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Background: Ultrasonography is used to diagnose osteochondritis dissecans (OCD) of the humerus; however, its reliability depends on the technical proficiency of the examiner. Recently, computer-aided diagnosis (CAD) using deep learning has been applied in the field of medical science, and high diagnostic accuracy has been reported. We aimed to develop a deep learning-based CAD system for OCD detection on ultrasound images and to evaluate the accuracy of OCD detection using the CAD system., Methods: The CAD process comprises 2 steps: humeral capitellum detection using an object-detection algorithm and OCD classification using an image classification network. Four-directional ultrasound images of the elbow of the throwing arm of 196 baseball players (mean age, 11.2 years), including 104 players with normal findings and 92 with OCD, were used for training and validation. An external dataset of 20 baseball players (10 with normal findings and 10 with OCD) was used to evaluate the accuracy of the CAD system. A confusion matrix and the area under the receiver operating characteristic curve (AUC) were used to evaluate the system., Results: Clinical evaluation using the external dataset resulted in high AUCs in all 4 directions: 0.969 for the anterior long axis, 0.966 for the anterior short axis, 0.996 for the posterior long axis, and 0.993 for the posterior short axis. The accuracy of OCD detection thus exceeded 0.9 in all 4 directions., Conclusions: We propose a deep learning-based CAD system to detect OCD lesions on ultrasound images. The CAD system achieved high accuracy in all 4 directions of the elbow. This CAD system with a deep learning model may be useful for OCD screening during medical checkups to reduce the probability of missing an OCD lesion., Level of Evidence: Diagnostic Level II . See Instructions for Authors for a complete description of levels of evidence., Competing Interests: Disclosure: This study was supported in part by a research project grant from the Japan Elbow Society (JES202001). The Disclosure of Potential Conflicts of Interest forms are provided with the online version of the article ( http://links.lww.com/JBJS/I13 )., (Copyright © 2024 by The Journal of Bone and Joint Surgery, Incorporated.)

Objective: We evaluated the effect of CHA 2 DS 2 -VASc score and prior use of oral anticoagulants (OACs) on endovascular treatment (EVT) in patients with acute ischemic stroke and atrial fibrillation (AF)., Methods: Patients with AF who received EVT in 353 centers in Japan (2018-2020) were included. The outcomes were symptomatic intracerebral hemorrhage (sICH), in-hospital mortality, functional independence, and successful and complete reperfusion. The effects of CHA 2 DS 2 -VASc score, its components, and prior use of OACs were assessed via a multiple logistic regression model., Results: Of the 6984 patients, 780 (11.2%) used warfarin and 1168 (16.7%) used direct oral anticoagulants (DOACs) before EVT. Based on the CHA 2 DS 2 -VASc score, 6046 (86.6%) presented a high risk (≥2 for males and ≥3 for females) while 938 (13.4%) had intermediate to low risks. Higher CHA 2 DS 2 -VASc scores were associated with increased sICH, in-hospital mortality, and decreased functional independence, regardless of prior OACs. For patients with a high-risk category, prior DOACs increased the odds of successful and complete reperfusion (adjusted odds ratio [95% confidence interval (CI)], 1.27 [1.00-1.61] and 1.30 [1.10-1.53]). For those with integrated intermediate to low risks, neither prior warfarin nor DOAC affected the outcomes. Regardless of total CHA 2 DS 2 -VASc scores, patients with congestive heart failure or left ventricular dysfunction, hypertension, age >75 years, or female benefited similarly from prior DOAC use., Interpretation: Prior DOAC use for patients with high- and selected intermediate-risk CHA 2 DS 2 -VASc scores increased prevalence of successful and complete reperfusion. These findings may provide supplemental evidence to introduce preventive DOAC for patients with AF., (© 2024 The Author(s). Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Purpose: Carotid endarterectomy (CEA) is a surgical treatment for carotid artery stenosis. After CEA, some patients experience cardiovascular events (myocardial infarction, stroke, etc.); however, the prognostic factor has yet to be revealed. Therefore, this study explores the predictive factors in pathological images and predicts cardiovascular events within one year after CEA using pathological images of carotid plaques and patients' clinical data., Method: This paper proposes a two-step method to predict the prognosis of CEA patients. The proposed method first computes the pathological risk score using an anomaly detection model trained using pathological images of patients without cardiovascular events. By concatenating the obtained image-based risk score with a patient's clinical data, a statistical machine learning-based classifier predicts the patient's prognosis., Results: We evaluate the proposed method on a dataset containing 120 patients without cardiovascular events and 21 patients with events. The combination of autoencoder as the anomaly detection model and XGBoost as the classification model obtained the best results: area under the receiver operating characteristic curve, accuracy, sensitivity, specificity, and F1-score were 81.9%, 84.1%, 79.1%, 86.3%, and 76.6%, respectively. These values were superior to those obtained using pathological images or clinical data alone., Conclusion: We showed the feasibility of predicting CEA patient's long-term prognosis using pathological images and clinical data. Our results revealed some histopathological features related to cardiovascular events: plaque hemorrhage (thrombus), lymphocytic infiltration, and hemosiderin deposition, which will contribute to developing preventive treatment methods for plaque development and progression., (© 2024. The Author(s).)

Purpose: Osteochondritis dissecans (OCD) of the humeral capitellum is a common cause of elbow disorders, particularly among young throwing athletes. Conservative treatment is the preferred treatment for managing OCD, and early intervention significantly influences the possibility of complete disease resolution. The purpose of this study is to develop a deep learning-based classification model in ultrasound images for computer-aided diagnosis., Methods: This paper proposes a deep learning-based OCD classification method in ultrasound images. The proposed method first detects the humeral capitellum detection using YOLO and then estimates the OCD probability of the detected region probability using VGG16. We hypothesis that the performance will be improved by eliminating unnecessary regions. To validate the performance of the proposed method, it was applied to 158 subjects (OCD: 67, Normal: 91) using five-fold-cross-validation., Results: The study demonstrated that the humeral capitellum detection achieved a mean average precision (mAP) of over 0.95, while OCD probability estimation achieved an average accuracy of 0.890, precision of 0.888, recall of 0.927, F1 score of 0.894, and an area under the curve (AUC) of 0.962. On the other hand, when the classification model was constructed for the entire image, accuracy, precision, recall, F1 score, and AUC were 0.806, 0.806, 0.932, 0.843, and 0.928, respectively. The findings suggest the high-performance potential of the proposed model for OCD classification in ultrasonic images., Conclusion: This paper introduces a deep learning-based OCD classification method. The experimental results emphasize the effectiveness of focusing on the humeral capitellum for OCD classification in ultrasound images. Future work should involve evaluating the effectiveness of employing the proposed method by physicians during medical check-ups for OCD., (© 2024. The Author(s).)

Vascular calcification affects the prognosis of patients with renal failure. Bisphosphonates are regarded as candidate anti-calcifying drugs because of their inhibitory effects on both calcium-phosphate aggregation and bone resorption. However, calcification in well-known rodent models is dependent upon bone resorption accompanied by excessive bone turnover, making it difficult to estimate accurately the anti-calcifying potential of drugs. Therefore, models with low bone resorption are required to extrapolate anti-calcifying effects to humans. Three bisphosphonates (etidronate, alendronate, and FYB-931) were characterised for their inhibitory effects on bone resorption in vivo and calcium-phosphate aggregation estimated by calciprotein particle formation in vitro. Then, their effects were examined using two models inducing ectopic calcification: the site where lead acetate was subcutaneously injected into mice and the transplanted, aorta obtained from a donor rat. The inhibitory effects of bisphosphonates on bone resorption and calcium-phosphate aggregation were alendronate > FYB-931 > etidronate and FYB-931 > alendronate = etidronate, respectively. In the lead acetate-induced model, calcification was most potently suppressed by FYB-931, followed by alendronate and etidronate. In the aorta-transplanted model, only FYB-931 suppressed calcification at a high dose. In both the models, no correlation was observed between calcification and bone resorption marker, tartrate-resistant acid phosphatase (TRACP). Results from the lead acetate-induced model showed that inhibitory potency against calcium-phosphate aggregation contributed to calcification inhibition. The two calcification models, especially the lead acetate-induced model, may be ideal for the extrapolation of calcifying response to humans because of calcium-phosphate aggregation rather than bone resorption as its mechanism., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Maximizing healthy life expectancy is essential for enhancing well-being. Optimal exercise intensity is crucial in promoting health and ensuring safe rehabilitation. Since heart rate is related to exercise intensity, the required exercise intensity is achieved by controlling the heart rate. This study aims to control heart rate during exercise by dynamically adjusting the load on a bicycle ergometer using a proportional-integral (PI) control. The choice of PI parameters is very important because the PI parameters significantly affect the performance of heart rate control. Since the dynamic characteristics of heart rate relative to work rate vary widely from subject to subject, the PI parameters for each subject must be determined individually. In this study, PI parameters are optimized directly from exercise data using a data-driven design approach. Thus, the proposed method does not require excessive exercise of the subject to model heart rate dynamics. Using the proposed method, the heart rate can be controlled to follow a designed reference model so that the heart rate is safely increased to the desired value. The quantitative evaluation of the control results of fifteen healthy volunteers confirmed that the proposed method improved the control error of the target heart rate trajectory by approximately 40%, regardless of gender or age. In addition, it was shown that control parameters from the exercise experiment also indicate that females are more likely than males to have an elevated heart rate at the same load., (© 2024. The Author(s).)

Pelvic fractures pose significant challenges in medical diagnosis due to the complex structure of the pelvic bones. Timely diagnosis of pelvic fractures is critical to reduce complications and mortality rates. While computed tomography (CT) is highly accurate in detecting pelvic fractures, the initial diagnostic procedure usually involves pelvic X-rays (PXR). In recent years, many deep learning-based methods have been developed utilizing ImageNet-based transfer learning for diagnosing hip and pelvic fractures. However, the ImageNet dataset contains natural RGB images which are different than PXR. In this study, we proposed a two-step transfer learning approach that improved the diagnosis of pelvic fractures in PXR images. The first step involved training a deep convolutional neural network (DCNN) using synthesized PXR images derived from 3D-CT by digitally reconstructed radiographs (DRR). In the second step, the classification layers of the DCNN were fine-tuned using acquired PXR images. The performance of the proposed method was compared with the conventional ImageNet-based transfer learning method. Experimental results demonstrated that the proposed DRR-based method, using 20 synthesized PXR images for each CT, achieved superior performance with the area under the receiver operating characteristic curves (AUROCs) of 0.9327 and 0.8014 for visible and invisible fractures, respectively. The ImageNet-based method yields AUROCs of 0.8908 and 0.7308 for visible and invisible fractures, respectively., (© 2024. The Author(s).)

Introduction: This study sought to identify the optimal caloric intake to improve function and survival in ALS patients by comparing oral intake per ideal body weight (IBW) and its discrepancy with total energy expenditure (TEE) using the Shimizu formula., Methods: A retrospective analysis of 104 ALS patients was conducted, categorizing them based on their average intake during the first week after admission using two primary intake cutoffs: 25 kcal/kgIBW and 30 kcal/kgIBW. The variance between oral intake and TEE was also evaluated using -300 kcal and 0 kcal as reference points., Results: Oral caloric intake per IBW and functional decline rate (rs = -0.35, p  < 0.001), but the variance from TEE was not significantly correlated (-0.11, p  = 0.27). Survival data showed that patients consuming less than 25 kcal/kgIBW had a median survival of 24 months, increasing to 38 months for those consuming between 25-30 kcal/kgIBW and 63 months for those consuming 30 kcal/kgIBW or more. Deviations from the TEE did not significantly affect survival ( p  = 0.36). Among patients consuming less than their TEE, those consuming less than 25 kcal/kgIBW had a shorter median survival (24 months) compared to their counterparts (46 months) ( p  = 0.022). Consumption of less than 25 kcal/kgBW emerged as a significant negative predictor of patient outcome, independent of factors such as age, gender or disease progression., Discussion: Intakes of 25 kcal/kgIBW or more are correlated with improved ALS outcomes, and larger, multi-regional studies are recommended for deeper insights., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Nakamura, Kurihara, Kobashi, Tamaki, Ogawa, Kitamura, Yamakawa, Bamba, Terashima and Urushitani.)

Deep learning techniques for automatically detecting teeth in dental X-rays have gained popularity, providing valuable assistance to healthcare professionals. However, teeth detection in X-ray images is often hindered by alterations in tooth appearance caused by dental prostheses. To address this challenge, our paper proposes a novel method for teeth detection and numbering in dental panoramic X-rays, leveraging two separate CNN-based object detectors, namely YOLOv7, for detecting teeth and prostheses, alongside an optimization algorithm to refine the outcomes. The study utilizes a dataset of 3138 radiographs, of which 2553 images contain prostheses, to build a robust model. The tooth and prosthesis detection algorithms perform excellently, achieving mean average precisions of 0.982 and 0.983, respectively. Additionally, the trained tooth detection model is verified using an external dataset, and six-fold cross-validation is conducted to demonstrate the proposed method's feasibility and robustness. Moreover, the investigation of performance improvement resulting from the inclusion of prosthesis information in the teeth detection process reveals a marginal increase in the average F1-score, rising from 0.985 to 0.987 compared to the sole teeth detection method. The proposed method is unique in its approach to numbering teeth as it incorporates prosthesis information and considers complete restorations such as dental implants and dentures of fixed bridges during the teeth enumeration process, which follows the universal tooth numbering system. These advancements hold promise for automating dental charting processes., (© 2023. Springer Nature Limited.)

Patients with chronic kidney disease develop vascular calcification, owing to impaired calcium and phosphate metabolism. The prevention of vascular calcification is important to improve the prognosis of such patients. In this study, we investigated whether treatment with FYB-931, a novel bisphosphonate compound, prevents vascular calcification in rat aortic rings cultured in high-phosphate medium for 9 days, assessed by measurement of the calcium content and the degree of calcium deposition, visualized using von Kossa staining. The effect on the transformation of calciprotein particles (CPPs) from primary to secondary CPPs was assessed using a fluorescent probe-based flow cytometric assay. FYB-931 dose-dependently prevented high phosphate-induced aortic calcification, but failed to rapidly cause the regression of high phosphate-induced vascular calcification once it had developed. Furthermore, the treatment dose-dependently inhibited the high phosphate-induced transformation from primary to secondary CPPs. In addition, the treatment with FYB-931 prevented the transformation from primary to secondary CPPs in vitamin D 3 -treated rats as a model of ectopic calcification, consistent with the results from rat aortic rings. In conclusion, treatment with FYB-931 prevents high phosphate-induced rat aortic vascular calcification by altering the dynamics of CPP transformation. This finding suggests that inhibition of the transformation from primary to secondary CPPs is an important target for the prevention of vascular calcification in patients with chronic kidney disease., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Diabetic sensorimotor polyneuropathy (DSPN) is a serious long-term complication of diabetes, which may lead to foot ulceration and amputation. Among the screening tools for DSPN, the Michigan neuropathy screening instrument (MNSI) is frequently deployed, but it lacks a straightforward rating of severity. A DSPN severity grading system has been built and simulated for the MNSI, utilizing longitudinal data captured over 19 years from the Epidemiology of Diabetes Interventions and Complications (EDIC) trial. Machine learning algorithms were used to establish the MNSI factors and patient outcomes to characterise the features with the best ability to detect DSPN severity. A nomogram based on multivariable logistic regression was designed, developed and validated. The extra tree model was applied to identify the top seven ranked MNSI features that identified DSPN, namely vibration perception (R), 10-gm filament, previous diabetic neuropathy, vibration perception (L), presence of callus, deformities and fissure. The nomogram's area under the curve (AUC) was 0.9421 and 0.946 for the internal and external datasets, respectively. The probability of DSPN was predicted from the nomogram and a DSPN severity grading system for MNSI was created using the probability score. An independent dataset was used to validate the model's performance. The patients were divided into four different severity levels, i.e., absent, mild, moderate, and severe, with cut-off values of 10.50, 12.70 and 15.00 for a DSPN probability of less than 50, 75 and 100%, respectively. We provide an easy-to-use, straightforward and reproducible approach to determine prognosis in patients with DSPN.

Ectopic calcification in the cardiovascular system adversely affects life prognosis. DBA/2 mice experience calcification owing to low expression of Abcc6 as observed in pseudoxanthoma elasticum (PXE) patients; however, little is known about its characteristics as a calcification model. In this study, we explore the suitability of a DBA/2 sub-strain as a PXE-like tissue calcification model, and the effect of a bisphosphonate which prevents calcification of soft tissues in hypercalcemic models was evaluated. The incidence of calcification of the heart was compared among several sub-strains and between both sexes of DBA/2 mice. mRNA expression of calcification-related genes was compared with DBA/2 sub-strains and other mouse strains. In addition, progression of calcification and calciprotein particle formation in serum were examined. Among several sub-strains of DBA/2 mice, male DBA/2CrSlc mice showed the most remarkable cardiac calcification. In DBA/2CrSlc mice, expression of the anti-calcifying genes Abcc6, Enpp1 and Spp1 was lower than that in C57BL/6J, and expression of Enpp1 and Spp1 was lower compared with other sub-strains. Calcification was accompanied by accelerated formation of calciprotein particle, which was prevented by daily treatment with bisphosphonate. A model suitable for ectopic calcification was identified by choosing a sub-strain of DBA/2 mice, in which genetic characteristics would contribute to extended calcification.

Background Aims: Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease. Neuroinflammation in the spinal cord plays a pivotal role in the pathogenesis of ALS, and microglia are involved in neuroinflammation. Microglia mainly have two opposite phenotypes involving cytotoxic and neuroprotective properties, and neuroprotective microglia are expected to be a novel application for the treatment of ALS. Therefore, to establish a clinically applicable therapeutic method using neuroprotective microglia, the authors investigated the effect of inducing neuroprotective microglia-like cells from bone marrow for transplantation into ALS model mice., Methods: Bone marrow-derived mononuclear cells were isolated from green fluorescent protein mice and cultured using different protocols of cytokine treatment with granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-4. Cells with a high potency of proliferation and differentiation into microglia were evaluated by gene analysis, flow cytometry and direct neuroprotective effects in vitro. These cells were named bone marrow-derived inducible microglia-like (BM-iMG) cells and transplanted into the spinal cords of ALS model mice, and behavioral tests, immunohistochemistry and gene expression profiling were performed., Results: Three-day GM-CSF and 4-day GM-CSF + IL-4 stimulations were most effective in inducing BM-iMG cells from the bone marrow. Transplantation of BM-iMG cells improved motor function, prolonged survival and suppressed neuronal cell death, astrogliosis and microgliosis in the spinal cords of ALS mice. Moreover, neuroprotective genes such as Arg1 and Mrc1 were upregulated, whereas pro-inflammatory genes such as Nos2 and Il6 were downregulated., Conclusions: Intraspinal transplantation of BM-iMG cells demonstrated therapeutic effects in a mouse model of ALS. Further studies and clinical applications in patients with ALS are expected in the future., Competing Interests: Declaration of Competing Interest The authors have no commercial, proprietary or financial interest in the products or companies described in this article., (Copyright © 2022 International Society for Cell & Gene Therapy. Published by Elsevier Inc. All rights reserved.)

Background: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques used for DSPN, however, it does not provide any direct severity grading system., Method: For designing and modeling the DSPN severity grading systems for MNSI, 19 years of data from Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials were used. Different Machine learning-based feature ranking techniques were investigated to identify the important MNSI features associated with DSPN diagnosis. A multivariable logistic regression-based nomogram was generated and validated for DSPN severity grading using the best performing top-ranked MNSI features., Results: Top-10 ranked features from MNSI features: Appearance of Feet (R), Ankle Reflexes (R), Vibration perception (L), Vibration perception (R), Appearance of Feet (L), 10-gm filament (L), Ankle Reflexes (L), 10-gm filament (R), Bed Cover Touch, and Ulceration (R) were identified as important features for identifying DSPN by Multi-Tree Extreme Gradient Boost model. The nomogram-based prediction model exhibited an accuracy of 97.95% and 98.84% for the EDIC test set and an independent test set, respectively. A DSPN severity score technique was generated for MNSI from the DSPN severity prediction model. DSPN patients were stratified into four severity levels: absent, mild, moderate, and severe using the cut-off values of 17.6, 19.1, 20.5 for the DSPN probability less than 50%, 75%-90%, and above 90%, respectively., Conclusions: The findings of this work provide a machine learning-based MNSI severity grading system which has the potential to be used as a secondary decision support system by health professionals in clinical applications and large clinical trials to identify high-risk DSPN patients., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Dotinurad, a novel selective urate reabsorption inhibitor, is used to treat hyperuricemia. In humans, orally administered dotinurad is excreted mainly as glucuronide and sulfate conjugates in urine. To identify the isoforms of UDP-glucuronosyltransferase (UGT) and sulfotransferase (SULT) involved in dotinurad glucuronidation and sulfation, microsome and cytosol fractions of liver, intestine, kidney, and lung tissues (cytosol only) were analyzed along with recombinant human UGT and SULT isoforms. Dotinurad was mainly metabolized to its glucuronide conjugate by human liver microsomes (HLMs), and the glucuronidation followed the two-enzyme Michaelis-Menten equation. Among the recombinant human UGT isoforms expressed in the liver, UGT1A1, UGT1A3, UGT1A9, and UGT2B7 catalyzed dotinurad glucuronidation. Based on inhibition analysis using HLMs, bilirubin, imipramine, and diflunisal decreased glucuronosyltransferase activities by 45.5%, 22.3%, and 22.2%, respectively. Diflunisal and 3'-azido-3'-deoxythymidine, in the presence of 1% bovine serum albumin, decreased glucuronosyltransferase activities by 21.1% and 13.4%, respectively. Dotinurad was metabolized to its sulfate conjugate by human liver cytosol (HLC) and human intestinal cytosol (HIC) samples, with the sulfation reaction in HLC samples following the two-enzyme Michaelis-Menten equation and that in HIC samples following the Michaelis-Menten equation. All eight recombinant human SULT isoforms used herein catalyzed dotinurad sulfation. Gavestinel decreased sulfotransferase activity by 15.3% in HLC samples, and salbutamol decreased sulfotransferase activity by 68.4% in HIC samples. These results suggest that dotinurad glucuronidation is catalyzed mainly by UGT1A1, UGT1A3, UGT1A9, and UGT2B7, whereas its sulfation is catalyzed by many SULT isoforms, including SULT1B1 and SULT1A3. SIGNIFICANCE STATEMENT: The identification of enzymes involved in drug metabolism is important to predicting drug-drug interactions (DDIs) and interindividual variability for safe drug use. The present study revealed that dotinurad glucuronidation is catalyzed mainly by UGT1A1, UGT1A3, UGT1A9, and UGT2B7 and that its sulfation is catalyzed by many SULT isoforms, including SULT1B1 and SULT1A3. Therefore, dotinurad, a selective urate reabsorption inhibitor, is considered safe for use with a small risk of DDIs and low interindividual variability., (Copyright © 2021 The Author(s).)

Objective: Ectopic calcification such as vascular calcification, involves the formation of calciprotein particle (CPP), that is, colloidal particle of calcium phosphate bound to serum protein. In this study, a novel parameter for CPP formation was introduced, thereby the effect of FYB-931, a bisphosphonate compound was evaluated., Methods: CPP formation in rat serum was assessed by the area under the curve (AUC) of the change in absorbance over time, and the commonly used T50, as indices. In vivo, the rats were treated with vitamin D3 to induce vascular calcification and then intravenously administered FYB-931 or etidronate thrice weekly for 2 weeks., Key Findings: In vitro, FYB-931 was the most potent inhibitor of CPP formation and it also inhibited the maximum response of CPP formation at higher concentrations. The AUC of the change in absorbance provided obvious dose-dependency, while T50 did not. FYB-931 dose-dependently prevented aortic calcification in vivo as well as CPP formation ex vivo more potently than etidronate. AUC showed a stronger correlation with the degree of aortic calcification than T50., Conclusions: The AUC in CPP formation can be an alternative parameter that reflects calcification. Based on the findings, FYB-931 has potential as an anti-calcifying agent., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Royal Pharmaceutical Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death within 1 year of fracture. This study proposes an automated method to detect pelvic fractures on 3-dimensional computed tomography (3D-CT). Deep convolutional neural networks (DCNNs) have been used for lesion detection on 2D and 3D medical images. However, training a DCNN directly using 3D images is complicated, computationally costly, and requires large amounts of training data. We propose a method that evaluates multiple, 2D, real-time object detection systems (YOLOv3 models) in parallel, in which each YOLOv3 model is trained using differently orientated 2D slab images reconstructed from 3D-CT. We assume that an appropriate reconstruction orientation would exist to optimally characterize image features of bone fractures on 3D-CT. Multiple YOLOv3 models in parallel detect 2D fracture candidates in different orientations simultaneously. The 3D fracture region is then obtained by integrating the 2D fracture candidates. The proposed method was validated in 93 subjects with bone fractures. Area under the curve (AUC) was 0.824, with 0.805 recall and 0.907 precision. The AUC with a single orientation was 0.652. This method was then applied to 112 subjects without bone fractures to evaluate over-detection. The proposed method successfully detected no bone fractures in all except 4 non-fracture subjects (96.4%).

Although benzbromarone (BBR) is a conventional, highly potent uricosuric drug, it is not a standard medicine because it causes rare but fatal fulminant hepatitis. We transformed the bis-aryl ketone structure of BBR to generate novel monocyclic amide-linked phenol derivatives that should possess uric acid excretion activity without adverse properties associated with BBR. The derivatives were synthesized and tested for uric acid uptake inhibition (UUI) in two assays using either urate transporter 1-expressing cells or primary human renal proximal tubule epithelial cells. We also evaluated their inhibitory activity against mitochondrial respiration as a critical mitochondrial toxicity parameter. Some derivatives with UUI activity had no mitochondrial toxicity, including compound 3f, which effectively lowered the plasma uric acid level in Cebus apella. Thus, 3f is a promising candidate for further development as a uricosuric agent., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: During baseball pitching, a high amount of elbow varus torque in the arm cocking-to-acceleration phase is thought to be a biomechanical risk factor for medial elbow pain and injury. The biomechanics of the stride phase may provide preparation for the arm cocking-to-acceleration phase that follows it., Purpose: To determine the kinematic parameters that predict peak elbow varus torque during the stride phase of pitching., Study Design: Descriptive laboratory study., Methods: Participants were 107 high school baseball pitchers (age range, 15-18 years) without shoulder or elbow problems. Whole-body kinematics and kinetics during fastball pitching were analyzed using 3-dimensional measurements from 36 retroreflective markers. A total of 26 kinematic parameters of the upper and lower limbs during the stride phase leading up to the stride foot contact were extracted for multiple regression analysis to assess their combined effect on the magnitude of peak elbow varus torque., Results: Increased wrist extension, elbow pronation, knee flexion on the leading leg, knee extension on the trailing leg at stride foot contact, and upward displacement of the body's center of mass in the stride phase were significantly correlated with decreased peak elbow varus torque (all P < .05). Moreover, 38% of the variance in peak elbow varus torque was explained by a combination of these 5 significant kinematic variables ( P < .001)., Conclusion: We found that 5 kinematic parameters during the stride phase and the combination of these parameters were associated with peak elbow varus torque. The stride phase provides biomechanical preparation for pitching and plays a key role in peak elbow varus torque in subsequent pitching phases., Clinical Relevance: The present data can be used to screen pitching mechanics with motion capture assessment to reduce peak elbow varus torque. Decreased peak elbow varus torque is expected to reduce the risk of elbow medial pain and injury., Competing Interests: The authors declared that there are no conflicts of interest in the authorship and publication of this contribution. AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto., (© The Author(s) 2020.)

Computer-assisted analysis of dental radiograph in dentistry is getting increasing attention from the researchers in recent years. This is mainly because it can successfully reduce human-made error due to stress, fatigue or lack of experience. Furthermore, it reduces diagnosis time and thus, improves overall efficiency and accuracy of dental care system. An automatic teeth recognition model is proposed here using residual network-based faster R-CNN technique. The detection result obtained from faster R-CNN is further refined by using a candidate optimization technique that evaluates both positional relationship and confidence score of the candidates. It achieves 0.974 and 0.981 mAPs for ResNet-50 and ResNet-101, respectively with faster R-CNN technique. The optimization technique further improves the results i.e. F 1 score improves from 0.978 to 0.982 for ResNet-101. These results verify the proposed method's ability to recognize teeth with high degree of accuracy. To test the feasibility and robustness of the model, a tenfold cross validation (CV) is presented in this paper. The result of tenfold CV effectively verifies the robustness of the model as the average F 1 score obtained is more than 0.970. Thus, the proposed model can be used as a useful and reliable tool to assist dental care professionals in dentistry.

Several treatments have been attempted in amyotrophic lateral sclerosis (ALS) animal models and patients. Recently, transplantation of bone marrow-derived mononuclear cells (MNCs) was investigated as a regenerative therapy for ALS, but satisfactory treatments remain to be established. To develop an effective treatment, we focused on mesenchymal stem cells (MSCs) expressing hepatocyte growth factor, glial cell line-derived neurotrophic factor, and insulin-like growth factor using human artificial chromosome vector (HAC-MSCs). Here, we demonstrated the transplantation of MNCs with HAC-MSCs in ALS mice. As per our results, the progression of motor dysfunction was significantly delayed, and their survival was prolonged dramatically. Additional analysis revealed preservation of motor neurons, suppression of gliosis, engraftment of numerous MNCs, and elevated chemotaxis-related cytokines in the spinal cord of treated mice. Therefore, growth factor-expressing MSCs enhance the therapeutic effects of bone marrow-derived MNCs for ALS and have a high potential as a novel cell therapy for patients with ALS., Competing Interests: The authors declare no competing interests., (© 2020 The Author(s).)

To derive new uricosuric agents, novel phenol derivatives were synthesized to overcome the disadvantages of benzbromarone (BBR), attributed by its structural features. Herein, we report the discovery of new phenol derivatives with a 1,1-dioxo-1,2-dihydro-3 H -1,3-benzothiazole scaffold. The selected compound 11 (dotinurad, FYU-981) demonstrated remarkable inhibitory activity on uric acid uptake by primary human renal proximal tubule epithelial cells (RPTECs) and URAT1-mediated uric acid transport, with weak inhibitory activity against mitochondrial respiration. Dotinurad also displayed favorable pharmacokinetic profiles and higher potency in decreasing uric acid than BBR did in Cebus monkeys. Dotinurad has been approved as a new uricosuric medicine in Japan. Our strategy, which focuses on the structural features resulting in unfavorable effects, could be applied to the future developments of other drugs with disadvantages, particularly those having a bis-aryl ketone structure., Competing Interests: The authors declare no competing financial interest.

Dotinurad, a novel selective urate reabsorption inhibitor (SURI), has potent inhibitory effects at low doses on the uptake of urate by urate transporter 1 (URAT1, solute carrier family 22 member 12 [SLC22A12]), localized at the apical membrane of renal proximal tubular cells. This study sought to clarify the pharmacokinetic (PK) profile of dotinurad. In rats, monkeys, and humans, the apparent distribution volume (0.257, 0.205, and 0.182 L/kg, respectively) and oral clearance (0.054, 0.037, and 0.013 L·h -1 ·kg -1 , respectively) of dotinurad were very low, whereas plasma and luminal concentrations were adequately maintained at high levels. In addition, species differences were scarcely observed with plasma protein binding of 99.4%. The main metabolite was dotinurad glucuronide (no specific metabolites in humans), and percentage excretion of unchanged dotinurad was low in all the investigated species. The risk of drug interaction with dotinurad was expected to be low, because it weakly inhibits metabolic enzymes such as cytochrome P450 (CYP). In conclusion, low-dose dotinurad exhibited excellent pharmacological effects as well as ideal PK properties as a SURI., Competing Interests: Declaration of competing interest Financial support for the present study was provided by FUJI YAKUHIN CO., LTD. All authors are employees of FUJI YAKUHIN CO., LTD., (Copyright © 2020 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.)

Despite the poor prognosis of spinal cord injury (SCI), effective treatments are lacking. Diverse factors regulate SCI prognosis. In this regard, microglia play crucial roles depending on their phenotype. The M1 phenotype exacerbates neuroinflammation, whereas the M2 phenotype promotes tissue repair and provides anti-inflammatory effects. Therefore, we compared the effects of M2 and M1 microglia transplantation on SCI. First, we established a method for effective induction of M1 or M2 microglia by exposure to granulocyte-macrophage colony-stimulating factor (GM-CSF) or interleukin (IL)-4, respectively, to be used for transplantation in a SCI mouse model. In the M2 microglia transplantation group, significant recovery of motor function was observed compared with the control and M1 groups. Elevated transcription of several neuroprotective molecules including mannose receptor C type 1 (Mrc1), arginase 1 (Arg1), and insulin-like growth factor 1 (Igf1) was observed. Moreover, intramuscular injection of FluoroRuby dye revealed recovery of retrograde axonal transport from the neuromuscular junction to upstream of the injured spinal cord only in the M2-transplanted group, although the number of migrated microglia were comparable in both M1 and M2 groups. In conclusion, our results indicated that M2 microglia obtained by IL-4 stimulation may be a promising candidate for cell transplantation therapy for SCI., (Copyright © 2019 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.)

Background: Anterior cruciate ligament (ACL) injury causes knee instability which affects sports activity involving cutting and twisting motions. The ACL reconstruction surgery replaces the damaged ACL with artificial one which is fixed to the bone tunnels opened by the surgeon. The outcome of the ACL reconstruction is strongly related to the placement of the bone tunnels, therefore, the optimization of tunnel drilling technique is an important factor to obtain satisfactory surgical results., Aims: The quadrant method is used for the post-operative evaluation of the ACL reconstruction surgery, which evaluates the bone tunnel opening sites on the lateral 2D X-ray radiograph., Methods: For the purpose of applying the quadrant method to the pre-operative knee MRI, we have synthesized the pseudo lateral 2D X-ray radiograph from the patients' knee MRI. This paper proposes a computer-aided surgical planning system for the ACL reconstruction. The proposed system estimates appropriate bone tunnel opening sites on the pseudo lateral 2D X-ray radiograph synthesized from the pre-operative knee MRI., Results: In the experiment, the proposed method was applied to 98 subjects including subjects with osteoarthritis. The experimental results showed that the proposed method can estimate the bone tunnel opening sites accurately. The other experiment using 36 healthy patients showed that the proposed method is robust to the knee shape deformation caused by disease., Conclusion: It is verified that the proposed method can be applied to subjects with osteoarthritis., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: This study presents a novel method of constructing a spatiotemporal statistical shape model (st-SSM) for adult brain. St-SSM is an extension of statistical shape model (SSM) in the temporal domain which will represent the statistical variability of shape as well as the temporal change of statistical variance with respect to time., Aims: Expectation-Maximization (EM) based weighted principal component analysis (WPCA) using a temporal weight function is applied where the eigenvalues of each data are estimated by Estep using temporal eigenvectors, and M-step updates Eigenvectors in order to maximize the variance. Both E and M-step are iterated until updating vectors reaches the convergence point. A weight parameter for each subject is allocated in accordance with the subject's age to calculate the weighted variance. A Gaussian function is utilized to define the weight function. The center of the function is a time point while the variance is a predefined parameter., Methods: The proposed method constructs adult brain st-SSM by changing the time point between minimum to maximum age range with a small interval. Here, the eigenvectors changes with aging. The feature vector of representing adult brain shape is extracted through a level set algorithm. To validate the method, this study employed 103 adult subjects (age: 22 to 93 y.o. with Mean ± SD = 59.32±16.89) from OASIS database. st-SSM was constructed for time point 40 to 90 with a step of 2., Results: We calculated the temporal deformation change between two-time points and evaluated the corresponding difference to investigate the influence of analysis parameter. An application of the proposed model is also introduced which involves Alzheimer's disease (AD) identification utilizing support vector machine., Conclusion: In this study, st-SSM based adult brain shape feature extraction and classification techniques are introduced to classify between normal and AD subject as an application., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

In patients with chronic kidney disease (CKD) or those undergoing hemodialysis, pathological calcific deposition known as ectopic calcification occurs in soft tissue, resulting in a life-threatening disorder. A potent and effective inhibitor of ectopic calcification is eagerly expected. In the current study, the effects of FYB-931, a novel bisphosphonate compound synthesized for the prevention of ectopic calcification, were compared with those of etidronate using both in vitro and in vivo models. In vitro, FYB-931 inhibited calcification of human aortic smooth muscle cells induced by high phosphate medium in a concentration-dependent manner, and the effect was slightly more potent than that of etidronate. In vivo, rats were administered with three subcutaneous injections of vitamin D3 to induce vascular calcification, and were given FYB-931 (1.5, 5, or 10 mg/kg) or etidronate (9, 30, or 60 mg/kg) orally once daily for 14 days. The increased aortic phosphorus content as an index of vascular calcification was inhibited by both FYB-931 and etidronate in a dose-dependent manner; however, FYB-931 was 10 times more potent than etidronate. FYB-931 inhibited serum tartrate-resistant acid phosphatase (TRACP) activity as a bone resorption marker 5.2 times more potently than etidronate. FYB-931, but not etidronate, significantly decreased serum phosphorus levels. The preferential inhibition of aortic calcification by FYB-931 suggested that possible additional effect including a decline in serum phosphorus may lead to an advantage in terms of its efficacy.