Nearly one in every six HIV-infected children lost from ART follow-up at Debre Markos Referral Hospital, Northwest Ethiopia: A 14-year retrospective follow-up study.

BackgroundAlthough antiretroviral therapy (ART) significantly improves the survival status and quality of life among human immunodeficiency virus (HIV)-infected children, loss to follow-up (LTFU) from HIV-care profoundly affecting the treatment outcomes of this vulnerable population. For better interventions, up-to-date information concerning LTFU among HIV-infected children on ART is vital. However, only a few studies have been conducted in Ethiopia to address this concern. Thus, this study aims to identify the predictors of LTFU among HIV-infected children receiving ART at Debre Markos Referral Hospital.MethodsAn institution-based retrospective follow-up study was done among 408 HIV-infected children receiving ART at Debre Markos Referral Hospital between 2005 and March 15, 2019. Data were abstracted from the medical records of HIV-infected children using a standardized data abstracted checklist. We used Epi-Data Version 3.1 for data entry and Stata Version 14 for statistical analysis. The Kaplan-Meier survival curve was used to estimate the survival time. A generalized log-rank test was used to compare the survival curves of different categorical variables. Finally, both bi-variable and multivariable Cox proportional hazard regression models were used to identify the predictors of LTFU.ResultsOf 408 HIV-infected children included in the final analysis, 70 (17.1%) children were LTFU at the end of the study. The overall incidence rate of LTFU among HIV-infected children was found to be 4.5 (95%CI: 3.5-5.7) per 100-child years of observation. HIV-infected children living in rural areas (AHR: 3.2, 95%CI: 2.0-5.3), having fair or poor ART drug adherence (AHR: 2.3, 95%CI: 1.4-3.7), children started ART through test and treat approach (AHR: 2.7, 95%CI: 1.4-5.5), and children started protease inhibiter (PI)-based ART regimens (AHR: 2.2, 95%CI: 1.1-4.4) were at higher risk of LTFU.ConclusionThis study found that one in every six HIV-infected children lost form ART follow-up. HIV-infected children living in rural areas, having fair or poor ART drug adherence, started ART based on test and treat approach, and taking PI-based ART regimens were at higher risk of LTFU

In vitro CALLOGENESIS OF MEDICINALLY IMPORTANT AYURVEDIC HERB Enicostema littorale BLUME

Purpose: The practice of in vitro culturing of medicinally important plants has gained much attention in enhancing the secondary metabolite production. In this perspective, the current study was carried out to promote a rapid and standard method for in vitro callogenesis of Enicostema littorale Blume using different explants. Research Methods: In vitro callogenesis of Enicostema littorale was done on Murashige and Skoog’s media. Explants were cautiously sterilised and later put on MS medium added with variable combinations and combinations of growth regulators and were maintained in culture room at temperature of 25 ± 2ºC with photoperiods of 16 h. The cultures were observed at regular intervals for callus initiation and results were recorded regularly. Findings: Maximum callus was yielded from nodal explants when Murashige and Skoog medium was added with various growth promoters (6-Benzylaminopurine and Kinetin -3.0 and 2,4-dichlorophenoxyacetic acid -1.5 mg each followed by Kinetin-2.0 and Naphthyl Acetic Acid -0.5 mg) per liter amount of media. Similarly, it was also revealed from the present investigation that leaf explants proved better for callogenesis on MS media added with 6-Benzylaminopurine-3.0 and Naphthyl Acetic Acid -1.0 mg/l followed by Kinetin-1.5 and NAA-0.5 mg/l. However, shoot tip explants weakly responded for callogenic induction during the present study. The present study while using combinations of growth regulators at different concentrations and combinations, all the selected explants responded distinctly. Value: The developed tissue culture protocol can be proved as rapid and reliable method for enhancing and extracting the secondary metabolite production, and as a landmark to meet the industrial need in the near future

The role of climate, foliar stoichiometry and plant diversity on ecosystem carbon balance

Global change is affecting terrestrial carbon (C) balances. The effect of climate on ecosystem C balance has been largely explored, but the roles of other concurrently changing factors, such as diversity and nutrient availability, remain elusive. We used eddy-covariance C-flux measurements from 62 ecosystems from which we compiled information on climate, ecosystem type, stand age, species abundance and foliar concentrations of N and P of the main species, to assess their importance in the ecosystem C balance. Climate and productivity were the main determinants of ecosystem C balance and its stability. In P-rich sites, increasing N was related to increased gross primary production and respiration and vice versa, but reduced net C uptake. Our analyses did not provide evidence for a strong relation between ecosystem diversity and their productivity and stability. Nonetheless, these results suggest that nutrient imbalances and, potentially, diversity loss may alter future global C balance

The role of climate, foliar stoichiometry and plant diversity on ecosystem carbon balance

Global change is affecting terrestrial carbon (C) balances. The effect of climate on ecosystem C balance has been largely explored, but the roles of other concurrently changing factors, such as diversity and nutrient availability, remain elusive. We used eddy-covariance C-flux measurements from 62 ecosystems from which we compiled information on climate, ecosystem type, stand age, species abundance and foliar concentrations of N and P of the main species, to assess their importance in the ecosystem C balance. Climate and productivity were the main determinants of ecosystem C balance and its stability. In P-rich sites, increasing N was related to increased gross primary production and respiration and vice versa, but reduced net C uptake. Our analyses did not provide evidence for a strong relation between ecosystem diversity and their productivity and stability. Nonetheless, these results suggest that nutrient imbalances and, potentially, diversity loss may alter future global C balance

Phylogenetic study of Metroxylon Palms in Southeast Asia and Oceania based on 5S nrDNA spacer sequence data

The genus Metroxylon is distributed from Southeast Asia (Thailand, Malaysia, Brunei, the Philippines, and Indonesia) to Micronesia, Melanesia (Papua New Guinea, the Solomon Islands, Vanuatu, and Fiji), and Polynesia (Samoa). It is divided into two sections, Metroxylon (Eumetroxylon) and Coelococcus (Beccari 1918; Rauwerdink 1986), representing the western half and the eastern half of this distribution,respectively (McClatchey 1999). Metroxylon sagu Rottb. (called the true sago palm: hereafter “sago palm”) is the only species in the section Metroxylon, although the monophyly of this section remains uncertain

The three major axes of terrestrial ecosystem function

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.ISSN:0028-0836ISSN:1476-468

The three major axes of terrestrial ecosystem function

The leaf economics spectrum(1,2) and the global spectrum of plant forms and functions(3) revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species(2). Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities(4). However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability(4,5). Here we derive a set of ecosystem functions(6) from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems(7,8).Peer reviewe