Tool For Identification Research Articles

DNA barcoding: An effective molecular tool for species identification, molecular authentication and phylogeny studies in plant science research

DNA barcoding is a technique for identifying specimens using brief, standardised DNA segments. In a variety of fields, including phylogeny, ecology, population genetics and biodiversity, DNA barcoding has become a successful method for precisely distinguishing species. The method is straightforward, efficient in both time and money and accurate. The key to successful DNA barcoding is choosing the right DNA marker. Since the idea of a quick approach for species identification was first put up in 2003, the scientific community has been keen to realise the potential of DNA barcodes. Cytochrome c oxidase, I (COI) region of the mitochondrial genome is mostly recognised as a standard barcoding region in animals. Later, rbcL + matK pairing, with a 70 % discriminating efficiency, was suggested by the Plant Working Group (PWG) of the Consortium for the Barcoding of Life (CBOL) as the standard barcode in plants. Three conditions must be met for a gene region to be an efficient DNA barcode: it must have sufficient species-level genetic divergence and variability, it must have conserved flanking regions for the widest taxonomic use and for generating universal PCR primers and it should be long enough to facilitate current capability for sequencing and extracting DNA. Different combinations of plastid coding, non-coding and nuclear markers are utilised as supplemental markers to boost the degree of plant species differentiation. The reliability of different barcodes in distinguishing species varies among different groups of plants. As DNA barcoding approaches its twentieth anniversary, technologies are still being developed that make use of this resource, which is constantly expanding in a variety of biological disciplines. Plant DNA barcoding, which became a scientific advance during the last ten years, is frequently employed as a taxonomical aid in identifying species. It is a way of choosing genetic loci that identifies and distinguishes an organism's membership from specific species, variations or even intervarieties. It varies from molecular phylogeny, which identifies an unknown sample from an existing classification rather than identifying patterns of association.

Chiral fluorescent carbon dots for tyrosine enantiomers: Discrimination, mechanism and cell imaging

The development of chiral analytical methods for tyrosine enantiomers, characterized by superior recognition performance and selectivity, holds significant potential for application in the biochemical and biomedical domains associated with tyrosine. Herein, a straightforward and effective strategy for tyrosine enantiomers identification and purity analysis by chiral carbon dots (CDs) fluorescence sensor were reported. The chiral CDs were designed by using L-cysteine and 2,4-diaminophenol hydrochloride through a gentle one-step synthesis strategy at room temperature. The resulting chiral CDs exhibited completely different fluorescence response to L-tyrosine and D-tyrosine, that is, L-tyrosine could enhance the fluorescence of the chiral CDs, but D-tyrosine made no difference. The fluorescent differential recognition factor for enantiomers was as high as 23.2, which was the highest be achievement to our best knowledge so far. The varying discriminatory capabilities of chiral CDs towards tyrosine enantiomers were also applicable to HeLa cells. To confirm the recognition mechanism of chiral CDs to tyrosine enantiomers, the chiral CDs-modified SiO2 stationary phase were synthesized and applied to separate the tyrosine enantiomers in reverse-phase HPLC mode. Furthermore, density functional theory was combined with the fluorescence spectroscopy and chromatographic results to verify that the recognition ability was related to the difference of weak interaction energy and Gibbs free energy between the precursor molecule of the chiral CDs and the tyrosine enantiomers. This cost-effective and highly selectivity assay not only provided a valuable tool for tyrosine enantiomers identification and purity analysis, but also delivered an important reference for the recognition and purity identification of other chiral drugs.

Development of SSR markers for genetic diversity analysis and species identification in Polygonatum odoratum (Mill.) Druce based on transcriptome sequences.

Polygonatum odoratum (Mill.) Druce is a well-known traditional Chinese herb belonging to the Polygonatum. However, the understanding of the genetic diversity of this species at the molecular level is limited due to the lack of transcriptomic and genomic information. In this study, 37,387 unigenes were assembled based on the transcriptome sequencing of the rhizome of Polygonatum odoratum (Mill.) Druce., and 11,021 single- sequence repeats (SSR) motifs, mainly consisting of single-nucleotide repeats (44.44%), dinucleotides (31.06%), and trinucleotides (22.59%), were identified. Based on these SSR motifs, 9,987 primer pairs of SSR markers were designed and 68 SSR markers were randomly selected for verification, of which 21 SSR markers showed polymorphisms among the 24 Polygonatum odoratum germplasms. Ninety-four alleles were detected: the observed alleles ranged from 2 to 11, the effective alleles varied from 1.086 8 to 4.916 8, the Shannon diversity index was 0.173 2~1.749 7, and the polymorphism information content PIC ranged from 0.076 7 to 0.803 9. Based on our analysis of genetic diversity (SSR genotypes) and population structure, we divided the 24 germplasm resources into two groups, indicating that the germplasm with similar geographical origins can be grouped together. In addition, the primers 'YZ14' and 'YZ47' could effectively distinguished the related species: Polygonatum kingianum Coll.et Hemsl., Polygonatum sibiricum Red., Polygonatum cyrtonema Hua, Polygonatum zanlanscianense Pamp. and Polygonatum odoratum (Mill.) Druce. This is the first study in which a dataset of expressed sequence tag (EST)-SSR markers is constructed for the Polygonatum odoratum (Mill.) Druce, and these newly developed EST-SSR markers provided a very efficient tool for genetic relationship analysis, species identification and marker-assisted selection breeding of Polygonatum odoratum (Mill.) Druce.

Preclinical Evaluation of Electronic Health Records (EHRs) to Predict Poor Control of Chronic Respiratory Diseases in Primary Care: A Novel Approach to Focus Our Efforts.

Background/Objectives: Managing chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD) within the Spanish Sistema Nacional de Salud (SNS) presents significant challenges, particularly due to their high prevalence and poor disease control rates-approximately 45.1% for asthma and 63.2% for COPD. This study aims to develop a novel predictive model using electronic health records (EHRs) to estimate the likelihood of poor disease control in these patients, thereby enabling more efficient management in primary care settings. Methods: The Seleida project employed a bioinformatics approach to identify significant clinical variables from EHR data in primary care centers in Seville and Valencia. Statistically significant variables were incorporated into a logistic regression model to predict poor disease control in patients with asthma and COPD patients. Key variables included the number of short-acting β-agonist (SABA) and short-acting muscarinic antagonist (SAMA) canisters, prednisone courses, and antibiotic courses over the past year. Results: The developed model demonstrated high accuracy, sensitivity, and specificity in predicting poorly controlled disease in both asthma and COPD patients. These findings suggest that the model could serve as a valuable tool for the early identification of at-risk patients, allowing healthcare providers to prioritize and optimize resource allocation in primary care settings. Conclusions: Integrating this predictive model into primary care practice could enhance the proactive management of asthma and COPD, potentially improving patient outcomes and reducing the burden on healthcare systems. Further validation in diverse clinical settings is warranted to confirm the model's efficacy and generalizability.

Non-invasive identification of historical textiles and leather by means of external reflection FTIR spectroscopy

Identifying the fibres in historical textiles presents a complex challenge due to the wide variety of plant, animal and early synthetic materials that have been used. Traditionally, this identification process involves sampling followed by either microscopic examination or ATR-FTIR spectroscopy. However, there are instances when sampling is restricted due to the good condition or significant value of the object under analysis. Additionally, the presence of leather components alongside textiles can further complicate the identification. This paper proposes a novel non-invasive method for fibre identification based on External Reflection (ER) FTIR spectroscopy, which has been rarely applied to textiles or leather. The current research demonstrates that ER-FTIR spectrum is a viable tool for fibre identification on both recent and historical textiles. The non-invasiveness of the analytical approach enables a comprehensive investigation without compromising the number or position of samples. Respect to ATR-FTIR spectra, the ER-FTIR spectra frequently exhibit an amplification of certain diagnostic bands, facilitating the identification of the various fibres examined in this study (cotton, hemp, viscose, silk, wool, leather, polyamide, acrylic, polyester). The extended spectral range (7500–375 cm−1) which is provided by ER-FTIR spectrometry also contains extra bands in the near infrared region, which can provide key information for the discrimination due to the lack of distortion phenomena. The technique was applied to the characterisation of textile materials coming from a collection of 10 traditional Japanese samurai armours spanning from the 16th to the 20th century (Museo delle Culture, Lugano, Switzerland). For the first time, the results provided a comprehensive overview of the textiles utilized in Japanese armours across various historical periods. Overall, the appearance of materials in samurai armours reflects the evolution of armour-making techniques and the influence of socio-cultural factors throughout Japanese history. Synthetic and semi-synthetic materials were easily detected, revealing the occurrence of a past conservation treatment or the early adoption of modern man-made materials in the manufacturing of traditional armours. The approach outlined in this case study can be applied to textile collections of various kinds, offering a reliable mean to discern the yarn composition and detect non-original components. The method also appears as a valuable prescreening tool for designing a less intrusive yet more informative sampling strategy, should additional details about fibre type and dyeing be necessary.

Evaluating the prognostic performance of the novel ERAP score in Vietnamese acute pancreatitis patients.

Early recognition of severe acute pancreatitis (AP) is crucial for timely intervention. This study aims to evaluate the prognostic accuracy of the Emergency Room Assessment of AP (ERAP) score and compare it with the Bedside Index for Severity in AP (BISAP) score in predicting severe AP, mortality, and persistent multiple organ failure (MOF) in Vietnamese patients. This prospective cohort study included AP patients admitted to Cho Ray Hospital between August 2021 and May 2022. Patient data, including demographics, clinical presentations, and laboratory results, were collected upon admission. The ERAP and BISAP scores were calculated from these admission data. The prognostic accuracy for severe AP, mortality, and persistent MOF was assessed via the area under the receiver-operating characteristic curve (AUC). Among 167 AP patients (mean age 41.5 ± 12.0 years), hypertriglyceridemia (34.7%) and alcohol (22.2%) were the most prevalent etiologies. Severe AP accounted for 33.5% of the patients. Mortality rates were higher in persistent MOF patients (42.9%) than in persistent single-organ failure patients (3.6%), with a P value <.001. The ERAP score had AUCs for predicting severe AP, mortality, and persistent MOF of 0.899, 0.817, and 0.867, respectively, with an optimal cutoff of ≥2. The ERAP score had a better prognostic value than the BISAP score in predicting severe AP (AUC: 0.899 vs 0.820; P = .0072) and persistent MOF (AUC: 0.867 vs 0.785; P = .0193) but had a similar prognostic value for mortality (AUC: 0.817 vs 0.728; P = .0628). The ERAP score has strong predictive value for severe AP and persistent MOF, surpassing the BISAP score in these categories while maintaining similar accuracy for mortality prediction in the Vietnamese population. The ERAP score can be a valuable tool for the early identification of high-risk AP patients, enabling timely and appropriate clinical interventions.

Construction and validation of a dynamic nomogram using Lasso-logistic regression for predicting the severity of severe fever with thrombocytopenia syndrome patients at admission

BackgroundSevere fever with thrombocytopenia syndrome (SFTS) is a highly fatal infectious disease caused by the SFTS virus (SFTSV), posing a significant public health threat. This study aimed to construct a dynamic model for the early identification of SFTS patients at high risk of disease progression.MethodsAll eligible patients enrolled between April 2014 and July 2023 were divided into training and validation sets. Thirty-four clinical variables in the training set underwent analysis using least absolute shrinkage and selection operator (LASSO) logistic regression. Selected variables were then input into the multivariate logistic regression model to construct a dynamic nomogram. The model’s performance was assessed using the area under the receiver operating characteristic curve (AUC-ROC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) in both training and validation sets. Kaplan-Meier survival analysis was utilized to evaluate prognostic performance.Results299 SFTS patients entered the final investigation, with 208 patients in the training set and 90 patients in the validation set. LASSO and the multivariate logistic regression identified six significant prediction factors: age (OR, 1.060; 95% CI, 1.017–1.109; P = 0.007), CREA (OR, 1.017; 95% CI, 1.003–1.031; P = 0.019), PT (OR, 1.765; 95% CI, 1.175–2.752; P = 0.008), D-dimer (OR, 1.039; 95% CI, 1.005–1.078; P = 0.032), nervous system symptoms (OR, 8.244; 95% CI, 3.035–26.858; P < 0.001) and hemorrhage symptoms (OR, 3.414; 95% CI, 1.096–10.974; P = 0.035). The AUC-ROC, C-index, calibration plots, and DCA demonstrated the robust performance of the nomogram in predicting severity at admission, and Kaplan-Meier survival analysis indicated its utility in predicting 28-day mortality among SFTS patients. The dynamic nomogram is accessible at https://sfts.shinyapps.io/SFTS_severity_nomogram/.ConclusionThis study provided a practical and readily applicable tool for the early identification of high-risk SFTS patients, enabling the timely initiation of intensified treatments and protocol adjustments to mitigate disease progression.

The first detection of SARS-CoV-2 RNA in the wastewater of Bucharest, Romania

Wastewater-based epidemiology (WBE) has been previously used as a tool for pathogen identification within communities. After the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak, in 2020, Daughton proposed the implementation of a wastewater surveillance strategy that could determine the incidence of COVID-19 (coronavirus disease 2019) nationally. Individuals in various stages of SARS-CoV-2 infection, including presymptomatic, asymptomatic and symptomatic patients, can be identified as carriers of the virus in their urine, saliva, stool and other bodily secretions. Studies using this method were conducted to monitor the prevalence of the virus in high-density populations, such as cities but also in smaller communities, such as schools and college campuses. The aim of this pilot study was to assess the feasibility and effectiveness of wastewater surveillance in Bucharest, Romania, and wastewater samples were collected weekly from seven locations between July and September 2023. RNA (ribonucleic acid) extraction, followed by dPCR (digital polymerase chain reaction) analysis, was performed to detect viral genetic material. Additionally, NGS (next generation sequencing) technology was used to identify the circulating variants within the wastewater of Bucharest, Romania. Preliminary results indicate the successful detection of SARS-CoV-2 RNA in wastewater, providing valuable insights into the circulation of the virus within the community.

Matters of assuring functional dependability compliance of digital manufacturing

Aim. To propose a methodological approach to ensuring the functional dependability of industrial facilities using SMART documents in the context of import-independent digital processes. Methods. The evolving applicability of the dependability theory and information systems design has defined the methodological provisions for algorithmising the application of SMART standards for minimising functional faults and failures of industrial processes. Digital models of production lines were examined as tools for machine-recognisable representation of standards. The proposed form of regulatory documents is intended to enable the transition from machine-readable data to machine-understandable content. Findings. The application of the proposed methods of content systematisation in the context of manufacturing process standardisation shows that the classification of process data based on standardised characteristics of digital information exchange processes is one of the key methodological provisions ensuring unambiguous interpretation of regulatory requirements. Specialised projects often use individual provisions rather than complete regulatory documents. In this case, in order to ensure machine-understandability of the developed content, it is proposed using special identifiers, e.g., «paragraph», «graphic object», «table cell». The deployment of such identification tools will allow creating a class of SMART standards that collect into a single document the provisions regarding the delivery of intended results in situations when the operating equipment is diverse. Publications created using intelligent processing of SMART documents are considered as containers of structured and unstructured data that take into account the conditions of particular projects. The existing dynamics of the demand for advanced industrial products often determines the admissibility of its industrial production by various companies with the parallel use of unique technologies. The conditions of such an organisation impose their limitations on the comparability of various process requirements, therefore, it is proposed to harmonise the presentation of the results of managerial, design, and process engineering solutions using the term «manufacturing system asset». The introduction of relative result estimates as part of the digital format is an efficient mechanism for ensuring management consistency. In this context, the importance of a uniform regulatory framework as the foundation for such assessments is growing. As one of the ways of minimising faults and failures of industrial equipment, it is proposed to create a situation centre with a decision support system based on the regulatory data with harmonised manufacturing system asset requirements. An experience of Industry 4.0 regulation is described in the review of the ISA digital manufacturing series of standards. It was shown that the deployment of SMART standards improves the stability of interaction between information management systems and the functional dependability of production lines. The introduction of provisions regulating the use of algorithms for the development, editing, and examination of draft regulatory documents into the content machine-understandability facilities is an important factor in ensuring the functional dependability of products. Conclusions. The presented approach is focused on the methodology for developing standards that take into account requirements from various subject areas. In the context of ongoing import substitution in manufacturing, the paper examines the feasibility of minimizing digital process faults and failures caused by the use of regulatory frameworks that are not equivalent to the provisions of international documents and take into account the specificity of Russian industrial systems.

A comprehensive guide to bioinformatics tools and databases

The interest in the functional aspects of the genome has increased eventually with the expansion of genomic databases. In this review, various genetic alterations within the genome, such as Single Nucleotide Polymorphisms (SNPs), disease-associated mutations, neutral polymorphisms, and small insertions or deletions (INDELs), have been identified and characterized. These polymorphisms, particularly SNPs, have become widely employed in genetic analyses, serving as valuable molecular markers. They are applied across diverse genetic studies, including the reconstruction of haplotypes. In addition to experimental methods for investigating specific genetic variants, there has been a significant surge in bioinformatics research over the past decade, aimed at the molecular consequences of these genetic alterations. Haplotypes, which represent various alleles of a gene, can be reconstructed not only for entire chromosomes but also for specific genes, utilizing the information derived from SNPs. The computational approach to SNP and haplotype discovery has gained prominence due to the continuous expansion of sequence data within public databases. This growth enables more precise identification of SNPs. This article aims to introduce easily accessible and practical online tools for researchers. In summary, SNP and haplotype identification tools are indispensable in bioinformatics for studying genetic variation, population genetics, disease associations, and personalized medicine. They provide valuable insights into the genetic underpinnings of various traits and diseases, helping advance our understanding of genetics and its applications in healthcare.

Quantifying rain-driven NO3-N dynamics in headwater: value of applying SISO system identification to multiple variables monitored at the same high frequency

The nitrate–nitrogen (NO3-N) concentration is a key variable affecting the ecosystem services supported by headwater streams. The availability of such data monitored continuously at a high frequency (in parallel to hydrometric and other water quality data) potentially permits a greater insight into the dynamics of this key variable. This study demonstrates how single-input single-output (SISO) system identification tools can make better use of these high-frequency data to identify a reduced number of numerical characteristics that support new explanatory hypotheses of rain-driven NO3-N dynamics. A second-order watershed managed for commercial forestry in upland Wales (United Kingdom) provided the illustrative data. Fifteen-minute rainfall time series were used to simulate NO3-N concentration dynamics and the potentially associated dynamics in dissolved organic carbon (DOC) and runoff, monitored at the same high resolution for two 30-day periods with a differing temperature regime. The approach identified robust, high-efficiency models needing few parameters. Comparison of only three derived dynamic response characteristics (DRCs) of δ, TC, and SSG for the three variables for the two different periods led to new hypotheses of rain-driven NO3-N dynamics for further exploratory field investigation.

Prevalence of anatomic variations of temporomandibular joint on orthopantomogram and cone-beam computed tomography: A retrospective study

Maxillofacial radiography by means of orthopantamogram is used as a routine screening tool in the diagnosis and treatment planning in various fields of dentistry and is found to be less expensive when compared to other advanced imaging modalities like computed tomography, magnetic resonance imaging and cone-beam computed tomography. Morphological variations in the shape of mandibular condyle, coronoid process and sigmoid notch have been documented in the literature as indispensable aids in anthropological and forensic studies. 100 OPG and CBCT scans of same participants, comprising of 200 temporo-mandibular joints were evaluated for anatomical variations in shapes of mandibular condyle, coronoid process and sigmoid notch. The prevalence of various morphological variations were correlated with age and gender and subjected to statistical analysis. The most common shape of condyle, coronoid process and sigmoid notch on OPG was round, whereas on CBCT the most common shape of condyle, coronoid process and sigmoid notch were flat, triangular and wide respectively. Variations in the morphology of shape of mandibular condyle, coronoid process and sigmoid notch using panoramic radiographs can be tentatively used as a screening tool in human identification, owing to its ready availability and low cost.

Abstract A028: MTAP deficiency is frequent and mostly homogeneous in ductal adenocarcinomas of the pancreas

Abstract Complete expression loss of S-methyl-5′-thioadenosine phosphorylase (MTAP) is caused by homozygous 9p21 deletion and results in a critical vulnerability of cancer cells towards drugs targeting multiple different pathways. MTAP deficiency is common in ductal adenocarcinoma of the pancreas, but data on its intratumoral heterogeneity - a potential obstacle for targeted therapies - are lacking. To learn more on the role and potential heterogeneity of MTAP deficiency in pancreatic adenocarcinoma, 236 primary tumors were analyzed in a tissue microarray (TMA) format by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) for MTAP expression and 9p21 deletions. The cohort included 236 cancers from which 6 samples were taken from as many as possible different tumor containing primary tumor blocks and 3 samples were added from as many as possible lymph node metastases to construct a “heterogeneity TMA”. All available tumor containing blocks (average 4) from 6 selected cancers were also analyzed by IHC and FISH on whole sections. Complete absence of MTAP staining was seen in 350 (38.6%) of 907 interpretable TMA samples. 284 (98.6%) of 288 samples with a complete MTAP expression loss and FISH data had a homozygous 9p21 deletion while there were only two tumor spots with homozygous deletions within 557 samples with retained MTAP expression (99.6% concordance). On a patient level, an MTAP deficiency was found in 64 (41.0%) of 156 tumors for which at least 3 different samples were interpretable on the TMAs. 62 (96.9%) of these patients showed an MTAP loss in all interpretable samples (homogeneous MTAP deficiency). The TMA data were confirmed on whole sections in 5 of 6 patients. In the discrepant case a focal MTAP loss was identified in a tumor considered MTAP wild type based on the TMA results. It is concluded that MTAP expression loss is frequent and highly homogeneous in ductal adenocarcinomas of the pancreas. Given the high concordance rate between homozygous deletion and MTAP expression loss homozygous deletion may represent the only mechanism for MTAP deficiency in pancreatic cancer. MTAP IHC is an excellent tool for identification of MTPA deficient cases. MTAP IHC may also have considerable diagnostic value as even low-grade cancer glands can be easily identified in small biopsies from MTAP deficient cases. Considering also their aggressive clinical behavior, pancreatic adenocarcinomas may represent an ideal cancer type for studying new drugs targeting MTAP deficient cancer cells in clinical trials. Citation Format: Natalia Gorbokon, Katharina Teljuk, Frank Jacobsen, Till Krech, Till Clauditz, Stefan Steurer, Ronald Simon, Guido Sauter, Sarah Minner, Lukas Bubendorf, Thilo Hackert, Nina Schraps, Faik G Uzunoglu, Martina Kluth. MTAP deficiency is frequent and mostly homogeneous in ductal adenocarcinomas of the pancreas [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A028.

Research on the Wild Mushroom Recognition Method Based on Transformer and the Multi-Scale Feature Fusion Compact Bilinear Neural Network

Wild mushrooms are popular for their taste and nutritional value; however, non-experts often struggle to distinguish between toxic and non-toxic species when foraging in the wild, potentially leading to poisoning incidents. To address this issue, this study proposes a compact bilinear neural network method based on Transformer and multi-scale feature fusion. The method utilizes a dual-stream structure that integrates multiple feature extractors, enhancing the comprehensiveness of image information capture. Additionally, bottleneck attention and efficient multi-scale attention modules are embedded to effectively capture multi-scale features while maintaining low computational costs. By employing a compact bilinear pooling module, the model achieves high-order feature interactions, reducing the number of parameters without compromising performance. Experimental results demonstrate that the proposed method achieves an accuracy of 98.03%, outperforming existing comparative methods. This proves the superior recognition performance of the model, making it more reliable in distinguishing wild mushrooms while capturing key information from multiple dimensions, enabling it to better handle complex scenarios. Furthermore, the development of public-facing identification tools based on this method could help reduce the risk of poisoning incidents. Building on these findings, the study suggests strengthening the research and development of digital agricultural technologies, promoting the application of intelligent recognition technologies in agriculture, and providing technical support for agricultural production and resource management through digital platforms. This would provide a theoretical foundation for the innovation of digital agriculture and promote its sustainable development.

Low-cost and simple PCR process for access to molecular diagnosis of HTLV-1/2 in low-resource countries

BackgroundHTLV-1/2 exhibit a widespread distribution globally and are associated with severe clinical manifestations, necessitating precise viral identification for diagnosis. Currently, there are no official diagnostic guidelines, and a variety of published protocols exists. We introduce an enhanced nested real-time PCR technique followed by high-resolution melting (rtPCR-HRM), designed to offer a cost-effective and straightforward tool for the simultaneous identification of both viruses. MethodsThe technique was tested in a retrospective, blinded study, involving a total panel of 110 samples, of which 47 were positive for HTLV-1, 12 for HTLV-2, and 51 tested negatives. Additionally, we compared the performance of this technique with a line immunoassay (LIA). ResultsThe results demonstrate 100 % sensitivity, specificity, and diagnostic accuracy for both viruses. Sensitivity analysis indicated that at least 1 viral copy of HTLV-1 and 14.4 viral copies of HTLV-2 could be reliably detected. ConclusionsOur results indicate that rtPCR-HRM is effective in confirming HTLV-1 and HTLV-2 infection, important in Latin American countries where both viruses circulate. Furthermore, the proposed strategy provides a new tool that can be used to resolve indeterminate cases identified by Western blot, with the added advantage of being faster and simpler than n-PCR and more cost-effective than other probe-based RT-PCRs.

PSVII-10 Genome-wide discovery and characterization of short interspersed nuclear elements (SINEs) in the bovine genome

Abstract Short interspersed nuclear elements (SINEs) constitute a class of nonautonomous retrotransposons endowed with the capability to multiply and spread within a genome. SINEs serve as reliable indicators for assessing genetic variability in dairy populations, aiding in precise determination of breed composition. However, SINEs within the bovine genome remain insufficiently characterized, hindering the understanding of their impact on dairy production and health. This study aimed to systematically identify, classify and unveil the characteristics of SINEs within the bovine reference genome (ARS-UCD1.3). Multiple de novo identification tools, including RepeatModeler, SINE_scan, LongRepMarker, and SINE-finder, were employed for SINE identification and characterization. A total of 1.6 million copies of SINEs were identified, constituting approximately 10.8% of the genome. The SINEs were stratified into seven distinct families based on their structural attributes, denoted as BosSINEL, BosSINE1, BosSINE2, BosSINE3, BosSINE4, BosSINE5 and BosSINE6. BosSINE1 represents a novel family, whereas the remaining six families were previously documented in Repbase. Among these families, BosSINE3 emerges as the most prolific, boasting 254,586 complete copies (over 80% of the length of the consensus sequence), followed by BosSINEL (164,538 copies), BosSINE2 (162,207 copies) and BosSINE1 (150,799 copies). Conversely, the remaining families exhibit lower abundance, each harboring no more than 100,000 copies within the genome. Structural comparisons among SINE families elucidate distinctive features. Notably, BosSINEL lacks a tRNA-related region, including boxA and boxB, which is the hallmark element of the classic SINE structure according to SINEBase. Conversely, all other families exhibit tRNA-related regions. BosSINE1, the lengthiest at 328 bp (excluding Poly-A), possesses two tRNA-related regions, distinguishing it from other families. BosSINEL, BosSINE1, BosSINE2 and BosSINE3 exhibit long interspersed nuclear elements (LINE)-related regions, suggesting their retrotransposition by engaging with the enzymatic machinery encoded by LINEs. In contrast, BosSINE6, the shortest at 109 bp, features a GC-rich region resulting in a high GC content of 67%. Additionally, BosSINE4 contains an AT-rich region. Evolutionary analysis disclosed that BosSINEL is the youngest SINE family in the bovine genome, potentially still harboring active roles and contributing to the genetic diversity related to different dairy production and health performance. Conversely, BosSINE1 to BosSINE6 are comparatively aged in terms of evolution, likely fixed in the bovine genome with diminished or lost activities. In summary, this investigation unveils the comprehensive profile of SINE in the bovine genome, delineating both structural and evolutionary characteristics. Particularly noteworthy is the emergence of BosSINEL as the youngest SINE family, suggesting active roles in the bovine genome. Since lineage-specific TEs (such as Bov-A2 elements) have been reported to regulate interferon-inducible gene expression in bovine, our data warrants further investigations to reveal the potential of SINEs as markers for improving dairy production and health.

Thromboelastography as an early prediction method for hypofibrinogenemia in emergency department patients with primary postpartum hemorrhage

BackgroundTimely and accurate assessment of coagulopathy is crucial for the management of primary postpartum hemorrhage (PPH). Thromboelastography (TEG) provides a comprehensive assessment of coagulation status and is useful for guiding the treatment of hemorrhagic events in various diseases. This study aimed to evaluate the role of TEG in predicting hypofibrinogenemia in emergency department (ED) patients with primary PPH.MethodsWe conducted a retrospective observational study in the ED of a university-affiliated tertiary hospital between November 2015 and August 2023. TEG was performed upon admission. The cutoff value for hypofibrinogenemia was 200 mg/dL. The primary outcome was the presence of hypofibrinogenemia.ResultsAmong the 174 patients, 73 (42.0%) had hypofibrinogenemia. The need for massive transfusion was higher in the hypofibrinogenemia group (37.0% vs. 5.0%, p < 0.001). Among the TEG parameters, all values were significantly different between the groups, except for lysis after 30 min, suggesting a tendency toward hypocoagulability. Multivariable analysis revealed that the alpha angle (odds ratio (OR) 0.924, 95% confidence interval (CI) 0.876–0.978) and maximum amplitude (MA) (OR 0.867, 95% CI 0.801–0.938) were independently associated with hypofibrinogenemia. The optimal cutoff values for the alpha angle and maximum amplitude (MA) for hypofibrinogenemia were 63.8 degrees and 56.1 mm, respectively.ConclusionPoint-of-care TEG could be a valuable tool for the early identification of hypofibrinogenemia in ED patients with primary PPH.

Landscape of the metaplasmidome of deep-sea hydrothermal vents located at Arctic Mid-Ocean Ridges in the Norwegian-Greenland Sea: ecological insights from comparative analysis of plasmid identification tools.

Plasmids are one of the key drivers of microbial adaptation and evolution. However, their diversity and role in adaptation, especially in extreme environments, remains largely unexplored. In this study, we aimed to identify, characterize, and compare plasmid sequences originating from samples collected from deep-sea hydrothermal vents located in Arctic Mid-Ocean Ridges. To achieve this, we employed, and benchmarked three recently developed plasmid identification tools-PlasX, GeNomad, and PLASMe-on metagenomic data from this unique ecosystem. To date, this is the first direct comparison of these computational methods in the context of data from extreme environments. Upon recovery of plasmid contigs, we performed a multiapproach analysis, focusing on identifying taxonomic and functional biases within datasets originating from each tool. Next, we implemented a majority voting system to identify high-confidence plasmid contigs, enhancing the reliability of our findings. By analysing the consensus plasmid sequences, we gained insights into their diversity, ecological roles, and adaptive significance. Within the high-confidence sequences, we identified a high abundance of Pseudomonadota and Campylobacterota, as well as multiple toxin-antitoxin systems. Our findings ensure a deeper understanding of how plasmids contribute to shaping microbial communities living under extreme conditions of hydrothermal vents, potentially uncovering novel adaptive mechanisms.

Focal cortical dysplasia lesion segmentation using multiscale transformer

ObjectivesAccurate segmentation of focal cortical dysplasia (FCD) lesions from MR images plays an important role in surgical planning and decision but is still challenging for radiologists and clinicians. In this study, we introduce a novel transformer-based model, designed for the end-to-end segmentation of FCD lesions from multi-channel MR images.MethodsThe core innovation of our proposed model is the integration of a convolutional neural network-based encoder-decoder structure with a multiscale transformer to augment the feature representation of lesions in the global field of view. Transformer pathways, composed of memory- and computation-efficient dual-self-attention modules, leverage feature maps from varying depths of the encoder to discern long-range interdependencies among feature positions and channels, thereby emphasizing areas and channels relevant to lesions. The proposed model was trained and evaluated on a public-open dataset including MR images of 85 patients using both subject-level and voxel-level metrics.ResultsExperimental results indicate that our model offers superior performance both quantitatively and qualitatively. It successfully identified lesions in 82.4% of patients, with a low false-positive lesion cluster rate of 0.176 ± 0.381 per patient. Furthermore, the model achieved an average Dice coefficient of 0.410 ± 0.288, outperforming five established methods.ConclusionIntegration of the transformer could enhance the feature presentation and segmentation performance of FCD lesions. The proposed model has the potential to serve as a valuable assistive tool for physicians, enabling rapid and accurate identification of FCD lesions. The source code and pre-trained model weights are available at https://github.com/zhangxd0530/MS-DSA-NET.Critical relevance statementThis multiscale transformer-based model performs segmentation of focal cortical dysplasia lesions, aiming to help radiologists and clinicians make accurate and efficient preoperative evaluations of focal cortical dysplasia patients from MR images.Key PointsThe first transformer-based model was built to explore focal cortical dysplasia lesion segmentation.Integration of global and local features enhances the segmentation performance of lesions.A valuable benchmark for model development and comparative analyses was provided.Graphical

Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches

Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches