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This study investigates factors influencing housing prices in Tehran's metropolitan area and predicts their values. We analysed a sample of 32,162 housing units using Hedonic Model and Artificial Neural Networks for prediction and comparison. The Results indicate that distance to certain transportation facilities, such as airports, bus terminals, and road intersections, positively affects housing prices, potentially due to their capacity to attract traffic and environmental externalities. Conversely, distance to facilities like public bike stations and bus rapid transit stations negatively impacts prices, signalling their role in enhancing accessibility. Notably, ANN outperformed hedonic in predicting housing prices. These findings hold significant implications for policymakers, investors, and housing market stakeholders, shedding light on the intricate relationship between transportation infrastructure and housing prices. The study underscores the importance of employing diverse modelling methods to capture the non-linear dynamics of housing markets. These insights are crucial for evidence-based decision-making and can inform more effective policies and strategies in metropolitan Tehran and other similar cities. By aligning transportation policies with housing market needs, cities can enhance urban development and promote sustainable growth. [ABSTRACT FROM AUTHOR]

Background/objective: Naringenin is a member of the flavonoid family that can perform many biological processes to treat a wide range of inflammatory diseases and pathological conditions related to oxidative stress (OS). Naringenin immunomodulatory activities have been the subject of recent research as an effective alternative treatment for autoimmune disorders. The effects of naringenin on the levels of inflammatory biomarkers and OS factors in animal models of autoimmune disorders (ADs) were studied in this meta-analysis. Methods: Up until January 2022, electronic databases such as Cochrane Library and EMBASE, PubMed, Web of Science, and Scopus were used to conduct a comprehensive literature search in English language. To evaluate the effect of naringenin on inflammatory mediators, such as TNF-α, IL-6, IL-β, IFN-γ, NF-κB, and nitric oxide, and OS biomarkers, such as CAT, SOD, GPx, GSH and MDA, in AD models, we measured the quality assessment and heterogeneity test using the PRISMA checklist protocol and I2 statistic, respectively. A random-effects model was employed based on the heterogeneity test, and then pooled data were standardized as mean difference (SMD) with a 95% confident interval (CI). Results: We excluded all clinical trials, cell experiment studies, animal studies with different parameters, non-autoimmune disease models, and an inadequate series of studies for quantitative synthesis. Finally, from 627 potentially reports, 12 eligible studies were included in the meta-analysis. Data were collected from several groups. Of these, 153 were in the naringenin group and 149 were in the control group. Our meta-analysis of the pooled data for the parameters of inflammation and OS indicated that naringenin significantly reduced the levels of NF-κB (SMD − 3.77, 95% CI [− 6.03 to − 1.51]; I2 = 80.1%, p = 0.002), IFN-γ (SMD − 6.18, 95% CI [− 8.73 to − 3.62]; I2 = 53.7%, p = 0.115), and NO (SMD − 3.97, 95% CI [− 5.50 to − 2.45]; I2 = 73.4%, p = 0.005), IL-1β (SMD − 4.23, 95% CI [− 5.09 to − 3.37]; I2 = 0.0%, p = 0.462), IL-6 (SMD − 5.84, 95% CI [− 7.83 to − 3.85]; I2 = 86.5%, p < 0.001), and TNF-α (SMD − 5.10, 95% CI [− 6.34 to − 3.86]; I2 = 74.7%, p < 0.001). These findings also demonstrated the efficacy of naringenin on increasing the levels of CAT (SMD 4.19, 95% CI [1.33 to 7.06]; I2 = 79.9%, p = 0.007), GSH (SMD 4.58, 95% CI [1.64 to 7.51]; I2 = 90.5%, p < 0.001), and GPx (SMD 9.65, 95% CI [2.56 to 16.74]; I2 = 86.6%, p = 0.001) and decreasing the levels of MDA (SMD − 3.65, 95% CI [− 4.80 to − 2.51]; I2 = 69.4%, p = 0.001) than control groups. However, treatment with naringenin showed no statistically difference in SOD activity (SMD 1.89, 95% CI [− 1.11 to 4.89]; I2 = 93.6%, p < 0.001). Conclusion: Overall, our findings revealed the immunomodulatory potential of naringenin as an alternative treatment on inhibition of inflammation and OS in several autoimmune-related diseases. Nevertheless, regarding the limitation of clinical trials, strong preclinical models and clinical settings in the future are needed that address the effects of naringenin on ADs. Before large-scale clinical studies, precise human pharmacokinetic investigations are required to determine the dosage ranges and evaluate the initial safety profile of naringenin. [ABSTRACT FROM AUTHOR]

Background/objective: Apigenin is a member of the flavonoid family that can regulate various biological processes, which is characterized as a treatment of different inflammatory disorders and pathological problems associated with oxidative stress (OS). Recent research has focused on apigenin immunomodulatory properties as a potential treatment for different types of lung injuries. This meta-analysis was designed to determine the impact of apigenin treatment on inflammatory markers and OS parameters in animal models of lung injuries. Methods: The comprehensive literature search was conducted using electronic databases such as Google Scholar, PubMed, Web of Science, Scopus, and Embase up to August 2021. To assess apigenin's effect on inflammatory mediators and OS biomarkers in lung injury animal models, we used the I2 statistic to determine the heterogeneity. We then pooled data as standardized mean difference (SMD) with a 95% confidence interval (CI). Results: Our meta-analysis of the pooled data for inflammatory biomarkers demonstrated that the apigenin administration significantly decreased the NF-κB expression (SMD − 1.60, 95% CI [− 2.93 to − 0.26]; I2 = 89.0%, p < 0.001), IL-1β (SMD − 4.30, 95% CI [− 6.24 to − 2.37]; I2 = 67.3%, p = 0.047), IL-6 (SMD − 4.10, 95% CI [− 5.04 to − 3.16]; I2 = 72.6%, p < 0.001), TNF-α (SMD − 3.74, 95% CI [− 4.67 to − 2.82]; I2 = 84.1%, p < 0.001), and TNF-α gene expression (SMD − 3.44, 95% CI [− 4.44 to − 2.43]; I2 = 0.0%, p = 0.622). This study also indicated the efficacy of apigenin in increasing the level of CAT (SMD 4.56, 95% CI [3.57 to 5.55]; I2 = 15.3%, p = 3.15), GSH (SMD 5.12, 95% CI [3.53 to 6.70]; I2 = 77.6%, p < 0.001), and SOD (SMD 3.45, 95% CI [2.50 to 4.40]; I2 = 79.2%, p < 0.001), and decreasing the level of MDA (SMD − 3.87, 95% CI [− 5.25 to − 2.49]; I2 = 80.3%, p < 0.001) and MPO (SMD − 4.02, 95% CI [− 5.64 to − 2.40]; I2 = 88.9%, p < 0.001), TGF− β (SMD − 3.81, 95% CI [− 4.91 to − 2.70]; I2 = 73.4%, p = 0.001) and W/D level (SMD − 3.22, 95% CI [− 4.47 to − 1.97]; I2 = 82.1%, p < 0.001) than control groups. Conclusion: Overall, our findings showed the immunomodulatory potential of apigenin as an alternative treatment for the suppression of inflammatory responses and OS in different types of lung injury diseases. Nevertheless, due to the paucity of clinical studies, reliable preclinical models, and clinical settings, evaluating the influence of apigenin on lung injury is required in the future. Before conducting large-scale clinical trials, detailed human pharmacokinetic studies are also needed to establish dosage ranges and determine the initial safety and tolerability of apigenin. [ABSTRACT FROM AUTHOR]

Background/objective: Systemic inflammation and oxidative stress (OS) are associated with breast cancer. CoQ10 as an adjuvant treatment with conventional anti-cancer chemotherapy has been demonstrated to help in the inflammatory process and OS. This systematic review and meta-analysis of randomized clinical trials (RCTs) aimed to evaluate the efficacy of CoQ10 supplementation on levels of inflammatory markers, OS parameters, and matrix metalloproteinases/tissue inhibitor of metalloproteinases (MMPs/TIMPs) in patients with breast cancer. Methods: A systematic literature search was carried out using electronic databases, including PubMed, Web of Science, Scopus, Google Scholar, and Embase, up to December 2020 to identify eligible RCTs evaluating the effect of CoQ10 supplementation on OS biomarkers, inflammatory cytokines, and MMPs/TIMPs. From 827 potential reports, 5 eligible studies consisting of 9 trials were finally included in the current meta-analysis. Quality assessment and heterogeneity tests of the selected trials were performed using the PRISMA checklist protocol and the I2 statistic, respectively. Fixed and random-effects models were assessed based on the heterogeneity tests, and pooled data were determined as the standardized mean difference (SMD) with a 95% confidence interval (CI). Results: Our meta-analysis of the pooled findings for inflammatory biomarkers of OS and MMPs showed that CoQ10 supplementation (100 mg/day for 45–90 days) significantly decreased the levels of VEGF [SMD: − 1.88, 95% CI: (− 2. 62 to − 1.13); I2 = 93.1%, p < 0.001], IL-8 [SMD: − 2.24, 95% CI: (− 2.68 to − 1.8); I2 = 79.6%, p = 0.001], MMP-2 [SMD: − 1.49, 95% CI: (− 1.85 to − 1.14); I2 = 76.3%, p = 0.005] and MMP-9 [SMD: − 1.58, 95% CI: (− 1.97 to − 1.19); I2 = 79.6%, p = 0.002], but no significant difference was observed between CoQ10 supplementation and control group on TNF-α [SMD: − 2.30, 95% CI: (− 2.50 to − 2.11); I2 = 21.8%, p = 0.280], IL-6 [SMD: − 1.56, 95% CI: (− 1.73 to − 1.39); I2 = 0.0%, p = 0.683], IL-1β [SMD: − 3.34, 95% CI: (− 3.58 to − 3.11); I2 = 0.0%, p = 0.561], catalase (CAT) [SMD: 1.40, 95% CI: (1.15 to 1.65); I2 = 0.0%, p = 0.598], superoxide dismutase (SOD) [SMD: 2.42, 95% CI: (2.12 to 2.71); I2 = 0.0%, p = 0.986], glutathione peroxidase (GPx) [SMD: 2.80, 95% CI: (2.49 to 3.11); I2 = 0.0%, p = 0.543]], glutathione (GSH) [SMD: 4.71, 95% CI: (4.26 to 5.16); I2 = 6.1%, p = 0.302] and thiobarbituric acid reactive substances (TBARS) [SMD: − 3.20, 95% CI: (− 3.53 to − 2.86); I2 = 29.7%, p = 0.233]. Conclusion: Overall, the findings showed that CoQ10 supplementation reduced some of the important markers of inflammation and MMPs in patients with breast cancer. However, further studies with controlled trials for other types of cancer are needed to better understand and confirm the effect of CoQ10 on tumor therapy. [ABSTRACT FROM AUTHOR]

In this work, equilibrium solubility of CO2 in aqueous blends of different amines is examined. The amines used are methyldiethanolamine (MDEA), N,N-dimethylaminoethanol (DMAE), N,N-diethylaminoethanol (DEAE), 2-(2-aminoethylamino)ethanol (AEEA), and 3-methylamino propylamine (MAPA). New equilibrium solubility data for CO2 in aqueous solutions of DMAE + MAPA, DMAE + AEEA, MDEA + MAPA, MDEA + AEEA, DEAE + MAPA and DEAE + AEEA over a range of low pressures are obtained. Each of the solutions contains 40 wt% of a tertiary amine (DMAE, MDEA, DEAE) and 5 wt% of a primary/secondary amine (MAPA, AEEA). The experimental temperature was set to 313.15 K and the measured CO2 loading was in the range of 0.274–4.563 (mol CO2 per kg of solution). In order to make a better comparison, viscosities and densities of the amine solutions were also measured at 303.15–353.15 K. Experiments show that the aqueous DMAE + MAPA blend has the highest absorption capacity, and at the same time, its viscosity and density are in a desirable range. [ABSTRACT FROM AUTHOR]

In the present study, compressive strength results of geopolymers produced by ordinary Portland cement (OPC) as aluminosilicate source have been modeled by artificial neural networks. Six main factors including NaOH concentration, water glass to NaOH weight ratio, alkali activator to cement weight ratio, oven curing temperature, oven curing time and water curing regime each at 4 levels were considered for designing. A total of 32 experiments were conducted according to the L32 array proposed by the method. The neural network models were constructed by 10 input parameters including NaOH concentration, water glass to NaOH weight ratio, alkali activator to cement weight ratio, oven curing temperature, oven curing time, water curing regime, water glass content, NaOH content, Portland cement content and test trial number. The value for the output layer was the compressive strength. According to the input parameters in feed-forward back-propagation algorithm, the constructed networks were trained, validated and tested. The results indicate that artificial neural networks model is a powerful tool for predicting the compressive strength of the geopolymers in the considered range. [ABSTRACT FROM AUTHOR]

In the recent years, temperature and pH-sensitive hydrogels were developed as suitable carriers for drug delivery. In this study, four different pH-sensitive nanohydrogels were designed for an oral insulin delivery modeling. NIPAAm-MAA-HEM copolymers were synthesized by radical chain reaction with 80:8:12 ratios respectively. Reactions were carried out in four conditions including 1,4-dioxan and water as two distinct solution under nitrogen gas-flow. The copolymers were characterized with FT-IR, SEM and TEM. Copolymers were loaded with regular insulin by modified double emulsion method with ratio of 1:10. Release study carried out in pH 1.2 and pH 6.8 at 37 °C. For pH 6.8 and pH 1.2, 2 mg of the insulin loaded nanohydrogels was float in a beaker containing 100 mL of PBS with pH 6.8 and 100 mL of HCl solution with pH 1.2, respectively. Sample collection was done in different times and HPLC was used for analysis of samples using water/acetonitrile (65/35) as the mobile phase. Nanohydrogels synthesis reaction yield was 95 %, HPLC results showed that loading in 1,4-dioxan without cross-linker nanohydrogels was more than others, also indicated that the insulin release of 1,4-dioxan without cross-linker nanohydrogels at acidic pH is less, but in pH 6.8 is the most. Results showed that by opting suitable polymerization method and selecting the best nanohydrogels, we could obtain a suitable insulin loaded nanohydrogels for oral administration. [ABSTRACT FROM AUTHOR]

The Editor-in-Chief has retracted this article [1] because it significantly overlaps with a number of articles including those that were under consideration at the same time [2, 3] and previously published articles [4-6]. Additionally, the article shows evidence of peer review manipulation. The authors have not responded to any correspondence regarding this retraction. [ABSTRACT FROM AUTHOR]