Search Results (6,096)

Large language models are part of everyday scholarly writing, but their influence may not always appear as obvious AI authorship. More often, it may appear through gradual changes in academic style. This study examines whether biomedical abstracts show measurable signs of LLM-associated “same-ification” after the public release of ChatGPT. Instead of classifying individual abstracts as AI-written, our study analyses population-level changes across 28,415 PubMed abstracts published between 2018 and 2025. A strict dictionary of LLM-associated stylistic markers was used alongside a control vocabulary, lexical diversity, semantic similarity, interrupted time-series modelling, journal-level heterogeneity analysis, and a study-specific validation framework called SAME-ML. The findings show a clear post-2022 stylistic shift. Mean strict marker use increased from 4.995 to 11.658 markers per 1000 words, representing a 133.4% rise, while the control vocabulary slightly declined. This increase was strongest in 2024 and 2025 and was mainly driven by markers linked to value framing, contribution signalling, connective phrasing, improvement rhetoric, and problem-solution positioning. SAME-ML further showed that the post-ChatGPT period contained a learnable stylistic signal that remained visible after topic-masked and matched-sample validation. Overall, the findings show a corpus-level rhetorical shift and provide a reproducible approach for tracking stylistic change in scholarly communication over time. Full article

Honeybees (Apis mellifera), as key pollinating insects, are undergoing population decline, which has become a critical environmental challenge affecting ecosystem stability and sustainable agriculture. Moreover, a potential association exists between the physiological and behavioral responses of honeybees induced by environmental stress and the pathological mechanisms of depression. The pathogenesis of depression remains complex and not fully understood, and a stable animal model is a prerequisite for investigating its mechanisms and screening antidepressants. This study aimed to examine the alterations induced by CUMS and to evaluate behavioral changes related to depression-like phenotypes and neurotransmitter levels in the honeybee brain. The results showed that CUMS treatment induced typical depression-like behaviors and downregulated monoamine neurotransmitters in honeybees, consistent with observations in mammalian depression models. Fluoxetine was found to reverse these abnormalities, further supporting the validity of the model. This study provides a novel tool for depression research, antidepressant screening, and stress-related investigations in pollinators. Full article

Structural changes occurring within a country’s economy are reflected in the composition of employment across economic sectors. Employment adapts to different stages of socio-economic development and can serve as an important indicator of economic growth or crisis, since changes in the level of employment accompany overall economic development. Therefore, analyzing the sectoral distribution of employment by type of economic activity is of both theoretical and practical importance under contemporary conditions. This article examines the methodological aspects of assessing structural changes in population employment based on an analysis of broader structural transformations, which allows for the estimation of the magnitude of changes across specific types of economic activity in the Republic of Tajikistan. The analysis is based on official employment statistics published by the Statistical Agency under the President of the Republic of Tajikistan for the period 2011–2022. The results indicate that agriculture, hunting, and forestry remained the dominant source of employment throughout the study period, although its share gradually declined, while employment increased in education, health and social services, and several service-related activities. Furthermore, this study investigates internal changes in the number of employed persons by type of activity within the overall sectoral employment composition, thereby reflecting the dynamics of changes in employment across other sectors of economic activity. Full article

Background/objective: Down syndrome (DS) is characterized by premature aging, with comorbidities observed in the older population without DS, a high prevalence of multimorbidity and cognitive decline. The use of multiple medications further increases clinical complexity. The objective of this paper is to evaluate anticholinergic use and the anticholinergic burden (ACB) in a sample of persons with DS. Methods: cross-sectional retrospective study involving community-dwelling persons with DS, afferent to the DS clinics of the Fondazione Policlinico Universitario “A. Gemelli” (Rome, Italy). Individuals were assessed through a standardized clinical protocol. ACB was evaluated according to the anticholinergic cognitive burden scale, with a score ≥ 3 indicating high risk of anticholinergic side effects. Results: 337 individuals were taking ≥ 1 chronic medication, mean age was 37.7 (±14.6), 158 (43.8%) were females. 143 (39.6%) individuals took ≥ 1 medication with known anticholinergic burden, 51 (14.1%) individuals showed high risk ACB score. High risk ACB score prevalence increased with age (<18 years n = 0, 0%; 18–39 years n = 14, 8.2%; 40+ years n = 37, 22.3% p < 0.001). Polypharmacy was more prevalent among individuals with high ACB score (n = 20, 39.2% vs. n = 23, 7.4%, p < 0.001). The most prevalent drugs in individuals with high risk ACB score were antipsychotics (n = 34, 66.6% vs. n = 17, 33.3%, p < 0.001). The most prevalent comorbid condition was psychosis (n = 34, 66.6% vs. n = 16, 33.3%, p < 0.001). Discussion: individuals with DS show a high prevalence of anticholinergic drug use, increasing with age and associated with polypharmacy and psychiatric conditions. These medications are directly addressing the underlying psychiatric or neurological conditions in DS, rather than causing them. Nevertheless, these medications are often essential for managing psychiatric disorders, simultaneously increasing ACB, posing a risk of exacerbating pre-existing vulnerabilities (e.g., cognitive decline), which warrants the need for a more personalized strategy. Conclusions: A thorough assessment of drug history is mandatory in the DS population, to apply deprescribing, pharmacological switches, non-pharmacological approaches, to lower or even prevent high ACB, promoting overall a personalized and tailored approach to this population. Full article

Non-grain production of cultivated land has increasingly affected regional food security and the stability of agricultural ecosystems. In traditional rice-producing regions, changes associated with non-rice cultivation, fallow land, rice-fishery integrated farming, and intensive agricultural management are reshaping the spatial structure of paddy landscapes. To identify the long-term spatiotemporal evolution of paddy systems, this study investigated Northern Jiangxi, China, using Landsat surface reflectance imagery from 2000, 2005, 2010, 2015, and 2020 on the Google Earth Engine (GEE) platform. The Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) were used to construct a phenology-based Flooding Frequency (FF) indicator. Based on the annual frequency with which pixels satisfied the condition LSWI > EVI, cultivated land was classified into three categories: non-flooded cropland, standard rice paddy, and high-frequency flooded cropland. In this study, non-flooded cropland was used as an indicator of potential non-rice cultivation rather than as direct evidence of confirmed non-grain production. Landscape metrics, transition matrices, gravity center migration, standard deviation ellipses, and geographically weighted regression (GWR) were then used to examine paddy landscape dynamics, fragmentation patterns, and county-level spatial associations with socioeconomic factors. The results suggest that the paddy system in Northern Jiangxi experienced marked stage-based fluctuations between 2000 and 2020. Standard rice paddy recovered during 2005–2010, whereas non-flooded cropland expanded considerably during 2010–2015, accompanied by intensified paddy landscape fragmentation. Non-flooded cropland was mainly distributed around urban fringes, transport corridors, and some hilly margins. Standard rice paddy was concentrated in traditional grain-producing areas, including the Poyang Lake Plain and the Gan-Fu Plain. High-frequency flooded cropland was primarily located in low-lying lake areas, where its dynamics were likely associated with rice-fishery integrated farming, continuous irrigation, and hydrological fluctuations. Landscape metrics showed that the largest patch index and mean patch size of standard rice paddy declined after 2010, indicating reduced spatial continuity of core paddy fields. The GWR analysis provided auxiliary evidence that total population, per capita gross domestic product (GDP), and urbanization rate were spatially associated with changes in non-flooded cropland at the county level; however, the results should be interpreted as exploratory associations rather than causal mechanisms. Overall, paddy landscape change in Northern Jiangxi was expressed not only through changes in cultivated land area, but also through the reorganization of paddy function, spatial continuity, and land-use intensity. Future cropland protection should therefore move beyond area-based control toward integrated management of quantity, quality, function, and spatial configuration. Future research should further verify these findings using dynamic cropland boundaries, higher-resolution imagery, and more detailed socioeconomic data. Full article

Population aging is a growing problem. This process is driven not only by genetic factors but also by environmental factors, such as diet. Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia worldwide, characterized by cognitive decline, synaptic dysfunction, and neuronal loss. Despite extensive research, effective disease-modifying therapies remain limited. Increasing evidence indicates that oxidative stress plays a central role in AD pathogenesis, acting as a key link between β-amyloid accumulation, tau hyperphosphorylation, mitochondrial dysfunction, and neuroinflammation. Accordingly, dietary strategies have been proposed to mitigate these pathological processes and may represent an important component of Alzheimer’s disease prevention. Moreover, emerging evidence on the gut–brain axis highlights the critical role of gut microbiota in regulating neuroinflammation and oxidative stress. Dysbiosis has been associated with increased permeability of the intestinal barrier, systemic inflammation, and accelerated neurodegeneration. Dietary patterns such as the Mediterranean, DASH, and MIND diets may exert beneficial effects by simultaneously influencing antioxidant status and microbial composition. This review aims to provide a comprehensive overview of the role of oxidative stress in Alzheimer’s disease and evaluate the potential of dietary interventions in modulating mechanisms involved in Alzheimer’s disease pathogenesis and supporting cognitive health. Particular attention is given to the neuroprotective effects of dietary antioxidants, including vitamins, polyphenols, and polyunsaturated fatty acids, which act through the reduction in reactive oxygen species, modulation of inflammatory pathways, and support of neuronal survival. Although current findings are promising, inconsistencies in clinical data indicate the need for further well-designed studies. Future research should focus on personalized nutritional strategies integrating dietary, genetic, and microbiome-related factors. Targeting oxidative stress through diet and microbiota modulation represents a promising complementary strategy for Alzheimer’s disease prevention and supportive management, although further clinical studies are required to establish disease-modifying effects. Full article

Background: Current treatments for myasthenia gravis (MG), while improving outcomes, are often associated with adverse effects, and a proportion of patients remain refractory to standard therapies. Eculizumab, a humanized monoclonal antibody targeting complement protein C5, is approved for refractory anti-acetylcholine receptor antibody-positive generalized MG (AChR-Ab+ gMG). Aim of the present study is to explore the rapidity of onset of eculizumab efficacy in a single-center cohort of MG patients. Methods: This retrospective, observational, single-center study evaluated the real-world effectiveness and rapidity of response to eculizumab in patients with AChR-Ab+ gMG. Patients received eculizumab according to the approved regimen and were assessed at baseline (T0), 5 weeks (T1), and 3 months (T2) using the Myasthenia Gravis Activities of Daily Living (MG-ADL) score, Quantitative Myasthenia Gravis (QMG) score, and Myasthenia Gravis Foundation of America (MGFA) classification. Results: Eight patients were eligible for the study with a mean age of 73.1 years. A rapid clinical improvement was observed after treatment initiation. Mean MG-ADL scores decreased from 8.38 at T0 to 2.13 at T1 (p < 0.001; Cohen’s d = 2.075), while QMG scores declined from 13.75 to 5.63 (p = 0.001; Cohen’s d = 1.824). Improvements were maintained at T2. Mean percentage reductions from T0 to T1 were 73.5% for MG-ADL and 60.6% for QMG. Eculizumab was well tolerated. Conclusions: These real-world findings confirm a rapid and clinically meaningful response to eculizumab in elderly patients with refractory gMG. These findings highlight its potential role in achieving early symptom control and reducing disease burden in this clinically vulnerable population. Full article

Background/Objectives: Korea has experienced rapid and heterogeneous shifts in cancer epidemiology since 1999. We aimed to characterize divergent incidence trajectories across the 24 major cancer types, quantify sex-specific burdens, and project case counts through 2030. Methods: Annual incidence data—including new case counts and age-standardized incidence rates (ASIRs) per 100,000 (2020 Korean standard population) stratified by sex—were extracted from the KCCR via the Korean Statistical Information Service (KOSIS) for 1999–2023. Annual percent change (APC) was estimated by log-linear regression with 95% confidence intervals (CIs). Holt–Winters damped exponential smoothing generated 2024–2030 projections with 95% prediction intervals (PIs). Changes in case ascertainment and coding over the study period were considered in interpretation. Results: Total incidence increased from 101,854 (1999) to 288,613 cases (2023), a 183.4% increase. Overall ASIR rose from 402.7 to 522.9 per 100,000. Of the 24 cancer types, 15 showed statistically significant increasing ASIR trends, 6 showed significant decreasing trends, and 3 showed no significant change. The highest-APC cancers were thyroid (+7.56%), prostate (+6.98%), testis (+5.39%), breast (+5.03%), and corpus uteri (+5.03%; all p < 0.001). The largest significant declines occurred in cervix uteri (−3.81%), larynx (−3.18%), liver (−2.90%), and stomach (−2.20%; all p < 0.001). Female ASIR increased from 294.7 to 488.9 per 100,000 (+65.9%); male ASIR increased from 573.3 to 587.0 per 100,000 (+2.4%). Total cancer incidence is projected to reach 307,091 (95% PI: 281,200–332,983) in 2026 and 330,213 (95% PI: 290,663–369,763) by 2030, with the steepest projected relative growth for prostate (+48.9%), kidney (+33.7%), and breast (+31.3%) cancers. Conclusions: Korean cancer epidemiology is undergoing a pronounced transition from infection-related toward metabolic, hormonal, and aging-related malignancies, with a marked and widening sex-specific divergence. Cancer-type-resolved projections through 2030 provide an evidence base for strategic capacity planning in Korean oncology. Full article

Background: Hearing health in Kazakhstan is documented through parallel administrative systems whose indicators are often conflated. We examined three administrative layers of hearing health during 2020–2025: dispensary registration of ear and hearing-loss diagnoses, disability certification as a severe administrative endpoint, and cochlear implantation (CI) as the specialised treatment response, with reference to Global Burden of Disease (GBD) 2021 estimates. Methods: We conducted a national ecological, region-year, multi-source administrative registry study across all 20 regions of Kazakhstan from 2020 to 2025. The dataset included 114 region-year observations and integrated Dispensary Report Form No. 12, the State Register of Persons with Disabilities, and the Electronic Register of Inpatient Patients. Dispensary indicators were interpreted as registered healthcare-utilisation measures, not population prevalence or incidence. Trends were assessed using Mann–Kendall tests with Benjamini–Hochberg false-discovery-rate correction. Regional patterns were examined using Spearman correlation, inequality metrics, and exploratory clustering. Results: Among adults, registered H60–H95 annual morbidity increased from 231,209 to 278,897 cases (CAGR +3.8%; FDR p = 0.016), and first-time registrations rose from 126,513 to 167,674 (CAGR +5.8%; FDR p = 0.016). Active dispensary observation declined modestly from 21,840 to 19,881. H65–H66 chronic otitis first-time registration remained stable, while active observation declined sharply. Paediatric H90–H91 registration was stable. In 2025, 31,560 persons were registered with hearing impairment-related disability, including 26,522 adults. CI procedures increased from 285 to 523. Adult CI activity was intermittent between 2012 and 2018 (peak 140 in 2013), ceased in 2019–2020, and was re-established from 2021 (14 → 129 procedures in 2025), reaching 24.7% of all CI. Most procedures were concentrated in Almaty and Astana. Compared with the GBD-2021 estimate of 17,212 per 100,000, administrative indicators captured much narrower service-utilisation and severe-certification layers. Conclusions: Kazakhstan’s administrative data describe distinct hearing-health layers rather than competing prevalence estimates. Adult screening, regional audiology capacity, post-CI rehabilitation, and longitudinal outcome registries are priority areas. Full article

Social and behavioral research often needs to examine policy shocks, information interventions, platform-mediated attention, and governance feedback, but direct experiments on real populations are constrained by ethical risks, intervention costs, and limited repeatability. This study proposes Multi-Agent Social Simulation (MASS), a protocolized form of large language model-driven agent-based modeling (LLM-driven ABM) designed as a low-risk, repeatable, and auditable pre-experimental simulation method for quantitative research. MASS embeds LLMs in an agent-based modeling (ABM) framework and uses role settings, round-based scheduling, information control, background-rule control, structured outputs, harness checks, reason-action logs, and replication manifests to transform open-ended language generation into recordable, checkable, and statistically analyzable agent-round observations. The method is evaluated through the New Jersey–Pennsylvania minimum wage natural experiment, the 2016 UK Brexit digital campaigning context, and the 2023 Zibo barbecue tourism public-opinion event. Results show that protocolized LLM-driven ABM can generate analyzable and empirically assessable outputs across policy-shock, information-intervention, and governance-feedback scenarios. The strongest evidence concerns rule-shock identification, declining undecided share under targeting, and mechanism-chain consistency among governance response, public sentiment, and behavioral intention. MASS is not a substitute for real-world experiments or causal inference; it is a pre-experimental simulation method for mechanism rehearsal, risk identification, counterfactual comparison, and research design preparation. Full article

The Mississippi River Delta region is of national and international relevance in terms of agriculture, energy, river navigation, and fisheries. Being one of the most engineered rivers in the world, the Mississippi River has been intensively altered over the past 150 years. The river alterations included the construction of dams, levees, diversions, channelization, spillway flood control systems, and many others. These engineering practices have significantly modified the natural hydrology and sediment dynamics of the river and its deltaic region. While these interventions have provided critical benefits such as flood protection, improved navigation, and economic development, they have also led to profound environmental and ecological consequences. The reduction in sediment delivery to the Mississippi River Delta has accelerated land loss, contributing to the disappearance of coastal wetlands at an alarming rate. The land loss has diminished critical habitats for wildlife, reduced storm surge protection for coastal communities, and disrupted the delta’s natural ability to adapt to fast subsidence. The long-term sustainability of the delta is further threatened by the compounding effects of climate change, including rising sea levels, increased storm intensity, and extreme precipitation and drought conditions. This paper examines the effects, consequences, and future risks of the major river engineering practices on the Mississippi River Delta and provides strategic recommendations that balance human needs with changing natural conditions to ensure sustainability. Specific recommendations include river diversion upstream of New Orleans, better strategies to deal with floods and droughts, strategic maintenance or removal of portions of levees, hybrid coastal-inland human migration, improved transportation connections between coast and inland, and better preparation for future ecosystem shifts. This review is needed because river engineering has made the Mississippi River Delta economically vital yet increasingly vulnerable to sediment loss, wetland collapse, saltwater intrusion, flooding, and population decline. By synthesizing these linked natural and human consequences, it provides a timely framework for rethinking delta sustainability under climate change. Full article

Background: Post-acute sequelae of COVID-19 (PASC), commonly known as long COVID, affects an estimated 10–30% of SARS-CoV-2 non-hospitalised and 50–70% of hospitalised survivors. This condition remains clinically heterogeneous, and the specific mechanisms driving the transition from acute infection to chronic sequelae remain poorly understood. We assessed independent risk factors, tracked the evolution of clinical features, defined distinct symptom-based phenotypes, and assessed the impact of different pandemic waves on the likelihood of developing long COVID in hospitalised survivors. Methods: We conducted a single-centre, retrospective cohort study at a university hospital in London. The population comprised 627 adults hospitalised with acute COVID-19 between February 2020 and December 2022. Baseline characteristics and outcomes were compared between long COVID and resolved cases using appropriate statistical tests for continuous and categorical variables. Multivariable logistic regression identified risk factors. McNemar’s test quantified the phenotypic shift from admission to follow-up. Latent Class Analysis (LCA) identified clinical subtypes based on symptom clusters. Results: Of 627 patients, 252 (40.2%) met long COVID criteria. Comorbidity burden was the strongest predictor; patients with a single condition had a 4-fold increase in odds (aOR 4.62, 95% CI 2.36–9.04). The ORs were also significantly elevated among patients with 2 (aOR 3.26), 3 (aOR 2.68), or 4 or more (aOR 3.24) comorbidities. Older age (aOR 1.04), acute disease severity (measured by length of hospital stay) (aOR 1.27 per log-day) and elevated admission fibrinogen (aOR 1.21 per g/L) were significant predictors. Temporal analysis revealed a precipitous decline in risk from Wild-type/Alpha (>50%) to Delta/Omicron (<21%). We observed a distinct phenotypic shift: while acute respiratory inflammation resolved, systemic fatigue increased fourfold (7.0% to 32.4%), and memory difficulties emerged in the post-acute phase. LCA identified two phenotypes: fatigue-dominant and multisystem phenotypes. Conclusions: Long COVID is a multifactorial syndrome driven by host susceptibility, acute severity, and persistent coagulopathy. Clinical management should move beyond a monolithic approach and favour phenotype-specific strategies. Full article

Maritime transport emits a range of atmospheric pollutants, including sulfur oxides (SO_x), nitrogen oxides (NO_x), particulate matter (PM), and volatile organic compounds (VOCs), which contribute to air pollution and are associated with adverse environmental and public health impacts. To mitigate these impacts, the International Maritime Organization (IMO), London, UK introduced the global sulfur cap (IMO 2020), which entered into force on 1 January 2020, limiting the sulfur content of marine fuels to 0.50% m/m. This study systematically reviews the environmental and public health impacts of shipping emissions following the implementation of IMO 2020. A systematic literature review was conducted in accordance with PRISMA 2020 guidelines using Scopus, Web of Science, PubMed, and supplementary sources. Following a structured screening process, 67 studies published between 2020 and 2025 were included and analyzed through descriptive, bibliometric, and thematic synthesis approaches. The reviewed studies consistently reported substantial reductions in sulfur dioxide (SO₂) emissions, sulfate aerosols, and shipping-related particulate matter following IMO 2020. These reductions were associated with improved air quality in major maritime and port regions and reduced population exposure to harmful pollutants. However, the reviewed evidence also identified ongoing challenges, including emissions of ultrafine particles and volatile organic compounds, secondary pollutant formation, contamination associated with scrubber washwater discharge, and reduced sulfate aerosols contributing to positive radiative forcing. Overall, the reviewed evidence suggests that sulfur-related air pollution generally declined following the entry into force of IMO 2020, although these observations should be interpreted alongside other concurrent developments that influenced global shipping activities during the study period. This review synthesizes current evidence on the environmental and public health impacts of IMO 2020, identifies emerging knowledge gaps, and provides an evidence base to support future shipping emission policies and research. Full article

Background: Thyroid function tests are frequently requested, but manufacturer reference intervals often lack age- or sex-based stratification. This study established indirect reference intervals for thyroid stimulating hormone (TSH), free thyroxine (fT4) and free triiodothyronine (fT3) in a large adult population. We evaluated unsupervised algorithms and conventional partitioning to identify subgroups, compared multiple limit estimation methods, and assessed the diagnostic performance of the derived intervals against an independent, clinically defined external validation cohort. Methods: Data from 37,255 adults (age ≥ 18) collected between 2022 and 2024 were analyzed; a reference population of 5870 individuals was established following standardized exclusion criteria. Age-based subgroups were identified through hierarchical clustering with the Elbow method, and variable importance was assessed using Random Forest analysis. Reference intervals were calculated using non-parametric, Bhattacharya, refineR, and reflimR algorithms, applied to three population frameworks: (1) the total population without stratification, (2) subgroups derived from hierarchical clustering and (3) subgroups defined by the conventional Harris–Boyd partitioning method. Diagnostic performance was subsequently evaluated in an independent external cohort (National Health and Nutrition Examination Survey [NHANES]; N = 2297) for all estimated reference intervals. Three classification scenarios were assessed: TSH-only, fT4-only, and combined TSH + fT4, with sensitivity, specificity, Youden index, and decision curve analysis performed for each. Results: Random Forest analysis identified age as the dominant variable influencing TSH, fT4 and fT3 distributions (mean decrease in accuracy: TSH 41.62, fT4 44.18, fT3 43.7), while sex showed the lowest impact. Clustering yielded six age-based subgroups for analytes. Harris–Boyd partitioning yielded six age-based subgroups for TSH, two sex-based subgroups for fT4, and six combined age-and-sex subgroups for fT3. TSH limits were broadly concordant across all three approaches (six-subgroup partitioning: 0.36–0.68 to 4.75–5.67 mIU/L). For fT4, conventional (sex-based) and clustering (age-based) partitioning produced similar ranges (11.33–20.08 pmol/L), except reflimR’s notably lower limit (10.90 pmol/L). For fT3, conventional (age + sex) and clustering (age-only) partitioning showed comparable ranges (3.36–7.03 pmol/L), with clustering revealing a clearer age-related decline in the oldest group. Diagnostic performance varied markedly by analyte. TSH-only classification achieved positive discrimination across all 13 methods (Youden index: 0.173–0.239). In contrast, fT4-only and combined TSH + fT4 classifications performed at or below chance for most methods, with 75% of the cohort falling outside fT4 reference intervals, indicating an inter-platform harmonization issue rather than a partitioning failure. Decision curve analysis confirmed TSH-only classification’s superiority, exceeding universal testing from pt ≈ 0.20 onward across all methods. Conclusions: Age-stratified reference intervals combined with limit estimation showed potential diagnostic advantages over manufacturer and non-stratified intervals; however, an independent external validation using a clinically defined outcome indicated that this advantage was not consistently reproduced and was dependent on the clinical decision threshold considered. These results suggest that age stratification and algorithm choice merit further clinically adjudicated validation before broad clinical adoption, and that unsupervised clustering offers a practical, objective alternative to manual subgrouping for laboratories pursuing this approach. Full article

Structural population imbalance has become a critical issue in rural areas under ongoing urban–rural transformation. Rural demographic change is closely linked to urban development and spatial planning, yet existing studies have largely focused on single-dimensional issues such as aging or population decline, limiting understanding of regional demographic diversity and rural–urban interactions. To address this limitation, this study proposes the Point–Flow–Area (PFA) model, a multidimensional framework integrating population age structure, migration patterns, and spatial distribution. The model is applied through empirical case studies to examine rural population imbalance across regions. The results reveal substantial regional differences in demographic structure, migration dynamics, and spatial clustering. Even regions with similar age structures exhibit different migration pathways and spatial patterns, reflecting varying relationships with nearby urban areas. These findings indicate that rural population change should be understood within broader urban–rural systems rather than as isolated local phenomena. The PFA model offers both a conceptual framework and an analytical tool for examining multidimensional population dynamics and supporting more place-sensitive approaches to regional and urban planning. Full article