Continuous monitoring of endotracheal tube position with near infrared light.

Significance: Endotracheal intubation is a common approach for airway management in critically ill patients. However, the position of the endotracheal tube (ETT) may be altered during the procedure due to head movements. Accidental displacement or dislodge of the ETT may reduce the airflow, leading to moderate to severe complications, and in some cases even fatality. Therefore, timely detection of changes in ETT position in the trachea is critical to ensure immediate and intermediate interventions to maintain the ETT in the proper position. Currently, there are no widely utilized tools for real-time monitoring of ETT positions. Aim: The goal of this study is to develop a cost-effective and easy-to-use near-infrared (NIR) device, named Opt-ETT, capable of continuously monitoring the ETT position in the trachea of a patient. Approach: A side-firing fiber is attached to the side of the ETT to illuminate the trachea tissue with NIR light, and a detector board containing five phototransistors is affixed to the chest skin to measure the intensity of diffusely transmitted light. Displacement of the ETT is estimated using second-order polynomial fitting to the ratios of the phototransistor readings. Monte Carlo simulations, ex vivo experiment on porcine tissue, and in vivo experiments using a swine model have been conducted to assess the feasibility of the device. Results: The design of the Opt-ETT device has been verified by the Monte Carlo simulations and ex vivo experiment. The estimation of displacement from in vivo experiments using the Opt-ETT exhibited a high degree of agreement with that measured by a reference sensor, with a discrepancy between -1.0 to +1.5 mm within a displacement range from -15 to +15 mm. Conclusions: The Opt-ETT device provides a potentially cost-effective solution for real-time and continuous monitoring of ETT position in patient during an intubation procedure.

[Advances on BTB protein ubiquitination mediated plant development and stress response].

The BTB (broad-complex, tramtrack, and bric-à-brac) domain is a highly conserved protein interaction motif in eukaryotes. They are widely involved in transcriptional regulation, protein degradation and other processes. Recently, an increasing number of studies have shown that these genes play important roles in plant growth and development, biotic and abiotic stress processes. Here, we summarize the advances of these proteins ubiquitination-mediated development and abiotic stress responses in plants based on the protein structure, which may facilitate the study of this type of gene in plants.

Deep learning classification of deep ultraviolet fluorescence images toward intra-operative margin assessment in breast cancer.

Background: Breast-conserving surgery is aimed at removing all cancerous cells while minimizing the loss of healthy tissue. To ensure a balance between complete resection of cancer and preservation of healthy tissue, it is necessary to assess themargins of the removed specimen during the operation. Deep ultraviolet (DUV) fluorescence scanning microscopy provides rapid whole-surface imaging (WSI) of resected tissues with significant contrast between malignant and normal/benign tissue. Intra-operative margin assessment with DUV images would benefit from an automated breast cancer classification method. Methods: Deep learning has shown promising results in breast cancer classification, but the limited DUV image dataset presents the challenge of overfitting to train a robust network. To overcome this challenge, the DUV-WSI images are split into small patches, and features are extracted using a pre-trained convolutional neural network-afterward, a gradient-boosting tree trains on these features for patch-level classification. An ensemble learning approach merges patch-level classification results and regional importance to determine the margin status. An explainable artificial intelligence method calculates the regional importance values. Results: The proposed method's ability to determine the DUV WSI was high with 95% accuracy. The 100% sensitivity shows that the method can detect malignant cases efficiently. The method could also accurately localize areas that contain malignant or normal/benign tissue. Conclusion: The proposed method outperforms the standard deep learning classification methods on the DUV breast surgical samples. The results suggest that it can be used to improve classification performance and identify cancerous regions more effectively.

Analysis of Deep Ultraviolet Fluorescence Images for Intraoperative Breast Tumor Margin Assessment.

Positive margin status after breast-conserving surgery (BCS) is a predictor of higher rates of local recurrence. Intraoperative margin assessment aims to achieve negative surgical margin status at the first operation, thus reducing the re-excision rates that are usually associated with potential surgical complications, increased medical costs, and mental pressure on patients. Microscopy with ultraviolet surface excitation (MUSE) can rapidly image tissue surfaces with subcellular resolution and sharp contrasts by utilizing the nature of the thin optical sectioning thickness of deep ultraviolet light. We have previously imaged 66 fresh human breast specimens that were topically stained with propidium iodide and eosin Y using a customized MUSE system. To achieve objective and automated assessment of MUSE images, a machine learning model is developed for binary (tumor vs. normal) classification of obtained MUSE images. Features extracted by texture analysis and pre-trained convolutional neural networks (CNN) have been investigated for sample descriptions. A sensitivity, specificity, and accuracy better than 90% have been achieved for detecting tumorous specimens. The result suggests the potential of MUSE with machine learning being utilized for intraoperative margin assessment during BCS.

Automated assessment of breast margins in deep ultraviolet fluorescence images using texture analysis.

Microscopy with ultraviolet surface excitation (MUSE) is increasingly studied for intraoperative assessment of tumor margins during breast-conserving surgery to reduce the re-excision rate. Here we report a two-step classification approach using texture analysis of MUSE images to automate the margin detection. A study dataset consisting of MUSE images from 66 human breast tissues was constructed for model training and validation. Features extracted using six texture analysis methods were investigated for tissue characterization, and a support vector machine was trained for binary classification of image patches within a full image based on selected feature subsets. A weighted majority voting strategy classified a sample as tumor or normal. Using the eight most predictive features ranked by the maximum relevance minimum redundancy and Laplacian scores methods has achieved a sample classification accuracy of 92.4% and 93.0%, respectively. Local binary pattern alone has achieved an accuracy of 90.3%.

Differentially phosphorylated proteins in the crimped and straight wool of Chinese Tan sheep.

Proteins can be post-translationally modified and this can be important in the regulation of cellular processes and function. However, little is known about whether protein phosphorylation plays a role in regulating wool fibre properties. In this study, we used a chemical labelling method combined with a high performance liquid chromatography-mass spectrometry (HPLC-MS) analysis to compare the phosphopeptides present in the wool of three Tan sheep with highly crimped wool and three Tan sheep with straighter wool. Thirty-six phosphopeptides that had differences in relative abundance between these two types of wool were identified. These peptides were derived from 28 to 33 different proteins, including two keratins (Ks) and 7 to 12 keratin-associated proteins (KAPs), with these proteins being common structural components of the wool fibre. The crimped wool had a higher relative abundance of phosphorylated K38, K72 and KAP13-x, whereas the straighter wool had a higher relative abundance of phosphorylated KAP2-1, KAP6-1, KAP4-x, KAP10-x and KAP13-y. These results confirm the phosphorylation of wool Ks and KAPs, and suggest that differential phosphorylation of Ks and KAPs may affect wool fibre crimping in Tan sheep. SIGNIFICANCE: Protein phosphorylation can alter the structural conformation and interaction of a protein, and hence affect the cellular processes that the protein undertakes. In this study, we compared the suite of phosphorylated proteins in crimped and straight wool from Chinese Tan sheep and found that some keratins and keratin-associated proteins were phosphorylated. Crimped wool had more keratin phosphorylation, while straight wool had more keratin-associated protein phosphorylation, with this suggesting that wool fibre crimping may be a regulated by phosphorylation of some wool proteins. This suggests that wool traits may be under epigenetic control and that post-translation modifications need to be considered in breeding for different wool types.

Rapid assessment of breast tumor margins using deep ultraviolet fluorescence scanning microscopy.

SIGNIFICANCE: Re-excision rates for women with invasive breast cancer undergoing breast conserving surgery (or lumpectomy) have decreased in the past decade but remain substantial. This is mainly due to the inability to assess the entire surface of an excised lumpectomy specimen efficiently and accurately during surgery. AIM: The goal of this study was to develop a deep-ultraviolet scanning fluorescence microscope (DUV-FSM) that can be used to accurately and rapidly detect cancer cells on the surface of excised breast tissue. APPROACH: A DUV-FSM was used to image the surfaces of 47 (31 malignant and 16 normal/benign) fresh breast tissue samples stained in propidium iodide and eosin Y solutions. A set of fluorescence images were obtained from each sample using low magnification (4 × ) and fully automated scanning. The images were stitched to form a color image. Three nonmedical evaluators were trained to interpret and assess the fluorescence images. Nuclear-cytoplasm ratio (N/C) was calculated and used for tissue classification. RESULTS: DUV-FSM images a breast sample with subcellular resolution at a speed of 1.0 min / cm2. Fluorescence images show excellent visual contrast in color, tissue texture, cell density, and shape between invasive carcinomas and their normal counterparts. Visual interpretation of fluorescence images by nonmedical evaluators was able to distinguish invasive carcinoma from normal samples with high sensitivity (97.62%) and specificity (92.86%). Using N/C alone was able to differentiate patch-level invasive carcinoma from normal breast tissues with reasonable sensitivity (81.5%) and specificity (78.5%). CONCLUSIONS: DUV-FSM achieved a good balance between imaging speed and spatial resolution with excellent contrast, which allows either visual or quantitative detection of invasive cancer cells on the surfaces of a breast surgical specimen.

A Dual-modality Smartphone Microendoscope for Quantifying the Physiological and Morphological Properties of Epithelial Tissues.

We report a nonconcurrent dual-modality fiber-optic microendoscope (named SmartME) that integrates quantitative diffuse reflectance spectroscopy (DRS) and high-resolution fluorescence imaging (FLI) into a smartphone platform. The FLI module has a spatial resolution of ~3.5 µm, which allows the determination of the nuclear-cytoplasmic ratio (N/C) of epithelial tissues. The DRS has a spectral resolution of ~2 nm and can measure the total hemoglobin concentration (THC) and scattering properties of epithelial tissues with mean errors of 4.7% and 6.9%, respectively, which are comparable to the errors achieved with a benchtop spectrometer. Our preliminary in vivo studies from a single healthy human subject demonstrate that the SmartME can noninvasively quantify the tissue parameters of normal human oral mucosa tissues, including labial mucosa tissue, gingival tissue, and tongue dorsum tissue. The THCs of the three oral mucosa tissues are significantly different from each other (p ≤ 0.003). The reduced scattering coefficients of the gingival and labial tissues are significantly different from those of the tongue dorsum tissue (p < 0.001) but are not significantly different from each other. The N/Cs for all three tissue types are similar. The SmartME has great potential to be used as a portable, cost-effective, and globally connected tool to quantify the THC and scattering properties of tissues in vivo.

Decellularized cartilage as a prospective scaffold for cartilage repair.

Articular cartilage lacks self-healing capacity, and there is no effective therapy facilitating cartilage repair. Osteoarthritis (OA) due to cartilage defects represents large and increasing healthcare burdens worldwide. Nowadays, the generation of scaffolds to preserve bioactive factors and the biophysical environment has received increasing attention. Furthermore, improved decellularization technology has provided novel insights into OA treatment. This review provides a comparative account of different cartilage defect therapies. Furthermore, some recent effective decellularization protocols have been discussed. In particular, this review focuses on the decellularization ratio of each protocol. Moreover, these protocols were compared particularly on the basis of immunogenicity and mechanical functionality. Further, various recellularization methods have been enlisted and the reparative capacity of decellularized cartilage scaffolds is evaluated herein. The advantages and limitations of different recellularization processes have been described herein. This provides a basis for the generation of decellularized cartilage scaffolds, thereby potentially promoting the possibility of decellularization as a clinical therapeutic target.

Statistical analysis of motion contrast in optical coherence tomography angiography.

Optical coherence tomography angiography (Angio-OCT), mainly based on the temporal dynamics of OCT scattering signals, has found a range of potential applications in clinical and scientific research. Based on the model of random phasor sums, temporal statistics of the complex-valued OCT signals are mathematically described. Statistical distributions of the amplitude differential and complex differential Angio-OCT signals are derived. The theories are validated through the flow phantom and live animal experiments. Using the model developed, the origin of the motion contrast in Angio-OCT is mathematically explained, and the implications in the improvement of motion contrast are further discussed, including threshold determination and its residual classification error, averaging method, and scanning protocol. The proposed mathematical model of Angio-OCT signals can aid in the optimal design of the system and associated algorithms.

Acute Tumor Lactate Perturbations as a Biomarker of Genotoxic Stress: Development of a Biochemical Model.

Ionizing radiation is the primary nonsurgical treatment modality for solid tumors. Its effectiveness is impacted by temporal constraints such as fractionation, hypoxia, and development of radioresistant clones. Biomarkers of acute radiation response are essential to developing more effective clinical algorithms. We hypothesized that acute perturbations in tumor lactate levels act as a surrogate marker of radiation response. In vitro experiments were carried out using validated human-derived cell lines from three histologies: anaplastic thyroid carcinoma (ATC), head and neck squamous cell carcinoma (HNSCC), and papillary thyroid carcinoma (PTC). Cellular metabolic activity was measured using standard biochemical assays. In vivo validation was performed using both an orthotopic and a flank derivative of a previously established ATC xenograft murine model. Irradiation of cells and tumors triggered a rapid, dose-dependent, transient decrease in lactate levels that was reversed by free radical scavengers. Acute lactate perturbations following irradiation could identify hypoxic conditions and correlated with hypoxia-induced radioresistance. Mutant TP53 cells and cells in which p53 activity was abrogated (shRNA) demonstrated a blunted lactate response to irradiation, consistent with a radioresistant phenotype. Lactate measurements therefore rapidly detected both induced (i.e., hypoxia) and intrinsic (i.e., mutTP53-driven) radioresistance. We conclude that lactate is a quantitative biomarker of acute genotoxic stress, with a temporal resolution that can inform clinical decision making. Combined with the spatial resolution of newly developed metabolic imaging platforms, this biomarker could lead to the development of truly individualized treatment strategies.

Density functional theory studies on the electronic and vibrational spectra of octaethylporphyrin diacid.

The ground-state structure and electronic and vibrational spectra of octaethylporphyrin diacid (H4OEP2+) have been studied with the density functional theory. The geometrical parameters computed with B3LYP, PBE1PBE and mPW1PW91 functionals and 6-31G* basis sets are well consistent with the experimental values. Electronic absorption spectrum of H4OEP2+ has been studied with the time-dependent DFT method, and the calculated excitation energies and oscillator strengths are compared with the experimental results. The Raman and IR spectra of H4OEP2+ and the Raman spectrum of its N-deuterated analogue (D4OEP2+) were measured. The observed Raman and IR bands have been assigned based on the frequency calculations at the B3LYP/6-31G* level of theory.