bluuebunny/crossref_metadata_2025_split huggingface dataset:
Promoting multiexciton interactions in singlet fission and triplet fusion upconversion dendrimers
Authors: He Guiying , Churchill Emily M. , Parenti Kaia R. , Zhang Jocelyn , Narayanan Pournima , Namata Faridah , Malkoch Michael , Congreve Daniel N. , Cacciuto Angelo , Sfeir Matthew Y. , Campos Luis M. 
Published: September 2023

AbstractSinglet fission and triplet-triplet annihilation upconversion are two multiexciton processes intimately related to the dynamic interaction between one high-lying energy singlet and two low-lying energy triplet excitons. Here, we introduce a series of dendritic macromolecules that serve as platform to study the effect of interchromophore interactions on the dynamics of multiexciton generation and decay as a function of dendrimer generation. The dendrimers (generations 1–4) consist of trimethylolpropane core and 2,2-bis(methylol)propionic acid (bis-MPA) dendrons that provide exponential growth of the branches, leading to a corona decorated with pentacenes for SF or anthracenes for TTA-UC. The findings reveal a trend where a few highly ordered sites emerge as the dendrimer generation grows, dominating the multiexciton dynamics, as deduced from optical spectra, and transient absorption spectroscopy. While the dendritic structures enhance TTA-UC at low annihilator concentrations in the largest dendrimers, the paired chromophore interactions induce a broadened and red-shifted excimer emission. In SF dendrimers of higher generations, the triplet dynamics become increasingly dominated by pairwise sites exhibiting strong coupling (Type II), which can be readily distinguished from sites with weaker coupling (Type I) by their spectral dynamics and decay kinetics.
Metabolic crosstalk between skeletal muscle cells and liver through IRF4-FSTL1 in nonalcoholic steatohepatitis
Authors: Guo Shanshan , Feng Yonghao , Zhu Xiaopeng , Zhang Xinyi , Wang Hui , Wang Ruwen , Zhang Qiongyue , Li Yiming , Ren Yan , Gao Xin , Bian Hua , Liu Tiemin , Gao Huanqing , Kong Xingxing 
Published: September 2023

AbstractInter-organ crosstalk has gained increasing attention in recent times; however, the underlying mechanisms remain unclear. In this study, we elucidate an endocrine pathway that is regulated by skeletal muscle interferon regulatory factor (IRF) 4, which manipulates liver pathology. Skeletal muscle specific IRF4 knockout (F4MKO) mice exhibited ameliorated hepatic steatosis, inflammation, and fibrosis, without changes in body weight, when put on a nonalcoholic steatohepatitis (NASH) diet. Proteomics analysis results suggested that follistatin-like protein 1 (FSTL1) may constitute a link between muscles and the liver. Dual luciferase assays showed that IRF4 can transcriptionally regulate FSTL1. Further, inducing FSTL1 expression in the muscles of F4MKO mice is sufficient to restore liver pathology. In addition, co-culture experiments confirmed that FSTL1 plays a distinct role in various liver cell types via different receptors. Finally, we observed that the serum FSTL1 level is positively correlated with NASH progression in humans. These data indicate a signaling pathway involving IRF4-FSTL1-DIP2A/CD14, that links skeletal muscle cells to the liver in the pathogenesis of NASH.
Cloning of the wheat leaf rust resistance gene Lr47 introgressed from Aegilops speltoides
Authors: Li Hongna , Hua Lei , Zhao Shuqing , Hao Ming , Song Rui , Pang Shuyong , Liu Yanna , Chen Hong , Zhang Wenjun , Shen Tao , Gou Jin-Ying , Mao Hailiang , Wang Guiping , Hao Xiaohua , Li Jian , Song Baoxing , Lan Caixia , Li Zaifeng , Deng Xing Wang , Dubcovsky Jorge , Wang Xiaodong , Chen Shisheng 
Published: September 2023

AbstractLeaf rust, caused by Puccinia triticina Eriksson (Pt), is one of the most severe foliar diseases of wheat. Breeding for leaf rust resistance is a practical and sustainable method to control this devastating disease. Here, we report the identification of Lr47, a broadly effective leaf rust resistance gene introgressed into wheat from Aegilops speltoides. Lr47 encodes a coiled-coil nucleotide-binding leucine-rich repeat protein that is both necessary and sufficient to confer Pt resistance, as demonstrated by loss-of-function mutations and transgenic complementation. Lr47 introgression lines with no or reduced linkage drag are generated using the Pairing homoeologous1 mutation, and a diagnostic molecular marker for Lr47 is developed. The coiled-coil domain of the Lr47 protein is unable to induce cell death, nor does it have self-protein interaction. The cloning of Lr47 expands the number of leaf rust resistance genes that can be incorporated into multigene transgenic cassettes to control this devastating disease.
A virus-like particle-based bivalent PCSK9 vaccine lowers LDL-cholesterol levels in non-human primates
Authors: Fowler Alexandra , Van Rompay Koen K. A. , Sampson Maureen , Leo Javier , Watanabe Jennifer K. , Usachenko Jodie L. , Immareddy Ramya , Lovato Debbie M. , Schiller John T. , Remaley Alan T. , Chackerian Bryce 
Published: September 2023

AbstractElevated low-density lipoprotein cholesterol (LDL-C) is an important risk factor in the development of atherosclerotic cardiovascular disease (ASCVD). Inhibitors of proprotein convertase subtilisin/kexin type 9 (PCSK9), a negative regulator of LDL-C metabolism, have emerged as promising approaches for reducing elevated LDL-C levels. Here, we evaluated the cholesterol-lowering efficacy of virus-like particle (VLP) based vaccines that target epitopes found within the LDL receptor (LDL-R) binding domain of PCSK9. In both mice and non-human primates, a bivalent VLP vaccine targeting two distinct epitopes on PCSK9 elicited strong and durable antibody responses and lowered cholesterol levels. In macaques, a VLP vaccine targeting a single PCSK9 epitope was only effective at lowering LDL-C levels in combination with statins, whereas immunization with the bivalent vaccine lowered LDL-C without requiring statin co-administration. These data highlight the efficacy of an alternative, vaccine-based approach for lowering LDL-C.
In-ear integrated sensor array for the continuous monitoring of brain activity and of lactate in sweat
Authors: Xu Yuchen , De la Paz Ernesto , Paul Akshay , Mahato Kuldeep , Sempionatto Juliane R. , Tostado Nicholas , Lee Min , Hota Gopabandhu , Lin Muyang , Uppal Abhinav , Chen William , Dua Srishty , Yin Lu , Wuerstle Brian L. , Deiss Stephen , Mercier Patrick , Xu Sheng , Wang Joseph , Cauwenberghs Gert 
Published: September 2023

AbstractOwing to the proximity of the ear canal to the central nervous system, in-ear electrophysiological systems can be used to unobtrusively monitor brain states. Here, by taking advantage of the ear’s exocrine sweat glands, we describe an in-ear integrated array of electrochemical and electrophysiological sensors placed on a flexible substrate surrounding a user-generic earphone for the simultaneous monitoring of lactate concentration and brain states via electroencephalography, electrooculography and electrodermal activity. In volunteers performing an acute bout of exercise, the device detected elevated lactate levels in sweat concurrently with the modulation of brain activity across all electroencephalography frequency bands. Simultaneous and continuous unobtrusive in-ear monitoring of metabolic biomarkers and brain electrophysiology may allow for the discovery of dynamic and synergetic interactions between brain and body biomarkers in real-world settings for long-term health monitoring or for the detection or monitoring of neurodegenerative diseases.
Systematic analysis of drug combinations against Gram-positive bacteria
Authors: Cacace Elisabetta , Kim Vladislav , Varik Vallo , Knopp Michael , Tietgen Manuela , Brauer-Nikonow Amber , Inecik Kemal , Mateus André , Milanese Alessio , Mårli Marita Torrissen , Mitosch Karin , Selkrig Joel , Brochado Ana Rita , Kuipers Oscar P. , Kjos Morten , Zeller Georg , Savitski Mikhail M. , Göttig Stephan , Huber Wolfgang , Typas Athanasios 
Published: September 2023

AbstractDrug combinations can expand options for antibacterial therapies but have not been systematically tested in Gram-positive species. We profiled ~8,000 combinations of 65 antibacterial drugs against the model species Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Thereby, we recapitulated previously known drug interactions, but also identified ten times more novel interactions in the pathogen S. aureus, including 150 synergies. We showed that two synergies were equally effective against multidrug-resistant S. aureus clinical isolates in vitro and in vivo. Interactions were largely species-specific and synergies were distinct from those of Gram-negative species, owing to cell surface and drug uptake differences. We also tested 2,728 combinations of 44 commonly prescribed non-antibiotic drugs with 62 drugs with antibacterial activity against S. aureus and identified numerous antagonisms that might compromise the efficacy of antimicrobial therapies. We identified even more synergies and showed that the anti-aggregant ticagrelor synergized with cationic antibiotics by modifying the surface charge of S. aureus. All data can be browsed in an interactive interface (https://apps.embl.de/combact/).
The Chinese thermal comfort dataset
Authors: Yang Liu , Zhao Shengkai , Zhai Yongchao , Gao Siru , Wang Feixiang , Lian Zhiwei , Duanmu Lin , Zhang Yufeng , Zhou Xiang , Cao Bin , Wang Zhaojun , Yan Haiyan , Zhang Hui , Arens Edward , de Dear Richard 
Published: September 2023

AbstractHeating and cooling in buildings accounts for over 20% of total energy consumption in China. Therefore, it is essential to understand the thermal requirements of building occupants when establishing building energy codes that would save energy while maintaining occupants’ thermal comfort. This paper introduces the Chinese thermal comfort dataset, established by seven participating institutions under the leadership of Xi’an University of Architecture and Technology. The dataset comprises 41,977 sets of data collected from 49 cities across five climate zones in China over the past two decades. The raw data underwent careful quality control procedure, including systematic organization, to ensure its reliability. Each dataset contains environmental parameters, occupants’ subjective responses, building information, and personal information. The dataset has been instrumental in the development of indoor thermal environment evaluation standards and energy codes in China. It can also have broader applications, such as contributing to the international thermal comfort dataset, modeling thermal comfort and adaptive behaviors, investigating regional differences in indoor thermal conditions, and examining occupants’ thermal comfort responses.
Green armoured tardigrades (Echiniscidae: Viridiscus), including a new species from the Southern Nearctic, exemplify problems with tardigrade variability research
Authors: Momeni Sogol , Gąsiorek Piotr , Loeffelholz Jacob , Chtarbanova Stanislava , Nelson Diane R. , Fletcher Rebecca Adkins , Michalczyk Łukasz , Pienaar Jason 
Published: September 2023

AbstractRanges of tardigrade intraspecific and interspecific variability are not precisely defined, both in terms of morphology and genetics, rendering descriptions of new taxa a cumbersome task. This contribution enhances the morphological and molecular dataset available for the heterotardigrade genus Viridiscus by supplying new information on Southern Nearctic populations of V.perviridis, V.viridianus, and a new species from Tennessee. We demonstrate that, putting aside already well-documented cases of significant variability in chaetotaxy, the dorsal plate sculpturing and other useful diagnostic characters, such as morphology of clavae and pedal platelets, may also be more phenotypically plastic characters at the species level than previously assumed. As a result of our integrative analyses, V.viridianus is redescribed, V.celatus sp. nov. described, and V.clavispinosus designated as nomeninquirendum, and its junior synonymy with regard to V.viridianus suggested. Morphs of three Viridiscus species (V.perviridis, V.viridianus, and V.viridissimus) are depicted, and the implications for general echiniscid taxonomy are drawn. We emphasise that taxonomic conclusions reached solely through morphological or molecular analyses lead to a distorted view on tardigrade α-diversity.
Low-density polyethylene microplastics alter chemical properties and microbial communities in agricultural soil
Authors: Palansooriya Kumuduni Niroshika , Sang Mee Kyung , El-Naggar Ali , Shi Liang , Chang Scott X. , Sung Jwakyung , Zhang Wei , Ok Yong Sik 
Published: September 2023

AbstractMicroplastic (MP) pollution in agricultural soils, resulting from the use of plastic mulch, compost, and sewage sludge, jeopardizes the soil microbial populations. However, the effects of MPs on soil chemical properties and microbial communities remain largely unknown. Here, we investigated the effects of different concentration levels (0, 0.1, 1, 3, 5, and 7%; w:w) of low-density polyethylene (LDPE) MPs on the chemical properties and bacterial communities of agricultural soil in an incubation study. The addition of LDPE MPs did not drastically change soil pH (ranging from 8.22 to 8.42). Electrical conductivity increased significantly when the LDPE MP concentrations were between 1 and 7%, whereas the total exchangeable cations (Na+, K+, Mg2+, and Ca2+) decreased significantly at higher LDPE MP concentrations (3–7%). The highest available phosphorus content (2.13 mg kg−1) was observed in 0.1% LDPE MP. Bacterial richness (Chao1 and Ace indices) was the lowest at 0.1% LDPE MP, and diversity indices (Shannon and Invsimpson) were higher at 0 and 1% LDPE MP than at other concentrations. The effect of LDPE MP concentrations on bacterial phyla remained unchanged, but the bacterial abundance varied. The relative abundance of Proteobacteria (25.8–33.0%) was the highest in all treatments. The abundance of Acidobacteria (15.8–17.2%) was also high, particularly in the 0, 0.1, and 1% LDPE MPs. With the increase in LDPE MP concentration, the abundance of Actinobacteria gradually increased from 7.80 to 31.8%. Our findings suggest that different MP concentration levels considerably alter soil chemical properties and microbial composition, which may potentially change the ecological functions of soil ecosystems.
Computer aided progression detection model based on optimized deep LSTM ensemble model and the fusion of multivariate time series data
Authors: Saleh Hager , Amer Eslam , Abuhmed Tamer , Ali Amjad , Al-Fuqaha Ala , El-Sappagh Shaker 
Published: September 2023

AbstractAlzheimer’s disease (AD) is the most common form of dementia. Early and accurate detection of AD is crucial to plan for disease modifying therapies that could prevent or delay the conversion to sever stages of the disease. As a chronic disease, patient’s multivariate time series data including neuroimaging, genetics, cognitive scores, and neuropsychological battery provides a complete profile about patient’s status. This data has been used to build machine learning and deep learning (DL) models for the early detection of the disease. However, these models still have limited performance and are not stable enough to be trusted in real medical settings. Literature shows that DL models outperform classical machine learning models, but ensemble learning has proven to achieve better results than standalone models. This study proposes a novel deep stacking framework which combines multiple DL models to accurately predict AD at an early stage. The study uses long short-term memory (LSTM) models as base models over patient’s multivariate time series data to learn the deep longitudinal features. Each base LSTM classifier has been optimized using the Bayesian optimizer using different feature sets. As a result, the final optimized ensembled model employed heterogeneous base models that are trained on heterogeneous data. The performance of the resulting ensemble model has been explored using a cohort of 685 patients from the University of Washington's National Alzheimer’s Coordinating Center dataset. Compared to the classical machine learning models and base LSTM classifiers, the proposed ensemble model achieves the highest testing results (i.e., 82.02, 82.25, 82.02, and 82.12 for accuracy, precision, recall, and F1-score, respectively). The resulting model enhances the performance of the state-of-the-art literature, and it could be used to build an accurate clinical decision support tool that can assist domain experts for AD progression detection.
Superconductivity in high-entropy alloy system containing Th
Authors: Sobota Piotr , Topolnicki Rafał , Ossowski Tomasz , Pikula Tomasz , Gnida Daniel , Idczak Rafał , Pikul Adam 
Published: September 2023

AbstractTh-containing superconducting high entropy system with the nominal composition (NbTa)$$_{0.67}$$

0.67

(MoWTh)$$_{0.33}$$

0.33

was synthesized. Its structural and physical properties were investigated by X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, specific heat, resistivity and magnetic measurements. Two main phases of alloy were observed: major bcc structure and minor fcc. The experimental results were supported by numerical simulation by the DFT Korringa-Kohn-Rostoker method with the coherent potential approximation (KKR-CPA).
MicroRNAs in Parkinson’s disease: a systematic review and diagnostic accuracy meta-analysis
Authors: Guévremont Diane , Roy Joyeeta , Cutfield Nicholas J. , Williams Joanna M. 
Published: September 2023

AbstractCurrent clinical tests for Parkinson’s disease (PD) provide insufficient diagnostic accuracy leading to an urgent need for improved diagnostic biomarkers. As microRNAs (miRNAs) are promising biomarkers of various diseases, including PD, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of biofluid miRNAs in PD. All studies reporting data on miRNAs expression in PD patients compared to controls were included. Gene targets and significant pathways associated with miRNAs expressed in more than 3 biofluid studies with the same direction of change were analyzed using target prediction and enrichment analysis. A bivariate model was used to calculate sensitivity, specificity, likelihood ratios, and diagnostic odds ratio. While miR-24-3p and miR-214-3p were the most reported miRNA (7 each), miR-331-5p was found to be consistently up regulated in 4 different biofluids. Importantly, miR-19b-3p, miR-24-3p, miR-146a-5p, and miR-221-3p were reported in multiple studies without conflicting directions of change in serum and bioinformatic analysis found the targets of these miRNAs to be associated with pathways important in PD pathology. Of the 102 studies from the systematic review, 15 studies reported sensitivity and specificity data on combinations of miRNAs and were pooled for meta-analysis. Studies (17) reporting sensitivity and specificity data on single microRNA were pooled in a separate meta-analysis. Meta-analysis of the combinations of miRNAs (15 studies) showed that biofluid miRNAs can discriminate between PD patients and controls with good diagnostic accuracy (sensitivity = 0.82, 95% CI 0.76–0.87; specificity = 0.80, 95% CI 0.74–0.84; AUC = 0.87, 95% CI 0.83–0.89). However, we found multiple studies included more males with PD than any other group therefore possibly introducing a sex-related selection bias. Overall, our study captures key miRNAs which may represent a point of focus for future studies and the development of diagnostic panels whilst also highlighting the importance of appropriate study design to develop representative biomarker panels for the diagnosis of PD.
Ex vivo study of molecular changes of stained teeth following hydrogen peroxide and peroxymonosulfate treatments
Authors: P. Gomes Paulo Wender , Zuffa Simone , Bauermeister Anelize , Caraballo-Rodríguez Andrés Mauricio , Zhao Haoqi Nina , Mannochio-Russo Helena , Dogo-isonagie Cajetan , Patel Om , Pimenta Paloma , Gronlund Jennifer , Lavender Stacey , Pilch Shira , Maloney Venda , North Michael , Dorrestein Pieter C. 
Published: September 2023

AbstractWhite teeth can give confidence and tend to be associated with a healthier lifestyle in modern society. Therefore, tooth-bleaching strategies have been developed, including the use of hydrogen peroxide. Recently, peroxymonosulfate has been introduced as an alternative bleaching method to hydrogen peroxide. Although both chemicals are oxidizing agents, their effects on the molecular composition of the stained teeth are yet unknown. In this study, the molecular profiles of teeth bleached with hydrogen peroxide and peroxymonosulfate were compared using Liquid Chromatography-Tandem Mass Spectrometry. Statistical analyses were used to assess the samples. In addition, reference spectral libraries and in silico tools were used to perform metabolite annotation. Overall, principal component analysis showed a strong separation between control and hydrogen peroxide and peroxymonosulfate samples (p < 0.001). The analysis of molecular changes revealed amino acids and dipeptides in stained teeth samples after hydrogen peroxide and peroxymonosulfate treatments. Noteworthy, the two bleaching methods led to distinct molecular profiles. For example, diterpenoids were more prevalent after peroxymonosulfate treatment, while a greater abundance of alkaloids was detected after hydrogen peroxide treatment. Whereas non-bleached samples (controls) showed mainly lipids. Therefore, this study shows how two different tooth-whitening peroxides could affect the molecular profiles of human teeth.
Reproducibility in pharmacometrics applied in a phase III trial of BCG-vaccination for COVID-19
Authors: van Wijk Rob C. , Mockeliunas Laurynas , van den Hoogen Gerben , Upton Caryn M. , Diacon Andreas H. , Simonsson Ulrika S. H. 
Published: September 2023

AbstractLarge clinical trials often generate complex and large datasets which need to be presented frequently throughout the trial for interim analysis or to inform a data safety monitory board (DSMB). In addition, reliable and traceability are required to ensure reproducibility in pharmacometric data analysis. A reproducible pharmacometric analysis workflow was developed during a large clinical trial involving 1000 participants over one year testing Bacillus Calmette-Guérin (BCG) (re)vaccination in coronavirus disease 2019 (COVID-19) morbidity and mortality in frontline health care workers. The workflow was designed to review data iteratively during the trial, compile frequent reports to the DSMB, and prepare for rapid pharmacometric analysis. Clinical trial datasets (n = 41) were transferred iteratively throughout the trial for review. An RMarkdown based pharmacometric processing script was written to automatically generate reports for evaluation by the DSMB. Reports were compiled, reviewed, and sent to the DSMB on average three days after the data cut-off, reflecting the trial progress in real-time. The script was also utilized to prepare for the trial pharmacometric analyses. The same source data was used to create analysis datasets in NONMEM format and to support model script development. The primary endpoint analysis was completed three days after data lock and unblinding, and the secondary endpoint analyses two weeks later. The constructive collaboration between clinical, data management, and pharmacometric teams enabled this efficient, timely, and reproducible pharmacometrics workflow.