Our latest publication on the inhibition of Alzheimer disease (AD) through mitophagy consolidates the 'defective mitophagy hypothesis of AD etiology'. Dementia (majorly AD) affects over 50 million ...people worldwide, and for AD there is no cure. AD leads to progressive loss of cognition, and pathological hallmarks of AD include aggregates of amyloid-β peptides extracellularly and MAPT (microtubule associated protein tau) intracellularly. However, there is no conclusive link between these pathological markers and cognitive symptoms. Anti-AD drug candidates have repeatedly failed, which led us to investigate other molecular etiologies to guide drug development. Mitochondria produce the majority of cellular ATP, affect Ca
2+
and redox signaling, and promote developmental and synaptic plasticity. Mitochondrial dysfunction and accumulation of damaged mitochondria are common in brain tissues from AD patients and transgenic AD animal models, but the underlying molecular mechanisms are not fully understood. Damaged mitochondria are removed through multiple pathways, the major 2 being mitophagy and the ubiquitin proteasome pathway. Mitophagy is essential for clearance of damaged mitochondria to maintain mitochondrial homeostasis, ATP production, and neuronal activity and survival. These pieces of evidence converge on the 'defective mitophagy hypothesis of AD etiology', and the current cross-species study provides strong support for this hypothesis.
Here we develop an option pricing method for European options based on the Fourier-cosine series and call it the COS method. The key insight is in the close relation of the characteristic function ...with the series coefficients of the Fourier-cosine expansion of the density function. In most cases, the convergence rate of the COS method is exponential and the computational complexity is linear. Its range of application covers underlying asset processes for which the characteristic function is known and various types of option contracts. We will present the method and its applications in two separate parts. The first one is this paper, where we deal with European options in particular. In a follow-up paper we will present its application to options with early-exercise features.
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Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Neurons affected in Alzheimer’s disease (AD) experience mitochondrial dysfunction and a bioenergetic deficit that occurs early and promotes the disease-defining amyloid beta peptide (Aβ) and Tau ...pathologies. Emerging findings suggest that the autophagy/lysosome pathway that removes damaged mitochondria (mitophagy) is also compromised in AD, resulting in the accumulation of dysfunctional mitochondria. Results in animal and cellular models of AD and in patients with sporadic late-onset AD suggest that impaired mitophagy contributes to synaptic dysfunction and cognitive deficits by triggering Aβ and Tau accumulation through increases in oxidative damage and cellular energy deficits; these, in turn, impair mitophagy. Interventions that bolster mitochondrial health and/or stimulate mitophagy may therefore forestall the neurodegenerative process in AD.
On-machine and in-process surface metrology are important for quality control in manufacturing of precision surfaces. The classifications, requirements and tasks of on-machine and in-process surface ...metrology are addressed. The state-of-the-art on-machine and in-process measurement systems and sensor technologies are presented. Error separation algorithms for removing machine tool errors, which is specially required in on-machine and in-process surface metrology, are overviewed, followed by a discussion on calibration and traceability. Advanced techniques on sampling strategies, measurement systems-machine tools interface, data flow and analysis as well as feedbacks for compensation manufacturing are then demonstrated. Future challenges and developing trends are also discussed.
•A recursive forecasting framework for a long lead-time forecast at multi-scales.•ANN and LSTM models provide accurate daily forecasts up to 20 days ahead.•LSTM model outperforms ANN model in long ...lead-time daily forecasting.•Parameter setting is the key for long lead-time streamflow forecasting.
Long lead-time streamflow forecasting is of great significance for water resources planning and management in both the short and long terms. Despite of some studies using machine learning methods in streamflow forecasting, only few studies have been conducted to explore long lead-time forecasting capabilities of these methods, and gain an insight into systematic comparison of model forecasting performance in both the short and long terms. In this work, an artificial neural network (ANN) and a long short term memory (LSTM), a powerful tool for learning long-term temporal dependencies and capturing nonlinear relationship, have been adopted to forecast streamflow at daily and monthly scales for a long lead-time period. For long lead-time streamflow forecasting, a recursive forecasting procedure, which takes the last one-step-ahead forecast as a new input for the next-step-ahead forecast, is used in the ANN and LSTM forecasting systems. Two models are trained and validated for streamflow forecasting using the rainfall and runoff datasets collected from the Nan River Basin and Ping River Basin, Thailand, covering the period 1974 to 2014. To further explore the impact of parameter settings on model performance, two parameters, i.e. the length of time lag and the number of maximum epochs, are examined in the ANN and LSTM models. The main findings are highlighted here. First, with an optimal setting up of model parameters, both the ANN and LSTM model can provide accurate daily forecasting (up to 20 days ahead). Second, in comparison to the ANN model, the LSTM model exhibits better model performance in long lead-time daily forecasting, but less satisfactory in multi-monthly forecasting due to lack of large monthly training dataset. Third, the selection of the length of the time lag and number of maximum epochs used in both ANN and LSTM modelling are the key for long lead-time streamflow forecasting at daily and monthly scales. These findings suggest that the LSTM could be advance in daily streamflow forecasting and thus would be helpful to assist in strategy decisions in water resource management.
The coenzyme NAD+ is critical in cellular bioenergetics and adaptive stress responses. Its depletion has emerged as a fundamental feature of aging that may predispose to a wide range of chronic ...diseases. Maintenance of NAD+ levels is important for cells with high energy demands and for proficient neuronal function. NAD+ depletion is detected in major neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases, cardiovascular disease and muscle atrophy. Emerging evidence suggests that NAD+ decrements occur in various tissues during aging, and that physiological and pharmacological interventions bolstering cellular NAD+ levels might retard aspects of aging and forestall some age-related diseases. Here, we discuss aspects of NAD+ biosynthesis, together with putative mechanisms of NAD+ action against aging, including recent preclinical and clinical trials.
Recent discoveries have demonstrated an age-dependent decrease in cellular and/or tissue NAD+ levels in laboratory animal models. Moreover, NAD+ depletion has been linked to multiple hallmarks of aging.
In premature aging animal models, NAD+ levels are decreased, while NAD+ replenishment can improve lifespan and healthspan through DNA repair and mitochondrial maintenance.
Mitochondrial autophagy (mitophagy) has a major role in clearance of damaged and/or dysfunctional mitochondria, and compromised mitophagy has been linked to metabolic disorders, neurodegeneration including Alzheimer’s disease (AD) and Parkinson’s disease (PD) in addition to aging, and other age-related diseases.
New evidence suggests that NAD+ precursors, such as nicotinamide and nicotinamide riboside, forestall pathology and cognitive decline in mouse models of AD.
NAD+ supplementation can inhibit multiple aging features in animal models. This highlights essential roles for NAD+ in maintaining healthy aging, and suggests that NAD+ repletion may have broad benefits in humans.
•Covered broad fields of ageing in China: statistics, basic and translational research, long-term care, policy and social networks.•Provided more detailed numerical updates of the ageing challenges ...in China.•New features of the aging-related challenges, e.g., oral ageing and STDs in the elderly in China.•A new and independent section on immune ageing.•We also mentioned the COVID-19-induced death in the Chinese elderly.
One of the key issues facing public healthcare is the global trend of an increasingly ageing society which continues to present policy makers and caregivers with formidable healthcare and socio-economic challenges. Ageing is the primary contributor to a broad spectrum of chronic disorders all associated with a lower quality of life in the elderly. In 2019, the Chinese population constituted 18 % of the world population, with 164.5 million Chinese citizens aged 65 and above (65+), and 26 million aged 80 or above (80+). China has become an ageing society, and as it continues to age it will continue to exacerbate the burden borne by current family and public healthcare systems. Major healthcare challenges involved with caring for the elderly in China include the management of chronic non-communicable diseases (CNCDs), physical frailty, neurodegenerative diseases, cardiovascular diseases, with emerging challenges such as providing sufficient dental care, combating the rising prevalence of sexually transmitted diseases among nursing home communities, providing support for increased incidences of immune diseases, and the growing necessity to provide palliative care for the elderly. At the governmental level, it is necessary to make long-term strategic plans to respond to the pressures of an ageing society, especially to establish a nationwide, affordable, annual health check system to facilitate early diagnosis and provide access to affordable treatments. China has begun work on several activities to address these issues including the recent completion of the of the Ten-year Health-Care Reform project, the implementation of the Healthy China 2030 Action Plan, and the opening of the National Clinical Research Center for Geriatric Disorders. There are also societal challenges, namely the shift from an extended family system in which the younger provide home care for their elderly family members, to the current trend in which young people are increasingly migrating towards major cities for work, increasing reliance on nursing homes to compensate, especially following the outcomes of the ‘one child policy’ and the ‘empty-nest elderly’ phenomenon. At the individual level, it is important to provide avenues for people to seek and improve their own knowledge of health and disease, to encourage them to seek medical check-ups to prevent/manage illness, and to find ways to promote modifiable health-related behaviors (social activity, exercise, healthy diets, reasonable diet supplements) to enable healthier, happier, longer, and more productive lives in the elderly. Finally, at the technological or treatment level, there is a focus on modern technologies to counteract the negative effects of ageing. Researchers are striving to produce drugs that can mimic the effects of ‘exercising more, eating less’, while other anti-ageing molecules from molecular gerontologists could help to improve ‘healthspan’ in the elderly. Machine learning, ‘Big Data’, and other novel technologies can also be used to monitor disease patterns at the population level and may be used to inform policy design in the future. Collectively, synergies across disciplines on policies, geriatric care, drug development, personal awareness, the use of big data, machine learning and personalized medicine will transform China into a country that enables the most for its elderly, maximizing and celebrating their longevity in the coming decades. This is the 2nd edition of the review paper (Fang EF et al., Ageing Re. Rev. 2015).
Summary
This paper presents a novel model reduction method: deep learning reduced order model, which is based on proper orthogonal decomposition and deep learning methods. The deep learning approach ...is a recent technological advancement in the field of artificial neural networks. It has the advantage of learning the nonlinear system with multiple levels of representation and predicting data. In this work, the training data are obtained from high fidelity model solutions at selected time levels. The long short‐term memory network is used to construct a set of hypersurfaces representing the reduced fluid dynamic system. The model reduction method developed here is independent of the source code of the full physical system.
The reduced order model based on deep learning has been implemented within an unstructured mesh finite element fluid model. The performance of the new reduced order model is evaluated using 2 numerical examples: an ocean gyre and flow past a cylinder. These results illustrate that the CPU cost is reduced by several orders of magnitude whilst providing reasonable accuracy in predictive numerical modelling.
This paper presents a novel model reduction method: deep learning reduced order model, which is based on proper orthogonal decomposition and deep learning methods. The reduced order model based on deep learning has been implemented within an unstructured mesh finite element fluid model. The performance of the new reduced order model is evaluated using 2 numerical examples: an ocean gyre and flow past a cylinder. These results illustrate that the CPU cost is reduced by several orders of magnitude whilst providing reasonable accuracy in predictive numerical modelling.
The transcription factor nuclear factor kappa B (NF-κB) and the long non-coding RNA (lncRNA) HOTAIR (HOX transcript antisense RNA) have diverse functional roles in cancer. In this study, we show that ...upregulation of HOTAIR induced platinum resistance in ovarian cancer, and increased HOTAIR levels were observed in recurrent platinum-resistant ovarian tumors vs primary ovarian tumors. To investigate the role of HOTAIR during DNA damage induced by platinum, we monitored double-strand breaks and show that HOTAIR expression results in sustained activation of DNA damage response (DDR) after platinum treatment. We demonstrate that ectopic expression of HOTAIR induces NF-κB activation during DDR and interleukin-6 and interleukin-6 expression, both key NF-κB target genes. We show that HOTAIR regulates activation of NF-κB by decreasing Iκ-Bα (NF-κB inhibitor) and establish that by inducing prolonged NF-κB activation and expression of NF-κB target genes during DNA damage, HOTAIR has a critical role in cellular senescence and platinum sensitivity. Our findings suggest that an NF-κB-HOTAIR axis drives a positive-feedback loop cascade during DDR and contributes to cellular senescence and chemotherapy resistance in ovarian and other cancers.
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