Tumor dormancy, a clinically undetectable state of cancer, makes a major contribution to the development of multidrug resistance (MDR), minimum residual disease (MRD), tumor outgrowth, cancer ...relapse, and metastasis. Despite its high incidence, the whole picture of dormancy-regulated molecular programs is far from clear. That is, it is unknown when and which dormant cells will resume proliferation causing late relapse, and which will remain asymptomatic and harmless to their hosts. Thus, identification of dormancy-related culprits and understanding their roles can help predict cancer prognosis and may increase the probability of timely therapeutic intervention for the desired outcome. Here, we provide a comprehensive review of the dormancy-dictated molecular mechanisms, including angiogenic switch, immune escape, cancer stem cells, extracellular matrix (ECM) remodeling, metabolic reprogramming, miRNAs, epigenetic modifications, and stress-induced p38 signaling pathways. Further, we analyze the possibility of leveraging these dormancy-related molecular cues to outmaneuver cancer and discuss the implications of such approaches in cancer treatment.
Electricity generation in Islanded Urban Microgrids (IUMG) now relies heavily on a diverse range of Renewable Energy Sources (RES). However, the dependable utilization of these sources hinges upon ...efficient Electrical Energy Storage Systems (EESs). As the intermittent nature of RES output and the low inertia of IUMGs often lead to significant frequency fluctuations, the role of EESs becomes pivotal. While these storage systems effectively mitigate frequency deviations, their high costs and elevated power density requirements necessitate alternative strategies to balance power supply and demand. In recent years, substantial attention has turned towards harnessing Electric Vehicle (EV) batteries as Mobile EV Energy Storage (MEVES) units to counteract frequency variations in IUMGs. Integrating MEVES into the IUMG infrastructure introduces complexity and demands a robust control mechanism for optimal operation. Therefore, this paper introduces a robust, high-order degree of freedom cascade controller known as the 1PD-3DOF-PID (1 + Proportional + Derivative—Three Degrees Of Freedom Proportional-Integral-Derivative) controller for Load Frequency Control (LFC) in IUMGs integrated with MEVES. The controller’s parameters are meticulously optimized using the Coati Optimization Algorithm (COA) which mimics coati behavior in nature, marking its debut in LFC of IUMG applications. Comparative evaluations against classical controllers and algorithms, such as 3DOF-PID, PID, Reptile Search Algorithm, and White Shark Optimizer, are conducted under diverse IUMG operating scenarios. The testbed comprises various renewable energy sources, including wind turbines, photovoltaics, Diesel Engine Generators (DEGs), Fuel Cells (FCs), and both Mobile and Fixed energy storage units. Managing power balance in this entirely renewable environment presents a formidable challenge, prompting an examination of the influence of MEVES, DEG, and FC as controllable units to mitigate active power imbalances. Metaheuristic algorithms in MATLAB-SIMULINK platforms are employed to identify the controller’s gains across all case studies, ensuring the maintenance of IUMG system frequency within predefined limits. Simulation results convincingly establish the superiority of the proposed controller over other counterparts. Furthermore, the controller’s robustness is rigorously tested under ± 25% variations in specific IUMG parameters, affirming its resilience. Statistical analyses reinforce the robust performance of the COA-based 1PD-3DOF-PID control method. This work highlights the potential of the COA Technique-optimized 1PD-3DOF-PID controller for IUMG control, marking its debut application in the LFC domain for IUMGs. This comprehensive study contributes valuable insights into enhancing the reliability and stability of Islanded Urban Microgrids while integrating Mobile EV Energy Storage, marking a significant advancement in the field of Load-Frequency Control.
Neurological disorders (NDs) comprise a heterogeneous group of conditions that affect the function of the nervous system. Often incurable, NDs have profound and detrimental consequences on the ...affected individuals’ lives. NDs have complex etiologies but commonly feature altered gene expression and dysfunctions of the essential chromatin-modifying factors. Hence, compounds that target DNA and histone modification pathways, the so-called epidrugs, constitute promising tools to treat NDs. Yet, targeting the entire epigenome might reveal insufficient to modify a chosen gene expression or even unnecessary and detrimental to the patients’ health. New technologies hold a promise to expand the clinical toolkit in the fight against NDs. (Epi)genome engineering using designer nucleases, including CRISPR-Cas9 and TALENs, can potentially help restore the correct gene expression patterns by targeting a defined gene or pathway, both genetically and epigenetically, with minimal off-target activity. Here, we review the implication of epigenetic machinery in NDs. We outline syndromes caused by mutations in chromatin-modifying enzymes and discuss the functional consequences of mutations in regulatory DNA in NDs. We review the approaches that allow modifying the (epi)genome, including tools based on TALENs and CRISPR-Cas9 technologies, and we highlight how these new strategies could potentially change clinical practices in the treatment of NDs.
Flexibility in the exchange of genetic material takes place between different organisms of the same or different species. This phenomenon is known to play a key role in the genetic, physiological, ...and ecological performance of the host. Exchange of genetic materials can cause both beneficial and/or adverse biological consequences. Horizontal gene transfer (HGT) or lateral gene transfer (LGT) as a general mechanism leads to biodiversity and biological innovations in nature. HGT mediators are one of the genetic engineering tools used for selective introduction of desired changes in the genome for gene/cell therapy purposes. HGT, however, is crucial in development, emergence, and recurrence of various human-related diseases, such as cancer, genetic-, metabolic-, and neurodegenerative disorders and can negatively affect the therapeutic outcome by promoting resistant forms or disrupting the performance of genome editing toolkits. Because of the importance of HGT and its vital physio- and pathological roles, here the variety of HGT mechanisms are reviewed, ranging from extracellular vesicles (EVs) and nanotubes in prokaryotes to cell-free DNA and apoptotic bodies in eukaryotes. Next, we argue that HGT plays a role both in the development of useful features and in pathological states associated with emerging and recurrent forms of the disease. A better understanding of the different HGT mediators and their genome-altering effects/potentials may pave the way for the development of more effective therapeutic and diagnostic regimes.
Induction of thrombosis in tumor vasculature represents an appealing strategy for combating cancer. Herein, we combined unique intrinsic coagulation properties of staphylocoagulase with new acquired ...functional potentials introduced by genetic engineering, to generate a novel bi-functional fusion protein consisting of truncated coagulase (tCoa) bearing an RGD motif on its C-terminus for cancer therapy. We demonstrated that free coagulase failed to elicit any significant thrombotic activity. Conversely, RGD delivery of coagulase retained coagulase activity and afforded favorable interaction of fusion proteins with prothrombin and α
β
endothelial cell receptors, as verified by in silico, in vitro, and in vivo experiments. Although free coagulase elicited robust coagulase activity in vitro, only targeted coagulase (tCoa-RGD) was capable of producing extensive thrombosis, and subsequent infarction and massive necrosis of CT26 mouse colon, 4T1 mouse mammary and SKOV3 human ovarian tumors in mice. Additionally, systemic injections of lower doses of tCoa-RGD produced striking tumor growth inhibition of CT26, 4T1 and SKOV3 solid tumors in animals. Altogether, the nontoxic nature, unique shortcut mechanism, minimal effective dose, wide therapeutic window, efficient induction of thrombosis, local effects and susceptibility of human blood to coagulase suggest tCoa-RGD fusion proteins as a novel and promising anticancer therapy for human trials.
Colorectal cancer (CRC) is one of the most disseminated diseases across the globe engaging the digestive system. Various therapeutic methods from traditional to the state-of-the-art ones have been ...applied in CRC patients, however, the attempts have been unfortunate to lead to a definite cure. MiRNAs are a smart group of non-coding RNAs having the capabilities of regulating and controlling coding genes. By utilizing this stock-in-trade biomolecules, not only disease's symptoms can be eliminated, there may also be a good chance for the complete cure of the disease in the near future. Herein, we provide a comprehensive review delineating the therapeutic relationship between miRNAs and CRC. To this, various clinical aspects of miRNAs which act as a tumor suppressor and/or an oncogene, their underlying cellular processes and clinical outcomes, and, in particular, their effects and expression level changes in patients treated with chemo- and radiotherapy are discussed. Finally, based on the results deducted from scientific research studies, therapeutic opportunities based on targeting/utilizing miRNAs in the preclinical as well as clinical settings are highlighted.
ABSTRACT Background and objective: Considering the toxic side effects of chemotherapy in treatment of cancer, anticancer drugs of natural origin including probiotic Lactobacillus strains ...have recently attracted a lot of attention. Methods: After culturing chronic myeloid leukemia cell line K562 in 96-well plates, effects of different concentrations of culture supernatant from Lactobacillus casei on differentiation of the cells were investigated after 48 and 72 hours under an inverted microscope. Number of live cells and percentage of viable cells were determined by trypan blue exclusion test of cell viability. Cytotoxicity was assessed by MTT assay. Data analysis was performed by SPSS (version) 22 using one-way analysis of variance and Tukeychr('39')s test at significance level of 0.05. Results: Secondary metabolites from the probiotic bacteria L. casei induced cellular differentiation, exerted anti-cancer effects and inhibited growth in K562 cells. Apoptotic cell death was confirmed by MTT and DNA fragmentation assays in a way that increasing the dilution from 1.2 to 1.32 significantly increased the viability of cells (P=0.001). In addition, increasing the dilution significantly increased the number of live cells in the first 48 hours (P=0.001). Conclusion: Culture supernatant of L. casei reduces the number of live cells, and induces apoptosis and monocytic differentiation in K562 cells in a dose- and time-dependent manner. Therefore, combined chemotherapy and differentiation therapy using such supernatants could be useful for treatment of cancer. Keywords: Cell differentiation, K562 cell line, Probiotic, Lactobacillus casei.
This paper presents a stochastic Mixed-Integer Linear Programming (MILP) model developed to address the collaborative expansion planning of modern multi-energy distribution networks, taking into ...account the integration of Electric Vehicle Charging Stations (EVCSs) in the presence of uncertainties. The model is comprehensively formulated to encompass Distributed Generation (DG) resources, Electric Vehicles (EVs), and Capacitor Banks (CBs), alongside traditional expansion options like substations and circuit construction/reinforcement. The essence of this Distribution System Expansion Planning (DSEP) problem formulation lies in its stochastic approach, featuring chance constraints to effectively manage and address uncertainties. The central objective of the model is to minimize the total investment and operational expenditures associated with the DSEP problem over a designated planning horizon. The rigorous application of optimization techniques ensures the convergence of the MILP model, thereby delivering an efficient and reliable solution. The model's effectiveness is initially assessed using an 18-bus system, followed by comprehensive testing on a larger 123- bus system to gauge its robustness. Thorough performance evaluations are conducted across various case studies, encompassing both the 18- bus and 123- bus systems, culminating in the validation of the model's resilience, scalability, and replicability. These case studies encompass deterministic and stochastic methodologies across six distinct scenarios. The numerical outcomes conclusively demonstrate that the DSEP solution, when utilizing the stochastic approach without considering EVCSs, is associated with elevated costs. However, with a strategic allocation strategy for EVCSs, noteworthy reductions in investment expenditures related to substations, lines, and overall costs are notably achieved. The incorporation of uncertainty management within the DSEP problem underscores the flexibility and adaptability intrinsic to the proposed stochastic MILP model. These attributes render it ideally suited to effectively orchestrating the expansion of multi-energy distribution networks in the presence of EVCSs, thereby enhancing its utility and relevance in addressing modern energy distribution challenges.
•Optimal multi-energy network planning with EV charging stations.•Stochastic MILP model for efficient expansion planning.•Integration of capacitors and DG resources.•Addressing uncertainties in distribution systems.•Cost-effective and flexible energy infrastructure.
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