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Background Public Health Dashboards (PHDs) facilitate the monitoring and prediction of disease outbreaks by continuously monitoring the health status of the community. This study aimed to identify design principles and determinants for developing public health surveillance dashboards. Methodology This scoping review is based on Arksey and O'Malley's framework as included in JBI guidance. Four databases were used to review and present the proposed principles of designing PHDs: IEEE, PubMed, Web of Science, and Scopus. We considered articles published between January 1, 2010 and November 30, 2022. The final search of articles was done on November 30, 2022. Only articles in the English language were included. Qualitative synthesis and trend analysis were conducted. Results Findings from sixty-seven articles out of 543 retrieved articles, which were eligible for analysis, indicate that most of the dashboards designed from 2020 onwards were at the national level for managing and monitoring COVID-19. Design principles for the public health dashboard were presented in five groups, i.e., considering aim and target users, appropriate content, interface, data analysis and presentation types, and infrastructure. Conclusion Effective and efficient use of dashboards in public health surveillance requires implementing design principles to improve the functionality of these systems in monitoring and decision-making. Considering user requirements, developing a robust infrastructure for improving data accessibility, developing, and applying Key Performance Indicators (KPIs) for data processing and reporting purposes, and designing interactive and intuitive interfaces are key for successful design and development.

Neurologic complications are commonly regarded as irreversible impairments that stem from limited potential of regeneration of the central nervous system (CNS). On the other side, the regenerative potential of stem cells has been evaluated in basic research, as well as in preclinical studies. Mesenchymal stem cells (MSCs) have been regarded as candidate cell sources for therapeutic purposes of various neurological disorders, because of their self-renewal ability, plasticity in differentiation, neurotrophic characteristics, and immunomodulatory properties. Exosomes are extracellular vesicles which can deliver biological information over long distances and thereby influencing normal and abnormal processes in cells and tissues. The therapeutic capacity of exosomes relies on the type of cell, as well as on the physiological condition of a given cell. Therefore, based on tissue type and physiological condition of CNS, exosomes may function as contributors or suppressors of pathological conditions in this tissue. When it comes to the therapeutic viewpoint, the most promising cellular source of exosomes is considered to be MSCs. The aim of this review article is to discuss the current knowledge around the potential of stem cells and MSC-derived exosomes in the treatment of neurodegenerative diseases.

Extracts with antimicrobial and antioxidant properties are limited in their application in food products due to their inability to withstand harsh environmental conditions, such as high temperatures and oxygen exposure. Therefore, the present study investigated the nanoencapsulation of Teucrium polium L. extract using the freeze‐drying method to facilitate its application and protection against environmental factors. In this regard, an emulsion containing Teucrium polium L. extract at concentrations of 10%, 20%, and 30% and a mixture of maltodextrin/Persian gum in three ratios of 1:2, 1:1, and 2:1 as the coating wall were produced and then dried in a freeze dryer. In the following, the properties of emulsions and produced nanocapsules were studied. According to the results, emulsions with high amounts of Persian gum showed more stability, zeta potential, and viscosity. However, their particle size and polydisparity index were lower than those of other emulsions. As the extract concentration increased, there was a decrease in stability, zeta potential, and viscosity, accompanied by an increase in particle size and polydispersity index. Concurrently, elevated concentrations of maltodextrin, Persian gum, and extract resulted in higher humidity, density, encapsulation efficiency, and antioxidant activity of the capsules. The most optimal properties of emulsions and nanocapsules were achieved at the 10% concentration of Teucrium polium L. extract and the 1:1 ratio of maltodextrin/Persian gum mixture as the wall material. It is noteworthy that the release rate of phenolic compounds reached its maximum value (88%) after 60 days. An emulsion containing Teucrium polium L. extract at concentrations of 10, 20, and 30%, and a mixture of maltodextrin/Persian gum (1:2, 1:1, and 2:1) as the coating wall were produced and dried in a freeze dryer. The optimal properties of emulsions and nanocapsules were achieved at the 10% concentration of extract and the 1:1 ratio of maltodextrin/Persian gum as the wall material. The release rate of phenolic compounds reached its maximum value (88%) after 60 days.

Despite advances in the treatment of acute myocardial infarction, due to the non-proliferative nature of adult cardiomyocytes, the injured myocardium is mainly replaced by fibrotic tissue, which ultimately causes heart failure. To prevent heart failure, particularly after myocardial infarction, exosome-based therapy has emerged as one of the most promising strategies to regenerate cardiac function. Exosomes can carry microRNAs in support of neovascularization, anti-inflammatory, and endogenous cardiac regeneration. This study demonstrated that animal rat models’ combination treatment with microRNA-126 and microRNA-146a mimics in exosomes is desirable for cardiac regeneration after myocardial infarction. The exosomes isolated from stem cells and loaded with microRNAs were characterized their impacts in cell migration, tube formation, and vascular endothelial growth factor degree. In the following, the usefulness of loaded microRNAs in exosomes and their encapsulation within alginate derivative hydrogel was analyzed in myocardial infarction for an animal model. Exosomes isolated and loaded with microRNAs showed the synergetic impact on cell migration, tube formation, and promoted vascular endothelial growth factor folding. Moreover, microRNAs loaded exosomes and encapsulated them in alginate hydrogel could help in reducing infarct size and improving angiogenesis in myocardial infarction. The angiogenesis markers including CD31 and connexion 43 upregulated for myocardial infarction models treated with alginate-based hydrogels loaded with exosomes and microRNAs-exosomes. Histological analysis indicated that myocardial infarction model rats treated with alginate hydrogel loaded with microRNAs-exosomes possessed lower and higher degrees of fibrosis and collagen fiber, respectively. These findings have important therapeutic implications for a myocardial infarction model through angiogenesis and vascular integrity regulation.

Background There has been an increasing resistance rate to tetracyclines, the first line treatment for cholera disease caused by V. cholera strains, worldwide. The aim of the present study was to determine the global status of resistance to this class of antibiotic among V. cholera isolates. Methods For the study, electronic databases were searched using the appropriate keywords including: ‘ Vibrio ’, ‘ cholera ’, ‘ Vibrio cholerae ’, ‘ V. cholerae ’, ‘resistance’, ‘antibiotic resistance’, ‘antibiotic susceptibility’, ‘antimicrobial resistance’, ‘antimicrobial susceptibility’, ‘tetracycline’, and ‘doxycycline’. Finally, after some exclusion, 52 studies from different countries were selected and included in the study and meta-analysis was performed on the collected data. Results The average resistance rate for serogroup O1 to tetracycline and doxycycline was 50% and 28%, respectively (95% CI). A high level of heterogeneity ( I 2  > 50%, p -value < 0.05) was observed in the studies representing resistance to tetracycline and doxycycline in O1 and non-O1, non-O139 serogroups. The Begg’s tests did not indicate the publication bias ( p -value > 0.05). However, the Egger’s tests showed some evidence of publication bias in the studies conducted on serogroup O1. Conclusions The results of the present study show that the overall resistance to tetracyclines is relatively high and prevalent among V. cholerae isolates, throughout the world. This highlights the necessity of performing standard antimicrobial susceptibility testing prior to treatment choice along with monitoring and management of antibiotic resistance patterns of V. cholerae strains in order to reduce the emergence and propagation of antibiotic resistant strains as well as the failure of treatment.

Energy consumption modeling in buildings is crucial for calculating energy performance indices and establishing criteria for energy labeling. Different countries utilize diverse approaches to calculate these indices based on energy efficiency regulations and classifications. In recent years, Iran has established energy compliance standards, outlined in Article 19 of the National Building Regulations, to improve the energy efficiency of buildings. This study aims to develop a systematic methodology for assessing energy consumption indicators in residential buildings using the criteria specified in the Iranian National Building Regulations. Our research examines three specific energy standard categories in residential buildings to evaluate the suitability of the energy compliance specifications and identify the distribution of energy indices, rather than relying solely on the fixed values prescribed in the regulations. Initially, three model building shapes were analyzed to demonstrate how different building envelope designs affect energy performance. This study fills a critical research gap by estimating energy consumption indices through a novel methodology that combines regression analysis and Monte Carlo simulation for the three energy classifications specified in Article 19 of the Iranian National Building Regulations. The study employs a permutation approach to evaluate the primary energy consumption indicators and the uncertainties arising from various adjacency configurations. Extensive simulations were conducted, resulting in the development of regression equations that account for the surface area of the building envelope adjacent to the outdoor environment. The Monte Carlo method was used to assess potential fluctuations in the adiabatic area of the building envelope and the area adjacent to the external environment for buildings with varying orientations, allowing for the generation of probability distributions for energy consumption intensities. The sensitivity analysis identified the critical components of the building envelope and their orientation that significantly impact the uncertainty of energy efficiency. The findings revealed that the west and east walls of buildings adjacent to the outdoor environment substantially influence the uncertainty of energy consumption. In contrast, the floor surface and south wall had the least significant effect on annual energy uncertainty. This innovative approach represents a significant advancement in the field. It plays a specific role in energy labeling for buildings by calculating the required standard deviation in energy consumption indices resulting from various envelope adjacencies. This research also has practical implications for building design and energy efficiency measurement.

This article studied the load frequency control (LFC) of a multi-source microgrid with the presence of renewable energy sources. To maintain a sustainable power supply, the frequency of the system must be kept constant. A Proportional–Integral–Derivative (PID) controller is presented as a secondary controller to control the frequency of the microgrid in island mode, and the integral of squared time multiplied by error squared (ISTES) is used as a performance index. The use of the Craziness-Based Particle Swarm Optimization (CRPSO), which is an improved version of Particle Swarm Optimization (PSO), improves the convergence speed in optimizing the nonlinear problem of load and frequency controller design. The test microgrid is composed of the load and distributed generation units such as diesel generators, photovoltaics and wind turbines. The proposed controller provided the desired response to adjusting the microgrid frequency, achieving the final response after a short time and making it more stable and less oscillatory compared with the conventional system.

There are conflicting results regarding the relationship between overweight/obesity and the outcomes of coronary artery bypass graft surgery (CABG), termed \"the obesity paradox\". This study aimed to evaluate the effects of body mass index (BMI) on the midterm outcomes of CABG. This historical cohort study included all patients who underwent isolated CABG at our center between 2007 and 2016. The patients were divided into five categories based on their preoperative BMIs (kg/m.sup.2 ): 18.5[less than or equal to]BMI<25, 25[less than or equal to]BMI<30, 30[less than or equal to]BMI<35, 35[less than or equal to]BMI<40, and BMI[greater than or equal to]40. Patients with BMIs below 18.5 kg/m.sup.2 were excluded. The endpoints of this study were all-cause mortality and major adverse cardio-cerebrovascular events (MACCEs), comprising acute coronary syndromes, cerebrovascular accidents, and all-cause mortality at five years. For the assessment of the linearity of the relationship between continuous BMI and the outcomes, plots for time varying hazard ratio of BMI with outcomes were provided. Of 17 751 patients (BMI = 27.30 ±4.17 kg/m.sup.2) who underwent isolated CABG at our center, 17 602 patients (mean age = 61.16±9.47 y, 75.4% male) were included in this study. Multivariable analysis demonstrated that patients with pre-obesity and normal weight had similar outcomes, whereas patients with preoperative BMIs exceeding 30 kg/m.sup.2 kg/m.sup.2 had a significantly higher risk of 5-year all-cause mortality and 5-year MACCEs than those with pre-obesity. Additionally, a positive association existed between obesity degree and all-cause mortality and MACCEs. Further, BMIs of 40 kg/m.sup.2 or higher showed a trend toward higher MACCE risks (adjusted hazard ratio, 1.32; 95% confidence interval, 0.89 to 1.95), possibly due to the small sample size. A nonlinear, albeit negligible, association was also found between continuous BMI and the study endpoints. Our findings suggest that preoperative obesity (BMI>30 kg/m.sup.2) in patients who survive early after CABG is associated with an increased risk of 5-year all-cause mortality and 5-year MACCEs. These findings indicate that physicians and cardiac surgeons should encourage patients with high BMIs to reduce weight for risk modification.

The fast pace of urban development and increasing intensity of precipitation events have made managing urban stormwater an increasingly difficult challenge. Hydrologic models are commonly used to predict flows and assess the performance of stormwater controls, often based on a hypothetical yet standardized design storm. The Storm Water Management Model (SWMM) is widely used for simulating runoff in urban watersheds. However, calibration of SWMM, as with all hydrologic models, is often plagued with issues such as subjectivity, and an abundance of model parameters, leading to delays and inefficiencies in model development and application. Further development of modeling and simulation tools to aid in design is critical in improving the function of stormwater management systems. To address these issues, we developed an integration of PySWMM (a Python wrapper (tool) for SWMM) and Pymoo (a Python package for multi-objective optimization) to automate the SWMM calibration process. The tool was tested using a case study urban watershed in Fredericksburg, VA. This tool can employ either a single-objective or multi-objective approach to calibrate a SWMM model by minimizing the error between prediction and observed values. This tool uses performance metrics including Nash-Sutcliffe Efficiency (NSE), Percent Bias (PBIAS), and Root Mean Square Error (RMSE) Standardized Ratio (RSR) for both single-event and long-term continuous rainfall-runoff processes. During multi-objective optimization calibration, the model achieved NSE, PBIAS, and RSR values of 0.73, 17.1, and 0.52, respectively; while the validation period recorded values of 0.86, 13.1, and 0.37, respectively. Additionally, in the single-objective optimization test case, the model yielded NSE values of 0.68 and 0.73 for the calibration and validation, respectively. The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. The tool successfully calibrated the SWMM model, delivering reliable results with suitable computational performance.

Chronic obstructive pulmonary disease (COPD) is a common condition that complicates major surgeries like coronary artery bypass grafting (CABG). This study aims to evaluate the impact of COPD on the outcome of CABG. A registry-based retrospective cohort study included individuals who received CABG between 2009 and 2016. Data were collected on patient demographics, intraoperative factors, and postoperative outcomes. Cox proportional hazard with inverse probability weighting (IPW) and propensity score matching (PSM) were conducted to assess the adjusted effect of COPD on 30-day and long-term mortality and major adverse cardiac and cerebrovascular events (MACCE). Moreover, the impact of COPD in smokers and non-smokers on short/long-term outcomes was assessed. Sensitivity analysis was conducted using multiple imputations. In the present investigation, 17,315 patients including 629 with COPD (mean age 69 ± 9.74), were followed up for a median duration of 8.25 years. Although COPD did not increase 30-day mortality and MACCE risk, the models showed that patients with COPD are at a significantly higher risk of long-term mortality and MACCE after CABG (IPW: HR for mortality: 1.53, 95% CI: 1.31–1.79; HR for MACCE: 1.29, 95% CI: 1.12–1.47). After multiple imputations, the mortality and MACCE hazard ratio in IPW analysis remained statistically significant. COPD significantly increases long-term mortality and MACCE following CABG, independent of smoking status.