During long-distance migrations, some bird species make use of in-wake flying, which should allow them to profit from the upwash produced by another bird. While indirect evidence supports energy saving as the primary benefit of in-wake flying, measurements are still missing. We equipped migrating northern bald ibises (Geronticus eremita) with high-precision global navigation satellite system data loggers to track their position in the flock. We estimated birds\' energy expenditure through different proxies, namely dynamic body acceleration (DBA), heart rate and effective wingbeat frequency. During active flapping flight, DBA estimates dropped off when in-wake compared with when not-in-wake. In addition, effective wingbeat frequency decreased, suggesting an increased use of intermittent gliding flight during in-wake periods. Heart rate varied greatly among individuals, with a clear decrease during gliding-corroborating its energy-saving function. Furthermore, we found consistent proof for decreased heart rate during in-wake flying, by up to 4.2%. Hence, we have shown that flying in the wake of another individual reduces birds\' DBA, heart rate and effective wingbeat frequency, which could reflect reduced energy requirement.

This study aimed to investigate the acute effects of lower limb wearable resistance on maximal horizontal deceleration biomechanics, across two different assessments. Twenty recreationally trained team sport athletes performed acceleration to deceleration assessments (ADA), and 5-0-5 change of direction (COD) tests across three load conditions (unloaded, 2% of BW, 4% of body weight (BW)), with load attached to the anterior and posterior thighs and shanks. Linear mixed effect models with participant ID as the random effect, and load condition as the fixed effect were used to study load-specific biomechanical differences in deceleration mechanics across both tests. Primary study findings indicate that for the ADA, in the 4% BW condition, participants exhibited significantly greater degrees of Avg Approach Momentum, as well as significant reductions in deceleration phase center of mass (COM) drop, and Avg Brake Step ground contact deceleration (GCD) in both the 2% BW, and 4% BW condition, compared to the unloaded condition. In the 5-0-5 tests, participants experienced significant reductions in Avg Approach Velocity, Avg deceleration (DEC), and Stopping Time in the 4% BW condition compared to the unloaded condition. Similar to the ADA test, participants also experienced significant reductions in Avg Brake Step GCD in both the 2% BW and 4% BW conditions, and significant increases in Avg Approach Momentum in the 4% BW condition, compared to the unloaded condition. Therefore, findings suggest that based on the test, and metric of interest, the addition of lower limb wearable resistance led to acute differences in maximal horizontal deceleration biomechanics. However, future investigations are warranted to further explore if the use of lower limb wearable resistance could present as an effective training tool in enhancing athlete\'s horizontal deceleration and change of direction performance.

BACKGROUND: Prolonged orthodontic treatment duration has long been a concern for orthodontists and patients, leading to a surge in publications on accelerated orthodontic tooth movement (OTM). This study aims to investigate the knowledge landscape, hotspots, and research trends in acceleration of OTM using bibliometric and visual analyses.
METHODS: A comprehensive search was conducted in the Web of Science (WOS) Core Collection to identify relevant publications related to acceleration of OTM. R Biblioshiny, VOS viewer, and a bibliometric online analysis platform were used to conduct the bibliometric and visualization analysis. Curve fitting and correlation analysis were performed to examine the correlation global and country economics and publication trends, and to predict publication numbers.
RESULTS: A total of 647 articles on accelerated OTM were included in the analysis, with clinical and non-clinical publications accounting for 43.59% and 31.22%, respectively. The annual publication numbers exhibited an upward trend, correlating positively with both global gross domestic product (GDP) (r = 0.915, P < .001) and the GDP of individual countries/regions (r = 0.976, P < .001). China produced the most documents (94), while the USA led in citation count (2758) and international collaborations. Wilcko WM was the top-cited author, with eight of the top 10 authors from the USA and the remainder from Asia. Keywords such as \'tooth movement\', \'corticotomy\', \'piezocision\' and \'low-level laser therapy\' were the most prominent themes, while topics like \'micro-osteoperforation\', \'plasma\', \'gingival crevicular fluid\' and \'pain\' have become recent research hotspots and frontiers.
CONCLUSIONS: This study provides a comprehensive overview of the research on accelerated OTM, highlighting hotspots and frontiers, fostering collaboration among authors and countries/regions, and contributing to future research endeavours.

Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used machine learning algorithms to assess non-contact injury risk in professional male soccer players from physiological and mechanical load variables. Twenty-five professional male soccer players with a first-time, non-contact muscle injury were included in this study. Recordings of external load (speed, distance, and acceleration/deceleration data) and internal load (heart rate) were obtained during all training sessions and official matches over a 4-year period. Machine learning model training and evaluation features were calculated for each of nine different metrics for a 28-day period prior to the injury and an equal-length baseline epoch. The acute surge in the values of each workload metric was quantified by the deviation of maximum values from the average, while the variations of cumulative workload over the last four weeks preceding injury were also calculated. Seven features were selected by the model as prominent estimators of injury incidence. Three of the features concerned acute load deviations (number of sprints, training load score-incorporating heart rate and muscle load- and time of heart rate at the 90-100% of maximum). The four cumulative load features were (total distance, high speed and sprint running distance and training load score). The accuracy of the muscle injury risk assessment model was 0.78, with a sensitivity of 0.73 and specificity of 0.85. Our model achieved high performance in injury risk detection using a limited number of training load variables. The inclusion, for the first time, of heart rate related variables in an injury risk assessment model highlights the importance of physiological overload as a contributor to muscle injuries in soccer. By identifying the important parameters, coaches may prevent muscle injuries by controlling surges of training load during training and competition.

Bioenergetics models are powerful tools used to address a range of questions in fish biology. However, these models are rarely informed by free-swimming activity data, introducing error. To quantify the costs of activity in free-swimming fish, calibrations produced from standardized laboratory trials can be applied to estimate energy expenditure from sensor data for specific tags and species. Using swim tunnel respirometry, we calibrated acceleration sensor-equipped transmitting tags to estimate the aerobic metabolic rates (ṀO2) of lake trout (Salvelinus namaycush) at three environmentally relevant temperatures. Aerobic and swim performance were also assessed. Like other calibrations, we found strong relationships between ṀO2 and acceleration or swimming speed, and jackknife validations and data simulations suggest that our models accurately predict metabolic costs of activity in adult lake trout (~5% algebraic error and ~20% absolute error). Aerobic and swim performance metrics were similar to those reported in other studies, but their critical swimming speed was lower than expected. Additionally, lake trout exhibited a wide aerobic scope, suggesting that the avoidance of waters ≥15°C may be related to selection for optimal growing temperatures. The ability to quantify the free-swimming energetic costs of activity will advance our understanding of lake trout ecology and may yield improvements to bioenergetics model.

BACKGROUND: Orchestration of tooth movement necessitates an equilibrium of bone synthesis and resorption. Vitamin D, through receptor-mediated actions, regulates the differentiation and maturation of osteoblasts and also induces osteoclastogenesis, maintaining this equilibrium.
OBJECTIVE: To analyze the impact of vitamin D in orthodontic tooth movement (OTM).
METHODS: A comprehensive exploration of the existing literature was conducted by systematic search through seven e-databases.
METHODS: The criteria for inclusion were established using the PICO format: Orthodontic patients treated with fixed appliance (P), administered with vitamin D3 (I), collated with appropriate control groups (C), with tooth movement as the primary outcome and root resorption, anchorage loss, gingival crevicular fluid (GCF) volume, pain perception, and alveolar bone density as the secondary outcome (O).
METHODS: After an extensive database search, 251 articles were obtained. Six articles were chosen following a stringent selection using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The critical appraisal of randomized control trials (RCTs) involved the meticulous application of the RoB 2 tool. The quantitative synthesis incorporated a subset of six articles only.
RESULTS: In the meta-analysis investigating the influence of vitamin D on OTM, a notable disparity was evident between the vitamin D and control groups. Specifically, the standardized mean difference (SMD) stood at 1.43, accompanied by a 95% confidence interval (CI) ranging from 0.691 to 2.169 (P = .00154). For root resorption, the SMD was recorded at -0.51, with a 95% CI spanning from -3.051 to 2.031 (P = .11).
CONCLUSIONS: The rate of tooth movement was enhanced by systemic and local administration of vitamin D. However, the inadequacy of available data is a hindrance in determining conclusively the impact of vitamin D on the extent of root resorption. The resolution of this quandary needs future human studies devoted toward investigating the influence of vitamin D in the realms of OTM and associated root resorption, thereby providing a definitive elucidation.
BACKGROUND: Prospero- CRD42023491783.

In clinical practice, obstetricians use visual interpretation of fetal heart rate (FHR) to diagnose fetal conditions, but inconsistencies among interpretations can hinder accuracy. This study introduces MTU-Net3+, a deep learning model designed for automated, multi-task FHR analysis, aiming to improve diagnostic accuracy and efficiency. The proposed MTU-Net3 + was built upon the UNet3 + architecture, incorporating an encoder, a decoder, full-scale skip connections, and a deep supervision module, and further integrates a self-attention mechanism and bidirectional Long Short-Term Memory layers to enhance its performance. The MTU-Net3 + model accepts the preprocessed 20-minute FHR signals as input, outputting categorical probabilities and baseline values for each time point. The proposed MTU-Net3 + model was trained on a subset of a public database, and was tested on the remaining data of the public database and a private database. In the remaining public datasets, this model achieved F1 scores of 84.21% for deceleration (F1.Dec) and 61.33% for acceleration (F1.Acc), with a Root Mean Square Baseline Difference (RMSD.BL) of 3.46 bpm, 0% of points with an absolute difference exceeding 15 bpm(D15bpm), a Synthetic Inconsistency Coefficient (SI) of 44.82%, and a Morphological Analysis Discordance Index (MADI) of 7.00%. On the private dataset, the model recorded an RMSD.BL of 1.37 bpm, 0% D15bpm, F1.Dec of 100%, F1.Acc of 87.50%, an SI of 12.20% and a MADI of 2.79%. The MTU-Net3 + model proposed in this study performed well in automated FHR analysis, demonstrating its potential as an effective tool in the field of fetal health assessment.

Purpose: The aim of this study is to investigate the dynamic and biomechanical response of the pelvis and thoracolumbar spine in simulated under-body blast (UBB) impacts and design of protective seat cushion for thoracolumbar spine injuries. Methods: A whole-body FE (finite element) human body model in the anthropometry of Chinese 50th% adult male (named as C-HBM) was validated against existing PHMS (Postmortem Human Subjects) test data and employed to understand the dynamic and biomechanical response of the pelvis and thoracolumbar spine from FE simulations of UBB impacts. Then, the protective capability of different seat cushion designs for UBB pelvis and thoracolumbar injury risk was compared based on the predictions of the C-HBM. Results: The predicted spinal accelerations from the C-HUM are almost within the PHMS corridors. UBB impact combined with the effects from physiological curve of the human thoracolumbar spine and torso inertia leads to thoracolumbar spine anterior bending and axial compression, which results in stress concentration in the segments of T4-T8, T12-L1 and L4-L5. Foam seat cushion can effectively reduce the risk of thoracolumbar spine injury of armored vehicle occupants in UBB impacts, and the DO3 foam has better protective performance than ordinary foam, the 60 mm thick DO3 foam could reduce pelvic acceleration peak and DRIz value by 52.8% and 17.2%, respectively. Conclusions: UBB spinal injury risk is sensitive to the input load level, but reducing the pelvic acceleration peak only is not enough for protection of spinal UBB injury risk, control of torso inertia effect would be much helpful.

BACKGROUND: Piezocision is a minimally invasive surgical method aiming to accelerate tooth movement. However, its effect was found to be transient, appertaining to the regional acceleratory phenomenon (RAP). Hence, the aim of the study was to evaluate the effect of single and multiple piezocisions on the rate of orthodontic tooth movement (OTM). Moreover, the impact of both protocols on canine tipping and orthodontically induced inflammatory root resorption (OIIRR) has been assessed.
METHODS: Thirty indicated patients for the therapeutic extraction of maxillary first premolars were enlisted in this split-mouth study, and they were randomly split into two equal groups, each including 15 subjects. In the Single Application Group (SAG), one side of the maxillary arch arbitrarily received a single piezocision before the onset of canine retraction, whereas in the Multiple Application Group (MAG), piezocisions were randomly performed on one side, three times on a monthly basis, over the 12-week study period. The contralateral sides of both groups served as the controls. Canine retraction was carried out bilaterally using nickel-titanium closed-coil springs, delivering 150 g of force, and the rate of tooth movement, as well as canine tipping were evaluated on a monthly basis, over a 3-month period. Cone-bean computed tomography scans were also conducted pre- and post- canine retraction, and OIIRR was assessed using Malmgren Index.
RESULTS: The reported outcomes revealed a significant increase in the amount of canine retraction, canine tipping, as well as root resorption scores on the experimental sides in both groups SAG and MAG post-retraction (p < 0.001). However, upon comparing the experimental sides in both groups, non-significant differences have been observed between them regarding all the assessed outcomes (p > 0.05).
CONCLUSIONS: Single and multiple piezocisions effectively accelerate OTM in comparison to conventional orthodontic treatment, with relative outcomes reported by both intervention frequencies. Accordingly, single piezocision is recommended as an adjunct to OTM. Furthermore, significant tooth tipping as well as a significantly higher root resorption risk accompanies both single and multiple piezocision applications in conjunction with OTM.
UNASSIGNED: Clinicaltrials.gov TRIAL REGISTRATION NUMBER: NCT05782088 DATE OF REGISTRATION: 23/03/2023 \"Retrospectively registered\". URL: https://clinicaltrials.gov/ct2/show/NCT05782088.

BACKGROUND: Thyroid cancer is a common thyroid malignancy. The majority of thyroid lesion needs intraoperative frozen pathology diagnosis, which provides important information for precision operation. As digital whole slide images (WSIs) develop, deep learning methods for histopathological classification of the thyroid gland (paraffin sections) have achieved outstanding results. Our current study is to clarify whether deep learning assists pathology diagnosis for intraoperative frozen thyroid lesions or not.
METHODS: We propose an artificial intelligence-assisted diagnostic system for frozen thyroid lesions that applies prior knowledge in tandem with a dichotomous judgment of whether the lesion is cancerous or not and a quadratic judgment of the type of cancerous lesion to categorize the frozen thyroid lesions into five categories: papillary thyroid carcinoma, medullary thyroid carcinoma, anaplastic thyroid carcinoma, follicular thyroid tumor, and non-cancerous lesion. We obtained 4409 frozen digital pathology sections (WSI) of thyroid from the First Affiliated Hospital of Sun Yat-sen University (SYSUFH) to train and test the model, and the performance was validated by a six-fold cross validation, 101 papillary microcarcinoma sections of thyroid were used to validate the system\'s sensitivity, and 1388 WSIs of thyroid were used for the evaluation of the external dataset. The deep learning models were compared in terms of several metrics such as accuracy, F1 score, recall, precision and AUC (Area Under Curve).
RESULTS: We developed the first deep learning-based frozen thyroid diagnostic classifier for histopathological WSI classification of papillary carcinoma, medullary carcinoma, follicular tumor, anaplastic carcinoma, and non-carcinoma lesion. On test slides, the system had an accuracy of 0.9459, a precision of 0.9475, and an AUC of 0.9955. In the papillary carcinoma test slides, the system was able to accurately predict even lesions as small as 2 mm in diameter. Tested with the acceleration component, the cut processing can be performed in 346.12 s and the visual inference prediction results can be obtained in 98.61 s, thus meeting the time requirements for intraoperative diagnosis. Our study employs a deep learning approach for high-precision classification of intraoperative frozen thyroid lesion distribution in the clinical setting, which has potential clinical implications for assisting pathologists and precision surgery of thyroid lesions.