Variations In Tissue Composition Research Articles

Comprehensive Postnatal Anatomical, Histological and Geometric Morphometric Analysis of Thymus Development in Dromedary Camels (Camelus dromedarius).

The thymus, a primary lymphoid organ, plays a critical role in T lymphocyte development and adaptive immunity. This study focuses on the anatomical, histological and geometric morphometric characteristics of the thymus in dromedary camels (Camelus dromedarius) during postnatal development. Thymus samples were collected from camels aged approximately 4, 8, 12 and 16 months. Using photogrammetry and 3D modelling, the samples were analysed to generate landmarks and conduct geometric morphometry with the 3D Slicer and ALPACA algorithm. Principal component analysis (PCA) was then performed to evaluate shape variations. Histologically, the samples underwent Haematoxylin and Eosin and Masson's trichrome staining. Image analysis using QuPath software quantified trabeculae, adipose tissue and Hassall's corpuscles. The results revealed significant anatomical and histological changes in the thymus across the different age groups. Notable variations in tissue composition and structural integrity were observed, with the PCA highlighting distinct morphometric patterns associated with age-related development. These findings provide a deeper understanding of thymus maturation in dromedaries and offer valuable data for comparative anatomy and veterinary medicine. This comprehensive analysis enhances our knowledge of species-specific immune development, with important implications for the health and resilience of these animals in arid environments.

Commercial maize hybrids have smaller root systems after 80 Years of breeding

Roots have gained attention for their role in improving plant function in high-stress environments and providing ecosystem services such as soil organic carbon storage. An important step in breeding for enhanced root phenotypes is understanding how root traits have changed historically due to selection for yield and other aboveground traits. However, among the few era panel studies focused on roots, there are conflicting findings about how breeding has altered traits such as root system length and biomass, while other traits such as root depth distribution, root size class distribution, and tissue quality remain largely unexplored. Our aim was to assess breeding-driven changes in root traits that are relevant to resource acquisition and soil carbon sequestration. We grew twelve maize (Zea mays L.) hybrids from the Corteva/Pioneer ERA panel, spanning from 1936 to 2014, in 1.5 m deep mesocosms. At the eight-leaf stage, intact root systems were imaged and analyzed using a custom root phenotyping platform, and roots and shoots were subjected to carbon and nitrogen analysis and Diffuse Reflectance FTIR to assess variation in tissue composition. We found that the newest hybrids produced 40% less root biomass and 36% less root length than the oldest hybrids, with declines of 0.024 g year−1 (s.e.: 0.005, p < 0.01) and 0.86 m year−1 (s.e.: 0.23, p < 0.01) with no changes in maximum rooting depth, which averaged 113 cm (±5.62). , and no directional shifts in chemical composition. We also found a decline in the root-to-shoot ratio from 0.58 g g−1 to 0.46 g g−1 (s.e.: 0.0006, p < 0.05). Our results suggest that selection for yield has indirectly decreased root system size over 80 years of maize breeding. Smaller root systems of modern hybrids may contribute to the higher optimum plant populations and higher yields of modern maize hybrids.

Prediction of proton stopping power ratios using dual-energy CT basis material decomposition.

Proton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single-energy computed tomography (SECT). Various studies have shown that multi-energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age-related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection-based MECT systems for SPR prediction. To present and evaluate a novel proton SPR prediction method based on MD images from dual-energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy. A theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non-tissue materials, by minimizing the root-mean-square relative attenuation error in the energy interval from 40 to 140keV. A model (here called MD-SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data-fitting. The goodness of fit of the MD-SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head- and an abdomen-sized phantom setup, were acquired with a clinical projection-based fast-kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non-tissue materials in the phantoms, as well as used for input to the MD-SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image-based consecutive scan DECT for the same phantom setups. The predicted SPRs of the tissue surrogates were similar for MD-SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non-adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between -0.7% and -1.8%. The SPRs of the non-tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD-SPR images, compared to 6.8% for DirectSPR. The MD-SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non-tissue materials.

Targeted spectroscopy in the eye fundus.

The assessment of biomarkers in the eye is rapidly gaining traction for the screening, diagnosis, and monitoring of ocular and neurological diseases. Targeted ocular spectroscopy is a technology that enables concurrent imaging of the eye fundus and analysis of high-quality spectra from a targeted region within the imaged area. This provides structural, compositional, and functional information of specific regions of the eye fundus from a non-invasive approach to ocular biomarker detection. The aim of our study was to demonstrate the multimodal functionality and validation of targeted ocular spectroscopy. This was done in vitro, using a reference target and a model eye, and in vivo. Images and spectra from different regions of a reference target and a model eye were acquired and analyzed to validate the system. Targeted ocular fluorescence spectroscopy was also demonstrated with the same model. Subsequently, in vivo imaging and diffuse reflectance spectra were acquired to assess blood oxygen saturation in the optic nerve head and the parafovea of healthy subjects. Tests conducted with the reference target showed accurate spectral analysis within specific areas of the imaging space. In the model eye, distinct spectral signatures were observed for the optic disc, blood vessels, the retina, and the macula, consistent with the variations in tissue composition and functions between these regions. An ocular oximetry algorithm was applied to in vivo spectra from the optic nerve head and parafovea of healthy patients, showing significant differences in blood oxygen saturation. Finally, targeted fluorescence spectral analysis was performed in vitro. Diffuse reflectance and fluorescence spectroscopy in specific regions of the eye fundus open the door to a whole new range of monitoring and diagnostic capabilities, from assessment of oxygenation in glaucoma and diabetic retinopathy to photo-oxidation and photodegradation in age-related macular degeneration.

Repeated subsamples during DNA extraction reveal increased diversity estimates in DNA metabarcoding of Malaise traps.

With increased application of DNA metabarcoding in biodiversity assessment, various laboratory protocols have been optimized, and their further evaluation is subject of current research. Homogenization of bulk samples and subsequent DNA extraction from a subsample of destructed tissue is a common first stage of the metabarcoding process. This can either be conducted using sample material soaked in a storage fixative, e.g., ethanol (here referred to as "wet" treatment) or from dried individuals ("dry"). However, it remains uncertain if perfect mixing and equal distribution of DNA within the tube is ensured during homogenization and to what extent incomplete mixing and resulting variations in tissue composition affect diversity assessments if only a fraction of the destructed sample is processed in the downstream metabarcoding workflow. Here we investigated the efficiency of homogenization under wet and dry conditions and tested how variations in destructed tissue composition might affect diversity assessments of complex arthropod samples. We considered five time intervals of Malaise trap bulk samples and process nine different subsamples of homogenized tissue (20 mg each) in both treatments. Results indicate a more consistent diversity assessment from dried material, but at the cost of a higher processing time. Both approaches detected comparable OTU diversity and revealed similar taxa compositions in a single tissue extraction. With an increased number of tissue subsamples during DNA extraction, OTU diversity increased for both approaches, especially for highly diverse samples obtained during the summer. Here, particularly the detection of small and low-biomass taxa increased. The processing of multiple subsamples in the metabarcoding protocol can therefore be a helpful procedure to enhance diversity estimates and counteract taxonomic bias in biodiversity assessments. However, the process induces higher costs and time effort and the application in large-scale biodiversity assessment, e.g., in monitoring schemes needs to be considered on project-specific prospects.

Regional variations of in vivo surface stiffness of soft tissue layers of musculoskeletal extremities

Surface stiffness of bulk soft tissue in musculoskeletal extremities is important to consider in the design of prosthetics, exoskeletons, and protective gear. This knowledge is also foundational for surgical simulation and clinical interventions leveraging manipulation of the musculoskeletal surfaces. Injuries to musculoskeletal extremities are common and surgical and preventive interventions require interactions between various objects such as surgical tools and support surfaces with tissue boundaries. While a handful of investigations examined the variations in indentation mechanics due to pathology or injury specific sites, a comprehensive analysis across the surfaces of musculoskeletal extremities has not been completed. In this study we examine variations of surface stiffness across 8 sites of the upper and lower arms and legs for 95 subjects using an instrumented ultrasound device. Differences in surface stiffness were observed between gender, activity level, and indentation location groups. The lower arm posterior location had the highest average stiffness (3.89 × 10−3 MPa/mm), while the lowest stiffness was observed at the upper leg posterior location (0.98 × 10−3 MPa/mm). The differences between indentation sites were larger in magnitude when compared to differences due to demographics (gender and activity level). However the large ranges of the 95% confidence intervals suggest that an aggregated metric based on population or sub-group may not capture individual variations. This study implicates the motivation to explore tissue composition variations within the indentation sites as well as the potential importance to include variations in surface stiffness during surgical simulations.

Effect of dietary clove basil, Ocimum gratissimum, leaves extract on healing of artificially wounded African catfish, Clarias gariepinus (B.), juveniles

ABSTRACT African catfish, Clarias gariepinus (B.), may be wounded naturally due to cannibalism, high density, and/or any other action. These wounds may be a precursor to further pathogen infection, causing health deterioration and economical loss if not well treated. Hence, the wound-healing capability of clove basil (Ocimum gratissimum) leaves extract (CBLE) on African catfish was investigated. A basal diet containing 40% crude protein was formulated and enriched with CBLE levels of 0.0, 5, 10, and 15 g/kg diet. Fish (54.20 ± 1.12 g) were lacerated (1 cm long) in the caudal and lateral regions. After that fish were fed one of the tested diets in a complete randomized design for 14 days, during which wound closures and histological changes were observed. Fish fed CBLE-enriched diets had faster wound-healing percentages and daily healing rates over those fed the control diet. Fish fed lower CBLE levels needed more time to achieve complete wound healing; meanwhile fish fed the 15 g/kg diet showed a complete wound healing (100%) on the 10th and 8th day postwound (dpw) in both lateral and caudal regions respectively. Wound healing in caudal and lateral regions of CBLE-fed fish in response to time period was related to the accumulation of bioactive compounds in fish, which enhanced their antioxidant and immunity. On the 14th dpw, the least healing percentage (88.09%) was recorded in the lateral and caudal regions in fish fed the control diet. On the other hand, the dermal wound in the caudal region healed faster than that in the lateral one; this was because of the variation in tissue composition and texture in both regions.

Canine insulinomas appear hyperintense on MRI T2-weighted images and isointense on T1-weighted images.

Clinical and imaging diagnosis of canine insulinomas has proven difficult due to nonspecific clinical signs and the small size of these tumors. The aim of this retrospective case series study was to describe MRI findings in a group of dogs with pancreatic insulinomas. Included dogs were presented for suspected pancreatic insulinoma, MRI was used to assist with localization of the primary lesion, and the diagnosis was confirmed with surgical exploratory laparotomy and histopathology. The MRI studies for each dog were retrieved and the following data were recorded: T1-weighted and T2-weighted signal intensities, type of contrast enhancement, size and location of the primary lesion, and characteristics of metastatic lesions (if present). A total of four dogs were sampled. In all patients, the insulinoma displayed high-intensity signal on T2-weighted fat saturation images, similar to human studies. On postcontrast T1-weighted fat saturation images, the tumors were primarily isointense to normal pancreatic tissue, in contrast to human studies where a low-intensity signal is typically identified. Abnormal islet tissue was detected with MRI in all four dogs and metastases were identified in three dogs. Variations in the MRI appearance of primary and metastatic lesions were identified and could have been related to the variation of tissue composition, including the presence of neoplastic cells, hemorrhage, and fibrovascular stroma, and to the transformation of this tissue throughout the disease process.

Quantifying the ultrastructure of carotid arteries using high-resolution micro-diffusion tensor imaging—comparison of intact versus open cut tissue

Diffusion magnetic resonance imaging (dMRI) can provide insights into the microstructure of intact arterial tissue. The current study employed high magnetic field MRI to obtain ultra-high resolution dMRI at an isotropic voxel resolution of 117 µm3 in less than 2 h of scan time. A parameter selective single shell (128 directions) diffusion-encoding scheme based on Stejskel-Tanner sequence with echo-planar imaging (EPI) readout was used. EPI segmentation was used to reduce the echo time (TE) and to minimise the susceptibility-induced artefacts. The study utilised the dMRI analysis with diffusion tensor imaging (DTI) framework to investigate structural heterogeneity in intact arterial tissue and to quantify variations in tissue composition when the tissue is cut open and flattened. For intact arterial samples, the region of interest base comparison showed significant differences in fractional anisotropy and mean diffusivity across the media layer (p < 0.05). For open cut flat samples, DTI based directionally invariant indices did not show significant differences across the media layer. For intact samples, fibre tractography based indices such as calculated helical angle and fibre dispersion showed near circumferential alignment and a high degree of fibre dispersion, respectively. This study demonstrates the feasibility of fast dMRI acquisition with ultra-high spatial and angular resolution at 7 T. Using the optimised sequence parameters, this study shows that DTI based markers are sensitive to local structural changes in intact arterial tissue samples and these markers may have clinical relevance in the diagnosis of atherosclerosis and aneurysm.

Abstract ID: 113 Accurate extraction of tissues parameters for Monte Carlo simulations using multi-energy CT

Purpose Robust tissue characterization is essential for accurate dose calculation [1] , [2] . In this work, we present a novel method called Bayesian eigentissue decomposition (BETD) [3] to extract Monte Carlo inputs from computed tomography (CT) data having an arbitrary number of energies. Method Principal component analysis is applied on a reference dataset of human tissues to define eigentissues which are used as an optimal base of materials representing tissue compositions. To ensure robustness against CT noise, the Bayesian estimator is constructed and resolves the maximum a posteriori fraction of eigentissues in each voxel. The performance of the method in deriving proton beam interaction properties is evaluated with dual-energy CT (DECT) data and compared to a state-of-the-art elemental composition parameterization. Comparison is made with several levels of noise and in the presence of statistical variations in tissue composition and density. The performance of the BETD to an arbitrary number of energies is also investigated by simulating CT data with two to five energy bins with equivalent noise levels. Results Using simulated noise-free CT numbers for 43 reference soft tissues, the BETD and parameterization methods give equivalent results for stopping powers estimation (0.11% and 0.13% respectively). However, when noise and tissue variation are present, the BETD reduces the RMS error on stopping powers from 2.79% for parameterization to 1.88% for the proposed approach. The BETD method also shows potential for using CT with more than 2 energies, where a number of four energy bins is shown to reduce proton beam range uncertainty by a factor of up to 1.5 compared to the parameterization method used with DECT. Conclusion This work proposes a general approach to determine elemental compositions and density for Monte Carlo inputs using CT data in a clinical context, where noise and tissues variations significantly degrade the performance of currently known methods.

Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds

Quantitative susceptibility mapping (QSM) is increasingly used to measure variation in tissue composition both in the brain and in other areas of the body in a range of disease pathologies. Although QSM measurements were originally believed to be independent of the echo time (TE) used in the gradient-recalled echo (GRE) acquisition from which they are derived; recent literature (Sood et al., 2016) has shown that these measurements can be highly TE-dependent in a number of brain regions.In this work we systematically investigate possible causes of this effect through analysis of apparent frequency and QSM measurements derived from data acquired at multiple TEs in vivo in healthy brain regions and in cerebral microbleeds (CMBs); QSM data acquired in a gadolinium-doped phantom; and in QSM data derived from idealized simulated phase data. Apparent frequency measurements in the optic radiations (OR) and central corpus callosum (CC) were compared to those predicted by a 3-pool white matter model, however the model failed to fully explain contrasting frequency profiles measured in the OR and CC.Our results show that TE-dependent QSM measurements can be caused by a failure of phase unwrapping algorithms in and around strong susceptibility sources such as CMBs; however, in healthy brain regions this behavior appears to result from intrinsic non-linear phase evolution in the MR signal. From these results we conclude that care must be taken when deriving frequency and QSM measurements in strong susceptibility sources due to the inherent limitations in phase unwrapping; and that while signal compartmentalization due to tissue microstructure and content is a plausible cause of TE-dependent frequency and QSM measurements in healthy brain regions, better sampling of the MR signal and more complex models of tissue are needed to fully exploit this relationship.

Transcriptome Analysis of Hamelia patens (Rubiaceae) Anthers Reveals Candidate Genes for Tapetum and Pollen Wall Development.

Studies of the anther transcriptome on non-model plants without a known genome are surprisingly scarce. RNA-Seq and digital gene expression (DGE) profiling provides a comprehensive approach to identify candidate genes contributing to developmental processes in non-model species. Here we built a transcriptome library of developing anthers of Hamelia patens and analyzed DGE profiles from each stage to identify genes that regulate tapetum and pollen development. In total 7,720 putative differentially expressed genes across four anther stages were identified. The number of putative stage-specific genes was: 776 at microspore mother cell stage, 807 at tetrad stage, 322 at uninucleate microspore stage, and the highest number (1,864) at bicellular pollen stage. GO enrichment analysis revealed 243 differentially expressed and 108 stage-specific genes that are potentially related to tapetum development, sporopollenin synthesis, and pollen wall. The number of expressed genes, their function and expression profiles were all significantly correlated with anther developmental processes. Overall comparisons of anther and pollen transcriptomes with those of rice and Arabidopsis together with the expression profiles of homologs of known anther-expressed genes, revealed conserved patterns and also divergence. The divergence may reflect taxon-specific differences in gene expression, the use RNA-seq as a more sensitive methodology, variation in tissue composition and sampling strategies. Given the lack of genomic sequence, this study succeeded in assigning putative identity to a significant proportion of anther-expressed genes and genes relevant to tapetum and pollen development in H. patens. The anther transcriptome revealed a molecular distinction between developmental stages, serving as a resource to unravel the functions of genes involved in anther development in H. patens and informing the analysis of other members of the Rubiaceae.

A linear, separable two-parameter model for dual energy CT imaging of proton stopping power computation.

To evaluate the accuracy and robustness of a simple, linear, separable, two-parameter model (basis vector model, BVM) in mapping proton stopping powers via dual energy computed tomography (DECT) imaging. The BVM assumes that photon cross sections (attenuation coefficients) of unknown materials are linear combinations of the corresponding radiological quantities of dissimilar basis substances (i.e., polystyrene, CaCl2 aqueous solution, and water). The authors have extended this approach to the estimation of electron density and mean excitation energy, which are required parameters for computing proton stopping powers via the Bethe-Bloch equation. The authors compared the stopping power estimation accuracy of the BVM with that of a nonlinear, nonseparable photon cross section Torikoshi parametric fit model (VCU tPFM) as implemented by the authors and by Yang et al. ["Theoretical variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues," Phys. Med. Biol. 55, 1343-1362 (2010)]. Using an idealized monoenergetic DECT imaging model, proton ranges estimated by the BVM, VCU tPFM, and Yang tPFM were compared to International Commission on Radiation Units and Measurements (ICRU) published reference values. The robustness of the stopping power prediction accuracy of tissue composition variations was assessed for both of the BVM and VCU tPFM. The sensitivity of accuracy to CT image uncertainty was also evaluated. Based on the authors' idealized, error-free DECT imaging model, the root-mean-square error of BVM proton stopping power estimation for 175 MeV protons relative to ICRU reference values for 34 ICRU standard tissues is 0.20%, compared to 0.23% and 0.68% for the Yang and VCU tPFM models, respectively. The range estimation errors were less than 1 mm for the BVM and Yang tPFM models, respectively. The BVM estimation accuracy is not dependent on tissue type and proton energy range. The BVM is slightly more vulnerable to CT image intensity uncertainties than the tPFM models. Both the BVM and tPFM prediction accuracies were robust to uncertainties of tissue composition and independent of the choice of reference values. This reported accuracy does not include the impacts of I-value uncertainties and imaging artifacts and may not be achievable on current clinical CT scanners. The proton stopping power estimation accuracy of the proposed linear, separable BVM model is comparable to or better than that of the nonseparable tPFM models proposed by other groups. In contrast to the tPFM, the BVM does not require an iterative solving for effective atomic number and electron density at every voxel; this improves the computational efficiency of DECT imaging when iterative, model-based image reconstruction algorithms are used to minimize noise and systematic imaging artifacts of CT images.

A model for the compressible, viscoelastic behavior of human amnion addressing tissue variability through a single parameter.

A viscoelastic, compressible model is proposed to rationalize the recently reported response of human amnion in multiaxial relaxation and creep experiments. The theory includes two viscoelastic contributions responsible for the short- and long-term time-dependent response of the material. These two contributions can be related to physical processes: water flow through the tissue and dissipative characteristics of the collagen fibers, respectively. An accurate agreement of the model with the mean tension and kinematic response of amnion in uniaxial relaxation tests was achieved. By variation of a single linear factor that accounts for the variability among tissue samples, the model provides very sound predictions not only of the uniaxial relaxation but also of the uniaxial creep and strip-biaxial relaxation behavior of individual samples. This suggests that a wide range of viscoelastic behaviors due to patient-specific variations in tissue composition can be represented by the model without the need of recalibration and parameter identification.

3D high spectral and spatial resolution imaging of ex vivo mouse brain.

Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T2*-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T2* and resonance frequency. The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm(3) and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16-24 h). High contrast T2*-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at -7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.

Regional variation in tissue composition and biomechanical properties of postmenopausal ovine and human vagina.

ObjectiveThere are increasing numbers of reports describing human vaginal tissue composition in women with and without pelvic organ prolapse with conflicting results. The aim of this study was to compare ovine and human posterior vaginal tissue in terms of histological and biochemical tissue composition and to assess passive biomechanical properties of ovine vagina to further characterise this animal model for pelvic organ prolapse research.Study DesignVaginal tissue was collected from ovariectomised sheep (n = 6) and from postmenopausal women (n = 7) from the proximal, middle and distal thirds. Tissue histology was analyzed using Masson's Trichrome staining; total collagen was quantified by hydroxyproline assays, collagen III/I+III ratios by delayed reduction SDS PAGE, glycosaminoglycans by dimethylmethylene blue assay, and elastic tissue associated proteins (ETAP) by amino acid analysis. Young's modulus, maximum stress/strain, and permanent strain following cyclic loading were determined in ovine vagina.ResultsBoth sheep and human vaginal tissue showed comparable tissue composition. Ovine vaginal tissue showed significantly higher total collagen and glycosaminoglycan values (p<0.05) nearest the cervix. No significant differences were found along the length of the human vagina for collagen, GAG or ETAP content. The proximal region was the stiffest (Young's modulus, p<0.05), strongest (maximum stress, p<0.05) compared to distal region, and most elastic (permanent strain).ConclusionSheep tissue composition and mechanical properties showed regional differences along the postmenopausal vaginal wall not apparent in human vagina, although the absolute content of proteins were similar. Knowledge of this baseline variation in the composition and mechanical properties of the vaginal wall will assist future studies using sheep as a model for vaginal surgery.

Effect of Daily Light Integral on Composition of Hydroponic Lettuce

The concentrations of metabolites in plants are affected by sunlight integral and other factors such as plant size, water content, and time of day. Tissue composition was measured for various sizes of hydroponic lettuce (Lactuca sativa L.) grown under seasonal variation in sunlight in a greenhouse and harvested in the morning or afternoon. Daily sunlight integral varied from 4 to 14 mol·m−2·day−1 photosynthetically active irradiance, and plant size varied from 2 to 260 g fresh weight (FW)/plant in this study. Much of the variation in tissue composition on a FW basis could be explained by the increase in dry matter content with irradiance normalized per unit area. Except for nitrate, metabolite concentrations on a FW basis increased with irradiance, and the changes resulting from irradiance were greater when harvested in the afternoon than in the morning. Nitrate concentration decreased with normalized irradiance, and the trend was the same whether measured in morning or afternoon. Malic acid increased with irradiance but not enough to counter the decrease in nitrate on a charge equivalence basis. Irradiance normalized per unit leaf area explained many effects of light and plant size on dry matter content and soluble metabolite concentrations. Lettuce for human consumption is best harvested in the afternoon after growth under high light, when it has the least nitrate and more of other nutrients.

The Effects of Ethanol Preservation on Fish Fin Stable Isotopes: Does Variation in C:N Ratio and Body Size Matter?

AbstractAlthough chemical preservation of stable isotope samples has been studied in a variety of species and tissue types, the effects of ethanol preservation on fish fin tissue have not been examined. Using caudal fin samples from juvenile Chinook Salmon Oncorhynchus tshawytscha and Rainbow Trout O. mykiss or steelhead (the anadromous form of Rainbow Trout), we investigated how storage time (2, 4, and 6 months), fin composition (C:N ratio), and fish body size (50–130 mm FL) influence preservation‐induced changes in δ13C and δ15N. In both species, we found that treatment fins (frozen and later preserved in ethanol) exhibited higher δ13C than did paired reference fins (frozen). The changes in δ15N, however, were smaller in magnitude and less consistent. Preservation‐induced increases in fin δ13C, but not δ15N, were significantly correlated with the change in C:N ratio (treatment–reference) in both species. In addition, these increases in δ13C were more highly correlated with body size in O. mykiss than in Chinook Salmon. Storage time had a significant effect on the shift in treatment fin δ13C and a small, but insignificant, effect on δ15N in O. mykiss. However, storage time was not a significant factor for explaining the isotopic shifts observed in Chinook Salmon fin tissue. This is the first study to document variation in preservation‐induced changes in δ13C within a species and to link this variation to C:N ratio. Future studies using species‐specific and tissue‐specific models to correct for preservation‐induced shifts in stable isotope ratios should be aware that these models do not account for intraspecific variation in tissue composition.

Morphometric analyses of the body and the branches of the normal third interosseous muscle (suspensory ligament) in Standardbreds

The third interosseous muscle (suspensory ligament, TIOM) is composed of connective tissue (CT) with a variable proportion of muscle (MT) and adipose tissue (AT). The aim of our study is to quantify the CT, MT and AT within the body and the branches of right thoracic and pelvic limbs TIOM in sound horses to determine whether there are differences in CT, MT and AT between age, sex, limbs and levels. Right limbs from 11 sound horses were collected. Samples from 6 levels of the TIOM were embedded in paraffin or in Tissue-Tek(®) . Most of the paraffin sections were shredded. Using the cryosection, some artefacts appeared. Cryoprotection was carried out, which produced the best results. Hematoxylin-phloxine-saffron and Hematoxylin-eosin gave a good contrast of colours between the tissues observed allowing the use of an image analysis programme to calculate percentage of each tissue within the TIOM. The percentage of MT and AT decreased significantly (P < 0.0001), whereas the percentage of CT increased significantly (P < 0.0001) with age and when descending from the proximal to the distal level of the TIOM. The percentage of MT was significantly higher (P < 0.0001) in females than males, while the percentage of CT was significantly higher (P < 0.0001) in males than females. The percentage of AT was significantly higher (P = 0.0278) in pelvic limbs than in thoracic limbs. These results confirm the variation in tissue composition within the TIOM of sound horses.

Regional difference in GABA levels between medial prefrontal and occipital cortices

To avoid the confounding effects of variations in tissue composition this study measured regional GABA differences using two voxels with the same tissue composition. Eighteen healthy adult volunteers were scanned using a 3 Tesla GE clinical scanner with a J-coupling based editing sequence. Spectroscopy voxels were placed in the medial prefrontal (MPFC) and occipital cortex (OCC) with essentially the same gray and white matter fractions. A 16% (P = 0.0001) significantly higher GABA to creatine ratio was found in the OCC (0.1103 ± 0.0050) compared with the MPFC (0.0953 ± 0.0041). When normalized to tissue water, GABA concentrations in the OCC were 14% higher than in the MPFC. A difference in GABA concentration was found between the OCC and MPFC voxels in healthy subjects which is attributable to differences other than tissue composition.