Promyelocytic leukaemia (PML) nuclear bodies are present in most mammalian cell nuclei. PML bodies are disrupted by PML retinoic acid receptor alpha (RAR alpha) oncoproteins in acute promyelocytic leukaemia. These bodies contain numerous proteins, including Sp100, SUMO-1, HAUSP(USP7), CBP and BLM, and they have been implicated in aspects of transcriptional regulation or as nuclear storage depots. Here, we show that three classes of PML nuclear bodies can be distinguished, on the basis of their dynamic properties in living cells. One class of PML bodies is particularly noteworthy in that it moves by a metabolic-energy-dependent mechanism. This represents the first example of metabolic-energy-dependent transport of a nuclear body within the mammalian cell nucleus.

Live-cell imaging technology using fluorescent proteins (green fluorescent protein and its homologues) has revolutionized the study of cellular dynamics. But tools that can quantitatively analyse complex spatiotemporal processes in live cells remain lacking. Here we describe a new technique--fast multi-colour four-dimensional imaging combined with automated and quantitative time-space reconstruction--to fill this gap. As a proof of principle, we apply this method to study the re-formation of the nuclear envelope in live cells. Four-dimensional imaging of three spectrally distinct fluorescent proteins is used to simultaneously visualize three different cellular compartments at high speed and with high spatial resolution. The highly complex data, comprising several thousand images from a single cell, were quantitatively reconstructed in time-space by software developed in-house. This analysis reveals quantitative and qualitative insights into the highly ordered topology of nuclear envelope formation, in correlation with chromatin expansion - results that would have been impossible to achieve by manual inspection alone. Our new technique will greatly facilitate study of the highly ordered dynamic architecture of eukaryotic cells.

The skin can serve as an interstitial Na+ reservoir. Local tissue Na+ accumulation increases with age, inflammation and infection. This increased local Na+ availability favors pro-inflammatory immune cell function and dampens their anti-inflammatory capacity. In this review, we summarize available data on how NaCl affects various immune cells. We particularly focus on how salt promotes pro-inflammatory macrophage and T cell function and simultaneously curtails their regulatory and anti-inflammatory potential. Overall, these findings demonstrate that local Na+ availability is a promising novel regulator of immunity. Hence, the modulation of tissue Na+ levels bears broad therapeutic potential: increasing local Na+ availability may help in treating infections, while lowering tissue Na+ levels may be used to treat, for example, autoimmune and cardiovascular diseases.

One of the biometric methods in authentication systems is the writer verification/identification using password handwriting. The main objective of this paper is to present a robust writer verification system by using cursive texts as well as block letter words. To evaluate the system, two datasets have been used. One of them is called Secure Password DB 150, which is composed of 150 users with 18 samples of single character words per user. Another dataset is public and called IAM online handwriting database, and it is composed of 220 users of cursive text samples. Each sample has been defined by a set of features, composed of 67 geometrical, statistical, and temporal features. In order to get more discriminative information, two feature reduction methods have been applied, Fisher Score and Info Gain Attribute Evaluation. Finally, the classification system has been implemented by hold-out cross validation and k-folds cross validation strategies for three different classifiers, K-NN, Naïve Bayes and Bayes Net classifiers. Besides, it has been applied for verification and identification approaches. The best results of 95.38% correct classification are achieved by using the k-nearest neighbor classifier for single character DB. A feature reduction by Info Gain Attribute Evaluation improves the results for Naïve Bayes Classifier to 98.34% for IAM online handwriting DB. It is concluded that the set of features and its reduction are a strong selection for the based-password handwritten writer identification in comparison with the state-of-the-art.