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PubMed2026

Proteomic insights into Helicobacter pylori infection in stomach cells, revealing host response and host-targeted therapeutics repurposing.

BACKGROUND: Helicobacter pylori (H. pylori) is a globally prevalent gastric pathogen strongly associated with chronic gastritis, peptic ulcers, and gastric cancer. While bacterial factors have been extensively studied, host proteomic responses and their therapeutic potential remain largely underexplored. RESEARCH DESIGN AND METHODS: Current analyses employed a systematic proteomics-based data integration and harmonization approach (retrospective qualitative cohort study) to identify important differentially regulated host proteins. Proteomic datasets were curated from in vitro studies and analyzed for functional enrichment, protein-protein interaction networks, and hub protein identification. To explore therapeutic repurposing, drug repositioning was performed using the DrugBank database. RESULTS: Data summation describing protein differential regulation in human gastric cells as a result of the infection revealed 1672 perturbed host proteins. Bioinformatics analysis revealed 11 proteins including CSK, MET, RELA, MARK2, GRB2, FTO, PLCG1, CRKL, RPS5, RPS9, and RPS27A to be ideal host targets for therapeutic repurposing. Clinically approved drugs such as Dasatinib (targeting CSK) and Crizotinib (targeting MET) emerged as promising candidates due to favorable pharmacokinetics and known bioactivity. CONCLUSIONS: Host-directed therapeutics could offer alternative strategies to conventional antibiotic therapy, addressing challenges such as resistance and infection recurrence, providing a foundation for future experimental validation and development of host-targeted interventions for infection control.

Humans↗

PubMed1990

Construction of validated, non-redundant composite protein sequence databases.

A strategy has been developed for the construction of a validated, comprehensive composite protein sequence database. Entries are amalgamated from primary source data bases by a largely automated set of processes in which redundant and trivially different entries are eliminated. A modular approach has been adopted to allow scientific judgement to be used at each stage of database processing and amalgamation. Source databases are assigned a priority depending on the quality of sequence validation and commenting. Rejection of entries from the lower priority database, in each pairwise comparison of databases, is carried out according to optionally defined redundancy criteria based on sequence segment mismatches. Efficient algorithms for this methodology are embodied in the COMPO software system. COMPO has been applied for over 2 years in construction and regular updating of the OWL composite protein sequence database from the source databases NBRF-PIR, SWISS-PROT, a GenBank translation retrieved from the feature tables, NBRF-NEW, NEWAT86, PSD-KYOTO and the sequences contained in the Brookhaven protein structure databank. OWL is part of the ISIS integrated data resource of protein sequence and structure [Akrigg et al. (1988) Nature, 335, 745-746]. The modular nature of the integration process greatly facilitates the frequent updating of OWL following releases of the source databases. The extent of redundancy in these sources is revealed by the comparison process. The advantages of a robust composite database for sequence similarity searching and information retrieval are discussed.

Amino Acid Sequence↗

PubMed2026

Scalable medium-density genotyping platforms for cultivar identification, pedigree authentication, marker-assisted and genomic selection, and other applications in strawberry.

A broad spectrum of high-density genotyping approaches, including single-nucleotide polymorphism (SNP) arrays, genotyping-by-sequencing, and whole-genome reduced-representation sequencing, have been shown to perform well in strawberry (Fragaria × ananassa), despite the inherent complexity of the octoploid genome. While these approaches are effective, their routine deployment in breeding programs can be constrained by cost, computational requirements, and workflow complexity. In parallel, many breeding programs continue to rely on locus-specific assays for marker-assisted selection, resulting in fragmented and inefficient genotyping strategies. Here, we describe medium-density amplicon-based genotyping platforms for strawberry designed to provide cost-effective, turnkey solutions that integrate markers used for marker-assisted selection with genome-wide markers suitable for genomic prediction in a single laboratory assay. These platforms were developed by targeting 1,650 or 4,811 target SNPs via amplicon sequencing, and are interoperable with existing high-density genotyping resources, including a widely used 50K SNP array, thereby facilitating data integration across platforms. We benchmarked their performance relative to the 50K SNP array across breeding-relevant applications, including identity and purity testing, pedigree authentication, marker-assisted selection, and genomic selection, and further evaluated the feasibility of genotype imputation to enhance genome-wide information content. Across analyses, the 1,650- and 4,811-amplicon platforms produced results comparable to higher-density platforms while substantially reducing genotyping cost and analytical overhead. This work demonstrates that targeted amplicon-based genotyping can support efficient, scalable, and integrated genome-informed breeding, enabling the routine application of both marker-assisted and genomic selection within strawberry breeding workflows. Open-source R workflows are provided to support streamlined analyses in breeding contexts.

Fragaria↗

PubMed2026

PathMED: an R toolkit for single-sample molecular scoring and machine learning with omics data.

MOTIVATION: Molecular scoring is a popular approach for studying pathway-level functional alterations with omics data. Using molecular scores for tasks such as single-sample molecular characterisation, phenotype prediction or disease stratification has several advantages compared to using omics data directly. Molecular scores provide biological interpretability and are more generalisable across datasets, facilitating data integration and machine learning applications. However, numerous scoring methods are available through different software packages, and currently there is a lack of tools to easily use these scores for model training and prediction. RESULTS: We developed pathMED, an R/Bioconductor package that unifies various scoring methods in a simple framework. Furthermore, pathMED also contains a machine learning module to train and test models that use the calculated molecular scores to predict clinical outcomes. We demonstrate some of its potential applications in three use cases using public omics data. We showed the generalisability of machine learning models trained on transcriptomic scores in predicting clinical outcomes when deploying on proteomic scores. We also demonstrated the application of transcriptomics scores in predicting breast cancer treatment response and identifying pathways strongly associated to tumour biology and treatment response. Finally, we demonstrated the benefit of integrating a novel gene set dissection step into the analysis pipeline to resolve disease heterogeneity at the pathway level. AVAILABILITY: PathMED is freely available in the Bioconductor repository (https://bioconductor.org/packages/release/bioc/html/pathMED.html). Code to reproduce the analyses is publicly available at https://github.com/GENyO-BioInformatics/pathMED_article.

Software↗

PubMed2026

Comprehensive in silico genomics analysis of global trends and host-specific emergence of aminoglycoside resistance in Staphylococcus aureus: a One-Health perspective.

BACKGROUND: Aminoglycosides remain clinically valuable against Staphylococcus aureus. Aminoglycoside resistance in S. aureus represents a critical One Health concern and is primarily driven by aminoglycoside-modifying enzymes (AMEs), which are frequently plasmid-encoded. Although regional studies have provided valuable insights, the global epidemiology of aminoglycoside resistance determinants remains poorly characterized because comprehensive data integrating human, animal, and environmental reservoirs are still lacking. This study addresses this gap by analyzing over 110,000 S. aureus genomes (2000-2025) to map the global resistome, quantify temporal and host-specific trends, and assess the association between genetic determinants and phenotypic resistance. METHODS: We performed a retrospective One Health meta-analysis of 110,309 S. aureus genomes collected between 2000 and 2025 from 128 countries. Genomes were quality-filtered and aminoglycoside resistance determinants were identified using NCBI AMRFinderPlus (v4.0.23). Multilocus sequence typing and host-source harmonization (Human, Animal, Environment, Unknown) enabled clonal and reservoir stratification. Temporal trends in gene prevalence and resistance burden were modeled with robust regression. Geographic and host-associated structuring of key genes was assessed via χ2 and enrichment tests. Machine-learning models (elastic-net, random forests, XGBoost) were benchmarked for minimum inhibitory concentration (MIC) prediction via nested cross-validation, with performance evaluated by mean absolute error, RMSE, and SHAP-based feature importance. All analyses were conducted in R and Python using publicly available, de-identified genomic data. RESULTS: Aminoglycoside resistance-associated genes were dominated by modifying enzyme determinants, with ant(6)-Ia, ant(9)-Ia, aph(3')-IIIa, sat4, aadD1, and aac(6')-Ie/aph(2'')-Ia occurring in 14-22% of isolates worldwide. Temporal analysis revealed significant declines in several major determinants, most notably ant(9)-Ia (-2.22 percentage points per year, p < 0.001), whereas apmA exhibited a non-significant decreasing trend in animal isolates. Host structuring was marked: human clinical isolates concentrated common determinants, while animal and environmental isolates harbored rare alleles (apmA, spw, str, spd). Geographic mapping confirmed near-universal distribution of common genes but focal restriction of rare ones. Publicly available phenotypic data indicated strong activity of amikacin, whereas gentamicin showed a distinct resistant subpopulation that closely corresponded with AME gene carriage. Genotype-phenotype analyses demonstrated strong concordance, with gene-rich complements predicting resistant MIC strata and absence of determinants predicting susceptibility. Analysis across different gene classes revealed frequent co-occurrence of aminoglycoside resistance genes with determinants from other classes, such as mecA, blaZ, and MLS_B, embedding them within multidrug-resistant (MDR) genomic contexts. CONCLUSION: Over 25 years, the prevalence of aminoglycoside resistance-associated genes in S. aureus has declined for several common determinants, while rare veterinary-linked alleles are emerging in animal isolates. Strong genotype-phenotype concordance supports genomic prediction for gentamicin and amikacin, where MIC data are available, although phenotypic confirmation remains essential. The frequent co-occurrence of aminoglycoside resistance genes with other antimicrobial resistance determinants indicates their integration within co-occurrence patterns of MDR genes, defined here as clusters of co-occurring resistance genes often carried on shared mobile genetic elements. These patterns highlight the need for integrated One Health surveillance combining clinical, veterinary, and environmental monitoring with plasmid-context resolution to anticipate emerging threats.

Aminoglycosides↗

PubMed1988

A successful experiment to reduce unnecessary laboratory use in a community hospital.

A series of interventions at a 228-bed general hospital provided physicians with feedback at regular intervals concerning the amount of laboratory services employed in treating their patients. Case-mix-adjusted estimates of laboratory tests allowed each physician to compare use of laboratory tests with that of peers in the same department at the same hospital. Physicians with "excess" practice patterns ordered hundreds more laboratory tests than average each year. A multifaceted educational program included the following: 1) meetings were held concerning costs and unnecessary laboratory tests; 2) physicians were given descriptions of their practice patterns relative to their peers as part of both large and small departmental discussions; 3) the feedback was repeated a year later; 4) a consensus conference established guidelines for test ordering; and 5) a sample of patient records was examined for appropriateness of laboratory test ordering. A total of 37% of a sample of tests ordered during the baseline period by physicians with "excess" practice patterns was classified as inappropriate. The intervention resulted in a reduction of 1.8 tests per patient (P = 0.0005). Eight of the nine tests individually showed reductions in use. Charge data from the target hospital showed a statistically significant reduction in laboratory charges per patient in the quarter following program initiation (P = 0.02) and no evidence for change in a group of five comparison hospitals. There was no evidence for reductions in the ordering of essential tests. These results demonstrate a cost-effective approach to reducing unnecessary costs that can be implemented in hospitals with integrated data systems.

Clinical Laboratory Techniques↗

PubMed1989

Differences between patient and family assessments of depression in Alzheimer's disease.

A structured interview covering the DSM-III criteria for major depression was adapted for separate use with Alzheimer's disease patients and with their families. Data from 36 patients yielded a depression rate of 13.9%, whereas information from their families indicated that the rate was 50.0%. This disagreement reflected greater family endorsement of patients' loss of interest or pleasure, irritability, fatigue, and feelings of worthlessness. Use of DSM-III-R criteria narrowed but did not eliminate the discrepancy between patients' and families' assessments of the patients' depression. Uniform procedures for gathering and integrating data from the family that are relevant to diagnosis in this group are indicated.

Aged↗

PubMed2026

GICPIdb: an archival repository of multimodal data focusing on pathological images for gastrointestinal cancers.

INTRODUCTION: Deep learning (DL) shows great potential for predicting biomarkers from routine histopathological slides of gastrointestinal (GI) cancers. Yet most existing models are validated on limited patient cohorts, while pathological image annotation and molecular marker standardization demand substantial professional expertise. To address these gaps, we constructed the Gastrointestinal Cancer Pathological Image Archive (GICPIdb, gicpidb.shubuzuo.top), a dedicated database and web platform covering seven major GI cancer types. METHODS: High-quality hematoxylin and eosin (H&E)-stained whole-slide images were collected from multiple sources and uniformly processed. Image annotations were performed by board-certified pathologists following standardized protocols. GICPIdb offers five interactive web modules for data uploading, quality control, feature extraction, online annotation and AI-based prediction. Its intuitive interface supports data browsing, retrieval, visualization and downloading. RESULTS: The database houses 2,863 pathologist-annotated, uniformly processed, high-quality H&E stained images collected from 2,655 patients. Of these, 1,699 patients were sourced from The Cancer Genome Atlas (TCGA), 182 from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and 424 from China-Japan Friendship Hospital and 350 from Chifeng Municipal Hospital in Inner Mongolia, China. It also integrates data on over 50 key molecular markers (e.g., MSI, TMB) and prognostic labels related to survival, recurrence and metastasis. DISCUSSION: GICPIdb aims to promote the development of DL-driven AI tools for cancer research and clinical translation. The multi-institutional data collection and standardized annotation pipeline are expected to enhance the generalizability and reproducibility of AI-based prediction models across diverse patient populations.

deep learning↗

PubMed1986

Computed tomographic evaluation of morphological and functional condition of left ventricle in heart aneurysm.

Computed tomography is a valuable method for the diagnosis of post-infarction aneurysm of the left ventricle of the heart. It gives additional information concerning the morphological and functional condition of the left ventricle. The suggested method of layer-by-layer scanning improves the diagnostic efficiency of CT during examination of patients with heart aneurysm and is noninvasive. Precise individual calculation of the peak concentration of contrast medium, defined by dynamic scanning, optimises the process of gated CT. CT makes it possible to study changes in cavity configuration, left ventricle wall thinning, induration and calcification of the myocardium, changes in left ventricle wall mobility, decreased thickening of the myocardium at systole and left ventricle cavity thrombosis--all changes characteristic of left ventricular aneurysm. CT provides important additional information about the condition of the inter-ventricular septum. EDV, ESV and EF data obtained using CT produce important information about the functional state of the left ventricle. Computed tomography can be used as an independent method of left ventricle aneurysm detection, especially in those institutions where more complicated investigation methods are not used and interventional cardiac procedures are not practised. Complex use of computed tomography and left ventriculography in cardiosurgical institutions makes it possible to improve significantly the diagnosis of cardiac aneurysm. Calculation of integral data about left ventricle pumping function based on CT and LVG data gives proper evaluation of the indications for operative intervention in left ventricular aneurysm.

Adult↗

PubMed2026

Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.

Single-cell and spatial omics (SPOs) technologies have advanced how healthcare physicians characterise brain tumours by enabling detailed understanding of their cellular architecture, functional states, and microenvironmental dynamics. These approaches provide high-resolution detection of tumour heterogeneity and allow precise analysis of the brain tumour microenvironment. Their application has also led to the discovery of novel biomarkers used for early brain tumour detection, prognosis, and improved tumour stratification. Furthermore, integrative multi-omic analyses have revealed new therapeutic targets, clarified mechanisms of drug resistance, and uncovered molecular pathways underpinning treatment failure. By bridging cellular-level insights with spatial context, SPOs hold significant promise for advancing personalised diagnostics, predicting therapeutic response, and guiding the development of targeted interventions for brain tumours. Despite these advances, several limitations constrain the full translational potential of SPOs, including high experimental costs, substantial computational demands, lack of standardised protocols, and challenges in data integration and reproducibility. Addressing these barriers through scalable bioinformatic pipelines, consensus experimental frameworks, and cost-effective platforms remains critical for broadening accessibility and enabling clinical adoption.

Brain Neoplasms↗

PubMed1979

An improved procedure for the preparation of rat uterine cell suspensions.

In the present paper we report on an improved procedure for the preparation of free uterine cells which avoids the use of trypsin and employs very low concentration of collagenase. The cells released mechanically from the digested tissue are constantly removed from the enzyme containing medium, thus minimizing exposure to collagenase. 60%-70% of the cells which make up the intact uterus are obtained as free cells and 95% of these cells are viable for at least 15 hours at 37 degrees. Metabolic integrity was assessed by measuring the cell's ability to oxidize glucose and synthesize proteins over extended periods of time. The membrane leucine carrier protein and the membrane Na+/K+ ATPase were found to be fully functional. Electron microscopic analysis of the cells confirmed their structural integrity. Data are presented illustrating that with this system the estrogen binding protein is stable at physiological temperatures. The cells contain approximately 30,000 specific estrogen binding sites, with an apparent KA of 5--6 x 10(9) M-1. At 37 degrees 80% of the hormone receptor complexes were in the nuclear fraction, 20% in the cytoplasm. The similarity of the estrogen receptor binding parameters with those measured in the intact tissue after in vivo hormone adminsistration, together with the cells' structural and metabolic integrity make this procedure for the preparation of uterine cell suspensions in high yields particularly suitable for studies in which minimal cell injury is an essential prerequisite.

Animals↗

PubMed2026

From fragmentation to coordination: strengthening One Health research to support H5N1 preparedness in Cambodia.

OBJECTIVES: Highly pathogenic avian influenza A (H5N1) remains a major zoonotic threat, characterized by persistent transmission in Cambodia since its re-emergence in 2023. Despite strengthened surveillance and the establishment of the Inter-Ministerial Coordination Committee on One Health, limited integration of research across sectors constrains preparedness and response. This viewpoint examines how research supports the One Health system in Cambodia. METHODS: This viewpoint draws on insights obtained from the first national multistakeholder workshop on H5N1, held in March 2026. RESULTS: Fragmentation across epidemiological, clinical, behavioral, environmental, and genomic domains limits the generation of actionable evidence and delays its translation into policy. CONCLUSION: We propose the establishment of a multisectoral technical working group on H5N1 research embedded within the Inter-Ministerial Coordination Committee on One Health to align research priorities, strengthen data integration, and improve evidence-to-policy translation. This approach could enhance national preparedness while simultaneously positioning Cambodia as a model for coordinated One Health research in the Western Pacific region and beyond.

Avian influenza A (H5N1)↗

PubMed2026

A One Health approach to Antimicrobial Resistance: Concepts, challenges, and advances in omics.

Antimicrobial resistance (AMR) is a global threat driven by the interplay between microbial evolution and human activity. Antimicrobial use in human and veterinary medicine, as well as in agriculture, accelerates the selection and dissemination of resistant bacteria and genes across interconnected human, animal, and environmental reservoirs. These dynamic exchanges render single-sector interventions ineffective. A One Health approach integrating human, animal, and environmental health is therefore essential to understand and mitigate the emergence and spread of AMR. This chapter focuses on bacterial antimicrobial resistance, addressing key concepts, major challenges, and emerging technologies within a One Health framework. Advances in next-generation sequencing and omics technologies have transformed our capacity to resolve AMR at unprecedented scale and resolution. These tools enable the tracking of resistance genes and high-risk clones across ecosystems, uncover transmission pathways, and identify key drivers of dissemination. Such insights support real-time epidemiological surveillance, outbreak detection, and targeted interventions. However, translating these advances into routine practice remains a major challenge, requiring harmonized methodologies, data integration, and cross-sector coordination. Addressing AMR demands sustained collaboration across disciplines and stakeholders, including clinicians, veterinarians, farmers, researchers, policymakers, industry, and the public. And framing AMR as a shared ecological and societal responsibility underscores the urgency of coordinated global action. We call for the urgent integration of One Health principles into surveillance, policy, and innovation to preserve antimicrobial effectiveness and safeguard future health.

Humans↗

PubMed1992

Mixed microprocessor-random logic approach for innovative pacing systems.

Modern pacing systems are becoming more and more sophisticated. Conversion of the information supplied by a sensor into suitable parameters for a rate controlling algorithm and the management of complex timing are common tasks for an integrated circuit (IC) in cardiac pacing. An effective solution consists of using a microprocessor to implement algorithms and pacing modes in a flexible way. The key point of using the same hardware resources for different tasks on a time sharing basis allows the design of a less complex IC when compared to a random logic structure with the same performances. The major design problems in a full microprocessor solution are its relatively low operating speed due to the low frequency clock necessary for low current drain, and the sequential structure of the machine itself. This can lead to unacceptable timing inaccuracy in all situations requiring the management of complex decision trees. In order to take full benefit from the advantages of a microprocessor structure without these drawbacks, a mixed microprocessor-random logic approach has been investigated. This architecture uses a microprocessor core to perform all high level nonreal-time operations (setup of the pacing cycle, data reduction and processing, data integrity checks) while a set of random logic peripherals is used for all critical timing aspects.

Algorithms↗

PubMed2024

ONCOLINER: A new solution for monitoring, improving, and harmonizing somatic variant calling across genomic oncology centers.

The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology.

Humans↗

PubMed1989

A relational database of protein structures designed for flexible enquiries about conformation.

A relational database of protein structure has been developed to enable rapid and flexible enquiries about the occurrence of many aspects of protein architecture. The coordinates of 294 proteins from the Brookhaven Data Bank have been processed by standard computer programs to generate many additional terms that quantify aspects of protein structure. These terms include solvent accessibility, main-chain and side-chain dihedral angles, and secondary structure. In a relational database, the information is stored in tables with columns holding the different terms and rows holding the different entries for the terms. The different relational base tables store the information about the protein coordinate set, the different chains in the protein, the amino acid residues and ligands, the atomic coordinates, the salt bridges, the hydrogen bonds, the disulphide bridges and the close tertiary contacts. The database was established under ORACLE management system. Enquiries are constructed in ORACLE using SQL (structured query language) which is simple to use and alleviates the need for extensive computer programs. A single table can be searched for entries that meet various criteria, e.g. all protein solved to better than a given resolution. The power of the database occurs when several tables, or the entries in a single table, are cross-correlated. For example the dihedral angles of proline in the fourth position in an alpha-helix in high resolution structures can be rapidly obtained. The structural database provides a powerful tool to obtain empirical rules about protein conformation. This database of protein structures is part of a joint project between Birkbeck College and Leeds University to establish an integrated data resource of protein sequences and structures (ISIS) that encodes the complex patterns of residues and coordinates that define protein conformation. The entire data resource (ISIS) will provide a system to guide all areas of protein modelling including structure prediction, site-directed mutagenesis and de novo protein design. The availability of ISIS is described in the paper.

Computer Simulation↗

PubMed2026

Comparative genomics reveals genotype-phenotype concordance and cryptic resistomes in clinical Pseudomonas aeruginosa.

BACKGROUND: Pseudomonas aeruginosa (P. aeruginosa) is a major pathogen because of its adaptability. It shows rapid evolution of multidrug resistance (MDR). Phenotype-based diagnostics often fail to detect silent resistance determinants and early adaptive changes. This study integrates phenotypic profiling with whole-genome sequencing (WGS) to examine resistance architecture in clinical isolates from eastern India. METHODS: From 1295 culture-positive P. aeruginosa specimens collected at a tertiary care hospital in eastern India. Using predefined criteria, representative MDR and non-MDR isolates were selected, including distinct resistance phenotypes, specimen-source diversity, and hospital and community-acquired settings; multivariate analysis of resistance profiles illustrated phenotypic diversity. Antimicrobial susceptibility assessed using VITEK-2 and Kirby-Bauer disk diffusion, species identity confirmed by 16 S rRNA sequencing, and genomic analysis processed through a reference-guided workflow. Antimicrobial Resistance (AMR) determinants were identified through CARD, and phylogenetic tree constructed from 454 publicly available P. aeruginosa genomes. RESULTS: MDR exhibited greater sequence divergence relative to PA14 (~ 69,000 variants) than the non-MDR isolate (~ 58,700 variants), with > 92% coverage at ≥ 30X depth. Strong genotype-phenotype concordance observed in MDR isolates across five antibiotic classes, associated with β-lactamase variants (PDC-67, OXA-396) and regulatory adaptations (ArmR, cprS). The non-MDR isolate harboured gyrA (T83I) resistance-associated mutations, PDC-1, and OXA-847 without phenotypic expression, indicating silent resistome. Phylogenetically, MDR isolates clustered tightly within the phylogeny, while the non-MDR isolate formed a distinct lineage. CONCLUSION: Observed genomic differences align with adaptation under antimicrobial selection, though confirmation requires larger collections. The non-MDR isolate retained a silent resistome. Findings highlight limitations of phenotype-only diagnostics, support genomic data integration, and emphasize transcriptomics for hidden resistance expression and regulatory dynamics.

Pseudomonas aeruginosa↗

PubMed1985

Costs of mandates for outpatient mental health care in private health insurance.

Various methods for estimating the cost of mandated mental health benefits have been devised, each resulting in substantially different estimates. These methods neglect to distinguish between the two components of cost to the insurer: social cost (due to increased utilization) and shifted cost (from other sources of payment). We apply a method we developed for estimating the two types of costs of mandates for outpatient mental health services that integrates data from insurers with information from the literature on financing of mental health services. We applied our method to legislation recently proposed in Massachusetts that would double the mandated minimum benefit level from +500 to +1,000. We expect payments by the largest carrier in the state to increase by a factor of 1.65. More than half of this increase represents shifted costs rather than new costs to society.

Ambulatory Care↗