COL8A1 is a potential prognostic biomarker associated with migration, proliferation, and tumor microenvironment in glioma.

Glioblastoma (GBM) is a common primary central nervous system tumor. The molecular mechanisms of glioma are unknown, and the prognosis is poor. Therefore, exploring the underlying mechanisms and screening for new prognostic markers and therapeutic targets is crucial. We utilized the weighted gene co-expression network analysis (WGCNA), Differentially Expressed Genes (DEGs), and LASSO-COX analysis to identify three target genes. Next, we constructed and evaluated a prognostic model, screening out COL8A1 as a risk gene. Through a sequence of cellular functional experiments, in vivo studies, and RNA sequencing, we delved into exploring the functional effects and molecular mechanisms of COL8A1 on GBM cells. Finally, the correlation between COL8A1 and tumor immune cells and different inflammatory responses was analyzed. Immunohistochemistry experiments revealed the influence of COL8A1 on macrophage polarization. The COL8A1 expression level was associated with the grade, prognosis, and tumor microenvironment (TME) of glioma. Functional experiments showed that COL8A1 inhibited GBM cell apoptosis and promoted migration, invasion, and proliferation in vitro and in vivo. We also found that COL8A1 promotes the epithelial-mesenchymal transition process and may mediate the activation of the ERK pathway through SHC1. In addition, immune infiltration analysis showed that COL8A1 was closely associated with macrophages in glioma tissues, significantly suppressing the signaling of M1-like -type macrophages and enhancing the signaling of M2-like -type macrophages. COL8A1 was first found to be associated with prognosis, progression, and immune microenvironment of glioma and may serve as a new marker of prognosis and a therapeutic target.

Preoperative C-reactive protein to prealbumin ratio is independently associated with prognosis in patients with resectable colorectal cancer.

BACKGROUND: Increasing attention has been drawn the prognostic value of inflammatory indices for colorectal cancer (CRC). However, the prognostic value of the preoperative C-reactive protein to prealbumin ratio (CPAR) in CRC remains unclear. METHODS: A retrospective study was conducted with 794 patients who had CRC and underwent radical surgical resection. The predictive performance of the inflammatory indices was analyzed and compared using the area under the time-dependent receiver operating characteristic curve. A competing risk regression model and Cox proportional hazard model were used to analyze the effects of CPAR on disease-free survival (DFS) and overall survival (OS), respectively. RESULTS: Patients with high CPAR (>7.25) had poor survival outcome. The CPAR had the best predictive performance among all inflammatory indices, and was significantly associated with several characteristics of tumor invasion, including histological grade, tumor stage, and tumor size. Multivariate analysis showed that high CPAR was independently associated with poor DFS (subdistribution hazard ratio = 2.28, 95% confidence interval [CI]: 1.74-2.82) and OS (hazard ratio = 1.78, 95% CI: 1.60-1.96). CONCLUSION: Preoperative CPAR assessment could serve as an effective and reliable tool for prognostic prediction in patients with resectable CRC.

Origami-Inspired Structure with Pneumatic-Induced Variable Stiffness for Multi-DOF Force-Sensing.

With the emerging need for human-machine interactions, multi-modal sensory interaction is gradually pursued rather than satisfying common perception forms (visual or auditory), so developing flexible, adaptive, and stiffness-variable force-sensing devices is the key to further promoting human-machine fusion. However, current sensor sensitivity is fixed and nonadjustable after fabrication, limiting further development. To solve this problem, we propose an origami-inspired structure to achieve multiple degrees of freedom (DoFs) motions with variable stiffness for force-sensing, which combines the ductility and flexibility of origami structures. In combination with the pneumatic actuation, the structure can achieve and adapt the compression, pitch, roll, diagonal, and array motions (five motion modes), which significantly increase the force adaptability and sensing diversity. To achieve closed-loop control and avoid excessive gas injection, the ultra-flexible microfiber sensor is designed and seamlessly embedded with an approximately linear sensitivity of ∼0.35 Ω/kPa at a relative pressure of 0-100 kPa, and an exponential sensitivity at a relative pressure of 100-350 kPa, which can render this device capable of working under various conditions. The final calibration experiment demonstrates that the pre-pressure value can affect the sensor's sensitivity. With the increasing pre-pressure of 65-95 kPa, the average sensitivity curve shifts rightwards around 9 N intervals, which highly increases the force-sensing capability towards the range of 0-2 N. When the pre-pressure is at the relatively extreme air pressure of 100 kPa, the force sensitivity value is around 11.6 Ω/N. Therefore, our proposed design (which has a low fabrication cost, high integration level, and a suitable sensing range) shows great potential for applications in flexible force-sensing development.

Chronic administration of caffeine alters acesulfame-K intake and features of fungiform taste buds in mice.

The objective of this study was to investigate the effects of chronic administration of caffeine on the anatomical characteristics of taste buds, the expression level of taste receptor protein in mice, and preference for a palatable solution. We found that following a 21-day administration of caffeine, mice showed increased behavioural responses to sweet stimuli (acesulfame-K solution). Mirroring this behavioural change, chronic caffeine treatment evidently decreased the maximal cross-sectional area and height of the longitudinal axis of fungiform taste buds, the number of taste cells per fungiform taste bud, and the expression of G protein α-gustducin, while the expression of the sweet taste receptors T1R2 and T1R3 was reversed. Our findings demonstrate that chronic administration of caffeine has an impact on taste sensitivity and changes in taste bud features, which may contribute to the alteration of taste behaviour.

Model predictive manipulation of compliant objects with multi-objective optimizer and adversarial network for occlusion compensation.

BACKGROUND: The manipulation of compliant objects by robotic systems remains a challenging task, largely due to their variable shapes and the complex, high-dimensional nature of their interaction dynamics. Traditional robotic manipulation strategies struggle with the accurate modeling and control necessary to handle such materials, especially in the presence of visual occlusions that frequently occur in dynamic environments. Meanwhile, for most unstructured environments, robots are required to have autonomous interactions with their surroundings. METHODS: To solve the shape manipulation of compliant objects in an unstructured environment, we begin by exploring the regression-based algorithm of representing the high-dimensional configuration space of deformable objects in a compressed form that enables efficient and effective manipulation. Simultaneously, we address the issue of visual occlusions by proposing the integration of an adversarial network, enabling guiding the shaping task even with partial observations of the object. Afterwards, we propose a receding-time estimator to coordinate the robot action with the computed shape features while satisfying various performance criteria. Finally, model predictive controller is utilized to compute the robot's shaping motions subject to safety constraints. Detailed experiments are presented to evaluate the proposed manipulation framework. SIGNIFICANT FINDINGS: Our MPC framework utilizes the compressed representation and occlusion-compensated information to predict the object's behavior, while the multi-objective optimizer ensures that the resulting control actions meet multiple performance criteria. Through rigorous experimental validation, our approach demonstrates superior manipulation capabilities in scenarios with visual obstructions, outperforming existing methods in terms of precision and operational reliability. The findings highlight the potential of our integrated approach to significantly enhance the manipulation of compliant objects in real-world robotic applications.

ADAMTSL2 is a potential prognostic biomarker and immunotherapeutic target for colorectal cancer: Bioinformatic analysis and experimental verification.

The ADAMTS Like 2 (ADAMTSL2) mutation has been identified to be associated with different human genetic diseases. The role of ADAMTSL2 is unclear in colorectal cancer (CRC). The study investigated the expression of ADAMTSL2 in both pan cancer and CRC, using data from The Cancer Genome Atlas (TCGA) database to assess its diagnostic value. The study examined the correlation between ADAMTSL2 expression levels and clinical characteristics, as well as prognosis in CRC. The study explored potential regulatory networks involving ADAMTSL2, including its association with immune infiltration, immune checkpoint genes, tumor mutational burden (TMB) / microsatellite instability (MSI), tumor stemness index (mRNAsi), and drug sensitivity in CRC. ADAMTSL2 expression was validated using GSE71187 and quantitative real-time PCR (qRT-PCR). ADAMTSL2 was aberrantly expressed in pan cancer and CRC. An increased level of ADAMTSL2 expression in patients with CRC was significantly associated with the pathologic N stage (p < 0.001), pathologic stage (p < 0.001), age (p < 0.001), histological type (p < 0.001), and neoplasm type (p = 0.001). The high expression of ADAMTSL2 in patients with CRC was found to be significantly associated with a poorer overall survival (OS) (HR: 1.67; 95% CI: 1.18-2.38; p = 0.004), progression-free survival (PFS) (HR: 1.55; 95% CI: 1.14-2.11; p = 0.005) and disease-specific survival (DSS) (HR: 1.83; 95% CI: 1.16-2.89; p = 0.010). The expression of ADAMTSL2 in patients with CRC (p = 0.009) was identified as an independent prognostic determinant. ADAMTSL2 was associated with extracellular matrix receptor (ECM-receptor) interaction, transforming growth factor ß (TGF-ß) signaling pathway, and more. ADAMTSL2 expression was correlated with immune infiltration, immune checkpoint genes, TMB / MSI and mRNAsi in CRC. ADAMTSL2 expression was significantly and negatively correlated with 1-BET-762, Trametinib, and WZ3105 in CRC. ADAMTSL2 was significantly upregulated in CRC cell lines. The high expression of ADAMTSL2 is significantly correlated with lower OS and immune infiltration of CRC. ADAMTSL2 may be a potential prognostic biomarker and immunotherapeutic target for CRC patients.

HaptGlove-Untethered Pneumatic Glove for Multimode Haptic Feedback in Reality-Virtuality Continuum.

Novel haptics technologies are urgently needed to bridge the gap between entirely physical world and fully digital environment to render a more realistic and immersive human-computer interaction. Current virtual reality (VR) haptic gloves either deliver limited haptic feedback or are bulky and heavy. The authors develop a haptic glove or HaptGlove, an untethered and lightweight pneumatic glove, that allows users to "physically" interact in a VR environment and enables both kinesthetic and cutaneous sensations naturally and realistically. Integrated with five pairs of haptic feedback modules and fiber sensors, HaptGlove provides variable stiffness force feedback and fingertip force and vibration feedback, allowing users to touch, press, grasp, squeeze, and pull various virtual objects and feel the dynamic haptic changes. Significant improvements in VR realism and immersion are observed in a user study with participants achieving 78.9% accuracy in sorting six virtual balls of different stiffnesses. Importantly, HaptGlove facilitates VR training, education, entertainment, and socialization in a reality-virtuality continuum.

Ultrahigh Strain-Insensitive Integrated Hybrid Electronics Using Highly Stretchable Bilayer Liquid Metal Based Conductor.

Human-interfaced electronic systems require strain-resilient circuits. However, present integrated stretchable electronics easily suffer from electrical deterioration and face challenges in forming robust multilayered soft-rigid hybrid configurations. Here, a bilayer liquid-solid conductor (b-LSC) with amphiphilic properties is introduced to reliably interface with both rigid electronics and elastomeric substrates. The top liquid metal can self-solder its interface with rigid electronics at a resistance 30% lower than the traditional tin-soldered rigid interface. The bottom polar composite comprising liquid metal particles and polymers can not only reliably interface with elastomers but also help the b-LSC heal after breakage. The b-LSC can be scalably fabricated by printing and subsequent peeling strategies, showing ultra-high strain-insensitive conductivity (maximum 22 532 S cm-1 ), extreme stretchability (2260%), and negligible resistance change under ultra-high strain (0.34 times increase under 1000% strain). It can act as stretchable vertical interconnect access for connecting multilayered layouts and can be scalably and universally fabricated on various substrates with a resolution of ≈200 µm. It is demonstrated that it can construct stretchable sensor arrays, multi-layered stretchable displays, highly integrated haptic user-interactive optoelectric E-skins, visualized heaters, robot touch sensing systems, and wireless powering for wearable electronics.

Flexible Wearable Sensors for Cardiovascular Health Monitoring.

Cardiovascular diseases account for the highest mortality globally, but recent advances in wearable technologies may potentially change how these illnesses are diagnosed and managed. In particular, continuous monitoring of cardiovascular vital signs for early intervention is highly desired. To this end, flexible wearable sensors that can be comfortably worn over long durations are gaining significant attention. In this review, advanced flexible wearable sensors for monitoring cardiovascular vital signals are outlined and discussed. Specifically, the functional materials, configurations, mechanisms, and recent advances of these flexible sensors for heart rate, blood pressure, blood oxygen saturation, and blood glucose monitoring are highlighted. Different mechanisms in bioelectric, mechano-electric, optoelectric, and ultrasonic wearable sensors are presented to monitor cardiovascular vital signs from different body locations. Present challenges, possible strategies, and future directions of these wearable sensors are also discussed. With rapid development, these flexible wearable sensors will potentially be applicable for both medical diagnosis and daily healthcare use in tackling cardiovascular diseases.

Fabrication and characterization of oil-in-water pickering emulsions stabilized by ZEIN-HTCC nanoparticles as a composite layer.

In this work, the ZEIN-HTCC nanoparticles formed by zein and N-(2-hydroxy)propyl-3-trimethylammonium chitosan chloride (HTCC) were used as stabilizers to prepare oil-in-water (O/W) Pickering emulsions. The preparation conditions including shearing time, volume fraction of corn oil, mass ratio of ZEIN:HTCC and total concentration of ZEIN-HTCC of emulsions were optimized by measuring the droplet size, zeta potential, PDI and surface tension of emulsions. The ZEIN-HTCC emulsions are stable at the pH range of 4-9 and in the low salt ion concentrations up to 0.2 mol L-1, and can keep stable up to 21 d during low temperature storage. Fourier transform infrared spectroscopy (FTIR), the confocal laser scanning microscope (CLSM) and scanning electron microscopy (SEM) were used to analyze the interaction between emulsion components, revealing that zein and HTCC form a composite layer by flocculation to adsorb on the surface of oil droplets, thus preventing emulsion droplets from aggregation. This novel, long-term stable, surfactant-free, and edible zein-based Pickering emulsion could be used as potential carriers for lipophilic nutrients delivery.

Signaling Mechanism of Transcriptional Bursting: A Technical Resolution-Independent Study.

Gene transcription has been uncovered to occur in sporadic bursts. However, due to technical difficulties in differentiating individual transcription initiation events, it remains debated as to whether the burst size, frequency, or both are subject to modulation by transcriptional activators. Here, to bypass technical constraints, we addressed this issue by introducing two independent theoretical methods including analytical research based on the classic two-model and information entropy research based on the architecture of transcription apparatus. Both methods connect the signaling mechanism of transcriptional bursting to the characteristics of transcriptional uncertainty (i.e., the differences in transcriptional levels of the same genes that are equally activated). By comparing the theoretical predictions with abundant experimental data collected from published papers, the results exclusively support frequency modulation. To further validate this conclusion, we showed that the data that appeared to support size modulation essentially supported frequency modulation taking into account the existence of burst clusters. This work provides a unified scheme that reconciles the debate on burst signaling.

Gene Biomarkers Derived from Clinical Data of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a common cancer of high mortality, mainly due to the difficulty in diagnosis during its clinical stage. Here we aim to find the gene biomarkers, which are of important significance for diagnosis and treatment. In this work, 3682 differentially expressed genes on HCC were firstly differentiated based on the Cancer Genome Atlas database (TCGA). Co-expression modules of these differentially expressed genes were then constructed based on the weighted correlation network algorithm. The correlation coefficient between the co-expression module and clinical data from the Broad GDAC Firehose was thereafter derived. Finally, the interactive network of genes was then constructed. Then, the hub genes were used to implement enrichment analysis and pathway analysis in the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. Results revealed that the abnormally expressed genes in the module played an important role in the biological process including cell division, sister chromatid cohesion, DNA repair, and G1/S transition of mitotic cell cycle. Meanwhile, these genes also enriched in a few crucial pathways related to Cell cycle, Oocyte meiosis, and p53 signaling. Via investigating the closeness centrality of the interactive network, eight gene biomarkers including the CKAP2, TPX2, CDCA8, KIFC1, MELK, SGO1, RACGAP1, and KIAA1524 gene were discovered, whose functions had been indeed revealed to be correlated with HCC. This study, therefore, suggests that the abnormal expression of those eight genes may be taken as gene biomarkers of HCC.

A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control.

In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation problem amongst multiple adaptive units that specialize in a local sensorimotor map. Different from traditional estimation algorithms, the proposed method requires little data to train and constrain it (the number of required data points can be analytically determined) and has rigorous stability properties (the conditions to satisfy Lyapunov stability are derived). Numerical simulations and experimental results are presented to validate the proposed method.

Leucine-rich repeat receptor-like gene screen reveals that Nicotiana RXEG1 regulates glycoside hydrolase 12 MAMP detection.

Activation of innate immunity by membrane-localized receptors is conserved across eukaryotes. Plant genomes contain hundreds of such receptor-like genes and those encoding proteins with an extracellular leucine-rich repeat (LRR) domain represent the largest family. Here, we develop a high-throughput approach to study LRR receptor-like genes on a genome-wide scale. In total, 257 tobacco rattle virus-based constructs are generated to target 386 of the 403 identified LRR receptor-like genes in Nicotiana benthamiana for silencing. Using this toolkit, we identify the LRR receptor-like protein Response to XEG1 (RXEG1) that specifically recognizes the glycoside hydrolase 12 protein XEG1. RXEG1 associates with XEG1 via the LRR domain in the apoplast and forms a complex with the LRR receptor-like kinases BAK1 and SOBIR1 to transduce the XEG1-induced defense signal. Thus, this genome-wide silencing assay is demonstrated to be an efficient toolkit to pinpoint new immune receptors, which will contribute to developing durable disease resistance.