Wetting Behavior Driven by Surface Morphology Changes Induced by Picosecond Laser Texturing

The laser surface texturing (LST) technique has recently been used to enhance adhesion bond strength in various coating applications and to create structures with controlled hydrophobic or superhydrophobic surfaces. The texturing processing parameters can be adjusted to tune the surface's polarity, thereby controlling the ratio between the polar and dispersed components of the surface free energy and determining its hydrophobic character. The aim of this work is to systematically select appropriate laser and scan head parameters for high-quality surface topography of metal-based materials. A correlation between texturing parameters and wetting properties was made in view of several technological applications, i.e., for the proper growth of conformal layers onto laser-textured metal surfaces. Surface analyses, carried out by scanning electron microscopy and profilometry, reveal the presence of periodic microchannels decorated with laser-induced periodic surface structures (LIPSS) in the direction parallel to the microchannels. The water contact angle varies widely from about 20° to 100°, depending on the treated material (titanium, nickel, etc.). Nowadays, reducing the wettability transition time from hydrophilicity to hydrophobicity, while also changing environmental conditions, remains a challenge. Therefore, the characteristics of environmental dust and its influence on the properties of the picosecond laser-textured surface (e.g., chemical bonding of samples) have been studied while monitoring ambient conditions.

Integrating physics in deep learning algorithms: a force field as a PyTorch module

MOTIVATION

Deep learning algorithms applied to structural biology often struggle to converge to meaningful solutions when limited data is available, since they are required to learn complex physical rules from examples. State-of-the-art force-fields, however, cannot interface with deep learning algorithms due to their implementation.

RESULTS

We present MadraX, a forcefield implemented as a differentiable PyTorch module, able to interact with deep learning algorithms in an end-to-end fashion.

AVAILABILITY AND IMPLEMENTATION

MadraX documentation, together with tutorials and installation guide, is available at madrax.readthedocs.io.

Chromothripsis orchestrates leukemic transformation in blast phase MPN through targetable amplification of DYRK1A

Chromothripsis, the process of catastrophic shattering and haphazard repair of chromosomes, is a common event in cancer. Whether chromothripsis might constitute an actionable molecular event amenable to therapeutic targeting remains an open question. We describe recurrent chromothripsis of chromosome 21 in a subset of patients in blast phase of a myeloproliferative neoplasm (BP-MPN), which alongside other structural variants leads to amplification of a region of chromosome 21 in ∼25% of patients ('chr21amp'). We report that chr21amp BP-MPN has a particularly aggressive and treatment-resistant phenotype. The chr21amp event is highly clonal and present throughout the hematopoietic hierarchy. DYRK1A , a serine threonine kinase and transcription factor, is the only gene in the 2.7Mb minimally amplified region which showed both increased expression and chromatin accessibility compared to non-chr21amp BP-MPN controls. We demonstrate that DYRK1A is a central node at the nexus of multiple cellular functions critical for BP-MPN development, including DNA repair, STAT signalling and BCL2 overexpression. DYRK1A is essential for BP-MPN cell proliferation in vitro and in vivo , and DYRK1A inhibition synergises with BCL2 targeting to induce BP-MPN cell apoptosis. Collectively, these findings define the chr21amp event as a prognostic biomarker in BP-MPN and link chromothripsis to a druggable target.

A data-driven model-free adaptive controller with application to wind turbines

A data-driven controller is presented in this paper, which stems from the well known model-free adaptive control approach based on an equivalent linearized dynamical model of the plant. Inspired by the recent paper (Liu and Yang, 2019), the output tracking problem is here solved by a data-driven adaptive sliding-mode controller simultaneously ensuring prescribed performance constraints. To allow a rigorous stability analysis, the sliding variable, and the consequently derived controller, have been redesigned with respect to the inspiring paper. A proper setting of the gain of the discontinuous term is shown necessary to ensure closed loop stability. Validation of the technique has been extensively performed on the well assessed high-fidelity tool FAST (NREL) to solve the efficiency maximization problem using the proposed approach for a 5 MW wind turbine operating in the medium wind speed region.

OS08.4.A Analysis of melanoma brain metastasis immune microenvironment through multiplex gene expression profiling

Background

Novel immunotherapies based on targeting of specific immune checkpoints enabled a significant improvement of melanoma outcome, but melanoma brain metastases (BM) remain an unmet oncological need with an overall 2-year survival rate lower than 10%. Tumour immune microenvironment has been demonstrated to play a key role in BM establishment and development, but data regarding the specific milieu of melanoma BM is limited.

Material and Methods

Gene expression profiles of 55 samples of primary melanoma and BM were evaluated using the nCounter PanCancer IO 360 Panel (NanoString Technologies) targeting 770 mRNA involved in tumor immune microenvironment modulation. The case series consisted of 10 primary melanomas and their 10 matched BM, 25 unmatched BM, and 10 locally advanced control melanomas without evidence of BM after >5 year follow up.

Results

Among BM samples, most patients (25/45) were males and median age at BM diagnosis was 61,2 years with a median time to BM development of 2,1 years. Median OS from BM diagnosis was 1,3 years. Several genes resulted significantly downregulated in BM compared to primary melanomas, including SERPINB5 (p<0.001), ARG1 (p=0.0067), S100A8 (p<0.001), S100A9 (p<0.001), S100A12 (p=0.0037), IL1RN (p=0.0012), CCL21 (p=0.0012), CCL22 (p=0.0012) and CCL13 (p=0.037) and SELE (p=0.026); conversely, C7 was upregulated (p<0.001). Downregulated signatures in BM involved those associated with multiple immune cell populations, including neutrophils, dendritic cells, mast cells and Treg, as well as inflammatory chemokines, the CTLA4 immune checkpoint and ARG1 enzyme function; conversely, MAGEs-related signature was upregulated. Comparison between primary melanomas which developed BM and those which did not showed a significant overexpression of RRM2 (p=0.0247) and TNFRSF1A (p=0.032) genes in the latter group and an upregulation of the PD-1 pathway. Analysis according to tumour mutational status showed an upregulation of signatures associated with inflammatory chemokines, dendritic and myeloid cells and neutrophils. No differences were observed according to time to BM development and survival from BM diagnosis.

Conclusion

Our findings show that melanoma BM harbor distinct immunosuppressive mechanisms compared to primary tumors: this data elicits the importance of investigating the heterogeneity of BM microenvironment. Genes and pathways selectively overexpressed or downregulated in melanoma BM should be validated to be possibly considered as novel therapeutic targets.

Physical function and physical activity in adults with X-linked hypophosphatemia

We described physical function and activity in UK adults with X-linked hypophosphatemia (XLH). Our data indicate that low physical activity and impaired mobility are common in adults with XLH. Deficits in lower limbs muscle power and functional capacity contribute to the loss of physical function in adults with XLH.

INTRODUCTION

There is a dearth of literature on physical function and physical activity in adults with X-linked hypophosphatemia (XLH). We described muscle strength and power, functional capacity, mobility and physical activity level and explored the relationships among these variables in adults with XLH.

METHODS

Participants were recruited as part of a UK-based prospective cohort study, the RUDY Study. They underwent a clinical visit and physical examination, including assessment of handgrip strength, jump power (mechanography), six-minute walk test (6MWT) and short physical performance battery (SPPB), and completed the International Physical Activity Questionnaire (IPAQ). Performance data were analysed using parametric and non-parametric tests, whereas correlations were assessed by univariate analysis.

RESULTS

Twenty-six adults with XLH (50% males) with a mean age of 44 ± 16.1 years were recruited. Jump power and 6MWT distances (p < 0.0001) were 54.4% and 38.6% lower respectively in individuals with XLH compared with normative values. These deficits were not associated with age or sex. Handgrip strength values were similar to expected values. Deficits in muscle power were more pronounced than those reported at 6MWT (p < 0.0001). Univariate analysis revealed only a correlation between total physical activity and muscle power (r = 0.545, p = 0.019).

CONCLUSIONS

Adults with XLH have a marked deficit in lower limb muscle power and a reduced functional capacity, with a high incidence of impaired mobility and inactivity. In addition to metabolic effects of XLH, low physical activity may contribute to deficits in lower limb power. Further studies are required to develop novel treatment approaches to improve physical function and mobility.

HPMPdb: a machine learning-ready database of protein molecular phenotypes associated to human missense variants

Current human Single Amino acid Variants (SAVs) databases provide a link between a SAVs and their effect on the carrier individual phenotype, often dividing them into Deleterious/Neutral variants. This is a very coarse-grained description of the genotype-to-phenotype relationship because it relies on un-realistic assumptions such as the perfect Mendelian behavior of each SAV and considers only dichotomic phenotypes. Moreover, the link between the effect of a SAV on a protein (its molecular phenotype) and the individual phenotype is often very complex, because multiple level of biological abstraction connect the protein and individual level phenotypes. Here we present HPMPdb, a manually curated database containing human SAVs associated with the detailed description of the molecular phenotype they cause on the affected proteins. With particular regards to machine learning (ML), this database can be used to let researchers go beyond the existing Deleterious/Neutral prediction paradigm, allowing them to build molecular phenotype predictors instead. Our class labels describe in a succinct way the effects that each SAV has on 15 protein molecular phenotypes, such as protein-protein interaction, small molecules binding, function, post-translational modifications (PTMs), sub-cellular localization, mimetic PTM, folding and protein expression. Moreover, we provide researchers with all necessary means to re-producibly train and test their models on our database. The webserver and the data described in this paper are available at hpmp.esat.kuleuven.be.

•

Current variant-effect predictors perform a coarse-grained modeling and rely on unrealistic assumptions.

•

The link between the effect of a variant and the individual phenotype is complex. It would be more intuitive to predict the molecular phenotype that each variant causes on the carrier protein.

•

HPMP is a manually curated database containing human variants associated with the molecular phenotype they cause on the affected proteins.

•

We manually translated variants from Uniprot into 15 Machine Learning-ready labels describing the affected protein molecular phenotype.

•

The goal of HPMP is to allow researchers to go beyond the existing variant-effect prediction paradigm and allow them to build molecular phenotype predictors instead.

•

The webserver and the data described in this paper are available at hpmp.esat.kuleuven.be

PyUUL provides an interface between biological structures and deep learning algorithms

Structural bioinformatics suffers from the lack of interfaces connecting biological structures and machine learning methods, making the application of modern neural network architectures impractical. This negatively affects the development of structure-based bioinformatics methods, causing a bottleneck in biological research. Here we present PyUUL ( https://pyuul.readthedocs.io/ ), a library to translate biological structures into 3D tensors, allowing an out-of-the-box application of state-of-the-art deep learning algorithms. The library converts biological macromolecules to data structures typical of computer vision, such as voxels and point clouds, for which extensive machine learning research has been performed. Moreover, PyUUL allows an out-of-the box GPU and sparse calculation. Finally, we demonstrate how PyUUL can be used by researchers to address some typical bioinformatics problems, such as structure recognition and docking.

Predictive factors for lymph node involvement in sporadic medullary thyroid microcarcinoma: a systematic review

OBJECTIVE

The aim of the study was to determine the impact of laboratory and imaging tests in predicting central and lateral neck lymph node/LN involvement and in decision making for surgical extent.

MATERIALS AND METHODS

A PubMed, Web of Science and Scopus search was performed according to PRISMA criteria. The relationship between nodule size, diagnostic biomarkers and imaging with LN involvement were evaluated.

RESULTS

The available data analysis did not yield clear indications of the relationship between each of these topics and the presence, number, and location of LN involved. There was no conclusive data for the selective indication of central neck dissection in the preoperative diagnosis of microMTC.

CONCLUSIONS

There is no justification for less invasive interventions than total thyroidectomy with lymph node dissection.

EXTH-20. SINGLE-CELL DRUG ACTIVITY MAPPING IN GLIOBLASTOMA IDENTIFIES EXTENDED DRUG RESPONSE HETEROGENEITY AND THERAPY-INDUCED CELLULAR PLASTICITY

Glioblastoma (GBM) remains a highly malignant and incurable brain tumour. The inability to achieve clinical improvements in GBM treatment can be attributed to the excessive heterogeneity and plasticity of GBM cells, which is reflected by the presence of various cellular states within each tumour. How each of these tumour cell subtypes respond to therapy remains largely unknown. In this work, we developed a functional diagnostic analysis pipeline to measure therapeutic activity in GBM tumour cells at single-cell resolution using mass cytometry by time-of-flight (CyTOF). By applying an optimised GBM-specific and therapy-tailored antibody panel, we measured therapeutic activity upon exposure to ionising radiation (RT) or a small molecule MDM2 inhibitor (AMG232) in a cohort of patient-derived GBM cell lines (n=14). As such, extended heterogeneity in drug responsiveness was reflected by diverse degrees of alterations in cell cycle progression and apoptotic signalling, in addition to shifts in tumoral phenotypic states implying therapy-induced plasticity. A similar approach was used to measure drug activity in freshly resected tumour samples (n=18) harvested from different tumour regions (core or invasive front) within hours following surgery. Accordingly, we identified highly variable fractions of responsive tumour and microenvironmental cell populations in a patient-specific way. The ability to measure drug activity at single-cell resolution in a patient-tailored manner by applying a genotype-agnostic method, paves the way for advanced precision cancer medicine in GBM by offering a novel approach to more precisely select eligible patients for prospective clinical trials.

The use of customized mouthguards during the training produced protective effects on salivary factors of young athletes

AIM

Custom-made mouthguards have many advantages compared to the stock and ready-made types, but sport treatments with custom made mouthguards involve changes in ecological factors of the oral cavity. In the present study we investigated the potential protective role of salivary factors, such as pH value, volume, prostaglandin E2 (PGE2) and 8-iso-prostaglandin F2? (8-iso-PGF2?) levels during training with customised mouthguards.

MATERIALS AND METHODS

A total of 80 subjects were selected: 40 athletes, of whom 20 practice volleyball and 20 basketball (test group), and 40 subjects who attend a gym at a non-competitive level (control group). The athletes (test group) were analyzed at baseline (T0), pre-training (T1), post-training with custom-made Ethylene-Vinyl-Acetate (EVA) mouthguards (T2), post-training without mouthguards (T3). The control group was analyzed only at baseline (T0). On each player, in the 4 time points, and on the control group at T0, we stimulated saliva for determining PGE2 and 8-iso-PGF2? levels by radioimmunoassay and pH value by a pH meter and volume/ml. Saliva pH was calculated with a pH meter.

RESULTS

We observed an inhibition of 8-iso-PGF2? salivary release induced by physical exercise and by use of custom-made mouthguard, while we found an increase in PGE2 salivary level in athletes after training and wearing the mouthguard. Furthermore, in the test of the volume of saliva produced in 5 minutes, a significant inhibition of saliva production emerged in the athletes who did not use the mouthguard during sports activities.

CONCLUSION

Sports activity could lead to a reduction in oxidative stress and the use of mouth guards seems even more effective for athletes.

b2bTools: online predictions for protein biophysical features and their conservation

We provide integrated protein sequence-based predictions via https://bio2byte.be/b2btools/. The aim of our predictions is to identify the biophysical behaviour or features of proteins that are not readily captured by structural biology and/or molecular dynamics approaches. Upload of a FASTA file or text input of a sequence provides integrated predictions from DynaMine backbone and side-chain dynamics, conformational propensities, and derived EFoldMine early folding, DisoMine disorder, and Agmata β-sheet aggregation. These predictions, several of which were previously not available online, capture 'emergent' properties of proteins, i.e. the inherent biophysical propensities encoded in their sequence, rather than context-dependent behaviour (e.g. final folded state). In addition, upload of a multiple sequence alignment (MSA) in a variety of formats enables exploration of the biophysical variation observed in homologous proteins. The associated plots indicate the biophysical limits of functionally relevant protein behaviour, with unusual residues flagged by a Gaussian mixture model analysis. The prediction results are available as JSON or CSV files and directly accessible via an API. Online visualisation is available as interactive plots, with brief explanations and tutorial pages included. The server and API employ an email-free token-based system that can be used to anonymously access previously generated results.

Clinical and trichoscopic features in various forms of scalp psoriasis

BACKGROUND

Scalp psoriasis is often undiagnosed or inadequately treated. The patient himself underestimates the seriousness of this hair disease and consults too late to a dermatologist.

OBJECTIVES

The aim of our study was to create a correlation between the clinical patterns and trichoscopy of scalp psoriasis such in a way to help the clinician to make the diagnosis and select the appropriate therapy.

MATERIAL AND METHODS

We gathered all patients affected of scalp psoriasis afferent to Outpatient's hair consultation of the Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, from January 2012 to December 2018. All patients were evaluated through clinical, trichoscopic examination and a skin biopsy only in doubtful cases. We quantified the severity of the disease with several objective and subjective parameters every 4 months, up to 1 year. We recorded therapies, outcome data and quality of life.

RESULTS

We collected 156 patients affected by scalp psoriasis, identifying seven clinical patterns with specific trichoscopical correlation. In the order of frequency, the clinical patterns were as follows: plaque psoriasis (with a prevalence of erythema, silver-white scales and twisted red loops vessels and red dots); thin scales (with silvery-white scales, simple red lines and signet red ring vessels); sebopsoriasis (with greasy scales, erythema with red dots, globules and twisted and bushy red loops at high magnification); psoriatic cap (with silver-white scales, erythema and polymorphic vascular pattern); pityriasis amiantacea (with yellowish adherent scales, erythema and simple red loops capillaries); cicatricial psoriatic alopecia (with erythema associated with yellowish, silver-white scales with twisted and bushy red loops capillaries) and pustular psoriasis (with 'flower shape' pustular lesions, erythema simple red loops capillaries).

CONCLUSIONS

The description of different clinical patterns of scalp psoriasis and its trichoscopical correlations may help the clinician to make the diagnosis also in atypical presentations and to prescribe an adequate therapeutic regimen.

In-silico prediction of in-vitro protein liquid-liquid phase separation experiments outcomes with multi-head neural attention

MOTIVATION

Proteins able to undergo Liquid-Liquid Phase Separation (LLPS) in-vivo and in-vitro are drawing a lot of interest, due to their functional relevance for cell life. Nevertheless, the proteome-scale experimental screening of these proteins seems unfeasible, because besides being expensive and time consuming, LLPS is heavily influenced by multiple environmental conditions such as concentration, pH and temperature, thus requiring a combinatorial number of experiments for each protein.

RESULTS

To overcome this problem, we propose an Neural Network model able to predict the LLPS behavior of proteins given specified experimental conditions, effectively predicting the outcome of in-vitro experiments. Our model can be used to rapidly screen proteins and experimental conditions searching for LLPS, thus reducing the search space that needs to be covered experimentally. We experimentally validate Droppler's prediction on the the TAR DNA-binding protein in different experimental conditions, showing the consistency of its predictions.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Physical function in UK adults with osteogenesis imperfecta: a cross-sectional analysis of the RUDY study

We describe the physical function in adults with osteogenesis imperfecta (OI) and explored clinical and non-clinical factors related to its impairment. Our data showed that physical dysfunction is a common feature of adults with OI, varying by OI severity, and mediated by the presence and quality of pain and fatigue symptoms.

INTRODUCTION

There is a paucity of data describing physical function in adults with osteogenesis imperfecta (OI). We investigated the effects of OI and its severity on physical function and explored the relationship between physical function and number of fractures and symptomatology.

METHODS

Adults with OI of different types were recruited from the RUDY study, an ongoing UK-based prospective cohort study. Participants completed demographic and clinical questions and questionnaires. These assessed physical function (SF-36), mobility (EQ-5D-5L and NEADL), fatigue (FACIT-F), and pain (SF-MQ-2). Scores were compared using parametric or non-parametric statistical analyses, whereas correlations between outcomes were examined using univariate and multivariate regression analysis.

RESULTS

Seventy-eight adults with OI aged 43.5 ± 14.5 years were enrolled (type I, 32; type III, 11; type IV, 10; unknown type, 26). Physical function (PCS, SF-36) was significantly lower in all participants than normative values (p < 0.001) and in type III than type I (p = 0.008). Mobility was significantly different across the types (EQ-5D-EL, p = 0.007; NEADL, p < 0.001), with type III having more severe problems, followed by types IV, unknown, and I. Physical function was associated with OI type (r = 0.26; p = 0.021), presence and quality of pain (r = - 0.57; p < 0.0001), and fatigue (r = - 0.51; p < 0.0001). Multivariate analysis revealed that physical function correlated independently with age, OI type, fatigue, and non-neuropathic pain.

CONCLUSIONS

Individuals with OI display a marked deterioration in physical function during adulthood. This impairment varies in severity according to the OI phenotype and is associated with the presence of non-neuropathic pain and fatigue.

ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values

Nuclear magnetic resonance (NMR) spectroscopy data provides valuable information on the behaviour of proteins in solution. The primary data to determine when studying proteins are the per-atom NMR chemical shifts, which reflect the local environment of atoms and provide insights into amino acid residue dynamics and conformation. Within an amino acid residue, chemical shifts present multi-dimensional and complexly cross-correlated information, making them difficult to analyse. The ShiftCrypt method, based on neural network auto-encoder architecture, compresses the per-amino acid chemical shift information in a single, interpretable, amino acid-type independent value that reflects the biophysical state of a residue. We here present the ShiftCrypt web server, which makes the method readily available. The server accepts chemical shifts input files in the NMR Exchange Format (NEF) or NMR-STAR format, executes ShiftCrypt and visualises the results, which are also accessible via an API. It also enables the ”biophysically-based” pairwise alignment of two proteins based on their ShiftCrypt values. This approach uses Dynamic Time Warping and can optionally include their amino acid code information, and has applications in, for example, the alignment of disordered regions. The server uses a token-based system to ensure the anonymity of the users and results. The web server is available at www.bio2byte.be/shiftcrypt.

Role and therapeutic potential of liquid-liquid phase separation in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a late-onset neurodegenerative disease selectively affecting motor neurons, leading to progressive paralysis. Although most cases are sporadic, ∼10% are familial. Similar proteins are found in aggregates in sporadic and familial ALS, and over the last decade, research has been focused on the underlying nature of this common pathology. Notably, TDP-43 inclusions are found in almost all ALS patients, while FUS inclusions have been reported in some familial ALS patients. Both TDP-43 and FUS possess ‘low-complexity domains’ (LCDs) and are considered as ‘intrinsically disordered proteins’, which form liquid droplets in vitro due to the weak interactions caused by the LCDs. Dysfunctional ‘liquid–liquid phase separation’ (LLPS) emerged as a new mechanism linking ALS-related proteins to pathogenesis. Here, we review the current state of knowledge on ALS-related gene products associated with a proteinopathy and discuss their status as LLPS proteins. In addition, we highlight the therapeutic potential of targeting LLPS for treating ALS.

Regenerative medicine, organ bioengineering and transplantation

Background

Organ transplantation is predicted to increase as life expectancy and the incidence of chronic diseases rises. Regenerative medicine-inspired technologies challenge the efficacy of the current allograft transplantation model.

Methods

A literature review was conducted using the PubMed interface of MEDLINE from the National Library of Medicine. Results were examined for relevance to innovations of organ bioengineering to inform analysis of advances in regenerative medicine affecting organ transplantation. Data reports from the Scientific Registry of Transplant Recipient and Organ Procurement Transplantation Network from 2008 to 2019 of kidney, pancreas, liver, heart, lung and intestine transplants performed, and patients currently on waiting lists for respective organs, were reviewed to demonstrate the shortage and need for transplantable organs.

Results

Regenerative medicine technologies aim to repair and regenerate poorly functioning organs. One goal is to achieve an immunosuppression-free state to improve quality of life, reduce complications and toxicities, and eliminate the cost of lifelong antirejection therapy. Innovative strategies include decellularization to fabricate acellular scaffolds that will be used as a template for organ manufacturing, three-dimensional printing and interspecies blastocyst complementation. Induced pluripotent stem cells are an innovation in stem cell technology which mitigate both the ethical concerns associated with embryonic stem cells and the limitation of other progenitor cells, which lack pluripotency. Regenerative medicine technologies hold promise in a wide array of fields and applications, such as promoting regeneration of native cell lines, growth of new tissue or organs, modelling of disease states, and augmenting the viability of existing ex vivo transplanted organs.

Conclusion

The future of organ bioengineering relies on furthering understanding of organogenesis, in vivo regeneration, regenerative immunology and long-term monitoring of implanted bioengineered organs.

Insight into the protein solubility driving forces with neural attention

Protein solubility is a key aspect for many biotechnological, biomedical and industrial processes, such as the production of active proteins and antibodies. In addition, understanding the molecular determinants of the solubility of proteins may be crucial to shed light on the molecular mechanisms of diseases caused by aggregation processes such as amyloidosis. Here we present SKADE, a novel Neural Network protein solubility predictor and we show how it can provide novel insight into the protein solubility mechanisms, thanks to its neural attention architecture. First, we show that SKADE positively compares with state of the art tools while using just the protein sequence as input. Then, thanks to the neural attention mechanism, we use SKADE to investigate the patterns learned during training and we analyse its decision process. We use this peculiarity to show that, while the attention profiles do not correlate with obvious sequence aspects such as biophysical properties of the aminoacids, they suggest that N- and C-termini are the most relevant regions for solubility prediction and are predictive for complex emergent properties such as aggregation-prone regions involved in beta-amyloidosis and contact density. Moreover, SKADE is able to identify mutations that increase or decrease the overall solubility of the protein, allowing it to be used to perform large scale in-silico mutagenesis of proteins in order to maximize their solubility.

The solubility of proteins is a crucial biophysical aspect when it comes to understanding many human diseases and to improve the industrial processes for protein production. Due to its relevance, computational methods have been devised in order to study and possibly optimize the solubility of proteins. In this work we apply a deep-learning technique, called neural attention to predict protein solubility while “opening” the model itself to interpretability, even though Machine Learning models are usually considered black boxes. Thank to the attention mechanism, we show that i) our model implicitly learns complex patterns related to emergent, protein folding-related, aspects such as to recognize β-amyloidosis regions and that ii) the N-and C-termini are the regions with the highes signal fro solubility prediction. When it comes to enhancing the solubility of proteins, we, for the first time, propose to investigate the synergistic effects of tandem mutations instead of “single” mutations, suggesting that this could minimize the number of required proposed mutations.

Pitch angle control of a wind turbine operating above the rated wind speed: A sliding mode control approach

The paper focuses on variable-rotor-speed/variable-blade-pitch wind turbines operating in the region of high wind speeds, where control is aimed at limiting the turbine energy capture to the rated power value. A robust sliding mode approach is proposed, using the blade pitch as control input, in order to regulate the rotor speed to a fixed rated value, in the presence of uncertainties characterizing the wind turbine model. Closed loop convergence of the overall control system is proved. The proposed control solution has been validated on a 5-MW three-blade wind turbine using the National Renewable Energy Laboratory (NREL) wind turbine simulator FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code. A comparison with the standard FAST baseline controller (NWTC 2012 and Jonkman et al. 2009) has been also included.

Accurate prediction of protein beta-aggregation with generalized statistical potentials

Motivation

Protein beta-aggregation is an important but poorly understood phenomena involved in diseases as well as in beneficial physiological processes. However, while this task has been investigated for over 50 years, very little is known about its mechanisms of action. Moreover, the identification of regions involved in aggregation is still an open problem and the state-of-the-art methods are often inadequate in real case applications.

Results

In this article we present AgMata, an unsupervised tool for the identification of such regions from amino acidic sequence based on a generalized definition of statistical potentials that includes biophysical information. The tool outperforms the state-of-the-art methods on two different benchmarks. As case-study, we applied our tool to human ataxin-3, a protein involved in Machado–Joseph disease. Interestingly, AgMata identifies aggregation-prone residues that share the very same structural environment. Additionally, it successfully predicts the outcome of in vitro mutagenesis experiments, identifying point mutations that lead to an alteration of the aggregation propensity of the wild-type ataxin-3.

Availability and implementation

A python implementation of the tool is available at https://bitbucket.org/bio2byte/agmata.

Supplementary information

Supplementary data are available at Bioinformatics online.

Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis

Machine learning (ML) is ubiquitous in bioinformatics, due to its versatility. One of the most crucial aspects to consider while training a ML model is to carefully select the optimal feature encoding for the problem at hand. Biophysical propensity scales are widely adopted in structural bioinformatics because they describe amino acids properties that are intuitively relevant for many structural and functional aspects of proteins, and are thus commonly used as input features for ML methods. In this paper we reproduce three classical structural bioinformatics prediction tasks to investigate the main assumptions about the use of propensity scales as input features for ML methods. We investigate their usefulness with different randomization experiments and we show that their effectiveness varies among the ML methods used and the tasks. We show that while linear methods are more dependent on the feature encoding, the specific biophysical meaning of the features is less relevant for non-linear methods. Moreover, we show that even among linear ML methods, the simpler one-hot encoding can surprisingly outperform the “biologically meaningful” scales. We also show that feature selection performed with non-linear ML methods may not be able to distinguish between randomized and “real” propensity scales by properly prioritizing to the latter. Finally, we show that learning problem-specific embeddings could be a simple, assumptions-free and optimal way to perform feature learning/engineering for structural bioinformatics tasks.

Significant chronic airway abnormalities in never-smoking HIV-infected patients

OBJECTIVES

The aim of the study was to describe chronic lung disease in HIV-infected never-smokers by looking at clinical, structural and functional abnormalities.

METHODS

This comparative cross-sectional study included 159 HIV-infected never-smoking patients [mean (± standard deviation) age 54.6 ± 9.1 years; 13.2% female; 98.1% with undetectable viral load] and 75 nonmatched never-smoking controls [mean (± standard deviation) age 52.6 ± 6.9 years; 46.7% female]. We examined calcium scoring computer tomography (CT) scans or chest CT scans, all with a lung-dedicated algorithm reconstruction, to assess emphysema and airway disease (respiratory bronchiolitis and/or bronchial wall thickening), tested pulmonary function using spirometry, lung volumes and the diffusion lung capacity of carbon monoxide (DLCO), and assessed respiratory symptoms using the Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT).

RESULTS

Twenty-five (17.2%) of the HIV-infected patients versus two (2.7%) of the controls had a CAT score > 10. Only 5% of the HIV-infected patients showed FEV1% < 80%, and 25% had DLCO < 75% of the predicted value. Based on the CT scans, they had increased prevalences, compared with the controls, of airway disease (37% versus 7.9%, respectively) and emphysema (18% versus 4%, respectively), with more severe and more frequent centrilobular disease. After correction for age, sex and clinical factors, HIV infection was significantly associated with CAT > 10 [odds ratio (OR) 7.7], emphysema (OR 4), airway disease (OR 4.5) and DLCO < 75% of predicted (OR 4).

CONCLUSIONS

Although comparisons were limited by the different enrolment methods used for HIV-infected patients and controls, the results suggest that never-smoking HIV-infected patients may present with chronic lung damage characterized by CT evidence of airway disease. A minority of them showed respiratory symptoms, without significant functional abnormalities.

Adherence to growth hormone (GH) therapy in naïve to treatment GH-deficient children: data of the Italian Cohort from the Easypod Connect Observational Study (ECOS)

BACKGROUND

With the use of non-objective measurement, adherence to growth hormone (GH) therapy has been reported suboptimal in a large proportion of patients, and poor adherence has been shown to affect short-term growth response in patients receiving GH treatment.

OBJECTIVE

The Easypod™ electronic device allows objective measurement of adherence. In this study, we report 3-year prospective adherence data of the Italian cohort of naïve GH deficient (GHD) children extrapolated from the Easypod Connect Observational Study (ECOS) database.

PATIENTS AND METHODS

Seventy-three GHD children naïve to GH treatment were included in the analysis. 22 Italian centers participated in the study.

RESULTS

Mean adherence rate was consistently above 85% across the 3-year observation period. Particularly, mean adherence was 88.5%, 86.6%, and 85.7% after 1, 2 and 3 years, respectively. Mean (± SD) height-SDS increase after the first year was 0.41 (± 0.38).

CONCLUSIONS

The majority of naïve GHD children starting GH treatment with Easypod maintained an adherence rate > 85% up to 3 years. Easypod is a useful tool to follow-up patients' adherence allowing timely intervention to improve optimal treatment for these patients.

Author Correction: Exploring the Sequence-based Prediction of Folding Initiation Sites in Proteins

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The non-surgical management for hemorrhoidal disease. A systematic review

The non-surgical treatments for hemorrhoids are cost and time-saving techniques usually performed in patients suffering early hemorrhoidal disease. The most used are rubber band ligation (RBL), injection sclerotherapy (IS), and infrared coagulation (IRC). We performed a systematic review in order to evaluate: do these procedures really help to avoid further more aggressive treatments? What are the common harms? What are the rare harms? How many recurrences there are? A total of 21 RCTs were included in this review: 12 on RBL, 4 on IRC and 5 on IS. In RBL bleeding stops in up to 90% and III degree hemorrhoids improves in 78%-83.8%. IV degree prolapse should have a more invasive treatment. The commonest complications are bleeding and pain (8-80%). IRC related improvement is 78%, 51% and 22% for I, II and III degree. Post-operative pain occurs in 15-100% and post-operative bleeding ranges from 15% to 44%. Recurrence rate is 13% at a three months follow-up. IS brings to the resolution of prolapse in 90%-100% of II degree and allows good results for III degree even if reported only by case series. The post-procedural pain is 36%-49%. Bleeding is a very rare harm. Even if not definitive, these treatments could be an alternative for mild symptomatic patients after a clear explanation of recurrence rates and possible complications.

DEOGEN2: prediction and interactive visualization of single amino acid variant deleteriousness in human proteins

High-throughput sequencing methods are generating enormous amounts of genomic data, giving unprecedented insights into human genetic variation and its relation to disease. An individual human genome contains millions of Single Nucleotide Variants: to discriminate the deleterious from the benign ones, a variety of methods have been developed that predict whether a protein-coding variant likely affects the carrier individual's health. We present such a method, DEOGEN2, which incorporates heterogeneous information about the molecular effects of the variants, the domains involved, the relevance of the gene and the interactions in which it participates. This extensive contextual information is non-linearly mapped into one single deleteriousness score for each variant. Since for the non-expert user it is sometimes still difficult to assess what this score means, how it relates to the encoded protein, and where it originates from, we developed an interactive online framework (http://deogen2.mutaframe.com/) to better present the DEOGEN2 deleteriousness predictions of all possible variants in all human proteins. The prediction is visualized so both expert and non-expert users can gain insights into the meaning, protein context and origins of each prediction.

Perspectives of the International Society for Cell & Gene Therapy Gastrointestinal Scientific Committee on the Intravenous Use of Mesenchymal Stromal Cells in Inflammatory Bowel Disease (PeMeGi)

Inflammatory bowel disease (IBD), namely, Crohn's disease and ulcerative colitis, remains a grievous and recalcitrant problem incurring significant human and health care costs, even in consideration of the growing incidence. Initial goals of care aimed to achieve the induction and maintenance of clinical remission. The advent of novel treat-to-target approaches using patient stratification, early introduction of immunosuppressants and rapid escalation to biologics or early use of combination therapy has refocused the goals of care toward the achievement of mucosal healing. This is in an attempt to preserve intestinal function, decrease hospitalization and surgery rates and improve the quality of life of affected patients. Cellular therapeutics for the treatment of IBD offers an unprecedented opportunity to change the current paradigm from single-targeted to systems-targeted therapy, trying to dampen the whole inflammatory cascade instead of a only molecule. Therefore, as we move forward, the importance of designing informative and possibly adaptive trial designs, standardizing methodologies, harmonizing goals of therapy and evaluating methods cannot be underemphasized. In this article, we review the current literature on the application of mesenchymal stromal cells for the treatment of IBD in an effort to establish a consensus on designing efficient and consistent clinical trials for the intravenous use of this cellular therapy in IBD.

Computational identification of prion-like RNA-binding proteins that form liquid phase-separated condensates

Motivation

Eukaryotic cells contain different membrane-delimited compartments, which are crucial for the biochemical reactions necessary to sustain cell life. Recent studies showed that cells can also trigger the formation of membraneless organelles composed by phase-separated proteins to respond to various stimuli. These condensates provide new ways to control the reactions and phase-separation proteins (PSPs) are thus revolutionizing how cellular organization is conceived. The small number of experimentally validated proteins, and the difficulty in discovering them, remain bottlenecks in PSPs research.

Results

Here we present PSPer, the first in-silico screening tool for prion-like RNA-binding PSPs. We show that it can prioritize PSPs among proteins containing similar RNA-binding domains, intrinsically disordered regions and prions. PSPer is thus suitable to screen proteomes, identifying the most likely PSPs for further experimental investigation. Moreover, its predictions are fully interpretable in the sense that it assigns specific functional regions to the predicted proteins, providing valuable information for experimental investigation of targeted mutations on these regions. Finally, we show that it can estimate the ability of artificially designed proteins to form condensates (r=−0.87), thus providing an in-silico screening tool for protein design experiments.

Availability and implementation

PSPer is available at bio2byte.com/psp.

Supplementary information

Supplementary data are available at Bioinformatics online.

A case-control study of risk factors associated with Zoon balanitis in men

BACKGROUND

Zoon balanitis (ZB) is a chronic inflammatory benign mucositis. Its etiopathogenesis still remains hypothetical and speculative.

OBJECTIVES

To determine risk factors associated with genital ZB in men.

METHODS

This is a case-control study including 30 patients diagnosed with ZB and 54 patients with dermatological diseases other than ZB enrolled in the Dermatological Clinic of the University of Padova, Italy, from September 2015 to June 2018. Univariate and multivariate logistic regression analyses were used for analysis of data collected.

RESULTS

According to multivariate logistic regression analysis, risk factors for ZB were as follows: the mean daily cigarettes consumption (OR 1.065; 95% CI 1.8-11.4; P = 0.006) and the number of weekly foreskin retractions (OR 0.847; 95% CI 5.5-24.1; P = 0.003). There were no statistically significant differences between cases and controls according to age, presence of circumcision as well in number of sexual partners.

CONCLUSIONS

To our knowledge, this is the first case-control study showing that smoking and poor genital hygiene are associated with being affected by ZB.

Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome

Next generation sequencing technologies are providing increasing amounts of sequencing data, paving the way for improvements in clinical genetics and precision medicine. The interpretation of the observed genomic variants in the light of their phenotypic effects is thus emerging as a crucial task to solve in order to advance our understanding of how exomic variants affect proteins and how the proteins' functional changes affect human health. Since the experimental evaluation of the effects of every observed variant is unfeasible, Bioinformatics methods are being developed to address this challenge in-silico, by predicting the impact of millions of variants, thus providing insight into the deleteriousness landscape of entire proteomes. Here we show the feasibility of this approach by using the recently developed DEOGEN2 variant-effect predictor to perform the largest in-silico mutagenesis scan to date. We computed the deleteriousness score of 170 million variants over 15000 human proteins and we analysed the results, investigating how the predicted deleteriousness landscape of the proteins relates to known functionally and structurally relevant protein regions and biophysical properties. Moreover, we qualitatively validated our results by comparing them with two mutagenesis studies targeting two specific proteins, showing the consistency of DEOGEN2 predictions with respect to experimental data.

SVM-dependent pairwise HMM: an application to protein pairwise alignments

Motivation

Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondary structure, have been used to improve the alignment performances. This is especially relevant for proteins with highly divergent sequences. However, recent works suggest that different features may have different importance in diverse protein classes and it would be an advantage to have more customizable approaches, capable to deal with different alignment definitions.

Results

Here we present Rigapollo, a highly flexible pairwise alignment method based on a pairwise HMM-SVM that can use any type of information to build alignments. Rigapollo lets the user decide the optimal features to align their protein class of interest. It outperforms current state of the art methods on two well-known benchmark datasets when aligning highly divergent sequences.

Availability and implementation

A Python implementation of the algorithm is available at http://ibsquare.be/rigapollo.

Contact

wim.vranken@vub.be.

Supplementary information

Supplementary data are available at Bioinformatics online.

Antimicrobial consumption and impact of antimicrobial stewardship programmes in long-term care facilities

BACKGROUND

Antimicrobials are among the most frequently prescribed drugs in long-term care facilities (LTCFs). Implementation of antimicrobial stewardship programmes (ASPs) is often challenging because of scarce data in this setting.

OBJECTIVES

This narrative review aimed to provide data about antibiotic consumption in LTCFs and the need, implementation, and organization of ASPs in this setting.

SOURCE

PubMed was searched for studies assessing antimicrobial consumption and implementation of ASPs in LTCFs. The search was restricted to articles published in English in the last 10 years. Experts belonging to the ESCMID Study Group for Infections in the Elderly (ESGIE) reviewed the selected studies and evaluated the studies on ASPs according to the GRADE approach. Moreover, the quality of reporting has been assessed according to TREND and CONSORT checklists for quasi-experimental and cluster randomized clinical trials (cRCT), respectively.

CONTENT

Data on antibiotic consumption in LTCFs show great variability in LTCFs across and within countries. Reasons for this variability are difficult to analyse because of the differences in the types of LTCFs, their organization, and the population cared-for in the different LTCFs. However, studies show that the use of antibiotics among elderly patients in LTCFs, especially in cases of asymptomatic bacteriuria and influenza-like syndromes, is often inappropriate. High-quality cRCTs and low to moderate quality quasi-experimental studies show that educational interventions direct at nurse and physicians are effective in reducing unnecessary antibiotic prescriptions.

IMPLICATIONS

There is an urgent need for ASPs tailored for LTCFs. Multifaceted organized educational interventions, involving both clinicians and nursing staff, should be advocated and require institutional intervention by health authorities. Future studies assessing the impact of well-defined ASPs in LTCFs should produce compelling evidence in this setting.

In vitro protective effects of resveratrol and stilbene alkanoic derivatives on induced oxidative stress on C2C12 and MCF7 cells

Resveratrol (3,4’,5-trihydroxy-trans-stilbene) is a natural phytoalexin found in grapes and wine, which has been extensively studied for a wide range of biological effects. A large number of stilbene-containing derivatives have displayed antioxidant and antiproliferative activities on various cancer cell lines. In this study, a series of stilbene hybrids 1-9, previously reported as peroxisome proliferator-activated receptor (PPAR) agonists, were assessed at micromolar concentrations using MTT cell viability assay in C2C12 and MCF7 cell lines. The modulation of oxidative stress was also evaluated by measuring the protective effects on reactive oxygen species (ROS) production induced or not by oxidative stimulus. Among these, compounds 2 and 8 showed significant radical scavenging activity.

Effects of central fibroblast growth factor 21 (FGF21) in energy balance

Fibroblast growth factor 21 (FGF21) is known as a major metabolic regulator of glucose and lipid homeostasis. Continuous intracerebroventricular (i.c.v.) administration of FGF21 was found to modulate feeding and energy expenditure in rats with diet-induced obesity, suggesting a central effect by the peptide. In this context, in the present work, we studied the effects of a single central FGF21 administration (0.5-5 µg) on feeding and energy expenditure by evaluating locomotor activity, interscapular brown adipose tissue (BAT) weight, gene expression of uncoupling protein-1 (UCP-1) in BAT and plasma norepinephrine (NE) levels in Sprague-Dawley fed rats. In addition, we evaluated the effects of FGF21 on orexigenic [agouti-related peptide (AgRP) and neuropeptide Y (NPY)] and anorexigenic [cocaine and amphetamine-regulated transcript (CART) and proopiomelanocortin (POMC)] peptides, in the hypothalamus, and dopamine (DA) and serotonin (5-hydroxytriptamine, 5-HT) levels in nucleus accumbens (NAc). We confirmed that central FGF21 administration induced a significant increase in food intake, possibly mediated by increased NPY and AgRP, and decreased POMC and CART gene expression. Moreover, FGF21 could modulate the motivational aspects of feeding, possibly through stimulated NAc DA levels. On the other hand, our findings of decreased locomotor activity, BAT weight, UCP-1 gene expression and plasma NE levels support a role for FGF21 in decreasing energy expenditure.

Effects of central fibroblast growth factor 21 and irisin in anxiety-like behavior

Adipose tissue and skeletal muscle are organs capable of secreting many bioactive molecules, such as adipomiokines that could be possibly involved in mood disorders. In the present work, we investigated the possible behavioral effects of a single intracerebroventricular (i.c.v.) injection of two adipomiokines, fibrobroblast growth factor (FGF)-21 (0.5-5.0 µg) and irisin (0.4-0.6 µg), in male rats tested in the open field and elevated plus maze tests. Prefrontal cortex levels of norepinephrine (NE), dopamine (DA) and serotonin (5-hydroxytryptamine, 5-HT) and the gene expression of catechol-O-methyltransferase (COMT), dopamine transport (DAT) and tyrosine hydroxylase (TH), were measured by high performance liquid chromatography (HPLC) analysis and real-time reverse transcription polymerase chain reaction (RT-PCR). Both FGF-21 and irisin administration induced anxiogenic behavior, increased DA levels in prefrontal cortex, decreased COMT, DAT and increased TH gene expression. In conclusion, in the present study we demonstrated behavioral effects induced by central FGF-21 and irisin injections that could involve increased DA signaling in the prefrontal cortex.

Crocus sativus, Serenoa repens and Pinus massoniana extracts modulate inflammatory response in isolated rat prostate challenged with LPS

Prostatitis is a common prostate disease that could be promoted by bacterial or non-bacterial infectious agents. In addition, inflammatory pathways involved in prostatitis have been increasingly studied, and herbal extracts endowed with anti-inflammatory effects are under investigation, individually or in combination, for their efficacy in alleviating the burden of inflammation, with possible improvements in symptoms. Serenoa repens (Serenoa), in combination with Crocus sativus (Crocus) and Pinus massoniana (Pinus), has previously shown to improve sexual function and limit urinary symptoms in patients suffering from concomitant erectile dysfunction and lower urinary tract symptoms. In this context, the aim of the present study is to evaluate the efficacy of Serenoa, Crocus and Pinus extracts, either alone or in combination, on immortalized prostate cells (PC3) and in an experimental model of bacterial prostatitis constituted by ex vivo prostate specimens challenged with lipopolysaccharide (LPS). We found that the tested extracts were able to reduce ROS production by PC3 cells and NFkB and PGE2 activity in prostate specimens challenged with LPS. In addition, the pharmacological association of the extracts displayed synergistic effects indicating a rational use of the mixture of the tested extracts as a novel anti-oxidant and anti-inflammatory formulation in bacterial prostatitis. Finally, we performed analytical and in vitro evaluation to better characterize the phytochemical profile and the mechanism of action of selected secondary metabolites.

Observation selection bias in contact prediction and its implications for structural bioinformatics

Next Generation Sequencing is dramatically increasing the number of known protein sequences, with related experimentally determined protein structures lagging behind. Structural bioinformatics is attempting to close this gap by developing approaches that predict structure-level characteristics for uncharacterized protein sequences, with most of the developed methods relying heavily on evolutionary information collected from homologous sequences. Here we show that there is a substantial observational selection bias in this approach: the predictions are validated on proteins with known structures from the PDB, but exactly for those proteins significantly more homologs are available compared to less studied sequences randomly extracted from Uniprot. Structural bioinformatics methods that were developed this way are thus likely to have over-estimated performances; we demonstrate this for two contact prediction methods, where performances drop up to 60% when taking into account a more realistic amount of evolutionary information. We provide a bias-free dataset for the validation for contact prediction methods called NOUMENON.

Investigating the Molecular Mechanisms Behind Uncharacterized Cysteine Losses from Prediction of Their Oxidation State

Cysteines are among the rarest amino acids in nature, and are both functionally and structurally very important for proteins. The ability of cysteines to form disulfide bonds is especially relevant, both for constraining the folded state of the protein and for performing enzymatic duties. But how does the variation record of human proteins reflect their functional importance and structural role, especially with regard to deleterious mutations? We created HUMCYS, a manually curated dataset of single amino acid variants that (1) have a known disease/neutral phenotypic outcome and (2) cause the loss of a cysteine, in order to investigate how mutated cysteines relate to structural aspects such as surface accessibility and cysteine oxidation state. We also have developed a sequence-based in silico cysteine oxidation predictor to overcome the scarcity of experimentally derived oxidation annotations, and applied it to extend our analysis to classes of proteins for which the experimental determination of their structure is technically challenging, such as transmembrane proteins. Our investigation shows that we can gain insights into the reason behind the outcome of cysteine losses in otherwise uncharacterized proteins, and we discuss the possible molecular mechanisms leading to deleterious phenotypes, such as the involvement of the mutated cysteine in a structurally or enzymatically relevant disulfide bond.

A natural formula containing lactoferrin, Equisetum arvensis, soy isoflavones and vitamin D3 modulates bone remodeling and inflammatory markers in young and aged rats

A pivotal role in osteoporosis development is played by radical oxygen species (ROS), the increased production of which is related to inhibited osteoblastic activity and bone formation. A new field of research could involve medicinal plants with antioxidant and protective effects in osteoporosis. Furthermore, considering the multifactorial metabolic aspects of osteoporosis, the pharmacological association of multiple medicinal plants could improve patient response. The aim of the present study is to evaluate in vitro and in vivo the protective effects of a natural formula containing lactoferrin 12%, Equisetum arvensis ES 54%, soy isoflavones 34% and vitamin D3 0.002%, in PBMC and C2C12 cells and in the bone matrix of young (3-month-old) and aged (12-month-old) female Sprague-Dawley rats, following chronic (21 days) administration. In this context, we assayed the activities of several inflammation and bone homeostasis mediators, such as IL-6, TNFα, PGE2, osteoprotegerin, RANK, RANKL and NFkB. In vitro studies showed that natural formula (5-1000μg/ml) was able to significantly inhibit ROS and PGE2 production. In the same concentration range, the natural formula inhibited both TNFα and IL-6 gene expression. In the in vivo studies, we administered to young and aged female rats the natural formula at 5mg/rat for 21 days, finding a significant reduction in inflammatory PGE2 and NFkB activity. Nevertheless, we observed a significant increase in osteoprotegerin/RANKL ratio only in aged rats, compared to the respective control group. In conclusion, our findings corroborate the rational use of natural formula in the prevention and management of osteoporotic disease.

Central apelin-13 administration modulates hypothalamic control of feeding

The 77 amino prepropeptide apelin has been isolated from bovine stomach tissue and several smaller fragments, including apelin-13, showed high affinity for the orphan APJ receptor. The distribution of apelinergic fibers and receptors in the hypothalamus may suggest a role of apelin-13 on energy balance regulation, albeit the studies reporting the acute effects of apelin on feeding control are inconsistent. Considering the possible involvement of apelinergic system on hypothalamic appetite controlling network, in the present study we evaluated in the rat the effects of intrahypothalamic apelin-13 injection on food intake and the involvement of orexigenic and anorexigenic hypothalamic peptides and neurotransmitters. Eighteen rats (6 for each group of treatment) were injected into the ARC with either vehicle or apelin-13 (1-2 μg/rat). Food intake and hypothalamic peptide and neurotransmitter levels were evaluated 2 and 24 h after injection. Compared to vehicle, apelin-13 administration increased food intake both 2 and 24 h following treatment. This effect could be related to inhibited cocaine- and amphetamine-regulated transcript (CART) gene expression and serotonin (5-hydroxytryptamine, 5-HT) synthesis and release, and increased orexin A gene expression in the hypothalamus.

Elevated 8-Isoprostane Levels in Basal Cell Carcinoma and in Uva Irradiated Skin

Isoprostanes are prostaglandin isomers produced from the peroxidation of polyunsaturated fatty acids from the cellular membrane. They have been used as a specific index of cellular lipoperoxidation and as an indirect measure of oxidative stress. However, these molecules also present several biological activities. An oxidative environment measured as the presence of other indirect measurements of reactive oxygen species lipoperoxidation has recently been described in basal cell carcinoma, the most frequent type of non-melanoma skin cancer. This study aims to measure the levels of 8-isoprostaglandin F2α, an isoprostane widely studied in other models as a by-product of ROS-induced lipid peroxidation, in basal cell carcinoma and in UVA irradiated healthy skin. We found that 8-iso-PGF2α is present in higher levels in BCC specimens compared to healthy non sun-exposed skin, confirming previous studies on the production of lipoperoxidation in this tumor. Moreover, we demonstrated that topical pre-treatment with a compound containing vitamin E is capable of reducing 8-iso-PGF2α formation in UV irradiated skin suggesting a role for isoprostanes in UV induced inflammation and eventually carcinogenesis and confirming the function of vitamin E as an antioxidant in this model.

The Regulation of Feeding: A Cross Talk between Peripheral and Central Signalling

Feeding and energy expenditures are modulated by the interplay of hormones and neurotransmitters in the central nervous system (CNS), where the hypothalamus plays a pivotal role in the transduction of peripheral afferents into satiety and feeding signals. Aminergic neurotransmitters such as dopamine (DA), norepinephrine (NE) and serotonin (5-hydroxytryptamine, 5-HT) are historically considered to play a key role, but a number of peptides are involved in finely tuning feeding regulation. This review summarizes the current understanding of the CNS mechanisms of orexigenic peptides, such as neuropeptide Y, orexins, and ghrelin, as well as anorectic peptides, such as leptin, neurotensin (NT), cocaine- and amphetamine regulated transcript (CART) peptide, thyrotropin-releasing hormone (TRH), corticotropin-releasing hormone (CRH), urocortin, amylin.

Independent association of subclinical coronary artery disease and emphysema in HIV-infected patients

OBJECTIVES

Chronic obstructive pulmonary disease (COPD) and coronary artery disease are inflammatory states with a significant clinical impact. The relationship between them has not been investigated in patients with HIV infection. We assessed the presence of subclinical emphysema and coronary artery disease using chest computed tomography (CT) imaging in a cohort of HIV-infected patients receiving antiretroviral therapy.

METHODS

Gated chest CT scans were performed in 1446 consecutive patients to assess the presence and severity of coronary artery calcium (CAC) (classified as a score of 0, 1-100 or > 100) and emphysema (classified using a visual semiquantitative scale: 0, absent; 1-4, mild to moderate; > 4, severe). Univariable and multivariable logistic regression analyses were performed to identify factors independently associated with CAC and emphysema.

RESULTS

The emphysema score was significantly higher in patients with CAC scores of 1-100 and > 100 compared with those with a CAC score of 0. After adjustments for age, sex, smoking status, pack-years of smoking, visceral adiposity and duration of HIV infection, the presence of any emphysema was significantly associated with a CAC score > 0 [odds ratio (OR) 1.43; 95% confidence interval (CI) 1.08-1.88; P = 0.012]. The association persisted after adjustment for the Framingham risk score (OR 1.52; 95% CI 1.16-1.99; P = 0.002). There was a dose-dependent effect in the association between emphysema score and CAC score.

CONCLUSIONS

In this cross-sectional study of HIV-infected patients, there was an independent association between emphysema and CAC, after adjustment for traditional cardiovascular risk factors, suggesting a common pathogenesis of these chronic inflammatory conditions in a chronic inflammatory disease such as HIV infection.