Aggregation Kinetics Research Articles

Helium aggregation and surface morphology near grain boundaries in plasma-facing tungsten

We conduct molecular dynamics simulations of helium in tungsten to study the interaction of helium with grain boundaries. Model systems with grain boundary planes perpendicular to the surface and parallel to the surface are considered. The net attraction of mobile helium to the grain boundary results in a “depleted region” within approximately 3.5 nm of the grain boundary plane at low fluence, and once on the plane of the grain boundary, helium transport slows considerably. Helium retention is also strongly affected by the grain boundaries and their density: grain boundary planes approximately 6 nm beneath the plasma-facing surface and parallel to the surface tend to reduce the maximum bubble size due to the attraction of mobile clusters to the grain boundary plane, which lowers the concentration of helium near the surface (where it is being implanted); grain boundaries perpendicular to the surface tend to increase retention due to retention on the grain boundary plane. For grain boundaries parallel to the surface, the strong gettering effect of the grain boundaries on helium results in essentially no helium penetration through the grain boundary during the first 1.5 μs of plasma exposure at a flux of 1.6×1025 m−2s−1, corresponding to fluences on the order of 1020 m−2. Coarse-grained simulations capable of capturing the long-term dynamics of helium aggregation near grain boundaries would be required to determine whether these effects would have any measurable impact on phenomena, such as tungsten fuzz growth.

Exploring asphaltene aggregation: Model systems based on toluene-heptane mixtures

This work evaluates how chemical characteristics, such as polarity and aromaticity, can affect asphaltene aggregation. The asphaltene fraction was extracted from two different crude oils by precipitation in n-heptane, and these extracted asphaltenes were named A and B. Based on infrared spectroscopy (FTIR) and nuclear magnetic resonance (NMR) analyses, we found that asphaltenes B present greater aromaticity. According to X-ray photoelectron spectroscopy (XPS), asphaltene B showed higher heteroatom content. Model systems based on toluene/n-heptane/asphaltene (0.05 g/L) were prepared to evaluate the aggregation/precipitation of asphaltenes. Dynamic light scattering (DLS) analysis of aggregation kinetics revealed that aromatic asphaltenes with higher heteroatom content tend to form larger aggregates. Moreover, hydroxyl content exhibits a greater impact on aggregation compared to diffusivity. Furthermore, once the aggregates reach a critical size, the suspension stability is reduced, and the aggregates sediment. The atomic force microscopy (AFM) and DLS results revealed a wide range of particle size distribution. The larger clusters likely consisted of smaller aggregates that adhered together. Still, we highlight that the sizes of these aggregates determined by AFM are not directly comparable to the measurements obtained from DLS. The drying of the samples for the AFM measurements probably affects the asphaltene aggregation process. For this reason, the results obtained from the AFM and DLS techniques are not comparable.

The role of shear forces in primary and secondary nucleation of amyloid fibrils

Shear forces affect self-assembly processes ranging from crystallization to fiber formation. Here, the effect of mild agitation on amyloid fibril formation was explored for four peptides and investigated in detail for A[Formula: see text]42, which is associated with Alzheimer's disease. To gain mechanistic insights into the effect of mild agitation, nonseeded and seeded aggregation reactions were set up at various peptide concentrations with and without an inhibitor. First, an effect on fibril fragmentation was excluded by comparing the monomer-concentration dependence of aggregation kinetics under idle and agitated conditions. Second, using a secondary nucleation inhibitor, Brichos, the agitation effect on primary nucleation was decoupled from secondary nucleation. Third, an effect on secondary nucleation was established in the absence of inhibitor. Fourth, an effect on elongation was excluded by comparing the seeding potency of fibrils formed under idle or agitated conditions. We find that both primary and secondary nucleation steps are accelerated by gentle agitation. The increased shear forces facilitate both the detachment of newly formed aggregates from catalytic surfaces and the rate at which molecules are transported in the bulk solution to encounter nucleation sites on the fibril and other surfaces. Ultrastructural evidence obtained with cryogenic transmission electron microscopy and free-flow electrophoresis in microfluidics devices imply that agitation speeds up the detachment of nucleated species from the fibril surface. Our findings shed light on the aggregation mechanism and the role of detachment for efficient secondary nucleation. The results inform on how to modulate the relative importance of different microscopic steps in drug discovery and investigations.

Effects of Macromolecular Cosolutes on the Kinetics of Huntingtin Aggregation Monitored by NMR Spectroscopy.

The effects of two macromolecular cosolutes, specifically the polysaccharide dextran-20 and the protein lysozyme, on the aggregation kinetics of a pathogenic huntingtin exon-1 protein (hhtex1) with a 35 polyglutamine repeat, httex1Q35, are described. A unified kinetic model that establishes a direct connection between reversible tetramerization occurring on the microsecond time scale and irreversible fibril formation on a time scale of hours/days forms the basis for quantitative analysis of httex1Q35 aggregation, monitored by measuring cross-peak intensities in a series of 2D 1H-15N NMR correlation spectra acquired during the course of aggregation. The primary effects of the two cosolutes are associated with shifts in the prenucleation tetramerization equilibrium resulting in substantial changes in concentration of "preformed" httex1Q35 tetramers. Similar effects of the two cosolutes on the tetramerization equilibrium observed for a shorter, nonaggregating huntingtin variant with a 7-glutamine repeat, httex1Q7, lend confidence to the conclusions drawn from the fits to the httex1Q35 aggregation kinetics.

Spatial distribution of the range-expanding species Seriola fasciata (Bloch, 1793) in Mediterranean Sea: From past to future

The Mediterranean Sea is a highly susceptible area to climate change, that facilitates the introduction of warm-affinity exotic species, contributing to the expansion of their biogeographical range. One such thermophilic species is the Atlantic fish Seriola fasciata, which has colonised this area over the past three decades. The present study analyzed its spatial distribution in the Mediterranean Sea to identify aggregation areas and dynamics over time, and the environmental predictors influencing its presence.The utilized statistical tools and the Species Distribution Model proved effective in identifying specific spatial and temporal distribution patterns, as well as discerning some environmental variables influencing the species presence, with distinctions recorded between juveniles and adults.S. fasciata was observed to be established in the central Mediterranean, with Fishing Aggregating Devices potentially influencing its presence, particularly of juveniles. Sea floor temperature and habitats emerged as the primary factors driving species distribution. An aggregation area in the Levant Sea, conducive mainly for the adults, was identified and is expected to intensify over time.These findings contribute valuable insights into a relatively understudied species and its presence in the Mediterranean Sea, where climate change is affecting marine biodiversity.

Plumbagin accelerates serum albumin's amyloid aggregation kinetics and generates fibril polymorphism by inducing non-native β-sheet structures

The ligand-induced conformational switch of proteins has great significance in understanding the biophysics and biochemistry of their self-assembly. In this work, we have investigated the ability of plumbagin (PL), a hydroxynaphthoquinone compound found in the root of the medicinal plant Plumbago zeylanica, to modulate aggregation precursor state, aggregation kinetics and generate distinct fibril of human serum albumin (HSA). PL was found to moderately bind (binding constant Ka ∼ 10−4 M−1)) to domain-II of HSA in the stoichiometric ratio of 1:1. We found that PL-HSA complex aggregation was accelerated as compared to that of HSA aggregation and it may be through an independent pathway. We also detected that fibril produced in the presence of PL is wider in diameter, contains a higher amount of β-sheet (∼18%) and disordered (∼46%) structures, and is less stable. We concluded that the acceleration of aggregation reaction and generation of fibril polymorphism was mainly because of the higher extent of unfolding and high content of non-native β-sheet structure in the aggregation precursor state of PL-HSA complex. This study offers opportunities to explore the ability of ligand binding to modulate aggregation reactions and generate polymorphic protein fibrils.

Polydopamine Adhesion: Catechol, Amine, Dihydroxyindole, and Aggregation Dynamics.

While polydopamine (PDA) possesses the surface-independent adhesion property of mussel-binding proteins, significant differences exist between them. Particularly, PDA's short and rigid backbone differs from the long and flexible protein sequence of mussel-binding proteins. Given that adhesion relies on achieving a conformal contact with large surface coverage, PDA has drawbacks as an adhesive. In our study, we investigated the roles of each building block of PDA to build a better understanding of their binding mechanisms. Initially, we anticipated that catecholamine oligomers form specific binding with substrates. However, our study showed that the universal adhesion of PDA is initiated by the solubility limit of growing oligomers by forming agglomerates, complemented by multiple binding modes of catechol. Notably, in the absence of amines, poly(catechol) either remained in solution or formed minor suspensions without any surface coating, underscoring the essential role of amines in the adhesion process by facilitating insoluble aggregate formation. To substantiate our findings, we induced poly(catechol) aggregation using quaternized poly(4-vinylpyridine) (qPVP), leading to subsequent surface adhesion upon agglomerate formation.

Modulation of Lipid Dynamics in the β-Amyloid Aggregates Induced Membrane Fragmentation.

Nonspecific membrane disruption is considered a plausible mechanism for the cytotoxicity induced by β-amyloid (Aβ) aggregates. In scenarios of high local Aβ concentrations, a two-step membrane fragmentation model has been proposed. Initially, membrane-embedded Aβ oligomeric aggregates form, followed by membrane fragmentation. However, the key molecular-level interactions between Aβ oligomeric aggregates and lipids that drive the second-stage membrane fragmentation remain unclear. This study monitors the time-dependent changes in lipid dynamics and water accessibility of model liposomes during Aβ-induced membrane fragmentation. Our results indicate that lipid dynamics on the nanosecond to microsecond time scale undergo rapid acceleration upon initial incubation with membrane-incorporated Aβ oligomeric aggregates, followed by a slow deceleration process. Concurrently, lipid headgroups become less accessible to water. Both observations suggest a carpet-like mechanism of membrane disruption for the Aβ-induced membrane fragmentation process.

Platinum (II) Schiff Base Complexes and their Effects on the Inhibition of Amyloid β1–42 Aggregation

For synthesizing metal–organic molecules with pro‐drug properties to prevent the accumulation of amyloid beta (Aβ1–42), which is a feature of neurodegenerative Alzheimer's disease, two new Schiff bases with imine/amine donors 2‐([3,3‐diphenylalidene]amino)‐N,N‐dimethylethane‐1‐amine and N,N‐dimethyl‐2‐([quinolin‐4‐ylmethylene]amino)ethane‐1‐amine, as well as their novel Pt (II) complexes (I and II), were synthesized and characterized via Fourier transform infrared spectroscopy, 1H‐ and 13C‐nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and elemental analyses. The spectroscopic data has shown that the ligands are coordinated to the central atom in a chelating manner.Furthermore, the interaction between these complexes and Aβ1–42 was investigated using the electrochemical methods, square wave voltammetry and pencil graphite electrode, while monitoring the changes in the oxidation signal of the Try residue in Aβ1–42.The ability of the compounds to inhibit Aβ1–42 aggregation was investigated using the human neuroblastoma cell line (SH‐SY5Y). Complex II could actively inhibit the aggregation of Aβ1–42 at a molar ratio of 1.0/1.0, and its Aβ1–42 aggregation kinetics were fluorometrically determined using thioflavin T.These results were supported by scanning electron microscopy and transmission electron microscopy analyses. Moreover, the interaction of complex II with Aβ1–16 was investigated via 1H‐NMR spectroscopy.As a result, it was observed that complex II was effective in inhibiting the aggregation of Aβ1–42 at a molar ratio of 1.0/1.0. This result shows that studies can be conducted on the effects of Schiff base‐Pt complexes as potential pro‐drugs on Alzheimer's disease.

A Novel Collaborative SRU Network With Dynamic Behaviour Aggregation, Reduced Communication Overhead and Explainable Features.

Leakage and tampering problems in collection and transmission of biomedical data have attracted much attention as these concerns instigates negative impression regarding privacy, security, and reputation of medical networks. This article presents a novel security model that establishes a threat-vector database based on the dynamic behaviours of smart healthcare systems. Then, an improved and privacy-preserved SRU network is designed that aims to alleviate fading gradient issue and enhance the learning process by reducing computational cost. Then, an intelligent federated learning algorithm is deployed to enable multiple healthcare networks to form a collaborative security model in a personalized manner without the loss of privacy. The proposed security method is both parallelizable and computationally effective since the dynamic behaviour aggregation strategy empowers the model to work collaboratively and reduce communication overhead by dynamically adjusting the number of participating clients. Additionally, the visualization of the decision process based on the explainability of features enhances the understanding of security experts by enabling them to comprehend the underlying data evidence and causal reasoning. Compared to existing methods, the proposed security method is capable of thoroughly analyzing and detecting severe security threats with high accuracy, reduce overhead and lower computation cost along with enhanced privacy of biomedical data.

GTFN

With the development of smart education, gaining insights into students' understanding during the learning process is crucial in teaching. However, traditional knowledge tracking methods face challenges in capturing the intricate relationships between problems and knowledge points, as well as students' temporal learning changes. Therefore, we design a knowledge tracking model based on a graph temporal fusion network. Firstly, we construct the structure of the question and knowledge skill graph. Then, we design a knowledge graph encoder layer to capture the complex relationships between questions and knowledge skills. Next, we apply a sequential information extraction layer to dynamically model the outputs of each layer in the upper network over time, capturing students' knowledge changes at different time steps. Finally, we use a dynamic attention aggregation network to learn node information at different levels and time sequences. Experimental results on three datasets demonstrate the effectiveness of our method.

Electrostatics Choreographs the Aggregation Dynamics of Full-Length TDP-43 via a Monomeric Amyloid Precursor.

TDP-43 is a ubiquitously expressed, multidomain functional protein that is distinctively known to form aggregates in many fatal neurodegenerative disorders. However, the information for arresting TDP-43 aggregation is missing due to a lack of understanding of the molecular mechanism of the aggregation and structural properties of TDP-43. TDP-43 is inherently prone to aggregation and has minimal protein solubility. Multiple studies have been performed on the smaller parts of TDP-43 or the full-length protein attached to a large solubilization tag. However, the presence of co-solutes or solubilization tags is observed to interfere with the molecular properties and aggregation mechanism of full-length TDP-43. Notably, this study populated and characterized the native, dimeric state of TDP-43 without the interference of co-solutes or protein modifications. We observed that the electrostatics of the local environment is capable of the partial unfolding and monomerization of the native dimeric state of TDP-43 into an amyloidogenic molten globule. By employing the tools of thermodynamics and kinetics, we reveal the structural characteristics and temporal order of the early intermediates and transition states during the transition of the molten globule to β-rich, amyloid-like aggregates of TDP-43, which is governed by the electrostatics of the environment. The current advanced understanding of the nature of native and early aggregation-prone intermediates, early steps, and the influence of electrostatics in TDP-43 aggregation is essential for drug design.

A Lightweight and Dynamic Feature Aggregation Method for Cotton Field Weed Detection Based on Enhanced YOLOv8

Weed detection is closely related to agricultural production, but often faces the problems of leaf shading and limited computational resources. Therefore, this study proposes an improved weed detection algorithm based on YOLOv8. Firstly, the Dilated Feature Integration Block is designed to improve the feature extraction in the backbone network by introducing large kernel convolution and multi-scale dilation convolution, which utilizes information from different scales and levels. Secondly, to solve the problem of a large number of parameters in the feature fusion process of the Path Aggregation Feature Pyramid Network, a new feature fusion architecture multi-scale feature interaction network is designed, which achieves the high-level semantic information to guide the low-level semantic information through the attention mechanism. Finally, we propose a Dynamic Feature Aggregation Head to solve the problem that the YOLOv8 detection head cannot dynamically focus on important features. Comprehensive experiments on two publicly accessible datasets show that the proposed model outperforms the benchmark model, with mAP50 and mAP75 improving by 4.7% and 5.0%, and 5.3% and 3.3%, respectively, whereas the number of model parameters is only 6.62 M. This study illustrates the utility potential of the algorithm for weed detection in cotton fields, marking a significant advancement of artificial intelligence in agriculture.

Phosphorus desorption regulates phosphorus fraction dynamics in soil aggregates of revegetated ecosystems

To elucidate the mechanisms and effects of phosphorus (P) desorption on P fractions in soil aggregates of revegetated ecosystems is fundamental for regulating the P supply and biogeochemical cycle. We selected four aggregate sizes (1–5, 0.5–1, 0.25–0.5, and <0.25 mm) from a desert revegetation chronosequence (11, 31, 40, 57, and 65 years) as our study targets and used the Freundlich model to reveal the dynamics of P desorption and changes in P fractions. The results showed that the calibrated model Q=A−KFdtnd for different size aggregates in seven deserts (two natural and five revegetated) described the P desorption characteristics well. In soil aggregates of revegetated deserts, smaller aggregates with higher specific surface area did not desorb more P, nor did older aggregates after revegetation. The natural P desorption process in aggregates resulted in significant changes in Ca2–P, Ca8–P, Al–P and Fe–P fractions (p < 0.05), and revegetation years also affected P fraction dynamics significantly (p < 0.05). This study highlights that the calibrated kinetic model in the revegetated soil aggregates elucidated the P desorption characteristics, and that the P desorption process drove P fraction changes.

Aggregate stability and carbon and N dymamics in macroaggregate size fractions with different soil texture

Soil nutrient cycling, the distribution of soil aggregates, and their stability are directly influenced by soil texture. Different sizes of soil aggregates provide microhabitats for microorganisms and therefore influence soil carbon (C) and nitrogen (N) mineralization. The purpose of the present study was to assess the aggregate stability and dynamics of carbon and nitrogen in macroaggregate size fractions (1-8 mm) with different clay content from meadow soils. Surface soil samples (0-15 cm) were collected from 4- to 5-year-old forage crops. Four macroaggregate size classes were isolated by dry sieving and analyzed for their mass proportions: fine macroaggregates (FM) (less than 1 mm), medium-fine macroaggregates (MFM) (1-2 mm), medium-coarse macroaggregates (MCM) (2-4 mm), and large-coarse macroaggregates (LCM) (4-8 mm). The dry mean weight diameter (MWD), organic carbon (OC), total nitrogen (TN), carbon and nitrogen of microbial biomass (C-MB, N-MB) were determined. CO2 emission and net nitrogen mineralized (NM) were measured after 14 weeks of incubation. The amounts of FM were significantly lower than those of intermediate macroaggregates (MCM and MFM) and decreased markedly with increasing clay content within soil macroaggregates. In general, the amounts of macroaggregate size fractions were lowest in soils with high clay content. MWD exhibited a significant correlation with particle size distribution, OC, and MB-C. OC, TN, MB-C, and MB-N contents within macroaggregates increased with decreasing macroaggregate size and increasing clay content of macroaggregate fractions. The CO2 emission and NM content increased with increasing macroaggregate size, indicating higher organic C and N mineralization activity in larger macroaggregates. Mineralization of OC was lowest in macroaggregate fractions with the highest clay content. We conclude that clay content can increase the protection of microbial biomass in meadow soils. Small macroaggregates tend to contain more recalcitrant organic matter compared to larger macroaggregates.

Ejection and dynamics of aggregates in the coma of comet 67P/Churyumov-Gerasimenko

The process of gas-driven ejection of refractory materials from cometary surfaces continues to pose a challenging question in cometary science. The activity modeling of comet 67P/Churyumov-Gerasimenko, based on data from the Rosetta mission, has significantly enhanced our comprehension of cometary activity. But thermophysical models have difficulties in simultaneously explaining the production rates of various gas species and dust. It has been suggested that different gas species might be responsible for the ejection of refractory material in distinct size ranges. This work focuses on investigating the abundance and the ejection mechanisms of large aggregates (gtrsim 1 cm) from the comet nucleus. We aim to determine their properties and map the distribution of their source regions across the comet surface. This can place constraints on activity models for comets. We examined 189 images acquired at five epochs by the OSIRIS/NAC instrument on board the Rosetta spacecraft. Our goal was to identify bright tracks produced by individual aggregates as they traversed the camera field of view. In parallel, we generated synthetic images based on the output of dynamical simulations involving various types of aggregates. By comparing these synthetic images with the observations, we determined the characteristics of the simulated aggregates that most closely resemble the observations. We have identified over 30000 tracks present in the OSIRIS images, derived constraints on the characteristics of the aggregates, and mapped their origins on the nucleus surface. The aggregates have an average radius of $ cm and a bulk density consistent with that of the comet's nucleus. Due to their size, gas drag exerts only a minor influence on their dynamical behavior, so an initial velocity is needed to bring them into the camera field of view. The source regions of these aggregates are predominantly located near the boundaries of distinct terrains on the surface.

Investigation on Fluorescence Origin and Spectral Heterogeneity in Carbon Dots: A Dynamic Perspective

AbstractHeterogeneity in the fluorescence of carbon dots (CDs) has been hard to figure out so far. This could potentially be related to structural factors, size or intermediate fluorophores, especially when employing the bottom‐up synthesis. Herein, we unveil the origin of fluorescence and spectral heterogeneity of CDs using a simple dynamic method. This work reports the room light‐excited green fluorescence and dual‐emissive N‐doped CDs synthesized using a hydrothermal method. Studies were carried out considering the factors of fluorescence phenomena, such as excitation‐independent emission, fluorescent impurities, aggregation and solvation dynamics. The new steady‐state, Excitation‐resolved area‐normalized emission spectroscopy (ERANES) and ensemble measurements, including time‐resolved studies reveal that a heterogeneous environment exists in the ground state. Eventually, the results show the existence of core, edge and surface states in the CDs. Additionally, the fluorescence characteristics depend on the structural functionalization that occurs in both the intrinsic and extrinsic states of the CDs and it is proven that this does not violate the Kasha‐Vavilov rule. Although a highly purified material could still exhibit heterogeneity due to the ensemble emissive states and structural variations. Our results provide insights into the enduring debates about fluorescence and a deeper understanding of the structure‐ property relationship of CDs.

Cu(II) binding to the λ6aJL2-R24G antibody light chain protein associated with light chain amyloidosis disease: The role of histidines

Light chain amyloidosis is a conformational disease caused by the abnormal proliferation and deposition of antibody light chains as amyloid fibers in organs and tissues. The effect of Cu(II) binding to the model recombinant protein 6aJL2-R24G was previously characterized in our group, and we found an acceleration of the aggregation kinetics of the protein. In this study, in order to confirm the Cu(II) binding sites, histidine variants of 6aJL2-R24G were prepared and the effects of their interaction with Cu(II) were analyzed by circular dichroism, fluorescence spectroscopy, isothermal calorimetry titrations, and molecular dynamics simulations. Confirming our earlier work, we found that His8 and His99 are the highest affinity Cu(II) binding sites, and that Cu(II) binding to both sites is a cooperative event.

Knowledge Graph Reasoning via Dynamic Subgraph Attention with Low Resource Computation

Knowledge graphs (KGs) suffer from inherent incompleteness, which has spurred research into knowledge graph reasoning (KGR), i.e., ways to infer missing facts based on existing triples. The most prevalent approaches employ a static mechanism for entity representation across the entire graph, sharing entity embeddings for different query relations. Nevertheless, these static entity embeddings fail to capture specific semantics for various query scenarios, resulting in inaccurate entity representations and susceptibility to reasoning errors. Furthermore, the whole graph learning style requires substantial computational resources, especially since KGs are often of large-scale. Consequently, these methods are impractical in low-resource environments. To address these issues, we devise a framework called dynamic subgraph attention (DSA), which learns dynamic entity embeddings for different query relations across subgraphs. In our approach, by utilizing multi-hop path history information obtained through path-based learning, we guide a dynamic attention mechanism to generate dynamic entity embeddings for different query relations. To ensure the semantic information of entities, the embedding-based and path-based learning are jointly trained for KGR. Additionally, the proposed dynamic aggregation mechanism operates on subgraphs, resulting in a remarkable 6–7 times resource conservation compared to GPU computations. Empirical experiments further demonstrate that DSA outperforms the current methods significantly on three benchmark datasets.

Molecular Insights into the Effects of F16L and F19L Substitutions on the Conformation and Aggregation Dynamics of Human Calcitonin.

Human calcitonin (hCT) regulates calcium-phosphorus metabolism, but its amyloid aggregation disrupts physiological activity, increases thyroid carcinoma risk, and hampers its clinical use for bone-related diseases like osteoporosis and Paget's disease. Improving hCT with targeted modifications to mitigate amyloid formation while maintaining its function holds promise as a strategy. Understanding how each residue in hCT's amyloidogenic core affects its structure and aggregation dynamics is crucial for designing effective analogues. Mutants F16L-hCT and F19L-hCT, where Phe residues in the core are replaced with Leu as in nonamyloidogenic salmon calcitonin, showed different aggregation kinetics. However, the molecular effects of these substitutions in hCT are still unclear. Here, we systematically investigated the folding and self-assembly conformational dynamics of hCT, F16L-hCT, and F19L-hCT through multiple long-time scale independent atomistic discrete molecular dynamics (DMD) simulations. Our results indicated that the hCT monomer primarily assumed unstructured conformations with dynamic helices around residues 4-12 and 14-21. During self-assembly, the amyloidogenic core of hCT14-21 converted from dynamic helices to β-sheets. However, substituting F16L did not induce significant conformational changes, as F16L-hCT exhibited characteristics similar to those of wild-type hCT in both monomeric and oligomeric states. In contrast, F19L-hCT exhibited substantially more helices and fewer β-sheets than did hCT, irrespective of their monomers or oligomers. The substitution of F19L significantly enhanced the stability of the helical conformation for hCT14-21, thereby suppressing the helix-to-β-sheet conformational conversion. Overall, our findings elucidate the molecular mechanisms underlying hCT aggregation and the effects of F16L and F19L substitutions on the conformational dynamics of hCT, highlighting the critical role of F19 as an important target in the design of amyloid-resistant hCT analogs for future clinical applications.