A Generalized Design for Affinity Chromatography Columns

In affinity chromatography, an adsorbent with a high selectivity for a target solute is used to isolate the target molecule from other impurities. With sufficient selectivity, the target molecule can be isolated in a highly purified and concentrated state. Common applications of affinity chromatography include Protein A chromatography for antibody purification and Immobilized Metal Affinity Chromatography (IMAC) for protein purification. The well-known design method based on constant-pattern mass transfer zone analysis does not apply to small feed batches, which are insufficient to form constant-pattern frontal waves. Other literature design methods rely on simulation or experimental trials that can be time-consuming and costly. In addition, it can be difficult to optimize the process to achieve the desired purity, yield, and throughput. In this study, a convenient graphical design method based on intrinsic adsorption parameters (void fractions, adsorption isotherm, and solute diffusivity), mass transfer parameters, and dimensionless groups is developed for affinity chromatography systems with Langmuir isotherms. Only a small number of experiments are needed to obtain these parameters. The method is tested with literature data for Protein A chromatography for antibody purification, and close agreement is obtained. Graphs can be used to examine the effects of material properties, capture yield, and throughput on column utilization. In addition, it can easily adjust to meet various design requirements and can take into account variations in the intrinsic parameters. Various sorbents can be evaluated for cost effectiveness based on the intrinsic parameters, making this method applicable to a broad range of affinity chromatography systems

Preserving User Preferences in Document-Category Management: An Ontology-based Evolution Approach

Preserving the user’s preference in document-category management is essential because it affects his/her search efficiency, cognitive processing load, and satisfaction. Prior research has investigated automated document category evolution by using lexicon-based documentcategory evolution techniques which take into account the document categories previously created by the user. However, comparing documents at the lexical level cannot solve word mismatch or ambiguity problems effectively. To address such problems inherent to the lexicon-based approach, we propose an ONtology-based Category Evolution (ONCE) technique, which uses an appropriate ontology to support document-category evolution at the conceptual level rather than at the lexical level. Specifically, we develop an Ontology Enrichment (OE) technique for automatic leaning of concept descriptors in the adopted ontology. We empirically evaluate the effectiveness of the proposed ONCE technique, using a lexicon-based document-category evolution technique (i.e., CE2) and the hierarchical agglomerative clustering (HAC) technique for benchmark purposes. According to our empirical results, ONCE appears more effective than CE2 and HAC, and achieves higher clustering recall and precision

Supporting Acute Appendicitis Diagnosis: A Pre-Clustering-Based Classification Technique

Service quality and cost containment represent two critical challenges in healthcare management. Toward that end, acute appendicitis, a common surgical condition, is important and requires timely, accurate diagnosis. The diverse and atypical symptoms make such diagnoses difficult, thus resulting in increased morbidity and negative appendectomy. While prior research has recognized the use of classification analysis to support acute appendicitis diagnosis, the skewed distribution of the cases pertaining to positive or negative acute appendicitis has significantly constrained the effectiveness of the existing classification techniques. In this study, we develop a pre-clustering-based classification (PCC) technique to address the skewed distribution problem common to acute appendicitis diagnosis. We empirically evaluate the proposed PCC technique with 574 clinical cases of positive and negative acute appendicitis obtained from a tertiary medical center in Taiwan. Our evaluation includes tradition support vector machine, a prevalent resampling classification technique, Alvarado scoring system, and a multi-classifier committee for performance benchmark purposes. Our results show the PCC technique more effective and less biased than the benchmark techniques, without favoring the positive or negative class

A Temporal Frequent Itemset-Based Clustering Approach For Discovering Event Episodes From News Sequence

When performing environmental scanning, organizations typically deal with a numerous of events and topics about their core business, relevant technique standards, competitors, and market, where each event or topic to monitor or track generally is associated with many news documents. To reduce information overload and information fatigues when monitoring or tracking such events, it is essential to develop an effective event episode discovery mechanism for organizing all news documents pertaining to an event of interest. In this study, we propose the time-adjoining frequent itemset-based event-episode discovery (TAFIED) technique. Based on the frequent itemset-based hierarchical clustering (FIHC) approach, our proposed TAFIED further considers the temporal characteristic of news articles, including the burst, novelty, and temporal proximity of features in an event episode, when discovering event episodes from the sequence of news articles pertaining to a specific event. Using the traditional feature-based HAC, HAC with a time-decaying function (HAC+TD), and FIHC techniques as performance benchmarks, our empirical evaluation results suggest that the proposed TAFIED technique outperforms all evaluation benchmarks in cluster recall and cluster precision

Effects of Noise Electrical Stimulation on Proprioception, Force Control, and Corticomuscular Functional Connectivity

Sensory afferent inputs play an important role in neuromuscular functions. Subsensory level noise electrical stimulation enhances the sensitivity of peripheral sensory system and improves lower extremity motor function. The current study aimed to investigate the immediate effects of noise electrical stimulation on proprioceptive senses and grip force control, and whether there are associated neural activities in the central nervous system. Fourteen healthy adults participated in 2 experiments on 2 different days. In day 1, participants performed grip force and joint proprioceptive tasks with and without (sham) noise electrical stimulation. In day 2, participants performed grip force steady hold task before and after 30-min noise electrical stimulation. Noise stimulation was applied with surface electrodes secured along the course of the median nerve and proximal to the coronoid fossa EEG power spectrum density of bilateral sensorimotor cortex and coherence between EEG and finger flexor EMG were calculated and compared. Wilcoxon Signed-Rank Tests were used to compare the differences of proprioception, force control, EEG power spectrum density and EEG-EMG coherence between noise electrical stimulation and sham conditions. The significance level (alpha) was set at 0.05. Our study found that noise stimulation with optimal intensity could improve both force and joint proprioceptive senses. Furthermore, individuals with higher gamma coherence showed better force proprioceptive sense improvement with 30-min noise electrical stimulation. These observations indicate the potential clinical benefits of noise stimulation on individuals with impaired proprioceptive senses and the characteristics of individuals who might benefit from noise stimulation

Aberrant KDM5B expression promotes aggressive breast cancer through MALAT1 overexpression and downregulation of hsa-miR-448

Relative expression of KDM5B, MALAT1, SNAIL, Vimentin and miR 448 normalized against GAPDH in MCF10A WT, MCF10A OE, MDA-MB-231 WT and MDA-MB-231 KD cells. Data are representative of 3 independent experiments and analyzed by student’s t-test. All data are shown as mean ± SEM. WT, wild type; OE, KDM5B overexpressed; KD, knockdown using shKDM5B clone II. (DOCX 519 kb