Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST).

The importance and value of real-world data in healthcare cannot be overstated because it offers a valuable source of insights into patient experiences. Traditional patient-reported experience and outcomes measures (PREMs/PROMs) often fall short in addressing the complexities of these experiences due to subjectivity and their inability to precisely target the questions asked. In contrast, diary recordings offer a promising solution. They can provide a comprehensive picture of psychological well-being, encompassing both psychological and physiological symptoms. This study explores how using advanced digital technologies, i.e., automatic speech recognition and natural language processing, can efficiently capture patient insights in oncology settings. We introduce the MRAST framework, a simplified way to collect, structure, and understand patient data using questionnaires and diary recordings. The framework was validated in a prospective study with 81 colorectal and 85 breast cancer survivors, of whom 37 were male and 129 were female. Overall, the patients evaluated the solution as well made; they found it easy to use and integrate into their daily routine. The majority (75.3%) of the cancer survivors participating in the study were willing to engage in health monitoring activities using digital wearable devices daily for an extended period. Throughout the study, there was a noticeable increase in the number of participants who perceived the system as having excellent usability. Despite some negative feedback, 44.44% of patients still rated the app's usability as above satisfactory (i.e., 7.9 on 1-10 scale) and the experience with diary recording as above satisfactory (i.e., 7.0 on 1-10 scale). Overall, these findings also underscore the significance of user testing and continuous improvement in enhancing the usability and user acceptance of solutions like the MRAST framework. Overall, the automated extraction of information from diaries represents a pivotal step toward a more patient-centered approach, where healthcare decisions are based on real-world experiences and tailored to individual needs. The potential usefulness of such data is enormous, as it enables better measurement of everyday experiences and opens new avenues for patient-centered care.

Breath Sensor Technology for the Use in Mechanical Lung Ventilation Equipment for Monitoring Critically Ill Patients.

BACKGROUND: The need for mechanical lung ventilation is common in critically ill patients, either with COVID-19 infection or due to other causes. Monitoring of patients being ventilated is essential for timely and improved management. We here propose the use of a novel breath volatile organic compound sensor technology to be used in a mechanical lung ventilation machine for this purpose; the technology was evaluated in critically ill COVID-19 patients on mechanical lung ventilation. METHODS: Based on the consistency results of our study data, the breath sensor device with metal oxide gas sensors and environment-controlling sensors was mounted on the ventilation exhaust port of the ventilation machine; this allowed to ensure additional safety since the device was placed outside the contour between the patient and equipment. RESULTS: The sensors allowed stable registration of the signals for up to several weeks for 10 patients in total, depending on the storage amount; a proportion of patients were intubated or received tracheostoma during the evaluation period. Future studies are on the way to correlate sensor readings to other parameters characterizing the severity of the patient condition and outcome. CONCLUSIONS: We suppose that such technology will allow patient monitoring in real-time for timely identification of deterioration, potentially requiring some change of management. The obtained results are preliminary and further studies are needed to examine their clinical significance.

Cancer microcell initiation and determination.

BACKGROUND: Cancer remains one of the leading causes of death worldwide, despite the possibilities to detect early onset of the most common cancer types. The search for the optimal therapy is complicated by the cancer diversity within tumors and the unsynchronized development of cancerous cells. Therefore, it is necessary to characterize cancer cell populations after treatment has been applied, because cancer recurrence is not rare. In our research, we concentrated on small cancer cell subpopulation (microcells) that has a potential to be cancer resistance source. Previously made experiments has shown that these cells in small numbers form in specific circumstances after anticancer treatment. METHODS: In experiments described in this research, the anticancer agents' paclitaxel and doxorubicin were used to stimulate the induction of microcells in fibroblast, cervix adenocarcinoma, and melanoma cell lines. Mainly for the formation of microcells in melanoma cells. The drug-stimulated cells were then characterized in terms of their formation efficiency, morphology, and metabolic activity. RESULTS: We observed the development of cancer microcells and green fluorescent protein (GFP) transfection efficiency after stress. In the time-lapse experiment, we observed microcell formation through a renewal process and GFP expression in the microcells. Additionally, the microcells were viable after anticancer treatment, as indicated by the nicotinamide adenine dinucleotide hydrogen phosphate (NADPH) enzyme activity assay results. Taken together, these findings indicate that cancer microcells are viable and capable of resisting the stress induced by anticancer drugs, and these cells are prone to chemical substance uptake from the environment. CONCLUSION: Microcells are not only common to a specific cancer type, but can be found in any tumor type. This study could help to understand cancer emergence and recurrence. The appearance of microcells in the studied cancer cell population could be an indicator of the individual anticancer therapy effectiveness and patient survival.