bluuebunny/crossref_metadata_2025_split huggingface dataset:
Germline β−1,3-glucan deposits are required for female gametogenesis in Arabidopsis thaliana
Authors: Pinto Sara C. , Leong Weng Herng , Tan Hweiting , McKee Lauren , Prevost Amelie , Ma Chao , Shirley Neil. J. , Petrella Rosanna , Yang Xiujuan , Koltunow Anna M. , Bulone Vincent , Kanaoka Masahiro M. , Higashyiama Tetsuya , Coimbra Sílvia , Tucker Matthew R. 
Published: July 2024

AbstractCorrect regulation of intercellular communication is a fundamental requirement for cell differentiation. In Arabidopsis thaliana, the female germline differentiates from a single somatic ovule cell that becomes encased in β−1,3-glucan, a water insoluble polysaccharide implicated in limiting pathogen invasion, regulating intercellular trafficking in roots, and promoting pollen development. Whether β−1,3-glucan facilitates germline isolation and development has remained contentious, since limited evidence is available to support a functional role. Here, transcriptional profiling of adjoining germline and somatic cells revealed differences in gene expression related to β−1,3-glucan metabolism and signalling through intercellular channels (plasmodesmata). Dominant expression of a β−1,3-glucanase in the female germline transiently perturbed β−1,3-glucan deposits, allowed intercellular movement of tracer molecules, and led to changes in germline gene expression and histone marks, eventually leading to termination of germline development. Our findings indicate that germline β−1,3-glucan fulfils a functional role in the ovule by insulating the primary germline cell, and thereby determines the success of downstream female gametogenesis.
Nucleation phenomena and extreme vulnerability of spatial k-core systems
Authors: Xue Leyang , Gao Shengling , Gallos Lazaros K. , Levy Orr , Gross Bnaya , Di Zengru , Havlin Shlomo 
Published: July 2024

AbstractK-core percolation is a fundamental dynamical process in complex networks with applications that span numerous real-world systems. Earlier studies focus primarily on random networks without spatial constraints and reveal intriguing mixed-order transitions. However, real-world systems, ranging from transportation and communication networks to complex brain networks, are not random but are spatially embedded. Here, we study k-core percolation on two-dimensional spatially embedded networks and show that, in contrast to regular percolation, the length of connections can control the transition type, leading to four different types of phase transitions associated with interesting phenomena and a rich phase diagram. A key finding is the existence of a metastable phase where microscopic localized damage, independent of system size, can cause a macroscopic phase transition, a result which cannot be achieved in traditional percolation. In this case, local failures spontaneously propagate the damage radially until the system collapses, a phenomenon analogous to the nucleation process.
Plasmonic trimers designed as SERS-active chemical traps for subtyping of lung tumors
Authors: Zhao Xing , Liu Xiaojing , Chen Dexiang , Shi Guodong , Li Guoqun , Tang Xiao , Zhu Xiangnan , Li Mingze , Yao Lei , Wei Yunjia , Song Wenzhe , Sun Zixuan , Fan Xingce , Zhou Zhixin , Qiu Teng , Hao Qi 
Published: July 2024

AbstractPlasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the ‘hotspots’, which account for ≈ 1% of the surface area, experiencing efficient enhancement. Herein, we propose patterned plasmonic trimers, consisting of a pair of plasmonic dimers at the bilateral sides and a trap particle positioned in between, to address this challenge. The trimer configuration selectively directs probe molecules to the central traps where ‘hotspots’ are located through chemical affinity, ensuring a precise spatial overlap between the probes and the location of maximum field enhancement. We investigate the Raman enhancement of the Au@Al2O3-Au-Au@Al2O3 trimers, achieving a detection limit of 10−14 M of 4-methylbenzenethiol, 4-mercaptopyridine, and 4-aminothiophenol. Moreover, single-molecule SERS sensitivity is demonstrated by a bi-analyte method. Benefiting from this sensitivity, our approach is employed for the early detection of lung tumors using fresh tissues. Our findings suggest that this approach is sensitive to adenocarcinoma but not to squamous carcinoma or benign cases, offering insights into the differentiation between lung tumor subtypes.
Molecular modeling applied to corrosion inhibition: a critical review
Authors: Castillo-Robles José María , de Freitas Martins Ernane , Ordejón Pablo , Cole Ivan 
Published: July 2024

AbstractIn the last few years, organic corrosion inhibitors have been used as a green alternative to toxic inorganic compounds to prevent corrosion in materials. Nonetheless, the fundamental mechanisms determining their inhibition performance are still far from understood. Molecular modeling can provide important insights into those mechanisms, allowing for a detailed analysis of the corrosion inhibition (CI) process. However, CI modeling is frequently underexplored and commonly used in a standardized way following a pre-determined recipe to support experimental data. We highlight six fundamental aspects (A) that one should consider when modeling CI: (A1) the electronic properties of isolated inhibitors, (A2) the interaction of the inhibitor with the surface, (A3) the surface model, (A4) the effect of the anodic and cathodic zones on the surface, (A5) the solvent effects, and (A6) the electrodes’ potential effects. While A1-A3 are more frequently investigated, A4-A6 and some more complex surface models from A3 are usually not considered and represent gaps in the CI modeling literature. In this review, we discuss the main features of molecular modeling applied to CI, considering the aforementioned key aspects and focusing on the gaps that the emerging approaches aim to fill. Filling these gaps will allow performing more detailed simulations of the CI process, which, coupled with artificial intelligence (AI) methods and multiscale approaches, might construct the bridge between the nanoscale CI modeling and the continuum scale of the CI processes.
Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling
Authors: Lê Quý Khang , Chernigovskaya Maria , Stensland Maria , Singh Sachin , Leem Jinwoo , Revale Santiago , Yadin David A. , Nice Francesca L. , Povall Chelsea , Minns Danielle H. , Galson Jacob D. , Nyman Tuula A. , Snapkow Igor , Greiff Victor 
Published: July 2024

AbstractImmunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the recognition and response to antigenic threats. The capability to jointly characterize the BCR and antibody repertoire is crucial for understanding human adaptive immunity. From peripheral blood, bulk BCR sequencing (bulkBCR-seq) currently provides the highest sampling depth, single-cell BCR sequencing (scBCR-seq) allows for paired chain characterization, and antibody peptide sequencing by tandem mass spectrometry (Ab-seq) provides information on the composition of secreted antibodies in the serum. Yet, it has not been benchmarked to what extent the datasets generated by these three technologies overlap and complement each other. To address this question, we isolated peripheral blood B cells from healthy human donors and sequenced BCRs at bulk and single-cell levels, in addition to utilizing publicly available sequencing data. Integrated analysis was performed on these datasets, resolved by replicates and across individuals. Simultaneously, serum antibodies were isolated, digested with multiple proteases, and analyzed with Ab-seq. Systems immunology analysis showed high concordance in repertoire features between bulk and scBCR-seq within individuals, especially when replicates were utilized. In addition, Ab-seq identified clonotype-specific peptides using both bulk and scBCR-seq library references, demonstrating the feasibility of combining scBCR-seq and Ab-seq for reconstructing paired-chain Ig sequences from the serum antibody repertoire. Collectively, our work serves as a proof-of-principle for combining bulk sequencing, single-cell sequencing, and mass spectrometry as complementary methods towards capturing humoral immunity in its entirety.
Data driven multiple objective optimization of AAO process towards wastewater effluent biological toxicity reduction
Authors: Hu Jie , Yin Ran , Wang Jinfeng , Ren Hongqiang 
Published: July 2024

AbstractWhile the anaerobic-anoxic-oxic (AAO) process is the most widely applied biological wastewater treatment process in municipal wastewater treatment plants (WWTPs), it struggles to meet the increasing demands on biological toxicity control of the treated effluent. To tackle this challenge, this study develops machine learning (ML)-based models for optimizing the AAO treatment process towards improving its toxicity reduction efficacy for the effluent. The water quality parameters, treatment process parameters, and biological toxicity information (based on the nematode bioassay) of the effluent collected from 122 WWTPs in China are used to train the models. The validated models accurately predict the effluent’s quality parameters (average R2 = 0.81) and the biological toxicity reduction ratio of treatment process (R2 = 0.86). To further improve the toxicity reduction, we developed a multiple objective optimization framework to optimize the AAO process via unit process recombination. In the short-range unit combination, the toxicity reduction ratio of the four-unit combined processes (up to 79.8% of anaerobic-aerobic-anaerobic-aerobic) is significantly higher than others. After optimization, it helps to improve the average toxicity reduction efficacy of 122 WWTPs from 48.6% to 70.7%, with a maximum of 87.5%. The methodologies and findings derived from this work are expected to provide the foundation for the optimization, expansion, and technical transformation of biological wastewater treatment in WWTPs.
The nature of the last universal common ancestor and its impact on the early Earth system
Authors: Moody Edmund R. R. , Álvarez-Carretero Sandra , Mahendrarajah Tara A. , Clark James W. , Betts Holly C. , Dombrowski Nina , Szánthó Lénárd L. , Boyle Richard A. , Daines Stuart , Chen Xi , Lane Nick , Yang Ziheng , Shields Graham A. , Szöllősi Gergely J. , Spang Anja , Pisani Davide , Williams Tom A. , Lenton Timothy M. , Donoghue Philip C. J. 
Published: July 2024

AbstractThe nature of the last universal common ancestor (LUCA), its age and its impact on the Earth system have been the subject of vigorous debate across diverse disciplines, often based on disparate data and methods. Age estimates for LUCA are usually based on the fossil record, varying with every reinterpretation. The nature of LUCA’s metabolism has proven equally contentious, with some attributing all core metabolisms to LUCA, whereas others reconstruct a simpler life form dependent on geochemistry. Here we infer that LUCA lived ~4.2 Ga (4.09–4.33 Ga) through divergence time analysis of pre-LUCA gene duplicates, calibrated using microbial fossils and isotope records under a new cross-bracing implementation. Phylogenetic reconciliation suggests that LUCA had a genome of at least 2.5 Mb (2.49–2.99 Mb), encoding around 2,600 proteins, comparable to modern prokaryotes. Our results suggest LUCA was a prokaryote-grade anaerobic acetogen that possessed an early immune system. Although LUCA is sometimes perceived as living in isolation, we infer LUCA to have been part of an established ecological system. The metabolism of LUCA would have provided a niche for other microbial community members and hydrogen recycling by atmospheric photochemistry could have supported a modestly productive early ecosystem.
Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis
Authors: Sun Meng , Phan Jolie M. , Kieswetter Nathan S. , Huang Huang , Yu Krystle K. Q. , Smith Malisa T. , Liu Yiran E. , Wang Chuangqi , Gupta Sanjana , Obermoser Gerlinde , Maecker Holden Terry , Krishnan Akshaya , Suresh Sundari , Gupta Neha , Rieck Mary , Acs Peter , Ghanizada Mustafa , Chiou Shin-Heng , Khatri Purvesh , Boom W. Henry , Hawn Thomas R. , Stein Catherine M. , Mayanja-Kizza Harriet , Davis Mark M. , Seshadri Chetan 
Published: July 2024

AbstractA subset of individuals exposed to Mycobacterium tuberculosis (Mtb) that we refer to as ‘resisters’ (RSTR) show evidence of IFN-γ− T cell responses to Mtb-specific antigens despite serially negative results on clinical testing. Here we found that Mtb-specific T cells in RSTR were clonally expanded, confirming the priming of adaptive immune responses following Mtb exposure. RSTR CD4+ T cells showed enrichment of TH17 and regulatory T cell-like functional programs compared to Mtb-specific T cells from individuals with latent Mtb infection. Using public datasets, we showed that these TH17 cell-like functional programs were associated with lack of progression to active tuberculosis among South African adolescents with latent Mtb infection and with bacterial control in nonhuman primates. Our findings suggested that RSTR may successfully control Mtb following exposure and immune priming and established a set of T cell biomarkers to facilitate further study of this clinical phenotype.
AgCNER, the First Large-Scale Chinese Named Entity Recognition Dataset for Agricultural Diseases and Pests
Authors: Yao Xiaochuang , Hao Xia , Liu Ruilin , Li Lin , Guo Xuchao 
Published: July 2024

AbstractNamed entity recognition is a fundamental subtask for knowledge graph construction and question-answering in the agricultural diseases and pests field. Although several works have been done, the scarcity of the Chinese annotated dataset has restricted the development of agricultural diseases and pests named entity recognition(ADP-NER). To address the issues, a large-scale corpus for the Chinese ADP-NER task named AgCNER was first annotated. It mainly contains 13 categories, 206,992 entities, and 66,553 samples with 3,909,293 characters. Compared with other datasets, AgCNER maintains the best performance in terms of the number of categories, entities, samples, and characters. Moreover, this is the first publicly available corpus for the agricultural field. In addition, the agricultural language model AgBERT is also fine-tuned and released. Finally, the comprehensive experimental results showed that BiLSTM-CRF achieved F1-score of 93.58%, which would be further improved to 94.14% using BERT. The analysis from multiple aspects has verified the rationality of AgCNER and the effectiveness of AgBERT. The annotated corpus and fine-tuned language model are publicly available at https://doi.org/XXX and https://github.com/guojson/AgCNER.git.
An UltraMNIST classification benchmark to train CNNs for very large images
Authors: Gupta Deepak K. , Bamba Udbhav , Thakur Abhishek , Gupta Akash , Agarwal Rohit , Sharan Suraj , Demir Ertugul , Agarwal Krishna , Prasad Dilip K. 
Published: July 2024

AbstractCurrent convolutional neural networks (CNNs) are not designed for large scientific images with rich multi-scale features, such as in satellite and microscopy domain. A new phase of development of CNNs especially designed for large images is awaited. However, application-independent high-quality and challenging datasets needed for such development are still missing. We present the ‘UltraMNIST dataset’ and associated benchmarks for this new research problem of ‘training CNNs for large images’. The dataset is simple, representative of wide-ranging challenges in scientific data, and easily customizable for different levels of complexity, smallest and largest features, and sizes of images. Two variants of the problem are discussed: standard version that facilitates the development of novel CNN methods for effective use of the best available GPU resources and the budget-aware version to promote the development of methods that work under constrained GPU memory. Several baselines are presented and the effect of reduced resolution is studied. The presented benchmark dataset and baselines will hopefully trigger the development of new CNN methods for large scientific images.
Effect of Flammulina velutipes polysaccharide on mitochondrial apoptosis in lung adenocarcinoma A549 cells
Authors: Zhao Fei , Chen Dan-yang , Jing Bo , Jiang Yu , Liu Lan-yue , Song Hui 
Published: July 2024

AbstractFVP is a polysaccharide extracted from Flammulina velutipes with immunomodulatory, anti-tumor, and anti-oxidation activities. In this study, we obtained the crude polysaccharide FVP-C from the water extract of Flammulina velutipes, and its main component FVP-S1 was obtained after further purification. Upon structural identification, we found that FVP-C is a neutral polysaccharide, and FVP-S1 was an acidic golden mushroom polysaccharide, consisting of glucuronic acid, xylose, and glucose. Lung adenocarcinoma (A549) was treated with FVP-S1 and FVP-C, respectively, and we found that FVP-S1 and FVP-C inhibited the proliferation and migration ability of tumor cells, as well as changed the morphology of the tumor cells and caused chromosome sheteropythosis, among which FVP-S1 had the best inhibition effect. The results of flow cytometry experiments and mitochondrial membrane potential, RT-qPCR, and Western blot showed that FVP-S1 and FVP-C were able to decrease the mitochondrial membrane potential, increase the expression level of apoptotic proteins Casepase-3 and Casepase-9 proteins, and at the same time, increase the ratio of Bax and Bcl-2, which promoted apoptosis of tumor cells. In conclusion, these data indicated that FVP-S1 and FVP-C were able to induce apoptosis in A549 cells through the mitochondrial pathway, which played an important role in inhibiting tumor cells.
High frequency electrical stimulation reduces α-synuclein levels and α-synuclein-mediated autophagy dysfunction
Authors: George Jimmy , Shafiq Kashfia , Kapadia Minesh , Kalia Lorraine V. , Kalia Suneil K. 
Published: July 2024

AbstractAccumulation of α-synuclein (α-Syn) has been implicated in proteasome and autophagy dysfunction in Parkinson’s disease (PD). High frequency electrical stimulation (HFS) mimicking clinical parameters used for deep brain stimulation (DBS) in vitro or DBS in vivo in preclinical models of PD have been found to reduce levels of α-Syn and, in certain cases, provide possible neuroprotection. However, the mechanisms by which this reduction in α-Syn improves cellular dysfunction associated with α-Syn accumulation remains elusive. Using HFS parameters that recapitulate DBS in vitro, we found that HFS led to a reduction of mutant α-Syn and thereby limited proteasome and autophagy impairments due to α-Syn. Additionally, we observed that HFS modulates via the ATP6V0C subunit of V-ATPase and mitigates α-Syn mediated autophagic dysfunction. This study highlights a role for autophagy in reduction of α-Syn due to HFS which may prove to be a viable approach to decrease pathological protein accumulation in neurodegeneration.
Verbena officinalis (VO) leaf extract as an anti-corrosion inhibitor for carbon steel in acidic environment
Authors: Fouda Abd El-Aziz S. , Molouk Ahmed F. , Atia Mohamed F. , El-Hossiany Ahmed , Almahdy Mohamed S. 
Published: July 2024

AbstractIn the present work, Verbena Officinalis (VO) leaf extract was used as potential corrosion inhibitor for the corrosion of carbon steel (CS) in 0.5 M H2SO4 medium. Further, the corrosion inhibiting nature of VO leaf extract towards the CS was evaluated using mass loss (ML), potentiodynamic polarization (PDP), electrical impedance spectroscopy (EIS) and surface morphological analyses using atomic force microscope (AFM) and X-ray photoelectron spectroscopy (XPS) techniques. Calculation of activation energy $$\left( {{\text{E}}_{{\text{a}}}^{*} } \right)$$

E

a

∗

using Arrhenius equation shows the increase in activation energy when adding the VO leaf extract in 0.5 M H2SO4 medium and the maximum activation energy ($${\text{E}}_{{\text{a}}}^{*}$$

E

a

∗

= 49.9 kJ mol−1) was observed for 1000 mg L−1 VO leaf extract in acid medium. The negative free energy values suggested the spontaneous and the stability of the adsorbed layer of VO leaf extract on the CS surface. Using EIS measurements, high percent inhibitory effectiveness of 91.1% for 1000 ppm solutions was achieved. With an increase in VO leaf extract dose, the double layer capacitance (Cdl) values fall while the values of charge transfer (Rct) increase. This showed that a protective layer of VO leaf extract on CS surface was formed. The polarization curves showed that the VO leaf extract acts as a mixed-type inhibitor. It is discovered that the adsorption of VO leaf extract molecules adhering to the CS surface followed the Langmuir isotherm. The anti-corrosion action of VO leaf extract is fully demonstrated by some surface techniques.
Contrast efficacy of novel phase convertible nanodroplets for safe CEUS imaging
Authors: Riaz R. , Shafiq S. , Fatima M. , Siddique M. A. , Shah S. , Abbas S. R. 
Published: July 2024

AbstractMicrobubble contrast agents in ultrasound/echocardiography are used to increase the echogenicity of the target tissues, thereby raising the contrast resolution of the resultant image. Recently, the trend has shifted toward the development of phase-convertible nanodroplets as ultrasound contrast agents due to their promising theragnostic potential by switching capability at the active site. Herein, we fabricated pre-PGS- perfluoropentane phase convertible nanodroplets and checked their in vitro and in vivo enhancement and safety profile. For this, we performed experiments on 20 male Wistar rats and 2 dogs. Biochemical assays of both rats and dogs included complete blood profiles, liver function tests, and renal function tests. For rat vitals, monitoring and histopathological analysis were also performed. Converted nanodroplets showed excellent contrast enhancement, better than Sonovue upon in vitro testing, with an enhancement time of up to 14 min. In vivo, experiments showed comparable opacification of the ventricles of both rats and dogs. All biochemical assays remained within the normal range during the study period. The histopathological analysis did not show any signs of drug-induced toxicity, showing the safety of these nanodroplets. Pre-PGS-PFP nanodroplets hold great potential for use in echocardiography and abdominal imaging in both human and veterinary applications after clinical trials.