Projection of water availability and sustainability in Nigeria due to climate change

This study projects water availability and sustainability in Nigeria due to climate change. This study used Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data (TWS), Global Precipitation Climatology Center (GPCC) precipitation data and Climate Research Unit (CRU) temperature data. Four general circulation models (GCMs) of the Coupled Model Intercomparison Project 5 were downscaled using the best of four downscaling methods. Two machine learning (ML) models, RF and SVM, were developed to simulate GRACE TWS data for the period 2002–2016 and were then used for the projection of spatiotemporal changes in TWS. The projected TWS data were used to assess the spatiotemporal changes in water availability and sustainability based on the reliability–resiliency–vulnerability (RRV) concept. This study revealed that linear scaling was the best for downscaling over Nigeria. RF had better performance than SVM in modeling TWS for the study area. This study also revealed there would be decreases in water storage during the wet season (June–September) and increases in the dry season (January–May). Decreases in projected water availability were in the range of 0–12 mm for the periods 2010–2039, 2040–2069, and 2070–2099 under RCP2.6 and in the range of 0–17 mm under RCP8.5 during the wet season. Spatially, annual changes in water storage are expected to increase in the northern part and decrease in the south, particularly in the country’s southeast. Groundwater sustainability was higher during the period 2070–2099 under all RCPs compared to the other periods and this can be attributed to the expected increases in rainfall during this period

Trend analysis of droughts during crop growing seasons of Nigeria

This study assesses the impacts of recent climate changes on drought-affected areas and the occurrence of droughts during different cropping seasons of Nigeria using the standardized precipitation evapotranspiration index (SPEI). The crop growing seasons are considered because the droughts for those periods are more destructive to national agricultural production. The Mann-Kendall test and binary logistic regression were used to quantify the trends in drought-affected areas and the occurrence of crop droughts with different areal extents, respectively. Gauge-based gridded rainfall and temperature data for the period 1961-2010 with spatial resolutions of 0.5° were used. Results showed an increase in the areal extent of droughts during some of the cropping seasons. The occurrences of droughts, particularly moderate droughts with smaller areal extents, were found to increase for all of the seasons. The SPEI values calculated decreased mostly in the regions where rainfall was decreasing. That is, the recent changes in climate were responsible for the increase in the occurrences of droughts with smaller areal extents. These trends in climate indicate that the occurrence of larger areal extent droughts may happen more frequently in Nigeria in the future

MAPPING POTENTIAL HABITATS FOR ARTHROPOD VECTORS OF TRYPANOSOMIASIS INFECTION IN NORTHERN NIGERIA: AN INTRODUCTORY SYNTHESIS

This paper presents an introductory synthesis for mapping potential habitats of arthropod vectors responsible for animal trypanosomiasis diseases in Northern Nigeria, where there is high production of livestock. Animal trypanosomiasis is considered an arthropod-borne viral disease which is endemic in 36 countries of sub-Saharan Africa and particularly in northern Nigeria. The disease which is transmitted by the vector tsetse fly remains a threat to both humans and livestock in many rural communities of Nigeria. The outbreak of the disease is known to occur as a result of the changing climate which relates to changes in sea surface temperatures otherwise known as “El Niño Southern Oscillations” (ENSO). Trypanosomiasis is mainly experienced whenever there are changes in global precipitation as a result of the changing climate. Monthly Satellite data of Normalized Difference Vegetation Index (NDVI) at 2.5° spatial resolution was sourced from NASA-MODIS/CMD and subjected to principal component analysis using standardized principal components of GIS with a digital elevation model (DEM) supplemented in the analysis. Results revealed pockets of probable habitats of arthropod vectors to be around forest islands characterized by dry woodland and savanna, and in other cases around gallery forests and few lowland and riverine areas. This study demonstrates that geospatial technology is a cost effective tool in mapping of the arthropod vector habitats for Northern Nigeria

Projection of meteorological droughts in Nigeria during growing seasons under climate change scenarios

Like many other African countries, incidence of drought is increasing in Nigeria. In this work, spatiotemporal changes in droughts under different representative concentration pathway (RCP) scenarios were assessed; considering their greatest impacts on life and livelihoods in Nigeria, especially when droughts coincide with the growing seasons. Three entropy-based methods, namely symmetrical uncertainty, gain ratio, and entropy gain were used in a multi-criteria decision-making framework to select the best performing General Circulation Models (GCMs) for the projection of rainfall and temperature. Performance of four widely used bias correction methods was compared to identify a suitable method for correcting bias in GCM projections for the period 2010–2099. A machine learning technique was then used to generate a multi-model ensemble (MME) of the bias-corrected GCM projection for different RCP scenarios. The standardized precipitation evapotranspiration index (SPEI) was subsequently computed to estimate droughts from the MME mean of GCM projected rainfall and temperature to predict possible spatiotemporal changes in meteorological droughts. Finally, trends in the SPEI, temperature and rainfall, and return period of droughts for different growing seasons were estimated using a 50-year moving window, with a 10-year interval, to understand driving factors accountable for future changes in droughts. The analysis revealed that MRI-CGCM3, HadGEM2-ES, CSIRO-Mk3-6-0, and CESM1-CAM5 are the most appropriate GCMs for projecting rainfall and temperature, and the linear scaling (SCL) is the best method for correcting bias. The MME mean of bias-corrected GCM projections revealed an increase in rainfall in the south-south, southwest, and parts of the northwest whilst a decrease in the southeast, northeast, and parts of central Nigeria. In contrast, rise in temperature for entire country during most of the cropping seasons was projected. The results further indicated that increase in temperature would decrease the SPEI across Nigeria, which will make droughts more frequent in most of the country under all the RCPs. However, increase in drought frequency would be less for higher RCPs due to increase in rainfall

ICEberg: a web-based resource for integrative and conjugative elements found in Bacteria

ICEberg (http://db-mml.sjtu.edu.cn/ICEberg/) is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. We propose that ICEberg will facilitate efficient, multi-disciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community

The Role of Lactic Acid Adsorption by Ion Exchange Chromatography

Background: The polyacrylic resin Amberlite IRA-67 is a promising adsorbent for lactic acid extraction from aqueous solution, but little systematic research has been devoted to the separation efficiency of lactic acid under different operating conditions. Methodology/Principal Findings: In this paper, we investigated the effects of temperature, resin dose and lactic acid loading concentration on the adsorption of lactic acid by Amberlite IRA-67 in batch kinetic experiments. The obtained kinetic data followed the pseudo-second order model well and both the equilibrium and ultimate adsorption slightly decreased with the increase of the temperature at 293–323K and 42.5 g/liter lactic acid loading concentration. The adsorption was a chemically heterogeneous process with a mean free energy value of 12.18 kJ/mol. According to the Boyd _ plot, the lactic acid uptake process was primarily found to be an intraparticle diffusion at a lower concentration (,50 g/liter) but a film diffusion at a higher concentration (.70 g/liter). The values of effective diffusion coefficient D i increased with temperature. By using our Equation (21), the negative values of DGu and DHu revealed that the adsorption process was spontaneous and exothermic. Moreover, the negative value of DSu reflected the decrease of solid-liquid interface randomness at the solid-liquid interface when adsorbing lactic acid on IRA-67. Conclusions/Significance: With the weakly basic resin IRA-67, in situ product removal of lactic acid can be accomplishe

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Selection of general circulation models for the projections of spatio-temporal changes in temperature of borneo island based on cmip5

A study has been conducted to evaluate the changes in temperature of Borneo Island for different representative concentration pathway (RCP) scenarios through statistical downscaling of an ensemble of general circulation models (GCMs) selected using entropy-based methods. A combination of past-performance and envelope approaches was used for the selection of GCM ensemble from a pool of 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) GCMs. Ranking of the GCMs was done separately at each grid point by using three entropy-based feature selection methods. Climate Research Unit (CRU) gridded temperature data was used as dependent variable and the simulated temperature of different GCMs for the period 1961–2005 was used as independent variable for the selection of GCMs. The scores obtained by the GCMs at different CRU grids were aggregated using compromise programming method and then ranked for entire Borneo Island using group decision-making method. Linear scaling method was applied to remove the biases in GCMs, followed by random forest (RF)–based regression method to generate multi-model ensemble projections. The results revealed that FIO-ESM, MRI-CGCM3, GFDL-CM3, and IPSL-CM5A-MR are the most suitable GCMs for the projection of temperature in the study area. The projection of temperature using the selected GCMs indicated increase in temperature in the Borneo Island, particularly in the southwest regions. The minimum temperature was projected to increase more (3.3 to 4.7 °C) compared with maximum temperature (3.0 to 4.6 °C) and thus, the diurnal temperature range (DTR) was projected to decrease gradually until the end of the twenty-first century. Increase in average and maximum temperatures was projected more during the southwest (SW) monsoon compared with the northeast (NE) monsoon. The study indicated that large increase in temperature and decrease in DTR would have significant impact on ecology and bio-environment of the island which have one of the dense ecological diversities in the world

Drug resistance in targeted cancer therapies with RAF inhibitors

Hyperactive RAS/RAF/MEK/ERK signaling has a well-defined role in cancer biology. Targeting this pathway results in complete or partial regression of most cancers. In recent years, cancer genomic studies have revealed that genetic alterations that aberrantly activate the RAS/RAF/MEK/ERK signaling mainly occur on RAF or upstream, which motivated the extensive development of RAF inhibitors for cancer therapy. Currently, the first-generation RAF inhibitors have been approved for treating late-stage cancers with BRAF(V600E) mutations. Although these inhibitors have achieved promising outcomes in clinical treatments, their efficacy is abolished by quick-rising drug resistance. Moreover, cancers with hyperactive RAS exhibit intrinsic resistance to these drugs. To resolve these problems, the second-generation RAF inhibitors have been designed and are undergoing clinical evaluations. Here, we summarize the recent findings from mechanistic studies on RAF inhibitor resistance and discuss the critical issues in the development of next-generation RAF inhibitors with better therapeutic index, which may provide insights for improving targeted cancer therapy with RAF inhibitors