Dataset Information

QUAM-AFM: A Free Database for Molecular Identification by Atomic Force Microscopy.

ABSTRACT: This paper introduces Quasar Science Resources-Autonomous University of Madrid atomic force microscopy image data set (QUAM-AFM), the largest data set of simulated atomic force microscopy (AFM) images generated from a selection of 685,513 molecules that span the most relevant bonding structures and chemical species in organic chemistry. QUAM-AFM contains, for each molecule, 24 3D image stacks, each consisting of constant-height images simulated for 10 tip-sample distances with a different combination of AFM operational parameters, resulting in a total of 165 million images with a resolution of 256 × 256 pixels. The 3D stacks are especially appropriate to tackle the goal of the chemical identification within AFM experiments by using deep learning techniques. The data provided for each molecule include, besides a set of AFM images, ball-and-stick depictions, IUPAC names, chemical formulas, atomic coordinates, and map of atom heights. In order to simplify the use of the collection as a source of information, we have developed a graphical user interface that allows the search for structures by CID number, IUPAC name, or chemical formula.

SUBMITTER: Carracedo-Cosme J

PROVIDER: S-EPMC9942089 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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QUAM-AFM: A Free Database for Molecular Identification by Atomic Force Microscopy.

Carracedo-Cosme Jaime J Romero-Muñiz Carlos C Pou Pablo P Pérez Rubén R

Journal of chemical information and modeling 20220302 5

This paper introduces Quasar Science Resources-Autonomous University of Madrid atomic force microscopy image data set (QUAM-AFM), the largest data set of simulated atomic force microscopy (AFM) images generated from a selection of 685,513 molecules that span the most relevant bonding structures and chemical species in organic chemistry. QUAM-AFM contains, for each molecule, 24 3D image stacks, each consisting of constant-height images simulated for 10 tip-sample distances with a different combin ...[more]

PMID: 35234034

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Project description:BackgroundLichen planopilaris (LPP) is a chronic lymphocytic skin disease manifested by progressive scarring alopecia. The diagnosis of LPP is made based on histopathological examination, although it is not always definite. The current study evaluates the effectiveness of non-invasive atomic force microscopy (AFM) hair examination in detecting morphological differences between healthy and diseased hair.Materials and methodsHere, three to five hairs from lesional skin of 10 LPP patients were collected and examined at nine locations using AFM. At least four images were taken at each of the nine sites. Metric measurements were taken and metric (length, width, and scale step height) and morphological features (striated and smooth surface of scales, the presence of endocuticle and cortex, shape of scales edges, scratches, pitting, cracks, globules, and wavy edge) were compared with hair from healthy controls. In addition, areas on diseased hair where the process of pathological, unnatural delamination of the hair fiber occurs are described.ResultsThere was a statistically significant difference in the number of scratches in the initial sections of the LPP hair, in the intensity of wavy edges along the entire length of the tested hair, and in the number of scales with pitting in the middle section of the hair. In addition, a statistically significant higher number of scales with striated surface was found in LPP group starting at 3.5 cm from the root continuing towards the free end of the hair. Other morphological changes such as presence of cortex, globules, oval indentations, and rod-like macrofibrillar elements were also assessed, however, detailed results are not presented, as the differences shown in the number of these morphological changes were not significantly different.ConclusionThis publication outlines the differences between virgin, healthy Caucasian hair, and the hair of LPP patients. The results of this study can be used for further research and work related to LPP. This is the first attempt to characterize the hair of LPP patients using AFM.

Dataset Information

QUAM-AFM: A Free Database for Molecular Identification by Atomic Force Microscopy.

Publications

QUAM-AFM: A Free Database for Molecular Identification by Atomic Force Microscopy.

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