Models for predicting coffee yield from chemical characteristics of soil and leaves using machine learning.

BACKGROUND: Coffee farming constitutes a substantial economic resource, representing a source of income for several countries due to the high consumption of coffee worldwide. Precise management of coffee crops involves collecting crop attributes (characteristics of the soil and the plant), mapping, and applying inputs according to the plants' needs. This differentiated management is precision coffee growing and it stands out for its increased yield and sustainability. RESULTS: This research aimed to predict yield in coffee plantations by applying machine learning methodologies to soil and plant attributes. The data were obtained in a field of 54.6 ha during two consecutive seasons, applying varied fertilization rates in accordance with the recommendations of soil attribute maps. Leaf analysis maps also were monitored with the aim of establishing a correlation between input parameters and yield prediction. The machine-learning models obtained from these data predicted coffee yield efficiently. The best model demonstrated predictive fit results with a Pearson correlation of 0.86. Soil chemical attributes did not interfere with the prediction models, indicating that this analysis can be dispensed with when applying these models. CONCLUSION: These findings have important implications for optimizing coffee management and cultivation, providing valuable insights for producers and researchers interested in maximizing yield using precision agriculture. © 2024 Society of Chemical Industry.

Selection of forage grasses for cultivation under water-limited conditions using Manhattan distance and TOPSIS.

Extreme weather events, such as severe droughts, pose a threat to the sustainability of beef cattle by limiting the growth and development of forage plants and reducing the available pasture for animals. Thus, the search for forage species that are more tolerant and adapted to soil water deficit conditions is an important strategy to improve food supply. In this study, we propose utilizing the mathematical concept of the Manhattan distance to assess the variations in the morphological variables of tropical forage grasses under water-limited conditions. This study aimed to select genotypes of tropical forage grasses under different water stress levels (moderate or severe) at this distance and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Nine varieties from five species were examined. Forage grasses were grown in 12-L pots under three soil irrigation regimes [100% pot capacity-PC (well-irrigated control), 60% PC (moderate drought stress), and 25% PC (severe drought stress)] with four replicates. Drought stress treatments were applied for 25 days during the forage grass tillering and stalk elongation phases. After exposure to drought stress, the growth and morphological traits of forage plants were evaluated. The results show that the use of the Manhattan distance combined with TOPSIS helps in the genotypic selection of more stable tropical forage grass varieties when comparing plants exposed to moderate and severe drought conditions in relation to the nonstressful environment (control). The 'ADR 300', 'Pojuca', 'Marandu', and 'Xaraés' varieties show greater stability when grown in a greenhouse and subjected to water stress environments. The selected forage varieties can be used as parents in plant breeding programs, allowing us to obtain new drought-resistant genotypes.

Effects of chemotherapeutic drugs on the antioxidant capacity of human erythroleukemia cells with MDR phenotype.

In this work, we identified that different chemotherapeutic drugs may select cells with different antioxidant capacities. For this, we evaluated the sensitivity of two multidrug-resistant (MDR) erythroleukemia cell lines: Lucena (resistant to vincristine, VCR) and FEPS (resistant to daunorubicin, DNR) derived from the same sensitive cell K562 (non-MDR) to hydrogen peroxide. In addition, we evaluated how the cell lines respond to the oxidizing agent in the absence of VCR/DNR. In absence of VCR, Lucena drastically decreases cell viability when exposed to hydrogen peroxide, while FEPS is not affected even without DNR. To analyze whether selection by different chemotherapeutic agents may generate altered energetic demands, we analyzed the production of reactive oxygen species (ROS) and the relative expression of the glucose transporter 1 gene (glut1). We observed that the selection through DNR apparently generates a higher energy demand than VCR. High levels of transcription factors genes expression (nrf2, hif-1α, and oct4) were kept even when the DNR is withdrawn from the FEPS culture for one month. Together, these results indicate that DNR selects cells with greater ability to express the major transcription factors related to the antioxidant defense system and the main extrusion pump (ABCB1) related to the MDR phenotype. Taking into account that the antioxidant capacity of tumor cells is closely related to resistance to multiple drugs, it is evident that endogenous antioxidant molecules may be targets for the development of new anticancer drugs.

Selection of Soybean Genotypes under Drought and Saline Stress Conditions Using Manhattan Distance and TOPSIS.

The search for soybean genotypes more adapted to abiotic stress conditions is essential to boost the development and yield of the crop in Brazil and worldwide. In this research, we propose a new approach using the concept of distance (or similarity) in a vector space that can quantify changes in the morphological traits of soybean seedlings exposed to stressful environments. Thus, this study was conducted to select soybean genotypes exposed to stressful environments (saline or drought) using similarity based on Manhattan distance and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS is a multi-criteria decision method for selecting the best alternative using the concept of distance. The use of TOPSIS is essential because the genotypes are not absolutely similar in both treatments. That is, just the distance measure is not enough to select the best genotype simultaneously in the two stress environments. Drought and saline stresses were induced by exposing seeds of 70 soybean genotypes to -0.20 MPa iso-osmotic solutions with polyethylene glycol-PEG 6000 (119.6 g L-1) or NaCl (2.36 g L-1) for 14 days at 25 °C. The germination rate, seedling length, and seedling dry matter were measured. We showed here how the genotypic stability of soybean plants could be quantified by TOPSIS when comparing drought and salinity conditions to a non-stressful environment (control) and how this method can be employed under different conditions. Based on the TOPSIS method, we can select the best soybean genotypes for environments with multiple abiotic stresses. Among the 70 tested soybean genotypes, RK 6813 RR, ST 777 IPRO, RK 7214 IPRO, TMG 2165 IPRO, 5G 830 RR, 98R35 IPRO, 98R31 IPRO, RK 8317 IPRO, CG 7464 RR, and LG 60177 IPRO are the 10 most stable genotypes under drought and saline stress conditions. Owing to high stability and gains with selection verified for these genotypes under salinity and drought conditions, they can be used as genitors in breeding programs to obtain offspring with higher resistance to antibiotic stresses.

New Mechanistic Insight on the PIM-1 Kinase Inhibitor AZD1208 Using Multidrug Resistant Human Erythroleukemia Cell Lines and Molecular Docking Simulations.

BACKGROUND: PIM-1 is a kinase which has been related to the oncogenic processes like cell survival, proliferation, and multidrug resistance (MDR). This kinase is known for its ability to phosphorylate the main extrusion pump (ABCB1) related to the MDR phenotype. OBJECTIVE: In the present work, we tested a new mechanistic insight on the AZD1208 (PIM-1 specific inhibitor) under interaction with chemotherapy agents such as Daunorubicin (DNR) and Vincristine (VCR). MATERIALS AND METHODS: In order to verify a potential cytotoxic effect based on pharmacological synergism, two MDR cell lines were used: Lucena (resistant to VCR) and FEPS (resistant to DNR), both derived from the K562 non-MDR cell line, by MTT analyses. The activity of Pgp was ascertained by measuring accumulation and the directional flux of Rh123. Furthermore, we performed a molecular docking simulation to delve into the molecular mechanism of PIM-1 alone, and combined with chemotherapeutic agents (VCR and DNR). RESULTS: Our in vitro results have shown that AZD1208 alone decreases cell viability of MDR cells. However, co-exposure of AZD1208 and DNR or VCR reverses this effect. When we analyzed the ABCB1 activity AZD1208 alone was not able to affect the pump extrusion. Differently, co-exposure of AZD1208 and DNR or VCR impaired ABCB1 activity, which could be explained by compensatory expression of abcb1 or other extrusion pumps not analyzed here. Docking analysis showed that AZD1208 is capable of performing hydrophobic interactions with PIM-1 ATP- binding-site residues with stronger interaction-based negative free energy (FEB, kcal/mol) than the ATP itself, mimicking an ATP-competitive inhibitory pattern of interaction. On the same way, VCR and DNR may theoretically interact at the same biophysical environment of AZD1208 and also compete with ATP by the PIM-1 active site. These evidences suggest that AZD1208 may induce pharmacodynamic interaction with VCR and DNR, weakening its cytotoxic potential in the ATP-binding site from PIM-1 observed in the in vitro experiments. CONCLUSION: Finally, the current results could have a pre-clinical relevance potential in the rational polypharmacology strategies to prevent multiple-drugs resistance in human leukemia cancer therapy.

Geometrical features for premature ventricular contraction recognition with analytic hierarchy process based machine learning algorithms selection.

BACKGROUND AND OBJECTIVE: Premature ventricular contraction is associated to the risk of coronary heart disease, and its diagnosis depends on a long time heart monitoring. For this purpose, monitoring through Holter devices is often used and computational tools can provide essential assistance to specialists. This paper presents a new premature ventricular contraction recognition method based on a simplified set of features, extracted from geometric figures constructed over QRS complexes (Q, R and S waves). METHODS: Initially, a preprocessing stage based on wavelet denoising electrocardiogram signal scaling is applied. Then, the signal is segmented taking into account the ventricular depolarization timing and a new set of geometrical features are extracted. In order to validate this approach, simulations encompassing eight different classifiers are presented. To select the best classifiers, a new methodology is proposed based on the Analytic Hierarchy Process. RESULTS: The best results, achieved with an Artificial Immune System, were 98.4%, 91.1% and 98.7% for accuracy, sensitivity and specificity, respectively. When artificial examples were generated to balance the dataset, the recognition performance increased to 99.0%, 98.5% and 99.5%, employing the Support Vector Machine classifier. CONCLUSIONS: The proposed approach is compared with some of latest references and results indicate its effectiveness as a method for recognizing premature ventricular contraction. Besides, the overall system presents low computation load.

Modeling drug-drug interactions of AZD1208 with Vincristine and Daunorubicin on ligand-extrusion binding TMD-domains of multidrug resistance P-glycoprotein (ABCB1).

In the present study, the molecular docking mechanism based on pharmacodynamic interactions between the ligands AZD1208 and recognized chemotherapy agents (Vincristine and Daunorubicin) with human ATP-binding cassette (ABC) transporters (ABCB1) was investigated. For the first time, were combined an in silico approaches like molecular docking and ab initio computational simulation based on Density Functional Theory (DFT) to explain the drug-drug interaction mechanism of aforementioned chemotherapy ligands with the transmembrane ligand extrusion binding domains (TMDs) of ABCB1. In this regard, the theoretical pharmacodynamic interactions were characterized by using the Gibbs free energy (FEB, kcal/mol) from the best ABCB1-ligand docking complexes. The molecular docking results pointing that for the three chemotherapy ABCB1-ligand complexes are mainly based in non-covalent hydrophobic and hydrogen-bond interactions showing a similar toxicodynamic behavior in terms of strength of interaction (FEB, kcal/mol) and very close free binding energies when compared with the FEB-values of the ABCB1 specific-inhibitor (Rhodamine B) = -6.0 kcal/mol used as theoretical docking control to compare with FEB (AZD1208-ABCB1) ∼ FEB (Vincristine-ABCB1) ∼ FEB (Daunorubicin-ABCB1) -6.2 kcal/mol as average. Ramachandran plot suggests that the 3D-crystallographic structure from ABCB1 transporter can be efficiently-modeled with conformationally-favored Psi versus Phi dihedral angles for all key TMDs-residues. Though, the results of DFT-simulation corroborate the existence of drug-drug interaction between (AZD1208/Vincristine) > (AZD1208/Daunorubicin). These theoretical pieces of evidence have preclinical relevance potential in the design of the new drugs to understand the polypharmacology influence in the molecular mechanism of multiple-drugs resistance, contributing with a higher success in chemotherapy and prognosis of cancer patients.

Perception of a nursing team in the implantation of a reception with risk classification sector for pregnant women / Percepção da equipe de enfermagem sobre a implantação do setor de acolhimento com classificação de risco às gestantes

Abstract Objectives: to analyze the perception of a nursing team in the implantation of a Reception with Risk Classification (RRC) sector for pregnant women. Methods: a descriptive cross-sectional study with a qualitative approach performed in a private hospital and linked to the Public Health System in Feira de Santana city in Bahia State in 2016. 10 nursing team professionals participated in the study that provided direct care for the pregnant women who were in labor and in puerperium. A semi-structured questionnaire was applied with questions identifying and characterizing their sociodemographic profile and an interview addressing questions about RRC sector, the advantages of implanting RRC sector to care for the pregnant women in labor and the possible changes in the implantation in the professionals' routine. Results: the interviewees recognize that the RSRC is a way to administrate in the health services, reorganizing the work process, ensuring the quality of care, so its implementation is useful to differentiate care for pregnant women, with humanization and sensitivity, and create a bond among the professionals and the health users. Conclusions: the implementation of the RRC sector establishes improvement that ensures a relationship of trust among the health users and the professionals and the effectiveness of care for pregnancy emergencies and urgencies.

Resumo Objetivos: analisar a percepção da equipe de enfermagem sobre a implantação do setor de Acolhimento com Classificação de Risco (ACCR) às gestantes. Métodos: estudo transversal descritivo com abordagem qualitativa, realizado num hospital privado e conveniado ao Sistema Único de Saúde, na cidade de Feira de Santana- BA, em 2016. Participaram do estudo 10 profissionais da equipe de enfermagem que prestam assistência direta às gestantes em trabalho de parto e no puerpério. Foi aplicado um questionário semiestruturado contendo questões de identificação e caracterização do perfil sociodemográfico e uma entrevista abordando indagações sobre ACCR, as vantagens da implantação do setor de ACCR para a assistência às gestantes em trabalho de parto e as possíveis mudanças decorrentes desta implantação na rotina destes profissionais. Resultados: as entrevistadas reconhecem que o ACCR é um modo de operar nos serviços de saúde, reorganizando o processo de trabalho, garantindo a qualidade do atendimento, portanto sua implantação é necessária para uma assistência diferenciada às gestantes, com humanização e sensibilidade, e a formação de vínculo entre profissionais e usuários. Conclusões: a implantação do ACCR estabelece melhorias que garantem uma relação de confiança entre usuárias e profissionais e eficácia no atendimento às urgências e emergências gravídicas.

A wavelet-based method for power-line interference removal in ECG signals

Abstract Introduction The analysis of electrocardiogram (ECG) signals allows the experts to diagnosis several cardiac disorders. However, the accuracy of such diagnostic depends on the signals quality. In this paper it is proposed a simple method for power-line interference (PLI) removal based on the wavelet decomposition, without the use of thresholding techniques. Methods This method consists in identifying the ECG and noise frequency range for further zeroing wavelet detail coefficients in the subbands with no ECG coefficients in the frequency content. Afterward, the enhanced ECG signal is obtained by the inverse discrete wavelet transform (IDWT). In order to choose the wavelet function, several experiments were performed with synthetic signals with worse Signal-to-Noise Ratio (SNR). Results Considering the relative error metrics and runtime, the best wavelet function for denoising was Symlet 8. Twenty synthetic ECG signals with different features and eight real ECG signals, obtained in the Physionet Challenge 2011, were used in the experiments. Results show the advantage of the proposed method against thresholding and notch filter techniques, considering classical metrics of assessment. The proposed method performed better for 75% of the synthetic signals and for 100% of the real signals considering most of the evaluation measures, when compared with a thresholding technique. In comparison with the notch filter, the proposed method is better for all signals. Conclusion The proposed method can be used for PLI removal in ECG signals with superior performance than thresholding and notch filter techniques. Also, it can be applied for high frequencies denoising even without a priori frequencies knowledge.

OCT4 mutations in human erythroleukemic cells: implications for multiple drug resistance (MDR) phenotype.

The OCT4 transcription factor is a crucial stem cells marker and it has been related to the cancer stem cells concept. Moreover, it has also been associated to the multiple drug resistance (MDR) phenotype. Our first results pointed out a straight relation between OCT4 and ABC transporters in K562-derivative MDR (Lucena) cells. Sequencing of ABC promoters did not reveal any mutation that could explain the differential expression of OCT4 in Lucena cells. Furthermore, sequencing of the homeobox domain region from the OCT4 gene isolated from both cell lines evinced, for the first time, that this transcription factor is a target of mutations and might be related to the MDR phenotype. The encountered mutations implied in several amino acids substitutions in both cell lines. K562 had seven amino acids substituted (three of them exclusive), while Lucena had 13 substitutions (nine of them exclusive). In addition, an in silico search for phosphorylation motifs within the amino acid stretch compared showed that human normal OCT4 has seven potential phosphorylation motifs. However, K562 has lost one phosphorylation motif and Lucena two of them. These findings bring OCT4 as an important target for cancer treatment, especially those resistant to chemotherapy.