jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Liudy García Hernández | Dai L | Arielis Rodríguez‐Ulloa | Ying Yi | Luis Javier González | Vladimir Besada | Wen Li | Yasser Perera
Source: Biological Chemistry (article, 2025-03-01)
Field: Chemistry — Spectroscopy

Time- and dose-dependent effects of CIGB-300 on the proteome of lung squamous cell carcinoma Proteome-wide scale in a dose- and time-depending setting is crucial to fully understand the pharmacological mechanism of anticancer drugs as well as identification of candidates for drug response biomarkers. Here, we investigated the effect of the CIGB-300 anticancer peptide at IC<sub>50</sub> and IC<sub>80</sub> doses during 1 and 4 h of treatment on the squamous lung cancer cell (NCI-H226) proteome. An overwhelming dose-dependent inhibitory effect with minor up-regulated proteins was observed by increasing CIGB-300 dose level. Functional enrichment was also CIGB-300 dose-dependent with common or exclusively regulated proteins in each dose and time settings. A protein core involving small molecule biosynthesis, aldehyde metabolism and metabolism of nucleobases was regulated irrespectively to the dose or the treatment time. Importantly, a group of proteins linked to NSCLC tumor biology, poor clinical outcome and some Protein Kinase CK2 substrates, were significantly regulated by treating with both CIGB-300 doses. Likewise, we observed a consistent downregulation of different proteins that had been already reported to be inhibited by CIGB-300 in lung adenocarcinoma and acute myeloid leukemia. Overall, our proteomics-guided strategy based on time and drug dose served to uncover novel clues supporting the CIGB-300 cytotoxic effect and also to identify putative pharmacodynamic biomarkers in NSCLC. Proteome ; Cancer research ; Downregulation and upregulation ; Lung cancer ; Proteomics ; Chemistry ; Kinase ; Drug ; Pharmacology ; Biology ; Medicine ; Oncology ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Ubiquitin and proteasome pathways ; Chemical Synthesis and Analysis
Authors: Yashwardhan Singh Chandrawat, Khemraj Beragi
Source:  (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

SINE COSINE OPTIMIZATION-BASED APPROACH FOR OPTIMIZING THERMOELECTRIC MODULES IN WASTE HEAT RECOVERY SYSTEMS In this paper, the topic of thermoelectric modules (TEMs) optimization in waste heat recovery systems is&nbsp;discussed, and it is addressed on the optimization of power to the maximum and efficiency to the optimum. The&nbsp;new strategy of employing the Sine Cosine Optimization (SCO) algorithm is proposed to optimize the most&nbsp;important parameters of TEMs, including length and cross-sectional area of thermoelectric legs. The objective of&nbsp;the study is to overcome the drawback of the conventional optimization methods, which include the Genetic&nbsp;Algorithms (GA) and Particle Swarm Optimization (PSO), as they are time-consuming and inconvenient with&nbsp;respect to making real-time changes. Using dynamic adjustment of the dimension of thermoelectric legs according&nbsp;to certain temperature gradients, SCO algorithm will help to improve the functionality of TEMs in reality. The&nbsp;simulation results indicate that the SCO-optimized TEM is superior to the base TEM, giving it power generation&nbsp;enhancing results, where the output becomes 33% more with optimal current amounts. The study is a suggestive&nbsp;solution to the enhancement of thermoelectric waste heat recovery systems effectiveness and fastidiousness.&nbsp; Sine ; Trigonometric functions ; Thermoelectric effect ; Thermoelectric generator ; Waste heat recovery unit ; Process engineering ; Non-sinusoidal waveform ; Materials science ; Computer science ; Environmental science ; Mathematics ; Engineering ; Mechanical engineering ; Physics ; Electrical engineering ; Thermodynamics ; Waveform ; Heat exchanger ; Voltage Advanced Thermoelectric Materials and Devices
Authors: Akbar Mirzaei | A. Ghadiri | Ali Mazaheri
Source: Mavādd-i pīshraftah dar muhandisī (article, 2025-10-01)
Field: Materials Science — Biomaterials

Investigating the Effect of Bentonite Heat Treatment Cycle on the Properties of Iron Ore Pellets Introduction and Objectives: The quality of produced pellets is directly dependent on the physicochemical properties of the bentonite used. This research aims to investigate the effect of heat treatment on the characteristics of bentonite and to evaluate the properties of the obtained raw and fired pellets.Materials and Methods: In this study, the impact of heat treatment on the properties of bentonite, as a binder additive in a pelletizing unit, was investigated. A sample of sodium bentonite from South Khorasan mines was selected as the raw material. Following thermal analyses, temperatures of 400, 800, and 1300 °C were chosen as heat treatment temperatures. X-ray diffraction (XRD), elemental analysis, and scanning electron microscopy (SEM) were employed to analyze the phase and structural characteristics of the samples after heat treatment. Water absorption, swelling percentage of the samples, and the properties of pellets produced from the heat-treated bentonite were examined to assess the effect of heat treatment on bentonite properties.Results: The results indicated that heat treatment led to structural and phase changes in bentonite. SEM images of raw bentonite revealed that the particle morphology and porosity of bentonite changed with increasing heat treatment temperature. Furthermore, the zeta potential test was utilized to compare the electrical potential difference between the layers of the samples. The results showed that heat-treated bentonite particles at 400 °C exhibited a lower tendency to settle.Conclusion: The results of this study declared that heat treatment up to 400 °C improved the properties of bentonite and the obtained pellets. Bentonite ; Pellets ; Pelletizing ; Raw material ; Zeta potential ; Particle size ; Porosity ; Scanning electron microscope Clay minerals and soil interactions ; Iron and Steelmaking Processes ; Recycling and utilization of industrial and municipal waste in materials production
Authors: Bin Zhou | Jiawei He | Peiqing Guo | Jianan Lin | Feng Shou | Hao Yin | Qirui Sun | Hongjun Zhou | Yanxiong Wu | Fanxin Zeng
Source: Research Square (preprint, 2025-07-10)
Field: Materials Science — Biomaterials

Method for dividing the static parameters of nailfold capillary: Improving measurement accuracy Capillary action ; Computer science ; Statistics ; Mathematics ; Materials science ; Composite material Silk-based biomaterials and applications ; Spectroscopy Techniques in Biomedical and Chemical Research
Source: REST Journal on Data Analytics and Artificial Intelligence (article, 2025-11-27)
Field: Chemistry — Analytical Chemistry

Advancing Scalar-on-Function Regression: A Functional Data Analysis Approach to Basis Selection and Truncation Optimization The study Functional Data Analysis (FDA) has emerged as a critical framework for analyzing data with inherent smoothness, enabling insights beyond classical statistical methods. This paper focuses on the scalar-on-function regression paradigm, where the predictor is a functional variable, necessitating specialized methodologies due to the infinite-dimensional nature of the coefficient function. We introduce and compare two key approaches for transforming this infinite-dimensional problem into a finite-dimensional one: basis expansion and Functional Principal Component Regression (FPCR). Both techniques rely on a truncation parameter to approximate the coefficient function, a crucial element that influences model performance. Through theoretical exploration and Monte Carlo simulations, we examine strategies for optimal truncation parameter selection using cross-validation. Finally, we apply these insights to predict octane numbers of gasoline samples from Near-Infrared (NIR) absorption spectra, showcasing the practical implications of functional regression in real-world applications. Limitations and potential extensions are discussed, paving the way for future research into robust and adaptive FDA methodologies. Functional principal component analysis ; Truncation (statistics) ; Principal component analysis ; Functional data analysis ; Basis (linear algebra) ; Monte Carlo method ; Regression analysis ; Selection (genetic algorithm) ; Component (thermodynamics) Spectroscopy and Chemometric Analyses ; Statistical Methods and Inference ; Machine Learning in Materials Science
Authors: Wenrong Chen | John M. Elizarraras | Fenglong Jiao | Lan Huang | Bing Zhang
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-07-23)
Field: Chemistry — Spectroscopy

XL-Ranker: A Computational Workflow for Prioritizing Protein-Protein Interactions from Cross-Linking Mass Spectrometry Data Protein-protein interactions (PPIs) are central to virtually all biological processes, and their disruption can lead to a wide spectrum of human diseases. Cross-linking mass spectrometry (XL-MS) enables proteome-scale detection of interacting peptide pairs, from which PPIs can be inferred. However, interpretating XL-MS data to assign homologous cross-linked peptide pairs to specific protein interactions can be challenging. A major hurdle arises when a single peptide can map to multiple proteins, and when two such peptides are paired, the number of possible protein-protein interactions increases combinatorially. This mapping ambiguity can lead to inflated interaction networks that could compromise downstream analysis and biological interpretation. However, this problem has often been overlooked or addressed using heuristic approaches in previous XL-MS studies. To tackle this challenge, we developed XL-Ranker, a computational framework that combines a set cover graph algorithm and machine learning to systematically resolve peptide-mapping ambiguity and infer high-confidence PPIs from XL-MS data. Applied to an XL-MS dataset from HEK293 cells, XL-Ranker identified a high-confidence network with 880 PPIs involving 964 unique genes. Among all possible PPIs, the ones selected by XL-Ranker for inclusion in the final network had significantly higher interaction scores in the STRING database than the excluded ones. Network analysis further demonstrated that these interactions form biologically meaningful clusters, supporting the accuracy of our approach. In summary, XL-Ranker provides a practical solution to a key analytical challenge in XL-MS data interpretation, enhancing the reliability of PPI discovery. Computational biology ; Workflow ; Proteome ; Computer science ; Ambiguity ; Interaction network ; Data mining ; Proteomics ; Chemistry ; Bioinformatics ; Biology ; Biochemistry ; Database ; Gene Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Biotin and Related Studies
Authors: Tania Hernández Fariñas | Lourenço Ribeiro | Simon Oiry | Guozhen Du | Vanda Brotas | Laurent Barillé
Source: SSRN Electronic Journal (preprint, 2025-01-01)
Field: Materials Science — Biomaterials

Using Niche Analysis as a Foundation for a New Diatom-Based Biotic Index in Transitional Waters Benthic zone ; Bioindicator ; Ecological niche ; Niche ; Intertidal zone ; Habitat ; Primary producers ; Ecosystem ; Estuary Diatoms and Algae Research
Authors: Anton A. A. Autzen | Sabine Beuermann | Marco Drache | Christopher M. Fellows | Simon Harrisson | Alex M. van Herk | Robin A. Hutchinson | Atsushi Kajiwara | Daniel J. Keddie | Bert Klumperman | Gregory T. Russell
Source: Pure and Applied Chemistry (article, 2025-09-25)
Field: Chemistry — Organic Chemistry

Experimental methods and data evaluation procedures for the determination of radical copolymerization reactivity ratios from composition data (IUPAC Recommendations 2025) Abstract This recommendation defines the preferred methodology for determining reactivity ratios from copolymer composition data using the terminal model for radical copolymerization. The method is based on measuring conversion ( X ) and copolymer composition ( F ) of three or more copolymerization reactions conducted with different initial monomer compositions ( f 0 ). Both low and high conversion experiments can be combined, or alternatively only low conversion experiments can be used. The method provides parameter estimates, but can also reveal deviations from the terminal model and the presence of systematic errors in the measurements. Special attention is given to error estimation in F and construction of the joint confidence interval for the reactivity ratios. Previous experiments measuring f 0 − F (i.e., copolymer composition as a function of varying f 0 ) or f − X (i.e., how f varies with X in an experiment) can also be analyzed with this IUPAC recommended method. The influence of systematic errors in the measurements on the reactivity ratio determinations is addressed. The document has a broad significance in that it seeks to eradicate the use of incorrect methods and common mistakes in determining reactivity ratios in radical copolymerizations. Reactivity (psychology) ; Copolymer ; Composition (language) ; Monomer ; Systematic error ; Function (biology) Chemistry and Stereochemistry Studies ; Analytical Chemistry and Chromatography ; Radioactive element chemistry and processing
Authors: Nina Javerzat | Éric Bertin | Misaki Ozawa
Source: SciPost Physics (article, 2025-04-10)
Field: Materials Science — Materials Chemistry

Rényi complexity in mean-field disordered systems Configurational entropy, or complexity, plays a critical role in characterizing disordered systems such as glasses, yet its measurement often requires significant computational resources. Recently, Rényi entropy, a one-parameter generalization of Shannon entropy, has gained attention across various fields of physics due to its simpler functional form, making it more practical for measurements. In this paper, we compute the Rényi version of complexity for prototypical mean-field disordered models, including the random energy model, its generalization, referred to as the random free energy model, and the p <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>p</mml:mi> </mml:math> -spin spherical model. We first demonstrate that the Rényi complexity with index m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>m</mml:mi> </mml:math> is related to the free energy difference for a generalized annealed Franz-Parisi potential with m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>m</mml:mi> </mml:math> clones. Detailed calculations show that for models having one-step replica symmetry breaking (RSB), the Rényi complexity vanishes at the Kauzmann transition temperature T_K <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>T</mml:mi> <mml:mi>K</mml:mi> </mml:msub> </mml:math> , irrespective of m&amp;gt;1 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>m</mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> , while RSB solutions are required even in the liquid phase. This study strengthens the link between Rényi entropy and the physics of disordered systems and provides theoretical insights for its practical measurements. Field (mathematics) ; Statistical physics ; Computer science ; Mathematics ; Physics ; Pure mathematics Material Dynamics and Properties ; Random lasers and scattering media ; Theoretical and Computational Physics
Authors: Amy J. Thompson | James Beilsten‐Edmands | Chi‐Pan Tam | Juan Sánchez-Weatherby | James Sandy | Halina Mikolajek | Danny Axford | Sofia Jaho | Michael A. Hough | Graeme Winter
Source: Acta Crystallographica Section D Structural Biology (article, 2025-05-29)
Field: Materials Science — Materials Chemistry

Enhanced intensity-based clustering of isomorphous multi-crystal data sets in the presence of subtle variations Multi-crystal processing of X-ray diffraction data has become highly automated to keep pace with the current high-throughput capabilities afforded by beamlines. A significant challenge, however, is the automated clustering of such data based on subtle differences such as ligand binding or conformational shifts. Intensity-based hierarchical clustering has been shown to be a viable method of identifying such subtle structural differences, but the interpretation of the resulting dendrograms is difficult to automate. Using isomorphous crystals of bovine, porcine and human insulin, the existing clustering methods in the multi-crystal processing software xia2.multiplex were validated and their limits were tested. It was determined that weighting the pairwise correlation coefficient calculations with the intensity uncertainties was required for accurate calculation of the pairwise correlation coefficient matrix (correlation clustering) and dimension optimization was required when expressing this matrix as a set of coordinates representing data sets (cosine-angle clustering). Finally, the introduction of the OPTICS spatial density-based clustering algorithm into DIALS allowed the automatic output of species-pure clusters of bovine, porcine and human insulin data sets. Cluster analysis ; Correlation clustering ; Pairwise comparison ; Computer science ; Software ; Correlation coefficient ; Similarity (geometry) ; Crystal (programming language) ; Data set ; Biological system ; Pattern recognition (psychology) ; Mathematics ; Data mining ; Artificial intelligence ; Biology ; Machine learning Enzyme Structure and Function ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Sebastian Wlaźlak | Mirosław Banaszak | Jakub Biesek
Source: BMC Veterinary Research (article, 2025-05-02)
Field: Materials Science — Biomaterials

Halloysite supplemented in the diet, and sex of Cherry Valley ducks affects growth, carcass composition, meat quality, and jejunum and leg bone strength Halloysite adversely impacted ducks' body weight and weight gain while altering meat quality by increasing pectoral muscle pH (pectoralis major) and fat content (pectoralis major and pectoralis minor) and changing leg muscles' color. Jejunum tensile strength was higher post-halloysite supplementation. These results suggest halloysite has both positive and negative effects on duck growth, meat properties, and jejunum strength, warranting further research. Jejunum ; Composition (language) ; Biology ; Animal science ; Food science ; Bone development ; Veterinary medicine ; Medicine ; Endocrinology Clay minerals and soil interactions ; Soil and Unsaturated Flow ; Soil Management and Crop Yield
Authors: Lu Liu | P. Cheng | Hao Xue | Lingsong Zhang | Na Liu | Zhilin Yang | Fansheng Meng
Source: Sustainability (article, 2025-12-27)
Field: Materials Science — Biomaterials

Development and Validation of a Benthic Diatom Index of Biotic Integrity (BD-IBI) for Ecosystem Health Assessment in the Songhua River Basin The Songhua River, as the third-largest river in China, has garnered increasing attention for its ecological health. This study established a water ecological health assessment system for the Songhua River Basin based on the BD-IBI. Through a comprehensive analysis, including distribution range analysis, discriminant ability analysis, and correlation analysis, 97 candidate indicators were evaluated. Among these, IDSE Leclercq (IDSE), Indice Diatomique Artois Picardie (IDAP), RA. motile individuals, RA. ß-mesosaprobic, and RA. polysaprobe were selected as the core indicators for BD-IBI construction in the Songhua River Basin. The water ecological health status of the Songhua River Basin was categorized into five levels. Furthermore, environmental factors influencing BD-IBI and water quality were analyzed using box plot analysis, redundancy analysis (RDA), and multiple linear regression model. The results indicated that while the Songhua River Basin exhibits an overall “Good” water ecological health, marked heterogeneity exists across sub-reaches. Specifically, the Tangwang River exhibited the highest BD-IBI score, while the Woken River showed the lowest score. Key water quality factors driving BD-IBI changes include DO, EC, NN, TN, TP and QHEI. These findings provide a valuable reference for the assessment and restoration of water ecological environment quality in the Songhua River Basin, promoting the sustainable development of aquatic ecosystems. Water quality ; Drainage basin ; Health assessment ; Benthic zone ; Hydrology (agriculture) ; Ecosystem health ; Aquatic ecosystem ; Ecological health ; Ecological assessment Diatoms and Algae Research ; Freshwater macroinvertebrate diversity and ecology ; Water Quality and Pollution Assessment
Authors: Paulo Quispe | Pedro Bertemes-Filho
Source: BIO Web of Conferences (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Towards a Feasible and Robust Technique for Non-invasive Food Analysis Growing requirements for food safety have driven the development of non-invasive monitoring technologies. Among these, electrical bioimpedance (BIA) has emerged as a method for assessing freshness, composition, and adulteration while preserving sample integrity. This work presents a systematic analysis of 259 Scopus-indexed publications from the last 10 years in order to strength and encourage new agricultural applications on food analysis. It was found 21 works on food quality using bioimpedance spectroscopy (BIA), which is the most non-destructive analysis. Due to measurement variability caused by product heterogeneity and environmental factors, standardizing protocols, accurate hardware designs and machine learning (ML) technique are the keys factors towards a feasible BIA system. It was also observed that portability will improve the supply chain management by enabling real-time quality control. It can be concluded that BIA data with ML is a robust and safe tool for the daily basis of consumers, farmers and industry, while supporting industry requirements for sustainable and efficient operations. Software portability ; Quality (philosophy) ; Product (mathematics) ; Sample (material) ; Food supply ; Supply chain ; Work (physics) ; Food industry Spectroscopy and Chemometric Analyses ; Electrical and Bioimpedance Tomography ; Food Drying and Modeling
Authors: Muhammad Amir | Rizwan Aslam Butt | Saqib Jamshed Rind | M. Waqas
Source: Polimery (article, 2025-12-03)
Field: Materials Science — Polymers and Plastics

Advanced algorithmic laser measurement system for seam pucker assessment A cost-effective laser measurement system was designed to convert fabric seam deformations into electrical signals. Three algorithms were developed: (i) extracting one-dimensional electrical signals from two-dimensional images; (ii) identifying peaks and valleys in these signals corresponding to changes in puckering; and (iii) introducing a new index for measuring seam puckering — the Pucker Index (PI). To validate the system, various lightweight woven fabrics susceptible to seam puckering were sewn using two types of core threads, T1 and T2, while maintaining constant machine settings to ensure uniform seams. A strong R-index correlation of 0.86 for T1 and 0.88 for T2 was demonstrated between the proposed PI values and manually assigned pucker grades (PG), according to the AATCC-88B seam puckering assessment standard. Moreover, in the paired t-test, the p-values for fabric samples sewn with T1 and T2 threads were less than the significance level of 0.05, indicating a statistically significant difference between the PG and PI values in both cases. Laser ; System of measurement ; Core (optical fiber) ; Significant difference ; Index (typography) ; Measure (data warehouse) Textile materials and evaluations ; Advanced Sensor and Energy Harvesting Materials ; Industrial Vision Systems and Defect Detection