We propose quantum versions of the Bell-Ziv-Zakai lower bounds for the error in multiparameter estimation. As an application, we consider measurement of a time-varying optical phase signal with ...stationary Gaussian prior statistics and a power-law spectrum ∼1/|ω|p , with p>1 . With no other assumptions, we show that the mean-square error has a lower bound scaling as 1/N2(p−1)/(p+1) , where N is the time-averaged mean photon flux. Moreover, we show that this scaling is achievable by sampling and interpolation, for any p>1 . This bound is thus a rigorous generalization of the Heisenberg limit, for measurement of a single unknown optical phase, to a stochastically varying optical phase.
Demonstrating nonclassical effects over longer and longer distances is essential for both quantum technology and fundamental science. The main challenge is the loss of photons during propagation, ...because considering only those cases where photons are detected opens a “detection loophole” in security whenever parties or devices are untrusted. Einstein-Podolsky-Rosen steering is equivalent to an entanglement-verification task in which one party (device) is untrusted. We derive arbitrarily loss-tolerant tests, enabling us to perform a detection-loophole-free demonstration of Einstein-Podolsky-Rosen steering with parties separated by a coiled 1-km-long optical fiber, with a total loss of 8.9 dB (87%).
Spontaneous fluctuations of resting state functional MRI (rsfMRI) have been widely used to understand the macro-connectome of the human brain. However, these fluctuations are not synchronized among ...subjects, which leads to limitations and makes utilization of first-level model-based methods challenging. Considering this limitation of rsfMRI data in the time domain, we propose to transfer the spatiotemporal information of the rsfMRI data to another domain, the connectivity domain, in which each value represents the same effect across subjects. Using a set of seed networks and a connectivity index to calculate the functional connectivity for each seed network, we transform data into the connectivity domain by generating connectivity weights for each subject. Comparison of the two domains using a data-driven method suggests several advantages in analyzing data using data-driven methods in the connectivity domain over the time domain. We also demonstrate the feasibility of applying model-based methods in the connectivity domain, which offers a new pathway for the use of first-level model-based methods on rsfMRI data. The connectivity domain, furthermore, demonstrates a unique opportunity to perform first-level feature-based data-driven and model-based analyses. The connectivity domain can be constructed from any technique that identifies sets of features that are similar across subjects and can greatly help researchers in the study of macro-connectome brain function by enabling us to perform a wide range of model-based and data-driven approaches on rsfMRI data, decreasing susceptibility of analysis techniques to parameters that are not related to brain connectivity information, and evaluating both static and dynamic functional connectivity of the brain from a new perspective.
Therapeutic use of psilocybin has become a focus of recent international research, with preliminary data showing promise to address a range of treatment-resistant mental health conditions. However, ...use of psilocybin as a healing entheogen has a long history through traditional consumption of mushrooms from the genus Psilocybe. The forthcoming adoption of new psilocybin-assisted therapeutic practices necessitates identification of preferred sources of psilocybin; consequently, comprehensive understanding of psilocybin-containing fungi is fundamental to consumer safety. Here we examine psilocybin producing fungi, discuss their biology, diversity, and ethnomycological uses. We also review recent work focused on elucidation of psilocybin biosynthetic production pathways, especially those from the genus Psilocybe, and their evolutionary history. Current research on psilocybin therapies is discussed, and recommendations for necessary future mycological research are outlined.
•Psilocybin is a naturally derived fungal medicine with potential to treat mental health.•There are hundreds of species belongings to at least 7 genera of psilocybin producing fungi.•Psilocybin is produced by the Psi genes in an ∼11–22 kilobase genomic region.•Psilocybin mushrooms have been used by the Mazatecs, Mixes, Nahuatls, Zapotecs and others.•The Nagoya protocol protects genetic resources and traditional knowledge, and pertains to psilocybin fungi.
An estimated 4% to 7% of the population will develop a clinically significant thyroid nodule during their lifetime. In many cases, preoperative diagnoses by needle biopsy are inconclusive. Thus, ...there is a clear need for improved diagnostic tests to distinguish malignant from benign thyroid tumors. The recent development of high-throughput molecular analytic techniques should allow the rapid evaluation of new diagnostic markers. However, researchers are faced with an overwhelming number of potential markers from numerous thyroid cancer expression profiling studies.
To address this challenge, we have carried out a comprehensive meta-review of thyroid cancer biomarkers from 21 published studies. A gene ranking system that considers the number of comparisons in agreement, total number of samples, average fold-change and direction of change was devised.
We have observed that genes are consistently reported by multiple studies at a highly significant rate (P < .05). Comparison with a meta-analysis of studies reprocessed from raw data showed strong concordance with our method.
Our approach represents a useful method for identifying consistent gene expression markers when raw data are unavailable. A review of the top 12 candidates revealed well known thyroid cancer markers such as MET, TFF3, SERPINA1, TIMP1, FN1, and TPO as well as relatively novel or uncharacterized genes such as TGFA, QPCT, CRABP1, FCGBP, EPS8 and PROS1. These candidates should help to develop a panel of markers with sufficient sensitivity and specificity for the diagnosis of thyroid tumors in a clinical setting.
Precise interferometric measurement is vital to many scientific and technological applications. Using quantum entanglement allows interferometric sensitivity that surpasses the shot-noise limit ...(SNL). To date, experiments demonstrating entanglement-enhanced sub-SNL interferometry, and most theoretical treatments, have addressed the goal of increasing signal-to-noise ratios. This is suitable for phase-sensing--detecting small variations about an already known phase. However, it is not sufficient for ab initio phase-estimation--making a self-contained determination of a phase that is initially completely unknown within the interval 0, 2π). Both tasks are important, but not equivalent. To move from the sensing regime to the ab initio estimation regime requires a non-trivial phase-estimation algorithm. Here, we implement a 'bottom-up' approach, optimally utilizing the available entangled photon states, obtained by post-selection. This enables us to demonstrate sub-SNL ab initio estimation of an unknown phase by entanglement-enhanced optical interferometry.
Direct chemical profiling of biological tissues, including metastatic human‐liver adenocarcinoma, was carried out by using mass spectrometry under ambient conditions. Desorption electrospray ...ionization revealed enhanced signals from sphingolipids and increased unsaturation levels of the phospholipids in the tumor region of the tissue (see picture).
•Academic surgeons are mentors, educators, researchers, and take care of patients.•There is a continuum of scholarly activity that surgeons may participate in.•Research experience during surgical ...residency is an important part of the training.•Surgeons have characteristics that make them well suited for conducting research.•Conducting research helps surgeons keep up and provide state of the art care.
This paper builds and tests a holistic model of risk in organizations. Using structural equations modeling, we disaggregated risk into two distinct components, managerial risk taking and income ...stream uncertainty, or organizational risk. This allowed us to identify an array of organizational and environmental antecedents that have either been examined in isolation or neglected in previous studies about risk. Our results suggest that both organizational and environmental factors promote risk taking. Further, we found strong support for behavioral theory of the firm and agency theory on risk but not upper echelons theory. Our data also suggest that environmental characteristics have a negligible direct effect on organizational risk. Instead, the environment's impact on risk occurs primarily through managerial choices.
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