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.

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.

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.

An ab initio molecular dynamics study of the solvation structure and ultrafast dynamics of lithium salts in organic carbonates: A comparison between linear and cyclic carbonates.

Carbonate-based lithium-ion electrolytes are of great importance due to their close relationship with the resulting battery efficiency and safety. Modifying the organic electrolyte has been paramount for achieving more efficient and safer lithium-ion batteries. However, the molecular picture of the electrolyte is still under scrutiny. Lately, ultrafast infrared spectroscopic studies have investigated the solvation structure and dynamics of the lithium ion (Li+) in both linear and cyclic carbonates. However, theoretical studies describing the molecular arrangements and transformation occurring in such time scales are scarce. In this study, ab initio molecular dynamics simulations were used to obtain the molecular structure and dynamics of the Li+ solvation shell in cyclic and linear carbonates. The theoretical results showed that molecular arrangement of the carbonates directly coordinating Li+ is not significantly altered by the carbonate chemical nature. However, the cyclic and linear carbonates showed significant different pictures of the overall solvation shell due to the intercalation phenomenon observed for cyclic carbonates, which significantly alters the motions of coordinated solvent. In addition, the intercalation appears to affect the propensity of ion pair formation and/or solvent exchange. Finally, the dynamics of the geometrical changes of the carbonates solvating Li+ is found to occur with characteristic times of tenths of picoseconds, while ion pair and solvent chemical exchange appear to happen in time scales which are at least an order of magnitude larger. Our study provides a comprehensive picture of the structure and dynamics of the molecular components in different carbonate-based lithium-ion electrolytes occurring in picosecond time scales.

Molecular extraction in single live cells by sneaking in and out magnetic nanomaterials.

Extraction of intracellular molecules is crucial to the study of cellular signal pathways. Disruption of the cellular membrane remains the established method to release intracellular contents, which inevitably terminates the time course of biological processes. Also, conventional laboratory extractions mostly use bulky materials that ignore the heterogeneity of each cell. In this work, we developed magnetized carbon nanotubes that can be sneaked into and out of cell bodies under a magnetic force. Using a testing model with overexpression of GFP, the nanotubes successfully transported the intracellular GFP out at the single-cell level. The confined nanoscale invasiveness did not change cell viability or proliferation. This study presents the proof of concept of a previously unidentified real-time and single-cell approach to investigate cellular biology, signal messengers, and therapeutic effects with nanomaterials.

Expression of mouse CD47 on human cancer cells profoundly increases tumor metastasis in murine models.

BACKGROUND: Many commonly used xenograft tumor models do not spontaneously metastasize to distant organs following subcutaneous or orthotopic implantation, limiting their usefulness in preclinical studies. It is generally believed that natural killer cells are the key component of the innate immune system in determining tumor metastatic potential in xenograft models. However, recent studies suggest that macrophages may play an important role, as resident macrophages can eliminate the invading tumor cells if they do not express adequate levels of the CD47 molecule. METHODS: We investigated the effect of overexpressing murine CD47 (mCD47) in PC-3 cells, a commonly used human prostate cancer line, on the metastatic potential in three mouse strains with different genetic background and varying degrees of immunodeficiency. We implanted the tumor cells either subcutaneously or orthotopically and then examined their local and distant metastases. RESULTS: Our results show that mCD47-expressing PC-3 cells subcutaneously implanted in NSG and CB17. Scid mice metastasized to the sentinel lymph node, lung and liver significantly more efficiently than the control cells. When implanted orthotopically to NOD. Scid mice, these cells spontaneously metastasized to lung and liver. CONCLUSIONS: Our data demonstrate that mCD47 can facilitate human tumor cell metastasis in murine models, and that these mCD47-expressing tumor cells may be useful for in vivo studies where spontaneous metastases are desirable.

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.

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.

Genetically modified T cells targeting neovasculature efficiently destroy tumor blood vessels, shrink established solid tumors and increase nanoparticle delivery.

Converting T cells into tumor cell killers by grafting them with a chimeric antigen receptor (CAR) has shown promise as a cancer immunotherapeutic. However, the inability of these cells to actively migrate and extravasate into tumor parenchyma has limited their effectiveness in vivo. Here we report the construction of a CAR containing an echistatin as its targeting moiety (eCAR). As echistatin has high binding affinity to αvß3 integrin that is highly expressed on the surface of endothelial cells of tumor neovasculature, T cells engrafted with eCAR (T-eCAR) can efficiently lyse human umbilical vein endothelial cells and tumor cells that express αvß3 integrin when tested in vitro. Systemic administration of T-eCAR led to extensive bleeding in tumor tissues with no evidence of damage to blood vessels in normal tissues. Destruction of tumor blood vessels by T-eCAR significantly inhibited the growth of established bulky tumors. Moreover, when T-eCAR was codelivered with nanoparticles in a strategically designed temporal order, it dramatically increased nanoparticle deposition in tumor tissues, pointing to the possibility that it may be used together with nanocarriers to increase their capability to selectively deliver antineoplastic drugs to tumor tissues.

Incorporation of the B18R gene of vaccinia virus into an oncolytic herpes simplex virus improves antitumor activity.

Interferon (IFN) antiviral defense mechanism plays a critical role in controlling virus infection. It thus represents a formidable hurdle for virotherapy. Despite the reported ability of herpes simplex virus (HSV) to counteract this defense, the duration and extent of HSV infection in vivo is still largely dictated by host's IFN activity status. Because the HSV genes that have been reported to block IFN activity mainly act intracellularly, we hypothesized that their inhibitory effect could be enhanced by exploiting a gene whose product acts extracellularly. The B18R gene from vaccinia virus encodes a secreted decoy receptor with a broad antagonizing effect against type I IFNs. We therefore cloned B18R into an HSV-1-based oncolytic virus to generate Synco-B18R. In the presence of increased IFN levels in vitro, Synco-B18R largely retained its oncolytic effect, whereas the tumor-killing ability of the parental virus, Synco-2D, was severely compromised. When injected intratumorally in vivo, Synco-B18R showed significantly greater oncolytic activity than Synco-2D. Our results suggest that incorporation of the vaccinia virus B18R gene can safely potentiate the antitumor effect of an oncolytic HSV, and that similar strategies may be useful with other types of oncolytic viruses.

Construction of an oncolytic herpes simplex virus that precisely targets hepatocellular carcinoma cells.

Selective replication in tumor cells is a highly desirable feature for oncolytic viruses. Recent studies have shown that microRNAs (miRNAs) play important roles in controlling gene expression, and that certain tissue-specific miRNAs are frequently downregulated in malignant cells. miR-122 is a liver-specific microRNA. It is abundantly expressed in normal hepatocytes but is absent in many hepatocellular carcinoma (HCC) cells. We hypothesized that expression of an essential viral gene by a liver-specific promoter would initially restrict virus replication to cells of hepatic origin and that adding miR-122 complementary sequences to the viral gene would make the transcripts degradable by miR-122 in normal hepatocytes, thus further confining its replication to HCC. We have constructed such an oncolytic herpes simplex virus by linking the essential viral glycoprotein H gene with the liver-specific apolipoprotein E (apoE)-AAT promoter and by adding the miR-122a complimentary sequence to the 3' untranslated region (3'UTR). To further increase the safety of this virus, complementary sequences from miR-124a and let-7 were also engineered into the same 3'UTR. Designated liver-cancer specific oncolytic virus (LCSOV), it was highly selective in killing HCC cells and in shrinking HCC xenografts. We conclude that LCSOV is a highly specific oncolytic virus that can precisely target HCC.

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.

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.

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.

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.

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.

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.