METHODS: Both instruments were operated according to manufacturer's instructions. Samples used include a commercially available normal control serum (NCS) and patients' specimens. The following were evaluated: precision and comparison studies for SPE, and reproducibility and comparison studies for IFE. Statistical analyses were performed using Microsoft Excel.
RESULTS: For SPE repeatability study, our results showed that EFG26 has higher coefficient of variation (%CV) compared with H2SCAN for both samples except for monoclonal component with %CV of 0.97% and 1.18%, respectively. Similar results were obtained for SPE reproducibility study except for alpha-1 (4.16%) and beta (3.13%) fractions for NCS, and beta fractions (5.36%) for monoclonal sample. Subsequently, reproducibility for IFE was 100% for both instruments. Values for correlation coefficients between both instruments ranged from 0.91 to 0.98 for the five classic bands.
CONCLUSION: Both instruments demonstrated good analytical performance characterized by high precision, reproducibility and correlation.
METHODS: A protein of 58 kd with an isoelectric point of 8.45 was purified from raw latex and from latex gloves and identified as the major allergen, completely blocking specific IgE antibodies in the serum of latex-sensitized subjects. The allergen is a noncovalent homotetramer molecule, in which the 14.6 kd monomer was identified, by amino acid composition and sequence homologies of tryptic peptides, to be the rubber elongation factor found in natural latex of the Malaysian rubber tree.
RESULTS: Competitive immunoinhibition tests showed that the starch powder covering the finished gloves is the airborne carrier of the allergen, resulting in bronchial asthma on inhalation. The purified allergen can induce allergic reactions in the nanogram range.
CONCLUSION: The identification of the allergen (Hev b I) may help to eliminate it during the production of latex-based articles in the future.
OBJECTIVE: This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.
METHOD: The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between 'serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria' and 'patient list based on novel MCDM method known as subjective and objective decision by opinion score method'. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix.
RESULT: An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments.
DISCUSSION: The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.