bluuebunny/crossref_metadata_2025_split huggingface dataset:
AAV gene therapy for hereditary spastic paraplegia type 50: a phase 1 trial in a single patient
Authors: Dowling James J. , Pirovolakis Terry , Devakandan Keshini , Stosic Ana , Pidsadny Mia , Nigro Elisa , Sahin Mustafa , Ebrahimi-Fakhari Darius , Messahel Souad , Varadarajan Ganapathy , Greenberg Benjamin M. , Chen Xin , Minassian Berge A. , Cohn Ronald , Bonnemann Carsten G. , Gray Steven J. 
Published: June 2024

AbstractThere are more than 10,000 individual rare diseases and most are without therapy. Personalized genetic therapy represents one promising approach for their treatment. We present a road map for individualized treatment of an ultra-rare disease by establishing a gene replacement therapy developed for a single patient with hereditary spastic paraplegia type 50 (SPG50). Through a multicenter collaboration, an adeno-associated virus-based gene therapy product carrying the AP4M1 gene was created and successfully administered intrathecally to a 4-year-old patient within 3 years of diagnosis as part of a single-patient phase 1 trial. Primary endpoints were safety and tolerability, and secondary endpoints evaluated efficacy. At 12 months after dosing, the therapy was well tolerated. No serious adverse events were observed, with minor events, including transient neutropenia and Clostridioides difficile gastroenteritis, experienced but resolved. Preliminary efficacy measures suggest a stabilization of the disease course. Longer follow-up is needed to confirm the safety and provide additional insights on the efficacy of the therapy. Overall, this report supports the safety of gene therapy for SPG50 and provides insights into precision therapy development for rare diseases. Clinical trial registration: NCT06069687.
The limits of fair medical imaging AI in real-world generalization
Authors: Yang Yuzhe , Zhang Haoran , Gichoya Judy W. , Katabi Dina , Ghassemi Marzyeh 
Published: June 2024

AbstractAs artificial intelligence (AI) rapidly approaches human-level performance in medical imaging, it is crucial that it does not exacerbate or propagate healthcare disparities. Previous research established AI’s capacity to infer demographic data from chest X-rays, leading to a key concern: do models using demographic shortcuts have unfair predictions across subpopulations? In this study, we conducted a thorough investigation into the extent to which medical AI uses demographic encodings, focusing on potential fairness discrepancies within both in-distribution training sets and external test sets. Our analysis covers three key medical imaging disciplines—radiology, dermatology and ophthalmology—and incorporates data from six global chest X-ray datasets. We confirm that medical imaging AI leverages demographic shortcuts in disease classification. Although correcting shortcuts algorithmically effectively addresses fairness gaps to create ‘locally optimal’ models within the original data distribution, this optimality is not true in new test settings. Surprisingly, we found that models with less encoding of demographic attributes are often most ‘globally optimal’, exhibiting better fairness during model evaluation in new test environments. Our work establishes best practices for medical imaging models that maintain their performance and fairness in deployments beyond their initial training contexts, underscoring critical considerations for AI clinical deployments across populations and sites.
The role of accelerometer-derived sleep traits on glycated haemoglobin and glucose levels: a Mendelian randomization study
Authors: Liu Junxi , Richmond Rebecca C. , Anderson Emma L. , Bowden Jack , Barry Ciarrah-Jane S. , Dashti Hassan S. , Daghlas Iyas S. , Lane Jacqueline M. , Kyle Simon D. , Vetter Céline , Morrison Claire L. , Jones Samuel E. , Wood Andrew R. , Frayling Timothy M. , Wright Alison K. , Carr Matthew J. , Anderson Simon G. , Emsley Richard A. , Ray David W. , Weedon Michael N. , Saxena Richa , Rutter Martin K. , Lawlor Deborah A. 
Published: June 2024

AbstractSelf-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be ‘objective’ measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.
Determinants of hemoglobin level and time to default from Highly Active Antiretroviral Therapy (HAART) for adult clients living with HIV under treatment; a retrospective cohort study design
Authors: Muhie Nurye Seid , Tegegne Awoke Seyoum 
Published: June 2024

AbstractHIV/AIDS is one of the most devastating infectious diseases affecting humankind all over the world and its impact goes beyond public health problems. This study was conducted to investigate the joint predictors of hemoglobin level and time to default from treatment for adult clients living with HIV/AIDS under HAART at the University of Gondar Comprehensive and Specialized Hospital, North-west Ethiopia. The study was conducted using a retrospective cohort design from the medical records of 403 randomly selected adult clients living with HIV whose follow-ups were from September 2015 to March 2022. Hemoglobin level was projected using Sahli’s acid-hematin method. Hence, the hemoglobin tube was filled with N/10 hydrochloric acid up to 2 g % marking and the graduated tube was placed in Sahli’s hemoglobin meter. The blood samples were collected using the finger-pick method, considering 22 G disposable needles. The health staff did this. From a total of 403 adult patients living with HIV/AIDS included in the current study, about 44.2% defaulted from therapy. The overall mean and median estimated survival time of adult clients under study were 44.3 and 42 months respectively. The patient’s lymphocyte count (AHR = 0.7498, 95% CI: (0.7411: 0.7587), p-value < 0.01), The weight of adult patients living with HIV/AIDS (AHR = 0.9741, 95% CI: (0.9736: 0.9747), p-value = 0.012), sex of adult clients (AHR = 0.6019, 95% CI: (0.5979, 0.6059), p-value < 0.01), WHO stages III compared to Stage I (AHR = 1.4073, 95% CI: (1.3262, 1.5078), p-value < 0.01), poor adherence level (AHR = 0.2796, 95% CI: (0.2082, 0.3705) and p-value < 0.01), bedridden patients (AHR = 1.5346, 95% CI: (1.4199, 1.6495), p-value = 0.008), and opportunistic infections (AHR = 0.2237, 95% CI: (0.0248, 0.4740), p-value = 0.004) had significant effect on both hemoglobin level and time to default from treatment. Similarly, other co-morbidity conditions, disclosure status of the HIV disease, and tobacco and alcohol addiction had a significant effect on the variables of interest. The estimate of the association parameter in the slope value of Hgb level and time default was negative, indicating that the Hgb level increased as the hazard of defaulting from treatment decreased. A patient with abnormal BMI like underweight, overweight, or obese was negatively associated with the risk of anemia (lower hemoglobin level). As a recommendation, more attention should be given to those patients with abnormal BMI, patients with other co-morbidity conditions, patients with opportunistic infections, and low lymphocytes, and bedridden and ambulatory patients. Health-related education should be given to adult clients living with HIV/AIDS to be good adherents for medical treatment.
Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings
Authors: Rashidi Hooman H. , Ikram Aamer , Dang Luke T. , Bashir Adnan , Zohra Tanzeel , Ali Amna , Tanvir Hamza , Mudassar Mohammad , Ravindran Resmi , Akhtar Nasim , Sikandar Rana I. , Umer Mohammed , Akhter Naeem , Butt Rafi , Fennell Brandon D. , Khan Imran H. 
Published: June 2024

AbstractAccurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore, during the early stages of the pandemic tests were not available in any capacity. We utilized an automated machine learning (ML) approach to train and evaluate thousands of models on a clinical dataset consisting of commonly available clinical and laboratory data, along with cytokine profiles for patients (n = 150). These models were then further tested for generalizability on an out-of-sample secondary dataset (n = 120). We were able to develop a ML model for rapid and reliable screening of patients as COVID-19 positive or negative using three approaches: commonly available clinical and laboratory data, a cytokine profile, and a combination of the common data and cytokine profile. Of the tens of thousands of models automatically tested for the three approaches, all three approaches demonstrated > 92% sensitivity and > 88 specificity while our highest performing model achieved 95.6% sensitivity and 98.1% specificity. These models represent a potential effective deployable solution for COVID-19 status classification for symptomatic patients in resource-limited settings and provide proof-of-concept for rapid development of screening tools for novel emerging infectious diseases.
SARS-CoV-2 antigenemia and RNAemia in association with disease severity in patients with COVID-19
Authors: Kim Dong-Min , Lawrence Panchali Merlin Jayalal , Kim Choon-Mee , Lee Da-Yeon , Seo Jun-Won , Kim Da Young , Yun Na Ra 
Published: June 2024

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, causes a spectrum of symptoms ranging from mild upper to severe lower respiratory tract infections. However, the dynamics of nucleocapsid (N) protein antigenemia and RNAemia are not fully understood. We conducted a cohort study involving 117 patients with clinically confirmed COVID-19, focusing on the kinetics of antigenemia and RNAemia and their association with various clinical characteristics. The patients had a median age of 66.0 years (52.0–79.0 years), with a gender distribution of 46.2% male and 53.8% female. Antigenemia reached 100% in fatal cases during the first week after admission. The sensitivity/specificity of antigenemia for diagnosis were 64.7%/73.0% at admission, 69.1%/100% in Week 1, and 66.3%/100% in Week 2. Additionally, the rates of antigenemia in asymptomatic patients were 27.3% upon admission and 22.0% in Week 1, respectively; however, no antigenemia was in samples collected in Week 2. Viral RNAemia was not detected in asymptomatic patients, but RNAemia viral loads were elevated in fatal cases. Kaplan–Meier survival curves demonstrated a higher mortality rate when antigenemia concentrations were elevated in the follow-up samples (P = 0.005). Our study provides a comprehensive analysis of the kinetics of viral N-protein antigenemia and RNAemia according to disease severity and clinical classification. Our findings suggest that highest concentrations of antigenemia in fatal cases occur in the first week after admission, indicating that early elevated antigenemia may serve as a marker of mortality risk.
Nonlinear adaptive pose motion control of a servicer spacecraft in approximation with an accelerated tumbling target
Authors: Kasiri Ali , Fani Saberi Farhad 
Published: June 2024

AbstractRemoving a limited number of large debris can significantly reduce space debris risks. These bodies are generally exposed to extreme environmental disturbance torques or consecutive accidents due to their large wet area, which causes them to experience accelerated high-rate tumbling motion. The existing literature has adequately explored the approximation operations with non-cooperative targets exhibiting 3-axis tumbling motion. However, the research gap lies in the lack of attention given to addressing this approximation for targets undergoing accelerated motion. Agile, accurate, and large-angle maneuvers are three common necessities for safely capturing such targets. Changes in the moment of inertia brought on by fuel slushing cannot be disregarded during such a maneuver. To deal with nonlinearities, adverse coupling effects, actuator saturation constraints, time-varying moment of inertia, and external disturbances that worsen during accelerated agile large-angle maneuvers, a novel adaptive control approach is developed in this paper. The controller's main advantage is its adjustable desired acceleration, which maintains its performance even when dealing with accelerated motion. The control law is directly synthesized from the nonlinear relative equations of motion, without any linearization or simplification of the system dynamics, making it robust to a variety of orbital elements and target behaviors. Adaptation laws are extracted from the Lyapunov stability theorem in a way that guarantees asymptotic stability. Moreover, control actuator roles (delay, saturation, and allocation) are accounted for in modeling and simulation. Finally, a comprehensive numerical simulation based on three different realistic and strict scenarios is carried out to demonstrate the effectiveness and performance of the proposed control approach. The controller's robustness against time-varying dynamic parameters (sharp and sudden change, smooth and slow change, and periodic change) is extensively demonstrated through simulation.
The mediation effect of Systemic Immunity Inflammation Index between urinary metals and TOFAT among adults in the NHANES dataset
Authors: Zhang Weipeng , Zhang Cong , Lu Dengqiu , Nie Junfeng , Hu Zhumin , Xian Cuiyao , He Minxing 
Published: June 2024

AbstractSystemic Immune Inflammatory Index (SII) is a novel indicator of inflammation. However, no studies have reported the effect of SII on the association between metals and total fat (TOFAT). We aim to investigate the mediated effect of SII on the relationship between urinary metals and TOFAT in a US adult population. This cross-sectional study was conducted among adults with complete information on SII, urine metal concentrations, and TOFAT from the 2011–2018 National Health and Nutrition Examination Survey (NHANES). Multifactorial logistic regression and restricted cubic splines were used to explore the association between urine metal levels and TOFAT. Furthermore, serial mediation analyses were used to investigate the mediating effect of SII on metals and TOFAT. A total of 3324 subjects were included in this study. After adjusting for confounders, arsenic (As), cadmium (Cd), cobalt (Co), cesium (Cs), inorganic mercury (Hg), molybdenum (Mo), manganese (Mn), lead (Pb), antimony (Sb), and thallium(Tl) had negative decreased trends of odds ratios for TOFAT (all P for trend < 0.05). In the total population, we found that Cd, Co, and Tu were positively associated with SII (β = 29.70, 79.37, and 31.08), whereas As and Hg had a negative association with SII. The mediation analysis showed that SII mediated the association of Co with TOFAT, with the β of the mediating effect being 0.9% (95%CI: 0.3%, 1.6%). Our findings suggested that exposure to As, Cd, and Hg would directly decrease the level of TOFAT. However, Co would increase TOFAT, completely mediated by SII, mainly exerted in females rather than males.
Intense impact of IL-1β expressing inflammatory macrophages in acute aortic dissection
Authors: Inoue Taishi , Emoto Takuo , Yamanaka Katsuhiro , Chomei Shunya , Miyahara Shunsuke , Takahashi Hiroaki , Shinohara Ryohei , Kondo Takeshi , Taniguchi Masayuki , Furuyashiki Tomoyuki , Yamashita Tomoya , Hirata Ken-ichi , Okada Kenji 
Published: June 2024

AbstractThere is no treatment for acute aortic dissection (AAD) targeting inflammatory cells. We aimed to identify the new therapeutic targets associated with inflammatory cells. We characterized the specific distribution of myeloid cells of both human type A AAD samples and a murine AAD model generated using angiotensin II (ANGII) and β-aminopropionitrile (BAPN) by single-cell RNA sequencing (scRNA-seq). We also examined the effect of an anti-interleukin-1β (IL-1β) antibody in the murine AAD model. IL1B+ inflammatory macrophages and classical monocytes were increased in human AAD samples. Trajectory analysis demonstrated that IL1B+ inflammatory macrophages differentiated from S100A8/9/12+ classical monocytes uniquely observed in the aorta of AAD. We found increased infiltration of neutrophils and monocytes with the expression of inflammatory cytokines in the aorta and accumulation of inflammatory macrophages before the onset of macroscopic AAD in the murine AAD model. In blocking experiments using an anti-IL-1β antibody, it improved survival of murine AAD model by preventing elastin degradation. We observed the accumulation of inflammatory macrophages expressing IL-1β in both human AAD samples and in a murine AAD model. Anti-IL-1β antibody could improve the mortality rate in mice, suggesting that it may be a treatment option for AAD.
Efficacy, drug sustainability, and safety of ustekinumab treatment in Crohn’s disease patients over three years
Authors: Barkai Laszlo J. , Gonczi Lorant , Balogh Fruzsina , Angyal Dorottya , Farkas Klaudia , Farkas Bernadett , Molnar Tamas , Szamosi Tamas , Schafer Eszter , Golovics Petra A. , Juhasz Mark , Patai Arpad , Vincze Aron , Sarlos Patricia , Farkas Alexandra , Dubravcsik Zsolt , Toth Tamas G. , Szekely Hajnal , Miheller Pal , Lakatos Peter L. , Ilias Akos 
Published: June 2024

AbstractLong-term data on ustekinumab in real-life Crohn’s disease patients are still missing, though randomized controlled trials demonstrated it as a favorable therapeutic option. We aimed to evaluate ustekinumab's clinical efficacy, drug sustainability, and safety in a prospective, nationwide, multicenter Crohn’s disease patient cohort with a three-year follow-up. Crohn’s disease patients on ustekinumab treatment were consecutively enrolled from 9 Hungarian Inflammatory Bowel Disease centers between January 2019 and May 2020. Patient and disease characteristics, treatment history, clinical disease activity (Harvey Bradshaw Index (HBI)), biomarkers, and endoscopic activity (Simple Endoscopic Score for Crohn’s Disease (SES-CD)) were collected for three-years’ time. A total of 148 patients were included with an overall 48.9% of complex behavior of the Crohn’s disease and 97.2% of previous anti-TNF exposure. The pre-induction remission rates were 12.2% (HBI), and 5.1% (SES-CD). Clinical remission rates (HBI) were 52.2%, 55.6%, and 50.9%, whereas criteria of an endoscopic remission were fulfilled in 14.3%, 27.5%, and 35.3% of the subjects at the end of the first, second, and third year, respectively. Dose intensification was high with 84.0% of the patients on an 8-weekly and 29.9% on a 4-weekly regimen at the end of year 3. Drug sustainability was 76.9% during the follow-up period with no serious adverse events observed. Ustekinumab in the long-term is an effective, sustainable, and safe therapeutic option for Crohn’s disease patients with severe disease phenotype and high previous anti-TNF biological failure, requiring frequent dose intensifications.
An integrated prediction model based on meta ensemble learning for short‐term wind speed forecasting
Authors: Ma Zhengwei , Wu Ting , Guo Sensen , Wang Huaizhi , Xu Gang , Aziz Saddam 
Published: June 2024

AbstractAs wind power increasingly integrates into power grids and energy systems, accurate and reliable wind speed forecasting (WSF) has become essential for wind power scheduling and management. Considering the fluctuating and random characteristics of wind speed, a novel integrated model for short‐term WSF is developed in this work, which integrates multiple models through meta ensemble learning to achieve better generalization, robustness, and accuracy. This model consists of four components: data input, base predictor, meta ensemble learning, and prediction data output. The base predictor component includes multiple pre‐trained base predictors of long short‐term memory recurrent neural network to provide initial prediction values for wind speed. The meta ensemble learning component is a multi‐input and multi‐output back propagation neural network that outputs automatically adjust weight coefficients for various base predictors, drawing on the environmental and meteorological characteristics of historical wind speed data. The ultimate prediction result of wind speed is obtained through a weighted summation of the initial prediction values of base predictors. The authors assess the effectiveness of the integrated WSF model by contrasting its performance with that of alternative forecasting models. The simulation results reveal that the proposed integrated prediction model surpasses both individual prediction models and traditional integrated prediction approaches in terms of prediction stability and accuracy for short‐term WSF.
Influence of electrons on granulation-generated solar chromosphere heating and plasma outflows
Authors: Pelekhata M. , Murawski K. , Poedts S. 
Published: June 2024

Context. It is known that the solar atmosphere exhibits a varying degree of ionization through its different layers. The ionization degree directly depends on plasma temperature, that is, the lower the temperature, the lower the ionization degree. As a result, the plasma in the lower atmospheric layers (the photosphere and the chromosphere) is only partially ionized, which motivates the use of a three-fluid model.
Aims. We consider, for the first time, the influence of electrons on granulation-generated solar chromosphere heating and plasma outflows. We attempt to detect variations in the ion temperature and plasma up- and downflows.
Methods. We performed 2.5D numerical simulations of the generation and evolution of granulation-generated waves, flows, and other granulation-associated phenomena with an adapted JOANNA code. This code solves the simplified three-fluid equations for ions (protons) and electrons and neutrals (hydrogen atoms) that are coupled by collision forces.
Results. Electron-neutral and electron–ion collisions provide extra heat in the low chromosphere and enhance plasma outflows in this region. The effect of electrons is small compared to ion–neutral collisions, which have a significantly greater effect on the heating process and the production of outflows. Ion–neutral collisions involve higher energy exchanges, making them the dominant mechanism over collisions with electrons.
Conclusions. Electrons do not play a major role in heating and producing outflows, primarily because their mass is much lower compared to that of neutrals and ions, resulting in lower energy transfer during collisions.