Herpes Simplex Virus Re-Activation in Patients with SARS-CoV-2 Pneumonia: A Prospective, Observational Study.

BACKGROUND: Herpes simplex 1 co-infections in patients with COVID-19 are considered relatively uncommon; some reports on re-activations in patients in intensive-care units were published. The aim of the study was to analyze herpetic re-activations and their clinical manifestations in hospitalized COVID-19 patients, performing HSV-1 PCR on plasma twice a week. METHODS: we conducted a prospective, observational, single-center study involving 70 consecutive patients with severe/critical SARS-CoV-2 pneumonia tested for HSV-1 hospitalized at Azienda Ospedaliero-Universitaria of Modena. RESULTS: of these 70 patients, 21 (30.0%) showed detectable viremia and 13 (62%) had clinically relevant manifestations of HSV-1 infection corresponding to 15 events (4 pneumonia, 5 herpes labialis, 3 gingivostomatitis, one encephalitis and two hepatitis). HSV-1 positive patients were more frequently treated with steroids than HSV-1 negative patients (76.2% vs. 49.0%, p = 0.036) and more often underwent mechanical ventilation (IMV) (57.1% vs. 22.4%, p = 0.005). In the unadjusted logistic regression analysis, steroid treatment, IMV, and higher LDH were significantly associated with an increased risk of HSV1 re-activation (odds ratio 3.33, 4.61, and 16.9, respectively). The association with the use of steroids was even stronger after controlling for previous use of both tocilizumab and IMV (OR = 5.13, 95% CI:1.36-19.32, p = 0.016). The effect size was larger when restricting to participants who were treated with high doses of steroids while there was no evidence to support an association with the use of tocilizumab Conclusions: our study shows a high incidence of HSV-1 re-activation both virologically and clinically in patients with SARS-CoV-2 severe pneumonia, especially in those treated with steroids.

The impact of tocilizumab on respiratory support states transition and clinical outcomes in COVID-19 patients. A Markov model multi-state study.

BACKGROUND: The benefit of tocilizumab on mortality and time to recovery in people with severe COVID pneumonia may depend on appropriate timing. The objective was to estimate the impact of tocilizumab administration on switching respiratory support states, mortality and time to recovery. METHODS: In an observational study, a continuous-time Markov multi-state model was used to describe the sequence of respiratory support states including: no respiratory support (NRS), oxygen therapy (OT), non-invasive ventilation (NIV) or invasive mechanical ventilation (IMV), OT in recovery, NRS in recovery. RESULTS: Two hundred seventy-one consecutive adult patients were included in the analyses contributing to 695 transitions across states. The prevalence of patients in each respiratory support state was estimated with stack probability plots, comparing people treated with and without tocilizumab since the beginning of the OT state. A positive effect of tocilizumab on the probability of moving from the invasive and non-invasive mechanical NIV/IMV state to the OT in recovery state (HR = 2.6, 95% CI = 1.2-5.2) was observed. Furthermore, a reduced risk of death was observed in patients in NIV/IMV (HR = 0.3, 95% CI = 0.1-0.7) or in OT (HR = 0.1, 95% CI = 0.0-0.8) treated with tocilizumab. CONCLUSION: To conclude, we were able to show the positive impact of tocilizumab used in different disease stages depicted by respiratory support states. The use of the multi-state Markov model allowed to harmonize the heterogeneous mortality and recovery endpoints and summarize results with stack probability plots. This approach could inform randomized clinical trials regarding tocilizumab, support disease management and hospital decision making.

Development of post-COVID-19 cardiovascular events: an analysis of clinical features and risk factors from a single hospital retrospective study.

Cardiovascular complications after a SARS-CoV-2 infection are a phenomenon of relevant scientific interest. The aim of this study was to analyze the onset of post-COVID-19 cardiovascular events in patients hospitalized in a tertiary care center. This is a retrospective study conducted on patients hospitalized over a period of three months. The patients were older than 18 years of age and had a diagnosis of COVID-19 infection confirmed from a nasopharyngeal swab sample. Anamnestic and clinical-laboratory data were collected. Cardiovascular events at 30 days were defined as follows: arrhythmias, myocardial infarction, myocarditis, and pulmonary embolism. Univariate analysis (Student's t-test or Mann-Whitney U test, as appropriate) and multivariate analysis (multinomial logistic regression) were applied to the data. A total of 394 patients were included; they were mostly males and had a median age of 65.5 years. Previous cardiovascular disease was present in 14.7% of patients. Oxygen therapy was required for 77.9%, and 53% received anticoagulant therapy. The overall 30-day mortality was 20.3%. A cardiovascular event developed in 15.7% of the subjects. These were mainly pulmonary embolism (9.4%), followed by arrhythmias (3.3%), myocardial infarction (2.3%), and myocarditis (0.8%). Patients who developed cardiovascular events upon univariate analysis were significantly older, with major comorbidities, a more compromised respiratory situation, and a higher mortality rate. Multivariate analysis revealed independent factors that were significantly associated with the development of cardiovascular events: hypertension, endotracheal intubation, and age older than 75 years. In patients with COVID-19, the development of a cardiovascular event occurs quite frequently and is mainly seen in elderly subjects with comorbidities (especially hypertension) in the presence of a severe respiratory picture.

Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia-Challenges, strengths, and opportunities in a global health emergency.

AIMS: The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia. METHODS: This was an observational prospective study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients' medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio <150 mmHg in at least one of two consecutive arterial blood gas analyses in the following 48 hours. Shapley Additive exPlanations values were used to quantify the positive or negative impact of each variable included in each model on the predicted outcome. RESULTS: A total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth "boosted mixed model" included 20 variables was selected from the model 3, achieved the best predictive performance (AUC = 0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example. CONCLUSION: This study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels.

Tocilizumab in patients with severe COVID-19: a retrospective cohort study.

BACKGROUND: No therapy is approved for COVID-19 pneumonia. The aim of this study was to assess the role of tocilizumab in reducing the risk of invasive mechanical ventilation and death in patients with severe COVID-19 pneumonia who received standard of care treatment. METHODS: This retrospective, observational cohort study included adults (≥18 years) with severe COVID-19 pneumonia who were admitted to tertiary care centres in Bologna and Reggio Emilia, Italy, between Feb 21 and March 24, 2020, and a tertiary care centre in Modena, Italy, between Feb 21 and April 30, 2020. All patients were treated with the standard of care (ie, supplemental oxygen, hydroxychloroquine, azithromycin, antiretrovirals, and low molecular weight heparin), and a non-randomly selected subset of patients also received tocilizumab. Tocilizumab was given either intravenously at 8 mg/kg bodyweight (up to a maximum of 800 mg) in two infusions, 12 h apart, or subcutaneously at 162 mg administered in two simultaneous doses, one in each thigh (ie, 324 mg in total), when the intravenous formulation was unavailable. The primary endpoint was a composite of invasive mechanical ventilation or death. Treatment groups were compared using Kaplan-Meier curves and Cox regression analysis after adjusting for sex, age, recruiting centre, duration of symptoms, and baseline Sequential Organ Failure Assessment (SOFA) score. FINDINGS: Of 1351 patients admitted, 544 (40%) had severe COVID-19 pneumonia and were included in the study. 57 (16%) of 365 patients in the standard care group needed mechanical ventilation, compared with 33 (18%) of 179 patients treated with tocilizumab (p=0·41; 16 [18%] of 88 patients treated intravenously and 17 [19%] of 91 patients treated subcutaneously). 73 (20%) patients in the standard care group died, compared with 13 (7%; p<0·0001) patients treated with tocilizumab (six [7%] treated intravenously and seven [8%] treated subcutaneously). After adjustment for sex, age, recruiting centre, duration of symptoms, and SOFA score, tocilizumab treatment was associated with a reduced risk of invasive mechanical ventilation or death (adjusted hazard ratio 0·61, 95% CI 0·40-0·92; p=0·020). 24 (13%) of 179 patients treated with tocilizumab were diagnosed with new infections, versus 14 (4%) of 365 patients treated with standard of care alone (p<0·0001). INTERPRETATION: Treatment with tocilizumab, whether administered intravenously or subcutaneously, might reduce the risk of invasive mechanical ventilation or death in patients with severe COVID-19 pneumonia. FUNDING: None.

Pneumocystosis as a Complication of H1N1 Influenza A Infection in an HIV-Positive Patient on Effective cART.

H1N1 influenza A virus can affect the immune system, causing lymphopenia. This might be of great concern for HIV individuals undergoing effective antireroviral therapy (cART). We report the first confirmed case of H1N1-induced AIDS and Pneumocystis jiroveci pneumonia in an HIV-positive woman on effective cART since 2006.

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

BACKGROUND: The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. METHODS: A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. RESULTS: The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. CONCLUSIONS: The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of planning and, further up-stream, the management of a waiting list in an interactive and bi-directional dynamic process.

A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience.

BACKGROUND: Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i) supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii) handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii) providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration. METHODS: A dynamically extensible data structure supporting collaborative multidisciplinary research projects in neuroscience has been defined and implemented. We have considered extensibility issues from two different points of view. First, the improvement of data flexibility has been taken into account. This has been done through the development of a methodology for the dynamic creation and use of data types and related metadata, based on the definition of "meta" data model. This way, users are not constrainted to a set of predefined data and the model can be easily extensible and applicable to different contexts. Second, users have been enabled to easily customize and extend the experimental procedures in order to track each step of acquisition or analysis. This has been achieved through a process-event data structure, a multipurpose taxonomic schema composed by two generic main objects: events and processes. Then, a repository has been built based on such data model and structure, and deployed on distributed resources thanks to a Grid-based approach. Finally, data integration aspects have been addressed by providing the repository application with an efficient dynamic interface designed to enable the user to both easily query the data depending on defined datatypes and view all the data of every patient in an integrated and simple way. RESULTS: The results of our work have been twofold. First, a dynamically extensible data model has been implemented and tested based on a "meta" data-model enabling users to define their own data types independently from the application context. This data model has allowed users to dynamically include additional data types without the need of rebuilding the underlying database. Then a complex process-event data structure has been built, based on this data model, describing patient-centered diagnostic processes and merging information from data and metadata. Second, a repository implementing such a data structure has been deployed on a distributed Data Grid in order to provide scalability both in terms of data input and data storage and to exploit distributed data and computational approaches in order to share resources more efficiently. Moreover, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications. CONCLUSIONS: Based on such repository, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications.

Effect of valsartan or olmesartan addition to amlodipine on ankle edema in hypertensive patients.

INTRODUCTION: The objective of this study was to compare the effect on ankle edema of adding valsartan (V) or olmesartan (O) to amlodipine (A) in the treatment of hypertension. METHODS: After a 4-week placebo period, 74 adult outpatients with essential hypertension (diastolic blood pressure [DBP] >90 and <110 mmHg, and systolic blood pressure [SBP] >140 mmHg) were treated with A 10 mg once daily for 4 weeks. Thereafter, nonresponder patients (DBP >90 mmHg and/or SBP >140 mmHg; n=51) were randomized to receive additional V 160 mg once daily or O 20 mg once daily for 8 weeks in two crossover periods, each separated by a 4-week placebo period. Clinic blood pressure (BP), heart rate, and ankle/foot volume (AFV) were evaluated and blood samples were drawn to evaluate plasma norepinephrine (NE) levels. RESULTS: Both V/A and O/A induced a greater SBP/DBP reduction than A monotherapy (-26.4/-20.8 mmHg and -24.4/-19.1 mmHg, respectively; all P<0.001 vs. baseline and P<0.01 vs. A). A monotherapy increased AFV by 24%, P<0.001 vs. baseline, while the addition of either V or A reduced such increases. However, with V/A the AFV increase (+9.7%, P<0.05 vs. baseline, P<0.01 vs. A) was lower than with O/A (+16.7%, P<0.01 vs. baseline, P<0.05 vs. A); the difference between the two combinations was significant. Plasma NE levels were significantly increased by A (+44.6%) and values did not change with the addition of V (+35.2%) or O (+33.7%). Plasma active renin (PAR) was unchanged by A but increased by V/A (+214.4%, P<0.05 vs. baseline) and further by O/A (+325.6%, P<0.01 vs. baseline; difference between the 2 combinations: P<0.05). An inverse correlation was found between the AFV decrease and PAR increase (r=-0.31, P<0.05). CONCLUSION: Adding V or O to A reduced ankle edema, but this effect was more pronounced with V. The greater degree of renin-angiotensin system activation observed with Ocould be related to such a difference.

Effect of body weight loss and normalization on blood pressure in overweight non-obese patients with stage 1 hypertension.

We evaluated the effects of body weight (BW) loss on blood pressure (BP) in overweight non-obese patients with stage 1 hypertension. We enrolled 376 overweight (body mass index (BMI) >or=25 and <30 kg m(-2)) stage 1 hypertensive patients in this prospective 12-month trial. Each patient received tailored, low caloric dietary advice. After 6 months, patients with a BW reduction <5% were excluded. Body weight, BMI, BP, fasting plasma glucose (FPG), fasting plasma insulin (FPI), leptin (pL), renin and aldosterone levels were evaluated at baseline and after 6 and 12 months. In 222 patients who completed the study, a mean weight reduction of 8.1 kg reduced systolic blood pressure (SBP) by 4.2 mm Hg and diastolic blood pressure (DBP) by 3.3 mm Hg (P<0.05), which was accompanied by a significant decrease in FPI, pL and aldosterone levels (P<0.05). Larger SBP/DBP reductions were observed in 106 patients with normalized BMI (-5/-4.5 mm Hg, P<0.01) compared with the 116 patients who did not become normalized (-3.3/-1.6 mm Hg). The former also presented with greater decreases in FPG, FPI, pL, renin and aldosterone levels. Of the 106 patients who had normalized BMI, 52 also had normalized BP. Clinical and metabolic characteristics of these patients were similar to those of the 56 patients who did not have normalized BP. In overweight, mild hypertensive patients, weight loss was effective in reducing BP and in reversing some endocrinologic alterations associated with being overweight. Half of the patients who had normalized BMI also had normalized BP, which could indicate that these patients essentially did not have a form of hypertension but that these effects were instead secondary to being overweight.

Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up data.

BACKGROUND: Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression data and clinico-pathological data through a combination of available and newly developed processing tools. RESULTS: We developed Survival Online (available at http://ada.dist.unige.it:8080/enginframe/bioinf/bioinf.xml), a Web-based system that allows for the analysis of Affymetrix GeneChip microarrays by using a parallel version of dChip. The user is first enabled to select pre-loaded datasets or single samples thereof, as well as single genes or lists of genes. Expression values of selected genes are then correlated with sample annotation data by uni- or multi-variate Cox regression and survival analyses. The system was tested using publicly available breast cancer datasets and GO (Gene Ontology) derived gene lists or single genes for survival analyses. CONCLUSION: The system can be used by bio-medical researchers without specific computation skills to validate potential biomarkers or multi-gene classifiers. The design of the service, the parallelization of pre-processing tasks and the implementation on an HPC (High Performance Computing) environment make this system a useful tool for validation on several independent datasets.

XTENS - an eXTensible environment for neuroscience.

The XTENS (eXTensible Environment for NeuroScience) platform consists in an highly extensible environment for collaborative work that improve repeatability of experiment and provides data storage and analysis capabilities. The platform is divided in repository and application domains, branched in services with different purpose. The first domain is the central component of the platform and consists in a multimodal repository with a client-server architecture. The second one provides remote tools for image and signal visualization and analysis. The main issue for such a platform is not only to provide an extensible collaborative environment, but also to build a development platform for testing models and algorithms in neuroscience. For these reasons a Grid approach has been considered. Both computational and data Grids infrastructures can be exploited to analyze and share large datasets of distributed data. The architecture has been deployed to support surgical planning for patients affected by drug resistant epilepsy. In that scenario, a complex analysis for a fully multimodal dataset including different image modalities, EEG and video is required to localize the origin of the ictal discharge and critical brain areas. As first results, prototype versions of both repository and application domain components are presented.

Efficacy and safety of two treatment combinations of hypertension in very elderly patients.

The study compared valsartan/amlodipine combination with irbesartan/hydrochlorothiazide (HCTZ) combination in very elderly hypertensives. After a 4-week placebo period, 94 hypertensives, aged 75-89 years were randomized to valsartan 160mg/amlodipine 5mg or irbesartan 300mg/HCTZ 12.5mg for 24 weeks according to a prospective, parallel group study. After 4 weeks amlodipine or HCTZ was doubled in non-responders. Patients were checked every 4 weeks. At each visit clinical sitting, lying and standing blood pressure (BP), systolic BP (SBP) and diastolic BP (DBP) were evaluated, and an electrocardiogram was performed. At the end of the placebo period and of the treatment period a non-invasive 24-h ambulatory BP monitoring (ABPM) was performed and electrolytes and uric acid were evaluated. Both combinations significantly reduced ambulatory BP. In the valsartan/amlodipine group the mean reduction (-29.9/-15.6 for 24h, -28.6/-14.5mmHg for day-time and -26.2/-17.4mmHg for night-time SBP/DBP) was similar to that of the irbesartan/HCTZ group (-29.6/-15.4 for 24h, -29.3/-14.9mmHg for day-time and -25.4/-16.9mmHg for night-time SBP/DBP). Both combinations significantly reduced clinical sitting and lying BP values with no difference between treatments. BP changes from lying to standing position were significantly greater in the irbesartan/HCTZ group (-17.2/-9.1mmHg) than in the valsartan/amlodipine group (-10.1/-1.9mmHg, p<0.05 for SBP and p<0.01 for DBP vs. irbesartan/HCTZ). Potassium significantly decreased and uric acid significantly increased (-0.4mmol/l, p<0.05 and +0.5mg/dl, p<0.05 vs. baseline, respectively) only in the irbesartan/HCTZ group. In conclusion, both combinations were similarly effective in reducing ambulatory and clinical BP in very elderly hypertensives. However, valsartan/amlodipine offered some advantages in terms of less pronounced BP orthostatic changes and absence of metabolic adverse effects.

Effect of valsartan addition to amlodipine on insulin sensitivity in overweight-obese hypertensive patients.

OBJECTIVE: The aim of the study was to evaluate the effect of valsartan/amlodipine combination on insulin sensitivity in overweight-obese hypertensive patients. METHODS: After a 4-week placebo period, 58 overweight-obese (BMI >or=25 kg/m(2)) patients, with mild to moderate essential hypertension (DBP >95 and <110 mmHg, SBP >140 mmHg) were treated with amlodipine 5 mg od or valsartan 160 mg od or amlodipine 5 mg plus valsartan 160 mg od for 8 weeks according to a randomized, open-label, blinded end-point, cross-over study. At the end of the placebo period and each treatment period, blood pressure (BP) and insulin sensitivity (IS) (by euglycemic hyperinsulinemic clamp technique) were evaluated. IS was expressed as the amount of glucose infused during the last 30 min (glucose infusion rate, GIR) in mg/kg/min. RESULTS: Valsartan/amlodipine combination produced a significantly greater decrease in SBP/DBP values (-22.3/16.7 mmHg, p<0.001 vs baseline) than valsartan (-15.2/11.7 mmHg, p<0.01 vs baseline) and amlodipine monotherapy (-16.1/12.6 mmHg, p<0.01 vs baseline). Both valsartan and amlodipine provided a significant increase in GIR (+1.24 mg/kg/min, p=0.036 vs baseline and +1.02 mg/kg/min, p=0.047, respectively), but such an increase was significantly greater with their combination (+1.82 mg/kg/min, p<0.01 vs baseline). These greater changes in IS were not related to BP changes. CONCLUSION: Valsartan/amlodipine combination improved IS more than respective monotherapy beyond affording greater BP reductions. This strengthens the rationale to use valsartan/amlodipine combination in the treatment of overweight-obese hypertensives.

A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data.

BACKGROUND: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible for serious diseases, with a great scientific impact and a wide application area. Several standalone applications had been developed in order to analyze microarray data. Two of the most known free analysis software packages are the R-based Bioconductor and dChip. The part of dChip software concerning the calculation and the analysis of gene expression has been modified to permit its execution on both cluster environments (supercomputers) and Grid infrastructures (distributed computing).This work is not aimed at replacing existing tools, but it provides researchers with a method to analyze large datasets without any hardware or software constraints. RESULTS: An application able to perform the computation and the analysis of gene expression on large datasets has been developed using algorithms provided by dChip. Different tests have been carried out in order to validate the results and to compare the performances obtained on different infrastructures. Validation tests have been performed using a small dataset related to the comparison of HUVEC (Human Umbilical Vein Endothelial Cells) and Fibroblasts, derived from same donors, treated with IFN-alpha.Moreover performance tests have been executed just to compare performances on different environments using a large dataset including about 1000 samples related to Breast Cancer patients. CONCLUSION: A Grid-enabled software application for the analysis of large Microarray datasets has been proposed. DChip software has been ported on Linux platform and modified, using appropriate parallelization strategies, to permit its execution on both cluster environments and Grid infrastructures. The added value provided by the use of Grid technologies is the possibility to exploit both computational and data Grid infrastructures to analyze large datasets of distributed data. The software has been validated and performances on cluster and Grid environments have been compared obtaining quite good scalability results.

Effect of valsartan and ramipril on atrial fibrillation recurrence and P-wave dispersion in hypertensive patients with recurrent symptomatic lone atrial fibrillation.

BACKGROUND: This study compared the effect of antihypertensive treatment with valsartan or ramipril on atrial fibrillation (AF) recurrence, on P-wave dispersion, (PWD) and on serum procollagen type I carboxy terminal peptide (PIP). METHODS: A total of 369 mild hypertensive (systolic blood pressure (SBP) >140 and/or 90 < diastolic blood pressure (DBP) < 110 mm Hg) outpatients in sinus rhythm but with at least two episodes of AF in the previous 6 months were randomized to valsartan (n = 122), ramipril (n = 124), or amlodipine (n = 123) for 1 year. Clinic blood pressure (BP) and a 24-h electrocardiogram (ECG) were evaluated monthly. Patients were asked to report any episode of symptomatic AF and to perform an ECG as early as possible. PWD and serum PIP levels were evaluated before and after each treatment period. RESULTS: SBP and DBP were significantly reduced by the three treatments (P < 0.001). A total of 46 (47.4%) patients treated with amlodipine had a recurrence of AF as did 26 (27.9%) patients treated with ramipril (P < 0.01 vs. amlodipine) and 16 (16.1%) patients treated with valsartan (P < 0.01 vs. amlodipine and P < 0.05 vs. ramipril). The Kaplan-Meyer analysis showed a significant reduction of AF episodes in the valsartan group (P = 0.005 log-rank test) as well as in the ramipril group (P = 0.021), even if at a lesser degree. PWD values were significantly reduced by ramipril (-4.2 ms, P < 0.05) and even more by valsartan (-11.2 ms, P < 0.01), the difference being significant (P < 0.01). Serum PIP levels were reduced by ramipril (-49.7 microg, P < 0.001) and valsartan (-49.3 microg, P < 0.001). CONCLUSIONS: Despite similar BP lowering, valsartan and ramipril were more effective than amlodipine in preventing new episodes of AF, but the effect of valsartan was greater than that of ramipril. This could be related to the greater PWD reduction observed with valsartan.

Comparative evaluation of effect of valsartan/amlodipine and atenolol/amlodipine combinations on atrial fibrillation recurrence in hypertensive patients with type 2 diabetes mellitus.

The aim of this study was to compare the effect of valsartan/amlodipine and atenolol/amlodipine combination in preventing the recurrence of atrial fibrillation (AF) in hypertensive diabetic patients with a history of recent paroxysmal atrial fibrillation. Two hundred ninety-six hypertensive patients with well-controlled type 2 diabetes in sinus rhythm but with at least 2 ECG-documented episodes of AF in the previous 6 months were randomized to 160 mg of valsartan plus amlodipine (titrated from 2.5 to 10 mg) or to 100 mg of atenolol plus amlodipine (2.5 to 10 mg) in addition to their previous antiarrhythmic treatment (if any) and were followed up for 1 year. Blood pressure (BP) and a 24-hour ECG were evaluated monthly. The patients were asked to report any episode of symptomatic AF and to perform an ECG as early as possible. SBP/DBP values were significantly reduced after 12 months with valsartan/amlodipine (from 150.4/93.5 to 126.37/7.4 mm Hg, P < 0.001) and atenolol/amlodipine (from 151.1/94.2 to 127.1/77.9 mm Hg, P < 0.001), with no difference between the 2 regimens. At least 1 ECG-documented episode of AF was reported in 20.3% of the patients treated with valsartan/amlodipine and in 34.1% of those treated with atenolol/amlodipine, with a significant difference between treatments (P < 0.01). The positive effect of valsartan/amlodipine combination on AF recurrence was more evident in patients treated with amiodarone or propafenone than in patients treated with other antiarrhythmic drugs or without antiarrhythmic treatment. Despite similar BP reduction, valsartan/amlodipine combination was more effective in patients treated with amiodarone or propafenone than atenolol/amlodipine in preventing new episodes of AF in hypertensive diabetic patients.

Effect of delapril/manidipine vs olmesartan/ hydrochlorothiazide combination on insulin sensitivity and fibrinogen in obese hypertensive patients.

OBJECTIVE: To compare the effect of delapril/manidipine vs olmesartan/hydrochlorothiazide (HCTZ) combination on insulin sensitivity and plasma fibrinogen in obese hypertensive patients. PATIENTS AND METHODS: After a 4-week placebo period, 88 obese, hypertensive (DBP >95 and <110 mmHg) outpatients were randomized to delapril 30 mg/manidipine 10 mg combination or to olmesartan 20 mg/HCTZ 12.5 mg combination for 24 weeks according to a prospective, randomized, open-label, blinded endpoint, parallel group design. At the end of the placebo period and treatment period, clinical BP, fasting plasma glucose (FPG), plasma insulin, insulin sensitivity (by euglycemic hyperinsulinemic clamp) and plasma fibrinogen were evaluated. Insulin sensitivity was expressed as the amount of glucose infused during the last 30 minutes (glucose infusion rate, GIR) in mg/Kg/min. The total glucose requirement (TGR) to maintain a steady-state blood glucose level in response to a defined increase in plasma insulin concentration was also evaluated. RESULTS: Both combinations significantly reduced SBP/DBP values (-22.3/16.4 mmHg and -22.6/17.2 mmHg, respectively, all p <0.001 vs placebo). GIR was significantly increased only by delapril/manidipine (+3.01 mg/min/Kg, p=0.038 vs placebo), the difference between treatments being significant (p <0.05). TGR was significantly increased by delapril/manidipine (+9.7 g, p=0.034), while it was unaffected by olmesartan/HCTZ. Plasma insulin as well as fibrinogen were significantly reduced by delapril/manidipine (-17.8 pmol/l, p=0.047 and -67.5 mg/dl, p=0.021, respectively), but not by olmesartan/HCTZ, the difference between the two treatments being statistically significant (p <0.05). CONCLUSION: In obese hypertensive patients the delapril/manidipine combination but not the olmesartan/HCTZ combination significantly decreased insulin resistance and plasma fibrinogen levels, despite the similar BP lowering efficacy.

Addition of manidipine improves the antiproteinuric effect of candesartan in hypertensive patients with type II diabetes and microalbuminuria.

BACKGROUND: We sought to compare the effect of manidipine versus hydrochlorothiazide (HCTZ) in addition to candesartan on the urinary albumin excretion rate (UAER) in hypertensive patients with type II diabetes and microalbuminuria. METHODS: After a 2-week washout and run-in period, and 8-week monotherapy with candesartan 16 mg every day, 174 microalbuminuric diabetic hypertensive patients with uncontrolled blood pressure (BP) (>130/80 mm Hg) were randomized to addition of manidipine 10 mg every day (n = 87) or HCTZ 12.5 mg every day (n = 87) for 24 weeks, with a titration after 4 weeks (manidipine or HCTZ dose-doubling) in nonresponder patients. Blood pressure, UAER, creatinine clearance, serum electrolytes, fasting plasma glycemia, and glycosylated hemoglobin were evaluated at baseline (end of run-in period), after candesartan monotherapy, and at the end of the combination treatment period. RESULTS: Both combinations produced greater systolic BP/diastolic BP reduction than candesartan monotherapy (-28/21 mm Hg versus -16/11 mm Hg and -28/20 mm Hg versus -15/11 mm Hg, respectively; all P < .05 versus monotherapy), with no significant difference between the two combinations. The addition of manidipine produced a greater reduction in UAER than candesartan monotherapy (-55.4 mg/24 h v -36.1 mg/24 h, P < .05), whereas the addition of HCTZ did not significantly modify UAER; the difference between the two combinations was statistically significant (P < .05). Similarly, the percentage of patients moving to a normoalbuminuric state (UAER <30 mg/24 h) was increased by the addition of manidipine to candesartan (from 35% to 64%, P < .05), but not by the addition of HCTZ (from 34% to 39%, NS), with a statistical difference between the two combinations (P < .05). CONCLUSIONS: These findings show that, despite equivalent reduction in BP, the addition of manidipine to candesartan further reduced the UAER, whereas the addition of HCTZ did not modify the UAER. This suggests that the antiproteinuric effect of manidipine is partially independent of BP reduction, and is attributable to mechanisms different from those mediated by angiotensin receptor blockade.

A Grid-based solution for management and analysis of microarrays in distributed experiments.

Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of uploading and accessing distributed datasets through the Grid middleware and against its ability in managing the execution of jobs on distributed computational resources. Results from the Grid test will be discussed in a further paper.