Search Results (641)

Background: Vaccine acceptance is a fundamental prerequisite for uptake, which may vary over time in response to contextual and vaccine-specific factors and major global disruption. This systematic review and meta-analysis evaluated global trends and determinants of vaccine acceptance between 2009 and 2024. Methods: A comprehensive literature search was conducted using pre-defined keywords and controlled vocabulary related to vaccination, vaccine acceptance or hesitancy, with a broad search strategy designed to capture global evidence across multiple vaccine categories and geographic settings. Studies restricted to high-risk groups or other specific sub-populations (e.g., healthcare workers) were excluded. Studies reporting vaccine acceptance outcomes were systematically identified and pooled estimates were calculated across vaccine categories, WHO regions, income groups, and pandemic periods. Temporal trends and interaction effects were assessed to evaluate changes in vaccine acceptance among different vaccines and before, during, and after the COVID-19 pandemic. Results: A total of 264 publications, including 650,772 participants from 97 countries, were included. Overall, pooled vaccine acceptance was 70.63% and remained relatively stable throughout the study period. Most studies originated from high-income countries, whereas low-income countries and the African region were underrepresented. Childhood vaccines demonstrated the highest pooled acceptance (80.26%), followed by HPV vaccines (66.48%), while influenza vaccines showed the lowest acceptance (52.00%). Childhood vaccine acceptance increased over time and during the COVID-19 period, whereas significant negative interaction trends were observed for HPV and influenza vaccines. Higher vaccine acceptance was observed in African and South-East Asian regions compared with Western Pacific and European regions. Acceptance also varied across income groups, with greater hesitancy generally observed in higher-income settings. Conclusions: Vaccine acceptance among the general population remained relatively stable globally between 2009 and 2024 but varied substantially by vaccine categories, geographic regions, and economic settings. These findings highlight the context-specific nature of vaccine acceptance and the need for harmonized measurement tools and stronger evidence from underrepresented regions to support equitable immunization strategies. Full article

The chemical composition of chocolate is influenced by multiple factors, including cocoa genotype, fermentation, roasting, and formulation, which complicate the identification of reliable compositional descriptors. In this study, amino acid and biogenic amine profiles were determined by LC–MS/MS in 91 commercial dark chocolates (56–100% cocoa content) to assess their potential for product characterization. Because the analytical sequence extended over several days, different signal-correction strategies (including internal standard normalization and quality-control-based drift correction) were evaluated to compensate for instrumental variability prior to chemometric analysis. Signal reductions of up to 91% were observed, and the selected correction procedures improved measurement precision by up to 18-fold. A total of 19 amino acids and 8 amines were detected, with tyrosine, hydroxyproline, proline, leucine, phenylalanine, and valine being the most abundant compounds. Principal Component Analysis revealed a compositional gradient primarily associated with cocoa content, whereas classifications based on cocoa variety, geographical origin, and certification status showed limited discrimination. In contrast, Partial Least Squares-Discriminant Analysis achieved a balanced classification accuracy of 75.2% under repeated M-fold cross-validation when classifying samples according to manufacturer. Furthermore, permutation tests were carried out, confirming that the observed classification performance was highly unlikely to arise by chance. These findings indicate that amino acid and biogenic amine profiles in commercial dark chocolates are influenced mainly by cocoa content and manufacturer-related factors, whereas the effects of cocoa origin and variety appear less evident within the products evaluated. Full article

Human skin is continuously exposed to microbial invasion and oxidative stress, highlighting the need for safe and effective natural skin-protective agents. This study aims to investigate the antibacterial, antioxidant, and anti-tyrosinase activities of methanolic leaf extracts of Syzygium nervosum collected from Chiang Mai (SNLM-CM) and Phayao (SNLM-PY), Thailand. LC–QTOF–MS analysis revealed distinct phytochemical profiles between the extracts, suggesting that geographical origin influenced their biological activities. Antibacterial activity against Staphylococcus aureus, Staphylococcus epidermidis, Pseudomonas aeruginosa, and Escherichia coli was evaluated, together with studies of bacterial membrane integrity. Antioxidant capacity was assessed using ABTS, DPPH, FRAP, and ORAC assays, while anti-tyrosinase activity and cytotoxicity toward normal human dermal fibroblasts (NHDF) were determined by MTT assay. Both extracts exhibited potent antibacterial activity, particularly against Gram-positive bacteria (S. aureus and S. epidermidis) likely through membrane disruption, as evidenced by propidium iodide uptake, intracellular DNA and protein leakage, and scanning electron microscopy observations. SNLM-CM showed stronger antioxidant activity, whereas SNLM-PY demonstrated greater anti-tyrosinase activity. The extracts maintained high NHDF viability at concentrations below 100 µg/mL and retained antibacterial efficacy when incorporated into a cleansing gel formulation. Overall, S. nervosum leaf extracts exhibit promising antibacterial, antioxidant, and anti-tyrosinase activities, warranting further investigation to optimize their safety and efficacy for dermatological and cosmetic use. Full article

Metagenomic analysis of extreme environments is essential in biotechnological research. This work aimed to determine and compare the microbial diversity of two Peruvian saline environments and characterise their functional profiles. Soil metagenomic DNA (mDNA) was analysed from Maras and Pilluana salterns, both with a thalassohaline origin but with different geographical and environmental conditions. Maras samples exhibited more diversity and a remarkably higher abundance of archaea (phylum Euryarchaeota). The most dominant bacterial phyla across all the samples were Pseudomonadota and Actinomycetota. Multiple pathways specific to archaea were more abundant in Maras, as were pathway-related synthesis and degradation of compatible osmolytes such as glycine betaine and ectoine. The most abundant pathways in Pilluana were associated with fatty acid biosynthesis and oxidation. A total of 49 and 47 metagenomic-assembled genomes (MAGs) were retrieved from Maras and Pilluana samples, respectively. Bacterial MAGs were mainly classified within the phyla Psudomonadota, Actinomycetota, Planctomycetota, and Gemmatimonadota. Additionally, a total of 20 putative aminotransferases class III (ATs, PF00202) from Maras3 were cloned and expressed in E. coli Rosetta, and their substrate scoping was assayed against several aldehyde and ketone substrates; AT pQR3082 and pQR3090 showed unique broad substrate acceptance for aromatic and aliphatic substrates. Our study provides new insights into the microorganisms and metabolic pathways of these unique extreme environments, highlighting the promising biotechnological potential of metagenomic ATs. Full article

Based on the elemental composition of 359 samples of dry wines (Riesling, Chardonnay, Muscat, Cabernet Sauvignon, and Merlot) produced in the Krasnodar Territory (Russia), the influence of data clustering on the generalizing properties of neural network models for solving classification problems was studied. Clustering as a property of predicted classes being compact and separate from each other was evaluated using scatterplots of canonical values from discriminant analysis and the Silhouette Score, Calinski-Harabasz, Davies-Bouldin, and Dunn metrics. With a decrease in data clustering, the generalization properties of neural network models decrease despite an increase in dataset size. Since the predictive properties of neural networks are primarily correlated with the clustering of data, it seems logical to say that their growth will occur when “quantity turns into quality”, that is, clustering will increase with increasing dataset size. The validity of the assumption explains the polarity of trends observed in literature. With the growth of training datasets, some researchers record improvements in the predictive properties of models, while others record deterioration. The results obtained are of great practical importance, as they indicate the unsuitability of unlimited data accumulation and allow optimizing the costs of collecting it, which is important, especially for food quality control. Full article

Geographical traceability of rice is critical for authenticity identification and quality control, yet it poses considerable challenges for tracing origins in adjacent small-scale producing areas. To explore the causes of metabolic differences and geographical traceability potential of rice from adjacent small-scale producing areas, non-targeted metabolomics combined with multivariate statistical analysis was employed to systematically investigate the metabolic profiles of rice from Panjin (PJ), Donggang (DG) and Yingkou (YK) in Liaoning Province. The characteristic metabolic markers for each producing area were screened, and the effects of climatic and soil factors as well as their interactive effects on grain metabolite composition were elucidated. The results showed that the partial least squares-discriminant analysis (PLS-DA) model established based on differential metabolites achieved acceptable discrimination among rice samples from the three regions. With variable importance in projection (VIP) > 2.0 as the screening threshold, the core characteristic markers of each producing area were determined: PJ is LPC 17:2, LPA 18:3, D-(+)-Arabitol, DG is 2′-Deoxyadenosine, LDGTS 18:2, and YK is LPE 17:2; the markers are mainly primary metabolites, including lipids, sugar alcohols and nucleotides. Sunshine duration, air humidity, wind conditions and soil layer temperature were highly correlated climatic drivers responsible for metabolic differentiation, and characteristic metabolic markers from different producing areas exhibited distinct meteorological response patterns. Soil physicochemical properties and mineral elements significantly affected the differential accumulation of metabolites, among which soil Sr element and organic matter exhibited crucial indicative significance for metabolic variation of rice in adjacent regions. Multi-factor interaction analysis verified significant synergistic coupling effects between regional climate and soil environment. Meteorological factors, including sunshine, wind and soil temperature, together with soil chemical factors involving organic matter, pH, Sr, K and Ca, were identified as core driving factors for the spatial differentiation of region-specific rice metabolites. The present study provides theoretical support at the metabolic level for the construction of a small-scale rice geographical traceability system and the mechanism research on the regional quality formation of rice. Full article

To establish the relationship between the composition of wine and its regional origin, the most stable chemical parameters are selected because their variation is easiest to trace. Together with “classical” micro- and macroelements, rare earth elements (REEs) can be used for such purposes. However, the relationship between REE content in wine and its regional origin has not been systematically studied. This study examines the migration of REEs in the “soil-grape-wine” system to identify the relationship along the entire chain and establish the geographical origin of grapes and wine. The research was carried out on grapes and wines from the Chardonnay and Cabernet Sauvignon varieties, as well as soil samples selected from different vineyards. The concentrations of La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu in the studied samples were determined using ICP-MS. It was established that the studied soil samples are characterized by relatively low REE concentrations. Low transfer of REEs from soil to grapes was observed because the soils are rich in clay minerals that firmly retain these elements. Statistically significant differences in the REE content of grapes from different regions were detected (p < 0.05). Multidimensional analysis methods allowed us to group grape samples into clusters based on varietal and regional origin. Discriminant analysis showed the possibility of using the concentration of REEs as markers of the geographical origin of grapes. Of all the REEs, only La and Ce are reliably established in all wines. When determining the geographical origin of wine, the use of REE content is limited due to their very low concentrations in wine. In this regard, it has been proposed to use them in combination with macro- and microelements, which improves the classification performance of the model. Full article

Waterborne, water-related, and foodborne infectious diseases remain preventable causes of mortality, but long-term evidence on their demographic, spatial, and premature mortality burden is limited in Costa Rica. This ecological population-based study described deaths classified under selected ICD-10 codes during 2000–2023 using official mortality and population data. Crude and age-standardized mortality rates, years of life lost (YLL), and YLL rates were estimated by time, sex, age group, and geographic area. A total of 2450 deaths were identified. Diarrhea and gastroenteritis of presumed infectious origin accounted for 1537 deaths (62.7%), followed by other bacterial intestinal infections (23.8%) and leptospirosis (7.0%). Annual crude mortality rates ranged from 1.28 per 100,000 population in 2021 to 3.03 in 2017. Mortality showed a bimodal age pattern, with the highest rate among persons aged 75 years or older and a relevant early-childhood component. A total of 57,625.5 YLL were estimated, with the largest burden among children aged 0–4 years and the highest provincial YLL rates in Limón, Puntarenas, and Guanacaste. These findings support incorporating premature mortality metrics into environmental health surveillance, although the ecological design does not identify exposure sources or causal determinants. Full article

Economic well-being is essential for assessing sustainability of human settlement in urbanizing regions; however, the geographic factors linking settlement characteristics to residents’ well-being remain underexplored, particularly in counties in China undergoing urban–rural transformation. In this study, six representative Chinese counties (Yanshou, Wafangdian, Bazhou, Yugan, Yongsheng, and Raoping) with varying urbanization levels are investigated to establish a multidimensional evaluation framework and reveal the geographic factors underlying economic well-being. Through original household surveys conducted across these six geographically and economically diverse counties, we collected primary data from 1659 households; these data provide unique insights into residents’ lived experiences. By integrating these original survey data with objective indicators from statistical yearbooks and geographic features from multisource spatial data, key drivers were identified using Pearson correlation and random forest models. The results show the following trends: (1) significant county-level variation in subjective well-being, with Wafangdian ranking the highest and Bazhou ranking the lowest, while well-being aligned more closely with economic development levels; (2) income and happiness were the dominant determinants of subjective well-being, with work-related factors also contributing substantially, whereas nighttime light intensity, building density, and construction land area drove fusion well-being; and (3) multifactor modeling demonstrated strong explanatory power for fusion well-being (training set R² = 0.8313; validation set R² = 0.7531), indicating generalizability. The primary data collection across varied settlement settings provides strong empirical grounding. The findings reveal the spatial differentiation of economic well-being in urbanizing settlements, offering empirical support for targeted settlement planning and urban governance policies to improve sustainability and residents’ well-being in developing countries. Full article

Mangosteen peel (Garcinia mangostana L.) is widely recognized as a rich source of xanthone derivatives, particularly α-mangostin, which exhibits diverse pharmacological activities and is increasingly utilized in herbal medicines and nutraceutical formulations. This study aimed to develop an integrated chemical fingerprinting approach combining chromatographic quantification and spectroscopic profiling to discriminate and evaluate the quality of GMP (Garcinia mangostana peel) extract collected from different Indonesian provinces. Ethanolic extracts of GMP, originating from ten distinct geographical regions, were subjected to high-performance liquid chromatography (HPLC) for the quantitative determination of α-mangostin. Fourier transform infrared (FTIR) spectroscopy was employed to generate characteristic fingerprint profiles and assess the functional group patterns present in the extracts. The correlation between chromatographic data and spectroscopic signatures was evaluated to elucidate regional variability. The geographical origin of the GMP extract significantly influences its phytochemical composition and α-mangostin content. The combined FTIR–HPLC approach offers a robust and practical framework for extract differentiation, preliminary estimation of α-mangostin content, and quality assurance of mangosteen-derived raw materials intended for 6a-standardized herbal and nutraceutical products. Full article

Campylobacter jejuni (C. jejuni) is a prevalent zoonotic pathogen that poses a significant threat to global public health, causing gastroenteritis with symptoms ranging from mild diarrhea to severe complications, and is widely distributed among various animal hosts, including poultry, livestock, and wild birds. Among these, wild birds, characterized by their exceptional species diversity, high mobility, and long-distance migratory behavior, are capable of disseminating infectious agents across geographic regions and ecological settings. However, wild birds are increasingly recognized as potential carriers, research on C. jejuni in these hosts remains nascent and fragmented, and a unified understanding has yet to emerge. Therefore, this review synthesizes current knowledge on the prevalence patterns, key determinants, and genetic and transmission characteristics of wild bird origin C. jejuni, aiming to provide a foundation for subsequent in-depth evaluation of the public health significance of C. jejuni derived from wild birds. Full article

The chemical composition and perceived quality of wild ginseng (WG) are influenced by its geographical origin, yet clear chemical criteria for origin authentication remain lacking, and this problem is further complicated by the confounding effect of growth year. In this study, volatile and non-volatile fingerprints of 15- and 20-year-old WG from Huanren, Tonghua, and Ji’an (China) were characterized using HS-GC-IMS and HPLC. Partial least squares discriminant analysis (PLS-DA) models constructed separately for each growth-year group achieved complete origin separation of volatile fingerprints, with ten shared VIP markers identified. However, none maintained a consistent origin ranking across years, suggesting that the geographical signal may reside in the multivariate patterns. Ginsenoside profiling revealed a hierarchical candidate marker system: Rf, Rg1, Rc, Rb2 as robust candidate markers for Huanren, and Re as a 20-year-specific discriminator for Tonghua. The pervasive origin × growth year interaction observed across both volatile and non-volatile fractions indicates that growth-year-specific chemometric models are a necessity for reliable WG origin authentication. A practical two-step workflow—growth year determination followed by age-matched origin assignment—is proposed. These findings provide a scientific foundation for the geographical traceability and quality evaluation of WG. Full article

Background/Objectives: This study aims to establish a systematic phytochemical characterization and quality evaluation method to systematically evaluate the influence of multiple factors on the chemical composition of Taxillus chinensis, thereby providing a scientific basis for its development, utilization, and quality control standards. Methods: To ensure a targeted and representative metabolic screening, six representative batches covering the major geographical origins and host plants were selected for initial metabolomic profiling. An integrated analytical approach combining UPLC-MS/MS-based widely targeted metabolomics, HPLC fingerprinting, and multi-component quantitative analysis with multivariate statistical analysis was employed. Results: Significant quality variations were identified across the samples. Metabolomics results indicated that while chemical component types were qualitatively consistent across growth conditions, their contents varied significantly. Unique differential metabolites clustered according to specific geographical origins or host plants. KEGG pathway analysis revealed that geographical origin primarily regulated phenylpropanoid biosynthesis, whereas host differences mainly influenced flavonoid and monoterpenoid biosynthesis. Furthermore, HPLC fingerprinting of 20 batches demonstrated similarities greater than 0.9, with 15 common peaks determined. Based on their high relative abundance, differential significance across samples, and documented pharmacological relevance to the herb’s traditional efficacy, six bioactive components—gallic acid, catechin, epicatechin, hyperoside, isoquercitrin, and quercitrin—were identified and quantified. Notably, samples originating from Wuzhou exhibited the highest total content of these components. Consistent with PCA and HCA results, gallic acid, hyperoside, isoquercitrin, and quercitrin were identified as potential markers driving quality differences. Conclusions: This integrated approach allows for a systematic analytical screening of Taxillus chinensis, clarifying chemical variations caused by environmental and biological factors, and supporting the standardization and comprehensive utilization of this medicinal plant. Full article

Background/Objectives: Early recurrence after curative-intent resection is a major determinant of poor prognosis in hepatocellular carcinoma (HCC). Artificial intelligence (AI)-driven predictive models have emerged to identify patients at high risk of recurrence but remain incompletely synthesized for early recurrence specifically. This review aimed to identify and appraise AI-driven models predicting early recurrence after surgical resection. Methods: PubMed/MEDLINE, Scopus and Web of Science were searched from inception to November 2025. Eligible studies developed and evaluated AI-driven models predicting early recurrence (≤24 months) after curative-intent hepatectomy as first-line treatment for HCC. Risk of bias and applicability were assessed using PROBAST+AI, and findings were synthesized narratively due to methodological heterogeneity. The review was registered in PROSPERO. Results: Thirty-six studies involving 14,716 patients were included. Most studies originated from China (33/36, 91.7%), were single-center (27/36, 75%), and retrospective (35/36, 97.2%). Magnetic resonance imaging (MRI) was the predominant imaging modality (15/36, 41.7%), followed by computed tomography (CT) (11/36, 30.6%) and ultrasound (US)/contrast-enhanced ultrasound (CEUS) (6/36, 16.7%). Three studies developed non-imaging models, and one combined CT and MRI. In within-study comparisons, multimodal models generally showed better discrimination than unimodal approaches. Peritumoral, habitat-based, and multiphasic strategies appeared promising. However, external validation was reported in only 6/36 studies (16.7%), calibration and decision-curve analysis were inconsistently reported, and most studies had high risk of bias. Conclusions: AI-driven models show potential to predict early recurrence of HCC after curative-intent resection. Nevertheless, evidence remains limited by methodological heterogeneity and restricted geographical diversity, while clinical utility remains inconsistently evaluated, and no model has yet been generalized in clinical practice. Prospective multicenter studies with standardized outcomes, transparent reporting, and external validation are needed for clinical implementation. Full article

This study investigated the influences of geographical origin, harvest season, and plucking position on the chemical composition and flavor characteristics of Hainan Dayezhong black tea. Systematic analysis of basic components, volatile profiles and metabolomes of tea samples collected under different pre-harvest conditions revealed significant variations in polyphenols, flavonoids and catechins, as well as distinct differences in volatile composition. Key aroma-active compounds identified were nerolidol, linalool, benzaldehyde, benzeneacetaldehyde and methyl salicylate, which were determined to be decisive for the characteristic aroma profile of Dayezhong black tea. Untargeted metabolomics further demonstrated that these factors do not merely alter individual metabolite levels, but also reprogram energy metabolism, carbon–nitrogen allocation, and secondary metabolic pathways, resulting in distinct metabolic signatures among samples. From a systematic chemical perspective, this study elucidates the metabolic basis of Hainan Dayezhong black tea quality formation and establishes a scientific foundation for targeted quality optimization through regulation of key components. Full article