Suchergebnisse

In this study, we used machine learning techniques to reconstruct the wavelength dependence of the absorption coefficient of human normal and pathological colorectal mucosa tissues. Using only diffuse reflectance spectra from the ex vivo mucosa tissues as input to algorithms, several approaches were tried before obtaining good matching between the generated absorption coefficients and the ones previously calculated for the mucosa tissues from invasive experimental spectral measurements. Considering the optimized match for the results generated with the multilayer perceptron regression method, we were able to identify differentiated accumulation of lipofuscin in the absorption coefficient spectra of both mucosa tissues as we have done before with the corresponding results calculated directly from invasive measurements. Considering the random forest regressor algorithm, the estimated absorption coefficient spectra almost matched the ones previously calculated. By subtracting the absorption of lipofuscin from these spectra, we obtained similar hemoglobin ratios at 410/550 nm: 18.9-fold/9.3-fold for the healthy mucosa and 46.6-fold/24.2-fold for the pathological mucosa, while from direct calculations, those ratios were 19.7-fold/10.1-fold for the healthy mucosa and 33.1-fold/17.3-fold for the pathological mucosa. The higher values obtained in this study indicate a higher blood content in the pathological samples used to measure the diffuse reflectance spectra. In light of such accuracy and sensibility to the presence of hidden absorbers, with a different accumulation between healthy and pathological tissues, good perspectives become available to develop minimally invasive spectroscopy methods for in vivo early detection and monitoring of colorectal cancer.The application of machine learning methods to noninvasivelike diffuse reflectance spectra allowed us to reconstruct the absorption coefficient spectra of human healthy and pathological mucosa tissues from the colorectal wall. Consequently, we were able to obtain differentiated blood and pigment content in both tissues, which can be used for the development of new noninvasive diagnostic methods for colorectal cancer. ; The work of L. M. Oliveira was supported by the Portuguese Science Foundation (Grant No. FCT-UIDB/04730/2020). The work of V. V. Tuchin was supported by a grant of the Government of the Russian Federation (Registration No. 2020-220-08-2389). ; info:eu-repo/semantics/publishedVersion

In this paper we present three studies that demonstrate the applicability of spectroscopy methods and optical clearing treatments in pathology identification and monitoring. In the first study, by obtaining the absorption spectra of human healthy and pathological (adenocarcinoma) colorectal mucosa tissues, it was possible to identify a higher content of a pigment in the diseased tissues. This study also shows that machine learning methods can be used to reach the same differentiated results in vivo through diffuse reflectance spectroscopy. In the second study, the combination of collimated transmittance spectroscopy with optical clearing treatments allowed to obtain the diffusion coefficients of glucose in healthy and pathological colorectal mucosa as: Dglucose=5.8x10–7 cm2/s and Dglucose=4.4x10–7 cm2/s, respectively. This study also demonstrated that the diseased tissues contains about 5% more mobile water than the healthy tissues. The third study was performed to evaluate the protein dissociation mechanism of optical clearing. By treating both healthy and pathological colorectal mucosa tissues with 93%-glycerol, a protein dissociation rate of about 3 times higher was obtained for the pathological mucosa. All the discriminating parameters that result from these studies can be obtained in the in vivo situation through diffuse reflectance spectroscopy and further studies to evaluate their values in different stages of cancer progression are of great importance to develop disease monitoring protocols. ; The authors of the article knew well and communicated with Ekaterina Borisova for many years, especially Valery Tuchin and in recent years Luís Oliveira. We had many joint plans to organize conferences and joint research projects, but COVID-19 mercilessly interrupted our communication. We have lost a great scientist and a person with a huge soul, sociable, but at the same time modest and kind. We will always remember our warm meetings and fruitful work with Ekaterina. This research was supported by the Portuguese grant FCT-UIDB/04730/2020. VVT was supported by grant under the Decree of the Government of the Russian Federation No. 220 of 09 April 2010 (Agreement No. 075-15-2021-615 of 04 June 2021). ; info:eu-repo/semantics/publishedVersion

Key stakeholders from the cancer research continuum met in May 2021 at the European Cancer Research Summit in Porto to discuss priorities and specific action points required for the successful implementation of the European Cancer Mission and Europe's Beating Cancer Plan (EBCP). Speakers presented a unified view about the need to establish high‐quality, networked infrastructures to decrease cancer incidence, increase the cure rate, improve patient's survival and quality of life, and deal with research and care inequalities across the European Union (EU). These infrastructures, featuring Comprehensive Cancer Centres (CCCs) as key components, will integrate care, prevention and research across the entire cancer continuum to support the development of personalized/precision cancer medicine in Europe. The three pillars of the recommended European infrastructures – namely translational research, clinical/prevention trials and outcomes research – were pondered at length. Speakers addressing the future needs of translational research focused on the prospects of multiomics assisted preclinical research, progress in Molecular and Digital Pathology, immunotherapy, liquid biopsy and science data. The clinical/prevention trial session presented the requirements for next‐generation, multicentric trials entailing unified strategies for patient stratification, imaging, and biospecimen acquisition and storage. The third session highlighted the need for establishing outcomes research infrastructures to cover primary prevention, early detection, clinical effectiveness of innovations, health‐related quality‐of‐life assessment, survivorship research and health economics. An important outcome of the Summit was the presentation of the Porto Declaration, which called for a collective and committed action throughout Europe to develop the cancer research infrastructures indispensable for fostering innovation and decreasing inequalities within and between member states. Moreover, the Summit guidelines will assist decision making in the ...