Hypoxia-enhanced YAP1-EIF4A3 interaction drives circ_0007386 circularization by competing with CRIM1 pre-mRNA linear splicing and promotes non-small cell lung cancer progression.

BACKGROUND: The progression of non-small cell lung cancer (NSCLC) is significantly influenced by circular RNAs (circRNAs), especially in tumor hypoxia microenvironment. However, the precise functions and underlying mechanisms of dysregulated circRNAs in NSCLC remain largely unexplored. METHODS: Differentially expressed circRNAs in NSCLC tissues were identified through high-throughput RNA sequencing. The characteristics of circ_0007386 were rigorously confirmed via Sanger sequencing, RNase R treatment and actinomycin D treatment. The effects of circ_0007386 on proliferation and apoptosis were investigated using CCK8, cloning formation assays, TUNEL staining, and flow cytometry assays in vitro. In vivo, xenograft tumor models were used to evaluate its impact on proliferation. Mechanistically, the regulatory relationships of circ_0007386, miR-383-5p and CIRBP were examined through dual luciferase reporter assays and rescue experiments. Additionally, we detected the binding of EIF4A3 to CRIM1 pre-mRNA by RNA immunoprecipitation and the interaction between YAP1 and EIF4A3 under hypoxic conditions by co-immunoprecipitation. RESULTS: Our investigation revealed a novel circRNA, designated as circ_0007386, that was upregulated in NSCLC tissues and cell lines. Circ_0007386 modulated proliferation and apoptosis in NSCLC both in vitro and in vivo. Functionally, circ_0007386 acted as a sponge for miR-383-5p, targeting CIRBP, which influenced NSCLC cell proliferation and apoptosis via the PI3K/AKT signaling pathway. Furthermore, under hypoxic conditions, the interaction between YAP1 and EIF4A3 was enhanced, leading to the displacement of EIF4A4 from binding to CRIM1 pre-mRNA. This facilitated the back-splicing of CRIM1 pre-mRNA, increasing the formation of circ_0007386. The circ_0007386/miR-383-5p/CIRBP axis was significantly associated with the clinical features and prognosis of NSCLC patients. CONCLUSIONS: Circ_0007386, regulated by YAP1-EIF4A3 interaction under hypoxia conditions, plays an oncogenic role in NSCLC progression via the miR-383-5p/CIRBP axis.

Selectivity Quantification with the Fluorescent Quantitative Model-Assisted Semi-Selective Probe (Carbon Dots): Accurate Determination of Chlortetracycline in Aqueous Environments with Interference.

Probes such as carbon dots (C-dots) have extensive and important applications in the quantitative analysis of complex biological and environmental systems. However, the development of probes is often hindered by incomplete selectivity, i.e., a probe that responds to one substance is also prone to respond to coexisting structurally similar substances. Therefore, the above dilemma often leads to be developed as semi-selective probes, so that the development of probes is abandoned halfway. This work shows how a semi-selective probe can enhance selectivity by combining a proper multivariate calibration model. Primarily, we developed a semi-selective fluorescent probe that responded to tetracyclines (TCs) with discarded tobacco leaves. Then, we introduced the multivariate quantitative fluorescence model (QFM) to enhance its selectivity and solve the problem of fluorescence spectral shift. For the determination of chlortetracycline (CTC) with this semi-selective C-dots probe in mineral and lake water samples and compared to the traditional quantitative model, the introduced QFM resulted in an average relative predictive error (ARPE) in mineral water spiked samples decreased from 57.1 to 5.6%, which reduced the ARPE in the lake water spiked samples from 18.1 to 4.7%. The above results show that the QFM-assisted semi-selective probe C-dots strategy (QFMC-dots) can enhance selectivity, and QFMC-dots achieved high-selective and accurate determination of CTC in interfering mineral and lake water samples, with the limit of detection and limit of quantitation of 0.55 and 1.66 µM, respectively. The proposed strategy of enhancing selectivity by introducing a proper multivariate calibration model can reduce the difficulty and increase success rate of developing probes, which can be expected to provide an interesting alternative for the development of probes, especially when encountering semi-selective problems.

The role of Sirtuin 1 and its activators in age-related lung disease.

Aging is a major driving factor in lung diseases. Age-related lung disease is associated with downregulated expression of SIRT1, an NAD+-dependent deacetylase that regulates inflammation and stress resistance. SIRT1 acts by inducing the deacetylation of various substrates and regulates several mechanisms that relate to lung aging, such as genomic instability, lung stem cell exhaustion, mitochondrial dysfunction, telomere shortening, and immune senescence. Chinese herbal medicines have many biological activities, exerting anti-inflammatory, anti-oxidation, anti-tumor, and immune regulatory effects. Recent studies have confirmed that many Chinese herbs have the effect of activating SIRT1. Therefore, we reviewed the mechanism of SIRT1 in age-related lung disease and explored the potential roles of Chinese herbs as SIRT1 activators in the treatment of age-related lung disease.

Deep-Learning-Based Automated Identification and Visualization of Oral Cancer in Optical Coherence Tomography Images.

Early detection and diagnosis of oral cancer are critical for a better prognosis, but accurate and automatic identification is difficult using the available technologies. Optical coherence tomography (OCT) can be used as diagnostic aid due to the advantages of high resolution and non-invasion. We aim to evaluate deep-learning-based algorithms for OCT images to assist clinicians in oral cancer screening and diagnosis. An OCT data set was first established, including normal mucosa, precancerous lesion, and oral squamous cell carcinoma. Then, three kinds of convolutional neural networks (CNNs) were trained and evaluated by using four metrics (accuracy, precision, sensitivity, and specificity). Moreover, the CNN-based methods were compared against machine learning approaches through the same dataset. The results show the performance of CNNs, with a classification accuracy of up to 96.76%, is better than the machine-learning-based method with an accuracy of 92.52%. Moreover, visualization of lesions in OCT images was performed and the rationality and interpretability of the model for distinguishing different oral tissues were evaluated. It is proved that the automatic identification algorithm of OCT images based on deep learning has the potential to provide decision support for the effective screening and diagnosis of oral cancer.

Multiscale reconstruction of bronchus and cancer cells in human lung adenocarcinoma.

BACKGROUND: While previous studies primarily focused on the structure of the normal whole mouse lung, the whole bronchus and cytoarchitectural details of the mouse intact lung lobe have been discovered at single-cell resolution. Revealing the sophisticated lung adenocarcinoma structure at three-dimensional (3D) and single-cell level remains a fundamental and critical challenge for the pathological mechanism research of lung adenocarcinoma (LA). METHODS: Fluorescence micro-optical Sectioning Tomography (fMOST) combined with PI staining were used to obtain the 3D imaging of the human LA tissue at single-cell resolution. RESULTS: With a spatial resolution of 0.32 × 0.32 × 1.0 µm3, the dataset of human LA with single-cell precision consists of two channels, each of which contains information about the bronchi and the cytoarchitecture. The bronchial wall is thicker and the lumen is smaller in the cancer tissue, in which its original normal structure is vanished. More solid components, more clustered cancer cells with larger nucleoli, and more significant atypia are found in cancer tissue. In paracancerous tissue, the bronchial wall cells have a monolayer or bilayer structure, cluster along the wall, and are relatively dispersed. Few fibrous structures and occasional dissemination of spread through air spaces (STAS) are observed. CONCLUSIONS: Based on the human LA tissue dataset obtained by fMOST and PI staining, the bronchi and cells were reconstructed and visualized. This work provides a technical roadmap for studying the bronchus and cytoarchitectural structure and their spatial relationship in LA tissue, which may help with the understanding of the main histological structure of LA among pathologists.

Interference-free quantitation of aromatic amino acids in two complex systems by three-way calibration with ultraviolet-visible spectrophotometer: Exploration of trilinear decomposition of spectrum-pH data.

Aromatic amino acids play an extremely important role in life activities and participate in many biological processes. Their concentration levels are associated with a variety of diseases, such as phenylketonuria and colorectal cancer. Therefore, the quantification of aromatic amino acids is an important task. In the present work, a novel and rapid three-way analytical method was proposed to detect the levels of aromatic amino acids in prostate cancer cells (PC3 cells) and Dulbecco's modified minimal essential medium (DMEM cell culture), by using the affordable ultraviolet-visible spectrophotometer. First, spectrum-pH second-order data were designed per sample; Second, properties of the resulted spectrum-pH-sample three-way data were investigated by utilizing the parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), and constrained alternating trilinear decomposition (CATLD) algorithms, and a flexible scanning approach for determining the constraint parameters of CATLD was proposed; Third, a three-way calibration method based on the CATLD algorithm with the proposed scanning approach was developed for interference-free quantification of aromatic amino acids in these systems. The average relative predictive errors of validation (ARPEV) for phenylalanine, tyrosine, and tryptophan were 1.4%, 3.0%, and 0.7% in prostate cancer cells, and ARPEV for phenylalanine, tyrosine, and tryptophan were 4.1%, 1.2%, and 0.7% in DMEM cell culture. The predicted contents of tyrosine and tryptophan in DMEM cell culture were 64.2 ± 2.9 µg mL-1, 5.6 ± 0.3 µg mL-1, there are no significant differences in the concentrations between the developed analytical method and high performance liquid chromatography method. The proposed spectrum-pH-sample three-way calibration method based on CATLD algorithm can provide an interesting analytical strategy with high selectivity and accuracy for ultraviolet-visible spectrophotometer.

Classification of neck tissues in OCT images by using convolutional neural network.

Identification and classification of surrounding neck tissues are very important in thyroid surgery. The advantages of optical coherence tomography (OCT), high resolution, non-invasion, and non-destruction make it have great potential in identifying different neck tissues during thyroidectomy. We studied the automatic classification for neck tissues in OCT images based on convolutional neural network in this paper. OCT images of five kinds of neck tissues were collected firstly by our home-made swept source (SS-OCT) system, and a dataset was built for neural network training. Three image classification neural networks: LeNet, VGGNet, and ResNet, were used to train and test the dataset. The impact of transfer learning on the classification of neck tissue OCT images was also studied. Through the comparison of accuracy, it was found that ResNet has the best classification accuracy among the three networks. In addition, transfer learning did not significantly improve the accuracy, but it can somewhat accelerate the convergence of the network and shorten the network training time.

Waste tobacco leaves derived carbon dots for tetracycline detection: Improving quantitative accuracy with the aid of chemometric model.

The recycling and reutilization of biomass wastes are significant for environmental protection and sustainable development. Recently, there have many studies on utilizing biomass wastes to produce carbon dots. Whereas, the spectrum shift effect that occurs in the quantitative application of carbon dots as fluorescent probes limits the accuracy of the quantitative analysis. In this work, waste tobacco leaves were used as the carbon source for synthesizing a novel carbon dots (CDs(WTL)) through a facile hydrothermal method. The CDs(WTL) possess a series of excellent properties, including good water solubility, well stability, and high fluorescence quantum yield. The fluorescent intensity of the CDs(WTL) can be quenched by tetracycline (TC) obviously, but there is a spectrum shift. In order to use the CDs(WTL) as fluorescent probes to quantify TC with higher accuracy, a quantification fluorescence model (QFM) was introduced to overcome this spectrum shift effect that often occurs. The coefficient of determination (R2) of traditional quantification model (TQ), partial least squares (PLS), and QFM are 0.9672, 0.9834, and 0.9991, respectively; the average relative predictive error (ARPE) of TQ, PLS, and QFM are 8.8%, 4.5%, and 3.9% for the spiked water samples, and 21.9%, 22.0%, and 2.9% for spiked tablet samples, respectively. The obtained results suggest that QFM is more accurate than PLS and TQ for the TC detection. By utilizing QFM, the spike recoveries (mean ± standard deviation) in three kinds of real tablet samples produced by different manufacturers are 98.9 ± 3.6%, 102.5 ± 6.2%, and 98.5 ± 2.7%, respectively; the spike recovery in river water samples is 99.4 ± 5.0%. In addition, high performance liquid chromatography (HPLC) was used as a reference method, the F and t tests suggest that there are no significant differences on the precision and accuracy between QFM and HPLC methods.

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography.

BACKGROUND AND OBJECTIVES: Distinguishing cancer from precancerous lesions is critical and challenging in oral medicine. As a noninvasive method, optical coherence tomography (OCT) has the advantages of real-time, in vivo, and large-depth imaging. Texture information hidden in OCT images can provide an important auxiliary effect for improving diagnostic accuracy. The aim of this study is to explore a reliable and accurate OCT-based method for the screening and diagnosis of human oral diseases, especially oral cancer. MATERIALS AND METHODS: Fresh ex vivo oral tissues including normal mucosa, leukoplakia with epithelial hyperplasia (LEH), and oral squamous cell carcinoma (OSCC) were imaged intraoperatively by a homemade OCT system, and 58 texture features were extracted to create computational models of these tissues. A principal component analysis algorithm was employed to optimize the combination of texture feature vectors. The identification based on artificial neural network (ANN) was proposed and the sensitivity/specificity was calculated statistically to evaluate the classification performance. RESULTS: A total of 71 sites of three types of oral tissues were measured, and 5176 OCT images of three types of oral tissues were used in this study. The superior classification result based on ANN was obtained with an average accuracy of 98.17%. The sensitivity and specificity of normal mucosa, LEH, and OSCC are 98.17% / 98.38%, 93.81% / 98.54%, and 98.11% / 99.04%, respectively. CONCLUSION: It is demonstrated from the high accuracies, sensitivities, and specificities that texture-based analysis can be used to identify oral precancerous and cancerous tissue in OCT images, and it has the potential to help surgeons in diseases screening and diagnosis effectively.

Classification of oral salivary gland tumors based on texture features in optical coherence tomography images.

Currently, the diagnoses of oral diseases primarily depend on the visual recognition of experienced clinicians. It has been proven that automatic recognition based on images can support clinical decision-making by extracting and analyzing objective hidden information. In recent years, optical coherence tomography (OCT) has become a powerful optical imaging technique with the advantages of high resolution and non-invasion. In our study, a dataset composed of four kinds of oral salivary gland tumors (SGTs) was obtained from a homemade swept-source OCT, including two benign and two malignant tumors. Seventy-six texture features were extracted from OCT images to create computational models of diseases. It was demonstrated that the artificial neural network (ANN) based on principal component analysis (PCA) can obtain high diagnostic sensitivity and specificity (higher than 99%) for these four kinds of tumors. The classification accuracy of each tumor is larger than 99%. In addition, the performances of two classifiers (ANN and support vector machine) were quantitatively evaluated based on SGTs. It was proven that the texture features in OCT images provided objective information to classify oral tumors.

Study on an artificial phenomenon observed in terahertz biological imaging.

Terahertz (THz) wave-based imaging of biological samples is an emerging but promising field. In the present work, we report an artificial phenomenon observed in imaging melanoma slices, which can lead to mistakenly interpretation of the experimental results. It was observed that a structure similar to but smaller than the sample contour appeared inside the melanoma slice image. The underlying mechanism of this phenomenon was then investigated both experimentally and theoretically. By imaging a regular standard sample (vinyl coverslip) with a THz time domain spectroscopy (THz-TDS) system and reconstructing its images at 0.8 and 1.2 THz, we can clearly observe the afore-mentioned artifacts. The experimental results are highly consistent with the simulations based on the Fresnel-Kirchhoff diffraction theory in which possible optical aberrations were incorporated. It can be concluded that this artifact was caused by the frequency-dependent diffraction of the sample edge. The work demonstrated here is essential for correct interpretation of the images obtained by the THz-TDS technique.

Classification of Salivary Gland Tumors Based on Quantitative Optical Coherence Tomography.

BACKGROUND AND OBJECTIVES: Visual inspection is the primary diagnostic method for oral diseases, and its accuracy of diagnosis mainly depends on surgeons' experience. Histological examination is still the golden standard, but it is invasive and time-consuming. In order to address these issues, as a noninvasive imaging technique, optical coherence tomography (OCT) can differentiate oral tissue with advantages of real-time, in situ, and high resolution. The aim of this study is to explore optimal quantitative parameters in OCT images to distinguish different salivary gland tumors. STUDY DESIGN/MATERIALS AND METHODS: OCT images of four salivary gland tumors were obtained from 14 patients, including mucoepidermoid carcinoma (MC), adenoid cystic carcinoma (ACC), basal cell adenoma (BCA), and pleomorphic adenoma (PA). Two parameters of optical attenuation coefficient (OAC) and standard deviation (SD) along the depth of OCT signal were combined to create a computational model of classification, and sensitivity/specificity of classification was calculated statistically to evaluate their results. RESULTS: A total of 5,919 two-dimensional (2D) OCT images were used for quantitative analysis. The classification sensitivities of 89.6%, 95.0%, 89.5%, 97.8%, and specificities of 97.6%, 99.0%, 98.0%, 98.2%, respectively, were obtained for MC, ACC, BCA, and PA, with the thresholds of 3.6 mm-1 based on OAC and 0.22/0.18 based on SD. CONCLUSION: It was demonstrated that OAC and SD could be considered as important parameters in quantitative analysis of OCT images for salivary gland tissue characterization and intraoperative diagnosis. It is of great potential value in promoting the application of this method based on OCT in clinical practice. Lasers Surg. © 2020 Wiley Periodicals LLC.

Multimodal imaging with integrated auto-fluorescence and optical coherence tomography for identification of neck tissues.

We report a multimodal optical system by combining OCT with autofluorescence imaging for identifying neck tissues, which can use the advantages of large field of view and high sensitivity for identifying parathyroid glands of fluorescence imaging, and high-resolution structural imaging of OCT to confirm them and identify lymph nodes and metastatic lymph nodes at the same time. It is proven that this multimodal optical system can be used to identify different neck tissues effectively and efficiently. We think that integrated auto-fluorescence and OCT imaging have the great potential in the application of navigation and assistant diagnosis of thyroid surgery.

Chlamydia trachomatis Infection, when Treated during Pregnancy, Is Not Associated with Preterm Birth in an Urban Safety-Net Hospital.

Preterm birth is a major public health problem, occurring in more than half a million births per year in the United States. A number of maternal conditions have been recognized as risk factors for preterm birth, but for the majority of cases, the etiology is not completely understood. Chlamydia trachomatis is one of the most prevalent sexually transmitted infections in the world. However, its role in adverse pregnancy outcome in women is still debated. In order to determine if genitourinary tract infection with C. trachomatis during pregnancy was associated with preterm birth, we conducted a case-control study on women who delivered at Boston Medical Center, an urban "safety-net" hospital that serves a socioeconomically disadvantaged and racially diverse population. Women with known risk factors for preterm birth or immune suppression were excluded. Variables collected on enrolled subjects included demographics; diagnosis of C. trachomatis during or prior to pregnancy; tobacco, alcohol, and illicit substance use; gestational age; and birthweight and gender of the newborn. We also collected urine for chlamydia testing at the time of delivery and placental biopsies for nucleic acid amplification and histological studies. A total of 305 subjects were enrolled: 100 who delivered preterm and 205 who delivered full term. Among those subjects, we identified 19 cases of pregnancy-associated C. trachomatis infection: 6/100 preterm and 13/205 full term, a difference which was not statistically significant. Only two cases of untreated chlamydia infection were identified postpartum, and both occurred in women who delivered at term. We conclude that genitourinary tract infection with C. trachomatis during pregnancy, when appropriately treated, is not associated with preterm birth.

Identification of oral cancer in OCT images based on an optical attenuation model.

Surgery is still the first choice to treat oral cancer, where it is important to detect surgical margins in order to reduce cancer recurrence and maintain oral-maxillofacial function simultaneously. As a non-invasive and in situ imaging technique, optical coherence tomography (OCT) can obtain images close to the resolution of histopathology, which makes it have great potential in intraoperative diagnosis. However, it is not enough to find surgical margins accurately just observing OCT images directly and qualitatively. The purpose of this study is to identify oral cancer in OCT images by investigating the quantitative difference of cancer and non-cancer tissue. Based on an available optical attenuation model and the axial confocal PSF of a home-made swept source OCT system, by using fresh ex vivo human oral tissues from 14 patients of oral squamous cell carcinoma (OSCC) as the samples, diagnosis with sensitivity (97.88%) and specificity (83.77%) was achieved at the attenuation threshold of 4.7 mm-1, and the accuracy of identification reached 91.15% in our study. Our preliminary results demonstrated that the oral cancer resection will be guided accurately and the clinical application of OCT will be further promoted by deeply mining the information hidden in OCT images.

Low-cost, ultracompact handheld optical coherence tomography probe for in vivo oral maxillofacial tissue imaging.

SIGNIFICANCE: Optical coherence tomography (OCT) has proven useful for detecting various oral maxillofacial abnormalities. To apply it to clinical applications including biopsy guidance and routine screening, a handheld imaging probe is indispensable. OCT probes reported for oral maxillofacial imaging were either based on a bulky galvanometric mirror pair (not compact or long enough) or a distal-end microelectromechanical systems (MEMS) scanner (raised safety concerns), or adapted from fiber-optic catheters (ill-suited for oral cavity geometry). AIM: To develop a handheld probe featuring great compactness and excellent maneuverability for oral maxillofacial tissue imaging. APPROACH: A dual-axis MEMS scanner was deployed at the proximal end of the probe and the scanned beam was relayed to the distal end through a 4f configuration. Such design provides both a perfect dual-axis telecentric scan and excellent compactness. RESULTS: A handheld probe with a rigid part 70 mm in length and 7 mm in diameter and weighing 25 g in total was demonstrated through both ex vivo and in vivo experiments, including structural visualization of various oral maxillofacial tissues and monitoring the recovery process of an oral mucosa canker sore. CONCLUSIONS: The proposed probe exhibits excellent maneuverability and imaging performance showing great potential in clinical applications.

Robust, accurate depth-resolved attenuation characterization in optical coherence tomography.

Depth-resolved optical attenuation coefficient is a valuable tissue parameter that complements the intensity-based structural information in optical coherent tomography (OCT) imaging. Herein we systematically analyzed the under- and over-estimation bias of existing depth-resolved methods when applied to real biological tissues, and then proposed a new algorithm that remedies these issues and accommodates general OCT data that contain incomplete decay and noise floor, thereby affording consistent estimation accuracy for practical biological samples of different scattering properties. Compared with other algorithms, our method demonstrates remarkably improved estimation accuracy and numerical robustness, as validated via numerical simulations and on experimental OCT data obtained from both silicone-TiO2 phantoms and human ventral tongue leukoplakia samples.

MiR-218 produces anti-tumor effects on cervical cancer cells in vitro.

BACKGROUND: As indoleamine-2,3-dioxygenase 1 (IDO1) is critical in tumor immune escape, we determined to study the regulatory mechanism of miR-218 on IDO1 in cervical cancer. METHODS: Real-time PCR (RT-qPCR) was carried out to measure the expression of miR-218. RT-qPCR and Western blot were performed to detect the expression of IDO1 in cervical cancer. Dual-luciferase reporter assay was used to determine the binding of miR-218 on the IDO1 3'UTR. Cell viability, apoptosis, and related factors were determined using cell counting kit-8 (CCK-8), Annexin-V/PI (propidium) assay, enzyme-linked immunosorbnent assay (ELISA), RT-qPCR, and Western blot assays after miR-218 mimics has been transfected to HeLa cervical cancer cells. RESULTS: MiR-218 was downregulated in cervical cancer. The expression of miR-218 was negatively correlated with IDO1 in cervical cancer tissues and cells. IDO1 is a direct target of miR-218. MiR-218 overexpression was found to inhibit cell viability and promoted apoptosis via activating the expression of Cleaved-Caspase-3 and to inhibit the expression of Survivin, immune factors (TGF-ß, VEGF, IL-6, PGE2, COX-2), and JAK2/STAT3 pathway. CONCLUSION: MiR-218 inhibits immune escape of cervical cancer cells by direct downregulating IDO1.

Species-specific differences in regulation of macrophage inflammation by the C3a-C3a receptor axis.

Complement is an important arm of the innate immune system. Recent studies have shown that products of complement pathway activation can interact directly with other innate immune signaling molecules, including TLRs and inflammasome family members, during some infectious and chronic inflammatory disorders. Activation of the complement system generates anaphylatoxins, such as C3a and C5a, which modulate inflammation. However, the biological effects of interactions between the anaphylatoxins with their receptors may vary across species. In this study, we demonstrate that human complement and rat complement differ in the way they modulate the inflammatory response to the human pathogen, Neisseria gonorrhoeae, as well as purified pathogen-associated ligands, such as LPS. While rat serum down-regulates MyD88-dependent pro-inflammatory cytokine responses in macrophages, human serum has no effect, or in some cases an enhancing effect. Further, the inhibitory effect of rat serum on otherwise pro-inflammatory stimuli is mediated by complement, specifically C3a-C3a receptor interactions, via an undefined signaling mechanism that down-regulates the transcription factor, NF-κB and NLRP3 inflammasome-mediated caspase-1 activation. This study highlights important functional differences between rodent and human complement that could explain some of the differences in immune responses between these two species. Understanding the crosstalk between complement and other arms of the innate immune system will facilitate the development of better anti-inflammatory therapeutics.

Automatic identification of parathyroid in optical coherence tomography images.

BACKGROUND AND OBJECTIVE: The identification and preservation of parathyroid is a major problem in thyroid surgery. In order to solve this problem, optical coherence tomography was involved as a real-time, non-invasive high-resolution imaging technique. This study demonstrated an effective and fast method to distinguish parathyroid tissue from thyroid, lymph node, and adipose tissue in their ex vivo optical coherence tomography (OCT) images automatically. METHODS: OCT images were obtained from parathyroid, thyroid, lymph node, and adipose tissue, respectively. A classification and an identification system based on texture features analysis and back propagation artificial neural network (BP-ANN) were established to classify the four types of tissue and identify each of the four types automatically. RESULTS: A total of 248 OCT images were taken from 16 patients undergoing thyroidectomy. The accuracy of classification for parathyroid, thyroid, lymph node, and adipose were 99.21, 98.43, 97.65, and 98.43%, respectively. CONCLUSION: The proposed automatic identification method is capable of distinguishing among parathyroid, thyroid, lymph, and adipose automatically and effectively. Compared with the identification results of human, it has a better accuracy and reliability. For identifying parathyroid from the other entities, it has a satisfying performance. Lasers Surg. Med. 49:305-311, 2017. © 2017 Wiley Periodicals, Inc.