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ChatGPT: Increasing accessibility for natural language processing in healthcare quality measurement
In this issue of Infection Control and Healthcare Epidemiology, Perret and Schmidt explore the potential for ChatGPT to support HAI surveillance activities for facilities with limited information technology (IT) resources to support automated detection.1 Although standardized definitions exist for HAIs, local data collection and recording practices vary, leading to differences in how these definitions are interpreted. Clinical notes can pose challenges, such as historical data copy forward, inconsistencies within the same note, variable spellings and abbreviations, among other real-world implementation barriers. [...]how their model performance will translate to actual clinical notes remains unknown; theoretically, however, ChatGPT should be able to learn how to read clinical documentation despite these challenges with real-world documentation. Not only could such technology reduce the human resources required to conduct HAI surveillance, but ChatGPT’s reduced need for location-specific training data also allows broader healthcare applications, potentially standardizing surveillance practices and workflows across facilities and improving interfacility comparison.
Journal Article
Human Papillomavirus 16 E6 and E7 Oncoproteins Alter the Abundance of Proteins Associated with DNA Damage Response, Immune Signaling and Epidermal Differentiation
The high-risk human papillomaviruses are oncogenic viruses associated with almost all cases of cervical carcinomas, and increasing numbers of anal, and oral cancers. Two oncogenic HPV proteins, E6 and E7, are capable of immortalizing keratinocytes and are required for HPV associated cell transformation. Currently, the influence of these oncoproteins on the global regulation of the host proteome is not well defined. Liquid chromatography coupled with quantitative tandem mass spectrometry using isobaric-tagged peptides was used to investigate the effects of the HPV16 oncoproteins E6 and E7 on protein levels in human neonatal keratinocytes (HEKn). Pathway and gene ontology enrichment analyses revealed that the cells expressing the HPV oncoproteins have elevated levels of proteins related to interferon response, inflammation and DNA damage response, while the proteins related to cell organization and epithelial development are downregulated. This study identifies dysregulated pathways and potential biomarkers associated with HPV oncoproteins in primary keratinocytes which may have therapeutic implications. Most notably, DNA damage response pathways, DNA replication, and interferon signaling pathways were affected in cells transduced with HPV16 E6 and E7 lentiviruses. Moreover, proteins associated with cell organization and differentiation were significantly downregulated in keratinocytes expressing HPV16 E6 + E7. High-risk HPV E6 and E7 oncoproteins are necessary for the HPV-associated transformation of keratinocytes. However their influence on the global dysregulation of keratinocyte proteome is not well documented. Here shotgun proteomics using TMT-labeling detected over 2500 significantly dysregulated proteins associated with E6 and E7 expression. Networks of proteins related to interferon response, inflammation and DNA damage repair pathways were altered.
Journal Article
Sustainable Workplaces and Employee Well-Being: A Systematic Review of ESG-Linked Physical Activity Programs
: Despite evidence of potential benefits, variability in exercise types, psychological outcomes, and methods hinders comprehensive cost-effectiveness evaluation, framed through Stimulus-Organism-Response (S-O-R) theory. In this context, Workplace Physical Activity-Based Programs (WPABPs) serve as environmental stimulation that influences employees' emotional states, which in turn shape mental health outcomes and behavioral responses.
This systematic review examines WPABPs through the social dimension of the Environmental, Social, Governance (ESG-S) framework, with a focus on their impact on employees' mental health.
: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, eligibility was assessed via the PICO (Population, Intervention, Comparison, Outcome) framework. The ScienceDirect, Scopus, Google Scholar, and PubMed databases were searched using Medical Subject Headings (MeSH) aligned keywords and Boolean operators.
: Of the 961 articles identified, 15 studies (2021-2025) met the inclusion criteria. WPABPs were found to improve employee mental health, reduce stress, and enhance well-being. Individualized interventions supported targeted psychological benefits, while group formats promoted social cohesion and engagement. Variations in type, duration, and delivery, as well as accessibility barriers for underrepresented employees, were noted. WPABPs enhance employee well-being and organizational outcomes, contributing to the Sustainable Development Goals (SDGs), specifically SDG 3 (Good Health and Well-being) and SDG 8 (Decent Work and Economic Growth).
: Hybrid models combining individual and group approaches with managerial and digital support are recommended. Integrating WPABPs within ESG-S and Corporate Social Responsibility (CSR) frameworks can institutionalize sustainable workplace health promotion, while future research should focus on standardized, inclusive, and long-term evaluations.
Journal Article
Systematic evaluation of supervised machine learning for sample origin prediction using metagenomic sequencing data
Background
The advent of metagenomic sequencing provides microbial abundance patterns that can be leveraged for sample origin prediction. Supervised machine learning classification approaches have been reported to predict sample origin accurately when the origin has been previously sampled. Using metagenomic datasets provided by the 2019 CAMDA challenge, we evaluated the influence of variable technical, analytical and machine learning approaches for result interpretation and novel source prediction.
Results
Comparison between 16S rRNA amplicon and shotgun sequencing approaches as well as metagenomic analytical tools showed differences in normalized microbial abundance, especially for organisms present at low abundance. Shotgun sequence data analyzed using Kraken2 and Bracken, for taxonomic annotation, had higher detection sensitivity. As classification models are limited to labeling pre-trained origins, we took an alternative approach using Lasso-regularized multivariate regression to predict geographic coordinates for comparison. In both models, the prediction errors were much higher in Leave-1-city-out than in 10-fold cross validation, of which the former realistically forecasted the increased difficulty in accurately predicting samples from new origins. This challenge was further confirmed when applying the model to a set of samples obtained from new origins. Overall, the prediction performance of the regression and classification models, as measured by mean squared error, were comparable on mystery samples. Due to higher prediction error rates for samples from new origins, we provided an additional strategy based on prediction ambiguity to infer whether a sample is from a new origin. Lastly, we report increased prediction error when data from different sequencing protocols were included as training data.
Conclusions
Herein, we highlight the capacity of predicting sample origin accurately with pre-trained origins and the challenge of predicting new origins through both regression and classification models. Overall, this work provides a summary of the impact of sequencing technique, protocol, taxonomic analytical approaches, and machine learning approaches on the use of metagenomics for prediction of sample origin.
Journal Article
The performance status gap in immunotherapy for frail patients with advanced non-small cell lung cancer
PurposeIn advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitor (ICI) monotherapy is often preferred over intensive ICI treatment for frail patients and those with poor performance status (PS). Among those with poor PS, the additional effect of frailty on treatment selection and mortality is unknown.MethodsPatients in the veterans affairs national precision oncology program from 1/2019–12/2021 who received first-line ICI for advanced NSCLC were followed until death or study end 6/2022. Association of an electronic frailty index with treatment selection was examined using logistic regression stratified by PS. We also examined overall survival (OS) on intensive treatment using Cox regression stratified by PS. Intensive treatment was defined as concurrent use of platinum-doublet chemotherapy and/or dual checkpoint blockade and non-intensive as ICI monotherapy.ResultsOf 1547 patients receiving any ICI, 66.2% were frail, 33.8% had poor PS (≥ 2), and 25.8% were both. Frail patients received less intensive treatment than non-frail patients in both PS subgroups (Good PS: odds ratio [OR] 0.67, 95% confidence interval [CI] 0.51 − 0.88; Poor PS: OR 0.69, 95% CI 0.44 − 1.10). Among 731 patients receiving intensive treatment, frailty was associated with lower OS for those with good PS (hazard ratio [HR] 1.53, 95% CI 1.2 − 1.96), but no association was observed with poor PS (HR 1.03, 95% CI 0.67 − 1.58).ConclusionFrail patients with both good and poor PS received less intensive treatment. However, frailty has a limited effect on survival among those with poor PS. These findings suggest that PS, not frailty, drives survival on intensive treatment.
Journal Article
Enhancing development team flexibility in IS projects
Information system development projects face tremendous challenges because of business changes and technology changes. Research has shown that software team flexibility has a positive effect on project outcomes, but specific requirements for enhancing flexibility are lacking. Drawing from the input-mediator-outcome (IMO) team effectiveness framework, this research investigates the contextual inputs and team processes that lead to development team flexibility and how well team flexibility improves project outcomes. A survey was developed to consider a model derived from the IMO framework. One hundred fourteen members of information systems development project teams in China responded to the survey. Partial least squares analysis was used served to analyze the data. Results indicate that a participatory culture and cooperative norms are an effective foundation for improving required processes that include project coordination of the project and knowledge sharing activities. In turn, the improved process performance extends responses to changes in technology and the business climate. The improved flexibility in meeting change is predictive of outcomes related to project performance and quality of the final product.
Journal Article
Specific insertions of zinc finger domains into Gag-Pol yield engineered retroviral vectors with selective integration properties
Retroviral vectors offer benefits of efficient delivery and stable gene expression; however, their clinical use raises the concerns of insertional mutagenesis and potential oncogenesis due to genomic integration preferences in transcriptional start sites (TSS). We have shifted the integration preferences of retroviral vectors by generating a library of viral variants with a DNA-binding domain inserted at random positions throughout murine leukemia virus Gag-Pol, then selecting for variants that are viable and exhibit altered integration properties. We found seven permissive zinc finger domain (ZFD) insertion sites throughout Gag-Pol, including within p12, reverse transcriptase, and integrase. Comprehensive genome integration analysis showed that several ZFD insertions yielded retroviral vector variants with shifted integration patterns that did not favor TSS. Furthermore, integration site analysis revealed selective integration for numerous mutants. For example, two retroviral variants with a given ZFD at appropriate positions in Gag-Pol strikingly integrated primarily into four common sites out of 3.1 × 10⁹ possible human genome locations (P = 4.6 × 10⁻²⁹). Our findings demonstrate that insertion of DNA-binding motifs into multiple locations in Gag-Pol can make considerable progress toward engineering safer retroviral vectors that integrate into a significantly narrowed pool of sites on human genome and overcome the preference for TSS.
Journal Article
Clinical Metagenomics Is Increasingly Accurate and Affordable to Detect Enteric Bacterial Pathogens in Stool
Stool culture is the gold standard method to diagnose enteric bacterial infections; however, many clinical laboratories are transitioning to syndromic multiplex PCR panels. PCR is rapid, accurate, and affordable, yet does not yield subtyping information critical for foodborne disease surveillance. A metagenomics-based stool testing approach could simultaneously provide diagnostic and public health information. Here, we evaluated shotgun metagenomics to assess the detection of common enteric bacterial pathogens in stool. We sequenced 304 stool specimens from 285 patients alongside routine diagnostic testing for Salmonella spp., Campylobacter spp., Shigella spp., and shiga-toxin producing Escherichia coli. Five analytical approaches were assessed for pathogen detection: microbiome profiling, Kraken2, MetaPhlAn, SRST2, and KAT-SECT. Among analysis tools and databases compared, KAT-SECT analysis provided the best sensitivity and specificity for all pathogens tested compared to culture (91.2% and 96.2%, respectively). Where metagenomics detected a pathogen in culture-negative specimens, standard PCR was positive 85% of the time. The cost of metagenomics is approaching the current combined cost of PCR, reflex culture, and whole genome sequencing for pathogen detection and subtyping. As cost, speed, and analytics for single-approach metagenomics improve, it may be more routinely applied in clinical and public health laboratories.
Journal Article