National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence.

The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and diverse. The National Cancer Institute (NCI) Imaging Data Commons (IDC) hosts large and diverse publicly available cancer image data collections. By harmonizing all data based on industry standards and colocalizing it with analysis and exploration resources, the IDC aims to facilitate the development, validation, and clinical translation of AI tools and address the well-documented challenges of establishing reproducible and transparent AI processing pipelines. Balanced use of established commercial products with open-source solutions, interconnected by standard interfaces, provides value and performance, while preserving sufficient agility to address the evolving needs of the research community. Emphasis on the development of tools, use cases to demonstrate the utility of uniform data representation, and cloud-based analysis aim to ease adoption and help define best practices. Integration with other data in the broader NCI Cancer Research Data Commons infrastructure opens opportunities for multiomics studies incorporating imaging data to further empower the research community to accelerate breakthroughs in cancer detection, diagnosis, and treatment. Published under a CC BY 4.0 license.

A case of SARS-CoV-2 pneumonia with successful antiviral therapy in a 77-year-old man with a heart transplant.

The SARS-CoV-2 infection can be seen as a single disease, but it also affects patients with relevant comorbidities who may have an increased risk of a severe course of infection. In this report, we present a 77-year-old patient with a heart transplant receiving relevant immunosuppressive therapy who tested positive for SARS-CoV-2 after several days of dyspnea, dry cough, and light general symptoms. Computed tomography confirmed interstitial pneumonia. The patient received antiviral therapy with hydroxychloroquine and showed no further deterioration of the clinical state. After 12 days of hospitalization, the patient was released; he was SARS-CoV-2 negative and completely asymptomatic.

Improved molecular replacement by density- and energy-guided protein structure optimization.

Molecular replacement procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 Å resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with >20% sequence identity.

AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons.

The National Cancer Institute (NCI) Image Data Commons (IDC) offers publicly available cancer radiology collections for cloud computing, crucial for developing advanced imaging tools and algorithms. Despite their potential, these collections are minimally annotated; only 4% of DICOM studies in collections considered in the project had existing segmentation annotations. This project increases the quantity of segmentations in various IDC collections. We produced high-quality, AI-generated imaging annotations dataset of tissues, organs, and/or cancers for 11 distinct IDC image collections. These collections contain images from a variety of modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). The collections cover various body parts, such as the chest, breast, kidneys, prostate, and liver. A portion of the AI annotations were reviewed and corrected by a radiologist to assess the performance of the AI models. Both the AI's and the radiologist's annotations were encoded in conformance to the Digital Imaging and Communications in Medicine (DICOM) standard, allowing for seamless integration into the IDC collections as third-party analysis collections. All the models, images and annotations are publicly accessible.

Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies.

The small animal imaging Digital Imaging and Communications in Medicine (DICOM) acquisition context structured report (SR) was developed to incorporate pre-clinical data in an established DICOM format for rapid queries and comparison of clinical and non-clinical datasets. Established terminologies (i.e., anesthesia, mouse model nomenclature, veterinary definitions, NCI Metathesaurus) were utilized to assist in defining terms implemented in pre-clinical imaging and new codes were added to integrate the specific small animal procedures and handling processes, such as housing, biosafety level, and pre-imaging rodent preparation. In addition to the standard DICOM fields, the small animal SR includes fields specific to small animal imaging such as tumor graft (i.e., melanoma), tissue of origin, mouse strain, and exogenous material, including the date and site of injection. Additionally, the mapping and harmonization developed by the Mouse-Human Anatomy Project were implemented to assist co-clinical research by providing cross-reference human-to-mouse anatomies. Furthermore, since small animal imaging performs multi-mouse imaging for high throughput, and queries for co-clinical research requires a one-to-one relation, an imaging splitting routine was developed, new Unique Identifiers (UID's) were created, and the original patient name and ID were saved for reference to the original dataset. We report the implementation of the small animal SR using MRI datasets (as an example) of patient-derived xenograft mouse models and uploaded to The Cancer Imaging Archive (TCIA) for public dissemination, and also implemented this on PET/CT datasets. The small animal SR enhancement provides researchers the ability to query any DICOM modality pre-clinical and clinical datasets using standard vocabularies and enhances co-clinical studies.

A DICOM dataset for evaluation of medical image de-identification.

We developed a DICOM dataset that can be used to evaluate the performance of de-identification algorithms. DICOM objects (a total of 1,693 CT, MRI, PET, and digital X-ray images) were selected from datasets published in the Cancer Imaging Archive (TCIA). Synthetic Protected Health Information (PHI) was generated and inserted into selected DICOM Attributes to mimic typical clinical imaging exams. The DICOM Standard and TCIA curation audit logs guided the insertion of synthetic PHI into standard and non-standard DICOM data elements. A TCIA curation team tested the utility of the evaluation dataset. With this publication, the evaluation dataset (containing synthetic PHI) and de-identified evaluation dataset (the result of TCIA curation) are released on TCIA in advance of a competition, sponsored by the National Cancer Institute (NCI), for algorithmic de-identification of medical image datasets. The competition will use a much larger evaluation dataset constructed in the same manner. This paper describes the creation of the evaluation datasets and guidelines for their use.

NCI Imaging Data Commons.

The National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a national cloud-based data science infrastructure. Imaging Data Commons (IDC) is a new component of CRDC supported by the Cancer Moonshot. The goal of IDC is to enable a broad spectrum of cancer researchers, with and without imaging expertise, to easily access and explore the value of deidentified imaging data and to support integrated analyses with nonimaging data. We achieve this goal by colocating versatile imaging collections with cloud-based computing resources and data exploration, visualization, and analysis tools. The IDC pilot was released in October 2020 and is being continuously populated with radiology and histopathology collections. IDC provides access to curated imaging collections, accompanied by documentation, a user forum, and a growing number of analysis use cases that aim to demonstrate the value of a data commons framework applied to cancer imaging research. SIGNIFICANCE: This study introduces NCI Imaging Data Commons, a new repository of the NCI Cancer Research Data Commons, which will support cancer imaging research on the cloud.

Enantiocomplementary enzymes: classification, molecular basis for their enantiopreference, and prospects for mirror-image biotransformations.

One often-cited weakness of biocatalysis is the lack of mirror-image enzymes for the formation of either enantiomer of a product in asymmetric synthesis. Enantiocomplementary enzymes exist as the solution to this problem in nature. These enzyme pairs, which catalyze the same reaction but favor opposite enantiomers, are not mirror-image molecules; however, they contain active sites that are functionally mirror images of one another. To create mirror-image active sites, nature can change the location of the binding site and/or the location of key catalytic groups. In this Minireview, X-ray crystal structures of enantiocomplementary enzymes are surveyed and classified into four groups according to how the mirror-image active sites are formed.

Stability and activity improvement of cephalosporin esterase EstB from Burkholderia gladioli by directed evolution and structural interpretation of muteins.

Esterase EstB from Burkholderia gladioli, which belongs to a family of esterases related to beta-lactamases and DD-peptidases was evolved for increased stability and simultaneously maintaining high cephalosporin C deacetylation activity. Random mutagenesis PCR was used to generate up to 5 aa substitutions per gene. A newly designed colony filter-screening assay, which was based on pH change after deacetylation of cephalosporin C in presence of DMF was established. In a first evolution round employing random mutagenesis, which included about 10(6) mutants, a set of interesting mutants was isolated. Distinct mutations identified as significant for stability were combined by a rational recombination step and the resulting recombinant was further evolved by an additional random mutagenesis round. After screening an additional 10(5) clones, it was possible to isolate a variant of EstB having more than 100-fold better activity in reactions containing 35% DMF. This mutant also showed a high increase in temperature stability (T(m) was raised by 13 degrees C) and retained high activity towards cephalosporin C under standard assay conditions. The molecular effects of mutations found in random mutants are discussed in view of the three-dimensional structure of wild-type EstB.

EstB from Burkholderia gladioli: a novel esterase with a beta-lactamase fold reveals steric factors to discriminate between esterolytic and beta-lactam cleaving activity.

Esterases form a diverse class of enzymes of largely unknown physiological role. Because many drugs and pesticides carry ester functions, the hydrolysis of such compounds forms at least one potential biological function. Carboxylesterases catalyze the hydrolysis of short chain aliphatic and aromatic carboxylic ester compounds. Esterases, D-alanyl-D-alanine-peptidases (DD-peptidases) and beta-lactamases can be grouped into two distinct classes of hydrolases with different folds and topologically unrelated catalytic residues, the one class comprising of esterases, the other one of beta-lactamases and DD-peptidases. The chemical reactivities of esters and beta-lactams towards hydrolysis are quite similar, which raises the question of which factors prevent esterases from displaying beta-lactamase activity and vice versa. Here we describe the crystal structure of EstB, an esterase isolated from Burkholderia gladioli. It shows the protein to belong to a novel class of esterases with homology to Penicillin binding proteins, notably DD-peptidase and class C beta-lactamases. Site-directed mutagenesis and the crystal structure of the complex with diisopropyl-fluorophosphate suggest Ser75 within the "beta-lactamase" Ser-x-x-Lys motif to act as catalytic nucleophile. Despite its structural homology to beta-lactamases, EstB shows no beta-lactamase activity. Although the nature and arrangement of active-site residues is very similar between EstB and homologous beta-lactamases, there are considerable differences in the shape of the active site tunnel. Modeling studies suggest steric factors to account for the enzyme's selectivity for ester hydrolysis versus beta-lactam cleavage.

Crystal structure analysis of EstA from Arthrobacter sp. Rue61a--an insight into catalytic promiscuity.

In this article we analyze the reasons for catalytic promiscuity of a type VIII esterase with ß-lactamase fold and the ability to cleave ß-lactams. We compared the structure of this enzyme to those of an esterase of the same type without any lactamase ability, an esterase with moderate lactamase ability, and a class C ß-lactamase with similar fold. Our results show that for these enzymes, the difference in the substrate specificity is sterically driven.

Structure and mechanism of an inverting alkylsulfatase from Pseudomonas sp. DSM6611 specific for secondary alkyl sulfates.

A highly enantioselective and stereoselective secondary alkylsulfatase from Pseudomonas sp. DSM6611 (Pisa1) was heterologously expressed in Escherichia coli BL21, and purified to homogeneity for kinetic and structural studies. Structure determination of Pisa1 by X-ray crystallography showed that the protein belongs to the family of metallo-ß-lactamases with a conserved binuclear Zn(2+) cluster in the active site. In contrast to a closely related alkylsulfatase from Pseudomonas aeruginosa (SdsA1), Pisa1 showed a preference for secondary rather than primary alkyl sulfates, and enantioselectively hydrolyzed the (R)-enantiomer of rac-2-octyl sulfate, yielding (S)-2-octanol with inversion of absolute configuration as a result of C-O bond cleavage. In order to elucidate the mechanism of inverting sulfate ester hydrolysis, for which no counterpart in chemical catalysis exists, we designed variants of Pisa1 guided by three-dimensional structure and docking experiments. In the course of these studies, we identified an invariant histidine (His317) near the sulfate-binding site as the general acid for crucial protonation of the sulfate leaving group. Additionally, amino acid replacements in the alkyl chain-binding pocket generated an enzyme variant that lost its stereoselectivity towards rac-2-octyl sulfate. These findings are discussed in light of the potential use of this enzyme family for applications in biocatalysis.

Characterization of the DMAE-modified juvenile excretory-secretory protein Juv-p120 of Litomosoides sigmodontis.

Juv-p120 is an excretory-secretory 160 kDa glycoprotein of juvenile female Litomosoides sigmodontis and exhibits features typical for mucins. 50% of its molecular mass is attributed to posttranslational modifications with the unusual substituent dimethylaminoethanol (DMAE). By that Juv-p120 corresponds to the surface proteins of the microfilarial sheath, Shp3 and Shp3a. The secreted protein consists of 697 amino acids, organized in two different domains of repeat elements separated by a stretch of polar residues. The N-terminal domain shows fourteen P/S/T/F-rich repeat elements highly modified with phospho-DMAE substituted O-glycans confering a negative charge to the protein. The C-terminal domain is extremely rich in glutamine (35%) and leucine (25%) in less organized repeats and may play a role in oligomerization of Juv-p120 monomers. A protein family with a similar Q/L-rich region and conserved core promoter region was identified in Brugia malayi by homology screening and in Wuchereria bancrofti and Loa loa by database similarity search. One of the Q/L-rich proteins in each genus has an extended S/T-rich region and due to this feature is supposed to be a putative Juv-p120 ortholog. The corresponding modification of Juv-p120 and the microfilarial sheath surface antigens Shp3/3a explains the appearance of anti-sheath antibodies before the release of microfilariae. The function of Juv-p120 is unknown.

A stereoselective inverting sec-alkylsulfatase for the deracemization of sec-alcohols.

A metallo-ß-lactamase-type alkylsulfatase was found to catalyze the enantioselective hydrolysis of sec-alkylsulfates with strict inversion of configuration. This catalytic event, which does not have an analog in chemocatalysis, yields homochiral (S)-configurated alcohols and nonreacted sulfate esters. The latter could be converted into (S)-sec-alcohols as the sole product in up to >99% ee via a chemoenzymatic deracemization protocol on a preparative scale.