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1.
World Neurosurg ; 148: 251-255, 2021 04.
Artículo en Inglés | MEDLINE | ID: mdl-33770847

RESUMEN

The COVID-19 pandemic has impacted neurosurgery in unforeseeable ways. Neurosurgical patient care, research, and education have undergone extraordinary modifications as medicine and mankind have adapted to overcome the challenges posed by this pandemic. Some changes will disappear as the situation slowly recovers to a prepandemic status quo. Others will remain: This pandemic has sparked some long-overdue systemic transformations across all levels of medicine, including in neurosurgery, that will be beneficial in the future. In this paper, we present some of the challenges faced across different levels of neurosurgical clinical care, research, and education, the changes that followed, and how some of these modifications have transformed into opportunities for improvement and growth in the future.


Asunto(s)
Investigación Biomédica/métodos , Prestación de Atención de Salud/métodos , Neurocirugia/métodos , Cuidados Críticos , Educación a Distancia/métodos , Procedimientos Quirúrgicos Electivos , Capacidad de Camas en Hospitales , Humanos , Unidades de Cuidados Intensivos , Neurocirugia/educación , Procedimientos Neuroquirúrgicos , Quirófanos , Innovación Organizacional , Consulta Remota/métodos , Telemedicina/métodos
2.
Undersea Hyperb Med ; 48(1): 59-72, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33648035

RESUMEN

It is widely accepted that bubbles are a necessary but insufficient condition for the development of decompression sickness. However, open questions remain regarding the precise formation and behavior of these bubbles after an ambient pressure reduction (decompression), primarily due to the inherent difficulty of directly observing this phenomenon in vivo. In decompression research, information about these bubbles after a decompression is gathered via means of ultrasound acquisitions. The ability to draw conclusions regarding decompression research using ultrasound is highly influenced by the variability of the methodologies and equipment utilized by different research groups. These differences play a significant role in the quality of the data and thus the interpretation of the results. The purpose of this review is to provide a technical overview of the use of ultrasound in decompression research, particularly Doppler and brightness (B)-mode ultrasound. Further, we will discuss the strengths and limitations of these technologies and how new advancements are improving our ability to understand bubble behavior post-decompression.


Asunto(s)
Investigación Biomédica/métodos , Enfermedad de Descompresión/diagnóstico por imagen , Ecocardiografía Doppler/métodos , Ultrasonografía Doppler/métodos , Descompresión , Enfermedad de Descompresión/etiología , Buceo/fisiología , Ecocardiografía Doppler/tendencias , Embolia Aérea/diagnóstico por imagen , Embolia Aérea/etiología , Humanos , Diseño de Software , Sonido , Transductores , Ultrasonografía Doppler/instrumentación , Ultrasonografía Doppler/tendencias
6.
IEEE Pulse ; 12(1): 7-11, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33630735

RESUMEN

With seasonal influenza, Ebola, shingles, pneumonia, human papillomavirus, and other pathogens-combined now with the novel coronavirus (SARS-CoV-2)-the world's demand for vaccines is on a steep incline. New vaccine development is progressing rapidly, as seen with recent announcements of coronavirus options [1], [2], but what about their manufacture?


Asunto(s)
Investigación Biomédica/métodos , Reactores Biológicos , /prevención & control , Animales , Técnicas de Cultivo de Célula , Células Cultivadas , Pollos , Huevos , Humanos
7.
Nat Commun ; 12(1): 1107, 2021 02 17.
Artículo en Inglés | MEDLINE | ID: mdl-33597541

RESUMEN

One of the primary tools that researchers use to predict risk is the case-control study. We identify a flaw, temporal bias, that is specific to and uniquely associated with these studies that occurs when the study period is not representative of the data that clinicians have during the diagnostic process. Temporal bias acts to undermine the validity of predictions by over-emphasizing features close to the outcome of interest. We examine the impact of temporal bias across the medical literature, and highlight examples of exaggerated effect sizes, false-negative predictions, and replication failure. Given the ubiquity and practical advantages of case-control studies, we discuss strategies for estimating the influence of and preventing temporal bias where it exists.


Asunto(s)
Investigación Biomédica/normas , Ensayos Clínicos como Asunto/normas , Selección de Paciente , Proyectos de Investigación/normas , Sesgo , Investigación Biomédica/métodos , Investigación Biomédica/tendencias , Estudios de Casos y Controles , Ensayos Clínicos como Asunto/métodos , Predicción , Humanos , Reproducibilidad de los Resultados
8.
J Korean Med Sci ; 36(5): e41, 2021 Feb 01.
Artículo en Inglés | MEDLINE | ID: mdl-33527783

RESUMEN

Infographics are pictorial representations of information intended to disseminate information quickly and clearly. Their use has increased in the past decade due to wider and easy access to technology. Infographics are being increasingly used for public advisories, disseminating protocols for healthcare professionals, and post-publication promotion of research. Due to their potential to rapidly reach a vast audience, these have gained larger importance during the coronavirus disease 2019 pandemic. Two key aspects determine the quality of infographics, content and visual appeal. In this brief, the authors attempt to delineate the key aspects of designing an infographic, and the freeware that they may have at their disposal for creating informative, appealing, and useful infographics.


Asunto(s)
Recursos Audiovisuales/tendencias , Investigación Biomédica/métodos , Comunicación en Salud , Difusión de la Información/métodos , Medios de Comunicación Sociales , Gráficos por Computador , Personal de Salud , Humanos , Pandemias
10.
Methods Mol Biol ; 2190: 33-71, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32804360

RESUMEN

With the biomedical field generating large quantities of time series data, there has been a growing interest in developing and refining machine learning methods that allow its mining and exploitation. Classification is one of the most important and challenging machine learning tasks related to time series. Many biomedical phenomena, such as the brain's activity or blood pressure, change over time. The objective of this chapter is to provide a gentle introduction to time series classification. In the first part we describe the characteristics of time series data and challenges in its analysis. The second part provides an overview of common machine learning methods used for time series classification. A real-world use case, the early recognition of sepsis, demonstrates the applicability of the methods discussed.


Asunto(s)
Investigación Biomédica/métodos , Aprendizaje Profundo , Aprendizaje Automático , Minería de Datos/métodos , Humanos
11.
Methods Mol Biol ; 2190: 289-305, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32804372

RESUMEN

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.


Asunto(s)
Investigación Biomédica/métodos , Minería de Datos/métodos , Redes Neurales de la Computación , Algoritmos , Ontologías Biológicas , Bases de Datos Factuales , Publicaciones
12.
Methods Mol Biol ; 2190: 317-336, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32804374

RESUMEN

Recently, digitization of biomedical processes has accelerated, in no small part due to the use of machine learning techniques which require large amounts of labeled data. This chapter focuses on the prerequisite steps to the training of any algorithm: data collection and labeling. In particular, we tackle how data collection can be set up with scalability and security to avoid costly and delaying bottlenecks. Unprecedented amounts of data are now available to companies and academics, but digital tools in the biomedical field encounter a problem of scale, since high-throughput workflows such as high content imaging and sequencing can create several terabytes per day. Consequently data transport, aggregation, and processing is challenging.A second challenge is maintenance of data security. Biomedical data can be personally identifiable, may constitute important trade-secrets, and be expensive to produce. Furthermore, human biomedical data is often immutable, as is the case with genetic information. These factors make securing this type of data imperative and urgent. Here we address best practices to achieve security, with a focus on practicality and scalability. We also address the challenge of obtaining usable, rich metadata from the collected data, which is a major challenge in the biomedical field because of the use of fragmented and proprietary formats. We detail tools and strategies for extracting metadata from biomedical scientific file formats and how this underutilized metadata plays a key role in creating labeled data for use in the training of neural networks.


Asunto(s)
Investigación Biomédica/métodos , Recolección de Datos/métodos , Algoritmos , Seguridad Computacional , Aprendizaje Automático , Redes Neurales de la Computación , Flujo de Trabajo
14.
Methods Mol Biol ; 2223: 169-182, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33226595

RESUMEN

Flow cytometry is a popular technique used for both clinical and research purposes. It involves laser-based technology to characterize cells based on size, shape, and complexity. Additionally, flow cytometers are equipped with the ability to take fluorescence measurements at multiple wavelengths. This capability makes the flow cytometer a practical resource in the utilization of fluorescently conjugated antibodies, fluorescent proteins, DNA binding dyes, viability dyes, and ion indicator dyes. As the technology advances, the number of parameters a flow cytometer can measure has increased tremendously, and now some has the capacity to analyze 30-50 or more parameters on a single cell. Here, we describe the basic principles involved in the mechanics and procedures of flow cytometry along with an insight into applications of flow cytometry techniques for biomedical and allergic disease research.


Asunto(s)
Citometría de Flujo/métodos , Hipersensibilidad/inmunología , Inmunofenotipificación/métodos , Análisis de la Célula Individual/métodos , Linfocitos T/citología , Animales , Anticuerpos/análisis , Antígenos CD/genética , Antígenos CD/inmunología , Biomarcadores/análisis , Investigación Biomédica/instrumentación , Investigación Biomédica/métodos , Supervivencia Celular , Citometría de Flujo/instrumentación , Colorantes Fluorescentes/química , Humanos , Hipersensibilidad/diagnóstico , Hipersensibilidad/genética , Hipersensibilidad/patología , Inmunoconjugados/análisis , Rayos Láser , Análisis de la Célula Individual/instrumentación , Linfocitos T/inmunología
16.
Biomed Pharmacother ; 134: 111017, 2021 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-33338751

RESUMEN

Myricetin(MYR) is a flavonoid compound widely found in many natural plants including bayberry. So far, MYR has been proven to have multiple biological functions and it is a natural compound with promising research and development prospects. This review comprehensively retrieved and collected the latest pharmacological abstracts on MYR, and discussed the potential molecular mechanisms of its effects. The results of our review indicated that MYR has a therapeutic effect on many diseases, including tumors of different types, inflammatory diseases, atherosclerosis, thrombosis, cerebral ischemia, diabetes, Alzheimer's disease and pathogenic microbial infections. Furthermore, it regulates the expression of Hippo, MAPK, GSK-3ß, PI3K/AKT/mTOR, STAT3, TLR, IκB/NF-κB, Nrf2/HO-1, ACE, eNOS / NO, AChE and BrdU/NeuN. MYR also enhances the immunomodulatory functions, suppresses cytokine storms, improves cardiac dysfunction, possesses an antiviral potential, can be used as an adjuvant treatment against cancer, cardiovascular injury and nervous system diseases, and it may be a potential drug against COVID-19 and other viral infections. Generally, this article provides a theoretical basis for the clinical application of MYR and a reference for its further use.


Asunto(s)
Investigación Biomédica/tendencias , Flavonoides/farmacología , Mediadores de Inflamación/antagonistas & inhibidores , Mediadores de Inflamación/metabolismo , Animales , Antiinfecciosos/química , Antiinfecciosos/farmacología , Antiinflamatorios/química , Antiinflamatorios/farmacología , Antineoplásicos/química , Antineoplásicos/farmacología , Investigación Biomédica/métodos , Proliferación Celular/efectos de los fármacos , Proliferación Celular/fisiología , Flavonoides/química , Humanos
17.
Methods Mol Biol ; 2194: 1-19, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32926358

RESUMEN

Translational bioinformatics for therapeutic discovery requires the infrastructure of clinical informatics. In this chapter, we describe the clinical informatics components needed for successful implementation of translational research at a cancer center. This chapter is meant to be an introduction to those clinical informatics concepts that are needed for translational research. For a detailed account of clinical informatics, the authors will guide the reader to comprehensive resources. We provide examples of workflows from Moffitt Cancer Center led by Drs. Perkins and Markowitz. This perspective represents an interesting collaboration as Dr. Perkins is the Chief Medical Information Officer and Dr. Markowitz is a translational researcher in Melanoma with an active informatics component to his laboratory to study the mechanisms of resistance to checkpoint blockade and an active member of the clinical informatics team.


Asunto(s)
Investigación Biomédica/métodos , Biología Computacional/organización & administración , Informática Médica/métodos , Informática Médica/organización & administración , Oncología Médica/métodos , Investigación en Medicina Traslacional/métodos , Investigación en Medicina Traslacional/organización & administración , Instituciones Oncológicas/organización & administración , Humanos , Flujo de Trabajo
18.
Zhonghua Liu Xing Bing Xue Za Zhi ; 41(12): 2160-2162, 2020 Dec 10.
Artículo en Chino | MEDLINE | ID: mdl-33378832

RESUMEN

Learning clinical research methods, we must master the essentials. Essentials are the theories, principles and methods that make a discipline a unique discipline, without which the discipline will no more exist. Essentials are those things that are long-lasting and reliable, those that address the most important issues, those that are most frequently used in practice, and those that normally should not be compromised. The core underlying theories of epidemiological research are causation and errors control. The essentials often have profound theoretical underpinnings and difficult to grasp. We will truly believe the theories and observe the principles only when we have truly grasped them.


Asunto(s)
Investigación Biomédica , Investigación Biomédica/métodos , Investigación Biomédica/normas , Humanos
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