Long-term treatment of osteoporosis: safety and efficacy appraisal of denosumab

Denosumab is a fully human monoclonal antibody to the receptor activator of nuclear factor-κB ligand (RANKL), a member of the tumor necrosis factor receptor superfamily essential for osteoclastogenesis. Denosumab treatment is associated with a rapid, sustained, and reversible reduction in bone turnover markers, a continuous marked increase in bone mineral density at all sites, and a marked decrease in the risk of vertebral, hip, and nonvertebral fractures in women with postmenopausal osteoporosis. Therefore, it could be considered as an effective alternative to previous bisphosphonate treatment as well as first-line treatment of severe osteoporosis. Cost-effectiveness studies support this suggestion. In addition, denosumab seems to be the safest treatment option in patients with impaired renal function. Denosumab is characterized by reversibility of its effect after treatment discontinuation, in contrast with bisphosphonates. Large-scale clinical trials, including the extension of FREEDOM trial for up to 5 years, are reassuring for its safety. However, given its brief post-market period, vigilance regarding adverse events related to putative RANKL inhibition in tissues other than bone, as well as those related to bone turnover oversuppression, is advised

FastSVD-ML-ROM\textit{FastSVD-ML-ROM}: A Reduced-Order Modeling Framework based on Machine Learning for Real-Time Applications

Digital twins have emerged as a key technology for optimizing the performance of engineering products and systems. High-fidelity numerical simulations constitute the backbone of engineering design, providing an accurate insight into the performance of complex systems. However, large-scale, dynamic, non-linear models require significant computational resources and are prohibitive for real-time digital twin applications. To this end, reduced order models (ROMs) are employed, to approximate the high-fidelity solutions while accurately capturing the dominant aspects of the physical behavior. The present work proposes a new machine learning (ML) platform for the development of ROMs, to handle large-scale numerical problems dealing with transient nonlinear partial differential equations. Our framework, mentioned as $\textit{FastSVD-ML-ROM}$, utilizes $\textit{(i)}$ a singular value decomposition (SVD) update methodology, to compute a linear subspace of the multi-fidelity solutions during the simulation process, $\textit{(ii)}$ convolutional autoencoders for nonlinear dimensionality reduction, $\textit{(iii)}$ feed-forward neural networks to map the input parameters to the latent spaces, and $\textit{(iv)}$ long short-term memory networks to predict and forecast the dynamics of parametric solutions. The efficiency of the $\textit{FastSVD-ML-ROM}$ framework is demonstrated for a 2D linear convection-diffusion equation, the problem of fluid around a cylinder, and the 3D blood flow inside an arterial segment. The accuracy of the reconstructed results demonstrates the robustness and assesses the efficiency of the proposed approach.Comment: 35 pages, 22 figure

Composite macroH2A/NRF-1 Nucleosomes Suppress Noise and Generate Robustness in Gene Expression

SummaryThe histone variant macroH2A (mH2A) has been implicated in transcriptional repression, but the molecular mechanisms that contribute to global mH2A-dependent genome regulation remain elusive. Using chromatin immunoprecipitation sequencing (ChIP-seq) coupled with transcriptional profiling in mH2A knockdown cells, we demonstrate that singular mH2A nucleosomes occupy transcription start sites of subsets of both expressed and repressed genes, with opposing regulatory consequences. Specifically, mH2A nucleosomes mask repressor binding sites in expressed genes but activator binding sites in repressed genes, thus generating distinct chromatin landscapes that limit genetic or extracellular inductive signals. We show that composite nucleosomes containing mH2A and NRF-1 are stably positioned on gene regulatory regions and can buffer transcriptional noise associated with antiviral responses. In contrast, mH2A nucleosomes without NRF-1 bind promoters weakly and mark genes with noisier gene expression patterns. Thus, the strategic position and stabilization of mH2A nucleosomes in human promoters defines robust gene expression patterns

Normal bone turnover markers in a patient with active Paget’s disease of bone: response to treatment with zoledronic acid

Celem leczenia choroby kości Pageta (PDB) jest zahamowanie zwiększonego obrotu kostnego. Obecnie lekami z wyboru są bisfosfoniany. Do wskazań do stosowania leków antyresorpcyjnych u pacjentów z objawowa postacią PDB należą: bóle kostne i stawowe, powikłania neurologiczne, planowany zabieg chirurgiczny w rejonie aktywnych zmian chorobowych i hiperkalcemia spowodowana unieruchomieniem. Celem terapii antyresorpcyjnej jest uzyskanie poprawy stanu klinicznego i remisji biochemicznej, ocenianej na podstawie normalizacji stężeń biomarkerów obrotu kostnego. Przed podjęciem decyzji o wdrożeniu terapii u chorych w późnej, sklerotycznej fazie choroby (burned out) należy wziąć pod uwagę pogorszenie stanu klinicznego, a zwłaszcza występowanie bólów kostnych. U tych chorych duże znaczenie ma badanie scyntygraficzne kości, ponieważ może ono uwidocznić zwiększoną aktywność osteoblastyczną, której mogą nie wykazać markery obrotu kostnego. W niniejszej pracy przedstawiono przypadek chorego w późnym, sklerotycznym stadium PDB, u którego występowały nasilone objawy kliniczne, lecz stężenia markerów obrotu kostnego były prawidłowe. Po leczeniu kwasem zoledronowym nastąpiła istotna poprawa kliniczna.The treatment of Paget’s disease of bone (PDB) aims at the suppression of abnormal bone turnover; bisphosphonates are currently the treatment of choice. Indications for antiresorptive treatment in symptomatic patients with PDB include bone or joint pain, neurological complications, surgery planned at an active pagetic site and hypercalcaemia from immobilisation. The goals of antiresorptive treatment are clinical improvement and biochemical remission, as assessed by the normalisation of bone turnover markers. Clinical deterioration, especially bone pain, should be considered before deciding to treat patients with late sclerotic (burned-out) PDB. Bone scintigraphy may be of importance in these patients, because it depicts increased osteoblastic activity, when bone markers may not. We present a case of late sclerotic PDB with clinical deterioration but normal bone turnover markers, who experienced significant clinical improvement after treatment with zoledronic acid

Multi-disciplinary optimization of variable rotor speed and active blade twist rotorcraft: Trade-off between noise and emissions

The concepts of variable rotor speed and active blade twist are emerging technologies for the next generation of civil rotorcraft. Previous research has focused on the optimum implementation of these technologies for improved fuel economy and environmental impact. Within this work, an integrated approach is deployed to quantify the concurrent reductions in rotor noise and NOx emissions. A relaxation-based free-wake inflow model, coupled with unsteady blade aerodynamics modeling, resolves the flow-field around the main rotor. Aero-acoustic predictions are performed through an acoustic-analogy-based formulation. Gaseous emissions are then predicted via stirred-reactor modeling, coupled with zero-dimensional engine performance analysis method. This strategy is incorporated into a multi-disciplinary genetic algorithm optimization process based on surrogate modeling. Optimal schedules of combined variable rotor speed and active blade twist controls are derived for a twin-engine light helicopter in descent. The accrued schedules suggest NOx reductions between 6% and 21%, simultaneously with source-noise reductions of the order of 2–8 dB, relative to the non-morphing rotor case. The developed strategy constitutes an enabling methodology for the holistic and multi-disciplinary assessment of morphing helicopter rotor configurations

A new mathematical model for the interpretation of translational research evaluating six CTLA-4 polymorphisms in high-risk melanoma patients receiving adjuvant interferon

Adjuvant therapy of stage IIB/III melanoma with interferon reduces relapse and mortality by up to 33% but is accompanied by toxicity-related complications. Polymorphisms of the CTLA-4 gene associated with autoimmune diseases could help in identifying interferon treatment benefits. We previously genotyped 286 melanoma patients and 288 healthy (unrelated) individuals for six CTLA-4 polymorphisms (SNP). Previous analyses found no significant differences between the distributions of CTLA-4 polymorphisms in the melanoma population vs. controls, no significant difference in relapse free and overall survivals among patients and no correlation between autoimmunity and specific alleles. We report new analysis of these CTLA-4 genetic profiles, using Network Phenotyping Strategy (NPS). It is graph-theory based method, analyzing the SNP patterns. Application of NPS on CTLA-4 polymorphism captures allele relationship pattern for every patient into 6-partite mathematical graph P. Graphs P are combined into weighted 6-partite graph S, which subsequently decomposed into reference relationship profiles (RRP). Finally, every individual CTLA-4 genotype pattern is characterized by the graph distances of P from eight identified RRP's. RRP's are subgraphs of S, collecting equally frequent binary allele co-occurrences in all studied loci. If S topology represents the genetic "dominant model", the RRP's and their characteristic frequencies are identical to expectation-maximization derived haplotypes and maximal likelihood estimates of their frequencies. The graphrepresentation allows showing that patient CTLA-4 haplotypes are uniquely different from the controls by absence of specific SNP combinations. New function-related insight is derived when the 6-partite graph reflects allelic state of CTLA-4. We found that we can use differences between individual P and specific RRPs to identify patient subpopulations with clearly different polymorphic patterns relatively to controls as well as to identify patients with significantly different survival. © 2014 Pancoska et al