bluuebunny/crossref_metadata_2025_split huggingface dataset:
Usmani‐Riazuddin syndrome can have a recognizable phenotype: Report of a novel AP1G1 variant
Authors: Gnazzo Maria , Pascolini Giulia , Parlapiano Giovanni , Petrizzelli Francesco , Perrino Daniele , Porco Luigina , Bartuli Andrea , Novelli Antonio , Baban Anwar 
Published: April 2024

AbstractUsmani‐Riazuddin syndrome (USRISR, MIM# 619548; USRISD, MIM#619467) is a very rare genetic condition. recently associated with deleterious variants in AP1G1 (MIM* 603533). It is characterized by multisystemic involvement including intellectual disability, speech and developmental delay, behavioral anomalies, muscular tone disorders, seizures, limb defects, and unspecified facial gestalt. In this report, we describe this syndrome for the second time, in association to a novel AP1G1 variant identified in a toddler with multisystemic involvement including intellectual disability, speech and developmental delay, behavioral anomalies, arrhythmias, hearing loss, skin changes, and limb defects. Next generation sequencing (NGS) analysis through clinical exome disclosed AP1G1: c.1969C>G (p.Leu657Val), de novo, likely pathogenic variant, according to ACMG classification criteria. Proband's facial features resembled the spectrum of chromatinopathies. Clinical pictures were analyzed and a clinical overlap was supported by DeepGestalt analysis (www.face2gene.com). The system identified 6 chromatin disorders out of 30 possible diagnoses. The remaining 24 included 9 miscellaneous cryptic chromosomal abnormalities (excluded due to normal microarray study). To the best of our knowledge, this is the first description of likely distinctive facial features in a patient with Usmani‐Riazuddin syndrome. Further multicentric analyses are needed for a better definition of this aspect.
Studying of anti‐inflammatory and antioxidant effects of tectorigenin in ovalbumin‐induced asthma mice models
Authors: Guo Jingning , Shi Yanping , Wang Yujun , Athari Seyyed Shamsadin , Chen Tao 
Published: April 2024

AbstractBackgroundAllergic asthma is an important respiratory system problem characterized by airway inflammation, breathlessness, and bronchoconstriction. Allergic asthma and its outcomes are triggered by type 2 allergic immune responses. Tectorigenin is a methoxy‐isoflavone with anti‐inflammatory effects. In this study, we investigated the effects of tectorigenin on the pathophysiology of allergic asthma in an animal model.MethodsAsthmatic mice were treated with tectorigenin. Then airway hyperresponsiveness (AHR), eosinophil percentage, levels of interleukin (IL)‐33, IL‐25, IL‐13, IL‐5, IL‐4, total and ovalbumin (OVA)‐specific immunoglobulin (Ig)E, and lung histopathology were evaluated.ResultTectorigenin significantly (P 〈 0.05) reduced eosinophil infiltration (41 ± 7%) in the broncho‐alveolar lavage fluid (BALF), serum IL‐5 level (41 ± 5, pg/mL), and bronchial and vascular inflammation (scores of 1.3 ± 0.2 and 1.1 ± 0.3, respectively) but had no significant effects on AHR, serum levels of IL‐33, −25, −13, and −4 (403 ± 24, 56 ± 7, 154 ± 11, and 89 ± 6 pg/mL, respectively), total and OVA‐specific IgE (2684 ± 265 and 264 ± 19 ng/mL, respectively), goblet cell hyperplasia, and mucus production.ConclusionTectorigenin could control inflammation and the secretion of inflammatory mediators of asthma, so it can be regarded as a potential antiasthma treatment with the ability to control eosinophilia‐related problems.
Subungual melanoma with cartilaginous differentiation: Molecular insights
Authors: Shaikh Umayr , Shah Payal , Jones Victoria , Ramos‐Rodriguez Alvaro J. , Sriharan Aravindhan , Loo Eric , Khan Wahab A. , Simmons Brian , Cloutier Jeffrey M. 
Published: April 2024

AbstractMelanoma's rare capacity to undergo heterologous differentiation can create significant diagnostic challenges. The molecular mechanisms underlying this phenomenon are not well understood. We present an unusual case of subungual melanoma exhibiting extensive cartilaginous differentiation and provide insights into its molecular and cytogenomic features. Histopathologically, the tumor was predominantly composed of nodules of malignant cartilage in association with a smaller population of nested epithelioid to rhabdoid cells. Immunohistochemically, the tumor cells in both components were positive for S100, SOX10, and PRAME, and were negative for Melan‐A and HMB‐45. Molecular analysis by whole exome DNA sequence did not detect any pathogenic variants in genes commonly implicated in melanoma. Additional analysis by SNP chromosomal microarray revealed a complex genome characterized by numerous chromosomal losses and gains, including a homozygous deletion of the CDKN2A locus and a heterozygous deletion of the locus containing EXT2, a tumor suppressor implicated in hereditary multiple osteochondromas and secondary chondrosarcomas. This case underscores the importance of recognizing cartilaginous differentiation as a rare manifestation of melanoma, particularly at subungual sites, and suggests that at least some of these melanomas may be driven by non‐canonical molecular pathways.
Defining paediatric neurorehabilitation: You cannot improve what you cannot characterize
Authors: Forsyth Rob , Whyte John 
Published: April 2024

AbstractNeurorehabilitation is the primary therapy for neurological impairment in children, yet its potential to achieve change remains incompletely understood and probably underestimated. Understanding ‘the difference neurorehabilitation can make’ against a background of neurological repair and recovery as well as ongoing neurological development is an enormous challenge, exacerbated to no small extent by the lack of a ‘common currency’ for the description and measurement of the neurorehabilitation services a child is receiving. This review addresses attempts to parse neurorehabilitation treatment content in theoretically and mechanistically valid ways that might help address this challenge.
Predictive value of quality of life as measured by KCCQ in heart failure patients: A meta‐analysis
Authors: Kao Guoying , Xu Gang , Zhang Ying , Li Chuanwei , Xiao Jun 
Published: April 2024

AbstractBackgroundStudies on the predictive ability of disease‐specific health quality of life (QoL) in patients with heart failure (HF) have produced conflicting results. To address these gaps in knowledge, we conducted a meta‐analysis to evaluate the predictive value of QoL measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ) in patients with HF.Materials and MethodsWe searched PubMed, and Embase databases to identify studies investigating the predictive utility of baseline QoL measured by the KCCQ in HF patients. The outcome measures were all‐cause mortality and HF hospitalisation. The predictive value of QoL was expressed by pooling the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for the bottom versus the top category of KCCQ score or for per 10‐point KCCQ score decrease.ResultsTwelve studies reporting on 11 articles with a total of 34,927 HF patients were identified. Comparison of the bottom with the top KCCQ score, the pooled adjusted HR was 2.34 (95% CI 2.10–2.60) and 2.53 (95% CI 2.23–2.88) for all‐cause mortality and HF hospitalisation, respectively. Additionally, a 10‐point decrease in KCCQ score was associated with a 12% (95% CI 7%–16%) increased risk of all‐cause mortality and a 14% (95% CI 13%–15%) increased risk of HF hospitalisation.ConclusionsPoor health‐related QoL as determined by the lower KCCQ score, was associated with an increased risk of all‐cause mortality and HF hospitalisation in patients with HF. Measuring disease‐specific health‐related QoL using the KCCQ score may provide valuable predictive information for HF patients.
Unravelling the relationship between English reading habits and individual, family and school factors: A Chinese perspective
Authors: Ao Narentuya , Zhang Mengchen 
Published: April 2024

AbstractIn English teaching, developing students' reading habits has been emphasized for its critical role in promoting overall core competencies. However, in practice, many teachers and parents are not informed of the effective approaches to developing good English reading habits, hindering the overall development of students' core competencies. In light of this, an empirical study was carried out to explore the developmental features of students' English reading habits and individual, family and school factors that affect its development. A questionnaire was adopted to collect quantitative data. A total of 2,130 primary and secondary school students from China participated in the study. The results indicated that their English reading habits varied with age and gender. In terms of age, secondary school students, especially middle school students, performed better than primary school students. In terms of gender, females performed better in reading frequency, reading time and ways of reading, while males had a larger reading volume. Reading habits were found to be impacted by individual, school and family factors. Among them, age had the strongest influence on the development of English reading habits. These findings shed light on effective ways to develop English reading habits, especially in foreign‐language‐learning contexts.
MEF2C contributes to axonal branching by regulating Kif2c transcription
Authors: Wu Ronghua , Sun Ying , Zhou Zhihao , Dong Zhangji , Liu Yan , Liu Mei , Gao Huasong 
Published: April 2024

AbstractNeurons are post‐mitotic cells, with microtubules playing crucial roles in axonal transport and growth. Kinesin family member 2c (KIF2C), a member of the Kinesin‐13 family, possesses the ability to depolymerize microtubules and is involved in remodelling the microtubule lattice. Myocyte enhancer factor 2c (MEF2C) was initially identified as a regulator of muscle differentiation but has recently been associated with neurological abnormalities such as severe cognitive impairment, stereotyping, epilepsy and brain malformations when mutated or deleted. However, further investigation is required to determine which target genes MEF2C acts upon to influence neuronal function as a transcription regulator. Our data demonstrate that knockdown of both Mef2c and Kif2c significantly impacts spinal motor neuron development and behaviour in zebrafish. Luciferase reporter assays and chromosome immunoprecipitation assays, along with down/upregulated expression analysis, revealed that MFE2C functions as a novel transcription regulator for the Kif2c gene. Additionally, the knockdown of either Mef2c or Kif2c expression in E18 cortical neurons substantially reduces the number of primary neurites and axonal branches during neuronal development in vitro without affecting neurite length. Finally, depletion of Kif2c eliminated the effects of overexpression of Mef2c on the neurite branching. Based on these findings, we provided novel evidence demonstrating that MEF2C regulates the transcription of the Kif2c gene thereby influencing the axonal branching.
Release, availability and geochemical interaction of Fe in soil after long‐term integrated nutrient management in wheat
Authors: Saroha Diksha , Yadav Narender , Raj Dev , Mukhopadhyay Raj , Duhan Anil , Kumar Rohtas 
Published: April 2024

AbstractWheat contributes to about one‐fifth of the total calories and protein consumption by humans but is found lower in total iron (Fe) concentration than the targeted nutritional requirement, leading to increasing cases of anaemia and malnutrition in humans, especially in the developing countries. Therefore, it is the need of the hour to understand the dynamics of Fe in soil and its supply in relation to wheat productivity and grain quality. The objectives of this study were to examine the impact of long‐term (54 years) annual and biannual application of different doses of farmyard manure (FYM) (0, 5, 10 and 15 Mg ha−1) and nitrogen (0, 60 and 120 kg ha−1) under integrated nutrient management on the dynamics of Fe in soil along with its relationship with total Fe uptake in wheat. Additionally, the release pattern of native soil Fe and risk of Fe toxicity were evaluated. The highest grain yield of wheat (6.08 Mg ha−1) was observed under biannual application of FYM and nitrogen at 10 Mg ha−1 and 120 kg ha−1, respectively, which was approximately 155% higher than the control plot (F0N0). Under the dual season application of 15 Mg ha−1 FYM and 120 kg ha−1 nitrogen, the total Fe content (48.48 mg kg−1) and its uptake (270.52 g ha−1) in wheat grains were found at maximum. The soil incubation study revealed that the rate of release of Fe increased up to 30 days of incubation followed by constant rates indicating the establishment of dynamic equilibrium among the different Fe fractions. Thus, the present study was conducted for the first time to improve the understanding of changes in Fe concentration and rate of release in soil, which directly influence the Fe uptake in wheat grain under the long‐term integrated nutrient management practices.
Optimization on selecting XGBoost hyperparameters using meta‐learning
Authors: Lima Marinho Tiago , do Nascimento Diego Carvalho , Pimentel Bruno Almeida 
Published: April 2024

AbstractWith computational evolution, there has been a growth in the number of machine learning algorithms and they became more complex and robust. A greater challenge is upon faster and more practical ways to find hyperparameters that will set up each algorithm individually. This article aims to use meta‐learning as a practicable solution for recommending hyperparameters from similar datasets, through their meta‐features structures, than to adopt the already trained XGBoost parameters for a new database. This reduced computational costs and also aimed to make real‐time decision‐making feasible or reduce any extra costs for companies for new information. The experimental results, adopting 198 data sets, attested to the success of the heuristics application using meta‐learning to compare datasets structure analysis. Initially, a characterization of the datasets was performed by combining three groups of meta‐features (general, statistical, and info‐theory), so that there would be a way to compare the similarity between sets and, thus, apply meta‐learning to recommend the hyperparameters. Later, the appropriate number of sets to characterize the XGBoost turning was tested. The obtained results were promising, showing an improved performance in the accuracy of the XGBoost, k = {4 − 6}, using the average of the hyperparameters values and, comparing to the standard grid‐search hyperparameters set by default, it was obtained that, in 78.28% of the datasets, the meta‐learning methodology performed better. This study, therefore, shows that the adoption of meta‐learning is a competitive alternative to generalize the XGBoost model, expecting better statistics performance (accuracy etc.) rather than adjusting to a single/particular model.
Modelling of healthcare data analytics using optimal machine learning model in big data environment
Authors: Fancy Chelladurai , Krishnaraj Nagappan , Ishwarya K. , Raja G. , Chandrasekaran Shyamala 
Published: April 2024

AbstractRecent advances in wireless networking, big data technologies, namely Internet of Things (IoT) 5G networks, health care big data analytics, and other technologies in artificial intelligence (AI) and wearables, have supported the progression of intellectual disease diagnosis methods. Medical data covers all patient data such as pharmacy texts, electronic health reports (EHR), prescriptions, study data from medical journals, clinical photographs, and diagnostic reports. Big data is a renowned method in the healthcare sector, with beneficial datasets that are highly difficult, voluminous, and rapid for healthcare providers for interpreting and computing using prevailing tools. This study combines concepts like deep learning (DL) and big data analytics in medical field. This article develops a new healthcare data analytics using optimal machine learning model in big data environment (HDAOML‐BDE) technique. The presented HDAOML‐BDE technique mainly aims to examine the healthcare data for disease detection and classification in the big data environment. For handling big data, the HDAOML‐BDE technique uses Hadoop MapReduce environment. In addition, the HDAOML‐BDE technique uses manta ray foraging optimization‐based feature selection (MRFO‐FS) technique to reduce high dimensionality problems. Moreover, the HDAOML‐BDE method uses relevance vector machine (RVM) model for the healthcare data environment. Furthermore, the arithmetic optimization algorithm (AOA) is utilized for the parameter tuning of the RVM classifier. The simulation results of the HDAOML‐BDE technique are tested on a healthcare dataset, and the outcomes portray the improved performance of the HDAOML‐BDE strategy over recent approaches in different measures.
Lost in translation: Therapeutic Alliance as a mediator in the relationship between teletherapy and marital satisfaction
Authors: Bradford Angela B. , Witting Alyssa Banford , Anderson Shayne R. , Johnson Lee N. , Hunt Quintin A. , Miller Richard B. , Bean Roy A. 
Published: April 2024

AbstractThe global impact of the SARS‐COV‐2 pandemic necessitated a rapid shift to online/teletherapy psychotherapy services. While research suggests the feasibility and efficacy of teletherapy, there is limited investigation into couple teletherapy's impact on satisfaction and therapeutic alliance. This study aimed to address this gap by examining changes in couple satisfaction during tele‐ and in‐person therapy sessions over 12 sessions and exploring whether therapeutic alliance development mediates these changes. Using growth curve modeling in a sample of 416 couples, it found that teletherapy participants initially reported higher couple satisfaction, but improvement in this domain was slower than in‐person therapy recipients. The development of the therapeutic alliance mediated this effect via two indirect paths. Implications include the need for focused attention on alliance development in teletherapy and more empirically‐informed approaches in couple teletherapy.
Corrosion fatigue mechanisms and evaluation methods of high‐strength steel wires: A state‐of‐the‐art review
Authors: Jie Zhiyu , Zhang Zenghui , Susmel Luca , Zhang Lexin , Lu Wei 
Published: April 2024

AbstractCorrosion significantly degrades the fatigue performance of high‐strength steel wires. This study conducts an extensive review of corrosion fatigue in corroded steel wires based on relevant literature. It outlines corrosion fatigue evolution mechanisms and discusses various test methodologies. Six distinct approaches are employed to assess corrosion fatigue life. A three‐stage multiscale corrosion fatigue evolution process involves pitting formation and growth, short crack propagation, and long crack propagation. Advanced fatigue assessment methods like the theory of critical distances (TCD) and the strain energy density (SED) are explored for predicting the corrosion fatigue life for corroded steel wires. A model utilizes an elastoplastic corrosion fatigue damage framework to comprehensively represent the complex interactions. The physics‐data‐driven method has garnered increasing attention due to its requirement of fewer sample data and good robustness. Moreover, the reliability method underscores its pivotal role in guaranteeing the longevity of suspenders and cables in practical settings.
PRIDASE 2024 guidelines for reporting diagnostic accuracy studies in endodontics: A consensus‐based development
Authors: Nagendrababu Venkateshbabu , Pigg Maria , Duncan Henry F. , Abbott Paul V. , Fouad Ashraf F. , Kruse Casper , Patel Shanon , Rechenberg Dan K. , Setzer Frank C , Rossi‐Fedele Giampiero , Dummer Paul M. H. 
Published: April 2024

AbstractStudies investigating the accuracy of diagnostic tests should provide data on how effectively they identify or exclude disease in order to inform clinicians responsible for managing patients. This consensus‐based project was undertaken to develop reporting guidelines for authors submitting manuscripts, which describe studies that have evaluated the accuracy of diagnostic tests in endodontics. These guidelines are known as the Preferred Reporting Items for Diagnostic Accuracy Studies in Endodontics (PRIDASE) 2024 guidelines. A nine‐member steering committee created an initial checklist by integrating and modifying items from the Standards for Reporting of Diagnostic Accuracy (STARD) 2015 checklist and the Clinical and Laboratory Images in Publications (CLIP) principles, as well as adding a number of new items specific to the specialty of endodontics. Thereafter, the steering committee formed the PRIDASE Delphi Group (PDG) and the PRIDASE Online Meeting Group (POMG) in order to collect expert feedback on the preliminary draft checklist. Members of the Delphi group engaged in an online Delphi process to reach consensus on the clarity and suitability of the items in the checklist. The online meeting group then held an in‐depth discussion on the online Delphi‐generated items via the Zoom platform on 20 October 2023. According to the feedback obtained, the steering committee revised the PRIDASE checklist, which was then piloted by several authors when preparing manuscripts describing diagnostic accuracy studies in endodontics. Feedback from this process resulted in the final version of the PRIDASE 2024 checklist, which has 11 sections and 66 items. Authors are encouraged to use the PRIDASE 2024 guidelines when developing manuscripts on diagnostic accuracy in endodontics in order to improve the quality of reporting in this area. Editors of relevant journals will be invited to include these guidelines in their instructions to authors.
A comparative analysis of the clinical and genetic profiles of blast phase BCR::ABL1‐negative myeloproliferative neoplasm and acute myeloid leukemia, myelodysplasia‐related
Authors: Chen Dong , Geyer Julia , Bagg Adam , Hasserjian Robert , Weinberg Olga K. 
Published: April 2024

AbstractIntroductionThe classic Philadelphia chromosome–negative myeloproliferative neoplasms (Ph (‐) MPNs), have variable potential for progression to the blast phase (MPN‐BP) of the disease. Except initiated by distinct driver mutations, MPN‐BP frequently carry similar genetic abnormalities defining acute myeloid leukemia myelodysplasia‐related (AML‐MR). Because of dissimilar initial pathogenesis, MPN‐BP and AML‐MR are retained under different disease categories. To determine if separately classifying these entities is justified, we compare MPN‐BP with AML‐MR patients based on mutational landscape and clinical parameters.Methods104 MPN‐BP patients and 145 AML‐MR patients were identified with available clinical, cytogenetic, and genetic data.ResultsAML‐MR patients presented with a higher blast count (median, 51% vs. 30%) while MPN‐BP patients had higher WBC counts, platelet counts and bone marrow cellularity (all p<0.0001). Patients with MPN‐BP showed similar genetic mutations with similar mutation pattern (functional domain, hotspot and locus involved by the mutations) but a different mutation rate from AML‐MR, with more frequent JAK2, CALR, MPL, ASXL1, IDH2, SETBP1 and SRSF2 mutations and less frequent TP53 and DNMT3A mutations. The overall survival (OS) of MPN‐BP (OS post‐BP‐progression) is comparable to that of AML‐MR (median OS, 9.5 months vs. 13.1 months, p=0.20). In addition, the subgroups of MPN‐BP show similar OS as AML‐MR. When harboring certain mutation such as TP53, ASXL1, DNMT3A, TET2, RUNX1, IDH1, IDH2, EZH2, U2AF1, BCOR and SRSF2, MPN‐BP and AML‐MR patients carrying the same somatic mutation show no difference in OS.ConclusionMPN‐BP and AML‐MR harbor similar somatic mutations and clinical outcomes, suggesting a unified clinical disease entity.