Pooling Procedure Research Articles

Comparison of RT-PCR cycle threshold values between individual and pooled SARS-CoV-2 infected nasopharyngeal swab specimens.

The molecular reverse transcription-polymerase chain reaction (RT-PCR) testing of respiratory tract swabs has become mandatory to confirm the diagnosis of coronavirus disease 2019 (COVID-19). However, RT-PCR tests are expensive, require standardized equipment, and relatively long testing times, and the sample pooling method has been introduced to solve this issue. The aim of this study was to compare the cycle threshold (Ct) values of the individual sample and pooled sample methods to assess how accurate the pooling method was. Repeat RT-PCR examinations were initially performed to confirm the Ct values for each sample before running the pooled test procedure. Sample extraction and amplification were performed in both assays to detect ORF1ab, N, and E genes with a cut-off point value of Ct <38. Overall, there was no difference in Ct values between individual sample and pooled sample groups at all concentrations (p=0.259) and for all pooled sizes. Only pooled size of five could detect the Ct value in the pooled samples for all concentration samples, including low-concentration sample (Ct values 36 to 38). This study highlighted that pooled RT-PCR testing strategy did not reduce the quality of individually measured RT-PCR Ct values. A pool size of five could provide a practical technique to expand the screening capacity of RT-PCR.

Screening for emerging chemical risks in the food chain (SCREENER)

Abstract In the European Union, all chemical substances that are manufactured, imported or used in tonnages equal or higher than one tonne per year must be registered under the REACH regulation. This regulatory framework requires the collection and dissemination of detailed information on the properties, uses, and potential health and environmental impacts of chemicals. However, some of these chemicals may pose emerging risks in the food chain, necessitating the development of approaches to identify and assess such risks. The SCREENER project addressed this critical issue by analysing food items for the presence of chemicals that may pose unrecognised hazards. Building on the findings from the previous REACH 1 and REACH 2 projects, which identified a suspect list of 212 chemicals, qualitative multi‐residue high‐resolution mass spectrometry (HRMS) methods have been developed. Diverse food items such as wheat flour, kale, carrots, potatoes, peas, strawberries, oranges, meat, hen's eggs, and trout were pooled from 3 samples each, while cow's milk, and other fish types (salmon and herring) were pooled from 4 samples each to form a single sample. This pooling procedure resulted in 194 analytical samples, which were screened for the presence of the chemicals in the suspect list. Additionally, non‐target analysis (NTA) was performed on the same samples, focusing on detecting halogenated compounds. The aim was to detect substances potentially introduced into the food chain unintentionally through industrial and anthropogenic activities, which were previously unrecognised in the food chain. In the final stage of the project, 15 chemicals were further prioritized for identification and quantitative analysis. Quantitative methods were developed and then applied to the same 194 samples, allowing for the identification and quantification of those chemicals. Subsequently, hazard characterization, exposure assessment, and risk characterisation were conducted. A preliminary characterization of the potential risk posed by the chemicals found in the samples during quantitative confirmatory analysis indicated no risk to human health in all but three cases where additional analysis on occurrence and detailed evaluation of the hazard can be considered as a possible follow‐up action in the future.

A new efficient sample pooling procedure for qualitative screening analysis. Application to the detection of salmonella spp and nut allergen by PCR

Foodborne pathogens and allergens are a major concern for public health that determines food safety policy, and their screening could be improved using pooled samples.The purpose of this paper is to propose a cost-effective and accurate pooling strategy for the unambiguous identification of foodborne pathogens and allergens, enabling laboratories to redouble testing capacity while saving time and making optimal use of resources.Although a variety of pooling algorithms have been used in different fields, the strategy suggested here is a logical analysis of sample pooling aimed at qualitative analytical screening problems. It involves, on the one hand, a design matrix to make the pooled samples, which is a supersaturated-based design, particularly, a half-fraction of a Plackett-Burman. On the other hand, a logical (non-algebraic) modeling of the problem, as well as a logical procedure for the identification of the original positive samples, is included.Regarding the efficiency of the proposal, it is higher than that of other pooling algorithms, with an expected number of tests per individual sample ranging between 0.10, for a prevalence below 1%, and 0.59, for a prevalence above 10%. In terms of accuracy, the pooling sensitivity reaches 0.9697 for a sensitivity of the analytical test about 0.99, while pooling specificity ranges from 0.9872 to 0.9999, provided that the sensitivity and specificity of the analytical test are equal to or greater than 0.90.This pooling strategy has been applied to the detection of salmonella spp and nut allergen with complete identification of the contaminated samples. Furthermore, based on the EU reported food samples contaminated with salmonella, a comprehensive comparison between individual sampling and the applied pooling strategy has been conducted. For the specific case of salmonella, detailed calculations have been made on the expected efficiency gains induced by this pooling methodology for different types of food samples monitored in the EU.

Comparing clinical outcomes of peroral endoscopic myotomy for achalasia between Eastern and Western countries: a systematic review and meta-analysis.

Peroral endoscopic myotomy (POEM) has revolutionized the therapeutic strategy for achalasia with promising results. We conducted this meta-analysis to compare clinical outcomes between Eastern and Western countries. A comprehensive literature search was conducted in PubMed, EMBASE, Web of Science and Cochrane Library databases to query for studies that assessed the efficacy of POEM for achalasia. All articles published from inception to December 31, 2021 were included. The primary outcome was the pooled clinical success rate. The secondary outcomes included the pooled technical success rate, incidence of adverse events, procedure time and hospital stay. Eighteen Eastern studies involving 5962 patients and 11 Western studies involving 1651 patients were included. The pooled clinical success rate and technical success rate for POEM was equal in the Eastern studies compared to Western studies. The pooled incidence of procedure adverse events for POEM was a little lower in the Eastern studies compared to Western studies (6.6% vs. 8.7%). Similarly, the incidence of reflux-related adverse events was lower in Eastern studies than that in Western studies. The pooled procedure time of POEM was shorter in Eastern studies compared to Western studies (61minutes vs. 80minutes), while the length of hospital stay was longer in Eastern studies compared to Western studies (5.8days vs. 2.4days). Overall, Eastern countries have the similar POEM outcomes compared to Western countries. However, Eastern countries still need to do more to reduce the length of hospital stay.

Locality Preserving Property Constrained Contrastive Learning for Object Classification in SAR Imagery

Robust unsupervised feature learning is a critical yet tough task for synthetic aperture radar (SAR) automatic target recognition (ATR) with limited labeled data. The developing contrastive self-supervised learning (CSL) method, which learns informative representations by solving an instance discrimination task, provides a novel method for learning discriminative features from unlabeled SAR images. However, the instance-level contrastive loss can magnify the differences between samples belonging to the same class in the latent feature space. Therefore, CSL can dispel these targets from the same class and affect the downstream classification tasks. In order to address this problem, this paper proposes a novel framework called locality preserving property constrained contrastive learning (LPPCL), which not only learns informative representations of data but also preserves the local similarity property in the latent feature space. In LPPCL, the traditional InfoNCE loss of the CSL models is reformulated in a cross-entropy form where the local similarity of the original data is embedded as pseudo labels. Furthermore, the traditional two-branch CSL architecture is extended to a multi-branch structure, improving the robustness of models trained with limited batch sizes and samples. Finally, the self-attentive pooling module is used to replace the global average pooling layer that is commonly used in most of the standard encoders, which provides an adaptive method for retaining information that benefits downstream tasks during the pooling procedure and significantly improves the performance of the model. Validation and ablation experiments using MSTAR datasets found that the proposed framework outperformed the classic CSL method and achieved state-of-the-art (SOTA) results.

Neoplasia detection via colonoscopic surveillance among young patients with MSH6 and PMS2-associated Lynch syndrome.

10516 Background: Lynch syndrome (LS) is the most common colorectal cancer (CRC) predisposition syndrome. While patients (pts) with MLH1/ MSH2-associated LS are recommended to start colonoscopy between age 20-25, recent guidelines recommend delaying initiation in pts with MSH6/ PMS2-associated LS to age 30-35. However, data on findings from colonic surveillance in young MSH6/ PMS2-LS pts are limited. Methods: We performed a retrospective review of a multi-institutional cohort of pts with MSH6/ PMS2-associated LS who underwent any colonic surveillance prior to age 50, and assessed corresponding pathology results. Neoplastic lesions were defined as a CRC, adenomas, or non-hyperplastic serrated lesions. Clinicopathologic variables were reported with summary statistics and compared using non-parametric tests at the patient level and among pooled procedures. Results: We identified 285 pts [161(56%) MSH6; 124(44%) PMS2] with history of colonic surveillance prior to age 50. 190 (67%) pts were female, with similar sex distribution among the MSH6 and PMS2 groups. 107 (38%) pts had personal history (hx) of any cancer, 67 (42%) MSH6 and 40 (32%) PMS2, including 58 (20%) with CRC [35(22%) MSH6; 23 (19%) PMS2]. Median age at CRC diagnosis (dx) was 39 and did not differ between groups (41 MSH6 vs. 37 PMS2, p = 0.47) with 16 (5.6%) pts dx prior to age 35. 157 (57%) pts had a family hx of CRC, and there was no difference in the rate of CRC between pts with or without family hx of CRC [50%(n = 25) vs 60%(n = 31), p = 0.33]. Pts underwent a median of 2 colonic surveillance procedures (range 1-12) with 824 total procedures, 806 (98%) colonoscopies and 18 (2%) sigmoidoscopies, with 691 (85%) occurring at an academic/tertiary center. Among the 824 pooled procedures, there were 194 (24%) procedures with neoplastic lesions identified, including 19 (2.3%) with advanced adenomas or advanced serrated lesions and 34 (4.1%) with CRC. Among 247 procedures completed at age &lt; 35, 43 (18%) detected neoplastic lesions, including 4 (1.6%) with advanced adenomas or advanced serrated lesions and 9 (3.6%) with CRCs. Notably, in 123 procedures performed prior to LS diagnosis, 43 (35%) had a neoplastic finding with 28 (23%) showing CRC. These findings did not differ between the MSH6 and PMS2 groups. Conclusions: Among this large, multi-institutional cohort of pts with MSH6/ PMS2-associated LS with history of colonic surveillance performed prior to age 50, colonic neoplasia was found at similar rates in both MSH6 and PMS2-associated LS. 20% of overall pts had CRC, with 48% presenting prior to LS dx. In surveillance procedures performed &lt; age 35, the upper threshold of initiation of colonic surveillance as per NCCN, 18% found a neoplastic finding with 3.6% finding CRC, highlighting the need to optimize the age of colonic surveillance initiation in MSH6/ PMS2-associated LS.

Preoperative lung ultrasound for confirming the double-lumen endotracheal tube position for one-lung ventilation: A systematic review and meta-analysis

ObjectivesInsertion of a double-lumen endotracheal tube (DLT) is the most commonly used method for one-lung ventilation (OLV). This meta-analysis was aimed at investigating the performance of lung ultrasound in assessing the DLT position in OLV. MethodsElectronic databases were searched for related trials from inception to October 2022. The primary outcome was the performance of ultrasound or clinical evaluation in confirming the correctness of the DLT position, using fiberoptic bronchoscopy or intraoperative direct visualization of lung collapse as the gold standard. The secondary outcome was the time required to confirm or adjust the DTL position. ResultsFive randomized controlled trials and three observational studies involving 771 patients were included in the meta-analysis. The pooled sensitivity and specificity of ultrasound were 0.93 (95% confidence interval [CI]: 0.79–0.98) and 0.61 (95% CI: 0.41–0.77), respectively, while those of clinical evaluation were 0.93 (95% CI: 0.73–0.99) and 0.35 (95% CI: 0.25–0.47), respectively. The pooled procedure duration was 122.27 s (95% CI: 20.85–223.69) with ultrasound and 112.03 s (95% CI: 95.30–128.76) with clinical evaluation. The area under the curve for discriminating the DLT position was 0.86 (95% CI: 0.82–0.88) for ultrasound and 0.52 (95% CI: 0.48–0.57) for clinical evaluation. ConclusionsCompared to clinical evaluation, ultrasound has a similar sensitivity but a better specificity for confirming the correctness of the DLT position. Ultrasound is an acceptable imaging tool for assessing DTL placement in OLV.

Accelerating the Laboratory Testing Capacity through Saliva Pooling Prior to Direct RT-qPCR for SARS-CoV-2 Detection.

The testing capacity of the laboratory is paramount for better control of the pandemic caused by SARS-CoV-2. The pooling method is promising to increase testing capacity, and the use of direct NAAT-based detection of SARS-CoV-2 on a non-invasive specimen such as saliva will ultimately accelerate the testing capacity. This study aims to validate the pooling-of-four method to quadruple the testing capacity using RNA-extraction-free saliva specimens. In addition, we intend to investigate the preferable stage of pooling, including pre- or post-heating. The compatibility of this approach was also tested on five commercial kits. Saliva specimens stored at -80 °C for several months were proven viable and were used for various tests in this study. Our findings revealed that pooling-of-four specimens had an overall agreement rate of 98.18% with their individual testing. Moreover, we proved that the pooling procedure could be conducted either pre- or post-heating, with no discordance and no significant difference in Ct values generated. When compared to other commercial detection kits, it demonstrated an overall agreement greater than 85%, which exhibits broad compatibility and ensures easy adaptability in clinical settings. This method has been proven reliable and increases the testing capacity up to fourfold.

Learning curve for esophageal peroral endoscopic myotomy: a systematic review and meta-analysis.

BACKGROUND AND STUDY AIMS : Peroral endoscopic myotomy (POEM) is a minimally invasive endoscopic procedure for the treatment of achalasia and certain spastic esophageal motility disorders, delivering excellent results in experienced hands. However, this complex and technically challenging procedure requires advanced endoscopic skills. The aim of this study was to conduct a systematic review and meta-analysis of current data to evaluate the learning curve for POEM in new adopters of this technique. METHODS : Electronic databases (PubMed, Embase, and Cochrane Library) from inception to November 2021 were searched for publications addressing the learning curve in POEM. Pooling was conducted by both fixed- and random-effects models. Secondary outcomes reviewed were clinical success defined by Eckardt score ≤ 3 when available and adverse events. RESULTS : Eight studies involving 1904 patients met the inclusion criteria. In the pooled analysis, new adopters of POEM attained proficiency at a mean of 24.67 procedures (95 %CI 23.93 to 25.41). Once proficiency was achieved, the pooled total procedure time plateaued at a mean of 85.38 minutes (95 %CI 81.48 to 89.28), the pooled mean procedure time per centimeter of myotomy was 6.25 minutes (95 %CI 5.69 to 6.82), and the pooled mean length of myotomy was 11.49 cm (95 %CI 10.90 to 12.08). CONCLUSIONS : Our analysis showed that new adopters of POEM with previous advanced endoscopy experience required about 25 procedures to attain proficiency. The average time for each procedure once proficiency was attained was about 85 minutes.

Use of compressed sensing to expedite high-throughput diagnostic testing for COVID-19 and beyond.

The rapid spread of SARS-CoV-2 has placed a significant burden on public health systems to provide swift and accurate diagnostic testing highlighting the critical need for innovative testing approaches for future pandemics. In this study, we present a novel sample pooling procedure based on compressed sensing theory to accurately identify virally infected patients at high prevalence rates utilizing an innovative viral RNA extraction process to minimize sample dilution. At prevalence rates ranging from 0-14.3%, the number of tests required to identify the infection status of all patients was reduced by 69.26% as compared to conventional testing in primary human SARS-CoV-2 nasopharyngeal swabs and a coronavirus model system. Our method provided quantification of individual sample viral load within a pool as well as a binary positive-negative result. Additionally, our modified pooling and RNA extraction process minimized sample dilution which remained constant as pool sizes increased. Compressed sensing can be adapted to a wide variety of diagnostic testing applications to increase throughput for routine laboratory testing as well as a means to increase testing capacity to combat future pandemics.

Inference following multiple imputation for generalized additive models: an investigation of the median p-value rule with applications to the Pulmonary Hypertension Association Registry and Colorado COVID-19 hospitalization data

BackgroundMissing data prove troublesome in data analysis; at best they reduce a study’s statistical power and at worst they induce bias in parameter estimates. Multiple imputation via chained equations is a popular technique for dealing with missing data. However, techniques for combining and pooling results from fitted generalized additive models (GAMs) after multiple imputation have not been well explored.MethodsWe simulated missing data under MCAR, MAR, and MNAR frameworks and utilized random forest and predictive mean matching imputation to investigate a variety of rules for combining GAMs after multiple imputation with binary and normally distributed outcomes. We compared multiple pooling procedures including the “D2” method, the Cauchy combination test, and the median p-value (MPV) rule. The MPV rule involves simply computing and reporting the median p-value across all imputations. Other ad hoc methods such as a mean p-value rule and a single imputation method are investigated. The viability of these methods in pooling results from B-splines is also examined for normal outcomes. An application of these various pooling techniques is then performed on two case studies, one which examines the effect of elevation on a six-minute walk distance (a normal outcome) for patients with pulmonary arterial hypertension, and the other which examines risk factors for intubation in hospitalized COVID-19 patients (a dichotomous outcome).ResultsIn comparison to the results from generalized additive models fit on full datasets, the median p-value rule performs as well as if not better than the other methods examined. In situations where the alternative hypothesis is true, the Cauchy combination test appears overpowered and alternative methods appear underpowered, while the median p-value rule yields results similar to those from analyses of complete data.ConclusionsFor pooling results after fitting GAMs to multiply imputed datasets, the median p-value is a simple yet useful approach which balances both power to detect important associations and control of Type I errors.

A sequential decoding procedure for pooled quantitative measure

Group testing (pooling) is a commonly used method while screening for rare diseases, especially for large-scale screening. In recent years there has been growing interest in direct analysis of quantitative measures to take advantage of full information. In this study, we develop a pooling procedure for identification of infected specimens and the measurement is quantitative. Exclusive simulations are conducted to investigate the performance of our procedure, “Qpool,” under a variety of scenarios. We also demonstrate its application in routine monitoring of Listeria monocytogenes.

Implementation of Sample Pooling Procedure Using a Rapid SARS-CoV-2 Diagnostic Real-Time PCR Test Performed Prior to Hospital Admission of People with Intellectual Disabilities.

Reliability, accuracy, and timeliness of diagnostic testing for SARS-CoV-2 infection have allowed adequate public health management of the disease, thus notably helping the timely mapping of viral spread within the community. Furthermore, the most vulnerable populations, such as people with intellectual disability and dementia, represent a high-risk group across multiple dimensions, including a higher prevalence of pre-existing conditions, lower health maintenance, and a propensity for rapid community spread. This led to an urgent need for reliable in-house rapid testing to be performed prior to hospital admission. In the present study, we describe a pooling procedure in which oropharyngeal and nasopharyngeal swabs for SARS-CoV-2 detection (performed prior to hospital admission using rapid RT-PCR assay) are pooled together at the time of sample collection. Sample pooling (groups of 2–4 samples per tube) allowed us to significantly reduce response times, consumables, and personnel costs while maintaining the same test sensitivity.

Inference and combination of missing data sets for the determination of [formula omitted] thermal decomposition rate uncertainty

The thermal decomposition of H2O2 is an important process in hydrocarbon combustion, playing a particularly crucial role in providing a source of radicals at high pressure where it controls the 3rd explosion limit in the H2-O2 system, and also as a branching reaction in intermediate-temperature hydrocarbon oxidation. As such, estimating the Arrhenius parameters of the rate expression for this reaction and their joint uncertainty is crucial for performing meaningful predictive combustion computations. Raw experimental data is typically unavailable for most reported investigations of elementary reaction rates. Rather, what is typically available are summary statistics on measured quantities. The unavoidable loss of information in the use of summary statistics versus raw data for inference makes the direct computation of the necessary joint uncertainty structure of the parameters in rate expressions difficult. To overcome this situation we perform a statistical inference procedure relying on maximum entropy principles and approximate Bayesian computation methods, and employing a two-level nested Markov Chain Monte Carlo algorithm, to approximate the joint posterior density on the H2O2 decomposition rate parameters for a selected case of laser absorption measurements in a shock tube study, subject to the constraints imposed by the rate constant statistics and available information reported for this experiment. This procedure constructs a set of hypothetical H2O2 concentration decay profiles consistent with the reported statistics in the form of mean values and error bars of rate constants at the given experiment temperatures, and the data fitting model originally employed by the experimentalists - essentially reconstructing the missing experimental data in an approximate form. These consistent hypothetical data sets are then used to determine the joint Arrhenius parameter density through straightforward Bayesian inference within a pooling procedure. We apply the method in the context of combining the information within a single experimental setting (i.e. across a temperature range for fixed pressure) for the purposes of estimating Arrhenius parameters, and then extend the analysis to incorporate information from additional experiments (at a different target pressure) resulting in a decrease in the uncertainty of the parameter estimates as this new information is employed. We also highlight the flexibility of operating in this data-centric framework with a view to generating unbiased consensus rate expressions up to the full mechanism level when using multiple sources of experimental results in different forms.

Pooling Samples as an Efficient Approach to Regular SARS-CoV-2 Testing in Residential Care Facilities

Background: Residents of care facilities for the elderly have accounted for a large proportion of all deaths due to COVID-19 globally. In Hong Kong, care home staff are required to undergo testing for SARS-CoV-2 every two weeks, regardless of symptoms. We aimed to optimize testing strategies in order to improve on existing screening programs.Methods: We estimated the reduced sensitivity of pooled PCR testing and used a decision analysis to determine the expected number of tests required. We assumed transmission occurred according to a time-varying Poisson process and that the time from infection to isolation followed a time-varying geometric distribution. We estimated the cumulative number of cases expected under syndromic surveillance, testing without pooling and pooled testing with pool sizes 2, 5 and 10 using an age of infection model.Findings: Assuming a prevalence of 0.02%, pooling 10 samples and conducting testing every two days instead of testing without pooling every 14 days could reduce the average size of an outbreak from between 2 and 14 cases (median 7 cases) to between 1 and 6 cases (median 2 cases). Pooling to allow for daily testing further reduced the average size of an outbreak from 4 cases to 1 case compared to weekly testing.Interpretation: Health authorities can improve on existing screening programs by employing pooled testing procedures and testing individuals more frequently to make the most use of available testing resources.Funding Information: This project was supported by a commissioned grant from the Health and Medical Research Fund, Food and Health Bureau, Government of the Hong Kong Special Administrative Region, and the Theme-based Research Scheme (Project No. T11-712/19-N) of the Research Grants Council of the Hong Kong SAR Government.Declaration of Interests: BJC consults for Roche, GSK, Moderna, AstraZeneca and Sanofi Pasteur and is supported by the AIR@innoHK program of the Innovation and Technology Commission of the Hong Kong SAR Government. The authors report no other potential conflicts of interest.Ethics Approval Statement: The study was approved by the Institutional Review Board of the University of Hong Kong.

Informed sequential pooling approach to detect SARS-CoV-2 infection.

The alarming spread of the pandemic coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus requires several measures to reduce the risk of contagion. Every successful strategy in controlling the SARS-CoV-2 infection depends on timely diagnosis, which should include testing of asymptomatic carriers. Consequently, increasing the throughput for clinical laboratories for the purposes of conducting large-scale diagnostic testing is urgently needed. Here we support the hypothesis that standard diagnostic protocol for SARS-CoV-2 virus could be conveniently applied to pooled samples obtained from different subjects. We suggest that a two-step sequential pooling procedure could identify positive subjects, ensuring at the same time significant benefits of cost and time. The simulation data presented herein were used to assess the efficiency, in terms of number of required tests, both for random assignment of the subjects to the pools and for situations in which epidemiological and clinical data are used to create "informed" pools. Different scenarios were simulated to measure the effect of different pool sizes and different values for virus frequency. Our results allow for a customization of the pooling strategy according to the specific characteristics of the cohort being tested.

Population Pharmacodynamic Modeling Using the Sigmoid Emax Model: Influence of Inter-individual Variability on the Steepness of the Concentration\u2013Effect Relationship. a Simulation Study

The relationship between the concentration of a drug and its pharmacological effect is often described by empirical mathematical models. We investigated the relationship between the steepness of the concentration–effect relationship and inter-individual variability (IIV) of the parameters of the sigmoid Emax model, using the similarity between the sigmoid Emax model and the cumulative log-normal distribution. In addition, it is investigated whether IIV in the model parameters can be estimated accurately by population modeling. Multiple data sets, consisting of 40 individuals with 4 binary observations in each individual, were simulated with varying values for the model parameters and their IIV. The data sets were analyzed using Excel Solver and NONMEM. An empirical equation (Eq. (11)) was derived describing the steepness of the population-predicted concentration–effect profile (γ*) as a function of γ and IIV in C50 and γ, and was validated for both binary and continuous data. The tested study design is not suited to estimate the IIV in C50 and γ with reasonable precision. Using a naive pooling procedure, the population estimates γ* are significantly lower than the value of γ used for simulation. The steepness of the population-predicted concentration–effect relationship (γ*) is less than that of the individuals (γ). Using γ*, the population-predicted drug effect represents the drug effect, for binary data the probability of drug effect, at a given concentration for an arbitrary individual.

A Rapid Identification and Counting Method for Particle Sensing Using Machine Learning

Cell identification and counting is important in all cell-related research steps including but not limited to culture, transformation, transfection, protein expression, etc. for cancer studies, disease diagnostics, bacterial detection, and so on. Although hemocytometry has been a traditional and conventional method of counting cells, it is tedious and laborious in general and often provides inaccurate counting. Flow cytometry is a far advanced and accurate method in cell counting but it requires an expensive and delicate instrument. Additionally, flow cytometry cannot be applicable to in situ cell counting. Image analysis is another method in cell counting, which has recently been developed but often suffers from inaccuracy for nonhomogeneous cell populations. In this work, we propose a rapid cell identification and counting method using image analysis and machine learning.This abstract presents preliminary results of a novel approach for counting spherical particles in a mixed population having spherically- and oddly-shaped particles using a machine learning technique based on convolutional neural networks (CNN). The proposed methodology utilizes segmentation of particles through scanning the input image in order to recognize and count spherically-shaped particles. Convolution layers process input images with respective filters to identify the shapes of the particles. Parameters of the filters (weights) are adjusted by the learning algorithm to extract different features of interest. Subsequently, a pooling procedure is applied for selecting identified features, in which the selected region is represented by the max or the average intensity of the scanned region in the input image. Both convolution and pooling procedures are applied multiple times in order to obtain better recognition and counting. Upon completing this learning process, features are fed into fully connected layers.Threshold segmentation and canny edge detection methods are applied in order to obtain a particle pattern of each selected shape to train the CNN. Particles having two different shapes, i.e., spherically- and oddly-shaped particles, are used for preliminary investigation. Data augmentation is used to create subsets of image data for training. After training the algorithm, an image containing many particles in different shapes was tested in order to assess the performance of learning process. Each particle was detected and segmented by a pixel size of 25 x 25.Preliminary results show that CNN has performed promising performance for identifying spherically shaped particles while massive images are currently being gathered and used for training to improve the accuracy. Additionally, initial findings indicate that machine learning could improve cell recognition and counting in biomedical research including cell population sensing. We intend to include a variety of particle shapes for generic cell identification and counting.

Agency problems and the value of advertising expenditures in an emerging market: role of product market competition

PurposeThis paper documents the impact of product market competition on the value of advertising expenditures.Design/methodology/approachThe authors use the data for non-financial firms from India and the pooled regression procedure to test their arguments during the period between 2009 and 2018.FindingsThe results show that advertising expenditures of firms operating in sectors with relatively high competition are more valuable than advertising expenditures of firms operating in sectors with relatively low competition. The results of the study are robust across various proxies of advertising expenditures and firm performance. Furthermore, the results also show that the positive impact of product market competition on the value of advertising expenditures is confined only to firms that already have lower agency problems.Originality/valueThe results of the study highlight the importance of product market competition on the value of advertising expenditure in the emerging market setting, where agency problems are supposed to be high.

Laparoscopy-assisted versus enteroscopy-assisted endoscopic retrograde cholangiopancreatography (ERCP) in Roux-en-Y gastric bypass: a meta-analysis.

Background and study aims Endoscopic retrograde cholangiopancreatography (ERCP) is technically challenging in patients with Roux-en-Y gastric bypass (RYGB) anatomy, which is increasing in frequency given the rise of obesity. Laparoscopy-assisted ERCP (LA-ERCP) and enteroscopy-assisted ERCP (EA-ERCP) are distinct approaches with their respective strengths and weaknesses. We conducted a meta-analysis comparing the procedural time, rates of success and adverse events of each method. Patients and methods A search of PubMed, EMBASE and the Cochrane library was performed from inception to October 2018 for studies reporting outcomes of LA or EA-ERCP in patients with RYGB anatomy. Studies using single, double, ‘short’ double-balloon or spiral enteroscopy were included in the EA-ERCP arm. Outcomes of interest included procedural time, papilla identification, papilla cannulation, therapeutic success and adverse events. Therapeutic success was defined as successful completion of the originally intended diagnostic or therapeutic indication for ERCP. Results A total of 3859 studies were initially identified using our search strategy, of which 26 studies met the inclusion criteria. The pooled rate of therapeutic success was significantly higher in LA-ERCP (97.9 %; 95 % CI: 96.7–98.7 %) with little heterogeneity (I 2 = 0.0 %) when compared to EA-ERCP (73.2 %; 95 % CI: 62.5–82.6 %) with significant heterogeneity (I 2 : 80.2 %). Conversely, the pooled rate of adverse events was significantly higher in LA-ERCP (19.0 %; 95 % CI: 12.6–26.4 %) when compared to EA-ERCP (6.5 %; 95% CI: 3.9–9.6 %). The pooled mean procedure time for LA-ERCP was 158.4 minutes (SD ± 20) which was also higher than the mean pooled procedure time for EA-ERCP at 100.5 minutes (SD ± 19.2). Conclusions LA-ERCP is significantly more effective than EA-ERCP in patients with RYGB but is associated with a higher rate of adverse events and longer procedural time.