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Abstract Objectives To present a framework to develop and implement a fast-track artificial intelligence (AI) curriculum into an existing radiology residency program, with the potential to prepare a new generation of AI conscious radiologists. Methods The AI-curriculum framework comprises five sequential steps: (1) forming a team of AI experts, (2) assessing the residents’ knowledge level and needs, (3) defining learning objectives, (4) matching these objectives with effective teaching strategies, and finally (5) implementing and evaluating the pilot. Following these steps, a multidisciplinary team of AI engineers, radiologists, and radiology residents designed a 3-day program, including didactic lectures, hands-on laboratory sessions, and group discussions with experts to enhance AI understanding. Pre- and post-curriculum surveys were conducted to assess participants’ expectations and progress and were analyzed using a Wilcoxon rank-sum test. Results There was 100% response rate to the pre- and post-curriculum survey (17 and 12 respondents, respectively). Participants’ confidence in their knowledge and understanding of AI in radiology significantly increased after completing the program (pre-curriculum means 3.25 ± 1.48 (SD), post-curriculum means 6.5 ± 0.90 (SD), p-value = 0.002). A total of 75% confirmed that the course addressed topics that were applicable to their work in radiology. Lectures on the fundamentals of AI and group discussions with experts were deemed most useful. Conclusion Designing an AI curriculum for radiology residents and implementing it into a radiology residency program is feasible using the framework presented. The 3-day AI curriculum effectively increased participants’ perception of knowledge and skills about AI in radiology and can serve as a starting point for further customization. Critical relevance statement The framework provides guidance for developing and implementing an AI curriculum in radiology residency programs, educating residents on the application of AI in radiology and ultimately contributing to future high-quality, safe, and effective patient care. Key points • AI education is necessary to prepare a new generation of AI-conscious radiologists. • The AI curriculum increased participants’ perception of AI knowledge and skills in radiology. • This five-step framework can assist integrating AI education into radiology residency programs. Graphical Abstract

Breast cancer remains a global health problem requiring effective diagnostic methods for early detection, in order to achieve the World Health Organization’s ultimate goal of breast self-examination. A literature review indicates the urgency of improving diagnostic methods and identifies thermography as a promising, cost-effective, non-invasive, adjunctive, and complementary detection method. This research explores the potential of using machine learning techniques, specifically Bayesian networks combined with convolutional neural networks, to improve possible breast cancer diagnosis at early stages. Explainable artificial intelligence aims to clarify the reasoning behind any output of artificial neural network-based models. The proposed integration adds interpretability of the diagnosis, which is particularly significant for a medical diagnosis. We constructed two diagnostic expert models: Model A and Model B. In this research, Model A, combining thermal images after the explainable artificial intelligence process together with medical records, achieved an accuracy of 84.07%, while model B, which also includes a convolutional neural network prediction, achieved an accuracy of 90.93%. These results demonstrate the potential of explainable artificial intelligence to improve possible breast cancer diagnosis, with very high accuracy.

Renewable energy sources are essential to address climate change, fossil fuel depletion, and stringent environmental regulations in the subsequent decades. Horizontal-axis wind turbines (HAWTs) are particularly suited to meet this demand. However, their efficiency is affected by environmental factors because they operate in open areas. Adverse weather conditions like rain reduce their aerodynamic performance. This study investigates wind turbine power prediction under rainy conditions by integrating Blade Element Momentum (BEM) theory with explainable artificial intelligence (XAI). The S809 airfoil’s aerodynamic characteristics, used in NREL wind turbines, were analyzed using ANSYS FLUENT and symbolic regression under varying rain intensities. Simulations at a Reynolds number (Re) of 1 × 106 were performed using the Discrete Phase Model (DPM) and k–ω SST turbulence model, with liquid water content (LWC) values of 0 (dry), 10, 25, and 39 g/m3. The lift and drag coefficients were calculated at various angles of attack for all the conditions. The results indicated that rain led to reduced lift and increased drag. The innovative aspect of this research is the development of machine learning models predicting changes in the airfoil coefficients under rain with an R2 value of 0.97. The proposed XAI framework models rain effects at a lower computational time, enabling efficient wind farm performance assessment in rainy conditions compared to conventional CFD simulations. It was found that a heavy rain LWC of 39 g/m3 could reduce power output by 5.7% to 7%. These findings highlight the impact of rain on aerodynamic performance and the importance of advanced predictive models for optimizing renewable energy generation.

This paper proposes a solution to address the challenges of high storage and transport costs associated with using hydrogen (H2) as an energy source. It suggests utilizing ammonia (NH3) as a hydrogen carrier to produce H2 onsite for hydrogen gas turbines. NH3 offers higher volumetric hydrogen density compared to liquid H2, potentially reducing shipping costs by 40%. The process involves NH3 pyrolysis, which utilizes the heat waste from exhaust gas generated by gas turbines to produce H2 and nitrogen (N2). Numerical simulations were conducted to design and understand the behaviour of the heat recapture NH3 decomposition system. The design considerations included the concept of the number of transfer units and heat exchanger efficiency, achieving a heat recapture system efficiency of up to 91%. The simulation of NH3 decomposition was performed using ANSYS, a commercial simulation software, considering wall surface reactions, turbulent flow, and chemical reaction. Parameters such as activation energy and pre-exponential factor were provided by a study utilizing a nickel wire for NH3 decomposition experiments. The conversion of NH3 reached up to 94% via a nickel-based catalyst within a temperature range of 823 K to 923 K which is the exhaust gas temperature range. Various factors were considered to compare the efficiency of the system, including the mass flow of NH3, operating gauge pressure, mass flow of exhaust gas, among others. Result showed that pressure would not affect the conversion of NH3 at temperatures above 800 K, thus a lower amount of energy is required for a compression purpose in this approach. The conversion is maintained at 94% to 97% when lower activation energy is applied via a ruthenium-based catalyst. Overall, this study showed the feasibility of utilizing convective heat transfer from exhaust gas in hydrogen production by NH3 pyrolysis, and this will further enhance the development of NH3 as the potential H2 carrier for onsite production in hydrogen power generation.

AbstractThe rapid rise in blockchain-based Decentralized Autonomous Organizations (DAOs) offers policy-makers and decision-makers new opportunities to automatically execute decisions and processes that help enhance transparency, accountability, participation and trust. Yet, many DAOs have a limited lifespan. There is little empirical evidence of the effect of governance elements on the viability of DAOs. Using 220 on-chain governed DAOs, this paper analyses how governance elements (accountability, decision/voting, and incentives) influence the viability of DAOs in the long-term. The findings show that DAOs without weighted decision-making and without incentive structures are more viable than those with weighted decision power and incentive mechanisms. This suggests that financial and share-like DAO governance elements do not or may even negatively contribute to the long-term viability of DAOs. Also, voting power distribution is found to have a statistically significant influence on DAOs’ viability. We further propose a preliminary theory that relates governance elements to the long-term viability of DAOs. These insights will help policy-makers in designing more viable DAOs. Future research should investigate how DAO objectives, the chosen deployment infrastructure and the type of users can impact the long-term viability of DAOs.

Abstract Lentiviral vectors (LV) have proven to be powerful tools for stable gene delivery in both dividing and non-dividing cells. Approval of these LVs for use in clinical applications has been achieved by improvements in LV design. Critically important characteristics concerning quality control are LV titer quantification and the detection of impurities. However, increasing evidence concerning high variability in titration assays indicates poor harmonization of the methods undertaken to date. In this study, we developed a direct reverse transcription droplet digital PCR (Direct RT-ddPCR) approach without RNA extraction and purification for estimation of LV titer and RNA genome integrity. The RNA genome integrity was assessed by RT-ddPCR assays targeted to four distant regions of the LV genome. Results of the analyses showed that direct RT-ddPCR without RNA extraction and purification performs similarly to RT-ddPCR on purified RNA from 3 different LV samples, in terms of robustness and assay variance. Interestingly, these RNA titer results were comparable to physical titers by p24 antigen ELISA (enzyme-linked immunosorbent assay). Moreover, we confirmed the partial degradation or the incomplete RNA genomes in the prepared 3 LV samples. These results may partially explain the discrepancy of the LV particle titers to functional titers. This work not only demonstrates the feasibility of direct RT-ddPCR in determining LV titers, but also provides a method that can be easily adapted for RNA integrity assessment.

Hg and Pb metals are major concerns because of their high degree of toxicity in public environment, which also pollute aquatic systems. Nanocomposite adsorbents have been developed for cleaning polluted water at low. The study aims to determine the removal efficiency of magnetite carbon dots nanocomposite in case of Hg and Pb in the aqueous solution. In this paper, magnetite carbon dots (symbolized as Fe3O4/CDs) nanocomposite was synthesized through a two-step process of co-precipitation and pyrolysis methods. The synthesized nanocomposite was analyzed using Utraviolet visible (UV-vis), Fourier transform infrared spectroscopy (FTIR), scanning electron electron microscopy (SEM), electron dispersive X-ray fluorescence (EDXRF), X-ray diffraction (XRD) and atomic absorption spectrophotometer (AAS). According to the results, the synthesized (Fe3O4/CDs) nanocomposites were found to be 20 nm in diameter, superparamagnetic property, surface roughness and deformations, important functional groups, iron-rich nanocomposite and favorable removal efficiency for Hg (82.70 %) and Pb (72.91 %), respectively. Therefore, the results indicated that these Fe3O4/CDs nanocomposites are potentially attractive agents for the removal of heavy metals ions, especially Hg and Pb from industrial wastewater.

OBJECTIVES (BACKGROUND):. To externally validate clinical prediction models that aim to predict progression to invasive ventilation or death on the ICU in patients admitted with confirmed COVID-19 pneumonitis. DESIGN:. Single-center retrospective external validation study. DATA SOURCES:. Routinely collected healthcare data in the ICU electronic patient record. Curated data recorded for each ICU admission for the purposes of the U.K. Intensive Care National Audit and Research Centre (ICNARC). SETTING:. The ICU at Manchester Royal Infirmary, Manchester, United Kingdom. PATIENTS:. Three hundred forty-nine patients admitted to ICU with confirmed COVID-19 Pneumonitis, older than 18 years, from March 1, 2020, to February 28, 2022. Three hundred two met the inclusion criteria for at least one model. Fifty-five of the 349 patients were admitted before the widespread adoption of dexamethasone for the treatment of severe COVID-19 (pre-dexamethasone patients). OUTCOMES:. Ability to be externally validated, discriminate, and calibrate. METHODS:. Articles meeting the inclusion criteria were identified, and those that gave sufficient details on predictors used and methods to generate predictions were tested in our cohort of patients, which matched the original publications’ inclusion/exclusion criteria and endpoint. RESULTS:. Thirteen clinical prediction articles were identified. There was insufficient information available to validate models in five of the articles; a further three contained predictors that were not routinely measured in our ICU cohort and were not validated; three had performance that was substantially lower than previously published (range C-statistic = 0.483–0.605 in pre-dexamethasone patients and C = 0.494–0.564 among all patients). One model retained its discriminative ability in our cohort compared with previously published results (C = 0.672 and 0.686), and one retained performance among pre-dexamethasone patients but was poor in all patients (C = 0.793 and 0.596). One model could be calibrated but with poor performance. CONCLUSIONS:. Our findings, albeit from a single center, suggest that the published performance of COVID-19 prediction models may not be replicated when translated to other institutions. In light of this, we would encourage bedside intensivists to reflect on the role of clinical prediction models in their own clinical decision-making.

IntroductionBCL-2 family proteins are important for tumour cell survival and drug resistance in multiple myeloma (MM). Although proteasome inhibitors are effective anti-myeloma drugs, some patients are resistant and almost all eventually relapse. We examined the function of BCL-2 family proteins in stromal-mediated resistance to carfilzomib-induced cytotoxicity in MM cells.MethodsCo-cultures employing HS5 stromal cells were used to model the interaction with stroma. MM cells were exposed to CFZ in a 1-hour pulse method. The expression of BCL-2 family proteins was assessed by flow cytometry and WB. Pro-survival proteins: MCL-1, BCL-2 and BCL-XL were inhibited using S63845, ABT-199 and A-1331852 respectively. Changes in BIM binding partners were examined by immunoprecipitation and WB.ResultsCFZ induced dose-dependent cell death of MM cells, primarily mediated by apoptosis. Culture of MM cells on HS-5 stromal cells resulted in reduced cytotoxicity to CFZ in a cell contact-dependent manner, upregulated expression of MCL-1 and increased dependency on BCL-XL. Inhibiting BCL-XL or MCL-1 with BH-3 mimetics abrogated stromal-mediated protection only at high doses, which may not be achievable in vivo. However, combining BH-3 mimetics at sub-therapeutic doses, which alone were without effect, significantly enhanced CFZ-mediated cytotoxicity even in the presence of stroma. Furthermore, MCL-1 inhibition led to enhanced binding between BCL-XL and BIM, while blocking BCL-XL increased MCL-1/BIM complex formation, indicating the cooperative role of these proteins.ConclusionStromal interactions alter the dependence on BCL-2 family members, providing a rationale for dual inhibition to abrogate the protective effect of stroma and restore sensitivity to CFZ.

Abstract Objective To determine a break‐even point in the carbon footprint of disposable and reusable instrument sets used in the delivery room. This can aid hospitals in making sustainable choices. Methods Observational study conducted in a university hospital with an obstetric care centre. The study used life cycle assessment (LCA) to compare a reusable (minimal 500 times use) with a disposable instrumental set (single use). LCA quantifies the environmental impact of products over their entire life cycle. The contribution to climate change (i.e., carbon footprint) was used as the environmental indicator [in kg CO2 equivalent (eq.)]. Primary outcome was to determine a ‘break‐even point’: the number of uses at which the carbon footprint of the two sets was similar. Secondary outcomes: (1) ‘worst case scenario’, in which both sets are only used once; (2) ‘scenario of 500 deliveries’ and (3) annual carbon footprint reduction when switching to the set with the lowest environmental impact. Results After ≥3 times use, the carbon footprint of the reusable set becomes lower than the disposable set. When both sets are used only once, the reusable set had a higher impact on the environment (1.2 kg CO2 eq. difference). In case of using both sets during 500 deliveries, the difference in kg CO2 eq. was 400 kg CO2 eq., corresponding with a 2.3 times lower environmental impact in favour of the reusable set and a reduction of about 1800 kg CO2 eq. per year. Conclusions Disposable instrumental sets used in the delivery room have a higher impact on the environment compared to reusable sets.

Objectives Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease affecting mainly the axial skeleton. Peripheral involvement (arthritis, enthesitis and dactylitis) and extra-musculoskeletal manifestations, including uveitis, psoriasis and bowel inflammation, occur in a relevant proportion of patients. AS is responsible for chronic and severe back pain caused by local inflammation that can lead to osteoproliferation and ultimately spinal fusion. The association of AS with the human leucocyte antigen-B27 gene, together with elevated levels of chemokines, CCL17 and CCL22, in the sera of patients with AS, led us to study the role of CCR4+ T cells in the disease pathogenesis.Methods CD8+CCR4+ T cells isolated from the blood of patients with AS (n=76) or healthy donors were analysed by multiparameter flow cytometry, and gene expression was evaluated by RNA sequencing. Patients with AS were stratified according to the therapeutic regimen and current disease score.Results CD8+CCR4+ T cells display a distinct effector phenotype and upregulate the inflammatory chemokine receptors CCR1, CCR5, CX3CR1 and L-selectin CD62L, indicating an altered migration ability. CD8+CCR4+ T cells expressing CX3CR1 present an enhanced cytotoxic profile, expressing both perforin and granzyme B. RNA-sequencing pathway analysis revealed that CD8+CCR4+ T cells from patients with active disease significantly upregulate genes promoting osteogenesis, a core process in AS pathogenesis.Conclusions Our results shed light on a new molecular mechanism by which T cells may selectively migrate to inflammatory loci, promote new bone formation and contribute to the pathological ossification process observed in AS.

Abstract Background Early parent-implemented intervention enhances parent-child interaction and improves language skills in children with autism spectrum disorders (ASD). Parent coaching is often delivered as standard care for children with ASD, where parents are taught to apply strategies in their child’s play activities and daily routines to achieve the prior stated goals. However, the ability to conduct parent coaching in physical in-clinic sessions is limited by resource constraints such as clinic space and therapist manpower. Furthermore, parents may experience difficulties with the generalisation of intervention strategies taught in the clinic to their natural home environments. In this study, telerehabilitation is evaluated as an alternative platform to deliver parent coaching for parent-implemented interventions to children with ASD in their homes. Methods This parallel-group, randomised, controlled, non-inferiority trial aims to evaluate the effectiveness of parent coaching delivered through video conferencing (telerehabilitation) versus in-clinic (standard care) delivery. Children aged 15 to 48 months (n = 200) who meet the cut-off score for ASD on the Autism Diagnostic Observation Schedule-2 are eligible. Parent-child dyads are randomly assigned to receive parent coaching either through weekly telerehabilitation or standard care. The primary outcome is the child’s development as measured by the subscale and composite scores of a standardised developmental assessment. Primary analysis will determine if the lower boundary of the 95% confidence interval for the mean difference in pre-post change between groups exceeds −5 (the non-inferiority margin). Secondary outcomes are the child’s adaptive behaviour, parent-child interaction, parental stress, and family quality of life. Outcomes will be measured pre-intervention, midterm, and post-intervention. Secondary analysis will determine if there is any between-group difference for the pre-post change in scores at the 5% significance level using two-sample t-test or Mann-Whitney U test. Discussion As a randomised controlled trial of a moderately large scale, this study will contribute to the limited existing literature on the effectiveness of parent coaching via telerehabilitation for early parent-implemented intervention for children with ASD. The results of this study will provide insights on whether telerehabilitation is comparable to conventional in-clinic parent coaching in enhancing parent-child interaction and improving language skills. Trial registration ClinicalTrials.gov NCT05792449. Registered (retrospectively) on 31 March 2023.

Abstract Longer-term outcomes with the anti-CD38 antibody isatuximab in combination with carfilzomib-dexamethasone (Isa-Kd) were evaluated in the randomized Phase 3 trial IKEMA (NCT03275285), in a prespecified, follow-up analysis of progression-free survival (PFS, primary study endpoint), final complete response (CR) using Hydrashift Isa immunofixation assay, minimal residual disease (MRD) negativity, and safety. Enrolled patients had relapsed/refractory multiple myeloma (1–3 prior treatment lines). Isa 10 mg/kg was administered intravenously weekly in cycle 1 then biweekly. Efficacy analyses were performed in the intent-to-treat population (Isa-Kd: n = 179, Kd: n = 123) and safety evaluated in treated patients (Isa-Kd: n = 177, Kd: n = 122). Consistent with the primary interim analysis, the addition of Isa to Kd prolonged PFS (HR 0.58, 95.4% CI: 0.42–0.79; median PFS 35.7 [95% CI: 25.8–44.0] vs 19.2 [95% CI: 15.8–25.0] months). PFS benefit was observed with Isa-Kd across subgroups, including patients with poor prognosis. The stringent CR/CR rate was 44.1% vs 28.5% (odds-ratio: 2.09, 95% CI: 1.26–3.48), the MRD negativity rate 33.5% vs 15.4% (odds-ratio: 2.78, 95% CI: 1.55–4.99) and the MRD negativity CR rate 26.3% vs 12.2%, with Isa-Kd vs Kd. The safety profile of Isa-Kd was similar to that reported in the prior interim analysis. These findings further support Isa-Kd as a standard-of-care treatment for relapsed multiple myeloma patients. Clinical trial information: ClinicalTrials.gov, NCT03275285.

Abstract Background Hemichorea typically results from a contralateral subthalamic nuclei (STN) lesion, although it has been reported in the cortex in a minority of cases. However, to our best knowledge, there are no documented cases in literature of hemichorea occurring as a secondary condition to an isolated temporal stroke. Case presentation We present a case of an elderly female who sustained a sudden onset of hemichorea in her right extremities, predominantly in the distal region, lasting over a period of two days. Brain diffuse weighted image (DWI) demonstrated a high signal in the temporal region, while magnetic resonance angiography (MRA) revealed severe stenosis of the middle cerebral artery. During the symptomatic phase, computed tomography perfusion (CTP) revealed delayed perfusion in the left middle cerebral artery territory, characterized by the time-to-peak (TTP) measure. Based on the results of her medical history and laboratory tests, we were able to rule out the possibility of infectious, toxic, or metabolic encephalopathy. Her symptoms gradually improved with antithrombotic and symptomatic treatment. Conclusions It is important to recognize and consider acute onset hemichorea as an initial symptom of stroke to avoid misdiagnosis and delays in appropriate treatment. Further research on temporal lesion that lead to hemichorea is warranted to gain a better understanding of the underlying mechanisms.

During this research, aerodynamic shape optimization is conducted on the Ahmed body with the drag coefficient as the objective function and the ramp shape as the design variable, while aero-structural optimization is conducted on NACA 0012 to reduce the drag coefficient for the aerodynamic performance with the shape as the design variable while reducing structural mass with the thickness of the panels as the design variables. This is accomplished through a gradient-based optimization process and coupled finite element and computational fluid dynamics (CFD) solvers under fluid–structure interaction (FSI). In this study, DAFoam (Discrete Adjoint with OpenFOAM for High-fidelity Multidisciplinary Design Optimization) and TACS (Toolkit for the Analysis of Composite Structures) are integrated to optimize the aero-structural design of an airfoil concurrently under the FSI condition, with TACS and DAFoam as coupled structural and CFD solvers integrated with a gradient-based adjoint optimization solver. One-way coupling between the fluid and structural solvers for the aero-structural interaction is adopted by using Mphys, a package that standardizes high-fidelity multiphysics problems in OpenMDAO. At the end of the paper, we compare and discuss our findings in the context of existing research, specifically highlighting previous results on the aerodynamic and aero-structural optimization of wind turbine blades.

Despite efforts in improving medication safety, medication administration errors are still common, resulting in significant clinical and economic impact. Studies conducted using a valid and reliable tool to assess clinical impact are lacking, and to the best of our knowledge, studies evaluating the economic impact of medication administration errors among neonates are not yet available. Therefore, this study aimed to determine the potential clinical and economic impact of medication administration errors in neonatal intensive care units and identify the factors associated with these errors. A national level, multi centre, prospective direct observational study was conducted in the neonatal intensive care units of five Malaysian public hospitals. The nurses preparing and administering the medications were directly observed. After the data were collected, two clinical pharmacists conducted independent assessments to identify errors. An expert panel of healthcare professionals assessed each medication administration error for its potential clinical and economic outcome. A validated visual analogue scale was used to ascertain the potential clinical outcome. The mean severity index for each error was subsequently calculated. The potential economic impact of each error was determined by averaging each expert's input. Multinomial logistic regression and multiple linear regression were used to identify factors associated with the severity and cost of the errors, respectively. A total of 1,018 out of 1,288 (79.0%) errors were found to be potentially moderate in severity, while only 30 (2.3%) were found to be potentially severe. The potential economic impact was estimated at USD 27,452.10. Factors significantly associated with severe medication administration errors were the medications administered intravenously, the presence of high-alert medications, unavailability of a protocol, and younger neonates. Moreover, factors significantly associated with moderately severe errors were intravenous medication administration, younger neonates, and an increased number of medications administered. In the multiple linear regression analysis, the independent variables found to be significantly associated with cost were the intravenous route of administration and the use of high-alert medications. In conclusion, medication administration errors were judged to be mainly moderate in severity costing USD 14.04 (2.22-22.53) per error. This study revealed important insights and highlights the need to implement effective error reducing strategies to improve patient safety among neonates in the neonatal intensive care unit.

Marbofloxacin (MBF) was once widely used as a veterinary drug to control diseases in animals. MBF residues in animal food endanger human health. In the present study, an immunochromatographic strip assay (ICSA) utilizing a competitive principle was developed to rapidly detect MBF in beef samples. The 50% inhibitory concentration (IC50) and the limit of detection (LOD) of the ICSAs were 2.5 ng/mL and 0.5 ng/mL, respectively. The cross-reactivity (CR) of the MBF ICSAs to Ofloxacin (OFL), enrofloxacin (ENR), norfloxacin (NOR), and Ciprofloxacin (CIP) were 60.98%, 32.05%, 22.94%, and 23.58%, respectively. The CR for difloxacin (DIF) and sarafloxacin (SAR) was less than 0.1%. The recovery rates of MBF in spiked beef samples ranged from 82.0% to 90.4%. The intra-assay and interassay coefficients of variation (CVs) were below 10%. In addition, when the same authentic beef samples were detected in a side-by-side comparison between the ICSAs and HPLC‒MS, no statistically significant difference was observed. Therefore, the proposed ICSAs can be a useful tool for monitoring MBF residues in beef samples in a qualitative and quantitative manner.

Placing a loved one in care does not relieve informal caregivers’ physical and emotional stresses. This study identified the unique psycho-social-spiritual processes of involuntary separation among spouses following long-term care admission. Participants were 17 spouse-caregivers (12 women and 5 men) with a mean age of 84 years who had been involuntarily separated for an average of 20 months. The basic psycho-social-spiritual process of spouse-caregiver involuntary separation was connecting in disconnection, w hich had three distinct stages: (1) Initial coping, (2) Adjusting to the new situation, and (3) Moving forward. Movement through the three stages was influenced by individuals’ capacity and willingness to reach out for connection and by the abilities of others to extend accurate empathy and practical help. The implications of this study highlight spouse-caregivers’ needs for connection and support not only during the crisis of separation, but in the months and years that follow.

BackgroundThere is emerging evidence which suggests the utility of artificial intelligence (AI) in the diagnostic assessment and pre-treatment evaluation of thyroid eye disease (TED). This scoping review aims to (1) identify the extent of the available evidence (2) provide an in-depth analysis of AI research methodology of the studies included in the review (3) Identify knowledge gaps pertaining to research in this area.MethodsThis review was performed according to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA). We quantify the diagnostic accuracy of AI models in the field of TED assessment and appraise the quality of these studies using the modified QUADAS-2 tool.ResultsA total of 13 studies were included in this review. The most common AI models used in these studies are convolutional neural networks (CNN). The majority of the studies compared algorithm performance against healthcare professionals. The overall risk of bias and applicability using the modified Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool led to most of the studies being classified as low risk, although higher deficiency was noted in the risk of bias in flow and timing.ConclusionsWhile the results of the review showed high diagnostic accuracy of the AI models in identifying features of TED relevant to disease assessment, deficiencies in study design causing study bias and compromising study applicability were noted. Moving forward, limitations and challenges inherent to machine learning should be addressed with improved standardized guidance around study design, reporting, and legislative framework.

Background The risk of SARS-CoV-2 infection does not appear to be increased for psoriasis patients using biologics compared to those on other treatments, but evidence is still limited. Objectives (1) to estimate the prevalence of SARS-CoV-2 infection in patients with psoriasis, (2) to compare SARS-CoV-2 infection rates for different psoriasis treatments groups (biologic vs. systemic conventional vs. topical therapy) corrected for confounders and (3) to describe patients with severe COVID-19 for all treatment groups. Methods In this cross-sectional cohort study all patients received a questionnaire to gather data on psoriasis treatment, SARS-CoV-2 infections and related risk factors. Simultaneously, they underwent a blood test to screen for antibodies to SARS-CoV-2 N-antigen. Prevalence of SARS-CoV-2 infections was calculated and logistic regression and Cox proportional-hazards models were performed to determine the association between treatment group and SARS-CoV-2 infection risk, corrected for confounders. Patients with severe COVID-19 disease were described and the mortality rate per treatment group was calculated for the target population. Results Patients were included between April 12 2021 and October 31 2021. Of 551 patients, 59 (10.7% (CI95% 8.3–13.6)) had experienced a SARS-CoV-2 infection, based on questionnaire data combined with serological data. In our study cohort, corrected for confounders, biologic or non-biologic systemic therapy users did not appear to have increased SARS-CoV-2 infection risk compared to patients using other treatment. Only 4 hospitalizations (0.7% (CI95% 0.2–1.0) were reported in our study population and no ICU admissions were reported. The rough mortality rate in the target cohort was 0.32% (CI95% 0.13–0.66) in all treatment groups. Conclusions Corrected for risk-mitigating behavior and vaccination status, a higher SARS-CoV-2 incidence for biologics or non-biologics systemics compared to other treatments could not be proven. Severe cases were infrequent in all treatment groups. This finding further strengthens treatment recommendations that systemic therapies for patients with psoriasis do not require preventive cessation for reduction of SARS-CoV-2 infection risk.

BackgroundStroke is a leading cause of lifelong disability worldwide, partially driven by a reduced ability to use the upper limb in daily life causing increased dependence on caregivers. However, post-stroke functional impairments have only been investigated using limited clinical scores, during short-term longitudinal studies in relatively small patient cohorts. With the addition of technology-based assessments, we propose to complement clinical assessments with more sensitive and objective measures that could more holistically inform on upper limb impairment recovery after stroke, its impact on upper limb use in daily life, and on overall quality of life. This paper describes a pragmatic, longitudinal, observational study protocol aiming to gather a uniquely rich multimodal database to comprehensively describe the time course of upper limb recovery in a representative cohort of 400 Asian adults after stroke. Particularly, we will characterize the longitudinal relationship between upper limb recovery, common post-stroke impairments, functional independence and quality of life.MethodsParticipants with stroke will be tested at up to eight time points, from within a month to 3 years post-stroke, to capture the influence of transitioning from hospital to community settings. We will perform a battery of established clinical assessments to describe the factors most likely to influence upper limb recovery. Further, we will gather digital health biomarkers from robotic or wearable sensing technology-assisted assessments to sensitively characterize motor and somatosensory impairments and upper limb use in daily life. We will also use both quantitative and qualitative measures to understand health-related quality of life. Lastly, we will describe neurophysiological motor status using transcranial magnetic stimulation.StatisticsDescriptive analyses will be first performed to understand post-stroke upper limb impairments and recovery at various time points. The relationships between digital biomarkers and various domains will be explored to inform key aspects of upper limb recovery and its dynamics using correlation matrices. Multiple statistical models will be constructed to characterize the time course of upper limb recovery post-stroke. Subgroups of stroke survivors exhibiting distinct recovery profiles will be identified.ConclusionThis is the first study complementing clinical assessments with technology-assisted digital biomarkers to investigate upper limb sensorimotor recovery in Asian stroke survivors. Overall, this study will yield a multimodal data set that longitudinally characterizes post-stroke upper limb recovery in functional impairments, daily-life upper limb use, and health-related quality of life in a large cohort of Asian stroke survivors. This data set generates valuable information on post-stroke upper limb recovery and potentially allows researchers to identify different recovery profiles of subgroups of Asian stroke survivors. This enables the comparisons between the characteristics and recovery profiles of stroke survivors in different regions. Thus, this study lays out the basis to identify early predictors for upper limb recovery, inform clinical decision-making in Asian stroke survivors and establish tailored therapy programs.Clinical trial registrationClinicalTrials.gov, identifier: NCT05322837.

Abstract Background The addition of qualitative methodology to randomised controlled trials evaluating complex interventions allows better understanding of contextualised factors and their potential influence on trial delivery and outcomes, as well as opportunities for feedback on trial participation to improve future trial protocols. This study explored the experiences of participation in cancer rehabilitation research during active cancer treatment. Participants were people living with haematological cancer myeloma, undergoing autologous stem cell transplantation (ASCT) recruited to the PERCEPT myeloma pilot trial. Methods A qualitative semi-structured interview study, embedded within a pilot randomised controlled trial of a physiotherapist-led exercise intervention delivered before, during and after ASCT among people living with myeloma. Transcripts were analysed using reflexive thematic analysis. Results Interviews from 16 trial participants (n = 8 intervention group; n = 8 control group; mean age 61 years, 56% male) were analysed. Four main themes were identified: (1) “It’s not just beneficial for me, it’s for people after me as well”; (2) Disparities in experience of recovery – expectations, feeling prepared and support; (3) “What I wanted to do was build myself back up and prepare”; (4) Active ingredients – participants’ experience of the trial intervention. Participants reported both altruistic and perceived personal gain as motivators for enrolling in the trial. Disappointment caused by allocation to control arm may have led to participants seeking exercise elsewhere, indicating possible contamination of control condition. Disparities in experience of recovery from transplant were evident with intervention participants reporting greater trajectory of recovery. Conclusions The findings from this embedded qualitative study highlight numerous considerations required when designing pilot and efficacy trials of complex interventions. The addition of qualitative investigation offers greater understanding of motivations for participation, intervention mechanisms at play as well as effects of participation that may impact interpretation of quantitative outcomes. Trial registration Qualitative findings from a prospectively registered pilot trial (ISRCTN15875290), registered 13/02/2019.

Abstract Background Aging degrades the balance and locomotion ability due to frailty and pathological conditions. This demands balance rehabilitation and assistive technologies that help the affected population to regain mobility, independence, and improve their quality of life. While many overground gait rehabilitation and assistive robots exist in the market, none are designed to be used at home or in community settings. Methods A device named Mobile Robotic Balance Assistant (MRBA) is developed to address this problem. MRBA is a hybrid of a gait assistive robot and a powered wheelchair. When the user is walking around performing activities of daily living, the robot follows the person and provides support at the pelvic area in case of loss of balance. It can also be transformed into a wheelchair if the user wants to sit down or commute. To achieve instability detection, sensory data from the robot are compared with a predefined threshold; a fall is identified if the value exceeds the threshold. The experiments involve both healthy young subjects and an individual with spinal cord injury (SCI). Spatial Parametric Mapping is used to assess the effect of the robot on lower limb joint kinematics during walking. The instability detection algorithm is evaluated by calculating the sensitivity and specificity in identifying normal walking and simulated falls. Results When walking with MRBA, the healthy subjects have a lower speed, smaller step length and longer step time. The SCI subject experiences similar changes as well as a decrease in step width that indicates better stability. Both groups of subjects have reduced joint range of motion. By comparing the force sensor measurement with a calibrated threshold, the instability detection algorithm can identify more than 93% of self-induced falls with a false alarm rate of 0%. Conclusions While there is still room for improvement in the robot compliance and the instability identification, the study demonstrates the first step in bringing gait assistive technologies into homes. We hope that the robot can encourage the balance-impaired population to engage in more activities of daily living to improve their quality of life. Future research includes recruiting more subjects with balance difficulty to further refine the device functionalities.

Abstract Background Psoriasis imposes a substantial burden on patients’ social, emotional, physical, and family life. Although psoriasis has no complete cure, various treatments are available to control its symptoms and improve a patients’ quality of life. Objective We aimed to compare the effectiveness of biologic versus non-biologic treatments on health-related quality of life among patients with psoriasis in Malaysia. Methods This retrospective cross-sectional study evaluated data of adult patients diagnosed with psoriasis during 2007–18 from the Malaysian Psoriasis Registry. Baseline demographics, disease, and treatment characteristics were described. For a subset of patients treated with biologics and non-biologics who had baseline and 6-month follow-up data available, changes in the mean Dermatology Life Quality Index scores and the proportion of patients with a clinically relevant improvement (≥ 4 points) post-treatment were assessed. Results Overall, 15,238 adult patients with psoriasis from the Malaysian Psoriasis Registry were included in the analysis. Patients receiving biologics showed a statistically significant reduction in the mean Dermatology Life Quality Index scores after 6 months compared with those receiving non-biologic treatment (− 5.7 vs − 0.8%; p < 0.001). The proportion of patients who achieved a ≥ 4-point improvement in Dermatology Life Quality Index scores was approximately two times greater in the biologic-treated group versus the non-biologic-treated group (56.4 vs 27.7%). Conclusions Biologic treatment showed a greater reduction in the Dermatology Life Quality Index scores of patients with psoriasis versus non-biologic treatment. These results highlight the importance of early treatment with more efficacious treatment options, such as biologic therapies, to improve the overall health-related quality of life of patients with psoriasis.