Source apportionment of microplastics in indoor dust: Two strategies based on shape and composition

Microplastic (MP) pollution is widely distributed in the environment. However, methods for source apportionment of MPs are still lacking. In this study, the shape and size of 102,860 MPs in indoor dust from 39 cities of China were analyzed by laser direct infrared, and accordingly, a shape index (fshape) based on MP's aspect ratio was developed to assess the contribution of textiles release. In addition, a composition index (fcomp) based on the ratio of the mass concentration of polyethylene terephthalate (PET) to polyamide (PA), which were detected by liquid chromatography-tandem mass spectrometry, was proposed. The contribution of textile source and non-textile source to the indoor MPs were also estimated based on fcomp. It is estimated by fshape that 43% of MPs in indoor dust was released from textiles. Among the most abundant MPs in indoor dust, 98% of polyurethane, 94% of PA and 92% of PET come from the textile source, 76% of polypropylene and almost all of polyethylene come from the non-textile source. fcomp indicates that 83% of PET MPs comes from textile source, i.e., polyester. Considering the application proportion of PET in textile and non-textile industry, it is estimated that 59% of MPs in indoor dust comes from textile source, which is similar to the result obtained by fshape.

Systematic cortical thickness and curvature patterns in primates

Humans are known to have significant and consistent differences in thickness throughout the cortex, with thick outer gyral folds and thin inner sulcal folds. Our previous work has suggested a mechanical basis for this thickness pattern, with the forces generated during cortical folding leading to thick gyri and thin sulci, and shown that cortical thickness varies along a gyral-sulcal spectrum in humans. While other primate species are expected to exhibit similar patterns of cortical thickness, it is currently unknown how these patterns scale across different sizes, forms, and foldedness. Among primates, brains vary enormously from roughly the size of a grape to the size of a grapefruit, and from nearly smooth to dramatically folded; of these, human brains are the largest and most folded. These variations in size and form make comparative neuroanatomy a rich resource for investigating common trends that transcend differences between species. In this study, we examine 12 primate species in order to cover a wide range of sizes and forms, and investigate the scaling of their cortical thickness relative to the surface geometry. The 12 species were selected due to the public availability of either reconstructed surfaces and/or population templates. After obtaining or reconstructing 3D surfaces from publicly available neuroimaging data, we used our surface-based computational pipeline (https://github.com/mholla/curveball) to analyze patterns of cortical thickness and folding with respect to size (total surface area), geometry (i.e. curvature, shape, and sulcal depth), and foldedness (gyrification). In all 12 species, we found consistent cortical thickness variations along a gyral-sulcal spectrum, with convex shapes thicker than concave shapes and saddle shapes in between. Furthermore, we saw an increasing thickness difference between gyri and sulci as brain size increases. Our results suggest a systematic folding mechanism relating local cortical thickness to geometry. Finally, all of our reconstructed surfaces and morphometry data are available for future research in comparative neuroanatomy.

A literature review of carpal tunnel syndrome and its association with body mass index, wrist ratio, wrist to palm ratio, and shape index

STUDY DESIGN

Systematic literature review of case-controlled studies.

INTRODUCTION

Carpal tunnel syndrome (CTS) is one of the most common tubular neuropathies where certain anatomical variations may be accounted for as risk factors for CTS, including body mass index (BMI), wrist ratio (WR), wrist to palm ratio (WPR), shape index (SI), and digit length.

PURPOSE OF THE STUDY

To assess case-control studies examining the association between specific anatomical variations of the wrist as risk factors for developing CTS and whether this effect is the same for both genders.

METHODS

The literature search was conducted between February-June 2020 through PubMed, Cochrane Library, CINAHL Plus and PEDro. The literature search yielded 149 potential publications, fifteen of which were filtered in accordance with eligibility criteria. The methodological quality was assessed by using the Newcastle-Ottawa Quality Assessment Form for Case-Control Studies (NOS).

RESULTS

The total number of subjects included in this review was n=4299. The largest sample was n=1117 participants and the smallest n=54. All studies included patients who had a clinical diagnosis of CTS confirmed with nerve conduction studies and or ultrasonography. CTS was significantly higher in patients with higher BMI, WR, WPR compared to control groups. BMI and WR were the only indicators that can be considered as strong risk factors.

CONCLUSIONS

Discussion: Despite the general patterns on the association of BMI, WPR, WR and SI as risk factors for the development of CTS, there were exceptions to the accepted results and conclusions.

CONCLUSION

Clinicians are recommended to conduct more research to confirm anthropometric measurements as risk factors for the development of CTS, mainly SI and WPR. When determining the cut-off values for BMI and WR, it is recommended to take into account additional risk factors such as occupation.

Modeling the role of land conversion on the spread of an epizootic disease

Land conversion and the resulting contact between domesticated and wild species has arguably been the single largest contributor to the emergence of novel epizootic and zoonotic diseases in the past century. An unintended consequence of these interactions is zoonotic or epizootic disease spillovers from wild species to humans and their domesticates. Disease spillovers are edge effects of land conversion and are sensitive to the size and shape of converted areas. We combine spatial metrics from landscape ecology with theoretical epidemiological models to understand how the size and shape of land conversion affect epizootic and zoonotic disease transmission of single and two species populations. We show that the less compact the converted area, and the greater the depth of the contact zone, the more rapidly will an introduced disease spread through the domesticated population.

Incremental value of left ventricular shape parameters measured by gated SPECT MPI in predicting the super-response to CRT

BACKGROUND

The purpose of this study was to evaluate the predictive value of left ventricular (LV) shape parameters measured by gated SPECT myocardial perfusion imaging (MPI) in super-responders enrolled in the VISION-CRT trial.

METHODS

One hundred and ninety-nine patients who met standard criteria for CRT from multiple centers were enrolled in this study. End-systolic eccentricity (ESE) and end-diastolic eccentricity (EDE) were measures of LV shape. Super-responders were the patients who had a relative increase in left ventricular ejection fraction (LVEF) ≥ 15%.

RESULTS

Complete data were obtained in 165 patients, and 43.6% of them were classified as super-responders. ESE was an independent predictor of CRT super-responders in univariate (OR 12.59, 95% CI 1.56-101.35, P = .017) and multivariate analysis (OR 35.71, 95% CI 1.66-766.03, P = .006). ESE had an incremental value over significant clinical and SPECT imaging variables, including angiotensin-converting enzyme inhibitors or angiotensin II receptor blocker, coronary artery disease, myocardial infarction, LVEF, end-diastolic volume index, and scar burden (AUC 0.82 vs. 0.80, sensitivity 0.68 vs. 0.65, specificity 0.82 vs. 0.78).

CONCLUSIONS

LV shape parameters derived from gated SPECT MPI have the promise to improve the prediction of the super-response to CRT. Moreover, ESE provides incremental value over existing clinical and nuclear imaging variables.

Behind Traditional Semi-quantitative Scores of Myocardial Perfusion Imaging: An Eye on Niche Parameters

The evaluation of stress-induced myocardial perfusion defects by non-invasive myocardial perfusion imaging (MPI) modalities has a leading role in the identification of coronary artery disease, and has excellent diagnostic and prognostic value. Non-invasive MPI can be performed using conventional and novel gamma cameras or by PET/CT. New software has allowed novel parameters that may have a role in the identification of early marks of cardiac impairment to be evaluated. We aim to give an overview of niche parameters obtainable by single photon emission CT (SPECT) and PET/CT MPI that may help practitioners to detect initial signs of cardiac damage and identify new therapy targets. In particular, we summarise the role of left ventricular geometry indices for remodelling, phase analysis parameters to evaluate mechanical dyssynchrony, the concept of relative flow reserve in the evaluation of flow-limiting epicardial stenosis, vascular age and epicardial adipose tissue as early markers of atherosclerotic burden, and emerging parameters for the evaluation of myocardial innervation, such as the total defect score.

Colloidal mobilization from soil and transport of uranium in (sub)-surface waters

An analytical methodology was developed to characterize the colloidal distribution of trace elements of interest in environmental waters sampled in a same site and enables the different colloidal distributions from waters to be compared. The purpose was to provide consistent information related to the origin and nature of colloids responsible for the transport of trace element(s). The work was motivated by the observed enhanced mobility of uranium in soil. The colloidal size continuum was investigated by a multi-technique approach involving asymmetric flow field-flow fractionation (AF4) coupled with ultraviolet spectroscopy (UV), multi angle light scattering (MALS), and atomic mass spectrometry (ICPMS). To take into consideration the size and shape variability specific to each sample, the size distributions were established from the gyration radii measured from MALS, also considering the size information from standard nanospheres fractionated by AF4. A new parameter called "shape index" was proposed. It expresses the difference in hydrodynamic behavior between analytes and spherical particles taken as reference. Under AF4 diffusion conditions, it can be considered as an evaluator of the deviation from the sphericity of the fractionated analytes. AF4-UV-MALS-ICPMS enabled the dimensional and chemical characteristics of the colloidal size continuum to be obtained. As a "proof of concept", the developed methodology was applied at a field scale, in a reference study site. In order to have a "dynamic understanding", the investigation was based on the joint characterization of colloids from surface waters and soil leachates from static and dynamic processes. In the water samples of the study site, the continuum of gyration radius ranged from a few nanometers up to 200 nm. Colloids containing iron, aluminum, and organic carbon were involved in the uranium transport in the soil column and surface waters. The colloidal uranium concentration in the surface water increased from the upstream location (approximately 13 ng (U) L^-1) to the downstream location (approximately 60 ng (U) L^-1).

Photometric stereo for three-dimensional leaf venation extraction

Leaf venation extraction studies have been strongly discouraged by considerable challenges posed by venation architectures that are complex, diverse and subtle. Additionally, unpredictable local leaf curvatures, undesirable ambient illuminations, and abnormal conditions of leaves may coexist with other complications. While leaf venation extraction has high potential for assisting with plant phenotyping, speciation and modelling, its investigations to date have been confined to colour image acquisition and processing which are commonly confounded by the aforementioned biotic and abiotic variations. To bridge the gaps in this area, we have designed a 3D imaging system for leaf venation extraction, which can overcome dark or bright ambient illumination and can allow for 3D data reconstruction in high resolution. We further propose a novel leaf venation extraction algorithm that can obtain illumination-independent surface normal features by performing Photometric Stereo reconstruction as well as local shape measures by fusing the decoupled shape index and curvedness features. In addition, this algorithm can determine venation polarity - whether veins are raised above or recessed into a leaf. Tests on both sides of different leaf species with varied venation architectures show that the proposed method is accurate in extracting the primary, secondary and even tertiary veins. It also proves to be robust against leaf diseases which can cause dramatic changes in colour. The effectiveness of this algorithm in determining venation polarity is verified by it correctly recognising raised or recessed veins in nine different experiments.

Automatic detection of pulmonary nodules in CT images by incorporating 3D tensor filtering with local image feature analysis

Computer-aided detection (CAD) technology has been developed and demonstrated its potential to assist radiologists in detecting pulmonary nodules especially at an early stage. In this paper, we present a novel scheme for automatic detection of pulmonary nodules in CT images based on a 3D tensor filtering algorithm and local image feature analysis. We first apply a series of preprocessing steps to segment the lung volume and generate the isotropic volumetric CT data. Next, a unique 3D tensor filtering approach and local image feature analysis are used to detect nodule candidates. A 3D level set segmentation method is used to correct and refine the boundaries of nodule candidates subsequently. Then, we extract the features of the detected candidates and select the optimal features by using a CFS (Correlation Feature Selection) subset evaluator attribute selection method. Finally, a random forest classifier is trained to classify the detected candidates. The performance of this CAD scheme is validated using two datasets namely, the LUNA16 (Lung Nodule Analysis 2016) database and the ANODE09 (Automatic Nodule Detection 2009) database. By applying a 10-fold cross-validation method, the CAD scheme yielded a sensitivity of 79.3% at an average of 4 false positive detections per scan (FP/Scan) for the former dataset, and a sensitivity of 84.62% and 2.8 FP/Scan for the latter dataset, respectively. Our detection results show that the use of 3D tensor filtering algorithm combined with local image feature analysis constitutes an effective approach to detect pulmonary nodules.

Development of cortical shape in the human brain from 6 to 24months of age via a novel measure of shape complexity

The quantification of local surface morphology in the human cortex is important for examining population differences as well as developmental changes in neurodegenerative or neurodevelopmental disorders. We propose a novel cortical shape measure, referred to as the 'shape complexity index' (SCI), that represents localized shape complexity as the difference between the observed distributions of local surface topology, as quantified by the shape index (SI) measure, to its best fitting simple topological model within a given neighborhood. We apply a relatively small, adaptive geodesic kernel to calculate the SCI. Due to the small size of the kernel, the proposed SCI measure captures fine differences of cortical shape. With this novel cortical feature, we aim to capture comparatively small local surface changes that capture a) the widening versus deepening of sulcal and gyral regions, as well as b) the emergence and development of secondary and tertiary sulci. Current cortical shape measures, such as the gyrification index (GI) or intrinsic curvature measures, investigate the cortical surface at a different scale and are less well suited to capture these particular cortical surface changes. In our experiments, the proposed SCI demonstrates higher complexity in the gyral/sulcal wall regions, lower complexity in wider gyral ridges and lowest complexity in wider sulcal fundus regions. In early postnatal brain development, our experiments show that SCI reveals a pattern of increased cortical shape complexity with age, as well as sexual dimorphisms in the insula, middle cingulate, parieto-occipital sulcal and Broca's regions. Overall, sex differences were greatest at 6months of age and were reduced at 24months, with the difference pattern switching from higher complexity in males at 6months to higher complexity in females at 24months. This is the first study of longitudinal, cortical complexity maturation and sex differences, in the early postnatal period from 6 to 24months of age with fine scale, cortical shape measures. These results provide information that complement previous studies of gyrification index in early brain development.

Three-dimensional protein model similarity analysis based on salient shape index

Background

Proteins play a special role in bioinformatics. The surface shape of a protein, which is an important characteristic of the protein, defines a geometric and biochemical domain where the protein interacts with other proteins. The similarity analysis among protein models has become an important topic of protein analysis, by which it can reveal the structure and the function of proteins.

Results

In this paper, a new protein similarity analysis method based on three-dimensional protein models is proposed. It constructs a feature matrix descriptor for each protein model combined by calculating the shape index (SI) and the related salient geometric feature (SGF), and then analyzes the protein model similarity by using this feature matrix and the extended grey relation analysis.

Conclusions

We compare our method to the Multi-resolution Reeb Graph (MRG) skeleton method, the L1-medial skeleton method and the local-diameter descriptor method. Experimental results show that our protein similarity analysis method is accurate and reliable while keeping the high computational efficiency.

Refinement of lung nodule candidates based on local geometric shape analysis and Laplacian of Gaussian kernels

This work is focused on application of a new technique in the first steps of computer-aided detection (CAD) of lung nodules. The scheme includes segmenting the lung volume and detecting most of the nodules with a low number of false positive (FP) objects. The juxtapleural nodules were properly included and the airways excluded in the lung segmentation. Among the suspicious regions obtained from the multiscale dot enhancement filter, those containing the center of nodule candidates, were determined. These center points were achieved from a 3D blob detector based on Laplacian of Gaussian kernels. Then the volumetric shape index (SI) that encodes the 3D local shape information was calculated for voxels in the determined regions. The performance of the scheme was evaluated by using 42 CT images from the Lung Image Database Consortium (LIDC). The results show that the average number of FPs reaches to 38.8 per scan with the sensitivity of 95.9% in the initial detections. The scheme is adaptable to detect nodules with wide variations in size, shape, intensity and location. Comparison of results with previously reported ones indicates that the proposed scheme can be satisfactory applied for initial detection of lung nodules in the chest CT images.