jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shaotong Pei | Weiqi Wang | Chenlong Hu | Haichao Sun | Keyu Li | M. Wu | Bo Lan
Source: Energy Science & Engineering (article, 2025-04-24)
Field: Materials Science — Materials Chemistry

Detection of Hydrophobicity Grade of Composite Insulators Based on MDC‐YOLO Algorithm ABSTRACT In the field of power equipment inspection, the aging condition of composite insulators is often determined by the detection of water repellency. However, the existing detection methods are difficult to effectively extract the water repellency level features in the complex background, and it is difficult to meet the real‐time requirements. Therefore, this paper proposes a MDC‐YOLO algorithm for water repellency detection and classification of composite insulators. The algorithm effectively combines the efficient convolutional network (EfficientNetV2), the deformable attention mechanism (DAttention), and the lightweight convolution (CSPPC), which significantly realizes the lightweight of the network, and at the same time improves the accuracy of the algorithm for the composite insulator umbrella skirt identification, water repellency class classification. Experimentally verified, the multilayer detection and classification YOLO algorithm of water repellency of composite insulators proposed in this paper, i.e., MDC‐YOLO algorithm, improves the detection accuracy of umbrella skirt by 5.19% and reduces the GFLOPs to 3.5, and improves the Top‐1 accuracy of water repellency grade classification by 4.654% and reduces the GFLOPs by 1.1. The results of the present research can be widely applied to The results of this study can be widely used in the fields of power equipment inspection, smart grid construction and insulator aging state assessment, which provides strong support for the technical development of related fields. It meets the requirements of hydrophobicity detection and classification of composite insulators, and proves the effectiveness and superiority of the algorithm proposed in this paper through ablation and comparison tests. Composite number ; Algorithm ; Computer science ; Materials science High voltage insulation and dielectric phenomena ; Image Enhancement Techniques ; Infrastructure Maintenance and Monitoring
Authors: Yang Yang | Ting Yu | Mengdan Tao | Yong Wang | Xinying Yao | Chenkai Zhu | Fengxue Xin | Min Jiang
Source: Polymers (article, 2025-01-23)
Field: Materials Science — Biomaterials

Development of Recombinant Human Collagen-Based Porous Scaffolds for Skin Tissue Engineering: Enhanced Mechanical Strength and Biocompatibility Skin tissue engineering scaffolds should possess key properties such as porosity, degradability, durability, and biocompatibility to effectively facilitate skin cell adhesion and growth. In this study, recombinant human collagen (RHC) was used to fabricate porous scaffolds via freeze-drying, offering an alternative to animal-derived collagen where bovine collagen (BC)-based scaffolds were also prepared for comparison. The internal morphology of the RHC scaffolds were characterized by scanning electron microscopy (SEM) and the pore size ranged from 68.39 to 117.52 µm. The results from compression and fatigue tests showed that the mechanical strength and durability of RHC scaffolds could be tailored by adjusting the RHC concentration, and the maximum compressive modulus reached to 0.003 MPa, which is comparable to that of BC scaffolds. The degradation test illustrated that the RHC scaffolds had a slower degradation rate compared to BC scaffolds. Finally, the biocompatibilities of the porous scaffolds were studied by seeding and culturing the human foreskin fibroblasts (HFFs) and human umbilical vein endothelial cells (HUVECs) in samples. The fluorescent images and Cell Counting Kit-8 (CCK-8) assay revealed RHC porous scaffolds were non-cytotoxic and supported the attachment as well as the proliferation of the seeded cells. Overall, the results demonstrated that RHC-based scaffolds exhibited adequate mechanical strength, ideal biodegradability, and exceptional biocompatibility, making them highly suitable for skin-tissue-engineering applications. Biocompatibility ; Tissue engineering ; Biomedical engineering ; Materials science ; Compressive strength ; Scaffold ; Umbilical vein ; Adhesion ; Porosity ; Chemistry ; Composite material ; In vitro Collagen: Extraction and Characterization ; Bone Tissue Engineering Materials ; Wound Healing and Treatments
Authors: Wassim Gabriel | Roxana González | Sophia Laposchan | Erik Riedel | Gönül Dündar | Brigitte Poppenberger | Mathias Wilhelm | Chien‐Yun Lee
Source: Molecular & Cellular Proteomics (article, 2025-02-05)
Field: Chemistry — Spectroscopy

Deep Learning Enhances Precision of Citrullination Identification in Human and Plant Tissue Proteomes Citrullination is a critical yet understudied post-translational modification (PTM) implicated in various biological processes. Exploring its role in health and disease requires a comprehensive understanding of the prevalence of this PTM at a proteome-wide scale. Although mass spectrometry has enabled the identification of citrullination sites in complex biological samples, it faces significant challenges, including limited enrichment tools and a high rate of false positives due to the identical mass with deamidation (+0.9840 Da) and errors in monoisotopic ion selection. These issues often necessitate manual spectrum inspection, reducing throughput in large-scale studies. In this work, we present a novel data analysis pipeline that incorporates the deep learning model Prosit-Cit into the MS database search workflow to improve both the sensitivity and the precision of citrullination site identification. Prosit-Cit, an extension of the existing Prosit model, has been trained on ∼53,000 spectra from ∼2500 synthetic citrullinated peptides and provides precise predictions for chromatographic retention time and fragment ion intensities of both citrullinated and deamidated peptides. This enhances the accuracy of identification and reduces false positives. Our pipeline demonstrated high precision on the evaluation dataset, recovering the majority of known citrullination sites in human tissue proteomes and improving sensitivity by identifying up to 14 times more citrullinated sites. Sequence motif analysis revealed consistency with previously reported findings, validating the reliability of our approach. Furthermore, extending the pipeline to a tissue proteome dataset of the model plant Arabidopsis thaliana enabled the identification of ∼200 citrullination sites across 169 proteins from 30 tissues, representing the first large-scale citrullination mapping in plants. This pipeline can be seamlessly applied to existing proteomics datasets, offering a robust tool for advancing biological discoveries and deepening our understanding of protein citrullination across species. Citrullination ; Proteome ; Identification (biology) ; Computational biology ; Human proteome project ; Proteomics ; Posttranslational modification ; Biology ; Chemistry ; Cell biology ; Biochemistry ; Botany ; Amino acid ; Enzyme ; Citrulline ; Gene Advanced Proteomics Techniques and Applications ; Glycosylation and Glycoproteins Research ; Genomics and Phylogenetic Studies
Authors: Shengtao Yu | Didar Baimanov | Zhenzhen Guo | Qing Gao | Chunying Chen | Mateus Borba Cardoso | Liming Wang
Source: Small Methods (review, 2025-06-16)
Field: Materials Science — Biomaterials

In Situ Analysis for Protein Corona: from Morphology, Composition, Structure to Dynamic Process The formation of a protein corona (PC) on the surface of nanoparticles (NPs) in biological environments is a critical factor influencing the fate and functionality of NPs in vivo. This biolayer affects NPs' biodistribution, immune recognition, cellular uptake, and therapeutic efficacy, making it essential for the rational design of nanomedicines. However, traditional analytical techniques often disrupt the native state of the PC, particularly its loosely bound soft corona (SC), leading to incomplete characterizations. In situ analysis methods offer a more accurate representation of PC composition, structure, and dynamics by preserving its native biological context. This review highlights critical advances in in situ PC analysis techniques, including methods for composition identification, structural visualization, and monitoring the dynamic evolution of the PC. It emphasizes the importance of real-time, non-disruptive analysis to better understand the nano-bio interface and its implications for nanomedicine design and safety. Additionally, it discusses challenges in current PC analysis methodologies and proposes future research directions to improve in situ characterization accuracy and standardization. Context (archaeology) ; Nanomedicine ; Rational design ; In situ ; Nanotechnology ; Computer science ; Characterization (materials science) ; Biodistribution ; Representation (politics) ; Computational biology ; Chemistry ; Materials science ; Nanoparticle ; Biology ; In vitro Nanoparticle-Based Drug Delivery ; Characterization and Applications of Magnetic Nanoparticles ; Polymer Surface Interaction Studies
Authors: Muhammad Panachikkool | Elagandula Aparna | Perumal Asaithambi | T. Pandiyarajan
Source: Scientific Reports (article, 2025-01-02)
Field: Materials Science — Materials Chemistry

Design and numerical simulation of CuBi2O4 solar cells with graphene quantum dots as hole transport layer under ideal and non-ideal conditions The simulation of ideal and non-ideal conditions using the SCAPS-1D simulator for novel structure Ag/FTO/CuBi<sub>2</sub>O<sub>4</sub>/GQD/Au was done for the first time. The recombination of charge carriers in CuBi<sub>2</sub>O<sub>4</sub> is an inherent problem due to very low hole mobility and polaron transport in the valence band. The in-depth analysis of the simulation result revealed that Graphene Quantum Dots (GQDs) can act as an appropriate hole transport layer (HTL) and can enhance hole transportation. The simulation was done under ideal and nonideal conditions. The non-ideal conditions include parasitic resistances, reflection losses, radiative, and Auger recombination whereas the ideal condition was studied without the inclusion of any losses. Under ideal conditions, the cell Ag/FTO/CuBi<sub>2</sub>O<sub>4</sub>/GQD/Au exhibited a photovoltaic (PV) parameter such as open circuit voltage (V<sub>oc</sub>), short circuit current (J<sub>sc</sub>), fill factor (FF), photo conversion efficiency (PCE) are 1.39 V, 25.898 mA/cm<sup>2</sup>, 90.92%, and 32.79%, respectively. The effect of various cell parameters such as the thickness of the absorber layer, HTL layer, and FTO, acceptor and defect density, the bandgap of the absorber and HTL layer, series and shunt resistance, back and front contact materials, radiation and Auger recombination of the absorber layer, reflection losses on the efficiency of the proposed cell is analysed. The drastic reduction in all PV parameters was observed under non-ideal conditions and the PV parameters are V<sub>oc</sub> (1.22 V), J<sub>sc</sub> (2.904 mA/cm<sup>2</sup>), FF (86.3), and PCE of 3.06%. The charge kinetics such as impedance, conductivity, and capacitance plots, and possible reasons for reductions in PV parameters are discussed in detail. Materials science ; Quantum dot ; Auger effect ; Optoelectronics ; Solar cell ; Band gap ; Open-circuit voltage ; Graphene ; Auger ; Voltage ; Physics ; Nanotechnology ; Atomic physics ; Quantum mechanics Quantum Dots Synthesis And Properties ; ZnO doping and properties ; Ga2O3 and related materials
Authors: Kun Wei | Jian-Hong Duan | He Qi | Linzhao Ma | Qianbiao Du | Huifen Yu | Haoyu Wang | Xiaoming Shi | Gaosheng Li | Zhikang Shuai | Hao Li
Source: Nature Communications (article, 2025-08-22)
Field: Materials Science — Materials Chemistry

Collaborative design of polarization and antiferrodistortion configurations in high energy capacitive relaxor ferroelectrics Lead-free relaxor ferroelectrics have been regarded as superior candidates for dielectric energy storage applications. Nonetheless, the degradation of energy storage performance resulted from the trade-off between high polarization and low hysteresis in RFEs under superhigh electric fields has become a bottleneck. Here, a chemical framework is established based on NaNbO<sub>3</sub>-based RFEs, bridging atomic-scale structural control to realize excellent energy storage performance. The framework design leads to unique local lattice distortion with both inhomogeneous polarization and antiferrodistortion configurations, including locally disordered polarization distribution, continuous polarization deflection and the co-existence of ordered and disordered oxygen octahedral tilts, as confirmed by phase-field simulation and scanning transmission electron microscopy. As a result, negligible polarization switching hysteresis as well as the large and delayed saturated polarization simultaneously contribute to the excellent energy storage performance. For instance, two NaNbO<sub>3</sub>-based RFEs with different compositions show ultrahigh recoverable energy densities of 16.48 and 20.08 J cm<sup>-3</sup>, respectively, as well as near-zero energy loss (η ~ 90.38% and 95.09%). This work presents new avenues toward designing high-performance lead-free RFEs. Capacitive sensing ; Materials science ; Polarization (electrochemistry) ; Relaxor ferroelectric ; High energy ; Condensed matter physics ; Engineering physics ; Nanotechnology ; Optoelectronics ; Ferroelectricity ; Computer science ; Physics ; Chemistry ; Dielectric ; Physical chemistry Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Dielectric materials and actuators
Authors: Muhammad Mohsin Altaf | Sahrish Ashraf | Muhammad Qaisar Naeem Khan | Xiaoyan Sun | Dong Li | Mohamed A. El‐Sheikh | Shunqing Xu | Zhiqiang Zhu
Source: Biochar (article, 2025-05-07)
Field: Chemistry — Inorganic Chemistry

Effectiveness of sulfur-modified wheat straw biochar in alleviating vanadium stress in rice: impacts on growth, photosynthesis, and redox regulation Abstract Vanadium (V) is recognized as an environmental contaminant that adversely affects plant growth and development. The main objective of this study was to investigate the effects of sulfur-modified biochar (SBC) compared to standard biochar (BC) on rice under V suppression (35 mg L −1 ). Our findings revealed that V stress significantly suppressed rice seedling growth, evidenced by reductions in shoot fresh weight, chlorophyll pigment content, photosynthetic assimilation, and root attributes, with higher V accumulation observed in both shoots and roots of V-stressed plants compared to BC- and SBC-treated plants. SBC application improved rice growth more effectively than BC, exhibiting increases of 61.41% in fresh weight, 63.04% in root length, 66.66% in chlorophyll a, 52.20% in chlorophyll b, and 52.95% in carotenoids, alongside enhanced gas exchange attributes. Notably, SBC reduced V accumulation by 58.33% in shoots and 43.79% in roots compared to V-stressed plants. SBC also induced V stress tolerance in rice by elevating antioxidant enzyme activities in roots and shoots, including superoxide dismutase (SOD, 85.25/89.41%), catalase (CAT, 119.04/100.01%), glutathione peroxidase (GPX, 82.20/79.82%), glutathione S-transferase (GST, 123.74/114.67%), ascorbate peroxidase (APX, 86.56/63.74%), glutathione reductase (GR, 204.87/60.36%), dehydroascorbate reductase (DHAR, 53.60/62.06%), and monodehydroascorbate reductase (MDHAR, 87.09/88.88%), while simultaneously reducing hydrogen peroxide (H 2 O 2 ) and malondialdehyde (MDA) levels. Furthermore, SBC increased the activities of glyoxalase enzymes (Gly I by 96.15/77.14% and Gly II by 115.78/104.25%), mitigating methylglyoxal (MG) induced toxicity, and enhanced the expression of metal-tolerant ( OsFSD1 ) genes and antioxidant-glyoxalase systems. Overall, SBC application was found to be more effective than raw BC in alleviating V-induced toxic effects and improving rice plant growth. Nonetheless, further studies must be performed to determine exactly driving mechanism involved in the promotion of growth. Graphical Abstract Biochar ; Vanadium ; Sulfur ; Photosynthesis ; Straw ; Redox ; Rice straw ; Biomass (ecology) ; Agronomy ; Chemistry ; Inorganic chemistry ; Biology ; Pyrolysis ; Biochemistry Vanadium and Halogenation Chemistry ; Fluoride Effects and Removal ; Mercury impact and mitigation studies
Authors: Kinga Nagy | Péter Sándor | Károly Vékey | László Drahos | Ágnes Révész
Source: Journal of the American Society for Mass Spectrometry (article, 2025-01-13)
Field: Chemistry — Spectroscopy

The Enzyme Effect: Broadening the Horizon of MS Optimization to Nontryptic Digestion in Proteomics In recent years, alternative enzymes with varied specificities have gained importance in MS-based bottom-up proteomics, offering orthogonal information about biological samples and advantages in certain applications. However, most mass spectrometric workflows are optimized for tryptic digests. This raises the questions of whether enzyme specificity impacts mass spectrometry and if current methods for nontryptic digests are suboptimal. The success of peptide and protein identifications relies on the information content of MS/MS spectra, influenced by collision energy in collision-induced dissociation. We investigated this by conducting LC-MS/MS measurements with different enzymes, including trypsin, Arg-C, Glu-C, Asp-N, and chymotrypsin, at varying collision energies. We analyzed peptide scores for thousands of peptides and determined optimal collision energy (CE) values. Our results showed a linear <i>m</i>/<i>z</i> dependence for all enzymes, with Glu-C, Asp-N, and chymotrypsin requiring significantly lower energies than trypsin and Arg-C. We proposed a tailored CE selection method for these alternative enzymes, applying ca. 20% lower energy compared to tryptic peptides. This would result in a 10-15 eV decrease on a Bruker QTof instrument and a 5-6 NCE% (normalized collision energy) difference on an Orbitrap. The optimized method improved bottom-up proteomics performance by 8-32%, as measured by peptide identification and sequence coverage. The different trends in fragmentation behavior were linked to the effects of C-terminal basic amino acids for Arg-C and trypsin, stabilizing y fragment ions. This optimized method boosts the performance and provides insight into the impact of enzyme specificity. Data sets are available in the MassIVE repository (MSV000095066). Chemistry ; Proteomics ; Enzyme ; Digestion (alchemy) ; Chromatography ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Protein purification and stability
Authors: Zhaoxiang Cai | Emma L. Boys | Zainab Noor | Adel T. Aref | Dylan Xavier | Natasha Lucas | Steven G. Williams | Jennifer M.S. Koh | Rebecca C. Poulos | Yangxiu Wu | Michael Dausmann | Karen L. MacKenzie | Adriana Aguilar‐Mahecha | Carolina Armengol | Maria M. Barranco | Mark Basik | Elise D. Bowman | Roderick Clifton‐Bligh | Elizabeth A. Connolly | Wendy A. Cooper | Bhavik Dalal | Anna DeFazio | Martin Filipits | Peter Flynn | J. Dinny Graham | Jacob George | Anthony J. Gill | Michael Gnant | Rosemary Habib | Curtis C. Harris | Kate Harvey | Lisa G. Horvath | Christopher C. Jackson | Maija R.J. Kohonen‐Corish | Elgene Lim | Jia Liu | Georgina V. Long | Reginald V. Lord | Graham J. Mann | Geoffrey W. McCaughan | Lucy Morgan | Leigh C. Murphy | Sumanth Nagabushan | Adnan Nagrial | Jordi Navinés | Benedict Panizza | Jaswinder S. Samra | Richard A. Scolyer | John Souglakos | Alexander Swarbrick | David M. Thomas | Rosemary L. Balleine | Peter G. Hains | Phillip J. Robinson | Qing Zhong | Roger R. Reddel
Source: Cancer Discovery (article, 2025-06-09)
Field: Chemistry — Spectroscopy

Federated Deep Learning Enables Cancer Subtyping by Proteomics A federated deep learning approach applied to human proteomic data, acquired using two distinct proteomic technologies from 40 tumor cohorts across eight countries, enabled accurate cancer histopathologic subtyping while preserving data privacy. This approach will enable the privacy-compliant development of large-scale proteomic artificial intelligence models, including foundation models, across institutions globally. Computer science ; Generalizability theory ; Subtyping ; Replicate ; Biomedicine ; Machine learning ; Artificial intelligence ; Matching (statistics) ; Data mining ; Bioinformatics ; Medicine ; Biology Advanced Proteomics Techniques and Applications ; Cancer Genomics and Diagnostics ; Privacy-Preserving Technologies in Data
Authors: Azeez Ahamed | Piumantha Samaranayake | Visal de Silva | Muhammad Raziq Rahimi Kooh | N. Wickramage | Indu Rajapaksha | Roshan Thotagamuge
Source: Molecules (article, 2025-02-14)
Field: Materials Science — Materials Chemistry

Unveiling the pH-Responsive Mechanisms of the Carbon Dot–Proximicin-A Peptide Conjugate for Targeted Cancer Therapy Using Density Functional Theory This study investigates the pH-responsive dissociation mechanism of carbon dot (CD) conjugated with the anticancer peptide proximicin-A (PROXI) using density functional theory (DFT) simulations. The CD@PROXI system, designed for targeted cancer therapy, releases the drug in acidic environments typical of cancer sites. DFT simulations, with the B3LYP-D3BJ functional and 6-311G (d, p) basis set, optimized the conjugate's geometry under neutral and acidic conditions. The focus was on the pH-sensitive C=N bond, existing in two protonation states. Key parameters evaluated included the HOMO-LUMO gap, bond length, IR spectroscopy, non-covalent interaction (NCI), electron localization function (ELF), density of states (DOSs), and electrostatic potential (ESP). Under neutral pH, the system showed stability with a HOMO-LUMO gap of 3.22 eV, indicating low reactivity. In acidic pH, this gap decreased to 0.40 eV, suggesting higher reactivity and potential for drug release. IR spectroscopy indicated weakened C=N bonds in acidic conditions, with bond length increasing from 1.288 Å to 1.324 Å. NCI analysis revealed increased van der Waals interactions, supporting bond weakening. ELF analysis showed electron localization at reactive sites, while DOS profiles and ESP maps highlighted distinct electronic states and potential dissociation regions in acidic conditions. These findings confirm the potential of CD@PROXI for targeted cancer therapy, with drug release triggered by the acidic tumor microenvironment. Conjugate ; Peptide ; Cancer ; Cancer therapy ; Chemistry ; Carbon fibers ; Density functional theory ; Combinatorial chemistry ; Nanotechnology ; Medicine ; Biochemistry ; Materials science ; Computational chemistry ; Internal medicine ; Mathematics Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Nanocluster Synthesis and Applications
Authors: Yanhua Li | Gangwei Jiang | Junliang Zhou | Ling Shi | Lin Yuan
Source: Chemistry - An Asian Journal (review, 2025-01-01)
Field: Chemistry — Organic Chemistry

Recent Advances in Enzyme‐Activated Dual‐Locked Probes for Biological Applications Enzymes catalyze reactions involved in diverse physiological, pathological, and pharmacological processes. By employing the optical probe, fluorescence imaging enables non-invasive, real-time detection and assessment of disease states based on enzymatic activity. However, most enzyme-activated probes are single-locked probes that respond to a single biomarker. In comparison to single-locked probes, enzyme-activated dual-locked probes can effectively minimize the occurrence of false-positive signals, circumvent the problem of low specificity associated with biologically active substances, and facilitate precise imaging. This review systematically summarizes the design and application of dual-locked probes in disease diagnosis, with the aim of providing inspiration for researchers in the field. Enzyme ; Biomarker ; Nanotechnology ; Dual (grammatical number) ; Dual role ; Fluorescence ; Computational biology ; Chemistry ; Biochemistry ; Combinatorial chemistry ; Materials science ; Biology ; Physics ; Optics Click Chemistry and Applications ; Nanoplatforms for cancer theranostics ; Lanthanide and Transition Metal Complexes