Multimodality assessment of the coronary microvasculature with TIMI frame count versus perfusion PET highlights coronary changes characteristic of coronary microvascular disease.

Background: The diagnosis of coronary microvascular disease (CMVD) remains challenging. Perfusion PET-derived myocardial blood flow (MBF) reserve (MBFR) can quantify CMVD but is not widely available. Thrombolysis in Myocardial Infarction (TIMI) frame count (TFC) is an angiography-based method that has been proposed as a measure of CMVD. Here, we compare TFC and PET-derived MBF measurements to establish the role of TFC in assessing for CMVD. We use coronary modeling to elucidate the relationship between MBFR and TFC and propose TFC thresholds for identifying CMVD. Methods: In a cohort of 123 individuals (age 58 ± 12.1, 63% women, 41% Caucasian) without obstructive coronary artery disease who had undergone perfusion PET and coronary angiography for clinical indications, we compared TFC and perfusion PET parameters using Pearson correlation (PCC) and linear regression modeling. We used mathematical modeling of the coronary circulation to understand the relationship between these parameters and performed Receiver Operating Curve (ROC) analysis. Results: We found a significant negative correlation between TFC and MBFR. Sex, race and ethnicity, and nitroglycerin administration impact this relationship. Coronary modeling showed an uncoupling between TFC and flow in epicardial vessels. In ROC analysis, TFC performed well in women (AUC 0.84-0.89) and a moderately in men (AUC 0.68-0.78). Conclusions: We established an inverse relationship between TFC and PET-derived MBFR, which is affected by patient selection and procedural factors. TFC represents a measure of the volume of the epicardial coronary compartment, which is increased in patients with CMVD, and performs well in identifying women with CMVD.

Summary of the National Cancer Institute 2023 Virtual Workshop on Medical Image De-identification-Part 1: Report of the MIDI Task Group - Best Practices and Recommendations, Tools for Conventional Approaches to De-identification, International Approaches to De-identification, and Industry Panel on Image De-identification.

De-identification of medical images intended for research is a core requirement for data-sharing initiatives, particularly as the demand for data for artificial intelligence (AI) applications grows. The Center for Biomedical Informatics and Information Technology (CBIIT) of the US National Cancer Institute (NCI) convened a virtual workshop with the intent of summarizing the state of the art in de-identification technology and processes and exploring interesting aspects of the subject. This paper summarizes the highlights of the first day of the workshop, the recordings, and presentations of which are publicly available for review. The topics covered included the report of the Medical Image De-Identification Initiative (MIDI) Task Group on best practices and recommendations, tools for conventional approaches to de-identification, international approaches to de-identification, and an industry panel.

Collective acoustic modes of a bubble plume.

We derive a simple formula for the lowest natural frequencies of an infinitely long bubble plume with arbitrary cross section. Expressions are derived in terms of bubble volume fraction and equivalent radius of the plume, and a criterion for the existence of collective modes is established. For the plume with the circular cross section, our analytical approach is validated with the results of previous studies and numerical solution.

Tirbanibulin decreases cell proliferation and downregulates protein expression of oncogenic pathways in human papillomavirus containing HeLa cells.

Tirbanibulin 1% ointment is a synthetic antiproliferative agent approved in 2021 by the European Union for treating actinic keratoses (AK). Topical tirbanibulin has clinically resolved HPV-57 ( +) squamous cell carcinoma (SCC), HPV-16 ( +) vulvar high-grade squamous intraepithelial lesion, epidermodysplasia verruciformis, and condyloma. We examined how tirbanibulin might affect HPV oncoprotein expression and affect other cellular pathways involved in cell proliferation and transformation. We treated the HeLa cell line, containing integrated HPV-18, with increasing doses of tirbanibulin to determine the effects on cell proliferation. Immunoblotting was performed with antibodies against the Src canonical pathway, HPV 18 E6 and E7 transcription regulation, apoptosis, and invasion and metastasis pathways. Cell proliferation assays with tirbanibulin determined the half-maximal inhibitory concentration (IC50) of HeLa cells to be 31.49 nmol/L. Increasing concentrations of tirbanibulin downregulates the protein expression of Src (p < 0.001), phospho-Src (p < 0.001), Ras (p < 0.01), c-Raf (p < 0.001), ERK1 (p < 0.001), phospho-ERK1 (p < 0.001), phospho-ERK2 (p < 0.01), phospho-Mnk1 (p < 0.001), eIF4E (p < 0.01), phospho-eIF4E (p < 0.001), E6 (p < 0.01), E7 (p < 0.01), Rb (p < 0.01), phospho-Rb (p < 0.001), MDM2 (p < 0.01), E2F1 (p < 0.001), phospho-FAK (p < 0.001), phospho-p130 Cas (p < 0.001), Mcl-1 (p < 0.01), and Bcl-2 (p < 0.001), but upregulates cPARP (p < 0.001), and cPARP/fPARP (p < 0.001). These results demonstrate that tirbanibulin may impact expression of HPV oncoproteins via the Src- MEK- pathway. Tirbanibulin significantly downregulates oncogenic proteins related to cell cycle regulation and cell proliferation while upregulating apoptosis pathways.

Tirbanibulin is Promising Novel Therapy for Human Papillomavirus (HPV)-associated Diseases.Tirbanibulin 1% ointment is an approved synthetic topical ointment for treating actinic keratoses (AK), a precancer of skin cancer. Topical tirbanibulin has previously been reported to clinically resolve human papillomavirus (HPV)-( +) diseases.In this study, we examine how tirbanibulin may affect the HPV and pathways associated with cancer.We treated the HeLa cell line to determine the effects on HPV cell proliferation. Increasing the concentration of tirbanibulin statistically significantly affected numerous cellular pathways often associated with cancer.These results demonstrate that tirbanibulin may impact expression of HPV oncoproteins and thereby kill cancer cells.

Expanding RNAi to Kidneys, Lungs, and Spleen via Selective ORgan Targeting (SORT) siRNA Lipid Nanoparticles.

Inhibition of disease-causing mutations using RNA interference (RNAi) has resulted in clinically approved medicines with additional candidates in late stage trials. However, targetable tissues currently in preclinical development are limited to liver following systemic intravenous (IV) administration because predictable delivery of siRNA to non-liver tissues remains an unsolved challenge. Here, evidence of durable extrahepatic gene silencing enabled by siRNA Selective ORgan Targeting lipid nanoparticles (siRNA SORT LNPs) to the kidneys, lungs, and spleen is provided. LNPs excel at dose-dependent silencing of tissue-enriched endogenous targets resulting in 60%-80% maximal knockdown after a single IV injection and up to 88% downregulation of protein expression in mouse lungs after two doses. To examine knockdown potency and unbiased organ targeting, B6.129TdTom/EGFP mice that constitutively express the TdTomato transgene across all cell types are utilized to demonstrate 58%, 45%, and 15% reduction in TdTomato fluorescence in lungs, spleen, and kidneys, respectively. Finally, physiological relevance of siRNA SORT LNP-mediated gene silencing is established via acute suppression of endogenous Tie2 which induces lung-specific phenotypic alteration of vascular endothelial barrier. Due to plethora of extrahepatic diseases that may benefit from RNAi interventions, it is anticipated that the findings will expand preclinical landscape of therapeutic targets beyond the liver.

The effect of selinexor on prostaglandin synthesis in virus-positive Merkel cell carcinoma cell lines.

Merkel cell carcinoma (MCC) is an aggressive neuroendocrine skin cancer with high rates of metastasis and mortality. In vitro studies suggest that selinexor (KPT-330), an inhibitor of exportin 1, may be a targeted therapeutic option for MCC. This selective inhibitor prevents the transport of oncogenic mRNA out of the nucleus. Of note, 80% of MCC tumors are integrated with Merkel cell polyomavirus (MCPyV), and virally encoded tumor-antigens, small T (sT) and large T (LT) mRNAs may require an exportin transporter to relocate to the cytoplasm and modulate host tumor-suppressing pathways. To explore selinexor as a targeted therapy for MCC, we examine its ability to inhibit LT and sT antigen expression in vitro and its impact on the prostaglandin synthesis pathway. Protein expression was determined through immunoblotting and quantified by densitometric analysis. Statistical significance was determined with t-test. Treatment of MCPyV-infected cell lines with selinexor resulted in a significant dose-dependent downregulation of key mediators of the prostaglandin synthesis pathway. Given the role of prostaglandin synthesis pathway in MCC, our findings suggest that selinexor, alone or in combination with immunotherapy, could be a promising treatment for MCPyV-infected MCC patients who are resistant to chemotherapy and immunotherapy.

In vivo editing of lung stem cells for durable gene correction in mice.

In vivo genome correction holds promise for generating durable disease cures; yet, effective stem cell editing remains challenging. In this work, we demonstrate that optimized lung-targeting lipid nanoparticles (LNPs) enable high levels of genome editing in stem cells, yielding durable responses. Intravenously administered gene-editing LNPs in activatable tdTomato mice achieved >70% lung stem cell editing, sustaining tdTomato expression in >80% of lung epithelial cells for 660 days. Addressing cystic fibrosis (CF), NG-ABE8e messenger RNA (mRNA)-sgR553X LNPs mediated >95% cystic fibrosis transmembrane conductance regulator (CFTR) DNA correction, restored CFTR function in primary patient-derived bronchial epithelial cells equivalent to Trikafta for F508del, corrected intestinal organoids and corrected R553X nonsense mutations in 50% of lung stem cells in CF mice. These findings introduce LNP-enabled tissue stem cell editing for disease-modifying genome correction.

Correction of multiplexing artefacts in multi-pinhole SPECT through temporal shuttering, de-multiplexing of projections, and alternating reconstruction.

Objective.Single-photon emission computed tomography (SPECT) with pinhole collimators can provide high-resolution imaging, but is often limited by low sensitivity. Acquiring projections simultaneously through multiple pinholes affords both high resolution and high sensitivity. However, the overlap of projections from different pinholes on detectors, known as multiplexing, has been shown to cause artefacts which degrade reconstructed images.Approach.Multiplexed projection sets were considered here using an analytic simulation model of AdaptiSPECT-C-a brain-dedicated multi-pinhole SPECT system. AdaptiSPECT-C has fully adaptable aperture shutters, so can acquire projections with a combination of multiplexed and non-multiplexed frames using temporal shuttering. Two strategies for reducing multiplex artefacts were considered: an algorithm to de-multiplex projections, and an alternating reconstruction strategy for projections acquired with a combination of multiplexed and non-multiplexed frames. Geometric and anthropomorphic digital phantoms were used to assess a number of metrics.Main results.Both de-multiplexing strategies showed a significant reduction in image artefacts and improved fidelity, image uniformity, contrast recovery and activity recovery (AR). In all cases, the two de-multiplexing strategies resulted in superior metrics to those from images acquired with only mux-free frames. The de-multiplexing algorithm provided reduced image noise and superior uniformity, whereas the alternating strategy improved contrast and AR.Significance.The use of these de-multiplexing algorithms means that multi-pinhole SPECT systems can acquire projections with more multiplexing without degradation of images.

Bone-marrow-homing lipid nanoparticles for genome editing in diseased and malignant haematopoietic stem cells.

Therapeutic genome editing of haematopoietic stem cells (HSCs) would provide long-lasting treatments for multiple diseases. However, the in vivo delivery of genetic medicines to HSCs remains challenging, especially in diseased and malignant settings. Here we report on a series of bone-marrow-homing lipid nanoparticles that deliver mRNA to a broad group of at least 14 unique cell types in the bone marrow, including healthy and diseased HSCs, leukaemic stem cells, B cells, T cells, macrophages and leukaemia cells. CRISPR/Cas and base editing is achieved in a mouse model expressing human sickle cell disease phenotypes for potential foetal haemoglobin reactivation and conversion from sickle to non-sickle alleles. Bone-marrow-homing lipid nanoparticles were also able to achieve Cre-recombinase-mediated genetic deletion in bone-marrow-engrafted leukaemic stem cells and leukaemia cells. We show evidence that diverse cell types in the bone marrow niche can be edited using bone-marrow-homing lipid nanoparticles.

Patient Perspectives of the Manifestations and Treatment of Anti-MDA5 Antibody-Positive Dermatomyositis: An Observational Survey.

Idiopathic inflammatory myopathies (IIM) are a heterogeneous group of autoimmune disorders classically characterized by proximal skeletal muscle inflammation leading to weakness, but they often possess additional systemic manifestations such as cutaneous, pulmonary, and articular disease.1 Although originally dichotomized as either dermatomyositis (DM) or polymyositis, the discovery of new myositis-specific antibodies (MSA) and myositis-associated antibodies has led to the delineation of more refined IIM patient subgroups.

Effect of MR head coil geometry on deep-learning-based MR image reconstruction.

PURPOSE: To investigate whether parallel imaging-imposed geometric coil constraints can be relaxed when using a deep learning (DL)-based image reconstruction method as opposed to a traditional non-DL method. THEORY AND METHODS: Traditional and DL-based MR image reconstruction approaches operate in fundamentally different ways: Traditional methods solve a system of equations derived from the image data whereas DL methods use data/target pairs to learn a generalizable reconstruction model. Two sets of head coil profiles were evaluated: (1) 8-channel and (2) 32-channel geometries. A DL model was compared to conjugate gradient SENSE (CG-SENSE) and L1-wavelet compressed sensing (CS) through quantitative metrics and visual assessment as coil overlap was increased. RESULTS: Results were generally consistent between experiments. As coil overlap increased, there was a significant (p < 0.001) decrease in performance in most cases for all methods. The decrease was most pronounced for CG-SENSE, and the DL models significantly outperformed (p < 0.001) their non-DL counterparts in all scenarios. CS showed improved robustness to coil overlap and signal-to-noise ratio (SNR) versus CG-SENSE, but had quantitatively and visually poorer reconstructions characterized by blurriness as compared to DL. DL showed virtually no change in performance across SNR and very small changes across coil overlap. CONCLUSION: The DL image reconstruction method produced images that were robust to coil overlap and of higher quality than CG-SENSE and CS. This suggests that geometric coil design constraints can be relaxed when using DL reconstruction methods.

Microarray-Based DNA Methylation Profiling: Validation Considerations for Clinical Testing.

Microarray-based methylation profiling has emerged as a valuable tool for refining diagnoses and revealing novel tumor subtypes, particularly in central nervous system tumors. Despite the increasing adoption of this technique in clinical genomic laboratories, no technical standards have been published in establishing minimum criteria for test validation. A working group with experience and expertise in DNA-based methylation profiling tests on central nervous system tumors collaborated to develop practical discussion points and focus on important considerations for validating this test in clinical laboratory settings. The experience in validating this methodology in a clinical setting is summarized. Specifically, the advantages and challenges associated with utilizing an in-house classifier compared with a third-party classifier are highlighted. Additionally, experiences in demonstrating the assay's sensitivity and specificity, establishing minimum sample criteria, and implementing quality control metrics are described. As methylation profiling for tumor classification expands to other tumor types and continues to evolve for various other applications, the critical considerations described here are expected to serve as a guidance for future efforts in establishing professional guidelines for this assay.

Fitting high-resolution electron density maps from atomic models to solution scattering data.

Solution scattering techniques, such as small- and wide-angle X-ray scattering (SWAXS), provide valuable insights into the structure and dynamics of biological macromolecules in solution. In this study, we present an approach to accurately predict solution X-ray scattering profiles at wide angles from atomic models by generating high-resolution electron density maps. Our method accounts for the excluded volume of bulk solvent by calculating unique adjusted atomic volumes directly from the atomic coordinates. This approach eliminates the need for one of the free fitting parameters commonly used in existing algorithms, resulting in improved accuracy of the calculated SWAXS profile. An implicit model of the hydration shell is generated that uses the form factor of water. Two parameters, namely the bulk solvent density and the mean hydration shell contrast, are adjusted to best fit the data. Results using eight publicly available SWAXS profiles show high-quality fits to the data. In each case, the optimized parameter values show small adjustments demonstrating that the default values are close to the true solution. Disabling parameter optimization produces significantly more accurate predicted scattering profiles compared to the leading software. The algorithm is computationally efficient, comparable to the leading software and up to 10 times faster for large molecules. The algorithm is encoded in a command line script called denss.pdb2mrc.py and is available open source as part of the DENSS v1.7.0 software package. In addition to improving the ability to compare atomic models to experimental SWAXS data, these developments pave the way for increasing the accuracy of modeling algorithms using SWAXS data and decreasing the risk of overfitting.

Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations.

Many of the world's agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two subspecies, Bos taurus indicus (Bos indicus) and Bos taurus taurus (Bos taurus). Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign SNP alleles to ancestral subspecies of origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies differing effects. Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies of origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies of origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies of origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of QTL association mapping in genetically diverse populations.

Cytogenetically Cryptic Acute Promyelocytic Leukemia: A Diagnostic Challenge.

Cytogenetically cryptic acute promyelocytic leukemia (APL) is rare, characterized by typical clinical and morphological features, but lacks t(15;17)(q24;q21)/PML::RARA translocation seen in conventional karyotyping or FISH. The prompt diagnosis and treatment of APL are critical due to life-threatening complications associated with this disease. However, cryptic APL cases remain a diagnostic challenge that could mislead the appropriate treatment. We describe four cryptic APL cases and review reported cases in the literature. Reverse transcriptase polymerase chain reaction (RT-PCR) is the most efficient diagnostic modality to detect these cases, and alternative methods are also discussed. This study highlights the importance of using parallel testing methods to diagnose cryptic APL cases accurately and effectively.

NeuroBridge: a prototype platform for discovery of the long-tail neuroimaging data.

Introduction: Open science initiatives have enabled sharing of large amounts of already collected data. However, significant gaps remain regarding how to find appropriate data, including underutilized data that exist in the long tail of science. We demonstrate the NeuroBridge prototype and its ability to search PubMed Central full-text papers for information relevant to neuroimaging data collected from schizophrenia and addiction studies. Methods: The NeuroBridge architecture contained the following components: (1) Extensible ontology for modeling study metadata: subject population, imaging techniques, and relevant behavioral, cognitive, or clinical data. Details are described in the companion paper in this special issue; (2) A natural-language based document processor that leveraged pre-trained deep-learning models on a small-sample document corpus to establish efficient representations for each article as a collection of machine-recognized ontological terms; (3) Integrated search using ontology-driven similarity to query PubMed Central and NeuroQuery, which provides fMRI activation maps along with PubMed source articles. Results: The NeuroBridge prototype contains a corpus of 356 papers from 2018 to 2021 describing schizophrenia and addiction neuroimaging studies, of which 186 were annotated with the NeuroBridge ontology. The search portal on the NeuroBridge website https://neurobridges.org/ provides an interactive Query Builder, where the user builds queries by selecting NeuroBridge ontology terms to preserve the ontology tree structure. For each return entry, links to the PubMed abstract as well as to the PMC full-text article, if available, are presented. For each of the returned articles, we provide a list of clinical assessments described in the Section "Methods" of the article. Articles returned from NeuroQuery based on the same search are also presented. Conclusion: The NeuroBridge prototype combines ontology-based search with natural-language text-mining approaches to demonstrate that papers relevant to a user's research question can be identified. The NeuroBridge prototype takes a first step toward identifying potential neuroimaging data described in full-text papers. Toward the overall goal of discovering "enough data of the right kind," ongoing work includes validating the document processor with a larger corpus, extending the ontology to include detailed imaging data, and extracting information regarding data availability from the returned publications and incorporating XNAT-based neuroimaging databases to enhance data accessibility.

Review: Use of assisted reproduction in seasonal-calving dairy herds.

A unique aspect of seasonal-calving pasture-based systems of dairy production is the intense focus placed on achieving a concentrated herd-calving period in late winter and early spring. Hence, excellent reproductive performance is required during a short breeding period. A concentrated calving period also produces a problem in the form of a large number of male dairy calves being born at the same time; as these calves have little economic value due to poor beef merit, they present a potential welfare concern. A solution exists in the form of sex-sorted semen, but this is typically associated with poorer pregnancy per artificial insemination, and hence, the use of sex-sorted semen must be carefully considered. The logical strategy to use sex-sorted semen is to target the best genetic merit dams in the herd to generate replacement heifers, thereby accelerating herd genetic gain. On the other hand, if all dairy farmers adopt such a strategy, there will be a corresponding reduction in elite genetic merit male dairy calves being born, potentially reducing availability of the next generation of future bulls to be used for artificial insemination. Use of in vitro embryo production on elite dairy donors could avoid this problem by acting as a multiplier, potentially in tandem with Y-sorted semen to skew the offspring sex ratio towards more male calves. Use of sex-sorted semen on the best genetic merit dams can also facilitate a marked increase in the usage of beef semen on any dams that are deemed unsuitable for sex-sorted semen. The use of "beef on dairy" requires selection of beef bulls that generate offspring with traits that meet the key requirements of both the dairy farmer (e.g., gestation length and calving ease) and the beef farmer that must be motivated to purchase the calves (e.g., growth rate, age at slaughter, carcass value). Beef breed dams that have elite genetic merit for these traits could also be considered for in vitro embryo production, potentially in tandem with Y-sorted semen, to facilitate genetic gain for the growing "beef-on-dairy" market. It is possible to transfer a beef embryo (75-100% beef breed genetics) into dairy dams that are not required to generate replacements, but this is likely to remain a niche practice as there are many barriers to widespread adoption. Such combinations of assisted reproduction have the potential to improve the efficiency and sustainability metrics of seasonal-calving pasture-based dairy herds.

Fitting high-resolution electron density maps from atomic models to solution scattering data.

Solution scattering techniques, such as small and wide-angle X-ray scattering (SWAXS), provide valuable insights into the structure and dynamics of biological macromolecules in solution. In this study, we present an approach to accurately predict solution X-ray scattering profiles at wide angles from atomic models by generating high-resolution electron density maps. Our method accounts for the excluded volume of bulk solvent by calculating unique adjusted atomic volumes directly from the atomic coordinates. This approach eliminates the need for a free fitting parameter commonly used in existing algorithms, resulting in improved accuracy of the calculated SWAXS profile. An implicit model of the hydration shell is generated which uses the form factor of water. Two parameters, namely the bulk solvent density and the mean hydration shell contrast, are adjusted to best fit the data. Results using eight publicly available SWAXS profiles show high quality fits to the data. In each case, the optimized parameter values show small adjustments demonstrating that the default values are close to the true solution. Disabling parameter optimization results in a significant improvement of the calculated scattering profiles compared to the leading software. The algorithm is computationally efficient, showing more than tenfold reduction in execution time compared to the leading software. The algorithm is encoded in a command line script called denss.pdb2mrc.py and is available open source as part of the DENSS v1.7.0 software package (https://github.com/tdgrant1/denss). In addition to improving the ability to compare atomic models to experimental SWAXS data, these developments pave the way for increasing the accuracy of modeling algorithms utilizing SWAXS data while decreasing the risk of overfitting.