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Abstract In order to identify the time-varying frequency and amplitude of structural vibration based on the bridge structural health monitoring data and obtain the cable force of cable-stayed bridges in real time, a spectrum analysis method based on amplitude and phase estimation (APES) was proposed in this study. The amplitude spectrum of the acceleration data is first calculated by the APES method, the real-time spectrogram of the cable is obtained by the sliding window method. Then the modal frequency and amplitude are automatically extracted from the real-time spectrum by using a frequency extrusion post-processing technique, which can be regarded as the average value of the instantaneous frequency and amplitude respectively. Next, the fundamental frequency of the cable is extracted by using an automatic identification method, and the performance of the proposed method is verified. Finally, real-time scoring of cable forces and structural condition assessment is achieved with consideration of the moderation index model as well as the material strength. The results show that the APES method can use shorter calculation samples than the traditional Fast Fourier Transform (FFT) to obtain higher resolution and more accurate amplitude, which provides a theoretical basis for the real-time identification of fundamental frequency based on short-term monitoring data. The frequency extrusion post-processing-algorithm can reduce the spectrum recognition delay and improve timeliness of the cable force evaluation. The time-varying cable force with an interval of 10 s can be used to reflect the health status of the cable in time. The research results can provide technical support for the real-time extraction of cable force of long-span cable-stayed bridges, and can also provide an effective basis for component condition evaluation and bridge maintenance decision-making.

The Mongolian Plateau in Central Asia is an intracontinental tectonic system far from active plate boundaries. Despite its distance from these boundaries, the plateau is characterized by intense crustal deformation accompanied by voluminous Cenozoic volcanism and active modern seismicity. However, the intraplate deformation mechanism has long been debated owing to the scarcity of observations and contradictions between different results. In recent years, growing geophysical studies have been conducted on the Mongolian Plateau, providing constraints on its lithospheric structure and dynamics. Here, we review the geophysical research on the Mongolian Plateau over the last decade, including seismological, geodetic, gravity, magnetotelluric, and geodynamic aspects. This review aims to (a) describe crustal and mantle structures based on multiscale seismic images; (b) describe deformation patterns based on seismic anisotropy, focal mechanisms, and global positioning system (GPS) observations; and (c) discuss the mechanisms behind intraplate deformation, volcanism, and seismic activity across the Mongolian Plateau. Seismic images show that the crustal structure of the plateau has significant east-west differences. Several blocks in the western Mongolian Plateau have thick crusts, including the Altai Mountains, Hovsgol Rift, and Hangay Dome. The lithospheric deformation across the Mongolian Plateau has strong lateral variation, with NE-SW shortening in the Altai Mountains and W-E or NW-SE shear deformation in the Hangay Dome region and the eastern part. The varied deformation may result from the superposition of multiple mechanisms, including far-field stress in the Altai Mountains, mantle upwelling, and mantle flow in the Hangay Dome region. However, it is difficult to identify the geodynamics of the formation of the entire Mongolian Plateau because the deformation is too complicated, and the present models are not sufficient and are always partial. Overall, this review encompasses recent advances in seismic observations of the Mongolian Plateau, illuminates the heterogeneities in the crust and mantle structure and deformation of the plateau, and discusses the mechanisms behind the deformation, magmatism, and seismicity.

Abstract Background Recent evidences have shown sex-differential cognitive deficits in bipolar disorder (BD) and differences in cognitions across BD subtypes. However, the sex-specific effect on cognitive impairment in BD subtype II (BD-II) remains obscure. The aim of the current study was to examine whether cognitive deficits differ by gender in youth with BD-II depression. Method This cross-sectional study recruited 125 unmedicated youths with BD-II depression and 140 age-, sex-, and education-matched healthy controls (HCs). The Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) was used to assess cognitive functions. Mood state was assessed using the 24-item Hamilton Depression Rating Scale (24-HDRS) and the Young Mania Rating Scale (YMRS). Multivariate analysis of covariance (MANCOVA) was conducted. Result ​Compared with HCs, patients with BD-II depression had lower scores on MCCB composite and its seven cognitive domains (all p

Lithospheric structure beneath the northeastern Qinghai-Xizang Plateau is of vital significance for studying the geodynamic processes of crustal thickening and expansion of the Qinghai-Xizang Plateau. We conducted a joint inversion of receiver functions and surface wave dispersions with P-wave velocity constraints using data from the ChinArray II temporary stations deployed across the Qinghai-Xizang Plateau. Prior to joint inversion, we applied the H-κ-c method (Li JT et al., 2019) to the receiver function data in order to correct for the back-azimuthal variations in the arrival times of Ps phases and crustal multiples caused by crustal anisotropy and dipping interfaces. High-resolution images of vS, crustal thickness, and vP/vS structures in the Qinghai-Xizang Plateau were simultaneously derived from the joint inversion. The seismic images reveal that crustal thickness decreases outward from the Qinghai-Xizang Plateau. The stable interiors of the Ordos and Alxa blocks exhibited higher velocities and lower crustal vP/vS ratios. While, lower velocities and higher vP/vS ratios were observed beneath the Qilian Orogen and Songpan-Ganzi terrane (SPGZ), which are geologically active and mechanically weak, especially in the mid-lower crust. Delamination or thermal erosion of the lithosphere triggered by hot asthenospheric flow contributes to the observed uppermost mantle low-velocity zones (LVZs) in the SPGZ. The crustal thickness, vS, and vP/vS ratios suggest that whole lithospheric shortening is a plausible mechanism for crustal thickening in the Qinghai-Xizang Plateau, supporting the idea of coupled lithospheric-scale deformation in this region.

Understanding and managing soil organic carbon stocks (SOCS) are integral to ensuring environmental sustainability and the health of terrestrial ecosystems. The information of soil bulk density (BD) is important in accurately determining SOCS while it is often missing in the soil database. Using 3,504 soil profiles (14,170 soil samples) that represented diverse regions across China, we investigated the effectiveness of various pedotransfer functions (PTFs), including traditional PTFs, machine learning (ML), and ensemble model (EM), in predicting BD. The results showed that refitting the parameter(s) in traditional PTFs was essential for BD prediction (coefficient of determination (R2) of 0.299–0.432, root mean squared error (RMSE) of 0.156–0.162 g cm−3, Lin’s concordance coefficient (LCCC) of 0.428–0.605). Compared to traditional PTFs, ML can greatly improve the model performance for BD prediction with R2 of 0.425–0.616, RMSE of 0.129–0.158 g cm−3 and LCCC of 0.622–0.765. Our results also showed that EM can further improve BD prediction by ensembling four ML models (R2 = 0.630, RMSE = 0.126 g cm−3, LCCC = 0.775). Using the EM model, we filled the missing BD (1207 soil profiles with 3,112 soil samples) in our database and built the SOC stock database (4,275 soil profiles with 17,282 soil samples). This study can be a good reference for gap-filling the missing BD depending on the data availability, thus contribute to a deeper understanding in soil C related climate change mitigation, ecological balance preservation and environmental sustainability promotion.

The scientific goal of the Anninghe seismic array is to investigate the detailed geometry of the Anninghe fault and the velocity structure of the fault zone. This 2D seismic array is composed of 161 stations forming sub-rectangular geometry along the Anninghe fault, which covers 50 km and 150 km in the fault normal and strike directions, respectively, with ∼ 5 km intervals. The data were collected between June 2020 and June 2021, with some level of temporal gaps. Two types of instruments, i.e. QS-05A and SmartSolo, are used in this array. Data quality and examples of seismograms are provided in this paper. After the data protection period ends (expected in June 2024), researchers can request a dataset from the National Earthquake Science Data Center.

Seismic attenuation is a fundamental property of the Earth's media. Attenuation structure for the complicated geological structures with strong seismicity in the Sichuan-Yunnan region is poorly studied. In this study, we collected 108,399 waveforms of 11,517 local small earthquakes with magnitudes between 1.5 and 3.5 from January 2014 to September 2021 in the Sichuan-Yunnan region and its adjacent areas. We employed an envelope inversion technique for separating the intrinsic and scattering attenuations of the S coda wave, and obtained the intrinsic and scattering attenuation structures for frequencies between 0.25 and 8.00 Hz. The attenuation structures correlate well with the geological units, and some major faults mark the attenuation variations where historic large earthquakes have occurred. The regional average attenuation shows a negative frequency dependence. The average scattering attenuation has a faster descending rate than the average intrinsic attenuation, and is dominant at low frequencies, while at high frequencies the average intrinsic attenuation is stronger. The lateral variation in the intrinsic attenuation is consistent with the variation in heat flow, the scattering attenuation may be related to the scatter distribution and size. The total attenuation is consistent with the previous studies in this region, and the separate intrinsic and scattering attenuation may be useful in understanding regional tectonics and important in earthquake prevention and disaster reduction.

BackgroundThe COVID-19 pandemic has significantly impacted the mental health of college students, prompting the need for universities to implement measures to mitigate these adverse effects. This study aims to assess the mental health status and mitigation measures of college students, identify the primary factors contributing to their mental health challenges, and provide suggestions for educational institutions to reduce negative psychological impacts.MethodsIn February 2023, a questionnaire survey was conducted among 1,445 college students. Statistical analysis was performed on the survey results, and multiple regression models were used to identify significant influencing factors and optimize the model.ResultsThe study revealed correlations between factors affecting mental health during the pandemic, with interactions observed among some factors. Significant differences in mental health status were found among different groups of college students based on their information-sharing habits through apps and engagement in thesis research. Multiple regression analysis indicated that conducting academic research related to COVID-19 significantly increased the psychological stress of college students during the pandemic (p = 0.043). Among all mitigation measures, playing games demonstrated significant effectiveness in model analysis (p = 0.047). The optimization of the model showed that the multiple regression model considering the interaction of factors was more effective.ConclusionOur research identifies crucial factors influencing the mental health of college students and investigates the mental health status of various student groups. We recommend that educational institutions adopt proactive strategies and a multifaceted approach to support the mental health of college students and address potential issues that may arise.

Abstract There is a lack of scoring system to predict the occurrence of cirrhosis in individuals with acute-on-chronic liver failure (ACLF) in the absence of cirrhosis. The goal of this study was to develop a psoas muscle index (PMI)-based nomogram for cirrhosis risk in non-cirrhotic patients with HBV-related ACLF. We included 274 non-cirrhotic HBV-ACLF patients who were randomly assigned to training and validation groups. Logistic analyses were performed to identify risk factors for cirrhosis. A nomogram was then constructed. The predictive performance of the nomogram was assessed using the area under the receiver operating characteristic curve (AUROC), calibration curve, and decision curve analysis (DCA). During the 360-day follow-up, 44.5% (122/274) of non-cirrhotic HBV-ACLF patients developed cirrhosis. A higher PMI at the L3 level was correlated with a decreased risk of long-term cirrhosis occurrence (OR 0.677, 95% CI 0.518–0.885, P = 0.004). The nomogram incorporating PMI, age, neutrophil-to-lymphocyte ratio (NLR), and international normalized ratio (INR), indicated satisfactory predictive performance for cirrhosis risk stratification in ACLF population. The nomograms had an AUROC of 0.812 (95% CI 0.747–0.866) and 0.824 (95% CI 0.730–0.896) in the training and validation cohorts, respectively. The calibration curves displayed excellent predictive accuracy of the nomogram in both sets. In both cohorts, the DCA verified the nomogram's clinical efficacy. In non-cirrhotic HBV-ACLF patients, a greater PMI appears to protect against long-term cirrhosis occurrence. Strong predictive performance has been demonstrated by PMI-based nomograms in assessing the likelihood of 1-year cirrhosis in those with HBV-ACLF.

We build a high-resolution early aftershock catalog for the 2023 SE Türkiye seismic sequence with PALM, a seamless workflow that sequentially performs phase picking, association, location, and matched filter for continuous data. The catalog contains 29,519 well-located events in the two mainshocks rupture region during 2023-02-01–2023-02-28, which significantly improves the detection completeness and relocation precision compared to the public routine catalog. Employing the new PALM catalog, we analyze the structure of the seismogenic fault system. We find that the Eastern Anatolian Fault (EAF) that generated the first MW7.9 mainshock is overall near-vertical, whereas complexities are revealed in a small-scale, such as subparallel subfaults, unmapped branches, and stepovers. The seismicity on EAF is shallow (

Oxidative dissolution of stibnite (Sb2S3) is the primary process that controls the release of antimony (Sb) from rock and ore into the soil and water environment and affects its transport and transformation. Fe(III) in acid mine wastewater is a widespread natural oxidant in the mine environment. However, the role of Fe(III) on the oxidative dissolution of Sb2S3 and Sb release is unknown. By simulating a dark anoxic and acidic mine groundwater environment, this study conducted Fe(III) concentration to Sb2S3 surface area ratio (I) controlled Sb2S3 oxidative dissolution kinetics experiments, and combined the dissolved state composition and solid phase characterization means of S-Sb-Fe redox products to reveal the mechanism of Fe(III) action on Sb release. The results show that the oxidative dissolution of Sb2S3 under the action of Fe(III) is an acid-producing process, and the larger the I value is, the more obvious the promotion effect of Fe(III) on Sb release. Under anoxic conditions, Fe(III) undergoes redox with Sb2S3, and the main products are Sb(V), S(0) and Fe(II). After the reaction, S(0) and Fe2O3 were detected on the mineral surface, which hindered the continuation of the oxidative dissolution reaction of Sb2S3. At a certain value of I, both the low concentration of Fe(III) and the increase of dissolved oxygen (DO) will reduce the attachment of S(0) on the mineral surface and promote the increase of Sb release; the Cl− in solution will promote the dissolution release of Sb2S3 through the coordination complexation effect. The interaction between Fe(III) and Sb2S3 under anoxic acidic conditions controls the release of Sb, which can provide an important theoretical basis for prevention and control of groundwater Sb contamination after mine pit closure.

Image defogging is an essential technology used in traffic safety monitoring, military surveillance, satellite and remote sensing image processing, medical image diagnostics, and other applications. Current methods often rely on various priors, with the dark-channel prior being the most frequently employed. However, halo and bright-field color distortion issues persist. To further improve image quality, an adaptive image-defogging algorithm based on bright-field region detection is proposed in this paper. Modifying the dark-channel image improves the abrupt changes in gray value in the traditional dark-channel image. By setting the first and second lower limits of transmittance and introducing an adaptive correction factor to adjust the transmittance of the bright-field region, the limitations of the dark-channel prior in extensive ranges and high-brightness areas can be significantly alleviated. In addition, a guide filter is utilized to enhance the initial transmittance image, preserving the details of the defogged image. The results of the experiment demonstrate that the algorithm presented in this paper effectively addresses the mentioned issues and has shown outstanding performance in both objective evaluation and subjective visual effects.

For river crossing bridges, the vehicle-induced vibration can be transmitted to the bridge tower and foundation system. This vibration induced low frequency underwater noise radiation can cause great harm to aquatic organisms. A river crossing suspension bridge was selected to study the sound contribution and spatial distribution of the underwater noise. A bridge-sediment coupling finite element model was developed, and the vehicle-bridge-sediment interaction analysis was conducted to investigate the dynamic response of the coupling system. An acoustic finite element model was built to predict the underwater noise radiated from the tower and sediment, and the noise contribution of these two sound sources was compared. The research shows that the noise radiated from the bridge tower and the sediment is below 6.3 Hz, and the peak frequency is around 3.15 Hz. The noise radiated from bridge tower only has a larger contribution to the total noise level in its vicinity than the sediment, especially around the water surface. In other space, the noise generated through the sediment vibration plays a dominant role in the total noise. The radiated noise from the tower has lateral directivity, and the directivity of the sediment radiation is similar to the point sound source.

ObjectiveTo assess the effect of B cell depletion therapy (BCDT) on circulating T follicular helper (cTfh) and circulating T helper 17 (cTh17) cells and its relation to clinical improvement in patients with myasthenia gravis (MG).Methods28 anti-AchR positive MG patients treated with ofatumumab and 28 healthy controls (HCs) were included. Frequencies of cTfh and cTh17 cells were monitored by flow cytometry at baseline and 4, and 12 weeks after the initial dose ofatumumab. Serum cytokines associated with cTfh and cTh17, including IL-6, IL-21, and IL-17, were also analyzed.ResultsThe frequency of cTfh and cTh17 significantly increased in MG patients compared with HCs. Additionally, elevated levels of both T-cell subsets correlated with MG severity. During the follow-up, cTfh and cTh17 return to normal after BCDT. Furthermore, the decrease in cTfh and cTh17 was associated with MG scores improvement over time. Notably, cTfh- and cTh17-related cytokines, including IL-6, IL-21, and IL-17, exhibited a marked decrease following ofatumumab therapy.ConclusionsAbnormal expansion of cTfh and cTh17 cells may be key features in the immunopathology of MG. Their levels returned to normal after BCDT, which was closely correlated with clinical amelioration. This result suggests that these two T-cell subsets may be targets for BCDT treatment of MG.

Abstract The central nervous system (CNS) is considered as one of the most frequently affected organs in antiphospholipid syndrome (APS). This study investigated the prevalence of CNS manifestations in APS and associated risk factors and evaluated stroke recurrence. We carried out this retrospective study from 2009 to 2021 at Peking University People’s Hospital, which enrolled 342 APS patients, and 174 neurologic events were suffered by 119 patients (34.8%). Patients with and without CNS involvement were compared regarding demographics and laboratory parameters. The analysis showed that older age, livedo reticularis, and dyslipidaemia were significant related factors for CNS manifestations (P = 0.047, 0.038, and 0.030 respectively). The use of anticoagulants (P = 0.004), and/or hydroxychloroquine (P = 0.016) appeared to associated with a lower incidence of CNS manifestations. During a median follow-up of 4.1 years, 10 individuals developed new episodes of stroke in APS patients with previous ischemic strokes. Livedo reticularis, smoking and male gender may predict the risk of recurrent stroke (P = 0.020, 0.006, and 0.026 respectively). Collectively, our results indicated the protective and risk factors for CNS manifestations, as well as demonstrated that APS patients appeared at high risk of stroke recurrence despite current therapy.

Surface-wave tomography is an important and widely used method for imaging the crust and upper mantle velocity structure of the Earth. In this study, we proposed a deep learning (DL) method based on convolutional neural network (CNN), named SfNet, to derive the vS model from the Rayleigh wave phase and group velocity dispersion curves. Training a network model usually requires large amount of training datasets, which is labor-intensive and expensive to acquire. Here we relied on synthetics generated automatically from various spline-based vS models instead of directly using the existing vS models of an area to build the training dataset, which enhances the generalization of the DL method. In addition, we used a random sampling strategy of the dispersion periods in the training dataset, which alleviates the problem that the real data used must be sampled strictly according to the periods of training dataset. Tests using synthetic data demonstrate that the proposed method is much faster, and the results for the vS model are more accurate and robust than those of conventional methods. We applied our method to a dataset for the Chinese mainland and obtained a new reference velocity model of the Chinese continent (ChinaVs-DL1.0), which has smaller dispersion misfits than those from the traditional method. The high accuracy and efficiency of our DL approach makes it an important method for vS model inversions from large amounts of surface-wave dispersion data.

Two large earthquakes (an earthquake doublet) occurred in south-central Turkey on February 6, 2023, causing massive damages and casualties. The magnitudes and the relative sizes of the two mainshocks are essential information for scientific research and public awareness. There are obvious discrepancies among the results that have been reported so far, which may be revised and updated later. Here we applied a novel and reliable long-period coda moment magnitude method to the two large earthquakes. The moment magnitudes (with one standard error) are 7.95±0.013 and 7.86±0.012, respectively, which are larger than all the previous reports. The first mainshock, which matches the largest recorded earthquakes in the Turkish history, is slightly larger than the second one by 0.11±0.035 in magnitude or by 0.04 to 0.18 at 95% confidence level.

BackgroundHepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide and has a poor prognosis. Thus, there is a need for an effective biomarker to improve and predict the prognosis of HCC.MethodsRNA sequencing data, simple nucleotide variation data, and clinical data of HCC patients from The Cancer Genome Atlas (TCGA) to identify mutant genes, simple nucleotide variation data, and clinical data of HCC patients from the International Cancer Genome Consortium (ICGC) to validate the prognostic value of mutant genes were the data sources of the present study. To identify the overall survival (OS)-related mutant genes, a Kaplan–Meier (KM) analysis was conducted. We carried out univariate Cox and multivariate Cox regression analyses to identify the independent prognostic factors. We also conducted a correlation analysis of immune cells and mutant genes. To explore the molecular mechanisms of mutant genes, we conducted a gene set enrichment analysis (GSEA). A nomogram was constructed to help predict the prognosis of HCC. In addition, we explored the expression profile of mutant genes in HCC based on a TCGA dataset, an ICGC dataset, and our own HCC tissue samples.ResultsWe identified and validated a mutant gene, dynein axonemal heavy chain 5 (DNAH5), which was negatively related to the OS of HCC patients. Univariate Cox and multivariate Cox regression analyses revealed that the mutant gene DNAH5 could act as an independent prognostic factor for HCC. Most pathways of the mutant gene DNAH5 were involved in cancer development and progression based on GSEA analysis. The mutant gene DNAH5 was negatively correlated with monocytes, naive CD4 T cells, activated dendritic cells, and activated mast cells. In addition, the mRNA and protein levels of DNAH5 had a significantly higher level of expression in the tissue samples of patients with HCC. A nomogram consisting of the pathological stage, DNAH5, and tumor mutation burden (TMB) performed well.ConclusionThe mutant gene DNAH5 had a significantly higher level of expression in the tissue samples of patients with HCC, could act as an independent prognostic factor for HCC, and is a potential new immunotherapy target for HCC.

The margin of the Tibetan Plateau of Southwest China is one of the most seismically active regions of China and is the location of the China Seismic Experimental Site (CSES). Many studies have developed seismic velocity models of Southwest China, but few have compared and evaluated these models which is important for further model improvement. Thus, we compared six published seismic shear-wave velocity models of Southwest China on absolute velocity and velocity perturbation patterns. The models are derived from different types of data (e.g., surface waves from ambient noise and earthquakes, body-wave travel times, receiver functions) and inversion methods. We interpolated the models into a uniform horizontal grid (0.5° × 0.5°) and vertically sampled them at 5, 10, 20, 30, 40, and 60 km depths. We found significant differences between the six models. Then, we selected three of them that showed greater consistency for further comparison. Our further comparisons revealed systematic biases between models in absolute velocity that may be related to different data types. The perturbation pattern of the model is especially divergent in the shallow part, but more consistent in the deep part. We conducted synthetic and inversion tests to explore possible causes and our results imply that systematic differences between the data, differences in methods, and other factors may directly affect the model. Therefore, the Southwest China velocity model still has considerable room for improvement, and the impact of inconsistency between different data types on the model needs further research. Finally, we proposed a new reference shear-wave velocity model of Southwest China (SwCM-S1.0) based on the three selected models with high consistency. We believe that this model is a better representation of more robust features of the models that are based on different data sets.

Abstract The nature of the inner core (IC) temporal changes is of great importance in understanding the deep earth dynamics. The comment by Tian and Wen (2023, https://doi.org/10.1029/2023gl103173) on our previous paper (Yang & Song, 2022, https://doi.org/10.1029/2022gl098393) provided a new observation as evidence against the IC rotation and proposed that our observations are instead from localized rapid changes at the IC surface. Here we argue the opposite to its conclusions. The comment misinterpreted our logic and many of our observations and arguments. Its one new waveform does not contradict with the “rotation” model. The original evidence for the “surface” model is demonstrated to be an artifact from station clock errors and instrument changes. Additionally, the surface model lacks a solid physical and quantitative basis to explain existing seismic evidence. We conclude that the rotation model is currently the best interpretation and the surface model is not a viable alternative.

IntroductionMelanoma is a common and aggressive type of skin cancer with rising incidence rate globally. Gender is one of the determining factors, and overall males have a higher risk of developing melanoma as well as worse prognosis. Emerging evidence show that GPR68, a G protein-coupled receptor that is sensitive to acid and mechanical stimulations for cellular microenvironment, plays an important role in tumor biology. However, whether GPR68 is involved in gender-dependent regulation of tumor growth is unclear.MethodsWe established a syngeneic melanoma model in Gpr68-deficient mice and investigated tumor growth in males and females. The GPR68 activation-induced cellular responses of melanocytes, including intracellular calcium dynamics, proliferation and migration were measured. The landscape of tumor-infiltrating immune cells were analyzed by flow cytometry and the expression various cytokines were checked by qRT-PCR.ResultsGPR68 is required for melanoma growth in males but dispensable in females. GPR68 is expressed and functional in B16-F10 melanocytes, but the activity of the receptor does not directly contribute to proliferation and migration of the cells. GPR68 inhibits infiltration of CD45+ lymphocytes, CD8+ T cells and NK cells in melanoma in male mice, but has no apparent effect in females. Furthermore, GPR68 functionally inhibits the expression of IFNγ in the tumor infiltrating CD8+ T cells and NK cells as well as the inflammatory cytokine expression in the spleen in male mice but not in females. Our results show the gender-dependent modulatory effect of GPR68 on tumor-infiltrating immune cells and their tumor-killing capacity.DiscussionGPR68 is sensor for acid and mechanical stimulations, which are two important factors in the microenvironment associated with tumor growth and metastasis. Our results suggest a prominent role of the receptor molecules in tumor biology in a gender-dependent manner. Since GPCRs are more feasible to develop small molecule drugs compared to transcription factors, our study demonstrates the potential of GPR68 as a novel druggable therapeutic target for melanoma in male patients.

Stroke is considered one of the most common and life-threatening manifestations of antiphospholipid syndrome (APS), which leads to high mortality and permanent disability. This study investigated the prevalence and the potential risk factors of stroke in APS. We enrolled 361 APS patients retrospectively from 2009 to 2022 at Peking University People’s Hospital. Stroke was found in 25.8% (93/361) of the participants. The multivariate logistic regression showed that hypertension, diabetes, livedo reticularis, and other central nervous system involvements were significant related factors for stroke. The use of hydroxychloroquine appeared to relate to a lower incidence of stroke. During a median follow-up of 3.0 years, 11.8% (11/93) of the individuals with a previous stroke developed stroke recurrence, and thrombocytopenia seemed to be a predictor of stroke recurrence.

BackgroundStroke-associated infection (SAI) is a common complication after a stroke. The incidence of infection was higher in people with sarcopenia than in the general population. However, the relationship between pre-stroke sarcopenia risk and SAI in older patients has not been confirmed. This study aimed to investigate the association between pre-stroke sarcopenia risk and SAI in older patients with acute ischemic stroke (AIS).MethodsThis retrospective study was conducted by the Peking University People’s Hospital. We evaluated the pre-stroke sarcopenia risk by applying the SARC-F questionnaire. Multivariate logistic regression was applied to explore the association between pre-stroke sarcopenia risk and SAI.ResultsA total of 1,002 elder patients with AIS (592 men; 72.9 ± 8.6 years) were enrolled in our study. Pre-stroke sarcopenia risk was found in 29.1% of the cohort. The proportion of patients with pre-stroke sarcopenia risk was larger in the SAI group than in the non-SAI group (43.2 vs. 25.3%, p

Anthropogenic activities have dramatically changed land uses over the last century, which has considerably increased soil disturbance. Despite considerable attention paid to the effects of land use on soil erosion, it remains controversial as to how much land use and climate contribute to erosion. In this study, we conducted a comprehensive meta-analysis of 1,380 measurements from published studies using the 137Cs method to examine the responses of erosion to land uses and climatic variables across terrestrial ecosystems in China. Our results showed that land use had significant impacts on the rate of erosion, with the lowest rates on natural and bamboo forests and the highest rates on farmland. Land use change of forest and grassland to farmland significantly increased erosion. Erosion rates respond significantly but differently to climatic variables in varying land use types. Correlations of erosion rates with mean annual temperature and precipitation were negative in forest ecosystems, positive in farmland, and nonsignificant in grassland. Variance partition analysis showed that land use types explained more of the variation in erosion rates than did environmental variables at a broad geographic scale, such as climate. This study highlights the importance of land use in affecting erosion rate. Incorporating these evidences into global erosion models may improve the simulation of long-term soil dynamics.

Fine particulate matter (PM2.5) has been widely reported to contribute to the pathogenesis of pulmonary diseases. The direct hazardous effect of PM2.5 on the respiratory system at high concentrations in vitro and in vivo have been well identified. However, its effect on the pre-existing respiratory diseases of patients at environment-related concentrations remains unclear. Diesel exhaust PM2.5 as a primary representative of ambient PM2.5 fine particles were used to investigated the effect of PM2.5 on the fibrosis progression of existing pulmonary fibrosis disease models. This study reported that PM2.5 could result in the enhanced sensitivity to fibrotic response, which may be ascribed to ferroptosis induced by PM2.5 in damaged lung areas. Proteomic analysis revealed that the upregulation of HO-1 as a key mechanism in the ferroptosis and exacerbation of pulmonary fibrosis induced by PM2.5. As a result, HO-1 degraded heme-containing protein and released iron in fibrotic cells, leading to generation of mitochondrial ROS and impaired mitochondrial function. Transmission electron microscopic assay verified that PM2.5 entered the mitochondria of fibrotic cells and was accompanied by significant mitochondrial morphological changes characterized by increased mitochondrial membrane density and reduced mitochondrial size. The HO-1 inhibitor zinc protoporphyrin and mitochondrion-targeted antioxidant Mito-TEMPO significantly attenuated PM2.5-induced ferroptosis and exacerbation of fibrosis. In addition, AMPK-ULK1 axis-triggered autophagy activation and NCOA4-mediated degradation of ferritin by autophagy were found to be related to the PM2.5-induced ferroptosis of fibrotic cells. As evidenced by the inhibition of autophagy with 3-methyladenine or AMPK inhibitor, NCOA4 knockdown decreased intracellular iron accumulation and lipid peroxidation, thereby relieving PM2.5-induced epithelial–mesenchymal transition and cell death in fibrotic cells. Overall, this study provided experimental support for the idea that PM2.5 greatly deteriorates fibrosis process in pre-existing pulmonary fibrosis, and HO-1-mediated mitochondrial dysfunction and NCOA4-mediated ferritinophagy are jointly required for the PM2.5-induced ferroptosis and enhanced fibrosis effects.

Marine buoys need to operate in high sea areas far from land for a long time. Therefore, how to provide a long-term power supply for the buoy system is critical to be addressed. Photovoltaic (PV) power supply systems are the most commonly used power supply method for marine buoys. Due to the limitations of the buoy structure and considering the rotation of the buoy in the ocean, most of the PV modules are placed in a four-sided enclosure. The output performance of the PV power supply system in this placement is affected by the tilt angle produced by waves. However, there are few relevant studies on the actual power generation performance of PV power supply systems for marine buoys, and there is a lack of methods for power generation performance analysis. In order to meet the power requirements of the marine buoy, a large design margin must be left. It increases the cost of marine buoys. In this paper, second-order Stokes waves are used to simulate waves of different levels by varying the wave height and frequency. The motion characteristics of the marine buoy are analyzed using ANSYS-AQWA under calm-rippled, smooth, slight, and moderate conditions. Combined with the tilted surface irradiance calculation model to get the variation law of solar radiation of PV modules under dynamic conditions, the effect of different tilt angle PV modules on the output of PV system under dynamic conditions was also studied. The experiments show that for every 5° increase in the tilt angle of the PV modules the output power of the system decreases by 3% on average. As the tilt angle of the PV modules increases, the impact on the system output performance is more pronounced. The output power decreased by 69.5% when the PV modules were tilted at an angle of 90°, and the PV system electrical parameters were similarly affected. By comparing the influence of different tilt angles on the power supply performance of PV modules, we optimize the design of the PV power supply system of the buoy. This enables the designers to maximize the use of limited area and space while reducing the cost and extending the power supply time and service life of the buoy.

In order to capture true-color information of distant targets under extremely low light, a large-format low-light imaging system is designed based on an RGB filter wheel. By decomposing the system indicators, this study proposes a method for acquiring low-light true-color images using a large-aperture, low-distortion optical lens combined with an RGB filter wheel capable of multi-line sequential exposure. The optical field segmentation is achieved using a four-panel optical reflective prism, and the images from four high-sensitivity SCOMS detectors are stitched together to form a composite image. The working principle of the system is explained, and the low-light imaging capability is thoroughly evaluated. The dimensions and rotation speed of the filter wheel are then calculated in detail, ensuring accurate synchronization of the filter wheel’s speed and exposure time. The calculation method for the parameters of the four-panel reflective prism structure is investigated, mathematical expressions for the geometric parameters of the prism assembly are provided, and a prism assembly suitable for four-way spectral separation is designed. Based on the research and design results, a large-swath-width, low-light true-color imaging system is developed that is suitable for an environmental illuminance of 0.01 lux. The system achieves a ground pixel resolution of 0.5 m (at an altitude of 5 km) and an effective image resolution of 4 K × 4 K, and is capable of accurately reproducing target color information. Laboratory and field flight tests verified that the large-swath-width images obtained by the imaging system are clear, with high contrast and resolution. After image fusion and spectral registration, the color images exhibit full saturation and high fidelity, meeting the requirements of low-light true-color imaging under airborne conditions. The design methodology of this low-light imaging system can serve as a reference for the development of airborne low-light imaging equipment.

BackgroundThe relationship between skeletal muscle mass index (SMI) and cirrhosis incidence in patients with non-cirrhotic acute-on-chronic (ACLF) has not been clarified. This study aimed to assess the predictive value of SMI on the incidence of long-term cirrhosis in male non-cirrhotic ACLF patients.Materials and methodsMale ACLF patients who were free of liver cirrhosis were retrospectively included in this study. Univariate and multivariate logistic analyses were conducted to determine the risk factors for the long-term (1-year) development of cirrhosis. The receiver operating characteristic curves (ROC) were used to assess the ability of SMI levels to predict the incidence of cirrhosis. Restricted triple spline (RCS) described the dose-response relationship between SMI and the risk of cirrhosis. Subgroup analysis was stratified by age (≤ 40 years and > 40 years).ResultsA total of 230 subjects were included in this study, of whom 45.2% (104/230) were diagnosed with cirrhosis within 360 days. Patients who progressed to cirrhosis had a lower SMI [46.1 ± 6.9 versus 49.2 ± 6.5 cm2/m2, P = 0.001] and a higher proportion of sarcopenia (19.2% versus 6.3%, P = 0.003). In multivariate logistic regression, SMI remained a protective agent against 360-days progression to cirrhosis in males with ACLF after adjustment (OR 0.950, 95% CI: 0.908–0.994, P < 0.05). SMI exerted a non-linear dose-dependent effect on the risk of cirrhosis. The area under the ROC curve (AUC) for the L3-SMI to predict the incidence of cirrhosis in male non-cirrhotic ACLF patients was 0.636 (P < 0.001). We observed significant differences in SMI among male ACLF patients in different age groups. Further subgroup analysis by age revealed that lower SMI was associated with the 1-year incidence of cirrhosis in male ACLF patients aged less than 40 years (OR 0.908, 95% CI: 0.842–0.979, P < 0.05), whereas SMI did not affect the 1-year risk of cirrhosis in older subjects (age > 40 years).ConclusionA higher SMI represents an independent protective factor for developing long-term cirrhosis in male ACLF patients who do not experience cirrhosis, especially in those under 40 years of age.

Idiopathic pulmonary fibrosis (IPF) is a chronic and lethal lung disease with limited treatment options. The onset of IPF increases with age, indicating that aging is a major risk factor for IPF. Among the hallmarks of aging, cellular senescence is the primordial driver and primary etiological factor for tissue and organ aging, and an independent risk factor for the progression of IPF. In this review, we focus on the senescence of alveolar type II epithelial cells (AECIIs) and systematically summarize abnormal changes in signal pathways and biological process and implications of senescent AECIIs during IPF progression. Meanwhile, we objectively analyze current medications targeting the elimination of senescent cells or restoration of vitality such as senolytics, senomorphics, autophagy regulators, and stem cell therapy. Finally, we dialectically discuss the feasibility and limitation of targeting senescent AECIIs for IPF treatment. We hope that the understanding will provide new insights to the development of senescent AECII-based approaches for the prevention and mitigation of IPF.

BackgroundStroke-associated pneumonia (SAP) commonly complicates acute ischemic stroke (AIS) and significantly worsens outcomes. Type 2 diabetes mellitus (T2DM) may contribute to malnutrition, impair innate immunity function, and increase the probability of SAP occurrence in AIS patients. We aimed to determine early predictors of SAP in AIS patients with T2DM and to construct a nomogram specifically for predicting SAP in this population by combining the A2DS2 score with available nutrition-related parameters.MethodsA total of 1,330 consecutive AIS patients with T2DM were retrospectively recruited. The patients were randomly allocated to the training (n = 887) and validation groups (n = 443). Univariate and multivariate binary logistic regression analyses were applied to determine the predictors of SAP in the training group. A nomogram was established according to the identified predictors. The areas under the receiver operating characteristic curve (AUROC) and calibration plots were performed to access the predictive values of the nomogram. The decision curve was applied to evaluate the net benefits of the nomogram.ResultsThe incidence of SAP was 9% and 9.7% in the training and validation groups, respectively. The results revealed that the A2DS2 score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP. A novel nomogram, A2DS2-Nutrition, was constructed based on these five predictors. The AUROC for A2DS2-Nutrition (0.820, 95% CI: 0.794–0.845) was higher than the A2DS2 score (0.691, 95% CI: 0.660–0.722) in the training group. Similarly, it showed a better predictive performance than the A2DS2 score [AUROC = 0.864 (95% CI: 0.828–0.894) vs. AUROC = 0.763 (95% CI: 0.720–0.801)] in the validation group. These results were well calibrated in the two groups. Moreover, the decision curve revealed that the A2DS2-Nutrition provided an additional net benefit to the AIS patients with T2DM compared to the A2DS2 score in both groups.ConclusionThe A2DS2 score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP in AIS patients with T2DM. Thus, the proposed A2DS2-Nutrition may be a simple and reliable prediction model for SAP occurrence in AIS patients with T2DM.

Pulmonary fibrosis is an irreversible fibrotic process that has a high mortality rate and limited treatment options; thus, developing a novel therapeutic drug is critical. In this study, we synthesized danshensu methyl ester (DME) and explored its anti-pulmonary fibrotic ability on TGF-β1-stimulated lung fibroblast in vitro and on bleomycin-induced pulmonary fibrosis in vivo. Results showed that DME decreased the expression of differentiation-related proteins, including fibroblast activation protein 1 (FAP1) and S100 calcium-binding protein A4 (S100A4), and fibrotic markers, such as a-SMA, vimentin, and collagen in vivo and in vitro. In addition, DME markedly repressed myofibroblast proliferation and migration. Mechanistically, chromatin immunoprecipitation–PCR, RNA immunoprecipitation, half-life, and other experiments revealed that DME inhibited activating transcription factor 3 expression via TGF-β1 signal transduction leading to a decrease in lncIAPF transcription and stability. Moreover, DME blocked human antigen R (HuR) nucleocytoplasmic translocation and promoted its degradation via downregulating lncIAPF, which markedly decreased the expression of HuR target genes such as negative autophagic regulators (EZH2, STAT1, and FOXK1). Collectively, our results demonstrated that DME enhanced autophagy to attenuate pulmonary fibrosis via downregulating the lncIAPF–HuR-mediated autophagic axis and the lncIAPF–HuR complex can be the target for drug action.

Abstract The central midcontinent of the USA's cratonic platform is a region of low elevation and relief underlain by tectonic basins, domes, faults, and monoclines. To investigate potential correlations among shallow crustal structure and crustal thickness, we produced a high‐resolution Moho‐depth map of the region by applying the recently developed H‐κ‐c receiver‐function method to data from EarthScope Transportable‐Array and Flexible‐Array stations. Results indicate that Moho depth varies from 38 to 57 km. Changes of Moho depth and of Vp/Vs ratios do not correlate with Precambrian tectonic boundaries, suggesting that they reflect post‐accretion tectonics. Deeper Moho underlies sedimentary basins, implying a relationship between crustal thickness and lithospheric subsidence. Thicker crust may be due to rift‐related underplating, and thinner crust may have undergone delamination. Some depth changes underlie known faults and fold zones. Since short‐wavelength undulations were detected only under high‐density seismic arrays, they may occur more widely but have yet to be resolved.

Kidney renal clear cell carcinoma (KIRC) is a heterogeneous malignant tumor with high incidence, metastasis, and mortality. The imbalance of copper homeostasis can produce cytotoxicity and cause cell damage. At the same time, copper can also induce tumor cell death and inhibit tumor transformation. The latest research found that this copper-induced cell death is different from the known cell death pathway, so it is defined as cuproptosis. We included 539 KIRC samples and 72 normal tissues from the Cancer Genome Atlas (TCGA) in our study. After identifying long non-coding RNAs (lncRNAs) significantly associated with cuproptosis, we clustered 526 KIRC samples based on the prognostic lncRNAs and obtained two different patterns (Cuproptosis.C1 and C2). C1 indicated an obviously worse prognostic outcome and possessed a higher immune score and immune cell infiltration level. Moreover, a prognosis signature (CRGscore) was constructed to effectively and accurately evaluate the overall survival (OS) of KIRC patients. There were significant differences in tumor immune microenvironment (TIME) and tumor mutation burden (TMB) between CRGscore-defined groups. CRGscore also has the potential to predict medicine efficacy.

PurposeThis study aimed to determine the prognostic impact of the neutrophil-to-lymphocyte ratio (NLR) in critically ill trauma patients.MethodsThis retrospective study involved adult trauma patients from 335 intensive care units (ICUs) at 208 hospitals stored in the eICU database. The primary outcome was ICU mortality. The lengths of ICU and hospital stay were calculated as the secondary outcomes. The multivariable logistic regression model was used to identify independent predictors of mortality. To identify the effect of the NLR on survival, a 15-day survival curve was used.ResultsA total of 3,865 eligible subjects were enrolled in the study. Univariate analysis showed that patients in the group with a higher NLR were more likely to receive aggressive methods of care delivery: mechanical ventilation, vasopressor, and antibiotics ( P 7.44 was an independent risk factor for ICU death in patients with TBI (OR: 1.837, 95% CI: 1.045–3.229) and TBI victims whose NLR > 7.44 had a 15-day survival disadvantage (P = 0.005).ConclusionA high NLR is associated with a poor prognosis in trauma patients, even worse in patients with TBI. An NLR > 7.44 is an independent risk factor for death in patients with TBI.

BackgroundCisplatin-based neoadjuvant chemotherapy combined with radical cystectomy (RC) plus pelvic lymph node dissection (PLND) is the preferred treatment option for muscle-invasive bladder cancer (MIBC). However, some patients are unable to tolerate RC or may have postoperative complications after RC. And most patients have a strong desire for bladder-preserving treatment. There are no reports on the efficacy of maximal transurethral resection of the bladder tumor (TURBT) in combination with chemotherapy plus tislelizumab for bladder-preserving in recurrent MIBC patients.Case presentationWe report two cases diagnosed with recurrent MIBC who achieved pathological complete response (pCR) and bladder-preserving after maximal TURBT combined with chemotherapy plus tislelizumab.ConclusionPostoperative immunotherapy should be considered for all patients with recurrent MIBC who are eligible for immunotherapy. In addition, high programmed death ligand-1 (PD-L1) expression, high tumor mutation burden (TMB), and TP53 mutation level can be combined to predict tislelizumab efficacy.

BackgroundIschemic stroke (IS) is the most common and life-threatening arterial manifestation of antiphospholipid syndrome (APS). It is related to high mortality and severe permanent disability in survivors. Thus, it is essential to identify patients with APS at high risk of IS and adopt individual-level preventive measures. This study was conducted to identify risk factors for IS in patients with APS and to develop a nomogram specifically for IS prediction in these patients by combining the adjusted Global Anti-Phospholipid Syndrome Score (aGAPSS) with additional clinical and laboratory data.MethodsA total of 478 consecutive patients with APS were enrolled retrospectively. All patients were randomly assigned to the training and validation cohorts. Univariate and multivariate binary logistic analyses were conducted to identify predictors of IS in the training cohort. Then, a nomogram was developed based on these predictors. The predictive performance of the nomogram for the training and validation cohorts was evaluated by determining areas under the receiver operating characteristic curve (AUROC) and creating calibration plots. A decision curve analysis (DCA) was conducted to compare the potential net benefits of the nomogram with those of the aGAPSS.ResultsDuring a mean follow-up period of 2.7 years, 26.9% (129/478) of the patients were diagnosed with IS. Binary logistic regression analysis revealed that five risk factors were independent clinical predictors of IS: age (P < 0.001), diabetes (P = 0.030), hyperuricemia (P < 0.001), the platelet count (P = 0.001), and the aGAPSS (P = 0.001). These predictors were incorporated into the nomogram, named the aGAPSS-IS. The nomogram showed satisfactory performance in the training [AUROC = 0.853 (95% CI, 0.802–0.896] and validation [AUROC = 0.793 (95% CI, 0.737–0.843)] cohorts. Calibration curves showed good concordance between observed and nomogram-predicted probability in the training and validation cohorts. The DCA confirmed that the aGAPSS-IS provided more net benefits than the aGAPSS in both cohorts.ConclusionAge, diabetes, hyperuricemia, the platelet count, and the aGAPSS were risk factors for IS in patients with APS. The aGAPSS-IS may be a good tool for IS risk stratification for patients with APS based on routinely available data.

Anomaly detection of remote sensing images has gained significant attention in remote sensing image processing due to their rich spectral information. The Local RX (LRX) algorithm, derived from the Reed–Xiaoli (RX) algorithm, is a hyperspectral anomaly detection method that focuses on identifying anomalous pixels in hyperspectral images by exploiting local statistics and background modeling. However, it is still susceptible to the noises in the Hyperspectral Images (HSIs), which limits its detection performance. To address this problem, a hyperspectral anomaly detection algorithm based on channel attention mechanism and LRX is proposed in this paper. The HSI is feed into the auto-encoder network that is constrained by the channel attention module to generate a more representative reconstructed image that better captures the characteristics of different land covers and has less noises. The channel attention module in the auto-encoder network aims to explore the effective spectral bands corresponding to different land covers. Subsequently, the LRX algorithm is utilized for anomaly detection on the reconstructed image obtained from the auto-encoder network with the channel attention mechanism, which avoids the influence of noises on the anomaly detection results and improves the anomaly detection performance. The experiments are conducted on three HSIs to verify the performance of the proposed method. The proposed hyperspectral anomaly detection method achieves higher Area Under Curve (AUC) values of 0.9871, 0.9916 and 0.9642 on HYDICE urban dataset, AVIRIS aircraft dataset and Salinas Valley dataset, respectively, compared with other six methods. The experimental results demonstrate that the proposed algorithm has better anomaly detection performance than LRX and other algorithms.

A new geological epoch—the Anthropocene—was voted by the 34-member Anthropocene Working Group (AWG) to mark the profound ways in which humans have altered our planet [...]

Prostate cancer (PCa) has a high incidence rate, mortality rate, and biochemical recurrence (BCR) rate. 7-Methylguanosine (m7G), as one of the RNA modifications, has been considered to be actively involved in cancer-related translation disorders in recent years. Therefore, we first used The Cancer Genome Atlas (TCGA) database to identify prognosis and m7G-related long non-coding RNAs (lncRNAs). Then we randomly divided the samples into the training set and test set and then constructed and verified the m7G lnRNA prognostic model (m7Gscore) by the least absolute shrinkage and selection operator (LASSO) regression analysis. The m7Gscore has been proved to be an independent marker of BCR-free survival in patients with PCa. Furthermore, the m7Gscore was significantly correlated with the tumor immune microenvironment (TIME) and somatic mutation of PCa patients and had the potential to be an indicator for the selection of drug treatment. We also clustered TCGA cohort into three m7G-related patterns (C1, C2, and C3). The Kaplan–Meier survival analysis revealed that C1 had the best BCR-free survival and C3 had the worst. The TIME was also significantly distinct among the three m7G-related patterns. According to the TIME characteristics of the patterns, we defined C1, C2, and C3 as immune-desert phenotype, immune-inflamed phenotype, and immune-excluded phenotype, respectively.

One of the most intriguing features of the Earth's inner core is its temporal variability over decadal time scale. Time-varying sesismic waves traversing the inner core, from high-quality repeating earthquakes, provide unequivocal evidence for the feature. However, the mechanism of the temporal change remains in debate. There have been two competing models, differential rotation of the inner core shifting its lateral heterogeneities and the rapid localized changes of the inner core boundary (ICB). Recent studies suggest that the time-varying seismic waves originate from the interior of the inner core, rather than the ICB. Consequently, the model of differential rotation provides so far the simplest and most reasonable explanation. Inner core is inferred to rotate at the rate of 0.05～0.1 degree per year, with the possibility of decadal fluctuation. The model can reconcile all the time-varying signals observed in previous studies. The investigations on the temporal change of the inner core and its mechanism shed lights on understanding the inner workings of our planet, especially the operation of the geodynamo.

The accurate mapping of soil organic carbon (SOC) distribution is important for carbon sequestration and land management strategies, contributing to mitigating climate change and ensuring agricultural productivity. The Heihe River Basin in China is an important region that has immense potential for SOC storage. Phenological variables are effective indicators of vegetation growth, and hence are closely related to SOC. However, few studies have incorporated phenological variables in SOC prediction, especially in alpine areas such as the Heihe River Basin. This study used random forest (RF) and extreme gradient boosting (XGBoost) to study the effects of phenological variables (e.g., Greenup, Dormancy, etc.) obtained from MODIS (i.e., Moderate Resolution Imaging Spectroradiometer) product (MCD12Q2) on SOC content prediction in the middle and upper reaches of Heihe River Basin. The current study also identified the dominating variables in SOC prediction and compared model performance using a cross validation procedure. The results indicate that: (1) when phenological variables were considered, the R2 (coefficient of determination) of RF and XGBoost were 0.68 and 0.56, respectively, and RF consistently outperforms XGBoost in various cross validation experiments; (2) the environmental variables MAT, MAP, DEM and NDVI play the most important roles in SOC prediction; (3) the phenological variables can account for 32–39% of the spatial variability of SOC in both the RF and XGBoost models, and hence were the most important factor among the five categories of predictive variables. This study proved that the introduction of phenological variables can significantly improve the performance of SOC prediction. They should be used as indispensable variables for accurately modeling SOC in related studies.

In the last 30 years, severe soil acidification has been found in China due to acid deposition and nitrogen fertilizer overuse. Understanding the spatial pattern and vertical variations in base saturation percentage (BSP) and exchangeable cations (Ca2+, Mg2+, K+, Na+, H+ and Al3+) can directly benefit fertilization management and ecological protection. Here, 1253 soil profiles were surveyed in tropical and subtropical regions in China to investigate the spatial variations in BSP and exchangeable cations at three soil depths of 0–20 cm, 20–50 cm and 50–100 cm. The spatial distributions were interpolated by using advanced machine learning techniques. We found that the exchangeable Ca2+ (Exch. Ca), Mg2+ (Exch. Mg) and BSP were significantly higher in paddy fields and uplands than in forests and gardens, regardless of soil depth, while the exchangeable K (Exch. K) did not significantly differ between various land-use types. The Exch. Ca and BSP in Anthrosols were significantly higher than those in Ferrosols, Argosols and Cambosols in the three soil layers. The spatial prediction results indicated that exchangeable cations and BSP were generally characterized by strong heterogeneity, and the Exch. Ca, Exch. K and exchangeable H+ (Exch. H) contents and BSP declined with increasing soil depth. This study helps us understand the spatial variation in BSP and exchangeable cations in the study area and benefits fertilization management and environmental protection.

Understanding the vertical structures of cloud condensation nuclei (CCN) and ice-nucleating particle (INP) number concentrations in desert source regions is crucial for examining dust-cloud interactions and other related impacts. To explore the vertical profiles of the CCN and INP number concentrations and their possible atmospheric–dynamic influence factors at the center of the Taklimakan Desert, intensive observations were conducted by employing a ground-based polarization Raman lidar, sounding balloons, and a sun photometer in Tazhong (83.39° E, 38.58° N, 1103 m above sea level) during the summer of 2019. Based on the GRASP algorithm, the extinction-to-volume conversion factor of dust aerosols was 0.85 × 10−12 Mmm3 m−3, and the extinction-to-number conversion factor was predicted to be 0.20 Mm cm−3 on the basis of the sun photometer observations. Thus, the vertical CCN and INP number concentration profiles obtained with different parameterization schemes in the presence of various pollution levels were calculated by combining dust extinction coefficients retrieved by lidar and meteorological data observed by sounding balloon observations. The achieved results indicated that the CCN number concentration varied from 10−2 to 102 cm−3 and decreased from ground level to 12 km with an average value of 36.57 cm−3 at the 10–12 km height range, while the INP number concentration based on parameterization schemes D10 and D15 mainly varied from 10−1 to 102 L−1 and from 1 L−1 to 103 L−1, with average values of 3.50 L−1 and 7.80 L−1, respectively. Moreover, we observed a strong relationship between the INP number concentration of scheme D10 and the wind speed, with an R2 value of 0.72, but a weak relationship between the CCN number concentration and the relative humidity in the boundary layer, with a Spearman’s rank correlation coefficient R2 value of 0.38. The present study provides original and valuable information regarding the CCN and INP number concentrations and their related influencing factors at the center of the Taklimakan Desert and can improve our understanding of the vertical distributions of dust–cloud–atmosphere dynamic interactions, as well as of the roles of dust aerosols in the desert hydrological cycle.

A reservoir with a thickness less than 0.5 m is generally considered to be a thin reservoir, in which it is difficult to directly identify oil-water layers with conventional logging data, and the identify result coincidence rate is low. Therefore, a support vector machine method (SVM) is introduced in the field of oil-water-dry layer identification. The basic approach is to map the nonlinear problem (input space) to a new high-dimensional feature space through the introduction of a kernel function, and then construct the optimal decision surface in the high-dimensional feature space and conduct sample classification. There are plenty of thin reservoirs in Wangguantun oilfield. Therefore, 63 samples are established by integrating general logging data and oil testing data from the study area, including 42 learning samples and 21 prediction samples, which are normalized. Then, the kernel function is selected, based on previous experience, and the fluid identification model of the thin reservoir is built. The model is used to identify 21 prediction samples; 18 are correct, and the prediction accuracy reaches 85.7%. The results show that the SVM method is feasible for fluid identification in thin reservoirs.

Background: Risk stratification plays an essential role in the decision making for sepsis management, as existing approaches can hardly satisfy the need to assess this heterogeneous population. We aimed to develop and validate a machine learning model to predict in-hospital mortality in critically ill patients with sepsis. Methods: Adult patients fulfilling the definition of Sepsis-3 were included at a large tertiary medical center. Relevant clinical features were extracted within the first 24 h in ICU, re-classified into different genres, and utilized for model development under three strategies: “Basic + Lab”, “Basic + Intervention”, and “Whole” feature sets. Extreme gradient boosting (XGBoost) was compared with logistic regression (LR) and established severity scores. Temporal validation was conducted using admissions from 2017 to 2019. Results: The final cohort included 24,272 patients, of which 4013 patients formed the test cohort for temporal validation. The trained and fine-tuned XGBoost model with the whole feature set showed the best discriminatory ability in the test cohort with AUROC as 0.85, significantly higher than the XGBoost “Basic + Lab” model (0.83), the LR “Whole” model (0.82), SOFA (0.63), SAPS-II (0.73), and LODS score (0.74). The performance in varying subgroups remained robust, and predictors, such as increased urine output and supplemental oxygen therapy, were crucially correlated with improved survival when interpretability was explored. Conclusions: We developed and validated a novel XGBoost-based model and demonstrated significantly improved performance to LR and other scores in predicting the mortality risks of sepsis patients in the hospital using features in the first 24 h.

Kidney renal clear cell carcinoma (KIRC) has high morbidity and gradually increased in recent years, and the rate of progression once relapsed is high. At present, owing to lack of effective prognosis predicted markers and post-recurrence drug selection guidelines, the prognosis of KIRC patients is greatly affected. Necroptosis is a regulated form of cell necrosis in a way that is independent of caspase. Induced necroptosis is considered an effective strategy in chemotherapy and targeted drugs, and it can also be used to improve the efficacy of immunotherapy. Herein, we quantified the necroptosis landscape of KIRC patients from The Cancer Genome Atlas (TCGA) database and divided them into two distinct necroptosis-related patterns (C1 and C2) through the non-negative matrix factorization (NMF) algorithm. Multi-analysis revealed the differences in clinicopathological characteristics and tumor immune microenvironment (TIME). Then, we constructed the NRG prognosis signature (NRGscore), which contained 10 NRGs (PLK1, APP, TNFRSF21, CXCL8, MYCN, TNFRSF1A, TRAF2, HSP90AA1, STUB1, and FLT3). We confirmed that NRGscore could be used as an independent prognostic marker for KIRC patients and performed excellent stability and accuracy. A nomogram model was also established to provide a more beneficial prognostic indicator for the clinic. We found that NRGscore was significantly correlated with clinicopathological characteristics, TIME, and tumor mutation burden (TMB) of KIRC patients. Moreover, NRGscore had effective guiding significance for immunotherapy, chemotherapy, and targeted drugs.

The morbidity of bladder cancer (BLCA) is high and has gradually elevated in recent years. BLCA is also characterized by high recurrence and high invasiveness. Due to the drug resistance and lack of effective prognostic indicators, the prognosis of patients with BLCA is greatly affected. Iron metabolism is considered to be a pivot of tumor occurrence, progression, and tumor microenvironment (TME) in tumors, but there is little research in BLCA. Herein, we used univariate COX regression analysis to screen 95 prognosis-related iron metabolism-related genes (IMRGs) according to transcription RNA sequencing and prognosis information of the Cancer Genome Atlas (TCGA) database. TCGA-BLCA cohort was clustered into four distinct iron metabolism patterns (C1, C2, C3, and C4) by the non-negative matrix factorization (NMF) algorithm. Survival analysis showed that C1 and C3 patterns had a better prognosis. Gene set variant analysis (GSVA) revealed that C2 and C4 patterns were mostly enriched in carcinogenic and immune activation pathways. ESTIMATE and single sample gene set enrichment analysis (ssGSEA) also confirmed the level of immune cell infiltration in C2 and C4 patterns was significantly elevated. Moreover, the immune checkpoint genes in C2 and C4 patterns were observably overexpressed. Studies on somatic mutations showed that the tumor mutation burden (TMB) of C1 and C4 patterns was the lowest. Chemotherapy response assessment revealed that C2 pattern was the most sensitive to chemotherapy, while C3 pattern was the most insensitive. Then we established the IMRG prognosis signature (IMRGscore) by the least absolute shrinkage and selection operator (LASSO), including 13 IMRGs (TCIRG1, CTSE, ATP6V0A1, CYP2C8, RNF19A, CYP4Z1, YPEL5, PLOD1, BMP6, CAST, SCD, IFNG, and ASIC3). We confirmed IMRGscore could be utilized as an independent prognostic indicator. Therefore, validation and quantification of iron metabolism landscapes will help us comprehend the formation of the BLCA immunosuppressive microenvironment, guide the selection of chemotherapeutic drugs and immunotherapy, and predict the prognosis of patients.