SLAS Technology最新文献

Abnormal expression of connexin 43 (Cx43) contributes to the development and progression of cancer. However, its regulation is complex and dependent on the environment. The expression of Cx43 in triple-negative cancer lesions was analyzed by immunohistochemistry and optical coherence tomography using experimental models and clinical samples. The model of TGFβ1-SMad3-in-αv signal axis was established and verified by experiments. The results show that Cx43 plays a key role in the regulation of triple-negative cancer metastasis. In vivo, over-expressed Cx43 decreased tumor volume and inhibited ITGαV, TGF-β1, Smad3 and N-cadherin expressions, but enhanced the E-cadherin. Cx43 had the lowest expression in the TNBC samples, especially in lymph node metastatic TNBC patients and had a negative correlation with ITG alpha V, TGF-β1 and Smad3.The study demonstrated Cx43 controlled metastatic behavior through TGF-β1 -Smad3-ITG αV signaling axis in MDA-MB-231 cells, providing evidence for Cx43’s function in TNBC. The optical image diagnosis method can realize the identification and quantitative evaluation of early cancer triple negative, and provide a new strategy and means for the treatment of cancer triple negative.

Computer vision technology is more and more widely used in the market. Target detection and feature extraction are two important auxiliary means of this technique, which are helpful to analyze target motion data. However, in the field of biology, there are some data limitations in the analysis of targets such as bacteria and tumors, which need to be further explored. Optical MRI imaging technology based on computer vision provides a new way to extract and analyze morphological features of renal tumors. In this paper, an optical MRI imaging method based on computer vision is designed and developed for the extraction and analysis of morphological features of kidney tumors. By using optical MRI imaging technology based on computer vision, the morphological characteristics of kidney tumors were extracted by analyzing the optical characteristics and MRI images of kidney tumors, and a simulation model was established to simulate the morphological characteristics of different types of kidney tumors, and feature extraction and analysis were carried out by computer algorithm. Through the analysis of the simulation model, the morphological characteristics of renal tumors were extracted and analyzed, which provided a new and non-invasive method for clinical diagnosis and treatment of renal tumors.

Carotid cavernous fistula is a rare but clinically important vascular abnormality that is challenging to diagnose and treat. The clinical data of a patient with bilateral carotid cavernous fistula diagnosed by CT images were retrospectively analyzed. Through the analysis of CT images, the patient was accurately located and the diagnosis was confirmed. CT images can provide detailed anatomical information and accurately show the location, morphology and hemodynamic characteristics of carotid cavernous fistula. Through CT image examination, we successfully diagnosed bilateral carotid cavernous fistula patients, and can provide an important reference for surgical treatment. Therefore, CT image examination can provide accurate diagnosis and surgical planning information, and provide support for the formulation of individual treatment plans for patients. The application of this method is helpful to improve the early diagnosis rate and treatment effect of carotid cavernous fistula.

Breast cancer (BC), a prevalent and severe malignancy, detrimentally affects women globally. Its prognostic implications are profoundly influenced by gene expression patterns. This study retrieved 509 BCE-associated oncogenes and 1,012 neurotransmitter receptor-related genes from the GSEA and KEGG databases, intersecting to identify 98 relevant genes. Clinical and transcriptomic expression data related to BC were downloaded from the TCGA, and differential genes were identified based on an FDR value <0.05 & |log2FC| ≥ 0.585. Univariate analysis of these genes revealed that high expression of NSF and low expression of HRAS, KIF17, and RPS6KA1 are closely associated with BC survival prognosis. A prognostic model constructed for these four genes demonstrated significant prognostic relevance for BC-TCGA patients (P < 0.001). Subsequently, an immunofunctional analysis of the BC oncogene-neurotransmitter receptor-related gene cluster revealed the involvement of immune cells such as T cells CD8, T cells CD4 memory resting, and Macrophages M2. Further analysis indicated that immune functions were primarily concentrated in APC_co_inhibition, APC_co_stimulation, CCR, and Check-point, among others. Lastly, a prognostic nomogram model was established, and ROC curve analysis revealed that the nomogram is a vital indicator for assessing BC prognosis, with 1-year, 3-year, and 5-year survival rates of 0.981, 0.897, and 0.802, respectively. This model demonstrates high calibration, clinical utility, and predictive capability, promising to offer an effective preliminary tool for clinical diagnostics.

The pharmaceutical industry is increasingly embracing laboratory automation to enhance experimental efficiency and operational resilience, particularly through the integration of automated liquid handlers (ALHs). This paper explores the integration of the low-cost Opentrons OT-2 liquid handling robot with F. Hoffmann-La Roche AG's in-house workflow orchestration software, AutoLab, to overcome barriers to lab automation. By leveraging the OT-2′s development-oriented interfaces and AutoLab's modular architecture, we achieved a user-friendly, cost-efficient, and flexible automation solution that aligns with FAIR (findable, accessible, interoperable, reusable) data principles. We demonstrate an advanced workflow development methodology, utilizing the software architecture, that facilitates the creation of two flexible pipetting protocols and medium complexity assays. This deep integration approach diminishes the learning curve for novice users while simultaneously enhancing the overall efficiency and reliability of the experimental workflow. Our findings suggest that such integrations can significantly mitigate the challenges associated with lab automation, including cost, complexity, and adaptability, paving the way for more accessible and robust automated systems in pharmaceutical research.