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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.

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.

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.

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.

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 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.

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.

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.

Summary: Metastasis is the leading cause of high ovarian-cancer-related mortality worldwide. Three major processes constitute the whole metastatic cascade: invasion, intravasation, and extravasation. Tumor cells often reprogram their metabolism to gain advantages in proliferation and survival. However, whether and how those metabolic alterations contribute to the invasiveness of tumor cells has yet to be fully understood. Here we performed a genome-wide CRISPR-Cas9 screening to identify genes participating in tumor cell dissemination and revealed that PTGES3 acts as an invasion suppressor in ovarian cancer. Mechanistically, PTGES3 binds to phosphofructokinase, liver type (PFKL) and generates a local source of prostaglandin E2 (PGE2) to allosterically inhibit the enzymatic activity of PFKL. Repressed PFKL leads to downgraded glycolysis and the subsequent TCA cycle for glucose metabolism. However, ovarian cancer suppresses the expression of PTGES3 and disrupts the PTGES3-PGE2-PFKL inhibitory axis, leading to hyperactivation of glucose oxidation, eventually facilitating ovarian cancer cell motility and invasiveness.

Multi-modal brain networks characterize the complex connectivities among different brain regions from structure and function aspects, which have been widely used in the analysis of brain diseases. Although many multi-modal brain network fusion methods have been proposed, most of them are unable to effectively extract the spatio-temporal topological characteristics of brain network while fusing different modalities. In this paper, we develop an adaptive multi-channel graph convolution network (GCN) fusion framework with graph contrast learning, which not only can effectively mine both the complementary and discriminative features of multi-modal brain networks, but also capture the dynamic characteristics and the topological structure of brain networks. Specifically, we first divide ROI-based series signals into multiple overlapping time windows, and construct the dynamic brain network representation based on these windows. Second, we adopt adaptive multi-channel GCN to extract the spatial features of the multi-modal brain networks with contrastive constraints, including multi-modal fusion InfoMax and inter-channel InfoMin. These two constraints are designed to extract the complementary information among modalities and specific information within a single modality. Moreover, two stacked long short-term memory units are utilized to capture the temporal information transferring across time windows. Finally, the extracted spatio-temporal features are fused, and multilayer perceptron (MLP) is used to realize multi-modal brain network prediction. The experiment on the epilepsy dataset shows that the proposed method outperforms several state-of-the-art methods in the diagnosis of brain diseases.

Relaxin family peptide receptor 4 (RXFP4) regulates pleiotropic biological processes. Here, authors report cryo-EM structures revealing the ligand-binding modes and key determinants of peptidomimetic agonism and subtype selectivity

Optically levitated oscillators in high vacuum have excellent environmental isolation and low mass compared with conventional solid-state sensors, which makes them suitable for ultrasensitive force detection. The force resolution usually scales with the measurement bandwidth, which represents the ultimate detection capability of the system under ideal conditions if sufficient time is provided for measurement. However, considering the stability of a real system, a method based on the Allan variance is more reliable to evaluate the actual force detection performance. In this study, a levitated optomechanical system with a force detection sensitivity of 6.33 ± 1.62 zN/Hz1/2 was demonstrated. And for the first time, the Allan variance was introduced to evaluate the system stability due to the force sensitivity fluctuations. The force detection resolution of 166.40 ± 55.48 yN was reached at the optimal measurement time of 2751 s. The system demonstrated in this work has the best force detection performance in both sensitivity and resolution that have been reported so far for optically levitated particles. The reported high-sensitivity force detection system is an excellent candidate for the exploration of new physics such as fifth force searching, high-frequency gravitational waves detection, dark matter research and so on.

Abstract Background Drug resistance is an important factor affecting the efficacy of chemotherapy in patients with colon cancer. However, clinical markers for diagnosing drug resistance of tumor cells are not only a few in number, but also low in specificity, and the mechanism of action of tumor cell drug resistance remains unclear. Methods Dipeptidase 1 (DPEP1) expression was analyzed using the cancer genome atlas (TCGA) and genotype‐Tissue Expression pan‐cancer data. Survival analysis was performed using the survival package in R software to assess the prognostic value of DPEP1 expression in colon cancer. Correlation and Venn analyses were adopted to identify key genes. Immunohistochemistry, western blot, qRT–PCR, Co‐immunoprecipitation, and dual‐luciferase reporter experiments were carried out to explore the underlying associations between DPEP1 and Achaete scute‐like 2 (ASCL2). MTT assays were used to evaluate the role of DPEP1 and ASCL2 in colon cancer drug resistance. Results DPEP1 was highly expressed in colon cancer tissues. DPEP1 expression correlated negatively with disease‐specific survival but not with overall survival. Bioinformatics analysis and experiments showed that the expressions of DPEP1 and ASCL2 in colon cancer tissues were markedly positively correlated. Mechanistic research indicated that DPEP1 enhanced the stability of protein ASCL2 by inhibiting its ubiquitination‐mediated degradation. In turn, ASCL2 functioned as a transcription factor to activate the transcriptional activity of the DPEP1 gene and boost its expression. Furthermore, DPEP1 also could enhance the expression of colon cancer stem cell markers (LGR5, CD133, and CD44), which strengthened the tolerance of colon cancer cells to chemotherapy drugs. Conclusions Our findings reveal that the DPEP1 enhances the stemness of tumor cells by forming a positive feedback loop with ASCL2 to improve resistance to chemotherapy drugs.

Abstract Symbiotic radio (SR) is a new spectrum sharing paradigm that allows backscatter device (BD) to transmit information over the ambient radio frequency signal, where the BD is parasitic in the primary transmission, and the secondary system (i.e. backscatter system) shares not only the same spectrum but also the same receiver with the primary system. Here, a multi‐BD SR system with a primary transmitter (PT), a cooperative receiver (CR) and two backscatter devices (BDs), that is, BD1 and BD2 is studied. The accurate expressions for the outage probability of both primary system and secondary system are derived. Simulation results verify the correctness of this theoretical analysis. Additionally, the effect of the distance parameters (i.e. the distance of the backscatter links) on the outage probability of BD1 and BD2 when the backscatter coefficients are fixed is investigated. Simulation results indicate that the desired outage performance can be obtained by adjusting the distance parameters. Finally, the performance of the multi‐BD SR system is compared with the SR system containing only one BD, and the results show that the multi‐BD SR system can enable the backscatter system to achieve better rate performance, which highlights the importance of applying multi‐BD to the SR system.

Abstract Background Increased frequency of circulating double negative T (DNT, CD4−CD8−CD3+) cells with protective immune function has been observed in human immunodeficiency virus (HIV) infection and tuberculosis (TB). Here the role of circulating TCRαβ+ DNT cells was further investigated in HIV/TB co-infection. Methods A cross-sectional study was conducted to investigate the frequency and functional profiles of peripheral TCRαβ+ DNT cells including apoptosis, chemokine and cytokine expression among healthy individuals and patients with TB, HIV infection and HIV/TB co-infection by cell surface staining and intracellular cytokine staining combined with flow cytometry. Results Significantly increased frequency of TCRαβ+ DNT cells was observed in HIV/TB co-infection than that in TB (p

Achieving higher accuracy and robustness stands as the central objective in the navigation field. In complex urban environments, the integrity of GNSS faces huge challenges and the performance of integrated navigation systems can be significantly affected. As the proportion of faulty measurements rises, it can result in both missed alarms and false positives. In this paper, a robust method based on factor graph is proposed to improve the performance of integrated navigation systems. We propose a detection method based on multi-conditional analysis to determine whether GNSS is anomalous or not. Moreover, the optimal weight of GNSS measurement is estimated under anomalous conditions to mitigate the impact of GNSS outliers. The proposed method is evaluated through real-world road tests, and the results show the positioning accuracy of the proposed method is improved by more than 60% and the missed alarm rate is reduced by 80% compared with the traditional algorithms.

Background: The study aimed to investigate the clinical value and prognostic patterns of the neutrophil-to-lymphocyte ratio (NLR) and imaging tumor capsule (ITC) in solitary hepatocellular carcinoma (HCC) patients undergoing narrow-margin hepatectomy. Methods: Data for solitary HCC patients treated with narrow-margin surgery were extracted from Shanghai General Hospital. Clinical features of recurrence-free survival (RFS), overall survival (OS), and early recurrence were investigated by Cox/logistic regression. The significant variables were subsequently incorporated into the nomogram pattern. Survival analysis stratified by NLR and ITC was also performed. Results: The study included a cohort of 222 patients, with median RFS and OS of 24.083 and 32.283 months, respectively. Both an NLR ≥ 2.80 and incomplete ITC had a significant impact on prognosis. NLR and ITC independently affected RFS and OS, whereas alpha-fetoprotein (AFP) and ITC were identified as independent factors for early relapse. The RFS and OS nomogram, generated based on the Cox model, demonstrated good performance in validation. The combination of NLR and ITC showed greater predictive accuracy for 5-year RFS and OS. Subgroups with an NLR ≥ 2.80 and incomplete ITC had the worst prognosis. Conclusions: Both NLR and ITC significantly affected RFS, OS, and early recurrence among solitary HCC patients who underwent narrow-margin hepatectomy. The combination of NLR and ITC has the potential to guide rational clinical treatment and determine the prognosis.

Obesity is one of the main risk factors for cardiovascular diseases, type II diabetes, hypertension, and certain cancers. Obesity in women at the reproductive stage adversely affects contraception, fertility, maternal well-being, and the health of their offspring. Being a major protein component in chylomicrons and high-density lipoproteins, apolipoprotein A-IV (apoA-IV) is involved in lipid metabolism, food intake, glucose homeostasis, prevention against atherosclerosis, and platelet aggregation. The goal of the present study is to determine the impact of apoA-IV deficiency on metabolic functions in 129X1/SvJ female mouse strain. After chronic high-fat diet feeding, apoA-IV−/− mice gained more weight with a higher fat percentage than wild-type (WT) mice, as determined by measuring their body composition. Increased adiposity and adipose cell size were also observed with a microscope, particularly in periovarian fat pads. Based on plasma lipid and adipokine assays, we found that obesity in apoA-IV−/− mice was not associated with hyperlipidemia but with higher leptin levels. Compared to WT mice, apoA-IV deficiency displayed glucose intolerance and elevated insulin levels, according to the data of the glucose tolerance test, and increased HOMA-IR values at fasting, suggesting possible insulin resistance. Lastly, we found obesity in apoA-IV−/− mice resulting from reduced energy expenditure but not food intake. Together, we established a novel and excellent female mouse model for future mechanistic study of obesity and its associated comorbidities.

Apolipoprotein A-IV (apoA-IV), synthesized by enterocytes, is potentially involved in regulating lipid absorption and metabolism, food intake, and glucose metabolism. In this study, we backcrossed apoA-IV knockout (apoA-IV−/−) mice onto the 129/SvJ background for eight generations. Compared to the wild-type (WT) mice, the 129/SvJ apoA-IV−/− mice gained more weight and exhibited delayed glucose clearance even on the chow diet. During a 16-week high-fat diet (20% by weight of fat) study, apoA-IV−/− mice were more obese than the WT mice, which was associated with their increased food intake as well as reduced energy expenditure and physical activity. In addition, apoA-IV−/− mice developed significant insulin resistance (indicated by HOMA-IR) with severe glucose intolerance even though their insulin levels were drastically higher than the WT mice. In conclusion, we have established a model of apoA-IV−/− mice onto the 129/SvJ background. Unlike in the C57BL/6J strain, apoA-IV−/− 129/SvJ mice become significantly more obese and insulin-resistant than WT mice. Our current investigations of apoA-IV in the 129/SvJ strain and our previous studies in the C57BL/6J strain underline the impact of genetic background on apoA-IV metabolic effects.

Gradient colors are widely used in product design. The variation of gradient colors muting a color as a series of steps from bright to dull creates a soft and gradual impression while also affecting people's perceptions. This study manipulates the types of gradient colors to explore the relationship between color gradients and perception of stability to determine whether weight perception plays a role. In the case of controlling for aesthetic differences, the study manipulated two types of color gradients (dark colors fading upward from the bottom versus downward from the top) and measured the perceptions of product stability. In the same hue, an upward gradient gives a stronger perception of stability. In addition, gradient colors significantly influence women's perception of stability more than men's. The study also investigated the mediating effect of weight perception: participants evaluated color fading-upward products with less weight relative to fading-downward colors. Furthermore, dark colors fading upward from the bottom lead to a stronger perception of weight, increasing the stability perception of the object. Finally, to aid future research, we discuss the practical implications of the current findings for areas such as sensory marketing, as well as possible directions for future research.