Phytoremediation: a transgenic perspective in omics era.

Phytoremediation is an environmental safety strategy that might serve as a viable preventative approach to reduce soil contamination in a cost-effective manner. Using plants to remediate pollution from the environment is referred to as phytoremediation. In the past few decades, plants have undergone genetic manipulation to overcome inherent limitations by using genetically modified plants. This review illustrates the eco-friendly process of cleaning the environment using transgenic strategies combined with omics technologies. Herbicides tolerance and phytoremediation abilities have been established in genetically modified plants. Transgenic plants have eliminated the pesticides atrazine and metolachlor from the soil. To expand the application of genetically engineered plants for phytoremediation process, it is essential to test strategies in the field and have contingency planning. Omics techniques were used for understanding various genetic, hormonal, and metabolic pathways responsible for phytoremediation in soil. Transcriptomics and metabolomics provide useful information as resources to understand the mechanisms behind phytoremediation. This review aims to highlight the integration of transgenic strategies and omics technologies to enhance phytoremediation efficiency, emphasizing the need for field testing and comprehensive planning for successful implementation.

Pyroptosis in Diabetic Peripheral Neuropathy and its Therapeutic Regulation.

Pyroptosis is a pro-inflammatory form of cell death resulting from the activation of gasdermins (GSDMs) pore-forming proteins and the release of several pro-inflammatory factors. However, inflammasomes are the intracellular protein complexes that cleave gasdermin D (GSDMD), leading to the formation of robust cell membrane pores and the initiation of pyroptosis. Inflammasome activation and gasdermin-mediated membrane pore formation are the important intrinsic processes in the classical pyroptotic signaling pathway. Overactivation of the NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome triggers pyroptosis and amplifies inflammation. Current evidence suggests that the overactivation of inflammasomes and pyroptosis may further induce the progression of cancers, nerve injury, inflammatory disorders and metabolic dysfunctions. Current evidence also indicates that pyroptosis-dependent cell death accelerates the progression of diabetes and its frequent consequences including diabetic peripheral neuropathy (DPN). Pyroptosis-mediated inflammatory reaction further exacerbates DPN-mediated CNS injury. Accumulating evidence shows that several molecular signaling mechanisms trigger pyroptosis in insulin-producing cells, further leading to the development of DPN. Numerous studies have suggested that certain natural compounds or drugs may possess promising pharmacological properties by modulating inflammasomes and pyroptosis, thereby offering potential preventive and practical therapeutic approaches for the treatment and management of DPN. This review elaborates on the underlying molecular mechanisms of pyroptosis and explores possible therapeutic strategies for regulating pyroptosis-regulated cell death in the pharmacological treatment of DPN.

Modelling the significance of value-belief-norm framework to predict mass adoption potentials of internet of things-enabled wearable fitness devices.

Self-health monitoring technologies have become increasingly popular in averting unanticipated health complications. However, the adoption rate of such technologies in developing countries is surprisingly low. Furthermore, empirical studies on the application of the value-belief-norm (VBN) model to elucidate intention to use IoT-enabled wearable fitness devices (IoT-enabled WFDs) are scarce. This study aimed to expand the VBN model by integrating health values, health consciousness, health knowledge-seeking, and social norms as influencing constructs. The proposed holistic framework was empirically tested to examine these constructs on users' decision-making process of adopting IoT-enabled WFDs. A web-based survey involving 866 adults in China aged 18-30 years was conducted. The gathered data were analysed using partial least squares-structural equation modeling. The results revealed the significant influence of health consciousness and health knowledge-seeking on personal health beliefs, as well as the favourable impact of personal health beliefs on personal norms and awareness of consequences. The results further demonstrated the substantial influence of awareness of consequences and ascription of responsibilities on personal norms. Besides that, personal norms and societal norms were found to have strong influence on the intention to adopt IoT-enabled WFDs, which was revealed to have significant influence on the actual usage. This study's findings offer novel theoretical insights on the behavioural characteristics of adopting IoT-enabled WFDs and serve as a practical guideline for industry experts and marketers to establish appropriate marketing strategies to support the IoT-enabled wearable sector. The findings also benefit policymakers in their efforts of developing strategies that emphasise the unique benefits of self-healthcare monitoring to encourage active lifestyle and decrease obesity and overweight-related health risks.

Impulse buying behavior during livestreaming: Moderating effects of scarcity persuasion and price perception.

This research aimed to identify the factors that influence impulse buying behavior during livestreaming and advance the existing literature based on a proposed conceptual framework grounded in the stimulus-organism-response (S-O-R) model. We also tested the moderating effects of price perception and scarcity persuasion. An online self-administered questionnaire was used to collect data from 837 Chinese participants aged over 18 years. The data were analyzed using partial least squares structural equation modeling using Smart-PLS version 4.0. The findings showed that susceptibility to social influence, impulse buying tendency, cognitive reactions, affective reactions, and the urge to buy impulsively are statistically significant predictors of impulse buying during livestreaming, with price perception and scarcity persuasion as moderators. The study expands the S-O-R model for livestreaming impulse buying in e-commerce context, highlighting its multifaceted nature and revealing the mediating role of Urge to Buy Impulsively in translating cognitive and emotional factors into impulse buying behavior. These insights offer practical guidance for marketers to design tailored strategies that leverage psychological triggers and external cues to enhance consumer engagement and encourage desired behaviors, ultimately leading to more effective marketing campaigns and improved consumer experiences.

Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies.

BACKGROUND: Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications. METHODS: Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes. Subsequently, a protein-protein interaction (PPI) network was established using the STRING database. The created network was visually inspected through Cytoscape, and HGs were identified using the CytoHubba plugin tool. Furthermore, enrichment analysis, expression pattern analysis, clinicopathological correlation, survival analysis, immune cell infiltration analysis, and examination of chemical compounds were carried out using Enrichr, GEPIA2, ULCAN, Kaplan Meier plotter, TIMER2.0, and CTD web platforms, respectively. The diagnostic and prognostic significance of HGs was evaluated through the ROC curve analysis. RESULTS: Ten genes associated with ECM functions were identified as HGs among 131 DEGs obtained from microarray datasets. Notably, the expression of these HGs exhibited significantly (p < 0.05) higher in PC, demonstrating a clear association with tumor advancement. Remarkably, higher expression levels of these HGs were inversely correlated with the likelihood of patient survival. Moreover, ROC curve analysis revealed that identified HGs are promising biomarkers for both diagnostic (AUC > 0.75) and prognostic (AUC > 0.64) purposes. Furthermore, we observed a positive correlation between immune cell infiltration and the expression of most HGs. Lastly, our study identified nine compounds with significant interaction profiles that could potentially act as effective chemical agents targeting the identified HGs. CONCLUSION: Taken together, our findings suggest that COL1A1, KRT19, MMP1, COL11A1, SDC1, ITGA2, COL1A2, POSTN, FN1, and COL5A1 hold promise as innovative biomarkers for both the diagnosis and prognosis of PC, and they present as prospective targets for therapeutic interventions aimed at impeding the progression PC.

Nitrogen and sulfur cycling and their coupling mechanisms in eutrophic lake sediment microbiomes.

Microorganisms play important roles in the biogeochemical cycles of lake sediment. However, the integrated metabolic mechanisms governing nitrogen (N) and sulfur (S) cycling in eutrophic lakes remain poorly understood. Here, metagenomic analysis of field and bioreactor enriched sediment samples from a typical eutrophic lake were applied to elucidate the metabolic coupling of N and S cycling. Our results showed significant diverse genes involved in the pathways of dissimilatory sulfur metabolism, denitrification and dissimilatory nitrate reduction to ammonium (DNRA). The N and S associated functional genes and microbial groups generally showed significant correlation with the concentrations of NH4+, NO2- and SO42, while with relatively low effects from other environmental factors. The gene-based co-occurrence network indicated clear cooperative interactions between N and S cycling in the sediment. Additionally, our analysis identified key metabolic processes, including the coupled dissimilatory sulfur oxidation (DSO) and DNRA as well as the association of thiosulfate oxidation complex (SOX systems) with denitrification pathway. However, the enriched N removal microorganisms in the bioreactor ecosystem demonstrated an additional electron donor, incorporating both the SOX systems and DSO processes. Metagenome-assembled genomes-based ecological model indicated that carbohydrate metabolism is the key linking factor for the coupling of N and S cycling. Our findings uncover the coupling mechanisms of microbial N and S metabolism, involving both inorganic and organic respiration pathways in lake sediment. This study will enhance our understanding of coupled biogeochemical cycles in lake ecosystems.

An Ensemble Feature Selection Approach-Based Machine Learning Classifiers for Prediction of COVID-19 Disease.

The respiratory disease of coronavirus disease 2019 (COVID-19) has wreaked havoc on the economy of every nation by infecting and killing millions of people. This deadly disease has taken a toll on the life of the entire human race, and an exact cure for it is still not developed. Thus, the control and cure of this disease mainly depend on restricting its transmission rate through early detection. The detection of coronavirus infection facilitates the isolation and exclusive care of infected patients. This research paper proposes a novel data mining system that combines the ensemble feature selection method and machine learning classifier for the effective identification of COVID-19 infection. Different feature selection approaches including chi-square test, recursive feature elimination (RFE), genetic algorithm (GA), particle swarm optimization (PSO), and random forest are evaluated for their effectiveness in enhancing the classification accuracy of the machine learning classifiers. The classifiers that are considered in this research work are decision tree, naïve Bayes, K-nearest neighbor (KNN), multilayer perceptron (MLP), and support vector machine (SVM). Two COVID-19 datasets were used for testing from which the best features supporting the dataset were extracted by the proposed system. The performance of the machine learning classifiers based on the ensemble feature selection methods is analyzed.

The Prevalence, Risk Factors, and Antimicrobial Resistance Determinants of Helicobacter pylori Detected in Dyspeptic Patients in North-Central Bangladesh.

Chronic infection of Helicobacter pylori represents a key factor in the etiology of gastrointestinal diseases, with high endemicity in South Asia. The present study aimed to determine the prevalence of H. pylori among dyspeptic patients in north-central Bangladesh (Mymensingh) and analyze risk factors of infection and antimicrobial resistance (AMR) determinants in the pathogen. Endoscopic gastrointestinal biopsy samples were collected from dyspeptic patients for a one-year period from March 2022 and were checked for the presence of H. pylori via the rapid urease test and PCR and further analyzed for the status of virulence factors vacA/cagA and genetic determinants related to AMR via PCR with direct sequencing or RFLP. Among a total of 221 samples collected, 80 (36%) were positive for H. pylori, with the vacA+/cagA+ genotype being detected in almost half of them. H. pylori was most prevalent in the age group of 41-50-year-olds, with it being more common in males and rural residents with a lower economic status and using nonfiltered water, though the rates of these factors were not significantly different from those of the H. pylori-negative group. Relatively higher frequency was noted for the A2147G mutation in 23S rRNA, related to clarithromycin resistance (18%, 7/39). Amino acid substitutions in PBP-1A (T556S) and GyrA (N87K and D91N) and a 200 bp deletion in rdxA were detected in samples from some patients with recurrence after treatment with amoxicillin, levofloxacin, and metronidazole, respectively. The present study describes the epidemiological features of H. pylori infection in the area outside the capital in Bangladesh, revealing the spread of AMR-associated mutations.

Envisaging the intention and adoption of electronic health applications among middle-aged and older adults: Evidence from an emerging economy.

Technology plays a substantial role in our daily lives, and the spread of COVID-19 paves the way for the use of healthcare technologies to manage health in the comfort of our homes. Middle-aged and older adults face health issues and require instant healthcare advice and support. Electronic healthcare (EH) applications have emerged to facilitate middle-aged and older adults receiving healthcare support instantly while remaining in their homes. The present study empirically evaluates the intention and adoption of electronic health applications with the technological attributes of perceived compatibility, cost, product value, technology accuracy, privacy issues and health motivation among middle-aged and older adults from Malaysia. Moreover, this research examines the mediating effect of the intention to adopt EH applications between technology attributes and the adoption of EH applications. This study uses a cross-sectional method and employs an online survey to assemble quantitative data from 298 middle-aged and older Malaysian adults. It utilizes partial least squares structural equation modelling for data analysis. The data analysis reveals that perceived compatibility, cost, privacy, product value and health motivation significantly influenced the intention to use EH apps. Furthermore, the analysis shows that the intention to adopt EH apps significantly mediates the relationship between the perception of cost, personal privacy, product value, health motivation and adoption of EH apps. However, the intention to use EH apps insignificantly instigates their adoption. Finally, the study presents its implications, limitations and future research directions.

The Mechanism of Pyroptosis and Its Application Prospect in Diabetic Wound Healing.

Pyroptosis defines a form of pro-inflammatory-dependent programmed cell death triggered by gasdermin proteins, which creates cytoplasmic pores and promotes the activation and accumulation of immune cells by releasing several pro-inflammatory mediators and immunogenic substances upon cell rupture. Pyroptosis comprises canonical (mediated by Caspase-1) and non-canonical (mediated by Caspase-4/5/11) molecular signaling pathways. Numerous studies have explored the contributory roles of inflammasome and pyroptosis in the progression of multiple pathological conditions such as tumors, nerve injury, inflammatory diseases and metabolic disorders. Accumulating evidence indicates that the activation of the NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome results in the activation of pyroptosis and inflammation. Current evidence suggests that pyroptosis-dependent cell death plays a progressive role in the development of diabetic complications including diabetic wound healing (DWH) and diabetic foot ulcers (DFUs). This review presents a brief overview of the molecular mechanisms underlying pyroptosis and addresses the current research on pyroptosis-dependent signaling pathways in the context of DWH. In this review, we also present some prospective therapeutic compounds/agents that can target pyroptotic signaling pathways, which may serve as new strategies for the effective treatment and management of diabetic wounds.

Association of biosecurity and hygiene practices with avian influenza A/H5 and A/H9 virus infections in turkey farms.

High pathogenicity avian influenza (HPAI) H5N1 outbreaks pose a significant threat to the health of livestock, wildlife, and humans. Avian influenza viruses (AIVs) are enzootic in poultry in many countries, including Bangladesh, necessitating improved farm biosecurity measures. However, the comprehension of biosecurity and hygiene practices, as well as the infection of AIV in turkey farms, are poorly understood in Bangladesh. Therefore, we conducted this study to determine the prevalence of AIV subtypes and their association with biosecurity and hygiene practices in turkey farms. We collected oropharyngeal and cloacal swabs from individual turkeys from 197 farms across 9 districts in Bangladesh from March to August 2019. We tested the swab samples for the AIV matrix gene (M gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We found 24.68% (95% CI:21.54-28.04) of turkey samples were AIV positive, followed by 5.95% (95% CI: 4.33-7.97) for H5, 6.81% (95% CI: 5.06-8.93) for H9 subtype and no A/H7 was found. Using a generalized linear mixed model, we determined 10 significant risk factors associated with AIV circulation in turkey farms. We found that the absence of sick turkeys, the presence of footbaths, the absence of nearby poultry farms, concrete flooring, and the avoidance of mixing newly purchased turkeys with existing stock can substantially reduce the risk of AIV circulation in turkey farms (odds ratio ranging from 0.02 to 0.08). Furthermore, the absence of nearby live bird markets, limiting wild bird access, no visitor access, improved floor cleaning frequency, and equipment disinfection practices also had a substantial impact on lowering the AIV risk in the farms (odds ratio ranging from 0.10 to 0.13). The results of our study underscore the importance of implementing feasible and cost-effective biosecurity measures aimed at reducing AIV transmission in turkey farms. Particularly in resource-constrained environments such as Bangladesh, such findings might assist governmental entities in enhancing biosecurity protocols within their poultry sector, hence mitigating and potentially averting the transmission of AIV and spillover to humans.

Social entrepreneurial intention among university students in China.

The issues of employment, social inequality, and resource scarcity can be effectively addressed through social entrepreneurship, contributing to the growing research interest on the formation of social entrepreneurial intention. Using the theory of planned behaviour, the current study examined the influence of selected key factors on social entrepreneurial intention among university students. Based on the cross-sectional quantitative research design, online survey was conducted, which involved 684 students and graduates from five universities in Southern China. The obtained results demonstrated the significant and positive influence of perceived values on sustainability, opportunity recognition competency, attitude towards entrepreneurship, subjective norms, and perceived behavioural control on social entrepreneurial intention. Additionally, attitude towards entrepreneurship partially mediated the relationships of risk-taking propensity, self-efficacy, and need for achievement on social entrepreneurial intention. The multi-group analysis results also showed that need for achievement and social entrepreneurial intention differed significantly between genders, which provides new ideas for future investigations into the impact of gender on social entrepreneurial intentions. Based on the findings of this study, it is crucial that university students are exposed to relevant courses or training to develop social entrepreneurship competencies and promote sustainable values. The findings of this study will provide policymakers with relevant policy guidelines and more effective theoretical support to achieve the goal of promoting social entrepreneurship among university students in a more resource-efficient and effective manner.

The relationship between mass customization and sustainable performance: The role of firm size and global E-commerce.

The formation of mass customization competencies is crucial for the increasing number of manufacturing companies in modern times. This study assessed the relationship between mass customization capability and its determinants on sustainable performance. Additionally, it explores the mediating role of mass customization capability and sustainable performance, while also examining the moderating effects of firm size and cross-border eCommerce in these associations. The study used online survey data from 339 manufacturing small-to-medium-sized enterprises in China to test the hypothesized relationships. The collected data were analyzed using partial least square structural equation modeling and necessary condition analysis. The results indicated that flexible manufacturing competencies, modular product architecture, and customer relationship management are significantly and positively connected to mass customization capability. Moreover, the study observed that mass customization capability and competitive pressure have a significant positive influence on the sustainable performance of Chinese manufacturing SMEs. The findings also revealed that firm size and cross-border e-commerce engagement have a negative and positive moderating effect, respectively, between mass customization capability on sustainable performance, which confirms a relatively higher effect of customization capability on sustainable performance among smaller firms and firms engaged in cross-border eCommerce. Fundamentally, these findings can lead to the development of a comprehensive framework to promote mass customization capability, cross-border e-commerce, and sustainable development of manufacturing small-to-medium-sized enterprises China.

The Potential of Fish Protein Hydrolysate Supplementation in Nile Tilapia Diets: Effects on Growth and Health Performance, Disease Resistance, and Farm Economic Analysis.

Fish protein hydrolysate (FPH) has shown immense potential as a dietary protein supplement and immunostimulant in aquaculture, especially in Nile tilapia production. Four isoproteic diets (30% crude protein) were prepared by including FPH at varying percentages (0%, 0.5%, 1%, and 2%). Nile tilapia fed with FPH diets for 90 days, and their growth performance, feed utilization, blood biochemistry, liver and gut morphology, and resistance against Streptococcus iniae were investigated. The findings revealed that diets physical attributes such as pellet durability index and water stability were remarkably (p < 0.05) varied between experimental diet groups. Furthermore, the test diets were more palatable when FPH was included at 1% and 2%. Fish that were fed with a 2% FPH-treated diet had significantly (p < 0.05) greater growth indices than other treatments. Additionally, their feed utilization was significantly (p < 0.05) improved. The experimental diets and intestinal total bacteria count (TBC) exhibited a rising trend with FPH levels, where the 2% FPH-treated diet recorded the highest TBC. Neutrophil (109/L), lymphocyte (109/L), eosinophil (109/L), and red blood cell(1012/L) counts were significantly (p < 0.05) higher in the 2% FPH-treated group, while the white blood cell (109/L), and basophil (109/L) counts were not influenced by the FPH inclusion. Moreover, the FPH-treated groups displayed lower creatinine, bilirubin, and urea levels than the control. The histological examination demonstrated that themid-intestine of 2% FPH-fed Nile tilapia had an unbroken epithelial wall, more villi with frequent distribution of goblet cells, wider tunica muscularis, and stronger stratum compactum bonding than other treatments. Additionally, this group exhibited more nuclei and erythrocytes and less vacuolar cytoplasm in liver than their counterparts. Nile tilapia that were given a diet containing 2% FPH had significantly (p < 0.05) higher resistance (83.33%) to S. iniae during the bacterial challenge test. A significant (p < 0.05) enhancement in farm economic efficiency was observed in the higher inclusion of FPH in diets. In summary, 2% FPH supplementation in Nile tilapia diets improved their growth performance, feed utilization, health status, disease resistance, and farm economic efficiency.

Understanding vermicompost and organic manure interactions: impact on toxic elements, nitrification activity, comammox Nitrospira inopinata, and archaea/bacteria.

Vermicompost is a substantial source of nutrients, promotes soil fertility, and maintains or increases soil organic matter levels. Potentially toxic elements (PTEs) in vermicompost impact on nitrification activity. However, it is yet unknown how vermicompost affects nitrifying bacteria and archaea, comammox Nitrospira inopinata (complete ammonia oxidizers), net nitrification rates (NNRs), and PTEs. The effects of vermicompost application on NNRs, potential nitrification rates (NPs), PTEs, and the abundances of comammox N. inopinata bacteria, nitrite-oxidizing bacteria (NOB), and ammonia-oxidizing bacteria (AOB)/archaea (AOA) were studied. NNRs and NPs were significantly higher (p < 0.05) in fresh cow-dung vermicompost (stored for 40 days) as compared with other organic manure. The level of PTEs (Cu2+, Fe2+, Pb2+, Cd2+, and Zn2+) was significantly lower (p < 0.05) in vermicompost as compared with compost of waste material with Trichoderma and cow dung. Comammox N. inopinata, NOB, AOB, and AOA were significantly higher (p < 0.05) in stored cow-dung vermicompost (more than 1 year) as compared with other organic manure. The results of the scatterplot matrix analysis suggested that Fe2+, total nitrogen (TN), soil organic carbon (SOC), and total carbon (TC) were linearly correlated (p < 0.001) with NNRs and NPs in vermicompost and organic manure. Similarly, comammox N. inopinata bacteria, NOB, AOB, and AOA were linearly correlated (p < 0.001) with NNR and NP. These results indicated that vermicompost promoted nitrification activity by increasing microbial diversity and abundance, supplying nutrients and organic matter for microbial growth, and facilitating complex microbial interactions. It may be concluded that the influence of vermicompost, which played a great role in PTE concentration reduction, increased chemical, and biological properties, increased the growth rate of nitrifying bacteria/archaea and the nitrogen cycle.

Modelling the significance of food delivery service quality on customer satisfaction and reuse intention.

The millions-worth revenue derived from large-scale food delivery characterises the service as a relatively established phenomenon with potential growth. The current cross-sectional research examined online food delivery service quality on consumer satisfaction and reuse intention. Service quality was divided into seven categories (i.e., reliability, assurance, security, maintaining food quality, system operation, traceability, and perceived service value). Perceived service value offer the unique understanding of the online food delivery consumer satisfaction. Empirical data were elicited from 1352 valid respondents and subsequently assessed through the partial least square structural equation modelling. Findings revealed that reliability, assurance, maintaining food quality, system operation, traceability, and perceived service value could elevate customer satisfaction and optimize the intention to reuse food delivery services. Specific measures to improve service quality, including staff training, improved after-sales service, and system optimisation, were proposed to increase users' satisfaction and intention to reuse optimally.

Poly (Betulinic Acid) Nanoparticles Loaded with bFGF Improve Functional Recovery After Spinal Cord Injury.

Oxidative stress (OS) is one of the crucial molecular events of secondary spinal cord injury (SCI). Basic fibroblast growth factor (bFGF) is a multipotent cell growth factor with an anti-oxidant effect. However, bFGF has a short half-life in vivo, which limits its therapeutic application. Biodegradable polymers with excellent biocompatibility have been recently applied in SCI. The negative aspect is that polymers cannot provide a significant therapeutic effect. Betulinic acid (BA), a natural anti-inflammatory compound, has been polymerized into poly (betulinic acid) (PBA) to serve as a drug carrier for bFGF. This study explores the therapeutic effects and underlying molecular mechanisms of PBA nanoparticles (NPs) loaded with bFGF (PBA-bFGF NPs) in SCI. Results show that PBA-bFGF NPs produce remarkable biocompatibility in vivo and in vitro. The results also demonstrate that local delivery of PBA-bFGF NPs enhances motor function recovery, inhibits OS, mitigates neuroinflammation, and alleviates neuronal apoptosis following SCI. Furthermore, the results indicate that local delivery of PBA-bFGF NPs activates the nuclear factor erythroid 2-related factor 2 (Nrf-2) signaling pathway following SCI. In summary, results suggest that local delivery of PBA-bFGF NPs delivers potential therapeutic advantages in the treatment and management of SCI.

Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology.

Addressing the growing popularity of mobile health (m-Health) technology in the health industry, the current study examined consumers' intention and behaviour related to the usage of digital applications based on the unified theory of acceptance and use of technology (UTAUT). In particular, this study quantitatively assessed the moderating role of perceived product value and mediating role of intention to use m-Health application among Indonesians. This study adopted a cross-sectional design and collected quantitative data from conveniently selected respondents through an online survey, which involved 2068 Telegram users in Indonesia. All data were subjected to the analysis of partial least square- structural equation modeling (PLS-SEM). The obtained results demonstrated the moderating effect of perceived product value on the relationship between intention to use m-Health application (m-health app) and actual usage of m-Health app and the mediating effects of intention to use m-Health app on the relationships of perceived critical mass, perceived usefulness, perceived convenience, perceived technology accuracy, and perceived privacy protection on actual usage of m-Health app. However, the intention to use m-Health app did not mediate the influence of health consciousness and health motivation on the actual usage of m-Health app. Overall, this study's findings on the significance of intention to use m-Health app and perceived product value based on the UTAUT framework serve as insightful guideline to expand the usage of m-Health app among consumers.

Modelling the mass consumption potential of Plant Based Meat: Evidence from an emerging economy.

The rising demand for plant-based meat (PBM) has the potential to minimize environmental degradation and save the lives of numerous animals. Furthermore, the intention to consume eco-friendly products triggers people to consume PBM. However, it is essential to understand the factors that influence consumer intentions and actual PBM consumption to enhance its adoption. By incorporating the Theory of Consumption Value, this study examines the impact of health consciousness, health motivation, personal innovativeness, perceived critical mass, perceived cost, and perceived product value on the intention to consume PBM. The impact of intention to consume PBM on actual consumption is also analyzed. Furthermore, the mediating role of the intention to consume PBM in the relationship between these factors and actual consumption behavior is investigated. Using a cross-sectional research design, 978 responses were obtained from Indonesia. The data were analyzed using partial least squares structural equation modelling (PLS-SEM). The results showed that health motivation, perceived critical mass perceived cost, and perceived product value were significant predictors of the intention to consume PBM. However, health motivation and personal innovation had insignificant effects on the intention to consume PBM. Moreover, the intention to consume PBM translated into actual consumption behavior. Furthermore, the intention to consume PBM significantly mediated the relationship between actual consumption behavior and factors other than health motivation, personal innovation, and perceived product value. The findings offer valuable insights for industry, policymakers, and producers interested in PBMA markets in developing focused marketing strategies, improving consumer perceptions, and addressing barriers, such as perceived costs to promote PBM consumption, particularly in emerging markets. Integrating the theory of consumption value and PLS-SEM provides a comprehensive understanding of the underlying dynamics and sheds light on the unique factors driving PBM consumption behavior.