DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets

One of the grand challenges of cell biology is inferring the gene regulatory network (GRN) which describes interactions between genes and their products that control gene expression and cellular function. We can treat this as a causal discovery problem but with two non-standard challenges: (1) regulatory networks are inherently cyclic so we should not model a GRN as a directed acyclic graph (DAG), and (2) observations have significant measurement noise, so for typical sample sizes there will always be a large equivalence class of graphs that are likely given the data, and we want methods that capture this uncertainty. Existing methods either focus on challenge (1), identifying cyclic structure from dynamics, or on challenge (2) learning complex Bayesian posteriors over DAGs, but not both. In this paper we leverage the fact that it is possible to estimate the "velocity" of gene expression with RNA velocity techniques to develop an approach that addresses both challenges. Because we have access to velocity information, we can treat the Bayesian structure learning problem as a problem of sparse identification of a dynamical system, capturing cyclic feedback loops through time. Since our objective is to model uncertainty over discrete structures, we leverage Generative Flow Networks (GFlowNets) to estimate the posterior distribution over the combinatorial space of possible sparse dependencies. Our results indicate that our method learns posteriors that better encapsulate the distributions of cyclic structures compared to counterpart state-of-the-art Bayesian structure learning approaches

A preexisting rare PIK3CA e545k subpopulation confers clinical resistance to MEK plus CDK4/6 inhibition in NRAS melanoma and is dependent on S6K1 signaling

Combined MEK and CDK4/6 inhibition (MEKi + CDK4i) has shown promising clinical outcomes in patients with NRAS- mutant melanoma. Here, we interrogated longitudinal biopsies from a patient who initially responded to MEKi + CDK4i therapy but subsequently developed resistance. Whole-exome sequencing and functional validation identified an acquired PIK3CA E545K mutation as conferring drug resistance. We demonstrate that PIK3CA E545K preexisted in a rare subpopulation that was missed by both clinical and research testing, but was revealed upon multiregion sampling due to PIK3CA E545K being nonuniformly distributed. This resistant population rapidly expanded after the initiation of MEKi + CDK4i therapy and persisted in all successive samples even after immune checkpoint therapy and distant metastasis. Functional studies identified activated S6K1 as both a key marker and specific therapeutic vulnerability downstream of PIK3CA E545K -induced resistance. These results demonstrate that difficult-to-detect preexisting resistance mutations may exist more often than previously appreciated and also posit S6K1 as a common downstream therapeutic nexus for the MAPK, CDK4/6, and PI3K pathways. SIGNIFICANCE: We report the first characterization of clinical acquired resistance to MEKi + CDK4i, identifying a rare preexisting PIK3CA E545K subpopulation that expands upon therapy and exhibits drug resistance. We suggest that single-region pretreatment biopsy is insufficient to detect rare, spatially segregated drug-resistant subclones. Inhibition of S6K1 is able to resensitize PIK3CA E545K -expressing NRAS-mutant melanoma cells to MEKi + CDK4i. © 2018 AAC

Efficacy of first-line doxorubicin and ifosfamide in myxoid liposarcoma

<p>Abstract</p> <p>Background</p> <p>Myxoid liposarcoma (MLS) is a soft tissue sarcoma with adipocytic differentiation characterized by a unique chromosome rearrangement, t(12;16)(q13;p11). The exact efficacy of chemotherapy in MLS has not been clearly established.</p> <p>Patients and methods</p> <p>We retrospectively analyzed the records of 37 histologically confirmed MLS patients who were treated at the University of Texas MD Anderson Cancer Center from January 2000 to December 2009 with doxorubicin 75-90 mg/m²over 72 hours combined with ifosfamide 10 gm/m²in the first-line setting. Response was assessed using RECIST and Choi criteria. The Kaplan-Meier method and log-rank test was used to estimate clinical outcomes.</p> <p>Results</p> <p>The median follow-up period was 50.1 months. The overall response rates were 43.2% using RECIST and 86.5% using the Choi criteria. The 5-year disease-free survival rate was 90% for patients with resectable tumors. Median time to progression and overall survival time for the advanced-disease group were 23 and 31.1 months, respectively.</p> <p>Conclusion</p> <p>Our study demonstrates that doxorubicin-ifosfamide combination therapy has a role in the treatment of MLS. The Choi criteria may be more sensitive in evaluating response to chemotherapy in MLS.</p

Fast Flux-Activated Leakage Reduction for Superconducting Quantum Circuits

Quantum computers will require quantum error correction to reach the low error rates necessary for solving problems that surpass the capabilities of conventional computers. One of the dominant errors limiting the performance of quantum error correction codes across multiple technology platforms is leakage out of the computational subspace arising from the multi-level structure of qubit implementations. Here, we present a resource-efficient universal leakage reduction unit for superconducting qubits using parametric flux modulation. This operation removes leakage down to our measurement accuracy of $7\cdot 10^{-4}$ in approximately $50\, \mathrm{ns}$ with a low error of $2.5(1)\cdot 10^{-3}$ on the computational subspace, thereby reaching durations and fidelities comparable to those of single-qubit gates. We demonstrate that using the leakage reduction unit in repeated weight-two stabilizer measurements reduces the total number of detected errors in a scalable fashion to close to what can be achieved using leakage-rejection methods which do not scale. Our approach does neither require additional control electronics nor on-chip components and is applicable to both auxiliary and data qubits. These benefits make our method particularly attractive for mitigating leakage in large-scale quantum error correction circuits, a crucial requirement for the practical implementation of fault-tolerant quantum computation

Vimentin Is a Novel Anti-Cancer Therapeutic Target; Insights from In Vitro and In Vivo Mice Xenograft Studies

BACKGROUND:Vimentin is a ubiquitous mesenchymal intermediate filament supporting mechano-structural integrity of quiescent cells while participating in adhesion, migration, survival, and cell signaling processes via dynamic assembly/disassembly in activated cells. Soft tissue sarcomas and some epithelial cancers exhibiting "epithelial to mesenchymal transition" phenotypes express vimentin. Withaferin-A, a naturally derived bioactive compound, may molecularly target vimentin, so we sought to evaluate its effects on tumor growth in vitro and in vivo thereby elucidating the role of vimentin in drug-induced responses. METHODS AND FINDINGS:Withaferin-A elicited marked apoptosis and vimentin cleavage in vimentin-expressing tumor cells but significantly less in normal mesenchymal cells. This proapoptotic response was abrogated after vimentin knockdown or by blockade of caspase-induced vimentin degradation via caspase inhibitors or overexpression of mutated caspase-resistant vimentin. Pronounced anti-angiogenic effects of Withaferin-A were demonstrated, with only minimal effects seen in non-proliferating endothelial cells. Moreover, Withaferin-A significantly blocked soft tissue sarcoma growth, local recurrence, and metastasis in a panel of soft tissue sarcoma xenograft experiments. Apoptosis, decreased angiogenesis, and vimentin degradation were all seen in Withaferin-A treated specimens. CONCLUSIONS:In light of these findings, evaluation of Withaferin-A, its analogs, or other anti-vimentin therapeutic approaches in soft tissue sarcoma and "epithelial to mesenchymal transition" clinical contexts is warranted

Patterns within Patterns within the Smart Living Experience

Modern technology is increasingly being employed to create a “smart” living experience. These “smart” technology entities are producing copious of amounts data, which in turn rely on increased storage, distribution and computation capacity to manage the data. Depending on the scenario, the diversity of piecemeal solutions almost reflects the diversity of problems they address. But some solutions can be reapplied. In the field of computing, design patterns can provide a general, reusable solution to commonly recurring problems within a given context through software design. This work seeks to determine the core elements of a technology-independent design pattern format and an open software framework can be developed to capture, share and redeploy existing successful and reusable strategies for commonly encountered smart environment use cases. Applying in areas such as assistive technology, energy management and environmental monitoring. The underpinning notion of this paper is to introduce “how, where and why” a rule set based in “design pattern” format could contribute to describe a general “understanding” of given cases in the smart environment domain, as well as allow different processes to collaborate with each other

The time-scales probed by star formation rate indicators for realistic, bursty star formation histories from the FIRE simulations

Understanding the rate at which stars form is central to studies of galaxy formation. Observationally, the star formation rates (SFRs) of galaxies are measured using the luminosity in different frequency bands, often under the assumption of a time-steady SFR in the recent past. We use star formation histories (SFHs) extracted from cosmological simulations of star-forming galaxies from the FIRE project to analyze the time-scales to which the H${\alpha}$ and far-ultraviolet (FUV) continuum SFR indicators are sensitive. In these simulations, the SFRs are highly time variable for all galaxies at high redshift, and continue to be bursty to z=0 in dwarf galaxies. When FIRE SFHs are partitioned into their bursty and time-steady phases, the best-fitting FUV time-scale fluctuates from its ~10 Myr value when the SFR is time-steady to >~100 Myr immediately following particularly extreme bursts of star formation during the bursty phase. On the other hand, the best-fitting averaging time-scale for H${\alpha}$ is generally insensitive to the SFR variability in the FIRE simulations and remains ~5 Myr at all times. These time-scales are shorter than the 100 Myr and 10 Myr time-scales sometimes assumed in the literature for FUV and H${\alpha}$, respectively, because while the FUV emission persists for stellar populations older than 100 Myr, the time-dependent luminosities are strongly dominated by younger stars. Our results confirm that the ratio of SFRs inferred using H${\alpha}$ vs. FUV can be used to probe the burstiness of star formation in galaxies.Comment: 14 pages, 10 figures, accepted to MNRA