Aptamer-Based Lateral Flow Assays: Current Trends in Clinical Diagnostic Rapid Tests

The lateral flow assay (LFA) is an extensively used paper-based platform for the rapid and on-site detection of different analytes. The method is user-friendly with no need for sophisticated operation and only includes adding sample. Generally, antibodies are employed as the biorecognition elements in the LFA. However, antibodies possess several disadvantages including poor stability, high batch-to-batch variation, long development time, high price and need for ethical approval and cold chain. Because of these limitations, aptamers screened by an in vitro process can be a good alternative to antibodies as biorecognition molecules in the LFA. In recent years, aptamer-based LFAs have been investigated for the detection of different analytes in point-of-care diagnostics. In this review, we summarize the applications of aptamer technology in LFAs in clinical diagnostic rapid tests for the detection of biomarkers, microbial analytes, hormones and antibiotics. Performance, advantages and drawbacks of the developed assays are also discussed.

A Data-Driven Packaging Efficiency Optimization Method for a Low Carbon System in Agri-Products Cold Chain

The of monitoring the Internet of Things (IoT) in the cold chain allows process data, including packaging data, to be more easily accessible. Proper optimization modelling is the core driving force towards the green and low-carbon operation of cold chain logistics, laying the necessary foundation for the development of a data-driven modelling system. Since efficient packaging is necessary for loss control in the cold chain, its final efficiency during circulation is important for realizing continuous loss prevention and efficient supply. Thus, it is urgent to determine how to utilize these continuously acquired data and how to formulate a more accurate packaging efficiency control methodology in the agri-products cold chain. Through continuous monitoring, we examined the feasibility of this topic by focusing on the concept of data-driven evaluation modelling and the dynamic formation mechanism of comprehensive packaging efficiency in cold chain logistics. The packaging efficiency in the table grape cold chain was used as an example to evaluate the comprehensive efficiency evaluation index system and data-driven evaluation framework proposed in this paper. Our results indicate that the established methodology can adapt to the continuity of comprehensive packaging efficiency, also reflecting the comprehensive efficiency evaluation of the packaging for different times and distances. Through the evaluation of our results, the differences and the dynamic processes between different final packaging efficiencies at different moments are effectively displayed. Thus, the continuous improvement of a low-carbon system in cold chain logistics could be realized.

Demand Forecast on the Orchard Cold Chain Logistics in Hunan Province Based on Cognitive Neuroscience

How to scientifically and effectively predict the cold chain logistics demand and provide basis for decision making has always been the focus of forestry and orchard logistics research. From the learning environment of neurons, cognitive neuroscience provides a new perspective for forecasting the demand for cold chain logistics. This paper uses the cognitive neuroscience theory to construct a BP neural network model containing two hidden layers to predict the cold chain logistics demand of the forestry and orchard industry in Hunan province in 2017-2021. Suggestions are then given from the aspects of cold chain logistics construction, transportation infrastructure construction, government policy, enterprise and industry according to the prediction results, thus, providing a theoretical basis for the planning of the cold chain logistics system of Hunan province in a certain period of time, as well as references for the development of cold chain logistics in other parts of the country.

The impact of COVID-19 on consumers' eating and purchasing habits of agricultural products in China: key determinants and policy implications

Background The study looks at a changed in consumer’s eating and purchasing habits during COVID-19 period. There are several modes of transmission but transmission through food as being speculated is one area that has not been confirmed through research. The study, therefore, looks at how speculations about COVID-19 spreading through food has affected consumers' eating and purchasing habits. This study through probit model analysed how consumers' eating and purchasing habits have been influenced. Results The result shows that age, gender and education have negatively influenced consumer’s eating and purchasing habits during the COVID-19 pandemic compared to pre-pandemic period. The preference for imported food items, preference for frozen food, been infected or knowing someone who has been infected by the virus, and been infected through agricultural source or knowing someone who has been infected by the COVID-19 through agricultural source have negatively affected consumers' eating and purchasing habits compared to pre-pandemic period. The result, however, suggests that consumers who trust in the cold-chain food systems ability to limit the spread of the COVID-19 still maintain a positive eating and purchasing habits. Conclusions The study provides evidence on the impact of COVID-19 on consumer’s eating and purchasing habits. Therefore, there is the need to institute proper sanitary measures, especially at cold-chain food systems to help curb the spread and also boost consumers’ confidence.

Demand Forecast on the Orchard Cold Chain Logistics in Hunan Province Based on Cognitive Neuroscience

How to scientifically and effectively predict the cold chain logistics demand and provide basis for decision making has always been the focus of forestry and orchard logistics research. From the learning environment of neurons, cognitive neuroscience provides a new perspective for forecasting the demand for cold chain logistics. This paper uses the cognitive neuroscience theory to construct a BP neural network model containing two hidden layers to predict the cold chain logistics demand of the forestry and orchard industry in Hunan province in 2017-2021. Suggestions are then given from the aspects of cold chain logistics construction, transportation infrastructure construction, government policy, enterprise and industry according to the prediction results, thus, providing a theoretical basis for the planning of the cold chain logistics system of Hunan province in a certain period of time, as well as references for the development of cold chain logistics in other parts of the country.

COVID-19 Serology Control Panel Using the Dried-Tube Specimen Method

The dried-tube specimen (DTS) procedure was used to develop the COVID-19 serology control panel (CSCP). The DTS offers the benefit of shipping materials without a cold chain, allowing for greater access without deterioration of material integrity. Samples in the panel were sourced from COVID-19 convalescent persons from March to May 2020. The immunoglobulin subtypes (total Ig, IgM, and IgG) and their respective reactivity to severe acute respiratory syndrome coronavirus 2 nucleocapsid, spike, and receptor-binding domain antigens of the samples were delineated and compared with the WHO International Standard to elucidate the exact binding antibody units of each CSCP sample and ensure the CSCP provides adequate reactivity for different types of serological test platforms. We distribute the CSCP as a kit with five coded tubes to laboratories around the world to be used to compare test kits for external quality assurance, for harmonizing laboratory testing, and for use as training materials for laboratory workers.

STATUS, CHALLENGES AND OPPORTUNITIES OF THE COLD CHAIN SYSTEM IN KENYA: THE CASE OF THE FISHERIES SECTOR IN LAMU AND MOMBASA COUNTIES

Purpose: This study examined the status, challenges and opportunities of the fishing sub-sector in Mombasa and Lamu counties in Kenya. The study examined the various opportunities cold chain have in development of the fisheries sector. The study zeroed on factors like the economic, administrative, financial, technological and cultural attributes that influence the efficiency of the cold chain. Methodology: Literature reviewed showed that shortage of reliable and adequate cold chain facilities in sub-Saharan Africa is one of the main causes of losses of perishable products however there’s little documentation of the study on the status, challenges and opportunities of cold chain technologies in the fishing sector in Kenya. The study adopted a descriptive research design. The study focusses on 2 counties in Coastal Kenya i.e. Mombasa and Lamu Counties. The justification for selecting the 2 sites was that Lamu fisheries industry is extensive and highly developed, Lamu receives the highest number of fish harvest. Primary data was obtained through questionnaires and personal interviews. The personal interviews took 5 days in Mombasa and 5 days in Lamu. The data was analyzed using the Statistical Package for the Social Sciences; SPSS version 20. Results: The main result of the study was showed that cold chain is widely used and required in the advancement of fishing in all the study sites. The study also revealed that Lamu County is more dependent on cold chain for fishing to earn profit for the sector as it final market is Mombasa a distance of over 200km away. The needs of the type, capacity and partnership is different from one Beach Management Unit to the other. This is primarily due to factor such fish catch, governance dynamics, access and affordability of cold chain technology and distance to the market. Unique contribution to theory, practice and policy: The study indicated that there has been deliberate effort by the two tier government – National and County to invest in Cold chain however this has been faced with myriad challenges where this installed equipment are either not operating efficiently or have stalled. The study indicated and showed that there needs to be systematic approach when selecting and managing cold chain equipment in the fishing sector.

Establishment and Evaluation of a Loop-Mediated Isothermal Amplification Assay for Rapid Detection of Pseudomonas fluorescens in Raw Milk

Raw milk is susceptible to microbial contamination during transportation and storage. Pseudomonas fluorescens producing heat-resistant enzymes have become the most common and harmful psychrophilic microorganisms in the cold chain logistics of raw milk. To rapidly detect P. fluorescens in raw milk, the protease gene aprX was selected as a detection target to construct a set of primers with strong specificity, and a loop-mediated isothermal amplification (LAMP) assay was established. The detection thresholds of the LAMP assay for pure cultured P. fluorescens and pasteurized milk were 2.57 × 102 and 3 × 102 CFU/mL, respectively. It had the advantages over conventional method of low detection threshold, strong specificity, rapid detection, and simple operation. This LAMP assay can be used for online monitoring and on-site detection of P. fluorescens in raw milk to guarantee the quality and safety of dairy products.