Biopharmaceutics Permeability Classification of Lorcaserin, a Selective 5-Hydroxytryptamine 2C Agonist: Method Suitability and Permeability Class Membership

2013 ◽  
Vol 10 (12) ◽  
pp. 4739-4745 ◽  
Author(s):  
Chuan Chen ◽  
Michael G. Ma ◽  
Cody L. Fullenwider ◽  
Weichao G. Chen ◽  
Abu J. M. Sadeque
Keyword(s):  
Class Membership ◽  
Method Suitability

scholarly journals Prediction of Solubility and Permeability Class Membership: Provisional BCS Classification of the World’s Top Oral Drugs

2009 ◽  
Vol 11 (4) ◽  
pp. 740-746 ◽  
Author(s):  
Arik Dahan ◽  
Jonathan M. Miller ◽  
Gordon L. Amidon
Keyword(s):  
Class Membership ◽  
Oral Drugs

Agreement on the Classification of Latent Class Membership Between Different Identification Constraint Approaches in the Mixture Rasch Model

Methodology ◽  
2018 ◽  
Vol 14 (2) ◽  
pp. 82-93
Author(s):  
Yi-Jhen Wu ◽  
Insu Paek
Keyword(s):  
Rasch Model ◽  
Latent Class ◽  
Model Identification ◽  
Real Data ◽  
Latent Classes ◽  
Class Membership ◽  
High Agreement ◽  
Common Scale ◽  
Constraint Approach

Abstract. When using the mixture Rasch model, the model identification constraints are either to set the equal means for all classes in the assumed normal ability distributions (equal ability mean constraint in short), or to set the sum of item difficulties to be zero for each class. In real data analysis, however, both constraints are not always sufficient to establish a common scale across latent classes unless some items are specified as anchor items in the estimation. If these two conventional constraint approaches recover the class membership as good as the anchor item constraint approach, the conventional constraint approaches may be considered useful for the purpose of class membership classification. This study investigated agreement on class membership between one conventional constraint (the equal ability mean) and the anchor item constraint approaches. Results showed high agreement between these two constraint approaches, indicating that the conventional constraint of the equal mean ability approach may be used to recover the latent class membership although item profiles are not correctly estimated across latent classes.

Effect of ECT on Responses to a Depression Questionnaire: Implications for Taxonomy

1970 ◽  
Vol 117 (541) ◽  
pp. 685-688 ◽  
Author(s):  
I. Pilowsky ◽  
M. D. McGrath
Keyword(s):  
Information Theory ◽  
Endogenous Depression ◽  
Original Study ◽  
Evidence Based ◽  
Class Membership ◽  
Class B ◽  
Statistical Approaches ◽  
The Many ◽  
Complex Question

The classification of depressive illnesses continues to be a problematic and controversial issue (Kendell, 1968; Hope, 1969). The many statistical approaches applied to this complex question since Hamilton's original study (1960) have been reviewed by Kendell (1968). More recently, Pilowsky, Levine and Boulton (1969) have offered evidence (based on the application of information theory taxonomy to patients' questionnaire responses) which supports the validity of regarding ‘endogenous' depression as a clinical entity. Following on this study, Pilowsky and Boulton (1970) have developed a decision rule for the identification of depressive class members and have shown that class membership is related to the response to electroconvulsive therapy; patients in the ‘endogenous' Class B group having a better clinical outcome.

scholarly journals Machine learning classification of Kuiper belt populations

2020 ◽  
Vol 497 (2) ◽  
pp. 1391-1403
Author(s):  
Rachel A Smullen ◽  
Kathryn Volk
Keyword(s):  
Machine Learning ◽  
Kuiper Belt ◽  
Giant Planet ◽  
Machine Learning Algorithms ◽  
Computational Time ◽  
Gradient Boosting ◽  
Class Membership ◽  
Machine Learning Classification ◽  
Tree Classifier

ABSTRACT In the outer Solar system, the Kuiper belt contains dynamical subpopulations sculpted by a combination of planet formation and migration and gravitational perturbations from the present-day giant planet configuration. The subdivision of observed Kuiper belt objects (KBOs) into different dynamical classes is based on their current orbital evolution in numerical integrations of their orbits. Here, we demonstrate that machine learning algorithms are a promising tool for reducing both the computational time and human effort required for this classification. Using a Gradient Boosting Classifier, a type of machine learning regression tree classifier trained on features derived from short numerical simulations, we sort observed KBOs into four broad, dynamically distinct populations – classical, resonant, detached, and scattering – with a >97 per cent accuracy for the testing set of 542 securely classified KBOs. Over 80 per cent of these objects have a >3σ probability of class membership, indicating that the machine learning method is classifying based on the fundamental dynamical features of each population. We also demonstrate how, by using computational savings over traditional methods, we can quickly derive a distribution of class membership by examining an ensemble of object clones drawn from the observational errors. We find two major reasons for misclassification: inherent ambiguity in the orbit of the object – for instance, an object that is on the edge of resonance – and a lack of representative examples in the training set. This work provides a promising avenue to explore for fast and accurate classification of the thousands of new KBOs expected to be found by surveys in the coming decade.

Biopharmaceutics Classification of Selected β-Blockers:  Solubility and Permeability Class Membership

2007 ◽  
Vol 4 (4) ◽  
pp. 608-614 ◽  
Author(s):  
Yongsheng Yang ◽  
Patrick J. Faustino ◽  
Donna A. Volpe ◽  
Christopher D. Ellison ◽  
Robbe C. Lyon ◽  
...  
Keyword(s):  
Class Membership ◽  
Β Blockers ◽  
Biopharmaceutics Classification

Note on the spectral classification of carbon stars in the photographic infrared region

1966 ◽  
Vol 24 ◽  
pp. 21-23
Author(s):  
Y. Fujita
Keyword(s):  
Infrared Region ◽  
Spectral Classification ◽  
Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

1970 ◽  
Vol 28 ◽  
pp. 220-221
Author(s):  
Gerald Fine ◽  
Azorides R. Morales
Keyword(s):  
Cardiac Myxoma ◽  
Osteogenic Sarcoma ◽  
Diagnostic Value ◽  
Soft Tissue Tumors ◽  
Amelanotic Melanoma ◽  
Growth Patterns ◽  
Light Microscopic Level ◽  
Mesenchymal Tumors ◽  
Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

Ultrastructure of mesotheliomas

1984 ◽  
Vol 42 ◽  
pp. 98-101
Author(s):  
Irving Dardick
Keyword(s):  
Electron Microscopy ◽  
Latent Period ◽  
Spindle Cell ◽  
Spindle Cell Sarcoma ◽  
Metastatic Adenocarcinoma ◽  
Cell Sarcoma ◽  
Cytological Features ◽  
Industrial Use ◽  
Degree Of Differentiation

With the extensive industrial use of asbestos in this century and the long latent period (20-50 years) between exposure and tumor presentation, the incidence of malignant mesothelioma is now increasing. Thus, surgical pathologists are more frequently faced with the dilemma of differentiating mesothelioma from metastatic adenocarcinoma and spindle-cell sarcoma involving serosal surfaces. Electron microscopy is amodality useful in clarifying this problem.In utilizing ultrastructural features in the diagnosis of mesothelioma, it is essential to appreciate that the classification of this tumor reflects a variety of morphologic forms of differing biologic behavior (Table 1). Furthermore, with the variable histology and degree of differentiation in mesotheliomas it might be expected that the ultrastructure of such tumors also reflects a range of cytological features. Such is the case.

Interpreting HVEM of muscle-cell impulse networks

1992 ◽  
Vol 50 (1) ◽  
pp. 126-127
Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn
Keyword(s):  
Structural Analysis ◽  
Muscle Cell ◽  
Electron Micrographs ◽  
Relative Size ◽  
Automatic Classification ◽  
Nerve Fibers ◽  
Analysis Algorithm ◽  
Structural Networks

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).

Dual stain kit for the microscopic gram classification of ocular infection bacteria

1993 ◽  
Vol 51 ◽  
pp. 248-249
Author(s):  
Jacob S. Hanker ◽  
Dale N. Holdren ◽  
Kenneth L. Cohen ◽  
Beverly L. Giammara
Keyword(s):  
Contact Lenses ◽  
Ocular Infection ◽  
Gram Negative Bacteria ◽  
Gram Negative ◽  
Gram Staining ◽  
Ocular Infections ◽  
Different Types ◽  
Culture Positive ◽  
Increased Susceptibility

Keratitis and conjunctivitis (infections of the cornea or conjunctiva) are ocular infections caused by various bacteria, fungi, viruses or parasites; bacteria, however, are usually prominent. Systemic conditions such as alcoholism, diabetes, debilitating disease, AIDS and immunosuppressive therapy can lead to increased susceptibility but trauma and contact lens use are very important factors. Gram-negative bacteria are most frequently cultured in these situations and Pseudomonas aeruginosa is most usually isolated from culture-positive ulcers of patients using contact lenses. Smears for staining can be obtained with a special swab or spatula and Gram staining frequently guides choice of a therapeutic rinse prior to the report of the culture results upon which specific antibiotic therapy is based. In some cases staining of the direct smear may be diagnostic in situations where the culture will not grow. In these cases different types of stains occasionally assist in guiding therapy.

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