Search Results (1,285)

Vehicular Ad Hoc Networks (VANETs) support safety-critical and traffic-optimization applications through low-latency, reliable V2X communication. However, securing integrity and auditability with blockchain is challenging because conventional BFT-style consensus incurs high message overhead and latency. We introduce CoCoChain, a concept-aware consensus mechanism tailored to VANETs. Instead of exchanging full payloads, CoCoChain trains a sparse autoencoder (SAE) offline on raw message payloads and encodes each message into a low-dimensional concept vector; only the top-k activations are broadcast during consensus. These compact semantic digests are integrated into a practical BFT workflow with per-phase semantic checks using a cosine-similarity threshold $\theta =0.85$ (calibrated on validation data to balance detection and false positives). We evaluate CoCoChain in OMNeT++/SUMO across urban, highway, and multi-hop broadcast under congestion scenarios, measuring latency, throughput, packet delivery ratio, and Age of Information (AoI), and including adversaries that inject semantically corrupted concepts as well as cross-layer stress (RF jamming and timing jitter). Results show CoCoChain reduces consensus message overhead by up to 25% and confirmation latency by 20% while maintaining integrity with up to 20% Byzantine participants and improving information freshness (AoI) under high channel load. This work focuses on OBU/RSU semantic-aware consensus (not 6G joint sensing or multi-base-station fusion). The code, configs, and an anonymized synthetic replica of the dataset will be released upon acceptance. Full article

RNA-based therapeutics offer transformative potential for treating devastating diseases. However, current RNA delivery technologies face significant hurdles, including inefficient tissue targeting, insufficient selectivity, and severe side effects, leading to the termination of many clinical trials. This review critically assesses the landscape of RNA-derived medicines, examining world-renowned mRNA vaccines (Spikevax, BNT162b2/Comirnaty) and RNA-based therapeutics like Miravirsen (anti-miR-122). It details the composition and clinical trial results of numerous modified short RNA drugs (e.g., siRNAs, miRNA mimetics/inhibitors) targeting various conditions. Prospects for RNA-based medicines are analysed for diseases with substantial societal impact, such as cancer, autoimmune disorders, and infectious diseases, with a focus on evolving delivery methods, including lipid nanoparticles, viral vectors, and exosomes. RNA-mediated macrophage reprogramming emerges as a promising strategy, potentially enhancing both delivery and clinical efficacy. This review highlights that while approved RNA therapies primarily target rare diseases due to delivery limitations, novel approaches in RNA modification, targeted delivery systems, and enhanced understanding of molecular mechanisms are crucial for expanding their application to prevalent diseases and unlocking their full therapeutic potential. Full article

Postal traffic and transport face challenges related to the rapid growth of parcel volumes, increasing demands for sustainability, and the need for integration into the smart transportation concept. This study explores the application of machine learning (ML) models for the classification of postal delivery times, with the aim of improving service efficiency and quality. As a case study, the Postal Center Zenica, one of the seven organizational units of the Public Enterprise “BH Pošta” in Bosnia and Herzegovina, was analyzed. The available dataset comprised 11,138 instances, which were cleaned and filtered, then expanded through two iterations of data augmentation using an autoencoder neural network. Five ML models, Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), k-Nearest Neighbors (kNN), and Multi-Layer Perceptron (MLP), were developed and compared, with hyperparameters optimized using the Bayesian method and evaluated through standard classification metrics. The results indicate that the data augmentation method significantly improves model performance, particularly in the classification of delayed shipments, with ensemble, especially Random Forest and XGBoost, emerging as the most robust solutions. Beyond contributions in the context of postal traffic and transport, the proposed methodological framework demonstrates interdisciplinary relevance, as it can also be applied in telecommunication traffic classes, where similar network dynamics require reliable predictive models. Full article

Accurate prediction of food delivery time is crucial for enhancing operational efficiency and customer satisfaction in real-world logistics and intelligent dispatch systems. To address this challenge, this study proposes a novel symmetric optimization prediction framework, termed SymOpt-CNSVR. The framework is designed to leverage the strengths of both deep learning and statistical learning models in a complementary architecture. It employs a Convolutional Neural Network (CNN) to extract and assess the importance of multi-feature data. An Enhanced Superb Fairy-Wren Optimization Algorithm (ESFOA) is utilized to optimize the diverse hyperparameters of the CNN, forming an optimal adaptive feature extraction structure. The significant features identified by the CNN are then fed into a Support Vector Regression (SVR) model, whose hyperparameters are optimized using Bayesian optimization, for final prediction. This combination reduces the overall parameter search time and incorporates probabilistic reasoning. Extensive experimental evaluations demonstrate the superior performance of the proposed SymOpt-CNSVR model. It achieves outstanding results with an R² of 0.9269, MAE of 3.0582, RMSE of 4.1947, and MSLE of 0.1114, outperforming a range of benchmark and state-of-the-art models. Specifically, the MAE was reduced from 4.713 (KNN) and 5.2676 (BiLSTM) to 3.0582, and the RMSE decreased from 6.9073 (KNN) and 6.9194 (BiLSTM) to 4.1947. The results confirm the framework’s powerful capability and robustness in handling high-dimensional delivery time prediction tasks. Full article

Peptide nanofibers (PNFs) have emerged as versatile platforms for delivering therapeutic agents due to their biocompatibility, tunable characteristics, and ability to form well-ordered nanostructures. The primary goal of this review is to elaborate on the key features of common PNF fabrication strategies, including both spontaneous and non-spontaneous methods, while exploring how the amino acid sequences of these peptides influence their secondary structure and fiber formation. Additionally, we have compiled studies on PNFs that investigate various delivery approaches, such as systemic delivery, localized delivery, controlled delivery, stimuli-responsive delivery, and targeted delivery. This analysis aims to guide researchers in selecting the most suitable fabrication strategy for specific delivery applications and provide insights into choosing optimal amino acids for rational peptide design. We also focused on the applications of PNFs in delivering various therapeutic agents, including drugs, functional peptides, diagnostic and imaging agents, genes, viral vectors, and vaccines, demonstrating their significant potential in biomedical applications. The synergy between nanofiber fabrication strategies and peptide chemistries offers new avenues for advancing therapeutic products. Overall, this review serves as an important reference for the design and development of advanced PNFs for the effective delivery of various therapeutic agents. Full article

Electronic Health Records (EHRs) have enhanced access to medical information but have also introduced challenges for healthcare providers, such as increased documentation workload and reduced face-to-face interaction with patients. To mitigate these issues, we propose RAGMed, a Retrieval-Augmented Generation (RAG)-based AI assistant designed to deliver automated and clinically grounded responses to frequently asked patient questions. This system combines a vector database for semantic retrieval with the generative capabilities of a large language model to provide accurate, reliable answers without requiring direct physician involvement. In addition to patient-facing support, the assistant facilitates appointment scheduling and assists clinicians by summarizing clinical notes, thereby streamlining healthcare workflows. Additionally, to evaluate the influence of retrieval quality on overall system performance, we compare two embedding models, gte-large and all-MiniLM-L6-v2, using real-world medical queries. The models are assessed within the RAG-Triad Framework, focusing on context relevance, answer relevance, and factual groundedness. The results indicate that gte-large, owing to its higher-dimensional embeddings, retrieves more informative context, resulting in more accurate and trustworthy responses. These findings underscore the importance of not only the potential of incorporating RAG-based systems to alleviate physician workload and enhance the efficiency and accessibility of healthcare delivery but also the dimensionality of models used to generate embeddings, as this directly influences the relevance, accuracy, and contextual understanding of retrieved information. This prototype is intended for the retrieval-augmented answering of medical FAQs and general informational queries, and is not designed for diagnostic use or treatment recommendations without professional validation. Full article

Adeno-associated virus (AAV) vectors are the preferred gene delivery tool in gene therapy owing to their safety, long-term gene expression, broad tissue tropism, and low immunogenicity. Affinity ligands that can bind multiple AAV serotypes endure harsh clean-in-place (CIP) conditions and are critical for industrial-scale purification. However, current ligands lack broad serotype recognition and adequate alkaline stability, which limits their reusability in large-scale manufacturing. In this study, we employed a competitive biopanning strategy to isolate a single-domain antibody (VHH) that simultaneously binds AAV2, AAV8, and AAV9. The VHH retained structural integrity and binding activity after exposure to 0.1 M NaOH, demonstrating robust alkaline stability. Structural modeling revealed that the VHH primarily recognizes the DE loop region of the VP3 capsid protein across the three serotypes, explaining its cross-serotype reactivity. Affinity chromatography using the VHH yielded infectious AAV particles, confirming its potential for downstream processing. This strategy provides a versatile platform for developing high-performance AAV affinity ligands and may be extended to other viral vector systems. Full article

Recent advances in biotechnology have fundamentally reshaped the landscape of vaccine development, offering innovative strategies to improve immunogenicity, safety and accessibility. This review explores the cutting-edge platforms—including mRNA, DNA, virus-like particles, viral and bacterial vectors, and bacteriophage-based vaccines—that are redefining how vaccine antigens are delivered to the immune system. We also discuss alternative delivery methods, such as transcutaneous and mucosal immunization, which have the potential to improve vaccine acceptance and distribution, as well as next-generation adjuvants targeting innate immune receptors aiming to further enhance vaccine efficacy, especially in vulnerable populations. By synthesizing these innovations, this review highlights how biotechnology is enabling the design of safer, more efficient, and more adaptable vaccines to address both existing and emerging infectious diseases. Full article

This study presents the design and experimental evaluation of a 10 MHz voltage regulator module (VRM) that incorporates a solenoid inductor embedded within a printed circuit board (PCB). To verify the performance of the inductor, a test PCB was fabricated and characterized using a vector network analyzer (VNA), with measurement data processed through 2x-thru de-embedding technique. A 10 MHz VRM was then implemented to assess the impact of the embedded inductor on system efficiency. Comparative measurements were conducted between two VRMs—one employing a surface-mounted (SMT) inductor and the other a PCB-embedded inductor. The SMT-based system achieved a peak efficiency of 65.24% at a load current of 800 mA, whereas the PCB-embedded inductor version reached 70.43% at 900 mA, reflecting an improvement of 5.19%. The VRM with an embedded inductor experienced less efficiency degradation under heavy load conditions, demonstrating superior energy delivery stability. These findings confirm the practical benefits of integrating solenoid inductors within a PCB for high-frequency, high-efficiency power conversion. Full article

Kinetoplastids are protozoa that possess a unique organelle called a kinetoplast. These include the parasites Trypanosoma cruzi, T. brucei and related African trypanosomes, and Leishmania spp. These parasites cause a variety of neglected tropical diseases in humans and livestock, with devastating consequences. In the absence of any vaccine, pharmaceutical interventions are the mainstay of control, but these have historically been underfunded, fragmented, and inadequately aligned with the complex zoonotic and ecological realities of the parasites’ transmission dynamics. In this review, the landscape of current and emerging drugs for treating leishmaniasis, Chagas disease, and African trypanosomiasis is critically evaluated across both veterinary and human contexts. It examines the challenges of legacy compounds, the pharmacological shortcomings in multi-host, multi-tropic and multi-stage disease systems, and the gaps in veterinary therapeutics, specifically for African animal trypanosomiasis and canine leishmaniasis but also the animal reservoir of T. cruzi. Emphasis is placed on pharmacokinetic divergence between species, the accompanying risks with the use of off-label human drugs in animals, and the ecological effects of environmental drug exposure. We propose a far-reaching One Health framework for pharmaceutical research and development, promoting dual-indication co-development, ecological pharmacology, regulatory harmonisation, and integrated delivery systems. In this context, we argue that the drug development pipeline must be rationalised as a transdisciplinary and ecologically embedded process, able to interrupt parasite transmission to human, animal, and vector interfaces. Our findings reveal that we can bridge age-old therapeutic gaps, advance towards sustainable control, and eventually eliminate the neglected diseases caused by kinetoplastid protozoan parasites by aligning pharmaceutical innovation with One Health principles. This article aims to promote future research and development of innovative drugs that are sustainable under the One Health framework. Full article

Plant viruses have evolved from being viewed exclusively as pathogens into versatile and powerful tools for modern biotechnology. Among them, Tomato bushy stunt virus (TBSV) holds a special place due to its well-studied molecular biology and unique structural properties. This review systematizes the knowledge on TBSV’s dual role as a multifunctional platform. On one hand, we cover its application as a viral vector for the highly efficient expression of recombinant proteins in plants, as well as a tool for functional genomics, including Virus-Induced Gene Silencing (VIGS) and the delivery of CRISPR/Cas9 gene-editing components. On the other hand, we provide a detailed analysis of the use of the stable and monodisperse TBSV virion in nanobiotechnology. Its capsid serves as an ideal scaffold for creating next-generation vaccine candidates, platforms for targeted drug delivery to tumor cells, and as a building block for the programmable self-assembly of complex nanoarchitectures. In conclusion, key challenges limiting the widespread adoption of the platform are discussed, including the genetic instability of vectors and difficulties in scalable purification, along with promising strategies to overcome them. Full article

Lactic acid bacteria (LAB) are central to food fermentation, probiotic delivery, and emerging synthetic biology applications, yet their robust cell envelopes and restriction–modification systems complicate DNA uptake. This review synthesizes practical routes for introducing DNA into LAB—natural competence, electroporation, conjugation, phage-mediated transduction, and biolistics—and outlines vector systems for expression and chromosomal editing, including food-grade strategies. We highlight recent advances that broaden strain tractability while noting strain-to-strain variability and host-specific barriers that still require tailored solutions. These advances directly enable applications in food and probiotic biotechnology, including improving starter robustness, tailoring flavor and texture pathways, and installing food-grade traits without residual selection markers. We close with near-term priorities for standardizing protocols, widening replicon compatibility, and leveraging modern genome-editing platforms to accelerate safe, marker-free engineering of industrial and probiotic LAB. Full article

Over the past decade, cellular immunotherapy has emerged as a transformative strategy for non-small cell lung cancer (NSCLC), with dendritic-cell (DC) vaccines, T-cell vaccines, and natural killer (NK)-cell therapies demonstrating distinct mechanisms and clinical potential. DC vaccines capitalize on antigen presentation to prime tumor-specific T-cell responses, showing excellent safety profiles limited mainly to injection-site reactions and flu-like symptoms. While monotherapy has shown limited efficacy, combinations with checkpoint inhibitors or chemotherapy enhance immune activation and survival outcomes. Recent innovations, including neoantigen-loaded, mRNA-electroporated, and exosome-pulsed DCs, demonstrate improved immunogenicity and personalized approaches. T-cell vaccines, designed to activate cytotoxic CD8+ T-cell responses, have been tested across multiple platforms, including peptide-based (MAGE-A3), viral vector (TG4010/MUC1), and mRNA (CV9201/92) formulations. While the phase III MAGRIT trial presented no disease-free survival (DFS) benefit with adjuvant MAGE-A3 vaccination, the TG4010 vaccine improved progression-free survival (PFS; HR 0.66) and overall survival (OS; HR 0.67) in MUC1-positive NSCLC when combined with chemotherapy. Current strategies focus on personalized neoantigen vaccines and KRAS-targeted approaches (e.g., ELI-002), with ongoing phase III trials evaluating their potential in resectable NSCLC. NK-cell therapies have also shown promise, with early trials establishing the feasibility of autologous and allogeneic infusions, while engineered CAR-NK cells enhance tumor-specific targeting. Combination strategies with checkpoint inhibitors significantly improve response rates and PFS, revealing synergies between innate and adaptive immunity. Recent advances include cytokine-enhanced, memory-like NK cells to overcome immunosuppression and “off-the-shelf” products for broader clinical use. Together, these cellular immunotherapies represent a versatile and evolving frontier in NSCLC treatment, with ongoing research optimizing combinations, delivery platforms, and patient selection to maximize therapeutic benefit. Full article

Rhodopsin, the prototypical Class A G protein-coupled receptor (GPCR) and visual pigment of rod photoreceptors, has long served as a structural and mechanistic model for GPCR biology. Mutations in rhodopsin are the leading cause of autosomal dominant retinitis pigmentosa (adRP), making this receptor a critical therapeutic target. In this review, we summarize the chemical, structural, and biophysical features of small-molecule modulators of this receptor, spanning both classical retinoid analogs and emerging non-retinoid scaffolds. These ligands reveal recurrent binding modes within the orthosteric chromophore pocket as well as peripheral allosteric and bitopic sites, where they mediate folding, rescue trafficking, photocycle modulation, and mutant stabilization. We organize ligand performance into a three-tier framework linking binding affinity, cellular rescue potency, and stability gains. Chemotypes in tier 2, which show sub-micromolar to low-micromolar activity with broad mutant coverage, emerge as promising candidates for optimization into next-generation scaffolds. Across scaffolds, a recurring minimal pharmacophore is evident by a contiguous hydrophobic π-surface anchored in the β-ionone region, coupled with a strategically oriented polar handle that modulates the Lys296/Glu113 microenvironment, offering tractable design vectors for non-retinoid chemotypes. Beyond the chromophore binding pocket, we highlight opportunities to exploit extracellular loop epitopes, cytoplasmic microswitch clefts, dimer/membrane interfaces, and ion co-binding sites to engineer safer, state-biased control with fewer photochemical liabilities. By integrating rhodopsin photobiophysics with environment-aware, multi-state medicinal chemistry, and by addressing current translational challenges in drug delivery, this review outlines a rational framework for advancing rhodopsin-targeted therapeutics toward clinically credible interventions for RP and related retinal degenerations. Full article

The combination of rGO-FETs (reduced Graphene Oxide Field-Effect Transistors) and DNA-oligonucleotide aptamers to sense analytes has been shown to be a promising technological approach, achieving high sensitivity and selectivity. With human adenovirus type 5 (HAdV-5) particles as the target, we here demonstrate the application of the aptamer/FET combination for detection of this medically and biotechnologically relevant viral vector. A focused anti-HAdV-5 aptamer library was evolved in a nine-round SELEX process, allowing for the specific fluorescent labeling of HAdV-5 and related subtypes. Moreover, this library was already sufficient to serve as the binding entity on a gFET sensor for sensitive quantification of the virus particles. Adenoviruses have been widely used as gene delivery vectors for gene therapy and genetic vaccination. The use of adenoviral vectors within the vaccination campaign against COVID-19 emphasized the need for robust biotechnological production processes, which additionally require sensitive product formation monitoring. We believe that these type of gFET-based aptasensors can serve as the technological monitoring basis in virus production processes in the near future. Full article