1. |
- De Stefano, V., et al.
(author)
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High rate of recurrent venous thromboembolism in patients with myeloproliferative neoplasms and effect of prophylaxis with Vitamin K antagonists
- 2016
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In: Leukemia. - : Springer Science and Business Media LLC. - 0887-6924 .- 1476-5551. ; 30:10, s. 2032-2038
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Journal article (peer-reviewed)abstract
- The optimal duration of treatment with vitamin K antagonists (VKA) after venous thromboembolism (VTE) in patients with Philadelphia-negative myeloproliferative neoplasms (MPNs) is uncertain. To tackle this issue, we retrospectively studied 206 patients with MPN-related VTE (deep venous thrombosis of the legs and/or pulmonary embolism). After this index event, we recorded over 695 pt-years 45 recurrences, venous in 36 cases, with an incidence rate (IR) of 6.5 per 100 pt-years (95% confidence interval (CI): 4.9-8.6). One hundred fifty-five patients received VKA; the IR of recurrent thrombosis per 100 pt-years was 4.7 (95% CI: 2.8-7.3) on VKA and 8.9 (95% CI: 5.7-13.2) off VKA (P=0.03). In patients receiving VKA, the IR of recurrent thrombosis per 100 pt-years was 5.3 (95% CI: 3.2-8.4) among 108 patients on long-term VKA and 12.8 (95% CI: 7.3-20.7) after discontinuation among the 47 who ceased treatment (P=0.008), with a doubled risk of recurrence after stopping VKA (hazard ratio: 2.21, 95% CI: 1.19-5.30). The IR of major bleeding per 100 pt-years was 2.4 (95%: CI: 1.1-4.5) on VKA and 0.7 (95% CI: 0.08-2.5) off VKA (P=0.08). In conclusion, in MPN patients with VTE recurrent thrombosis is significantly reduced by VKA and caution should be adopted in discontinuation; however, the incidence of recurrence on treatment remains high, calling for clinical trials aimed to improve prophylaxis in this setting.
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2. |
- De Stefano, V., et al.
(author)
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Splanchnic vein thrombosis in myeloproliferative neoplasms : Risk factors for recurrences in a cohort of 181 patients
- 2016
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In: Blood Cancer Journal. - : Springer Science and Business Media LLC. - 2044-5385. ; 6:11
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Journal article (peer-reviewed)abstract
- We retrospectively studied 181 patients with polycythaemia vera (n=67), essential thrombocythaemia (n=67) or primary myelofibrosis (n=47), who presented a first episode of splanchnic vein thrombosis (SVT). Budd-Chiari syndrome (BCS) and portal vein thrombosis were diagnosed in 31 (17.1%) and 109 (60.3%) patients, respectively; isolated thrombosis of the mesenteric or splenic veins was detected in 18 and 23 cases, respectively. After this index event, the patients were followed for 735 patient years (pt-years) and experienced 31 recurrences corresponding to an incidence rate of 4.2 per 100 pt-years. Factors associated with a significantly higher risk of recurrence were BCS (hazard ratio (HR): 3.03), history of previous thrombosis (HR: 3.62), splenomegaly (HR: 2.66) and leukocytosis (HR: 2.8). Vitamin K-antagonists (VKA) were prescribed in 85% of patients and the recurrence rate was 3.9 per 100 pt-years, whereas in the small fraction (15%) not receiving VKA more recurrences (7.2 per 100 pt-years) were reported. Intracranial and extracranial major bleeding was recorded mainly in patients on VKA and the corresponding rate was 2.0 per 100 pt-years. In conclusion, despite anticoagulation treatment, the recurrence rate after SVT in myeloproliferative neoplasms is high and suggests the exploration of new avenues of secondary prophylaxis with new antithrombotic drugs and JAK-2 inhibitors.
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3. |
- Glover, Tom Eivind, et al.
(author)
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Investigating Rules and Parameters of Reservoir Computing with Elementary Cellular Automata, with a Criticism of Rule 90 and the Five-Bit Memory Benchmark
- 2023
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In: Complex Systems. - : Complex Systems Publications, Inc. - 0891-2513. ; 32:3, s. 309-351
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Journal article (peer-reviewed)abstract
- Reservoir computing with cellular automata (ReCAs) is a promising concept by virtue of its potential for effective hardware implementation. In this paper, we explore elementary cellular automata rules in the context of ReCAs and the 5-bit memory benchmark. We combine elementary cellular automaton theory with our results and use them to identify and explain some of the patterns found. Furthermore, we use these findings to expose weaknesses in the 5-bit memory benchmark as it is typically applied in ReCAs, such as pointing out what features it selects for or solving it using random vectors. We look deeply into previ-ously successful rules in ReCAs such as rule 90 and explain some of the consequences of its additive properties as well as the correlation between grid size and performance. Additionally, we present results from exhaustively exploring ReCAs on key parameters such as distrac-tor period, iterations and grid size. The findings of this paper should motivate the ReCAs community to move away from using the 5-bit memory benchmark as it is being applied today.
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4. |
- Konkoli, Zoran, 1966, et al.
(author)
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Philosophy of computation
- 2018
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In: Natural Computing Series. - Cham : Springer International Publishing. - 1619-7127. ; , s. 153-184
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Book chapter (other academic/artistic)abstract
- Unconventional computation emerged as a response to a series of technological and societal challenges. The main source of these challenges is the expected collapse of Moore’s law. It is very likely that the existing trend of building faster digital information processing machines will come to an end. This chapter provides a broad philosophical discussion of what might be needed to construct a theoretical machinery that could be used to understand the obstacles and identify the alternative designs. The key issue that has been addressed is simple to formulate: given a physical system, what can it compute? There is an enormous conceptual depth to this question and some specific aspects are systematically discussed. The discussion covers digital philosophy of computation, two reasons why rocks cannot be used for computation are given, a new depth to the ontology of number, and the ensemble computation inspired by recent understanding of the computing ability of living cell aggregates.
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5. |
- Konkoli, Zoran, 1966, et al.
(author)
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Reservoir computing with computational matter
- 2018
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In: Natural Computing Series. - Cham : Springer International Publishing. - 1619-7127. ; , s. 269-293
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Book chapter (other academic/artistic)abstract
- The reservoir computing paradigm of information processing has emerged as a natural response to the problem of training recurrent neural networks. It has been realized that the training phase can be avoided provided a network has some well-defined properties, e.g. the echo state property. This idea has been generalized to arbitrary artificial dynamical systems. In principle, any dynamical system could be used for advanced information processing applications provided that such a system has the separation and the approximation property. To carry out this idea in practice, the only auxiliary equipment that is needed is a simple read-out layer that can be used to access the internal states of the system. In the following, several applications scenarios of this generic idea are discussed, together with some related engineering aspects. We cover both practical problems one might meet when trying to implement the idea, and discuss several strategies of solving such problems.
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6. |
- Valderhaug, Vibeke D., et al.
(author)
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Early functional changes associated with alpha-synuclein proteinopathy in engineered human neural networks
- 2021
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In: American Journal of Physiology - Cell Physiology. - : American Physiological Society. - 0363-6143 .- 1522-1563. ; 320:6, s. C1141-C1152
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Journal article (peer-reviewed)abstract
- A patterned spread of proteinopathy represents a common characteristic of many neurodegenerative diseases. In Parkinson's disease (PD), misfolded forms of α-synuclein proteins accumulate in hallmark pathological inclusions termed Lewy bodies and Lewy neurites. Such protein aggregates seem to affect selectively vulnerable neuronal populations in the substantia nigra and to propagate within interconnected neuronal networks. Research findings suggest that these proteinopathic inclusions are present at very early time points in disease development, even before clear behavioral symptoms of dysfunction arise. In this study, we investigate the early pathophysiology developing after induced formation of such PD-related α-synuclein inclusions in a physiologically relevant in vitro setup using engineered human neural networks. We monitor the neural network activity using multielectrode arrays (MEAs) for a period of 3 wk following proteinopathy induction to identify associated changes in network function, with a special emphasis on the measure of network criticality. Self-organized criticality represents the critical point between resilience against perturbation and adaptational flexibility, which appears to be a functional trait in self-organizing neural networks, both in vitro and in vivo. We show that although developing pathology at early onset is not clearly manifest in standard measurements of network function, it may be discerned by investigating differences in network criticality states.
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7. |
- Valderhaug, Vibeke Devold, et al.
(author)
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Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation
- 2024
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In: Frontiers in Cellular Neuroscience. - : Frontiers Media S.A.. - 1662-5102. ; 18
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Journal article (peer-reviewed)abstract
- Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been widely linked to Parkinson’s disease, where the G2019S variant has been shown to contribute uniquely to both familial and sporadic forms of the disease. LRRK2-related mutations have been extensively studied, yet the wide variety of cellular and network events related to these mutations remain poorly understood. The advancement and availability of tools for neural engineering now enable modeling of selected pathological aspects of neurodegenerative disease in human neural networks in vitro. Our study revealed distinct pathology associated dynamics in engineered human cortical neural networks carrying the LRRK2 G2019S mutation compared to healthy isogenic control neural networks. The neurons carrying the LRRK2 G2019S mutation self-organized into networks with aberrant morphology and mitochondrial dynamics, affecting emerging structure–function relationships both at the micro-and mesoscale. Taken together, the findings of our study points toward an overall heightened metabolic demand in networks carrying the LRRK2 G2019S mutation, as well as a resilience to change in response to perturbation, compared to healthy isogenic controls.
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