High Number Of Replicates Research Articles

Closed-form expressions of the run-length distribution of the nonparametric double sampling precedence monitoring scheme

AbstractA significant challenge in statistical process monitoring (SPM) is to find exact and closed-form expressions (CFEs) (i.e. formed with constants, variables and a finite set of essential functions connected by arithmetic operations and function composition) for the run-length properties such as the average run-length ($$ARL$$ ARL ), the standard deviation of the run-length ($$SDRL$$ SDRL ), and the percentiles of the run-length ($$PRL$$ PRL ) of nonparametric monitoring schemes. Most of the properties of these schemes are usually evaluated using simulation techniques. Although simulation techniques are helpful when the expression for the run-length is complicated, their shortfall is that they require a high number of replications to reach reasonably accurate answers. Consequently, they take too much computational time compared to other methods, such as the Markov chain method or integration techniques, and even with many replications, the results are always affected by simulation error and may result in an inaccurate estimation. In this paper, closed-form expressions of the run-length properties for the nonparametric double sampling precedence monitoring scheme are derived and used to evaluate its ability to detect shifts in the location parameter. The computational times of the run-length properties for the CFE and the simulation approach are compared under different scenarios. It is found that the proposed approach requires less computational time compared to the simulation approach. Moreover, once derived, CFEs have the added advantage of ease of implementation, cutting off on complex convergence techniques. CFE's can also easily be built into mathematical software for ease of computation and may be recalled for further work.

Diversity, distribution patterns and indicatory potential of echinoderm communities of the tropical East Atlantic (Gulf of Guinea): Influence of multiple natural and anthropogenic factors along a 25–1000 m depth gradient

All earlier studies of the West African echinoderm fauna have focused on taxonomy, and general knowledge about benthic community responses to various human related threats are poorly diagnosed and not monitored along the whole African coast. Our analysis of diversity and distribution patterns of Ghanaian echinoderms yielded 36 species. Material was collected at nine transects distributed along the coast of Ghana (25–1000 m depth range, total of over 270 samples). Gradual decreases in species richness, diversity, evenness and abundance were observed along the depth gradient, with the most diverse fauna being recorded on the shelf (25–50 m). The most abundant species were Ophiactis luetkeni and Ophiothrix congensis, although both had very patchy distributions. Cluster analysis separated shelf communities (25–100 m) from slope communities (500–1000 m), although on a low level of similarity. Our analysis allowed to select most vulnerable benthic habitats that should be amongst priorities of the future monitoring. Local influence of arsenic was observed at some shelf sites, while slope fauna was affected by elevated levels of hydrocarbons and barium. Changes in salinity and fluorescence also influenced echinoderm assemblages. The most general trend showed patchily distributed, diverse shallow water fauna being influenced by increased microhabitat diversity and food availability, while depauperate slope fauna was affected by local disturbances associated with oil extraction. Tropical echinoderm communities have a great potential as indicators of even minor and local pollution, although high patchiness and low abundance creates difficulties in the multivariate analysis. High sampling effort and high number of replicates allowed to minimise those problems and demonstrated small scale microhabitat diversity.

Identification of Cellular Factors Required for SARS-CoV-2 Replication

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the recently emerged virus responsible for the COVID-19 pandemic. Clinical presentation can range from asymptomatic disease and mild respiratory tract infection to severe disease with lung injury, multiorgan failure, and death. SARS-CoV-2 is the third animal coronavirus to emerge in humans in the 21st century, and coronaviruses appear to possess a unique ability to cross borders between species and infect a wide range of organisms. This is somewhat surprising as, except for the requirement of host cell receptors, cell–pathogen interactions are usually species-specific. Insights into these host–virus interactions will provide a deeper understanding of the process of SARS-CoV-2 infection and provide a means for the design and development of antiviral agents. In this study, we describe a complex analysis of SARS-CoV-2 infection using a genome-wide CRISPR-Cas9 knock-out system in HeLa cells overexpressing entry receptor angiotensin-converting enzyme 2 (ACE2). This platform allows for the identification of factors required for viral replication. This study was designed to include a high number of replicates (48 replicates; 16 biological repeats with 3 technical replicates each) to prevent data instability, remove sources of bias, and allow multifactorial bioinformatic analyses in order to study the resulting interaction network. The results obtained provide an interesting insight into the replication mechanisms of SARS-CoV-2.

Optimising sampling and analysis protocols in environmental DNA studies

Ecological surveys risk incurring false negative and false positive detections of the target species. With indirect survey methods, such as environmental DNA, such error can occur at two stages: sample collection and laboratory analysis. Here we analyse a large qPCR based eDNA data set using two occupancy models, one of which accounts for false positive error by Griffin et al. (J R Stat Soc Ser C Appl Stat 69: 377–392, 2020), and a second that assumes no false positive error by Stratton et al. (Methods Ecol Evol 11: 1113–1120, 2020). Additionally, we apply the Griffin et al. (2020) model to simulated data to determine optimal levels of replication at both sampling stages. The Stratton et al. (2020) model, which assumes no false positive results, consistently overestimated both overall and individual site occupancy compared to both the Griffin et al. (2020) model and to previous estimates of pond occupancy for the target species. The inclusion of replication at both stages of eDNA analysis (sample collection and in the laboratory) reduces both bias and credible interval width in estimates of both occupancy and detectability. Even the collection of > 1 sample from a site can improve parameter estimates more than having a high number of replicates only within the laboratory analysis.

Benchmarking Quantitative Performance in Label-Free Proteomics.

Previous benchmarking studies have demonstrated the importance of instrument acquisition methodology and statistical analysis on quantitative performance in label-free proteomics. However, the effects of these parameters in combination with replicate number and false discovery rate (FDR) corrections are not known. Using a benchmarking standard, we systematically evaluated the combined impact of acquisition methodology, replicate number, statistical approach, and FDR corrections. These analyses reveal a complex interaction between these parameters that greatly impacts the quantitative fidelity of protein- and peptide-level quantification. At a high replicate number (n = 8), both data-dependent acquisition (DDA) and data-independent acquisition (DIA) methodologies yield accurate protein quantification across statistical approaches. However, at a low replicate number (n = 4), only DIA in combination with linear models for microarrays (LIMMA) and reproducibility-optimized test statistic (ROTS) produced a high level of quantitative fidelity. Quantitative accuracy at low replicates is also greatly impacted by FDR corrections, with Benjamini–Hochberg and Storey corrections yielding variable true positive rates for DDA workflows. For peptide quantification, replicate number and acquisition methodology are even more critical. A higher number of replicates in combination with DIA and LIMMA produce high quantitative fidelity, while DDA performs poorly regardless of replicate number or statistical approach. These results underscore the importance of pairing instrument acquisition methodology with the appropriate replicate number and statistical approach for optimal quantification performance.

Comparison of Droplet Digital PCR versus qPCR Measurements on the International Scale for the Molecular Monitoring of Chronic Myeloid Leukemia Patients.

BCR-ABL1/ABL1 p210 measurement by quantitative polymerase chain reaction (qPCR) is used worldwide to monitor the molecular response in chronic myeloid leukemia (CML) patients. Droplet digital polymerase chain reaction (ddPCR) seems to show a greater sensitivity than qPCR, probably due to the high number of replicates analyzed in ddPCR for the comparison. Additionally, in a recently published comparison, ddPCR measurements were not adequately transformed into International Scale (IS). We have analyzed 50 CML patients and ten non-CML donors in parallel by qPCR and ddPCR. To the best of our knowledge, this is the first study comparing both techniques under similar conditions, with BCR-ABL1/ABL1 measurements performed via both techniques transformed into IS. Qualitative and quantitative comparisons showed excellent results. The qualitative correlation showed a Kappa index of 0.94 (95% confidence interval [CI] 0.90-0.98) (P < 0.001). In the quantitative comparison, the absolute intra-class correlation coefficient was 0.868 (95% CI 0.734-0.937; P < 0.001), and Lin's concordance correlation coefficient was 0.863. The Passing-Bablock test indicated a slight proportional difference between qPCR and ddPCR. A quantitative and qualitative subanalysis including 40 patients with a molecular response of 3.0 or deeper showed similar results in every test. In addition, the proportional difference in the Passing-Bablock test disappeared. There were no differences in the sensitivity for BCR-ABL1 detection between qPCR and ddPCR (McNemar test, P = 0.5). In conclusion, our results show very good quantitative and qualitative correlations between BCR-ABL1/ABL1 p210 results obtained by qPCR and by ddPCR and confirm previous scarce data regarding the lack of an increase in sensitivity of ddPCR over qPCR in this setting.

Evaluation of CRM homogeneity in cases of insufficient method repeatability: Comparison of Bayesian analysis with substitutes for ANOVA based estimates

Insufficient method repeatability is a problem characterising the evaluation of certified reference materials (CRMs). In investigating the homogeneity studies of 216 certified parameters from 36 CRMs released by the European Commission’s Joint Research Centre (JRC) over the last four years, it was found that in 1/3 of the cases, the method repeatability (sr) was too high to calculate the standard deviation between units (sbb) by classical analysis of variance (ANOVA). It was also found that the application of the repeatability requirement stated in the ISO Guide 35:2017 is not feasible since it would require unrealistically low repeatability standard deviations or an impossibly high number of replicates per unit.Evaluation of the uncertainty of homogeneity (ubb) as evaluated by ANOVA using both the maximum of sbb and 0, the maximum of sbb and u∗bb, the uncertainty hidden by method repeatability, the maximum of sbb and sbb/√n and Bayesian analysis, using both informative and diffuse priors, as well as the standard deviation of the unit means, were compared using simulated homogeneity studies with repeatabilities of 1–8% and sbb between 0.2 and 2.8%. It was found that using the maximum of sbb and sbb/√n as an estimate of ubb guards against severe underestimation but usually results in a severe overestimation of the between-unit variation. Using the maximum of (sbb, 0) shows the least average bias but results in a severe underestimation of ubb in a high fraction of cases. Using the maximum of (sbb, u∗bb) limits, but does not completely eliminate cases of a severe underestimation. Also, it leads to average results biased towards high values. For the range of sbb and sr investigated, Bayesian analysis performed worse than max (sbb, u∗bb) in limiting severe underestimation of ubb, but limited the average bias towards high results.A risk-based approach to cases of insufficient method repeatability is proposed where, after evaluating the other contributions to the uncertainty of certified values, the effect of severe over- and underestimation of ubb is evaluated, and an appropriate approach is chosen based on this analysis.

Can time‐to‐detection models with fewer survey replicates provide a robust alternative to traditional site‐occupancy models?

Abstract Traditional occupancy models that record detection/non‐detection (DND) of a species typically rely on either spatial or temporal survey replication to estimate model parameters. Recording the time until a species is first encountered after starting a survey is often possible with little extra effort and such time‐to‐detection (TTD) surveys may be more efficient than pure DND surveys. Using continuous time data, TTD occupancy models can in theory estimate occupancy and detection parameters using a single TTD survey. However, the robustness and general applicability of TTD models has not been widely addressed and their effectiveness in different study systems remains unknown. We use simulations and bird data of 63 species from a field study in the Karoo region of South Africa to explicitly compare estimates of occupancy, detection and species richness between DND and TTD models under various levels of survey replication and for species with different occupancy and detection characteristics. Simulations revealed that for inconspicuous species single survey TTD models can perform better or equally as well as DND models with a higher number of replicates. This effect was attenuated in widespread species. The benefits of TTD models were more pronounced at low survey replicates and performance of the two methods converged quickly as the number of survey replicates increased. However, results from the field data showed that a single TTD survey was not adequate to reliably estimate occupancy, detection and species richness; especially in rare and inconspicuous species. Increasing the number of TTD surveys to two replicates improved the models substantially. Our results demonstrate that the general utility of TTD surveys depends on the characteristics of the species considered in the study. A single TTD survey may be sufficient in some study designs but is unlikely to be sufficient in most multi‐species field scenarios where communities are made up of species that have a wide range of detection and occupancy probabilities. TTD surveys do provide benefits, however, in that data can be used to construct detection curves which can be used to guide survey effort in the design of future studies.

Optimal number of replications and test locations for soybean yield trials in Brazil

An optimal number of test locations and replications in yield trials allows improvements in the efficiency of a breeding program and selection reliability. The objectives of this study were to verify the optimal number of test locations and replications per test location in edaphoclimatic regions (ECR) and macroregions (MRs) of soybean adaptation in Brazil. Grain yield data from 184 soybean trials in 57 locations was evaluated in crop seasons 2012–2013 to 2015–2016. The number of replications currently used (3) is sufficient to achieve selection reliability and reduce costs in all MRs. However, the optimal number of replications needs to be determined for each location. Locations that require a high number of replicates to achieve H = 0.75 must be removed and/or replaced to improve selective accuracy. The optimal mean number of test locations in macroregions MR1 and MR2 is seven locations per ECR, and in MR3 and MR4, it is five locations per ECR. Thus, analyses of the optimal number of locations and replications may be applied to other regions to improve the yield trial efficiency of soybean cultivars.

Can we water crops with our phones? Smartphone technology application to infrared thermography for use in irrigation management

Infrared thermography has been used to assess plant transpiration and infer stress levels in different agricultural production systems. The development of low cost infrared cameras adapted to smart phones provides an opportunity to develop applications that would allow growers to monitor crop water status. We explored the capabilities of this system by assessing the response of crop water stress index (CWSI) to treatments differing in irrigation frequency. Soya bean plants were grown in pots in a glasshouse and different irrigation treatments were applied for two weeks. CWSI, stomatal conductance (gs) and biomass growth were compared in fully irrigated (FI), deficit irrigation (50% ET) applied either at high (HFDI) and low (LFDI) frequency. Statistical differences in CWSI between deficit irrigation and FI treatments were observed when CWSI'0.5. CWSI and gs followed very similar patterns in all treatments, but the higher number of replicates that the thermal camera could measure in a given time and its low variability compared to the porometer increased the capacity to detect differences between treatments. As gs decreased at the end of the experiment in FI plants, probably because of restricted soil volume, differences in CWSI between well-watered and stressed plants diminished, suggesting the need to maintain well-watered plants grown under optimal conditions as a reference baseline. Within the deficit irrigation treatments, CWSI decreased and gs, increased when irrigation was more frequent, but dry biomass and water use efficiency (biomass/irrigation volume) did not change, and were lower and higher than FI plants respectively. These results demonstrate that the low cost thermal camera is suitable to rapidly assess gs, but highlight the issues associated with irrigation scheduling based on this physiological response.

Abstract 41: A novel high-throughput microfluidic drug screening platform using pancreatic ductal adenocarcinoma derived organoids

Abstract Pancreatic cancer is one of the deadliest tumors due to the limited treatment options and late diagnosis. Here, we describe a novel high throughput drug screening platform combining a microfluidic based 3D-culture plate, and the recently described pancreatic ductal adenocarcinoma (PDAC) derived organoids. The microfluidic plate is a high throughput microfluidic 3D cell culture platform, supporting physiologically relevant models with a minimal requirement of cell material and enabling a wide range of flow and co-culture options (e.g. with blood vessels). Organoids were derived from human PDAC xenografts and seeded in the microfluidic plate. The low amount of tissue material required (4000 cells per chip) and the high number of replicates on one plate (n=96 on a standard microtiter format plate) renders the microfluidic plate an efficient and cost-effective platform for drug screening and toxicity assays on complex, 3D models. Organoids were exposed to various chemotherapeutic drugs for 72 hours. The viability of the organoids before and after drug treatment is monitored with standard viability assays and subsequently used to generate dose response curves. In conclusion, we showed that the microfluidic plate can be used for high throughput drug screening assays and toxicity screening, and demonstrated its compatibility with human pancreatic PDAC derived organoids. Citation Format: Bart Kramer, Wijnand van Paassen, Luuk de Haan, Henriette Lanz, Jos Joore. A novel high-throughput microfluidic drug screening platform using pancreatic ductal adenocarcinoma derived organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 41.

Evidence for relative grain yield simulation by red color level of beneath-canopy soil at wheat booting phase: An unexpected observation using image processing

Digital cameras are increasingly utilized as a reliable and readily available remote sensing tool in the emerging technology of high throughput phenotyping and agronomic field assessments. In almost every image analysis of green canopies, image segmentation into the vegetation and non-vegetation parts using thresholding is a fundamental step. Therefore, only the vegetation parts of the high resolution images are considered for estimations and the data recorded in the remained pixels will be ignored. In the present study, an accidental observation is described, in which the red color level of the non-vegetation segments of the images taken at the wheat booting phase could simulate the relative pattern of final grain yield. An image archive of heterogeneous wheat canopies (i.e. cultivar mixtures), captured from experimental plots of a field study conducted at the School of Agriculture, Shiraz University, Iran, was analyzed. It was observed that the red color levels of the image background (BRL, mostly composed of soil pixels) were accurately simulating the final grain yields of the treatments, (i.e. very precise mimicry of relative grain yields –RGY– in monocultures, and exact determination of curve extrema and also the direction of fluctuations, in the case of mixtures). Compared with other colors and image-derived criteria evaluated, BRLs had the pattern most similar to the relative grain yields. Moreover, assessments showed the importance of using higher number of replicates in analyses (i.e. 6 vs 3 replications). This observation suggests the red color level of the image-background as a potential novel index for the prediction of wheat grain yield during the preanthesis period; and also the ability of the non-vegetation image segments to provide valuable data for crop remote sensing and image processing studies.

Fluidic resistance control enables high-throughput establishment of mixed-species biofilms.

Bacteria often live in communities of mixed species embedded in a self-produced extracellular matrix of polysaccharides, proteins and DNA, termed biofilms. The BioFlux microfluidic flow system is useful for studying biofilm formation in different media under flow. However, analyzing the architecture and maturation of biofilms under flow requires a proper seeding, which can prove difficult when working with bacteria of different sizes, motile bacteria or aiming for a high number of replicates. Here we developed an efficient protocol that exploits viscosity tuning and seeding indicator dyes to improve seeding and allow for high-throughput examination and visualization of consistent mono- and mixed-species biofilm developments under flow.

26 Season affects cryotolerance of in vitro-produced buffalo embryos

Buffaloes are tendentially short-day breeders, and seasonality is one of the main factors affecting the feasibility of ovum pickup and in vitro embryo production technology in this species. An improvement of oocyte developmental competence during decreasing daylight months was previously reported in Italian Mediterranean buffalo (Di Francesco et al. 2011 Anim. Reprod. Sci. 123, 48-53). The aim of this work was to evaluate whether season also affects embryo quality and cryotolerance. Abattoir-derived buffalo cumulus-oocyte complexes were collected during the breeding season, characterised by decreasing daylight length (n=349 over 6 replicates), and the non-breeding season, characterised by increasing daylight length (n=770 over 12 replicates). Buffalo cumulus-oocyte complexes were in vitro matured, fertilized, and cultured according to standard procedures (Di Francesco et al. 2011 Anim. Reprod. Sci. 123, 48-53). The embryos obtained by the end of culture (i.e. on Day 7 post-IVF) were scored for quality and developmental stage, and the percentages of total transferable embryos (tight morulae and blastocysts) were recorded. Embryos (n=107 and 110 in the breeding and non-breeding seasons, respectively) were vitrified by cryotop in 16.5% ethylene glycol, 16.5% dimethyl sulfoxide, and 0.5M sucrose (Boccia et al. 2013 Ital. J. Anim. Sci. 12, 492-496). Warming was carried out by plunging the cryotop strip into a 0.25M sucrose solution and transferring the embryos into 0.15M sucrose for 5min. Embryos were then washed and cultured in SOF for 24h to evaluate post-culture viability. The resistance to cryopreservation was evaluated by assessing the survival rate, on the basis of morphological criteria, and development rate (i.e. the percentage of embryos that resumed their development and reached a more advanced developmental stage) after 24h post-warming culture. Data were analysed by Student’s t-test. Both cleavage (82.8±4.3v. 73.1±1.7 in the breeding and non-breeding seasons, respectively; P&amp;lt;0.05) and blastocyst (32.9±3.5v. 18.3±1.7 in the breeding and non-breeding seasons, respectively; P&amp;lt;0.01) rates increased during the breeding season, confirming previous observations. Due to the different efficiency, a higher number of replicates was required during the non-breeding season to obtain an equal number of embryos. In addition, a seasonal effect was recorded on embryo quality, indicated by poorer cryotolerance of in vitro-produced buffalo embryos during the non-breeding season. Indeed, both survival (94.6±2.7% and 74.0±5.5% in the breeding and non-breeding seasons, respectively; P&amp;lt;0.01) and development (67.3±7.6% and 40.0±7.2% in the breeding and non-breeding seasons, respectively; P&amp;lt;0.01) rates of vitrified blastocysts decreased after 24h post-warming culture in the non-breeding season. These findings suggest that the reduced developmental competence of buffalo oocytes during the non-breeding season may also lead to lower blastocyst quality. This is in contrast to the evidence in cattle that embryo quality is mainly determined by culture conditions, whereas blastocyst production depends on oocyte quality.

Experimental planning for the evaluation of phenotipic descriptors in banana

Abstract This work aimed to subsidize experimental planning for the evaluation of phenotypic characters in banana. The experiment consisted of a uniformity trial with Tropical cultivar spaced of 3 m x 2 m, in a useful area with nine rows of 40 plants. Vegetative and yield aspects were evaluated in two production cycles. Plants and basic units (UB) were combined to form various plot sizes, from which the variation coefficient and the soil heterogeneity index were estimated. To define the experimental design, the Hatheway method was used. Variability, resulting from the soil anisotropy and other factors such as desuckering cultural practice increases between mother plant and daughter plant cycles, with effects on experimental design. The variation coefficient and number of replicates are the factors that most influenced the experimental design. For the same precision level required, the combination that maximizes efficient in the use of experimental area can be adopted, that is, smaller plot size and higher number of replicates or larger plot size and fewer replicates. Estimates of plot size and number of replicates are subsides for the design of experiments for the evaluation of phenotypic descriptors in banana.

The double-stage delay-multiply-and-sum image reconstruction method improves imaging quality in a LED-based photoacoustic array scanner

Light-emitting diode-based photoacoustic imaging is more compact and affordable than laser-based systems, but it has low power and hence a high number of replicates. Here, we describe double-stage delay-multiply-and-sum (DS-DMAS) to improve image quality collected on a LED-based scanner. DS-DMAS was evaluated experimentally using point targets (in different laterals and depths) as well as a hair and a rabbit eye. This algorithm can compensate for the low SNR of LED-based systems and offer better lateral resolution of about 60%, 25%, higher contrast ratio of about 97%, 34%, and better full-width-half-maximum of about 60%, 25%, versus delay-and-sum) and delay-multiply-and-sum, respectively. More importantly, DS-DMAS offers this using a smaller number of frames (only 2% of all the frames). These results indicate that DS-DMAS might be a valuable tool in the translation of LED-based and other low power PAI systems.

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing.

In recent decades, vector-borne diseases have re-emerged and expanded at alarming rates, causing considerable morbidity and mortality worldwide. Effective and widely available vaccines are lacking for a majority of these diseases, necessitating the development of novel disease mitigation strategies. To this end, a promising avenue of disease control involves targeting the vector microbiome, the community of microbes inhabiting the vector. The vector microbiome plays a pivotal role in pathogen dynamics, and manipulations of the microbiome have led to reduced vector abundance or pathogen transmission for a handful of vector-borne diseases. However, translating these findings into disease control applications requires a thorough understanding of vector microbial ecology, historically limited by insufficient technology in this field. The advent of next-generation sequencing approaches has enabled rapid, highly parallel sequencing of diverse microbial communities. Targeting the highly-conserved 16S rRNA gene has facilitated characterizations of microbes present within vectors under varying ecological and experimental conditions. This technique involves amplification of the 16S rRNA gene, sample barcoding via PCR, loading samples onto a flow cell for sequencing, and bioinformatics approaches to match sequence data with phylogenetic information. Species or genus-level identification for a high number of replicates can typically be achieved through this approach, thus circumventing challenges of low detection, resolution, and output from traditional culturing, microscopy, or histological staining techniques. Therefore, this method is well-suited for characterizing vector microbes under diverse conditions but cannot currently provide information on microbial function, location within the vector, or response to antibiotic treatment. Overall, 16S next-generation sequencing is a powerful technique for better understanding the identity and role of vector microbes in disease dynamics.

PO-421 A novel high-throughput drug screening platform using pancreatic ductal adenocarcinoma derived organoids in the organoplate®

Introduction Pancreatic cancer is one of the deadliest tumours due to the limited treatment options and late diagnosis. Here, we describe a novel high throughput drug screening platform combining the OrganoPlate, a microfluidic based 3D-culture plate, and the recently described Pancreatic Ductal AdenoCarcinoma (PDAC) derived organoids. Material and methods The OrganoPlate is a high throughput microfluidic 3D cell culture platform, supporting physiologically relevant models with a minimal requirement of cell material and enabling a wide range of flow and co-culture options (e.g. with blood vessels). Organoids were derived from human PDAC xenografts and seeded in the OrganoPlate. The low amount of tissue material required (4000 cells per chip) and the high number of replicates on one plate (n=96 on a standard microtiter format plate) renders the OrganoPlate an efficient and cost-effective platform for drug screening and toxicity assays on complex, 3D models. Results and discussions Organoids were exposed to various chemotherapeutic drugs for 72 hours. The viability of the organoids before and after drug treatment is monitored with standard viability assays and subsequently used to generate dose response curves. Conclusion In conclusion, we showed that the OrganoPlate can be used for high throughput drug screening assays and toxicity screening, and demonstrated its compatibility with human pancreatic PDAC derived organoids.

Optimal computing budget allocation to the differential evolution algorithm for large-scale portfolio optimization

Differential evolution (DE) is one of the popular techniques in large-scale portfolio optimization, which is noticed for its applications in the problems that are non-convex, non-continuous, non-differentiable, and so on. This technique suffers specific short-comings, for example, unstable convergence in the final solution, trapped in local optimum, and demand for high number of replications. Optimal Computing Budget Allocation (OCBA) technique gives an efficient way to reach the global optimum by optimally assigning computing resource among designs. The integration of DE and OCBA gives better performance than DE alone in terms of convergence rate and the attained global optimum. The ordering of the integration also plays a vital role, that is, the strategy of first applying DE before OCBA outperforms the reversely ordered one. Both integration strategies are essentially the improved DE algorithms for large-scale portfolio optimization. In addition to numerical tests, empirical analysis of 100 stocks in S&P500 over a 10-year period confirms the conclusions.

Study of Electrochemical Reduction of CO2 for Future Use in Secondary Microbial Electrochemical Technologies.

The fluctuation and decentralization of renewable energy have triggered the search for respective energy storage and utilization. At the same time, a sustainable bioeconomy calls for the exploitation of CO2 as feedstock. Secondary microbial electrochemical technologies (METs) allow both challenges to be tackled because the electrochemical reduction of CO2 can be coupled with microbial synthesis. Because this combination creates special challenges, the electrochemical reduction of CO2 was investigated under conditions allowing microbial conversions, that is, for their future use in secondary METs. A reproducible electrodeposition procedure of In on a graphite backbone allowed a systematic study of formate production from CO2 with a high number of replicates. Coulomb efficiencies and formate production rates of up to 64.6±6.8 % and 0.013±0.002 mmolformate h-1 cm-2 , respectively, were achieved. Electrode redeposition, reusability, and long-term performance were investigated. Furthermore, the effect of components used in microbial media, that is, yeast extract, trace elements, and phosphate salts, on the electrode performance was addressed. The results demonstrate that the integration of electrochemical reduction of CO2 in secondary METs can become technologically relevant.