jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Umesh Maske | Quadri Mohammed Soheb | Giri Nk
Source: International Journal of Research Publication and Reviews (review, 2025-06-01)
Field: Materials Science — Biomaterials

A Review on Targeted Drug Delivery Systems in Cancer Therapy: Challenges and Future Directions Cancer remains one of the leading causes of morbidity and mortality worldwide, prompting the need for more effective and less toxic treatment strategies.Traditional chemotherapy, while effective in many cases, is often associated with systemic toxicity, non-specific distribution, and multidrug resistance.In response, targeted drug delivery systems (TDDS) have emerged as a promising approach to enhance the therapeutic index of anticancer agents by selectively directing drugs to tumor cells while minimizing exposure to healthy tissues.This review explores the various types of targeted delivery mechanisms-including passive targeting via the enhanced permeability and retention (EPR) effect, active targeting using ligands such as antibodies or aptamers, and stimuli-responsive systems that release drugs in response to pH, temperature, enzymes, or redox conditions within the tumor microenvironment.The paper also highlights nanocarriers such as liposomes, dendrimers, polymeric nanoparticles, and micelles that serve as versatile platforms for targeted delivery.Despite promising preclinical and clinical results, challenges such as heterogeneous tumor vasculature, immune clearance, limited tumor penetration, and the high cost of production remain significant barriers to widespread clinical translation.Moreover, the dynamic and adaptive nature of the tumor microenvironment often reduces the efficacy of otherwise well-designed carriers.Future directions focus on personalized medicine, multifunctional nanocarriers, and smart delivery systems integrated with real-time imaging and diagnostic capabilities to enable theranostics.Advances in tumor biology, material science, and bioengineering are expected to synergize for the development of nextgeneration targeted therapies.This review concludes that overcoming existing limitations through multidisciplinary collaboration is crucial for the successful implementation of TDDS in clinical oncology. Drug delivery ; Medicine ; Cancer ; Cancer therapy ; Drug ; Cancer drugs ; Targeted drug delivery ; Intensive care medicine ; Medical physics ; Pharmacology ; Nanotechnology ; Internal medicine ; Materials science Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery ; Computational Drug Discovery Methods
Authors: M. Raja | SSivalakshmi | TBalusamy | MSudharshan | TGopalakrishnan | D. Simon
Source:  (preprint, 2025-07-29)
Field: Materials Science — Polymers and Plastics

Heat Transfer Studies on Sodium based PCM Infused Mattress Temperature is a crucial factor influencing the quality of sleep, as it directly affects thermal comfort during sleep. The present work reports the investigation of the thermal performance of high-density (HDF) and low-density (LDF) polyurethane foam Heat transfer ; Sodium ; Transfer (computing) ; Materials science ; Environmental science ; Chemistry ; Thermodynamics ; Computer science ; Physics ; Parallel computing ; Metallurgy Natural Fiber Reinforced Composites ; Phase Change Materials Research
Authors: Banu Özgen Keleş | Elif Yılmaz
Source: Uludağ University Journal of The Faculty of Engineering (article, 2025-07-30)
Field: Materials Science — Polymers and Plastics

INVESTIGATION AND MODELING OF THE BAGGING PROPERTIES OF KNITTED FABRICS MADE FROM RECYCLED YARNS The primary objective of this study is to investigate the bagging behavior of knitted fabrics produced from various fiber blends—namely recycled cotton/recycled polyester, recycled cotton/polyester, cotton/polyester, recycled cotton/acrylic, and cotton/acrylic—and to evaluate their suitability for home wear applications. The study further aims to compare these fabrics with those produced from virgin yarns and to model their bagging properties using artificial neural networks (ANNs). A total of 15 knitted fabric samples were produced using both recycled and virgin yarns in three different fabric structures: single jersey, rib, and interlock. The bagging performance of the fabrics was assessed through key parameters, including bagging hysteresis percentage, bagging fatigue percentage, residual bagging hysteresis percentage, and bagging resistance. Statistical analysis of the test results revealed that, depending on the yarn composition and fabric structure, the incorporation of recycled fibers in yarns led to improvements in certain bagging properties. These improvements were observed across all fabric types and knitting structures. Additionally, the ANN-based modeling demonstrated high accuracy in predicting the bagging behavior of recycled knitted fabrics, thereby offering a valuable tool for optimizing fabric design before production. Materials science ; Composite material Textile materials and evaluations ; Mechanical Engineering and Vibrations Research
Authors: Vrinda Kalia | Katherine E. Manz | Jaime Benavides | Suhang Song | Brandi Vollmer | Beizhan Yan | Jeff Goldsmith | Kurt D. Pennell | Yaakov Stern | Marianthi‐Anna Kioumourtzoglou | Gary W. Miller | Christian Habeck | Yian Gu
Source: medRxiv (preprint, 2025-10-19)
Field: Chemistry — Analytical Chemistry

Mixture of organic pollutants is associated with cognitive aging Abstract INTRODUCTION Environmental organic pollutants impact brain function and cognitive aging, but the effects of real-world complex mixtures of these pollutants is unexplored. METHODS Using data collected at two time points from 170 cognitively normal adults, we used hierarchical Bayesian kernel machine regression to examine the association between joint exposure to 49 organic pollutants and latent variables, derived from neuropsychological tests, that capture key aspects of cognitive aging. RESULTS We observed a non-linear, inverted U-shaped relationship between the pollutant mixture and the global cognitive score. Polychlorinated biphenyls (PCBs) were the most important pollutant group in the mixture followed by industrial-use pollutants. DISCUSSION Exposure to a mixture of organic pollutants was associated with poor cognitive aging. Even though many of these pollutants, like PCBs, have been banned for decades, they persist in our environment. Strategies to reduce exposure to these organic pollutants are needed to minimize their impact on cognitive aging. Pollutant ; Cognition ; Organic chemicals ; Neuropsychology ; Kernel (algebra) Dye analysis and toxicity
Authors: Marco Reverenna | Maike Wennekers Nielsen | Darian S. Wolff | Elpida Lytra | Pasquale Colaianni | Anne Ljungars | Andreas H. Laustsen | Erwin M. Schoof | Jeroen Van Goey | Timothy P. Jenkins | Marie V. Lukassen | Alberto Santos | Konstantinos Kalogeropoulos
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-07-31)
Field: Chemistry — Spectroscopy

Generalizable direct protein sequencing with InstaNexus Abstract Protein-based therapeutics, such as antibodies and nanobodies, are not encoded in reference genomes, challenging their accurate characterization via standard proteomics. Current methods rely on indirect inference, fragmented outputs, and labor-intensive workflows, which hinder functional insights and routine application. Here, we present a generalizable, end-to-end workflow for direct protein sequencing, combining streamlined sample preparation, AI-driven de novo peptide sequencing, and tailored assembly to reconstruct contiguous protein sequences. A novel composite scoring framework prioritises longer assemblies and coverage, enhancing accuracy and reducing ambiguity. Validation across diverse protein modalities demonstrates its utility and ability to robustly sequence functionally critical regions of selected proteins. This workflow represents an advance in precision proteomics with promising applications in therapeutic discovery, immune profiling, and protein science. Computational biology ; Computer science ; Genetics ; Biology Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Glycosylation and Glycoproteins Research
Authors: Tomasi Francesca G. | Andrei Ivanovich K
Source: Journal of Biomedical Research & Environmental Sciences (article, 2025-07-01)
Field: Chemistry — Physical and Theoretical Chemistry

Molecular Investigation of Cytochrome P-450 Enzymes Inductors Cytochrome P-450 enzymes play a critical role in xenobiotic metabolism and homeostasis, with their induction offering therapeutic potential for liver diseases and metabolic disorders. Using molecular docking and statistical analyses, the research examines the binding affinities and structural features of 46 known inducers, classifying them into Type I (affecting apo-protein expression) and Type II (directly influencing the heme center). Linear Discriminant Analysis (LDA) achieved an 87% accuracy in classifying these inducers, with key interactions identified at amino acid residues Glu301, Phe115, and Ser294. Compounds such as 3,5-difluoromethylurea and 3,4-dichlorophenylmethylurea demonstrated strong binding, highlighting their potential as effective inducers. The study also developed Quantitative Structure-Activity Relationship (QSAR) models to predict binding constants, providing insights into the structural determinants of induction. These findings advance the understanding of cytochrome P-450 induction mechanisms and lay the groundwork for designing safer, more selective drugs. Cytochrome ; Enzyme ; Chemistry ; Cytochrome P450 ; Biochemistry ; Inductor ; Engineering ; Electrical engineering Various Chemistry Research Topics
Authors: Taehun Cha | Dong‐Hoon Lee
Source: Proceedings of the AAAI Conference on Artificial Intelligence (article, 2025-04-11)
Field: Materials Science — Materials Chemistry

ABC3: Active Bayesian Causal Inference with Cohn Criteria in Randomized Experiments In causal inference, a randomized experiment is a de facto method to overcome various theoretical issues in observational study. However, the experimental design requires expensive costs, so an efficient experimental design is necessary. We propose ABC3, a Bayesian active learning policy for causal inference. We show a policy minimizing an estimation error on conditional average treatment effect is equivalent to minimizing an integrated posterior variance, similar to Cohn criteria. We theoretically prove ABC3 also minimizes an imbalance between the treatment and control groups and the type 1 error probability. Imbalance-minimizing characteristic is especially notable as several works have emphasized the importance of achieving balance. Through extensive experiments on real-world data sets, ABC3 achieves the highest efficiency, while empirically showing the theoretical results hold. Causal inference ; Bayesian probability ; Inference ; Bayesian inference ; Econometrics ; Artificial intelligence ; Bayesian statistics ; Randomized experiment ; Computer science ; Machine learning ; Statistics ; Mathematics Machine Learning in Materials Science ; Fault Detection and Control Systems
Authors: William Comstock | M.V.A.S. Navarro | Deanna V. Maybee | Yiseo Rho | Mateusz Wagner | Khoula Jaber | Yingzheng Wang | Marcus B. Smolka
Source: Nature Communications (article, 2025-11-13)
Field: Chemistry — Spectroscopy

Proteomic sensors for quantitative multiplexed and spatial monitoring of kinase signaling Understanding kinase action requires precise quantitative measurements of their activity in vivo. In addition, the ability to capture spatial information of kinase activity is crucial to deconvolute complex signaling networks, interrogate multifaceted kinase actions, and assess drug effects or genetic perturbations. Here we develop a proteomic kinase activity sensor technique (ProKAS) for the analysis of kinase signaling using mass spectrometry. ProKAS is based on a tandem array of peptide sensors with amino acid barcodes that allow multiplexed analysis for spatial, kinetic, and screening applications. We engineered a ProKAS module to simultaneously monitor the activities of the DNA damage response kinases ATR, ATM, and CHK1 in response to genotoxic drugs, while also uncovering differences between these signaling responses in the nucleus, cytosol, and replication factories. Furthermore, we developed an in silico approach for the rational design of specific substrate peptides expandable to other kinases. Overall, ProKAS is a versatile system for systematically and spatially probing kinase action in cells. Kinase ; In silico ; Protein kinase A ; Signal transduction ; Proteomics ; Cell signaling ; Quantitative proteomics ; Rational design Advanced Proteomics Techniques and Applications ; Protein Degradation and Inhibitors ; Advanced Biosensing Techniques and Applications
Authors: Run‐Cang Sun | Chaojun Hou | Huawei Cui
Source: Innovative applications of AI. (article, 2025-06-30)
Field: Chemistry — Analytical Chemistry

Inversion Models for Orchard Soil Nutrient Content Using Near- Infrared Spectroscopy Precise determination of available nitrogen (N), phosphorus (P) and potassium (K) concentrations in soil is essential for orchard fertilizer management. However, conventional chemical analytical methods are time-consuming and costly, making it difficult to meet the demand for rapid detection in modern agriculture. Near-infrared spectroscopy (NIRS) is a promising approach for rapidly detecting soil nutrient concentrations. This study aims to develop inversion models, including partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF), to accurately determine the concentrations of available N, P, and K in soil using NIRS. To mitigate spectral interference and enhance prediction performance of inversion models. we systematically implemented multiple preprocessing methods including Savitzky-Golay smoothing (SG), multiplicative scatter correction (MSC), standard normal variate transformation (SNV), moving average (MA) and first-derivative transformation (FD). The results indicated that the RF model achieved superior predictive accuracy compared to the PLSR and SVR, with prediction performance for available N being R²=0.539, RMSE=21.408 mg/kg, and RPD=1.490; for available P, R²=0.536, RMSE=25.056 mg/kg, and RPD=1.484; and for available P, R²=0.429, RMSE=42.452 mg/kg, and RPD=1.338. Compared with the spectral data without preprocessing, the performance of RF model improved by 8.53%, 3.17%, and 0.47% for the R² values for available N, P, and K, respectively. The comparison of the preprocessing methods in combination with the RF model revealed that MSC had the best model accuracy for the available N (R²=0.585, RMSE=20.326 mg/kg, RPD=1.569), SG had the best model accuracy for the available P (R²=0.553, RMSE=24.585 mg/kg, RPD=1.513), and MA had the best model accuracy for the available K (R²=0.431, RMSE=42.383 mg/kg, RPD=1.340). It is noteworthy that the model accuracy is worst for the available K, possibly due to its inherently weaker spectral response characteristics and lower signal-to-noise ratio. This study shows that NIR spectroscopy using appropriate preprocessing methods and regression models can accurately predict soil nutrient concentrations, supporting precision fertilization management in orchard production systems. Orchard ; Inversion (geology) ; Soil science ; Environmental science ; Spectroscopy ; Nutrient ; Infrared ; Soil nutrients ; Near-infrared spectroscopy ; Infrared spectroscopy ; Remote sensing ; Geology ; Soil water ; Optics ; Chemistry ; Agronomy ; Physics ; Geomorphology ; Biology Spectroscopy and Chemometric Analyses
Authors: Angeliki I. Katsafadou | Sofia I. Prodromou | Reza Aalizadeh | Jason C. White | Νikolaos S. Τhomaidis | Ioannis S. Vizirianakis | Paul T. Anastas | Tassos C. Kyriakides | Harris Pastides | Prisco Piscitelli | Annamaria Colao | David C. Thompson | Vasilis Vasiliou
Source: Frontiers in Public Health (review, 2025-09-19)
Field: Chemistry — Organic Chemistry

Olive tree at the intersection of environment, public health, and One Health: a sustainable path to global wellbeing The olive tree and its derivatives-olives, olive oil, and their by-products-are foundational to the Mediterranean diet and are increasingly recognized for their roles in nutrition, medicine, and ecological sustainability. Indeed, one of the most prominent examples of sustainable production and consumption paradigm in a changing climate lies in the olive sector, approached within One Health framework, i.e., the interconnectedness of human health with animal and environmental health. This review explores the multifaceted roles of olive cultivation, olive oil production and consumption, and olive by-products in relation to health benefits, sustainable agriculture, and environmental impact. Olive oil consumption offers significant human health benefits, primarily involving its anti-inflammatory and antioxidant properties. These effects, largely attributed to its rich composition of monounsaturated fatty acids and other antioxidants, mediate its cardioprotective and neuroprotective roles. Beyond human health, olive oil cultivation and its by-products (such as pomace and mill wastewater) have gained attention as valuable feed additives in animal nutrition. These enhance livestock health and welfare, improve meat and dairy quality, and promote sustainable agricultural practices and bioenergy production-ultimately reducing environmental impact and supporting circular economies. From an environmental perspective, the olive sector contributes meaningfully to soil conservation, biodiversity support, and climate change mitigation through carbon sequestration and reduced greenhouse gas emissions. As such, the olive tree is more than a source of a valuable food product: it is a nexus of sustainable development, public health, and ecosystem stewardship. Considering the olive sector within the One Health paradigm highlights its relevance in addressing global challenges at the intersection of food systems, health, and environmental sustainability. Olive trees ; Agriculture ; Consumption (sociology) ; Sustainability ; Nexus (standard) ; Livestock ; Production (economics) ; Sustainable development ; Public health Edible Oils Quality and Analysis ; Nutritional Studies and Diet ; Nuts composition and effects
Authors: Roger Olivella | Cristina Chiva | Marc Serret | Antonio Hermoso | Eva Borràs | Guadalupe Espadas | Julia Morales‐Sanfrutos | Olga Pastor | Amanda Solé | Julia Ponomarenko | Eduard Sabidó
Source: Journal of Proteome Research (article, 2025-08-19)
Field: Chemistry — Spectroscopy

QSample: An Automated System for Rapid Monitoring of Quality Indicators in Proteomics Samples Mass spectrometry-based proteomics is an essential technique in contemporary biomedicine, offering quantitative, sensitive, and rapid analysis of proteomes. Recent advancements in mass spectrometry have enabled the acquisition of data from increasingly large-scale experiments, often conducted in core facilities and research infrastructures. While automated tools exist to assess instrument performance using predefined control samples, the analysis of experimental samples typically occurs postacquisition, which can delay decision-making and lead to potential data integrity issues. To address these challenges, we developed QSample, an open-source automated system for rapidly monitoring quality indicators in proteomics samples during data collection. QSample enhances the quality control framework by facilitating prompt actions and fast decision-making, ensuring that proteomics core facilities deliver data that adhere to best research practices. Proteomics ; Computer science ; Data quality ; Biomedicine ; Quality (philosophy) ; Data science ; Proteome ; Data collection ; Engineering ; Bioinformatics ; Chemistry ; Operations management Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Emmanuel Kotu Robertson | Meng Li | Hampus Månefjord | Jadranka Rota | Nina Reistad | Mikkel Brydegaard
Source:  (preprint, 2025-09-10)
Field: Chemistry — Analytical Chemistry

Goniometric Investigation of Spectral Scattering from Insect Wings in Near Infrared Insect wing interference is highly sensitive to the membrane thickness and has shown remarkable potential to differentiate insect species, both ex vivo in laboratory settings and for free flying insects in situ . While several studies have reported diversity of wing interference patterns, no study has tied this resonant coherent scattering from membranes to the goniometric scattering phase function. We present a combined spectral and goniometric study and demonstrate that resonant wavelengths for a species selectively communicate with the thin and flat wing membrane, whereas scattering at dissonant wavelengths to a greater extent arises from the tubular veins. This report paves the way for better understanding of range dependence in entomological lidar and insect differentiation by spectral and modulation properties. Goniometer ; Scattering ; Wing ; Interference (communication) ; Wavelength ; Forward scatter ; Phase (matter) ; Phase modulation Spectroscopy and Chemometric Analyses ; Bee Products Chemical Analysis
Authors: Evangelos Tsiaras | Antonios Kanavouras | Frank A. Coutelieris
Source: Applied Sciences (article, 2025-08-30)
Field: Chemistry — Organic Chemistry

Mathematical Modeling of Packaging Properties as Hurdles for Food Degradation: A Case Study on Olive Oil Context and Objective: Food quality and shelf life are strongly influenced by the interaction between packaging properties and mass transport processes. This study explored how hurdle technology can be applied to food preservation, focusing on olive oil as a practical case due to its high sensitivity to oxidation and light. Methodology: An analogy was developed between transport phenomena in packaging and the fundamental laws of electricity, providing a simple physical basis for understanding preservation mechanisms. This was supported by parametric simulations and mathematical modeling, which were used to predict how different packaging materials and conditions influence product stability. Main Results: The application to olive oil showed that packaging properties such as resistance to oxygen and light permeation have a direct effect on preservation effectiveness. Model predictions highlighted clear differences in stability depending on the choice of packaging, demonstrating the critical role of material selection. Conclusions: The study presents an integrated framework that links packaging characteristics with food preservation outcomes. By combining physical analogies with modeling tools, it offers a practical basis for designing packaging solutions that extend shelf life and protect sensitive foods such as olive oil. Olive oil ; Food science ; Environmental science ; Process engineering ; Engineering ; Chemistry Edible Oils Quality and Analysis