Linear Model Approach Research Articles

Correlation between diminished vagal tone and somatic dysfunction severity in very and extremely low birth weight preterm infants assessed with frequency spectrum heart rate variability and salivary cortisol.

Osteopathic manipulative treatment (OMT) is evolving in the neonatal intensive care unit (NICU) setting. Studies showed its efficacy in length of stay and hospitalization costs reduction. Moreover, it was suggested that OMT has a modulatory effect on the preterm infants’ autonomic nervous system (ANS), influencing saturation and heart rate. Even if OMT is based on the palpatory examination of the somatic dysfunctions (SD), there are controversies about its identification and clinical relevance. The objective of this study was to evaluate the inter-rater reliability, clinical characteristics, and functional correlation of the SD Grade score with the heart rate variability (HRV) and the salivary cortisol (sCor) using a multivariate linear model approach. To evaluate those features, we implemented an ad hoc SD examination for preterm infants that was performed by 2 trained osteopaths. It was based on the new variability model of SD that includes an SD Grade assessment procedure. The ANS features were assessed by frequency parameters of HRV studying high frequency (HF), low frequency (LF), and HF/LF, whereas sCor was tested with a radioimmunoassay. The ANS assessment was standardized and performed before SD testing. Sixty-nine premature infants were eligible. SD Grade showed excellent concordance between the blinded raters. Using SD Grade as a grouping variable, the infants presented differences in GA, Apgar, pathological findings, length of stay, and ventilatory assistance. In our multivariate model, HF, LF, and LF/HF resulted linearly correlated with SD Grade. Instead, sCor presented a linear correlation with 5’ Apgar and respiratory distress syndrome but not with SD Grade. SD Grade was in line with the natural history of the underdevelopment due to prematurity. Our models indicate that the cardiac vagal tone is linearly related with SD Grade. This finding may improve the multidisciplinary decision making inside NICU and the management of modifiable factors, like SD, for cardiac vagal tone regulation.

The longitudinal biomonitoring of residents living near the waste incinerator of Turin: Polycyclic Aromatic Hydrocarbon metabolites after three years from the plant start-up

The waste-to-energy (WTE) incinerator plant located in the Turin area (Italy) started to recover energy from the combustion of municipal solid waste in 2013. A health surveillance program was implemented to evaluate the potential health effects on the population living near the plant. This program included a longitudinal biomonitoring to evaluate temporal changes of some environmental pollutants, including polycyclic aromatic hydrocarbons (PAHs), in residents living in areas near the Turin incinerator (exposed group, E) compared to those observed in subjects living far from the plant (not exposed group, NE). Ten monohydroxy-PAHs (OH-PAHs), consisting in the principal metabolites of naphthalene, fluorine, phenanthrene, and pyrene, were analyzed in urines collected from the E and NE subjects after one (T1) and three years (T2) of plant activity and compared with those determined in the same cohort established before the plant start-up (T0). Spearman correlation analysis was undertaken to explore possible associations between OH-PAHs and personal characteristics, lifestyle variables, and dietary habits. A linear mixed model (LMM) approach was applied to determine temporal trends of OH-PAHs observed in the E and NE subjects and to evaluate possible differences in trend between the two groups. Temporal trends of OH-PAHs determined by LMM analysis demonstrated that, at all times, the E group had concentrations lower than those assessed in the NE group, all other conditions being equal. Moreover, no increase in OH-PAH concentrations was observed at T1 and T2 either in E or in NE group. Significant positive correlations were found between all OH-PAHs and smoking habits. Regarding variables associated to outdoor PAH exposure, residence near high traffic roads and daily time in traffic road was positively correlated with 1-hydroxynaphthalene and 1-hydroxypyrene, respectively. In conclusion, no impact of the WTE plant on exposure to PAHs was observed on the population living near the plant.

Land Use Regression modelling of airborne microbial markers in the vicinity of livestock farms: evaluation of stepwise linear regression and random forest modelling approaches

Land Use Regression modelling of airborne microbial markers in the vicinity of livestock farms: evaluation of stepwise linear regression and random forest modelling approaches

Evaluation of approaches to estimate scapular kinematics during baseball pitching

ABSTRACT Biomechanical analyses of pitching possess limitations in accurately measuring dynamic scapular orientation and are thus unable to distinguish between glenohumeral and scapulothoracic contributions to global shoulder motion. In lieu of direct measurement, several methods to estimate scapular kinematics have been developed. This study evaluated the ability of the linear model and the double calibration acromion marker cluster (D-AMC) approaches to estimate scapular kinematics throughout a full-speed pitching motion. Each approach’s estimates were compared against scapulothoracic range of motion limits established in a non-pitching biplane fluoroscopy study involving various functional arm movements that approximate physiological limits of scapular motion. Fourteen healthy collegiate pitchers participated. Motion capture measured upper extremity joint kinematics during full-speed fastball pitches. Linear model and D-AMC approaches estimated scapulothoracic kinematics during each pitch. Linear model estimates of scapulothoracic kinematics were largely within established physiological limits on each scapular axis of motion while D-AMC estimates exceeded fluoroscopy-established bounds for more subjects and by larger, less physiologically plausible amounts. These findings demonstrate that the linear model outperforms the D-AMC and suggest that it is a viable approach to estimate scapular kinematics during pitching. Finally, these results offer additional evidence to support the accepted pattern of scapular kinematics during pitching.

Modeling of surface sediment concentration in the Doce River basin using satellite remote sensing

Surface sediment concentration (SSC) is linked to several problems related to water quality and its monitoring is costly because of the required fieldwork and laboratory analyses. Thus, sediment measurements are often sporadic, punctual, and performed during a short period. Orbital remote sensing allows the monitoring of SSC along the river channel permitting continuous and spatial information. This work had two objectives: (1) to model the surface concentration of sediments in the main channel of the Doce river using data from Multispectral Instrument (MSI)/Sentinel 2 and Operational Land Imager (OLI)/Landsat 8 satellite sensors; and (2) to compare different linear modeling approaches to select the best variables for SSC monitoring. For comparison with actual field data, we used mean SSC measurements in 14 sediment gauge stations from 2013 to 2020. Reflectance data of the MSI/Sentinel 2 and OLI/Landsat 8 satellites bands and spectral indices related to the monitoring of water resources were used as explanatory variables. Simple and multiple linear regression models (SLR and MLR), least absolute shrinkage and selection operator (LASSO), and Elastic Net regression were used to predict the SSC. The near-infrared band images from both MSI/Sentinel 2 and OLI/Landsat 8 satellites showed a strong linear relationship with the SSC. Multiple linear regression, LASSO and Elastic Net regressions showed good performance for SSC prediction. Sediment flow maps show an SSC reduction in the Doce river channel in recent years, indicating that part of the material from the Fundão tailings dam rupture may have been transported through sediment resuspension and transport processes.

Use of geostatistical models to evaluate landscape and stream network controls on post‐fire stream nitrate concentrations

AbstractForested watersheds provide many ecosystem services, such as the filtration of sediment, pollutants, and nutrients, which are increasingly threatened by wildfire. For example, stream nutrient concentrations often increase following wildfire and can remain elevated for decades, making downstream waters susceptible to eutrophication. We investigated the drivers of persistent elevated stream nutrients, specifically nitrate (NO3−), in nine watersheds that were burned 16 years prior by the Hayman fire, Colorado, USA. We evaluated the ability of multiple linear regression and spatial stream network modeling approaches to predict observed concentrations of the biologically active solute NO3− and the conservative solute sodium (Na+) which serves as a partial control. Specifically, we quantified the degree to which landscape and stream network characteristics predict stream solute concentrations. Stream Na+ exhibited strong spatial autocorrelation that was primarily controlled by topography and hydrology. In contrast, stream NO3− had higher spatial variability and was inversely correlated to vegetation cover, measured as mean normalized differenced moisture index (NDMI). Spatially heterogeneous wildfire behaviour left intact forest patches interspersed with high burn severity patches dominated by shrubs and grasses which contributes to the spatial variability in stream NO3− concentrations. Post‐fire vegetation also interacts with watershed structure to influence stream NO3− patterns. For example, severely burned convergent hillslopes in headwaters positions were associated with the highest stream NO3− concentrations due to the high proportional influence of hillslope water in these locations. Our findings suggest that targeted reforestation in severely burned convergent hillslopes in headwater positions may enhance the recovery of stream NO3− concentrations to pre‐fire levels.

Modeling the Impacts of Positive Interaction Frequency on Subjective Trust in an Autonomous Agent: A Linear Mixed Model Approach

With the advancement of technology, automation has rapidly embedded itself in many parts of daily function. As a result, it is imperative to understand the processes in which individuals use and develop trust with automation. Specifically, how this relationship is formed and how it evolves over time. Previous research has theorized that the frequency and the positivity of interaction with automated systems is a prominent influencer in the creation of trust. In the present study, we examined subjective trust ratings when participants performed a pattern recognition task with an autonomous agent which varied in positivity and number of interactions. Results showed that positivity amongst other parameters were significant predictors of subjective trust when analyzed using linear mixed models.

Toward Sustainable Water: Prediction of non-revenue water via Artificial Neural Network and Multiple Linear Regression modelling approach in Egypt

This research paper studied the parameters affecting the non-revenue water in Egypt. The neural model was developed to forecast the NRW ratio before and after network rehabilitation using main parameters and statistical data for various measured district metered areas (DMAs) in Egypt. The non-revenue water (NRW) ratio is a parameter of significant concern for the water distribution system's performance evaluation. Therefore, NRW ratio parameter evaluation requires analysis of variables that influence the NRW ratio. This study aims to offer findings that will lay the basis for sustainable water resources management in Egypt. Consequently, a comprehensive evaluation of water distribution systems and parameters affecting NRW was conducted. The predictive models were developed using the historical data of the water company for various measured district metered areas (DMAs) in Egypt. The automated meta-models were developed at steady-state and over a prolonged period using a series of principles, rules, and constraints. It was based on multi hidden units of feed-forward neural networks trained by the back-propagation algorithm. Thus, the iterative methods of weight adjustment and activation function of Levenberg-Marquardt was used. Two scenarios were assumed, one that has complete data of the DMA investigated while the other assumed total lack of knowledge. Therefore, four models were built to forecast multiple parameters affecting the percentage of non-revenue water. However, three models were combined to reach the final NRW ratio with no historical data. An optimal number of neurons was determined to be 10. Each model result was tested against numeral statistical indicators showing a different level of accuracy. The model results showed high accuracy in NRW final estimation. The performance indicators (i.e., RMSE, MAE, and correlation) also showed that the machine-learning algorithm better identifies complex relationships between different parameters. The models developed in this research can be applied to other DMAs in Egypt. Overall, these findings indicate that the machine-learning model may be adequate for water companies seeking immediate, cost-effective and long-term improvement of their water distribution systems. Results can provide the basis for decision-makers to reduce costs after applying the rehabilitation process upon any new DMA created. This study presents a modelling approach that provides the best prediction of non-revenue water. It allows the use of a model that enables the accurate projection of NRW ratio and approximating NRW in Egypt and elsewhere in similar countries around the world. Thus, it will help decision-makers enhance the overall NRW ratio strategically across Egypt and elsewhere worldwide.

Diagnostic test accuracy of sentinel lymph node biopsy in squamous cell carcinoma of the oropharynx, larynx, and hypopharynx: A systematic review and meta-analysis.

The aim of this meta-analysis was to determine the diagnostic test accuracy of sentinel lymph node biopsy (SLNB) in patients with oropharyngeal, laryngeal, and hypopharyngeal squamous cell carcinoma (SCC). For this purpose, MEDLINE, EMBASE, and Web of Science were searched from inception to March 8, 2022. Included were studies evaluating diagnostic test accuracy of SLNB to identify cervical lymph node metastases with elective neck dissection or follow-up as reference. A bivariate generalized linear mixed model approach was used for the meta-analysis. Nineteen studies were eligible, evaluating 377 cases in total. The pooled estimates of sensitivity and negative predictive value were 0.93 (95% CI: 0.86-0.96) and 0.97 (95% CI: 0.94-0.98), respectively. The excellent accuracy of SLNB justifies a place in the diagnostic workup of patients with larynx and pharynx SCC. Randomized trials are required to demonstrate oncologic safety and benefits on treatment related morbidity and quality of life when omitting elective neck treatment based on SLNB.

Empirical Power and Type I Error of Covariate Adjusted Nonparametric Methods

In clinical trials, practitioners collect baseline covariates for enrolled patients prior to treatment assignment. In recent guidance from Food and Drug Administration and European Medicines Agency, regulators encourage practitioners to utilize baseline information at the analysis stage to improve the efficiency. However, the current guidance focused on linear or non-linear modelling approach. Nonparametric statistical methods were not focus in the guidance. In this article, we conducted simulations of several covariate-adjusted nonparametric statistical tests. Wilcoxon rank sum test is a widely used method for non-normally distributed response variables between two groups but its original form does not take into account the possible effect of covariates. We investigated the empirical power and the type I error of the Wilcoxon type test statistics under various settings of covariate adjustments commonly encountered in clinical trials. In addition to Wilcoxon type test statistics, we also compared simulation results to more advanced nonparametric test statistics such as the aligned rank test and Jaeckel, Hettmansperger-McKean test. The simulation result shows when there is covariate imbalance, applying Wilcoxon rank sum test without adjusting the covariates will become problematic. The survey of the covariate adjustments for varies tests under investigation gives brief guidance to trial practitioners in real practice, particularly whose baseline covariates are not well balanced.

MAPEAMENTO ASSOCIATIVO PARA PRODUTIVIDADE DE GRÃOS EM GERMPLASMA EXÓTICO DE SOJA SOB ALTAS TEMPERATURAS

ABSTRACT Soybeans are among the world’s main crops because they are excellent sources of proteins, micronutrients, and oil. Considering that abiotic stress affects agribusiness, resulting in losses, the grain yield of the crop must be maintained even at high temperatures. In this context, the objective of this study was to select markers related to soybean yield assessed under high temperatures, using associative mapping. The mapping population included 80 soybean PIs and 15 controls. For phenotyping, genotypes were evaluated at high temperatures in an experiment conducted in Teresina (in the state of Piauí) and four characters of interest for agronomy were evaluated: height of the plant when mature, agronomic value, 100-seed weight, and grain yield. Genotyping was carried out using the Affymetrix Platform (180 K Axiom® Soybean Genotyping Array), and the imbalance in the connection between pairs of markers was calculated through the coefficient of determination using the fast permutation test. The analysis of the association between markers and the phenotype of interest was carried out using a generalized linear model approach, including phenotyping data, SNP markers, and information on population structure. The results revealed that 34.06% of loci showed a significant linkage disequilibrium (p < 0.001), and 16 significant associations were found for the four characters related to heat tolerance. These associations can aid breeders that aim to incorporate high temperature tolerance in programs of soybean genetic improvement via selection assisted by markers.

Validation of machine learning approaches for estimating wheel fatigue loads at the front suspension of a race car during track driving

AbstractThe wheel loads of a race car have been estimated in view of structural durability assessments. First, the front left double‐wishbone suspension of a rear‐wheel‐drive race vehicle has been instrumented; then, wheel loads have been estimated by means of four approaches: (i) a geometric matrix (GM) method, (ii) a feedforward neural network (FNN) approach applied to the fully instrumented suspension (FIS), (iii) a FNN approach involving a reduced number of sensors (the partially instrumented suspension (PIS)) and an inertial measurement unit (IMU), and (iv) a linear modeling approach (LM). After having trained the FNNs by using suspension signals acquired in a racetrack as inputs and related tire forces measured with the GM method as targets, the FNN‐based methods have been validated on three different racetracks by comparing the estimated loads with those estimated by means of the GM method. According to the results achieved, the FNN approaches are effective for the estimation of the wheel forces.

Sleep behavior and training load in adolescent elite basketball players during COVID-19 pandemic development

ABSTRACT The COVID-19 pandemic caused strong restrictions in organized sports. Specifically, adolescent athletes, whose daily routine is usually determined by school and practice schedules, experienced a sudden lifestyle change. The aim of this study was to examine sleep and training patterns of German elite adolescent basketball players (N = 115, 15.70 ± 1.22 years, female = 32.17%) during different phases of the 2021 lockdown. Sleep and training behavior were documented by a subjective monitoring over 10 days at three different lockdown phases in February, April, and June/July. A linear mixed model approach was conducted for the statistical analyses. Sleep duration and time in bed decreased between phase 1 (prohibition of organized sports) and phase 3 (normal training conditions), while sleep efficiency and quality increased. There was no change in training duration over time, but in training intensity, which peaked in the third phase. This study contains meaningful evidence to analyze the lockdown-related return to practice process. Athletes were able to maintain training duration with alternative protocols during pandemic conditions. Interestingly, athletes slept less under non-lockdown conditions, but reported a better sleep quality. It is recommended to consider athletes’ individual preferences when planning training and recovery schedules.

Impact of medications, mood state, and electrode placement on ECT outcomes in treatment-refractory psychosis

BackgroundTreatment-refractory psychosis (TRP) is a significant clinical challenge. While clozapine is frequently effective, alternate or augmentation strategies are often necessary. Evidence supports effectiveness of electroconvulsive therapy (ECT), but questions remain about optimal treatment parameters and impacts of concomitant pharmacotherapy. Objective/Hypothesis: To analyze the impact of clozapine, anticonvulsant medication, mood state, and ECT electrode placement on outcomes in TRP. We hypothesized that ECT would lead to greater reduction in positive symptoms, particularly in patients receiving clozapine. MethodsRetrospective study in a tertiary TRP program. The Positive and Negative Syndrome Scale (PANSS) was used for clinical outcomes, with positive subscore as primary outcome. Clinical and ECT data were analyzed using a linear modelling approach, controlling for relevant covariates. ResultsA total of 309 patients were included. ECT plus clozapine associated with greater improvement in positive, general, and total symptoms than ECT alone. ECT associated with greater improvement in negative symptoms in depressed patients. Bifrontal placement was mostly equivalent to bitemporal, with greater reduction of positive symptoms in patients receiving clozapine, and associated with lower electrical dose in patients on anticonvulsants. Clozapine increased seizure duration, while anticonvulsants decreased it. Anticonvulsant use in ECT patients associated with equivalent to slightly improved symptom reduction. ConclusionsECT's benefit in TRP may be greatest in patients receiving clozapine. ECT can improve negative symptoms in depressed TRP patients. Bifrontal placement is effective in TRP. Clozapine and anticonvulsants have opposite effects on seizure duration, but anticonvulsants may not adversely affect clinical outcomes of ECT for TRP.

Least Squares and Robust Rank-Based Double Bootstrap Analyses for Time-Series Intervention Designs.

Time-series intervention designs that include two or more phases have been widely discussed in the healthcare literature for many years. A convenient model for the analysis of these designs has a linear model part (to measure changes in level and trend) plus a second part that measures the random error structure; the error structure is assumed to follow an autoregressive time-series process. Traditional generalized linear model approaches widely used to estimate this model are less than satisfactory because they tend to provide substantially biased intervention tests and confidence intervals. We describe an updated version of the original double bootstrap approach that was developed by McKnight et al. (2000) to correct for this problem. This updated analysis and a new robust version were recently implemented in an R package (McKean & Zhang, 2018). The robust method is insensitive to outliers and problems associated with common departures from normality in the error distribution. Monte Carlo studies as well as published data are used to demonstrate the properties of both versions. The R code required to perform the analyses is provided and illustrated.

Assessment of approaches to estimate scapular orientation in children with brachial plexus birth injury

BackgroundChallenges in measuring dynamic scapular orientation limit assessment of scapulothoracic and glenohumeral contributions to shoulder function in children with brachial plexus birth injury (BPBI). Double calibration acromion marker cluster (D-AMC) and linear model approaches have been validated to estimate scapular motion in healthy adults, but neither has been evaluated in BPBI. Research questionAre the linear model and D-AMC approaches able to accurately estimate scapular orientation in children with BPBI at functional arm postures? MethodsSeventeen children with BPBI positioned their affected limbs in 11 static positions while their segment orientations were measured with motion capture. Linear model and D-AMC estimates of scapular orientation were compared against palpation at six of the static positions with functional relevance to BPBI using a three-way repeat measures ANOVA and a comparison of root mean square errors (RMSE) against literature AMC values for healthy adults. ResultsThe D-AMC was similar to palpation across all positions and scapular axes while the linear model differed from palpation in a few instances. RMSEs of the D-AMC (3.7–14.8°) and particularly the linear model (4.6–24.8°) were generally at or beyond the upper range of past AMC analyses on healthy adults (1.6–14.2°), especially for more complex, multiplanar arm postures. Despite the D-AMC outperforming the linear model, this approach still produced clinically meaningful (>10°) errors for roughly (12.7–22.5%) of subjects. SignificanceCurrent methods for estimating dynamic scapular orientation remain less than ideal for BPBI. Use of the D-AMC may be appropriate to gain broad insights into general dynamic scapulothoracic and glenohumeral function; however, given their potential for producing clinically meaningful errors, the D-AMC and linear model are not recommended for diagnostic purposes or outcomes assessment on an individual patient basis unless their patient-specific accuracy has been evaluated and confirmed prior to use.

Preconception care utilization and associated factors among reproductive age women in Mizan-Aman town, Bench Sheko zone, Southwest Ethiopia, 2020. A content analysis.

BackgroundPreconception care is highly important in reducing a number of adverse pregnancy outcomes and helps to improve maternal health. Preconception care optimizes women’s health and improves pregnancy outcomes. It is a cost-effective first-line preventive strategy for birth defects. However, preconception care utilization in Ethiopia was very low. Studies on these issues are limited in Ethiopia in general and in Mizan-Aman town in particular.ObjectiveTo assess preconception care utilization and associated factors among reproductive age women in Mizan-Aman town, Bench-Sheko Zone, Southwest Ethiopia.MethodsA community based cross-sectional study design was employed from April 16 to May 26, 2020 in Mizan-Aman town. The total study participants were 624 reproductive age women. Data were collected by using pre-tested interviewer administered questionnaires and entered into Epi-data version 3.1 then exported to STATA version 14 and analyzed accordingly. Univeriate and Bivariable analysis was done by analysis of variance (ANOVA) and independent t-test. Multivariable statistical analysis using generalized linear regression model (GLM) approach was used to classify factors of preconception care utilization. Since our response variable is measured in terms of count variable, we used a Poisson regression model with a log link function. Finally, Statistical significance between dependent and independent variables were assessed by odds ratios and 95% confidence intervals.ResultsOverall, 28.6% of the women receipt atleast one item of preconception care while only 1.5% were taken the whole recommended components of preconception care services. The most common item received in the study area was taking micronutrient supplementation (18.5%). Age of women, educational status, husbands educational status, husbands occupation, wealth status, distance from the health facility, waiting time to get services, planning to pregnancy, age at first pregnancy, previous ANC use, Previous PNC use, adverse pregnancy experience, women’s knowledge of preconception care, and attitude on preconception care were determinants of preconception service utilization.ConclusionsPreconception care component utilization was lower as compare with recommended service with different disparities. Multipurpose tailored strategies which incorporate a woman with no formal education, poor knwledge on preconception care,never take maternal services previously and distant from health facility could improve preconception care service utilization. Advocative strategies on preconception care component and planning pregnancy may elicite more women to use the services of preconception care.

Prediction of acute toxicity of pesticides for Americamysis bahia using linear and nonlinear QSTR modelling approaches

Globally, pesticides are toxic substances with wide applications. However, the widespread use of pesticides has received increasing attention from regulatory agencies due to their various acute and chronic effects on multiple organisms. In this study, Quantitative Structure-Toxicity Relationship (QSTR) models were established using Multiple Linear Regression (MLR) and five Machine Learning (ML) algorithms to predict pesticide toxicity in Americamysis bahia. The most influential descriptors included in the MLR model are RBF, JGI2, nCbH, nRCOOR, nRSR, nPO4 and ‘Cl-090’, with positive contributions to the dependent variable (negative decimal logarithm of median lethal concentration at 96-h). The Random Forest (RF) regression model was superior amongst the five ML models. We observed higher values of R2 (0.812) and lower values of RMSE (0.595) and MAE (0.462) in the cross-validation training set and external validation set. Similarly, this study had a high level of fitness and was internally robust and externally predictive compared to models presented in similar studies. The results suggest that the developed QSTR models are suitable for reliably predicting the aquatic toxicity of structurally diverse pesticides and can be used for screening, prioritising new pesticides, filling data gaps and overcoming the limitations of in vivo and in vitro tests.

Neural substrates of saccadic adaptation: Plastic changes versus error processing and forward versus backward learning

Previous behavioral, clinical, and neuroimaging studies suggest that the neural substrates of adaptation of saccadic eye movements involve, beyond the central role of the cerebellum, several, still incompletely determined, cortical areas. Furthermore, no neuroimaging study has yet tackled the differences between saccade lengthening (“forward adaptation”) and shortening (“backward adaptation”) and neither between their two main components, i.e. error processing and oculomotor changes. The present fMRI study was designed to fill these gaps. Blood-oxygen-level-dependent (BOLD) signal and eye movements of 24 healthy volunteers were acquired while performing reactive saccades under 4 conditions repeated in short blocks of 16 trials: systematic target jump during the saccade and in the saccade direction (forward: FW) or in the opposite direction (backward: BW), randomly directed FW or BW target jump during the saccade (random: RND) and no intra-saccadic target jump (stationary: STA). BOLD signals were analyzed both through general linear model (GLM) approaches applied at the whole-brain level and through sensitive Multi-Variate Pattern Analyses (MVPA) applied to 34 regions of interest (ROIs) identified from independent 'Saccade Localizer’ functional data. Oculomotor data were consistent with successful induction of forward and backward adaptation in FW and BW blocks, respectively. The different analyses of voxel activation patterns (MVPAs) disclosed the involvement of 1) a set of ROIs specifically related to adaptation in the right occipital cortex, right and left MT/MST, right FEF and right pallidum; 2) several ROIs specifically involved in error signal processing in the left occipital cortex, left PEF, left precuneus, Medial Cingulate cortex (MCC), left inferior and right superior cerebellum; 3) ROIs specific to the direction of adaptation in the occipital cortex and MT/MST (left and right hemispheres for FW and BW, respectively) and in the pallidum of the right hemisphere (FW). The involvement of the left PEF and of the (left and right) occipital cortex were further supported and qualified by the whole brain GLM analysis: clusters of increased activity were found in PEF for the RND versus STA contrast (related to error processing) and in the left (right) occipital cortex for the FW (BW) versus STA contrasts [related to the FW (BW) direction of error and/or adaptation]. The present study both adds complementary data to the growing literature supporting a role of the cerebral cortex in saccadic adaptation through feedback and feedforward relationships with the cerebellum and provides the basis for improving conceptual frameworks of oculomotor plasticity and of its link with spatial cognition.

Pojava volonje Hexanchus griseus (Bonnaterre, 1788.) u Tršćanskom zaljevu (sjeverni Jadran) s posebnim osvrtom na povijesne i nove zapise u Jadranskom moru

A specimen of a sixgill bluntnose shark, Hexanchus griseus (Bonnaterre, 1788), was caught 1.5 NM north of Cape Ronek (Izola, Slovenia) in a fishing net for large-sized flatfish (such as turbot) on 28 January 2018. Three other older cases of catch of sixgill bluntnose sharks were recorded in Slovenia and the Gulf of Trieste. Among these, the finding of the specimen in the Lagoon of Marano and Grado is unusual although there are reported cases of sixgill bluntnose sharks in rivers. An analysis of the available data on the bluntnose sixgill shark in the Adriatic Sea, obtained from different published papers, social media and other sources, was done to understand whether the occurrence of H. griseus in the northern Adriatic differs from other parts. A generalised linear model (GLM) approach revealed that larger specimens are more frequently sighted across the Adriatic Sea, while in the Northern Adriatic part, significantly smaller specimens (juveniles) were recorded in comparison to the Central and Southern parts. It seems that the bluntnose sixgill shark is not in conjunction with a common large shark decreasing trend across the whole Mediterranean Sea.