bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of spinal alignment in standing position using Biplanar X-ray images and three-dimensional vertebral models
Authors: Kobayashi Koichi , Sakamoto Makoto , Sasagawa Keisuke , Nakai Masaaki , Okamoto Masashi , Hasegawa Kazuhiro , Narita Kengo 
Published: June 2024

Abstract
We developed two methods for three-dimensional (3D) evaluation of spinal alignment in standing position by image matching between biplanar x-ray images and 3D vertebral models. One used a Slot-Scanning 3D x-ray Imager (sterEOS) to obtain biplanar x-ray images, and the other used a conventional x-ray system and a rotating table. The 3D vertebral model was constructed from the CT scan data. The spatial position of the vertebral model was determined by minimizing the contour difference between the projected image of the model and the biplanar x-ray images. Verification experiments were conducted using a torso phantom. The relative positions of the upper vertebrae to the lowest vertebrae of the cervical, thoracic, and lumbar vertebrae were evaluated. The mean, standard deviation, and mean square error of the relative position were less than 1° and 1 mm in all cases for sterEOS. The maximum mean squared errors of the conventional x-ray system and the rotating table were 0.7° and 0.4 mm for the cervical spine, 1.0° and 1.2 mm for the thoracic spine, and 1.1° and 1.2 mm for the lumbar spine. Therefore, both methods could be useful for evaluating the spinal alignment in standing position.
Experience of Patients With Heroin Addiction Receiving Methadone Maintenance Treatment in Community Settings in Taiwan
Authors: SHIH Meng-Hsiu , HSU Wen-Yu , SIAO Chun-Ling , LEE Li-Hung , CHEN Shu-Ling , TSAY Shiow-Luan , YANG Cheng-I 
Published: June 2024

ABSTRACT

Background
The World Health Organization has identified methadone maintenance therapy (MMT) as the most effective treatment for reducing patient dependence on heroin. In Taiwan, MMT has been used as a heroin harm reduction strategy since 2006. Although the effectiveness of MMT in reducing heroin addiction has been examined quantitatively in prison samples, little attention has been paid to the experiences and perspectives of patients with heroin addiction receiving MMT. This study was designed to address this gap in scientific knowledge.

Purpose
The aim of this study was to investigate the experiences of individuals struggling with heroin addiction who are receiving MMT in the community.

Methods
A qualitative descriptive research approach and semistructured interviews were used in this study. We interviewed 14 participants who had received MMT in a medical center in central Taiwan. All of the interview data were recorded, transcribed, and analyzed using qualitative content analysis.

Results
Four themes emerged: (a) a chance to change one's life, (b) the helpfulness of MMT, (c) a sense of being restricted and controlled, and (d) need for support.

Conclusions/Implications for Practice
This article fills a gap in current scholarly understanding of patient experiences and their perspectives on the helpfulness of MMT. Understanding patient experiences and perspectives is critical to informing and developing concrete strategies for clinical practice and MMT policy. Clinical professionals should assess patient needs and concerns to determine whether they are met by current treatment programs. Policymakers should design more flexible policies to facilitate easier access by patients to methadone to reduce the risk of relapse.
Current opinion: functional dyspepsia
Authors: Olson Caroline G. , Travers Paul , Lacy Brian E. 
Published: June 2024

Purpose of reviewFunctional dyspepsia is a common gastrointestinal disease that is under-recognized and under-diagnosed. It is a complex disorder of gut–brain interaction with no FDA-approved treatment options. The purpose of this review is to highlight updates in the proposed pathophysiology and present new data regarding potential therapies for functional dyspepsia.Recent findingsAlterations in the intestinal microbiome and integrity of the intestinal membrane may play a crucial role in the pathogenesis of functional dyspepsia. The low FODMAP diet, in addition to modulating the microbiome with antibiotics and probiotics, are targets for large future studies. Novel methods of delivery of gut–brain therapies have shown promising results, especially virtual reality.SummaryThe pathophysiology and management of functional dyspepsia is complex and there is still much unknown; however, continued research is identifying new targets for treatment. New and more targeted treatment options provide clinicians a variety of tools to offer patients with functional dyspepsia.
Use of piezoelectric instrumentation in craniofacial surgery
Authors: Bessen Sarah , Gadkaree Shekhar K. , Derakhshan Adeeb 
Published: June 2024

Purpose of reviewThe use of piezoelectric instrumentation is increasingly recognized as an alternative to traditional bone-cutting techniques across a wide array of surgeries. Here, we provide an overview of the technique, including device principles, benefits, and drawbacks. We also review its use in craniofacial surgery.Recent findingsPiezoelectric surgery is a minimally invasive bone-cutting system with lower risk of damage to surrounding soft tissue structures. Indications for its use are rapidly expanding across multiple fields, including craniofacial surgery. To date, piezosurgical techniques have been most widely adopted and studied in the contexts of rhinoplasty, orthognathic surgery, and cranioplasty in craniosynostosis. Piezosurgery can facilitate more precise and consistent osteotomies while decreasing morbidities associated with traditional osteotomy techniques. Primary limitations include cost and concerns regarding increased operative times secondary to operator learning curves and decreased cutting efficiency.SummaryPiezoelectric surgery represents an alternative to traditional bone-cutting modalities to improve precision, consistency, and safety of osteotomies. Further research is needed to better understand the efficacy of the technique as well as potential for additional applications.
Factors affecting anal sphincter recruitment during intraoperative pudendal nerve stimulation
Authors: Lagunas Amador C , Chen Po-Ju , Ruiz Luis , Jhand Amolak S , Baishya Nystha , Lempka Scott F , Gupta Priyanka , Bruns Tim M 
Published: June 2024

AbstractIntroduction and HypothesisThe relationship between pudendal neuromodulation and patient factors is not well understood. This study aimed to identify and quantify physiological, demographic, and stimulation factors that significantly affect external anal sphincter (EAS) recruitment and outcomes in participants receiving pudendal neuromodulation for treatment of lower urinary tract symptoms and pelvic pain.MethodsParticipants (N=16) provided demographic and diagnostic information upon entry to this observational study. EAS activation at different stimulation amplitudes and pulse widths was recorded during lead implantation. Magnetic resonance imaging and computed tomography were used to determine the distance of the electrodes on the implanted lead from the nerve. Linear mixed modeling was used to quantify the impact of each variable on EAS recruitment.ResultsParticipant sex, age, and body-mass index did not significantly affect EAS recruitment with pudendal nerve stimulation. Participant diagnoses had significant relationships to EAS recruitment, likely due to unbalanced group sizes. A pulse width of 210 µs required less current than 60 µs (p = 0.005) and less charge than 450 µs (p = 0.02) to activate the EAS at threshold. Increased electrode-to-nerve distance decreased the magnitude of the EAS response (p = 0.0011), increased the EAS activation threshold (p < 0.001), and was related to reduced bladder symptom improvements.ConclusionsOf the three tested pulse widths, 210 µs requires the least charge and is a good choice for stimulation. The distance between the electrode and pudendal nerve has an important role in nerve recruitment and minimizing this distance should be a priority during lead implantation.Brief SummaryThis study identifies key factors in external anal sphincter recruitment during pudendal neuromodulation that should be considered during lead implantation.
Training data composition determines machine learning generalization and biological rule discovery
Authors: Ursu Eugen , Minnegalieva Aygul , Rawat Puneet , Chernigovskaya Maria , Tacutu Robi , Sandve Geir Kjetil , Robert Philippe A. , Greiff Victor 
Published: June 2024

AbstractSupervised machine learning models rely on training datasets with positive (target class) and negative examples. Therefore, the composition of the training dataset has a direct influence on model performance. Specifically, negative sample selection bias, concerning samples not representing the target class, presents challenges across a range of domains such as text classification and protein-protein interaction prediction. Machine-learning-based immunotherapeutics design is an increasingly important area of research, focusing on designing antibodies or T-cell receptors (TCRs) that can bind to their target molecules with high specificity and affinity. Given the biomedical importance of immunotherapeutics, there is a need to address the unresolved question of how negative training set composition impacts model generalization and biological rule discovery to enable rational and safe drug design. We set out to study this question in the context of the antibody-antigen binding prediction problem by varying the negative class, encompassing a binding affinity gradient. We based our investigation on large synthetic datasets that provide ground truth structure-based antibody-antigen binding data, allowing access to residue-wise binding energy on the binding interface. We found that both out-of-distribution generalization and binding rule discovery depended on the type of negative dataset used. Importantly, we discovered that a model’s capacity to learn the binding rules of the positive dataset is not a trivial correlate of its classification accuracy. We confirmed our findings with real-world relevant experimental data. Our work highlights the importance of considering training dataset composition for achieving optimal out-of-distribution performance and rule learning in machine-learning-based research.Significance StatementThe effectiveness of supervised machine learning models hinges on the composition of their training datasets, particularly the inclusion of negative examples. This bias in negative sample selection can greatly impact model performance. As the development of immunotherapeutic agents using machine learning is becoming increasingly crucial in biomedicine, understanding the impact of negative training set composition is imperative. Our study, focused on the antibody-antigen binding prediction problem, reveals that the choice of negative dataset significantly affects both out-of-distribution generalization and binding rule discovery across synthetic and experimental data. These findings underscore the necessity of carefully considering training dataset composition in machine-learning-driven biomedical research for optimal performance, robustness and meaningful rule acquisition.
Mutations in the albinism geneoca2alter vision-dependent prey capture behavior in the Mexican tetra
Authors: Choy Stefan , Thakur Sunishka , Polyakov Ellen , Abdelaziz Jennah , Lloyd Evan , Enriquez Maya , Jayan Nikita , Fily Yaouen , McGaugh Suzanne , Keene Alex C , Kowalko Johanna E 
Published: June 2024

AbstractUnderstanding the phenotypic consequences of naturally occurring genetic changes, as well as their impact on fitness, is fundamental to understanding how organisms adapt to an environment. This is critical when genetic variants have pleiotropic effects, as determining how each phenotype impacted by a gene contributes to fitness is essential to understand how and why traits have evolved. A striking example of a pleiotropic gene contributing to trait evolution is theoca2gene, coding mutations in which underlie albinism and reductions of sleep in the blind Mexican cavefish,Astyanax mexicanus. Here, we characterize the effects of mutations in theoca2gene on larval prey capture. We find that when conspecific surface fish with engineered mutations in theoca2allele are hunting, they use cave-like, wide angle strikes to capture prey. However, unlike cavefish or surface fish in the dark, which rely on lateral line mediated hunting,oca2mutant surface fish use vision when striking at prey from wide angles. Finally, we find that whileoca2mutant surface fish do not outcompete pigmented surface siblings in the dark, pigmented fish outcompete albino fish in the light. This raises the possibility that albinism is detrimental to larval feeding in a surface-like lighted environment, but does not have negative consequences for fish in cave-like, dark environments. Together, these results demonstrate thatoca2plays a role in larval feeding behavior inA. mexicanus. Further, they expand our understanding of the pleiotropic phenotypic consequences ofoca2in cavefish evolution.
Age differences in brain functional connectivity underlying proactive interference in working memory
Authors: Andersson P , Schrooten M.G.S. , Persson J 
Published: June 2024

ABSTRACTAging is typically accompanied by a decline in working memory (WM) capacity, even in the absence of pathology. Proficient WM requires cognitive control processes which can retain goal-relevant information for easy retrieval and resolve interference from irrelevant information. Aging has been associated with a reduced ability to resolve proactive interference (PI) in WM, leading to impaired retrieval of goal-relevant information. It remains unclear how age-related differences in the ability to resolve PI in WM are related to patterns of resting-state functional connectivity (rsFC) in the brain. Here we investigated the association between PI in WM and rsFC cross-sectionally (n = 237) and 5-year longitudinally (n = 134) across the adult life span by employing both seed-based and data-driven approaches. Results revealed that the ability to resolve PI was associated with differential patterns of rsFC in younger/middle-aged adults (25-60y) and older adults (65-80y) in two clusters centered in the vermis and caudate. Specifically, more PI was associated with stronger inferior frontal gyrus – vermis connectivity and weaker inferior frontal gyrus – caudate connectivity in older adults, while younger/middle-aged adults showed associations in the opposite directions with the identified clusters. Whole brain multivariate pattern analyses showed age-differential patterns of rsFC indicative of age-related structural decline and age-related compensation. The current results show that rsFC is associated with the ability to control PI in WM and that these associations are modulated by age.
Multi-task Bayesian Model Combining FDG-PET/CT Imaging and Clinical Data for Interpretable High-Grade Prostate Cancer Prognosis
Authors: Larose Maxence , Archambault Louis , Touma Nawar , Brodeur Raphaël , Desroches Félix , Raymond Nicolas , Bédard-Tremblay Daphnée , LeBlanc Danahé , Rasekh Fatemeh , Hovington Hélène , Neveu Bertrand , Vallières Martin , Pouliot Frédéric 
Published: June 2024

AbstractWe propose a fully automatic multi-task Bayesian model, named Bayesian Sequential Network (BSN), for predicting high-grade (Gleason≥8) prostate cancer (PCa) prognosis using pre-prostatectomy FDG-PET/CT images and clinical data. BSN performs one classification task and five survival tasks: predicting lymph node invasion (LNI), biochemical recurrence-free survival (BCR-FS), metastasis-free survival, definitive androgen deprivation therapy-free survival, castration-resistant PCa-free survival, and PCa-specific survival (PCSS). Experiments are conducted using a dataset of 295 patients. BSN outperforms widely used nomograms on all tasks except PCSS, leveraging multi-task learning and imaging data. BSN also provides automated prostate segmentation, uncertainty quantification, personalized feature-based explanations, and introducesdynamic predictions, a novel approach that relies on short-term outcomes to refine long-term prognosis. Overall, BSN shows great promise in its ability to exploit imaging and clinico-pathological data to predict poor outcome patients that need treatment intensification with loco-regional or systemic adjuvant therapy for high-risk PCa.
Multi-joint approach for assessing lower limb proprioception: reliability and precision in school-aged children
Authors: Jacobs Nina , van den Bogaart Maud , Hallemans Ann , Meyns Pieter 
Published: June 2024

AbstractBackgroundThe Joint Position Reproduction (JPR) approach has been commonly used to assess joint position sense (JPS), however, no prior study investigated its psychometric properties in children. This study aimed to assess the reliability and precision of a newly developed multi-joint JPR protocol for assessing lower limb JPS in school-aged typically developing (TD) children.MethodsAnkle, knee and hip JPS was assessed in TD children (aged 5–12 years), on two different days, by a single rater using a standardized JPR protocol (re-identification of a passively placed target position of the ipsilateral joint). The mean and best error(JRE,°) between target and reproduction angle were calculated from three-dimensional(3D) kinematics for each tested joint on both sides for three trials. Furthermore, total, joint- and limb-JRE scores were provided for clinical use. For JPR-reliability, the Intraclass Correlation Coefficient(ICC,2.1) was reported. For JPR-precision, the standard error of measurement (SEM) was calculated.Results270 JPR trials were assessed in 15 TD children (8.6±1.2 years,8boys). The mean and best JRE, summarized for all joints for test and retest, was 3.7° and 2.5°, respectively. The ICC were poor to fair(0.01-0.44) for mean JRE, but fair to very good(0.46-0.77) for best JRE. The SEM ranged from 0.8°–1.8°, depending on the joint and side being tested.ConclusionEvaluating ankle, knee and hip JPS in children, using passive JPR, is more reliable and precise when using the best JRE. This study highlights the need for a multi-joint JPR approach in research and clinics, and provides joint- and limb-specific SEM values.
An artificial-intelligence interpretable tool to predict risk of deep vein thrombosis after endovenous thermal ablation
Authors: Tabari Azadeh , Ma Yu , Alfonso Jesus , Gebran Anthony , Kaafarani Haytham , Bertsimas Dimitris , Daye Dania 
Published: June 2024

AbstractIntroductionEndovenous thermal ablation (EVTA) stands as one of the primary treatments for superficial venous insufficiency. Concern exists about the potential for thromboembolic complications following this procedure. Although rare, those complications can be severe, necessitating early identification of patients prone to increased thrombotic risks. This study aims to leverage AI-based algorithms to forecast patients’ likelihood of developing deep vein thrombosis (DVT) within 30 days following EVTA.Materials and MethodsFrom 2007 to 2017, all patients who underwent EVTA were identified using the American College of Surgeons National Surgical Quality Improvement Program database. We developed and validated 4 machine learning models using demographics, comorbidities, and laboratory values to predict the risk of postoperative deep vein thrombosis: Classification and Regression Trees (CART), Optimal Classification Trees (OCT), Random Forests, and Extreme Gradient Boosting (XGBoost). The models were trained using all the available variables. SHAP analysis was adopted to interpret model outcomes and offer medical insights into feature importance and interactions.ResultsA total of 21,549 patients were included (mean age of 54 ± SD years, 67% female). In this cohort, 1.59% developed DVT. The XGBoost model had good discriminative power for predicting DVT risk with AUC of 0.711 in the hold-out test set for all-variable model. Stratification of the test set by age, BMI, preoperative white blood cell and platelet count shows that the model performs equally well across these groups.ConclusionWe developed and validated an interpretable model that enables physicians to predict which patients with superficial venous insufficiency has higher risk of developing deep vein thrombosis within 30 days following endovenous thermal ablation.
Multiple Physiological and Behavioural Parameters Identification for Dietary Monitoring Using Wearable Sensors: A Study Protocol
Authors: Shi Mayue , Zhou Jiaying , Cai Mingzhu 
Published: June 2024

AbstractIntroductionTraditional dietary intake assessment is labour- and time-consuming and prone to inaccuracies and biases. Emerging wearable sensing technology may offer a promising solution. This protocol paper describes a study investigating the physiological responses to energy intake utilising a customised wearable multi-sensor band, which is specifically designed to monitor multiple physiological and behavioural responses related to eating and digestion events for dietary monitoring.Methods and AnalysisThis study will recruit 10 healthy volunteers from databases and public advertisements, with informed consent required prior to participation. Participants will attend two main study visits at a clinical research facility, consuming pre-defined high- and low-calorie meals in a randomised order. Wearable sensors will be worn throughout the eating episodes to track hand-to-mouth movements and physiological changes, including skin temperature (Tsk), heart rate (HR), and oxygen saturation (SpO2). These sensor readings will be validated against a traditional bedside monitor which additionally measures blood pressure. Blood samples will be collected via intravenous cannula to measure blood glucose, insulin, and hormone levels. Relationship between eating episodes (e.g., occurrence, duration, use of cutlery, high- vs. low-calorie) with hand movement patterns, as well as physiological and blood biochemical responses, will be analysed.Ethics and DisseminationEthical approval has been granted by London – Westminster Research Ethics Committee. REC reference: 23/PR/1379. Written informed consent will be obtained from all participants. Findings will be disseminated through peer-reviewed journals, conferences, and seminar presentations. Protocol V.5. Protocol date: 16 January 2024.Trial Registration NumberNCT06398340.Strengths and Limitations of This StudyThis study is the first trial to develop an objective and reproducible wearable dietary monitoring tool by tracking physiological and motor changes. The novelty of this tool is the ability to estimate food intake without capturing food images which raises fewer privacy concerns compared to the existing technologies in this field.The comprehensive monitoring of various physiological and behavioural parameters provides a thorough evaluation of the relationship between eating behaviour and physiological changes, with validation through bedside monitors.The exploratory outcomes of the study offer the opportunity to identify physiological markers that can be tracked by a wearable device to predict postprandial blood glucose and hormone levels that have implications for glycaemic control and appetite regulation.This study recruits healthy subjects, and investigations should be expanded to include disease groups such as obese individuals who may have different cardiac outputs.The study will be conducted under a controlled environment and requires further investigations in real-life settings.