Search Results (104)

We address surrogate-assisted multi-objective optimization for computationally expensive structural designs. The testbed is an axisymmetric laminated composite shell whose geometry, ply angles, and plywise materials are optimized to simultaneously (i) maximize separation of selected natural frequencies from a known excitation and (ii) minimize material cost. To reduce high-fidelity (HF) finite element evaluations, we develop a deep neural network surrogate framework with three variants: an HF-only baseline; a multi-fidelity (MF) pipeline using an auxiliary refinement network to convert abundant low-fidelity (LF) data into pseudo-HF labels for a single-fidelity evaluator; and a cascaded ensemble that emulates HF responses and then maps them to pseudo-experimental targets. During optimization, only surrogates are queried—no FEM calls—while final designs are verified by FEM. Pareto-front quality is quantified primarily by a normalized relative hypervolume indicator computed against an envelope approximation of the True Pareto Front, complemented where appropriate by standard indicators. A controlled training protocol and common validation regime isolate the effect of fidelity strategy from architectural choices. Results show that MF variants markedly reduce HF data requirements and improve Pareto-front quality over the HF-only baseline, offering a practical route to scalable, accurate design under strict computational budgets. Full article

Reducing thermal losses through building envelopes remains a key strategy in the pursuit of low-carbon, energy-efficient buildings. This study presents an innovative and sustainable retrofitting approach involving thermal insulation plaster modified with finely ground hazelnut shells, an abundant agricultural by-product in Türkiye. The modified plaster is applied symmetrically on both sides of standard masonry briquettes in varying proportions (2%, 4%, and 6%), and its thermal performance is experimentally assessed via the laboratory-scale coheating test method. The results reveal a substantial reduction in U-values compared to the uninsulated briquette (5.5 W/m²K): the 2% shell-modified plaster achieves a U-value of 2.40 W/m²K (56.4% improvement), the 4% variant achieves 2.14 W/m²K (61.1%), and the 6% formulation performs best at 2.04 W/m²K (62.9%). In terms of effective thermal conductivity, the modified plasters exhibit values in the range of 0.0408–0.04856 W/mK. Additionally, the 6% composition exhibits enhanced thermal inertia, delaying internal heat loss and offering extended indoor comfort. All samples demonstrate exceptional measurement repeatability, with day-to-day U-value variation below 2%. These findings surpass thermal performance benchmarks reported in previous studies using bamboo or plaster thickness alterations, and position hazelnut shell-modified plaster as a high-potential solution for sustainable building retrofits. The outcomes offer practical implications for low-cost housing, rural construction, and building refurbishment programmes, while also informing policymakers and material standardisation bodies about scalable bio-based alternatives that align with circular economy and decarbonisation goals. Full article

Obesity is a global health challenge marked by substantial inter-individual differences in responses to dietary and lifestyle interventions. Traditional weight loss strategies often overlook critical biological variations in genetics, metabolic profiles, and gut microbiota composition, contributing to poor adherence and variable outcomes. Our primary aim is to identify key biological and behavioral effectors relevant to precision medicine for weight control, with a particular focus on nutrition, while also discussing their current and potential integration into digital health platforms. Thus, this review aligns more closely with the identification of influential factors within precision medicine (e.g., genetic, metabolic, and microbiome factors) but also explores how these factors are currently integrated into digital health tools. We synthesize recent advances in nutrigenomics, nutritional metabolomics, and microbiome-informed nutrition, highlighting how tailored dietary strategies—such as high-protein, low-glycemic, polyphenol-enriched, and fiber-based diets—can be aligned with specific genetic variants (e.g., FTO and MC4R), metabolic phenotypes (e.g., insulin resistance), and gut microbiota profiles (e.g., Akkermansia muciniphila abundance, SCFA production). In parallel, digital health tools—including mobile health applications, wearable devices, and AI-supported platforms—enhance self-monitoring, adherence, and dynamic feedback in real-world settings. Mechanistic pathways such as gut–brain axis regulation, microbial fermentation, gene–diet interactions, and anti-inflammatory responses are explored to explain inter-individual differences in dietary outcomes. However, challenges such as cost, accessibility, and patient motivation remain and should be addressed to ensure the effective implementation of these integrated strategies in real-world settings. Collectively, these insights underscore the pivotal role of precision nutrition as a cornerstone for personalized, scalable, and sustainable obesity interventions. Full article

Allergic rhinitis and asthma are common chronic airway diseases that present significant public health challenges. Previous research has shown how the nasal and oral mycobiomes influence the onset, progression and severity of these two conditions, but no study so far has directly compared those mycobiomes within the same cohort during health and disease. To address this gap, I analyzed next-generation fungal ITS sequence data from 349 participants, including individuals with allergic rhinitis, asthma, and healthy controls. The nasal and oral mycobiomes showed a great overlap in composition but differed significantly (p < 0.04) in the relative abundance of several dominant genera. Moreover, only 18.6% of the fungal amplicon variants were shared among cavities. Microbial alpha-diversity was significantly higher (p < 0.05) in the nasal cavity, while beta-diversity varied significantly (p < 0.045) across all indices and clinical groups. Fungal networks were largely fragmented and showed relatively low ecological niche specialization, which contrasts with a previous study of bacteriomes from the same cohort. These networks also differed in structure, complexity and keystone nodes across clinical phenotypes. Overall, these findings highlight that the nasal and oral mycobiomes play distinct yet interconnected roles in allergic rhinitis and asthma. Full article

Genetic mutation detection for colorectal cancer (CRC) is crucial for precision diagnosis and treatment, yet current methods often suffer from challenges such as low sensitivity, time consumption, and high costs. In our preliminary bioinformatic analysis of 751 CRC cases from The Cancer Genome Atlas and 131 Chinese patient samples, APC, TP53, and KRAS were identified as the most frequently mutated genes. Among them, KRAS missense mutations emerged as key diagnostic biomarkers. In this study, we applied a fluorescence-based long block displacement amplification (LBDA) sensing method for the rapid, high-throughput, and cost-effective detection of KRAS genetic mutations. In the LBDA system, SYBR Green dye binds to the amplified double-stranded DNA, generating a fluorescence signal that directly reflects the abundance of mutant types (MTs). This real-time signal output enables the enrichment and sensitive detection of MTs, establishing LBDA as an efficient biosensing platform for KRAS genotyping. Using this technique, a detection limit of 0.08% variant allele frequency was achieved with 20 ng of synthetic DNA input. To evaluate clinical performance, the LBDA method was applied to 118 tissue samples from 59 CRC patients, including tumor and matched peritumoral tissues. For 59 CRC tumor samples, LBDA successfully identified KRAS mutations in 37.29% of cases, closely matching results (42.37%) obtained by next-generation sequencing and achieving 88% sensitivity and 100% specificity. In conclusion, this study presents a rapid and cost-effective mutation detection method based on optical biosensing, offering strong potential for advancing personalized CRC diagnosis and treatment. Full article

Meiofauna are frequently overlooked in biodiversity assessments, resulting in a lack of understanding regarding their current status, the potential impact of anthropogenic activities, and climate change. This study on the intertidal zone of the Small Beach of Ostend marks a new effort to characterize meiofaunal communities along the Belgian coast. Sampling was carried out on five separate occasions throughout the year, with abiotic data collected during each event. Collected specimens were sorted according to their taxonomic group, resulting in a retrieval of 1742 organisms. Among these, Platyhelminthes and Nematoda were most abundant. Through metabarcoding of the 18S ribosomal region, a biodiversity assessment was conducted, yielding a total of 106 Amplicon Sequence Variants (ASVs). After filtering out rare reads, 65 metazoan ASVs were retained: 18 representing Platyhelminthes, 16 Nematoda, 15 Copepoda, 12 Polychaeta, and 4 Acoela. Identification of the ASVs through blasting generated 23 unique species-level identifications. The highest species richness was observed among Proseriata and Nematoda, each comprising six different species. Additionally, four different species of Polychaeta and Copepoda, two species of Acoela, and one species of Rhabdocoela were identified. Compared to findings on similar beaches along the Belgian coast from about 40 years ago, the meiofaunal communities on this beach exhibit an overall low species richness. Finding fewer and other species might be linked to the potential impact of beach nourishments, human trampling, and climate change. However, confirming this hypothesis requires future research. Full article

Background. The increase in antibiotic resistance in human-impacted environments, such as coastal waters with aquaculture activity, is related to the widespread use of antibiotics, even at sub-lethal concentrations. In Chile, the world’s second largest producer of salmon, aquaculture is considered the main source of antibiotics in coastal waters. In this work, we aimed to characterize the genetic and phenotypic profiles of antibiotic resistance in bacterial communities from salmon farms. Methods. Bacterial metagenomes from an intensive aquaculture zone in southern Chile were sequenced, and the composition, abundance and sequence of antibiotic resistance genes (ARGs) were analyzed using assembled and raw read data. Total DNA from bacterial communities was used as a template to recover floR gene variants, which were tested by heterologous expression and functional characterization of phenicol resistance. Results. Prediction of ARGs in salmon farm metagenomes using more permissive parameters yielded significantly more results than the default Resistance Gene Identifier (RGI) software. ARGs grouped into drug classes showed similar abundance profiles to global ocean bacteria. The floR gene was the most abundant phenicol-resistance gene with the lowest gene counts, showing a conserved sequence although with variations from the reference floR. These differences were recovered by RGI prediction and, in greater depth, by mapping reads to the floR sequence using SNP base-calling. These variants were analyzed by heterologous expression, revealing the co-existence of high- and low-resistance sequences in the environmental bacteria. Conclusions. This study highlights the importance of combining metagenomic and phenotypic approaches to study the genetic variability in and evolution of antibiotic-resistant bacteria associated with salmon farms. Full article

Background: Low-density lipoprotein cholesterol (LDL-C) is a well-established risk factor for cardiovascular disease, and it plays a causal role in the development of atherosclerosis. Genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with LDL-C. Most of these risk loci fall in non-coding regions of the genome, and it is unclear how these non-coding variants affect circulating lipid levels. One hypothesis is that genetically mediated variation in transcript abundance, detected via the analysis of expressed quantitative trait loci (eQTLs), is key to the biologic function of causal variants. Here, we investigate the hypothesis that non-coding GWAS risk variants affect the homeostatic expression of a nearby putatively causal gene for serum LDL-C levels. Methods: We establish a set of twenty-one expert-curated and validated genes implicated in hypercholesterolemia via dose-dependent pharmacologic modulation in human adults, for which the relevant tissue type has been established. We show that the expression of these LDL-C genes is impacted by eQTLs in relevant tissues and that there are significant genomic-risk loci in LDL-GWAS near these causal genes. We evaluate, using statistical colocalization, whether a single variant or set of variants in each genetic locus is responsible for the GWAS and eQTL signals. Results: Genome-wide association study results for serum LDL-C levels demonstrate that the 402 identified genomic-risk loci for LDL-C are highly enriched for known causal genes for LDL-C (OR 527, 95% CI 126–5376, p < 2.2 × 10⁻¹⁶). However, we find limited evidence for colocalization between GWAS signals near validated hypercholesterolemia genes and eQTLs in relevant tissues (colocalization rate of 26% at a locus-level colocalization probability > 50%). Conclusions: Our results highlight the complexity of genetic regulatory effects for causal hypercholesterolemia genes; we suggest that context-responsive eQTLs may explain the effects of non-coding GWAS hits that do not overlap with standard eQTLs. Full article

Background/Objectives: Stargardt disease (STGD1) is an autosomal recessive disorder caused by pathogenic variants in ABCA4 that affects the retina and is characterised by progressive central vision loss. The onset of disease manifestations varies from childhood to early adulthood. Methods: Whole exome (WES), whole gene, and whole genome sequencing (WGS) were performed for a patient with STGD1. Results: WES revealed a heterozygous pathogenic missense variant in ABCA4, but no second pathogenic variant was found. ABCA4 whole-gene sequencing, subsequent WGS, and segregation analysis identified a complex deep-intronic allele (NM_000350.2(ABCA4):c.[1555-5882C>A;1555-5784C>G]) in trans to the missense variant. Minigene assays combined with nanopore sequencing were performed to characterise this deep-intronic complex allele in more detail. Surprisingly, the reference minigene revealed the existence of two pseudoexons in intron 11 of the ABCA4 gene that are included in low-abundance (<1%) transcripts. Both pseudoexons could be confirmed in cDNA derived from wildtype retinal organoids. Despite mild splicing predictions, the variant minigene revealed that the complex deep-intronic allele substantially increased the abundance of transcripts that included the pseudoexon overlapping with the variants. Two antisense oligonucleotides (AONs) were designed to rescue the aberrant splicing events. Both AONs increased the proportion of correctly spliced transcripts, and one of them rescued correct splicing to reference levels. Conclusions: Minigene assays combined with nanopore sequencing proved instrumental in identifying low-abundance transcripts including pseudoexons from wildtype ABCA4 intron 11, one of which was substantially increased by the complex allele. Full article

Omics approaches were extensively applied during the coronavirus disease 2019 (COVID-19) pandemic to understand the disease, identify biomarkers with diagnostic and prognostic value, and discover new molecular targets for medications. COVID-19 continues to challenge the healthcare system as the virus mutates, becoming more transmissible or adept at evading the immune system, causing resurgent epidemic waves over the last few years. In this study, we used saliva from volunteers who were negative and positive for COVID-19 when Omicron and its variants became dominant. We applied a direct solid-phase extraction approach followed by non-target metabolomics analysis to identify potential salivary signatures of hospital-recruited volunteers to establish a model for COVID-19 screening. Our model, which aimed to differentiate COVID-19-positive individuals from controls in a hospital setting, was based on 39 compounds and achieved high sensitivity (85%/100%), specificity (82%/84%), and accuracy (84%/92%) in training and validation sets, respectively. The salivary diagnostic signatures were mainly composed of amino acids and lipids and were related to a heightened innate immune antiviral response and an attenuated inflammatory profile. The higher abundance of thyrotropin-releasing hormone in the COVID-19 positive group highlighted the endocrine imbalance in low-severity disease, as first reported here, underscoring the need for further studies in this area. Full article

Next-generation sequencing (NGS) for HIV drug resistance (DR) testing has an increasing number of applications for the detection of low-abundance drug-resistant variants (LA-DRVs) in regard to its features as a quasi-species. However, there is less information on its detection performance in DR detection with NGS. To determine the feasibility of using NGS technology in LA-DRV detection for HIV-1 pretreatment drug resistance, 80 HIV-infected individuals who had never undergone antiretroviral therapy were subjected to both NGS and Sanger sequencing (SS) in HIV-1 drug resistance testing. The results reported in this study show that NGS exhibits higher sensitivity for drug resistance identification than SS at a 5% detection threshold. NGS showed a better consistency compared with that of SS for both protease inhibitors (PIs) and integrase inhibitors (INSTIs), with a figure amounting to more than 90%, but worse consistency in nucleotide reverse transcriptase inhibitors (NRTIs), with a consistency ranging from only 61.25% to 87.50%. The consistency of non-nucleotide reverse transcriptase inhibitors (NNRTIs) between NGS and SS was around 85%. NGS showed the highest sensitivity of 87.0% at a 5% threshold. The application of NGS technology in HIV-1 genotype resistance detection in different populations infected with HIV requires further documentation and validation. Full article

The salivary microbiota of Italian and sub-Saharan African individuals was investigated using Nanopore sequencing technology (ONT: Oxford Nanopore Technologies). We detected variations in community composition in relation to endogenous (ethnicity, sex, and diplotypic variants of the TRPV1 gene) and exogenous (sensitivity to capsaicin) factors. The results showed that Prevotella, Haemophilus, Neisseria, Streptococcus, Veillonella, and Rothia are the most abundant genera, in accordance with the literature. However, alpha diversity and frequency spectra differed significantly between DNA pools. The microbiota in African, male TRPV1 bb/ab diplotype and capsaicin low-sensitive DNA pools was more diverse than Italian, female TRPV1 aa diplotype and capsaicin high-sensitive DNA pools. Relative abundance differed at the phylum, genus, and species level. Full article

Toxigenic cyanobacteria and microcystins in the oligotrophic pelagic zone and mesotrophic bay of Lake Onego—the second largest lake in Europe—were found for the first time. Microscopic analysis revealed that Dolichospermum lemmermannii, D. circinale and D. spiroides dominated in bloom spots in the oligotrophic zone of the lake and D. flos-aquae and Microcystis aeruginosa OKin the eutrophic bay. The abundance of cyanobacteria in bloom spots is potentially hazardous for humans and animals. PCR-analysis showed that mcyA gene involved in microcystin biosynthesis was found in cyanobacteria of the genera Dolichospermum and Microcystis. Five structural variants of intracellular microcystins were detected in a trace amount using high-performance liquid chromatography–mass-spectrometry of high resolution. The most hazardous hepatotoxin, MC-LR, was found only in the eutrophic bay. In the present study, the reasons for the low cyanotoxin content in the phytoplankton dominated by Dolichospermum are discussed. The findings of our study make a significant contribution to the accumulation of facts which state that toxigenic cyanobacterial blooms can occur in large oligotrophic lakes. Full article

Background/Objective: Current treatments for eosinophilic and mast cell disorders are often ineffective. One promising target to improve outcomes is sialic acid-binding immunoglobulin-like lectin-8 (Siglec-8). As limitations, there are few Siglec-8 monoclonal antibodies (mAbs) available to date, and Siglec-8-directed treatments have so far primarily focused on unconjugated mAbs, which may be inadequate, especially against mast cells. Methods: Here, we used transgenic mice to raise a diverse panel of fully human mAbs that either recognize the V-set domain, membrane-distal C2-set domain, or membrane-proximal C2-set domain of full-length Siglec-8 as a basis for novel therapeutics. Results: All mAbs were efficiently internalized into Siglec-8-expressing cells, suggesting their potential to deliver cytotoxic payloads. Tool T cell-engaging bispecific antibodies (BiAbs) and chimeric antigen receptor (CAR)-modified natural killer (NK) cells using single-chain variable fragments from Siglec-8 mAbs showed highly potent cytolytic activity against Siglec-8-positive cells even in cases of very low target antigen abundance, whereas they elicited no cytolytic activity against Siglec-8-negative target cells. Siglec-8^V-set-directed T cell-engaging BiAbs and Siglec-8^V-set-directed CAR-modified NK cells induced substantially greater cytotoxicity against cells expressing an artificial smaller Siglec-8 variant containing only the V-set domain than cells expressing full-length Siglec-8, consistent with the notion that targeting membrane-proximal epitopes enhances effector functions of Siglec-8 antibody-based therapeutics. Indeed, unconjugated Siglec-8^C2-set mAbs, Siglec-8^C2-set-directed T cell-engaging BiAbs, and Siglec-8^C2-set-directed CAR-modified NK cells showed high antigen-specific cytolytic activity against Siglec-8-positive human cell lines and primary patient eosinophils. Conclusions: Together, these data demonstrate Siglec-8-directed immunotherapies can be highly potent, supporting their further development for eosinophilic and mast cell disorders. Full article

Sequence analysis of the Zaire ebolavirus (EBOV) polymerase (L gene) mRNA, using online tools, identified a highly ranked −1 programmed ribosomal frameshift (FS) signal including an ideal slippery sequence heptamer (UUUAAAA), with an overlapping coding region featuring two tandem UGA codons, immediately followed by an RNA region that is the inverse complement (antisense) to a region of the mRNA of the selenoprotein iodothyronine deiodinase II (DIO2). This antisense interaction was confirmed in vitro via electrophoretic gel shift assay, using cDNAs at the EBOV and DIO2 segments. The formation of a duplex between the two mRNAs could trigger the ribosomal frameshift, by mimicking the enhancing role of a pseudoknot structure, while providing access to the selenocysteine insertion sequence (SECIS) element contained in the DIO2 mRNA. This process would allow the −1 frame UGA codons to be recoded as selenocysteine, forming part of a C-terminal module in a low abundance truncated isoform of the viral polymerase, potentially functioning in a redox role. Remarkably, 90 bases downstream of the −1 FS site, an active +1 FS site can be demonstrated, which, via a return to the zero frame, would enable the attachment of the entire C-terminal of the polymerase protein. Using a construct with upstream and downstream reporter genes, spanning a wildtype or mutated viral insert, we show significant +1 ribosomal frameshifting at this site. Acting singly or together, frameshifting at these sites (both of which are highly conserved in EBOV strains) could enable the expression of several modified isoforms of the polymerase. The 3D modeling of the predicted EBOV polymerase FS variants using the AI tool, AlphaFold, reveals a peroxiredoxin-like active site with arginine and threonine residues adjacent to a putative UGA-encoded selenocysteine, located on the back of the polymerase “hand”. This module could serve to protect the viral RNA from peroxidative damage. Full article