Impact of dietary ingredients on radioprotection and radiosensitization: a comprehensive review.

Radiation exposure poses significant health risks, particularly in radiotherapy and nuclear accidents. Certain dietary ingredients offer potential radioprotection and radiosensitization. In this review, we explore the impact of dietary ingredients, including vitamins, minerals, antioxidants, and other bioactive compounds, on radiation sensitivity and their potential for radioprotection. Radiosensitizers reoxygenate hypoxic tumor cells, increase the radiolysis of water molecules, and regulate various molecular mechanisms to induce cytotoxicity and inhibit DNA repair in irradiated tumor cells. Several dietary ingredients, such as vitamins C, E, selenium, and phytochemicals, show promise in protecting against radiation by reducing radiation-induced oxidative stress, inflammation, and DNA damage. Radioprotectors, such as ascorbic acid, curcumin, resveratrol, and genistein, activate and modulate various signaling pathways, including Keap1-Nrf2, NF-κB, PI3K/Akt/mammalian target of rapamycin (mTOR), STAT3, and mitogen-activated protein kinase (MAPK), in response to radiation-induced oxidative stress, regulating inflammatory cytokine expression, and promoting DNA damage repair and cell survival. Conversely, natural dietary radiosensitizers impede these pathways by enhancing DNA damage and inducing apoptosis in irradiated tumor cells. Understanding the molecular basis of these effects may aid in the development of effective strategies for radioprotection and radiosensitization in cancer treatment. Dietary interventions have the potential to enhance the efficacy of radiation therapy and minimize the side effects associated with radiation exposure.

Social sustainability in Bangladesh marine fisheries management: A case from Hatiya fishing community.

Social sustainability in fisheries focuses on retaining or improving societal welfare in the fishery system without threatening its long-term financial benefits and socio-cultural welfare. However, often social sustainability issues are ignored while implementing any fisheries management actions rather than only focusing on economic and environmental sustainability issues. This study assesses the social sustainability in Bangladesh marine fisheries management gaining insights from the coastal and marine fisheries-dependent communities of Hatiya Upazila in 2021-2022 using a mixed method approach especially focusing on the social issues during the marine fishing ban. Results have shown positive effects on fish production but negative implications on the socio-economic circumstances of the reliant households after the implementation of the marine fishing ban. During the ban, the ability of around 33 % of fisher households to have 3 meals a day has drastically reduced to 2 or 1 meal per day. Households' average fish intake has reduced from 7 kg to 4 kg per week during the ban. Similarly, there have been detrimental effects on family relationships, healthcare access and children's education during the ban. Moreover, pregnant women and children have suffered greatly from protein deficiencies as fishers could not buy protein-rich foods for their families during the ban. Due to the shortage of alternate income-generating activities (AIGAs), almost 71 % of fishers became indebted during the ban. To assist the fishers during the ban, the government has implemented several measures, such as offering incentives (40 kg of rice per registered fisherman per month) and/or AIGA but those are too scant to recompense for the loss that is incurred due to the fishing ban. Finally, this study provides some way forward to bring social sustainability that is affected due to the marine fishing ban as well as to partly meet the targets of Sustainable Development Goals 1, 2, 14 and 15.

Mass Spectrometry Imaging Combined with Sparse Autoencoder Method Reveals Altered Phosphorylcholine Distribution in Imipramine Treated Wild-Type Mice Brains.

Mass spectrometry imaging (MSI) is essential for visualizing drug distribution, metabolites, and significant biomolecules in pharmacokinetic studies. This study mainly focuses on imipramine, a tricyclic antidepressant that affects endogenous metabolite concentrations. The aim was to use atmospheric pressure matrix-assisted laser desorption/ionization (AP-MALDI)-MSI combined with different dimensionality reduction methods to examine the distribution and impact of imipramine on endogenous metabolites in the brains of treated wild-type mice. Brain sections from both control and imipramine-treated mice underwent AP-MALDI-MSI. Dimensionality reduction methods, including principal component analysis, multivariate curve resolution, and sparse autoencoder (SAE), were employed to extract valuable information from the MSI data. Only the SAE method identified phosphorylcholine (ChoP) as a potential marker distinguishing between the control and treated mice brains. Additionally, a significant decrease in ChoP accumulation was observed in the cerebellum, hypothalamus, thalamus, midbrain, caudate putamen, and striatum ventral regions of the treated mice brains. The application of dimensionality reduction methods, particularly the SAE method, to the AP-MALDI-MSI data is a novel approach for peak selection in AP-MALDI-MSI data analysis. This study revealed a significant decrease in ChoP in imipramine-treated mice brains.

A real-time dataset of air quality index monitoring using IoT and machine learning in the perspective of Bangladesh.

This paper produces a real-time air quality index dataset of three places named Kuril Bishow Road, Uttara, and Tongi in Dhaka and Gazipur City, Bangladesh. The IoT framework consists of MQ9, MQ135, MQ131, and dust or PM sensors with an Arduino microcontroller to collect real data on sulfur dioxide, carbon monoxide, nitrogen dioxide, ozone, particle matters 2.5 and 10 µm. The data is stored in an Excel file as a comma-separated file and after that, authors applied regression type and classification type machine learning algorithms to analyze the data. The dataset consists of 11 columns and 155,406 rows, where sulfur dioxide, carbon monoxide, nitrogen dioxide, ozone, and particle matter 2.5 and 10 are recorded where AQI is marked as the target variable and the others are indicated as independent variables. In the dataset, AQI is categorized into five classes named Good, satisfactory, Moderate, Poor and Very Poor. After experimental results, it is seen that two places including Uttara and Kuril are comparatively suitable for Air Quality among the three places as well as the Random Forest algorithm outperforms the models. The study describes details of the embedded system's hardware as well. This dataset will be beneficial for environmental researchers to use to analyze the air quality.

Heavy Metal Accumulation in Fish, Sediment and Water from Three Riverine Ecosystems in the South-western Bangladesh and Nexus to Human Health.

This study investigated heavy metal accumulations in fish, water and sediment from three rivers around a major urban area in Bangladesh, namely the Rupsha, the Atai, and the Bhairab with a view to assessing the ecological and human health risks. Samples were collected from 10 stations over two seasons (summer and winter) and concentrations of 11 metals (As, Se, Pb, Be, Cd, Co, Cr, Cu, Mn, Ni, V) were measured using ICP-MS. Heavy metals in water of these rivers were above the WHO higher thresholds. The Rupsha River, which runs close to industrially dense areas and the downstream part of the three-river network, demonstrated the highest As, Cu, and V concentrations during both seasons. On the other hand, As, Mn and Cr were highest in the Bhairab which is the upstream to the Rupsha and connected to several industrial setups which differ from Bhairab. The less anthropogenically connected Atai River only showed elevated concentrations of Cu and Se. Ecological risk indices indicated low pollution in the rivers during both seasons. In all three rivers and in nearly all fish species, the contamination was higher in winter than summer. Benthic and carnivorous fish species such as, Cynoglossus lingua, Glossogobius giuris, Pseudapocryptes elongatus showed higher metal accumulation compared to other species. Health risk indices like the target hazard quotient (THQ) and carcinogenic risk (CR) suggested low risks but pointed potential risks to human health. The outcomes of this research reports insights into metal contamination pattern in interconnected river systems.

Effectiveness of a Community Pharmacy-Based Health Promotion Program on Hypertension in Bangladesh and Pakistan: Study Protocol for a Cluster-Randomized Controlled Trial.

The aim of this multi-country, cluster-randomized trial is to test the impact of pharmacy-based health promotion to reduce the blood pressure of individuals with hypertension over a 12-month period in Bangladesh and Pakistan. The trial will be implemented with two arms. In Bangladesh, the estimated sample size is around 3600 hypertensive patients. In Pakistan, we will select samples equivalent to 10% of the participants from Bangladesh, comprising 360 hypertensive patients from four pharmacies. Community pharmacies will be randomized into one of two parallel groups (allocation ratio 1:1). Pharmacy professionals in the treatment arm will provide their patients with educational training and counseling, as well as phone calls/mobile text messages and care coordination in the health sector, as part of the intervention. The study will be conducted in three phases: a baseline survey with intervention, a midline survey with intervention and follow-up, and an endline survey with impact evaluation. The primary outcome of the study will be BP. The secondary outcomes will be BP controlled to target, treatment adherence, quality of life, mortality or hospital admission rates resulting from hypertension and its related complications, incremental cost per health-related quality of life gained, knowledge on healthy lifestyle and dietary behavior, and change in the prevalence of current smoking status.

Sweet potato (Ipomoea batatas L.) genotype selection using advanced indices and statistical models: A multi-year approach.

In Bangladesh, sweet potato holds the fourth position as a crucial carbohydrate source, trailing rice, wheat, and potato. However, locally grown sweet potato varieties often display limited stability and yield. To tackle this challenge, diverse selection methods and statistical models were utilized to pinpoint sweet potato genotypes showcasing both stability and superior yield and quality traits. In the initial two years, multiple selection methods were employed to narrow down the collections based on preferences for yield and its contributing traits. Subsequently, a multi-environment trial (MET) was conducted in the following year to pinpoint superior and stable genotypes with desirable yield and quality characteristics. An integrated approach involving the Multi-Trait Genotype Ideotype Distance Index (MGIDI), Factor Analysis and Ideotype-Design (FAI-BLUP), and Smith-Hazel Index (SH) led to the identification of 71 superior sweet potato genotypes out of a total of 351 in the initial growing season. In the subsequent season, the MGIDI selection index was applied to the 71 genotypes, resulting in the selection of 11 top-performing genotypes. This selection process was complemented by a detailed analysis of the strengths and weaknesses of the selected genotypes. In the MET, the mixed effect model, specifically the linear mixed model (LMM), identified significant genotypic and genotype-environment interaction (GEI) variances. This points to elevated heritability and selection accuracy, ultimately boosting the model's reliability. By combining the strengths of LMM and additive main effects and multiplicative interaction (AMMI), the best linear unbiased prediction (BLUP) index identified H20 as the top-performing genotype for marketable root yield (MRY), H37 for dry weight of root (DW), H8 for beta carotene (BC) and H41 for vitamin c (VC). These genotypes surpassed the overall average in the WAAS index. For simultaneous stability and high performance, the WAASBY index selected H37 for MRY, H6 for DW, H61 for BC, and H3 for VC. Finally, genotypes H3 and H20 were selected using multi-trait stability index (MTSI), as they possessed high performance and stability. Based on the selection sense, the objective has been achieved with regards to the trait MRW, which serves as a major criterion for a superior variety of sweet potato.

Exploring cigarette butts pollution in Saint Martin Island: A marine protected area.

Saint Martin Island (SMI), the only coral island in Bangladesh, is located in the Bay of Bengal and has been identified as a marine protected area (MPA). Littering cigarette butts (CBs) waste in an ecologically sensitive environment can have numerous adverse effects. The purpose of this research is to investigate the abundance and density of CBs in SMI and to assess the pollution status using the Cigarette Butt Pollution Index (CBPI). This study is conducted based on the visual survey method in the three types of land use zones of SMI. During the peak season, the investigation was carried out from 9 a.m. to 5 p.m. in December 2023. A total of 4481 CBs item were counted, and the density ranged from 0.37 to 1.76 m-2 with an average value of 0.99 m-2 across 12 sampling campaigns. The highest density was observed at service zones, and the fishing zones had the lowest density. The calculated CBPI values revealed that 75 % of the sampling stations were in the "severe pollution" while 25 % were classified as "high pollution" status, underscoring the prevalence of hazardous CBs across most areas of SMI. To tackle these issues requires regulatory measures, public awareness initiatives, and community involvement. Effective waste management and eco-friendly product promotion can help reduce CBs pollution risks in marine protected islands.

Elucidating Gender-Specific Distribution of Imipramine, Chloroquine, and Their Metabolites in Mice Kidney Tissues through AP-MALDI-MSI.

Knowledge of gender-specific drug distributions in different organs are of great importance for personalized medicine and reducing toxicity. However, such drug distributions have not been well studied. In this study, we investigated potential differences in the distribution of imipramine and chloroquine, as well as their metabolites, between male and female kidneys. Kidneys were collected from mice treated with imipramine or chloroquine and then subjected to atmospheric pressure matrix-assisted laser desorption ionization-mass spectrometry imaging (AP-MALDI-MSI). We observed differential distributions of the drugs and their metabolites between male and female kidneys. Imipramine showed prominent distributions in the cortex and medulla in male and female kidneys, respectively. Desipramine, one of the metabolites of imipramine, showed significantly higher (*** p < 0.001) distributions in the medulla of the male kidney compared to that of the female kidney. Chloroquine and its metabolites were accumulated in the pelvis of both male and female kidneys. Interestingly, they showed a characteristic distribution in the medulla of the female kidney, while almost no distributions were observed in the same areas of the male kidney. For the first time, our study revealed that the distributions of imipramine, chloroquine, and their metabolites were different in male and female kidneys.

A comprehensive account on ethnobotany, phytochemistry and pharmacological insights of genus Celtis.

The plants of Celtis L. genus have been traditionally used to cure aches, sore throats, fevers, cancer, sexually transmitted diseases, sexual weakness, diarrhea, stomach problems, amenorrhea, menstrual disorders, kidney stones, and pain. The review aims to give a comprehensive account of the current state of ethnopharmacology, phytochemistry, and biological activities of the Celtis genus, as well as to describe the potential area of future avenues. Information on the Celtis genus was obtained from internet sources such as Google Scholar, Web of Science, PubMed, ScienceDirect, and so on by using appropriate keywords, including ethnobotanical, pharmacological, pharmaceutical, bioactivity, phytochemistry, and botanical features of the Celtis genus. This review identified 14 species in the genus Celtis that have a phytopharmacological investigation, including C.africana Burm. f., C. australis L., C. occidentalis L., C. sinensis Pers., C. philippensis Blanco., C. tetrandra Roxb., C. tessmannii Rendle., C. jessoensis Koidz., C. adolfi-friderici Engl., C. iguanaea (Jacq.) Sarg., C. laevigata Wild., C. pallida Torr., C. zenkeri Engl., and C. tournefortii Lam. This genus contains many classified phytoconstituents, such as terpenoids, organic acids, flavonoids, and volatile compounds. Their extracts and pure substances have been shown to have the same anticancer, antibacterial, anti-inflammatory, antioxidant, hepatoprotective, cardioprotective, urease-inhibiting, and antidiarrheal properties as their traditional uses. In terms of current information on ethnopharmacology, phytochemicals, and pharmacological uses, the data acquired in this review could be beneficial and needed for future research. Some phytoconstituents (for instance, kaempferol, myricetin, quercetin, and eugenol) and extracts (for example, leaves, seeds, and ripe fruits extracts of C. australis) showed tremendous results in preliminary testing with promising antimicrobial, anticancer, and urease inhibitory effects. Further research and clinical investigations are needed to develop them as lead compounds and neutraceuticals, which may provide an advance over traditional medicinal systems.

Sea-level rise and mental health among coastal communities: A quantitative survey and conditional process analysis.

This is the first large-scale empirical study examining the impact of sea-level rise induced by climate change on mental health outcomes among coastal communities. The study focuses on Bangladesh, a country severely affected by salinity ingress, flood risks, and agricultural damage due to sea-level changes. Participants (n = 1,200) randomly selected from three coastal regions each having high, moderate, or low vulnerability to sea-level rise were surveyed during the pre-monsoon season in 2021. The cross-sectional survey included validated measures of psychological distress, depression, anxiety, stress, environmental stressors, resource loss, and demographics. The results indicated significantly higher levels of psychological distress, depression, anxiety, and stress in residents of high-vulnerability areas compared to moderate or low-vulnerability regions. Resource loss served as a mediating variable between environmental stressors and mental health outcomes. Furthermore, demographic analyses showed that older adults and women reported higher levels of psychological distress. These findings align with the Sendai Framework for Disaster Risk Reduction, highlighting urgent need for targeted mental health interventions and sustainable models of care in coastal areas increasingly threatened by sea-level rise.

Involvement of Peptidoglycan Receptor Proteins in Mediating the Growth-Promoting Effects of Bacillus pumilus TUAT1 in Arabidopsis thaliana.

Bacillus pumilus TUAT1 acts as plant growth-promoting rhizobacteria for various plants like rice and Arabidopsis. Under stress conditions, B. pumilus TUAT1 forms spores with a thick peptidoglycan (PGN) cell wall. Previous research showed that spores were significantly more effective than vegetative cells in enhancing plant growth. In Arabidopsis, lysin motif proteins, LYM1, LYM3 and CERK1, are required for recognizing bacterial PGNs to mediate immunity. Here, we examined the involvement of PGN receptor proteins in the plant growth promotion (PGP) effects of B. pumilus TUAT1 using Arabidopsis mutants defective in PGN receptors. Root growth of wild-type (WT), cerk1-1, lym1-1 and lym1-2 mutant plants was significantly increased by TUAT1 inoculation, but this was not the case for lym3-1 and lym3-2 mutant plants. RNA-seq analysis revealed that the expression of a number of defense-related genes was upregulated in lym3 mutant plants. These results suggested that B. pumilus TUAT1 may act to reduce the defense response, which is dependent on a functional LYM3. The expression of the defense-responsive gene, WRKY29, was significantly induced by the elicitor flg-22, in both WT and lym3 mutant plants, while this induction was significantly reduced by treatment with B. pumilus TUAT1 and PGNs in WT, but not in lym3 mutant plants. These findings suggest that the PGNs of B. pumilus TUAT1 may be recognized by the LYM3 receptor protein, suppressing the defense response, which results in plant growth promotion in a trade-off between defense and growth.

Minerals and fatty acid profile of small indigenous fish species from homestead ponds within a Sub-tropical coastal region.

Malnutrition has emerged as a noticeable obstruction to the socio-economic advancement of rural areas along the coastal regions of Bangladesh. Small indigenous fish species (SIS) have the potential to alleviate the malnutrition issue because of having higher nutritional compositions. However, prior research has overlooked the detailed nutritional value of SIS originating from coastal regions. Consequently, the current investigation sought to analyze the mineral and fatty acid composition of twelve SIS obtained from coastal homestead ponds. The findings indicated that the mineral composition in SIS exhibited the following descending order: calcium (Ca) > phosphorus (P) > potassium (K) > magnesium (Mg) > iron (Fe) > zinc (Zn). Furthermore, when considering the overall mineral content in SIS, it ranked in the following decreasing order: A. testudineus, M. tengara, C. punctatus, N. nandus, P. sophore, C. fasciatus, A. mola, C. batrachus, H. fossilis, P. sarana, M. aculeatus, and O. pabda. The analysis of the fatty acid profile further revealed that SIS is a rich source of palmitic acid, linoleic acid, oleic acid, stearic acid, myristic acid, palmitoleic acid, and linolenic acid. The saturated fatty acid content of the SIS varied between 42.66 % and 63.37 %, and the highest content was found in A. mola whereas the lowest was in A. testudineus. On the other hand, the total monounsaturated fatty acid content of the SIS ranged from 26.49 % (A. mola) to 46.12 % (P. sarana), and the total PUFAs contents among the fish species ranged from 5.7 % (A. mola) to 16.54 % (H. fossilis). Therefore, SIS could be a key source of minerals and essential fatty acids for human well-being. This can help fulfill nutrient requirements and reduce malnutrition among coastal populations. It can be said that, if these fishes are introduced in the culture systems, it will be used for consumption as well as support the livelihood of coastal people.

Real-time dataset of pond water for fish farming using IoT devices.

This paper introduces a real-time water quality dataset of five ponds for fish farming obtained through an IoT framework for monitoring the aquatic environmental conditions. It utilizes sensors and an Arduino microcontroller to collect data on pH, temperature, and turbidity in pond water in Jamalpur District, Bangladesh. The data is stored in an IoT cloud platform named ThingSpeak and analyzed using 10 machine learning algorithms. The dataset consists of 4 columns and 40,280 rows, where pH, temperature, turbidity, and fish are recorded. Fish represents the target variable, while the others serve as independent variables. Within the dataset, there are 11 distinct fish categories including sing, silver carp, Katla, prawn, karpio, shrimp, rui, pangas, tilapia, magur, and koi. Results showed that only three ponds are suitable for fish farming among five ponds and the Random Forest algorithm performs the best. The study also includes details of the IoT system's hardware. This dataset will be useful for researchers and fish farmers to predict fish survival.

Gut microbiota in obesity and related complications: Unveiling the complex interplay.

In recent years, the obesity epidemic has escalated into a serious public health catastrophe that is only getting worse. However, research into the pathophysiological pathways behind the obesity development and the illnesses that it is associated with is ongoing. In the last decades, it is now clear that the gut microbiota plays a significant role in the genesis and progression of obesity and obesity-related illnesses, particularly changes in its metabolites and composition as obesity progresses. Here, we provide a summary of the processes by which variations in gut metabolite levels and the composition of gut microbiota affect obesity and associated disorders. The bacteria residing in the gut release several chemicals that influence the appetite control, metabolism, and other systems. Since it can either encourage or restrict the deposition of fat in several different ways, the gut microbiota's role in obesity is debatable. Additionally, we go over potential therapeutic approaches that could be utilized to alter gut microbiota composition and focus on the important metabolic pathways associated with obesity and metabolic disorders linked to obesity.

Internet of Things in Pregnancy Care Coordination and Management: A Systematic Review.

The Internet of Things (IoT) has positioned itself globally as a dominant force in the technology sector. IoT, a technology based on interconnected devices, has found applications in various research areas, including healthcare. Embedded devices and wearable technologies powered by IoT have been shown to be effective in patient monitoring and management systems, with a particular focus on pregnant women. This study provides a comprehensive systematic review of the literature on IoT architectures, systems, models and devices used to monitor and manage complications during pregnancy, postpartum and neonatal care. The study identifies emerging research trends and highlights existing research challenges and gaps, offering insights to improve the well-being of pregnant women at a critical moment in their lives. The literature review and discussions presented here serve as valuable resources for stakeholders in this field and pave the way for new and effective paradigms. Additionally, we outline a future research scope discussion for the benefit of researchers and healthcare professionals.

Benign and Malignant Oral Lesion Image Classification Using Fine-Tuned Transfer Learning Techniques.

Oral lesions are a prevalent manifestation of oral disease, and the timely identification of oral lesions is imperative for effective intervention. Fortunately, deep learning algorithms have shown great potential for automated lesion detection. The primary aim of this study was to employ deep learning-based image classification algorithms to identify oral lesions. We used three deep learning models, namely VGG19, DeIT, and MobileNet, to assess the efficacy of various categorization methods. To evaluate the accuracy and reliability of the models, we employed a dataset consisting of oral pictures encompassing two distinct categories: benign and malignant lesions. The experimental findings indicate that VGG19 and MobileNet attained an almost perfect accuracy rate of 100%, while DeIT achieved a slightly lower accuracy rate of 98.73%. The results of this study indicate that deep learning algorithms for picture classification demonstrate a high level of effectiveness in detecting oral lesions by achieving 100% for VGG19 and MobileNet and 98.73% for DeIT. Specifically, the VGG19 and MobileNet models exhibit notable suitability for this particular task.

Role of Neutrophil Extracellular Traps in Health and Disease Pathophysiology: Recent Insights and Advances.

Neutrophils are the principal trouper of the innate immune system. Activated neutrophils undergo a noble cell death termed NETosis and release a mesh-like structure called neutrophil extracellular traps (NETs) as a part of their defensive strategy against microbial pathogen attack. This web-like architecture includes a DNA backbone embedded with antimicrobial proteins like myeloperoxidase (MPO), neutrophil elastase (NE), histones and deploys in the entrapment and clearance of encountered pathogens. Thus NETs play an inevitable beneficial role in the host's protection. However, recent accumulated evidence shows that dysregulated and enhanced NET formation has various pathological aspects including the promotion of sepsis, pulmonary, cardiovascular, hepatic, nephrological, thrombotic, autoimmune, pregnancy, and cancer diseases, and the list is increasing gradually. In this review, we summarize the NET-mediated pathophysiology of different diseases and focus on some updated potential therapeutic approaches against NETs.

Estimation of concrete materials uniaxial compressive strength using soft computing techniques.

This study addresses a critical gap in concrete strength prediction by conducting a comparative analysis of three deep learning algorithms: convolutional neural networks (CNNs), gated recurrent units (GRUs), and long short-term memory (LSTM) networks. Unlike previous studies that employed various machine learning algorithms on diverse concrete types, our study focuses on mixed-design concrete and fine-tuned deep learning algorithms. The objective is to identify the optimal deep learning (DL) algorithm for predicting concrete uniaxial compressive strength, a crucial parameter in construction and structural engineering. The dataset comprises experimental records for mixed-design concrete, and models were developed and optimized for predictive accuracy. The results show that the CNN model consistently outperformed GRU and LSTM. Hyperparameter tuning and regularization techniques further improved model performance. This research offers practical solutions for material property prediction in the construction industry, potentially reducing resource burdens and enhancing efficiency and construction quality.

The impacts of COVID-19 on seafood prices in Japan: A comparison between cheap and luxury products.

Like many other countries, the economy and society of Japan have been severely affected by the COVID-19 outbreak, and the fishery sector particularly seafood is no exception. Among seafood, since luxury seafood is more commonly consumed at restaurants it has a higher possibility of getting affected by the pandemic compared with cheap popular seafood for the masses. Considering this motivation, this study investigates the variations in the COVID-19 impact on luxury and cheap seafood prices in the Tokyo Toyosu wholesale market. Using the non-linear autoregressive distributed lag model (NARDL), the study identifies that an increase in the hours of stay-at-home during the initial stage of the pandemic is causing a negative influence on both cheap and luxury seafood prices and that this negative impact was severer in the luxury seafood prices. The study also finds a positive influence from the hours of stay-at-home on some cheap popular seafood like horse mackerel and sardine during the third state of emergency (SOE) where at least most of the elderly people have received their first vaccine dose but the negative impact from the SOE measure remained on luxury seafood. It is evident from the findings that the luxury seafood market is heavily dependent on the restaurant sector, which will likely suffer adverse effects when human mobility is restricted. In the event of a pandemic like COVID-19, policymakers should stabilize the price and provide subsidies to the luxury seafood stakeholders.