The Role of Estrogen in Anxiety-Like Behavior and Memory of Middle-Aged Female Rats.

Aging in women is associated with low estrogen, but also with cognitive decline and affective disorders. Whether low estrogen is causally responsible for these behavioral symptoms is not clear. Thus, we aimed to examine the role of estradiol in anxiety-like behavior and memory in rats at middle age. Twelve-month old female rats underwent ovariectomy (OVX) or were treated with 1 mg/kg of letrozole-an aromatase inhibitor. In half of the OVX females, 10 µg/kg of 17ß-estradiol was supplemented daily for 4 weeks. Vehicle-treated sham-operated and OVX females served as controls. For behavioral assessment open field, elevated plus maze and novel object recognition tests were performed. Interaction between ovarian condition and additional treatment had the main effect on anxiety-like behavior of rats in the open field test. In comparison to control females, OVX females entered less frequently into the center zone of the open field (p < 0.01) and showed lower novel object discrimination (p = 0.05). However, estradiol-supplemented OVX rats had higher number of center-zone entries (p < 0.01), spent more time in the center zone (p < 0.05), and showed lower thigmotaxis (p < 0.01) when compared to OVX group. None of the hormonal manipulations affected anxiety-like behavior in the elevated plus maze test significantly, but a mild effect of interaction between ovarian condition and treatment was shown (p = 0.05). In conclusion, ovariectomy had slight negative effect on open-field ambulation and short-term recognition memory in middle-aged rats. In addition, a test-specific anxiolytic effect of estradiol supplementation was found. In contrast, letrozole treatment neither affected anxiety-like behavior nor memory.

A new set up for multi-analyte sensing: at-line bio-process monitoring.

A multi-analyte sensing device is described, for simultaneous at-line monitoring of glucose, ethanol, pO2-value and cell density. It consists of a dual biosensor, a modified microscope and a fiber optical pO2-sensor that are integrated into a flow analysis (FA) system. The biosensor is based on a conventional thin layer flow-through cell equipped with a gold (Au) dual electrode (serial configuration). The biosensors with no cross-talking were produced by modifying the electrochemical transducers. Each Au surface was initially modified by self-assembled monolayer (SAM) of cysteamine. Alcohol oxidase (AOx) and pyranose oxidase (PyOx) were immobilized each onto a gold surface by means of PAMAM (polyamidoamine) dendrimer via glutaraldehyde cross-linking. The responses for glucose and ethanol were linear up to 0.5 mM. The operational stability of the biosensors was very promising, after 11 h continuous operation, only 6.0% of the initial activity was lost. The potential of the described biosensor was demonstrated by parallel determination of ethanol and glucose in yeast fermentation process. Simultaneously the cell density of the culture was monitored with an in situ microscope (ISM), which was integrated into the FA system. Both the used in situ microscope and the image processing algorithm used for the analysis of the acquired image data are described. Furthermore the pO2-value was monitored using a fiber optical sensor, which was embedded in a flow cell. The multi-sensor device allows the at-line monitoring of several process values without the need for further sampling or time consuming offline measurements.

Offline glucose biomonitoring in yeast culture by polyamidoamine/cysteamine-modified gold electrodes.

This article deals with the use of pyranose oxidase (PyOx) and glucose oxidase (GOx) enzymes in amperometric biosensor design and their application in monitoring fermentation processes with the combination of flow injection analysis (FIA). The amperometric studies were carried out at -0.7 V by following the oxygen consumption due to the enzymatic reactions for both batch and FIA modes. Optimization studies (enzyme amounts and pH) and analytical parameters such as linearity, repeatability, effect of interference, storage, and operational stabilities have been studied. Under optimized conditions, for the PyOx-based biosensor, linear graph was obtained from 0.025 to 0.5 mM glucose in phosphate buffer (50 mM) at pH 7.0 with the equation of y = 3.358x + 0.028 and R(2) = 0.998. Linearity was found to be 0.01-1.0 mM in citrate buffer (50 mM and pH 4.0) with the equation of y = 1.539x + 0.181 and R(2) = 0.992 for the GOx biosensor. Finally, these biosensor configurations were further evaluated in a conventional flow injection system. Results from batch experiments provide a guide to design sensitive, stable, and interference-free biosensors for FIA mode. Biosensor stability, dynamic range, and repeatability were also studied in FIA conditions, and the applicability for the determination of glucose in fermentation medium could be successfully demonstrated. The FIA-combined glucose biosensor was used for the offline monitoring of yeast fermentation. The obtained results correlated well with HPLC measurements.

In-situ imaging sensors for bioprocess monitoring: state of the art.

Over the last two decades, more and more applications of sophisticated sensor technology have been described in the literature on upstreaming and downstreaming for biotechnological processes (Middendorf et al. J Biotechnol 31:395-403, 1993; Lausch et al. J Chromatogr A 654:190-195, 1993; Scheper et al. Ann NY Acad Sci 506:431-445, 1987), in order to improve the quality and stability of these processes. Generally, biotechnological processes consist of complex three-phase systems--the cells (solid phase) are suspended in medium (liquid phase) and will be streamed by a gas phase. The chemical analysis of such processes has to observe all three phases. Furthermore, the bioanalytical processes used must monitor physical process values (e.g. temperature, shear force), chemical process values (e.g. pH), and biological process values (metabolic state of cell, morphology). In particular, for monitoring and estimation of relevant biological process variables, image-based inline sensors are used increasingly. Of special interest are sensors which can be installed in a bioreactor as sensor probes (e.g. pH probe). The cultivation medium is directly monitored in the process without any need for withdrawal of samples or bypassing. Important variables for the control of such processes are cell count, cell-size distribution (CSD), and the morphology of cells (Höpfner et al. Bioprocess Biosyst Eng 33:247-256, 2010). A major impetus for the development of these image-based techniques is the process analytical technology (PAT) initiative of the US Food and Drug Administration (FDA) (Scheper et al. Anal Chim Acta 163:111-118, 1984; Reardon and Scheper 1995; Schügerl et al. Trends Biotechnol 4:11-15, 1986). This contribution gives an overview of non-invasive, image-based, in-situ systems and their applications. The main focus is directed at the wide application area of in-situ microscopes. These inline image analysis systems enable the determination of indirect and direct cell variables in real time without sampling, but also have application potential in crystallization, material analysis, polymer research, and the petrochemical industry.

Development of a flow-through microscopic multitesting system for parallel monitoring of cell samples in biotechnological cultivation processes.

The automated monitoring of cell variables in cultivation processes is a key technology in modern bioscience. In this article an innovative analytical tool for monitoring of cell densities in shaking-flask cultivations--consisting of a flow-through microscope with an automated image analysis software integrated in a FIA sampling system--is presented. This atline multitesting system was optimized by varying the height of the microscopes sampling zone. A calibration of the system was performed by correlating the FIA result peaks to known concentrations of Baker's yeast. It was successfully applied in cell density monitoring of cultivation processes of Saccharomyces cerevisiae with a good correlation with offline methods, and further used to monitor 3 parallel cultivations. This methodology was successfully transferred to Bacillus megaterium cultures and applied to measure the cell densities of parallel cultivation setups of B. megaterium and S. cerevisiae.

On-line infrared spectroscopy for bioprocess monitoring.

One of the major aims of bioprocess engineering is the real-time monitoring of important process variables. This is the basis of precise process control and is essential for high productivity as well as the exact documentation of the overall production process. Infrared spectroscopy is a powerful analytical technique to analyze a wide variety of organic compounds. Thus, infrared sensors are ideal instruments for bioprocess monitoring. The sensors are non-invasive, have no time delay due to sensor response times, and have no influence on the bioprocess itself. No sampling is necessary, and several components can be analyzed simultaneously. In general, the direct monitoring of substrates, products, metabolites, as well as the biomass itself is possible. In this review article, insights are provided into the different applications of infrared spectroscopy for bioprocess monitoring and the complex data interpretation. Different analytical techniques are presented as well as example applications in different areas.

Alcohol biosensing by polyamidoamine (PAMAM)/cysteamine/alcohol oxidase-modified gold electrode.

A highly stable and sensitive amperometric alcohol biosensor was developed by immobilizing alcohol oxidase (AOX) through Polyamidoamine (PAMAM) dendrimers on a cysteamine-modified gold electrode surface. Ethanol determination is based on the consumption of dissolved oxygen content due to the enzymatic reaction. The decrease in oxygen level was monitored at -0.7 V vs. Ag/AgCl and correlated with ethanol concentration. Optimization of variables affecting the system was performed. The optimized ethanol biosensor showed a wide linearity from 0.025 to 1.0 mM with 100 s response time and detection limit of (LOD) 0.016 mM. In the characterization studies, besides linearity some parameters such as operational and storage stability, reproducibility, repeatability, and substrate specificity were studied in detail. Stability studies showed a good preservation of the bioanalytical properties of the sensor, 67% of its initial sensitivity was kept after 1 month storage at 4 degrees C. The analytical characteristics of the system were also evaluated for alcohol determination in flow injection analysis (FIA) mode. Finally, proposed biosensor was applied for ethanol analysis in various alcoholic beverage as well as offline monitoring of alcohol production through the yeast cultivation.

A review of non-invasive optical-based image analysis systems for continuous bioprocess monitoring.

To observe and control cultivation processes, optical sensors are used increasingly. Important variables for controlling such processes are cell count, cell size distribution and the morphology of cells. Among turbidity measurement methods, imaging procedures are applied for determining these process values. A disadvantage of most previously developed imaging procedures is that they are only available offline, which requires sampling. On the other hand, available imaging inline probes can only deliver a limited number of process values so far. This contribution gives an overview of optical procedures for the inline determination of cell count, cell size distribution and other variables. In particular, by in situ microscopy, an imaging procedure will be described, which allows the determination of direct and non-direct cell variables in real time without sampling.