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Abstract Background Manual annotation of enzymatic functions cannot keep up with automatic genome sequencing. In this work we explore the capacity of InterPro sequence signatures to automatically predict enzymatic function. Results We present EnzML, a multi-label classification method that can efficiently account also for proteins with multiple enzymatic functions: 50,000 in UniProt. EnzML was evaluated using a standard set of 300,747 proteins for which the manually curated Swiss-Prot and KEGG databases have agreeing Enzyme Commission (EC) annotations. EnzML achieved more than 98% subset accuracy (exact match of all correct Enzyme Commission classes of a protein) for the entire dataset and between 87 and 97% subset accuracy in reannotating eight entire proteomes: human, mouse, rat, mouse-ear cress, fruit fly, the S. pombe yeast, the E. coli bacterium and the M. jannaschii archaebacterium. To understand the role played by the dataset size, we compared the cross-evaluation results of smaller datasets, either constructed at random or from specific taxonomic domains such as archaea, bacteria, fungi, invertebrates, plants and vertebrates. The results were confirmed even when the redundancy in the dataset was reduced using UniRef100, UniRef90 or UniRef50 clusters. Conclusions InterPro signatures are a compact and powerful attribute space for the prediction of enzymatic function. This representation makes multi-label machine learning feasible in reasonable time (30 minutes to train on 300,747 instances with 10,852 attributes and 2,201 class values) using the Mulan Binary Relevance Nearest Neighbours algorithm implementation (BR-kNN).

Abstract Background Traditionally, housekeeping and tissue specific genes have been classified using direct assay of mRNA presence across different tissues, but these experiments are costly and the results not easy to compare and reproduce. Results In this work, a Naive Bayes classifier based only on physical and functional characteristics of genes already available in databases, like exon length and measures of chromatin compactness, has achieved a 97% success rate in classification of human housekeeping genes (93% for mouse and 90% for fruit fly). Conclusion The newly obtained lists of housekeeping and tissue specific genes adhere to the expected functions and tissue expression patterns for the two classes. Overall, the classifier shows promise, and in the future additional attributes might be included to improve its discriminating power.

Introduction: Chronic obstructive pulmonary disease (COPD) is a frequent cause of morbidity and mortality. Dysregulated and enhanced immune-inflammatory responses have been described in COPD. Recent data showed impaired immune responses and, in particular, of interferon (IFNs) signaling pathway in these patients., Aim: To evaluate in peripheral lung of COPD patients, the expression of some of the less investigated key components of the innate immune responses leading to IFN productions including: IFN-receptors (IFNAR1/IFNAR2), IRF-3 and MDA-5. Correlations with clinical traits and with the inflammatory cell profile have been assessed., Methods: Lung specimens were collected from 58 subjects undergoing thoracic surgery: 22 COPD patients, 21 smokers with normal lung function (SC) and 15 non-smoker controls (nSC). The expression of IFNAR1, IFNAR2, IRF-3 and MDA-5, of eosinophils and activated NK cells (NKp46+) were quantified in the peripheral lung by immunohistochemistry., Results: A significant increase of IRF-3 + alveolar macrophages were observed in COPD and SC compared with nSC subjects. However, in COPD patients, the lower the levels of IRF-3 + alveolar macrophages the lower the FEV1 and the higher the exacerbation rate. The presence of chronic bronchitis (CB) was also associated with low levels of IRF-3 + alveolar macrophages. NKp46 + cells, but not eosinophils, were increased in COPD patients compared to nSC patients (p < 0.0001)., Conclusions: Smoking is associated with higher levels of innate immune response as showed by higher levels of IRF-3 + alveolar macrophages and NKp46 + cells. In COPD, exacerbation rates, severe airflow obstruction and CB were associated with lower levels of IRF-3 expression, suggesting that innate immune responses characterize specific clinical traits of the disease., (© 2024. The Author(s).)

Thymic stromal lymphopoietin (TSLP), is a protein belonging to a class of epithelial cytokines commonly called alarmins, which also includes IL-25 and IL-33. Functionally, TSLP is a key player in the immune response to environmental insults, initiating a number of downstream inflammatory pathways. TSLP performs its role by binding to a high-affinity heteromeric complex composed of the thymic stromal lymphopoietin receptor (TSLPR) chain and IL-7Rα. In recent years, the important role of proinflammatory cytokines in the etiopathogenesis of various chronic diseases such as asthma, chronic rhinosinusitis with nasal polyposis (CRSwNP), chronic obstructive pulmonary diseases (COPDs), and chronic spontaneous urticaria has been studied. Although alarmins have been found to be mainly implicated in the mechanisms of type 2 inflammation, studies on monoclonal antibodies against TSLP demonstrate partial efficacy even in patients whose inflammation is not definable as T2 and the so-called low T2. Tezepelumab is a human anti-TSLP antibody that prevents TSLP-TSLPR interactions. Several clinical trials are evaluating the safety and efficacy of Tezepelumab in various inflammatory disorders. In this review, we will highlight major recent advances in understanding the functional role of TSLP, its involvement in Th2-related diseases, and its suitability as a target for biological therapies.

Purpose of Review: Global Initiative for Asthma (GINA) document provides a classification of asthma severity according with the current level of treatment required to achieve diseases control and underlines the limitations of this approach. In this review, we will provide an overview of recent investigations that have analyzed clinical and molecular features of moderate asthma., Recent Findings: Moderate asthma is heterogeneous in terms of response to inhaled treatment and pathogenetic mechanisms underlying the clinical features. Analysis of inflammatory pathways in patients who do not achieve disease remission allows identification of patient subgroups that may benefit from specific biological treatments., Summary: Scientific progress makes increasingly clear that there are biological mechanisms capable of identifying and justifying the degree of severity of asthma. The identification of these, combined with the development of new pharmacological treatments, will be the cornerstones of improving the management of asthma in its degrees of severity., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: This umbrella review will synthesize evidence on the effectiveness of holistic assessment-based interventions in improving health outcomes in adults (aged ≥18) with multiple long-term conditions and/or frailty., Introduction: Health systems need effective, evidence-based interventions to improve health outcomes for adults with multiple long-term conditions. Holistic assessment-based interventions are effective in older people admitted to hospital (usually called "comprehensive geriatric assessments" in that context); however, the evidence is inconclusive on whether similar interventions are effective in community settings., Inclusion Criteria: We will include systematic reviews examining the effectiveness of community and/or hospital holistic assessment-based interventions in improving health outcomes for community-dwelling and hospitalized adults aged ≥ 18 with multiple long-term conditions and/or frailty., Methods: The review will follow the JBI methodology for umbrella reviews. MEDLINE, Embase, PsycINFO, CINAHL Plus, Scopus, ASSIA, Cochrane Library, and the TRIP Medical Database will be searched to identify reviews published in English from 2010 till the present. This will be followed by a manual search of reference lists of included reviews to identify additional reviews. Two reviewers will independently screen titles and abstracts against the selection criteria, followed by screening of full texts. Methodological quality will be assessed using the JBI critical appraisal checklist for systematic reviews and research syntheses and data will be extracted using an adapted and piloted JBI data extraction tool. The summary of findings will be presented in tabular format, with narrative descriptions and visual indications. The citation matrix will be generated and the corrected covered area calculated to analyze the overlap in primary studies across the reviews., Review Registration: PROSPERO CRD42022363217., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of JBI.)

The efficacy mepolizumab in severe asthmatic patients is proven in the literature. Primarily to study the effect of mepolizumab on exacerbations, steroid dependence, and the continuation of efficacy in the long term. Secondarily to evaluate the effect of the drug on nasal polyps. Analyzing data from SANI (Severe Asthma Network Italy) clinics, we observed severe asthmatic patients treated with mepolizumab 100 mg/4 weeks, for a period of 3 years. 157 patients were observed. Exacerbations were reduced from the first year (-84.6%) and progressively to 90 and 95% in the second and third ones. Steroid-dependent patients decreased from 54% to 21% and subsequently to 11% in the second year and 6% in the third year. Patients with concomitant nasal polyps, assessed by SNOT-22, showed a 49% reduction in value from baseline to the third year. The study demonstrated the long-term efficacy of mepolizumab in a real-life setting.

Background: The identification of type-2 inflammation in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) acquires a crucial role in the endotypization needed for selecting patients for biological drugs targeting type-2 inflammation: to date, the parameters used include systemic and histological biomarkers. The aim of this study was to investigate whether nasal cytology could identify type-2 inflammation in patients with CRSwNP., Methodology: Thirty-three consecutive patients with CRSwNP underwent nasal cytology sampling at the level of the lower nasal turbinate, and of the polypoid tissue, and surgical polyp tissue sample was collected. The cellularity of the 3 collected samples were compared., Results: Mean nasal polyp tissue, nasal polyps cytology and inferior turbinate cytology eosinophils counts were 43.7 ± 39.6 cells/HPF, 32.8 ± 44.7 cells/HPF and 27.6 ± 58.0 cells/HPF respectively with inferior turbinate cytology eosinophils significantly lower than nasal polyp tissue count (p = 0.007). Both mean nasal polyps cytology eosinophils and mean inferior turbinate cytology eosinophils were significantly higher in patients with type-2 CRSwNP (52.5 ± 67.0 cells/HPF vs 12.2 ± 17.3 cells/HPF, p = 0.012, and 32.0 ± 62.1 cells/HPF vs 2.9 ± 2.9 cells/HPF, p = 0.020 respectively)., Conclusions: Nasal cytology is suitable tool for assessing local biomarkers of type-2 inflammation in CRSwNP., (© 2022 The Author(s).)

Introduction: There is, so far, no universal definition of severe asthma. This definition usually relies on: number of exacerbations, inhaled therapy, need for oral corticosteroids, and respiratory function. The use of such parameters varies in the different definitions used. Thus, according to the parameters chosen, each patient may result in having severe asthma or not. The aim of this study was to evaluate how the choice of a specific definition of severe asthma can change the allocation of patients., Methods: Data collected from the Severe Asthma Network Italy (SANI) registry were analyzed. All the patients included were then reclassified according to the definitions of U-BIOPRED, NICE, WHO, ATS/ERS, GINA, ENFUMOSA, and TENOR., Results: 540 patients, were extracted from the SANI database. We observed that 462 (86%) met the ATS/ERS criteria as well as the GINA criteria, 259 (48%) the U-Biopred, 222 (41%) the NICE, 125 (23%) the WHO, 313 (58%) the Enfumosa, and 251 (46%) the TENOR criteria. The mean eosinophil value were similar in the ATS/ERS, U-Biopred, and Enfumosa (528, 532 and 516 cells/mcl), higher in WHO and Tenor (567 and 570 cells/mcl) and much higher in the NICE classification (624 cells/mcl). Lung function tests resulted similarly in all groups, with WHO (67%) and ATS/ERS-GINA (73%), respectively, showing the lower and upper mean FEV1 values., Conclusions: The present observations clearly evidence the heterogeneity in the distribution of patients when different definitions of severe asthma are used. However, the recent definition of severe asthma, provided by the GINA document, is similar to that indicated in 2014 by ATS/ERS, allowing mirror reclassification of the patients examined. This lack of homogeneity could complicate the access to biological therapies. The definition provided by the GINA document, which reflects what suggested by ATS/ERS, could partially overcome the problem., Competing Interests: None to declare., (© 2021 The Authors.)

Urinary tract infections are often polymicrobial and are mainly due to uropathogenic Escherichia coli (UPEC). We previously demonstrated a link among clinical fluoroquinolone susceptible E. coli reducing in vitro urothelial interleukin-8 (CXCL8) induced by E. coli K-12, polymicrobial cystitis, and pyuria absence. Here, we evaluated whether fifteen clinical fluoroquinolone susceptible UPEC were able to reduce CXCL8 induced by Enterococcus faecalis that had been isolated from the same mixed urines, other than CXCL8 induced by E. coli K-12. We also evaluated the connection between fluoroquinolone susceptibility and pathogenicity by evaluating the immune modulation of isogenic gyrA , a mutant UPEC resistant to ciprofloxacin. Using the 5637 bladder epithelial cell line, we observed that lower CXCL8 induced the most UPEC isolates than K-12 and the corresponding E. faecalis . During coinfections of UPEC/K-12 and UPEC/ E. faecalis , we observed lower CXCL8 than during infections caused by K-12 and E. faecalis alone. UPEC strains showed host-pathogen and pathogen-pathogen interaction, which in part explained their persistence in the human urinary tract and coinfections, respectively. Mutant UPEC showed lower modulating activity with respect to the wildtypes, confirming the connection between acquired fluoroquinolone resistance and the decrease of innate microbial properties.

Introduction: Severe asthma occurs in 5-10% of asthmatic patients, with nasal polyposis as one of the most frequent comorbidity. Benralizumab was recently marketed, thus we could analyse its effects in real-life in severe asthma, and compare the effects of the drug in patients with and without polyposis., Methods: Patients with severe asthma, receiving Benralizumab were enrolled in Italian asthma centres. The efficacy criteria for asthma (exacerbation rate, oral corticosteroid intake, hospitalizations, pulmonary function, exhaled nitric oxide) were evaluated at baseline and after 24 weeks of treatment. Patients were then sub-analysed according to the presence/absence of nasal polyposis., Results: Fifty-nine patients with severe uncontrolled asthma (21 males, age range 32-78) and treated with benralizumab for at least 24 weeks has been evaluated, showing significant improvements in asthma-related outcomes, except for pulmonary function and exhaled nitric oxide. This included a reduction in the sino-nasal outcome-22 score versus baseline of 13.7 points (p = .0037) in the 34 patients with nasal polyposis. Anosmia disappeared in 31% patients (p = .0034). When comparing the groups with and without nasal polyposis, a similar reduction of exacerbations was seen, with a greater reduction of the steroid dependence in patients with polyposis (-72% vs -53%; p < .0001), whereas lung function was significantly more improved (12% vs 34%, p = .0064) without polyposis patients., Conclusions: Benralizumab, after 6 months of treatment, confirmed its efficacy in severe asthma, and also in nasal polyposis, which is the most frequent comorbidity. The efficacy of Benralizumab in reducing steroid dependence was even higher in patients with polyposis., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Introduction : The development of biologic molecules led to a drastic change in the therapeutic approach to asthma. With the prospect of acting on different pathophysiological mechanisms of the disease, the idea of precision medicine was developed, in which a single molecule is able to modify a specific triggering mechanism. Thus, it seemed limiting to stop at the distinction of patients phenotypes and the concept of endotypes became more relevant in the therapeutic approach. Areas covered : This review deepened the topic of precision medicine through the transition from phenotyping to endotyping. We performed a review of the literature, preferring articles quoted in Medline and published in journals with an impact factor. Results showed that it is fundamental to take into consideration the role of biomarkers and the related therapies currently available for precision medicine. Expert opinion : The possible overlap of patients in different phenotypes requires a more precise classification, which considers endotypization. With the development of biological drugs able to modify and modulate some pathophysiological mechanisms of the disease, the theoretical concept of endotyping becomes practical, allowing the clinician to choose the specific mechanism to 'attack' in order to control the disease.

Background: Patients with severe allergic asthma (SAA) when treated with omalizumab may exhibit different extent of response. Identifying biomarkers that can predict the extent of treatment effectiveness in patients can be useful in personalizing omalizumab treatment., Methods: Patients from the longitudinal phase of the PROXIMA study were selected for this ancillary study. After 12 months of omalizumab treatment, patients were categorized according to their response to treatment as: "clinical responder" (Asthma Control Questionnaire [ACQ] total score <1 at Month 12 and/or with a reduction in number of exacerbation versus the previous year); "functional responder" (an increment of ≥0.1 L in forced expiratory volume in 1 s [FEV 1 ] at Month 12 versus baseline); and "super responder" (among clinical responders group, who also showed a functional response). Plasma galectin-3 (GAL-3) levels were quantified using a micro titer plate-based enzyme linked immunosorbent assay kit., Results: The Majority of patients (86.36%) in sub-study population were identified as clinical responders. Of the total patients identified as clinical responders, 64.86% were identified as super responders . A statistically significant difference in the baseline plasma GAL-3 levels between responders and non-responders was observed only in the functional responders group ( P  = 0.0446). Patients with plasma GAL-3 level of ≥11 ng/mL had a greater probability of being a super responder ( P  = 0.0118) or a functional responder ( P  = 0.0032)., Conclusion: Our findings support the use of plasma GAL-3 as a predictive marker to stratify responders and identify super responders and functional responders to omalizumab treatment in patients with severe allergic asthma using less invasive sample like plasma., Competing Interests: AMR, PLM, LDF, RR, DDS, GWC have no competing interests. FS and MB are employees of Novartis., (© 2019 The Authors.)

Background: Bronchial asthma is a heterogeneous disease characterized by three cardinal features: chronic inflammation, variable airflow obstruction, and airway hyperresponsiveness. Asthma has traditionally been defined using nonspecific clinical and physiologic variables that encompass multiple phenotypes and are treated with nonspecific anti-inflammatory therapies. Based on the modulation of airway remodeling after 12 months of anti-immunoglobulin E (IgE) treatment, we identified two phenotypes (omalizumab responder, OR; and non-omalizumab responder, NOR) and performed morphometric analysis of bronchial biopsy specimens. We also found that these two phenotypes were correlated with the presence/absence of galectin-3 (Gal-3) at baseline (i.e., before treatment). The aims of the present study were to investigate the histological and molecular effects of long-term treatment (36 months) with anti-IgE and to analyze the behavior of OR and NOR patients., Methods: All patients were treated with the monoclonal antibody anti-IgE omalizumab for 36 months. The bronchial biopsy specimens were evaluated using morphometric, eosinophilic, and proteomic analysis (MudPIT). New data were compared with previous data, and unsupervised cluster analysis of protein profiles was performed., Results: After 36 months of treatment with omalizumab, reduction of reticular basement membrane (RBM) thickness was confirmed in OR patients (Gal-3-positive at baseline); similarly, the protein profiles (over 500 proteins identified) revealed that, in the OR group, levels of proteins specifically related to fibrosis and inflammation (e.g., smooth muscle and extracellular matrix proteins (including periostin), Gal-3, and keratins decreased by between 5- and 50-fold. Eosinophil levels were consistent with molecular data and decreased by about tenfold less in ORs and increased by twofold to tenfold more in NORs. This tendency was confirmed (p < 0.05) based on both fold change and DAVE algorithms, thus indicating a clear response to anti-IgE treatment in Gal-3-positive patients., Conclusions: Our results showed that omalizumab can be considered a disease-modifying treatment in OR. The proteomic signatures confirmed the presence of Gal-3 at baseline to be a biomarker of long-term reduction in bronchial RBM thickness, eosinophilic inflammation, and muscular and fibrotic components in omalizumab-treated patients with severe asthma. Our findings suggest a possible relationship between Gal-3 positivity and improved pulmonary function.

Precision medicine (PM) can be defined as a structural model aimed at customizing healthcare, with medical decisions/products tailored on an individual patient at a highly detailed level. In this sense, allergy diagnostics based on molecular allergen components allows to accurately define the patient's IgE repertoire. The availability of highly specialized singleplexed and multiplexed platforms support allergists with an advanced diagnostic armamentarium. The therapeutic intervention, driven by the standard diagnostic approach, but further supported by these innovative tools may result, for instance, in a more appropriate prescription of allergen immunotherapy (AIT). Also, the phenotyping of patients, which may have relevant effects on the treatment strategy, could be take advantage by the molecular allergy diagnosis.

Background: Chronic obstructive pulmonary disease (COPD) is a progressive lung disorder characterized by poorly reversible airway obstruction and its pathogenesis remains largely misunderstood. Local changes of regulatory T-cell populations in the lungs of COPD patients have been demonstrated although data concerning their pathologic role are contrasting. The aim of our study was to evaluate the relative percentage of regulatory T-cells in the peripheral blood of current and former smoker subjects, affected or not by COPD. Furthermore, the effect of different concentrations of budesonide and formoterol, on regulatory T-cells has been investigated., Methods: T regulatory lymphocytes were isolated and assessed as CD4(+)CD25(high)CD127(-) cells by flow cytometry and cultured for 48 hours in the absence or in the presence of budesonide and/or formoterol at different doses., Results: CD4(+)CD25(high)CD127(-) regulatory T-cells percentage was significantly reduced in COPD patients, both current and former smokers, with respect to volunteers. Furthermore, CD4(+)CD25(high)CD127(-) cells of COPD patients showed a not statistically significant response to drugs compared to healthy subjects., Discussion: Our results evidenced a different behaviour of CD4(+)CD25(high)CD127(-) Treg cells in COPD patients after in vitro treatments., Conclusions: Based on our data, we suggested a possible role of CD4 CD25(high)CD127 T-cells in COPD pathogenesis.

Although different phenotypes of severe asthma can be identified, all are characterized by common symptoms. Due to their heterogeneity, they exhibit differences in pathogenesis, etiology and clinical responses to therapeutic approaches. The identification of distinct molecular phenotypes to define severe asthmatic patients will allow us to better understand the pathophysiology of the disease and thus to more precisely target the treatment for each patient. To achieve this goal, a systematic search for new, reliable and stable biomarkers specific for each phenotype is essential. This review focuses on the current known molecular phenotypes of severe asthma and highlights the need for biomarkers that could (either alone or in combination) be predictive of the treatment outcome.

First, we identify InterPro sequence signatures representing evolutionary relatedness and, second, signatures identifying specific chemical machinery. Thus, we predict the chemical mechanisms of enzyme-catalyzed reactions from catalytic and non-catalytic subsets of InterPro signatures. We first scanned our 249 sequences using InterProScan and then used the MACiE database to identify those amino acid residues that are important for catalysis. The sequences were mutated in silico to replace these catalytic residues with glycine and then again scanned using InterProScan. Those signature matches from the original scan that disappeared on mutation were called catalytic. Mechanism was predicted using all signatures, only the 78 "catalytic" signatures, or only the 519 "non-catalytic" signatures. The non-catalytic signatures gave indistinguishable results from those for the whole feature set, with precision of 0.991 and sensitivity of 0.970. The catalytic signatures alone gave less impressive predictivity, with precision and sensitivity of 0.791 and 0.735, respectively. These results show that our successful prediction of enzyme mechanism is mostly by homology rather than by identifying catalytic machinery.

Background: We recently reported that one may be able to predict with high accuracy the chemical mechanism of an enzyme by employing a simple pattern recognition approach: a k Nearest Neighbour rule with k = 1 (k1NN) and 321 InterPro sequence signatures as enzyme features. The nearest-neighbour rule is known to be highly sensitive to errors in the training data, in particular when the available training dataset is small. This was the case in our previous study, in which our dataset comprised 248 enzymes annotated against 71 enzymatic mechanism labels from the MACiE database. In the current study, we have carefully re-analysed our dataset and prediction results to "explain" why a high variance k1NN rule exhibited such remarkable classification performance., Results: We find that enzymes with different chemical mechanism labels in this dataset reside in barely overlapping subspaces in the feature space defined by the 321 features selected. These features contain the appropriate information needed to accurately classify the enzymatic mechanisms, rendering our classification problem a basic look-up exercise. This observation dovetails with the low misclassification rate we reported., Conclusion: Our results provide explanations for the "anomaly"-a basic nearest-neighbour algorithm exhibiting remarkable prediction performance for enzymatic mechanism despite the fact that the feature space was large and sparse. Our results also dovetail well with another finding we reported, namely that InterPro signatures are critical for accurate prediction of enzyme mechanism. We also suggest simple rules that might enable one to inductively predict whether a novel enzyme possesses any of our 71 predefined mechanisms.

Severe asthma (SA) is a clinically and etiologically heterogeneous respiratory disease which affects among 5-10 % of asthmatic patients. Despite high-dose therapy, a large patients percentage is not fully controlled and has a poor quality of life. In this review, we describe the biomarkers actually known in scientific literature and used in clinical practice for SA assessment and management: neutrophils, eosinophils, periostin, fractional exhaled nitric oxide, exhaled breath condensate and galectins. Moreover, we give an overview on clinical and biological features characterizing severe asthma, paying special attention to the potential use of these ones as reliable markers. We finally underline the need to define different biomarkers panels to select patients affected by severe asthma for specific and personalized therapeutic approach.

Asthma is a chronic inflammatory disease. Reticular basement membrane (RBM) thickening is considered feature of airway remodelling (AR) particularly in severe asthma (SA). Omalizumab, mAb to IgE is effective in SA and can modulate AR. Herein we describe protein profiles of bronchial biopsies to detect biomarkers of anti-IgE effects on AR and to explain potential mechanisms/pathways. We defined the bronchial biopsy protein profiles, before and after treatment. Unsupervised clustering of baseline proteomes resulted in very good agreement with the morphometric analysis of AR. Protein profiles of omalizumab responders (ORs) were significantly different from those of non-omalizumab responders (NORs). The major differences between ORs and NORs lied to smooth muscle and extra cellular matrix proteins. Notably, an IgE-binding protein (galectin-3) was reliable, stable and predictive biomarker of AR modulation. Omalizumab down-regulated bronchial smooth muscle proteins in SA. These findings suggest that omalizumab may exert disease-modifying effects on remodelling components., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly sequenced organism has the potential to perform a certain reaction, but how the reaction is performed, using which cofactors and with susceptibility to which drugs or inhibitors, details with important consequences for drug and enzyme design. Work that predicts enzyme catalytic activity based on 3D protein structure features limits the prediction of mechanism to proteins already having either a solved structure or a close relative suitable for homology modelling., Results: In this study, we evaluate whether sequence identity, InterPro or Catalytic Site Atlas sequence signatures provide enough information for bulk prediction of enzyme mechanism. By splitting MACiE (Mechanism, Annotation and Classification in Enzymes database) mechanism labels to a finer granularity, which includes the role of the protein chain in the overall enzyme complex, the method can predict at 96% accuracy (and 96% micro-averaged precision, 99.9% macro-averaged recall) the MACiE mechanism definitions of 248 proteins available in the MACiE, EzCatDb (Database of Enzyme Catalytic Mechanisms) and SFLD (Structure Function Linkage Database) databases using an off-the-shelf K-Nearest Neighbours multi-label algorithm., Conclusion: We find that InterPro signatures are critical for accurate prediction of enzyme mechanism. We also find that incorporating Catalytic Site Atlas attributes does not seem to provide additional accuracy. The software code (ml2db), data and results are available online at http://sourceforge.net/projects/ml2db/ and as supplementary files.

We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure-property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ~1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9-1.0 log S units.

Background: A preferential association between systemic mastocytosis (SM) and hymenoptera allergy (HVA) has been observed. Patients with both diseases are at risk for more severe reactions, and venom immunotherapy (VIT) may represent a life-saving treatment, but the use of VIT in such patients raised concerns about its safety., Objective: We evaluated a large population of patients with SM and HVA who received VIT., Methods: This prospective study was performed in Italy and Spain. A diagnosis of SM and HVA and a VIT prescription were made according to international recommendations. The patients were carefully followed up during VIT, with special attention to field stings., Results: A total of 84 patients (70 men, 14 women; mean age 52.1 years) were included, 81% with grade IV reaction, 91% with indolent SM. No difference was seen between the Italian and Spanish patients. There were 10 adverse reactions during the induction phase: 3 with the conventional induction and 7 with the rush-modified induction, none resulted in epinephrine administration and/or hospitalization. Fifty patients had one or more field re-sting (95 episodes), none during induction. The time elapsed from starting VIT and first re-sting was 2 months to 7 years, and the number of re-stings per patient was 1-6. Of the 50 patients who were re-stung, 43 (86%) resulted in being fully protected. Seven patients had reactions, and the maintenance dose was safely increased to 200 mcg. The maintenance dose interval was not different between patients with and those without reactions at re-stings., Conclusion: VIT is well tolerated, safe, and effective in patients with SM., (Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Over the last 50 years, sequencing, structural biology and bioinformatics have completely revolutionised biomolecular science, with millions of sequences and tens of thousands of three dimensional structures becoming available. The bioinformatics of enzymes is well served by, mostly free, online databases. BRENDA describes the chemistry, substrate specificity, kinetics, preparation and biological sources of enzymes, while KEGG is valuable for understanding enzymes and metabolic pathways. EzCatDB, SFLD and MACiE are key repositories for data on the chemical mechanisms by which enzymes operate. At the current rate of genome sequencing and manual annotation, human curation will never finish the functional annotation of the ever-expanding list of known enzymes. Hence there is an increasing need for automated annotation, though it is not yet widespread for enzyme data. In contrast, functional ontologies such as the Gene Ontology already profit from automation. Despite our growing understanding of enzyme structure and dynamics, we are only beginning to be able to design novel enzymes. One can now begin to trace the functional evolution of enzymes using phylogenetics. The ability of enzymes to perform secondary functions, albeit relatively inefficiently, gives clues as to how enzyme function evolves. Substrate promiscuity in enzymes is one example of imperfect specificity in protein-ligand interactions. Similarly, most drugs bind to more than one protein target. This may sometimes result in helpful polypharmacology as a drug modulates plural targets, but also often leads to adverse side-effects. Many chemoinformatics approaches can be used to model the interactions between druglike molecules and proteins in silico. We can even use quantum chemical techniques like DFT and QM/MM to compute the structural and energetic course of enzyme catalysed chemical reaction mechanisms, including a full description of bond making and breaking.

Background: Traditionally, housekeeping and tissue specific genes have been classified using direct assay of mRNA presence across different tissues, but these experiments are costly and the results not easy to compare and reproduce., Results: In this work, a Naive Bayes classifier based only on physical and functional characteristics of genes already available in databases, like exon length and measures of chromatin compactness, has achieved a 97% success rate in classification of human housekeeping genes (93% for mouse and 90% for fruit fly)., Conclusion: The newly obtained lists of housekeeping and tissue specific genes adhere to the expected functions and tissue expression patterns for the two classes. Overall, the classifier shows promise, and in the future additional attributes might be included to improve its discriminating power.

Tramadol quantitative determination by gas chromatography-mass spectrometry (GC/MS) using nefopam hydrochloride as internal standard (IS) and two calibration curves because of the large range of concentration attended in the plasmatic samples is described. Plasma samples drawn from subjects in postoperative period treated with two different initial intravenous (iv) bolus of tramadol (50 and 100 mg) followed by tramadol at the same infusion rate (12 mg h(-1)) are analysed. We operated for the qualitative analysis in Scan mode while for the quantitative analysis in SIM mode, selecting the ion m/z 58 for tramadol and m/z 179 for IS. The limit of detection (LOD) was 0.01 microg ml(-1) and the limit of quantification was 0.04 microg ml(-1).