Experimental Confirmation Research Articles

Computational staining of CD3/CD20 positive lymphocytes in human tissues with experimental confirmation in a genetically engineered mouse model

IntroductionImmune dysregulation plays a major role in cancer progression. The quantification of lymphocytic spatial inflammation may enable spatial system biology, improve understanding of therapeutic resistance, and contribute to prognostic imaging biomarkers.MethodsIn this paper, we propose a knowledge-guided deep learning framework to measure the lymphocytic spatial architecture on human H&E tissue, where the fidelity of training labels is maximized through single-cell resolution image registration of H&E to IHC. We demonstrate that such an approach enables pixel-perfect ground-truth labeling of lymphocytes on H&E as measured by IHC. We then experimentally validate our technique in a genetically engineered, immune-compromised Rag2 mouse model, where Rag2 knockout mice lacking mature lymphocytes are used as a negative experimental control. Such experimental validation moves beyond the classical statistical testing of deep learning models and demonstrates feasibility of more rigorous validation strategies that integrate computational science and basic science.ResultsUsing our developed approach, we automatically annotated more than 111,000 human nuclei (45,611 CD3/CD20 positive lymphocytes) on H&E images to develop our model, which achieved an AUC of 0.78 and 0.71 on internal hold-out testing data and external testing on an independent dataset, respectively. As a measure of the global spatial architecture of the lymphocytic microenvironment, the average structural similarity between predicted lymphocytic density maps and ground truth lymphocytic density maps was 0.86 ± 0.06 on testing data. On experimental mouse model validation, we measured a lymphocytic density of 96.5 ± %1% in a Rag2+/- control mouse, compared to an average of 16.2 ± %5% in Rag2-/- immune knockout mice (p<0.0001, ANOVA-test).DiscussionThese results demonstrate that CD3/CD20 positive lymphocytes can be accurately detected and characterized on H&E by deep learning and generalized across species. Collectively, these data suggest that our understanding of complex biological systems may benefit from computationally-derived spatial analysis, as well as integration of computational science and basic science.

Investigation of the influence of initial residual stress and toolpaths on milling deformation of titanium alloy

Titanium alloy structural components are widely used in the aerospace industry due to their excellent physical properties. However, their susceptibility to machining deformation during milling, attributed to the presence of initial residual stress, poses a significant challenge. Therefore, this paper proposes a finite element model for predicting milling deformation in Ti6Al4V titanium alloy structural parts, considering initial residual stress. The methodology involves establishing the initial residual stress field of titanium alloy components based on a mathematical model of annealing heat transfer and a theoretical study of thermal elasto-plastic constitutive relation, with experimental confirmation of model accuracy. Based on the initial residual stress, a finite element model was developed to predict the maximum deformation under different toolpaths. Finally, a comparative analysis with milling experiments validated the proposed models. The experimental results demonstrated a remarkable alignment with the finite element model, showcasing the correctness of the developed models. The maximum deviation in deformation observed was within the range of 0.003 mm–0.011 mm. This study is the first to comprehensively consider the effects of initial residual stress and toolpaths on titanium alloy milling deformation, and to experimentally verify the proposed model’s accuracy and practicality. It provides a new theoretical basis and technical guidelines for titanium alloy milling deformation.

Investigating the influence of the SIRT6 gene and alternative splicing on canine longevity: an in-depth bioinformatics analysis and experimental confirmation via NGS-based targeted sequencing.

Sirtuin 6 (SIRT6) has many functions, but its most notable contribution lies in the intricate regulation of cell senescence and lifespan. The effect of the SIRT6 gene on body size and longevity in dogs has not been extensively studied, particularly with regard to alternative splicing mechanisms. To address this gap, the present study used a comprehensive approach that integrated bioinformatics analysis, DNA sequence analysis, and next-generation sequencing-based targeted sequencing analyses. Our results show that, according to the reference genomes of different dog breeds, the canine SIRT6 gene exhibits different variants according to the dog breed. Except for the exonic variant g.55,146,051C > T (rs851065050) detected in the Boxer breed, all variants obtained from other genomes were determined to be intronic variants. The g.56,075,604 G > T (rs3343377774) intronic variant previously detected in the Labrador Retriever breed was only detected in the small breed group in our study. As a result of in silico analysis, the g.56,075,604 G > T variant has an exonic splicing enhancer (ESE) site; this variant has created the motif of the binding site for the splicing factor ESE_SRp55. The g.55.146,051C > T variant was associated with a change in the ratio of exonic splicing silencer/ESE binding motifs. This change indicates an increased probability of exon skipping for the mutant allele. Thus, as with the intronic variant g.56,075,604 G > T, the mis-splicing induced by the exonic variant g.55,146,051C > T could potentially be associated with an altered distribution of regulatory splicing factors of the canine SIRT6 gene.

Underdetermination in classic and modern tests of general relativity

Canonically, ‘classic’ tests of general relativity (GR) include perihelion precession, the bending of light around stars, and gravitational redshift; ‘modern’ tests have to do with, inter alia, relativistic time delay, equivalence principle tests, gravitational lensing, strong field gravity, and gravitational waves. The orthodoxy is that both classic and modern tests of GR afford experimental confirmation of that theory in particular. In this article, we question this orthodoxy, by showing there are classes of both relativistic theories (with spatiotemporal geometrical properties different from those of GR) and non-relativistic theories (in which the lightcones of a relativistic spacetime are ‘widened’) which would also pass such tests. Thus, (a) issues of underdetermination in the context of GR loom much larger than one might have thought, and (b) given this, one has to think more carefully about what exactly such tests in fact are testing.

First experimental confirmation of island SOL geometry effects in a high radiation regime on W7-X

Abstract This work characterizes the detachment behavior and radiation characteristics of the low
iota configuration in the Wendelstein 7-X (W7-X) stellarator. The island scrape-off layer (SOL) of the
low iota has a poloidal mode number of 6 islands surrounding the last closed flux surface (LCFS).
The island geometry of the low iota configuration is significantly different to that of the standard
magnetic field configuration, whose detachment characteristics have already been described in previous
work[2, 3, 4]. Experimental results show that the radiation pattern in the low iota configuration
is starkly different to that of the standard magnetic field configuration, with radiation concentrated
at the island SOL O-points, rather than the X-points. Additionally, this O-point localized radiation
pattern is associated with unstable detachment, with both radiation oscillations in experiments and the
lack of a self-consistent plasma solution at high radiated power fraction in EMC3-Eirene simulations.
EMC3-Eirene simulations are used to understand the radiation distribution. It was found that the O-
point localized radiation arises first from local impurity accumulation near the parallel flow stagnation,
which is located close to the geometrical center of the island (”O-point”). The local cooling in this
region leads to plasma condensation in the islands in closest magnetic connection to the divertor target
plates. The heat source to this region of the island, which is thermally isolated from the upstream heat
source in terms of parallel transport, must arise via perpendicular heat transport. This heat source is
expected to be large for the low iota configuration due to its very small internal island field line pitch.
This work highlights the importance (complementary to previous work, e. g. [5, 6]) of the internal
island field line pitch not only on the radiation pattern, but also the detachment performance of the
island divertor.

Ultrasound Imaging of Nonlinear Media Response Using a Pressure-Dependent Nonlinearity Index

It has been shown that within the range of acoustic pressures used in ultrasound imaging, waveforms are distorted during propagation in tissue due to the physically nonlinear behavior of the tissue. This distortion leads to changes in the spectrum of the received ultrasound echoes, causing the transfer of signal energy from the fundamental frequency to higher harmonics. Interestingly, adipose tissue exhibits up to 50 % stronger nonlinear behavior compared to other soft tissues. The tissue nonlinearity parameter B/A is typically measured ex vivo using an ultrasound method in transmission mode, which requires extensive receiving systems. Currently, there is no improved ultrasound method for measuring the B/A nonlinearity parameter in vivo, which could be used in assessing the degree of fatty liver disease. We propose a new, simple approach to estimating nonlinear tissue properties. The proposed method involves transmitting ultrasound waves at significantly different acoustic pressures, recording echoes only in the fundamental frequency band at various depths, and introducing a nonlinearity index (NLI) based on specific echo amplitude ratios. The NLI at a given depth is calculated using the ratio of two dimensionless parameters. The first parameter is a predetermined constant obtained by dividing the total echo values from transmitting a signal at higher sound pressure by those from a signal at lower sound pressure, summed over a small tissue sample volume located near the transducer. The second parameter is calculated at a fixed distance from the transducer, determined by dividing the total echo values from transmitting a signal at higher sound pressure by those from a signal at lower pressure, summed over a small tissue volume of the tissue at that distance from the transducer. The reliability of the proposed measurements for assessing tissue nonlinearity has been substantiated through experimental confirmation of the existing correlations between the values of NLI and B/A in water, sunflower oil, and animal liver tissue samples with oil-enriched regions. The NLI was more than 15 % higher in sunflower oil than in water. The NLI in bovine liver sample below the area with injected oil (mimicking “steatosis”) was more than 35 % higher than in regions without oil. This method represents a promising modality for the nonlinear characterization of tissue regions in vivo, particularly for diagnosing fatty liver disease.

Planar Tetracoordinate Silicon in Si3Cu3- Cluster.

Photoelectron spectroscopy and theoretical calculations have identified the global minimum structure of the 16-valence electron Si3Cu3- cluster, which features a planar tetracoordinate silicon (ptSi) in a rhombic arrangement. The Si3 and Cu3 triangles are interconnected by an Si2/Cu2 edge, forming an ordered chain-like structure. Besides the conventional 2c-2e σ-bond connecting Si3 and Cu3, the stability of this cluster is reinforced by a delocalized 3c-2e σ-bond in Cu3 and a π-bond in Si3. Our study provides rare experimental confirmation of a planar hypercoordinate heavier Group 14 element, opening possibilities for exploring similar structures in two-dimensional materials.

The divisive normalization model of visual number sense: model predictions and experimental confirmation.

Our intuitive sense of number allows rapid estimation for the number of objects (numerosity) in a scene. How does the continuous nature of neural information processing create a discrete representation of number? A neurocomputational model with divisive normalization explains this process and existing data; however, a successful model should not only explain existing data but also generate novel predictions. Here, we experimentally test novel predictions of this model to evaluate its merit for explaining mechanisms of numerosity perception. We did so by consideration of the coherence illusion: the underestimation of number for arrays containing heterogeneous compared to homogeneous items. First, we established the existence of the coherence illusion for homogeneity manipulations of both area and orientation of items in an array. Second, despite the behavioral similarity, the divisive normalization model predicted that these two illusions should reflect activity in different stages of visual processing. Finally, visual evoked potentials from an electroencephalography experiment confirmed these predictions, showing that area and orientation coherence modulate brain responses at distinct latencies and topographies. These results demonstrate the utility of the divisive normalization model for explaining numerosity perception, according to which numerosity perception is a byproduct of canonical neurocomputations that exist throughout the visual pathway.

Systems biology approach for enhancing limonene yield by re-engineering Escherichia coli

Engineered microorganisms have emerged as viable alternatives for limonene production. However, issues such as low enzyme abundance or activities, and regulatory feedback/forward inhibition may reduce yields. To understand the underlying metabolism, we adopted a systems biology approach for an engineered limonene-producing Escherichia coli strain K-12 MG1655. Firstly, we generated time-series metabolomics data and, secondly, developed a dynamic model based on enzyme dynamics to track the native metabolic networks and the engineered mevalonate pathway. After several iterations of model fitting with experimental profiles, which also included 13C-tracer studies, we performed in silico knockouts (KOs) of all enzymes to identify bottleneck(s) for optimal limonene yields. The simulations indicated that ALDH/ADH (aldehyde dehydrogenase/alcohol dehydrogenase) and LDH (lactate dehydrogenase) suppression, and HK (hexokinase) enhancement would increase limonene yields. Experimental confirmation was achieved, where ALDH-ADH and LDH KOs, and HK overexpression improved limonene yield by 8- to 11-fold. Our systems biology approach can guide microbial strain re-engineering for optimal target production.

Genome-wide comparative analysis of CC1 Staphylococcus aureus between colonization and infection

BackgroundStaphylococcus aureus is one of the most important bacteria in human colonization and infection. Clonal complex1 (CC1) is one of the largest and most important S. aureus CCs, and it is a predominant clone in S. aureus colonization and can cause a series of S. aureus infections including bloodstream infections. No studies on the relationship of CC1 S. aureus between colonization and infection have been published.MethodsTo figure out if there are some significant factors in CC1 S. aureus help its colonization or infection, 15 CC1 S. aureus isolates including ten from colonization and five from bloodstream infections were enrolled in this study. Whole-genome sequencing and bioinformatics analysis were performed.ResultsVirulence factor regulators XdrA, YSIRK signal peptide, CPBP family and OmpR family specifically found in infection isolates can promote virulence factors and enhance the pathogenicity of S. aureus. In addition, some significant differences in metabolism and human diseases were discovered between colonization and infection. Fst family of type I toxin–antitoxin system that mainly maintains stable inheritance was specifically found in CC1 S. aureus colonization isolates and might help S. aureus survive for colonization. No significant differences in genomic evolutionary relationship were found among CC1 S. aureus isolates between colonization and infection.ConclusionsVirulence factor regulators and metabolic state can promote CC1 S. aureus pathogenic process compared with colonization, and it seems that the strains of colonization origin cannot have pathogenic potential. Experimental confirmation and a bigger number of CC1 S. aureus strains are necessary for further study about the details and mechanism between colonization and infection.

Integrating network pharmacology, molecular docking and experimental verification to explore the therapeutic effect and potential mechanism of nomilin against triple-negative breast cancer

BackgroundNomilin is a limonoid compound known for its multiple biological activities, but its role in triple negative breast cancer (TNBC) remains unclear. This study aims to uncover the potential therapeutic effect of nomilin on TNBC and elucidate the specific mechanism of its action.MethodsWe employed weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the GeneCards database to identify potential targets for TNBC. Simultaneously, we utilized the Swiss Target Prediction, ChEMBL, and STITCH databases to identify potential targets of nomilin. The core targets and mechanisms of nomilin against TNBC were predicted through protein-protein interaction (PPI) network analysis, molecular docking, and enrichment analysis. The results of the network pharmacology were corroborated by conducting experiments.ResultsA total of 17,204 TNBC targets were screened, and 301 potential targets of nomilin were identified. Through the PPI network, eight core targets of nomilin against TNBC were pinpointed, namely BCL2, Caspase3, CyclinD1, EGFR, HSP90AA1, KRAS, PARP1, and TNF. Molecular docking, molecular dynamics simulation and proteome microarray revealed that nomilin exhibits strong binding activity to these core proteins. Enrichment analysis results indicated that the anti-TNBC effect of nomilin is associated with PI3K/Akt pathway. In vitro and in vivo experiments have demonstrated that nomilin inhibits TNBC cell proliferation and migration while promoting cell apoptosis through the PI3K/Akt pathway.ConclusionFor the first time, the research effectively discovered the objectives and mechanisms of nomilin in combating TNBC using network pharmacology, molecular docking, molecular dynamics simulation, proteome microarray and experimental confirmation, presenting a hopeful approach for treating TNBC.Graphical

Molecular profiling of a rat model of vascular dementia: Evidences from proteomics, metabolomics and experimental validations

Decrease of cerebral blood flow is the primary cause of vascular dementia (VD), but its pathophysiological mechanisms are still not known. This study aims to profile the molecular changes of a rat model of VD induced by bilateral common carotid artery ligation. The Morris water maze and new object recognition tasks were used to test the cognitive function of rats. Hematoxylin and Eosin (HE) staining was used to detect pathological changes in the hippocampus. After confirming the model, proteomics was used to detect differentially expressed proteins in the hippocampus, and metabolomics was used to detect differential metabolites in rat serum. Thereafter, bioinformatics were used to integrate and analyze the potential molecular profile. The results showed that compared with the sham control group, the spatial and recognition memory of the rats were significantly reduced, and pathological changes were observed in the hippocampal CA1 region of the model group. Proteomic analysis suggested 206 differentially expressed proteins in the hippocampus of VD rats, with 117 proteins upregulated and 89 downregulated. Protein-protein interaction network analysis suggested that those differentially expressed proteins might play crucial roles in lipid metabolism, cell adhesion, intracellular transport, and signal transduction. Metabolomics analysis identified 103 differential metabolites, and comparison with the human metabolome database revealed 22 common metabolites, which predicted 265 potential targets. Afterwards, by intersecting the predicted results from metabolomics with the differentially expressed proteins from proteomics, we identified five potential targets, namely ACE, GABBR1, Rock1, Abcc1 and Mapk10. Furthermore, western blotting confirmed that compared with control group, hippocampal GABBR1 and Rock1 were enhanced in the model group. Together, this study showed the molecular profile of VD rats through a combination of proteomics, metabolomics, and experimental confirmation methods, offering crucial molecular targets for the diagnosis and treatment of VD.

Maximization of entropy production during vibration in a suspension based on graphite and silicone oil.

The electrical conductivity of a suspension of graphite and silicone oil in the presence of a small electric potential difference and vibration (40÷50Hz) is considered. The concentration of the suspension was selected near the percolation threshold. It has been found that such a nonequilibrium system evolves to increase its dissipation power, and low-energy vibrations accelerate, and high-energy ones hinder this process. Since the dissipation power of the considered system is proportional to entropy production, the results obtained are consistent with the so-called maximum entropy production principle (MEPP). This is the first experimental confirmation of MEPP in the case of a nonequilibrium process with continuous transformations under conditions for the emergence of alternative variants for the development. The possibility of choice among alternatives in a complex system is a fundamental point in the experimental discussion of MEPP, and it was previously underestimated.

Physiology, Pathophysiology and Clinical Relevance of D-Amino Acids Dynamics: From Neurochemistry to Pharmacotherapy.

Over three decades ago, two independent groups of investigators identified free D-aspartic and later D-serine in specific brain nuclei and endocrine glands. This finding revealed a novel, non-proteinogenic role of these molecules. Moreover, the finding that aged proteins from the human eye crystallin, teeth, bone, blood vessels or the brain incorporate D-aspartic acids to specific primary protein sequences fostered the hypothesis that aging might be related to D-amino acid isomerization of body proteins. The experimental confirmation that schizophrenia and neurodegenerative diseases modify plasma free D-amino acids or tissue levelsnurtured the opportunity of using D-amino acids as therapeutic agents for several disease treatments, a strategy that prompted the successful current application of D-amino acids to human medicine.

Novel Insights into Enzymatic Thermostability: The “Short Board” Theory and Zero‐Shot Hamiltonian Model

AbstractUnderstanding the mechanism underlying thermostabilization in naturally stable enzymes and enhancing the thermostability of unstable enzymes are crucial aspects in enzyme engineering. Despite the development of various engineering methods, there remains substantial scope for improvement. In this study, a novel concept termed as the “short board” theory is proposed, which conceptualizes proteins as barrels with each component representing a jagged board. Notably, optimizing modifications to the shortest board yields optimal enhancements in terms of thermostability performance. To validate this theory, α‐amylase, an industrial bulk enzyme with multiple domains, is employed as a model enzyme. The existence of “short boards” and their impact on thermostability modification are demonstrated at the domain, residue, and atomic levels through experimental confirmation using domain substitution. Furthermore, a novel thermostable design and prediction model called Zero‐Shot Hamiltonian (ZSH) is established and evaluated on α‐amylase. This coevolutionary approach based on thermostability and deep learning exhibits remarkable success exclusively when applied to enzymes with fixed short boards. The integration of the “short board” theory with the ZSH model presents an innovative tool for enhancing enzymatic thermostability.

Kinematic analysis and advanced control of a vectored thruster based on 3RRUR parallel manipulator for micro-size AUVs

Abstract Autonomous underwater vehicles (AUVs) have played a pivotal role in advancing ocean exploration and exploitation. However, traditional AUVs face limitations when executing missions at minimal or near-zero forward velocities due to the ineffectiveness of their control surfaces, considerably constraining their potential applications. To address this challenge, this paper introduces an innovative vectored thruster system based on a 3RRUR parallel manipulator tailored for micro-sized AUVs. The incorporation of a vectored thruster enhances the performance of micro-sized AUVs when operating at minimal and low forward speeds. A comprehensive exploration of the kinematics of the thrust-vectoring mechanism has been undertaken through theoretical analysis and experimental validation. The findings from theoretical analysis and experimental confirmation unequivocally affirm the feasibility of the devised thrust-vectoring mechanism. The precise control of the vector device is studied using Physics-informed Neural Network and Model Predictive Control (PINN-MPC). Through the adoption of this pioneering thrust-vectoring mechanism rooted in the 3RRUR parallel manipulator, AUVs can efficiently and effectively generate the requisite motion for thrust-vectoring propulsion, overcoming the limitations of traditional AUVs and expanding their potential applications across various domains.

Exact burst-size distributions for gene-expression models with complex promoter structure

In prokaryotic and eukaryotic cells, most genes are transcribed in a bursty fashion on one hand and complex gene regulations may lead to complex promoter structure on the other hand. This raises an unsolved issue: how does promoter structure shape transcriptional bursting kinetics characterized by burst size and frequency? Here we analyze stochastic models of gene transcription, which consider complex regulatory mechanisms. Notably, we develop an efficient method to derive exact burst-size distributions. The analytical results show that if the promoter of a gene contains only one active state, the burst size indeed follows a geometric distribution, in agreement with the previous result derived under certain limiting conditions. However, if it contains a multitude of active states, the burst size in general obeys a non-geometric distribution, which is a linearly weighted sum of geometric distributions. This superposition principle reveals the essential feature of bursting kinetics in complex cases of transcriptional regulation although it seems that there has been no direct experimental confirmation. The derived burst-size distributions not only highlight the importance of promoter structure in regulating bursting kinetics, but can be also used in the exact inference of this kinetics based on experimental data.

About the structure of water

It is shown that during 10–10–10–11s, only clusters consisting of 4 or 3 water molecules can statistically form in water. It is shown that Brownian motion in water occurs as a result of collision of ice nanocrystals with Brownian particles. Brownian motion is an experimental confirmation of the nanocrystalline structure of water. It is shown that water consists of 13 % molecules and 87 % ice nanocrystals. Such a two‑phase structure provides water with structural properties, high fluidity and elasticity of steam.

Experimental investigation on seismic performance of a super high-rise mega frame-double core tube composite structure

Increasing population density and urbanization have intensified the need for high-rise buildings in recent years. The seismic resistance of high-rise buildings should be carefully concerned in seismic regions, especially for super high-rise buildings which are most vulnerable to long-period earthquakes. This paper introduced the model design of a 499 m super high-rise mega frame-double core tube composite structure and presented the shaking table test results of the 1/50 scaled structural model. This super high-rise building possesses many conducive merits to resist seismic hazard, including steel reinforced concrete members, high-strength concrete and double core tube. In the test, there were three groups of long-period earthquakes and four incremental seismic intensity levels considered. The test phenomena indicated that the coupling beams of exterior tube were the first line of defense to resist seismic actions. The existence of inner tube improved the shear resistance of this building and there was no observed shear damage on the walls. Based on the instrumented data, the vibration characteristics, acceleration, displacement and strain responses of the structure were reported. The seismic performance of this super high-rise building meets the requirements of design specifications and its collapse resistance capacity is physically proved under severe earthquakes. However, the whiplash effect of acceleration is serious on the roof due to the reduction of mass and constraint for the mega column end. Furthermore, the inter-story drifts and strain responses of trusses in the top region are significantly larger. For the seismic measurement, great attentions should be paid to the exterior coupling beams and structural members in the top region of this super high-rise building. The presented work provides well experimental confirmation and reference for super high-rise buildings with mega frame-double core tube composite system.

Effects of spherical fillers reinforcement on the efficacy of thermal conductivity in epoxy and polyester matrices: Experimental validation and prediction using finite element method

AbstractThe creation of a theoretical heat conduction model for polymers embedded with spherical inclusions is described in this study. It also contains the experimental confirmation of the suggested correlation for utilizing the model to estimate the effective thermal conductivity (K) of such composites. According to ASTM‐E‐1530, composites are made with varying amounts of aluminium oxide and pine wood dust reinforced in polyester resin. The effective thermal conductivities (Keff) of the composites are then determined using the Unitherm TM model 2022. Ansys 19.R2 software is used to evaluate the effective thermal conductivity of these composites with a uniform filler distribution, while Digimat‐FE software is used determine the thermal conductivity values of such particle filled polymer composites with a random filler distribution. After comparison and validation with experimental data, these values are shown to be fairly good agreement with the theoretical values from the suggested correlation. The investigation is further expanded to determine the thermal conductivities for epoxy composites using wood apple shell dust and coir dust particle. Also epoxy and polyester composites reinforced with SiO2 and TiO2 have been investigated in the similar manner. The main thrust of this report to validate the numerical results of composites by varying numerous polymers. The thermal conductivity all the composites grow monotonically with increase in filler content. The thermal conductivity of silicon dioxide, titanium oxide, and aluminium oxide filled epoxy composites is measured as 1.5, 7, and 35 W/m‐K respectively.Highlights In this study spherical fillers are successfully used as a potential filler material in polyester composites The thermal conductivity predicted by proposed mathematical model of polyester is validated with measured value and found better agreement. The Ansys 19.R2 and digimat software are used to predict the thermal conductivity values of these composites. The mathematical model is further used to predict thermal conductivity of epoxy composites to check the accuracy of the model.