Improved approximation algorithms for inventory problems

We give new approximation algorithms for the submodular joint replenishment problem and the inventory routing problem, using an iterative rounding approach. In both problems, we are given a set of N items and a discrete time horizon of T days in which given demands for the items must be satisfied. Ordering a set of items incurs a cost according to a set function, with properties depending on the problem under consideration. Demand for an item at time t can be satisfied by an order on any day prior to t, but a holding cost is charged for storing the items during the intermediate period; the goal is to minimize the sum of the ordering and holding cost. Our approximation factor for both problems is [Formula Presented]; this improves exponentially on the previous best results

Outlier Edge Detection Using Random Graph Generation Models and Applications

Outliers are samples that are generated by different mechanisms from other normal data samples. Graphs, in particular social network graphs, may contain nodes and edges that are made by scammers, malicious programs or mistakenly by normal users. Detecting outlier nodes and edges is important for data mining and graph analytics. However, previous research in the field has merely focused on detecting outlier nodes. In this article, we study the properties of edges and propose outlier edge detection algorithms using two random graph generation models. We found that the edge-ego-network, which can be defined as the induced graph that contains two end nodes of an edge, their neighboring nodes and the edges that link these nodes, contains critical information to detect outlier edges. We evaluated the proposed algorithms by injecting outlier edges into some real-world graph data. Experiment results show that the proposed algorithms can effectively detect outlier edges. In particular, the algorithm based on the Preferential Attachment Random Graph Generation model consistently gives good performance regardless of the test graph data. Further more, the proposed algorithms are not limited in the area of outlier edge detection. We demonstrate three different applications that benefit from the proposed algorithms: 1) a preprocessing tool that improves the performance of graph clustering algorithms; 2) an outlier node detection algorithm; and 3) a novel noisy data clustering algorithm. These applications show the great potential of the proposed outlier edge detection techniques.Comment: 14 pages, 5 figures, journal pape

Defining the role of cellular immune signatures in diagnostic evaluation of suspected tuberculosis

BACKGROUND: Diagnosis of paucibacillary tuberculosis (TB) including extrapulmonary TB is a significant challenge, particularly in high-income, low-incidence settings. Measurement of Mycobacterium tuberculosis (Mtb)-specific cellular immune signatures by flow cytometry discriminates active TB from latent TB infection (LTBI) in case-control studies; however, their diagnostic accuracy and clinical utility in routine clinical practice is unknown. METHODS: Using a nested case-control study design within a prospective multicenter cohort of patients presenting with suspected TB in England, we assessed diagnostic accuracy of signatures in 134 patients who tested interferon-gamma release assay (IGRA)-positive and had final diagnoses of TB or non-TB diseases with coincident LTBI. Cellular signatures were measured using flow cytometry. RESULTS: All signatures performed less well than previously reported. Only signatures incorporating measurement of phenotypic markers on functional Mtb-specific CD4 T cells discriminated active TB from non-TB diseases with LTBI. The signatures measuring HLA-DR+IFNγ + CD4 T cells and CD45RA-CCR7-CD127- IFNγ -IL-2-TNFα + CD4 T cells performed best with 95% positive predictive value (95% confidence interval, 90-97) in the clinically challenging subpopulation of IGRA-positive but acid-fast bacillus (AFB) smear-negative TB suspects. CONCLUSIONS: Two cellular immune signatures could improve and accelerate diagnosis in the challenging group of patients who are IGRA-positive, AFB smear-negative, and have paucibacillary TB

Patterns of lung cancer mortality in 23 countries: Application of the Age-Period-Cohort model

BACKGROUND: Smoking habits do not seem to be the main explanation of the epidemiological characteristics of female lung cancer mortality in Asian countries. However, Asian countries are often excluded from studies of geographical differences in trends for lung cancer mortality. We thus examined lung cancer trends from 1971 to 1995 among men and women for 23 countries, including four in Asia. METHODS: International and national data were used to analyze lung cancer mortality from 1971 to 1995 in both sexes. Age-standardized mortality rates (ASMR) were analyzed in five consecutive five-year periods and for each five-year age group in the age range 30 to 79. The age-period-cohort (APC) model was used to estimate the period effect (adjusted for age and cohort effects) for mortality from lung cancer. RESULTS: The sex ratio of the ASMR for lung cancer was lower in Asian countries, while the sex ratio of smoking prevalence was higher in Asian countries. The mean values of the sex ratio of the ASMR from lung cancer in Taiwan, Hong Kong, Singapore, and Japan for the five 5-year period were 2.10, 2.39, 3.07, and 3.55, respectively. These values not only remained quite constant over each five-year period, but were also lower than seen in the western countries. The period effect, for lung cancer mortality as derived for the 23 countries from the APC model, could be classified into seven patterns. CONCLUSION: Period effects for both men and women in 23 countries, as derived using the APC model, could be classified into seven patterns. Four Asian countries have a relatively low sex ratio in lung cancer mortality and a relatively high sex ratio in smoking prevalence. Factors other than smoking might be important, especially for women in Asian countries

Reversible Keap1 inhibitors are preferential pharmacological tools to modulate cellular mitophagy

Mitophagy orchestrates the autophagic degradation of dysfunctional mitochondria preventing their pathological accumulation and contributing to cellular homeostasis. We previously identified a novel chemical tool (hereafter referred to as PMI), which drives mitochondria into autophagy without collapsing their membrane potential (ΔΨm). PMI is an inhibitor of the protein-protein interaction (PPI) between the transcription factor Nrf2 and its negative regulator, Keap1 and is able to up-regulate the expression of autophagy-associated proteins, including p62/SQSTM1. Here we show that PMI promotes mitochondrial respiration, leading to a superoxide-dependent activation of mitophagy. Structurally distinct Keap1-Nrf2 PPI inhibitors promote mitochondrial turnover, while covalent Keap1 modifiers, including sulforaphane (SFN) and dimethyl fumarate (DMF), are unable to induce a similar response. Additionally, we demonstrate that SFN reverses the effects of PMI in co-treated cells by reducing the accumulation of p62 in mitochondria and subsequently limiting their autophagic degradation. This study highlights the unique features of Keap1-Nrf2 PPI inhibitors as inducers of mitophagy and their potential as pharmacological agents for the treatment of pathological conditions characterized by impaired mitochondrial quality control

N- and C-Terminal Domains of the Calcium Binding Protein EhCaBP1 of the Parasite Entamoeba histolytica Display Distinct Functions

Entamoeba histolytica, a protozoan parasite, is the causative agent of amoebiasis, and calcium signaling is thought to be involved in amoebic pathogenesis. EhCaBP1, a Ca2+ binding protein of E. histolytica, is essential for parasite growth. High resolution crystal structure of EhCaBP1 suggested an unusual arrangement of the EF-hand domains in the N-terminal part of the structure, while C-terminal part of the protein was not traced. The structure revealed a trimer with amino terminal domains of the three molecules interacting in a head-to-tail manner forming an assembled domain at the interface with EF1 and EF2 motifs of different molecules coming close to each other. In order to understand the specific roles of the two domains of EhCaBP1, the molecule was divided into two halves, and each half was separately expressed. The domains were characterized with respect to their structure, as well as specific functional features, such as ability to activate kinase and bind actin. The domains were also expressed in E. histolytica cells along with green fluorescent protein. The results suggest that the N-terminal domain retains some of the properties, such as localization in phagocytic cups and activation of kinase. Crystal structure of EhCaBP1 with Phenylalanine revealed that the assembled domains, which are similar to Calmodulin N-terminal domain, bind to Phenylalanine revealing the binding mode to the target proteins. The C-terminal domain did not show any of the activities tested. However, over-expression in amebic cells led to a dominant negative phenotype. The results suggest that the two domains of EhCaBP1 are functionally and structurally different from each other. Both the domains are required for structural stability and full range of functional diversity

Bright ligand-activatable fluorescent protein for high-quality multicolor live-cell super-resolution microscopy

We introduce UnaG as a green-to-dark photoswitching fluorescent protein capable of high-quality super-resolution imaging with photon numbers equivalent to the brightest photoswitchable red protein. UnaG only fluoresces upon binding of a fluorogenic metabolite, bilirubin, enabling UV-free reversible photoswitching with easily controllable kinetics and low background under Epi illumination. The on- and off-switching rates are controlled by the concentration of the ligand and the excitation light intensity, respectively, where the dissolved oxygen also promotes the off-switching. The photo-oxidation reaction mechanism of bilirubin in UnaG suggests that the lack of ligand-protein covalent bond allows the oxidized ligand to detach from the protein, emptying the binding cavity for rebinding to a fresh ligand molecule. We demonstrate super-resolution single-molecule localization imaging of various subcellular structures genetically encoded with UnaG, which enables facile labeling and simultaneous multicolor imaging of live cells. UnaG has the promise of becoming a default protein for high-performance super-resolution imaging. Photoconvertible proteins occupy two color channels thereby limiting multicolour localisation microscopy applications. Here the authors present UnaG, a new green-to-dark photoswitching fluorescent protein for super-resolution imaging, whose activation is based on a noncovalent binding with bilirubin

Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author

Atomic structures of TDP-43 LCD segments and insights into reversible or pathogenic aggregation.

The normally soluble TAR DNA-binding protein 43 (TDP-43) is found aggregated both in reversible stress granules and in irreversible pathogenic amyloid. In TDP-43, the low-complexity domain (LCD) is believed to be involved in both types of aggregation. To uncover the structural origins of these two modes of β-sheet-rich aggregation, we have determined ten structures of segments of the LCD of human TDP-43. Six of these segments form steric zippers characteristic of the spines of pathogenic amyloid fibrils; four others form LARKS, the labile amyloid-like interactions characteristic of protein hydrogels and proteins found in membraneless organelles, including stress granules. Supporting a hypothetical pathway from reversible to irreversible amyloid aggregation, we found that familial ALS variants of TDP-43 convert LARKS to irreversible aggregates. Our structures suggest how TDP-43 adopts both reversible and irreversible β-sheet aggregates and the role of mutation in the possible transition of reversible to irreversible pathogenic aggregation