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PubMed2026

Meta-analysis of growth and inactivation kinetics of Legionella.

Quantitative risk assessments intended to inform evidence-based water management plans and public health targets for Legionella in engineered water systems are constrained by fragmented and heterogeneous growth and inactivation kinetics. We conducted a meta-analysis of 25 growth and 39 thermal- and chemical-inactivation studies, fitting microbial persistence models to harmonize parameters. Nonlinear models outperformed first-order formulations, indicating that lag phases and resistant or protected subpopulations are central to Legionella persistence. Random forest analysis identified environmental and methodological drivers of variability based on 226 growth rates and reduction times for thermal (209) and chemical (135) inactivation. Growth was primarily governed by temperature, nutrient availability, and compatible Legionella-host pairings; thermal inactivation by quantification method, temperature, and turbidity; and chemical inactivation by inoculum size, disinfectant type, concentration, and host-associations. Accordingly, temperature-dependent growth parameters and exposure metrics for heat, free-chlorine, and monochloramine, expressed as TT (Temperature×time) and CT (Concentration×time), were derived as condition-specific inputs for predictive models. Growth optima around 37-40 °C, together with lag-time estimates, indicate that hot-water temperature setbacks and energy-saving practices may favor Legionella proliferation under repeated or prolonged lukewarm exposure. Culture- and viability-based TT differences highlight the need to consider viable‑but-non-culturable persistence in monitoring programs. CT comparisons suggest monochloramine may be advantageous because of its lower apparent sensitivity to host-associated protection. Although limited by restricted experimental conditions, the findings show that predictive models should account for microbial ecology, water matrix effects, and quantification endpoints. Future kinetic studies should prioritize realistic multi-host systems, strain pre-adaptation, complementary viability measurements, and standardized protocols and reporting to ensure reproducibility and enable robust system-level predictive modeling.

Legionella↗

PubMed1979

[The problems of lipid metabolism. Demands for diagnostically improved insight into the function of lipoproteins (author's transl)].

In the course of a follow-up of 87 subjects with known hyperlipoproteinemia a new, simplified method was tested for quantification of the individual lipoprotein fractions capable of being performed by every larger laboratory, in contrast to the expensive ultracentrifugation. The LDL/HDL ratio proved to be the conclusive parameter for daily diagnosis in hospital and general practise. This enabled the most important aspects of the lipid metabolic situation of a patient to be recognized immediately.

Arteriosclerosis↗

PubMed2023

Bovine meat and milk factor protein expression in tumor-free mucosa of colorectal cancer patients coincides with macrophages and might interfere with patient survival.

Bovine milk and meat factors (BMMFs) are plasmid-like DNA molecules isolated from bovine milk and serum, as well as the peritumor of colorectal cancer (CRC) patients. BMMFs have been proposed as zoonotic infectious agents and drivers of indirect carcinogenesis of CRC, inducing chronic tissue inflammation, radical formation and increased levels of DNA damage. Data on expression of BMMFs in large clinical cohorts to test an association with co-markers and clinical parameters were not previously available and were therefore assessed in this study. Tissue sections with paired tumor-adjacent mucosa and tumor tissues of CRC patients [individual cohorts and tissue microarrays (TMAs) (n = 246)], low-/high-grade dysplasia (LGD/HGD) and mucosa of healthy donors were used for immunohistochemical quantification of the expression of BMMF replication protein (Rep) and CD68/CD163 (macrophages) by co-immunofluorescence microscopy and immunohistochemical scoring (TMA). Rep was expressed in the tumor-adjacent mucosa of 99% of CRC patients (TMA), was histologically associated with CD68+/CD163+ macrophages and was increased in CRC patients when compared to healthy controls. Tumor tissues showed only low stromal Rep expression. Rep was expressed in LGD and less in HGD but was strongly expressed in LGD/HGD-adjacent tissues. Albeit not reaching statistical significance, incidence curves for CRC-specific death were increased for higher Rep expression (TMA), with high tumor-adjacent Rep expression being linked to the highest incidence of death. BMMF Rep expression might represent a marker and early risk factor for CRC. The correlation between Rep and CD68 expression supports a previous hypothesis that BMMF-specific inflammatory regulations, including macrophages, are involved in the pathogenesis of CRC.

Humans↗

PubMed1975

Protease inhibitors in chronic obstructive pulmonary disease.

Quantification of the major plasma protease inhibitors and genetic typing of alpha1-antirypsin were done in 107 patients with chronic obstructive pulmonary disease and in 91 control subjects with normal ventilatory function who were similar with respect to age, race, and sex. There was a significant increase in frequency of the PiZ gene and the Pi MZ phenotype of alpha1-antitrypsin among the patients when compared with the control subjects. No evidence for a primary deficiency of any other antiprotease was found; however, the mean concentration of inter-alpha-trypsin inhibitor was significantly lower in the patients than the control subjects, and moderate deficiency of alpha1-antichymotrypsin was noted in a few patients. These data indicate an increased risk of developing chronic obstructive pulmonary disease in persons with the Pi MZ phenotype of alpha1-antirypsin and suggest a possible relationship between these diseases and low serum concentrations of inter-alpha-trypsin inhibitor.

Adult↗

PubMed2026

Calibrated Prediction Intervals for Polygenic Scores: Updated Comparisons, Contextual Calibration, and Data Normalization.

Calibrated prediction intervals for polygenic scores (PGS) are essential for communicating individual-level uncertainty in genomic medicine. We present updated comparisons of two methods for constructing such intervals: CalPred, a parametric approach, and PredInterval, a non-parametric approach. Our results show that both methods can achieve calibrated coverage, although CalPred additionally requires a sufficiently large calibration set. The two methods also exhibit complementary trade-offs with respect to dataset size and risk identification. We further show that contextual calibration, as introduced in Hou et al. and followed in Shi et al., is most naturally achieved through appropriate phenotype normalization and data preprocessing. Apparent miscalibration can arise from inadequate normalization or from providing contextual information to some methods but not others. In UK Biobank, standard GWAS phenotype normalization procedures are sufficient to achieve contextual calibration for traits analyzed. In the extreme simulations of Hou et al. and Shi et al., supplying contextual covariates to PredInterval restores contextual calibration without normalization, and appropriate normalization can achieve contextual calibration without supplying covariates, while also substantially improving upstream tasks including association power and PGS accuracy. Together, these results underscore the central role of phenotype normalization and data preprocessing in GWAS analyses, including reliable uncertainty quantification for PGS.

Journal Article↗

PubMed2026

Telomere length in patients with non-functional adrenal incidentalomas.

Telomeres maintain genomic integrity during cell replication by preventing chromosomal fusions. Beside genetic influences, telomere length is affected by environmental factors such as oxidative stress and inflammation. These mechanisms also contribute to metabolic syndrome components linked to cellular aging. We aim to evaluate whether telomere length is shortened in patients with non-functional adrenal incidentaloma (NFAI) compared to the control group. This study was designed as a prospective, single-center study. The total of 88 participants included were 44 patients aged between 40 and 60 years with NFAI in our endocrinology clinic and 44 control subjects. An Absolute Human Telomere Lengths Quantification qPCR Assay kit (Nucleotestbio, Budapest, Hungary) was used for analyses. There was no significant difference between the NFAI and control groups regarding age and sex distribution. Telomere length was significantly shorter in the NFAI group (NFAI group: 3.680 ± 1.970 kb; control group: 4.469 ± 1.672 kb; p = 0.046). While no significant difference was found in telomere lengths in subgroup analyses, patients with basal adrenocorticotropic hormone (ACTH) levels <15 pg/mL had significantly shorter telomeres than those with basal ACTH levels ≥15 pg/mL (p = 0.034). A strong positive correlation was observed only between telomere length and ACTH level (p = 0.001). This study demonstrated that telomere length is significantly shortened in NFAI patients. Here, we propose that the underlying cause of telomere length shortening in the NFAI group may be related to increased cardiovascular risk and an elevated inflammatory state, even in the presence of cortisol levels within the normal range.

Humans↗

PubMed2026

Emergence of cefiderocol resistance in carbapenem-resistant Escherichia coli ST167 prior to clinical use: A multifactored resistance landscape.

OBJECTIVES: Cefiderocol is a novel siderophore cephalosporin with potent activity against multidrug-resistant Gram-negative bacteria. Here, we reported the prevalence and mechanisms of cefiderocol resistance in carbapenem-resistant Escherichia coli (CREC) in China before its clinical use. METHODS: A total of 443 non-duplicate CREC isolates collected from 67 hospitals in China (2013-2021) underwent antimicrobial susceptibility testing according to CLSI guidelines. Whole-genome sequencing, transcriptomic analysis, siderophore quantification, and targeted genetic manipulation were performed to investigate the underlying resistance mechanisms. RESULTS: Among the 443 CREC isolates, 102 (23.0%) were resistant to cefiderocol, and 34 (7.6%) showed intermediate susceptibility. Multivariable logistic regression identified ST167 lineage (OR, 3.05; 95% CI, 1.12-8.29; P = 0.028), blaNDM-5 carriage (OR, 9.04; 95% CI, 2.96-27.57; P < 0.001), and cirA truncation (OR, 49.56; 95% CI, 20.33-120.79; P < 0.001) as independent factors associated with cefiderocol resistance. Among ST167 isolates, cefiderocol-resistant isolates showed increased yersiniabactin carriage and siderophore production but comparable TonB-dependent transporter expression profiles. Phylogenetic analysis revealed that cefiderocol-resistant ST167 isolates clustered into a distinct subclade enriched with resistance-associated determinants, including a recurrent FhuA P50S substitution detected in 59/64 (92.2%) resistant isolates. Functional assays showed that the P50S substitution increased cefiderocol minimum inhibitory concentration (0.032-0.125 µg/mL), particularly in an NDM-5-producing background (0.032-0.5 µg/mL). CONCLUSIONS: Cefiderocol resistance is highly prevalent among high-risk ST167 CREC isolates before the clinical introduction of cefiderocol in China, highlighting the need for continued surveillance of this epidemic lineage. Cefiderocol resistance is mediated by multiple resistance determinants, and we identify the recurrent FhuA P50S substitution as a novel contributor to reduced cefiderocol susceptibility.

Antimicrobial resistance↗

PubMed2025

Patterns of HIV-1 viral load suppression and drug resistance during the dolutegravir transition: a population-based longitudinal study.

BACKGROUND: Data on the population-scale impact of dolutegravir (DTG)-based HIV regimens in sub-Saharan Africa are extremely limited. We used data from a surveillance cohort in southern Uganda to assess viral suppression and antiretroviral (ART) resistance over 10-years alongside DTG scale-up. METHODS: Consenting participants in the population-based Rakai Community Cohort Study between August 2011 and March 2023 aged 15-59 completed questionnaires and provided samples for HIV testing, viral load quantification, and viral deep-sequencing. We collected data on DTG-utilization at HIV care clinics. We estimated the prevalence of HIV suppression (<1,000 copies/mL) and ART resistance using robust Poisson regression. Bayesian logistic regression quantified associations between resistance and individual-level suppression across surveys. FINDINGS: Among 20,383 people living with HIV (PLHIV), suppression increased from 57.1% (95% confidence interval [CI]: 55.4%-58.8%) to 90.3% (95%CI: 89.2%-91.4%) between 2014 and 2022. By 2020 84.4% (95%CI: 83.7%-85.2%) and 64.6% (95%CI: 63.9%-65.3%) of men and women were on DTG regimens. Among treatment-experienced viremic PLHIV, overall resistance decreased from 51.1% (95%CI: 40.7%-64.1%, 2014) to 27.9% (95%CI: 21.3%-36.5%, 2022). Only two participants harbored intermediate/high-level DTG resistance, attributable to inQ148R, inE138K, and inG140A. Low-level INSTI resistance (inS153Y) was observed in 23/207 (7.5%) of viremic individuals, with putative evidence of transmission. By 2022, suppression was unrelated to prior history of NNRTI/NRTI resistance (risk ratios: 1.14, 95%HPD: 0.96-1.32 and 1.12, 95%HPD: 0.88 - 1.35). INTERPRETATION: Viral suppression increased during the DTG-transition with minimal emerging intermediate/high-level resistance. Falling resistance among treatment-experienced PLHIV underscores the role of ART adherence in reducing viremia. The emergence of inS153Y justifies continued genomic surveillance of ART resistance. FUNDING: National Institutes of Health and the Gates Foundation.

Journal Article↗

PubMed2026

Dual β-lactam therapy against high-risk Pseudomonas aeruginosa isolates: a dynamic in-vitro infection model study integrating population genomics with quantitative systems pharmacology modelling and simulations.

BACKGROUND: Pseudomonas aeruginosa has an extraordinary capacity for resistance emergence during treatment, even with newer antipseudomonals. There is a gap in understanding how resistance mechanisms affect the time-course of bacterial response to these newer agents. Traditional approaches for predicting pathogen response to an antibiotic do not apply to combination therapy. We aimed to develop a modelling framework to predict treatment response based on resistome information, using isolates of the worldwide-disseminated high-risk clone sequence type (ST) 235 and β-lactam antibiotics as the example. METHODS: In this hollow-fibre in-vitro infection study, we used three extensively drug-resistant ST235 clinical isolates from the national collection of the Clinical Microbiology Department of the Hospital Son Espases (Palma de Mallorca, Spain) that were hospital-acquired, were isolated following routine microbiological procedures from different patients between 2017 and 2022, were susceptible to ceftolozane-tazobactam, and had different levels of meropenem resistance. The selected isolates (ST235-05, ST235-09, and ST235-10) showed classical β-lactam resistance mechanisms pre-treatment. The isolates were investigated in 240-h dynamic hollow-fibre in-vitro infection models (HFIMs). The studies exposed the isolates to pharmacokinetic profiles of ceftolozane-tazobactam (simulating 1 g of ceftolozane and 0·5 g of tazobactam as a 3-h infusion every 8 h) and meropenem (simulating 6 g per day continuous infusion) as observed in hospitalised patients, as monotherapy and in combination. Treatment response was assessed through the quantification of the time-courses of viable total and resistant bacteria. Whole-genome sequencing identified the mechanisms of emerging resistance. A quantitative systems pharmacology (QSP) approach was used to model total and resistant bacterial counts and corresponding pharmacokinetic data from the HFIM. Monte Carlo simulations were used to predict treatment responses in 1000 virtual infected patients treated with ceftolozane-tazobactam and meropenem as monotherapies or in combination over 10 days. FINDINGS: In the HFIMs, each antibiotic alone amplified resistance by approximately 48 h for all isolates; that is, monotherapies resulted in a higher concentration of resistant bacteria compared with the control treatment at the respective time, except ceftolozane-tazobactam against ST235-10. Combination of ceftolozane-tazobactam and meropenem was synergistic (bacterial counts ≥2 log10 colony forming units [CFU] per mL lower than the best performing monotherapy and initial inoculum) against all isolates and suppressed resistance. Against ST235-10, ceftolozane-tazobactam monotherapy reduced counts to less than 1 log10 CFU per mL from 192 h onwards, whereas the combination reached less than 1 log10 CFU per mL by 24 h. Across strains, population genomics confirmed monotherapy failures were associated with emerging resistance mechanisms (ceftolozane-tazobactam: ampC Ω-loop mutations; meropenem: ftsl mutation). The developed QSP model incorporated baseline resistance mechanisms and those emerging in resistant mutant subpopulations. The model explained and predicted the monotherapy failures involving amplification of these subpopulations, and synergistic killing and resistance suppression by the combination. Simulations using the model predicted bacterial regrowth above the initial inoculum for more than 90% of patients after 0 to approximately 3 days for meropenem monotherapy across all strains and for ceftolozane-tazobactam monotherapy against ST235-05 and ST235-09. For ceftolozane-tazobactam monotherapy against ST235-10, regrowth was predicted for approximately 30% of patients. In contrast, the simulations predicted sustained bacterial killing of at least 2 log10 CFU per mL compared with the initial inoculum by the combination for more than 89% of patients across all strains. INTERPRETATION: To our knowledge, this model is the first to characterise and predict the time-course of responses of clinical isolates to antibiotics only by the resistance mechanisms present and their complex interplay, representing a step towards pathogen-specific, personalised medicine. FUNDING: Australian National Health and Medical Research Council.

Pseudomonas aeruginosa↗

PubMed2026

Metagenomic-based quantification of Pseudomonas aeruginosa burden links microbiome collapse to mortality in severe community-acquired pneumonia.

BACKGROUND: Severe community-acquired pneumonia (sCAP) remains a major cause of mortality in critically ill patients, Pseudomonas aeruginosa (P. aeruginosa) is a frequent pathogen associated with poor prognosis in this population. While metagenomic next-generation sequencing (mNGS) is widely used for pathogen detection, its value in quantifying pathogen abundance and linking it to lung microbiome alterations remains unclear. OBJECTIVES: This study investigated the association between P. aeruginosa abundance quantified by mNGS and lung microbiome alterations and clinical outcomes in sCAP patients. METHODS: This multicenter retrospective study included 130 patients with sCAP caused by P. aeruginosa from five hospitals (September 2021-June 2025). Patients were stratified into low, medium, and high abundance groups according to mNGS-derived reads per ten million (RPTM) values of P. aeruginosa. Lung microbiome diversity and community structure were analyzed, and differences between groups were assessed using appropriate statistical methods. The association between P. aeruginosa abundance and clinical outcomes was evaluated using correlation analysis, sankey diagram, receiver operating characteristic curve, grey zone analysis and logistic regression. RESULTS: A total of 130 patients with sCAP due to P. aeruginosa were stratified into low, medium, and high abundance groups based on mNGS-derived RPTM value. Microbial diversity decreased progressively with increasing abundance, and community structures differed significantly among groups (all P < 0.05). P. aeruginosa became increasingly dominant, accounting for up to 95.99% of the microbiota in the high abundance group. Higher P. aeruginosa abundance was associated with increased disease severity, including longer mechanical ventilation, prolonged hospital stay, and higher 28-day mortality. Sankey diagram showed a progressive decline in treatment effectiveness and an increase in mortality with increasing P. aeruginosa abundance. P. aeruginosa_RPTM showed moderate predictive value for mortality (AUC = 0.761, Sens = 69.40%, Spec = 75.30%, cutoff: 41122, grey zone: 2287-220339) and remained independently associated with 28-day mortality in multivariable analysis [2.219 (1.509 to 3.262), P < 0.001]. CONCLUSION: In patients with sCAP, higher P. aeruginosa_RPTM measured by mNGS was associated with reduced lung microbiome diversity and unfavorable clinical outcomes. RPTM-based risk stratification may help identify patients at increased risk of poor prognosis.

Humans↗

PubMed2026

Targeting the F17-A Fimbrial gene: An efficient method for the quantitative detection of Escherichia coli F17.

Escherichia coli (E. coli) F17 is one of the leading bacterial causes of diarrhea in farm livestock, which cause huge economic losses and could also pose potential risks to public health. Generally, the monitoring the E. coli F17 is based on the polymerase chain reaction (PCR) and bacteria plate counting method, which were largely limited by the time-consuming nature and susceptibility to detection errors. Hence, there is an urgent need to develop a rapid and quantitative detection method for E. coli F17. In the present study, an E. coli F17 challenge experiment in ovine intestinal epithelial cells (IECs) was employed as an in vitro model. At different post-challenge time points (1 h, 2 h, and 3 h), two conventional methods (bacteria plate counting and microplate method) were conducted as benchmarks to estimate the number of E. coli F17 adhering to the IECs. Additionally, total genomic DNA was extracted and quantitative Real-time PCR (qPCR) was performed to detect the relative abundance of E. coli F17 fimbrial pilin (F17-A) and adhesion (F17-G) genes. Subsequently, statistical analyses, including Pearson's correlation coefficient (PCC) method and linear curve-fitting, were performed to evaluate the correlation between the abundance of F17-A/G genes and the results of the benchmark methods. The results showed that the relative abundances of both genes were highly correlated with the number of E. coli F17 that adhered to the IECs, among them, the F17-A gene showed a stronger correlation with the bacterial counts, exhibiting a correlation coefficient > 0.85. Furthermore, standard curves analyses further confirmed the out-performed quantitative performance of F17-A gene and a significantly stronger correlation with bacterial counts which exhibited an outstanding linear correlation (r = -0.9534, R2 = 0.9252) with amplification efficiency of 101.4%, The results of the present study indicate that targeting fimbrial genetic hallmarks via qPCR is an effective and promising method for E. coli F17 quantification, which could potentially contribute to epidemiological studies and pathogen monitoring in the livestock industry.

Detection↗

PubMed1976

Predictive tests in Huntington's disease.

HD is a dominantly inherited disorder that affects mental and motor systems and includes a rigid form as well as the better known choreic form. Many articles have been devoted to predicting the future onset of the disease in patients who are at risk, but none of the suggested predictors is currently considered completely reliable. Members from individual families do tend to show a similar age of onset, and similar intellectual and motor abnormalities do develop within a single family; but the presence or absence of this dominant gene of high penetrance is not usually certain until the obvious physical signs appear. Predictive tests are of importance not only to decide which person may develop the disorder, but they may also offer a clue to associated or causal features of the disease. This chapter is a review of reported predictive tests in HD, emphasizing the rationale for their use. Psychological testing has often been abnormal early in the course of the disease of some patients, particularly when motor dexterity or apraxia is tested. Family members often insist that various psychological traits enable them to predict which members are affected by the gene. These opinions are summarized. Neurophysiologic tests are briefly reviewed, including new data on increased liklihood of H-reflexes in HD. Electroencephalography was once touted as a possible predictive test but, although there is frequently an association of a low voltage EEG activity with HD, this change is too variable for certainty in prediction. Pneumoencephalography with specific measurements of caudate atrophy is of clinical interest, but a pneumoencephalogram is rarely needed for diagnosis and caudate atrophy may not actually be an early sign. Metabolic changes in HD include the biochemical effects of hypothalamic dysfunction, changes in growth hormone, and reported change in GABA levels in the CSF or brain. Provocative tests have utilized numerous drugs in an attempt to predict the onset of the disease, including particularly physostigmine and L-DOPA. All of the tests elucidate peculiarities of the disease, and all are of ethical as well as neurological interest. Many of the provocative tests utilize quantification of known neurologic features of the disease, such as reduction in saccadic movements of the eye, increased reflexes, or patterns of movement. The ethical problems in predictive tests, especially tests intended to provoke features of the disease, have been a matter of quiet controversy. Should a nontreatable disease be overtly diagnosed? And if so, will it benefit the patient? Can any of the tests tend to accelerate the patient's decline, either by physical or by psychological trauma? This chapter reviews the various predictive tests and their rationale and concludes that none of the tests are totally reliable. Many offer interesting insights into the effects of HD and do broaden the overall significance of this fascinating disorder of basal ganglion function.

Age Factors↗

PubMed2026

Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are a robust prognostic marker in patients with triple-negative breast cancer. Artificial intelligence (AI)-derived computational tools assessing TILs could improve efficiency, but require independent validation against clinical outcomes. We aimed to compare the prognostic performance of AI-derived TIL scores with pathologist-scored TILs in a large, prospectively collected dataset pooled from randomised controlled trials. METHODS: CATALINA was an independent, external validation study using prospectively collected long-term clinical outcome data pooled from seven randomised clinical trials conducted at multiple sites. We independently evaluated two previously validated AI pipelines that generate five computationally assessed tumour-infiltrating lymphocyte (cTIL) scores by masked, independent deployment of locked models. cTIL scores were correlated with the mean of the pathologist-scored stromal TILs (sTILs) in 220 digitised haematoxylin and eosin whole slide images in a cohort of patients with early-stage triple-negative or HER-2 positive breast cancer, previously scored by trained pathologists in a TIL-reproducibility study. Prognostic performance was assessed in a separate cohort of patients with early triple-negative breast cancer pooled from seven prospective, randomised adjuvant trials. Multivariable Cox regression models adjusted for clinicopathological factors and study heterogeneity assessed associations of cTIL score and sTIL score with invasive disease-free survival, distant disease-free survival, and overall survival. 5-year discrimination was estimated using time-dependent area under the receiver operating characteristic curve (AUC). FINDINGS: Individual data were collated from 1759 patients, of whom 1356 had complete clinicopathological data, pathologist sTIL scores, and cTIL scores available. Modest correlation (r 0·375-0·473) was observed between cTIL scores and the mean pathologist sTIL score. Both sTIL and cTIL were independently associated with 5-year invasive disease-free survival, distant disease-free survival, and overall survival after adjustment for clinicopathological factors (hazard ratio for invasive disease-free survival was 0·73 [95% CI 0·66-0·82]; q<0·0001, distant disease-free survival was 0·70 [0·61-0·79]; q<0·0001, and overall survival was 0·72 [0·63-0·82]; q<0·0001 for sTIL scores and 0·80 [0·73-0·89]; q<0·0001, 0·77 [0·69-0·86]; q<0·0001, and 0·79 [0·70-0·88]; q=0·0002, respectively, for percentage_lymphocyte scores). In models adjusted for clinicopathological variables and sTIL score, cTIL score did not maintain a statistically significant prognostic association. Both sTIL and cTIL scores improved the 5-year AUC over clinicopathological variables alone, while cTIL score did not significantly further improve AUC when combined with clinicopathological variables and sTIL score. INTERPRETATION: Two cTIL models deployed entirely without retraining or modification provided statistically significant prognostic information and improved risk discrimination compared with clinicopathological variables alone in this large, platform-based, independent validation study. Although cTIL score did not incrementally improve prognostication compared with models combining clinicopathological variables with sTIL score, these findings support the application of cTILs as a reproducible prognostic biomarker, particularly in settings where routine or widespread pathologist assessment is unavailable. FUNDING: Breast Cancer Research Foundation (USA).

Humans↗

PubMed1978

Potential of plant genetic systems for monitoring and screening mutagens.

Plants have too long been ignored as useful screening and monitoring systems of environmental mutagens. However, there are about a dozen reliable, some even unique, plant genetic systems that can increase the scope and effectiveness of chemical and physical mutagen screening and monitoring procedures. Some of these should be included in the Tier II tests. Moreover, plants are the only systems now in use as monitors of genetic effects caused by polluted atmosphere and water and by pesticides. There are several major advantages of the plant test systems which relate to their reproductive nature, easy culture and growth habits that should be considered in mutagen screening and monitoring. In addition to these advantages, the major plant test systems exhibit numerous genetic and chromosome changes for determining the effects of mutagens. Some of these have not yet been detected in other nonmammalian and mammalian test systems, but probably occur in the human organism. Plants have played major roles in various aspects of mutagenesis research, primarily in mutagen screening (detection and verification of mutagenic activity), mutagen monitoring, and determining mutagen effects and mechanisms of mutagen action. They have played lesser roles in quantification of mutagenic activity and understanding the nature of induced mutations.Mutagen monitoring with plants, especially in situ on land or in water, will help determine potential genetic hazards of air and water pollutants and protect the genetic purity of crop plants and the purity of the food supply. The Tradescantia stamen-hair system is used in a mobile laboratory for determining the genetic effects of industrial and automobile pollution in a number of sites in the U.S.A. The fern is employed for monitoring genetic effects of water pollution in the Eastern states. The maize pollen system and certain weeds have monitored genetic effects of pesticides. Several other systems that have considerable value and should be developed and more widely used in mutagen monitoring and screening, especially for in situ monitoring, are discussed. Emphasis is placed on pollen systems in which changes in pollen structure, chemistry, and chromosomes can be scored for monitoring; and screening systems which can record low levels of genetic effects as well as provide information on the nature of induced mutations. THE VALUE OF PLANT SYSTEMS FOR MONITORING AND SCREENING MUTAGENS CAN BE IMPROVED BY: greater knowledge of plant cell processes at the molecular and ultrastructural levels; relating these processes to mutagen effects and plant cell responses; improving current systems for increased sensitivity, ease of detecting genetic and chromosome changes, recording of data (including automation), and for extending the range of genetic and chromosome end points; and designing and developing new systems with the aid of previous and current botanical and genetic knowledge.

Biological Assay↗