As the consumption of cultural and creative products (CCPs) increasingly shifts to e-commerce channels, consumers rely heavily on online visual-textual displays to perceive and compare cultural value, whereas systematic design-oriented methods for assessing such perceived value remain insufficient. To address this gap, this study proposes a hybrid method for assessing the perceived cultural value of CCPs in e-commerce visual-textual presentation. First, a three-domain indicator framework covering formal representation, usage inference, and meaning construction is developed by integrating hierarchical cultural semantics with narrative-structure organization, and refined through content validity testing. Second, a hybrid DEMATEL-CRITIC-MULTIMOORA model is used to integrate indicator influence and alternative-performance variation across indicators for weight determination, followed by multi-perspective alternative ranking. Using cultural aromatherapy burners as a case, Kendall's concordance tests reveal evident divergence in expert judgments, with W = 0.128 and p = 0.797 for indicator interaction judgments, and W = 0.414 and p = 0.066 for indicator-level assessments of alternative performance. Within this context, the model outputs should be interpreted as structured perceived cultural value assessment results aggregated from heterogeneous expert judgments, rather than as objective measurements of products' intrinsic cultural quality. External questionnaire validation demonstrates relatively high rank-order consistency between the model results and user-side assessments (Spearman's ρ = 0.829; Kendall's τ = 0.733). The proposed approach transforms implicit cultural semantic features of CCPs into observable and comparable evidence, providing a decision-support reference for competitor comparison, visual-textual presentation refinement, and CCP design practice.
Korarima (Aframomum corrorima) is a perennial aromatic herb native to Ethiopia, widely valued for its culinary, medicinal, and cultural importance. It naturally grows under shaded forest ecosystems; however, deforestation and habitat degradation have led to a significant decline in its wild populations. Despite its economic importance, consolidated information on its production systems, ecology, chemical properties, and market potential remains limited. This review systematically synthesizes existing knowledge on korarima by focusing on four key areas: its ecological requirements and distribution, agronomic and production practices, chemical composition and quality attributes, and its economic importance, including household income contribution, trade potential, and value chain characteristics. In addition, the review highlights major production and utilization constraints such as genetic erosion, limited agronomic technologies, and weak market development. The paper also outlines future prospects for sustainable production, conservation, and improved utilization of korarima as a high-value Ethiopian spice, emphasizing its role in biodiversity conservation and rural livelihood enhancement.
Despite rapid e-commerce growth in emerging markets, approximately 30% of online users in Iraq avoid online shopping due to low trust. Prior research has conflated distinct dimensions of store quality, and no study has specifically investigated how information quality, system quality, and service quality differentially influence customer perceptual attractiveness-a distinct construct comprising emotional attraction, wisdom in purchasing, and confidence when purchasing. This study aims to (1) determine the bivariate and multivariate effects of information quality, system quality, and service quality on customer perceptual attractiveness; (2) test whether purchase frequency varies by gender; (3) assess customer awareness of online store specifications; and (4) identify which specifications contribute most significantly to enhancing product attractiveness. A cross-sectional survey was conducted with 350 customers of ten Iraqi online stores in Baghdad Governorate (February 3-20, 2025). Convenience sampling with stratified targeting was employed. Data were analyzed using a two-stage approach: PLS-SEM (SmartPLS 4.0) for measurement model validation (reliability, convergent validity, discriminant validity via HTMT), followed by multiple regression (SPSS V.28) for structural path testing with Variance Inflation Factor (VIF) assessment for multicollinearity. The measurement model demonstrated acceptable reliability (Cronbach's α: 0.804-0.920; CR: 0.812-0.916) and convergent validity (AVE: 0.528-0.743). Discriminant validity was established (all HTMT values <0.85). Bivariate analyses showed significant positive effects for all three dimensions (IQ: β = 0.815, p < 0.001; SQ: β = 0.616, p < 0.001; SEQ: β = 0.787, p < 0.001). However, in multivariate analysis, information quality (β = 0.436, p < 0.001, VIF = 2.14) and service quality (β = 0.493, p < 0.001, VIF = 2.08) remained significant, while system quality became non-significant (β = -0.037, p = 0.493, VIF = 1.96). The combined model explained 67% of variance (R 2 = 0.674, F = 188.878, p < 0.001). No significant gender difference was found in purchase frequency (Mann-Whitney U = 6430.1, p = 0.442). Customer awareness of store specifications was moderate (M = 3.592, SD = 0.725 on a 5-point scale). Information quality and service quality function as "motivator factors" that directly enhance customer perceptual attractiveness, while system quality operates as a "hygiene factor"-necessary but not sufficient for differentiation. The suppression of system quality's effect in multivariate analysis is attributable to multicollinearity among the highly correlated dimensions (r = 0.62-0.71), not to theoretical irrelevance. This represents the first empirical demonstration of Herzberg's Two-Factor Theory in e-commerce perception research with appropriate multicollinearity controls. (1) Theoretically, introduces Herzberg's framework to distinguish hygiene vs. motivator factors in e-commerce; (2) Empirically, provides the first PLS-SEM analysis of e-commerce perception in Iraq with full discriminant validity and multicollinearity reporting; (3) Methodologically, demonstrates the necessity of VIF assessment when interpreting dimension-specific effects in multidimensional quality constructs.
South Korea is a highly import-dependent food economy and therefore offers a useful case for examining how an integrated national food control system can be built under trade openness, limited domestic agricultural capacity and changing consumer risk perceptions. This article presents a structured narrative review, rather than a causal impact evaluation, of South Korea's transition from multi-agency food safety regulation toward an integrated, risk-based food control system. The review is organized through the FAO/WHO national food control system framework and maps Korean legal, institutional and operational evidence onto six analytical dimensions: legal foundations, institutional coordination, risk-based official controls, import supervision, traceability and recall, and risk communication. Examples of embedded risk-analysis principles include the Positive List System for pesticide residues with a default limit of 0.01 mg/kg for substances without a Korean MRL, inspection orders and risk-ranked import controls, barcode-linked recall blocking through the Hazardous Food Sales Prevention System, and public disclosure of unsafe directly purchased overseas products. Quantitative evidence is used descriptively: Korea's agricultural and food imports reached USD 45.3 billion in 2024, hepatitis A notifications fell from 17,598 in 2019 to 3989 in 2020 after the salted-clam outbreak, and MFDS reported that 12 of 544 overseas direct-purchase products tested in the first half of 2020 contained restricted substances. These indicators suggest improvements in coordination and crisis response capacity, but they do not prove that institutional integration alone reduced foodborne disease incidence. The review finds that South Korea's model is strongest in institutional consolidation, import-oriented technical standards and digital recall communication, while key challenges remain in small-business compliance burden, scientific independence, data transparency, cross-border e-commerce and novel foods such as cell-cultured food ingredients.
Since the Convention on Biological Diversity (1992), international frameworks have emphasized benefit-sharing and private-sector engagement in conservation, a call reinforced by the Kunming-Montreal Global Biodiversity Framework (2022). Yet biodiversity continues to decline, highlighting the need for funding models that effectively link commerce with conservation. Here, we examine how the fragrance industry-a sector deeply dependent on plant diversity and cultural value chains-can contribute more meaningfully to global plant conservation. Drawing on international policy frameworks, published literature, and illustrative conservation-industry partnerships, we assess mechanisms through which fragrance-related initiatives support biodiversity protection, accountability, and culturally grounded conservation narratives. We then examine The Red List Project as a conservation-first model that integrates biodiversity objectives directly into fragranced product development, using scent inspiration rather than wild harvesting. We argue that scaling such approaches could reposition the fragrance industry as an active partner in safeguarding plant diversity, biocultural heritage, and equitable benefit-sharing.
The rise of e-commerce and social media has overwhelmed systems with image data, challenging real-time clustering and recommendation. Although multistage or large-pretrained-model (LPM) assisted clustering methods achieve high accuracy, they often suffer from large model sizes and high computational costs. Single-stage methods, while saving clustering resources, face challenges like weak augmentations limiting feature diversity and false-positives/negatives harming accuracy. We propose debiased contrastive clustering (DCC), an efficient lightweight model that addresses these issues by integrating differential augmentations, refined sampling, and debiased contrastive loss to reduce false negatives. Pseudo-labels and consistency regularization mitigate false positives, boosting accuracy without multistage training or LPM reliance. Experiments on seven challenging datasets show that DCC outperforms state-of-the-art (SOTA) methods in accuracy, normalized mutual information (NMI), adjusted Rand index (ARI), and efficiency, converging faster with superior results.
V2O5 and Fe2O3 doped phosphotellurite glasses were synthesized and investigated experimentally for density, structure, temperature and frequency dependent dielectric properties, ac conductivity and, radiation shielding parameters were computed. Electric modulus and impedance spectra exhibited a non-Debye type relaxation behavior. Conductivity master curves demonstrated that the dielectric relaxation and conductivity depend on composition and unaffected by temperature. By fitting measured conductivity to Jonscher's universal power law, conductivity (ac and dc) and frequency exponent were extracted. Conductivity and activation energy passed through maximum and minimum respectively for 0.2 mol fractions of Fe2O3 indicating occurrence of mixed transition effect. Overall electric studies suggest that the present glasses are promising candidates for energy storage devices and solid-state electrolytes. For the energy range 0.015-15 MeV, various gamma and neutron shielding parameters were computed using the Phy-X software. They were analyzed and compared with literature and found that these glasses are most useful for radiation shielding.
This study meticulously discusses spillover effects among agricultural futures (AGF), crude oil prices (CRO), and the U.S. dollar (USD) during the volatile phase of China's economic policy (CEPU), utilizing the quantile connectedness approach. The empirical findings show that, in the face of economic instabilities and tail incidents, AGF, CRO, USD, and CEPU exhibit significantly higher return spillover at extreme quantiles in comparison to mean one. Furthermore, the dynamic properties of AGF, CRO, USD, and CEPU are empirically substantiated, and certain crises obviously enhance these spillover effects. The primary innovation involves the integration of CEPU into the analytical framework of the agriculture-energy-financial system. This integration illustrates the interdependencies of the system across a variety of market conditions through dynamic quantile shifts, thereby expanding the theoretical scope. This study recommends actions for different market participants, such as an cross-nation economic cooperation and financial market tracking mechanism.
Prenatal cannabis use is increasing, and pregnant individuals often seek guidance from cannabis retailers. It is unknown whether budtender messaging varies by community social vulnerability. This cross-sectional mystery shopper study included 505 randomly selected California licensed cannabis retailers (2/26/2024-1/28/2025). Social vulnerability within a 15-minute drive-time buffer around retailers was measured by the CDC Social Vulnerability Index (SVI; range 0-1; four domains: socioeconomic status, household characteristics, racial/ethnic minority status, housing/transportation). The primary outcome was a 4-category prenatal cannabis risk communication measure: clear risk messaging [reference], mode-specific lower-risk messaging, no clear safety/risk messaging, and safety-affirming messaging. Secondary outcomes included product recommendations, fetal or infant health risks, information sources, and guidance to consult a clinician. Logistic and multinomial logistic regression models assessed associations between SVI and outcomes; SVI was multiplied by 10, so estimates reflect odds associated with a 0.1 increase in SVI. Greater household vulnerability was associated with safety-affirming messaging (OR=1.26;95%CI:1.01-1.56) and no clear safety/risk messaging (OR=1.25; 95%CI:1.05-1.50) versus clear risk messaging. Greater racial/ethnic minority vulnerability was associated with safety-affirming versus clear risk messaging (OR=1.21; 95%CI:1.00-1.47). Greater housing/transportation vulnerability was associated with mode-specific lower-risk messaging versus clear risk messaging (OR=1.42; 95%CI:1.06-1.91). Citing warnings was more common in areas with greater socioeconomic vulnerability (OR=1.23; 95%CI:1.01-1.51). Other outcomes did not differ by SVI. Budtenders in more vulnerable areas were more likely to provide safety-affirming, mode-specific lower-risk, or no clear safety/risk messaging rather than clear prenatal cannabis risk messaging. Findings highlight the need for consistent, evidence-based communication in retail settings.
Rolling bearings in agricultural machinery operate under pronounced operating-condition shifts, such as speed and load fluctuations and contamination-related noise, which often induce a distribution mismatch between training and deployment signals. This work studies bearing fault diagnosis under a source-only, single-source domain generalization (DG) setting, where the model is trained and selected using only source-domain data, and samples from the target operating condition or target dataset are not used for training, validation, hyperparameter selection, band-pass selection, or early stopping. We formulate cross-condition robustness as a semantic consistency problem between two complementary representations: an analytic mechanism-oriented representation emphasizing impact-related resonance demodulation, and a data-driven temporal representation learned from raw waveforms. A dual-path framework is developed accordingly. The analytic path learns a differentiable soft band-pass mask to localize an informative resonance band and constructs an impulse-oriented descriptor from statistics of the band-pass signal, its Hilbert envelope, and squared-envelope energy. The temporal path encodes normalized raw segments using a lightweight dilated one-dimensional convolutional network with temporal-attention pooling. The two embeddings are fused by a sample-wise gate, with an entropy penalty used to discourage near-uniform averaging. This design aims to improve cross-condition generalization by using the analytic path as a mechanism-oriented semantic anchor, constraining the temporal path through cross-view agreement, and allowing the fused representation to adapt to sample-dependent reliability changes. To reduce representation drift under regime changes, the two views are aligned using a bidirectional InfoNCE objective with a learnable temperature that adapts similarity scaling across operating conditions. A mechanism-critical control is also reported: replacing the analytic path with same-dimensional non-mechanistic features consistently degrades cross-condition performance, indicating that the analytic anchor is not interchangeable with generic auxiliary branches. Experiments on CWRU, SEU, and an agricultural-machinery-relevant test-rig dataset show in-domain accuracies of 99.48%, 98.50%, and 97.53%, respectively. In strict cross-speed evaluation on the test-rig dataset, the method achieves 98.22% accuracy when trained at 1500 r/min and tested at 2000 r/min, and 98.03% accuracy in the reverse setting. In cross-dataset evaluation using the shared normal, inner-race, outer-race, and rolling-element fault classes, the proposed method achieves the best average performance among the evaluated source-only baselines, including generic DG methods and recent bearing-diagnosis generalization methods. These comparisons include DPICEN and a protocol-matched single-source adaptation of FARNet, denoted FARNet-SS, both evaluated without target-domain access during training or model selection. The model remains lightweight, with 0.1348 M parameters and 127.11 M FLOPs for the neural forward pass.
The Northern Territory (NT) is a geographically large, sparsely populated territory in Australia. It has the highest smoking prevalence in Australia (13.3% compared to 8.3% nationwide). Although international and national studies report associations between tobacco retailer density and higher smoking prevalence, no Australian state or territory currently regulates the location or density of tobacco outlets. In this article, we map the locations of retailers licensed to sell tobacco in the NT, analyse tobacco retailer density, and explore associations between tobacco retailer density, population density, percentage of First Nations residents, geographic remoteness and area socioeconomic status. We obtained licensing data in November 2023 from Licensing NT and, using Australian Bureau of Statistics Statistical Area 2 as our unit of analysis, we geolocated retailers and used multiple regression to analyse associations between tobacco retailer density and explanatory variables, including socioeconomic status, population density, percentage of First Nations residents and remoteness. The mean tobacco retailer density in the NT was 1.81 per 1000 residents (95% confidence interval 1.38-2.23 per thousand) and tobacco retailer density increased with remoteness (p=0.02), although this relationship did not follow a strict gradient because remote areas did not show a significant increase relative to outer regional areas. In bivariate analyses, population density and percentage of First Nations residents, and remoteness were significantly associated with tobacco retailer density. In the multivariate analysis, only remoteness remained statistically significant. In the NT, tobacco retailer density increased with geographic remoteness, consistent with findings elsewhere in Australia. This finding is probably influenced by small population denominations. Compliance and enforcement are more difficult in small and geographically isolated communities, making it crucial that strategies to address tobacco supply are generated with community support. Policies should also ensure equitable access to smoking cessation support for people who are already addicted to nicotine.
Salmonella enterica serovar Typhimurium (S. Typhimurium) is a major enteric pathogen that causes severe intestinal damage, characterized by epithelial disruption, inflammation, and impaired regeneration. Nutritional intervention has emerged as a promising strategy to mitigate such injury and promote mucosal repair. Casein enzymatic hydrolysate (CEH) possesses well-documented anti-inflammatory and mucosa-protective properties. However, whether CEH exerts its protective effects against S. Typhimurium-induced intestinal injury by modulating the gut microbiota, and the underlying mechanisms, remains largely unknown. Twelve-month-old C57BL/6J mice were pretreated with streptomycin and challenged with S. Typhimurium. In the primary efficacy study, mice were assigned to four groups: control, control + CEH, model, and model + CEH (2% CEH in diet for 10 days before and throughout infection). Disease severity, intestinal histology (H&E and PAS staining), inflammation (TNF-α and IL-10 ELISA; CD45+ flow cytometry), barrier function (E-cadherin flow cytometry; PEPT1/SGLT1 immunofluorescence), stem cell activity (LGR5/Ki67 and CD24+LGR5+ staining), Paneth cell niche factors (LYZ1/Wnt3A immunofluorescence and western blot), gut microbiota composition (16S rDNA sequencing), and luminal L-lactate levels (biochemical assay) were evaluated. To establish causality, additional mechanistic experiments were performed using exogenous L-lactate supplementation, the GPR81 inhibitor 2,5-DHBA, and the Wnt secretion inhibitor Wnt-C59, with the same panel of tests. CEH administration significantly improved survival, alleviated clinical disease severity, and attenuated systemic and intestinal inflammation. CEH preserved mucosal architecture, restored goblet cells and barrier proteins (PEPT1, SGLT1, E-cadherin), and promoted LGR5+ and CD24+LGR5+ intestinal stem cell regeneration. CEH reshaped the gut microbiota, enriched lactate-producing genera, and increased luminal L-lactate levels, accompanied by restored Paneth cell LYZ1 expression and elevated Wnt3A in the crypt niche. Strikingly, lactate supplementation improved CEH's protective effects on Paneth cell function, ISC proliferation, barrier integrity, and inflammatory cytokines. LYZ1+ Paneth cells co-expressed the lactate-sensing receptor GPR81. Pharmacological blockade of GPR81 or Wnt abrogated the beneficial effects of both CEH and lactate, confirming that CEH acts through the lactate-GPR81-Wnt3A axis. Collectively, these findings demonstrate that CEH alleviates S. Typhimurium-induced enteritis in adult mice via a microbiota-lactate-GPR81-Wnt3A-ISC axis. CEH represents a promising nutritional strategy to counteract infection-induced intestinal injury and promote regeneration in adult hosts with diminished regenerative reserve.
Sarcopenia is a prevalent age-related muscle disorder characterized by progressive loss of muscle mass and function, and chronic low-grade inflammation ("inflammaging") is recognized as a key contributor to its pathogenesis. Exercise has been proposed as an effective non-pharmacological strategy to counteract inflammation and improve muscle health; however, the anti-inflammatory effects and underlying mechanisms of different exercise modalities remain incompletely understood. This review aims to summarize and compare the effects of different exercise modalities on inflammatory responses in older adults with sarcopenia and to elucidate the potential molecular and cellular mechanisms involved. A narrative review was conducted by searching PubMed, Web of Science, and Scopus for relevant studies published in the past decade. Clinical trials and experimental studies investigating aerobic exercise, resistance training, high-intensity interval training, and combined training interventions in older adults with sarcopenia were included. Outcomes of interest focused on systemic and muscle-derived inflammatory markers, including tumor necrosis factor-α, interleukin-6, C-reactive protein, and anti-inflammatory cytokines. Aerobic exercise predominantly reduces systemic inflammatory markers and improves metabolic regulation, whereas resistance training mainly attenuates muscle-derived inflammatory signaling and promotes anabolic responses. High-intensity interval training and combined training programs appear to exert complementary effects on both systemic and local inflammation. At the molecular level, exercise-induced anti-inflammatory effects are associated with suppression of pro-inflammatory pathways such as nuclear factor-κB and toll-like receptor 4, and activation of regulatory pathways including AMP-activated protein kinase/sirtuin 1 and nuclear factor erythroid 2-related factor 2. In addition, exercise modulates myokine secretion and immune cell phenotypes, contributing to an improved inflammatory microenvironment in skeletal muscle. Different exercise modalities exert distinct but overlapping anti-inflammatory effects in older adults with sarcopenia. Understanding the specific inflammatory targets and mechanisms of various exercise interventions may facilitate the development of individualized and optimized exercise prescriptions for the prevention and management of sarcopenia.
Early differentiation of startup founders with high success potential remains a central challenge for entrepreneurship research, innovation policy, and capital allocation in high-uncertainty environments. Existing approaches rely largely on broad personality models or intention-based instruments developed primarily to explain entry into entrepreneurship rather than differentiation of founders associated with realized venture success. In this study, we introduce a domain-specific model of founder success characteristics and develop a 31-item Startup Founder Success Scale (SFSS) to differentiate realized success from entrepreneurial intent. The sample (N = 10,007) included startup founders recruited from predefined pools meeting objective funding, revenue, or acquisition benchmarks, as well as corporate managers and aspiring entrepreneurs. Exploratory and confirmatory factor analyses supported six distinct dimensions-Relentless Resilience, Value-Creating Opportunism, Intrinsic Curiosity, Courageous Decision-Making, Strategic Innovativeness, and Transformational Leadership-which together accounted for 71% of the common variance in founder-specific latent trait measures within the scale, indicating strong internal coherence. Group comparisons showed that these dimensions reliably distinguished Successful Startup Founders from Corporate Managers and Aspiring Entrepreneurs, with large effect-size separations (Cohen's d = 0.83-1.77) exceeding the small-to-moderate effects (d ≈ 0.2-0.5) typically reported for broad personality traits in entrepreneurship research. Conceptually, these findings are consistent with a multi-level framework in which founder-specific characteristics are closely aligned with decision-making under uncertainty and resource orchestration during early venture execution, helping explain why intent-based and general personality models, while valuable for understanding entrepreneurial entry, may be less closely aligned with realized startup success. Practically, the SFSS provides a validated psychometric tool that may support more structured evaluation of founder-related characteristics, targeted training, and resource allocation across venture capital, angel investing, public investment bodies, accelerators, and entrepreneurial education programs. Prospective longitudinal research is required to establish predictive validity for real-world outcomes.
The classification of fashion images is an essential task in the e-commerce sector, where accurate categorization improves user experience and refines product discovery. Convolutional Neural Networks (CNNs) and Transformers have demonstrated strong performance in image classification tasks due to their ability to learn complex visual features. However, deep variants of these architectures, such as VGG-19, ResNet-50, Vision Transformer (ViT), and Swin Transformer, contain tens of millions of parameters, requiring high memory and powerful GPUs for training, which makes them less suitable for low-resource and edge device environments. To address these limitations, this research proposes a lightweight hybrid architecture, TinyCNN with Linear Self-Attention (LSA), optimized for resource-constrained settings. The proposed model contains fewer than half a million parameters and is trainable on a CPU, achieving a classification accuracy of 91.47% on the Fashion-MNIST dataset. In addition, multiple Explainable Artificial Intelligence (XAI) techniques are implemented, including Self-Attention visualization, Multi-Head Attention, Attention Flow, Attention Rollout, Fixed query position attention maps, Integrated Gradients, LIME, and SHAP, to provide visual interpretability of the model's predictions and enhance transparency in its decision-making process.
Negative emotion differentiation-the capacity to make fine-grained distinctions between discrete negative emotions-plays a foundational role in adaptive emotion regulation, psychological well-being, and effective goal pursuit. Despite its theoretical and practical significance, research on this emotional competency within entrepreneurship remains nascent. Integrating an experience sampling methodology with a 2-year time-lagged design, this study investigated the antecedents and consequences of entrepreneurs' negative emotion differentiation. Results demonstrated that stressor variability-rather than mean levels of stressors-undermines negative emotion differentiation, which in turn positively predicts both work engagement and entrepreneurial orientation. These findings advance theoretical understanding of entrepreneurial emotions, stressor dynamics, and their downstream implications for well-being and performance outcomes.
Commercial determinants of health (CDoHs) describe how corporate practices influence population health. This scoping review aimed to characterize the extant evidence base regarding how CDoH in the sugar-sweetened beverage (SSB) industry affects health and health-related outcomes among Latinx populations in the United States of America (USA). The present study was conducted in accordance with the JBI methodology for scoping reviews. Overall, 1236 references were identified and imported for screening. After duplicate removal, screening, and full-text eligibility assessment, 33 studies met all inclusion criteria. SSB marketing and advertising was the most frequently examined CDoH (61%), including advertising exposure, messaging strategies, and warning label interventions. SSB taxation studies projected reductions in consumption and obesity prevalence. Outcomes associated with health focused primarily on perceptions of marketing and purchasing intentions (94%). Additional studies examined the impact on knowledge, attitudes, beliefs, and behaviors (e.g., purchasing and consumption of SSBs) (66%), while a few studies included chronic disease (27%) or healthcare outcomes (6%). Evidence highlights several gaps in CDoH research associated with SSBs, with 94% of the included studies focused on understanding marketing exposure, signaling a need to examine other domains of CDoH, SSB industry practices, and impacts on health disparities. Findings suggest that structural policy interventions such as taxation and stronger regulation of commercial practices are necessary to address higher exposure to marketing and consumption of SSBs among Latinx populations in the USA.
Changes in orthodontic devices and how they are distributed to patients have created competition in the marketplace of orthodontic services. This study was undertaken to analyze the factors influencing patients' advertising preferences when they are selecting an orthodontic treatment provider. Methods A 2-part questionnaire was distributed to residents of a midwestern Canadian city in the form of physical copies and through an online survey platform. The first part of the survey focused on determining which types of marketing patients found to be most trustworthy, whereas the second part explored the aspects of advertising materials that were considered important by patients when choosing a provider for orthodontic treatment. Participants' age, gender and orthodontic experience, as well as the recruitment source for survey participation, were analyzed as potential contributing factors. A total of 290 participants responded. Word of mouth, online reviews and official websites of orthodontic practices were the most popular types of marketing. Social media were more popular among younger people, whereas participants recruited from local dental clinics were the least interested in interviews or articles from a newspaper, magazine or community newsletter. Participants recruited from dental clinics or a university orthodontic clinic were not interested in services offered by direct-to-consumer companies. When asked to select the types of information they considered relevant, participants frequently cited before-and-after photographs, flexible payment arrangements, provision of repairs/adjustments at no cost, the option of evening or weekend appointments, the clinician's experience and whether the clinician was knowledgeable about the latest technologies. Consumers' preferences varied according to different demographic parameters. Although the findings suggest a shift away from some traditional modalities of advertisement, word of mouth and clinicians' expertise remained important to survey participants.
Skin cancer presents a significant global health burden with rising incidence. The side effects of current therapies and the emergence of drug resistance necessitate the exploration of alternative and complementary strategies. Natural products, with their long history of use in treating skin disorders, have emerged as a promising source of novel therapeutic agents. This review comprehensively elucidates the potential efficacy of natural bioactive compounds in both preventing and treating skin cancer. We summarize the molecular mechanisms through which key natural bioactive compounds exert their anti-skin cancer effects, including induction of apoptosis, inhibition of proliferation and metastasis, anti-inflammatory and antioxidant activities, DNA damage repair, and photoprotection. Furthermore, we discuss the biological barriers relevant to skin cancer therapy using natural bioactive compounds and link them to corresponding delivery strategies, while identifying key translational challenges. In conclusion, natural bioactive compounds offer a multi-targeted and synergistic approach against skin carcinogenesis, holding substantial promise as sources of adjuvant therapies and chemopreventive agents to improve patient outcomes.
Using a multi-source dataset of 777 Listed Companies in the Food Manufacturing Industry (LCFMI), this study examines their spatial and relational organization in China. Key findings are: 1) The geographical distribution of LCFMIs closely aligns with China's macro-economic landscape, with more developed regions hosting a greater concentration and larger scale of firms. 2) While similarity in business scope (SBS) is generally low, significant distance-decay effect is noted, particularly within "0 ~ xx km"; the resulting SBS network demonstrates small-world properties and distinct clustering patterns based on both geography and industrial sub-categories, highlighting the interplay between spatial and cognitive proximity. 3) The inter-city recruitment network, which reflects the spatial expansion of corporate influence, is predominantly shaped by transportation accessibility between cities. This research provides new empirical insights into the geographical organization of manufacturing and the formation of city networks, offering practical implications for regional industrial policy and infrastructure planning.