Semantic, perceptual and number space: relations between category width and spatial processing.

Coarse semantic encoding and broad categorization behavior are the hallmarks of the right cerebral hemisphere's contribution to language processing. We correlated 40 healthy subjects' breadth of categorization as assessed with Pettigrew's category width scale with lateral asymmetries in perceptual and representational space. Specifically, we hypothesized broader category width to be associated with larger leftward spatial biases. For the 20 men, but not the 20 women, this hypothesis was confirmed both in a lateralized tachistoscopic task with chimeric faces and a random digit generation task; the higher a male participant's score on category width, the more pronounced were his left-visual field bias in the judgement of chimeric faces and his small-number preference in digit generation ("small" is to the left of "large" in number space). Subjects' category width was unrelated to lateral displacements in a blindfolded tactile-motor rod centering task. These findings indicate that visual-spatial functions of the right hemisphere should not be considered independent of the same hemisphere's contribution to language. Linguistic and spatial cognition may be more tightly interwoven than is currently assumed.

Is mental practice an effective adjunct therapeutic strategy for upper limb motor restoration after stroke?

Stroke is one of the most common conditions requiring rehabilitation, and its motor impairments are a major cause of permanent disability. Hemiparesis is observed by 80% of the patients after acute stroke. Neuroimaging studies showed that real and imagined movements have similarities regarding brain activation, supplying evidence that those similarities are based on the same process. Within this context, the combination of MP with physical and occupational therapy appears to be a natural complement based on neurorehabilitation concepts. Our study seeks to investigate if MP for stroke rehabilitation of upper limbs is an effective adjunct therapy. PubMed (Medline), ISI knowledge (Institute for Scientific Information) and SciELO (Scientific Electronic Library) were terminated on 20 February 2015. Data were collected on variables as follows: sample size, type of supervision, configuration of mental practice, setting the physical practice (intensity, number of sets and repetitions, duration of contractions, rest interval between sets, weekly and total duration), measures of sensorimotor deficits used in the main studies and significant results. Random effects models were used that take into account the variance within and between studies. Seven articles were selected. As there was no statistically significant difference between the two groups (MP vs Control), showed a – 0.6 (95% CI: –1.27 to 0.04), for upper limb motor restoration after stroke. The present meta-analysis concluded that MP is not effective as adjunct therapeutic strategy for upper limb motor restoration after stroke.

All-ceramic or metal-ceramic tooth-supported fixed dental prostheses (FDPs)? A systematic review of the survival and complication rates. Part II: Multiple-unit FDPs.

OBJECTIVE To assess the 5-year survival of metal-ceramic and all-ceramic tooth-supported fixed dental prostheses (FDPs) and to describe the incidence of biological, technical and esthetic complications. METHODS Medline (PubMed), Embase and Cochrane Central Register of Controlled Trials (CENTRAL) searches (2006-2013) were performed for clinical studies focusing on tooth-supported FDPs with a mean follow-up of at least 3 years. This was complemented by an additional hand search and the inclusion of 10 studies from a previous systematic review [1]. Survival and complication rates were analyzed using robust Poisson's regression models to obtain summary estimates of 5-year proportions. RESULTS Forty studies reporting on 1796 metal-ceramic and 1110 all-ceramic FDPs fulfilled the inclusion criteria. Meta-analysis of the included studies indicated an estimated 5-year survival rate of metal-ceramic FDPs of 94.4% (95% CI: 91.2-96.5%). The estimated survival rate of reinforced glass ceramic FDPs was 89.1% (95% CI: 80.4-94.0%), the survival rate of glass-infiltrated alumina FDPs was 86.2% (95% CI: 69.3-94.2%) and the survival rate of densely sintered zirconia FDPs was 90.4% (95% CI: 84.8-94.0%) in 5 years of function. Even though the survival rate of all-ceramic FDPs was lower than for metal-ceramic FDPs, the differences did not reach statistical significance except for the glass-infiltrated alumina FDPs (p=0.05). A significantly higher incidence of caries in abutment teeth was observed for densely sintered zirconia FDPs compared to metal-ceramic FDPs. Significantly more framework fractures were reported for reinforced glass ceramic FDPs (8.0%) and glass-infiltrated alumina FDPs (12.9%) compared to metal-ceramic FDPs (0.6%) and densely sintered zirconia FDPs (1.9%) in 5 years in function. However, the incidence of ceramic fractures and loss of retention was significantly (p=0.018 and 0.028 respectively) higher for densely sintered zirconia FDPs compared to all other types of FDPs. CONCLUSIONS Survival rates of all types of all-ceramic FDPs were lower than those reported for metal-ceramic FDPs. The incidence of framework fractures was significantly higher for reinforced glass ceramic FDPs and infiltrated glass ceramic FDPs, and the incidence for ceramic fractures and loss of retention was significantly higher for densely sintered zirconia FDPs compared to metal-ceramic FDPs.

P-T-t estimation of syn-kinematic strain in low-grade quartz-feldspar bearing rocks using thermodynamic modeling and 40Ar/39Ar dating techniques: example of the Plan-de-Phasy shear zone unit (Briançonnais Zone, Western Alps)

Pressure–Temperature–time (P–T–t) estimates of the syn-kinematic strain at the peak-pressure conditions reached during shallow underthrusting of the Briançonnais Zone in the Alpine subduction zone was made by thermodynamic modelling and 40Ar/39Ar dating in the Plan-de-Phasy unit (SE of the Pelvoux Massif, Western Alps). The dated phengite minerals crystallized syn-kinematically in a shear zone indicating top-to-the-N motion. By combining X-ray mapping with multi-equilibrium calculations, we estimate the phengite crystallization conditions at 270 ± 50 °C and 8.1 ± 2 kbar at an age of 45.9 ± 1.1 Ma. Combining this P–T–t estimate with data from the literature allows us to constrain the timing and geometry of Alpine continental subduction. We propose that the Briançonnais units were scalped on top of the slab during ongoing continental subduction and exhumed continuously until collision.

The Quiet Eye in Motor Performance and Learning – Functional and Theoretical Considerations

High precision in motor skill performance, in both sport and other domains (e.g. surgery and aviation), requires the efficient coupling of perceptual inputs (e.g. vision) and motor actions. A particular gaze strategy, which has received much attention within the literature, has been shown to predict both inter- (expert vs. novice) and intra-individual (successful vs. unsuccessful) motor performance (see Vine et al., 2014). Vickers (1996) labelled this phenomenon the quiet eye (QE) which is defined as the final fixation before the initiation of the crucial phase of movement. While the positive influence of a long QE on accuracy has been revealed in a range of different motor skills, there is a growing number of studies suggesting that the relationship between QE and motor performance is not entirely monotonic. This raises interesting questions regarding the QE’s purview, and the theoretical approaches explaining its functionality. This talk aims to present an overview of the issues described above, and to discuss contemporary research and experimental approaches to examining the QE phenomenon. In the first part of the talk Dr. Vine will provide a brief and critical review of the literature, highlighting recent empirical advancements and potential directions for future research. In the second part, Dr. Klostermann will communicate three different theoretical approaches to explain the relationship between QE and motor performance. Drawing upon aspects of all three of these theoretical approaches, a functional inhibition role for the QE (related to movement parameterisation) will be proposed.

Anatomy of the nail unit and the nail biopsy

The nail unit is the largest and a rather complex skin appendage. It is located on the dorsal aspect of the tips of fingers and toes and has important protective and sensory functions. Development begins in utero between weeks 7 and 8 and is fully formed at birth. For its correct development, a great number of signals are necessary. Anatomically, it consists of 4 epithelial components: the matrix that forms the nail plate; the nail bed that firmly attaches the plate to the distal phalanx; the hyponychium that forms a natural barrier at the physiological point of separation of the nail from the bed; and the eponychium that represents the undersurface of the proximal nail fold which is responsible for the formation of the cuticle. The connective tissue components of the matrix and nail bed dermis are located between the corresponding epithelia and the bone of the distal phalanx. Characteristics of the connective tissue include: a morphogenetic potency for the regeneration of their epithelia; the lateral and proximal nail folds form a distally open frame for the growing nail; and the tip of the digit has rich sensible and sensory innervation. The blood supply is provided by the paired volar and dorsal digital arteries. Veins and lymphatic vessels are less well defined. The microscopic anatomy varies from nail subregion to subregion. Several different biopsy techniques are available for the histopathological evaluation of nail alterations.

Respiratory rhythm generation: A modeling study of the respiratory central pattern generator and the phrenic motor neuron

The respiratory central pattern generator is a collection of medullary neurons that generates the rhythm of respiration. The respiratory central pattern generator feeds phrenic motor neurons, which, in turn, drive the main muscle of respiration, the diaphragm. The purpose of this thesis is to understand the neural control of respiration through mathematical models of the respiratory central pattern generator and phrenic motor neurons. ^ We first designed and validated a Hodgkin-Huxley type model that mimics the behavior of phrenic motor neurons under a wide range of electrical and pharmacological perturbations. This model was constrained physiological data from the literature. Next, we designed and validated a model of the respiratory central pattern generator by connecting four Hodgkin-Huxley type models of medullary respiratory neurons in a mutually inhibitory network. This network was in turn driven by a simple model of an endogenously bursting neuron, which acted as the pacemaker for the respiratory central pattern generator. Finally, the respiratory central pattern generator and phrenic motor neuron models were connected and their interactions studied. ^ Our study of the models has provided a number of insights into the behavior of the respiratory central pattern generator and phrenic motor neurons. These include the suggestion of a role for the T-type and N-type calcium channels during single spikes and repetitive firing in phrenic motor neurons, as well as a better understanding of network properties underlying respiratory rhythm generation. We also utilized an existing model of lung mechanics to study the interactions between the respiratory central pattern generator and ventilation. ^

Critical indicators associated with negative performance in a selectively manned unit

Introduction. Selectively manned units have a long, international history, both military and civilian. Some examples include SWAT teams, firefighters, the FBI, the DEA, the CIA, and military Special Operations. These special duty operators are individuals who perform a highly skilled and dangerous job in a unique environment. A significant amount of money is spent by the Department of Defense (DoD) and other federal agencies to recruit, select, train, equip and support these operators. When a critical incident or significant life event occurs, that jeopardizes an operator's performance; there can be heavy losses in terms of training, time, money, and potentially, lives. In order to limit the number of critical incidents, selection processes have been developed over time to “select out” those individuals most likely to perform below desired performance standards under pressure or stress and to "select in" those with the "right stuff". This study is part of a larger program evaluation to assess markers that identify whether a person will fail under the stresses in a selectively manned unit. The primary question of the study is whether there are indicators in the selection process that signify potential negative performance at a later date. ^ Methods. The population being studied included applicants to a selectively manned DoD organization between 1993 and 2001 as part of a unit assessment and selection process (A&S). Approximately 1900 A&S records were included in the analysis. Over this nine year period, seventy-two individuals were determined to have had a critical incident. A critical incident can come in the form of problems with the law, personal, behavioral or family problems, integrity issues, and skills deficit. Of the seventy-two individuals, fifty-four of these had full assessment data and subsequent supervisor performance ratings which assessed how an individual performed while on the job. This group was compared across a variety of variables including demographics and psychometric testing with a group of 178 individuals who did not have a critical incident and had been determined to be good performers with positive ratings by their supervisors.^ Results. In approximately 2004, an online pre-screen survey was developed in the hopes of preselecting out those individuals with items that would potentially make them ineligible for selection to this organization. This survey has aided the organization to increase its selection rates and save resources in the process. (Patterson, Howard Smith, & Fisher, Unit Assessment and Selection Project, 2008) When the same prescreen was used on the critical incident individuals, it was found that over 60% of the individuals would have been flagged as unacceptable. This would have saved the organization valuable resources and heartache.^ There were some subtle demographic differences between the two groups (i.e. those with critical incidents were almost twice as likely to be divorced compared with the positive performers). Upon comparison of Psychometric testing several items were noted to be different. The two groups were similar when their IQ levels were compared using the Multidimensional Aptitude Battery (MAB). When looking at the Minnesota Multiphasic Personality Inventory (MMPI), there appeared to be a difference on the MMPI Social Introversion; the Critical Incidence group scored somewhat higher. When analysis was done, the number of MMPI Critical Items between the two groups was similar as well. When scores on the NEO Personality Inventory (NEO) were compared, the critical incident individuals tended to score higher on Openness and on its subscales (Ideas, Actions, and Feelings). There was a positive correlation between Total Neuroticism T Score and number of MMPI critical items.^ Conclusions. This study shows that the current pre-screening process is working and would have saved the organization significant resources. ^ If one was to develop a profile of a candidate who potentially could suffer a critical incident and subsequently jeopardize the unit, mission and the safety of the public they would look like the following: either divorced or never married, score high on the MMPI in Social Introversion, score low on MMPI with an "excessive" amount of MMPI critical items; and finally scores high on the NEO Openness and subscales Ideas, Feelings, and Actions.^ Based on the results gleaned from the analysis in this study there seems to be several factors, within psychometric testing, that when taken together, will aid the evaluators in selecting only the highest quality operators in order to save resources and to help protect the public from unfortunate critical incidents which may adversely affect our health and safety.^

HPV vaccine coverage in Texas counties: An application of multilevel, small area estimation

Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

An outbreak of Multi-Drug Resistant Acinetobacter in the burn intensive care unit of a large tertiary care center

Risk factors for Multi-Drug Resistant Acinetobacter (MDRA) acquisition were studied in patients in a burn intensive care unit (ICU) where there was an outbreak of MDRA. Forty cases were matched with eighty controls based on length of stay in the Burn ICU and statistical analysis was performed on data for several different variables. Matched analysis showed that mechanical ventilation, transport ventilation, number of intubations, number of bronchoscopy procedures, total body surface area burn, and prior Methicillin Resistant Staphylococcus aureus colonization were all significant risk factors for MDRA acquisition. ^ MDRA remains a significant threat to the burn population. Treatment for burn patients with MDRA is challenging as resistance to antibiotics continues to increase. This study underlined the need to closely monitor the most critically ill ventilated patients during an outbreak of MDRA as they are the most at risk for MDRA acquisition.^

Ozone and fine particulate matter association with CVD and COPD emergency room visits in Harris County, Texas: Spatiotemporal analysis

This study represents a secondary analysis of the merging of emergency room visits and daily ozone and PM2.5. Although the adverse health effects of ozone and fine particulate matter have been documented in the literature, evidence regarding the health risks of these two pollutants in Harris County, Texas, is limited. Harris County (Houston) has sufficiently unique characteristics that analysis of these relationships in this setting and with the ozone and industry issues in Houston is informative. The objective of this study was to investigate the association between the joint exposure to ozone and fine particulate matter, and emergency room diagnoses of chronic obstructive pulmonary disease and cardiovascular disease in Harris County, Texas, from 2004 to 2009, with zero and one day lags. ^ The study variables were daily emergency room visits for Harris County, Texas, from 2004 to 2009, temperature, relative humidity, east wind component, north wind component, ozone, and fine particulate matter. Information about each patient's age, race, and gender was also included. The two dichotomous outcomes were emergency room visits diagnoses for chronic obstructive pulmonary disease and cardiovascular disease. Estimates of ozone and PM2.5 were interpolated using kriging, in which estimates of the two pollutants were predicted from monitoring data for every case residence zip code for every day of the six years, over 3 million estimates (one of each pollutant for each case in the database). ^ Logistic regressions were conducted to estimate odds ratios of the two outcomes. Three analyses were conducted: one for all records, another for visits during the four months of April and September of 2005 and 2009, and a third one for visits from zip codes that are close to PM2.5 monitoring stations (east area of Harris County). The last two analyses were designed to investigate special temporal and spatial characteristics of the associations. ^ The dataset included all ER visits surveyed by Safety Net from 2004 to 2009, exceeding 3 million visits for all causes. There were 95,765 COPD and 96,596 CVD cases during this six year period. A 1-μg/m3 increase in PM2.5 on the same day was associated with a 1.0% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses, a 0.4% increase in the odds of cardiovascular disease emergency room diagnoses, and a 0.2% increase in the odds of cardiovascular disease emergency room diagnoses on the following day. A 1-ppb increase in ozone was associated with a 0.1% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses on the same day. These four percentages add up to 1.7% of ER visits. That is, over the period of six years, one unit increase for both ozone and PM2.5 (joint increase), resulted in about 55,286 (3,252,102 * 0.017) extra ER visits for CVD or COPD, or 9,214 extra ER visits per year. ^ After adjustment for age, race, gender, day of the week, temperature, relative humidity, east wind component, north wind component, and wind speed, there were statistically significant associations between emergency room chronic obstructive pulmonary disease diagnosis in Harris County, Texas, with joint exposure to ozone and fine particulate matter for the same day; and between emergency room cardiovascular disease diagnosis and exposure to PM2.5 of the same day and the previous day. ^ Despite the small association between the two air pollutants and the health outcomes, this study points to important findings. Namely, the need to identify reasons for the increase of CVD and COPD ER visits over the course of the project, the statistical association between humidity (or whatever other variables for which it may serve as a surrogate) and CVD and COPD cases, and the confirmatory finding that males and blacks have higher odds for the two outcomes, as consistent with other studies. ^ An important finding of this research suggests that the number and distribution of PM2.5 monitors in Harris County - although not evenly spaced geographically—are adequate to detect significant association between exposure and the two outcomes. In addition, this study points to other potential factors that contribute to the rising incidence rates of CVD and COPD ER visits in Harris County such as population increases, patient history, life style, and other pollutants. Finally, results of validation, using a subset of the data demonstrate the robustness of the models.^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

A four-year record of UK'37- and TEX86-derived sea surface temperature estimates from sinking particles in the filamentous upwelling region off Cape Blanc, Mauritania

Lipid biomarker records from sinking particles collected by sediment traps are excellent tools to study the seasonality of biomarker production as well as processes of particle formation and settling, ultimately leading to the preservation of the biomarkers in sediments. Here we present records of the biomarker indices UK'37 based on alkenones and TEX86 based on isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs), both used for the reconstruction of sea surface temperatures (SST). These records were obtained from sinking particles collected using a sediment trap moored in the filamentous upwelling zone off Cape Blanc, Mauritania, at approximately 1300 water depth during a four-year time interval between 2003 and 2007. Mass and lipid fluxes are highest during peak upwelling periods between October and June. The alkenone and GDGT records both display pronounced seasonal variability. Sinking velocities calculated from the time lag between measured SST maxima and minima and corresponding index maxima and minima in the trap samples are higher for particles containing alkenones (14-59 m/d) than for GDGTs (9-17 m/d). It is suggested that GDGTs are predominantly exported from shallow waters by incorporation in opal-rich particles. SST estimates based on the UK'37 index faithfully record observed fluctuations in SST during the study period. Temperature estimates based on TEX86 show smaller seasonal amplitudes, which can be explained with either predominant production of GDGTs during the warm season, or a contribution of GDGTs exported from deep waters carrying GDGTs in a distribution that translates to a high TEX86 signal.