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Demand for clean energy has increased due to the proliferation of climate change impact from excessive emission of greenhouse gases (GHG) from the combustion of fossil fuels. H2 is a clean energy source since water vapor is the only byproduct after its combustion. Growing microalgae offers a promising low-energy and low-cost approach for bioH2 production. In this study, a bibliometric analysis was performed for the production of H2 using microalgae to evaluate the conceptual, intellectual, and social structure of the dataset. In addition, a scoping review of articles was conducted to highlight recent advancements and identify future research recommendations. A total of 184 relevant publications over 23 years (2000–2022) were retrieved from the Scopus database for analysis. The results demonstrated an exponential increase in citations from 283 to 996 in the last decade, indicating the interest in bioH2 production from microalgae. Results also revealed that the International Journal of Hydrogen Energy accounted for more than 25% of the published articles, of which China contributed almost 28%. Oxygen sensitivity of the H2ase enzyme and sulfur deprivation were highlighted as the main limiting factors of bioH2 production using microalgae. It was also evident that the most widely studied microalgae species were green algae, especially Chlamydomonas and Chlorella. Effective process modifications, particularly hybridizing microalgae with bacteria consortium and implementing oxygen regulating strategies, were shown to give up to a 10-fold increase in H2 yield. This study also discusses recent developments in technologies, strategies, microalgal species, and optimizing controlling factors affecting bioH2 production.

Background: Risk stratification assessment of patients with non-ST elevation acute coronary syndrome (NSTE ACS) plays an important role in optimal management and defines the patient's prognosis. This study aimed to evaluate the ability of CHA2DS2-VASc-HSF score (comprising of the components of the CHA2DS2-VASc score with a male instead of female sex category, hyperlipidemia, smoking, and family history of coronary artery disease respectively) to predict the severity and complexity of CAD and its efficacy in stratification for major adverse cardiovascular events (MACE) in patients with NSTE ACS without known atrial fibrillation. Methods: This study included 200 patients (males 72.5%, mean age 55.8 ± 10.1 years) who were admitted with NSTE ACS. CHA2DS2-VASC-HSF score was calculated on admission. Patients were classified into three groups according to their CHA2DS2-VASC-HSF score: low score group (< 2; 29 patients), intermediate score group (2–4; 83 patients), and high score group (≥ 5; 88 patients). Coronary angiography was conducted and the Syntax score (SS) was calculated. Clinical follow-up at 6 months of admission for the development of MACE was recorded. Results: SS was significantly high in the high CHA2DS2-VASc-HSF score group compared with low and intermediate score groups. CHA2DS2-VASc-HSF score had a significant positive strong correlation with syntax score (r = 0.64, P < 0.001). Smoking, vascular disease, hyperlipidemia, and CHA2DS2-VASc-HSF score were independent predictors of high SS. For the prediction of severe and complex CAD, CHA2DS2-VASc-HSF score had a good predictive power at a cut-off value ≥ 5 with a sensitivity of 86% and specificity of 65%. Hypertension, vascular disease, high SS, and CHA2DS2-VASc-HSF score were independent predictors of MACE. CHA2DS2-VASC-HSF score ≥ 4 was identified as an effective cut-off point for the development of MACE with 94% sensitivity and 70% specificity. Conclusions: CHA2DS2-VASC-HSF score is proposed to be a simple bedside score that could be used for the prediction of the severity and complexity of CAD as well as a risk stratification tool for the development of MACE in NSTE ACS patients. [ABSTRACT FROM AUTHOR]

An artificial neural network (ANN) approach with response surface methodology (RSM) technique has been applied to model and optimize the removal process of Brilliant Green dye by batch electrocoagulation process. A multilayer perceptron (MLP) - ANN model has been trained by four input neurons which represent the reaction time, current density, pH, NaCl concentration, and two output neurons representing the dye removal efficiency (%) and electrical energy consumption (kWh/kg). The optimized hidden layer neurons were obtained based on a minimum mean squared error. The batch electrocoagulation process was optimized using central composite design with RSM once the ANN network was trained and primed to anticipate the output. At optimized condition (electrolysis time 10 min, current density 80 A/m2, initial pH 5 and electrolyte NaCl concentration 0.5 g/L), RSM projected decolorization of 98.83% and electrical energy consumption of 14.99 kWh/kg. This study shows that the removal of brilliant green dye can be successfully carried out by a batch electrocoagulation process. Therefore, the process is successfully trained by ANN and optimized by RSM for similar applications.

The aim of this study was to find the correlation between severity of dry eye and rheumatoid arthritis (RA) disease activity. Forty- two RA patients with dry eye were recruited from Rheumatology Outpatient Clinic in Minia University Hospital. Assessment of RA disease activity was performed using disease activity score (DAS-28). Ocular tests include Schirmer test I, tear film break up time (TBUT) and ocular staining score (OSS) was performed by ophthalmologist to find evidence of ocular dryness. Erythrocyte sedimentation rate (ESR), rheumatoid factor (RF), anti SSA/Ro and anti SSB/La was also tested. Patients with severe dry (OSS ≥ 3) underwent minor salivary gland biopsy (MSGB) as suspected to have secondary Sjögren’s syndrome (SS). Of 42 RA patients, 30 had definite dry eye. DAS-28 did not show significant correlation with any of ocular tests for dryness while the duration of RA was significantly positively correlated with Schirmer test and OSS. The biopsy results of RA patients with severe dry eye show no evidence of SS. The severity of dry eye is not correlated with activity of RA but with its duration.

The water-soluble acidic polysaccharide from Thalassodendron ciliatum (Forss.) den Hartog was successfully extracted, fractionated and purified. The phytochemical profile of the two water-soluble fractions (F1 and F2), were detected using different analytic techniques. GC-MS analysis revealed the presence of 22 saccharide. Acidic polysaccharide, galacturonic and glucuronic acid were the most abundant. Moreover, paper chromatography and electrophoresis also performed as a preliminary chemical characterization of the polymer. The hepatoprotective activity of the fractions against thioacetamide (TAA) induced liver failure; antioxidant potential and preliminary immunomodulatory activity were assigned in-vivo. The results revealed a potent competence to improve the liver function profile (ALT, AST, total bilirubin, total glyceride, etc.) and a remarkable improvement in liver architecture in comparison to the challenged intoxicated groups. Moreover, they showed high anti-oxidative properties and a promising immunomodulatory influence via Il6. These findings provide new insight into the possible role of polysaccharide purified two fractions in the treatment of acute liver injury.

Researchers have agreed upon the importance of social media in regard to establishing athlete brands. In this sense, Twitter is a very important example of social media which represents fans’ perspectives about their favorite (or least favorite) athletes and provides solid fan feedback, which can be helpful in the context of image branding for an athlete. The current study has employed a qualitative content analysis of Twitter users during Pakistan Super League (PSL). The tweets were collected during the 2017 edition of PSL. Data containing #HBLPSL and #PSL was collected and tweets with names of foreign athletes were selected from more than 38,000 tweets. Findings from this study suggested that fans’ tweets about athletes could be separated into two major categories: 1) fan related motives and 2) athlete’ related motives. Fan related motives included sharing: information, visuals, predictions and feedback regarding certain athletes. Athlete’ related motives included: athlete performance, style of celebration and athlete comments. Results of the current study have highlighted the motives that persuaded fans to tweet about a certain athlete during the PSL. Resumen: Los investigadores han estado de acuerdo en la importancia de las redes sociales en la búsqueda de establecer marcas de atletas. En este sentido, Twitter es un tipo muy importante de medios de comunicación social que representa las perspectivas de los aficionados sobre sus atletas favoritos (o no) y proporciona información sólida de los aficionados, que puede ser útil en el contexto de la imagen de marca para un atleta. El presente estudio utiliza un análisis cualitativo del contenido de los usuarios de Twitter durante el PSL. Las colecciones de tweets comenzaron el primer día del PSL 2017 (9 de febrero de 2017) y concluyeron el último día del estudio (5 de marzo de 2017). Se recopilaron datos que contenían #HBLPSL y #PSL y se seleccionaron tweets con nombres de atletas extranjeros de entre más de 38. 000 tweets. Los resultados de este estudio sugirieron que los tweets de los aficionados sobre los atletas, podrían separarse en dos categorías principales: 1) motivos relacionados con los aficionados, y 2) motivos relacionados con los atletas. Los motivos relacionados con los aficionados eran compartir información, imágenes, predicciones y comentarios sobre ciertos atletas. Los motivos relacionados con los atletas fueron el rendimiento de los atletas, el estilo de celebración de los atletas y los comentarios de los atletas. Los resultados del estudio actual han resaltado los motivos que persuadieron a los aficionados a utilizer twittear sobre un determinado atleta durante la PSL.

Estimating groundwater quality parameters through conventional methods is time-consuming through laboratory measurements for megacities. There is a need to develop models that can help decision-makers make policies for sustainable groundwater reserves. The current study compared the efficiency of multivariate linear regressions (MLR) and artificial neural network (ANN) models in the prediction of groundwater parameters for total dissolved solids (TDS) for three sub-divisions in Lahore, Pakistan. The data for this study were collected every quarter of a year for six years. ANN was applied to investigate the feasibility of feedforward, backpropagation neural networks with three training functions T-BR (Bayesian regularization backpropagation), T-LM (Levenberg–Marquardt backpropagation), and T-SCG (scaled conjugate backpropagation). Two activation functions were used to analyze the performance of algorithmic training functions, i.e., Logsig and Tanh. Input parameters of pH, electrical conductivity (EC), calcium (Ca2+), magnesium (Mg2+), chloride (Cl−), and sulfate (SO42−) was used to predict TDS as an output parameter. The computed values of TDS by ANN and MLR were in close agreement with their respective measured values. Comparative analysis of ANN and MLR showed that TDS root means square error (RMSE) for city sub-division and Pearson’s coefficient of correlation (r) for ANN and MLR were 2.9% and 0.981 and 4.5% and 0.978, respectively. Similarly, for the Farrukhabad sub-division, RMSE and r for ANN were 4.9% and 0.952, while RMSE and r for MLR were 5.5% and 0.941, respectively. For the Shahadra sub-division, RMSE was 10.8%, r was 0.869 for ANN, RMSE was 11.3%, and r was 0.860 for MLR. The results exhibited that the ANN model showed less error in results than MLR. Therefore, ANN can be employed successfully as a groundwater quality prediction tool for TDS assessment.

Hydrogen sulfide (H2S) is a naturally occurring, highly toxic gas that is formed from the decomposition of sulfur compounds. H2S is a common source of concrete and metal corrosion that results in huge economic losses in wastewater collection and treatment plants. Hence, it is necessary to analyze H2S generation and emission. H2S concentrations were measured at the Al-Saad wastewater treatment plant in the United Arab Emirates. Wastewater samples were collected, and water quality parameters were characterized in the laboratory. Simultaneously, flow characteristics, humidity, headspace airflow, and temperature were measured onsite. A neural network model to predict H2S emissions was formulated using significant parameters. It was observed that flowrate, velocity, sulfate, and total sulfur had a similar cyclic pattern throughout the sampling events. The temperature, humidity, total sulfur, and depth of wastewater were identified as the most important parameters influencing H2S emissions through correlation analysis. The neural model validation and testing had an R value of 0.9. The training had an R value of 0.8. The model provided an accuracy of 80% for the prediction of H2S concentration in wastewater treatment plants. The accuracy can be improved by increasing the data. The model is limited to its applicability in the prediction of H2S emissions under conditions similar to the inlet of a wastewater treatment plant.

This study evaluated the effect of the addition of green iron microparticles (Fe-MPs) as a three-dimensional electrode on efficiency of the electrochemical oxidation process. Polyphenols present in green tea extract act as a reducing and capping agent during green synthesis of the Fe-MPs. Scanning electron microscopy and energy-dispersive X-ray spectroscopy analysis indicates that the average size of particles is 100 µm, with about ~47 wt % of Fe in oxide form. The addition of Fe-MPs as a third electrode in the conventional electro-oxidation (EO) process converts it into a three-dimensional (3D) catalytic EO process to enhance the decolorization efficiency. Green synthesized Fe-MPs function as several microelectrodes in the process. Adsorption study indicated that only 12% of decolorization is due to adsorption on the Fe-MPs surface. Moreover, improvement in generation of hydroxyl radicals was validated by applying dimethyl sulfoxide as scavenger, and it was observed that generation of hydroxyl radicals decreased with the addition of DMSO. Results showed that decolorization efficiency increased in the 3D EO process with Fe-MPs by about 24% compared to the conventional 2D process without the Fe-MPs dosing, and initial pH as well as the Fe-MPs dose has a significant effect on decolorization efficiency during the 3D process. It is observed that reaction works better at highly acidic pH (2-4), and decolorization efficiency improved with higher doses of Fe-MPs.

Background: COVID-19 pandemic was caused by the SARS-CoV-2 virus that was thought to be associated with microvascular endothelial injury. This study aimed to demonstrate the effect of COVID-19 on markers of endothelial shedding and its effect on patient morbidity and mortality. Settings and design: This was a prospective cohort study. Methods: This study was conducted at the isolation hospital at Alexandria Main University hospitals on 40 adult patients infected with COVID-19. Patients were divided according to the severity of the presenting symptoms into two groups; moderate and severe. Serum levels of Syndecan-1 and Heparan sulfate were measured at hospital admission and at the end of the first week. Clinical and demographic data along with laboratory investigations and outcomes were compared between the two groups. Results: Our results indicated that patients with severe symptoms of COVID-19 had notably high levels of syndecan-1 and Heparan sulfate compared to patients with moderate symptoms on day 1 and day 7. Further investigations revealed that D-dimer, CRP, and IL-6 levels in patients with severe symptoms were higher in patients with severe symptoms. Our results also indicated that IL-6 increased on day 4 and gradually decreased on day 7 in both groups. Furthermore, serum levels of Syndecan-1, Heparan sulfate, D-dimer, and CRP decreased gradually from day 1 to day 7 in both groups. There was an association between markers of endothelial shedding with thrombotic and cardiovascular complications. It seems that the serum Syndecan-1 and Heparan sulfate might be good candidates to monitor COVID-19 activity. Conclusion: Patients with severe symptoms of COVID-19 have high serum levels of syndecan 1 compared to patients with moderate symptoms and have higher mortality and more prolonged hospital stay due to more endothelial injury and inflammatory reaction. Syndecan-1 may be used to monitor disease progression and severity. [ABSTRACT FROM AUTHOR]

Background Diagnosis of the cause of fever of unknown origin (FUO) is a great challenge. Serum ferritin may be a useful index for differentiating between infectious and noninfectious causes of FUO (malignant disease or collagen disease). In this respect, serum ferritin has the advantage of decreasing the number of unnecessary tests and helping to exclude infectious disease. Objective This study aimed to evaluate serum ferritin levels among patients suffering from FUO. Methods A comparison was made between infectious, noninfectious, and undiagnosed cases of FUO as regards serum ferritin level using an in-vitro enzyme-linked immunosorbent assay. Results The most common causes of FUO were infectious diseases (120/300, 40%), followed by noninfectious diseases such as malignant (61/300, 20.4%) and autoimmune causes (49/300, 16.3%). Undiagnosed cases constituted 70/300 (23.3%). The mean serum ferritin level in the infectious group, noninfectious group, and undiagnosed group was 99.25±49.58, 1098.94±284.54, and 112.40±183.23, respectively, with highly significant difference between infectious and noninfectious causes of FUO (P559 ng/ml) helps in differentiation between infectious and noninfectious causes of FUO. In undiagnosed cases of FUO we must direct our thinking to infectious diseases.

Objectives: To evaluate the presence of cell-free fetal DNA in the maternal urine in relation to gestational age as a potential source for non-invasive prenatal diagnosis. Material and methods: One hundred and sixty normal pregnant women were included in the study; 80 women pregnant with male fetuses and 80 women pregnant with female fetuses. Maternal urine of all patients was examined at 12, 16 and 20 wks’ gestation for the SRY gene (sex-determining region Y) as a cffDNA (cell free fetal DNA) marker and Ribonuclease P RNA component H1 (RPPH1) as a total cfDNA (cell free DNA) marker using a quantitative real-time PCR assay. Results: SRY gene was detected in maternal urine of those pregnant with male fetuses starting from 16 weeks in 25% (20/80) of cases only and in 80% of cases (64/80) at 20 weeks, but it was not detected at 12 weeks. All women female fetuses were negative for SRY gene. Conclusions: Cell free fetal DNA in maternal urine was not detected in early gestational age using SRY gene alone despite the use of extraction kit specific for extraction of Free-circulating nucleic acids and highly sensitive reported PCR technique. Further studies should be done to evaluate whether cell free fetal DNA in maternal urine can be detected after reaching a certain threshold in blood.

Mixing the Scenedesmus species with nanoclay and immobilizing in sodium alginate was evaluated as a sustainable treatment method for removing nitrate, atrazine, and metals from groundwater. Gel beads containing the hybrid mixture removed 100% of 10 mg/L N nitrate and 98% of 100 µg/L atrazine from synthetic groundwater in three days. The optimal amount of nanoclay was found to be 0.30 mg per bead. The experimental data fit well into a Freundlich adsorption isotherm and followed pseudo first-order kinetics. When tested in actual groundwater, 91% of nitrate and 100% of Cr, Se, and V were eliminated in three days without need for any nutrients or carbon source. Immobilizing algal beads embedded with nanoclay is a natural, low-cost alternative for groundwater treatment. The gel beads can be reused for at least two cycles without a compromise in performance. They are water-insoluble, easy to harvest, and offer high removal efficiency.

Detoxification is one of the main vital tasks performed by the liver. The purpose of this study was to investigate whether mustard in its normal or nanoparticles could confer a protective/therapeutic effect against TAA-induced acute liver failure in experimental animal models. Mustard ethanolic extract was analyzed by HPLC/MS. To induce liver failure, male rats were injected with 350 mg/kg bw TAA IP, then treated orally with a dose of 100 mg/kg for 15 d of mustard extract and its nanoform before and following induction. The levels of serum liver functions, total cholesterol (TCHo), total glyceride (TG), total bilirubin (TBIL), hepatic malonaldhyde (MDA) and nitric oxide (NO),glutathione (GSH), sodium oxide dismutase (SOD), as well as tumor necrosis factor (TNF-α,) and interleukin 6 (IL-6), were estimated. DNA genotoxicity and hepatic pathology, and immunohistologic (IHC) changes were assayed. The antioxidant content of Phenolic acids, flavonoids in mustard ethanolic extract substantially decreased the levels of ALT, AST, ALP and rehabilitated the histopathological alterations. In addition, nanoforms of mustard ethanol extract have notably increased the levels of GSH, SOD and significantly reduced the levels of MDA. The expression levels of TNF-α and IL-6 in serum and tissue were markedly downregulated. DNA genotoxicity was significantly reversed. Mustard introduced a protective and medicinal effect against TAA in both its forms.