Large Clusters Research Articles

Local geometry of NAE-SAT solutions in the condensation regime

AbstractThe local behavior of typical solutions of random constraint satisfaction problems (csp) describes many important phenomena including clustering thresholds, decay of correlations, and the behavior of message passing algorithms. When the constraint density is low, studying the planted model is a powerful technique for determining this local behavior which in many examples has a simple Markovian structure. The work of Coja-Oghlan, Kapetanopoulos, Müller (Comb Prob Comput 29:346-422, 2020) showed that for a wide class of models, this description applies up to the so-called condensation threshold. Understanding the local behavior after the condensation threshold is more complex due to long-range correlations. In this work, we revisit the random regular nae-sat model in the condensation regime and determine the local weak limit which describes a random solution around a typical variable. This limit exhibits a complicated non-Markovian structure arising from the space of solutions being dominated by a small number of large clusters. This is the first description of the local weak limit in the condensation regime for any sparse random csps in the one-step replica symmetry breaking (1rsb) class. Our result is non-asymptotic and characterizes the tight fluctuation $$O(n^{-1/2})$$ O ( n - 1 / 2 ) around the limit. Our proof is based on coupling the local neighborhoods of an infinite spin system, which encodes the structure of the clusters, to a broadcast model on trees whose channel is given by the 1rsb belief-propagation fixed point. We believe that our proof technique has broad applicability to random csps in the 1rsb class.

TMIC-71. ELUCIDATING IMMUNE MICROENVIRONMENTAL DISTINCTIONS BETWEEN IDH-MUTANT ASTROCYTOMA AND OLIGODENDROGLIOMA USING SINGLE-CELL TRANSCRIPTIONAL PROFILING

Abstract Despite exhibiting longer overall survival that IDH-wt counterparts, IDH-mutant gliomas remain uniformly deadly and impact patients in the prime of adult life. The immune microenvironment of IDH-mutant gliomas remains incompletely characterized, particularly with regard to distinctions between IDH-mutant astrocytoma and IDH-mutant, 1p/19q codeleted oligodendroglioma. To address this knowledge gap, we subjected dissociated tumor suspensions derived from 7 astrocytoma and 7 oligodendroglioma clinical samples to flow cytometry-based sorting for the pan-immune marker, CD45, and the microglial marker, P2RY12. This process yielded both microglial and non-microglial immune cell populations, which were then analyzed by scRNA sequencing. This workflow revealed a single large cluster of microglia, characterized by expression of Galectin-1 and lysosomal Lipase A, which was present at a significantly higher level in oligodendroglioma. While the biological significance of this cluster is unclear, gene set enrichment analysis exploring phenotypic differences between microglia in astrocytoma and oligodendroglioma revealed significant increases in expression of gene sets related to antigen presentation in astrocytoma. Parallel analysis of the non-microglial immune fraction showed an increase in the expression of pro-inflammatory gene sets, such as genes related to cytokine secretion, within the CD8 T-cell compartment of astrocytomas. We also observed upregulation of the expression of inflammatory gene sets within the dendritic cells of astrocytomas. Taken together, these changes suggest that the immune compartment of astrocytoma is more active and inflamed, and targeting the immune system in these tumors may represent a potential therapeutic avenue.

Bibliometric analysis of scientific literature on the use of suppositories in the treatment of prostate cancer patients

Nowadays, cancer remains one of the main causes of death worldwide. Statistical data from various literary sources indicate that more than 130,000 people in Ukraine receive this diagnosis as a sentence every year. Cancer can affect any organs of the human body and, over time, the entire organism. In 2024, the agency of the World Health Organization on cancer and the International Agency of Cancer Research published the latest statistical estimates of this pathology in a global format, where prostate cancer is among the five most common oncological pathologies and takes the fourth place. Oncological diseases are one of the priority areas of healthcare development in accordance with the Order of the Ministry of Health of Ukraine No. 1832 dated 07.10.2022 “On Approval of Priority Areas of Healthcare Development for 2023–2025”. It was this fact that determined the choice of the direction of this research in the matter of finding information on the provision of pharmaceutical care, namely the use of a drug – a rectal suppository for the treatment of prostate cancer. The aim of the work is to carry out a bibliometric analysis and further generalize the data of the scientific literature to study the prognostic value and features of the prescription of suppositories in the treatment of prostate cancer. Materials and methods. The data search was conducted in the PubMed electronic database using the following key terms: “prostate cancer and suppositories”, “prostate cancer”. To monitor and analyze international scientific research, with the help of visualization tools and modern SciVal citation metrics using the online platform, bibliometric analysis can be performed. Using the VOSviewer functional program, bibliometric networks were constructed and visualized. Results. A map of the relationships between the most used keywords on the topics of “prostate cancer” and “prostate cancer and suppositories”, grouped into clusters for the period from 1986 to 2024, was built. The clustering of the most used keywords on the subject of “prostate cancer” for the specified period is summarized. According to the bibliographic analysis, interest in the above topic was highest in 2014 and 2021. Conclusions. According to the bibliographic analysis, the interest in the subject of the patients’ treatment with prostate cancer disease continues to grow from 1998 up to the present. The analysis of publication activity using the visualization tool of bibliometric networks VOSviewer for the period from 2014 to 2024 for the key words “prostate cancer” has shown the presence of 14 clusters. The largest cluster is devoted to modern methods of prostate cancer treatment, studies of gene rearrangement, target therapy, carcinogenesis.

Development of significantly hard hypereutectoid plain carbon steel through incomplete austenitization based cyclic quenching treatment

AbstractIn this investigation hot rolled steel bars of 1.24 weight % carbon steel are subjected to incomplete austenitization based cyclic quenching treatment. Each cycle consists of inserting the specimen in an electric resistance furnace at a temperature of 894 °C and holding for a short duration (6 minutes), followed by oil quenching to the room temperature. Such a typical thermal cycling results in the evolution of a novel microstructure that comprises of large clusters and blocks of cementite in a matrix of martensite after 3 and 4 cycles. Accordingly, a significantly high hardness (7.13 GPa) is achieved on execution of 3 cycles which envisages a new pathway of incomplete austenitization based cyclic quenching treatment for development of new‐generation plain carbon hypereutectoid tool steel.

Genetic Divergence Analysis for Quantitative Traits in Rice (Oryza sativa L.) Germplasm under Irrigated Conditions

The present study was with the aim of knowing genetic divergence analysis for quantitative traits among the rice genotypes for agronomical and yield traits. The experimental material consists of 36 rice genotypes sown in a Randomized Block Design with three replications and observations recorded on randomly selected five plants for 13 quantitative traits. The results indicated that the genotype Nagarjuna shows greater yield among the genotypes. The genetic parameters show high GCV and PCV in grain yield per plant, and according to D2 analysis, the 36 genotypes were grouped into 6 clusters based on Tocher's method of cluster formation. Cluster I is the largest cluster, consisting of 29 genotypes, while Cluster II has 3 genotypes. Cluster III, IV, V, and VI were the smallest, with only a single genotype. The maximum intra-cluster distance was found in cluster II (39.19), followed by cluster I (30.15), and the maximum inter-cluster distance was shown in between cluster VI and cluster II (178.97), followed by cluster VI and cluster V (151.75). Based on cluster means, Cluster III (39.67) shows greater among 6 clusters for grain yield per plant as contributing the highest among all the quantitative characters. Hence, these traits could be focused on for selection while improving seed yield and seed quality. On the basis of their greater inter-cluster distance, high value of cluster means, and performance of the individual germplasms for the character, the germplasm could be used in improving seed yield and seed quality programs for improvement of different plant characters of the rice.

CILP-2 expression in the intervertebral discs of patients with lumbar radiculopathy

BackgroundIntervertebral disc (IVD) degeneration (IVDD) is one of the main causes of low back pain. One of the most important features of IVDD is the loss of extracellular matrix (ECM) with its structural components. Cartilage intermediate layer proteins (CILPs), minor glycoproteins residing in ECM, have been found to be increased in IVD as degeneration and aging progresses. The aim of the present study was to evaluate the expression of CILP-2 in the IVD of patients with lumbar radiculopathy.MethodsThe IVD samples were collected from 25 patients during spinal surgery (interlaminectomy, herniated disc removal). The control IVD samples were obtained from nine patients who underwent lateral corpectomies in the thoracic region. CILP-2 expression was detected by immunohistochemistry. The patients were divided into two groups – aged under or over 50 years. A standardized clinical examination with assessment of radicular signs and deficits was performed. Subjective disability and pain were assessed using the visual analogue scale and Oswestry Disability Index (ODI). The pre-operative MRI was graded for the degree of IVD degeneration by Pfirrmann grading system. IVD samples obtained during operations were subjected to the standardized histopathological analysis applying modified Boos classification. The data were analysed by t-test, Mann-Whitney U-test, and Spearman correlation test.ResultsBoth histopathology scores and Pfirrmann grades did not differ between patients’ groups. Also, no correlations were found between histopathology and Pfirrmann grades, neither were any differences seen when correlating both grades to ODI, back pain or leg pain scores. CILP-2 staining was noted in all studied samples, notably strong staining was seen around large cell clusters. However, no differences in CILP-2 staining were seen between the age groups of patients. No correlations were found between CILP-2 staining and Pfirrmann grades. Grading of CILP-2 immunostaining in nine control patient samples resulted in significantly lower values. The difference is statistically significant (P = 0.002) compared to CILP-2 staining scores of all 25 patients’ samples.ConclusionIn this study, we detected increased CILP-2 expression in the human IVD as compared to the control group patients. CILP-2 can be a possible IVDD marker; however, as knowledge about the role of CILP-2 is limited, further studies are required.

High stability of charged particle clusters in protoplanetary disks

Context. The initial particle growth in protoplanetary disks is limited by a bouncing barrier at submillimeter wavelengths. Bouncing leads to tribocharging and the electrostatic attraction of tribocharged aggregates may eventually draw them into large clusters. A charge- mediated growth phase allows for the formation of larger entities, namely, clusters of aggregates that are more prone to further particle concentrations, such as the streaming instability. Aims. We aim to quantify the strength of the electrostatic forces. Methods. In laboratory experiments, we used an acoustic trap to levitate small aggregates of tribocharged submm grains. These aggregates spin up within the trap until they lose grains. Thus, we used the centrifugal force as a measure of the local force. Results. Grains are regularly bound strongly to their neighbors. In comparison, the force at ejection can be stronger than the attractive scattering forces of the trap and can therefore be several orders of magnitude larger than expected. We note that these forces are long- ranging, compared to van der Waals forces. Thus, charged aggregates are much more stable than uncharged ones. Conclusions. Particle aggregates in disks might grow to centimeter clusters or larger as tribocharging increases the effective binding forces. This allows for hydrodynamic concentration and planetesimal formation to eventually take place throughout a wide part of the disk.

A complex network analysis of groundwater wells in and around the Doñana Natural Space, Spain

This paper proposes the use of Complex Network Analysis tools to study the spatial distribution and temporal evolution of groundwater abstraction wells within a region of interest. To that end a weighted undirected network connecting wells within a certain distance was built. The edge weights take into account the distance between the wells as well as their corresponding abstraction volumes. In addition to the conventional complex network metrics, two specific abstraction-based centrality indexes are proposed, based on the total impact of a groundwater abstraction well on its surrounding wells and on the total impact of surrounding wells on a specific location. The proposed approach has been applied to the area of the Doñana Natural Space, one of the most important wetlands in Europe. The topology of the network reveals a large number of small, disconnected components and a few large components. This is reflected also in the degree distribution, which follows a Power Law distribution. The network has a large average clustering coefficient, a small average path length and a low level of centralisation. Global and average local network efficiency are also high. The network is assortative in terms of degree-degree and strength-strength correlations. Eigenvector centrality of the nodes reveals the location of influential wells.

Forecasting Constraints from Surface Brightness Fluctuations in Galaxy Clusters

Studies of surface brightness (SB) fluctuations in the intracluster medium present an indirect estimate of turbulent pressure support and associated Mach numbers. While high-resolution X-ray spectroscopy can directly constrain line-of-sight gas motions, including those due to turbulence, such observations are relatively expensive and will be limited to nearby, bright clusters. In this respect, SB fluctuations are the most economical means to constrain turbulent motions at large cluster radii across a range of redshifts and masses. To forecast what current and future X-ray and Sunyaev–Zel’dovich facilities may achieve in SB fluctuation studies, I review and synthesize matters of accuracy and precision with respect to calculating power spectra of SB fluctuations, from which turbulent properties are derived. Balancing concerns of power spectrum accuracy and precision across a range of spatial scales, I propose the use of three annuli with [0, 0.4]R 500, [0.4, 1]R 500, and [1, 1.5]R 500. Adopting these three regions, I calculate the uncertainty in the hydrostatic mass bias, σbM , that can be achieved for various instruments in several scenarios. I find that Lynx and AtLAST are competitive in their constraints at R 500, while AtLAST should perform better when constraining σbM at R 200.

Phosphorus removal and recovery from water and wastewater by the struvite crystallization

The precipitation of phosphorus naturally present in water, in the form of struvite, constitutes an interesting alternative for the phosphate water treatment. In this context, the main objective of the present study is to follow the crystallization of struvite, in a stirred tank, from real phosphated water (wastewater and natural water) at 25°C and at optimum pH 8.5 and to study the effect of environmental conditions on the crystallization stages (nucleation and crystal growth) and the morphology of struvite crystals.Various analytical methods (spectrophotometry, FTIR, SEM and XRD) were used to characterize the solid and liquid phases. In the light of the results obtained in this investigation, it appears that the precipitates formed in all the samples of treated waters were identified as ammonium magnesium phosphate (i.e. struvite). The precipitation of struvite in water allowed a significant elimination of phosphorus (up to 70%). On the other hand, the SEM analysis was able to highlight the presence of large clusters of large struvite crystals up to 146.8µm, as in the case of the precipitation of struvite with wastewater, where the conversion rate was the highest. The supersaturation ratio is the most important factor influencing the crystallization process.

Sequences of sickness absence, disability pension and unemployment four years before and five years after musculoskeletal diagnosis among Swedish twins.

To investigate sustainable working life via identification of time-related sequences of sickness absence (SA), disability pension (DP) and unemployment four years before and five years after the first musculoskeletal diagnosis in a Swedish twin cohort. Other aims were to account for familial confounding and to examine the associations between sequences and sociodemographic characteristics. Among 28,474 Swedish twins, the patterns of interruptions of working life four years before the first M00-M99 diagnosis (MSD) and five years after MSD diagnosis were investigated with a sequence analysis in a seven-element state space consisting of sustainable working life, unemployment >90 days, moderate SA/DP (30-179 days), almost full year of SA/DP (180-365 days), full year of SA/DP (⩾ 365 days), death, and old-age pension. The six-cluster solution had the best fit to the data. Five clusters had varying patterns of interruptions of sustainable working life (Clusters 2-6, n = 537-1949 with SA/DP, unemployment, but also accounting death and old-age pension) compared with the largest cluster with primarily sustainable working life (n = 23,316). Age, sex and familial factors affected the likelihood of belonging to the clusters with SA/DP. Most Swedish twins with or without MSD diagnosis have a sustainable working life, although MSD was both prevalent and a strong risk factor for belonging to the clusters with SA/DP. Thus, early prevention of MSD and prevention of recurrent or long sickness absences due to any cause would be merited while paying special attention to women also.

A multi-task spatio-temporal fusion network for offshore wind power ramp events forecasting

With the accelerated development of offshore wind farms, the impact of Wind Power Ramp Events (WPRE) on power systems has become more pronounced. Accurate prediction of WPRE is essential for mitigating their adverse effects on the grid. However, current studies on offshore WPRE are limited, especially regarding their spatio-temporal correlations and variability across large wind farm clusters. To address this, a novel forecasting approach using a multi-task spatio-temporal fusion network is presented. This method improves WPRE prediction by integrating spatial and temporal data and utilizing multitask learning to characterize ramp features. Firstly, an index system for WPRE characterization is developed, including metrics such as power change rate and duration. Based on this, an X-means classification method for WPRE is established. Secondly, a spatio-temporal encoder combining graph convolutional networks and temporal attention mechanisms has been proposed to model the spatiotemporal dependencies of meteorological changes in offshore wind farms. Finally, a multitask learning framework has been introduced to predict WPRE characteristic indices and occurrence probabilities. This approach enhances feature extraction efficiency through the joint feedback of multiple related tasks, thereby improving prediction accuracy. A case study using data from five offshore wind farms in Eastern China validates the efficacy of the proposed method.

Molecular Dynamic Simulation of Primary Damage with Electronic Stopping in Indium Phosphide.

Indium phosphide (InP) is an excellent material used in space electronic devices due to its direct band gap, high electron mobility, and high radiation resistance. Displacement damage in InP, such as vacancies, interstitials, and clusters, induced by cosmic particles can lead to the serious degradation of InP devices. In this work, the analytical bond order potential of InP is modified with the short-range repulsive potential, and the hybrid potential is verified for its reliability to simulate the atomic cascade collisions. By using molecular dynamics simulations with the modified potential, the primary damage defects evolution of InP caused by 1-10 keV primary knock-on atoms (PKAs) are studied. The effects of electronic energy loss are also considered in our research. The results show that the addition of electronic stopping loss reduces the number of point defects and weakens the damage regions. The reduction rates of point defects caused by electronic energy loss at the stable state are 32.2% and 27.4% for 10 keV In-PKA and P-PKA, respectively. In addition, the effects of electronic energy loss can lead to an extreme decline in the number of medium clusters, cause large clusters to vanish, and make the small clusters dominant damage products in InP. These findings are helpful to explain the radiation-induced damage mechanism of InP and expand the application of InP devices.

Clustering by detecting skeletal structure and identifying density fluctuation

Clustering is one of the most important techniques for unsupervised learning, it tries to divide points into different clusters without any priori knowledge of data. Therefore, several criterions for clustering algorithm are as follows: 1. Handling clusters with arbitrary shape and various density; 2. Finding cluster centers automatically; 3. Low parameter sensitivity and computational complexity. In this context, a novel algorithm namely clustering by detecting skeletal structure and identifying density fluctuation (CSSDF) was presented. In CSSDF, an efficient strategy based on density and local information of neighborhood is firstly proposed to detect the skeletal structure, which can collect the local information and identify the rough distribution of data. With the identified distribution information, a method takes expanded neighborhood and density fluctuation into consideration is proposed to further collect global information of data, which can assign all skeleton points and find cluster centers. To sum up, CSSDF can not only discover the underlying structure of data regardless of its’ distribution, but also ensure the correct assignment of all skeleton points and thus lead to a satisfying clustering performance. In addition, the computational complexity of the proposed approach is O(nlogn), which makes it possible to deal with some large clustering problem.

Plausible Photomolecular Effect and Microwave in Phase Transition of Water as a New Dawn for Renewable Energy and Ensemble Holistic Approach to Health Management

Interaction among light and water molecules have baffled scientists for many decades, and even centuries. In this regards, photons in the visible spectrum, where bulk water normally doesn't absorb light, can surprisingly cleave off large water clusters from the water-vapor interface, according to a recent study by Tu and Chen [2]. This discovery, termed the "photomolecular effect," opens exciting possibilities for not only revolutionizing renewable energy but also paving the way for a more integrated-ensemble approach to health management [1-3]. In a sense, other than with green or red LED, we can also introduce low-intensity laser to alter water molecule, as we discussed earlier in this journal [6, 7].

Non-genetic differences underlie variability in proliferation among esophageal epithelial clones.

Individual cells grown in culture exhibit remarkable differences in their growth, with some cells capable of forming large clusters, while others are limited or fail to grow at all. While these differences have been observed across cell lines and human samples, the growth dynamics and associated cell states remain poorly understood. In this study, we performed clonal tracing through imaging and cellular barcoding of an in vitro model of esophageal epithelial cells (EPC2-hTERT). We found that about 10% of clones grow exponentially, while the remaining have cells that become non-proliferative leading to a halt in the growth rate. Using mathematical models, we demonstrate two distinct growth behaviors: exponential and logistic. Further, we discovered that the propensity to grow exponentially is largely heritable through four doublings and that the less proliferative clones can become highly proliferative through increasing plating density. Combining barcoding with single-cell RNA-sequencing (scRNA-seq), we identified the cellular states associated with the highly proliferative clones, which include genes in the WNT and PI3K pathways. Finally, we identified an enrichment of cells resembling the highly proliferative cell state in the proliferating healthy human esophageal epithelium.

The self-organized structure of glioma oncostreams and the disruptive role of passive cells

Oncostreams are self-organized structures formed by spindle-like, elongated, self-propelled cells recently described in glioblastomas and especially in gliosarcomas. Cells within these structures either move as large clusters in one main direction, flocks, or as linear, intermingling collections of cells advancing in opposite directions, streams. Round, passive cells are also observed, either inside or segregated from the oncostreams. Here we generalize a recently formulated particle-field approach to investigate the genesis and evolution of these structures, first showing that, in systems consisting only of identical self-propelled cells, both flocks and streams emerge as self-organized dynamic configurations. Flocks are the more stable configurations, while streams are transient and usually originate in collisions between flocks. Stream degradation is easier at low self-propulsion speeds. In systems consisting of both motile and passive cells, the latter block stream formation and accelerate their degradation and flock stabilization. Since the flock appears to be the most effective invasive structure, we thus argue that a phenotype mixture (motile and passive cells) may favor glioblastoma invasion. hlBy relating cellular properties to the observed outcome, our model shows that oncostreams are self-organized structures that result from the interplay between speed, shape, and steric repulsion.

Pangenome graph analysis reveals extensive effector copy-number variation in spinach downy mildew.

Plant pathogens adapt at speeds that challenge contemporary disease management strategies like the deployment of disease resistance genes. The strong evolutionary pressure to adapt, shapes pathogens' genomes, and comparative genomics has been instrumental in characterizing this process. With the aim to capture genomic variation at high resolution and study the processes contributing to adaptation, we here leverage an innovative, multi-genome method to construct and annotate the first pangenome graph of an oomycete plant pathogen. We expand on this approach by analysing the graph and creating synteny based single-copy orthogroups for all genes. We generated telomere-to-telomere genome assemblies of six genetically diverse isolates of the oomycete pathogen Peronospora effusa, the economically most important disease in cultivated spinach worldwide. The pangenome graph demonstrates that P. effusa genomes are highly conserved, both in chromosomal structure and gene content, and revealed the continued activity of transposable elements which are directly responsible for 80% of the observed variation between the isolates. While most genes are generally conserved, virulence related genes are highly variable between the isolates. Most of the variation is found in large gene clusters resulting from extensive copy-number expansion. Pangenome graph-based discovery can thus be effectively used to capture genomic variation at exceptional resolution, thereby providing a framework to study the biology and evolution of plant pathogens.

Super-Enhancer-Driven IRF2BP2 is Activated by Master Transcription Factors and Sustains T-ALL Cell Growth and Survival.

Super enhancers (SEs) are large clusters of transcriptional enhancers driving the expression of genes crucial for defining cell identity. In cancer, tumor-specific SEs activate key oncogenes, leading to tumorigenesis. Identifying SE-driven oncogenes in tumors and understanding their functional mechanisms is of significant importance. In this study, a previously unreported SE region is identified in T-cell acute lymphoblastic leukemia (T-ALL) patient samples and cell lines. This SE activates the expression of interferon regulatory factor 2 binding protein 2 (IRF2BP2) and is regulated by T-ALL master transcription factors (TFs) such as ETS transcription factor ERG (ERG), E74 like ETS transcription factor 1 (ELF1), and ETS proto-oncogene 1, transcription factor (ETS1). Hematopoietic system-specific IRF2BP2 conditional knockout mice is generated and showed that IRF2BP2 has minimal impact on normal T cell development. However, in vitro and in vivo experiments demonstrated that IRF2BP2 is crucial for T-ALL cell growth and survival. Loss of IRF2BP2 affects the MYC and E2F pathways in T-ALL cells. Cleavage under targets and tagmentation (CUT&Tag) assays and immunoprecipitation revealed that IRF2BP2 cooperates with the master TFs of T-ALL cells, targeting the enhancer of the T-ALL susceptibility gene recombination activating 1 (RAG1) and modulating its expression. These findings provide new insights into the regulatory network within T-ALL cells, identifying potential new targets for therapeutic intervention.

Nanobody-Induced Aggregation of Gold Nanoparticles: A Mix-and-Read Strategy for the Rapid Detection of Cronobacter sakazakii.

Protein-nanoparticle interactions play a crucial role in both biomedical applications and the biosafety assessment of nanomaterials. Here, we found that nanobodies can induce citrate-capped gold nanoparticles (AuNPs) to aggregate into large clusters. Subsequently, we explored the mechanism behind this aggregation and proposed the "gold nucleation mechanism" to explain this phenomenon. Building on this observation, we developed a one-step label-free colorimetric method based on nanobody-induced AuNP aggregation. When nanobodies bind to target bacteria, spatial hindrance occurs, preventing further AuNPs aggregation. This alteration in surface plasmon resonance properties results in visible color changes. As an example, we present a simple and sensitive "mix-and-read" chromogenic immunosensor for Cronobacter sakazakii (C. sakazakii). The experiment can be completed within 20 min, with a visual detection limit of 103 CFU/mL and a quantitative detection limit of 136 CFU/mL. Importantly, our method exhibits no cross-reactivity with other bacterial species. This strategy harnesses the excellent properties of nanobodies and the optical characteristics of AuNPs for direct and rapid detection of foodborne pathogen.