Explore the vast range of titles available.

To evaluate the stability, accuracy, and clinical performance of the Snibe CO₂ assay compared with the Roche CO₂ reagent and to investigate factors affecting total CO₂ measurements in different clinical conditions. Total CO₂ was measured in patient samples using enzymatic assays. Stability was assessed over time, and CO₂ loss was examined in different blood collection tubes. Method comparison was conducted between the Snibe and the Roche CO₂ assays in various diseases. The Snibe CO₂ assay showed excellent linearity (r = 0.9997) and maintained stability for 42 days without recalibration, with control material deviations within ±5% of the target. CO₂ loss was observed in uncapped non-anticoagulant tubes (24.0% decline over 48 hours), but was less in EP tubes (9.4% decline). Significant differences of median CO₂ measurements were observed in only the renal group (Snibe: 13.35 mmol/L, Roche: 12.80 mmol/L) and the cardiovascular disease group (Snibe: 25.90 mmol/L, Roche: 26.40 mmol/L) versus the healthy group (Snibe: 22.70 mmol/L, Roche: 22.90 mmol/L) for both the Snibe and Roche assays. The Snibe CO₂ assay demonstrated superior stability and comparable accuracy compared with the Roche reagent. Preanalytical CO₂ loss remains a critical issue, emphasizing the need for standardized sample handling. Given the correlation between total CO₂ and bicarbonate levels, accurate measurement is critical for diagnosing metabolic disorders. Laboratories should establish protocols to minimize errors and ensure reliable acid-base assessment in clinical practice.

Background The anaphase-promoting complex/cyclosome (APC/C) is a multi-subunit E3 ubiquitin ligase critically involved in cell cycle regulation. However, the pathological functions of its individual subunits, particularly in hepatocellular carcinoma (HCC), remain largely unexplored. Aim To systematically analyze the expression and prognosis of APC/C in pan-cancer, and also focus on studying the function and mechanism of APC7 in the progression of HCC. Methods Transcriptome data were downloaded from TCGA, ICGC, and GEO databases. The analysis of differential expression genes and clinical characteristics were performed to identify the key APC gene. Moreover, immune subtype analysis was conducted to elucidate potential functions, and immune cell infiltration was assessed using the CIBERSORT algorithm. Then, gain- and loss‐of‐function studies were employed to elucidate the role of APC7 in HCC. Finally, RNA sequencing and ubiquitination assays were employed to elucidate the underlying mechanisms of APC7 in HCC. Results This study systematically analyzed the expression and prognosis of various subunits of the APC/C complex in pan-cancer samples, and identified APC7 as a key subunit in HCC. APC7 exhibited the most significant upregulation in HCC and was closely associated with poor prognosis in patients. Moreover, the expression profiles of APC7 is closely related to immune checkpoint genes and tumor-infiltrating immune cells. The results of multiplex immunohistochemistry showed that APC7 overexpression markedly increased the infiltration of Foxp3⁺, CD25⁺, and CD4⁺ Treg cells. Functional studies demonstrated that the knockdown of APC7 inhibited HCC cell proliferation, migration, invasion, and G1/S phase transition, whereas overexpression of APC7 promoted these malignant phenotypes in vitro and in vivo. Mechanistically, RNA sequencing and molecular studies revealed that APC7 interacts with CDH1 to mediate ubiquitin-dependent degradation of LATS1 at K860, leading to YAP/TAZ activation. Rescue experiments confirmed that LATS1 ablation reversed the tumor-suppressive effects of APC7 knockdown. Conclusions Our findings identify APC7 as a key oncogenic driver in HCC, promoting tumor progression via the Hippo signaling pathway. APC7 may represent a prognostic biomarker and a potential therapeutic target in HCC. Highlights Pan-cancer analysis of APC/C identifies APC7 as the most significantly upregulated and is strongly associated with poor prognosis in patients with HCC. APC7 expression is correlated with immune checkpoint genes and tumor-infiltrating immune cells, suggesting a role in the tumor immune microenvironment. The overexpression of APC7 promotes HCC malignant progression by facilitating proliferation, migration, invasion, and cell cycle progression. APC7 interacts with CDH1 to mediate ubiquitin-dependent degradation of LATS1 at K860, leading to YAP/TAZ activation and dysregulation of the Hippo pathway.

The complex modeling and computational cost are unavoidable in analysis of finite element models (FEMs) when mechanical properties of woven composite materials are predicted. To overcome the drawbacks of FEMs, two different artificial neural network models (ANNMs) based on quasi-static axial compression experimental data of 2.5D woven composite plates (2.5DWCPs) are constructed: (1) The direct strength prediction model (DSPM) is a non-destructive way to predict strength, which is meaningful in engineering; (2) The indirect strength prediction model (ISPM) is based on stress–strain curves, which firstly proposes a simplified data processing method including the state variables (SVs). The SVs are introduced to modify the experimental stress–strain curves, which not only reduces training data size but also significantly improves prediction accuracy. Then, the performance of the DSPM and the ISPM has been evaluated by numerical examples. The results indicate that the DSPM has simple and direct expressions of input parameters (IPs) and output parameters (OPs), which makes it easier to construct and train ANNMs. The ISPM not only utilizes sufficient training data from experiments but also performs well in predicting stress–strain curve and failure strain. In short, two proposed ANNMs have ability to fast and accurately predict compression strength, which are more suitable for engineering than FEMs. To reduce experimental costs, the DSPM is proposed to produce reasonable results. If a lot of experimental data are prepared, the ISPM can produce more accurate results.

To evaluate the stability, accuracy, and clinical performance of the Snibe COâ assay compared with the Roche COâ reagent and to investigate factors affecting total COâ measurements in different clinical conditions. Total COâ was measured in patient samples using enzymatic assays. Stability was assessed over time, and COâ loss was examined in different blood collection tubes. Method comparison was conducted between the Snibe and the Roche COâ assays in various diseases. The Snibe COâ assay showed excellent linearity (r = 0.9997) and maintained stability for 42 days without recalibration, with control material deviations within ±5% of the target. COâ loss was observed in uncapped non-anticoagulant tubes (24.0% decline over 48 hours), but was less in EP tubes (9.4% decline). Significant differences of median COâ measurements were observed in only the renal group (Snibe: 13.35 mmol/L, Roche: 12.80 mmol/L) and the cardiovascular disease group (Snibe: 25.90 mmol/L, Roche: 26.40 mmol/L) versus the healthy group (Snibe: 22.70 mmol/L, Roche: 22.90 mmol/L) for both the Snibe and Roche assays. The Snibe COâ assay demonstrated superior stability and comparable accuracy compared with the Roche reagent. Preanalytical COâ loss remains a critical issue, emphasizing the need for standardized sample handling. Given the correlation between total COâ and bicarbonate levels, accurate measurement is critical for diagnosing metabolic disorders. Laboratories should establish protocols to minimize errors and ensure reliable acid-base assessment in clinical practice.

How to optimize the quality of the truss so that the truss meets the load-bearing requirements has always been a key issue of research. In this paper, a genetic algorithm (GA) and finite element analysis (FEA) based optimization method is proposed for the size and topology of a space truss. According to the results of space truss, four kinds of components are divided and their cross-sectional areas are optimized respectively. The coded value on the chromosome in GA is used to represent the truss topology, and the adjacent value represents the adjacent truss structure. The nodal displacement and member stress of the truss are solved by finite element method to ensure the safety of the truss. All work is done using python.

Truss structure is widely used in aircraft design. In this paper, the lightweight design of a certain type of aircraft truss structure is carried out through topology analysis and size optimization to improve the performance of the aircraft. The original truss model is established based on ABAQUS, and its static strength is checked and analyzed. According to the design domain of the original model, a topology optimization method is used to obtain a new material distribution. Then the section size of each truss member is taken as the optimization variable, the maximum deformation of the structure is taken as the constraint, and the overall model volume is the minimum as the optimization goal, the genetic algorithm is used to obtain the new structure size. The results show that the truss members after the second optimization can meet the requirements of use and have a 75.15% reduction in mass compared to the original structure, which verifies that the method is feasible and provides a new idea for the lightweight design of truss structures.

CD8 + T-cell exhaustion is a state of dysfunction that promotes tumor progression and is marked by the generation of Slamf6 + progenitor exhausted (Tex prog ) and Tim-3 + terminally exhausted (Tex term ) subpopulations. Inhibitor of DNA binding protein 2 (Id2) has been shown to play important roles in T-cell development and CD8 + T-cell immunity. However, the role of Id2 in CD8 + T-cell exhaustion is unclear. Here, we found that Id2 transcriptionally and epigenetically regulates the generation of Tex prog cells and their conversion to Tex term cells. Genetic deletion of Id2 dampens CD8 + T-cell-mediated immune responses and the maintenance of stem-like CD8 + T-cell subpopulations, suppresses PD-1 blockade and increases tumor susceptibility. Mechanistically, through its HLH domain, Id2 binds and disrupts the assembly of the Tcf3-Tal1 transcriptional regulatory complex, and thus modulates chromatin accessibility at the Slamf6 promoter by preventing the interaction of Tcf3 with the histone lysine demethylase LSD1. Therefore, Id2 increases the abundance of the permissive H3K4me2 mark on the Tcf3-occupied E-boxes in the Slamf6 promoter, modulates chromatin accessibility at the Slamf6 promoter and epigenetically regulates the generation of Slamf6 + Tex prog cells. An LSD1 inhibitor GSK2879552 can rescue the Id2 knockout phenotype in tumor-bearing mice. Inhibition of LSD1 increases the abundance of Slamf6 + Tim-3 − Tex prog cells in tumors and the expression level of Tcf1 in Id2-deleted CD8 + T cells. This study demonstrates that Id2-mediated transcriptional and epigenetic modification drives hierarchical CD8 + T-cell exhaustion, and the mechanistic insights gained may have implications for therapeutic intervention with tumor immune evasion.

Up to 50% of hepatocellular carcinoma (HCC) is caused by hepatitis B virus (HBV) infection, and the surface protein of HBV is essential for the progression of HBV-related HCC. The expression of large HBV surface antigen (LHB) is presented in HBV-associated HCC tissues and is significantly associated with the development of HCC. Gene set enrichment analysis revealed that LHB overexpression regulates the cell cycle process. Excess LHB in HCC cells induced chronic endoplasmic reticulum (ER) stress and was significantly correlated with tumor growth in vivo. Cell cycle analysis showed that cell cycle progression from G1 to S phase was greatly enhanced in vitro. We identified intensive crosstalk between ER stress and cell cycle progression in HCC. As an important regulator of the G1/S checkpoint, p27 was transcriptionally upregulated by transcription factors ATF4 and XBP1s, downstream of the unfolded protein response pathway. Moreover, LHB-induced ER stress promoted internal ribosome-entry-site-mediated selective translation of p27, and E3 ubiquitin ligase HRD1-mediated p27 ubiquitination and degradation. Ultimately, the decrease in p27 protein levels reduced G1/S arrest and promoted the progress of HCC by regulating the cell cycle.

Convolutional neural networks (CNNs) have long been the cornerstone of target detection, but they are often limited by limited receptive fields, which hinders their ability to capture global contextual information. We re-examined the DETR-inspired detection head and found substantial redundancy in its self-attention module. To solve these problems, we introduced the Context-Gated Scale-Adaptive Detection Network (CSDN), a Transformer-based detection header inspired by human visual perception: when observing an object, we always concentrate on one site, perceive the surrounding environment, and glance around the object. This mechanism enables each region of interest (ROI) to adaptively select and combine feature dimensions and scale information from different patterns. CSDN provides more powerful global context modeling capabilities and can better adapt to objects of different sizes and structures. Our proposed detection head can directly replace the native heads of various CNN-based detectors, and only a few rounds of fine-tuning on the pre-trained weights can significantly improve the detection accuracy.

Traditional child patient care needs human workers, who are limited due wage shortage and other factors. Using technologies such as robotics may be a viable alternative as a care assistant to improve child patients' wellbeing, especially when the UK government is encouraging robotics and artificial intelligence innovation. Literature found positive implications for the use of robotics for child patients, such as social humanoid robots providing emotional support and helping child patients reduce pain, which allows for more possibilities of using social humanoid robots to explore serving child patients. This research aims to develop an effective solution to entertain and comfort child patients who have been negatively impacted by the threatened and declining social care sector. The researchers introduced a new design of the robot - Iva: a playful humanoid robot with educational flare for little patients. Iva is based on the NAO robot's hardware and equipped with various sensors and abilities, such as tactile sensors, facial detection and speech and object recognition, enabling it to interact with children through interactive activities. Iva can perform conversation, games, shows, exercises and more activities, based on the thinking of the child patients' needs and preferences, forms of expression and programming workflow. The whole process emphasised user friendliness and ethical considerations, including data privacy and informed consent. The design, development and testing have been conducted in the novel EUREKA Tokku Zone to ensure ethical integrity. Preliminary testing in a laboratory setting shows all the functions of Iva work correctly for providing multiple interesting activities to let child patients play and relax. In terms of Iva's performance, she is a meaningful robot that contributes to a more positive and supportive environment for children during hospitalisation. Future work contains improvements of Iva's program for a more accessible experience, and the test in the real hospital setting within the Tokku Zones in Wales.