Watching a synapse grow: noninvasive confocal imaging of synaptic growth in Drosophila

The glutamatergic neuromuscular junction (NMJ) in Drosophila adds new boutons and branches during larval development. We generated transgenic fruit flies that express a novel green fluorescent membrane protein at the postsynaptic specialization, allowing for repeated noninvasive confocal imaging of synapses in live, developing larvae. As synapses grow, existing synaptic boutons stretch apart and new boutons insert between them; in addition, new boutons are added at the ends of existing strings of boutons. Some boutons are added de novo, while others bud from existing boutons. New branches form as multiple boutons bud from existing boutons. Nascent boutons contain active zones, T bars, and synaptic vesicles; we observe no specialized growth structures. Some new boutons exhibit a lower level of Fasciclin II, suggesting that the levels of this synaptic cell adhesion molecule vary locally during synaptic growth.     

A predictive model for respiratory syncytial virus (RSV) hospitalisation of premature infants born at 33–35 weeks of gestational age,based on data from the Spanish FLIP study

Background

The aim of this study, conducted in Europe, was to develop a validated risk factor based model to predict RSV-related hospitalisation in premature infants born 33–35 weeks'' gestational age (GA).

Methods

The predictive model was developed using risk factors captured in the Spanish FLIP dataset, a case-control study of 183 premature infants born between 33–35 weeks'' GA who were hospitalised with RSV, and 371 age-matched controls. The model was validated internally by 100-fold bootstrapping. Discriminant function analysis was used to analyse combinations of risk factors to predict RSV hospitalisation. Successive models were chosen that had the highest probability for discriminating between hospitalised and non-hospitalised infants. Receiver operating characteristic (ROC) curves were plotted.

Results

An initial 15 variable model was produced with a discriminant function of 72% and an area under the ROC curve of 0.795. A step-wise reduction exercise, alongside recalculations of some variables, produced a final model consisting of 7 variables: birth ± 10 weeks of start of season, birth weight, breast feeding for ≤ 2 months, siblings ≥ 2 years, family members with atopy, family members with wheeze, and gender. The discrimination of this model was 71% and the area under the ROC curve was 0.791. At the 0.75 sensitivity intercept, the false positive fraction was 0.33. The 100-fold bootstrapping resulted in a mean discriminant function of 72% (standard deviation: 2.18) and a median area under the ROC curve of 0.785 (range: 0.768–0.790), indicating a good internal validation. The calculated NNT for intervention to treat all at risk patients with a 75% level of protection was 11.7 (95% confidence interval: 9.5–13.6).

Conclusion

A robust model based on seven risk factors was developed, which is able to predict which premature infants born between 33–35 weeks'' GA are at highest risk of hospitalisation from RSV. The model could be used to optimise prophylaxis with palivizumab across Europe.     

Diacylglycerols interact with the L2 lipidation site in TRPC3 to induce a sensitized channel state

Coordination of lipids within transient receptor potential canonical channels (TRPCs) is essential for their Ca²⁺ signaling function. Single particle cryo‐EM studies identified two lipid interaction sites, designated L1 and L2, which are proposed to accommodate diacylglycerols (DAGs). To explore the role of L1 and L2 in TRPC3 function, we combined structure‐guided mutagenesis and electrophysiological recording with molecular dynamics (MD) simulations. MD simulations indicate rapid DAG accumulation within both L1 and L2 upon its availability within the plasma membrane. Electrophysiological experiments using a photoswitchable DAG‐probe reveal potentiation of TRPC3 currents during repetitive activation by DAG. Importantly, initial DAG exposure generates a subsequently sensitized channel state that is associated with significantly faster activation kinetics. TRPC3 sensitization is specifically promoted by mutations within L2, with G652A exhibiting sensitization at very low levels of active DAG. We demonstrate the ability of TRPC3 to adopt a closed state conformation that features partial lipidation of L2 sites by DAG and enables fast activation of the channel by the phospholipase C‐DAG pathway.     

Identification of novel Y chromosome encoded transcripts by testis transcriptome analysis of mice with deletions of the Y chromosome long arm

Background  

The male-specific region of the mouse Y chromosome long arm (MSYq) is comprised largely of repeated DNA, including multiple copies of the spermatid-expressed Ssty gene family. Large deletions of MSYq are associated with sperm head defects for which Ssty deficiency has been presumed to be responsible.     

The second National Toxicology Program comparative exercise on the prediction of rodent carcinogenicity: definitive results

Chemical carcinogenicity has been the target of a large array of attempts to create alternative predictive models, ranging from short-term biological assays (e.g. mutagenicity tests) to theoretical models. Among the theoretical models, the application of the science of structure-activity relationships (SAR) has earned special prominence. A crucial element is the independent evaluation of the predictive ability. In the past decade, there have been two fundamental comparative exercises on the prediction of chemical carcinogenicity, held under the aegis to the US National Toxicology Program (NTP). In both exercises, the predictions were published before the animal data were known, thus using a most stringent criterion of predictivity. We analyzed the results of the first comparative exercise in a previous paper [Mutat. Res. 387 (1997) 35]; here, we present the complete results of the second exercise, and we analyze and compare the prediction sets. The range of accuracy values was quite large: the systems that performed best in this prediction exercise were in the range 60-65% accuracy. They included various human experts approaches (e.g. Oncologic) and biologically based approaches (e.g. the experimental transformation assay in Syrian hamster embryo (SHE) cells). The main difficulty for the structure-activity relationship-based approaches was the discrimination between real carcinogens, and non-carcinogens containing structural alerts (SA) for genotoxic carcinogenicity. It is shown that the use of quantitative structure-activity relationship models, when possible, can contribute to overcome the above problem. Overall, given the uncertainty linked to the predictions, the predictions for the individual chemicals cannot be taken at face value; however, the general level of knowledge available today (especially for genotoxic carcinogens) allows qualified human experts to operate a very efficient priority setting of large sets of chemicals.     

Raman detection and identification of normal and leukemic hematopoietic cells

The analysis of leukocytes of peripheral blood is a crucial step in hematologic exams commonly used for disease diagnosis and, typically, requires molecular labelling. In addition, only a detailed, laborious phenotypic analysis allows identifying the presence and stage of specific pathologies such as leukemia. Most of the biochemical information is lost in the routine blood tests. In the present study, we tackle 2 important issues of label‐free biochemical identification and classification of leukocytes using Raman spectroscopy (RS). First, we demonstrate that leukocyte subpopulations of lymphocytes (B, T and NK cells), monocytes and granulocytes can be identified by the unsupervised statistical approach of principal component analysis and classified by linear discriminant analysis with approximately 99% of accuracy. Second, we apply the same procedure to identify and discriminate normal B cells and transformed MN60 lymphocyte leukemic cell lines. In addition, we demonstrate that RS can be efficiently used for monitoring the cell response to low‐dose chemotherapy treatment, experimentally eliciting the sensitivity to a dose‐dependent cell response, which is of fundamental importance to determine the efficacy of any treatment. These results largely expand established Raman‐based research protocols for label‐free analysis of white blood cells, leukemic cells and chemotherapy treatment follow‐up.