bluuebunny/crossref_metadata_2025 huggingface dataset:
Aerobic exercise attenuates dysautonomia, cardiac diastolic dysfunctions, and hemodynamic overload in female mice with atherosclerosis
Authors: Nascimento-Carvalho Bruno , da Silva Bruno Durante , da Silva Maikon Barbosa , Dos-Santos Adriano , Ribeiro Thayna Fabiana , da Silva Dias Danielle , de Souza Leandro Eziquiel , Dutra Marina Rascio Henriques , Catanozi Sergio , Caldini Elia G. , De Angelis Kátia , Scapini Katia Bilhar , Sanches Iris Callado , Irigoyen Maria Claudia
Published: April 2024

Cardiovascular risk increases during the aging process in women with atherosclerosis and exercise training is a strategy for management of cardiac risks in at-risk populations. Therefore, the aims of this study were to evaluate: (1) the influence of the aging process on cardiac function, hemodynamics, cardiovascular autonomic modulation, and baroreflex sensitivity in females with atherosclerosis at the onset of reproductive senescence; and (2) the impact of exercise training on age-related dysfunctions in this model. Eighteen Apolipoprotein-E knockout female mice were divided equally into young (Y), middle-aged (MA), and trained middle-aged (MAT). Echocardiographic exams were performed to verify cardiac morphology and function. Cannulation for direct recording of blood pressure and heart rate, and analysis of cardiovascular autonomic modulation, baroreflex sensitivity were performed. The MA had lower cardiac diastolic function (E'/A' ratio), and higher aortic thickness, heart rate and mean arterial pressure, lower heart rate variability and baroreflex sensitivity compared with Y. There were no differences between Y and MAT in these parameters. Positive correlation coefficients were found between aortic wall thickness with hemodynamics data. The aging process causes a series of deleterious effects such as hemodynamic overload and dysautonomia in female with atherosclerosis. Exercise training was effective in mitigating aged-related dysfunctions.
ANN: adversarial news net for robust fake news classification
Authors: Maham Shiza , Tariq Abdullah , Khan Muhammad Usman Ghani , Alamri Faten S. , Rehman Amjad , Saba Tanzila
Published: April 2024

With easy access to social media platforms, spreading fake news has become a growing concern today. Classifying fake news is essential, as it can help prevent its negative impact on individuals and society. In this regard, an end-to-end framework for fake news detection is developed by utilizing the power of adversarial training to make the model more robust and resilient. The framework is named "ANN: Adversarial News Net," emoticons have been extracted from the datasets to understand their meanings concerning fake news. This information is then fed into the model, which helps to improve its performance in classifying fake news. The performance of the ANN framework is evaluated using four publicly available datasets, and it is found to outperform baseline methods and previous studies after adversarial training. Experiments show that Adversarial Training improved the performance by 2.1% over the Random Forest baseline and 2.4% over the BERT baseline method in terms of accuracy. The proposed framework can be used to detect fake news in real-time, thereby mitigating its harmful effects on society.
HD-tDCS mitigates the executive vigilance decrement only under high cognitive demands
Authors: Hemmerich Klara , Lupiáñez Juan , Martín-Arévalo Elisa
Published: April 2024

Maintaining vigilance is essential for many everyday tasks, but over time, our ability to sustain it inevitably decreases, potentially entailing severe consequences. High-definition transcranial direct current stimulation (HD-tDCS) has proven to be useful for studying and improving vigilance. This study explores if/how cognitive load affects the mitigatory effects of HD-tDCS on the vigilance decrement. Participants (N = 120) completed a modified ANTI-Vea task (single or dual load) while receiving either sham or anodal HD-tDCS over the right posterior parietal cortex (rPPC). This data was compared with data from prior studies (N = 120), where participants completed the standard ANTI-Vea task (triple load task), combined with the same HD-tDCS protocol. Against our hypotheses, both the single and dual load conditions showed a significant executive vigilance (EV) decrement, which was not affected by the application of rPPC HD-tDCS. On the contrary, the most cognitively demanding task (triple task) showed the greatest EV decrement; importantly, it was also with the triple task that a significant mitigatory effect of the HD-tDCS intervention was observed. The present study contributes to a more nuanced understanding of the specific effects of HD-tDCS on the vigilance decrement considering cognitive demands. This can ultimately contribute to reconciling heterogeneous effects observed in past research and fine-tuning its future clinical application.
Experience shapes non-linearities between team behavioral interdependence, team collaboration, and performance in massively multiplayer online games
Authors: Carrasco-Farré Carlos , Hakobjanyan Nancy
Published: April 2024

This paper examines quantitative predictors of team performance in Massively Multiplayer Online Games (MMOGs) based on team management literature. Analyzing data from more than 140,000 squad-mode matches involving over 500,000 players, we replicate and extend existing research by confirming a curvilinear association between behavioral interdependence and team performance and introduce the moderating effect of experience. For less experienced teams, behavioral interdependence follows an inverted U-shaped pattern showing that excessive collaboration may be counterproductive. However, this is not the case for experienced teams, where the relationship is fairly linear. Additionally, we observe that riskier teams tend to perform worse. Moreover, our research also highlights the potential of e-sports data in advancing behavioral science and management research. The digital nature of e-sports datasets, characterized by size and granularity, mitigates concerns related to reproducibility, replicability, and generalizability in social science research, offering a cost-effective platform for scholars with diverse backgrounds.
SU-101 for the removal of pharmaceutical active compounds by the combination of adsorption/photocatalytic processes
Authors: Chacón-García Antonio J. , Rojas Sara , Grape Erik Svensson , Salles Fabrice , Willhammar Tom , Inge A. Ken , Pérez Yolanda , Horcajada Patricia
Published: April 2024

Pharmaceutical active compounds (PhACs) are some of the most recalcitrant water pollutants causing undesired environmental and human effects. In absence of adapted decontamination technologies, there is an urgent need to develop efficient and sustainable alternatives for water remediation. Metal–organic frameworks (MOFs) have recently emerged as promising candidates for adsorbing contaminants as well as providing photoactive sites, as they possess exceptional porosity and chemical versatility. To date, the reported studies using MOFs in water remediation have been mainly focused on the removal of a single type of PhACs and rarely on the combined elimination of PhACs mixtures. Herein, the eco-friendly bismuth-based MOF, SU-101, has been originally proposed as an efficient adsorbent-photocatalyst for the elimination of a mixture of three challenging persistent PhACs, frequently detected in wastewater and surface water in ng L−1 to mg·L−1 concentrations: the antibiotic sulfamethazine (SMT), the anti-inflammatory diclofenac (DCF), and the antihypertensive atenolol (At). Adsorption experiments of the mixture revealed that SU-101 exhibited a great adsorption capacity towards At, resulting in an almost complete removal (94.1 ± 0.8% for combined adsorption) in only 5 h. Also, SU-101 demonstrated a remarkable photocatalytic activity under visible light to simultaneously degrade DCF and SMT (99.6 ± 0.4% and 89.2 ± 1.4%, respectively). In addition, MOF-contaminant interactions, the photocatalytic mechanism and degradation pathways were investigated, also assessing the toxicity of the resulting degradation products. Even further, recycling and regeneration studies were performed, demonstrating its efficient reuse for 4 consecutive cycles without further treatment, and its subsequent successful regeneration by simply washing the material with a NaCl solution.
Regional reef fish assemblage maps provide baseline biogeography for tropicalization monitoring
Authors: Walker Brian K. , Fisco Becker Dana , Williams Gareth J. , Kilfoyle Audie K. , Smith Steven G. , Kozachuk Allie
Published: April 2024

The Anthropocene rise in global temperatures is facilitating the expansion of tropical species into historically non-native subtropical locales, including coral reef fish. This redistribution of species, known as tropicalization, has serious consequences for economic development, livelihoods, food security, human health, and culture. Measuring the tropicalization of subtropical reef fish assemblages is difficult due to expansive species ranges, temporal distribution shifts with the movement of isotherms, and many dynamic density-dependent factors affecting occurrence and density. Therefore, in locales where tropical and subtropical species co-occur, detecting tropicalization changes relies on regional analyses of the relative densities and occurrence of species. This study provides a baseline for monitoring reef fish tropicalization by utilizing extensive monitoring data from a pivotal location in southeast Florida along a known transition between tropical and subtropical ecotones to define regional reef fish assemblages and use benthic habitat maps to spatially represent their zoogeography. Assemblages varied significantly by ecoregion, habitat depth, habitat type, and topographic relief. Generally, the southern assemblages had higher occurrences and densities of tropical species, whereas the northern assemblages had a higher occurrence and density of subtropical species. A total of 108 species were exclusive to regions south of the Bahamas Fracture Zone (BFZ) (South Palm Beach, Deerfield, Broward-Miami) and 35 were exclusive to the north (North Palm Beach, Martin), supporting the BFZ as a pivotal location that affects the coastal biogeographic extent of tropical marine species in eastern North America. Future tropicalization of reef fish assemblages are expected to be evident in temporal deviance of percent occurrence and/or relative species densities between baseline assemblages, where the poleward expansion of tropical species is expected to show the homogenization of assemblage regions as adjacent regions become more similar or the regional boundaries expand poleward. Ecoregions, habitat depth, habitat type, and relief should be incorporated into the stratification and analyses of reef fish surveys to statistically determine assemblage differences across the seascape, including those from tropicalization.
Effect of a fixed combination of ripasudil and brimonidine on aqueous humor dynamics in mice
Authors: Yamagishi-Kimura Reiko , Honjo Megumi , Aihara Makoto
Published: April 2024

Ripasudil–brimonidine fixed-dose combination (K-232) simultaneously targets three different intraocular pressure (IOP) lowering mechanisms, increasing trabecular meshwork outflow and uveoscleral outflow, and reducing aqueous humor production Vascularly, ripasudil induces transient vasodilation, brimonidine transient vasoconstriction. Investigating effects on IOP, aqueous dynamics, and EVP in mice eyes by microneedle and constant-pressure perfusion methods, and on cytoskeletal and fibrotic proteins changes in HTM cells by a gel contraction assay and immunocytochemistry. Ripasudil, K-232, and brimonidine droplets significantly reduced IOP at 30 min, with K-232 sustaining the effect at 60 min. For EVP, only K-232 exhibited reduced EVP until 60 min after instillation. In vitro, ripasudil inhibited gel contractility and TGFβ2-induced fibrotic changes, whereas brimonidine did not. K-232 significantly lowered IOPs in mice by combining the effects of ripasudil and brimonidine. Brimonidine alone also showed IOP reductions with enhanced outflow facility, and the drug did not interfere with the effects of ripasudil on the trabecular meshwork outflow; K-232 and ripasudil alone both significantly lowered the EVP and enhanced outflow facility, demonstrating that K-232 efficiently reduces IOPs.
Human health risk of nitrate in groundwater of Tehran–Karaj plain, Iran
Authors: Alizadeh Maedeh , Noori Roohollah , Omidvar Babak , Nohegar Ahmad , Pistre Severin
Published: April 2024

Groundwater pollution by nitrate has is a major concern in the Tehran–Karaj aquifer, Iran, where the wells provide up to 80% of the water supply for a population of more than 18 million—yet detailed human health risks associated with nitrate are unknown due to the lack of accessible data to adequately cover the aquifer in both place and time. Here, using a rich dataset measured annually in more than 75 wells, we mapped the non-carcinogenic risk of nitrate in the aquifer between 2007 and 2018, a window with the most extensive anthropogenic activities in this region. Nitrate concentration varied from ~ 6 to ~ 150 mg/L, around three times greater than the standard level for drinking use, i.e. 50 mg/L. Samples with a non-carcinogenic risk of nitrate, which mainly located in the eastern parts of the study region, threatened children’s health, the most vulnerable age group, in almost all of the years during the study period. Our findings revealed that the number of samples with a positive risk of nitrate for adults decreased in the aquifer from 2007 (17 wells) to 2018 (6 wells). Although we hypothesized that unsustainable agricultural practices, the growing population, and increased industrial activities could have increased the nitrate level in the Tehran-Karaj aquifer, improved sanitation infrastructures helped to prevent the intensification of nitrate pollution in the aquifer during the study period. Our compilation of annually mapped non-carcinogenic risks of nitrate is beneficial for local authorities to understand the high-risk zones in the aquifer and for the formulation of policy actions to protect the human health of people who use groundwater for drinking and other purposes in this densely populated region.
Classifying early infant feeding status from clinical notes using natural language processing and machine learning
Authors: Lemas Dominick J. , Du Xinsong , Rouhizadeh Masoud , Lewis Braeden , Frank Simon , Wright Lauren , Spirache Alex , Gonzalez Lisa , Cheves Ryan , Magalhães Marina , Zapata Ruben , Reddy Rahul , Xu Ke , Parker Leslie , Harle Chris , Young Bridget , Louis-Jaques Adetola , Zhang Bouri , Thompson Lindsay , Hogan William R. , Modave François
Published: April 2024

The objective of this study is to develop and evaluate natural language processing (NLP) and machine learning models to predict infant feeding status from clinical notes in the Epic electronic health records system. The primary outcome was the classification of infant feeding status from clinical notes using Medical Subject Headings (MeSH) terms. Annotation of notes was completed using TeamTat to uniquely classify clinical notes according to infant feeding status. We trained 6 machine learning models to classify infant feeding status: logistic regression, random forest, XGBoost gradient descent, k-nearest neighbors, and support-vector classifier. Model comparison was evaluated based on overall accuracy, precision, recall, and F1 score. Our modeling corpus included an even number of clinical notes that was a balanced sample across each class. We manually reviewed 999 notes that represented 746 mother-infant dyads with a mean gestational age of 38.9 weeks and a mean maternal age of 26.6 years. The most frequent feeding status classification present for this study was exclusive breastfeeding [n = 183 (18.3%)], followed by exclusive formula bottle feeding [n = 146 (14.6%)], and exclusive feeding of expressed mother’s milk [n = 102 (10.2%)], with mixed feeding being the least frequent [n = 23 (2.3%)]. Our final analysis evaluated the classification of clinical notes as breast, formula/bottle, and missing. The machine learning models were trained on these three classes after performing balancing and down sampling. The XGBoost model outperformed all others by achieving an accuracy of 90.1%, a macro-averaged precision of 90.3%, a macro-averaged recall of 90.1%, and a macro-averaged F1 score of 90.1%. Our results demonstrate that natural language processing can be applied to clinical notes stored in the electronic health records to classify infant feeding status. Early identification of breastfeeding status using NLP on unstructured electronic health records data can be used to inform precision public health interventions focused on improving lactation support for postpartum patients.
The redox-sensitive R-loop of the carbon control protein SbtB contributes to the regulation of the cyanobacterial CCM
Authors: Mantovani Oliver , Haffner Michael , Walke Peter , Elshereef Abdalla A. , Wagner Berenike , Petras Daniel , Forchhammer Karl , Selim Khaled A. , Hagemann Martin
Published: April 2024

SbtB is a PII-like protein that regulates the carbon-concentrating mechanism (CCM) in cyanobacteria. SbtB proteins can bind many adenyl nucleotides and possess a characteristic C-terminal redox sensitive loop (R-loop) that forms a disulfide bridge in response to the diurnal state of the cell. SbtBs also possess an ATPase/ADPase activity that is modulated by the redox-state of the R-loop. To investigate the R-loop in the cyanobacterium Synechocystis sp. PCC 6803, site-specific mutants, unable to form the hairpin and permanently in the reduced state, and a R-loop truncation mutant, were characterized under different inorganic carbon (Ci) and light regimes. Growth under diurnal rhythm showed a role of the R-loop as sensor for acclimation to changing light conditions. The redox-state of the R-loop was found to impact the binding of the adenyl-nucleotides to SbtB, its membrane association and thereby the CCM regulation, while these phenotypes disappeared after truncation of the R-loop. Collectively, our data imply that the redox-sensitive R-loop provides an additional regulatory layer to SbtB, linking the CO2-related signaling activity of SbtB with the redox state of cells, mainly reporting the actual light conditions. This regulation not only coordinates CCM activity in the diurnal rhythm but also affects the primary carbon metabolism.
Utility of new FDG-PET/CT guidelines for diagnosing cardiac sarcoidosis in patients with implanted cardiac pacemakers for atrioventricular block
Authors: Tanabe Subaru , Nakano Yusuke , Ando Hirohiko , Fujimoto Masanobu , Onishi Tomohiro , Ohashi Hirofumi , Kuno Shimpei , Naito Kazuhiro , Waseda Katsuhisa , Takahashi Hiroshi , Suzuki Yasushi , Fukuta Motoyuki , Amano Tetsuya
Published: April 2024

Diagnosing cardiac sarcoidosis (CS), especially in isolated cases, is challenging, particularly due to the limitations of endomyocardial biopsy, leading to potential undiagnosed cases in pacemaker-implanted patients. This study aims to provide real world findings to support new guideline for CS using 18F-fluoro-deoxyglucose positron-emission tomography computed tomography (FDG-PET/CT) which give a definite diagnosis of isolated CS (iCS) without histological findings. We examined consecutive patients with cardiac pacemakers for atrioventricular block (AV-b) attending our outpatient pacemaker clinic. The patients underwent periodical follow-up echocardiography and were divided into two groups according to echocardiographic findings: those with suspected CS and those without suspected CS. Patients suspected of having nonischemic cardiomyopathy underwent FDG-PET/CT for CS diagnosis. We investigated the utility of the new guideline for CS using FDG-PET/CT. Among the 272 patients enrolled, 97 patients were implanted with cardiac pacemakers for AV-b. Twenty-two patients were suspected of having CS during a median observation period of 5.4 years after pacemaker implantation. Of these, one did not consent, and nine of 21 cases (43%) were diagnosed with definite CS according to the new guidelines. Five of these nine patients were diagnosed with iCS using FDG-PET/CT. The number of patients diagnosed with definite CS using the new guidelines tended to be approximately 2.3 times that of the conventional criteria (p = 0.074). Three of the nine patients underwent steroid treatment. The composite outcome, comprising all-cause death, heart failure hospitalization, and a substantial reduction in left ventricular ejection fraction, were significantly lower in patients receiving steroid treatment compared to those without steroid treatment (p = 0.048). The utilization of FDG-PET/CT in accordance with the new guidelines facilitates the diagnosis of CS, including iCS, resulting in approximately 2.3 times as many diagnoses of CS compared to the conventional criteria. This guideline has the potential to support the early identification of iCS and may contribute to enhancing patient clinical outcomes.
Comprehensive evaluation and performance analysis of machine learning in heart disease prediction
Authors: Al-Alshaikh Halah A. , P Prabu , Poonia Ramesh Chandra , Saudagar Abdul Khader Jilani , Yadav Manoj , AlSagri Hatoon S. , AlSanad Abeer A.
Published: April 2024

Heart disease is a leading cause of mortality on a global scale. Accurately predicting cardiovascular disease poses a significant challenge within clinical data analysis. The present study introduces a prediction model that utilizes various combinations of information and employs multiple established classification approaches. The proposed technique combines the genetic algorithm (GA) and the recursive feature elimination method (RFEM) to select relevant features, thus enhancing the model’s robustness. Techniques like the under sampling clustering oversampling method (USCOM) address the issue of data imbalance, thereby improving the model’s predictive capabilities. The classification challenge employs a multilayer deep convolutional neural network (MLDCNN), trained using the adaptive elephant herd optimization method (AEHOM). The proposed machine learning-based heart disease prediction method (ML-HDPM) demonstrates outstanding performance across various crucial evaluation parameters, as indicated by its comprehensive assessment. During the training process, the ML-HDPM model exhibits a high level of performance, achieving an accuracy rate of 95.5% and a precision rate of 94.8%. The system’s sensitivity (recall) performs with a high accuracy rate of 96.2%, while the F-score highlights its well-balanced performance, measuring 91.5%. It is worth noting that the specificity of ML-HDPM is recorded at a remarkable 89.7%. The findings underscore the potential of ML-HDPM to transform the prediction of heart disease and aid healthcare practitioners in providing precise diagnoses, exerting a substantial influence on patient care outcomes.
Phylogeny and structural modeling of the transcription factor CsqR (YihW) from Escherichia coli
Authors: Rybina Anna A. , Glushak Roman A. , Bessonova Tatiana A. , Dakhnovets Artemiy I. , Rudenko Alexander Yu. , Ozhiganov Ratislav M. , Kaznadzey Anna D. , Tutukina Maria N. , Gelfand Mikhail S.
Published: April 2024

CsqR (YihW) is a local transcription factor that controls expression of yih genes involved in degradation of sulfoquinovose in Escherichia coli. We recently showed that expression of the respective gene cassette might be regulated by lactose. Here, we explore the phylogenetic and functional traits of CsqR. Phylogenetic analysis revealed that CsqR had a conserved Met25. Western blot demonstrated that CsqR was synthesized in the bacterial cell as two protein forms, 28.5 (CsqR-l) and 26 kDa (CsqR-s), the latter corresponding to start of translation at Met25. CsqR-s was dramatically activated during growth with sulfoquinovose as a sole carbon source, and displaced CsqR-l in the stationary phase during growth on rich medium. Molecular dynamic simulations revealed two possible states of the CsqR-s structure, with the interdomain linker being represented by either a disordered loop or an ɑ-helix. This helix allowed the hinge-like motion of the N-terminal domain resulting in a switch of CsqR-s between two conformational states, “open” and “compact”. We then modeled the interaction of both CsqR forms with putative effectors sulfoquinovose, sulforhamnose, sulfoquinovosyl glycerol, and lactose, and revealed that they all preferred the same pocket in CsqR-l, while in CsqR-s there were two possible options dependent on the linker structure.
Chronic replication stress invokes mitochondria dysfunction via impaired parkin activity
Authors: Kawabata Tsuyoshi , Sekiya Reiko , Goto Shinji , Li Tao-Sheng
Published: April 2024

Replication stress is a major contributor to tumorigenesis because it provides a source of chromosomal rearrangements via recombination events. PARK2, which encodes parkin, a regulator of mitochondrial homeostasis, is located on one of the common fragile sites that are prone to rearrangement by replication stress, indicating that replication stress may potentially impact mitochondrial homeostasis. Here, we show that chronic low-dose replication stress causes a fixed reduction in parkin expression, which is associated with mitochondrial dysfunction, indicated by an increase in mtROS. Consistent with the major role of parkin in mitophagy, reduction in parkin protein expression was associated with a slight decrease in mitophagy and changes in mitochondrial morphology. In contrast, cells expressing ectopic PARK2 gene does not show mtROS increases and changes in mitochondrial morphology even after exposure to chronic replication stress, suggesting that intrinsic fragility at PARK2 loci associated with parkin reduction is responsible for mitochondrial dysfunction caused by chronic replication stress. As endogenous replication stress and mitochondrial dysfunction are both involved in multiple pathophysiology, our data support the therapeutic development of recovery of parkin expression in human healthcare.
Urban Nature Indexes tool offers comprehensive and flexible approach to monitoring urban ecological performance
Authors: Pierce Jennifer Rae , Costadone Laura , Mannetti Lelani , Morpurgo Joeri , Green Charlyn Elaine , Halder Michael D. , Guijosa Pablo Arturo Lopez , Bogan Abner L. , Galt Russell , Hughes Jonathan
Published: April 2024

We present the Urban Nature Indexes (UNI), a comprehensive tool that measures urban ecological performance under one standard framework linked to global commitments. The UNI was developed by interdisciplinary experts and evaluated by practitioners from diverse cities to capture each city’s ecological footprint from local to global scale. The UNI comprises six themes (consumption drivers, human pressures, habitat status, species status, nature’s contributions to people, and governance responses) that encompass measurable impacts on climate change, biodiversity loss, ecosystem services, pollution, consumption, water management, and equity within one comprehensive system. Cities then adapt the UNI to their context and capacity by selecting among indicator topics within each theme. This adaptability and holistic approach position the UNI as an essential instrument for nature-positive transformations. With the institutional support of IUCN, the UNI offers an opportunity for cities to assess and enhance their contributions towards a more sustainable and biodiverse future.
Theoretical evidence for the enantioselectivity of Mannich reactions with fluorinated aromatic ketones
Authors: Peng Cheng , Zhang Jian , Wang Yong , Liu Wei
Published: April 2024

The enantioselective mechanism of the Mannich reaction with fluorinated aromatic ketones catalyzed by Zn/prophenol was examined using B3LYP density functional theory.
Metal shields with crystallographic discrepancies incorporated into integrated architectures for stable lithium metal batteries
Authors: Cho Ki-Yeop , Cho Sungjun , Jung Gun Young , Eom KwangSup
Published: April 2024

The lithiophobic properties of metals are investigated to discover metal shields preventing top-surface Li accumulation on versatile 3D-hosts. A facile top-down method is devised for the first time to integrate the metal shields into 3D-hosts.
Ultra-high surface area ionic-liquid-derived carbons that meet both gravimetric and volumetric methane storage targets
Authors: Albeladi Nawaf , Blankenship L. Scott , Mokaya Robert
Published: April 2024

Activation of N-rich and O-poor carbonised matter from ionic liquids yields ultraporous carbon (4000 m2 g−1 and 3.3 cm3 g−1) with high packing density that translates to methane uptake of up to 0.53 g g−1 and 289 cm3 (STP) cm−3 at 25 °C and 100 bar.
Phase transition of recombinant fusion protein assemblies in macromolecularly crowded conditions
Authors: Shin Jooyong , Jia Yinhao , Sampath Janani , Jang Yeongseon
Published: April 2024

This study investigates the phase transition of globular protein vesicles – a model for protein-constructed artificial cells and organelles – under macromolecular crowding conditions in biomimetic environments.
Exploring the stable structures of cerium oxide nanoclusters using high-dimensional neural network potential
Authors: Cai Huabing , Ren Qinghua , Gao Yi
Published: April 2024

In this work, a machine learning model is developed to construct high-dimensional neural network potential to search for the most stable structures of cerium oxide nanoclusters.
Exceptional stability of ultrasmall cubic copper metal nanoclusters – a molecular dynamics study
Authors: Chathoth Nayana Edavan , S Hafila Khairun , Krishna Manya , Anjukandi Padmesh
Published: April 2024

The cubic metal nanoclusters, especially the smaller ones, exhibited stability when placed in 4 M [N1114][C1SO3] ionic liquid solution.
Time-averaged atomic volume spectrum: locating and identifying vacancies
Authors: Wu YongQuan , Wang Hao , Fu JiaHao , Zhang BoYang , Zhao Xu , Zhang Kai
Published: April 2024

We developed the TAVS method to accurately locate and fully identify vacancies based on a new concept of the atomic cage enwrapping vacancies. This flexible method is believed to be applicable to any type of vacancy in any type of material.
Correction: Excitons in metal halide perovskite nanoplatelets: an effective mass description of polaronic, dielectric and quantum confinement effects
Authors: Movilla Jose L. , Planelles Josep , Climente Juan I.
Published: April 2024

Correction for ‘Excitons in metal halide perovskite nanoplatelets: an effective mass description of polaronic, dielectric and quantum confinement effects’ by Jose L. Movilla et al., Nanoscale Adv., 2023, 5, 6093–6101, https://doi.org/10.1039/d3na00592e.
Enantioselective synthesis of 8-membered lactone derivatives via organocatalytic cascade reactions
Authors: Ji Dong-Sheng , Zhang Rui , Han Xu-Yan , Chai Hai-Long , Gu Yucheng , Hu Xiu-Qin , Xu Peng-Fei
Published: April 2024

The challenging 8-membered lactone derivatives bearing two vicinal chiral stereocenters were synthesized via a cascade reaction mediated by the chiral squaramide.
Electrochemically dehydrogenative C(sp2)–H/S–H cross-coupling: efficient synthesis of ortho-aminophenyl thioglycoside derivatives
Authors: Hu Li-Yan , Zhu Li , Zhang Shen-Yuan , Guo Yu-Xin , Li Yuan , Zhu Jie , Wu Lei
Published: April 2024

A method has been reported for synthesizing aryl thioglycosides through direct electrocatalytic dehydrogenative C(sp2)–H/S–H cross-coupling.
Decarbonylative C(sp2)–C(sp2) reductive cross-coupling of aroyl fluorides with aryl bromides by palladium/cobalt co-catalysis
Authors: He Chen , Song Zhiyong , Yao Wei , Lin Rui , Ma Yuanhong
Published: April 2024

Herein, we report a decarbonylative C(sp2)–C(sp2) reductive cross-coupling of aroyl fluorides with aryl bromides by palladium and cobalt co-catalysis.
Vaska's complex–PMHS combination enabled mild and chemoselective reduction of sulfoxides to sulfides with low catalyst loading
Authors: Xu Fang-Fang , Ruan Zhong-Lei , Huang Pei-Qiang
Published: April 2024

We report a highly efficient, versatile, and chemoselective method for the catalytic reduction of sulfoxides to sulfides under mild conditions.
Stereodivergent synthesis of chiral spiropyrazolones through Pd-catalyzed asymmetric sequential hydroalkylation of 1,3-enynes: unusual solvent effects on the enantioselectivity
Authors: Wang Shan , Li Long , Zheng Yifei , Li Luqing , Wang Yingcheng , Peng Fangzhi , Shao Zhihui
Published: April 2024

Chiral spiropyrazolones were constructed through Pd-catalyzed asymmetric sequential hydroalkylation of 1,3-enynes. Four stereoisomers could be obtained through substrate control and chiral ligand control.
Review of application of the I2 and dimethyl sulfoxide combined reagent system to aryl methyl ketones for diverse transformations
Authors: Yang Dong-Sheng , Chen Xiang-Long , Wu An-Xin
Published: April 2024

The synthesis of small molecules and complex scaffolds is one of the most important topics in organic synthesis.
Multicomponent synthesis via acceptorless alcohol dehydrogenation: an easy access to tri-substituted pyridines
Authors: P. Hima , M. Vageesh , Dey Raju
Published: April 2024

The multicomponent synthesis of 2,4,6-trisubstituted pyridine via acceptorless alcohol dehydrogenation using ammonium acetate as a nitrogen source catalyzed by hydroxyapatite-supported palladium nanoparticles as a heterogeneous catalyst.
Study on microstructure evolution of waxy crude oil emulsions under dynamic cooling conditions
Authors: Dong Hang , Guo Nan , Zhang Pengfei , Zhao Jian , Wang Zhihua
Published: April 2024

Emulsified water droplets and wax crystals can show different collision and aggregation behaviors in stages under dynamic cooling conditions.
Photochemical organocatalytic heteroarylation of anilines and secondary alicyclic amines in continuous-flow
Authors: Boronin Egor N. , Svetlakova Milena M. , Vorobyov Ilya I. , Malysheva Yulia B. , Polushtaytsev Yuri V. , Mensov Sergey N. , Vorotyntsev Andrey V. , Fedorov Alexey Yu. , Noël Timothy , Nyuchev Alexander V.
Published: April 2024

Photoorganocatalytic arylation of amines in continuous-flow enables scaling up including decreasing of both reaction time and catalyst loading.
Engineering of the perovskite/electron-transporting layer interface with transition metal chalcogenides for improving the performance of inverted perovskite solar cells
Authors: Tsikritzis Dimitris , Chatzimanolis Konstantinos , Tzoganakis Nikolaos , Rogdakis Konstantinos , Zappia Marilena Isabella , Martín-García Beatriz , Bagheri Ahmad , Beydaghi Hossein , Děkanovský Lukáš , Sofer Zdeněk , Bellani Sebastiano , Bonaccorso Francesco , Kymakis Emmanuel
Published: April 2024

Representative 2D transition metal chalcogenides (InSe, SnS2, MoSe2) were placed at the perovskite/ETL interface in inverted perovskite solar cells to improve performance and stability.
A novel multifunctional C3-symmetric triphenylamine discotic liquid crystal: synthesis, columnar self-assembly, organogel behavior, selective detection of PA and application in Si solar cells
Authors: Liu Lu , Li Jiayang , Zhu He , Yang Hanyan , Feng Xi , Xiao Daping , Yang Yu , Gao Hongfei
Published: April 2024

A novel C3-symmetric triphenylamine discotic liquid crystal with fluorescent gel properties has important applications in detection of PA and Si hybrid solar cells.
Effects of solution processable CuI thin films with Al2O3-based sandwiched architecture for high-performance p-type transistor applications
Authors: Lee Hyun-Ah , Kim Tae In , Kwon Hyuck-In , Park Ick-Joon
Published: April 2024

The enhancement in electrical performance of the solution-processed p-type CuI TFTs is achieved by constructing the aluminum oxide-based sandwiched architecture, which can improve the crystallinity and anion vacancy states in the CuI channel layer.
Universal and Language-Specific Connected Speech Characteristics of Bilingual Speakers With Alzheimer's Disease: Insights From Case Studies of Structurally Distinct Languages
Authors: Dutta Manaswita , Mello Tina M. D. , Cheng Yesi , Dash Niladri Sekhar , Nandi Ranita , Dutt Aparna , Bose Arpita
Published: April 2024

Purpose:

Connected speech analysis has been effectively utilized for the diagnosis and disease monitoring of individuals with Alzheimer's disease (AD). Existing research has been conducted mostly in monolingual English speakers with a noticeable lack of evidence from bilinguals and non-English speakers, particularly in non-European languages. Using a case study approach, we characterized connected speech profiles of two Bengali–English bilingual speakers with AD to determine the universal features of language impairments in both languages, identify language-specific differences between the languages, and explore language impairment characteristics of the participants with AD in relation to their bilingual language experience.

Method:

Participants included two Bengali–English bilingual speakers with AD and a group of age-, gender-, education-, and language-matched neurologically healthy controls. Connected speech samples were collected in first language (L1; Bengali) and second language (L2; English) using a novel storytelling task (i.e.,
Frog, Where Are You?
). These samples were analyzed using an augmented quantitative production analysis and correct information unit analyses for productivity, fluency, syntactic and morphosyntactic features, and lexical and semantic characteristics.

Results:

Irrespective of the language, AD impacted speech productivity (speech rate and fluency) and semantic characteristics in both languages. Unique language-specific differences were noted on syntactic measures (reduced sentence length in Bengali), lexical distribution (fewer pronouns and absence of reduplication in Bengali), and inflectional properties (no difficulties with noun or verb inflections in Bengali). Among the two participants with AD, the individual who showed lower proficiency and usage in L2 (English) demonstrated reduced syntactic complexity and morphosyntactic richness in English.

Conclusions:

Evidence from these case studies suggests that language impairment features in AD are not universal across languages, particularly in comparison to impairments typically associated with language breakdowns in English. This study underscores the importance of establishing connected speech profiles in AD for non–English-speaking populations, especially for structurally different languages. This would in turn lead to the development of language-specific markers that can facilitate early detection of language deterioration and aid in improving diagnosis of AD in individuals belonging to underserved linguistically diverse populations.

Supplemental Material:

https://doi.org/10.23641/asha.25412458
Medical knowledge graph question answering for drug‐drug interaction prediction based on multi‐hop machine reading comprehension
Authors: Gao Peng , Gao Feng , Ni Jian‐Cheng , Wang Yu , Wang Fei , Zhang Qiquan
Published: April 2024

Drug‐drug interaction (DDI) prediction is a crucial issue in molecular biology. Traditional methods of observing drug‐drug interactions through medical experiments require significant resources and labour. The authors present a Medical Knowledge Graph Question Answering (MedKGQA) model, dubbed MedKGQA, that predicts DDI by employing machine reading comprehension (MRC) from closed‐domain literature and constructing a knowledge graph of “drug‐protein” triplets from open‐domain documents. The model vectorises the drug‐protein target attributes in the graph using entity embeddings and establishes directed connections between drug and protein entities based on the metabolic interaction pathways of protein targets in the human body. This aligns multiple external knowledge and applies it to learn the graph neural network. Without bells and whistles, the proposed model achieved a 4.5% improvement in terms of DDI prediction accuracy compared to previous state‐of‐the‐art models on the QAngaroo MedHop dataset. Experimental results demonstrate the efficiency and effectiveness of the model and verify the feasibility of integrating external knowledge in MRC tasks.
A universal method for solar filament detection from Hαobservations using semi-supervised deep learning
Authors: Diercke Andrea , Jarolim Robert , Kuckein Christoph , González Manrique Sergio J. , Ziener Marco , Veronig Astrid M. , Denker Carsten , Pötzi Werner , Podladchikova Tatiana , Pevtsov Alexei A.
Published: April 2024

Filaments are omnipresent features in the solar atmosphere. Their location, properties, and time evolution can provide important information about changes in solar activity and assist in the operational space weather forecast. Therefore, filaments have to be identified in full-disk images and their properties extracted from these images, but manual extraction is tedious and too time-consuming, and extraction with morphological image processing tools produces a large number of false positive detections. Automatic object detection, segmentation, and extraction in a reliable manner would allow for the processing of more data in a shorter time frame. The Chromospheric Telescope (ChroTel; Tenerife, Spain), the Global Oscillation Network Group (GONG), and the Kanzelhöhe Observatory for Solar and Environmental Research (KSO; Austria) provide regular full-disk observations of the Sun in the core of the chromospheric Hαabsorption line. In this paper, we present a deep learning method that provides reliable extractions of solar filaments from Hαfiltergrams. First, we trained the object detection algorithm YOLOv5 with labeled filament data of ChroTel Hαfiltergrams. We used the trained model to obtain bounding boxes from the full GONG archive. In a second step, we applied a semi-supervised training approach where we used the bounding boxes of filaments to train the algorithm on a pixel-wise classification of solar filaments with u-net. We made use of the increased data set size, which avoids overfitting of spurious artifacts from the generated training masks. Filaments were predicted with an accuracy of 92%. With the resulting filament segmentations, physical parameters such as the area or tilt angle could be easily determined and studied. We demonstrated this in an example where we determined the rush-to-the pole for Solar Cycle 24 from the segmented GONG images. In a last step, we applied the filament detection to Hαobservations from KSO and demonstrated the general applicability of our method to Hαfiltergrams.
Vitamin D deficiency in Scheuermann’s disease is associated with increased adverse outcomes
Authors: Chokshi Shivan N. , Mudiganty Srikanth , Clement Rutledge Carter , Accousti William
Published: April 2024

Introduction: Scheuermann’s disease is a diagnosis of hyperkyphosis commonly encountered in pediatric patients. Studies in animal models suggest an association with vitamin D deficiency, however, extensive studies have not been performed in humans. This study analyzes the role of vitamin D deficiency on unfavorable results in patients with Scheuermann’s disease. Methods: The TriNetX database was utilized to perform a retrospective analysis. Patients in the United States aged 0–18 years with Scheuermann’s disease were identified using International Classification of Diseases, Tenth Revision (ICD-10) codes and categorized into those with and without a diagnosis of vitamin D deficiency. Comparison of patient groups depending on age, sex, ethnic origin, prior diagnosis of fibromyalgia, anxiety disorder, myositis, and major depressive disorder. Statistical analysis was conducted to identify the association between vitamin D levels and unfavorable results including pain, depression, suicide attempt, emergency department (ED) consult, hospitalization, and procedures on the spine or spinal cord. Results: In total, 11,277 patients were identified, 39% of whom had a concurrent diagnosis of scoliosis. A total of 1,024 (9.08%) were deficient in vitamin D. Patients with vitamin D deficiency had greater odds of pain (P < 0.0001), depression (P < 0.0001), suicide attempt (P = 0.0021), ED visits (P = 0.0246), and hospital admission (P < 0.0015). Conversely, patients with vitamin D deficiency had decreased odds of surgery on the spine or spinal cord (P = 0.0009). Conclusion: Vitamin D deficiency is associated with an elevated risk of pain, depression, suicide attempts, ED visits, and hospitalization. Our analysis highlights the need for more research to study the effect of vitamin D on Scheuermann’s disease.

Level of evidence: Level III, Prognostic
Effect of Abstract Phonemic Complexity on Mismatch Negativity Amplitude
Authors: Najem Fadi , White-Minnis Letitia , Elangovan Saravanan , Franklin Clifford , Jamos Abdullah
Published: April 2024

Purpose Mismatch negativity (MMN) reflects a preperceptual neurophysiological response that is generated subconsciously due to the interruption of a memory trace of ongoing sensory events in the environment. It has been widely used by researchers to understand complex perceptual mechanisms. Furthermore, it has been recommended as an objective tool to investigate disorders related to auditory cognition in hearing aid and cochlear implant users. Many researchers suggest that utilizing a larger acoustic difference between standard and deviant stimuli within the oddball paradigm will lead to a more robust MMN response. The purpose of the present study is to examine if increasing the abstract phonemic contrast between standard and deviant stimuli in the oddball paradigm leads to a more robust MMN response.

Methods Fourteen young female adults participated in the present study. To ensure that the MMN response was elicited by phonemic and not acoustic differences in the stimuli, a one-to-many ratio was created for the abstract phonemic features while controlling the acoustic features when designing the oddball paradigm as described by Phillips et al. (2000). MMN amplitude was measured at the Cz and Fz electrodes in two conditions, with two trials in each condition. In condition 1, the standards and deviants differed by one distinctive feature: voicing in trial 1 (/tӕ/ was standard and /dӕ/ was deviant) and place of articulation in trial 2 (/bӕ/ was standard and /dӕ/ was deviant). In condition 2, the standards and deviants differed across two distinctive features: voicing and place of articulation. In trial 1, /pӕ/ was standard and /dӕ/ was deviant; in trial 2, /dӕ/ was standard and /pӕ/ was deviant.

Results MMN amplitudes elicited by two distinctive features were significantly larger than MMN amplitudes elicited by one distinctive feature (p < 0.001). Trials 1 and 2 in each condition showed no statistical difference, and they were repeatable and highly correlated. Recordings from the Cz and Fz electrodes showed no statistical difference and were highly correlated and similar in morphology.

Conclusion It is known in the literature that increasing acoustic complexity elicits a more robust MMN. The present study showed that this assumption can be extended to abstract phonemic complexity. Increasing the phonemic complexity by utilizing more distinctive features in the oddball paradigm increased the amplitude and robustness of the MMN.