Comprehensive analysis of the Cullin family of genes reveals that CUL7 and CUL9 are the significant prognostic biomarkers in colorectal cancer.

OBJECTIVES: The purpose of this study is to decipher the role of Cullin family genes in colorectal cancer (CRC), drawing insights from comprehensive analyses encompassing multiple databases and experimental validations. METHODS: UALCAN, GEPIA2, Human Protein Atlas (HPA), KM plotter, cBioPortal, TISIDB, DAVID, colon cancer cell lines culturing, gene knockdown, CCK8 assay, colony formation, and Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) assays. RESULTS: Initial scrutiny of The Cancer Genome Atlas (TCGA) CRC datasets through the UALCAN and GEPIA databases unveiled significant alterations in Cullin family gene expressions. Elevations in CUL1, CUL2, CUL4A, CUL4B, CUL5, CUL7, and CUL9 were observed in CRC tissues compared to normal counterparts, while CUL3 demonstrated down-regulation consistently across datasets. Further exploration revealed notable correlations between Cullin gene expressions and various clinical parameters of CRC patients, substantiating the potential diagnostic and prognostic utility of these genes. Protein expression analyses conducted via the HPA corroborated the transcriptomic findings, indicating high levels of Cullin proteins in CRC tissues. Prognostic assessments identified CUL7 and CUL9 as significant predictors of poor survival outcomes in CRC patients, emphasizing their clinical relevance. Genetic alterations within the Cullin family genes were elucidated through the cBioPortal database, shedding light on the mutation landscape and prevalence of missense mutations in CRC. Immune subtype and tumor immune microenvironment analyses underscored the intricate interplay between Cullin family genes and immune processes in CRC. Experimental validation in CRC cell lines demonstrated the functional significance of CUL7 and CUL9 in promoting CRC growth, further solidifying their roles as potential therapeutic targets. CONCLUSION: Overall, these multifaceted analyses elucidated the intricate involvement of Cullin family genes in CRC pathogenesis and provided valuable insights for future diagnostic and therapeutic endeavors in CRC management.

Coordination of hydraulic and leaf-level gas exchange traits during water-deficit acclimation in apple rootstocks.

Water deficit episodes impact apple (Malus domestica) productivity through challenging the trees' water status, the influence of extreme high temperature climate has become increasingly prominent in recent years. Rootstocks can bestow specific properties on the fruit trees such as the resistance to drought stress. However, the related hydraulic mechanisms in response to water deficit have not been fully understood. Herein, five rootstocks (SH6, GM256, M9, M26, and MM106) were examined under water limitation. The hydraulic conductance of root (Kroot), shoots (Kshoot), and stems (Kstem-shoot) in the five rootstocks reduced slightly during drought stress. Whereas the leaf water potential and photosynthesis of five rootstocks decreased dramatically when they were exposed to drought stress. Additionally, the Kshoot and Kstem-shoot were strongly correlated with the total plant leaf area. Aquaporins (AQPs) involved in the symplastic water transport pathway, the PIP2:1, TIP1:1, and TIP2:2 mRNA levels of all genotypic rootstocks showed significant regulation under drought stress. We examined the relationships among photosynthesis, apoplastic, and symplastic water movement pathways to achieve a comprehensive understanding of rootstocks' hydraulic strategy for improving drought adaptation. The PIP2:1 and TIP2:1 in leaves were more sensitive to root hydraulic conductance in response to drought stress. Furthermore, the coordinated relationship existed in leaf-specific conductance of shoot (Kl -shoot) and transpiration rate (Tr) under drought stress in the rootstocks. Overall, the drought resistance in the five dwarfing rootstocks is associated with the rapid re-establishment of water-related traits, and the effect of the canopy on the drought resistance in apple rootstocks merits much more attention.

A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate.

During intravascular interventional surgery, the 3D surgical navigation system can provide doctors with 3D spatial information of the vascular lumen, reducing the impact of missing dimension caused by digital subtraction angiography (DSA) guidance and further improving the success rate of surgeries. Nevertheless, this task often comes with the challenge of complex registration problems due to vessel deformation caused by respiratory motion and high requirements for the surgical environment because of the dependence on external electromagnetic sensors. This article proposes a novel 3D spatial predictive positioning navigation (SPPN) technique to predict the real-time tip position of surgical instruments. In the first stage, we propose a trajectory prediction algorithm integrated with instrumental morphological constraints to generate the initial trajectory. Then, a novel hybrid physical model is designed to estimate the trajectory's energy and mechanics. In the second stage, a point cloud clustering algorithm applies multi-information fusion to generate the maximum probability endpoint cloud. Then, an energy-weighted probability density function is introduced using statistical analysis to achieve the prediction of the 3D spatial location of instrument endpoints. Extensive experiments are conducted on 3D-printed human artery and vein models based on a high-precision electromagnetic tracking system. Experimental results demonstrate the outstanding performance of our method, reaching 98.2% of the achievement ratio and less than 3 mm of the average positioning accuracy. This work is the first 3D surgical navigation algorithm that entirely relies on vascular interventional robot sensors, effectively improving the accuracy of interventional surgery and making it more accessible for primary surgeons.

Design and Performance Evaluation of a Novel Vascular Robotic System for Complex Percutaneous Coronary Interventions.

The robotic-assisted percutaneous coronary intervention is an emerging technology with great potential to solve the shortcomings of existing treatments. However, the current robotic systems can not manipulate two guidewires or ballons/stents simultaneously for coronary bifurcation lesions. This paper presents VasCure, a novel bio-inspired vascular robotic system, to deliver two guidewires and stents into the main branch and side branch of bifurcation lesions in sequence. The system is designed in master-slave architecture to reduce occupational hazards of radiation exposure and orthopedic injury to interventional surgeons. The slave delivery device has one active roller and two passive rollers to manipulate two interventional devices. The performance of the VasCure was verified by in vitro and in vivo animal experiments. In vitro results showed the robotic system has good accuracy to deliver guidewires and the maximum error is 0.38mm. In an animal experiment, the interventional surgeon delivered two guidewires and balloons to the left circumflex branch and the left anterior descending branch of the pig, which confirmed the feasibility of the vascular robotic system.

A directed essential dynamics simulation of peptide folding.

We present a directed essential dynamics (DED) method for peptide and protein folding. DED is a molecular dynamics method based on the essential dynamics sampling and the principal component analysis. The main idea of DED is to use principal component analysis to determine the direction of the most active collective motion of peptides at short intervals of time (20 fs) during the folding process and then add an additional force along it to adjust the folding direction. This method can make the peptides avoid being trapped in the local minima for a long time and enhance the sampling efficiency in conformational space during the simulation. An S-peptide with 15 amino acids is used to demonstrate the DED method. The results show that DED can lead the S-peptide to fold quickly into the native state, whereas traditional molecular dynamics needs more time to do this.