Publications by authors named "Andres Jaramillo-Botero"

The accurate calculation of reaction-free energies (Δ°) for diboronic acids and carbohydrates is challenging due to reactant flexibility and strong solute-solvent interactions. In this study, these challenges are addressed with a semiautomatic workflow based on quantum chemistry methods to calculate conformational free energies, generate microsolvated solute structural ensembles, and compute Δ°. Workflow parameters were optimized for accuracy and precision while controlling computational costs.

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Drought and salinity stresses present significant challenges that exert a severe impact on crop productivity worldwide. Understanding the dynamics of salicylic acid (SA), a vital phytohormone involved in stress response, can provide valuable insights into the mechanisms of plant adaptation to cope with these challenging conditions. This paper describes and tests a sensor system that enables real-time and non-invasive monitoring of SA content in avocado plants exposed to drought and salinity.

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Nanocomposites made of magnetite (FeO) nanoparticles (NP)s with different surface chemistry and polyvinyl difluoride (PVDF) polymer were investigated using full atom molecular dynamics (MD) simulation. NPs with hydroxyl (OH), hexanoic, and oleic acid terminations were considered in this study. The effect of each surface chemistry was investigated in terms of the mechanical properties, the distribution of the internal energy around the NP, and the chain polarization gradient from the interface to the bulk.

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Aluminum in its Al form is a metal that inhibits plant growth, especially in acidic soils (pH < 5.5). Rapid and accurate quantitative detection of Al in agricultural soils is critical for the timely implementation of remediation strategies.

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Article Synopsis
  • - The integration of artificial intelligence (AI) in cancer research is growing, particularly in analyzing diagnostic images for cervical cancer, with a review of literature conducted under systematic guidelines.
  • - A comprehensive search identified 32 studies from 2009 to 2022, highlighting various AI algorithms like support vector machines, deep learning methods, and their performance in diagnosing cervical cancer from sources such as digital colposcopy and cervicography.
  • - Results indicated that deep learning techniques, especially convolutional neural networks, achieved over 97% accuracy in diagnosis, suggesting promising advancements, yet emphasizing the need for more research to confirm these outcomes.
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The use of Unmanned Aerial Vehicle (UAV) images for biomass and nitrogen estimation offers multiple opportunities for improving rice yields. UAV images provide detailed, high-resolution visual information about vegetation properties, enabling the identification of phenotypic characteristics for selecting the best varieties, improving yield predictions, and supporting ecosystem monitoring and conservation efforts. In this study, an analysis of biomass and nitrogen is conducted on 59 rice plots selected at random from a more extensive trial comprising 400 rice genotypes.

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Plant stress responses involve a suite of genetically encoded mechanisms triggered by real-time interactions with their surrounding environment. Although sophisticated regulatory networks maintain proper homeostasis to prevent damage, the tolerance thresholds to these stresses vary significantly among organisms. Current plant phenotyping techniques and observables must be better suited to characterize the real-time metabolic response to stresses.

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GCR1 has been proposed as a plant analogue to animal G-protein-coupled receptors that can promote or regulate several physiological processes by binding different phytohormones. For instance, abscisic acid (ABA) and gibberellin A1 (GA1) have been shown to promote or regulate germination and flowering, root elongation, dormancy, and biotic and abiotic stresses, among others. They may act through binding to GCR1, which would put GCR1 at the heart of key signaling processes of agronomic importance.

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Sucrose is a primary metabolite in plants, a source of energy, a source of carbon atoms for growth and development, and a regulator of biochemical processes. Most of the traditional analytical chemistry methods for sucrose quantification in plants require sample treatment (with consequent tissue destruction) and complex facilities, that do not allow real-time sucrose quantification at ultra-low concentrations (nM to pM range) under in vivo conditions, limiting our understanding of sucrose roles in plant physiology across different plant tissues and cellular compartments. Some of the above-mentioned problems may be circumvented with the use of bio-compatible ligands for molecular recognition of sucrose.

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The OMICAS alliance is part of the Colombian government's Scientific Ecosystem, established between 2017-2018 to promote world-class research, technological advancement and improved competency of higher education across the nation. Since the program's kick-off, OMICAS has focused on consolidating and validating a multi-scale, multi-institutional, multi-disciplinary strategy and infrastructure to advance discoveries in plant science and the development of new technological solutions for improving agricultural productivity and sustainability. The strategy and methods described in this article, involve the characterization of different crop models, using high-throughput, real-time phenotyping technologies as well as experimental tissue characterization at different levels of the omics hierarchy and under contrasting conditions, to elucidate epigenome-, genome-, proteome- and metabolome-phenome relationships.

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A critical path to solving the SARS-CoV-2 pandemic, without further socioeconomic impact, is to stop its spread. For this to happen, pre- or asymptomatic individuals infected with the virus need to be detected and isolated opportunely. Unfortunately, there are no current ubiquitous (i.

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The 21st century has already brought us a plethora of new threats related to viruses that emerge in humans after zoonotic transmission or drastically change their geographic distribution or prevalence. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first spotted at the end of 2019 to rapidly spread in southwest Asia and later cause a global pandemic, which paralyzes the world since then. We have designed novel immunosensors targeting conserved protein sequences of the N protein of SARS-CoV-2 based on lab-produced and purified anti-SARS-CoV-2 nucleocapsid antibodies that are densely grafted onto various surfaces (diamond/gold/glassy carbon).

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The pervasive use of portable electronic devices, powered from rechargeable batteries, represents a significant portion of the electricity consumption in the world. A sustainable and alternative energy source for these devices would require unconventional power sources, such as harvesting kinetic/potential energy from mechanical vibrations, ultrasound waves, and biomechanical motion, to name a few. Piezoelectric materials transform mechanical deformation into electric fields or, conversely, external electric fields into mechanical motion.

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We developed a new coarse-grained (CG) molecular dynamics force field for polyacrylamide (PAM) polymer based on fitting to the quantum mechanics (QM) equation of state (EOS). In this method, all nonbond interactions between representative beads are parameterized using a series of QM-EOS, which significantly improves the accuracy in comparison to common CG methods derived from atomistic molecular dynamics. This CG force-field has both higher accuracy and improved computational efficiency with respect to the OPLS atomistic force field.

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The atomic-scale fragmentation processes involved in molecules undergoing hypervelocity impacts (HVIs; defined as 3 km/s) are challenging to investigate via experiments and still not well understood. This is particularly relevant for the consistency of biosignals from small-molecular-weight neutral organic molecules obtained during solar system robotic missions sampling atmospheres and plumes at hypervelocities. Experimental measurements to replicate HVI effects on neutral molecules are challenging, both in terms of accelerating uncharged species and isolating the multiple transition states over very rapid timescales (1 ps).

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Traditional methods to measure spatio-temporal variations in biomass rely on a labor-intensive destructive sampling of the crop. In this paper, we present a high-throughput phenotyping approach for the estimation of Above-Ground Biomass Dynamics (AGBD) using an unmanned aerial system. Multispectral imagery was acquired and processed by using the proposed segmentation method called GFKuts, that optimally labels the plot canopy based on a Gaussian mixture model, a Montecarlo based K-means, and a guided image filtering.

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The potential for phosphorene-based devices has been compromised by the material's fast degradation under ambient conditions. Its tendency to fully oxidize under O-rich and humid environments, leads to the loss of its appealing semiconducting properties. However, partially-oxidized phosphorene (po-phosphorene), has been demonstrated to remain stable over significantly longer periods of time, thereby enabling its use in sensing applications.

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With the increasing power of computation systems, theoretical calculations provide a means for quick determination of material properties, laying out a research plan, and lowering material development costs. One of the most common is Density Functional Theory (DFT), which allows us to simulate the structure of chemical molecules or crystals and their interaction. In developing a new generation of biosensors, understanding the nature of functional linkers, antibodies, and ligands become essential.

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The development of new techniques or instruments for detecting and accurately measuring biomarker concentrations in living organisms is essential for early diagnosis of diseases, and for tracking the effectiveness of treatments. In chronic diseases, such as asthma, precise phenotyping can help predict the response of patients to treatments and reduce the risk of complications. Fractional exhaled nitric oxide (Fe) is a positive biomarker for eosinophilic asthma in humans, and it can be directly detected in the respiratory tract, at very low and volatile concentrations, which makes real-time measurement a challenge.

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This issue of PNAS features "nonequilibrium transport and mixing across interfaces," with several papers describing the nonequilibrium coupling of transport at interfaces, including mesoscopic and macroscopic dynamics in fluids, plasma, and other materials over scales from microscale to celestial. Most such descriptions describe the materials in terms of the density and equations of state rather than specific atomic structures and chemical processes. It is at interfacial boundaries where such atomistic information is most relevant.

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The development of new energetic materials (EMs) with improved detonation performance but low sensitivity and environmental impact is of considerable importance for applications in civilian and military fields. Often new designs are difficult to synthesize so predictions of performance in advance is most valuable. Examples include MTO (2,4,6-triamino-1,3,5-triazine-1,3,5-trioxide) and MTO3N (2,4,6-trinitro-1,3,5-triazine-1,3,5-trioxide) suggested by Klapötke as candidate EMs but not yet successfully synthesized.

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According to the World Health Organization (WHO), almost 2 billion people each year are infected worldwide with flu-like pathogens including influenza. This is a contagious disease caused by viruses belonging to the family Orthomyxoviridae. Employee absenteeism caused by flu infection costs hundreds of millions of dollars every year.

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Understanding the structural, thermal, and mechanical properties of thaumasite is of great interest to the cement industry, mainly because it is the phase responsible for the aging and deterioration of civil infrastructures made of cementitious materials attacked by external sources of sulfate. Despite the importance, effects of temperature and strain rate on the mechanical response of thaumasite had remained unexplored prior to the current study, in which the mechanical properties of thaumasite are fully characterized using the reactive molecular dynamics (RMD) method. With employing a first-principles based reactive force field, the RMD simulations enable the description of bond dissociation and formation under realistic conditions.

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Recently Debe reported that PtNi leads to extraordinary Oxygen Reduction Reaction (ORR) activity. However, several reports show that hardly any Ni remains in the layers of the catalysts close to the surface ("Pt-skin effect"). This paradox that Ni is essential to the high catalytic activity with the peak ORR activity at PtNi while little or no Ni remains close to the surface is explained here using large-scale first-principles-based simulations.

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