Combined exposure of polystyrene microplastics and benzo[a]pyrene in rat: Study of the oxidative stress effects in the liver.

Microplastics (MPs) and benzo[a]pyrene (B[a]P) are prevalent environmental pollutants. Numerous studies have extensively reported their individual adverse effects on organisms. However, the combined effects and mechanisms of exposure in mammals remain unknown. Thus, this study aims to investigate the potential effects of oral administration of 0.5µm polystyrene (PS) MPs (1 mg/mL or 5 mg/mL), B[a]P (1 mg/mL or 5 mg/mL) and combined (1 mg/mL or 5 mg/mL) on 64 male SD rats by gavage method over 6-weeks. The results demonstrate that the liver histopathological examination showed that the liver lobules in the combined (5 mg/kg) group had blurred and loose boundaries, liver cord morphological disorders, and significant steatosis. The levels of AST, ALT, TC, and TG in the combined dose groups were significantly higher than those in the other groups, the combined (5 mg/kg) group had the lowest levels of antioxidant enzymes and the highest levels of oxidants. The expression of Nrf2 was lowest and the expression of P38, NF-κB, and TNF-α was highest in the combined (5 mg/kg) group. In conclusion, these findings indicate that the combination of PSMPs and B[a]P can cause the highest levels of oxidative stress and elicit markedly enhanced toxic effects, which cause severe liver damage.

Attenuated total reflection Fourier-transform infrared spectroscopy for the prediction of hormone concentrations in plants.

Plant hormones are important in the control of physiological and developmental processes including seed germination, senescence, flowering, stomatal aperture, and ultimately the overall growth and yield of plants. Many currently available methods to quantify such growth regulators quickly and accurately require extensive sample purification using complex analytic techniques. Herein we used ultra-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) to create and validate the prediction of hormone concentrations made using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectral profiles of both freeze-dried ground leaf tissue and extracted xylem sap of Japanese knotweed (Reynoutria japonica) plants grown under different environmental conditions. In addition to these predictions made with partial least squares regression, further analysis of spectral data was performed using chemometric techniques, including principal component analysis, linear discriminant analysis, and support vector machines (SVM). Plants grown in different environments had sufficiently different biochemical profiles, including plant hormonal compounds, to allow successful differentiation by ATR-FTIR spectroscopy coupled with SVM. ATR-FTIR spectral biomarkers highlighted a range of biomolecules responsible for the differing spectral signatures between growth environments, such as triacylglycerol, proteins and amino acids, tannins, pectin, polysaccharides such as starch and cellulose, DNA and RNA. Using partial least squares regression, we show the potential for accurate prediction of plant hormone concentrations from ATR-FTIR spectral profiles, calibrated with hormonal data quantified by UHPLC-HRMS. The application of ATR-FTIR spectroscopy and chemometrics offers accurate prediction of hormone concentrations in plant samples, with advantages over existing approaches.

LbSakA-mediated phosphorylation of the scaffolding protein LbNoxR in the ectomycorrhizal basidiomycete Laccaria bicolor regulates NADPH oxidase activity, ROS accumulation and symbiosis development.

Ectomycorrhizal symbiosis, which involves mutually beneficial interactions between soil fungi and tree roots, is essential for promoting tree growth. To establish this symbiotic relationship, fungal symbionts must initiate and sustain mutualistic interactions with host plants while avoiding host defense responses. This study investigated the role of reactive oxygen species (ROS) generated by fungal NADPH oxidase (Nox) in the development of Laccaria bicolor/Populus tremula × alba symbiosis. Our findings revealed that L. bicolor LbNox expression was significantly higher in ectomycorrhizal roots than in free-living mycelia. RNAi was used to silence LbNox, which resulted in decreased ROS signaling, limited formation of the Hartig net, and a lower mycorrhizal formation rate. Using Y2H library screening, BiFC and Co-IP, we demonstrated an interaction between the mitogen-activated protein kinase LbSakA and LbNoxR. LbSakA-mediated phosphorylation of LbNoxR at T409, T477 and T480 positively modulates LbNox activity, ROS accumulation and upregulation of symbiosis-related genes involved in dampening host defense reactions. These results demonstrate that regulation of fungal ROS metabolism is critical for maintaining the mutualistic interaction between L. bicolor and P. tremula × alba. Our findings also highlight a novel and complex regulatory mechanism governing the development of symbiosis, involving both transcriptional and posttranslational regulation of gene networks.

Draft genome sequencing and assembly of Favolaschia claudopus CIRM-BRFM 2984 isolated from oak limbs.

Favolaschia claudopus, a wood-inhabiting basidiomycete of the Mycenaceae family, is considered an invasive species that has recently spread from Oceania to Europe. The CIRM-BRFM 2984 strain of this fungus was originally isolated from a basidiome collected from the fallen limb of a decayed oak tree in Southwest France. The genome sequence of this strain shared characteristics with other Mycenaceae species, including a large genome size and enriched content of protein-coding genes. The genome sequence provided here will facilitate further investigation on the factors that contribute to the successful global dissemination of F. claudopus.

Sesquiterpenes of the ectomycorrhizal fungus Pisolithus microcarpus alter root growth and promote host colonization.

Trees form symbioses with ectomycorrhizal (ECM) fungi, maintained in part through mutual benefit to both organisms. Our understanding of the signaling events leading to the successful interaction between the two partners requires further study. This is especially true for understanding the role of volatile signals produced by ECM fungi. Terpenoids are a predominant class of volatiles produced by ECM fungi. While several ECM genomes are enriched in the enzymes responsible for the production of these volatiles (i.e., terpene synthases (TPSs)) when compared to other fungi, we have limited understanding of the biochemical products associated with each enzyme and the physiological impact of specific terpenes on plant growth. Using a combination of phylogenetic analyses, RNA sequencing, and functional characterization of five TPSs from two distantly related ECM fungi (Laccaria bicolor and Pisolithus microcarpus), we investigated the role of these secondary metabolites during the establishment of symbiosis. We found that despite phylogenetic divergence, these TPSs produced very similar terpene profiles. We focused on the role of P. microcarpus terpenes and found that the fungus expressed a diverse array of mono-, di-, and sesquiterpenes prior to contact with the host. However, these metabolites were repressed following physical contact with the host Eucalyptus grandis. Exposure of E. grandis to heterologously produced terpenes (enriched primarily in γ -cadinene) led to a reduction in the root growth rate and an increase in P. microcarpus-colonized root tips. These results support a very early putative role of fungal-produced terpenes in the establishment of symbiosis between mycorrhizal fungi and their hosts.

Populus MYC2 orchestrates root transcriptional reprogramming of defence pathway to impair Laccaria bicolor ectomycorrhizal development.

The jasmonic acid (JA) signalling pathway plays an important role in the establishment of the ectomycorrhizal symbiosis. The Laccaria bicolor effector MiSSP7 stabilizes JA corepressor JAZ6, thereby inhibiting the activity of Populus MYC2 transcription factors. Although the role of MYC2 in orchestrating plant defences against pathogens is well established, its exact contribution to ECM symbiosis remains unclear. This information is crucial for understanding the balance between plant immunity and symbiotic relationships. Transgenic poplars overexpressing or silencing for the two paralogues of MYC2 transcription factor (MYC2s) were produced, and their ability to establish ectomycorrhiza was assessed. Transcriptomics and DNA affinity purification sequencing were performed. MYC2s overexpression led to a decrease in fungal colonization, whereas its silencing increased it. The enrichment of terpene synthase genes in the MYC2-regulated gene set suggests a complex interplay between the host monoterpenes and fungal growth. Several root monoterpenes have been identified as inhibitors of fungal growth and ECM symbiosis. Our results highlight the significance of poplar MYC2s and terpenes in mutualistic symbiosis by controlling root fungal colonization. We identified poplar genes which direct or indirect control by MYC2 is required for ECM establishment. These findings deepen our understanding of the molecular mechanisms underlying ECM symbiosis.

The mycorrhizal symbiosis: research frontiers in genomics, ecology, and agricultural application.

Mycorrhizal symbioses between plants and fungi are vital for the soil structure, nutrient cycling, plant diversity, and ecosystem sustainability. More than 250 000 plant species are associated with mycorrhizal fungi. Recent advances in genomics and related approaches have revolutionized our understanding of the biology and ecology of mycorrhizal associations. The genomes of 250+ mycorrhizal fungi have been released and hundreds of genes that play pivotal roles in regulating symbiosis development and metabolism have been characterized. rDNA metabarcoding and metatranscriptomics provide novel insights into the ecological cues driving mycorrhizal communities and functions expressed by these associations, linking genes to ecological traits such as nutrient acquisition and soil organic matter decomposition. Here, we review genomic studies that have revealed genes involved in nutrient uptake and symbiosis development, and discuss adaptations that are fundamental to the evolution of mycorrhizal lifestyles. We also evaluated the ecosystem services provided by mycorrhizal networks and discuss how mycorrhizal symbioses hold promise for sustainable agriculture and forestry by enhancing nutrient acquisition and stress tolerance. Overall, unraveling the intricate dynamics of mycorrhizal symbioses is paramount for promoting ecological sustainability and addressing current pressing environmental concerns. This review ends with major frontiers for further research.

Comparative analyses of Pleurotus pulmonarius mitochondrial genomes reveal two major lineages of mini oyster mushroom cultivars.

Pleurotus pulmonarius, commonly known as the mini oyster mushroom, is highly esteemed for its crisp texture and umami flavor. Limited genetic diversity among P. pulmonarius cultivars raises concerns regarding its sustainable industrial production. To delve into the maternal genetic diversity of the principal P. pulmonarius cultivars, 36 cultivars and five wild isolates were subjected to de novo sequencing and assembly to generate high-quality mitogenome sequences. The P. pulmonarius mitogenomes had lengths ranging from 69,096 to 72,905 base pairs. The mitogenome sizes of P. pulmonarius and those of other mushroom species in the Pleurotus genus showed a significant positive correlation with the counts of LAGLIDAG and GIY-YIG homing endonucleases encoded by intronic open reading frames. A comparison of gene arrangements revealed an inversion of a fragment containing atp9-nad3-nad2 between P. pulmonarius and P. ostreatus. The mitogenomes of P. pulmonarius were clustered into three distinct clades, two of which were crowded with commercial cultivars. Clade I, all of which possess an inserted dpo gene, shared a maternal origin linked to an ancestral cultivar from Taiwan. Primers were designed to target the dpo gene, potentially safeguarding intellectual property rights. The wild isolates in Clade III exhibited more divergent mitogenomes, rendering them valuable for breeding.

On the origin of bird's nest fungi: Phylogenomic analyses of fungi in the Nidulariaceae (Agaricales, Basidiomycota).

Nidulariaceae, also known as bird's nest fungi, is an understudied group of mushroom-forming fungi. The common name is derived from their nest-like morphology. Bird's nest fungi are ubiquitous wood decomposers or saprobes on dung. Recent studies showed that species in the Nidulariaceae form a monophyletic group with five sub-clades. However, phylogenetic relationships among genera and placement of Nidulariaceae are still unclear. We present phylogenomic analyses of bird's nest fungi and related Agaricales fungi to gain insight into the evolution of Nidulariaceae. A species tree with 17 newly generated genomes of bird's nest fungi and representatives from all major clades of Agaricales was constructed using 1044 single-copy genes to explore the intergeneric relationships and pinpoint the placement of Nidulariaceae within Agaricales. We corroborated the hypothesis that bird's nest fungi are sister to Squamanitaceae, which includes mushroom-shaped fungi with a stipe and pileus that are saprobes and mycoparasites. Lastly, stochastic character mapping of discrete traits on phylogenies (SIMMAP) suggests that the ancestor of bird's nest fungi likely possessed an evanescent, globose peridium without strings attaching to the spore packets (funiculi). This analysis suggests that the funiculus was gained twice and that the persistent, cupulate peridium form was gained at least four times and lost once. However, alternative coding schemes and datasets with a wider array of Agaricales produced conflicting results during ancestral state reconstruction, indicating that there is some uncertainty in the number of peridium transitions and that taxon sampling may significantly alter ancestral state reconstructions. Overall, our results suggest that several key morphological characters of Nidulariaceae have been subject to homoplasy.

Genome sequencing of Porostereum spadiceum to study the degradation of levofloxacin.

Despite various plans to rationalize antibiotic use, antibiotic resistance in environmental bacteria is increasing due to the accumulation of antibiotic residues in the environment. This study aimed to test the ability of basidiomycete fungal strains to biotransform the antibiotic levofloxacin, a widely-used third-generation broad-spectrum fluoroquinolone, and to propose enzyme targets potentially involved in this biotransformation. The biotransformation process was performed using fungal strains. Levofloxacin biotransformation reached 100% after 9 days of culture with Porostereum spadiceum BS34. Using genomics and proteomics analyses coupled with activity tests, we showed that P. spadiceum produces several heme-peroxidases together with H2O2-producing enzymes that could be involved in the antibiotic biotransformation process. Using UV and high-resolution mass spectrometry, we were able to detect five levofloxacin degradation products. Their putative identity based on their MS2 fragmentation patterns led to the conclusion that the piperazine moiety was the main target of oxidative modification of levofloxacin by P. spadiceum, leading to a decrease in antibiotic activity.

Serum-based ATR-FTIR spectroscopy combined with multivariate analysis for the diagnosis of pre-diabetes and diabetes.

Diabetes mellitus (DM) is a metabolic disease with an increasing prevalence that is causing worldwide concern. The pre-diabetes stage is the only reversible stage in the patho-physiological process towards DM. Due to the limitations of traditional methods, the diagnosis and detection of DM and pre-diabetes are complicated, expensive, and time-consuming. Therefore, it would be of great benefit to develop a simple, rapid and inexpensive diagnostic test. Herein, the infrared (IR) spectra of serum samples from 111 DM patients, 111 pre-diabetes patients and 333 healthy volunteers were collected using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy and this was combined with the multivariate analysis of principal component analysis linear discriminant analysis (PCA-LDA) to develop a discriminant model to verify the diagnostic potential of this approach. The study found that the accuracy of the test model established by ATR-FTIR spectroscopy combined with PCA-LDA was 97%, and the sensitivity and specificity were 100% and 100% in the control group, 94% and 98% in the pre-diabetes group, and 91% and 98% in the DM group, respectively. This indicates that this method can effectively diagnose DM and pre-diabetes, which has far-reaching clinical significance.

Phosphorus/nitrogen sensing and signaling in diverse root-fungus symbioses.

Establishing mutualistic relationships between plants and fungi is crucial for overcoming nutrient deficiencies in plants. This review highlights the intricate nutrient sensing and uptake mechanisms used by plants in response to phosphate and nitrogen starvation, as well as their interactions with plant immunity. The coordination of transport systems in both host plants and fungal partners ensures efficient nutrient uptake and assimilation, contributing to the long-term maintenance of these mutualistic associations. It is also essential to understand the distinct responses of fungal partners to external nutrient levels and forms, as they significantly impact the outcomes of symbiotic interactions. Our review also highlights the importance of evolutionarily younger and newly discovered root-fungus associations, such as endophytic associations, which offer potential benefits for improving plant nutrition. Mechanistic insights into the complex dynamics of phosphorus and nitrogen sensing within diverse root-fungus associations can facilitate the identification of molecular targets for engineering symbiotic systems and developing plant phenotypes with enhanced nutrient use efficiency. Ultimately, this knowledge can inform tailored fertilizer management practices to optimize plant nutrition.

Fast screening using attenuated total reflectance- fourier transform infrared (ATR-FTIR) spectroscopy of patients based on D-dimer threshold value.

Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy is an emerging technology in the medical field. Blood D-dimer was initially studied as a marker of the activation of coagulation and fibrinolysis. It is mainly used as a potential diagnosis screening test for pulmonary embolism or deep vein thrombosis but was recently associated with COVID-19 severity. This study aimed to evaluate the use of ATR-FTIR spectroscopy with machine learning to classify plasma D-dimer concentrations. The plasma ATR-FTIR spectra from 100 patients were studied through principal component analysis (PCA) and two supervised approaches: genetic algorithm with linear discriminant analysis (GA-LDA) and partial least squares with linear discriminant (PLS-DA). The spectra were truncated to the fingerprint region (1800-1000 cm-1). The GA-LDA method effectively classified patients according to D-dimer cutoff (≤0.5 µg/mL and >0.5 µg/mL) with 87.5 % specificity and 100 % sensitivity on the training set, and 85.7 % specificity, and 95.6 % sensitivity on the test set. Thus, we demonstrate that ATR-FTIR spectroscopy might be an important additional tool for classifying patients according to D-dimer values. ATR-FTIR spectral analyses associated with clinical evidence can contribute to a faster and more accurate medical diagnosis, reduce patient morbidity, and save resources and demand for professionals.

Metatranscriptomics sheds light on the links between the functional traits of fungal guilds and ecological processes in forest soil ecosystems.

Soil fungi belonging to different functional guilds, such as saprotrophs, pathogens, and mycorrhizal symbionts, play key roles in forest ecosystems. To date, no study has compared the actual gene expression of these guilds in different forest soils. We used metatranscriptomics to study the competition for organic resources by these fungal groups in boreal, temperate, and Mediterranean forest soils. Using a dedicated mRNA annotation pipeline combined with the JGI MycoCosm database, we compared the transcripts of these three fungal guilds, targeting enzymes involved in C- and N mobilization from plant and microbial cell walls. Genes encoding enzymes involved in the degradation of plant cell walls were expressed at a higher level in saprotrophic fungi than in ectomycorrhizal and pathogenic fungi. However, ectomycorrhizal and saprotrophic fungi showed similarly high expression levels of genes encoding enzymes involved in fungal cell wall degradation. Transcripts for N-related transporters were more highly expressed in ectomycorrhizal fungi than in other groups. We showed that ectomycorrhizal and saprotrophic fungi compete for N in soil organic matter, suggesting that their interactions could decelerate C cycling. Metatranscriptomics provides a unique tool to test controversial ecological hypotheses and to better understand the underlying ecological processes involved in soil functioning and carbon stabilization.

Identification and visualization of environmental microplastics by Raman imaging based on hyperspectral unmixing coupled machine learning.

Microplastics (MPs) are ubiquitous contaminants that have become an emerging pollutant of concern, potentially threatening human health and ecosystem environments. Although current detection methods can accurately identify various types of MPs, it remains necessary to develop non-destructive and rapid methods to meet growing demands for detection. Herein, we combine a hyperspectral unmixing method and machine learning to analyse Raman imaging data of environmental MPs. Five MPs types including poly(butylene adipate-co-terephthalate) (PBAT), poly(butylene succinate) (PBS), p-polyethylene (PE), polystyrene (PS) and polypropylene (PP) were visualized and identified. Individual or mixed pure or aged MPs along with environmental samples were analysed by Raman imaging. Alternating volume maximization (AVmax) combined with unconstrained least squares (UCLS) method estimated end members and abundance maps of each of the MPs in the samples. Pearson correlation coefficients (r) were used as the evaluation index; the results showed that there is a high similarity between the raw spectra and the average spectra calculated by AVmax. This indicates that Raman imaging based on machine learning and hyperspectral unmixing is a novel imaging analysis method that can directly identify and visualize MPs in the environment.

Comparative analysis of simulated in-situ colonization and degradation by Lentinula edodes on oak wafer and corn stalk.

Introduction: The depolymerization of lignocellulose biomass by white-rot fungi has been an important research topic. However, few simulated in-situ analyses have been conducted to uncover the decay. Methods: In this study, the white-rot Lentinula edodes was used to colonize the wood and non-wood substrates, and then hyphal transcriptional response and substrate degradation were analyzed during the spatial-temporal colonization on different type substrates to better understand the depolymerization of lignocellulose. Results and discussion: Faster growth and thicker mat of hyphae on corn stalk were observed in comparison to oak wafer. Coincide with the higher levels of gene transcripts related to protein synthesis on corn stalk. The higher lignin oxidase activity of hyphae was detected on oak wafer, and the higher cellulase activity was observed on corn stalk containing a much higher content of soluble sugars. A large number of carbohydrate-binding module (CBM1 and CBM20)-containing enzyme genes, including lytic polysaccharide monooxygenase (AA9), cellobiohydrolase (GH6 and GH7), glucanase (GH5), xylanase (GH10 and GH11), glucoamylase (GH15), and alpha-amylase (GH13), were significantly upregulated in the back-distal hyphae colonized on corn stalk. The hyphae tended to colonize and degrade the secondary cell wall, and the deposited oxalate crystal suggested that oxalate may play an important role during lignocellulose degradation. In addition, lignin was degraded in priority in oak wafer. Of note, three lignin monomers were degraded simultaneously in oak wafer but sequentially in corn stalk. This growth Our results indicated that the white-rot degradation pattern of lignocellulose is determined by the chemical composition and structure of the colonized biomass.

Baricitinib and ß-Cell Function in Patients with New-Onset Type 1 Diabetes.

BACKGROUND: Janus kinase (JAK) inhibitors, including baricitinib, block cytokine signaling and are effective disease-modifying treatments for several autoimmune diseases. Whether baricitinib preserves ß-cell function in type 1 diabetes is unclear. METHODS: In this phase 2, double-blind, randomized, placebo-controlled trial, we assigned patients with type 1 diabetes diagnosed during the previous 100 days to receive baricitinib (4 mg once per day) or matched placebo orally for 48 weeks. The primary outcome was the mean C-peptide level, determined from the area under the concentration-time curve, during a 2-hour mixed-meal tolerance test at week 48. Secondary outcomes included the change from baseline in the glycated hemoglobin level, the daily insulin dose, and measures of glycemic control assessed with the use of continuous glucose monitoring. RESULTS: A total of 91 patients received baricitinib (60 patients) or placebo (31 patients). The median of the mixed-meal-stimulated mean C-peptide level at week 48 was 0.65 nmol per liter per minute (interquartile range, 0.31 to 0.82) in the baricitinib group and 0.43 nmol per liter per minute (interquartile range, 0.13 to 0.63) in the placebo group (P = 0.001). The mean daily insulin dose at 48 weeks was 0.41 U per kilogram of body weight per day (95% confidence interval [CI], 0.35 to 0.48) in the baricitinib group and 0.52 U per kilogram per day (95% CI, 0.44 to 0.60) in the placebo group. The levels of glycated hemoglobin were similar in the two trial groups. However, the mean coefficient of variation of the glucose level at 48 weeks, as measured by continuous glucose monitoring, was 29.6% (95% CI, 27.8 to 31.3) in the baricitinib group and 33.8% (95% CI, 31.5 to 36.2) in the placebo group. The frequency and severity of adverse events were similar in the two trial groups, and no serious adverse events were attributed to baricitinib or placebo. CONCLUSIONS: In patients with type 1 diabetes of recent onset, daily treatment with baricitinib over 48 weeks appeared to preserve ß-cell function as estimated by the mixed-meal-stimulated mean C-peptide level. (Funded by JDRF International and others; BANDIT Australian New Zealand Clinical Trials Registry number, ACTRN12620000239965.).

Point-of-Care Disease Screening in Primary Care Using Saliva: A Biospectroscopy Approach for Lung Cancer and Prostate Cancer.

Saliva is a largely unexplored liquid biopsy that can be readily obtained noninvasively. Not dissimilar to blood plasma or serum, it contains a vast array of bioconstituents that may be associated with the absence or presence of a disease condition. Given its ease of access, the use of saliva is potentially ideal in a point-of-care screening or diagnostic test. Herein, we developed a swab "dip" test in saliva obtained from consenting patients participating in a lung cancer-screening programme being undertaken in north-west England. A total of 998 saliva samples (31 designated as lung-cancer positive and 17 as prostate-cancer positive) were taken in the order in which they entered the clinic (i.e., there was no selection of participants) during the course of this prospective screening programme. Samples (sterile Copan blue rayon swabs dipped in saliva) were analysed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. In addition to unsupervised classification on resultant infrared (IR) spectra using principal component analysis (PCA), a range of feature selection/extraction algorithms were tested. Following preprocessing, the data were split between training (70% of samples, 22 lung-cancer positive versus 664 other) and test (30% of samples, 9 lung-cancer positive versus 284 other) sets. The training set was used for model construction and the test set was used for validation. The best model was the PCA-quadratic discriminant analysis (QDA) algorithm. This PCA-QDA model was built using 8 PCs (90.4% of explained variance) and resulted in 93% accuracy for training and 91% for testing, with clinical sensitivity at 100% and specificity at 91%. Additionally, for prostate cancer patients amongst the male cohort (n = 585), following preprocessing, the data were split between training (70% of samples, 12 prostate-cancer positive versus 399 other) and test (30% of samples, 5 prostate-cancer positive versus 171 other) sets. A PCA-QDA model, again the best model, was built using 5 PCs (84.2% of explained variance) and resulted in 97% accuracy for training and 93% for testing, with clinical sensitivity at 100% and specificity at 92%. These results point to a powerful new approach towards the capability to screen large cohorts of individuals in primary care settings for underlying malignant disease.