Diseño de Modelo de Gestión Basado en el Modelo EFQM y Balanced Scorecard para una Empresa Distribuidora de Repuestos e Insumos de Maquinaria

El presente trabajo de tesis desarrolla un modelo de gestión basado en el modelo EFQM y la herramienta de gestión de estrategias Balanced Scorecard, orientado a una empresa distribuidora de repuestos e insumos para maquinaria en la ciudad de Arequipa. La finalidad de este trabajo es brindar un modelo de gestión que puede ser utilizado por la empresa en estudio de tal manera que aumente su nivel de rentabilidad, mejore el nivel de servicio al cliente y por lo tanto aumente su competitividad frente al mercado. El trabajo de investigación contempla en su estructura 5 capítulos: Capítulo 1: Se desarrollan los planteamientos metodológicos que sirven de marco general, es la base que guía la realización del trabajo de investigación, debido a que se plantean los objetivos, variables, justificación e hipótesis. Capítulo 2: Se describen definiciones importantes y se plantea el modelo gestión basado en el modelo EFQM y Balanced Scorecard, que será utilizado para el cumplimiento del objetivo de la presente tesis. Capítulo 3: Se describe la empresa de manera general, los procesos claves desarrollados y su situación actual dentro de la industria Capítulo 4: Se hace uso de la metodología EFQM para evaluar a la empresa y describir la problemática de manera más detallada. Capítulo 5: Se realiza un modelo de gestión aplicado a las necesidades de la empresa, desarrollando las matrices de planificación y tableros de control. De la misma manera se realiza la primera evaluación luego de su implementación, para posteriormente analizar los resultados obtenidos. Palabras Claves: EFQM, Balanced Scorecard, modelo de gestión, calida

Free-standing flexible and biomimetic hybrid membranes for ions and ATP transport

The transport of metabolites across robust, flexible and free-standing biomimetic membranes made of three perforated poly (lactic acid) (pPLA) layers, separated by two anodically polymerized conducting layers of poly (3,4-ethylenedioxythiophene-co-3-dodecylthiophene), and functionalized on the external pPLA layers with a voltage dependent anion channel (VDAC) protein, has been demonstrated. The three pPLA layers offer robustness and flexibility to the bioactive platform and the possibility of obtaining conducing polymer layers by in situ anodic polymerization. The incorporation of dodecylthiophene units, which bear a 12 carbon atoms long linear alkyl chain, to the conducting layers allows mimicking the amphiphilic environment offered by lipids in cells, increasing 32% the efficiency of the functionalization. Electrochemical impedance measurements in NaCl and adenosine triphosphate (ATP) solutions prove that the integration of the VDAC porin inside the PLA perforations considerably increases the membrane conductivity and is crucial for the electrolyte diffusion. Such results open the door for the development of advanced sensing devices for a broad panel of biomedical applicationsPeer ReviewedPostprint (author's final draft

Comparing Cognitive and Somatic Symptoms of Depression in Myocardial Infarction Patients and Depressed Patients in Primary and Mental Health Care

Depression in myocardial infarction patients is often a first episode with a late age of onset. Two studies that compared depressed myocardial infarction patients to psychiatric patients found similar levels of somatic symptoms, and one study reported lower levels of cognitive/affective symptoms in myocardial infarction patients. We hypothesized that myocardial infarction patients with first depression onset at a late age would experience fewer cognitive/affective symptoms than depressed patients without cardiovascular disease. Combined data from two large multicenter depression studies resulted in a sample of 734 depressed individuals (194 myocardial infarction, 214 primary care, and 326 mental health care patients). A structured clinical interview provided information about depression diagnosis. Summed cognitive/affective and somatic symptom levels were compared between groups using analysis of covariance, with and without adjusting for the effects of recurrence and age of onset. Depressed myocardial infarction and primary care patients reported significantly lower cognitive/affective symptom levels than mental health care patients (F (2,682) = 6.043, p = 0.003). Additional analyses showed that the difference between myocardial infarction and mental health care patients disappeared after adjusting for age of onset but not recurrence of depression. These group differences were also supported by data-driven latent class analyses. There were no significant group differences in somatic symptom levels. Depression after myocardial infarction appears to have a different phenomenology than depression observed in mental health care. Future studies should investigate the etiological factors predictive of symptom dimensions in myocardial infarction and late-onset depression patients

Enhanced amygdala reactivity to emotional faces in adults reporting childhood emotional maltreatment

In the context of chronic childhood emotional maltreatment (CEM; emotional abuse and/or neglect), adequately responding to facial expressions is an important skill. Over time, however, this adaptive response may lead to a persistent vigilance for emotional facial expressions. The amygdala and the medial prefrontal cortex (mPFC) are key regions in face processing. However, the neurobiological correlates of face processing in adults reporting CEM are yet unknown. We examined amydala and mPFC reactivity to emotional faces (Angry, Fearful, Sad, Happy, Neutral) vs scrambled faces in healthy controls and unmedicated patients with depression and/or anxiety disorders reporting CEM before the age of 16 years (n = 60), and controls and patients who report no childhood abuse (n = 75). We found that CEM was associated with enhanced bilateral amygdala reactivity to emotional faces in general, and independent of psychiatric status. Furthermore, we found no support for differential mPFC functioning, suggesting that amygdala hyper-responsivity to emotional facial perception in adults reporting CEM may be independent from top-down influences of the mPFC. These findings may be key in understanding the increased emotional sensitivity and interpersonal difficulties, that have been reported in individuals with a history of CEM.</p

Hypoactive medial prefrontal cortex functioning in adults reporting childhood emotional maltreatment

Childhood emotional maltreatment (CEM) has adverse effects on medial prefrontal cortex (mPFC) morphology, a structure that is crucial for cognitive functioning and (emotional) memory and which modulates the limbic system. In addition, CEM has been linked to amygdala hyperactivity during emotional face processing. However, no study has yet investigated the functional neural correlates of neutral and emotional memory in adults reporting CEM. Using functional magnetic resonance imaging, we investigated CEM-related differential activations in mPFC during the encoding and recognition of positive, negative and neutral words. The sample (N = 194) consisted of patients with depression and/or anxiety disorders and healthy controls (HC) reporting CEM (n = 96) and patients and HC reporting no abuse (n = 98). We found a consistent pattern of mPFC hypoactivation during encoding and recognition of positive, negative and neutral words in individuals reporting CEM. These results were not explained by psychopathology or severity of depression or anxiety symptoms, or by gender, level of neuroticism, parental psychopathology, negative life events, antidepressant use or decreased mPFC volume in the CEM group. These findings indicate mPFC hypoactivity in individuals reporting CEM during emotional and neutral memory encoding and recognition. Our findings suggest that CEM may increase individuals' risk to the development of psychopathology on differential levels of processing in the brain; blunted mPFC activation during higher order processing and enhanced amygdala activation during automatic/lower order emotion processing. These findings are vital in understanding the long-term consequences of CEM

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

White matter disturbances in major depressive disorder : a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Altres ajuts: The ENIGMA-Major Depressive Disorder working group gratefully acknowledges support from the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to PMT) and NIH grant R01 MH116147 (PMT). LS is supported by an NHMRC MRFF Career Development Fellowship (APP1140764). We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. NESDA: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10-000-1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. M-JvT was supported by a VENI grant (NWO grant number 016.156.077). UCSF: This work was supported by the Brain and Behavior Research Foundation (formerly NARSAD) to TTY; the National Institute of Mental Health (R01MH085734 to TTY; K01MH117442 to TCH) and by the American Foundation for Suicide Prevention (PDF-1-064-13) to TCH. Stanford: This work was supported by NIMH Grants R01MH59259 and R37101495 to IHG. MS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. Muenster: This work was funded by the German Research Foundation (SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). Marburg: This work was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD; KI 588/ 14-1, KI 588/14-2 to TK; KR 3822/7-1, KR 3822/7-2 to AK; JA 1890/ 7-1, JA 1890/7-2 to AJ). IMH-MDD: This work was supported by the National Healthcare Group Research Grant (SIG/15012) awarded to KS. Barcelona: This study was funded by two grants of the Fondo de Investigación Sanitaria from the Instituto de Salud Carlos III, by the Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM). The author is funded through 'Miguel Servet' research contract (CP16-0020), co-financed by the European Regional Development Fund (ERDF) (2016-2019). QTIM: We thank the twins and singleton siblings who gave generously of their time to participate in the QTIM study. We also thank the many research assistants, radiographers, and IT support staff for data acquisition and DNA sample preparation. This study was funded by White matter disturbances in major depressive disorder: a coordinated analysis across 20 international. . . 1521 the National Institute of Child Health & Human Development (RO1 HD050735); National Institute of Biomedical Imaging and Bioengineering (Award 1U54EB020403-01, Subaward 56929223); National Health and Medical Research Council, Australia (Project Grants 496682, 1009064). NIH ENIGMA-BD2K U54 EB020403 (Thompson); R01 MH117601 (Jahanshad/Schmaal). Magdeburg: M.L. and M.W. are funded by SFB 779. Bipolar Family Study: This study has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013). This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award (104036/Z/14/Z). Minnesota Adolescent Depression Study: The study was funded by the National Institute of Mental Health (K23MH090421), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, the Minnesota Medical Foundation, and the Biotechnology Research Center (P41 RR008079 to the Center for Magnetic Resonance Research), University of Minnesota, and the Deborah E. Powell Center for Women's Health Seed Grant, University of Minnesota. Dublin: This study was supported by Science Foundation Ireland through a Stokes Professorhip grant to TF. MPIP: The MPIP Sample comprises patients included in the Recurrent Unipolar Depression (RUD) Case-Control study at the clinic of the Max Planck Institute of Psychiatry, Munich, German. The RUD study was supported by GlaxoSmithKline.Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors