Predicting Cardiotoxicity of Molecules Using Attention-Based Graph Neural Networks

In drug discovery, the search for new and effective medications is often hindered by concerns about toxicity. Numerous promising molecules fail to pass the later phases of drug development due to strict toxicity assessments. This challenge significantly increases the cost, time, and human effort needed to discover new therapeutic molecules. Additionally, a considerable number of drugs already on the market have been withdrawn or re-evaluated because of their unwanted side effects. Among the various types of toxicity, drug-induced heart damage is a severe adverse effect commonly associated with several medications, especially those used in cancer treatments. Although a number of computational approaches have been proposed to identify the cardiotoxicity of molecules, the performance and interpretability of the existing approaches are limited. In our study, we proposed a more effective computational framework to predict the cardiotoxicity of molecules using an attention-based graph neural network. Experimental results indicated that the proposed framework outperformed the other methods. The stability of the model was also confirmed by our experiments. To assist researchers in evaluating the cardiotoxicity of molecules, we have developed an easy-to-use online web server that incorporates our model.

Planning the future of oral health care workforce: Moving beyond demographic change

The adoption of Universal Health Coverage for oral health care will not be sufficient to ensure that health care resources are accessible in accordance with needs for care. Government intervention in planning and allocating resources will be required to replace traditional market forces if market failure is not to be replaced by government failure. In this paper we explore the limitations of current 'fixed in time' approaches to planning the oral health care workforce and present an enhanced dynamic model for workforce planning that responds directly to changes in population, evidence-based best practice and new models of care.

Macrophage-related gingival transcriptomic patterns and microbiome alterations in experimental periodontitis in nonhuman primates

OBJECTIVE

This study examined the microbiome features specifically related to host macrophage polarization in health, initiation and progression of periodontitis, and in resolution samples using a nonhuman primate model of ligature-induced periodontitis.

BACKGROUND

The oral microbiome is a complex of bacterial phyla, genera, and species acquired early in life into the individual autochthonous oral ecology. The microbiome changes overtime in response to both intrinsic and extrinsic stressors, and transitions to a dysbiotic ecology at sites of periodontal lesions.

METHODS

Comparisons were made between the microbial and host features in young (≤7 years) and adult (≥12 years) cohorts of animals. Footprints of macrophage-related genes in the gingival tissues were evaluated using expression profiles including M0, M1, and M2 related genes.

RESULTS

Within the gingival tissues, similar macrophage-related gene patterns were observed with significant increases with disease initiation and continued elevation throughout disease in both age groups. Approximately, 70% of the taxa were similar in relative abundance between the two groups; however, the adults showed a large number of OTUs that were significantly altered compared with the younger animals. Developing a correlation map identified three major node levels of interactions that comprised approximately ⅓ of the Operational Taxonomic Units (OTUs) that dominated the microbiomes across the samples. Also noted was a much greater frequency of significant correlations of individual OTUs with the macrophage phenotype markers, compared with disease and resolution samples in both age groups, with a greater frequency in the younger group. Moreover, these correlations were assigned to differentially expressed genes representing M0, M1, and M2-related phenotypes. A cluster analyses across the macrophage-related transcriptome and the OTUs demonstrated multiple somewhat distinct bacterial consortia, incorporating both commensal and putative pathogens, linked to the gene responses that differed in health, disease, and resolution samples. Finally, there were minimal alterations in the OTUs in individual clusters with specific macrophage-related responses in the younger group, while in the adult samples substantial variations were noted with genes from all macrophage phenotypes.

CONCLUSIONS

The results confirmed important features that could reflect macrophage polarization in periodontal lesions, and provided some initial data supporting specific members of the oral microbiome feature prominently related to specific gene response patterns consistent with macrophages in the gingival tissues.

Sexual Orientation and Gender Identity (SOGI) Data Collection: Opportunities to Advance Best Clinical Practices for LGBTQ+ Patients in Radiation Oncology

PURPOSE/OBJECTIVE(S)

A long-standing barrier to progress against health disparities is the lack of data regarding cancer risks, prevalence, treatment, and outcomes for sexual and gender minority (SGM) patients. Sexual orientation and gender identity (SOGI) data are not routinely collected by individual oncologists, cancer centers, or most non-federal hospital systems. Alarmingly high proportions of SGM patients report discrimination in healthcare or avoid routine care due to perceived lack of acceptance in the healthcare system. For these and other reasons, healthcare institutions must adopt practices that promote an inclusive environment for all patients including those self-identified from SGM groups. One strategy to achieve this aim is through SOGI data collection. The purpose of this study was to pilot new procedures and training for SOGI data collection, the aims of this project were to standardize the collection of SOGI data for all new patients referred to the Division of Radiation Oncology; promote clinical staff awareness of SGM health disparities and strategies for fostering an inclusive hospital environment; and to provide SGM patients and caregivers educational resources and support systems tailored to their needs.

MATERIALS/METHODS

We designed a Quality Improvement program for collecting SOGI data, which was approved by our institution's QIAB. Patient access specialists (PAS) were trained to collect SOGI data from newly registered patients and enter the data into the electronic health record. Radiation Oncology staff completed surveys before and after SOGI training to estimate its impact on the provision of patient care. A Fisher's exact test was utilized to evaluate associations between training and provider-reported outcomes.

RESULTS

Within a 3-week period starting in January 2023, two 1-hour interactive training sessions were offered to twenty-five PAS. Three 1-hour training sessions were offered to twenty-seven Radiation Oncology clinical staff. (1) Confidence for incorporating SOGI classifiers around patients improved from before training (52%, 13/25) to after training (100%, 17/17) among medical providers surveyed (odds ratio (OR) 32, 95% confidence interval (CI) 0.70-1493, p = 0.005). Use of SOGI data in clinical decision making increased from before training (9/25, 36%) to after training (100%, 17/17) among medical providers (OR 60.79, 95% CI 3.271-1130, p<0.0001). (2) A clinical pathway for SGM patients was developed to facilitate referral to our institution's SGM patient support group and distribution of patient education materials focused on sexual health.

CONCLUSION

Establishing standardized SOGI data collection can facilitate the provision of tailored resources and care that meets the needs of patients and staff in a large comprehensive cancer center. Specialized training for staff developed through this initiative helps foster an inclusive and welcoming environment that promotes the integration, visibility, and advancement of SGM cancer care at our institution.

Hippocampal-Sparing Radiotherapy in Primary Sinonasal and Cutaneous Head and Neck Malignancies: A Feasibility Study

PURPOSE/OBJECTIVE(S)

Patients with primary sinonasal and cutaneous head and neck (H&N) malignancies often receive meaningful hippocampal doses, but the hippocampus is not a classic avoidance structure in radiation planning of these primary sites. This series characterizes the feasibility and tradeoffs of hippocampal-sparing radiotherapy (HSRT) for patients with primary sinonasal and cutaneous H&N malignancies.

MATERIALS/METHODS

We retrospectively identified patients at a single institution treated definitively for primary sinonasal or cutaneous malignancies of the H&N. Each patient received (chemo)radiation and all received clinically-significant radiation dose to one or both hippocampi. We created new HSRT plans for each patient with intensity-modulated radiotherapy using original target and organ-at-risk (OAR) volumes. Hippocampi were contoured based on Radiation Therapy Oncology Group guidelines. Absolute and relative differences in radiation dose to the hippocampi, planning target volumes (PTV), and OARs were recorded. We used paired-samples t-tests to compare hippocampal and PTV dosimetric measures with and without HSRT.

RESULTS

Thirty-seven patients were included (22 sinonasal, 11 cutaneous H&N, and 4 parotid primary tumors). Median prescription dose was 6600cGy (range: 5000-7440cGy). The most common fractionation regimens were 200cGy/fraction daily (51%, 19/37 patients) and 120cGy/fraction twice daily (41%, 15/37 patients). There were significant decreases in hippocampal Dmax and D100% using HSRT without compromising PTV coverage (Table 1). HSRT resulted in a relative increase of mean lacrimal gland dose by an average of 3.8%, optic chiasm Dmax by 1.3%, and whole brain Dmax of 1.2%. However, other OAR doses were lower with HSRT, including parotid gland mean dose, lens Dmax, optic nerve Dmax, cochlea mean dose, brainstem Dmax, and whole brain mean dose.

CONCLUSION

HSRT is feasible and results in meaningful radiation dose reduction to the hippocampi without reducing PTV coverage or increasing dose to other OARs. The hippocampi should be regularly included as avoidance structures when treating primary sinonasal and cutaneous H&N tumors with radiation. We suggest target hippocampal constraints of Dmax < 1600cGy and D100% < 500cGy when feasible (without compromising PTV coverage). The clinical significance of HSRT in patients with primary H&N tumors should be investigated prospectively.

i4mC-GRU: Identifying DNA N4-Methylcytosine sites in mouse genomes using bidirectional gated recurrent unit and sequence-embedded features

N⁴-methylcytosine (4mC) is one of the most common DNA methylation modifications found in both prokaryotic and eukaryotic genomes. Since the 4mC has various essential biological roles, determining its location helps reveal unexplored physiological and pathological pathways. In this study, we propose an effective computational method called i4mC-GRU using a gated recurrent unit and duplet sequence-embedded features to predict potential 4mC sites in mouse (Mus musculus) genomes. To fairly assess the performance of the model, we compared our method with several state-of-the-art methods using two different benchmark datasets. Our results showed that i4mC-GRU achieved area under the receiver operating characteristic curve values of 0.97 and 0.89 and area under the precision-recall curve values of 0.98 and 0.90 on the first and second benchmark datasets, respectively. Briefly, our method outperformed existing methods in predicting 4mC sites in mouse genomes. Also, we deployed i4mC-GRU as an online web server, supporting users in genomics studies.

Relevance of 18F-DOPA visual and semi-quantitative PET metrics for the diagnostic of Parkinson disease in clinical practice: a machine learning-based inference study

PURPOSE

To decipher the relevance of visual and semi-quantitative 6-fluoro-(18F)-L-DOPA (¹⁸F-DOPA) interpretation methods for the diagnostic of idiopathic Parkinson disease (IPD) in hybrid positron emission tomography (PET) and magnetic resonance imaging.

MATERIAL AND METHODS

A total of 110 consecutive patients (48 IPD and 62 controls) with 11 months of median clinical follow-up (reference standard) were included. A composite visual assessment from five independent nuclear imaging readers, together with striatal standard uptake value (SUV) to occipital SUV ratio, striatal gradients and putamen asymmetry-based semi-quantitative PET metrics automatically extracted used to train machine learning models to classify IPD versus controls. Using a ratio of 70/30 for training and testing sets, respectively, five classification models-k-NN, LogRegression, support vector machine, random forest and gradient boosting-were trained by using 100 times repeated nested cross-validation procedures. From the best model on average, the contribution of PET parameters was deciphered using the Shapley additive explanations method (SHAP). Cross-validated receiver operating characteristic curves (cv-ROC) of the most contributive PET parameters were finally estimated and compared.

RESULTS

The best machine learning model (k-NN) provided final cv-ROC of 0.81. According to SHAP analyses, visual PET metric was the most important contributor to the model overall performance, followed by the minimum between left and right striatal to occipital SUV ratio. The 10-time cv-ROC curves of visual, min SUVr or both showed quite similar performance (mean area under the ROC of 0.81, 0.81 and 0.79, respectively, for visual, min SUVr or both).

CONCLUSION

Visual expert analysis remains the most relevant parameter to predict IPD diagnosis at 11 months of median clinical follow-up in ¹⁸F-FDOPA. The min SUV ratio appears interesting in the perspective of simple semi-automated diagnostic workflows.

iPromoter-Seqvec: identifying promoters using bidirectional long short-term memory and sequence-embedded features

Background

Promoters, non-coding DNA sequences located at upstream regions of the transcription start site of genes/gene clusters, are essential regulatory elements for the initiation and regulation of transcriptional processes. Furthermore, identifying promoters in DNA sequences and genomes significantly contributes to discovering entire structures of genes of interest. Therefore, exploration of promoter regions is one of the most imperative topics in molecular genetics and biology. Besides experimental techniques, computational methods have been developed to predict promoters. In this study, we propose iPromoter-Seqvec – an efficient computational model to predict TATA and non-TATA promoters in human and mouse genomes using bidirectional long short-term memory neural networks in combination with sequence-embedded features extracted from input sequences. The promoter and non-promoter sequences were retrieved from the Eukaryotic Promoter database and then were refined to create four benchmark datasets.

Results

The area under the receiver operating characteristic curve (AUCROC) and the area under the precision-recall curve (AUCPR) were used as two key metrics to evaluate model performance. Results on independent test sets showed that iPromoter-Seqvec outperformed other state-of-the-art methods with AUCROC values ranging from 0.85 to 0.99 and AUCPR values ranging from 0.86 to 0.99. Models predicting TATA promoters in both species had slightly higher predictive power compared to those predicting non-TATA promoters. With a novel idea of constructing artificial non-promoter sequences based on promoter sequences, our models were able to learn highly specific characteristics discriminating promoters from non-promoters to improve predictive efficiency.

Conclusions

iPromoter-Seqvec is a stable and robust model for predicting both TATA and non-TATA promoters in human and mouse genomes. Our proposed method was also deployed as an online web server with a user-friendly interface to support research communities. Links to our source codes and web server are available at https://github.com/mldlproject/2022-iPromoter-Seqvec.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08829-6.

iANP-EC: Identifying Anticancer Natural Products Using Ensemble Learning Incorporated with Evolutionary Computation

Cancer is one of the most deadly diseases that annually kills millions of people worldwide. The investigation on anticancer medicines has never ceased to seek better and more adaptive agents with fewer side effects. Besides chemically synthetic anticancer compounds, natural products are scientifically proved as a highly potential alternative source for anticancer drug discovery. Along with experimental approaches being used to find anticancer drug candidates, computational approaches have been developed to virtually screen for potential anticancer compounds. In this study, we construct an ensemble computational framework, called iANP-EC, using machine learning approaches incorporated with evolutionary computation. Four learning algorithms (k-NN, SVM, RF, and XGB) and four molecular representation schemes are used to build a set of classifiers, among which the top-four best-performing classifiers are selected to form an ensemble classifier. Particle swarm optimization (PSO) is used to optimise the weights used to combined the four top classifiers. The models are developed by a set of curated 997 compounds which are collected from the NPACT and CancerHSP databases. The results show that iANP-EC is a stable, robust, and effective framework that achieves an AUC-ROC value of 0.9193 and an AUC-PR value of 0.8366. The comparative analysis of molecular substructures between natural anticarcinogens and nonanticarcinogens partially unveils several key substructures that drive anticancerous activities. We also deploy the proposed ensemble model as an online web server with a user-friendly interface to support the research community in identifying natural products with anticancer activities.

iCYP-MFE: Identifying Human Cytochrome P450 Inhibitors Using Multitask Learning and Molecular Fingerprint-Embedded Encoding

The human cytochrome P450 (CYP) superfamily holds responsibilities for the metabolism of both endogenous and exogenous compounds such as drugs, cellular metabolites, and toxins. The inhibition exerted on the CYP enzymes is closely associated with adverse drug reactions encompassing metabolic failures and induced side effects. In modern drug discovery, identification of potential CYP inhibitors is, therefore, highly essential. Alongside experimental approaches, numerous computational models have been proposed to address this biochemical issue. In this study, we introduce iCYP-MFE, a computational framework for virtual screening on CYP inhibitors toward 1A2, 2C9, 2C19, 2D6, and 3A4 isoforms. iCYP-MFE contains a set of five robust, stable, and effective prediction models developed using multitask learning incorporated with molecular fingerprint-embedded features. The results show that multitask learning can remarkably leverage useful information from related tasks to promote global performance. Comparative analysis indicates that iCYP-MFE achieves three predominant tasks, one equivalent task, and one less effective task compared to state-of-the-art methods. The area under the receiver operating characteristic curve (AUC-ROC) and the area under the precision-recall curve (AUC-PR) were two decisive metrics used for model evaluation. The prediction task for CYP2D6-inhibition achieves the highest AUC-ROC value of 0.93 while the prediction task for CYP1A2-inhibition obtains the highest AUC-PR value of 0.92. The substructural analysis preliminarily explains the nature of the CYP-inhibitory activity of compounds. An online web server for iCYP-MFE with a user-friendly interface was also deployed to support scientific communities in identifying CYP inhibitors.

Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features

As a critical issue in drug development and postmarketing safety surveillance, drug-induced liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market approved drugs. Therefore, it is important to identify DILI compounds in the early-stages through in silico and in vivo studies. It is difficult using conventional safety testing methods, since the predictive power of most of the existing frameworks is insufficiently effective to address this pharmacological issue. In our study, we employ a natural language processing (NLP) inspired computational framework using convolutional neural networks and molecular fingerprint-embedded features. Our development set and independent test set have 1597 and 322 compounds, respectively. These samples were collected from previous studies and matched with established chemical databases for structural validity. Our study comes up with an average accuracy of 0.89, Matthews's correlation coefficient (MCC) of 0.80, and an AUC of 0.96. Our results show a significant improvement in the AUC values compared to the recent best model with a boost of 6.67%, from 0.90 to 0.96. Also, based on our findings, molecular fingerprint-embedded featurizer is an effective molecular representation for future biological and biochemical studies besides the application of classic molecular fingerprints.

Experimental Demonstration of Hadron Beam Cooling Using Radio-Frequency Accelerated Electron Bunches

Cooling of beams of gold ions using electron bunches accelerated with radio-frequency systems was recently experimentally demonstrated in the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. Such an approach is new and opens the possibility of using this technique at higher energies than possible with electrostatic acceleration of electron beams. The challenges of this approach include generation of electron beams suitable for cooling, delivery of electron bunches of the required quality to the cooling sections without degradation of beam angular divergence and energy spread, achieving the required small angles between electron and ion trajectories in the cooling sections, precise velocity matching between the two beams, high-current operation of the electron accelerator, as well as several physics effects related to bunched-beam cooling. Here we report on the first demonstration of cooling hadron beams using this new approach.

Nondestructive evaluation of 3D microstructure evolution in strontium titanate

Nondestructive X-ray diffraction contrast tomography imaging was used to characterize the microstructure evolution in a polycrystalline bulk strontium titanate specimen. Simultaneous acquisition of diffraction and absorption information allows for the reconstruction of shape and orientation of more than 800 grains in the specimen as well as porosity. Three-dimensional microstructure reconstructions of two coarsening states of the same specimen are presented alongside a detailed exploration of the crystallographic, topological and morphological characteristics of the evolving microstructure. The overall analysis of the 3D structure shows a clear signature of the grain boundary anisotropy, which can be correlated to surface energy anisotropy: the grain boundary plane distribution function shows an excess of 〈100〉-oriented interfaces with respect to a random structure. The results are discussed in the context of interface property anisotropy effects.

Targeting Oncogenic Super Enhancers in MYC-Dependent AML Using a Small Molecule Activator of NR4A Nuclear Receptors

Epigenetic reprogramming in Acute Myeloid Leukemia (AML) leads to the aberrant activation of super enhancer (SE) landscapes that drive the expression of key oncogenes, including the oncogenic MYC pathway. These SEs have been identified as promising therapeutic targets, and have given rise to a new class of drugs, including BET protein inhibitors, which center on targeting SE activity. NR4A nuclear receptors are tumor suppressors of AML that function in part through transcriptional repression of the MYC-driven oncogenic program via mechanisms that remain unclear. Here we show that NR4A1, and the NR4A inducing drug dihydroergotamine (DHE), regulate overlapping gene expression programs in AML and repress transcription of a subset of SE-associated leukemic oncogenes, including MYC. NR4As interact with an AML-selective SE cluster that governs MYC transcription and decommissions its activation status by dismissing essential SE-bound coactivators including BRD4, Mediator and p300, leading to loss of p300-dependent H3K27 acetylation and Pol 2-dependent eRNA transcription. DHE shows similar efficacy to the BET inhibitor JQ1 at repressing SE-dependent MYC expression and AML growth in mouse xenografts. Thus, DHE induction of NR4As provides an alternative strategy to BET inhibitors to target MYC dependencies via suppression of the AML-selective SE governing MYC expression.

Plant Metabolite Databases: From Herbal Medicines to Modern Drug Discovery

Traditional herbal medicine has been an inseparable part of the traditional medical science in many countries throughout history. Nowadays, the popularity of using herbal medicines in daily life, as well as clinical practices, has gradually expanded to numerous Western countries with positive impacts and acceptance. The continuous growth of the herbal consumption market has promoted standardization and modernization of herbal-derived products with present pharmacological criteria. To store and extensively share this knowledge with the community and serve scientific research, various herbal metabolite databases have been developed with diverse focuses under the support of modern advances. The advent of these databases has contributed to accelerating research on pharmaceuticals of natural origins. In the scope of this study, we critically review 30 herbal metabolite databases, discuss different related perspectives, and provide a comparative analysis of 18 accessible noncommercial ones. We hope to provide you with fundamental information and multidimensional perspectives from herbal medicines to modern drug discovery.

Determination of Domoic Acid Toxins in Shellfish by Biosense ASP ELISAA Direct Competitive Enzyme-Linked Immunosorbent Assay: Collaborative Study

A collaborative study was conducted on the Biosense amnesic shellfish poisoning (ASP) enzyme-linked immunosorbent assay (ELISA) for the determination of domoic acid (DA) toxins in shellfish in order to obtain interlaboratory validation data for the method. In addition, a method comparison study was performed to evaluate the ASP ELISA as an alternative to the current liquid chromatography (LC) reference method for DA determination. The study material comprised 16 shellfish samples, including blue mussels, Pacific oysters, and king scallops, spiked with contaminated mussel homogenates to contain 0.120 mg DA/kg shellfish flesh. The shellfish samples were extracted with 50% aqueous methanol, and the supernatants were directly analyzed. Sixteen participating laboratories in 10 countries reported data from the ASP ELISA, and 4 of these laboratories also reported data from instrumental LC analysis. The participating laboratories achieved interlaboratory precision estimates for the 8 Youden paired shellfish samples in the range of 1020% for RSDr (mean 14.8 4%), and 1329% for RSDR (mean 22.7 6%). The precision estimates for the ELISA data did not show a strong dependence on the DA concentration in the study samples, and the overall precision achieved was within the acceptable range of the Horwitz guideline with HorRat values ranging from 1.1 to 2.4 (mean HorRat 1.7 0.5). The analysis of shellfish samples spiked with certified reference material (CRM)-ASP-MUS-b gave recoveries in the range of 88122%, with an average recovery of 104 10%. The estimate on method accuracy was supported by a correlation slope of 1.015 (R2 = 0.992) for the determined versus the expected DA values. Furthermore, the correlation of the ASP ELISA results with those for the instrumental LC analyses of the same sample extracts gave a correlation slope of 1.29 (R2 = 0.984). This indicates some overestimation of DA levels in shellfish by the ELISA, but it is also a result of apparent low recoveries for the LC methods. This interlaboratory study demonstrates that the ASP ELISA is suitable for the routine determination and monitoring of DA toxins in shellfish, and that it offers a rapid and cost-effective methodology with high sample throughput.

The genomic landscape of estrogen receptor α binding sites in mouse mammary gland

Estrogen receptor α (ERα) is the major driving transcription factor in the mammary gland development as well as breast cancer initiation and progression. However, the genomic landscape of ERα binding sites in the normal mouse mammary gland has not been completely elucidated. Here, we mapped genome-wide ERα binding events by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) in the mouse mammary gland in response to estradiol. We identified 6237 high confidence ERα binding sites in two biological replicates and showed that many of these were located at distal enhancer regions. Furthermore, we discovered 3686 unique genes in the mouse genome that recruit ER in response to estradiol. Interrogation of ER-DNA binding sites in ER-positive luminal epithelial cells showed that the ERE, PAX2, SF1, and AP1 motifs were highly enriched at distal enhancer regions. In addition, comprehensive transcriptome analysis by RNA-seq revealed that 493 genes are differentially regulated by acute treatment with estradiol in the mouse mammary gland in vivo. Through integration of RNA-seq and ERα ChIP-seq data, we uncovered a novel ERα targetome in mouse mammary epithelial cells. Taken together, our study has identified the genomic landscape of ERα binding events in mouse mammary epithelial cells. Furthermore, our study also highlights the cis-regulatory elements and cofactors that are involved in estrogen signaling and may contribute to ductal elongation in the normal mouse mammary gland.

Temporal patterning of apical progenitors and their daughter neurons in the developing neocortex

During corticogenesis, distinct subtypes of neurons are sequentially born from ventricular zone progenitors. How these cells are molecularly temporally patterned is poorly understood. We used single-cell RNA sequencing at high temporal resolution to trace the lineage of the molecular identities of successive generations of apical progenitors (APs) and their daughter neurons in mouse embryos. We identified a core set of evolutionarily conserved, temporally patterned genes that drive APs from internally driven to more exteroceptive states. We found that the Polycomb repressor complex 2 (PRC2) epigenetically regulates AP temporal progression. Embryonic age-dependent AP molecular states are transmitted to their progeny as successive ground states, onto which essentially conserved early postmitotic differentiation programs are applied, and are complemented by later-occurring environment-dependent signals. Thus, epigenetically regulated temporal molecular birthmarks present in progenitors act in their postmitotic progeny to seed adult neuronal diversity.

Shape of (101955) Bennu indicative of a rubble pile with internal stiffness

The shapes of asteroids reflect interplay between their interior properties and the processes responsible for their formation and evolution as they journey through the Solar System. Prior to the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) mission, Earth-based radar imaging gave an overview of (101955) Bennu's shape. Here, we construct a high-resolution shape model from OSIRIS-REx images. We find that Bennu's top-like shape, considerable macroporosity, and prominent surface boulders suggest that it is a rubble pile. High-standing, north-south ridges that extend from pole to pole, many long grooves, and surface mass wasting indicate some low levels of internal friction and/or cohesion. Our shape model indicates that, similar to other top-shaped asteroids, Bennu formed by reaccumulation and underwent past periods of fast spin leading to its current shape. Today, Bennu might follow a different evolutionary pathway, with interior stiffness permitting surface cracking and mass wasting.

Abstract P3-14-07: Evaluation of the effects of talazoparib on QT interval prolongation

Background: Talazoparib (TAL), an oral poly ADP-ribose polymerase inhibitor, is under investigation in multiple oncologic clinical trials and has been submitted to the US FDA for use in patients (pts) with germline BRCA-mutated, HER2-negative advanced breast cancer.

International Conference on Harmonisation guidance recommends all new drugs be evaluated for effects on cardiac repolarization in a well-controlled clinical study. For drugs for which such evaluation cannot be conducted in healthy volunteers (eg, most anticancer agents), collection of robust corrected QT (QTc) interval data from a dedicated QTc study (hybrid thorough QT/QTc study) in pts is required in the registration dossier. The effect of steady-state (ss) TAL (1 mg once daily) on cardiac repolarization in pts with advanced solid tumors was evaluated in an open-label phase 1 study (NCT03042910).

Methods: Continuous 12-lead electrocardiogram (ECG) recordings were collected at baseline (Day -1); time-matched pharmacokinetic (PK) samples and continuous ECG recordings were obtained on Days 1, 2, and 22 (when TAL concentrations achieved ss). On Day -1, pts had continuous 12-lead ECG recording starting at Time 0 (Day 1 dosing time) for 6 hrs. On Days 1 and 22, ECG recording started 45 min before TAL administration and continued for 6 hrs post dose and blood samples for PK were collected before dose and at 1, 2, 4, and 6 hrs post dose. On Day 2, a 30-min ECG recording and a PK sample were obtained before dose at Time 0.

Continuous ECG recordings were submitted to a central laboratory; triplicate 10-sec ECGs were extracted from a 5-min extraction window beginning 15 min before each PK collection time. ECG measurements were reported via blinded manual adjudication process and included PR interval, QT interval, RR interval, and QRS complex. The QT interval was corrected for effect of heart rate using Fridericia's correction (QTcF) and Bazett's correction (QTcB).

The estimate of change from time-matched baseline and its 2-sided 90% confidence interval (CI) was calculated for each nominal time point using PROC MEANS. Additionally, a prespecified PK/pharmacodynamic (PD) model was used to describe the relationship between plasma TAL concentrations ([TAL]) and QTc. The prespecified linear mixed-effects model included [TAL], time (categorical), and treatment with random pt effects on [TAL] and the intercept. If the upper bounds (UB) of 1-sided 95% CIs of time-matched ΔQTc for all ECG time points were &lt;20 msec and the UB of 1-sided 95% CIs of the predicted ΔQTc at the mean ss maximum [TAL] was &lt;20 msec, the effect of TAL on QTc was not of clinical relevance.

Results: 37 of 38 pts enrolled received TAL and were included in the ECG and PK/PD analyses. No pts had a postbaseline absolute maximum QTcF or QTcB ≥500 msec or ΔQTc ≥60 msec. The UB of the 1-sided 95% CI for the time-matched ΔQTcF and ΔQTcB were &lt;12 msec at all nominal ECG time points. In the PK/PD analysis, the slopes (95% CI) of QTcF-[TAL] and QTcB-[TAL] relationships were -0.14 (-0.78 to 0.50) msec/ng/mL and -0.24 (-0.88 to 0.41) msec/ng/mL, respectively, indicating that TAL did not have a concentration-dependent effect on QTcF or QTcB.

Conclusion: TAL does not have a clinically relevant effect on QTc.

Funding: Medivation LLC, acquired by Pfizer.

Citation Format: Hoffman J, Chakrabarti J, Wainberg ZA, Plotka A, Babu S, Milillo Naraine A, Kanamori D, Moroose R, Nguyen L, Wang D. Evaluation of the effects of talazoparib on QT interval prolongation [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-14-07.

Age and Periodontal Health - Immunological View

PURPOSE OF THE REVIEW

Aging clearly impacts a wide array of systems, in particular the breadth of the immune system leading to immunosenescence, altered immunoactivation, and coincident inflammaging processes. The net result of these changes leads to increased susceptibility to infections, increased neoplastic occurrences, and elevated frequency of autoimmune diseases with aging. However, as the bacteria in the oral microbiome that contribute to the chronic infection of periodontitis is acquired earlier in life, the characteristics of the innate and adaptive immune systems to regulate these members of the autochthonous microbiota across the lifespan remains ill defined.

RECENT FINDINGS

Clear data demonstrate that both cells and molecules of the innate and adaptive immune response are adversely impacted by aging, including in the oral cavity, yielding a reasonable tenet that the increased periodontitis noted in aging populations is reflective of the age-associated immune dysregulation. Additionally, this facet of host-microbe interactions and disease needs to accommodate the population variation in disease onset and progression, which may also reflect an accumulation of environmental stressors and/or decreased protective nutrients that could function at the gene level (ie. epigenetic) or translational level for production and secretion of immune system molecules.

SUMMARY

Finally, the majority of studies of aging and periodontitis have emphasized the increased prevalence/severity of disease with aging, all based upon chronological age. However, evolving areas of study focusing on "biological aging" to help account for population variation in disease expression, may suggest that chronic periodontitis represents a co-morbidity that contributes to "gerovulnerability" within the population.

The strength and spread of the electric field induced by transcranial rotating permanent magnet stimulation in comparison with conventional transcranial magnetic stimulation

BACKGROUND

Weak or low intensity transcranial stimulation of the brain, such as low field magnetic stimulation and electrical stimulation, can produce significant functional and therapeutic neuromodulatory effects.

NEW METHOD

We have recently developed a portable wearable multifocal brain stimulator called transcranial rotating permanent magnet stimulator (TRPMS) that uses rapidly spinning high field strength permanent magnets attached to a cap. It produces oscillatory stimuli of different frequencies and patterns. Here we compared the strengths and spatial profiles of the changing magnetic fields of a figure-of-eight transcranial magnetic stimulator (TMS) coil, a TRPMS prototype, and a scaled-up version of TRPMS. We measured field strengths and directions of voltages induced in a magnetic field sensor oriented along all three orthogonal axes.

RESULTS AND COMPARISON WITH EXISTING METHODS

The spatial spread of the TRPMS-induced electric field is more restricted, and its shape and strength vary less with the orientation of the inductance than TMS. The maximum voltage induced by the current prototype is ∼7% of the maximal TMS output at depths corresponding to the human cerebral cortex from the scalp surface. This field strength can be scaled up by a factor ∼8 with a larger diametrically magnetized magnet. These comparative data allow us to estimate that intracortical effects of TRPMS could be stronger than other low intensity stimulation methods.

CONCLUSIONS

TRPMS might enable greater uniformity, consistency and focality in stimulation of targeted cortical areas subject to significant anatomical variability. Multiple TRPMS microstimulators can also be combined to produce patterned multifocal spatiotemporal stimulation.

Abstract P1-14-03: ABRAZO: Exposure-efficacy and -safety analyses of breast cancer patients with germline BRCA1/2 mutations receiving talazoparib in a phase 2 open-label trial

Background: Talazoparib (TALA) is a dual-mechanism poly (ADP-ribose) polymerase (PARP) inhibitor that traps PARP on DNA. Efficacy results of this phase 2 trial were previously presented (Turner et al, ASCO 2017, abstract 1007). This study included sparse pharmacokinetic (PK) sampling for patients through cycle 4 of therapy. Exploratory analyses included assessment of exposure versus parameters of efficacy and safety.

Methods: ABRAZO (NCT02034916) was a parallel-cohort, open-label phase 2 study of TALA (1 mg/d) following (i) platinum-based therapy (cohort 1) or (ii) ≥3 platinum-free cytotoxic-based regimens (cohort 2) in patients with locally advanced or metastatic breast cancer and germline BRCA1/2 mutation. Sparse PK sampling was performed on day 1 of cycles 1-4, consisting of a predose sample collected ≤60 minutes prior to dosing and 2 postdose samples collected ≥30 minutes after dosing (time of food ingestion prior to the dose was collected). The collection times of the 2 postdose samples were separated by ≥2 hours. Efficacy parameters included radiographic progression-free survival (rPFS) by central review and objective response rate (ORR). Safety parameters included incidence of overall adverse events (AEs) and grade ≥3 AEs. Individual AUCs (area under concentration-time curves) for exposure-response analyses were predicted by population PK analyses.

Results: Patients were divided into AUC tertiles: low (median, 109.0 ng*hr/mL; n=27), intermediate (median, 170.8 ng*hr/mL; n=27), and high (median, 219.2 ng*hr/mL; n=27). Median rPFS was 5.3 months (95% confidence interval [CI], 3.1, 8.3) in the lowest AUC tertile, 5.6 months (95% CI, 3.7, 8.4) in the intermediate AUC tertile, and 5.3 months (95% CI, 3.9, 5.6) in the highest AUC tertile. The ORR was 22.2% (95% CI, 8.6, 42.3) in the lowest AUC tertile, 25.9% (95% CI, 11.1, 46.3) in the intermediate AUC tertile, and 37.0% (95% CI, 19.4, 57.6) in the highest AUC tertile. AEs of any grade were reported in 11 patients (40.7%) in the lowest AUC tertile, 21 patients (77.8%) in the intermediate AUC tertile, and 22 patients (81.5%) in the highest AUC tertile. Grade ≥3 AEs were reported in 8 patients (29.6%) in the lowest AUC tertile and in 18 patients (66.7%) in the intermediate and highest AUC tertiles. The most common AEs in all 3 exposure tertiles were anemia, thrombocytopenia, and neutropenia.

Conclusions: Median rPFS did not change with increasing systemic exposure. There may be a trend to higher ORR in patients with highest systemic exposure. A larger percentage of patients experienced AEs with elevated systemic exposure. Increased response rates with greater exposure does not translate to improved rPFS. These results should be interpreted with caution due to the low patient numbers in each cohort.

Citation Format: Telli ML, Turner NC, Mailliez A, Ettl J, Grischke E-M, Mina LA, Balmaña J, Hurvitz SA, Wardley AM, Fasching PA, Tudor C, Nguyen L, Hannah AL, Robson ME, Rugo HS. ABRAZO: Exposure-efficacy and -safety analyses of breast cancer patients with germline BRCA1/2 mutations receiving talazoparib in a phase 2 open-label trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-14-03.

Cone dystrophy and ectopic synaptogenesis in a Cacna1f loss of function model of congenital stationary night blindness (CSNB2A)

Congenital stationary night blindness 2A (CSNB2A) is an X-linked retinal disorder, characterized by phenotypically variable signs and symptoms of impaired vision. CSNB2A is due to mutations in CACNA1F, which codes for the pore-forming α1F subunit of a L-type voltage-gated calcium channel, Cav1.4. Mouse models of CSNB2A, used for characterizing the effects of various Cacna1f mutations, have revealed greater severity of defects than in human CSNB2A. Specifically, Cacna1f-knockout mice show an apparent lack of visual function, gradual retinal degeneration, and disruption of photoreceptor synaptic terminals. Several reports have also noted cone-specific disruptions, including axonal abnormalities, dystrophy, and cell death. We have explored further the involvement of cones in our 'G305X' mouse model of CSNB2A, which has a premature truncation, loss-of-function mutation in Cacna1f. We show that the expression of genes for several phototransduction-related cone markers is down-regulated, while that of several cellular stress- and damage-related markers is up-regulated; and that cone photoreceptor structure and photopic visual function - measured by immunohistochemistry, optokinetic response and electroretinography - deteriorate progressively with age. We also find that dystrophic cone axons establish synapse-like contacts with rod bipolar cell dendrites, which they normally do not contact in wild-type retinas - ectopically, among rod cell bodies in the outer nuclear layer. These data support a role for Cav1.4 in cone synaptic development, cell viability, and synaptic transmission of cone-dependent visual signals. Although our novel finding of cone-to-rod-bipolar cell contacts in this mouse model of a retinal channelopathy may challenge current views of the role of Cav1.4 in photopic vision, it also suggests a potential new target for restorative therapy.

ARCHITECTURAL PATTERNS FOR DIFFERENTIAL DIAGNOSIS OF PROLIFERATIVE BREAST LESIONS FROM HISTOPATHOLOGICAL IMAGES

The differential diagnosis of proliferative breast lesions, benign usual ductal hyperplasia (UDH) versus malignant ductal carcinoma in situ (DCIS) is challenging. This involves a pathologist examining histopathologic sections of a biopsy using a light microscope, evaluating tissue structures for their architecture or size, and assessing individual cell nuclei for their morphology. Imposing diagnostic boundaries on features that otherwise exist on a continuum going from benign to atypia to malignant is a challenge. Current computational pathology methods have focused primarily on nuclear atypia in drawing these boundaries. In this paper, we improve on these approaches by encoding for both cellular morphology and spatial architectural patterns. Using a publicly available breast lesion database consisting of UDH and three different grades of DCIS, we improve the classification accuracy by 10% over the state-of-the-art method for discriminating UDH and DCIS. For the four way classification of UDH and the three grades of DCIS, our method improves the results by 6% in accuracy, 8% in micro-AUC, and 19% in macro-AUC.

Nausea and vomiting in gastroparesis: similarities and differences in idiopathic and diabetic gastroparesis

BACKGROUND

Nausea and vomiting are classic symptoms of gastroparesis. It remains unclear if characteristics of nausea and vomiting are similar in different etiologies of gastroparesis. The aims of this article were as follows: to describe characteristics of nausea and vomiting in patients with gastroparesis and to determine if there are differences in nausea and vomiting in diabetic (DG) and idiopathic gastroparesis (IG).

METHODS

Gastroparetic patients enrolling in the NIDDK Gastroparesis Registry underwent assessment with history and questionnaires assessing symptoms, quality of life, and a questionnaire characterizing nausea and vomiting.

KEY RESULTS

Of 159 gastroparesis patients (107 IG, 52 DG), 96% experienced nausea, whereas 65% experienced vomiting. Nausea was predominant symptom in 28% and vomiting was predominant in 4%. Nausea was severe or very severe in 41%. PAGI-SYM nausea/vomiting subscore was greater with increased vomiting severity, but not nausea severity in DG than IG. Nausea was related to meals in 71%; lasting most of the day in 41%. Increasing nausea severity was related to decreased quality of life. Nausea often preceded vomiting in 82% of patients and vomiting often relieved nausea in 30%. Vomiting was more common in DG (81%) compared to IG (57%; p = 0.004). Diabetic patients more often had vomiting in the morning before eating, during the night, and when not eating.

CONCLUSIONS & INFERENCES

Nausea is present in essentially all patients with gastroparesis irrespective of cause and associated with decreased quality of life. In contrast, vomiting was more prevalent, more severe, and occurred more often in DG than IG. Thus, characteristics of vomiting differ in IG vs DG.