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Background: One of the most critical practices in mass casualty incident management is vacating the victims from scene of the incident and transporting them to proper healthcare facilities. Decision on distribution of casualties needs to be taken on pre-developed policies and structured decision support mechanisms. While many studies tried to present models for the distribution of casualties, no systematic review has yet been conducted to evaluate the existing models on casualty distribution following mass casualty incidents. A systematic review is therefore needed to examine the existing models of patient distribution and to provide a summary of the models. This systematic review protocol is aimed to examine the existing models and extracting rules and principles of mass casualty distribution. Methods: This study will comprehensively investigate existing papers with search phrases and terms including "mass casualty incident", distribution, evacuation, and Mesh terms directly corresponding to search phrases. No limitations on the type of studies, date of publication, or language of the relevant documents will be imposed. PubMed, Web of Science, Scopus, and Google Scholar will be searched to access the relevant documents. Included papers will be critically appraised by two independent reviewers. The data including incidents type, scene characteristics, patient features, pre-hospital resources, and hospital resources will be categorized. Subgroup analysis will be conducted when possible. Discussion: To the best of our knowledge, no study has yet addressed the effects and interaction of contributing factors on the decision-making processes for casualty's distribution. This is the first study that comprehensively assesses and critically appraises the current models of casualty distribution. This study will provide evidences about models and criteria for casualty distribution following mass casualty incidents. Systematic review registration: PROSPERO Registration Number: CRD42016049115. [ABSTRACT FROM AUTHOR]

While the use of extensive green roofs (EGRs) is increasing worldwide, Mediterranean conditions complicate EGR design due to their long, dry summers with intense solar radiation. To inform sustainable EGR design for Mediterranean regions, we explored the use of resilient, drought-tolerant species in experimental EGRs. We selected four native species that are known to spontaneously establish themselves on urban structures, including roofs, in Lisbon, Portugal: Antirrhinum linkianum, Asphodelus fistulosus, Centranthus ruber , and Sedum sediforme. We evaluated growth and aesthetic value under two irrigation treatments (100 and 60% ETo, reference evapotranspiration). The presence of moss covering for the lower level of irrigation was also evaluated. Antirrhinum linkianum presented the highest number of flowers, most extended seed production duration, and the highest area coverage. Irrigation level did not significantly affect flowering and green coverage for any of the species. Antirrhinum linkianum is an ideal starting species for Lisbon EGRs. Irrigation costs can be reduced by starting at a 60%ETo irrigation level. • Native plants that grow spontaneously in urban areas can considered a suitable option in implementing green roofs. • Antirrhinum linkianum under 60% ETo produced flowers, seeds, and green coverage well. • There are no evident differences between irrigation levels 60% ETo and 100% ETo. [ABSTRACT FROM AUTHOR]

[Display omitted] • Novel copolymers were directly synthesized through a step-growth polymerization. • The synthesized nanopolymers displayed excellent antibacterial activity. • The prepared copolymer reduced the number of biofilm cells. • In vivo experiments using infected burn wounds in mice demonstrated good antibacterial activity. • This cationic polymer revealed anti-inflammatory effects in a mouse model. Infectious diseases caused by new or unknown bacteria and viruses, such as anthrax, cholera, tuberculosis and even COVID-19, are a major threat to humanity. Thus, the development of new synthetic compounds with efficient antimicrobial activity is a necessity. Herein, rationally designed novel multifunctional cationic alternating copolymers were directly synthesized through a step-growth polymerization reaction using a bivalent electrophilic cross-linker containing disulfide bonds and a diamine heterocyclic ring. To optimize the activity of these alternating copolymers, several different diamines and cross-linkers were explored to find the highest antibacterial effects. The synthesized nanopolymers not only displayed good to excellent antibacterial activity as judged by minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) against Staphylococcus aureus , Enterococcus faecalis , Pseudomonas aeruginosa , and Escherichia coli, but also reduced the number of biofilm cells even at low concentrations, without killing mammalian cells. Furthermore, in vivo experiments using infected burn wounds in mice demonstrated good antibacterial activity and stimulated wound healing, without causing systemic inflammation. These findings suggest that the multifunctional cationic nanopolymers have potential as a novel antibacterial agent for eradication of multidrug resistant bacterial infections. [ABSTRACT FROM AUTHOR]

This study aims to find an appropriate way to minimize water utility in the petrochemical and petroleum industries due to high rate of water consumption. For this purpose, Tehran oil refinery has been well studied. In this research, three key contaminants including suspended solid, hardness as well as COD have been considered to analyze the water network. In addition, the potential of water reuse was studied for all methods. These key contaminants once were analyzed separately as a single contaminant and the amount of required freshwater was calculated for them. In this stage, amount of freshwater was reduced to about 60.9 (17%), 203 (59.7%) and 143 m/h (42.5%) in terms of suspended solids, hardness, and COD, respectively. Water minimization within operations for suspended solids is less than two others. Therefore, this is a limiting contaminant and can be selected as a key contaminant. In the next stage, three contaminants were analyzed two by two based on their mass transfer. Results show that, in the targeting for minimization based on the suspended solids and hardness, the amount of required water is reduced to 142.74 m/h or 42%. This amount for suspended solids and COD is equal to 86.3 m/h (26%) and for COD and hardness is 124 m/h (37%). Analyzing the methods shows that the method based on the double contaminant gives more precise results rather than single contaminant. [ABSTRACT FROM AUTHOR]

Recent advances in miniaturized nano-based devices are rapidly extending the boundaries of biomedical technologies, particularly biosensors. Highly selective biosensors with the ability to simultaneously detect multiple targets were developed in recent years. The most eye-catching classifications of such biosensors coupled with the emergence of stimuli-responsive and CRISPR/Cas-sensitive systems. Furthermore, attractive features of wearable and implantable biosensors have led to the design of portable, remote controllable diagnostic systems for tackling healthcare challenges in every part of the world, especially in places with limited access to clinical resources. Nevertheless, there are still some barriers to widespread applications of biosensors due mainly to their high costs and the lack of a single biosensing device for highly selective targeting of multiple analytes. Herein, we review the latest developments in biomedical technologies with a focus on biosensors including smart stimuli-responsive, CRISPR/Cas-sensitive, wearable, and implantable biosensors to spark innovations in this field. In the current study, the advancing, innovative, and attractive field of biosensor technologies have been reviewed, along with the simultaneous and recent advances in miniaturized nano-based devices, development of smart stimuli-responsive, and CRISPR/Cas-sensitive diagnostic tools. Highly selective biosensors with the ability to simultaneously detect multiple targets extended from wearable and implantable biosensors to smart stimuli-responsive and CRISPR/Cas-sensitive biosensors, their advantages, disadvantages, barriers, and the latest developments have been discussed. [ABSTRACT FROM AUTHOR]

Karoon River as water supply provider of 16 cities, several villages, and thousands of hectares agricultural land is a very important river in Iran. The present research was conducted at the Mollasani hydrometer station in Karoon River using statistical data of a 49-year period. The aim of the present study is to evaluate the quality of the Karoon River using artificial neural network analysis of multilayer perceptron (MLP), radial basis function (RBF), and regression methods. The studied parameters included: TDS, pH, HCO3, Cl, SO4, Ca, Mg, Na, K, total anions and cations, sodium absorption ratio (SAR), total hardness (TH), and electrical conductivity (EC). The study results showed that the MLP neural network with a hidden layer and R2 = 0.903 gives a more accurate estimation of SAR compared to the RBF model and regression method. Based on these parameters, the water quality was classified as good. In general, with due regard to the precautions currently in place, the basis of the Kendall test, in recent years, despite decreasing the pH of water, the amount of salts in the water has increased, which indicates a decrease in river water quality. [ABSTRACT FROM AUTHOR]

This study is an attempt to identify seismic zones utilizing number-size (N-S) and concentration-area (C-A) fractal models in the West Yazd province, Central Iran. The analysis was based on the earthquakes’ magnitude and Quaternary faults’ density. Fault density map was generated and classified by fractal modeling. The result indicates that the main fault densities correlate with Dehshir and Eqlid faults. Furthermore, the areas with relatively large earthquake magnitudes are located in the SE and NE parts of the region. The Quaternary faults’ density and earthquake magnitudes were weighted based on the results of the fractal modeling. Finally, weighted maps were combined and classified to show that Dehshir fault has the main role for seismicity in this area. Comparison between results derived via the fractal modeling and conventional seismic zonation map is satisfactory. Furthermore, fractal modeling approach distinguishes different seismic zones with higher accuracy in smaller areas. For validation of results, earthquakes since 2012 were collected and associated with seismic zones. These earthquakes which are correlated with major seismic zones are mainly located near the Dehshir and main Zagros faults. [ABSTRACT FROM AUTHOR]

Given the increase in global energy consumption, the scarcity of fossil fuel resources, and the rise in environmental pollution have necessitated the use of novel technologies in energy production. Among these technologies, fuel cells have attracted researcher's attention due to their low environmental pollution, high efficiency, and ability to be combined with other power generation systems. The present research studies the performance of a hybrid solid oxide fuel cell-Stirling engine (SOFC-ST) system from a thermodynamic perspective. To this end, the fuel cell and the Stirling engine were modeled via coding in MATLAB software. The decision variables in this analysis were the current density, fuel utilization factor, fuel flow rate, number of fuel cells, air flow rate, and type of fuel used in the fuel cell. According to the results, when hydrogen is used as the fuel in the fuel cell, its power generation increases from 60 kW to 67 kW and its efficiency rises from 44.2 % to 49.4 % with the addition of the Stirling engine. However, if the fuel is methane, the power generated by the fuel cell increases from 19.9 kW to 26.6 kW, while its efficiency increases from 36.9 % to 49.2 %. [ABSTRACT FROM AUTHOR]

Stimulus-responsive delivery systems allow controlled, highly regulated, and efficient delivery of various cargos while minimizing side effects. Owing to the unique properties of nucleic acids, including the ability to adopt complex structures by base pairing, their easy synthesis, high specificity, shape memory, and configurability, they have been employed in autonomous molecular motors, logic circuits, reconfigurable nanoplatforms, and catalytic amplifiers. Moreover, the development of nucleic acid (NA)-responsive intelligent delivery vehicles is a rapidly growing field. These vehicles have attracted much attention in recent years due to their programmable, controllable, and reversible properties. In this work, we review several types of NA-responsive controlled delivery vehicles based on locks and keys, including DNA/RNA-responsive, aptamer-responsive, and CRISPR-responsive, and summarize their advantages and limitations., Competing Interests: Declaration of competing interest The authors have no conflict of interest., (Copyright © 2024. Published by Elsevier Inc.)

Candida parapsilosis is known to cause severe and persistent outbreaks in clinical settings. Patients infected with multidrug-resistant C. parapsilosis (MDR Cp) isolates were identified in a large Turkish hospital from 2017-2020. We subsequently identified three additional patients infected with MDR Cp isolates in 2022 from the same hospital and two echinocandin-resistant (ECR) isolates from a single patient in another hospital. The increasing number of MDR and ECR isolates contradicts the general principle that the severe fitness cost associated with these phenotypes could prevent their dominance in clinical settings. Here, we employed a multidimensional approach to systematically assess the fitness costs of MDR and ECR C. parapsilosis isolates. Whole-genome sequencing revealed a novel MDR genotype infecting two patients in 2022. Despite severe in vitro defects, the levels and tolerances of the biofilms of our ECR and MDR isolates were generally comparable to those of susceptible wild-type isolates. Surprisingly, the MDR and ECR isolates showed major alterations in their cell wall components, and some of the MDR isolates consistently displayed increased tolerance to the fungicidal activities of primary human neutrophils and were more immunoevasive during exposure to primary human macrophages. Our systemic infection mouse model showed that MDR and ECR C. parapsilosis isolates had comparable fungal burden in most organs relative to susceptible isolates. Overall, we observed a notable increase in the genotypic diversity and frequency of MDR isolates and identified MDR and ECR isolates potentially capable of causing persistent outbreaks in the future.

Personalized medicine is a new approach toward safer and even cheaper treatments with minimal side effects and toxicity. Planning a therapy based on individual properties causes an effective result in a patient's treatment, especially in a complex disease such as cancer. The benefits of personalized medicine include not only early diagnosis with high accuracy but also a more appropriate and effective therapeutic approach based on the unique clinical, genetic, and epigenetic features and biomarker profiles of a specific patient's disease. In order to achieve personalized cancer therapy, understanding cancer biology plays an important role. One of the crucial applications of personalized medicine that has gained consideration more recently due to its capability in developing disease therapy is related to the field of stem cells. We review various applications of pluripotent, somatic, and cancer stem cells in personalized medicine, including targeted cancer therapy, cancer modeling, diagnostics, and drug screening. CRISPR-Cas gene-editing technology is then discussed as a state-of-the-art biotechnological advance with substantial impacts on medical and therapeutic applications. As part of this section, the role of CRISPR-Cas genome editing in recent cancer studies is reviewed as a further example of personalized medicine application., Competing Interests: The authors declare no competing financial interest., (© 2023 American Chemical Society.)

Multi-drug resistant bacteria are a major problem in the treatment of infectious diseases, such as pneumonia, meningitis, or even coronavirus disease 2019 (COVID-19). Cationic nanopolymers are a new type of antimicrobial agent with high efficiency. We synthesized and characterized cationic polymer based on 1,4-diazabicyclo [2.2.2] octane (DABCO) and Bis (bromoacetyl)cystamine (BBAC), named poly (DABCO-BBAC) nanoparticles(NPs), and produced 150 nm diameter NPs. The antibacterial activity of poly (DABCO-BBAC) against eight multi drug resistant (MDR) Pseudomonas aeruginosa isolates from human burns, its possible synergistic effect with gentamicin, and the mechanism of action were examined. Poly(DABCO-BBAC) could effectively inhibit and kill bacterial strains at a very low concentration calculated by minimum inhibitory concentration (MIC) assay. Nevertheless, its synergism index with gentamicin showed an indifferent effect. Moreover, transmission electron microscopy and lipid peroxidation assays showed that poly (DABCO-BBAC) distorted and damaged the bacterial cell wall. These results suggest that the poly (DABCO-BBAC) could be an effective antibacterial agent for MDR clinical pathogens., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)