An intelligent telemedicine system for detection of diabetic foot complications

Early identification and timely treatment of diabetic foot complications are essential in preventing their devastating consequences such as lower-extremity amputation and mortality. Frequent and automatic risk assessment by an intelligent telemedicine system may be feasible and cost-effective. As the first step to approach such a telemedicine system, an experimental setup that combined three promising imaging modalities, namely spectral imaging, infrared thermal imaging, and photometric stereo imaging, was developed and investigated. \ud \ud The spectral imaging system in the experimental setup contains nine cameras in a matrix configuration, fitted with the preselected optical filters. Using the spectral images acquired, front-end pixel classifiers were developed to detect the diabetic foot complications automatically. Taking the image annotations based on live assessment as ground truth, the validation results indicate that these front-end classifiers can identify the diabetic foot complications with acceptable performance. However, future studies are needed on enhancing the performance of current pixel classifiers and designing the back-end classifiers.\ud \ud With the infrared thermal imaging, images of temperature distributions can be acquired from patients’ feet. The temperature differences between the corresponding areas of the contralateral feet are clinically significant parameters for identifying the diabetic foot complications. To detect this temperature differences automatically, an asymmetric analysis were proposed and investigated. Results show that the corresponding points on the two feet can be identified irrespective of the shapes, sizes or poses of the feet. \ud \ud With the photometric stereo imaging, a feasibility study were conducted to detect diabetic foot complications with the 3D surface reconstruction. The results indicate that this imaging technology may be promising but subjected to some limitations currently, such as the movement in patients' foot during image acquisition. To determine the potential value of this modality in the future telemedicine system, further improvement is required.\ud \ud The outcomes of the studies presented in this thesis showed the feasibility of developing a telemedicine system to detect diabetic foot complications with the three imaging modalities. The studies acted as the precursors for developing an intelligent telemedicine system, which proposed potential detection methodologies and provided the directions for the future study

The C-terminal motif of SiAGO1b is required for the regulation of growth, development and stress responses in foxtail millet (\u3ci\u3eSetaria italica\u3c/i\u3e (L.) P. Beauv)

Foxtail millet (Setaria italica (L.) P. Beauv), which belongs to the Panicoideae tribe of the Poaceae, is an important grain crop widely grown in Northern China and India. It is currently developing into a novel model species for functional genomics of the Panicoideae as a result of its fully available reference genome sequence, small diploid genome (2n=18, ~510 Mb), short life cycle, small stature and prolific seed production. Argonaute 1 (AGO1), belonging to the argonaute (AGO) protein family, recruits small RNAs and regulates plant growth and development. Here, we characterized an AGO1 mutant (siago1b) in foxtail millet, which was induced by ethyl methanesulfonate treatment. The mutant exhibited pleiotropic developmental defects, including dwarfing stem, narrow and rolled leaves, smaller panicles and lower rates of seed setting. Map-based cloning analysis demonstrated that these phenotypic variations were attributed to a C–A transversion, and a 7-bp deletion in the C-terminus of the SiAGO1b gene in siago1b. Yeast two-hybrid assays and BiFC experiments revealed that the mutated region was an essential functional motif for the interaction between SiAGO1b and SiHYL1. Furthermore, 1598 differentially expressed genes were detected via RNAseq- based comparison of SiAGO1b and wild-type plants, which revealed that SiAGO1b mutation influenced multiple biological processes, including energy metabolism, cell growth, programmed death and abiotic stress responses in foxtail millet. This study may provide a better understanding of the mechanisms by which SiAGO1b regulates the growth and development of crops

The C-terminal motif of SiAGO1b is required for the regulation of growth, development and stress responses in foxtail millet (\u3ci\u3eSetaria italica\u3c/i\u3e (L.) P. Beauv)

Foxtail millet (Setaria italica (L.) P. Beauv), which belongs to the Panicoideae tribe of the Poaceae, is an important grain crop widely grown in Northern China and India. It is currently developing into a novel model species for functional genomics of the Panicoideae as a result of its fully available reference genome sequence, small diploid genome (2n=18, ~510 Mb), short life cycle, small stature and prolific seed production. Argonaute 1 (AGO1), belonging to the argonaute (AGO) protein family, recruits small RNAs and regulates plant growth and development. Here, we characterized an AGO1 mutant (siago1b) in foxtail millet, which was induced by ethyl methanesulfonate treatment. The mutant exhibited pleiotropic developmental defects, including dwarfing stem, narrow and rolled leaves, smaller panicles and lower rates of seed setting. Map-based cloning analysis demonstrated that these phenotypic variations were attributed to a C–A transversion, and a 7-bp deletion in the C-terminus of the SiAGO1b gene in siago1b. Yeast two-hybrid assays and BiFC experiments revealed that the mutated region was an essential functional motif for the interaction between SiAGO1b and SiHYL1. Furthermore, 1598 differentially expressed genes were detected via RNAseq- based comparison of SiAGO1b and wild-type plants, which revealed that SiAGO1b mutation influenced multiple biological processes, including energy metabolism, cell growth, programmed death and abiotic stress responses in foxtail millet. This study may provide a better understanding of the mechanisms by which SiAGO1b regulates the growth and development of crops

A Thymidine Kinase recombinant protein-based ELISA for detecting antibodies to Duck Plague Virus

<p>Abstract</p> <p>Background</p> <p>Duck plague virus (DPV) is the causative agent of Duck Plague (DP) that causes significant morbidity and mortality throughout duck-producing areas of the world. The diagnosis of DP currently relies on the use of live or inactivated whole DPV virion as antigens in ELISA, but it is too laborious and expensive for routine application, and it is still difficult to get purified DPV virion with current technology.</p> <p>Results</p> <p>In this study, we describe the expression and purification of a recombinant Thymidine Kinase (TK) protein which makes antigen in an in-house developed, optimized and standardized ELISA. The specificity of the optimized TK-ELISA was evaluated by antisera against Duck Plague Virus (DPV), Duck Hepatitis B Virus (DHBV), Duck Hepatitis Virus (DHV), <it>Riemerella Anatipestifer</it>(<it>R. A</it>), <it>Escherichia coli </it>(<it>E. coli</it>) and <it>Salmonella anatum </it>(<it>S. anatum</it>). Only antisera against DPV yielded a specific and strong signal. In order to determine the sensitivity of the TK-ELISA, a panel of diluted sera was tested, and the minimum detection limit of 1:2560 (OD450 nm = 0.401) was obtained according to the endpoint cut-off (0.2438). The repeatability and reproducibility under the experimental conditions demonstrates a low variability (P > 0.05). The suspected sera samples (n = 30) were determined by TK-ELISA and the positive rate is 90% (27/30), and the TK-ELISA showed 83.33% (22+3/30) coincidence rate with the Serum Neutralization Test (SNT) and 90% (24+3/30) coincidence rate with the whole DPV virion based-ELISA (DPV-ELISA). When defining the dynamics of antibody response to attenuated live DPV vaccine, the maximum antibodies is reached after 4 weeks.</p> <p>Conclusions</p> <p>The results suggest that the TK-ELISA provides high specificity, sensitivity, repeatability and reproducibility for detection of anti-DPV antibodies in duck sera, and has the potential to be much simpler than DPV-ELISA and SNT for the sera epidemiological investigation.</p

USP21 deubiquitylates Nanog to regulate protein stability and stem cell pluripotency

The homeobox transcription factor Nanog has a vital role in maintaining pluripotency and self-renewal of embryonic stem cells (ESCs). Stabilization of Nanog proteins is essential for ESCs. The ubiquitin–proteasome pathway mediated by E3 ubiquitin ligases and deubiquitylases is one of the key ways to regulate protein levels and functions. Although ubiquitylation of Nanog catalyzed by the ligase FBXW8 has been demonstrated, the deubiquitylase that maintains the protein levels of Nanog in ESCs yet to be defined. In this study, we identify the ubiquitin-specific peptidase 21 (USP21) as a deubiquitylase for Nanog, but not for Oct4 or Sox2. USP21 interacts with Nanog protein in ESCs in vivo and in vitro. The C-terminal USP domain of USP21 and the C-domain of Nanog are responsible for this interaction. USP21 deubiquitylates the K48-type linkage of the ubiquitin chain of Nanog, stabilizing Nanog. USP21-mediated Nanog stabilization is enhanced in mouse ESCs and this stabilization is required to maintain the pluripotential state of the ESCs. Depletion of USP21 in mouse ESCs leads to Nanog degradation and ESC differentiation. Overall, our results demonstrate that USP21 maintains the stemness of mouse ESCs through deubiquitylating and stabilizing Nanog

Nondestructive detection of Pleurotus geesteranus strain degradation based on micro-hyperspectral imaging and machine learning

In the production of edible fungi, the use of degraded strains in cultivation incurs significant economic losses. Based on micro-hyperspectral imaging and machine learning, this study proposes an early, nondestructive method for detecting different degradation degrees of Pleurotus geesteranus strains. In this study, an undegraded strain and three different degradation-level strains were used. During the mycelium growth, 600 micro-hyperspectral images were obtained. Based on the average transmittance spectra of the region of interest (ROI) in the range of 400-1000 nm and images at feature bands, feature spectra and images were extracted using the successive projections algorithm (SPA) and the deep residual network (ResNet50), respectively. Different feature input combinations were utilized to establish support vector machine (SVM) classification models. Based on the results, the spectra-input-based model performed better than the image-input-based model, and feature extraction improved the classification results for both models. The feature-fusion-based SPA+ResNet50-SVM model was the best; the accuracy rate of the test set was up to 90.8%, which was better than the accuracy rates of SPA-SVM (83.3%) and ResNet50-SVM (80.8%). This study proposes a nondestructive method to detect the degradation of Pleurotus geesteranus strains, which could further inspire new methods for the phenotypic identification of edible fungi

High-throughput sequencing and characterization of potentially pathogenic fungi from the vaginal mycobiome of giant panda (Ailuropoda melanoleuca) in estrus and non-estrus

IntroductionThe giant panda (Ailuropoda melanoleuca) reproduction is of worldwide attention, and the vaginal microbiome is one of the most important factors affecting the reproductive rate of giant pandas. The aim of this study is to investigate the diversity of vaginal mycobiota structure, and potential pathogenic fungi in female giant pandas during estrus and non-estrus.MethodsThis study combined with high-throughput sequencing and laboratory testing to compare the diversity of the vaginal mycobiota in giant pandas during estrus and non-estrus, and to investigate the presence of potentially pathogenic fungi. Potentially pathogenic fungi were studied in mice to explore their pathogenicity.Results and discussionThe results revealed that during estrus, the vaginal secretions of giant pandas play a crucial role in fungal colonization. Moreover, the diversity of the vaginal mycobiota is reduced and specificity is enhanced. The abundance of Trichosporon and Cutaneotrichosporon in the vaginal mycobiota of giant pandas during estrus was significantly higher than that during non-estrus periods. Apiotrichum and Cutaneotrichosporon were considered the most important genera, and they primarily originate from the environment owing to marking behavior exhibited during the estrous period of giant pandas. Trichosporon is considered a resident mycobiota of the vagina and is an important pathogen that causes infection when immune system is suppressed. Potentially pathogenic fungi were further isolated and identified from the vaginal secretions of giant pandas during estrus, and seven strains of Apiotrichum (A. brassicae), one strain of Cutaneotrichosporon (C. moniliiforme), and nine strains of Trichosporon (two strains of T. asteroides, one strain of T. inkin, one strain of T. insectorum, and five strains of T. japonicum) were identified. Pathogenicity results showed that T. asteroides was the most pathogenic strain, as it is associated with extensive connective tissue replacement and inflammatory cell infiltration in both liver and kidney tissues. The results of this study improve our understanding of the diversity of the vaginal fungi present in giant pandas and will significantly contribute to improving the reproductive health of giant pandas in the future

ACAA2 Is a Novel Molecular Indicator for Cancers With Neuroendocrine Phenotype

BACKGROUND: Neuroendocrine phenotype is commonly associated with therapy resistance and poor prognoses in small-cell neuroendocrine cancers (SCNCs), such as neuroendocrine prostate cancer (NEPC) and small-cell lung cancer (SCLC). Expression levels of current neuroendocrine markers exhibit high case-by-case variability, so multiple markers are used in combination to identify SCNCs. Here, we report that ACAA2 is elevated in SCNCs and is a potential molecular indicator for SCNCs. METHODS: ACAA2 expressions in tumour xenografts, tissue microarrays (TMAs), and patient tissues from prostate and lung cancers were analysed via immunohistochemistry. ACAA2 mRNA levels in lung and prostate cancer (PC) patients were assessed in published datasets. RESULTS: ACAA2 protein and mRNA levels were elevated in SCNCs relative to non-SCNCs. Medium/high ACAA2 intensity was observed in 78% of NEPC PDXs samples (N = 27) relative to 33% of adeno-CRPC (N = 86), 2% of localised PC (N = 50), and 0% of benign prostate specimens (N = 101). ACAA2 was also elevated in lung cancer patient tissues with neuroendocrine phenotype. 83% of lung carcinoid tissues (N = 12) and 90% of SCLC tissues (N = 10) exhibited medium/high intensity relative to 40% of lung adenocarcinoma (N = 15). CONCLUSION: ACAA2 expression is elevated in aggressive SCNCs such as NEPC and SCLC, suggesting it is a potential molecular indicator for SCNCs