The Primary Outcomes and Epidemiological and Clinical Features of Coronavirus Disease 2019 (COVID-19) in Iran.

AIM: We aimed to describe the epidemiological and clinical characteristics of Iranian patients with COVID-19. METHODS: In this single-center and retrospective study, patients with confirmed COVID-19 infections were enrolled. Univariate and multivariate logistic regression methods were used to explore the risk factors associated with outcomes. RESULTS: Of 179 patients with confirmed COVID-19 infection, 12 remained hospitalized at the end of the study and 167 were included in the final analysis. Of these, 153 (91.6%) were discharged and 14 (8.38%) died in hospital. Approximately half (50.9%) of patients suffered from a comorbidity, with diabetes or coronary heart disease being the most common in 20 patients. The most common symptoms on admission were fever, dyspnea, and cough. The mean durations from first symptoms to hospital admission was 8.64 ± 4.14 days, whereas the mean hospitalization time to discharge or death was 5.19 ± 2.42 and 4.35 ± 2.70 days, respectively. There was a significantly higher age in non-survivor patients compared with survivor patients. Multivariate regression showed increasing odds ratio (OR) of in-hospital death associated with respiratory rates >20 breaths/min (OR: 5.14, 95% CI: 1.19-22.15, p = 0.028) and blood urea nitrogen (BUN) >19 mg/dL (OR: 4.54, 95% CI: 1.30-15.85, p = 0.017) on admission. In addition, higher respiratory rate was associated with continuous fever (OR: 4.08, 95% CI: 1.18-14.08, p = 0.026) and other clinical symptoms (OR: 3.52, 95% CI: 1.05-11.87, p = 0.04). CONCLUSION: The potential risk factors including high respiratory rate and BUN levels could help to identify COVID-19 patients with poor prognosis at an early stage in the Iranian population.

Kinetic Modeling and Degradation Study of Liquid Polysulfide Resin-Clay Nanocomposite.

Kinetic modeling and degradation study of liquid polysulfide (LPS)/clay nanocomposite is possible through Ozawa-Flynn-Wall (OFW) and Kissinger methods. Comparing the results of these models with experimental data leads to provide an accurate degradation kinetic evaluation of these materials. To this aim, the morphology and distribution of clay nanoparticles (CNPs) within the LPS matrix were investigated using Field Emission Scanning Electron Microscopy (FESEM) and X-ray diffraction (XRD). To evaluate the interaction between the LPS and the CNPs, the Fourier transform infrared (FTIR) identification was utilized. Furthermore, to investigate the kinetics of degradation, the thermal gravimetric analysis (TGA) and derivative thermogravimetry (DTG) of the samples were used in the nitrogen atmosphere with the help of Kissinger and Ozawa-Flynn-Wall (OFW) models. The characterization results confirmed the homogenous dispersion of the CNPs into the LPS matrix. In addition, the presence of CNPs increased the thermal stability and activation energy (Ea) of the samples at different conversion rates. Moreover, the OFW method was highly consistent with the experimental data and provided an appropriate fit for the degradation kinetics.

Thermal Degradation Kinetics and Modeling Study of Ultra High Molecular Weight Polyethylene (UHMWP)/Graphene Nanocomposite.

The incorporation of nanofillers such as graphene into polymers has shown significant improvements in mechanical characteristics, thermal stability, and conductivity of resulting polymeric nanocomposites. To this aim, the influence of incorporation of graphene nanosheets into ultra-high molecular weight polyethylene (UHMWPE) on the thermal behavior and degradation kinetics of UHMWPE/graphene nanocomposites was investigated. Scanning electron microscopy (SEM) analysis revealed that graphene nanosheets were uniformly spread throughout the UHMWPE's molecular chains. X-Ray Diffraction (XRD) data posited that the morphology of dispersed graphene sheets in UHMWPE was exfoliated. Non-isothermal differential scanning calorimetry (DSC) studies identified a more pronounced increase in melting temperatures and latent heat of fusions in nanocomposites compared to UHMWPE at lower concentrations of graphene. Thermogravimetric analysis (TGA) and derivative thermogravimetric (DTG) revealed that UHMWPE's thermal stability has been improved via incorporating graphene nanosheets. Further, degradation kinetics of neat polymer and nanocomposites have been modeled using equations such as Friedman, Ozawa-Flynn-Wall (OFW), Kissinger, and Augis and Bennett's. The "Model-Fitting Method" showed that the auto-catalytic nth-order mechanism provided a highly consistent and appropriate fit to describe the degradation mechanism of UHMWPE and its graphene nanocomposites. In addition, the calculated activation energy (Ea) of thermal degradation was enhanced by an increase in graphene concentration up to 2.1 wt.%, followed by a decrease in higher graphene content.

Machine-learning-assisted prediction and optimized kinetic modelling of residual chlorine decay for enhanced water quality management.

The quality of water changes from source to tap, presenting challenges in maintaining consistent water quality across the system. Predicting water quality in distribution systems, including disinfectant residual loss and by-product formation, has been the subject of research since the early 1990s. Although numerous models have been proposed to predict residual chlorine decay, disputes exist among researchers and experts over the superiority of certain models. Accordingly, this study modified the existing process-based bulk decay models by replacing the initial Total Residual Chlorine (TRC) concentration parameter with TRC demand, leading to an improvement in the models' performance. The modification resulted in a 38.03%, 28.02%, 23.11%, and 33.29% average improvement in Mean Squared Error (MSE) values for the First Order Model (FOM), Parallel First Order Model (PFOM), Second Order Model (SOM), and Parallel Second Order Model (PSOM), respectively. The study also introduced an online predictive method based on a Machine Learning (ML) algorithm that predicts the first-order TRC bulk decay rate by using water quality parameters as inputs. A Gaussian Process Regression (GPR) model was used to predict the kinetic parameters in FOM, which accurately predicted the test sets for most of the cases. In addition, a new methodology was proposed in this study for predicting TRC in water distribution systems that incorporates the variability of source natural organic matter, operational actions, and water demands. This method seeks to develop high-fidelity and robust water quality predictions that provide operational decision support for optimized distribution system management. In conclusion, this study emphasizes the importance of understanding water quality changes from source to tap and the challenges of maintaining consistent water quality across the system. The study suggests modifying existing models and introducing a novel methodology for predicting residual chlorine in water distribution systems that can improve water quality management and, ultimately, better public health outcomes.

Degradation of organics and formation of DBPs in the combined LED-UV and chlorine processes: Effects of water matrix and fluorescence analysis.

Combined processes of light-emitting diodes ultraviolet (LED UV) and chlorination (Cl2) are alternative disinfection technologies in drinking water, while the formation of disinfection by-products (DBPs) needs to be evaluated. This study investigated the impacts of critical water matrix factors on the DBP formation in the combined processes. Moreover, the correlation between the degraded natural organic matter (NOM) and the formed DBP was studied. Simultaneous UV/Cl2 outperformed single Cl2 and sequential combined processes in degrading humic acids (HA) and resulted in the highest DBP yield. Iodide at 5-20 µg/L and bromide at 0.05-0.2 mg/L slightly affected the degradation of organics, while increased the formation of brominated DBPs up to 36.6 µg/L. pH 6 was regarded as the optimum pH, achieving high efficiency of HA degradation and a lower level of total DBP formation than pH 7 and 8 by 11 % and 24 %, respectively. Compared to HA samples (46.8-103.9 µg/L per mg/L DOC), NOM in canal water were less aromatic and yielded fewer DBPs (19.6 and 21.2 µg/L per mg/L DOC). However, the extremely high bromide in site 1 samples (18.6 mg/L) shifted the chlorinated DBPs to their brominated analogues, posting around 1 order of magnitude higher levels of toxicities than HA samples. The reduction of absorbance at 254 nm (UV254) correlated with all DBP categories in HA samples, while the correlation coefficients were compromised when included in the canal samples. For the first time, this study found that parallel factor analysis (PARAFAC) would neglect the fluorescence change caused by iodide/bromide in UV/Cl2, while the changes could be captured by self-organising map (SOM) trained with full fluorescence spectra. Fluorescence Ex/Em pairs were proposed to predict DBP formation, suggesting a potential method to develop an online monitoring system for DBPs.

Investigation of the efficacy of the UV/Chlorine process for the removal of trimethoprim: Effects of operational parameters and artificial neural networks modelling.

The UV/Cl2 process (also known as chlorine photolysis, which is the combination of chlorine and simultaneous irradiation of UV light) is conventionally applied at acidic mediums for drinking water treatment and further treatment of wastewater effluents for secondary reuse. This is because the quantum yield of HO• from HOCl (ϕHO•, 254 = 1.4) is greater than the one from OCl- (ϕHO•, 254 = 0.278) by approximately 5 times. Moreover, chlorine photolysis in acidic mediums also tends to have lower radical quenching rates than that of their alkaline counterparts by up to 1000 times. The aim of this research is to investigate the applicability of the UV/Cl2 process by assessing its efficacy on the removal of trimethoprim (TMP) at not only acidic to neutral conditions (pH 6-7), but also alkaline mediums (pH 8-9). At alkaline pH, free chlorine exists as OCl- and since OCl- has a higher molar absorption coefficient as compared to HOCl at higher wavelengths, there would be higher reactive chlorine species (RCS) formation and contribution. TMP removal followed pseudo-first order kinetics and depicted that a maximum fluence based constant (kf' = 0.275 cm2/mJ) was obtained using 42.25 µM (3 mg/L) of chlorine at pH 9, with an irradiation of 275 nm. At alkaline conditions, chlorine photolysis performance followed the trend of UV (275)/Cl2 > UV (265)/Cl2 > UV (310)/Cl2 > UV (254)/Cl2. RCS like Cl•, Cl2-• and ClO• contributed to the degradation of TMP. When the pH was increased from 6 to 8, contribution from hydroxyl radicals (HO• ) was decreased whilst that of RCS was increased. Application of UV (310)/Cl2 had the highest HO• generation, contributing to TMP removals up to 13% to 48% as compared to 5% to 27% in UV (254, 265, 275)/Cl2 systems at pH 6-9. Artificial neural networks modelling was found to be able to verify and predict the contribution of HO• and RCS conventionally calculated via the general kinetic equations in the UV/Cl2 system at 254, 265, 275 and 310 nm.

Innovations in Drug Delivery for Chronic Wound Healing.

Wound healing is a varied and complex process designed to restore normal skin structure, function, and appearance in a timely manner. To achieve this goal, different immune and biological systems participate in coordination through four separate steps, including homeostasis, inflammation, proliferation, and regeneration. Each step involves the function of different cells, cytokines, and growth factors. However, chronic ulcers, which are classified into three types of ulcers, namely vascular ulcers, diabetic ulcers, and pressure ulcers, are not able to heal through the mentioned natural stages. This, in turn, causes mental and physical problems for these people and, as a result, imposes high economic and social costs on the society. In this regard, using a system that can accelerate the healing process of such chronic wounds, as an urgent need in society, should be considered. Therefore, in this study, the innovations of drug delivery systems for the healing of chronic wounds using hydrogels, nanomaterials, and membranes are discussed and reviewed.

Synthesis and characterization of a novel molecularly imprinted polymer for the controlled release of rivastigmine tartrate.

To develop novel imprinted poly (methacrylic acid) nanoparticles for the controlled release of Rivastigmine Tartrate (RVS), the amalgamation of molecular imprinting techniques and polymerization of precipitates were applied in this work. By permuting different concentrations of pentaerythritol triacrylate (PETA) or trimethylolpropane triacrylate (TMPTA) as cross-linkers, ten different samples were synthesized, and their abilities assessed for RVS absorption. Among them, uniform mono-disperse nanoparticles were synthesized in an RVS/PMAA/PETA mole ratio of 1:6:12, named molecularly imprinted polymers 2 (MIP2), which showed the highest RVS absorption. Analytical procedures involving the Fourier transform infrared (FT-IR), Thermogeometric analysis (TGA), Field emission scanning electron microscopy (FE-SEM), Dynamic light scattering (DLS), and absorption/desorption porosimetry (BET) measurements were applied to characterize the morphology and physicochemical properties of the MIP2. In addition, the cytotoxicity of the MIP2 sample was measured by MTT assay on an L929 cell line. Studies pertaining to the in-vitro release of RVS from MIP2 samples showed that the prepared sample had a controlled and sustained release compared, which differed from the results obtained from the non-imprinted polymer (NIP) with the same formulization. Results obtained further reinforced the feasibility of prepared MIPs as a prime candidature for RVS drug delivery to alleviate Alzheimer's and other diseases.

Cationic liposomes formulated with a novel whole Leishmania lysate (WLL) as a vaccine for leishmaniasis in murine model.

Although there have been numerous attempts to develop a successful vaccine against leishmaniasis, based on the clinical trial in this field, no vaccine against Leishmania in routine way can be found for globally effective vaccination in human. Amongst, first generation vaccines consisting of parasite fractions or whole killed Leishmania showed more successful results in clinical trials. It seems that the main reason for the low efficacy of these vaccines is lack of a suitable adjuvant. In this study, a crude extract of detergent-solubilized L. major promastigotes as a novel developed antigen (whole Leishmania lysate (WLL)) was formulated in liposomal form. The cationic liposomes consisting of 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) were used to deliver WLL. Liposomes formulations containing different WLL concentrations (prepared from 103, 104, 105, 106 and 107 parasites) were prepared and characterized for particle size, surface charge, proteins, DNA and phospholipids contents. Moreover, to explore the type of immune response generated and extend of immunization, in vivo and in vitro tests including evaluation of lesion development, parasite burden in the foot and spleen, Th1 and Th2 cytokine analysis, and titration of IgG isotypes before and after the challenge were used. The maximum immunization was provided by WLL06 as depicted by the reduction of footpad swelling andparasite load, increase in anti-Leishmania IgG2a production, though no significant difference was observed between mice which received WLL05 vs WLL06. While maximum immunization was seen in WLL06 group, most of the liposomal WLL formulations induced a mixed Th1/Th2 response. Hence, a more protective immune response is expected to be induced when an immune potentiator adjuvant such as CpG ODNs would be co-deliverd in WLL liposomal formulations.