Islamic Azad University, Shahrood

• Comprehensive review of recent advancements in BMS integrating DTs, DL and BD. • Identification and classification of key sources of uncertainty across BMS modules and strategies for their management. • Critical analysis of DT and DL-based frameworks for reliability enhancement and informed decision-making. • Discussion of research gaps and opportunities for integrating advanced technologies into bridge maintenance and monitoring. • Emphasis on future directions toward intelligent, adaptive, and uncertainty-aware bridge management systems Bridge infrastructure, as a critical capital asset and an integral component of transportation networks, is increasingly affected by aging, deterioration, and external damage, potentially compromising its safety, performance, and functionality. These challenges, compounded by the growing demand for infrastructure expansion and limited funding resources, underscore the necessity of adopting efficient bridge management systems to prioritize maintenance and remediation strategies. To address these demands, different Bridge Management Systems (BMSs) have been developed to support operators in maintaining safe operations while optimizing budget allocation and maintenance strategies. Despite advancements in this field, most state-of-the-art research lacks a comprehensive overview of the role of Digital Twins (DTs), Deep learning (DL) and Big Data (BD) integration in enhancing BMS, particularly in managing uncertainties across BMS modules. Therefore, this paper provides a dedicated review of recent research in BMSs, with particular emphasis on the integration of DT and DL-enabled frameworks into bridge management practices and organizes key sources of uncertainty and discusses how emerging technologies can address these aspects in BMSs, which has yet to be comprehensively addressed. The review critically explores current methodologies, highlights challenges and identifies opportunities for uncertainty management in BMSs through the integration of advanced technologies and future trends for more reliable bridge management.

ABSTRACT Because of its special qualities, including its mechanical qualities, porosity, water absorption, moldability, biodegradability, and high biocompatibility, bacterial cellulose (BC) has emerged as a viable carrier for composite materials. The purpose of this study is to improve BC performance by the use of bioactive glass (BG) in a unique way. The Gram‐negative rod‐shaped bacterium Gluconobacter oxydans was used to generate the BC for this investigation, and it was identified using molecular techniques. Following that, two distinct synthesis methods were used for BC functionalization. The first method used the ex‐situ immersion technique to include the previously synthesized BG(Ag/TiO 2 ). In the second technique, a novel approach was used to make a reconstructed bacterial cellulose (RBC) using BG(Ag/TiO 2 ) by dissolving BC powder in urea and combining it with different concentrations of BG(Ag/TiO 2 ) in the BC solution to create RBC nanocomposite films. FTIR spectroscopy verified the synthesis of Ag/TiO 2 by analyzing the functional groups, and XRD and EDS results showed that BG(Ag/TiO 2 ) (6%) and BG(Ag/TiO 2 ) (4%) have sizes of 16 nm and 13 nm, respectively. TGA, FTIR, and FE‐SEM techniques were used to examine the physicochemical and microstructural characteristics of BC/BG(Ag/TiO 2 ) and RBC/BG(Ag/TiO 2 ) wound dressings. The antimicrobial qualities were assessed against both Gram‐positive and Gram‐negative bacteria using the swelling test, bioactivity test under lab settings, MTT toxicity analysis, and contact angle. Analysis results confirmed the presence of BG(Ag/TiO 2 ) on BC and the resulting BC/BG and RBC/BG exhibited suitable thermal resistance and surface absorption capability, possess antimicrobial properties, and are nontoxic.

ABSTRACT Introduction Conventional drug delivery for cancer therapy often suffer from poor targeting efficiency, limited bioavailability, and severe off-target toxicity. Nanoparticle-based approaches have emerged as transformative alternatives, particularly when integrated with microfluidic technologies. In the context of liver cancer, microfluidic-assisted polymeric nanocarriers provide a highly controllable and reproducible route for improving drug delivery outcomes. Areas covered We cover recent developments in polymeric nanoparticle systems; their integration with microfluidic fabrication platforms for liver cancer therapy; the ability to encapsulate therapeutic agents, achieve controlled release, and facilitate passive and active tumor targeting through physicochemical modulation and ligand functionalization; microfluidic-assisted synthesis, which enables fine-tuned control over particle size, surface chemistry, and payload distribution with minimal batch-to-batch variation; PEGylated PLGA, cyclodextrin-based, and stimuli-responsive polymeric nanocarriers, highlighting their potential in overcoming biological barriers and enhancing therapeutic index. Expert opinion Microfluidic-assisted nanoparticle fabrication represents a paradigm shift in the design and clinical translation of targeted therapies for liver cancer. By allowing real-time control over nanoparticle synthesis and enabling combination delivery strategies, this approach holds great promise for personalized and precision oncology. Continued integration of microfluidic engineering with biomaterial science and clinical insights is expected to accelerate the realization of safe, reproducible, and patient-tailored nanotherapeutics for hepatocellular carcinoma.

As renewable energy sources and energy storage systems (ESS) become more common, effective energy management is increasingly important. Grid operators are exploring systems like power-to-gas (P2G), which convert surplus electricity from renewables or batteries into gas that can be sold back to the gas grid. The integration of distributed gas production systems and P2G creates a complex relationship between electricity and gas networks, requiring a practical approach to energy management and profit optimization. This research focuses on optimizing integrated energy systems to identify the most efficient solutions. Effective demand-side management is essential for optimal power grid operation, as it can reduce peak loads and improve profits. This paper introduces a mixed integer non-linear programming (MINLP) model to jointly optimize electricity and gas networks, incorporating distributed generation, P2G systems, storage, electric vehicles (EVs), and demand-side management. To address computational challenges, the study uses the Meerkat Optimization Algorithm (MOA). The proposed model is tested on a 33-bus distribution network, showing its effectiveness in different scenarios. Key results include: 1) demand-side management reduces peak loads on the grid, 2) renewable energy and batteries help convert excess electricity into gas for market sale, and 3) distributed generation lowers energy purchases from the upstream grid, leading to a 32 % cost reduction.Index terms: Evolutionary algorithm, joined systems, P2G, gas grid, energy system.

Assessment of biomarkers through liquid biopsy, accompanied by low invasiveness, provides a more comprehensive analysis of the genetic profile of tumors, a deeper understanding of cancer mechanisms, the capacity for repeated testing over time, a short processing time, ease of obtaining, and economic benefits, making it easier to monitor diseases compared to tissue biopsy. Circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, non-coding RNAs, and metabolites provide precise and timely strategies for managing cancer patients. The main challenges are the low concentration of analytes isolated from liquid biopsies, the development of assays with both high sensitivity and specificity, and the lack of clear and comprehensive guidelines for assays, which further complicate the standardization process. Combined detection, including both CTCs and ctDNA assessment in circular bodies, provides valuable information at different stages of the tumor, despite the heterogeneity of tumor cells, for prognosis, dynamic monitoring, and mutation detection. In addition, the combination of biofluid biomarkers and artificial intelligence can enhance the accuracy and efficiency of liquid biopsy, improve real-time monitoring of tumor procedures and treatment responses, and provide precision medicine. This review examines the challenges in standardizing biofluid assays and explores potential solutions to achieve more consistent clinical outcomes.

The management of the global COVID-19 pandemic relies, in part, on the rapid development of preventive vaccines at an unparalleled speed. The infection caused by the coronavirus is facilitated by the spike glycoprotein trimmer located on the surface of the virion, specifically through its receptor binding domain (RBD). The response of antibodies to this domain is a key indicator of the immunization's effectiveness and is well correlated with the neutralization of the viral agent. The failure of COVID-19 vaccines to induce complete neutralization provides an opportunity to find an alternative way. In this study, we show that recombinant RBD, Wuhan-specific; fused to mPLD1 protein, a highly effective immunogen from Hemiscorpius lepturus scorpion's venom, induce a potent immune response in mouse model. Conventional virus neutralization test (cVNT) with serum of mice immunized with mPLD1-RBD fusion protein, protects the Vero cells against the Omicron and Wuhan variants at the minimum of 1/64 and 1/32 dilution, respectively. The data strongly suggests that the subunit recombinant fusion protein could be a promising candidate for vaccine development against COVID-19. Our research showed that fusion of mPLD1, a highly effective immunogen, with RBD significantly boosts the immune response and substantially amplifies RBD antigenic properties in lab animals, setting the stage for their assessment in a comprehensive preclinical study.

Microfluidics-based polymers are transforming drug delivery systems for liver cancer treatment as they enable precise synthesis of nano- and microparticles suitable for targeted therapy. The manufacture of programmable nanoparticles and tunable sizes is made possible by microfluidic platforms, which are essential for improving the effectiveness of medication administration. A wide range of therapeutic chemicals, including hydrophobic medications like doxorubicin, can be encapsulated in these systems to target liver cancers while reducing systemic toxicity effectively. It has also been demonstrated that combining natural hydrogels and droplet microfluidics can create multicellular tumor spheroids that resemble the tumor microenvironment more closely. This methodology improves screening and drug efficacy research and offers a strong foundation for assessing treatment outcomes. This research also explores novel uses of microfluidic technologies to develop intelligent drug delivery devices that respond to particular stimuli and release medication at the tumor site. It also investigated how artificial cell assemblies made with microfluidics can open new possibilities for individualized cancer treatment. To sum up, microfluidic-based polymers offer advanced tools for developing tailored and efficient drug delivery systems that can enhance patient outcomes, and represent a significant advancement in the treatment of liver cancer. The review paper discusses challenges in liver cancer treatment, including high drug clearance rates, low concentrations, and multidrug resistance. It suggests microfluidic technology can improve drug delivery systems by creating controlled particles and responding to tumor conditions. This could revolutionize liver cancer therapies, enabling better drug testing and treatment prediction, as well as designing tailored therapies.