Investigations into some important fish larvae in the south east Atlantic in relation to the hydrological environment

Includes bibliographies at end of chapters.The following objectives are covered in the study: (i) the description of the seasonal hydrological changes in the survey area and a comparison between years. (ii) an examination of the seasonal distribution and abundance of the larval stages in relation to hydrological conditions. (iii) the determination of the preferential temperature and salinity ranges for the larvae. (iv) an examination of seasonal shift in location and intensity of spawning from the geographic distribution, abundance and size composition of the larvae. (v) the establishment of dispersal trends of developing larvae from the spawning grounds. (vi) the provision of information on the identity and development of important fish eggs and larvae. (vii) the determination of diurnal changes in abundance and size composition of various larval species. The results reported are regarded as scientifically significant in view of the paucity of basic information on the early life history of any fish species off South West Africa. Many aspects such as identity, development, distribution, abundance, hydrological affinities, diurnal variation and dispersal are given for the first time. The findings make a positive contribution not only to knowledge of the early stages and biology of the species but also provide an insight into the general ecology of fish larvae in what is probably the most productive and lucrative fishing grounds in the South East Atlantic

Characterising live cell behaviour: traditional label-free and quantitative phase imaging approaches

Label-free imaging uses inherent contrast mechanisms within cells to create image contrast without introducing dyes/labels, which may confound results. Quantitative phase imaging is label-free and offers higher content and contrast compared to traditional techniques. High-contrast images facilitate generation of individual cell metrics via more robust segmentation and tracking, enabling formation of a label-free dynamic phenotype describing cell-to-cell heterogeneity and temporal changes. Compared to population-level averages, individual cell-level dynamic phenotypes have greater power to differentiate between cellular responses to treatments, which has clinical relevance e.g. in the treatment of cancer. Furthermore, as the data is obtained label-free, the same cells can be used for further assays or expansion, of potential benefit for the fields of regenerative and personalised medicine

Characterising live cell behaviour: traditional label-free and quantitative phase imaging approaches

Label-free imaging uses inherent contrast mechanisms within cells to create image contrast without introducing dyes/labels, which may confound results. Quantitative phase imaging is label-free and offers higher content and contrast compared to traditional techniques. High-contrast images facilitate generation of individual cell metrics via more robust segmentation and tracking, enabling formation of a label-free dynamic phenotype describing cell-to-cell heterogeneity and temporal changes. Compared to population-level averages, individual cell-level dynamic phenotypes have greater power to differentiate between cellular responses to treatments, which has clinical relevance e.g. in the treatment of cancer. Furthermore, as the data is obtained label-free, the same cells can be used for further assays or expansion, of potential benefit for the fields of regenerative and personalised medicine

Correlative super-resolution fluorescence and electron microscopy using conventional fluorescent proteins in vacuo

Super-resolution light microscopy, correlative light and electron microscopy, and volume electron microscopy are revolutionising the way in which biological samples are examined and understood. Here, we combine these approaches to deliver super-accurate correlation of fluorescent proteins to cellular structures. We show that YFP and GFP have enhanced blinking properties when embedded in acrylic resin and imaged under partial vacuum, enabling in vacuo single molecule localisation microscopy. In conventional section-based correlative microscopy experiments, the specimen must be moved between imaging systems and/or further manipulated for optimal viewing. These steps can introduce undesirable alterations in the specimen, and complicate correlation between imaging modalities. We avoided these issues by using a scanning electron microscope with integrated optical microscope to acquire both localisation and electron microscopy images, which could then be precisely correlated. Collecting data from ultrathin sections also improved the axial resolution and signal-to-noise ratio of the raw localisation microscopy data. Expanding data collection across an array of sections will allow 3-dimensional correlation over unprecedented volumes. The performance of this technique is demonstrated on vaccinia virus (with YFP) and diacylglycerol in cellular membranes (with GFP)

Can EEG accurately predict 2-year neurodevelopmental outcome for preterm infants?

Objective: Establish if serial multichannel video electroencephalography (EEG) in preterm infants can accurately predict 2-year neurodevelopmental outcome. Design and patients: EEGs were recorded at three time points over the neonatal course for infants <32 weeks’ gestational age (GA). Monitoring commenced soon after birth and continued over the first 3 days. EEGs were repeated at approximately 32 and 35 weeks’ postmenstrual age (PMA). EEG scores were based on an age- specific grading scheme. Clinical score of neonatal morbidity risk and cranial ultrasound imaging were completed. Setting: Neonatal intensive care unit at Cork University Maternity Hospital, Ireland. Main outcome measures: Bayley Scales of Infant Development III at 2 years’ corrected age. Results: Sixty- seven infants were prospectively enrolled in the study and 57 had follow- up available (median GA 28.9 weeks (IQR 26.5–30.4)). Forty had normal outcome, 17 had abnormal outcome/died. All EEG time points were individually predictive of abnormal outcome; however, the 35- week EEG performed best. The area under the receiver operating characteristic curve (AUC) for this time point was 0.91 (95% CI 0.83 to 1), p<0.001. Comparatively, the clinical course AUC was 0.68 (95% CI 0.54 to 0.80, p=0.015), while abnormal cranial ultrasound was 0.58 (95% CI 0.41 to 0.75, p=0.342). Conclusion: Multichannel EEG is a strong predictor of 2- year outcome in preterm infants particularly when recorded around 35 weeks’ PMA. Infants at high risk of brain injury may benefit from early postnatal EEG recording which, if normal, is reassuring. Postnatal clinical complications can contribute to poor outcome; therefore, we state that a later EEG around 35 weeks has a role to play in prognostication

Voltage-dependent activation of Rac1 by Nav1.5 channels promotes cell migration

Ion channels can regulate the plasma membrane potential (Vm) and cell migration as a result of altered ion flux. However, the mechanism by which Vm regulates motility remains unclear. Here, we show that the Nav1.5 sodium channel carries persistent inward Na+ current which depolarizes the resting Vm at the timescale of minutes. This Nav1.5-dependent Vm depolarization increases Rac1 colocalization with phosphatidylserine, to which it is anchored at the leading edge of migrating cells, promoting Rac1 activation. A genetically-encoded FRET biosensor of Rac1 activation shows that depolarization-induced Rac1 activation results in acquisition of a motile phenotype. By identifying Nav1.5-mediated Vm depolarization as a regulator of Rac1 activation, we link ionic and electrical signaling at the plasma membrane to small GTPase-dependent cytoskeletal reorganization and cellular migration. We uncover a novel and unexpected mechanism for Rac1 activation, which fine tunes cell migration in response to ionic and/or electric field changes in the local microenvironment

The CellPhe toolkit for cell phenotyping using time-lapse imaging and pattern recognition

Approaches for temporal analysis and quantitative characterisation of single cell morphology and dynamics remain in high demand. Here authors present CellPhe, a pattern recognition toolkit for the unbiased characterisation of cellular phenotypes within time-lapse videos