Dynamics of immersed molecules in superfluids

The dynamics of a molecule immersed in a superfluid medium are considered. Results are derived using a classical hydrodynamic approach followed by canonical quantization. The classical model, a rigid body immersed in incompressible fluid, permits a thorough analysis; its effective Hamiltonian generalizes the usual rigid-rotor Hamiltonian. In contrast to the free rigid rotor, the immersed body is shown to have chaotic dynamics. Quantization of the classical model leads to new and experimentally verifiable features. It is shown, for instance, that chiral molecules can behave as "quantum propellers": the rotational-translational coupling induced by the superfluid leads to a nonzero linear momentum in the ground state. Hydrogen peroxide is a strong candidate for experimental detection of this effect. The signature is a characteristic splitting of rotational absorption lines. The 1_{01} --> 1_{10} line in hydrogen peroxide, for example, is predicted to split into three lines separated by as much as 0.01 cm^{-1}, which is about the experimental linewidth.Comment: 10 pages, 3 figure

Chromosomal instability in untreated primary prostate cancer as an indicator of metastatic potential.

BackgroundMetastatic prostate cancer (PC) is highly lethal. The ability to identify primary tumors capable of dissemination is an unmet need in the quest to understand lethal biology and improve patient outcomes. Previous studies have linked chromosomal instability (CIN), which generates aneuploidy following chromosomal missegregation during mitosis, to PC progression. Evidence of CIN includes broad copy number alterations (CNAs) spanning > 300 base pairs of DNA, which may also be measured via RNA expression signatures associated with CNA frequency. Signatures of CIN in metastatic PC, however, have not been interrogated or well defined. We examined a published 70-gene CIN signature (CIN70) in untreated and castration-resistant prostate cancer (CRPC) cohorts from The Cancer Genome Atlas (TCGA) and previously published reports. We also performed transcriptome and CNA analysis in a unique cohort of untreated primary tumors collected from diagnostic prostate needle biopsies (PNBX) of localized (M0) and metastatic (M1) cases to determine if CIN was linked to clinical stage and outcome.MethodsPNBX were collected from 99 patients treated in the VA Greater Los Angeles (GLA-VA) Healthcare System between 2000 and 2016. Total RNA was extracted from high-grade cancer areas in PNBX cores, followed by RNA sequencing and/or copy number analysis using OncoScan. Multivariate logistic regression analyses permitted calculation of odds ratios for CIN status (high versus low) in an expanded GLA-VA PNBX cohort (n = 121).ResultsThe CIN70 signature was significantly enriched in primary tumors and CRPC metastases from M1 PC cases. An intersection of gene signatures comprised of differentially expressed genes (DEGs) generated through comparison of M1 versus M0 PNBX and primary CRPC tumors versus metastases revealed a 157-gene "metastasis" signature that was further distilled to 7-genes (PC-CIN) regulating centrosomes, chromosomal segregation, and mitotic spindle assembly. High PC-CIN scores correlated with CRPC, PC-death and all-cause mortality in the expanded GLA-VA PNBX cohort. Interestingly, approximately 1/3 of M1 PNBX cases exhibited low CIN, illuminating differential pathways of lethal PC progression.ConclusionsMeasuring CIN in PNBX by transcriptome profiling is feasible, and the PC-CIN signature may identify patients with a high risk of lethal progression at the time of diagnosis

Nutrient Restoration of a Large, Impounded, Ultra-Oligotrophic Western River to Recover Declining Native Fishes

Declines in many fish populations in large, western rivers have been primarily attributed to the anthropogenic reduction of nutrient inputs and subsequent impacts to the food web. The largest known river fertilization program was implemented starting in 2005 on the Kootenai River in northern Idaho to restore resident fisheries. Annual electrofishing surveys were conducted at multiple sites in Idaho and Montana before and during nutrient addition to evaluate assemblage and population-level responses. Although few responses in fish assemblage structure were observed, the addition of liquid ammonium polyphosphate fertilizer (3 μg/L) to the Kootenai River increased fish abundance and biomass over the 20-km stretch of river downstream of the treatment site. Increases were most notable in Largescale Suckers Catostomus macrocheilus, Mountain Whitefish Prosopium williamsoni, and Rainbow Trout Oncorhynchus mykiss populations, although increases in catch and biomass were detected for nearly all fish species. The Kootenai River is approximately 30 times larger in discharge than other rivers that have been experimentally fertilized and provides compelling evidence that the mitigation of nutrient declines in rivers of similar size can result in positive influences on the fish populations where primary and secondary production are limiting growth, survival, and recruitment. However, results from our study also highlight the importance of completing evaluations across varying levels of biological organization (e.g., assemblage and population) and over biologically relevant timeframes

Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy.

Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization

Deep Functional and Molecular Characterization of a High-Risk Undifferentiated Pleomorphic Sarcoma.

Nonrhabdomyosarcoma soft-tissue sarcomas (STSs) are a class of 50+ cancers arising in muscle and soft tissues of children, adolescents, and adults. Rarity of each subtype often precludes subtype-specific preclinical research, leaving many STS patients with limited treatment options should frontline therapy be insufficient. When clinical options are exhausted, personalized therapy assignment approaches may help direct patient care. Here, we report the results of an adult female STS patient with relapsed undifferentiated pleomorphic sarcoma (UPS) who self-drove exploration of a wide array of personalized Clinical Laboratory Improvement Amendments (CLIAs) level and research-level diagnostics, including state of the art genomic, proteomic

Fish Species of Greatest Conservation Need in Wadeable Iowa Streams: Current Status and Effectiveness of Aquatic Gap Program Distribution Models

Effective conservation of fish species of greatest conservation need (SGCN) requires an understanding of species– habitat relationships and distributional trends. Thus, modeling the distribution of fish species across large spatial scales may be a valuable tool for conservation planning. Our goals were to evaluate the status of 10 fish SGCN in wadeable Iowa streams and to test the effectiveness of IowaAquatic Gap Analysis Project (IAGAP) species distribution models. We sampled fish assemblages from 86 wadeable stream segments in the Mississippi River drainage of Iowa during 2009 and 2010 to provide contemporary, independent fish species presence–absence data. The frequencies of occurrence in stream segments where species were historically documented varied from 0.0% for redfin shiner Lythrurus umbratilis to 100.0% for American brook lamprey Lampetra appendix, with a mean of 53.0%, suggesting that the status of Iowa fish SGCN is highly variable. Cohen’s kappa values and other model performance measures were calculated by comparing field-collected presence–absence data with IAGAP model–predicted presences and absences for 12 fish SGCN. Kappa values varied from 0.00 to 0.50, with a mean of 0.15. The models only predicted the occurrences of banded darter Etheostoma zonale, southern redbelly dace Phoxinus erythrogaster, and longnose dace Rhinichthys cataractae more accurately than would be expected by chance. Overall, the accuracy of the twelve models was low, with a mean correct classification rate of 58.3%. Poor model performance probably reflects the difficulties associated with modeling the distribution of rare species and the inability of the large-scale habitat variables used in IAGAP models to explain the variation in fish species occurrences. Our results highlight the importance of quantifying the confidence in species distribution model predictions with an independent data set and the need for long-term monitoring to better understand the distributional trends and habitat associations of fish SGCN