Clinical Outcomes for BRCA Pathogenic Variant Carriers With Breast Cancer Undergoing Breast Conservation.

Importance: Although most women with BRCA-associated breast cancer choose bilateral mastectomy, current guidelines support breast-conserving therapy as an option. As the indications for genetic testing expand and targeted therapies emerge, understanding the outcomes of breast-conserving therapy in the population of patients choosing breast conservation is important. Objective: To describe the clinical outcomes of women with BRCA-associated breast cancer who were treated with breast-conserving therapy, including the risks of ipsilateral and contralateral cancer events and bilateral mastectomy-free survival. Design, Setting, and Participants: This cohort study conducted at a single-institution academic national comprehensive cancer center included 172 women identified from a prospectively maintained database who had pathogenic BRCA1/2 variants and were treated with breast-conserving therapy from January 1, 1977, to December 31, 2021. Main Outcomes and Measures: Clinical and pathologic characteristics for patients with BRCA1 and BRCA2 were compared, and estimates of overall survival, bilateral mastectomy-free survival, distant disease-free survival, risk of ipsilateral breast cancer, and risk of contralateral cancer were computed. Results: The cohort included 172 women (mean [SD] age, 47.1 [11.7] years), with 42 (24.4%) receiving a diagnosis of breast cancer prior to 40 years of age. Compared with BRCA2 variant carriers (80 [46.5%]), women with BRCA1 variants (92 [53.5%]) were younger at breast cancer diagnosis and tended to have more advanced tumors, which were more likely to be hormone receptor negative and higher grade. At a median follow-up of 11.8 years (IQR, 5.7-18.2 years), estimates of 10-year survival and risk were: overall survival, 88.5% (95% CI, 83.1%-94.2%); bilateral mastectomy-free survival, 70.7% (95% CI, 63.3%-78.9%); risk of an ipsilateral breast cancer event, 12.2% (95% CI, 5.8%-18.2%); and risk of contralateral cancer, 21.3% (95% CI, 13.3%-28.6%). Risks continued to increase after 10 years of follow-up. Conclusions and Relevance: In this cohort study, although women with breast cancer and pathogenic BRCA1/2 variants treated with breast-conserving therapy had above-average risks of ipsilateral and contralateral breast cancer events, most did not have another cancer event and remained bilateral mastectomy free. These findings may be useful for informing patients with BRCA variants choosing breast conservation.

CAManim: Animating end-to-end network activation maps.

Deep neural networks have been widely adopted in numerous domains due to their high performance and accessibility to developers and application-specific end-users. Fundamental to image-based applications is the development of Convolutional Neural Networks (CNNs), which possess the ability to automatically extract features from data. However, comprehending these complex models and their learned representations, which typically comprise millions of parameters and numerous layers, remains a challenge for both developers and end-users. This challenge arises due to the absence of interpretable and transparent tools to make sense of black-box models. There exists a growing body of Explainable Artificial Intelligence (XAI) literature, including a collection of methods denoted Class Activation Maps (CAMs), that seek to demystify what representations the model learns from the data, how it informs a given prediction, and why it, at times, performs poorly in certain tasks. We propose a novel XAI visualization method denoted CAManim that seeks to simultaneously broaden and focus end-user understanding of CNN predictions by animating the CAM-based network activation maps through all layers, effectively depicting from end-to-end how a model progressively arrives at the final layer activation. Herein, we demonstrate that CAManim works with any CAM-based method and various CNN architectures. Beyond qualitative model assessments, we additionally propose a novel quantitative assessment that expands upon the Remove and Debias (ROAD) metric, pairing the qualitative end-to-end network visual explanations assessment with our novel quantitative "yellow brick ROAD" assessment (ybROAD). This builds upon prior research to address the increasing demand for interpretable, robust, and transparent model assessment methodology, ultimately improving an end-user's trust in a given model's predictions. Examples and source code can be found at: https://omni-ml.github.io/pytorch-grad-cam-anim/.

Combination of Searches for Resonant Higgs Boson Pair Production Using pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector.

A combination of searches for a new resonance decaying into a Higgs boson pair is presented, using up to 139 fb^{-1} of pp collision data at sqrt[s]=13 TeV recorded with the ATLAS detector at the LHC. The combination includes searches performed in three decay channels: bb[over ¯]bb[over ¯], bb[over ¯]τ^{+}τ^{-}, and bb[over ¯]γγ. No excess above the expected Standard Model background is observed and upper limits are set at the 95% confidence level on the production cross section of Higgs boson pairs originating from the decay of a narrow scalar resonance with mass in the range 251 GeV-5 TeV. The observed (expected) limits are in the range 0.96-600 fb (1.2-390 fb). The limits are interpreted in the type-I two-Higgs-doublet model and the minimal supersymmetric standard model, and constrain parameter space not previously excluded by other searches.

Azimuthal Angle Correlations of Muons Produced via Heavy-Flavor Decays in 5.02 TeV Pb+Pb and pp Collisions with the ATLAS Detector.

Angular correlations between heavy quarks provide a unique probe of the quark-gluon plasma created in ultrarelativistic heavy-ion collisions. Results are presented of a measurement of the azimuthal angle correlations between muons originating from semileptonic decays of heavy quarks produced in 5.02 TeV Pb+Pb and pp collisions at the LHC. The muons are measured with transverse momenta and pseudorapidities satisfying p_{T}^{µ}>4 GeV and |η^{µ}|<2.4, respectively. The distributions of azimuthal angle separation Δϕ for muon pairs having pseudorapidity separation |Δη|>0.8, are measured in different Pb+Pb centrality intervals and compared to the same distribution measured in pp collisions at the same center-of-mass energy. Results are presented separately for muon pairs with opposite-sign charges, same-sign charges, and all pairs. A clear peak is observed in all Δϕ distributions at Δϕ∼π, consistent with the parent heavy-quark pairs being produced via hard-scattering processes. The widths of that peak, characterized using Cauchy-Lorentz fits to the Δϕ distributions, are found to not vary significantly as a function of Pb+Pb collision centrality and are similar for pp and Pb+Pb collisions. This observation will provide important constraints on theoretical descriptions of heavy-quark interactions with the quark-gluon plasma.

Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study.

BACKGROUND: Current postpartum hemorrhage (PPH) risk stratification is based on traditional statistical models or expert opinion. Machine learning could optimize PPH prediction by allowing for more complex modeling. OBJECTIVE: We sought to improve PPH prediction and compare machine learning and traditional statistical methods. METHODS: We developed models using the Consortium for Safe Labor data set (2002-2008) from 12 US hospitals. The primary outcome was a transfusion of blood products or PPH (estimated blood loss of ≥1000 mL). The secondary outcome was a transfusion of any blood product. Fifty antepartum and intrapartum characteristics and hospital characteristics were included. Logistic regression, support vector machines, multilayer perceptron, random forest, and gradient boosting (GB) were used to generate prediction models. The area under the receiver operating characteristic curve (ROC-AUC) and area under the precision/recall curve (PR-AUC) were used to compare performance. RESULTS: Among 228,438 births, 5760 (3.1%) women had a postpartum hemorrhage, 5170 (2.8%) had a transfusion, and 10,344 (5.6%) met the criteria for the transfusion-PPH composite. Models predicting the transfusion-PPH composite using antepartum and intrapartum features had the best positive predictive values, with the GB machine learning model performing best overall (ROC-AUC=0.833, 95% CI 0.828-0.838; PR-AUC=0.210, 95% CI 0.201-0.220). The most predictive features in the GB model predicting the transfusion-PPH composite were the mode of delivery, oxytocin incremental dose for labor (mU/minute), intrapartum tocolytic use, presence of anesthesia nurse, and hospital type. CONCLUSIONS: Machine learning offers higher discriminability than logistic regression in predicting PPH. The Consortium for Safe Labor data set may not be optimal for analyzing risk due to strong subgroup effects, which decreases accuracy and limits generalizability.

Observing the Clinical Course of Duchenne Muscular Dystrophy in Medicaid Real-World Healthcare Data.

INTRODUCTION: Duchenne muscular dystrophy (DMD) is a rare, severe progressive neuromuscular disease. Health insurance claims allow characterization of population-level real-world outcomes, based on observed healthcare resource use. An analysis of data specific to those with Medicaid insurance is presently unavailable. The objective was to describe the real-world clinical course of DMD based on claims data from Medicaid-insured individuals in the USA. METHODS: Individuals with DMD were identified from the MarketScan Multi-State Medicaid datasets (2013-2018). Diagnosis and procedure codes from healthcare claims were used to characterize the occurrence of DMD-relevant clinical observations; categories were scoliosis, cardiovascular-related, respiratory and severe respiratory-related, and neurologic/neuropsychiatric. Age-restricted analyses were conducted to focus on the ages at which DMD-relevant clinical observations were more likely to be captured, and to better understand the impact of both age and follow-up time. RESULTS: Of 2007 patients with DMD identified, median (interquartile range) age at index was 14 (9-20) years, and median follow-up was 3.1 (1.6-4.7) years. Neurologic and neuropsychiatric observations were most frequently identified, among 49.3% of the cohort; followed by cardiovascular (48.5%), respiratory (38.1%), scoliosis (36.3%), and severe respiratory (25.0%). Prevalence estimates for each category were higher when analyzed within age-restricted subgroups; and increased as follow-up time increased. CONCLUSIONS: This study is the first to use diagnosis and procedure codes from real-world Medicaid claims to document the clinical course in DMD. Findings were consistent with previously published estimates from commercially insured populations and clinical registries; and contribute to the expanding body of real-world evidence around clinical progression of patients with DMD.

Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector.

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13 TeV and corresponding to an integrated luminosity of 137 fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be µ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst) pb.

A Facile Method to Append a Bio-ID Tag to Endogenous Mutant Kras Alleles.

KRAS mutations occur in approximately ~50% of colorectal cancers (CRCs) and are associated with poor prognosis and resistance to therapy. While these most common mutations found at amino acids G12, G13, Q61, and A146 have long been considered oncogenic drivers of CRC, emerging clinical data suggest that each mutation may possess different biological functions, resulting in varying consequences in oncogenesis. Currently, the mechanistic underpinnings associated with each allelic variation remain unclear. Elucidating the unique effectors of each KRAS mutant could both increase the understanding of KRAS biology and provide a basis for allele-specific therapeutic opportunities. Biotinylation identification (BioID) is a method to label and identify proteins located in proximity of a protein of interest. These proteins are captured through the strong interaction between the biotin label and streptavidin bead and subsequently identified by mass spectrometry. Here, we developed a protocol using CRISPR-mediated gene editing to generate endogenous BioID2-tagged KrasG12D and KrasG12V isogenic murine colon epithelial cell lines to identify unique protein proximity partners by BioID.

Neighborhood disadvantage is associated with working memory and hippocampal volumes among older adults.

It is not well understood how neighborhood disadvantage is associated with specific domains of cognitive function and underlying brain health within older adults. Thus, the objective was to examine associations between neighborhood disadvantage, brain health, and cognitive performance, and examine whether associations were more pronounced among women. The study included 136 older adults who underwent cognitive testing and MRI. Neighborhood disadvantage was characterized using the Area Deprivation Index (ADI). Descriptive statistics, bivariate correlations, and multiple regressions were run. Multiple regressions, adjusted for age, sex, education, and depression, showed that higher ADI state rankings (greater disadvantage) were associated with poorer working memory performance (p < .01) and lower hippocampal volumes (p < .01), but not total, frontal, and white matter lesion volumes, nor visual and verbal memory performance. There were no significant sex interactions. Findings suggest that greater neighborhood disadvantage may play a role in working memory and underlying brain structure.

KRAS mutation-selective requirement for ACSS2 in colorectal adenoma formation.

Oncogenic KRAS mutations are prevalent in colorectal cancer (CRC) and are associated with poor prognosis and resistance to therapy. There is a substantial diversity of KRAS mutant alleles observed in CRC. Emerging clinical and experimental analysis of common KRAS mutations suggest that each mutation differently influences the clinical properties of a disease and response to therapy. Although there is some evidence to suggest biological differences between mutant KRAS alleles, these are yet to be fully elucidated. One approach to study allelic variation involves the use of isogenic cell lines that express different endogenous Kras mutants. Here, we generated Kras isogenic Apc-/- mouse colon epithelial cell lines using CRISPR-driven genome editing by altering the original G12D Kras allele to G12V, G12R, or G13D. We utilized these cell lines to perform transcriptomic and proteomic analysis to compare different signaling properties between these mutants. Both screens indicate significant differences in pathways relating to cholesterol and lipid regulation that we validated with targeted metabolomic measurements and isotope tracing. We found that these processes are upregulated in G12V lines through increased expression of nuclear SREBP1 and higher activation of mTORC1. G12V cells showed higher expression of ACSS2 and ACSS2 inhibition sensitized G12V cells to MEK inhibition. Finally, we found that ACSS2 plays a crucial role early in the development of G12V mutant tumors, in contrast to G12D mutant tumors. These observations highlight differences between KRAS mutant cell lines in their signaling properties. Further exploration of these pathways may prove to be valuable for understanding how specific KRAS mutants function, and identification of novel therapeutic opportunities in CRC.

mTORC1 is required for differentiation of germline stem cells in the Drosophila melanogaster testis.

Metabolism participates in the control of stem cell function and subsequent maintenance of tissue homeostasis. How this is achieved in the context of adult stem cell niches in coordination with other local and intrinsic signaling cues is not completely understood. The Target of Rapamycin (TOR) pathway is a master regulator of metabolism and plays essential roles in stem cell maintenance and differentiation. In the Drosophila male germline, mTORC1 is active in germline stem cells (GSCs) and early germ cells. Targeted RNAi-mediated downregulation of mTor in early germ cells causes a block and/or a delay in differentiation, resulting in an accumulation of germ cells with GSC-like features. These early germ cells also contain unusually large and dysfunctional autolysosomes. In addition, downregulation of mTor in adult male GSCs and early germ cells causes non-autonomous activation of mTORC1 in neighboring cyst cells, which correlates with a disruption in the coordination of germline and somatic differentiation. Our study identifies a previously uncharacterized role of the TOR pathway in regulating male germline differentiation.

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13 TeV with the ATLAS Detector.

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb^{-1} of pp collisions at sqrt[s]=13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e,µ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector.

ATLAS measured the centrality dependence of the dijet yield using 165 nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16 TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Observation of WZγ Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector.

This Letter reports the observation of WZγ production and a measurement of its cross section using 140.1±1.2 fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The WZγ production cross section, with both the W and Z bosons decaying leptonically, pp→WZγ→ℓ^{'}^{±}νℓ^{+}ℓ^{-}γ (ℓ^{(^{'})}=e, µ), is measured in a fiducial phase-space region defined such that the leptons and the photon have high transverse momentum and the photon is isolated. The cross section is found to be 2.01±0.30(stat)±0.16(syst) fb. The corresponding standard model predicted cross section calculated at next-to-leading order in perturbative quantum chromodynamics and at leading order in the electroweak coupling constant is 1.50±0.06 fb. The observed significance of the WZγ signal is 6.3σ, compared with an expected significance of 5.0σ.

Unique vulnerability of RAC1-mutant melanoma to combined inhibition of CDK9 and immune checkpoints.

RAC1P29S is the third most prevalent hotspot mutation in sun-exposed melanoma. RAC1 alterations in cancer are correlated with poor prognosis, resistance to standard chemotherapy, and insensitivity to targeted inhibitors. Although RAC1P29S mutations in melanoma and RAC1 alterations in several other cancers are increasingly evident, the RAC1-driven biological mechanisms contributing to tumorigenesis remain unclear. Lack of rigorous signaling analysis has prevented identification of alternative therapeutic targets for RAC1P29S-harboring melanomas. To investigate the RAC1P29S-driven effect on downstream molecular signaling pathways, we generated an inducible RAC1P29S expression melanocytic cell line and performed RNA-sequencing (RNA-seq) coupled with multiplexed kinase inhibitor beads and mass spectrometry (MIBs/MS) to establish enriched pathways from the genomic to proteomic level. Our proteogenomic analysis identified CDK9 as a potential new and specific target in RAC1P29S-mutant melanoma cells. In vitro, CDK9 inhibition impeded the proliferation of in RAC1P29S-mutant melanoma cells and increased surface expression of PD-L1 and MHC Class I proteins. In vivo, combining CDK9 inhibition with anti-PD-1 immune checkpoint blockade significantly inhibited tumor growth only in melanomas that expressed the RAC1P29S mutation. Collectively, these results establish CDK9 as a novel target in RAC1-driven melanoma that can further sensitize the tumor to anti-PD-1 immunotherapy.

Measurement of Suppression of Large-Radius Jets and Its Dependence on Substructure in Pb+Pb Collisions at sqrt[s_{NN}]=5.02 TeV with the ATLAS Detector.

This letter presents a measurement of the nuclear modification factor of large-radius jets in sqrt[s_{NN}]=5.02 TeV Pb+Pb collisions by the ATLAS experiment. The measurement is performed using 1.72 nb^{-1} and 257 pb^{-1} of Pb+Pb and pp data, respectively. The large-radius jets are reconstructed with the anti-k_{t} algorithm using a radius parameter of R=1.0, by reclustering anti-k_{t} R=0.2 jets, and are measured over the transverse momentum (p_{T}) kinematic range of 158

Observation of Single-Top-Quark Production in Association with a Photon Using the ATLAS Detector.

This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139 fb^{-1} of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688±23(stat) _{-71}^{+75}(syst) fb, to be compared with the standard model prediction of 515_{-42}^{+36} fb at next-to-leading order in QCD.

Measurement of the Sensitivity of Two-Particle Correlations in pp Collisions to the Presence of Hard Scatterings.

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the "ridge"-i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities-and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at sqrt[s]=13 TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8 pb^{-1}, in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v_{2}, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

Observation of the γγ→ττ Process in Pb+Pb Collisions and Constraints on the τ-Lepton Anomalous Magnetic Moment with the ATLAS Detector.

This Letter reports the observation of τ-lepton-pair production in ultraperipheral lead-lead collisions Pb+Pb→Pb(γγ→ττ)Pb and constraints on the τ-lepton anomalous magnetic moment a_{τ}. The dataset corresponds to an integrated luminosity of 1.44 nb^{-1} of LHC Pb+Pb collisions at sqrt[s_{NN}]=5.02 TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a τ-lepton decay, an electron or charged-particle track(s) from the other τ-lepton decay, little additional central-detector activity, and no forward neutrons. The γγ→ττ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations and a signal strength of µ_{ττ}=1.03_{-0.05}^{+0.06} assuming the standard model value for a_{τ}. To measure a_{τ}, a template fit to the muon transverse-momentum distribution from τ-lepton candidates is performed, using a dimuon (γγ→µµ) control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for a_{τ} is -0.057