OBJECTIVE: Volume status assessment of a patient by ultrasound (US) imaging of the inferior vena cava (IVC) is important for the diagnosis and prognosis of various clinical conditions. In order to improve the clinical investigation of IVC, which is mainly based on unidirectional US (in M-mode), automated processing of 2-D US scans (in B-mode) has enabled tissue movement tracking on the visualized plane and can average this in various directions. However, IVC geometry outside of the visualized plane is not under control and could result in errors that have not yet been evaluated.
METHODS: We used a method that integrates information from long- and short-axis IVC views (simultaneously acquired in the X-plane) to assess challenges in IVC diameter estimations using 2-D US scans in eight healthy subjects.
RESULTS: Relative movements between the US probe and IVC induced the following problems when assessing IVC diameter via 2-D view: a median error (i.e., absolute difference with respect to diameter measured in the X-plane) of 17% using 2-D US scans in the long-axis view of the IVC affected by medio-lateral displacements (median: 4 mm); and a median error of 7% and 9% when measuring the IVC diameter from a short-axis view in the presence of pitch angle (median: 0.12 radians) and cranio-caudal movement (median: 15 mm), respectively.
CONCLUSIONS: Relative movements in the IVC that are out of view of B-mode scans cannot be detected, which results in challenges in IVC diameter estimation.

BACKGROUND: Little is known on the prospective associations between an empirically derived dietary pattern (DP) and life satisfaction among adolescents. This PUTRA-Adol follow-up study aimed to assess the prospective associations between the empirically derived DP and life satisfaction during adolescence.
METHODS: A total of 585 and 262 adolescents participated in the baseline PUTRA-Adol study in 2016 and PUTRA-Adol follow-up study in 2019-2020, respectively. These adolescents were recruited from three southern states in peninsular Malaysia, namely Negeri Sembilan, Melaka and Johor. Dietary assessments were estimated using a validated food frequency questionnaire (FFQ) while a Multidimensional Students\' Life Satisfaction Scale (MSLSS) was used to measure life satisfaction at baseline in 2016 as well as at follow-up in 2019-2020. A DP characterised by foods high in free sugar and energy dense was identified using reduced rank regression (RRR), cross-sectionally at baseline and was reported elsewhere. Similar RRR analysis was used to find a DP that best explained the variation in response variables linked to poorer life satisfaction, including dietary energy density (DED), fiber density, and percentage of energy from total fat and sugar at the PUTRA-Adol follow-up study. Prospective relationship between adherence to the identified DPs and overall life satisfaction scores as well as its domains between 2016 and 2019-2020 were evaluated using generalized estimating equation models (GEE).
RESULTS: A DP characterized by high intakes of percentage energy from sugar, fibre and low in DED and percentage energy from total fat was identified at the 2019-2020 follow-up. The identified DP explained 11% of total variations in the response variables and was characterized by high intakes of sweets, sugar sweetened beverages (SSB) and fruits. Female adolescents [67.6(8.9)] had a mean (SD) of life satisfaction that was higher than male adolescents [67.5(10.8)] p < 0.05 in 2019-2020. Prospective analysis found a significant positive association between the identified DP and school domain, in male adolescents (β = 0.117; 95% CI 0.001, 0.234) and an inverse relationship between the DP z-score and self-domain in all adolescents (β = - 0.060; 95% CI - 0.115, - 0.005) from 2016 to 2019-2020.
CONCLUSIONS: An increasing score for the predominant \'High sugar and High fibre\' DP was prospectively associated with increasing life satisfaction score for the school domain in male adolescents and decreasing score for self-domain in both male and females during adolescence. A lifestyle intervention targeting reduced dietary intakes, particularly sugar, may improve life satisfaction in adolescents and promote healthier future without compromising dietary intakes for chronic disease prevention later in life.

BACKGROUND: Quantification of microscopy time-series of in vitro reconstituted motor driven microtubule (MT) transport in \'gliding assays\' is typically performed using computational object tracking tools. However, these are limited to non-intersecting and rod-like filaments.
RESULTS: Here, we describe a novel computational image-analysis pipeline, KnotResolver, to track image time-series of highly curved self-intersecting looped filaments (knots) by resolving cross-overs. The code integrates filament segmentation and cross-over or \'knot\' identification based on directed graph representation, where nodes represent cross-overs and edges represent the path connecting them. The graphs are mapped back to contours and the distance to a reference minimized. The accuracy of contour detection is sub-pixel with a robustness to noise. We demonstrate the utility of KnotResolver by automatically quantifying \'flagella-like\' curvature dynamics and wave-like oscillations of clamped microtubules in a \'gliding assay\'.
METHODS: The MATLAB based source code is released as OpenSource and is available at https://github.com/CyCelsLab/MTKnotResolver.
BACKGROUND: Supplementary data are available at Bioinformatics.

BACKGROUND: Recent technological advances have resulted in low-cost GPS loggers that are small enough to be used on a range of seabirds, producing accurate location estimates (± 5 m) at sampling intervals as low as 1 s. However, tradeoffs between battery life and sampling frequency result in studies using GPS loggers on flying seabirds yielding locational data at a wide range of sampling intervals. Metrics derived from these data are known to be scale-sensitive, but quantification of these errors is rarely available. Very frequent sampling, coupled with limited movement, can result in measurement error, overestimating movement, but a much more pervasive problem results from sampling at long intervals, which grossly underestimates path lengths.
METHODS: We use fine-scale (1 Hz) GPS data from a range of albatrosses and petrels to study the effect of sampling interval on metrics derived from the data. The GPS paths were sub-sampled at increasing intervals to show the effect on path length (i.e. ground speed), turning angles, total distance travelled, as well as inferred behavioural states.
RESULTS: We show that distances (and per implication ground speeds) are overestimated (4% on average, but up to 20%) at the shortest sampling intervals (1-5 s) and underestimated at longer intervals. The latter bias is greater for more sinuous flights (underestimated by on average 40% when sampling > 1-min intervals) as opposed to straight flight (11%). Although sample sizes were modest, the effect of the bias seemingly varied with species, where species with more sinuous flight modes had larger bias. Sampling intervals also played a large role when inferring behavioural states from path length and turning angles.
CONCLUSIONS: Location estimates from low-cost GPS loggers are appropriate to study the large-scale movements of seabirds when using coarse sampling intervals, but actual flight distances are underestimated. When inferring behavioural states from path lengths and turning angles, moderate sampling intervals (10-30 min) may provide more stable models, but the accuracy of the inferred behavioural states will depend on the time period associated with specific behaviours. Sampling rates have to be considered when comparing behaviours derived using varying sampling intervals and the use of bias-informed analyses are encouraged.

BACKGROUND: Breast cancer is the most common type of cancer worldwide. If diagnosed and treated early, it has a high chance of cure, and for this, screening tests are necessary, namely mammograms, which are the most commonly used. The objective of this study was to analyze the association between the number of screening and diagnostic mammograms and the number of hospitalizations and deaths from breast cancer.
METHODS: This is a cross-sectional, analytical, retrospective study with secondary data made available by the Ministry of Health. Pearson correlation analysis was employed to assess whether the number of mammograms is associated with the number of deaths and hospitalizations, Poisson regression was used to assess whether an increase in the number of mammograms and hospitalizations is related to the number of deaths, and the Cox-Stuart test was used to analyze the temporal trend of the variables under study and the projection of time series.
RESULTS: There was a strong positive correlation for all age groups when relating the variables hospitalizations and deaths, a moderate-to-strong correlation for the variables mammography and hospitalization, and a weak correlation for the variables mammography and death. There was no statistical significance in the relationship between the number of mammograms and deaths, whereas the hospitalization variable had a significant impact in relation to death, increasing the chance by 0.015%. There has also been a significant growth trend in the variables deaths and hospitalizations in Brazil over the years.
CONCLUSIONS: A growing trend was identified from 2013 to 2021, both in hospitalizations and deaths, thus suggesting that strategies aimed at reformulating public health policies are necessary for earlier diagnosis in order to improve the treatment of breast cancer and the prognosis of the disease.

Salted duck egg yolk, a key ingredient in various specialty foods in China, frequently contains broken eggshell fragments embedded in the yolk due to high-speed shell-breaking processes, which pose significant food safety risks. This paper presents an online detection method, YOLOv7-SEY-DeepSORT (salted egg yolk, SEY), designed to integrate an enhanced YOLOv7 with DeepSORT for real-time and accurate identification of salted egg yolks with impurities on production lines. The proposed method utilizes YOLOv7 as the core network, incorporating multiple Coordinate Attention (CA) modules in its Neck section to enhance the extraction of subtle eggshell impurities. To address the impact of imbalanced sample proportions on detection accuracy, the Focal-EIoU loss function is employed, adaptively adjusting bounding box loss values to ensure precise localization of yolks with impurities in images. The backbone network is replaced with the lightweight MobileOne neural network to reduce model parameters and improve real-time detection performance. DeepSORT is used for matching and tracking yolk targets across frames, accommodating rotational variations. Experimental results demonstrate that YOLOv7-SEY-DeepSORT achieves a mean average precision (mAP) of 0.931, reflecting a 0.53% improvement over the original YOLOv7. The method also shows enhanced tracking performance, with Multiple Object Tracking Accuracy (MOTA) and Multiple Object Tracking Precision (MOTP) scores of 87.9% and 73.8%, respectively, representing increases of 17.0% and 9.8% over SORT and 2.9% and 4.7% over Tracktor. Overall, the proposed method balances high detection accuracy with real-time performance, surpassing other mainstream object detection methods in comprehensive performance. Thus, it provides a robust solution for the rapid and accurate detection of defective salted egg yolks and offers a technical foundation and reference for future research on the automated and safe processing of egg products.

The overall goal of this review is to summarize what is currently known regarding the tracking of blood pressure levels from early childhood into later adulthood and to describe the factors contributing to increased hypertension prevalence across the lifespan. This review describes 4 theoretical constructs of blood pressure trajectory across the lifespan: forward development, forward tracking, forward reversal, and maintenance of normal blood pressure levels.

Half of kindergarten teachers split children into higher and lower ability groups for reading or math. In national data, we predicted kindergarten ability group placement using linear and ordinal logistic regression with classroom fixed effects. In fall, test scores were the best predictors of group placement, but there was bias favoring girls, high-SES (socioeconomic status) children, and Asian Americans, who received higher placements than their scores alone would predict. Net of SES, there was no bias against placing black children in higher groups. By spring, one third of kindergartners moved groups, and high-SES children moved up more than their score gains alone would predict. Teacher-reported behaviors (e.g., attentiveness, approaches to learning) helped explain girls\' higher placements, but did little to explain the higher placements of Asian American and high-SES children.

OBJECTIVE: The integration of a surgical robotic instrument tracking module within optical microscopes holds the potential to advance microsurgery practices, as it facilitates automated camera movements, thereby augmenting the surgeon\'s capability in executing surgical procedures.
METHODS: In the present work, an innovative detection backbone based on spatial attention module is implemented to enhance the detection accuracy of small objects within the image. Additionally, we have introduced a robust data association technique, capable to re-track surgical instrument, mainly based on the knowledge of the dual-instrument robotics system, Intersection over Union metric and Kalman filter.
RESULTS: The effectiveness of this pipeline was evaluated through testing on a dataset comprising ten manually annotated videos of anastomosis procedures involving either animal or phantom vessels, exploiting the Symani®Surgical System-a dedicated robotic platform designed for microsurgery. The multiple object tracking precision (MOTP) and the multiple object tracking accuracy (MOTA) are used to evaluate the performance of the proposed approach, and a new metric is computed to demonstrate the efficacy in stabilizing the tracking result along the video frames. An average MOTP of 74±0.06% and a MOTA of 99±0.03% over the test videos were found.
CONCLUSIONS: These results confirm the potential of the proposed approach in enhancing precision and reliability in microsurgical instrument tracking. Thus, the integration of attention mechanisms and a tailored data association module could be a solid base for automatizing the motion of optical microscopes.

UNASSIGNED: The integration of health and activity data from various wearable devices into research studies presents technical and operational challenges. The Awesome Data Acquisition Method (ADAM) is a versatile, web-based system that was designed for integrating data from various sources and managing a large-scale multiphase research study. As a data collecting system, ADAM allows real-time data collection from wearable devices through the device\'s application programmable interface and the mobile app\'s adaptive real-time questionnaires. As a clinical trial management system, ADAM integrates clinical trial management processes and efficiently supports recruitment, screening, randomization, data tracking, data reporting, and data analysis during the entire research study process. We used a behavioral weight-loss intervention study (SMARTER trial) as a test case to evaluate the ADAM system. SMARTER was a randomized controlled trial that screened 1741 participants and enrolled 502 adults. As a result, the ADAM system was efficiently and successfully deployed to organize and manage the SMARTER trial. Moreover, with its versatile integration capability, the ADAM system made the necessary switch to fully remote assessments and tracking that are performed seamlessly and promptly when the COVID-19 pandemic ceased in-person contact. The remote-native features afforded by the ADAM system minimized the effects of the COVID-19 lockdown on the SMARTER trial. The success of SMARTER proved the comprehensiveness and efficiency of the ADAM system. Moreover, ADAM was designed to be generalizable and scalable to fit other studies with minimal editing, redevelopment, and customization. The ADAM system can benefit various behavioral interventions and different populations.