13 mm; 95% confidence interval [CI] = -0.10-0.35) and control group (MD = 0.14 mm; 95% CI = -0.10-0.37). Most of the roots in the MOP and control groups (42.86% and 52.38%, respectively) showed only mild resorption. Less than 8% of the roots in both groups (7.14% in the MOP group and 4.76% in the control group) showed moderate resorption.
 
  Acceleration of orthodontic tooth movement with adjunctive MOPs therapy during the alignment phase does not exacerbate EARR in patients with moderate crowding of the upper labial segment in comparison with controls.
 Acceleration of orthodontic tooth movement with adjunctive MOPs therapy during the alignment phase does not exacerbate EARR in patients with moderate crowding of the upper labial segment in comparison with controls.
  To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks.
 
  The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesized from cone-beam computed tomography scans (CBCT-PA) were selected as samples. Twenty-three landmarks used for Tweemac analysis were manually identified on all CBCT-PA images by a single examiner. Intra-examiner reproducibility was confirmed by repeating the identification on 85 randomly selected images, which were subsequently set as test data, with a two-week interval before training. For initial learning stage of the multi-stage CNN model, the data from 345 of 430 CBCT-PA images were used, after which the multi-stage CNN model was tested with previous 85 images. The first manual identification on these 85 images was set as a truth ground. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the errors in manual identification and artificial intelligence (AI) prediction.
 
  The AI showed an average MRE of 2.23 ± 2.02 mm with an SDR of 60.88% for errors of 2 mm or lower. However, in a comparison of the repetitive task, the AI predicted landmarks at the same position, while the MRE for the repeated manual identification was 1.31 ± 0.94 mm.
 
  Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.
 Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.It has been confirmed that the new coronavirus SARS-CoV-2 caused the global pandemic of coronavirus disease 2019 (COVID-19). Studies have found that 3-chymotrypsin-like protease (3CLpro) is an essential enzyme for virus replication, and could be used as a potential target to inhibit SARS-CoV-2. In this work, 3CLpro was used as the target to complete the high-throughput virtual screening of the FDA-approved drugs, and Indinavir and other 10 drugs with high docking scores for 3CLpro were obtained. Studies on the binding pattern of 3CLpro and Indinavir found that Indinavir could form the stable hydrogen bond (H-bond) interactions with the catalytic dyad residues His41-Cys145. Binding free energy study found that Indinavir had high binding affinity with 3CLpro. Subsequently, molecular dynamics simulations were performed on the 3CLpro and 3CLpro-Indinavir systems, respectively. The post-dynamic analyses showed that the conformational state of the 3CLpro-Indinavir system transformed significantly and the system tended to be more stable. Moreover, analyses of the residue interaction network (RIN) and H-bond occupancy revealed that the residue-residue interaction at the catalytic site of 3CLpro was significantly enhanced after binding with Indinavir, which in turn inactivated the protein. In short, through this research, we hope to provide more valuable clues against COVID-19.An 87-year-old woman was admitted to our hospital because of speech disturbance and right facio-pharyngo-glosso-masticatory diplegia. She had bronchial asthma, was previously diagnosed with cerebral infarction, had experienced two events of convulsive status epilepticus, and was undergoing treatment with theophylline, levetiracetam, and clopidogrel.  https://www.selleckchem.com/products/aticaprant.html  Head diffusion-weighted magnetic resonance imaging revealed a high-signal area in the left crus posterior capsula interna. For this, we administered cilostazol along with her regular medicines. On day 14, she had tonic-clonic convulsions, extending from the right upper and lower limbs to the whole body. Subsequently, cilostazol was discontinued, and the dose of levetiracetam was increased. However, she developed severe tonic-clonic seizures with right sensory aphasia and right hemiplegia, for which an increased dose of lacosamide was added. When theophylline was discontinued 5 days after the onset of convulsions, the blood concentration of theophylline was 9.7μg/mL. After theophylline was discontinued, tonic-clonic convulsions improved. The disturbance of consciousness and right hemiparesis were improved after one week, while the disturbance of sensory aphasia was improved after one month. We suspect that cerebral infarction may have aggravated the central nervous system damage caused by theophylline, thereby resulting in aminophylline-related non-convulsive status epilepticus. (Received 20 July 2020; Accepted 27 October 2020; Published 1 March 2021).The current therapeutic approach for Parkinson's disease (PD) is mainly dopamine replacement with levodopa and other anti-parkinsonian drugs. As PD progresses, the number of these drugs used steadily increases. Using prescription-based database for 10 or more years up to October 2019, we investigated actual prescribing patterns for anti-parkinsonian drugs in Japan. The main analyses included data from patients continuously prescribed levodopa for 1 or more years (n=16,270), and of these, those continuously prescribed adjuvants to levodopa for 1 or more years (n=3,675). The results showed that the number of anti-parkinsonian drugs, their daily dose frequencies, and the number of tablets increased over time. These trends were observed not only for levodopa but also for adjuvants to levodopa; the number of adjuvants, their daily dose frequencies and number of tablets also increased. As the daily number of tablets increased, the proportion of dopamine agonists increased. Moreover, as the daily dosage of levodopa increased, the daily number of tablets increased for both overall anti-parkinsonian drugs and adjuvants to levodopa.