Characteristics of patients with haematological and breast cancer (1996–2009) who died of heart failure-related causes after cancer therapy

Aims: To describe the characteristics and time to death of patients with breast or haematological cancer who died of heart failure (HF) after cancer therapy. Patients with an index admission for HF who died of HF-related causes (IAHF) and those with no index admission for HF who died of HF-related causes (NIAHF) were compared. Methods and results: We performed a linked data analysis of cancer registry, death registry, and hospital administration records (n = 15 987). Index HF admission must have occurred after cancer diagnosis. Of the 4894 patients who were deceased (30.6% of cohort), 734 died of HF-related causes (50.1% female) of which 279 (38.0%) had at least one IAHF (41.9% female) post-cancer diagnosis. Median age was 71 years [interquartile range (IQR) 62–78] for IAHF and 66 years (IQR 56–74) for NIAHF. There were fewer chemotherapy separations for IAHF patients (median = 4, IQR 2–9) compared with NIAHF patients (median = 6, IQR 2–12). Of the IAHF patients, 71% had died within 1 year of the index HF admission. There was no significant difference in HF-related mortality in IAHF patients compared with NIAHF (HR, 1.10, 95% CI, 0.94–1.29, P = 0.225). Conclusions: The profile of IAHF patients who died of HF-related causes after cancer treatment matched the current profile of HF in the general population (over half were aged ≥70 years). However, NIAHF were younger (62% were aged ≤69 years), female patients with breast cancer that died of HF-related causes before hospital admission for HF-related causes—a group that may have been undiagnosed or undertreated until death

Evolutionary and Reinforcement Fuzzy Control

Many modern and classical techniques exist for the design of control systems. However, many real world applications are inherently complex and the application of traditional design and control techniques is limited. In addition, no single design method exists which can be applied to all types of system. Due to this 'deficiency', recent years have seen an exponential increase in the use of methods loosely termed 'computational intelligent techniques' or 'soft- computing techniques'. Such techniques tend to solve problems using a population of individual elements or potential solutions or the flexibility of a network as opposed to using a rigid, single point of computing. Through use of computational redundancies, soft-computing allows unmatched tractability in practical problem solving. The intelligent paradigm most successfully applied to control engineering, is that of fuzzy logic in the form of fuzzy control. The motivation of using fuzzy control is twofold. First, it allows one to incorporate heuristics into the control strategy, such as the model operator actions. Second, it allows nonlinearities to be defined in an intuitive way using rules and interpolations. Although it is an attractive tool, there still exist many problems to be solved in fuzzy control. To date most applications have been limited to relatively simple problems of low dimensionality. This is primarily due to the fact that the design process is very much a trial and error one and is heavily dependent on the quality of expert knowledge provided by the operator. In addition, fuzzy control design is virtually ad hoc, lacking a systematic design procedure. Other problems include those associated with the curse of dimensionality and the inability to learn and improve from experience. While much work has been carried out to alleviate most of these difficulties, there exists a lack of drive and exploration in the last of these points. The objective of this thesis is to develop an automated, systematic procedure for optimally learning fuzzy logic controllers (FLCs), which provides for autonomous and simple implementations. In pursuit of this goal, a hybrid method is to combine the advantages artificial neural networks (ANNs), evolutionary algorithms (EA) and reinforcement learning (RL). This overcomes the deficiencies of conventional EAs that may omit representation of the region within a variable's operating range and that do not in practice achieve fine learning. This method also allows backpropagation when necessary or feasible. It is termed an Evolutionary NeuroFuzzy Learning Intelligent Control technique (ENFLICT) model. Unlike other hybrids, ENFLICT permits globally structural learning and local offline or online learning. The global EA and local neural learning processes should not be separated. Here, the EA learns and optimises the ENFLICT structure while ENFLICT learns the network parameters. The EA used here is an improved version of a technique known as the messy genetic algorithm (mGA), which utilises flexible cellular chromosomes for structural optimisation. The properties of the mGA as compared with other flexible length EAs, are that it enables the addressing of issues such as the curse of dimensionality and redundant genetic information. Enhancements to the algorithm are in the coding and decoding of the genetic information to represent a growing and shrinking network; the defining of the network properties such as neuron activation type and network connectivity; and that all of this information is represented in a single gene. Another step forward taken in this thesis on neurofuzzy learning is that of learning online. Online in this case refers to learning unsupervised and adapting to real time system parameter changes. It is much more attractive because the alternative (supervised offline learning) demands quality learning data which is often expensive to obtain, and unrepresentative of and inaccurate about the real environment. First, the learning algorithm is developed for the case of a given model of the system where the system dynamics are available or can be obtained through, for example, system identification. This naturally leads to the development of a method for learning by directly interacting with the environment. The motivation for this is that usually real world applications tend to be large and complex, and obtaining a mathematical model of the plant is not always possible. For this purpose the reinforcement learning paradigm is utilised, which is the primary learning method of biological systems, systems that can adapt to their environment and experiences, in this thesis, the reinforcement learning algorithm is based on the advantage learning method and has been extended to deal with continuous time systems and online implementations, and which does not use a lookup table. This means that large databases containing the system behaviour need not be constructed, and the procedure can work online where the information available is that of the immediate situation. For complex systems of higher order dimensions, and where identifying the system model is difficult, a hierarchical method has been developed and is based on a hybrid of all the other methods developed. In particular, the procedure makes use of a method developed to work directly with plant step response, thus avoiding the need for mathematical model fitting which may be time-consuming and inaccurate. All techniques developed and contributions in the thesis are illustrated by several case studies, and are validated through simulations

Vulnerability to HIV infection among sex worker and non-sex worker female injecting drug users in Dhaka, Bangladesh: evidence from the baseline survey of a cohort study

BACKGROUND: Very little is known about female injecting drug users (IDU) in Bangladesh but anecdotal evidence suggests that they are hidden and very vulnerable to HIV through both their injection sharing and sexual risk behaviors. In order to better understand the risks and vulnerability to HIV of female IDU, a cohort study was initiated through which HIV prevalence and risk behaviors was determined. METHODS: All female IDU (those who had injected in the last six months and were 15 years or older) who could be identified from three cities in the Dhaka region were enrolled at the baseline of a cohort study. The study was designed to determine risk behaviors through interviews using a semi-structured questionnaire and measure prevalence of HIV, hepatitis C and syphilis semiannually. At the baseline of the cohort study 130 female IDU were recruited and female IDU selling sex in the last year (sex workers) versus those not selling sex (non-sex workers) were compared using descriptive statistics and logistic regression. RESULTS: Of the 130 female IDU enrolled 82 were sex workers and 48 were non-sex workers. None had HIV but more sex workers (60%) had lifetime syphilis than non-sex workers (37%). Fewer sex worker than non-sex worker IDU lived with families (54.9% and 81.3% respectively), but more reported lending needles/syringes (29.3% and 14.6% respectively) and sharing other injection paraphernalia (74.4% and 56.3% respectively) in the past six months. Although more sex workers used condoms during last sex than non-sex workers (74.4% and 43.3% respectively), more reported anal sex (15.9% and 2.1% respectively) and serial sex with multiple partners (70.7% and 0% respectively). Lifetime sexual violence and being jailed in the last year was more common in sex workers. CONCLUSION: Female IDU are vulnerable to HIV through their injection and sexual risk behaviors and sex worker IDU appear especially vulnerable. Services such as needle exchange programs should become more comprehensive to address the needs of female IDU

Heart Failure Following Cancer Therapy in Patients with Hematological Malignancies Aged 18 Years and Under: A Linked Health Data Analysis (1996-2009)

Made available in accordance with Publisher's Open Access policyntroduction: The causal link between chemotherapy treatments and subsequent cardiotoxicity is well established, particularly for children with hematological malignancies. Little information exists on the characteristics and outcomes for patients with heart failure (HF) after chemotherapy. This study aimed to describe the characteristics, survival and mortality of patients who received chemotherapy for hematological cancer (leukemias, lymphomas and related disorders) before 18 years old and subsequently developed HF compared to those who did not. Methods: Linked health data (1996-2009) from the Queensland Cancer Registry, Death Registry and Hospital Administration records for HF and chemotherapy admissions were reviewed. From all breast and hematological cancers patients (n=73,158), 15,987 received chemotherapy, including 819 patients aged ≤18 years at time of cancer diagnosis. Patients were categorized as those with an index HF admission (occurred after cancer diagnosis) and those without an index HF admission (non HF). Results: Of the 819 patients, 3.7% (n=30) had an index HF admission. Median age of HF patients at time of cancer diagnosis was 5 years (IQR 3-12) compared to 7 years (IQR 3-14) in the non HF group (p=0.503). Median follow up from cancer diagnosis was 2.5 years in the HF group compared to 5.42 years in the non HF group (p<0.01). Of those who developed HF, 70% (n=21) had the index admission within 12 months of their cancer diagnosis. Of those with HF, 53.3% (n=16) died (all cause) compared to 14.6% (n=115) with no HF. On adjustment for age, sex and chemotherapy admissions, HF patients had an almost 5 fold increased mortality risk compared to non HF patients (HR 4.91 [95% CI, 2.88-8.36]) Conclusions: This study demonstrated that in children with hematological cancers the onset of HF occurred soon after chemotherapy and mortality risk is almost 5 times that of children who do not develop HF. Innovative strategies are still needed for the prevention and management of cardiotoxicity in this populatio

Sustainable supply chain management towards disruption and organizational ambidexterity:A data driven analysis

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts’ evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations.Peer reviewe

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations

Projecting marine fish production and catch potential in Bangladesh in the 21st century under long-term environmental change and management scenarios

The fisheries sector is crucial to the Bangladeshi economy and wellbeing, accounting for 4.4% of national Gross Domestic Product (GDP) and 22.8% of agriculture sector production, and supplying ca.60% of the national animal protein intake. Fish is vital to the 16 million Bangladeshis living near the coast, a number that has doubled since the 1980s. Here we develop and apply tools to project the long term productive capacity of Bangladesh marine fisheries under climate and fisheries management scenarios, based on downscaling a global climate model, using associated river flow and nutrient loading estimates, projecting high resolution changes in physical and biochemical ocean properties, and eventually projecting fish production and catch potential under different fishing mortality targets. We place particular interest on Hilsa shad (Tenualosa ilisha), which accounts for ca.11% of total catches, and Bombay duck (Harpadon nehereus), a low price fish that is the second highest catch in Bangladesh and is highly consumed by low income communities. It is concluded that the impacts of climate change, under greenhouse emissions scenario A1B, are likely to reduce the potential fish production in the Bangladesh Exclusive Economic Zone (EEZ) by less than 10%. However, these impacts are larger for the two target species. Under sustainable management practices we expect Hilsa shad catches to show a minor decline in potential catch by 2030 but a significant (25%) decline by 2060. However, if overexploitation is allowed catches are projected to fall much further, by almost 95% by 2060, compared to the Business as Usual scenario for the start of the 21st century. For Bombay duck, potential catches by 2060 under sustainable scenarios will produce a decline of less than 20% compared to current catches. The results demonstrate that management can mitigate or exacerbate the effects of climate change on ecosystem productivity