Jove
Visualize
Contáctanos
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Videos de Conceptos Relacionados

Indeterminate Products01:29

Indeterminate Products

139
Indeterminate forms also arise in the evaluation of limits involving products, particularly when one factor approaches zero while the other tends to positive or negative infinity. This situation, commonly described as a zero-times-infinity form, does not have an immediately interpretable outcome. Depending on how the factors behave relative to one another, the limit of such a product may be zero, infinite, or a finite nonzero value.Product Limits and Algebraic RewritingTo analyze limits of this...
139
The Entropy as a State Function01:14

The Entropy as a State Function

134
Consider an arbitrary process that moves between two specific states (A and B) in a cyclic manner. This process is reversible and broken down into smaller parts that each follow a Carnot cycle. A Carnot cycle has two isothermal (constant temperature) processes. During these processes, the ratio of the amount of heat transferred to their respective temperature remains constant. The other two processes in the Carnot cycle are also reversible but adiabatic, which means they occur without any heat...
134
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

2.4K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.4K
Entropy02:39

Entropy

26.1K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
26.1K
Entropy01:18

Entropy

2.8K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
2.8K
Neural Circuits01:25

Neural Circuits

3.0K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
3.0K

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Intrinsic and extrinsic regulators of cancer dormancy and awakening.

Journal of the National Cancer Center·2026
Same author

Editorial Expression of Concern: Creation of human tumour cells with defined genetic elements.

Nature·2026
Same author

Ether lipids influence cancer cell fate by modulating iron uptake.

Nature communications·2026
Same author

Inflammation awakens dormant cancer cells by modulating the epithelial-mesenchymal phenotypic state.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

EMT-ciliary signaling in quasi-mesenchymal-stem-like cells drives therapeutic resistance and is a druggable vulnerability in triple-negative breast cancer.

EMBO molecular medicine·2025
Same author

It took a long, long time: Ras and the race to cure cancer.

Cell·2024
Same journal

A viral ORFeome library for systems-level genetic dissection of host-pathogen interactions.

Cell·2026
Same journal

Co-option of lysosomal machinery shapes the evolution of the intracellular photosymbiosis supporting coral reefs.

Cell·2026
Same journal

LEF1 and niche factors determine T cell stemness across chronic diseases.

Cell·2026
Same journal

Recurrent patterns of TOP1-mediated neuronal genomic damage shared by major neurodegenerative disorders.

Cell·2026
Same journal

Four-dimensional molecular mapping from a spatial snapshot reveals the dynamics of hair follicle organogenesis.

Cell·2026
Same journal

Whole-cell particle-based digital twin simulations from 4D lattice light-sheet microscopy data.

Cell·2026
Ver todos los artículos relacionados

Video Experimental Relacionado

Updated: May 1, 2026

The Power of Simplicity: Sea Urchin Embryos as in Vivo Developmental Models for Studying Complex Cell-to-cell Signaling Network Interactions
07:34

The Power of Simplicity: Sea Urchin Embryos as in Vivo Developmental Models for Studying Complex Cell-to-cell Signaling Network Interactions

Published on: February 16, 2017

7.5K

El círculo se cierra: de la infinita complejidad a la simplicidad y viceversa.

Robert A Weinberg1

  • 1Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Ludwig/MIT Center for Molecular Oncology, Cambridge, MA 02142, USA; MIT Department of Biology, Cambridge, MA 02142, USA.

Cell
|April 1, 2014
PubMed
Resumen
Este resumen es generado por máquina.

La investigación del cáncer ha evolucionado durante más de 40 años, pasando de fenómenos complejos a enfoques reduccionistas y ahora abrazando la intrincada naturaleza de la enfermedad. Este cambio pone de relieve el desafío continuo de comprender el cáncer.

Más Videos Relacionados

Perspectives on Neuroscience
26:41

Perspectives on Neuroscience

Published on: July 31, 2007

4.7K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K

Videos de Experimentos Relacionados

Last Updated: May 1, 2026

The Power of Simplicity: Sea Urchin Embryos as in Vivo Developmental Models for Studying Complex Cell-to-cell Signaling Network Interactions
07:34

The Power of Simplicity: Sea Urchin Embryos as in Vivo Developmental Models for Studying Complex Cell-to-cell Signaling Network Interactions

Published on: February 16, 2017

7.5K
Perspectives on Neuroscience
26:41

Perspectives on Neuroscience

Published on: July 31, 2007

4.7K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K

Área de la Ciencia:

  • Oncología y Biología Molecular.

Sus antecedentes:

  • La Biología Celular y Molecular ha avanzado significativamente en la investigación del cáncer durante cuatro décadas.
  • El campo ha experimentado cambios entre enfocarse en fenómenos biológicos complejos y enfoques moleculares reduccionistas.
  • Las tendencias recientes indican un retorno a abordar la complejidad inherente del cáncer.

Objetivo del estudio:

  • Reflexionar sobre la trayectoria histórica de las metodologías de investigación del cáncer.
  • Para reconocer los éxitos de la biología molecular reduccionista.
  • Para enfatizar la necesidad actual de enfrentar la complejidad del cáncer.

Principales métodos:

  • Revisión histórica de los paradigmas de investigación en el cáncer.
  • Análisis del impacto de la biología molecular reduccionista.
  • Discusión de la evolución de los enfoques de investigación del cáncer.

Principales resultados:

  • La biología molecular reduccionista ha producido éxitos significativos en la investigación del cáncer.
  • El campo ha oscilado entre la fenomenología compleja y los enfoques reduccionistas.
  • Hay un creciente reconocimiento de la necesidad de abordar la complejidad multifacética del cáncer.

Conclusiones:

  • La historia de la investigación del cáncer está marcada por la evolución de las metodologías.
  • Si bien el reduccionismo ha sido poderoso, es insuficiente para abordar completamente el cáncer.
  • La investigación futura sobre el cáncer debe integrar enfoques de sistemas complejos para superar los desafíos.