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Abstract Purpose To investigate the value of CT urography (CTU) indicators in the quantitative differential diagnosis of bladder urothelial carcinoma (BUC) and inverted papilloma of the bladder (IPB). Material and methods The clinical and preoperative CTU imaging data of continuous 103 patients with histologically confirmed BUC or IPB were retrospectively analyzed. The imaging data included 6 qualitative indicators and 7 quantitative measures. The recorded clinical information and imaging features were subjected to univariate and multivariate logistic regression analysis to find independent risk factors for BUC, and a combined multi-indicator prediction model was constructed, and the prediction model was visualized using nomogram. ROC curve analysis was used to calculate and compare the predictive efficacy of independent risk factors and nomogram. Results Junction smoothness, maximum longitudinal diameter, tumor-wall interface and arterial reinforcement rate were independent risk factors for distinguishing BUC from IPB. The AUC of the combined model was 0.934 (sensitivity = 0.808, specificity = 0.920, accuracy = 0.835), and its diagnostic efficiency was higher than that of junction smoothness (AUC=0.667, sensitivity = 0.654, specificity = 0.680, accuracy = 0.660), maximum longitudinal diameter (AUC=0.757, sensitivity = 0.833, specificity = 0.604, accuracy = 0.786), tumor-wall interface (AUC=0.888, sensitivity = 0.755, specificity = 0.808, accuracy = 0.816) and Arterial reinforcement rate (AUC=0.786, sensitivity = 0.936, specificity = 0.640, accuracy = 0.864). Conclusion Above qualitative and quantitative indicators based on CTU and the combination of them may be helpful to the differential diagnosis of BUC and IPB, thus better assisting in clinical decision-making. Key points 1. Bladder urothelial carcinoma (BUC) and inverted papilloma of the bladder (IPB) exhibit similar clinical symptoms and imaging presentations. 2. The diagnostic value of CT urography (CTU) in distinguishing between BUC and IPB has not been documented. 3. BUC and IPB differ in lesion size, growth pattern and blood supply. 4. The diagnostic efficiency is optimized by integrating multiple independent risk factors into the prediction model.

F. taipaiensis P. Y. Li represents a significant asset within traditional Chinese medicinal flora, though it confronts the challenge of germplasm deterioration during its cultivation phase. This study aimed to discern the implications of single strains or combinations of diverse growth-promoting actinomycetes on the growth metrics, antioxidant competence and pertinent gene expression in the leaves of F. taipaiensis. The result revealed that the malondialdehyde content within the plant's leaves notably diminished in the treatment groups compared to the CK group, with the S6 group showcasing the most pronounced malondialdehyde reduction, amounting to approximately one-third of the CK's value. Leaf area, length and width peaked in the S5 cohort, registering values 4.55, 2.46 and 1.85 times surpassing the CK group. Concurrently, plant height and stem thickness were maximal in the S6 group, being 2.29 and 1.75 times that of the CK group, whereas leaf thickness reached its zenith in the S7 group, marking a 2.17-fold elevation compared to the CK. Photosynthetic pigments, soluble sugars and soluble proteins in the leaves, exhibited augmentation across the inoculated groups to varying magnitudes. Specifically, the S5 group was superior in photosynthetic metrics and pigments, while the S6 group manifested the highest soluble sugar concentration, which was 1.35 times that of the CK. The S3 group demonstrated the pinnacle of soluble protein content, an impressive 5.86-fold increment relative to the CK group. The enzymatic activities of superoxide dismutase, peroxidase and catalase, along with their affiliated gene expressions, were observably augmented in the inoculated groups, with the S5 group standing out. To encapsulate, the actinomycete inoculation holds potential in fostering the growth and maturation of F. taipaiensis, amplifying its environmental resilience. The revelations from this study extend valuable insights for the judicious choice of microbial fertilizers in the cultivated propagation of Fritillaria taipaiensis P. Y. Li.

Abstract Background and aims Stress ulcer (SU) is a common complication in patients with acute ischemic stroke. The relationship of infarction location and the incidence of SU was unclear. Herein, we aim to investigate the association between ischemic insular damage and the development of SU. Methods Data were retrieved from the SPARK study (Effect of Cardiac Function on Short‐Term Functional Prognosis in Patients with Acute Ischemic Stroke). We included the patients who had experienced an ischemic stroke within 7 days. The diagnosis of SU was based on clinical manifestations, including hematemesis, bloody nasogastric tube aspirate, or hematochezia. Evaluation of ischemic insular damage was conducted through magnetic resonance imaging. Cyclo‐oxygenase regression analysis and Kaplan–Meier survival curves were used to assess the relationship between ischemic insular damage and the occurrence of SU. Results Among the 1357 patients analyzed, 110 (8.1%) developed SUs during hospitalization, with 69 (6.7%) experiencing infarctions in the anterior circulation. After adjusting for potential confounders, patients with ischemic insular damage exhibited a 2.16‐fold higher risk of developing SUs compared to those without insular damage (p = .0206). Notably, among patients with infarctions in the anterior circulation, those with insular damage had a 2.21‐fold increased risk of SUs (p = .0387). Moreover, right insular damage was associated with a higher risk of SUs compared to left insular damage or no insular damage (p for trend = .0117). Kaplan–Meier curves demonstrated early separation among groups, persisting throughout the follow‐up period (all p

Background and objective: The association between cardiac dysfunction and functional outcome in acute ischemic stroke (AIS) is not clear. We aimed to investigate the relationship between the routinely assessed left ventricular ejection fraction (LVEF) and functional outcomes in patients with AIS. Methods: Data came from a prospective, observational, single-center study (Effect of Cardiac Function on Short-term Functional Prognosis in Patients with Acute Ischemic Stroke, SPARK). The LVEF was assessed with transthoracic echocardiography within 7 days of stroke onset. The primary outcome was functional disability, defined as a modified Rankin Scale score of 3–6 at 90 days (range: 0–6, with higher scores indicating greater disability). We also investigated the association of the LVEF with mortality, early neurological deterioration, hospital stay, and costs. Multivariate logistic regression analysis and 2:1 propensity score matching (PSM) were performed to compare the differences in outcomes. Results: A total of 1181 patients were included in this analysis, of which 87 (7.4 %) patients were found to have LVEF of

ObjectivesThe aims of this study were to report the effectiveness and safety of teriflunomide in Chinese patients with relapsing–remitting multiple sclerosis (RRMS) and to explore the association of paramagnetic rim lesion (PRL) burden with patient outcome in the context of teriflunomide treatment and the impact of teriflunomide on PRL burden.MethodsThis is a prospective observational study. A total of 100 RRMS patients treated with teriflunomide ≥3 months were included in analyzing drug persistence and safety. Among them, 96 patients treated ≥6 months were included in assessing drug effectiveness in aspects of no evidence of disease activity (NEDA) 3. The number and total volume of PRL were calculated in 76 patients with baseline susceptibility-weighted imaging (SWI), and their association with NEDA3 failure during teriflunomide treatment was investigated.ResultsOver a treatment period of 19.7 (3.1–51.7) months, teriflunomide reduced annualized relapse rate (ARR) from 1.1 ± 0.8 to 0.3 ± 0.5, and Expanded Disability Status Scale (EDSS) scores remained stable. At month 24, the NEDA3% and drug persistence rate were 43.8% and 65.1%, respectively. In patients with a baseline SWI, 81.6% had at least 1 PRL, and 42.1% had ≥4 PRLs. The total volume of PRL per patient was 0.3 (0.0–11.5) mL, accounting for 2.3% (0.0%–49.0%) of the total T2 lesion volume. Baseline PRL number ≥ 4 (OR = 4.24, p = 0.009), younger onset age (OR = 0.94, p = 0.039), and frequent relapses in initial 2 years of disease (OR = 13.40, p = 0.026) were associated with NEDA3 failure. The PRL number and volume were not reduced (p = 0.343 and 0.051) after teriflunomide treatment for more than 24 months. No new safety concerns were identified in this study.ConclusionTeriflunomide is effective in reducing ARR in Chinese patients with RRMS. Patients with less PRL burden, less frequent relapses, and relatively older age are likely to benefit more from teriflunomide, indicating that PRL might be a valuable measurement to inform clinical treatment decision.

Conducting risk and early warning assessments of heavy metals (HMs) pollution in agricultural soils holds significant importance for pollution prevention and sustainable agricultural development. Early warning studies on heavy metal contamination of agricultural soils in oases in arid zones are rare in previous studies, therefore, this study carried out spatial and temporal simulation and early warning studies on the environmental capacity of agricultural soils in the Hexi Corridor based on field monitoring data and remote sensing technology and other methods. The results revealed that agricultural soils have been affected by human activities, leaving HMs at a moderate pollution level. The mean environmental capacity indices for Cr, Ni, Cu, Zn, As and Pb showed that they all belonged to the medium-capacity state, and 7.01 % of the sampling points being overloaded and in the low capacity for As. Cr, Ni, Zn and As were found in the moderate and high capacity zones located in the study area's western part, and the spatial distribution was basically the same. HMs in the middle parts area were dominated by low to medium capacity status, which may be related to agricultural activities such as application of fertilizers and pesticides and sewage irrigation. Based on the soil dynamic capacity model, it was found that in the next 20 years, HMs showed a decrease of 70–80 %, and the soil environment dynamic capacity was smaller than both the static and existing capacity, and it showed a decreasing trend with the change of time, which indicated that the soil's capacity for pollutants in the study area would be reduced if no pollution control measures were taken. Risk warning results showed that the overall spatial distribution pattern of the probability of pollution in the study area during the next 10 and 20 years was lower in the west and the northern part of Wuwei City, and higher in the middle part. This study suggests constructing a management system of “pollution evaluation - source treatment - risk early warning” for heavy metal contaminated sites, formulating corresponding policies and early warning measures, strengthening the research and development of monitoring, remediation, and treatment technologies, and realizing the prevention and control of agricultural soil pollution and sustainable development in the study area.

Abstract Women with polycystic ovary syndrome are prone to develop gestational diabetes mellitus, a disease which may have significant impact on the postpartum health of both mother and infant. We performed a retrospective cohort study to develop and test a model that could predict gestational diabetes mellitus in the first trimester in women with polycystic ovary syndrome. Our study included 434 pregnant women who were referred to the obstetrics department between December 2017 and March 2020 with a diagnosis of polycystic ovary syndrome. Of these women, 104 were diagnosed with gestational diabetes mellitus in the second trimester. Univariate analysis revealed that in the first trimester, Hemoglobin A1c (HbA1C), age, total cholesterol(TC), low-density lipoprotein cholesterol (LDL-C), SBP (systolic blood pressure), family history, body mass index (BMI), and testosterone were predictive factors of gestational diabetes mellitus (P

Abstract Purpose To develop machine learning-based radiomics models derive from different MRI sequences for distinction between benign and malignant PI-RADS 3 lesions before intervention, and to cross-institution validate the generalization ability of the models. Methods The pre-biopsy MRI datas of 463 patients classified as PI-RADS 3 lesions were collected from 4 medical institutions retrospectively. 2347 radiomics features were extracted from the VOI of T2WI, DWI and ADC images. The ANOVA feature ranking method and support vector machine classifier were used to construct 3 single-sequence models and 1 integrated model combined with the features of three sequences. All the models were established in the training set and independently verified in the internal test and external validation set. The AUC was used to compared the predictive performance of PSAD with each model. Hosmer–lemeshow test was used to evaluate the degree of fitting between prediction probability and pathological results. Non-inferiority test was used to check generalization performance of the integrated model. Results The difference of PSAD between PCa and benign lesions was statistically significant (P = 0.006), with the mean AUC of 0.701 for predicting clinically significant prostate cancer (internal test AUC = 0.709 vs. external validation AUC = 0.692, P = 0.013) and 0.630 for predicting all cancer (internal test AUC = 0.637 vs. external validation AUC = 0.623, P = 0.036). T2WI-model with the mean AUC of 0.717 for predicting csPCa (internal test AUC = 0.738 vs. external validation AUC = 0.695, P = 0.264) and 0.634 for predicting all cancer (internal test AUC = 0.678 vs. external validation AUC = 0.589, P = 0.547). DWI-model with the mean AUC of 0.658 for predicting csPCa (internal test AUC = 0.635 vs. external validation AUC = 0.681, P = 0.086) and 0.655 for predicting all cancer (internal test AUC = 0.712 vs. external validation AUC = 0.598, P = 0.437). ADC-model with the mean AUC of 0.746 for predicting csPCa (internal test AUC = 0.767 vs. external validation AUC = 0.724, P = 0.269) and 0.645 for predicting all cancer (internal test AUC = 0.650 vs. external validation AUC = 0.640, P = 0.848). Integrated model with the mean AUC of 0.803 for predicting csPCa (internal test AUC = 0.804 vs. external validation AUC = 0.801, P = 0.019) and 0.778 for predicting all cancer (internal test AUC = 0.801 vs. external validation AUC = 0.754, P = 0.047). Conclusions The radiomics model based on machine learning has the potential to be a non-invasive tool to distinguish cancerous, noncancerous and csPCa in PI-RADS 3 lesions, and has relatively high generalization ability between different date set.

Natural ecosystems are changing more quickly because of human activities, the type and intensity of which are directly correlated with vegetation greenness. To effectively determine how human activities affect trends in vegetation under climate change, we must differentiate between various types of human activities. The GTWR model can study the spatiotemporal non-stationary relationship between the NDVI trend and climate change. The GTWR model was incorporated into multiple climate variables and improved residual analysis to quantify the contributions of climate change and human activities on vegetation change trends in the Hexi region during different periods. This study divides human activities into four groups based on land use change: urbanization, agricultural expansion, desertification, and ecological restoration to further investigate their contribution to vegetation greenness change. The results showed that in 56.9% of the significant vegetation greening trends between 1982 and 2015, climate factors contributed only 7.4%, while human factors contributed a significant 22.7%. Since the ecological restoration project implemented in 2000, the expansion intensity of ecological restoration and urbanization increased significantly, followed by agricultural expansion and desertification. For the considerable greening trends in the Hexi region, the ecological restoration project contributed 26.7%, while agricultural expansion and urbanization contributed 17.5% and 4.6%, respectively. This study aims to provide new insights for more accurate simulation and evaluation of the interaction effects of climate change and human socio-economic development on vegetation growth.

BackgroundThe differential diagnosis between autoimmune encephalitis and low-grade diffuse astrocytoma remains challenging. We aim to develop a quantitative model integrating radiomics and spatial distribution features derived from MRI for discriminating these two conditions.MethodsIn our study, we included 188 patients with confirmed autoimmune encephalitis (n = 81) and WHO grade II diffuse astrocytoma (n = 107). Patients with autoimmune encephalitis (AE, n = 59) and WHO grade II diffuse astrocytoma (AS, n = 79) were divided into training and test sets, using stratified sampling according to MRI scanners. We further included an independent validation set (22 patients with AE and 28 patients with AS). Hyperintensity fluid-attenuated inversion recovery (FLAIR) lesions were segmented for each subject. Ten radiomics and eight spatial distribution features were selected via the least absolute shrinkage and selection operator (LASSO), and joint models were constructed by logistic regression for disease classification. Model performance was measured in the test set using the area under the receiver operating characteristic (ROC) curve (AUC). The discrimination performance of the joint model was compared with neuroradiologists.ResultsThe joint model achieved better performance (AUC 0.957/0.908, accuracy 0.914/0.840 for test and independent validation sets, respectively) than the radiomics and spatial distribution models. The joint model achieved lower performance than a senior neuroradiologist (AUC 0.917/0.875) but higher performance than a junior neuroradiologist (AUC 0.692/0.745) in the test and independent validation sets.ConclusionThe joint model of radiomics and spatial distribution from a single FLAIR could effectively classify AE and AS, providing clinical decision support for the differential diagnosis between the two conditions.

Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder with the underlying etiology yet incompletely understood and no cure treatment. Patients of fragile X syndrome (FXS) also manifest symptoms, e.g. deficits in social behaviors, that are core traits with ASD. Several studies demonstrated that a mutual defect in retinoic acid (RA) signaling was observed in FXS and ASD. However, it is still unknown whether RA replenishment could pose a positive effect on autistic-like behaviors in FXS. Herein, we found that RA signaling was indeed down-regulated when the expression of FMR1 was impaired in SH-SY5Y cells. Furthermore, RA supplementation rescued the atypical social novelty behavior, but failed to alleviate the defects in sociability behavior or hyperactivity, in Fmr1 knock-out (KO) mouse model. The repetitive behavior and motor coordination appeared to be normal. The RNA sequencing results of the prefrontal cortex in Fmr1 KO mice indicated that deregulated expression of Foxp2, Tnfsf10, Lepr and other neuronal genes was restored to normal after RA treatment. Gene ontology terms of metabolic processes, extracellular matrix organization and behavioral pathways were enriched. Our findings provided a potential therapeutic intervention for social novelty defects in FXS.

To enhance environmental protection and sustainable development, green innovation (GI) is an inevitable choice for enterprises. This study incorporates social identity theory and social learning theory to explore the impact of ethical leadership on employee GI behavior. In addition, this study also examines the mediating effects of green organizational identity (GOI) and the moderating role of strategic flexibility (SF). Using the structural equation modeling, an empirical survey was conducted among 300 Chinese manufacturing companies. The study found that ethical leadership (EL) positively affects employees’ GI behavior (EGIB). It also positively impacts the GOI, which led to EGIB. In addition, the study also confirmed that GOI played a mediating role in the relationship between EL and EGIB. The results further indicated that SF positively enhanced the effect of GOI on EGIB. The findings have important contributions to theory and practice in the current research context.

The Wuwei area in the arid region of northwestern China is impacted by the harsh natural environment and human activities, and the problem of ecological degradation is severe there. In order to ensure the sustainable development of the regional social economy, it is necessary to monitor the changes in vegetation in Wuwei and its corresponding nonlinear relationships with climate change and human activities. In this study, the inter-annual and spatial–temporal evolution characteristics of vegetation in Wuwei from 1982 to 2015 have been analyzed based on non-parametric statistical methods. The analysis revealed that the areas of vegetation restoration and degradation accounted for 77 and 23% of the total area of the research area, respectively. From 1982 to 1999, vegetation degradation became extremely serious (14.4%) and was primarily concentrated in Gulang County and the high-altitude areas in the southwest. Since the ecological restoration project was implemented in 2000, there have been prominent results in vegetation restoration. The geographically and temporally weighted regression model shows that each climate factor has contributed to the vegetation restoration in the Wuwei area during the last 34 years, with their contributions ranked as precipitation (71.2%), PET (43.9%), solar radiation (34.8%), temperature (33.1%), and wind speed (31%). An analysis of the land-use data with 30 m resolution performed in this study revealed that the conversion area among land cover from 1985 to 2015 accounts for 14.9% of the total area. In it, the conversion area from non-ecological land to ecological land accounts for 5.7% of the total area. The farmland, grassland, and woodland areas have increased by 20.1, 20.6, and 8.5%, respectively, indicating that human activities such as agricultural intensification and ecological restoration projects have played a crucial role in vegetation restoration.

PurposeTo determine the predictive performance of the integrated model based on clinical factors and radiomic features for the accurate identification of clinically significant prostate cancer (csPCa) among Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions.Materials and MethodsA retrospective study of 103 patients with PI-RADS 3 lesions who underwent pre-operative 3.0-T MRI was performed. Patients were randomly divided into the training set and the testing set at a ratio of 7:3. Radiomic features were extracted from axial T2WI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images of each patient. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) feature selection methods were used to identify the radiomic features and construct a radiomic model for csPCa identification. Moreover, multivariable logistic regression analysis was used to integrate the clinical factors with radiomic feature model to further improve the accuracy of csPCa identification, and the two are presented in the form of normogram. The performance of the integrated model was compared with radiomic model and clinical model on testing set.ResultsA total of four radiomic features were selected and used for radiomic model construction producing a radiomic score (Radscore). Radscore was significantly different between the csPCa and the non-csPCa patients (training set: p < 0.001; testing set: p = 0.035). Multivariable logistic regression analysis showed that age and PSA could be used as independent predictors for csPCa identification. The clinical–radiomic model produced the receiver operating characteristic (ROC) curve (AUC) in the testing set was 0.88 (95%CI, 0.75–1.00), which was similar to clinical model (AUC = 0.85; 95%CI, 0.52–0.90) (p = 0.048) and higher than the radiomic model (AUC = 0.71; 95%CI, 0.68–1.00) (p < 0.001). The decision curve analysis implies that the clinical–radiomic model could be beneficial in identifying csPCa among PI-RADS 3 lesions.ConclusionThe clinical–radiomic model could effectively identify csPCa among biparametric PI-RADS 3 lesions and thus could help avoid unnecessary biopsy and improve the life quality of patients.

BackgroundIncreasing evidence has proved that chronic ankle instability (CAI) is highly related to the central nervous system (CNS). However, it is still unclear about the inherent cerebral activity among the CAI patients.PurposeTo investigate the differences of intrinsic functional cerebral activity between the CAI patients and healthy controls (HCs) and further explore its correlation with clinical measurement in CAI patients.Materials and MethodsA total of 25 CAI patients and 39 HCs were enrolled in this study. Resting-state functional magnetic resonance imaging (rs-fMRI) was used to detect spontaneous cerebral activity. The metrics of amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of the two groups were compared by two-sample t-test. The brain regions that demonstrated altered functional metrics were selected as the regions of interest (ROIs). The functional connectivity (FC) was analyzed based on the ROIs. The Spearman correlation was calculated between rs-fMRI metrics and clinical scale scores.ResultsCompared with HCs, CAI patients showed higher ALFF and ReHo values in the right postcentral gyrus, the right precentral gyrus, and the right middle frontal gyrus, while lower fALFF values in the orbital-frontal cortex (OFC, p < 0.01 after correction). Increasing FC between the right precentral gyrus and the right postcentral gyrus while decreasing FC between the right precentral gyrus and the anterior cingulum cortex (ACC), the right middle frontal gyrus and the left middle temporal gyrus, and the OFC and left inferior parietal lobule (IPL) was observed. In addition, in the CAI group, the ReHo value negatively correlated with the Cumberland Ankle Instability Tool score in the right middle frontal gyrus (r = −0.52, p = 0.007).ConclusionThe CAI patients exhibited enhanced and more coherent regional inherent neuronal activity within the sensorimotor network while lower regional inherent activity in pain/emotion modulation related region. In addition, the information exchanges were stronger within the sensorimotor network while weaker between distant interhemispheric regions. Besides, the increased inherent activity in the right middle frontal gyrus was related to clinical severity. These findings may provide insights into the pathophysiological alteration in CNS among CAI patients.

Abstract Background Goose parvovirus (GPV) is the etiological agent of Derzsy’s disease and is fatal for gosling. Research on the molecular basis of GPV pathogenicity has been hampered by the lack of a reliable reverse genetics system. At present, the GPV infectious clone has been rescued by transfection in the goose embryo, but the growth character of it is unclear in vitro. Methods In this study, we identified the full-length genome of GPV RC16 from the clinical sample, which was cloned into the pACYC177, generating the pIRC16. The recombinant virus (rGPV RC16) was rescued by the transfection of pIRC16 into goose embryo fibroblasts (GEFs). The rescued virus was characterized by whole genome sequencing, indirect immunofluorescence assays (IFA) and western blot (WB) using rabbit anti-GPV Rep polyclonal antibody as the primary antibody. Previously, we found the 164 K, 165 K, and 167 K residues in the 160YPVVKKPKLTEE171 are required for the nuclear import of VP1 (Chen S, Liu P, He Y, et al. Virology 519:17–22). According to that, the GPV infectious clones with mutated K164A, K165A, or K167A in VP1 were constructed, rescued and passaged. Results The rGPV RC16 has been successfully rescued by transfection of pIRC16 into the GEFs and can proliferate in vitro. Furthermore, the progeny virus produced by pIRC16 transfected cells was infectious in GEFs. Moreover, mutagenesis experiments showed that the rGPV RC16 with mutated 164 K, 165 K and 167 K in VP1 could not proliferate in GEFs based on the data of IFA and WB in parental virus and progeny virus. Conclusions The rGPV RC16 containing genetic maker and the progeny virus are infectious in GEFs. The 164 K, 165 K, and 167 K of VP1 are vital for the proliferation of rGPV RC16 in vitro.

The alkyl salicylaldoxime has attracted more and more attention recently due to the complex branched alkyl groups. In this study, a novel alkyl salicylaldoxime, tert-octylsalicylaldoxime, was successfully synthesized by the one-pot method. The yield and purity by the elemental analysis were 96.17 and 94.13%, respectively. The structure was confirmed by elemental analysis, FT-IR, 1H NMR (Nuclear Magnetic Resonance), 13C NMR spectroscopy, and MS. Results showed that tert-octylsalicylaldoxime with a new structure exhibited excellent extraction ability and selectivity for Cu(II) and can be successfully used to recover Cu from copper-nickel alloy electroplating wastewater. Thus, this product has the potential to be used as a powerful copper extractant in the future.

The practical application of photocatalytic H2-evolution is greatly limited by its sluggish charge separation, insufficient active sites, and stability of photocatalysts. Zero-dimensional (0D) Ti3C2 MXene quantum dots (MQDs) and amorphous Ti(IV) have been proven to be potential substitutes for noble co-catalyst to accelerate the separation of photogenerated electron-hole pairs and prevent the self-oxidation of photocatalysts, leading to better photocatalytic H2-evolution performance with long-term stability. In this study, amorphous Ti(IV) and MQDs co-catalysts were successfully deposited on ZnIn2S4 (ZIS) microspheres composed of ultra-thin nanosheets via a simple impregnation and self-assembly method (denoted as MQDs/ZIS/Ti(IV)). As expected, the optimal MQDs/ZIS/Ti(IV) sample exhibited a photocatalytic H2-evolution rate of 7.52 mmol·g−1·h−1 and excellent photostability without metallic Pt as the co-catalyst in the presence of Na2S/Na2SO3 as hole scavenger, about 16, 4.02 and 4.25 times higher than those of ZIS, ZIS/Ti(IV), and MQDs/ZIS, respectively. The significantly enhanced photocatalytic H2-evolution activity is attributed to the synergistic effect of the three-dimensional (3D) flower-like microsphere structure, the amorphous Ti(IV) hole co-catalyst, and a Schottky junction formed at the ZIS–MQDs interface, which offers more active sites, suppresses self-photocorrosion, and photo-generates the charge recombination of ZIS.

Mitochondrial encephalomyopathy with lactic acidosis and stroke‐like episodes (MELAS) is a rare maternally inherited genetic disease; however, little is known about its underlying brain basis. Furthermore, the topological organization of brain functional network in MELAS has not been explored. Here, 45 patients with MELAS (22 at acute stage, 23 at chronic stage) and 22 normal controls were studied using resting- state functional magnetic resonance imaging and graph theory analysis approaches. Topological properties of brain functional networks including global and nodal metrics, rich club organization and modularity were analyzed. At the global level, MELAS patients exhibited reduced clustering coefficient, normalized clustering coefficient, normalized characteristic path length and local network efficiency compared with the controls. At the nodal level, several nodes with abnormal degree centrality and nodal efficiency were detected in MELAS patients, and the distribution of these nodes was partly consistent with the stroke-like lesions. For rich club organization, rich club nodes were reorganized and the connections among them were decreased in MELAS patients. Modularity analysis revealed that MELAS patents had altered intra- or inter-modular connections in default mode network, fronto-parietal network, sensorimotor network, occipital network and cerebellum network. Notably, the patients at acute stage showed more obvious changes in these topological properties than the patients at chronic stage. These findings indicated that MELAS patients, particularly those at acute stage, exhibited topological reorganization of the whole-brain functional network. This study may help us to understand the neuropathological mechanisms of MELAS.

Polyurethane anticorrosion coating has been widely used as a metal coating material in recent years, but it has some shortcomings in hydrophobicity, heat resistance and hardness. In this paper, we add organic silicon to improve the performance of polyurethane through chemical modification. We show that the addition of organic silicon improves the chemical stability of polyurethane based on chemical rules, and prepare polyurethane prepolymer and add organic silicon to test its performance in the form of experimental study. The experimental results show that the addition of organic silicon can improve the contact angle, hardness and impact strength of polyurethane coating. This study is of theoretical guiding significance to the performance improvement of polyurethane and its application in the anticorrosion coating.

Golden wild yak is a rare and unique Yak subspecies in China. In this study, we first identified the complete mitochondrial genome sequence of golden wild yak. The complete mitogenome was 16,323 bp in length, with 37 typical animal mitochondrial genes (22 transfer RNA, 2 ribosomal RNA and 13 protein-coding genes) and one non-coding region (D-loop), and its contents of A, T, G, and C were 33.71%, 27.26%, 13.21%, 25.82, respectively. The phylogenetic analysis showed that the golden wild yak is closer with Pali yak, and it might be a mutant type of Yak living in Qinghai–Tibetan Plateau area.

This paper uses the data on four provinces in Northwest China from 2000 to 2015 to establish a panel model to test the long-term relationship between the size of provincial governments and economic growth, industrialization, urbanization and marketization, and estimates the results by using the fixed effect model, and obtains the empirical results of the size of the four provinces in Northwest China for the above four effects.

Objectives Develop risk-adapted conditional biopsy pathways utilizing MRI in combination with prostate-specific antigen (PSA) density (PSAD) and the ratio of free to total PSA (f/tPSA), respectively, to enhance the detection of clinically significant prostate cancer (csPCa) while minimizing ‘negative’ biopsies in low-risk patients.Methods The Prostate Imaging Reporting and Data System (PI-RADS) category, PSAD, f/tPSA and biopsy-pathology of 1018 patients were collected retrospectively. Subsequently, PSAD and f/tPSA were divided into four intervals, which were then combined with the MRI findings to construct two risk stratification matrix tables. Six biopsy decision pathways were established: three clinical pathways based solely on PSAD and f/tPSA, and three MRI-combined pathways incorporating both PI-RADS and PSA-derived indicators. The biopsy and clinically insignificant PCa (ciPCa) avoidance, csPCa detection rate, and ‘negative’ biopsies proportion were assessed. Decision curve analysis (DCA) was employed to evaluate the net benefit associated with each pathway.Results When reporting PI-RADS 1 - 2, PSAD ≥ 0.20 ng/ml/cm3 or f/tPSA ≤ 0.10 were found to be useful for patient stratification. When reporting PI-RADS 3, PSAD ≥ 0.10 − 0.15 ng/ml/cm3 and f/tPSA ≤ 0.16 − 0.25 were helpful in distinguishing the risk of csPCa. The three MRI-combined pathways showed higher csPCa detection rates (94% to 96%) than the three clinical pathways (85% to 91%); ‘MRI + PSAD + f/tPSA’ demonstrated a high csPCa detection rate of 94% while maintaining the maximum biopsy avoidance and lowest ‘negative’ biopsy proportion of 40% and 25%, respectively. The DCA showed significantly higher net benefits for three MRI-combined pathways compared to all clinical pathways.Conclusions The integration of MRI and PSA-derived indicators enables effective patient risk stratification, thereby providing valuable decision-making pathways to enhance the management of csPCa while minimizing ‘negative’ biopsies.

The arid region of northwest China provides a unique terrestrial ecosystem to identify the response of vegetation activities to natural and anthropogenic changes. To reveal the influences of climate and anthropogenic factors on vegetation, the Normalized Difference Vegetation Index (NDVI), climate data, and land use and land cover change (LUCC) maps were used for this study. We analyzed the spatiotemporal change of NDVI during 2000–2015. A partial correlation analysis suggested that the contribution of precipitation (PRE) and temperature (TEM) on 95.43% of observed greening trends was 47% and 20%, respectively. The response of NDVI in the eastern section of the Qilian Mountains (ESQM) and the western section of the Qilian Mountains (WSQM) to PRE and TEM showed opposite trends. The multiple linear regressions used to quantify the contribution of anthropogenic activity on the NDVI trend indicated that the ESQM and oasis areas were mainly affected by anthropogenic activities (26%). The observed browning trend in the ESQM was attributed to excessive consumption of natural resources. A buffer analysis and piecewise regression methods were further applied to explore the influence of urbanization on NDVI and its change rate. The study demonstrated that urbanization destroys the vegetation cover within the developed city areas and extends about 4 km beyond the perimeter of urban areas and the NDVI of buffer cities (counties) in the range of 0–4 km (0–3 km) increased significantly. In the range of 5–15 (4–10) km (except for Jiayuguan), climate factors were the major drivers of a slight downtrend in the NDVI. The relationship of land use change and NDVI trends showed that construction land, urban settlement, and farmland expanded sharply by 171.43%, 60%, and 10.41%, respectively. It indicated that the rapid process of urbanization and coordinated urban-rural development shrunk ecosystem services.

Seed-based cross-correlation analysis (sCCA) and independent component analysis have been widely employed to extract functional networks from the resting state functional magnetic resonance imaging data. However, the results of sCCA, in terms of both connectivity strength and network topology, can be sensitive to seed selection variations. ICA avoids the potential problems due to seed selection, but choosing which component(s) to represent the network of interest could be subjective and problematic. In this study, we proposed a seed-based iterative cross-correlation analysis (siCCA) method for resting state brain network analysis. The method was applied to extract default mode network (DMN) and stable task control network (STCN) in two independent datasets acquired from normal adults. Compared with the networks obtained by traditional sCCA and ICA, the resting state networks produced by siCCA were found to be highly stable and independent on seed selection. siCCA was used to analyze DMN in first-episode major depressive disorder (MDD) patients. It was found that, in the MDD patients, the volume of DMN negatively correlated with the patients' social disability screening schedule scores.