Hybridization Signals Research Articles

Molecular cytogenetics of four species of Calendula (Asteraceae)

For the first time, a comparative molecular cytogenetic study of four species of Calendula L. (Asteraceae): C. officinalis, C. stellata, C. tripterocarpa, and C. arvensis was carried out. In each species, chromosome numbers were determined: C. stellata (2n = 2х = 14), C. officinalis (2n = 4x = 32), C. tripterocarpa (2n = 2x = 30), and C. arvensis (2n = 4x = 44), and also specific chromosome localization of 45S and 5S rDNA clusters was revealed with the use of fluorescence in situ hybridization. An additional polymorphic minor 45S rDNA hybridization signal was found in the C. officinalis karyotype, which was located median in the short arm of one chromosome. The patterns of chromosome distribution of the major sites of 45S and 5S rDNA in karyotypes of the studied species confirmed the hybrid origin of C. arvensis (2n = 4x = 44) which could be a result of the introgressive hybridization of two other species: C. stellata (2n = 2x = 14) and C. tripterocarpa (2n = 2x = 30) during speciation.

True-T – Improving T-cell response quantification with holistic artificial intelligence based prediction in immunohistochemistry images

The immune response associated with oncogenesis and potential oncological therapeutic interventions has dominated the field of cancer research over the last decade. T-cell lymphocytes in the tumor microenvironment are a crucial aspect of cancer’s adaptive immunity, and the quantification of T-cells in specific cancer types has been suggested as a potential diagnostic aid. However, this is currently not part of routine diagnostics. To address this challenge, we present a new method called True-T, which employs artificial intelligence-based techniques to quantify T-cells in colorectal cancer (CRC) using immunohistochemistry (IHC) images. True-T analyses the chromogenic tissue hybridization signal of three widely recognized T-cell markers (CD3, CD4, and CD8). Our method employs a pipeline consisting of three stages: T-cell segmentation, density estimation from the segmented mask, and prediction of individual five-year survival rates. In the first stage, we utilize the U-Net method, where a pre-trained ResNet-34 is employed as an encoder to extract clinically relevant T-cell features. The segmentation model is trained and evaluated individually, demonstrating its generalization in detecting the CD3, CD4, and CD8 biomarkers in IHC images. In the second stage, the density of T-cells is estimated using the predicted mask, which serves as a crucial indicator for patient survival statistics in the third stage. This approach was developed and tested in 1041 patients from four reference diagnostic institutions, ensuring broad applicability. The clinical effectiveness of True-T is demonstrated in stages II-IV CRC by offering valuable prognostic information that surpasses previous quantitative gold standards, opening possibilities for potential clinical applications. Finally, to evaluate the robustness and broader applicability of our approach without additional training, we assessed the universal accuracy of the CD3 component of the True-T algorithm across 13 distinct solid tumors.

Comparative effects of two in situ hybridization methods for the pinewood nematode (Bursaphelenchus xylophilus)

The gene localization technique of Bursaphelenchus xylophilus (pinewood nematode, PWN) is used for study gene expression in PWNs. Two in situ hybridization methods, namely, whole-mount in situ hybridization and the cut-off method are used widely. To compare the effects of these two in situ hybridization methods, the present study investigated the patterns of two functional genes expression in PWNs. The Bx-vap-2 gene (GenBank accession number: OR228482), related to pathogenicity, and the fem-2 gene (GenBank accession number: OR228481), related to sex determination, were selected to map related genes in the whole-mount and amputated PWNs at different ages using these in situ hybridization methods. Based on the overall statistical comparison, we found that compared to the cut-off method, the whole-mount method exhibited higher staining rates and correct staining rates for the fem-2 gene and Bx-vap-2 gene. However, considering the correct staining aspect, the cut-off method yielded better staining effects on pinewood nematode sections than the whole-mount method, with clearer hybridization signal locations and less non-specific staining. In other words, the cut-off method demonstrated more precise gene localization. Both methods are applicable for gene localization, but considering the overall staining pattern, analysis of experimental results, and comprehensive experimental operations, we believe that the whole-mount method is more suitable for gene localization and expression analysis of development-related genes in pinewood nematodes. This is because intact pinewood nematodes are better suited for showcasing the continuous developmental process of development-related genes. On the other hand, considering the experimental time, accuracy of staining site, and the amount of non-specific staining, the cut-off method is more suitable for disease-related genes. Additionally, to achieve better performance, the cut-off method can be selectively applied to samples during the experimental process.

Contribution of the satellitome to the exceptionally large genome of dinoflagellates: The case of the harmful alga Alexandrium minutum

Dinoflagellates are known to possess an exceptionally large genome organized in permanently condensed chromosomes. Focusing on the contribution of satellite DNA (satDNA) to the whole DNA content of genomes and its potential role in the architecture of the chromosomes, we present the characterization of the satellitome of Alexandriun minutum strain VGO577. To achieve this, we analyzed Illumina reads using graph-based clustering and performed complementary bioinformatic analyses. In this way, we discovered 180 satDNAs occupying 17.38 % of the genome. The 12 most abundant satDNAs represent the half of the satellitome but no satDNA is overrepresented, with the most abundant contributing ∼1.56 % of the genome. The largest repeat unit is 517 bp long but more than the half of the satDNAs (101) have repeat units shorter than 20 bp. We used FISH to map a selected set of 26 satDNAs. Although some satDNAs generate discrete hybridization signals at specific chromosomal locations (hybridization sites, HS), our cytological analysis showed that most satDNAs are dispersed throughout the genome, probably forming short arrays. Two satDNAs co-localize with the 45S rDNA. With the exception of telomeric DNA, no other satDNA yields HS on all chromosomes. In addition, we analyzed nine satDNAs yielding HS in VGO577 in four other A. minutum strains. Polymorphism at the intraspecific level was found for the presence/absence and/or abundance of some satDNAs, suggesting the amplification/deletion of these satDNAs following geographic separation or during culture maintenance of the strains. We also discuss how these results contribute to the understanding of chromosome architecture and evolution of dinoflagellate genomes.

In situ hybridization to detect Escherichia coli in canine granulomatous colitis.

Canine granulomatous colitis (histiocytic ulcerative colitis) is an uncommon disease, predominantly of young French Bulldogs and Boxer dogs, that manifests from a dysregulated immune response, primarily to adherent-invasive Escherichia coli (AIEC). In conjunction with histopathology and periodic acid-Schiff staining, the diagnosis of granulomatous colitis currently relies on fluorescence in situ hybridization (ISH) or immunohistochemistry to identify and localize AIEC organisms within macrophages in the mucosa and/or submucosa. We investigated the utility of ISH for E. coli using formalin-fixed, paraffin-embedded specimens collected from 29 cases of suspected granulomatous colitis. Most confirmed cases of granulomatous colitis were in French Bulldogs (12 of 20; 60%) and Boxers (3 of 20; 15%), and the mean age was 25 ± 6 mo with no sex predilection. E. coli ISH signal localized bacterial genetic material within the mucosa in 20 of 29 (69%) cases, supporting the diagnosis. ISH signal was limited to the lumen in 8 of 29 (28%) cases, which did not support the identification of these organisms as AIEC. The remaining case had no hybridization signal, and the diagnosis of granulomatous colitis was not supported. Our results revealed that ISH is a quick and specific detection method that can effectively confirm the diagnosis of canine granulomatous colitis.

The Application of Hybridization Chain Reaction in the Detection of Foodborne Pathogens.

Today, with the globalization of the food trade progressing, food safety continues to warrant widespread attention. Foodborne diseases caused by contaminated food, including foodborne pathogens, seriously threaten public health and the economy. This has led to the development of more sensitive and accurate methods for detecting pathogenic bacteria. Many signal amplification techniques have been used to improve the sensitivity of foodborne pathogen detection. Among them, hybridization chain reaction (HCR), an isothermal nucleic acid hybridization signal amplification technique, has received increasing attention due to its enzyme-free and isothermal characteristics, and pathogenic bacteria detection methods using HCR for signal amplification have experienced rapid development in the last five years. In this review, we first describe the development of detection technologies for food contaminants represented by pathogens and introduce the fundamental principles, classifications, and characteristics of HCR. Furthermore, we highlight the application of various biosensors based on HCR nucleic acid amplification technology in detecting foodborne pathogens. Lastly, we summarize and offer insights into the prospects of HCR technology and its application in pathogen detection.

The Improvement of Fluorescence In Situ Hybridization Technique Based on Explorations of Symbionts in Cicadas.

Fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes is widely used for the identification of microbes in complex samples, but it suffers from some limitations resulting in the weak or even absence of fluorescence signals of microbe(s), which may lead to the underestimation or misunderstanding of a microbial community. Herein, we explored symbionts in the bacteriomes and fat bodies of cicadas using modified FISH, aiming to improve this technique. We initially revealed that the probes of Candidatus Sulcia muelleri (Sulcia) and the yeast-like fungal symbiont (YLS) are suitable for detection of these symbionts in all cicadas and some other species of Auchenorrhyncha, whereas the probe of Candidatus Hodgkinia cicadicola (Hodgkinia) is only suitable for detection of Hodgkinia in a few cicada species. The fluorescence signal of Sulcia, Hodgkinia and YLS exhibited weak intensity without the addition of unlabeled oligonucleotides (helpers) and heat shock in some cicadas; however, it can be significantly improved by the addition of both helpers and heat shock. Results of this study suggest that heat shock denaturing rRNA and proteins of related microbe(s) together with helpers binding to the adjacent region of the probe's target sites prevent the re-establishment of the native secondary structure of rRNA; therefore, suitable probe(s) can more easily access to the probe's target sites of rRNA. Our results provide new information for the significant improvement of hybridization signal intensities of microbes in the FISH experiment, making it possible to achieve a more precise understanding of the microbial distribution, community and density in complex samples.

The Performance of a Lip-Sync Imagery Model, New Combinations of Signals, a Supplemental Bond Graph Classifier, and Deep Formula Detection as an Extraction and Root Classifier for Electroencephalograms and Brain–Computer Interfaces

Many current brain–computer interface (BCI) applications depend on the quick processing of brain signals. Most researchers strive to create new methods for future implementation and enhance existing models to discover an optimal feature set that can operate independently. This study focuses on four key concepts that will be used to complete future works. The first concept is related to potential future communication models, whereas the others aim to enhance previous models or methodologies. The four concepts are as follows. First, we suggest a new communication imagery model as a substitute for a speech imager that relies on a mental task approach. As speech imagery is intricate, one cannot imagine the sounds of every character in every language. Our study proposes a new mental task model for lip-sync imagery that can be employed in all languages. Any character in any language can be used with this mental task model. In this study, we utilized two lip-sync movements to indicate two sounds, characters, or letters. Second, we considered innovative hybrid signals. Choosing an unsuitable frequency range can lead to ineffective feature extractions. Therefore, the selection of an appropriate frequency range is crucial for processing. The ultimate goal of this method is to accurately discover distinct frequencies of brain imagery activities. The restricted frequency range combination presents an initial proposal for generating fragmented, continuous frequencies. The first model assesses two 4 Hz intervals as filter banks. The primary objective is to discover new combinations of signals at 8 Hz by selecting filter banks with a 4 Hz scale from the frequency range of 4 Hz to 40 Hz. This approach facilitates the acquisition of efficient and clearly defined features by reducing similar patterns and enhancing distinctive patterns of brain activity. Third, we introduce a new linear bond graph classifier as a supplement to a linear support vector machine (SVM) when handling noisy data. The performance of the linear support vector machine (SVM) significantly declines under high-noise conditions. To complement the linear support vector machine (SVM) in noisy-data situations, we introduce a new linear bond graph classifier. Fourth, this paper presents a deep-learning model for formula recognition that converts the first-layer data into a formula extraction model. The primary goal is to decrease the noise in the formula coefficients of the subsequent layers. The output of the final layer comprises coefficients chosen by different functions at various levels. The classifier then extracts the root interval for each formula, and a diagnosis is established based on these intervals. The final goal of the last idea is to explain the main brain imagery activity formula using a combination formula for similar and distinctive brain imagery activities. The results of implementing all of the proposed methods are reported. The results range between 55% and 98%. The lowest result is 55% for the deep detection formula, and the highest result is 98% for new combinations of signals.

Series Arc Fault Detection Method Based on Signal-Type Enumeration and Zoom Circular Convolution Algorithm

AC series arc fault (SAF) detection under various circuits is always a challenging task because arcing current is affected by different circuit types and fault points. Additionally, normal current is confused as arcing current when non-linear loads are present in the circuit. To cope with these issues, this paper presents a detection method using signal-type enumeration and a zoom circular convolution (CC) (ZCC) algorithm. The generalization ability of the detection method under unknown conditions is improved by means of signal-type enumeration. The impulsive components of current can be divided into stable, periodically impulsive, non-periodically impulsive and hybrid signals by enumeration. Then, given the CC limitations, the ZCC is presented to extract distinguishable features and decrease the computation complexity of CC, and the signal function is partially reconstructed to improve the CC performance. Finally, the presented detection method is analyzed in a laptop and evaluated by TMS320F28335. The online detection results show that the proposed method determined by known single-load circuits has good detection accuracy under unknown conditions and can be achieved in practical application.

Introgressive hybridization levels of Tilapiine species in Lake Victoria basin, Kenya inferred from microsatellite and mitochondrial DNA genotyping based on next-generation sequencing

Despite their high abundance and species richness, tilapiines have been compromised by various factors especially overfishing, climate change, and uncontrolled fish transfers and introductions. Fish introductions have negatively impacted native tilapiine populations through competition, predation, hybridization, and introgression compromising their genetic integrity. The hybridization levels of different tilapiines in the Lake Victoria basin remain relatively understudied. The study utilized nuclear microsatellite and mitochondrial DNA (mtDNA) genetic markers to investigate hybridization signals and compare the genetic diversity of different tilapiines in Lake Victoria, Kenya, using next-generation sequencing. Low levels of hybridization from Oreochromis niloticus into other Oreochromis species were detected by Bayesian clustering analysis and principal coordinate analysis (PCoA). The results contribute to the need for conservation measures for these fish species.

Semantic Hybrid Signal Temporal Logic Learning-Based Data-Driven Anomaly Detection in the Textile Process

The development of sensor networks allows for easier time series data acquisition in industrial production. Due to the redundancy and rapidity of industrial time series data, accurate anomaly detection is a complex and important problem for the efficient production of the textile process. This paper proposed a semantic inference method for anomaly detection by constructing the formal specifications of anomaly data, which can effectively detect exceptions in process industrial operations. Furthermore, our method provides a semantic interpretation of exception data. Hybrid signal temporal logic (HSTL) was proposed to improve the insufficient expressive ability of signal temporal logic (STL) systems. The epistemic formal specifications of fault offline were determined, and a data-driven semantic anomaly detector (SeAD) was constructed, which can be used for online anomaly detection, helping people understand the causes and effects of anomalies. Our proposed method was applied to time-series data collected from a representative textile plant in Zhejiang Province, China. Comparative experimental results demonstrated the feasibility of the proposed method.

Differential Spreading of Microsatellites in Holocentric Chromosomes of Chagas Disease Vectors: Genomic and Evolutionary Implications.

This study focused on analyzing the distribution of microsatellites in holocentric chromosomes of the Triatominae subfamily, insect vectors of Chagas disease. We employed a non-denaturing FISH technique to determine the chromosomal distribution of sixteen microsatellites across twenty-five triatomine species, involving five genera from the two principal tribes: Triatomini and Rhodniini. Three main hybridization patterns were identified: strong signals in specific chromosomal regions, dispersed signals dependent on microsatellite abundance and the absence of signals in certain chromosomal regions or entire chromosomes. Significant variations in hybridization patterns were observed between Rhodniini and Triatomini species. Rhodniini species displayed weak and scattered hybridization signals, indicating a low abundance of microsatellites in their genomes. In contrast, Triatomini species exhibited diverse and abundant hybridization patterns, suggesting that microsatellites are a significant repetitive component in their genomes. One particularly interesting finding was the high abundance of GATA repeats, and to a lesser extent AG repeats, in the Y chromosome of all analyzed Triatomini species. In contrast, the Y chromosome of Rhodniini species did not show enrichment in GATA and AG repeats. This suggests that the richness of GATA repeats on the Y chromosome likely represents an ancestral trait specific to the Triatomini tribe. Furthermore, this information can be used to elucidate the evolutionary relationships between Triatomini and other groups of reduviids, contributing to the understanding of the subfamily's origin. Overall, this study provides a comprehensive understanding of the composition and distribution of microsatellites within Triatominae genomes, shedding light on their significance in the evolutionary processes of these species.

Deep Learning Assisted Surface-Enhanced Raman Spectroscopy (SERS) for Rapid and Direct Nucleic Acid Amplification and Detection: Toward Enhanced Molecular Diagnostics.

Surface-enhanced Raman scattering (SERS) has evolved into a robust analytical technique capable of detecting a variety of biomolecules despite challenges in securing a reliable Raman signal. Conventional SERS-based nucleic acid detection relies on hybridization assays, but reproducibility and signal strength issues have hindered research on directly amplifying nucleic acids on SERS surfaces. This study introduces a deep learning assisted ZnO-Au-SERS-based direct amplification (ZADA) system for rapid, sensitive molecular diagnostics. The system employs a SERS substrate fabricated by depositing gold on uniformly grown ZnO nanorods. These nanorods create hot spots for the amplification of the target nucleic acids directly on the SERS surface, eliminating the need for postamplification hybridization and Raman reporters. The limit of detection of the ZADA system was superior to those of the conventional amplification methods. Clinical validation of the ZADA system with coronavirus disease 2019 (COVID-19) samples from human patients yielded a sensitivity and specificity of 92.31% and 81.25%, respectively. The integration of a deep learning program further enhanced sensitivity and specificity to 100% and reduced SERS analysis time, showcasing the potential of the ZADA system for rapid, label-free disease diagnosis via direct nucleic acid amplification and detection within 20 min.

Granulomatous mural folliculitis in 16 domestic goats: Infection with malignant catarrhal fever viruses and colocalization with ovine herpesvirus-2 using in situ hybridization.

Granulomatous mural folliculitis (GMF) is an uncommon reaction pattern occasionally observed in nonadapted ruminant hosts infected with malignant catarrhal fever viruses. This report characterizes GMF and concurrent cutaneous lesions in 16 goats with crusting dermatitis using histochemistry including hematoxylin and eosin, periodic acid-Schiff, and Grocott's methenamine silver, and immunohistochemistry for CD3, CD20, ionized calcium binding adaptor molecule 1, and cytokeratin AE1/3. Infiltrates in all 16 GMF cases consisted of macrophages and fewer T lymphocytes, and variably included eosinophils, multinucleated histiocytic giant cells, and/or neutrophils. Formalin-fixed paraffin-embedded skin and fresh skin samples from caprine GMF cases were tested using pan-herpesvirus nested conventional polymerase chain reaction (PCR) and partial sequencing, ovine herpesvirus-2 (OvHV-2) real-time PCR, and OvHV-2 colorimetric in situ hybridization (ISH). Five of 16 goats with GMF (31%) were PCR positive for malignant catarrhal fever viruses, including caprine herpesvirus 3 in 1 goat and OvHV-2 in 4 goats. Three goats also had positive intranuclear OvHV-2 hybridization signal in follicular keratinocytes, among other cell types, localized to areas of GMF. Herpesviruses were not detected in the formalin-fixed paraffin-embedded skin of 9 goats without GMF. This case series describes relatively frequent detections of malignant catarrhal fever viruses in the skin of goats with GMF, including the first report of caprine herpesvirus 3, and localizes OvHV-2 infected follicular keratinocytes within areas of GMF.

A subset of equine oral squamous cell carcinomas is associated with Equus caballus papillomavirus 2 infection

The aetiology of oral squamous cell carcinoma (SCC) in horses is unknown, but papillomavirus infection as well as chronic periodontal disease are suspected to play a pathogenic role. In humans, some oropharyngeal cancers develop in association with human papillomaviruses. Equus caballus papillomavirus 2 (EcPV2) is suspected to play a causal role in the development of equine genital SCC. Given that association, we hypothesized that EcPV2 is associated with the development of oral SCC in horses. We performed standard polymerase chain reaction (PCR) and in-situ hybridization (ISH) for EcPV2 on 31 formalin-fixed paraffin-embedded equine oral SCCs (lingual, gingival, palate) and 10 equine non-SCC oral samples. PCR for EcPV2 was positive in 10/31 (32%) oral SCCs while all non-SCC oral samples were negative. Intense hybridization signals for EcPV2 nucleic acid were detected by ISH within neoplastic epithelial cells in 8/31 (26%) oral SCCs but not in the adjacent normal oral mucosa. No hybridization signals were detected within control samples. This study provides additional support for a pathogenic association of EcPV2 in oral SCC in horses.

Extrachromosomal DNA-mediated glyphosate resistance in Italian ryegrass.

An Italian ryegrass population from Arkansas, USA developed glyphosate resistance due to 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) gene amplification. The plants in this population with approximately 70 EPSPS copies were used in the present study for the physical mapping of amplified copies of EPSPS gene to determine the possible mechanism of EPSPS gene amplification conferring glyphosate resistance in Italian ryegrass. Fluorescence in situ hybridization (FISH) analysis of glyphosate resistant (GR) Italian ryegrass plants with approximately 70 EPSPS copies displayed EPSPS hybridization signals randomly on most of the metaphase chromosomes. Glyphosate susceptible (GS) Italian ryegrass plants with one EPSPS copy displayed single prominent EPSPS hybridization signal, which was co-localized with 5S rDNA locus along with few additional signals on the outside of chromosomes. Pulsed-field gel electrophoresis (PFGE) followed by DNA blot using EPSPS gene as a probe identified a prominent EPSPS hybridization around the 400 kb region in GR DNA samples, but not in GS DNA samples. We report the extrachromosomal DNA-mediated glyphosate resistance in Italian ryegrass. Physical mapping of amplified copies of EPSPS gene in Italian ryegrass by FISH gives us a clue that the amplified copies of EPSPS gene may be present in the extrachromosomal DNA elements. Further analysis by PFGE followed by DNA blotting revealed that the extrachromosomal DNA containing EPSPS is approximately 400 kb similar in size with that of eccDNA replicon in Amaranthus palmeri. © 2023 Society of Chemical Industry.

A Fast Acquisition Algorithm for Hybrid Signals of 5G and BeiDou B1

With the large-scale use of BeiDou navigation and 5G technology worldwide, integrating BeiDou navigation and communication has become a hot research topic in navigation and positioning technology. Low-cost, miniaturized, and susceptible mixed-signal receivers will become the future receiver technology development trend. However, the current receiver technology still faces the challenge of further improving the positioning service capability and communication quality, which includes the lack of practical analysis of the compatibility between signals and the lack of mixed-signal processing capability of the receiver baseband key technology. To address these problems, we start by analyzing the signal part of 5G out-of-band signals falling into the BD B1 signal band, conduct a detailed analysis of the mixed signal regime and frequency planning, and design a hybrid receiver architecture compatible with both signals, and propose an SC-PMF-FFT fast capture algorithm based on strong correlation, which takes advantage of the strong correlation of signals broadcast on the BD B1 frequency point from B1I to B1C, and reuses the structure of the CDMA system signal capture algorithm to complete the fast capture of 5G signals using an OFDM system. The experiments show that the method can capture the BeiDou B1 signal with a sensitivity of −154 dBm and a whole constellation capture time of no more than 40 ms with the inlet power of the 5G signal not exceeding −45 dBw.

Hybrid High Dynamic Range Imaging fusing Neuromorphic and Conventional Images.

Reconstruction of high dynamic range image from a single low dynamic range image captured by a conventional RGB camera, which suffers from over- or under-exposure, is an ill-posed problem. In contrast, recent neuromorphic cameras like event camera and spike camera can record high dynamic range scenes in the form of intensity maps, but with much lower spatial resolution and no color information. In this paper, we propose a hybrid imaging system (denoted as NeurImg) that captures and fuses the visual information from a neuromorphic camera and ordinary images from an RGB camera to reconstruct high-quality high dynamic range images and videos. The proposed NeurImg-HDR+ network consists of specially designed modules, which bridges the domain gaps on resolution, dynamic range, and color representation between two types of sensors and images to reconstruct high-resolution, high dynamic range images and videos. We capture a test dataset of hybrid signals on various HDR scenes using the hybrid camera, and analyze the advantages of the proposed fusing strategy by comparing it to state-of-the-art inverse tone mapping methods and merging two low dynamic range images approaches. Quantitative and qualitative experiments on both synthetic data and real-world scenarios demonstrate the effectiveness of the proposed hybrid high dynamic range imaging system. Code and dataset can be found at: https://github.com/hjynwa/NeurImg-HDR.

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images

Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer patients who may respond to targeted anti-HER2 therapy. This study aims to develop an automated method for quantifying HER2 fluorescence in situ hybridization (FISH) signals and improve the working efficiency of pathologists. An Aitrox artificial intelligence (AI) model based on deep learning was constructed, and a comparison between the AI model and traditional manual counting was performed. In total, 918 FISH images from 320 consecutive invasive breast cancers were analysed and automatically classified into 5 groups according to the 2018 ASCO/CAP guidelines. The overall classification accuracy was 85.33% (157/184) with a mean average precision of 0.735. In Group 5, the most common group, the consistency was as high as 95.90% (117/122), while the consistency was low in the other groups due to the limited number of cases. The causes of this inconsistency, including clustered HER2 signals, coarse CEP17 signals and some section quality problems, were analysed. The developed AI model is a reliable tool for evaluating HER2 amplification statuses, especially for breast cancer in Group 5; additional cases from multiple centres could further improve the accuracy achieved for other groups.

Genomic evidence reveals high genetic diversity in a narrowly distributed species and natural hybridization risk with a widespread species in the genus Geodorum

BackgroundUnderstanding genetic diversity is a core issue in conservation genetics. However, previous genetic diversity evaluations of narrowly distributed species have rarely used closely related widespread species as a reference. Furthermore, identifying natural hybridization signals between narrowly and widely distributed sympatric species is of great importance for the development of species conservation programs.MethodsIn this study, population genotyping by sequencing (GBS) was performed for a narrowly distributed species, Geodorum eulophioides (endemic and endangered in Southwest China), and a widespread species, G. densiflorum. A total of 18,490 high-quality single nucleotide polymorphisms (SNPs) were identified at the whole-genome level.ResultsThe results showed that the nucleotide diversity and heterozygosity of G. eulophioides were significantly higher than those of G. densiflorum, confirming that narrowly distributed species can still preserve high genetic diversity. Consistent with taxonomic boundaries, all sampled individuals from the two species were divided into two genetic clusters and showed high genetic differentiation between species. However, in a sympatric population, a few G. eulophioides individuals were detected with genetic components from G. densiflorum, suggesting potential interspecific natural hybridization. This hypothesis was supported by Treemix analysis and hand-hybridization trials. Invasion of the habitat of G. eulophioides invasion by G. densiflorum under anthropogenic disturbance may be the main factor causing interspecific hybridization.ConclusionsTherefore, reducing or avoiding habitat disturbance is a key measure to protect the G. eulophioides populations. This study provides valuable information for future conservation programs for narrowly distributed species.