Can environmental conditions experienced in early life influence future generations?

The consequences of early developmental conditions for performance in later life are now subjected to convergent interest from many different biological sub-disciplines. However, striking data, largely from the biomedical literature, show that environmental effects experienced even before conception can be transmissible to subsequent generations. Here, we review the growing evidence from natural systems for these cross-generational effects of early life conditions, showing that they can be generated by diverse environmental stressors, affect offspring in many ways and can be transmitted directly or indirectly by both parental lines for several generations. In doing so, we emphasize why early life might be so sensitive to the transmission of environmentally induced effects across generations. We also summarize recent theoretical advancements within the field of developmental plasticity, and discuss how parents might assemble different ‘internal’ and ‘external’ cues, even from the earliest stages of life, to instruct their investment decisions in offspring. In doing so, we provide a preliminary framework within the context of adaptive plasticity for understanding inter-generational phenomena that arise from early life conditions

Stunting and Selection Effects of Famine: A Case Study of the Great Chinese Famine

Many developing countries experience famine. If survival is related to height, the increasingly common practice of using height as a measure of well-being may be misleading. We devise a novel method for disentangling the stunting from the selection effects of famine. Using data from the 1959-1961 Great Chinese Famine, we find that taller children were more likely to survive the famine. Controlling for selection, we estimate that children under the age of five who survived the famine grew up to be 1 to 2 cm shorter. Our results suggest that average height is potentially a biased measure of economic conditions during childhood.Famine, height, China, panel data

Automatic plant pest detection and recognition using k-means clustering algorithm and correspondence filters

Plant pest recognition and detection is vital for food security, quality of life and a stable agricultural economy. This research demonstrates the combination of the k-means clustering algorithm and the correspondence filter to achieve pest detection and recognition. The detection of the dataset is achieved by partitioning the data space into Voronoi cells, which tends to find clusters of comparable spatial extents, thereby separating the objects (pests) from the background (pest habitat). The detection is established by extracting the variant distinctive attributes between the pest and its habitat (leaf, stem) and using the correspondence filter to identify the plant pests to obtain correlation peak values for different datasets. This work further establishes that the recognition probability from the pest image is directly proportional to the height of the output signal and inversely proportional to the viewing angles, which further confirmed that the recognition of plant pests is a function of their position and viewing angle. It is encouraging to note that the correspondence filter can achieve rotational invariance of pests up to angles of 360 degrees, which proves the effectiveness of the algorithm for the detection and recognition of plant pests

Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring

Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl-D-aspartate receptor (NMDAR)–mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia

Divergences for prototype-based classification and causal structure discovery:Theory and application to natural datasets

Dit proefschrift bestaat uit twee delen. In het eerste deel beschrijven we hoe de op prototypen gebaseerde classificator LVQ uitgebreid kan worden door gebruik te maken van maten uit de informatie theorie. Daarnaast vergelijken we verschillende manieren van datarepresentatie in deze LVQ configuratie, in dit geval histogrammen van foto’s, SIFT- en SURF-kenmerken. We tonen hoe hiervoor een enkele gecombineerde afstandsmaat kan worden geformuleerd, door de afzonderlijke afstandsmaten samen te nemen. In het tweede deel onderzoeken we het vinden van causale verbanden en toepassingen op problemen die uit het leven zijn gegrepen. Daarnaast verkennen we de combinatie met relevantie leren in LVQ en tonen we enkele toepassingen

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Intrauterine and genetic risk factors for proliferative diabetic retinopathy

Diabetes is a complex progressive metabolic disorder characterized by hyperglycemia and caused by different etiopathogenic factors. Individuals with diabetes have heterogeneous clinical representation and increased risk of micro- and macrovascular complications. Diabetic retinopathy (DR) is the most frequent microvascular complication of diabetes and one of the leading causes of blindness. Currently, existing treatment modalities target a severe sight-threatening form of the disease, proliferative DR (PDR), and are characterized by significant side effects. The prevailing strategy for prevention or slowing down DR progression is glucose-lowering therapy, which is not efficient enough and might be harming to older groups of patients. Risk factors for PDR include duration of diabetes, hypertension, dyslipidemia, genetics and environment, and their interplay. The adverse intrauterine environment, particularly exposure to prenatal famine, was shown to play an important role in predisposition to diverse metabolic disorders in adults such as type 2 diabetes (T2D), hypertension, and cardiovascular diseases (CVD). In this Ph.D. thesis, we aimed to study novel diabetes subgroups based on pathophysiological characteristics of patients, highlighting subgroup(s) with an elevated risk of diabetic complications, particularly PDR. Further, we aimed to investigate the association of intrauterine exposure to famine with the risk of PDR in adult individuals with T2D. Finally, we wanted to study the molecular mechanisms linked to famine-related PDR. In paper 1, we performed a k-means cluster analysis to identify novel subgroups of individuals with new-onset and long-term diabetes, and estimated the risks of diabetic complications using logistic regression. In paper 2, we evaluated effect of intrauterine famine exposure on the risk of PDR in individuals with T2D using logistic regression adjusted for established risk factors such as age, sex, duration of diabetes and HbA1c. In paper 3, we performed candidate gene analysis using generalized estimation equation (GEE) to study the effect of interaction between SNPs and perinatal famine exposure on the risk of PDR. In paper 4, we performed genome-wide association (GWAS) and interaction (GWIS) studies using a linear mixed model (LMM) to investigate molecular underpinnings of famine-related PDR. In paper 1, we identified three subgroups with severe diabetes and two subgroups with mild diabetes. The highest risk of PDR was observed in the severe autoimmune diabetes (SAID) and severe insulin-deficient diabetes (SIDD) subgroups and the lowest in the insulin-resistant obesity-related diabetes 2 (IROD2) subgroup. In paper 2, we demonstrated that individuals with T2D, who were perinatally exposed to famine had an elevated risk of PDR in adult life. In paper 3, we demonstrated a significant association between famine-associated PDR and SNPs which were located in genes with neuronal function. In paper 4, we identified diverse pathways potentially linked to famine-related PDR, among them the most significant were lipid metabolism and inflammation pathways. In conclusion, we suggested that the altered development of neurovascular unit in the retina due to exposure to intrauterine famine may increase susceptibility to PDR later in life. Changes in metabolic adaptations during developmental programming induced by adverse early life events may affect insulin secretion and lipid metabolism, which consequently may increase predisposition to PDR under diabetes environment in adulthood. We suggested that drugs targeting these mechanisms in addition to glucose-lowering treatments may be beneficial for the prevention or slowing down the progression to PDR in the early stages of the disease.Diabetes er en kompleks progressiv metabolsk sykdom som kjennetegnes ved hyperglykemi og er forårsaket av forskjellige etiopatogenetiske faktorer. Personer med diabetes har heterogen klinisk representasjon og økt risiko for mikro- og makrovaskulære komplikasjoner. Diabetisk retinopati (DR) er den hyppigste mikrovaskulære komplikasjonen ved diabetes og en av de viktigste årsakene til blindhet. For tiden er eksisterende behandlingsmetoder rettet mot en alvorlig synstruende form av sykdommen, proliferativ DR (PDR), og medfører betydelige bivirkninger. Den rådende strategien for forebygging eller forsinking av DR-progresjon er glukosesenkende terapi, som ikke er effektiv nok og kan være skadelig for eldre pasienter. Risikofaktorer for PDR inkluderer varighet av diabetes, hypertensjon, dyslipidemi, genetikk og miljø, og deres samspill. Det ugunstige intrauterine miljøet, spesielt eksponering for prenatal hungersnød, ble vist å spille en viktig rolle i predisposisjon for ulike metabolske forstyrrelser hos voksne som type 2 diabetes (T2D), hypertensjon og kardiovaskulære sykdommer (CVD). I denne doktorgradsavhandlingen, har vi hatt som mål å studere nye diabetes-undergrupper basert på patofysiologiske egenskaper hos pasienter, og fremheve undergruppe(r) med økt risiko for diabetiske komplikasjoner, spesielt PDR. Videre hadde vi som mål å undersøke sammenheng mellom intrauterin eksponering for hungersnød og risikoen for utvikling av PDR hos voksne med T2D. Til slutt ønsket vi å studere de molekylære mekanismene knyttet til hungersnød-relatert PDR. I artikkel 1 utførte vi en k-means-klyngeanalyse for å identifisere nye undergrupper av individer med nyoppstått og langvarig diabetes, og estimerte risikoen for diabetiske komplikasjoner ved hjelp av logistisk regresjon. I artikkel 2 evaluerte vi effekten av eksponering for intrauterin hungersnød på risikoen for PDR hos individer med T2D ved bruk av logistisk regresjon justert for etablerte risikofaktorer som alder, kjønn, varighet av diabetes og HbA1c. I artikkel 3 utførte vi kandidatgenanalyse ved å bruke generalisert estimeringsligning (GEE) for å studere effekten av interaksjon mellom SNP-er og perinatal hungersnødeksponering på risikoen for PDR. I artikkel 4 utførte vi genomomfattende assosiasjonsstudier (GWAS) og interaksjonsstudier (GWIS) ved å bruke en lineær blandet modell (LMM) for å undersøke molekylært grunnlag for hungersnødrelatert PDR. I artikkel 1 identifiserte vi tre undergrupper med alvorlig diabetes og to undergrupper med mild diabetes. Den høyeste risikoen for PDR ble observert i undergruppene med alvorlig diabetes type 1 (SAID) og alvorlig diabetes type 2 (SIDD), og den laveste i undergruppen insulinresistent fedme-relatert diabetes 2 (IROD2). I artikkel 2 viste vi at personer med T2D, som ble perinatalt utsatt for hungersnød, hadde en forhøyet risiko for utvikling av PDR i voksenlivet. I artikkel 3 viste vi en signifikant sammenheng mellom hungersnødassosiert PDR og SNP-er som var lokalisert i gener med nevronal funksjon. I artikkel 4 identifiserte vi ulike veier som er potensielt knyttet til hungersnød-relatert PDR, blant dem var de mest betydningsfulle lipidmetabolisme og betennelsesveier. Avslutningsvis foreslo vi at den endrede utviklingen av nevrovaskulær kretsløp i netthinnen på grunn av eksponering for intrauterin hungersnød kan øke følsomheten for PDR senere i livet. Endringer i metabolske tilpasninger under utviklingsprogrammering indusert av uønskede hendelser i tidlig liv kan påvirke insulinsekresjon og lipidmetabolisme, som følgelig kan øke predisposisjon for PDR under diabetesmiljø i voksen alder. Vi foreslo at medikamenter som retter seg mot disse mekanismene i tillegg til glukosesenkende behandlinger kan være gunstig for forebygging eller forsinke progresjon til PDR i de tidlige stadiene av sykdommen.Doktorgradsavhandlin

The effect of peer and parental smoking on adolescent smoking initiation: Exploring potential moderators

The factors that contribute to smoking initiation among adolescents are poorly understood. The current approaches to smoking prevention may have achieved their maximum potential as evidenced by a stalling in the decline in smoking rates. To date, approaches to smoking prevention based on social and individual factors have previously met with limited success. A promising new approach will be to examine the interaction between social and individual factors and the effects of their interaction on smoking initiation. Parental and peer smoking behaviors are well-known risk factors for smoking initiation. Several theoretical models suggest that perceptual or interpretative processes may moderate the influence of factors such as these on the smoking initiation process. This study looks at age (as a proxy for adolescent development), depression and school performance as potential moderators of the impact of parental or peer smoking. This study uses a large longitudinal sample (The Teenage Attitudes and Practices Surveys -- 1989 and 1993) to explore for these relationships. Results show very limited support for the impact of potential moderated relationships, with only one of the six hypothesized interactions being supported (peer smoking and school performance). This would suggest that theoretical models which include concepts of perceptual or interpretative processes as moderating influences need to continue to evaluate their validity. Another finding of the study is a significant main effect of school performance on smoking initiation --a relationship which has not been previously reported in a national longitudinal sample. This study also found support for depression as an antecedent to smoking initiation -- a relationship whose causal direction continues to be controversial. Continued exploration of the complex relationships between these social and individual factors may allow for the development of more effective evidence-based smoking prevention programs