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PubMed2026

Fantastic microbes and where to find them: evaluating learning-by-doing outcomes in a crowdfunded metagenomics workshop.

Metagenomics offers a powerful framework for authentic, interdisciplinary learning, yet it remains underrepresented in undergraduate education due to technical and infrastructural barriers. We hypothesized that a research-based, learning-by-doing metagenomics workshop supported by accessible bioinformatics tools could enhance students' perceived skills, self-efficacy, and conceptual understanding of metagenomic analysis. To test this hypothesis, we designed and evaluated a hybrid hands-on workshop in which undergraduate and postgraduate students analyzed real environmental shotgun metagenomic datasets generated from soil samples collected during a citizen science initiative. Using the graphical workflow platform KBase, participants completed an end-to-end metagenomic analysis, from quality control and assembly to genome reconstruction, taxonomic classification, functional annotation, and scientific presentation of results. Educational outcomes were assessed through validated retrospective pre-post questionnaires, self-efficacy scales, and an open-ended conceptual understanding task. Participants showed significant increases in perceived metagenomic skills and confidence in performing metagenomic analyses, while gains in perceived learning showed a positive trend. Conceptual understanding improved across educational levels, particularly among participants with limited prior experience. Together, these findings demonstrate that authentic, data-driven metagenomics activities can effectively lower barriers to computational biology and foster meaningful learning through hands-on research experiences.

Metagenomics↗

PubMed2026

Conference report: the third Bacterial Genome Sequencing Pan-European Network conference.

The third Bacterial Genome Sequencing Pan-European Network conference, held in Engelberg, Switzerland (12-15 January 2026), brought together experts from six European countries to discuss the implementation of bacterial genome sequencing in clinical microbiology and public health. Key themes included regulatory frameworks (In Vitro Diagnostic Regulation, General Data Protection Regulation), standardization, quality control, data sharing, economic evaluation, and the integration of artificial intelligence and long-read sequencing into diagnostic workflows. Across presentations, panel discussions, and workshops, participants emphasized that successful implementation of genome sequencing requires more than technical capacity: it depends on robust validation, sustainable funding, interoperable data standards, ethical governance, and interdisciplinary collaboration. The meeting highlighted that sequencing should remain question-driven and clinically meaningful, balancing cost, turnaround time, and public health impact. Overall, the conference reinforced the need for coordinated European efforts to advance responsible, standardized, and sustainable genomic surveillance and diagnostics.

bacterial genome sequencing↗

PubMed2026

Reducing haystacks to needles - ViralClust: A Nextflow pipeline to cluster viral sequences.

BACKGROUND: The rapid accumulation of viral genome sequences presents major challenges for downstream analysis tools, including tools for multiple sequence alignments, phylogeny, and genome/alignment visualization, due to computational constraints and sampling biases caused by outbreak-driven over-representation. Selecting representative genomes through clustering offers a principled alternative to random subsampling, yet choosing appropriate clustering strategies remains non-trivial and context-dependent. RESULTS: Here, we present ViralClust, a modular Nextflow pipeline for bias-aware representative selection from large viral genome datasets. ViralClust integrates five distinct clustering algorithms (CD-HIT-EST, SUMACLUST, VSEARCH, MMSeqs2, and HDBSCAN) within a unified workflow, enabling direct comparison of clustering outcomes and flexible adaptation to diverse biological questions, considering a balanced phylogenetic distribution of the selected sequences. We evaluated ViralClust on six RNA and DNA virus datasets ranging from 632 to 156,586 sequences and spanning genome lengths from 890 to 197,185 nucleotides. Across all datasets, clustering reduced dataset size by ~95 % or more while preserving genetic diversity across species, genera, and families, and effectively mitigating biases introduced by outbreaks, partial genomes, and sequence orientation artifacts. CONCLUSIONS: By supporting whole-genome clustering and scalable representative selection, ViralClust enables efficient and reproducible downstream analyses that would otherwise be computationally infeasible. Rather than offering a prescriptive, guided analysis engine, our framework functions as a flexible comparative collection of complementary strategies, allowing users to empirically evaluate trade-offs and choose the ideal method tailored to their specific analytical endpoints.

Bioinformatics↗

PubMed2026

scATAnno: Automated Cell Type Annotation for Single-cell ATAC-seq Data.

Recent advances in single-cell epigenomic techniques have increased the demand for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) analysis. One key analytical task is to determine cell type identity based on epigenetic data. Here, we introduce scATAnno, a Python package designed to automatically annotate scATAC-seq data using large-scale scATAC-seq reference atlases. This workflow generates reference atlases from publicly available datasets, enabling accurate cell type annotation by integrating query data with reference atlases without the use of single-cell RNA sequencing (scRNA-seq) data. To enhance annotation accuracy, we incorporated k-nearest neighbors (KNN)-based and weighted distance-based uncertainty scores to effectively detect cell populations within the query data that are distinct from all cell types in the reference data. We compared and benchmarked scATAnno against five other published cell annotation approaches, demonstrating its superior performance across multiple datasets and metrics. We further showcased the utility of scATAnno across multiple datasets, including peripheral blood mononuclear cells (PBMCs), triple-negative breast cancer (TNBC), and basal cell carcinoma (BCC), and demonstrated that scATAnno accurately annotates cell types across diverse biological conditions. Overall, scATAnno is a useful tool for scATAC-seq reference atlas construction and cell type annotation and can facilitate the interpretation of new scATAC-seq datasets in complex biological systems. scATAnno is publicly available at https://scatanno-main.readthedocs.io/.

Single-Cell Analysis↗

PubMed2025

Accurate identification of abnormal ploidy using an artificial intelligence model in preimplantation genetic testing.

STUDY QUESTION: Can ultra-low-coverage whole-genome sequencing (ulc-WGS) accurately identify abnormal ploidy during preimplantation genetic testing (PGT)? SUMMARY ANSWER: The artificial intelligence (AI)-based PGT-Plus model demonstrates high accuracy in ploidy detection, offering a cost-effective solution that enhances clinical utility of PGT. WHAT IS KNOWN ALREADY: The predominant PGT for aneuploidy can identify chromosomal aneuploidies but cannot determine ploidy status. Transferring embryos with ploidy abnormalities can result in miscarriage and molar pregnancy. On the other hand, in ART, fertilization is assessed by morphological pronuclear assessment at the zygote stage. However, it has a low specificity in the prediction of abnormal ploidy status and embryos deemed abnormally fertilized can yield healthy pregnancies. Accurately identified abnormal ploidy in PGT-A can resolve current limitations and expand the utility range of PGT-A. Several studies have identified ploidy abnormalities; however, they were mainly based on single-nucleotide polymorphism (SNP) arrays or needed to combine additional targeted-next-generation sequencing (NGS) information. Studies based on ulc-WGS remain scarce. STUDY DESIGN SIZE DURATION: The study consisted of two stages: methodology establishment and validation. An AI model, named PGT-Plus, was developed using 653 samples with known ploidy status, which was further validated using 792 different ploidy status samples. In the clinical application stage, the approach was used to analyse the ploidy status of 19 103 normally fertilized PGT blastocysts and 140 single pronucleus (1PN)-derived blastocysts collected between May 2022 and December 2023. All blastocysts were tested using trophectoderm biopsy and NGS. PARTICIPANTS/MATERIALS SETTING METHODS: The methodology is based on the ulc-WGS data. First, based on samples with known ploidy status: the heterozygosity rate of high-frequency biallelic SNPs, the likelihood ratio (LLR) of alleles was calculated under different assumptions ('both parental homologs' [BPH] from a single parent, 'single parental homolog' [SPH] from each parent, disomy, and monosomy) by leveraging allele frequencies and linkage disequilibrium (LD) measured in the 1000 genomes project database. Twenty-three continuous candidate features derived from heterozygosity rates and LLRs of chromosomes or selected windows were included to establish the ploidy prediction AI model. Gini importance analysis and multicollinearity mitigation was performed for feature selection, then the performance of Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression for modelling was compared. Subsequently, the parameter optimization was performed based on the RF model. Ploidy constitution concordance was evaluated in known ploidy status samples. The frequency of abnormal ploidy in normal fertilized PGT blastocysts and 1PN-derived blastocysts (including conventional IVF and ICSI) was evaluated. MAIN RESULTS AND THE ROLE OF CHANCE: Eleven features were collected for model architecture compared to SVM and Logistic Regression; RF achieved superior performance for ploidy detection. The AI model achieved an AUC of 1 for genome-wide-uniparental diploidy (GW-UPD), 1 for triploidy, and 0.99 for diploidy. For the 792 validation samples, 99.5% of samples were successfully detected using the AI model, and the model showed 100% accuracy for ploidy classification. In the clinical application stage, out of 19 103 PGT samples, 19 069 were successfully analysed using the model, with 110 (0.57%) identified as having abnormal ploidy embryos. Among these, 12.7% (14/110) were identified as GW-UPD, and 87.3% (96/110) were triploid. Among 5563 diploid blastocysts transferred, 3478 clinical pregnancies were achieved. Subsequent ploidy analysis was performed for 217 spontaneous abortion and 935 prenatal diagnostic samples, and no abnormal ploidy was identified. Furthermore, of the 140 1PN embryos tested, 40 (28.6%) exhibited GW-UPD, 3 (2.1%) exhibited triploidy, and 97 (69.3%) were determined to be biparental and normally fertilized. Among the 97 biparental embryos, 46 were diploid, 11 were mosaic, and 40 were aneuploid. In terms of the insemination pattern, the percentage of abnormal ploidy in ICSI was significantly higher than in conventional IVF (P < 0.01, 37.1% vs. 2.9%, respectively). With full informed consent, 20 patients without euploidy from normal fertilization chose 1PN-derived biparental and diploid blastocysts to transfer, resulting in 10 clinical pregnancies and 9 ongoing pregnancies. LARGE-SCALE DATA: N/A. LIMITATIONS REASONS FOR CAUTION: Some rare ploidy abnormalities, such as polyploidy with an equal number of identical sets of chromosomes and ploidy mosaicism cannot be accurately identified. Moreover, the origin of abnormal ploidy was not identified due to the unavailability of DNA from both parents. WIDER IMPLICATIONS OF THE FINDINGS: The PGT-Plus AI model provides a ploidy evaluation method based on the conventional PGT-A data and integrates directly into standard PGT-A workflows. Clinical utility results suggest that the model is a valuable tool for identifying embryos with abnormal ploidy in PGT-A and rescuing normal diploid embryos from abnormally fertilized embryos. These findings demonstrate that PGT-Plus significantly enhances the diagnostic accuracy of PGT. STUDY FUNDING/COMPETING INTERESTS: This study was supported by grants from Major Scientific Program of CITIC Group (No. 2023ZXKYB34100, to Ge.L.), Hunan Provincial Grant for Innovative Province Construction (2019SK4012), Hunan Xiangjiang New District (Changsha High-tech Zone) key core technology research project in 2023, and Science Foundation of Hunan Province (Grant 2023JJ30422). All authors declared no conflicts of interest..

artificial intelligence↗

PubMed2006

Reduction of broad-spectrum antibiotic use with computerized decision support in an intensive care unit.

OBJECTIVE: To implement and evaluate the effect of a computerized decision support tool on antibiotic use in an intensive care unit (ICU). DESIGN: Prospective before-and-after cohort study. SETTING: Twenty-four bed tertiary hospital adult medical/surgical ICU. PARTICIPANTS: All consecutive patients from May 2001 to November 2001 (N = 524) and March 2002 to September 2002 (N = 536). INTERVENTION: A real-time microbiology browser and computerized decision support system for isolate directed antibiotic prescription. MAIN OUTCOME MEASURES: Number of courses of antibiotic prescribed, antibiotic utilization (defined daily doses (DDDs)/100 ICU bed-days), antibiotic susceptibility mismatches, and system uptake. RESULTS: There was a significant reduction in the proportion of patients prescribed carbapenems [odds ratio (OR) = 0.61, 95% confidence interval (CI) = 0.39-0.97, P = 0.04], third-generation cephalosporins (OR = 0.58, 95% CI = 0.42-0.79, P = 0.001), and vancomycin (OR = 0.67, 95% CI = 0.45-1.00, P = 0.05) after adjustment for risk factors including Apache II score, suspected infection, positive microbiology, intubation, and length of stay. The decision support tool was associated with a 10.5% reduction in both total antibiotic utilization (166-149 DDDs/100 ICU bed days) and the highest volume broad-spectrum antibiotics. There were fewer susceptibility mismatches for initial antibiotic therapy (OR = 0.63, 95% CI = 0.39-0.98, P = 0.02) and increased de-escalation to narrower spectrum antibiotics. Uptake of the program was high with 6028 access episodes during the 6-month evaluation period. CONCLUSIONS: This tool streamlined collation and clinical use of microbiology results and integrated into the daily ICU workflow. Its introduction was accompanied by a reduction in both total and broad-spectrum antibiotic use and an increase in the number of switches to narrower spectrum antibiotics.

Adult↗

PubMed2026

Computational mass spectrometry and genome mining guided discovery of metallophores produced by Microbulbifer.

Iron is an essential component of cellular biology. Thus, iron's low bioavailability is a key evolutionary pressure guiding microbial dynamics in the marine environment. Among marine bacteria, Microbulbifer is a chemically underexplored and functionally versatile bacterial genus, which is commonly associated with sponges, algae, corals, and sediments. Previously, genome analyses have revealed that Microbulbifer spp. can degrade polymers and synthesize natural products. Despite their recognized potential to produce secondary metabolites, siderophores are yet to be identified in Microbulbifer, and their iron acquisition strategies remain largely unknown. Here, we developed a comprehensive mass spectrometry-based query language code to determine siderophore production by Microbulbifer spp. in mono- and mixed cultures. Using this workflow, we discovered a new metallophore, which we named bulbichelin, as well as a suite of previously unreported petrobactins containing an unprecedented longer chain length acylation on the central spermidine moiety. We applied genome mining methods to describe the biosynthesis of these compounds. Using metal infusion mass spectrometry, we show that bulbichelins bind a variety of metals. Notably, neither of these compounds were produced in a co-culture of Microbulbifer with coral-derived pathogen Vibrio coralliilyticus Cn52-H1. Understanding how siderophores shape interspecies interactions between Microbulbifer spp. and other marine organisms will aid in unraveling the chemical and catalytic versatility of this genus and adaptation in nutrient deplete marine environment.

MassQL↗

PubMed2026

AI'm Here to Help: Enhancing Laboratory Genetic Counseling with Artificial Intelligence.

BACKGROUND: Artificial intelligence (AI) is transforming the fields of genetics and genetic counseling, enhancing both clinical and laboratory practices. The rise of AI technologies has drawn attention to their potential impact on genetic counseling, particularly in patient diagnosis and the counseling processes. CONTENT: In the laboratory, AI plays a critical role in improving communication between laboratory genetic counselors and healthcare providers by automating routine tasks and optimizing workflows. These advancements allow genetic counselors to dedicate more time to addressing complex inquiries, improving genetic test selection, and helping providers interpret genetic test results. As AI continues to integrate into laboratory genetic counseling practice, it presents both opportunities and challenges. At the time of submission, there is a large knowledge gap regarding AI and its application to laboratory genetic counseling, given the lack of published information on this topic. SUMMARY: This article summarizes existing literature, the history and current applications of AI in laboratory genetic counseling, examines its benefits and limitations, and explores future directions for its implementation in the field.

Humans↗

PubMed2026

An efficient woody plant protoplast platform enables transgene-free multiplex genome editing and rapid trait validation in pear.

Multiplex editing is crucial for analysing complex multiple-gene traits in woody plants, yet its application remains limited because of low transformation efficiency and lengthy regeneration cycles. To overcome these barriers, in this study we establish an efficient protoplast isolation protocol for pear (Pyrus) that employs 1.0% cellulase R10 and 0.4% macerozyme R10 with an 8.5 h digestion. Its broad applicability using different digestion times across seven other economically important woody plants is demonstrated. Coupling a 40% PEG-4000-mediated transfection regimen with DNA-free CRISPR/Cas9 ribonucleoprotein (RNP) delivery enables multiplex genome editing in isolated protoplasts. Using this platform, we simultaneously disrupted the key components of the chloroplast division apparatus ARC3, PARC6, and FtsZ2-1a in Pyrus bretschneideri and found that it consistently reproduced macro-chloroplast abnormalities, confirming effective multigene perturbation within a single cellular context. Notably, failure of chloroplast division activated chloroplast-to-nucleus retrograde signaling, as evidenced by the induction of the nuclear stress-response genes RBOHD and ZAT12, a concomitant surge in reactive oxygen species, and progression to severe cellular deformation. Thus, our study establishes a rapid, cross-genus protoplast-RNP workflow that enables DNA-free multiplex editing and accelerates genotype-to-phenotype analyses in woody perennials. The approach provides a practical foundation for functional genomics and supports advances in non-transgenic precision breeding of tree crops.

Protoplasts↗

PubMed2025

Newly Developed Structure-Based Methods Do Not Outperform Standard Sequence-Based Methods for Large-Scale Phylogenomics.

Recent developments in protein structure prediction have allowed the use of this previously limited source of information at genome-wide scales. It has been proposed that the use of structural information may offer advantages over sequences in phylogenetic reconstruction, due to their slower rate of evolution and direct correlation to function. Here, we examined how recently developed methods for structure-based homology search and tree reconstruction compare with current state-of-the-art sequence-based methods in reconstructing genome-wide collections of gene phylogenies (i.e. phylomes). While structure-based methods can be useful in specific scenarios, we found that their current performance does not justify using the newly developed structure-based methods as a default choice in large-scale phylogenetic studies. On the one hand, the best performing sequence-based tree reconstruction methods still outperform structure-based methods for this task. On the other hand, structure-based homology detection methods provide larger lists of candidate homologs, as previously reported. However, this comes at the expense of missing hits identified by sequence-based methods, as well as providing sets of homolog candidates with higher fractions of false positives. These insights help to guide the use of structural data in comparative genomics and highlight the need to continue improving structure-based approaches. Our pipeline is fully reproducible and has been implemented in a Snakemake workflow. This will facilitate a continuous assessment of future improvements of structure-based tools in the AlphaFold era.

Phylogeny↗

PubMed2025

Deep learning guided programmable design of Escherichia coli core promoters from sequence architecture to strength control.

Core promoters are essential regulatory elements that control transcription initiation, but accurately predicting and designing their strength remains challenging due to complex sequence-function relationships and the limited generalizability of existing AI-based approaches. To address this, we developed a modular platform integrating rational library design, predictive modelling, and generative optimization into a closed-loop workflow for end-to-end core promoter engineering. Conserved and spacer region of core promoters exert distinct effects on transcriptional strength, with the former driving large-scale variation and the latter enabling finer gradation. Based on this insight, Mutation-Barcoding-Reverse Sequencing approach was used and constructed a synthetic promoter library comprising 112 955 variants with minimal redundancy and a 16 226-fold expression range. A Transformer-based model trained on this dataset achieved a Pearson correlation of 0.87 with experimentally measured promoter strengths. When combined with a conditional diffusion model, the system enabled de novo generation of promoter sequences with defined strengths, achieving a design-to-measurement correlation of 0.95 and maintaining high accuracy (R = 0.93) across varied sequence contexts. The designed promoters consistently preserved their intended strength gradients, demonstrating robust plug-and-play functionality. This work establishes a scalable and extensible platform (www.yudenglab.com) for deep learning-guided programmable design of Escherichia coli core promoters, enabling precise transcriptional control.

Promoter Regions, Genetic↗

PubMed2026

Target site selection and P1 engineering enable highly efficient circular RNA production via end-to-end self-targeting and splicing.

Circular RNAs (circRNAs) are more stable than linear RNAs, enabling expanding applications in RNA vaccines and therapeutics. We previously developed an in vitro circRNA preparation method based on end-to-end self-targeting and splicing (STS) using the Tetrahymena group I intron, which generates circRNAs without extraneous sequences. However, self-circularization efficiency declines as gene of interest (GOI) length increases, limiting its application to longer GOIs. Here, we systematically optimized key determinants of STS efficiency, including target site selection and P1 construct engineering. Target site screening revealed that selection of optimal target sites within each GOI markedly improved self-circularization efficiency. Moreover, engineering of the P1 construct, including incorporation of a polyA10 sequence upstream of the internal guide sequence of the intron and an antisense sequence complementary to the target site and its upstream region at the 5' side of polyA10, further enhanced efficiency. Notably, the optimized STS strategy achieved up to two-fold higher self-circularization efficiency than the conventional permuted intron-exon (PIE) method for long GOIs (∼8 K-nt). Collectively, these results establish an improved STS workflow for efficient circRNA production without extraneous sequences across a wide range of GOI lengths, outperforming the PIE method for long GOIs, and broadening biomedical applications.

RNA, Circular↗

PubMed2005

ASIAN: a web server for inferring a regulatory network framework from gene expression profiles.

The standard workflow in gene expression profile analysis to identify gene function is the clustering by various metrics and techniques, and the following analyses, such as sequence analyses of upstream regions. A further challenging analysis is the inference of a gene regulatory network, and some computational methods have been intensively developed to deduce the gene regulatory network. Here, we describe our web server for inferring a framework of regulatory networks from a large number of gene expression profiles, based on graphical Gaussian modeling (GGM) in combination with hierarchical clustering (http://eureka.ims.u-tokyo.ac.jp/asian). GGM is based on a simple mathematical structure, which is the calculation of the inverse of the correlation coefficient matrix between variables, and therefore, our server can analyze a wide variety of data within a reasonable computational time. The server allows users to input the expression profiles, and it outputs the dendrogram of genes by several hierarchical clustering techniques, the cluster number estimated by a stopping rule for hierarchical clustering and the network between the clusters by GGM, with the respective graphical presentations. Thus, the ASIAN (Automatic System for Inferring A Network) web server provides an initial basis for inferring regulatory relationships, in that the clustering serves as the first step toward identifying the gene function.

Cluster Analysis↗

PubMed2006

The MIGenAS integrated bioinformatics toolkit for web-based sequence analysis.

We describe a versatile and extensible integrated bioinformatics toolkit for the analysis of biological sequences over the Internet. The web portal offers convenient interactive access to a growing pool of chainable bioinformatics software tools and databases that are centrally installed and maintained by the RZG. Currently, supported tasks comprise sequence similarity searches in public or user-supplied databases, computation and validation of multiple sequence alignments, phylogenetic analysis and protein-structure prediction. Individual tools can be seamlessly chained into pipelines allowing the user to conveniently process complex workflows without the necessity to take care of any format conversions or tedious parsing of intermediate results. The toolkit is part of the Max-Planck Integrated Gene Analysis System (MIGenAS) of the Max Planck Society available at www.migenas.org (click 'Start Toolkit').

Animals↗

PubMed2006

Nanoliter high throughput quantitative PCR.

Understanding biological complexity arising from patterns of gene expression requires accurate and precise measurement of RNA levels across large numbers of genes simultaneously. Real time PCR (RT-PCR) in a microtiter plate is the preferred method for quantitative transcriptional analysis but scaling RT-PCR to higher throughputs in this fluidic format is intrinsically limited by cost and logistic considerations. Hybridization microarrays measure the transcription of many thousands of genes simultaneously yet are limited by low sensitivity, dynamic range, accuracy and sample throughput. The hybrid approach described here combines the superior accuracy, precision and dynamic range of RT-PCR with the parallelism of a microarray in an array of 3072 real time, 33 nl polymerase chain reactions (RT-PCRs) the size of a microscope slide. RT-PCR is demonstrated with an accuracy and precision equivalent to the same assay in a 384-well microplate but in a 64-fold smaller reaction volume, a 24-fold higher analytical throughput and a workflow compatible with standard microplate protocols.

Cells, Cultured↗

PubMed2003

Validation of a novel, fully integrated and flexible microarray benchtop facility for gene expression profiling.

Here we describe a novel microarray platform that integrates all functions needed to perform any array-based experiment in a compact instrument on the researcher's laboratory benchtop. Oligonucle otide probes are synthesized in situ via a light- activated process within the channels of a three-dimensional microfluidic reaction carrier. Arrays can be designed and produced within hours according to the user's requirements. They are processed in a fully automatic workflow. We have characterized this new platform with regard to dynamic range, discrimination power, reproducibility and accuracy of biological results. The instrument detects sample RNAs present at a frequency of 1:100 000. Detection is quantitative over more than two orders of magnitude. Experiments on four identical arrays with 6398 features each revealed a mean coefficient of variation (CV) value of 0.09 for the 6398 unprocessed raw intensities indicating high reproducibility. In a more elaborate experiment targeting 1125 yeast genes from an unbiased selection, a mean CV of 0.11 on the fold change level was found. Analyzing the transcriptional response of yeast to osmotic shock, we found that biological data acquired on our platform are in good agreement with data from Affymetrix GeneChips, quantitative real-time PCR and--albeit somewhat less clearly--to data from spotted cDNA arrays obtained from the literature.

Automation↗

PubMed2005

Status and prospects of digital detector technology for CR and DR.

Projection radiography is in the middle of the transition from conventional screen-film imaging to digital image acquisition modalities, mainly based on imaging plates (computed radiography, CR) and flat-panel detectors (direct radiography, DR). Cassette-based CR has been available for the past 20 y, and constitutes the major part of direct radiography installations in hospitals today. direct radiography systems based on large-area amorphous silicon active matrix arrays are commercially available for the last 5 y and exist basically in two different types: with scintillators or photoconductors as X-ray conversion material ('indirect' or 'direct' type). direct radiography systems allow for improved image quality and/or dose reduction due to their high detective quantum efficiency and enable faster workflow because of instant image availability. However, new technology developments are improving the performance for CR systems as well, rendering it competitive to direct radiography in many practical aspects. Therefore, it is assumed that the CR and direct radiography systems will coexist for many years to come. This paper reviews the digital detector technologies and the possible future directions of development.

Computers↗

PubMed2026

A liquid handling platform for standardized quantification of cell-free enzymatic activity encoded by antimicrobial resistance genes.

Antimicrobial resistance (AMR) is a growing global threat to human health, and rapid methods for characterizing emerging antimicrobial resistance genes (ARGs) are needed. Here, we develop a semi-automated workflow using cell-free gene expression systems to measure the activity of two ARGs encoded on plasmid DNA that produce rifampicin-inactivating and gentamicin-inactivating enzymes. We validated the use of a small benchtop Myra liquid handling system compared to manual pipetting, with no statistical differences observed. After optimizing the pre-incubation time of ARGs and dispensing protocol, expression of aac(3)-IIa increased the half-maximal inhibition concentration (IC50) of gentamicin by over 150-fold, whilst arr-3 increased the IC50 of rifampicin by ~20-fold compared to controls. This methodology for rapid, semi-automated ARG characterization offers a strategy to combat AMR by assessing novel ARGs identified through genomic surveillance or profiling activity of new or derivative antibiotics.

aminoglycoside resistance↗