Effect of byrosima crassa and phenolic constituents on helicobacter pylori: induced neutrophils oxdative burst

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudos biológicos de nanopartículas de óxido de zinco: interação com proteínas e avaliação de “Burst” oxidativo de leucócitos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analgesic effects of repetitive transcranial magnetic stimulation of the motor cortex in neuropathic pain: Influence of theta burst stimulation priming

Background Conventional protocols of high-frequency repetitive transcranial magnetic stimulation (rTMS) delivered to M1 can produce analgesia. Theta burst stimulation (TBS), a novel rTMS paradigm, is thought to produce greater changes in M1 excitability than conventional protocols. After a preliminary experiment showing no analgesic effect of continuous or intermittent TBS trains (cTBS or iTBS) delivered to M1 as single procedures, we used TBS to prime a subsequent session of conventional 10?Hz-rTMS. Methods In 14 patients with chronic refractory neuropathic pain, navigated rTMS was targeted over M1 hand region, contralateral to painful side. Analgesic effects were daily assessed on a visual analogue scale for the week after each 10?Hz-rTMS session, preceded or not by TBS priming. In an additional experiment, the effects on cortical excitability parameters provided by single- and paired-pulse TMS paradigms were studied. Results Pain level was reduced after any type of rTMS procedure compared to baseline, but iTBS priming produced greater analgesia than the other protocols. Regarding motor cortex excitability changes, the analgesic effects were associated with an increase in intracortical inhibition, whatever the type of stimulation, primed or non-primed. Conclusions The present results show that the analgesic effects of conventional 10?Hz-rTMS delivered to M1 can be enhanced by TBS priming, at least using iTBS. Interestingly, the application of cTBS and iTBS did not produce opposite modulations, unlike previously reported in other systems. It remains to be determined whether the interest of TBS priming is to generate a simple additive effect or a more specific process of cortical plasticity.

Effect of Byrsonima crassa and Phenolic Constituents on Helicobacter pylori-Induced Neutrophils Oxidative Burst

Byrsonima crassa Niedenzu (Malpighiaceae) is used in Brazilian folk medicine for the treatment of diseases related mainly to gastric ulcers. In a previous study, our group described the gastric protective effect of the methanolic extract from the leaves of B. crassa. The present study was carried out to investigate the effects of methanolic extract and its phenolic compounds on the respiratory burst of neutrophils stimulated by H. pylori using a luminol-based chemiluminescence assay as well as their anti-H. pylori activity. The suppressive activity on oxidative burst of H. pylori-stimulated neutrophils was in the order of methyl gallate > (+)-catechin > methanol extract > quercetin 3-O-alpha-L-arabinopyranoside > quercetin 3-O-beta-D-galactopyranoside > amentoflavone. Methyl gallate, compound that induced the highest suppressive activity with IC50 value of 3.4 mu g/mL, did not show anti-H. pylori activity. B. crassa could be considered as a potential source of natural antioxidant in gastric ulcers by attenuating the effects on the damage to gastric mucosa caused by neutrophil generated reactive oxygen species, even when H. pylori displays its evasion mechanisms.

Progettazione di un sistema di Social Intelligence e Sentiment Analysis per un'azienda del settore consumer goods

Progettazione di un sistema di Social Intelligence e Sentiment Analysis per un'azienda del settore consumer goods

Sentiment analysis in Twitter

Gli ultimi anni hanno visto una crescita esponenziale nell’uso dei social media (recensioni, forum, discussioni, blog e social network); le persone e le aziende utilizzano sempre più le informazioni (opinioni e preferenze) pubblicate in questi mezzi per il loro processo decisionale. Tuttavia, il monitoraggio e la ricerca di opinioni sul Web da parte di un utente o azienda risulta essere un problema molto arduo a causa della proliferazione di migliaia di siti; in più ogni sito contiene un enorme volume di testo non sempre decifrabile in maniera ottimale (pensiamo ai lunghi messaggi di forum e blog). Inoltre, è anche noto che l’analisi soggettiva delle informazioni testuali è passibile di notevoli distorsioni, ad esempio, le persone tendono a prestare maggiore attenzione e interesse alle opinioni che risultano coerenti alle proprie attitudini e preferenze. Risulta quindi necessario l’utilizzo di sistemi automatizzati di Opinion Mining, per superare pregiudizi soggettivi e limitazioni mentali, al fine di giungere ad una metodologia di Sentiment Analysis il più possibile oggettiva.

Entity extraction e text classification come strumenti per la sentiment analysis di testi giornalistici

In this thesis we are going to talk about technologies which allow us to approach sentiment analysis on newspapers articles. The final goal of this work is to help social scholars to do content analysis on big corpora of texts in a faster way thanks to the support of automatic text classification.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Elaborazione del linguaggio naturale nell'IA e tecnologie moderne: Sentiment Analysis come caso di studio.

L'informatica e le sue tecnologie nella società moderna si riassumono spesso in un assioma fuorviante: essa, infatti, è comunemente legata al concetto che ciò che le tecnologie ci offrono può essere accessibile da tutti e sfruttato, all'interno della propria quotidianità, in modi più o meno semplici. Anche se quello appena descritto è un obiettivo fondamentale del mondo high-tech, occorre chiarire subito una questione: l'informatica non è semplicemente tutto ciò che le tecnologie ci offrono, perchè questo pensiero sommario fa presagire ad un'informatica "generalizzante"; l'informatica invece si divide tra molteplici ambiti, toccando diversi mondi inter-disciplinari. L'importanza di queste tecnologie nella società moderna deve spingerci a porre domande, riflessioni sul perchè l'informatica, in tutte le sue sfaccettature, negli ultimi decenni, ha portato una vera e propria rivoluzione nelle nostre vite, nelle nostre abitudini, e non di meno importanza, nel nostro contesto lavorativo e aziendale, e non ha alcuna intenzione (per fortuna) di fermare le proprie possibilità di sviluppo. In questo trattato ci occuperemo di definire una particolare tecnica moderna relativa a una parte di quel mondo complesso che viene definito come "Intelligenza Artificiale". L'intelligenza Artificiale (IA) è una scienza che si è sviluppata proprio con il progresso tecnologico e dei suoi potenti strumenti, che non sono solo informatici, ma soprattutto teorico-matematici (probabilistici) e anche inerenti l'ambito Elettronico-TLC (basti pensare alla Robotica): ecco l'interdisciplinarità. Concetto che è fondamentale per poi affrontare il nocciolo del percorso presentato nel secondo capitolo del documento proposto: i due approcci possibili, semantico e probabilistico, verso l'elaborazione del linguaggio naturale(NLP), branca fondamentale di IA. Per quanto darò un buono spazio nella tesi a come le tecniche di NLP semantiche e statistiche si siano sviluppate nel tempo, verrà prestata attenzione soprattutto ai concetti fondamentali di questi ambiti, perché, come già detto sopra, anche se è fondamentale farsi delle basi e conoscere l'evoluzione di queste tecnologie nel tempo, l'obiettivo è quello a un certo punto di staccarsi e studiare il livello tecnologico moderno inerenti a questo mondo, con uno sguardo anche al domani: in questo caso, la Sentiment Analysis (capitolo 3). Sentiment Analysis (SA) è una tecnica di NLP che si sta definendo proprio ai giorni nostri, tecnica che si è sviluppata soprattutto in relazione all'esplosione del fenomeno Social Network, che viviamo e "tocchiamo" costantemente. L'approfondimento centrale della tesi verterà sulla presentazione di alcuni esempi moderni e modelli di SA che riguardano entrambi gli approcci (statistico e semantico), con particolare attenzione a modelli di SA che sono stati proposti per Twitter in questi ultimi anni, valutando quali sono gli scenari che propone questa tecnica moderna, e a quali conseguenze contestuali (e non) potrebbe portare questa particolare tecnica.

Interference with gesture production by theta burst stimulation over left inferior frontal cortex

The traditional view of a predominant inferior parietal representation of gestures has been recently challenged by neuroimaging studies demonstrating that gesture production and discrimination may critically depend on inferior frontal lobe function. The aim of the present work was therefore to investigate the effect of transient disruption of these brain sites by continuous theta burst stimulation (cTBS) on gesture production and recognition.

Theta Burst Stimulation Over the Right Broca's Homologue Induces Improvement of Naming in Aphasic Patients

Improvements of language production in aphasic patients have been reported following repeated 1-Hz transcranial magnetic stimulation over the nondamaged right hemisphere. Most studies examined aphasic patients in the chronic phase. The effect of transcranial magnetic stimulation application in acute or subacute patients has not been systematically studied. We aimed to evaluate whether continuous theta burst stimulation, an inhibitory protocol with a shorter application time than the common 1-Hz protocol, is able to improve naming performance in aphasic patients in different poststroke phases.

Theta burst TMS increases cerebral blood flow in the primary motor cortex during motor performance as assessed by arterial spin labeling (ASL)

Theta burst stimulation (TBS) is a novel variant of repetitive transcranial magnetic stimulation (rTMS), which induces changes in neuronal excitability persisting up to 1h. When elicited in the primary motor cortex, such physiological modulations might also have an impact on motor behavior. In the present study, we applied TBS in combination with pseudo continuous arterial spin labeling (pCASL) in order to address the question of whether TBS effects are measurable by means of changes in physiological parameters such as cerebral blood flow (CBF) and if TBS-induced plasticity can modify motor behavior. Twelve right-handed healthy subjects were stimulated using an inhibitory TBS protocol at subthreshold stimulation intensity targeted over the right motor cortex. The control condition consisted of within-subject Sham treatment in a crossover design. PCASL was performed before (pre TBS/pre Sham) and immediately after treatment (post TBS/post Sham). During the pCASL runs, the subjects performed a sequential fingertapping task with the left hand at individual maximum speed. There was a significant increase of CBF in the primary motor cortex after TBS, but not after Sham. It is assumed that inhibitory TBS induced a "local virtual lesion" which leads to the mobilization of more neuronal resources. There was no TBS-specific modulation in motor behavior, which might indicate that acute changes in brain plasticity caused by TBS are immediately compensated. This compensatory reaction seems to be observable at the metabolic, but not at the behavioral level.

Theta burst stimulation reduces disability during the activities of daily living in spatial neglect

Left-sided spatial neglect is a common neurological syndrome following right-hemispheric stroke. The presence of spatial neglect is a powerful predictor of poor rehabilitation outcome. In one influential account of spatial neglect, interhemispheric inhibition is impaired and leads to a pathological hyperactivity in the contralesional hemisphere, resulting in a biased attentional allocation towards the right hemifield. Inhibitory transcranial magnetic stimulation can reduce the hyperactivity of the contralesional, intact hemisphere and thereby improve spatial neglect symptoms. However, it is not known whether this improvement is also relevant to the activities of daily living during spontaneous behaviour. The primary aim of the present study was to investigate whether the repeated application of continuous theta burst stimulation trains could ameliorate spatial neglect on a quantitative measure of the activities of daily living during spontaneous behaviour. We applied the Catherine Bergego Scale, a standardized observation questionnaire that can validly and reliably detect the presence and severity of spatial neglect during the activities of daily living. Eight trains of continuous theta burst stimulation were applied over two consecutive days on the contralesional, left posterior parietal cortex in patients suffering from subacute left spatial neglect, in a randomized, double-blind, sham-controlled design, which also included a control group of neglect patients without stimulation. The results showed a 37% improvement in the spontaneous everyday behaviour of the neglect patients after the repeated application of continuous theta burst stimulation. Remarkably, the improvement persisted for at least 3 weeks after stimulation. The amelioration of spatial neglect symptoms in the activities of daily living was also generally accompanied by significantly better performance in the neuropsychological tests. No significant amelioration in symptoms was observed after sham stimulation or in the control group without stimulation. These results provide Class I evidence that continuous theta burst stimulation is a viable add-on therapy in neglect rehabilitation that facilitates recovery of normal everyday behaviour.