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Body segment parameters are inputs for a range of applications. Participant-specific estimates of body segment parameters are desirable as this requires fewer prior assumptions and can reduce outcome measurement errors. Commonly used methods for estimating participant-specific body segment parameters are either expensive and out of reach (medical imaging), have many underlying assumptions (geometrical modelling) or are based on a specific subset of a population (regression models). Our objective was to develop a participant-specific 3D scanning and body segmentation method that estimates body segment parameters without any assumptions about the geometry of the body, ethnic background, and gender, is low-cost, fast, and can be readily available. Using a Microsoft Kinect Version 2 camera, we developed a 3D surface scanning protocol that enabled the estimation of participant-specific body segment parameters. To evaluate our system, we performed repeated 3D scans of 21 healthy participants (10 male, 11 female). We used open source tools to segment each body scan into 16 segments (head, torso, abdomen, pelvis, left and right hand, forearm, upper arm, foot, shank and thigh) and wrote custom software to estimate each segment's mass, mass moment of inertia in the three principal orthogonal axes relevant to the center of the segment, longitudinal length, and center of mass. We compared our body segment parameter estimates to those obtained using two comparison methods and found that our system was consistent in estimating total body volume between repeated scans (male p = 0.1194, female p = 0.2240), estimated total body mass without significant differences when compared to our comparison method and a medical scale (male p = 0.8529, female p = 0.6339), and generated consistent and comparable estimates across a range of the body segment parameters of interest. Our work here outlines and provides the code for an inexpensive 3D surface scanning method for estimating a range of participant-specific body segment parameters.
Radiative communication using electro-magnetic (EM) fields amongst the wearable and implantable devices act as the backbone for information exchange around a human body, thereby enabling prime applications in the fields of connected healthcare, electroceuticals, neuroscience, augmented and virtual reality. However, owing to such radiative nature of the traditional wireless communication, EM signals propagate in all directions, inadvertently allowing an eavesdropper to intercept the information. In this context, the human body, primarily due to its high water content, has emerged as a medium for low-loss transmission, termed human body communication (HBC), enabling energy-efficient means for wearable communication. However, conventional HBC implementations suffer from significant radiation which also compromises security. In this article, we present Electro-Quasistatic Human Body Communication (EQS-HBC), a method for localizing signals within the body using low-frequency carrier-less (broadband) transmission, thereby making it extremely difficult for a nearby eavesdropper to intercept critical private data, thus producing a covert communication channel, i.e. the human body. This work, for the first time, demonstrates and analyzes the improvement in private space enabled by EQS-HBC. Detailed experiments, supported by theoretical modeling and analysis, reveal that the quasi-static (QS) leakage due to the on-body EQS-HBC transmitter-human body interface is detectable up to <0.15 m, whereas the human body alone leaks only up to ~0.01 m, compared to >5 m detection range for on-body EM wireless communication, highlighting the underlying advantage of EQS-HBC to enable covert communication.
The human cytomegalovirus (HCMV) UL35 gene encodes two proteins, UL35 and UL35a. Expression of UL35 in transfected cells results in the formation of UL35 nuclear bodies that associate with promyelocytic leukemia (PML) protein. PML forms the basis for PML nuclear bodies that are important for suppressing viral lytic gene expression. Given the important relationship between PML and viral infection, we have further investigated the association of UL35 with PML bodies. We demonstrate that UL35 bodies form independently of PML and subsequently recruit PML, Sp100 and Daxx. In contrast, UL35a did not form bodies; however, it could bind UL35 and inhibit the formation of UL35 bodies. The HCMV tegument protein pp71 promoted the formation of UL35 bodies and the cytoplasmic localization of UL35a. Similarly, UL35a shifted pp71 to the cytoplasm. These results indicate that the interplay between UL35, UL35a and pp71 affects their subcellular localization and likely their functions throughout infection.
The ciliary body is the circumferential muscular tissue located just behind the iris in the anterior chamber of the eye. It plays a pivotal role in the production of aqueous humor, maintenance of the lens zonules and accommodation by changing the shape of the crystalline lens. The ciliary body is the major target of drugs against glaucoma as its inhibition leads to a drop in intraocular pressure. A molecular study of the ciliary body could provide a better understanding about the pathophysiological processes that occur in glaucoma. Thus far, no large-scale proteomic investigation has been reported for the human ciliary body.
The cytoarchitectonic map as proposed by Brodmann currently dominates models of human sensorimotor cortical structure, function, and plasticity. According to this model, primary motor cortex, area 4, and primary somatosensory cortex, area 3b, are homogenous areas, with the major division lying between the two. Accumulating empirical and theoretical evidence, however, has begun to question the validity of the Brodmann map for various cortical areas. Here, we combined in vivo cortical myelin mapping with functional connectivity analyses and topographic mapping techniques to reassess the validity of the Brodmann map in human primary sensorimotor cortex. We provide empirical evidence that area 4 and area 3b are not homogenous, but are subdivided into distinct cortical fields, each representing a major body part (the hand and the face). Myelin reductions at the hand-face borders are cortical layer-specific, and coincide with intrinsic functional connectivity borders as defined using large-scale resting state analyses. Our data extend the Brodmann model in human sensorimotor cortex and suggest that body parts are an important organizing principle, similar to the distinction between sensory and motor processing.
Genes are typically assumed to express both parental alleles similarly, yet cell lines show random allelic expression (RAE) for many autosomal genes that could shape genetic effects. Thus, understanding RAE in human tissues could improve our understanding of phenotypic variation. Here, we develop a methodology to perform genome-wide profiling of RAE and biallelic expression in GTEx datasets for 832 people and 54 tissues. We report 2,762 autosomal genes with some RAE properties similar to randomly inactivated X-linked genes. We found that RAE is associated with rapidly evolving regions in the human genome, adaptive signaling processes, and genes linked to age-related diseases such as neurodegeneration and cancer. We define putative mechanistic subtypes of RAE distinguished by gene overlaps on sense and antisense DNA strands, aggregation in clusters near telomeres, and increased regulatory complexity and inputs compared with biallelic genes. We provide foundations to study RAE in human phenotypes, evolution, and disease.
Humans recognize body parts in categories. Previous studies have shown that responses in the fusiform body area (FBA) and extrastriate body area (EBA) are evoked by the perception of the human body, when presented either as whole or as isolated parts. These responses occur approximately 190 ms after body images are visualized. The extent to which body-sensitive responses show specificity for different body part categories remains to be largely clarified. We used a decoding method to quantify neural responses associated with the perception of different categories of body parts. Nine subjects underwent measurements of their brain activities by magnetoencephalography (MEG) while viewing 14 images of feet, hands, mouths, and objects. We decoded categories of the presented images from the MEG signals using a support vector machine (SVM) and calculated their accuracy by 10-fold cross-validation. For each subject, a response that appeared to be a body-sensitive response was observed and the MEG signals corresponding to the three types of body categories were classified based on the signals in the occipitotemporal cortex. The accuracy in decoding body-part categories (with a peak at approximately 48%) was above chance (33.3%) and significantly higher than that for random categories. According to the time course and location, the responses are suggested to be body-sensitive and to include information regarding the body-part category. Finally, this non-invasive method can decode category information of a visual object with high temporal and spatial resolution and this result may have a significant impact in the field of brain-machine interface research.
The retrosplenial complex (RSC) plays a crucial role in spatial orientation by computing heading direction and translating between distinct spatial reference frames based on multi-sensory information. While invasive studies allow investigating heading computation in moving animals, established non-invasive analyses of human brain dynamics are restricted to stationary setups. To investigate the role of the RSC in heading computation of actively moving humans, we used a Mobile Brain/Body Imaging approach synchronizing electroencephalography with motion capture and virtual reality. Data from physically rotating participants were contrasted with rotations based only on visual flow. During physical rotation, varying rotation velocities were accompanied by pronounced wide frequency band synchronization in RSC, the parietal and occipital cortices. In contrast, the visual flow rotation condition was associated with pronounced alpha band desynchronization, replicating previous findings in desktop navigation studies, and notably absent during physical rotation. These results suggest an involvement of the human RSC in heading computation based on visual, vestibular, and proprioceptive input and implicate revisiting traditional findings of alpha desynchronization in areas of the navigation network during spatial orientation in movement-restricted participants.
Uranium oxide microparticles ingestion is one of the potential sources of internal radiation doses to the humans at accidental or undesirable releases of radioactive materials. It is important to predict the obtained dose and possible biological effect of these microparticles by studying uranium oxides transformations in case of their ingestion or inhalation. Using a combination of methods, a complex examination of structural changes of uranium oxides in the range from UO2 to U4O9, U3O8 and UO3 as well as before and after exposure of uranium oxides in simulated biological fluids: gastro-intestinal and lung-was carried out. Oxides were thoroughly characterized by Raman and XAFS spectroscopy. It was determined that the duration of expose has more influence on all oxides transformations. The greatest changes occurred in U4O9, that transformed into U4O9-y. UO2.05 and U3O8 structures became more ordered and UO3 did not undergo significant transformation.
The ganglion cardiacum or juxtaductal body is situated along the left recurrent laryngeal nerve in the aortic window and is an extremely large component of the cardiac nerve plexus. This study was performed to describe the morphologies of the ganglion cardiacum or juxtaductal body in human fetuses and to compare characteristics with intracardiac ganglion. Ganglia were immunostained in specimens from five fetuses of gestational age 12-16 weeks and seven fetuses of gestational age 28-34 weeks. Many ganglion cells in the ganglia were positive for tyrosine hydroxylase (TH; sympathetic nerve marker) and chromogranin A, while a few neurons were positive for neuronal nitric oxide synthase (NOS; parasympathetic nerve marker) or calretinin. Another ganglion at the base of the ascending aorta carried almost the same neuronal populations, whereas a ganglion along the left common cardinal vein contained neurons positive for chromogranin A and NOS but no or few TH-positive neurons, suggesting a site-dependent difference in composite neurons. Mixtures of sympathetic and parasympathetic neurons within a single ganglion are consistent with the morphology of the cranial base and pelvic ganglia. Most of the intracardiac neurons are likely to have a non-adrenergic non-cholinergic phenotype, whereas fewer neurons have a dual cholinergic/noradrenergic phenotype. However, there was no evidence showing that chromogranin A- and/or calretinin-positive cardiac neurons corresponded to these specific phenotypes. The present study suggested that the ganglion cardiacum was composed of a mixture of sympathetic and parasympathetic neurons, which were characterized the site-dependent differences in and near the heart.
Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.
Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from over 12,000 genes across 32 normal human tissues. Tissue-specific or tissue-enriched proteins were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode tissue-specific proteins. Discordance of RNA and protein enrichment revealed potential sites of synthesis and action of secreted proteins. The tissue-specific distribution of proteins also provides an in-depth view of complex biological events that require the interplay of multiple tissues. Most importantly, our study demonstrated that protein tissue-enrichment information can explain phenotypes of genetic diseases, which cannot be obtained by transcript information alone. Overall, our results demonstrate how understanding protein levels can provide insights into regulation, secretome, metabolism, and human diseases.
Transformative technologies are enabling the construction of three-dimensional maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible three-dimensional molecular and cellular atlas of the human body, in health and under various disease conditions.
Characterizing the biogeography of the microbiome of healthy humans is essential for understanding microbial associated diseases. Previous studies mainly focused on a single body habitat from a limited set of subjects. Here, we analyzed one of the largest microbiome datasets to date and generated a biogeographical map that annotates the biodiversity, spatial relationships, and temporal stability of 22 habitats from 279 healthy humans.
Space heating accounts for the largest energy end-use of buildings that imposes significant burden on the society. The energy wasted for heating the empty space of the entire building can be saved by passively heating the immediate environment around the human body. Here, we demonstrate a nanophotonic structure textile with tailored infrared (IR) property for passive personal heating using nanoporous metallized polyethylene. By constructing an IR-reflective layer on an IR-transparent layer with embedded nanopores, the nanoporous metallized polyethylene textile achieves a minimal IR emissivity (10.1%) on the outer surface that effectively suppresses heat radiation loss without sacrificing wearing comfort. This enables 7.1 °C decrease of the set-point compared to normal textile, greatly outperforming other radiative heating textiles by more than 3 °C. This large set-point expansion can save more than 35% of building heating energy in a cost-effective way, and ultimately contribute to the relief of global energy and climate issues.Energy wasted for heating the empty space of the entire building can be saved by passively heating the immediate environment around the human body. Here, the authors show a nanophotonic structure textile with tailored infrared property for passive personal heating using nanoporous metallized polyethylene.
Normal human body temperature (BT) has long been considered to be 37.0°C. Yet, BTs have declined over the past two centuries in the United States, coinciding with reductions in infection and increasing life expectancy. The generality of and reasons behind this phenomenon have not yet been well studied. Here, we show that Bolivian forager-farmers (n = 17,958 observations of 5481 adults age 15+ years) inhabiting a pathogen-rich environment exhibited higher BT when first examined in the early 21st century (~37.0°C). BT subsequently declined by ~0.05°C/year over 16 years of socioeconomic and epidemiological change to ~36.5°C by 2018. As predicted, infections and other lifestyle factors explain variation in BT, but these factors do not account for the temporal declines. Changes in physical activity, body composition, antibiotic usage, and thermal environment are potential causes of the temporal decline.
Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery. Database URL: https://bmbl.bmi.osumc.edu/HBFP/.
Many pathophysiological mechanisms in human health and disease are dependent on sex. Systems biology approaches are successfully used to decipher human disease etiology, yet the effect of sex on gene network biology is mostly unknown. To address this, we used RNA-sequencing data of over 700 individuals spanning 24 tissues from the Genotype-Tissue Expression project to generate a whole-body gene co-expression map and quantified the sex differences per tissue. We found that of the 13,787 genes analyzed in 24 tissues, 29.5% of the gene co-expression is influenced by sex. For example, skeletal muscle was predominantly enriched with genes co-expressed stronger in males, whereas thyroid primarily contained genes co-expressed stronger in females. This was accompanied by consistent sex differences in pathway enrichment, including hypoxia, epithelial-to-mesenchymal transition, and inflammation over the human body. Furthermore, multi-organ analyses revealed consistent sex-dependent gene co-expression over numerous tissues which was accompanied by enrichment of transcription factor binding motifs in the promoters of these genes. Finally, we show that many sex-biased genes are associated with sex-biased diseases, such as autoimmunity and cancer, and more often the target of FDA-approved drugs than non-sexbiased genes. Our study suggests that sex affects biological gene networks by differences in gene co-expression and that attention to the effect of sex on biological responses to medical drugs is warranted.
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