Aggregation Patterns Research Articles

Spatially mapping the tumour immune microenvironments of non-small cell lung cancer.

Lung cancer is the leading cause of cancer-related deaths. An enhanced understanding of the immune microenvironments within these tumours may foster more precise and efficient treatment, particularly for immune-targeted therapies. The spatial architectural differences between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are relatively unexplored. Here, we applied imaging mass cytometry to a balanced cohort of LUAD and LUSC patients, matched for clinical factors such as age, sex, and smoking history, to analyze 204 histopathology images of tumours from 102 individuals with non-small cell lung cancer (NSCLC). By analyzing interactions and broader cellular networks, we interrogate the tumour microenvironment to understand how immune cells are spatially organized in clinically matched adenocarcinoma and squamous cell carcinoma subsets. This spatial analysis revealed distinct patterns of immune cell aggregation, particularly among macrophage populations, that correlated with patient prognosis differentially in adenocarcinoma and squamous cell carcinoma, suggesting potential new strategies for therapeutic intervention. Our findings underscore the importance of analyzing NSCLC histological subtypes separately when investigating the spatial immune landscape, as microenvironmental characteristics and cellular interactions differed by subtype. Recognizing these distinctions is essential for designing precision therapies tailored to each subtype's unique immune architecture, ultimately enhancing patient outcomes.

Plant Diversity and Interspecific Interactions in Desert-Oasis Transition Zones: Insights from the Badain Jilin Desert

Plant species diversity and spatial distribution patterns are critical for understanding ecosystem dynamics in arid and fragile environments. This study investigates the diversity, spatial distribution, and interspecific associations of shrubs and herbaceous plants in the transition zone of the desert oasis located in the Hexi Corridor and southern edge of the Badanjilin Desert, China. Vegetation data were collected across sample plots spanning three counties in Zhangye City. Important values, diversity indices, and spatial distribution metrics were calculated to evaluate plant species dominance and community structure. Interspecific relationships were analyzed using variance ratio (VR), clumping indicators, and corrected χ2 tests. The shrub community exhibited low species diversity (H′ = 1.754) and was dominated by Reaumuria songarica (Pall.) Maxim (IV = 111.175), reflecting its superior adaptability to arid conditions. In contrast, the herbaceous community displayed higher diversity (H′ = 2.498), with Aristida adscensionis L. (IV = 48.6174) as the dominant species. Both communities showed predominantly aggregative spatial distribution patterns, influenced by localized resource availability and adaptive strategies. Weak interspecific associations characterized the shrub community, with limited competition among dominant species, while the herbaceous community demonstrated significant negative correlations, indicating stronger resource competition. The study highlights the contrasting diversity and ecological roles of shrubs and herbaceous plants in arid ecosystems, shaped by resource limitations and environmental stressors. Effective conservation strategies are needed to protect dominant species and sustain ecosystem resilience in desert regions. Future research should focus on below-ground interactions and long-term monitoring to enhance understanding of species coexistence and community stability.

Deciphering the Role of Vinylene Carbonate in Shaping CO2 Cluster Growth and Stability via Wavelet-Enhanced Microwave Spectroscopy.

This study presents the first integration of wavelet denoising with resonator-enhanced microwave spectroscopy to explore the formation and characteristics of gas-phase heterogeneous vinylene carbonate-(CO2)1-5 clusters. Through this innovative approach, faint spectral lines were detected with efficiency, enhancing our understanding of complex interaction patterns that govern the growth and stability of these molecular clusters. It was found that CO2 aggregates preferentially around the vinylene carbonate molecule through C···O tetrel bonds at the carbonyl and ether groups, altering the typical self-aggregation topology of free CO2 clusters. This leads to more symmetrical growth around the vinylene carbonate monomer. Our findings provide insights into the solvation mechanisms of compounds in supercritical CO2 thereby advancing the understanding of subnanoscale CO2 aggregation patterns.

Temperature-Dependent Wax Precipitation Characteristics in Gas Condensates: Composition, Aggregation, and Crystallization Patterns

Temperature-Dependent Wax Precipitation Characteristics in Gas Condensates: Composition, Aggregation, and Crystallization Patterns

CRISPR-associated Plasmonic Colorimeter Method (Ca-PCM): A real-time RGB detection system for gold nanoparticles-based nucleic acid biosensors.

The detection of genetic sequences represents the gold standard procedure for species discrimination, genetic characterisation of tumours, and identification of pathogens. The development of new molecular detection methods, accessible and cost effective, is of great relevance. Biosensors based on plasmonic nanoparticles, such as gold nanoparticles (AuNPs), provide a powerful and versatile platform for highly sensitive, economic, user-friendly and label-free sensing. However, the readout techniques typically employed with such sensors lack temporal and kinetic information, which hampers the ability to perform quantitative detection. In this study, a novel methodology designated the 'CRISPR-associated Plasmonic Colorimeter Method' (Ca-PCM), has been developed. This method combines RNA target recognition by CRISPR LwaCas13a, AuNPs' aggregation, and real-time colorimetric Red-Green-Blue (RGB) analysis. The system registers the AuNP's plasmonic signatures in real-time using a RGB colour sensor with 3-channel silicon photodiodes having blue, green and red sensitivities. The acquired signals are automatically analysed by an algorithm designed to distinguish between positive and negative samples and to correlate the temporal spectral patterns of aggregation with dose-dependent molecular detection of the RNA target. In addition, the combination of Ca-PCM with a previous isothermal amplification allows the target efficient detection in real clinical applications. We have shown that the combination of RGB analysis and continuous temporal measurements is a novel and promising method to characterise the behaviour of gold nanoparticle-based biosensors and to achieve dose-dependent target detection. In addition, the simplicity and cost-effectiveness of this new approach expand the possibilities of other plasmonic-based biosensors and their applicability in low-resources clinical environments.

Delineating the effect of trehalose nanoparticles on aggregation pattern of apo-α-lactalbumin protein: A nano-approach towards counteracting proteinopathies

Delineating the effect of trehalose nanoparticles on aggregation pattern of apo-α-lactalbumin protein: A nano-approach towards counteracting proteinopathies

Contrasting seasonal patterns in particle aggregation and dissolved organic matter transformation in a sub-Arctic fjord

Contrasting seasonal patterns in particle aggregation and dissolved organic matter transformation in a sub-Arctic fjord

A Novel Stochastic Interacting Particle-Field Algorithm for 3D Parabolic-Parabolic Keller-Segel Chemotaxis System

We introduce an efficient stochastic interacting particle-field (SIPF) algorithm with no history dependence for computing aggregation patterns and near singular solutions of parabolic-parabolic Keller-Segel (KS) chemotaxis system in three-dimensional (3D) space. In our algorithm, the KS solutions are approximated as empirical measures of particles coupled with a smoother field (concentration of chemo-attractant) variable computed by a spectral method. Instead of using heat kernels that cause history dependence and high memory cost, we leverage the implicit Euler discretization to derive a one-step recursion in time for stochastic particle positions and the field variable based on the explicit Green’s function of an elliptic operator of the form Laplacian minus a positive constant. In numerical experiments, we observe that the resulting SIPF algorithm is convergent and self-adaptive to the high-gradient part of solutions. Despite the lack of analytical knowledge (such as a self-similar ansatz) of a blowup, the SIPF algorithm provides a low-cost approach to studying the emergence of finite-time blowup in 3D space using only dozens of Fourier modes and by varying the amount of initial mass and tracking the evolution of the field variable. Notably, the algorithm can handle multi-modal initial data and the subsequent complex evolution involving the merging of particle clusters and the formation of a finite time singularity with ease.

Disproportionate vulnerability to and unique aggregation pattern of non-AIDS comorbidities among women with HIV in China

Abstract Background Whether and how sex plays differential roles in aging-related multimorbidity among people with HIV (PWH) is poorly characterized. Methods We included 2479 PWH and 5376 people without HIV (PWoH) from the baseline assessment of the Comparative HIV and Aging Research in Taizhou (CHART) cohort. Ten non-AIDS comorbidities (NACM) were investigated. Multiple logistic regression was used to assess the correlates of multimorbidity (defined as the coexistence of ≥2 NACM). Multimorbidity patterns were identified through hierarchical cluster analysis. Results The prevalence of multimorbidity was higher in PWH than in PWoH (74.6% vs. 66.9%, p < 0.001). This difference was particularly pronounced in women in each of the age groups from 18 through 59 years and among men in each of the age groups from 18 through 49 years. A significant interaction between sex and HIV on multimorbidity was identified (p < 0.001), with the strength of the association between HIV infection and multimorbidity being stronger in women than in men. Women with HIV presented a unique aggregation pattern of multimorbidity, where neuropsychiatric disorders (depression, neurocognitive impairment) clustered with cardiometabolic diseases. In contrast, all men and women without HIV manifested a similar multimorbidity pattern, where depression and neurocognitive impairment were clustered with hematologic abnormalities but not with cardiometabolic diseases. Conclusions Earlier onset and higher burden of multimorbidity in PWH, as well as disproportionate vulnerability to and unique multimorbidity pattern among women with HIV, underscore the urgent need for early and sexually-oriented integrative interventions and health services targeting multimorbidity in PWH.

Familial Aggregation of Alcohol Consumption and Associated Factors in East Azerbaijan Province: A Cross-Sectional Study

Background and Objectives: The present study aimed to assess the prevalence and familial aggregation pattern of alcohol consumption among father-offspring, mother-offspring, siblings, and spouses in Tabriz city, and to investigate the associated risk factors. Methods: This cross-sectional study was conducted in 2023 on 860 individuals in Tabriz city. The heads of households were selected as proband individuals. Conveniently, probands were recruited from daily visitors, and upon agreeing to participate, their first-degree relatives (spouse and children) were also invited to join in. Data were collected using standard self-reported questionnaires. Generalized Estimating Equations (GEE) were employed to assess family aggregation among father- offspring, mother-offspring, and siblings. Results: No significant of familial aggregation alcohol consumption was observed between spouses (OR=0.54 (0.16-1.8)). Although familial aggregation was observed between mothers and children, this was not statistically significant (OR=1.54 (0.8-2.94)). There was a significant familial aggregation of alcohol consumption between fathers and children (OR=1.98 (1.08-2.5)). Among siblings, familial aggregation was not statistically significant (OR=1.38 (0.41-4.63)). Conclusion: Based on the findings of this study, family members play an important role in influencing the alcohol consumption behaviors of other family members. Additionally, individuals with lower socioeconomic status, those who are divorced, and singles may be more appropriate targets for alcohol consumption screening programs.

The Grouping Patterns of Cervus canadensis songaricus in the Tianchi Bogda Peak Nature Reserve of Tianshan Mountain, Northwestern China.

Grouping behavior is a fundamental component of animal population dynamics, shaped by both environmental factors and the social interactions among individuals, ultimately enhancing adaptability to their habitats. However, the social organization of the wapiti subspecies inhabiting the Tian Shan Mountains remains poorly understood. In this study, we investigated the grouping behavior of Tianshan wapiti in the Bogda Peak Nature Reserve, northwestern China from July 2019 to November 2020. Using infrared-triggered camera traps, we analyzed seasonal variation in group size and group frequency, as well as sex-specific aggregation and segregation pattern. Our results showed that Tianshan wapiti group sizes varied considerably, ranging from 1 to 32 individuals, with most groups being relatively smaller, typically consisting of 1 to 9 individuals. Seasonal differences in group size were significant (H = 28.91, df = 3, p < 0.05). Additionally, group type showed significant variation across seasons (χ2 = 93.32, df = 18, p < 0.05). Anakysis of sex-specifia aggregation and segregation (SSAS) indicated no consistent segregation of females and males throughout the year. However, there was a notable tendency for sex-specific aggregation during July and from October to December. These findings provide new insights into the social organization and seasonal grouping behavior of Tianshan wapiti, contributing to a better understanding of their behavioral ecology and informing conservation and management strategies for this subspecies.

Re‐identification of patterned animals by multi‐image feature aggregation and geometric similarity

AbstractImage‐based re‐identification of animal individuals allows gathering of information such as population size and migration patterns of the animals over time. This, together with large image volumes collected using camera traps and crowdsourcing, opens novel possibilities to study animal populations. For many species, the re‐identification can be done by analysing the permanent fur, feather, or skin patterns that are unique to each individual. In this paper, the authors study pattern feature aggregation based re‐identification and consider two ways of improving accuracy: (1) aggregating pattern image features over multiple images and (2) combining the pattern appearance similarity obtained by feature aggregation and geometric pattern similarity. Aggregation over multiple database images of the same individual allows to obtain more comprehensive and robust descriptors while reducing the computation time. On the other hand, combining the two similarity measures allows to efficiently utilise both the local and global pattern features, providing a general re‐identification approach that can be applied to a wide variety of different pattern types. In the experimental part of the work, the authors demonstrate that the proposed method achieves promising re‐identification accuracies for Saimaa ringed seals and whale sharks without species‐specific training or fine‐tuning.

Charge Arrangement Determines the Sensitivity of Aggregation Patterns between Peptide-Chains to the Surrounding Ionic Environment.

The molecular basis for the liquid-liquid phase separation (LLPS) behavior of various biomolecular components in the cell is the formation of multivalent and low-affinity interactions. When the content of these components exceeds a certain critical concentration, the molecules will spontaneously coalesce to form a new liquid phase; i.e., LLPS occurs. Intrinsically disordered proteins (IDPs) are usually rich in amino acids with charged side-chains, and thus, LLPS-involving interactions between their side-chains are of great interest. However, the molecular details of the coalescence of such charged IDPs in a salt solution are still lacking. Here, we focus on two types of peptide-chains with oppositely charged amino acids in extreme arrangements and investigate their aggregation patterns in various ionic environments. The results show that the interaction patterns between peptide-chains with nonuniform charge arrangement sequences are more sensitive to the surrounding cationic environment, and Na+ ions are more likely to cause aggregation of ASP residues compared to Mg2+ ions. As the ionic concentration increases, the electrostatic interactions between oppositely charged residues are gradually converted into a negative-negative amino acid interaction network bridged by Na+ ions, while the positive charge-rich regions are more strongly inclined to be exposed to the solvent environment and gain greater freedom of movement. Simultaneously, this effect will reach saturation with a further increase of salt concentration. The present study enriches insights into the electrostatic dominant factors in phase separation phenomena at the atomic level, which will hopefully inspire the design and application of targeted LLPS in the future.

Invariant Spatial Pattern Across Mediterranean Scrublands in the Iberian Pear (Pyrus bourgaeana).

The spatial distribution pattern of plant species is frequently driven by a combination of biotic and abiotic factors that jointly influence the arrival, establishment, and reproduction of plants. Comparing the spatial distribution of a target plant species in different populations represents a robust approach to identify the underlying mechanisms. We mapped all reproductive individuals of the Iberian pear (Pyrus bourgaeana) in five plots (1.39-8.57 km2) differing in the activity of seed dispersers and vertebrate herbivores in southern Iberian Peninsula. We used Thomas point process models to quantify the consistency in the spatial pattern and the level of spatial aggregation of this mammal-dispersed tree among the five populations. We tested two hypotheses: (i) because the clumped defecation behavior of some dispersers can lead to local tree aggregation, and because denser groups of fruiting trees can limit seed dispersal by attracting frugivores to specific sites, we expected a consistent small-scale aggregation pattern across all populations; and (ii) because ungulates reduce recruitment by preying on seeds and seedlings, we hypothesize that ungulate activity will show negative relationships with tree density and level of aggregation. Our spatial analysis revealed consistent and highly aggregated small-scale patterns of all Iberian pear populations, with one critical scale aggregation, a low density of clusters and high variability in the number of trees per cluster. Ungulate activity and the number of trees per cluster showed a marginally significant negative correlation, suggesting that in areas with higher ungulate activity, trees tend to form less dense clusters. Although several of the underlying processes varied greatly among the five study sites, the Iberian pear showed a relatively consistent spatial pattern with just quantitative nuances throughout the entire region. This result has significant implications for the reproductive success of the species, management strategies, and ultimately the long-term persistence of populations.

Modeling and Analyzing the Spatiotemporal Travel Patterns of Bike Sharing: A Case Study of Citi Bike in New York

As the urban transportation demand continues to grow, the effective management and optimization of bike-sharing systems are of significant importance for urban planning and transportation engineering. This study aims to identify the spatiotemporal distribution of the peak-period departures and arrivals of bike sharing within Manhattan, New York, and to analyze the community clustering patterns and their underlying rules. Additionally, a comparative analysis across multiple time periods was conducted to enhance the research’s practical value. This study utilized GPS trajectory data from the New York City bike-sharing system for 2023. After analyzing the travel patterns throughout the year, we selected August, the month with the highest usage, to study the origin-destination (OD) travel aggregation patterns using flow models and the theoretical constructs of travel networks, measuring and analyzing travel characteristics. Subsequently, community detection algorithms were applied to analyze the clustering patterns and relationships among various neighborhoods. The findings revealed that the use of bike sharing in New York exhibits an overall trend of increasing and then decreasing throughout the year, with significantly higher usage in the spring and summer compared to the fall and winter. Notably, August saw the highest usage levels, with hotspots primarily concentrated in the southwestern part of Manhattan, which is also the economic center of New York City. The OD aggregation patterns across the upper, middle, and lower parts of August show distinct variations. Through community analysis, several strongly associated neighborhood clusters were identified, which exhibited both aggregation and dispersion trends over time. In southern Manhattan, a community with high modularity emerged, showcasing strong interconnections among neighborhoods. These findings provide valuable insights into the usage patterns of bike sharing in New York and the factors influencing them, offering significant implications for the optimization of bike-sharing system operations and planning.

Cortical Tau Aggregation Patterns Associated With Apraxia in Patients With Alzheimer Disease.

Apraxia is a frequently observed symptom in Alzheimer disease (AD), but the causal pathomechanism underlying this dysfunction is not well understood. Previous studies have demonstrated associations between various cognitive dysfunctions in AD and cortical tau deposition in specific brain areas, suggesting a causal relationship. Thus, we hypothesized that specific regional patterns of tau pathology in praxis-related brain regions may be associated with apraxic deficits in AD. For this purpose, we performed PET imaging with the second-generation tau-PET tracer [18F]PI-2620 in a well-defined group of patients with AD (N = 33) who had been systematically assessed for apraxia. Patients with a biomarker-confirmed diagnosis of AD were recruited in addition to a sample of cognitively unimpaired (CU1) control participants. Both groups underwent apraxia assessments with the Dementia Apraxia Screening Test. In addition, PET imaging with [18F]PI-2620 was performed to assess tau pathology in the patients with AD. To specifically investigate the association of apraxia severity with regional tau pathology, we compared the PET data from this group with an independent sample of amyloid-negative cognitively intact participants (CU2) by generation of z-score deviation maps and submitted these maps to a voxel-based multiple regression analysis. A total of 120 participants (39% female) with a mean age of 67.9 (9.2) years were included in the study (AD = 33; CU1; N = 33; CU2; N = 54). We identified a significant correlation between circumscribed clusters of tau aggregation in praxis-related brain regions (including parietal (angular gyrus), temporal, and occipital regions) and severity of apraxia in patients with AD. By contrast, no significant correlations between tau tracer uptake in primary motor cortex or subcortical brain regions and apraxia were observed. These results suggest that tau deposition in specific cortical praxis-related brain regions may induce local neuronal dysfunction leading to a dose-dependent functional decline in praxis performance in AD. The awareness of this relationship could further refine a differentiated individual diagnostic characterization and classification of patients with AD.

Wildlife trade at the interface between deeply-rooted animal-based traditional medicine and unregulated harvesting of wild animals in West Africa

Local trade remains a data poor component of wildlife crime that must be better understood for more effective combat against the illegal wildlife trade. We assessed the distribution of wildlife markets, diversity of species traded and the extent of the trade chain through spatial analysis of wildlife sale sites and semi-structured interviews with 75 vendors in the 10 largest traditional medicine markets of Benin. GPS coordinates of wildlife markets were used to map their geographic distribution and assess their spatial patterns. We used a generalized linear model to determine the drivers underlying the spatial patterns of wildlife markets. A circular layout was designed to delineate the geographic extent of wildlife trade in terms of supplying sources. We found that wildlife was traded at 121 sale sites in Benin, highly dominated by traditional medicine markets (106 sites). The spatial analysis of markets exhibited an aggregative distribution pattern, and the type of market, the number of stalls in the markets and the municipality status influence significantly the spatial temporality of market distribution. Wildlife trade for traditional medicine affected 268, 96 and 61 bird, mammal and reptile species, respectively, and included species of both high national and global conservation concern. We also found that the national wildlife trade in Benin was supplied from 80% (12/15) West African Economic and Monetary countries, and all the Economic Community of West African States (except Guinea-Bissau) in violation of national laws, CITES, and regional commitments to combat wildlife trafficking (e.g., the West African Strategy for Combatting Wildlife Crime). Our study in Benin is a big step to revealing trade throughout in West Africa. It provides much needed information on wildlife trade structure and driving forces that could help to inform decision-making for better trade regulation and for effective wildlife law enforcement in West Africa. Other studies should do the same to help paint a more complete picture of wildlife trade in West Africa.

JAK2 p.R564 germ line variants associated with hereditary thrombocythemia and hematologic neoplasms.

The Janus kinase 2 (JAK2) V617F mutation activates the transcription pathway and has been well-characterized as a driver of myeloproliferative neoplasms (MPNs). Recently, there has been a heightened interest in understanding germline predisposition to hematological malignancies including MPN, including several reports of familial MPN. Here, we retrospectively analyzed medical records and data from genetic testing to describe twelve patients with germline variants at amino acid position 564 of JAK2. This includes three supportive cases adding to prior literature regarding the germline JAK2 R564Q association with hereditary thrombocythemia, as well as confirmation of JAK2 R564L as a germline variant associated with MPN. Importantly, the symptomatic burden for many of the individuals in this series is comparable to that of individuals with the canonical V617F mutation profile. In the JAK2 R564Q cases, we noted a pattern of familial aggregation, presence of congenital thrombocythemia and co-occurrence with hematological neoplasms. Identification of germline predisposition is essential to understanding the pathogenesis of disease, impact on families, and opportunities for preventive care. Continued research is essential to further characterize the penetrance of these conditions, and how best to monitor, treat and optimize management for these families.

Patterns of soil-transmitted helminth aggregation in the human host population after several years of intensive mass drug administration.

Community-wide mass drug administration (cMDA) is known as an effective, albeit costly, control strategy for soil-transmitted helminth (STH) parasites. A better understanding of STH aggregation after many rounds of cMDA could help shape more cost-effective policies. This analysis uses data from the Geshiyaro project, aiming to break STH transmission by cMDA and water, sanitation and hygiene interventions. Ascaris lumbricoides infection prevalence is derived from egg count data and parasite aggregation is obtained by fitting a negative binomial distribution to the frequency distribution of faecal egg counts. The relationship between parasite dispersion and infection prevalence is approximately linear. Parasite aggregation increases as infection prevalence decreases. A minority of individuals carry most parasites as prevalence decreases in the community. These individuals could be selectively targeted for repeated treatment.

A novel amyloid MRI imaging based on analysis of texture features representing Aß aggregation

AbstractBackgroundThe importance of detecting amyloid β (Aβ) in the early stages of Alzheimer's disease has markedly increased following the approval of Lecanemab, a disease‐modifying drug. MRI is a non‐invasive and less expensive rather than amyloid PET as gold standard for Aβ biomarker, but its clinical ability to detect Aβ has not been demonstrated. MRI phase information reflects paramagnetic substance including iron associated with Aβ aggregation. We have developed a novel approach utilizing multi‐gradient echo (GRE) to perform texture analysis of the phase information, enabling visualization of Aβ. The primary aim of this study is to evaluate the diagnostic capabilities of this "Amyloid MRI" technique.MethodThe consecutive 48 participants (mean age: 72±10, mean MMSE: 25±4) who visited our memory clinic, and underwent both MRI and amyloid PET were enrolled. Amyloid PET images were visually interpreted as Aβ positive (n=30) or negative (n=18), and standardized uptake value ratio (SUVr) maps were generated. Multi‐GRE images were acquired with a 3‐Tesla MRI. We generated a phase slope map, i.e. a first‐order linear estimate of the phase change in time, and segmented four anatomical regions‐of‐interest (ROI) for cortex‐based analysis. Statistical analysis of texture features (mean, SD and entropy) derived from the phase slope map over each ROI was performed. We investigated the correlation between the mean value of regional SUVr and that of texture parameters of the phase slope map, and determined the optimal cut‐off of a linear classifier by ROC analysis based on the diagnosis of amyloid PET.ResultThe correlation coefficients between the mean value of SUVr and the texture features of the phase slope map in parietal, PCCpre, frontal and temporal were 0.57 (p&lt;0.0001), 0.56 (p&lt;0.0001), 0.48 (p&lt;0.0006) and 0.22 (p&lt;0.22), respectively. The optimal cut‐off values for diagnosing Aβ positive or negative showed a sensitivity of 83% (73‐93%), specificity of 89% (74‐103%) and accuracy of 85%(75‐96%).ConclusionThe texture features of the phase slope map could reflect the spatial aggregation pattern of Aβ. Our method highlighted the potential to visualize Aβ using MRI.