Nestor Cubillan
@uniatlantico.edu.co
Associated Professor
Universidad del Atlántico
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Daniela Navarro-Acosta, Ludis Coba-Jiménez, Waldo León-Sotomayor, Ricardo Vivas-Reyes, and Néstor Cubillán
Elsevier BV
Abiodun A. Ajibola, Néstor Cubillán, Ludis Coba-Jiménez, Julia Kłak, Lesław Sieroń, and Waldemar Maniukiewicz
Elsevier BV
Abiodun A. Ajibola, Néstor Cubillán, Agnieszka Wojciechowska, Lesław Sieroń, and Waldemar Maniukiewicz
Elsevier BV
Abiodun A. Ajibola, Néstor Cubillán, Agnieszka Wojciechowska, Lesław Sieroń, and Waldemar Maniukiewicz
Elsevier BV
Alejandro Romero, Joe Villa‐Medina, Jorge Ropero, and Néstor Cubillán
Wiley
AbstractIn the manufacturing process of ibuprofen soft gelatin capsules, controlling moisture content at each production line stage, including in their components—gelatin, fill content, and shell—is vital to ensure quality and stability. This study developed and assessed an analytical method for rapid and non‐destructive moisture determination using near‐infrared spectroscopy (NIRS) coupled with deep neural networks (DNN) on all stages of the ibuprofen production line. The NIRS‐DNN classifier models were able to distinguish between the three components, achieving accuracy scores of up to 99%. The DNN models for moisture quantification also demonstrated high accuracy, with R2 values exceeding 0.997 across all production stages and prediction errors to those of previously reported models. A significant advantage of the NIRS‐DNN approach was its ability to maintain accuracy over a wide moisture concentration range, from 7% to 48%. The ensemble model, NIRS‐EDNN, seamlessly integrated classification and quantification, revealing its potential for real‐time process control in soft gel manufacturing. The comprehensive sampling approach ensured a diverse representation of moisture content, thereby enhancing the understanding of its impact on the final product stability, demonstrating that this methodology is potentially applicable to any soft gelatin capsule tracking worldwide.
Farrah Cañavera‐Buelvas, María Ospina‐Castro, and Néstor Cubillán
Wiley
AbstractThis work presents a study investigating the inter‐ and intra‐molecular interactions within the Os3(CO)9(μ‐H)2(μ3‐η1: η1: η2‐C16H8) crystal. The crystal‘s behavior is analyzed by comparing experimental distances, revealing intriguing interactions. In the isolated molecule, an unconventional pyrene‐C−H⋅⋅⋅CO interaction is observed, an electron transfer from σ(C−H) to π*(CO). Strikingly, the Quantum Theory of Atoms in Molecules identifies similarities to an intramolecular charge‐inverted hydrogen bond, despite its relatively low stability due to proximity to critical points. Energy surface scans demonstrate that the interaction arises from van der Waals strain induced by the crystal‘s packing structure. The proximity between carbonyl and pyrene facilitates electron transfer between σ(C−H) and π*(CO) at distances similar to the crystal structure. A significant correlation is established between total energy and the ratio (|V|/G) of potential energy density (V) to Lagrangian kinetic energy (G) at bond (BCP) and ring (RCP) critical points, underscoring the role of electron delocalization on the pseudo‐ring in determining the existence and characteristics of these interactions. In conclusion, this study provides valuable insights into molecular interactions within the Os3(CO)9(μ‐H)2(μ3‐η1: η1: η2‐C16H8) crystal, enriching our understanding of crystal interactions and offering perspectives for further exploration in this field.
Jaime Echeverría-Pérez, Wendy Carvajal-Palacio, Leandro Gómez-Plata, Víctor Vacca-Jimeno, and Néstor Cubillán
Springer Science and Business Media LLC
Daniela Navarro‐Acosta, Ludis Coba‐Jimenez, Alfredo Pérez‐Gamboa, Néstor Cubillan, and Ricardo Vivas‐Reyes
Wiley
Quantitative structure-activity relationship(QSAR) modeled the biological activities of 30 cannabinoids with quantum similarity descriptors(QSD) and Comparative Molecular Field Analysis(CoMFA). The PubChem[https://pubchem.ncbi.nlm.nih.gov/] database provided the geometries, binding affinities(Ki) to the cannabinoid receptors type 1(CB1) and 2(CB2), and the median lethal dose(LD50) to breast cancer cells. An innovative quantum similarity approach combining (self)-similarity indexes calculated with different charge-fitting schemes under the Topo-Geometrical Superposition Algorithm(TGSA) were used to obtain QSARs. The determination coefficient(R2) and leave-one-out cross-validation[Q2(LOO)] quantified the quality of multiple linear regression and support vector machine models. This approach was efficient in predicting the activities, giving predictive and robust models for each endpoint [pLD50: R2=0.9666 and Q2(LOO)=0.9312; pKi(CB1): R2=1.0000 and Q2(LOO)=0.9727, and pKi(CB2): R2=0.9996 and Q2(LOO)=0.9460], where p is the negative logarithm. The descriptors based on the electrostatic potential encrypted better electronic information involved in the interaction. Moreover, the similarity-based descriptors generated unbiased models independent of an alignment procedure. The obtained models showed better performance than those reported in the literature. An additional 3D-QSAR CoMFA analysis was applied to 15 cannabinoids, taking THC as a template in a ligand-based approach. From this analysis, the region surrounding the amino group of the SR141716 ligand is the more favorable for the antitumor activity.
Zouaoui Setifi, Néstor Cubillán, Christopher Glidewell, Diego M. Gil, Elham Torabi, Miguel Morales-Toyo, Necmi Dege, Fatima Setifi, and Masoud Mirzaei
Elsevier BV
Rodolfo Izquierdo, Gustavo Chacón, Néstor Cubillán, and Hubert Stassen
Elsevier BV
Dayra Suárez-Martínez, Edgardo Angulo-Mercado, Ivan Mercado-Martínez, Victor Vacca-Jimeno, Claudia Tapia-Larios, and Néstor Cubillán
American Chemical Society (ACS)
Karen Saldaña, Edgardo Angulo, Ivan Mercado, Grey Castellar, and Néstor Cubillán
Elsevier BV
Ludis Coba‐Jiménez, Julio Maza, Mayamarú Guerra, Julio Deluque‐Gómez, and Néstor Cubillán
Wiley
Rodolfo Izquierdo, Ana Pérez, and Néstor Cubillán
EnPress Publisher
A theoretical study was carried out for the adsorption of N2, O2, NO and NO+ with Cerium (Ce) modified mordenite (MOR). A two-layer ONIOM2 (two layer Integrated molecular Orbital + molecular Mechanics) methodology was employed, combining UFF (Universal Force Field) and DFT (Density Functional Theory) calculations for the low and high level, respectively. The formation of active Ce species based on the adsorption of CeO+ on the crystallographic positions T1, T2 and T4 in the H-MOR was studied. The geometrical, vibrational and thermodynamic results indicate that the Ce atom of CeO+ binds exothermically and spontaneously to two of the non-equivalent (Om) crystallographic oxygens of MOR (TnOm1Om2) according to: T1O1O4, T1O2O3, T2O4O7, T2O5O7 and T4O7O10 (T: Al or Si). The results of the interaction of N2, O2, NO and NO+ with Ce-MOR indicate that only exothermic and spontaneous adsorptions occur on the active sites located over the main channel of the 12-membered ring (12-MR) according to T1O1O4, T2O5O7 and T4O7O10. In general, the Ce-MOR system stabilizes electrophilic [CeO(NO+)] species, with possible activity deNOx reactions in the presence of nucleophilic reductants such as NH3; while for CeO(NO) species adsorbed on MOR a dynamic equilibrium between κ1NO, κ1ON, κ2NO adsorptions is reported which could be applicable for deNOx catalysis in the absence of reductants. On the basis of thermodynamic reaction functions, it is proposed that the most likely site for the location of active CeO+ is T2O5O7.
Rodolfo Izquierdo, Néstor Cubillan, Mayamaru Guerra, and Merlín Rosales
Elsevier BV
Miguel Morales-Toyo, Sevgi Kansız, Necmi Dege, Christopher Glidewell, Ana Fuenmayor-Zafra, and Néstor Cubillán
Elsevier BV
Zouaoui Setifi, Néstor Cubillán, Christopher Glidewell, Susanta K. Nayak, Miguel Morales-Toyo, Ruhollah Khajavian, Fatima Setifi, and Masoud Mirzaei
Elsevier BV
Ernesto San‐Blas, Gabriel Paba, Néstor Cubillán, Edgar Portillo, Ana M. Casassa‐Padrón, César González‐González, and Mayamarú Guerra
Wiley
Plant parasitic nematodes are generally soilborne pathogens that attack plants and cause economic losses in many crops. The infested plants show nonspecific symptoms or, often, are symptomless; therefore, diagnosis is performed by taking soil and root tissue samples. Here, we show that a combination of different infrared spectra analysis and machine learning algorithms can be used to detect plant parasitic nematode infestations before symptoms become visible, using leaves instead of roots and soil as samples. We found that tomato and guava plants infested with Meloidogyne enterorlobii produced different spectral patterns compared to uninfested plants. Using partial spectra from 1,450 to 900/cm as the "fingerprint region", principal component analyses indicated that after 5 (tomatoes) or 8 weeks (guava), plants with no visible symptoms of infestations were positively diagnosed. To improve the early detection response, we used machine learning modelling. A support vector machine (SVM) was used to obtain more robust, accurate models. The SVM model contained 34 support vectors, 17 for each level. The overall performance of the model was >97% and the total accuracy was significantly higher, demonstrating the absence of chance prediction. The best prediction of infestation was obtained at the second and fourth weeks for tomatoes and guavas, respectively, reducing the diagnostic time by half. The combined application of these techniques reduces the processing time from field to laboratory and shows enormous advantages by avoiding root and soil sampling.
Miguel Morales-Toyo, Néstor Cubillán, Christopher Glidewell, Luis Seijas, Katerin Boscan-Melean, and Jelen Restrepo
Elsevier BV
Yovani Marrero-Ponce, Julio E. Teran, Ernesto Contreras-Torres, César R. García-Jacas, Yunierkis Perez-Castillo, Nestor Cubillan, Facundo Peréz-Giménez, and José R. Valdés-Martini
Elsevier BV
Mayamarú Guerra, Gabriel Paba, Néstor Cubillán, Edgar Portillo, Ana M. Casassa-Padrón, Erwin Aballay, and Ernesto San-Blas
Brill
Summary In this work, we found that tomato and guava plants infected with Meloidogyne enterolobii showed different Fourier-transformed infrared spectral patterns compared to non-infected plants. Additionally, by using two-dimensional correlation spectroscopy (2D-COS) we were able to track and explain those spectral differences according to the progression of the nematode infection in the plants. In general, 2D-COS reveals the same chain of changes in both tomatoes and guavas when under nematode infection. There is a decrease in bands representing amino acids and proteins, fatty acids and lipids are down-regulated, and sugars and total phenols increase in leaves of infected plants. The application of this technique provides useful information on the metabolic and biochemical changes in plant tissues when diseased in a rapid manner. This technique could be used in the future, combined with other methods, to improve field diagnosis, quality control, or to reduce analytical time for biochemical purposes.
Néstor Cubillán, Yovani Marrero-Ponce, and Alicia Inciarte
Universidad Nacional Autonoma de Mexico
A problem-based learning experience integrating mathematical concepts of linear and abstract algebra for undergraduate chemistry students is presented. The pedagogical framework was focused on the conceptual understanding of the vector space, graph theory and matrix algebra as a tool to obtain chemical information. The students were capable to solve a problem of physicochemical properties prediction through the calculation of molecular descriptors of the TOMOCOMD (acronym for TO pological MO lecular COM puter D esign) approach. A “scientific congress” was organized by students to expose the results of the research. This evaluation strategy stimulated the self- and co-evaluation. The proposed experience demonstrated an enhanced learning compared to the traditional model.
Miguel Morales-Toyo, Christopher Glidewell, Julia Bruno-Colmenares, Néstor Cubillán, Ronald Sánchez-Colls, Ysaias Alvarado, and Jelen Restrepo
Elsevier BV
V. Araujo-Contreras, F. Yepez, O. Castellano, J. Urdaneta, and N. Cubillán
Informa UK Limited
ABSTRACT The molecular electric properties and energy of the complexes formed between graphene models of different areas with chrysene, 20 dibenzo[a,h]anthracene and dibenzo[a,h]pyrene were investigated at the density functional theory (DFT) level. Three different sizes (in Å) of graphene models were analyzed: 10 × 10, 15 × 15 and 20 × 20. DFT calculations were performed with the software Materials Studio 5.5, using the functionals HCTH and PBE with Grimme's dispersion correction (PBE-D), within the generalized gradient approximation GGA and numerical DNP basis set. According to results, the PBE-D functional allows a good description of structure, energy and electrical properties of studied systems. In contrast, the HCTH functional poorly reproduced the energy and structures, whereas it allows the description of the complexes through the interaction electric properties. The close relationship between the interaction energy with the interaction polarizability suggests a high contribution of the London dispersion forces.
Jelem Restrepo, Christopher Glidewell, Néstor Cubillán, Ysaias Alvarado, Necmi Dege, and Miguel Morales-Toyo
Elsevier BV