Using partition designs to enhance purification process understanding

Characterization of purification processes by identifying significant input parameters and establishing predictive models is vital to developing robust processes. Current experimental design approaches restrict analysis to one process step at a time, which can severely limit the ability to identify interactions between process steps. This can be overcome by the use of partition designs which can model multiple, sequential process steps simultaneously. This paper presents the application of partition designs to a monoclonal antibody purification process. Three sequential purification steps were modeled using both traditional experimental designs and partition designs and the results compared as a proof of concept study. The partition and traditional design approaches identified the same input parameters within each process step that significantly affected the product quality output examined. The partition design also identified significant interactions between input parameters across process steps that could not be uncovered by the traditional approach. Biotechnol. Bioeng. 2010;107: 814–824. © 2010 Wiley Periodicals, Inc.     

Flexible Kernel Memory

This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces.     

Sleep-Effects on Implicit and Explicit Memory in Repeated Visual Search

In repeated visual search tasks, facilitation of reaction times (RTs) due to repetition of the spatial arrangement of items occurs independently of RT facilitation due to improvements in general task performance. Whereas the latter represents typical procedural learning, the former is a kind of implicit memory that depends on the medial temporal lobe (MTL) memory system and is impaired in patients with amnesia. A third type of memory that develops during visual search is the observers’ explicit knowledge of repeated displays. Here, we used a visual search task to investigate whether procedural memory, implicit contextual cueing, and explicit knowledge of repeated configurations, which all arise independently from the same set of stimuli, are influenced by sleep. Observers participated in two experimental sessions, separated by either a nap or a controlled rest period. In each of the two sessions, they performed a visual search task in combination with an explicit recognition task. We found that (1) across sessions, MTL-independent procedural learning was more pronounced for the nap than rest group. This confirms earlier findings, albeit from different motor and perceptual tasks, showing that procedural memory can benefit from sleep. (2) Likewise, the sleep group compared with the rest group showed enhanced context-dependent configural learning in the second session. This is a novel finding, indicating that the MTL-dependent, implicit memory underlying contextual cueing is also sleep-dependent. (3) By contrast, sleep and wake groups displayed equivalent improvements in explicit recognition memory in the second session. Overall, the current study shows that sleep affects MTL-dependent as well as MTL-independent memory, but it affects different, albeit simultaneously acquired, forms of MTL-dependent memory differentially.     

Cognitive Behavioral Performance of Untreated Depressed Patients with Mild Depressive Symptoms

This study evaluated the working memory performance of 18 patients experiencing their first onset of mild depression without treatment and 18 healthy matched controls. The results demonstrated that working memory impairment in patients with mild depression occurred when memorizing the position of a picture but not when memorizing the pictures themselves. There was no significant difference between the two groups in the emotional impact on the working memory, indicating that the attenuation of spatial working memory was not affected by negative emotion; however, cognitive control selectively affected spatial working memory. In addition, the accuracy of spatial working memory in the depressed patients was not significantly reduced, but the reaction time was significantly extended compared with the healthy controls. This finding indicated that there was no damage to memory encoding and function maintenance in the patients but rather only impaired memory retrieval, suggesting that the extent of damage to the working memory system and cognitive control abilities was associated with the corresponding depressive symptoms. The development of mild to severe depressive symptoms may be accompanied by spatial working memory damage from the impaired memory retrieval function extending to memory encoding and memory retention impairments. In addition, the impaired cognitive control began with an inadequate capacity to automatically process internal negative emotions and further extended to impairment of the ability to regulate and suppress external emotions. The results of the mood-congruent study showed that the memory of patients with mild symptoms of depression was associated with a mood-congruent memory effect, demonstrating that mood-congruent memory was a typical feature of depression, regardless of the severity of depression. This study provided important information for understanding the development of cognitive dysfunction.     

Olfactory memory capacity of the cricket Gryllus bimaculatus

Olfactory learning in insects is a useful model for studying neural mechanisms underlying learning and memory, but memory storage capacity for olfactory learning in insects has not been studied. We investigate whether crickets are capable of simultaneously memorizing seven odour pairs. Fourteen odours were grouped into seven A/B pairs, and crickets in one group were trained to associate A odours with water reward and B odours with saline punishment for all the seven pairs. Crickets in another group were trained with the opposite stimulus arrangement. Crickets in all the groups exhibited significantly greater preference for the odours associated with water reward for all the seven odour pairs. We conclude that crickets are capable of memorizing seven odour pairs at the same time.     

Conditional inversion to estimate parameters from eddy-flux observations

Aims Data assimilation is a useful tool to extract information from large datasets of the net ecosystem exchange (NEE) of CO₂ obtained by eddy-flux measurements. However, the number of parameters in ecosystem models that can be constrained by eddy-flux data is limited by conventional inverse analysis that estimates parameter values based on one-time inversion. This study aimed to improve data assimilation to increase the number of constrained parameters.Methods In this study, we developed conditional Bayesian inversion to maximize the number of parameters to be constrained by NEE data in several steps. In each step, we conducted a Bayesian inversion to constrain parameters. The maximum likelihood estimates of the constrained parameters were then used as prior to fix parameter values in the next step of inversion. The conditional inversion was repeated until there were no more parameters that could be further constrained. We applied the conditional inversion to hourly NEE data from Harvard Forest with a physiologically based ecosystem model.Important findings Results showed that the conventional inversion method constrained 6 of 16 parameters in the model while the conditional inversion method constrained 13 parameters after six steps. The cost function that indicates mismatch between the modeled and observed data decreased with each step of conditional Bayesian inversion. The Bayesian information criterion also decreased, suggesting reduced information loss with each step of conditional Bayesian inversion. A wavelet analysis reflected that model performance under conditional Bayesian inversion was better than that under conventional inversion at multiple time scales, except for seasonal and half-yearly scales. In addition, our analysis also demonstrated that parameter convergence in a subsequent step of the conditional inversion depended on correlations with the parameters constrained in a previous step. Overall, the conditional Bayesian inversion substantially increased the number of parameters to be constrained by NEE data and can be a powerful tool to be used in data assimilation in ecology.     

Rheological properties of myometrium: experimental quantification and mathematical modeling

This work answers some questions related to detection of rheological properties of soft tissues exemplified in myometrium, stressed by external tensile force. In the first stage of the experiment the tissue samples were ciclically stressed and response loops were recorded. This test proved severe plastical deformation of samples, which is not usually being stated for living tissues. In addition to course, growth and stabilizing this deformation also energetical losses of individual hysteresis loops of the response were evaluated. In the second stage of the experiment the tissue samples were exposed to a loading force changed in step-wise manner in four steps. The sample response to each force step was processed and evaluated separately to obtain basic properties of used model. In next step, the changes in model characteristics were obtained and evaluated for each element in subsequent force steps. By reason of following easier interpretation, the quite simple visco-elastic model, defined by differential equation with analytic solution, is used. The results prove necessary to introduce in model both spring and damper constants dependent on the magnitude of the loading force and one damper with even time dependent constant. The interindividual variability of characteristic values of the model elements is surprisingly low. On the other side, they are strongly dependent on load magnitude. Complete mathematical model of uterine wall tissue is obtained by amending the principal equation by formulas describing changes in individual components of the model.     

Facilitating memory for novel characters by reducing neural repetition suppression in the left fusiform cortex

Background

The left midfusiform and adjacent regions have been implicated in processing and memorizing familiar words, yet its role in memorizing novel characters has not been well understood.

Methodology/Principal Findings

Using functional MRI, the present study examined the hypothesis that the left midfusiform is also involved in memorizing novel characters and spaced learning could enhance the memory by enhancing the left midfusiform activity during learning. Nineteen native Chinese readers were scanned while memorizing the visual form of 120 Korean characters that were novel to the subjects. Each character was repeated four times during learning. Repetition suppression was manipulated by using two different repetition schedules: massed learning and spaced learning, pseudo-randomly mixed within the same scanning session. Under the massed learning condition, the four repetitions were consecutive (with a jittered inter-repetition interval to improve the design efficiency). Under the spaced learning condition, the four repetitions were interleaved with a minimal inter-repetition lag of 6 stimuli. Spaced learning significantly improved participants'' performance during the recognition memory test administered one hour after the scan. Stronger left midfusiform and inferior temporal gyrus activities during learning (summed across four repetitions) were associated with better memory of the characters, based on both within- and cross-subjects analyses. Compared to massed learning, spaced learning significantly reduced neural repetition suppression and increased the overall activities in these regions, which were associated with better memory for novel characters.

Conclusions/Significance

These results demonstrated a strong link between cortical activity in the left midfusiform and memory for novel characters, and thus challenge the visual word form area (VWFA) hypothesis. Our results also shed light on the neural mechanisms of the spacing effect in memorizing novel characters.     

毛乌素沙地草地种植管理咨询系统的开发

 本研究初步开发了一个用于毛乌素沙地草地种植管理咨询的专家系统ASSG。这个系统将当地生态系统管理专家们的经验知识和对土壤水分动态的理论研究成果结合起来以产生对于土地利用和种植的作物种类及品种的最优管理策略和最适的植被覆盖率。本系统利用3个层次的推理过程和结构化的知识库,通过咨询过程—步步地引导用户得到最优种植管理策略。在每—层次的推理中,本系统提供给用户多重选择,根据用户的意愿进行下一步的推理。这一推理的交互作用机制为用户获得适宜的咨询结果提供了最大的便利性。本系统的主体部分山Turbo Prolog语言完成,该语言是一种用于开发专家系统的描述性语言。基于土壤水分平衡原理的最优植被覆盖率模型由C语言实现,并应用多语言编程技术将之嵌入程序主体中。系统的样本运行结果表明本系统运行便利,并能产生合理的种植管理策略。     

Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates

Synaptic plasticity is believed to underlie the formation of appropriate patterns of connectivity that stabilize stimulus-selective reverberations in the cortex. Here we present a general quantitative framework for studying the process of learning and memorizing of patterns of mean spike rates. General considerations based on the limitations of material (biological or electronic) synaptic devices show that most learning networks share the palimpsest property: old stimuli are forgotten to make room for the new ones. In order to prevent too-fast forgetting, one can introduce a stochastic mechanism for selecting only a small fraction of synapses to be changed upon the presentation of a stimulus. Such a mechanism can be easily implemented by exploiting the noisy fluctuations in the pre- and postsynaptic activities to be encoded. The spike-driven synaptic dynamics described here can implement such a selection mechanism to achieve slow learning, which is shown to maximize the performance of the network as an associative memory.     

Sequential Push-Pull Pumping Mechanism for Washing and Evacuation of an Immunoassay Reaction Chamber on a Microfluidic CD Platform

A centrifugal compact disc (CD) microfluidic platform with reservoirs, micro-channels, and valves can be employed for implementing a complete immunoassay. Detection or biosensor chambers are either coated for immuno-interaction or a biosensor chip is inserted in them. On microfluidic CDs featuring such multi-step chemical/biological processes, the biosensor chamber must be repeatedly filled with fluids such as enzymes solutions, buffers, and washing solutions. After each filling step, the biosensor chamber needs to be evacuated by a passive siphoning process to prepare it for the next step in the assay. However, rotational speed dependency and limited space on a CD are two big obstacles to performing such repetitive filling and siphoning steps. In this work, a unique thermo-pneumatic (TP) Push-Pull pumping method is employed to provide a superior alternative biosensor chamber filling and evacuation technique. The proposed technique is demonstrated on two CD designs. The first design features a simple two-step microfluidic process to demonstrate the evacuation technique, while the second design shows the filling and evacuation technique with an example sequence for an actual immunoassay. In addition, the performance of the filling and evacuation technique as a washing step is also evaluated quantitatively and compared to the conventional manual bench top washing method. The two designs and the performance evaluation demonstrate that the technique is simple to implement, reliable, easy to control, and allows for repeated push-pulls and thus filling and emptying of the biosensor chamber. Furthermore, by addressing the issue of rotational speed dependency and limited space concerns in implementing repetitive filling and evacuation steps, this newly introduced technique increases the flexibility of the microfluidic CD platform to perform multi-step biological and chemical processes.     

Blood pressure variations real-time reflect the conditioned fear learning and memory

The conditioned fear learning and memory occurs when a neutral conditioned stimulus (CS) is paired with an aversive unconditioned stimulus (US). This process is critically dependent on the amygdala and inevitably involves blood pressure (BP) alterations. We hypothesized that BP variations could instantaneously reveal individual steps during conditioned fear learning and memory. An implanted telemetric probe was used to monitor the BP real-time in rats during training and testing sessions of the fear-potentiated startle. Our results showed that (i) the conditioned fear learning during the training sessions was reflected by light (CS)-induced rapid BP elevations and by electric shock (US)-evoked sympathetic tone elevations; (ii) these two BP-related parameters were not only negatively correlated with each other but also coupled to each other in the training session trials; (iii) both parameters closely predicted the performance of fear-potentiated startle on the next day; and (iv) although local blocking of one of the two fear-conditioned pathways in the training session partially inhibited fear learning, the fear memory retrieval still used both pathways. Altogether, real-time blood pressure variations faithfully revealed the critical steps involved in conditioned fear learning and memory, and our results supported a coupling between the cued learning and the post-shock calmness.     

Slow Potentials in the Rhinal Region of the Cat Brain Cortex Related to Visual Recognition Memory

We examined correlation between the development of slow potentials in the rhinal cortical region of cats and results of behavioral testing of visual recognition memory of these animals in the “delayed nonmatching-to-sample” (DNMS) selection version. Among different types of cognitive memory, the recognition memory occupies a special position because the process of taking off (retrieval) of a memory trace from the “stores” can be completely and effectively controlled by the experimenter (this process is initiated only after repetitive presentation of a stimulus identical to that whose trace should be subjected to retrieval or after presentation of an absolutely new stimulus whose trace had not been formed earlier). Recording of the field potentials was performed from the surface of the rhinal cortex using stereotaxically implanted mono- or bipolar Ag-AgCl electrodes after the experimental animals reached a sufficiently high level of successful performance of the test for recognition memory. Analysis of relations between negative slow potentials in the rhinal cortex and the correctness of performance (according to Spearman’s nonparametric test) demonstrated the existence of significant correlation between the electrophysiological and behavioral indices of visual recognition memory only within a late portion (final 10 sec but not initial 10 ones) of the retention interval for memorizing the trace of single presentation of a visual stimulus. The data obtained are interpreted as a confirmation of the existence of correlation between generation of negative slow potentials in the rhinal cortical region and the process of retrieval of the sample from the visual memory stores.     

Prebiotic thermal polymerization of crystals of amino acids via the diketopiperazine reaction

In this work, we continue our studies on the thermal prebiotic oligomerization of amino acids. The next step is to consider all four types of electromagnetic interactions that our model may admit. In addition, only the polymerization of amino acids via the formation of diketopiperazine, which arises from the cyclodehydration of two amino acids, will be considered. By assuming that only one residue group of two will predominate in the diketopiperazine molecule, it is possible to reduce the three-body problem to a simpler situation with the two objects that we have already solved.     

The chronotron: a neuron that learns to fire temporally precise spike patterns

In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons), one that provides high memory capacity (E-learning), and one that has a higher biological plausibility (I-learning). With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm.     

Process characterization strategy for a precipitation step for host cell protein reduction

Process characterization using QbD approaches has rarely been described for precipitation steps used for impurity removal in biopharmaceutical processes. We propose a two-step approach for process characterization in which the first step focuses on product quality and the second focuses on process performance. This approach provides an efficient, streamlined strategy for the characterization of precipitation steps under the Quality by Design paradigm. This strategy is demonstrated by a case study for the characterization of a precipitation using sodium caprylate to reduce host cell proteins (HCP) during a monoclonal antibody purification process. Process parameters were methodically selected through a risk assessment based on prior development data and scientific knowledge described in the literature. The characterization studies used two multivariate blocks to decouple and distinguish the impact of product quality (e.g., measured HCP of the recovered product from the precipitation) and process performance (e.g., step yield). Robustness of the precipitation step was further demonstrated through linkage studies across the overall purification process. HCP levels could be robustly reduced to ≤100 ppm in the drug substance when the precipitation step operated within an operation space of ≤1% (m/v) sodium caprylate, pH 5.0–6.0, and filter flux ≤300 L/m²-hr for a load HCP concentration up to 19,000 ppm. This two-step approach for characterization of precipitation steps has several advantages, including tailoring of the experimental design and scale-down model to the intended purpose for each step, use of a manageable number of experiments without compromising scientific understanding, and limited time and material consumption.     

The neurobiology of the human memory

Memory can be defined as the ability to acquire, process, store, and retrieve information. Memory is indispensable for learning, adaptation, and survival of every living organism. In humans, the remembering process has acquired great flexibility and complexity, reaching close links with other mental functions, such as thinking and emotions. Changes in synaptic connectivity and interactions among multiple neural networks provide the neurobiological substrates for memory encoding, retention, and consolidation. Memory may be categorized as short-term and long-term memory (according to the storage temporal duration), as implicit and explicit memory (with respect to the consciousness of remembering), as declarative (knowing that [fact]) and procedural (knowing how [skill]) memory, or as sensory (echoic, iconic and haptil), semantic, and episodic memory (according to the various remembering domains). Significant advances have been obtained in understanding memory neurobiology, but much remains to be learned in its cognitive, psychological, and phenomenological aspects.     

Estimating diurnal to annual ecosystem parameters by synthesis of a carbon flux model with eddy covariance net ecosystem exchange observations

We performed a synthetic analysis of Harvard Forest net ecosystem exchange of CO₂ (NEE) time series and a simple ecosystem carbon flux model, the simplified Photosynthesis and Evapo‐Transpiration model (SIPNET). SIPNET runs at a half‐daily time step, and has two vegetation carbon pools, a single aggregated soil carbon pool, and a simple soil moisture sub‐model. We used a stochastic Bayesian parameter estimation technique that provided posterior distributions of the model parameters, conditioned on the observed fluxes and the model equations. In this analysis, we estimated the values of all quantities that govern model behavior, including both rate constants and initial conditions for carbon pools. The purpose of this analysis was not to calibrate the model to make predictions about future fluxes but rather to understand how much information about process controls can be derived directly from the NEE observations. A wavelet decomposition enabled us to assess model performance at multiple time scales from diurnal to decadal. The model parameters are most highly constrained by eddy flux data at daily to seasonal time scales, suggesting that this approach is not useful for calculating annual integrals. However, the ability of the model to fit both the diurnal and seasonal variability patterns in the data simultaneously, using the same parameter set, indicates the effectiveness of this parameter estimation method. Our results quantify the extent to which the eddy covariance data contain information about the ecosystem process parameters represented in the model, and suggest several next steps in model development and observations for improved synthesis of models with flux observations.     

Biodegradation of N-Methylmorpholine-N-oxide

N-Methylmorpholine-N-oxide (NMMO) is capable of dissolving cellulose without any further addition of chemicals. The solution can be used to produce cellulosic staple fibres by pressing it through spinning jets into an aqueous spinning bath. Because of results from conventional biodegradation tests using non-adapted activated sludge, the solvent is generally considered being persistent. The object of the described work was to show, whether and how activated sludge can be adapted to N-methylmorpholine-N-oxide and whether it is possible to purify NMMO-containing wastewaters in conventional wastewater treatment plants. The experiments showed that the sludge can be adapted within about 15–20 days. Adapted sludge can degrade the substance itself and its most important metabolites to concentrations below their detection levels and retain this ability even during limited periods without solvent being present in the wastewater. The main requirement for a successful adaptation is a high sludge age. The degradation takes place in several steps. First, NMMO is reduced to N-methylmorpholine. The next step is a demethylation of N-methylmorpholine to morpholine. This step is crucial for the adaptation process. Once morpholine has been formed, the adaptation proceeds very quickly until none of the substances in question can be detected any longer. So the next step must be the cleavage of the morpholine ring structure.