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This study aims to quantitatively assess the adjustment effects of various visual guiding schemes on the abrupt change of vehicle trajectory. A driving simulation experiment was conducted using five simulated scenes: (1) baseline (actual situation), (2) pavement (road studs), (3) low position (flexible guideposts), (4) high position (warning alignment signs and retroreflective arches) and (5) multilayer (combination of all devices). Raw data, including vehicle positions, steering wheel angles and lateral offset, were collected. Based on these data, the gradual change degree of vehicle trajectory (G) and average steering wheel angle (SWAav) were computed to quantitatively evaluate the extent of vehicle trajectory deviation and the stability of steering wheel operations respectively. These two evaluation indicators were then translated into trajectory gradualness (TG) and operation stability (OS), respectively, to assess the adjustment effects of different visual guiding schemes. The study results demonstrate that road studs perform a certain degree of enhancement on operation stability (OS). Flexible guideposts exhibit the best effects on operation stability (OS). Additionally, the combination of warning alignment signs and retroreflective arches demonstrate the best regulation of trajectory gradualness (TG). Multilayer visual guiding system achieves the optimal trajectory gradualness (TG) and operation stability (OS).

Abstract Antiferromagnets are promising for nano-scale oscillator in a wide frequency range from gigahertz up to terahertz. Experimentally realizing antiferromagnetic moment oscillation via spin-orbit torque, however, remains elusive. Here, we demonstrate that the optical spin-orbit torque induced by circularly polarized laser can be used to drive free decaying oscillations with a frequency of 2 THz in metallic antiferromagnetic Mn2Au thin films. Due to the local inversion symmetry breaking of Mn2Au, ultrafast a.c. current is generated via spin-to-charge conversion, which can be detected through free-space terahertz emission. Both antiferromagnetic moments switching experiments and dynamics analyses unravel the antiferromagnetic moments, driven by optical spin-orbit torque, deviate from its equilibrium position, and oscillate back in 5 ps once optical spin-orbit torque is removed. Besides the fundamental significance, our finding opens a new route towards low-dissipation and controllable antiferromagnet-based spin-torque oscillators.

Abstract Glioblastoma (GBM) represents a primary malignant brain tumor. Temozolomide resistance is a major hurdle in GBM treatment. Proteins encoded by circular RNAs (circRNAs) can modulate the sensitivity of multiple tumor chemotherapies. However, the impact of circRNA-encoded proteins on GBM sensitivity to temozolomide remains unknown. Herein, we discover a circRNA (circCOPA) through the circRNA microarray profile in GBM samples, which can encode a novel 99 amino acid protein (COPA-99aa) through its internal ribosome entry site. Functionally, circCOPA overexpression in GBM cells inhibits cell proliferation, migration, and invasion in vitro and growth in vivo. Rather than itself, circCOPA mainly functions as a suppressive effector by encoding COPA-99aa. Moreover, we reveal that circCOPA is downregulated in GBM tissues and high expression of circCOPA is related to a better prognosis in GBM patients. Mechanistically, a heteromer of SFPQ and NONO is required for double-strand DNA break repair. COPA-99aa disrupts the dimerization of NONO and SFPQ by separately binding with the NONO and SFPQ proteins, thus resulting in the inhibition of proliferation or invasion and the increase of temozolomide-induced DNA damage in GBM cells. Collectively, our data suggest that circCOPA mainly contributes to inhibiting the GBM malignant phenotype through its encoded COPA-99aa and that COPA-99aa increases temozolomide-induced DNA damage by interfering with the dimerization of NONO and SFPQ. Restoring circCOPA or COPA-99aa may increase the sensitivity of patients to temozolomide.

When the CO2 in a supercritical state (SCCO2) is released from deep coal seams, it reacts with minerals in coal, changing the porosity of coal, which in turn affects the effect of CO2 sequestration in coal seams and the effect of increasing methane production. In order to discover the influence characteristics of SCCO2-H2O-coal rock interaction on the porosity in coal, the experiments on the supercritical CO2 reforming coal under different water content conditions were carried out with coking coal as the research object. Based on the results of mineral composition and porosity measurements, the differences between the main minerals and the changes in pore cleavage at various scales in coal were compared, and the action mechanism of the SCCO2 fluid on the pore cleavage properties under various water content states was explored. The results show that: ① After the SCCO2 treatment, the surface of the coal body is rough and loose, some fissures are penetrated as a result of mineral dissolution, and the connectivity of micro fissure is improved. ② The SCCO2 fluid has a “pore-expanding”effect on coal, which is manifested by a decrease of the content of micro- and small pores, and an increase of the proportion of medium- and large pores, i.e., the conversion of micro- and small-sized pores to large pores, as well as the improvement of pore connectivity. Furthermore, it is discovered that the fractal dimension of the adsorption pores of the coal samples increases slightly in size and roughness, while the fractal dimension of the seepage pores decreases significantly, and the complexity and non-homogeneity are reduced. ③ The SCCO2 fluid has the best solubility on the carbonate minerals in coal, followed by clay minerals, and with the increase of water content, the proportion of carbonate minerals in the extracted coal first increases and then decreases. The SCCO2 fluid makes the carbonate minerals in the coal samples of the dry basal state and saturated water state dissolve significantly, which effectively improves the pore structure, and the effect on the coal samples of the saturated water state is better. After the air-dry basal coal samples were subjected to the SCCO2, the newly formed dolomite minerals gathered in the pore throats to cause the plugging effect, reducing the original large pore size, which is the main cause of the differential changes in the pore space of coals with different water content states.

Air staged combustion reduces NOx emissions, but increases the H2S concentration in primary combustion zone. The excessive H2S concentration near the furnace wall is an important factor that aggravates the high-temperature corrosion of the water-cooled wall. With large-scale renewable power integrated into the grid, the demand for flexible peak-shaving operation of traditional thermal power units has increased. The H2S concentration distribution near the furnace wall under different boiler loads deserves attention. Hence, the influence of different operating parameters of tangentially coal-fired boiler on H2S concentration distribution near the furnace wall was investigated by orthogonal test. A supercritical 600 MW tangentially coal-fired boiler was selected to establish a numerical model. The L16(45) orthogonal numerical conditions was designed to cover four boiler loads, including 100% BMCR, 75% THA, 50% THA and 35% BMCR. A user-defined SOx generation model was employed to calculate the H2S concentration distribution inside the furnace. The release of fuel sulfur and mutual transformation of sulfur components were considered. At the same time, the model included a multiple surface reaction model for describing the heterogeneous reaction between coke and O2/CO2/H2O, and the ratio of the gasification rate to the consumption rate for char particle was calculated. The results show that the high H2S concentration areas are mainly located below the bottom burner that on operation and between the top burner and SOFA nozzle. The main reason for the high H2S concentration in the latter area is that the tangential circle of flue gas increases gradually along the furnace height. The orthogonal analysis indicates that the average H2S concentration in the key area of the furnace wall under 35% BMCR load is 364 μL/L, which is significantly lower than that under the other loads. In addition, the impact of operating parameters on the H2S concentration in key areas follows the order of boiler load > primary air rate > excess air coefficient of main combustion zone > imaginary tangent circle diameter > vertical swing angle of burner.

Abstract Objective The aim of our study is to find a better way to identify a group of papillary thyroid carcinoma (PTC) with more aggressive behaviors and to provide a prediction model for lymph node metastasis to assist in clinic practice. Methods Targeted sequencing of DNA/RNA was used to detect genetic alterations. Gene expression level was measured by quantitative real-time PCR, western blotting or immunohistochemistry. CCK8, transwell assay and flow cytometry were used to investigate the effects of concomitant gene alterations in PTC. LASSO-logistics regression algorithm was used to construct a nomogram model integrating radiomic features, mutated genes and clinical characteristics. Results 172 high-risk variants and 7 fusion types were detected. The mutation frequencies in BRAF, TERT, RET, ATM and GGT1 were significantly higher in cancer tissues than benign nodules. Gene fusions were detected in 16 samples (2 at the DNA level and 14 at the RNA level). ATM mutation (ATM MUT) was frequently accompanied by BRAF MUT, TERT MUT or gene fusions. ATM MUT alone or ATM co-mutations were significantly positively correlated with lymph node metastasis. Accordingly, ATM knock-down PTC cells bearing BRAF V600E, KRAS G12R or CCDC6-RET had higher proliferative ability and more aggressive potency than cells without ATM knock-down in vitro. Furthermore, combining gene alterations and clinical features significantly improved the predictive efficacy for lymph node metastasis of radiomic features, from 71.5 to 87.0%. Conclusions Targeted sequencing of comprehensive genetic alterations in PTC has high prognostic value. These alterations, in combination with clinical and radiomic features, may aid in predicting invasive PTC with higher accuracy.

Abstract A large number of economic forests, especially apple orchards (AOs) in the Loess Plateau region of China, have been planted to develop the local economy and increase the income of farmers. The two main constraints preventing AOs on the Loess Plateau from developing sustainably and producing a high and steady yield are soil moisture content (SMC) and soil organic carbon (SOC). Nevertheless, little is currently known about the contributions of roots to these changes in the soil profile and the temporal modes of the SMC-SOC coupled effects. In our research, we analyzed the dynamic changes in SMC and SOC in AOs of various years in northern Shaanxi Province, as well as the coupled relationship between the two, and attempted to describe the function of roots in these changes. Research have shown: (1) As the age of the AOs increased, the SMC continued to decline throughout the 0–500 cm profile, especially at depths of 100–500 cm. SMC depletion mainly occurred in AOs aged 20 years (30.02%/year) and 30 years (31.18%/year). (2) Compared with abandoned land (AL), all the AOs except for the 6-year-old AO showed a carbon sequestration effect, and the carbon sequestration effect increased with age. The carbon sequestration rate of the 12-year-old AO was the highest and then decreased with age. Both surface and deeper soils showed better carbon sequestration, with a large amount of SOC being sequestered in deeper soil layers (> 100 cm). (3) The coupled effects of SMC and SOC varied with age and depth. The SMC in the deeper layers was significantly negatively correlated with SOC. Root dry weight density (RDWD) was significantly negatively correlated with SMC and significantly positively correlated with SOC. Path analysis suggested that SMC directly affects SOC at different soil depths, and regulates SOC by affecting RDWD, but these effects are significantly different at different depths. Therefore, we propose that management of AO should focus on the moisture deficit and carbon sequestration capabilities of deeper soils to ensure the sustainability of water use in AOs and the stability of agricultural carbon sequestration on the Loess Plateau.

Abstract Néel spin-orbit torque allows a charge current pulse to efficiently manipulate the Néel vector in antiferromagnets, which offers a unique opportunity for ultrahigh density information storage with high speed. However, the reciprocal process of Néel spin-orbit torque, the generation of ultrafast charge current in antiferromagnets has not been demonstrated. Here, we show the experimental observation of charge current generation in antiferromagnetic metallic Mn2Au thin films using ultrafast optical excitation. The ultrafast laser pulse excites antiferromagnetic magnons, resulting in instantaneous non-equilibrium spin polarization at the antiferromagnetic spin sublattices with broken spatial symmetry. Then the charge current is generated directly via spin-orbit fields at the two sublattices, which is termed as the reciprocal phenomenon of Néel spin-orbit torque, and the associated THz emission can be detected at room temperature. Besides the fundamental significance on the Onsager reciprocity, the observed magnonic charge current generation in antiferromagnet would advance the development of antiferromagnetic THz emitter.

ABSTRACTCandida albicans is a common fungal pathogen that can cause life-threatening infections. MIR1 is considered to be a mitochondrial phosphate carrier of C. albicans, while its role in virulence has not been fully elucidated. In this study, we found that mir1Δ/Δ mutant exhibited severe virulence defect in both nematode and murine models. Further mechanism studies revealed that the mir1Δ/Δ mutant grew more slowly than the wild-type strain and showed severe filamentation defects on the hypha-inducing agar media, including YPD + serum, Lee, Spider + glucose, SLAD, SLD, and YPS. Furthermore, the loss of MIR1 resulted in unfermentable carbon utilisation defect, ATP decrease, and reactive oxygen species (ROS) accumulation in C. albicans. Antioxidant proanthocyanidins, vitamin E, and N-acetyl cysteine (NAC) could reduce intracellular ROS levels and partially rescue the filamentation defects of the mir1Δ/Δ mutant. Accordingly, hypha-specific genes, as well as CEK1 and RIM101 were down-regulated in the mir1Δ/Δ mutant, and this down-regulation could be partially rescued by the addition of the antioxidant NAC. Collectively, MIR1 plays an important role in C. albicans mitochondrial function, filamentation and virulence, and would be a promising antifungal target.

In this study, a quantitative model was developed using near-infrared spectroscopy to analyze protein content in dried purple alfalfa, employing preprocessing methods (SG, SNV, MSC, FD) and variable selection algorithms (CARS, IRIV) to optimize spectra. Models using ELM, PLSR, SVM, and LSTM were tested; the MSC-CARS-PLSR-SVM model achieved the highest accuracy, with a calibration determination coefficient (R²) of 0.9982 and root mean square error (RMSE) of 0.1088, and a prediction R² of 0.9645 with RMSE of 0.5230, offering a precise and reliable method for protein content prediction.

Abstract Objectives Silicosis people are at high risk of developing pulmonary tuberculosis. Whether silica exposure increases the likelihood of latent tuberculosis infection (LTBI) was not well understood, and potential factors involved in LTBI risk among silicosis people were not evaluated before. Thus, LTBI among silicosis people and potential risk factors for LTBI among silicosis people were evaluated in this study. Methods A cross-sectional study was undertaken for 130 miner workers with silicosis. The QFT-GIT was performed for LTBI detection. Results The LTBI was high to 31.6% (36/114) for silicosis participants, and 13.1% (13/99) had a history of tuberculosis. Drinking was associated with LTBI risk (OR = 6.92, 95%CI, 1.47–32.66, P = 0.015). Meanwhile, tunneling work was associated with an increased risk of LTBI compared with other mining occupations (OR = 3.91,95%CI,1.20–12.70, P = 0.024). Conclusions The LTBI rate of silicosis participants was high and more than 10% had a history of tuberculosis. Drinking alcohol and tunneling were independent risk factors for LTBI in silicosis participants.

Abstract Aging is a global challenge, marked in the lungs by function decline and structural disorders, which affects the health of the elderly population. To explore anti-aging strategies, we develop a dynamic atlas covering 45 cell types in human lungs, spanning from embryonic development to aging. We aim to apply the discoveries of lung’s development to address aging-related issues. We observe that both epithelial and immune cells undergo a process of acquisition and loss of essential function as they transition from development to aging. During aging, we identify cellular phenotypic alternations that result in reduced pulmonary compliance and compromised immune homeostasis. Furthermore, we find a distinctive expression pattern of the ferritin light chain (FTL) gene, which increases during development but decreases in various types of lung cells during the aging process.

Microorganisms are closely related to human health, and changes in the microbiome can lead to the occurrence of diseases. With advances in sequencing technology and research, it has been discovered that intratumoral microbiota exists in various cancer tissues and differs in various cancers. Microorganism can colonize tumor tissues through intestine of damaged mucosal barrier, proximity to normal tissues and bloodstream circulation. Increasing evidence suggests that intratumoral microbiota promotes tumor progression by increasing genomic instability, affecting host immune systems, promoting tumor migration, and regulating tumor signaling pathways. This review article summarizes the latest progress in intratumoral microbiome research, including the development history of intratumoral microbiota, their composition and sources within tumors, their distribution in various cancer tissues, as well as their role in cancer development. Furthermore, the application of intratumoral microbiota in clinical settings is emphasized and we innovatively summarize the clinical trials involving microbial applications for cancer diagnosis and treatment across different countries.

Benzene is a common environmental pollutant and significant health hazard. Low-dose benzene exposure is common in most industrial settings, and some workers exhibit hematotoxicity characterized by impaired hematopoietic function. Consequently, understanding the early hematopoietic damage and biomarkers associated with low-dose benzene exposure is of critical importance for health risk assessment. Using data from a 5-year prospective cohort study on benzene exposure and the National Center for Biotechnology Information's Gene Expression Omnibus database, we detected significant downregulation of the ubiquitin-conjugating enzyme UBE2L3 (E2) in benzene-exposed subjects compared to control subjects. Liquid chromatography tandem mass spectrometry and co-immunoprecipitation experiments illustrated the binding interaction between UBE2L3 and the ubiquitin-protein ligase ZNF598 (E3). We applied deep learning algorithms to predict candidate interacting proteins and then conducted validation via co-immunoprecipitation experiments, which showed that ZNF598 engages in binding with the autophagy protein LAMP-2. Subsequent overexpression and knockdown of UBE2L3 coupled with immunofluorescence experiments and transmission electron microscopy revealed that UBE2L3 disrupts the ubiquitination-degradation of LAMP-2 by ZNF598, reduces GPX4 expression levels, and activates an autophagy-dependent ferroptosis pathway. It also leads to increased lipid peroxidation, thereby promoting ferroptosis and contributing to the hematotoxicity induced by benzene. In summary, our results suggest that UBE2L3 may be involved in early hematopoietic damage by modulating the autophagy-dependent ferroptosis signaling pathway in benzene-induced hematotoxicity.

Diamond-Blackfan anemia syndrome (DBAS) is an inherited bone marrow failure disorder that typically presents in infancy as hypoplastic anemia and developmental abnormalities in approximately 50% of cases. DBAS is caused by haploinsufficiency in one of 24 ribosomal protein genes, with RPS19 mutations accounting for 25% of cases. We generated iPSC lines from two patients with different heterozygous RPS19 mutations (c.191T > C and c.184C > T) and isogenic lines in which the mutations were corrected by Cas9-mediated homology directed repair.

Developing high‐performance, high‐stability, and low‐cost nonprecious metal catalysts to enhance the performance of zinc–air batteries (ZABs) holds significant importance. A bifunctional catalyst consisting of cobalt oxide (CoO) nanocrystals on nitrogen‐doped reduced graphene oxide nanoribbons (N‐rGONR) as a novel substrate is successfully synthesized in this work. This synthesized bifunctional catalyst exhibits mesoporous structure, and remarkable synergistic effects between CoO nanocrystals and N‐rGONR, demonstrating excellent activity and durability in both oxygen reduction reactions and oxygen evolution reactions. Notably, the resulting aqueous electrolyte ZABs show a high discharge peak power density of 196 mW cm−2, a high specific capacity of 615.9 mAh g−1, and long‐time stability for 648 h. Furthermore, the assembly of 1D and 2D flexible solid‐state ZABs fabricated using this bifunctional catalyst exhibits stable electrochemical performance, even under severe deformation. These results underscore the considerable promise of implementing the CoO@N‐rGONR catalyst structure in next‐generation advanced energy storage and conversion devices.

To study the bond performance of ultra-high performance concrete (UHPC) and steel bar after freeze-thaw cycles (FTCs), the eccentric pull-out test of 10 groups of reinforced UHPC bond specimens, the compressive test of 24 cube specimens and the splitting tensile test of 24 cube specimens were carried out. The degradation of UHPC mechanical properties and bond performance of UHPC and steel bar after FTCs were studied. The influence of UHPC strength, cover thickness, and bond length on bond strength after FTCs was analyzed. The relationship between mechanical and bond properties is established by using compressive strength and average bond strength as indexes. A formula for calculating average bond strength of UHPC after FTCs was developed. The results show that the elastic modulus loss, compressive strength loss, and splitting tensile strength loss after FTCs increase slowly at first and then rapidly. With the increase of FTCs, the relationship between dynamic elastic modulus and compressive strength, compressive strength, and splitting tensile strength showed strong linear characteristics. UHPC strength is an important factor affecting the average bond strength after FTCs, followed by the cover thickness. After 600 freeze-thaw cycles, the failure mode of the UHPC bond specimen changed. The compressive strength and the average bond strength show a strong linear relationship in the process of 900 FTCs. The average bond strength between UHPC and steel bar decreased by 13.76 ∼ 17.23 % after 900 freeze-thaw cycles.

For wearable smart textile sensors, stability, accuracy and multi-functionality are key objectives. Achieving the optimal application requires delicately balancing the crucial physical properties of strain sensors, presenting a key technological challenge. This study addresses these challenges by presenting several properties and potential applications of a triple hierarchic polymeric knitted fabric. The fabric incorporates an internal conductive network constructed with silver nanowires (AgNWs) and polydopamine (PDA) coating on its outer surface. This innovative textile successfully strikes a balance between strain sensing and electromagnetic interference shielding while concurrently exhibiting biocompatibility and antimicrobial properties. Significantly, acknowledging the susceptibility of measurements from polymer-based strain sensor materials to time drift, we introduce both a modeling approach and a novel calibration technique. This advancement facilitates the generation of stable cyclic sensing signals, even under substantial deformations of up to 80 % at a high stretching speed. Importantly, it provides a practical solution for addressing signal drift observed in flexible sensors when utilized in environments characterized by long-term and large deformations.

Turbine blisk is one of the typical components of gas turbine engines. The fatigue life of turbine blisk directly affects the reliability and safety of both turbine blisk and aeroengine whole-body. To monitor the performance degradation of an aeroengine, an efficient deep learning-based modeling method called convolutional-deep neural network (C-DNN) method is proposed by absorbing the advantages of both convolutional neural network (CNN) and deep neural network (DNN), to perform the probabilistic low cycle fatigue (LCF) life prediction of turbine blisk regarding uncertain influencing parameters. In the C-DNN method, the CNN method is used to extract the useful features of LCF life data by adopting two convolutional layers, to ensure the precision of C-DNN modeling. The two close-connected layers in DNN are employed for the regression modeling of aeroengine turbine blisk LCF life, to keep the accuracy of LCF life prediction. Through the probabilistic analysis of turbine blisk and the comparison of methods (ANN, CNN, DNN and C-DNN), it is revealed that the proposed C-DNN method is an effective mean for turbine blisk LCF life prediction and major factors affecting the LCF life were gained, and the method holds high efficiency and accuracy in regression modeling and simulations. This study provides a promising LCF life prediction method for complex structures, which contribute to monitor health status for aeroengines operation.

Abstract Mobile edge computing (MEC) is a novel computing paradigm that pushes computation and storage resources to the edge of the network. The interconnection of edge servers forms small-scale data centers, enabling MEC to provide low-latency network services for mobile users. Nowadays, Remote Direct Memory Access (RDMA) has been widely deployed in such data centers to reduce CPU overhead and network latency. Plenty of congestion control mechanisms have been proposed for RDMA data centers, aiming to provide low-latency data delivery and high throughput network services. However, our fine-grained experimental analysis reveals that existing congestion control mechanisms still have performance limitations due to inappropriate congestion notifications and the long congestion feedback cycle. In this paper, we propose Mercury, which is an accurate and fast congestion feedback mechanism. Mercury comprises two key components: (1) the state-driven congestion detection and (2) the window-based congestion notification. Specifically, the state-driven congestion detection monitors the queue length and the number of packets received at the switch egress port when the PFC is triggered. It determines the states of egress ports and identifies flows that really contribute to congestion. Then, window-based congestion notification calculates the window sizes for congested flows and rapidly returns Congestion Notification Packets (CNPs) with the window information to the sender. It facilitates the rate adjustment of congested flows. Mercury is compatible with existing RDMA CC mechanisms and can be easily implemented in switches. We employ real-world data sets and conduct both micro-benchmark and large-scale simulations to evaluate the performance of Mercury. The results indicate that, thanks to the accurate and fast congestion feedback, Mercury achieves a reduction in the 99th tail flow completion time by up to 45.1%, 41.8%, 38.7%, 30.9%, and 37.9% compared with Timely, DCQCN, DCQCN+TCD, PACC, and HPCC, respectively.

Abstract Cancer has become one of the most important causes of human death. In particular, the 5 year survival rate of patients with digestive tract cancer is low. Although chemotherapy drugs have a certain efficacy, they are highly toxic and prone to chemotherapy resistance. With the advancement of antitumor research, many natural drugs have gradually entered basic clinical research. They have low toxicity, few adverse reactions, and play an important synergistic role in the combined targeted therapy of radiotherapy and chemotherapy. A large number of studies have shown that the active components of Paris polyphylla (PPA), a common natural medicinal plant, can play an antitumor role in a variety of digestive tract cancers. In this paper, the main components of PPA such as polyphyllin, C21 steroids, sterols, and flavonoids, amongst others, are introduced, and the mechanisms of action and research progress of PPA and its active components in the treatment of various digestive tract cancers are reviewed and summarized. The main components of PPA have been thoroughly explored to provide more detailed references and innovative ideas for the further development and utilization of similar natural antitumor drugs.

Abstract Blue light promotes primordium differentiation and fruiting body formation of mushroom. However, the blue light response mechanism of mushroom remains unclear. In this study, mycelium of Flammulina filiformis was exposed to blue light, red light and dark conditions, and then the comparative metabolome and transcriptome analysis was applied to explore metabolic regulation mechanism of F. filiformis under blue light and red light conditions. The yield of the fruiting body of F. filiformis under blue light condition was much higher than that under dark and red light conditions. Metabolome analysis showed that blue light treatment reduced the concentrations of many low molecular weight carbohydrates in the pilei, but it promoted the accumulation of some low molecular weight carbohydrates in the stipes. Blue light also decreased the accumulation of organic acids in the stipes. Blue light treatment reduced the levels of tyrosine and tryptophan in the stipes, but it largely promoted the accumulation of lysine in this organ. In the stipes of F. filiformis, blue light shifted metabolite flow to synthesis of lysine and carbohydrates through inhibiting the accumulation of aromatic amino acids and organic acids, thereby enhancing its nutritional and medicinal values. The transcriptome analysis displayed that blue light enhanced accumulation of lysine in fruiting body of F. filiformis through downregulation of lysine methyltransferase gene and L-lysine 6-monooxygenase gene. Additionally, in the stipes, blue light upregulated many hydrolase genes to improve the ability of the stipe to biodegrade the medium and elevated the growth rate of the fruiting body.

Abstract Background Intractable postpartum hemorrhage (PPH) during cesarean section has been a significant concern for obstetricians. We aimed to explore the effectiveness and safety of a new type of uterine compression suture, the step-wise surgical technique of knapsack-like sutures for treating intractable PPH caused by uterine atony and placenta factors in cesarean section. Methods The step-wise surgical technique of knapsack-like sutures was established on the basis of the artful combination of vertical strap-like sutures and an annular suture-ligation technique. This novel surgical technique was applied to 34 patients diagnosed with PPH during cesarean section due to severe uterine atony and placental factors in our department. The hemostatic effects, clinical outcomes and follow-up visit results were all reviewed and analyzed. Results This new uterine compression suture successfully stopped bleeding in 33 patients, and the effective rate was 97.06%. Only 1 patient failed and was changed to use bilateral uterine arterial embolization and internal iliac artery embolization. The follow-up visits indicated that 33 patients restored menstruation except for 1 who was diagnosed with amenorrhea. The gynecological ultrasound tests of all the patients suggested good uterine involutions, and they had no obvious complaints such as hypogastralgia. Conclusions This step-wise surgical technique of knapsack-like uterine compression sutures can compress the uterus completely. It is a technique that can conserve the uterus and fertility function without special equipment in caesarean section for PPH, with the characteristics of being safe, simple and stable (3 S) with rapid surgery, reliable hemostasis and resident doctor to operation (3R).

Self-powered photodetectors which operate without external power sources hold immense promise in future photodetection systems. To achieve high-performance self-powered optoelectronic devices, efficient electron-hole pair separation is critical to generate high photocurrents. In this work, we successfully synthesized semiconducting graphene nanoribbons (GNRs) with a direct bandgap of 1.80 eV and employed them to construct a high-performance GNR/Al2O3/IGZO heterostructure photodetector. The built-in electric field in the heterojunctions enables this photodetector to exhibit remarkable performance, showing a responsivity of up to 68 mA/W, a detectivity of 8.34 × 1010 Jones, and rapid response times of 21/20 ms at zero bias. Furthermore, the photodetector features a wide spectral detection range of 405 to 1550 nm. These results highlight the promising potential of GNR/IGZO p-n heterojunction-based self-powered photodetectors in optoelectronic applications.

Understanding the paleoenvironment and phytogeographical history of the Tibetan Plateau, China relies on discovering new plant fossils. The Qaidam Basin has long been regarded as an ideal ‘field laboratory’ to investigate the paleoclimate and paleobiological evolution of the northern Tibetan Plateau. However, fossil angiosperms from the Qaidam Basin are rare, and our knowledge of its paleovegetation is poor. Here, we report fossil leaves and fruits of Betulaceae found from the Oligocene Shangganchaigou Formation of northwestern Qaidam Basin (Huatugou area). Comparative morphological analysis led us to assign the fruits to the Betula subgenus Betula and the leaves to Carpinus grandis. These findings, together with other reported fossil plants from the same locality, reveal a close floristic linkage between the Qaidam Basin and Europe during the Oligocene. The northern pathway of this floristic exchange may have crossed through the Qaidam Basin during the late Paleogene. This floristic linkage may have been facilitated by the continuous narrowing of the Turgai Strait and stronger westerlies, which transported moisture and provided favorable climatic conditions. Indeed, fossil plants collected from the Qaidam Basin suggest that during the Oligocene this region had warm and humid deciduous broad-leaf forest, which differs from the region’s modern vegetation and indicates that the Qaidam Basin may have been a suitable region for these plants to flourish and spread during the Oligocene.

Oceanic uptake and storage of anthropogenic CO2 (CANT) are regulated by ocean circulation and ventilation. To decipher the storage and redistribution of CANT in the western North Pacific, where a major CANT sink develops, we investigated the water column carbonate system, dissolved inorganic radiocarbon and ancillary parameters in May and August 2018, spanning the Kuroshio Extension (KE, 35–39 °N), Kuroshio Recirculation (KR, 27–35 °N) and subtropical (21–27 °N) zones. Water column CANT inventories were estimated to be 40.5 ± 1.1 mol m−2 in the KR zone and 37.2 ± 0.9 mol m−2 in the subtropical zone. In comparison with historical data obtained in 2005, relatively high rates of increase of the CANT inventory of 1.05 ± 0.20 and 1.03 ± 0.12 mol m−2 yr−1 in the recent decade were obtained in the KR and subtropical zones, respectively. Our water-mass-based analyses suggest that formation and transport of subtropical mode water dominate the deep penetration, storage, and redistribution of CANT in those two regions. In the KE zone, however, both the water column CANT inventory and the decadal CANT accumulation rate were small and uncertain owing to the dynamic hydrology, where the naturally uplifting isopycnal surfaces make CANT penetration relatively shallow. The findings of this study improve the understanding of the spatiotemporal variations of CANT distribution, storage, and transport in the western North Pacific.

Abstract An intrinsic link between metabolism and function in immune cells, and in particular macrophages, has been well established recently. However, the molecular mechanisms controlling the metabolic switch in these sentinel cells for their integral roles in host defense, inflammation, homeostasis, and pathogenesis remain largely unknown. Here, we identify the master transcription factor NF-κB RelA as a vital cell-intrinsic checkpoint restricting aerobic glycolysis to favor mitochondrial oxidative phosphorylation (OXPHOS) and “M2” activation (alternative anti-inflammatory and pro-tumorigenic activation, in contrast to classical pro-inflammatory and anti-tumor M1 activation) of macrophages under oncogenic stress. RelA specific knockdown or genetic deletion in macrophages causes metabolism to shift away from OXPHOS toward glycolysis, resulting in drastically decreased oxygen consumption but significantly increased lactate and ATP production. The metabolic change in RelA deficient cells is associated with the decrease in the expressions of the OXPHOS gene SCO2 as well as the M2 marker and function genes arginase-1 and VEGF. These data suggest that RelA induces SCO2 expression to enhance OXPHOS and restrict glycolysis in macrophages for their pro-tumorigenic activation.

This research aimed to determine the effect of dietary guar gum inclusion in high-lipid diets on the liver health of common carp (Cyprinus carpio). Four high-fat diets (10 % crude lipid) containing 0 % (HF), 0.3 % (HFG0.3), 1 % (HFG1), and 3 % (HFG3) of guar gum and a normal-lipid diet (5 % crude lipid; Control) were formulated. The tested diets were evenly and randomly distributed to fifteen tanks, with each tank containing thirty fish (4.53 ± 0.05 g). Fish were fed until apparent satiation for eight weeks. Compared to HF, diets HFG0.3, HFG1, and HFG3 significantly improved feed efficiency, with the HFG0.3 diet enhancing weight gain rate and specific growth rate. The results indicated that HF induced gut dysbiosis, hepatic lipid accumulation, oxidative stress, inflammation, and disturbance in hepatic lipid and cholesterol metabolism. Compared to the HF diet, diets HFG0.3, HFG1, and HFG3 substantially decreased hepatic lipid accumulation and malonaldehyde content, increased catalase activity and the expression of AMP-activated protein kinase (AMPKα2), peroxisomal proliferator-activated receptor alpha (PPARα), cholesterol 7alpha-hydroxylase, and decreased the expression of interleukin-1β (IL-1β). Moreover, the HFG0.3 and HFG1 diets dramatically increased nuclear factor erythroid 2-related factor 2 and liver X receptor expression and decreased protein carbonyl contents and expression of IL-8, nuclear factor kappa B (NF-κB p65), and tumor necrosis factor α. Furthermore, the HFG1 diet significantly increased carnitine palmitoyltransferase 1 and peroxisomal proliferator-activated receptor gamma coactivator 1 expression and reduced expression levels of fibroblast growth factor 19, farnesoid X receptor, and sterol regulatory element-binding protein type 1. The linear discriminant analysis effect size (LEfSe) analysis showed that HFG 0.3 and HFG1 substantially increased the enrichment of beneficial microbiota (e.g., lactic acid bacteria, Cetobacterium, and Fusobacterial) and decreased the enrichment of harmful microbiota (e.g., Proteobacteria, Acinetobacter, and Pseudomonas) compared to HF. These results suggested that guar gum can mitigate high-fat diet-induced liver damage in fish.

Abstract Tornadoes, as highly destructive weather events, require accurate detection for effective decision‐making. Traditional radar‐based tornado detection algorithms (TDA) face challenges with limited tornado feature extraction capabilities, leading to high false alarm rates and low detection probabilities. This study introduces the Multi‐Task Identification Network (MTI‐Net), leveraging Doppler radar data to enhance tornado recognition. MTI‐Net integrates tornado detection and estimation tasks to acquire comprehensive spatial and locational information. As part of MTI‐Net, we introduce a novel backbone network of Multi‐Head Convolutional Block (MHCB), which incorporates Spatial and Channel Attention Units (SAU and CAU). SAU optimizes local tornado feature extraction, while CAU reduces false alarms by enhancing dependencies among input variables. Experiments demonstrate the superiority of MTI‐Net over TDA, with a decrease in false alarm rates from 0.94 to 0.46 and an increase in hit rates from 0.23 to 0.81, highlighting the effectiveness of MTI‐Net in handling small‐scale tornado events.

Abstract Machine learning‐based approaches demonstrate a significant potential in radar quantitative precipitation estimation (QPE) applications. In contrast to conventional methods that depend on local raindrop size distributions, deep learning (DL) can establish an effective mapping from three‐dimensional radar observations to ground rain rates. However, the lack of transparency in DL models poses challenges toward understanding the underlying physical mechanisms that drive their outcomes. This study aims to develop a DL‐based QPE system and provide a physical explanation of radar precipitation estimation process. This research is designed by employing a deep neural network consisting of two modules. The first module is a quantitative precipitation estimation network that has the capability to learn precipitation patterns and spatial distribution from multidimensional polarimetric radar observations. The second module introduces a quantitative precipitation estimation shapley additive explanations method to quantify the influence of each radar observable on the model estimate across various precipitation intensities.

Bisphenol compounds (BPs) are commonly used in industry and agriculture. However, BPs pollution has already raised global concerns due to their ecological risks. This study investigated nine types of BPs in agricultural soil and irrigation rivers, and evaluated the occurrence, source apportionment, and ecological risks for BPs in soils of agricultural environment by using principal component analysis-multivariate linear regression (PCA-MLR) and risk quotients (RQ). The average concentration of BPs in soil, irrigation water and sediments were 29.19 ng/g, 30.21 ng/L and 610.09 ng/g dw, respectively. BPA was the most highly detected contaminant in all media. In soil, the primary BPA substitutes were bisphenol S (BPS) and bisphenol F (BPF), contributing about 50 % to the pollution in total. PCA-MLR analysis indicated that the release of solid waste was the primary cause of BPs pollution in the agricultural soils, following by waste water discharge. The evaluation of RQ revealed that BPs presented a low to medium risk to algae, daphnia, and fish in irrigation rivers, while more than 90 % of soil sampling sites faced medium or high risk, with BPA and BPS as the main contributors to the risk. The research findings offer evidence to support the assessment of contaminants concentration, source pathways, and risk management strategies pertaining to BPs in the agricultural system. With ongoing BPA substitute occurrence, addressing risks to agricultural soil ecosystems remains crucial.

Part-set cuing facilitation and impairment effects are rarely found in spatial memory, which is a challenge to the theories of part-set cuing effects based on lexical stimulus. This study aims to investigate whether there part-set cuing facilitation and impairment effects are present in spatial memory by constructing two types of memory scenes with high and low degrees of interitem associations, achieved by manipulating the presentation of miniatures. This study examined the effects of different part-set cues on free recall, recognition, and reconstruction tasks. The results of two experiments revealed that matrix cues impaired the performance of three recall tasks in memory scenes with a high degree of interitem associations, and scene cues facilitated the reconstruction performance (Experiment 1). Conversely, in memory scenes with a low degree of interitem associations, the impairment effect of matrix cues was not observed in the three recall tasks, but scene cues still facilitated the reconstruction performance (Experiment 2). These findings supported the retrieval strategy disruption hypothesis, the two-mechanism and the multi-mechanism accounts, demonstrating the significance of interitem associations in spatial memory. Furthermore, the results provided direct evidence for the importance of the encoding-retrieval strategy matching principle in spatial memory tasks.

Background Escherichia coli is an important intestinal flora, of which pathogenic E. coli is capable of causing many enteric and extra-intestinal diseases. Antibiotics are essential for the treatment of bacterial infections caused by pathogenic E. coli; however, with the widespread use of antibiotics, drug resistance in E. coli has become particularly serious, posing a global threat to human, animal, and environmental health. While the drug resistance and pathogenicity of E. coli carried by tigers and leopards in captivity have been studied intensively in recent years, there is an extreme lack of information on E. coli in these top predators in the wild environment. Methods Whole genome sequencing data of 32 E. coli strains collected from the feces of wild Amur tiger (Panthera tigris altaica, n = 24) and North China leopard (Panthera pardus japonensis, n = 8) were analyzed in this article. The multi-locus sequence types, serotypes, virulence and resistance genotypes, plasmid replicon types, and core genomic SNPs phylogeny of these isolates were studied. Additionally, antimicrobial susceptibility testing (AST) was performed on these E. coli isolates. Results Among the E. coli isolates studied, 18 different sequence types were identified, with ST939 (21.9%), ST10 (15.6%), and ST3246 (9.4%) being the most prevalent. A total of 111 virulence genes were detected, averaging about 54 virulence genes per sample. They contribute to invasion, adherence, immune evasion, efflux pump, toxin, motility, stress adaption, and other virulence-related functions of E. coli. Sixty-eight AMR genes and point mutations were identified. Among the detected resistance genes, those belonging to the efflux pump family were the most abundant. Thirty-two E. coli isolates showed the highest rate of resistance to tetracycline (14/32; 43.8%), followed by imipenem (4/32; 12.5%), ciprofloxacin (3/32; 9.4%), doxycycline (2/32; 6.3%), and norfloxacin (1/32; 3.1%). Conclusions Our results suggest that E. coli isolates carried by wild Amur tigers and North China leopards have potential pathogenicity and drug resistance.

Synergistic regional emission reduction (SRER) is an important part of the strategy to achieve carbon neutrality. In this paper, a system efficiency value-added model is proposed to measure the strength of SRER network relationships for 40,186 sets of city pairs and the SRER levels of 284 cities in China from 2011 to 2021. Subsequently, the evolution characteristics of the SRER network, the spatial and temporal characteristics of urban SRER levels, and the driving factors of the SRER network evolution are further analyzed. The results are as follows: SRER network is shifting from a fan-shaped network pattern of “three-region clustering and sporadic coverage” to a shuttle-shaped nested network pattern of “east-west linkage and multi-region support”. Time series analysis found that urban SRER level in China showed fluctuating growth characteristics during the study period. Spatial analysis reveals that the spatial autocorrelation of urban SRER level is decreasing, and the spatial distribution range is expanding towards the southwest. Emission reduction comparative advantages (CAER), green innovation division of labor (GIDL) and urban economic linkages (LCEL) are driver factors of SRER network evolution. This study proposes an evaluation method for the urban SRER level from network relationships perspective. Subsequently, network evolution characterization, spatial and temporal characterization, and driving factor analysis were conducted. The results of the study provide important theoretical guidance and inspiration for grasping the current status and enhancement paths of China's urban SRER level.

Neural cell adhesion molecule L1 (L1CAM) is a cell-surface glycoprotein involved in cancer occurrence and migration. Up to today, L1CAM-targeted therapy appeared limited efficacy in clinical trials although quite a few attempts by monoclonal antibody (mAb) or chimeric antigen receptor T-cell therapy (CAR-T) have been reported. Therefore, the development of new effective therapies targeting L1CAM is highly desirable. It has been demonstrated that T cell-engaging bispecific antibody (TCE) plays an effective role in cancer immunotherapy by redirecting the cytotoxic activity of CD3+ T cells to tumor cells, resulting in tumor cell death. In this study, we designed and characterized a novel bispecific antibody (CE7-TCE) based on the IgG-(L)-ScFv format, which targets L1CAM and CD3 simultaneously. In vitro, CE7-TCE induced specific killing of L1CAM-positive tumor cells through T cells. In vivo, CE7-TCE inhibited tumor growth in human peripheral blood mononuclear cell/tumor cell co-grafting models. To overcome the adaptive immune resistance (AIR) that impairs the efficacy of TCEs, we conducted a combination therapy of CE7-TCE with Pembrolizumab (anti-PD1 mAb), which enhanced the anti-tumor activity of CE7-TCE. Our results confirmed the feasibility of using L1CAM as a TCE target for the treatment of solid tumors and revealed the therapeutic potential of CE7-TCE combined with immune checkpoint inhibitors.

Non-coding RNAs (ncRNAs) play essential regulatory functions in various physiological and pathological processes in the brain. To systematically characterize the ncRNA profile in cortical cells, we downloaded single-cell SMART-Seq v4 data of mouse cerebral cortex. Our results revealed that the ncRNAs alone are sufficient to define the identity of most cortical cell types. We identified 1,600 ncRNAs that exhibited cell type specificity, even yielding to distinguish microglia from perivascular macrophages with ncRNA. Moreover, we characterized cortical layer and region specific ncRNAs, in line with the results by spatial transcriptome (ST) data. By constructing a co-expression network of ncRNAs and protein-coding genes, we predicted the function of ncRNAs. By integrating with genome-wide association studies data, we established associations between cell type-specific ncRNAs and traits related to neurological disorders. Collectively, our study identified differentially expressed ncRNAs at multiple levels and provided the valuable resource to explore the functions and dysfunctions of ncRNAs in cortical cells.

IDH wild-type glioblastoma (GBM) intrinsic subtypes have been linked to different molecular landscapes and outcomes. Accurate prediction of molecular subtypes of GBM is very important to guide clinical diagnosis and treatment. Leveraging machine learning technology to improve the subtype classification was considered a robust strategy. Several single machine learning models have been developed to predict survival or stratify patients. An ensemble learning strategy combines several basic learners to boost model performance. However, it still lacked a robust stacking ensemble learning model with high accuracy in clinical practice. Here, we developed a novel integrative stacking ensemble model framework (ecGBMsub) for improving IDH wild-type GBM molecular subtype classification. In the framework, nine single models with the best hyperparameters were fitted based on extrachromosomal circular DNA (eccDNA) molecular profiling. Then, the top five optimal single models were selected as base models. By randomly combining the five optimal base models, 26 different combinations were finally generated. Nine different meta-models with the best hyperparameters were fitted based on the prediction results of 26 different combinations, resulting in 234 different stacked ensemble models. All models in ecGBMsub were comprehensively evaluated and compared. Finally, the stacking ensemble model named “XGBoost.Enet-stacking-Enet” was chosen as the optimal model in the ecGBMsub framework. A user-friendly web tool was developed to facilitate accessibility to the XGBoost.Enet-stacking-Enet models (https://lizesheng20190820.shinyapps.io/ecGBMsub/).

Objective: To investigate the effectiveness of a multimodal deep learning model in predicting tumor budding (TB) grading in rectal cancer (RC) patients. Materials and methods: A retrospective analysis was conducted on 355 patients with rectal adenocarcinoma from two different hospitals. Among them, 289 patients from our institution were randomly divided into an internal training cohort (n = 202) and an internal validation cohort (n = 87) in a 7:3 ratio, while an additional 66 patients from another hospital constituted an external validation cohort. Various deep learning models were constructed and compared for their performance using T1CE and CT-enhanced images, and the optimal models were selected for the creation of a multimodal fusion model. Based on single and multiple factor logistic regression, clinical N staging and fecal occult blood were identified as independent risk factors and used to construct the clinical model. A decision-level fusion was employed to integrate these two models to create an ensemble model. The predictive performance of each model was evaluated using the area under the curve (AUC), DeLong's test, calibration curve, and decision curve analysis (DCA). Model visualization Gradient-weighted Class Activation Mapping (Grad-CAM) was performed for model interpretation. Results: The multimodal fusion model demonstrated superior performance compared to single-modal models, with AUC values of 0.869 (95% CI: 0.761–0.976) for the internal validation cohort and 0.848 (95% CI: 0.721–0.975) for the external validation cohort. N-stage and fecal occult blood were identified as clinically independent risk factors through single and multivariable logistic regression analysis. The final ensemble model exhibited the best performance, with AUC values of 0.898 (95% CI: 0.820–0.975) for the internal validation cohort and 0.868 (95% CI: 0.768–0.968) for the external validation cohort. Conclusion: Multimodal deep learning models can effectively and non-invasively provide individualized predictions for TB grading in RC patients, offering valuable guidance for treatment selection and prognosis assessment.

Abstract Hepatocellular carcinoma (HCC), one of the most prevalent forms of cancer worldwide, presents a significant global healthcare challenge. Cancer stem cells (CSCs), which can influence neighboring non-CSCs, are believed to play a crucial role in tumor growth and resistance to treatment, but the specific mechanisms and mediators are not fully understood. Regulation of the CSC state is considered an ideal therapeutic strategy both in the early stages of tumor formation and within established tumors. Exosomes have emerged as key players in intercellular communication, similar to classical hormone signaling, and are essential for facilitating communication between cells in liver cancer. Here, by coupling immunomagnetic bead sorting and exosomal sequencing, we found that exosome-derived circRNAs enriched in liver cancer CSCs were the key subsets with stemness characteristics and ultimately promoted HCC development. Of interest, we found that circ-ZEB1 and circ-AFAP1 are strongly correlated with liver cancer stemness and a poor prognosis, and can regulate the epithelial-mesenchymal transition (EMT) process. Our novel exosome-derived circRNAs play a vital role as key components of various intercellular crosstalk and communication systems in malignant transmission. This finding not only provides valuable support for utilizing plasma exosomal circRNAs as clinical prognostic indicators for HCC patients but also highlights a new research direction in exploring the signaling between liver CSCs and the messenger molecules contained within exosomes.

The effects of ScCO2 on pore structure should be investigated in order to properly apply supercritical carbon dioxide (ScCO2) fracturing on tight sandstone. ScCO2 treatment was applied to three sets of tight sandstone samples. The pore structure was characterized using a combination of high-pressure mercury intrusion porosimetry and nuclear magnetic resonance. Furthermore, the pore size distribution’s multi-fractal dimensions were estimated. After SCCO2 treatment, the number of transitional pores decreased significantly, while the number of mesopores and macropores increased. At all scales, the fractal dimension characteristics indicate that pore structure gets more complicated and heterogeneous. Furthermore, due to their larger contact area, large pores have a higher fractal dimension than small pores. The accumulative pore volume of the calcite-rich group increases and a decreasing trend occurs for the calcite-rare group. The content of calcite sharply decreased while clay, feldspar, and plagioclase content have a slight drop after ScCO2 treatment, which affects the alternation of pore structure. Thus, the accumulative porosity volume and pore connectivity do not always increase after ScCO2 exposure because re-precipitation and fine migration can potentially clog pores and channels.

Abstract The organic thin-film transistor is advantageous for monolithic three-dimensional integration attributed to low temperature and facile solution processing. However, the electrical properties of solution deposited organic semiconductor channels are very sensitive to the substrate surface and processing conditions. An organic-last integration technology is developed for wafer-scale heterogeneous integration of a multi-layer organic material stack from solution onto the non-even substrate surface of a III-V micro light emitting diode plane. A via process is proposed to make the via interconnection after fabrication of the organic thin-film transistor. Low-defect uniform organic semiconductor and dielectric layers can then be formed on top to achieve high-quality interfaces. The resulting organic thin-film transistors exhibit superior performance for driving micro light emitting diode displays, in terms of milliampere driving current, and large ON/OFF current ratio approaching 1010 with excellent uniformity and reliability. Active-matrix micro light emitting diode displays are demonstrated with highest brightness of 150,000 nits and highest resolution of 254 pixels-per-inch.

Highlights The tactile performance of ultralight multifunctional sensors can reach the level of human tactile perception. An individual sensor can provide multiple tactile sensations: pressure, temperature, materials recognition, and 3D location. Therefore, it is no longer necessary to integrate multiple sensing modules with different functions, which greatly simplifies system complexity and reduces energy loss. The tactile system with multimodal learning algorithms has universality and can accommodate object recognition tasks in various application scenarios (e.g., Mars and Kitchen).

Abstract Background It has been demonstrated that circularRNA (circRNAs) plays a critical role in various cancers. While the potential molecular mechanism of circRNAs in the progression of colorectal cancer (CRC) remains uncertain. Methods Differentially expressed circRNAs were identified by RNA sequencing. RT-qPCR detected the expression of circ_0009092, miR-665, and NLK in CRC tissues and cells. Functions of circ_0009092 on tumor cell proliferation, migration, and invasion were investigated by a series of in vitro assays. The underlying mechanism of circ_0009092 was explored by bioinformatics analysis, RNA immunoprecipitation (RIP) and luciferase assays. A co-culture assay in vitro was performed to detect the affection of circ_0009092 on macrophage recruitment in the tumor microenvironment (TME). A xenograft mouse model was used to explore the effect of circ_0009092 on tumor growth. Results Circ_0009092 was downregulated in CRCand predicted a good prognosis. Overexpression of circ_0009092 reduced tumor cell EMT, proliferation, migration, and invasion in vitro and in vivo. Mechanistically, circ_0009092 elevated the NLK expression via sponging miR-665 and suppressed the Wnt/β-catenin signaling pathway. EIF4EA3 induced circ_0009092 expression in CRC cells. In addition, NLK regulates phosphorylation and O-GlcNAcylation of STAT3 by binding to STAT3, thereby inhibiting CCL2 expression, in which it inhibits macrophage recruitment in the tumor microenvironment (TME). Conclusion EIF4A3 suppressed circ_0009092 biogenesis, whichinhibits CRC progression by sponging miR-665 to downregulate NLK. Circ_0009092/miR-665/NLK suppressed tumor EMT, proliferation, migration, and invasion by acting on the Wnt/β-catenin signaling pathway. NLK directly interacted with STAT3 and decreased the CCL2 expression, inhibiting the recruitment of tumor-associated macrophages (TAMs) in the TME. Our study provided novel insights into the roles of circ_0009092 as a novel promising prognostic and therapeutic target in CRC.

Abstract As a major neuron type in the brain, the excitatory neuron (EN) regulates the lifespan in C. elegans. How the EN acquires senescence, however, is unknown. Here, we show that growth differentiation factor 11 (GDF11) is predominantly expressed in the EN in the adult mouse, marmoset and human brain. In mice, selective knock-out of GDF11 in the post-mitotic EN shapes the brain ageing-related transcriptional profile, induces EN senescence and hyperexcitability, prunes their dendrites, impedes their synaptic input, impairs object recognition memory and shortens the lifespan, establishing a functional link between GDF11, brain ageing and cognition. In vitro GDF11 deletion causes cellular senescence in Neuro-2a cells. Mechanistically, GDF11 deletion induces neuronal senescence via Smad2-induced transcription of the pro-senescence factor p21. This work indicates that endogenous GDF11 acts as a brake on EN senescence and brain ageing.

In order to fully understand the research progress of human factors and traffic safety in curve driving, from the perspective of driver-vehicle-road-environment dynamic traffic system, this paper explored the current research status and development trend of human factors of curve driving, and displayed the development process and structural relationship of human factors research of curve driving by using scientific knowledge map. Through the core collection database of Web of Science, 1408 English literatures related to human factors research of curve driving published from 2012 to 2022 (as of October 1, 2022) were obtained, and the literatures in this field were sorted and analyzed based on the VOSviewer visualization software. The results show that China, Tongji University and Accident Analysis and Prevention are the country, institution and journal with the largest contribution rate in the field of human factors research on curve driving. Co-citation analysis shows that the research contents in this field are divided into 5 clusters: driver's visual characteristics, risk of collision, vehicle dynamics characteristics, the influence of traffic engineering facilities on driving behavior, selection of driving speed. The co-occurrence analysis of keywords shows that the topics of curve geometry design and vehicle dynamics, driving behavior and risk, driving speed and safety, behavior prediction and intervention measures are the current research hotspots in the research field. It is found that the development trend of traffic safety improvement in curves is to construct a continuous, consistent, multi-level visual reference frame conforming to driving expectation through visual guiding technology, and summarizes the technical concept of linear visual guidance. This study can provide a reference for the study of human factors of curve driving.

Abstract Background Energy homeostasis is essential for the adaptation of animals to their environment and some wild animals keep low metabolism adaptive to their low-nutrient dietary supply. Giant panda is such a typical low-metabolic mammal exhibiting species specialization of extremely low daily energy expenditure. It has low levels of basal metabolic rate, thyroid hormone, and physical activities, whereas the cellular bases of its low metabolic adaptation remain rarely explored. Results In this study, we generate a single-nucleus transcriptome atlas of 21 organs/tissues from a female giant panda. We focused on the central metabolic organ (liver) and dissected cellular metabolic status by cross-species comparison. Adaptive expression mode (i.e., AMPK related) was prominently displayed in the hepatocyte of giant panda. In the highest energy-consuming organ, the heart, we found a possibly optimized utilization of fatty acid. Detailed cell subtype annotation of endothelial cells showed the uterine-specific deficiency of blood vascular subclasses, indicating a potential adaptation for a low reproductive energy expenditure. Conclusions Our findings shed light on the possible cellular basis and transcriptomic regulatory clues for the low metabolism in giant pandas and helped to understand physiological adaptation response to nutrient stress.

The traditional Satcom-on-the-Move (SOTM) mechanical structure consists of a dual-axis configuration with an azimuth axis and a pitch axis. In this structure, when the pitch angle is 90 degrees, the rotation of the azimuth axis cannot change the antenna’s direction. To solve this issue, a three-axis SOTM mechanical structure has been developed. The traditional three-axis SOTM servo control system adopts a closed-loop control scheme. In this scheme, due to the difficulty in directly obtaining the antenna’s rotation angle, the angles of rotation for each axis are typically selected to represent the antenna’s rotation angle. The closed-loop feedback includes the angles and angular velocities of the axes, which cannot completely capture the antenna’s motion state, essentially constituting an indirect closed-loop control. Addressing the shortcomings of this indirect closed-loop control, this paper first establishes the kinematic relations between the axes of the three-axis SOTM antenna using the Denavit–Hartenberg (DH) method. Subsequently, the relationship between antenna pointing and the rotational states of the three axes was derived using the Jacobian operator. Building upon this foundation, a direct closed-loop control structure for a three-axis SOTM antenna was designed. To enable the control system to achieve rapid convergence with minimal overshoot, an Active Disturbance Rejection Control (ADRC) algorithm based on smooth continuous functions is introduced as the inner and outer loop controller algorithms within the direct closed-loop control structure. To address the nonlinearity in the design scheme, a piecewise linearization method is proposed to reduce the demands on the microprocessor’s performance and enhance the engineering feasibility of the solution. Finally, the effectiveness of the proposed approach is validated through experiments. The experimental results demonstrate that compared to traditional indirect closed-loop control methods, utilizing the direct closed-loop control method for the three-axis SOTM antenna presented in this paper can lead to higher precision in pointing the antenna towards satellites and enhance communication effectiveness.