Ultra-low dose hip CT-based automated measurement of volumetric bone mineral density at proximal femoral subregions.

BACKGROUND: Forty to fifty percent of women and 13%-22% of men experience an osteoporosis-related fragility fracture in their lifetimes. After the age of 50 years, the risk of hip fracture doubles in every 10 years. x-Ray based DXA is currently clinically used to diagnose osteoporosis and predict fracture risk. However, it provides only 2-D representation of bone and is associated with other technical limitations. Thus, alternative methods are needed. PURPOSE: To develop and evaluate an ultra-low dose (ULD) hip CT-based automated method for assessment of volumetric bone mineral density (vBMD) at proximal femoral subregions. METHODS: An automated method was developed to segment the proximal femur in ULD hip CT images and delineate femoral subregions. The computational pipeline consists of deep learning (DL)-based computation of femur likelihood map followed by shape model-based femur segmentation and finite element analysis-based warping of a reference subregion labeling onto individual femur shapes. Finally, vBMD is computed over each subregion in the target image using a calibration phantom scan. A total of 100 participants (50 females) were recruited from the Genetic Epidemiology of COPD (COPDGene) study, and ULD hip CT imaging, equivalent to 18 days of background radiation received by U.S. residents, was performed on each participant. Additional hip CT imaging using a clinical protocol was performed on 12 participants and repeat ULD hip CT was acquired on another five participants. ULD CT images from 80 participants were used to train the DL network; ULD CT images of the remaining 20 participants as well as clinical and repeat ULD CT images were used to evaluate the accuracy, generalizability, and reproducibility of segmentation of femoral subregions. Finally, clinical CT and repeat ULD CT images were used to evaluate accuracy and reproducibility of ULD CT-based automated measurements of femoral vBMD. RESULTS: Dice scores of accuracy (n = 20), reproducibility (n = 5), and generalizability (n = 12) of ULD CT-based automated subregion segmentation were 0.990, 0.982, and 0.977, respectively, for the femoral head and 0.941, 0.970, and 0.960, respectively, for the femoral neck. ULD CT-based regional vBMD showed Pearson and concordance correlation coefficients of 0.994 and 0.977, respectively, and a root-mean-square coefficient of variation (RMSCV) (%) of 1.39% with the clinical CT-derived reference measure. After 3-digit approximation, each of Pearson and concordance correlation coefficients as well as intraclass correlation coefficient (ICC) between baseline and repeat scans were 0.996 with RMSCV of 0.72%. Results of ULD CT-based bone analysis on 100 participants (age (mean ± SD) 73.6 ± 6.6 years) show that males have significantly greater (p < 0.01) vBMD at the femoral head and trochanteric regions than females, while females have moderately greater vBMD (p = 0.05) at the medial half of the femoral neck than males. CONCLUSION: Deep learning, combined with shape model and finite element analysis, offers an accurate, reproducible, and generalizable algorithm for automated segmentation of the proximal femur and anatomic femoral subregions using ULD hip CT images. ULD CT-based regional measures of femoral vBMD are accurate and reproducible and demonstrate regional differences between males and females.

Deep learning-based harmonization of trabecular bone microstructures between high- and low-resolution CT imaging.

BACKGROUND: Osteoporosis is a bone disease related to increased bone loss and fracture-risk. The variability in bone strength is partially explained by bone mineral density (BMD), and the remainder is contributed by bone microstructure. Recently, clinical CT has emerged as a viable option for in vivo bone microstructural imaging. Wide variations in spatial-resolution and other imaging features among different CT scanners add inconsistency to derived bone microstructural metrics, urging the need for harmonization of image data from different scanners. PURPOSE: This paper presents a new deep learning (DL) method for the harmonization of bone microstructural images derived from low- and high-resolution CT scanners and evaluates the method's performance at the levels of image data as well as derived microstructural metrics. METHODS: We generalized a three-dimensional (3D) version of GAN-CIRCLE that applies two generative adversarial networks (GANs) constrained by the identical, residual, and cycle learning ensemble (CIRCLE). Two GAN modules simultaneously learn to map low-resolution CT (LRCT) to high-resolution CT (HRCT) and vice versa. Twenty volunteers were recruited. LRCT and HRCT scans of the distal tibia of their left legs were acquired. Five-hundred pairs of LRCT and HRCT image blocks of 64 × 64 × 64 $64 \times 64 \times 64 $ voxels were sampled for each of the twelve volunteers and used for training in supervised as well as unsupervised setups. LRCT and HRCT images of the remaining eight volunteers were used for evaluation. LRCT blocks were sampled at 32 voxel intervals in each coordinate direction and predicted HRCT blocks were stitched to generate a predicted HRCT image. RESULTS: Mean ± standard deviation of structural similarity (SSIM) values between predicted and true HRCT using both 3DGAN-CIRCLE-based supervised (0.84 ± 0.03) and unsupervised (0.83 ± 0.04) methods were significantly (p < 0.001) higher than the mean SSIM value between LRCT and true HRCT (0.75 ± 0.03). All Tb measures derived from predicted HRCT by the supervised 3DGAN-CIRCLE showed higher agreement (CCC  ∈ $ \in $ [0.956 0.991]) with the reference values from true HRCT as compared to LRCT-derived values (CCC  ∈ $ \in $ [0.732 0.989]). For all Tb measures, except Tb plate-width (CCC = 0.866), the unsupervised 3DGAN-CIRCLE showed high agreement (CCC  ∈ $ \in $ [0.920 0.964]) with the true HRCT-derived reference measures. Moreover, Bland-Altman plots showed that supervised 3DGAN-CIRCLE predicted HRCT reduces bias and variability in residual values of different Tb measures as compared to LRCT and unsupervised 3DGAN-CIRCLE predicted HRCT. The supervised 3DGAN-CIRCLE method produced significantly improved performance (p < 0.001) for all Tb measures as compared to the two DL-based supervised methods available in the literature. CONCLUSIONS: 3DGAN-CIRCLE, trained in either unsupervised or supervised fashion, generates HRCT images with high structural similarity to the reference true HRCT images. The supervised 3DGAN-CIRCLE improves agreements of computed Tb microstructural measures with their reference values and outperforms the unsupervised 3DGAN-CIRCLE. 3DGAN-CIRCLE offers a viable DL solution to retrospectively improve image resolution, which may aid in data harmonization in multi-site longitudinal studies where scanner mismatch is unavoidable.

Computational Investigations of the Water Structure at the α-Al2O3(0001)-Water Interface.

The α-Al2O3(0001)-water interface is investigated using ab initio molecular dynamics (AIMD) simulations. The spectral signatures of the vibrational sum frequency generation (vSFG) spectra of OH stretching mode for water molecules at the interface are related to the interfacial water orientation, hydrogen bond network, and water dissociation process at different water/alumina interfaces. Significant differences are found between alumina surfaces at different hydroxylation levels, namely, Al-terminated and O-terminated α-Al2O3(0001). By calculating the vibrational sum frequency generation spectrum and its imaginary component from AIMD results, the structure of interfacial waters as well as the termination of alumina slab are related to the spectral signatures of vSFG data.

Abnormal brain spontaneous activity in major depressive disorder adolescents with non-suicidal self injury and its changes after sertraline therapy.

Background: Non-suicidal self-injury (NSSI) commonly occurs among adolescents with major depressive disorder (MDD), causing adverse effects on the physical and mental health of the patients. However, the underlying neurobiological mechanism of NSSI in adolescents with MDD (nsMDDs) remains unclear, and there are still challenges in the treatment. Studies have suggested that sertraline administration could be an effective way for treatment. Methods: To verify the effectiveness and to explore the neurobiological processes, we treated a group of adolescents with nsMDDs with sertraline in this study. The brain spontaneous activity alteration was then investigated in fifteen unmedicated first-episode adolescent nsMDDs versus twenty-two healthy controls through the resting-state functional magnetic resonance imaging. Besides the baseline scanning for all participants, the nsMDDs group was scanned again after eight weeks of sertraline therapy to examine the changes after treatment. Results: At pre-treatment, whole brain analysis of mean amplitude of low-frequency fluctuation (mALFF) was performed to examine the neuronal spontaneous activity alteration, and increased mALFF was found in the superior occipital extending to lingual gyrus in adolescent nsMDDs compared with controls. Meanwhile, decreased mALFF was found in the medial superior frontal in adolescent nsMDDs compared with controls. Compared with the pre-treatment, the nsMDDs group was found to have a trend of, respectively, decreased and increased functional neuronal activity at the two brain areas after treatment through the region of interest analysis. Further, whole brain comparison of mALFF at pre-treatment and post-treatment showed significantly decreased spontaneous activity in the orbital middle frontal and lingual gyrus in adolescent nsMDDs after treatment. Also, depression severity was significantly decreased after treatment. Conclusion: The abnormal functional neuronal activity found at frontal and occipital cortex implied cognitive and affective disturbances in adolescent nsMDDs. The trend of upregulation of frontal neuronal activity and downregulation of occipital neuronal activity after sertraline treatment indicated that the therapy could be effective in regulating the abnormality. Notably, the significantly decreased neuronal activity in the decision related orbital middle frontal and anxiety-depression related lingual gyrus could be suggestive of reduced NSSI in adolescent MDD after therapy.

Severity related neuroanatomical and spontaneous functional activity alteration in adolescents with major depressive disorder.

Background: Major depressive disorder (MDD) is a disabling and severe psychiatric disorder with a high rate of prevalence, and adolescence is one of the most probable periods for the first onset. The neurobiological mechanism underlying the adolescent MDD remains unexplored. Methods: In this study, we examined the cortical and subcortical alterations of neuroanatomical structures and spontaneous functional activation in 50 unmedicated adolescents with MDD vs. 39 healthy controls through the combined structural and resting-state functional magnetic resonance imaging. Results: Significantly altered regional gray matter volume was found at broader frontal-temporal-parietal and subcortical brain areas involved with various forms of information processing in adolescent MDD. Specifically, the increased GM volume at the left paracentral lobule and right supplementary motor cortex was significantly correlated with depression severity in adolescent MDD. Furthermore, lower cortical thickness at brain areas responsible for visual and auditory processing as well as motor movements was found in adolescent MDD. The lower cortical thickness at the superior premotor subdivision was positively correlated with the course of the disease. Moreover, higher spontaneous neuronal activity was found at the anterior cingulum and medial prefrontal cortex, and this hyperactivity was also negatively correlated with the course of the disease. It potentially reflected the rumination, impaired concentration, and physiological arousal in adolescent MDD. Conclusion: The abnormal structural and functional findings at cortico-subcortical areas implied the dysfunctional cognitive control and emotional regulations in adolescent depression. The findings might help elaborate the underlying neural mechanisms of MDD in adolescents.

Individuals with problem gambling and obsessive-compulsive disorder learn through distinct reinforcement mechanisms.

Obsessive-compulsive disorder (OCD) and pathological gambling (PG) are accompanied by deficits in behavioural flexibility. In reinforcement learning, this inflexibility can reflect asymmetric learning from outcomes above and below expectations. In alternative frameworks, it reflects perseveration independent of learning. Here, we examine evidence for asymmetric reward-learning in OCD and PG by leveraging model-based functional magnetic resonance imaging (fMRI). Compared with healthy controls (HC), OCD patients exhibited a lower learning rate for worse-than-expected outcomes, which was associated with the attenuated encoding of negative reward prediction errors in the dorsomedial prefrontal cortex and the dorsal striatum. PG patients showed higher and lower learning rates for better- and worse-than-expected outcomes, respectively, accompanied by higher encoding of positive reward prediction errors in the anterior insula than HC. Perseveration did not differ considerably between the patient groups and HC. These findings elucidate the neural computations of reward-learning that are altered in OCD and PG, providing a potential account of behavioural inflexibility in those mental disorders.

Continuum finite element analysis generalizesin vivotrabecular bone microstructural strength measures between two CT scanners with different image resolution.

Fragility of trabecular bone (Tb) microstructure is increased in osteoporosis, which is associated with rapid bone loss and enhanced fracture-risk. Accurate assessment of Tb strength usingin vivoimaging available in clinical settings will be significant for management of osteoporosis and understanding its pathogenesis. Emerging CT technology, featured with high image resolution, fast scan-speed, and wide clinical access, is a promising alternative forin vivoTb imaging. However, variation in image resolution among different CT scanners pose a major hurdle in CT-based bone studies. This paper presents nonlinear continuum finite element (FE) methods for computation of Tb strength fromin vivoCT imaging and evaluates their generalizability between two scanners with different image resolution. Continuum FE-based measures of Tb strength under different loading conditions were found to be highly reproducible (ICC ≥ 0.93) using ankle images of twenty healthy volunteers acquired on low- and high-resolution CT scanners 44.6 ± 2.7 days apart. FE stress propagation was mostly confined to Tb micro-network (2.3 ± 1.7 MPa) with nominal leakages over the marrow space (0.4 ± 0.5 MPa) complying with the fundamental principle of mechanics atin vivoimaging. In summary, nonlinear continuum FE-based Tb strength measures are reproducible among different CT scanners and suitable for multi-site longitudinal human studies.

Quantum mechanical effects in acid-base chemistry.

Acid-base chemistry has immense importance for explaining and predicting the chemical products formed by an acid and a base when mixed together. However, the traditional chemistry theories used to describe acid-base reactions do not take into account the effect arising from the quantum mechanical nature of the acidic hydrogen shuttling potential and its dependence on the acid base distance. Here, infrared and NMR spectroscopies, in combination with first principles simulations, are performed to demonstrate that quantum mechanical effects, including electronic and nuclear quantum effects, play an essential role in defining the acid-base chemistry when 1-methylimidazole and acetic acid are mixed together. In particular, it is observed that the acid and the base interact to form a complex containing a strong hydrogen bond, in which the acidic hydrogen atom is neither close to the acid nor to the base, but delocalized between them. In addition, the delocalization of the acidic hydrogen atom in the complex leads to characteristic IR and NMR signatures. The presence of a hydrogen delocalized state in this simple system challenges the conventional knowledge of acid-base chemistry and opens up new avenues for designing materials in which specific properties produced by the hydrogen delocalized state can be harvested.

Erratum: A chimeric virus-based probe unambiguously detects live circulating tumor cells with high specificity and sensitivity.

[This corrects the article DOI: 10.1016/j.omtm.2021.08.007.].

Automatic Prostate Gleason Grading Using Pyramid Semantic Parsing Network in Digital Histopathology.

Purpose: Prostate biopsy histopathology and immunohistochemistry are important in the differential diagnosis of the disease and can be used to assess the degree of prostate cancer differentiation. Today, prostate biopsy is increasing the demand for experienced uropathologists, which puts a lot of pressure on pathologists. In addition, the grades of different observations had an indicating effect on the treatment of the patients with cancer, but the grades were highly changeable, and excessive treatment and insufficient treatment often occurred. To alleviate these problems, an artificial intelligence system with clinically acceptable prostate cancer detection and Gleason grade accuracy was developed. Methods: Deep learning algorithms have been proved to outperform other algorithms in the analysis of large data and show great potential with respect to the analysis of pathological sections. Inspired by the classical semantic segmentation network, we propose a pyramid semantic parsing network (PSPNet) for automatic prostate Gleason grading. To boost the segmentation performance, we get an auxiliary prediction output, which is mainly the optimization of auxiliary objective function in the process of network training. The network not only includes effective global prior representations but also achieves good results in tissue micro-array (TMA) image segmentation. Results: Our method is validated using 321 biopsies from the Vancouver Prostate Centre and ranks the first on the MICCAI 2019 prostate segmentation and classification benchmark and the Vancouver Prostate Centre data. To prove the reliability of the proposed method, we also conduct an experiment to test the consistency with the diagnosis of pathologists. It demonstrates that the well-designed method in our study can achieve good results. The experiment also focused on the distinction between high-risk cancer (Gleason pattern 4, 5) and low-risk cancer (Gleason pattern 3). Our proposed method also achieves the best performance with respect to various evaluation metrics for distinguishing benign from malignant. Availability: The Python source code of the proposed method is publicly available at https://github.com/hubutui/Gleason. All implementation details are presented in this paper. Conclusion: These works prove that the Gleason grading results obtained from our method are effective and accurate.

Finite element analysis of trabecular bone microstructure using CT imaging and continuum mechanical modeling.

PURPOSE: Osteoporosis is a bone disease associated with enhanced bone loss, microstructural degeneration, and fracture-risk. Finite element (FE) modeling is used to estimate trabecular bone (Tb) modulus from high-resolution three-dimensional (3-D) imaging modalities including micro-computed tomography (CT), magnetic resonance imaging (MRI), and high-resolution peripheral quantitative CT (HR-pQCT). This paper validates an application of voxel-based continuum finite element analysis (FEA) to predict Tb modulus from clinical CT imaging under a condition similar to in vivo imaging by comparing with measures derived by micro-CT and experimental approaches. METHOD: Voxel-based continuum FEA methods for CT imaging were implemented using linear and nonlinear models and applied on distal tibial scans under a condition similar to in vivo imaging. First, tibial axis in a CT scan was aligned with the coordinate z-axis at 150 µm isotropic voxels. FEA was applied on an upright cylindrical volume of interests (VOI) with its axis coinciding with the tibial bone axis. Voxel volume, edge, and vertex elements and their connectivity were defined as per the isotropic image grid. A calibration phantom was used to calibrate CT numbers in Hounsfield unit to bone mineral density (BMD) values, which was then converted into calcium hydroxyapatite (CHA) density. Mechanical properties at each voxel volume element was defined using its ash-density defined on CT-derived CHA density. For FEA, the bottom surface of the cylindrical VOI was fixed and a constant displacement was applied along the z-direction at each vertex element on the top surface to simulate a physical axial compressive loading condition. Finally, a Poisson's ratio of 0.3 was applied, and Tb modulus (MPa) was computed as the ratio of average von Mises stress (MPa) of volume elements on the top surface and the applied displacement. FEA parameters including mesh element size, substep number, and different tolerance values were optimized. RESULTS: CT-derived Tb modulus values using continuum FEA showed high linear correlation with the micro-CT-derived reference values (r ∈ [0.87 0.90]) as well as experimentally measured values (r ∈ [0.80 0.87]). Linear correlation of computed modulus with their reference values using continuum FEA with linear modeling was comparable with that obtained by nonlinear modeling. Nonlinear continuum FEA-based modulus values (mean of 1087.2 MPa) showed greater difference from their reference values (mean of 1498.9 MPa using micro-CT-based FEA) as compared with linear continuum methods. High repeat CT scan reproducibility (intra-class correlation [ICC] = 0.98) was observed for computed modulus values using both linear and nonlinear continuum FEA. It was observed that high stress regions coincide with Tb microstructure as fuzzily characterized by BMD values. Distributions of von Mises stress over Tb microstructure and marrow regions were significantly different (p < 10-8 ). CONCLUSION: Voxel-based continuum FEA offers surrogate measures of Tb modulus from CT imaging under a condition similar to in vivo imaging that alleviates the need for segmentation of Tb and marrow regions, while accounting for bone distribution at the microstructural level. This relaxation of binary segmentation will extend the scope of FEA application to assess mechanical properties of bone microstructure at relatively low-resolution imaging.

Comprehensive characterization of tumor immune landscape following oncolytic virotherapy by single-cell RNA sequencing.

An important mechanism of oncolytic virotherapy in ameliorating cancer immunotherapy is by inducing significant changes in the immune landscape in the tumor microenvironment (TME). Despite this notion and the potential therapeutic implications, a comprehensive analysis of the immune changes in carcinomas induced by virotherapy has not yet been elucidated. We conducted single-cell RNA sequencing analysis on carcinomas treated with an HSV-2-based oncolytic virus to characterize the immunogenic changes in the TME. We specifically analyzed and compared the immune cell composition between viral treated and untreated tumors. We also applied CellChat to analyze the complex interactions among the infiltrated immune cells. Our data revealed significant infiltration of B cells in addition to other important immune cells, including CD4+, CD8+, and NK cells following virotherapy. Further analysis identified distinct subset compositions of the infiltrated immune cells and their activation status upon virotherapy. The intensive interactions among the infiltrated immune cells as revealed by CellChat analysis may further shape the immune landscape in favor of generating antitumor immunity. Our findings will facilitate the design of new strategies in incorporating immunotherapy into virotherapy for clinical translation. Moreover, the significant infiltration of B cells makes it suitable for combining virotherapy with immune checkpoint inhibitors.

Single-cell RNA sequencing reveals a strong connection between Gadd45g upregulation and oncolytic HSV infection in tumor tissue.

The oncolytic effect of virotherapy derives from the intrinsic capability of the applied virus in selectively infecting and killing tumor cells. Although oncolytic viruses of various constructions have been shown to efficiently infect and kill tumor cells in vitro, the efficiency of these viruses to exert the same effect on tumor cells within tumor tissues in vivo has not been extensively investigated. Here we report our studies using single-cell RNA sequencing to comprehensively analyze the gene expression profile of tumor tissues following herpes simplex virus 2-based oncolytic virotherapy. Our data revealed the extent and cell types within the tumor microenvironment that could be infected by the virus. Moreover, we observed changes in the expression of cellular genes, including antiviral genes, in response to viral infection. One notable gene found to be upregulated significantly in oncolytic virus-infected tumor cells was Gadd45g, which is desirable for optimal virus replication. These results not only help reveal the precise infection status of the oncolytic virus in vivo but also provide insight that may lead to the development of new strategies to further enhance the therapeutic efficacy of oncolytic virotherapy.

A chimeric virus-based probe unambiguously detects live circulating tumor cells with high specificity and sensitivity.

The current methods for detecting circulating tumor cells (CTCs) suffer from several drawbacks. We report a novel method that is based on a chimeric virus probe and can detect CTCs with extremely high specificity and sensitivity. Moreover, it exclusively detects live CTCs, and its detection efficacy is not impacted by the variation of epithelial cell adhesion molecule (EpCAM) expression. The chimeric virus probe is composed of a capsid from human papillomavirus that provides the detection with high specificity and an SV40-based genome that can amplify extensively inside CTCs and, hence, endows the detection with high sensitivity. Furthermore, different marker genes can be incorporated into the probe to provide detection with versatility. These unique capabilities will likely improve the validity and utility of this CTC detection in several clinical applications, which is one of the drawbacks suffered by many of the current CTC detection methods.

Co-delivery of novel bispecific and trispecific engagers by an amplicon vector augments the therapeutic effect of an HSV-based oncolytic virotherapy.

BACKGROUND: Although oncolytic virotherapy has shown substantial promises as a new treatment modality for many malignancies, further improvement on its therapeutic efficacy will likely bring more clinical benefits. One plausible way of enhancing the therapeutic effect of virotherapy is to enable it with the ability to concurrently engage the infiltrating immune cells to provide additional antitumor mechanisms. Here, we report the construction and evaluation of two novel chimeric molecules (bispecific chimeric engager proteins, BiCEP and trispecific chimeric engager protein, TriCEP) that can engage both natural killer (NK) and T cells with tumor cells for enhanced antitumor activities. METHODS: BiCEP was constructed by linking orthopoxvirus major histocompatibility complex class I-like protein, which can selectively bind to NKG2D with a high affinity to a mutant form of epidermal growth factor (EGF) that can strongly bind to EGF receptor. TriCEP is similarly constructed except that it also contains a modified form of interleukin-2 that can only function as a tethered form. As NKG2D is expressed on both NK and CD8+ T cells, both of which can thus be engaged by BiCEP and TriCEP. RESULTS: Both BiCEP and TriCEP showed the ability to engage NK and T cells to kill tumor cells in vitro. Coadministration of BiCEP and TriCEP with an oncolytic herpes simplex virus enhanced the overall antitumor effect. Furthermore, single-cell RNA sequencing analysis revealed that TriCEP not only engaged NK and T cells to kill tumor cells, it also promotes the infiltration and activation of these important immune cells. CONCLUSIONS: These novel chimeric molecules exploit the ability of the oncolytic virotherapy in altering the tumor microenvironment with increased infiltration of important immune cells such as NK and T cells for cancer immunotherapy. The ability of BiCEP and TriCEP to engage both NK and T cells makes them an ideal choice for arming an oncolytic virotherapy.

Neutralizing Aptamers Block S/RBD-ACE2 Interactions and Prevent Host Cell Infection.

The receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 spike (S) protein plays a central role in mediating the first step of virus infection to cause disease: virus binding to angiotensin-converting enzyme 2 (ACE2) receptors on human host cells. Therefore, S/RBD is an ideal target for blocking and neutralization therapies to prevent and treat coronavirus disease 2019 (COVID-19). Using a target-based selection approach, we developed oligonucleotide aptamers containing a conserved sequence motif that specifically targets S/RBD. Synthetic aptamers had high binding affinity for S/RBD-coated virus mimics (K D≈7 nM) and also blocked interaction of S/RBD with ACE2 receptors (IC50≈5 nM). Importantly, aptamers were able to neutralize S protein-expressing viral particles and prevent host cell infection, suggesting a promising COVID-19 therapy strategy.

Quantitative CT-Based Methods for Bone Microstructural Measures and Their Relationships With Vertebral Fractures in a Pilot Study on Smokers.

Osteoporosis causes fragile bone, and bone microstructural quality is a critical determinant of bone strength and fracture risk. This study pursues technical validation of novel CT-based methods for assessment of peripheral bone microstructure together with a human pilot study examining relationships between bone microstructure and vertebral fractures in smokers. To examine the accuracy and reproducibility of the methods, repeat ultra-high-resolution (UHR) CT and micro-CT scans of cadaveric ankle specimens were acquired. Thirty smokers from the University of Iowa COPDGene cohort were recruited at their 5-year follow-up visits. Chest CT scans, collected under the parent study, were used to assess vertebral fractures. UHR CT scans of distal tibia were acquired for this pilot study to obtain peripheral cortical and trabecular bone (Cb and Tb) measures. UHR CT-derived Tb measures, including volumetric bone mineral density (BMD), network area, transverse trabecular density, and mean plate width, showed high correlation (r > 0.901) with their micro-CT-derived values over small regions of interest (ROIs). Both Cb and Tb measures showed high reproducibility-intra-class correlation (ICC) was greater than 0.99 for all Tb measures except erosion index and greater than 0.97 for all Cb measures. Female sex was associated with lower transverse Tb density (p < 0.1), higher Tb spacing (p < 0.05), and lower cortical thickness (p < 0.001). Participants with vertebral fractures had significantly degenerated values (p < 0.05) for all Tb measures except thickness. There were no statistically significant differences for Cb measures between non-fracture and fracture groups. Vertebral fracture-group differences of Tb measures remained significant after adjustment with chronic obstructive pulmonary disease (COPD) status. Although current smokers at baseline had more fractures-81.8% versus 63.2% for former smokers-the difference was not statistically significant. This pilot cross-sectional human study demonstrates CT-based peripheral bone microstructural differences among smokers with and without vertebral fractures. © 2021 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Computing the frequency fluctuation dynamics of highly coupled vibrational transitions using neural networks.

The description of frequency fluctuations for highly coupled vibrational transitions has been a challenging problem in physical chemistry. In particular, the complexity of their vibrational Hamiltonian does not allow us to directly derive the time evolution of vibrational frequencies for these systems. In this paper, we present a new approach to this problem by exploiting the artificial neural network to describe the vibrational frequencies without relying on the deconstruction of the vibrational Hamiltonian. To this end, we first explored the use of the methodology to predict the frequency fluctuations of the amide I mode of N-methylacetamide in water. The results show good performance compared with the previous experimental and theoretical results. In the second part, the neural network approach is used to investigate the frequency fluctuations of the highly coupled carbonyl stretch modes for the organic carbonates in the solvation shell of the lithium ion. In this case, the frequency fluctuation predicted by the neural networks shows a good agreement with the experimental results, which suggests that this model can be used to describe the dynamics of the frequency in highly coupled transitions.

Neutralizing Aptamers Block S/RBD-ACE2 Interactions and Prevent Host Cell Infection.

The receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 spike (S) protein plays a central role in mediating the first step of virus infection to cause disease: virus binding to angiotensin-converting enzyme 2 (ACE2) receptors on human host cells. Therefore, S/RBD is an ideal target for blocking and neutralization therapies to prevent and treat coronavirus disease 2019 (COVID-19). Using a target-based selection approach, we developed oligonucleotide aptamers containing a conserved sequence motif that specifically targets S/RBD. Synthetic aptamers had high binding affinity for S/RBD-coated virus mimics (KD ≈7 nM) and also blocked interaction of S/RBD with ACE2 receptors (IC50 ≈5 nM). Importantly, aptamers were able to neutralize S protein-expressing viral particles and prevent host cell infection, suggesting a promising COVID-19 therapy strategy.

Effects of fluoride intake on cortical and trabecular bone microstructure at early adulthood using multi-row detector computed tomography (MDCT).

PURPOSE: The aim of this study was to examine the effects of period-specific and cumulative fluoride (F) intake on bone at the levels of cortical and trabecular bone microstructural outcomes at early adulthood using emerging multi-row detector computed tomography (MDCT)-based novel techniques. METHODS: Ultra-high resolution MDCT distal tibia scans were collected at age 19 visits under the Iowa Bone Development Study (IBDS), and cortical and trabecular bone microstructural outcomes were computed at the distal tibia using previously validated methods. CT scans of a tissue characterization phantom were used to calibrate CT numbers (Hounsfield units) into bone mineral density (mg/cc). Period-specific and cumulative F intakes from birth up to the age of 19 years were assessed for IBDS participants through questionnaire, and their relationships with MDCT-derived bone microstructural outcomes were examined using bivariable and multivariable analyses, adjusting for height, weight, maturity offset (years since age of peak height velocity (PHV)), physical activity (questionnaire for adolescents (PAQ-A)), healthy eating index version 2010 (HEI-2010) scores, and calcium and protein intakes. RESULTS: MDCT distal tibia scans were acquired for 324 participants from among the total of 329 participants at age 19 visits. No motion artifacts were observed in any MDCT scans, and all images were successfully processed to measure cortical and trabecular bone microstructural outcomes. At early adulthood, males were observed to have stronger trabecular bone microstructural features, as well as thicker cortical bone (p < 0.01), as compared to age-similar females; however, females were found to have less cortical bone porosity as compared to males. Among participants with available F intake estimates (75 to 91% of the 324 with MDCT scans, depending on the period-specific F intake measure), no statistically significant associations were detected between any period-specific or cumulative F intake and bone microstructural outcomes of the tibia at the p < 0.01 level. Only for females, statistically suggestive associations (p < 0.05) were found between recent F intake (from 14 to 19 years) and trabecular mean plate width and trabecular thickness at the tibia. Those associations became somewhat weaker, but still statistically suggestive, for trabecular thickness in fully adjusted analysis with height, weight, PHV, calcium and protein intake, and HEI-2010 and PAQ-A scores as covariates. CONCLUSION: The findings show that the effects of lifelong or period-specific F intake from combined sources for adolescents typical to the United States Midwest region are not strongly associated with bone microstructural outcomes at age 19 years. These findings are generally consistent with previously reported results of IBDS analyses, which further confirms that effects of lifelong or period-specific F intake on skeletons in early adulthood are absent or weak, even at the levels of cortical and trabecular bone microstructural details.