Simplified algorithm for reliability sensitivity analysis of structures: A spreadsheet implementation.
Ontology highlight
ABSTRACT:
SUBMITTER: Shadab Far M
PROVIDER: S-EPMC6407918 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The need for synthetic route design arises frequently in discovery-oriented chemistry organizations. While traditionally finding solutions to this problem has been the domain of human experts, several computational approaches, aided by the algorithmic advances and the availability of large reaction collections, have recently been reported. Herein we present our own implementation of a retrosynthetic analysis method and demonstrate its capabilities in an attempt to identify synthetic routes for a collection of approved drugs. Our results indicate that the method, leveraging on reaction transformation rules learned from a large patent reaction dataset, can identify multiple theoretically feasible synthetic routes and, thus, support research chemist everyday efforts.
| S-EPMC6689887 | biostudies-other
Project description:Looking at the population's behavior by taking samples is quite uncertain due to its big and dynamic structure and unimaginable variability. All quantitative sampling approaches aim to draw a representative sample from the population so that the results of the studying samples can then be generalized back to the population. The probability of detecting a true effect of a study largely depends on the sample size and if taking small samples will give lowers statistical power, higher risk of missing a meaningful underlying difference. The probability of rejecting the null hypothesis i.e., finding significant difference using the sample largely depends upon the statistical power. There are a lot of online tools used for calculating the sample size, but none tell us about the availability of samples from single site in a fixed span. This study aims to provide an efficient calculation method for the availability of samples during a specific period of a research study which is an important question to be answered during the research study design. So, we have designed a spreadsheet-based sample availability calculator tool implemented in MS-Excel 2007.
| S-EPMC8814063 | biostudies-literature
Project description:Background & objectivesAlthough the World Health Organization recommends same day or rapid (< seven days) antiretroviral therapy (ART) initiation, delays in ART initiation remain common due to waiting for laboratory test results. This study employed a simplified clinical algorithm the HATI [HIV Awal (Early) Test & Treat Indonesia]-SAI (Simple ART Initiation) aimed to increase the proportion of ART uptake and decrease the time to ART initiation that can be used in various care settings.MethodsThis study compared the percentage of ART uptake and retention, viral load (VL) suppression and time to ART initiation between the observation and intervention phases among newly diagnosed HIV patients from key populations. As part of the intervention, the newly diagnosed patients underwent screening using a simple form [consisting of data on age, height and weight (for body mass index calculation), questions on the presence of symptoms of HIV stages 1 and 2, tuberculosis, history of diabetes, hypertension and kidney disease], to determine eligibility for immediate ART initiation. Those who met the pre-defined criteria immediately received a combination of tenofovir lamivudine and efavirenz for two weeks. The baseline laboratory examination due to this was moved up to two weeks post ART. Factors significantly associated with ART uptake were also determined and their odds ratios were measured using logistic regression analysis.ResultsA total of 2173 people newly diagnosed with HIV were recruited, with 1579 and 594 in the observation and intervention phases, respectively. In both phases, the majority were men who have sex with men, who were young (<30 yr old) and employed, with high levels of education. The intervention phase significantly increased the proportion of ART initiation [91%, 95% confidence interval (CI): 89-93% vs. 78%, 95% CI: 76-80%] but did not have any impact on the proportion of six months retention and VL suppression. The intervention also significantly decreased the time to ART initiation from median ± interquartile range: 9±20 days to 2±10 days.Interpretation & conclusionsThe findings of this study suggest that the HATI-SAI intervention increased the uptake and decreased the time for immediate ART initiation. The HATI-SAI provides a simple and safe clinical approach that can readily be adopted in different settings without a costly investment in technology.
| S-EPMC10278919 | biostudies-literature
Project description:BACKGROUND:Creating a case formulation is an important and basic skill in psychotherapy meant to guide treatment. A patient's interpersonal pattern is an essential part of a case formulation. Core Conflictual Relationship Theme (CCRT) is a well-known structured method to describe interpersonal patterns. The CCRT method is based on the assumption that humans display a central relationship theme, which is shown in most relationships as well as in the patient-therapist relation. The CCRT scoring is based on how the patient describes interactions with others, in therapy sessions or in a specific interview. These descriptions are transcribed. Raters then score the identified relational episodes by choosing elements from the clustered categories of Wishes, Response from Others and Response from Self. The method has shown high validity and reliability. Inter rater reliability is generally good: Cohen's kappa ranging from 0.55 to 0.70. To decide CCRT pattern from transcribed material is time consuming and labour intensive This study investigates a labour- and timesaving version of the method. METHODS:This study aimed to investigate rater agreement in a simplified method of scoring the CCRT, based directly on live semi-structured dynamic interviews without transcribing the material. Fifty-two patients referred for psychotherapy in a clinical trial, were scored for CCRT pattern. Based on information that came forth during the two-hour interview, raters scored the patients choosing elements from the clustered categories of Wishes, Response from Others and Response from Self. More than one category in each component could be chosen without ranking. Five raters compared two by two were investigated. Inter rater reliability was measured by Cohen's kappa. RESULTS:Mean kappa for Wishes, Response from Others and Response from Self was .33, .41 and .45 respectively. Mean kappa for CCRT in total was .41 among 5 raters. CONCLUSION:In this simplified method to score the CCRT based on oral dynamic interviews, fair to moderate IRR was obtained. TRIAL REGISTRATION:First Experimental Study of Transference-interpretations (FEST307/95). Registration number: ClinicalTrials.gov Identifier: NCT00423462.
| S-EPMC7137424 | biostudies-literature
Project description:MotivationSensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows.ResultsThe experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42×?compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations.ConclusionsOur work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines.Availability and implementationSource code: https://github.com/SBU-BMI/region-templates/ .Contactteodoro@unb.br.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC5409344 | biostudies-literature
Project description:Genetic classification helps to disclose molecular heterogeneity and therapeutic implications in diffuse large B-cell lymphoma (DLBCL). Using whole exome/genome sequencing, RNA-sequencing, and fluorescence in situ hybridization in 337 newly diagnosed DLBCL patients, we established a simplified 38-gene algorithm (termed 'LymphPlex') based on the information on mutations of 35 genes and rearrangements of three genes (BCL2, BCL6, and MYC), identifying seven distinct genetic subtypes: TP53Mut (TP53 mutations), MCD-like (MYD88, CD79B, PIM1, MPEG1, BTG1, TBL1XR1, PRDM1, IRF4 mutations), BN2-like (BCL6 fusion, NOTCH2, CD70, DTX1, BTG2, TNFAIP3, CCND3 mutations), N1-like (NOTCH1 mutations), EZB-like (BCL2 fusion, EZH2, TNFRSF14, KMT2D, B2M, FAS, CREBBP, ARID1A, EP300, CIITA, STAT6, GNA13 mutations, with or without MYC rearrangement), and ST2-like (SGK1, TET2, SOCS1, DDX3X, ZFP36L1, DUSP2, STAT3, IRF8 mutations). Extended validation of 1001 DLBCL patients revealed clinical relevance and biological signature of each genetic subtype. TP53Mut subtype showed poor prognosis, characterized by p53 signaling dysregulation, immune deficiency, and PI3K activation. MCD-like subtype was associated with poor prognosis, activated B-cell (ABC) origin, BCL2/MYC double-expression, and NF-κB activation. BN2-like subtype showed favorable outcome within ABC-DLBCL and featured with NF-κB activation. N1-like and EZB-like subtypes were predominated by ABC-DLBCL and germinal center B-cell (GCB)-DLBCL, respectively. EZB-like-MYC+ subtype was characterized by an immunosuppressive tumor microenvironment, while EZB-like-MYC- subtype by NOTCH activation. ST2-like subtype showed favorable outcome within GCB-DLBCL and featured with stromal-1 modulation. Genetic subtype-guided targeted agents achieved encouraging clinical response when combined with immunochemotherapy. Collectively, LymphPlex provided high efficacy and feasibility, representing a step forward to the mechanism-based targeted therapy in DLBCL.
| S-EPMC10083170 | biostudies-literature
Project description:BACKGROUND: A useful application of flow cytometry is the investigation of cell receptor-ligand interactions. However such analyses are often compromised due to problems interpreting changes in ligand binding where the receptor expression is not constant. Commonly, problems are encountered due to cell treatments resulting in altered receptor expression levels, or when cell lines expressing a transfected receptor with variable expression are being compared. To overcome this limitation we have developed a Microsoft Excel spreadsheet that aims to automatically and effectively simplify flow cytometric data and perform statistical tests in order to provide a clearer graphical representation of results. RESULTS: To demonstrate the use and advantages of this new spreadsheet method we have investigated the binding of the transmembrane adhesion receptor CD44 to its ligand hyaluronan. In the first example, phorbol ester treatment of cells results in both increased CD44 expression and increased hyaluronan binding. By applying the spreadsheet method we effectively demonstrate that this increased ligand binding results from receptor activation. In the second example we have compared AKR1 cells transfected either with wild type CD44 (WT CD44) or a mutant with a truncated cytoplasmic domain (CD44-T). These two populations do not have equivalent receptor expression levels but by using the spreadsheet method hyaluronan binding could be compared without the need to generate single cell clones or FACS sorting the cells for matching CD44 expression. By this method it was demonstrated that hyaluronan binding requires a threshold expression of CD44 and that this threshold is higher for CD44-T. However, at high CD44-T expression, binding was equivalent to WT CD44 indicating that the cytoplasmic domain has a role in presenting the receptor at the cell surface in a form required for efficient hyaluronan binding rather than modulating receptor activity. CONCLUSION: Using the attached spreadsheets and instructions, a simple post-acquisition method for analysing bivariate flow cytometry data is provided. This method constitutes a straightforward improvement over the standard graphical output of flow cytometric data and has the significant advantage that ligand binding can be compared between cell populations irrespective of receptor expression levels.
| S-EPMC395826 | biostudies-other
Project description:Protein-protein interactions are critical to protein function, but three-dimensional (3D) arrangements of interacting proteins have proven hard to predict, even given the identities and 3D structures of the interacting partners. Specifically, identifying the relevant pairwise interaction surfaces remains difficult, often relying on shape complementarity with molecular docking while accounting for molecular motions to optimize rigid 3D translations and rotations. However, such approaches can be computationally expensive, and faster, less accurate approximations may prove useful for large-scale prediction and assembly of 3D structures of multi-protein complexes. We asked if a reduced representation of protein geometry retains enough information about molecular properties to predict pairwise protein interaction interfaces that are tolerant of limited structural rearrangements. Here, we describe a reduced representation of 3D protein accessible surfaces on which molecular properties such as charge, hydrophobicity, and evolutionary rate can be easily mapped, implemented in the MorphProt package. Pairs of surfaces are compared to rapidly assess partner-specific potential surface complementarity. On two available benchmarks of 185 overall known protein complexes, we observe predictions comparable to other structure-based tools at correctly identifying protein interaction surfaces. Furthermore, we examined the effect of molecular motion through normal mode simulation on a benchmark receptor-ligand pair and observed no marked loss of predictive accuracy for distortions of up to 6 Å Cα-RMSD. Thus, a shape reduction of protein surfaces retains considerable information about surface complementarity, offers enhanced speed of comparison relative to more complex geometric representations, and exhibits tolerance to conformational changes.
| S-EPMC7855953 | biostudies-literature
Project description:Pediatric Index of Mortality 3 is a validated tool including 11 variables for the assessment of mortality risk in PICU patients. With the recent advances in explainable machine learning algorithms, we aimed to assess feasibility of application of these machine learning models to simplify the Pediatric Index of Mortality 3 scoring system in order to decrease time and labor required for data collection and entry for Pediatric Index of Mortality 3.DesignSingle-center, retrospective cohort study. Data from the Virtual Pediatric Systems for patients admitted to Cleveland Clinic Children`s PICU between January 2008 and December 2019 was obtained. Light Gradient Boosting Machine Regressor (a gradient boosting decision tree algorithm) was used for building the machine learning models. Variable importance was analyzed by SHapley Additive exPlanations. All of the 11 Pediatric Index of Mortality 3 variables were used as input variables in the machine learning models to predict Pediatric Index of Mortality 3 risk of mortality as the outcome variable. Mean absolute error, root mean squared error, and R-squared were calculated for each of the 11 machine learning models as model performance parameters.SettingQuaternary children's hospital.PatientsPICU patients.InterventionsNone.Measurements and main resultsFive-thousand sixty-eight patients were analyzed. The machine learning models were able to maintain similar predictive error until the number of input variables decreased to four. The machine learning model with five input variables (mechanical ventilation in the first hour of PICU admission, very-high-risk diagnosis, surgical recovery from a noncardiac procedure, low-risk diagnosis, and base excess) produced lowest mean root mean squared error of 1.49 (95% CI, 1.05-1.93) and highest R-squared of 0.73 (95% CI, 0.6-0.86) with mean absolute error of 0.43 (95% CI, 0.35-0.5) among all the 11 machine learning models.ConclusionsExplainable machine learning methods were feasible in simplifying the Pediatric Index of Mortality 3 scoring system with similar risk of mortality predictions compared to the original Pediatric Index of Mortality 3 model tested in a single-center dataset.
| S-EPMC8528230 | biostudies-literature
Project description:Network properties can be estimated using functional connectivity MRI (fcMRI). However, regional variation of the fMRI signal causes systematic biases in network estimates including correlation attenuation in regions of low measurement reliability. Here we computed the spatial distribution of fcMRI reliability using longitudinal fcMRI datasets and demonstrated how pre-estimated reliability maps can correct for correlation attenuation. As a test case of reliability-based attenuation correction we estimated properties of the default network, where reliability was significantly lower than average in the medial temporal lobe and higher in the posterior medial cortex, heterogeneity that impacts estimation of the network. Accounting for this bias using attenuation correction revealed that the medial temporal lobe's contribution to the default network is typically underestimated. To render this approach useful to a greater number of datasets, we demonstrate that test-retest reliability maps derived from repeated runs within a single scanning session can be used as a surrogate for multi-session reliability mapping. Using data segments with different scan lengths between 1 and 30 min, we found that test-retest reliability of connectivity estimates increases with scan length while the spatial distribution of reliability is relatively stable even at short scan lengths. Finally, analyses of tertiary data revealed that reliability distribution is influenced by age, neuropsychiatric status and scanner type, suggesting that reliability correction may be especially important when studying between-group differences. Collectively, these results illustrate that reliability-based attenuation correction is an easily implemented strategy that mitigates certain features of fMRI signal nonuniformity.
| S-EPMC4803495 | biostudies-literature