OBJECTIVES: To find the optimal acceleration factor (AF) of the compressed SENSE (CS) technique for uterine isotropic high-resolution 3D T2-weighted imaging (3D-ISO-T2WI). METHODS: A total of 91 female volunteers from the XXX, XXX and XXX were recruited. A total of 44 volunteers received uterus sagittal 3D-ISO-T2WI scans on 3.0 T MRI device with different CS AFs (including SENSE3, CS3, CS4, CS5, CS6, and CS7), 51 received 3D-ISO-T2WI scans with different degrees of fat suppression (none, light, moderate, and severe), while 4 volunteers received both series of scans. Image quality was subjectively evaluated with a three-point scoring system. Junction zone signal-to-noise ratio (SNR) and contrast to noise ratio (CNR) and myometrial SNR were also calculated. Intraclass correlation coefficients (ICC) were used to analyze the consistency of the measurement results by two observers. ANOVA test or Friedman rank sum test was used to compare the differences in subjective scores, SNR and CNR under different AFs/different degrees of fat suppression. RESULTS: Images by AFs of CS3, CS4, and CS5 had the highest SNR and CNR. Among them, CS5 had the shortest scan time. CS5 also had one of the highest subjective scores. There was no significant difference in SNR and CNR among images acquired with different degrees of fat suppression. Also, images with moderate fat suppression had the highest subjective scores. CONCLUSION: The CS5 combined with moderate fat suppression is recommended for routine female pelvic 3D-ISO-T2WI scan. ADVANCES IN KNOWLEDGE: The CS5 has the highest images quality and has the shortest scan time, which is the best AF. Moderate fat suppression has the highest subjective scores. The CS5 and moderate fat suppression are the best combination for female pelvic 3D-ISO-T2WI scan.
As the world grapples with the challenges of energy transition and industrial decarbonization, the development of carbon capture technologies presents a promising solution. The Scalable Modeling, Artificial Intelligence (AI), and Rapid Theoretical calculations, referred as SMART here, is an interdisciplinary approach that combines high-throughput calculation and data-driven modeling with expertise from chemical, materials, environmental, computer and data science and engineering, leading to the development of advanced capabilities in simulating and optimizing carbon capture processes. This perspective discusses the state-of-the-art material discovery research enabled by high-throughput calculation and data-driven modeling. Further, we propose a framework for material discovery, and illustrate the synergies among deep learning models, pretrained models, and comprehensive data sets, emerging as a robust framework for data-driven design and development in carbon capture. In essence, the adoption of the SMART approach promises a revolutionary impact on efforts in energy transition and industrial decarbonization.
Artificial Intelligence , Machine Learning , Technology , Carbon , Industry
Zero-carbon energy and negative emission technologies are crucial for achieving a carbon neutral future, and nanomaterials have played critical roles in advancing such technologies. More recently, due to the explosive growth in data, the adoption and exploitation of artificial intelligence (AI) as part of the materials research framework have had a tremendous impact on the development of nanomaterials. AI has enabled revolutionary next-generation paradigms to significantly accelerate all stages of material discovery and facilitate the exploration of the enormous design space. In this review, we summarize recent advancements of AI applications in nanomaterials discovery, with a special emphasis on the selected applications of AI and nanotechnology for the net-zero emission future including the development of solar cells, hydrogen energy, battery materials for renewable energy, and CO2 capture and conversion materials for carbon capture, utilization and storage (CCUS) technologies. In addition, we discuss the limitations and challenges of current AI applications in this area by identifying the gaps that exist in current development. Finally, we present the prospect for future research directions in order to facilitate the large-scale applications of artificial intelligence for advancements in nanomaterials.
An ideal artificial bone implant should have similar mechanical properties and biocompatibility to natural bone, as well as an internal structure that facilitates stomatal penetration. In this work, 3D printing was used to fabricate and investigate artificial bone composites based on HA-ZrO2-PVA. The composites were proportionally configured using zirconia (ZrO2), hydroxyapatite (HA) and polyvinyl alcohol (PVA), where the ZrO2 played a toughening role and PVA solution served as a binder. In order to obtain the optimal 3D printing process parameters for the composites, a theoretical model of the extrusion process of the composites was first established, followed by the optimization of various parameters including the spray head internal diameter, extrusion pressure, extrusion speed, and extrusion line width. The results showed that, at the optimum parameters of a spray head diameter of 0.2 mm, extrusion pressure values ranging from 1-3 bar, a line spacing of 0.8-1.5 mm, and a spray head displacement range of 8-10 mm/s, a better structure of biological bone scaffolds could be obtained. The mechanical tests performed on the scaffolds showed that the elastic modulus of the artificial bone scaffolds reached about 174 MPa, which fulfilled the biomechanical requirements of human bone. According to scanning electron microscope observation of the scaffold sample, the porosity of the scaffold sample was close to 65%, which can well promote the growth of chondrocytes and angiogenesis. In addition, c5.18 chondrocytes were used to verify the biocompatibility of the composite materials, and the cell proliferation was increased by 100% when compared with that of the control group. The results showed that the composite has good biocompatibility.
Aerobic glycolysis is a metabolic mode of tumor cells different from normal cells that plays an important role in tumor proliferation and distant metastasis. Radiotherapy has now become a routine and effective treatment for many malignancies, however, resistance to radiotherapy remains a major challenge in the treatment of malignant tumors. Recent studies have found that the abnormal activity of the aerobic glycolysis process in tumor cells is most likely involved in regulating chemoresistance and radiation therapy resistance in malignant tumors. However, research on the functions and mechanisms of aerobic glycolysis in the molecular mechanisms of resistance to radiotherapy in malignant tumors is still in its early stages. This review collects recent studies on the effects of aerobic glycolysis and radiation therapy resistance in malignant tumors, to further understand the progress in this area. This research may more effectively guide the clinical development of more powerful treatment plans for radiation therapy resistant subtypes of cancer patients, and take an important step to improve the disease control rate of radiation therapy resistant subtypes of cancer patients.
Neoplasms , Radiation Tolerance , Humans , Neoplasms/radiotherapy , Glycolysis
PURPOSE: The purpose of this study was to compare the diagnostic performance and the interpretation time of breast ultrasound examination between reading without and with the artificial intelligence (AI) system as a concurrent reading aid. MATERIAL AND METHODS: A fully crossed multi-reader and multi-case (MRMC) reader study was conducted. Sixteen participating physicians were recruited and retrospectively interpreted 172 breast ultrasound cases in two reading scenarios, once without and once with the AI system (BU-CAD™, TaiHao Medical Inc.) assistance for concurrent reading. Interpretations of any given case set with and without the AI system were separated by at least 5 weeks. These reading results were compared to the reference standard and the area under the LROC curve (AUCLROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for performance evaluations. The interpretation time was also compared between the unaided and aided scenarios. RESULTS: With the help of the AI system, the readers had higher diagnostic performance with an increase in the average AUCLROC from 0.7582 to 0.8294 with statistically significant. The sensitivity, specificity, PPV, and NPV were also improved from 95.77%, 24.07%, 44.18%, and 93.50%-98.17%, 30.67%, 46.91%, and 96.10%, respectively. Of these, the improvement in specificity reached statistical significance. The average interpretation time was significantly reduced by approximately 40% when the readers were assisted by the AI system. CONCLUSION: The concurrent-read AI system improves the diagnostic performance in detecting and diagnosing breast lesions on breast ultrasound images. In addition, the interpretation time is effectively reduced for the interpreting physicians.
Breast Neoplasms , Physicians , Artificial Intelligence , Breast Neoplasms/diagnostic imaging , Female , Humans , Mammography/methods , Reading , Retrospective Studies , Sensitivity and Specificity
Background: The milk fat globule membrane (MFGM), a tri-layer membrane structure surrounding the milk fat globule, has been shown to have immune-modulating properties. This study aimed to investigate the effects of MFGM supplementation in a rat model of short bowel syndrome (SBS) associated liver disease and its possible mechanisms. Materials and Methods: Twenty one male Sprague-Dawley rats were randomly divided into three groups: Sham, SBS (underwent massive small bowel resection), and SBS+MFGM (SBS rats supplemented with 1.5 g/kg/d MFGM). Liver pathology, myeloperoxidase (MPO) staining, serum levels of aspartate aminotransferase (AST)/alanine aminotransferase (ALT), endotoxin concentration, protein expression of autophagy and nucleotide binding oligomerization domain, leucine-rich repeat and pyrin domain-containing protein 3 (NLRP3) pathway in the liver tissue were measured. Results: Both SBS and SBS + MFGM groups had higher serum levels of ALT and liver endotoxin levels than the Sham group (P < 0.05), with no difference detected between each other. Compared with the SBS group, the SBS+MFGM group showed lower liver pathology scores of steatosis and inflammation, less MPO positive cells and reduced expressions of NLRP3, apoptosis-associated speck-like protein containing a CARD (ASC), Caspase-1, interleukin (IL)-1ß(P < 0.05) in the liver. Additionally, the expression of Beclin-1 and microtubule-associated protein1 light chain 3(LC3) B, the fluorescence intensity of NLRP3 and LC3B in the SBS + MFGM group were lower than the SBS group (P < 0.05). The LC3B expression was positively correlated with the NLRP3 level. Conclusion: Enteral supplementation of MFGM help to alleviate liver injury in SBS rats, which might be related to inhibition of aberrant activation of autophagy and NLRP3 inflammasome pathways.
Hydrogel microspheres are widely used in tissue engineering, such as 3D cell culture and injection therapy, and among which, heterogeneous microspheres are drawing much attention as a promising tool to carry multiple cell types in separated phases. However, it is still a big challenge to fabricate heterogeneous gel microspheres with excellent resolution and different material components in limited sizes. Here, we developed a multi-channel dynamic micromixer, which can use active mechanical mixing to achieve rapid mixing with multi-component materials and extrude the homogenized material. By changing the flow rate ratio of the solutions of the two components and by rapidly mixing in the micromixer, real-time concentration change of the mixed material at the outlet could be monitored in a process so-called "gradient printing". By studying the mixing efficiency of the micromixer, its size and process parameters were optimized. Using the novel dynamic gradient printing method, the composition of the hydrogel microspheres can be distributed in any proportion and alginate heterogeneous gel microspheres with adjustable cell concentration were fabricated. The effects of cell concentration on cell viability and proliferation ability under three-dimensional culture conditions were also studied. The results showed that cells have very low death rate and can exchange substances within the microspheres. Due to the micromixing ability of the micromixers, the demand for biological reagents and materials such as cells, proteins, cytokines and other materials could be greatly reduced, which helps reduce the experimental cost and improve the feasibility of the method in practical use. The heterogeneous gel microsphere can be greatly valuable for research in various fields such as analytical chemistry, microarray, drug screening, and tissue culture.
Introduction: Diorhabda tarsalis Weise is an important insect pest of the Chinese licorice Glycyrrhiza uralensis Fisch. Behavior of the beetle, including host location, oviposition site selection, self-defense, and aggregation, were regulated by plant volatiles or insect pheromones. Aim: In this study, Identification of ORs and function research on orco were carried out, these could lead to the development of understand for olfaction mechanism in D. tarsalis. Methods: ORs were identified by PacBio RS II platform to sequence the antennas of adult D. tarsalis, the function of orco was explored by dsRNA interference. Results: 29 odorant receptor candidate genes of D. tarsalis were obtained, which code for 130-479 amino acids. Phylogenetic trees of olfactory receptors were constructed with 243 ORs from eight Coleoptera species. DtarORco, DtarOR7 and DtarOR26 are specifically expressed in the antenna, and the expression levels were significantly higher than other DtarORs in antenna, there were no differential expression between male and female beetles. An odorant coreceptor gene (DtarORco) has characteristics of an odorant receptor family member, the encoded mature protein has a predicted molecular weight of 53.898 kDa, dsRNA L4440 expression vectors were constructed and successfully transformed into ribonuclease III-deficient Escherichia coli strain HT115 DE3. After interference treatment, the relative expression level of DtarORco in D. tarsalis antennae significantly decreased and electrophysiological responses to host localization odor signals significantly decreased. At the same time, beetles lost the ability to locate hosts. Discussion: The research on its mechanism of olfaction may lead to the development of new control measures that are environmentally friendly.
BACKGROUND: Previous researches have suggested that LINC00673 rs11655237 C>T polymorphism might be correlated to cancer susceptibility. However, its correlation with pediatric glioma is unknown. Therefore, this study aimed to determine whether LINC00673 rs11655237 C>T polymorphism is correlated with pediatric glioma. METHODS: In total, we included 399 subjects from South China. The Student's t-test was performed to evaluate age differences between glioma cases and controls. Differences in the categorical variables between the two groups were assessed using the χ2 test. A logistic regression was conducted to calculate the odds ratio (OR) and the 95% confidence interval (CI). RESULTS: We conducted this case-control study to investigate the association between LINC00673 polymorphism and pediatric glioma susceptibility. Our results revealed that LINC00673 rs11655237 C>T polymorphism was not correlated to pediatric glioma susceptibility in a Chinese population (CC/CT compared with TT: adjusted OR =2.49, 95% CI: 0.87-7.15, P=0.091). Furthermore, a stratified analysis also indicated LINC00673 rs11655237 C>T polymorphism did not increase the risk of glioma in different subgroups. CONCLUSIONS: Our study revealed that LINC00673 rs11655237 C>T polymorphism was not correlated to pediatric glioma susceptibility in a Chinese population. In the future, further exploration of this genetic factor in relation to glioma susceptibility will require a larger sample size to verify the current findings.
BACKGROUND: A previous study revealed that single nucleotide polymorphisms (SNPs) in coding genes play a key role in tumorigenesis, genetic disorders, and drug resistance. Xeroderma pigmentosum group C (XPC) protein is a key DNA damage recognition factor that is required for maintaining the genomic stability. However, the correlation between XPC polymorphisms and glioma susceptibility is still unclear. Hence, this study aimed to investigate the correlation between XPC polymorphisms and pediatric glioma susceptibility. METHODS: A total of 399 participants (171 glioma patients and 228 controls) were enrolled to evaluate the correlation between XPC polymorphism and pediatric glioma susceptibility. The count data of two groups was analyzed by chi-squared (χ2) test. Moreover, logistic regression was used to assess the strength of XPC polymorphisms associated with glioma susceptibility. RESULTS: We identified that XPC rs1870134 G>C reduced pediatric glioma susceptibility. Compared to participants with rs1870134 GG/GC genotypes, those with rs1870134 CC genotype had a significantly lower risk for glioma [adjusted odds ratio (AOR) =0.10, 95% confidence interval (CI): 0.01 to 0.78, P=0.028]. Patients with 4-5 genotypes have higher risk of glioma than those with 0-3 genotypes (AOR =1.59, 95% CI: 1.04 to 2.43, P=0.031). The stratified analysis showed that the risky effects of rs2228000 CT/TT genotypes and rs2229090 GC/CC genotypes were more predominant among children aged ≥60 months, astrocytic tumors, and clinical stage I. CONCLUSIONS: We found for the first time that XPC polymorphisms had a statistically significant correlation with pediatric glioma susceptibility in a Chinese population. The XPC rs2228000 CT/TT and rs2229090 GC/CC genotypes could both increase the risk of pediatric glioma in subgroups with females, astrocytic tumors, and clinical stage I. The XPC polymorphism has potential to be a useful adjunct method to screen pediatric glioma.
Circular RNAs (circRNAs) are a type of endogenous non-coding RNA that were discovered to regulate gene expression through multiple pathways. Metastasis remains one of the biggest obstacles in cancer treatment. In this review, we focus on circRNAs involved in cancer tumorigenesis and metastasis. We present recently identified tumor-related circRNAs and discuss their functioning in tumor progression and metastasis. These circRNAs are categorized into different functional mechanisms, including microRNA (miRNA) sponging, protein binding, regulation of host genes, translation of circRNAs, and exosomal circRNAs. Additionally, the indirect functions of circRNAs that regulate epithelial-mesenchymal transition and autophagy are also discussed.
Circular RNAs (circRNAs) are circularized, single-stranded RNAs that are covalently linked. With their abundance in tissues and developmental stage-specific expression, circRNAs participate in a variety of physiological and pathological processes. In this review, we discuss the development of circRNAs used as biomarkers and therapeutic targets for cardiovascular diseases (CVDs), focusing on recent discoveries and applications of exosomal circRNAs that highlight opportunities and challenges. Some studies have identified a spectrum of circRNAs that are differentially expressed in CVDs, while other studies further manipulated specific circRNA expression and showed an ameliorated pathogenic state such as ischemic injury, hypertrophy, and cardiac fibrosis. Studies and applications of circRNAs are being rapidly developed. We expect to see clinical use of circRNAs as biomarkers and targets for disease treatment in the near future.
This study sought novel ionizing radiation-response (IR-response) genes in Caenorhabditis elegans (C. elegans). C. elegans was divided into three groups and exposed to different high doses of IR: 0 gray (Gy), 200 Gy, and 400 Gy. Total RNA was extracted from each group and sequenced. When the transcriptomes were compared among these groups, many genes were shown to be differentially expressed, and these genes were significantly enriched in IR-related biological processes and pathways, including gene ontology (GO) terms related to cellular behaviours, cellular growth and purine metabolism and kyoto encyclopedia of genes and genomes (KEGG) pathways related to ATP binding, GTPase regulator activity, and RNA degradation. Quantitative reverse-transcription PCR (qRT-PCR) confirmed that these genes displayed differential expression across the treatments. Further gene network analysis showed a cluster of novel gene families, such as the guanylate cyclase (GCY), Sm-like protein (LSM), diacylglycerol kinase (DGK), skp1-related protein (SKR), and glutathione S-transferase (GST) gene families which were upregulated. Thus, these genes likely play important roles in IR response. Meanwhile, some important genes that are well known to be involved in key signalling pathways, such as phosphoinositide-specific phospholipase C-3 (PLC-3), phosphatidylinositol 3-kinase age-1 (AGE-1), Raf homolog serine/threonine-protein kinase (LIN-45) and protein cbp-1 (CBP-1), also showed differential expression during IR response, suggesting that IR response might perturb these key signalling pathways. Our study revealed a series of novel IR-response genes in Caenorhabditis elegans that might act as regulators of IR response and represent promising markers of IR exposure.
PURPOSE: Somatic mutations in TP53 and PIK3CA genes, the two most frequent genetic alternations in breast cancer, are associated with prognosis and therapeutic response. This study predicted the presence of TP53 and PIK3CA mutations in breast cancer by using texture and morphology analyses on breast MRI. MATERIALS AND METHODS: A total of 107 breast cancers (dataset A) from The Cancer Imaging Archive (TCIA) consisting of 40 TP53 mutation cancer and 67 cancers without TP53 mutation; 35 PIK3CA mutations cancer and 72 without PIK3CA mutation. 122 breast cancer (dataset B) from Seoul National University Hospital containing 54 TP53 mutation cancer and 68 without mutations were used in this study. At first, the tumor area was segmented by a region growing method. Subsequently, gray level co-occurrence matrix (GLCM) texture features were extracted after ranklet transform, and a series of features including compactness, margin, and ellipsoid fitting model were used to describe the morphological characteristics of tumors. Lastly, a logistic regression was used to identify the presence of TP53 and PIK3CA mutations. The classification performances were evaluated by accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Taking into account the trade-offs of sensitivity and specificity, the overall performances were evaluated by using receiver operating characteristic (ROC) curve analysis. RESULTS: The GLCM texture feature based on ranklet transform is more capable of recognizing TP53 and PIK3CA mutations than morphological feature, especially for the TP53 mutation that achieves statistically significant. The area under the ROC curve (AUC) for TP53 mutation dataset A and dataset B achieved 0.78 and 0.81 respectively. For PIK3CA mutation, the AUC of ranklet texture feature was 0.70. CONCLUSION: Texture analysis of segmented tumor on breast MRI based on ranklet transform is potential in recognizing the presence of TP53 mutation and PIK3CA mutation.
Breast Neoplasms/diagnostic imaging , Breast Neoplasms/genetics , Breast/diagnostic imaging , Class I Phosphatidylinositol 3-Kinases/genetics , Magnetic Resonance Imaging , Tumor Suppressor Protein p53/genetics , Adult , Aged , Aged, 80 and over , Female , Gene Expression Regulation, Neoplastic , Humans , Middle Aged , Mutation , Prognosis , ROC Curve , Radiography
An efficient [2 + 2 + 2] benzannulation of phthalic acids/anhydrides with two alkynes was developed for synthesis of multisubstituted 1-naphthoic acids via Ru-catalyzed C-H activation. The reaction preceded well using atmospheric oxygen as the sole oxidant with high atom/step economies. Facilitated by the free carboxyl group, the products can be easily converted to diverse polycyclic molecules.
The outbreak of food-borne pathogens has become a serious concern; therefore, the detection of pathogenic bacteria in food is required. Untreated, sensitive, and reliable sensors should be developed for the detection of Staphylococcus aureus (S. aureus). In this study, a sensitive antibody-based electrochemical immunosensor was developed using antibody (Ab)-hierarchical mesoporous silica (HMS) bio-conjugates for label-free detection of low concentrations of S. aureus. First, a bio-template method based on butterfly wings was used to prepare the HMS. Then, the carrier material was amino-functionalized to cross-link the antibody with glutaraldehyde. The Ab-HMS bio-conjugates were then immobilized on a glassy carbon electrode (GCE), and the presence of S. aureus was detected by analyzing the changes in the peak currents after the antigen-antibody complex formation. Differential pulse voltammetry (DPV) was performed with bacterial concentrations ranging from 10 to 2 × 103 colony forming units (CFU) mL-1. Selective tests were performed using Escherichia coli (E. coli), Listeria monocytogenes (L. monocytohenes), and Salmonella, and the selective assays showed specific detection of S. aureus using the sensor. In addition, the immunosensor showed a good linear relationship between the peak current increase and logarithmic S. aureus concentration (R 2 = 0.9759) with a fast detection time (20 min) and detection limit of 11 CFU mL-1. When the electrochemical impedance spectroscopy (EIS) was performed under the same conditions, the results showed a good linear relationship between the impedance change value and the bacterial concentration (R 2 = 0.9720), the limit of detection (LOD) was 12 CFU mL-1. The performance of the sensor was compared with that of the colony counting method in the spiked milk sample test. The results showed no significant difference in the test results. Hence, this electrochemical immunosensor can be used to quickly detect S. aureus in actual food samples with a high sensitivity, specificity and stability.
BACKGROUND: The milk fat globule membrane (MFGM) contains various bioactive components which have been shown to maintain gut barrier integrity. This study aimed to evaluate the protective effects of MFGM on intestinal barrier function and its possible mechanisms in a rat model of short bowel syndrome (SBS). MATERIALS AND METHODS: Five-week-old male Sprague-Dawley rats were divided into 3 groups (n = 8 per group), consisting of Sham group and rats submitted to massive small-bowel resection then supplemented with either water (SBS) or 1.5g/kg/d MFGM (SBS+MFGM) by daily gavage. Rats were sacrificed on day 15 postoperation. Intestinal adaptation, gut permeability, bacterial translocation (BT), expression of tight junction proteins, mucin 1 (MUC1), and nucleotide-binding oligomerization domain leucine-rich repeat and pyrin domain-containing protein 3 (NLRP3) pathway in the ileum were evaluated. RESULTS: Both SBS+MFGM and SBS groups exhibited lower body weight and higher ileum villus height than Sham group, but no difference was detected between each other. SBS group had significantly higher intestinal permeability and BT rate than other groups (P < .05). Compared with SBS rats, SBS+MFGM group showed higher expression of tight junction proteins and MUC1, lower expression of NLRP3 and caspase-1 in the ileum, as well as lower interleukin (IL)-1ß but higher IL-18 levels in ileum tissue. CONCLUSIONS: Supplementation of MFGM helps to modulate NLRP3 inflammasome activation and enhances gut barrier integrity in rats after massive small-bowel resection, which provides experimental support for potential applications of MGFM in intestinal barrier dysfunction, although further studies are needed.
Glycolipids/pharmacology , Glycoproteins/pharmacology , Inflammasomes/drug effects , Intestines/drug effects , NLR Family, Pyrin Domain-Containing 3 Protein/drug effects , Short Bowel Syndrome/physiopathology , Animals , Disease Models, Animal , Intestinal Mucosa/drug effects , Intestinal Mucosa/physiology , Intestines/physiology , Lipid Droplets , Male , Rats , Rats, Sprague-Dawley
PURPOSE: Ureteropelvic junction obstruction (UPJO) is a common obstructive disease. To investigate useful urinary biomarkers in UPJO children, the urinary proteome in UPJO infants is analyzed and it is compared with normal controls. EXPERIMENTAL DESIGN: A tandem mass tag (TMT)-based quantitative proteomics study is performed to analyze the proteome of bladder urine (BU) and pelvis urine (PU) from unilateral UPJO infants with differential renal function less than 40% and they are compared with normal control urine (CON). GO analysis is then utilized to analyze general characterization of the proteins. Proteomic results are verified by western blot. RESULTS: There are 81 and 186 proteins significantly changed in BU and PU groups, respectively, as compared to the CON group. Fifty proteins overlaps are found between these two sets of statistically significant differential proteins. These 50 common differential proteins are involved in multiple biological processes. The increased urinary abundance of Fetuin-A, AGP1, AGP2, Alpha-1-microglobulin/Bikunin Precursor (AMBP), and prostaglandin-H2D-isomerase (PGDS) are verified by western blot analysis. CONCLUSIONS AND CLINICAL RELEVANCE: This proteomic analysis indicates that urinary Fetuin-A, AGP1, AGP2, protein AMBP, and PGDS may serve as noninvasive potential biomarkers and these proteins can help to further yield pathological mechanisms involved in UPJO.
Proteome/metabolism , Proteomics , Ureteral Obstruction/urine , Biomarkers/urine , Humans , Infant , Infant, Newborn , Male , Tandem Mass Spectrometry
BACKGROUND AND OBJECTIVE: Liver cancer is the tenth most common cancer in the USA, and its incidence has been increasing for several decades. Early detection, diagnosis, and treatment of the disease are very important. Computed tomography (CT) is one of the most common and robust imaging techniques for the detection of liver cancer. CT scanners can provide multiple-phase sequential scans of the whole liver. In this study, we proposed a computer-aided diagnosis (CAD) system to diagnose liver cancer using the features of tumors obtained from multiphase CT images. METHODS: A total of 71 histologically-proven liver tumors including 49 benign and 22 malignant lesions were evaluated with the proposed CAD system to evaluate its performance. Tumors were identified by the user and then segmented using a region growing algorithm. After tumor segmentation, three kinds of features were obtained for each tumor, including texture, shape, and kinetic curve. The texture was quantified using 3 dimensional (3-D) texture data of the tumor based on the grey level co-occurrence matrix (GLCM). Compactness, margin, and an elliptic model were used to describe the 3-D shape of the tumor. The kinetic curve was established from each phase of tumor and represented as variations in density between each phase. Backward elimination was used to select the best combination of features, and binary logistic regression analysis was used to classify the tumors with leave-one-out cross validation. RESULTS: The accuracy and sensitivity for the texture were 71.82% and 68.18%, respectively, which were better than for the shape and kinetic curve under closed specificity. Combining all of the features achieved the highest accuracy (58/71, 81.69%), sensitivity (18/22, 81.82%), and specificity (40/49, 81.63%). The Az value of combining all features was 0.8713. CONCLUSIONS: Combining texture, shape, and kinetic curve features may be able to differentiate benign from malignant tumors in the liver using our proposed CAD system.
Diagnosis, Computer-Assisted , Liver Neoplasms/diagnostic imaging , Tomography, X-Ray Computed , Algorithms , Humans , Sensitivity and Specificity
