A dual-mode method for detection of miRNA based on the photoluminescence and resonance light scattering.

MicroRNAs (miRNAs) hold potential as useful biomarkers for early diagnosis and evaluation of diverse cancers, but their low abundance and short length make the detection of miRNAs face low sensitivity and accuracy. Herein, a photoluminescence (PL)-resonance light scattering (RLS) dual-mode method was developed for the sensitive and accurate detection of miRNA-141 using CdTe quantum dots (QDs) and Au nanoparticles. The presence of miRNA-141 induced PL quenching and RLS increasing. The limit of detection (LOD) was as low as 3.7 fM, and the miRNA-141 was detected linearly in a range from 10 fM to 10 nM. The dual signals generated no mutual interference and were detected using the same spectrophotometer, allowing for mutual validation to ensure the accuracy and reliability of the detection results. This study proposes valuable references for constructing dual-mode detection methods.

A novel hybrid design and modelling of a customised graded Ti-6Al-4V porous hip implant to reduce stress-shielding: An experimental and numerical analysis.

Stress shielding secondary to bone resorption is one of the main causes of aseptic loosening, which limits the lifespan of hip prostheses and exacerbates revision surgery rates. In order to minimise post-hip replacement stress variations, this investigation proposes a low-stiffness, porous Ti6Al4V hip prosthesis, developed through selective laser melting (SLM). The stress shielding effect and potential bone resorption properties of the porous hip implant were investigated through both in vitro quasi-physiological experimental assays, together with finite element analysis. A solid hip implant was incorporated in this investigation for contrast, as a control group. The stiffness and fatigue properties of both the solid and the porous hip implants were measured through compression tests. The safety factor of the porous hip stem under both static and dynamic loading patterns was obtained through simulation. The porous hip implant was inserted into Sawbone/PMMA cement and was loaded to 2,300 N (compression). The proposed porous hip implant demonstrated a more natural stress distribution, with reduced stress shielding (by 70%) and loss in bone mass (by 60%), when compared to a fully solid hip implant. Solid and porous hip stems had a stiffness of 2.76 kN/mm and 2.15 kN/mm respectively. Considering all daily activities, the porous hip stem had a factor of safety greater than 2. At the 2,300 N load, maximum von Mises stresses on the hip stem were observed as 112 MPa on the medial neck and 290 MPa on the distal restriction point, whereby such values remained below the endurance limit of 3D printed Ti6Al4V (375 MPa). Overall, through the strut thickness optimisation process for a Ti6Al4V porous hip stem, stress shielding and bone resorption can be reduced, therefore proposing a potential replacement for the generic solid implant.

A shortcut weighted fusion pyramid network for microcalcification detection in breast mammograms.

BACKGROUND: High-precision detection for individual and clustered microcalcifications in mammograms is important for the early diagnosis of breast cancer. Large-scale differences between the two types and low-contrast images are major difficulties faced by radiologists when performing diagnoses. OBJECTIVE: Deep learning-based methods can provide end-to-end solutions for efficient detection. However, multicenter data bias, the low resolution of network inputs, and scale differences between microcalcifications lead to low detection rates. Aiming to overcome the aforementioned limitations, we propose a pyramid feature network for microcalcification detection in mammograms, MicroDMa, with adaptive image adjustment and shortcut connections. METHODS: First, mammograms from multiple centers are represented as histograms and cropped by adaptive image adjustment, which mitigates the impact of dataset bias. Second, the proposed shortcut connection pyramid network ensures that the feature map contains more information for multiscale objects, while a shortcut path that jumps over layers enhances the efficiency of feature propagation from bottom to top. Third, the weights of each feature map at different scales in the fusion are trainable; thus, the network can automatically learn the contributions of all feature maps in the fusion stage. RESULT: Experiments were conducted on our in-house dataset and the public dataset INbreast. When the average number of positives per image is one on the in-house dataset, the recall rates of MicroDMa are the 96.8% for individual microcalcification and 98.9% for clustered microcalcification, which are higher than 69.1% and 91.2% achieved by recent deep learning model. Free-response receiver operating characteristic curve of MicroDMa is also higher than other methods when models are performed on INbreast. CONCLUSION: MicroDMa network is better than other methods and it can effectively help radiologists detect and identify two types of microcalcifications in clinical applications.

Stress Shielding and Bone Resorption of Press-Fit Polyether-Ether-Ketone (PEEK) Hip Prosthesis: A Sawbone Model Study.

Stress shielding secondary to bone resorption is one of the main causes of aseptic loosening, which limits the lifespan of the hip prostheses and increases the rates of revision surgery. This study proposes a low stiffness polyether-ether-ketone (PEEK) hip prostheses, produced by fused deposition modelling to minimize the stress difference after the hip replacement. The stress shielding effect and the potential bone resorption of the PEEK implant was investigated through both experimental tests and FE simulation. A generic Ti6Al4V implant was incorporated in this study to allow fair comparison as control group. Attributed to the low stiffness, the proposed PEEK implant showed a more natural stress distribution, less stress shielding (by 104%), and loss in bone mass (by 72%) compared with the Ti6Al4V implant. The stiffness of the Ti6Al4V and the PEEK implant were measured through compression tests to be 2.76 kN/mm and 0.276 kN/mm. The factor of safety for the PEEK implant in both static and dynamic loading scenarios were obtained through simulation. Most of the regions in the PEEK implant were tested to be safe (FoS larger than 1) in terms of representing daily activities (2300 N), while the medial neck and distal restriction point of the implant attracts large von Mises stress 82 MPa and 76 MPa, respectively, and, thus, may possibly fail during intensive activities by yield and fatigue. Overall, considering the reduction in stress shielding and bone resorption in cortical bone, PEEK could be a promising material for the patient-specific femoral implants.

Rapid death due to pulmonary epithelioid haemangioendothelioma in several weeks: A case report.

A 49-year-old woman was admitted to our hospital because of haemoptysis for 6 days. This patient claimed no medical history except high blood sugar. Chest computed tomography (CT) showed infection and multiple nodules on both sides of the lung. Blood tests showed no obvious abnormalities. Tracheoscopy showed haemorrhagic discharge in the left upper lobe and an old thrombus obstructing the lumen in the anterior basal segment of the right lower lobe. Then, CT-guided percutaneous lung biopsy was performed. The pathological results suggested multiple nodular-like lesions in the submitted tissues, and tumour cells were round or short fusiform, forming a solid nest structure, visible mitosis, and a vascular cavity-like structure containing red blood cells. Immunohistochemistry revealed positive staining for Vimentin, Bcl-2, CD31, and CD34; negative staining for CD68, SMA, CR, and D2-40; and 40% Ki67+ positivity. Based on the earlier data, the patient was diagnosed with pulmonary epithelioid haemangioendothelioma. This patient did not receive any treatment for several reasons. Unfortunately, the patient died 8 weeks after diagnosis. In conclusion, we present a case featuring the rapid death due to PEH.

Using the apparent diffusion coefficient histogram analysis to predict response to neoadjuvant chemotherapy in patients with breast cancer: comparison among three region of interest selection methods.

Background: The apparent diffusion coefficient (ADC) value using histogram analysis is helpful to predict responses to neoadjuvant chemotherapy (NAC) in breast cancer. However, the measurement method has not reached a consensus. This study was to assess the diagnostic performance of the ADC histogram analysis at predicting patient response prior to NAC in breast cancer patients using different region of interest (ROI) selection methods. Methods: A total of 75 patients who underwent diffusion weighted imaging (DWI) prior to NAC were retrospectively enrolled from February 2017 to December 2019. Images were measured using small 2-dimensional (2D) ROI, large 2D ROI, and volume ROI methods. The measurement time and ROI size were recorded. Histopathologic responses were acquired using the Miller-Payne grading system after surgery. The inter- and intra-observer repeatability was analyzed and the ADC histogram values from the three ROI methods were compared. The efficacy of each method at predicting patient response prior to NAC was assessed using the area under the receiver operating characteristic curve (AUC) for the whole study population and subgroups according to molecular subtype. Results: Among the 75 enrolled patients, 26 (34.67%) were responsive to NAC therapy. The ADC histogram values were significantly different among the three ROI methods (P≤0.038). Inter- and intra-observer repeatability of the large 2D ROI method and the volume ROI method was generally greater than that observed with the 2D ROI method. The 10% ADC value of the large 2D ROI method showed the greatest AUC (0.701) in the whole study population and in the luminal subgroup (AUC 0.804). The volume ROI method required significantly more time than the other two ROI methods (P<0.001). Conclusions: The small 2D ROI method is not appropriate for predicting response prior to NAC in breast cancer patients due to the poor repeatability. When choosing the ROI method and the histogram parameters for predicting response prior to NAC in breast cancer patients using ADC-derived histogram analysis, 10% of the large 2D ROI method is recommended, especially in luminal A subtype patients.

Erythrobacter aurantius sp. nov., isolated from intertidal seawater in Taizhou.

A Gram-stain-negative, aerobic, chemoheterotrophic and rod-shaped strain, designated as C5T, was isolated from intertidal surface seawater in Taizhou, Zhejiang Province, PR China and characterized using a polyphasic taxonomic approach. Strain C5T could produce carotenoids and bacteriochlorophyll a. Growth was observed at 20-45 °C, at pH 6.0-9.0 and with 0-8.0 % (w/v) NaCl. The 16S rRNA gene sequence identity analysis revealed that strain C5T was the most closely related to Qipengyuania nanhaisediminis CGMCC 1.7715T (98.8%) and Erythrobacter litoralis DSM 8509T (98.7%). The phylogenetic reconstruction based on core genes demonstrated that strain C5T was clustered into the members of the genus Erythrobacter. The average nucleotide identity and digital DNA-DNA hybridization values between strain C5T and Erythrobacter type strains were lower than 76 and 25 %, respectively. The predominant and minor respiratory quinones were identified as ubiquinone-10 and ubiquinone-9. The major fatty acids were summed feature 8 (C18 : 1 ω7c and/or C18 : 1 ω6c) and iso-C18 : 0. Polar lipids included phosphatidylethanolamine, phosphatidylglycerol, a glycosphingolipid and an unidentified aminolipid. Based on the genetic, chemotaxonomic and phenotypic data, strain C5T is concluded to represent a novel species in the genus Erythrobacter, for which the name Erythrobacter aurantius sp. nov. is proposed. The type strain is C5T (=MCCC 1K05108T=KCTC 92307T).

The predictive value of DKI in breast cancer: Does tumour subtype affect pathological response evaluations?

PURPOSE: To explore the differences in quantitative parameters based on diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) between different immunohistochemical indicator statuses and their predictive value for neoadjuvant chemotherapy (NAC) among different phenotypes of breast cancer. METHODS: Eighty-one breast cancer patients who underwent NAC were enrolled in this retrospective study. Correlations between diffusion parameters and immunohistochemical indicators were determined using Spearman's test, and receiver operating characteristic (ROC) curves were constructed to assess the apparent diffusion coefficient (ADC), mean diffusivity (MD), and mean kurtosis (MK) in predicting the pathologic complete response (PCR). RESULTS: Correlations were observed between MK values and hormone receptor (HR) expression (oestrogen receptor (ER): r = 0.315 and progesterone receptor (PR): r = 0.268). The parameters ADC(0,1000), MK, and MD all showed correlations with Ki67 expression (r = 0.276, 0.316 and - 0.224, respectively). ER and Ki67 expression and the parameters MD and MK were significantly different between the PCR and non-PCR groups (AUC = 0.783, 0.688, 0.649 and 0.684, respectively). After splitting patients into subgroups, no significant differences were observed between the PCR and non-PCR groups with human epidermal growth factor receptor 2 (HER2) + and triple-negative (TN) breast cancer. However, we were surprised to find that ADC(0, 1000), MD, and MK were significantly different between different remission groups with HR+/HER2+ subtypes, and the AUCs of each parameter reached 0.794, 0.825, and 0.712, respectively. CONCLUSION: MK was correlated with HR expression. ADC(0, 1000) and DKI were correlated with Ki67 expression. ADC(0, 1000) and the non-Gaussian diffusion model are suitable for predicting PCR in patients with HR+/HER2+ breast cancer before NAC.

[Effect of RITA on TP53 Mutant Human Mantle Cell Lymphoma Cell Line and Its Mechanism].

OBJECTIVE: To investigate the effect of RITA on TP53 mutant human mantle cell lymphoma (MCL) cell line Mino and its possible mechanism. METHODS: Mino cells were cultured in RPMI-1640 and treated with RITA at a concentration of 0-16 µmol/L for 24,48,72 hours. Cell viability was assessed by CCK-8 assay. The cells were treated by RITA (0-8 µmol/L) for 48 h, the cell apoptosis induced by RITA was detected by annexin V/PI flow cytometry. Western blot was performed to evaluate the expression of protein BCL-2, Caspase-3, Cleaved Caspase-3, PARP, MDM2, and P53 in Mino cells. RESULTS: After treatment with 0.5, 1, 2, 4, 8, and 16 µmol/L RITA for 48 h, the proliferation inhibition rate of Mino cells was (1.2±5.6)%, (14.9±4.9)%, (41.7±5.0)%, (61.8±2.4)%, (70.2±2.8)%, and (70.8±2.4)%, respectively. RITA could inhibit the proliferation of Mino cells significantly, and statistical analysis showed that the inhibition rate was increased with the increasing of RITA concentration (r=0.767). After the cells were treated by 4 µmol/L RITA for 24, 48, and 72 h, the proliferation inhibition rate was (25.2±3.8)%, (61.8±2.4)%, and (87.0±0.7)%, respectively. Satistical analysis showed that the inhibition rate was also increased with the increasing of treatment time (r=0.978). The apoptosis rate of Mino cells treated by 0, 2, 4, and 8 µmol/L RITA for 48 h was (5.4±0.4)%, (15.3±0.6)%, (38.7±1.7)%, and (50.8±1.1)%, respectively, and it showed dose-dependent manner (r=0.961). Western blot showed that with the increasing of RITA concentration, the BCL-2 protein expression was decreased in a dose-dependent manner (r=0.932), moreover, PARP cleavage and Caspase-3 activation were found, while the protein expression of MDM2 and P53 showed no change. CONCLUSION: RITA can inhibit the proliferation and induce the apoptosis of Mino cells significantly. The mechanism may be dependent on the Caspase pathway, but independent on the P53 pathway.

Halomonas populi sp. nov. isolated from Populus euphratica.

Three yellow-pigmented, Gram-stain-negative, aerobic, motile by flagella and rod-shaped strains, designated as MCT, PC and RC, were isolated from stems of Populus euphratica. Growth of those three strains occurs at 4-40 °C, pH 6.0-10.0 and with 0.5-18.0% (w/v) NaCl. Respiratory quinones contained ubiquinone-9 and ubiquione-8 as major and minor components, respectively. Major fatty acids (> 10%) were summed feature 8 (C18:1ω6c and/or C18:1ω7c), summed feature 3 (C16:1ω6c and/or C16:1ω7c) and C16:0. Polar lipids included diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, two unidentified phospholipids, one unidentified aminolipid, one unidentified glycolipid and four unidentified lipids. Strains MCT, PC and RC shared pairwise 16S rRNA gene sequence similarities of 99.9-100.0%, and showed higher similarities of 98.4-98.5% with Halomonas songnenensis NEAU-ST10-39T and 98.3-98.4% with Halomonas nanhaiensis YIM M 13059T than to other Halomonas type strains. Genomic comparisons revealed that those three strains had the pan-genome consisting of 4446 orthologous clusters, among which 676 orthologous clusters were absent in other Halomonas type strains. Phylogenomic tree indicated that strains MCT, PC and RC formed an independently stable clade with Halomonas nanhaiensis YIM M 13059T and Halomonas songnenensis NEAU-ST10-39T. The average nucleotide identity and digital DNA-DNA hybridization values between those three strains and other Halomonas type strains were < 89.9% and < 39.3%, respectively. Based upon phenotypic, chemotaxonomic, phylogenetic and genomic results, strains MCT, PC and RC represent a novel species in the genus Halomonas, for which the name Halomonas populi sp. nov. is proposed. The type strain is MCT (= JCM 33545T = MCCC 1K03942T).

Screen Key Genes Associated with Distraction-Induced Osteogenesis of Stem Cells Using Bioinformatics Methods.

Background: Applying mesenchymal stem cells (MSCs), together with the distraction osteogenesis (DO) process, displayed enhanced bone quality and shorter treatment periods. The DO guides the differentiation of MSCs by providing mechanical clues. However, the underlying key genes and pathways are largely unknown. The aim of this study was to screen and identify hub genes involved in distraction-induced osteogenesis of MSCs and potential molecular mechanisms. Material and Methods: The datasets were downloaded from the ArrayExpress database. Three samples of negative control and two samples subjected to 5% cyclic sinusoidal distraction at 0.25 Hz for 6 h were selected for screening differentially expressed genes (DEGs) and then analysed via bioinformatics methods. The Gene Ontology (GO) terms and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were investigated. The protein-protein interaction (PPI) network was visualised through the Cytoscape software. Gene set enrichment analysis (GSEA) was conducted to verify the enrichment of a self-defined osteogenic gene sets collection and identify osteogenic hub genes. Results: Three hub genes (IL6, MMP2, and EP300) that were highly associated with distraction-induced osteogenesis of MSCs were identified via the Venn diagram. These hub genes could provide a new understanding of distraction-induced osteogenic differentiation of MSCs and serve as potential gene targets for optimising DO via targeted therapies.

Diffusion-weighted MRI for predicting pathologic response to neoadjuvant chemotherapy in breast cancer: evaluation with mono-, bi-, and stretched-exponential models.

BACKGROUND: To investigate the performance of diffusion-weighted (DW) MRI with mono-, bi- and stretched-exponential models in predicting pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) for breast cancer, and further outline a predictive model of pCR combining DW MRI parameters, contrast-enhanced (CE) MRI findings, and/or clinical-pathologic variables. METHODS: In this retrospective study, 144 women who underwent NACT and subsequently received surgery for invasive breast cancer were included. Breast MRI including multi-b-value DW imaging was performed before (pre-treatment), after two cycles (mid-treatment), and after all four cycles (post-treatment) of NACT. Quantitative DW imaging parameters were computed according to the mono-exponential (apparent diffusion coefficient [ADC]), bi-exponential (pseudodiffusion coefficient and perfusion fraction), and stretched-exponential (distributed diffusion coefficient and intravoxel heterogeneity index) models. Tumor size and relative enhancement ratio of the tumor were measured on contrast-enhanced MRI at each time point. Pre-treatment parameters and changes in parameters at mid- and post-treatment relative to baseline were compared between pCR and non-pCR groups. Receiver operating characteristic analysis and multivariate regression analysis were performed. RESULTS: Of the 144 patients, 54 (37.5%) achieved pCR after NACT. Overall, among all DW and CE MRI measures, flow-insensitive ADC change (ΔADC200,1000) at mid-treatment showed the highest diagnostic performance for predicting pCR, with an area under the receiver operating characteristic curve (AUC) of 0.831 (95% confidence interval [CI]: 0.747, 0.915; P < 0.001). The model combining pre-treatment estrogen receptor and human epidermal growth factor receptor 2 statuses and mid-treatment ΔADC200,1000 improved the AUC to 0.905 (95% CI: 0.843, 0.966; P < 0.001). CONCLUSION: Mono-exponential flow-insensitive ADC change at mid-treatment was a predictor of pCR after NACT in breast cancer.

Three-dimensional breast tumor segmentation on DCE-MRI with a multilabel attention-guided joint-phase-learning network.

Accurate breast and tumor segmentations from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is vital in breast disease diagnosis. Here, we propose a novel attention-guided joint-phase-learning network for multilabel segmentation including the breast and tumors simultaneously and automatically. Instead of common multichannel inputs, our novel network consists of five separated streams designed for extracting comprehensive features for each DCE-MRI phase to fully use the dynamic intensity of enhanced images. A new time-signal intensity map was designed based on the DCE-MRI pixel-by-pixel values and added as an additional stream to reflect breast tumor dynamic variations. The multiple streams were fused in a fully connected layer to integrate the comprehensive tumor information. Weighted-loss was applied to the multilabel strategy to highlight breast tumor segmentation. In addition, the net applies the self-attention module with grid-based attention coefficients based on a global feature vector to emphasize breast regions and suppress irrelevant non-breast tissue features. We trained our method on 144 DCE-MRI datasets acquired from Philips and achieved mean Dice coefficients of 0.92 and 0.86 for breast and tumor segmentations that were superior to common networks with multichannel structures. The model was extended to an independent test set with 59 cases from two different MRI machines and achieved a Dice coefficient of 0.83 for breast tumor segmentation, which illustrates the robustness of our framework. The automatically generated masks can improve the accuracy and time of diagnosis of malignant and benign breast tumors. Qualitative comparisons illustrate that the proposed method has high precision and generalizability.

Long-term dynamic compression enhancement TGF-ß3-induced chondrogenesis in bovine stem cells: a gene expression analysis.

BACKGROUND: Bioengineering has demonstrated the potential of utilising mesenchymal stem cells (MSCs), growth factors, and mechanical stimuli to treat cartilage defects. However, the underlying genes and pathways are largely unclear. This is the first study on screening and identifying the hub genes involved in mechanically enhanced chondrogenesis and their potential molecular mechanisms. METHODS: The datasets were downloaded from the Gene Expression Omnibus (GEO) database and contain six transforming growth factor-beta-3 (TGF-ß3) induced bovine bone marrow-derived MSCs specimens and six TGF-ß3/dynamic-compression-induced specimens at day 42. Screening differentially expressed genes (DEGs) was performed and then analysed via bioinformatics methods. The Database for Annotation, Visualisation, and Integrated Discovery (DAVID) online analysis was utilised to obtain the Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment. The protein-protein interaction (PPI) network of the DEGs was constructed based on data from the STRING database and visualised through the Cytoscape software. The functional modules were extracted from the PPI network for further analysis. RESULTS: The top 10 hub genes ranked by their connection degrees were IL6, UBE2C, TOP2A, MCM4, PLK2, SMC2, BMP2, LMO7, TRIM36, and MAPK8. Multiple signalling pathways (including the PI3K-Akt signalling pathway, the toll-like receptor signalling pathway, the TNF signalling pathway, and the MAPK pathway) may impact the sensation, transduction, and reaction of external mechanical stimuli. CONCLUSIONS: This study provides a theoretical finding showing that gene UBE2C, IL6, and MAPK8, and multiple signalling pathways may play pivotal roles in dynamic compression-enhanced chondrogenesis.

Combining multiple biomarkers to linearly maximize the diagnostic accuracy under ordered multi-class setting.

Either in clinical study or biomedical research, it is a common practice to combine multiple biomarkers to improve the overall diagnostic performance. Despite the fact there exist a large number of statistical methods for biomarker combination under binary classification, research on this topic under multi-class setting is sparse. The overall diagnostic accuracy, i.e. the sum of correct classification rates, directly measures the classification accuracy of the combined biomarkers. Hence the overall accuracy can serve as an important objective function for biomarker combination, especially when the combined biomarkers are used for the purpose of making medical diagnosis. In this paper, we address the problem of combining multiple biomarkers to directly maximize the overall diagnostic accuracy by presenting several grid search methods and derivation-based methods. A comprehensive simulation study was conducted to compare the performances of these methods. An ovarian cancer data set is analyzed in the end.

Manufacture and clinical application of the forearm pronation's assistant tableware in the severely burned.

INTRODUCTION: Even after reconstructive surgery, it is still difficult for patients with severe burns to achieve independent eating activity. In this project, we customized the forearm pronation's assistant tableware to assist in improvement with eating activities. METHODS: From January 2017 to December 2018, 28 patients with severe burns including the hands were recruited. For the patient's independent eating activities, we customized forearm pronation's tableware (forks and spoons). We compared modified Barthel index (MBI) and Visual analogue scale (VAS) of satisfaction under three conditions: no auxiliary tableware, ADL universal cuff, or forearm pronation tableware; to compare the duration and the weight of food spilled during lunch when the patients wore the ADL universal cuff or the forearm pronation's tableware. Differences in MBI (rank data) were tested by the Friedman test, differences in VAS (normal distribution) were tested with One-way ANOVA (Bonferroni), differences in the duration and the weight (normal distribution data) were tested by paired sample t test. RESULTS: After wearing the forearm pronation's assistant tableware, MBI VAS both increased more than when the patients did not wear the auxiliary tableware (all p＜0.05). When the subjects wore forearm pronation tableware, the duration of lunch significantly decreased and the quality of eating activity significantly improved compared to the ADL universal cuff in eating activity (all p＜0.05). CONCLUSION: After wearing the forearm pronation's assistant tableware, the patients with severe burns completely or almost completely accomplished independent eating, the duration was decreased, and during eating activity the quality and the satisfaction were improved. CLINICAL TRIAL REGISTRATION: Chinese Clinical trial registry, ChiCTR1800019963.

Breast DCE-MRI radiomics: a robust computer-aided system based on reproducible BI-RADS features across the influence of datasets bias and segmentation methods.

PURPOSE: A highly accurate and robust computer-aided system based on quantitative high-throughput Breast Imaging Reporting and Data System (BI-RADS) features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can drive the success of radiomic applications in breast cancer diagnosis. We aim to build a stable system with highly reproducible radiomics features, which can make diagnostic performance independent of datasets bias and segmentation methods. METHOD: We applied a dataset of 267 patients including 136 malignant and 131 benign tumors from two MRI manufacturers, where 211 cases from a Philips system and 55 cases from a GE system. First, manual annotations, 3D-Unet and 2D-Unet were applied as different segmentation methods. Second, we designed and extracted 3172 features from six modalities of DCE-MRI based on BI-RADS. Third, the feature selection was conducted. Between-class distance was utilized to eliminate the effect of dataset bias caused by two machines. Concordance correlation coefficient, intraclass correlation coefficient and deviation were employed to evaluate the influence of three segmentation methods. We further eliminated features redundancy using genetic algorithm. Finally, three classifiers including support vector machine (SVM), the bagged trees and K-Nearest Neighbor were evaluated by their performance for diagnosing malignant and benign tumors. RESULTS: A total of 246 features were preserved to have high stability and reproducibility. The final feature set showed the robust performance under these factors and achieved the area under curve of 0.88, the accuracy of 0.824, the sensitivity of 0.844, the specificity of 0.807 in differentiating benign and malignant tumors with the SVM classifier using manually segmentation results. CONCLUSION: The final selected 246 features are reproducible and show little dependence on segmentation methods and data perturbation. The high stability and effectiveness of diagnosis across these factors illustrate that the preserved features can be used for prognostic analysis and help radiologists in the diagnosis of breast cancer.

A comprehensive and comparative review of optimal cut-points selection methods for diseases with multiple ordinal stages.

Cut-points selection is a key topic in the field of diagnostic studies. For binary classification, there exist several well-developed methods, some of which have been extended to three-class settings and beyond. This paper focuses on optimal cut-points selection methods for diseases with multiple ordinal stages. The purpose of this paper is two-fold: 1) to propose three new cut-points selection methods; and 2) to present a comprehensive simulation study to assess and compare the performance of all the available methods. Two real data sets, one from ovarian cancer and the other from pancreatic cancer, are analyzed.

Tumor Necrosis Factor-α Gene Polymorphism (G-308A) and Dilated Cardiomyopathy.

The issue that genetic polymorphism of tumor necrosis factor-α (TNF-α) is associated with dilated cardiomyopathy (DCM) is debatable. We sought to investigate the potential role of TNF-α gene polymorphism (G-308A) in the susceptibility to dilated cardiomyopathy.We retrieved PubMed, EMBASE, and CNKI to collect all articles which reported on the association between TNF-α G-308A polymorphism and dilated cardiomyopathy. Two authors used the Newcastle-Ottawa Scale (NOS) checklist to assess the quality of the included studies. The odds ratio (OR) with 95% confidence intervals (CI) were pooled in a specific genetic model to assess the association and Stata version 14.0 software was used.A total of 9 studies with 1338 patients and 1677 controls were included in this study. The results from this meta-analysis indicated that TNF-α G-308A polymorphism significantly increased the risk of dilated cardiomyopathy in heterozygous comparison (GA versus GG: OR = 1.87; 95%CI = 1.03-3.40; P < 0.05). The increased risk of DCM was also found in Asian populations using a dominant model and heterozygous comparison (GA+AA versus GG: OR = 2.00, 95%CI = 1.02-3.92, P < 0.05; GA versus GG: OR = 1.94, 95%CI = 1.23-3.06, P < 0.05).The current meta-analysis revealed that TNF-α gene polymorphism (G-308A) may be associated with the susceptibility to DCM.

Diagnostic value of cadmium-zinc-telluride myocardial perfusion imaging versus coronary angiography in coronary artery disease: A PRISMA-compliant meta-analysis.

BACKGROUND: Rapid progress has been made in research of cadmium-zinc-telluride (CZT) technology in the last few years, which might serve as a new method to diagnose coronary artery disease. However, compared with coronary angiography, the diagnostic value of CZT is still controversial. We aimed to evaluate diagnosis value of coronary angiography versus CZT in coronary artery disease. METHODS: We searched the database for eligible researches associated with CZT- myocardial perfusion imaging (MPI) and invasive coronary angiography, extracted the relevant data, and rigorously screened it according to the inclusion and exclusion criteria. The accuracy indicators included sensitivity, specificity, accuracy, positive and negative likelihood ratios. RESULTS: According to the inclusion and exclusion criteria, we finally found 20 studies containing 2350 patients in this search. Pooled results showed that sensitivity of CZT-MPI was 0.84% and 95% confidence interval (95% CI): 0.78 to 0.89, specificity was 0.72, 95% CI (0.62-0.76), the specificity was lower apparently. The positive likelihood ratio was 3.0, 95% CI (2.4-3.8), the negative likelihood ratio was 0.22, 95% CI (0.16-0.31), diagnostic odds ratio was 14, 95% CI (7.84-17.42). CONCLUSION: This meta-analysis showed that CZT-MPI had satisfactory sensitivity and specificity for diagnosing coronary artery disease. Larger studies are required for further evaluation.