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Residual intravenous foreign bodies following hand trauma are relatively rare; only a few previous reports of this situation are available. It has been reported that foreign bodies often migrate to the heart and atrium dextrum. Herein, we report a recent case of needle breakage in the dorsal vein of the hand that was removed with lignification using an intraoperative C-arm fluoroscopy machine and tape tourniquet to avoid proximal movement during removal. The mandate should be to remove within the capacity allowed so that rare cases and terrible complications can be avoided. The case was seen at The Yanji City, Jilin Province, China at the Yanbian University Hospital emergency at February 20, 2023.
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Cuerpos Extraños , Agujas , Humanos , Agujas/efectos adversos , Cuerpos Extraños/cirugía , Cuerpos Extraños/diagnóstico por imagen , Masculino , Traumatismos de la Mano/cirugía , Fluoroscopía , Venas/lesiones , Venas/diagnóstico por imagen , Venas/cirugía , Administración IntravenosaRESUMEN
PURPOSE: Bioactive glass-ceramic (BGC) coatings have been extensively studied and clinically used as bone substitute materials because of their osteogenesis, osteoinduction, and osteoconduction characteristics. Although the Hedgehog (Hh) signaling pathway plays an important role in skeletal development, the relationship between BGC coatings and the Hh signaling pathway is unknown. METHODS: In this study, a BGC coating is fabricated by furnace sintering, and its surface is investigated by a scanning electron microscope (SEM) and a transmission electron microscope (TEM). Furthermore, the expression of Ki67 is evaluated using immunofluorescence, and osteogenesis-related factors and Hh signaling pathway molecules on the BGC coating are examined by real-time reverse transcription polymerase chain reaction (real-time RT-PCR) and Western blotting in bone marrow mesenchymal stem cells (BMSCs). RESULTS: The SEM and the TEM show that the BGC coating surface is smooth, without cracks, and composed of particles with mesoporous structure. The expression of Ki67 positive BMSCs of the BGC group is higher than that of the control group. Real-time RT-PCR and Western blotting assay reveal that the expression levels of osteoblast-related genes (BMP2, Osteocalcin, ALP, Runx2) and Hh signaling pathway molecules (Gli1, Smo) are much higher for the BGC coating group than those for the control group. Furthermore, after treating with Smo inhibitor cyclopamine, the Smo and Gli1 expressions in BMSCs are dramatically down-regulation for the BGC coating compared to those for the control group. Both mRNA and protein expression levels of osteogenesis-related factors was downregulated after treating Smo inhibitor cyclopamine in BMSCs with the BGC coating. CONCLUSIONS: The BGC coatings promote osteogenesis probably via the Hh signaling pathway, which provides a theory reference for future clinical application of bone formation.
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Cerámica , Materiales Biocompatibles Revestidos , Proteínas Hedgehog/fisiología , Células Madre Mesenquimatosas/fisiología , Osteogénesis/fisiología , Transducción de Señal/fisiología , Técnicas de Cultivo de Célula , HumanosRESUMEN
Tenascin-C (TNC), as a member of the extracellular matrix (ECM), plays an important role in cancer cell proliferation and migration and tumor invasion in various types of cancer. Here, we attempted to investigate the role of TNC as a prognostic factor in prostate cancer. We studied TNC expression via immunohistochemistry in 145 prostate cancer tissue samples. The clinicopathological relevance of TNC expression was examined, as well as other cancer-associated fibroblasts (CAFs)-related factors. Our results showed that the high levels of TNC expression in prostate cancer stroma was significantly associated with lymph node metastasis (P = 0.024) and clinical stage (P = 0.032). Furthermore, TNC was positively correlated with increased micro-vessel density (MVD) (P = 0.017) and tumor associated macrophage (TAM) population (P = 0.025). In both univariate and multivariate Cox regression analyses, TNC (P < 0.001) was an independent poor prognostic factor for overall survival in prostate cancer patients. Moreover, over-expression of TNC (P < 0.001), SMA (P = 0.042) and vimentin (P = 0.010) were significantly correlated with the lower overall survival. In addition, TNC expression in prostate cancer stroma was significantly associated with FSP1 (P = 0.011), SMA (P = 0.021), and vimentin (P = 0.002). In conclusion, our study revealed that high level of TNC as a potential biomarker of CAFs was significantly correlated with the poor prognosis for prostate cancer patients.
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Actinas/genética , Biomarcadores de Tumor/genética , Carcinoma/diagnóstico , Neoplasias de la Próstata/diagnóstico , Tenascina/genética , Vimentina/genética , Actinas/metabolismo , Anciano , Biomarcadores de Tumor/metabolismo , Proteínas de Unión al Calcio/genética , Proteínas de Unión al Calcio/metabolismo , Fibroblastos Asociados al Cáncer/metabolismo , Fibroblastos Asociados al Cáncer/patología , Carcinoma/genética , Carcinoma/mortalidad , Carcinoma/patología , Regulación Neoplásica de la Expresión Génica , Humanos , Metástasis Linfática , Masculino , Persona de Mediana Edad , Clasificación del Tumor , Estadificación de Neoplasias , Pronóstico , Neoplasias de la Próstata/genética , Neoplasias de la Próstata/mortalidad , Neoplasias de la Próstata/patología , Proteína de Unión al Calcio S100A4 , Transducción de Señal , Análisis de Supervivencia , Tenascina/metabolismo , Vimentina/metabolismoRESUMEN
Tenascin C (TNC) is a key of extracellular matrix glycoprotein and highly express in numerous human malignancies. Herein, we attempted to clarify the clinicopathological significance of TNC as a prognostic determinant of breast ductal carcinoma. Then, we investigated TNC immunohistochemical expression in 150 breast ductal carcinomas and 27 normal breast tissue samples. Clinical relevance of TNC expression and the association TNC expression with other factors related to cancer-associated fibroblasts were also examined. In results, TNC expression was significantly higher in breast ductal carcinoma (56.0%) than normal breast tissues (25.9%). The upregulation TNC in cancer stromal were associated with pT stage (P=0.003), lymph node metastasis (P=0.002) and tumor node metastasis stage (P=0.001), also was correlated with an increase in tumor-associated macrophage population (P<0.001). The microvessel density (MVD) was significantly higher in TNC positive group than in negative group (P<0.001). In both univariate and multivariate Cox regression analyses, TNC was an independent poor prognostic factor for overall survival (OS) in breast ductal carcinoma patients. Importantly, over-expression TNC (P<0.001), FSP1 (P<0.001), SMA (P=0.002) and Vimentin (P=0.049) were significantly correlation with the lower OS (P<0.005). In addition, TNC expression in breast ductal carcinoma stromal was positively correlated with FSP1 (P<0.001), SMA (P=0.001) and Vimentin (P<0.001). In conclusion, the high expression of TNC could be a useful cancer-associated fibroblasts marker for the prediction of prognosis of breast ductal carcinoma patients.
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Neoplasias de la Mama/diagnóstico , Fibroblastos Asociados al Cáncer/metabolismo , Carcinoma Ductal de Mama/diagnóstico , Metástasis Linfática/diagnóstico , Tenascina/análisis , Biomarcadores de Tumor/análisis , Mama/citología , Mama/metabolismo , Neoplasias de la Mama/patología , Fibroblastos Asociados al Cáncer/citología , Carcinoma Ductal de Mama/patología , Estudios de Casos y Controles , Femenino , Humanos , Metástasis Linfática/patología , Persona de Mediana Edad , Pronóstico , Modelos de Riesgos Proporcionales , Manejo de EspecímenesRESUMEN
This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.
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With the rapid growth of RNA sequences generated in the postgenomic age, it is highly desired to develop a flexible method that can generate various kinds of vectors to represent these sequences by focusing on their different features. This is because nearly all the existing machine-learning methods, such as SVM (support vector machine) and KNN (k-nearest neighbor), can only handle vectors but not sequences. To meet the increasing demands and speed up the genome analyses, we have developed a new web server, called "representations of RNA sequences" (repRNA). Compared with the existing methods, repRNA is much more comprehensive, flexible and powerful, as reflected by the following facts: (1) it can generate 11 different modes of feature vectors for users to choose according to their investigation purposes; (2) it allows users to select the features from 22 built-in physicochemical properties and even those defined by users' own; (3) the resultant feature vectors and the secondary structures of the corresponding RNA sequences can be visualized. The repRNA web server is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repRNA/ .
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ARN/genética , Análisis de Secuencia de ARN/métodos , Secuencia de Bases , Biología Computacional/métodos , Genoma/genética , Internet , Programas Informáticos , Máquina de Vectores de SoporteRESUMEN
MOTIVATION: Enhancers are of short regulatory DNA elements. They can be bound with proteins (activators) to activate transcription of a gene, and hence play a critical role in promoting gene transcription in eukaryotes. With the avalanche of DNA sequences generated in the post-genomic age, it is a challenging task to develop computational methods for timely identifying enhancers from extremely complicated DNA sequences. Although some efforts have been made in this regard, they were limited at only identifying whether a query DNA element being of an enhancer or not. According to the distinct levels of biological activities and regulatory effects on target genes, however, enhancers should be further classified into strong and weak ones in strength. RESULTS: In view of this, a two-layer predictor called ' IENHANCER-2L: ' was proposed by formulating DNA elements with the 'pseudo k-tuple nucleotide composition', into which the six DNA local parameters were incorporated. To the best of our knowledge, it is the first computational predictor ever established for identifying not only enhancers, but also their strength. Rigorous cross-validation tests have indicated that IENHANCER-2L: holds very high potential to become a useful tool for genome analysis. AVAILABILITY AND IMPLEMENTATION: For the convenience of most experimental scientists, a web server for the two-layer predictor was established at http://bioinformatics.hitsz.edu.cn/iEnhancer-2L/, by which users can easily get their desired results without the need to go through the mathematical details. CONTACT: bliu@gordonlifescience.org, bliu@insun.hit.edu.cn, xlan@stanford.edu, kcchou@gordonlifescience.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Elementos de Facilitación Genéticos , Análisis de Secuencia de ADN/métodos , Programas Informáticos , ADN/química , Genómica/métodos , Nucleótidos/análisisRESUMEN
A microRNA (miRNA) is a small non-coding RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene expression. The human genome may encode over 1000 miRNAs. Albeit poorly characterized, miRNAs are widely deemed as important regulators of biological processes. Aberrant expression of miRNAs has been observed in many cancers and other disease states, indicating that they are deeply implicated with these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Particularly, with the avalanche of RNA sequences generated in the post-genomic age, it is highly desired to develop computational sequence-based methods for effectively identifying the human pre-miRNAs. Here, we propose a predictor called "iMiRNA-PseDPC", in which the RNA sequences are formulated by a novel feature vector called "pseudo distance-pair composition" (PseDPC) with 10 types of structure statuses. Rigorous cross-validations on a much larger and more stringent newly constructed benchmark data-set showed that our approach has remarkably outperformed the existing ones in either prediction accuracy or efficiency, indicating the new predictor is quite promising or at least may become a complementary tool to the existing predictors in this area. For the convenience of most experimental scientists, a user-friendly web server for the new predictor has been established at http://bioinformatics.hitsz.edu.cn/iMiRNA-PseDPC/, by which users can easily get their desired results without the need to go through the mathematical details. It is anticipated that the new predictor may become a useful high throughput tool for genome analysis particularly in dealing with large-scale data.
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MicroARNs/química , Conformación de Ácido Nucleico , Análisis de Secuencia de ARN/métodos , Programas Informáticos , Algoritmos , Biología Computacional , Genoma Humano , Genómica , Humanos , Internet , MicroARNs/genéticaRESUMEN
The microRNA (miRNA), a small non-coding RNA molecule, plays an important role in transcriptional and post-transcriptional regulation of gene expression. Its abnormal expression, however, has been observed in many cancers and other disease states, implying that the miRNA molecules are also deeply involved in these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Most existing methods in this regard were based on the strategy in which RNA samples were formulated by a vector formed by their Kmer components. But the length of Kmers must be very short; otherwise, the vector's dimension would be extremely large, leading to the "high-dimension disaster" or overfitting problem. Inspired by the concept of "degenerate energy levels" in quantum mechanics, we introduced the "degenerate Kmer" (deKmer) to represent RNA samples. By doing so, not only we can accommodate long-range coupling effects but also we can avoid the high-dimension problem. Rigorous jackknife tests and cross-species experiments indicated that our approach is very promising. It has not escaped our notice that the deKmer approach can also be applied to many other areas of computational biology. A user-friendly web-server for the new predictor has been established at http://bioinformatics.hitsz.edu.cn/miRNA-deKmer/, by which users can easily get their desired results.
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MicroARNs/genética , Precursores del ARN/genética , Análisis de Secuencia de ARN/métodos , Animales , Biología Computacional/métodos , Bases de Datos Genéticas , Vectores Genéticos/genética , Humanos , Internet , Especificidad de la Especie , Máquina de Vectores de SoporteRESUMEN
With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems in computational biology is how to effectively formulate the sequence of a biological sample (such as DNA, RNA or protein) with a discrete model or a vector that can effectively reflect its sequence pattern information or capture its key features concerned. Although several web servers and stand-alone tools were developed to address this problem, all these tools, however, can only handle one type of samples. Furthermore, the number of their built-in properties is limited, and hence it is often difficult for users to formulate the biological sequences according to their desired features or properties. In this article, with a much larger number of built-in properties, we are to propose a much more flexible web server called Pse-in-One (http://bioinformatics.hitsz.edu.cn/Pse-in-One/), which can, through its 28 different modes, generate nearly all the possible feature vectors for DNA, RNA and protein sequences. Particularly, it can also generate those feature vectors with the properties defined by users themselves. These feature vectors can be easily combined with machine-learning algorithms to develop computational predictors and analysis methods for various tasks in bioinformatics and system biology. It is anticipated that the Pse-in-One web server will become a very useful tool in computational proteomics, genomics, as well as biological sequence analysis. Moreover, to maximize users' convenience, its stand-alone version can also be downloaded from http://bioinformatics.hitsz.edu.cn/Pse-in-One/download/, and directly run on Windows, Linux, Unix and Mac OS.
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Análisis de Secuencia de ADN/métodos , Análisis de Secuencia de Proteína/métodos , Análisis de Secuencia de ARN/métodos , Programas Informáticos , Internet , Aprendizaje AutomáticoRESUMEN
Containing about 22 nucleotides, a micro RNA (abbreviated miRNA) is a small non-coding RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene expression. The human genome may encode over 1000 miRNAs. Albeit poorly characterized, miRNAs are widely deemed as important regulators of biological processes. Aberrant expression of miRNAs has been observed in many cancers and other disease states, indicating they are deeply implicated with these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Particularly, with the avalanche of RNA sequences generated in the postgenomic age, it is highly desired to develop computational sequence-based methods in this regard. Here two new predictors, called "iMcRNA-PseSSC" and "iMcRNA-ExPseSSC", were proposed for identifying the human pre-microRNAs by incorporating the global or long-range structure-order information using a way quite similar to the pseudo amino acid composition approach. Rigorous cross-validations on a much larger and more stringent newly constructed benchmark dataset showed that the two new predictors (accessible at http://bioinformatics.hitsz.edu.cn/iMcRNA/) outperformed or were highly comparable with the best existing predictors in this area.
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MicroARNs/genética , Precursores del ARN/genética , Aminoácidos/genética , Secuencia de Bases , Biología Computacional/métodos , Genoma Humano/genética , Humanos , Conformación de Ácido Nucleico , Nucleótidos/genética , ARN Pequeño no Traducido/genéticaRESUMEN
MicroRNA precursor identification is an important task in bioinformatics. Support Vector Machine (SVM) is one of the most effective machine learning methods used in this field. The performance of SVM-based methods depends on the vector representations of RNAs. However, the discriminative power of the existing feature vectors is limited, and many methods lack an interpretable model for analysis of characteristic sequence features. Prior studies have demonstrated that sequence or structure order effects were relevant for discrimination, but little work has explored how to use this kind of information for human pre-microRNA identification. In this study, in order to incorporate the structure-order information into the prediction, a method called "miRNA-dis" was proposed, in which the feature vector was constructed by the occurrence frequency of the "distance structure status pair" or just the "distance-pair". Rigorous cross-validations on a much larger and more stringent newly constructed benchmark dataset showed that the miRNA-dis outperformed some state-of-the-art predictors in this area. Remarkably, miRNA-dis trained with human data can correctly predict 87.02% of the 4022 pre-miRNAs from 11 different species ranging from animals, plants and viruses. miRNA-dis would be a useful high throughput tool for large-scale analysis of microRNA precursors. In addition, the learnt model can be easily analyzed in terms of discriminative features, and some interesting patterns were discovered, which could reflect the characteristics of microRNAs. A user-friendly web-server of miRNA-dis was constructed, which is freely accessible to the public at the web-site on http://bioinformatics.hitsz.edu.cn/miRNA-dis/.
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Biología Computacional/métodos , MicroARNs/química , MicroARNs/genética , Interfaz Usuario-Computador , Animales , Bases de Datos Genéticas , Humanos , Internet , ARN de Planta , ARN ViralRESUMEN
UNLABELLED: In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facilitate the studies of DNAs and nucleotides, we developed a Python package called representations of DNAs (repDNA) for generating the widely used features reflecting the physicochemical properties and sequence-order effects of DNAs and nucleotides. There are three feature groups composed of 15 features. The first group calculates three nucleic acid composition features describing the local sequence information by means of kmers; the second group calculates six autocorrelation features describing the level of correlation between two oligonucleotides along a DNA sequence in terms of their specific physicochemical properties; the third group calculates six pseudo nucleotide composition features, which can be used to represent a DNA sequence with a discrete model or vector yet still keep considerable sequence-order information via the physicochemical properties of its constituent oligonucleotides. In addition, these features can be easily calculated based on both the built-in and user-defined properties via using repDNA. AVAILABILITY AND IMPLEMENTATION: The repDNA Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repDNA/. CONTACT: bliu@insun.hit.edu.cn or kcchou@gordonlifescience.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Biología Computacional/métodos , ADN/química , ADN/genética , Oligonucleótidos/química , Análisis de Secuencia de ADN/métodos , Programas Informáticos , Máquina de Vectores de Soporte , Humanos , Oligonucleótidos/genéticaRESUMEN
When female mice are mated, they form a memory to the pheromonal signal of their male partner. Several lines of evidence indicate that the neural changes underlying this memory occur in the accessory olfactory bulb (AOB) at the first stage of the vomeronasal system. The formation of this memory depends on the mating-induced release of noradrenaline in the AOB. In addition to noradrenaline, the neuropeptide oxytocin (OT) is also released within the central nervous system during mating. Because OT has been implicated in social memory and its receptors are expressed in the AOB, we hypothesized that OT might promote the strength of synaptic transmission from mitral to granule cells in the AOB. To test this hypothesis, we analyzed the lateral olfactory tract-evoked field potential that represents the granule cell response to mitral cell activation and its plasticity in parasagittal slices of the AOB. Of the 10-, 20-, 50-, and 100-Hz stimulations tested, the 100-Hz stimulation was optimal for inducing long-term potentiation (LTP). OT paired with 100-Hz stimulation that only produced short-term potentiation enhanced LTP induction in a dose-dependent manner. OT-paired LTP was blocked by both the selective OT antagonist desGly-NH(2),d(CH(2))(5)[Tyr(Me)(2),Thr(4)]-ornithine vasotocin and the N-methyl-d-aspartate (NMDA) receptor antagonist dl-2-amino-5-phosphonovaleric acid. These results indicate that OT can function as a gate to modulate the establishment of NMDA receptor-dependent LTP at the mitral-to-granule cell synapse in the AOB.