Decision making with belief functions: Compatibility and incompatibility with the sure-thing principle

This article studies situations in which information is ambiguous and only part of it can be probabilized. It is shown that the information can be modeled through belief functions if and only if the nonprobabilizable information is subject to the principles of complete ignorance. Next the representability of decisions by belief functions on outcomes is justified by means of a neutrality axiom. The natural weakening of Savage's sure-thing principle to unambiguous events is examined and its implications for decision making are identified

Depletion of New Neurons by Image Guided Irradiation

Ionizing radiation continues to be a relevant tool in both imaging and the treatment of cancer. Experimental uses of focal irradiation have recently been expanded to studies of new neurons in the adult brain. Such studies have shown cognitive deficits following radiation treatment and raised caution as to possible unintentional effects that may occur in humans. Conflicting outcomes of the effects of irradiation on adult neurogenesis suggest that the effects are either transient or permanent. In this study, we used an irradiation apparatus employed in the treatment of human tumors to assess radiation effects on rat neurogenesis. For subjects we used adult male rats (Sprague-Dawley) under anesthesia. The irradiation beam was directed at the hippocampus, a center for learning and memory, and the site of neurogenic activity in adult brain. The irradiation was applied at a dose-rate 0.6 Gy/min for total single-fraction, doses ranging from 0.5 to 10.0 Gy. The animals were returned to home cages and recovered with no sign of any side effects. The neurogenesis was measured either 1 week or 6 weeks after the irradiation. At 1 week, the number of neuronal progenitors was reduced in a dose-dependent manner with the 50% reduction at 0.78 Gy. The dose–response curve was well fitted by a double exponential suggesting two processes. Examination of the tissue with quantitative immunohistochemistry revealed a dominant low-dose effect on neuronal progenitors resulting in 80% suppression of neurogenesis. This effect was partially reversible, possibly due to compensatory proliferation of the remaining precursors. At higher doses (>5 Gy) there was additional, nearly complete block of neurogenesis without compensatory proliferation. We conclude that notwithstanding the usefulness of irradiation for experimental purposes, the exposure of human subjects to doses often used in radiotherapy treatment could be damaging and cause cognitive impairments

Image-guided fluorescence tomography in head & neck surgical models

Clinical indications for fluorescence-guided surgery continue to expand, and are being spurred by the rapid development of new agents that improve biological targeting.1 There is a corresponding need to develop imaging systems that quantify fluorescence - not only at the tissue surface, but at depth. We have recently described an image-guided fluorescence tomography system that leverages geometric data from intraoperative cone-beam CT and surgical navigation,2 and builds on finite-element method software (NIRFAST) for diffuse optical tomography (DOT).3 DOT systems have most commonly been used for sub-surface inclusions buried within tissue (e.g., breast and neurological tumors). Here, we focus on inclusion models relevant to tumors infiltrating from the mucosal surface (an “iceberg” model), as is most often the case in head and neck cancer, where over 85% of tumors are squamous cell carcinoma.4 This work presents results from simulations, tissue-simulating anatomical phantoms, and animal studies involving infiltrative tumor models. The objective is to characterize system performance across a range of inclusion diameters, depths, and optical properties. For example, Fig. 1 shows a fluorescence reconstruction of a simulated tonsil tumor in an oral cavity phantom. Future clinical studies are necessary to assess in vivo performance and intraoperative workflow. Please click Additional Files below to see the full abstract

Androgen receptor acetylation governs trans activation and MEKK1-induced apoptosis without affecting in vitro sumoylation and trans-repression function

This work was supported by grants from the NIH (R01CA86072 to R.G.P. and R01CA72038-01 to S.A.W.F.) and The Susan Komen Breast Cancer Foundation (to R.G.P.). R.T.H. and E.J. were supported by the Medical Research Council. Y.-G.Y. is supported by grant CA26504 to E. R. Stanley. Work conducted at the Albert Einstein College of Medicine was supported by Cancer Center Core National Institutes of Health grant 5-P30-CA13330-26.The androgen receptor (AR) is a nuclear hormone receptor superfamily member that conveys both traits repression and ligand-dependent trans-activation function. Activation of the AR by dihydrotestosterone (DHT) regulates diverse physiological functions including secondary sexual differentiation in the male and the induction of apoptosis by the JNK kinase, MEKK1. The AR is posttranslationally modified on lysine residues by acetylation and sumoylation. The histone acetylases p300 and P/CAF directly acetylate the AR in vitro at a conserved KLKK motif. To determine the functional properties governed by AR acetylation, point mutations of the KLKK motif that abrogated acetylation were engineered and examined in vitro and in vivo. The AR acetylation site point mutants showed wild-type trans repression of NF-kappaS, AP-1, and Sp1 activity; wild-type sumoylation in vitro; wild-type ligand binding; and ligand-induced conformational changes. However, acetylation-deficient AR mutants were selectively defective in DHT-induced trans activation of androgen-responsive reporter genes and coactivation by SRC1, Ubc9, TIP60, and p300. The AR acetylation site mutant showed 10-fold increased binding of the N-CoR corepressor compared with the AR wild type in the presence of ligand. Furthermore, histone deacetylase 1 (HDAC1) bound the AR both in vivo and in cultured cells and HDAC1 binding to the AR was disengaged in a DHT-dependent manner. MEKK1 induced AR-dependent apoptosis in prostate cancer cells. The AR acetylation mutant was defective in MEKK1-induced apoptosis, suggesting that the conserved AR acetylation site contributes to a pathway governing prostate cancer cellular survival. As AR lysine residue mutations that abrogate acetylation correlate with enhanced binding of the N-CoR repressor in cultured cells, the conserved AR motif may directly or indirectly regulate ligand-dependent corepressor disengagement and, thereby, ligand-dependent trans activation.Publisher PDFPeer reviewe

Genetic disarray follows mutant KLF1-E325K expression in a congenital dyserythropoietic anemia patient

C ongenital dyserythropoietic anemia type IV is caused by a heterozygous mutation, Glu325Lys (E325K), in the KLF1 transcription factor. Molecular characteristics of this disease have not been clarified, partly due to its rarity. We expanded erythroid cells from a patient\u2019s peripheral blood and analyzed its global expression pattern. We find that a large number of erythroid pathways are disrupted, particularly those related to membrane transport, globin regulation, and iron utilization. The altered genetics lead to significant deficits in differentiation. Glu325 is within the KLF1 zinc finger domain at an amino acid critical for site specific DNA binding. The change to Lys is predicted to significantly alter the target site recognition sequence, both by subverting normal recognition and by enabling interaction with novel sites. Consistent with this, we find high level ectopic expression of genes not normally present in the red cell. These altered properties explain patients\u2019 clinical and phenotypic features, and elucidate the dominant character of the mutation

Functional 3D architecture in an intrinsically disordered E3 ligase domain facilitates ubiquitin transfer

Funding: Wellcome Trust Investigator Awards (098391/Z/12/Z and 217196/Z/19/Z) and Cancer Research UK Programme grant (C434/A21747) to R.T.H., Wellcome Trust Studentship (109113/Z/15/Z) to P.M., Wellcome Trust Collaborative Award (215539) and multiuser equipment grant (104833) to S.J.M. Additionally J.C.P. thanks the Scottish Universities Physics Alliance (SUPA) and the University of St. Andrews for financial support.The human genome contains an estimated 600 ubiquitin E3 ligases, many of which are single-subunit E3s (ssE3s) that can bind to both substrate and ubiquitin-loaded E2 (E2~Ub). Within ssE3s structural disorder tends to be located in substrate binding and domain linking regions. RNF4 is a ssE3 ligase with a C-terminal RING domain and disordered N-terminal region containing SUMO Interactions Motifs (SIMs) required to bind SUMO modified substrates. Here we show that, although the N-terminal region of RNF4 bears no secondary structure, it maintains a compact global architecture primed for SUMO interaction. Segregated charged regions within the RNF4 N-terminus promote compaction, juxtaposing RING domain and SIMs to facilitate substrate ubiquitination. Mutations that induce a more extended shape reduce ubiquitination activity. Our result offer insight into a key step in substrate ubiquitination by a member of the largest ubiquitin ligase subtype and reveal how a defined architecture within a disordered region contributes to E3 ligase function.Publisher PDFPeer reviewe

A frequentist framework of inductive reasoning

Reacting against the limitation of statistics to decision procedures, R. A. Fisher proposed for inductive reasoning the use of the fiducial distribution, a parameter-space distribution of epistemological probability transferred directly from limiting relative frequencies rather than computed according to the Bayes update rule. The proposal is developed as follows using the confidence measure of a scalar parameter of interest. (With the restriction to one-dimensional parameter space, a confidence measure is essentially a fiducial probability distribution free of complications involving ancillary statistics.) A betting game establishes a sense in which confidence measures are the only reliable inferential probability distributions. The equality between the probabilities encoded in a confidence measure and the coverage rates of the corresponding confidence intervals ensures that the measure's rule for assigning confidence levels to hypotheses is uniquely minimax in the game. Although a confidence measure can be computed without any prior distribution, previous knowledge can be incorporated into confidence-based reasoning. To adjust a p-value or confidence interval for prior information, the confidence measure from the observed data can be combined with one or more independent confidence measures representing previous agent opinion. (The former confidence measure may correspond to a posterior distribution with frequentist matching of coverage probabilities.) The representation of subjective knowledge in terms of confidence measures rather than prior probability distributions preserves approximate frequentist validity.Comment: major revisio

SwarmDeepSurv: Swarm Intelligence Advances Deep Survival Network for Prognostic Radiomics Signatures in Four Solid Cancers

Survival models exist to study relationships between biomarkers and treatment effects. Deep learning-powered survival models supersede the classical Cox proportional hazards (CoxPH) model, but substantial performance drops were observed on high-dimensional features because of irrelevant/redundant information. To fill this gap, we proposed SwarmDeepSurv by integrating swarm intelligence algorithms with the deep survival model. Furthermore, four objective functions were designed to optimize prognostic prediction while regularizing selected feature numbers. When testing on multicenter sets (n = 1,058) of four different cancer types, SwarmDeepSurv was less prone to overfitting and achieved optimal patient risk stratification compared with popular survival modeling algorithms. Strikingly, SwarmDeepSurv selected different features compared with classical feature selection algorithms, including the least absolute shrinkage and selection operator (LASSO), with nearly no feature overlapping across these models. Taken together, SwarmDeepSurv offers an alternative approach to model relationships between radiomics features and survival endpoints, which can further extend to study other input data types including genomics