Search Results (26)

The cHER2+ breast cancer subtype is characterized by the overexpression of the HER2 oncoprotein based on immunohistochemistry (IHC)/or by ERBB2 gene amplification using in situ hybridization (ISH) techniques. Targeted therapies are significantly changing cancer treatment outcomes. However, not all patients benefit from it due to misclassification or intrinsic mechanisms of resistance. Identifying predictive factors of response to therapy is thus crucial for optimizing treatment protocol. In addition, with the development of effective antibody–drug conjugates for targeting HER2-low subtypes, enhancing the HER2 molecular classification is crucial. In this study, a comprehensive analysis of publicly available datasets (TCGA, METABRIC, I-SPY, NOAH and CHER-LOB trials) has been considered. We present a metagene expression score (HER2MtGx 31-gene assay) based on the most informative genes associated with each molecular profile. HER2MtGx scores represent three linear subspaces associated with the HER2, Luminal and Basal-like profiles (STAT). In the METABRIC cohort, the scores are useful to discriminate against the HER2-enriched phenotype and this classification is significantly associated with long-term survival in cHER2+ patients (HR = 1.76; 95%CI = 1.09–2.86). In terms of response to neoadjuvant chemo/target therapy including I-SPY, NOAH, and CHER-LOB trials, the metagene scores are associated with the pathological response to therapy (OR = 2.26; 95%CI = 1.74–2.98). The HER2MtGx assay is a reliable tool for selecting patients for HER2-targeted therapy. Full article

Optimal sensing devices exhibit a combination of key performance attributes, including an extensive detection limit, exceptional selectivity, high sensitivity, consistent repeatability, precise measurement, and rapid response times with efficient analyte flow. In recent years, biosensing platforms incorporating nanoscale materials have garnered considerable attention due to their diverse applications across various scientific and technological domains. The integration of nanoparticles (NPs) in biosensor design primarily bridges the dimensional gap between the signal transduction element and the biological recognition component, both of which operate at nanometer scales. The synergistic combination of NPs with electrochemical techniques has facilitated the development of biosensors characterized by enhanced sensitivity and superior analyte discrimination capabilities. This comprehensive analysis examines the evolution and recent advancements in nanomaterial (NM)-based biosensors, encompassing an extensive array of nanostructures. These consists of one-dimensional nanostructures including carbon nanotubes (CNTs), nanowires (NWs), nanorods (NRs), and quantum dots (QDs), as well as noble metal and metal and metal oxide nanoparticles (NPs). The article examines how advancements in biosensing techniques across a range of applications have been fueled by the growth of nanotechnology. Researchers have significantly improved biosensor performance parameters by utilizing the distinct physiochemical properties of these NMs. The developments have increased the potential uses of nanobiosensors in a wide range of fields, from food safety and biodefense to medical diagnostics and environmental monitoring. The continuous developments in NM-based biosensors are the result of the integration of several scientific areas, such as analytical chemistry, materials science, and biotechnology. This interdisciplinary approach continues to drive innovations in sensor design, signal amplification strategies, and data analysis techniques, ultimately leading to more sophisticated and capable biosensing platforms. As the field progresses, challenges related to the scalability, reproducibility, and long-term stability of nanobiosensors are being addressed through innovative fabrication methods and surface modification techniques. These efforts aim to translate the promising results observed in laboratory settings into practical, commercially viable biosensing devices that can address real-world analytical challenges across various sectors. Full article

Objectives: The aim of this study was to validate the Polish version of the Somatosensory Amplification Scale (SSAS-PL) and examine its psychometric properties in clinical and non-clinical samples. Methods: The study included 1128 participants (711 healthy adults, 194 cardiac patients, 223 psychiatric patients). The analyses were categorized into exploratory and confirmatory phases. Exploratory analyses were conducted on a randomly selected sample that comprised 60% of the study participants (training sample) to estimate the reliability (Cronbach’s alpha) and factorial validity (EFA with varimax rotation). Confirmatory analyses were performed on an independent (test) sample that represented 40% of the total sample size to facilitate the cross-validation of the factor structure (CFA) and to assess the convergent and discriminant validities (using the HTMT method) in relation to health anxiety (SHAI) and psychopathological symptoms (KOFF-58). Additionally, measurement invariance was examined with respect to gender (female vs. male) and health status (healthy vs. clinical). Results: The SSAS-PL demonstrated good internal consistency (α = 0.75–0.78) after removing item 1. A one-factor structure showed the best fit and theoretical interpretability. The measurement invariance was supported across clinical groups. The SSAS-PL showed convergent validity with the measures of somatic symptoms, anxiety, and health anxiety. It demonstrated discriminant validity from other psychopathology measures. Conclusions: The SSAS-PL was a reliable and valid measure of somatosensory amplification in the Polish population. Its unidimensional structure aligned with most cross-cultural adaptations. The scale may be useful for assessing somatosensory amplification in both research and clinical settings in Poland. Further research on its utility in specific clinical populations is warranted. Full article

Aquilaria sinensis (Lour.) Spreng. is an economically important tree specie that produces agarwood, a valuable medicinal and aromatic resin, when injured. However, its large-scale cultivation has led to confusion regarding its resources and genetic backgrounds, hindering the conservation and management of A. sinensis accessions. This study systematically developed and validated simple sequence repeat (SSR) molecular markers by using whole-genome resequencing (WGR) data from 60 A. sinensis accessions to elucidate their genetic diversity and population structure. A total of 56,657 SSR sequences (24,430 loci) were identified, which were dominated with dinucleotide repeat motifs (73.59%). After stringent quality control, 46 high-quality SSR loci were obtained, and 93 primer pairs were designed for amplification validation. Ultimately, 20 primer pairs with stable amplification and high polymorphism were selected, of which 11 exhibited high polymorphism (polymorphic information content: 0.554–0.688). These 20 primer pairs identified a total of 121 alleles, with an average of 6 alleles per locus. These primers successfully classified 149 A. sinensis accessions into three subpopulations, achieving a discrimination rate of 95.97%. The analysis of molecular variance revealed that genetic variation within the individuals accounted for 84% of the total variation. This study establishes a rapid and efficient SSR-based method by leveraging resequencing data for large-scale marker discovery in A. sinensis. It further provides a robust technical framework for the conservation and sustainable utilization of this valuable species. Full article

Nanhaia speciosa is a valuable industrial crop known for its significant edible and medicinal properties, attributed to its abundance of secondary metabolites. This study aims to elucidate the genetic relationships among N. speciosa, enhance species identification accuracy, and select genetically stable, high-quality germplasms of N. speciosa. To achieve this, we conducted chloroplast gene amplification and sequencing, alongside an analysis of the agronomic traits of 19 N. speciosa germplasms. Additionally, non-targeted metabolomic profiling using UPLC-Q-Orbitrap/MS and chemometric methods was employed to assess their metabolic diversity and genetic relationships. The results revealed notable differences in DNA barcodes and secondary structures across the germplasms, with the atpF-atpH sequence successfully distinguishing all 19 germplasms into distinct varieties. Multivariate statistical analyses, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and hierarchical clustering, identified 12 key marker metabolites that effectively differentiated the germplasms, consistent with the observed phenotypic diversity. A clustering analysis integrating genetic, phenotypic, and metabolomic data further validated the utility of DNA barcoding for species identification. The results of the comprehensive analysis showed that NDL-2 and NDL-18 exhibited relatively good edible and medicinal properties, while NDL-1 and NDL-19 exhibited relatively poor edible and medicinal properties. This study provides crucial insights for the breeding and genetic improvement of N. speciosa and related species, offering a valuable reference for the identification, conservation, and utilization of germplasm resources within the N. speciosa. Full article

At present, a large number of studies have demonstrated that miRNAs can be used as biological indicators for the diagnosis and treatment of diseases such as tumours and cancer, so it is important to develop a new miRNA detection platform. In this work, miRNA-122 is used as the basis for targeting detection agents. We have designed an unlabelled DNA1 that undergoes partial hybridisation and has a 20 T base long strand. The fluorescent signal in this experiment is derived from copper nanoclusters (CuNCs) generated on the circular T-long strand of DNA1. At the same time, DNA1 is able to react with miRNA-122 and achieve hydrolysis of the part bound to miRNA-122 via the action of nucleic acid exonuclease III (Exo III), leaving a part of the DNA, called DNA3, while releasing miRNA-122 to participate in the next reaction, thus achieving circular amplification. DNA3 is able to react with DNA2, which is bound to streptavidin magnetic beads (SIBs) and separated from the reaction solution via the application of a magnetic field. Overall, this is a fluorescence signal reduction experiment, and the strength of the fluorescence signal from the copper nanoclusters can determine whether the target miRNA-122 is present or not. The degree of fluorescence reduction indicates how much DNA1, and thus the amount of target miRNA-122, has been hydrolysed. By evaluating the variations in the fluorescence signal under optimised conditions, we discovered that this method has good sensitivity, with a detection limit as low as 0.46 nM, better than many other previous works on fluorescence signal-based biosensors for miRNA detection. This technique offers high discrimination and selectivity and can serve as a persuasive reference for early diagnosis. Full article

Conventional methods for the detection and differentiation of Bacillus cereus group species have drawbacks mostly due to the complexity of genetic discrimination between the Bacillus cereus species. Here, we describe a simple and straightforward assay based on the detected unamplified bacterial 16S rRNA by DNA nanomachine (DNM). The assay uses a universal fluorescent reporter and four all-DNA binding fragments, three of which are responsible for “opening up” the folded rRNA while the fourth stand is responsible for detecting single nucleotide variation (SNV) with high selectivity. Binding of the DNM to 16S rRNA results in the formation of the 10–23 deoxyribozyme catalytic core that cleaves the fluorescent reporter and produces a signal, which is amplified over time due to catalytic turnover. This developed biplex assay enables the detection of B. thuringiensis 16S rRNA at fluorescein and B. mycoides at Cy5 channels with a limit of detection of 30 × 10³ and 35 × 10³ CFU/mL, respectively, after 1.5 h with a hands-on time of ~10 min. The new assay may simplify the analysis of biological RNA samples and might be useful for environmental monitoring as a simple and inexpensive alternative to amplification-based nucleic acid analysis. The DNM proposed here may become an advantageous tool for detecting SNV in clinically significant DNA or RNA samples and can easily differentiate SNV under broadly variable experimental conditions and without prior amplification. Full article

Red sea bream iridovirus (RSIV) is an important aquatic virus that causes high mortality in marine fish. RSIV infection mainly spreads through horizontal transmission via seawater, and its early detection could help prevent disease outbreaks. Although quantitative PCR (qPCR) is a sensitive and rapid method for detecting RSIV, it cannot differentiate between infectious and inactive viruses. Here, we aimed to develop a viability qPCR assay based on propidium monoazide (PMAxx), which is a photoactive dye that penetrates damaged viral particles and binds to viral DNA to prevent qPCR amplification, to distinguish between infectious and inactive viruses effectively. Our results demonstrated that PMAxx at 75 μM effectively inhibited the amplification of heat-inactivated RSIV in viability qPCR, allowing the discrimination of inactive and infectious RSIV. Furthermore, the PMAxx-based viability qPCR assay selectively detected the infectious RSIV in seawater more efficiently than the conventional qPCR and cell culture methods. The reported viability qPCR method will help prevent the overestimation of red sea bream iridoviral disease caused by RSIV. Furthermore, this non-invasive method will aid in establishing a disease prediction system and in epidemiological analysis using seawater. Full article

In tomato plants, Fusarium spp. have been increasingly associated with several wilt and rot diseases that are responsible for severe yield losses. Here, we present a real-time PCR TaqMan^® MGB (Minor Groove Binder) assay to detect and discriminate Fusarium spp. from other fungal species that affect tomato plants. The methodology used is based on the selective amplification of the internal transcribed spacer (ITS) region of Fusarium spp. This assay revealed to be highly specific and sensitive for Fusarium species, targeting only the 29 Fusarium isolates from the 45 tested isolates associated to tomato diseases. Sensitivity was assessed with serial dilutions of Fusarium genomic DNA, with the limit of detection of 3.05 pg. An absolute DNA quantification method was also established, based on the determination of the absolute number of target copies. Finally, the effectiveness of the assay was successfully validated with the detection and quantification of Fusarium spp. in potentially infected tomato plants from an experimental field and in control plants grown under controlled conditions. The established methodology allows a reliable, sensitive, and reproducible estimation of Fusarium accumulation in infected tomato plants, gaining new insights for disease control and providing an additional tool in the screening of resistant plants. Full article

Background: The analysis of liquid biopsies brings new opportunities in the precision oncology field. Under this context, extracellular vesicle circular RNAs (EV-circRNAs) have gained interest as biomarkers for lung cancer (LC) detection. However, standardized and robust protocols need to be developed to boost their potential in the clinical setting. Although nCounter has been used for the analysis of other liquid biopsy substrates and biomarkers, it has never been employed for EV-circRNA analysis of LC patients. Methods: EVs were isolated from early-stage LC patients (n = 36) and controls (n = 30). Different volumes of plasma, together with different number of pre-amplification cycles, were tested to reach the best nCounter outcome. Differential expression analysis of circRNAs was performed, along with the testing of different machine learning (ML) methods for the development of a prognostic signature for LC. Results: A combination of 500 μL of plasma input with 10 cycles of pre-amplification was selected for the rest of the study. Eight circRNAs were found upregulated in LC. Further ML analysis selected a 10-circRNA signature able to discriminate LC from controls with AUC ROC of 0.86. Conclusions: This study validates the use of the nCounter platform for multiplexed EV-circRNA expression studies in LC patient samples, allowing the development of prognostic signatures. Full article

High-throughput and rapid screening testing is highly desirable to effectively combat the rapidly evolving COVID-19 pandemic co-presents with influenza and seasonal common cold epidemics. Here, we present a general workflow for iterative development and validation of an antibody-based microarray assay for the detection of a respiratory viral panel: (a) antibody screening to quickly identify optimal reagents and assay conditions, (b) immunofluorescence assay design including signal amplification for low viral titers, (c) assay characterization with recombinant proteins, inactivated viral samples and clinical samples, and (d) multiplexing to detect a panel of common respiratory viruses. Using RT-PCR-confirmed SARS-CoV-2 positive and negative pharyngeal swab samples, we demonstrated that the antibody microarray assay exhibited a clinical sensitivity and specificity of 77.2% and 100%, respectively, which are comparable to existing FDA-authorized antigen tests. Moreover, the microarray assay is correlated with RT-PCR cycle threshold (Ct) values and is particularly effective in identifying high viral titers. The multiplexed assay can selectively detect SARS-CoV-2 and influenza virus, which can be used to discriminate these viral infections that share similar symptoms. Such protein microarray technology is amenable for scale-up and automation and can be broadly applied as a both diagnostic and research tool. Full article

Because microRNAs (miRNAs) are biological indicators for the diagnosis, treatment, and monitoring of tumors, cancers, and other diseases, it is significant to develop a rapid, sensitive, and reliable miRNA detection platform. In this study, based on miRNA-21 detection, DNA-a with a 3′ end overhang and Texas Red fluorophore-labeled 5′ end was designed, which reacts with miRNA-21 and hybridizes with exonuclease III (Exo III), where the part connected to miRNA-21 is hydrolyzed, leaving a-DNA. At the same time, miRNA-21 is released to participate in the following reaction, to achieve cyclic amplification. a-DNA reacts with DNA-b conjugated to gold nanoparticles to achieve fluorescence quenching, with the quenching value denoted as F; additionally, after adding DNA-d and linked streptavidin immunomagnetic beads (SIBs), fluorescence recovery was achieved using DNA-c, with the recovered fluorescence recorded as F₀. By comparing the difference in the fluorescence (F₀ − F) between the two experiments, the amount of DNA-a hydrolyzed to produce a-DNA was established to determine the target miRNA-21 content. Under optimized conditions, by comparing the changes in the fluorescence signal, the developed strategy shows good sensitivity and repeatability, with a detection limit of 18 pM, good discriminative ability and selectivity, and promise for the early diagnosis of breast and intestinal cancers. Full article

The objective of this work was to use the random amplification of the polymorphic DNA–polymerase chain reaction (RAPD-PCR) technique to select polymorphic patterns through qualitative and quantitative analyses to differentiate the species A. flavus, A. fumigatus, A. niger and A. tubingensis. Twenty-seven Aspergillus isolates from different species were typified using phenotypic (macro- and micromorphology) and genotypic (partial BenA gene sequencing) methods. Thirty-four primers were used to obtain polymorphic patterns, and with these a qualitative analysis was performed to select the primers that presented species-specific patterns to distinguish each species. For the quantitative selection, a database was built from the polymorphic patterns and used for the construction of logistic regression models; later, the model that presented the highest value of sensitivity against specificity was evaluated through ROC curves. The qualitative selection showed that the primers OPA-19, P54, 1253 and OPA-02 could differentiate the species. A quantitative analysis was carried out through logistic regression, whereby a species-specific correlation of sensitivity and specificity greater than 90% was obtained for the primers: OPC-06 with a 96.32% match to A. flavus; OPF-01 with a 100% match to A. fumigatus; OPG-13 with a 98.01% match to A. tubingensis; and OPF-07 with a 99.71% match to A. niger. The primer OPF-01 discriminated the four species as well as closely related species. The quantitative methods using the selected primers allowed discrimination between species and showed their usefulness for genotyping some of the species of medical relevance belonging to the genus Aspergillus. Full article

Grass pollen is one of the major causes of allergy. Aerobiological monitoring is a necessary element of the complex of anti-allergic measures, but the similar pollen morphology of Poaceae species makes it challenging to discriminate species in airborne pollen mixes, which impairs the quality of aerobiological monitoring. One of the solutions to this problem is the metabarcoding approach employing DNA barcodes for taxonomical identification of species in a mix by high-throughput sequencing of the pollen DNA. A diverse set of 14 grass species of different genera were selected to create a local reference database of nuclear ITS1, ITS2, 5′-ETS, and plastome trnL-F DNA barcodes. Sequences for the database were Sanger sequenced from live field and herbarium specimens and collected from GenBank. New Poaceae-specific primers for 5′-ETS were designed and tested to obtain a 5′-ETS region less than 600 bp long, suitable for high-throughput sequencing. The DNA extraction method for single-species pollen samples and mixes was optimized to increase the yield for amplification and sequencing of pollen DNA. Barcode sequences were analyzed and compared by the barcoding gap and intra- and interspecific distances. Their capability to correctly identify grass pollen was tested on artificial pollen mixes of various complexity. Metabarcoding analysis of the artificial pollen mixes showed that nuclear DNA barcodes ITS1, ITS2, and 5′-ETS proved to be more efficient than the plastome barcode in both amplification from pollen DNA and identification of grass species. Although the metabarcoding results were qualitatively congruent with the actual composition of the pollen mixes in most cases, the quantitative results based on read-counts did not match the actual ratio of pollen grains in the mixes. Full article

We established an innovative approach that included direct, viability, and nested PCR for rapid and reliable identification of the fecal indicator organism Escherichia coli (E. coli). Direct PCR enabled successful amplification of the target uidA gene, omitting a prior DNA isolation or purification step. Furthermore, we applied viability PCR (v-PCR) to ensure the detection of only relevant viable bacterial cells. The principle involves the binding of propidium monoazide (PMA), a selective nucleic acid intercalating dye, to accessible DNA of heat killed bacteria cells and, consequently, allows viable and heat killed E. coli cells to be discriminated. To ensure high sensitivity, direct v-PCR was followed by a nested PCR step. The resulting amplicons were analyzed by a rapid 30 min microarray-based DNA hybridization assay for species-specific DNA detection of E. coli. A positive signal was indicated by enzymatically generated silver nanoparticle deposits, which served as robust endpoint signals allowing an immediate visual readout. The presented novel protocol allows the detection of 1 × 10¹ viable E. coli cells per PCR run. Full article