Journal of biophotonics最新文献

Malignant melanoma (MM) continues to claim millions of lives around the world due to its limited therapeutic alternatives. Photodynamic therapy (PDT) has gained popularity in cancer treatment due it increased potency and low off-target toxicity. Studies have pointed out that the heterogeneity of MM tumours reduces the efficacy of current therapeutic approaches, including PDT, leading to high chances of recurrences post-treatment. Accumulating evidence suggests that cannabidiol (CBD), a non-psychoactive derivative of cannabis, can synergise with various anticancer agents to increase their efficacy. However, CBD demonstrates low bioavailability, which is attributed to factors relating to poor water compatibility, poor absorption and rapid metabolism. Nanotechnology offers tools that address these issues and enhance the biological efficiency and targeted specificity of anticancer agents. Herein, we highlighted the standard therapeutic modalities of MM and their pitfalls, as well as pointed out the need for further investigation into PDT combination therapy with CBD.

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3-12.8 μm (780-1890 cm^-1), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations.

Autofluorescence spectroscopy has emerged in recent years as a powerful tool to report label-free contrast between normal and diseased tissues, both in vivo and ex-vivo. We report the application of an instrument employing an optical fiber probe and capable of performing real-time autofluorescence lifetime imaging at a macroscopic scale, under bright background conditions. We validate and demonstrate the practicality of this technology to discriminate healthy against neoplastic tissue in freshly excised tumor biopsies. The capability of delineating tumor margins through processing the fluorescence decays in the phasors domain was demonstrated on four different types of cancer, highlighting the broad range of potential clinical applications for the proposed approach. The presented results suggest that our autofluorescence lifetime imaging probe, together with phasor analysis, can offer a real-time tool to observe lifetime contrast on tissues and, thus, is a suitable candidate for improving in situ tissue diagnostics during surgery.

In this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern, such as hospitals, schools, and so on. The proposed spectroscopy method supported with machine learning for real-time detection of infectious agents will eliminate the need for time-consuming processes, which contribute to reducing costs. The spectra in range 220-750 nm were used for the study. We achieve accuracy of our prediction model up to 68% with using only absorption spectrophotometer and machine learning. The use of such a set makes the method universal, due to the possibility of using many different detectors.

Optical clearing agents (OCAs) are substances that temporarily modify tissue's optical properties, enabling better imaging and light penetration. This study aimed to assess the impact of OCAs on the nail bed and blood using in vivo and in vitro optical methods. In the in vivo part, OCAs were applied to the nail bed, and optical coherence tomography and optical digital capillaroscopy were used to evaluate their effects on optical clearing and capillary blood flow, respectively. In the in vitro part, the collected blood samples were incubated with the OCA and blood aggregation properties were estimated using diffuse light scattering techniques. The results indicate that OCAs significantly influence the optical properties of the nail bed and blood microrheology. These findings suggest that OCAs hold promise for improving optical imaging and diagnostics, particularly for nail bed applications, and can modify blood microrheology.

The broadband absorption coefficient spectrum of the rabbit lung presents some particular characteristics that allow the identification of the chromophores in this tissue. By performing a weighted combination of the absorption spectra of water, hemoglobin, DNA, proteins and the pigments melanin and lipofuscin, it was possible to obtain a good match to the experimental absorption spectrum of the lung. Such reconstruction provided reasonable information about the contents of the tissue components in the lung tissue, and allowed to identify a similar accumulation of melanin and lipofuscin.

With the objective of developing new methods to acquire diagnostic information, the reconstruction of the broadband absorption coefficient spectra (μ_a [λ]) of healthy and chromophobe renal cell carcinoma kidney tissues was performed. By performing a weighted sum of the absorption spectra of proteins, DNA, oxygenated, and deoxygenated hemoglobin, lipids, water, melanin, and lipofuscin, it was possible to obtain a good match of the experimental μ_a (λ) of both kidney conditions. The weights used in those reconstructions were estimated using the least squares method, and assuming a total water content of 77% in both kidney tissues, it was possible to calculate the concentrations of the other tissue components. It has been shown that with the development of cancer, the concentrations of proteins, DNA, oxygenated hemoglobin, lipids, and lipofuscin increase, and the concentration of melanin decreases. Future studies based on minimally invasive spectral measurements will allow cancer diagnosis using the proposed approach.

COVID-19-related pneumonia is typically diagnosed using chest x-ray or computed tomography images. However, these techniques can only be used in hospitals. In contrast, thermal cameras are portable, inexpensive devices that can be connected to smartphones. Thus, they can be used to detect and monitor medical conditions outside hospitals. Herein, a smartphone-based application using thermal images of a human back was developed for COVID-19 detection. Image analysis using a deep learning algorithm revealed a sensitivity and specificity of 88.7% and 92.3%, respectively. The findings support the future use of noninvasive thermal imaging in primary screening for COVID-19 and associated pneumonia.

This study investigates the relationship between body hydration levels and skin hydration using spatially resolved diffuse reflectance spectroscopy. The research involved monitoring skin dehydration and rehydration under various conditions, including thermal and physical loads on healthy volunteers, and diuretic therapy in patients with edema syndrome. Findings indicate a correlation between body mass reduction and skin hydration: a 1% loss in body mass corresponds to a 10% decrease in skin hydration. During thermal stress, water absorption at 970 nm decreased monotonically without recovery. Physical activity resulted in approximately 10% changes in skin water content within 20 min, followed by rehydration. Patients with edema syndrome exhibited the most substantial decrease in water absorption amplitude, at nearly 30%, during diuretic treatment. These results support optical spectroscopy as a non-invasive tool for assessing body hydration, with implications for developing portable hydration monitoring devices for clinical and sports applications.