Selective inhibition of toxic cyanobacteria by β-carboline-containing bacterium Bacillus flexus isolated from Saudi freshwaters

AbstractA bacterial strain SSZ01 isolated from a eutrophic lake in Saudi Arabia dominated by cyanobacterial blooms, showed an antialgal activity against cyanobacteria species. Based on the analysis of the 16S rDNA gene sequence, the isolated strain (SSZ01) most likely belonged to the genus Bacillus with a 99% similarity to Bacillus flexus strain EMGA5. The thin layer chromatography (TLC) analysis of the ethyl acetate extract of this bacterium revealed that this strain can produce harmine and norharmane compared to different β-carboline analog standards. Harmine and norharmane were also detected in considerable amounts in bacterial growth medium, indicating a potential excretion of these compounds into the aquatic environment. The crude extract of Bacillus flexus as well as pure materials of harmine and norharmane inhibited the growth of tested species of cyanobacteria. However, the bacterial crude extract has a higher toxicity against tested species of cyanobacteria than harmine and norharmane. In addition, harmine was more toxic to cyanobacteria than norharmane. On the other hand, neither pure compounds of harmine and norharmane nor crude bacterial extract showed any antialgal activity against tested species of green algae. The results of the present study suggest that B. flexus SSZ01 or its crude extract containing harmine and norharmane could be a candidate for the selective control of cyanobacterial blooms without affecting other algal species

Application of fluorescence in situ hybridization (FISH) to the analysis of sulfate reducing bacterial community in an oily bench scale reactor

Advances in the field of genomics and meta-genomics have led to rapid and accurate strategies for the monitoring of microbial biodiversity and have revealed its potential for biotechnological applications. In this study, fluorescent in situ hybridization (FISH) as a culture-independent molecular approach using specific CY3-labelled oligonucleotide probes was used to study the dynamics of the sulfate reduction bacterial community (SRB) of the activated sludge from an oily wastewater treatment system. The relative abundance of members of the dominant bacteria in the oily water reactor was determined by FISH for 16S rRNA using EUB338 probes, for detecting general eubacteria, and SRB385 for targeting SRBs and major species of delta-proteobacteria sulfate reducers. The percentage of cells hybridizing with probe EUB338 for the dominant bacteria decreased from 25.85 to 6.25%, while with the SRB385 probe for SRB bacteria, it increased from 7.21 to 10.20% of total cells during the reactor process. These data show that SRB bacteria dominated the active microbial community in the system. It is interesting that delta-proteobacterial SRBs occupied a high percentage and took place in an oily biological system under aerobic conditions.Keywords: Sulfate reducing bacteria, fluorescence in situ hybridization, 16S rRNA oligonucleotide probes, microbial community, dynamic

Scaling up stochastic gradient descent for non-convex optimisation

Stochastic gradient descent (SGD) is a widely adopted iterative method for optimizing differentiable objective functions. In this paper, we propose and discuss a novel approach to scale up SGD in applications involving non-convex functions and large datasets. We address the bottleneck problem arising when using both shared and distributed memory. Typically, the former is bounded by limited computation resources and bandwidth whereas the latter suffers from communication overheads. We propose a unified distributed and parallel implementation of SGD (named DPSGD) that relies on both asynchronous distribution and lock-free parallelism. By combining two strategies into a unified framework, DPSGD is able to strike a better trade-off between local computation and communication. The convergence properties of DPSGD are studied for non-convex problems such as those arising in statistical modelling and machine learning. Our theoretical analysis shows that DPSGD leads to speed-up with respect to the number of cores and number of workers while guaranteeing an asymptotic convergence rate of O(1/T) given that the number of cores is bounded by T1 / 4 and the number of workers is bounded by T1 / 2 where T is the number of iterations. The potential gains that can be achieved by DPSGD are demonstrated empirically on a stochastic variational inference problem (Latent Dirichlet Allocation) and on a deep reinforcement learning (DRL) problem (advantage actor critic - A2C) resulting in two algorithms: DPSVI and HSA2C. Empirical results validate our theoretical findings. Comparative studies are conducted to show the performance of the proposed DPSGD against the state-of-the-art DRL algorithms

Isolation of Thermoalkalophilic-?-amylase Producing Bacteria and Optimization of Potato Waste Water Medium for Enhancement of ?-amylase Production

Sixty one thermoalkalophilic bacteria were isolated from soil samples in Saudi Arabia’s southern region. Isolate TA-38, obtained from the Tanomah region, showed the best performance for enzyme production and was submitted for further study. It was identified as Bacillus axarquiensis based on 16S rRNA gene sequencing studies. The feasibility of using potato waste water as a simple and cheap medium for the production of ?-amylase was evaluated compared with starch broth medium. The production of ?-amylase in the potato waste water medium was only 13.8% less than that of the starch medium. Maximum enzyme production was achieved after 48 hours of cultivation at the beginning of the stationary phase at pH 10.0 and 50 0C. The appropriate addition of starch; nitrogen; phosphate; and calcium to potato waste water significantly enhanced the production of ?-amylase. The enzyme production reached a maximum of 64.5 Uml-1 with the potato wastewater adding with 0.5 % starch; 0.4 % yeast extract; 0.04% CaCl2-2H2O and 0.05 % KH2PO4.  The optimization of the potato waste water medium led to an approximately 4.02 fold increase in the production of ?-amylase compared to starch broth medium. Data indicated that the potato waste water contained substrates which could be used by bacterial isolate for the production of ?-amylase production and the developed procedure was cost effective since it requires only a slightly addition of nutrients to the medium. Keywords: Isolation; ?-amylase; 16S rRNA; Production; Potato waste water; Thermoalkaliphilic bacteria

Integration of radiometric ground-based data and high-resolution quickbird imagery with multivariate modeling to estimate maize traits in the nile delta of Egypt

In site-specific management, rapid and accurate identification of crop stress at a large scale is critical. Radiometric ground-based data and satellite imaging with advanced spatial and spectral resolution allow for a deeper understanding of crop stress and the level of stress in a given area. This research aimed to assess the potential of radiometric ground-based data and high-resolution QuickBird satellite imagery to determine the leaf area index (LAI), biomass fresh weight (BFW) and chlorophyll meter (Chlm) of maize across well-irrigated, water stress and salinity stress areas in the Nile Delta of Egypt. Partial least squares regression (PLSR) and multiple linear regression (MLR) were evaluated to estimate the three measured traits based on vegetation spectral indices (vegetation-SRIs) derived from these methods and their combination. Maize field visits were conducted during the summer seasons from 28 to 30 July 2007 to collect ground reference data concurrent with the acquisition of radiometric ground-based measurements and QuickBird satellite imagery. The results showed that the majority of vegetation-SRIs extracted from radiometric ground-based data and high-resolution satellite images were more effective in estimating LAI, BFW, and Chlm. In general, the vegetation-SRIs of radiometric ground-based data showed higher R2 with measured traits compared to the vegetation-SRIs extracted from high-resolution satellite imagery. The coefficient of determination (R2) of the significant relationships between vegetation-SRIs of both methods and three measured traits varied from 0.64 to 0.89. For example, with QuickBird high-resolution satellite images, the relationships of the green normalized difference vegetation index (GNDVI) with LAI and BFW showed the highest R2 of 0.80 and 0.84, respectively. Overall, the ground-based vegetation-SRIs and the satellite-based indices were found to be in good agreement to assess the measured traits of maize. Both the calibration (Cal.) and validation (Val.) models of PLSR and MLR showed the highest performance in predicting the three measured traits based on the combination of vegetation-SRIs from radiometric ground-based data and high-resolution QuickBird satellite imagery. For example, validation (Val.) models of PLSR and MLR showed the highest performance in predicting the measured traits based on the combination of vegetation-SRIs from radiometric ground-based data and high-resolution QuickBird satellite imagery with R2 (0.91) of both methods for LAI, R2 (0.91–0.93) for BFW respectively, and R2 (0.82) of both methods for Chlm. The models of PLSR and MLR showed approximately the same performance in predicting the three measured traits and no clear difference was found between them and their combinations. In conclusion, the results obtained from this study showed that radiometric ground-based measurements and high spectral resolution remote-sensing imagery have the potential to offer necessary crop monitoring information across well-irrigated, water stress and salinity stress in regions suffering lack of freshwater resources

Heat Stroke in Emergency Department: Diagnosis and Management

Background: Heat stroke is a severe health concern with the potential for multi-organ failure, necessitating rapid and effective management. With rising global temperatures, there is increasing concern regarding the vulnerability of populations in high-heat areas, notably in Saudi Arabia, especially during the annual Hajj pilgrimage. Objective: This paper aims to review the epidemiology, evaluation and management techniques of heat stroke, emphasizing the situation during Hajj pilgrimages in Saudi Arabia, and to outline the best practices for emergency management. Methodology: A comprehensive review of literature and studies related to heat stroke, both globally and specific to Saudi Arabia, was undertaken. An in-depth analysis of emergency management, including initial assessment, cooling methods, organ support, medication, and prevention strategies, was conducted. Results: Heat stroke remains a significant cause of emergency department visits, with specific groups, such as men and the elderly, being more susceptible. During the Hajj in 2016, 267 patients were diagnosed with heat-related illnesses, with heatstroke accounting for 29% of these cases. With the threat of global warming, studies indicate a potential tenfold increase in heat stroke risk with a 2°C rise in temperatures. Swift and comprehensive cooling is pivotal for recovery. Management emphasizes rapid recognition, assessment, and varied cooling methods, along with targeted treatments for organ dysfunctions. Prevention strategies play a vital role, given the higher efficacy and practicality over treating organ dysfunctions. Conclusion: Heat stroke is a pressing health challenge, particularly in high-risk environments like Saudi Arabia during the Hajj pilgrimage. While effective emergency management protocols exist, an emphasis on prevention is crucial. It is imperative to incorporate a comprehensive approach to address both the immediate threat and long-term risks of heat stroke, especially with the looming challenge of global warming

Social and Economic Factors that Influence Health Outcomes in Family Medicine

Over the last twenty years, the social determinants of health (SDOH) have gained more and more attention in the public health community. SDOH are non-medical elements that may be significantly impacted by social policies and have an impact on health. The increasing variety that exists within our societies makes it absolutely necessary for us to incorporate into undergraduate medical education social determinants of health such as racial factors, financial instability, partner violence, insufficient accessibility to transportation, and inadequate social supports, as well as the crucial role of health education.  Nonetheless, a growing body of research indicates that a variety of health outcomes are fundamentally caused by socioeconomic variables including wealth, income, and education together. In this review we highlight the influence of socio-economic factors on health outcomes, approaches to incorporate social determinants of health in family medicine practice, and we also talk about challenges and solutions in addressing social determinants in family medicine. The objective of this research was to assess the impact of social determinants of health on family medicine practice in which socioeconomic determinants of health might have an effect on health outcomes and healthcare delivery within the context of a family medicine clinical environment

Prediction Models Based on Soil Characteristics for Evaluation of the Accumulation Capacity of Nine Metals by Forage Sorghum Grown in Agricultural Soils Treated with Varying Amounts of Poultry Manure

Predictive models were generated to evaluate the degree to which nine metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) were absorbed by the leaves, stems and roots of forage sorghum in growing media comprising soil admixed with poultry manure concentrations of 0, 10, 20, 30 and 40 g/kg. The data revealed that the greatest contents of the majority of the metals were evident in the roots rather than in the stems and leaves. A bioaccumulation factor (BAF)  1. Translocation factor values were < 1 for all metals with the exception of Co, Cr and Ni, which displayed values of 1.20, 1.67 and 1.35 for the leaves, and 1.12, 1.23 and 1.24, respectively, for the stems. The soil pH had a negative association with metal tissues in plant parts. A positive relationship was observed with respect to plant metal contents, electrical conductivity and organic matter quantity. The designed models exhibited a high standard of data precision; any variations between the predicted and experimentally observed contents for the nine metals in the three plant tissue components were nonsignificant. Thus, it was concluded that the presented predictive models constitute a pragmatic tool to establish the safety from risk to human well-being with respect to growing forage sorghum when cultivating media fortified with poultry manure.The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number IFP-KKU-2020/3.Peer reviewe

A Single DC Source Nine-Level Switched-Capacitor Boost Inverter Topology with Reduced Switch Count

This paper presents a new boost inverter topology with nine level output voltage waveform using a single dc source and two switched capacitors. The capacitor voltages are self-balancing and thus is devoid of any sensors and auxiliary circuitry. The output voltage is twice higher than the input voltage, which eliminates the need for an input dc boost converter especially when the inverter is powered from a renewable source. The merits of the proposed topology in terms of the number of devices and cost are highlighted by comparing the recent and conventional inverter topologies. In addition to this, the total voltage stress of the proposed topology is lower and have a maximum efficiency of 98.25%. The operation and dynamic performance of the proposed topology have been simulated using PLECS software and are validated using an experimental setup considering a different dynamic operation.This work was supported in part by the Scientific Research Deanship, Taif University, Saudi Arabia, under Grant 1-439 - 6072.Scopu

Global prevalence of Colistin resistance in Klebsiella Pneumoniae from bloodstream infection: A systematic review and meta-analysis

Background: Among gram-negative bacteria, Klebsiella pneumoniae is one of the most common causes of healthcare-related infection. Bloodstream infections (BSIs) caused by Klebsiella pneumoniae are notorious for being difficult to treat due to resistance to commonly used antimicrobials. Klebsiella pneumoniae isolates from bloodstream infections are becoming increasingly resistant to carbapenems. In the fight against carbapenem-resistant Klebsiella pneumoniae, colistin [polymyxin E] is the antimicrobial of choice and is thus widely used.Objective: This study aimed to determine the global prevalence of colistin resistance amongst Klebsiella pneumoniae isolates from bloodstream infections. Methods: PubMed, Medline, Scopus, and the Cochrane Library were searched for published articles without restricting the search period. Studies meeting the predefined inclusion and exclusion criteria were included, and quality was assessed using Joanna Briggs Institute Checklist. We used a statistical random effect model to analyze data with substantial heterogeneity (I2 > 50%) in the meta-analysis. Results: A total of 10 studies out of 2873 search results that met the inclusion criteria were included in the final synthesis for this study. A pooled prevalence of colistin resistance was 3.1%, 95% CI (1.5–4.7%). The highest colistin resistance pooled prevalence was recorded in isolates studied in 2020 and beyond 12.90% (4/31), while Klebsiella pneumoniae isolates studied in 2015 and before and in 2016–2019 showed a pooled colistin resistance rate of 2.89% (48/1661) and 2.95% (28/948), respectively. The highest colistin resistance was found in Klebsiella pneumoniae isolates from Thailand (19.2%), while the least pooled resistance was in Klebsiella pneumoniae from South Korea (0.8%). The pooled prevalence of the multidrug-resistant (MDR) of Klebsiella pneumoniae from bloodstream infection ranged from 80.1%, 95% CI (65.0–95.2%), and the resistance prevalence of other antibiotics by Klebsiella pneumoniae from bloodstream infections were as follows; ciprofloxacin (45.3%), ertapenem (44.4%), meropenem (36.1%), imipenem (35.2%), gentamicin (33.3%), amikacin (25.4%) and tigecycline (5.1%). Klebsiella pneumoniae recovered from the intensive care unit (ICU) showed higher colistin resistance, 11.5% (9/781%), while non-ICU patients showed 3.03% (80/2604) pooled colistin resistance. Conclusion: This study showed low colistin resistance in Klebsiella pneumoniae isolates from global bloodstream infections. However, significant colistin resistance was observed in isolates collected from 2020 and beyond. Significant colistin resistance was also observed in Klebsiella pneumoniae isolates in bloodstream infections from the intensive care unit (ICU) compared to those from non-ICUs. As a result, there is a need to institute colistin administration stewardship in the ICU in clinical settings