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The surface-enhanced Raman scattering (SERS) technique provides outstanding molecular fingerprint identification and high sensitivity of analytes. Herein, colloidal sphere-shaped gold nanoparticles (Au-NPs) trapped in concentric rings of the Bessel beam generated from the optical fiber-based negative axicon has been reported as a SERS substrate. With the trapping of Au-NPs, the SERS ability of colloidal Au-NPs improved, and the average enhancement factor (AEF) of the rhodamine-6G (R6G) and 4-aminothiophenol (4-ATP) molecules can reach up to the order of 107. Control experiments were also carried out with the trapping of Au-NPs by Gaussian beam illumination, without any illumination of the light and with the trapping of Au-NPs by the Bessel beam illumination on a silver (Ag)-coated silicon (Si) substrate with a self-assembled monolayer (SAM) of 4-ATP. Theoretical studies were also carried out using the finite element method (FEM) to identify the hotspots generated in the gaps formed between the Au-NPs, leading to an enhancement in the SERS signal of the molecules, and the results were consistent with the experimentally determined AEFs. The obtained results demonstrate that the proposed SERS technique is stable. This study has significant potential applications in clinical diagnosis, food safety, environment safety, chemical sensing, and biosensing. [ABSTRACT FROM AUTHOR]

[Display omitted] • Our dataset is sourced from multiple datasets representing different species, ensuring an ample quantity and quality of samples. • We employ two different representation methods and incorporate a global attention mechanism. • We extract shared features for multiple tasks through two fully connected layers and create separate output layers for each task. With the escalating menace of organic compounds in environmental pollution imperiling the survival of aquatic organisms, the investigation of organic compound toxicity across diverse aquatic species assumes paramount significance for environmental protection. Understanding how different species respond to these compounds helps assess the potential ecological impact of pollution on aquatic ecosystems as a whole. Compared with traditional experimental methods, deep learning methods have higher accuracy in predicting aquatic toxicity, faster data processing speed and better generalization ability. This article presents ATFPGT-multi, an advanced multi-task deep neural network prediction model for organic toxicity. The model integrates molecular fingerprints and molecule graphs to characterize molecules, enabling the simultaneous prediction of acute toxicity for the same organic compound across four distinct fish species. Furthermore, to validate the advantages of multi-task learning, we independently construct prediction models, named ATFPGT-single, for each fish species. We employ cross-validation in our experiments to assess the performance and generalization ability of ATFPGT-multi. The experimental results indicate, first, that ATFPGT-multi outperforms ATFPGT-single on four fish datasets with AUC improvements of 9.8%, 4%, 4.8%, and 8.2%, respectively, demonstrating the superiority of multi-task learning over single-task learning. Furthermore, in comparison with previous algorithms, ATFPGT-multi outperforms comparative methods, emphasizing that our approach exhibits higher accuracy and reliability in predicting aquatic toxicity. Moreover, ATFPGT-multi utilizes attention scores to identify molecular fragments associated with fish toxicity in organic molecules, as demonstrated by two organic molecule examples in the main text, demonstrating the interpretability of ATFPGT-multi. In summary, ATFPGT-multi provides important support and reference for the further development of aquatic toxicity assessment. All of codes and datasets are freely available online at https://github.com/zhaoqi106/ATFPGT-multi. [ABSTRACT FROM AUTHOR]

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Copyright of Rechtsmedizin is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

MLinvitroTox is an automated Python pipeline developed for high-throughput hazard-driven prioritization of toxicologically relevant signals detected in complex environmental samples through high-resolution tandem mass spectrometry (HRMS/MS). MLinvitroTox is a machine learning (ML) framework comprising 490 independent XGBoost classifiers trained on molecular fingerprints from chemical structures and target-specific endpoints from the ToxCast/Tox21 invitroDBv4.1 database. For each analyzed HRMS feature, MLinvitroTox generates a 490-bit bioactivity fingerprint used as a basis for prioritization, focusing the time-consuming molecular identification efforts on features most likely to cause adverse effects. The practical advantages of MLinvitroTox are demonstrated for groundwater HRMS data. Among the 874 features for which molecular fingerprints were derived from spectra, including 630 nontargets, 185 spectral matches, and 59 targets, around 4% of the feature/endpoint relationship pairs were predicted to be active. Cross-checking the predictions for targets and spectral matches with invitroDB data confirmed the bioactivity of 120 active and 6791 nonactive pairs while mislabeling 88 active and 56 non-active relationships. By filtering according to bioactivity probability, endpoint scores, and similarity to the training data, the number of potentially toxic features was reduced by at least one order of magnitude. This refinement makes the analytical confirmation of the toxicologically most relevant features feasible, offering significant benefits for cost-efficient chemical risk assessment. Scientific Contribution: In contrast to the classical ML-based approaches for toxicity prediction, MLinvitroTox predicts bioactivity for HRMS features (i.e., distinct m/z signals) based on MS2 fragmentation spectra rather than the chemical structures from the identified features. While the original proof of concept study was accompanied by the release of a MLinvitroTox v1 KNIME workflow, in this study, we release a Python MLinvitroTox v2 package, which, in addition to automation, expands functionality to include predicting toxicity from structures, cleaning up and generating chemical fingerprints, customizing models, and retraining on custom data. Furthermore, as a result of improvements in bioactivity data processing, realized in the concurrently released pytcpl Python package for the custom processing of invitroDBv4.1 input data used for training MLinvitroTox, the current release introduces enhancements in model accuracy, coverage of biological mechanistic targets, and overall interpretability. [ABSTRACT FROM AUTHOR]

A large set of antimalarial molecules (N ~ 15k) was employed from ChEMBL to build a robust random forest (RF) model for the prediction of antiplasmodial activity. Rather than depending on high throughput screening (HTS) data, molecules tested at multiple doses against blood stages of Plasmodium falciparum were used for model development. The open-access and code-free KNIME platform was used to develop a workflow to train the model on 80% of data (N ~ 12k). The hyperparameter values were optimized to achieve the highest predictive accuracy with nine different molecular fingerprints (MFPs), among which Avalon MFPs (referred to as RF-1) provided the best results. RF-1 displayed 91.7% accuracy, 93.5% precision, 88.4% sensitivity and 97.3% area under the Receiver operating characteristic (AUROC) for the remaining 20% test set. The predictive performance of RF-1 was comparable to that of the malaria inhibitor prediction platform (MAIP), a recently reported consensus model based on a large proprietary dataset. However, hits obtained from RF-1 and MAIP from a commercial library did not overlap, suggesting that these two models are complementary. Finally, RF-1 was used to screen small molecules under clinical investigations for repurposing. Six molecules were purchased, out of which two human kinase inhibitors were identified to have single-digit micromolar antiplasmodial activity. One of the hits (compound 1) was a potent inhibitor of β-hematin, suggesting the involvement of parasite hemozoin (Hz) synthesis in the parasiticidal effect. The training and test sets are provided as supplementary information, allowing others to reproduce this work. [ABSTRACT FROM AUTHOR]

The gram-negative, facultative anaerobic bacterium Morganella morganii is linked to a number of illnesses, including nosocomial infections and urinary tract infections (UTIs). A clinical isolate from a UTI patient in Bangladesh was subjected to high-throughput whole genome sequencing and extensive bioinformatics analysis in order to gather knowledge about the genomic basis of bacterial defenses and pathogenicity in M. morganii. With an average nucleotide identity (ANI) of more than 97% similarity to a reference genome and phylogenetic analysis verified the isolate as M. morganii. Genome annotation identified 3,718 protein-coding sequences, including genes for metabolism, protein processing, stress response, energy, and membrane transport. The presence of biosynthetic gene clusters points to the isolate's ability to create bioactive compounds, including antibiotics. Genomic islands contained genes for metal transporters, stress proteins, toxin proteins, and genes related to horizontal gene transfer. The beta-lactam resistance gene blaDHA was found using antimicrobial resistance (AMR) gene analysis across three databases. The virulence genes kdsA and cheY, which may be involved in chemotaxis and lipopolysaccharide production, were also available in the isolate, suggesting its high pathogenicity. The genome contained mobile genetic components and defense mechanisms, such as restriction modification and CRISPR-Cas systems, indicating the bacterium's ability to defend itself against viral attacks. This thorough investigation sheds important light on M. morganii's pathogenicity and adaptive tactics by revealing its genetic characteristics, AMR, virulence components, and defense mechanisms. For the development of targeted treatments and preventing the onset of resistance in clinical care, it is essential to comprehend these genetic fingerprints. [ABSTRACT FROM AUTHOR]

Cymbidium ensifolium (L.) Sw. is a valuable ornamental plant in the genus Cymbidium , family Orchidaceae, with high economic and ecological significance. However, the lack of population genetic information and molecular markers has hindered the development of the sales market and genetic breeding of C. ensifolium despite the abundance of commercial cultivars available. In this study, we aimed to develop a set of single nucleotide polymorphism (SNP) markers to distinguish the main cultivated C. ensifolium cultivars in China and provide technical support for domestic cultivar protection, registration, and market rights protection. A total of 1,280,516 high-quality loci were identified from 10,021,591 SNPs obtained by sequencing 50 C. ensifolium commercial cultivars using double digest restriction site-assisted DNA sequencing technology. A total of 7,599 SNPs were selected for kompetitive allele-specific PCR (KASP) primer design, and 4,360 were successfully designed as KASP markers. Population structure analysis revealed that the 50 commercial cultivars were best divided into four populations, with some correlation between the group distribution and the morphological and geographical characteristics of the germplasm. Using the genotyping results from 28 KASP markers screened from the cultivars, a minimum set of 11 markers was identified that could distinguish 83 C. ensifolium commercial cultivars completely, with the remaining 17 markers serving as extended markers. The average PIC value of the 11 markers was 0.345, which was considered medium polymorphism. DNA fingerprints were constructed for the 83 cultivars on the basis of the 11 KASP markers, providing a new approach for mapping DNA fingerprints in C. ensifolium cultivars with high efficiency, accuracy, and low cost compared with traditional methods. [ABSTRACT FROM AUTHOR]

The mid-infrared (MIR) waveband is significant for chemical and biological sensing since it covers several atmospheric windows and molecular fingerprint regions. On-chip photonic integrated one-dimensional (1D) microcavities have great potential for high-performance mid-IR sensing because of their high sensitivity and compact structure. However, high-performance 1D microcavities based on the promising silicon-on-sapphire (SoS) MIR platform have not yet been designed or realized. Based on the photonic band structure induced by 1D photonic crystals (PhC), a high-performance Bragg reflector, an inward apodized Bragg grating, and a free spectral range (FSR)-free PhC microcavity integrated system operating in the MIR waveband were developed on the SoS platform. By carefully designing the period and penetration depth of the corrugation in the Bragg reflector, a stopband of 45 nm and an extinction ratio of −12 dB were achieved. The inward apodized Bragg grating was optimized by adjusting the apodization depth and the number of periods, resulting in a quality factor of 1043 at a wavelength of 3088.4 nm. Furthermore, introducing a Fabry–Pérot (F-P) cavity between two Bragg reflectors (with side-coupled light) and precisely tuning the stopband of the Bragg reflector and the FSR of the F-P cavity enabled the realization of an FSR-free PhC microcavity. This microcavity exhibited a single deep resonance dip with subnanometer bandwidth across a record-wide operational waveband from 3025 to 3200 nm, achieving a quality factor of approximately 5090. The MIR 1D PhC microcavities on the SoS platform hold great promise for high-performance gas detection and molecular sensing in future applications. [ABSTRACT FROM AUTHOR]

The German Fruit Genebank is a decentralized network focused on coordinating various germplasm collections across Germany to conserve and utilize the genetic resources of native fruit species. This aim emphasizes the necessity of trueness-to-type validation of genetic resources based on pomological and molecular characteristics. Between 2009 and 2021, multiple projects were undertaken to create an inventory of the apple (Malus ssp.) network of the German Fruit Genebank. Eight partner locations across Germany participated in these projects to assess the authenticity of apple cultivars. Firstly, at least two knowledgeable experts from the German Pomological Association characterized the apple accessions pomologically. Secondly, DNA fingerprint analysis was conducted for molecular characterization. The DNA fingerprint analysis employed a set of 17 simple sequence repeat markers and 8 reference genotypes recommended by the European Cooperative Programme for Plant Genetic Resources Malus/Pyrus working group and was carried out by ecogenics GmbH (c/o Microsynth AG, Balgach, Switzerland). 8,184 samples were analysed, resulting in the compilation of 1,404 molecular groups that correspond to distinct apple cultivars. [ABSTRACT FROM AUTHOR]

Recent genomic studies have allowed the subdivision of intracranial ependymomas into molecularly distinct groups with highly specific clinical features and outcomes. The majority of supratentorial ependymomas (ST-EPN) harbor ZFTA-RELA fusions which were designated, in general, as an intermediate risk tumor variant. However, molecular prognosticators within ST-EPN ZFTA-RELA have not been determined yet. Here, we performed methylation-based DNA profiling and transcriptome RNA sequencing analysis of 80 ST-EPN ZFTA-RELA investigating the clinical significance of various molecular patterns. The principal types of ZFTA-RELA fusions, based on breakpoint location, demonstrated no significant correlations with clinical outcomes. Multigene analysis disclosed 1892 survival-associated genes, and a metagene set of 100 genes subdivided ST-EPN ZFTA-RELA into favorable and unfavorable transcriptome subtypes composed of different cell subpopulations as detected by deconvolution analysis. BGN (biglycan) was identified as the top-ranked survival-associated gene and high BGN expression levels were associated with poor survival (Hazard Ratio 17.85 for PFS and 45.48 for OS; log-rank; p-value < 0.01). Furthermore, BGN immunopositivity was identified as a strong prognostic indicator of poor survival in ST-EPN, and this finding was confirmed in an independent validation set of 56 samples. Our results indicate that integrating BGN expression (at mRNA and/or protein level) into risk stratification models may improve ST-EPN ZFTA-RELA outcome prediction. Therefore, gene and/or protein expression analyses for this molecular marker could be adopted for ST-EPN ZFTA-RELA prognostication and may help assign patients to optimal therapies in prospective clinical trials. [ABSTRACT FROM AUTHOR]

In this work, an open‐source, versatile, and flexible code named Groupy is present for calculating various molecular properties and preparing input files of molecular simulation software such as Gaussian. This code requires only SMILES as input, but can output many new useful data and files in multiple formats. The output information is clear and easy to read. The tips to the users are very detailed and easy to follow when using. Message passing interface (MPI) parallelization is supported to reduce computing time when the properties of a large number of molecules are calculated. Groupy not only supports the calculation of molecular properties using the traditional group contribution method, but also directly outputs the group‐contribution‐style molecular fingerprints for machine learning. The code has strong extensibility, which can be used as an external library to build other programs. We hope that Groupy brings great convenience to both computational and experimental chemists in their daily research. The code of Groupy can be freely obtained at https://github.com/47‐5/Groupy [ABSTRACT FROM AUTHOR]

Predicting drug target binding affinity has huge relevance in Modern drug discovery and drug repositioning processes which assist doctors to come up with new drugs or even use the existing drugs for new target proteins. In silico models, using advanced deep learning techniques could further assist these prediction tasks by providing most prominent drug target pairs. Considering these factors, a deep learning based algorithmic framework is developed in this study to support drug target interaction prediction. The proposed SeqDPI model extract the relevant drug and protein features from the one dimensional Sequential representation of the dataset considered using optimized CNN networks that deploy convolutions on varying length of amino acid subsequence's to capture hidden pattern, the convolved drug‐ protein features obtained are then used as an input to L2 penalized feed forward neural network which matches the local residue patterns in protein classes with molecular fingerprints of drugs to predict the binding strength for all drug target pairs. The proposed model reduces the convolution strain typically encountered in existing in silico models that utilize complex 3D structures of drug protein datasets. The result shows that the SeqDPI model achieves a mean square error MSE of (0.167) across cross validation folds, outperforming baseline models such as KronRLS (0.406), Simboost (0.226), and DeepPS (0.214). Additionally, SeqDPI attains a high CI score of 0.9114 on the benchmark KIBA dataset, demonstrating its statistical significance and computational efficiency compared to existing methods. This gives the relevance and effectiveness of SeqDPI model in accurately predicting binding affinities while working with simpler one‐dimensional data, making it a robust and computationally cost‐effective solution for drug‐target interaction prediction. [ABSTRACT FROM AUTHOR]

In many human rights and criminal contexts, skeletal remains are often the only available samples, and they present a significant challenge for forensic DNA profiling due to DNA degradation. Ancient DNA methods, particularly capture hybridization enrichment, have been proposed for dealing with severely degraded bones, given their capacity to yield results in ancient remains. Background/Objectives: This paper aims to test the efficacy of genome-wide capture enrichment on degraded forensic human remains compared to autosomal STRs analysis. Methods: Six highly degraded human bones from the Spanish Civil War (1936–1939) were quantified with Quantifiler™ Trio and amplified with GlobalFiler™. Independently, partially UDG-treated double-stranded DNA libraries were generated and shotgun sequenced to screen for endogenous human DNA content. Subsequently, libraries were enriched with the Twist Bioscience "Twist Ancient DNA" reagent enrichment kit, which had not been previously tested for forensic purposes. Results: The results show that the samples behave similarly with both approaches (well-preserved samples yield good results). However, capture enrichment provides some new relevant insights, suggesting that its implementation in current NGS forensic platforms could be beneficial. Conclusions: Shotgun results show that the analyzed samples exhibit the same characteristics as ancient DNA samples in terms of DNA fragmentation and molecular damage, which may enhance the value of this approach when authenticating the endogenous DNA of forensic samples. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) is an established technique for studying plant-insect interactions, that has so far had very limited use in exploring flower-visiting insect communities. This study provides important evidence of the effectiveness of eDNA for studying flower-visiting insects, proving its ability to provide a comprehensive overview of pollinator communities beyond traditional observational methods. Our data revealed a surprising diversity of flower-visiting insects, including both expected pollinators and possible non-pollinating species utilising pollen and/or nectar as a nutritional resource. Native bees, such as Leioproctus spp., and various flies, including those with uncertain roles in pollination, were detected. This study also shed light on the underexplored area of nocturnal pollination, providing evidence of native moth involvement in pollinating plant species. While there was no definitive evidence of rare insects visiting mānuka (Leptospermum scoparium) or Lophomyrtus spp., this study did reveal the importance of these plant species and the resources the flowers provide not just to pollinators, but insects with other key roles in the ecosystem. [ABSTRACT FROM AUTHOR]

Palm trees (Arecaceae) are among the most popular ornamental plants worldwide. Despite extensive research on the fungi associated with Arecaceae, the diversity and ecological dynamics of fungi affecting ornamental palms remain poorly studied, although they have significant impact on palm health and economic value. Furthermore, while research on palm fungal diversity has traditionally focused on tropical assemblages, ornamental palms in temperate climates offer a unique opportunity to explore the diversity of palm fungi in non-native habitats. The present study conducted a preliminary assessment of the diversity and ecology of potential phytopathogenic fungi associated with foliar lesions on various ornamental palm host species in Portugal, combining morphological examination, PCR-based genomic fingerprinting, and biodiversity data analysis. The examination of 134 foliar lesions sampled from 100 palm trees resulted in a collection of 2064 palm leaf spotting fungi (PLSF), representing a diverse fungal assemblage of 320 molecular operational taxonomic units (MOTUs) across 97 genera. The overall fungal community composition revealed a distinct assemblage dominated by Neosetophoma, Alternaria, Phoma, and Cladosporium, with a profusion of infrequent and rare taxa consistent with a logseries distribution. Significantly positive co-occurrence (CO) patterns among prevalent and uncommon taxa suggest potential synergistic interactions enhancing fungal colonisation, persistence, and pathogenicity. The taxonomic structures of the PLSF contrasted markedly from tropical palm fungi, especially in the prevalence of pleosporalean coelomycetes of the Didymellaceae and Phaeosphaeriaceae, including recently introduced or not previously documented genera on Arecaceae. This novel assemblage suggests that climatic constraints shape the structure of palm fungal communities, resulting in distinctive temperate and tropical assemblages. In addition, the fungal assemblages varied significantly across palm host species, with temperate-native palms hosting more diverse, coelomycete-enriched communities. The present findings highlight foliar lesions as hyperdiverse microhabitats harbouring fungal communities with intricate interactions and a complex interplay of climatic, host, and ecological factors. With climate change altering environmental conditions, the identification of fungi thriving in or inhabiting these microhabitats becomes crucial for predicting shifts in pathogen dynamics and mitigating future fungal disease outbreaks. Understanding these complex ecological dynamics is essential for identifying potential phytopathogenic threats and developing effective management strategies for the health and sustainability of ornamental plants. [ABSTRACT FROM AUTHOR]

Modern techniques can generate highly discriminatory DNA profiles from minuscule biological samples, providing valuable information in criminal investigations and court proceedings. However, trace and touch DNA samples, due to their nature, often have lower success rates than other biological materials, such as blood. Further, forensically aware criminals can utilize gloves and meticulously clean the crime scene to remove DNA traces of themselves from contacted surfaces. Air sampling offers a novel approach to the collection of human DNA that has the potential to bypass some of these issues. This study reports on the results of research into the prevalence and persistence of human DNA in the air. The ability to collect human DNA from the air was investigated with the use of an AirPrep Cub Sampler ACD220 in different spaces, with and without the presence of individuals for various durations of sample collection. Results of this study demonstrate that level of occupation and sampling duration each have an influence on quantity and quality of DNA recovered from the air whereas the effects of orientation and distance of participants from the collection device as well as sequence of occupation remain unclear and require further investigation. [ABSTRACT FROM AUTHOR]

Advancements in forensic DNA typing technology and methods have increased sensitivity and, while beneficial, carry the weight of more challenging profile interpretation. In response, the forensic DNA community has often requested more complex reference materials to address commonly encountered measurement and interpretation issues such as complex DNA mixtures, DNA degradation, and PCR inhibition. The National Institute of Standards and Technology (NIST) released Research Grade Test Material 10235: Forensic DNA Typing Resource Samples to support the forensic DNA community. Components include three single source samples, two degraded samples, and three mixture samples. As part of the Research Grade Test Material (RGTM) process, automated methods for bottling, alternative sample tube types, and the addition of carrier RNA for stabilizing low‐quantity samples were investigated. Both internal and external testing demonstrate the stability of the material over time at 4°C through qPCR testing. In the development of a data portal, users have been allowed to anonymously upload results and compare their data with NIST and others. This report describes the preparation and stability of this material. [ABSTRACT FROM AUTHOR]

Introduction: Analysis of a single tooth and nail can provide valuable forensic information, including year of birth, year of death, age, sex, DNA-profile, geographic residence during childhood and at time of death and drug exposure. The aim is to minimize the amount of used bodily material and to validate the applicability of a multidisciplinary sampling protocol. Methods: A nail of the big toe, a tooth and blood of seven deceased individuals were collected postmortem. Collected materials were sampled and segmented in accordance with the multidisciplinary sampling protocol. DNA analysis was conducted on the pulp of the tooth, isotope analysis (Sr, Pb, O and C) on the enamel and 14C-, toxicological and tooth cementum annulation analysis on root segments. DNA-, isotope (Sr, Pb, O and C) -, toxicological-, and 14C -analysis were conducted on toenail segments. The acquired DNA profiles were compared with profiles acquired from blood. Results: Material from seven deceased persons was analysed. 45 out of 56 analyses on dental samples were successful, constituting a success rate of 80%. Additionally, 27 out of 35 analyses were successful on nail samples, yielding a success rate of 77%. DNA-, toxicological and 14C- analyses performed better in nail than in tooth. Isotope analyses performed better in tooth than in nail. A profile with personal characteristics was constructed and matched for 62% of parameters with collected medical information. Conclusion: The performed sampling protocol for simultaneous multidisciplinary forensic analysis on a single tooth and nail sample provided applicable results and valuable information. [ABSTRACT FROM AUTHOR]

Background: A liquid biopsy is a test that evaluates the status of a disease by analyzing a sample of bodily fluid, most commonly blood. In recent years, there has been progress in the development and clinical application of liquid biopsy methods to identify blood-based, tumor-specific biomarkers for many cancer types. However, the implementation of these technologies to aid in the treatment of patients who have a sarcoma remains behind other fields of cancer medicine. For this study, we chose to evaluate a sarcoma liquid biopsy based on circulating tumor DNA (ctDNA). All human beings have normal cell-free DNA (cfDNA) circulating in the blood. In contrast with cfDNA, ctDNA is genetic material present in the blood stream that is derived from a tumor. ctDNA carries the unique genomic fingerprint of the tumor with changes that are not present in normal circulating cfDNA. A successful ctDNA liquid biopsy must be able to target these tumor-specific genetic alterations. For instance, epidermal growth factor receptor (EGFR) mutations are common in lung cancers, and ctDNA liquid biopsies are currently in clinical use to evaluate the status of disease in patients who have a lung cancer by detecting EGFR mutations in the blood. As opposed to many carcinomas, sarcomas do not have common recurrent mutations that could serve as the foundation to a ctDNA liquid biopsy. However, many sarcomas have structural changes to their chromosomes, including gains and losses of portions or entire chromosomes, known as copy number alterations (CNAs), that could serve as a target for a ctDNA liquid biopsy. Murine double minute 2 (MDM2) amplification in select lipomatous tumors or parosteal osteosarcoma is an example of a CNA due to the presence of extra copies of a segment of the long arm of chromosome 12. Since a majority of sarcomas demonstrate a complex karyotype with numerous CNAs, a blood-based liquid biopsy strategy that searches for these CNAs may be able to detect the presence of sarcoma ctDNA. Whole-genome sequencing (WGS) is a next-generation sequencing technique that evaluates the entire genome. The depth of coverage of WGS refers to how detailed the sequencing is, like higher versus lower power on a microscope. WGS can be performed with high-depth sequencing (that is, > 60×), which can detect individual point mutations, or low-depth sequencing (that is, 0.1× to 5×), referred to as low-passage whole-genome sequencing (LP-WGS), which may not detect individual mutations but can detect structural chromosomal changes including gains and losses (that is, CNAs). While similar strategies have shown favorable early results for specific sarcoma subtypes, LP-WGS has not been evaluated for applicability to the broader population of patients who have a sarcoma. Questions/purposes: Does an LP-WGS liquid biopsy evaluating for CNAs detect ctDNA in plasma samples from patients who have sarcomas representing a variety of histologic subtypes? Methods: This was a retrospective study conducted at a community-based, tertiary referral center. Nine paired (plasma and formalin-fixed paraffin-embedded [FFPE] tissue) and four unpaired (plasma) specimens from patients who had a sarcoma were obtained from a commercial biospecimen bank. Three control specimens from individuals who did not have cancer were also obtained. The paired and unpaired specimens from patients who had a sarcoma represented a variety of sarcoma histologic subtypes. cfDNA was extracted, amplified, and quantified. Libraries were prepared, and LP-WGS was performed using a NextSeq 500 next-generation sequencing machine at a low depth of sequencing coverage (∼1×). The ichorCNA bioinformatics algorithm, which was designed to detect CNAs from low-depth genomic sequencing data, was used to analyze the data. In contrast with the gold standard for diagnosis in the form of histopathologic analysis of a tissue sample, this test does not discriminate between sarcoma subtypes but detects the presence of tumor-derived CNAs within the ctDNA in the blood that should not be present in a patient who does not have cancer. The liquid biopsy was positive for the detection of cancer if the ichorCNA algorithm detected the presence of ctDNA. The algorithm was also used to quantitatively estimate the percent ctDNA within the cfDNA. The concentration of ctDNA was then calculated from the percent ctDNA relative to the total concentration of cfDNA. The CNAs of the paired FFPE tissue and plasma samples were graphically visualized using aCNViewer software. Results: This LP-WGS liquid biopsy detected ctDNA in 9 of 13 of the plasma specimens from patients with a sarcoma. The other four samples from patients with a sarcoma and all serum specimens from patients without cancer had no detectable ctDNA. Of those 9 patients with positive liquid biopsy results, the percent ctDNA ranged from 6% to 11%, and calculated ctDNA quantities were 0.04 to 5.6 ng/mL, which are levels to be expected when ctDNA is detectable. Conclusion: In this small pilot study, we were able to detect sarcoma ctDNA with an LP-WGS liquid biopsy searching for CNAs in the plasma of most patients who had a sarcoma representing a variety of histologic subtypes. Clinical Relevance: These results suggest that an LP-WGS liquid biopsy evaluating for CNAs to identify ctDNA may be more broadly applicable to the population of patients who have a sarcoma than previously reported in studies focusing on specific subtypes. Large prospective clinical trials that gather samples at multiple time points during the process of diagnosis, treatment, and surveillance will be needed to further assess whether this technique can be clinically useful. At our institution, we are in the process of developing a large prospective clinical trial for this purpose. [ABSTRACT FROM AUTHOR]

Many chemicals in food packaging can leach as complex mixtures to food, potentially including substances hazardous to consumer health. Detecting and identifying all of the leachable chemicals are impractical with current analytical instrumentation and data processing methods. Therefore, our work aims to expand the analytical toolset for prioritizing and identifying chemical hazards in food packaging. We used a high-performance thin-layer chromatography (HPTLC)-based bioassay to detect genotoxic fractions in paperboard packaging. These fractions were then processed with non-targeted liquid chromatography high-resolution mass spectrometry (LC-HRMS/MS) and machine learning-based toxicity prediction (MLinvitroTox). The HPTLC bioassay detected four genotoxic zones in extracts of the paperboard. One-dimensional HPTLC separation and targeted fraction collection reduced the number of chemical features extracted from paperboard and detected with LC-HRMS by at least 98% (from 1695–2693 to 14–50). The entire process was successful for spiked genotoxic chemicals, which were correctly prioritized in the fractionation and non-target analysis workflow. The native chemical with the strongest genotoxicity signal was identified with a suspect list as 5-chloro-2-methyl-4-isothiazolin-3-one and confirmed with LC-HRMS/MS and HPTLC bioassay. Toward identification of the remaining unknown genotoxicants, two-dimensional HPTLC further reduced the number of chemical features. Genotoxicity predictions with MLinvitroTox based on molecular fingerprints of the unknown signals derived from their MS2 fragmentation spectra helped prioritize two chemical features and suggested candidate structures. This work demonstrates strategies for using HPTLC, HRMS, and toxicity prediction to help identify toxicants in food packaging. [ABSTRACT FROM AUTHOR]

Terahertz (THz) molecular fingerprint spectroscopy provides a powerful label-free tool for detecting trace-amount analytes. Introducing extra microstructures such as metasurfaces to confine the field energy is essential to improve the sensitivity. However, the area of analyte film on conventional enhancing metasurfaces must be larger than the beam spot in a free-space measuring setup. Here, we propose a tunable defect cavity of one-dimensional photonic crystal in the combined coaxial waveguide (CCW) and enhance the broadband THz fingerprint of trace analytes on a much smaller area. The peaks of high Q resonances can form a wide absorption spectrum by changing the length of the rubber part of the coaxial waveguide. For the 0.2 µm α-lactose film sample in the frequency range of 0.48–0.58 THz, the absorption enhancement factor of 89.2 times based on the thickness can be achieved and the sample area is about 1/1700 of that in the free-space measurement with the 5 mm beam waist. We first introduce the coaxial waveguide in the terahertz absorption spectra enhancement. With our proposed structure the analyte volume is effectively reduced which is significant in the real application scenario. [ABSTRACT FROM AUTHOR]

Background/aim: The purpose of this study was to examine the hepatic bacterial composition and metabolome characteristics of patients with NAFLD using 16S rDNA sequencing and metabolomics. The results of the study revealed substantial differences in hepatic bacterial composition and metabolites between the NAFLD group and the control group. These differences were used to identify potential biomarkers that could be employed to diagnose NAFLD. Subjects/methods: Liver tissues from 13 patients in the NAFLD group and 12 patients in the control group were collected for microbiota examination. Results: The bacterial DNA profiles of the liver were significantly different between NAFLD patients and controls. NAFLD patients exhibited an enrichment of Enterobacterales, Mycobacteriales, Pseudomonadales, Flavobacteriales and Xanthomonadales, Sphingomonadales, Lysobact, which was characterised by a lack of erales. At the genus level, the abundance values of Escherichia - Shigella , Rhodococcus , and Chryseobacterium in the NAFLD group were significantly elevated, while the abundance values of Stenotrophomonas , Lawsonella and Sphingobium were significantly reduced. A total of 402 distinct metabolites were identified between the two groups, with 78 metabolites that were up-regulated and 14 metabolites that were down-regulated. The enrichment of metabolic pathways indicated that linoleic acid metabolism was the most significant contributor to the metabolic differences, and lipid metabolism was substantially differentiated. The hepatic metabolite levels were substantially correlated with the changes in hepatic microflora, as demonstrated by the correlation analysis. Conclusion: Differences in pathogenesis and host physiological function of NAFLD may be attributed to the hepatic flora and metabolomic characteristics. In the future, this presents new opportunities for the investigation of prospective diagnostic and therapeutic targets for NAFLD. [ABSTRACT FROM AUTHOR]

Finger millet blast caused by Pyricularia grisea hinders crop's growth and is a serious threat to economic yield. It can lead to massive yield losses i.e. up to 80%, which is a cause of major concern. In this study, we evaluated 200 accessions of finger millet at Banda University of Agriculture & Technology in Banda, India, under natural conditions to determine their resistance against leaf, neck, & finger blast diseases. Nine accessions displayed strong resistance against all forms of blast. The genetic variability analysis revealed high phenotypic & genotypic coefficients of variation. This was especially true for seed yield, plant height, & days to flowering. Most traits had heritability estimates exceeding 80%. Such results indicate a significant potential for effective selection in breeding programs. Leaf blast ratings had a significant but weaker correlation to both neck blast (r = 0.31) and finger blast (r = 0.31) whereas neck and finger blast ratings were very highly correlated and significant (r = 0.97). All types of blast had negative correlation with various agronomic traits studied. Furthermore, DNA fingerprinting of resistant genotypes with SSR markers displayed 10 polymorphic markers with an average of 2.6 alleles per locus. This points to the genetic diversity present within the germplasm. In summary, these findings provide vital insights for breeding initiatives focused on enhancing blast resistance in finger millet. Such efforts are crucial for maintaining the sustainability of this important crop for global food security. [ABSTRACT FROM AUTHOR]

Sweetpotato (Ipomoea batatas L.), an important food and industrial crop in the world, has a highly heterozygous hexaploid genome, making the development of single nucleotide polymorphism (SNP) markers challenging. Identifying SNP loci and developing practical SNP markers are crucial for genomic and genetic research on sweetpotato. A restriction site-associated DNA sequencing analysis of 60 sweetpotato accessions in this study yielded about 7.97 million SNPs. Notably, 954 candidate SNPs were obtained from 21,681 high-quality SNPs. Based on their stability and polymorphism, 274 kompetitive allele specific PCR (KASP) markers were then developed and uniformly distributed on chromosomes. The 274 KASP markers were used to genotype 93 sweetpotato accessions to evaluate their utility for assessing germplasm and analyzing genetic diversity and population structures. These markers had respective mean values of 0.24, 0.34, 0.31, and 0.25 for minor allele frequency, heterozygosity, gene diversity, and polymorphic information content (PIC). Their genetic pedigree led to the division of all accessions into three primary clusters, which were found to be both interrelated and independent. Finally, 74 KASP markers with PIC values greater than 0.35 were selected as core markers. These markers were used to construct the DNA fingerprints of 93 sweetpotato accessions and were able to differentiate between all accessions. To the best of our knowledge, this is the first attempt at the development and application of KASP markers in sweetpotato. However, due to sweetpotato's polyploidy, heterozygosity and the complex genome, the KASP marker conversion rate in this study was relatively low. To improve the KASP marker conversion rate, and accuracies in SNP discovery and marker validation, further studies including more accessions from underrepresented regions are needed in sweetpotato. [ABSTRACT FROM AUTHOR]

Roselle (Hibiscus sabdariffa L.) simple sequence repeat (SSR) markers were developed using RNA sequencing technology, providing a foundation for genetic analysis and the identification of roselle varieties. In this study, 10 785 unigenes containing 12 994 SSR loci with an average of one SSR locus per 6.87 Kb were identified, and the occurrence frequency of the SSR loci was 11.36%. Trinucleotide repeat motifs were the most abundant, followed by dinucleotide repeats, with AAG/CTT and AT/AT being the predominant types, respectively. After screening 100 primer pairs with a polymorphic ratio of 32.0%, we obtained 32 primer pairs, resulting in clear and stable polymorphic bands. Twenty-seven primer pairs were highly or moderately polymorphic, and seven primer pairs were highly polymorphic. Genetic relationship analysis based on the selected SSR primers showed that 38 roselle accessions were classified into different clades, with those from the same regions clustered into the same subgroups. In contrast, individuals with unique morphological traits were separated. DNA fingerprints of 38 roselle varieties were constructed using five SSR primers, providing an effective method for identifying roselle varieties at a molecular level. Our data provide novel insights into the genetics of H. sabdariffa and may be used in SSR-assisted roselle breeding. [ABSTRACT FROM AUTHOR]

Introduction: Tomato (Solanum lycopersicum) is a highly valuable fruit crop. However, due to the lack of scientific and accurate variety identification methods and unified national standards, production management is scattered and non-standard, resulting in mixed varieties. This poses considerable difficulties for the cataloging and preservation of germplasm resources as well as the identification, promotion, and application of new tomato varieties. Methods: To better understand the genetic diversity and population structure of representative tomato varieties, we collected 418 tomato varieties from the past 20 years and analyzed them using genome-wide single nucleotide polymorphism (SNP) markers. We initially assessed the population structure, genetic relationships, and genetic profiles of the 418 tomato germplasm resources utilizing simplified genome sequencing techniques. A total of 3,374,929 filtered SNPs were obtained and distributed across 12 chromosomes. Based on these SNP loci, the 418 tomatoes samples were divided into six subgroups. Results: The population structure and genetic relationships among existing tomato germplasm resources were determined using principal component analysis, population structure analysis, and phylogenetic tree analysis. Rigorous selection criteria identified 15 additional high-quality DNA fingerprints from 50 validated SNP loci, effectively enabling the identification of the 418 tomato varieties, which were successfully converted into KASP (Kompetitive Allele Specific PCR) markers. Discussion: This study represents the first comprehensive investigation assessing the diversity and population structure of a large collection of tomato varieties. Overall, it marks a considerable advancement in understanding the genetic makeup of tomato populations. The results broadened our understanding of the diversity, phylogeny, and population structure of tomato germplasm resources. Furthermore, this study provides a scientific basis and reference data for future analysis of genetic diversity, species identification, property rights disputes, and molecular breeding in tomatoes. [ABSTRACT FROM AUTHOR]

Tailoring metamaterial design for desired absorption in the mid‐infrared region is pivotal for molecular sensing and identification. Surface‐enhanced infrared absorption (SEIRA) spectroscopy with metamaterials promises accurate molecular fingerprint detection. However, challenges arise due to narrow resonant wavelengths and the extensive design space of the metamaterial, thus hindering its application in accurate molecular detection. This work introduces an integrated AI workflow for designing electrically tunable metamaterial absorbers using phase‐change materials for broadband molecular fingerprint retrieval and identification. A free‐form inverse design method based on a neural‐adjoint optimization technique is utilized to predict phase‐change metamaterial absorber (PCMA) designs for desired mid‐infrared absorption spectra. Using the trained inverse neural network model coupled with a genetic algorithm, nanostructure designs spanning the spectral range from 800 cm−1 to 2000 cm−1 are predicted. The phase change is achieved by integrating the designed PCMA with an energy‐efficient microheater, allowing resonant absorption peaks to be tuned via voltage pulses. The neural network‐predicted PCMA successfully detected molecular vibration fingerprints of four molecules and their mixtures. A machine learning model based on a support vector machine developed for molecular identification shows 100% identification accuracy. This AI‐driven approach for PCMA design and molecular identification via SEIRA marks a significant advancement in accurate molecular detection. [ABSTRACT FROM AUTHOR]

The article discusses the use of systemic anti-inflammatory therapy in treating congenital ichthyosis based on a study of 22 cases. The study found that drugs targeting Type 2 inflammation reduced itch in certain types of ichthyosis, while drugs against Type 3 inflammation had an impact on erythema and overall skin condition. The research highlights the potential benefits of systemic anti-inflammatory therapies for patients with challenging genodermatoses, emphasizing the need for further research and clinical trials in this area. [Extracted from the article]

Summary A unique cell size‐sensing mechanism is at the heart of the life cycle of diatoms. During population growth, cell size decreases until a sexual size threshold (SST) is reached, below which cells become sexually competent. In most pennate diatoms, the two mating types undergo biochemical and behavioral differentiation below the SST, although the molecular pathways underlying their size‐dependent maturation remain unknown. Here, we developed a method to shorten the generation time of Cylindrotheca closterium through single‐cell microsurgery, enabling the transcriptomic comparison of genetically identical large and undifferentiated cells with small, sexually competent cells for six different genotypes. We identified 21 genes upregulated in small cells regardless of their mating type, revealing how cells undergo specific transcriptional reprogramming when passing the SST. Furthermore, we revealed a size‐regulated gene cluster with three mating type‐specific genes susceptible to sex‐inducing pheromones. In addition, comparative transcriptomics confirmed the shared mating type specificity of Mating‐type Related Minus 2 homologs in three pennate diatoms, suggesting them to be part of a conserved partner recognition mechanism. This study sheds light on how diatoms acquire sexual competence in a strictly size‐dependent manner, revealing a complex machinery underlying size‐dependent maturation, mating behavior, and heterothally in pennate diatoms. [ABSTRACT FROM AUTHOR]

The article is devoted to the analysis of the norms of the criminal procedural legislation of Ukraine and other normative legal acts on the issues of forensic expert activity, which regulate the procedural mechanism of involving experts from other states who possess special knowledge and skills necessary to provide substantiated and objective written conclusions during pretrial investigation and trial. Since the introduction of martial law in Ukraine in February 2022, the country has faced an urgent need to conduct an excessive number of forensic examinations in criminal proceedings related, in particular, to the identification of unidentified bodies and human remains. The scale of the tragedy required the involvement of foreign experts to conduct relevant research related to the development of DNA profiles of the victims and their relatives. The article states that international cooperation during criminal proceedings includes, in addition to the fulfillment of requests for investigative (search) actions on the territory of other states in order to obtain evidence, the creation of joint investigative teams for the investigation of crimes, as well as the use of special knowledge in the form of forensic examinations. It is concluded that the involvement of foreign experts in criminal proceedings in Ukraine in the order of international cooperation is provided for by the provisions of normative legal acts of a national nature, albeit in a rather general form. However, the procedural mechanism of involving experts and the order of international cooperation clearly need to be refined. Based on the results of the analysis, the actual mechanisms for involving foreign experts in criminal proceedings, which are provided for by the Criminal Procedure Code of Ukraine and the Law of Ukraine «On Forensic Expertise», as well as existing gaps in the legislative regulation in this area, have been determined. Judicial practice also points to the possibility of involving specialists from other states for joint forensic examinations in criminal proceedings. [ABSTRACT FROM AUTHOR]

Biological mechanisms related to cancer development can leave distinct molecular fingerprints in tumours. By leveraging multi-omics and epidemiological information, we can unveil relationships between carcinogenesis processes that would otherwise remain hidden. Our integrative analysis of DNA methylome, transcriptome, and somatic mutation profiles of kidney tumours linked ageing, epithelial–mesenchymal transition (EMT), and xenobiotic metabolism to kidney carcinogenesis. Ageing process was represented by associations with cellular mitotic clocks such as epiTOC2, SBS1, telomere length, and PBRM1 and SETD2 mutations, which ticked faster as tumours progressed. We identified a relationship between BAP1 driver mutations and the epigenetic upregulation of EMT genes (IL20RB and WT1), correlating with increased tumour immune infiltration, advanced stage, and poorer patient survival. We also observed an interaction between epigenetic silencing of the xenobiotic metabolism gene GSTP1 and tobacco use, suggesting a link to genotoxic effects and impaired xenobiotic metabolism. Our pan-cancer analysis showed these relationships in other tumour types. Our study enhances the understanding of kidney carcinogenesis and its relation to risk factors and progression, with implications for other tumour types. Synopsis: Integrative analysis of multi-omics and epidemiological data implicated ageing, epithelial-mesenchymal transition (EMT), and xenobiotic metabolism as biological mechanisms driving clear cell renal cell carcinoma (ccRCC). Cellular mitotic ageing is a major source of variance between ccRCC tumours, with faster ticking mitotic clocks (epiTOC2, SBS1, and telomere length), genomic instability and PBRM1 and SETD2 mutations related to tumour progression. There is a relationship between BAP1 driver mutations, the epigenetic activation of EMT related genes (IL20RB and WT1), tumour immune infiltration, and worse survival outcomes. Epigenetic silencing of GSTP1, especially in smokers, points to impaired xenobiotic metabolism and increased genotoxic risk in ccRCC tumours. These biological mechanisms were also observed across other cancer types, highlighting broader implications for tumour progression. Integrative analysis of multi-omics and epidemiological data implicated ageing, epithelial-mesenchymal transition (EMT), and xenobiotic metabolism as biological mechanisms driving clear cell renal cell carcinoma (ccRCC). [ABSTRACT FROM AUTHOR]

There may be cases where malignant tumor samples can be used for forensic DNA profiling studies. STRs are the first systems preferred in forensic science laboratories for identification purposes. However, genetic instability in tumoral tissues causes STR polymorphism to change, leading to erroneous results. On the other hand, insertion/deletion polymorphism (InDels) are used as genetic markers in forensic science, as they have features that make both STR and SNPs preferable. Although previous studies approved that STR instability is observed in many different tumors, there are only a few studies that have displayed the instability of InDels in tumoral tissues before. In this study, it was aimed to determine whether instability is observed in formalin-fixed paraffin-embedded breast and thyroid tumoral tissues at 36plex InDel Panel. A total of 47 cases, 26 of which were diagnosed as breast cancer and 21 as thyroid cancer, were included in the study. In 21 of 26 (80.76%) breast cancers mutational changes were observed, however only 6 of 21 (28.57%) thyroid carcinoma cases displayed instability.Moreover, in these six cases, mutations were detected at only 1 or 2 loci. The most common change in both tissues was loss of heterozygosity. These findings suggest that paraffin embedded tissues of thyroid tumor can be used in cases of forensic genetic identification, however paraffin embedded breast cancer tissues should be examined with care. In conclusion, low InDel mutation rates compared to STR instability, make InDel analysis from paraffin blocks suitable for forensic genetic identification. However, researchers should keep in mind that there may be differences between the profiles of the tumoral tissues taken as reference and the actual case. In addition, by incorporating additional markers such as SNPs and microhaplotypes with low mutation rates into the study alongside Indels, researchers can significantly enhance the discrimination power in identification processes. [ABSTRACT FROM AUTHOR]

The escalating rates of rape and sexual assault cases underscore the essential need to analyze associative evidence of sexual assault to ensure justice. The condom, when used during the act of sexual assault/rape, leaves behind traces of lubricant that could be instrumental in establishing the link between the victim and perpetrator. This leading evidence is crucial especially when the traditional DNA analysis is challenging owing to the lack of biological evidence. The present study employs the use of ATR FTIR spectroscopy coupled with the chemometric, to discern the chemical discrimination of condom lubricants. The study also aimed to investigate simulated real-case scenarios by analysing the effect of different matrices such as vaginal fluid, menstrual blood, and undergarment substrates (cotton, polyester and nylon) on condom traces. The difference in the spectral profile of pre-coitus and post-coitus samples was also investigated. The results of the present study are noteworthy, unveiling the efficacy of discriminating the condom lubricants of different brands and other frequently used household lubricants with 100% sensitivity, specificity, and accuracy. Condom lubricants are detected despite the presence of contaminants such as menstrual blood, and vaginal fluid, across different substrates and, in post-coital conditions. In conclusion, this study presents a comprehensive approach to analysing condom lubricants, offering a potential breakthrough in the investigation of sexual assault cases, coupled with the ability to counter false accusations. [ABSTRACT FROM AUTHOR]

Vitreous humour (VH) is routinely collected for toxicological analyses. However, only a few studies have examined its possible use in genotyping. Because of its isolation from the rest of the body, later onset of postmortem changes, and availability, VH could be a potential source of DNA for postmortem identification and other molecular analyses in forensic genetics. During forensic autopsies, samples of different VH volumes (5 ml, 4 ml, 3 ml, 2 ml, 1 ml, and 0.5 ml) were taken from 66 cadavers 24–48 h after death. DNA was also isolated from the samples immediately after collection and after a specific time of storage (1, 2, and 6 months). DNA was isolated using phenol‒chloroform‒isoamyl alcohol (PCI), and the yield and purity of the obtained DNA were determined spectrophotometrically using a FastGene NanoView Photometer. The integrity of the isolated DNA molecule was determined by PCR amplification of the hTERT (113 bp) gene. The results showed that VH could be a reliable source of genetic material for forensic analysis, and the method used for DNA extraction was effective. The yield of the isolated DNA ranged from 6.20 to 609.5 ng/µl, and the purity of the samples was 1.24–2.34. The isolated DNA concentration and integrity depend on the sample volume, but the DNA purity does not. It is also shown that DNA can be extracted from VH samples that have been stored for up to 6 months at − 20 °C. Therefore, using VH can be a valuable material for DNA identification. [ABSTRACT FROM AUTHOR]

This study was conducted to examine the possibility of reducing PCR reaction volume of the PowerPlex Fusion system to produce full DNA genotyping of some forensic casework samples. Human DNA profiling was analyzed by half and quarter PCR reaction volume of the PowerPlex® Fusion system amplification kit to examine the reliability of the obtained STR profiles. Serial DNA dilutions (1 ng, 0.5 ng, 0.125 ng, 0.0625 ng) of a buccal swab were used with half PCR reaction volume to analyze STR loci via estimating their peak height and stutter ratio. The peak height ratio was above 60% in all heterozygous loci obtained and the best ratio of stutter was in the sample with a concentration of 0.0125, as it was less than 16% in all loci. Half and quarter PCR reaction volumes were evaluated by different casework samples (blood, hairs, and nails). The results showed that half reaction volumes gave 100% STR profiles of blood and nail samples and 60% of hair samples gave complete profiles. In 40% of hair samples, alleles were dropped out in the loci Penta E and Penta D. Quarter PCR reaction volumes gave 30% of blood and hair samples and 20% of nail samples produced a complete STR profile. It was possible to reduce the PCR reaction volume by more than half while still obtaining a complete STR profile suitable for human identification, despite some negative results that may have been due to DNA purity issues. Further studies are necessary to generalize this conclusion. [ABSTRACT FROM AUTHOR]

Background/Objectives: Varicoceles are a common contributor to male infertility, significantly impacting male-factor infertility cases. Traditional diagnostic methods often lack the sensitivity to detect the molecular and cellular disruptions caused by varicoceles, limiting the development of effective, personalized treatments. This narrative review aims to explore the advancements in proteomics and metabolomics as innovative, non-invasive diagnostic tools for varicocele-associated male infertility and their potential in guiding personalized therapeutic strategies. Methods: A comprehensive literature search was conducted using databases such as PubMed, Scopus, and Web of Science up to October 2024. Studies focusing on the application of proteomic and metabolomic analyses in varicocele-associated male infertility were selected. The findings were critically analyzed to synthesize current knowledge and identify future research directions. Results: Proteomic analyses revealed differentially expressed proteins in the sperm and seminal plasma of varicocele patients, revealing disruptions in pathways related to oxidative stress, mitochondrial dysfunction, apoptosis, and energy metabolism. Key proteins such as heat shock proteins, mitochondrial enzymes, and apoptotic regulators were notably altered. Metabolomic profiling uncovered specific metabolites in seminal plasma—such as decreased levels of lysine, valine, and fructose—that correlate with impaired sperm function and fertility potential. The integration of proteomic and metabolomic data provides a comprehensive molecular fingerprint of varicocele-induced infertility, facilitating the identification of novel biomarkers for early diagnosis and the development of personalized therapeutic interventions. Conclusions: Advances in proteomics and metabolomics have significantly enhanced our understanding of the molecular mechanisms underlying varicocele-associated male infertility. These "omics" technologies hold great promise for improving diagnostic accuracy and personalizing treatment, ultimately leading to better outcomes for affected men. Future large-scale clinical trials and validations are essential to confirm these biomarkers and facilitate their integration into routine clinical practice. [ABSTRACT FROM AUTHOR]

Simple Summary: The analysis of the interaction between incident light and matter can reveal certain properties about the matter itself. This phenomenon can be utilised in the form of Raman spectroscopy. The application of Raman spectroscopy to biological matrices may enable both quantitative and qualitative analysis of the sample. There are many potential applications in medicine, particularly in oncology. Individualisation of care may be achieved by precisely measuring drug exposure in therapeutic drug monitoring, as well as precisely assessing treatment response by measuring changes in tumour DNA levels in the blood. The existing methods to measure these parameters are expensive, specialized and time-consuming. Raman spectroscopy may provide a more accessible and highly accurate alternative. Raman spectroscopy is a technique which involves quantitative and qualitative molecular analysis based on the interaction between incident light and isolation of scattered wavelengths in generating a molecular fingerprint. It has a broad array of potential scientific applications, encompassing areas as diverse as food science and forensics. However, it may also be highly useful in clinical oncology. A recent focus of research in oncology has been in achieving the individualisation of care. Two important strategies to achieve a so-called "precision oncology" approach may include the detection of circulating tumour DNA (ctDNA) in more objectively evaluating treatment response and guiding de-escalation and intensification approaches in systemic therapy and therapeutic drug monitoring (TDM). Therapeutic drug monitoring involves the quantitation of plasma drug levels in order to tailor medication dosing in optimizing outcomes. The existing approaches to characterize small molecules, such as fluorescence-based and chromatographic strategies, may be limited by high costs, long turnaround times, and bulky equipment. Surface-enhanced Raman spectroscopy (SERS) may be deployed by utilizing a handheld device, with the potential for point of care, rapid turnaround, low-cost assessment of clinically relevant parameters, and prompt implementation of attendant changes in treatment. Although there is a growing body of data supporting the implementation of TDM and evaluation of ctDNA in achieving precision medicine, the uptake of such approaches remains relatively limited outside of clinical trials. As stated, the nature of existing analytical methodologies may prove to be a significant barrier to the routine clinic-based implementation of such approaches. Therefore, we provide the existing evidence for SERS in alleviating these barriers. We also provide insights into how SERS could contribute to clinical oncology. [ABSTRACT FROM AUTHOR]

This study illustrates the use of chemical fingerprints with machine learning for blood–brain barrier (BBB) permeability prediction. Employing the Blood Brain Barrier Database (B3DB) dataset for BBB permeability prediction, we extracted nine different fingerprints. Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) algorithms were used to develop models for permeability prediction. Random Forest recursive Feature Selection (RF-RFS) method was used for extracting informative attributes. An additional database was employed for the validation phase. The results indicate that all nine datasets achieved good performance in training, test and validation stages. We further took MACC Keys fingerprints, one of the best performing models for explainability analysis. For this purpose, we used SHapley Additive exPlanations (SHAP) analysis on this dataset for the identification of key structural features influencing BBB permeability prediction. These features include aliphatic carbons, methyl groups and oxygen-containing groups. This study highlights the effectiveness of different fingerprint descriptors in predicting BBB permeability. SHAP analysis provides value additions to the simulations. These simulations will be of significant help in drug discovery processes, particularly in developing Central Nervous System (CNS) therapeutics. [ABSTRACT FROM AUTHOR]

Simple Summary: The genetic diversity of naked barley (Hordeum vulgare var. nudum) varieties from Tibet, including traditional (T), modern (M), and germplasm-resources-bank (G) types, was assessed by analyzing SSR molecular fingerprints. The results show significant genetic diversity, particularly in the T varieties that contain a higher number of private (unique) alleles. Principal coordinates and STRUCTURE analyses reveal considerable deviation of M varieties from T/G varieties. Evidence of seed mixture in M varieties suggests the use of mixed seeds in contemporary cultivation practices. Cluster analysis further indicates that M varieties have a narrower genetic background, likely due to the limited number of T or G varieties that were used in naked barley breeding. Relationships between increases in genetic diversity and sample sizes highlight the importance of effective sampling strategies for field collections of naked barley varieties. Naked barley (Hordeum vulgare var. nudum) is a staple food crop, contributing significantly to global food security. Understanding genetic diversity will facilitate its effective conservation and utilization. To determine genetic diversity and its distribution within and among varieties, we characterized 30 naked barley varieties from Tibet, representing the traditional, modern, and germplasm-resources-bank gene pools, by analyzing SSR molecular fingerprints. The results demonstrate abundant genetic diversity in Tibetan naked barley varieties, particularly those in the traditional gene pool that holds much more private (unique) alleles. Principal coordinates and STRUCTURE analyses indicate substantial deviation of the modern varieties from the traditional and germplasm-resources-bank varieties. A considerable amount of seed mixture is detected in the modern varieties, suggesting the practices of using mixed seeds in modern-variety cultivation. Cluster analyses further indicate the narrow genetic background of the modern varieties, likely due to the limited number of traditional/germplasm-resources-bank varieties applied in breeding. Relationships between increases in genetic diversity and sample sizes within naked barley varieties highlight the importance of effective sampling strategies for field collections. The findings from this study have important implications for the sustainable utilization and effective conservation of different types of naked barley germplasm, both in Tibet and in other regions around the world. [ABSTRACT FROM AUTHOR]

Hematophagous mosquitoes are considered among the biological evidence that can be collected at the crime scene to identify missing persons, perpetrators, or victims. This study is to simulate what might be expected at a crime scene with an insect that took a human blood meal and then died after various time intervals of post-feeding and remained at the crime scene for more periods. It aimed to analyze the DNA profiling of the Culex pipiens human blood meal stored at room temperature for a week after 24-, 48-, 72- and 96-hours of post-feeding. The two hypervariable regions (HV1 and HV2) of the mtDNA D-loop region were also used to define the possible period for identifying a person at the crime scene. The DNA concentration showed degraded amounts between 8.9 to 0.00 pg/µL due to the long storage. A complete STR profile was possible by direct PCR at 48 hours of postfeeding, while a partial profile was obtained 72 hours of post-feeding. It was possible to amplify HV1 & HV2 up to 96 hours of post-feeding. A gradual decrease of STR allele appearance and mtDNA with time course of postfeeding was recorded. MtDNA is more efficient than STR as HV1 & HV2 regions were possible to be amplified up to 96 hours blood meal of postfeeding. Thus, we conclude that mtDNA is an efficient molecular marker for time course identification of human DNA from blood meals taken by the mosquito. Examination of the blood meal of insects collected from the crime scene over a sufficient period, potentially aids in the identification of suspects and victims. [ABSTRACT FROM AUTHOR]

Escherichia coli harbors various virulence factors responsible for diarrhea and other diseases in neonatal calves. The antimicrobial resistance (AMR) among the diarrheagenic and non-diarrheagenic E. coli may impose a potential health hazard among the calves and make the antibacterial therapy ineffective. The virulence gene expression among AMR strains plays a crucial role in establishing diarrheal disease with therapeutic complications. This study investigates the diversity of E. coli isolates from neonatal calves. E. coli isolated from the fecal samples were subsequently subjected to pathotyping and virulotyping using the PCR technique. AMR profiling was done by phenotypic and genotypic methods. The ERIC pattern of E. coli pathotypes was compared and correlated with the pattern of AMR and virulence traits. 179 isolates were obtained from 158 fecal samples collected from neonatal calves. Forty-two isolates were pathotypable; predominated by shigatoxigenic E. coli. Seventy-four isolates were ESBL producers. Nineteen isolates were carbapenem resistant and 68 isolates exhibited quinolone resistance. blaAmpC, blaVIM and qnrS were the predominant genes detected among ESBL, carbapenem and quinolone resistance genes, respectively. The present study indicated diverse virulence profiles and the presence of significant ESBL, carbapenem and fluoroquinolone resistance among E. coli pathotypes from calves. The analysis of resistance profiling indicates the risks associated with the indiscriminate antibiotic use among farm animals, which may pose a potential health hazard to livestock owners. [ABSTRACT FROM AUTHOR]

This study examines a boreal peatland (the Sagnes peatland, Fanay, Limousin, France) with a depth of 1 m. This peatland is currently in the late stages of organic deposition, as evidenced by the growth of Carex species, along with Sphagnum mosses, in the uppermost level. To gain molecular insights, we conducted an analysis of the lignin and polyphenolic counterparts using HMDS (hexamethyldisilazane) thermochemolysis, enabling the identification of lignin degradation proxies. The goal was to develop characteristic indicators for the state of lignin degradation based on the relative distribution of lignin phenols, measured by gas chromatography coupled with mass spectrometry (GC-MS) after the HMDS thermochemolysis. For that purpose, the singular contribution of the 11 aromatic moieties yielded, along with SGC (sum of lignin moieties) and the most lignin degradation proxies, were applied. It has been shown that HMDS thermochemolysis exhibited the capacity to reveal oxidized and degraded lignin fractions, following the increasing trend yielded for most moieties and SGC proxy, in the mesotelm and catotelm layers. In addition, the C/G (Cinnamyl/Guaiacyl) and S/G (Syringyl/Guaiacyl) ratios showed their highest input in the upper half of the core. This bias in the aforementioned ratios could indicate that HMDS thermochemolysis is to be applied for geological samples, where low G-compounds exist. For the sake of validating HMDS thermochemolysis' application, Principal Component Analysis (PCA) was then applied to the molecular fingerprint. For ratios and proxies of aromatic moieties of HMDS thermochemolysis, the PCA approach exhibited a higher contribution (79%). This indicates the efficiency of these ratios in describing the molecular fingerprint of peat depth records. In addition, a higher separation between the contributions of the investigated variables (molecular proxies) along the first two PCs was noticed. In other words, the variables that showed a high contribution towards PC1 exhibited a low contribution towards PC2, and vice versa. These findings indicate the high reliance of applying the ratios and proxies of HMDS thermochemolysis. [ABSTRACT FROM AUTHOR]

Passports are the number one form of individual identification when crossing borders resulting in counterfeit or modified passports being used to allow illegal travel. Here we report on the use of Diamond Dye to detect cells deposited by touch onto parts of the photograph page of a passport. The passport page was divided into a grid of 11 rectangles of approximately equal dimensions. Thumbprints were deposited at 10 of the 11 squares, with the 11th left blank as a negative control. The location and number of deposited cells were determined and recorded. Cellular material was removed from each square separately, using a moistened swab or a tapelift. Tapelifting was better suited for the substrate resulting in an increase in DNA recovered. The highest total quantity of DNA isolated from the 10 samples post extraction was 0.162 ng. Short tandem repeat data were obtained from all 10 samples using the GlobalFilerTM PCR Amplification Kit. The DNA profiles were single source or two-person mixtures and the donor was always the major contributor. These data show the potential to visualize cellular material deposited by touch and then generate STR data from an item such as a passport after only brief physical contact. [ABSTRACT FROM AUTHOR]

Context.--Tissue contaminants on histology slides represent a serious risk of diagnostic error. Despite their pervasive presence, published peer-reviewed criteria defining contaminants are lacking. The absence of a standardized diagnostic workup algorithm for contaminants contributes to variation in management, including investigation and reporting by pathologists. Objective.--To study the frequency and type of tissue contaminants on microscopic slides using standardized criteria. Using these data, we propose a taxonomy and algorithm for pathologists on "floater" management, including identification, workup, and reporting, with an eye on patient safety. Design.--A retrospective study arm of 1574 histologic glass slides as well as a prospective study arm of 50 slide contamination events was performed. Using these data we propose a structured classification taxonomy and guidelines for the workup and resolution of tissue contamination events. Results.--In the retrospective arm of the study, we identified reasonably sized benign tissue contaminants on 52 of 1574 slides (3.3%). We found size to be an important parameter for evaluation, among other visual features including location on the slide, folding, ink, and tissue of origin. The prospective arm of the study suggested that overall, pathologists tend to use similar features when determining management of potentially actionable contaminants. We also report successfully used case-based ancillary testing strategies, including fluorescence in situ hybridization analysis of chromosomes and DNA finger-printing. Conclusions.--Tissue contamination events are underreported and represent a patient safety risk. Use of a reproducible classification taxonomy and a standardized algorithm for contaminant workup, management, and reporting may aid pathologists in understanding and reducing risk. [ABSTRACT FROM AUTHOR]

Background: Freeze-tolerant animals undergo significant physiological and biochemical changes to overcome challenges associated with prolonged whole-body freezing. In wood frog Rana sylvatica (now Lithobates sylvaticus), up to 65% of total body water freezes in extracellular ice masses and, during this state of suspended animation, it is completely immobile and displays no detectable brain, heart, or respirometry activity. To survive such extensive freezing, frogs integrate various regulatory mechanisms to ensure quick and smooth transitions into or out of this hypometabolic state. One such rapid and reversible regulatory molecule capable of coordinating many aspects of biological functions is microRNA. Herein, we present a large-scale analysis of the biogenesis and regulation of microRNAs in wood frog liver over the course of a freeze–thaw cycle (control, 24 h frozen, and 8 h thawed). Methods/Results: Immunoblotting of key microRNA biogenesis factors showed an upregulation and enhancement of microRNA processing capacity during freezing and thawing. This was followed with RT-qPCR analysis of 109 microRNA species, of which 20 were significantly differentially expressed during freezing and thawing, with the majority being upregulated. Downstream bioinformatics analysis of miRNA/mRNA targeting coupled with in silico protein–protein interactions and functional clustering of biological processes suggested that these microRNAs were suppressing pro-growth functions, including DNA replication, mRNA processing and splicing, protein translation and turnover, and carbohydrate metabolism. Conclusions: Our findings suggest that this enhanced miRNA maturation capacity might be one key factor in the vital hepatic miRNA-mediated suppression of energy-expensive processes needed for long-term survival in a frozen state. [ABSTRACT FROM AUTHOR]

(1) Background: Chagas disease is a public health problem affecting nearly 2 million women of reproductive age in Latin America. From these, 4–8% can transmit the infection to the foetus through the vertical route, whereas horizontal transmission through milk during breastfeeding remains controversial. Therefore, the presence of Trypanosoma cruzi (T. cruzi) DNA in the milk of women seropositive for Chagas disease was analysed to determine whether a relationship with the infection of their children can exist. (2) Methods: 260 pairs (mother–child) from four hospitals located in rural areas endemic to T. cruzi (state of Oaxaca) were studied. The presence of anti-T. cruzi antibodies in the serum of lactating women were determined by ELISA, whereas parasitic DNA in either breast milk or newborn's blood was identified by PCR; (3) Results: The seroprevalence of infection in lactating women was 5.76%, and the frequency of infection detected by PCR in breast milk was 1.92%, while the frequency of infection in the blood of newborns was 1.92%. Pochutla-Oaxaca presented the highest number of positive cases in both breast milk and blood. The only risk factor found was the presence of the vector in the geographical area analysed, favouring the parasite's transmission. Overall, the results suggest a probable transmission of T. cruzi, although whether it was through breastfeeding or through the blood during delivery could not be determined. (4) Conclusions: T. cruzi DNA was identified in lactating women's milk and newborn blood, which is probable evidence of transmission through breastfeeding; nevertheless, future studies must be performed to confirm the presence of the parasite, alive or dead. [ABSTRACT FROM AUTHOR]

Snappers (Lutjaniformes, Lutjanidae) are among the commonest world fish families. They play a vital ecological role as components of coral reef-associated ecosystems. Also, they are very commonly consumed fish. This work implied the application of DNA barcoding to identify some key lutjanids in international fish markets. Samples of Lutjanus ehrenbergii, L. kasmira, L. bohar, L. gibbus, L. argentimaculatus, and L. monostigma were obtained from Hurghada city fish market in the Red Sea, Egypt. Also, samples of L. malabaricus, L. ehrenbergii, and L. fulviflamma were collected from Doha City, Qatar fish markets. These samples were DNA barcoded through sequencing of their mitochondrial cytochrome oxidase subunit 1 (COI) and 12SrDNA barcodes. The resulting DNA barcodes exhibited several cases of misidentification. This included L. gibbus which showed mixed identity with L. erythropterus; L. ehrenbergii with L. fulviflamma; L. malabaricus with L. erythropterus and L. sanguineus; and L. kasmira that was misidentified as L. quinquelineatus, L. rufolineatus, L. fulvus, L. boutton, and L. bengalensis. Moreover, the westernmost L. ehrenbergii showed a polyphyletic relationship with its conspecifics in the Indo-Pacific region. The first encompassed Egyptian, Qatari, and the Western Indian Ocean samples. The second encompassed references from Indo-Pacific countries. This discordant phylogenetic pattern referred to a possible cryptic lineage in L. ehrenbergii. Results of the current research supported the need for more extensive, morphogenetic-based authentication of different lutjanids in the Indian Ocean and its related environments. [ABSTRACT FROM AUTHOR]

Background/Objectives: Beta-lactam antibiotics, derived from penicillin, are the most used class of antimicrobials used for treating bacterial infections. Over the years, microorganisms have developed resistance mechanisms capable of preventing the effect of these drugs. This condition has been a significant public health concern for the 21st century, especially after predictions that antimicrobial resistance could lead to 10 million deaths annually by 2050. The challenge of developing new antimicrobials brings with it the need to ensure the efficacy of existing ones, hence the importance of developing fast and low-cost monitoring techniques. Methods: In this study, we present an alternative based on nanophotonics using Surface-Enhanced Raman Spectroscopy (SERS) mediated by nanoparticles for the detection of antimicrobials, with emphasis on some beta-lactam antibiotics commonly prescribed in cases of critically ill patients. It is a sensitive and accurate technique for drug monitoring, allowing for rapid and specific detection of its molecular signatures. This approach is crucial to address the challenge of antimicrobial resistance and ensure the therapeutic efficacy of existing treatments. Results: Our experiments demonstrate the possibility of identifying spectra with characteristic vibrations (fingerprints) of these antimicrobials via SERS. Conclusions: Our results point to new strategies for molecular monitoring of drugs by optical techniques using unconventional nanoparticles. [ABSTRACT FROM AUTHOR]