bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changes in Dynamic Mean Ankle Moment Arm in Unimpaired Walking Across Speeds, Ramps, and Stairs
Authors: Fehr Katherine Heidi , Kent Jenny A. , Major Matthew J. , Adamczyk Peter Gabriel 
Published: April 2024

Abstract
Understanding the natural biomechanics of walking at different speeds and activities is crucial to develop effective assistive devices for persons with lower-limb impairments. While continuous measures such as joint angle and moment are well-suited for biomimetic control of robotic systems, whole-stride summary metrics are useful for describing changes across behaviors and for designing and controlling passive and semi-active devices. Dynamic mean ankle moment arm (DMAMA) is a whole-stride measure representing the moment arm of the ground reaction impulse about the ankle joint—effectively, how “forefoot-dominated” or “hindfoot-dominated” a movement is. DMAMA was developed as a target and performance metric for semi-active devices that adjust once per stride. However, for implementation in this application, DMAMA must be characterized across various activities in unimpaired individuals. In our study, unimpaired participants walked at “slow,” “normal,” and “fast” self-selected speeds on level ground and at a normal self-selected speed while ascending and descending stairs and a 5-degree incline ramp. DMAMA measured from these activities displayed a borderline-significant negative sensitivity to walking speed, a significant positive sensitivity to ground incline, and a significant decrease when ascending stairs compared to descending. The data suggested a nonlinear relationship between DMAMA and walking speed; half of the participants had the highest average DMAMA at their “normal” speed. Our findings suggest that DMAMA varies substantially across activities, and thus, matching DMAMA could be a valuable metric to consider when designing biomimetic assistive lower-limb devices.
Continuous Softening as a State of Hyperelasticity: Examples of Application to the Softening Behavior of the Brain Tissue
Authors: Anssari-Benam Afshin , Saccomandi Giuseppe 
Published: April 2024

Abstract
The continuous softening behavior of the brain tissue, i.e., the softening in the primary loading path with an increase in deformation, is modeled in this work as a state of hyperelasticity up to the onset of failure. That is, the softening behavior is captured via a core hyperelastic model without the addition of damage variables and/or functions. Examples of the application of the model will be provided to extant datasets of uniaxial tension and simple shear deformations, demonstrating the capability of the model to capture the whole-range deformation of the brain tissue specimens, including their softening behavior. Quantitative and qualitative comparisons with other models within the brain biomechanics literature will also be presented, showing the clear advantages of the current approach. The application of the model is then extended to capturing the rate-dependent softening behavior of the tissue by allowing the parameters of the core hyperelastic model to evolve, i.e., vary, with the deformation rate. It is shown that the model captures the rate-dependent and softening behaviors of the specimens favorably and also predicts the behavior at other rates. These results offer a clear set of advantages in favor of the considered modeling approach here for capturing the quasi-static and rate-dependent mechanical properties of the brain tissue, including its softening behavior, over the existing models in the literature, which at best may purport to capture only a reduced set of the foregoing behaviors, and with ill-posed effects.
Using Local Concentration to Model the Progress of Acoustophoretic Assembly of Microspheres in Planar Standing Waves
Authors: Wang Y. J. , Anthony B. W. 
Published: April 2024

Abstract
Acoustophoretic assembly uses a standing acoustic field to move dispersed small particles into a geometric pattern. The technique relies on the acoustic radiation force (ARF), which arises from the interaction between the acoustic field and the particles, and drives the particles toward the pressure nodes or antinodes of the standing wave. Acoustophoretic assembly shows potential for a wide range of applications, including organizing filler materials in composites, creating metamaterials, and fabricating functional biological tissue. However, the method has not yet been incorporated into large-scale manufacturing processes. One barrier is the incomplete understanding of the assembly process. While an ideal final pattern geometry can be calculated from the acoustic field and material properties, there are currently no widespread metrics for measuring the progress of the pattern formation. As a result, it is difficult to know how long the acoustic field should be applied during manufacturing. Our approach uses the local particle concentration to model the acoustophoretic assembly process in bulk acoustic waves. We show that the time-dependent local particle concentration can be derived from the force balance on the particles and a control volume analysis. The analysis is applied to microspheres in a planar standing wave, and an analytical expression is obtained, which yields a time parameter for pattern assembly and suggests a cutoff time. We then use the local concentration to define measurements for the quality of the assembled microsphere pattern. Experiments were carried out using polystyrene microspheres in a glycerol–water mixture to validate the theoretical results.
Effects of the COVID-19 pandemic on people experiencing incarceration: a systematic review
Authors: Williams Darius Benedict , Spinks Bethany , Williams Denitza , Lewis Ruth , Bull Francesca , Edwards Adrian 
Published: April 2024

ObjectiveTo assess the effect of the COVID-19 pandemic on people experiencing incarceration (PEI), focusing particularly on clinical outcomes compared with the general population.DesignSystematic review with narrative synthesis in accordance with the Centre for Reviews and Dissemination’s good practice guidelines.Data sourcesMedline, Social Policy and Practice, Criminology Connection, ASSIA, EMBASE, SCOPUS, Web Of Science, CINAHL, Cochrane Library, Cochrane COVID-19 reviews, COVID-19 Evidence Reviews and L*OVE COVID-19 Evidence databases were searched up to 21 October 2022.Eligibility criteria for selecting studiesWe included studies presenting data specific to adults ≥18 years experiencing incarceration, with exposure to SARS-CoV-2 infection. All studies with a comparison group, regardless of study design and country were included. Studies with no comparison group data or not measuring clinical outcomes/health inequalities were excluded. Studies focussing on detained migrants, forensic hospitals, prison staff and those not in English were also excluded.Data extraction and synthesisTwo reviewers extracted data and assessed risk of bias. Data underwent narrative synthesis using a framework analysis based on the objectives, for infection rates, testing, hospitalisation, mortality, vaccine uptake rates and mental health outcomes. There was no scope for meta-analysis, due to the heterogeneity of evidence available.Results4516 references were exported from the databases and grey literature searched, of which 55 met the inclusion criteria. Most were from the USA and were retrospective analyses. Compared with the general population, PEI were usually found to have higher rates of SARS-CoV-2 infection and poorer clinical outcomes. Conflicting data were found regarding vaccine uptake and testing rates compared with the general population. The mental health of PEI declined during the pandemic. Certain subgroups were more adversely affected by the COVID-19 pandemic, such as ethnic minorities and older PEI.ConclusionPEI have poorer COVID-19 clinical outcomes than the general public, as shown by largely low-quality heterogenous evidence. Further high-quality research of continuing clinical outcomes and appropriate mitigating interventions is required to assess downstream effects of the pandemic on PEI. However, performing such research in the context of incarceration facilities is highly complex and potentially challenging. Prioritisation of resources for this vulnerable group should be a focus of national policy in the event of future pandemics.PROSPERO registration numberCRD42022296968.
Updated cost-effectiveness analysis of adebrelimab plus chemotherapy for extensive-stage small cell lung cancer in China
Authors: Long Yunchun , Wang Hao , Xie Xianhai , Li Junlin , Xu Yuan , Zhou Yujie 
Published: April 2024

ObjectiveThe CAPSTONE-1 trial demonstrated that adebrelimab-based immunotherapy yielded a favourable survival benefit compared with chemotherapy for patients with extensive-stage small cell lung cancer (ES-SCLC). This study aims to evaluate the cost-effectiveness of this immunotherapy in the treatment of ES-SCLC from a healthcare system perspective in China.DesignThe TreeAge Pro software was used to establish a three-state partitioned survival model. Survival data came from the CAPSTONE-1 trial (NCT03711305), and only direct medical costs were included. Utility values were obtained from the published literature. Sensitivity analysis was performed to explore the robustness of the model. The cost-effectiveness of immunotherapy was investigated through scenario and exploratory analyses in various settings.Outcome measuresTotal costs, incremental costs, life years, quality-adjusted life-years (QALYs), incremental QALYs and incremental cost-effectiveness ratio (ICER).ResultsThe basic analysis revealed that the adebrelimab group achieved a total of 1.1 QALYs at a cost of US$65 385, while the placebo group attained 0.78 QALYs at a cost of US$12 741. ICER was US$163 893/QALY. Sensitivity analysis confirmed that the model was robust. Results from scenario and exploratory analyses indicated that the combination of adebrelimab and chemotherapy did not demonstrate cost-effectiveness in any scenario.ConclusionsFrom the perspective of the Chinese healthcare system, adebrelimab in combination with chemotherapy for the treatment of ES-SCLC was not economical compared with chemotherapy.
Comparing nurses attending a specialised mental health programme with and without substance use disorder: a retrospective, observational study in Spain
Authors: Braquehais María Dolores , Mozo Xulián , Llavayol Enric , Gausachs Eva , Santiago Regina , Nieva Gemma , Valero Sergi , Grau-López Lara , Ramos-Quiroga Josep Antoni , Bruguera Eugeni 
Published: April 2024

ObjectivesTo analyse the differences between nurses with and without substance use disorders (SUDs) admitted to a specialised mental health programme.DesignRetrospective, observational study.SettingSpecialised mental health treatment programme for nurses in Catalonia, Spain.Participants1091 nurses admitted to the programme from 2000 to 2021.InterventionsNone.Primary and secondary outcomesSociodemographic, occupational and clinical variables were analysed. Diagnoses followed Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision criteria.ResultsMost nurses admitted to the programme were women (88%, n=960) and came voluntarily (92.1%, n=1005). The mean age at admission was 45 (SD=10.4) years. The most common diagnoses were adjustment disorders (36.6%, n=399), unipolar mood disorders (25.8%, n=282), anxiety disorders (16.4%, n=179) and SUDs (13.8%, n=151). Only 19.2% (n=209) of the sample were hospitalised during their first treatment episode. After multivariate analysis, suffering from a SUD was significantly associated with being a man (OR=4.12; 95% CI 2.49 to 6.82), coming after a directed referral (OR=4.55; 95% CI 2.5 to 7.69), being on sick leave at admission (OR=2.21; 95% CI 1.42 to 3.45) and needing hospitalisation at the beginning of their treatment (OR=12.5; 95% CI 8.3 to 20).ConclusionsNurses with SUDs have greater resistance to voluntarily asking for help from specialised mental health treatment programmes and have greater clinical severity compared with those without addictions. SUDs are also more frequent among men. More actions are needed to help prevent and promote earlier help-seeking behaviours among nurses with this type of mental disorder.
Eating and drinking experience in patients with idiopathic pulmonary fibrosis: a qualitative study
Authors: Alamer Amal Ahmad , Ward Christopher , Forrest Ian , Drinnan Michael , Patterson Joanne 
Published: April 2024

ObjectiveTo explore eating and drinking experiences of patients with idiopathic pulmonary fibrosis (IPF), the impact of any changes associated with their diagnosis and any coping mechanisms developed by patients.SettingPulmonary fibrosis support groups around the UK and the regional Interstitial Lung Diseases Clinic, Newcastle upon Tyne.Participants15 patients with IPF (9 men, 6 women), median age 71 years, range (54–92) years, were interviewed. Inclusion criteria included competent adults (over the age of 18 years) with a secure diagnosis of IPF as defined by international consensus guidelines. Patients were required to have sufficient English language competence to consent and participate in an interview. Exclusion criteria were a history of other lung diseases, a history of pre-existing swallowing problem of other causes that may be associated with dysphagia and individuals with significant communication or other memory difficulties that render them unable to participate in an interview.DesignA qualitative study based on semistructured interviews used purpose sampling conducted between February 2021 and November 2021. Interviews were conducted via video videoconferencing call platform or telephone call, transcribed and data coded and analysed using a reflexive thematic analysis.ResultsThree main themes were identified, along with several subthemes, which were: (1) Eating, as such, is no longer a pleasure. This theme mainly focused on the physical and sensory changes associated with eating and drinking and their effects and the subsequent emotional and social impact of these changes; (2) It is something that happens naturally and just try and get on with it. This theme centred on the self-determined strategies employed to manage changes to eating and drinking; and (3) What is normal. This theme focused on patients seeking information to better understand the changes in their eating and drinking and the patients’ beliefs about what has changed their eating and drinking.ConclusionsTo our knowledge, this is the first study to report on IPF patients’ lived experience of eating and drinking changes associated with their diagnosis. Findings demonstrate that some patients have substantial struggles and challenges with eating and drinking, affecting them physically, emotionally and socially. There is a need to provide better patient information for this area and further study.
Qualitative study exploring the design of a patient-reported symptom-based risk stratification system for suspected head and neck cancer referrals: protocol for work packages 1 and 2 within the EVEREST-HN programme
Authors: Albutt Abigail , Hardman John , McVey Lynn , Odo Chinasa , Paleri Vinidh , Patterson Jo , Webb Sarah , Rousseau Nikki , Kellar Ian , Randell Rebecca 
Published: April 2024

IntroductionBetween 2009/2010 and 2019/2020, England witnessed an increase in suspected head and neck cancer (sHNC) referrals from 140 to 404 patients per 100 000 population. 1 in 10 patients are not seen within the 2-week target, contributing to patient anxiety. We will develop a pathway for sHNC referrals, based on the Head and Neck Cancer Risk Calculator. The evolution of a patient-reported symptom-based risk stratification system to redesign the sHNC referral pathway (EVEREST-HN) Programme comprises six work packages (WPs). This protocol describes WP1 and WP2. WP1 will obtain an understanding of language to optimise the SYmptom iNput Clinical (SYNC) system patient-reported symptom questionnaire for sHNC referrals and outline requirements for the SYNC system. WP2 will codesign key elements of the SYNC system, including the SYNC Questionnaire, and accompanying behaviour change materials.Methods and analysisWP1 will be conducted at three acute National Health Service (NHS) trusts with variation in service delivery models and ensuring a broad mixture of social, economic and cultural backgrounds of participants. Up to 150 patients with sHNC (n=50 per site) and 15 clinicians (n=5 per site) will be recruited. WP1 will use qualitative methods including interviews, observation and recordings of consultations. Rapid qualitative analysis and inductive thematic analysis will be used to analyse the data. WP2 will recruit lay patient representatives to participate in online focus groups (n=8 per focus group), think-aloud technique and experience-based codesign and will be analysed using qualitative and quantitative approaches.Ethics and disseminationThe committee for clinical research at The Royal Marsden, a research ethics committee and the Health Research Authority approved this protocol. All participants will give informed consent. Ethical issues of working with patients on an urgent cancer diagnostic pathway have been considered. Findings will be disseminated via journal publications, conference presentations and public engagement activities.
Literature review and protocol for a prospective multicentre cohort study on multimodal prediction of seizure recurrence after unprovoked first seizure
Authors: Beattie Brooke C , Batista García-Ramó Karla , Biggs Krista , Boissé Lomax Lysa , Brien Donald C , Gallivan Jason P , Ikeda Kristin , Schmidt Matthias , Shukla Garima , Whatley Benjamin , Woodroffe Stephanie , Omisade Antonina , Winston Gavin P 
Published: April 2024

IntroductionEpilepsy is a common neurological disorder characterised by recurrent seizures. Almost half of patients who have an unprovoked first seizure (UFS) have additional seizures and develop epilepsy. No current predictive models exist to determine who has a higher risk of recurrence to guide treatment. Emerging evidence suggests alterations in cognition, mood and brain connectivity exist in the population with UFS. Baseline evaluations of these factors following a UFS will enable the development of the first multimodal biomarker-based predictive model of seizure recurrence in adults with UFS.Methods and analysis200 patients and 75 matched healthy controls (aged 18–65) from the Kingston and Halifax First Seizure Clinics will undergo neuropsychological assessments, structural and functional MRI, and electroencephalography. Seizure recurrence will be assessed prospectively. Regular follow-ups will occur at 3, 6, 9 and 12 months to monitor recurrence. Comparisons will be made between patients with UFS and healthy control groups, as well as between patients with and without seizure recurrence at follow-up. A multimodal machine-learning model will be trained to predict seizure recurrence at 12 months.Ethics and disseminationThis study was approved by the Health Sciences and Affiliated Teaching Hospitals Research Ethics Board at Queen’s University (DMED-2681-22) and the Nova Scotia Research Ethics Board (1028519). It is supported by the Canadian Institutes of Health Research (PJT-183906). Findings will be presented at national and international conferences, published in peer-reviewed journals and presented to the public via patient support organisation newsletters and talks.Trial registration numberNCT05724719.
UISA: User Information Separating Architecture for Commodity Recommendation Policy with Deep Reinforcement Learning
Authors: Xu Aobo , Jian Ling , Yin Yue , Zhang Na 
Published: April 2024

Commodity recommendation contributes an important part of individuals’ daily life. In this context, deep reinforcement learning methods have demonstrated substantial efficacy in enhancing recommender systems’ performance. Nevertheless, several recommender systems directly utilize original feature information as a foundational element for decision-making, which seems simplistic and low efficient. Furthermore, the incorporation of sequential decision-making adds complexity to the task of recommendation.In pursuit of maximizing the long-term sequential returns of recommender systems, our study introduces a novel architecture, named User Information Separating Architecture (UISA). This framework is tailored to align with classic reinforcement learning algorithms and aims to extract the user’s interest value through the discrete processing of both static and dynamic user information. Through integration with deep reinforcement learning, the architecture is oriented towards the maximization of long-term profit and is applicable in sequential recommendation scenarios. We conduct experimental assessments by combining the proposed architecture with proximal policy optimization (PPO) and deep deterministic policy gradient (DDPG) algorithms. The outcomes illustrate marked improvements in commodity recommendation, showcasing enhancements ranging from approximately 5% to 40% in both reward and click-through rate metrics across a self-constructed JDEnv environment and the Virtual Taobao environment. Through comparison experiments, the UISA models demonstrate comparable performance.
Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors
Authors: Zhang Weijie , Maeser Danielle , Lee Adam , Huang Yingbo , Gruener Robert F. , Abdelbar Israa G. , Jena Sampreeti , Patel Anand G. , Huang R. Stephanie 
Published: April 2024

Abstract

Single-cell RNA sequencing (scRNA-seq) greatly advanced the understanding of intratumoral heterogeneity by identifying distinct cancer cell subpopulations. However, translating biological differences into treatment strategies is challenging due to a lack of tools to facilitate efficient drug discovery that tackles heterogeneous tumors. Developing such approaches requires accurate prediction of drug response at the single-cell level to offer therapeutic options to specific cell subpopulations. Here, we developed a transparent computational framework (nicknamed scIDUC) to predict therapeutic efficacies on an individual cell basis by integrating single-cell transcriptomic profiles with large, data-rich pan-cancer cell line screening data sets. This method achieved high accuracy in separating cells into their correct cellular drug response statuses. In three distinct prospective tests covering different diseases (rhabdomyosarcoma, pancreatic ductal adenocarcinoma, and castration-resistant prostate cancer), the predicted results using scIDUC were accurate and mirrored biological expectations. In the first two tests, the framework identified drugs for cell subpopulations that were resistant to standard-of-care (SOC) therapies due to intrinsic resistance or tumor microenvironmental effects, and the results showed high consistency with experimental findings from the original studies. In the third test using newly generated SOC therapy-resistant cell lines, scIDUC identified efficacious drugs for the resistant line, and the predictions were validated with in vitro experiments. Together, this study demonstrates the potential of scIDUC to quickly translate scRNA-seq data into drug responses for individual cells, displaying the potential as a tool to improve the treatment of heterogenous tumors.

Significance:
A versatile method that infers cell-level drug response in scRNA-seq data facilitates the development of therapeutic strategies to target heterogeneous subpopulations within a tumor and address issues such as treatment failure and resistance.