Design and Validation of a Bifunctional Ligand Display System for Receptor Targeting

AbstractHere we developed a bacteriophage display particle designed to serve as a bifunctional entity that can target tumors while delivering an agent. We engineered a chimera phage vector containing a pIII-displayed αv integrins-targeting moiety and a pVIII-displayed streptavidin binding adaptor moiety. By using the chimeric phage particle, targeting of αv integrins on cells in culture and tumor-related blood vessels was shown through different applications, including luminescent quantum dots localization, surface plasmon resonance-based binding detection, and an in vivo tumor model. The strategy validated here will accelerate the discovery and characterization of receptor-ligand binding events in high throughput, and cell-specific delivery of diagnostics or therapeutics to organs of choice without the need for chemical conjugation

Hyperonic mixing in five-baryon double-strangeness hypernuclei in a two-channel treatment

Properties of hypernuclei $_{\Lambda \Lambda}^5$H and $_{\Lambda \Lambda }^5$He are studied in a two-channel approach with explicit treatment of coupling of channels ^3\text{Z}+\Lambda+\Lambda and \alpha+\Xi. Diagonal \Lambda\Lambda and coupling \Lambda\Lambda-\Xi N interactions are derived within G-matrix procedure from Nijmegen meson-exchange models. Bond energy \Delta B_{\Lambda\Lambda} in $_{\Lambda \Lambda}^5$He exceeds significantly that in $_{\Lambda \Lambda}^5$H due to the channel coupling. Diagonal \Xi\alpha attraction amplifies the effect, which is sensitive also to \Lambda-core interaction. The difference of the \Delta B_{\Lambda\Lambda} values can be an unambiguous signature of the \Lambda\Lambda-\Xi N coupling in \Lambda\Lambda hypernuclei. However, improved knowledge of the hyperon-nucleus potentials is needed for quantitative extraction of the coupling strength from future data on the \Lambda\Lambda hypernuclear binding energies.Comment: 11 pages with 3 figures; Phys. Rev. C, accepte

Assay Type Detection Using Advanced Machine Learning Algorithms

The colourimetric analysis has been used in diversified fields for years. This paper provides a unique overview of colourimetric tests from the perspective of computer vision by describing different aspects of a colourimetric test in the context of image processing, followed by an investigation into the development of a colorimetric assay type detection system using advanced machine learning algorithms. To the best of our knowledge, this is the first attempt to define colourimetric assay types from the eyes of a machine and perform any colorimetric test using deep learning. This investigation utilizes the state-of-the-art pre-trained models of Convolutional Neural Network (CNN) to perform the assay type detection of an enzyme-linked immunosorbent assay (ELISA) and lateral flow assay (LFA). The ELISA dataset contains images of both positive and negative samples, prepared for the plasmonic ELISA based TB-antigen specific antibody detection. The LFA dataset contains images of the universal pH indicator paper of eight pH levels. It is noted that the pre-trained models offered 100% accurate visual recognition for the assay type detection. Such detection can assist novice users to initiate a colorimetric test using his/her personal digital devices. The assay type detection can also aid in calibrating an image-based colorimetric classification

An intelligent mobile-enabled expert system for tuberculosis disease diagnosis in real time

This paper presents an investigation into the development of an intelligent mobile-enabled expert system to perform an automatic detection of tuberculosis (TB) disease in real-time. One third of the global population are infected with the TB bacterium, and the prevailing diagnosis methods are either resource-intensive or time consuming. Thus, a reliable and easy–to-use diagnosis system has become essential to make the world TB free by 2030, as envisioned by the World Health Organisation. In this work, the challenges in implementing an efficient image processing platform is presented to extract the images from plasmonic ELISAs for TB antigen-specific antibodies and analyse their features. The supervised machine learning techniques are utilised to attain binary classification from eighteen lower-order colour moments. The proposed system is trained off-line, followed by testing and validation using a separate set of images in real-time. Using an ensemble classifier, Random Forest, we demonstrated 98.4% accuracy in TB antigen-specific antibody detection on the mobile platform. Unlike the existing systems, the proposed intelligent system with real time processing capabilities and data portability can provide the prediction without any opto-mechanical attachment, which will undergo a clinical test in the next phase.</p

Kebolehupayaan sistem penuaian hujan sebagai bekalan air alternatif di Malaysia: Suatu penelitian awal

Sistem Penuaian Air Hujan dianggap sebagai Kaedah Pengurusan Terbaik atau "Best Management Practice (BMP)" yang diamalkan di Malaysia. Sistem ini bukan sahaja bertujuan untuk melambatkan aliran air larian permukaan malahan ianya juga dijadikan sebagai sumber bekalan air alternatif yang percuma dan selamat digunakan. Terdapat juga pandangan yang mengatakan sistem tersebut tidak viable dan praktikal memandangkan kos binaan dan penyelenggaraan yang terpaksa ditanggung oleh pengguna sistem berkenaan. Bagaimanapun, terdapat beberapa kajian di dalam dan diluar negara menunjukkan faktor ‘return on capital’ atau ROC bagi sistem ini hanyalah di dalam tempoh masa yang pendek, iaitu antara dua hingga tiga tahun. Artikel ini cuba meneliti tapak pelaksanaan sistem berkenaan di kampus Universiti Kebangsaan Malaysia sebagai makmal ujikaji khusus. Hasil pengoperasian sistem analisis TANGKINAHRIM (2010), telah mendapati taburan hujan yang konsisten sepanjang tahun, di samping keluasan tapak tadahan air yang besar dan mencukupi untuk kegunaan operasi pejabat di Fakulti Sains Sosial dan Kemanusiaan. Kebolehpercayaan terhadap sistem berkenaan adalah tinggi iaitu 89.3% dan didapati saiz tangki yang optimum adalah di sekitar 60 hingga 65 meter padu air yang mampu diisi. Anggaran saiz berkenaan adalah didapati bersesuaian dengan saiz tadahan, jumlah populasi (pengguna) dan juga perletakan lokasi yang strateg

Clustering and Classification of a Qualitative Colorimetric Test

In this paper, we present machine learning based detection methods for a qualitative colorimetric test. Such an automatic system on mobile platform can emancipate the test result from the color perception of individuals and its subjectivity of interpretation, which can help millions of populations to access colorimetric test results for healthcare, allergen detection, forensic analysis, environmental monitoring and agricultural decision on point-of-care platforms. The case of plasmonic enzyme-linked immunosorbent assay (ELISA) based tuberculosis disease is utilized as a model experiment. Both supervised and unsupervised machine learning techniques are employed for the binary classification based on color moments. Using 10-fold cross validation, the ensemble bagged tree and k-nearest neighbors algorithm achieved 96.1% and 97.6% accuracy, respectively. The use of multi-layer perceptron with Bayesian regularization backpropagation provided 99.2% accuracy. Such high accuracy system can be trained off-line and deployed to mobile devices to produce an automatic colourimetric diagnostic decision anytime anywhere

Evidence on anti-malarial and diagnostic markets in Cambodia to guide malaria elimination strategies and policies

BACKGROUND: Understanding Cambodia's anti-malarial and diagnostic landscape in 2015 is critical for informing and monitoring strategies and policies as Cambodia moves forward with national efforts to eliminate malaria. The aim of this paper is to present timely and key findings on the public and private sector anti-malarial and diagnostic landscape in Cambodia. This evidence can serve as a baseline benchmark for guiding implementation of national strategies as well as other regional initiatives to address malaria elimination activities. METHODS: From August 17th to October 1st, 2015, a cross sectional, nationally-representative malaria outlet survey was conducted in Cambodia. A census of all public and private outlets with potential to distribute malaria testing and/or treatment was conducted among 180 communes. An audit was completed for all anti-malarials, malaria rapid diagnostic tests (RDT) and microscopy. RESULTS: A total of 26,664 outlets were screened, and 1303 outlets were eligible and interviewed. Among all screened outlets in the public sector, 75.9% of public health facilities and 67.7% of community health workers stocked both malaria diagnostic testing and a first-line artemisinin-based combination therapy (ACT). Among anti-malarial-stocking private sector outlets, 64.7% had malaria blood testing available, and 70.9% were stocking a first-line ACT. Market share data illustrate that most of the anti-malarials were sold or distributed through the private sector (58.4%), including itinerant drug vendors (23.4%). First-line ACT accounted for the majority of the market share across the public and private sectors (90.3%). Among private sector outlets stocking any anti-malarial, the proportion of outlets with a first-line ACT or RDT was higher among outlets that had reportedly received one or more forms of 'support' (e.g. reportedly received training in the previous year on malaria diagnosis [RDT and/or microscopy] and/or the national treatment guidelines for malaria) compared to outlets that did not report receiving any support (ACT: 82.1 and 60.6%, respectively; RDT: 78.2 and 64.0%, respectively). CONCLUSION: The results point to high availability and distribution of first-line ACT and widespread availability of malaria diagnosis, especially in the public sector. This suggests that there is a strong foundation for achieving elimination goals in Cambodia. However, key gaps in terms of availability of malaria commodities for case management must be addressed, particularly in the private sector where most people seek treatment. Continued engagement with the private sector will be important to ensure accelerated progress towards malaria elimination

Enhancing Agricultural Productivity of CLMV Countries: Challenges and Agenda for Reforms

Responding positively to economic reforms, the economies of Cambodia, the Lao People's Democratic Republic, Myanmar, and Viet Nam (CLMV) have shown tremendous growth since the mid-1980s, including in their respective agriculture sectors. Recent developments, however, have brought into question the CLMV countries' ability to sustain further increases in agricultural productivity given the slow pace of reforms and emerging challenges. Going forward, the reform agenda must go beyond the traditional view of expanding yields and supply of agricultural products for development gains in the sector to contribute to inclusive growth, poverty alleviation, and food security. This will require changing the market structures and regulatory policies that govern the sector

Availability and quality of anti-malarials among private sector outlets in Myanmar in 2012: results from a large, community-based, cross-sectional survey before a large-scale intervention

BACKGROUND: Global malaria control efforts are threatened by the spread and emergence of artemisinin-resistant Plasmodium falciparum parasites. In 2012, the widespread sale of partial courses of artemisinin-based monotherapy was suspected to take place in the highly accessed, weakly regulated private sector in Myanmar, posing potentially major threats to drug resistance. This study investigated the presence of artemisinin-based monotherapies in the Myanmar private sector, particularly as partial courses of therapy, to inform the targeting of future interventions to stop artemisinin resistance. METHODS: A large cross-sectional survey comprised of a screening questionnaire was conducted across 26 townships in Myanmar between March and May, 2012. For outlets that stocked anti-malarials at the time of survey, a stock audit was conducted, and for outlets that stocked anti-malarials within 3 months of the survey, a provider survey was conducted. RESULTS: A total of 3,658 outlets were screened, 83% were retailers (pharmacies, itinerant drug vendors and general retailers) and 17% were healthcare providers (private facilities and health workers). Of the 3,658 outlets screened, 1,359 outlets (32%) stocked at least one anti-malarial at the time of study. Oral artemisinin-based monotherapy comprised of 33% of self-reported anti-malarials dispensing volumes found. The vast majority of artemisinin-based monotherapy was sold by retailers, where 63% confirmed that they sold partial courses of therapy by cutting blister packets. Very few retailers (5%) had malaria rapid diagnostic tests available, and quality-assured artemisinin-based combination therapy was virtually nonexistent among retailers. CONCLUSION: Informal private pharmacies, itinerant drug vendors and general retailers should be targeted for interventions to improve malaria treatment practices in Myanmar, particularly those that threaten the emergence and spread of artemisinin resistance