MultiToxPred 1.0: a novel comprehensive tool for predicting 27 classes of protein toxins using an ensemble machine learning approach.

Protein toxins are defense mechanisms and adaptations found in various organisms and microorganisms, and their use in scientific research as therapeutic candidates is gaining relevance due to their effectiveness and specificity against cellular targets. However, discovering these toxins is time-consuming and expensive. In silico tools, particularly those based on machine learning and deep learning, have emerged as valuable resources to address this challenge. Existing tools primarily focus on binary classification, determining whether a protein is a toxin or not, and occasionally identifying specific types of toxins. For the first time, we propose a novel approach capable of classifying protein toxins into 27 distinct categories based on their mode of action within cells. To accomplish this, we assessed multiple machine learning techniques and found that an ensemble model incorporating the Light Gradient Boosting Machine and Quadratic Discriminant Analysis algorithms exhibited the best performance. During the tenfold cross-validation on the training dataset, our model exhibited notable metrics: 0.840 accuracy, 0.827 F1 score, 0.836 precision, 0.840 sensitivity, and 0.989 AUC. In the testing stage, using an independent dataset, the model achieved 0.846 accuracy, 0.838 F1 score, 0.847 precision, 0.849 sensitivity, and 0.991 AUC. These results present a powerful next-generation tool called MultiToxPred 1.0, accessible through a web application. We believe that MultiToxPred 1.0 has the potential to become an indispensable resource for researchers, facilitating the efficient identification of protein toxins. By leveraging this tool, scientists can accelerate their search for these toxins and advance their understanding of their therapeutic potential.

Joint Object Detection and Re-Identification for 3D Obstacle Multi-Camera Systems.

The growing on-board processing capabilities have led to more complex sensor configurations, enabling autonomous car prototypes to expand their operational scope. Nowadays, the joint use of LiDAR data and multiple cameras is almost a standard and poses new challenges for existing multi-modal perception pipelines, such as dealing with contradictory or redundant detections caused by inference on overlapping images. In this paper, we address this last issue in the context of sequential schemes like F-PointNets, where object candidates are obtained in the image space, and the final 3D bounding box is then inferred from point cloud information. To this end, we propose the inclusion of a re-identification branch into the 2D detector, i.e., Faster R-CNN, so that objects seen from adjacent cameras can be handled before the 3D box estimation takes place, removing duplicates and completing the object's cloud. Extensive experimental evaluations covering both the 2D and 3D domains affirm the effectiveness of the suggested methodology. The findings indicate that our approach outperforms conventional Non-Maximum Suppression (NMS) methods. Particularly, we observed a significant gain of over 5% in terms of accuracy for cars in camera overlap regions. These results highlight the potential of our upgraded detection and re-identification system in practical scenarios for autonomous driving.

Depth and proximity of third molars to the inferior alveolar canal in panoramic radiographs of a Latin American population

Introduction: extraction of lower third molars involve the possible occurrence of complications such as injury of the content of the Inferior Alveolar Canal. Methods: a cross-sectional study was conducted with a sample of 6488 lower molar records of digital panoramic radiographs of patients from 6 Latin American countries from 2010-2015. The variables studied were the depth of lower third molar according to the Pell and Gregory classification, and the proximity of a third molar to the Inferior Alveolar Canal that was evaluated according to the proposed classification, based on a modification of the Langlais et al classification.20 Descriptive and bivariate statistical analyses were performed. Results: in terms of the proximity, the highest frequency was Intact with 27.45%(n=1781). Regarding the depth of the lower third molar, the most frequent were the Position B with 46.90%(n=3043) and Position A with 46.75%(n=3033). The proximity and depth of the lower third molar had statistical difference according to age(p<0.01) and sex (p<0.001). The overall proximity of the lower third molar to the Inferior alveolar canal, according to depth was 37.52%(n=1766) in Position A, in Position B it was 54.51%(n=2566) and Position C was 7.97%(n=375) and had association between variables(p<0.001). Conclusions: taking into consideration the modified classification of Langlais et al.20, lower third molars are close to the Inferior Alveolar Canal, and according to the Pell and Gregory classification for the depth, the most frequent positions are A and B. In addition, proximity and depth were associated with each other, and with the co-variables country, age, and sex.

Introducción: la extracción de terceros molars inferiores implica la posible aparición de complicaciones, como la lesión del contenido del Canal Alveolar Inferior. Métodos: se realizó un estudio transversal con una muestra de 6488 registros de terceros molares inferiores de radiografías panorámicas digitales en pacientes de 6 países latinoamericanos, entre 2010-2015. Las variables fueron profundidad del tercer molar inferior según la clasificación de Pell y Gregory, y proximidad del tercer molar al Canal Alveolar Inferior, evaluada según una clasificación propuesta, basada en la clasificación modificada de Langlais et al.20 Se realizaron análisis estadísticos descriptivos y bivariados. Resultados: en la proximidad, la mayor frecuencia se presentó en Intacto con 27,45%(n=1781); en cuanto a la profundidad del tercer molar inferior, las más frecuentes fueron la Posición B con 46,90%(n=3043) y la Posición A con 46,75%(n=3033). La proximidad y profundidad del tercer molar inferior presentaron diferencias estadísticas de acuerdo con la edad (p<0,01) y sexo (p<0,001). La proximidad total del tercer molar inferior al canal alveolar inferior, según la profundidad fue de 37,52%(n=1766) en Posición A, en Posición B de 54,51%(n=2566) y Posición C de 7,97%(n=375). Además, se presentó asociación entre las variables (p<0,001). Conclusiones: considerando la clasificación modificada de Langlais et al.20, la mayoría de los terceros molares inferiores están próximos al canal alveolar inferior; y según la profundidad de Pell y Gregory, las posiciones más frecuentes son A y B. Además, la proximidad y la profundidad se asociaron entre sí, y con las co-variables país, edad y sexo.

VirusHound-I: prediction of viral proteins involved in the evasion of host adaptive immune response using the random forest algorithm and generative adversarial network for data augmentation.

Throughout evolution, pathogenic viruses have developed different strategies to evade the response of the adaptive immune system. To carry out successful replication, some pathogenic viruses encode different proteins that manipulate the molecular mechanisms of host cells. Currently, there are different bioinformatics tools for virus research; however, none of them focus on predicting viral proteins that evade the adaptive system. In this work, we have developed a novel tool based on machine and deep learning for predicting this type of viral protein named VirusHound-I. This tool is based on a model developed with the multilayer perceptron algorithm using the dipeptide composition molecular descriptor. In this study, we have also demonstrated the robustness of our strategy for data augmentation of the positive dataset based on generative antagonistic networks. During the 10-fold cross-validation step in the training dataset, the predictive model showed 0.947 accuracy, 0.994 precision, 0.943 F1 score, 0.995 specificity, 0.896 sensitivity, 0.894 kappa, 0.898 Matthew's correlation coefficient and 0.989 AUC. On the other hand, during the testing step, the model showed 0.964 accuracy, 1.0 precision, 0.967 F1 score, 1.0 specificity, 0.936 sensitivity, 0.929 kappa, 0.931 Matthew's correlation coefficient and 1.0 AUC. Taking this model into account, we have developed a tool called VirusHound-I that makes it possible to predict viral proteins that evade the host's adaptive immune system. We believe that VirusHound-I can be very useful in accelerating studies on the molecular mechanisms of evasion of pathogenic viruses, as well as in the discovery of therapeutic targets.

Enzyme Engineering Strategies for the Bioenhancement of L-Asparaginase Used as a Biopharmaceutical.

Over the past few years, there has been a surge in the industrial production of recombinant enzymes from microorganisms due to their catalytic characteristics being highly efficient, selective, and biocompatible. L-asparaginase (L-ASNase) is an enzyme belonging to the class of amidohydrolases that catalyzes the hydrolysis of L-asparagine into L-aspartic acid and ammonia. It has been widely investigated as a biologic agent for its antineoplastic properties in treating acute lymphoblastic leukemia. The demand for L-ASNase is mainly met by the production of recombinant type II L-ASNase from Escherichia coli and Erwinia chrysanthemi. However, the presence of immunogenic proteins in L-ASNase sourced from prokaryotes has been known to result in adverse reactions in patients undergoing treatment. As a result, efforts are being made to explore strategies that can help mitigate the immunogenicity of the drug. This review gives an overview of recent biotechnological breakthroughs in enzyme engineering techniques and technologies used to improve anti-leukemic L-ASNase, taking into account the pharmacological importance of L-ASNase.

Review and perspective on bioinformatics tools using machine learning and deep learning for predicting antiviral peptides.

Viruses constitute a constant threat to global health and have caused millions of human and animal deaths throughout human history. Despite advances in the discovery of antiviral compounds that help fight these pathogens, finding a solution to this problem continues to be a task that consumes time and financial resources. Currently, artificial intelligence (AI) has revolutionized many areas of the biological sciences, making it possible to decipher patterns in amino acid sequences that encode different functions and activities. Within the field of AI, machine learning, and deep learning algorithms have been used to discover antimicrobial peptides. Due to their effectiveness and specificity, antimicrobial peptides (AMPs) hold excellent promise for treating various infections caused by pathogens. Antiviral peptides (AVPs) are a specific type of AMPs that have activity against certain viruses. Unlike the research focused on the development of tools and methods for the prediction of antimicrobial peptides, those related to the prediction of AVPs are still scarce. Given the significance of AVPs as potential pharmaceutical options for human and animal health and the ongoing AI revolution, we have reviewed and summarized the current machine learning and deep learning-based tools and methods available for predicting these types of peptides.

Current state of molecular and metabolic strategies for the improvement of L-asparaginase expression in heterologous systems.

Heterologous expression of L-asparaginase (L-ASNase) has become an important area of research due to its clinical and food industry applications. This review provides a comprehensive overview of the molecular and metabolic strategies that can be used to optimize the expression of L-ASNase in heterologous systems. This article describes various approaches that have been employed to increase enzyme production, including the use of molecular tools, strain engineering, and in silico optimization. The review article highlights the critical role that rational design plays in achieving successful heterologous expression and underscores the challenges of large-scale production of L-ASNase, such as inadequate protein folding and the metabolic burden on host cells. Improved gene expression is shown to be achievable through the optimization of codon usage, synthetic promoters, transcription and translation regulation, and host strain improvement, among others. Additionally, this review provides a deep understanding of the enzymatic properties of L-ASNase and how this knowledge has been employed to enhance its properties and production. Finally, future trends in L-ASNase production, including the integration of CRISPR and machine learning tools are discussed. This work serves as a valuable resource for researchers looking to design effective heterologous expression systems for L-ASNase production as well as for enzymes production in general.

Current Status of Omics in Biological Quality Elements for Freshwater Biomonitoring.

Freshwater ecosystems have been experiencing various forms of threats, mainly since the last century. The severity of this adverse scenario presents unprecedented challenges to human health, water supply, agriculture, forestry, ecological systems, and biodiversity, among other areas. Despite the progress made in various biomonitoring techniques tailored to specific countries and biotic communities, significant constraints exist, particularly in assessing and quantifying biodiversity and its interplay with detrimental factors. Incorporating modern techniques into biomonitoring methodologies presents a challenging topic with multiple perspectives and assertions. This review aims to present a comprehensive overview of the contemporary advancements in freshwater biomonitoring, specifically by utilizing omics methodologies such as genomics, metagenomics, transcriptomics, proteomics, metabolomics, and multi-omics. The present study aims to elucidate the rationale behind the imperative need for modernization in this field. This will be achieved by presenting case studies, examining the diverse range of organisms that have been studied, and evaluating the potential benefits and drawbacks associated with the utilization of these methodologies. The utilization of advanced high-throughput bioinformatics techniques represents a sophisticated approach that necessitates a significant departure from the conventional practices of contemporary freshwater biomonitoring. The significant contributions of omics techniques in the context of biological quality elements (BQEs) and their interpretations in ecological problems are crucial for biomonitoring programs. Such contributions are primarily attributed to the previously overlooked identification of interactions between different levels of biological organization and their responses, isolated and combined, to specific critical conditions.

Protein Modelling and Molecular Docking Analysis of Fasciola hepatica ß-Tubulin's Interaction Sites, with Triclabendazole, Triclabendazole Sulphoxide and Triclabendazole Sulphone.

PURPOSE: Fasciola hepatica is a globally distributed trematode that causes significant economic losses. Triclabendazole is the primary pharmacological treatment for this parasite. However, the increasing resistance to triclabendazole limits its efficacy. Previous pharmacodynamics studies suggested that triclabendazole acts by interacting mainly with the ß monomer of tubulin. METHODS: We used a high-quality method to model the six isotypes of F. hepatica ß-tubulin in the absence of three-dimensional structures. Molecular dockings were conducted to evaluate the destabilization regions in the molecule against the ligands triclabendazole, triclabendazole sulphoxide and triclabendazole sulphone. RESULTS: The nucleotide binding site demonstrates higher affinity than the binding sites of colchicine, albendazole, the T7 loop and pßVII (p < 0.05). We suggest that the binding of the ligands to the polymerization site of ß-tubulin can lead a microtubule disruption. Furthermore, we found that triclabendazole sulphone exhibited significantly higher binding affinity than other ligands (p < 0.05) across all isotypes of ß-tubulin. CONCLUSIONS: Our investigation has yielded new insight on the mechanism of action of triclabendazole and its sulphometabolites on F. hepatica ß-tubulin through computational tools. These findings have significant implications for ongoing scientific research ongoing towards the discovery of novel therapeutics to treat F. hepatica infections.

Time elapsed since peruvian children's last dental care and head of household educational attainment: findings from a national database.

BACKGROUND: It has been documented that the parents' highest level of education has an impact on their children's access to oral health services and the frequency of their use.This study aimed to determine the association between time elapsed since peruvian children's last dental care and head of household educational attainment. METHODS: Cross-sectional study using a database of children aged 0 to 11 years, with a final sample of 8012 participants. The dependent variable in this study was the time elapsed since last dental care and the independent variable was the head of household educational attainment. Other covariates considered were natural region, area of residence, place of residence, altitude, wealth index, health insurance coverage, sex and age. Descriptive, bivariate and multivariate statistical analyses were applied. RESULTS: Time elapsed since last dental care in the year 2021 was 5.68 years (SD = 5.25). A hierarchical multiple linear regression analysis was performed, analyzing the variables dimensions by separate and joint models. When head of household educational attainment was analyzed, there was no statistical significance (p = 0.262); however, other models did (p < 0.05). Model 4, which addresses all dimensions, was significant (p < 0.001) with an R2% of 0.011 and constant equal to 5.788; it showed significance with place of dental care, health insurance, altitude and age. CONCLUSIONS: No association was found between head of household educational attainment and time elapsed since last dental care; however, the latter was associated with place of care, health insurance coverage, altitude and age in Peruvian children.

In Silico Design of a Chimeric Humanized L-asparaginase.

Acute lymphoblastic leukemia (ALL) is the most common cancer among children worldwide, characterized by an overproduction of undifferentiated lymphoblasts in the bone marrow. The treatment of choice for this disease is the enzyme L-asparaginase (ASNase) from bacterial sources. ASNase hydrolyzes circulating L-asparagine in plasma, leading to starvation of leukemic cells. The ASNase formulations of E. coli and E. chrysanthemi present notorious adverse effects, especially the immunogenicity they generate, which undermine both their effectiveness as drugs and patient safety. In this study, we developed a humanized chimeric enzyme from E. coli L-asparaginase which would reduce the immunological problems associated with current L-asparaginase therapy. For these, the immunogenic epitopes of E. coli L-asparaginase (PDB: 3ECA) were determined and replaced with those of the less immunogenic Homo sapiens asparaginase (PDB:4O0H). The structures were modeled using the Pymol software and the chimeric enzyme was modeled using the SWISS-MODEL service. A humanized chimeric enzyme with four subunits similar to the template structure was obtained, and the presence of asparaginase enzymatic activity was predicted by protein-ligand docking.

Antibiotic discovery against Piscirickettsia salmonis using a combined in silico and in vitro approach.

Piscirickettsia salmonis is one of the main pathogens causing considerable economic losses in salmonid farming. The DNA gyrase of several pathogenic bacteria has been the target of choice for antibiotic design and discovery for years, due to its key function during DNA replication. In this study, we carried out a combined in silico and in vitro approach to antibiotic discovery targeting the GyrA subunit of Piscirickettsia salmonis. The in silico results of this work showed that flumequine (-6.6 kcal/mol), finafloxacin (-7.2 kcal/mol), rosoxacin (-6.6 kcal/mol), elvitegravir (-6.4 kcal/mol), sarafloxacin (-8.3 kcal/mol), orbifloxacin (-7.9 kcal/mol), and sparfloxacin (-7.2 kcal/mol) are docked with good affinities in the DNA binding domain of the Piscirickettsia salmonis GyrA subunit. In the in vitro inhibition assay, it was observed that most of these molecules inhibit the growth of Piscirickettsia salmonis, except for elvitegravir. We believe that this methodology could help to significantly reduce the time and cost of antibiotic discovery trials to combat Piscirickettsia salmonis within the salmonid farming industry.

Diagnosis and Treatment in Unilateral Condylar Hyperplasia.

Unilateral condylar hyperplasia (UCH) is an uncommon disease involving progressive facial asymmetry. The aim of this research was to perform an analysis of the diagnosis and treatment of patients with UCH in a clinical series. An observational retrospective study was performed on subjects with progressive facial asymmetry in the lower third of the face; all the subjects were under treatment with condylectomy and orthodontics to improve occlusion and face balance. Variables such as age, sex, clinical type, SPECT (single photon emission computed tomography) intensity and a requirement for secondary surgery were included; the Shapiro Wilk test was performed to analyze the normality of the data and nonparametric analysis and the Kruskal-Wallis or Mann-Whitney tests were used to assess the association between the SPECT difference and the variables, where 2-tailed p values < 0.05 were considered to be statistically significant. Forty-nine patients between 10 and 45 y.o. (average age: 19.1 ± 7.4 y.o.) were included in the study. There were 41 female (83.6%) and 8 male (16.4%) subjects. The SPECT analysis comparing the right and left condyles with more than 10% in caption of the isotope was present in 46 subjects; the results obtained using SPECT were not statistically related to the age or sex of the sample (p = 0.277). The patients were classified into clinical types I, II and III, and no correlations could be confirmed between the clinical type and other variables. High condylectomy was conducted on all patients, among which 14 patients underwent a secondary surgery for orthognathic or cosmetic treatment, and was not related to the initial variables used in diagnosis (p = 0.98); interestingly, the second surgical treatment was more present in the clinical type I and in subjects under 16 years old with no statistical differences. Clinical analysis, medical records, 3D imaging and SPECT should be used as a complementary analysis in assessing the diagnosis of UCH and progressive facial asymmetry.

Peruvian children toothbrushing during the COVID-19 pandemic.

Background: Toothbrushing is a convenient, inexpensive, widespread and culturally accepted method, resulting in an ideal public health outcome. This study aimed to determine the impact of the COVID-19 pandemic on toothbrushing in Peruvian children. Methods: This was a cross-sectional study conducted using a database of children aged 0 to 11 years, with a final sample of 39,124 participants, 15,974 in 2019 (62.03%) and 7088 in 2020 (55.54%). General toothbrushing, daily toothbrushing and minimum frequency of two times a day were dependent variables; the year was considered as the independent variable. In addition, other covariates such as geographical landscape, area of residence, place of residence, altitude, wealth index, health insurance cover, sex and age. Descriptive, bivariate and multivariate statistical analyses were applied. Results: General toothbrushing was 96.19% (n=51 013), daily toothbrushing was 87.47% (n=42 246) and minimum toothbrushing two times a day was 84.53% (n=33 957). In multivariate form, the year presented a negative association with daily toothbrushing (RPa: 0.97; CI95%: 0.96-0.98; p<0.001) and minimum toothbrushing two times a day (RPa: 0.97; CI95%: 0.95-0.98; p<0.001), adjusted for the previously associated co-variables. Conclusions: The year 2020 of the COVID-19 pandemic negatively impacted daily toothbrushing and minimum twice-daily toothbrushing of Peruvian children.

Helicobacter pyloril-asparaginase: a study of immunogenicity from an in silico approach.

Helicobacter pylori has become the causal agent of multiple forms of gastric disease worldwide, including gastric cancer. The enzyme l-asparaginase (ASNase) has been studied as a virulence factor. In this work, we performed an in silico investigation to characterize the immunological profile of H. pylori ASNase (HpASNase) to ascertain the possible implication of HpASNase immunogenicity in the H. pylori virulence mechanism. We applied a workflow based on bioinformatics tools, which, by calculating the relative frequency of immunogenic T-cell and B-cell epitopes, allowed us to predict the immunogenicity and allergenicity of HpASNase in silico. We also visualized the epitopes by mapping them into the native structure of the enzyme. We report for the first time the T-cell and B-cell epitope composition that contributes to the immunogenicity of this HpASNase, as well as the regions that could generate a hypersensitivity response in humans. ASNase from H. pylori resulted in highly immunogenic and allergenic. The high immunogenicity of HpASNase could imply the pathogenic mechanisms of H. pylori. This knowledge could be important for the development of new drugs against H. pylori infections. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03359-0.

Anthocyanins Found in Pinot Noir Waste Induce Target Genes Related to the Nrf2 Signalling in Endothelial Cells.

Grape pomace is a source of anthocyanins, which can prevent cardiovascular diseases due to their antioxidant properties. Anthocyanin activity is associated with the ability to regulate oxidative stress through the transcription factor Nrf2. Thus, the present study aimed to evaluate if the anthocyanins found in Pinot noir pomace extract can affect the target genes related to the Nrf2 signalling pathway in endothelial cells. Our results highlight that the predominant anthocyanin in the Pinot noir pomace extract was malvidin-3-glucoside (3.7 ± 2.7 Eq. Malv-3-glu/kg). Molecular docking indicated that cyanidin-3-glucoside (-6.9 kcal/mol), malvidin-3-glucoside (-6.6 kcal/mol) and peonidin-3-glucoside (-6.6 kcal/mol) showed the highest affinities for the binding sites of the BTB domains in Keap1, suggesting that these components may modify the interaction of this protein with Nrf2. In addition, when HUVEC cells were exposed to different concentrations of Pinot noir pomace extract (100 µg/mL, 200 µg/mL, and 400 µg/mL), no changes in Nrf2 gene expression were observed. However, the gene expression of HO-1 and NQO1, which are in the signalling pathway of this transcription factor, increased according the concentrations of the extract (p = 0.0004 and p = 0.0084, respectively). In summary, our results show that anthocyanins play a very important role in Nrf2 activation and release, while at the same time not promoting its transcription. These preliminary results strongly suggest that the Pinot noir pomace extract can serve as a potent bioactive component source that protects cells against oxidative stress.

Analysis of Muscle Lipidome in Juvenile Rainbow Trout Fed Rapeseed Oil and Cochayuyo Meal.

This study aimed to analyze the effects on the lipidome of juvenile Oncorhynchus mykiss muscle fed 90% Brassica napus "rapeseed" oil and different amounts of Durvillaea antarctica "Cochayuyo" meal (1.5, 3 and 6%) as a replacement for cellulose. The analysis allowed for the identification of 329 lipids, mainly represented by phospholipids and fatty esters. The inclusion of Brassica napus oil significantly increased the levels of C18:2 species and fatty esters of hydroxylated fatty acids, which could play a bioactive role in human health. One of the most abundant lipids in all fillets was Phosphatidylcholine 33:6, which, according to the literature, could be considered a biomarker for the identification of Oncorhynchus mykiss. In all experimental diets, the species Phosphatidylethanolamine 15:1-18:24 showed four-fold higher levels than the control; increments of n-3- and n-6-rich phospholipids were also observed. Diets containing Durvillaea antarctica meal did not generate more significant variation in fish muscle phospholipids relative to the muscle of the rapeseed-oil-only group. These lipid species consist of medium- and long-chain fatty acids with different degrees of unsaturation. Still, it appears that the rapeseed oil masks the lipid contribution of the meal, possibly due to the low levels of total lipids in the macroalgae.

Impact of the COVID-19 pandemic on the timing of dental care in elderly peruvians.

In Peru, there is low dental service use among older adults, in addition to a social gradient for use. Furthermore, the COVID-19 pandemic triggered complex scenarios characterized by inadequate access to health services, with greater impact on vulnerable population groups such as the elderly. The aim of this study was to determine the impact of the COVID-19 pandemic on the time since last dental care visit among elderly Peruvians. It was a cross-sectional study conducted on a population of 5247 respondents in 2019, and 5066 respondents in 2020. The study considered the answers of people who responded to the question on the last time they had received dental care, extracting a total 4045 subjects for 2019 and 3943 for 2020. The dependent variable was time since last dental care measured in years, while the variables on health, geographic and sociodemographic characteristics were grouped within three dimensions. A descriptive bivariate and multivariateanalysiswasapplied by means of multiple linear regression to analyze the behavior of the variables. Time since the last dental care visit was 7.93 years (SD=8.03) in 2019 and 7.94 years (SD=7.28) in 2020. A hierarchical multiple linear regression analysis was performed, where no variable in the 2019 model was significant; while for 2020, health, geographic, and sociodemographic characteristics variables were significant. In the analysis where the 'year' variable becomes independent, only model 4, which considers all variables, was valid (p=0.018). The variables 'area of residence' and 'wealth index' were also significant. To conclude, the 2020 pandemic year for COVID-19 had no impact on the time since last dental care visit among elderly Peruvians, though factors such as area of residence and wealth index were found to be associated with the time since last dental care visit.

En Perú, los adultos mayores presentan un bajo uso de los servicios odontológicos, además de percibirse una gradiente social para su utilización. Adicionalmente, la pandemia por COVID-19 desencadenó escenarios complejos, caracterizados por un inadecuado acceso a los servicios de salud, que afectó con mayor énfasis a grupos poblacionales vulnerables, como las personas en edades extremas. El objetivo de este estudio fue determinar el impacto de la pandemia por COVID-19 en el tiempo de atención odontológica en adultos mayores peruanos. Estudio transversal con población de 5247 encuestados para el 2019 y 5066 para el 2020. Se consideraron los registros de quienes respondieron a la pregunta sobre el tiempo desde su última atención odontológica, extrayéndose del 2019 un total de 4045 y para 2020, 3943 sujetos. La variable dependiente consistió en el tiempo desde la última atención odontológica medido en años; mientras que dentro de tres dimensiones,seagruparon a lasvariables sobre características de salud, geográficas y sociodemográficas. Se aplicó un análisis descriptivo, bivariado y multivariado, donde el tiempo desde la última atención odontológica en el año 2019 fue de 7.93 años (DE=8.03) y en el 2020 fue de 7.94 años (DE=7.28). Se realizó un análisis de regresión lineal múltiple jerárquica, donde ninguna variable del modelo 2019 fue significativa; mientras que para 2020, las variables características de salud, geográficas y sociodemográficas si lo fueron. Al análisis, donde el año pasa a ser independiente, sólo el modelo 4, que considera todas las variables fue válido (p=0.018); asimismo, el área de residencia e índice de riqueza presentaron significancia estadística. Para concluir, en el año 2020 la pandemia por COVID-19 no impactó en el tiempo de atención odontológica en adultos mayores peruanos, sin embargo, factores como área de residencia e índice de riqueza si presentaron asociación con el tiempo desdelaúltimaatención.

Impact of the COVID-19 pandemic on the timing of dental care in elderly peruvians / Impacto de la pandemia de COVID-19 en el tiempo de la atención odontológica en adultos mayores peruanos

ABSTRACT In Peru, there is low dental service use among older adults, in addition to a social gradient for use. Furthermore, the COVID-19 pandemic triggered complex scenarios characterized by inadequate access to health services, with greater impact on vulnerable population groups such as the elderly. The aim of this study was to determine the impact of the COVID-19 pandemic on the time since last dental care visit among elderly Peruvians. It was a cross-sectional study conducted on a population of 5247 respondents in 2019, and 5066 respondents in 2020. The study considered the answers of people who responded to the question on the last time they had received dental care, extracting a total 4045 subjects for 2019 and 3943 for 2020. The dependent variable was time since last dental care measured in years, while the variables on health, geographic and sociodemographic characteristics were grouped within three dimensions. A descriptive bivariate and multivariate analysis was applied by means of multiple linear regression to analyze the behavior of the variables. Time since the last dental care visit was 7.93 years (SD=8.03) in 2019 and 7.94 years (SD=7.28) in 2020. A hierarchical multiple linear regression analysis was performed, where no variable in the 2019 model was significant; while for 2020, health, geographic, and sociodemographic characteristics variables were significant. In the analysis where the 'year' variable becomes independent, only model 4, which considers all variables, was valid (p=0.018). The variables 'area of residence' and 'wealth index' were also significant. To conclude, the 2020 pandemic year for COVID-19 had no impact on the time since last dental care visit among elderly Peruvians, though factors such as area of residence and wealth index were found to be associated with the time since last dental care visit.

RESUMEN En Perú, los adultos mayores presentan un bajo uso de los servicios odontológicos, además de percibirse una gradiente social para su utilización. Adicionalmente, la pandemia por COVID-19 desencadenó escenarios complejos, caracterizados por un inadecuado acceso a los servicios de salud, que afectó con mayor énfasis a grupos poblacionales vulnerables, como las personas en edades extremas. El objetivo de este estudio fue determinar el impacto de la pandemia por COVID-19 en el tiempo de atención odontológica en adultos mayores peruanos. Estudio transversal con población de 5247 encuestados para el 2019 y 5066 para el 2020. Se consideraron los registros de quienes respondieron a la pregunta sobre el tiempo desde su última atención odontológica, extrayéndose del 2019 un total de 4045 y para 2020, 3943 sujetos. La variable dependiente consistió en el tiempo desde la última atención odontológica medido en años; mientras que dentro de tres dimensiones, se agruparon a las variables sobre características de salud, geográficas y sociodemográficas. Se aplicó un análisis descriptivo, bivariado y multivariado, donde el tiempo desde la última atención odontológica en el año 2019 fue de 7.93 años (DE=8.03) y en el 2020 fue de 7.94 años (DE=7.28). Se realizó un análisis de regresión lineal múltiple jerárquica, donde ninguna variable del modelo 2019 fue significativa; mientras que para 2020, las variables características de salud, geográficas y sociodemográficas si lo fueron. Al análisis, donde el año pasa a ser independiente, sólo el modelo 4, que considera todas las variables fue válido (p=0.018); asimismo, el área de residencia e índice de riqueza presentaron significancia estadística. Para concluir, en el año 2020 la pandemia por COVID-19 no impactó en el tiempo de atención odontológica en adultos mayores peruanos, sin embargo, factores como área de residencia e índice de riqueza si presentaron asociación con el tiempo desde la última atención.

A bioinformatics analysis of the CatSper channel in the class Actinopterygii.

The regulation of sperm motility is controlled by several variables, including mainly ion concentrations. In fish, Ca2+ concentrations play an important role in the regulation of sperm motility, and several reports highlight the importance of certain Ca2+ channels in the regulation of this cell function. CatSper is a calcium channel scarcely studied in fish. In the species Salmo salar, it has been shown that it is key in the regulation of sperm motility. Taking into account the relevance of this channel in sperm activation in fish, in this study we evaluated the presence and probable functionality of this channel in the class Actinopterygii. For this purpose, a rational bioinformatic analysis was carried out, which had been previously validated using in vitro techniques by our group. The bioinformatic analysis of the present work revealed that the functionality of CatSper of the species of the class Actinopterygii could be exclusive to freshwater and anadromous fish species. The results of this study showed that only some anadromous and freshwater fish species contain 11 subunits of the CatSper channel, which are enough to trigger sperm motility. Consequently, this study provides new data for a better understanding of the sperm activation mechanism in fish.