Differential expression of biomarkers in saliva related to SARS-CoV-2 infection in patients with mild, moderate and severe COVID-19.

BACKGROUND: Severe COVID-19 is a disease characterized by profound dysregulation of the innate immune system. There is a need to identify highly reliable prognostic biomarkers that can be rapidly assessed in body fluids for early identification of patients at higher risk for hospitalization and/or death. This study aimed to assess whether differential gene expression of immune response molecules and cellular enzymes, detected in saliva samples of COVID-19 patients, occurs according to disease severity staging. METHODS: In this cross-sectional study, subjects with a COVID-19 diagnosis were classified as having mild, moderate, or severe disease based on clinical features. Transcripts of genes encoding 6 biomarkers, IL-1ß, IL-6, IL-10, C-reactive protein, IDO1 and ACE2, were measured by RT‒qPCR in saliva samples of patients and COVID-19-free individuals. RESULTS: The gene expression levels of all 6 biomarkers in saliva were significantly increased in severe disease patients compared to mild/moderate disease patients and healthy controls. A significant strong inverse relationship between oxemia and the level of expression of the 6 biomarkers (Spearman's correlation coefficient between -0.692 and -0.757; p < 0.001) was found. CONCLUSIONS: Biomarker gene expression determined in saliva samples still needs to be validated as a potentially valuable predictor of severe clinical outcomes early at the onset of COVID-19 symptoms.

Metallo-beta-lactamase-producing Escherichia coli in the sewage of Mexico City: where do they come from?

While monitoring the presence of antibiotic resistance in municipal wastewater bacteria from Mexico City, five Escherichia coli isolates were found to be resistant to carbapenems, antibiotics of "last resort" used mostly in hospitals. Further analysis revealed that these carbapenem-resistant isolates carried the gene encoding a metallo-beta-lactamase, NDM-5. The gene was found to be beared by a large, ∼145 kb conjugative plasmid, which also carries putative genes encoding resistance to sulfonamides, trimethoprim, tetracycline, ciprofloxacin, and chloramphenicol (although no phenotypic chloramphenicol resistance was detected) and quaternary-ammonium compounds. The plasmid also carried gene mobility determinants, such as integron integrase and two transposases. In addition to the direct public health threat posed by the presence of such multi-resistant organisms in wastewater released into the environment and used for crop irrigation; it is particularly concerning that carbapenem-resistant E. coli is rather rare in Mexican hospitals (<1%), but was found in small, 100 mL samples of municipal wastewater. This suggests that these organisms are under-reported by clinical microbiology laboratories, underlining the usefulness of wastewater monitoring, or that there is an unknown source of such carbapenem-resistant organisms that are being dumped into the wastewater. The source of these bacteria must be assessed and controlled to prevent further spread of this multi-resistance plasmid among other environmental and clinical microorganisms.

RNA Microarray-Based Comparison of Innate Immune Phenotypes between Human THP-1 Macrophages Stimulated with Two BCG Strains.

Currently, the only available vaccine against tuberculosis is Mycobacterium bovis Bacille Calmette-Guérin (BCG). Pulmonary tuberculosis protection provided by the vaccine varies depending on the strain, the patient's age and the evaluated population. Although the adaptive immune responses induced by different BCG strains have been widely studied, little conclusive data is available regarding innate immune responses, especially in macrophages. Here, we aimed to characterize the innate immune responses of human THP-1-derived macrophages at the transcriptional level following a challenge with either the BCG Mexico (M.BCG) or Phipps (P.BCG) strains. After a brief in vitro characterization of the bacterial strains and the innate immune responses, including nitric oxide production and cytokine profiles, we analyzed the mRNA expression patterns and performed pathway enrichment analysis using RNA microarrays. Our results showed that multiple biological processes were enriched, especially those associated with innate inflammatory and antimicrobial responses, including tumor necrosis factor (TNF)-α, type I interferon (IFN-I) and IFN-γ. However, four DEGs were identified in macrophages infected with M.BCG compared to P. BCG. These findings indicated the proinflammatory stimulation of macrophages induced by both BCG strains, at the cytokine level and in terms of gene expression, suggesting a differential expression pattern of innate immune transcripts depending on the mycobacterial strain.

The Cysteine Protease Giardipain-1 from Giardia duodenalis Contributes to a Disruption of Intestinal Homeostasis.

In giardiasis, diarrhoea, dehydration, malabsorption, weight loss and/or chronic inflammation are indicative of epithelial barrier dysfunction. However, the pathogenesis of giardiasis is still enigmatic in many aspects. Here, we show evidence that a cysteine protease of Giardia duodenalis called giardipain-1, contributes to the pathogenesis of giardiasis induced by trophozoites of the WB strain. In an experimental system, we demonstrate that purified giardipain-1 induces apoptosis and extrusion of epithelial cells at the tips of the villi in infected jirds (Meriones unguiculatus). Moreover, jird infection with trophozoites expressing giardipain-1 resulted in intestinal epithelial damage, cellular infiltration, crypt hyperplasia, goblet cell hypertrophy and oedema. Pathological alterations were more pronounced when jirds were infected intragastrically with Giardia trophozoites that stably overexpress giardipain-1. Furthermore, Giardia colonization in jirds results in a chronic inflammation that could relate to the dysbiosis triggered by the protist. Taken together, these results reveal that giardipain-1 plays a key role in the pathogenesis of giardiasis.

Non-tuberculous mycobacteria immunopathogenesis: Closer than they appear. a prime of innate immunity trade-off and NTM ways into virulence.

INTRODUCTION: The growing incidence of non-tuberculous mycobacteria (NTM) and changes in epidemiological factors have indicated that immune dysregulation may be associated with the emergence of NTM. Minireview entails to acknowledge complex interaction and new ways NTM are evolving around diverse immune status. METHODS: In order to perform this review, we selected peer reviewed, NLM database articles under the terms NTM, mycobacterium complex 'AND' -Host- immune response, immunity regulation, Disease, Single Nucleotide Polymorphism (SNP´s), and -pathogen- followed by a snow ball rolling basis search on immune components and NTM related with diseases distribution. RESULTS: The universal exposure and diversity of NTM are well-documented; however, hospitals seldom establish vigilant control of water quality or immunodeficiencies for patients with NTM infections. Depending on the chemical structures and immune mechanisms presented by various NTM varieties, they can trigger different effects in dendritic and natural killer cells, which release interleukin (IL)-17, tumour necrosis factor-α (TNF-α), interferon-γ (IFN-γ) and rIL-1B. The T helper (Th)2-acquired immune response is responsible for autoimmune responses in patients with NTM infections, and, quite disturbingly, immunocompetent patients have been reported to suffer from NTM infections. CONCLUSION: New technologies and a comprehensive view has taught us; to acknowledge metabolic/immune determinants and trade-offs along transit through mutualism-parasite continuous.

Sensors for Structural Health Monitoring and Condition Monitoring.

Structural control and health monitoring as condition monitoring are some essential areas that allow for different system parameters to be designed, supervised, controlled, and evaluated during the system's operation in different processes, such as those used in machinery, structures, and different physical variables in mechanical, chemical, electrical, aeronautical, civil, electronics, mechatronics, and agricultural engineering applications, among others [...].

Entropy Indicators: An Approach for Low-Speed Bearing Diagnosis.

To increase the competitiveness of wind energy, the maintenance costs of offshore floating and fixed wind turbines need to be reduced. One strategy is the enhancement of the condition monitoring techniques for pitch bearings, because their low operational speed and the high loads applied to them make their monitoring challenging. Vibration analysis has been widely used for monitoring the bearing condition with good results obtained for regular bearings, but with difficulties when the operational speed decreases. Therefore, new techniques are required to enhance the capabilities of vibration analysis for bearings under such operational conditions. This study proposes the use of indicators based on entropy for monitoring a low-speed bearing condition. The indicators used are approximate, dispersion, singular value decomposition, and spectral entropy of the permutation entropy. This approach has been tested with vibration signals acquired in a test rig with bearings under different health conditions. The results show that entropy indicators (EIs) can discriminate with higher-accuracy damaged bearings for low-speed bearings compared with the regular indicators. Furthermore, it is shown that the combination of regular and entropy-based indicators can also contribute to a more reliable diagnosis.

Wind Turbine Main Bearing Fault Prognosis Based Solely on SCADA Data.

As stated by the European Academy of Wind Energy (EAWE), the wind industry has identified main bearing failures as a critical issue in terms of increasing wind turbine reliability and availability. This is owing to major repairs with high replacement costs and long downtime periods associated with main bearing failures. Thus, the main bearing fault prognosis has become an economically relevant topic and is a technical challenge. In this work, a data-based methodology for fault prognosis is presented. The main contributions of this work are as follows: (i) Prognosis is achieved by using only supervisory control and data acquisition (SCADA) data, which is already available in all industrial-sized wind turbines; thus, no extra sensors that are designed for a specific purpose need to be installed. (ii) The proposed method only requires healthy data to be collected; thus, it can be applied to any wind farm even when no faulty data has been recorded. (iii) The proposed algorithm works under different and varying operating and environmental conditions. (iv) The validity and performance of the established methodology is demonstrated on a real underproduction wind farm consisting of 12 wind turbines. The obtained results show that advanced prognostic systems based solely on SCADA data can predict failures several months prior to their occurrence and allow wind turbine operators to plan their operations.

Unsupervised Damage Detection for Offshore Jacket Wind Turbine Foundations Based on an Autoencoder Neural Network.

Structural health monitoring for offshore wind turbine foundations is paramount to the further development of offshore fixed wind farms. At present time there are a limited number of foundation designs, the jacket type being the preferred one in large water depths. In this work, a jacket-type foundation damage diagnosis strategy is stated. Normally, most or all the available data are of regular operation, thus methods that focus on the data leading to failures end up using only a small subset of the available data. Furthermore, when there is no historical precedent of a type of fault, those methods cannot be used. In addition, offshore wind turbines work under a wide variety of environmental conditions and regions of operation involving unknown input excitation given by the wind and waves. Taking into account the aforementioned difficulties, the stated strategy in this work is based on an autoencoder neural network model and its contribution is two-fold: (i) the proposed strategy is based only on healthy data, and (ii) it works under different operating and environmental conditions based only on the output vibration data gathered by accelerometer sensors. The proposed strategy has been tested through experimental laboratory tests on a scaled model.

More fuel to the fire: some patients with non-celiac self-reported wheat sensitivity exhibit adaptive immunological responses in duodenal mucosa.

BACKGROUND: In contrast to the well-characterized Celiac Disease (CD), the clinical scenarios encompassed by the non-celiac self-reported wheat sensitivity (NCSRWS) might be related to different antigens that trigger distinct immune-inflammatory reactions. Although an increased number of intestinal intraepithelial lymphocytes is observed at the inception of both diseases, the subsequent immunopathogenic pathways seem to be different. We aimed to describe the cytokine profile observed in the duodenal mucosa of patients with NCSRWS. METHODS: In a blind, cross-sectional study, we included duodenal biopsies from 15 consecutive untreated patients with active CD, 9 individuals with NCSRWS and 10 subjects with dyspepsia without CD and food intolerances. Immunohistochemistry and flow-cytometry were used to determine the presence of pro-inflammatory cytokine expressing monocytes and monocyte-derived dendritic cells involved in innate immune activation, cytokine-driven polarization and maintenance of Th1 and Th17/Th 22, and anti-inflammatory/profibrogenic cytokines. RESULTS: The percentage of cells expressing all tested cytokines in the lamina propria and the epithelium was higher in CD patients than in the control group. Cytokines that induce and maintain Th1 and Th17 polarization were higher in CD than in NCSRWS and controls, also were higher in NCSRWS compared to controls. Similar differences were detected in the expression of IL-4 and TGF-1, while IL-10-expressing cells were lower in NCSRWS patients than in controls and CD subjects. CONCLUSIONS: NCSRWS patients exhibit components of both, innate and adaptive immune mechanisms but to a lesser extent compared to CD.

Antimicrobial resistance and antibiotic consumption in Mexican hospitals.

OBJECTIVE: To establish the current situation of antimicrobial resistance and antibiotic consumption in Mexican hospitals. MATERIALS AND METHODS: Antimicrobial susceptibility data from blood and urine isolates were collected. Defined daily dose (DDD) of antibiotic consumption/100 occupied beds (OBD) was calculated. RESULTS: Study period: 2016 and 2017. Of 4 382 blood isolates, E. coli and K. pneumoniae were most frequently reported, with antimicrobial resistance >30% for most drugs tested, only for carbapenems and amikacin resistance were <20%. A. baumannii had antimicrobial resistance >20% to all drugs. Resistance to oxacillin in S. aureus was 20%. From 12 151 urine isolates, 90% corresponded to E. coli; resistance to ciprofloxacin, cephalosporins and trimethoprim/sulfamethoxazole was >50%, with good susceptibility to nitrofurantoin, amikacin and carbapenems. Global median antimicrobial consumption was 57.2 DDD/100 OB. CONCLUSIONS: s. This report shows a high antimicrobial resistance level in Gram-negative bacilli and provides an insight into the seriousness of the problem of antibiotic consumption.

OBJETIVO: Establecer la situación actual de la resistencia antimicrobiana y el consumo de antibióticos en hospitales mexicanos. MATERIAL Y MÉTODOS: Se colectaron datos de susceptibilidad antimicrobiana de aislamientos de sangre y orina. Se calculó la dosis diaria definida (DDD) del consumo de antibióticos/100 estancias. RESULTADOS: Periodo de estudio de 2016 a 2017. De 4 382 aislamientos en sangre, E. coli y K. pneumoniae fueron las más frecuentes, con resistencia >30% a la mayoría de las drogas evaluadas; sólo para carbapenémicos y amikacina la resistencia fue <20%. A. baumannii tuvo resistencia >20% a todos los fármacos. La resistencia a oxacilina en S. aureus fue de 20%. De 12 151 aislamientos en urocultivos, 90% correspondió a E. coli; la resistencia a ciprofloxacina, cefalosporinas y trimetoprima/sulfametoxazol fue >50%, con buena susceptibilidad a nitrofurantoína, amikacina y carbapenémicos. La mediana del consumo global de antibióticos en DDD/100 estancias fue de 57.2. CONCLUSIONES: Este reporte muestra el nivel elevado de resistencia en bacilos Gram-negativos y brinda una perspectiva de la gravedad del problema del consumo de antibióticos.

Vibration-Response-Only Structural Health Monitoring for Offshore Wind Turbine Jacket Foundations via Convolutional Neural Networks.

This work deals with structural health monitoring for jacket-type foundations of offshore wind turbines. In particular, a vibration-response-only methodology is proposed based on accelerometer data and deep convolutional neural networks. The main contribution of this article is twofold: (i) a signal-to-image conversion of the accelerometer data into gray scale multichannel images with as many channels as the number of sensors in the condition monitoring system, and (ii) a data augmentation strategy to diminish the test set error of the deep convolutional neural network used to classify the images. The performance of the proposed method is analyzed using real measurements from a steel jacket-type offshore wind turbine laboratory experiment undergoing different damage scenarios. The results, with a classification accuracy over 99%, demonstrate that the stated methodology is promising to be utilized for damage detection and identification in jacket-type support structures.

Structural Health Monitoring for Jacket-Type Offshore Wind Turbines: Experimental Proof of Concept.

Structural health monitoring for offshore wind turbines is imperative. Offshore wind energy is progressively attained at greater water depths, beyond 30 m, where jacket foundations are presently the best solution to cope with the harsh environment (extreme sites with poor soil conditions). Structural integrity is of key importance in these underwater structures. In this work, a methodology for the diagnosis of structural damage in jacket-type foundations is stated. The method is based on the criterion that any damage or structural change produces variations in the vibrational response of the structure. Most studies in this area are, primarily, focused on the case of measurable input excitation and vibration response signals. Nevertheless, in this paper it is assumed that the only available excitation, the wind, is not measurable. Therefore, using vibration-response-only accelerometer information, a data-driven approach is developed following the next steps: (i) the wind is simulated as a Gaussian white noise and the accelerometer data are collected; (ii) the data are pre-processed using group-reshape and column-scaling; (iii) principal component analysis is used for both linear dimensionality reduction and feature extraction; finally, (iv) two different machine-learning algorithms, k nearest neighbor (k-NN) and quadratic-kernel support vector machine (SVM), are tested as classifiers. The overall accuracy is estimated by 5-fold cross-validation. The proposed approach is experimentally validated in a laboratory small-scale structure. The results manifest the reliability of the stated fault diagnosis method being the best performance given by the SVM classifier.

Recombinant O-mannosylated protein production (PstS-1) from Mycobacterium tuberculosis in Pichia pastoris (Komagataella phaffii) as a tool to study tuberculosis infection.

BACKGROUND: Pichia pastoris (syn. Komagataella phaffii) is one of the most highly utilized eukaryotic expression systems for the production of heterologous glycoproteins, being able to perform both N- and O-mannosylation. In this study, we present the expression in P. pastoris of an O-mannosylated recombinant version of the 38 kDa glycolipoprotein PstS-1 from Mycobacterium tuberculosis (Mtb), that is similar in primary structure to the native secreted protein. RESULTS: The recombinant PstS-1 (rPstS-1) was produced without the native lipidation signal. Glycoprotein expression was under the control of the methanol-inducible promoter pAOX1, with secretion being directed by the α-mating factor secretion signal. Production of rPstS-1 was carried out in baffled shake flasks (BSFs) and controlled bioreactors. A production up to ~ 46 mg/L of the recombinant protein was achieved in both the BSFs and the bioreactors. The recombinant protein was recovered from the supernatant and purified in three steps, achieving a preparation with 98% electrophoretic purity. The primary and secondary structures of the recombinant protein were characterized, as well as its O-mannosylation pattern. Furthermore, a cross-reactivity analysis using serum antibodies from patients with active tuberculosis demonstrated recognition of the recombinant glycoprotein, indirectly indicating the similarity between the recombinant PstS-1 and the native protein from Mtb. CONCLUSIONS: rPstS-1 (98.9% sequence identity, O-mannosylated, and without tags) was produced and secreted by P. pastoris, demonstrating that this yeast is a useful cell factory that could also be used to produce other glycosylated Mtb antigens. The rPstS-1 could be used as a tool for studying the role of this molecule during Mtb infection, and to develop and improve vaccines or kits based on the recombinant protein for serodiagnosis.

[Diagnóstico tardío de psoriasis: motivos y consecuencias]. / Late diagnosis of psoriasis: Reasons and consequences.

BACKGROUND: Psoriasis is an autoimmune skin disease that may be associated with articular manifestations, and the most common clinical presentation is the variety "in plaques". In Mexico, in the Centro Dermatológico Pascua, it is the eighth leading cause of consultation. The aim of this study was to determine the diagnostic process of patients in a reference center for diseases of the skin. METHODS: Performing an analytical cross-sectional study that included 100 patients where the diagnostic process was questioned, clinimetric scales were applied and evaluated anthropometric. RESULTS: It was found that 70% of patients had taken over a month to get medical care (median: 3 months; IQR: 11 months), having consulted in 61% to a general physician as a doctor of first contact and 89% being diagnosed by a dermatologist. Eighty-eight percent of the patients were overweight or obese. We found as a factor of delay, a partnership with the variable of having an Institutional Medical Service (p = 0.019; U = 695.5). CONCLUSION: it is necessary to design a system to shorten the diagnostic process, not only in psoriasis, in addition to emphasizing dermatological education.

An Experimental Realization of a Chaos-Based Secure Communication Using Arduino Microcontrollers.

Security and secrecy are some of the important concerns in the communications world. In the last years, several encryption techniques have been proposed in order to improve the secrecy of the information transmitted. Chaos-based encryption techniques are being widely studied as part of the problem because of the highly unpredictable and random-look nature of the chaotic signals. In this paper we propose a digital-based communication system that uses the logistic map which is a mathematically simple model that is chaotic under certain conditions. The input message signal is modulated using a simple Delta modulator and encrypted using a logistic map. The key signal is also encrypted using the same logistic map with different initial conditions. In the receiver side, the binary-coded message is decrypted using the encrypted key signal that is sent through one of the communication channels. The proposed scheme is experimentally tested using Arduino shields which are simple yet powerful development kits that allows for the implementation of the communication system for testing purposes.

[Resistance to antibiotic: A serious global problem]. / La resistencia a los antibióticos: Un grave problema global.

An important piece of improvement in public health standards, medicine achievements, and development is based on the impressive effect of vaccines and antibiotics on infectious diseases. However, the last three or so decades have witnessed how an unsound use of antibiotics has resulted in antibiotic multi-resistant clones in hospitals and community environments. It also has been said that antibiotic research and the development pipeline has crashed, leading to no new antibiotic molecules to be tested at a time of treatment failure, manifest with unacceptable frequency as an increased economic and human cost in lives. Like the name of the series, antibiotic resistance is a global problem with clear evolutionary roots and a broad local impact. In that sense, this review explores the interaction among resistant mechanisms, underlying motives of expansion and actual trends in antibiotic resistance upgrade to limit the problem. Conceivably, only the involvement of players at every level, and coordinated actions accordingly constitute the necessary elements for effectively intervention.

The detection of inherent homologous recombination between repeat sequences in H. pylori 26695 by the PCR-based method.

Helicobacter pylori infects more than half of the world's population, making it the most widespread infection of bacteria. It has high genetic diversity and has been considered as one of the most variable bacterial species. In the present study, a PCR-based method was used to detect the presence and the relative frequency of homologous recombination between repeat sequences (>500 bp) in H. pylori 26695. All the recombinant structures have been confirmed by sequencing. The inversion generated between inverted repeats showed distinct features from the recombination for duplication or deletion between direct repeats. Meanwhile, we gave the mathematic reasoning of a general formula for the calculation of relative recombination frequency and indicated the conditions for its application. This formula could be extensively applied to detect the frequency of homologous recombination, site-specific recombination, and other types of predictable recombination. Our results should be helpful for better understanding the genome evolution and adaptation of bacteria.

Structural health monitoring of jacket-type support structures in offshore wind turbines: A comprehensive dataset for bolt loosening detection through vibrational analysis.

This dataset provides a comprehensive collection of vibrational data for the purpose of structural health monitoring, particularly focusing on the detection of bolt loosening in offshore wind turbine jacket foundations. The data set comprises 780 comma-separated values (CSV) files, each corresponding to specific experimental conditions, including various structural states of the wind turbine's support structure. These states are systematically varied considering three main aspects: the amplitude of a white noise (WN) signal, the type of bolt damage, and the level at which damage has occurred. The data were meticulously collected using eight triaxial accelerometers (PCB R Piezotronic model 356A17), strategically placed at different locations on a scaled-down replica of an offshore jacket-type wind turbine. This setup facilitated the acquisition of detailed vibrational data through a National Instruments' data acquisition (DAQ) system, comprising six input modules (NI 9234 model) housed in a chassis (cDAQ model). The white noise signal, simulating wind disturbance at the nacelle, was produced by a modal shaker and varied in three amplitudes (0.5, 1, and 2), directly proportional to the induced vibration in the wind turbine. The dataset uniquely captures the vibrational behaviour under different scenarios of bolt loosening in the turbine's foundation. The conditions include a healthy state (bolts tightened to 12 Nm) and various degrees of loosening (bolts loosened to 9 Nm, 6 Nm, and completely absent), examined at four distinct levels of the turbine's base structure. This granular approach offers a nuanced view of how varying degrees of bolt loosening impact the vibrational characteristics of the structure. The value of this dataset lies in its potential for wide-ranging applications in the field of structural health monitoring. Researchers and engineers can leverage this data for developing and testing new methodologies for early damage detection and progressive damage assessment in offshore wind turbines. The dataset's comprehensive coverage of damage scenarios makes it a valuable resource for the validation and enhancement of existing damage detection algorithms. Furthermore, the dataset can serve as a benchmark for comparing the efficacy of different vibrational analysis techniques in the context of wind turbine maintenance and safety. Its application is not only limited to wind turbines but can extend to other structures where bolt integrity is critical for operational safety. This dataset represents a significant contribution to the field of structural health monitoring, providing a detailed and practical resource for enhancing the reliability and safety of offshore wind turbines and similar structures.

Catecholamine norepinephrine diminishes lung epithelial cell adhesion of Streptococcus pneumoniae by binding iron.

Systemic release of norepinephrine (NE) is a component of the acute host response to infection, and studies in the field of microbial endocrinology indicate generally that NE increases the bacterial growth rate and promotes invasive disease. However, NE attenuates experimental invasive pneumococcal disease. We determined that NE promoted pneumococcal growth but paradoxically decreased pneumococcal adhesion to host cells. This effect was independent of the classical adhesin CbpA. Microarray analysis indicated that the effect of NE involved two two-component regulatory systems that both regulate expression of the Piu iron uptake ABC transport operon. We propose that NE, a known siderophore, enhances iron availability to the bacteria, resulting in greater bacterial replication and decreased expression of Piu operon products. Downregulation of the operon includes decreased expression of the Piu-associated adhesin PiuD. Our results suggested that the iron-dependent inhibitory effect of NE on pneumococcal adherence is a mechanism underlying the amelioration of pneumococcal disease by NE.