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Investigation results of micro-arc coating on the (Ti-7Nb-6Al) alloy were presented. It has potential clinical value in applications such as dental implant, knee, and hip prostheses. An electrolyte solution of ( Na2CO3 + Na2SiO3). The micro-arc oxidation (MAO) technique was employed for in situ oxidation of Ti-6Al-7Nb surface. The wettability of a porous TiO2 covering made up of anatase and rutile phases was investigated. The test findings revealed that the possibility of deposition of ceramics coatings on the surface of Ti-6Al-7Nb alloy by using voltages (400V )at different deposition times (7, 15, and 30) min. The results indicate that ceramics layer of titanium oxide (TiO2) which is formed during coating porous and homogenous distribution. The bioactive composition of the oxide layers can be suitable for use as advanced biomedical implants. The coatings also revealed an increased surface roughness, porosity, microhardness, surface wettability and corrosion resistance of the Ti-6Al-7Nb substrate reaches to (CR= 0.1114×10−3mpy) in Ringer’s solution and (CR= 1.03×10−3mpy) in Saliva’s solution with increased deposition time.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Liver fibrosis is closely correlated with liver functional reserve and the risk of HCC development. Meanwhile, malignant tumors generally have high cellularity compared to benign tumors, which results in increased stiffness. Magnetic resonance elastography (MRE) has emerged as a new non-invasive technique for assessing tissue stiffness with excellent diagnostic accuracy, not only for assessing liver fibrosis but also for measuring tumor stiffness. Recent studies provide new evidence that MRE may play an important role in the management of patients with HCC and show several novel clinical applications, such as predicting the development of HCC, differentiating between benign/malignant liver lesions (FLL) and HCC pathological grades, assessing treatment response, and predicting recurrence after treatment, although some findings are controversial. Therefore, we conducted this review to summarize these novel applications of MRE in HCC patients and also discuss their limitations and future advancement.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Liver fibrosis is closely correlated with liver functional reserve and the risk of HCC development. Meanwhile, malignant tumors generally have high cellularity compared to benign tumors, which results in increased stiffness. Magnetic resonance elastography (MRE) has emerged as a new non-invasive technique for assessing tissue stiffness with excellent diagnostic accuracy, not only for assessing liver fibrosis but also for measuring tumor stiffness. Recent studies provide new evidence that MRE may play an important role in the management of patients with HCC and show several novel clinical applications, such as predicting the development of HCC, differentiating between benign/malignant liver lesions (FLL) and HCC pathological grades, assessing treatment response, and predicting recurrence after treatment, although some findings are controversial. Therefore, we conducted this review to summarize these novel applications of MRE in HCC patients and also discuss their limitations and future advancement.

BackgroundDespite advances in early detection and therapies, cancer is still one of the most common causes of death worldwide. Since each tumor is unique, there is a need to implement personalized care and develop robust tools for monitoring treatment response to assess drug efficacy and prevent disease relapse.Main bodyRecent developments in liquid biopsies have enabled real-time noninvasive monitoring of tumor burden through the detection of molecules shed by tumors in the blood. These molecules include circulating tumor nucleic acids (ctNAs), comprising cell-free DNA or RNA molecules passively and/or actively released from tumor cells. Often highlighted for their diagnostic, predictive, and prognostic potential, these biomarkers possess valuable information about tumor characteristics and evolution. While circulating tumor DNA (ctDNA) has been in the spotlight for the last decade, less is known about circulating tumor RNA (ctRNA). There are unanswered questions about why some tumors shed high amounts of ctNAs while others have undetectable levels. Also, there are gaps in our understanding of associations between tumor evolution and ctNA characteristics and shedding kinetics. In this review, we summarize current knowledge about ctNA biology and release mechanisms and put this information into the context of tumor evolution and clinical utility.ConclusionsA deeper understanding of the biology of ctDNA and ctRNA may inform the use of liquid biopsies in personalized medicine to improve cancer patient outcomes.

The escalating rate of cancer cases, together with treatment deficiencies and long-term side effects of currently used cancer drugs, has made this disease a global burden of the 21st century. The number of breast and lung cancer patients has sharply increased worldwide in the last few years. Presently, surgical treatment, radiotherapy, chemotherapy, and immunotherapy strategies are used to cure cancer, which cause severe side effects, toxicities, and drug resistance. In recent years, anti-cancer peptides have become an eminent therapeutic strategy for cancer treatment due to their high specificity and fewer side effects and toxicity. This review presents an updated overview of different anti-cancer peptides, their mechanisms of action and current production strategies employed for their manufacture. In addition, approved and under clinical trials anti-cancer peptides and their applications have been discussed. This review provides updated information on therapeutic anti-cancer peptides that hold great promise for cancer treatment in the near future., QC 20230725

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Liver fibrosis is closely correlated with liver functional reserve and the risk of HCC development. Meanwhile, malignant tumors generally have high cellularity compared to benign tumors, which results in increased stiffness. Magnetic resonance elastography (MRE) has emerged as a new non-invasive technique for assessing tissue stiffness with excellent diagnostic accuracy, not only for assessing liver fibrosis but also for measuring tumor stiffness. Recent studies provide new evidence that MRE may play an important role in the management of patients with HCC and show several novel clinical applications, such as predicting the development of HCC, differentiating between benign/malignant liver lesions (FLL) and HCC pathological grades, assessing treatment response, and predicting recurrence after treatment, although some findings are controversial. Therefore, we conducted this review to summarize these novel applications of MRE in HCC patients and also discuss their limitations and future advancement.

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Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Liver fibrosis is closely correlated with liver functional reserve and the risk of HCC development. Meanwhile, malignant tumors generally have high cellularity compared to benign tumors, which results in increased stiffness. Magnetic resonance elastography (MRE) has emerged as a new non-invasive technique for assessing tissue stiffness with excellent diagnostic accuracy, not only for assessing liver fibrosis but also for measuring tumor stiffness. Recent studies provide new evidence that MRE may play an important role in the management of patients with HCC and show several novel clinical applications, such as predicting the development of HCC, differentiating between benign/malignant liver lesions (FLL) and HCC pathological grades, assessing treatment response, and predicting recurrence after treatment, although some findings are controversial. Therefore, we conducted this review to summarize these novel applications of MRE in HCC patients and also discuss their limitations and future advancement.

Lung cancer continues to pose a significant challenge as a prominent contributor to global cancer-related mortality. Despite the considerable strides made in therapeutic interventions within the past decade, a substantial population of patients diagnosed with non-small cell lung cancer (NSCLC) still face the grim reality of an incurable condition. In the realm of optimal management strategies for individuals afflicted with locally advanced, yet amenable to surgical resection, NSCLC, a therapeutic approach encompassing chemoradiation stands as a fundamental component. Significant strides have been made in the therapeutic landscape of NSCLC during the preceding two decades, facilitating an enhanced comprehension of the underlying disease biology, and mechanisms governing tumor progression, as well as advancements in early detection modalities and multimodal therapeutic interventions. Nevertheless, the overall rates of curative interventions and survival outcomes for NSCLC continue to exhibit a discouragingly low trajectory, particularly in the context of metastatic disease. Hence, the imperative for sustained research endeavors in the realm of novel pharmaceutical agents and combinatorial therapeutic approaches remains paramount, with the overarching objective of broadening the scope of clinical advantages conferred upon a wider demographic of patients, thereby fostering tangible improvements in outcomes pertaining to NSCLC. The primary objective of this review is to provide an all-encompassing examination encompassing the clinical application and synthetic routes of specific drugs, with the explicit aim of disseminating invaluable knowledge that can inform future research and development endeavors focused on NSCLC.

Extracellular vesicles (EVs) have gained tremendous interest in the search for next-generation therapeutics for the treatment of a range of pathologies, including cancer, especially due to their small size, biomolecular cargo, ability to mediate intercellular communication, high physicochemical stability, low immunogenicity and biocompatibility. The theranostic potential of EVs have been enhanced by adopting several strategies such as genetic or metabolic engineering, parental cell modification or direct functionalization to incorporate therapeutic compounds into these nanoplatforms. The smart nano-sized EVs indeed offer huge opportunities in the field of cancer, and current research is set at overcoming the existing pitfalls. Smart EVs are already being applied in the clinics despite the challenges faced. We provide, herein, an update on the technologies employed for EV functionalization in order to achieve optimal tumor cell targeting and EV tracking in vivo with bio-imaging modalities, as well as the preclinical and clinical studies making use of these modified EVs, in the context of gastrointestinal tumors.

Anthracyclines are a widely used class of chemotherapy in pediatric and adult cancers, however, their use is hampered by the development of cardiotoxic side-effects and ensuing complications, primarily heart failure. Clinically used imaging modalities to screen for cardiotoxicity are mostly echocardiography and occasionally cardiac magnetic resonance imaging. However, the assessment of diastolic and global or segmental systolic function may not be sensitive to detect subclinical or early stages of cardiotoxicity. Multiple studies have scrutinized molecular nuclear imaging strategies to improve the detection of anthracycline-induced cardiotoxicity. Anthracyclines can activate all forms of cell death in cardiomyocytes. Injury mechanisms associated with anthracycline usage include apoptosis, necrosis, autophagy, ferroptosis, pyroptosis, reactive oxygen species, mitochondrial dysfunction, as well as cardiac fibrosis and perturbation in sympathetic drive and myocardial blood flow; some of which have been targeted using nuclear probes. This review retraces the pathobiology of anthracycline-induced cardiac injury, details the evidence to date supporting a molecular nuclear imaging strategy, explores disease mechanisms which have not yet been targeted, and proposes a clinical strategy incorporating molecular imaging to improve patient management.

Adhesion G protein-coupled receptors (aGPCRs) are a class of structurally and functionally highly intriguing cell surface receptors with essential functions in health and disease. Thus, they display a vastly unexploited pharmacological potential. Our current understanding of the physiological functions and signaling mechanisms of aGPCRs form the basis for elucidating further molecular aspects. Combining these with novel tools and methodologies from different fields tailored for studying these unusual receptors yields a powerful potential for pushing aGPCR research from singular approaches toward building up an in-depth knowledge that will facilitate its translation to applied science. In this review, we summarize the state-of-the-art knowledge on aGPCRs in respect to structure-function relations, physiology, and clinical aspects, as well as the latest advances in the field. We highlight the upcoming most pressing topics in aGPCR research and identify strategies to tackle them. Furthermore, we discuss approaches how to promote, stimulate, and translate research on aGPCRs 'from bench to bedside' in the future.

Background: Recent studies indicate that a high proportion of patients in the intensive care unit fail to attain adequate antibiotic levels. Thus, there is a need to monitor the antibiotic concentration to ensure effective treatment. In this article, the authors aimed to develop an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for the simultaneous quantification of antimicrobials to assess individualized therapeutic drug monitoring. Methods: A UHPLC-MS/MS method with 11 antibiotics (ciprofloxacin, moxifloxacin, benzylpenicillin, levofloxacin, linezolid, rifampicin, meropenem, cloxacillin, cefotaxime, clindamycin, and piperacillin) was developed. Chromatographic separation was performed using a Kinetex Biphenyl reversed-phase column, with gradient elution using 0.1% formic acid and methanol with 0.1% formic acid. Sample preparation was performed using methanol protein precipitation. The total run time was 5 minutes. Results: For all analytes, the interassay inaccuracies for calibrators were <= 5%. The interday inaccuracies for the quality controls (QCs) were <= 5% for all analytes. The interassay precision for calibration standards ranged between 1.42% and 6.11%. The interassay imprecision for QCs of all antibiotics and concentrations ranged between 3.60% and 16.1%. Interassay inaccuracy and imprecision for the QCs and calibration standards were <= 15% for all drugs, except benzylpenicillin. Conclusions: A rapid UHPLC-MS/MS method was developed for the simultaneous quantification of 11 different antibiotics. Minimal sample preparation was required to ensure a rapid turnaround time. The method was applied to clinical samples collected from 4 intensive care units.

Inhaled nitric oxide (iNO) acts as a selective pulmonary vasodilator and it is currently approved by the FDA for the treatment of persistent pulmonary hypertension of the newborn. iNO has been demonstrated to effectively decrease pulmonary artery pressure and improve oxygenation, while decreasing extracorporeal life support use in hypoxic newborns affected by persistent pulmonary hypertension. Also, iNO seems a safe treatment with limited side effects. Despite the promising beneficial effects of NO in the preclinical literature, there is still a lack of high quality evidence for the use of iNO in clinical settings. A variety of clinical applications have been suggested in and out of the critical care environment, aiming to use iNO in respiratory failure and pulmonary hypertension of adults or as a preventative measure of hemolysis-induced vasoconstriction, ischemia/reperfusion injury and as a potential treatment of renal failure associated with cardiopulmonary bypass. In this narrative review we aim to present a comprehensive summary of the potential use of iNO in several clinical conditions with its suggested benefits, including its recent application in the scenario of the COVID-19 pandemic. Randomized controlled trials, meta-analyses, guidelines, observational studies and case-series were reported and the main findings summarized. Furthermore, we will describe the toxicity profile of NO and discuss innovative proposed strategies to produce iNO. Overall, iNO exhibits a wide range of potential clinical benefits, that certainly warrants further efforts with randomized clinical trials to determine specific therapeutic roles of iNO.

Robotics is routinely used in several surgical fields. Different robots have been applied in neurosurgery, but only a few of them are relevant to neuroendoscopy. This chapter provides an overview of robotics applied to the different fields of cranial neuroendoscopy. It describes the advantages and disadvantages of reported preclinical prototypes and reviews the few clinical studies that have described robotics as applied to neuroendoscopic cranial surgery. Robotics in neurosurgical practice is a growing field of interest. As it stands, more research is needed to develop systems that are conceived specifically for cranial neuroendoscopy. Further preclinical and clinical studies are required to evaluate the benefits and limits of current commercially available systems.

Current research data reveal microenvironment as a significant modifier of physical functions, pathologic changes, as well as the therapeutic effects of stem cells. When comparing regeneration potential of various stem cell types used for cytotherapy and tissue engineering, mesenchymal stem cells (MSCs) are currently the most attractive cell source for bone and tooth regeneration due to their differentiation and immunomodulatory potential and lack of ethical issues associated with their use. The microenvironment of donors and recipients selected in cytotherapy plays a crucial role in regenerative potential of transplanted MSCs, indicating interactions of cells with their microenvironment indispensable in MSC-mediated bone and dental regeneration. Since a variety of MSC populations have been procured from different parts of the tooth and tooth-supporting tissues, MSCs of dental origin and their achievements in capacity to reconstitute various dental tissues have gained attention of many research groups over the years. This review discusses recent advances in comparative analyses of dental MSC regeneration potential with regards to their tissue origin and specific microenvironmental conditions, giving additional insight into the current clinical application of these cells.

Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.

Current research data reveal microenvironment as a significant modifier of physical functions, pathologic changes, as well as the therapeutic effects of stem cells. When comparing regeneration potential of various stem cell types used for cytotherapy and tissue engineering, mesenchymal stem cells (MSCs) are currently the most attractive cell source for bone and tooth regeneration due to their differentiation and immunomodulatory potential and lack of ethical issues associated with their use. The microenvironment of donors and recipients selected in cytotherapy plays a crucial role in regenerative potential of transplanted MSCs, indicating interactions of cells with their microenvironment indispensable in MSC-mediated bone and dental regeneration. Since a variety of MSC populations have been procured from different parts of the tooth and tooth-supporting tissues, MSCs of dental origin and their achievements in capacity to reconstitute various dental tissues have gained attention of many research groups over the years. This review discusses recent advances in comparative analyses of dental MSC regeneration potential with regards to their tissue origin and specific microenvironmental conditions, giving additional insight into the current clinical application of these cells.

Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.

Studies on complex biological phenomena often combine two or more imaging techniques to collect high-quality comprehensive data directly in situ, preserving the biological context. Mass spectrometry imaging (MSI) and vibrational spectroscopy imaging (VSI) complement each other in terms of spatial resolution and molecular information. In the past decade, several combinations of such multimodal strategies arose in research fields as diverse as microbiology, cancer, and forensics, overcoming many challenges toward the unification of these techniques. Here we focus on presenting the advantages and challenges of multimodal imaging from the point of view of studying biological samples as well as giving a perspective on the upcoming trends regarding this topic. The latest efforts in the field are discussed, highlighting the purpose of the technique for clinical applications.

[ES] La planificación en radioterapia requiere simular la distribución de la dosis basada en la imagen del paciente, obtenida mediante Tomografía Axial Computarizada. La forma de generar esta simulación es mediante algoritmos basados en Montecarlo, pero, estos algoritmos producen un cierto ruido que debe ser eliminado. Las redes neuronales convolucionales (RNC) han revolucionado el state-of-the-art en los últimos años mediante el reconocimiento de características de forma jerarquizada. El propósito del presente trabajo es la construcción de una red neuronal que tome por entrada una distribución de dosis tridimensional generada mediante algoritmos Montecarlo y, mediante los diferentes parámetros que esta incluye, remover el ruido que tenga para obtener una imagen perfectamente funcional en la práctica hospitalaria. La calidad de las imágenes generadas por Montecarlo depende del número de partículas que se modelicen, por lo que, mejorar la calidad de las mismas implica un aumento exponencial del tiempo de cálculo. Las distribuciones de dosis consideradas libres de ruido , requieren el uso de 1e9 partículas, lo que implica una hora de computación. Nosotros hemos filtrado imágenes generadas con 1e7 y 1e6, que conllevan, respectivamente, un minuto y 10 segundos de computación. Ambas redes neuronales se corresponden a la arquitectura U-Net, ampliamente usada en el área de segmentación de imágenes. Ambas redes superan el state-of-the-art actual, obteniendo un signal-to-noise ratio de 73.03 y 35.69 respectivamente, y empleando, aproximadamente 45 segundos en filtrar la imagen 3D., [EN] Radiation therapy planning requires to simulate the dose distribution on a CT patient image. It is used an algorithm based on Monte Carlo to generate that simulation, but this algorithm produces some noise that need to be removed. Convolutional Neural Networks (CNN) have improved the state-of-the-art in the recent years by recognizing hierarchical features on an image. The purpose of the current work is to build a Neural Network that take a 3D Monte Carlo Dose Distribution as an input and denoise it through the different layers it includes, to use it in hospital practice. The quality of Monte Carlo generated images depends on the number of particles employed, consequently, improving the quality of the images involves an exponential increase of the computing time. Simulations generated with 1e9 particles could be considered as free-noisy because the residual noise they have does not compromise the clinical application. We filtered distributions generated with 1e7 and 1e6 particles, what result in one minute and 10 seconds of computing, respectively. Both networks architectures are U-Net, commonly used in the segmentation task, both of them exceed the state-of-the-art, achieving a signal-to-noise ratio of 73.03 and 35.69 respectively, and they spend 45 seconds around on filtering the whole 3D-image.

[ES] La planificación en radioterapia requiere simular la distribución de la dosis basada en la imagen del paciente, obtenida mediante Tomografía Axial Computarizada. La forma de generar esta simulación es mediante algoritmos basados en Montecarlo, pero, estos algoritmos producen un cierto ruido que debe ser eliminado. Las redes neuronales convolucionales (RNC) han revolucionado el state-of-the-art en los últimos años mediante el reconocimiento de características de forma jerarquizada. El propósito del presente trabajo es la construcción de una red neuronal que tome por entrada una distribución de dosis tridimensional generada mediante algoritmos Montecarlo y, mediante los diferentes parámetros que esta incluye, remover el ruido que tenga para obtener una imagen perfectamente funcional en la práctica hospitalaria. La calidad de las imágenes generadas por Montecarlo depende del número de partículas que se modelicen, por lo que, mejorar la calidad de las mismas implica un aumento exponencial del tiempo de cálculo. Las distribuciones de dosis consideradas libres de ruido , requieren el uso de 1e9 partículas, lo que implica una hora de computación. Nosotros hemos filtrado imágenes generadas con 1e7 y 1e6, que conllevan, respectivamente, un minuto y 10 segundos de computación. Ambas redes neuronales se corresponden a la arquitectura U-Net, ampliamente usada en el área de segmentación de imágenes. Ambas redes superan el state-of-the-art actual, obteniendo un signal-to-noise ratio de 73.03 y 35.69 respectivamente, y empleando, aproximadamente 45 segundos en filtrar la imagen 3D., [EN] Radiation therapy planning requires to simulate the dose distribution on a CT patient image. It is used an algorithm based on Monte Carlo to generate that simulation, but this algorithm produces some noise that need to be removed. Convolutional Neural Networks (CNN) have improved the state-of-the-art in the recent years by recognizing hierarchical features on an image. The purpose of the current work is to build a Neural Network that take a 3D Monte Carlo Dose Distribution as an input and denoise it through the different layers it includes, to use it in hospital practice. The quality of Monte Carlo generated images depends on the number of particles employed, consequently, improving the quality of the images involves an exponential increase of the computing time. Simulations generated with 1e9 particles could be considered as free-noisy because the residual noise they have does not compromise the clinical application. We filtered distributions generated with 1e7 and 1e6 particles, what result in one minute and 10 seconds of computing, respectively. Both networks architectures are U-Net, commonly used in the segmentation task, both of them exceed the state-of-the-art, achieving a signal-to-noise ratio of 73.03 and 35.69 respectively, and they spend 45 seconds around on filtering the whole 3D-image.

[ES] La planificación en radioterapia requiere simular la distribución de la dosis basada en la imagen del paciente, obtenida mediante Tomografía Axial Computarizada. La forma de generar esta simulación es mediante algoritmos basados en Montecarlo, pero, estos algoritmos producen un cierto ruido que debe ser eliminado. Las redes neuronales convolucionales (RNC) han revolucionado el state-of-the-art en los últimos años mediante el reconocimiento de características de forma jerarquizada. El propósito del presente trabajo es la construcción de una red neuronal que tome por entrada una distribución de dosis tridimensional generada mediante algoritmos Montecarlo y, mediante los diferentes parámetros que esta incluye, remover el ruido que tenga para obtener una imagen perfectamente funcional en la práctica hospitalaria. La calidad de las imágenes generadas por Montecarlo depende del número de partículas que se modelicen, por lo que, mejorar la calidad de las mismas implica un aumento exponencial del tiempo de cálculo. Las distribuciones de dosis consideradas libres de ruido , requieren el uso de 1e9 partículas, lo que implica una hora de computación. Nosotros hemos filtrado imágenes generadas con 1e7 y 1e6, que conllevan, respectivamente, un minuto y 10 segundos de computación. Ambas redes neuronales se corresponden a la arquitectura U-Net, ampliamente usada en el área de segmentación de imágenes. Ambas redes superan el state-of-the-art actual, obteniendo un signal-to-noise ratio de 73.03 y 35.69 respectivamente, y empleando, aproximadamente 45 segundos en filtrar la imagen 3D., [EN] Radiation therapy planning requires to simulate the dose distribution on a CT patient image. It is used an algorithm based on Monte Carlo to generate that simulation, but this algorithm produces some noise that need to be removed. Convolutional Neural Networks (CNN) have improved the state-of-the-art in the recent years by recognizing hierarchical features on an image. The purpose of the current work is to build a Neural Network that take a 3D Monte Carlo Dose Distribution as an input and denoise it through the different layers it includes, to use it in hospital practice. The quality of Monte Carlo generated images depends on the number of particles employed, consequently, improving the quality of the images involves an exponential increase of the computing time. Simulations generated with 1e9 particles could be considered as free-noisy because the residual noise they have does not compromise the clinical application. We filtered distributions generated with 1e7 and 1e6 particles, what result in one minute and 10 seconds of computing, respectively. Both networks architectures are U-Net, commonly used in the segmentation task, both of them exceed the state-of-the-art, achieving a signal-to-noise ratio of 73.03 and 35.69 respectively, and they spend 45 seconds around on filtering the whole 3D-image.

[ES] La planificación en radioterapia requiere simular la distribución de la dosis basada en la imagen del paciente, obtenida mediante Tomografía Axial Computarizada. La forma de generar esta simulación es mediante algoritmos basados en Montecarlo, pero, estos algoritmos producen un cierto ruido que debe ser eliminado. Las redes neuronales convolucionales (RNC) han revolucionado el state-of-the-art en los últimos años mediante el reconocimiento de características de forma jerarquizada. El propósito del presente trabajo es la construcción de una red neuronal que tome por entrada una distribución de dosis tridimensional generada mediante algoritmos Montecarlo y, mediante los diferentes parámetros que esta incluye, remover el ruido que tenga para obtener una imagen perfectamente funcional en la práctica hospitalaria. La calidad de las imágenes generadas por Montecarlo depende del número de partículas que se modelicen, por lo que, mejorar la calidad de las mismas implica un aumento exponencial del tiempo de cálculo. Las distribuciones de dosis consideradas libres de ruido , requieren el uso de 1e9 partículas, lo que implica una hora de computación. Nosotros hemos filtrado imágenes generadas con 1e7 y 1e6, que conllevan, respectivamente, un minuto y 10 segundos de computación. Ambas redes neuronales se corresponden a la arquitectura U-Net, ampliamente usada en el área de segmentación de imágenes. Ambas redes superan el state-of-the-art actual, obteniendo un signal-to-noise ratio de 73.03 y 35.69 respectivamente, y empleando, aproximadamente 45 segundos en filtrar la imagen 3D., [EN] Radiation therapy planning requires to simulate the dose distribution on a CT patient image. It is used an algorithm based on Monte Carlo to generate that simulation, but this algorithm produces some noise that need to be removed. Convolutional Neural Networks (CNN) have improved the state-of-the-art in the recent years by recognizing hierarchical features on an image. The purpose of the current work is to build a Neural Network that take a 3D Monte Carlo Dose Distribution as an input and denoise it through the different layers it includes, to use it in hospital practice. The quality of Monte Carlo generated images depends on the number of particles employed, consequently, improving the quality of the images involves an exponential increase of the computing time. Simulations generated with 1e9 particles could be considered as free-noisy because the residual noise they have does not compromise the clinical application. We filtered distributions generated with 1e7 and 1e6 particles, what result in one minute and 10 seconds of computing, respectively. Both networks architectures are U-Net, commonly used in the segmentation task, both of them exceed the state-of-the-art, achieving a signal-to-noise ratio of 73.03 and 35.69 respectively, and they spend 45 seconds around on filtering the whole 3D-image.

Purpose/objectivesThree-dimensional (3D) printing is recognized as an effective clinical and educational tool in procedurally intensive specialties. However, it has a nascent role in radiation oncology. The goal of this investigation is to clarify the extent to which 3D printing applications are currently being used in radiation oncology through a systematic review of the literature.Materials/methodsA search protocol was defined according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Included articles were evaluated using parameters of interest including: year and country of publication, experimental design, sample size for clinical studies, radiation oncology topic, reported outcomes, and implementation barriers or safety concerns.ResultsOne hundred and three publications from 2012 to 2019 met inclusion criteria. The most commonly described 3D printing applications included quality assurance phantoms (26%), brachytherapy applicators (20%), bolus (17%), preclinical animal irradiation (10%), compensators (7%), and immobilization devices (5%). Most studies were preclinical feasibility studies (63%), with few clinical investigations such as case reports or series (13%) or cohort studies (11%). The most common applications evaluated within clinical settings included brachytherapy applicators (44%) and bolus (28%). Sample sizes for clinical investigations were small (median 10, range 1-42). A minority of articles described basic or translational research (11%) and workflow or cost evaluation studies (3%). The number of articles increased over time (P < 0.0001). While outcomes were heterogeneous, most studies reported successful implementation of accurate and cost-effective 3D printing methods.ConclusionsThree-dimensional printing is rapidly growing in radiation oncology and has been implemented effectively in a diverse array of applications. Although the number of 3D printing publications has steadily risen, the m

This review focuses on new and/or less standardized event-related potentials methods, in order to improve their knowledge for future clinical applications. The olfactory event-related potentials (OERPs) assess the olfactory functions in time domain, with potential utility in anosmia and degenerative diseases. The transcranial magnetic stimulation-electroencephalography (TMS-EEG) could support the investigation of the intracerebral connections with very high temporal discrimination. Its application in the diagnosis of disorders of consciousness has achieved recent confirmation. Magnetoencephalography (MEG) and event-related fields (ERF) could improve spatial accuracy of scalp signals, with potential large application in pre-surgical study of epileptic patients. Although these techniques have methodological limits, such as high inter- and intraindividual variability and high costs, their diffusion among researchers and clinicians is hopeful, pending their standardization.

Event-related potentials (ERPs) are obtained from the electroencephalogram (EEG) or the magnetoencephalogram (MEG, event-related fields (ERF)), extracting the activity that is time-locked to an event. Despite the potential utility of ERP/ERF in cognitive domain, the clinical standardization of their use is presently undefined for most of procedures. The aim of the present review is to establish limits and reliability of ERP medical application, summarize main methodological issues, and present evidence of clinical application and future improvement. The present section of the review focuses on well-standardized ERP methods, including P300, Contingent Negative Variation (CNV), Mismatch Negativity (MMN), and N400, with a chapter dedicated to laser-evoked potentials (LEPs). One section is dedicated to proactive preparatory brain activity as the Bereitschaftspotential and the prefrontal negativity (BP and pN). The P300 and the MMN potentials have a limited but recognized role in the diagnosis of cognitive impairment and consciousness disorders. LEPs have a well-documented usefulness in the diagnosis of neuropathic pain, with low application in clinical assessment of psychophysiological basis of pain. The other ERP components mentioned here, though largely applied in normal and pathological cases and well standardized, are still confined to the research field. CNV, BP, and pN deserve to be largely tested in movement disorders, just to explain possible functional changes in motor preparation circuits subtending different clinical pictures and responses to treatments.

Y3Fe5O12@Na0.5K0.5NbO3 (YIG@NKN) core-shell nanofibers were synthesized by the coaxial electrospinning technique. For comparison, samples of YIG and NKN nanofibers were prepared. Scanning Electron Microscopy (SEM) and 3D laser-scanning confocal microscopy (TDLM) of YIG@NKN nanofibers revealed long uniform size distributed fibers with the average diameter of 100–150 nm. X-Ray diffraction (XRD) examination shows the existence of the distinct peaks of orthorhombic NKN and cubic YIG. Magnetic force microscopy (MFM) of individual YIG@NKN nanofiber demonstrates a magnetic core that is extended in one half of the diameter of the fiber. These nanofibers show obvious Ferromagnetic resonance (FMR) with resonance near 2 KOe similar to YIG fibers but in such a way that it starts to increase linearly with applying magnetic field from zero up to near resonance field. Also they show a soft magnetic behavior with saturation magnetization of 10 emu/gr. Furthermore, we propose a model to explain line shape of randomly oriented fibers and extract all the magnetic anisotropy parameters from FMR data. The results rely the shape anisotropy as dominant effect, however the dipolar field among fibers should be considered. The highest degree of asymmetry observed in the case of core-shell fibers in hard direction that it can be originated from magneto electric effects. By taking into account the observed FMR, the ability of adequate control of microwave absorption by applying magnetic field and biocompatibility, the synthesized core-shell nanofibers are the most promising candidate for clinical application such as microwave cancer thermotherapy and adjustable microwave absorbers., QC 20191106

Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like “How do dynamic processes alter the underlying structural network?” and “Can we use network neuroscience for disease classification?” This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others., Network Architectures and Services

The detection of panels of inflammatory biomarkers such as cytokines has potential for the rapid and specific diagnostic of several devastating diseases such as primary cancers and/or metastatic tumors, as opposed to less serious conditions. For point-of-care clinical applications, the detection of these biomarkers requires a combination of pg/mL sensitivities and multiplexing capabilities, coupled with fit-for-purpose signal transduction strategies. Here, we report the development of a versatile centrifugal microfluidic platform combined with nanoporous microbeads for immunoaffinity-based profiling of cytokines. The device allows sample and analyte multiplexing and detection limits below 1 ng/mL were achieved within 30 minutes, using colorimetric detection., QC 20210330

Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like “How do dynamic processes alter the underlying structural network?” and “Can we use network neuroscience for disease classification?” This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others., Network Architectures and Services

Robotics has already been applied to several surgical fields, but only transoral robotic surgery has a recognized role in skull base surgery. Different preclinical prototypes have been described for endoscopic transnasal skull base surgery (ESBS), but only recently a dedicated, hybrid robotic system has become available for clinical practice.This chapter reviews the use of holders in neurosurgery and skull base surgery, provides an overview of limitations of previous robotic systems that were designed for other surgical applications, describes the different preclinical robotic prototypes that have been developed for ESBS, and reports the initial preclinical and clinical experience with a novel, dedicated, hybrid robotic solution for endoscopic skull base surgery (EndoscopeRobot®, Medineering, Munich, Germany).The era of robotics in skull base surgery is at its dawn, but advantages of the hybrid solution are already evident, though further studies are needed to gain additional data.

The concept of antibody microarrays is one of the most versatile approaches within multiplexed immunoassay technologies. These types of arrays have increasingly become an attractive tool for the exploratory detection and study of protein abundance, function, pathways, and potential drug targets. Due to the properties of the antibody microarrays and their potential use in basic research and clinical analytics, various types of antibody microarrays have already been developed. In spite of the growing number of studies utilizing this technique, few reviews about antibody microarray technology have been presented to reflect the quality and future uses of the generated data. In this review, we provide a summary of the recent applications of antibody microarray techniques in basic biology and clinical studies, providing insights into the current trends and future of protein analysis., QC 20180322

The CRISPR/Cas9 system has been applied in the genome editing and disruption of latent infections for herpesviruses such as the herpes simplex virus, Epstein⁻Barr virus, cytomegalovirus, and Kaposi's sarcoma-associated herpesvirus. CRISPR/Cas9-directed mutagenesis can introduce similar types of mutations to the viral genome as can bacterial artificial chromosome recombination engineering, which maintains and reconstitutes the viral genome successfully. The cleavage mediated by CRISPR/Cas9 enables the manipulation of disease-associated viral strains with unprecedented efficiency and precision. Additionally, current therapies for herpesvirus productive and latent infections are limited in efficacy and cannot eradicate viruses. CRISPR/Cas9 is potentially adapted for antiviral treatment by specifically targeting viral genomes during latent infections. This review, which focuses on recently published progress, suggests that the CRISPR/Cas9 system is not only a useful tool for basic virology research, but also a promising strategy for the control and prevention of herpesvirus latent infections.

The CRISPR/Cas9 system has been applied in the genome editing and disruption of latent infections for herpesviruses such as the herpes simplex virus, Epstein⁻Barr virus, cytomegalovirus, and Kaposi's sarcoma-associated herpesvirus. CRISPR/Cas9-directed mutagenesis can introduce similar types of mutations to the viral genome as can bacterial artificial chromosome recombination engineering, which maintains and reconstitutes the viral genome successfully. The cleavage mediated by CRISPR/Cas9 enables the manipulation of disease-associated viral strains with unprecedented efficiency and precision. Additionally, current therapies for herpesvirus productive and latent infections are limited in efficacy and cannot eradicate viruses. CRISPR/Cas9 is potentially adapted for antiviral treatment by specifically targeting viral genomes during latent infections. This review, which focuses on recently published progress, suggests that the CRISPR/Cas9 system is not only a useful tool for basic virology research, but also a promising strategy for the control and prevention of herpesvirus latent infections.

Acute brain injury resulting from ischemic/hemorrhagic or traumatic damage is one of the leading causes of mortality and disability worldwide and is a significant burden to society. Neuroprotective options to counteract brain damage are very limited in stroke and traumatic brain injury (TBI). Given the multifaceted nature of acute brain injury and damage progression, several therapeutic targets may need to be addressed simultaneously to interfere with the evolution of the injury and improve the patient’s outcome. Stem cells are ideal candidates since they act on various mechanisms of protection and repair, improving structural and functional outcomes after experimental stroke or TBI. Stem cells isolated from placenta offer advantages due to their early embryonic origin, ease of procurement, and ethical acceptance. We analyzed the evidence for the beneficial effects of placenta-derived stem cells in acute brain injury, with the focus on experimental studies of TBI and stroke, the engineering strategies pursued to foster cell potential, and characterization of the bioactive molecules secreted by placental cells, known as their secretome, as an alternative cell-free strategy. Results from the clinical application of placenta-derived stem cells for acute brain injury and ongoing clinical trials are summarily discussed.

Pluripotent stem cells (PSCs) provide unique opportunities for understanding basic biology, for developing tissue models for drug testing, and for clinical applications in regenerative medicine. These require the development of robust platforms and protocols for maintenance of their self-renewal as well as for differentiation to a specific cell fate. Cell fate and functions are influenced by components of the surrounding microenvironment, including soluble factors, extracellular matrix (ECM), cell-cell and cell-matrix interactions, and mechanical forces. Various culture substrates and surfaces based on feeder cells, decellularized matrices, ECM proteins, and cell adhesion molecules have been reported, with profound effects on proliferation and differentiation of stem cells. Synthetic substrates, based on peptides and polymers, have also emerged as alternative platforms to provide a chemically defined and xeno-free culture system for expansion and long-term maintenance of stem cells. These advances in surface engineering will continue to grow and guide the development of processes for stem cell application.

Background: The placebo effect and the placebo response is a misunderstood phenomenon and their potential is wildly underestimated. Most people, including health care professionals, consider the placebo effect to be a “make believe” effect which only affects gullible people. It is argued that the nurse is in an unusually advantageous position to observe and facilitate the placebo effect and make use of the benefits for the patients. Observation of said response is made by many authors but there is little to no research on the placebo effect from a nursing standpoint. Some of the research results can however be translated to the nurse profession and used in clinical settings. Aim: The purpose is to describe areas where the placebo effect may affect nursing of the patient. Method: A literature review format was chosen to comprise existing knowledge on the placebo effect, which can be applied for nursing. Results: Themes that arose from examination of chosen literature included: Emotional state, Expectation and Conditioning, Conscious and Social learning and Patient-caregiver relationship. Many of the observed interventions could be applied using the nursing philosophy of Hildegard Peplau. Conclusion: The placebo effect can be used by the nurse to improve the result of the patient´s treatment. If placebo becomes a focus in nursing research the results could be more applicable to benefit patients than if researched by other professional groups.

Annealing, or heat treatment, has traditionally been used as a treatment to improve the strength and stiffness of electrospun materials. Understanding the extent to which annealing can improve the mechanical properties and alter the degradation rate of electrospun polydioxanone filaments could influence the range of its potential clinical applications. In this study, we investigated the effect of annealing electrospun polydioxanone filaments at varying times and temperatures and subsequently subjecting them to in vitro degradation in phosphate buffer saline for up to 6 weeks. Fibre alignment, tensile strength and thermal properties were assessed. It was determined that annealing at 65 °C for 3 h only marginally improved the tensile strength (9±2%) but had a significant effect on reducing strain and rate of degradation, as well as maintaining fibre alignment within the filament. The filament retained significantly more of its force at failure after 4 weeks (82±15%, compared to 61±20% for non annealed filaments) and after 6 weeks of degradation (81±9%, compared to 55±13% for non annealed filaments). Conversely, annealing filaments at 75°C improved the initial tensile strength of the filament (17±6%), but over 6 weeks, both samples annealed at 75 °C and 85 °C otherwise performed similarly or mechanically worse than those not annealed. These findings suggest that annealing at low temperatures is more useful as a method to tailor degradation rate than to improve mechanical properties. The ability to modulate the degradation profile with annealing may become useful to tailor the properties of electrospun materials without altering the chemistry of the polymer used. This might better match the degradation of the implant and gradual loss of mechanical properties with the new matrix deposition within the structure, enabling multiple regenerative strategies within a single

A combined optical coherence tomography (OCT)-Raman probe was designed and built into a spectral domain OCT head, and its performance was evaluated and compared to the most common Raman probe setups, based on a fiber bundle and confocal free space optics. Due to the use of the full field of view of an OCT scanning lens, the combined probe has a superior performance within maximum permissible exposure limits, compared to the other two probes. Skin Raman spectra, recorded in vivo, further prove the feasibility of the OCT-Raman probe for the future in vivo clinical applications in skin cancer screening. © 2017 Author(s).

Background: The placebo effect and the placebo response is a misunderstood phenomenon and their potential is wildly underestimated. Most people, including health care professionals, consider the placebo effect to be a “make believe” effect which only affects gullible people. It is argued that the nurse is in an unusually advantageous position to observe and facilitate the placebo effect and make use of the benefits for the patients. Observation of said response is made by many authors but there is little to no research on the placebo effect from a nursing standpoint. Some of the research results can however be translated to the nurse profession and used in clinical settings. Aim: The purpose is to describe areas where the placebo effect may affect nursing of the patient. Method: A literature review format was chosen to comprise existing knowledge on the placebo effect, which can be applied for nursing. Results: Themes that arose from examination of chosen literature included: Emotional state, Expectation and Conditioning, Conscious and Social learning and Patient-caregiver relationship. Many of the observed interventions could be applied using the nursing philosophy of Hildegard Peplau. Conclusion: The placebo effect can be used by the nurse to improve the result of the patient´s treatment. If placebo becomes a focus in nursing research the results could be more applicable to benefit patients than if researched by other professional groups.

The coenzyme NAD+ is critical in cellular bioenergetics and adaptive stress responses. Its depletion has emerged as a fundamental feature of aging that may predispose to a wide range of chronic diseases. Maintenance of NAD+ levels is important for cells with high energy demands and for proficient neuronal function. NAD+ depletion is detected in major neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases, cardiovascular disease and muscle atrophy. Emerging evidence suggests that NAD+ decrements occur in various tissues during aging, and that physiological and pharmacological interventions bolstering cellular NAD+ levels might retard aspects of aging and forestall some age-related diseases. Here, we discuss aspects of NAD+ biosynthesis, together with putative mechanisms of NAD+ action against aging, including recent preclinical and clinical trials. Recent discoveries have demonstrated an age-dependent decrease in cellular and/or tissue NAD+ levels in laboratory animal models. Moreover, NAD+ depletion has been linked to multiple hallmarks of aging. In premature aging animal models, NAD+ levels are decreased, while NAD+ replenishment can improve lifespan and healthspan through DNA repair and mitochondrial maintenance. Mitochondrial autophagy (mitophagy) has a major role in clearance of damaged and/or dysfunctional mitochondria, and compromised mitophagy has been linked to metabolic disorders, neurodegeneration [including Alzheimer's disease (AD) and Parkinson's disease (PD)] in addition to aging, and other age-related diseases. New evidence suggests that NAD+ precursors, such as nicotinamide and nicotinamide riboside, forestall pathology and cognitive decline in mouse models of AD. NAD+ supplementation can inhibit multiple aging features in animal models. This highlights essential roles for NAD+ i

Background: Adipose derived stromal cells (ASCs) are a rich and convenient source of cells for clinical regenerative therapeutic approaches. However, applications of ASCs often require cell expansion to reach the needed dose. In this study, cultivation of ASCs from stromal vascular fraction (SVF) over two passages in the automated and functionally closed Quantum Cell Expansion System (Quantum system) is compared with traditional manual cultivation. Methods: Stromal vascular fraction was isolated from abdominal fat, suspended in α-MEM supplemented with 10% Fetal Bovine Serum and seeded into either T75 flasks or a Quantum system that had been coated with cryoprecipitate. The cultivation of ASCs from SVF was performed in 3 ways: flask to flask; flask to Quantum system; and Quantum system to Quantum system. In all cases, quality controls were conducted for sterility, mycoplasmas, and endotoxins, in addition to the assessment of cell counts, viability, immunophenotype, and differentiation potential. Results: The viability of ASCs passage 0 (P0) and P1 was above 96%, regardless of cultivation in flasks or Quantum system. Expression of surface markers and differentiation potential was consistent with ISCT/IFATS standards for the ASC phenotype. Sterility, mycoplasma, and endotoxin tests were consistently negative. An average of 8.0 × 107 SVF cells loaded into a Quantum system yielded 8.96 × 107 ASCs P0, while 4.5 × 106 SVF cells seeded per T75 flask yielded an average of 2.37 × 106 ASCs-less than the number of SVF cells seeded. ASCs P1 expanded in the Quantum system demonstrated a population doubling (PD) around 2.2 regardless of whether P0 was previously cultured in flasks or Quantum, while ASCs P1 in flasks only reached a PD of 1.0. Conclusion: Manufacturing of ASCs in a Quantum system enhances ASC expansion rate and yield significantly relative to manual processing in T-flasks, while maintaining the purity and quality essent

Advances in neuroprosthetics in recent years have made an enormous impact on the quality of life for many people with disabilities, helping them regain the functionality of damaged or impaired abilities. One of the main hurdles to regaining full functionality regarding neuroprosthetics is the integration between the neural prosthetic device and the method in which the neural prosthetic device is controlled or manipulated to function correctly and efficiently. One of the most promising methods for integrating neural prosthetics to an efficient method of control is through Brian-computer Interfacing (BCI). With this method, the neuroprosthetic device is integrated into the human brain through the use of a specialized computer, which allows for users of neuroprosthetic devices to control the devices in the same way that they would control a normally working human function- with their mind. There are both invasive and non-invasive methods to implement Brain-computer Interfacing, both of which involve the process of acquiring a brain signal, processing the signal, and finally providing a usable device output. There are several examples of integration between Brain-computer Interfacing and neural prosthetics that are currently being researched. Many challenges must be overcome before a widespread clinical application of integration between Brain-computer Interfaces and neural prosthetics becomes a reality, but current research continues to provide promising advancement toward making this technology available as a means for people to regain lost functionality.

Hydrogels are a versatile tool for a multitude of applications in biomedical research and clinical practice. Especially collagen and fibrin hydrogels are distinguished by their excellent biocompatibility, natural capacity for cell adhesion and low immunogenicity. In many ways, collagen and fibrin represent an ideal biomaterial, as they can serve as a scaffold for tissue regeneration and promote the migration of cells, as well as the ingrowth of tissues. On the other hand, pure collagen and fibrin materials are marked by poor mechanical properties and rapid degradation, which limits their use in practice. This paper will review methods of modification of natural collagen and fibrin materials to next-generation materials with enhanced stability. A special focus is placed on biomedical products from fibrin and collagen already on the market. In addition, recent research on the in vivo applications of collagen and fibrin-based materials will be showcased. © 2016 by De Gruyter.

Este artículo presenta información centrada en la aplicación de la Activación Conductual y las dificultades que pueden aparecer durante su puesta en práctica. Tras recodar brevemente su punto de partida como terapia independiente y explicar su modelo teórico que da cuenta del origen y del mantenimiento de los estados depresivos, se presenta una información más detallada sobre las técnicas de intervención, así como de la secuencia que se aconseja para su aplicación en el contexto clínico. A partir de una numeración, se describen los pasos que parecen más recomendables según una integración de los principales protocolos de la terapia. Así mismo, se presentan algunas pistas para el manejo de las situaciones difíciles más características de la aplicación de la Activación Conductual. Finalmente, se repasan algunos de los ámbitos hacia los que se ha expandido esta intervención, más allá de la depresión unipolar. Una conclusiones sobre su papel e importancia como herramienta para la lucha contra la depresión desde el plano de la terapia psicológica cierran este trabajo., This article presents information focused on the application of Behavioral Activation and the difficulties that may arise during its implementation. After briefly remind its origin as an independent therapy and explain their theoretical model that accounts for the origin and maintenance of depressive moods, more detailed information on intervention techniques and the recommended sequence for its application in the clinical context is submitted. Through a list that integrates the core protocols of therapy, the more appropriate steps are put forward. Also, some clues for handling the most difficult and common situations of the application of Behavioral Activation are presented. Finally, some of the areas to which this intervention has expanded beyond unipolar depression are reviewing. Some conclusions about its role and importance as a tool for fighting depression from the perspective of psychological therapy ends this work.

Promising targeted therapy and personalized medicine are making molecular profiling of tumours a priority. For colorectal cancer (CRC) patients, international guidelines made RAS (KRAS and NRAS) status a prerequisite for the use of anti-epidermal growth factor receptor agents (anti-EGFR). Daily, new data emerge on the theranostic and prognostic role of molecular biomarkers, which is a strong incentive for a validated, sensitive and broadly available molecular screening test in order to implement and improve multi-modal therapy strategy and clinical trials. Next generation sequencing (NGS) has begun to supplant other technologies for genomic profiling. Targeted NGS is a method that allows parallel sequencing of thousands of short DNA sequences in a single test offering a cost-effective approach for detecting multiple genetic alterations with a minimum amount of DNA. In the present review, we collected data concerning the clinical application of NGS technology in the setting of colorectal cancer., SCOPUS: re.j, info:eu-repo/semantics/published