High Reproducibility Research Articles

Optimizing the SERS activity of PS@Ag/Au chips for quantitative analysis of carcinoembryonic antigen

Tumor markers play an important role in the diagnosis, treatment, and monitoring of tumors. Carcinoembryonic antigen (CEA) is a breast and rectal cancer biomarker that plays a crucial role in the early detection of cancer. Therefore, designing a suitable and ultrasensitive method for CEA analysis is very important. In this study, we demonstrated the high surface-enhanced Raman scattering (SERS) performance, high reproducibility, and good biocompatibility of a polystyrene (PS)@Ag/Au chip. This chip was produced layer-by-layer by magnetron sputtering to generate abundant “hotspots” between the Ag and Au layers covering the PS microspheres. Interestingly, the thickness of the Au layer was easily controlled to the appropriate value. When 4-mercaptobenzoic acid (MBA) was used as a probe molecule to explore the SERS activity of the chip, the enhancement factor (EF) reached 1.12×108, with a relative standard deviation of 3.059 %. A chip labeled with 5,5’-dithiobis(succinimidyl-2-nitrobenzoic acid) (DSNB) was used for CEA immunological recognition. With a linear range of 0–10,000 ng/mL, the limit of detection (LOD) was 0.0229 ng/mL. The standard recovery of CEA in fetal bovine serum (FBS) was between 84.90 % and 103.1 %. This chip is expected to be a novel tool in the field of cancer detection.

Plant‐assisted synthesis of Fe3O4 nanoparticles for catalytic degradation of methyl orange dye and electrochemical sensing of nitrite

AbstractThe present study details a more environmentally friendly method for synthesizing iron oxide nanoparticles (Fe3O4‐NPs) utilizing Hibiscus sabdariffa (H. sabdariffa) leaf extract. The produced H. sabdariffa/Fe3O4‐NPs underwent characterization through VSM, XRD, FESEM‐EDX, TEM and FTIR analyses. The FESEM and TEM images revealed that the H. sabdariffa/Fe3O4‐NPs had a narrow distribution and an average particle size of 5±2 nm. Catalytic degradation studies of the synthesized Fe3O4‐NPs exhibited efficient reduction of methyl orange (MO) dye. The degradation of MO catalysed by H. sabdariffa/Fe3O4‐NPs follow the pseudo‐first order kinetics, with a rate constant of 0.0328 s−1 (R2=0.9866). Moreover, in electrochemical sensing studies, the anodic peak current of nitrite (NO2−) for H. sabdariffa/Fe3O4‐NPs/GCE showed a linear relationship with its concentration within the range of 0.5–7.5 mM, achieving a detection limit of 0.29 μM. These findings demonstrate that the modified electrode with Fe3O4‐NPs synthesized using H. sabdariffa leaf extract serve as a novel electrochemical sensor for determining NO2− with high sensitivity and reproducibility.

Detection of lymphoma biomarker ferritin using functionalized carbon nanotube platform

For the detection of ferritin, this work engineered an electrochemical immunosensor by functionalizing multi-walled carbon nanotubes (MWCNTs) and integrating them into a screen-printed carbon electrode (SPCE) platform. Under optimal conditions (pH 7.4, antibody concentration 10 μg/mL, incubation time 30 min), the developed immunosensor exhibited a linear relationship between the electrochemical signal and ferritin concentrations spanning 1–500 ng/mL. Notably, it demonstrated an impressive ability to detect ferritin at exceptionally low levels, with a limit of detection reaching 0.3 ng/mL. The immunosensor demonstrated high selectivity, good reproducibility (RSD = 3.2 %, n = 5), and stability (87.3 % of initial response after 14 days at 4°C). The immunosensor was used to sensing ferritin in serum and good agreement with the commercial ELISA method (relative error < 5 %). The proposed sensor shows promise as a analytical approach for early diagnosis of lymphoma and point-of-care testing.

Nanochannel-confined platinum nanostructure for enhancement of luminol-dissolved oxygen electrochemiluminescence coupled with gated aptasensor for sensitive detection of carcinoembryonic antigen

Rapid and precise detection of tumor biomarkers in serum is of great significance for early diagnosis, treatment assessment, and recurrence monitoring of cancers. The fabrication of user-friendly electrochemiluminescence (ECL) aptasensors with effective signal amplification is highly desirable. In this study, an ECL aptasensor was developed with luminol-based ternary ECL platform using dissolved oxygen as endogenous co-reactant and nanochannel-confined platinum nanoparticles (PtNPs) as co-reactant promoter, which can realize highly sensitive detection of the tumor biomarker, carcinoembryonic antigen (CEA). On the cost-effective indium tin oxide (ITO) electrode, amino-modified vertically-ordered mesoporous silica film (NH2-VMSF) was easily grown to form high-density nanochannel array with ultrasmall nanochannels. PtNPs were then in-situ synthesized within the nanochannels via electrodeposition. Ternary ECL system was successfully fabricated as confined PtNPs can catalyze the electroreduction of dissolved oxygen at negative potentials as well as electrochemical oxidation of luminol, enhancing the ECL signal of luminol. The recognitive aptamer (Apt) was covalently immobilized on the outer surface of NH2-VMSF, resulting in the fabrication of an aptasensor. In presence of CEA, a decreased ECL signal was obtained as the formed complex on the recognition interface hindered the diffusion of ECL emitter to the supporting electrode. Based on this signal turn-off mode, sensitive detection of CEA was achieved ranged from 10 fg mL−1 to 100 ng mL−1, with a low detection limit (DL, 0.4 fg mL−1). The aptasensor displayed high selectivity and good reproducibility. The nanochannel-based aptasensor and ternary ECL system demonstrates great potential in convenient and sensitive detection of cancer biomarker.

Temporal dominance of Sensations: Do different concepts of “dominance” affect the results?

The purpose of this study was to understand the role of “dominance” definitions in the results of TDS applied to consumers. This study compared two temporal dominance of sensations (TDS) approaches − TDS-I − that attracts the most attention and TDS-II − most intense/strongest sensation − in the context of evaluating artisanal Minas cheeses from the Serra da Canastra and chocolate with different cocoa concentrations samples. TDS curves were constructed and a trajectory-based principal component analysis (PCA) was performed dominance rates at ten equally spaced time points. Additionally, difference curves, multiple factor analysis (MFA) and regression vector coefficient (RV coefficient) were performed to compare the two approaches. The findings showed that the two approaches produced similar results, suggesting that consumers interpret the terms dominant and intense in a similar way during TDS evaluations, the results were even closer at the chocolate study than at the cheese study. However, in both approaches were observed low dominance rates and differences between the sensation perception time, mainly in the evaluation of cheese flavor. This variability may be attributed to the complexity of the cheese’s flavor and the varied interpretations of dominance among evaluators. Despite these differences, the approaches showed similar characterizations across the same samples, demonstrating high reproducibility and a strong ability to differentiate between samples. This study demonstrates that the choice between the terms dominant (which captures more attention) or intense (stronger) to guide consumers in performing the sensory test does not significantly influence the results. Consequently, it is possible to adopt greater freedom and flexibility in the terminology used to instruct participants in conducting the test.

Flake size-dependent water transport through graphene oxide membranes and rejection of geosmin (GSM) and 2-methylisoborneol (MIB) from drinking water

Water transport through graphene oxide membranes (GOMs) and the rejection of inorganic and organic solutes have been extensively studied. However, the influence of the lateral size of GO flakes on membrane performance remains unclear. Here, we investigate the water permeation and separation performance of GOMs fabricated using various sizes of flakes. The membranes prepared with larger flakes showed higher water flux. Our experiment clearly shows that GOMs consist of both lamellae and void structures. Monte Carlo simulations indicate that water transport through the voids is faster than that through the lamellae in GO membranes. Moreover, the voids are more predominant for the membranes prepared with larger sizes of GO flakes and, hence, higher water flux for larger flake membranes. Additionally, the GOMs prepared with the large flakes effectively rejected more than 98 % of geosmin (GSM) and 2-methylisoborneol (MIB) with high reproducibility and a stable water flux of 1.49 LMH. Our results contribute to a better understanding of the complex structure of GOMs, where the rejection performance of membranes mainly depends on the interlayer space, but the water transport is governed by the voids. Our study also demonstrated the industrial potential of GOMs in drinking water purification technology.

Deep Learning‐Based Classification of Histone–DNA Interactions Using Drying Droplet Patterns

Developing scalable and accurate predictive analytical methods for the classification of protein‐DNA binding is critical for advancing our understanding of molecular biology, disease mechanisms, and a wide spectrum of biotechnological and medical applications. It is discovered that histone–DNA interactions can be stratified based on stain patterns created by the deposition of various nucleoprotein solutions onto a substrate. In this study, a deep‐learning neural network is applied to categorize polarized light microscopy images of drying droplet deposits originating from different histone–DNA mixtures. These DNA stain patterns featured high reproducibility across different species and thus enabled comprehensive DNA categorization (100% accuracy) and accurate prediction of their respective binding affinities to histones. Eukaryotic DNA, which has a higher binding affinity to mammalian histones than prokaryotic DNA, is associated with a higher overall prediction accuracy. For a given species, the average prediction accuracy increased with DNA size. To demonstrate generalizability, a pre‐trained CNN is challenged with unknown images that originated from DNA samples of species not included in the training set. The CNN classified these unknown histone‐DNA samples as either strong or medium binders with 84.4% and 96.25% accuracy, respectively.

(Digital Presentation) A Microfluidic Approach for Direct Immobilization of Extracellular Vesicles on Gold Nanoislands for Efficient Detection Using Localized Surface Plasmon Resonance

Extracellular vesicles (EVs) are crucial for intercellular communication and are potential biomarkers for cancer diagnosis. To improve the detection of EVs, we have developed a platform that uses an ultra-thin film of gold to form gold nanoislands. This platform allows for the direct immobilization of EVs onto the gold nanoislands, using a simple microfluidic device. Detection of the EVs is based on the Localized Surface Plasmon Resonance (LSPR) method. With this innovative approach, we aim to enhance the accuracy and efficiency of EV detection, which could ultimately lead to faster detection and therefore the possibility of an early-stage diagnosis of cancer.Gold nanoparticles are deposited on glass substrates using physical vapor deposition to create an ultra-thin layer of gold. Annealing the nanoparticle film forms gold nano-islands, which are drops with varying shapes and sizes from solid dewetting. A PDMS microfluidic device with a tapered channel of 200-micron depth and a 4mm diameter collection chamber bonded to gold-coated substrates is used to detect EVs from MCF7. The EVs flow through the channel at a rate of 10 µL/min, and the LSPR spectrum of the gold nanoislands is measured before and after EV immobilization. Changes in the refractive index of the surrounding medium due to the presence of EVs cause a shift in the Au LSPR band, which can be used to detect EVs.In this study, we will utilize extracellular vesicles (EVs) obtained from a breast cancer cell line (MCF7) that had been grown in a small bioreactor. A simple microfluidic device will be designed and fabricated to evaluate the Localized Surface Plasmon Resonance (LSPR) shift of the gold plasmon band for different EV concentrations. The microfluidic device was chosen due to its high reproducibility, sensitivity, and ability to work with small amounts of EVs. To understand the sensitivity of this platform, a calibration curve will be plotted and compared with the results of other platforms that we have previously studied. To validate the LSPR detection using the microfluidic device, the eluted exosomes from the device will be characterized using TRPS and FESEM techniques.Overall, our findings will demonstrate the potential of utilizing EVs and LSPR-based microfluidic devices as a promising tool for the detection of EVs and further clinical analysis for cancer diagnosis.

( General Student Poster Award Winner, 2nd Place) Template-Assisted Fabrication of Transparent SERS Sensor with Uniform Au-Ag Nanoparticle Electrodeposition

Surface-enhanced Raman spectroscopy (SERS) is a very powerful tool for analyzing molecular interactions and provides unique spectral fingerprint information about chemical bondings.[1] SERS enhances weak Raman scattering signals through surface-localized plasmon resonance (LSPR) of the plasmonic metal nanoparticles. Arbitrarily distribution of plasmonic metal nanoparticles can result in a non-uniform SERS enhancement effect (EF) and low reproducibility, which hinders the practical application of this ultra-sensitive analysis technology.[2] The development of a cost-effective, highly reliable, and highly reproducible SERS sensor with precisely controlled nanoparticle size and distribution is still a challenge.[3] Electron beam lithography (EBL) is commonly used to achieve well-controlled nanoscale patterns, which can be used as a top-down SERS sensor fabrication technique.[2] However, the time-consuming and extremely costly method makes the SERS sensor not easily accessible.In this research, we propose a template-assisted fabrication process by electrodepositing nanoparticles into nanoarrays on a transparent ITO surface. This method precisely controls the surface morphology and provides high reproducibility without relying on EBL techniques. For the fabrication process, first, a layer of sol-gel SiO2 solution was spin-coated onto the ITO surface, and an array of nano-pillars was used to imprint the nanopattern to the sol-gel solution layer, to realize the nano-ordered uniformly distributed nanoarrays. (Fig.1) For the plasmonic material, Au-Ag alloy was deposited into the nanoarray due to its high durability and high SERS EF.[4] The use of a pulse current deposition, additives, and self-assembled monolayer (SAM) was also discussed from the perspective of altering the surface property of the ITO surface, to achieve dense and smooth filling of deposits in the nanoarray. The SERS sensor fabricated was tested with Janus Green B (JGB) and demonstrated a good SERS EF and good signal uniformity. We believe this sensor is widely applicable for different systems, further optimization and application of this sensor can bring us one step closer to the quantitative analysis by SERS. The fabricated sensor should be especially useful in electrochemical reaction analysis and biomolecular sensing.[1] Fleishmann et al., Phys. Lett., 26, 163(1974)[2] Lee et al., Chemical Society reviews., 48, 731(2019)[3] Shi et al., 66, 6525(2018)[4] B. Liu et al., 55 , 117104(2016) Figure 1

Between-Visit Reproducibility of Shear Wave Viscoelastography in Volunteers and Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease.

To assess the reproducibility of six ultrasound (US)-determined shear wave (SW) viscoelastography parameters for assessment of mechanical properties of the liver in volunteers and patients with biopsy-proven metabolic dysfunction-associated steatotic liver disease (MASLD) or metabolic dysfunction-associated steatohepatitis (MASH). This prospective, cross-sectional, institutional review board-approved study included 10 volunteers and 20 patients with MASLD or MASH who underwent liver US elastography twice, at least 2 weeks apart. SW speed (SWS), Young's modulus (E), shear modulus (G), SW attenuation (SWA), SW dispersion (SWD), and viscosity were computed from radiofrequency data recorded on a research US scanner. Linear mixed models were used to consider the sonographer on duty as a confounder. The reproducibility of measurements was assessed by intraclass correlation coefficient (ICC), coefficient of variation (CV), reproducibility coefficient (RDC), and Bland-Altman analyses. The sonographer performing the exam had no impact on viscoelastic parameters (P > .05). ICCs of SWS, E, G, SWA, SWD, and viscosity were, respectively, 0.89 (95% confidence intervals [CI]: 0.79-0.95), 0.81 (95% CI: 0.79-0.95), 0.90 (95% CI: 0.80-0.95), 0.96 (95% CI: 0.93-0.98), 0.78 (95% CI: 0.60-0.89), and 0.90 (95% CI: 0.80-0.95); CVs were 11.9, 23.3, 24.2, 10.1, 29.0, and 32.2%; RDCs were 33.0, 64.5, 66.9, 27.7, 80.3, and 89.2%, and Bland-Altman mean biases and 95% limits of agreement were -0.05 (-0.45, 0.35) m/s, -0.61 (-5.33, 4.10) kPa, -0.25 (-2.06, 1.56) kPa, -0.01 (-0.27, 0.26) Np/m/Hz, -0.09 (-7.09, 6.91) m/s/kHz, and -0.33 (-2.60, 1.94) Pa/s, between the two visits. US-determined viscoelastography parameters can be measured with high reproducibility and consistency between two visits 2 weeks apart on the same ultrasound machine.

Ionic liquid-reinforced Hydroxyapatite@nano-TiO2 as a green platform for Immuno-electrochemical sensing applications

In contemporary society, developing dependable point-of-care (POC) biosensors for the timely detection of cancer markers is crucial. Among various sensor types, screen-printed electrode (SPE)-based sensors, particularly electrochemical ones, stand out as promising candidates for POC applications. Despite ongoing efforts to create numerous SPE-based sensors, there is a continuous pursuit to enhance their sensitivity and analytical capabilities. This study presents an advanced electrochemical sensor designed to sensitively detect the hepatocellular carcinoma (HCC) marker Alpha-fetoprotein (AFP) in saliva. The sensor employs a gold SPE modified with hydroxyapatite, TiO2 nanoparticles, 1-butyl-3-methylimidazolium bis(trifluoromethyl sulfonyl)imide ionic liquid (IL), and AFP monoclonal antibodies. After thorough characterization and optimization using cyclic voltammetry (CV) and differential pulse voltammetry (DPV), the biosensor exhibited a broad detection range (0.01–400 ng/mL), a low limit of detection (LOD) at 0.058 ng/mL, and demonstrated high selectivity, repeatability, reproducibility, and stability. Furthermore, when tested with spiked human saliva samples, the biosensor displayed excellent recovery and robustness, showcasing its potential for noninvasive and POC diagnosis of HCC. In an environmentally conscious evaluation, the biosensor's greenness was assessed using the AGREE metric, yielding a high score of 0.85. This score indicates the biosensor's alignment with the principles of green analytical chemistry, underlining its eco-friendly attributes. This innovative electrochemical sensor contributes to the ongoing efforts for efficient and reliable POC diagnostic tools and aligns with a broader commitment to developing environmentally friendly solutions.

A comparative study of population structure and genetic diversity of commercial and indigenous chickens from different agro-ecological zones in Ghana using SilicoDArT and SNP markers

Chicken production, both in the local and commercial sectors, contributes significantly to human livelihood and food security. Precise use of diverse genetic resources is primary in breeding programs. The study analyzed the genetic diversity and population structure of commercial chickens and indigenous chicken ecotypes from three different agro-ecological zones (Semi-Deciduous Rainforest Zone, Guinea Savannah, and Coastal Savannah) using SilicoDArT and SNP markers, utilizing whole-genome sequencing and phenotypic data. Phenotypic data were collected from 72 indigenous chicken ecotypes across the three AEZs, and 32 commercial birds kept at the Kwame Nkrumah University of Science and Technology (KNUST). DNA samples used for sequencing were obtained from 88 chickens (62 indigenous chicken ecotypes and 26 commercial chickens). A total of 54,995 SilicoDArT and 85,396 SNPs markers were generated from DArTseq genotyping. After filtering, 44,784 SilicoDArT and 58,353 SNP were used for genetic diversity and population structure analysis. Both markers showed high reproducibility and call rate. Polymorphic information content (PIC) values ranged from 0.00 to 0.50, while ≥ 50 % showed PIC values more than the median. Furthermore, we obtained FST values, Nei’s genetic distance, dendrogram analysis, and principal component analysis (PCA) of commercial and indigenous chickens. The FST and Nei’s genetic distance showed that there is high genetic diversity between the commercial chickens and the indigenous chicken ecotypes. However, there was low genetic diversity among the indigenous chicken ecotypes. The PCA analysis indicated a clear separation between the commercial and indigenous chicken ecotypes, while no clear separation was observed between the indigenous chicken ecotypes. The phenotypic data and the dendrogram indicated that naked and frizzle genes do not markedly alter the genetics of indigenous and commercial birds, and their influence on economic traits may be solely determined by the prevailing environmental conditions. The results indicate that there is high genetic differentiation between commercial and indigenous chickens based on SilicoDArT and SNP markers. The indigenous chickens from the agro-ecological zones have low genetic diversity and might have a common origin. Naked neck and frizzle genes do not markedly alter the genetic performance of birds in terms of economic traits. Therefore, the superiority of birds carrying these genes in economic traits may be solely due to environmental variation.

Supramolecular Electronics: Monolayer Assembly of Nonamphiphilic Molecules via Water Surface-Assisted Molecular Deposition.

Utilizing softly confined self-assembly at the water surface represents a promising approach for the fabrication of two-dimensional molecular monolayers (2D MMs), which have predominantly been concentrated on amphiphilic organic compounds before. Herein, we introduce a straightforward method termed "water surface-assisted molecular deposition (WSAMD)" to organize nonamphiphilic molecules into dense monolayers with high reproducibility. To underscore the versatility and merit of this methodology in the field of supramolecular electronics, we have successfully fabricated a range of defect-free, uniform semiconducting polymer monolayers, featuring a thickness reflective of molecular architectures. The charge carrier mobility could reach 0.05 cm2 V-1 s-1 for holes and 3.5 × 10-4 cm2 V-1 s-1 for electrons, respectively, in p-type and n-type polymeric monolayers when tested as the active layer in field-effect transistors. Furthermore, in situ polymerization reactions can be exploited to generate conductive monolayers of macromolecules such as polybenzylaniline (PBnANI) and polypyrrole (PPy), where PBnANI monolayers exhibit channel length-dependent conductivity, up to 0.37 S cm-1. The advent of the WSAMD method heralds a significant leap forward in the advancement of molecular 2D materials, catalyzing new avenues of exploration within material chemistry.

A Concise and Accurate Method for Evaluating Alveolar Cleft ReconstructionDiet al Concise and Accurate Method for Evaluating.

Currently, there remain unresolved issues in the treatment of alveolar clefts, the resolution of which could greatly benefit many patients with cleft lip and palate. In alveolar cleft treatment research, a reliable tool for pre- and postoperative assessment is crucial. This study presents a concise and accurate method for postoperative evaluations of alveolar treatment, which can rapidly and accurately obtain the shape and volume of the newly formed bone. This study included helical computed tomography (CT) datasets of 20 patients who underwent alveolar bone grafting at our institute. Two observers independently measured the volume of newly formed bone in the patient's CT images one year postoperatively, with each observer performing the measurement twice. To acquire the volume of the newly formed bone at 1 year postoperatively, the model of the newly formed bone must be constructed first. The acquisition of this model involves Boolean operations on registered preoperative and postoperative cranial 3-dimensional (3D) images. The registration of the preoperative and postoperative models is performed in MIMICS software, and the registration results can be directly confirmed layer by layer on the CT images to ensure accuracy. The mean newly formed bone ratio in this study was 39.81%±17.96%, and the mean processing time was 05:11±01:41 minutes. The intraclass correlation coefficient for bone volume measurements between the two observers was 0.999, indicating high consistency and reproducibility. This method enhances accuracy, is time-efficient, and demonstrates high reliability in evaluating postoperative bone formation.

A Simplified Method for Comprehensive Capture of the Staphylococcus aureus Proteome.

Staphylococcus aureus is a major human pathogen causing myriad infections in both community and healthcare settings. Although well studied, a comprehensive exploration of its dynamic and adaptive proteome is still somewhat lacking. Herein, we employed streamlined liquid- and gas-phase fractionation with PASEF analysis on a TIMS-TOF instrument to expand coverage and explore the S. aureus dark proteome. In so doing, we captured the most comprehensive S. aureus proteome to date, totaling 2,231 proteins (85.6% coverage), using a significantly simplified process that demonstrated high reproducibility with minimal input material. We then showcase application of this library for differential expression profiling by investigating temporal dynamics of the S. aureus proteome. This revealed alterations in metabolic processes, ATP production, RNA processing, and stress-response proteins as cultures progressed to stationary growth. Notably, a significant portion of the library (94%) and proteome (80.5%) was identified by this single-shot, DIA-based analysis. Overall, our study shines new light on the hidden S. aureus proteome, generating a valuable new resource to facilitate further study of this dangerous pathogen.

Highly selective sustainable ethanol gas sensor based on p-p heterojunction of SnS/MoSe2 nanocomposite at room temperature

Herein, a high-performance chemiresistive ethanol gas sensor operating at room temperature (RT) is demonstrated based on SnS/MoSe2 nanocomposite. The ethanol-sensing capabilities of the pristine-SnS and SnS/MoSe2 nanocomposite sensor are examined by exposing it to various ethanol concentrations ranging from 50 to 400 ppm at room temperature (RT). The sensing device based on the nanocomposite exhibits a high gas sensing response (Rg/Ra) of 26.8 to 400 ppm for ethanol gas. This results in improved response and recovery times of 9.1 s and 15.7 s respectively, along with high stability, selectivity, and reproducibility. Employing heterojunction in gas-sensing is an effective method for boosting the gas-sensing capabilities of 2D semiconductors. However, selecting semiconductors with compatible energy bands is equally crucial for optimizing gas sensing performance. The synergy arising from the p-p type heterojunction of SnS nanoplates and MoSe2 nanosheets is observed to enhance the sensor's response to ethanol gas. The sensing mechanism of the SnS/MoSe2 nanocomposite sensor is attributed to the formation of p-p heterojunction, modulation of the potential barrier, and charge carrier transfer. The findings suggest that the SnS/MoSe2-based nanocomposite stands out as a potential candidate for fabricating high-performance ethanol gas sensors for electronic applications in environmental monitoring.

Early detection of the ovarian cancer with a label-free and disposable ITO-PET based immunosensor platform

Alpha fetoprotein (AFP), a popular biomarker for ovarian cancer, was the target of this studyto create an immunosensor based on electrochemical impedance spectroscopy (EIS). For this purpose, a disposable Indium tin oxide coated PET (In2O3/SnO2, ITO-PET) electrode was used as a basic electrode for working of the triple electrode system and the electrodes were modified with 3-(Trimethoxy silyl) propyl methacrylate (3- TMSPM) silanization agent. Although there are studies on the determination of AFP, the determination of AFP with a cheap, flexible and sensitive electrode system such as ITO-PET in this study makes the study remarkable. With the designed biosensors, AFP protein determination at a wide concentration range (0.05 pg/mL-100 pg/mL) could be successfully performed. To prove that the designed immunosensor was constructed correctly, linear range, repeatability, reproducibility and regeneration capacity (characterization studies) were investigated. Obtaining successful results in the storage capacity studies of the biosensor, which has high reproducibility and repeatability, showed that it also has potential for commercial use. The high specificity of the biosensor also proves its reliability. Finally, the performance of the biosensor in commercial human serum samples was also evaluated.

A fluorescence-enhanced method specific for furfural determination in Chinese Baijiu based on luminescent carbon dots and direct surface reaction

Detecting the furfural concentration in Baijiu can be used to assess the quality of Baijiu, allowing for the optimization of processing techniques and the enhancement of overall quality. In this paper, a fluorescence-enhanced method based on carbon dots (o-CDs) is developed for the furfural determination in Chinese Baijiu. In an environment full-filled with ·SO4‐ and ·OH, furfural undergone a direct surface reaction with the ortho-diamino groups at o-CDs. The created furan-based imidazole increased the surface electron density, leading an emission enhancement and color changes from orange to green. Thereby, a linear fluorescence response of o-CDs-TA to furfural is established in water with a detection limit of 30.5 nM. Finally, after ethanol correction it is used to determine furfural in Chinese Baijiu with high precision and reproducibility, providing a new strategy with low-cost and high sensitivity. In particular, the idea of covalently connecting target molecule to the CDs surface via the assistance of free radical opens a new avenue to merge the nanoscale and molecular realms through implementing chemical role into carbon nanostructures.

Abstract We007: High Throughput 3D-Printed Human Engineered Heart Tissues for Cardiac Disease Modeling

While cell models have been used to study cardiac diseases, there is currently no standardization or fully mature in vitro system. Obtaining a mature cardiomyocyte (CM) phenotype is necessary to create a physiologically relevant environment and accurately model and study cardiac diseases. Increased success in maturation of human induced pluripotent stem cell derived CMs (hiPS-CMs) has been achieved in 3D in vitro models in the form of engineered heart tissues (EHTs). Digital light processing (DLP) offers a high throughput and efficient method to fabricate hydrogels that recapitulate properties of native tissues. In this study, we use DLP-printed EHTs to seed and mature differentiated hiPS-CMs and test their potential for modeling pathological cardiac hypertrophy. To further encourage maturity of CMs, we utilized a low glucose maturation medium supplemented with fatty acids. DLP-printed EHTs displayed high reproducibility and increased CM maturity. To determine degree of maturity of our system, we performed RT-qPCR, western blot analysis, and immunofluorescence (IF) microscopy. We found increased expression of fatty-acid transport and beta oxidation genes and improved sarcomere alignment compared to 2D hiPS-CMs. To model pathological cardiac hypertrophy, we used two different approaches: 1. acute adrenergic agonism with isoproterenol and phenylephrine; 2. chronic culturing of EHTs in pathologically stiff conditions. To assess pathology, we conducted RT-qPCR, western blot, ELISA, IF microscopy, and functional analyses. We found that agonist-treated EHTs displayed increased pathology-associated gene expression compared to standard 2D hiPS-CMs. Both agonist-treated and stiff EHTs had increased secreted B-Type Natriuretic Peptide (BNP) and phosphorylation of proteins involved in pathological remodeling, including ERK and P38. Additionally, we observed increased nuclear area, increased calcium handling, and increased contractile force in the treatment groups. In conclusion, we have established a high throughput, reproducible, mature EHT platform that can be used to model pathological cardiac hypertrophy. This platform can be easily adopted by other laboratories to study a wide array of cardiac diseases.

Effect of Deep Learning Image Reconstruction Algorithms on Radiomic Features of Pulmonary Nodules in Ultra-Low-Dose CT.

The purpose of this study is to explore the impact of deep learning image reconstruction (DLIR) algorithm on the quantification of radiomic features in ultra-low-dose computed tomography (ULD-CT) compared with adaptive statistical iterative reconstruction-Veo (ASIR-V). One hundred eighty-three patients with pulmonary nodules underwent standard-dose computed tomography (SDCT) (4.30 ± 0.36 mSv) and ULD-CT (UL-A, 0.57 ± 0.09 mSv or UL-B, 0.33 ± 0.04 mSv). SDCT was the reference standard using (ASIR-V) at 50% strength (50%ASIR-V). ULD-CT was reconstructed with 50%ASIR-V, DLIR at medium and high strength (DLIR-M, DLIR-H). Radiomics analysis extracted 102 features, and the intraclass correlation coefficient (ICC) quantified reproducibility between ULD-CT and SDCT reconstructed by 50%ASIR-V, DLIR-M, and DLIR-H for each feature. Among 102 radiomic features, the percentages of reproducibility of 50%ASIR-V, DLIR-M, and DLIR-H were 48.04% (49/102), 49.02% (50/102), and 52.94% (54/102), respectively. Shape and first order features demonstrated high reproducibility across different reconstruction algorithms and radiation doses, with mean ICC values exceeding 0.75. In texture features, DLIR-M and DLIR-H showed improved mean ICC values for pure ground glass nodules (pGGNs) from 0.69 ± 0.23 to 0.75 ± 0.18 and 0.81 ± 0.12, respectively, compared with 50%ASIR-V. Similarly, the mean ICC values for solid nodules (SNs) increased from 0.60 ± 0.19 to 0.66 ± 0.14 and 0.69 ± 0.13, respectively. Additionally, the mean ICC values of texture features for pGGNs and SNs in both ULD-CT groups decreased with reduced radiation dose. DLIR can improve the reproducibility of radiomic features at ultra-low doses compared with ASIR-V. In addition, pGGNs showed better reproducibility at ultra-low doses than SNs.