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  1. Karami N, Mohammadi P, Zinatizadeh A, Falahi F, Aghamohammadi N
    Ultrason Sonochem, 2018 Sep;46:89-98.
    PMID: 29739516 DOI: 10.1016/j.ultsonch.2018.04.009
    The biomass concentration of conventional activated sludge (CAS) process due to low sludge sedimentation in clarifiers is limited to 3000 mg/L. In this study, high-frequency ultrasound wave (1.8 MHz) was applied to enhance the CAS process performance using high Mixed Liquor Suspended Solid (MLSS) concentration. The study conducted using a pilot scale CAS bioreactor (with and without ultrasound) and their performance for treating a hospital wastewater were compared. Experimental conditions were designed based on a Central Composite Design (CCD). The sets of data analyzed, modeled and optimized using Response Surface Methodology (RSM). The effect of MLSS concentration 3000-8000 mg/L and hydraulic retention time (HRT) 2-8 h are considered as operating variables to investigate on process responses. The obtained results showed that high-frequency ultrasound was significantly decreased the sludge volume index (SVI) 50% and effluent turbidity about 88.5% at high MLSS. Also, observed that COD removal of both systems was nearly similar, as the maximum COD removal for sonicated and non-sonicated systems were 92 and 92.5% respectively. However, this study demonstrates that the ultrasound irradiation has not had any negative effect on the microbial activity.
  2. Mohammadi P, Karami N, Zinatizadeh AA, Falahi F, Aghamohammadi N, Almasi A
    Ultrason Sonochem, 2019 Jan 22.
    PMID: 30712854 DOI: 10.1016/j.ultsonch.2019.01.030
    In this study, high-frequency ultrasound wave (1.8 MHz) at low intensity was applied to improve activated sludge settleability at high MLSS concentration. The effect of irradiation intensity, sonication mode, MLSS concentration and sample volume on the physical characteristics of sludge in a pilot scale settling column were investigated for optimizing the conditions. The obtained results showed that high-frequency ultrasound decreased the height of sludge (44%) and effluent turbidity (82.2%) and increased sludge settling velocity about 3 times at high biomass concentration. Irradiation intensity of 0.4 w/cm2 and sonication mode with interval times of 10 s showed the best results on the performance of the system at MLSS concentration of 8000 mg/L with a sample volume of 3 L.
  3. Hosseinzadeh-Bandbafha H, Tabatabaei M, Aghbashlo M, Khanali M, Khalife E, Roodbar Shojaei T, et al.
    Data Brief, 2020 Jun;30:105428.
    PMID: 32322611 DOI: 10.1016/j.dib.2020.105428
    Integrated environmental analysis using life cycle assessment for different fuel blends used in a single-cylinder diesel engine was performed to select the most eco-friendly fuel blend. More specifically, the inventory data in support of the integrated environmental analysis of water-emulsified 5% biodiesel/diesel blends (B5) containing different levels of carbon nanoparticles (i.e., 38, 75, and 150 µM) as a novel fuel nanoadditives at a fixed engine speed of 1000 rpm and four different engine loads (i.e., 25, 50, 75, and 100%) are presented. Neat diesel, B5, and B5 containing water (3 wt.%) were used as controls. Raw data related to the production and combustion of fuel blends were experimentally collected. Industrial (i.e., experiments at large scale) and laboratory (i.e., experiments at small scale) data were used for fuel blends production while experimental data obtained by engine tests were used for the combustion stage. Then raw data were processed with the IMPACT 2002+ methods by using the SimaPro software and EcoInvent database and were then converted into environmental impacts. Accordingly, six supplementary files including the inventory data on integrated environmental analysis of the different fuel blends are presented (Supplementary Files 1-6). The data could be applied for integrated environmental analysis in order to avoid subjective weighting of combustion parameters for selecting the most eco-friendly fuel blend for use in diesel engines. More specifically, by developing a single score indicator obtained through conducting integrated combustion analysis, comparison of various fuel blends is largely facilitated.
  4. Salari N, Fatahi B, Bartina Y, Kazeminia M, Fatahian R, Mohammadi P, et al.
    J Transl Med, 2021 Dec 20;19(1):516.
    PMID: 34930325 DOI: 10.1186/s12967-021-03185-7
    BACKGROUND: Myasthenia gravis is a neuromuscular autoimmune disorder characterized by weakness and disability in the voluntary muscles. There have been several preliminary studies on the epidemiology of myasthenia gravis in different parts of the world and the effectiveness of common drugs in its treatment, but there has been no comprehensive study of the efficacy of common drugs in the treatment of myasthenia gravis. Therefore, this study aimed to determine the epidemiology of myasthenia gravis globally and the effectiveness of common drugs in its treatment using systematic review and meta-analysis.

    METHODS: Research studies were extracted from IranDoc, MagIran, IranMedex, SID, ScienceDirect, Web of Sciences (WoS), ProQuest, Medline (PubMed), Scopus and Google Scholar based on Cochran's seven-step guidelines using existing keywords extracted in MeSH browser. The I2 test was used to calculate the heterogeneity of studies, and Begg and Mazumdar rank correlation tests were used to assess publication bias. Data were analyzed using Comprehensive Meta-Analysis software (Version 2).

    RESULTS: In the search for descriptive studies based on the research question, 7374 articles were found. After deleting articles unrelated to the research question, finally, 63 articles with a sample size of 1,206,961,907 people were included in the meta-analysis. The prevalence of MG worldwide was estimated to be 12.4 people (95% CI 10.6-14.5) per 100,000 population. For analytical studies on the effectiveness of common myasthenia gravis drugs, 4672 articles were found initially, and after removing articles unrelated to the research question, finally, 20 articles with a sample size of 643 people in the drug group and 619 people in the placebo group were included in the study. As a result of the combination of studies, the difference between the mean QMGS score index after taking Mycophenolate and Immunoglobulin or plasma exchange drugs in the group of patients showed a significant decrease of 1.4 ± 0.77 and 0.62 ± 0.28, respectively (P < 0.01).

    CONCLUSION: The results of systematic review of drug evaluation in patients with myasthenia gravis showed that Mycophenolate and Immunoglobulin or plasma exchange drugs have positive effects in the treatment of MG. It also represents the positive effect of immunoglobulin or plasma exchange on reducing SFEMG index and QMGS index and the positive effect of Mycophenolate in reducing MG-ADL index, SFEMG and Anti-AChR antibodies index. In addition, based on a meta-analysis of the random-effect model, the overall prevalence of MG in the world is 12.4 people per 100,000 population, which indicates the urgent need for attention to this disease for prevention and treatment.

  5. Amid S, Aghbashlo M, Peng W, Hajiahmad A, Najafi B, Ghaziaskar HS, et al.
    Sci Total Environ, 2021 Oct 20;792:148435.
    PMID: 34147796 DOI: 10.1016/j.scitotenv.2021.148435
    A diesel engine running on diesel/biodiesel mixtures containing ethylene glycol diacetate (EGDA) was investigated from the exergoeconomic and exergoenvironmental viewpoints. Biodiesel was mixed with petrodiesel at 5% and 20% volume ratios, and the resultant mixtures were then doped with EGDA at 1-3% volume ratios. The exergetic sustainability indicators of the engine operating on the prepared fuel formulations were determined at varying engine loads. The indicators were selected to support decision-making on fuel composition and engine load following thermodynamic, economic, and environmental considerations. The engine load markedly affected all the studied exergetic parameters. The highest engine exergetic efficiency (39.5%) was obtained for petrodiesel doped with 1 v/v% EGDA at the engine load of 50%. The minimum value of the unit cost of brake power exergy (49.6 US$/GJ) was found for straight petrodiesel at full-load conditions, while the minimum value of the unit environmental impact of brake power exergy (29.9 mPts/GJ) was observed for petrodiesel mixed with 5 v/v% biodiesel at the engine load of 75%. Overall, adding EGDA to fuel mixtures did not favorably influence the outcomes of both exergetic methods due to its energy-intensive and cost-prohibitive production process. In conclusion, although petrodiesel fuel improvers such EGDA used in the present study could properly mitigate pollutant emissions, the adverse effects of such additives on thermodynamic parameters of diesel engines, particularly on exergoeconomic and exergoenvironmental indices, need to be taken into account, and necessary optimizations should be made before their real-world application.
  6. Khounani Z, Abdul Razak NN, Hosseinzadeh-Bandbafha H, Madadi M, Sun F, Mohammadi P, et al.
    Environ Res, 2024 May 01;248:118286.
    PMID: 38280524 DOI: 10.1016/j.envres.2024.118286
    This study assesses the environmental impact of pine chip-based biorefinery processes, focusing on bioethanol, xylonic acid, and lignin production. A cradle-to-gate Life Cycle Assessment (LCA) is employed, comparing a novel biphasic pretreatment method (p-toluenesulfonic acid (TsOH)/pentanol, Sc-1) with conventional sulfuric acid pretreatment (H2SO4, Sc-2). The analysis spans biomass handling, pretreatment, enzymatic hydrolysis, yeast fermentation, and distillation. Sc-1 yielded an environmental impact of 1.45E+01 kPt, predominantly affecting human health (96.55%), followed by ecosystems (3.07%) and resources (0.38%). Bioethanol, xylonic acid, and lignin contributed 32.61%, 29.28%, and 38.11% to the total environmental burdens, respectively. Sc-2 resulted in an environmental burden of 1.64E+01 kPt, with a primary impact on human health (96.56%) and smaller roles for ecosystems (3.07%) and resources (0.38%). Bioethanol, xylonic acid, and lignin contributed differently at 22.59%, 12.5%, and 64.91%, respectively. Electricity generation was predominant in both scenarios, accounting for 99.05% of the environmental impact, primarily driven by its extensive usage in biomass handling and pretreatment processes. Sc-1 demonstrated a 13.05% lower environmental impact than Sc-2 due to decreased electricity consumption and increased bioethanol and xylonic acid outputs. This study highlights the pivotal role of pretreatment methods in wood-based biorefineries and underscores the urgency of sustainable alternatives like TsOH/pentanol. Additionally, adopting greener electricity generation, advanced technologies, and process optimization are crucial for reducing the environmental footprint of waste-based biorefineries while preserving valuable bioproduct production.
  7. Mohammadi P, Taghavi E, Foong SY, Rajaei A, Amiri H, de Tender C, et al.
    Int J Biol Macromol, 2023 Jul 01;242(Pt 2):124841.
    PMID: 37182628 DOI: 10.1016/j.ijbiomac.2023.124841
    Depending on its physicochemical properties and antibacterial activities, chitosan can have a wide range of applications in food, pharmaceutical, medicine, cosmetics, agriculture, and aquaculture. In this experimental study, chitosan was extracted from shrimp waste through conventional extraction, microwave-assisted extraction, and conventional extraction under microwave process conditions. The effects of the heating source on the physicochemical properties and antibacterial activity were investigated. The results showed that the heating process parameters affected the physicochemical properties considerably. The conventional procedure yielded high molecular weight chitosan with a 12.7 % yield, while the microwave extraction procedure yielded a porous medium molecular weight chitosan at 11.8 %. The conventional extraction under microwave process conditions led to medium molecular weight chitosan with the lowest yield (10.8 %) and crystallinity index (79 %). Antibacterial assessment findings revealed that the chitosan extracted using the conventional method had the best antibacterial activity in the agar disk diffusion assay against Listeria monocytogenes (9.48 mm), Escherichia coli. (8.79 mm), and Salmonella Typhimurium (8.57 mm). While the chitosan obtained by microwave-assisted extraction possessed the highest activity against E. coli. (8.37 mm), and Staphylococcus aureus (8.05 mm), with comparable antibacterial activity against S. Typhimurium (7.34 mm) and L. monocytogenes (6.52 mm). Moreover, the minimal inhibitory concentration and minimal bactericidal concentration assays demonstrated that among the chitosan samples investigated, the conventionally-extracted chitosan, followed by the chitosan extracted by microwave, had the best antibacterial activity against the target bacteria.
  8. Atarod P, Khlaife E, Aghbashlo M, Tabatabaei M, Hoang AT, Mobli H, et al.
    J Hazard Mater, 2021 04 05;407:124369.
    PMID: 33160782 DOI: 10.1016/j.jhazmat.2020.124369
    This study was set up to model and optimize the performance and emission characteristics of a diesel engine fueled with carbon nanoparticle-dosed water/‎diesel emulsion fuel using a combination of soft computing techniques. Adaptive neuro-fuzzy inference system tuned by particle ‎swarm algorithm was used for modeling the performance and emission parameters of the engine, while optimization of the engine operating parameters and the fuel composition was conducted via multiple-objective particle ‎swarm algorithm. The model input variables were: injection timing (35-41° CA BTDC), engine load (0-100%), nanoparticle dosage (0-150 μM), and water content (0-3 wt%). The model output variables included: brake specific fuel consumption, brake thermal efficiency, as well as carbon monoxide, carbon dioxide, nitrogen oxides, and unburned hydrocarbons emission concentrations. The training and testing of the modeling system were performed on the basis of 60 data patterns obtained from the experimental trials. The effects of input variables on the performance and emission characteristics of the engine were thoroughly analyzed and comprehensively discussed as well. According to the experimental results, injection timing and engine load could significantly affect all the investigated performance and emission parameters. Water and nanoparticle addition to diesel could markedly affect some performance and emission parameters. The modeling system could predict the output parameters with an R2 > 0.93, MSE 
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