In-depth Characterization Research Articles

Green Synthesis Gold Nanoparticles using Bioreductant Red Shoot Leaf Extract (Syzygium myrtifolium Walp.) and Activity as Antioxidant

Gold nanoparticles (AuNPs) are small-sized materials important in various commercial and industrial applications. Several methods have been developed to synthesise AuNPs. This study was conducted by synthesizing AuNPs using HAuCl4 as a precursor and red shoot leaf extract as a bioreductor. The concentrations of AuNPs used were 20, 10, 5, and 2.5 ppm. Characterization of gold nanoparticles at a concentration of 20 ppm was carried out using a UV-Vis spectrophotometer to measure the maximum wavelength and Transmission Electron Microscopy (TEM) to determine particle size. Antioxidant activity at 20, 10, 5, and 2.5 ppm was determined by measuring free radical capture activity using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) method. The results showed that gold nanoparticles had a maximum wavelength of 530 nm with a ruby red color and an average particle size of 14.907 nm. The synthesized AuNPs showed high antioxidant activity: 99.6% (20 ppm), 98.9% (10 ppm), 96.7% (5 ppm), and 91.0% (2.5 ppm), indicating that higher concentrations of AuNPs resulted in more significant free radical scavenging. This study successfully synthesized gold nanoparticles using red shoot leaf extract as an environmentally friendly bioreduction. The resulting nanoparticles have a nanometer particle size with very high antioxidant activity, especially at a concentration of 20 ppm. The method used in this study offers a more environmentally friendly alternative for synthesizing gold nanoparticles, which previously often used hazardous chemicals. The use of red shoot leaf extract as a bioreductor has not been widely reported in the literature, thus providing a new contribution to green nanotechnology. Further research is recommended to explore the potential applications of gold nanoparticles synthesized by this method in medical and other industrial fields. In addition, additional studies are needed to optimize the synthesis conditions and more in-depth characterization of the stability and toxicity of gold nanoparticles in practical applications.

Characterisation of European Field Goat Prion Isolates in Ovine PrP Overexpressing Transgenic Mice (Tgshp IX) Reveals Distinct Prion Strains.

After the detection of bovine spongiform encephalopathy (BSE), and a zoonotic transmissible spongiform encephalopathy (TSE) caused by the pathological prion protein (PrPSc) in two goats, the investigation of goat prions became of greater interest. Therefore, a broad collection of European goat TSE isolates, including atypical scrapie, CH1641 and goat BSE as reference prion strains were biochemically characterised and subsequently inoculated into seven rodent models for further analysis (already published results of this comprehensive study are reviewed here for comparative reasons). We report here the histopathological and immunohistochemical data of this goat TSE panel, obtained after the first passage in Tgshp IX (tg-shARQ) mice, which overexpress the ovine prion protein. In addition to the clear-cut discrimination of all reference prion strains from the classical scrapie (CS) isolates, we were further able to determine three categories of CS strains. The investigation further indicates the occurrence of sub-strains that slightly resemble distant TSE strains, such as BSE or CH1641, reinforcing the theory that CS is not a single strain but a mixture of sub-strains, existing at varying extents in one isolate. This study further proved that Tgshp IX is a potent and reliable tool for the in-depth characterisation of prion strains.

Infusion of Fly Ash/MgO in CaO-based sorbent for high-temperature CO2 capture: Precursor selection and its effect on uptake kinetics

Calcium Looping Technology for high-temperature CO2 capture suffers from a gradual decline of uptake capacity over repeated cycles caused by the sintering-induced agglomeration of CaO particles. The latter is typically inhibited by infusing inert into the sorbent to disperse CaO grains. In this respect, current work investigates the infusion of inerts like Fly ash (FA) and Magnesium salt in CaO-based sorbent through sol-gel combustion, assessing sorbent performance under harsh conditions: carbonation at 650 °C for 30 min and calcination at 950 °C for 15 min under a CO2 (100%) atmosphere. The study includes (i) in-depth characterization of various sorbents: both unsupported and modified with inert, synthesized using inorganic (InOP) and organometallic (OMP) precursors for different fuel-to-metal oxide molar ratios (MR = 2 and 3), (ii) thermogravimetric analysis for evaluating uptake kinetics based on carbonation conversion (XCBN) and cyclic stability and (iii) kinetic modeling to evaluate rate parameters. Kinetic analysis after a single cycle revealed the highest XCBN (78%) for unsupported InOP (MR = 2 and 3) and OMP (MR = 2) among thermally pre-treated sorbents. MgO-modified InOP (MR = 2) performed better (XCBN = 66%) than its OMP counterpart, while both MgO-modified sorbents (MR = 3) performed similarly (XCBN = 66%). Cyclic stability studies conducted for 30 cycles established higher stability of FA-modified OMP with lower deterioration by 13.47% (XCBN = 22.60%) than unsupported OMP by 62.99% (XCBN = 15.06%). Overall, the results showcase FA infusion in OMP as a viable route to develop stable modified CaO-sorbents with considerable carbonation conversion.

DiaPASEF Enables High-Throughput Proteomic Analysis of Host Cell Proteins for Biopharmaceutical Process Development.

Monitoring and quantifying host cell proteins (HCPs) in biotherapeutic production processes is crucial to ensure product quality, stability, and safety. Liquid chromatography-mass spectrometry (LC-MS) analysis has emerged as an important tool for identifying and quantifying individual HCPs. However, LC-MS-based approaches face challenges due to the wide dynamic range between HCPs and the therapeutic protein as well as laborious sample preparation and long instrument time. To address these limitations, we evaluated the application of parallel accumulation-serial fragmentation combined with data-independent acquisition (diaPASEF) to HCP analysis for biopharmaceutical process development applications. We evaluated different library generation strategies and LC methods, demonstrating the suitability of these workflows for various HCP analysis needs, such as in-depth characterization and high-throughput analysis of process intermediates. Remarkably, the diaPASEF approach enabled the quantification of hundreds of HCPs that were undetectable by a standard data-dependent acquisition mode while considerably improving sample requirement, throughput, coverage, quantitative precision, and data completeness.

Farm management practices and host species richness associated with higher likelihood of tuberculosis positive farms in Western Spain

Despite enormous efforts, complete animal tuberculosis (TB) eradication has only been achieved in few regions. Epidemiological analyses are key to identify TB risk factors and set up targeted biosecurity measures. Here, we conducted an in-depth characterization of 84 extensive beef cattle farms from a high TB prevalence region in Western Spain, and assessed how farm management and wildlife presence on farms contribute to cattle TB risk. Twenty-six out of 84 variables were associated with cattle farm TB positivity. Farm management variables associated with TB positivity included older cattle, larger herd size, highly fragmented farm structure and greater connectivity between farms. TB-positive farms provided supplemental feed over a higher number of months, used calf feeders, and had higher number of waterholes. Detecting Eurasian wild boar (Sus scrofa), red fox (Vulpes vulpes), European badger (Meles meles), roe deer (Capreolus capreolus), or Egyptian mongoose (Herpestes ichneumon) on cattle farms was also associated with farm TB positivity. The best ordinal regression model indicated that in farms with a large herd size (> 167 animals) the odds of being positive or recurrently positive (versus negative) was 7.34 (95% CI = 2.43–23.51) times higher that of farms with small herd size. Further, for every additional host species detected in the farm premises, the odds of being TB-positive increased 56%. We conclude that both cattle management and wildlife need to be targeted for successful TB control in grazing-based farming systems.

Mechanical characterization of lattice structures fabricated by selective laser melting via an image-based finite cell method with a damage model

Lattice structures fabricated by the selective laser melting (SLM) additive manufacturing process hold great potential for diverse applications. However, their actual mechanical behaviors often deviate from their counterparts with the as-designed geometries due to manufacturing defects. In this study, we presented an in-depth mechanical characterization of imperfect octet lattice structures via an image-based finite cell method (FCM) in combination with the multi-level hp refinement scheme for resolving the local defects and a Lemaitre damage model to conduct the damage analysis. Micro-computed tomography scanning was utilized to scan six SLM-fabricated octet lattice cells to obtain their as-built geometries. Based on the obtained geometry, the force-displacement curves and the damage distribution of the octet lattice cells and struts under given loads were predicted. The numerical results indicate that external defects significantly affect the struts' damage distribution, while internal voids have a lesser influence due to their low volume fraction. It is identified that the SLM-fabricated octet lattice cell presents better elastoplastic behavior along the loading direction perpendicular than parallel to its build direction. These insights into the mechanical performance of imperfect octet lattice cells underscore the defects' adverse effects and advance the understanding of their significance in SLM components.

Cellular heterogeneity and key subsets of tissue-resident memory T cells in cervical cancer

Tissue-resident memory T cells (TRMs) play a critical role in cancer immunity by offering quick and effective immune responses. However, the cellular heterogeneity of TRMs and their significance in cervical cancer (CC) remain unknown. In this study, we generated and analyzed single-cell RNA sequencing data from 12,945 TRMs (ITGAE+CD3D+) and 25,627 non-TRMs (ITGAE−CD3D+), derived from 11 CC tissues and 5 normal cervical tissues. We found that TRMs were more immunoreactive than non-TRMs, and TRMs in CC tissues were more activated than those in normal cervical tissues. Six CD8+ TRM subclusters and one CD4+ TRM subcluster were identified. Among them, CXCL13+ CD8+ TRMs were more abundant in CC tissues than in normal cervical tissues, had both cytotoxic and inhibitory features, and were enriched in pathways related to defense responses to the virus. Meanwhile, PLAC8+ CD8+ TRMs were less abundant in CC tissues than in normal cervical tissues but had highly cytotoxic features. The signature gene set scores of both cell subclusters were positively correlated with the overall survival and progression-free survival of patients with CC following radiotherapy. Of note, the association between HLA-E and NKG2A, either alone or in a complex with CD94, was enriched in CXCL13+ CD8+ TRMs interacting with epithelial cells at CC tissues. The in-depth characterization of TRMs heterogeneity in the microenvironment of CC could have important implications for advancing treatment and improving the prognosis of patients with CC.

In-depth genomic characterisation of SARS-CoV-2 variants from Egypt exhibited heterogeneous lineages.

Genetic variation of SARS-CoV-2 remains a public health challenge worldwide because of it influences the pathogenicity and transmissibility of the virus. To determine the genomic mutations of SARS-CoV-2 isolated in Egypt. This was an in silico cross-sectional study of 200 SARS-CoV-2 variants of concern, which were retrieved from the National Centre for Biotechnology Information on 11 January 2021 and aligned with the original Wuhan strain (NC_045512). Nucleotide basic local alignment search tool (BLASTN) was used to identify the nucleotide variations. Corresponding proteins were identified using protein basic local alignment search tool (BLASTP). A phylogenetic tree was constructed to study the evolutionary relationships using the neighbour-joining method. The variants of concern belonged to 26 species and there were 4 non-classified variants. All variants of concern showed 99.47-99.98% homology with the original Wuhan strain and demonstrated up to 60 mutations per variant. There were 1101 mutations identified among the variants of concern, with 458 synonymous and 583 nonsynonymous mutations. Specific mutations that were characteristically present in various SARS-CoV-2 lineages were identified, showing the microevolutionary genetic variations. This study showed vast genetic variations of the Egyptian SARS-CoV-2 with characteristic mutations for the A, B and C lineages. The study contributes to a better understanding of the epidemiological and demographic variations of COVID-19 in Egypt based on SARS-CoV-2 genomic evolution and supports further investigation of SARS-CoV-2 contextbased vaccine development and preventive measures.

Mitigating the impact of image processing variations on tumour [18F]-FDG-PET radiomic feature robustness

Radiomics analysis of [18F]-fluorodeoxyglucose ([18F]-FDG) PET images could be leveraged for personalised cancer medicine. However, the inherent sensitivity of radiomic features to intensity discretisation and voxel interpolation complicates its clinical translation. In this work, we evaluated the robustness of tumour [18F]-FDG-PET radiomic features to 174 different variations in intensity resolution or voxel size, and determined whether implementing parameter range conditions or dependency corrections could improve their robustness. Using 485 patient images spanning three cancer types: non-small cell lung cancer (NSCLC), melanoma, and lymphoma, we observed features were more sensitive to intensity discretisation than voxel interpolation, especially texture features. In most of our investigations, the majority of non-robust features could be made robust by applying parameter range conditions. Correctable features, which were generally fewer than conditionally robust, showed systematic dependence on bin configuration or voxel size that could be minimised by applying corrections based on simple mathematical equations. Melanoma images exhibited limited robustness and correctability relative to NSCLC and lymphoma. Our study provides an in-depth characterisation of the sensitivity of [18F]-FDG-PET features to image processing variations and reinforces the need for careful selection of imaging biomarkers prior to any clinical application.

Influence of the processing route on the mechanical properties of Cu–35Cr metal matrix composites

Cu–Cr-based composites with Cr content ranging from 20 to 50 wt% are widely used as electrical contacts for vacuum interrupters for medium voltage applications because of their excellent combination of mechanical, thermal, and electrical conductivity. Cu–Cr electrical contacts are usually processed by sintering or casting. Their mechanical properties have been the interest of some studies to enhance their percussion welding performance. However, a detailed microstructure-mechanical properties relationship for such composites is yet to be established. Herein, we report an in-depth multi-scale microstructural characterization of solid-state sintered and vacuum arc-remelted Cu–35Cr composites, coupled with the characterization of their mechanical properties. The strengthening mechanisms in both Cu and Cr phases are discussed in light of the microstructure differences caused by the processing route. The presence of large and interconnected pores at the Cu/Cr interfaces in the sintered Cu–Cr composites reduces the load transfer from the Cu matrix to the Cr reinforcing particles and leads to a lower dislocation density by differential thermal mismatch in the Cu matrix. We shed light on the influence of the processing routes on the microstructure-mechanical property relationships for Cu–35Cr composite materials.

Large-Scale Direct Growth of Monolayer MoS2 on Patterned Graphene for van der Waals Ultrafast Photoactive Circuits.

Two-dimensional (2D) van der Waals heterostructures combine the distinct properties of individual 2D materials, resulting in metamaterials, ideal for emergent electronic, optoelectronic, and spintronic phenomena. A significant challenge in harnessing these properties for future hybrid circuits is their large-scale realization and integration into graphene interconnects. In this work, we demonstrate the direct growth of molybdenum disulfide (MoS2) crystals on patterned graphene channels. By enhancing control over vapor transport through a confined space chemical vapor deposition growth technique, we achieve the preferential deposition of monolayer MoS2 crystals on monolayer graphene. Atomic resolution scanning transmission electron microscopy reveals the high structural integrity of the heterostructures. Through in-depth spectroscopic characterization, we unveil charge transfer in Graphene/MoS2, with MoS2 introducing p-type doping to graphene, as confirmed by our electrical measurements. Photoconductivity characterization shows that photoactive regions can be locally created in graphene channels covered by MoS2 layers. Time-resolved ultrafast transient absorption (TA) spectroscopy reveals accelerated charge decay kinetics in Graphene/MoS2 heterostructures compared to standalone MoS2 and upconversion for below band gap excitation conditions. Our proof-of-concept results pave the way for the direct growth of van der Waals heterostructure circuits with significant implications for ultrafast photoactive nanoelectronics and optospintronic applications.

Thermal Studies of Fractionated Lignite and Brown Coal Fly Ashes.

Coal fly ash (CFA), a by-product of coal combustion, is a valuable raw material for various applications. However, the heterogeneous nature of the composition and properties of CFA provides challenges to its effective usage and utilisation. This study investigates the thermal behaviour of the fly ashes of lignite (FA1) and brown coal (FA2) and their fractions obtained by dry aerodynamic separation. Thermal analysis techniques, including thermogravimetry (TG), differential scanning calorimetry (DSC), and evolved gas analysis (EGA), were used to characterise the behaviour of the fly ash fractions while heating up to 1250 °C. The results reveal distinct differences in the thermal behaviour between ash types and among their different size fractions. For the FA1 ashes, the concentration of calcium-rich compounds and the level of recrystallisation at 950 °C increased with the decrease in particle size. The most abundant detected newly formed minerals were anhydrite, gehlenite, and anorthite, while coarser fractions were rich in quartz and mullite. For the FA2 ashes, the temperature of the onset of melting and agglomeration decreased with decreasing particle size and was already observed at 995 °C. Coarser fractions mostly remain unchanged, with a slight increase in quartz, mullite, and hematite content. Recrystallisation takes place in less extension compared to the FA1 ashes. The findings demonstrate that the aerodynamic separation of fly ashes into different size fractions can produce materials with varied thermal properties and reactivity, which can be used for specific applications. This study highlights the importance of thermal analysis in characterising fly ash properties and understanding their potential for utilisation in various applications involving thermal treatment or exposure to high-temperature conditions. Further research on advanced separation techniques and the in-depth characterisation of fly ash fractions is necessary to obtain materials with desired thermal properties and identify their most beneficial applications.

Quantitative comparison of bile acid glucuronides sub-metabolome between intrahepatic cholestasis and healthy pregnant women.

Because of the pathological indication and the physiological functions, bile acids (BAs) have occupied the research hotspot in recent decades. Although extensive efforts have been paid onto BAs sub-metabolome characterization, as the subfamily, BA glucuronides (gluA-BAs) profile is seldom concerned. Here, we made efforts to develop a LC-MS/MS program enabling quantitative gluA-BAs sub-metabolome characterization and to explore the differential species in serum between intrahepatic cholestasis of pregnancy (ICP) patients and healthy subjects. To gain as many authentic gluA-BAs as possible, liver microsomes from humans, rats, and mice were deployed to conjugate glucuronyl group to authentic BAs through in vitro incubation. Eighty gluA-BAs were captured and subsequently served as authentic compounds to correlate MS/MS spectral behaviors to structural features using squared energy-resolved MS program. Optimal collision energy (OCE) of [M-H]->[M-H-176.1]- was jointly administrated by [M-H]- mass and glucuronidation site, and identical exciting energies corresponding to 50% survival rate of 1st-generation fragment ion (EE50) were observed merely when the aglycone of a gluA-BA was consistent with the suspected structure. Through integrating high-resolution m/z, OCE, and EE50 information to identify gluA-BAs in a BAs pool, 97 ones were found and identified, and further, quantitative program was built for all annotated gluA-BAs by assigning OCEs to [M-H]->[M-H-176.1]- ion transitions. Quantitative gluA-BAs sub-metabolome of ICP was different from that of the healthy group. More GCDCA-3-G, GDCA-3-G, TCDCA-7-G, TDCA-3-G, and T-β-MCA-3-G were distributed in the ICP group. Above all, this study not only offered a promising analytical tool for in-depth gluA-BAs sub-metabolome characterization, but also clarified gluA-BAs allowing the differentiation of ICP and healthy subjects.

Intersecting Blood Cytokines With Cholesterol Parameters to Profile Patients With Advanced Solid Tumors Receiving Immune Checkpoint Inhibitors.

The study investigated the relationship between serum proinflammatory cytokine levels, cholesterol metabolism, and clinical outcome in cancer patients undergoing immune checkpoint inhibitors (ICIs). Peripheral blood was collected before therapy from ICI-treated advanced cancer patients. We retrospectively assessed plasma total cholesterol (TC), ABCA1- and ABCG1-mediated cholesterol efflux (CE), passive diffusion (PD), cholesterol loading capacity (CLC), and serum IL-6, IL-10, and TNF-α. The association between blood cholesterol parameters and inflammatory cytokines and their effect on overall survival (OS), progression-free survival (PFS), and clinical benefit (CB) from ICIs were statistically assessed. Among 70 consecutively enrolled patients (nonsmall cell lung cancer: 94%; renal cell carcinoma: 6%), TC, CLC, and cholesterol PD resulted significantly higher in IL-6 low and IL-10 low cases ( P <0.05), whereas ABCA1-mediated CE was increased in IL-10 high patients ( P =0.018). Uni- and multivariable analysis revealed meaningfully longer OS and PFS in IL-6 low (HR 2.13 and 2.97, respectively) and IL-10 low (HR 3.17 and 2.62) groups. At univariate analysis all cholesterol-related indices significantly correlated with OS and PFS, whereas at multivariate only high PD was validated as a protection factor (OS, HR 0.75; PFS, HR 0.84). Finally, uni- and multivariable showed a statistically significant inverse association of CB with ABCG1-CE (OR 0.62), as with IL-6 (OR 0.13) and IL-10 (OR 0.10). In-depth characterization of the interplay between blood cholesterol metabolism and immune-inflammatory cytokines might provide novel insights into the complex relationship among cancer, inflammation, lipids profile, and response to immunotherapy.

Transfer Learning-Based Approach for Thickness Estimation on Optical Coherence Tomography of Varicose Veins.

In-depth mechanical characterization of veins is required for promising innovations of venous substitutes and for better understanding of venous diseases. Two important physical parameters of veins are shape and thickness, which are quite challenging in soft tissues. Here, we propose the method TREE (TransfeR learning-based approach for thicknEss Estimation) to predict both the segmentation map and thickness value of the veins. This model incorporates one encoder and two decoders which are trained in a special manner to facilitate transfer learning. First, an encoder-decoder pair is trained to predict segmentation maps, then this pre-trained encoder with frozen weights is paired with a second decoder that is specifically trained to predict thickness maps. This leverages the global information gained from the segmentation model to facilitate the precise learning of the thickness model. Additionally, to improve the performance we introduce a sensitive pattern detector (SPD) module which further guides the network by extracting semantic details. The swept-source optical coherence tomography (SS-OCT) is the imaging modality for saphenous varicose vein extracted from the diseased patients. To demonstrate the performance of the model, we calculated the segmentation accuracy-0.993, mean square error in thickness (pixels) estimation-2.409 and both these metrics stand out when compared with the state-of-art methods.

Hippocampal hub failure is linked to long-term memory impairment in anti-NMDA-receptor encephalitis: insights from structural connectome graph theoretical network analysis

BackgroundAnti-N-methyl-d-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis.MethodsStructural networks from 61 NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and 61 age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically constrained tractography and volumetry of a selection of subcortical and white matter brain volumes was performed. We calculated global, modular, and nodal graph measures with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were investigated regarding their potential association with clinical course, disease severity, and cognitive outcome.ResultsPatients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p = 0.049; right: p = 0.013) and increased node strength of right precuneus (p = 0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p = 0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p = 0.021). We found decreased left (p = 0.013) and right (p = 0.001) hippocampal volumes that were associated with hippocampal node strength (left p = 0.009; right p < 0.001).ConclusionsFocal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis.

Upgrading and Enhancement of Recycled Polyethylene Terephthalate with Chain Extenders: In-Depth Material Characterization.

Chemical chain extenders (CEs) can be used to restore the properties of recycled low-molecular-weight polyethylene terephthalate (PET). The aim of this work is to investigate the influence of the type and concentration of the CEs Joncryl and pyromellitic dianhydride (PMDA) on the viscosity and other rheological properties with a unique combination of different methods based on industrial samples originating from recycled PET bottles and trays. The resulting chain-extended thermoplastics were characterized by a combination of differential scanning calorimetry, viscometry, cone plate rheometry, pyrolysis-gas chromatography-mass spectroscopy, optical photothermal infrared spectroscopy, 13C solid-state- and 1H NMR liquid spectroscopy, and size exclusion chromatography. For a recycled PET mixture containing bottle and tray materials, our investigations have shown that a significantly better effect for chain elongation can be achieved with Joncryl compared to PMDA. This can presumably be attributed to water molecules formed during the use of PMDA, which accelerate the degradation of PET. The storage modulus values are therefore significantly higher for the samples with Joncryl compared to PMDA. The results of this study show that chain extension with Joncryl proceeds better compared to the reaction with PMDA.

Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 h

Aims/hypothesisDisruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes.MethodsWe exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-βH1 cells, followed by a glucose-stimulated insulin secretion assay.ResultsIn the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA1c, random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three (ERO1B, HNRNPA2B1 and RHOBTB3) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-βH1 cells.Conclusions/interpretationThe findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production.Data availabilityThe scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/) with accession no. phs001188.v3.p1. Study metadata and summary statistics for the differential expression, gene set enrichment and candidate effector gene prediction analyses are available in the Zenodo data repository (https://zenodo.org/) under accession number 11123248. The code used in this study is publicly available at https://github.com/CollinsLabBioComp/publication-islet_glucose_timecourse.Graphical

A combination of multiple LC-MS approaches for the comprehensive characterization of cysteine-linked ADCs

Antibody-drug conjugates (ADCs) represent the forefront of the next generation of biopharmaceuticals. An ADC typically comprises an antibody covalently linked to a cytotoxic drug via a linker, resulting in a highly heterogeneous product. This study focuses on the analysis of a custom-made cysteine-linked ADC. Initially, we developed a LC-MS-based characterization workflow using brentuximab vedotin (Adcetris®), encompassing native intact MS, analysis of reduced chains and subunits under denaturing condition, peptide mapping and online strong cation exchange chromatography coupled with UV and mass spectrometry detection (SCX-UV-MS) applied for brentuximab vedotin first time reported. Subsequently, we applied this in-depth characterization workflow to a custom-made cysteine-linked ADC. The measured drug-to-antibody ratio(DAR) of this ADC is 6.9, further analysis shown that there is a small amount of unexpected over-conjugation. Over-conjugation sites were successfully identified using multiple UHPLC-MS based characterization techniques. Also, one competitively cysteine-conjugated impurity was observed in native intact MS results, by combing native intact MS, reduced chains, subunit analysis and peptide mapping results, the impurity conjugation sites were also identified. Since this molecule is at early development stage, this provides important information for conjugation process improvement and link-drug material purification. SCX-UV-MS approach can separate the custom-made cysteine-linked ADC carrying different payloads and reduce the complexity of the spectra. The integrated approach underscores the significance of combining the SCX-UV-MS online coupling technique with other characterization methods to elucidate the heterogeneity of cysteine-linked ADCs.

Unraveling the Role of the Stoichiometry of Atomic Layer Deposited Nickel Cobalt Oxides on the Oxygen Evolution Reaction.

Nickel cobalt oxides (NCOs) are promising, non-precious oxygen evolution reaction (OER) electrocatalysts. However, the stoichiometry-dependent electrochemical behavior makes it crucial to understand the structure-OER relationship. In this work, NCO thin film model systems are prepared using atomic layer deposition. In-depth film characterization shows the phase transition from Ni-rich rock-salt films to Co-rich spinel films. Electrochemical analysis in 1m KOH reveals a synergistic effect between Co and Ni with optimal performance for the 30 at.% Co film after 500 CV cycles. Electrochemical activation correlates with film composition, specifically increasing activation is observed for more Ni-rich films as its bulk transitions to the active (oxy)hydroxide phase. In parallel to this transition, the electrochemical surface area (ECSA) increases up to a factor 8. Using an original approach, the changes in ECSA are decoupled from intrinsic OER activity, leading to the conclusion that 70 at.% Co spinel phase NCO films are intrinsically the most active. The studies point to a chemical composition dependent OER mechanism: Co-rich spinel films show instantly high activities, while the more sustainable Ni-rich rock-salt films require extended activation to increase the ECSA and OER performance. The results highlight the added value of working with model systems to disclose structure-performance mechanisms.