Examining organizational health practices among universities in the central region of Uganda

This study gives insights on the organizational health practices applied in Ugandan universities of the central region. The paper examined four subdimensions of the construct through the use of the data obtained from eight hundred twenty (N=820) randomly selected sample of volunteers from the six universities that have been in existence for the last fifteen (15) years. The data were gathered using a 25- items adopted and adapted from the previous studies reviewed, a Likert scale ranging from strongly disagree to strongly agree  (1-5) was used based on by Keller and Price conception of the construct. Confirmatory Factor analysis a component of structural equation modelling was employed to analyze the four subdimensions of the construct organizational health. The research findings of the empirical cross section survey reflected that there is a relationship between the four factor subdimensions; culture and climate, control and coordination, innovation/invention and accountability even though they are all distinct in nature. Meanwhile, accountability as one of the construct was eliminated from the results in figure 2 due to lower scores in the average variance explained (AVE). The results further exhibited that the four subdimensions of organizational health are reliable and valid measurements of the construct. The data generated was deemed appropriate for the study since structure equation modelling requires a big sample, and fitted the model due to the fact that all the parameter estimates were met. Lastly, the data was analysed through the use of confirmatory factor analysis and the study findings generated are an extension of the previous study findings since there was no similar study done in Uganda especially on higher education using this methodology. The study has greater implications to managers towards improvement of university staff performance and institutional transformation

A MEASUEMENT MODEL OF TALENT MANAGEMENT PRACTICES AMONG UNIVERSITY STAFF IN CENTRAL REGION OF UGANDA

The empirical study objective was twofold; first to survey the degree to which university staff perceive on the use of talent management instituted a meaningful practice at universities of central region in Uganda; secondly it focused on testing the suitability of the dimension in terms of reliability, convergent validity, discriminant validity; and measurement equivalence for both working experience, and gender of university staff. The sample covered 808 university staff from six universities in the Central Region of Uganda in the year 2016. Data collection was done using a self-reported 24-item questionnaire so as to determine how the university staff perceive the construct of talent management practices. The Survey tool was distributed by the researcher and researcher assistants to volunteers in the six universities that participated in this study. The outcomes of the study reinforced, illuminated and gave a deeper insight into the results of previous studies on the same subject which has been infused in the university business and strategy. The study furthermore found evidence of validity and reliability for a multidimensional construct of talent management practices. Also, the measurement for working experience proved variant whereas gender was invariant. The findings of the study will be help stakeholders to contrive informed suggestions towards decision making for developing and retaining university staff to towards university effective performance, and is a source of information and knowledge to future research in the same area.

Analysing the relationship between sustainable leadership, talent management and organization health as predictors of university transformation

Research objective: The objective of the study was to examine the relationship between sustainable leadership, talent management and organizational health as predictors of university transformation. This study went further to establish the mediation effect of organizational health as a mediating factor between the exogenous variables (sustainable leadership and talent management) and endogenous variable (university transformation). Research technique and methodology: The study used a cross sectional survey design and the sample of respondents (N=820) was randomly chosen from six universities in which the central region of Uganda. The sample was deemed convenient for this study since the method used for data analysis was structural equation modelling that normally requires a big number of sample population. A confirmatory factor analysis (CFA) was used to analyze each of the individual constructs used to attain reasonable parameters estimates. The fully fledged structural equation modelling (SEM) was used in the study to analyze the hypothesized structural model and its casual relationships plus the mediation effect between the constructs. Main findings: The findings of the study showed that there is positive relationship between sustainable leadership, talent management and organizational health. However, the relationship between sustainable leadership and university transformation, talent management and university transformation were negatively related. 33 Practical implications: It was recommended to educational practitioners, lecturers and policy makers to use this model to harness university transformation. For researchers, it could be used to do further examination of university transformation on other universities both locally and internationally

Effects of Clinacanthus nutans leaf extract on lipopolysaccharide -induced neuroinflammation in rats: A behavioral and 1H NMR-based metabolomics study

Objective: This research revealed the biochemical outcomes of metabolic dysregulation in serum associated with physiological sickness behavior following lipopolysaccharide (LPS)-induced neuroinflammation in rats, and treatment with Clinacanthus nutans (CN). Verification of 1H NMR analysis of the CN aqueous extract proved the existence of bioactive phytochemical constituents’ in extract. Materials and Methods: Twenty-five rats were subjected to unilateral stereotaxic injection of 10 µL LPS (1 mg/mL), while another ten rats were injected with phosphate-buffered saline (PBS, 10 µL) as control. Then, 29 parameters of rat behavior related to sickness were tracked by a device software (SMART 3.0.1) on days 0 and 14 of CN treatment. The acquired and accumulated data were analyzed using multivariate data analysis with the SIMCA Software package (version 13, Umetrics AB; Umeå, Sweden). The pattern trends of related groups were documented using PCA and OPLS analysis. Results: A similar ameliorated correlation pattern was detected between improvement in physiological sickness behavior and anti-inflammatory biomarkers by the 1H NMR spectra of the sera following treatment with CN (500 and 1000 mg/kg body weight (bw)) and the control drug (dextromethorphan hydrobromide, 5 mg/kg of rats bw) in rats. Here, 21 biomarkers were detected for neuroinflammation. Treatment with the aqueous CN extract resulted in a statistically significant alteration in neuroinflammation metabolite biomarkers, including ethanol, choline, and acetate. Conclusion: This result denotes that the metabolomics approach is a reliable tool to disclose the relationship between central neuroinflammation, and systemic metabolic and physiological disturbances which could be used for future ethno-pharmacological assessments

Effects of Clinacanthus nutans leaf extract on lipopolysaccharide -induced neuroinflammation in rats: A behavioral and 1H NMR-based metabolomics study

Objective: This research revealed the biochemical outcomes of metabolic dysregulation in serum associated with physiological sickness behavior following lipopolysaccharide (LPS)-induced neuroinflammation in rats, and treatment with Clinacanthus nutans (CN). Verification of 1H NMR analysis of the CN aqueous extract proved the existence of bioactive phytochemical constituents’ in extract. Materials and Methods: Twenty-five rats were subjected to unilateral stereotaxic injection of 10 µL LPS (1 mg/mL), while another ten rats were injected with phosphate-buffered saline (PBS, 10 µL) as control. Then, 29 parameters of rat behavior related to sickness were tracked by a device software (SMART 3.0.1) on days 0 and 14 of CN treatment. The acquired and accumulated data were analyzed using multivariate data analysis with the SIMCA Software package (version 13, Umetrics AB; Umeå, Sweden). The pattern trends of related groups were documented using PCA and OPLS analysis. Results: A similar ameliorated correlation pattern was detected between improvement in physiological sickness behavior and anti-inflammatory biomarkers by the 1H NMR spectra of the sera following treatment with CN (500 and 1000 mg/kg body weight (bw)) and the control drug (dextromethorphan hydrobromide, 5 mg/kg of rats bw) in rats. Here, 21 biomarkers were detected for neuroinflammation. Treatment with the aqueous CN extract resulted in a statistically significant alteration in neuroinflammation metabolite biomarkers, including ethanol, choline, and acetate. Conclusion: This result denotes that the metabolomics approach is a reliable tool to disclose the relationship between central neuroinflammation, and systemic metabolic and physiological disturbances which could be used for future ethno-pharmacological assessments

Multi-Platform Metabolomics Analyses Revealed the Complexity of Serum Metabolites in LPS-Induced Neuroinflammed Rats Treated with Clinacanthus nutans Aqueous Extract

The use of metabolomics as a comprehensive tool in the analysis of metabolic profiles in disease progression and therapeutic intervention is rapidly advancing. Yet, a single analytical platform could not be applied to cover the entire spectrum of a biological sample’s metabolome. In the present paper, multi-platform metabolomics approaches were explored to determine the diverse rat sera metabolites extracted from intracerebroventricular lipopolysaccharides (LPS)-induced neuroinflammed rats treated with oral therapeutic interventions of positive drug (dextromethorphan, 5 mg/kg BW); with Clinacanthus nutans (CN) aqueous extract (CNE, 500 mg/kg BW); and with phosphate buffer saline (PBS) as the control group for 14 days. Analyzed by nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC-MS) techniques, this study depicted the potential of metabolites associated with neuroinflammation and verified by MetDisease. The key observations in the perturbed metabolic pathways that showed ameliorative effects were linked to the class of amino acid and peptide metabolism involving valine, leucine, and isoleucine biosynthesis; phenylalanine, tyrosine, and tryptophan biosynthesis; and phenylalanine metabolism. Lipid metabolism of arachidonic acid metabolism, glycerophospholipid metabolism, terpenoid backbone biosynthesis, and glycosphingolipid metabolism were also affected. Current findings suggested that the putative biomarkers, especially lysophosphatidic acid (LPA) and 5-diphosphomevalonic acid from glycerophospholipid and squalene/terpenoid and cholesterol biosynthesis, respectively, showed the ameliorative effects of the drug and CN treatments by controlling cell differentiation and proliferation. Our study proved that the complex and dynamic sera profiling affected during the CN treatment was greatly influenced by the analytical platform selection as integration between the two data yielded a more holistic summary of the metabolite pattern changes. Hence, an evidence-based herb, such as CN, can be used for novel diagnostic tools in the quest for ethnopharmacological studies

Cloud forcing of surface energy balance from in situ measurements in diverse mountain glacier environments

Clouds are an important component of the climate system, yet our understanding of how they directly and indirectly affect glacier melt in different climates is incomplete. Here we analyse high-quality datasets from 16 mountain glaciers in diverse climates around the globe to better understand how relationships between clouds and near-surface meteorology, radiation and surface energy balance vary. The seasonal cycle of cloud frequency varies markedly between mountain glacier sites. During the main melt season at each site, an increase in cloud cover is associated with increased vapour pressure and relative humidity, but relationships to wind speed are site specific. At colder sites (average near-surface air temperature in the melt season <0gg C), air temperature generally increases with increasing cloudiness, while for warmer sites (average near-surface air temperature in the melt season ≫0gg C), air temperature decreases with increasing cloudiness. At all sites, surface melt is more frequent in cloudy compared to clear-sky conditions. The proportion of melt from temperature-dependent energy fluxes (incoming longwave radiation, turbulent sensible heat and latent heat) also universally increases in cloudy conditions. However, cloud cover does not affect daily total melt in a universal way, with some sites showing increased melt energy during cloudy conditions and others decreased melt energy. The complex association of clouds with melt energy is not amenable to simple relationships due to many interacting physical processes (direct radiative forcing; surface albedo; and co-variance with temperature, humidity and wind) but is most closely related to the effect of clouds on net radiation. These results motivate the use of physics-based surface energy balance models for representing glacier-climate relationships in regional- and global-scale assessments of glacier response to climate change

Cloud forcing of surface energy balance from in situ measurements in diverse mountain glacier environments

Clouds are an important component of the climate system, yet our understanding of how they directly and indirectly affect glacier melt in different climates is incomplete. Here we analyse high-quality datasets from 16 mountain glaciers in diverse climates around the globe to better understand how relationships between clouds and near-surface meteorology, radiation and surface energy balance vary. The seasonal cycle of cloud frequency varies markedly between mountain glacier sites. During the main melt season at each site, an increase in cloud cover is associated with increased vapour pressure and relative humidity, but relationships to wind speed are site specific. At colder sites (average near-surface air temperature in the melt season <0° C), air temperature generally increases with increasing cloudiness, while for warmer sites (average near-surface air temperature in the melt season ≫0° C), air temperature decreases with increasing cloudiness. At all sites, surface melt is more frequent in cloudy compared to clear-sky conditions. The proportion of melt from temperature-dependent energy fluxes (incoming longwave radiation, turbulent sensible heat and latent heat) also universally increases in cloudy conditions. However, cloud cover does not affect daily total melt in a universal way, with some sites showing increased melt energy during cloudy conditions and others decreased melt energy. The complex association of clouds with melt energy is not amenable to simple relationships due to many interacting physical processes (direct radiative forcing; surface albedo; and co-variance with temperature, humidity and wind) but is most closely related to the effect of clouds on net radiation. These results motivate the use of physics-based surface energy balance models for representing glacier-climate relationships in regional- and global-scale assessments of glacier response to climate change