Impairment of Renal and Hematopoietic Stem/Progenitor Cell Compartments in Frailty Syndrome: Link with Oxidative Stress, Plasma Cytokine Profiles and Nuclear DNA Damage.

Frailty is an age-related syndrome that drives multiple physiological system impairments in some older adults, and its pathophysiological mechanisms remain unclear. We evaluated whether frailty-related biological processes could impair stem cell compartments, specifically the renal stem compartment, given that kidney dysfunctions are frequent in frailty. A well-characterized in vitro nephrosphere model of human adult renal stem/progenitor cells has been instrumental to and was appropriate for verifying this hypothesis in our current research. Evaluating the effects of plasma from older individuals with frailty (frail plasma) on allogeneic renal stem/progenitor cells, we showed significant functional impairment and nuclear DNA damage in the treated cells of the renal stem compartment. The analysis of the frail plasma revealed mitochondrial functional impairment associated with the activation of oxidative stress and a unique inflammatory mediator profile in frail individuals. In addition, the plasma of frail subjects also contained the highest percentage of DNA-damaged autologous circulating hematopoietic progenitor/stem cells. The integration of both molecular and functional data obtained allowed us to discern patterns associated with frailty status, irrespective of the comorbidities present in the frail individuals. The data obtained converged toward biological conditions that in frailty caused renal and hematopoietic impairment of stem cells, highlighting the possibility of concomitant exhaustion of several stem compartments.

AIEC-dependent pathogenic Th17 cell transdifferentiation in Crohn's disease is suppressed by rfaP and ybaT deletion.

Mucosal enrichment of the Adherent-Invasive E. coli (AIEC) pathotype and the expansion of pathogenic IFNγ-producing Th17 (pTh17) cells have been linked to Crohn's Disease (CD) pathogenesis. However, the molecular pathways underlying the AIEC-dependent pTh17 cell transdifferentiation in CD patients remain elusive. To this aim, we created and functionally screened a transposon AIEC mutant library of 10.058 mutants to identify the virulence determinants directly implicated in triggering IL-23 production and pTh17 cell generation. pTh17 cell transdifferentiation was assessed in functional assays by co-culturing AIEC-infected human dendritic cells (DCs) with autologous conventional Th17 (cTh17) cells isolated from blood of Healthy Donors (HD) or CD patients. AIEC triggered IL-23 hypersecretion and transdifferentiation of cTh17 into pTh17 cells selectively through the interaction with CD-derived DCs. Moreover, the chronic release of IL-23 by AIEC-colonized DCs required a continuous IL-23 neutralization to significantly reduce the AIEC-dependent pTh17 cell differentiation. The multi-step screenings of the AIEC mutant's library revealed that deletion of ybaT or rfaP efficiently hinder the IL-23 hypersecretion and hampered the AIEC-dependent skewing of protective cTh17 into pathogenic IFNγ-producing pTh17 cells. Overall, our findings indicate that ybaT (inner membrane transport protein) and rfaP (LPS-core heptose kinase) represent novel and attractive candidate targets to prevent chronic intestinal inflammation in CD.

Bacterial degradation of perfluoroalkyl acids.

Advances in biological degradation of per- and polyfluoroalkyl substances (PFAS) have shown that bioremediation is a promising method of PFAS mineralization; however, most of these studies focus on remediation of more reactive polyfluorinated compounds. This review focuses on the defluorination of the more recalcitrant perfluorinated alkyl acids (PFAAs) by bacteria. We highlight key studies that report PFAA degradation products, specific bacteria, and relevant genes. Among these studies, we discuss trends in anaerobic versus aerobic conditions with specific bacterial species or consortia. This holistic review seeks to elucidate the state of PFAA biodegradation research and discuss the need for future research for environmental application.

Frequency of prediabetes in individuals with increased adiposity and metabolically healthy or unhealthy phenotypes.

AIMS: To utilize the estimated glucose disposal rate (eGDR) index of insulin sensitivity, which is based on readily available clinical variables, namely, waist circumference, hypertension and glycated haemoglobin, to discriminate between metabolically healthy and unhealthy phenotypes, and to determine the prevalence of prediabetic conditions. METHODS: Non-diabetic individuals (n = 2201) were stratified into quartiles of insulin sensitivity based on eGDR index. Individuals in the upper quartiles of eGDR were defined as having metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW) or metabolically healthy obesity (MHO) according to their body mass index, while those in the lower quartiles were classified as having metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW) and metabolically unhealthy obesity (MUO), respectively. RESULTS: The frequency of impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and IFG + IGT status was comparable among the MHNW, MHOW and MHO groups, while it increased from those with MUNW status towards those with MUOW and MUO status. As compared with participants with MHNW, the odds ratio of having IFG, IGT, or IFG + IGT was significantly higher in participants with MUOW and MUO but not in those with MUNW, MHOW and MHO, respectively. CONCLUSIONS: A metabolically healthy phenotype is associated with lower frequency of IFG, IGT, and IFG + IGT status across all body weight categories.

Deep learning for dual detection of microsatellite instability and POLE mutations in colorectal cancer histopathology.

In the spectrum of colorectal tumors, microsatellite-stable (MSS) tumors with DNA polymerase ε (POLE) mutations exhibit a hypermutated profile, holding the potential to respond to immunotherapy similarly to their microsatellite-instable (MSI) counterparts. Yet, due to their rarity and the associated testing costs, systematic screening for these mutations is not commonly pursued. Notably, the histopathological phenotype resulting from POLE mutations is theorized to resemble that of MSI. This resemblance not only could facilitate their detection by a transformer-based Deep Learning (DL) system trained on MSI pathology slides, but also indicates the possibility for MSS patients with POLE mutations to access enhanced treatment options, which might otherwise be overlooked. To harness this potential, we trained a Deep Learning classifier on a large dataset with the ground truth for microsatellite status and subsequently validated its capabilities for MSI and POLE detection across three external cohorts. Our model accurately identified MSI status in both the internal and external resection cohorts using pathology images alone. Notably, with a classification threshold of 0.5, over 75% of POLE driver mutant patients in the external resection cohorts were flagged as "positive" by a DL system trained on MSI status. In a clinical setting, deploying this DL model as a preliminary screening tool could facilitate the efficient identification of clinically relevant MSI and POLE mutations in colorectal tumors, in one go.

Australia's Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change.

We examine the characteristics and causes of southeast Australia's Tinderbox Drought (2017 to 2019) that preceded the Black Summer fire disaster. The Tinderbox Drought was characterized by cool season rainfall deficits of around -50% in three consecutive years, which was exceptionally unlikely in the context of natural variability alone. The precipitation deficits were initiated and sustained by an anomalous atmospheric circulation that diverted oceanic moisture away from the region, despite traditional indicators of drought risk in southeast Australia generally being in neutral states. Moisture deficits were intensified by unusually high temperatures, high vapor pressure deficits, and sustained reductions in terrestrial water availability. Anthropogenic forcing intensified the rainfall deficits of the Tinderbox Drought by around 18% with an interquartile range of 34.9 to -13.3% highlighting the considerable uncertainty in attributing droughts of this kind to human activity. Skillful predictability of this drought was possible by incorporating multiple remote and local predictors through machine learning, providing prospects for improving forecasting of droughts.

Modulation of faecal miRNAs highlights the preventive effects of a Mediterranean low-inflammatory dietary intervention.

BACKGROUND: Dietary interventions have been proposed as therapeutic approaches for several diseases, including cancer. A low-inflammatory Mediterranean dietary intervention, conducted as a pilot study in subjects with Familial Adenomatous Polyposis (FAP), reduced markers of local and systemic inflammation. We aim to determine whether this diet may modulate faecal microRNA (miRNA) and gene expression in the gut. METHODS: Changes in the faecal miRNome were evaluated by small RNA sequencing at baseline (T0), after the three-month intervention (T1), and after an additional three months (T2). Changes in the transcriptome of healthy rectal mucosa and adenomas were evaluated by RNA sequencing at T0 and T2. The identification of validated miRNA-gene interactions and functional analysis of miRNA targets were performed using in silico approaches. RESULTS: Twenty-seven subjects were included in this study. It was observed that the diet modulated 29 faecal miRNAs (p < 0.01; |log2 Fold Change|>1), and this modulation persisted for three months after the intervention. Levels of miR-3612-3p and miR-941 correlated with the adherence to the diet, miR-3670 and miR-4252-5p with faecal calprotectin, and miR-3670 and miR-6867 with serum calprotectin. Seventy genes were differentially expressed between adenoma and normal tissue, and most were different before the dietary intervention but reached similar levels after the diet. Functional enrichment analysis identified the proinflammatory ERK1/2, cell cycle regulation, and nutrient response pathways as commonly regulated by the modulated miRNAs and genes. CONCLUSIONS: Faecal miRNAs modulated by the dietary intervention target genes that participate in inflammation. Changes in levels of miRNAs and genes with oncogenic and tumour suppressor functions further support the potential cancer-preventive effect of the low-inflammatory Mediterranean diet. CLINICAL TRIAL NUMBER REGISTRATION: NCT04552405, Registered in ClinicalTrials.gov.

Automated curation of large-scale cancer histopathology image datasets using deep learning.

BACKGROUND: Artificial intelligence (AI) has numerous applications in pathology, supporting diagnosis and prognostication in cancer. However, most AI models are trained on highly selected data, typically one tissue slide per patient. In reality, especially for large surgical resection specimens, dozens of slides can be available for each patient. Manually sorting and labelling whole-slide images (WSIs) is a very time-consuming process, hindering the direct application of AI on the collected tissue samples from large cohorts. In this study we addressed this issue by developing a deep-learning (DL)-based method for automatic curation of large pathology datasets with several slides per patient. METHODS: We collected multiple large multicentric datasets of colorectal cancer histopathological slides from the United Kingdom (FOXTROT, N = 21,384 slides; CR07, N = 7985 slides) and Germany (DACHS, N = 3606 slides). These datasets contained multiple types of tissue slides, including bowel resection specimens, endoscopic biopsies, lymph node resections, immunohistochemistry-stained slides, and tissue microarrays. We developed, trained, and tested a deep convolutional neural network model to predict the type of slide from the slide overview (thumbnail) image. The primary statistical endpoint was the macro-averaged area under the receiver operating curve (AUROCs) for detection of the type of slide. RESULTS: In the primary dataset (FOXTROT), with an AUROC of 0.995 [95% confidence interval [CI]: 0.994-0.996] the algorithm achieved a high classification performance and was able to accurately predict the type of slide from the thumbnail image alone. In the two external test cohorts (CR07, DACHS) AUROCs of 0.982 [95% CI: 0.979-0.985] and 0.875 [95% CI: 0.864-0.887] were observed, which indicates the generalizability of the trained model on unseen datasets. With a confidence threshold of 0.95, the model reached an accuracy of 94.6% (7331 classified cases) in CR07 and 85.1% (2752 classified cases) for the DACHS cohort. CONCLUSION: Our findings show that using the low-resolution thumbnail image is sufficient to accurately classify the type of slide in digital pathology. This can support researchers to make the vast resource of existing pathology archives accessible to modern AI models with only minimal manual annotations.

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical labels, whereas biomarkers are often continuous measurements. We hypothesize that regression-based DL outperforms classification-based DL. Therefore, we develop and evaluate a self-supervised attention-based weakly supervised regression method that predicts continuous biomarkers directly from 11,671 images of patients across nine cancer types. We test our method for multiple clinically and biologically relevant biomarkers: homologous recombination deficiency score, a clinically used pan-cancer biomarker, as well as markers of key biological processes in the tumor microenvironment. Using regression significantly enhances the accuracy of biomarker prediction, while also improving the predictions' correspondence to regions of known clinical relevance over classification. In a large cohort of colorectal cancer patients, regression-based prediction scores provide a higher prognostic value than classification-based scores. Our open-source regression approach offers a promising alternative for continuous biomarker analysis in computational pathology.

Asymmetric dimethylarginine (ADMA) is associated with reduced myocardial mechano-energetic efficiency in hypertensive subjects.

BACKGROUND AND AIMS: Our prior study showed that endothelial dysfunction contributed to reduced myocardial mechano-energetics efficiency (MEEi) independently of several confounders. Reduced activity of endothelial nitric oxide synthase may be due to increased levels of the endogenous inhibitor asymmetric dimethylarginine (ADMA). The impact of ADMA on myocardial MEEi has not been determined yet. This study aims to investigate the association between plasma ADMA levels and MEEi in drug-naïve hypertensive individuals. METHODS AND RESULTS: 63 hypertensive individuals participating in the CATAnzaro MEtabolic RIsk factors (CATAMERI) study were included. All participants underwent to an echocardiogram for myocardial MEEi measurement. ADMA plasma concentrations were measured by high-performance liquid chromatography. A multivariate linear regression analysis was conducted to investigate the independent association between ADMA levels and MEEi. In a univariate analysis, ADMA levels were significantly associated with myocardial MEEi (r = 0.438; P < 0.001). In a multivariate regression analysis, plasma ADMA levels were associated to decreased myocardial MEEi (ß = 0.458, P < 0.001) independently of well-established cardiovascular risk factors including age, sex, BMI, waist circumference, smoking status, total cholesterol and HDL, triglycerides, glucose tolerance status, and HOMA-IR index of insulin resistance. CONCLUSIONS: ADMA may contribute to reduced myocardial MEEi by reducing nitric oxide bioavailability.

Interactions between achiral porphyrins and a mature miRNA.

Recent discoveries have revealed that mature miRNAs could form highly ordered structures similar to aptamers, suggesting diverse functions beyond mRNA recognition and degradation. This study focuses on understanding the secondary structures of human miR-26b-5p (UUCAAGUAAUUCAGGAUAGGU) using circular dichroism (CD) and chiroptical probes; in particular, four achiral porphyrins were utilized to both act as chiroptical probes and influence miRNA thermodynamic stability. Various spectroscopic techniques, including UV-Vis, fluorescence, resonance light scattering (RLS), electronic circular dichroism (ECD), and CD melting, were employed to study their interactions. UV-Vis titration revealed that meso-tetrakis(4-N-methylpyridyl) porphyrin (H2T4) and meso-tetrakis(4-carboxyphenylspermine) porphyrin (H2TCPPSpm4) formed complexes with distinct binding stoichiometries up to 6 : 1 and 3 : 1 ratios, respectively, and these results were supported by RLS and fluorescence, while the zinc(II) derivative porphyrin ZnT4 exhibited a weaker interaction. ZnTCPPSpm4 formed aggregates in PBS with higher organization in the presence of miRNA. CD titrations displayed an induced CD signal in the Soret region for every porphyrin investigated, indicating that they can be used as chiroptical probes for miR-26b-5p. Lastly, CD melting experiments revealed that at a 1 : 1 ratio, porphyrins did not significantly affect miRNA stability, except for H2TCPPSpm4. However, at a 3 : 1 ratio, all porphyrins, except ZnTCPPSpm4, exhibited a strong destabilizing effect on miRNA secondary structures. These findings shed light on the structural versatility of miR-26b-5p and highlight the potential of porphyrins as chiroptical probes and modulators of miRNA stability.

Whole blood viscosity is associated with reduced myocardial mechano-energetic efficiency in nondiabetic individuals.

INTRODUCTION: This cross-sectional study aimed to investigate the association between myocardial mechano-energetic efficiency (MEE) and whole blood viscosity (WBV) in nondiabetic adults participating in the CATAnzaro MEtabolic RIsk factors (CATAMERI) study. METHODS: 1143 participants underwent an oral glucose tolerance test and an echocardiogram for myocardial MEE per gram of left ventricular mass (MEEi) measurement. WBV was measured as: [0.12 × h] + [0.17 × (p-2.07)], where h is haematocrit and p is plasma protein levels. RESULTS: Study population includes 595 males and 548 females with a mean age of 46 ± 12 years and a mean BMI of 30.0 ± 6.2 kg/m2 . Individuals with normal glucose tolerance were 63%, while those with impaired fasting glucose, impaired glucose tolerance and or the combination of both were 14.3%, 13% and 9.7%, respectively. A univariate analysis showed that MEEi was significantly associated with sex, age, smoking, BMI, waist circumference, total cholesterol, HDL, triglycerides, fasting glucose, fasting insulin, HOMA-IR index, glucose tolerance, C-reactive protein, haematocrit, haemoglobin, plasma protein and WBV. In a multivariable regression model including variables that were significantly associated with MEEi in univariate analysis, MEEi was associated with HOMA-IR (ß = -0.144, p < .001), age (ß = -0.140, p < .001), WBV (ß = -0.129, p < .001) and glucose tolerance (ß = -0.064, p = .04). The independent association between WBV and MEEi remained statistically significant (ß = -0.122, p < .001) when antihypertensive therapy and lipid-lowering therapy were included in the model. CONCLUSION: WBV is associated with decreased myocardial MEE independently of other cardiovascular risk factors.

Novel biomarker SARIFA in colorectal cancer: highly prognostic, not genetically driven and histologic indicator of a distinct tumor biology.

SARIFA (Stroma AReactive Invasion Front Areas) has recently emerged as a promising histopathological biomarker for colon and gastric cancer. To elucidate the underlying tumor biology, we assessed SARIFA-status in tissue specimens from The-Cancer-Genome-Atlas (TCGA) cohorts COAD (colonic adenocarcinoma) and READ (rectal adenocarcinoma). For the final analysis, 207 CRC patients could be included, consisting of 69 SARIFA-positive and 138 SARIFA-negative cases. In this external validation cohort, H&E-based SARIFA-positivity was strongly correlated with unfavorable overall, disease-specific, and progression-free survival, partly outperforming conventional prognostic factors. SARIFA-positivity was not associated with known high-risk genetic profiles, such as BRAF V600E mutations or microsatellite-stable status. Transcriptionally, SARIFA-positive CRCs exhibited an overlap with CRC consensus molecular subtypes CMS1 and CMS4, along with distinct differential gene expression patterns, linked to lipid metabolism and increased stromal cell infiltration scores (SIIS). Gene-expression-based drug sensitivity prediction revealed a differential treatment response in SARIFA-positive CRCs. In conclusion, SARIFA represents the H&E-based counterpart of an aggressive tumor biology, demonstrating a partial overlap with CMS1/4 and also adding a further biological layer related to lipid metabolism. Our findings underscore SARIFA-status as an ideal biomarker for refined patient stratification and novel drug developments, particularly given its cost-effective assessment based on routinely available H&E slides.

Fruit quality and shelf-life of Sardinian tomato (Solanum lycopersicum L.) landraces.

The conservation and characterization of landraces have key roles in the safeguarding and valorization of agrobiodiversity. Indeed, these plant genetic resources represent an important crop heritage with quality and sensory characteristics that can be of great use to consumers and industry. In addition, the preservation of genetic resources from the risk of progressive genetic erosion, and the enhancement of their potential can contribute to food security and improve the nutritional value of food. Accordingly, this study aimed to investigate a collection of Sardinian tomato landraces for parameters that have determinant roles in evaluating their responses to conservation, and therefore to consumer acceptance. Six Sardinian landraces and two commercial varieties were cultivated in a two-years off-season trial, harvested at two different maturity stages (turning, red-ripe) and characterized using 14 fruit-related quality parameters that define the marketability, nutritional value, and flavor of the fruit. Data were collected at intervals of 10 days, starting from the harvest date and over 30 days of storage under refrigeration. The simultaneous analysis of all the qualitative characteristics for the different genotypes allowed to clearly differentiate the local varieties from the commercial varieties and a few landraces emerged for their satisfactory performances, e.g. "Tamatta kaki" ad "Tamatta groga de appiccai". In particular, the "Tamatta groga de appiccai" showed satisfactory lycopene content at marketable stages (average 5.65 mg 100g-1 FF), a peculiar orange-pink color with the highest hue angle values (range: H°T0 = 72.55-H°T30 = 48.26), and the highest firmness among the landraces of the red-ripe group (range: EpT0 = 1.64-EpT30 = 0.54 N mm-1). These results highlight the potential of some of the Sardinian tomato landraces for developing new varieties or promoting their direct valorization in local markets and could considerably increase the effectiveness and efficiency of agrobiodiversity conservation strategies.

Direct image to subtype prediction for brain tumors using deep learning.

Background: Deep Learning (DL) can predict molecular alterations of solid tumors directly from routine histopathology slides. Since the 2021 update of the World Health Organization (WHO) diagnostic criteria, the classification of brain tumors integrates both histopathological and molecular information. We hypothesize that DL can predict molecular alterations as well as WHO subtyping of brain tumors from hematoxylin and eosin-stained histopathology slides. Methods: We used weakly supervised DL and applied it to three large cohorts of brain tumor samples, comprising N = 2845 patients. Results: We found that the key molecular alterations for subtyping, IDH and ATRX, as well as 1p19q codeletion, were predictable from histology with an area under the receiver operating characteristic curve (AUROC) of 0.95, 0.90, and 0.80 in the training cohort, respectively. These findings were upheld in external validation cohorts with AUROCs of 0.90, 0.79, and 0.87 for prediction of IDH, ATRX, and 1p19q codeletion, respectively. Conclusions: In the future, such DL-based implementations could ease diagnostic workflows, particularly for situations in which advanced molecular testing is not readily available.

Pancreatic ACTH Hypersecretion and Pituitary Macroadenoma.

A 55-year-old woman admitted for hypertensive emergency and myocardial infarction reported weight gain, muscle weakness, easy bruising, and recent-onset diabetes in the past 3 to 12 months. Urinary and salivary cortisol and adrenocorticotropin hormone (ACTH) levels were elevated. Pituitary imaging detected a macroadenoma. ACTH and cortisol did not increase after corticotropin-releasing hormone administration. Imaging revealed a large pancreatic mass. Pathology indicated a well-differentiated World Health Organization (WHO) grade 2 distal pancreatic neuroendocrine neoplasm which stained for ACTH by immunohistochemistry. Postoperatively, Cushing manifestations resolved, ACTH and cortisol levels became low, and patient required hydrocortisone replacement for 7 months. During the 3.5 years of follow-up, the pituitary macroadenoma size remained stable and pituitary hormone axes other than ACTH remained normal. This extremely rare case of ectopic ACTH-secreting pancreatic neuroendocrine tumor coexisting with a nonfunctioning pituitary macroadenoma illustrates the importance of dynamic endocrine testing in Cushing syndrome.

Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study.

AIM: Gastric cancer (GC) is a tumour entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesised that GC primary tissue contains information that is predictive of lymph node status and patient prognosis and that this information can be extracted using deep learning (DL). METHODS: Using three patient cohorts comprising 1146 patients, we trained and validated a DL system to predict lymph node status directly from haematoxylin and eosin-stained GC tissue sections. We investigated the concordance between the DL-based prediction from the primary tumour slides (aiN score) and the histopathological lymph node status (pN). Furthermore, we assessed the prognostic value of the aiN score alone and when combined with the pN status. RESULTS: The aiN score predicted the pN status reaching area under the receiver operating characteristic curves of 0.71 in the training cohort and 0.69 and 0.65 in the two test cohorts. In a multivariate Cox analysis, the aiN score was an independent predictor of patient survival with hazard ratios of 1.5 in the training cohort and of 1.3 and 2.2 in the two test cohorts. A combination of the aiN score and the pN status prognostically stratified patients by survival with p-values <0.05 in logrank tests. CONCLUSION: GC primary tumour tissue contains additional prognostic information that is accessible using the aiN score. In combination with the pN status, this can be used for personalised management of GC patients after prospective validation.

Differential expression of Type I interferon and inflammatory genes in SARS-CoV-2-infected patients treated with monoclonal antibodies.

INTRODUCTION: Considering the reported efficacy of monoclonal antibodies (mAbs) directed against the Spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in reducing disease severity, the aim of this study was to investigate the innate immune response before and after mAbs treatment in 72 vaccinated and 31 unvaccinated SARS-CoV-2 patients. METHODS: The mRNA levels of IFN-I, IFN-related genes and cytokines were evaluated using RT/real-time quantitative PCR. RESULTS: Vaccinated patients showed increased rate of negative SARS-CoV-2 PCR tests on nasopharyngeal swab compared with unvaccinated ones after mAbs treatment (p = .002). Unvaccinated patients had lower IFN-α/ω and higher IFN-related genes (IFNAR1, IFNAR2, IRF9, ISG15, ISG56 and IFI27) and cytokines (IL-6, IL-10 and TGF-ß) mRNA levels compared to vaccinated individuals before mAbs (p < .05 for all genes). Increased IFN-α/ω, IFNAR1, IFNAR2 and IRF9 levels were observed in unvaccinated patients after mAbs treatment, while the mRNA expression ISGs and IL-10 were reduced in all patients. CONCLUSION: These data suggest that anti-S vaccinated patients have increased levels of innate immune genes compared to unvaccinated ones. Also, gene expression changes in IFN genes after mAbs administration are different according to the vaccination status of patients.

Rod-like nanostructures through amphiphilic OPE-porphyrin self-organization.

A new amphiphilic monosubstituted porphyrin functionalized by a ß-D-glucoside terminated oligophenylenethylene (OPE) able to self-arrange into nano-aggregates in polar solvents has been synthesized and fully characterized in its monomeric and aggregated forms.