bluuebunny/crossref_metadata_2025 huggingface dataset:
YTHDF1 boosts the lactate accumulation to potentiate cervical cancer cells immune escape
Authors: Xiong Jing , He Ling , Chai Xiaoshan , Zhang Yongjing , Sun Shujuan
Published: November 2024

Lactate is a major metabolic product of tumor cells in microenvironment. Increasing evidence has indicated that lactate accumulation could alter the immune response in human cancers, including cervical cancer. However, the function and significance of N6-methyladenosine (m6A) reader YTHDF1 in cervical cancer cells’ lactate metabolism and immunotherapy remain obscure. Results illustrated that YTHDF1 predicted unfavorable clinical outcomes of cervical cancer, which was negatively correlated with CD8+ T cell infiltration. In the co-culture of tumor cells with CD8+ T cells, YTHDF1 overexpression promoted the lactate accumulation and attenuated the cytotoxic CD8+ T cell’s killing effect. Correspondingly, YTHDF1 knockdown exerted the opposite effects. Mechanistically, YTHDF1 targeted the m6A site on SLC16A1 gene (MCT1) to determine its fate. YTHDF1 upregulated MCT1 expression by enhancing MCT1 stability mediated by m6A-modified manner. Collectively, our results revealed an oncogenic role played by YTHDF1 in cervical cancer through m6A/MCT1-dependent manner. In conclusion, these findings unveil the immune escape-promoting effect of YTHDF1 in cervical cancer by boosting the lactate accumulation, which might illuminate a novel target for more precise immunotherapy.
New insights into crosstalk between Nrf2 pathway and ferroptosis in lung disease
Authors: Chen Yonghu , Jiang Zhe , Li Xuezheng
Published: November 2024

Ferroptosis is a distinctive process of cellular demise that is linked to amino acid metabolism, lipid oxidation, and iron oxidation. The ferroptosis cascade genes, which are closely associated with the onset of lung diseases, are among the regulatory targets of nuclear factor erythroid 2-related factor 2 (Nrf2). Although the regulation of ferroptosis is mostly mediated by Nrf2, the precise roles and underlying regulatory mechanisms of ferroptosis and Nrf2 in lung illness remain unclear. This review provides new insights from recent discoveries involving the modulation of Nrf2 and ferroptosis in a range of lung diseases. It also systematically describes regulatory mechanisms involving lipid peroxidation, intracellular antioxidant levels, ubiquitination of Nrf2, and expression of FSP1 and GPX4. Finally, it summarises active ingredients and drugs with potential for the treatment of lung diseases. With the overarching aim of expediting improvements in treatment, this review provides a reference for novel therapeutic mechanisms and offers suggestions for the development of new medications for a variety of lung disorders.
Artificial intelligence in assessing progression of age-related macular degeneration
Authors: Frank-Publig Sophie , Birner Klaudia , Riedl Sophie , Reiter Gregor S. , Schmidt-Erfurth Ursula
Published: November 2024

The human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising patient numbers accompanied by ongoing developments of therapeutic approaches. Concurrent advances in imaging modalities provide eye care professionals with a large amount of data for each patient. Furthermore, with continuous progress in therapeutics, there is an unmet need for reliable structural and functional biomarkers in clinical trials and practice to optimize personalized patient care and evaluate individual responses to treatment. A fast and objective solution is Artificial intelligence (AI), which has revolutionized assessment of AMD in all disease stages. Reliable and validated AI-algorithms can aid to overcome the growing number of patients, visits and necessary treatments as well as maximize the benefits of multimodal imaging in clinical trials. Therefore, there are ongoing efforts to develop and validate automated algorithms to unlock more information from datasets allowing automated assessment of disease activity and disease progression. This review aims to present selected AI algorithms, their development, applications and challenges regarding assessment and prediction of AMD progression.
Rational strategies for improving the efficiency of design and discovery of nanomedicines
Authors: Shan Xiaoting , Cai Ying , Zhu Binyu , Zhou Lingli , Sun Xujie , Xu Xiaoxuan , Yin Qi , Wang Dangge , Li Yaping
Published: November 2024

The rise of rational strategies in nanomedicine development, such as high-throughput methods and computer-aided techniques, has led to a shift in the design and discovery patterns of nanomedicines from a trial-and-error mode to a rational mode. This transition facilitates the enhancement of efficiency in the preclinical discovery pipeline of nanomaterials, particularly in improving the hit rate of nanomaterials and the optimization efficiency of promising candidates. Herein, we describe a directed evolution mode of nanomedicines driven by data to accelerate the discovery of nanomaterials with high delivery efficiency. Computer-aided design strategies are introduced in detail as one of the cutting-edge directions for the development of nanomedicines. Ultimately, we look forward to expanding the tools for the rational design and discovery of nanomaterials using multidisciplinary approaches. Rational design strategies may potentially boost the delivery efficiency of next-generation nanomedicines.
An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022
Authors: Pham Vu-Dong , de Waard Farina , Thiel Fabian , Bobertz Bernd , Hellmann Christina , Nguyen Duc-Viet , Beer Felix , Arasumani M. , Schwieder Marcel , Hartleib Jörg , Frantz David , van der Linden Sebastian
Published: November 2024

We present detailed annual land cover maps for the Baltic Sea region, spanning more than two decades (2000–2022). The maps provide information on eighteen land cover (LC) classes, including eight general LC types, eight major crop types and grassland, and two peat bog-related classes. Our maps represent the first homogenized annual dataset for the region and address gaps in current land use and land cover products, such as a lack of detail on crop sequences and peat bog exploitation. To create the maps, we used annual multi-temporal remote sensing data combined with a data encoding structure and deep learning classification. We obtained the training data from publicly available open datasets. The maps were validated using independent field survey data from the Land Use/Cover Area Frame Survey (LUCAS) and expert annotations from high-resolution imagery. The quantitative and qualitative results of the maps provide a reliable data source for monitoring agricultural transformations, peat bog exploitation, and restoration activities in the Baltic Sea region and its surrounding countries.
Expanding the genotypic and phenotypic spectrum of Egyptian children with maple syrup urine disease
Authors: Abdelkhalek Zeinab S. , Hussein Shadia M. , Mahmoud Iman G. , Ramadan Areef , Kamel Mona A. , Girgis Marian Y. , Elmonem Mohamed A.
Published: November 2024

Maple Syrup Urine Disease (MSUD, OMIM# 248600) is an autosomal recessive inborn error of metabolism characterized by elevated branched chain amino acids (BCAA) leucine/isoleucine and valine in blood of affected children. The phenotypic and genotypic spectrum of MSUD is largely unreported in Egypt. We recruited ten patients (4 males/6 females, 2weeks-12years) from nine unrelated families with clinical and biochemical evidence of MSUD. We performed Sanger sequencing for the three most-commonly responsible genes: BCKDHA, BCKDHB and DBT and conducted exome sequencing for unresolved cases. Through Sanger sequencing, we detected eight homozygous pathogenic/likely pathogenic variants (four in BCKDHB, three in BCKDHA and one in DBT gene) in eight different families. The proband of family VI, who had no significant genetic findings by Sanger, had a peculiar phenotype and atypical radiological findings. His exome sequencing revealed a previously reported homozygous likely pathogenic variant in the RARS2 gene (NM_020320.5:c.1026G > A;p.(Met342Ile)) causing the mitochondrial-encephalopathy disorder pontocerebellar hypoplasia, type 6 (OMIM# 611523). Furthermore, the copy-number-variant analysis of the exome data revealed a biallelic duplication affecting exons 2–6 of the BCKDHB gene (GRCh38: Chr.6-g.80127496:80171441dup) evaluated as variant of uncertain significance but expected to cause a breakpoint and may disrupt gene function, which can explain the markedly elevated BCAA levels in the patient’s blood. In conclusion, we expanded the genotypic and phenotypic spectrum of the disease and showed that aggressive intervention with specific treatment in the first few days of life resulted in normal development even in a developing country setting. Inclusion of MSUD in the national newborn screening program in Egypt is highly recommended.
Association between periodontitis and cardiometabolic index (CMI): a study from NHANES 2009–2014
Authors: Shuning Li , Zhiyong Zhang , Wei Yang , Jilun Liu , Xuhui Fan
Published: November 2024

Cardiometabolic index (CMI) is a novel anthropometric metric that integrates lipid and adiposity characteristics. The correlation between periodontitis development and CMI is ambiguous. The objective of this study was to establish the association between CMI and periodontitis by analyzing data from the NHANES (National Health and Nutrition Examination Survey) database. A cross-sectional study was conducted on a cohort of 6188 people selected from the NHANES database, covering the period from 2009 to 2014. The study employed multivariate logistic regression to examine the independent correlation between CMI and periodontitis. Subgroup data were analyzed and interaction tests were conducted to assess the impact of variables on the correlation between CMI and periodontitis. The CMI index was significantly and positively associated with the presence of periodontitis (β = 0.03, 95%CI(0.01, 0.05), p = 0.0092). In addition, a U-shaped relationship was found between CMI index and periodontitis severity in an older American population (65 < = age < = 80, with a folding point of 1.44, p = 0.008). This study demonstrates a significant correlation between CMI and periodontitis, positioning CMI as a crucial indicator for assessing periodontal health. Future efforts should prioritize oral hygiene interventions for patients with elevated CMI levels to facilitate early intervention and enhance overall health outcomes.
Genetic diversity of Anadara tuberculosa in two localities of the Colombian Pacific Coast
Authors: Fuentes Luis , Guevara-Suarez Marcela , Zambrano María Mercedes , Jiménez Pedro , Duitama Jorge , Restrepo Silvia
Published: November 2024

Piangua, Anadara tuberculosa, is an economically important mollusk for the human population living on the Colombian Pacific Coast. In the last years, the demand and exploitation of this mollusk have increased, putting it at risk to the point of being endangered. This research aimed to identify the genetic diversity and population structure of piangua in two localities on the Pacific Coast of Colombia. We assembled a chromosome-level genome using PacBio-Hifi and Arima sequencing. We obtained 274 scaffolds with an N50 of 45.42 Mbp, a total size of 953 Mbp, and a completeness of 91% based on BUSCO scores. The transposable elements accounted for 30.29% of the genome, and 24,317 genes were annotated. Genome-guided variant calling for 89 samples using DArT sequencing data delivered 4,825 bi-allelic SNPs, which supported genetic diversity and population structure analyses. Data showed that the piangua populations in the two localities were under expansion events more than 100k years ago. However, results also showed a reduction in genetic diversity, as evidenced by the loss of heterozygosity, which may be caused by high levels of inbreeding, probably due to a recent overexploitation. Furthermore, although we evidenced gene flow between the two localities, there is also a subtle geographical population structure between the two localities and among mangroves in one of the localities. This is the first study in Colombia that provides relevant genetic information on piangua to lay the foundations for conservation strategies.
Increased cell killing effect in neutron capture enhanced proton beam therapy
Authors: Shiba Shintaro , Shimo Takahiro , Yamanaka Masashi , Yagihashi Takayuki , Sakai Makoto , Ohno Tatsuya , Tokuuye Koichi , Omura Motoko
Published: November 2024

Thermal neutrons generated in the body during proton beam therapy (PBT) can be used to cause boron neutron capture reactions and have recently been proposed as neutron capture enhanced PBT (NCEPBT). However, the cell killing effect of NCEPBT remains underexplored. Here, we show an increase in the cell killing effect of NCEPBT. Using Monte Carlo simulations, we showed that neutrons generated by proton beam irradiation are uniformly spread on tissue culture plates. Human salivary gland tumor cell line (HSG), human osteosarcoma cell line (MG63), human tongue squamous cell carcinoma cell line (SAS), and human malignant melanoma cell line (G-361) were irradiated with X-rays, proton beams, and proton beams with 10B-enriched boronophenylalanine (boron concentration of 20 and 80 ppm). The relative biological effectiveness (RBE) values of proton beams alone, proton beams with 20 ppm boron, and proton beams with 80 ppm boron for HSG, MG63, SAS, and G-361 were 1.02, 1.07, and 1.23; 1.01, 1.08, and 1.44; 1.05, 1.09, and 1.46; and 1.04, 1.13, and 1.63, respectively. NCEPBT with high boron concentration showed high RBE and a high sensitizing effect. Our results confirm an increase in the cell killing effect of NCEPBT, should aid in its clinical use, and warrant its further investigation.
An adaptive multi-graph neural network with multimodal feature fusion learning for MDD detection
Authors: Xing Tao , Dou Yutao , Chen Xianliang , Zhou Jiansong , Xie Xiaolan , Peng Shaoliang
Published: November 2024

Major Depressive Disorder (MDD) is an affective disorder that can lead to persistent sadness and a decline in the quality of life, increasing the risk of suicide. Utilizing multimodal data such as electroencephalograms and patient interview audios can facilitate the timely detection of MDD. However, existing depression detection methods either consider only a single modality or do not fully account for the differences and similarities between modalities in multimodal approaches, potentially overlooking the latent information inherent in various modal data. To address these challenges, we propose EMO-GCN, a multimodal depression detection method based on an adaptive multi-graph neural network. By employing graph-based methods to model data from various modalities and extracting features from them, the potential correlations between modalities are uncovered. The model’s performance on the MODMA dataset is outstanding, achieving an accuracy (ACC) of 96.30%. Ablation studies further confirm the effectiveness of the model’s individual components.The experimental results of EMO-GCN demonstrate the application prospects of graph-based multimodal analysis in the field of mental health, offering new perspectives for future research.
Optimal placement of renewable distributed generators and electric vehicles using multi-population evolution whale optimization algorithm
Authors: Zangmo Rinchen , Sudabattula Suresh Kumar , Mishra Sachin , Dharavat Nagaraju , Golla Naresh Kumar , Sharma Naveen Kumar , Jadoun Vinay Kumar
Published: November 2024

This research takes on a crucial task- exploring the optimal placement of Renewable Distributed Generators such as Solar Photovoltaic, wind turbines and Electric Vehicles into the Radial Distribution System (RDS). This is a strategic move aimed at minimising power loss (PLoss) and improving the voltage profile and stability index. The RDGs are integrated into RDS with and without considering the uncertainty of the different load demands for 24 h. The probability function of Beta and Weibull distribution functions are employed to attain the solar irradiance and wind speed in a particular region. In addition, EVs are also integrated into RDS, employing meta-heuristic algorithms intended to reduce power loss (PLoss) and improve the voltage profile. The study uses an Indian 28-bus test system mimicking a balanced radial distribution network to integrate distributed generators (DGs) and EV charging stations. The simulated results demonstrate that integrating DGs into power systems has offered considerable benefits, including reduced PLoss, heightened efficiency, decreased dependency on centralised generation, and improved environmental sustainability. It is discovered that the Multi-population Evolution Whale Optimization Algorithm (MEWOA) produces better results than other methods in the literature and is valuable and practical for handling these nonlinear optimisation situations.
A cross-tissue transcriptome-wide association study reveals GRK4 as a novel susceptibility gene for COPD
Authors: Chen Guanglei , Jin Yaxian , Chu Cancan , Zheng Yuhao , Yang Changfu , Chen Yunzhi , Zhu Xing
Published: November 2024

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disorder with environmental factors being the primary risk determinants. However, genetic factors also substantially contribute to the susceptibility and progression of COPD. Although genome-wide association studies (GWAS) have identified several loci associated with COPD susceptibility, the specific pathogenic genes underlying these loci, along with their biological functions and roles within regulatory networks, remain unclear. This lack of clarity constrains our ability to achieve a deeper understanding of the genetic basis of COPD. This study leveraged the FinnGen R11 genetic dataset, comprising 21,617 cases and 372,627 controls, along with GTEx V8 eQTLs data to conduct a cross-tissue transcriptome-wide association study (TWAS). Initially, we performed a cross-tissue TWAS analysis using the Unified Test for Molecular Signatures (UTMOST), followed by validation of the UTMOST findings in single tissues using the Functional Summary-based Imputation (FUSION) method and conditional and joint (COJO) analyses of the identified genes. Subsequently, candidate susceptibility genes were screened using Multi-marker Analysis of Genomic Annotation (MAGMA). The causal relationship between these candidate genes and COPD was further evaluated through summary data-based Mendelian randomization (SMR), colocalization analysis, and Mendelian randomization (MR). Additionally, the identified results were validated against the COPD dataset in the GWAS Catalog (GCST90399694). GeneMANIA was employed to further explore the functional significance of these susceptibility genes. In the cross-tissue TWAS analysis (UTMOST), we identified 17 susceptibility genes associated with COPD. Among these, a novel susceptibility gene, G protein-coupled receptor kinase 4 (GRK4), was validated through single-tissue TWAS (FUSION) and MAGMA analyses, with further confirmation via SMR, MR, and colocalization analyses. Moreover, GRK4 was validated in an independent dataset. This study identifies GRK4 as a potential novel susceptibility gene for COPD, which may influence disease risk by exacerbating inflammatory responses. The findings address gaps in previous single-tissue GWAS studies, revealing consistent expression and potential function of GRK4 across different tissues. However, considering the study’s limitations, further investigation and validation of GRK4’s role in COPD are warranted.
Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases
Authors: Singh Ravnoor , Kaur Satinder , Singh Gurpreet , Kaur Mehakdeep , Kaur Parminder
Published: November 2024

Machine learning has gained attention in the medical field. Continuous efforts are being made to develop robust models for early prognosis purposes. The brain is the most pivotal organ in the human body. A brain stroke is generally caused by a blockage in the brain arteries. A brain stroke is one of the primary reasons for death. Therefore, early prediction of diseases like brain stroke, heart attack can significantly help in making decisions for doctors. The research study aims to find a robust and potential technique for the early prediction of brain stroke, Alzheimer’s, heart attack, cancer, Parkinson’s and potentially reducing the incidence of severe post complications of the mentioned diseases. By considering the five datasets as input, machine learning models have been trained for the research study. Early prediction of brain stroke has been done using eight individual classifiers along with 56 other models which are designed by merging the pairs of individual models using soft and hard voting for brain stroke and eight individual classifiers have been used for early prediction of heart attack, cancer, Alzheimer and Parkinson’s. After analyzing the results of each classifier for each disease, the proposed method, which is a pair of random forest and decision tree using a hard voting method for early brain stroke prediction, achieves the highest accuracy of 99%, which is better than all classifiers. Along with accuracy, the proposed method attained a value of 98% in precision, an outstanding 100% in recall, and 99% in F1 score. XGBoost performed best for cancer, Parkinson’s, Alzeihmer’s and Bernoulli naive bayes performed best in case of Heart attack .Upon comparing the values of these performance metrics, they outshine all the other model’s values.
Simulating A/B testing versus SMART designs for LLM-driven patient engagement to close preventive care gaps
Authors: Basu Sanjay , Schillinger Dean , Patel Sadiq Y. , Rigdon Joseph
Published: November 2024

Population health initiatives often rely on cold outreach to close gaps in preventive care, such as overdue screenings or immunizations. Tailoring messages to diverse patient populations remains challenging, as traditional A/B testing requires large sample sizes to test only two alternative messages. With increasing availability of large language models (LLMs), programs can utilize tiered testing among both LLM and manual human agents, presenting the dilemma of identifying which patients need different levels of human support to cost-effectively engage large populations. Using microsimulations, we compared both the statistical power and false positive rates of A/B testing and Sequential Multiple Assignment Randomized Trials (SMART) for developing personalized communications across multiple effect sizes and sample sizes. SMART showed better cost-effectiveness and net benefit across all scenarios, but superior power for detecting heterogeneous treatment effects (HTEs) only in later randomization stages, when populations were more homogeneous and subtle differences drove engagement differences.
Embedding machine-learnt sub-grid variability improves climate model precipitation patterns
Authors: Giles Daniel , Briant James , Morcrette Cyril J. , Guillas Serge
Published: November 2024

Parameterisation schemes within General Circulation Models are required to capture cloud processes and precipitation formation but exhibit long-standing known biases. Here, we develop a hybrid approach that tackles these biases by embedding a Multi-Output Gaussian Process trained to predict high resolution variability within each climate model grid box. The trained multi-output Gaussian Process model is coupled in-situ with a simplified Atmospheric General Circulation Model named SPEEDY. The temperature and specific humidity profiles of SPEEDY are perturbed at fixed intervals according to the variability predicted from the Gaussian Process. Ten-year predictions are generated for both control and machine learning hybrid models. The hybrid model reduces the global precipitation area-weighted root-mean squared error by up to 17% and over the tropics by up to 20%. Hybrid techniques have been known to introduce non-physical states therefore physical quantities are explored to ensure that climatic drift is not observed. Furthermore, to understand the drivers of the precipitation improvements the changes to thermodynamic profiles and the distribution of lifted index values are investigated.
Layered entrenchment maintains essentiality in the evolution of Form I Rubisco complexes
Authors: Schulz Luca , Zarzycki Jan , Steinchen Wieland , Hochberg Georg K A , Erb Tobias J
Published: November 2024

Protein complexes composed of strictly essential subunits are abundant in nature and often arise through the gradual complexification of ancestral precursor proteins. Essentiality can arise through the accumulation of changes that are tolerated in the complex state but would be deleterious for the standalone complex components. While this theoretical framework to explain how essentiality arises has been proposed long ago, it is unclear which factors cause essentiality to persist over evolutionary timescales. In this work we show that the central enzyme of photosynthesis, ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), can easily start to depend on a newly recruited interaction partner through multiple, genetically distinct mechanisms that affect stability, solubility, and catalysis. We demonstrate that layering multiple mechanisms of essentiality can lead to its persistence, even if any given mechanism reverts. More broadly, our work highlights that new interaction partners can drastically re-shape which substitutions are tolerated in the proteins they are recruited into. This can lead to the evolution of multilayered essentiality through the exploration of areas of sequence space that are only accessible in the complex state.
Bioorthogonally activated probes for precise fluorescence imaging
Authors: Fu Youxin , Zhang Xing , Wu Luling , Wu Miaomiao , James Tony D. , Zhang Run
Published: November 2024

This article provides a comprehensive overview of recent advances in the development of bioorthogonally activated probes for labelling and precise in situ fluorescence imaging both in vitro and in vivo.
Retraction: p-Chloranil modified carbon nanotubes paste electrode as a voltammetric sensor for the simultaneous determination of methyldopa and uric acid
Authors: Karimi-Maleh Hassan , Khalilzadeh Mohammad A. , Ranjbarha Zahra , Beitollahi Hadi , Ensafi Ali A. , Zareyee Daryoush
Published: November 2024

Retraction of ‘p-Chloranil modified carbon nanotubes paste electrode as a voltammetric sensor for the simultaneous determination of methyldopa and uric acid’ by Hassan Karimi-Maleh et al., Anal. Methods, 2012, 4, 2088–2094, https://doi.org/10.1039/C2AY05865K.
Surface coverage and reconstruction analyses bridge the correlation between structure and activity for electrocatalysis
Authors: Guo Zhongyuan , Wang Tianyi , Xu Jiang , Cao Ang , Li Hao
Published: November 2024

The electrocatalyst-electrolyte interface complicates identifying true structure–activity relationships and reaction mechanisms. Surface state analysis can resolve conflicting views on surface-active phases and their corresponding performance.
A Janus structured TaO/TaN heterojunction as an efficient oxygen reduction electrocatalyst for H2O2 production
Authors: Li Mei , Yang Ting , Du Wenling , Bai Jiaxin , Ma Haoran , Liu Jiansheng , Chai Zhanli
Published: November 2024

A novel electrocatalyst composed of a Janus structured TaO/TaN heterojunction with graphene exhibits superior 2e− ORR activity, selectivity and durability in alkaline electrolytes, surpassing the comparative TaON@Gr.
A cobalt-tetraphenylporphyrin-based hypercrosslinked polymer for efficient CO2 photoreduction to CO
Authors: Ullah Saif , Hu Xunliang , Zhang Yaqin , Hussain Irshad , Wang Xiaoyan , Gao Hui , Tan Bien
Published: November 2024

One of the main impediments during the CO2 photocatalytic reduction process is controlling a particular product's selectivity while keeping a high conversion rate.
Investigating the properties of fatty acid-based ionic liquids: advancement in AMOEBA force field
Authors: Heidari Sahar , Torabifard Hedieh
Published: November 2024

Developing fragment-based force field for large molecules ensures parameters transferability to investigate various systems.
Transitions between positive and negative charge states of dangling bonds on a halogenated Si(100) surface
Authors: Pavlova Tatiana V. , Shevlyuga Vladimir M.
Published: November 2024

Two-electron transition between positively and negatively charged states of a dangling bond was observed in the nonequilibrium regime in STM.
Pure spin current generation with photogalvanic effects in h-BN/graphene/h-BN van der Waals vertical heterostructures
Authors: Tao Xixi , Jiang Peng , Dong Yaojun , Zhou Jinhua , Yang Xifeng , Zheng Xiaohong , Liu Yushen
Published: November 2024

A pure spin-current device based on a h-BN/graphene/h-BN van der Waals vertical heterostructure under light irradiation from the top view (a) and the front view (b).
Experimental evidence of the Sx state and fluorescence emission from the intramolecular charge transfer states in fucoxanthin
Authors: Liu Zhengtang , Ni Wenjun , Huang Yin , Gurzadyan Gagik , Chen Xin
Published: November 2024

Fucoxanthin absorbs blue light and transfers most of the energy to BChls/Chls via Sx, ICT/S1 and ICT1 states, while also releasing them via the ICT1 state to protect against light-induced damage.
Bifunctional bimetallic zeolitic imidazolate frameworks with a nanoflower structure for sodium-ion storage and non-enzymatic glucose sensing
Authors: Liu Jingjing , Shi Yu , Xu Jianhua , Yang Yajie , Yang Wenyao
Published: November 2024

Although zeolitic imidazolate frameworks (ZIFs) are widely applied in the energy storage and catalysis fields, their multifunctional applications are extremely limited by their closed rhombohedral dodecahedron structure.
Sorption of metal ions onto PET-derived microplastic fibres
Authors: Frost H. , Bond T. , Sizmur T. , Felipe-Sotelo M.
Published: November 2024

Retention of metal ions onto PET microplastic fibres is expected during sewage treatment.
Fluorinated aromatic PBCTF and 6:2 diPAP in bridge and traffic paints
Authors: Kim-Fu Mitchell L. , Moll Ansel R. , Hernandez Esteban E. , Droz Boris , Fouquet Thierry N. J. , Field Jennifer
Published: November 2024

This study takes a multifaceted approach toward characterizing total fluorine and per- and polyfluoroalkyl substances (PFAS) in traffic and bridge paints.
An introduction to machine learning tools for the analysis of microplastics in complex matrices
Authors: Coleman Brian R.
Published: November 2024

This work introduces the reader to machine learning principles and highlights its usage in examining microplastics in soil samples.
Synergistic effect of foliar exposure to TiO2 nanoparticles and planting density modulates the metabolite profile and transcription to alleviate cadmium induced phytotoxicity to wheat (Triticum aestivum L.)
Authors: Wang Min , Luo Junxiao , Li Hongbo , Ge Chenghao , Jing Feng , Guo Jingxia , Zhang Qingya , Gao Xuezhen , Cheng Cheng , Zhou Dongmei
Published: November 2024

A reasonable planting density is vital for wheat resource efficiency and yield enhancement.
Nanotechnology for oil spill response and cleanup in coastal regions
Authors: Bi Huifang , Mulligan Catherine N. , Lee Kenneth , Zhang Baiyu , Chen Zhi , An Chunjiang
Published: November 2024

Oil spills frequently cause devastating impacts on coastal ecosystems and communities.
Potential of a mammalian and avian environmental DNA metabarcoding assay as a tool for fecal pollution source tracking in river waters
Authors: Hata Akihiko , Meuchi Yuno , Kuroda Keisuke , Sankoda Kenshi , Hanamoto Seiya
Published: November 2024

A variety of animal DNA in surface water was identified by a metabarcoding approach. They corresponded to host-specific Bacteroidales markers, highlighting the potential of this approach for comprehensively identifying pollution sources.
The neurotoxicity of acrylamide in ultra-processed foods: interventions of polysaccharides through the microbiota–gut–brain axis
Authors: Cai Chen , Song Zheyi , Xu Xinrui , Yang Xin , Wei Siyu , Chen Fang , Dong Xu , Zhang Xin , Zhu Yuchen
Published: November 2024

Acrylamide contained in UPFs is neurotoxic and will do harm to human intestine and brain through the MGB axis. Polysaccharides are active substances, which can alleviate the neurotoxicity caused by acrylamide by improving the MGB axis.
Analysis of interactions between amino acids and monolayers of charged side chains
Authors: Nomoto Akira , Shiraki Kentaro , Minamiki Tsukuru
Published: November 2024

The report on an analytical platform for amino acid–amino acid interactions between charged amino acids and accumulated side chains on self-assembled monolayers combined with field-effect transistors.
Hierarchically porous Zn0.76Co0.24S/CoS heterostructures confined in N,S-co-doped carbon as high-performance anodes for sodium-ion batteries
Authors: Li Chao , Li Qing , Zhang Yu , Cao Kangzhe
Published: November 2024

Hierarchically porous Zn0.76Co0.24S/CoS heterostructures confined in N,S-co-doped carbon anodes are prepared using a MOF-engaged sulfurization method. The synergistic effects endow the ZCS@NSC anode with a good cycling stability.
One-step synthesis of new fluorescent carbon dots for the selective detection of ferric ions in aqueous environments
Authors: Jiang Xiu-Juan , Zhu Rong-Gui , Zhang Chen-Xi , Yang Bing , Yang Wen-Xia , Jiang Ming-Xuan
Published: November 2024

In recent years, carbon dots (CDs), a type of new carbon nanomaterial, have been widely used.
Synthesis, and antitumoral and antiviral evaluation of polyacetylene glycoside derivatives
Authors: Santos Jonh A. M. , Caiana Robrigo R. A. , Almeida Cláudia L. A. , Pimenta Daniel C. , Farias Kleber J. S. , de Almeida Júnior Renato F. , Machado Paula R. L. , Menezes Paulo H. , Freitas Juliano C. R.
Published: November 2024

A series of novel derivatives of Poliacetylene Glycosides (PAGs) were synthesized, and their antiproliferative and antiviral properties were evaluated.
Tannic acid salt-modified CoFe-layered double hydroxide boosts stable seawater oxidation at an industrial-level current density
Authors: Cai Zhengwei , Guo Yaxin , Yang Chaoxin , Li Zixiao , Sun Shengjun , Yue Meng , Wang Xiaoyan , Zhang Min , Wang Hefeng , Yao Yongchao , Zheng Dongdong , Farouk Asmaa , Ibrahim Fatma A. , Lv Yanqin , Sun Xuping , Tang Bo
Published: November 2024

Tannic acid salt-modified CoFe layer double hydroxide on nickel foam (CoFe LDH@CoFe-TA/NF) as an efficient OER electrocatalyst, requiring an overpotential of 379 mV to achieve 1000 mA cm−2 and maintaining stability for 450 h in alkaline seawater.
Selenenylsulfide covalent-directed chemistry for the detection of sulfhydryl groups using a diselenide fluorescent probe
Authors: Ma Chunqiu , Xu Jichao , Wang Xiaolu , Wang Xuewen , Zhang Lei , Jing Su
Published: November 2024

Design of a diglycosyldiselenide-fluorophore probe for the rapid fluorescent detection of sulfhydryl containing biomole.
Targeting reactive oxygen species to ameliorate T cell-mediated inflammation in dry eye syndrome: a novel therapeutic approach
Authors: Zheng Yi , Liu Haochen , Lu Bingkun , Dong Muchen , Wang Xinhai
Published: November 2024

Dry eye syndrome (DES) is a prevalent condition linked to oxidative stress from Orthokeratology (OK) lens use, causing significant discomfort and impacting quality of life.
Novel interfaces for internet of wearable electrochemical sensors
Authors: Shahzad Suniya , Iftikhar Faiza Jan , Shah Afzal , Rehman Hassan Abdur , Iwuoha Emmanuel
Published: November 2024

The integration of wearable devices, the Internet of Things (IoT), and advanced sensing platforms imply a significant paradigm shift in technological innovations and human interactions.
6,6′-Biindeno[1,2-b]fluorene: an open-shell indenofluorene dimer
Authors: Sharma Himanshu , Jana Palash , Mallick Dibyendu , Bandyopadhyay Subhajit , Das Soumyajit
Published: November 2024

Dimerization of antiaromatic indeno[1,2-b]fluorene units by linking the non-bridgehead carbons 6 and 6′ is reported to exhibit an open-shell ground state for the resulting biindenofluorene.
Enhanced electrocatalytic nitrate-to-ammonia performance from Mott–Schottky design to induce electron redistribution
Authors: Qi Ruikai , Jiang Qiuling , Deng Li , Yu Xianqiang , Shi Bingyan , Zhong Mengxiao , Wang Ying , Lu Xiaofeng
Published: November 2024

A Mott–Schottky type electrocatalyst of Co/In2O3 fiber is fabricated for electrocatalytic nitrate-to-ammonia conversion, presenting a NH3 yield rate of 70.1 mg cm−2 h−1 at −0.8 V vs. RHE, greatly surpassing the single-component Co and In2O3 samples.
Modeling collagen fibril degradation as a function of matrix microarchitecture
Authors: Debnath Bhanjan , Narasimhan Badri Narayanan , Fraley Stephanie I. , Rangamani Padmini
Published: November 2024

Modeling the enzymatic degradation of collagen fibrils.
Phase behavior of symmetric diblock copolymers under 3D soft confinement
Authors: He Zhijuan , Huang Jin , Jiang Kai , Shi An-Chang
Published: November 2024

The phase behavior of symmetric diblock copolymers under three-dimensional (3D) soft confinement is investigated using self-consistent field theory.
Chemical innovations in nuclear energy: paving the way for a carbon-neutral future
Authors: Geo Sarah
Published: November 2024

Chemical innovations in nuclear technology offer solutions to combat climate change, from carbon-free power generation to enabling greener techniques in agriculture and manufacturing.
Synthesis of Nd3+-doped α-γ bismuth oxide homojunction nanoparticles: a smart multifunctional solar photocatalyst
Authors: Joseph Aji , K. S. Ambili , John Anju , Yoon Minjoong , Thomas Jesty
Published: November 2024

A Nd3+-doped α-γ-bismuth oxide homojunction: an eco-friendly, NIR reflective, cool yellow pigment with upconversion luminescence and antibacterial activity, capable of degrading organic pollutants under sunlight.
Correction: MOF-derived CeO2 catalysts with Pr doping: engineering oxygen vacancies for improved CO2 conversion to dimethyl carbonate
Authors: So Jungseob , Jeong Min Hye , Yun Jungwon , An Byeong-Seon , Kim Seung-ik , Kim Geun-yeong , Kim Hyun-Tak , Chang Tae Sun , Lee Jin Hee , Heo Iljeong , An Jinjoo , You Young-Woo , Kim Minkyu , Kim Young Jin
Published: November 2024

Correction for ‘MOF-derived CeO2 catalysts with Pr doping: engineering oxygen vacancies for improved CO2 conversion to dimethyl carbonate’ by Jungseob So et al., J. Mater. Chem. A, 2024, https://doi.org/10.1039/d4ta05554c.
Enhancing molecular aggregation and decreasing the optical gap by a dual-additive to reduce the energy loss of all-polymer organic solar cells
Authors: Pan Jiaqi , Zhang Qiang , Guan Jian , Gao Hanyue , Li Luzhuo , Zhang Rui , Li Hongxiang , Yu Xinhong , Han Yanchun
Published: November 2024

1. The introduction of dual-additive extend the aggregation time of PYIT; 2. A better vertical phase separation structure has been formed; 3. Eloss: 0.500–0.476 eV; PCE: 14.58–16.67%.
ZTF SN Ia DR2: The spectral diversity of Type Ia supernovae in a volume-limited sample
Authors: Burgaz U. , Maguire K. , Dimitriadis G. , Harvey L. , Senzel R. , Sollerman J. , Nordin J. , Galbany L. , Rigault M. , Smith M. , Goobar A. , Johansson J. , Rosnet P. , Alburai A. , Amenouche M. , Deckers M. , Dhawan S. , Ginolin M. , Kim Y.-L. , Miller A. A. , Muller-Bravo T. E. , Nugent P. E. , Terwel J. H. , Dekany R. , Drake A. , Graham M. J. , Groom S. L. , Kasliwal M. M. , Kulkarni S. R. , Nolan K. , Nir G. , Riddle R. L. , Rusholme B. , Sharma Y.
Published: November 2024

More than 3000 spectroscopically confirmed Type Ia supernovae (SNe Ia) are presented in the second data release (DR2) of the Zwicky Transient Facility survey. In this paper we detail the spectral properties of 482 SNe Ia near maximum light, up to a redshift limit of z ≤ 0.06. We measured the velocities and pseudo-equivalent widths (pEW) of key spectral features (Si IIλ5972 and Si IIλ6355) and investigated the relation between the properties of the spectral features and the photometric properties from the SALT2 light-curve parameters as a function of spectroscopic sub-class. We discuss the non-negligible impact of host galaxy contamination on SN Ia spectral classifications, and we investigate the accuracy of spectral template matching of the DR2 sample. We define a new subclass of underluminous SNe Ia (04gs-like) that lie spectroscopically between normal SNe Ia and transitional 86G-like SNe Ia (stronger Si IIλ5972 than normal SNe Ia, but significantly weaker Ti II features than 86G-like SNe). We model these 04gs-like SN Ia spectra using the radiative-transfer spectral synthesis code TARDIS and show that cooler temperatures alone are unable to explain their spectra; some changes in elemental abundances are also required. However, the broad continuity in spectral properties seen from bright (91T-like) to faint normal SN Ia, including the transitional and 91bg-like SNe Ia, suggests that variations within a single explosion model may be able to explain their behaviour.
The emergence of the MD − Ṁ* correlation in the magnetohydrodynamic wind scenario
Authors: Zallio Luigi , Rosotti Giovanni , Tabone Benoît , Testi Leonardo , Lodato Giuseppe , Somigliana Alice
Published: November 2024

Context. There is still much uncertainty around the mechanism that rules the accretion of proto-planetary disks. In recent years, magnetohydrondynamic (MHD) wind-driven accretion has been proposed as a valid alternative to the more conventional viscous accretion. In particular, winds have been shown to reproduce the observed correlation between the mass of the disk MD and the mass accretion rate onto the central star Ṁ*, but this has been done only for specific conditions. It is not clear whether this implies fine tuning or if it is a general result.

Aims. We investigated under which conditions the observed correlation between the mass of the disk MD and the mass accretion rate onto the central star Ṁ*, can be obtained.

Methods. We present mainly analytical calculations, supported by Monte Carlo simulations. We also perform a comparison with the observed data to test our predictions.

Results. In the absence of a correlation between the initial mass M0 and the initial accretion timescale tacc,0 , we find that the slope of the MD − Ṁ* correlation depends on the value of the spread of the initial conditions of masses and lifetimes of disks. Then we clarify the conditions under which a disk population can be fitted with a single power law. Moreover, we derive an analytical expression for the spread of log(MD/Ṁ*) valid when the spread of tacc is taken to be constant. In the presence of a correlation between M0 and tacc,0, we derive an analytical expression for the slope of the MD−Ṁ* correlation in the initial conditions of disks and at late times. In this new scenario, we clarify under which conditions the disk population can be fitted by a single power law, and we provide empirical constraints on the parameters ruling the evolution of disks in our models.

Conclusions. We conclude that MHD winds can predict the observed values of the slope and the spread of the MD−Ṁ* correlation under a broad range of initial conditions. This is a fundamental expansion of previous works on the MHD paradigm, exploring the establishment of this fundamental correlation beyond specific initial conditions.
Cosmography from accurate mass modeling of the lens group SDSS J0100+1818: Five sources at three different redshifts
Authors: Bolamperti A. , Grillo C. , Caminha G. B. , Granata G. , Suyu S. H. , Cañameras R. , Christensen L. , Vernet J. , Zanella A.
Published: November 2024

Systems where multiple sources at different redshifts are strongly lensed by the same deflector allow one to directly investigate the evolution of the angular diameter distances as a function of redshift, and thus to learn about the geometry of the Universe. We present measurements of the values of the total matter density, Ωm, and of the dark energy equation of state parameter, w, through a detailed strong lensing analysis of SDSS J0100+1818, a group-scale system at z = 0.581 with five lensed sources, from z = 1.698 to 4.95. We take advantage of new spectroscopic data from the Multi Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope to securely measure the redshift of 65 sources, including the 5 multiply imaged background sources (lensed into a total of 18 multiple images) and 19 galaxies on the deflector plane, all employed to build robust strong lensing models with the software GLEE. The total mass distribution of the deflector is described in a relatively simple way, and includes an extended halo, the brightest group galaxy (BGG) with a measured stellar velocity dispersion of (380.5 ± 4.4) km s−1, and fainter members. We measure Ωm = 0.14−0.09+0.16 in a flat Λ cold dark matter (CDM) model, and Ωm = 0.19−0.10+0.17 and w = −1.27−0.48+0.43 in a flat wCDM model. Given the presence of different sources angularly close in projection, we quantify through a multiplane approach their impact on the inferred values of the cosmological parameters. We obtain consistent median values, with uncertainties for only Ωm increasing by approximately a factor of 1.5. Thanks to the remarkably wide radial interval where the multiple images are observed, ranging from 15 to 77 kpc from the BGG, we accurately measure the total mass profile and infer the stellar over total mass profile of the deflector. They result in a total mass of (1.55 ± 0.01)×1013 M⊙ within 50 kpc and a stellar over total mass profile decreasing from 45.6−8.3+8.7% at the BGG effective radius to (6.6 ± 1.1)% at R ≈ 77 kpc. Our results confirm that SDSS J0100+1818 is one of the most massive (lens) galaxies known at intermediate redshift and one of the most distant candidate fossil systems. We also show that group-scale systems that act as lenses for ≥3 background sources at different redshifts enable one to estimate the values of the cosmological parameters Ωm and w with an accuracy that is competitive with that obtained from lens galaxy clusters.
Non-parametric identification of single-lined binary candidates in young clusters using single-epoch spectroscopy
Authors: Rinaldi Stefano , Ramírez-Tannus María Claudia
Published: November 2024

Aims. Binarity plays a crucial role in star formation and evolution. Consequently, identifying binary stars is essential to deepening our understanding of these processes. We propose a method to investigate the observed radial velocity distribution of massive stars in young clusters with the goal of identifying binary systems.

Methods. We reconstruct the radial velocity distribution using a three-layer hierarchical Bayesian non-parametric approach; nonparametric methods are data-driven models able to infer arbitrary probability densities under minimal mathematical assumptions. When applying our statistical framework, it is possible to identify variable stars and binary systems because these deviate significantly from the expected intrinsic Gaussian distribution for radial velocities.

Results. We tested our method with the massive star-forming region within the giant HII region M17. We are able to confidently identify binaries and variable stars with as little as single-epoch observations. The distinction between variable and binary stars improves significantly when introducing additional epochs.