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Abstract Lung cancer is a malignant tumor with highly heterogeneous characteristics. A classic Chinese medicine, Pinellia ternata (PT), was shown to exert therapeutic effects on lung cancer cells. However, its chemical and pharmacological profiles are not yet understood. In the present study, we aimed to reveal the mechanism of PT in treating lung cancer cells through metabolomics and network pharmacology. Metabolomic analysis of two strains of lung cancer cells treated with Pinellia ternata extracts (PTE) was used to identify differentially abundant metabolites, and the metabolic pathways associated with the DEGs were identified by MetaboAnalyst. Then, network pharmacology was applied to identify potential targets against PTE-induced lung cancer cells. The integrated network of metabolomics and network pharmacology was constructed based on Cytoscape. PTE obviously inhibited the proliferation, migration and invasion of A549 and NCI-H460 cells. The results of the cellular metabolomics analysis showed that 30 metabolites were differentially expressed in the lung cancer cells of the experimental and control groups. Through pathway enrichment analysis, 5 metabolites were found to be involved in purine metabolism, riboflavin metabolism and the pentose phosphate pathway, including D-ribose 5-phosphate, xanthosine, 5-amino-4-imidazolecarboxyamide, flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD). Combined with network pharmacology, 11 bioactive compounds were found in PT, and networks of bioactive compound–target gene–metabolic enzyme–metabolite interactions were constructed. In conclusion, this study revealed the complicated mechanisms of PT against lung cancer. Our work provides a novel paradigm for identifying the potential mechanisms underlying the pharmacological effects of natural compounds.

Abstract Intrahepatic cholestasis of pregnancy (ICP) can lead to many adverse pregnancy outcomes, and the influencing factors remain unclear at present. This study retrospectively analyzed clinical data from 1815 pregnant women with ICP and evaluated the relationship between ICP subtypes, gestational age at onset, and pregnancy outcomes. The results of this study show that during pregnancy, the levels of biochemical indicators (TBA, DBIL and ALT) in the serum of pregnant women initially diagnosed with subtypes of ICP were noted to constantly change, and the subtype of ICP and its severity also changed. The incidence of adverse pregnancy outcomes [meconium-stained amniotic fluid (MSAF), NICU transfer, Apgar score ≤ 7 at 1 min, and preterm birth] in patients with ICP1 (icteric type) was significantly higher than for patients with ICP2, ICP3 or ICP4. The preterm birth rate of early-onset ICP was higher than that of late-onset ICP in ICP1 and ICP3 subtypes. In conclusion, the outcome of pregnancy in women with ICP is closely related to the serum TBA level and ICP subtype, which should be recognized in the clinic.

Abstract Glioblastoma multiforme (GBM) is a highly aggressive brain tumor characterized by invasive behavior and a compromised immune response, presenting treatment challenges. Surgical debulking of GBM fails to address its highly infiltrative nature, leaving neoplastic satellites in an environment characterized by impaired immune surveillance, ultimately paving the way for tumor recurrence. Tracking and eradicating residual GBM cells by boosting antitumor immunity is critical for preventing postoperative relapse, but effective immunotherapeutic strategies remain elusive. Here, we report a cavity-injectable bacterium-hydrogel superstructure that targets GBM satellites around the cavity, triggers GBM pyroptosis, and initiates innate and adaptive immune responses, which prevent postoperative GBM relapse in male mice. The immunostimulatory Salmonella delivery vehicles (SDVs) engineered from attenuated Salmonella typhimurium (VNP20009) seek and attack GBM cells. Salmonella lysis-inducing nanocapsules (SLINs), designed to trigger autolysis, are tethered to the SDVs, eliciting antitumor immune response through the intracellular release of bacterial components. Furthermore, SDVs and SLINs administration via intracavitary injection of the ATP-responsive hydrogel can recruit phagocytes and promote antigen presentation, initiating an adaptive immune response. Therefore, our work offers a local bacteriotherapy for stimulating anti-GBM immunity, with potential applicability for patients facing malignancies at a high risk of recurrence.

BackgroundLong-term heat stress (HS) severely restricts the growth performance of beef cattle and causes various health problems. The gut microbiota plays a crucial role in HS-associated inflammation and immune stress involving lymphocyte function. This study investigated the effects of dietary tea polysaccharide (TPS), a natural acidic glycoprotein, on HS-induced anorexia, inflammation, and gut microbiota dysbiosis in Simmental beef cattle.MethodsThe cattle were divided into two groups, receiving either normal chow or normal chow plus TPS (8 g/kg, 0.8%). Transcriptome sequencing analysis was used to analysis the differential signaling pathway of liver tissue. 16S rDNA sequencing was performed to analysis gut microbiota of beef cattle. Serum metabolite components were detected by untargeted metabolomics analysis.ResultsHepatic transcriptomics analysis revealed that differentially expressed genes in TPS-fed cattle were primarily enriched in immune processes and lymphocyte activation. TPS administration significantly reduced the expression of the TLR4/NF-κB inflammatory signaling pathway, alleviating HS-induced hepatic inflammation. Gut microbiota analysis revealed that TPS improved intestinal homeostasis in HS-affected cattle by increasing bacterial diversity and increasing the relative abundances of Akkermansia and Alistipes while decreasing the Firmicutes-to-Bacteroidetes ratio and the abundance of Agathobacter. Liquid chromatography-tandem mass spectrometry (LC‒MS/MS) analysis indicated that TPS significantly increased the levels of long-chain fatty acids, including stearic acid, linolenic acid, arachidonic acid, and adrenic acid, in the serum of cattle.ConclusionThese findings suggest that long-term consumption of tea polysaccharides can ameliorate heat stress-induced hepatic inflammation and gut microbiota dysbiosis in beef cattle, suggesting a possible liver-gut axis mechanism to mitigate heat stress.

Recent studies show that cellular neighborhoods play an important role in evolving biological events such as cancer and diabetes. Therefore, it is critical to accurately and efficiently identify cellular neighborhoods from spatially-resolved single-cell transcriptomic data or single-cell resolution tissue imaging data. In this work, we develop CNTools, a computational toolbox for end-to-end cellular neighborhood analysis on annotated cell images, comprising both the identification and analysis steps. It includes state-of-the-art cellular neighborhood identification methods and post-identification smoothing techniques, with our newly proposed Cellular Neighbor Embedding (CNE) method and Naive Smoothing technique, as well as several established downstream analysis approaches. We applied CNTools on three real-world CODEX datasets and evaluated identification methods with smoothing techniques quantitatively and qualitatively. It shows that CNE with Naive Smoothing overall outperformed other methods and revealed more convincing biological insights. We also provided suggestions on how to choose proper identification methods and smoothing techniques according to input data.

Abstract Electrocatalytic nitrate reduction is a promising approach to remove harmful nitrate and produce ammonia in aqueous media. Here, we demonstrate how 3D printed polymer electrodes can be electroless plated with a bimetallic NiCu alloy film suitable for sustained nitrate‐to‐ammonia reduction. Characterization by powder X‐ray diffraction, X‐ray photoelectron spectroscopy, scanning/transmission electron microscopy and energy‐dispersive X‐ray spectroscopy indicate that the electrode has a two‐layer structure consisting of polymer/ coating layer of metal alloys. The composite electrode shows high‐performance in the nitrate‐to‐ammonia electroreduction, giving NH3 Faradaic efficiencies of up to 83 % and NH3 yield rates up to 860 μg/(h cm2) at −0.38 V vs. RHE. We show that the electrode can easily be integrated into a Zn‐nitrate battery, giving a power density of 3.8 mW cm−2 with continuous NH3 production. The system combines three productive outputs, that is removal of nitrate pollutants, synthesis of valuable ammonia and generation of “green” electricity.

To analyze the aerodynamic characteristics of helicopter biplane tailplane, computational models for helicopter biplane tailplane and monoplane tailplane were established via CFD. The aerodynamic characteristics of different configurations of tailplanes at low speed forward flight and high angle of attack was obtained. The aerodynamic characteristics and flow characteristics of biplane/monoplane tailplane were analyzed. The mechanism of biplane tailplane to improve the longitudinal static stability at low speed forward flight and high angle of attack was investigated. The results show that the biplane tailplane can improve the helicopter pitch moment surge at low speed forward flight by restraining the rotor/tailplane interference, comparing with the monplane tailplane, the pitch moment of the biplane tailplane was reduced by about 56.8% at an advance ratio of 0.05. The stall angle of attack and maximum pitch moment of the biplane tailplane were larger, which can enhance the helicopter longitudinal static stability at high angle of attack, comparing with the monplane tailplane, the pitch moment of the biplane tailplane increased by about 60.1% at an attack angle of 20°.

The numerical calculation model for the aero-acoustic analysis of a tilt rotor was established by combining the free wake method and the FW-H (Ffowcs Williams-Hawkings) equation. The numerical method was validated by using the tilt rotor′s aero-acoustic test results. The aero-acoustic characteristics of dual tilt rotors that take into account the force and moment trim of an aircraft in its typical transition path were calculated. The unsteady air load of a rotor blade and its noise data in different observational positions were acquired. The acoustic directivity and sound pressure level of the tilt rotor in its different tilt angles were analysed. The results show that: the acoustic directivity characteristics of an isolate tilt rotor and dual tilt rotors were quite different due to the superposition and offset during noise radiation; the sound pressure level first increases and then decreases along with the rotor′s tilt angle; the maximum sound pressure level occurs at the tilt angle of 30 degree; the acoustic directivity and sound pressure level in different tilt angles vary due to multiple factors such as the Mach number at the rotor tip, air load and rotor orientation.

Abstract Background Temperature control plays a pivotal role in patients with heat stroke (HS), but little work has been done sufficiently on the use of temperature control to reflect disease progression. Here, we defined and analyzed the concrete role of controlling time for core temperature to physiological level (CTTP), in order to explore a potential index to guide the treatment of HS. Method This is a retrospective cohort study. From three hospitals located in Sichuan province, China, we collected a total of 179 HS cases with clinical diagnosis and treatment records. We defined CTTP as the time interval of HS onset to stabilization of core temperature (rectal temperature) below 37.7°C and analyzed the correlation between CTTP and inpatient death of HS patients. Results Of all the cases, 64.80% were male and 53.07% were exertional heat stroke (EHS). The median (IQR) age was 59 (23.5–73) years old, and the median (IQR) onset temperature was 42 (40.4–42)°C. Multivariable analysis demonstrated significantly high inpatient death in the highest CTTP tertile (>18 h) (hazard ratio: 18.75; 99% confidence interval: 4.06–86.59; p = .0002). In addition, compared with patients in lowest CTTP tertile, patients in highest CTTP tertile were at significantly higher risk of organ damage: 3.48‐fold for respiratory failure (95% CI: 1.41–8.59, p = .0069); 3.18‐fold for shock (95% CI: 1.37–7.39, p = .0071); 4.09‐fold for rhabdomyolysis (95% CI: 1.73–9.64, p = .0013); 4.64‐fold for renal damage (95% CI: 2.12–10.14, p = .0001). Conclusion Long of CTTP predicts inpatient death of HS patients with a CTTP tertile >18 h associated with the highest rate of inpatient death.

Abstract The lattice reduction-aided algorithm has received broad attention from researchers since it operates as a maximum likelihood receiver with better system performance for multiple-input multiple-output orthogonal frequency division multiplexing systems and contains a full diversity. A novel iterative detection algorithm canceling parallel iterations that employ the lattice reduction-aided approach is proposed. Soft information is exchanged through the detector itself. Its iteration occurs inside the detector, which reduces much of the exchange cost between the multiple-input multiple-output orthogonal frequency division multiplexing detector and the turbo decoder. Since the parallel interference cancellation algorithm is constrained by the accuracy of the initial value of the detection, it is easy to form error propagation after several iterations. Due to the lattice reduction-aided algorithm, its performance is approximated with the maximum likelihood algorithm. Therefore, the lattice reduction-aided algorithm is introduced into the parallel interference cancellation algorithm to make its detection algorithm more accurate and overcome the effect of error propagation in the manuscript. Simulation results indicate that the proposed algorithm leads to an improvement of 0.8–2 dB when the bit error rate is set to 10–4 when compared to other algorithms.

Although particular attention has been paid to responses of hydrocarbon storage and percolation capacity to the devitrification concerning lacustrine tuffaceous shale reservoirs in recent years, there is still a lack of systematical and comparative investigation on differential patterns and potential triggering mechanisms concerning development of the pore-microfracture systems and characteristics of surface wettability between the fresh-water and saline lacustrine settings, which is of considerable importance in fully understanding of genesis and spatial distribution of dessert reservoir intervals of tuffaceous shale reservoirs, and to provide further conceptual basis for deciphering shale-oil movability of saline lacustrine fine-grained mixed sedimentary sequences. In this study, tuffaceous shales from both the Upper Triassic Yanchang Formation in the Ordos Basin and Middle Permian Jingjingzigou Formation in the Junggar Basin are targeted to unravel the differential behavior of tuff devitrification and potential impacts on reservoir wettability and pore connectivity concerning fresh-water and saline lacustrine settings, and we present new results here from integrated analyses and combined interpretation of FE-SEM, Image Pro Plus (IPP) software image processing, contact angle and spontaneous imbibition experiments. In view of comparative analysis from representative samples, the tuffaceous shales from saline lacustrine environments are characterized by well-developed intergranular-intercrystalline and dissolution pores, and inorganic microfractures, generally yield a higher plane porosity of representative pore-fracture spaces and spontaneous imbibition slopes, a relatively lower average of n-decane contact angles and corresponding wettability parameters. The saline lacustrine tuffaceous shales are thus suspected to have undergone more intense devitrification resulting in a higher amount of devitrification and associated dissolution pores, and a relatively better connectivity between isolated micropore systems with adjacent microfractures. This would significantly facilitate the interface wettability reversal and occurrence of movable hydrocarbon fluid in microscopic reservoir spaces. Finally, a comprehensive and conceptual model is established illustrating the effects of differential devitrification on reservoir-forming patterns concerning tuffaceous shales developed in the fresh-water and saline lacustrine settings, respectively. These findings are of great theoretical and practical significance to enrich theory of high-quality reservoir formation and shale-oil accumulation in saline lacustrine tuffaceous shale reservoirs, and lay the foundation for guiding efficient exploration of continental fine-grained mixed sedimentary sequences.

Background: Esophageal cancer (EC) is a prevalent malignancy with heterogeneous outcomes. This study explores the significance of anoikis-related long non-coding RNAs (lncRNAs) in EC, aiming to unravel their molecular roles and clinical implications. Methods: Transcriptome and clinical data were obtained from TCGA database for EC samples. We identified anoikis-related genes and lncRNAs by Pearson correlation analysis. The risk score model hinged on prognostic lncRNAs filtered from multiple steps. Risk scores were calculated using the derived formula, and categorized patients into low- and high-risk groups. Model robustness was assessed through Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) curve, with clinical utility achieved via a constructed nomogram. We also explored the interplay between the risk score and immune cell infiltration, and investigated drug sensitivity. Results: We identified 2365 anoikis-related lncRNAs through co-expression analysis, including 1415 significant lncRNAs differentially expressed between normal and tumor samples. A risk score model was constructed from ten prognostic lncRNAs. The risk score model effectively stratified patients based on the median score, and its predictive capacity was validated through KM survival, ROC curve analyses, and the external GSE53622 dataset. The nomogram provided a practical tool for individualized prognosis evaluation. We unveiled significant correlations between specific immune cell subsets and the risk score. Eosinophils and common lymphoid progenitors exhibited positive associations, while endothelial cells and myeloid dendritic cells showed negative correlations. Drug sensitivity analysis revealed potential sensitive drugs for EC treatment that aligned with the risk subgroups. Conclusion: This study established an anoikis-related lncRNAs risk score model that may predict the prognosis, immune infiltration, and drug sensitivity in EC, in hope of facilitating tailored patient management.

Abstract Metallofullerenes are an important type of metallic nanomaterial with promising applications in several medical fields. Thermal ablation, including radiofrequency ablation (RFA) and microwave ablation (MWA), is an important treatment strategy for advanced hepatocellular carcinoma (HCC). The thermal expansion of fullerenes makes them good adjuncts to thermal ablation treatment of HCC. In this study, we used an innovative method of emulsification and cross-linking to produce CS-C60-Fe3O4 (Chitosan-C60-Fe3O4) nanoparticles, which have the advantages of uniform particle size and high bioavailability, as a kind of novel nano-pharmaceutical. The CS-C60-Fe3O4 nanoparticles were prepared by the cross-linking reaction from chitosan–acetic acid solution, Fe3O4 nanoparticles by Fe2SO4·7H2O and FeCl3·6H2O, and C60. The average particle size of CS-C60-Fe3O4 was 194.3 nm. Because CS-C60-Fe3O4 is magnetic, it can achieve specific and tissue aggregation in HCC tumor tissues. Moreover, compared with normal soluble C60 (EL35-C60), CS-C60-Fe3O4 prolonged the retention time of C60 in the blood of mice. CS-C60-Fe3O4 alone is not cytotoxic to cultured cells or tumor tissues, but when combined with thermal ablation strategies (RFA and MWA), it significantly upregulates the antitumor effects of thermal ablation on HCC tissues, that is, it acts as a sensitiser to thermal ablation. In the presence of thermal ablation, CS-C60-Fe3O4 interfered with iron metabolism in HCC cells and induced ferroptosis of HCC cells in the tumor tissues. These results not only expand our understanding of metallofullerenes but also provide additional options for the treatment of advanced HCC.

Abstract Carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and alpha-fetoprotein (AFP) are widely used tumor markers for colorectal cancer (CRC), but their clinical significance is unknown when the levels of these tumor markers were within the normal range. This retrospective study included 2145 CRC patients. The entire cohort was randomly divided into training and validation datasets. The optimal cut-off values of tumor markers were calculated using X-tile software, and univariate and multivariate analyses were performed to assess its association with overall survival (OS). The nomogram model was constructed and validated. The entire cohort was randomly divided into a training dataset (1502 cases, 70%) and a validation dataset (643 cases,30%). Calculated from the training dataset, the optimal cut-off value was 2.9 ng/mL for CEA, 10.1 ng/mL for CA19-9, 13.4 U/mL for CA125, and 1.8 ng/mL for AFP, respectively. Multivariate analysis revealed that age, tumor location, T stage, N stage, preoperative CA19-9, and CA125 levels were independent prognostic predictors. Even within the normal range, CRC patients with relatively high levels of CA19-9 or CA125 worse OS compared to those with relatively low levels. Then, based on the independent prognostic predictors from multivariate analysis, two models with/without (model I/II) CA19-9 and CA125 were built, model I showed better prediction and reliability than model II. Within the normal range, relatively high levels of preoperative CA19-9 and CA125 were significantly associated with poor OS in CRC patients. The nomogram based on CA19-9 and CA125 levels showed improved predictive accuracy ability for CRC.

Abstract The role of mast cells (MCs) in colorectal cancer (CRC) remains unclear, and a comprehensive single-cell study on CRC MCs has not been conducted. This study used a multi-omics approach, integrating single-cell sequencing, spatial transcriptomics, and bulk tissue sequencing data to investigate the heterogeneity and impact of MCs in CRC. Five MC signature genes (TPSAB1, TPSB2, CPA3, HPGDS, and MS4A2) were identified, and their average expression was used as a marker of MCs. The MC density was found to be lower in CRC compared to normal tissue, but MCs in CRC demonstrated distinct activation features. Activated MCs were defined by high expression of receptors and MC mediators, while resting MCs had low expression. Most genes, including the five MC signature genes, were expressed at higher levels in activated MCs. The MC signature was linked to a better prognosis in both CRC and pan-cancer patient cohorts. Elevated KITLG expression was observed in fibroblasts and endothelial cells in CRC samples compared to normal tissue, and co-localization of MCs with these cell types was revealed by spatial transcriptome analysis. In conclusion, this study finds decreased MC density in CRC compared to normal tissue, but highlights a shift in MC phenotype from CMA1 high resting cells to activated TPSAB1 high, CPA3 high, and KIT high cells. The elevated KITLG expression in the tumor microenvironment’s fibroblasts and endothelial cells may activate MCs through the KITLG-KIT axis, potentially suppressing tumor progression.

The use of ferronickel slag powder (FNSP) as a cementitious additional material has been supported by numerous reports. FNSP concrete has the same shortcomings as ordinary concrete, including low hardness. In this study, in order to make FNSP concrete more durable, end-hooked type steel fibers were incorporated. To understand how various elements affect the mechanical properties of steel fibers, an experiment was carried out on the mechanical properties of steel FNSP concrete (SFNSPC). FNSP’s principal ingredients, with a particle size distribution ranging from 0.5 to 100 μm and a sheet-like powder shape, are CaO, SiO2, Al2O3, MgO, and others, according to tests conducted on the material’s microstructure and composition. Then, eighteen mix proportions were developed, comprising six distinct FNSP replacement rate types and three distinct steel fiber content types. Crucial metrics were evaluated and analyzed, including the relationship among the toughness, tensile strength, and compressive strength as well as slump, splitting tensile strength, compressive strength, and uniaxial compressive stress–strain curve of SFNSPC. The results showed that the slump of SFNSPC under different FNSP replacement rates decreased with increasing steel fiber volume. Steel fibers have a small but positive effect on SFNSPC’s compressive strength; nonetheless, as FNSP replacement rates increased, SFNSPC’s slump gradually decreased, though not by much. These results show that FNSP is a viable alternative cementitious material in terms of strength. Specifically, the splitting tensile strength of SFNSPC improves with an increase in steel fiber content, and the pace at which SFNSPC strength drops with an increase in the FNSP replacement rate. With varying mix proportions, the stress–strain curve trend of SFNSPC remains mostly constant, and steel fibers improve the compressive toughness of SFNSPC. After adding 0.5% and 1.0% steel fibers, the toughness index of concrete with different FNSP replacement rates increased by 8–30% and 12–43%, respectively.

Data aggregation plays a critical role in sensor networks for efficient data collection. However, the assumption of uniform initial energy levels among sensors in existing algorithms is unrealistic in practical production applications. This discrepancy in initial energy levels significantly impacts data aggregation in sensor networks. To address this issue, we propose Data Aggregation with Different Initial Energy (DADIE), a novel algorithm that aims to enhance energy-saving, privacy-preserving efficiency, and reduce node death rates in sensor networks with varying initial energy nodes. DADIE considers the transmission distance between nodes and their initial energy levels when forming the network topology, while also limiting the number of child nodes. Furthermore, DADIE reconstructs the aggregation tree before each round of data transmission. This allows nodes closer to the receiving end with higher initial energy to undertake more data aggregation and transmission tasks while limiting energy consumption. As a result, DADIE effectively reduces the node death rate and improves the efficiency of data transmission throughout the network. To enhance network security, DADIE establishes secure transmission channels between transmission nodes prior to data transmission, and it employs slice-and-mix technology within the network. Our experimental simulations demonstrate that the proposed DADIE algorithm effectively resolves the data aggregation challenges in sensor networks with varying initial energy nodes. It achieves 5–20% lower communication overhead and energy consumption, 10–20% higher security, and 10–30% lower node mortality than existing algorithms.

Tungsten (W) stands out as a highly promising plasma-facing materials (PFMs) for future nuclear fusion reactors due to its advantages of excellent high temperature strength, low tritium retention and high recrystallization temperature (RCT). Notably, the potassium-doped tungsten-rhenium (W-Re-K) alloy exhibits exceptional performance when compared to other potential W-based alloys. Nevertheless, even a small amount of Re addition can reduce the thermal conductivity of W, which falls short of the requirement for PFMs. In this study, W-Re-K alloys with Re addition from 0.1 wt% to 0.5 wt% and minor K doping (40 ∼ 50 ppm) were manufactured via powder metallurgy and thermo-mechanical processes. The results revealed that the presence of Re had a grain-refining effect, which became more obvious as its content increased. The incorporation of a small amount of Re (W-0.5 wt% Re-K) exhibited favorable characteristics. Featuring an average grain size of 20.25 µm, and displayed a room temperature thermal conductivity of 163 W/(m⋅K), and an elevated RCT of approximately 1588 °C.

This research aims to evaluate various traditional or deep machine learning algorithms for the prediction of groundwater level (GWL) using three key input variables specific to Izeh City in the Khuzestan province of Iran: groundwater extraction rate (E), rainfall rate (R), and river flow rate (P) (with 3 km distance). Various traditional and deep machine learning (DML) algorithms, including convolutional neural network (CNN), recurrent neural network (RNN), support vector machine (SVM), decision tree (DT), random forest (RF), and generative adversarial network (GAN), were evaluated. The convolutional neural network (CNN) algorithm demonstrated superior performance among all the algorithms evaluated in this study. The CNN model exhibited robustness against noise and variability, scalability for handling large datasets with multiple input variables, and parallelization capabilities for fast processing. Moreover, it autonomously learned and identified data patterns, resulting in fewer outlier predictions. The CNN model achieved the highest accuracy in GWL prediction, with an RMSE of 0.0558 and an R2 of 0.9948. It also showed no outlier data predictions, indicating its reliability. Spearman and Pearson correlation analyses revealed that P and E were the dataset’s most influential variables on GWL. This research has significant implications for water resource management in Izeh City and the Khuzestan province of Iran, aiding in conservation efforts and increasing local crop productivity. The approach can also be applied to predicting GWL in various global regions facing water scarcity due to population growth. Future researchers are encouraged to consider these factors for more accurate GWL predictions. Additionally, the CNN algorithm’s performance can be further enhanced by incorporating additional input variables.

Abstract Osteoarthritis is a prevalent age-related disease characterized by dysregulation of extracellular matrix metabolism, lipid metabolism, and upregulation of senescence-associated secretory phenotypes. Herein, we clarify that CircRREB1 is highly expressed in secondary generation chondrocytes and its deficiency can alleviate FASN related senescent phenotypes and osteoarthritis progression. CircRREB1 impedes proteasome-mediated degradation of FASN by inhibiting acetylation-mediated ubiquitination. Meanwhile, CircRREB1 induces RanBP2-mediated SUMOylation of FASN and enhances its protein stability. CircRREB1-FASN axis inhibits FGF18 and FGFR3 mediated PI3K-AKT signal transduction, then increased p21 expression. Intra-articular injection of adenovirus–CircRreb1 reverses the protective effects in CircRreb1 deficiency mice. Further therapeutic interventions could have beneficial effects in identifying CircRREB1 as a potential prognostic and therapeutic target for age-related OA.

In order to better understand the formation of thrust fault in coal measures and how it makes a difference on mining-induced disasters, a simulation system for the formation process of a new type of thrust fault in coal measures has been improved, which adopts hydraulic servo control to realize the double precise control of displacement and stress. During the coal seam mining test, only part of the transparent plate at the mining position behind the coal seam is removed to keep the internal structural stress from being released. The system is used to carry out the experimental research on the formation of thrust fault in coal measures and coal winning operation. The results indicate that the displacement of each rock stratum can be divided into three regions during the formation of thrust fault: displacement region, compression region and stability region. The maximum displacement of the measuring point is in the displacement region and the relative displacement in various measuring points is small, its extents increase with the decrease of the burial depth of rock stratum. The displacement of measuring points in the compression region gradually decreases from hanging wall to footwall, and the displacement and relative displacement in the stability region are both the smallest, and their extents decrease with the burial depth of the rock stratum. The displacement angle of hanging wall measuring point increases gradually as the measuring point approaches the fault plane, reaching a maximum of 87.5°. In the formation of thrust fault, the horizontal stress on the roof and floor increases and then decreases, and the horizontal stress on the hanging wall is greater than that at the foot wall. The vertical stress of the coal roof in the foot wall of the fault tends to increase, while the vertical stress of the coal seam roof in the hanging wall of the fault tends to present the change of increase−decrease – increase. When comparing and analyzing the in-situ stress measurements of 22 domestic thrust faults in coal measures, it suggests that the ratio of maximum horizontal principal stress to vertical principal stress is in the range of 1−4 in the tectonic zones of thrust fault. After the thrust fault is stabilized in the test, the k of the hanging wall and foot wall is stable between 2−3. After the formation of thrust fault in coal measures, in the footwall coal seam mining process, the vertical and horizontal stresses in the coal seam roof both tend to increase and then decrease. Under the superposition of tectonic stress and mining-induced stress, the rock stratum near the fault produces stress aggregation, and its peak stress is greater. The conditions mentioned above lead to more violent movement of the overlying strata after coal winning. The coal winning can be divided into the cyclic evolution stage of rock pressure and the dynamic disaster stage. In the cyclic evolution stage of rock pressure, the vertical stress of wall and working face increases significantly periodically, and the high stress area migrates to the footwall structure coal. In the dynamic disaster stage, the working face is already in high stress area, which is easy to cause coal mine dynamic disasters such as rock burst.

Abstract Background To develop an ultrasound scoring system for placenta accreta spectrum (PAS), evaluate its diagnostic value, and provide a practical approach to prenatal diagnosis of PAS. Methods A total of 532 pregnant women (n = 184 no PAS, n = 120 placenta accreta, n = 189 placenta increta, n = 39 placenta percreta) at high-risk for placenta accreta who delivered in the Third Affiliated Hospital of Zhengzhou University between January 2021 and December 2022 underwent prenatal ultrasound to evaluate placental invasion. An ultrasound scoring system that included placental and cervical morphology and history of cesarean section was created. Each feature was assigned a score of 0 ~ 2, according to severity. Thresholds for the total ultrasound score that discriminated between no PAS, placenta accreta, placenta increta, and placenta percreta were calculated. Results Univariate and multivariate regression analysis identified seven indicators of PAS that were included in the ultrasound scoring system, including placental location, placental thickness, presence/absence of the retroplacental space, thickness of the retroplacental myometrium, presence/absence of placental lacunae, retroplacental myometrial blood flow and history of cesarean section. Using the final ultrasound scoring system, no PAS is diagnosed at a total score

Abstract The secretory properties of cancer-associated fibroblasts (CAFs) play predominant roles in shaping a pro-metastatic tumor microenvironment. The present study demonstrated that SLIT2, an axon guidance protein, produced by CAFs and promoted gastric cancer (GC) metastasis in two gastric cancer cell lines (AGS and MKN45) by binding to roundabout guidance receptor 1 (ROBO1). Mass-spectrometry analysis revealed that ROBO1 could interact with NEK9, a serine/threonine kinase. And their mutual binding activities were further enhanced by SLIT2. Domain analysis revealed the kinase domain of NEK9 was critical in its interaction with the intracellular domain (ICD) of ROBO1, and it also directly phosphorylated tripartite motif containing 28 (TRIM28) and cortactin (CTTN) in AGS and MKN45 cells. TRIM28 function as a transcriptional elongation factor, which directly facilitate CTTN activation. In addition, Bioinformatics analysis and experimental validation identified transcriptional regulation of STAT3 and NF-κB p100 by TRIM28, and a synergetic transcription of CTTN by STAT3 and NF-κB p100 was also observed in AGS and MKN45. Therefore, CAF-derived SLIT2 increased the expression and phosphorylation levels of CTTN, which induced cytoskeletal reorganization and GC cells metastasis. A simultaneous increase in the expression levels of NEK9, TRIM28 and CTTN was found in metastatic GC lesions compared with paired non-cancerous tissues and primary cancer lesions via IHC and Multiplex IHC. The analysis of the data from a cohort of patients with GC revealed that increased levels of NEK9, TRIM28 and CTTN were associated with a decreased overall survival rate. On the whole, these findings revealed the connections of CAFs and cancer cells through SLIT2/ROBO1 and inflammatory signaling, and the key molecules involved in this process may serve as potential biomarkers and therapeutic targets for GC.

As an effective risk prevention and control tool for contaminated sites, Monitoring Natural Attenuation (MNA) has been applied worldwide. The core of this technology is to determine the ability and efficiency of pollutant attenuation, which are influenced by the nature of the pollutants themselves, as well as the typical geochemical and hydrogeological conditions and other inherent characteristics of the site. It is of greater practical importance to clarify the influence of the inherent properties of the site on the natural attenuation of pollutants for the rational application of the technology. The authors address the influence of typical site geochemical characteristics and hydrogeological characteristics on the natural attenuation process of pollutants in groundwater and its mechanism. The typical geochemical characteristics, such as the organic matter and mineral composition of sediments, control the adsorption and complexation behavior of pollutants, and participate in the electron transfer process to influence the biodegradation and chemical transformation of pollutants. Hydrogeological characteristics influence the ability of natural attenuation through the differences in permeability, adsorption and desorption capacity caused by the lithologic characteristics of sediments. Groundwater flow rate controls the convection and dispersion of pollutants and affects the dissolution and release of pollutants from sediment to groundwater as well as the kinetic process of biodegradation. In general, due to the complexity of organic matter, mineral and microbial components and the heterogeneity of hydrogeological conditions, the study of the influence of site intrinsic properties on the natural attenuation of pollutants needs to be further strengthened. In particular, we need to identify the spatial and temporal dynamics of pollutant attenuation through long-term site monitoring, and deepen the understanding of the mechanisms underlying the interaction between typical site geochemistry, hydrogeological conditions and pollutants.

Abstract Clinical evidence shows that the mechanical stimulation obtained from occlusion could enhance periodontal ligament (PDL) remodeling. Mechano‐growth factor (MGF) is a growth factor produced specifically following mechanical stimulus Here, we aim to investigate the mechanical enhancement potential and mechanism of the MGF in PDL regeneration. In vivo study found that MGF produced from the PDL under occlusion force could strongly enhance PDL remodeling. In vitro experiments and mathematical modeling further confirmed the mechanical enhancement effect of MGF for PDLSC differentiation toward fibroblasts. A mechanochemical coupling effect of MGF mediated the enhancement of mechanical effect, which was modulated by Fyn‐FAK kinases signaling and subsequent MAPK pathway. Finally, enhanced PDL regeneration under the mechanochemical coupling of MGF and occlusal force was verified in vivo. There exists an additive mechanical effect of MGF mediated by Fyn‐FAK crosstalk and subsequent ERK1/2 and p38 phosphorylation, which could be developed as an MGF‐centered adjuvant treatment to optimize PDL remodeling, especially for patients with weakened bite force or destroyed periodontium.

Beijing Plain is an important region for ecological planning and management. In the past decade, human activities have dramatically changed the spatial and landscape patterns of greenspaces in Beijing Plains. However, very few studies have assessed the main causative factors of these changes. Herein, we analyzed the spatial patterns of greenspaces in the Beijing Plains between 2015 and 2020 using multi-source remote sensing data, geographical information system, and the landscape pattern index. Additionally, we utilized gray correlation analysis to quantitatively analyze the main factors contributing to dynamic changes in the greenspace landscape patterns. We found that the greenspaces in Beijing showed a gradual increase annually from 2015 to 2020. Further, the conversion of greenspace types throughout the study period mainly included the interconversion of woodland and cropland, water, and impervious surfaces. The transfer out of woodlands has been decreasing annually while the transfer in has been increasing. Grassland and shrubs were almost entirely converted into woodlands and other land use types. The fragmentation of the overall greenspace reduced, aggregation increased, and landscape patches tended to be fully distributed, connected, simpler, concentrated, and regular. The advantages of woodland landscapes were gradually becoming more evident. Population urbanization, rapid economic growth, and policies were important factors affecting changes in greenspace landscape patterns. The study findings provide a scientific reference to adjust the greenspace structure, transform and upgrade the existing greenspaces, and ensure sustainable development of cities.

The Well Tashen 5 (TS5), drilled and completed at a vertical depth of 9017 m in the Tabei Uplift of the Tarim Basin, NW China, is the deepest well in Asia. It has been producing both oil and gas from the Sinian at a depth of 8780–8840 m, also the deepest in Asia in terms of oil discovery. In this paper, the geochemical characteristics of Sinian oil and gas from the well were investigated and compared with those of Cambrian oil and gas discovered in the same basin. The oil samples, with Pr/Ph ratio of 0.78 and a whole oil carbon isotopic value of −31.6‰, have geochemical characteristics similar to those of Ordovician oils from the No. 1 fault in the North Shuntuoguole area (also named Shunbei area) and the Middle Cambrian oil from wells Zhongshen 1 (ZS1) and Zhongshen 5 (ZS5) of Tazhong Uplift. The maturity of light hydrocarbons, diamondoids and aromatic fractions all suggest an approximate maturity of 1.5%–1.7% Ro for the samples. The (4-+3-) methyldiamantane concentration of the samples is 113.5 μg/g, indicating intense cracking with a cracking degree of about 80%, which is consistent with the high bottom hole temperature (179 °C). The Sinian gas samples are dry with a dryness coefficient of 0.97. The gas is a mixture of kerogen-cracking gas and oil-cracking gas and has Ro values ranging between 1.5% and 1.7%, and methane carbon isotopic values of −41.6‰. Based on the equivalent vitrinite reflectance (Reqv = 1.51%–1.61%) and the thermal evolution of source rocks from the Cambrian Yu'ertusi Formation of the same well, it is proposed that the Sinian oil and gas be mainly sourced from the Cambrian Yu'ertusi Formation during the Himalayan period but probably also be joined by hydrocarbon of higher maturity that migrated from other source rocks in deeper formations. The discovery of Sinian oil and gas from Well TS5 suggests that the ancient ultra-deep strata in the northern Tarim Basin have the potential for finding volatile oil or condensate reservoirs.

Target variant detection has been challenging for Synthetic Aperture Radar (SAR), and the performance of the target variant recognition needs to be further enhanced. SAR images are widely used in the field of target recognition and are important to support reconnaissance operations. This paper proposes a novel research approach to improve the efficiency of target recognition. First, the theory surrounding sparse representation and dictionary learning is presented. Secondly, a SAR image target recognition model is constructed according to the theory. Meanwhile, a dynamic joint sparse representation model is proposed based on multi-information and applied to SAR image target recognition when sparse representation is under consideration. Finally, experiments are set up to validate the proposed model. The results are presented as follows: 1. the recognition rate range of the sample SAR image target is 0.811–0.995 and 0.867–0.990, respectively, when the two cases, without registration processing and with registration processing, utilize the recognition method of dictionary learning and sparse representation. 2. with the increase in dictionary size, the average recognition rate of SAR images based on multi-information dynamic joint sparse representation also increases under the conditions of no logarithm transformation and median filtering and after logarithm transformation and median filtering are run. Then, the average recognition rate range is 0.63–0.9 and 0.65–0.96, respectively. Thus, the recognition rate is improved by 5%-10%. 3. the recognition approach based on the sparse representation of multi-information dynamic joint has distinct sparse degrees of SAR image recognition in the case of logarithmic transformation and median filtering when the sample image has been registered and not been registered. The relative average recognition rates were 0.950–0.970 and 0.955–0.977, respectively. The key contribution of the research is to offer a workable solution to the issues plaguing SAR target variant recognition and to improve the significant limitations in the state-of-the-art literature thoroughly.

Abstract Ferroptosis, a nonapoptotic form of programmed cell death characterized by significant iron-dependent peroxidation of phospholipids, is regulated by cellular metabolism, redox homeostasis, and various cancer-related signaling pathways. Recently, considerable progress has been made in demonstrating the critical role of lipid metabolism in regulating ferroptosis, indicating the potential of combinational strategies for treating cancer in the future. In this study, we explored the combinational effects of lipid metabolism compounds and ferroptosis inducers on renal cell carcinoma (RCC) cells. We found potent synergy of the fatty acid amide hydrolase (FAAH) inhibitor URB597 with ferroptosis inducer (1S, 3R)-RSL3 (RSL3) in inhibiting the growth and metastasis of RCC cells both in vitro and in vivo via induction of G1 cell cycle arrest and promotion of the production of lipid peroxides, malondialdehyde (MDA), 4-hydroxynonenal (4-HNE), and cytosolic reactive oxygen species (ROS). In addition, inhibition of FAAH increased the sensitivity of RCC cells to ferroptosis. Genome-wide RNA sequencing indicated that the combination of URB597 and RSL3 has more significant effects on regulation of the expression of genes related to cell proliferation, the cell cycle, cell migration and invasion, and ferroptosis than either single agent alone. Moreover, we found that combinational treatment modulated the sensitivity of RCC cells to ferroptosis via the phosphatidylinositol 3 kinase (PI3K)-AKT signaling pathway. These data demonstrate that dual targeting of FAAH and ferroptosis could be a promising strategy for treating RCC.

Abstract Background Gliomas are a group of primary intracranial tumors with high morbidity and mortality. The previous researches indicated a crucial role of CKS2 (cyclin‐dependent kinases regulatory subunit 2) in hepatocellular carcinoma and breast cancer; however, little is known about the molecular mechanism of CKS2 in the tumorigenesis and epithelial‐mesenchymal transition‐like (EMT) process in glioma. Methods Datasets for bioinformatics analysis were obtained from the GEO, TCGA and CGGA databases. qRT‐PCR, western blotting (WB), and immunohistochemistry (IHC) assays were used to investigate the expression patterns of CKS2 among glioma and brain tissues. Glioma cells were transfected with small interfering RNA/overexpression plasmid against CKS2, then clone formation assay, CCK‐8, wound healing, Transwell assay, and flow cytometry were performed to detect changes in cell viability, invasiveness, and the apoptosis rate. Markers of cell invasion, apoptosis, EMT and TGFβ/SMAD signaling were evaluated by WB and immunofluorescence (IF) assays. Results We found that CKS2 overexpression correlates with poor prognosis in human glioma and knockdown of CKS2 could inhibit cell proliferation, migration, invasion, and induced apoptosis in glioma cells. Besides, we also found that knockdown of CKS2 could reverse the EMT process via modulating EMT‐related molecules. Glioma cells with overexpression of CKS2 were constructed to confirmed the fact that CKS2 induced nucleocytoplasmic translocation of SMAD2/3 and activated TGFβ/SMAD pathway, then upregulated its downstream targets expression, while inhibition of TGFβ/SMAD (by TGFβ inhibitor LY2157299 or SMAD4 siRNA) could reverse the tumor‐promoting effects and malignant phenotype caused by CKS2 overexpression. Conclusions We identified CKS2 as a critical contributor to the gliomagenesis, which might provide a novel therapeutic target for inhibiting the spread and infiltration of glioma.

In the exploration of sustainable construction materials, the application of ferronickel slag (FNS) in creating pervious concrete has been investigated, considering its potential to meet the dual requirements of mechanical strength and fluid permeability. To elucidate the statistical properties and models for predicting the performance of FNS-composited pervious concrete with different sizes of aggregates and mixtures, a series of experiments, including 54 kinds of mixtures and three kinds of aggregate, were conducted. The focus was on measuring the compressive strength and the permeability coefficient. The results indicate that the compressive strength of pervious concrete decreases with the increase in aggregate size, while the permeability coefficient increases with the increase in aggregate size. Through normalization, the variability of these properties was quantitatively analyzed, revealing coefficients of variation for the concrete’s overall compressive strength and the permeability coefficient at 0.166, 0.132, and 0.150, respectively. Predictive models were developed using machine learning techniques, such as Linear Regression, Support Vector Machines, Regression Trees, and Gaussian Process Regression. These models demonstrated proficiency in forecasting the concrete’s compressive strength and permeability coefficient.

It is unknown whether Ferronickel slag (FNS)-ordinary Portland cement (OPC)-based pervious concrete (FOPC) is feasible. To this end, a feasibility study was conducted on FOPC. Firstly, a detailed microscopic examination of the FNS powder was conducted, encompassing analyses of its particle size distribution, SEM, EDS, and chemical composition. These analyses aimed to establish the suitability of a composite of FNS and OPC as a composite cementitious material. Subsequent experimentation focused on evaluating the compressive strength of the composite paste material with varying mixed proportions, revealing a slight reduction in strength as the FNS substitution rate increased. Furthermore, the study designed eighteen different mix proportions of FOPC to investigate the key physical properties, including porosity, density, compressive strength, and the coefficient of permeability. Findings indicated that increases in the cementitious material proportion correlate with enhanced concrete strength, where the ratio of cementitious to aggregate increased by 6.7% and 16.5%, and the strength of FOPC increased by 10–13% and 30–50%, respectively. Conversely, a rise in the FNS substitution rate led to a reduction in compressive strength across different mix ratios. Additionally, the ratio of paste material to aggregate was found to significantly influence the permeability coefficient. These comprehensive performance evaluations suggest that incorporating FNS into OPC for pervious concrete applications is a feasible approach, offering valuable insights for the promotion of waste reuse and the advancement of energy conservation and emissions reduction efforts.

Digital twin technology has evolved from a theoretical concept to practical application, facilitating seamless data exchange between virtual and physical domains. Although there has been progress, the infrastructure industry, which is recognized for its intricate nature and the need for timely action, is still in the first phases of digital twin advancement. A significant obstacle in this field is the absence of established definitions and modeling standards, which impede the precise depiction of infrastructure systems. To address these challenges, this paper proposes a high-precision digital twin modeling method tailored for pumping stations. The method focuses on two key scenarios: first, we construct an overall digital twin model that contains both physical entities and operational processes of pumping stations; second, we design a modeling process applicable to pumping stations by analyzing the deficiencies of the existing standard system. Additionally, we selected the East–West Water Transfer Project in China as a case study to demonstrate the high-precision digital twin model of a pumping station. This model will include essential components, such as the modeling of pumping stations, the operational processes of pumping stations, and the modeling of system operation analysis. Serving as the database for the digital twin, it can complete the automatic inspection of the pumping station, optimization of scheduling, prediction and regulation of energy and carbon emissions, and visualization of results for display and other applications. The model realized the benefits of 100% automatic inspection rate, reduction of eight corresponding operating personnel, and comprehensive cost saving of RMB 2.25 million. The objective of this research is to narrow the divide between theoretical concepts and real-world implementations by pushing the boundaries of digital twin modeling and offering valuable insights for its utilization in the infrastructure industry. It establishes the foundation for progress in the field of digital twin technology in the specific context of intricate infrastructure projects. This project aims to improve the practicality of digital twin technology in real-world situations, namely in the infrastructure industry.

Objective: The objective of this research is to construct a method to alleviate the problem of sample imbalance in classification, especially for arrhythmia classification. This approach can improve the performance of the model without using data enhancement.Methods: In this study, we have developed a new Multi-layer Perceptron (MLP) block and have used a Weight Capsule (WCapsule) network with MLP combined with sequence-to-sequence (Seq2Seq) network to classify arrhythmias. Our work is based on the MIT-BIH arrhythmia database, the original electrocardiogram (ECG) data is classified according to the criteria recommended by the American Association for Medical Instrumentation (AAMI). Also, our method’s performance is further evaluated.Results: The proposed model is evaluated using the inter-patient paradigm. Our proposed method shows an accuracy (ACC) of 99.88% under sample imbalance. For Class N, sensitivity (SEN) is 99.79%, positive predictive value (PPV) is 99.90%, and specificity (SPEC) is 99.19%. For Class S, SEN is 97.66%, PPV is 96.14%, and SPEC is 99.85%. For Class V, SEN is 99.97%, PPV is 99.07%, and SPEC is 99.94%. For Class F, SEN is 97.94%, PPV is 98.70%, and SPEC is 99.99%. When using only half of the training sample, our method shows that the SEN of Class N and V is 0.97% and 5.27% higher than the traditional machine learning algorithm.Conclusion: The proposed method combines MLP, weight capsule network with Seq2seq network, effectively addresses the problem of sample imbalance in arrhythmia classification, and produces good performance. Our method also shows promising potential in less samples.

High heat flux as 20 MW m−2 during stationary operation can be foreseen in future fusion devices, leading to recrystallization and thermal creep in tungsten targets. Both recrystallization and thermal creep impact would play significant roles in service. Strength loss would happen after tungsten has recrystallized. Meanwhile, continuous plastic deformation namely thermal creep occurs and is visible when temperature exceeds the recrystallization temperature (RCT). In this paper, thermo-mechanical analysis of four different analytical models has been performed: stress-relieved tungsten without recrystallization, tungsten with RCT as 1500℃, 1300℃ and 1150℃ separately using finite element method based on ITER-like tungsten divertor monoblock, since the RCT of new developed tungsten base materials and pure tungsten is normally in this range. Low-cycle fatigue lifetime and creep rupture lifetime of these models has been calculated and compared to identify the impact of recrystallization and thermal creep, respectively, under cyclic thermal loads. A linear rule fracture criterion is used to roughly estimate the creep-fatigue interaction impact. The results reveal that low-cycle fatigue lifetime would be decreased to a great extent if recrystallization happens, and the lifetime is shorter for model with lower RCT. Creep rupture life is fairly dependent on the heating duration, and it’s of much concern to estimate divertor tungsten allowable cycles when consider creep-fatigue interaction.

Giant landslides and dammed lakes occurred frequently during the prehistoric period; however, their mechanisms often remain an open issue because they are complex. This study used field investigations to observe four old landslides and three landslide dams in Daning County, Shanxi Province, China. Remote sensing images captured during different periods were used to compare the landforms of landslides, landslide dams, and their surrounding environments in detail. Subsequently, their shapes, scales, spatial distributions, and positional relationships were determined. The ages of 14C obtained from the paleolandslide dam lake (PDL) deposits were 3742 ± 95, 4115 ± 121, 6544 ± 91, 7814 ± 109 cal a BP. The 14C ages of the deposits under the sliding surfaces of the old landslides were 2748 ± 27, 4470 ± 54, and 8245 ± 79 cal a BP. Based on the actual physical geographical conditions and geomorphological characteristics of the region, combined with the above age data, that the following conclusions were made: (i) During the Holocene, from 2700 to 8200 years ago, heavy rainfall was the main reason for the occurrence of landslides and landslide dams in the region. (ii) Under the condition of heavy rainfall, the slopes with angles >60° in the Loess Plateau are prone to form landslide masses, and the size of the landslide is related to rainfall intensity. A landslide dam was easily formed when the sliding direction was perpendicular to the direction of the valley. It is difficult to form landslide dams when the sliding direction is almost consistent with the downward direction of the valley. (iii) The formation mechanism of old landslides shows that collapse or sliding may occur suddenly in loess geological masses under an external rainfall scenario. Moreover, the process of landslide dams is related to the geomorphic forms of the original valley.

Abstract Background Intrahepatic cholestasis of pregnancy is a pregnancy-specific liver disease. In this study, we sought to explore the distribution of lipopolysaccharide in the maternal body, and its effect on the fetal body in the intrahepatic cholestasis of pregnancy mice. It provides a new sight for the clinical treatment of women with intrahepatic cholestasis of pregnancy. Methods The serum levels of lipopolysaccharide and lipopolysaccharide binding protein in women with intrahepatic cholestasis of pregnancy were analyzed. To assess the association between lipopolysaccharide levels and adverse fetal outcomes, ursodeoxycholic acid, resveratrol, and phosphatidylinositol-3-kinase inhibitor were employed in intrahepatic cholestasis of pregnancy mice, and we studied the fluorescence intensity and distribution of lipopolysaccharide in mice with intrahepatic cholestasis of pregnancy. Results Our data indicated significantly elevated levels of lipopolysaccharide and lipopolysaccharide binding protein in women with intrahepatic cholestasis of pregnancy. In vivo fluorescence imaging revealed that the intensity of lipopolysaccharide in mice with intrahepatic cholestasis of pregnancy was higher than that in the control group, and decreased after ursodeoxycholic and resveratrol treatment. The fluorescence intensity analysis indicated that lipopolysaccharide levels in maternal liver, placenta, fetal brain and fetal liver were significantly higher in the intrahepatic cholestasis pregnancy mice group than in the control group. Conclusions This study provided evidence of endotoxin distribution in maternal liver, placenta, fetal liver and fetal brain in mice with intrahepatic cholestasis of pregnancy. Ursodeoxycholic acid and resveratrol treatment effectively reduced lipopolysaccharide levels in pregnant mice with intrahepatic cholestasis of pregnancy.

CRY2 mediates photoperiod-responsive floral initiation in Arabidopsis. Here the authors show that CRY2 also regulates temperature sensitive flowering and that CRY2 can interact with and regulate the splicing factor CIS1 to affect alternative splicing of transcripts that regulate flowering.

Multiple Input Multiple Output (MIMO) detection algorithm is used to compensate the Mode Dependent Loss (MDL) in Mode Division Multiplexing (MDM) optical fiber channel. The problem of MIMO detection algorithm is that the computational complexity is too high and the performance is degraded with a large number of modes. This paper proposes to apply Massive-MIMO detection algorithms to the fiber channel, The algorithms include Minimum Mean Square Error (MMSE) , Conjugate Gradient (CG) , Gauss Seidel (GS) , and Alternating Direction Method of multipliers based Infinity-Norm (ADMIN) , and Optimized Coordinate Descent based BOX constraint (OCDBOX) . The result shows that the OCDBOX has the best Bit Error Rate (BER) performance in MDL-impaired MDM optical fiber communication system while higher complexity. The ADMIN has the second best BER performance and lower computational complexity. Therefore, the ADMIN detection algorithm can represent a good candidate in the MDM system with MDL.

Objective Conventional localization technique of V point for full‐endoscopic posterior cervical foraminotomy and discectomy (FPCD) required repeated fluoroscopies, especially in patients with short and thick necks. To address this issue, the present study aimed to introduce a new localization technique of V point, and further evaluate its efficacy. Methods A K‐wire was inserted and fixed at the pedicle eye under A/P fluoroscopy, then a working channel was established quickly along with it. Thirty‐four patients who underwent minimally invasive FPCD assisted by the new technique were included in this study. The clinical and radiological data were collected and analyzed, including radiation dose, operative time, positioning time, visual analog scale (VAS) for neck and arm pain, neck disability index (NDI) scores, Cobb angle of operative level and range of motion of the cervical spine. Results All operations were performed successfully, and no iatrogenic nerve or vascular injury occurred. None of the patients needed to be transferred to open surgery or revision surgery. The mean radiation dose was found to be1.68 ± 0.36 mSv. The mean positioning time observed was 10.68 ± 5.42 min and the average operation time was 81.18 ± 10.87 min. The operation time significantly declined as the number of patients increased. A significant difference in operation time between the first (96.22 ± 10.36 min) and last quartile (75.00 ± 3.84 min) of cases was observed (t = 4.82, P

Mesenchymal stem cells (MSCs) are becoming more popular in therapy. Therefore, in-depth studies on mesenchymal stem cells in therapy are urgently needed. However, the difficulty in culturing and propagating MSCs in vitro complicates potential studies on MSCs in a murine model. OP9 cells are a stromal cell line from mouse bone marrow, which have similar characteristics and functions to MSCs and can maintain their original characteristics. Because of these properties, OP9 cells have become a suitable substitute for research on MSCs. Previously, we have found that MSCs can cure inflammatory bowel disease in mice. In this study, we aimed to investigate whether OP9 cells can functionally regulate and alleviate inflammatory diseases. We evaluated the therapeutic effect of OP9 cells in the mouse model of inflammatory bowel disease and found OP9 cells were able to ameliorate inflammatory bowel disease. We explored the existence of NLRP3 inflammasome in OP9 cells, and showed better therapeutic effects when the NLRP3 inflammasome was suppressed. Thus, OP9 cell line is similar to MSCs in characteristic and function, and is an ideal substitute for MSCs research. The preliminary exploration of the inflammasome system in OP9 cells lays a theoretical and methodological foundation for further study of MSCs.

The potential release capacity of arsenic (As) from sediment was evaluated under a high level of exogenous organic matter (EOM) with both bioreactive and chemically reactive organic matters (OMs). The OMs were characterized by FI, HIX, BIX, and SUVA254 fluorescence indices showing the biological activities were kept at a high level during the experimental period. At the genus level, Fe/Mn/As-reducing bacteria (Geobacter, Pseudomonas, Bacillus, and Clostridium) and bacteria (Paenibacillus, Acidovorax, Delftia, and Sphingomonas) that can participate in metabolic transformation using EOM were identified. The reducing condition occurs which promoted As, Fe, and Mn releases at very high concentrations of OM. However, As release increased during the first 15–20 days, followed by a decline contributed by secondary iron precipitation. The degree of As release may be limited by the reactivity of Fe (hydro)oxides. The EOM infiltration enhances As and Mn releases in aqueous conditions causing the risk of groundwater pollution, which could occur in specific sites such as landfills, petrochemical sites, and managed aquifer recharge projects.

Abstract Sodium iron hexacyanoferrate (FeHCF) is one of the most promising cathode materials for sodium‐ion batteries (SIBs) due to its low cost theoretical capacity. However, the low electrochemical activity of FeLS(C) in FeHCF drags down its practical capacity and potential plateau. Herein, FeHCF with high FeLS(C) electrochemical activity (C‐FeHCF) is synthesized via a facile citric acid‐assisted solvothermal method. As the cathode of SIBs, C‐FeHCF shows superior cycling stability (ca. 87.3% capacity retention for 1000 cycles at 10 C) and outstanding rate performance (ca. 68.5% capacity retention at 50 C). Importantly, the contribution of FeLS(C) to the whole capacity was quantitatively analyzed via combining dQ/dV and discharge curve for the first time, and the index reaches 44.53% for C‐FeHCF, close to the theoretical value. In‐situ X‐ray diffraction proves the structure stability of C‐FeHCF during charge–discharge process, ensuring its superior cycling performance. Furthermore, the application feasibility of the C‐FeHCF cathode in quasi‐solid SIBs is also evaluated. The quasi‐solid SIBs with the C‐FeHCF cathode exhibit excellent electrochemical performance, delivering an initial discharge capacity of 106.5 mAh g−1 at 5 C and high capacity retention of 89.8% over 1200 cycles. This work opens new insights into the design and development of advanced cathode materials for SIBs and the beyond.

Surface damage and microscopic defect evolution of tungsten (W) armor under transient heat loads are key factors for fuel retention in fusion reactors. In this work, experiments were conducted to investigate the effects of cyclic thermal shocks on deuterium (D) retention and surface blistering in W. Thermal shock experiments were conducted on recrystallized W using an electron beam with a power density of 0.15 GW m ^−2 across 100–1500 cycles, followed by D plasma exposure with high-fluence (∼1 × 10 ^26 D m ^−2 ). The results demonstrate that samples subjected to 500 and 1500 cycles exhibit a significant presence of sub-grains within 90 μ m. Notably, the inhibition of blistering induced by thermal shock leads to a substantial reduction in D retention (5.45 × 10 ^19 D m ^−2 ) at lower cycle numbers (100 cycles) compared to the reference sample (2.35 × 10 ^20 D m ^−2 ) which was only exposed to D plasma. When cycle numbers increase to 500 and 1500, D retention reaches 1.98 × 10 ^20 D m ^−2 and 4.56 × 10 ^20 D m ^−2 , respectively. Based on the tritium migration analysis program, we propose that total D retention is a consequence of the competition between defects reduced by thermal shock-induced suppression of blistering and defects generated by plastic deformation induced by thermal stress. D retention initially decreases with the increase in cycle numbers, followed by a subsequent rise, with the inflection point slightly higher than 500 cycles. Additionally, due to the extensive scope of thermal stress, an escalated exposure period will result in substantial D captured by heat-induced defects, consequently intensifying the D retention. Whether there exists an upper limit to D retention induced by the increasing thermal shock cycles necessitates further experimental analysis. Nonetheless, it is evident that thermal shock significantly contributes to D retention within a profoundly deep bulk region under high cycles.

With further urbanization, household consumption firmly plays a key role in China’s national carbon emissions. However, current research concerning carbon issues has mainly focused on urban household consumption, and few studies have paid attention to herder households, leading to a research gap in the field of low-carbon shifting related to nomadic economies. In this study, we interviewed more than one-thousand herder households in the Sanjiangyuan region of the Qinghai–Tibet Plateau in China. The household carbon emissions and their influencing factors were investigated across the herder households of 15 counties. Our findings revealed the following: (1) There exist differences in the amounts of household carbon emissions and their compositions in the Sanjiangyuan region. From the perspective of spatial distribution, the emission hotspots are mainly concentrated in the eastern part of the Sanjiangyuan region. (2) At the prefecture level, average personal emissions were larger in the Hainan Prefecture (3.26 t ce/year), while they were approximately 1.36 times that of the Huangnan Prefecture (2.4 t ce/year), though with smaller personal emissions. The indirect carbon emissions of the four prefectures all occupied larger percentages of household carbon emissions that were mainly contributed by food consumption and housing. (3) Family type was the main diver influencing personal carbon emissions in the Huangnan Prefecture, Guoluo Prefecture, and Yushu Prefecture. The more people living in the household, the lower the per capita carbon emissions. However, the effect size of potential carbon reductions was weakened when the number of family members rose to over three. (4) We propose that grazing prohibitions and low-carbon dietary shifts would contribute to low-carbon herder livelihoods, especially for small-sized households that should be peer-to-peer targeted by regional government propaganda, which may help to strengthen the implementation of in-depth low-carbon promotions across the Sanjiangyuan region and even the overall Qinghai–Tibet Plateau.

Length-biased failure time data occur often in various biomedical fields, including clinical trials, epidemiological cohort studies and genome-wide association studies, and their analyses have been attracting a surge of interest. In practical applications, because one may collect a large number of candidate covariates for the failure event of interest, variable selection becomes a useful tool to identify the important risk factors and enhance the estimation accuracy. In this paper, we consider Cox’s proportional hazards model and develop a penalized variable selection technique with various popular penalty functions for length-biased data, in which the failure event of interest suffers from interval censoring. Specifically, a computationally stable and reliable penalized expectation-maximization algorithm via two-stage data augmentation is developed to overcome the challenge in maximizing the intractable penalized likelihood. We establish the oracle property of the proposed method and present some simulation results, suggesting that the proposed method outperforms the traditional variable selection method based on the conditional likelihood. The proposed method is then applied to a set of real data arising from the Prostate, Lung, Colorectal and Ovarian cancer screening trial. The analysis results show that African Americans and having immediate family members with prostate cancer significantly increase the risk of developing prostate cancer, while having diabetes exhibited a significantly lower risk of developing prostate cancer.

Given the complexity and the difficulty of controlling contributors effectively, road passenger transport often results in serious injuries and fatalities. The purpose of this study is to identify the main contributors to coach and bus accidents and to provide policy recommendations for making improvements in accident prevention. The Driving Reliability and Error Analysis Method 3.0 (DREAM 3.0) was modified and used to analyze the contributing factors (i.e. phenotypes and genotypes in DREAM) and their casual mechanisms. By having statistical analysis and social network analysis (SNA) adopted, the main genotypes and phenotypes of the DREAM charts were identified. The results of the study showed that A2.1 (too high speed) was the key phenotype and the main genotypic process chain leading to the phenotype was “inadequate safety management → inadequate training → inadequate skills/knowledge → misjudgment of the situation → too high speed” on all types of road. For A2.1 (too high speed), C2 (misjudgment of the situation) was the dominant genotype, while N5 (inadequate safety management) was the root cause of most genotypes. This suggests that road passenger transport companies, as the responsible parties, often fail to implement or violate safety prevention and control systems. Government regulators should promote the policy system and incentivize them to fulfil their safety management responsibilities. The government should also educate the public and improve the road environment to reduce passenger-related risks and the impact of environmental factors on drivers.

A developed tungsten (W) grade was prepared by powder metallurgy technology plus multi-step low-temperature rolling. The relative density, thermal conductivity, microstructure, tensile properties of original and high-temperature annealed states, micro-hardness and transient thermal shock resistance were characterized. The results of tensile test with a strain rate of 2 × 10-4 s−1 show that the ductile–brittle transition temperature (DBTT) of rolled-W in the original and recrystallized state are 150–200 °C and 250–300 °C, respectively. The rolled-W presents high strength and great plasticity simultaneously. For example, the maximum ultimate tensile strength (UTS) below DBTT is as high as ∼ 1189 MPa, and the maximum total elongation (TE) above DBTT reaches 28.9 %. In particular, the TE of recrystallized W achieves an incredible 81.4 % at 500 °C, which is the highest value among all the published literatures so far. The results of transient thermal shock tests indicate that the rolled-W has an outstanding transient thermal shock resistance. It can withstand the thermal bombardment at an absorbed power densities (APD) of 0.33 GW·m−2 without causing any surface damages, and still no cracks are observed as the APD rises to 0.88 GW·m−2. Moreover, the failure mechanism of rolled-W was also studied in details. This work plays an important role in establishing a dependable China Fusion Engineering Test Reactor (CFETR) data-library on a unitary W grade, which can provide an effective reference for the identification of material performance under the high heat flux and subsequent numerical simulation.

Wubao County is located in the northeastern part of the loess plateau in northern Shaanxi, geological disasters are developing in the area, which seriously threatens the life and property safety of local residents. On the basis of fully analyzing the geological disaster survey data in Wubao County, the evaluation indicators such as slope, slope aspect, and surface curvature were selected for the whole county scale, and the risk assessment was carried out based on the 25 m×25 m grid unit based on the information model based on the GIS platform. The evaluation results are divided into: extremely high risk area, high risk area, medium risk area and low risk area, accounting for 0.63%, 12.58%, 24.40% and 62.39% of the total area respectively. According to the scale of key areas, the factors of slope and slope height are selected, and the analytic hierarchy process model is used to carry out risk assessment of slope units divided by hydrological method based on GIS platform, including 19 extremely high-risk slopes, 69 high-risk slopes, 145 medium-risk slopes, 359 low-risk slopes. The same area (area A) under the two scales was selected to conduct variance analysis on the risk assessment results. It shows that at different scales and the same geographical location, the evaluation results of risk level may be inconsistent. At the county-wide scale, various mathematical statistical models with predictive functions should be used, but at the smaller key area scale, due to the insufficient number of samples used for training, it is not appropriate to use mathematical statistical models. Correspondingly, the grid unit based on GIS tools can be used as the evaluation unit at the county scale; the actual slope body can be used as the evaluation unit at the key area scale.