Clinical Proteomics for Solid Organ Tissues.

The evaluation of biopsied solid organ tissue has long relied on visual examination using a microscope. Immunohistochemistry is critical in this process, labeling and detecting cell lineage markers and therapeutic targets. However, while the practice of immunohistochemistry has reshaped diagnostic pathology and facilitated improvements in cancer treatment, it has also been subject to pervasive challenges with respect to standardization and reproducibility. Efforts are ongoing to improve immunohistochemistry, but for some applications, the benefit of such initiatives could be impeded by its reliance on monospecific antibody-protein reagents and limited multiplexing capacity. This perspective surveys the relevant challenges facing traditional immunohistochemistry and describes how mass spectrometry, particularly liquid chromatography-tandem mass spectrometry, could help alleviate problems. In particular, targeted mass spectrometry assays could facilitate measurements of individual proteins or analyte panels, using internal standards for more robust quantification and improved interlaboratory reproducibility. Meanwhile, untargeted mass spectrometry, showcased to date clinically in the form of amyloid typing, is inherently multiplexed, facilitating the detection and crude quantification of 100s to 1000s of proteins in a single analysis. Further, data-independent acquisition has yet to be applied in clinical practice, but offers particular strengths that could appeal to clinical users. Finally, we discuss the guidance that is needed to facilitate broader utilization in clinical environments and achieve standardization.

Automatic soft-tissue analysis on orthodontic frontal and lateral facial photographs based on deep learning.

BACKGROUND: To establish the automatic soft-tissue analysis model based on deep learning that performs landmark detection and measurement calculations on orthodontic facial photographs to achieve a more comprehensive quantitative evaluation of soft tissues. METHODS: A total of 578 frontal photographs and 450 lateral photographs of orthodontic patients were collected to construct datasets. All images were manually annotated by two orthodontists with 43 frontal-image landmarks and 17 lateral-image landmarks. Automatic landmark detection models were established, which consisted of a high-resolution network, a feature fusion module based on depthwise separable convolution, and a prediction model based on pixel shuffle. Ten measurements for frontal images and eight measurements for lateral images were defined. Test sets were used to evaluate the model performance, respectively. The mean radial error of landmarks and measurement error were calculated and statistically analysed to evaluate their reliability. RESULTS: The mean radial error was 14.44 ± 17.20 pixels for the landmarks in the frontal images and 13.48 ± 17.12 pixels for the landmarks in the lateral images. There was no statistically significant difference between the model prediction and manual annotation measurements except for the mid facial-lower facial height index. A total of 14 measurements had a high consistency. CONCLUSION: Based on deep learning, we established automatic soft-tissue analysis models for orthodontic facial photographs that can automatically detect 43 frontal-image landmarks and 17 lateral-image landmarks while performing comprehensive soft-tissue measurements. The models can assist orthodontists in efficient and accurate quantitative soft-tissue evaluation for clinical application.

Long-term retention and distribution of highly enriched uranium in an occupationally exposed female.

The United States Transuranium and Uranium Registries' (USTUR) female whole body tissue donor studied here was occupationally exposed to highly enriched uranium for 17 years. One hundred and twenty-nine tissue samples were collected at the time of death, 31 years post-exposure. These samples were radiochemically analyzed for uranium. The highest uranium concentration of 16.5 ± 2.0 µg kg-1 was measured in the lungs, and the lowest concentration of 0.11 ± 0.01 µg kg-1 in the liver. The thyroid had the highest concentration of 6.3 ± 2.9 µg kg-1 among systemic tissues. Mass-weighted average concentration in the entire skeleton was estimated to be 1.60 ± 0.19 µg kg-1. In the skeleton, uranium was non-uniformly distributed among different bones. Thirty-one years after the intake, approximately 40% of occupational uranium was still retained in the skeleton, followed by the kidneys (~ 30%), and the brain and liver (~ 10%). Systemic uranium was equally distributed between the skeleton and soft tissues. Uranium content in systemic organs followed the pattern: skeleton > > brain ≈ kidneys > heart ≈ liver > thyroid ≈ spleen. Uranium distribution in this female was compared to previously published USTUR data for male tissue donors. It is concluded that no difference in uranium systemic distribution was observed between female and male individuals. It is demonstrated that dose assessment based on the current ICRP biokinetic model overestimated the dose to the brain by 20%.

Forty-eight-year follow-up of a female worker exposed to highly enriched uranium via chronic and acute inhalation.

The United States Transuranium and Uranium Registries (USTUR) is a unique resource of data and materials for studying biokinetics of uranium in the human body. In this study, bioassay data and post-mortem organ activities from a female whole-body USTUR donor who was exposed to highly enriched uranium were analyzed using the IMBA Professional Plus® software to derive the best estimate of the total intake. The resulting radiation doses delivered to this individual's whole body and major target organs were calculated from estimated intake based on case-specific dose coefficients derived using the AIDE® software. Both intake and dose calculations were carried out using the biokinetic and dosimetric models recommended by the International Commission on Radiological Protection (ICRP) in its Occupational Intakes of Radionuclides publication series. Different exposure scenarios including chronic and acute inhalation intakes were tested. A combination of a chronic inhalation intake and two acute inhalation intakes appears to best describe the bioassay data. To fit this female individual's autopsy data, the transfer rate from the liver to the blood was increased by a factor of 8 and the transfer rate from the kidneys to the blood was decreased by a factor of 2.2. This resulted in the best fit to all data (p = 0.519). The total intake was estimated to be 44.1 kBq, and the committed effective dose was 211 mSv with 96.8% contributed by 234U. 96.6% of the committed effective dose was contributed by the lungs. The remaining 3.4% of the committed effective dose was contributed by all systemic tissues and organs with the highest contribution (0.40%) from the red bone marrow. It is concluded that the current ICRP models, with the adjustment for smoking status, adequately describe uranium biokinetics for this individual except retention in the liver and kidneys. However, this study was based on a single case and may not be sufficient to identify any apparent sex-specific differences in uranium biokinetics.

Natural mercury exposure of European insectivorous bats may exceed a recognized toxicity threshold.

Heavy metals are an important group of toxic substances harmful for many organisms. Of these, mercury is one of the most monitored in the environment. Several matrices are used for the monitoring of environmental load, including a range of organisms; bats, however, have only been examined rarely. Insectivorous bats are apex predators threatened by several human interventions in their natural environment, including heavy metal pollution. The aim of this study was to analyze the content of total mercury in the fur, flight membrane, and pectoral muscle of greater mouse-eared bats (Myotis myotis). Total mercury concentrations were also measured in carabid beetles from the catch locality Zastávka u Brna. Samples were obtained from 43 bat carcasses at two different localities in the Czech Republic (Zastávka u Brna, Malá Morávka). Total mercury content varied between 1.76-72.20 µg/g in fur, 0.04-0.14 µg/g in skin, and 0.05-0.20 µg/g in muscle. Total mercury values in the fur of some individuals from Malá Morávka exceeded the recognized toxicity limit. Furthermore, there was a significant difference (p < 0.001) in content of total mercury in fur between localities, and there was a clear effect of age on concentrations in fur, skin, and muscle, the concentrations being significantly correlated (fur and skin rs = 0.783; fur and muscle rs = 0.716; skin and muscle rs = 0.884). These findings confirm the usefulness of fur samples from living bats for biomonitoring mercury burden in the environment.

Integrated Analysis of Serum and Tissue microRNA Transcriptome for Biomarker Discovery in Gastric Cancer.

Gastric cancer (GC) poses a significant global health challenge, demanding a detailed exploration of its molecular landscape. Studies suggest that exposure to environmental pollutants can lead to changes in microRNA (miRNA) expression patterns, which may contribute to the development and progression of GC. MiRNAs have emerged as crucial regulators implicated in GC pathogenesis. The largest GC serum miRNA dataset to date, comprising 1417 non-cancer controls and 1417 GC samples was used. We conducted a comprehensive analysis of miRNA expression profiles. Differential expression analysis, co-expression network construction, and machine learning models were employed to identify key serum miRNAs and their association with clinical parameters. Weighted Gene Co-expression Network Analysis (WGCNA) and immune infiltration analysis were used to validate the importance of the key miRNA. A total of 1766 differentially expressed miRNAs were identified, with miR-1290, miR-1246, and miR-451a among the top up-regulated, and miR-6875-5p, miR-6784-5p, miR-1228-5p, and miR-6765-5p among the top down-regulated. WGCNA revealed that modules M1 and M5 were significantly associated with GC subtypes and disease status. MiRNA-target gene network analysis identified prognostically significant genes TP53, EMCN, CBX8, and ALDH1A3. Machine learning models LASSO, SVM, randomforest, and XGBOOST demonstrated the diagnostic potential of miRNA profiles. Tissue and serum miR-187 emerged as an independent prognostic factor, influencing patient survival across clinical parameters. Gene expression and immune cell infiltration were different in tissues stratified by miR-187 expression. In summary, the integration of differential gene expression, co-expression analysis, and immune cell profiling provided insights into the molecular intricacies of GC progression.

Fast and low-cost method for direct and simultaneous determination of nitrogen and carbon in soybean leaves using benchtop and portable near-infrared devices.

BACKGROUND: The current techniques for determining carbon and nitrogen content to provide information about the nutritional status of plants are time-consuming and expensive. For this reason, the objective of this study was to develop an analytical method for the direct and simultaneous determination of nitrogen and carbon elemental content in soybean leaves using near-infrared spectroscopy and compare the performance of conventional (1100-2500 nm spectral range) and portable equipment (1100-1700 nm spectral range). Partial least-squares regression models were developed using 27 soybean leaf samples collected during the 2021 harvest and applied for the simultaneous determination of carbon and nitrogen in 13 samples collected during the 2022 harvest. RESULTS: The root-mean-square error of prediction values for nitrogen and carbon were low (2.42 g kg-1 and 4.37 g kg-1 respectively) for the benchtop method yielded low but higher for the portable method (3.82 g kg-1 and 10.7 g kg-1 respectively). The benchtop method did not show significant differences when compared with the reference method for determining nitrogen and carbon. In contrast, the portable methodology showed potential as a screening method for determining nitrogen levels, particularly in fieldwork. CONCLUSION: The methodologies evaluated in this study were implemented and evaluated under real crop monitoring conditions, using independent sets of calibration and prediction samples. Their utilization enables the acquisition of cost-effective, safe analytical data aligning with the principles of green analytical chemistry. © 2023 Society of Chemical Industry.

Evaluation of the soft tissue facial profile in different skeletal malocclusions in relation to age.

BACKGROUND: The aim of the study was to assess the thickness of the soft tissue facial profile (STFP) in relation to the skeletal malocclusion, age and gender. METHODS: All patients, aged 7-35 years, who were seeking orthodontic treatment at the Department of Orthodontics, Medical University of Warsaw between 2019 and 22 were included in the study. All patients had lateral head radiographs taken before the treatment. The cephalometric analysis was performed including the STFP analysis. The patients were allocated to one of six groups based on age and skeletal relations (ANB angle). The minimum number of patients in each group was 60 with equal gender distribution. The STFP analysis included ten linear measurements. RESULTS: A total of 300 patients were included in the study and allocated to five groups. Group 6 (growing patients with skeletal Class III malocclusion) was not included in the study as it failed to achieve the assumed group size. There were significant differences in the thickness of the STFP in relation to the skeletal malocclusions. Adults with skeletal Class III malocclusion had significantly thicker subnasal soft tissues compared to patients with skeletal Class I and Class II malocclusions. The thickness of the lower lip in patients with Class II skeletal malocclusion was significantly bigger compared to the other groups. Children and adolescents with Class II malocclusions had thicker lower lip in comparison to the group with Class I malocclusion. The majority of the STFP measurements were significantly smaller in children and adolescents compared to adults. The thickness of the STFP in males was significantly bigger in all age groups compared to females. CONCLUSIONS: The thickness of facial soft tissues depends on the patient's age and gender. The degree of compensation of the skeletal malocclusion in the STFP may be a decisive factor during orthodontic treatment planning regarding a surgical approach or a camouflage treatment of skeletal defects.

Advances in Imaging Mass Spectrometry for Biomedical and Clinical Research.

Imaging mass spectrometry (IMS) allows for the untargeted mapping of biomolecules directly from tissue sections. This technology is increasingly integrated into biomedical and clinical research environments to supplement traditional microscopy and provide molecular context for tissue imaging. IMS has widespread clinical applicability in the fields of oncology, dermatology, microbiology, and others. This review summarizes the two most widely employed IMS technologies, matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI), and covers technological advancements, including efforts to increase spatial resolution, specificity, and throughput. We also highlight recent biomedical applications of IMS, primarily focusing on disease diagnosis, classification, and subtyping.

Breast tissue analysis using a clinically compatible combined time-resolved fluorescence and diffuse reflectance (TRF-DR) system.

OBJECTIVE: This work aims to develop a clinically compatible system that can perform breast tissue analysis in a more time efficient process than conventional histopathological assessment. The potential for such a system to be used in vivo in the operating room or surgical suite to improve patient outcome is investigated. METHOD: In this work, 80 matched pairs of invasive ductal carcinoma and adjacent normal breast tissue were measured in a combined time-resolved fluorescence and diffuse reflectance (DA) system. Following measurement, the fluorescence intensity of collagen and flavin adenine dinucleotide (FAD); the fluorescence lifetime of collagen, nicotinamide adenine dinucleotide (NADH), and FAD; the DA; absorption coefficient; and reduced scattering coefficient were extracted. Samples then underwent histological processing and H&E staining to classify composition as tumor, fibroglandular, and/or adipose tissue. RESULTS: Statistically significant differences in the collagen and FAD fluorescence intensity, collagen and FAD fluorescence lifetime, DA, and scattering coefficient were found between each tissue group. The NADH fluorescence lifetime and absorption coefficient were statistically different between the tumor and fibroglandular groups, and the tumor and adipose groups. While many breast tissue analysis studies label fibroglandular and adipose together as "normal" breast tissue, this work indicates that some differences between tumor and fibroglandular tissue are not the same as differences between tumor and adipose tissue. Observations of the reduced scatter coefficient may also indicate further classification to include fibro-adipose may be necessary. Future work would benefit from the additional tissue classification. CONCLUSION: With observable differences in optical parameters between the three tissue types, this system shows promise as a breast analysis tool in a clinical setting. With further work involving samples of mixed composition, this combined system could potentially be used intraoperatively for rapid margin assessment.

MATLAB-Based Algorithm and Software for Analysis of Wavy Collagen Fibers.

Knowledge of soft tissue fiber structure is necessary for accurate characterization and modeling of their mechanical response. Fiber configuration and structure informs both our understanding of healthy tissue physiology and of pathological processes resulting from diseased states. This study develops an automatic algorithm to simultaneously estimate fiber global orientation, abundance, and waviness in an investigated image. To our best knowledge, this is the first validated algorithm which can reliably separate fiber waviness from its global orientation for considerably wavy fibers. This is much needed feature for biological tissue characterization. The algorithm is based on incremental movement of local regions of interest (ROI) and analyzes two-dimensional images. Pixels belonging to the fiber are identified in the ROI, and ROI movement is determined according to local orientation of fiber within the ROI. The algorithm is validated with artificial images and ten images of porcine trachea containing wavy fibers. In each image, 80-120 fibers were tracked manually to serve as verification. The coefficient of determination R2 between curve lengths and histograms documenting the fiber waviness and global orientation were used as metrics for analysis. Verification-confirmed results were independent of image rotation and degree of fiber waviness, with curve length accuracy demonstrated to be below 1% of fiber curved length. Validation-confirmed median and interquartile range of R2, respectively, were 0.90 and 0.05 for curved length, 0.92 and 0.07 for waviness, and 0.96 and 0.04 for global orientation histograms. Software constructed from the proposed algorithm was able to track one fiber in about 1.1 s using a typical office computer. The proposed algorithm can reliably and accurately estimate fiber waviness, curve length, and global orientation simultaneously, moving beyond the limitations of prior methods.

Ratiometric luminescent sensor based on BSA-coated gold/silver nanoclusters for the selective determination and spatiotemporal imaging of gallic acid in plants.

A new fluorescence sensing strategy has been developed. Four bimetallic nanoclusters, gold/silver, gold/copper, gold/molybdenum and gold/cobalt, were prepared using bovine serum albumin (BSA) as a reducing and stabilizing agent. The fluorescence properties of four nanoclusters were explored by solid-state UV and XPS. The gold/silver nanoclusters (BSA-Au/Ag NCs) with the best ratiometric fluorescence properties for gallic acid (GA) in plants were selected to realize the sensitive detection of GA. GA affected the conformation of BSA, thereby disrupting the luminescent environment of the nanoclusters, resulting in a pronounced fluorescence quenching at 566 nm. The ratiometric fluorescence signal (I566/I453) was used for trace detection of GA in plants. It has a wide response range of 1.25-40.0 µM and a low detection limit of 45.27 nM. GA was detected at 19.49 µM in the plant extract, and the spiked recoveries ranged from 96.09 to 104.6%. In addition, due to the non-toxic and biocompatible properties of BSA, BSA-Au/Ag NCs have also been validated for fluorescence imaging of plant tissues. It realized the comparison of GA content in different parts of plants and the difference of GA content in plants after abiotic stress. Therefore, the developed strategy offers potential application for the analytical study of active substances in plants.

Comparing Direct Measurements and Three-Dimensional (3D) Scans for Evaluating Facial Soft Tissue.

The inspection of patients' soft tissues and the effects of various dental procedures on their facial physiognomy are quite challenging. To minimise discomfort and simplify the process of manual measuring, we performed facial scanning and computer measurement of experimentally determined demarcation lines. Images were acquired using a low-cost 3D scanner. Two consecutive scans were obtained from 39 participants, to test the scanner repeatability. An additional ten persons were scanned before and after forward movement of the mandible (predicted treatment outcome). Sensor technology that combines red, green, and blue (RGB) data with depth information (RGBD) integration was used for merging frames into a 3D object. For proper comparison, the resulting images were registered together, which was performed with ICP (Iterative Closest Point)-based techniques. Measurements on 3D images were performed using the exact distance algorithm. One operator measured the same demarcation lines directly on participants; repeatability was tested (intra-class correlations). The results showed that the 3D face scans were reproducible with high accuracy (mean difference between repeated scans <1%); the actual measurements were repeatable to some extent (excellent only for the tragus-pogonion demarcation line); computational measurements were accurate, repeatable, and comparable to the actual measurements. Three dimensional (3D) facial scans can be used as a faster, more comfortable for patients, and more accurate technique to detect and quantify changes in facial soft tissue resulting from various dental procedures.

GluN3 subunit expression correlates with increased vulnerability of hippocampus and entorhinal cortex to neurodegeneration in a model of temporal lobe epilepsy.

Temporal lobe epilepsy (TLE) is the most common type of epilepsy in adults that is often refractory to antiepileptic medication therapy. Neither the pathology nor the etiology of TLE is fully characterized, although recent studies have established that the two are causally related. TLE pathology entails a stereotypic pattern of neuron loss in hippocampal and parahippocampal regions, predominantly in CA1 subfield of the hippocampus and layer 3 of the medial entorhinal area (MEA), deemed hallmark pathological features of the disease. Through this work, we address the contribution of glutamatergic N-methyl-d-aspartate receptors (NMDARs) to the pathology (vulnerability and pattern of neuronal loss), and by extension to the pathophysiology (Ca2+-induced excitotoxicity), by assaying the spatial expression of their subunit proteins (GluN1, GluN2A, GluN2B, and GluN3A) in these regions using area-specific tissue analysis (ASTA), a novel methodology for harvesting brain chads from hard-to-reach regions within brain slices for Western blotting. Our data suggest gradient expression of the GluN3A subunit along the mid-lateral extent of layer 3 MEA and along the CA1-subicular axis in the hippocampus, unlike GluN1 or GluN2 subunits that are uniformly distributed. Incorporation of GluN3A in the subunit composition of conventional diheteromeric (d-) NMDARs yield triheteromeric (t-) NMDARs which by virtue of their increased selectivity for Ca2+ render neurons vulnerable to excitotoxic damage. Thus, the expression profile of this subunit sheds light on the spatial extent of the pathology observed in these regions and implicates the GluN3 subunit of NMDARs in hippocampal and entorhinal cortical pathology underlying TLE.NEW & NOTEWORTHY The role of the GluN3 subunit in NMDAR-mediated pathophysiology underlying TLE is not known. Here, we demonstrate using ASTA (area-specific tissue analysis) that its expression in specific regions of the entorhinal cortex and the hippocampus is correlated with significant cell loss and neurodegeneration, hallmark features of the disease.

Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning.

Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue integrity and the effects at the molecular level in organisms is of increasing interest due to the environmental exposure to numerous contaminants. The analysis of tissues can be performed by histological examination, which is still time-consuming and restricted to target-specific staining methods. The histological approaches can be complemented with chemical imaging analysis. Chemical imaging of tissue sections is typically performed using a single imaging approach. However, for toxicological testing of environmental pollutants, a multimodal approach combined with improved data acquisition and evaluation is desirable, since it may allow for more rapid tissue characterization and give further information on ecotoxicological effects at the tissue level. Therefore, using the soil model organism Eisenia fetida as a model, we developed a sequential workflow combining Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) for chemical analysis of the same tissue sections. Data analysis of the FTIR spectra via random decision forest (RDF) classification enabled the rapid identification of target tissues (e.g., digestive tissue), which are relevant from an ecotoxicological point of view. MALDI imaging analysis provided specific lipid species which are sensitive to metabolic changes and environmental stressors. Taken together, our approach provides a fast and reproducible workflow for label-free histochemical tissue analyses in E. fetida, which can be applied to other model organisms as well.

Relationship between glomerular number in fresh kidney biopsy samples and light microscopy samples.

BACKGROUND: On-site evaluation of fresh kidney biopsy (FKB) samples at the time of biopsy is useful to verify that adequate specimens are acquired. However, some cases present poor correlation between glomerular number in FKB samples and light microscopy (LM) samples. We examined the usefulness of such on-site evaluation. METHODS: We conducted a retrospective cross-sectional observational study (n = 129) to assess the correlation between glomerular number in FKB samples and LM samples and the associated factors hindering the evaluation. RESULTS: There was a significant positive correlation between glomerular number in FKB samples and LM samples. The median ratio of glomerular number (LM samples/FKB samples) was 0.74. According to this ratio, cases were divided into three groups: reasonable estimation (65 cases), underestimation (32 cases), and overestimation (32 cases). Comparing the reasonable and underestimation groups, significant differences were detected in the extent of interstitial fibrosis and tubular atrophy (IFTA) and interstitial inflammation. Logistic regression analysis demonstrated that IFTA and interstitial inflammation were significantly associated with the underestimation. Moreover, the cortex length of FKB samples correlated with glomerular number in LM samples regardless of tubulointerstitial lesions. CONCLUSIONS: Glomerular number determined during on-site evaluation can be a reference for the actual number of glomeruli in LM samples. Since tubulointerstitial lesions make it difficult to recognize glomeruli in FKB samples, the possibility of underestimation for cases with possibly severe tubulointerstitial lesions should be considered. In such cases, evaluation of cortex length of FKB samples may substitute for evaluating glomeruli on-site.

Three-dimensional evaluation of soft tissues in hyperdivergent skeletal class II females in Guangdong.

OBJECTIVES: To establish the three-dimensional facial soft tissue morphology of adolescent and adult females in the Guangdong population and to study the morphological characteristics of hyperdivergent skeletal class II females in Guangdong compared with that of normodivergent class I groups. MATERIALS AND METHODS: The 3dMDface system was used to capture face scans of 160 patients, including 45 normal and 35 hyperdivergent skeletal class II adolescents (aged 11-14 years old) and 45 normal and 35 hyperdivergent skeletal class II adults (aged 18-30 years old). Thirty-two soft tissue landmarks were mapped, and 21 linear, 10 angular and 17 ratio measurements were obtained by 3dMDvultus analysis software. Data were assessed with a t-test of two independent samples between the normal adolescent and adult groups and between the normal and hyperdivergent skeletal class II groups. RESULTS: The linear measurements of the Guangdong adult females were larger than those of the adolescents in both Class I and Class II groups. However, the angular and ratio measurements had no significant difference. The vertical linear measurements were higher and the sagittal and transverse linear measurements were smaller in the hyperdivergent class II group (p < 0.05). The soft tissue ANB angle, chin-lip angle, and mandibular angle were significantly larger and the soft tissue facial convexity angle and nasal convexity angle were significantly smaller in the hyperdivergent class II group (p < 0.05). Additionally, there were significant differences in the ratio measurements between the hyperdivergent class II groups and the control groups (p < 0.05). CONCLUSIONS: The three-dimensional facial morphology of Guangdong adolescent and adult females was acquired. The facial soft tissue measurements of the adults were higher in the three dimensions except for the facial convexity and proportional relationships which were similar, suggesting that the growth pattern remained the same. The three-dimensional facial soft tissue features of hyperdivergent skeletal class II were characterized by the terms "long, convex, and narrow". Three-dimensional facial measurements can reflect intrinsic hard tissue characteristics.

ShapeMetrics: A userfriendly pipeline for 3D cell segmentation and spatial tissue analysis.

The demand for single-cell level data is constantly increasing within life sciences. In order to meet this demand, robust cell segmentation methods that can tackle challenging in vivo tissues with complex morphology are required. However, currently available cell segmentation and volumetric analysis methods perform poorly on 3D images. Here, we generated ShapeMetrics, a MATLAB-based script that segments cells in 3D and, by performing unbiased clustering using a heatmap, separates the cells into subgroups according to their volumetric and morphological differences. The cells can be accurately segregated according to different biologically meaningful features such as cell ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. Our machine learning based script enables dissection of a large amount of novel data from microscope images in addition to the traditional information based on fluorescent biomarkers. Furthermore, the cells in different subgroups can be spatially mapped back to their original locations in the tissue image to help elucidate their roles in their respective morphological contexts. In order to facilitate the transition from bulk analysis to single-cell level accuracy, we emphasize the user-friendliness of our method by providing detailed step-by-step instructions through the pipeline hence aiming to reach users with less experience in computational biology.

A Novel Method Facilitating the Simple and Low-Cost Preparation of Human Osteochondral Slice Explants for Large-Scale Native Tissue Analysis.

For in vitro modeling of human joints, osteochondral explants represent an acceptable compromise between conventional cell culture and animal models. However, the scarcity of native human joint tissue poses a challenge for experiments requiring high numbers of samples and makes the method rather unsuitable for toxicity analyses and dosing studies. To scale their application, we developed a novel method that allows the preparation of up to 100 explant cultures from a single human sample with a simple setup. Explants were cultured for 21 days, stimulated with TNF-α or TGF-ß3, and analyzed for cell viability, gene expression and histological changes. Tissue cell viability remained stable at >90% for three weeks. Proteoglycan levels and gene expression of COL2A1, ACAN and COMP were maintained for 14 days before decreasing. TNF-α and TGF-ß3 caused dose-dependent changes in cartilage marker gene expression as early as 7 days. Histologically, cultures under TNF-α stimulation showed a 32% reduction in proteoglycans, detachment of collagen fibers and cell swelling after 7 days. In conclusion, thin osteochondral slice cultures behaved analogously to conventional punch explants despite cell stress exerted during fabrication. In pharmacological testing, both the shorter diffusion distance and the lack of need for serum in the culture suggest a positive effect on sensitivity. The ease of fabrication and the scalability of the sample number make this manufacturing method a promising platform for large-scale preclinical testing in joint research.

Z-score mapping for standardized analysis and reporting of cardiovascular magnetic resonance modified Look-Locker inversion recovery (MOLLI) T1 data: Normal behavior and validation in patients with amyloidosis.

BACKGROUND: T1 mapping using modified Look-Locker inversion recovery (MOLLI) provides quantitative information on myocardial tissue composition. T1 results differ between sites due to variations in hardware and software equipment, limiting the comparability of results. The aim was to test if Z-scores can be used to compare the results of MOLLI T1 mapping from different cardiovascular magnetic resonance (CMR) platforms. METHODS: First, healthy subjects (n = 15) underwent 11 combinations of native short-axis T1 mapping (four CMR systems from two manufacturers at 1.5 T and 3 T, three MOLLI schemes). Mean and standard deviation (SD) of septal myocardial T1 were derived for each combination. T1 maps were transformed into Z-score maps based on mean and SD values using a prototype post-processing module. Second, Z-score mapping was applied to a validation sample of patients with cardiac amyloidosis at 1.5 T (n = 25) or 3 T (n = 13). RESULTS: In conventional T1 analysis, results were confounded by variations in field strength, MOLLI scheme, and manufacturer-specific system characteristics. Z-score-based analysis yielded consistent results without significant differences between any two of the combinations in part 1 of the study. In the validation sample, Z-score mapping differentiated between patients with cardiac amyloidosis and healthy subjects with the same diagnostic accuracy as standard T1 analysis regardless of field strength. CONCLUSIONS: T1 analysis based on Z-score mapping provides consistent results without significant differences due to field strengths, CMR systems, or MOLLI variants, and detects cardiac amyloidosis with the same diagnostic accuracy as conventional T1 analysis. Z-score mapping provides a means to compare native T1 results acquired with MOLLI across different CMR platforms.