Rapid Assessment Approach Research Articles

One-step impedimetric NT-proBNP aptasensor targeting cardiac insufficiency in artificial saliva

Currently, sensitive and accurate approaches for diagnosis, rapid assessment, and cardiac biomarker monitoring in patients with heart failure are needed. In this context, the advantages of aptamers over traditional antibodies have been employed to fabricate a single-step impedimetric N-terminal pro b-type natriuretic peptide (NT-proBNP)-modified gold microelectrode array. The development of an electrochemical aptasensing platform was based on the coimmobilization of alkanethiol self-assembled monolayers and amine-terminated aptamer that specifically recognized cardiac NT-proBNP protein resulting in charge electron transfer. Electroimpedimetric signals of the sensor were observed to be linear to the NT-proBNP concentrations in the range of 5.0 × 10−3 to 1.0 pg mL−1 (R2 = 0.9624), while achieving a low detection limit of 5.0 × 10−3 pg mL−1. Clinically relevant detection levels for NT-proBNP were achieved in a simple, rapid, and label-free measurement using artificial saliva, which was highlighted to be specific, regenerative, and selective over potential interferers occurring during the processes of cardiac insufficiency, Therefore, the novel NT-proBNP aptasensor is a promising point-of-care tool exhibiting safe, non-invasive, affordable, and non-prescription home use accessible to overcome the limitations associated with conventional ELISA and previous aptasensing.

Analysis of Musculoskeletal Disorder Risk in Cotton Garment Industry Workers

ABSTRACT Work-related musculoskeletal disorders (wMSDs) are common workplace health hazard among sewing, ironing and packing workers, which can be caused by the manual and repetitive work in the garment industry. This research evaluates and categories the risk variables for 63 people took part in the Musculoskeletal Disorders study for garment material protection. The primary goal of this research is to determine the prevalence of Musculoskeletal Disorders (MSDs) and to reduce their risk. The data were gathered using a questionnaire and an observational checklist, and the risk was calculated using the Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment (RULA) approach and human postures were captured by camera for analysis. Reported musculoskeletal symptoms occurring in sewing, packing, ironing are lower back pain (50%, 61.5%, 42.5%), knee (30%, 15.3%, 27.5%), wrist pain (20%, 23%, 20%), shoulder pain (40%, 46.15%, 27.5%) and neck pain (40%, 23%, 32.5%), respectively, and ironing workers reported calf pain of 52.5% were the most common sites of pain. It is critical that awkward posture, uncomfortable movements, prolonged standing, and other factors contributed to an increase in worker risk while protecting garments.

Deep Learning Methods for Wood Composites Failure Predication

For glulam bonding performance assessment, the traditional method of manually measuring the wood failure percentage (WFP) is insufficient. In this paper, we developed a rapid assessment approach to predicate the WFP based on deep-learning (DL) techniques. bamboo/Larch laminated wood composites bonded with either phenolic resin (PF) or methylene diphenyl diisocyanate (MDI) were used for this sample analysis. Scanning of bamboo/larch laminated wood composites that have completed shear failure tests using an electronic scanner allows a digital image of the failure surface to be obtained, and this image is used in the training process of a deep convolutional neural networks (DCNNs).The result shows that the DL technique can predict the accurately localized failures of wood composites. The findings further indicate that the UNet model has the highest values of MIou, Accuracy, and F1 with 98.87%, 97.13%, and 94.88, respectively, compared to the values predicted by the PSPNet and DeepLab_v3+ models for wood composite failure predication. In addition, the test conditions of the materials, adhesives, and loadings affect the predication accuracy, and the optimal conditions were identified. The predicted value from training images assessed by DL techniques with the optimal conditions is 4.3%, which is the same as the experimental value measured through the traditional manual method. Overall, this advanced DL method could significantly facilitate the quality identification process of the wood composites, particularly in terms of measurement accuracy, speed, and stability, through the UNet model.

A new approach for rapid fatigue limit assessment for C45 steel based on contrast damage parameters

In the present work, a different procedure for rapid estimation of fatigue limit is employed for a case of study on C45 steel elements under two fatigue stress ratios. Specifically, three damage parameters are proposed for fatigue limit assessment of metallic materials. These damage factors are estimated employing a simply contrast-based approach that processes raw thermal data to provide dissipative, reversible, or local contrast measurements in selected inspected zones, respectively. Then, the obtained data of three thermal factors are correlated to related loading conditions. Simplified fatigue test campaigns of only 4 ÷ 8 specimens and few testing hours are carried out for both stress ratio conditions employing the ‘stepwise’ loading procedure. The fatigue limit estimation is performed through the standard linear regression approach and a different proposed approach based on the signal to noise ratio data. An interesting agreement between different proposed damage variables and well-established classical methods is observed in terms of fatigue limit estimations for both stress ratio conditions. In addition, a comparative analysis is performed between the obtained results and other research data obtained through thermal or energy methods by different authors, highlighting comparable results and adding robustness and reliability to the proposed approach for the fatigue limit estimation on tempered steel.

Abstract 15485: Tectonic Infarct Analysis: A User-Friendly Standalone Software for Whole-Brain Infarct Volume Estimation From 2,3,5-Triphenyltetrazolium Chloride-Stained Tissues

Introduction: Infarct volume measured from 2,3,5-Triphenyltetrazolium Chloride (TTC)-stained brain slices is critical for in vivo stroke models. However, current image tools are not automated and severely limited in their capability. Here, we developed an interactive, trainable software application that computes whole-brain infarct volume metrics from batches of serial TTC-stained brain sections. Methods: Male Wistar Rats ( n =21) received middle cerebral artery occlusion and were euthanized after 24 h. Brains were serially sectioned (2 mm, coronal), stained with TTC, and optically scanned (anterior and posterior sides). Manual annotations of infarcted regions and calculation of infarct volume were used as ground truth. We performed computational image analysis to segment brain tissue and develop a custom semantic segmentation model for infarct detection ( n =3 training cases) (Figure, top). Stroke parameters, including brain volume, infarct volume, infarct/non-infarct volume ratio (V), and % infarct were computed by measuring each feature per section, averaging over anterior and posterior faces, and summing across all slices. Results were compared against manual ground truth ( n =18 testing cases) using accuracy, f1-score, and Spearman correlation. The pipeline was then packaged as a standalone, opensource software named Tectonic Infarct Analysis (Figure, bottom). Results: The software performed well for brain (accuracy=0.95, f1-score=0.90) and infarct (accuracy=0.96, f1-score=0.89) segmentation. Strong, significant correlation was observed between manual and computational calculation of infarct parameters: V brain ( ρ =0.91, p <0.001), V infarct (0.97, p <0.001), V non-infarct (0.96, p <0.001), and % infarct (0.81, p =0.001). The software reduced analysis time by 25 min per case vs. manual effort. Conclusions: Tectonic Infarct Analysis software offers a robust and adaptable approach for rapid TTC-based stroke assessment.

Multivariate analysis of liquid biopsies for real-time detection of patients with biofilm-associated infections (BAI)

Biofilm-associated infections (BAI) are chronic infections that are refractory to standard antibiotic therapy and challenging to diagnose. Detecting biofilms in patients remains a major challenge in the clinical field. Here, we introduced a microfluidic-based label-free and multivariate analysis (LF-MA) platform to assess biofilm-associated infection disease via multivariate analysis of severity parameters for point-of-care (POC) management. The integrated LF-MA platform consisted of two components: Biofilm Enrichment Device (BED) and Severity Detection Device (SDD), and allowed simultaneous real-time biofilm enrichment and viscosity-based BAI severity detection. High recovery efficiencies (>80 %) were observed for both gram-positive and gram-negative strains. A novel biosensor HMS indicator (Healthy: 1–3+, Mild: 1–3-, Severe: 1 + 3-) was developed to evaluate the severity of BAI based on microbeads distribution in target outletsSDD (for viscosity assessment) and the presence of biofilms. The one-step strategy was validated with patient-derived clinical isolates and could be completed within 2 h. We envisioned that the ease of operations and derived HMS biosensor indicator could facilitate new patient-centric approaches for rapid and multivariate assessment of patients with BAI.

Probability-based residual displacement estimation of unbonded laminated rubber bearing supported highway bridges retrofitted with Transverse Steel Damper

Predicting the post-earthquake residual displacement of isolated bridges is crucial in deciding their operational and recovery strategies after a seismic event. This study proposes a probability-based approach to estimate the residual displacement of a trilinear hysteretic system representing the unbonded laminated rubber bearing (ULRB) supported highway bridge retrofitted with transverse steel dampers (TSDs), considering the uncertainty of structural parameters and the variability of ground motions. To this end, this study systematically derives the quasi-static residual displacement of a trilinear hysteretic system, and presents the statistical distribution model for the related structural parameters, especially for the pier height and the TSD model parameters. After that, the dynamic residual displacement property of the ULRB supported highway bridge retrofitted with TSDs is investigated considering the uncertainty of various parameters, including model parameters of TSD and ULRB, the mass of superstructure, the height of piers, as well as the ground motions with and without pulse. The maximum possible residual displacement of the trilinear hysteretic system is then related to its quasi-static residual displacement and peak displacement demand. Finally, an innovative probability-based approach is developed in this study to estimate the conditional probability of the dynamic residual displacement of the trilinear system exceeding a threshold at the given ground motion intensity, and this innovative approach is further validated by comparing it with the incremental dynamic analysis (IDA) method. Results show that the dynamic residual displacement of the TSD retrofitted ULRB supported highway bridge system is random, and the ratio between the dynamic residual displacement and the maximum possible residual displacement approximately satisfies a uniform distribution bounded by zero and one. The probability-based approach can obtain a close result with the IDA method and significantly reduce computational efforts. This research represents a first step toward developing a rapid post-earthquake assessment approach for seismically isolated bridges and the seismic design of these bridges considering the residual displacement.

Numerical modelling of thermal quantities for improving remote laser welding process capability space with consideration to beam oscillation

This research aims to explore the impact of welding process parameters and beam oscillation on weld thermal cycle during laser welding. A three-dimensional heat transfer model is developed to simulate the welding process, based on finite element method. The results obtained from the model pertaining to thermal cycle and weld morphology are in good agreement with experimental results found in the literature. The developed heat transfer model can quantify the effect of welding process parameters (i.e. heat source power, welding speed, radius of oscillation, and frequecy of oscillation) on the intermediate performance indicators (IPIs) (i.e. peak temperature, heat-affected zone (HAZ) volume, and cooling rate). Parametric contour maps for peak temperature, HAZ volume, and cooling rate are developed for the estimation of the process capability space. An integrated approach for rapid process assessment, and process capability space refinement, based on IPIs is proposed. The process capability space will guide the identification of the initial welding process parameters window and helps in reducing the number of experiments required by refining the process parameters based on the interactions with the IPIs. Among the IPIs, the peak temperature indicates the mode of welding while the HAZ volume and cooling rate represent weld quality. The regression relationship between the welding process parameters and the IPIs is established for quick estimation of IPIs to replace time-consuming numerical simulations. The application of beam oscillation widens the process capability space, making the process parameter selection more flexible due to the increase in distance from the tolerance boundaries.

FT-IR combined with chemometrics in the quality evaluation of Nongxiangxing baijiu

Recently, there has been an increasing demand for developing a reliable method to assess the quality of liquor in the baijiu industry quickly and accurately. The present study sought to establish a strategy for rapid quantitative analysis of the primary flavor components in Nongxiangxing baijiu. Under the experimental conditions, 7 of the 10 major flavor components in Nongxiangxing baijiu could be quantified effectively, such as ethyl butyrate (R2p = 0.9942), ethyl lactate (R2p = 0.9438), n-butanol (R2p = 0.9048), isobutanol (R2p = 0.9696), acetic acid (R2p = 0.9600), butyric acid (R2p = 0.8448), caproic acid (R2p = 0.9971). This result indicates that FT-IR combined with quantitative chemometric modeling could be a potential approach for rapid quality assessment of Nongxiangxing baijiu. Overall, this study provides a theoretical basis for subsequent related studies on Nongxiangxing baijiu.

Integrated reflection-FTIR and multivariate partial least squares approach for rapid and accurate assessment of total organic carbon concentration in shale

Spectral data of 193 shale samples collected from Cleveland and Wessex Basins in the United Kingdom were generated from the mid-infrared (MIR) region of the electromagnetic spectrum using two types of Fourier transform infrared (FTIR) spectroscopic techniques, attenuated total reflectance (ATR) and diffuse reflectance infrared fourier transform (DRIFT). Spectral data acquired using these techniques were combined with partial least square regression (PLSR) to calibrate models capable of rapid, routine, and accurate quantification of total organic carbon (TOC) concentration in sediment. At the validation stage, DRIFT presented high correlation coefficient (R2 = 0.96) between LECO measured and model-predicted TOC concentration relative to ATR (R2 = 0.89). Further optimisation of the DRIFT model with a balanced data set offered an improved correlation coefficient (R2 = 0.99) at the calibration and validation stages. Prediction of TOC content of shale samples with unknown values using the optimised model presented good correlation and low modelling error (R2 = 0.93; RMSE = 1.5 wt %): an indication that MIR-DRIFT-PLSR has the potential for accurate and precise quantification of sediment TOC concentration. The presence of organic functional groups and mineral absorption bands observed on the MIR spectra renders the technique indispensable for real-time simultaneous characterisation of TOC and minerals in Gas Shales and other formations during exploration.

High vulnerability and a big conservation gap: Mapping the vulnerability of coastal scleractinian corals in South China

Scleractinian corals build the most complex and diverse ecosystems in the ocean with various ecosystem services, yet continue to be degraded by natural and anthropogenic stressors. Despite the rapid decline in scleractinian coral habitats in South China, they are among the least concerning in global coral vulnerability maps. This study developed a rapid assessment approach that combines vulnerability components and species distribution models to map coral vulnerability within a large region based on limited data. The approach contained three aspects including, exposure, habitat suitability, and coral-conservation-based adaptive capacity. The exposure assessment was based on seven indicators, and the habitat suitability was mapped using Maximum Entropy and Random Forest models. Vulnerability of scleractinian corals in South China was spatially evaluated using the approach developed here. The results showed that the average exposure of the study region was 0.62, indicating relatively high pressure. The highest exposure occurred from the east coast of the Leizhou Peninsula to the Pearl River Estuary. Aquaculture and shipping were the most common causes of exposure. Highly suitable habitats for scleractinian corals are concentrated between 18°N–22°N. Only 21.6 % of the potential coral habitats are included in marine protected areas, indicating that there may still be large conservation gaps for scleractinian corals in China. In total, 37.7 % of the potential coral habitats were highly vulnerable, with the highest vulnerability appearing in the Guangdong Province. This study presents the first attempt to map the vulnerability of scleractinian corals along the coast of South China. The proposed approach and findings provide an essential tool and information supporting the sustainable management and conservation of coral reef ecosystems, addressing an important gap on the world's coral reef vulnerability map.

The effects of wheat‐pea mixed intercropping on biocontrol potential of generalist predators in a long‐term experimental trial

AbstractArthropod generalist predators can be effective natural control agents of pests and weeds in agroecosystems. Their activity and contribution to biocontrol may increase in response to more complex agricultural habitats. In this study, we investigated the effects of winter wheat‐pea mixed intercropping on the biocontrol potential of generalist predators compared with the respective mono‐crops. We evaluated not only the effects during the intercropping season but also the pre‐crop values of the mixture for the subsequent barley crop. Furthermore, we evaluated the influence of different long‐term soil organic carbon and fertility management regimes on activity and biocontrol potential of predators. Field work was conducted over two seasons in a field experiment located in Gembloux, Belgium. A set of proxies for ecosystem functions were measured using the Rapid Ecosystem Function Assessment approach. We measured attack and predation rates of sentinel prey and weed seeds artificially placed in the field. Furthermore, we assessed activity density of the main groups of generalist predators during the exposure of the baits. Our results showed that crop type affected activity and biocontrol potential of predators. Predation rates were much lower in wheat than pea and wheat‐pea. The mixture wheat‐pea had a positive effect on predator activity density compared to wheat mono‐crop, while pea supported an intermediate activity of epigeal predators. In the second season of the field work, we found the highest biocontrol potential by predators in barley plots cultivated after pea. Finally, our results failed to find any differences in biocontrol potential of predators between long‐term soil organic carbon and fertilisation management strategies. These results suggest that crop type has a major relevance in influencing the activity of generalist predators, and the mixed intercropping wheat‐pea may represent a valid strategy to enhance biological pest control in comparison to wheat cultivated as mono‐crop. Furthermore, we show that the cultivation of pea as mono‐crop may have an important pre‐crop value within the rotation increasing the provision of ecosystem services such as biocontrol.

Covid-19 and Coal Industry in Indonesia: A Preliminary Analysis

Corona Virus Disease (COVID-19) pandemic dramatically impacted the energy sector. About 4.5% of global primary energy consumption dropped in 2020, where coal demand decreased by 220 million tons of coal equivalent. The drop was driven by lower electricity demand due to policies against Covid-19 (i.e., travel restriction, lockdown, and new standard). In particular, the COVID-19 crisis has already created profound uncertainties for the Indonesian coal mining industry as one of the world's largest coal producers and exporters. Coal is the primary energy source for Indonesian electricity, contributing to the national revenues. A debate about action to take, whether to focus on dealing with Covid-19 health or maintaining economic growth, is unavoidable. With the number of cases continuing to rise, we set out to investigate the impact of COVID-19 on Indonesia's coal mining industry. Rapid desk assessment and descriptive statistical approach were used in this study by evaluating secondary data during the pandemic, comparing with previous years before the COVID-19 pandemic. The results revealed a tangible transformation in coal demand, production, and price. Despite domestic coal consumption for power generation decreased, the coal price increased in mid of 2021 due to rising coal demand in China.

High-rate (20 Hz) single-frequency GPS/GALILEO variometric approach for real-time structural health monitoring and rapid risk assessment

Real-time monitoring and the rapid risk assessment of the engineering structures after a natural event is crucial to prevent further disasters. Global Navigation Satellite System (GNSS) relative positioning and Precise Point Positioning (PPP) have been widely used in determining the seismic waveform and structural displacement. On the other hand, variometric approach (VA) is a future-promising method in capturing the real-time dynamic motions. VA technique has been broadly used in real-time co-seismic displacement retrieval so far. However, the usability of the high-rate single-frequency (SF) variometric approach in real-time structural health monitoring has not been investigated in the literature, yet. This paper examines the ability of the SF-VA based on 20 Hz GPS-only and GPS/GALILEO observations to capture high-frequency dynamic displacement and time difference displacement. The dynamic harmonic motions with various frequency and amplitude values were created using a single-axis shake table. In addition to that 1995 Kobe earthquake’s ground motion was also tested on the shake table to evaluate the performance of SF-VA for GNSS seismology applications. Displacement time and frequency series of SF-VA were compared with a series of Linear Variable Differential Transformer (LVDT) sensor installed to the shake-table. The comparisons show that SF-VA can effectively capture the harmonic motions’ vibrational frequencies and displacement amplitudes. The observed amplitudes of the displacement of harmonic movements are slightly different from the LVDT values at the order of millimeters. Thus, it is found that the SF-VA approach is a powerful and reliable tool in real-time structural health monitoring and rapid risk assessment.

A Two-stage Approach for Rapid Assessment of the Proportion Achieving Viral Suppression Using Routine Clinical Data.

Improving viral suppression among people with HIV reduces morbidity, mortality, and transmission. Accordingly, monitoring the proportion of patients with a suppressed viral load is important to optimizing HIV care and treatment programs. But viral load data are often incomplete in clinical records. We illustrate a two-stage approach to estimate the proportion of treated people with HIV who have a suppressed viral load in the Dominican Republic. Routinely collected data on viral load and patient characteristics were recorded in a national database, but 74% of patients on treatment at the time of the study did not have a recent viral load measurement. We recruited a subset of these patients for a rapid assessment that obtained additional viral load measurements. We combined results from the rapid assessment and main database using a two-stage weighting approach and compared results to estimates obtained using standard approaches to account for missing data. Of patients with recent routinely collected viral load data, 60% had a suppressed viral load. Results were similar after applying standard approaches to account for missing data. Using the two-stage approach, we estimated that 77% (95% confidence interval [CI] = 74, 80) of those on treatment had a suppressed viral load. When assessing the proportion of people on treatment with a suppressed viral load using routinely collected data, applying standard approaches to handle missing data may be inadequate. In these settings, augmenting routinely collected data with data collected through sampling-based approaches could allow more accurate and efficient monitoring of HIV treatment program effectiveness.

Engagement, experience, and satisfaction with peer-delivered whole health coaching for veterans with PTSD: A mixed methods process evaluation.

To describe the process of peer-delivered Whole Health Coaching, a primary care-based intervention in which peers provide patients with individualized support to set and work toward wellness goals. Fifteen primary care Veterans with PTSD participated in peer-delivered Whole Health Coaching during a multiple baseline design study. This is a planned mixed methods concurrent equal status analysis of the process of peer-delivered Whole Health Coaching including patient engagement, patient experience, fidelity to the coaching and peer roles, and patient satisfaction. Data sources were feedback interviews, electronic medical record reviews, self-report assessments, and observer fidelity ratings of session recordings. Qualitative data were used to expand the interpretation of quantitative descriptive data. A rapid assessment approach was used for qualitative analysis. Retention in peer-delivered Whole Health Coaching was 11 of 15 participants, and factors facilitating engagement were peers as providers and flexibility in scheduling/modality of sessions. Peers demonstrated high fidelity to coaching skills, Whole Health Coaching phases and stages, and the peer role. Participants expressed high satisfaction and perceived peer-delivered Whole Health Coaching as helpful with making progress on individualized wellness goals. Results build on the literature describing the expansion of peer services into primary care and implementation of interventions such as wellness coaching. This initial small study suggests that peers can deliver high-quality wellness coaching, and this description of the process can guide the integration of peers doing wellness coaching in similar clinical settings and for future research trials. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Analysis on the Development of Pakancupung Agropolitan Area in Kediri District, Indonesia

Regional economic growth can be expressed as an increase in the number of commodities that can be used or obtained in an area. Meanwhile, regional development is one of the development programs that aim to boost the growth rate of a region. Pakancupung agropolitan area is one of the agropolitan areas in Kediri Regency which has good potential of natural resources to be developed. This study aims at identifying the potential and problems of natural physical factors as well as supporting factors that influence the development of Pakancupung agropolitan area in Kediri regency. This study uses Rapid Assessment approach through several analysis techniques including LQ analysis, Growth Share analysis, Linkage System analysis, Institutional analysis, and Agropolitan Subsystem analysis. The results show that Pakancupung area has 3 commodities, namely rice, chilli and shallot, and the main commodities to be developed are rice, organic rice, shallot, red chilli and catfish. The development of agropolitan area in Pakancupung region has close linkages to other sectors, such as the industrial sector, the trade sector and the tourism sector. Overall, the number of supporting facilities and infrastructure for the agropolitan area at Pakancupung is sufficient. Keywords: Agropolitan, Commodities, Regional Development, LQ Analysis, Growth Share Analysis, Linkage System Analysis DOI: 10.7176/JESD/13-8-02 Publication date: April 30 th 2022

Expanding catalytic sensor capabilities to combustible gas mixtures monitoring

Preventing the explosion of mixtures of combustible gases and vapors is an important task in industry. This research presents an approach for rapid assessment of the explosiveness of combustible gas mixtures of unknown composition. The technique is based on registering the amount of heat released during the combustion of a portion of gases inside the catalytic sensor. The phenomenological theory of the approach for rapid assessment of the explosiveness was also presented. To carry out the measurements, a two-stage heating pulse and an approach to the calibration of the catalytic sensor were developed. The experiments were carried out for various mixtures of methane, propane, butane and hexane within the pre-explosive range (up to 50% Low Explosive Limit). In order to calculate the Lower Explosive Limit (LEL) of a mixture of flammable gases, Le Chatelier’s rule was used. Industrial catalytic sensors with additional diaphragm that limits the gas leakage into the sensor were used for measurements. The advanced data processing which is based on integrating the area under the measured dependence of sensor response on time was used to calculate the heat released. The parameters affecting the measurement results were analyzed. The measurement values were in good agreement with the prescribed values. The measurement errors did not exceed 10%. Since in this approach there is no need to identify gases, or their quantity and concentration, it can be used in industry for quick determination of potentially explosive mixtures in the air.

Phenotyping clonal populations of glioma stem cell reveals a high degree of plasticity in response to changes of microenvironment

AbstractThe phenotype of glioma-initiating cells (GIC) is modulated by cell-intrinsic and cell-extrinsic factors. Phenotypic heterogeneity and plasticity of GIC is an important limitation to therapeutic approaches targeting cancer stem cells. Plasticity also presents a challenge to the identification, isolation, and propagation of purified cancer stem cells. Here we use a barcode labelling approach of GIC to generate clonal populations over a number of passages, in combination with phenotyping using the established stem cell markers CD133, CD15, CD44, and A2B5. Using two cell lines derived from isocitrate dehydrogenase (IDH)-wildtype glioblastoma, we identify a remarkable heterogeneity of the phenotypes between the cell lines. During passaging, clonal expansion manifests as the emergence of a limited number of barcoded clones and a decrease in the overall number of clones. Dual-labelled GIC are capable of forming traceable clonal populations which emerge after as few as two passages from mixed cultures and through analyses of similarity of relative proportions of 16 surface markers we were able to pinpoint the fate of such populations. By generating tumour organoids we observed a remarkable persistence of dominant clones but also a significant plasticity of stemness marker expression. Our study presents an experimental approach to simultaneously barcode and phenotype glioma-initiating cells to assess their functional properties, for example to screen newly established GIC for tumour-specific therapeutic vulnerabilities.The authors barcoded glioma-initiating cells (GIC) using combinations of virally encoded fluorophores. GIC show a strong tendency to form clonal populations over as few as two passages. Combined with stem cell marker phenotyping and computational analysis, they could trace the fate of such populations. This model presents an approach for rapid assessment of newly established GIC to assess tumour-specific vulnerabilities.

Integrated Reflection-Ftir and Multivariate Partial Least Squares Approach for Rapid and Accurate Assessment of Total Organic Carbon Concentration in Shale

Integrated Reflection-Ftir and Multivariate Partial Least Squares Approach for Rapid and Accurate Assessment of Total Organic Carbon Concentration in Shale