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Pine Island Glacier (PIG), the largest glacier in the Amundsen Sea Embayment of West Antarctica, has contributed to over a quarter of the observed sea level rise around Antarctica. In recent years, multiple observations have confirmed its continuous retreat, ice flow acceleration and profound surface melt. Understanding these changes is crucial for accurately monitoring ice mass discharge and future Antarctic contributions to sea level rise. Therefore, it is essential to investigate the complex interactions between these variables to comprehend how they collectively affect the overall stability of the intricate PIG system. In this study, we utilized high-resolution remote sensing data and deep learning method to detect and analyze the spatio-temporal variations of surface melt, ice shelf calving, and ice flow velocity of the PIG from 2015 to 2023. We explored the correlations among these factors to understand their long-term impacts on the glacier's stability. Our findings reveal a retreat of 26.3 km and a mass loss of 1001.6 km2 during 2015–2023. Notably, extensive surface melting was observed, particularly in the 2016/2017 and 2019/2020 melting seasons. Satellite data vividly illustrate prolonged and intense melting periods, correlating with a significant retreat in the glacier's terminus position in 2019/2020. Furthermore, the comprehensive analysis of surface melting and the cumulative retreat of the ice shelf from 2017 to 2020 on the PIG shows a temporal relationship with subsequent significant changes in ice flow velocity, ranging from 10.9 to 12.2 m d−1, with an average acceleration rate of 12%. These empirical findings elucidate the intricate relationship among surface melt, ice flow velocity, and consequential glacier dynamics. A profound understanding of these interrelationships holds paramount importance in glacier dynamic changes and modeling, providing invaluable insights into potential glacier responses to global climate change.

Abstract Background Obesity is a global health issue with detrimental effects on various human organs, including the reproductive system. Observational human data and several lines of animal experimental data suggest that maternal obesity impairs ovarian function and early embryo development, but the precise pathogenesis remains unclear. Methods We established a high-fat diet (HFD)-induced obese female mouse model to assess systemic metabolism, ovarian morphology, and oocyte function in mice. For the first time, this study employed single-cell RNA sequencing to explore the altered transcriptomic landscape of preimplantation embryos at different stages in HFD-induced obese mice. Differential gene expression analysis, enrichment analysis and protein-protein interactions network analysis were performed. Results HFD-induced obese female mice exhibited impaired glucolipid metabolism and insulin resistance. The ovaries of HFD mice had a reduced total follicle number, an increased proportion of atretic follicles, and irregular granulosa cell arrangement. Furthermore, the maturation rate of embryonic development by in vitro fertilization of oocytes was significantly decreased in HFD mice. Additionally, the transcriptional landscapes of preimplantation embryos at different stages in mice induced by different diets were significantly distinguished. The maternal-to-zygotic transition was also affected by the failure to remove maternal RNAs and to turn off zygotic genome expression. Conclusions HFD-induced obesity impaired ovarian morphology and oocyte function in female mice and further led to alterations in the transcriptional landscape of preimplantation embryos at different stages of HFD mice.

[Introduction] In order to improve heat exchange efficiency, the condensate pipelines, main water supply pipelines drain pipelines and partial extraction pipelines of nuclear power plants are all coated outside the pipelines. At present, the test methods of ferromagnetic pipelines are mainly conventional ultrasound and ultrasonic guided waves. These test methods are limited by the detection environment and preconditions, which increase the difficulty of test. In order to improve the test efficiency of pipelines with insulation layer, we shall enrich technical methods, shorten maintenance period and improve economic benefit of nuclear power plant. [Method] This paper mainly studied the feasibility and reliability of pulsed eddy current testing method under low frequency electromagnetic interference in nuclear power plant, and used the measured and calculated values of the induced voltage to establish the optimal parameter inversion problem. In combination with the coupling relationship between the parameters and based on the time-domain analytical solution of the pipeline pulsed eddy current field, the paper established the specific relationship between the measured value and the calculated value of the induced voltage, and established the optimization parameter inversion problem. In combination with the coupling relationship between the parameters, the paper proposed a pulsed eddy current detection method for in-service operation and maintenance of insulated pipes in nuclear power plants. [Result] Using the pulsed eddy current detection method for the relative wall thickness of ferromagnetic pipelines proposed in this paper, in-service sample pipelines of nuclear power plant are tested and the testing result is compared with conventional ultrasonic testing. The error of the two testing results is about 5%. [Conclusion] The testing results of impulse eddy current testing are reliable and it is suitable for non-destructive testing and evaluation of nuclear power plant ferromagnetic pipeline wall thickness corrosion thinning.

[Introduction] In the nuclear power plant, the steam pipeline is generally installed with an insulation layer on the outer wall to improve heat transfer efficiency. Currently, the main detection means for ferromagnetic pipelines are conventional ultrasound and ultrasonic guided waves. Prior to the inspection, the insulation layer on the outer wall of the pipeline needs to be removed, leading to extended inspection time, increased labor costs, and an inability to meet the requirements for high-quality development in nuclear power plants. The application of the pulsed eddy current (PEC) technique for nuclear power plants can eliminate the need for insulation layer removal, enabling non-stop online screening. The defects testing by coil placement is an essential indicator of the PEC technique. [Method] In this paper, the modeling and simulation of the pipelines was conducted by applying ANSYS Maxwell, coaxial and vertical detection coils were designed respectively to simulate the detection capability of PEC on flat bottom defects with consistency in the lift-off distance, materials and other conditions. Sample pipes were selected from the nuclear power plant for coaxial and vertical PEC testing. The pulsed eddy current testing (PECT) results were cross-validated with ultrasonic thickness measurement, and the effects of two coil placement methods on PECT were compared. [Result] The results show that vertical coils are more effective in defect detection compared to coaxial coils. [Conclusion] The defects testing by coil placement has great significance for implementing PEC in the nuclear power sector.

Abstract The second-order nonlinear Hall effect (NLHE) in non-centrosymmetric materials has recently drawn intense interest, since its inherent rectification could enable various device applications such as energy harvesting and wireless charging. However, previously reported NLHE systems normally suffer from relatively small Hall voltage outputs and/or low working temperatures. In this study, we report the observation of a pronounced NLHE in tellurium (Te) thin flakes at room temperature. Benefiting from the semiconductor nature of Te, the obtained nonlinear response can be readily enhanced through electrostatic gating, leading to a second-harmonic output at 300 K up to 2.8 mV. By utilizing such a giant NLHE, we further demonstrate the potential of Te as a wireless Hall rectifier within the radiofrequency range, which is manifested by the remarkable and tunable rectification effect also at room temperature. Extrinsic scattering is then revealed to be the dominant mechanism for the NLHE in Te, with symmetry breaking on the surface playing a key role. As a simple elemental semiconductor, Te provides an appealing platform to advance our understanding of nonlinear transport in solids and to develop NLHE-based electronic devices.

Abstract Background Neuronal guanine nucleotide exchange factor (NGEF) plays a key role in several cancers; however, its role in lung adenocarcinoma (LUAD) remains unclear. The aim of this study was to evaluate the efficacy of NGEF as a prognostic biomarker and potential therapeutic target for LUAD. Methods NGEF expression data for multiple cancers and LUAD were downloaded from multiple databases. The high- and low-NGEF expression groups were constructed based on median NGEF expression in LUAD samples, and then performed Kaplan–Meier survival analysis. Differentially expressed genes (DEGs) from the two NGEF expression groups were screened and applied to construct a protein-protein interaction network. The primary pathways were obtained using gene set enrichment analysis. The associations between NGEF expression and clinical characteristics, immune infiltration, immune checkpoint inhibitors (ICIs), sensitivity to chemotherapy, and tumor mutation burden (TMB) were investigated using R. Levels of NGEF expression in the lung tissue was validated using single-cell RNA sequencing, quantitative polymerase chain reaction (qPCR), immunohistochemical staining, and western blot analysis. Results The expression of NGEF mRNA was upregulated in multiple cancers. mRNA and protein expression levels of NGEF were higher in patients with LUAD than in controls, as validated using qPCR and western blot. High NGEF expression was an independent prognostic factor for LUAD and was associated with advanced tumor stage, large tumor size, more lymph node metastasis, and worse overall survival (OS). A total of 182 overlapping DEGs were screened between The Cancer Genome Atlas and GSE31210, among which the top 20 hub genes were identified. NGEF expression was mainly enriched in the pathways of apoptosis, cell cycle, and DNA replication. Moreover, elevated NGEF expression were associated with a high fraction of activated memory CD4+ T cells and M0 macrophages; elevated expression levels of the ICIs: programmed cell death 1 and programmed cell death 1 ligand 1 expression; higher TMB; and better sensitivity to bortezomib, docetaxel, paclitaxel, and parthenolide, but less sensitivity to axitinib and metformin. Conclusion NGEF expression is upregulated in LUAD and is significantly associated with tumor stages, OS probability, immune infiltration, immunotherapy response, and chemotherapy response. NGEF may be a potential diagnostic and prognostic biomarker and therapeutic target in LUAD.

Abstract Conventional material processing approaches often achieve strengthening of materials at the cost of reduced ductility. Here, we show that high-pressure and high-temperature (HPHT) treatment can help overcome the strength-ductility trade-off in structural materials. We report an initially strong-yet-brittle eutectic high entropy alloy simultaneously doubling its strength to 1150 MPa and its tensile ductility to 36% after the HPHT treatment. Such strength-ductility synergy is attributed to the HPHT-induced formation of a hierarchically patterned microstructure with coherent interfaces, which promotes multiple deformation mechanisms, including dislocations, stacking faults, microbands and deformation twins, at multiple length scales. More importantly, the HPHT-induced microstructure helps relieve stress concentration at the interfaces, thereby arresting interfacial cracking commonly observed in traditional eutectic high entropy alloys. These findings suggest a new direction of research in employing HPHT techniques to help develop next generation structural materials.

Abstract Objective Alcohol withdrawal syndrome (AWS) is a complex condition associated with alcohol use disorder (AUD), characterized by significant variations in symptom severity among patients. The psychological and emotional symptoms accompanying AWS significantly contribute to withdrawal distress and relapse risk. Despite the importance of neural adaptation processes in AWS, limited genetic investigations have been conducted. This study primarily focuses on exploring the single and interaction effects of single-nucleotide polymorphisms in the ANK3 and ZNF804A genes on anxiety and aggression severity manifested in AWS. By examining genetic associations with withdrawal-related psychopathology, we ultimately aim to advance understanding the genetic underpinnings that modulate AWS severity. Methods The study involved 449 male patients diagnosed with alcohol use disorder. The Self-Rating Anxiety Scale (SAS) and Buss-Perry Aggression Questionnaire (BPAQ) were used to assess emotional and behavioral symptoms related to AWS. Genomic DNA was extracted from peripheral blood, and genotyping was performed using PCR. Results Single-gene analysis revealed that naturally occurring allelic variants in ANK3 rs10994336 (CC homozygous vs. T allele carriers) were associated with mood and behavioral symptoms related to AWS. Furthermore, the interaction between ANK3 and ZNF804A was significantly associated with the severity of psychiatric symptoms related to AWS, as indicated by MANOVA. Two-way ANOVA further demonstrated a significant interaction effect between ANK3 rs10994336 and ZNF804A rs7597593 on anxiety, physical aggression, verbal aggression, anger, and hostility. Hierarchical regression analyses confirmed these findings. Additionally, simple effects analysis and multiple comparisons revealed that carriers of the ANK3 rs10994336 T allele experienced more severe AWS, while the ZNF804A rs7597593 T allele appeared to provide protection against the risk associated with the ANK3 rs10994336 mutation. Conclusion This study highlights the gene-gene interaction between ANK3 and ZNF804A, which plays a crucial role in modulating emotional and behavioral symptoms related to AWS. The ANK3 rs10994336 T allele is identified as a risk allele, while the ZNF804A rs7597593 T allele offers protection against the risk associated with the ANK3 rs10994336 mutation. These findings provide initial support for gene-gene interactions as an explanation for psychiatric risk, offering valuable insights into the pathophysiological mechanisms involved in AWS.

This study presents a comprehensive transcriptome analysis of canine intestinal epithelial cells following treatment with sulforaphane (SFN), a naturally occurring compound found in cruciferous vegetables with established anti-inflammatory and antioxidant properties. Through high-throughput sequencing, we identified 29,993 genes, among which 1,612 were differentially expressed, with 792 up-regulated and 820 down-regulated in response to SFN treatment. Our analysis revealed significant enrichment of genes in pathways associated with the inflammatory response, lipid metabolism, oxidative stress response, and T-cell mediated immunity, suggesting SFN’s potential in modulating these biological processes. Notably, the PPARγ gene, which plays a crucial role in the body’s oxidative stress and inflammatory response, was highly up-regulated, indicating its possible centrality in SFN’s effects. Gene–gene interaction analysis further supported SFN’s role in alleviating inflammation through PPARγ, with key genes in oxidative stress and inflammatory response pathways showing significant correlations with PPARγ. Overall, our findings provide molecular evidence for SFN’s protective effects on canine intestinal health, potentially through the modulation of inflammatory and oxidative stress pathways, with PPARγ emerging as a critical mediator.

Aim: Parkinson's disease (PD) tremor is associated with dysfunction in the basal ganglia (BG), cerebellum (CB), and sensorimotor networks (SMN). We investigated tremor-related static functional network connectivity (SFNC) and dynamic functional network connectivity (DFNC) in PD patients. Methods: We analyzed the resting-state functional MRI data of 21 tremor-dominant Parkinson's disease (TDPD) patients and 29 healthy controls. We compared DFNC and SFNC between the three networks and assessed their associations with tremor severity. Results: TDPD patients exhibited increased SFNC between the SMN and BG networks. In addition, they spent more mean dwell time (MDT) in state 2, characterized by sparse connections, and less MDT in state 4, indicating stronger connections. Furthermore, enhanced DFNC between the CB and SMN was observed in state 2. Notably, the MDT of state 2 was positively associated with tremor scores. Conclusion: The enhanced dynamic connectivity between the CB and SMN in TDPD patients suggests a potential compensatory mechanism. However, the tendency to remain in a state of sparse connectivity may contribute to the severity of tremor symptoms.

A clear understanding of the interactions at multiple scales among ecosystem services (ESs) is essential to the reasonable spatial planning of ecosystems in large-scale ecological barrier regions. This study assessed the provision of 5 typical ESs: water yield (WY), soil conservation (SC), crop production (CP), net primary productivity (NPP), and habitat quality (HQ). We explored the tradeoff/synergy relationship, mapped the bundles and analyzed their underlying socioecological influencing factors at both grid and watershed scales in the northeast forest belt (NFB). Furthermore, we provided a spatial planning and management strategy of NFB and suggested concrete practices within the range of identified ecological bundles. Our results showed that WY, SC and CP presented an obvious spatiotemporal heterogeneity while NPP and HQ only exhibited spatial heterogeneity at both gird and watershed scales. Divergences were observed in correlations between provisioning and regulating service pairs. Specifically, CP-related correlations were all negative and WY-related correlations varied depending on the combination of ES pairs, time, and scale. Notably, the absolute value of most ES pairs increased from the grid to the watershed scale, indicating a clear scale dependence. Moreover, six ES bundles (ESBs) varying spatially during the study period were further identified at both the grid and watershed scale in NFB, respectively. Geodetector analysis revealed that ESs at the grid scale shared similar determinants with those at the watershed scale, albeit with slight variations in ranking or the number of determinants. Our findings offer detailed insights for incorporating ES interactions into spatially targeted ecosystem management and future ES payment policies.

BackgroundCardioembolic Stroke (CS) and Atrial Fibrillation (AF) are prevalent diseases that significantly impact the quality of life and impose considerable financial burdens on society. Despite increasing evidence of a significant association between the two diseases, their complex interactions remain inadequately understood. We conducted bioinformatics analysis and employed machine learning techniques to investigate potential shared biomarkers between CS and AF.MethodsWe retrieved the CS and AF datasets from the Gene Expression Omnibus (GEO) database and applied Weighted Gene Co-Expression Network Analysis (WGCNA) to develop co-expression networks aimed at identifying pivotal modules. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the shared genes within the modules related to CS and AF. The STRING database was used to build a protein-protein interaction (PPI) network, facilitating the discovery of hub genes within the network. Finally, several common used machine learning approaches were applied to construct the clinical predictive model of CS and AF. ROC curve analysis to evaluate the diagnostic value of the identified biomarkers for AF and CS.ResultsFunctional enrichment analysis indicated that pathways intrinsic to the immune response may be significantly involved in CS and AF. PPI network analysis identified a potential association of 4 key genes with both CS and AF, specifically PIK3R1, ITGAM, FOS, and TLR4.ConclusionIn our study, we utilized WGCNA, PPI network analysis, and machine learning to identify four hub genes significantly associated with CS and AF. Functional annotation outcomes revealed that inherent pathways related to the immune response connected to the recognized genes might could pave the way for further research on the etiological mechanisms and therapeutic targets for CS and AF.

Abstract Background The preparation of the middle mesial (MM) canal of mandibular molars represents a challenge because it is often curved, narrow, and close to the root concave. The purpose of this study was to evaluate the ex vivo shaping ability of 3 nickel-titanium (NiTi) rotary systems in the MM canal using 3D printed resin tooth replicas. Methods A permanent mandibular first molar with a MM canal was acquired from a pool of extracted teeth and reproduced by a 3D printer. The resin tooth replicas (n = 18) were equally assigned to 3 groups for the evaluation of the shaping abilities of 3 NiTi rotary systems (OneShape [OS], Twisted Files [TF], and ProTaper Gold [PTG]) according to the manufacturer’s recommendations. The tooth replicas were scanned by micro-computed tomography (micro-CT) twice before and after instrumentation of the mesiobuccal (MB), mesiolingual (ML), and MM root canals. After 3D reconstruction, the canal straightening, change of root canal volume and surface area, the mesial and distal canal wall thickness and canal transportation at the levels of 1, 2, and 3 mm below furcation were assessed. One-way variance analysis and Turkey’s post hoc test were used for comparisons of the means among different groups, and paired-t test was used to compare the mesial and distal sides of the mesial roots. Results As compared with OS and TF, the use of PTG in preparation of MM canals resulted in significantly more straightening of canal curvature (p 0.05) after the preparation of the MB and ML canals. However, in the MM canal, more pronounced transportation was detected in the PTG group at 2 mm below furcation, and in the TF group at 3 mm below furcation as compared with the other 2 systems (both p

Abstract In the realm of robotics and automation, robot teleoperation, which facilitates human–machine interaction in distant or hazardous settings, has surged in significance. A persistent issue in this domain is the delays between command issuance and action execution, causing negative repercussions on operator situational awareness, performance, and cognitive load. These delays, particularly in long-distance operations, are difficult to mitigate even with the most advanced computing advancements. Current solutions mainly revolve around machine-based adjustments to combat these delays. However, a notable lacuna remains in harnessing human perceptions for an enhanced subjective teleoperation experience. This paper introduces a novel approach of sensory manipulation for induced human adaptation in delayed teleoperation. Drawing from motor learning and rehabilitation principles, it is posited that strategic sensory manipulation, via altered sensory stimuli, can mitigate the subjective feeling of these delays. The focus is not on introducing new skills or adapting to novel conditions; rather, it leverages prior motor coordination experience in the context of delays. The objective is to reduce the need for extensive training or sophisticated automation designs. A human-centered experiment involving 41 participants was conducted to examine the effects of modified haptic cues in teleoperations with delays. These cues were generated from high-fidelity physics engines using parameters from robot-end sensors or physics engine simulations. The results underscored several benefits, notably the considerable reduction in task time and enhanced user perceptions about visual delays. Real-time haptic feedback, or the anchoring method, emerged as a significant contributor to these benefits, showcasing reduced cognitive load, bolstered self-confidence, and minimized frustration. Beyond the prevalent methods of automation design and training, this research underscores induced human adaptation as a pivotal avenue in robot teleoperation. It seeks to enhance teleoperation efficacy through rapid human adaptation, offering insights beyond just optimizing robotic systems for delay compensations.

Abstract The catalytic valorisation of biomass to afford synthetically useful small molecules is essential for sustainable biorefinery processes. Herein, we present a mild cascaded electrochemical protocol for converting furoic acid, a common biomass-derived feedstock, into a versatile platform chemical, gamma-butyrolactone. In the platinum(+)|nickel(−) electrode paired undivided cell, furoic acid is electrochemically oxidised with 84.2% selectivity to 2(5H)-furanone, the olefin of which is then hydrogenated to yield gamma-butyrolactone with 98.5% selectivity. The final gamma-butyrolactone yield is 69.1% with 38.3% Faradaic efficiency and 80.1% carbon balance when the reaction is performed with 100 mM furoic acid at 80 °C at +2.0 VAg/AgCl. Mechanistic investigation revealed the critical temperature and electrolyte pH conditions that maximise the production and protection of the key intermediate, furan radical, promoting its transition to 2(5H)-furanone rather than self-polymerising. The reaction is scalable, as 2.1 g of 98.1% pure gamma-butyrolactone is isolated through a simple solvent extraction.

Abstract Aberrant upregulation of the ubiquitin-specific protease 14 (USP14) has been found in some malignant tumors, including oral squamous cell carcinoma (OSCC). In this study, we further demonstrated that aberrantly overexpressed USP14 was also closely related to adverse clinicopathological features and poor prognosis in patients with OSCC, so we hypothesized that USP14 might act as a tumor-promoting factor during the progression of OSCC. Notably, we originally proved that USP14 is a deubiquitinating enzyme for phosphofructokinase-1 liver type (PFKL), a key rate-limiting enzyme involved in the glycolytic pathway. USP14 interacts with PFKL and enhances its stability through deubiquitination in OSCC cells, which in turn enhances PFKL-mediated glycolytic metabolism and ultimately promote cellular proliferation, migration, and tumorigenesis. In this work, we have also demonstrated for the first time that USP14 is a critical regulator of glycolysis in OSCC and verified a novel mechanism whereby it is involved in tumor metastasis and growth. Collectively, our findings provide novel insights into the tumor-promoting role of USP14 and establish mechanistic foundations for USP14-targeting therapies.

IntroductionAs robot teleoperation increasingly becomes integral in executing tasks in distant, hazardous, or inaccessible environments, operational delays remain a significant obstacle. These delays, inherent in signal transmission and processing, adversely affect operator performance, particularly in tasks requiring precision and timeliness. While current research has made strides in mitigating these delays through advanced control strategies and training methods, a crucial gap persists in understanding the neurofunctional impacts of these delays and the efficacy of countermeasures from a cognitive perspective.MethodsThis study addresses the gap by leveraging functional Near-Infrared Spectroscopy (fNIRS) to examine the neurofunctional implications of simulated haptic feedback on cognitive activity and motor coordination under delayed conditions. In a human-subject experiment (N = 41), sensory feedback was manipulated to observe its influences on various brain regions of interest (ROIs) during teleoperation tasks. The fNIRS data provided a detailed assessment of cerebral activity, particularly in ROIs implicated in time perception and the execution of precise movements.ResultsOur results reveal that the anchoring condition, which provided immediate simulated haptic feedback with a delayed visual cue, significantly optimized neural functions related to time perception and motor coordination. This condition also improved motor performance compared to the asynchronous condition, where visual and haptic feedback were misaligned.DiscussionThese findings provide empirical evidence about the neurofunctional basis of the enhanced motor performance with simulated synthetic force feedback in the presence of teleoperation delays. The study highlights the potential for immediate haptic feedback to mitigate the adverse effects of operational delays, thereby improving the efficacy of teleoperation in critical applications.

Surface melt plays a vital role in impacting the polar mass balance and global sea level rise. Over the past decades, synthetic aperture radar (SAR) imagery has garnered considerable attention due to its capacity to provide high-precision and long-term information. However, the traditional SAR-based large-scale surface melt detection methods utilizing co-orbit normalization predominantly depend on reference images and the precise spatial registration to mitigate geometric distortions arising from diverse incidence angles. Consequently, both the absence of reference imagery and the movement of ice sheets and shelves present challenges to the method. In this study, we address this issue by developing a reference-free deep learning network integrating the Convolutional Block Attention Module (CBAM) into DeepLabv3+ to automatically detect surface melt and establishing the surface melt dataset based on multi-temporal Sentinel-1 SAR imagery, encompassing diverse surface conditions of the Antarctic. Our model achieves an accuracy of 95.67%, surpassing the reference-based method and an advanced deep learning-based approach by 4.23% and 4.67%, respectively. Moreover, compared to 500 m resolution UMelt product and the kilometer-level results obtained from Advanced Scatterometer (ASCAT) and Special Sensor Microwave Imager Sounder (SSMIS), our model demonstrates the capability to accurately capture the small-scale melting patterns of ice shelves with a higher spatial resolution of 40 m. Notably, our findings underscore the dispensability of reference imagery in traditional methods through the formidable information extraction capabilities of deep learning. We finally applied the proposed method to extract and analyze the spatiotemporal characteristics of surface melt on the Larsen C Ice Shelf during the 2019/2020 period. The corresponding code of this study is at https://github.com/Tangyu35/Surface-melt-detection.

Abstract Cache‐enabled device‐to‐device (D2D) network has been deemed as an effective technique to offload the data traffic. However, the gain of the caching schemes is closely related to the homogeneity among users' preference distribution. To tackle this issue, recommendation is a promising proactive approach. It increases the request probability of recommended contents, reshaping users' contents demand patterns, and improving caching performance. Moreover, considering the heterogeneous network settings, i.e. content retrieval costs vary, the routing design becomes a non‐negligible factor on caching performance optimization. On these grounds, the average system cost of D2D‐enabled wireless caching networks with multiple BSs is first described. Then the routing strategies are designed together with caching and recommendation policies by minimizing the average cost of these networks. The optimization problem is proven as NP‐hard. To facilitate the analysis, the original problem is decoupled into two sub‐problems and solve them respectively. Afterwards, all the variables are optimized in an alternating manner until the convergence is achieved. The proposed algorithm's convergence performance and benefits over benchmark strategies in terms of total cost and cache hit ratio are supported by Monte‐Carlo simulation results.

Ice shelves play an essential role in the dynamics of the Antarctic ice sheet. The surface meltwater is important, as it can irreversibly weaken ice shelves by exerting additional hydrostatic pressure. Therefore, high-resolution snowmelt products are urgently needed to accurately analyze melting patterns of ice shelves and further estimate mass loss. In this study, a new high-resolution (40 m) snowmelt dataset over all of the Antarctic Peninsula ice shelves larger than 100 km$^2$ was developed based on the modified snowmelt detection framework by using a co-orbit normalization method. The dataset provides detailed snowmelt information on each ice shelf, including the image coverage, melting area and melting ratio every 5 days. The melting patterns of three typical ice shelves (George VI, Wilkins and Larsen C Ice Shelves) and the spatio-temporal melting distribution of the Antarctic Peninsula (AP) were further analyzed. The snowmelt information indicates that both the extent and duration of snowmelt have been increasing in the Antarctic Peninsula from 2015 to 2021, and we found that the snowmelt on the Antarctic Peninsula showed a spatial pattern of significantly intense snowmelt on the western side. We believe this study will provide essential data for ice shelf investigation to support other fields of polar research.

Abstract Background Chinese indigenous pigs are popular with consumers for their juiciness, flavour and meat quality, but they have lower meat production. Insulin-like growth factor 2 (IGF2) is a maternally imprinted growth factor that promotes skeletal muscle growth by regulating cell proliferation and differentiation. A single nucleotide polymorphism (SNP) within intron 3 of porcine IGF2 disrupts a binding site for the repressor, zinc finger BED-type containing 6 (ZBED6), leading to up-regulation of IGF2 and causing major effects on muscle growth, heart size, and backfat thickness. This favorable mutation is common in Western commercial pig populations, but absent in most Chinese indigenous pig breeds. To improve meat production of Chinese indigenous pigs, we used cytosine base editor 3 (CBE3) to introduce IGF2-intron3-C3071T mutation into porcine embryonic fibroblasts (PEFs) isolated from a male Liang Guang Small Spotted pig (LGSS), and single-cell clones harboring the desired mutation were selected for somatic cell nuclear transfer (SCNT) to generate the founder line of IGF2 T/T pigs. Results We found the heterozygous progeny IGF2 C/T pigs exhibited enhanced expression of IGF2, increased lean meat by 18%–36%, enlarged loin muscle area by 3%–17%, improved intramuscular fat (IMF) content by 18%–39%, marbling score by 0.75–1, meat color score by 0.53–1.25, and reduced backfat thickness by 5%–16%. The enhanced accumulation of intramuscular fat in IGF2 C/T pigs was identified to be regulated by the PI3K-AKT/AMPK pathway, which activated SREBP1 to promote adipogenesis. Conclusions We demonstrated the introduction of IGF2-intron3-C3071T in Chinese LGSS can improve both meat production and quality, and first identified the regulation of IMF deposition by IGF2 through SREBP1 via the PI3K-AKT/AMPK signaling pathways. Our study provides a further understanding of the biological functions of IGF2 and an example for improving porcine economic traits through precise base editing.

Abstract Objective Develop and evaluate an ensemble clinical machine learning–deep learning (CML-DL) model integrating deep visual features and clinical data to improve the prediction of supraspinatus/infraspinatus tendon complex (SITC) injuries. Methods Patients with suspected SITC injuries were retrospectively recruited from two hospitals, with clinical data and shoulder x-ray radiographs collected. An ensemble CML-DL model was developed for diagnosing normal or insignificant rotator cuff abnormality (NIRCA) and significant rotator cuff tear (SRCT). All patients suspected with SRCT were confirmed by arthroscopy examination. The model’s performance was evaluated using sensitivity, specificity, accuracy, and area under the curve (AUC) metrics, and a two-round assessment was conducted to authenticate its clinical applicability. Results A total of 974 patients were divided into three cohorts: the training cohort (n = 828), the internal validation cohort (n = 89), and the external validation cohort (n = 57). The CML-DL model, which integrates clinical and deep visual features, demonstrated superior performance compared to individual models of either type. The model’s sensitivity, specificity, accuracy, and area under curve (95% confidence interval) were 0.880, 0.812, 0.836, and 0.902 (0.858–0.947), respectively. The CML-DL model exhibited higher sensitivity and specificity compared to or on par with the physicians in all validation cohorts. Furthermore, the assistance of the ensemble CML-DL model resulted in a significant improvement in sensitivity for junior physicians in all validation cohorts, without any reduction in specificity. Conclusions The ensembled CML-DL model provides a solution to help physicians improve the diagnosis performance of SITC injury, especially for junior physicians with limited expertise. Critical relevance statement The ensembled clinical machine learning–deep learning (CML-DL) model integrating deep visual features and clinical data provides a superior performance in the diagnosis of supraspinatus/infraspinatus tendon complex (SITC) injuries, particularly for junior physicians with limited expertise. Key points 1. Integrating clinical and deep visual features improves diagnosing SITC injuries. 2. Ensemble CML-DL model validated for clinical use in two-round assessment. 3. Ensemble model boosts sensitivity in SITC injury diagnosis for junior physicians. Graphical Abstract

Abstract Background Although gene expression data play significant roles in biological and medical studies, their applications are hampered due to the difficulty and high expenses of gathering them through biological experiments. It is an urgent problem to generate high quality gene expression data with computational methods. WGAN-GP, a generative adversarial network-based method, has been successfully applied in augmenting gene expression data. However, mode collapse or over-fitting may take place for small training samples due to just one discriminator is adopted in the method. Results In this study, an improved data augmentation approach MDWGAN-GP, a generative adversarial network model with multiple discriminators, is proposed. In addition, a novel method is devised for enriching training samples based on linear graph convolutional network. Extensive experiments were implemented on real biological data. Conclusions The experimental results have demonstrated that compared with other state-of-the-art methods, the MDWGAN-GP method can produce higher quality generated gene expression data in most cases.

With the rising popularity of pet cats as companion animals, the survival of newborn kittens is often threatened by factors such as inadequate nursing, maternal behavior and blood incompatibility. These challenges require the use of milk replacers for nurturing. To investigate the effects that feeding kittens with an experimental milk replacer (EMR) have on growth and development, intestinal microbiota, immune response and nutrient metabolism, 12 British shorthair kittens were randomly divided into two groups after nursing for the first week of life. Kittens were fed queen’s milk or EMR, whereby kittens fed queen’s milk served as the control (CON) group. The findings revealed that the CON group exhibited superoxide dismutase (SOD) activity and total antioxidant capacity (T-AOC) (p < 0.01) on day 7. However, the EMR group had better growth performance during the later stage of the experiment (p < 0.05); the immunocompetence and antioxidant capacity of the EMR group were not significantly different from those of the CON group in the middle and late stages of the experiment, and the mean values of all the indexes were slightly better than those of the control group. Sequencing of the 16S rRNA gene in microbiota demonstrated that EMR increased the colonization of bacterial genera, including Lachnospiraceae, Enterococcus, Rothia and Ligilactobacillus. Compared to the CON group, acetate acid (p < 0.05), propionate acid (p < 0.01) and total SCFAs (p < 0.01) in the EMR group were significantly increased. Moreover, the intake of the EMR resulted in the production of distinct metabolites implicated in the metabolism of lipids and amino acids, among other nutrients, thus invigorating the associated metabolic pathways. These results elucidate the impact of administering a milk replacer on gastrointestinal health and nutrient assimilation in kittens. The study provides insights into the use of milk powder alternatives and sets the stage for future research on the formulation and effectiveness of kitten milk replacers.

Integrated sensing and communication (ISAC) systems assisted by unmanned aerial vehicles (UAVs) are susceptible to eavesdropping, making secure information transmission a critical area of research. We propose a joint optimization algorithm to improve the security of UAV-assisted ISAC systems through coordinated adjustments of transmit beamforming and UAV position. The optimization problem aims to minimize the maximum eavesdropping signal-to-interference-plus-noise ratio (SINR) across multiple legitimate users while adhering to three distinct constraints: service quality for legitimate users, sensing requirements for detecting eavesdroppers, and limitations on system transmit power. To address the non-convex optimization challenge effectively, the problem is decomposed into sub-problems focusing on the optimization of transmit beamforming and UAV position. These sub-problems are solved using semidefinite relaxation (SDR), the Dinkelbach method, and successive convex approximation (SCA), with iterative alternation achieving optimal values for the transmit beamforming and UAV position while also proving the convergence of the algorithm. Lastly, simulation results illustrate that the proposed algorithm markedly improves the system’s security performance while preserving its communication and sensing capabilities.

Background: The involvement of molecules associated with PANoptosis in hepatocellular carcinoma (HCC) is still not well understood. Methods: Various R packages were utilized to analyze within the R software. Data that was freely accessible was obtained from the databases of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Results: Here, we comprehensively explored the role of PANoptosis-related genes in HCC. The caspase 2 (CASP2) was identified as the interest gene for further analysis. We found that CASP2 is related to the poor prognosis and worse clinical features of HCC patients. Moreover, we explored the biological pathway CASP2 is involved in and found that CASP2 is associated with multiple carcinogenic pathways. Also, we noticed that CASP2 can significantly reshape the HCC immune microenvironment and affect the response rate of immunotherapy. Analysis of drug sensitivity suggested that individuals exhibiting elevated CASP2 levels may display increased susceptibility to doxorubicin and vorinostat while demonstrating resistance towards erlotinib, lapatinib, sunitinib, and temsirolimus. Meanwhile, we explored the single-cell distribution of CASP2 in the HCC microenvironment. To enhance the clinical application of CASP2 in HCC, we constructed a prognosis model using the molecules derived from CASP2, which demonstrated good efficiency in predicting patients prognosis. Moreover, in vitro experiments indicated that CASP2 can significantly inhibits cell proliferation, invasion and migration ability of HCC cells. Conclusions: Our study comprehensively explored the role of PANoptosis-related molecule CASP2 in HCC, which can provide directions for future studies.

Autoimmune hepatitis (AIH) is a chronic inflammatory disease of the liver that is mediated by autoimmunity and has complex pathogenesis. Its prevalence has increased globally. Since the liver is the first organ to be exposed to harmful substances, such as gut-derived intestinal microbiota and its metabolites, gut health is closely related to liver health, and the “liver-gut axis” allows abnormalities in the gut microbiota to influence the development of liver-related diseases such as AIH. Changes in the composition of the intestinal microbiota and its resultant disruption of the intestinal barrier and microbial transport are involved in multiple ways in the disruption of immune homeostasis and inflammation, thereby influencing the development of AIH. In terms of the mechanisms involved in immune, the gut microbiota or its metabolites, which is decreased in secondary bile acids, short-chain fatty acids (SCFAs), and polyamines, and increased in lipopolysaccharide (LPS), branched-chain amino acids (BCAA), tryptophan metabolite, amino acid, and bile acid, can disrupt immune homeostasis by activating various immune cells and immune-related signaling pathways, resulting in aberrant activation of the immune system. Clarifying this mechanism has significant clinical implications for the treatment of AIH with drugs that target intestinal microbiota and related signaling pathways. Therefore, this narrative review summarizes the progress in exploring the involvement of gut microbiota in the pathogenesis of AIH, with the aim of helping to improve the precise targeting of therapeutic treatments against AIH for the benefit of clinical AIH treatment.

Abstract Objectives Ankylosing spondylitis (AS) is a chronic inflammatory disease that mainly affects the sacroiliac joint and spine. However, the real mechanisms of immune cells acting on syndesmophyte formation in AS are not well identified. We aimed to find the key AS-associated cytokine and assess its pathogenic role in AS. Methods A protein array with 1000 cytokines was performed in five AS patients with the first diagnosis and five age- and gender-matched healthy controls to discover the differentially expressed cytokines. The candidate differentially expressed cytokines were further quantified by multiplex protein quantitation (3 AS-associated cytokines and 3 PDGF-pathway cytokines) and ELISA (PDGFB) in independent samples (a total of 140 AS patients vs 140 healthy controls). The effects of PDGFB, the candidate cytokine, were examined by using adipose-derived stem cells (ADSCs) and human fetal osteoblast cell line (hFOB1.19) as in vitro mesenchymal cell and preosteoblast models, respectively. Furthermore, whole-transcriptome sequencing and enrichment of phosphorylated peptides were performed by using cell models to explore the underlying mechanisms of PDGFB. The xCELLigence system was applied to examine the proliferation, chemotaxis, and migration abilities of PDGFB-stimulated or PDGFB-unstimulated cells. Results The PDGF pathway was observed to have abnormal expression in the protein array, and PDGFB expression was further found to be up-regulated in 140 Chinese AS patients. Importantly, PDGFB expression was significantly correlated with BASFI (Pearson coefficient/p value = 0.62/6.70E − 8) and with the variance of the mSASSS score (mSASSS 2 years − baseline, Pearson coefficient/p value = 0.76/8.75E − 10). In AS patients, preosteoclasts secreted more PDGFB than the healthy controls (p value = 1.16E − 2), which could promote ADSCs osteogenesis and enhance collagen synthesis (COLI and COLIII) of osteoblasts (hFOB 1.19). In addition, PDGFB promoted the proliferation, chemotaxis, and migration of ADSCs. Mechanismly, in ADSCs, PDGFB stimulated ERK phosphorylation by upregulating GRB2 expression and then increased the expression of RUNX2 to promote osteoblastogenesis of ADSCs. Conclusion PDGFB stimulates the GRB2/ERK/RUNX2 pathway in ADSCs, promotes osteoblastogenesis of ADSCs, and enhances the extracellular matrix of osteoblasts, which may contribute to pathological bone formation in AS.

Abstract Krüppel-like factor 4 (KLF4) is an evolutionarily conserved zinc finger-containing transcription factor that regulates diverse cellular processes such as cell proliferation, apoptosis, and differentiation. Our previous study showed that KLF4 expression is upregulated in skeletal muscle ontogeny during embryonic development in pigs, suggesting its importance for skeletal muscle development and muscle function. We revealed here that KLF4 plays a critical role in skeletal muscle development and regeneration. Specific knockout of KLF4 in skeletal muscle impaired muscle formation further affecting physical activity and also defected skeletal muscle regeneration. In vitro, KLF4 was highly expressed in proliferating myoblasts and early differentiated cells. KLF4 knockdown promoted myoblast proliferation and inhibited myoblast fusion, while its overexpression showed opposite results. Mechanically, in proliferating myoblasts, KLF4 inhibits myoblast proliferation through regulating cell cycle arrest protein P57 by directly targeting its promoter; while in differentiated myoblasts, KLF4 promotes myoblast fusion by transcriptionally activating Myomixer. Our study provides mechanistic information for skeletal muscle development, reduced muscle strength and impaired regeneration after injury and unveiling the mechanism of KLF4 in myogenic regulation.

Abstract Background In recent years, cone-beam computed tomography (CBCT) has been widely used to evaluate patients’ root canal anatomy due to its high resolution and noninvasive nature. As voxel size is one of the most important parameters affecting CBCT image quality, the current study evaluated the diagnostic potential of CBCT with 4 different voxel sizes in the detection of double root canal systems and accessory canals (ACs) in permanent mandibular incisors. Methods A total of 106 extracted mandibular permanent incisors were collected from the dental clinics, and then were scanned by using micro-CT with a voxel size of 9 μm. The teeth were then fixed in the tooth sockets of human dry mandibles and scanned by using a CBCT device with 4 different voxel sizes (300, 200, 250, and 125 μm). Four observers detected in blind the root canal morphology of the teeth according to the CBCT images, and the presence or absence of a double root canal system, and the presence or absence of ACs, were scored according to a 5-point scale, respectively. Receiver operating characteristic (ROC) analysis was performed, and DeLong test was used to compare the area under the curve (AUC) values and the micro-CT data was taken as a gold standard. Results Among 106 sample teeth, 25 specimens with a double root canal system were identified by the micro-CT. ROC curve analysis of the data obtained by the four observers showed that in the detection of double root canal systems, the AUC values ranged from 0.765 to 0.889 for 300 μm voxel size, from 0.877 to 0.926 for 250 μm voxel size, from 0.893 to 0.967 for 200 μm voxel size, and from 0.914 to 0.967 for 125 μm voxel size (all p

Electron diffusion caused by plasmaspheric hiss is an important mechanism for the loss of electrons in Earth's inner magnetosphere; it has also been considered responsible for the formation of the slot region between inner and outer radiation belts. The cold plasma dispersion relation of plasmaspheric hiss is widely used to quantify the scattering effect of energetic electrons. However, the existence of hot plasma in a realistic magnetospheric plasma environment modifies the dispersion relation of plasmaspheric hiss, thereby affecting wave-induced energetic electron scattering. This paper presents the results of some recent studies on the influence of hot plasma on the dispersion relation and electron scattering effects of plasmaspheric hiss. Using statistical analysis results based on satellite wave observations, the modification of the hiss dispersion relation under the effects of hot plasma was verified. Furthermore, based on typical case analyses and numerical calculations using the quasi-linear diffusion theory, we investigated the dependence of the hiss-driven electron scattering rates on the geomagnetic activities and hot plasma parameters (i.e., temperature anisotropy, hot electron temperature, and hot electron abundance). The results revealed that the cold plasma dispersion relation overestimates the scattering rate of energetic electrons below 100 keV. For electrons above 100 keV, the differences between the cold plasma and hot plasma dispersion relations in terms of the induced scattering rates are somewhat smaller; this indicates that using the cold plasma dispersion relation can lead to the underestimation of the hiss-driven rates of electron pitch angle diffusion at smaller pitch angles and the overestimation of the rates at higher pitch angles. In addition, the cold plasma assumption can cause resonant diffusion down to lower electron energies; however, when the observed hiss wave dispersion curves are used, the resonant electron diffusion tends to extend to smaller pitch angles with a broader range. Notably, the differences in the scattering rates between the cold plasma and hot plasma dispersion relations increase with the hot plasma parameters. Therefore, our results are important for future simulations of the hiss wave-induced electron diffusion processes in the actual magnetospheric plasma environment and the dynamic variability of radiation belt electrons.

Drug discovery and development affects various aspects of human health and dramatically impacts the pharmaceutical market. However, investments in a new drug often go unrewarded due to the long and complex process of drug research and development (R&D). With the advancement of experimental technology and computer hardware, artificial intelligence (AI) has recently emerged as a leading tool in analyzing abundant and high-dimensional data. Explosive growth in the size of biomedical data provides advantages in applying AI in all stages of drug R&D. Driven by big data in biomedicine, AI has led to a revolution in drug R&D, due to its ability to discover new drugs more efficiently and at lower cost. This review begins with a brief overview of common AI models in the field of drug discovery; then, it summarizes and discusses in depth their specific applications in various stages of drug R&D, such as target discovery, drug discovery and design, preclinical research, automated drug synthesis, and influences in the pharmaceutical market. Finally, the major limitations of AI in drug R&D are fully discussed and possible solutions are proposed.

Abstract Dysfunctional autophagy and impairment of adult hippocampal neurogenesis (AHN) each contribute to the pathogenesis of major depressive disorder (MDD). However, whether dysfunctional autophagy is linked to aberrant AHN underlying MDD remains unclear. Here we demonstrate that the expression of nuclear receptor binding factor 2 (NRBF2), a component of autophagy-associated PIK3C3/VPS34-containing phosphatidylinositol 3-kinase complex, is attenuated in the dentate gyrus (DG) under chronic stress. NRBF2 deficiency inhibits the activity of the VPS34 complex and impairs autophagic flux in adult neural stem cells (aNSCs). Moreover, loss of NRBF2 disrupts the neurogenesis-related protein network and causes exhaustion of aNSC pool, leading to the depression-like phenotype. Strikingly, overexpressing NRBF2 in aNSCs of the DG is sufficient to rescue impaired AHN and depression-like phenotype of mice. Our findings reveal a significant role of NRBF2-dependent autophagy in preventing chronic stress-induced AHN impairment and suggest the therapeutic potential of targeting NRBF2 in MDD treatment.

Pleurotus tuoliensis is a unique species discovered in Xinjiang, China, which is recognized for its significant edible, medicinal, and economic value. It has been successfully incorporated into industrial production. Controversy has emerged concerning the evolution and environmental adaptability of this species due to inadequate interspecific ecology and molecular data. This study examines the germplasm resources of P. tuoliensis in the Xinjiang region. A total of 225 wild and cultivated strains of P. tuoliensis were gathered from seven representative regions. Phylogenetic analysis revealed that seven populations were notably segregated into three distinct groups, primarily attributed to environmental factors as the underlying cause for this differentiation. Population historical size data indicate that P. tuoliensis underwent two expansion events, one between 2 and 0.9 Mya (Miocene) and the other between 15 and 4 Mya (Early Pleistocene). The ancient climate fluctuations in the Xinjiang region might have contributed to the comparatively modest population size during the Pliocene epoch. Moreover, through the integration of biogeography and ancestral state reconstruction, it was determined that group C of P. tuoliensis emerged initially and subsequently dispersed to groups D and B, in that order. Subsequently, group D underwent independent evolution, whereas group B continued to diversify into groups A and EFG. The primary factor influencing this mode of transmission route is related to the geographical conditions and prevailing wind direction of each group. Subsequent research endeavors focused on assessing the domestication adaptability of P. tuoliensis to different substrates. It was found that the metabolic processes adapted during the domestication process were mainly related to energy metabolism, DNA repair, and environmental adaptability. Processes adapted to the host adaptability include responses to the host (meiosis, cell cycle, etc.) and stress in the growth environment (cysteine and methionine metabolism, sulfur metabolism, etc.). This study analyzed the systematic evolution and genetic differentiation of P. tuoliensis in Xinjiang. The identified loci and genes provide a theoretical basis for the subsequent improvement of germplasm resources and conducting molecular breeding.

Sulfurized polyacrylonitrile (SPAN) is a promising cathode material for lithium-sulfur batteries owing to its reversible solid–solid conversion for high-energy-density batteries. However, the sluggish reaction kinetics of SPAN cathodes significantly limit their output capacity, especially at high cycling rates. Herein, a CNT-interpenetrating hierarchically porous SPAN electrode is developed by a simple phase-separation method. Flexible self-supporting SPAN cathodes with fast electron/ion pathways are synthesized without additional binders, and exceptional high-rate cycling performances are obtained even with substantial sulfur loading. For batteries assembled with this special cathode, an impressive initial discharge capacity of 1090 mAh g−1 and a retained capacity of 800 mAh g−1 are obtained after 1000 cycles at 1 C with a sulfur loading of 1.5 mg cm−2. Furthermore, by incorporating V2O5 anchored carbon fiber as an interlayer with adsorption and catalysis function, a high initial capacity of 614.8 mAh g−1 and a notable sustained capacity of 500 mAh g−1 after 500 cycles at 5 C are achieved, with an ultralow decay rate of 0.037% per cycle with a sulfur loading of 1.5 mg cm−2. The feasible construction of flexible SPAN electrodes with enhanced cycling performance enlists the current processing as a promising strategy for novel high-rate lithium-sulfur batteries and other emerging battery electrodes.

Abstract The development of the Internet of things brings exponential growth of wireless traffic, which puts great pressure on the backhaul link. The proactive caching of some contents in the edge device of mobile network can effectively reduce the repeated transmission of the same contents and relieve the burden of the backhaul link. Moreover, the introduction of recommendation mechanisms can reshape user's request and improve cache hit ratio. However, the optimization of recommendation and caching decisions is highly dependent on the users’ preference information for files. Here, a joint optimization algorithm of recommendation and caching based on users’ preference prediction with multiple base stations cooperative caching is proposed. To improve the caching efficiency, the Deep Crossing model is adopted to predict users’ preferences. Under the constraints of cache capacity, recommendation quantity and bandwidth, an optimization problem to minimize the total transmission delay of the system is formulated. Then, the NP‐hardness of the proposed optimization problem is proved and it is decoupled it into three sub‐problems, namely recommendation, user access and caching optimization sub‐problems. Simulation results show that the proposed algorithm can effectively reduce the total transmission delay of the system.

Abstract Ulcerative colitis is a chronic inflammatory bowel disorder with cellular heterogeneity. To understand the composition and spatial changes of the ulcerative colitis ecosystem, here we use imaging mass cytometry and single-cell RNA sequencing to depict the single-cell landscape of the human colon ecosystem. We find tissue topological changes featured with macrophage disappearance reaction in the ulcerative colitis region, occurring only for tissue-resident macrophages. Reactive oxygen species levels are higher in the ulcerative colitis region, but reactive oxygen species scavenging enzyme SOD2 is barely detected in resident macrophages, resulting in distinct reactive oxygen species vulnerability for inflammatory macrophages and resident macrophages. Inflammatory macrophages replace resident macrophages and cause a spatial shift of TNF production during ulcerative colitis via a cytokine production network formed with T and B cells. Our study suggests components of a mechanism for the observed macrophage disappearance reaction of resident macrophages, providing mechanistic hints for macrophage disappearance reaction in other inflammation or infection situations.

Parkinson's disease (PD) is the most common neurodegenerative movement disease. It is featured by abnormal alpha-synuclein (α-syn) aggregation in dopaminergic neurons in the substantia nigra. Macroautophagy (autophagy) is an evolutionarily conserved cellular process for degradation of cellular contents, including protein aggregates, to maintain cellular homeostasis. Corynoxine B (Cory B), a natural alkaloid isolated from Uncaria rhynchophylla (Miq.) Jacks., has been reported to promote the clearance of α-syn in cell models by inducing autophagy. However, the molecular mechanism by which Cory B induces autophagy is not known, and the α-syn-lowering activity of Cory B has not been verified in animal models. Here, we report that Cory B enhanced the activity of Beclin 1/VPS34 complex and increased autophagy by promoting the interaction between Beclin 1 and HMGB1/2. Depletion of HMGB1/2 impaired Cory B-induced autophagy. We showed for the first time that, similar to HMGB1, HMGB2 is also required for autophagy and depletion of HMGB2 decreased autophagy levels and phosphatidylinositol 3-kinase III activity both under basal and stimulated conditions. By applying cellular thermal shift assay, surface plasmon resonance, and molecular docking, we confirmed that Cory B directly binds to HMGB1/2 near the C106 site. Furthermore, in vivo studies with a wild-type α-syn transgenic drosophila model of PD and an A53T α-syn transgenic mouse model of PD, Cory B enhanced autophagy, promoted α-syn clearance and improved behavioral abnormalities. Taken together, the results of this study reveal that Cory B enhances phosphatidylinositol 3-kinase III activity/autophagy by binding to HMGB1/2 and that this enhancement is neuroprotective against PD.

Abstract Background Hepatoid adenocarcinoma of the stomach (HAS) is a highly malignant and rare extrahepatic tumor. The prognosis is controversial because of its rarity and the lack of multi-center cohort studies, especially on the influence of serum Alpha-fetoprotein (AFP) level on prognosis. We aimed to analyze the clinicopathological characteristics and prognosis of HAS, particularly the effect of serum AFP on the prognosis of HAS. Methods We retrospectively reviewed clinical data of one HAS patient treated at our institution in 2019 and of 252 patients reported between 1984 and 2020 in research databases. Results Among these patients, 60.1% were > 60 years, 51% had lesions in the gastric antrum, and 51.0% (73/143) had the ulcerative lesion type. The preoperative elevated levels of serum alpha-fetoprotein (AFP) were detected in most patients (76.7%). Lymph-node (84.6%) and preoperative liver metastasis (39.1%) were often found. The high-AFP group was characterized by a higher rate of stage IV (P = 0.000682) and liver metastasis (P = 0.000068). The 1-, 3-and 5-year progression-free survival(PFS) rates were 41%, 18%, and 0%, and the 1-, 3-, and 5-year overall survival (OS) rates were 64%, 26%, and 21%, respectively. The survival analysis showed that OS was significantly shorter for HAS with high-AFP (> 300 ng/ml) than with low-AFP (≤ 300 ng/ml) (P = 0.023). The univariate analysis indicated that the OS of HAS was associated with tumor location, pTNM stage, lymph-node metastasis, surgical resection, and serum AFP > 300 ng/ml. However,the prognostic factors for PFS was only pTNM stage and surgical resection. The multivariate analysis confirmed that the independent prognostic factor affecting OS of HAS included pTNM stage and surgical resection. Conclusions Liver metastasis was increasingly more likely with increasingly higher serum AFP, but the prognosis of HAS is not necessarily poor. Serum AFP level is an important prognostic indicator in HAS and should be monitored.

Abstract Background Fibrodysplasia ossificans progressiva (FOP) is an ultrarare and disabling genetic disorder of connective tissue characterized by congenital malformation of the great toes, and progressive heterotopic ossification (HO) in soft connective tissues. A gain-of-function mutation of activin A receptor type I (ACVR1) enables ACVR1 to recognize activin A as an agonist with bone morphogenetic protein (BMP) signalling that leads to HO. Previous studies confirmed that activin A stimulates BMP signalling in vitro and drives HO in mouse models of FOP. However, the roles for BMP4 and BMP6 in FOP are supported only by correlative evidence in vitro. Thus, it remains unclear whether the circulating levels of activin A, BMP4 and BMP6 correlate with flare-ups in FOP patients. Hence, we investigated the protein levels of activin A, BMP4 and BMP6 in the serum of FOP patients. Results We recruited 16 untreated FOP patients and 16 age- and sex- matched healthy control subjects in this study. The 16 FOP patients were retrospectively divided into the flare-up group (n = 8) and remission group (n = 8) depending on whether they had flare-ups or worsening of any joint movement in the last 6 months. The serum activin A, BMP4 and BMP6 levels were detected by enzyme-linked immunosorbent assay. The serum activin A, BMP4 and BMP6 levels were slightly higher in FOP patients (median: 434.05 pg/mL, 459.48 pg/mL and 67.84 pg/mL) versus healthy control subjects (median: 364.14 pg/mL, 450.39 pg/mL and 55.36 pg/mL). However, there were no statistically significant differences between the two groups (p > 0.05 for all items), nor were there significant differences between the flare-up and remission groups of FOP (p > 0.05 for all items). Univariate and multivariate logistic regression analyses showed that age, sex, and serum activin A, BMP4 and BMP6 levels were not related to flare-up in FOP patients. Conclusions There were no significant differences in the serum levels of activin A, BMP4 and BMP6 in FOP patients compared with healthy control subjects. Serum activin A, BMP4 and BMP6 proteins might not be the stimulators for FOP flare-up, and may not be biomarkers for FOP diagnosis.

Identifying biomarkers for computer-aided diagnosis (CAD) is crucial for early intervention of psychiatric disorders. Multi-site data have been utilized to increase the sample size and improve statistical power, while multi-modality classification offers significant advantages over traditional single-modality based approaches for diagnosing psychiatric disorders. However, inter-site heterogeneity and intra-modality heterogeneity present challenges to multi-site and multi-modality based classification. In this paper, brain functional and structural networks (BFNs/BSNs) from multiple sites were constructed to establish a joint multi-site multi-modality framework for psychiatric diagnosis. To do this we developed a hypergraph based multi-source domain adaptation (HMSDA) which allowed us to transform source domain subjects into a target domain. A local ordinal structure based multi-task feature selection (LOSMFS) approach was developed by integrating the transformed functional and structural connections (FCs/SCs). The effectiveness of our method was validated by evaluating diagnosis of both schizophrenia (SZ) and autism spectrum disorder (ASD). The proposed method obtained accuracies of 92.2 %±2.22 % and 84.8 %±2.68 % for the diagnosis of SZ and ASD, respectively. We also compared with 6 DA, 10 multi-modality feature selection, and 8 multi-site and multi-modality methods. Results showed the proposed HMSDA+LOSMFS effectively integrated multi-site and multi-modality data to enhance psychiatric diagnosis and identify disorder-specific diagnostic brain connections.

Regarding the issue of information freshness in systems that aid in data collection using unmanned aerial vehicles (UAVs), a data collection algorithm that is based on freshness and UAV assistance is proposed. Under the limitations of wireless sensor node communication distance and UAV parameters, the optimization problem of minimizing the average spatial correlation age of information (SCAoI) of all nodes in the area is set up. This problem is solved by optimizing the number of clusters, UAV flight trajectories, and the order of data collection from cluster member nodes. The maximum communication distance of the nodes is used as the cluster formation radius, and the maximum-minimum distance clustering algorithm is used to cluster the nodes in the region to obtain the minimum number of clusters. After it has been proven that the trajectory optimization problem in this study is NP-hard, the ant colony algorithm is applied to obtain the minimum flight time and the corresponding trajectory. By using the greedy algorithm to determine the member nodes in the sequence of data collection for a cluster, the instantaneous SCAoI of the UAV arriving at the cluster head is solved. Simulation results show that the proposed algorithm in this paper can effectively improve the freshness of data and reduce the average SCAoI of the system compared with the algorithm in the comparative literature, reducing the average SCAoI by about 61%.

Plant-derived nucleic acids, especially small RNAs have been proved by increasing evidence in the pharmacological activities and disease treatment values in macrophage meditated anti-tumor performance, immune regulating functions and antiviral activities. But the uptake, application and delivery strategies of RNAs as biodrugs are different from the small molecules and recombinant protein drugs. This article summarizes the reported evidence for cross-kingdom regulation by plant derived functional mRNAs and miRNAs. Based on that, their involvement and potentials in macrophage-mediated anti-tumor/inflammatory therapies are mainly discussed, as well as the load prospect of plant RNAs in viruses and natural exosome vehicles, and their delivery to mammalian cells through macrophage were also summarized. This review is to provide evidence and views for the plant derived RNAs as next generation of drugs with application potential in nucleic acid-based bio-therapy.

In this study, by doping the iridium (III) double ((4,6-difluorobenzene) -pyridine-N, C2’Pyridinformate (FIrpic) into 4,4′, 4″ three (carbazole) trioxilamine (TcTa) and 9 (4 tert-butyl-benzene) −3,6 double (triphenylsilyl) -9H carbazole (CzSi) layers as light emitting layers (EMLs) to achieve sky blue phosphor organic electroluminescence (EL) devices with very low efficiency roll-off. The dependence of the EL performance on the doping concentration of the light-emitting molecules and the different EML thicknesses are studied in detail. Experimental data show that the thin-film-doped TcTa layer is very important for the efficiency of the device. Finally, the optimal device achieves extremely high power efficiency, current efficiency, and external quantum efficiency (EQE), reaching 74.82 lm/W, 66.68 cd/A, and 31.9 %, respectively. At a certain luminance of 2000 cd/m2 (3.4 V), the same device retained power efficiency with current efficiency and external quantum efficiency of 57.71 lm/W, 62.46 cd/A and 29.3 %, respectively, based on theoretical discussion, the improved EL efficiency was attributed to the energy levels of the host and luminescent molecules, which helps to balance the charge carrier in the emitter molecule distribution and expand the recombination region.

Abstract Background Older adults are a growing segment of oncology population in China and beyong. However, older cancer patients were vastly underrepresented in clinical trial. To facilitate that all patients with cancer have equal access to the cutting edging treatment and receive evidence-based medication in mainland China, it’s of particular importance to fully grasp the proportion of upper age restriction in cancer clinical trials, as well as associated factors. Methods Based on clinical trials registered on the China Food and Drug Administration Registration and Information Disclosure Platform, we sought to characterize the overall proportion and trajectory of upper age-restriction among registered cancer drug trials in mainland China from 2009 to 2021, and potential influencing factors were determined by multivariate logistic regression. Results According to the 3485 trials, upper age restriction proportion of cancer drug trials for patients over 65 years and 75 years was 18.8% (95% CI = 17.5%-20.1%) and 56.5% (95% CI = 51.3%-54.6%), respectively. Phase IV trials, international multicenter trials, or trials initiated by global companies seldom excluded patients over 65 years compared with phase I trials, domestic trials and trials initiated by Chinese enterprise, similar for 75 years and above. Both of 65 and 75 years old age limit sponsored by domestic enterprises showed slowly downward trend, while no such trend was observed for that of foreign companies. Solution to upper age eligibility of cancer drug trials was also provided. Conclusions Although there is a certain downward trend, use of eligibility criteria that explicitly exclude older cancer patients in mainland China was remarkably high, especially for trials initiated by domestic enterprise, domestic trials and early-phase trials. Action is urgently needed to promote treatment equity in the older patients while obtaining adequate evidence in clinical trials.

Abstract Background Skeletal muscle development is a multistep process whose understanding is central in a broad range of fields and applications, from the potential medical value to human society, to its economic value associated with improvement of agricultural animals. Skeletal muscle initiates in the somites, with muscle precursor cells generated in the dermomyotome and dermomyotome-derived myotome before muscle differentiation ensues, a developmentally regulated process that is well characterized in model organisms. However, the regulation of skeletal muscle ontogeny during embryonic development remains poorly defined in farm animals, for instance in pig. Here, we profiled gene expression and chromatin accessibility in developing pig somites and myotomes at single-cell resolution. Results We identified myogenic cells and other cell types and constructed a differentiation trajectory of pig skeletal muscle ontogeny. Along this trajectory, the dynamic changes in gene expression and chromatin accessibility coincided with the activities of distinct cell type-specific transcription factors. Some novel genes upregulated along the differentiation trajectory showed higher expression levels in muscular dystrophy mice than that in healthy mice, suggesting their involvement in myogenesis. Integrative analysis of chromatin accessibility, gene expression data, and in vitro experiments identified EGR1 and RHOB as critical regulators of pig embryonic myogenesis. Conclusions Collectively, our results enhance our understanding of the molecular and cellular dynamics in pig embryonic myogenesis and offer a high-quality resource for the further study of pig skeletal muscle development and human muscle disease.

The tight formation of unmanned aerial vehicles (UAVs) provides numerous advantages in practical applications, increasing not only their range but also their efficiency during missions. However, the wingman aerodynamics are affected by the tail vortices generated by the leading aircraft in a tight formation, resulting in unpredictable interference. In this study, a mathematical model of wake vortex was developed, and the aerodynamic characteristics of a tight formation were simulated using Xflow software. A robust control method for tight formations was constructed, in which the disturbance is first estimated with an extended state observer, and then a sliding mode controller (SMC) was designed, enabling the wingman to accurately track the position under conditions of wake vortex from the leading aircraft. The stability of the designed controller was confirmed. Finally, the controller was simulated and verified in mathematical simulation and semi-physical simulation platforms, and the experimental results showed that the controller has high tight formation accuracy and is robust.

Maglev transportation is a highly promising form of transportation for the future, primarily due to its friction-free operation, exceptional comfort, and low risk of derailment. Unlike conventional transportation systems, maglev trains operate with no mechanical contact with the track. Maglev trains achieve levitation and guidance using electromagnetic forces controlled by a magnetic levitation control system. Therefore, the magnetic levitation control system is of utmost importance in maintaining the stable operation performance of a maglev train. However, due to the open-loop instability and strong nonlinearity of the control system, designing an active controller with self-adaptive ability poses a substantial challenge. Moreover, various uncertainties exist, including parameter variations and unknown external disturbances, under different operating conditions. Although several review papers on maglev levitation systems and control methods have been published over the last decade, there has been no comprehensive exploration of their modeling and related control technologies. Meanwhile, many review papers have become outdated and no longer reflect the current state-of-the-art research in the field. Therefore, this article aims to summarize the models and control technologies for maglev levitation systems following the preferred reporting items for systematic reviews and meta-analysis (PRISMA) criteria. The control technologies mainly include linear control methods, nonlinear control methods, and artificial intelligence methods. In addition, the article will discuss maglev control in other scenarios, such as vehicle–guideway vibration control and redundancy and fault-tolerant design. First, the widely used maglev levitation system modeling methods are reviewed, including the modeling assumptions. Second, the principle of the control methods and their control performance in maglev levitation systems are presented. Third, the maglev control methods in other scenarios are discussed. Finally, the key issues pertaining to the future direction of maglev levitation control are discussed.