Vapor-phase synthesis, growth mechanism and thickness-independent elastic modulus of single-crystal tungsten nanobelts

Single-crystal tungsten nanobelts with thicknesses from tens to hundreds of nanometers, widths of several micrometers and lengths of tens of micrometers were synthesized using chemical vapor deposition. Surface energy minimization was believed to have played a crucial role in the growth of the synthesized nanobelts enclosed by the low-energy {110} crystal planes of body-centered-cubic structure. The anisotropic growth of the crystallographically equivalent {110} crystal planes could be attributable to the asymmetric concentration distribution of the tungsten atom vapor around the nanobelts during the growth process. The elastic moduli of the synthesized tungsten nanobelts with thicknesses ranging from 65 to 306 nm were accurately measured using a newly developed thermal vibration method. The measured modulus values of the tungsten nanobelts were thickness-dependent. After eliminating the effect of surface oxidization using a core-shell model, the elastic modulus of tungsten nanobelts became constant, which is close to that of the bulk tungsten value of 410 GPa

An invasive podosome-like structure promotes fusion pore formation during myoblast fusion

An F-actin–enriched protrusion resembling an invasive podosome promotes fusion pore formation between muscle founder cells and fusion-competent myoblasts

Rapidly progressive interstitial lung disease risk prediction in anti-MDA5 positive dermatomyositis: the CROSS model

BackgroundThe prognosis of anti-melanoma differentiation-associated gene 5 positive dermatomyositis (anti-MDA5+DM) is poor and heterogeneous. Rapidly progressive interstitial lung disease (RP-ILD) is these patients’ leading cause of death. We sought to develop prediction models for RP-ILD risk in anti-MDA5+DM patients.MethodsPatients with anti-MDA5+DM were enrolled in two cohorts: 170 patients from the southern region of Jiangsu province (discovery cohort) and 85 patients from the northern region of Jiangsu province (validation cohort). Cox proportional hazards models were used to identify risk factors of RP-ILD. RP-ILD risk prediction models were developed and validated by testing every independent prognostic risk factor derived from the Cox model.ResultsThere are no significant differences in baseline clinical parameters and prognosis between discovery and validation cohorts. Among all 255 anti-MDA5+DM patients, with a median follow-up of 12 months, the incidence of RP-ILD was 36.86%. Using the discovery cohort, four variables were included in the final risk prediction model for RP-ILD: C-reactive protein (CRP) levels, anti-Ro52 antibody positivity, short disease duration, and male sex. A point scoring system was used to classify anti-MDA5+DM patients into moderate, high, and very high risk of RP-ILD. After one-year follow-up, the incidence of RP-ILD in the very high risk group was 71.3% and 85.71%, significantly higher than those in the high-risk group (35.19%, 41.69%) and moderate-risk group (9.54%, 6.67%) in both cohorts.ConclusionsThe CROSS model is an easy-to-use prediction classification system for RP-ILD risk in anti-MDA5+DM patients. It has great application prospect in disease management

Improved Margin Sampling for Active Learning

Abstract. Active learning is a learning mechanism which can actively query the user for labels. The goal of an active learning algorithm is to build an effective training set by selecting those most informative samples and improve the efficiency of the model within the limited time and resource. In this paper, we mainly focus on a state-of-the-art active learning method, the SVM-based margin sampling. However, margin sampling does not consider the distribution and the structural space connectivity among the unlabeled data when several examples are chosen simultaneously, which may lead to oversampling on dense regions. To overcome this shortcoming, we propose an improved margin sampling method by applying the manifold-preserving graph reduction algorithm to the original margin sampling method. Experimental results on multiple data sets demonstrate that our method obtains better classification performance compared with the original margin sampling

Preconditioned MSCs Alleviate Cerebral Ischemia-Reperfusion Injury in Rats by Improving the Neurological Function and the Inhibition of Apoptosis

Mesenchymal stem cells (MSCs) have great application prospects in the treatment of ischemic injury. However, their long-time cultivation before transplantation and poor survival after transplantation greatly limit the therapeutic effect and applications. This study aimed to investigate whether MSCs under the ischemic microenvironment could improve their survival and better alleviate cerebral ischemic injury. Firstly, we used ischemic brain tissue to culture MSCs and evaluated the functional changes of MSCs. Then a middle cerebral artery occlusion (MCAO) model was induced in rats, and the pretreated MSCs were injected via the tail vein. The adhesive removal test, rotarod test, modified neurological severity score, and pathological analyses were applied to assess the rats’ neurological function. Then the expression of neuron and apoptosis related markers was detected. The results indicated that ischemic brain tissue pretreated MSCs promoted the proliferation and the release of the growth factors of MSCs. Meanwhile, in MCAO model rats, transplantation of pretreated MSCs enhanced the neurogenesis, attenuated behavioral changes, reduced infarct size, and inhibited apoptosis. The expression of B-cell lymphoma-2 (Bcl-2), brain-derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), NF-L, and NeuN were increased, while BCL2-Associated X (Bax) and Caspase-3 decreased. Our results suggest that MSCs pretreatment with stroke brain tissue could be an effective strategy in treating cerebral ischemic injury

Removal of foreign bodies embedded in the urinary bladder wall by a combination of laparoscopy and carbon dioxide cystoscopic assistance: Case report and literature review

Purpose: To report a case of combined laparoscopic and carbon dioxide partial cystectomy and foreign body removal and to review the existing literature on the topic. Materials and Methods: A 43-year-old Asian woman was found to have an intrauterine device embedded in the bladder wall during evaluation for chronic pelvic pain and urinary tract infection. She underwent cystoscopic-laparoscopic partial cystectomy, with an uncomplicated postoperative course. She had normal renal function during the follow-up period. This case demonstrates the possibility and safety of performing cystoscopic-laparoscopic partial cystectomy for the removal of a partially implanted intravesical foreign body. Results: The patient recovered without incident and was discharged 7 days after surgery. No abnormalities were noted in the urine output or renal function in the postoperative follow-up period. No complications due to retrograde flow of carbon dioxide up the ureters or air embolism were noted during the procedure or postoperatively. Conclusions: The combination of laparoscopy and air cystoscopy has been shown to be an optimal method for retracting foreign bodies embedded in the bladder wall. Also, air cystoscopy can be used to give doctors a better view in cases in which vision is compromised under water-contrast cystoscopy

Music video affective understanding using feature importance analysis

Music video is a popular type of entertainment by viewers. Currently, the novel indexing and retrieval approach based on the affective cues contained in music videos becomes more and more attractive to users. Music video affective analysis and understanding is one of the most popular topics in current multimedia community. In this paper, we propose a novel feature importance analysis approach to select most representative arousal and valence features for arousal and valence modeling. Compared with state-of-the-art work by Zhang on music video affective analysis, our main contributions are in the following aspects: (1) Another 3 affect-related features are extracted to enrich the feature set and exploit their correlation with arousal and valence. (2) All extracted features are ordered via feature importance analysis, and then optimal feature subset is selected after ordering. (3) Different regression methods are compared for arousal and valence modeling in order to find the fittest estimation function. Our method achieves 33.39% and 42.17% deduction in terms of mean absolute error compared with Zhang's method. Experimental results demonstrate our proposed method has a considerable improvement on music video affective understanding

Correlation-based feature selection and regression

Music video is a well-known medium in music entertainment which contains rich affective information and has been widely accepted as emotion expressions. Affective analysis plays an important role in the content-based indexing and retrieval of music video. This paper proposes a general scheme for music video affective estimation using correlation based feature selection followed by regression. Arousal score and valence score with four grade scales are used to measure music video affective content in 2D arousal/valence space. The main contributions are in the following aspects: (1) correlation-based feature selection is performed after feature extraction to select representative arousal and valence features; (2) different regression methods including multiple linear regression and support vector regression with different kernels are compared to find the fittest estimation model. Significant reductions in terms of both mean absolute error and variation of absolute error compared with the state-of-the-art methods clearly demonstrate the effectiveness of our proposed method

Association of Plasma Myeloperoxidase Level with Risk of Coronary Artery Disease in Patients with Type 2 Diabetes

Aims. This study aimed to investigate whether the change of plasma myeloperoxidase (MPO) level would be associated with the incidence of coronary artery disease (CAD) among diabetic patients. Methods. 339 patients with type 2 diabetes mellitus (DM) underwent coronary angiography. Of them, 204 cases had CAD and were assigned to CAD group and 135 cases without CAD were assigned to non-CAD group. Results. Compared to non-CAD group, CAD group had higher level of plasma MPO (p<0.01). Multiple linear regression analysis showed that plasma MPO level was correlated with Gensini score. Multiple logistic analysis showed that the odds ratios for CAD across increasing tertiles of MPO level were 1.191 (0.971–1.547) and 1.488 (1.115–2.228) (p=0.048, p=0.009 versus 1st tertile of MPO level, resp.) by adjusting for age, sex, and other conventional risk factors for CAD. The subjects were stratified into nine groups according to tertiles of MPO and HbA1c. The odds ratio for CAD was significantly higher in group with highest levels of MPO and HbA1c (OR = 4.08, p<0.01). Conclusion. Plasma MPO level was positively correlated with the degree of coronary artery stenosis in type 2 diabetic patients, and increasing blood glucose might amplify the association between MPO and CAD