Prevalence of concha bullosa in a pediatric population.

OBJECTIVE: Existing literature on the prevalence of middle turbinate pneumatization, or concha bullosa (CB), in the pediatric population is limited. CB is an anatomic variant important to identify prior to sinonasal surgery and is often associated with congenital nasal septal deviation (SD). This paper aims to describe the prevalence of CB in the pediatric population on head imaging. METHODS: A retrospective chart review was performed for 695 children undergoing CT head for trauma from 2021 to 2022. Nearly equal numbers of males and females were evaluated, with at least 19-20 per year from 0.5 to 18 years. Patients with significant facial fractures, sinusitis, craniofacial syndromes, prior sinus surgery, and sinonasal masses were excluded. Two pediatric neuroradiologists evaluated the CTs. CB was defined as aeration >50 % of the vertical height of the middle turbinate. RESULTS: In this study, 384 patients were included. The prevalence of CB was 153 (39.8 %), which was significantly higher in children >4 years (p < 0.0001). Lamellar type CB was the most common, present in 160 out of 768 middle turbinates assessed (20.8 %). SD occurred in 60 (39.2 %) patients with CB and was more commonly contralateral to the CB. CONCLUSIONS: The prevalence of CB in the pediatric population is at the lower range of what is reported in the adult literature. The most common type of CB in patients is lamellar. Similar to previous studies, there is an association between CB and contralateral SD. Finally, there is a positive correlation between the severity of CB and the severity of SD.

Building Frontline Capability for Shared Decision-Making (SDM) in a Major Academic Oncology Center Caring for People With Non-Small Cell Lung Cancer: Performance Outcomes of a SDM Simulation Training Program.

BACKGROUND: There is a growing body of evidence on shared decision-making (SDM) training programs worldwide. However, there is wide variation in program design, duration, effectiveness, and evaluation in both academia (ie, medical school) and the practice setting. SDM training has been slow to integrate in practice settings. METHODS: A pilot study of 6 multidisciplinary clinicians was conducted using quantitative and qualitative methods to evaluate changes in participant understanding and implementation of SDM in the practice setting. A 2-rater criterion-based evaluation method was used to assess a simulation-based case study role-play program using 7 domains of SDM pre and post training. The authors assessed whether clinicians addressed each of the 7 domains or what fraction of each domain was addressed as part of their simulation case study role-play performance. Focus groups were conducted pre- and postintervention to provide feedback to participants and to understand the clinician experience in greater detail. RESULTS: The increase in improvement in SDM ranged from 17% to 37%, and 7 of 8 domains for which participants were rated showed significant improvement. The areas of greatest improvement were seen in determining a patient's goals/preferences, including risk tolerance regarding treatments (+37%) and values and self-efficacy (+37%). CONCLUSION: The results of this study reveal a significant shift in clinician awareness of a patient's goals, preferences, and values. Postintervention, clinicians began to understand the value of building a partnership with their patients whereby the patient becomes an active participant in their clinical care.

A Comparison of In-Person and Telemedicine Triage in Otolaryngology.

INTRODUCTION: The integration of virtual visits has been met with skepticism by many surgical specialties, including otolaryngology, due to the lack of a complete physical exam. Analysis of differences in the workup between patients triaged virtually or in-person is warranted. METHODS: A chart review was performed for a cohort of adults undergoing septoplasty (January 2021-May 2022). Groups (telemedicine, in-person) were compared by 2-sample t-test and chi-square test to determine the difference in the number of preoperative visits and to assess the variation in patients with preoperative laboratory testing, imaging, or referrals. RESULTS: Of 338 patients, initial evaluation was in-person for 225 (66.5%) and via telemedicine for 113 (33.5%). The groups were similar in demographics (mean age 39.1 years for telemedicine vs 38.8 years for in-person, female 28.9% vs male 37.7%, P = 0.088). The telemedicine group had a significantly higher number of preoperative visits (3.03) compared to the in-person group (2.38, P = 0.001). There was no significant difference in patients who underwent preoperative laboratory testing, imaging, or referrals. Patients triaged via telemedicine experienced a shorter time to surgery compared to those triaged in person (434 vs 208, P = 0.003). DISCUSSION: In this cohort, triage by telemedicine allowed otolaryngology patients to have an expedited path to surgery despite having more visits. There is no evidence to suggest that otolaryngologists had an overreliance on diagnostic modalities when triaging by telemedicine. CONCLUSION: Among patients undergoing septoplasty, those initially evaluated by telemedicine were more likely to have more preoperative visits and shorter time to surgery than those evaluated in person. Telemedicine can serve as an effective method for triaging surgical patients without excess diagnostics.

Decoupling and predicting natural gas deviation factor using machine learning methods.

Accurately predicting the deviation factor (Z-factor) of natural gas is crucial for the estimation of natural gas reserves, evaluation of gas reservoir recovery, and assessment of natural gas transport in pipelines. Traditional machine learning algorithms, such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Artificial Neural Network (ANN) and Bidirectional Long Short-Term Memory Neural Networks (BiLSTM), often lack accuracy and robustness in various situations due to their inability to generalize across different gas components and temperature-pressure conditions. To address this limitation, we propose a novel and efficient machine learning framework for predicting natural gas Z-factor. Our approach first utilizes a signal decomposition algorithm like Variational Mode Decomposition (VMD), Empirical Fourier Decomposition (EFD) and Ensemble Empirical Mode Decomposition (EEMD) to decouple the Z-factor into multiple components. Subsequently, traditional machine learning algorithms is employed to predict each decomposed Z-factor component, where combination of SVM and VMD achieved the best performance. Decoupling the Z-factors firstly and then predicting the decoupled components can significantly improve prediction accuracy of all traditional machine learning algorithms. We thoroughly evaluate the impact of the decoupling method and the number of decomposed components on the model's performance. Compared to traditional machine learning models without decomposition, our framework achieves an average correlation coefficient exceeding 0.99 and an average mean absolute percentage error below 0.83% on 10 datasets with different natural gas components, high temperatures, and pressures. These results indicate that hybrid model effectively learns the patterns of Z-factor variations and can be applied to the prediction of natural gas Z-factors under various conditions. This study significantly advances methodologies for predicting natural gas properties, offering a unified and robust solution for precise estimations, thereby benefiting the natural gas industry in resource estimation and reservoir management.

Supreme Constitutional Court review of the legislative omission in Egypt in light of international experiences.

This study examined the concept of legislative omission and distinguished it from several similar concepts. It also showed the reasons for its occurrence and analyzed the conditions that must be met for the phenomenon to be considered a legislative omission. Furthermore, the study reviewed some international experiences related to the judicial constitutional oversight of the practice of legislative omission. The study concluded that some countries regulate constitutional judicial review over legislative omission by the provisions of the constitution and other countries by the provisions of the law.

The Application of Mask Region-Based Convolutional Neural Networks in the Detection of Nasal Septal Deviation Using Cone Beam Computed Tomography Images: Proof-of-Concept Study.

BACKGROUND: Artificial intelligence (AI) models are being increasingly studied for the detection of variations and pathologies in different imaging modalities. Nasal septal deviation (NSD) is an important anatomical structure with clinical implications. However, AI-based radiographic detection of NSD has not yet been studied. OBJECTIVE: This research aimed to develop and evaluate a real-time model that can detect probable NSD using cone beam computed tomography (CBCT) images. METHODS: Coronal section images were obtained from 204 full-volume CBCT scans. The scans were classified as normal and deviated by 2 maxillofacial radiologists. The images were then used to train and test the AI model. Mask region-based convolutional neural networks (Mask R-CNNs) comprising 3 different backbones-ResNet50, ResNet101, and MobileNet-were used to detect deviated nasal septum in 204 CBCT images. To further improve the detection, an image preprocessing technique (contrast enhancement [CEH]) was added. RESULTS: The best-performing model-CEH-ResNet101-achieved a mean average precision of 0.911, with an area under the curve of 0.921. CONCLUSIONS: The performance of the model shows that the model is capable of detecting nasal septal deviation. Future research in this field should focus on additional preprocessing of images and detection of NSD based on multiple planes using 3D images.

A hierarchical residual correction-based hyperspectral inversion method for soil heavy metals considering spatial heterogeneity.

Promising hyperspectral remote sensing exhibits substantial potential in monitoring soil heavy metal (SHM) contamination. Nevertheless, the local spatial perturbation effects induced by environmental factors introduce considerable variability in SHM distribution. This engenders non-stationary relationship between SHM concentrations and spectral reflectance, posing challenges for accurate inversion of SHM globally. Addressing this gap, a novel Hierarchical Residual Correction-based Hyperspectral Inversion Method (HRCHIM) is proposed for SHM, considering their spatial heterogeneity. Initially, a global model is constructed using ground hyperspectral data to predict SHM concentration, capturing overarching contamination trends. Subsequently, four hierarchical levels, segmented by residual standard deviation (SD) intervals, identify critical environmental factors via Geodetector. These factors inform local residual correction models, refining global model predictions. HRCHIM aims to synergize global trends and local stochasticity to enhance prediction accuracy and interpretation of SHM spatial heterogeneity. Validated through a case study of a Cadmium(Cd)-contaminated mine area, six critical environmental factors were identified, exhibiting significant differences across hierarchical levels. By incorporating hierarchical correction models, HRCHIM demonstrated superior inversion performance compared to other conventional methods, achieving optimal prediction accuracies (Rv2 = 0.94, RMSEv = 0.21, and RPDv = 4.11). This innovative method can facilitate more precise and targeted strategies for preventing and controlling SHM contamination.

Validating genomic predictions for economic traits in purebred U.S. dairy heifers.

Most genotypes in the National Cooperator Database now originate from cows, but most previous studies validating genomic predictions have primarily focused on bulls. This study paired official within-breed genomic predicted transmitting ability (GPTA) and parent average (PA) for genotyped heifer calves born between 2019 and 2021 using the August 2021 database with their corresponding performance deviations (PDEV) for 17 different traits. The PDEV data became available when the heifers completed their first lactation and were extracted from the August 2023 database in which at least one PDEV value for those 17 traits existed for each genotyped heifer record. The separate breed analyses included records for 219 Ayrshires (AY), 2,715 Brown Swiss (BS), 1,055 Guernseys (GU), 949,904 Holsteins (HO), and 125,275 Jerseys (JE). These validation cows were heifer calves born between 2019 and 2021. However, due to timing or recording patterns, each trait had missing or incomplete PDEV data, leading to unbalanced distributions of records across traits. The squared accuracy of genomic prediction, or genomic reliability (r2), was divided by the corresponding heritability for each trait, as only the heritable portion of cow records could be predicted, and this reliability varied across different traits and breeds. For HO and JE, the predictive ability of GPTA outperformed PA in predicting cow PDEV for yield, productive life, somatic cell score, fertility, and health traits. The improvement ranged from 33% to 142% compared with the predictive ability of the PA. However, the results for AY, BS, and GU breeds were less consistent due to the smaller number of genotyped heifers. The r2 gains in those breeds were smaller and aligned with the published reliabilities of GPTA. Weighted and unweighted regressions of PDEV on GPTA and PA traits mostly exceeded the expected value of 2.00 when predicting the future trait PDEV using GPTA or PA. The larger number of observations and lower standard error of the weighted regression coefficient prediction in HO and JE breeds contributed to more stable and consistent regression coefficients for all traits except milk fever and heifer livability. Our study suggests that herd owners may experience greater benefits from genomics than originally forecast.

Impact of Toolpath Pitch Distance on Cutting Tool Nose Radius Deviation and Surface Quality of AISI D3 Steel Using Precision Measurement Techniques.

The selection of the right tool path trajectory and the corresponding machining parameters for end milling is a challenge in mold and die industries. Subsequently, the selection of appropriate tool path parameters can reduce overall machining time, improve the surface finish of the workpiece, extend tool life, reduce overall cost, and improve productivity. This work aims to establish the performance of end milling process parameters and the impact of trochoidal toolpath parameters on the surface finish of AISI D3 steel. It especially focuses on the effect of the tool tip nose radius deviation on the surface quality using precision measurement techniques. The experimental design was carried out in a systematic manner using a face-centered central composite design (FCCD) within the framework of response surface methodology (RSM). Twenty different experiment trials were conducted by changing the independent variables, such as cutting speed, feed rate, and trochoidal pitch distance. The main effects and the interactions of these parameters were determined using analysis of variance (ANOVA). The optimal conditions were identified using a multiple objective optimization method based on desirability function analysis (DFA). The developed empirical models showed statistical significance with the best process parameters, which include a feed rate of 0.05 m/tooth, a trochoidal pitch distance of 1.8 mm, and a cutting speed of 78 m/min. Further, as the trochoidal pitch distance increased, variations in the tool tip cutting edge were observed on the machined surface due to peeling off of the coating layer. The flaws on the tool tip, which alter the edge micro-geometry after machining, resulted in up to 33.83% variation in the initial nose radius. Deviations of 4.25% and 5.31% were noted between actual and predicted values of surface roughness and the nose radius, respectively.

Wall Shear Stress (WSS) Analysis in Atherosclerosis in Partial Ligated Apolipoprotein E Knockout Mouse Model through Computational Fluid Dynamics (CFD).

Atherosclerosis involves an inflammatory response due to plaque formation within the arteries, which can lead to ischemic stroke and heart disease. It is one of the leading causes of death worldwide, with various contributing factors such as hyperlipidemia, hypertension, obesity, diabetes, and smoking. Wall shear stress (WSS) is also known as a contributing factor of the formation of atherosclerotic plaques. Since the causes of atherosclerosis cannot be attributed to a single factor, clearly understanding the mechanisms and causes of its occurrence is crucial for preventing the disease and developing effective treatment strategies. To better understand atherosclerosis and define the correlation between various contributing factors, computational fluid dynamics (CFD) analysis is primarily used. CFD simulates WSS, the frictional force caused by blood flow on the vessel wall with various hemodynamic changes. Using apolipoprotein E knockout (ApoE-KO) mice subjected to partial ligation and a high-fat diet at 1-week, 2-week, and 4-week intervals as an atherosclerosis model, CFD analysis was conducted along with the reconstruction of carotid artery blood flow via magnetic resonance imaging (MRI) and compared to the inflammatory factors and pathological staining. In this experiment, a comparative analysis of the effects of high WSS and low WSS was conducted by comparing the standard deviation of time-averaged wall shear stress (TAWSS) at each point within the vessel wall. As a novel approach, the standard deviation of TAWSS within the vessel was analyzed with the staining results and pathological features. Since the onset of atherosclerosis cannot be explained by a single factor, the aim was to find the correlation between the thickness of atherosclerotic plaques and inflammatory factors through standard deviation analysis. As a result, the gap between low WSS and high WSS widened as the interval between weeks in the atherosclerosis mouse model increased. This finding not only linked the occurrence of atherosclerosis to WSS differences but also provided a connection to the causes of vulnerable plaques.

Preliminary study of feasibility of surface-guided radiotherapy with concurrent tumor treating fields for glioblastoma: region of interest.

OBJECTIVE: To evaluate the impact of the residual setup errors from differently shaped region of interest (ROI) and investigate if surface-guided setup can be used in radiotherapy with concurrent tumor treating fields (TTFields) for glioblastoma. METHODS: Fifteen patients undergone glioblastoma radiotherapy with concurrent TTFields were involved. Firstly, four shapes of region of interest (ROI) (strip-shaped, T-shaped, ⊥ -shaped and cross-shaped) with medium size relative to the whole face were defined dedicate for patients wearing TTFields transducer arrays. Then, ROI-shape-dependent residual setup errors in six degrees were evaluated using an anthropomorphic head and neck phantom taking CBCT data as reference. Finally, the four types of residual setup errors were converted into corresponding dosimetry deviations (including the target coverage and the organ at risk sparing) of the fifteen radiotherapy plans using a feasible and robust geometric-transform-based method. RESULTS: The algebraic sum of the average residual setup errors in six degrees (mm in translational directions and ° in rotational directions) of the four types were 6.9, 1.1, 4.1 and 3.5 respectively. In terms of the ROI-shape-dependent dosimetry deviations, the D98% of PTV dropped off by (3.4 ± 2.0)% (p < 0.05), (0.3 ± 0.5)% (p < 0.05), (0.9 ± 0.9)% (p < 0.05) and (1.1 ± 0.8)% (p < 0.05). The D98% of CTV dropped off by (0.5 ± 0.6)% (p < 0.05) for the strip-shaped ROI while remained unchanged for others. CONCLUSION: Surface-guided setup is feasible in radiotherapy with concurrent TTFields and a medium-sized T-shaped ROI is appropriate for the surface-based guidance.

Sensitivity analysis and compensation for tooth surface deviation of spiral bevel gear machine tool.

To analyze the quantitative mapping relationship between the geometric errors of the five-axis CNC machine tool and the tooth surface deviation of spiral bevel gears, and identify the key geometric errors that affect the machining deviation of the spiral bevel gear tooth surface, a sensitivity analysis method for tooth surface machining deviation of spiral bevel gear based on screw theory and EFAST method is proposed. Firstly, the machining model of the spiral bevel gear tooth surface based on the five-axis CNC machine tool is established. Then, the geometric error transfer model of the machine tool is established based on the screw theory. Combined with the EFAST global sensitivity analysis method, the key geometric errors that affect tooth surface deviation are identified. Finally, the reliability and effectiveness tests are performed by comparing the results to the local sensitivity analysis method and simulating compensation for the key geometric errors. The result of compensation shows that the tooth surface deviation is reduced significantly according to global sensitivity analysis. The feasibility of applying sensitivity analysis to control the tooth surface deviation of spiral bevel gears has been demonstrated.

Evaluation of disease activity in systemic lupus erythematosus using standard deviation of lymphocyte volume combined with red blood cell count and lymphocyte percentage.

Systemic lupus erythematosus (SLE) commonly damages the blood system and often manifests as blood cell abnormalities. The performance of biomarkers for predicting SLE activity still requires further improvement. This study aimed to analyze blood cell parameters to identify key indicators for a SLE activity prediction model. Clinical data of 138 patients with SLE (high activity, n = 40; moderate activity, n = 44; mild activity, n = 37; low activity, n = 17) and 100 healthy controls (HCs) were retrospectively analyzed. Data from 89 paired admission-discharge patients with SLE were collected. Differences and associations between blood cell parameters and disease indicators, as well as the relationship between the these parameters and organ damage, were examined. Machine-learning methods were employed to develop a prediction model for disease activity evaluation. Most blood cell parameters (22/26, 84.62%) differed significantly between patients with SLE and HCs. Analysis of 89 paired patients with SLE revealed significant changes in most blood cell parameters at discharge. The standard deviation of lymphocyte volume (SD-V-LY), red blood cell (RBC) count, lymphocyte percentage (LY%), hemoglobin(HGB), hematocrit(HCT), and neutrophil percentage(NE%) correlated with disease activity. By employing machine learning, an optimal model was established to predict active SLE using SD-V-LY, RBC count, and LY% (area under the curve [AUC] = 0.908, sensitivity = 0.811). External validation indicated impressive performance (AUC = 0.940, sensitivity = 0.833). Correlation analysis revealed that SD-V-LY was positively correlated with ESR, IgG, IgA, and IgM but was negatively correlated with C3 and C4. The RBC count was linked to renal and hematopoietic system impairments, whereas LY% was associated with joint/muscle involvement. In conclusion, SD-V-LY is associated with SLE disease activity. SD-V-LY combined with RBC count and LY% contributes to a prediction model, which can be utilized as an effective tool for assessing SLE activity.

A cost-effectiveness analysis of intraosseous basivertebral nerve ablation for the treatment of chronic low back pain.

BACKGROUND CONTEXT: Randomized trials have demonstrated the superiority of intraosseous basivertebral nerve ablation (BVNA) compared with sham and standard care in terms of improvements in pain, disability, and health-related quality of life in patients with vertebrogenic chronic low back pain (cLBP). PURPOSE: To assess the cost effectiveness of BVNA in patients with vertebrogenic cLBP compared to standard care alone. STUDY DESIGN/SETTING: A model-based economic analysis. PATIENT SAMPLE: Base case analysis used INTRACEPT, a randomized trial comparing BVNA with standard care in 140 patients with vertebrogenic cLBP, recruited from 23 sites across the United States, with a follow-up, up to 5 years. Scenario analyses compared data from the Surgical Multi-center Assessment of Radiofrequency Ablation for the Treatment of Vertebrogenic Back Pain (SMART) randomized trial against a sham control, and a single-arm study. OUTCOME MEASURES: Costs and quality-adjusted life years (QALYs) were calculated to determine the incremental cost-effectiveness ratio (ICER). METHODS: A cost-effectiveness model was built in Microsoft Excel® to evaluate the costs and health outcomes of patients undergoing BVNA using the Intracept Procedure (Relievant Medsystems) to treat vertebrogenic cLBP from a US payor perspective. Alternative scenario sensitivity analyses and probabilistic sensitivity analyses were conducted to assess the robustness of the model results. QALYs were discounted at 3.0% per year. RESULTS: Base case analysis showed that BVNA relative to standard care alone was a cost-effective strategy for the management of patients with vertebrogenic cLBP, with an ICER of US$11,376 per QALY at a 5-year time horizon from introduction of the procedure. Modeling demonstrated a >99% probability that this was cost effective in the US, based on a willingness-to-pay threshold of US$100,000 to US$150,000. Various sensitivity and scenario analyses produced ICERs that all remained below this threshold. CONCLUSIONS: BVNA with the Intracept Procedure offers patients with vertebrogenic cLBP, clinicians, and healthcare systems a cost-effective treatment compared to standard care alone.

Exploring the temporal-spatial characteristics and determinants of high-quality development of city clusters in China.

The complexity, severity, and uncertainty of the international situation have prompted the development of city clusters to focus more on resilience and the building of infrastructures and safeguards. Chinese-style modernization proposes a new realization path for the high-quality development (HQD) of city clusters, based on which an evaluation system for HQD indicators of city clusters is constructed. We also measured the HQD levels of 19 city clusters from 2011 to 2021 and analyzed their spatial differentiation characteristics, agglomeration evolution characteristics, and influencing factors by using kernel density, standard deviation ellipse, Moran's index, geographic detector, and geographically weighted regression. The study revealed that (1) the overall level of HQD of China's city clusters shows a trend of continuous growth, and there is obvious polarization in the high quality of city clusters in different regions. (2) The spatial distribution of HQD in city clusters decreased in the "East, Center and West" direction, but the spatial patterns of "Southeast highlighting" and "Northwest rising" became more obvious. (3) The HQD of city clusters shows obvious spatial agglomeration characteristics and overall presents a spatial pattern of "hot in the east and cold in the west", with the scope of the cold spot area gradually shrinking, and the hot spot area tends to spread outward, with mature city clusters at the core. (4) The influencing factors of HQD in Chinese city clusters are diverse, with financial levels, digital economics, human capital and green innovations having decreasing influence on HQD in city clusters but showing an obvious two-factor enhancement trend, with financial levels being able to effectively stimulate the driving potential of other factors. Financial levels can effectively stimulate the driving potential of other factors. (5) The coefficients of the driving factors affecting the HQD of city clusters vary significantly spatially, with human capital, financial levels and green innovations showing a north‒south hierarchical banded distribution of "high in the south and low in the north", and digital economy shows an east-west hierarchical belt distribution of "high west and low east". Based on the above conclusions, the realization path of accelerating the HQD of China's city clusters is proposed by optimizing the functional division of labor of the city clusters, giving full play to the comparative advantages of the hinterland city clusters, and relying on the high level of the city clusters for opening up.

Splenectomy as a Risk Factor for Graft Rejection Following Endothelial Transplantation: Retrospective Study.

BACKGROUND: Anterior chamber-associated immune deviation (ACAID) is an active immunotolerance mechanism, which is induced by placing antigen into the anterior eye chamber as long as a major surgical trauma is avoided. For this reason, ACAID may be a major contributor to the favorable immunologic outcomes in Descemet membrane endothelial keratoplasty (DMEK). Rodent models have demonstrated the importance of a functional spleen for the development of an ACAID. OBJECTIVE: This study aimed to investigate whether splenectomy leads to increased rejection rates after DMEK in humans. METHODS: A retrospective evaluation was conducted on the course following DMEK at the Eye Center, Medical Center, University of Freiburg, for patients with a self-reported history of splenectomy compared to patients without this condition. Potential study patients were contacted by mail. A questionnaire to self-report splenectomy and the time thereof was sent out. The medical records of all consenting patients at the Eye Center were reviewed for graft survival and immune reactions. RESULTS: We asked 1818 patients after DMEK to report their history of splenectomy. A total of 1340 patients responded and were included in the study. Of these 1340 patients, 16 (1.2%) reported a history of splenectomy (ie, 26 DMEKs, with 10 patients being transplanted in both eyes and 6 patients being transplanted in 1 eye; median age at surgery 73.7, range 66.7-76.1 y). The remaining patients (1324 patients, ie, 1941 eyes) served as controls, with 1941 DMEKs (median age at surgery 71.5, range 64.1-77.2 y). Five (19%) out of the 26 eyes from the splenectomy group required a second transplant due to dislocation (n=2.8%), failure (n=2.8%), and rejection (n=1.4%). Kaplan-Meier analysis revealed no relevant difference compared with controls. CONCLUSIONS: Our results suggest that splenectomy has no major effect on the outcome following DMEK. Subsequent, ACAID may not be the main reason for the favorable immunological outcomes in DMEK, or the camero-splenic axis may be subordinate in humans. However, we only included 16 patients who underwent splenectomy, so it might be possible that we missed a minor effect.

Investigating the Mechanisms of Antibody Binding to Alpha-Synuclein for the Treatment of Parkinson's Disease.

Parkinson's disease (PD) is an idiopathic neurodegenerative disorder with the second-highest prevalence rate behind Alzheimer's disease. The pathophysiological hallmarks of PD are both degeneration of dopaminergic neurons in the substantia nigra pars compacta and the inclusion of misfolded α-synuclein (α-syn) aggregates known as Lewy bodies. Despite decades of research for potential PD treatments, none have been developed, and developing new therapeutic agents is a time-consuming and expensive process. Computational methods can be used to investigate the properties of drug candidates currently undergoing clinical trials to determine their theoretical efficiency at targeting α-syn. Monoclonal antibodies (mAbs) are biological drugs with high specificity, and Prasinezumab (PRX002) is an mAb currently in Phase II, which targets the C-terminus (AA 118-126) of α-syn. We utilized BioLuminate and PyMol for the structure prediction and preparation of the fragment antigen-binding (Fab) region of PRX002 and 34 different conformations of α-syn. Protein-protein docking simulations were performed using PIPER, and 3 of the docking poses were selected based on the best fit. Molecular dynamics simulations were conducted on the docked protein structures in triplicate for 1000 ns, and hydrogen bonds and electrostatic and hydrophobic interactions were analyzed using MDAnalysis to determine which residues were interacting and how often. Hydrogen bonds were shown to form frequently between the HCDR2 region of PRX002 and α-syn. Free energy was calculated to determine the binding affinity. The predicted binding affinity shows a strong antibody-antigen attraction between PRX002 and α-syn. RMSD was calculated to determine the conformational change of these regions throughout the simulation. The mAb's developability was determined using computational screening methods. Our results demonstrate the efficiency and developability of this therapeutic agent.

Effects of facial forms and midline deviations and rolls on female facial beauty according to laypeople, orthodontists, and prosthodontists or restorative dentists.

No study has examined the simultaneous effect of facial forms, midline deviations and midline angulations on facial beauty. Therefore, this comprehensive study aimed to evaluate these and many other hypotheses. This psychometric study was performed on 15,042 observations. A female frontal photograph was edited to 45 perceptometric images with controlled anatomical alteration: 3 facial forms (euryprosopic [brachyfacial], mesoprosopic [mesofacial], leptoprosopic [dolichofacial]), each having either 9 bidirectional midline deviations (0, 1, 2, 3, and 4 mm deviated to the left and right) or 7 bidirectional midline angular deviations (0°, 5°, 10°, and 15° deviated to the left and right). One of the photographs were repeated. These 46 images were esthetically judged by 327 participants (243 laypeople, 49 orthodontists, and 35 'prosthodontists or restorative dentists'). Hierarchical mixed-model multiple linear regressions and post hoc tests were adopted to evaluate the simultaneous impacts of the photomodel's facial forms, midline deviations to the right or left, and midline rolls to the right or left plus sex, age, experience, and dental specialty of the referees on their perception of facial beauty as well as the tolerable zones of midline alterations. These were also done separately for each specialty group, and also for each facial face. Ideal combinations of anatomic features were determined using repeated-measures ANOVAs. Differences between esthetic preferences of different groups in terms of each image were assessed using one-way ANOVAs and t-tests (α = 0.05, α = 0.008, α = 0.001). All 5 anatomical features significantly and independently influenced perception of facial beauty. The tolerance threshold for midline deviations was 1 mm deviations to the right and left sides. For midline rolls, the only tolerable form was the no-roll ('on') midline; the judges preferred right-oriented defects over left-sided ones. The most beautiful facial form was mesoprosopic, followed by leptoprosopic. Men perceived the female face slightly more attractive than did women. The viewers' specialty (or lack of it), their age, or their experience did not affect their esthetic preferences. Predictors of esthetic preferences were all 5 anatomical features plus views' sex, but not their dental specialty, age, or experience. Zones of acceptability and also the ideal range of anatomical features were determined.

Evaluation of nasal septal deviation and maxillary bone and nasal airway dimensions and volumes using cone-beam computed tomography in patients with unilateral palatal canine displacement: a retrospective study.

OBJECTIVES: To detect any association between palatally displaced canine (PDC) and nasal septal deviation (NSD), palatal bone thickness and volume, and nasal airway dimensions and volume. MATERIALS AND METHODS: A total of 92 patients were included and subdivided into two groups: group 1, unilateral PDCs (44 patients), and group 2, normally erupted canines (NDCs) (48 subjects). The following variables were measured using cone-beam computed tomography: presence and type of NSD, nasal width, inferior conchae, hard palate and nasal septum thickness, maxillary bone and nasal airway volumes. RESULTS: NSD was detected in 77% and 50% of PDC and NDC subjects, respectively. Within the PDC subjects, significant differences between the displaced and nondisplaced sides were detected. Palate thickness was increased in the canine region and reduced in the molar region. Compared with the control group, PDC subjects had reduced palate thickness and lower nasal airway volume. Two predictors were significant for predicting the odds of PDC occurrence: NSD and maxillary bone volume. CONCLUSIONS: NSD is more frequent in PDC subjects. PDC subjects have reduced palate thickness and decreased nasal airway volume. In the presence of NSD, the odds of developing PDC increase by 3.35 times, and for each one-unit increase in the maxillary bone volume, the odds of developing PDC decrease by 20%.