Evaluating Two Automatic Methods for Classifying Information Technology Concepts

How are IT concepts related to each other, what is the best way to automatically detect these relationships, and how do such automatic methods compare with traditional methods? We address each of these questions by developing and evaluating two statistical natural language processing methods: co-occurrence and Kullback-Liebler (KL) divergence when used in combination with hierarchical clustering. The results of these automatic methods were then compared to a ground truth classification scheme using statistical methods as well as a survey of IT experts. Co-occurrence outperformed KL divergence according to both the statistical and survey results. Further, co-occurrence had some benefits in comparison to the ground truth, and was preferred by some of the experts included in the survey. The main contribution of this research is the demonstration that automatic methods can be used effectively to classify IT concepts, and that success does not always depend on the complexity of the methods

Building an IT Taxonomy with Co-occurrence Analysis, Hierarchical Clustering, and Multidimensional Scaling

Different information technologies (ITs) are related in complex ways. How can the relationships among a large number of ITs be described and analyzed in a representative, dynamic, and scalable way? In this study, we employed co-occurrence analysis to explore the relationships among 50 information technologies discussed in six magazines over ten years (1998-2007). Using hierarchical clustering and multidimensional scaling, we have found that the similarities of the technologies can be depicted in hierarchies and two-dimensional plots, and that similar technologies can be classified into meaningful categories. The results imply reasonable validity of our approach for understanding technology relationships and building an IT taxonomy. The methodology that we offer not only helps IT practitioners and researchers make sense of numerous technologies in the iField but also bridges two related but thus far largely separate research streams in iSchools - information management and IT management

Understanding IT Innovations Through Computational Analysis of Discourse

How do Information Technology (IT) innovation concepts emerge, coexist, evolve, and relate to each other? To address this question, we theorize that innovation concepts are interrelated in an idea network, where they can be likened to species in a competitive and symbiotic resource space. Communities of organizations and people interested in the innovations produce discourse that both reflects and enables the flows of attention among innovations. From this ecological perspective, we apply discourse analysis to innovation research and propose computational approach to scale up the analysis. Specifically, we employed Kullback-Leibler divergence to compare the linguistic patterns of 48 IT innovations reported in InformationWeek and Computerworld over a decade. Using multidimensional scaling, we found that similar innovations demonstrated similar discourses. The results demonstrate the validity, scalability, and utility of computational discourse analysis for practitioners and scholars to understand the socio-technical dynamics in the IT innovation ecosystem

Biodistribution and pharmacokinetics of 188Re-liposomes and their comparative therapeutic efficacy with 5-fluorouracil in C26 colonic peritoneal carcinomatosis mice

Chia-Che Tsai1, Chih-Hsien Chang1, Liang-Cheng Chen1, Ya-Jen Chang1, Keng-Li Lan2, Yu-Hsien Wu1, Chin-Wei Hsu1, I-Hsiang Liu1, Chung-Li Ho1, Wan-Chi Lee1, Hsiao-Chiang Ni1, Tsui-Jung Chang1, Gann Ting3, Te-Wei Lee11Institute of Nuclear Energy Research, Taoyuan, 2Cancer Center, Taipei Veterans General Hospital, Taipei, 3National Health Research Institutes, Taipei, Taiwan, ROCBackground: Nanoliposomes are designed as carriers capable of packaging drugs through passive targeting tumor sites by enhanced permeability and retention (EPR) effects. In the present study the biodistribution, pharmacokinetics, micro single-photon emission computed tomography (micro-SPECT/CT) image, dosimetry, and therapeutic efficacy of 188Re-labeled nanoliposomes (188Re-liposomes) in a C26 colonic peritoneal carcinomatosis mouse model were evaluated.Methods: Colon carcinoma peritoneal metastatic BALB/c mice were intravenously administered 188Re-liposomes. Biodistribution and micro-SPECT/CT imaging were performed to determine the drug profile and targeting efficiency of 188Re-liposomes. Pharmacokinetics study was described by a noncompartmental model. The OLINDA|EXM® computer program was used for the dosimetry evaluation. For therapeutic efficacy, the survival, tumor, and ascites inhibition of mice after treatment with 188Re-liposomes and 5-fluorouracil (5-FU), respectively, were evaluated and compared.Results: In biodistribution, the highest uptake of 188Re-liposomes in tumor tissues (7.91% ± 2.02% of the injected dose per gram of tissue [%ID/g]) and a high tumor to muscle ratio (25.8 ± 6.1) were observed at 24 hours after intravenous administration. The pharmacokinetics of 188Re-liposomes showed high circulation time and high bioavailability (mean residence time [MRT] = 19.2 hours, area under the curve [AUC] = 820.4%ID/g*h). Micro-SPECT/CT imaging of 188Re-liposomes showed a high uptake and targeting in ascites, liver, spleen, and tumor. The results were correlated with images from autoradiography and biodistribution data. Dosimetry study revealed that the 188Re-liposomes did not cause high absorbed doses in normal tissue but did in small tumors. Radiotherapeutics with 188Re-liposomes provided better survival time (increased by 34.6% of life span; P < 0.05), tumor and ascites inhibition (decreased by 63.4% and 83.3% at 7 days after treatment; P < 0.05) in mice compared with chemotherapeutics of 5-fluorouracil (5-FU).Conclusion: The use of 188Re-liposomes for passively targeted tumor therapy had greater therapeutic effect than the currently clinically applied chemotherapeutics drug 5-FU in a colonic peritoneal carcinomatosis mouse model. This result suggests that 188Re-liposomes have potential benefit and are safe in treating peritoneal carcinomatasis of colon cancer.Keywords: biodistribution, dosimetry, 5-fluorouracil, micro-SPECT/CT, 188Re-liposome

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Studying the Relationships of Information Technology Concepts

Different information technology concepts are related in complex ways. How can the relationships among multiple IT concepts be described and analyzed in a scalable way? It is a challenging research question, not only because of the complex relationships among IT concepts, but also due to lack of reliable methods. Seeking to meet the challenge, this dissertation offers a computational approach for analyzing, visualizing, and understanding the relationships among IT concepts. The dissertation contains five empirical studies. The first study employs Kullback-Leibler (KL) divergence to compare the semantic similarity of forty-seven IT concepts discussed in a trade magazine over a ten-year period. Results show that the similarity of IT concepts can be mapped in a hierarchy and similar technologies demonstrated similar discourses. The second study employs co-occurrence analysis to explore the relationships among fifty IT concepts in six magazines over ten years. Results show general patterns similar to those found in the first study, but with interesting nuances. Together, findings from the first two studies imply reasonable validity of this computational approach. The third study validates and evaluates the approach, making use of an existing thesaurus as ground truth. Results show that the co-occurrence-based IT classification outperforms the KL divergence-based IT classification in agreeing with the ground truth. The fourth study is a survey of information professionals who help evaluate this computational approach. Results are generally consistent with the findings in the previous study. The fifth study explores the co-occurrence analysis further and has generated IT classifications very much similar to the ground truth. The computational approach developed in this dissertation is expected to help IT practitioners and researchers make sense of the numerous concepts in the IT field. Overall, the dissertation establishes a good foundation for studying the relationships of IT concepts in a representative, dynamic, and scalable way

Understanding IT Innovations through Discourse Analysis

The dynamic information field is characterized by the constant ebbs and flows of innovations in information technologies (IT). Accordingly, managing information and formulating policies in the iField require understanding IT innovations ??? what they are and will be, who develops and/or adopts them, and how innovations may be effectively developed, implemented, and used. Despite a relatively sustained research literature on IT innovations [2], our knowledge of innovations is still inadequate to effectively inform strategic information management and policy-making in the iField. For instance, the field is filled with numerous buzzwords and acronyms, making it hard to differentiate true progress from mere change. And most research and practice are focused on highly popular innovations such as Web 2.0 and cloud computing; little is known about why only some innovations come to be popular while others do not. The lack of understanding is in part caused by limited research designs that focus on only one or a few innovations, owing to the difficulty in analyzing large-scale data on multiple innovations. The present study seeks to address these limitations by offering a theoretical foundation and an analytical method for understanding the dynamic interactions among IT innovations. Theoretically, we posit that innovations emerge and evolve in an ecosystem. Each innovation can be likened to a species competing with or supporting others in a resource space. One important resource that every innovation relies on is attention from people and organizations. A certain innovation requires a certain type of attention. For example, the innovation of computer-aided software engineering (CASE) asks for attention mainly from system analysts and programmers. Their attention may also be ???nutritious??? to the innovation of object-oriented programming (OOP), but not so much to customer relationship management (CRM), which thrives on the attention from a different group of people. Because CASE and OOP ???consume??? the same type of attention (i.e., from the same group of people), the two innovations are related. Innovations may be related for other reasons as well. For example, different innovations may be developed to solve similar problems, require common knowledge for understanding the problems or similar skills to implement the solutions, or share the practices or roles to be affected by the innovations. To the extent two innovations are related, attention may flow from one to the other. The relationship between a pair of innovations may take on different forms: They may compete with each other or they may complement each other

Dehydroepiandrosterone Shifts Energy Metabolism to Increase Mitochondrial Biogenesis in Female Fertility with Advancing Age

Female reproductive aging is an irreversible process associated with a decrease in oocyte quality, which is a limiting factor for fertility. Previous studies have shown that dehydroepiandrosterone (DHEA) has been shown to improve in vitro fertilization (IVF) outcomes in older women. Herein, we showed that the decline in oocyte quality with age is accompanied by a significant decrease in the level of bioenergetic metabolism genes. We compared the clinical characteristics between groups of infertile women who either received DHEA or did not. Treatment with DHEA may enhance oocyte quality by improving energy production and metabolic reprogramming in cumulus cells (CCs) of aging women. Our results showed that compared with the group without DHEA, the group with DHEA produced a large number of day-three (D3) embryos, top-quality D3 embryos, and had improved ongoing pregnancy rate and clinical pregnancy rate. This may be because DHEA enhances the transport of oxidative phosphorylation and increases mitochondrial oxygen consumption in CCs, converting anaerobic to aerobic metabolism commonly used by aging cells to delay oocyte aging. In conclusion, our results suggest that the benefit of DHEA supplementation on IVF outcomes in aging cells is significant and that this effect may be mediated in part through the reprogramming of metabolic pathways and conversion of anaerobic to aerobic respiration