Characterization Methods Research Articles

Immune Cells at the Feto-Maternal Interface: Comprehensive Characterization and Insights into Term Labor

Immune cells at the feto-maternal interface play an important role in pregnancy; starting at implantation, maintenance of pregnancy, and parturition. The role of decidual immune cells in induction of labor still needs to be understood. Published reports on this topic show heterogeneity in methods of cell isolation, assay, analysis and cellular characterization making it difficult to collate available information in order to understand the contribution of immune cells at term leading to parturition. In the present study, available literature was reviewed to study the differences in immune cells between the decidua basalis and decidua parietalis, as well as between immune cells in term and preterm labor. Additionally, immune cells at the decidua parietalis were isolated from term not in labor (TNL) or term in labor (TL) samples and characterized via flow cytometry using a comprehensive, high-dimensional antibody panel. This allowed a full view of immune cell differences without combining multiple studies, which must include variation in isolation and analysis methods, for more conclusive data. The ratio of cells found in decidua parietalis in this study generally matched those reported in the literature, although we report a lower percentage of natural killer (NK) cells at term. We report that CD4 expression on CD8- NK cells decreased in term labor compared to not in labor samples, suggesting that natural killer cells may be migrating to other sites during labor. Also, we report a decrease in CD38 expression on CD8+ CD57+ T cells in labor, indicative of cytotoxic T cell senescence. Our study provides a comprehensive status of immune cells at the decidua-chorion interface at term.

Counting the truxillines-11 or more, the question is now.

Truxillines are a group of tropane alkaloids present in coca leaves that are formed by photochemical dimerization of cinnamoylcocaine(s). Proportion of different truxilline forms present in cocaine serves as its geographical, manufacture, and storage "fingerprint"; thus, the quantitative determination of truxilline content represents one of the powerful methods of analysis and characterization of cocaine samples. Contrary to the statements repeatedly presented in the literature, namely, that there exist exactly 11 truxillines and that every single truxilline is diastereomer of any other, here we show that,in fact, a total of 15 truxillines exist, which can be divided in two structurally isomeric groups-five mutually diastereomeric truxillates and 10 mutually diastereomeric truxinates.

Preparation and Characterization of Liposomes in Novel Drug Delivery Systems: A Review

Liposomes have emerged as versatile drug delivery vehicles with the potential to improve the therapeutic efficacy and safety profiles of various drugs. These lipid-based vesicles offer advantages such as biocompatibility, versatility in encapsulating hydrophilic and hydrophobic drugs, and the ability to target specific tissues or cells. This review provides a detailed examination of the preparation and characterization methods of liposomes in novel drug delivery systems (NDDS). It covers various techniques for liposome preparation, including conventional methods and advanced approaches, as well as the characterization parameters essential for evaluating liposomal formulations. Additionally, recent advancements, challenges, and future directions in the field are discussed.

Investigation of the Affinity of Aptamers for Bacteria by Surface Plasmon Resonance Imaging Using Nanosomes.

The cell-SELEX method enables efficient selection of aptamers that bind whole bacterial cells. However, after selection, it is difficult to determine their binding affinities using common screening methods because of the large size of the bacteria. Here we propose a simple surface plasmon resonance imaging method (SPRi) for aptamer characterization using bacterial membrane vesicles, called nanosomes, instead of whole cells. Nanosomes were obtained from membrane fragments after mechanical cell disruption in order to preserve the external surface epitopes of the bacterium used for their production. The study was conducted on Bacillus cereus (B. cereus), a Gram-positive bacterium commonly found in soil, rice, vegetables, and dairy products. Four aptamers and one negative control were initially grafted onto a biochip. The binding of B. cereus cells and nanosomes to immobilized aptamers was then compared. The use of nanosomes instead of cells provided a 30-fold amplification of the SPRi signal, thus allowing the selection of aptamers with higher affinities. Aptamer SP15 was found to be the most sensitive and selective for B. cereus ATCC14579 nanosomes. It was then truncated into three new sequences (SP15M, SP15S1, and SP15S2) to reduce its size while preserving the binding site. Fitting the results of the SPRi signal for B. cereus nanosomes showed a similar trend for SP15 and SP15M, and a slightly higher apparent association rate constant kon for SP15S2, which is the truncation with a high probability of a G-quadruplex structure. These observations were confirmed on nanosomes from B. cereus ATCC14579 grown in milk and from the clinical strain B. cereus J066. The developed method was validated using fluorescence microscopy on whole B. cereus cells and the SP15M aptamer labeled with a rhodamine. This study showed that nanosomes can successfully mimic the bacterial membrane with great potential for facilitating the screening of specific ligands for bacteria.

Sequencing of Phosphopeptides Using a Sequential Charge Inversion Ion/Ion Reaction and Electron Capture Dissociation Workflow.

Protein phosphorylation, a common post-translational modification (PTM), is fundamental in a plethora of biological processes, most importantly in modulating cell signaling pathways. Matrix-assisted laser desorption/ionization (MALDI) coupled to tandem mass spectrometry (MS/MS) is an attractive method for phosphopeptide characterization due to its high speed, low limit of detection, and surface sampling capabilities. However, MALDI analysis of phosphopeptides is constrained by relatively low abundances in biological samples and poor relative ionization efficiencies in positive ion mode. Additionally, MALDI tends to produce singly charged ions, generally limiting the accessible MS/MS techniques that can be used for peptide sequencing. For example, collision induced dissociation (CID) is readily amendable to the analysis of singly charged ions, but results in facile loss of phosphoric acid, precluding the localization of the PTM. Electron-based dissociation methods (e.g., electron capture dissociation, ECD) are well suited for PTM localization, but require multiply charged peptide cations to avoid neutralization during ECD. Conversely, phosphopeptides are readily ionized using MALDI in negative ion mode. If the precursor ions are first formed in negative ion mode, a gas-phase charge inversion ion/ion reaction could then be used to transform the phosphopeptide anions produced via MALDI into multiply charged cations that are well-suited for ECD. Herein we demonstrate a multistep workflow combining a charge inversion ion/ion reaction that first transforms MALDI-generated phosphopeptide monoanions into multiply charged cations, and then subjects these multiply charged phosphopeptide cations to ECD for sequence determination and phosphate bond localization.

The High Temperature Strength of Single Crystal Ni‐base Superalloys – Re‐visiting Constant Strain Rate, Creep, and Thermomechanical Fatigue Testing

The present work takes a new look at the high temperature strength of single crystal (SX) Ni‐base superalloys. It compares high temperature constant strain rate (CSR) testing, creep testing, and out‐of‐phase thermomechanical fatigue (OP TMF) testing, which represent key characterization methods supporting alloy development and component design in SX material science and technology. The three types of tests are compared using the same SX alloy, working with precisely oriented <001>‐specimens and considering the same temperature range between 1023 and 1223 K, where climb controlled micro‐creep processes need to be considered. Nevertheless, the three types of tests provide different types of information. CSR testing at imposed strain rates of 3.3 × 10−4 s−1 shows a yield stress anomaly (YSA) with a YSA stress peak at a temperature of 1073 K. This increase of strength with increasing temperature is not observed during constant load creep testing at much lower deformation rates around 10−7 s−1. Creep rates show a usual behavior and increase with increasing temperatures. During OP‐TMF loading, the temperature continuously increases/decreases in the compression/tension part of the mechanical strain‐controlled cycle (±0.5%). At the temperature, where the YSA peak stress temperature is observed, no peculiarities are observed. It is shown that OP‐TMF life is sensitive to surface quality, which is not the case in creep. A smaller number of cycles to failure is observed when reducing the heating rate in the compression/heating part of the mechanical strain‐controlled OP‐TMF cycle. The results are discussed on a microstructural basis, using results from scanning and transmission electron microscopy, and in light of previous work published in the literature.

Deep learning algorithm-enabled sediment characterization techniques to determination of water saturation for tight gas carbonate reservoirs in Bohai Bay Basin, China

Understanding water saturation levels in tight gas carbonate reservoirs is vital for optimizing hydrocarbon production and mitigating challenges such as reduced permeability due to water saturation (Sw) and pore throat blockages, given its critical role in managing capillary pressure in water drive mechanisms reservoirs. Traditional sediment characterization methods such as core analysis, are often costly, invasive, and lack comprehensive spatial information. In recent years, several classical machine learning models have been developed to address these shortcomings. Traditional machine learning methods utilized in reservoir characterization encounter various challenges, including the ability to capture intricate relationships, potential overfitting, and handling extensive, multi-dimensional datasets. Moreover, these methods often face difficulties in dealing with temporal dependencies and subtle patterns within geological formations, particularly evident in heterogeneous carbonate reservoirs. Consequently, despite technological advancements, enhancing the reliability, interpretability, and applicability of predictive models remains imperative for effectively characterizing tight gas carbonate reservoirs. This study employs a novel data-driven strategy to prediction of water saturation in tight gas reservoir powered by three recurrent neural network type deep/shallow learning algorithms—Gated Recurrent Unit (GRU), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), K-nearest neighbor (KNN) and Decision tree (DT)—customized to accurately forecast sequential sedimentary structure data. These models, optimized using Adam's optimizer algorithm, demonstrated impressive performance in predicting water saturation levels using conventional petrophysical data. Particularly, the GRU model stood out, achieving remarkable accuracy (an R-squared value of 0.9973) with minimal errors (RMSE of 0.0198) compared to LSTM, RNN, SVM, KNN and, DT algorithms, thus showcasing its proficiency in processing extensive datasets and effectively identifying patterns. By achieving unprecedented accuracy levels, this study not only enhances the understanding of sediment properties and fluid saturation dynamics but also offers practical implications for reservoir management and hydrocarbon exploration in complex geological settings. These insights pave the way for more reliable and efficient decision-making processes, thereby advancing the forefront of reservoir engineering and petroleum geoscience.

Elucidating the Impact of Polyol Functional Moieties on Exothermic Poly(urethane-urea) Polymerization: A Thermo-Kinetic Simulation Approach

The pursuit of sustainable polyurethane (PU) product development necessitates a profound understanding of precursor materials. Particularly, polyol plays a crucial role, since PU properties are heavily influenced by the type of polyol employed during production. While traditional PUs are solely derived from hydroxyl functionalized polyols, the emergence of amine-hydroxyl hybrid polyols has garnered significant attention due to their potential for enhancing PU product properties. These hybrid polyols are characterized by the presence of both amine and hydroxyl functional groups. However, characterizing these polyols remains a daunting challenge due to the lack of established experimental testing standards for properties, such as fractional hydroxyl and amine moieties and thermo-kinetic parameters for amine reactions with isocyanates. Additionally, characterization methods demand extensive time and resources and pose risks to health and the environment. To bridge these gaps, this study employed computational simulation via MATLAB to determine the moieties’ fractions and thermo-kinetic parameters for hybrid polyols. The computational method integrated energy balance and reaction kinetics analysis for various polyols to elucidate the influence of functional moieties on the thermo-kinetic behavior of PU formations. Validation of the simulated results was conducted by comparing their experimental and simulated prepolymer and foam temperature profiles, highlighting the direct influence of fractional moieties on PU formations. The comparisons revealed an average relative error of less than 5%, indicating the accuracy and credibility of the simulation. Thus, this study represents a pivotal opportunity for advancing knowledge and driving sustainable developments in bio-based polyol characterization for PU production streamlining and formulation optimization.

Sulfur Modified Carbon-Based Single-Atom Catalysts for Electrocatalytic Reactions.

Efficient and sustainable energy development is a powerful tool for addressing the energy and environmental crises. Single-atom catalysts (SACs) have received high attention for their extremely high atom utilization efficiency and excellent catalytic activity, and have broad application prospects in energy development and chemical production. M-N4 is an active center model with clear catalytic activity, but its catalytic properties such as catalytic activity, selectivity, and durability need to be further improved. Adjustment of the coordination environment of the central metal by incorporating heteroatoms (e.g., sulfur) is an effective and feasible modification method. This paper describes the precise synthetic methods for introducing sulfur atoms into M-N4 and controlling whether they are directly coordinated with the central metal to form a specific coordination configuration, the application of sulfur-doped carbon-based single-atom catalysts in electrocatalytic reactions such as ORR, CO2RR, HER, OER, and other electrocatalytic reaction are systematically reviewed. Meanwhile, the effect of the tuning of the electronic structure and ligand configuration parameters of the active center due to doped sulfur atoms with the improvement of catalytic performance is introduced by combining different characterization and testing methods. Finally, several opinions on development of sulfur-doped carbon-based SACs are put forward.

On the influence of graphene oxide and hydroxyapatite modification on alginate-based hydrogel matrix: thermal, physicochemical, and biological considerations

AbstractSodium alginate (SA) hydrogels with an addition of graphene oxide (GO) and hydroxyapatite (HAp) crosslinked by calcium chloride solution were investigated as potential materials for osteochondral tissue regeneration. The influence of various ratios of the nanoadditives in the natural derived polymer matrix on the thermal, physiochemical and biological properties was studied. Two thermal characterization methods (DSC and TGA) were employed to examine the thermal properties of the materials and provide information regarding the different types of water within the hydrogel structure. These parameters are crucial for the assessing and understanding of the adsorption/desorption processes in hydrogels and also impact their biocompatibility. The effect of GO and HAp addition on thermal characteristics of alginate hydrogel is reported, as well as the nanoadditives polymer chains interaction, as evidenced by FTIR results. The compression test confirmed that the nanoadditives, uniformly dispersed in the polymer matrix, improved the mechanical properties of the hydrogels, but only up to a certain content of additives. The composite hydrogels exhibited a very low friction coefficient. Both GO and HAp also enhanced chemical stability of alginate hydrogels under in vitro conditions. Biological assays demonstrated that most of the tested hydrogel extracts were not cytotoxic to hUC-MSCs, but they can affect the proliferation rate of the cells. Developed materials may present an intriguing alternative for osteochondral tissue regeneration.

Detection and analysis technologies for single biological nanoparticles

In recent years, nanoscale detection has played an increasingly important role in the research on viruses, exosomes, small bacteria, and organelles. The small size and complex biological natures of these particles, with the smallest known virus particle measuring only 17 nm in diameter and exosomes ranging from 30 nm to 150 nm in size, pose challenges to the classical large-scale (typically micron-scale) characterization methods, which has become a major obstacle in the research. The emergence of nanoscale detection and analysis technologies has filled the gap of optical microscopy, a conventional technique in this field. These technologies enable the sensitive and robust detection of objects that exceed the lower limit of optical detection, revealing the molecular composition and biological roles simultaneously. Currently, several commercialized instruments based on nanotechnology have emerged, providing complete single-particle detection solutions and achieving unique functionality based on their respective technological advantages. However, it is inevitable that these technologies have limitations in terms of application and detection capabilities, as they continue to evolve. This paper offers a thorough overview of the principles, advantages, limitations, and future development trends of several mainstream commercial instruments, aiming to serve researchers in selecting and utilizing these technologies.

Nickel Disulfide (NiS2): A Sustainable Low‐Cost Electrode Material for High‐Performance Supercapacitors

In the family of transition metal sulfides, nickel disulfide (NiS2) received significant attention in the recent past, particularly as an electrode‐active material for supercapacitors due to its high specific capacitance, high power density, long cyclic stability, and low cost. A detailed overview on the supercapacitor applications of NiS2 is lacking in the literature. In this review article, the unique features of NiS2 in terms of its various methods of synthesis, characterizations, and electrochemical performance evaluations are described. This review provides an in‐depth understanding on the unique properties of ultrathin nanostructured NiS2 such as structural properties, electronic properties, optical properties, and so on. Later, the various methods of synthesis including hydrothermal method, solvothermal method, solvent‐free approach, and so on are reviewed. Further, the strategies are discussed to improve the electrochemical performance of NiS2 by preparing hybrids or nanocomposites with other types of electrode‐active materials. The influence of electrode nanostructure and surface morphology on the charge storage is discussed with the help of specific examples. Furthermore, the potential challenges and future perspectives of NiS2 for commercial supercapacitors are examined. This review proclaims the development of novel approaches and strategies for the effective utilization of NiS2‐based electrodes for high‐performance low‐cost supercapacitors.

Intelligent prediction of wave loads based on multi-source data-driven methods

ABSTRACT High-fidelity wave-load tests is pivotal in the design and development of modern ship structures. Nonetheless, the prohibitive cost of conducting such tests limits their applicability. A wave-load data fusion method was implemented using the model test data from a typical displacement-type ship to generalise the small sample test, and a multi-source data characterisation and model parameter optimisation method were established to achieve efficient wave-load (wave frequency and slamming superposition) prediction. Using multi-source data, a multi-fidelity wave-load prediction (MFWLP) model was constructed by combining numerical computation, regular wave tests (RWT), and irregular wave test (IWT) data based on transfer learning with a secondary correction wave load prediction under irregular wave conditions. The model was effectively employed in a ship wave-load engineering case. This study reveals that the adopted MFWLP model demonstrates adequate extrapolation and prediction capabilities, even with limited high-fidelity test samples. The discrepancy between the nonlinear wave load prediction and model test was found to be within 15%. Therefore, the proposed method can serve as a foundation for rapidly assessing ship wave loads across various sea conditions, especially under high sea states.

Observation of Grain Boundary Sliding in a Lamellar Ultrafine‐Grained Steel

The deformation behavior of a ferrite steel with ultrafine‐grained (UFG) lamellar microstructure generated by linear flow splitting is investigated and compared to a coarser cold‐worked reference state, using a set of complementary local deformation and microstructural characterizations methods. The pile‐up around indentations shows a pronounced anisotropy for the UFG lamellar microstructure indicating the relative motion of grains along their elongated boundaries. This observation is confirmed by stepwise compression testing of micropillars along the normal direction of lamellar‐shaped grains using a new faceted pillar geometry to image the initial microstructure and its evolution throughout the test. The surface roughening in pillar compression testing can be categorized into the formation of discrete steps at the surface along particular grain boundaries and a more gradual roughening that is attributed to intragranular dislocation slip. Potential mechanisms for the observed grain boundary sliding are discussed taking several factors such as the strain rate sensitivity and potential Coble creep rates into account. In conclusion, a grain boundary sliding process carried by grain boundary dislocations appears to be the most likely explanation for the observed behavior.

Carboxymethyl-imidazolium O-vanillin Schiff base grafted into NH2-tagged MIL-101 (Cr) for effective removal of cupric ions from aqueous effluents.

A novel adsorbent (MIL-CMIVSB) was fabricated by modification of H2N-MIL-101(Cr) with carboxymethyl-imidazolium O-vanillin Schiff base. The MIL-CMIVSB's physicochemical characteristics were examined using the pertinent characterization methods. NH2-MIL-101(Cr) has a BET surface area of 1492.4 m2g-1, while MIL-CMIVSB adsorbent had 1278.7 m2g-1. Batch adsorption experiments examined the MIL-CMIVSB's cupric ion adsorption capacity from aqueous solutions at different adsorbent doses (0.1-3mg), pH (2.0-10.0), contact times (0-240min), metal ion initial concentrations (10-300mg/L), and temperatures (298-308K). The optimum conditions were 1mg/mL of MIL-CMIVSB adsorbent, 46min adsorption time, pH 7, 100ppm initial cupric ion concentration, and 303K temperature. MIL-CMIVSB effectively and selectively removes cupric ions with an adsorption capability of 359.05 ± 12.06mg/g. The nonlinear Liu isotherm governed Cu(II) sorption performance on MIL-CMIVSB (KL = 0.257 ± 0.01mg/g, R2 = 0.99892) and pseudo-2nd-order kinetically (k2 = 0.00116 × 10-4g/mg min, R2 = 0.99721).

Analytical Ultracentrifugation to Assess the Quality of LNP-mRNA Therapeutics

The approval of safe and effective LNP-mRNA vaccines during the SARS-CoV-2 pandemic is catalyzing the development of the next generation of mRNA therapeutics. Proper characterization methods are crucial for assessing the quality and efficacy of these complex formulations. Here, we show that analytical ultracentrifugation (AUC) can measure, simultaneously and without any sample preparation step, the sedimentation coefficients of both the LNP-mRNA formulation and the mRNA molecules. This allows measuring several quality attributes, such as particle size distribution, encapsulation efficiency and density of the formulation. The technique can also be applied to study the stability of the formulation under stress conditions and different buffers.

Uncovering the potential of industrial waste: turning discarded resources into sustainable advanced materials

To identify solutions for utilizing industrial wastes (slag, sludge, fly ash, and bottom ash) in the development of pro-environmental systems, this paper reviews existing literature and explores material characterization methods. A review analysis was conducted to uncover their potential, and it was found that many utilizations can be made to recycle them into sustainable materials. Structure characterization, optical-dielectric function, and morphology analysis were analyzed to confirm the recent review. Structural properties are represented by crystallite size and crystallinity, where nickel slag shows the smallest distribution (55 ± 10) nm with the highest crystallinity (25.42%), indicating its association with uniformity of response to external disturbances and micro-structural stability. From the analysis of optical and dielectric functions via Kramers Kronig relation, the widening of ∆(LO−TO) was shown by fly ash and slag indicating stable bonding suitable as x-ray shielding and sensor, while high electron loss functions were shown by sludge and bottom ash indicating high potential electronic transition performance. Based on their chemical and physical properties, these industrial wastes are not limited as construction materials and can even be upgraded to more advanced development materials.

Synthesis, MTT assay, 99m-Technetium radiolabeling, biodistribution evaluation of radiotracer and in vitro magnetic resonance imaging study of P,N-doped graphene quantum dots as a new multipurpose imaging nano-agent

Abstract In this study, a new nano-structure, N,P-doped graphene quantum dots (N,P-GQDs), were synthesized as multipurpose imaging agent for performing scintigraphy and magnetic resonance imaging (MRI). Some standard characterization methods were used to identify the nano-structure. In vitro cytotoxicity evaluation using MTT assay revealed that N,P-GQDs nanoparticles had no significant cytotoxicity after 24 and 48 h against normal (MCF-10A) and cancerous (MCF 7) human breast cell line in concentration up to 200 μg/mL. The N,P-GQDs were radiolabeled with Technetium-99m as 99mTc-(N,P-GQDs) and the radiochemical purity was assayed by ITLC concluding RCP ≥ 95 %. The passing of 99mTc-(N,P-GQDs) through 0.1 µm filter demonstrated that 70.8 % of particles were <0.1 µm. In order to perform scintigraphy, the 99mTc-(N,P-GQDs) were injected to female healthy Wistar rats. The results showed that the radio-complex was captured and eliminated just by kidneys. Moreover, in vitro T1-weighted phantom MRI imaging showed that the N,P-GQDs have proper relaxivity in comparison to Dotarem® as a clinically available contrast agent. The results showed that the N,P-GQDs have potential to be considered as a novel and encouraging agent for both molecular MRI and nuclear medicine imagings.

Aging Characterization of Modified Insulating Paper Based on the Transmission Characteristics of Microstrip Resonant Sensors

In this paper, the aging characterization of a kind of insulating paper modified by magnetron sputtering MgO particles based on a microstrip resonant sensor was presented. Firstly, the modified insulating paper with 0, 15 and 30 min MgO particle sputtering times was prepared by a magnetron sputtering device. After that, the properties of the modified insulating paper with different sputtering times were analyzed through microscopic characterization, infrared spectrum, polymerization degree, dielectric constant, AC breakdown strength and thermal aging experiments. The results show that the dielectric constant of the modified insulating paper decreased obviously, the AC breakdown strength increased and the thermal aging resistance was better after 15 min of sputtering. The overall performance of the modified insulating paper after 30 min of sputtering is reduced due to excessive sputtering. In addition, microstrip resonant sensors are introduced to characterize the thermal aging degree of the modified insulating paper, and two microstrip resonant sensors are prepared: a complementary split ring resonator (CSRR) and an interdigital-capacitor-shaped defected ground structure resonator (IDCS-DGS). The resonance frequency deviation of the modified insulating paper samples after aging was measured by microstrip resonance sensors to show the influence of aging temperature on aging degree. The experimental results show that the test results of the microstrip resonance sensors are in good agreement with the traditional characterization methods and can characterize the various aging stages of the modified insulating paper to a certain extent, which proves the feasibility of the characterization method.

#1949 Comparison of two commercial available primary human mesangial cell clones reveal differences

Abstract Background and Aims Mesangial cells and their matrix form the central stalk of the glomerulus but is often overlooked when studying glomerular function. The cells are however highly involved in glomerular function and crosstalk between the different cell types of the glomerulus. They are important in onset and progression of several glomerular diseases, such as IgA nephropathy and diabetic kidney disease. As mesangial cells have several functions and are involved in glomerular disease they are often used for in vitro work studying response to various stimuli and downstream signaling. This includes changes in the production and regulation or their matrix, proliferation, contractility, protein expression and release of different inflammatory mediators such as cytokines and growth factors [1]. Using primary cells when doing in vitro work is usually considered the best option, but there might be differences between origin of cells in their response and physiology. For this study, our aim was to compare two types of commercially available primary human mesangial cells from Cell systems (CS) and Novabiosis (NBS). Method For characterization of the CS and NBS mesangial cells, gene expression of commonly used mesangial cell markers, including KRT19, ACTA2, PDGFRA and PDGFRB, was analyzed with real time qPCR. Staining of smooth muscle actin was done in order to compare the phenotype of CS and NBS. To compare the cells, differences in protein expression were determined using proteomics. CS and NBS Cells were cultured in the same way and were also treated with PDGF-BB for 24 h to compare with untreated control. For further comparison, proliferation assay was used to compare proliferation after treating cells with PDGF-BB for 24 h. Results Both sources of cells expressed all markers, but there was a difference in level of gene expression. CS cells showed higher expression than NBS cells for all markers, apart from ACTA2. NBS cells had a more stellate phenotype whereas the CS cells were more elongated. There was a difference in proteins expressed by CS and NBS mesangial cells from our proteomics. The level of upregulation of proteins seen with proteomics was stronger for CS than NBS cells when treated with PDGF-BB. The number of proteins upregulated was also higher for CS than NBS cells. Both mesangial cell types had increased proliferation when treated with PDGF-BB, however CS cells were seen to grow faster in cell culture and seemed to be more responsive to the treatment with PDGF-BB. Conclusion In conclusion, this study compares two commercially available primary human mesangial cells and show that there is a difference between the two. The cell types react differently when treated with PDGF-BB and has some difference in what proteins they express. This needs to be considered when conducting cell culture experiments with mesangial cells, depending on what the aim and focus for the study is.