Low but not moderate amounts of caffeine increase co-consumption of ethanol in C57BL/6J mice.

The increasingly popular combination of "energy drinks" containing high amounts of caffeine and alcohol has been shown to induce a stimulated, rather than sedated, state which may result in increased binge drinking and increased risk for alcohol-attributable accidents. We sought to examine consumption patterns of and withdrawal from alcohol and caffeine using a voluntary co-consumption animal model. Male and female adult C57BL/6J mice were given access to increasing doses of caffeine (0.01-0.05%) and/or alcohol (3-20%) in a two-bottle choice, intermittent access voluntary paradigm with fluid consumption recorded daily. Anxiety-like behavior during withdrawal was assessed via elevated plus maze or open field test in experiment 2. Increasing both alcohol and caffeine simultaneously in Experiment 1 resulted in no significant changes in co-consumption compared to mice given access to only alcohol or caffeine. Experiment 2 held caffeine concentration steady while slowly increasing alcohol content and resulted in mice consuming more alcohol when it was consumed in tandem with low dose caffeine. Both male and female mice consumed more caffeine when it was paired with alcohol; however, no significant differences were observed during withdrawal behavior. These results suggest that caffeine may dose-dependently positively influence alcohol consumption in mice and echo clinical literature suggesting that caffeine and alcohol together may result in a heightened state of stimulation and lead to further binge drinking. The intermittent access paradigm affords increased translational validity regarding investigations of alcohol and caffeine co-consumption and may be useful in identifying the neurobiological mechanisms concerning co-consumption of such substances.

Detección de trayectorias de espermatozoides humanos mediante técnicas de procesamiento de video / Detection of human sperm tracks using video processing techniques

Resumen: El análisis de motilidad espermática es muy importante para la evaluación de fertilidad humana. A menudo este análisis se lleva a cabo de forma manual, pero puede ser susceptible a errores inherentes a la naturaleza del procedimiento. Además de conllevar largos periodos de tiempo, los resultados son subjetivos y carentes de repetitividad. Con el fin de mejorar esto, presentamos un algoritmo semi-automático que rastree de manera precisa el desplazamiento de los espermatozoides. La metodología implementada se basó en la aplicación de modelos gaussianos adaptativos para detectar los espermatozoides en movimiento y segmentarlos a lo largo de los fotogramas de un video, posteriormente fueron aplicadas operaciones morfológicas y análisis de componentes conectados para reducir ruido en la imagen y calcular los centroides respectivamente. Luego, el algoritmo de Munkres y el filtro de Kalman fueron utilizados con el propósito de asignar centroides a las trayectorias. Finalmente, las trayectorias son visualizadas en pantalla. Los resultados evidencian un 90.91% de precision con respecto al análisis manual por parte de un experto. La herramienta tiene como único objetivo detectar el movimiento y trazar el desplazamiento de los espermatozoides en vídeo para muestras espermáticas humanas. Por otra parte, permite a los expertos en andrología llevar a cabo un análisis más exacto de las características individuales de los espermaozoides, teniendo así un soporte tecnológico a bajo costo, preciso y con repetitividad en los resultados que les permita emitir un diagnóstico más acertado. Por lo tanto, este método puede ayudar a especialistas a reducir periodos de tiempo y realizar un análisis más objetivo de motilidad espermática. De esta manera, el diagnóstico de fertilidad será más confiable.

Abstract: Sperm motility analysis is very important for human fertility assessment. It is often carried on manually, but this could be susceptible to mistakes due to the nature of procedure. In addition to being time-consuming, results are merely subjective and non-repeatable. In order to overcome this, we present a semi-automated algorithm that tracks accurately the sperm movements. Adaptive Gaussian models are implemented for detecting moving spermatozoa and segment them throughout video frames. Morphological operators and connected-components labeling are applied to reduce noise and calculate centroids, respectively. Then, the Munkres algorithm along with the Kalman filter are used for the purpose of assigning centroids to tracks. Finally, tracks are displayed on screen. Outcomes show a 90.91 % of accuracy regarding to manual analysis. This algorithm aims only to detect spermatozoa movement and trace its displacement in video for human sperm samples. Moreover, it allows andrology experts to perform a more exact analysis of the individual characteristics of spermatozoa, having so a low cost, accurate and repetitive technological support that will allow them to emit more precise diagnosis. Thus, this method will help specialists to reduce time periods and make more objective analysis of sperm motility. In this way, fertility diagnosis will be more reliable.

Integrated capture, transport, and magneto-mechanical resonant sensing of superparamagnetic microbeads using magnetic domain walls.

An integrated platform for the capture, transport, and detection of individual superparamagnetic microbeads is described for lab-on-a-chip biomedical applications. Magnetic domain walls in magnetic tracks have previously been shown to be capable of capturing and transporting individual beads through a fluid at high speeds. Here it is shown that the strong magnetostatic interaction between a bead and a domain wall leads to a distinct magneto-mechanical resonance that reflects the susceptibility and hydrodynamic size of the trapped bead. Numerical and analytical modeling is used to quantitatively explain this resonance, and the magneto-mechanical resonant response under sinusoidal drive is experimentally characterized both optically and electrically. The observed bead resonance presents a new mechanism for microbead sensing and metrology. The dual functionality of domain walls as both bead carriers and sensors is a promising platform for the development of lab-on-a-bead technologies.