Integer Weights Research Articles

An Integer Weighted Genomic Mutation Score (GMS) Using Next Generation Sequencing Is Predictive of Prognosis in Intermediate Risk AML Patients

Introduction: The genomic heterogeneity in Acute Myeloid Leukemia (AML) has been shown to affect the overall prognosis and should be taken into account to decide the best course of treatment. Study of AML genomic landscape by The Cancer Genome Atlas (TCGA) research network by Ley, et.al, analyzed the genomes of 200 patients (pts) with de-novo AML and showed at least one potential driver mutation in nearly all AML samples and further classified these mutation in 9 functional categories: Myeloid transcription factor and fusion genes, Tumor suppressor genes, gene encoding Nucleophosmin, Activated signaling genes, DNA methylation related genes, Chromatin modifying genes, Cohesion complex genes and Spliceosome complex genes . The availability of Next Generation Sequencing (NGS) has allowed easy characterization of patient samples. However, this has now became increasingly important to prioritize the influence of different mutations clones so as to give actionable and prognostic information. We developed an Integer Weighted Genomic Mutation Score (GMS) to address this in the context of the TCGA data and applied this to a retrospective cohort of pts with AML. The goal was to meaningfully stratify the Intermediate risk AML patients per current ELN criteria based identified by NGS technique into low and high risk group and correlate this with clinical outcome.Study Method: We screened 1200 AML patients at our institution from 2010 to 2016 and identified 111 patients from our hospital database who had information on both cytogenetics and gene mutation detected by NGS. We queried for the diagnosis of AML and demographics, Cy, NGS and OS. We divided the patients into 3 groups according to their cytogenetic risks- Favorable (FCy), Intermediate (ICy),Poor (PCy). Mutations in 54 genes associated with myeloid disorders were tested in NGS by using the TruSight Myeloid Sequencing Panel (Illumina) (Table1). We also performed flow cytometric evaluation on a BD FACSCantos™ II 3-laser (405, 488, 630 nm excitation sources), 8-color flow cytometer (BD Biosciences, San Jose, CA, USA) and data analyzed using BD FACSDiva software. We then utilized the TCGA data by Leyet.al and developed a system of Integer Weights forthe Genomic Mutation Score (GMS) obtained by targeted NGS at Houston Methodist Hospital mentioned below. GMS was designed by assigning a score for each genomic mutation between the range of negative 2 (-2) for good risk to positive 2 (+2) for each of 9 TCGA mutation categories .The total IWGMS for each patient was calculated by the sum of mutation scores in each 9 categories. A score of 3 or greater than 3 was defined as high risk. We then performed a retrospective analysis of 111 AML patients to correlate the GMS with 2 year mortality and survival outcome. Statistical Analysis was done using multivariate logistic regression method.Results: Pts were grouped into 51 intermediate risk and 60 poor risk cytogenetics. Median age of the pts was 66 years and 57.6% were male. Immunophenotyping of CD34 and CD38, and CD117 did not emerge as significant predictors of survival when adjusting for covariates. 32% of patients underwent allogeneic stem cell transplant as consolidation therapy. Median overall survival for the entire study population was 24 months with a median follow up time was 20.01 months (95% CI; 15.77 - 25.17). Univariate analysis using cox proportional hazard method showed age and cytogenetics risk as a statistically significant predictor of overall survival as shown in Fig: 1. Overall survival in all AML patients and Intermediate risk patients showed a trend toward better OS with lower GMS but no such trend was seen in poor risk AML patients as shown in Fig: 2-4.Conclusion: We have developed an GMS system to further stratify Intermediate Risk AML patients into high and low risk groups. Age and cytogenetics risk per ELN criteria were independent prognostic factor for overall survival in our study cohort as expected. Patients with lower GMS in our study cohort had a trend towards better OS but patients with high GMS had a trend towards worse OS in intermediate risk AML patients. Larger size prospective study is required to validate this scoring system; it has a great potential to identify high risk patients among Intermediate risk group and plan different consolidation therapies to further improve their outcomes.Further treatment related analysis will be presented at ASH,Atlanta 2017. [Display omitted] DisclosuresIyer:Takeda: Research Funding; Genentech: Research Funding.

Mod p modular forms and simple congruences

In this article, we first give a complete description of the algebra of integer weight modular forms on the congruence subgroup $$\Gamma _0(2)$$ modulo a prime $$p\ge 3$$ . This result parallels results of Swinnerton-Dyer in the $$SL_2(\mathbb {Z})$$ case, Katz on the subgroup $$\Gamma (N)$$ for $$N\ge 3$$ , Gross on the subgroup $$\Gamma _1(N)$$ for $$N\ge 4$$ and Tupan on modular forms of half-integral weight on $$\Gamma _1(4)$$ . Next, we use the theory of mod p modular forms on $$\Gamma _0(2)$$ to prove the non-existence of simple congruences for Fourier coefficients of quotients of certain integer weight Eisenstein series on $$\Gamma _0(2)$$ . The non-existence of simple congruences for coefficients of quotients of Eisenstein series on $$SL_2(\mathbb {Z})$$ has been shown by Dewar.

Random Gap Processes and Asymptotically Complete Sequences

We study a process of generating random positive integer weight sequences \(\{ W_n \}\) where the gaps between the weights \(\{ X_n = W_n - W_{n-1} \}\) are i.i.d. positive integer-valued random variables. The main result of the paper is that if the gap distribution has a moment generating function with large enough radius of convergence, then the weight sequence is almost surely asymptotically m-complete for every \(m\ge 2\), i.e. every large enough multiple of the greatest common divisor (gcd) of gap values can be written as a sum of m distinct weights for any fixed \(m \ge 2\). Under the weaker assumption of finite \(\frac{1}{2}\)-moment for the gap distribution, we also show the simpler result that, almost surely, the resulting weight sequence is asymptotically complete, i.e. all large enough multiples of the gcd of the possible gap values can be written as a sum of distinct weights.

Hyperelliptic curves and newform coefficients

We study which integers are admissible as Fourier coefficients of even integer weight newforms. In the specific case of the tau-function, we show that for all odd primes ℓ<100 and all integers m≥1, we haveτ(n)≠±ℓ,±5m. For general newforms f with even integer weight 2k and integer coefficients, we prove for most integers j dividing 2k−1 and all ordinary primes p that af(p2) is never a j-th power. We prove a similar result for af(p4), conditional on the Frey-Mazur Conjecture. Our primary method involves relating questions about values of newforms to the existence of perfect powers in certain binary recurrence sequences, and makes use of bounds from the theory of linear forms in logarithms. The method extends without difficulty to a large family of Lebesgue-Nagell equations with fixed exponent. To prove results about general newforms, we also make use of the modular method and Ribet's level-lowering theorem.

Time-dependent reliability of (weighted) k-out-of-n systems with identical component deterioration

The performance of civil infrastructure systems is vital in supporting a community’s functionalities. Reliability assessment of these systems is a powerful approach to evaluate whether the system performance is desirably safe under the impacts of resistance degradation and non-stationary loads. A k-out-of-n system is a widely-used logic model for a system with n components, which survives (works) if at least k components work. Its special cases include a series or a parallel system. Furthermore, a weighted k-out-of-n system has components with positive integer weights and the system survives if the total weight of working components reaches the predefined threshold k. This paper proposes a method for estimating the time-dependent reliability of both ordinary and weighted k-out-of-n systems, taking into account the effects of resistance deterioration, resistance correlation and load non-stationarity, for which a mathematical solution is derived. The applicability of the proposed method is illustrated through reliability evaluation of a representative k-out-of-n system.

A new robust tilt-PID controller based upon an automatic selection of adjustable fractional weights for permanent magnet synchronous motor drive control

This paper focuses on achieving a good trade-off between performance and robustness for a class of uncertainty models including unstructured multiplicative uncertainties. In robust control, the simultaneous improvement of the two secure margins for nominal performances and robust stability using a standard controller structure represents two contradictory objectives and guaranteeing simultaneously of these goals represents therefore a major challenge for most researchers. In this context, a robust tilt-proportional integral derivative (T-PID) controller synthesized with an automatic selection of adjustable fractional weights (AFWs) is discussed in our work. Their parameters are optimized through solving a weighted-mixed sensitivity problem using an optimization tool which is based on the genetic algorithm. This problem is formulated from performance and robustness requirements where a fitness function is accordingly determined. Furthermore, thus its search space is built according to some guidelines for ensuring an automatic selection of adequate AFWs. The proposed constrained optimization problem is initialized by using arbitrary T-PID speed controller as well as through initial fixed integer weights (FIWs) which were chosen previously by the designer. To highlight the proposed control strategy, the synthesized robust T-PID speed controller is applied on the permanent magnet synchronous motor. Their performance and robustness are compared to those provided by an integer-order PID (IO-PID) and two conventional fractional-order PID (FO-PID) controllers. This comparison reveals superiority of the proposed robust T-PID controller over the remaining controllers in terms of robustness with reduced control energy.

Arithmetic properties of septic partition functions

Congruences and related identities are derived for a set of colored and weighted partition functions whose generating functions generate the graded algebra of integer weight modular forms of level seven. The work determines a general strategy for identifying and proving identities and associated congruences for modular forms on the principal congruence subgroup of level [Formula: see text]. Ramanujan’s partition congruence modulo [Formula: see text] serves as a prototype for the process used to prove new congruences for modular forms of level [Formula: see text].

TMA: Tera‐MACs/W neural hardware inference accelerator with a multiplier‐less massive parallel processor

SummaryComputationally intensive inference tasks of deep neural networks have brought about a revolution in accelerator architecture, aiming to reduce power consumption as well as latency. The key figure‐of‐merit in hardware inference accelerators is the number of multiply‐and‐accumulation operations per watt (MACs/W); the state‐of‐ the‐art MACs/W, so far, has been several hundreds Giga‐MACs/W. We propose a Tera‐ MACS/W neural hardware inference accelerator (TMA) with 8‐bit activations and scalable integer weights less than 1‐byte. The architecture's main feature is a configurable neural processing element for matrix‐vector operations. The proposed neural processing element uses a multiplier‐less massive parallel processor that works without multipliers, which makes it attractive for energy efficient high‐performance neural network applications. We benchmark our system's latency, power, and performance using Alexnet trained on ImageNet. Finally, we compared our accelerator's throughput and power consumption to that of the prior works. The proposed accelerator outperforms the state‐of‐the‐art counterparts, in terms of the energy and area efficiency, achieving 2.3 TMACs/W@1.0 V on a 28‐nm Virtex‐7 FPGA chip.

Double cover of modular S4 for flavour model building

We develop the formalism of the finite modular group Γ4′≡S4′, a double cover of the modular permutation group Γ4≃S4, for theories of flavour. The integer weight k>0 of the level 4 modular forms indispensable for the formalism can be even or odd. We explicitly construct the lowest-weight (k=1) modular forms in terms of two Jacobi theta constants, denoted as ε(τ) and θ(τ), τ being the modulus. We show that these forms furnish a 3D representation of S4′ not present for S4. Having derived the S4′ multiplication rules and Clebsch-Gordan coefficients, we construct multiplets of modular forms of weights up to k=10. These are expressed as polynomials in ε and θ, bypassing the need to search for non-linear constraints. We further show that within S4′ there are two options to define the (generalised) CP transformation and we discuss the possible residual symmetries in theories based on modular and CP invariance. Finally, we provide two examples of application of our results, constructing phenomenologically viable lepton flavour models.

Abstract 12923: Development of a Novel Biomarker-based Risk Score for Heart Failure in Patients With Diabetes

Introduction: Heart failure (HF) is a prognostically important complication of T2DM, the risk of which can be reduced by SGLT2 inhibitors. Clinical factors and circulating biomarkers of myocardial injury and hemodynamic stress predict risk of hosp for HF (HHF) in pts with T2DM. Aim: We aimed to develop and validate a biomarker-based risk score for HHF in pts with T2DM and to assess whether this score can identify high-risk pts with T2DM who have the greatest reduction in HHF risk with SGLT2 inhibition. Methods: Blood samples were prospectively collected from pts enrolled in SAVOR-TIMI 53 and DECLARE-TIMI 58 at randomization; high-sensitivity troponin T (hsTnT) and N-terminal B-type natriuretic peptide (NT-proBNP) were measured. We derived a risk score in 6106 pts with T2DM in the placebo arm of SAVOR-TIMI 53. Candidate variables (n=27) were assessed using Cox regression. The strongest indicators of HHF risk (based on Wald χ;2 values) were selected for inclusion and assigned integer weights. We externally validated the score in 7251 T2DM pts in the placebo arm of DECLARE-TIMI 58. Hazard ratios (HR) and absolute risk reductions (ARR) in HHF with the SGLT2 inhibitor dapagliflozin were assessed by baseline risk group. Results: The strongest independent indicators of HHF risk were NT-proBNP and hsTnT concentrations, and prior HF (each p&lt;0.001). A risk score using these 3 variables identified a strong gradient of HHF risk (p-trend &lt;0.001) in both the derivation and validation cohorts, with c-indices of 0.87 and 0.84, respectively. HRs with dapagliflozin were similar across risk groups (p-int = 0.64); however, ARRs were greater in those at higher baseline risk (p-trend &lt;0.001), with high- (10-13 points) and very high-risk (14+ points) pts having 3.2% and 4.4% ARRs in KM estimates of HHF at 4 yrs, respectively ( Fig ). Conclusions: A novel biomarker-based risk score for HHF in pts with T2DM identifies pts at higher risk of HHF who derive greater absolute benefit from SGLT2 inhibitors.

A Modified Decomposition Algorithm for Maximum Weight Bipartite Matching and Its Experimental Evaluation

Let G be an undirected bipartite graph with positive integer weights on the edges. We refine the existing decomposition theorem originally proposed by Kao et al., for computing maximum weight bipartite matching. We apply it to design an efficient version of the decomposition algorithm to compute the weight of a maximum weight bipartite matching of G in O(|V |W /k(|V |, W /N))-time by employing an algorithm designed by Feder and Motwani as a subroutine, where |V | and N denote the number of nodes and the maximum edge weight of G, respectively and k(x, y) = log x/ log(x 2 /y). The parameter W is smaller than the total edge weight W, essentially when the largest edge weight differs by more than one from the second largest edge weight in the current working graph in any decomposition step of the algorithm. In best case W = O(|E|) where |E| be the number of edges of G and in worst case W = W, that is, |E| ≤ W ≤ W. In addition, we talk about a scaling property of the algorithm and research a better bound of the parameter W. An experimental evaluation on randomly generated data shows that the proposed improvement is significant in general.

Existence of $$\eta $$-quotients for squarefree levels

Determining which integer weight modular forms can be represented using Dedekind’s $$\eta $$ -function is a question of interest. It has been determined by Rouse and Webb for exactly which integers $$N \le 500$$ the graded ring of modular forms $$M(\varGamma _0(N))$$ can be generated by $$\eta $$ -quotients. Arnold-Roksandich, James, and Keaton have given explicit counts of the number of linearly independent $$\eta $$ -quotients in $$M_k(\varGamma _0(p))$$ for p prime. In this paper, we extend joint work of the author with Anderson, Hamakiotes, Oltsik, and Swisher to investigate which integer weight modular form spaces can contain $$\eta $$ -quotient. For $$k\ge 2$$ even and N coprime to 6, we give necessary conditions for the space $$M_k(\varGamma _1(N))$$ to contain $$\eta $$ -quotients. We then show that these conditions are sufficient as well for a large family of squarefree levels N coprime to 6.

The binary knapsack problem with qualitative levels

A variant of the classical knapsack problem is considered in which each item is associated with an integer weight and a qualitative level. We define a dominance relation over the feasible subsets of the given item set and show that this relation defines a preorder. We propose a dynamic programming algorithm to compute the entire set of non-dominated rank cardinality vectors and we state two greedy algorithms, which efficiently compute a single efficient solution.

Improved Single Haze Removal using Weighted Filter and Gaussian-Laplacian

Generally computer applications use digital images. Digital image plays a vital role in the analysis and explanation of data, which is in the digital form. Images and videos of outside scenes are generally affected by the bad weather environment such as haze, fog, mist etc. It will result in bad visibility of the scene caused by the lack of quality. This paper exhibits a study about various image defogging techniques to eject the haze from the fog images caught in true world to recuperate a fast and enhanced nature of fog free images. In this paper, we propose a simple but effective the weighted median (WM) filter was first presented as an overview of the standard median filter, where a nonnegative integer weight is assigned to each position in the filter window image .Gaussian and laplacian pyramids are applying Gaussian and laplacian filter in an image in cascade order with different kernel sizes of gaussian and laplacian filter .The dark channel prior is a type of statistics of the haze-free outdoor images. It is based on a key observation - most local patches in haze-free outdoor images contain some pixels which have very low intensities in at least one-color channel. Using this prior with the haze imaging model, we can directly estimate the thickness of the haze and recover a high-quality haze-free image. Results on a variety of outdoor haze images demonstrate the power of the proposed prior. Moreover, a high-quality depth map can also be obtained as a by-product of haze removal and Calculate the PSNR and MSE of three sample images.

Exact-2-relation graphs

Pairwise compatibility graphs (PCGs) with non-negative integer edge weights recently have been used to describe rare evolutionary events and scenarios with horizontal gene transfer. Here we consider the case that vertices are separated by exactly two discrete events: Given a tree T with leaf set L and edge-weights λ:E(T)→N0, the non-negative integer pairwise compatibility graph nniPCG(T,λ,2,2) has vertex set L and xy is an edge whenever the sum of the non-negative integer weights along the unique path from x to y in T equals 2. A graph G has a representation as nniPCG(T,λ,2,2) if and only if its point-determining quotient ▪ is a block graph, where two vertices are in relation ▪ if they have the same neighborhood in G. If G is of this type, a labeled tree (T,λ) explaining G can be constructed efficiently. In addition, we consider an oriented version of this class of graphs.

Distributed Integer Balancing Under Weight Constraints in the Presence of Transmission Delays

We consider the distributed weight balancing problem in networks of nodes that are interconnected via directed edges, each of which admits a positive integer weight. A digraph with positive integer weights on its edges is weight balanced if, for each node, the sum of the weights of the incoming edges equals the sum of the weights of the outgoing edges. In this article, we develop a distributed iterative algorithm, which solves the integer weight balancing problem in the presence of arbitrary (time-varying and inhomogeneous) time delays that might affect transmissions at particular links. We assume that each positive weight is constrained to lie within a certain interval, captured by individual lower and upper limits and that communication between neighboring nodes is bidirectional. We show that even when different transmissions on communication links are affected from bounded delays, the proposed distributed algorithm allows nodes to obtain a set of weights that solves the integer weight balancing problem, after a finite number of iterations, as long as a feasible solution exists. Finally, we provide examples to illustrate the operation and performance of the proposed algorithm.

Parameterized Algorithms for Finding a Collective Set of Items

We extend the work of Skowron et al. (AIJ, 2016) by considering the parameterized complexity of the following problem. We are given a set of items and a set of agents, where each agent assigns an integer utility value to each item. The goal is to find a set of k items that these agents would collectively use. For each such collective set of items, each agent provides a score that can be described using an OWA (ordered weighted average) operator and we seek a set with the highest total score. We focus on the parameterization by the number of agents and we find numerous fixed-parameter tractability results (however, we also find some W[1]-hardness results). It turns out that most of our algorithms even apply to the setting where each agent has an integer weight.

Faster Replacement Paths and Distance Sensitivity Oracles

Shortest paths computation is one of the most fundamental problems in computer science. An important variant of the problem is when edges can fail, and one needs to compute shortest paths that avoid a (failing) edge. More formally, given a source node s , a target node t , and an edge e , a replacement path for the triple ( s , t , e ) is a shortest s - t path avoiding edge e . Replacement paths computation can be seen either as a static problem or as a data structure problem. In the static setting, a typical goal is to compute for fixed s and t , for every possible failed edge e , the length of the best replacement path around e ( replacement paths problem ). In the data structure setting, a typical goal is to design a data structure ( distance sensitivity oracle ) that, after some preprocessing, quickly answers queries of the form: What is the length of the replacement path for the triple ( s , t , e )? In this article, we focus on n -node directed graphs with integer edge weights in [− M , M ], and present improved replacement paths algorithms and distance sensitivity oracles based on fast matrix multiplication. In more detail, we obtain the following main results: • We describe a replacement paths algorithm with runtime Õ( Mn ω ), where ω &lt; 2.373 is the fast matrix multiplication exponent. For a comparison, the previous fastest algorithms have runtime õ( Mn 1+2ω /3 ) [Weimann,Yuster—FOCS’10] and, in the unweighted case, õ( n 2.5 ) [Roditty, Zwick—ICALP’05]. Our result shows that, at least for small integer weights, the replacement paths problem in directed graphs may be easier than the related all-pairs shortest paths problem, as the current best runtime for the latter is õ( M 1\4−ω n 2+1 \ 4−ω ): this is Ω ( n 2.5 ) even if ω = 2. Our algorithm also implies that the k shortest simple s - t paths can be computed in õ( kMn ω ) time. • We consider the single-source generalization of the replacement paths problem, where only the source s is fixed. We show how to solve this problem in all-pairs shortest paths time, currently õ( M 1\4−ω n 2+1\4−ω ). Our runtime reduces to õ( Mn ω ) for positive weights, hence matching our mentioned result for the simpler replacement paths case (that, however, holds also for nonpositive weights). One of the ingredients that we use is an algorithm to compute the distances from a set s of source nodes to a set T of target nodes in õ( Mn ω +| S |ṡ | T |ṡ ( Mn ) 1\4−ω ) time. This improves on a result in Yuster,Zwick—FOCS’05. • We present the first distance sensitivity oracle that achieves simultaneously subcubic preprocessing time and sublinear query time. More precisely, for a given parameter α ∈ [0,1], our oracle has preprocessing time Õ( Mn ω + 1\ 2 + Mn ω + α (4−ω) ) and query time Õ( n 1−&amp;alpha ). The previous best oracle for small integer weights has Õ( Mn ω +1−α ) preprocessing time and (superlinear) Õ( n 1+α ) query time [Weimann,Yuster-FOCS’10]. From a technical point of view, an interesting and novel aspect of our oracle is that it exploits as a subroutine our single-source replacement paths algorithm. We also present an oracle with the same preprocessing time as in Weimann,Yuster—FOCS’10 and with smaller query time õ( n 1−1−α\4−ω + n 2α ).

Molecular-Based Score Inspired on Metabolic Signature Improves Prognostic Stratification for Myelodysplastic Syndrome

Background : The recent efforts to uncover the molecular heterogeneity of myelodysplastic syndromes (MDS), mainly by new sequencing technologies, allow the comprehensive identification of driver mutations and/or altered gene expression recurrently found in a recognizable fraction of patients. Ongoing efforts are being made to clarify the impact of molecular changes on clinical phenotype and prognosis, as well as their role in the pathogenesis of MDS. Refining risk stratification allows the proposition of risk-adapted therapy and may shed light in biology of MDS. Aims: Based on the gene expression of selected metabolic targets, we aimed to design a score system that improves MDS overall survival prediction. Patients and methods: Clinical, mutations and transcriptomic data from CD34+ cells from 159 MDS patients and 17 healthy volunteers freely available at Gene Expression Omnibus (GEO/NCBI: GSE58831) were used in the present work. Forty-one genes related to metabolic processes, previously demonstrated as deregulated among diverse neoplastic conditions, were ranked and asked for differential expression and prognostic impact. Each gene was dichotomized according to Receiving-Operating Curve (ROC) and Cox Proportional-Hazard Model was used for multivariate analysis using gender, age and IPSS-R as cofounders. Genes independently associated with overall survival (OS) were selected to compose the Molecular-Based Score (MBS) and integer weight of each one was defined according Hazard Ratio (HR). Survival curves were constructed using Kaplan-Meyer method and compared with Log-Rank Test. ROC c-statistic was used to measure the predictive function of MBS. Prediction accuracy of MBS was cross-validated by a nonparametric bootstrap procedure with 1,000 resamplings of the original cohort allowing replacement and also estimated their respective 95% confidence interval (95% CI) computing the bias-corrected and accelerated bootstrap interval. Results: Among selected genes, 18 were differentially expressed between CD34+ cells from MDS and healthy volunteers. Fifteen genes predict OS in univariate analysis, of which ACLY (HR: 0.48; 95%CI: 0.24 - 0.96; P=0.04), ANPEP (HR: 2.16; 95%CI: 1.08 - 4.31; P=0.02), PANK1 (HR: 0.43; 95%CI: 0.19 - 0.98; P=0.04), PKM (HR: 2.01; 95%CI: 1.02 - 3.93; P=0.04) and SLC25A5 (HR: 0.52; 95%CI: 0.27 - 0.99; P=0.05) were independently associated with OS. Higher expression of ANPEP and PKM, as well as lower expression of ACLY, PANK1 and SLC25A5 were considered to integer high risk being attributed weight 2 for each condition. MBS varied from 0 to 10 (median=2) and was calculated as: MBS Low-Risk =0 (MBS-LR; n=28); MBS Intermediate-Risk=2 and 4 (MBS-IR; n=90) and High-Risk: ≥6 (MBS-HR; n=48). The modeled MBS showed a ROC c-statistic of 0.699 (95%CI: 0.603 - 0.794) and HR=3.05 (95%CI: 1.81 - 5.05; P&lt;0.001) and efficiently identified patients with different risk: MBS-LR (3-year OS: 100%; median time [MT]: not reached); MBS-IR (3-year OS: 66% [95%CI: 53% - 83%]; MT: 52.2 months [95%CI: 34.2 - 71.5]) and MBS-HR (3-year OS: 32% [95%CI: 17% - 61%]; MT: 23.5 months [95%CI: 11.6 - 35.4]). Using Cox Proportional Hazard Model for multivariate analysis, the proposed MBS (HR:2.5 [95%CI: 1.2-4.96]; P=0.008) was independently associated with OS using gender (HR:0.48 [95%CI: 0.21-1.06]; P=0.07), age (HR:1.03 [95%CI: 1.001-1.07]; P=0.02) and IPSS-R (HR:0.98 [95%CI: 0.69-1.36]; P=0.88) as confounders. The bootstrap resampling procedure validated the MBS and demonstrated the stability of its prediction (3-year OS for MBS-LR: 100% [95%CI: 100-100%]; MBS-IR: 66% [95%CI: 49-80%]; MBS-HR: 32% [95%CI: 13-54%]; P&lt;0.001). Conclusions: The proposed Molecular-Based Score (MBS) independently predict OS with superior efficacy in comparison to the most clinically relevant prognostic factors, and reinforce the therapeutic opportunity of metabolic processes in MDS. Figure Disclosures No relevant conflicts of interest to declare.

Distributed Balancing With Constrained Integer Weights

We consider the distributed integer-weight-balancing problem in networks of nodes that are interconnected via directed edges, each able to admit a positive integer weight (or flow) within a certain interval, captured by lower and upper limits. We propose and analyze distributed iterative algorithms for obtaining admissible and balanced integer weights, i.e., integer weights within the given interval constraints, such that, for each node, the sum of the weights of the incoming edges equals the sum of the weights of the outgoing edges. The proposed algorithms assume that communication among pairs of nodes that are interconnected is bidirectional and are shown to lead to a set of admissible and balanced integer weights after a finite number of time steps (as long as the necessary and sufficient integer circulation conditions are satisfied on the given digraph).