Plasmonic Control of Radiative Properties of Semiconductor Quantum Dots Coupled to Plasmonic Ring Cavities

In recent years, a lot of effort has been made to achieve controlled delivery of target particles to the hotspots of plasmonic nanoantennas, in order to probe and/or exploit the extremely large field enhancements produced by such structures. While in many cases such high fields are advantageous, there are instances where they should be avoided. In this work, we consider the implications of using the standard nanoantenna geometries when colloidal quantum dots are employed as target entities. We show that in this case, and for various reasons, dimer antennas are not the optimum choice. Plasmonic ring cavities are a better option despite low field enhancements, as they allow collective coupling of many quantum dots in a reproducible and predictable manner. In cases where larger field enhancements are required, or for larger quantum dots, nonconcentric ring-disk cavities can be employed instead

Predicting the onset of anxiety syndromes at 12 months in primary care attendees. The PredictA-Spain study

Background: There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. Methods: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. Results: The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval = 0.78–0.83) and the Hedges' g = 1.17 (95% confidence interval = 1.04–1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. Conclusions: The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care.This study was supported by the Spanish Ministry of Health (grant FIS references: PI041980, PI041771, PI042450 and PI06/1442) and the Andalusian Council of Health (grant references: 05/403 and 06/278); as well as the Spanish Network of Primary Care Research ‘redIAPP’ (RD06/0018), the ‘Aragón group’ (RD06/0018/0020), the ‘Baleares group’ (RD07/0018/0033), and the ‘SAMSERAP group’ (RD06/0018/0039)

Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: Methodology

Background: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. Methods: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. Results: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. Conclusion: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health care.The research in Spain was funded by grants from the Spanish Ministry of Health (grant FIS references: PI04/1980, PI0/41771, PI04/2450, and PI06/1442), Andalusian Council of Health (grant references: 05/403, 06/278 and 08/0194), and the Spanish Ministry of Education and Science (grant reference SAF 2006/07192). The Malaga sample, as part of the predictD-International study, was also funded by a grant from The European Commission (reference QL4-CT2002-00683)

Continuous monitoring of molecular biomarkers in microfluidic devices

The ability to monitor molecular targets is crucial in fields ranging from healthcare to industrial processing to environmental protection. Devices employing biomolecules to achieve this goal are called biosensors. Over the last half century researchers have developed dozens of different biosensor approaches. In this chapter we analyze recent advances in the biosensing field aiming at adapting these to the problem of continuous molecular monitoring in complex sample streams, and how the merging of these sensors with lab-on-a-chip technologies would be beneficial to both. To do so we discuss (1) the components that comprise a biosensor, (2) the challenges associated with continuous molecular monitoring in complex sample streams, (3) how different sensing strategies deal with (or fail to deal with) these challenges, and (4) the implementation of these technologies into lab-on-a-chip architectures

Structural Analysis of the Interaction between the Bacterial Cell Division Proteins FtsQ and FtsB

In most bacteria and archaea, filaments of FtsZ protein organize cell division. FtsZ forms a ring structure at the division site and starts the recruitment of 10 to 20 downstream proteins that together form a multiprotein complex termed the divisome. The divisome is thought to facilitate many of the steps required to make two cells out of one. FtsQ and FtsB are part of the divisome, with FtsQ being a central hub, interacting with most of the other divisome components. Here we show for the first time in detail how FtsQ interacts with its downstream partner FtsB and show that mutations that disturb the interface between the two proteins effectively inhibit cell division.Most bacteria and archaea use the tubulin homologue FtsZ as its central organizer of cell division. In Gram-negative Escherichia coli bacteria, FtsZ recruits cytosolic, transmembrane, periplasmic, and outer membrane proteins, assembling the divisome that facilitates bacterial cell division. One such divisome component, FtsQ, a bitopic membrane protein with a globular domain in the periplasm, has been shown to interact with many other divisome proteins. Despite its otherwise unknown function, it has been shown to be a major divisome interaction hub. Here, we investigated the interactions of FtsQ with FtsB and FtsL, two small bitopic membrane proteins that act immediately downstream of FtsQ. We show in biochemical assays that the periplasmic domains of E. coli FtsB and FtsL interact with FtsQ, but not with each other. Our crystal structure of FtsB bound to the β domain of FtsQ shows that only residues 64 to 87 of FtsB interact with FtsQ. A synthetic peptide comprising those 24 FtsB residues recapitulates the FtsQ-FtsB interactions. Protein deletions and structure-guided mutant analyses validate the structure. Furthermore, the same structure-guided mutants show cell division defects in vivo that are consistent with our structure of the FtsQ-FtsB complex that shows their interactions as they occur during cell division. Our work provides intricate details of the interactions within the divisome and also provides a tantalizing view of a highly conserved protein interaction in the periplasm of bacteria that is an excellent target for cell division inhibitor searches