Do deep learning models make a difference in the identification of antimicrobial peptides?

In the last few decades, antimicrobial peptides (AMPs) have been explored as an alternative to classical antibiotics, which in turn motivated the development of machine learning models to predict antimicrobial activities in peptides. The first generation of these predictors was filled with what is now known as shallow learning-based models. These models require the computation and selection of molecular descriptors to characterize each peptide sequence and train the models. The second generation, known as deep learning-based models, which no longer requires the explicit computation and selection of those descriptors, started to be used in the prediction task of AMPs just four years ago. The superior performance claimed by deep models regarding shallow models has created a prevalent inertia to using deep learning to identify AMPs. However, methodological flaws and/or modeling biases in the building of deep models do not support such superiority. Here, we analyze the main pitfalls that led to establish biased conclusions on the leading performance of deep models. Also, we analyze whether deep models truly contribute to achieve better predictions than shallow models by performing fair studies on different state-of-the-art benchmarking datasets. The experiments reveal that deep models do not outperform shallow models in the classification of AMPs, and that both types of models codify similar chemical information since their predictions are highly similar. Thus, according to the currently available datasets, we conclude that the use of deep learning could not be the most suitable approach to develop models to identify AMPs, mainly because shallow models achieve comparable-to-superior performances and are simpler (Ockham's razor principle). Even so, we suggest the use of deep learning only when its capabilities lead to obtaining significantly better performance gains worth the additional computational cost.

Upregulated Nuclear Expression of Soluble Epoxide Hydrolase Predicts Poor Outcome in Breast Cancer Patients: Importance of the Digital Pathology Approach.

Breast cancer (BC) is the most common cancer in women, with incidence rates increasing globally in recent years. Therefore, it is important to find new molecules with prognostic and therapeutic value to improve therapeutic response and quality of life. The polyunsaturated fatty acids (PUFAs) metabolic pathway participates in various physiological processes, as well as in the development of malignancies. Although aberrancies in the PUFAs metabolic pathway have been implicated in carcinogenesis, the functional and clinical relevance of this pathway has not been well explored in BC. To evaluate the clinical significance of soluble epoxide hydrolase (EPHX2) expression in Mexican patients with BC using tissue microarrays (TMAs) and digital pathology (DP). Immunohistochemical analyses were performed on 11 TMAs with 267 BC samples to quantify this enzyme. Using DP, EPHX2 protein expression was evaluated solely in tumor areas. The association of EPHX2 with overall survival (OS) was detected through bioinformatic analysis in public databases and confirmed in our cohort via Cox regression analysis. Clear nuclear expression of EPHX2 was identified. Receiver operating characteristics (ROC) curves revealed the optimal cutoff point at 2.847062 × 10-3 pixels, with sensitivity of 69.2% and specificity of 67%. Stratification based on this cutoff value showed elevated EPHX2 expression in multiple clinicopathological features, including older age and nuclear grade, human epidermal growth factor receptor 2 (HER2) and triple negative breast cancer (TNBC) subtypes, and recurrence. Kaplan-Meier curves demonstrated how higher nuclear expression of EPHX2 predicts shorter OS. Consistently, multivariate analysis confirmed EPHX2 as an independent predictor of OS, with a hazard ratio (HR) of 3.483 and a 95% confidence interval of 1.804-6.724 (p < 0.001). Our study demonstrates for the first time that nuclear overexpression of EPHX2 is a predictor of poor prognosis in BC patients. The DP approach was instrumental in identifying this significant association. Our study provides valuable insights into the potential clinical utility of EPHX2 as a prognostic biomarker and therapeutic target in BC.

Alignment-Free Antimicrobial Peptide Predictors: Improving Performance by a Thorough Analysis of the Largest Available Data Set.

In the last two decades, a large number of machine-learning-based predictors for the activities of antimicrobial peptides (AMPs) have been proposed. These predictors differ from one another in the learning method and in the training and testing data sets used. Unfortunately, the training data sets present several drawbacks, such as a low representativeness regarding the experimentally validated AMP space, and duplicated peptide sequences between negative and positive data sets. These limitations give a low confidence to most of the approaches to be used in prospective studies. To address these weaknesses, we propose novel modeling and assessing data sets from the largest experimentally validated nonredundant peptide data set reported to date. From these novel data sets, alignment-free quantitative sequence-activity models (AF-QSAMs) based on Random Forest are created to identify general AMPs and their antibacterial, antifungal, antiparasitic, and antiviral functional types. An applicability domain analysis is carried out to determine the reliability of the predictions obtained, which, to the best of our knowledge, is performed for the first time for AMP recognition. A benchmarking is undertaken between the models proposed and several models from the literature that are freely available in 13 programs (ClassAMP, iAMP-2L, ADAM, MLAMP, AMPScanner v2.0, AntiFP, AMPfun, PEPred-suite, AxPEP, CAMPR3, iAMPpred, APIN, and Meta-iAVP). The models proposed are those with the best performance in all of the endpoints modeled, while most of the methods from the literature have weak-to-random predictive agreements. The models proposed are also assessed through Y-scrambling and repeated k-fold cross-validation tests, demonstrating that the outcomes obtained by them are not given by chance. Three chemometric analyses also confirmed the relevance of the peptides descriptors used in the modeling. Therefore, it can be concluded that the models built by fixing the drawbacks existing in the literature contribute to identifying antibacterial, antifungal, antiparasitic, and antiviral peptides with high effectivity and reliability. Models are freely available via the AMPDiscover tool at https://biocom-ampdiscover.cicese.mx/.

Driver's Personality and Behavior for Boosting Automobile Security and Sensing Health Problems Through Fuzzy Signal Detection Case Study: Mexico City.

Automobile security became an essential theme over the last years, and some automakers invested much money for collision avoidance systems, but personalization of their driving systems based on the user's behavior was not explored in detail. Furthermore, efficiency gains could be had with tailored systems. In Mexico, 80% of automobile accidents are caused by human beings; the remaining 20% are related to other issues such as mechanical problems. Thus, 80% represents a significant opportunity to improve safety and explore driving efficiency gains. Moreover, when driving aggressively, it could be connected with mental health as a post-traumatic stress disorder. This paper proposes a Tailored Collision Mitigation Braking System, which evaluates the driver's personality driving treats through signal detection theory to create a cognitive map that understands the driving personality of the driver. In this way, aggressive driving can be detected; the system is then trained to recognize the personality trait of the driver and select the appropriate stimuli to achieve the optimal driving output. As a result, when aggressive driving is detected continuously, an automatic alert could be sent to the health specialists regarding particular risky behavior linked with mental problems or drug consumption. Thus, the driving profile test could also be used as a detector for health problems.

Mapping Opportunities for Transportation Electrification to Address Social Marginalization and Air Pollution Challenges in Greater Mexico City.

Amid climate change and public health concerns, world economies are seeking to reduce the greenhouse gas emissions and local air pollution from transportation. Population growth in cities worldwide will further increase demand for clean and affordable transportation. We propose a city-specific environmental justice mapping index, inspired by a similar index used in California, that highlights promising areas for clean transportation interventions in Greater Mexico City to reduce greenhouse gas emissions and local pollution. This novel approach leverages highly spatially resolved population, pollution, and transportation data. The proposed index score is designed as an open source, updateable point of orientation for decisionmakers as they consider investment in transportation electrification from the standpoint of overlapping atmospheric pollution and social vulnerability.

Factors associated with early platelet activation in obese children.

OBJECTIVE: To investigate the factors associated with platelet activation in obese children. DESIGN: Cross-sectional study. SETTING: Department of Pediatrics of Regional Hospital N∘ 1 of Mexican Institute of Social Security in Morelia, Michoacán, Mexico. PARTICIPANTS: 79 obese and 64 non-obese children between the ages of 5 and 10 years. MAIN OUTCOMES MEASURES: Obese children (body mass index [BMI] >85 in growth curves for Centers for Disease Control/National Center for Health Statistics), and the control group of 64 non-obese children (percentile <85), % body fat, platelet activation was assessed by sP-selectin. Other measures were leptin, uric acid (UA), von Willebrand Factor (vWF), plasminogen activator inhibitor (PAI-1), lipid profile, and glucose. RESULTS: Obese children displayed higher plasma sP-selectin, leptin, PAI-1, and vWF than non-obese children. In the univariate logistic regression analysis, leptin, vWF, UA, and high density lipoprotein (HDL), but not with PAI-1, were factors associated with platelet activation. By stepwise linear regression analysis adjusted by sex and age, the best predictor variables for platelet activation were leptin (ß:0.381; t:4.665; P=0.0001), vWF (ß:0.211; t:2.926; P=0.004), UA (ß:0.166; t:2.146; P=0.034), and HDL (ß:-0.215; t:-2.819; P=0.006). CONCLUSIONS: Obese children have a higher risk of developing early platelet activation. Factors associated with platelet activation were Leptin, vWF, UA, and HDL. Further studies involving larger numbers of patients over a longer duration are needed to understand the possible molecular mechanism underlying the association between leptin, vWF, and UA and endothelial activation and/or endothelial damage/dysfunction in obese children and its influence in cardiovascular disease in adults.

C4d expression in focal segmental glomerulosclerosis.

BACKGROUND: There is a little information about of expression of C4d (complement fragment) in Focal segmental glomerulosclerosis (FSGS) subtypes. Our aim was to determine the expression of C4d in FSGS subtypes in percutaneous native renal biopsies in a second-level hospital and its correlation with clinical, biochemical and histological variables. MATERIAL AND METHODS: A retrospective study in paraffin blocks of patients with biopsy with FSGS aged 16-65 years, indistinct sex, not diabetic or obese. Immunohistochemistry was performed for C4d and their expression was analyzing in non-sclerosed glomerular capillaries (GC) and sclerosis areas (SA). Clinical and biochemical variables were recorded. The cases were divided into C4d positive and C4d negative groups and compared. The correlation between C4d staining scores in CG and SA with clinical and biochemical variables were analyzed. RESULTS: Twenty samples were analyzed, 4 for each subtype. At the time of biopsy average age 38.8 ±â€¯18.6 years, 65% male, 8.7% were hypertension. The percentage of positivity for C4d was 40% in GC, 30% SA and 35% in mesangium. The highest expression was for cellular and collapsing subtypes. C4d positivity cases had increased proteinuria (p = 0.035). A significant correlation was found between percentage of C4d expression in CG with SA (p = 0.012) and SA with tubular atrophy and interstitial fibrosis (p < 0.05). CONCLUSIONS: C4d expression in FSGS predominated in the cellular and collapsing subtypes, which translates complement activation. C4d is a possible surrogate marker in GSFS.

Sequencing and description of the genome of a strain of Stenotrophomonas geniculata isolated from a patient infected with COVID-19 at Hospital Regional No.1 de Charo, Michoacán, México.

Stenotrophomonas is a bacterial genus that can be found in various environments, such as water, soil, and clinical samples. Due to their high genetic and phenotypic diversity, it is difficult to properly identify and classify all isolates. The COVID-19 pandemic caused an increase in nosocomial infections, which played a major role in the high mortality rate among patients in intensive care. This is the first report of the identification of S. geniculata as a nosocomial opportunistic pathogen isolated from a patient with COVID-19. Their genome was isolated, sequenced, and assembled, and it consists of 4,488,090 bp in 24 contigs, 4,103 coding sequences, and a G+C content of 66.58%.

An observational study investigating soluble immune checkpoints as indicators of severe COVID-19.

This study aimed to investigate the immunomodulatory behavior of soluble immune checkpoints (sICPs) and other biomarkers in the pathophysiology of SARS-CoV-2 infection. The study included 59 adult participants, 43 of whom tested positive for SARS-CoV-2. Patients were divided into three cohorts: those with moderate disease (n = 16), recovered patients with severe disease (n = 13), and deceased patients with severe disease (n = 16). In addition, 16 participants were pre-pandemic subjects negative for SARS-CoV-2. The relative activity of neutralizing antibodies (rNAbs) against SARS-CoV-2 and the values of 14 sICPs in peripheral blood were compared between the four groups. Because the increase of markers values of inflammation [NLR > 12; CRP > 150 mg/L] and venous thromboembolism [D-dimer > 0.5 mg/L] has been associated with mortality from COVID-19, the total and differential leukocyte counts, the NLR, and CRP and D-dimer values were obtained in patients with severe disease. No differences in rNAbs were observed between the cohorts. Only the levels of five sICPs, sCD27, sHVEM sTIM-3, sPD-1, and sPDL-1, were significantly higher in patients with severe rather than moderate disease. The sPDL-2 level and NLR were higher in deceased patients than in recovered patients. However, there was no difference in CRP and D-dimer values between the two groups. Of the five soluble biomarkers compared among patients with severe disease, only sPDL-2 was higher in deceased patients than in recovered patients. This suggests that immuno-inhibitory sICPs might be used as indicators for severe COVID-19, with sPDL-2 used to assess individual risk for fatality.IMPORTANCECOVID-19, the disease caused by a SARS-CoV-2 infection, generates a broad spectrum of clinical symptoms, progressing to multiorgan failure in the most severe cases. As activation of the immune system is pivotal to eradicating the virus, future research should focus on identifying reliable biomarkers to efficiently predict the outcome in severe COVID-19 cases. Soluble immune checkpoints represent the function of the immune system and are easily determined in peripheral blood. This research could lead to implementing more effective severity biomarkers for COVID-19, which could increase patients' survival rate and quality of life.

B-Cell Activating Factor Increases Related to Adiposity, Insulin Resistance, and Endothelial Dysfunction in Overweight and Obese Subjects.

Obesity (OB) is a major healthcare problem that results from long-term energy imbalance. Adipokines and pro-inflammatory cytokines facilitate adipose tissue (AT) remodeling to safely store excess nutrients. B-cell activating factor (BAFF) is a newly described adipokine whose role in enhancing adipogenesis has been reported. The present study aimed to evaluate serum BAFF association with adiposity distribution, serum adipokines, pro-inflammatory cytokines, and metabolic and endothelial dysfunction markers. The study included 124 young Mexican adults with no diagnosed comorbidities, divided according to their BMI. Anthropometric measurements, blood counts, and serum molecules (i.e., glucose, lipid profile, insulin, leptin, pro- and anti-inflammatory cytokines, von Willebrand factor (vWF), and BAFF) were assessed. The analysis showed positive correlation between BAFF and increased fat mass in all anthropometric measurements (p < 0.0001). BAFF augmentation was related to systemic inflammatory environment (p < 0.05), and linked with insulin resistance status (p < 0.05). BAFF increment was also correlated with early endothelial damage markers such as vWF (p < 0.0001). Linear regression analysis showed a role for BAFF in predicting serum vWF concentrations (p < 0.01). In conclusion, our data show that BAFF is an adipokine dynamically related to OB progression, insulin resistance status, and systemic inflammatory environment, and is a predictor of soluble vWF augmentation, in young overweight and obese Mexican subjects.

Glycogen Synthase Kinase 3ß Modulates the Inflammatory Response Activated by Bacteria, Viruses, and Parasites.

Knowledge of glycogen synthase kinase 3ß (GSK3ß) activity and the molecules identified that regulate its function in infections caused by pathogenic microorganisms is crucial to understanding how the intensity of the inflammatory response can be controlled in the course of infections. In recent years many reports have described small molecular weight synthetic and natural compounds, proteins, and interference RNA with the potential to regulate the GSK3ß activity and reduce the deleterious effects of the inflammatory response. Our goal in this review is to summarize the most recent advances on the role of GSK3ß in the inflammatory response caused by bacteria, bacterial virulence factors (i.e. LPS and others), viruses, and parasites and how the regulation of its activity, mainly its inhibition by different type of molecules, modulates the inflammation.

Behavior of Eosinophil Counts in Recovered and Deceased COVID-19 Patients over the Course of the Disease.

Knowledge about the immune responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, particularly regarding the function of eosinophils, has been steadily emerging recently. There exists controversy regarding the implications of eosinophils in the coronavirus disease 2019 (COVID-19)'s pathology. We report a retrospective cohort study including the comparison of leukocyte counts in COVID-19 patients, considering the outcomes of recovery (n = 59) and death (n = 60). Among the different types of leukocytes, the eosinophil counts were those that showed the greatest difference between recovered and deceased patients. Eosinopenia (eosinophil count < 0.01 × 109/L) was more frequently observed in deceased than recovered patients (p = 0.0012). The eosinophil counts more rapidly increased and showed a greater proportion over the course of the disease in the recovered than deceased patients. Furthermore, the estimated survival rate was greater in patients without eosinopenia than in patients with eosinopenia (p = 0.0070) during hospitalization. Importantly, recovered but not deceased patients showed high negative correlations of the eosinophils with the neutrophil-to-lymphocyte ratio (NLR) and neutrophil counts at Day 9 of the onset of clinical symptoms (p ≤ 0.0220). Our analysis suggests that eosinopenia may be associated with unfavorable disease outcomes and that the eosinophils have a beneficial function in COVID-19 patients, probably contributing by controlling the exacerbated inflammation induced by neutrophils.

Prevalence of malnutrition-inflammation complex syndrome and its correlation with thyroid hormones in chronic haemodialysis patients. / Prevalencia del síndrome complejo de malnutrición e inflamación y su correlación con las hormonas tiroideas en pacientes en hemodiálisis crónica.

INTRODUCTION: Low levels of thyroid hormones, total triiodothyronine (T3) and free triiodothyronine (FT3) in haemodialysis patients is a marker of malnutrition and inflammation and are predictors of mortality. The aim of this study was to determine the prevalence of malnutrition-inflammation complex syndrome in haemodialysis and its relationship with the thyroid hormones thyrotropin, T3, FT3 and free thyroxine (FT4), as well as to evaluate the prevalence of low FT3 syndrome and its correlation with nutritional and inflammatory markers. MATERIALS AND METHODS: Cross-sectional, analytical and comparative study that enrolled 128 haemodialysis patients: 50.8% females; mean age 45.05±17.01 years; mean time on haemodialysis 45.4±38.8 months; 29.7% diabetics; 79.7% with hypertension. Serum thyroid hormones thyrotropin, T3, FT3 and FT4 concentrations were measured and Malnutritition-Inflammation Score (MIS) was applie to diagnostic. RESULTS: Mean thyroid hormone values were: thyroid hormones thyrotropin 2.48±1.8 mIU/ml (range: 0.015-9.5), T3 1.18±0.39 ng/ml (range 0.67-2.64), FT3 5.21±0.96pmol/l (range: 3.47-9.75); FT4 1.35±0.4 ng/ml (range: 0.52-2.57). Malnutrition-inflammation complex syndrome prevalence was 53.9%; 11.7% presented low FT3 levels. Serum T3 and FT3 concentrations inversely correlated with Malnutritition-Inflammation Score (MIS), while FT4 correlated positively with Malnutrition-Inflammation Score. In the linear regression analysis, low FT3 was associated with IL-6 (ß= 0.265, p=.031), C-reactive protein (CRP) (ß= -0.313, p=.018) and albumin (ß= 0.276, p=.002). CONCLUSION: Low T3 and FT3 levels are correlated with malnutrition and inflammation parameters. Malnutrition-inflammation complex syndrome can affect serum concentrations of thyroid hormones.

Prevalencia del síndrome complejo de malnutrición e inflamación y su correlación con las hormonas tiroideas en pacientes en hemodiálisis crónica / Prevalence of malnutrition-inflammation complex syndrome and its correlation with thyroid hormones in chronic haemodialysis patients

Introducción: La reducción de las hormonas tiroideas, triyodotironina total (T3) y triyodotironina libre (T3L) en pacientes en hemodiálisis, es un marcador de malnutrición e inflamación y son predictores de mortalidad. El objetivo del estudio fue determinar la prevalencia del síndrome complejo de malnutrición e inflamación en hemodiálisis y su asociación con las hormonas tiroideas: tirotropina, T3, T3L y tiroxina libre (T4L); además de evaluar la incidencia del síndrome de T3L y su correlación con marcadores nutricionales e inflamatorios. Materiales y métodos: Estudio transversal, analítico y comparativo, incluyó 128 pacientes en HD, 50,8% mujeres, edad 45,05±17,01 años, 45,4±38,8 meses en hemodiálisis, 29,7% diabéticos y 79,7% hipertensos. Se determinó en suero la concentración de tirotropina, T3, T3L y T4L, se aplicó la encuesta Malnutrition-Inflammation Score para diagnosticar malnutrición e inflamación. Resultados: La media de valores de las hormonas tiroideas fueron: tirotropina 2,48±1,8 mUI/mL (rango 0,015-9,5), T3 1,18±0,39ng/mL (0,67-2,64), T3L 5,21±0,96pmol/l (3,47-9,75), T4L 1,35±0,4ng/mL (0,52-2,57). La prevalencia de síndrome complejo de malnutrición e inflamación es 53,9%; un 11,7% mostró T3L baja. Las concentraciones séricas de T3 y T3L correlacionan negativamente con Malnutrition-Inflammation Score y T4L correlaciona positivamente con Malnutrition-Inflammation Score. El análisis de regresión lineal de T3L baja fue asociado con IL-6 (β=0,265 p=0,031), proteína C reactiva (β=-0,313 p=0,018) y albúmina (β=0,276 p=0,002). Conclusiones: Bajos niveles de T3 y T3L correlacionan con parámetros de inflamación y nutrición. El síndrome complejo de malnutrición e inflamación puede afectar la concentración sérica de hormonas tiroideas (AU)

Introduction: Low levels of thyroid hormones, total triiodothyronine (T3) and free triiodothyronine (FT3) in haemodialysis patients is a marker of malnutrition and inflammation and are predictors of mortality. The aim of this study was to determine the prevalence of malnutrition-inflammation complex syndrome in haemodialysis and its relationship with the thyroid hormones thyrotropin, T3, FT3 and free thyroxine (FT4), as well as to evaluate the prevalence of low FT3 syndrome and its correlation with nutritional and inflammatory markers. Materials and methods: Cross-sectional, analytical and comparative study that enrolled 128 haemodialysis patients: 50.8% females; mean age 45.05±17.01 years; mean time on haemodialysis 45.4±38.8 months; 29.7% diabetics; 79.7% with hypertension. Serum thyroid hormones thyrotropin, T3, FT3 and FT4 concentrations were measured and Malnutritition-Inflammation Score (MIS) was applie to diagnostic. Results: Mean thyroid hormone values were: thyroid hormones thyrotropin 2.48±1.8 mIU/ml (range: 0.015-9.5), T3 1.18±0.39 ng/ml (range 0.67-2.64), FT3 5.21±0.96pmol/l (range: 3.47-9.75); FT4 1.35±0.4 ng/ml (range: 0.52-2.57). Malnutrition-inflammation complex syndrome prevalence was 53.9%; 11.7% presented low FT3 levels. Serum T3 and FT3 concentrations inversely correlated with Malnutritition-Inflammation Score (MIS), while FT4 correlated positively with Malnutrition-Inflammation Score. In the linear regression analysis, low FT3 was associated with IL-6 (β= 0.265, p=.031), C-reactive protein (CRP) (β= -0.313, p=.018) and albumin (β= 0.276, p=.002). Conclusion: Low T3 and FT3 levels are correlated with malnutrition and inflammation parameters. Malnutrition-inflammation complex syndrome can affect serum concentrations of thyroid hormones (AU)

Inflamación en hemodiálisis y su correlación con los índices neutrófilos/linfocitos y plaquetas/linfocitos / Inflammation in hemodialysis and their correlation with neutrophil-lymphocyte ratio and platelet- lymphocyte ratio

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Distracción osteogénica en el servicio de cirugía oral ymaxilofacial del Hospital Militar Central de Bogotá / Distraction osteogenesis at the oral and maxillofacial surgery department of the Hospital Militar Central Bogotá

Introducción: La distracción osteogénica es una técnica quirúrgica basada en el principio de "tensión-estrés", que estimula la histogénesis y neoformación ósea. Objetivo: Describir el uso de la distracción osteogénica, así como analizar las fases de distracción de los pacientes tratados en el Servicio de Cirugía Oral y Maxilofacial del Hospital Militar Central. Diseño: Estudio observacional descriptivo. Materiales y métodos: Se realizó un muestreo no probabilístico por conveniencia donde fueron incluidos en el estudio todos los pacientes sometidos a distracción osteogénica para corrección de secuelas de trauma facial, defectos ocasionados por resecciones tumorales, corrección de anomalías dentofaciales y malformaciones congénitas entre Marzo de 2009 a Diciembre 2014. Resultados: El 73.6% de los pacientes correspondían al genero masculino, con una media de 21.79 años. El factor etiológico más frecuente fueron las anomalías dentofaciales (50.9%) seguido por las herida por arma de fuego (22.6%). Se evidenció un tiempo de latencia de 7.02 días, un período de activación de 18.25 días y un período de consolidación/remodelación de 27.30 semanas. Conclusiones: La distracción osteogénica permite la formación del hueso de soporte así como del tejido blando involucrado, es considerada una solución ideal para la restitución de tejidos independientemente del tipo de patología.

Introduction: Distraction osteogenesis is a surgical technique based on the principle of "tension-stress", which stimulates bone formation and histogenesis. Objective: To describe the use of distraction osteogenesis and to analyze its phases in patients treated at the Oral and Maxillofacial Department of the Hospital Militar Central. Design: A descriptive observational study was performed. Materials and methods: A non-probabilistic convenience sample which included all patients who underwent distraction osteogenesis from March 2009 to December 2014 for correcting sequelae of facial trauma, defects caused by tumor resection or by dentofacial anomalies and congenital malformations was analyzed. Results: 73.6% of patients were male, with an average of 21.79 years. The most common etiologic factor was the Dentofacial deformities (50.9%) followed by Gunshot wounds (22.6%). It showed a latency of 7.02 days, an activation period of 18.25 days and a period of consolidation / remodeling of 27.30 weeks. Conclusions: Distraction osteogenesis allows the formation of supporting bone and soft tissue, it is considered as an ideal solution for tissue restitution regardless the type of pathology.