Visual histological grading system for the evaluation of in vitro-generated neocartilage

Here we present the development of a visual evaluation system for routine assessment of in vitro-engineered cartilaginous tissue. Neocartilage was produced by culturing human articular chondrocytes in pellet culture systems or in a scaffold-free bioreactor system. All engineered tissues were embedded in paraffin and were sectioned and stained with Safranin O-fast green. The evaluation of each sample was broken into 3 categories (uniformity and intensity of Safranin O stain, distance between cells/amount of matrix produced, and cell morphology), and each category had 4 components with a score ranging from 0 to 3. Three observers evaluated each sample, and the new system was independently tested against an objective computer-based histomorphometry system. Pellets were also assessed biochemically for glycosaminoglycan (GAG) content. Pellet histology scores correlated significantly with GAG contents and were in agreement with the computer-based histomorphometry system. This system allows a valid and rapid assessment of in vitro-generated cartilaginous tissue that has a relevant association with objective parameters indicative of cartilage quality.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Home-based training to improve manual dexterity in patients with multiple sclerosis: A randomized controlled trial.

BACKGROUND Impaired manual dexterity is frequent and disabling in patients with multiple sclerosis (MS), affecting activities of daily living (ADL) and quality of life. OBJECTIVE We aimed to evaluate the effectiveness of a standardized, home-based training program to improve manual dexterity and dexterity-related ADL in MS patients. METHODS This was a randomized, rater-blinded controlled trial. Thirty-nine MS patients acknowledging impaired manual dexterity and having a pathological Coin Rotation Task (CRT), Nine Hole Peg Test (9HPT) or both were randomized 1:1 into two standardized training programs, the dexterity training program and the theraband training program. Patients trained five days per week in both programs over a period of 4 weeks. Primary outcome measures performed at baseline and after 4 weeks were the CRT, 9HPT and a dexterous-related ADL questionnaire. Secondary outcome measures were the Chedoke Arm and Hand Activity Inventory (CAHAI-8) and the JAMAR test. RESULTS The dexterity training program resulted in significant improvements in almost all outcome measures at study end compared with baseline. The theraband training program resulted in mostly non-significant improvements. CONCLUSION The home-based dexterity training program significantly improved manual dexterity and dexterity-related ADL in moderately disabled MS patients. Trial Registration NCT01507636.

New Shuttle Vector-Based Expression System To Generate Polyhistidine-Tagged Fusion Proteins in Staphylococcus aureus and Escherichia coli.

Four Staphylococcus aureus-Escherichia coli shuttle vectors were constructed for gene expression and production of tagged fusion proteins. Vectors pBUS1-HC and pTSSCm have no promoter upstream of the multiple cloning site (MCS), and this allows study of genes under the control of their native promoters, and pBUS1-Pcap-HC and pTSSCm-Pcap contain the strong constitutive promoter of S. aureus type 1 capsule gene 1A (Pcap) upstream of a novel MCS harboring codons for the peptide tag Arg-Gly-Ser-hexa-His (rgs-his6). All plasmids contained the backbone derived from pBUS1, including the E. coli origin ColE1, five copies of terminator rrnB T1, and tetracycline resistance marker tet(L) for S. aureus and E. coli. The minimum pAMα1 replicon from pBUS1 was improved through either complementation with the single-strand origin oriL from pUB110 (pBUS1-HC and pBUS1-Pcap-HC) or substitution with a pT181-family replicon (pTSSCm and pTSSCm-Pcap). The new constructs displayed increased plasmid yield and segregational stability in S. aureus. Furthermore, pBUS1-Pcap-HC and pTSSCm-Pcap offer the potential to generate C-terminal RGS-His6 translational fusions of cloned genes using simple molecular manipulation. BcgI-induced DNA excision followed by religation converts the TGA stop codon of the MCS into a TGC codon and links the rgs-his6 codons to the 3' end of the target gene. The generation of the rgs-his6 codon-fusion, gene expression, and protein purification were demonstrated in both S. aureus and E. coli using the macrolide-lincosamide-streptogramin B resistance gene erm(44) inserted downstream of Pcap. The new His tag expression system represents a helpful tool for the direct analysis of target gene function in staphylococcal cells.

Computer-based summative assessment of clinical reasoning in clerkships: A mixed-method comparison of key feature problems with case-based multiple choice questions

Background: It is yet unclear if there are differences between using electronic key feature problems (KFPs) or electronic case-based multiple choice questions (cbMCQ) for the assessment of clinical decision making. Summary of Work: Fifth year medical students were exposed to clerkships which ended with a summative exam. Assessment of knowledge per exam was done by 6-9 KFPs, 9-20 cbMCQ and 9-28 MC questions. Each KFP consisted of a case vignette and three key features (KF) using “long menu” as question format. We sought students’ perceptions of the KFPs and cbMCQs in focus groups (n of students=39). Furthermore statistical data of 11 exams (n of students=377) concerning the KFPs and (cb)MCQs were compared. Summary of Results: The analysis of the focus groups resulted in four themes reflecting students’ perceptions of KFPs and their comparison with (cb)MCQ: KFPs were perceived as (i) more realistic, (ii) more difficult, (iii) more motivating for the intense study of clinical reasoning than (cb)MCQ and (iv) showed an overall good acceptance when some preconditions are taken into account. The statistical analysis revealed that there was no difference in difficulty; however KFP showed a higher discrimination and reliability (G-coefficient) even when corrected for testing times. Correlation of the different exam parts was intermediate. Conclusions: Students perceived the KFPs as more motivating for the study of clinical reasoning. Statistically KFPs showed a higher discrimination and higher reliability than cbMCQs. Take-home messages: Including KFPs with long menu questions into summative clerkship exams seems to offer positive educational effects.

An ultrasensitive NanoLuc-based luminescence system for monitoring Plasmodium berghei throughout its life cycle

BACKGROUND: Bioluminescence imaging is widely used for cell-based assays and animal imaging studies, both in biomedical research and drug development. Its main advantages include its high-throughput applicability, affordability, high sensitivity, operational simplicity, and quantitative outputs. In malaria research, bioluminescence has been used for drug discovery in vivo and in vitro, exploring host-pathogen interactions, and studying multiple aspects of Plasmodium biology. While the number of fluorescent proteins available for imaging has undergone a great expansion over the last two decades, enabling simultaneous visualization of multiple molecular and cellular events, expansion of available luciferases has lagged behind. The most widely used bioluminescent probe in malaria research is the Photinus pyralis firefly luciferase, followed by the more recently introduced Click-beetle and Renilla luciferases. Ultra-sensitive imaging of Plasmodium at low parasite densities has not been previously achieved. With the purpose of overcoming these challenges, a Plasmodium berghei line expressing the novel ultra-bright luciferase enzyme NanoLuc, called PbNLuc has been generated, and is presented in this work. RESULTS: NanoLuc shows at least 150 times brighter signal than firefly luciferase in vitro, allowing single parasite detection in mosquito, liver, and sexual and asexual blood stages. As a proof-of-concept, the PbNLuc parasites were used to image parasite development in the mosquito, liver and blood stages of infection, and to specifically explore parasite liver stage egress, and pre-patency period in vivo. CONCLUSIONS: PbNLuc is a suitable parasite line for sensitive imaging of the entire Plasmodium life cycle. Its sensitivity makes it a promising line to be used as a reference for drug candidate testing, as well as the characterization of mutant parasites to explore the function of parasite proteins, host-parasite interactions, and the better understanding of Plasmodium biology. Since the substrate requirements of NanoLuc are different from those of firefly luciferase, dual bioluminescence imaging for the simultaneous characterization of two lines, or two separate biological processes, is possible, as demonstrated in this work.

The impact of a computer based adult literacy program on literacy and numeracy : evidence from India

With over 700 million illiterate adults in the world, many governments have implemented adult literacy programs across the world, although typically with low rates of success partly because the quality of teaching is low. One solution may lie in the standardization of teaching provided by computer-aided instruction. We present the first rigorous evidence of the effectiveness of a computer-based adult literacy program. A randomized control trial study of TARA Akshar Plus, an Indian adult literacy program, was implemented in the state of Uttar Pradesh in India. We find large, significant impacts of this computer-aided program on literacy and numeracy outcomes. We compare the improvement in learning to that of other traditional adult literacy programs and conclude that TARA Akshar Plus is effective in increasing literacy and numeracy for illiterate adult women.

Hybrid Approach Combining Machine Learning and a Rule-Based Expert System for Text Categorization

This paper discusses a novel hybrid approach for text categorization that combines a machine learning algorithm, which provides a base model trained with a labeled corpus, with a rule-based expert system, which is used to improve the results provided by the previous classifier, by filtering false positives and dealing with false negatives. The main advantage is that the system can be easily fine-tuned by adding specific rules for those noisy or conflicting categories that have not been successfully trained. We also describe an implementation based on k-Nearest Neighbor and a simple rule language to express lists of positive, negative and relevant (multiword) terms appearing in the input text. The system is evaluated in several scenarios, including the popular Reuters-21578 news corpus for comparison to other approaches, and categorization using IPTC metadata, EUROVOC thesaurus and others. Results show that this approach achieves a precision that is comparable to top ranked methods, with the added value that it does not require a demanding human expert workload to train

Approach to integrate product conceptual design information into a computer-aided design system

Commercial computer-aided design systems support the geometric definition of product, but they lack utilities to support initial design stages. Typical tasks such as customer need capture, functional requirement formalization, or design parameter definition are conducted in applications that, for instance, support ?quality function deployment? and ?failure modes and effects analysis? techniques. Such applications are noninteroperable with the computer-aided design systems, leading to discontinuous design information flows. This study addresses this issue and proposes a method to enhance the integration of design information generated in the early design stages into a commercial computer-aided design system. To demonstrate the feasibility of the approach adopted, a prototype application was developed and two case studies were executed.

A Multingual Web-based Educational System for Professional Musicians

This paper presents the main results of the eContent HARMOS project. The project has developed a webbased educational system for professional musicians. The main idea of the project consists of recording master classes taught by highly recognised maestros and annotate this multimedia material using an educational musical taxonomy and automatic annotation tools. Users of the system access a multi-criteria search engine that allows them to find and play video segments according to a combination of criteria, which include instrument, teacher, composer, composition, movement and pedagogical concept. In order to preserve teachers and students rights, a DRM and protection system has been developed. The system is being publicly exploited. This model preserves musical heritage, since these valuable master classes are usually not recorded and it also provides a sustainable model for musical institutions.

A proposal for an Internet of Things-based monitoring system composed by low capability, open source and open hardware devices

The Internet of Things makes use of a huge disparity of technologies at very different levels that help one to the other to accomplish goals that were previously regarded as unthinkable in terms of ubiquity or scalability. If the Internet of Things is expected to interconnect every day devices or appliances and enable communications between them, a broad range of new services, applications and products can be foreseen. For example, monitoring is a process where sensors have widespread use for measuring environmental parameters (temperature, light, chemical agents, etc.) but obtaining readings at the exact physical point they want to be obtained from, or about the exact wanted parameter can be a clumsy, time-consuming task that is not easily adaptable to new requirements. In order to tackle this challenge, a proposal on a system used to monitor any conceivable environment, which additionally is able to monitor the status of its own components and heal some of the most usual issues of a Wireless Sensor Network, is presented here in detail, covering all the layers that give it shape in terms of devices, communications or services.