Geographical Location Research Articles

Trauma Outcomes Based on Remoteness of Injury in Australia: A Systemic Review.

Research suggests a significant disparity between rural and urban trauma patient outcomes, causing substantial social, economic and emotional costs, impacting health-related quality of life and functionality, and straining our healthcare system. There has not been a systematic examination of contributing factors in Australia. This study aims to systematically describe the nature of research on trauma outcomes by geographical location and (where possible) describe factors found to increase or decrease the likelihood and severity of injury in rural Australia. Five databases (EMBASE, PubMed/MEDLINE, Web of Science, Scopus, CINAHL) and reference lists were searched. Eligible studies compared injury outcomes by geographic location in Australia, using a quantitative study design. No restrictions were placed on publication year or outcomes explored. The results were synthesised narratively. We found 14 papers. Mortality, the most studied outcome (n = 11), was overall positively related to traumatic incidents in more rural locations. Other data outcomes included hospital admissions and length of stay, admission to ICU, 28-day hospital readmission, rehabilitation, and patient-reported quality of life. Study findings show different mechanisms of injury (e.g., falls) and limited accounts of pre-hospital experiences. Geographical location of trauma may impact the likelihood of injury mortality but is potentially confounded by the different mechanisms and severity of injury. There is insufficient evidence to make conclusions on other non-mortality and longer-term outcomes, and a greater understanding of prehospital outcomes is also needed. This relationship is considered weak due to the limited geographic representation across Australia and the general paucity of recent literature.

Revealing the process and mechanism of non-grain production of cropland in rapidly urbanized Deqing County of China.

Non-grain production of cropland (NGPCL) is a common consequence of rapid urbanization, but excessive NGPCL threatens food security and sustainable cropland use. However, the evolutionary processes and mechanisms of different NGPCL types remain largely unknown, compromising the scientific basis for NGPCL management. Thus, taking rapidly urbanized Deqing as the study area, this research constructed an NGPCL theoretical framework from the perspective of agricultural location, classified NGPCL types using Landsat images, random forest algorithm and Google Earth Engine, and revealed their spatiotemporal changes and different influencing factors through the Multinomial Logit Regression model, and provided targeted zoning and categorized policy suggestions. Our constructed theoretical framework modeled NGPCL by the complex interactions among geographical location, natural conditions, socioeconomic levels, and policy forces. From 2000 to 2022, NGPCL in Deqing County had a high degree and significantly increased from 68.65% to 89.19%. Pond farming and horticultural crops increased by 4046.46ha (38.0%) and 1307ha (27.1%), while tree planting slightly decreased by 54ha (-2.5%). However, these NGPCL expansions resulted in a drastic decrease of 5299ha (-65.5%) in grain crops plantation. Different NGPCL types showed varied spatial distribution characteristics and differentiated driving mechanism. Horticultural crops depended on geographical location and socioeconomic factors and were widely planted near towns and roads with high population density and economic strength. Pond farming mainly extended along the eastern flat rivers and relied on resource endowment. Tree planting was closely related to the natural condition and was concentrated in the sparsely populated mountainous areas. The NGPCL is the result of balancing various factors, and under conditions of extremely scarce cropland resources, the Chinese government needs to strike a reasonable threshold for non-grain production and propose targeted policies of zoning classification to prevent excessive NGPCL from threatening grain yield security.

Provider perspectives on non-medical barriers to GI cancer care at a regional cancer center.

807 Background: Disparities in care for patients with gastrointestinal (GI) cancers are well-documented, but solutions remain elusive. Understanding the barriers faced by healthcare providers is essential to improving care equity. This study explored the perceptions of healthcare providers at a regional academic health system regarding barriers to care for GI cancer patients. Methods: A cross-sectional survey was conducted among healthcare providers, including physicians, advanced care providers (APPs), nurses, dietitians, social workers, care coordinators, and physical/occupational therapists who directly care for patients with GI malignancies. Survey items assessed specific barriers encountered in clinical practice and suggestions for improving care. Descriptive statistical analysis evaluated the quantitative data from the closed-ended questions across professional roles. A thematic analysis was performed on open-response items and assessed to further identify key barriers to care based on respondents' clinical roles and experiences. Results: Seventy-nine healthcare providers responded to the survey. Initial treatment planning was consistently identified as the phase with the most significant barriers across all disciplines. Health literacy was cited as the most critical barrier to diagnosis, while insurance coverage, financial constraints, geographic location, lack of transportation, and social support were the primary obstacles to treatment. The importance of these barriers varied by profession: physicians noted geographic and transportation limitations, while nurses and social workers emphasized gaps in health literacy, insurance, and social support. Systemic issues such as limited access to specialized care and healthcare personnel shortages were also noted. Notably, 55% of physicians spent 10-30% of their time addressing non-medical barriers to treatment, while 38% of nurses spent 30-50%. Care coordination across disciplines was commonly cited as a challenge, with many calling for improved communication and establishing multidisciplinary clinics. Food insecurity, housing stability, and language/cultural barriers were less prominent concerns at this institution. Conclusions: Oncology providers at a large regional cancer center spend significant time addressing non-medical barriers to treatment for GI cancer patients, particularly during initial treatment planning. The most common challenges reported were insurance, transportation, health literacy, and social support. We will use these findings to guide in-depth provider and patient interviews and develop a team-based, equity-focused intervention. These efforts aim to improve care delivery at our institution and serve as a model enhancing GI cancer care in broader healthcare settings.

Using supervised machine learning algorithms to predict bovine leukemia virus seropositivity in dairy cattle in Florida: A 10-year retrospective study

Supervised machine-learning (SML) algorithms are potentially powerful tools that may be used for screening cows for infectious diseases such as bovine leukemia virus (BLV) infection. Here, we compared six different SML algorithms to identify the most important risk factors for predicting BLV seropositivity in dairy cattle in Florida. We used a dataset of 1,279 dairy blood sample records from the Bronson Animal Disease Diagnostic Laboratory that were submitted for BLV antibody testing from 2012 to 2022. The SML algorithms that we used were logistic regression (LR), decision tree (DT), gradient boosting (GB), random forest (RF), neural network (NN), and support vector machine (SVM). A total of 312 serum samples were positive for BLV with corrected seroprevalence of 26.0%. Subject to limitations of the analyzed retrospective data, the RF model was the best model for predicting BLV seropositivity in dairy cattle indicated by the highest Kolmogorov-Smirnov (KS) statistic of 0.75, area under the receiver operating characteristic (AUROC) of 0.93, gain of 2.6; and lowest misclassification rate of 0.10. The LR model was the worst. The RF model showed that the best predictors for BLV seropositivity were age (dairy cows of age ≥ 5 years) and geographic location (southern Florida). We concluded that the RF and other SML algorithms hold promise for predicting BLV seropositivity in dairy cattle and that dairy cattle 5 years of age or older raised in southern Florida have a higher likelihood of testing positive for BLV. This study makes an important methodological contribution to the needed development of predictive tools for effective screening for BLV infection and emphasizes the importance of collecting and using representative data in such predictive models.

Ahmed glaucoma valve implant for refractory glaucoma in children: A systematic review and meta-analysis.

The aim of this study was to evaluate the efficacy and safety of the Ahmed glaucoma valve in pediatric patients with refractory glaucoma. A comprehensive literature search was conducted across multiple major databases, including PubMed, Embase, the Cochrane Library of Systematic Reviews, Science Direct, China's National Knowledge Infrastructure, and the Wanfang database. We retrieved studies published before December 2022 that met the inclusion criteria, including clinical controlled trials (randomized controlled trials) and clinical noncontrolled trials (non-randomized controlled trials) on the use of Ahmed glaucoma valve in pediatric patients with refractory glaucoma. We performed a meta-analysis and systematic review. The efficacy measures included intraocular pressure, number of anti-glaucoma medications, visual acuity, and success rate. The safety measures were complications. Statistical analysis was performed using RevMan 5.0 software. We identified 46 eligible studies: Compared with geographic location and study type, the Ahmed glaucoma valve showed a decrease in postoperative intraocular pressure and number of anti-glaucoma medications compared to preoperative levels in children with refractory glaucoma (P < 0.001). Compared with etiological, the Ahmed glaucoma valve showed a decrease in intraocular pressure after surgery compared to preoperative levels in children with refractory glaucoma (SMD: 14.57, 95% CI: 14.05-15.08, P < 0.00 1), and a decrease in postoperative number of anti-glaucoma medications compared to preoperative number of anti-glaucoma medications (SMD: 1.45, 95% CI: 1.37-1.54, P < 0.001). Compared with trabeculectomy revision surgery, there was no significant difference in the complete success rate between the two groups (SMD: 0.86, 95% CI: 0.52-1.39; P = 0.37).Overall, the postoperative intraocular pressure at the time of Ahmed glaucoma valve implantation was lower than that at the time of trabeculectomy revision surgery (SMD: 1.01, 95% CI: 0.71-1.31, I2 = 99%, P < 0.001). Subgroup analyses based on whether mitomycin C was use d or not. There was a statistically significant difference in intraocular pressure between Ahmed's glaucoma valve surgery and preoperative (SMD: 14.13, 95% CI: 13.47-14.80, P = 0.007). Comparison of cumulative complete success rates of Ahmed S2, S3, and Ahmed FP7, FP8 in Ahmed glaucoma valve surgery (SMD: 0.74, 95% CI: 0.38-1.45, I2 = 85%, P = 0.38). There is no statistical difference between the two groups. Choroidal effusion and anterior chamber hemorrhage are the two most common adverse events after Ahmed's glaucoma valve surgery. The Ahmed glaucoma valve implantation has some effectiveness in reducing intraocular pressure in children with refractory glaucoma, but there are still many complications. Valve model may not be the key factor affecting the postoperative effectiveness and adverse reactions of refractory glaucoma in children.

Patients' perspectives on pain relief during childbirth and labor epidurals: A pilot qualitative study among women who chose to deliver without neuraxial labor analgesia.

Studies have identified widespread variation in neuraxial labor analgesia use by race, ethnicity, and geographic location. However, limited research has investigated patient-level factors in the decision not to use neuraxial analgesia for labor. We conducted semi-structured interviews at a New York City medical center from October 1, 2022, to May 30, 2023. Participants had delivered vaginally and selected not to receive neuraxial labor analgesia. Structured demographic questions were asked after interview completion. Interviews were recorded and transcribed verbatim. We analyzed data and grouped responses into themes according to grounded theory. We identified five themes encompassing the main factors participants had considered when deciding not to receive neuraxial analgesia for birth: preferences for a natural birth experience, an empowering and supportive labor environment, preparation or preparedness for birth without medication, positive outlook on labor pain, and information, misinformation, knowledge gaps and fears about the epidural. All study participants mentioned these overarching themes in their interviews. Participants described various factors important in their decision to give birth without an epidural, which we mapped onto five primary themes. Our results can be used to guide effective patient-provider interactions centered on mutual understanding, evidence-based medicine, and honoring patients' wishes. The information gathered may provide insight into how providers can incorporate shared decision-making into their practice.

Height development trends among 7-18-year-old school-age children in central plains of China between 2000 and 2019: A serial cross-sectional surveillance study in China.

The aim of this study was to analyze changes in height of 7-18-year-old school-age children in China during the year of 2000-2019. We used the survey data from the Chinese National Survey on Students' Constitution and Health in Henan Province for the years 2000, 2005, 2010, 2014, and 2019. Data were categorized into subgroups based on geographic location, gender, and age; mean, standard deviation, and Pearson's correlation coefficient were used to analyze trends in height change among children and adolescents and the correlation between socioeconomic indicators and height change. The height of children and adolescents in Henan has shown a continuous upward trend. The height difference between urban and rural areas has gradually narrowed but has not disappeared. The correlation of height development trends between neighbouring urban areas was higher than in other areas. The level of medical care was significantly associated with the change in height for both boys (r = 0.950, p = 0.013) and girls (r = 0.897, p = 0.039); GDP per capita (r = 0.940，p = 0.018) was significantly associated with the change in height for boys only. The height of Chinese children and adolescents will continue to maintain a positive growth trend, but we need to pay attention to the health status and nutritional intake of children and adolescents in economically disadvantaged areas in order to narrow the height disparity between different socio-economic groups.

An Approach to Forecast Quality of Water Effectively Using Machine Learning Algorithms

Background:: The quality of water directly or indirectly impacts the health and environmental well-being. Data about water quality can be evaluated using a Water Quality Index (WQI). Computing WQI is a quick and affordable technique to accurately summarise the quality of water. Objective:: The objective of this study is to find strategies for data preparation to categorize a dataset on the water quality in two remote Indian villages in different geographic locations, to predict the quality of water, and to identify low-quality water before it is made accessible for human consumption. Methods:: To accomplish this task, four water quality features Nitrate, pH, Residual Chlorine, and Total Dissolved Solids which are crucial for human consumption, are considered to dictate the quality of water. Methods used in handling these features include five steps that are data preprocessing with min-max normalization, finding WQI, using feature correlation to identify parameter importance with WQI, application of supervised machine learning regression models such as Random Forest (RF), Multiple Linear Regression (MLR), Gradient Boosting (GB) and Support Vector Machine (SVM) for WQI prediction. Then, a variety of machine learning classification models, including K-Nearest Neighbour (KNN), Support Vector Classifier (SVC), and Multi-layer Perceptron (MLP), are ensembled with Logistic Regression (LR), acting as a meta learner, to create a stack ensemble model classifier to predict the Water Quality Class (WQC) more accurately. Results:: The examination of the testing model revealed that RF regression and MLR algorithms performed best in predicting the WQI with mean absolute error (MAE) of 0.003 and 0.001 respectively. Mean square error (MSE), root mean square error (RMSE), R squared (R2), and Explained Variance Score (EVS) findings are 0.002,0.005,0.988 and 0.998 respectively with RF while 0.001,0.031,0.999 and 0.999 respectively with MLR. Meanwhile, for predicting WQC, the stack model classifier showed the best performance with an Accuracy of 0.936, F1 score of 0.93, and Matthews Correlation Coefficient (MCC) of 0.893 for the dataset of Lalpura and Accuracy of 0.991, F1 Score of 0.991 and MCC of 0.981 respectively for the dataset of Heingang. Conclusion:: This study explores a method for predicting water quality that combines easy and feasible water quality measurements with machine learning. The stack model classifier performed best for multiclass classification, according to this study. To ensure that the highest quality of water is given throughout the year, information from this study will motivate researchers to look into the underlying root causes of the quality variations.

Mercury bioaccumulation and assimilation in marine plankton in meltwater influenced fjords and shelf waters along the east coast of Greenland.

The rapid melting of the Arctic cryosphere due to climate change will result in significant freshwater input into Arctic marine ecosystems. This might also cause the release of legacy mercury (Hg) stored in the cryosphere, increasing Hg concentration and its subsequent effects on the marine biota. However, there is scarce knowledge on the concentration of Hg in the lower trophic level organisms at the base of the Arctic pelagic food web. This is particularly important since these organisms modulate the transfer of Hg to higher trophic levels, including fish and marine mammals. We quantified the Hg concentration in two plankton size classes (> 200 and 50 – 200 μm) in coastal waters along the east Greenland coast and investigated the potential assimilation efficiency of both inorganic Hg (IHg) and methyl Hg (MeHg) in mesozooplankton and their faecal pellets in experimental incubations. The concentration of Hg in plankton ranged from 12 to 109 ng (g dw)-1 without clear trends between geographic locations or between fjords and coastal areas. Also, the concentrations did not vary between the different plankton size fractions. MeHg concentrations were lower in the mesozooplankton faecal pellets than IHg, which may be due to the higher assimilation of MeHg than IHg in mesozooplankton tissue. Our results confirm that Arctic zooplankton assimilates MeHg more efficiently than IHg and may contribute significantly to the partitioning and cycling of different Hg types in Arctic marine ecosystems.

First de novo genome-specific development, characterization and validation of simple sequence repeat (SSR) markers in Bambusa polymorpha, a commercially important bamboo of India.

The natural population of Bambusa polymorpha have not been genetically enumerated due to a lack of genome sequence information or robust species-specific molecular marker. The present study was conducted to develop and validate genome-wide de novo simple sequence repeat (SSRs) markers in B. polymorpha through shallow-pass genome sequencing. The genome sequence data of about 13Gb was generated using Illumina technology, and high-quality sequence reads were de novo assembled into 1,390,995 contigs with GC content 42.34%, contig N 50 value 1047bp. The Benchmark Universal Single-Copy Ortholog (BUSCO) analysis indicated 75.29% of complete and single-copy genome assembly. By scanning of genome assembly, a total of 73,468 simple sequence repeats (SSRs) were identified, and 44,383 primer pairs were designed. Repeat analysis revealed that the dinucleotide and trinucleotide repeats were most abundantly distributed in the genome with 52.95 and 41.17%, respectively. A subset of 33 SSRs was randomly selected for their PCR amplification and polymorphism in 16 random individuals. Of these, 29 SSRs were successfully amplified with the expected product size and 20 showed polymorphic banding patterns. Polymorphic SSRs were characterized by high expected heterozygosity (H e = 0.72) and polymorphism information content (PIC = 0.68). The clustering pattern obtained using the neighbor joining (NJ) dendrogram revealed the genotypes were clustered in accordance with their geographical locations. The genomic and marker information generated in this study are novel and useful for future studies for genetic improvement and conservation of B. polymorpha.

Bisphenols in indoor dust: A comprehensive review of global distribution, exposure risks, transformation, and biomonitoring.

Bisphenols (BPs) are pervasive environmental contaminants extensively found in indoor environments worldwide. Despite their ubiquitous presence and potential health risks, there remains a notable gap in the comprehensive reviews focusing on BPs in indoor dust. Existing literature often addresses specific aspects such as exposure pathways, transformation products, or biomonitoring techniques, but lacks a consolidated, in-depth review encompassing all these facets. This review provides a comprehensive overview of the global distribution of BPs, emphasizing their prevalence in diverse indoor settings ranging from households and workplaces to public areas. Variations in BP concentrations across these environments are explored, influenced by factors such as industrial activities, consumer product usage patterns, and geographical location. Exposure assessments highlight ingestion, inhalation, and dermal contact as primary pathways for BP exposure, with ingestion being particularly significant for vulnerable groups such as infants and young children. Studies consistently reveal higher concentrations of BPs in urban indoor dust compared to rural settings, reflecting the impact of urbanization and intensive consumer practices. Moreover, BPs from mobile sources like vehicles contribute significantly to overall human exposure, further complicating exposure assessments. The review also delves into the transformation of BPs within indoor environments, emphasizing the diverse roles of physical, chemical, and biological processes in generating various transformation products (TPs). These TPs can exhibit heightened toxicity compared to their parent compounds, necessitating deeper investigations into their environmental fate and potential health implications. Critical examination of biomonitoring techniques for BPs and their metabolites underscores the importance of non-invasive sampling methods, offering ethical advantages and practicality in assessing human exposure levels. The emerging use of bioindicators, encompassing plants, animals, and innovative approaches like spider webs, presents promising avenues for effectively monitoring environmental contamination.

Survival disparities in small intestine carcinoid tumors: A SEER-based analysis.

653 Background: Small intestine carcinoid tumors (SI-carcinoids) are rare neuroendocrine neoplasms with variable survival outcomes. This study examines the impact of age, sex, race, income, and geographic location on overall survival (OS) in patients with SI-carcinoid tumors. Methods: A retrospective cohort study was conducted using the Surveillance, Epidemiology, and End Results (SEER) registry 22 to identify patients aged 20 and above with SI-carcinoid tumors from 2000 to 2021. Kaplan-Meier survival analysis and log-rank tests were used to assess differences in survival. Cox proportional hazards models estimated hazard ratios (HR) for Overall Survival (OS). Results: 20,777 patients were included, with 7,029 deaths recorded. Median OS varied significantly by age, sex, race, income, and tumor site. Patients aged 60-85 had a median OS of 10 months (95% CI: 9.75-10.42), while those over 85 had 2.92 months (95% CI: 2.67-3.33). Females had better OS (13.92 months; 95% CI: 13.42-14.42) than males (12.83 months; 95% CI: 12.42-13.25). Non-Hispanic Black patients had worse OS (12.33 months; 95% CI: 11.50-13.33) compared to Non-Hispanic Whites (13.25 months; 95% CI: 12.92-13.67). Patients earning less than $50,000 had worse OS (11.42 months; 95% CI: 10.67-12.42) than those earning $100,000–$120,000 (15.42 months; 95% CI: 14.25-17.83). Geographic disparities were noted, with nonmetropolitan areas showing worse OS (11.42 months; 95% CI: 10.83-12.92) compared to large metropolitan areas (14.00 months; 95% CI: 13.50-14.42). Cox models confirmed age (HR for 85+ years: 21.99; 95% CI: 17.40-27.81), male sex (HR: 1.12; 95% CI: 1.07-1.17), and Black race (HR: 1.29; 95% CI: 1.18-1.42) were linked to worse OS. Tumor site also affected OS, with ileal tumors showing better survival compared to duodenal tumors (HR: 0.89; 95% CI: 0.84-0.94). Conclusions: Age, sex, race, income, and geographic location significantly affect OS in patients with small intestine carcinoid tumors, highlighting the need for tailored interventions for vulnerable groups.

Spatial Variations in Per- and Polyfluoroalkyl Substance Concentrations in Pooled Sera from Inland, Coastal, and Island Populations

Per- and polyfluoroalkyl substances (PFAS) are a class of ubiquitously detected chemicals, some of which are highly persistent and bioaccumulative in humans. Within the general population, dietary ingestion is considered a primary pathway for PFAS exposure, and seafood consumption specifically has been associated with higher serum PFAS concentrations. Proximity of residence to the ocean may influence dietary habits, particularly seafood consumption, and exposure to geographically specific PFAS sources such as sea spray aerosols (SSA). The objective of this study was to evaluate potential spatial trends in serum PFAS concentrations between Australian coastal and island populations compared to those with inland residency. Human sera were obtained from deidentified surplus pathology samples and pooled with respect to geographical location, sex (male or female), and age group (males: ≥15-<45 years, ≥45 years; females: ≥15-<45 years, ≥45-<60 years, ≥60 years) stratification criteria. Serum samples were then analysed for PFAS using High Performance Liquid Chromatography-Mass Spectrometry (HP LC-MS). A total of 13 of the 45 targeted PFAS were quantifiable in at least one pooled sample, including the detection of perfluorooctane sulfonate (PFOS) replacement compounds 5:3 fluorotelomer carboxylic acid (5:3 FTCA) and potassium 9-chlorohexadecafluoro-3-oxanonane-1-sulfonate (9Cl-F53B). Significant spatial trends were observed in males aged ≥45 years, with serum concentrations of PFOS, perfluorobutanoic acid (PFBA), perfluorodecanoic acid (PFDA) and perfluoroheptane sulfonic acid (PFHpS) demonstrated to be 32-77% higher in pooled samples from island locations compared with inland. A similar trend was observed for PFHpS in coastal locations. Whilst deidentification of samples limited inferences about exposure pathways associated with the observed trends, this study indicated the feasibility of utilising pooled samples for assessing spatial variations in serum PFAS concentrations between geographically distinct subpopulations.

Geographical location of ischemic stroke patients affects thrombolysis availability in Denmark.

Early recognition and treatment of stroke is paramount for good outcome. Transport distance may result in delayed arrival for revascularization therapy. We investigated how transport time and distance to the revascularization unit affected the probability of receiving intravenous thrombolysis in Denmark between 2015 and 2020, for patients calling the Emergency Medical Services within three hours of symptom onset. We obtained records from the Danish Stroke Registry (DanStroke) and the patient administrative computer-assisted dispatch system (CAD). All patients diagnosed with stroke from the Capital Region and Region Zealand, who contacted the EMS within three hours of symptom onset were included. The study population was analyzed using multivariate logistical regression models. For the Capital Region, longer transport time was associated with lower IVT rates, with an Odds-Ratio 0.91, 95% CI [0.83;0.99], P-value 0.0386. There was no significant correlation between transport time and IVT rates for the Region of Zealand. However, fewer patients with >60min estimated transport time received IVT than patients with 0-20min estimated transport time in the Region of Zealand (Odds-ratio 0.63, 95% CI [0.44;0.91], p-value 0.016). Longer transport time to a revascularization unit is associated with significantly poorer IVT rates in the Capital Region of Denmark, despite calling in a timely manner for arrival within the 4.5-h treatment window. The same association was not established for the rural Region of Zealand; however, our findings do suggest that living >60min from a revascularization unit is associated with a lower probability of receiving IVT in this region.

Prevalence and Factors Associated With Depression and Depressive Symptoms Among Chinese Older Persons: An Integrative Review.

China is the country with the largest population of older persons. Depression is the most common mental health issue among older adults, a trend expected to increase as societies continue to age. With the global increase in depression and depressive symptoms among this demographic, the resulting disease burden poses a significant challenge to health and social care systems in China. To map, summarise and examine the empirical literature on the prevalence and factors associated with depression and depressive symptoms in Chinese older adults, an integrative literature review was conducted informed by the guidelines of Whittemore and Knafl. The literature search encompassed EMBASE, SCOPUS, CINAHL, Web of Science, PubMed, PsycINFO, SocINDEX, China National Knowledge Infrastructure Database and Wanfang Database. The review included 65 studies, 29 in English and 36 in Chinese. The reported prevalence of depression or depressive symptoms in Chinese older adults was 3.78%-84.3%. Based on the biopsychosocial model, the associated factors were clustered as follows: biological factors (physical health, disability, drug effects, gender, age, diets, physical activities), psychological factors (self-esteem, coping skills, trauma, emotions, beliefs, hobbies, lifestyle) and social factors (family relationships, peers, family circumstances, school, residential areas, social support, social structure). This review synthesised research on depression among older adults in China, highlighting varying prevalence across diverse geographical locations. Given the high prevalence among certain older Chinese cohorts, the early identification and assessment of the factors associated with depression is essential to reducing disease burden. The use of the biopsychosocial model provided a theoretical lens to examine depression in this population in an integrative and holistic way. Thus, furthering understanding of the factors that require close consideration in future research and practice innovations on depression in older persons.

Unravelling a new focus of spotted fever rickettsioses as causative agents of acute undifferentiated febrile illness in Odisha, a state in eastern coastal India.

Spotted fever group Rickettsia (SFGR) infections remain largely under-investigated as causative agents of acute undifferentiated febrile illness (AUFI) in resource-limited settings. Few studies are available on the prevalence of SFGR infections in India, especially in eastern India. In a cross-sectional study conducted in 192 hospitalized adult and paediatric patients with AUFI, the frequency of SFGR using sequential PCR targeting genes encoding citrate synthase (gltA), 17 kDa lipoprotein precursor antigen (17kDa), outer membrane proteins A and B (omp A & omp B) was 6.2% (12/192) including 7.4% (8/108) in adults and 4.7% (4/84) in paediatric patients with AUFI. Phylogenetic analysis of SFGR based on the concatenated sequences of omp A-gltA-17kDa-omp B showed that the patients' isolates obtained in the study clustered with Rickettsia conorii str. Malish 7 (AE006914.1). The SFGR cases described here, to the best of our knowledge, are the first human cases diagnosed in Odisha, eastern coastal India that were laboratory-confirmed by molecular detection and sequencing. The findings of this study will be beneficial for designing systematic future studies covering more geographical locations for continued surveillance of SFGR human infections along with vector surveillance.

Distribution characteristics, source analysis and ecological risk assessment of PAHs in tea garden soil in China.

In this study, we collected 177 soil samples from major tea-producing areas in China, systematically investigated the spatial distribution characteristics of the polycyclic aromatic hydrocarbons (PAHs) in the soil of these tea plantations and discussed the environmental factors influencing of the PAHs in tea garden soil. The feature ratio method and source analysis methods were used to determine the PAHs source in tea garden soil, and the potential risk of PAHs in tea garden soil was also evaluated. The results showed that the concentrations of the 16 PAHs in 177 samples ranged from 6.21 to 4068.91ngg-1, with an average of 257.00ngg-1. The majority of PHAs in tea garden soils predominantly contained a 5-6 ring pattern, and the highest content was indeno (1,2,3-cd) pyrene (InP, 23%) and benzo (b) fluoranthrene (BbF, 16%). In addition, 10.16% of the PAHs in tea plantation soils contained a 2-3-ring pattern, with naphthalene (NAP) having the highest content. PAH source in Chinese tea garden soil was predominantly mixed combustion, such as incomplete biomass combustion, petroleum combustion, coal combustion and wood combustion. The PAHs distribution was mainly affected by the industrial structure, geographical location of tea plantation, climatic conditions, soil properties and other factors in different regions. According to the Dutch Maliszewska-Kordybach grading standard, 79% of the soil samples from Chinese tea plantations were classified as unpolluted, 13% as mildly polluted, and 2% and 6% as moderately and severely polluted, respectively. Although the PAH pollution in tea plantations was generally low, BaP and InP pose significant ecological risk in some areas. Therefore, strategies such as effective guidelines and environmentally friendly technologies, must be developed to reduce the risk of PAH pollution in tea plantation soils.

Enhancing Road Safety through Crime Hotspot Detection and Secure Route Planning

In the light of increasing criminal activities, it is become important that everyone should concern about individual safety. It has been seen those criminal activities near criminal hot spot happening frequently. Road safety is of paramount significance, as people frequently need to travel often through unfamiliar areas via various modes of transport, such as walking, public transport, private vehicles, auto rickshaws, or cabs. It is observed this incident are more often when victims are likely to be individual. This paper aims to enhance the safety of people. It analyzed criminal records happened recently and aims to take individual feedback regarding certain incident in particular area. This System intended to take geographical locations as input, to identify the safest route between a given source and destination at a particular time. The approach uses optimized A algorithm to determine optimized route considering crime rate severity and proximity. Open-Source Routing Machine (OSRM) to handle the real-time mapping and routing data. OSRM provides efficient and accurate routing, allowing the system to dynamically calculate the shortest and safest routes based on real world road networks. The system offers three types of routes fastest, safest, and optimized using a modified A algorithm that balances travel efficiency with safety.

Advancing public safety and housing solutions: A comprehensive framework for machine learning and predictive analytics in urban policy optimization

Urban areas worldwide face mounting challenges, including public safety concerns, housing shortages, and efficient resource allocation. Addressing these complexities requires innovative solutions that integrate technology and policy frameworks. This paper proposes an integrated framework leveraging machine learning (ML) and predictive analytics to optimize urban policy-making and provide actionable insights for sustainable urban development. The framework combines real-time data streams with advanced predictive modeling to enhance decision-making in urban governance. Key features include the ability to assess and respond to emerging trends in public safety by analyzing crime patterns, resource deployment, and community risk factors. Similarly, the framework addresses housing shortages by evaluating demand-supply dynamics, forecasting population growth, and identifying areas requiring immediate intervention. A critical review of existing models underscores the limitations of traditional urban policy approaches in managing socioeconomic disparities and environmental influences. Building upon these insights, the proposed framework integrates diverse data sources, such as demographic information, environmental metrics, and public sentiment analysis, to create a holistic view of urban systems. This multidimensional approach ensures that policy recommendations are context-sensitive, equitable, and inclusive. Moreover, the framework emphasizes stakeholder engagement, fostering collaboration among policymakers, urban planners, community leaders, and data scientists. It prioritizes scalability and adaptability, allowing its application across diverse urban contexts and geographic locations. This adaptability ensures that the framework remains relevant as urban environments evolve and new challenges arise. By addressing the interplay between data-driven insights and policy optimization, this research aims to bridge the gap between theoretical models and practical implementation. The framework holds the potential to redefine urban governance by enabling proactive decision-making, equitable resource allocation, and sustainable development. Future research should explore real-world applications of this framework to validate its efficacy and refine its components further.

The role and impact of MICE (Meetings, Incentives, Conferences, and Exhibitions) industry in Thailand

This research paper presents a comprehensive analysis of the pivotal role and profound impact that the MICE industry plays in the beautiful country of Thailand. An attempt has been made to give significance to this multi-billion-dollar industry, which has not only been boosting the economy of the nation but also shaping and enriching its tourism landscape. It broadly defines the concept of the MICE industry primarily going deep into the understanding of the multi-composites involved within it and meeting its diversity-strength of incentives, conferences, and exhibitions. Thus, a framework has been developed from this process, important to the ensuing analysis of Thailand's unique positionality as a Southeast Asia leader for MICE destinations. Against this background, the richness of the culture of Thailand, trademark hospitality, and the strategic geographical location are seen as major driving elements toward its success as a favorite destination for events related to MICE. The next section highlights the economic impact of the MICE Industry in Thailand. It also describes in detail, through voluminous data and rigorous analysis, the immense generation of revenue, creation of jobs, and infrastructure development in direct relation to MICE activities. This quantification acts to attest to the huge potential and transformative power that the MICE industry can bring about in the overall economic growth and prosperity of Thailand. While the paper acknowledges the astonishing success of the MICE industry, it never fails to discuss its challenges. It gives light to various challenges that are, or may be, threatening for the continued success of the industry, such as political instability and emerging competition. Additionally, environmental considerations are given due to the research, with an emphasis on the need for sustainable practices within the MICE sector. In the process of identifying these challenges, the study further identifies a set of opportunities that exist for the sustainable growth and innovation of Thailand's MICE industry. It identifies various effective strategies that could be adopted to enhance the position of Thailand within the global MICE market. This includes strategies related to increased collaboration between the government and private sectors in substantial investment in infrastructure, and a focus on promoting and implementing sustainability throughout the industry. In all, this meta-research study sends across that the MICE industry plays an important role in knowledge exchange, economic growth, and global connectivity. Thus, it creates a sense of optimism and exuberance from the comprehensive outlook toward the future potential of the MICE industry in Thailand and continued growth and success within this vibrant and diverse nation.