Occlusion Conditions Research Articles

Three-dimensional finite element feature analysis of the mandible and morphology and position of temporomandibular joint in patients with unilateral and bilateral molar scissor bite.

The objective of this study is to measuring the morphology and position of bilateral temporomandibular joints in patients with unilateral and bilateral molar scissor bite and simulating the deformation of the mandible during occlusion, in order to provide thesis for the diagnosis of temporomandibular joint disease in patients with unilateral and bilateral molar scissor bite. This study was a retrospective study. A total of 10 patients with unilateral molar scissor bite (the unilateral molar scissor bite group) and 10 patients with bilateral molar scissor bite (the bilateral molar scissor bite group) were selected as the experimental group, and 20 adult patients with classⅠ of angle classification of similar ages were selected as the control group. All patients underwent cone beam computed tomography scans, by measuring the width of the fossa, height of the fossa, articular eminence inclination, long axis of the condyle, minor axis of the condyle, horizontal angle of the condyle and the space of the temporomandibular joint, compare temporomandibular joint morphology and position. The three-dimensional finite element analysis of the mandible morphology was carried out to evaluate the force and deformation of the mandible by using software to simulate the occlusion of the patients. It was further explored the relationship between the force of the mandible morphology and the possible temporomandibular joint disorder symptoms of the patients. Intergroup comparisons for the unilateral molar scissor bite group and left sides of the other groups revealed that the superior articular space in the group with unilateral molar scissor bite was shorter than that in the control group (P<0.05); the long axis of the condyle in the unilateral and bilateral molar scissor bite group were both shorter than that of the control group (P<0.05); among which the unilateral group was larger than the bilateral group, and the minor axis of the condyle in bilateral molar scissor bite group was smaller than in the control group (P<0.05), and the unilateral and bilateral condylar groups were larger than the control group (P<0.05); and the condylar horizontal angle in the unilateral and bilateral groups were larger than that in the control group (P<0.05). The normal sides of the unilateral molar scissor bite group and right sides of the other groups had smaller superior articular space than the control group (P<0.05); and the condylar long-axis in bilateral group was smaller than the control group (P<0.05); and the normal side of the condylar short-axis unilateral group was larger than that of the bilateral condylar group. Three-dimensional finite element analysis: the condyle of patients with molar scissor bite was a concentrated area of deformation during the bite of the mandible, when the first molar occlusion of the scissors bite side was simulated, the maximum deformation was located in the condyle in the X-axis and Z-axis directions. The amount of deformation was greater than that of the scissor bite side in the X-axis direction, while in the Z-axis direction, the normal side was greater than the scissor bite side. The maximum sites of local deformation in the X-axis direction were located in anterior and posterior the transverse crest of scissor bite side, and the minimum sites of local deformation was at 1/3 of the anterior slope of the inner pole of the normal side, the maximum local deformation sites in the Z-axis direction were located in the outer pole and below the outer pole of the normal side. The X-axis deformation value was the largest in the molars occlusion on the normal side, the Y-axis deformation value was in the premolars occlusion on the normal side, and the Z-axis deformation value was the largest in the centric occlusion, the deformation value of the condyle was not most significant in molar scissor bite. Unilateral and bilateral molar scissor bite resulting in a short condyle morphology, and the bilateral group had a shorter condylar morphology than the unilateral group. The condyle of the patient with molar scissor bite is a concentrated area of poor occlusal deformation, and the largest sites of deformation are distributed near the transverse ridge of the inner and outer poles of the condyle. Different occlusion conditions have an effect on condylar deformation values, but do not indicate whether there is a clear association between them.

An efficient and lightweight detection method for stranded elastic needle defects in complex industrial environments using VEE-YOLO

Deep learning has achieved significant success in the field of defect detection; however, challenges remain in detecting small-sized, densely packed parts under complex working conditions, including occlusion and unstable lighting conditions. This paper introduces YOLOv8-n as the core network to propose VEE-YOLO, a robust and high-performance defect detection model. Firstly, GSConv was introduced to enhance feature extraction in depthwise separable convolution and establish the VOVGSCSP module, emphasizing feature reusability for more effective feature engineering. Secondly, improvements were made to the model’s feature extraction quality by encoding inter-channel information using efficient multi-Scale attention to consider channel importance. Precise integration of spatial structural and channel information further enhanced the model’s overall feature extraction capability. Finally, EIoU Loss replaced CIoU Loss to address bounding box aspect ratio variability and sample imbalance challenges, significantly improving overall detection task performance. The algorithm’s performance was evaluated using a dataset to detect stranded elastic needle defects. The experimental results indicate that the enhanced VEE-YOLO model’s size decreased from 6.096 M to 5.486 M, while the detection speed increased from 179FPS to 244FPS, achieving a mAP of 0.926. Remarkable advancements across multiple metrics make it well-suited for deploying deep detection models in complex industrial environments.

Multimodal mapping of spatial attention for unilateral spatial neglect in VR: a proof of concept study using eye-tracking and mobile EEG

Unilateral spatial neglect (USN) is a complex spatial attentional disorder consisting of a failure to attend to the contralesional side of space, frequently seen after a stroke. However, the majority of cases go undiagnosed due to the lack of a valid and reliable tool that is able to assess USN and its many variants. Recent technological advances in virtual reality (VR) and physiological sensors, allow for the study of this disorder under controlled, and ecologically-valid environments, which hold the promise of reliable and early detection. This proof of concept study aims to evaluate the feasibility of a system for discriminating different attentional states using a multimodal dataset derived from a spatial attention task conducted in VR. Nine healthy young adults underwent two experimental conditions: a Control condition and a Left Occlusion condition. Participants performed a visual search task while their behavioral data, including performance metrics, eye-gaze, head, and controller movement data, were recorded. Additionally, electroencephalography data was synchroniously collected to capture neural correlates of attentional processing. Analysis of results of this within-subjects study found worse performance (higher RT), changes in behavior (right-ward gaze bias, left-ward bias in head and controller movement) in the Left Occlusion condition. Neural differences were found (parieto-occipital mean alpha band power and event related potentials) between the two conditions. If validated, this system could be utilized as a diagnostic VR tool, while it holds the potential to facilitate the participation of stroke patients with USN in VR-driven rehabilitation.

Robot Closed-Loop Grasping Based on Deep Visual Servoing Feature Network

Robot visual servoing for grasping has long been challenging to execute in complex visual environments because of issues with efficient feature extraction. This paper proposes a novel visual servoing grasping approach based on the Deep Visual Servoing Feature Network (DVSFN) to tackle this issue. The approach enables feasible to extract scale-invariant point features and target bounding boxes in real time by building an effective single-stage multi-dimensional feature extractor. The DVSFN is then integrated into a Levenberg–Marquardt–based image visual servoing (LM-IBVS) controller. The above creates a mapping link between the robot’s joint space and image features. The robot is then guided in positioning and grabbing by converting the difference between the expected and present features into the corresponding robot joint velocities. Experimental results demonstrate that the proposed method achieves a mean average precision (mAP) of 0.80 and 0.87 for detecting target bounding boxes and point features, respectively, in scenarios with significant lighting variations and occlusions. Under low-light and partial occlusion conditions, the method achieves an average grasping success rate approximately 80%.

Non-Linear Biomechanical Evaluation and Comparison in the Assessment of Three Different Piece Dental Implant Systems for the Molar Region: A Finite Element Study.

The widely available options of different manufacturers in dental implant systems have complicated the selection criteria process for periodontists, necessitating careful consideration of various factors when selecting suitable solutions for individual patient needs. Optimal implant selection requires careful consideration of the patient-specific factors, implant design, and surgical technique. Understanding the biomechanical behavior of implant-tissue interactions is crucial for achieving successful and long-lasting implant therapy. To adequately address this issue and improve the rigorous selection criteria from a biomechanically numerical approach, this research aims to analyze the stress distribution fields, strain patterns, and load transfer displacements within the implant system and the implant-biological interface (gingival and bony tissues) of titanium three-piece to two-one-piece ceramic implant systems. Thus, three different commercially available dental implants designed to be placed in the jaw molar region were considered for evaluation through the finite element method under both oblique and occlusal loading conditions. The results have exhibited an increasing trend to highlight the outstanding behavior of two-piece ceramic implants to dissipate the stress distribution better (6 and 2 times lower than the three- and one-piece systems under occlusal loads and almost 5 and 1.3 times more efficient for oblique loading, respectively), minimize peak stress values (below 100 MPa), and reduce strain peak patterns compared with the other two evaluated designs. On the other hand, the effects generated in biological tissues are strongly associated with implant geometry features. This biomechanical approach could provide a promising strategy for predicting micro-strains and micromotion in implant system pieces and geometries. Hence, these findings contribute to a deeper understanding of the biomechanics spectrum in the behavior of dental implant systems and emphasize the importance of carefully selecting appropriate material systems for accurate patient-specific biomechanical performance.

Three-dimensional-printed restorations for prosthetic rehabilitation of localized tooth wear using the Dahl concept: A case report.

A 26-year-old man with localized tooth wear and demand for aesthetic rehabilitation of the anterior teeth presented to our department. The patient reported excessive consumption of energy drinks. Furthermore, multiple trauma and tooth fractures have occurred in the past. In the present case, three-dimensional (3D)-printed restorations were used to restore the vertical dimensions according to the Dahl concept. An indirect build-up using noninvasive restorations has been demonstrated to be beneficial due to its pleasing aesthetic outcome and the advantage of the 3D printing process. Adhesive bonding was adapted from previous studies using direct composite materials. Thus far, whether, and to what extent, the color of these restorations changes remains unclear. Furthermore, the material wear should be evaluated in future studies. Moreover, 3D-printed, noninvasive restorations made of a computer-aided design/computer-aided manufacturing hybrid material are suitable for the application of the Dahl concept. Aesthetic improvement in combination with minimally invasive pretreatment of the teeth and subsequent noninvasive restorations led to the rehabilitation of the vertical dimension of occlusion. After a follow-up period of two years, harmonious occlusal conditions were observed in the posterior region.

Developing AI Smart Sprayer for Punch-Hole Herbicide Application in Plasticulture Production System

In plasticulture production systems, the conventional practice involves broadcasting pre-emergent herbicides over the entire surface of raised beds before laying plastic mulch. However, weed emergence predominantly occurs through the transplant punch-holes in the mulch, leaving most of the applied herbicide beneath the plastic, where weeds cannot grow. To address this issue, we developed and evaluated a precision spraying system designed to target herbicide application to the transplant punch-holes. A dataset of 3378 images was manually collected and annotated during a tomato experimental trial at the University of Florida. A YOLOv8x model with a p2 output layer was trained, converted to TensorRT® to improve the inference time, and deployed on a custom-built computer. A Python-based graphical user interface (GUI) was developed to facilitate user interaction and the control of the smart sprayer system. The sprayer utilized a global shutter camera to capture real-time video input for the YOLOv8x model, which activates or disactivates a TeeJet solenoid for precise herbicide application upon detecting a punch-hole. The model demonstrated excellent performance, achieving precision, recall, mean average precision (mAP), and F1score exceeding 0.90. Field tests showed that the smart sprayer reduced herbicide use by up to 69% compared to conventional broadcast methods. The system achieved an 86% punch-hole recognition rate, with a 14% miss rate due to challenges such as plant occlusion and variable lighting conditions, indicating that the dataset needs to be improved. Despite these limitations, the smart sprayer effectively minimized off-target herbicide application without causing crop damage. This precision approach reduces chemical inputs and minimizes the potential environmental impact, representing a significant advancement in sustainable plasticulture weed management.

Robust Formation Control for Unmanned Ground Vehicles Using Onboard Visual Sensors and Machine Learning

The performance of unmanned ground vehicle (UGV) formation is crucial for large-scale material transport. In a non-communicative environment, visual perception plays a central role in formation control. However, due to unstable lighting conditions, dust, fog, and visual occlusions, developing a high-precision visual formation control technology that does not rely on external markers remains a significant challenge in UGVs. This study developed a new UGV formation controller that relies solely on onboard visual sensors and proposed a teacher–student training method, TSTMIPI, combining the PPO algorithm with imitation learning, which significantly improves the control precision and convergence speed of the vision-based reinforcement learning formation controller. To further enhance formation control stability, we constructed a belief state encoder (BSE) based on convolutional neural networks, which effectively integrates visual perception and proprioceptive information. Simulation results show that the control strategy combining TSTMIPI and BSE not only eliminates the reliance on external markers but also significantly improves control precision under different noise levels and visual occlusion conditions, surpassing existing visual formation control methods in maintaining the desired distance and angular precision.

Upgrading skin barrier Protection: Addition of active ingredients to a Gelatin/Tannic Acid-Based hydrogel patch for treating skin lesions related to Personal protective Equipment.

Prolonged use of Personal Protective Equipment, like surgical masks, can cause skin issues such as acne ("maskne") and rosacea flare-ups due to pressure and moisture. While dressings can protect the skin, they often reduce mask effectiveness and lack pharmaceuticals to treat common skin lesions. This study introduces an innovative dual-function gelatin/tannic acid-based hydrogel patch incorporating metronidazole (1% w/w) or salicylic acid (2% w/w) to offer both skin protection and treatment. The hydrogels were characterized for gelation temperature, burst strength, extensibility, adhesivity, and tribological properties to assess the effects of the active ingredients on their mechanical performance. In vitro release studies using Franz diffusion cells under occlusive conditions evaluated the drug release profile from the patches. Results showed that gelatin/tannic acid and gelatin/tannic acid-metronidazole hydrogels had similar gelation temperatures (41.65 ± 1.95 °C), while the salicylic acid formulation exhibited a lower gelation temperature (33.24 ± 0.40 °C). Adhesivity improved with the addition of active ingredients, increasing by about 0.5 N, and burst strength significantly increased with metronidazole (about 6 N). Both formulations demonstrated enhanced extensibility and were suitable for all skin types in tribological studies. The in vitro release studies showed an initial burst release followed by controlled release, unaffected by mask placement. These findings suggest that dual-function hydrogel patches could provide effective skin protection and improve skin health during prolonged mask use, offering a promising solution for conditions like "maskne" and rosacea.

Accuracy of digital jaw relation determination in different occlusal conditions - an in vitro study.

In orthodontics, accurate registration of jaw relationships is essential for correct diagnosis and treatment planning. Therefore, accuracy of the digital spatial registration of maxillary and mandibular models and - for the first time-the influence of dentition stage and malocclusion type on this procedure were investigated under controlled conditions. Eight pairs of jaw models, representing different occlusal and developmental statuses (m1-m8), were scanned using two IOS types (PS: Primescan; TR: Trios4). Buccal scans for registering maxillary and mandibular models were repeated (n = 3). Reference scans were obtained using a desktop scanner (RDS; Ceramill Map 600). Arch-specific 3D coordinate systems were used to calculate the linear and angular deviations among different registrations. Trueness of registration by PS and TR was calculated using a statistical mixed-effect model (random-effect: model-type). Precision values of IOS registrations across m1-m8 were characterized as standard deviations (SDs). As maximum deviations compared to RDS, PS showed caudal translation (0.11 ± 0.02mm), while TR showed ventral translation (0.08 ± 0.06mm), of the maxillary relative to the mandibular model. Maximum rotational values were calculated for tilting around the transverse axis (PS: anteinclination (0.25 ± 0.16°), TR: retroinclination (0.27 ± 0.16°)). These deviations varied with the malocclusion type. The lowest IOS precision was recorded for sagittal translation (PS: 0.013 ± 0.005mm, TR: 0.021 ± 0.010mm) and rotation around the transverse axis (PS: 0.051 ± 0.013°, TR: 0.076 ± 0.031°). Registrations using buccal IOS scans showed quantifiable but clinically negligible 3D deviations from reference scan registrations, whereby the type of tooth and jaw misalignment did not appear to have a clinically relevant influence. Therefore, the examined IOSs appear to be suitable for digital jaw relation determination in everyday clinical orthodontic practice.

D3-YOLOv10: Improved YOLOv10-BasedLightweight Tomato Detection Algorithm Under Facility Scenario

Accurate and efficient tomato detection is one of the key techniques for intelligent automatic picking in the area of precision agriculture. However, under the facility scenario, existing detection algorithms still have challenging problems such as weak feature extraction ability for occlusion conditions and different fruit sizes, low accuracy on edge location, and heavy model parameters. To address these problems, this paper proposed D3-YOLOv10, a lightweight YOLOv10-based detection framework. Initially, a compact dynamic faster network (DyFasterNet) was developed, where multiple adaptive convolution kernels are aggregated to extract local effective features for fruit size adaption. Additionally, the deformable large kernel attention mechanism (D-LKA) was designed for the terminal phase of the neck network by adaptively adjusting the receptive field to focus on irregular tomato deformations and occlusions. Then, to further improve detection boundary accuracy and convergence, a dynamic FM-WIoU regression loss with a scaling factor was proposed. Finally, a knowledge distillation scheme using semantic frequency prompts was developed to optimize the model for lightweight deployment in practical applications. We evaluated the proposed framework using a self-made tomato dataset and designed a two-stage category balancing method based on diffusion models to address the sample class-imbalanced issue. The experimental results demonstrated that the D3-YOLOv10 model achieved an mAP0.5 of 91.8%, with a substantial reduction of 54.0% in parameters and 64.9% in FLOPs, compared to the benchmark model. Meanwhile, the detection speed of 80.1 FPS more effectively meets the demand for real-time tomato detection. This study can effectively contribute to the advancement of smart agriculture research on the detection of fruit targets.

Construction of tennis pose estimation and action recognition model based on improved ST-GCN

With the rapid growth of computer vision and deep learning technologies, the application of pose estimation and action recognition in sports training has become increasingly widespread. Due to factors such as complex movements, fast speed, and limb occlusion, pose estimation and action recognition in tennis face significant challenges. Therefore, this study first introduces selective dropout and pyramid region of interest pooling layer strategies in fast region convolutional neural networks. Secondly, a pose estimation algorithm based on multi-scale fusion pose residual network 50 is designed, and finally a spatiotemporal graph convolutional network model is constructed by fusing channel attention module and multi-scale dilated convolution module. The data showed that the average detection accuracy of the improved attitude residual network 50 was 70.4%, and the accuracy of object detection for small, medium, and large objects was 57.4%, 69.3%, and 79.2%, respectively. The continuous action recognition accuracy and inter action fluency detection time of the improved spatiotemporal graph convolutional network were 93.8% and 19.2 ms, respectively. When the sample size was 1000, its memory usage was 1378 MB and the running time was 32.7 ms. Experiments have shown that the improved model achieves high accuracy and robustness in tennis action recognition tasks, especially in complex scenes and limb occlusion conditions, where the model shows significant advantages. This study aims to provide an efficient and accurate motion recognition technology for tennis posture analysis and intelligent training.

Survey on the management of retinal arterial occlusions in Spain

ObjectiveTo determine the current status of retinal artery occlusion (RAO) management in Spain. Material and MethodsAn anonymous questionnaire of 22 questions was carried out on the Google Forms® platform between April 27 and May 28, 2023. This questionnaire was distributed via email by the Spanish Society of Retina and Vitreous and the Spanish Society of Ophthalmology. Results159 ophthalmologists from 91 public and 44 private centers in the 17 autonomous communities answered the questionnaire. Fifty-one percent of the ophthalmologists who answered the survey were women, 56.6% worked in public centers, 9.4% in private centers and 34% in both centers.Of the ophthalmologists working in public centers, 41.7% attend ophthalmologic emergencies 24 hours a day, 365 days a year, while the rest delay their attention outside the usual hours. In 62.6% of the public centers with responses collected there are no protocols for the management of OAR in the ophthalmology services and as for multidisciplinary protocols, 57% recognize that they do not have one, 23% have one with neurology or internal medicine and only 13% of the centers include OAR within the stroke code. The most frequently reported treatments are hypotensors and anterior chamber paracentesis.In private centers, 73.7% report not having their own protocol, and 78.9% do not have a protocol with other services.The main barriers perceived by the ophthalmologists surveyed were: patients arriving outside the window period (77.2%), no specific treatment and lack of established protocols (55.4%), low incidence (32.9%).Suggestions for improvement were: need to implement protocols, coordination with other services and that OAR be included as a stroke code. ConclusionsDespite its limitations, (simple questionnaire, open design of some questions, lack of representation of centers and provinces and contradictory responses within the same center), we consider that it can serve as an approximation to the current management of RAO in Spain. It is necessary to develop protocols adapted to the different centers and to comply with them effectively in order to improve accessibility and equity.

Removable denture use, fit, and all-cause mortality in older adults with reduced occlusal support: The OHSAKA study

Statement of problemAs the global population ages, tooth loss among older adults has become increasingly prevalent, impacting oral function and overall health. Although removable dentures have been used to improve masticatory function, the long-term effects of denture conditions on mortality are unclear. PurposeThe purpose of this clinical study was to clarify the association between removable denture condition and the mortality rate in older adults with reduced occlusal support. Material and methodsThis longitudinal study analyzed survival data (up to 2022) for 186893 individuals aged ≥75 years who underwent dental examinations through public healthcare services between 2018 and 2020. The participants were categorized into 10 groups (A1 to A3, B1 to B4, and C1 to C3) based on their occlusal support status using the Eichner index. Denture conditions were assessed by private practice dentists and classified into 3 categories: well-fitting, poorly fitting, and not used. Cox proportional hazards regression analyses were conducted to examine the association between denture conditions and mortality by considering the following control variables: age, sex, history of chronic diseases (hypertension, diabetes, hyperlipidemia, and dementia), smoking habits, and body mass index for the entire study population and within each of the B1 to B4 and C1 to C3 groups. ResultsSignificantly higher hazard ratios (HRs) for mortality were observed with occlusal support deterioration, poorly fitting dentures, and nonusage, with the peak observed in the C3 group with no dentures. The HRs (with 95% confidence intervals) of well-fitting dentures were consistently the lowest across all groups as follows: 0.98 (0.90 to 1.06) in B1, 1.02 (0.95 to 1.10) in B2, 1.11 (1.03 to 1.19) in B3, 1.14 (1.07 to 1.22) in B4, 1.15 (1.05 to 1.26) in C1, 1.28 (1.21 to 1.37) in C2, and 1.58 (1.46 to 1.72) in C3, with the A1 to A3 group as the reference. Poorly fitting or no dentures were associated with increased HRs in the Eichner groups B3 to C3, compared with well-fitting dentures. ConclusionsThis large population-based cohort study found that well-fitting dentures were associated with lower mortality risk in older adults with reduced posterior occlusal support. Nonusage or poorly fitting dentures were associated with an increased risk of mortality as occlusal support deteriorated.

A multimodal framework for pepper diseases and pests detection

Pepper diseases and pests typically exhibit small target proportions, diverse shapes and sizes, complex imaging backgrounds, and similarities with the background. Existing detection methods perform poorly in identifying targets of different sizes and shapes within the same scene, and they lack adequate noise suppression capabilities. To address the practical needs of detecting pepper diseases and pests in complex scenarios, we have constructed the first multimodal pepper diseases and pests object detection dataset (PDD). This dataset includes a wide variety of diseases and pests images, along with detailed natural language descriptions of their attributes. Locating the described targets in complex scenes with similar disease symptoms and leaf occlusion presents a significant challenge. To tackle this issue, we propose the PepperNet model for object detection in pepper diseases and pests images using natural language descriptions. This model decomposes complex multimodal features of language and images into explicit attribute features and employs fine-grained multimodal attribute contrast learning strategies. This approach effectively distinguishes subtle local differences between similar objects, achieving fine-grained mapping from language to vision in complex scenarios. Our detection results show a mAP@0.5 of 91.93% and a detection speed of 121.8 frames per second. Visualizations indicate that the model maintains high robustness under varying noise levels and occlusion conditions, demonstrating superior performance and stability across diverse complex scenarios.

Safety and Efficacy of Tiny (≤3 mm) Unruptured Middle Cerebral Artery Aneurysm Treatment: An Analysis of the NeuroVascular Quality Initiative-Quality Outcomes Database Cerebral Aneurysm Registry.

Improved imaging modalities have led to an increased detection of intracranial aneurysms, many of which are small. There is uncertainty in the appropriate management of tiny aneurysms. The objective of this study was to use a large, multi-institutional NeuroVascular Quality Initiative-Quality Outcomes Database (NVQI-QOD) to assess the frequency, safety, and efficacy of treatment of tiny, unruptured middle cerebral artery (MCA) aneurysms. The NeuroVascular Quality Initiative-Quality Outcomes Database registry was queried for patients with tiny unruptured MCA aneurysms who underwent treatment. Tiny size was defined as an aneurysm with a maximum dimension of ≤3 mm. Demographics, aneurysm characteristics, and treatment safety were queried. Outcomes included modified Rankin Score (mRS) at discharge and the last follow-up as well as aneurysm occlusion status at discharge. Of 674 treated, unruptured MCA aneurysms, 57 (8.5%) were tiny. The mean aneurysm width was 2.2 mm, and the mean patient age was 55.9 years. Most aneurysms were treated with microsurgery (61.4%, 35/57). The overall intraoperative complication rate was 5.3% (3/57), and the postoperative complication rate was 10.5% (6/57). 10.5% (6/57) of patients were discharged to rehabilitation. At discharge, 42 (87.5%) of the treated aneurysms had complete occlusion. In the subgroup of patients with recorded follow-up data, 48.3% (14/29) had a mRS of 0 at discharge and 46.9% (15/32) had an mRS of 0 at the last follow-up (median follow-up 166 days). Treatment of tiny, unruptured MCA aneurysms is efficacious but may have a high rate of complications. Physicians should be cautious when deciding to treat tiny, unruptured MCA aneurysms.

Longitudinal association between posterior occlusal contact and dementia development in a large retrospective cohort study using a Japanese claims database

This study examines the association between posterior occlusal contact and the risk of dementia development in the Japanese population, utilizing Eichner classification to evaluate occlusal status. Data from Japanese health insurance claims were analyzed for the period from April 2016 to March 2022. Participants had undergone specific health checkups, had no prior history of dementia, and were classified according to their dental occlusal contact. Dementia diagnoses were determined using ICD-10 codes, and participants were divided into three groups—A, B, and C—based on the Eichner classification, which indicates the extent of occlusal contact. Over an average follow-up period of 35.6 months, 691 dementia were identified among 931,309 participants. Those diagnosed with dementia were more likely to belong to Eichner B and C groups, signifying reduced occlusal contact. After adjusting for covariates, the hazard ratios (95% confidence intervals) for Eichner B and C were 1.73 (1.31–2.28) and 2.10 (1.35–3.26), respectively. Sensitivity analyses confirmed these findings in adults aged 60–75. These findings suggest that reduced posterior occlusal contact correlates with an increased risk of dementia. Since the study is limited to participants under the age of 75, further research is required to determine its generalizability to older populations.

Method for Non-Contact Measuring the Weight of Sturgeon in Intensive Aquaculture

Weight information plays a pivotal role in sturgeon breeding and production management. However, manual measurement is time consuming and labor intensive due to the immense size of the sturgeon. Due to the unique body shape of the sturgeon, traditional image segmentation algorithms struggle to extract the necessary features from sturgeon images, which makes them unsuitable for this particular species. Moreover, accurately measuring weight in an occlusion environment is difficult. To address these challenges, an improved YOLOv5s model with a context augmentation module, focal-efficient intersection over union, and soft non-maximum suppression was proposed in this paper. To validate the model’s feasibility, the improved YOLOv5s model was first pre-trained using the sturgeon dataset, followed by further training on the occlusion dataset for segmentation tasks. Based on the phenotypic data obtained from the improved model, a multilayer perceptron method was used to estimate the sturgeon’s weight accurately. Experimental results demonstrated that the average precision of the improved YOLOv5s model reached 89.80% under occlusion conditions, and the correlation coefficient of noncontact weight measurement results reached 89.80%. The experimental results showed that the improved algorithm effectively performs segmentation of sturgeon in occlusion conditions and can accurately estimate the mass.

Oral function status of older patients seeking dental implant treatment.

In recent years, dental implant treatment has become an option for prosthetic treatment for missing teeth and is often performed in older patients. However, the complex oral functional decline in old age presents challenges in terms of frailty prevention, making oral function management after prosthetic treatment crucial. Nonetheless, the actual status of oral function in older patients seeking dental implant treatment remains unclear. In this study, we aimed to assess the oral function status of older patients seeking dental implant treatment. Among patients receiving prosthetic treatment for missing teeth, 227 older patients (111 in the pre-dental implant group and 116 in the pre-bridge/denture group) who underwent a thorough examination of their oral function were included in this study. Age, sex, comorbidities, smoking status, number of functional teeth, and occlusal support status were obtained from the medical records. Statistical analyses were performed using the t-test, chi-square test, and logistic regression (p < 0.05). Compared with the pre-bridge/denture group, the pre-dental implant group had significantly better oral hygiene, occlusal force, tongue-lip motor function, tongue pressure, masticatory function, and swallowing function and a significantly lower prevalence of oral hypofunction. Older age and decreased occlusal support were associated with the diagnosis of oral hypofunction, even after adjusting for confounding factors including prosthetic treatment. Although older patients seeking dental implant treatment have a higher oral function than those seeking general prosthetic treatment, older age and a lower number of occlusal supports suggest that appropriate oral function management is needed.

Open reduction and internal fixation of mandibular condyle fractures using AUTOFIX 2.0® cannulated compression screw system: A technical innovation with intraoperative CT-scan

Condylar process fractures remain a matter of ongoing controversy in maxillofacial surgery because of variety of opinions and proposed treatment modalities offered in the literature. The trend is toward open reduction and internal fixation (ORIF) whenever there is displacement or dislocation combined with unstable occlusal conditions. The fundamental treatment goals are anatomical fixation and early return to function. However, ORIF of a fractured condyle carries significant risks, including facial nerve damage, and presents challenges in reducing and stabilizing the fractured segment in an area of limited access. We present here an innovative technique for ORIF of condylar head fractures. It consists in fracture reduction and stabilization with two Kirschner wires followed by osteosynthesis with two cannulated headless compression screws using the AUTOFIX 2.0® system (Stryker, Kalamazoo, USA). This new technique, combined with intraoperative CT scan, ensures satisfactory reduction and stabilization of the dislocated joint segment, thereby restoring the condyle to its physiologically normal position.