Combination therapy with aliskiren versus ramipril or losartan added to conventional therapy in patients with type 2 diabetes mellitus, uncontrolled hypertension and microalbuminuria.

Hypothesis/Introduction: The aim of this study was to assess the antihypertensive efficacy and safety of aliskiren versus ramipril or losartan in hypertensive patients with type 2 diabetes mellitus, microalbuminuria and uncontrolled hypertension, despite the use of optimal conventional antihypertensive therapy. Materials and methods: In this open-label active comparator study, 126 patients were randomly assigned to receive 24 weeks of additional therapy with aliskiren (Group A) or either losartan or ramipril (Group B), according to whether a patient was already treated with an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker, respectively. Results: After 24 weeks, both treatment groups experienced a significant reduction of systolic blood pressure (−11.37% and −8.47%, respectively; both p <0.001 vs . baseline) and diastolic blood pressure levels (−10.67% and −9.28%, respectively; both p <0.001 vs . baseline), with a greater reduction of mean systolic values in Group A compared with Group B ( p <0.001). Furthermore, after six months microalbuminuria was significantly decreased in both treatment groups (−67.62% and −49.1%, respectively; both p <0.001), with a reduction rate in Group A significantly higher than in Group B ( p <0.001). Conclusions: The addition of aliskiren to optimal conventional therapy provided a higher reduction of blood pressure and urinary albumin excretion when compared with the addition of losartan or ramipril

Automatic crack classification by exploiting statistical event descriptors for Deep Learning

In modern building infrastructures, the chance to devise adaptive and unsupervised data-driven health monitoring systems is gaining in popularity due to the large availability of big data from low-cost sensors with communication capabilities and advanced modeling tools such as Deep Learning. The main purpose of this paper is to combine deep neural networks with Bidirectional Long Short Term Memory and advanced statistical analysis involving Instantaneous Frequency and Spectral Kurtosis to develop an accurate classification tool for tensile, shear and mixed modes originated from acoustic emission events (cracks). We investigated on effective event descriptors to capture the unique characteristics from the different types of modes. Tests on experimental results confirm that this method achieves promising classification among different crack events and can impact on the design of future on structural health monitoring (SHM) technologies. This approach is effective to classify incipient damages with 92% of accuracy, which is advantageous to plan maintenance.Comment: 19 pages, 2 tables, 9 figure

The trafficking of natural killer cells.

International audienceNatural killer (NK) cells are large granular lymphocytes of the innate immune system that participate in the early control of microbial infections and cancer. NK cells can induce the death of autologous cells undergoing various forms of stress, recognizing and providing non-microbial 'danger' signals to the immune system. NK cells are widely distributed in lymphoid and non-lymphoid organs. NK cell precursors originate from the bone marrow and go through a complex maturation process that leads to the acquisition of their effector functions, to changes in their expression of integrins and chemotactic receptors, and to their redistribution from the bone marrow and lymph nodes to blood, spleen, liver, and lung. Here, we describe the tissue localization of NK cells, using NKp46 as an NK cell marker, and review the current knowledge on the mechanisms that govern their trafficking in humans and in mice

Impaired emotion recognition is linked to alexithymia in heroin addicts

Several investigations document altered emotion processing in opiate addiction. Nevertheless, the origin of this phenomenon remains unclear. Here we examined the role of alexithymia in the ability (i.e., number of errors—accuracy and reaction times—RTs) of thirty-one heroin addicts and thirty-one healthy controls to detect several affective expressions. Results show generally lower accuracy and higher RTs in the recognition of facial expressions of emotions for patients, compared to controls. The hierarchical multivariate regression analysis shows that alexithymia might be responsible of the between groups difference with respect to the RTs in emotion detection. Overall, we provide new insights in the clinical interpretation of affective deficits in heroin addicts suggesting a role of alexithymia in their ability to recognize emotions

Automatic Crack Classification by Exploiting Statistical Event Descriptors for Deep Learning

In modern building infrastructures, the chance to devise adaptive and unsupervised data-driven structural health monitoring (SHM) systems is gaining in popularity. This is due to the large availability of big data from low-cost sensors with communication capabilities and advanced modeling tools such as deep learning. A promising method suitable for smart SHM is the analysis of acoustic emissions (AEs), i.e., ultrasonic waves generated by internal ruptures of the concrete when it is stressed. The advantage in respect to traditional ultrasonic measurement methods is the absence of the emitter and the suitability to implement continuous monitoring. The main purpose of this paper is to combine deep neural networks with bidirectional long short term memory and advanced statistical analysis involving instantaneous frequency and spectral kurtosis to develop an accurate classification tool for tensile, shear and mixed modes originated from AE events (cracks). We investigated effective event descriptors to capture the unique characteristics from the different types of modes. Tests on experimental results confirm that this method achieves promising classification among different crack events and can impact on the design of the future of SHM technologies. This approach is effective to classify incipient damages with 92% of accuracy, which is advantageous to plan maintenance

Cyberknife for meningiomas: new treatment paradigms

INTRODUZIONE: Stereotactic radiosurgery has progressively emerged as both an adjuvant treatment modality for residual tumors and an effective primary treatment of properly selected meningiomas. Frameless radiosurgery enabled the use of \u201cmulti-session\u201d radiosurgery (2-5 fractions) and hypofractionated stereotactic radiotherapy (hFSR). This has expanded the spectrum of tumors that can be managed by high-doses, high-conformality radiotherapy treatments. OBIETTIVI: We reviewed our series of meningiomas treated with CyberKnife (CK) radiosurgery reporting internmediate-term results. We also propose a classification of meningiomas in the light of technical requirements, complications and clinical results using the CK SRS system. MATERIALI E METODI: Between July 2007 and March 2015, 238 patients with meningiomas were treated by CK at the University of Messina (Italy). All patients had either evidence of tumor growth or post-surgery residual or recurrent tumor. On the basis of technical requirements, including doses and number of fractions, risk of radio-induced complications, probability of tumor control we divided meningiomas in 6 categories: 1) perioptic meningiomas that included tumors lying &lt;2 mm from the optic nerves and chiasm; 2) skull base meningiomas including tumors involving the anterior, middle and posterior skull base; 3) parasagittal and convexity meningiomas; 4) large meningiomas, namely tumors with a volume &gt;50 cc; 5) malignant meningiomas including atypical and anaplastic tumors; 6) spinal meningiomas. RISULTATI E CONCLUSIONI: At a median follow up of 45 months, the tumor control was 94% for benign lesions; shrinkage was recorded in 35%. Six percent of patients underwent surgery because of tumor progression or symptomatic edema. Three percent of tumor progressed. Seven cases of transient trigeminal neuralgia were recorded in middle fossa or petrosal meningiomas. 1) for perioptic meningiomas we calculated, using radiobiological models, that a BED of 100 Gy was necessary to control progression and a 10% dose gradient to avoid hazardous irradiation of the optic nerve. This was possible with 5 fractions in presence of minimal distance between the tumor and the nerve; up to 15 fractions were used in other cases. No radioinduced optic neuropathy was recorded in 67 patients. 2) Skull base meningiomas (85 patients). The extra-arachnoidal localization of these tumors and the use of hypofractionation granted the avoidance of brain complication and injuries of the cranial nerves, even in large tumors. 3) Parasagittal and convexity meningiomas were associated to a higher risk of radio-induced symptomatic post-treatment edema (6 of 56 patients). Neither fractionation, nor staging was sufficient to avoid complications. The difference with basal meningiomas could be attributed to the absence of brain tumor arachnoid interface. 4) Large meningiomas (&gt;50 cc) were treated using 10-15 fractions. This CK hFSR resulted in a treatment with a high BED and a relatively high conformality representing an attractive alternative to other 3D radiotherapy treatments definitely less conformal. 5) Atypical/Malignant meningiomas (21 patients) were treated with high doses (24-30 Gy in 3 fractions) for large volumes (40-70 cc). Results were unsatisfactory, with only 20% progression-free at 2 years. 6) Spinal meningiomas (4 patients): radiosurgery was used for recurrent tumors. Satisfactory results were obtained with low doses (18 Gy in 3 fractions); no radio-induced complications were recorded to date. With fractionation, we could manage lesions not amenable to single-fraction radiosurgery, including tumors compressing or even encasing the optic nerves, brainstem and cranial nerves, very large tumors, and spinal meningiomas. The treatment of these lesions appeared possible using BED values that are not dissimilar from those of single fraction radiosurgery. Complication rates at short term were satisfactory. Finally, we used such innovative approaches to treatment to classify tumors under a radiosurgical perspective

Type I IFN signaling is crucial for host resistance against different species of pathogenic bacteria

It is known that host cells can produce type I IFNs (IFN-alpha beta) after exposure to conserved bacterial products, but the functional consequences of such responses on the outcome of bacterial infections are incompletely understood. We show in this study that IFN-alpha beta signaling is crucial for host defenses against different bacteria, including group B streptococci (GBS), pneumococci, and Escherichia coli. In response to GBS challenge, most mice lacking either the IFN-alpha beta R or IFN-beta died from unrestrained bacteremia, whereas all wild-type controls survived. The effect of IFN-alpha beta R deficiency was marked, with mortality surpassing that seen in IFN-gamma R-deficient mice. Animals lacking both IFN-alpha beta R and IFN-gamma R displayed additive lethality, suggesting that the two IFN types have complementary and nonredundant roles in host defenses. Increased procluction of IFN-alpha beta was detected in macrophages after exposure to GBS. Moreover, in the absence of IFN-alpha beta signaling, a marked reduction in macrophage production of IFN-gamma, NO, and TNF-alpha was observed after stimulation with live bacteria or with purified LPS. Collectively, our data document a novel, fundamental function of IFN-alpha beta in boosting macrophage responses and host resistance against bacterial pathogens. These data may be useful to devise alternative strategies to treat bacterial infections