Joaquin De Juan

Donor oocyte dysmorphisms and their influence on fertilization and embryo quality

The aim of this study was to identify predictors of fertilization rate (FR) and embryo quality (EQ) in 126 donor women who underwent 160 intracytoplasmic sperm injection (ICSI) cycles. Main outcome measures were oocyte dysmorphisms (OD) [perivitelline space (normal/large), perivitelline debris (no/yes), oocyte shape (spherical/non-spherical), zona pellucida (normal/abnormal), first polar body morphology (normal/fragmented or irregular), cytoplasmic granularity (normal/excessive), cytoplasmic vacuoles (no/yes) and colour of cytoplasm (normal/dark)], semen source (ejaculated or testicular), donor age, number of days of stimulation, plasma oestradiol concentration (pg/ml) on the day of human chorionic gonadotrophin administration, FR and day 2 EQ. No significant predictors of fertilization were identified. However, the presence of a dark cytoplasm decreased by 83% the likelihood of obtaining good quality embryos (OR=0.17; 95% CI: 0.04-0.74). Oocytes with a larger than normal perivitelline space were associated with 1.8 times higher chance of having good quality embryos (OR=1.80; 95% CI: 1.15-2.80). Patients and ovarian stimulation characteristics evaluated here did not affect FR and EQ. ICSI technique may guarantee good FR in spite of OD; however, certain cytoplasmic anomalies at the oocyte level, such as a dark cytoplasm, could compromise subsequent embryo development.

Predicting seminal quality with artificial intelligence methods

Fertility rates have dramatically decreased in the last two decades, especially in men. It has been described that environmental factors, as well as life habits, may affect semen quality. Artificial intelligence techniques are now an emerging methodology as decision support systems in medicine. In this paper we compare three artificial intelligence techniques, decision trees, Multilayer Perceptron and Support Vector Machines, in order to evaluate their performance in the prediction of the seminal quality from the data of the environmental factors and lifestyle. To do that we collect data by a normalized questionnaire from young healthy volunteers and then, we use the results of a semen analysis to asses the accuracy in the prediction of the three classification methods mentioned above. The results show that Multilayer Perceptron and Support Vector Machines show the highest accuracy, with prediction accuracy values of 86% for some of the seminal parameters. In contrast decision trees provide a visual and illustrative approach that can compensate the slightly lower accuracy obtained. In conclusion artificial intelligence methods are a useful tool in order to predict the seminal profile of an individual from the environmental factors and life habits. From the studied methods, Multilayer Perceptron and Support Vector Machines are the most accurate in the prediction. Therefore these tools, together with the visual help that decision trees offer, are the suggested methods to be included in the evaluation of the infertile patient.

Localization of Choline Acetyltransferase in the Developing and Adult Turtle Retinas

Acetylcholine has important epigenetic roles in the developing retina. In this study, cells that expressed choline acetyltransferase (ChAT), the enzyme that synthesizes acetylcholine, were investigated in embryonic, postnatal, and adult turtle retinas by using immunofluorescence histochemistry. ChAT was present at stage 15 (S15) in cells near the vitreal surface. With the formation of the inner plexiform layer (IPL) at S18, ChAT‐immunoreactive (‐IR) cells were located in the inner nuclear layer (INL) and the ganglion cell layer (GCL). In the INL, presumed starburst amacrine cells were homogenous in appearance and formed a single row next to the IPL: This pattern was conserved until adulthood. In the GCL, however, there were multiple rows of ChAT‐IR cells early in development, and this high density of labeled cells continued during the embryonic stages, until around birth. The high density of ChAT‐IR cells in the GCL was due in part to a population of cells that expressed ChAT transiently. In postnatal stages and adult retinas, the presumed starburst amacrine ChAT‐IR cells formed two mirror‐like rows of homogenous cells on both borders of the IPL. Two cholinergic dendritic strata that were continuous with these cells were observed as early as S18, and their depths in the IPL were relatively stable throughout development. A third population of ChAT‐IR cells was observed toward the middle of the INL around S25 and persisted into adulthood. Finally, cells in the outer nuclear layer (ONL) were ChAT‐IR during the embryonic stages, were less immunoreactive during the postnatal stages, and were not immunoreactive in the adult retinas. J. Comp. Neurol. 420:512–526, 2000.

Brief Communication: Short- and Long-Term In Vivo Human Buccal-Dental Microwear Turnover

Buccal-dental microwear depends on the abrasive content of chewed foodstuffs and can reveal long-term dietary trends in human populations. However, in vivo experimental analyses of buccal microwear formation processes are scarce. Here, we report the effects of an abrasive diet on microwear rates in two adult volunteers at intervals of 8 days over a period of 1 month and document long-term turnover over 5 consecutive years in the same subjects under an ad libitum Mediterranean diet. Buccal microwear was analyzed on mandibular first molars using high-resolution replicas and scanning electron microscopy. Microwear turnover was assessed by recording the scratches lost and gained at each time point. Our results indicate that scratch formation on enamel surfaces increased with a highly abrasive diet compared to both pre-test and post-test ad libitum dietary controls. In the long-term analysis, scratch turnover was higher than expected, but no significant long-term trends in microwear density or length were observed, because microwear formation was compensated by scratch disappearance. Our results confirm that buccal microwear patterns on mandibular molars show a dynamic formation process directly related to the chewing of abrasive particles along with ingested food. In addition, the observed long-term stability of buccal microwear patterns makes them a reliable indicator of overall dietary habits.

Statistics of Optical Coherence Tomography Data From Human Retina

Optical coherence tomography (OCT) has recently become one of the primary methods for noninvasive probing of the human retina. The pseudoimage formed by OCT (the so-called B-scan) varies probabilistically across pixels due to complexities in the measurement technique. Hence, sensitive automatic procedures of diagnosis using OCT may exploit statistical analysis of the spatial distribution of reflectance. In this paper, we perform a statistical study of retinal OCT data. We find that the stretched exponential probability density function can model well the distribution of intensities in OCT pseudoimages. Moreover, we show a small, but significant correlation between neighbor pixels when measuring OCT intensities with pixels of about 5 ¿m. We then develop a simple joint probability model for the OCT data consistent with known retinal features. This model fits well the stretched exponential distribution of intensities and their spatial correlation. In normal retinas, fit parameters of this model are relatively constant along retinal layers, but varies across layers. However, in retinas with diabetic retinopathy, large spikes of parameter modulation interrupt the constancy within layers, exactly where pathologies are visible. We argue that these results give hope for improvement in statistical pathology-detection methods even when the disease is in its early stages.

Sensory adaptation as Kalman filtering: theory and illustration with contrast adaptation.

Sensory adaptation allows biological systems to adjust to variations in the environment. A recent theoretical work postulated that the goal of adaptation is to minimize errors in the performance of particular tasks. The proposed minimization was Bayesian and required prior knowledge of the environment and of the limitations of the mechanisms processing the information. One problem with that formulation is that the environment changes in time and the theory did not specify how to know what the current state of the environment is. Here, we extend that theory to estimate optimally the environmental state from the temporal stream of responses. We show that such optimal estimation is a generalized form of Kalman filtering. An application of this new Kalman-filtering framework is worked out for retinal contrast adaptation. It is shown that this application can account for surprising features of the data. For example, it accounts for the differences in responses to increases and decreases of mean contrasts in the environment. In addition, it accounts for the two-phase decay of contrast gain when the mean contrast in the environment rises suddenly. The success of this and related theories suggest that sensory adaptation is a form of constrained biological optimization.

Semen Parameters Can Be Predicted from Environmental Factors and Lifestyle Using Artificial Intelligence Methods

ABSTRACT Fertility rates have dramatically decreased in the last two decades, especially in men. It has been described that environmental factors as well as life habits may affect semen quality. In this paper we use artificial intelligence techniques in order to predict semen characteristics resulting from environmental factors, life habits, and health status, with these techniques constituting a possible decision support system that can help in the study of male fertility potential. A total of 123 young, healthy volunteers provided a semen sample that was analyzed according to the World Health Organization 2010 criteria. They also were asked to complete a validated questionnaire about life habits and health status. Sperm concentration and percentage of motile sperm were related to sociodemographic data, environmental factors, health status, and life habits in order to determine the predictive accuracy of a multilayer perceptron network, a type of artificial neural network. In conclusion, we have developed an artificial neural network that can predict the results of the semen analysis based on the data collected by the questionnaire. The semen parameter that is best predicted using this methodology is the sperm concentration. Although the accuracy for motility is slightly lower than that for concentration, it is possible to predict it with a significant degree of accuracy. This methodology can be a useful tool in early diagnosis of patients with seminal disorders or in the selection of candidates to become semen donors.

Diet-related buccal dental microwear patterns in Central African Pygmy foragers and Bantu-speaking farmer and pastoralist populations.

Pygmy hunter-gatherers from Central Africa have shared a network of socioeconomic interactions with non-Pygmy Bantu speakers since agropastoral lifestyle spread across sub-Saharan Africa. Ethnographic studies have reported that their diets differ in consumption of both animal proteins and starch grains. Hunted meat and gathered plant foods, especially underground storage organs (USOs), are dietary staples for pygmies. However, scarce information exists about forager–farmer interaction and the agricultural products used by pygmies. Since the effects of dietary preferences on teeth in modern and past pygmies remain unknown, we explored dietary history through quantitative analysis of buccal microwear on cheek teeth in well-documented Baka pygmies. We then determined if microwear patterns differ among other Pygmy groups (Aka, Mbuti, and Babongo) and between Bantu-speaking farmer and pastoralist populations from past centuries. The buccal dental microwear patterns of Pygmy hunter-gatherers and non-Pygmy Bantu pastoralists show lower scratch densities, indicative of diets more intensively based on nonabrasive foodstuffs, compared with Bantu farmers, who consume larger amounts of grit from stoneground foods. The Baka pygmies showed microwear patterns similar to those of ancient Aka and Mbuti, suggesting that the mechanical properties of their preferred diets have not significantly changed through time. In contrast, Babongo pygmies showed scratch densities and lengths similar to those of the farmers, consistent with sociocultural contacts and genetic factors. Our findings support that buccal microwear patterns predict dietary habits independent of ecological conditions and reflect the abrasive properties of preferred or fallback foods such as USOs, which may have contributed to the dietary specializations of ancient human populations.

Morphological changes of short-wavelength cones in the developing S334ter-3 transgenic rat

The S334ter-3 rat is a transgenic model of retinal degeneration (RD) developed to express a rhodopsin mutation similar to that found in human retinitis pigmentosa. Due to this advantage over other models of RD, a few retina transplant studies have been reported on this animal model. Currently, no information is available on cone photoreceptor changes that occur in the S334ter RD model. In this study, we investigated the effect of RD on the morphology, distribution, and synaptic connectivity of short-wavelength cones (S-cones) during development of S334ter-3 rat retinas. At P21 RD retinas, the outer-nuclear layer was significantly narrower, while S-cones showed shortening of their segments and axons compared to control retinas. From P90 onward, S-opsin-immunoreactive cells appeared at the outer margin of the inner-nuclear layer of RD retinas. Double-labelling experiments showed these cells contained recoverin and cone arrestin. Furthermore, ultra-structure study showed that synaptic ribbons are conserved in the S-cone at P180 RD retinas. Although cell density of S-cones significantly dropped after P90, survival rates depended on the retinal region. Overall, the S334ter-3 RD model shows hallmarks of cone remodelling due to photoreceptor degeneration.

Characterization of the lectin binding pattern in human spermatozoa after swim-up selection

Capacitation is characterized by a hyperactivated pattern of sperm motility. The acquisition of highly motility is present in the early stages of capacitation. Sperm progressive motility is one of the most important parameters for determining the suitability of semen for processing. However, previous studies have shown that some sperm showing good motility have membrane damage. The aim of our study was to characterize the lectin staining pattern on the sperm plasma membrane of unselected and selected human sperm of normozoospermic donors. Sperm selection was performed by the swim-up technique. Fourteen samples from healthy consenting donors classified as normozoospermic according to the World Health Organization were used. We observed changes in the distribution of the carbohydrate residues after the swim-up selection. With Triticum vulgaris, the most abundant pattern was dotted labeling all over the head plasma membrane in the unselected sperm. However, this lectin was distributed homogenously over the acrosomal region after selection. With Arachis hypogaea, the most abundant pattern in fresh sperm was a highly stained acrosomal region. In the highly motility sperm population, the most frequent pattern was dotted fluorescence on the acrosomal region and a highly stained equatorial segment. Meanwhile, with the Aleuria aurantia and Canavalia ensiformis lectins, the most representative patterns were the same before and after the swim-up selection. Our data indicate that modifications which occur in carbohydrate residues during swim-up selection could be important for the regulation of progressive motility and prepare the sperm for capacitation.