Cold-tolerance mechanisms in foodborne pathogens: Escherichia coli and Listeria monocytogenes as examples.

The cold chain is an integral part of the modern food industry. Low temperatures can effectively alleviate food loss and the transmission of foodborne diseases caused by microbial reproduction. However, recent reports have highlighted shortcomings in the current cold chain technology's ability to prevent and control cold-tolerant foodborne pathogens. Furthermore, it has been observed that certain cold-chain foods have emerged as new sources of infection for foodborne disease outbreaks. Consequently, there is a pressing need to enhance control measures targeting cold-tolerant pathogens within the existing cold chain system. This paper aims to review the recent advancements in understanding the cold tolerance mechanisms of key model organisms, identify key issues in current research, and explore the potential of utilizing big data and omics technology in future studies.

The quality of frozen-thawed Atlantic salmon (Salmo salar L.) fillets as affected by sub-chilling before freezing.

BACKGROUND: To maintain the quality of frozen Atlantic salmon after thawing and highlight the potential for moving from air fright to boat for long-distance export, a study was designed to investigate the effects of sub-chilling before rapid freezing on the quality of thawed fillets. Atlantic salmon chilled on wet ice before filleting and freezing was used as a control for the experimental factor chilling, whereas fresh fillets were used for the frozen-thawed samples. RESULTS: The pre-freezing chilling method interacted with the storage protocol and significantly affected the product. For fresh stored fillets, sub-chilling improved the microbiological and textural stability and degradation of proteins. After 1 month of frozen storage, sub-chilled fillets gave better color and textural properties, less adenosine triphosphate degradation and protein denaturation. In addition, sub-chilled 4-month-frozen fillets also showed improved microbial stability compared to those initially chilled with ice before frozen storage. Quality was lost as a function of storage. Fresh fillets generally had higher bacterial counts, surface breaking force, firmness, hue and contents of inosine monophosphate, and lower drip loss and inosine (HxR) levels than those stored frozen-thawed. Moreover, 4-month-frozen fillets had higher HxR levels and lower psychrotrophic viable count growth than those that were frozen for 1 month. The time fillets were stored frozen did not profoundly affect their quality. CONCLUSION: It is concluded that a frozen product might be competitive with a fresh product when sub-chilling is performed before freezing, especially when including the environmental benefits of frozen export by boat rather than air freight. © 2024 The Author(s). Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Effects of temperature fluctuations on the quality and microbial diversity of beef meatballs during simulated cold chain distribution.

BACKGROUND: Cold chain distribution with multiple links maintains low temperatures to ensure the quality of meat products, whereas temperature fluctuations during this are often disregarded by the industry. The present study simulated two distinct temperatures cold chain distribution processes. Quality indicators and high-throughput sequencing were employed to investigate the effects of temperature fluctuations on the quality and microbial diversity of beef meatballs during cold chain distribution. RESULTS: Quality indicators revealed that temperature fluctuations during simulated cold chain distribution significantly (P < 0.05) exacerbated the quality deterioration of beef meatballs. High-throughput sequencing demonstrated that temperature fluctuations affected the diversity and structure of microbial community. Lower microbial species abundance and higher microbial species diversity were observed in the temperature fluctuations group. Proteobacteria and Pseudomonas were identified as the dominant phylum and genus in beef meatballs, respectively, exhibiting faster growth rates and greater relative abundance under temperature fluctuations. CONCLUSION: The present study demonstrates that temperature fluctuations during simulated cold chain distribution can worsen spoilage and shorten the shelf life of beef meatballs. It also offers certain insights into the spoilage mechanism and preservation of meat products during cold chain distribution. © 2024 Society of Chemical Industry.

Safe storage of medicines.

The correct storage of vaccines is vital to ensuring that they work effectively and keep patients safe. In this article the author explains how to ensure compliance with regulations without placing an undue burden on community nursing staff.

Stability and transmissibility of SARS-CoV-2 in the environment.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing the ongoing global coronavirus disease 2019 (COVID-19) pandemic, is believed to be transmitted primarily through respiratory droplets and aerosols. However, reports are increasing regarding the contamination of environmental surfaces, shared objects, and cold-chain foods with SARS-CoV-2 RNA and the possibility of environmental fomite transmission of the virus raises much concern and debate. This study summarizes the current knowledge regarding potential mechanisms of environmental transmission of SARS-CoV-2, including the prevalence of surface contamination in various settings, the viability and stability of the virus on surfaces or fomites, as well as environmental factors affecting virus viability and survival such as temperature and relative humidity. Instances of fomite transmission, including cold-chain food transmission, and the importance of fomite transmission in epidemics, are discussed. The knowledge gaps regarding fomite transmission of SARS-CoV-2 are also briefly analyzed.

Capsule-based colorimetric temperature monitoring system for customizable cold chain management.

The COVID-19 pandemic and the resulting supply chain disruption have rekindled crucial needs for safe storage and transportation of essential items. Despite recent advances, existing temperature monitoring technologies for cold chain management fall short in reliability, cost, and flexibility toward customized cold chain management for various products with different required temperature. In this work, we report a novel capsule-based colorimetric temperature monitoring system with precise and readily tunable temperature ranges. Triple emulsion drop-based microfluidic technique enables rapid production of monodisperse microcapsules with an interstitial phase-change oil (PCO) layer with precise control over its dimension and composition. Liquid-solid phase transition of the PCO layer below its freezing point triggers the release of the encapsulated payload yielding drastic change in color, allowing user-friendly visual monitoring in a highly sensitive manner. Simple tuning of the PCO layer's compositions can further broaden the temperature range in a precisely controlled manner. The proposed simple scheme can readily be formulated to detect both temperature rise in the frozen environment and freeze detection as well as multiple temperature monitoring. Combined, these results support a significant step forward for the development of customizable colorimetric monitoring of a broad range of temperatures with precision.

Mediating Role of Viral Anxiety and Insomnia in Relationship Between Work-Related Stress and Depression Among Cold Chain Workers During COVID-19 Pandemic.

BACKGROUND: Here we investigated whether cold chain workers' insomnia, work-related stress, and viral anxiety contributed to their depression. Furthermore, we investigated the role of viral anxiety in mediating the association between work-related stress and depressive symptoms. METHODS: All 200 invited cold chain workers voluntarily responded to an online survey. All were working at a market in Taiyuan, Shanxi Province, China, and responsible for testing nucleic acids in imported cold chain foods and disinfecting outer packaging at government request. We collected their demographic variables and rated their symptoms using the Stress and Anxiety to Viral Epidemics-6 Items (SAVE-6), Patient Health Questionnaire-9, Insomnia Severity Index (ISI), Perceived Stress Scale (PSS), and Maslach Burnout Inventory - General Survey (MBI-GS). RESULTS: Cold chain workers' depression was significantly correlated with higher SAVE-6 (r = 0.450, P < 0.01), ISI (r = 0.603, P < 0.01), MBI-GS (r = 0.481, P < 0.01), and PSS (r = 0.390, P < 0.01) scores. SAVE-6 score was significantly correlated with ISI (r = 0.462, P < 0.01), MBI-GS (r = 0.305, P < 0.01), and PSS (r = 0.268, P < 0.01) scores. Linear regression revealed that their depression was predicted by SAVE-6 (ß = 0.183, P = 0.003), ISI (ß = 0.409, P < 0.001), and MBI-GS (ß = 0.236, P = 0.002, adjusted R² = 0.440, F = 40.04, P < 0.001) scores. Mediation analysis showed that their burnout directly influenced their depression, while viral anxiety or insomnia severity mediated the influence of burnout on depression. CONCLUSION: The study showed that burnout was a direct cause of depression and that viral anxiety and insomnia severity mediated the relationship between burnout and depression.

Response Characteristics Study of Ethylene Sensor for Fruit Ripening under Temperature Control.

Post-ripening fruits need to be ripened to reach edible conditions, as they are not yet mature enough when picked. Ripening technology is based mainly on temperature control and gas regulation, with the proportion of ethylene being one of the key gas regulation parameters. A sensor's time domain response characteristic curve was obtained through the ethylene monitoring system. The first experiment showed that the sensor has good response speed (maximum of first derivative: 2.01714; minimum of first derivative: -2.01714), stability (xg: 2.42%; trec: 2.05%; Dres: 3.28%), and repeatability (xg: 20.6; trec: 52.4; Dres: 2.31). The second experiment showed that optimal ripening parameters include color, hardness (Change Ⅰ: 88.53%, Change Ⅱ: 75.28%), adhesiveness (Change Ⅰ: 95.29%, Change Ⅱ: 74.72%), and chewiness (Change Ⅰ: 95.18%, Change Ⅱ: 74.25%), verifying the response characteristics of the sensor. This paper proves that the sensor was able to accurately monitor changes in concentration which reflect changes in fruit ripeness, and that the optimal parameters were the ethylene response parameter (Change Ⅰ: 27.78%, Change Ⅱ: 32.53%) and the first derivative parameter (Change Ⅰ: 202.38%, Change Ⅱ: -293.28%). Developing a gas-sensing technology suitable for fruit ripening is of great significance.

ML Approach to Improve the Costs and Reliability of a Wireless Sensor Network.

Temperature-controlled closed-loop systems are vital to the transportation of produce. By maintaining specific transportation temperatures and adjusting to environmental factors, these systems delay decomposition. Wireless sensor networks (WSN) can be used to monitor the temperature levels at different locations within these transportation containers and provide feedback to these systems. However, there are a range of unique challenges in WSN implementations, such as the cost of the hardware, implementation difficulties, and the general ruggedness of the environment. This paper presents the novel results of a real-life application, where a sensor network was implemented to monitor the environmental temperatures at different locations inside commercial temperature-controlled shipping containers. The possibility of predicting one or more locations inside the container in the absence or breakdown of a logger placed in that location is explored using combinatorial input-output settings. A total of 1016 machine learning (ML) models are exhaustively trained, tested, and validated in search of the best model and the best combinations to produce a higher prediction result. The statistical correlations between different loggers and logger combinations are studied to identify a systematic approach to finding the optimal setting and placement of loggers under a cost constraint. Our findings suggest that even under different and incrementally higher cost constraints, one can use empirical approaches such as neural networks to predict temperature variations in a location with an absent or failed logger, within a margin of error comparable to the manufacturer-specified sensor accuracy. In fact, the median test accuracy is 1.02 degrees Fahrenheit when using only a single sensor to predict the remaining locations under the assumptions of critical system failure, and drops to as little as 0.8 and 0.65 degrees Fahrenheit when using one or three more sensors in the prediction algorithm. We also demonstrate that, by using correlation coefficients and time series similarity measurements, one can identify the optimal input-output pairs for the prediction algorithm reliably under most instances. For example, discrete time warping can be used to select the best location to place the sensors with a 92% match between the lowest prediction error and the highest similarity sensor with the rest of the group. The findings of this research can be used for power management in sensor batteries, especially for long transportation routes, by alternating standby modes where the temperature data for the OFF sensors are predicted by the ON sensors.

Fault Detection for Vaccine Refrigeration via Convolutional Neural Networks Trained on Simulated Datasets.

In low-and middle-income countries, the cold chain that supports vaccine storage and distribution is vulnerable due to insufficient infrastructure and interoperable data. To bolster these networks, we developed a convolutional neural network-based fault detection method for vaccine refrigerators using datasets synthetically generated by thermodynamic modelling. We demonstrate that these thermodynamic models can be calibrated to real cooling systems in order to identify system-specific faults under a diverse range of operating conditions. If implemented on a large scale, this portable, flexible approach has the potential to increase the fidelity and lower the cost of vaccine distribution in remote communities.

Optimizing the COVID-19 cold chain vaccine distribution network with medical waste management: A robust optimization approach.

This paper investigates the distribution problem of the COVID-19 vaccine at the provincial level in Turkey and the management of medical waste, considering the cold chain requirements and the perishable nature of vaccines. In this context, a novel multi-period multi-objective mixed-integer linear programming model is initially presented over a 12-month planning horizon for solving the deterministic distribution problem. The model includes newly structured constraints due to the feature of COVID-19 vaccines, which must be administered in two doses at specified intervals. Then, the presented model is tested for the province of Izmir with deterministic data, and the results show that the demand can be satisfied and community immunity can be achieved in the specified planning horizon. Moreover, for the first time, a robust model is created using polyhedral uncertainty sets to manage uncertainties related to supply and demand quantities, storage capacity, and deterioration rate, and it has been analyzed under different uncertainty levels. Accordingly, as the level of uncertainty increases, the percentage of meeting the demand gradually decreases. It is observed that the biggest effect here is the uncertainty in supply, and in the worst case, approximately 30% of the demand cannot be met.

Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19.

As an abrupt epidemic occurs, healthcare systems are shocked by the surge in the number of susceptible patients' demands, and decision-makers mostly rely on their frame of reference for urgent decision-making. Many reports have declared the COVID-19 impediments to trading and global economic growth. This study aims to provide a mathematical model to support pharmaceutical supply chain planning during the COVID-19 epidemic. Additionally, it aims to offer new insights into hospital supply chain problems by unifying cold and non-cold chains and considering a wide range of pharmaceuticals and vaccines. This approach is unprecedented and includes an analysis of various pharmaceutical features such as temperature, shelf life, priority, and clustering. To propose a model for planning the pharmaceutical supply chains, a mixed-integer linear programming (MILP) model is used for a four-echelon supply chain design. This model aims to minimize the costs involved in the pharmaceutical supply chain by maintaining an acceptable service level. Also, this paper considers uncertainty as an intrinsic part of the problem and addresses it through the wait-and-see method. Furthermore, an unexplored unsupervised learning method in the realm of supply chain planning has been used to cluster the pharmaceuticals and the vaccines and its merits and drawbacks are proposed. A case of Tehran hospitals with real data has been used to show the model's capabilities, as well. Based on the obtained results, the proposed approach is able to reach the optimum service level in the COVID conditions while maintaining a reduced cost. The experiment illustrates that the hospitals' adjacency and emergency orders alleviated the service level significantly. The proposed MILP model has proven to be efficient in providing a practical intuition for decision-makers. The clustering technique reduced the size of the problem and the time required to solve the model considerably.

SARS-CoV-2 cold-chain transmission: Characteristics, risks, and strategies.

Low temperature and certain humidity are conducive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for long-time survival and long-distance spread during logistics and trades. Contaminated cold-chain or frozen products and outer packaging act as the carrier of SARS-CoV-2, that infects the high-risk population who works in the ports, cold storage or seafood market. Since the coronavirus disease 2019 (COVID-19) pandemic worldwide, multiple localized outbreaks caused by SARS-CoV-2 contaminated imported cold-chain products have been reported in China, which brought challenges to COVID-19 prevention and control. Here, we review the evidences of SARS-CoV-2 cold-chain transmission from six confirmed cold-chain related COVID-19 outbreaks in China, especially in terms of SARS-CoV-2 whole-genome sequencing and virus isolation. In addition, we summarize the characteristics and mode of SARS-CoV-2 cold-chain transmission from both six COVID-19 outbreaks in China and the outbreaks suspected cold-chain transmission in other countries. Finally, we analyze the underlying risks of SARS-CoV-2 cold-chain transmission and propose the preventive countermeasures.

Thermal fogging with disinfectants and antifreezes enables effective industrial disinfection in subzero cold-chain environment.

AIM: During several local COVID-19 outbreaks in China in 2020, SARS-CoV-2 or its RNA was isolated or detected from frozen food or packages, revealing the lack of effective disinfection measures in the frozen food chain and risk of transmission. We explored the possibility that disinfectant plus antifreeze could be delivered as thermal fog to realize effective disinfection at subzero temperatures. METHODS AND RESULTS: We selected two disinfectant-antifreeze combinations, didecyl dimethyl ammonium bromide (DDAB) - propylene glycol (PPG) and peracetic acid (PAA) - triethylene glycol (TEG), and each combination is used with a custom-optimized thermal fogging machine. The two fogs were tested in -20°C freezer warehouses for their disinfection efficacy against a coronavirus porcine epidemic diarrhoea virus (PEDV) field strain, a swine influenza virus (SIV) field strain, and three indicator bacteria, Escherichia coli, Staphylococcus aureus and Bacillus subtilis endospores. At -20°C, the DDAB-PPG or PAA-TEG thermal fogs settle within 3.5 to 4.5 h and effectively inactivated PEDV with median tissue culture infective dose of 10-3.5 0.1 ml-1 and SIV-H1N1 with hemagglutination titre of 26  ml-1 within 15-60 min. DDAB-PPG could inactivate S. aureus and E. coli vegetative cells (106  cfu ml-1 ) within 15-60 min but not effective on B. subtilis spores, while PAA-TEG could disinfect B. subtilis spores more effectively than for S. aureus and E. coli. CONCLUSIONS: We showed that a practical subzero temperature disinfection technology was effective in killing enveloped viruses and vegetative bacteria or bacterial spores. DDAB-PPG or PAA-TEG thermal fogging may be a practical technology for cold-chain disinfection. SIGNIFICANCE AND IMPACT OF THE STUDY: This subzero temperature disinfection technology could help to meet the urgent public health need of environmental disinfection in frozen food logistics against pandemic and other potential pathogens and to enhance national and international biosecurity.

THERMOD: Development of a Cost Effective Solution for Integrated Sensing and Logging.

With the outbreak of the Covid-19 pandemic, vaccination has become mandatory. Further, for effective results, the vaccines should be stored within the recommended temperature range, typically between 2°C to 8°C, transported safely without any mishandling and temperature excursion. In order to assure vaccine potency, it is essential to have detailed information on the entire temperature data recorded at user-defined intervals. In this paper, we develop functionality interaction to bring different sensors, memory, and processing units to an integrated platform, providing a compact, power-efficient, and low-cost commercial TemperatuRE, Humidity, and MOvement Data-logger (THERMOD). Moreover, the THERMOD hardware is packed with interactive algorithms that address the aforementioned concerns and log the real-time temperature and jerks (3-dimensional movement) encountered throughout the journey, and the logged data can be retrieved by plugging THERMOD into the host computer/laptop. The THERMOD hardware formulation and algorithm embedding have been done in the institution lab, which enables end-to-end storage and monitoring. Also, the proposed design is built with the defined standards by health organizations, e.g., WHO. Further, to validate the proficiency of the proposed design, comparative analysis has been done; a) a cost analysis has been done to state the cost efficiency of the proposed solution, b) real-time power performance graphs have been plotted which depict that THERMOD outperforms the existing solutions. Moreover, a number of experiments were performed for the validation of the proposed design.

Quality assessment of cold chain storage facilities for regulatory and quality management compliance in a developing country context.

BACKGROUND: Supply chain management is essential for cold chain medicines since they are temperature-controlled and must be maintained within a specific temperature range to ensure product integrity and quality. In Nigeria, guidelines that address drug distribution do not adequately address the issue of cold chain management in addition to challenges in implementation. Given the chaotic medicines distribution system, this study examined the quality of practice of supply chain management of cold chain products in line with the World Health Organisation's Expert Committee report on Specifications for Pharmaceutical Preparations. METHODS: The study was set in Abuja Nigeria and descriptive survey was used to explore cold chain supply management. A checklist developed from regulatory requirements stipulated by the World Health Organisation covering documentations, storage and distribution guidelines was used to assess supply chain management of cold chain medicines across various facilities. Data were analysed using IBM Statistical Package for the Social Sciences (SPSS) version 25. RESULTS: The results from this study showed that most of the storage facilities assessed (66.7%) did not meet up to the required standards of quality management for cold chain products. In addition, 50.4% of retail and hospital pharmacy facilities performed poorly in cold chain management practices. Many of aspects of quality management guidelines and regulations were not met by the facilities. Most facilities (66.7%) do not have their equipment calibrated, 43.6% of the hospital and retail pharmacies assessed do not have an automated system to cater for power failure while 37.6% do not perform a temperature check on cold chain products before receiving from suppliers. CONCLUSION: The study has shown that the levels of the supply chain assessed for quality management and regulatory compliance performed poorly. There was limited availability and use of validated quality monitoring systems for cold chain medicines in these facilities.

Food cold chain management improvement: A conjoint analysis on COVID-19 and food cold chain systems.

Cold chains are effective in maintaining food quality and reducing food losses, especially for long-distance international food commerce. Several recent reports have demonstrated that frozen foods are serving as carriers of SARS-CoV-2 and transmitting the virus from one place to another without any human-to-human contact. This finding highlights significant difficulties facing efforts to control the spread of COVID-19 and reveal a transmission mechanism that may have substantially worsened the global pandemic. Traditional food cold chain management practices do not include specific procedures related to SARS-CoV-2-related environmental control and information warnings; therefore, such procedures are urgently needed to allow food to be safely transported without transmitting SARS-CoV-2. In this study, a conjoint analysis of COVID-19 and food cold chain systems was performed, and the results of this analysis were used to develop an improved food cold chain management system utilizing internet of things (IoT) and blockchain technology. First, 45 COVID-19-related food cold chain incidents in China, primarily involving frozen meat and frozen aquatic products, were summarized. Critical food cold chain control points related to COVID-19 were analyzed, including temperature and cold chain requirements. A conceptual system structure to improve food cold chain management, including information sensing, chain linking and credible tracing, was proposed. Finally, a prototype system, which consisted of cold chain environment monitoring equipment, a cold chain blockchain platform, and a food chain management system, was developed. The system includes: 1) a defining characteristic of the newly developed food cold chain system presented here is the use of IoT technology to enhance real-time environmental information sensing capacity; 2) a hybrid data storage mechanism consisting of off-chain and on-chain systems was applied to enhance data security, and smart contracts were used to establish warning levels for food cold chain incidents; and 3) a hypothetical food cold chain failure scenario demonstration in which information collection, intelligent decision making, and cold chain tracing were integrated and automatically generated for decision-making. By integrating existing technologies and approaches, our study provides a novel solution to improve traditional food cold chain management and thus meet the challenges associated with the COVID-19 pandemic. Although our system has been shown to be effective, subsequent studies are still required to develop precise risk evaluation models for SARs-CoV-2 in food cold chains and more precisely control the entire process. By ensuring food safety and reliable traceability, our system could also contribute to the formulation of appropriate mechanisms for international cooperation and minimize the effect of the COVID-19 pandemic on international food commerce.

Decontamination of SARS-CoV-2 from cold-chain food packaging provides no marginal benefit in risk reduction to food workers.

Countries continue to debate the need for decontamination of cold-chain food packaging to reduce possible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fomite transmission among frontline workers. While laboratory-based studies demonstrate persistence of SARS-CoV-2 on surfaces, the likelihood of fomite-mediated transmission under real-life conditions is uncertain. Using a quantitative microbial risk assessment model of a frozen food packaging facility, we simulated 1) SARS-CoV-2 fomite-mediated infection risks following worker exposure to contaminated plastic packaging; and 2) reductions in these risks from masking, handwashing, and vaccination. In a frozen food facility without interventions, SARS-CoV-2 infection risk to a susceptible worker from contact with contaminated packaging was 1.5 × 10-3 per 1h-period (5th - 95th percentile: 9.2 × 10-6, 1.2 × 10-2). Standard food industry infection control interventions, handwashing and masking, reduced risk (99.4%) to 8.5 × 10-6 risk per 1h-period (5th - 95th percentile: 2.8 × 10-8, 6.6 × 10-5). Vaccination of the susceptible worker (two doses Pfizer/Moderna, vaccine effectiveness: 86-99%) with handwashing and masking reduced risk to 5.2 × 10-7 risk per 1h-period (5th - 95th percentile: 1.8 × 10-9, 5.4 × 10-6). Simulating increased transmissibility of current and future variants (Delta, Omicron), (2-, 10-fold viral shedding) among a fully vaccinated workforce, handwashing and masking continued to mitigate risk (1.4 × 10-6 - 8.8 × 10-6 risk per 1h-period). Additional decontamination of frozen food plastic packaging reduced infection risks to 1.2 × 10-8 risk per 1h-period (5th - 95th percentile: 1.9 × 10-11, 9.5 × 10-8). Given that standard infection control interventions reduced risks well below 1 × 10-4 (World Health Organization water quality risk thresholds), additional packaging decontamination suggest no marginal benefit in risk reduction. Consequences of this decontamination may include increased chemical exposures to workers, food quality and hazard risks to consumers, and unnecessary added costs to governments and the global food industry.

Sustainable food cold chain logistics: From microenvironmental monitoring to global impact.

Food cold chain logistics (FCCL) is a systematic engineering process involving the use of a low-temperature environment to maintain the quality and safety of perishable food and reduce food loss and waste (FLW). From a mechanism perspective, FCCL must balance resource costs for a required level of food quality and safety with the costs of greenhouse gas (GHG) emissions. In the context of global warming, the sustainability trade-off between FLW and environmental impact has recently become an important topic in research on efficient, green FCCL. This is mainly reflected in technological innovation, management optimization, and policy responses. With a focus on three levels (micro, meso, macro), this review analyzes current research areas and the gaps and challenges of FCCL in microenvironmental monitoring, life cycle assessment (LCA), and global impact. Future trends pertaining to FCCL in technology, management, and industry and sustainable development are also summarized. Future trends involving sustainable FCCL must be intelligent, systematic, and low carbon. Industry empowerment through next-generation information technologies (e.g., IoT, AI, big data, blockchain) will promote the multidimensional perception, real-time information transmission, and sustainable control of microenvironmental monitoring, as well as support LCA management transformation from fragmentation to system integration. From a macro level, due to the serious global loss of perishable food, the FCCL scale demand is growing greatly, causing a huge environmental burden. Global cooperation, low-carbon consensus, and appropriate policies will become the basis for promoting sustainable FCCL development.

Live, Genetically Attenuated, Cold-Chain-Free Cholera Vaccine-A Research and Development Journey: Light at the End of a Long Tunnel.

Cholera, a diarrheal disease caused by Vibrio cholerae (V. cholerae) O139 and O1 strains, remains a public health problem. The existing World Health Organization (WHO)-licenced, killed, multiple-dose oral cholera vaccines demand 'cold-chain supply' at 2 °C-8 °C. Therefore, a live, single-dose, cold-chain-free vaccine would relieve significant bottlenecks and costs of cholera vaccination campaigns. Our cholera vaccine development journey started in 2000 at Universiti Sains Malaysia with isolation of the hemA gene from V. cholerae, followed by development of a gene mutant vaccine candidate VCUSM2 against V. cholerae O139 in 2006. In 2010, VCUSM2 reactogenicity was reduced by replacing its two wild-type ctxA gene copies with mutated ctxA to produce strain VCUSM14. Introducing the hemA gene into VCUSM14 created VCUSM14P, a strain with the 5-aminolaevulinic acid (ALA) prototrophic trait and excellent colonisation and immunological properties (100% protection to wild-type challenged rabbits). It was further refined in Asian Institute of Medicine, Science and Technology (AIMST University), with completion of single- and repeated-dose toxicity evaluations in 2019 in Sprague Dawley (SD) rats, followed by development of a novel cold-chain-free VCUSM14P formulation in 2020. VCUSM14P is unique for its intact cholera toxin B, a known mucosal adjuvant. The built-in adjuvant makes VCUSM14P an ideal vaccine delivery platform for emerging diseases (e.g. severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] and tuberculosis). Our vaccine formulation mimics natural infection, remains non-reactogenic and immunogenic in vivo, and protects against infection and disease. It will also cost less and be less cumbersome to distribute due to its stability at room temperature. These features could revolutionise the outreach of this and other vaccines to meet global immunisation programmes, particularly in low-resourced areas. The next stage of our journey will be meeting the requisite regulatory requirements to produce the vaccine for rollout to countries where it is most needed.