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Distinguish the geographical origin of the pear is important due to the increasingly valued brand protection and reducing the potential food safety risks. In this study, the profiles of stable isotopes (δ13C, δ15N, δ2H, δ18O) and the contents of 16 elements in pear peer from four production areas were analyzed. The δ13C, δ15N, δ2H, δ18O and 12 elements were significantly different (p < 0.05) in the four production areas. Chemometrics analysis including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and linear discriminant analysis (LDA) were exploited for geographical origin classification of samples. OPLS-DA analysis showed that crucial variables (δ13C, δ18O, δ2H, Ni, Cd, Ca, δ15N, Sr and Ga) are more relevant for the discrimination of the samples. OPLS-DA achieved pear origin accuracy rates of 87.76 % by combining stable isotope ratios and elemental contents. LDA had a higher accuracy rate than OPLS-DA, and the LDA analysis showed that the original discrimination rate reached to 100 %, while the cross-validated rate reached to 95.7 %. These studies indicated that this method could be used to assess the geographical discrimination of pear from different producing areas and could potentially control the fair trade of pear in fruit markets.

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Previous research ignored the characteristics of environmental, social, and governance (ESG). ESG is soft information. Geographical proximity is important for external stakeholders to monitor firms' soft information. This study examines the impact of customer geographic proximity (CGP) on firms' ESG performance. We hand-collect data on the geographical distance of 29,111 pairs of Chinese A-share listed companies and their top-five customers from 2009 to 2022. First, we find that CGP promotes firms' ESG performance. The results still hold after considering the exogenous influence of the introduction of high-speed rail on CGP. Second, cross-sectional analysis shows that CGP exerts a more pronounced influence on firms with severe information asymmetry. Third, impact channel tests indicate that CGP promotes firms' ESG performance by increasing firms' cash flows. Fourth, the impact of CGP is more obvious when customers have stronger risk management motivation. Collectively, this study provides new insights into factors affecting firms' ESG performance.

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Staphylea bumalda (SHC) and Staphylea holocarpa (PGG) were recognized as geographical indication agricultural products due to unique flavor. 1218 differential non-volatile compounds and 536 differential volatile compounds were detected and identified through UPLC-MS/MS and HS-SPME-GC-MS methods. In SHC samples, catechins, epicatechins, proanthocyanidins, quinic acid derivatives, and kaempferol glycoside derivatives were the main flavor compounds, with bitter and harsh taste. L-tartaric acid, citraconic acid and citric acid were contributed to increase acidity. 4-Hexen-1-ol acetate, butanoic acid butyl ester, 3-Hexen-1-ol acetate, (E)-, and 3-Hexen-1-ol acetate, (Z)- were identified as characteristic odor compounds with strong floral, fruity and sweet odor. In PGG samples, epicatechin gallate, quercetin glycoside derivatives, L-histidine, and L-tyrosine were the leading contributors to bitter and harsh taste. The spicy, herbal, and bad smell odor were mainly brought by 2-octanol, and 3-Octen-1-ol, (Z)-. Our results offered comprehensive insights into the flavor and quality characteristics differences between PGG and SHC.

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The article by Leone et al. (2024) highlights the significant barrier of transport costs in accessing headache care for HIV-positive patients in Malawi, a concern that resonates with challenges observed in opioid agonist therapy (OAT) in Taiwan. This letter draws parallels between the findings of Leone et al. and the Taiwanese experience, where distance to treatment centers has been shown to influence patients' choice of OAT. The discussion underscores the importance of expanding healthcare service availability and exploring telemedicine as potential solutions to mitigate geographical barriers. Integrating these approaches could improve patient retention and treatment outcomes in both regions. This commentary emphasizes the broader implications of transport-related barriers in healthcare access, advocating for strategic interventions to enhance healthcare delivery in resource-limited settings.

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Panax ginseng C.A. Meyer, known as the "King of Herbs," has been used as a nutritional supplement for both food and medicine with the functions of relieving fatigue and improving immunity for thousands of years in China. In agricultural planting, soil environments of different geographical origins lead to obvious differences in the quality of ginseng, but the potential mechanism of the differences remains unclear. In this study, 20 key differential metabolites, including ginsenoside Rb1, glucose 6-phosphate, etc., were found in ginseng from 10 locations in China using an ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS)-untargeted metabolomics approach. The soil properties were analyzed and combined with metagenomics technology to explore the possible relationships among microbial elements in planting soil. Through Spearman correlation analysis, it was found that the top 10 microbial colonies with the highest abundance in the soil were significantly correlated with key metabolites. In addition, the relationship model established by the random forest algorithm and the quantitative relationship between soil microbial abundance and ginseng metabolites were successfully predicted. The XGboost model was used to determine 20(R)-ginseng Rg2 and 2'(R)-ginseng Rg3 as feature labeled metabolites, and the optimal ginseng production area was discovered. These results prove that the accumulation of metabolites in ginseng was influenced by microorganisms in the planting soil, which led to geographical differences in ginseng quality.

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Background and Objective: The healthcare-seeking behavior of vulnerable groups, such as children under five, depends on a multitude of factors, including the caregiver's decision making. Approximately 60% of Indians seek care from private hospitals. Recent health policy in India has favored the establishment of multispecialty hospitals. However, it remains unclear to what extent this policy has changed the number of Indians seeking healthcare from these government-established multispecialty hospitals. The study aims to assess the health-seeking behavior of parents of children under five in the vicinity of a public multispecialty tertiary care hospital. Methods: This was a community-based cross-sectional survey with geospatial mapping conducted among the parents of children under five using a semi-structured questionnaire in Epi-collect mobile app. The study site was an urban slum in a catchment area [within five kilometers (km)] of a multispecialty tertiary care public hospital in the central Indian state of Chhattisgarh. The study was conducted for one year duration from February 2019 to January 2020. A questionnaire was administered to the parents of the children under five (N = 353) after their household confirmation from the nearby Anganwadi center, the community level service providing center under the Integrated Child Development Scheme by the Ministry of Women and Child Development (WCD). The questionnaire included sections for demographic characteristics, the illness pattern among their children, health-seeking decision-making, and more. Descriptive analysis was presented with numbers and percentages. Univariate analysis was used to assess the association between sociodemographic variables and health-seeking characteristics. Statistical significance was considered at p value less than 0.05. We used geospatial mapping using coordinates collected and compiled using the Microsoft Excel version 2021 and analyzed using QGIS (Quantum Geographic Information System) software. Results: Among the parents interviewed patients (N = 353), maternal literacy rates were over 85%. Approximately 54% of the families were below poverty line. Among 95.2% of the families, mothers were part of decision-making regarding their children's health-seeking. Over 92% of the families opted for consultation in a nearby private hospital or dispensary. Geospatial mapping of private hospitals was a favored place for healthcare-seeking by mothers, irrespective of their socioeconomic status or education rather than multispecialty hospital. Conclusion and Global Health Implications: The majority of the parents in the vicinity of public multispecialty hospitals seek care from private clinics for ailments for children under five. The establishment of public multispecialty tertiary care hospitals, which are mandated for tertiary level of care and research, cannot replace primary-level healthcare institutions, showed that private hospitals were the favored places healthcare seeking by mothers. These primary-level institutions are critical for the management of common ailments for children under five near home and reducing the financial burden on the family, even in the vicinity of a multispecialty hospital.

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Background: Although dementia incidence has decreased in high-income countries, it is important to monitor the prevalence of dementia and identify potential underdiagnosis in population subgroups. This study provides the most up-to-date prevalence of dementia diagnosis in Sweden, by geographical regions and sociodemographic groups. Methods: We identified all individuals aged ≥62 years, registered and alive in Sweden at the end of 2022 (n = 2.48 million). Dementia diagnoses were identified using ICD-9/10 codes in the National Patient Register since 1987, as well as anti-dementia drug use from the Prescribed Drug Register since 2005. Findings: At the end of 2022, 3.7% (92,293/2,483,798) of people aged ≥62 years in Sweden had a dementia diagnosis from specialist care or drug prescriptions and varied from 0.6% in ages 62-69 to 14.8% in ages ≥90. The prevalence of cognitive impairment diagnosis was 2.5%. There was some geographical variation in the prevalence of dementia diagnosis, with a larger proportion of diagnoses coming from drug prescriptions than from specialist care in northern Sweden. While people born abroad and people without a close relative had a slightly higher prevalence of dementia diagnosis than Swedish born and those with close relatives, the prevalence was substantially lower for people living alone than for cohabiting individuals. Interpretation: Comparing case estimates from previous screening cohorts, our results suggest underdiagnosis of dementia in the general older population, particularly among people who live alone. In more rural areas with lower availability of memory clinics, primary care may play an important role in diagnosing older adults with dementia. Funding: Swedish Research Council for Health, Working Life and Welfare; Swedish Research Council; Region Stockholm.

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Ticks of the Amblyomma maculatum (Ixodida Ixodidae) complex, the Amblyomma cajennense (Ixodida Ixodidae) complex and Amblyomma ovale (Ixodida Ixodidae) are known to transmit various Rickettsia species in Colombia, but their exact distribution is unknown. We built several models based on current climate and projected future climate changes using a maximum entropy approach. A total of 314 records of the A. cajennense complex (65.9%; n = 207), A. ovale (22.9%; n = 72), and the A. maculatum complex (11.1%; n = 35) were obtained. Amblyomma ovale has a current distribution in the Pacific, Caribbean and Andean regions and could be potentially found in the Amazon. Amblyomma maculatum has a current distribution in the Andean and could potentially be found in the Caribbean and Orinoco regions. Amblyomma mixtum can be found near the Caribbean Sea and in the Pacific region, and A. patinoi is likely to be found in the Andean region and the Caribbean. In 2070, it will be possible to find an expansion of A. ovale and A. maculatum and a decrease of A. mixtum and A. patinoi. The variables that best predict the distribution of these species are isothermality (small fluctuations in temperature) and annual precipitation. Amblyomma cajennense s.l and A. ovale, A. cajennese s.l and A. patinoi, as well as A. maculatum and A. patinoi, have an important environmental sympatry. Epidemiological and acarological surveillance is crucial to investigate rickettsiosis caused by R. parkeri in A. ovale regions, by R. rickettsii in A. patinoi and A. mixtum areas, and by R. parkeri s.s in A. maculatum regions.

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This study aims to assess the prevalence of Autism Spectrum Disorder (ASD) and its treatment. The study population was children aged 3-17 years with information on current ASD from National Survey of Children's Health, 2016-2022. Analysis of treatment was also conducted within the population of children with a current ASD diagnosis. A multivariate log-binomial regression model was used to assess the change of current ASD prevalence and ASD treatment by two study period (prior to COVID-19 pandemic: 2016-2019; during COVID-19 pandemic: 2020-22) and sociodemographic information. Compared to the current ASD at 2.5% in 2016, it increased to 3.6% in 2022. The treatment has decreased from 70.5% in 2016 to 61.6% in 2022 for any treatment and from 27.2% in 2016 to 20.4% in 2022 for medication treatment. Compared to children from 2016-2019, children from the following group were more likely to have ASD diagnosis during the pandemic (2020-2022), including those aged 3-5 years (aPR = 1.66, 95%CI 1.29-2.13), non-Hispanic white children, children from family with above national family income, and those with private insurance. However, medication treatment almost halved during the pandemic for non-Hispanic black children (aPR = 0.49, 95%CI 0.26-0.93) and children born overseas. In conclusion, higher prevalence of ASD might indicate a better awareness of ASD. The reduction in treatment correlates to the health service disruption caused by the pandemic, highlighting the needs of policy efforts to improve treatment for ASD.

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This paper aims to analyse the social selectivity of internal movers in six European countries, by examining the influence of education and social origin on the likelihood of moving. The study, using ShareLife data, reveals country-specific variations in social selectivity. France and Poland show a skilled selection of internal movers, where education is the primary factor affecting the likelihood of moving, with no additional effect of social origin. In Germany and Sweden, internal movers are selected based on their social origin as well as education, but this double selection differs between the two countries, with a boosting scenario in Germany and a systematic effect of social origin in Sweden, regardless of educational level. Finally, in Spain and Italy, the social selectivity of movers is less evident. Overall, the study highlights the importance of considering the interplay of education and social origin in understanding the social selectivity of internal movers.

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OBJECTIVES: The regional population mortality patterns in China exhibit substantial geographical distribution characteristics. This paper aims to explore the impact and mechanisms of geographical environmental factors on regional population mortality patterns. METHODS: This study first utilized the data from China's Seventh Population Census to obtain mortality patterns for the 31 provincial-level administrative regions. Subsequently, a functional regression method was employed to explore the geographical environmental driving factors of regional mortality patterns. RESULTS: The study provides a detailed explanation of the mechanisms and marginal contributions of key geographical environmental factors at different age groups. CONCLUSIONS: (1) The impact of geographical environmental factors on mortality patterns shows distinct phased characteristics. Mortality patterns before the age of 40 years are hardly influenced by geographical environmental factors, with a noticeable impact beginning at ages 40-69 years and reaching the maximum influence after the age of 70 years. (2) In mortality patterns at ages 40-69 years, average altitude have the most substantial impact, followed by extreme low-temperature days and PM2.5 concentration. In mortality patterns at ages 70-94 years, high-temperature days have the greatest influence, followed by the impact of SO2 concentration. (3) In comparisons based on gender, socioeconomic factors, and geographical environmental factors, gender and urban-rural differences have the most significant impact on regional population mortality patterns, followed by the influence of other socioeconomic factors, with geographical environmental factors having a relatively smaller impact.

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BACKGROUND: Eclampsia and pre-eclampsia rank as the third leading causes of maternal death in Ecuador, following pre-existing chronic diseases and postpartum haemorrhage, as reported by the Ecuadorian National Institute of Statistics and Census (INEC). In contrast, HELLP (Haemolysis, Elevated Liver enzymes, Low Platelet count) syndrome remains underexplored epidemiologically, not only in Latin America but globally. This study marks the first population-based investigation into HELLP syndrome incidence and mortality in Ecuador, examining geographical variations, altitude influences and ethnic backgrounds. METHODS: Conducted as a retrospective population-based cohort study from 2015 to 2017, this research delves into the incidence, risk factors and maternal mortality associated with HELLP syndrome in Ecuador. Utilising data from INEC and the Ecuadorian Ministry of Health, we identified HELLP syndrome cases through ICD-10 (International Classification of Diseases, tenth revision) coding in hospitalised individuals. Logistic regression analysis was employed to explore association, whilst geospatial statistical analysis focused on cantons to identify significant spatial clusters. Primary outcome measures include HELLP syndrome incidence and maternal mortality, supplying crucial insights into the syndrome's impact on maternal health in Ecuador. RESULTS: The incidence of HELLP syndrome is 0.76 (0.69-0.84)/ 1000 deliveries. Afro-Ecuadorian communities have a higher risk (Odds Ratio (OR) = 2.18 (1.03-4.63)) compared to Indigenous Ecuadorian communities. Living at mid-level or high altitude is a significant risk factor OR of 2.79 (2.19-3.55) and an OR 3.61 (2.58-5.03), respectively. Being an older mother was also identified as a risk factor. Women living more than 20 km from the obstetric unit have an OR of 2.55 (2.05-3.18). Moreover, we found that cantons with higher crude HELLP syndrome incidence also have lower numbers of physicians (R = 0.503, p-value < 0.001). The mortality incidence of women with HELLP syndrome is 21.22 (12.05-20.59)/1000 deliveries with HELLP syndrome diagnoses. CONCLUSIONS: High altitude, advanced maternal age and geographical distance between residence and health centres are risk factors for HELLP syndrome. Maternal mortality in women with HELLP syndrome is higher than pre-eclampsia and eclampsia but comparable with previous reports in other countries.

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PURPOSE OF REVIEW: Recent stroke treatment advances have necessitated agile, broad-scale healthcare system redesign, to achieve optimal patient outcomes and access equity. Optimised hyperacute stroke care requires integrated pre-hospital, emergency department, stroke specialist, radiology, neurosurgical and endovascular neurointervention services, guided by a population-wide needs analysis. In this review, we survey system integration efforts, providing case studies, and identify common elements of successful initiatives. RECENT FINDINGS: Different regions and nations have evolved varied acute stroke systems depending on geography, population density and workforce. However, common facilitators to these solutions have included stroke unit care as a foundation, government-clinician synergy, pre-hospital pathway coordination, service centralisation, and stroke data guiding system improvement. Further technological advantages will minimize the geographical distance disadvantages and facilitate virtual expertise redistribution to remote areas. Continued treatment advances necessitate an integrated, adaptable, population-wide trans-disciplinary approach. A well-designed clinician-led and government-supported system can facilitate hyperacute care and scaffold future system enhancements.

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This study explored the efficacy of multi-elements combined with chemometrics to discriminate the geographical origins of oysters (Crassostrea ariakensi). We determined 52 elements in 166 samples from four regions along the southeast coast of China. Significant regional variations of 51 elements were revealed (P < 0.05), while the principal component analysis (PCA) provided no clear regional delineations. The training models (n = 117) established on linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), and random forest (RF) uniformly achieved 100% predictive accuracy. The cross-validation accuracies of the final models (n = 166) derived from LDA, PLS-DA, and RF were 100%, 100%, and 99.4%, respectively. Even with the models simplified to 8 elements (Zn, Al, K, Cd, Cu, Rb, B, and Ag), high predictive and cross-validation accuracies were maintained, underscoring the robustness and algorithm flexibility of elemental profiling for accurately identifying the geographical origins of oysters.

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The field of spatial analysis in traffic crash studies can often enhance predictive performance by addressing the inherent spatial dependence and heterogeneity in crash data. This research introduces the Geographical Support Vector Regression (GSVR) framework, which incorporates generated distance matrices, to assess spatial variations and evaluate the influence of a wide range of factors, including traffic, infrastructure, socio-demographic, travel demand, and land use, on the incidence of total and fatal-or-serious injury (FSI) crashes across Greater Melbourne's zones. Utilizing data from the Melbourne Activity-Based Model (MABM), the study examines 50 indicators related to peak hour traffic and various commuting modes, offering a detailed analysis of the multifaceted factors affecting road safety. The study shows that active transportation modes such as walking and cycling emerge as significant indicators, reflecting a disparity in safety that heightens the vulnerability of these road users. In contrast, car commuting, while a consistent factor in crash risks, has a comparatively lower impact, pointing to an inherent imbalance in the road environment. This could be interpreted as an unequal distribution of risk and safety measures among different types of road users, where the infrastructure and policies may not adequately address the needs and vulnerabilities of pedestrians and cyclists compared to those of car drivers. Public transportation generally offers safer travel, yet associated risks near train stations and tram stops in city center areas cannot be overlooked. Tram stops profoundly affect total crashes in these areas, while intersection counts more significantly impact FSI crashes in the broader metropolitan area. The study also uncovers the contrasting roles of land use mix in influencing FSI versus total crashes. The proposed framework presents an approach for dynamically extracting distance matrices of varying sizes tailored to the specific dataset, providing a fresh method to incorporate spatial impacts into the development of machine learning models. Additionally, the framework extends a feature selection technique to enhance machine learning models that typically lack comprehensive feature selection capabilities.

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Lycium barbarum L. (L. barbarum) is renowned worldwide for its nutritional and medicinal benefits. Rapid and accurate identification of L.barbarum's geographic origin is essential because its nutritional content, medicinal efficacy, and market price significantly vary by region. This study proposes an innovative method combining hyperspectral imaging (HSI), nuclear magnetic resonance (NMR), and an improved ResNet-34 deep learning model to accurately identify the geographical origin and geographical indication (GI) markers of L.barbarum. The deep learning model achieved a 95.63% accuracy, surpassed traditional methods by 6.26% and reduced runtime by 29.9% through SHapley Additive exPlanations (SHAP)-based feature selection. Pearson correlation analysis between GI markers and HSI characteristic wavelengths enhanced the interpretability of HSI data and further reduced runtime by 33.99%. This work lays the foundation for portable multispectral devices, offering a rapid, accurate, and cost-effective solution for quality assurance and market regulation of L.barbarum products.

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Phytic acid (IP6) and its degradation products lower myo-inositol phosphates exert different impacts on nutrient bioavailability and product quality characteristics. However, information regarding the occurrence of IP6 and its degradation products is scarce. In this work, simultaneous determination of IP6 and its degradation products in soybeans was developed, with emphasis on analysis by UPLC-MS/MS and a BEH Amide column both with hybrid surface technology. The retention and analyte/metal surface interactions issues were effectively addressed without ion-pairing reagents addition or derivatization. This method was applied to analyze soybeans from China. Total contents were 0.44-13.2 mg/g, and IP6 and its degradation product myo-inositol pentakisphosphate (IP5) were the predominant analytes, accounting for over 99%. Accession type significantly affected IP5 content, and landraces had significantly higher IP5 than cultivars. Geographically, the lowest IP6 was concentrated in the Huanghuaihai region. Significant correlations existed between IP6 and longitude, altitude, and annual cumulative sunshine hours. This study provides comprehensive insights into the IP6 and its degradation product profile in soybeans, which will benefit breeding soybeans based on specific requirements.

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Agricultural carbon emissions pose a significant challenge in combating climate change and achieving sustainable development objectives. These emissions predominantly stem from the decisions made by stakeholders, and the potential economic and social benefits associated with agricultural product brands determine their capacity to influence stakeholder behavior. This study utilizes panel data from 30 provinces in China spanning from 2008 to 2021 to examine the impact of agricultural product brands on agricultural carbon emission intensity and its underlying mechanisms. The findings indicate that: (1) Agricultural product brands contribute to lowering agricultural carbon emission intensity within a region, while also exerting a negative spillover effect on neighboring areas. (2) Agricultural product brands foster a decline in agricultural carbon emission intensity by bolstering the agricultural industry agglomeration. (3) Agricultural scale operation exhibits a threshold effect between agricultural product brands and agricultural carbon emission intensity, with the mitigation effect becoming increasingly pronounced as the threshold range expands. The research findings can offer valuable insights into leveraging the advantages of agricultural product brands to facilitate the reduction of agricultural carbon emissions.

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This dataset consists of 190,832 manually-digitized cropland field boundaries, with associated attributes, within Brazil, Ukraine, United States of America, Canada, and Russia. Specifically, 22 regions of various sizes (74km2 - 38,000km2) spanning 5 countries were digitized over a range of predominant crop types over different time periods. These field boundaries were drawn over 20 m Sentinel-2 imagery. This field boundary dataset is a byproduct of a larger effort to map cropland burned area (Global Cropland Area Burned: GloCAB product [1]), however, it has several benefits beyond its original intent, including as a training dataset for machine-learning field size analyses, or a dataset to derive cropland field characteristics across different predominant crop types and geographies.

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As we strive towards the ambitious goal of malaria elimination, we must embrace integrated strategies and interventions. Like many diseases, malaria is heterogeneously distributed. This inherent spatial component means that geography and geospatial data is likely to have an important role in malaria control strategies. For instance, focussing interventions in areas where malaria risk is highest is likely to provide more cost-effective malaria control programmes. Equally, many malaria vector control strategies, particularly interventions like larval source management, would benefit from accurate maps of malaria vector habitats - sources of water that are used for malarial mosquito oviposition and larval development. In many landscapes, particularly in rural areas, the formation and persistence of these habitats is controlled by geographical factors, notably those related to hydrology. This is especially true for malaria vector species like Anopheles funestsus that show a preference for more permanent, often naturally occurring water sources like small rivers and spring-fed ponds. Previous work has embraced geographical concepts, techniques, and geospatial data for studying malaria risk and vector habitats. But there is much to be learnt if we are to fully exploit what the broader geographical discipline can offer in terms of operational malaria control, particularly in the face of a changing climate. This chapter outlines potential new directions related to several geographical concepts, data sources and analytical approaches, including terrain analysis, satellite imagery, drone technology and field-based observations. These directions are discussed within the context of designing new protocols and procedures that could be readily deployed within malaria control programmes, particularly those within sub-Saharan Africa, with a particular focus on experiences in the Kilombero Valley and the Zanzibar Archipelago, United Republic of Tanzania.

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