The gut-brain axis, BDNF, NMDA and CNS disorders

Gastro-intestinal (GI) microbiota and the ‘gut-brain axis’ are proving to be increasingly relevant to early brain development and the emergence of psychiatric disorders. This review focuses on the influence of the GI tract on Brain-Derived Neurotrophic Factor (BDNF) and its relationship with receptors for N-methyl-d-aspartate (NMDAR), as these are believed to be involved in synaptic plasticity and cognitive function. NMDAR may be associated with the development of schizophrenia and a range of other psychopathologies including neurodegenerative disorders, depression and dementias. An analysis of the routes and mechanisms by which the GI microbiota contribute to the pathophysiology of BDNF-induced NMDAR dysfunction could yield new insights relevant to developing novel therapeutics for schizophrenia and related disorders. In the absence of GI microbes, central BDNF levels are reduced and this inhibits the maintenance of NMDAR production. A reduction of NMDAR input onto GABA inhibitory interneurons causes disinhibition of glutamatergic output which disrupts the central signal-to-noise ratio and leads to aberrant synaptic behaviour and cognitive deficits. Gut microbiota can modulate BDNF function in the CNS, via changes in neurotransmitter function by affecting modulatory mechanisms such as the kynurenine pathway, or by changes in the availability and actions of short chain fatty acids (SCFAs) in the brain. Interrupting these cycles by inducing changes in the gut microbiota using probiotics, prebiotics or antimicrobial drugs has been found promising as a preventative or therapeutic measure to counteract behavioural deficits and these may be useful to supplement the actions of drugs in the treatment of CNS disorders

Occupational Status and Earnings Inequality: Evidence from PIHS 2001-02 and PSLM 2004-05

Wage/earnings inequalities are one source of overall inequality in a country. The former inequalities in turn are closely linked with differential occupational status either defined in a contractual or productive/skill sense. Using the Pakistan Standard Classification of Occupations[PSCO (1994)], this paper estimates Gini coefficients for three types (all types, employee, selfemployed) of individuals/earners by occupational status from the Pakistan Integrated Household Survey (PIHS) 2001-02 and Pakistan Social and Living Standards Measurement Survey (PSLM) 2004-05. Long-term trends in earnings inequality from 1992-93 to 2004-05 are documented with the benchmark estimates in the Ahmad (2002) study, while the short-term trends are measured from 2001-02 to 2004-05 for self-employed and paid employee. The longas well as the short-term trends indicate rising earnings disparities within each occupational category. Over the longer period, these disparities have risen in the range of 50 to 100 percent. Shifts across occupation and across employment status indicate doubling of the share of Shop and Market Sales and Services Workers and the transition towards becoming self-employed. A few tentative explanations for the observed increasing occupational inequalities at the individual level are: (a) Availability of credit and improved efficiency of capital market may have relaxed capital constraints of former employees and enabled them to transit as selfemployed. Right-sizing and down-sizing in public organisations may also have pushed the previous employees into utilising the ‘golden handshake’ packages towards self-employment. Assuming that returns on capital (internal or borrowed) are higher and financial contracts are more lucrative than wage contracts, the situation can lead to wider disparities. (b) At the paid employee level, the fall in the share of workers in elementary occupations improved the wage contracts of those still remaining in this occupation, and thereby increased the income/earnings inequality within this category. (c) Premium on skills, education, experience, and talent, in spite of the entry of a large number of individuals in the Service, Shop and Market Sales Workers category, has widened the inequalities within this category.Earnings Inequality, Occupational Status, Occupational Inequality

Food Security in Pakistan: Can It Be Achieved?

Wide fluctuations in world prices of food-grains, especially rice and wheat, in the seventies and the early eighties forced many developing countries to strive for self-sufficiency in food-grain production. Pakistan is among the countries where near self-sufficiency was achieved in wheat in the early eighties. It also maintained its status as a leading rice-exporting country. However, a continuously high rate of population growth, a changing pattern of income distribution, and a greater level of urbanisation have greatly influenced the demand for food-grains. At the same time, additional factors like a sharp rise in the cost of irrigation, a dramatic decline in the world price of rice, a heavy debt burden, the lack of technology and human capital development, and mismanagement in the distribution system have contributed towards a slower growth of grain production as compared with the levels achieved in the sixties and the eighties. This change in the demand and supply situation with respect to food has necessitated the need to re-evaluate the existing agricultural policies. Within demand and supply constraints, the question is whether or not Pakistan can attain selfsufficiency in wheat while at the same time maintaining its status as a significant exporter of rice. In the immediate future, the situation appears desperate, but in the long-run, when available resources are adequately utilised and consistent policies are adopted, there is hope and optimism. This study not only reviews the current food situation in Pakistan but also develops alternative policy scenarios which are consistent with the target of food security in Pakistan. This paper is developed as follows. The second section reviews the current food situation in Pakistan briefly. Based on supply and demand elasticities, the baseline forecasts or the control solution is generated in the third section. Alternative policy scenarios are developed in the fourth section, and the last section concludes this study.

The Relationship between Real Wages and Output: Evidence from Pakistan

Information on wage levels is essential in evaluating the living standards and conditions of work and life of the workers. Since nominal wage fails to explain the purchasing power of employees, real wage is considered as a major indicator of employees purchasing power and can be used as proxy for their level of income. Any fluctuations in the real wage rate have a significant impact on poverty and the distribution of income. When used in relation with other economic variables, for instance employment or output they are valuable indicators in the analysis of business cycles. There has been a long debate regarding the relationship between real wages and the employment (output). Despite the apparent simplicity, the relationship between real wages and output has remained deceptive both theoretically and empirically. Keynes (1936) viewed cyclical movements in employment along a stable labour demand schedule thus indicating counter cyclical real wages. His deduction is in line with sticky wages and sticky expectations, which augments models like Phillips curve. In these models real wages behaved as counter-cyclical as nominal wages are slow to adjust during recession (decrease in aggregate demand and associated slowdown in price growth). Stickiness of wages or expectations shifts the labour supply over the business cycles [Abraham and Haltiwanger (1995)]. Barro (1990) and Christiano and Eichenbaum (1992) have associated these labour supply shifts with intertemporal labour-leisure substitution. This in response to temporary changes in real interest rates (fiscal policy shocks) could yield counter-cyclical real wages. However, Long and Plosser (1983) and Kydland and Prescott (1982) while studying the real business cycle models highlight on the technology shocks which leads to pro-cyclical real wages.

Effect of increasing salinity on growth and mineral composition of wheat varieties and role of sodium exclusion capacity in salt tolerance mechanisms

A few wheat varieties including two Japanese wheat varieties were evaluated for their salt tolerance at seeding stage, their behavior to increasing salinity levels and role of Na exclusion capacity in salt tolerance mechanisms. The wheat varieties were grown in nutrient solution and subjected to 0 (control), 25,75 and 125 mM NaCl salinity levels for 7 days. Although the shoot growth was reduced while Na contents were increased progressively with increasing salinity in all varieties, the varieties were quite different in their response. Salt tolerant va rieties maintained less reduction in their root and shoot growth and better water relations in their shoots than salt sensitive varieties under saline conditions. The wheat varieties were quite different in their Na exclusion capacity. Poor growth in salt sensitive varieties might be due to higher accumulation of Na in their shoots resulting from low Na exclusion capacity of roots, higher Na transport to shoot and/or inferior compartmentation capability

The Taylor Rule and the Macroeconomic Performance in Pakistan

A widely agreed proposition in modern economics is that policy rules have greater advantage over discretion in improving economic performance. Simple monetary policy instrument rules are feasible options for developing countries lacking the pre-requisites for more sophisticated targeting rules. Notwithstanding the focus of modern literature on the issue, the State Bank of Pakistan (SBP) has never declared itself to be following any type of rule. Surprisingly, this topic has remained out of research focus (among the academia and the practitioners) in Pakistan. This is the first attempt to deal with a rulebased monetary policy strategy in the case of the SBP. We have estimated the Taylor rule and simulated the economy using this rule as a monetary policy strategy. Our results indicate that the SBP has not been following the Taylor rule. In fact, the actual policy can be taken as an extreme deviation from it. On the other hand, counterfactual simulation confirms that macroeconomic performance can be improved, in terms of stability in inflation and output, when a simple Taylor rule is adopted. In this regard the parameter values (especially the inflation target) in the rule must be set according to the conditions of the economy under consideration rather than by relying on the ones suggested by the Taylor rule.Taylor Rule, Macroeconomic Performance, Counterfactual Simulation

Affordable interactive virtual reality system for the Dynamic Hip Screw surgery training in vitro

Interactive virtual reality systems provide safe and cost-effective training environment to improve the technical skills and competence of surgeons. The trainees can have as many practice sessions, without need to the trainer all the time, before even start carrying out the procedure on any real patient. In this paper, we present an affordable interactive virtual reality system for the Dynamic Hip Screw (DHS) surgery training in vitro, through 3D tracking. The system facilitates a safe (in vitro / off patient) training to improve the cognitive coordination of trainees and junior surgeons, in particular the Hands, Eyes and Brain coordination. The system is based on very cheap commercial off-the-shelf (COT) components, which are very affordable, and needs minimum setup effort and knowledge. It also provides a range of visual and quantitative feedback information and measures, such as position, orientation, insertion point, and depth of drilling. It is envisaged that improving this level of coordination, through the training system, will contribute to reducing the failure rate of the DHS procedure. This means better treatment for patients and less costs for the Health services systems (e.g. UK's NHS system)

The Taylor Rule and the Macroeconomic Performance in Pakistan

A widely agreed proposition in modern economics is that policy rules have greater advantage over discretion in improving economic performance. Simple monetary policy instrument rules are feasible options for developing countries lacking the pre-requisites for more sophisticated targeting rules. Notwithstanding the focus of modern literature on the issue, the State Bank of Pakistan (SBP) has never declared itself to be following any type of rule. Surprisingly, this topic has remained out of research focus (among the academia and the practitioners) in Pakistan. This is the first attempt to deal with a rule-based monetary policy strategy in the case of the SBP. We have estimated the Taylor rule and simulated the economy using this rule as a monetary policy strategy. Our results indicate that the SBP has not been following the Taylor rule. In fact, the actual policy can be taken as an extreme deviation from it. On the other hand, counterfactual simulation confirms that macroeconomic performance can be improved, in terms of stability in inflation and output, when a simple Taylor rule is adopted. In this regard the parameter values (especially the inflation target) in the rule must be set according to the conditions of the economy under consideration rather than by relying on the ones suggested by the Taylor rule.Taylor Rule, Macroeconomic Performance, Counterfactual Simulation

Regional adaptive smoothing in disease mapping models

Disease mapping focuses on estimating spatial patterns and evolution of disease risk based on measures of disease effect, incidence ratio, for instance. These measures on maps provide a good visual representation of disease risk, featuring spatial heterogeneities and highlighting units or clusters of high risk. There are a number of factors due to which some units may have higher numbers of disease incidences compared to others, for example, differences in environmental exposures, deprived communities, different administrative structures, lack of awareness about the disease(s), to name a few. To clearly differentiate areas of low or high risk, we must apply some type of smoothing over regions which are presumably similar to each other. The process of such local smoothing increases our ability to clearly discern clusters in the spatial variation. In this thesis, we propose a novel approach to smooth local spatial units based on their larger regional location. The degree of smoothing is constant within each region, but differs between regions. For the purpose of illustration, we consider the spatial structure of German counties as local spatial units with Federal states of Germany as larger regions to apply state-wise adaptive smoothing. Chapters 4 and 5 propose univariate and multivariate spatial models of regional smoothing. We define that the incidences in each county follow a binomial density with probability of risk linked to spatial correlation matrix in a hierarchical way. The correlation matrix is partitioned into sub-matrices, corresponding to regions (Federal states), and smoothing parameters are introduced into the sub-matrices to locally smooth regions. Appropriate prior assumptions are stated for unknown parameters and samples from full conditional posterior densities are generated using MCMC. In Chapters 5, we adopt coregionalization framework of MacNab (2016) to build multivariate GMRFs as a linear combination of latent independent univariate GMRFs. The smoothing parameters are first applied to each sample separately, in a similar fashion to univariate regionalized spatial model, and then combined in the form of joint correlation matrix. We use the approach of Anderson et al. (2014) to identify spatial units exhibiting alike disease risks. The approach first elicits configuration of clusters based on past data of disease. In the second step, it fits a Poisson log-linear model using current data to select the best configuration based on deviance information criterion. The proposed method of smoothing is illustrated using real data sets of Oral cancer (univariate) and Colon, Lung and Pancreatic cancers (multivariate) on spatial structure of German counties. We are able to identify 13 clusters of Oral cancer, 9 of Colon, 6 of Lung and 8 of Pancreatic cancer. The identified clusters are further ranked based on incidence ratios. The analysis of real data and its comparison with simple GMRF (BYM model of Besag et al. (1991)) reveals that the novel method of incorporating smoothing parameters in spatial correlation matrix performs equally well, if not better.Krankheitskartierung (Disease Mapping) befasst sich mit der Schätzung räumlicher Muster und Entwicklungen des Krankheitsrisikos auf der Grundlage von Messungen des Krankheitsinzidenz. Die Kartierung von Messungen auf Landkarten bietet eine gute visuelle Darstellung des Krankheitsrisikos, wobei räumliche Heterogenitäten deutlich werden und Einheiten und Cluster mit hohem Risiko sichtbar gemacht werden können. Aufgrund einer Reihe von Faktoren können manche Einheiten im Vergleich zu anderen eine höhere Anzahl von Krankheitsfällen aufweisen, z.B. wegen unterschiedlicher Umweltbelastungen, sozial benachteiligter Bevölkerungsgruppen, unterschiedlicher Verwaltungsstrukturen, fehlendem Bewusstsein für die Krankheit(en), um nur einige Faktoren zu nennen. Um Bereiche mit niedrigem oder hohem Risiko klar zu unterscheiden, muss eine Art Glättung über Regionen vorgenommen werden, die einander ähnlich sein dürften. Der Prozess einer solchen lokalen Glättung verbessert den Prozess der klaren Unterscheidung von Clustern hinsichtlich der räumlichen Variation. In dieser Arbeit schlagen wir einen neuartigen Ansatz zur Glättung lokaler räumlicher Einheiten auf der Grundlage ihrer großräumigen regionalen Lage vor. Der Grad der Glättung ist innerhalb jeder Region konstant, unterscheidet sich jedoch von Region zu Region. Zur Veranschaulichung betrachten wir die räumliche Struktur von deutschen Landkreisen als lokale Raumeinheiten mit Bundesländern als größere Regionen, um die länderspezifische adaptive Glättung anzuwenden. In den Kapiteln 4 und 5 schlagen wir univariate und multivariate räumliche Modelle zur regionalen Glättung vor. Wir legen fest, dass die Inzidenzen in jedem Kreis einer binomialen Dichte mit Risikowahrscheinlichkeit folgen, die mit einer räumlichen Korrelationsmatrix in hierarchischer Weise verknüpft ist. Die Korrelationsmatrix wird in Untermatrizen unterteilt, die Regionen (Bundesländern) entsprechen, und Glättungsparameter werden in die Untermatrizen eingeführt, um die Regionen lokal zu glätten. Für unbekannte Parameter werden geeignete Vorannahmen aufgestellt und mit Hilfe von MCMC werden Stichproben aus den Posterioridichten generiert. In Kapitel 5 übernehmen wir den Koregionalisierungsrahmen von MacNab (2016), um multivariate GMRFs als Linearkombination von latenten unabhängigen univariaten GMRFs zu erstellen. Die Glättungsparameter werden zunächst auf jede Stichprobe einzeln angewendet, ähnlich wie bei einem univariaten regionalisierten Raummodell, und dann in Form einer gemeinsamen Korrelationsmatrix kombiniert. Wir verwenden den Ansatz von Anderson et al. (2014), um räumliche Einheiten zu identifizieren, die ähnliche Krankheitsrisiken aufweisen. Der Ansatz eruiert zunächst die Konfiguration von Clustern auf der Grundlage früherer Krankheitsdaten. Im zweiten Schritt passt er ein log-lineares Poisson-Modell unter Verwendung aktueller Daten an, um die beste Konfiguration auf der Grundlage des Abweichungsinformationskriteriums auszuwählen. Die vorgeschlagene Methode der Glättung wird anhand realer Datensätze von Mundkrebs (univariat) und Dickdarm-, Lungen- und Bauchspeicheldrüsenkrebs (multivariat) auf der räumlichen Struktur deutscher Landkreise veranschaulicht. Wir sind in der Lage, 13 Cluster für Mundkrebs, 9 für Dickdarmkrebs, 6 für Lungenkrebs und 8 für Bauchspeicheldrüsenkrebs zu identifizieren. Die identifizierten Cluster werden anhand von Inzidenzverhältnissen weiter gereiht. Die Analyse der realen Daten und ihr Vergleich mit dem einfachen GMRF (BYM-Modell von Besag et al. (1991)) zeigt, dass die neuartige Methode der Einbeziehung von Glättungsparametern in der räumlichen Korrelationsmatrix gleich gut, wenn nicht sogar besser abschneidet