provide spatial visualization information, and provide reference for finding the hot spots and difficulties of current metallogenic chronology research.

Background: Definitive concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced, inoperable non-small cell lung cancer (NSCLC). Previous studies have mainly focused on examining local failure and recurrence patterns after surgery and the principles of lymph node metastasis (LNM) in surgical candidates with NSCLC. However, these studies were just only able to guide postoperative radiotherapy (PORT) and the patterns of LNM in patients with resected NSCLC was inadequate to represent that in locally advanced inoperable NSCLC patients for guiding target volume delineation of CCRT. In this study, we aimed to analyze the metastasis regularities and establish the correlations between different lymph node levels in NSCLC patients without any intervention using positron emission tomography/computed tomography (PET/CT) images. Methods: Overall, 358 patients with N1–N3 NSCLC admitted in our hospital between 2018 and 2022 were retrospectively analyzed. The diagnosis of metastatic lymph nodes was reviewed and determined using the European Organization for Research and Treatment of Cancer standard and the standardized value of the PET/CT examination. Univariate and multivariate analysis were performed to investigate the correlations between the different levels were evaluated by using of the chi-square test and logistic regression model. Results: The lymph nodes with the highest metastasis rates in patients with left lung cancer were in order as follows: 10L, 4L, 5, 4R, and 7; while in those with right lung cancer they were 10R, 4R, 7, 2R, and 1R. Notably, we found left lung patients were more likely to have contralateral hilar, mediastinal and supraclavicular lymph nodes involved, and the right lung group exhibited a higher propensity for ipsilateral mediastinum and supraclavicular lymph node invasion. Furthermore, correlation analysis revealed there were significant correlative patterns in the LNM across different levels. Conclusions: This study elucidated the patterns of primary LNM in patients with NSCLC who had not undergone surgery (without any treatment interventions) and the correlations between lymph node levels. These findings were expected to provide useful reference for target volume delineation in definitive concurrent chemoradiotherapy in locally advanced NSCLC patients. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate early stage dynamic changes in relevant indicators in neurocritical patients to identify biomarkers that can predict a poor prognosis at an early stage (1–4 days after admission). This study retrospectively collected clinical data, inflammatory indicators, and nutritional indicators from 77 patients at the neurology intensive care unit. The 3-month modified Rankin scale score was used as the outcome indicator. A linear mixed model was used to analyze changes in inflammatory indicators and nutritional indicators in neurocritical patients over time from 1–4 days after admission. Logistic regression was used to determine the independent risk factors for a poor prognosis in neurocritical patients and to construct a predictive model. The predictive efficacy of the model was verified using leave-one-out cross-validation and decision curve analysis methods. The analysis results showed that 1–4 days after admission, the inflammatory indicators of white blood cell and absolute monocyte counts and the nutritional indicators of body cell mass(BCM), fat-free mass, body cell mass/phase angle (BCM/PA), intracellular water, extracellular water, and skeletal muscle index increased overall, while the nutritional indicators of albumin and visceral fat area decreased overall. The logistic multivariate regression model showed that the Charlson comorbidity index (CCI) (odds ratio (OR) = 2.526, 95% CI [1.202, 5.308]), hemoglobin (Hb)(on admission)-Hb(min) (OR = 1.049, 95% CI [1.015, 1.083), BCM(on admission) (OR = 0.794, 95% CI [0.662, 0.952]), and the change in BCM/PA 1–4 days after admission (OR = 1.157, 95% CI [1.070, 1.252]) were independent risk factors for a poor prognosis in neurocritical patients. The predictive analysis showed that the predictive power of Model 1 with BCM/PA (area under the curve (AUC) = 0.95, 95% CI (0.90, 0.99)) was 93%, 65%, 141%, and 133% higher than that of Model 2 without BCM/PA, the CCI, the APACHE II score, and the NRS2002 score (all P < 0.05), respectively. The CCI, Hb(on admission)-Hb(min), BCM(on admission), and an increase in BCM/PA 1–4 days after admission were independently associated with a poor prognosis in neurocritical patients. Of these variables, BCM/PA may be a valid indicator for early stage prediction of a poor prognosis in neurocritical patients. [ABSTRACT FROM AUTHOR]

A coaxially integrated macro-micro composite actuator (MMCA) with large stroke and high accuracy is proposed by combining a voice coil motor (VCM) with the giant magnetostrictive actuator (GMA). The magnetic circuit model of the macro-motion part is established based on the driving principle of VCM, and the multi-field coupling model of the micro-motion part is established based on the Jiles-Atherton model. The finite element method was used to analyze the relationship between displacement, output force, velocity, acceleration, and time of the macro-motion part under different currents, the magnetic flux density, output force, and displacement curves of the micro-motion part, and the mutual influence between the macro and micro motion parts were analyzed. The prototype of the MMCA was developed, and an experimental test platform was built. The results show that the MMCA macro-motion displacement curve can fit the simulation curve well during open-loop positioning, and when the current size of the input macro-motion coil is 4 A, the experimental curve of the MMCA is the most consistent with the simulation curve. When closed-loop control, the motion curve of the drive can well follow the set displacement curve, in which the maximum stroke of the prototype developed is 50 mm, the positioning error of the macro-motion part is less than 20 μm, the maximum stroke of the micro-motion part is 40 μm, and the overall positioning accuracy of the MMCA is 0.14 μm. The research results provide a new idea and theoretical basis for further optimization and development of precision positioning platform with high precision and large stroke. [ABSTRACT FROM AUTHOR]

In this study, the effect of annealing atmosphere on the electrical properties, optical properties, microstructure and defects of ZnO∶Al films was investigated in detail. The crystallization, surface and fracture morphologies, electrical properties, resistivity, transmittance, Raman vibration and photoluminescence of ZnO∶Al films were characterized by SEM, XRD, Hall effect test instruments, ultraviolet-visible spectrophotometer, Raman spectra and PL spectra. The results show that after annealing in air atmosphere, the carrier concentration of AZO films decreases from 1.63 × 1020 cm−3 to 7.1 × 1018 cm−3, the optical band gap varies from 3.51 eV to 3.37 eV, the transmittance in NIR increased and the band edge emission in PL spectrum shifted from 3.49 eV to 3.34 eV. On the other hand, while the carrier concentration of AZO films annealing in H2 atmosphere was 5.3 × 1020 cm-3, the optical band gap increases to 3.78 eV, the transmittance in NIR decreases remarkably, the emission intensity of the band edge increases by more than 10 times and the band edge emission in PL spectrum shifts to 3.57 eV. Furthermore, the 4 order LO phonons are observed in ZnO:Al films annealed in air.

Background and purpose: The expression of programmed death ligand-1 (PD-L1) in lung cancer not only is the most important biomarker for predicting the efficacy of programmed death-1 (PD-1)/PD-L1 inhibitors, but also may affect the efficacy of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) targeted therapy. However, there are currently few reports in the relevant literature on whether the expression of PD-L1 in lung cancer can affect the efficacy of chemotherapy in patients with lung adenocarcinoma. This study mainly explored the effect of PD-L1 expression in lung adenocarcinoma on the efficacy of pemetrexed-based chemotherapy and its underlying mechanism. Methods: From Oct. 2015 to Dec. 2018, 185 eligible lung adenocarcinoma patients treated in Department of Pathology, The General Hospital of Western Theater Command PLA were enrolled. The expressions of PD-L1 and thymidylate synthase (TS), a molecule predicting the efficacy of pemetrexed-based chemotherapy, were detected by immunohistochemistry. The survival curve of patients was drawn by Kaplan-Meier method. The log-rank test and COX regression model were used to analyze the clinicopathological factors affecting the patients’ progression-free survival (PFS) and overall survival (OS). The log-rank test was used to analyze the effects of PD-L1 and TS expressions on the patients’ PFS and OS. Spearman rank correlation test was used to analyze the correlation between PD-L1 expression and TS expression in lung cancer tissues. Western blot and real-time fluorescent quantitative polymerase chain reaction (RTFQ-PCR) were used to detect the protein and mRNA expressions of PD-L1 and TS in 6 types of lung adenocarcinoma cell lines. The Pearson correlation test was used to analyze the correlation between PD-L1 and TS at protein expression level and mRNA expression level. Results: Among 51 patients with advanced lung adenocarcinoma who received pemetrexed-based chemotherapy as first-line treatment, the objective response rate (ORR) of the PD-L1 positive group was 20.0%, and the disease control rate (DCR) was 60.0%. There was no significant difference compared with the PD-L1 negative group (ORR: 20.0% vs 35.5%, χ 2 =1.404, P=0.236; DCR: 60.0% vs 80.6%, χ 2 =2.602, P=0.107). The median PFS (mPFS) of patients with negative expression of PD-L1 was significantly better than that of patients with positive expression of PD-L1 (mPFS: 5.6 months vs 4.1 months, log-rank=5.406, P=0.020), and there was no significant difference in median OS (mOS) between them (mOS: 15.9 months vs 12.7 months, log-rank=0.525, P=0.469). Univariate analysis found that the positive expressions of PD-L1 and TS were risk factors for PFS ［PD-L1 negative vs positive: HR=2.002 (1.100-3.645), P=0.023; TS negative vs positive: HR=2.205 (1.367-4.587), P=0.003］. Multivariate analysis found that TS positive expression was an independent risk factor for PFS ［TS negative vs positive: HR=3.245 (1.091-9.652), P=0.034］. Among the 51 patients with advanced lung adenocarcinoma who received pemetrexed-based chemotherapy as the first-line treatment, the expression of PD-L1 in cancer tissues was significantly positively correlated with the expression of TS (r s =0.691, P

Background: The short-term prognosis of stroke patients is mainly influenced by the severity of the primary disease at admission and the trend of disease development during the acute phase (1–7 days after admission). Objective: The aim of this study is to explore the relationship between the bioelectrical impedance analysis (BIA) parameter trajectories during the acute phase of stroke patients and their short-term prognosis, and to investigate the predictive value of the prediction model constructed using BIA parameter trajectories and clinical indicators at admission for short-term prognosis in stroke patients. Methods: A total of 162 stroke patients were prospectively enrolled, and their clinical indicators at admission and BIA parameters during the first 1–7 days of admission were collected. A Group-Based Trajectory Model (GBTM) was employed to identify different subgroups of longitudinal trajectories of BIA parameters during the first 1–7 days of admission in stroke patients. The random forest algorithm was applied to screen BIA parameter trajectories and clinical indicators with predictive value, construct prediction models, and perform model comparisons. The outcome measure was the Modified Rankin Scale (mRS) score at discharge. Results: PA in BIA parameters can be divided into four separate trajectory groups. The incidence of poor prognosis (mRS: 4–6) at discharge was significantly higher in the "Low PA Rapid Decline Group" (85.0%) than in the "High PA Stable Group " (33.3%) and in the "Medium PA Slow Decline Group "(29.5%) (all P < 0.05). In-hospital mortality was the highest in the "Low PA Rapid Decline Group" (60%) compared with the remaining trajectory groups (P < 0.05). Compared with the prediction model with only clinical indicators (Model 1), the prediction model with PA trajectories (Model 2) demonstrated higher predictive accuracy and efficacy. The area under the receiver operating characteristic curve (AUC) of Model 2 was 0.909 [95% CI 0.863, 0.956], integrated discrimination improvement index (IDI), 0.035 (P < 0.001), and net reclassification improvement (NRI), 0.175 (P = 0.031). Conclusion: PA trajectories during the first 1–7 days of admission are associated with the short-term prognosis of stroke patients. PA trajectories have additional value in predicting the short-term prognosis of stroke patients. [ABSTRACT FROM AUTHOR]

The ecologically fragile agro-pastoral ecotone in northern China is characterized by relatively poor arable land quality. Yunzhou District in Datong City, which is situated within this transitional zone, boasts over 600 years of Hemerocallis citrina Baroni cultivation. Exploring the effects of soil physicochemical properties on daylily yield and related agronomic traits is essential for enhancing the ecological and economic value of dominant crops in ecologically fragile areas. Therefore, in this study, we focused on the daylily, a characteristic cash crop that is grown in the agro-pastoral ecotone in Yunzhou District. Physicochemical property measurement and yield estimation were performed using soil samples collected from 37 sites, with Spearman's correlation analysis, one-way analysis of variance with multiple comparisons, path analysis, and stepwise regression analysis used to analyze the generated data. The results showed the following: (1) The pathway analysis of daylily yield with each agronomic trait showed that the BN and PH directly affected the yield of daylily with direct pathway coefficients of 0.844 and 0.7, respectively, whereas the SN indirectly affected the yield of daylily through the BD and PH, with indirect pathway coefficients of 0.827 and 0.566, respectively. (2) A total of four principal components were extracted for the soil factors, of which SMC, ST and BD had large loadings on PC1; OM, TN and pH had large loadings on PC2; AK had large loadings on PC3; and AP had large loadings on PC4. (3) From the principal component regression and stepwise regression, it can be seen that SMC is the most critical factor affecting the yield of daylily, as well as the related agronomic traits, and the results also show that yield prediction was affected by OM, ST, and AK, while BN was influenced by OM and ST, and SN and PH were influenced by AP. Comparing the goodness of fit and significance of the two models, it can be concluded that the stepwise regression model is the optimal model for this study. [ABSTRACT FROM AUTHOR]