jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zenghao Bi | Yuting Liang | Xinyu Tang | Yun Shu | Zhuangyuan Xie | Guiling Xu | Jing Mo | Pang Jit Seng | Yifan Qing | Zhaotong Cong | Liang Leng | Shilin Chen
Source: International Journal of Molecular Sciences (article, 2026-02-23)
Field: Chemistry — Analytical Chemistry

Identification of Neferine as a DOR Agonist Activating Gi and Gz Signaling: In Silico and In Vitro Studies Benzylisoquinoline alkaloids (BIAs) exhibit diverse biological activities, such as neuroprotective effects. The delta-opioid receptor (DOR) has emerged as a promising therapeutic target due to its potential role in enhancing neuroprotection and regeneration. However, reports on the binding of BIAs to the DOR remain scarce. Here, neferine, a BIA from <i>Nelumbo nucifera</i>, as a potential DOR agonist. Molecular docking ranked neferine among the top of 15 BIAs. Initial binding was detected by cellular membrane chromatography and quantitatively confirmed by bio-layer interferometry, with a K<sub>D</sub> value of 37.4 μM. ONE vector G protein Optical biosensor revealed that G<sub>i2</sub>, G<sub>i3</sub> and G<sub>Z</sub> signaling could be activated by neferine through DOR modulation. Consistent with the G<sub>i/z</sub> activation, neferine dose-dependently inhibited cAMP accumulation with an EC<sub>50</sub> of 0.25 µM. Transcriptomic analysis in DOR-overexpressing HEK293T cells indicated that neferine stimulation predominantly regulates gene networks governing cell cycle and stress adaptation. However, direct transcriptional signature for neuroprotection was not predominant in our system, suggesting that DOR signaling may exhibit context-dependent effects. In conclusion, we identified the neferine as a natural DOR agonist through in silico and in vitro approach, providing a reference for further investigation into its pharmacological potential. In silico ; Agonist ; Neuroprotection ; In vitro ; Signal transduction ; Virtual screening Chromatography in Natural Products ; Neuropeptides and Animal Physiology ; Berberine and alkaloids research
Authors: Paulina Maria Rybicka | Marta Kulik | Vladislav Mikhailovich Ignat'ev | P.M. Dominiak
Source: ChemRxiv (article, 2026-01-22)
Field: Materials Science — Materials Chemistry

From atoms to a data bank: optimizing transferability of electron density symmetry The multipole model provides a significantly improved description of electron density compared to the spherical atom approximation and is widely applied in the crystallographic refinement on X-ray diffraction data. The Multipolar Atom Types From Theory and Statistical clustering (MATTS) data bank collects multipole model parameters for atom types. These parameters are derived from quantum chemical calculations performed on experimental geometries of model molecules and rely on the concept of transferability between chemically similar atoms. An essential component of each atom type is the definition of the local coordinate system (LCS) and the symmetry of the electron density, which so far have been defined manually during data bank construction. In this work, we focus on the electron densities of atoms from model molecules and atom types from MATTS data bank. We introduce a systematic procedure in which symmetry constraints are removed during multipole model refinement of model molecules and multiple types of LCS are tested using chemically meaningful directions. We examine how different LCS choices influence the pseudosymmetry, the apparent symmetry of electron density, identified empirically based on the refined multipole model parameters and their statistical significance. Our results show that refinement without symmetry constraints improves the representation of pseudosymmetry and, in some cases, leads to changes in both the values of the multipole model parameters and the assigned symmetry of the electron density. We propose an optimal LCS for each topological kind of atom types and provide clear criteria for symmetry assignment. This work contributes to the future development of the MATTS data bank with improved descriptions of local coordinate systems and transferability of electron density symmetry. Multipole expansion ; Symmetry (geometry) ; Atom (system on chip) ; Electron density ; Representation (politics) ; Atoms in molecules ; Molecule ; Transferability ; Type (biology) Enzyme Structure and Function ; Crystallography and molecular interactions ; X-ray Diffraction in Crystallography
Authors: Lorena Alamillo | Alexander Black | Matthew C. Juber | Dominic C.M. Ng | Maggie PY Lam | Edward Lau
Source: STAR Protocols (article, 2026-03-01)
Field: Chemistry — Spectroscopy

Protocol to measure protein half-life in cell culture using heavy water Protein turnover, comprising the continued synthesis and clearance of proteins, is required for protein homeostasis and cell survival. Here, we present a protocol to measure protein turnover half-life in cultured cells using D<sub>2</sub>O labeling. We describe steps to determine the extent of deuterium exchange in amino acids, perform dynamic labeling, and collect protein samples, followed by mass spectrometry and kinetic analysis. The protocol is suitable for measuring protein half-life under steady-state conditions and perturbations in multiple cell types and culture media. For complete details on the use and execution of this protocol, please refer to Alamillo et al.<sup>1</sup>. Protocol (science) ; Mass spectrometry ; Protein turnover ; Measure (data warehouse) ; Cell culture ; Cell ; Amino acid ; Protein biosynthesis Advanced Proteomics Techniques and Applications ; Muscle metabolism and nutrition ; Biotin and Related Studies
Authors: Wenxuan Wang | Zhiheng Hu | Ruoyi Zhou | Yitao Huang | Yilun Wang | Bo Mu | Minglong Chen
Source: Sustainability (article, 2026-04-10)
Field: Materials Science — Biomaterials

Influence of Printing Orientation on the Mechanical Performance and Environmental Footprint of PLA/TPU Heterogeneous Composites This study examines how 3D-printing orientation affects the mechanical behavior and environmental impact of polymer materials and heterogeneous PLA/TPU composites. Tensile properties of PLA, TPU, and PLA/TPU heterogeneous samples were systematically compared in horizontal and vertical printing orientations. Results show that printing orientation governs mechanical performance: vertical printing generally reduces ductility and exhibits unstable post-peak behavior, with heterogeneous samples performing worse than their single-material counterparts. In contrast, horizontal printing enhances strength, ductility, and energy absorption due to continuous load transfer along the filament path, improved interlayer adhesion, and larger effective contact areas. Specifically, TPU demonstrates higher ductility and energy absorption in the horizontal orientation, while PLA achieves higher strength but lower ductility; both materials degrade substantially in the vertical orientation. For heterogeneous composites, vertical printing yields the poorest outcomes due to load transfer across multiple perpendicular interfaces and thermal shrinkage mismatch, which promote crack initiation and propagation. Horizontal printing delivers an optimal balance of strength and toughness via stronger interface bonding. Life cycle assessment (LCA) indicates that horizontal printing reduces environmental burdens by lowering energy consumption and waste, whereas vertical printing amplifies these impacts, particularly for TPU and composite systems. Based on these findings, we recommend employing horizontally printed PLA/TPU heterogeneous composites to achieve favorable load paths and interface integrity while prioritizing bio-based PLA to enhance sustainability. Toughness ; Ductility (Earth science) ; Ultimate tensile strength ; 3D printing ; Composite number ; Perpendicular ; Thermal ; Orientation (vector space) ; Fused deposition modeling biodegradable polymer synthesis and properties ; Additive Manufacturing and 3D Printing Technologies ; Natural Fiber Reinforced Composites
Authors: Deepankar Sri Gyan | Hyeon Jun Lee | Xiangwei Guo | Youngjun Ahn | Samuel D. Marks | Mohammed Yusuf | M. Dawber | J. Glownia | Diling Zhu | Takahiro Sato | S. Song | Haidan Wen | Jia‐Mian Hu | P. S. Evans
Source: Advanced Science (article, 2026-02-03)
Field: Materials Science — Materials Chemistry

Transient Terahertz Oscillations During Photoinduced Polarization Topology Reconfiguration in Ferroelectric Superlattices Terahertz resonances embedded in crystalline heterostructures could close a spectral gap between conventional electronics and photonics while opening new windows on phenomena in non-equilibrium lattice dynamics. We show that femtosecond optical screening of the depolarization field in epitaxial PbTiO<sub>3</sub>/SrTiO<sub>3</sub> superlattices launches a collective polar mode that oscillates near 1 THz and coherently spans the entire mini-Brillouin zone. Wave-vector-resolved pump-probe X-ray diffraction resolves a nearly dispersion-less oscillation at 0.87 and 0.94 THz at the zone boundary and zone center, respectively, persisting for ∼2.5 ps, corresponding to a weakly damped resonance. Dynamical phase-field simulations reveal the origin of the mode to mesoscopic rotation of closure-domain textures during the photoexcited transition from an unscreened to a screened electrostatic state. Varying the PbTiO<sub>3</sub> and SrTiO<sub>3</sub> ratio tunes the mode frequency continuously from 0.9 to 1.4 THz, providing a quantitative design rule for frequency-selectable THz oscillators in ferroelectric heterostructures. By coupling nanoscale polarization reconfiguration to long-wavelength coherent dynamics, this work establishes depolarization-field engineering to topology-driven THz functionality and expanding the landscape of collective lattice dynamics. Terahertz radiation ; Superlattice ; Polarization (electrochemistry) ; Ferroelectricity ; Phonon ; Polariton ; Femtosecond ; Control reconfiguration Ferroelectric and Piezoelectric Materials ; Topological Materials and Phenomena ; Nonlinear Photonic Systems
Authors: Shuai Yang | Zhikai Liu | Junbing Tao | Fengxu Xiao | Guiyang Shi | Youran Li
Source: Processes (article, 2026-03-25)
Field: Chemistry — Analytical Chemistry

Near-Infrared Spectroscopy for Online Glucose Detection in Fermentation Processes: Transflectance/Transmission Sensor Evaluation and Modeling Optimization This study employed near-infrared (NIR) spectroscopy for real-time spectral acquisition of fermentation broth in lab-scale bioreactors, comparing the performance of transflectance and transmission sensors through glucose modeling and prediction while optimizing modeling approaches. The results demonstrated superior adaptability of transflectance sensors in fermentation environments: in conventional fermentation, glucose models exhibited lower errors (RMSEC = 4.087 g/L, RMSEV = 9.829 g/L) compared to transmission sensors (RMSEC = 5.972 g/L, RMSEV = 10.904 g/L), with significantly higher predictive performance (RPD = 3.735 vs. 2.369), indicating enhanced fitting accuracy and stability. In complex natural media containing peptone and yeast extract, transmission sensor performance deteriorated dramatically due to turbidity interference (R2cal = 0.134), whereas transflectance sensors maintained robust performance (R2cal = 0.993), confirming their adaptability to complex matrices. Regarding modeling strategies, the 1550–1700 nm spectral region demonstrated optimal feature extraction capability (RMSEC = 3.269 g/L, R2cal = 0.987). Basic preprocessing methods such as the moving average smoothing method have become the preferred preprocessing methods, as they strike a balance between calibration and prediction performance. Outlier removal analysis revealed that moderate elimination of 12 high-error samples (accounting for 30% of the total 39 samples) reduced RMSEC to 1.441 g/L and improved R2cv to 0.996, optimizing model performance; however, excessive removal of outlier samples degraded model capability, necessitating judicious sample selection. For fixed total sample sizes, calibration sets comprising 70–80% of samples yielded more reliable predictions. In conclusion, transflectance sensors demonstrate superior compatibility with multicomponent fermentation systems. Combined with wavelength selection, moving average preprocessing, and rational sample removal and partitioning strategies, this approach provides an effective solution for NIR-based online glucose monitoring. Calibration ; Partial least squares regression ; Outlier ; Analyte ; Smoothing ; Preprocessor ; Sample preparation ; Principal component analysis ; Fermentation Spectroscopy and Chemometric Analyses ; Viral Infectious Diseases and Gene Expression in Insects ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Guillermo Jiménez-Hernández | M. Gracia Bagur-González | Fidel Ortega-Gavilán | L. F. García del Moral | Vanessa M. Martos | Antonio González-Casado
Source: Foods (article, 2026-02-13)
Field: Chemistry — Organic Chemistry

ATR-FTIR and FORS Fingerprints for Authentication of Commercial Sunflower Oils and Quantification of Their Oleic Acid The composition of sunflower oil, rich in fatty acids, largely depends on the seed variety. Commercial sunflower oils are classified as low (SFO), medium (MOSFO), and high (HOSFO) oleic, distinguished by their oleic and linoleic acid content. Higher oleic acid levels enhance health benefits and oxidative stability. Due to their differing market values, ensuring the correct quality and authenticity of these oils is essential. Unsupervised chemometric methods have been applied to visualise the natural behaviour of sunflower oils, while supervised models have been used for authentication based on Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) fingerprints obtained from a benchtop spectrometer. Authentication of MOSFO is particularly challenging because of its wider oleic acid range (43.1-74.9%) and production via genetic modification or blending SFO/HOSFO. To address this, two multivariable PLS-R regression models were developed using ATR FT-IR and Fibre Optic Reflectance Spectroscopy (FORS) fingerprints, the latter obtained with a portable, cost-effective device. The results indicate that FORS could be used as a rapid quality control tool for on-site quantification. In contrast, ATR FT-IR is a more accurate tool for confirmation and quantification, achieving excellent results (Residual Predictive Deviation, RPD = 7.09 and Range Error Ratio, RER = 17.82). Oleic acid ; Linoleic acid ; Sunflower oil ; Authentication (law) ; Sunflower ; Attenuated total reflection ; Fatty acid Edible Oils Quality and Analysis ; Spectroscopy and Chemometric Analyses ; Sunflower and Safflower Cultivation
Authors: Yuqi Kang | Hu Bin | Dongxing Li | Jan Hamann
Source: ArXiv.org (article, 2026-03-18)
Field: Materials Science — Materials Chemistry

TUNeS: Neural Emulation of Large-Scale Structure Across Redshifts In this work, we introduce TUNeS (Temporal UNet emulator for Structure formation), a neural network framework for accelerating N-body simulations by predicting the nonlinear evolution of the matter density field from an initial particle distribution. TUNeS employs a two-stage modeling strategy, combining particle-based inference with a density-field refinement on a regular grid, enabling accurate reconstruction of both large- and small-scale structures. The model is designed to operate across redshift, taking particle snapshots at arbitrary input redshifts and predicting density fields at arbitrary target redshifts. In this work, we evaluate its performance using simulations initialized at $z=100$, with predictions generated at multiple lower redshifts. Trained on only eight N-body simulations, TUNeS reproduces reference results with good agreement in both Gaussian and non-Gaussian statistics, including two-point correlations, one-point distributions, peak counts, and three-dimensional Minkowski functionals. In particular, at $k \simeq 1\,h\,\mathrm{Mpc}^{-1}$, the power spectrum error remains at the few-percent level. End-to-end inference from $256^3$ particles to a $256^3$ density grid can be completed in $\sim25\,\mathrm{second}$ on a single GPU. Thanks to its architectural design, the model naturally scales to larger particle numbers and larger volumes through particle batching and window-based refinement. Emulation ; Spectral density ; Artificial neural network ; Inference ; Minkowski space ; Gaussian ; Field (mathematics) ; Grid Machine Learning in Materials Science ; Nuclear physics research studies ; Gaussian Processes and Bayesian Inference
Authors: Zhongxiu Yuan | Mengshu HAN | Ling Chen | Yu Chen | J. C. Xiao | Qingyan Chen | Qi Li | Yongxia Liu
Source: Plants (article, 2026-03-26)
Field: Materials Science — Biomaterials

Multidimensional Drivers of Phytoplankton Assembly in a Karst Reservoir: Seasonal Dynamics and Regulatory Implications Baihua Reservoir, a typical large waterbody in the karst region of southwestern China and an essential drinking water source, is characterized by a high carbonate buffering capacity that profoundly shapes the structure and function of its phytoplankton community. This study systematically elucidates the multi-dimensional driving mechanisms underlying seasonal phytoplankton community assembly in karst reservoirs by integrating multiple analytical models—including the Neutral Community Model, β-diversity decomposition, co-occurrence network analysis, XGBoost-SHAP machine learning, and Partial Least Squares Path Modeling—based on monthly sampling at five sites from 2020 to 2024. The results revealed that: (1) Stochastic processes dominated community assembly across all four seasons, while deterministic processes played a crucial role in local species turnover. (2) The co-occurrence network structure showed significant seasonal dynamics, with the composition of keystone species adaptively shifting in response to changing environmental conditions. (3) The key environmental factors influencing the phytoplankton community exhibited clear seasonal patterns, primarily pH, NH3-N, and CODMn in spring; water temperature, CODMn, and NH3-N in summer; TN, TP, and pH in autumn; and pH, water temperature, and DO in winter. To support the sustainable management of karst reservoirs, we propose seasonally differentiated strategies derived from our phytoplankton community analysis: target CODMn reduction in spring and summer, focus on TN and TP load control in autumn, prioritize water column stability in winter, and maintain hydrological connectivity and pH monitoring year-round. This approach enhances phytoplankton community stability, safeguards drinking water safety, and provides a targeted management model for similar reservoir ecosystems globally. Phytoplankton ; Karst ; Community structure ; Ecosystem ; Water column ; Spring (device) ; Hydrology (agriculture) Diatoms and Algae Research ; Aquatic Ecosystems and Phytoplankton Dynamics ; Subterranean biodiversity and taxonomy
Authors: Mustafa Eroğlu | Mehmet Aki̇f Koç | İsmail Esen
Source: Acta Mechanica (article, 2026-03-02)
Field: Materials Science — Materials Chemistry

Mechanical characterization and thermomechanical free vibration of butterfly-shaped sandwich nanoplates with MEE face layers Abstract This study examines the thermomechanical free vibration buckling behavior of three-layer sandwich nanoplate structures featuring a butterfly-shaped auxetic core and magneto-electro-elastic (MEE) face layers. The study derived the equations of motion using the Hamilton principle, followed by the development of a Navier-type solution method. A comparison was conducted with existing literature to verify the study's results. This analysis examines the geometrical properties of the butterfly-shaped auxetic, nonlocal effects, and the influences of electric, magnetic, and temperature variations. The findings emphasize the need to vary geometrical parameters, such as edge and thickness ratios, to enhance the structural performance of butterfly core sandwich nanoplates at different temperatures. The findings indicate unforeseen thermal instability trends that could influence future design for high-temperature applications. This study offers insights into the thermomechanical behavior of advanced sandwich structures, contributing to the field within evolving technological demands. Auxetics ; Solid mechanics ; Vibration ; Core (optical fiber) ; Thermal ; Characterization (materials science) ; Enhanced Data Rates for GSM Evolution Nonlocal and gradient elasticity in micro/nano structures ; Composite Structure Analysis and Optimization ; Cellular and Composite Structures
Authors: Gaocheng Fu | Shiji Zhang | Kai Huang | Xue Yang | Huilin Zhang | Daxiu Wei | Ye-Feng Yao
Source: ArXiv.org (article, 2026-04-02)
Field: Chemistry — Spectroscopy

A Differentiable Physical Framework for Goal-Driven Spin-State Engineering in Magnetic Resonance Spectroscopy Magnetic Resonance Spectroscopy (MRS) offers a unique non-invasive window into metabolic processes, yet its potential remains strictly constrained by severe spectral congestion and intrinsic insensitivity. Traditional pulse sequence design, tethered to human intuition, predominantly targets simple quantum states, thereby overlooking the vast majority of the exponentially scaling operator space which consists of complex spin superpositions. Here, we introduce a spectrum-driven, end-to-end differentiable physical framework that transcends these heuristic limitations. By integrating physical laws with automatic differentiation algorithm, our approach directly navigates the high-dimensional spin dynamics space, bypassing the intractable inverse problem of state preparation. This enables the discovery of non-intuitive, complex mixed states that simultaneously satisfy the dual objectives of selective excitation and interferometric signal enhancement. We validate this paradigm by achieving the robust separation of Glutamate and Glutamine, which is a longstanding neuroimaging challenge, in the human brain at 3T, demonstrating spectral fidelity superior to conventional methods. By unlocking the "dark" informational content of nuclear spin ensembles, our work establishes a generalizable paradigm for goal-driven quantum state engineering in magnetic resonance and beyond. Differentiable function ; Operator (biology) ; Pulse sequence ; Quantum ; Spin network ; Spin (aerodynamics) ; Physical system ; Quantum computer ; Spectroscopy Advanced NMR Techniques and Applications ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies