jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xinnong Li | Mark Sale | Keith Nieforth | James C. Craig | Fenggong Wang | David B. Solit | Kairui Feng | Meng Hu | Robert R. Bies | Liang Zhao
Source: Journal of Pharmacokinetics and Pharmacodynamics (article, 2024-06-28)
Field: Chemistry — Spectroscopy

pyDarwin machine learning algorithms application and comparison in nonlinear mixed-effect model selection and optimization Forward addition/backward elimination (FABE) has been the standard for population pharmacokinetic model selection (PPK) since NONMEM® was introduced. We investigated five machine learning (ML) algorithms (Genetic algorithm [GA], Gaussian process [GP], random forest [RF], gradient boosted random tree [GBRT], and particle swarm optimization [PSO]) as alternatives to FABE. These algorithms were applied to PPK model selection with a focus on comparing the efficiency and robustness of each of them. All machine learning algorithms included the combination of ML algorithms with a local downhill search. The local downhill search consisted of systematically changing one or two "features" at a time (a one-bit or a two-bit local search), alternating with the ML methods. An exhaustive search (all possible combinations of model features, N = 1,572,864 models) was the gold standard for robustness, and the number of models examined leading prior to identification of the final model was the metric for efficiency.All algorithms identified the optimal model when combined with the two-bit local downhill search. GA, RF, GBRT, and GP identified the optimal model with only a one-bit local search. PSO required the two-bit local downhill search. In our analysis, GP was the most efficient algorithm as measured by the number of models examined prior to finding the optimal (495 models), and PSO exhibited the least efficiency, requiring 1710 unique models before finding the best solution. Additionally, GP was also the algorithm that needed the longest elapsed time of 2975.6 min, in comparison with GA, which only required 321.8 min. Algorithm ; Robustness (evolution) ; Particle swarm optimization ; Local search (optimization) ; Computer science ; Population ; Mathematical optimization ; Model selection ; Random forest ; Local optimum ; Mathematics ; Artificial intelligence ; Machine learning Analytical Chemistry and Chromatography ; Statistical Methods in Clinical Trials ; Pharmacogenetics and Drug Metabolism
Authors: Julio Nogales‐Bueno | Francisco J. Rodríguez‐Pulido | Francisco J. Heredia | José Miguel Hernández‐Hierro | Berta Baca‐Bocanegra
Source: LWT (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Use of hyperspectral imaging devices for the measurement of small granular samples: Evaluation of grape seed protein concentrates Hyperspectral imaging is a well-known technique for quality control of food and agricultural products. This technique is often applied to the measurement of large and heterogeneous samples, where chemical imaging is extremely useful. In addition, when the amount of sample is limited by different factors (price, other analyses, sample production, etc.) hyperspectral imaging is an alternative to traditional spectroscopes for acquiring its spectral information. In this study, a new and specific methodology to acquire hyperspectral information from small amounts of granular samples has been developed. For this purpose, two different hyperspectral devices (400–1100 nm, 900–1700 nm) have been used. A statistical procedure has been followed to test the proposed method. In grape seed protein concentrates, NIR radiation (900–1700 nm) penetrates deeper into the sample than VisNIR radiation (400–1100 nm). Therefore, the minimum amount of sample needed to measure in the NIR range is larger than that needed to measure in the VisNIR range. Finally, different calibration models have been developed for the control of protein content in the tested samples. Standard errors of prediction obtained in external validation are similar to those reported in the literature when sample amount is not an issue (9–10 %). Hyperspectral imaging ; Calibration ; Sample (material) ; Computer science ; Measure (data warehouse) ; Remote sensing ; Environmental science ; Biological system ; Data mining ; Artificial intelligence ; Mathematics ; Chemistry ; Statistics ; Chromatography Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Meat and Animal Product Quality
Authors: Olga Monago‐Maraña | Jens Petter Wold | Siv Fagertun Remberg | Karen Wahlstrøm Sanden | Nils Kristian Afseth
Source: Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (article, 2024-07-30)
Field: Chemistry — Analytical Chemistry

Raman spectroscopy as a tool for characterisation of quality parameters in Norwegian grown apples during ripening This study shows for the first time the feasibility of Raman spectroscopy as a non-destructive method to follow the ripening process of apple fruits. Two different varieties of apples were studied: 'Aroma' and 'Elstar'. By visual inspection, Raman spectra showed that the starch content was higher in 'Elstar' apples compared to 'Aroma'. The degradation of starch over time could be detected in the Raman spectra, indicating that the method can be used to monitor the ripening process. The ripeness markers starch index, soluble solids content (SSC), and the sugars glucose, fructose and sucrose were determined with traditional destructive methods. Cross validated calibration models based on Raman spectroscopy were obtained for all quality parameters, and test set validation offered good results, with R<sup>2</sup> in the range 0.4-0.86 for 'Aroma' and 0.4-0.95 for 'Elstar', respectively. The regression coefficients showed that the calibrations relied on Raman bands associated with starch and different sugars. The results suggest that Raman spectroscopy in the future could be used to determine the optimal time of harvesting and to sort apples into different degrees of ripeness. Chemistry ; Raman spectroscopy ; Ripening ; Ripeness ; Starch ; Aroma ; Sucrose ; Food science ; Analytical Chemistry (journal) ; Chromatography ; Optics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Listeria monocytogenes in Food Safety
Authors: Weizheng Cao | Juefei Wu | Yongkai Li | Cuiying Pei | Qi Wang | Yi Zhao | Changhua Li | Shihao Zhu | Mingxin Zhang | Lili Zhang | Yulin Chen | Zhiwei Wang | Yanpeng Qi
Source: Advanced Physics Research (article, 2024-03-03)
Field: Materials Science — Materials Chemistry

Pressure‐Induced Superconductivity and Structure Phase Transition in SnAs‐Based Zintl Compound SrSn<sub>2</sub>As<sub>2</sub> Abstract Layered SnAs‐based Zintl compounds exhibit a distinctive electronic structure, igniting extensive research efforts in areas of superconductivity, topological insulators, and quantum magnetism. In this paper, the crystal structures and electronic properties of the Zintl compound SrSn 2 As 2 upon compression are systematically investigated. Pressure‐induced superconductivity is observed in SrSn 2 As 2 with a nonmonotonic evolution of superconducting transition temperature T c . Theoretical calculations together with high‐pressure synchrotron X‐ray diffraction and Raman spectroscopy have identified that SrSn 2 As 2 undergoes a structural transformation from a rhombohedral R m phase to the monoclinic C 2 /m phase. Beyond 28.3 GPa, T c is suppressed due to a reduction of the density of state (DOS) at the Fermi level. The discovery of pressure‐induced superconductivity, accompanied by structural transitions in SrSn 2 As 2 , greatly expands the physical properties of layered SnAs‐based compounds and provides new ground states upon compression. Superconductivity ; Zintl phase ; Phase (matter) ; Phase transition ; High pressure ; Materials science ; Crystallography ; Condensed matter physics ; Chemistry ; Crystal structure ; Physics ; Engineering physics Electronic and Structural Properties of Oxides ; Iron-based superconductors research ; Magnetic and transport properties of perovskites and related materials
Authors: Hyeona Lim | Seon Yeong Lee | Jin Young Kim | Yeon Ju Shin | Yoon Jung Jang | Hyeonjin Kim | Byung Hee Kim | Sangdoo Ahn
Source: Bulletin of the Korean Chemical Society (article, 2024-12-23)
Field: Chemistry — Analytical Chemistry

Comparison of machine learning models for classifying edible oils using Fourier‐transform infrared spectroscopy Abstract Accurate classification and authentication of edible oils are essential for maintaining product quality, ensuring consumer safety, and preserving market integrity. Therefore, this study aims to propose Fourier‐transform infrared (FT‐IR) spectroscopy, combined with advanced machine learning models, as a rapid and non‐destructive technique for classifying edible oils. The FT‐IR spectra of seven edible oil types were analyzed across three spectral regions: the full range, the C‐H stretching range, and the fingerprint region. Both absorbance and second derivative spectra were used to evaluate the influence of spectral preprocessing on classification accuracy. Six machine learning models—principal component analysis followed by linear discriminant analysis (PCA‐LDA), k‐nearest neighbors, decision tree, random forest, eXtreme Gradient Boosting, and support vector machines (SVM)—were employed to classify the oils, achieving training accuracies of 96.4%–100% and testing accuracies of 88.1%–100%. The second derivative spectra enhanced model performance by improving the resolution of overlapping peaks, particularly in the CH and CO stretching regions. Additionally, the SHapley Additive exPlanations analysis further revealed the most critical spectral features influencing model predictions, offering valuable insights into the decision‐making processes. This study demonstrates the effectiveness of combining FT‐IR spectroscopy, second derivative preprocessing, and machine learning techniques for classifying edible oils. The findings highlight the benefits of second derivative spectra in enhancing spectral resolution and the superior classification performance of PCA‐LDA and SVM models. These results offer a robust framework for advancing edible oil analysis and emphasize the potential of artificial intelligence in food authentication and quality control. Fourier transform infrared spectroscopy ; Fourier transform ; Infrared ; Fourier transform spectroscopy ; Infrared spectroscopy ; Materials science ; Analytical Chemistry (journal) ; Computer science ; Chemistry ; Chromatography ; Mathematics ; Engineering ; Physics ; Chemical engineering ; Organic chemistry ; Optics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Federico Napoli | Jia‐Ying Guan | Charles‐Adrien Arnaud | Pavel Macek | Hugo Fraga | Cécile Breyton | Paul Schanda
Source: Magnetic Resonance (article, 2024-04-19)
Field: Chemistry — Spectroscopy

Deuteration of proteins boosted by cell lysates: high-resolution amide and H <i>α</i> magic-angle-spinning (MAS) NMR without the reprotonation bottleneck Amide-proton-detected magic-angle-spinning NMR of deuterated proteins has become a main technique in NMR-based structural biology. In standard deuteration protocols that rely on D <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi></mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:math> O-based culture media, non-exchangeable amide sites remain deuterated, making these sites unobservable. Here we demonstrate that proteins produced with a H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi></mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:math> O-based culture medium doped with deuterated cell lysate allow scientists to overcome this "reprotonation bottleneck" while retaining a high level of deuteration (ca. 80 %) and narrow linewidths. We quantified coherence lifetimes of several proteins prepared with this labeling pattern over a range of magic-angle-spinning (MAS) frequencies (40-100 kHz). We demonstrate that under commonly used conditions (50-60 kHz MAS), the amide <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi></mml:mi> <mml:mn>1</mml:mn></mml:msup> </mml:math> H linewidths with our labeling approach are comparable to those of perdeuterated proteins and better than those of protonated samples at 100 kHz. For three proteins in the 33-50 kDa size range, many previously unobserved amides become visible. We report how to prepare the deuterated cell lysate for our approach from fractions of perdeuterated cultures which are usually discarded, and we show that such media can be used identically to commercial media. The residual protonation of H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>α</mml:mi></mml:math> sites allows for well-resolved H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>α</mml:mi></mml:math> -detected spectra and H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>α</mml:mi></mml:math> resonance assignment, exemplified by the de novo assignment of 168 H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>α</mml:mi></mml:math> sites in a 39 kDa protein. The approach based on this H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi></mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:math> O/cell-lysate deuteration and MAS frequencies compatible with 1.3 or 1.9 mm rotors presents a strong sensitivity benefit over 0.7 mm 100 kHz MAS experiments. Magic angle spinning ; High resolution ; Amide ; Chemistry ; Spinning ; Nuclear magnetic resonance spectroscopy ; Stereochemistry ; Biochemistry ; Geology ; Polymer chemistry Advanced NMR Techniques and Applications ; Chemical Reactions and Isotopes ; Mass Spectrometry Techniques and Applications
Authors: Zhaohui Li | Yiqing Lv
Source: IEEE photonics journal (article, 2024-01-29)
Field: Materials Science — Surfaces, Coatings and Films

Optimization for Si Nano-Pillar-Based Broadband Achromatic Metalens An innovative optimization algorithm, named the hybrid particle swarm and genetic algorithm (PSO_GA), is proposed for designing broadband achromatic metalenses. A database is first constructed by scanning the parameters of the unit cell of the metalenses using FDTD software, mapping each unit cell to its phase modulation capability. The PSO_GA is then utilized to identify the optimal phase matrix that minimizes chromatic aberration for a metalens operating within a specific wave band. Using the PSO_GA, a broadband achromatic metalens is designed and its performance is validated by simulation. The results reveal that the designed metalens successfully focuses light in a wide band (1000nm∼1250nm), achieving a mean focusing efficiency of up to 58%. This metalens design method offers a solution for the intelligent design of flat optical devices. Achromatic lens ; Broadband ; Particle swarm optimization ; Optics ; Finite-difference time-domain method ; Computer science ; Genetic algorithm ; Materials science ; Phase (matter) ; Optoelectronics ; Physics ; Algorithm Optical Coatings and Gratings ; Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications
Authors: Deniz Üresin | Jonathan Schulte | Nina Morgner | Jörg Soppa
Source: International Journal of Molecular Sciences (article, 2024-06-28)
Field: Materials Science — Materials Chemistry

C(P)XCG Proteins of Haloferax volcanii with Predicted Zinc Finger Domains: The Majority Bind Zinc, but Several Do Not In recent years, interest in very small proteins (µ-proteins) has increased significantly, and they were found to fulfill important functions in all prokaryotic and eukaryotic species. The halophilic archaeon <i>Haloferax volcanii</i> encodes about 400 µ-proteins of less than 70 amino acids, 49 of which contain at least two C(P)XCG motifs and are, thus, predicted zinc finger proteins. The determination of the NMR solution structure of HVO_2753 revealed that only one of two predicted zinc fingers actually bound zinc, while a second one was metal-free. Therefore, the aim of the current study was the homologous production of additional C(P)XCG proteins and the quantification of their zinc content. Attempts to produce 31 proteins failed, underscoring the particular difficulties of working with µ-proteins. In total, 14 proteins could be produced and purified, and the zinc content was determined. Only nine proteins complexed zinc, while five proteins were zinc-free. Three of the latter could be analyzed using ESI-MS and were found to contain another metal, most likely cobalt or nickel. Therefore, at least in haloarchaea, the variability of predicted C(P)XCG zinc finger motifs is higher than anticipated, and they can be metal-free, bind zinc, or bind another metal. Notably, AlphaFold2 cannot correctly predict whether or not the four cysteines have the tetrahedral configuration that is a prerequisite for metal binding. Haloferax volcanii ; Zinc ; Zinc finger ; Chemistry ; Biochemistry ; Archaea ; Metal ; Haloarchaea ; Crystallography ; Biology ; Gene ; Organic chemistry Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: Wesley Tien Chiang | Yao-Kai Chang | Wei-Han Hui | Shu-Wei Chang | Chenyi Liao | Yi-Chuan Chang | Chun‐Jung Chen | Wei‐Chen Wang | Chien‐Chen Lai | Chun-Hsiung Wang | Siou-Ying Luo | Yaping Huang | Shan‐Ho Chou | Tzyy‐Leng Horng | Ming‐Hon Hou | Stephen P. Muench | Ren‐Shiang Chen | Ming‐Daw Tsai | Nien‐Jen Hu
Source: Nature Communications (article, 2024-05-08)
Field: Materials Science — Materials Chemistry

Structural basis and synergism of ATP and Na+ activation in bacterial K+ uptake system KtrAB The K<sup>+</sup> uptake system KtrAB is essential for bacterial survival in low K<sup>+</sup> environments. The activity of KtrAB is regulated by nucleotides and Na<sup>+</sup>. Previous studies proposed a putative gating mechanism of KtrB regulated by KtrA upon binding to ATP or ADP. However, how Na<sup>+</sup> activates KtrAB and the Na<sup>+</sup> binding site remain unknown. Here we present the cryo-EM structures of ATP- and ADP-bound KtrAB from Bacillus subtilis (BsKtrAB) both solved at 2.8 Å. A cryo-EM density at the intra-dimer interface of ATP-KtrA was identified as Na<sup>+</sup>, as supported by X-ray crystallography and ICP-MS. Thermostability assays and functional studies demonstrated that Na<sup>+</sup> binding stabilizes the ATP-bound BsKtrAB complex and enhances its K<sup>+</sup> flux activity. Comparing ATP- and ADP-BsKtrAB structures suggests that BsKtrB Arg417 and Phe91 serve as a channel gate. The synergism of ATP and Na<sup>+</sup> in activating BsKtrAB is likely applicable to Na<sup>+</sup>-activated K<sup>+</sup> channels in central nervous system. Chemistry ; Adenosine triphosphate ; Biophysics ; Cell biology ; Biochemistry ; Biology Enzyme Structure and Function ; Photosynthetic Processes and Mechanisms ; Bacterial Genetics and Biotechnology
Authors: Abdul Rehman Basharat | Xingzhao Xiong | Tian Xu | Yong Zang | Liangliang Sun | Xiaowen Liu
Source: Journal of Proteome Research (article, 2024-12-06)
Field: Chemistry — Spectroscopy

TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the past decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using <i>Escherichia coli</i> K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS. Proteomics ; Computer science ; Software ; Computational biology ; Data mining ; Chemistry ; Biology ; Operating system ; Biochemistry Advanced Proteomics Techniques and Applications ; vaccines and immunoinformatics approaches ; Advanced Biosensing Techniques and Applications
Authors: Hongwei Cui | Haolei Zhang | Hao Ma | Jiangtao Ji
Source: Sensors (article, 2024-03-06)
Field: Chemistry — Analytical Chemistry

Research on SPAD Estimation Model for Spring Wheat Booting Stage Based on Hyperspectral Analysis With the rapid progression of agricultural informatization technology, the methodologies of crop monitoring based on spectral technology are constantly upgraded. In order to carry out the efficient, precise and nondestructive detection of relative chlorophyll (SPAD) during the booting stage, we acquired hyperspectral reflectance data about spring wheat vertical distribution and adopted the fractional-order differential to transform the raw spectral data. After that, based on correlation analysis, fractional differential spectra and fractional differential spectral indices with strong correlation with SPAD were screened and fused. Then, the least-squares support vector machine (LSSSVM) and the least-squares support vector machine (SMA-LSSSVM) optimized on the slime mold algorithm were applied to construct the estimation models of SPAD, and the model accuracy was assessed to screen the optimal estimation models. The results showed that the 0.4 order fractional-order differential spectra had the highest correlation with SPAD, which was 9.3% higher than the maximum correlation coefficient of the original spectra; the constructed two-band differential spectral indices were more sensitive to SPAD than the single differential spectra, in which the correlation reached the highest level of 0.724. The SMA-LSSSVM model constructed based on the two-band fractional-order differential spectral indices was better than the single differential spectra and the integration of both, which realized the assessment of wheat SPAD. Hyperspectral imaging ; Mathematics ; Correlation coefficient ; Correlation ; Spectral line ; Algorithm ; Statistics ; Artificial intelligence ; Computer science ; Physics ; Geometry Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research