Barnettnolan0441

This approach potentially provides physicians with valuable and complementary information that holds promises in helping with the diagnostics of colon tissue specimens.We propose surface plasmon resonance biosensors based on crumpled graphene and molybdenum disulphide (MoS2) flakes supported on stretchable polydimethylsiloxane (PDMS) or silicon substrates. Accumulation of specific biomarkers resulting in measurable shifts in the resonance wavelength of the plasmon modes of two-dimensional (2D) material structures, with crumpled structures demonstrating large refractive index shifts. Using theoretical calculations based on the semiclassical Drude model, combined with the finite element method, we demonstrate that the interaction between the surface plasmons of crumpled graphene/MoS2 layers and the surrounding analyte results in high sensitivity to biomarker driven refractive index shifts, up to 7499 nm/RIU for structures supported on silicon substrates. We can achieve a high figure of merit (FOM), defined as the ratio of the refractive index sensitivity to the full width at half maximum of the resonant peak, of approximately 62.5 RIU-1. Furthermore, the sensing properties of the device can be tuned by varying crumple period and aspect ratio through simple stretching and integrating material interlayers. By stacking multiple 2D materials in heterostructures supported on the PDMS layer, we produced hybrid plasmon resonances detuned from the PDMS absorbance region allowing higher sensitivity and FOM compared to pure crumpled graphene structures on the PDMS substrates. The high sensitivity and broad mechanical tunability of these crumpled 2D material biosensors considerable advantages over traditional refractive index sensors, providing a new platform for ultrasensitive biosensing.Advancements in medical laser technology have paved the way for its widespread acceptance in a variety of treatments and procedures. Selectively targeting particular tissue structures with minimally invasive procedures limits the damage to surrounding tissue and allows for reduced post-procedural downtime. In many treatments that are hyperthermia-based, the efficiency depends on the achieved temperature within the targeted tissues. Current approaches for monitoring subdermal temperature distributions are either invasive, complex, or offer inadequate spatial resolution. Numerical studies are often therapy-tailored and source tissue parameters from the literature, lacking versatility and a tissue-specific approach. Here, we show a protocol that estimates the temperature distribution within the tissue based on a thermographic recording of its surface temperature evolution. It couples a time-dependent matching algorithm and thermal-diffusion-based model, while recognizing tissue-specific characteristics yielded by a fast calibration process. The protocol was employed during hyperthermic laser treatment performed ex-vivo on a heterogeneous porcine tissue, and in-vivo on a human subject. In both cases the calibrated thermal parameters correlate with the range of values reported by other studies. The matching algorithm sufficiently reproduced the temperature dynamics of heterogeneous tissue. The estimated temperature distributions within ex-vivo tissue were validated by simultaneous reference measurements, and the ones estimated in-vivo reveal a distribution trend that correlates well with similar studies. The presented method is versatile, supported by the protocol for tissue-specific tailoring, and can readily be implemented for temperature monitoring of various hyperthermia-based procedures by means of recording the surface temperature evolution with a miniature thermal camera implemented within a handheld laser scanner or similar.Surgical removal is the primary treatment for liver cancer, but frequent recurrence caused by residual malignant tissue remains an important challenge, as recurrence leads to high mortality. It is unreliable to distinguish tumors from normal tissues merely under visual inspection. Hyperspectral imaging (HSI) has been proved to be a promising technology for intra-operative use by capturing the spatial and spectral information of tissue in a fast, non-contact and label-free manner. In this work, we investigated the feasibility of HSI for liver tumor delineation on surgical specimens using a multi-task U-Net framework. Measurements are performed on 19 patients and a dataset of 36 specimens was collected with corresponding pathological results serving as the ground truth. The developed framework can achieve an overall sensitivity of 94.48% and a specificity of 87.22%, outperforming the baseline SVM method by a large margin. In particular, we propose to add explanations on the well-trained model from the spatial and spectral dimensions to show the contribution of pixels and spectral channels explicitly. On that basis, a novel saliency-weighted channel selection method is further proposed to select a small subset of 5 spectral channels which provide essentially as much information as using all 224 channels. According to the dominant channels, the absorption difference of hemoglobin and bile content in the normal and malignant tissues seems to be promising markers that could be further exploited.Nanoparticles (NPs) based drugs for topical administration are gaining interest in the biomedical world. However, a study tool of their penetration depth to the different tissue layers without additional markers or contrast agents is required in order to relieve safety concerns. While common diagnostic tools, e.g. X-ray, computed tomography or magnetic resonance imaging, can provide in vivo detection of the metallic NPs, their resolution cannot determine the exact penetration depth to the thin skin layers. In this work, we propose the noninvasive nanophotonics iterative multi-plane optical property extraction (IMOPE) technique for the novel iron-based NPs detection in leishmaniasis lesions. The optical properties of the different tissue layers epidermis, dermis, subcutaneous fat and muscle, were examined before and after topical drug administration. The potential topical drug was detected in the epidermis (∼13µm) and dermis (∼160µm) layers in mice lesions at different stages of the disease (two or four weeks post infection). The lesion size influence on the detection was also observed, where in larger lesions the IMOPE senses a greater presence of the topical drug.Laser Doppler holography (LDH) is a full-field blood flow imaging technique able to reveal human retinal and choroidal blood flow with high temporal resolution. We here report on using LDH in the anterior segment of the eye without making changes to the instrument. Blood flow in the bulbar conjunctiva and episclera as well as in corneal neovascularization can be effectively imaged. We additionally demonstrate simultaneous holographic imaging of the anterior and posterior segments by simply adapting the numerical propagation distance to the plane of interest. We used this feature to track the movements of the retina and pupil with high temporal resolution. Finally, we show that the light backscattered by the retina can be used for retro-illumination of the anterior segment. Hence digital holography can reveal opacities caused by absorption or diffusion in the cornea and eye lens.Optical coherence tomography (OCT) has become widespread in clinical applications in which precise three-dimensional functional imaging of living organs is required. Nevertheless, the kidney is inaccessible for the high resolution OCT imaging due to a high light attenuation coefficient of skin and soft tissues that significantly limits the penetration depth of the probing laser beam. Here, we introduce a surgical protocol and fixation scheme that enables functional visualization of kidney's peritubular capillaries via OCT microangiography. The model of reversible/irreversible glomerulus embolization using drug microcarriers confirms the ability of OCT to detect circulatory disorders. This approach can be used for choosing optimal carriers, their dosages and diagnosis of other blood flow pathologies.The nerve fiber bundles constitutive of the white matter in the brain are organized in such a way that they exhibit a certain degree of structural anisotropy and birefringence. The birefringence exhibited by such aligned fibrous tissue is known to be extremely sensitive to small pathological alterations. Indeed, highly aligned anisotropic fibers exhibit higher birefringence than structures with weaker alignment and anisotropy, such as cancerous tissue. In this study, we performed experiments on thick coronal slices of a healthy human brain to explore the possibility of (i) measuring, with a polarimetric microscope the birefringence exhibited by the white matter and (ii) relating the measured birefringence to the fiber orientation and the degree of alignment. This is done by analyzing the spatial distribution of the degree of polarization of the backscattered light and its variation with the polarization state of the probing beam. Proteasomal inhibitors We demonstrate that polarimetry can be used to reliably distinguish between white and gray matter, which might help to intraoperatively delineate unstructured tumorous tissue and well organized healthy brain tissue. In addition, we show that our technique is able to sensitively reconstruct the local mean nerve fiber orientation in the brain, which can help to guide tumor resections by identifying vital nerve fiber trajectories thereby improving the outcome of the brain surgery.Limited by the lack of training spectral data in different kinds of tissues, the diagnostic accuracy of laser-induced breakdown spectroscopy (LIBS) is hard to reach the desired level with normal supervised learning identification methods. In this paper, we proposed to apply the predictive data clustering methods with supervised learning methods together to identify tissue information accurately. The meanshift clustering method is introduced to compare with three other clustering methods which have been used in LIBS field. We proposed the cluster precision (CP) score as a new criterion to work with Calinski-Harabasz (CH) score together for the evaluation of the clustering effect. The influences of principal component analysis (PCA) on all four kinds of clustering methods are also analyzed. PCA-meanshift shows the best clustering effect based on the comprehensive evaluation combined CH and CP scores. Based on the spatial location and feature similarity information provided by the predictive clustering, the PCA-Meanshift can improve diagnosis accuracy from less than 95% to 100% for all classifiers including support vector machine (SVM), k nearest neighbor (k-NN), soft independent modeling of class analogy (Simca) and random forests (RF) models.This study aims to demonstrate the feasibility of cylindrical interstitial laser ablation (CILA) in porcine pancreatic tissue to develop a EUS-guided PC ablation technique with enhanced safety. A diffusing applicator created a uniformly symmetrical laser ablation in pancreatic tissue. Ex vivo tests presented that both ablation thickness and volume increased linearly with the applied power (R2 = 0.96 and 0.90, respectively) without carbonization and fiber degradation. The numerical simulations matched well with the experimental results in terms of temperature development and thermal damage (deviation of ≤ 15%). In vivo tests with EUS confirmed easy insertion and high durability of the diffusing applicator. EUS-guided CILA warranted a feasible therapeutic capacity of ablating in vivo pancreatic tissue. The proposed EUS-guided CILA can be a feasible therapeutic approach to treat PC with predictable thermal ablation and enhanced safety.