Distribution Patterns Research Articles

Effect of High-Stress Levels on the Shear Behavior of Geosynthetic-Reinforced Marine Coral Sands

As an important construction material, the mechanical and deformation properties of marine coral sand determine the safety and stability of related island and coastal engineering construction. The porous and easily broken characteristics of coral sand often make it difficult to meet engineering construction needs. In particular, coral sand undergoes a large amount of particle breakage under high-stress conditions, which in turn negatively affects its mechanical and deformation properties. In this study, the macro- and micro-mechanical behavior of geosynthetic-reinforced coral sand under high confining pressure was investigated and compared with unreinforced cases using the three-dimensional discrete element method (DEM), which was verified by indoor triaxial tests. The results showed that the stress–strain responses of unreinforced and reinforced coral sand under high confining pressure showed completely different trends, i.e., the hardening tendency shown in the reinforced case. Geosynthetic reinforcement can significantly inhibit the stress–strain softening and bulging deformation of coral sand under high confining pressure, thus improving the shear mechanical performance of the reinforced sample. At the microscopic scale, high confining pressure and reinforcement affected the contact force distribution pattern and stress level between particles, determining the macroscopic mechanical and deformation performance. In addition, the breakage of particles under high confining pressure was mainly affected by shear strain and reinforcement. The particle fragment distribution, particle gradation, and relative breakage index exhibited different trends at different confining pressure levels. These breakage characteristics were closely related to the deformation and stress levels of unreinforced and reinforced samples.

An Analysis of Marketing Status of BT Cotton Seed in Devbhumi Dwarka District, Gujarat, India

The main objectives of the study were to assess the company’s distribution pattern of quality seed material their market share, marketing channels. Multistage sampling technique were adopted. The total 120 farmers and 20 dealers were selected from four taluka i.e., Bhanvad, Khambhalia, Kalyanpur, Okhamandal (Dwarka) of Devbhumi Dwarka district of Gujarat state. The five wholesaler/distributors were selected from district headquarters. The primary data were collected through personal interview with farmers, dealers, wholesaler/distributors using well-structured questionnaires and interview scheduled. Results revealed that most of Bt cotton growers to be middle aged farmers. The pattern of land holding distribution shows that majority of the Bt cotton growers belonged to the small and marginal land holding category. Social participation of Bt cotton growers shows that they are not members of any organization. The well was found to be the main source of irrigation water and most of Bt cotton growers were reported to attained primary level of education From the study, it was found that Rasi seed (P) Ltd. Occupied major market share in Devbhumi Dwarka district. Among different marketing channels, it was observed that marketing channel-I (MC-I) (Company→ Wholesaler/Distributors→ Dealer→ Bt cotton grower) is the most prevalent channel in the sampling area.

Repeatome Analysis and Satellite DNA Chromosome Patterns in Hedysarum Species

The cosmopolitan genus Hedysarum L. (Fabaceae) is divided into sections Hedysarum, Stracheya, and Multicaulia. This genus includes many valuable medicinal, melliferous, and forage species. The species taxonomy and genome relationships within the sections are still unclear. We examined intra- and interspecific diversity in the section (sect.) Hedysarum based on repeatome analyses using NGS data, bioinformatic technologies, and chromosome FISH mapping of 35S rDNA, 5S rDNA, and the identified satellite DNA families (satDNAs). A comparison of repeatomes of H. alpinum, H. theinum, and H. flavescens revealed differences in their composition. However, similarity in sequences of most satDNAs indicated a close relationship between genomes within sect. Hedysarum. New effective satDNA chromosomal markers were detected, which is important for karyotype analyses within Hedysarum. Intra- and interspecific variability in the chromosomal distribution patterns of the studied markers were revealed, and species karyograms were constructed. These results provided new insight into the karyotype structures and genomic diversity within sect. Hedysarum, clarified the systematic position of H. sachalinense and H. arcticum, and confirmed the distant genomic relationships between species from sections Hedysarum and Multicaulia. Our findings are important for further comparative genome studies within the genus Hedysarum.

Effects of exposure to outdoor light at night on blood lipids in China: a nationwide cross-sectional study.

Previous studies have reported that a potential association between exposure to outdoor light at night (LAN) and diseases. However, there is no evidence regarding the impacts of outdoor LAN exposure on lipid metabolism in humans. This study aims to evaluate the associations between outdoor LAN exposure and the prevalence of dyslipidemia, using a nationwide sample of 10,894 adults aged ≥ 45 years from 150 investigated sites across China in 2011-2012. Outdoor LAN exposure was assessed by using satellite imaging data. The prevalence ratio (PR) was calculated. The present study found that a per-quintile LAN exposure was positively associated with the prevalence of high LDL-cholesterol (PR = 1.10, 95% CI = 1.04-1.16), high triglyceride (PR = 1.07, 95% CI = 1.03-1.12), low HDL-cholesterol (PR = 1.11, 95% CI = 1.08-1.16), and dyslipidemia (PR = 1.06, 95% CI = 1.03-1.09). The fifth quintile of LAN exposure was associated with a significantly increased prevalence of dyslipidemia (PR = 1.20, 95% CI = 1.07-1.35) compared with the first quintile of exposure. Long-term exposure to outdoor LAN was positively associated with dyslipidemia prevalence. Public policies aimed at reducing light pollution at night, guided by the spatial distribution patterns, could lessen the adverse effects.

Habitat suitability models reveal extensive distribution of deep warm-water coral frameworks in the Red Sea

AbstractDeep-sea coral frameworks are understudied in the Red Sea, where conditions in the deep are conspicuously warm and saline compared to other basins. Habitat suitability models can be used to predict the distribution pattern of species or assemblages where direct observation is difficult. Here we show how coral frameworks, built by species within the families Caryophylliidae and Dendrophylliidae, are distributed between water depths of 150 m and 700 m in the northern Red Sea and Gulf of Aqaba. To extrapolate the known (ground-truthed) positions of these deep frameworks, we use environmental and geomorphometric variables to inform well-performing maximum entropy models. Over 250 km2 of seafloor in our study area are identified as suitable for such frameworks, equivalent to at least 35% of the area of photic-zone coral reefs in the same region. We hence contend that deep-water coral frameworks are an important and underappreciated repository of Red Sea biodiversity.

Putative past, present, and future spatial distributions of deep-sea coral and sponge microbiomes revealed by predictive models

Abstract Knowledge of spatial distribution patterns of biodiversity is key to evaluate and ensure ocean integrity and resilience. Especially for the deep ocean, where in situ monitoring requires sophisticated instruments and considerable financial investments, modelling approaches are crucial to move from scattered data points to predictive continuous maps. Those modelling approaches are commonly run on the macrobial level, but spatio-temporal predictions of host-associated microbiomes are not being targeted. This is especially problematic as previous research has highlighted that host-associated microbes may display distribution patterns that are not perfectly correlated with host biogeographies, but also with other factors such as prevailing environmental conditions. We here establish a new simulation approach and present predicted spatio-temporal distribution patterns of deep-sea sponge and coral microbiomes, making use of a combination of environmental data, host data, and microbiome data. This approach allows predictions of microbiome spatio-temporal distribution patterns on scales that are currently not covered by classical sampling approaches at sea. In summary, our presented predictions allow (i) identification of microbial biodiversity hotspots in the past, present, and future, (ii) trait-based predictions to link microbial with macrobial biodiversity, and (iii) identification of shifts in microbial community composition (key taxa) across environmental gradients and shifting environmental conditions.

Time Series Clustering of Sea Surface Temperature in the Mediterranean and Black Sea Marine System

ABSTRACTSea surface temperature (SST) is a significant climatic variable that affects the climate of the Earth. Monitoring a location's SST pattern is useful for several research areas, including weather forecasting and climate change. In this study, the emerging hot spot and cold spot patterns of SST in the Mediterranean and Black Sea Marine System (MBMS) were examined, the spatial distribution characteristics and temporal changes of SST in the sub‐basins were analysed, and future predictions were made. A distinctive aspect of the research lies in the introduction of novel techniques, specifically the application of space time cube and evolving hot spot analysis, for visualising and evaluating SST in the MBMS. This approach sets the study apart by pioneering the utilisation of these methods in this particular context. In the examined region, SST demonstrates a decreasing trend from east to west and from south to north. The forecast suggests that this spatial distribution pattern will persist in 2033, further accentuated by the intensification of the warming effect. Nine different time series clusters are defined within this distribution pattern. Although it changes seasonally, the prevailing statistically significant hot spots in the study area are primarily characterised by new hot spots, intensifying hot spots, sporadic hot spots and oscillating hot spots. The trends of hot and cold spot clusters, along with SST values, were assessed for all sub‐basins in the MBMS. Conversely, the observed clustering category among statistically significant cold spots is identified as persistent cold spots, diminishing cold spots, sporadic cold spots, oscillating cold spots and historical cold spots. The spatiotemporal analysis in this research has provided notable insights, offering a spatial context to the previously explored temporal trends of SST in the MBMS.

Revealing How Human Activity and Native Plants Outshine Climate in Shaping New Invasive Alien Plant Elevational Patterns in Nature Reserves

ABSTRACTAimWe aim to investigate whether invasive alien plants introduced at different times exhibit variations in elevational distribution patterns and to explore the correlations of these patterns with climate, native plants and human activity.LocationGuangxi, China.MethodsWe recorded plant richness and cover across elevational gradients at 25–34 sites within each reserve, utilising 84–134 roadside plots per site. Using generalised linear mixed model (GLMM), we assessed the impacts of climate, native plants and human activity on the distributions of all, old and new invasive alien plants across the region and within the nature reserves.ResultsAt regional scales, the cover of all, new and old invasive alien plants decreased with increasing elevation, while only the richness of old invasive alien plants exhibited a similar pattern. Contrasting patterns were observed in Dayao Mountain, where the cover of old invasive alien plants decreased while the cover of new invasive alien plants increased. The richness patterns of all and new invasive alien plants were opposite between Dayao Mountain and Yachang Orchid. Moreover, native plant richness was negatively correlated with the richness of invasive alien plants, while interference intensity positively affected new invasive alien plants at both regional and reserve scales. At the regional scale, native plant richness accounted for 78.27%, 91.94% and 60.9% of all, old and new invasive alien plants respectively. Interference intensity accounted for 33.85% of the variation in new invasive alien plants. Annual mean temperature positively influenced the cover of all and old invasive alien plants at both regional and reserve scales, explaining 36.91% and 74.28% of their regional variation. Additionally, interference intensity and distance to human settlements positively impacted the cover of new invasive alien plants, contributing to 50.95% and 31.92% of their variation at regional scales.Main ConclusionThe distinct distribution patterns of old and new invasive alien plants highlight the significance of residence time in understanding their dynamics. Climate factors constrain the cover distribution of all and old invasive alien plants, whereas interference intensity and distance to settlements determine the distribution of new invasive alien plants. Notably, native plants play a vital role in preventing the establishment and spread of invasive alien plants within nature reserves, and their effectiveness increases with longer residence times. Our findings highlight the critical importance of minimising human interference and conserving native species for the effective management of invasive alien plants in nature reserves.

Vehicle Collision Analysis of the Reinforced Concrete Barriers Installed on Bridges Using Node-Independent Model

This paper focuses on improving vehicle collision simulations using finite element analysis (FEA) to examine interactions between reinforced concrete barriers and bridge decks. Three scenarios are explored: treating the barrier as a rigid body, analyzing reinforcement with a fixed base, and including the bridge deck’s cantilever portion beneath the barrier. Except for the rigid body model, a node-independent approach models the complex interactions between reinforcement and concrete in barriers on the bridge deck. This study evaluates barrier strength, occupant risk, and post-collision vehicle safety. Strength is assessed by examining stress in reinforcement and concrete, while occupant risk is measured using Theoretical Head Impact Velocity (THIV) and Post-impact Head Deceleration (PHD). Vehicle trajectory during collisions is also analyzed for stability. The results show significant differences in stress distribution and failure patterns when the bridge deck is considered compared to scenarios without it. Occupant risk evaluations suggest more flexible responses when the bridge deck is included. However, vehicle trajectory post-collision showed no significant differences across scenarios. These findings indicate that modeling efficiency varies based on evaluation criteria, suggesting a more realistic and effective approach for assessing barriers on bridges.

Investigating the Annual Cross-Correlation between HPF, OWF and BUF Ionospheric Parameters over Middle East Region

In this work various correlation methods were employed to investigate the annual cross-correlation patterns among three different ionospheric parameters: Optimum Working Frequency (OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF). The annual predicted dataset for these parameters were generated using VOCAP and ASASPS models based on the monthly Sunspot Numbers (SSN) during two years of solar cycle 24, minimum 2009 and maximum 2014. The investigation was conducted for Thirty-two different transmitter/receiver stations distributed over Middle East. The locations were selected based on the geodesic parameters which were calculated for different path lengths (500, 1000, 1500, and 2000) km and bearings (N, NE, E, SE, S, SW, W, NW) using a Matlab program that was designed and implemented for this purpose. Depending on the investigation results of the cross-correlation, a third order polynomial equation provides a better representation of the correlation between the tested parameters. Also, the annual values of the HPF, OWF, and BUF parameters were predicted using the proposed mathematical correlation equations. These equations were confirmed by comparing their results with the observed datasets for the studied years. Several statistical methods were used to validate the presented data, all of which gave good results for all tested cases. Also, contour plot diagrams were used to visually illustrate the annual average distribution pattern of the tested ionospheric parameters for all geodetic factors for the minimum and maximum years of Solar Cycle 24.

Phthalate esters in baltic lagoons: Spatial distribution, ecological risks, and novel insights into their fate using transcriptomics.

Plasticizers such as phthalate esters (PAEs) are organic compounds widely used in various consumer and industrial products, raising strong environmental concerns due to their pervasive presence and potential adverse effects. Lagoon ecosystems are particularly vulnerable to PAE pollution as they are semi-enclosed and receive high loads of organic materials. The present study investigates the distribution of seven common PAEs in three large European lagoons (Curonian, Vistula and Szczecin) in the southern Baltic Sea. The concentration levels of PAEs in the water column, encompassing both the dissolved and particulate-bound phases, and in sediments were assessed to elucidate distribution patterns and potential ecological risks within these lagoon ecosystems. The average concentration of total PAEs in the water column ranged from 0.03 to 1.45 μg L-1, whereas sediment concentration varied from 0.008 to 1.06 μg g-1, levels comparable to or lower than those found in other European coastal areas. Distribution patterns of PAEs in sediment showed notable similarity across all three lagoons, whereas variations were observed in the water column. Notably, di(2-ethylhexyl) phthalate (DEHP), di-n-octyl phthalate (DOP) and dimethyl phthalate (DMP) emerged as the most concerning congeners in studied lagoons, all of which pose a moderate risk to aquatic organisms. This study applied shotgun transcriptomic analysis to field samples, revealing active microbial communities involved in PAEs degradation in the Baltic lagoons for the first time. The degradation of phthalic acid (PA) into intermediate compounds such as protocatechuate was not identified as a rate-limiting step in the studied environment. The degradation activity was primarily localized in the sediment layers, with Gram-negative bacteria playing a major role, while Gram-positive bacteria appeared incapable of degrading PA. These findings provide valuable insights into the distribution and transformation mechanisms of PAEs in estuarine environments.

Observing character displacement from process to pattern in a novel vertebrate community.

Ecological character displacement, whereby shifts in resource use in the presence of competing species leads to adaptive evolutionary divergence, is widely considered an important process in community assembly and adaptive radiation. However, most evidence for character displacement has been inferred from macro-scale geographic or phylogenetic patterns; direct tests of the underlying hypothesis of divergent natural selection driving character displacement in the wild are rare. Here, we document character displacement between two ecologically similar lizards (Anolis sagrei and A. cristatellus) experiencing novel contact. We identify directional selection during the incipient stages of sympatry in a new community that corresponds to repeated trait divergence across multiple established sympatric communities. By identifying the role of natural selection as character displacement unfolds, we connect how natural selection operating at short timescales may drive broader patterns of trait distributions at larger spatial and temporal scales.

The Dynamics of Air Pollution in the Southwestern Part of the Caspian Sea Basin (Based on the Analysis of Sentinel-5 Satellite Data Utilizing the Google Earth Engine Cloud-Computing Platform)

The Caspian region represents a complex and unique system of terrestrial, coastal, and aquatic environments, marked by an exceptional landscape and biological diversity. This diversity, however, is increasingly threatened by substantial anthropogenic pressures. One notable impact of this human influence is the rising concentration of pollutants atypical for the atmosphere. Advances in science and technology now make it possible to detect certain atmospheric pollutants using remote Earth observation techniques, specifically through data from the Sentinel-5 satellite, which provides continuous insights into atmospheric contamination. This article investigates the dynamics of atmospheric pollution in the southwestern part of the Caspian Sea basin using Sentinel-5P satellite data and the cloud-computing capabilities of the Google Earth Engine (GEE) platform. The study encompasses an analysis of concentrations of seven key pollutants: nitrogen dioxide (NO2), formaldehyde (HCHO), carbon monoxide (CO), ozone (O3), sulfur dioxide (SO2), methane (CH4), and the Aerosol Index (AI). Spatial and temporal variations in pollution fields were examined for the Caspian region and the basins of the seven rivers (key areas) flowing into the Caspian Sea: Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan. The research methodology is based on the use of data from the Sentinel-5 satellite, SRTM DEM data on absolute elevations, surface temperature data, and population density data. Data processing is performed using the Google Earth Engine cloud-computing platform and the ArcGIS software suite. The main aim of this study is to evaluate the spatiotemporal variability of pollutant concentration fields in these regions from 2018 to 2023 and to identify the primary factors influencing pollution distribution. The study’s findings reveal that the Heraz and Gorgan River basins have the highest concentrations of nitrogen dioxide and Aerosol Index levels, marking these basins as the most vulnerable to atmospheric pollution among those assessed. Additionally, the Gorgan basin exhibited elevated carbon monoxide levels, while the highest ozone concentrations were detected in the Sunzha basin. Our temporal analysis demonstrated a substantial influence of the COVID-19 pandemic on pollutant dispersion patterns. Our correlation analysis identified absolute elevation as a key factor affecting pollutant distribution, particularly for carbon monoxide, ozone, and aerosol indices. Population density showed the strongest correlation with nitrogen dioxide distribution. Other pollutants exhibited more complex distribution patterns, influenced by diverse mechanisms associated with local emission sources and atmospheric dynamics.

Assessing Distribution Patterns and Prediction of Metals in Wildlife Sanctuary by Employing Lichen, Expanding Machine Learning Techniques

Assessing Distribution Patterns and Prediction of Metals in Wildlife Sanctuary by Employing Lichen, Expanding Machine Learning Techniques

How elevation and soil properties affect plant distribution patterns and species diversity in the Mediterranean mountain ecosystem of Al-Jabal Al-Akhdar, Libya

How elevation and soil properties affect plant distribution patterns and species diversity in the Mediterranean mountain ecosystem of Al-Jabal Al-Akhdar, Libya

The natural stability of autonomous morphology: how an attraction–repulsion dynamic emerges from paradigm cell filling

AbstractAutonomous morphology, such as inflection class systems and paradigmatic distribution patterns, is widespread and diachronically resilient in natural language. Why this should be so has remained unclear given that autonomous morphology imposes learning costs, offers no clear benefit relative to its absence and could easily be removed by the analogical forces which are constantly reshaping it. Here we propose an explanation for the resilience of autonomous morphology, in terms of a diachronic dynamic of attraction and repulsion between morphomic categories, which emerges spontaneously from a simple paradigm cell filling process. Employing computational evolutionary models, our key innovation is to bring to light the role of ‘dissociative evidence’, i.e., evidence for inflectional distinctiveness which a rational reasoner will have access to during analogical inference. Dissociative evidence creates a repulsion dynamic which prevents morphomic classes from collapsing together entirely, i.e., undergoing complete levelling. As we probe alternative models, we reveal the limits of conditional entropy as a measure for predictability in systems that are undergoing change. Finally, we demonstrate that autonomous morphology, far from being ‘unnatural’, is rather the natural (emergent) consequence of a natural (rational) process of inference applied to inflectional systems.

Numerical simulation of three-dimensional seepage field in a tailing pond under multiple operating conditions.

Establishing strong seepage stability for tailings dams is crucial for ensuring their safety and mitigating the risk of failure. This study developed a three-dimensional seepage numerical model using finite element numerical computation for four different elevation conditions (5070m, 5081m, 5159m, and 5213m) encompassing the pond area and dam body. Seepage calculations were conducted under normal and flooding conditions, and the tailings pond's seepage stability was assessed for various stacking scenarios. The spatial distribution pattern of the infiltration surface and the hydraulic stability of the tailings pond were evaluated, which provides insights into the three-dimensional infiltration stability. Examining the seepage stability under different accumulation conditions revealed distinct spatial distribution patterns of the infiltration surface and hydraulic ratio drop values. The findings indicated that the maximum permeability slope at 5070m elevation ranged from 0.66 to 0.75 at normal operation water level and maximum flood level. Most hydraulic ratio drop values at 5081m were below 0.2, while the anti-seepage lining sections at 5159m and 5213m showed larger values, and maintained the overall hydraulic ratio drop within safe limits. Consequently, the dam body's permeability was deemed secure, and no infiltration damage was anticipated with the proposed design of seepage control and drainage facilities. Moreover, sensitivity analysis of the tailing sand's permeability coefficient demonstrated that variations between 0.2 and 5 times the given parameter align with the seepage control requirements for the tailings dam. Additionally, local geomembrane breakage was found to have minimal impact on the tailing pond's seepage field and the dam body's permeability stability, which provides a scientific foundation for analyzing and designing the seismic static-dynamic stability of the tailings pond.

Respiratory tract bacteria distribution and transmission patterns among individuals in close contact.

Respiratory disease outbreaks frequently occur in settings where individuals are in close contact, for example, schools and factories. However, the transmission patterns of oropharyngeal microbiota among healthy individuals living in clusters are unclear. Therefore, we aimed to investigate the respiratory tract bacteria distribution and transmission patterns among individuals in close contact. A total of 36 freshmen from Peking University Medical School participated in the study. We collected pharyngeal swabs on the first day of enrollment, 15, 30, and 60 days after cohabitation. DNA was extracted from the swabs and subjected to high-throughput sequencing to profile the microbial composition. Statistical analyses were performed to assess diversity and significance. Neisseriaceae, Prevotellaceae, and Streptococcaceae were the most abundant bacterial families detected. Over time, changes were observed in the bacterial communities, with a tendency for increased similarity between dormitory room members. By day 60 of cohabitation, the bacterial communities appeared to be more similar compared to the baseline (prior to cohabitation). The transmission patterns included spreading with colonization, spreading without colonization, and non-spreading. Bacteria belonging to the core genera are most likely to spread and colonize easily. The risk of healthy cohabitants acquiring respiratory pathogens through close contact may be overestimated in epidemiological studies. Therefore, monitoring the spread of core genera that are easily transmitted and colonized is crucial for effective prevention of respiratory pathogen transmission.

Abstract B075: Detection of early gastric carcinoma by micronuclei DNA from erythrocytes

Abstract Background: Advancements in non-invasive diagnostic technologies for gastric carcinoma (GC), including serum microRNA and cell-free DNA assays, have shown promise but still face challenges in achieving consistent early detection. Micronuclei (MN), extranuclear bodies harboring fragmented chromosomal segments, are indicative of genomic instability and have been employed in genotoxicity assessments and cancer diagnostics. We have developed a novel technique (WO2021/228246 A1) for the purification and characterization of micronuclei DNA (MN-DNA) extracted from erythrocytes in peripheral blood. Here, we evaluated the potential of micronuclei DNA (MN-DNA) from 2ml peripheral blood for early gastric carcinoma detection and explored its application for early cancer diagnosis. Methods: We assembled a clinical cohort consisting of 425 healthy donors (HDs) and 282 gastric cancer patients, from whom 1-2 mL peripheral blood samples were collected. Participants were randomly allocated into training, validation, and independent test cohorts in a 7:2:1 ratio, ensuring similar distributions of cancer stages and gender. MN-DNA was isolated from erythrocytes and subjected to comprehensive whole-genome sequencing. Predictive machine learning models were constructed utilizing distinct tumor-associated MN-DNA features identified through genome-wide analysis to distinguish between HDs and GC. Results: Comprehensive genome-wide analysis of MN-DNA demonstrated pronounced disparities in distribution patterns between HDs and GC patients. The predictive model built on MN-DNA features achieved an AUC of 97.69% (95%CI: 95.57- 99.81%), with an 96.47% specificity and 91.07% sensitivity in the independent test cohort. The model identified early GC (stage 0-I) and advanced GC (stage II-IV) with sensitivities of 95.24% or 78.57%, respectively. Conclusions: Our results demonstrate that MN-DNA from 1-2mL peripheral blood enable accurate detection of GC, especially in early GC. As a type of cytoplasmic DNA, MN-DNA can provide a valuable tool for early cancer detection, offering different underlying mechanisms compared to current methods. Research sponsor: Timing Biotech. Citation Format: Yuehua Han, Xingyun Yao, Haobo Sun, Cheng Fang, Peiwei Li, Honghao Liang, Jie Jin, Xiaofei Gao. Detection of early gastric carcinoma by micronuclei DNA from erythrocytes [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B075.

Semantic and distributional patterns of Spanish negation with nouns and adjectives: A Lexical-Realizational Functional Grammar approach

This study examines the semantic and distributional characteristics of the Spanish negation no when it occurs before nouns and adjectives, specifically, whether these instances diverge from sentential negation, but also from negation via prefixes such as des- ‘dis-’ or in- ‘in-, un-’. Using data from the Spanish Web 2011 corpus, it is shown that the use of no before adjectives aligns with other forms of constituent negation, often resulting in a contradictory interpretation, that is similar to that of sentential negation. However, the interpretation of no preceding nouns exhibits a broader range of interpretations, depending on whether the noun refers to an eventuality, quality, or entity. In such instances, no shows parallels to negative prefixes, frequently indicating privation rather than contradiction. Consequently, no can be analyzed as a building block of phrases, expressing syntactic negation, behaving similarly to other adverbs, as well as a building block of words, expressing lexical negation, resembling Spanish prefix-like elements like cuasi ‘almost’ or ex ‘ex-’. The analysis is couched within the framework of Lexical-Realizational Functional Grammar (LRFG), integrating aspects of Lexical Functional Grammar and Distributed Morphology. This approach does not treat morphology and syntax as separate modules, thus allowing us to account for the variable distribution and interpretation of no by means of a single representation in vocabulary structure, drawing on constituent structure representations which are needed on independent grounds for adverbs and for prefix-like elements.