Exploration of the photothermal role of curcumin-loaded targeted carbon nanotubes as a potential therapy for melanoma cancer.

In this research, the hydrophilic structure of multi-walled carbon nanotubes (MWCNTs) was modified by synthesizing polycitric acid (PCA) and attaching folic acid (FA) to create MWCNT-PCA-FA. This modified nanocomplex was utilized as a carrier for the lipophilic compound curcumin (Cur). Characterization techniques including TGA, TEM, and UV-visible spectrophotometry were used to analyze the nanocomplex. The mechanism of cancer cell death induced by MWCNT-PCA-FA was studied extensively using the MTT assay, colony formation analysis, cell cycle assessment via flow cytometry, and apoptosis studies. Furthermore, we assessed the antitumor efficacy of these targeted nanocomplexes following exposure to laser radiation. The results showed that the nanocomposites and free Cur had significant toxicity on melanoma cancer cells (B16F10 cells) while having minimal impact on normal cells (NHDF cells). This selectivity for cancerous cells demonstrates the potential of these compounds as therapeutic agents. Furthermore, MWCNT-PCA-FA/Cur showed superior cytotoxicity compared to free Cur alone. Colony formation studies confirmed these results. The researchers found that MWCNT-FA-PCA/Cur effectively induced programmed cell death. In photothermal analysis, MWCNT-PCA-FA/Cur combined with laser treatment achieved the highest mortality rate. These promising results suggest that this multifunctional therapeutic nanoplatform holds the potential for combination cancer therapies that utilize various established therapeutic methods.

Resource-constrained time-cost-quality-energy-environment tradeoff problem by considering blockchain technology, risk and robustness: a case study of healthcare project.

Blockchain Technology (BCT) is expanding day by day and is used in all pillars of life and projects. In this research, we survey applicable BCT in project management for the first time. We presented a Resource-Constrained Time-Cost-Quality-Energy-Environment Tradeoff Problem by considering BCT, Risk and Robustness (RCTCQEETPBCTRR) in project scheduling. We utilize hybrid robust stochastic programming, worst case, and Conditional Value at Risk (CVaR) to cope with uncertainty and risks. This type of robustification and risk-averse is presented in this research. A real case study is presented in a healthcare project. We utilize GAMS-CPLEX to solve the model. Finally, we analyze finish time, conservative coefficient, the confidence level of CVaR, and the number of scenarios. The most important research result is that applying BCT decreases cost, energy, and pollution and increases quality. Moreover, the total gap between RCTCQEETPBCTRR and without BCT is approximately 2.6%. When compacting finish time happens or if the conservative coefficient increases to 100%, costs, energy, and pollution environment increase, but quality decreases. If the confidence level of CVaR increases, the cost, energy, and environment function functions grow up, and quality is approximately not changed.

Viable medical waste chain network design by considering risk and robustness.

Medical waste management (MWM) is an important and necessary problem in the COVID-19 situation for treatment staff. When the number of infectious patients grows up, the amount of MWMs increases day by day. We present medical waste chain network design (MWCND) that contains health center (HC), waste segregation (WS), waste purchase contractor (WPC), and landfill. We propose to locate WS to decrease waste and recover them and send them to the WPC. Recovering medical waste like metal and plastic can help the environment and return to the production cycle. Therefore, we proposed a novel viable MWCND by a novel two-stage robust stochastic programming that considers resiliency (flexibility and network complexity) and sustainable (energy and environment) requirements. Therefore, we try to consider risks by conditional value at risk (CVaR) and improve robustness and agility to demand fluctuation and network. We utilize and solve it by GAMS CPLEX solver. The results show that by increasing the conservative coefficient, the confidence level of CVaR and waste recovery coefficient increases cost function and population risk. Moreover, increasing demand and scale of the problem makes to increase the cost function.

Mapping the intellectual structure of the coronavirus field (2000-2020): a co-word analysis.

Over the two last decades, coronaviruses have affected human life in different ways, especially in terms of health and economy. Due to the profound effects of novel coronaviruses, growing tides of research are emerging in various research fields. This paper employs a co-word analysis approach to map the intellectual structure of the coronavirus literature for a better understanding of how coronavirus research and the disease itself have developed during the target timeframe. A strategic diagram has been drawn to depict the coronavirus domain's structure and development. A detailed picture of coronavirus literature has been extracted from a huge number of papers to provide a quick overview of the coronavirus literature. The main themes of past coronavirus-related publications are (a) "Antibody-Virus Interactions," (b) "Emerging Infectious Diseases," (c) "Protein Structure-based Drug Design and Antiviral Drug Discovery," (d) "Coronavirus Detection Methods," (e) "Viral Pathogenesis and Immunity," and (f) "Animal Coronaviruses." The emerging infectious diseases are mostly related to fatal diseases (such as Middle East respiratory syndrome, severe acute respiratory syndrome, and COVID-19) and animal coronaviruses (including porcine, turkey, feline, canine, equine, and bovine coronaviruses and infectious bronchitis virus), which are capable of placing animal-dependent industries such as the swine and poultry industries under strong economic pressure. Although considerable research into coronavirus has been done, this unique field has not yet matured sufficiently. Therefore, "Antibody-virus Interactions," "Emerging Infectious Diseases," and "Coronavirus Detection Methods" hold interesting, promising research gaps to be both explored and filled in the future.