bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stable hydrogen evolution reaction at high current densities via designing the Ni single atoms and Ru nanoparticles linked by carbon bridges
Authors: Yao Rui , Sun Kaian , Zhang Kaiyang , Wu Yun , Du Yujie , Zhao Qiang , Liu Guang , Chen Chen , Sun Yuhan , Li Jinping 
Published: March 2024

AbstractContinuous and effective hydrogen evolution under high current densities remains a challenge for water electrolysis owing to the rapid performance degradation under continuous large-current operation. In this study, theoretical calculations, operando Raman spectroscopy, and CO stripping experiments confirm that Ru nanocrystals have a high resistance against deactivation because of the synergistic adsorption of OH intermediates (OHad) on the Ru and single atoms. Based on this conceptual model, we design the Ni single atoms modifying ultra-small Ru nanoparticle with defect carbon bridging structure (UP-RuNiSAs/C) via a unique unipolar pulse electrodeposition (UPED) strategy. As a result, the UP-RuNiSAs/C is found capable of running steadily for 100 h at 3 A cm−2, and shows a low overpotential of 9 mV at a current density of 10 mA cm−2 under alkaline conditions. Moreover, the UP-RuNiSAs/C allows an anion exchange membrane (AEM) electrolyzer to operate stably at 1.95 Vcell for 250 h at 1 A cm−2.
Identification of four biotypes in temporal lobe epilepsy via machine learning on brain images
Authors: Jiang Yuchao , Li Wei , Li Jinmei , Li Xiuli , Zhang Heng , Sima Xiutian , Li Luying , Wang Kang , Li Qifu , Fang Jiajia , Jin Lu , Gong Qiyong , Yao Dezhong , Zhou Dong , Luo Cheng , An Dongmei 
Published: March 2024

AbstractArtificial intelligence provides an opportunity to try to redefine disease subtypes based on similar pathobiology. Using a machine-learning algorithm (Subtype and Stage Inference) with cross-sectional MRI from 296 individuals with focal epilepsy originating from the temporal lobe (TLE) and 91 healthy controls, we show phenotypic heterogeneity in the pathophysiological progression of TLE. This study was registered in the Chinese Clinical Trials Registry (number: ChiCTR2200062562). We identify two hippocampus-predominant phenotypes, characterized by atrophy beginning in the left or right hippocampus; a third cortex-predominant phenotype, characterized by hippocampus atrophy after the neocortex; and a fourth phenotype without atrophy but amygdala enlargement. These four subtypes are replicated in the independent validation cohort (109 individuals). These subtypes show differences in neuroanatomical signature, disease progression and epilepsy characteristics. Five-year follow-up observations of these individuals reveal differential seizure outcomes among subtypes, indicating that specific subtypes may benefit from temporal surgery or pharmacological treatment. These findings suggest a diverse pathobiological basis underlying focal epilepsy that potentially yields to stratification and prognostication – a necessary step for precise medicine.
High-throughput evaluation of genetic variants with prime editing sensor libraries
Authors: Gould Samuel I. , Wuest Alexandra N. , Dong Kexin , Johnson Grace A. , Hsu Alvin , Narendra Varun K. , Atwa Ondine , Levine Stuart S. , Liu David R. , Sánchez Rivera Francisco J. 
Published: March 2024

AbstractTumor genomes often harbor a complex spectrum of single nucleotide alterations and chromosomal rearrangements that can perturb protein function. Prime editing has been applied to install and evaluate genetic variants, but previous approaches have been limited by the variable efficiency of prime editing guide RNAs. Here we present a high-throughput prime editing sensor strategy that couples prime editing guide RNAs with synthetic versions of their cognate target sites to quantitatively assess the functional impact of endogenous genetic variants. We screen over 1,000 endogenous cancer-associated variants of TP53—the most frequently mutated gene in cancer—to identify alleles that impact p53 function in mechanistically diverse ways. We find that certain endogenous TP53 variants, particularly those in the p53 oligomerization domain, display opposite phenotypes in exogenous overexpression systems. Our results emphasize the physiological importance of gene dosage in shaping native protein stoichiometry and protein–protein interactions, and establish a framework for studying genetic variants in their endogenous sequence context at scale.
Metabolic syndrome is not associated with erosive hand osteoarthritis: a cross-sectional study using data from the PROCOAC cohort
Authors: Silva-Díaz Maite , Pértega-Díaz Sonia , Balboa-Barreiro Vanesa , Tilve-Álvarez Carlos M. , Raga-Sivira Ana , Rego-Pérez Ignacio , Blanco Francisco J. , Oreiro Natividad 
Published: March 2024

AbstractTo delineate the phenotype of erosive hand osteoarthritis (EHOA) in a Spanish population and assess its correlation with metabolic syndrome. We conducted a cross-sectional study using baseline data from the Prospective Cohort of Osteoarthritis from A Coruña (PROCOAC). Demographic and clinical variables, obtained through questionnaires, clinical examinations, and patient analytics, were compared among individuals with hand OA, with and without EHOA. We performed appropriate univariate and multivariate stepwise regression analyses using SPSS v28. Among 1039 subjects diagnosed with hand OA, 303 exhibited EHOA. Multivariate logistic regression analysis revealed associations with inflamed joints, nodular hand OA, and total AUSCAN. Furthermore, the association with a lower prevalence of knee OA remained significant. The influence of metabolic syndrome (MetS) on EHOA patients was analyzed by including MetS as a covariate in the model. It was observed that MetS does not significantly impact the presence of EHOA, maintaining the effect size of other factors. In conclusion, in the PROCOAC cohort, EHOA is associated with nodular hand OA, inflammatory hand OA, and a higher total AUSCAN. However, EHOA is linked to a lower prevalence of knee OA. Importantly, in our cohort, no relationship was found between EHOA and MetS.
Silicon and iron nanoparticles protect rice against lead (Pb) stress by improving oxidative tolerance and minimizing Pb uptake
Authors: Ghouri Fozia , Sarwar Samreen , Sun Lixia , Riaz Muhammad , Haider Fasih Ullah , Ashraf Humera , Lai Mingyu , Imran Muhammad , Liu Jingwen , Ali Shafaqat , Liu Xiangdong , Shahid Muhammad Qasim 
Published: March 2024

AbstractLead (Pb) is toxic to the development and growth of rice plants. Nanoparticles (NPs) have been considered one of the efficient remediation techniques to mitigate Pb stress in plants. Therefore, a study was carried out to examine the underlying mechanism of iron (Fe) and silicon (Si) nanoparticle-induced Pb toxicity alleviation in rice seedlings. Si–NPs (2.5 mM) and Fe-NPs (25 mg L−1) were applied alone and in combination to rice plants grown without (control; no Pb stress) and with (100 µM) Pb concentration. Our results revealed that Pb toxicity severely affected all rice growth-related traits, such as inhibited root fresh weight (42%), shoot length (24%), and chlorophyll b contents (26%). Moreover, a substantial amount of Pb was translocated to the above-ground parts of plants, which caused a disturbance in the antioxidative enzyme activities. However, the synergetic use of Fe- and Si–NPs reduced the Pb contents in the upper part of plants by 27%. It reduced the lethal impact of Pb on roots and shoots growth parameters by increasing shoot length (40%), shoot fresh weight (48%), and roots fresh weight (31%). Both Si and Fe–NPs synergistic application significantly elevated superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and glutathione (GSH) concentrations by 114%, 186%, 135%, and 151%, respectively, compared to plants subjected to Pb stress alone. The toxicity of Pb resulted in several cellular abnormalities and altered the expression levels of metal transporters and antioxidant genes. We conclude that the synergistic application of Si and Fe-NPs can be deemed favorable, environmentally promising, and cost-effective for reducing Pb deadliness in rice crops and reclaiming Pb-polluted soils.
General protocol for predicting outbreaks of infectious diseases in social networks
Authors: Kwon Sungchul , Park Jeong-Man 
Published: March 2024

AbstractEpidemic spreading on social networks with quenched connections is strongly influenced by dynamic correlations between connected nodes, posing theoretical challenges in predicting outbreaks of infectious diseases. The quenched connections introduce dynamic correlations, indicating that the infection of one node increases the likelihood of infection among its neighboring nodes. These dynamic correlations pose significant difficulties in developing comprehensive theories for threshold determination. Determining the precise epidemic threshold is pivotal for diseases control. In this study, we propose a general protocol for accurately determining epidemic thresholds by introducing a new set of fundamental conditions, where the number of connections between individuals of each type remains constant in the stationary state, and by devising a rescaling method for infection rates. Our general protocol is applicable to diverse epidemic models, regardless of the number of stages and transmission modes. To validate our protocol’s effectiveness, we apply it to two widely recognized standard models, the susceptible–infected–recovered-susceptible model and the contact process model, both of which have eluded precise threshold determination using existing sophisticated theories. Our results offer essential tools to enhance disease control strategies and preparedness in an ever-evolving landscape of infectious diseases.
BMP2 rs1005464 is associated with mandibular condyle size variation
Authors: Marañón-Vásquez Guido Artemio , de Souza Araújo Mônica Tirre , de Oliveira Ruellas Antônio Carlos , Matsumoto Mírian Aiko Nakane , Figueiredo Marcio , Meyfarth Sandra Regina Santos , Antunes Lívia Azeredo Alves , Baratto-Filho Flares , Scariot Rafaela , Flores-Mir Carlos , Kirschneck Christian , Santos Antunes Leonardo , Küchler Erika Calvano 
Published: March 2024

AbstractThis study aimed to evaluate the association between single nucleotide polymorphisms (SNPs) in endochondral development-related genes and mandibular condyle shape, size, volume, and symmetry traits. Cone-beam Computed Tomographies and genomic DNA from 118 individuals were evaluated (age range: 15–66 years). Data from twelve 3D landmarks on mandibular condyles were submitted to morphometric analyses including Procrustes fit, principal component analysis, and estimation of centroid sizes and fluctuating asymmetry scores. Condylar volumes were additionally measured. Seven SNPs across BMP2, BMP4, RUNX2 and SMAD6 were genotyped. Linear models were fit to evaluate the effect of the SNPs on the mandibular condyles’ quantitative traits. Only the association between BMP2 rs1005464 and centroid size remained significant after adjusting to account for the false discovery rate due to multiple testing. Individuals carrying at least one A allele for this SNP showed larger condylar size than common homozygotes GG (β = 0.043; 95% CI: 0.014—0.071; P value = 0.028). The model including BMP2 rs1005464, age and sex of the participants explained 17% of the variation in condylar size. Shape, volume, and symmetry were not associated with the evaluated SNPs. These results suggest that BMP2 rs1005464 might be associated with variation in the mandibular condyles size.
A new method to experimentally quantify dynamics of initial protein–protein interactions
Authors: Janakaloti Narayanareddy Babu Reddy , Allipeta Nathan Reddy , Allard Jun , Gross Steven P. 
Published: March 2024

AbstractCells run on initiation of protein-protein interactions, which are dynamically tuned spatially and temporally to modulate cellular events. This tuning can be physical, such as attaching the protein to a cargo or protein complex, thereby altering its diffusive properties, or modulating the distance between protein pairs, or chemical, by altering the proteins’ conformations (e.g., nucleotide binding state of an enzyme, post-translational modification of a protein, etc.). Because a dynamic and changing subset of proteins in the cell could be in any specific state, ensemble measurements are not ideal—to untangle which of the factors are important, and how, we need single-molecule measurements. Experimentally, until now we have not had good tools to precisely measure initiation of such protein-protein interactions at the single-molecule level. Here, we develop a new method to measure dynamics of initial protein-protein interactions, allowing measurement of how properties such as the distance between proteins, and their tethered length can modulate the rate of interactions. In addition to precise measurement distance dependent motor-MT rebinding dynamics, we demonstrate the use of a dithered optical trap to measure dynamic motor-MT interactions and further discuss the possibilities of this technique being applicable to other systems.
Artificial intelligence-enabled electrocardiography contributes to hyperthyroidism detection and outcome prediction
Authors: Lin Chin , Kuo Feng-Chih , Chau Tom , Shih Jui-Hu , Lin Chin-Sheng , Chen Chien-Chou , Lee Chia-Cheng , Lin Shih-Hua 
Published: March 2024

Abstract
Background
Hyperthyroidism is frequently under-recognized and leads to heart failure and mortality. Timely identification of high-risk patients is a prerequisite to effective antithyroid therapy. Since the heart is very sensitive to hyperthyroidism and its electrical signature can be demonstrated by electrocardiography, we developed an artificial intelligence model to detect hyperthyroidism by electrocardiography and examined its potential for outcome prediction.

Methods
The deep learning model was trained using a large dataset of 47,245 electrocardiograms from 33,246 patients at an academic medical center. Patients were included if electrocardiograms and measurements of serum thyroid-stimulating hormone were available that had been obtained within a three day period. Serum thyroid-stimulating hormone and free thyroxine were used to define overt and subclinical hyperthyroidism. We tested the model internally using 14,420 patients and externally using two additional test sets comprising 11,498 and 596 patients, respectively.

Results
The performance of the deep learning model achieves areas under the receiver operating characteristic curves (AUCs) of 0.725–0.761 for hyperthyroidism detection, AUCs of 0.867–0.876 for overt hyperthyroidism, and AUC of 0.631–0.701 for subclinical hyperthyroidism, superior to a traditional features-based machine learning model. Patients identified as hyperthyroidism-positive by the deep learning model have a significantly higher risk (1.97–2.94 fold) of all-cause mortality and new-onset heart failure compared to hyperthyroidism-negative patients. This cardiovascular disease stratification is particularly pronounced in subclinical hyperthyroidism, surpassing that observed in overt hyperthyroidism.

Conclusions
An innovative algorithm effectively identifies overt and subclinical hyperthyroidism and contributes to cardiovascular risk assessment.
Using ChatGPT to Improve Health Communication and Plain Language Writing for Students in Communication Sciences and Disorders
Authors: Slavych Bonnie K. , Atcherson Samuel R. , Zraick Richard 
Published: March 2024

Purpose:
This article explores the potential of using ChatGPT, an artificial intelligence–powered chatbot, as a tool to teach plain language writing to students in communication sciences and disorders (CSD). It addresses the importance of plain language writing in health care communication and identifies the challenges faced by graduate students in adopting plain language writing.

Conclusions:
Integrating ChatGPT into CSD education can empower students to develop effective plain language writing skills, with the potential of ultimately improving their communication skills and patient outcomes. The article highlights the potential positive impact of ChatGPT on clinical documentation and health communication, emphasizing the potential to enhance accuracy, consistency, productivity, efficiency, and language accessibility. While considering the limitations and ethical considerations of ChatGPT, the article concludes by emphasizing the need for a balanced approach that combines ChatGPT technology with human instruction to ensure responsible utilization and promote student competency in plain language writing.
Dynamic Assessments of Word Reading Skills in Diverse School-Age Children: A Meta-Analysis
Authors: Wood Emily , Biggs Kereisha , Molnar Monika 
Published: March 2024

Purpose:
Dynamic assessments evaluate ability to learn and may be less biased against children who historically have underperformed on static measures that evaluate acquired knowledge. This meta-analysis examined the validity of dynamic assessments of word reading skills (phonological awareness, sound–symbol knowledge, and decoding), as measured by the strength of their correlation with performance on word reading measures. The consistency of their validity across participant reading status (typically developing vs. at risk), language status (monolingual vs. bilingual), and age group (4–5 vs. 6–7 vs. 8–9 years) was also examined to determine whether this assessment approach is an equitable means of evaluating early word reading skills.

Method:
Electronic databases and preprint repositories were searched to identify studies that evaluated dynamic assessments of word reading skills conducted with children between the ages of 4 and 10 years. Pearson's correlation coefficients representing the relationship between dynamic assessments and word reading measures were extracted, and an overall pooled mean effect size was calculated using a random-effects meta-analysis with robust variance estimation. Subgroup analyses for participant reading status, language status, and age group were also conducted to determine whether there were significant differences in effect sizes across groups.

Results:

Thirty-five studies with 192 effect sizes were identified. Overall, dynamic assessments of word reading skills demonstrated strong correlations with word reading measures (
g
= 0.49). Subgroup analysis by age indicated that dynamic assessments are significantly better suited to evaluate word reading in younger children (ages 4–5 and 6–7 years) than older students (ages 8–9 years;
p
= .0001). Validity was consistent across typically developing and at-risk participants and across bilinguals and monolinguals. There were few studies conducted with bilinguals despite dynamic assessment's purported application for this population.

Conclusion:
This meta-analysis provides preliminary evidence to support dynamic assessments as a valid and equitable means of evaluating word reading skills with diverse children aged 4–7 years.

Supplemental Material:

https://doi.org/10.23641/asha.25293046
Thermal runaway and induced electrical failure of epoxy resin in high‐frequency transformers: Insulation design reference
Authors: Shang Xingyu , Pang Lei , Bu Qinhao , Zhang Qiaogen 
Published: March 2024

AbstractSolid‐state transformers (SSTs) have applications in medium‐voltage direct current (MVDC) grids and compact power systems. High‐frequency transformer (HFT) is the core component of SSTs. High levels of high frequency high dv/dt voltage stresses challenged the integrity of the galvanic insulation of HFTs. However, dielectric thermal runaway and resultant electrical failure mechanisms in epoxy resin (EP) cast insulation remain unclear. Dielectric heating of EP across varying voltages, frequencies, rising edges, duty cycles and DC biases were measured and corroborated by simulation. The thermal runaway threshold mainly depends on the tangency point of the loss generation and heat dissipation curves below the glass transition temperature. Observations reveal that thermal runaway does not directly cause breakdown; instead, thermal decomposition above 200°C triggers discharge and eventual failure. Simulations demonstrate that temperature rise mainly depends on the average field within the electrode region and inter‐segment and inter‐layer distances within the HFT winding definitively impact insulation thermal runaway. By applying different criteria for MV and high‐voltage (HV) transformers, the reference electric fields for insulation design with unfilled and filled EP were obtained. For instance, limiting dielectric heating below 5 K at 50 kHz necessitates an RMS average field less than 0.44 V/mm, which is much lower than dry‐type transformer conventions. The authors prove the necessity of re‐evaluating the permissible field strength in HFT insulation design.
Solar photovoltaic panel soiling accumulation and removal methods: A review
Authors: Liu Yunpeng , Li Haoyi , Li Le , Yin Xiaoxuan , Wu Xinyue , Su Zheng , Gao Fengsheng , Cai BinBin , Tang Li , Zhou Songsong 
Published: March 2024

AbstractPhotovoltaic (PV) power generation has become a key area for investment worldwide. Solar PV panels are the core components of PV power generation systems, and the accumulation of soiling on their surfaces has numerous adverse effects on power generation. This paper provides an overview of the soiling accumulation on PV panels and the existing soiling removal methods. Firstly, the sources of soiling particles and the mechanism of soiling fall are analyzed, based on which the accumulation of soiling on the surface of the PV panels is described in detail, and then the effect of the surface soiling on the PV panels is investigated in the order of optics‐thermology‐electrical, with the necessary semiempirical formulas provided to assist in more in‐depth analyses. In addition, the principles, status quo, effects, costs, advantages, and disadvantages of existing soiling removal methods are specifically described, thus providing a reference for the selection of soiling removal methods in different regions. The paper also analyses the soiling accumulation and removal challenges of PV panels in different regions of China. The results of the study are important for the improvement of the effectiveness of soiling removal and the rational optimization of the soiling removal scheme.
WHO-Leitlinie zur psychischen Gesundheit am
Arbeitsplatz
Authors: Piso Brigitte , Nußbaumer-Streit Barbara , Gartlehner Gerald 
Published: March 2024

ZusammenfassungDie Weltgesundheitsorganisation (WHO) veröffentlichte im September 2022 die
Leitlinie „Guidelines on mental health at work“. Die WHO erarbeitete die
Leitlinie gemäß WHO-Standards. Um den Transfer in den deutschsprachigen Raum zu
erleichtern, wurde die Zusammenfassung dieser Leitlinie vom Team des WHO
Collaborating Centres für Evidenzbasierte Medizin an der Universität für
Weiterbildung Krems (Österreich) ins Deutsche übersetzt. Schätzungsweise 15+%
der Erwachsenen im erwerbsfähigen Alter sind im Laufe ihres Lebens von einer
psychischen Erkrankung betroffen. In der Folge kann die Fähigkeit zur
beruflichen Teilhabe unter anderem durch eine verringerte Produktivität und
Leistungsfähigkeit oder durch Schwierigkeiten bei der Aufrechterhaltung oder
Erlangung eines Beschäftigungsverhältnisses beeinträchtigt sein. Die Leitlinie
beinhaltet 12 Empfehlungen. Diese bieten eine evidenzbasierte Orientierungshilfe
zu organisatorischen Maßnahmen, zur Schulung von Führungskräften und
ArbeitnehmerInnen, zu spezifischen gesundheitsfördernden und präventiven
Maßnahmen, sowie zur Rückkehr an den Arbeitsplatz nach psychisch bedingten
Fehlzeiten und zu Beschäftigungsverhältnissen für Menschen mit psychischen
Erkrankungen. Durch die Bereitstellung dieser neuen WHO-Empfehlungen soll die
Strategieentwicklung und die Planung und Erbringung von Dienstleistungen, die
psychische Gesundheit und Gesundheit am Arbeitsplatz betreffen, auf nationaler
und betrieblicher Ebene erleichtert werden.