Cercetatorii au identificat 281 de markeri genetici asociati cu longevitatea, dupa ce au examinat un grup de 800 de persoane cu o medie de vârsta de 104 ani, comparând apoi genele acestora cu un grup de persoane din toate grupele de vârsta.

Multe dintre persoanele studiate cu o vârsta de peste 100 de ani atinsesera aceasta etate în ciuda unui stil de viata nesanatos. De aceea, cercetatorii de la Boston School of Medicine au concluzionat ca aceste gene au un efect mai puternic asupra longevitatii decât stilul de viata nesanatos.

Folosind doar datele genetice, cercetatorii au reusit sa prezica cu o acuratete de 71% persoanele din grup care au atins vârsta de 102 ani si cu o acuratete de 85% care sunt persoanele care au atins vârsta de 105 ani.

Profesorul Thomas Perls, conducatorul studiului, a declarat ca "multe dintre genele identificate de studiul nostru erau deja asociate de cercetari precedente unor boli precum Alzheimer, afectiuni cardiovasculare, diabet si leziunilor provocate de radicalii liberi, toate acestea fiind afectiuni specifice vârstei a treia. Acest lucru este foarte interesant, pentru ca dovezile acumulate pâna acum indica faptul ca persoanele care traiesc peste 100 de ani amâna sau chiar evita aceste afectiuni ale batrânetii".

Pentru a identifica cele 281 de variatiuni genetice asociate longevitatii, cercetatorii au studiat aproximativ 250.000 de astfel de variatiuni (denumite "polimorfisme ale unui singur nucleotid").

Profesorul Perls afirma ca o studiere mai amanuntita a acestor 281 de variatiuni genetice ar putea permite oamenilor de stiinta sa înteleaga de ce unele persoane evita afectiunile tipice batrânetii, ducând în cele din urma la conceperea unor noi tratamente pentru aceste boli.

De asemenea, acest studiu ar putea fi un prim pas spre conceperea unui test de sânge care ar identifica persoanele care au sanse mari sa atinga vârsta de 100 de ani. Oamenii de stiinta avertizeaza, însa, ca aceste teste ar putea încuraja aceste persoane sa nu se preocupe la fel de mult de a duce un stil de viata sanatos.

"Chiar daca unele persoane prezinta o combinatie de variante genetice care sunt corelate cu longevitatea si care par sa compenseze pentru un stil de viata de nesanatos, recomandam în continuare ca toata lumea sa încerce sa aiba un stil de viata sanatos", a conchis profesorul Perls.

Sursa: Daily Mail - via descopera.ro

Part of a suite of statistical tools called MINE, it can tease out multiple patterns hidden in health information from around the globe, statistics amassed from a season of major league baseball, data on the changing bacterial landscape of the gut, and much more.

The researchers report their findings in a paper appearing in the December 16 2011 issue of the journal Science.

From Facebook to physics to the global economy, the world is filled with data sets that could take a person hundreds of years to analyze by eye. Sophisticated computer programs can search these data sets with great speed, but fall short when researchers attempt to even-handedly detect different kinds of patterns in large data collections.

"There are massive data sets that we want to explore, and within them, there may be many relationships that we want to understand," said Broad Institute associate member Pardis Sabeti, senior author of the paper and an assistant professor at the Center for Systems Biology at Harvard University. "The human eye is the best way to find these relationships, but these data sets are so vast that we can't do that. This toolkit gives us a way of mining the data to look for relationships."

The researchers tested their analytical toolkit on several large data sets, including one provided by Harvard colleague Peter Turnbaugh who is interested in the trillions of microorganisms that live in the gut. Working with Turnbaugh, the research team harnessed MINE to make more than 22 million comparisons and narrowed in on a few hundred patterns of interest that had not been observed before.

"The goal of this statistic is to take data with a lot of different dimensions and many possible correlations and pick out the top ones," said Michael Mitzenmacher, a senior author of the paper and professor of computer science at Harvard University. "We view this as an exploration tool -- it can find patterns and rank them in an equitable way."

One of the tool's greatest strengths is that it can detect a wide range of patterns and characterize them according to a number of different parameters a researcher might be interested in. Other statistical tools work well for searching for a specific pattern in a large data set, but cannot score and compare different kinds of possible relationships. MINE, which stands for Maximal Information-based Nonparametric Exploration, is able to analyze a broad spectrum of patterns.

"Standard methods will see one pattern as signal and others as noise," said David Reshef, a co-first author of the paper who is currently a graduate student in the Harvard-MIT Health Sciences and Technology program and also worked on this project as a graduate student in the department of statistics at the University of Oxford. "There can potentially be a variety of different types of relationships in a given data set. What's exciting about our method is that it looks for any type of clear structure within the data, attempting to find all of them."

Not only does MINE attempt to identify any pattern within the data, but it also attempts to do so with an eye toward capturing different types of patterns equally well. "This ability to search for patterns in an equitable way offers tremendous exploratory potential in terms of searching for patterns without having to know ahead of time what to search for," said David Reshef.

MINE is especially powerful in exploring data sets with relationships that may harbor more than one important pattern. As a proof of concept, the researchers applied MINE to social, economic, health, and political data from the World Health Organization (WHO) and its partners. When they compared the relationship between household income and female obesity, they found two contrasting trends in the data. Many countries follow a parabolic rate, with obesity rates rising with income but peaking and tapering off after income reaches a certain level. But in the Pacific Islands, where female obesity is a sign of status, countries follow a steep trend, with the rate of obesity climbing as income increases.

"Many data sets will contain these types of complicated relationships that are guided by multiple drivers," said Sabeti. MINE is able to identify these. "This greatly extends our capability to find interesting relationships in data."

Researchers can use MINE to generate new ideas and connections that no one has thought to look for before.

"Our tool is a hypothesis generator," said Yakir Reshef, a co-first author of the paper and a Fulbright scholar at the Weizmann Institute of Science. "The standard paradigm is hypothesis-driven science, where you come up with a hypothesis based on your personal observations. But by exploring the data, you get ideas for hypotheses that would never have occurred to you otherwise."

In addition to testing the ability of the suite of tools to detect patterns in biological and health data, the researchers examined data collected from the 2008 baseball season.

"One question that we thought would be particularly interesting would be to see what things were most strongly associated with salary," said David Reshef. The researchers generated a list of relationships, finding that the strongest associations with salary were hits, total bases, and an aggregate statistic that reflects how many runs a player generated for a team. "Given the stakes, baseball is so well documented. We're curious to see what can be done in this realm with tools like MINE."

Researchers from many different fields, including systems biology, computer science, statistics, and mathematics, all contributed to this project. "People are getting better at combining data from different sources, and in some ways, this project is in the spirit of that," said Yakir Reshef. "The project brought together authors from many disciplines. It symbolizes the kind of collaborations that we hope people will use this for in the future."

Other authors who contributed to this work include Hilary Finucane, Sharon Grossman, Gilean McVean, and Eric Lander. Funding for this work was provided by the Packard Foundation, Marshall Aid Commemoration Commission, National Science Foundation, European Research Council, and the National Institutes of Health.

Source: ScienceDaily via ZeitNews.org

Né sacerdote né avvocato. Alessandro Volta (1745-1827), come molti illustri colleghi, disobbedì al volere di famiglia (dello zio, in particolare) e virò dagli studi giuridici a quelli scientifici. Formandosi per lo più da autodidatta, aiutato in parte dalla grande curiosità che lo aveva accompagnato sin da piccolo e in parte da alcuni fortunati incontri. Uno dei quali fu quello con l’amico Giulio Cesare Gattoni, che aveva conosciuto proprio in seminario.

Fu infatti nel laboratorio improvvisato dell’amico che Volta - complici anche le letture di alcuni libri, come The History and Present State of Electricity di Joseph Priestley (lo scienziato che aveva contribuito alla scoperta dell’ossigeno) - cominciò a interessarsi di scienza. Dell’elettricità, in particolare. Ma anche se lo ricordiamo per la costruzione dell’elettroforo (uno strumento per accumulare carica elettrica), dell’elettrometro (per misurare la differenza di potenziale), per la sua disputa con Luigi Galvani sull’ elettricità animale e per la creazione della pila, Alessandro Volta non si occupò solo di elettricità.

Intorno agli anni Settanta del Diciottesimo secolo, Volta aveva sentito degli strani racconti sul fiume Lambro, in Lombardia: passando con una candela sulla superficie delle sue acque paludose, si accendevano fiammelle di un insolito colore azzurro. Non era la prima volta che qualcuno riportava l’insolito fenomeno, fino ad allora etichettato come un’ “esalazione di aria infiammabile, di origine minerale”. Ma Volta era comunque deciso a toccare con mano quei fuochi.

L’occasione sarebbe stata una passeggiata negli stagni di Angera, nei pressi del Lago Maggiore. Si  racconta che durante una gita in barca lo scienziato smosse con un bastoncino il fondale, notando delle bollicine che risalivano verso l’alto. Se fosse riuscito a catturare quelle bollicine, pensò Volta, avrebbe potuto capirne meglio le caratteristiche. Così, come si fa con un insetto per studiarlo al microscopio una volta tornati in laboratorio, il giovane Alessandro raccolse dei campioni di quell’aria melmosa e le imprigionò in un contenitore.

Si accorse presto che così come l’idrogeno, il gas emanato dalle paludi era infiammabile. Aveva scoperto quello che solo molti anni dopo sarebbe stato riconosciuto come il più semplice degli idrocarburi della famiglia degli alcani, il metano, formula CH 4, prodotto della decomposizione di organismi viventi. Una scoperta che si dice risalire al 31 gennaio 1776 e per la quale lo scienziato italiano trovò presto un’applicazione.

Con quell’ “aria nativa delle paludi”, come si riferiva al metano, costruì infatti la pistola elettroflogopneumatica: all’interno di un contenitore di vetro mescolò insieme ossigeno e aria infiammabile che, in presenza di una scintilla, potevano esplodere lanciando in aria un tappo di sughero. Una sorta di sistema di allarme. E nelle sue ipotesi il sistema poteva funzionare anche a distanza, con un segnale di innesco trasportato per via elettrica. Non vi ricorda il telegrafo?

Fonte: Wired.it