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*Maurer AH, Burshteyn M, Adler LP, Steiner RM. How to differentiate benign versus malignant cardiac and paracardiac 18F FDG uptake at oncologic PET/CT. RadioGraphics. 2011;31:1287–1305.

Simple Summary The synthetic lethality (SL) clinical success of PARP inhibitors in homologous recombinant deficient tumors has established a new concept for cancer treatment. For decades, efforts have centered on identifying genetic interactions for determining essential tumoral genes, and more recently, SL interactions to determine combinational treatments against persistent cancer reappearance. Currently, the feasibility of CRISPR screen methodology has emerged as the state of the art for uncovering new SL or viable interactors in the biology and treatment of cancers. We present the up-to-date research of numerous laboratories that take advantage of the genome-wide forward genetic CRISPR screen tools and protocols to identify cancer biomarkers, genetic interactions and novel therapies. Indeed, investigations are nowadays focused on defining innovative combinatorial treatments based on SL interactions. By coupling different drugs, concentration treatments can be lowered and therefore toxicity reduced. CRISPR screen technologies have deeply impacted cancer research to promote a robust advance in combined therapies. Cancer is a complex disease resulting from the accumulation of genetic dysfunctions. Tumor heterogeneity causes the molecular variety that divergently controls responses to chemotherapy, leading to the recurrent problem of cancer reappearance. For many decades, efforts have focused on identifying essential tumoral genes and cancer driver mutations. More recently, prompted by the clinical success of the synthetic lethality (SL)-based therapy of the PARP inhibitors in homologous recombinant deficient tumors, scientists have centered their novel research on SL interactions (SLI). The state of the art to find new genetic interactions are currently large-scale forward genetic CRISPR screens. CRISPR technology has rapidly evolved to be a common tool in the vast majority of laboratories, as tools to implement CRISPR screen protocols are available to all researchers. Taking advantage of SLI, combinatorial therapies have become the ultimate model to treat cancer with lower toxicity, and therefore better efficiency. This review explores the CRISPR screen methodology, integrates the up-to-date published findings on CRISPR screens in the cancer field and proposes future directions to uncover cancer regulation and individual responses to chemotherapy.

We present the clinical and neuropathological findings of a patient with early onset Alzheimer's dementia (AD), heterozygous carrier of the rare Apolipoprotein E Christchurch (APOEch) variant. The patient did not harbor any pathogenic mutation in known Mendelian genes related to AD or other neurodegenerative disorders. A sibling of this patient, also carrying the APOEch variant, developed AD at the age of 66 years old. Our data suggest a possible deleterious effect of this variant, which contrast with the protective role that has been previously shown in a subject homozygous for the APOEch with he Paisa PSEN1 mutation.

Este trabajo consistió en la realización de una serie de predicciones de la pandemia covid-19 en Colombia. Presentándose 2 tipos de modelos, modelos de machine learning y modelos analíticos basados en ecuaciones diferenciales. De modelos analíticos se realizaron 2 y de modelos basados en machine learning 3, posteriormente se realizaron las correspondientes evaluaciones de los modelos y su comparación, encontrando que modelos son los que presentan el mejor desempeño en este problema en particular. CAPÍTULO 1. INTRODUCCIÓN 5 1.1. MOTIVACIÓN 5 1.2. ANTECEDENTES 8 1.3. PLANTEAMIENTO DEL PROBLEMA 8 1.4. JUSTIFICACIÓN 11 1.6. OBJETIVOS 11 1.6.1. OBJETIVO GENERAL 11 1.6.2. OBJETIVOS ESPECÍFICOS 11 CAPÍTULO 2. MODELOS EPIDEMIOLÓGICOS BASADOS EN ECUACIONES DIFERENCIALES 12 2.1 MODELOS EPIDEMIOLÓGICOS Y SUS VARIANTES 12 2.1.1. MODELO SIR 12 2.1.2. MODELO SEIR 14 2.1.2.1. MODELO SEAIR/SEIAR 15 2.2. USO DE MODELOS EN COLOMBIA 17 2.3. IMPLEMENTACIÓN DE MODELOS ESTÁTICOS 19 2.3.1. MODELO SIR 19 2.3.2. MODELO SEIR 22 2.3.4. ANÁLISIS DE MODELOS ESTÁTICOS 25 2.4. IMPLEMENTACIÓN MODELOS CON VALORES DE R0 DINÁMICOS 26 2.4.1 MODELO SIR 26 2.4.2. MODELO SEIR 26 2.4.3. ANÁLISIS DE MODELOS DINÁMICOS 27 CAPÍTULO 3. TÉCNICAS DE MACHINE LEARNING PARA SERIES DE TIEMPO 28 3.1. REGRESIÓN LINEAL 28 3.1.1. ESTIMACIÓN POR MÍNIMOS CUADRADOS 29 3.2. SUPPORT VECTOR MACHINE (SVM) 31 3.2.1. SVM EN SERIES DE TIEMPO 32 3.2.2. KERNEL RADIAL BASIS FUNCTION (RBF) 33 3.3.LONG SHORT TERM MEMORY ( LSTM) 33 CAPÍTULO 4. IMPLEMENTACIÓN Y VALIDACIÓN DE MODELOS 35 4.1. DATASET 35 4.2. PREPROCESAMIENTO DE DATOS 37 4.3. ESQUEMA DE VALIDACIÓN 38 4.4. APLICACIÓN DE MODELOS CLÁSICOS 40 4.4.1. SIR 41 4.4.2. SEIR 45 4.5. APLICACIÓN DE MODELOS DE MACHINE LEARNING 50 4.5.1 REGRESIÓN LINEAL 50 4.5.2. SUPPORT VECTOR REGRESSION (SVR) 54 3 4.5.3 LONG SHORT TERM MEMORY (LSTM) 61 CAPÍTULO 5 - CONCLUSIONES Y TRABAJOS FUTUROS 68 5.1. CONCLUSIONES 68 5.2. TRABAJOS FUTUROS 69 BIBLIOGRAFÍA 70 ANEXOS 74 This work consisted of making a series of predictions of the covid-19 pandemic in Colombia. Presenting 2 types of models, machine learning models and analytical models based on differential equations. Two of analytical models were carried out and 3 of models based on machine learning, later the corresponding evaluations of the models and their comparison were carried out, finding which models are the ones that present the best performance in this particular problem. Pregrado

As animals navigate through their environment, they must integrate external stimuli with previous experience to guide behavioral decisions. In group living animals, these decisions are embedded in a social context that influences their interactions, access to resources, and ultimately, their behavior. To acquire and learn new information that is vital to their survival, individuals must successfully navigate social interactions that are often embedded in dominance hierarchies. Such hierarchies arise from dyadic relationships between dominant and subordinate individuals and confer fitness benefits to those of high rank. A great deal is known regarding the ultimate underpinnings of dominance, especially as it pertains to differences between dominant and subordinate individuals (reviewed in Chapter 1, along with a summary of the social learning field). However, we have much to learn regarding the neurobiological mechanisms through which individuals navigate these social hierarchies in order to learn and acquire new information that is critical for their survival, such as finding food. To begin to address this knowledge gap in understanding the neurobiology of learning in dynamic social groups, I conducted a series of experiments using the African cichlid fish, Astatotilapia burtoni. Males of this species form dominance hierarchies which are vital for gaining territories and access to reproductive opportunities. In chapter 2, I examined the unique social traits that differentiate dominant and subordinate males in social groups, and how these traits influence group learning and decision-making. In chapter 3, I examined the neural activity patterns that drive learning in a social and asocial context by quantifying immediate-early gene expression at different time points during the learning process. Finally, in chapter 4, I examined how these neural activity patterns in key brain regions, the putative homologues of the basolateral amygdala and hippocampus, vary with the extent of social stability during the learning process. Taken together, my research offers important new insights into the behavioral and neural mechanisms underlying social learning and suggests several directions for future study

This paper presents the numerical and experimental analysis performed on the polymeric material Polyethylene Terephthalate Glycol (PETG) manufactured with Fused Deposition Modeling Technology (FDM) technology, aiming at obtaining its mechanical characterization under uniaxial compression loads. Firstly, with the objective of evaluating the printing direction that poses a greater mechanical strength, eighteen test specimens were manufactured and analyzed according to the requirements of the ISO-604 standards. After that, a second experimental test analyzed the mechanical behavior of an innovative structural design manufactured in Z and X&ndash, Y directions under uniaxial compression loads according to the requirements of the Spanish CTE standard. The experimental results point to a mechanical linear behavior of PETG in X, Y and Z manufacturing directions up to strain levels close to the yield strength point. SEM micrographs show different structural failures linked to the specimen manufacturing directions. Test specimens manufactured along X present a brittle fracture caused by a delamination process. On the contrary, test specimens manufactured along X and Y directions show permanent plastic deformations, great flexibility and less strength under compression loads. Two numerical analyses were performed on the structural part using Young&rsquo, s compression modulus obtained from the experimental tests and the load specifications required for the Spanish CTE standards. The comparison between numerical and experimental results presents a percentage of relative error of 2.80% (Z-axis), 3.98% (X-axis) and 3.46% (Y-axis), which allows characterizing PETG plastic material manufactured with FDM as an isotropic material in the numerical simulation software without modifying the material modeling equations in the data software. The research presented here is of great help to researchers working with polymers and FDM technology for companies that might need to numerically simulate new designs with the PETG polymer and FDM technology.

A growing body of empirical literature&mdash, both on the micro and macro scale&mdash, is devoted to exploring the existence of hysteresis&mdash, or at least persistence&mdash, in self-employment, i.e., whether policy, economic or external shocks have transitory or persistent effects on the probability of survival, and in turn, on the natural rate of self-employment. In aggregate time series studies, the usual method to address this issue has been to look for unit roots by using alternative tests or by using unobservable components models. In this research, we performed a battery of tests and competing approaches to check the robustness of our results with UK self-employment time series. The UK is a suitable case for study because the recent evolution of the UK self-employment rate figures shows a steady growth since the beginning of the millennium. This long-term rise in UK self-employment has attracted the attention of scholars, at least, before the Great Lockdown. We find evidence of hysteresis, while business cycle output variations significantly affect self-employment rates. The article discusses the implications of the findings.

The paper presents the geometric design of a new lattice element of conformal type integrated into the cooling system of an injection mold. The geometric variables of this element are parameterized and are included in the design of the mold cooling system so that it can be valid for any type of geometry of plastic parts. Similarly, a physical model is presented to analyze the energetic behavior of the cooling lattice. Through the application of expert-type optimization algorithms to the presented physical model, the geometrical variables of the cooling lattice are dimensioned as well as the technological variables that govern the cooling phase of the plastic part. This methodology has been applied to four plastic parts with different geometrical characteristics. The results obtained have been compared with numerical simulations carried out by means of CFD-type software for plastic parts analysis, concluding that the new cooling lattices are adapted to the design criteria of an optimal cooling system. The new cooling lattices improve, in turn, the efficiency of thermal exchange in the cooling phase for plastic parts with large concavities, fine details, internal turrets, and housings. A simplified model focused on the energy analysis of a single cooling cell has been defined, which allows us to evaluate the thermal exchange between the cooling lattice and the plastic part, avoiding the computational complexity in the generation of the discrete mesh of the mold inserts. Similarly, in order to guarantee the structural safety of the cooling grids, a numerical mechanical analysis of the structural behavior of the injection mold insert under the most unfavorable contour conditions during the injection process has been carried out. The new conformal system presented in the paper does not require expert designers for its dimensioning, considering it as an adequate tool for reducing the overall design time of the mold while allowing the manufacturing process to be more efficient, reducing cycle time, and increasing the quality of the parts produced.

The cost of corrosion remains a sizeable budgetary concern across the Department of Defense. Naval aviation and material are particularly impacted due to their mission profiles. As such, ongoing re...

New Co(III), Cu(II) and Zn(II) complexes of 4,4′-dihydroxy-2,2′-bipyridine (dhbpyH2) have been structurally characterized by single crystal X-ray diffraction methods and studied by electrochemical and spectroscopic techniques. Both bis- and tris-dhbpyH2 zinc complexes were characterized in solution and solid state. A rare case of accidental isochronism of the H5 and H6 protons was identified in the 1H NMR spectrum of the Co(III) complex. The cobalt and copper complexes show reversible one-electron electrochemical reductions. Luminescent emission with a life time t = 4.95 ns was recorded for [Zn(dhbpyH2)2]2+ upon UV irradiation.

Many psychiatric disorders are associated with cognitive dysfunction that is ineffectively treated by existing pharmacotherapies and which may contribute to poor real-world functioning. D-cycloserine (DCS) is a partial N-methyl- D -aspartate (NMDA) agonist that has attracted attention because of its cognitive enhancing properties, including in people with post-traumatic stress disorder (PTSD). Here, we examined the effect of DCS on reversal learning - a type of cognitive flexibility – following exposure to single prolonged stress (SPS), a rodent model of PTSD . Male Sprague Dawley rats ( n = 64) were trained to press levers in an operant chamber, matched for performance and assigned to SPS or control (unstressed) groups. Following SPS, rats received three additional lever press sessions, followed by a side bias test on day three. One day later they learned a response discrimination rule (press left or right lever, opposite to side bias) and on a subsequent day were trained (and tested) for reversal to the opposite lever. DCS (15 mg/kg) or vehicle was administered 30 minutes prior to the reversal session. No between-group differences were found in acquisition or retrieval of the initial rule, but a significant drug x stress interaction on response discrimination reversal indicated that DCS had a greater beneficial effect on SPS rats’ cognitive flexibility than it did on performance in controls. These findings add to a growing literature on the beneficial effects of DCS for treating a wide variety of deficits that develop following exposure to extreme stress and may have implications for the development of novel pharmacotherapies for PTSD.