Improved ambient air quality is associated with decreased prevalence of childhood asthma and infancy shortly after weaning is a sensitive exposure window.

BACKGROUND: The urban ambient air quality has been largely improved in the past decade. It is unknown whether childhood asthma prevalence is still increasing in ever top-ranking city of Shanghai, whether the improved air quality is beneficial for children's asthma and what time window of exposure plays critical roles. METHODS: Using a repeat cross-sectional design, we analyzed the association between early life exposure to particles and wheezing/asthma in each individual and combined surveys in 2011 and 2019, respectively, in 11,825 preschool children in Shanghai. RESULTS: A significantly lower prevalence of doctor-diagnosed asthma (DDA) (6.6% vs. 10.5%, p < 0.001) and wheezing (10.5% vs. 23.2%, p < 0.001) was observed in 2019 compared to 2011. Exposure to fine particulate matter (PM2.5 ), coarse particles (PM2.5-10 ) and inhalable particles (PM10 ) was decreased in 2019 by 6.3%, 35.4%, and 44.7% in uterus and 24.3%, 20.2%, and 31.8% in infancy, respectively. Multilevel log-binomial regression analysis showed exposure in infancy had independent association with wheezing/DDA adjusting for exposure in uterus. For each interquartile range (IQR) increase of infancy PM2.5 , PM2.5-10 and PM10 exposure, the odds ratios were 1.39 (95% confidence interval (CI): 1.24-1.56), 1.51 (95% CI:1.15-1.98) and 1.53 (95% CI:1.27-1.85) for DDA, respectively. The distributed lag non-linear model showed the sensitive exposure window (SEW) was 5.5-11 months after birth. Stratified analysis showed the SEWs were at or shortly after weaning, but only in those with <6 months of exclusive breastfeeding. CONCLUSIONS: Improved ambient PM benefits in decreasing childhood asthma prevalence. We firstly reported the finding of SEW to PM at or closely after weaning on childhood asthma.

An Asian Perspective on Gender Differences in Clinical Outcomes and Echocardiographic Profiles of Patients With Medically Managed Severe Aortic Stenosis.

BACKGROUND: Gender differences in valvular heart disease are increasingly recognised. A prior study has suggested better surgical outcomes in women with symptomatic aortic stenosis (AS). We investigate gender differences in medically managed severe AS. METHOD: We studied 347 patients with severe AS (aortic valve area index <0.6 cm2/m2) in terms of baseline clinical background, echocardiographic characteristics, and clinical outcomes. Appropriate univariate and multivariate models were employed, while Kaplan-Meier curves were constructed to compare mortality outcomes. RESULTS: In total, 205 (59%) patients were women. Despite higher incidences of hypertension (75.6% vs 47.3%) and diabetes mellitus (46.5% vs 29.5%) in women, women had improved survival (Kaplan-Meier log-rank = 6.24, p = 0.012). After adjusting for age (hazard ratio [HR], 1.034; 95% confidence interval [CI], 1.014-1.054), hypertension (HR, 1.469; 95% CI, 0.807-2.673), diabetes (HR, 1.219; 95% CI, 0.693-2.145), and indexed aortic valve area (HR 0.145, 95% CI 0.031-0.684) on multivariate analyses, female gender remained independently associated with lower mortality (HR, 0.561; 95%, CI 0.332-0.947). Women tended to have smaller body surface area (BSA), left ventricular (LV) internal diastolic diameter, and smaller LV outflow tract diameter but were similar to men in terms of LV ejection fraction, AS severity, and patterns of LV remodelling. CONCLUSIONS: Women appeared to have better outcomes compared to men in medically managed severe AS. These gender differences warrant further study and may affect prognosis, follow-up, and timing of valve surgery.

A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study.

Tumor volume estimation, as well as accurate and reproducible borders segmentation in medical images, are important in the diagnosis, staging, and assessment of response to cancer therapy. The goal of this study was to demonstrate the feasibility of a multi-institutional effort to assess the repeatability and reproducibility of nodule borders and volume estimate bias of computerized segmentation algorithms in CT images of lung cancer, and to provide results from such a study. The dataset used for this evaluation consisted of 52 tumors in 41 CT volumes (40 patient datasets and 1 dataset containing scans of 12 phantom nodules of known volume) from five collections available in The Cancer Imaging Archive. Three academic institutions developing lung nodule segmentation algorithms submitted results for three repeat runs for each of the nodules. We compared the performance of lung nodule segmentation algorithms by assessing several measurements of spatial overlap and volume measurement. Nodule sizes varied from 29 µl to 66 ml and demonstrated a diversity of shapes. Agreement in spatial overlap of segmentations was significantly higher for multiple runs of the same algorithm than between segmentations generated by different algorithms (p < 0.05) and was significantly higher on the phantom dataset compared to the other datasets (p < 0.05). Algorithms differed significantly in the bias of the measured volumes of the phantom nodules (p < 0.05) underscoring the need for assessing performance on clinical data in addition to phantoms. Algorithms that most accurately estimated nodule volumes were not the most repeatable, emphasizing the need to evaluate both their accuracy and precision. There were considerable differences between algorithms, especially in a subset of heterogeneous nodules, underscoring the recommendation that the same software be used at all time points in longitudinal studies.

Epidermal growth factor receptor mutation in lung adenocarcinomas: relationship with CT characteristics and histologic subtypes.

PURPOSE: To retrospectively identify quantitative computed tomographic (CT) features that correlate with epidermal growth factor receptor (EGFR) mutation in surgically resected lung adenocarcinomas stratified by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS) classification in an East Asian cohort of patients known to have a high prevalence of EGFR mutations. MATERIALS AND METHODS: An institutional review board approved this study and waived informed consent. In 153 surgically resected lung adenocarcinomas, EGFR mutation was determined by direct DNA sequencing. Histologic subtype was classified according to IASLC/ATS/ERS classification of lung adenocarcinoma. At preoperative chest CT, the percentage of ground-glass opacity (GGO) volume and total tumor volume of each tumor were measured by using a semiautomated algorithm. Distribution of EGFR mutation according to histologic subtype, percentage of GGO volume, and total tumor volume was evaluated by using the Fisher exact test, the Student t test, trend analysis, and multiple logistic regression analysis. RESULTS: Exon 21 missense mutation was more frequent in lepidic predominant adenocarcinomas than in other histologic subtypes (odds ratio, 3.44; 95% confidence interval: 1.53, 7.74; P = .003). GGO volume percentage in tumors with exon 21 missense mutation (61.7% ± 31.9 [standard deviation]) was significantly higher than that in EGFR wild-type tumors (30.0% ± 38.5) (P = .0001) and exon 19-mutated tumors (28.9% ± 37.7) (P = .0006). A significant trend of prevalence of exon 21 missense mutation increasing along with increasing GGO volume (P = .0008) was found. CONCLUSION: GGO volume percentage in tumors with exon 21 missense mutation was significantly higher than that in tumors with other EGFR mutation status. This can be related to the fact that exon 21 missense mutation was significantly more frequent in lepidic predominant adenocarcinomas, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic predominant invasive adenocarcinoma, according to IASLE/ATS/ERS classification.

Multiphasic contrast-enhanced MRI: single-slice versus volumetric quantification of tumor enhancement for the assessment of renal clear-cell carcinoma fuhrman grade.

PURPOSE: To assess the association between clear-cell carcinoma pathology grade at nephrectomy and magnetic resonance imaging (MRI) tumor enhancement. MATERIALS AND METHODS: The Institutional Review Board approved this retrospective study and waived the informed consent requirement. In all, 32 patients underwent multiphase contrast-enhanced MRI prior to nephrectomy. MRI tumor enhancement was measured using two approaches: 1) the most enhancing portion of the tumor on a single slice and 2) volumetric analysis of enhancement in the entire tumor. Associations between pathological grade, tumor size, and enhancement were evaluated using the Kruskal-Wallis test and generalized logistic regression models. RESULTS: No significant association between pathology grade and enhancement was found when measurements were made on a single slice. When measured in the entire tumor, significant associations were found between higher pathology grades and lower mean, median, top 10%, top 25%, and top 50% tumor enhancement (P < 0.001-0.002). On multivariate analysis the association between grade and enhancement remained significant (P = 0.041-0.043), but tumor size did not make an additional contribution beyond tumor enhancement alone in differentiating between tumor grades. CONCLUSION: There is significant association between tumor grade and enhancement, but only when measured in the entire tumor and not on the most enhancing portion on a single slice.

Evolution of the oxidation behaviors of highly oxidation-resistant (Ti0.8Nb0.2)C in 1000-1200 °C steam.

The evolution of the oxidation behaviors of the highly oxidation-resistant (Ti0.8Nb0.2)C was investigated in a 1000-1200 °C steam environment. For the specimen oxidized below 1200 °C, a compact oxide layer less than 7 µm thick was obtained. By increasing the temperature to 1200 °C, the oxide layer grows quickly to over 30 µm. Variable distribution of Ti and Nb in the oxide scales reveals the significance of the outward diffusion of the metal elements during oxidation. Synchronized variations in Ti and Nb were observed in the specimen oxidized below 1200 °C, while the distribution trends of Ti and Nb were opposite in the specimen oxidized at 1200 °C. The incorporation of Nb effectively lowered the diffusion rate of Ti through the oxide scales and the grain growth of the oxides. Suppressed diffusion and dense oxide scales are responsible for the excellent oxidation resistance of (Ti0.8Nb0.2)C below 1200 °C.

A Highly Efficient Model to Study the Semantics of Salient Object Detection.

CNN-based salient object detection (SOD) methods achieve impressive performance. However, the way semantic information is encoded in them and whether they are category-agnostic is less explored. One major obstacle in studying these questions is the fact that SOD models are built on top of the ImageNet pre-trained backbones which may cause information leakage and feature redundancy. To remedy this, here we first propose an extremely light-weight holistic model tied to the SOD task that can be freed from classification backbones and trained from scratch, and then employ it to study the semantics of SOD models. With the holistic network and representation redundancy reduction by a novel dynamic weight decay scheme, our model has only 100K parameters,  âˆ¼  0.2% of parameters of large models, and performs on par with SOTA on popular SOD benchmarks. Using CSNet, we find that a) SOD and classification methods use different mechanisms, b) SOD models are category insensitive, c) ImageNet pre-training is not necessary for SOD training, and d) SOD models require far fewer parameters than the classification models. The source code is publicly available at https://mmcheng.net/sod100k/.

High-Entropy Pyrochlore A2B2O7 with Both Heavy and Light Rare-Earth Elements at the A Site.

A novel class of high-entropy pyrochlore ceramics (HEPCs) with multiple heavy and light rare-earth elements at the A site were successfully synthesized via solid-state reaction. Both the XRD patterns and Raman spectroscopy demonstrated the single pyrochlore structure feature of seven kinds of HEPCs. Electron microscopic images revealed the typical morphology and the homogeneous distribution of all rare-earth elements. It can be concluded that the significance of configuration entropy in the HEPC system has promoted the tervalent lanthanide nuclides to form a single pyrochlore structure. This work is expected to provide guidance for the further design of high-entropy pyrochlore/fluorite ceramics.

Cost-effectiveness of olaparib maintenance therapy when used with and without restriction by BRCA1/2 mutation status for platinum-sensitive relapsed ovarian cancer.

Objectives: To determine whether olaparib maintenance therapy, used with and without restriction by BRCA1/2 mutation status, is cost-effective at the population level for platinum-sensitive relapsed ovarian cancer in Singapore.Methods: A partitioned survival model compared three management strategies: 1) treat all patients with olaparib; 2) test for germline BRCA1/2 mutation, followed by targeted olaparib use in mutation carriers only; 3) observe all patients. Mature overall survival (OS) data from Study 19 and a 15-year time horizon were used and direct medical costs were applied. Sensitivity analyses were conducted to explore uncertainties.Results: Treating all patients with olaparib was the most costly and effective strategy, followed by targeted olaparib use, and observation of all patients. Base-case incremental cost-effectiveness ratios (ICERs) for all-olaparib and targeted use strategies were SGD133,394 (USD100,926) and SGD115,736 (USD87,566) per quality-adjusted life year (QALY) gained, respectively, compared to observation. ICERs were most sensitive to the cost of olaparib, time horizon and discount rate for outcomes. When these parameters were varied, ICERs remained above SGD92,000 (USD69,607)/QALY.Conclusions: At the current price, olaparib is not cost-effective when used with or without restriction by BRCA1/2 mutation status in Singapore, despite taking into account potential OS improvement over a long time horizon.

Feature selection and performance evaluation of support vector machine (SVM)-based classifier for differentiating benign and malignant pulmonary nodules by computed tomography.

There are lots of work being done to develop computer-assisted diagnosis and detection (CAD) technologies and systems to improve the diagnostic quality for pulmonary nodules. Another way to improve accuracy of diagnosis on new images is to recall or find images with similar features from archived historical images which already have confirmed diagnostic results, and the content-based image retrieval (CBIR) technology has been proposed for this purpose. In this paper, we present a method to find and select texture features of solitary pulmonary nodules (SPNs) detected by computed tomography (CT) and evaluate the performance of support vector machine (SVM)-based classifiers in differentiating benign from malignant SPNs. Seventy-seven biopsy-confirmed CT cases of SPNs were included in this study. A total of 67 features were extracted by a feature extraction procedure, and around 25 features were finally selected after 300 genetic generations. We constructed the SVM-based classifier with the selected features and evaluated the performance of the classifier by comparing the classification results of the SVM-based classifier with six senior radiologists' observations. The evaluation results not only showed that most of the selected features are characteristics frequently considered by radiologists and used in CAD analyses previously reported in classifying SPNs, but also indicated that some newly found features have important contribution in differentiating benign from malignant SPNs in SVM-based feature space. The results of this research can be used to build the highly efficient feature index of a CBIR system for CT images with pulmonary nodules.

Adsorption of glucose oxidase onto single-walled carbon nanotubes and its application in layer-by-layer biosensors.

In this study, we describe the use of a sodium cholate suspension-dialysis method to adsorb the redox enzyme glucose oxidase (GOX) onto single-walled carbon nanotubes (SWNT). By this method, solutions of dispersed and debundled SWNTs were prepared that remained stable for 30 days and which retained 75% of the native enzymatic activity. We also demonstrate that GOX-SWNT conjugates can be assembled into amperometric biosensors with a poly[(vinylpyridine)Os(bipyridyl)2Cl(2+/3+)] redox polymer (PVP-Os) through a layer-by-layer (LBL) self-assembly process. Incorporation of SWNT-enzyme conjugates into the LBL films resulted in current densities as high as 440 microA/cm2, which were a 2-fold increase over the response of films without SWNTs. We also demonstrate that the adsorption pH of the redox polymer solution and the dispersion quality of SWNTs were important parameters in controlling the electrochemical and enzymatic properties of the LBL films.

Malignant lesion segmentation in contrast-enhanced breast MR images based on the marker-controlled watershed.

Breast tumor volume measured on MRI has been used to assess response to neoadjuvant chemotherapy. However, accurate and reproducible delineation of breast lesions can be challenging, since the lesions may have complicated topological structures and heterogeneous intensity distributions. In this article, the authors present an advanced computerized method to semiautomatically segment tumor volumes on T1-weighted, contrast-enhanced breast MRI. The method starts with manual selection of a region of interest (ROI) that contains the lesion to be segmented in a single image, followed by automated separation of the lesion volume from its surrounding breast parenchyma by using a unique combination of the image processing techniques including Gaussian mixture modeling and a marker-controlled watershed transform. Explicitly, the Gaussian mixture modeling is applied to an intensity histogram of the pixels inside the ROI to distinguish the tumor class from other tissues. Based on the ROI and the intensity distribution of the tumor, internal and external markers are determined and the tumor contour is delineated using the marker-controlled watershed transform. To obtain the tumor volume, the segmented tumor in one slice is propagated to the adjacent slice to form an ROI in that slice. The marker-controlled watershed segmentation is then used again to obtain a tumor contour in the propagated slice. This procedure is terminated when there is no lesion in an adjacent slice. To reduce measurement variations possibly caused by the manual selection of the ROI, the segmentation result is refined based on an automatically determined ROI based on the segmented volume. The algorithm was applied to 13 patients with breast cancer, prospectively accrued prior to beginning neoadjuvant chemotherapy. Each patient had two MRI scans, a baseline MRI examination prior to commencing neoadjuvant chemotherapy and a 1 week follow-up after receiving the first dose of neoadjuvant chemotherapy. Blinded to the computer segmentation results, two experienced radiologists manually delineated all tumors independently. The computer results were then compared with the manually generated results using the volume overlap ratio, defined as the intersection of the computer- and radiologist-generated tumor volumes divided by the union of the two. The algorithm reached overall overlap ratios of 62.6% +/- 9.1% and 61.0% +/- 11.3% in comparison to the two manual segmentation results, respectively. The overall overlap ratio between the two radiologists' manual segmentations was 64.3% +/- 10.4%. Preliminary results suggest that the proposed algorithm is a promising method for assisting in tumor volume measurement in contrast-enhanced breast MRI.

Mxenes Derived Laminated and Magnetic Composites with Excellent Microwave Absorbing Performance.

Two dimensional materials have been widely identified as promising microwave absorbers, owing to their large surface area and abundant interfaces. Here, a novel laminated and magnetic composite derived from Mxene was designed and successfully synthesized via facile hydrothermal oxidization of nickel ion intercalated Ti3C2. Highly disordered carbon sheets were obtained by low temperature hydrothermal oxidization, and the in-situ produced TiO2 and NiO nanoparticles embedded closely between them. This layered hybrid exhibits excellent microwave absorbing performance with an effective absorbing bandwidth as high as 11.1 GHz (6.9-18 GHz) and 9 GHz (9-18 GHz) when the thickness is 3 and 2 mm, respectively. Besides the high dielectric loss, magnetic loss and ohmic loss of the composite, the amorphous nature of obtained carbon sheets and multi-reflections between them are believed to play a decisive role in achieving such superior microwave absorbing performance.

Dependences of microstructure on electromagnetic interference shielding properties of nano-layered Ti3AlC2 ceramics.

The microstructure dependent electromagnetic interference (EMI) shielding properties of nano-layered Ti3AlC2 ceramics were presented in this study by comparing the shielding properties of various Ti3AlC2 ceramics with distinct microstructures. Results indicate that Ti3AlC2 ceramics with dense microstructure and coarse grains are more favourable for superior EMI shielding efficiency. High EMI shielding effectiveness over 40 dB at the whole Ku-band frequency range was achieved in Ti3AlC2 ceramics by microstructure optimization, and the high shielding effectiveness were well maintained up to 600 °C. A further investigation reveals that only the absorption loss displays variations upon modifying microstructure by allowing more extensive multiple reflections in coarse layered grains. Moreover, the absorption loss of Ti3AlC2 was found to be much higher than those of highly conductive TiC ceramics without layered structure. These results demonstrate that nano-layered MAX phase ceramics are promising candidates of high-temperature structural EMI shielding materials and provide insightful suggestions for achieving high EMI shielding efficiency in other ceramic-based shielding materials.

Lymph node segmentation by dynamic programming and active contours.

PURPOSE: Enlarged lymph nodes are indicators of cancer staging, and the change in their size is a reflection of treatment response. Automatic lymph node segmentation is challenging, as the boundary can be unclear and the surrounding structures complex. This work communicates a new three-dimensional algorithm for the segmentation of enlarged lymph nodes. METHODS: The algorithm requires a user to draw a region of interest (ROI) enclosing the lymph node. Rays are cast from the center of the ROI, and the intersections of the rays and the boundary of the lymph node form a triangle mesh. The intersection points are determined by dynamic programming. The triangle mesh initializes an active contour which evolves to low-energy boundary. Three radiologists independently delineated the contours of 54 lesions from 48 patients. Dice coefficient was used to evaluate the algorithm's performance. RESULTS: The mean Dice coefficient between computer and the majority vote results was 83.2%. The mean Dice coefficients between the three radiologists' manual segmentations were 84.6%, 86.2%, and 88.3%. CONCLUSIONS: The performance of this segmentation algorithm suggests its potential clinical value for quantifying enlarged lymph nodes.

Subgroup analysis reveals molecular heterogeneity and provides potential precise treatment for pancreatic cancers.

BACKGROUND: The relationship between molecular heterogeneity and clinical features of pancreatic cancer remains unclear. In this study, pancreatic cancer was divided into different subgroups to explore its specific molecular characteristics and potential therapeutic targets. PATIENTS AND METHODS: Expression profiling data were downloaded from The Cancer Genome Atlas database and standardized. Bioinformatics techniques such as unsupervised hierarchical clustering was used to explore the optimal molecular subgroups in pancreatic cancer. Clinical pathological features and pathways in each subgroup were also analyzed to find out the potential clinical applications and initial promotive mechanisms of pancreatic cancer. RESULTS: Pancreatic cancer was divided into three subgroups based on different gene expression features. Patients included in each subgroup had specific biological features and responded significantly different to chemotherapy. CONCLUSION: Three distinct subgroups of pancreatic cancer were identified, which means that patients in each subgroup might benefit from targeted individual management.

[VTK-based free multi-planar reformation].

This paper introduces the development of the Free-MPR module, based on VC++6.0 environment and VTK5.0, and on Windows XP platform. The Free-MPR module can adjust freely the display plane according to the change of the visual angle, and implement the free multi-planar reformation.

Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data.

PURPOSE: Radiomics utilizes a large number of image-derived features for quantifying tumor characteristics that can in turn be correlated with response and prognosis. Unfortunately, extraction and analysis of such image-based features is subject to measurement variability and bias. The challenge for radiomics is particularly acute in Positron Emission Tomography (PET) where limited resolution, a high noise component related to the limited stochastic nature of the raw data, and the wide variety of reconstruction options confound quantitative feature metrics. Extracted feature quality is also affected by tumor segmentation methods used to define regions over which to calculate features, making it challenging to produce consistent radiomics analysis results across multiple institutions that use different segmentation algorithms in their PET image analysis. Understanding each element contributing to these inconsistencies in quantitative image feature and metric generation is paramount for ultimate utilization of these methods in multi-institutional trials and clinical oncology decision making. METHODS: To assess segmentation quality and consistency at the multi-institutional level, we conducted a study of seven institutional members of the National Cancer Institute Quantitative Imaging Network. For the study, members were asked to segment a common set of phantom PET scans acquired over a range of imaging conditions as well as a second set of head and neck cancer (HNC) PET scans. Segmentations were generated at each institution using their preferred approach. In addition, participants were asked to repeat segmentations with a time interval between initial and repeat segmentation. This procedure resulted in overall 806 phantom insert and 641 lesion segmentations. Subsequently, the volume was computed from the segmentations and compared to the corresponding reference volume by means of statistical analysis. RESULTS: On the two test sets (phantom and HNC PET scans), the performance of the seven segmentation approaches was as follows. On the phantom test set, the mean relative volume errors ranged from 29.9 to 87.8% of the ground truth reference volumes, and the repeat difference for each institution ranged between -36.4 to 39.9%. On the HNC test set, the mean relative volume error ranged between -50.5 to 701.5%, and the repeat difference for each institution ranged between -37.7 to 31.5%. In addition, performance measures per phantom insert/lesion size categories are given in the paper. On phantom data, regression analysis resulted in coefficient of variation (CV) components of 42.5% for scanners, 26.8% for institutional approaches, 21.1% for repeated segmentations, 14.3% for relative contrasts, 5.3% for count statistics (acquisition times), and 0.0% for repeated scans. Analysis showed that the CV components for approaches and repeated segmentations were significantly larger on the HNC test set with increases by 112.7% and 102.4%, respectively. CONCLUSION: Analysis results underline the importance of PET scanner reconstruction harmonization and imaging protocol standardization for quantification of lesion volumes. In addition, to enable a distributed multi-site analysis of FDG PET images, harmonization of analysis approaches and operator training in combination with highly automated segmentation methods seems to be advisable. Future work will focus on quantifying the impact of segmentation variation on radiomics system performance.

Tailoring (n,m) structure of single-walled carbon nanotubes by modifying reaction conditions and the nature of the support of CoMo catalysts.

The (n,m) population distribution of single-walled carbon nanotubes obtained on supported CoMo catalysts has been determined by photoluminescence and optical absorption. It has been found that the (n,m) distribution can be controlled by varying the gaseous feed composition, the reaction temperature, and the type of catalyst support used. When using CO as a feed over CoMo/SiO2 catalysts, increasing the synthesis temperature results in an increase in nanotube diameter, without a change in the chiral angle. By contrast, by changing the support from SiO2 to MgO, nanotubes with similar diameter but different chiral angles are obtained. Finally, keeping the same reaction conditions but varying the composition of the gaseous feed results in different (n,m) distribution. The clearly different distributions obtained when varying catalysts support and/or reaction conditions demonstrate that the (n,m) distribution is a result of differences in the growth kinetics, which in turn depends on the nanotube cap-metal cluster interaction.