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In the complex dynamics of modern information systems such as e-commerce and streaming services, managing uncertainty and leveraging information theory are crucial in enhancing session-aware recommender systems (SARSs). This paper presents an innovative approach to SARSs that combines static long-term and dynamic short-term preferences within a counterfactual causal framework. Our method addresses the shortcomings of current prediction models that tend to capture spurious correlations, leading to biased recommendations. By incorporating a counterfactual viewpoint, we aim to elucidate the causal influences of static long-term preferences on next-item selections and enhance the overall robustness of predictive models. We introduce a dual-tower architecture with a novel data augmentation process and a self-supervised training strategy, tailored to tackle inherent biases and unreliable correlations. Extensive experiments demonstrate the effectiveness of our approach, outperforming existing benchmarks and paving the way for more accurate and reliable session-based recommendations. [ABSTRACT FROM AUTHOR]

Climate warming, rising atmospheric CO2 concentration (C a), and nitrogen (N) availability are exerting profound impacts on global forest ecosystems, particularly in high-altitude mountains. This study investigated the tree-growth dynamics of timberline Larix chinensis in the Taibai Mountain, central China, and explored its ecophysiological responses to environmental stresses by combining tree growth and stable isotopes. The results showed that the growth rate of L. chinensis has significantly increased since the 1960s, and that tree growth in this timberline was particularly sensitive to temperature in spring. Moreover, the continuously rising intrinsic water-use efficiency (iWUE), linked to higher C a and warmer environment, promoted the growth of L. chinensis. Before the 1960s, tree-ring δ15N gradually increased, then shifted to an insignificant decline with the acceleration of tree growth, and broke the preexisting carbon–nitrogen balance. Meanwhile, climate warming and increased iWUE have replaced N as the principal drivers of tree growth since the 1960s. It is believed that L. chinensis may gradually suffer a decline in N availability as it continues to grow rapidly. The insightful understanding of the biochemical mechanisms of plant responses to growth-related environmental conditions will improve our ability to predict the evolution of high-elevation mountain ecosystems in the future. [ABSTRACT FROM AUTHOR]

Objective: Investigating the utility of serum exosomal markers CA125, HE4, and C5a, both individually and in combination, for distinguishing between benign and malignant ovarian tumors. Methods: In this study, we selected a total of 234 patients diagnosed with ovarian tumors, including 34 with malignant tumors, 10 with borderline ovarian tumors, and 190 with benign tumors. This study conducted comparisons of exosomal levels of CA125, HE4, and C5a among distinct groups, as well as making comparisons between serum and exosomal levels of CA125 and HE4. Furthermore, the diagnostic performance was assessed through Receiver Operating Characteristic (ROC) curve analysis. The Area Under the Curve (AUC) was computed, and a comparative evaluation of sensitivity and specificity was conducted to ascertain their effectiveness in determining the nature of ovarian tumors across different markers. Results: Serum CA125 and HE4 levels, the ROMA index, exosomal CA125, HE4, C5a levels, and their combined applied value (OCS value) were notably elevated in the ovarian non-benign tumor group compared to the benign tumor group, with statistical significance (P < 0.05). Exosomal and serum levels of CA125 and HE4 exhibited a positive correlation, with concentrations of these markers in serum surpassing those in exosomes. The combined OCS (AUC = 0.871) for CA125, HE4, and C5a in exosomes demonstrated superior sensitivity (0.773) and specificity (0.932) compared to serum tumor markers (CA125, HE4) and the ROMA index. The tumor stage represents an autonomous risk factor influencing the prognosis of individuals with ovarian malignancies. Conclusion: The stage of ovarian malignancy is an independent risk factor for its prognosis. The combination of exosomal CA125, HE4 and C5a has a higher clinical value for the identification of the nature of ovarian tumours. [ABSTRACT FROM AUTHOR]

This study focuses on effectively controlling landslides at the boundary of a soft rock open-pit dump while ensuring safe increases in the dump's capacity and optimal utilization of external dump sites. To achieve this, the adoption of a local filling method for the dump base is proposed. By leveraging the concepts of limit equilibrium theory and equivalent shear strength parameters, the mathematical expression of the slope stability coefficient in the Morgenstern-Price method is derived and improved. This improved method is then applied to a real engineering example to determine the optimal basement replacement rate required to maintain slope stability. The findings reveal that the local filling of the base is well-suited for slopes susceptible to potential landslides associated with cutting layers, bedding layers, and swelling. For practical ease, it is advisable to choose the lowest step in the dump's slope for construction convenience. As the local replacement rate of the base increases, the slope's stability coefficient gradually improves, with the K-Fs ratio showing a prominent role in this process. Additionally, numerical simulation methods are employed to elucidate the mechanism of the dump's landslide following local basement replacement, thereby providing comprehensive evidence of the engineering applicability of this method. The research results demonstrate a promising practical application prospect for effectively controlling the stability of soft base dump slopes. [ABSTRACT FROM AUTHOR]

The increasing frequency of global drought events poses a significant threat to the stability of grassland ecosystems' functionality. The Inner Mongolian grasslands stand out as one of the world's most drought-prone regions, facing elevated drought risks compared to other biomes. An in-depth comprehension of the impact of drought on grassland ecosystems is paramount for their long-term sustainability. Using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2018, this study identified various drought events within the Inner Mongolian grasslands, encompassing moderate drought, severe drought, and extreme drought. The resistance of the vegetation to the different drought conditions, assessed through net primary productivity (NPP) as a metric (reflecting its capacity to maintain its original level during drought periods), was examined. The research findings indicated that the period from 2001 to 2018 witnessed a substantial increase in both the frequency and the extent of drought events compared to the period from 1982 to 2000, particularly concerning severe and extreme droughts. The areas most severely impacted by extreme drought were the Xilingol League and the Alxa League. From 1982–2000 to 2001–2018, under moderate drought conditions, vegetation resistance exhibited a minor decrease in the central and eastern regions but experienced a slight increase in the western region. In contrast, under severe drought conditions, the western region saw a significant decrease in vegetation resistance. Remarkably, under extreme drought conditions, the western region showed a substantial increase in vegetation resistance, while the central and eastern regions experienced a slight decrease. Across all three drought conditions, as precipitation levels declined, the resistance of the meadow–steppe–desert ecosystems demonstrated a high–low–high distribution pattern. The temperate desert steppe exhibited a minimal vulnerability to drought, boasting resistance levels exceeding 0.9. Notably, extreme drought had the most pronounced impact on the temperate meadow steppe, temperate steppe, and temperate desert steppe, particularly within the temperate meadow steppe category. Given these findings, the authorities responsible for grassland management should prioritize regions characterized by frequent drought occurrences and low drought resistance, such as Ulanqab City, the Xilingol League, and the western part of Hulun Buir City. Safeguarding steppe ecosystems is of paramount importance for stabilizing vegetation productivity and land carbon sinks, especially under the anticipated exacerbation of climate conditions in the future. [ABSTRACT FROM AUTHOR]

Resilience is a fundamental concept for vegetation health. The increasing drought frequency and severity may pose severe threat to vegetation resilience. However, it is still not clear how vegetation resilience is evolving in response to climate change in pivotal biographical zones. Here, we examined the resilience changes in terms of leaf area index (LAI, an indicator of canopy structure) and gross primary productivity (GPP, an indicator of carbon uptake) in responding to the Standardized Precipitation‐Evapotranspiration Index (SPEI) and vapor pressure deficit (VPD) over China's Loess Plateau and Qinling Mountains. Linking remote sensing variables and tree ring width allows the upscaling of plot‐based vegetation growth information. We further explored potential explanatory factors associated with the heterogeneous spatial distributions of resilience changes. Results revealed that the resilience of GPP weakened more than LAI in response to drought, suggesting that compared to LAI, productivity requires more time to recover to the pre‐drought levels. Regionally, the change of vegetation resilience on the Loess Plateau and in high‐altitude areas was highly susceptible to SPEI and VPD, respectively. The observed spatial heterogeneity in resilience changes was mainly attributed by climate zone, water deficit, and their interactions. Our findings provide direct and empirical evidence that the vegetation in the Loess Plateau and Qinling Mountains is gradually losing resilience. The results indicate that sustained ecosystem water deficit and atmospheric dryness will continue to threaten vegetation survival and terrestrial ecosystem service. Plain Language Summary: Vegetation resilience in pivotal biographical regions is altered by increasingly severe drought pressures. However, to what extent resilience changes and how the regional responses vary to different drought indicators have not yet been well explored. Here we quantify the resilience changes regarding vegetation physiological function and canopy structure after the significant changes in drought conditions over the Loess Plateau and Qinling Mountains of China. Results show that the vegetation physiological function has been damaged more seriously than the canopy structure, suggesting vegetation is gradually losing resilience. In relatively high‐altitude regions, the change of vegetation resilience is more sensitive to high vapor pressure deficit than the Standardized Precipitation‐Evapotranspiration Index, but in opposite direction on the Loess Plateau. Spatial heterogeneity analysis shows that these changes are mainly affected by climate zone, water‐related factors (precipitation, relative humidity, soil water), and their interactive effects. Characterizing of resilience changes as reference conditions for ecosystem management and restoration has significant implications in the context of global warming. Key Points: The resilience of vegetation productivity weakened more than that of canopy structure in response to droughtThe impacts of atmospheric dryness on vegetation resilience changes are much larger than those of Standardized Precipitation‐Evapotranspiration Index (SPEI) in high‐altitude regionsCombined effects of climate zone (CZ) and water deficits explain the spatial heterogeneity of vegetation resilience changes [ABSTRACT FROM AUTHOR]

We construct a spacecraft performance-fault relationship graph of the control system, which can help space robots locate and repair spacecraft faults quickly. In order to improve the performance-fault relationship graph, we improve the Deep Deterministic Policy Gradient (DDPG) algorithm, and propose a relationship prediction method that combines representation learning reasoning with deep reinforcement learning reasoning. We take the spacecraft performance-fault relationship graph as the agent learning environment and adopt reinforcement learning to realize the optimal interaction between the agent and the environment. Meanwhile, our model uses a deep neural network to construct a complex value function and strategy function, which makes the agent have excellent perceptual decision-making ability and accurate value judgment ability. We evaluate our model on a performance-fault relationship graph of the control system. The experimental results show that our model has high prediction speed and accuracy, which can completely infer the optimal relationship path between entities to complete the spacecraft performance-fault relationship graph. [ABSTRACT FROM AUTHOR]

Grassland aboveground biomass (AGB) is an important indicator for studying the change in grassland ecological quality and carbon cycle. The rapid development of high-resolution remote sensing and unmanned aerial vehicles (UAV) provides a new opportunity for accurate estimation of grassland AGB on the plot scale. In this study, the mountain grassland was taken as the research object. Using UAV Light Detection and Ranging (LiDAR) data and multispectral satellite images, the influence of topographic correction methods on AGB estimation was compared and a series of LiDAR metrics and vegetation indices were extracted. On this basis, a comprehensive indicator, the vegetation index-height-intensity model (VHI), was proposed to estimate AGB quickly. The results show that: (1) Among the four topographic correction methods, the Teillet regression has the best effect, and can effectively improve the accuracy of AGB estimation in mountain grassland. The correlation between corrected ratio vegetation index and AGB was the highest (correlation coefficient: 0.682). (2) Among the height and intensity metrics, median height and max intensity yielded the higher accuracy in estimating AGB, with Root Mean Square Error (RMSE) of 322 g/m2 and 333 g/m2, respectively. (3) The VHI integrated spectrum and LiDAR information, and its accuracy for AGB estimation for mountain grassland, was obviously better than other indicators, with an RMSE of 272 g/m2. We also found that the accuracy of VHI in univariate models was comparable to that of complex multivariate models such as stepwise regression, support vector machine, and random forest. This study provides a new approach for estimating grassland AGB with multi-source data. As a simple and effective indicator, VHI has shown strong application potential for grassland AGB estimating in mountainous areas, and can be further applied to grassland carbon cycle research and fine management. [ABSTRACT FROM AUTHOR]

This paper presents a method to invert the two-dimensional distribution of a temperature and volume concentration of soot particles from color images. By using numerical simulation, the temperature field and particle volume-concentration field of a non-uniform soot flame are simultaneously reconstructed using the wide-response spectrum of a color CCD camera without adding monochromatic filters. The influence of number of cameras, error of camera position angle, measurement noise and different reconstruction algorithms on measurement accuracy are analyzed. The numerical-simulation results demonstrate that camera-position angle errors play a crucial role in the reconstruction accuracy. In addition, increasing the number of cameras can improve the reconstruction result accuracy. Compared with the least squares algorithm, the Tikhonov-regularization algorithm has a stronger anti-noise ability and can resist 39 dB of noise. The conclusions obtained in this paper are helpful to guide following experimental studies. [ABSTRACT FROM AUTHOR]

In the past few years, Leydig cell (LC) transplantation has been regarded as an effective strategy for providing physiological patterns of testosterone in vivo. Recently, we have successfully converted human foreskin fibroblasts (HFFs) into functional Leydig‐like cells (iLCs) in vitro by using the CRISPR/dCas9 system, which shows promising potential for seed cells. However, it is not known whether the reprogrammed iLCs can survive or restore serum testosterone levels in vivo. Therefore, in this study, we evaluate whether reprogrammed iLCs can restore the serum testosterone levels of castrated rats when they are transplanted into the fibrous capsule. We first developed the castrated Sprague Dawley rat model through bilateral orchiectomy and subsequently injected extracellular matrix gel containing transplanted cells into the fibrous capsule of castrated rats. Finally, we evaluated dynamic serum levels of testosterone and luteinizing hormone (LH) in castrated rats, the survival of implanted iLCs, and the expression levels of Leydig steroidogenic enzymes by immunofluorescence staining and Western blotting. Our results demonstrated that implanted iLCs could partially restore the serum testosterone level of castrated rats, weakly mimic the role of adult Leydig cells in the hypothalamic‐pituitary‐gonadal axis for a short period, and survive and secrete testosterone, through 6 weeks after transplantation. Therefore, this study may be valuable for treating male hypogonadism in the future. [ABSTRACT FROM AUTHOR]

Recently, Leydig cell (LC) transplantation has been revealed as a promising strategy for treating male hypogonadism; however, the key problem restricting the application of LC transplantation is a severe lack of seed cells. It seems that targeted activation of endogenous genes may provide a potential alternative. Therefore, the aim of this study was to determine whether targeted activation of Nr5a1, Gata4 and Dmrt1 (NGD) via the CRISPR/dCas9 synergistic activation mediator system could convert human foreskin fibroblasts (HFFs) into functional Leydig‐like cells. We first constructed the stable Hsd3b‐dCas9‐MPH‐HFF cell line using the Hsd3b‐EGFP, dCas9‐VP64 and MS2‐P65‐HSF1 lentiviral vectors and then infected it with single guide RNAs. Next, we evaluated the reprogrammed cells for their reprogramming efficiency, testosterone production characteristics and expression levels of Leydig steroidogenic markers by quantitative real‐time polymerase chain reaction or Western blotting. Our results showed that the reprogramming efficiency was close to 10% and that the reprogrammed Leydig‐like cells secreted testosterone rapidly and, more importantly, responded effectively to stimulation with human chorionic gonadotropin and expressed Leydig steroidogenic markers. Our findings demonstrate that simultaneous targeted activation of the endogenous NGD genes directly reprograms HFFs into functional Leydig‐like cells, providing an innovative technology that may have promising potential for the treatment of male androgen deficiency diseases. [ABSTRACT FROM AUTHOR]

Temperature and precipitation are considered to be the most important indicators affecting the green-up date. Sensitivity of the green-up date to temperature and precipitation is considered to be one of the key indicators to characterize the response of terrestrial ecosystems to climate change. We selected the main grassland types for analysis, including temperate steppe, temperate meadow steppe, upland meadow, and lowland meadow. This study investigates the variation in key meteorological indicators (daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation) between 2001 and 2018. We then examined the partial correlation and sensitivity of green-up date (GUD) to Tmax, Tmin, and precipitation. Our analysis indicated that the average GUD across the whole area was DOY 113. The mean GUD trend was −3.1 days/decade and the 25% region advanced significantly. Tmax and Tmin mainly showed a decreasing trend in winter (p > 0.05). In spring, Tmax mainly showed an increasing trend (p > 0.05) and Tmin a decreasing trend (p > 0.05). Precipitation showed no significant (p > 0.05) change trend and the trend range was ±10 mm/decade. For temperate steppe, the increase in Tmin in March promotes green-up (27.3%, the proportion of significant pixels), with a sensitivity of −0.17 days/°C. In addition, precipitation in April also promotes green-up (21.7%), with a sensitivity of −0.32 days/mm. The GUDs of temperate meadow steppe (73.9%), lowland meadow (65.9%), and upland meadow (22.1%) were mainly affected by Tmin in March, with sensitivities of −0.15 days/°C, −0.13 days/°C, and −0.14 days/°C, respectively. The results of this study reveal the response of vegetation to climate warming and contribute to improving the prediction of ecological changes as temperatures increase in the future. [ABSTRACT FROM AUTHOR]

Land surface phenology (LSP), as a precise bio-indicator that responds to climate change, has received much attention in fields concerned with climate change and ecology. Yet, the dynamics of LSP changes in the Qinling Mountains (QMs)—A transition zone between warm-temperate and north subtropical climates with complex vegetation structure—under significant climatic environmental evolution are unclear. Here, we analyzed the spatiotemporal dynamics of LSP for different vegetation types in the QMs from 2001 to 2019 and quantified the degree of influence of meteorological factors (temperature, precipitation, and shortwave radiation), and soil (temperature and moisture), and biological factors (maximum of NDVI and middle date during the growing season) on LSP changes using random forest models. The results show that there is an advanced trend (0.15 days/year) for the start of the growing season (SOS), a delayed trend (0.24 days/year) for the end of the growing season (EOS), and an overall extended trend (0.39 days/year) for the length of the growing season (LOS) in the QMs over the past two decades. Advanced SOS and delayed EOS were the dominant patterns leading to a lengthened vegetation growing season, followed by a joint delay of SOS and EOS, and the latter was particularly common in shrub and evergreen broadleaved forests. The growth season length increased significantly in western QMs. Furthermore, we confirmed that meteorological factors are the main factors affecting the interannual variations in SOS and EOS, especially the meteorological factor of preseason mean shortwave radiation (SWP). The grass and crop are most influenced by SWP. The soil condition has, overall, a minor influence the regional LSP. This study highlighted the specificity of different vegetation growth in the QMs under warming, which should be considered in the accurate prediction of vegetation growth in the future. [ABSTRACT FROM AUTHOR]

Northern China has been long threatened by aeolian desertification. In recent years, all levels of the Chinese government have performed a series of ecological protection and sand control projects. To grasp the implementation effects of these projects and adjust policies in time, it is necessary to understand the process of aeolian desertification quickly and accurately. Remote sensing technologies play an irreplaceable role in aeolian desertification monitoring. In this study, the Zhenglan Banner, which is in the hinterland of the Hunshandake Sandy Land, was considered as the research area. Based on unmanned aerial vehicle (UAV) images, ground survey data, and Landsat images called in Google Earth Engine (GEE), the aeolian desertified land (ADL) in 2000, 2004, 2010, 2015, and 2019 was extracted using spectral mixture analysis. A desertification index (DI) was constructed to evaluate the spatial and temporal dynamics of the ADL in the Zhenglan Banner. Finally, a residual analysis explored the driving forces of aeolian desertification. The results showed that (1) the ADL area in the Zhenglan Banner has been trending downwards over the past 20 years but rebounded from 2004 to 2010; (2) over the past 20 years, the area of slightly, moderately, and severely desertified land has decreased at annual rates of 0.4%, 2.7%, and 3.4%, respectively; (3) human activities had significantly positive and negative impacts on the aeolian desertification trend for 20.0% and 21.0% of the study area, respectively, but not for the rest. This paper explored new techniques for rapid aeolian desertification monitoring and is of great significance for controlling and managing aeolian desertification in this region. [ABSTRACT FROM AUTHOR]

The accumulation of heat and moderate precipitation are the primary factors that are used by grasslands to trigger a green-up date. The accumulated growing degree-days (AGDD) requirement over the preseason is an important indicator of the response of grassland spring phenology to climate change. This study adopted the Normalized Difference Phenology Index (NDPI), which derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), to extract annual green-up dates in the Hulun Buir grassland in China between 2001–2015. Our analysis indicated that the range (standard deviation) and trend for the green-up date were DOY (day of year) 104 to DOY 144 (10.6 days) and −2.0 days per decade. Nine point two percent of the study area had significant (p < 0.05) changes in AGDD requirements. The partial correlations between the AGDD requirements and chilling days (67.04%, pixels proportion) were negative and significant (p < 0.05). The partial correlations between the AGDD requirement and precipitation (28.87%) were positive and significant (p < 0.05). Finally, the partial correlation between the AGDD requirement and insolation (97.65%) were positive and significant (p < 0.05). The results of this study could reveal the response of vegetation to climate warming and contribute to improving the phenological mechanism model of different grassland types in future research. [ABSTRACT FROM AUTHOR]

• The RSDI is suitable for monitoring aeolian desertification. • The areas with significant restoration (34.1%) exceeded those with significant deterioration (6%) in the NSPB. • In the areas with significant restoration, 57.4% of the land was mainly affected by human activities. The northern sand-prevention belt (NSPB) is the key area for sand control in China, and the various ecological projects conducted there are important to the Chinese strategy for ecological security. In this paper, a new remote sensing-based desertification index (RSDI) based on principal component analysis was constructed from four aspects of vegetation greenness, surface moisture, soil grain size, and surface radiation. The overall evaluation accuracy of the index was 89.2%, and the kappa coefficient was 0.80, indicating high sensitivity to different degrees of aeolian desertification and suitability for multiscale research. The coefficient of variation, Mann–Kendall test, Theil–Sen median trend analysis, and residual analysis were used to analyze the spatiotemporal changes and driving forces of the RSDI in the NSPB from 2000 to 2020. The RSDI was used to compare aeolian desertification in different subregions, land use types, and ecological project areas. The important results are as follows: (1) the trend of the average RSDI was downward, but it increased significantly in 2008–2009 and 2013–2014; (2) the RSDI was characterized by relatively high volatility in 28.9% and moderate volatility in 27.1% of the area; (3) the areas with significant restoration (34.1%) greatly exceeded those with significant deterioration (6%), whereas 59.9% of the total area was stable; and (4) within the area with significant restoration, 57.4% was primarily affected by human activities, and 42.4% was primarily affected by climate change; however, most of the area with significant deterioration (71.1%) was affected by human activities. In general, the degree of aeolian desertification in the NSPB has decreased in the past 20 years and its ecological quality has continued to recover. However, unreasonable human activities still need to be reduced, and the ecological management of areas under serious threat of desertification needs to be strengthened. [ABSTRACT FROM AUTHOR]

Introduction: The disconnected-interacting protein 2 homolog A (DIP2A), a member of disconnected-interacting 2 protein family, has been shown to be involved in human nervous system-related mental illness. This protein is highly expressed in the nervous system of mouse. Mutation of mouse DIP2A causes defects in spine morphology and synaptic transmission, autism-like behaviors, and defective social novelty [5], [27], indicating that DIP2A is critical to the maintenance of neural development. However, the role of DIP2A in neural differentiation has yet to be investigated., Objective: To determine the role of DIP2A in neural differentiation, a neural differentiation model was established using mouse embryonic stem cells (mESCs) and studied by using gene-knockout technology and RNA-sequencing-based transcriptome analysis., Results: We found that DIP2A is not required for mESCs pluripotency maintenance, but loss of DIP2A causes the neural differentiation abnormalities in both N2B27 and KSR medium. Functional knockout of Dip2a gene also decreased proliferation of mESCs by perturbation of the cell cycle and profoundly inhibited the expression of a large number of neural development-associated genes which mainly enriched in spinal cord development and postsynapse assembly., Conclusions: The results of this report demonstrate that DIP2A plays an essential role in regulating differentiation of mESCs towards the neural fate., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Recent investigations have described the use of urinary matrix remodeling-associated protein 5 (MXRA5) as a novel biomarker of kidney impairment in the setting of chronic kidney disease. In this study, we aimed to evaluate the possible clinical application of urinary MXRA5 as a useful non-invasive marker in the urine from the affected renal pelvis and bladder of children with ureteropelvic junction obstruction (UPJO). We conducted a prospective cohort study of patients aged <12 months with prenatally diagnosed unilateral UPJO who underwent dismembered pyeloplasty in 2018 or 2019, and a sex- and age-matched control group of healthy children. Blood urea nitrogen and creatinine levels were normal in all the patients. The whole urine and urinary exosomal concentrations of MXRA5 were measured by enzyme-linked immunosorbent assay. The correlations between bladder/renal pelvic MXRA5 levels and differential renal function (DRF) in the affected kidney were also determined. A total of 35 UPJO patients and 12 controls were enrolled in the study. There was no significant difference in whole-urine MXRA5 level between the controls and UPJO patients. However, the exosomal MXRA5 level was significantly lower in the controls than in patients with UPJO ( p < 0.05). There were non-significant correlations between bladder and renal pelvis whole-urine MXRA5 levels and DRF ( R 2 = 0.1115, p = 0.05 and R 2 = 0.3313, p = 0.0502, respectively). The strongest correlation was between exosomal MXRA5 level in the renal pelvis and DRF ( R 2 = 0.8128, p < 0.0001). Urinary exosomal MXRA5 level was significantly higher in children with UPJO than controls. Higher urinary exosomal MXRA5 levels were significantly correlated with lower DRF in the affected kidney in children with UPJO., (Copyright © 2020 Wang, Shi, Xing, Deng, Li, Xie and Jiang.)

Although previous studies have shown that stem cells can be differentiated into Leydig cells by gene transfection, a simple, safe and effective induction method has not yet been reported. Therefore, the present study investigated novel methods for the induction of human umbilical cord mesenchymal stem cell (HUMSC) differentiation into Leydig-like, steroidogenic cells. HUMSCs were acquired using the tissue block culture attachment method, and the expression of MSC surface markers was evaluated by flow cytometry. Leydig cells were obtained by enzymatic digestion and identified by lineage-specific markers via immunofluorescence. Third-passage HUMSCs were cultured with differentiation-inducing medium (DIM) or Leydig cell-conditioned medium (LC-CM), and HUMSCs before induction were used as the control group. Following the induction of HUMSCs, Leydig cell lineage-specific markers (CYP11A1, CYP17A1 and 3β-HSD) were positively identified using immunofluorescence analysis. Additionally, reverse transcription-quantitative polymerase chain reaction and western blot analysis were performed to evaluate the expression levels of these genes and enzymes. In contrast, the control group cells did not show the characteristics of Leydig cells. Collectively, these results indicate that, under in vitro conditions, LC-CM can achieve a comparable effect to that of DIM on inducing HUMSCs differentiation into steroidogenic cells.