Enhancing endometrial cancer detection: Blood serum intrinsic fluorescence data processing and machine learning application.

Endometrial cancer (EC) is the most prevalent cancer within the female reproductive system in developed countries. Despite its high incidence, there is currently no established laboratory screening test for EC, making early detection challenging. This study introduces an innovative, minimally invasive, and cost-effective method utilizing three-dimensional fluorescence analysis combined with machine learning algorithms to enhance early EC detection.

Non-Invasive Endometrial Cancer Screening through Urinary Fluorescent Metabolome Profile Monitoring and Machine Learning Algorithms.

Endometrial cancer is becoming increasingly common, highlighting the need for improved diagnostic methods that are both effective and non-invasive. This study investigates the use of urinary fluorescence spectroscopy as a potential diagnostic tool for endometrial cancer. Urine samples were collected from endometrial cancer patients ( = 77), patients with benign uterine tumors ( = 23), and control gynecological patients attending regular checkups or follow-ups ( = 96).

Potential application of body fluids autofluorescence in the non-invasive diagnosis of endometrial cancer.

Background: Endometrial carcinoma (EC) is the most common cancer of the female reproductive tract in developed countries. The prognosis and 5-year survival rates are closely tied to the stage diagnosis. Current routine diagnostic methods of EC are either lacking specificity or are uncomfortable, invasive and painful for the patient.

Visualization of the composition of the urinary fluorescent metabolome. Why is it important to consider initial urine concentration?

Urine is a highly complex fluorescent system, the fluorescence of which can be affected by many factors, including the often-ignored initial urine concentration in comprehensive fluorescent urine analysis. In this study, a total urine fluorescent metabolome profile (uTFMP) was created as a three-dimensional fluorescence profile of serial synchronous spectra of urine diluted by geometric progression. uTFMP was generated using software designed for this purpose after recalculating the 3D data concerning the initial urine concentration.

The gut microbiota, its relationship to the immune system, and possibilities of its modulation.

Research of the gut microbiota allows a better understanding of its composition and function and reveals the links between changes in the composition of bacteria and various intestinal but also systemic diseases. The gut microbiota performs several of important functions in the host body and influences many physiological processes. Gut bacteria synthesize many compounds needed for the proper function of the body (e.