For many years, surface has quality received a serious attention due to its influence on various mechanical properties. The main contribution made in this scientific paper is the performance of actual experiments, as well as the experimental processing obtained in order to develop a model for predicting the surface roughness based on the optimization of cutting parameters. The novelty of this paper is brought by the method of obtaining the regression equation of the surface roughness, resulted from a standard end-milling process (standard milling tools, standard milling parameters, recommended by the tool manufacturer, 3 axis CNC machine and standard vice), on aluminum alloy 7136 in temper T76511, through two statistical methods of data analysis. This material is used for the production of extruded parts and is poorly understood for the proposed line of research. This study’s aim is to determine the surface roughness equation obtained by the milling of aluminum alloy 7136 in two ways: using Taguchi′s experimental design once and the other, using the central composite design. The Taguchi method and the central composite design are used to develop an efficient mathematical model to predict the optimal level of certain processing parameters. Using ANOVA analysis, a comparative study of calculated and experimental surface roughness values is carried out. The initial characteristics (surface roughness) and the controlled factors (cutting speed, depth of cut and feed) are analyzed with the Minitab program. Finally, an analysis of the advantages and disadvantages of the two methods used is presented. This study has a great industrial application, since the main task of every manufacturer is to achieve a better quality of the final product with minimal processing time.

Exosomes are nanosized vesicles that have been found to be involved in many diseases. Exosomes can mediate communication between cells in a variety of ways. Certain types of mediators derived from cancer cells can play a crucial role in the development of this pathology, promoting tumor growth, invasion, metastasis, angiogenesis, and immunomodulation. Exosomes in the bloodstream show promise as a future tool for detecting cancer at an early stage. The sensitivity and specificity of clinical exosome biomarkers need to be enhanced. Knowledge of exosomes is not only important for understanding the significance of cancer progression but also for providing clinicians with useful information for the diagnosis, treatment, and discovery of methods to prevent cancer from recurring. The widespread adoption of diagnostic tools based on exosomes may revolutionize cancer diagnosis and treatment. Tumor metastasis, chemoresistance, and immunity are all aided by exosomes. A potential new approach to cancer therapy involves preventing metastasis by inhibiting miRNA intracellular signaling and blocking the formation of pre-metastatic niches. For colorectal patients, exosomes represent a promising area of investigation for improving the diagnosis, treatment, and management. Reported data demonstrate that the serum expression level of certain exosomal miRNA is significantly higher in primary colorectal cancer patients. The present review discusses mechanisms and clinical implications of exosomes in colorectal cancer.

Tetraspanins are transmembrane proteins expressed in a multitude of cells throughout the organism. They contribute to many processes that surround cell–cell interactions and are associated with the progress of some diseases, including cancer. Their crucial role in cell physiology is often understated. Furthermore, recent studies have shown their great potential in being used as targeting molecules. Data have suggested the potential of tetraspanins as a targeting vector for nanomediated distribution and delivery for colorectal cancer applications. Our aim is to provide a review on the important part that tetraspanins play in the human organism and highlight their potential use for drug delivery systems using nanotechnology.

This scientific paper explores the increasingly widespread use of collaborative and industrial robots in the industrial environment, highlighting them as a solution to challenges related to the high costs of human labor and associated management difficulties. The authors focus on the process of defining requirements for the implementation of collaborative and industrial robots, providing strategies based on mathematical management models. This approach translates into significant benefits for companies, such as cost reduction, quality improvement, and increased operational efficiency. Additionally, the paper proposes an innovative mathematical model for assessing total costs, budgeting, profitability, and electric power consumption associated with the operation of collaborative and industrial robots. This model allows for a comparison between the costs involved in using human labor and those associated with collaborative and industrial robots, providing critical information for technological investment decisions. The efficiency of this mathematical model is demonstrated through a practical application, where collaborative robots were integrated into a production environment and costs and efficiency were evaluated compared to the use of human labor and industrial robots. This scientific paper provides a systematic and efficient approach to implementing collaborative robots in industrial processes, benefiting from strategies based on mathematical management models and an original mathematical model for evaluating performance and associated costs.

Background and Objectives: Local and distant relapse (LR, DR) in breast cancer vary according to its molecular subtypes, with triple-negative breast cancer (TNBC) being the most aggressive. The surgical resection margin width (SRMW) for breast-conserving surgery (BCS) has been intensely debated, especially for the aforementioned subtype. The aim of this study was to examine the impact of SRMW on LR following BCS in TNBC patients. Materials and Methods: We conducted a retrospective study including all patients with TNBC for whom BCS was performed between 2005 and 2014. Results: Final analysis included a total of 92 patients, with a median tumor size of 2.5 cm (range 0–5 cm) and no distant metastasis at the time of diagnosis. A total of 87 patients had received neoadjuvant and/or adjuvant chemotherapy, and all patients had received adjuvant whole-breast radiotherapy. After a median follow-up of 110.7 months (95% CI, 95.23–126.166), there were 5 local recurrences and 8 regional/distant recurrences with an overall LR rate of 5.4%. The risk of LR and DR was similar between groups of patients with several SRMW cut-off values. Conclusions: Our study supports a safe “no ink on tumor” approach for TNBC patients treated with BCS.

Background/Objectives: Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide. This study evaluates the predictive value of Carcinoembryonic Antigen (CEA) in identifying CRC recurrence following surgical resection. Methods: This retrospective study was realized in the Oncology Institute in Cluj-Napoca and included 88 patients diagnosed with CRC. Clinical, demographic, and tumor-specific data were collected, including TNM staging, tumor histology. CEA levels were recorded before surgery. Receiver Operating Characteristic (ROC) analysis was performed to determine the diagnostic accuracy of CEA in predicting tumor relapse, and the sensitivity and specificity of various CEA cut-off values were assessed. Results: Most patients presented with advanced-stage tumors (T3/T4, 80.6%). CEA levels were significantly higher in patients with lymphatic and perineural invasion and in those with metastases (mean CEA: 45.0 ng/mL for M1 vs. 13.2 ng/mL for M0, p = 0.032). ROC analysis revealed an area under the curve (AUC) of 0.877 (95% CI: 0.763–0.949). A CEA cut-off value of 11.73 ng/mL yielded 100% sensitivity and 74.5% specificity for detecting recurrence; Conclusions: CEA is a valuable non-invasive biomarker for predicting CRC relapse, with high sensitivity and acceptable specificity. Regular CEA monitoring post-surgery can facilitate early detection of recurrence, improving prognosis.