Evaluation of Polyphenolic Composition and Antimicrobial Properties of Sanguisorba officinalis L. and Sanguisorba minor Scop.

The most widespread Sanguisorba species are Sanguisorba officinalis L. and Sanguisorba minor Scop. which are also found in the Romanian flora and classified as medicinal plants because of hemostatic, antibacterial, antitumor, antioxidant and antiviral activities. This study aimed to characterize and compare Sanguisorba species in order to highlight which species is more valuable according to phenolic profile and antimicrobial activity. Based on high-performance liquid chromatography equipped with photodiode array detection and mass spectrometry (electrospray ionization) (HPLC-DAD-MS (ESI+)) analysis, it was evident that the ethanol extract obtained from the leaves of S. minor Scop. contains the highest content of phenolic compounds at 160.96 mg/g p.s., followed by the flower and root extract (131.56 mg/g dw and 121.36 mg/g dw, respectively). While in S. officinalis, the highest amount of phenols was recorded in the root extract (127.06 mg/g), followed by the flower and leaves extract (102.31 mg/g and 81.09 mg/g dw, respectively). Our results show that among the two species, S. minor Scop. is richer in phenolic compounds compared with the S. officinalis L. sample. In addition, the antimicrobial potential of each plant organ of Sanguisorba species was investigated. The ethanol extract of S. minor Scop. leaves exhibited better antibacterial activity against all of the bacteria tested, especially on Staphylococcus aureus, with an inhibition zone of 15.33 ± 0.83 mm. Due to the chemical composition and antimicrobial effect, the Sanguisorba species can be used as food supplements with beneficial effects on human health.

The dynamic changes in the pattern of liver function tests in pregnant obese women.

Obesity is an important problem in healthcare regarding gestating women. The objective of the present study was to highlight the impact that obesity has on the hepatic function in pregnant women by comparing the functional tests used in current practice. In addition, the aim was to identify possible predictors of liver damage by analyzing specific anthropometric data. The present study was descriptive, observational, retrospective, and based on the observation sheets found in the database of the Institute for the Health of the Mother and Child, the Obstetrics Gynecology Department of Polizu Hospital. Patients who presented for consultation in each trimester of pregnancy were included in the study. Demographic data taken into account included age, body mass index (BMI), provenance environment, anthropometric data: Abdominal circumference and the complete set of paraclinical data from which we extracted these specific liver tests: Aspartate aminotransferase (AST), alanine transferase (ALT), direct bilirubin (BD), serum albumin and gamma-glutamyl transferase (GGT). The present study included 157 patients divided into two groups, distributed as follows: Group A: 66 obese pregnant women (BMI >25 kg/m2) and group B: 91 patients with normal weight (BMI <25 kg/m2). Measurement of serum ALT and AST were the most useful tests for routine diagnosis of liver disease. The effects of pregnancy on serum levels of ALT and AST are controversial. In some studies, there was a slight increase in ALT and AST during the second and third trimesters, a fact confirmed by our study, albeit the result was not statistically significant Most published studies claim that serum ALT and AST levels do not change during pregnancy. In conclusion, obesity during pregnancy does not drastically influence liver function. However, patients with greater abdominal circumference are prone to developing minor hepatic cytolysis syndrome during the gestation period. The liver functional tests described in the aforementioned groups agree with the results provided by the specialized studies.

Obesity and pregnancy.

Introduction: Obesity is the most frequent metabolic disturbance that can target women of reproductive age, among other population groups, and when obese pregnant women become patients, it represents a serious risk factor for both mother and fetus. Aim: The aim of this study is to offer an overview of the effects exerted by this disturbance on pregnancy. Materials and methods: The study targets 157 pacients admitted to "Alessandrescu-Rusescu" National Institute for Mother and Child Health - Polizu (INSMC), Bucharest, Romania. In order to define the criterion for obesity, WHO classification (body mass index > 30 kg/m²) was used. Data was collected restrospectively after acceptance by the Ethics Committee. Also, we gathered anthropometric data (weight, body mass index and analysis regarding the metabolic profile, including total cholesterol, HDL cholesterol, LDL cholesterol, triglyceride, blood sugar, glycosylated haemoglobin) from all subjects. Each analysis was correlated with each patient's body mass index. Another correlation was made between metabolic profile, antenatal complications and onset of gestational diabetes and premature birth. Statistical analysis was conducted using GraphPad 8 and MedCalc 14.1. Results: Patients had an average body weight of 66.75 kg with a standard deviation of 12.99 kg and a median of 64 kg. Average body mass index was 25.05 kg/m², with a standard deviation of 5,03 kg/m² and a median of 24.2 kg/m². There is a directly proportional and statistically significative correlation between the values of blood sugar, glycosylated haemoglobin, LDL, TG, uric acid and BMI. Also, there is a inversely proportional and statistically significative correlation between the values of HDL and BMI. The CT/HDL ratio, low HDL level and elevated LDL level are the main risk factors for premature birth, while the CT/HDL ratio, low HDL level and elevated TG are the main risk factors for the onset of gestational diabetes. Conclusions: According to the results of this study, the onset of obesity in pregnant woman is rather dependent on each patient's metabolic profile than body weight.

Evaluation of an action's effectiveness by the motor system in a dynamic environment.

An important model for explaining humans' feeling of agency-the Comparator model-draws on ideas used to explain effective motor control. The model describes how our brain estimates the degree of control over the environment offered by a specific motor program (in short, an action's effectiveness). However, given its current level of specification, the model is at best vague on how (or even whether) the prediction of effectiveness of an action is dynamically updated. To test the issue empirically, our participants performed multiple experimental blocks of a task (reliably shown to measure reinforcement from effectiveness) in which blocks with and without action-effects (or with spatially unpredictable feedback) were interlaced. This design creates a sinusoidal-like objective increase or decrease in effectiveness (quantified as the n-trials back probability of receiving feedback), which participants were unable to report. As previously found, response speed indexed reinforcement from effectiveness. The results suggest that reinforcement from effectiveness is sensitive to both the degree and trend of effectiveness; that is, reinforcement is sensitive to whether it is increasing, decreasing, or is unchanged. Given the previous links made between reinforcement from effectiveness and the computation of effectiveness by the motor-system, the results are the first to show an online, dynamic and complex sensitivity to a motor-programs' effectiveness that is directly translated to its production. The importance of testing the so-called sense of agency in a dynamic environment and the implications of the current findings for a dominant model of the sense of agency are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Working Memory Has Better Fidelity Than Long-Term Memory: The Fidelity Constraint Is Not a General Property of Memory After All.

How detailed are long-term-memory representations compared with working memory representations? Recent research has found an equal fidelity bound for both memory systems, suggesting a novel general constraint on memory. Here, we assessed the replicability of this discovery. Participants (total N = 72) were presented with colored real-life objects and were asked to recall the colors using a continuous color wheel. Deviations from study colors were modeled to generate two estimates of color memory: the variability of remembered colors-fidelity-and the probability of forgetting the color. Estimating model parameters using both maximum-likelihood estimation and Bayesian hierarchical modeling, we found that working memory had better fidelity than long-term memory (Experiments 1 and 2). Furthermore, within each system, fidelity worsened as a function of time-correlated mechanisms (Experiments 2 and 3). We conclude that fidelity is subject to decline across and within memory systems. Thus, the justification for a general fidelity constraint in memory does not seem to be valid.

Formation of abstract task representations: Exploring dosage and mechanisms of working memory training effects.

Working memory is strongly involved in human reasoning, abstract thinking and decision making. Past studies have shown that working memory training generalizes to untrained working memory tasks with similar structure (near-transfer effect). Here, we focused on two questions: First, we ask how much training might be required in order to find a reliable near-transfer effect? Second, we ask which choice- mechanism might underlie training benefits? Participants were allocated to one of three groups: working-memory training (combined set-shifting and N-back task), active-control (visual search) and no-contact control. During pre/post testing, all participants completed tests tapping procedural and declarative working memory as well as reasoning. We found improved performance only in the procedural working-memory transfer tasks, a transfer task that shared a similar structure to that of the training task. Intermediate testing throughout the training period suggest that this effect emerged as soon as after 2 training sessions. We applied evidence accumulation modeling to investigate the choice process responsible for this near-transfer effect and found that trained participants, compared with active-controls had quicker retrieval of the action rules, and more efficient classification of the target. We conclude that participants were able to form abstract representations of the task procedure (i.e., stimulus-response rules) that was then ~applied to novel stimuli and responses.

Modeling 2-alternative forced-choice tasks: Accounting for both magnitude and difference effects.

We present a model-based analysis of two-alternative forced-choice tasks in which two stimuli are presented side by side and subjects must make a comparative judgment (e.g., which stimulus is brighter). Stimuli can vary on two dimensions, the difference in strength of the two stimuli and the magnitude of each stimulus. Differences between the two stimuli produce typical RT and accuracy effects (i.e., subjects respond more quickly and more accurately when there is a larger difference between the two). However, the overall magnitude of the pair of stimuli also affects RT and accuracy. In the more common two-choice task, a single stimulus is presented and the stimulus varies on only one dimension. In this two-stimulus task, if the standard diffusion decision model is fit to the data with only drift rate (evidence accumulation rate) differing among conditions, the model cannot fit the data. However, if either of one of two variability parameters is allowed to change with stimulus magnitude, the model can fit the data. This results in two models that are extremely constrained with about one tenth of the number of parameters than there are data points while at the same time the models account for accuracy and correct and error RT distributions. While both of these versions of the diffusion model can account for the observed data, the model that allows across-trial variability in drift to vary might be preferred for theoretical reasons. The diffusion model fits are compared to the leaky competing accumulator model which did not perform as well.

Examining procedural working memory processing in obsessive-compulsive disorder.

Previous research has suggested that a deficit in working memory might underlie the difficulty of obsessive-compulsive disorder (OCD) patients to control their thoughts and actions. However, a recent meta-analyses found only small effect sizes for working memory deficits in OCD. Recently, a distinction has been made between declarative and procedural working memory. Working memory in OCD was tested mostly using declarative measurements. However, OCD symptoms typically concerns actions, making procedural working-memory more relevant. Here, we tested the operation of procedural working memory in OCD. Participants with OCD and healthy controls performed a battery of choice reaction tasks under high and low procedural working memory demands. Reaction-times (RT) were estimated using ex-Gaussian distribution fitting, revealing no group differences in the size of the RT distribution tail (i.e., τ parameter), known to be sensitive to procedural working memory manipulations. Group differences, unrelated to working memory manipulations, were found in the leading-edge of the RT distribution and analyzed using a two-stage evidence accumulation model. Modeling results suggested that perceptual difficulties might underlie the current group differences. In conclusion, our results suggest that procedural working-memory processing is most likely intact in OCD, and raise a novel, yet untested assumption regarding perceptual deficits in OCD.

Absolutely relative or relatively absolute: violations of value invariance in human decision making.

Making decisions based on relative rather than absolute information processing is tied to choice optimality via the accumulation of evidence differences and to canonical neural processing via accumulation of evidence ratios. These theoretical frameworks predict invariance of decision latencies to absolute intensities that maintain differences and ratios, respectively. While information about the absolute values of the choice alternatives is not necessary for choosing the best alternative, it may nevertheless hold valuable information about the context of the decision. To test the sensitivity of human decision making to absolute values, we manipulated the intensities of brightness stimuli pairs while preserving either their differences or their ratios. Although asked to choose the brighter alternative relative to the other, participants responded faster to higher absolute values. Thus, our results provide empirical evidence for human sensitivity to task irrelevant absolute values indicating a hard-wired mechanism that precedes executive control. Computational investigations of several modelling architectures reveal two alternative accounts for this phenomenon, which combine absolute and relative processing. One account involves accumulation of differences with activation dependent processing noise and the other emerges from accumulation of absolute values subject to the temporal dynamics of lateral inhibition. The potential adaptive role of such choice mechanisms is discussed.

Memory for Action Rules and Reaction Time Variability in Attention-Deficit/Hyperactivity Disorder.

BACKGROUND: Patients with attention-deficit/hyperactivity disorder (ADHD) exhibit increased reaction time (RT) variability. This finding is consistent across various choice RT tasks and is considered a core ADHD phenotype, often interpreted as expressing occasional attention lapses. This study explores the selective contribution of perceptual and working memory (WM) processes to increased RT variability in ADHD. METHODS: Low and high WM demands were manipulated in a battery of choice RT tasks administered to two groups of college students (subjects with ADHD vs. healthy control subjects). RESULTS: Ex-Gaussian distribution fitting revealed an increased rate of exceptionally slow RTs (i.e., higher τ values) in subjects with ADHD under all conditions. These group differences interacted with WM demands, showing the largest group differences when WM processing was most demanding (ηp2 = .32). Under demanding WM conditions, evidence accumulation modeling demonstrated that increased RT variability in ADHD is not associated with either momentary or constant deficits in perceptual processing of the target. Rather, results favored a model associating increased RT variability in ADHD with reduced rate of WM retrieval. CONCLUSIONS: These results suggest a pivotal contribution for the retrieval of action rules from WM to increased RT variability in ADHD.

Post choice information integration as a causal determinant of confidence: Novel data and a computational account.

Confidence judgments are pivotal in the performance of daily tasks and in many domains of scientific research including the behavioral sciences, psychology and neuroscience. Positive resolution i.e., the positive correlation between choice-correctness and choice-confidence is a critical property of confidence judgments, which justifies their ubiquity. In the current paper, we study the mechanism underlying confidence judgments and their resolution by investigating the source of the inputs for the confidence-calculation. We focus on the intriguing debate between two families of confidence theories. According to single stage theories, confidence is based on the same information that underlies the decision (or on some other aspect of the decision process), whereas according to dual stage theories, confidence is affected by novel information that is collected after the decision was made. In three experiments, we support the case for dual stage theories by showing that post-choice perceptual availability manipulations exert a causal effect on confidence-resolution in the decision followed by confidence paradigm. These finding establish the role of RT2, the duration of the post-choice information-integration stage, as a prime dependent variable that theories of confidence should account for. We then present a novel list of robust empirical patterns ('hurdles') involving RT2 to guide further theorizing about confidence judgments. Finally, we present a unified computational dual stage model for choice, confidence and their latencies namely, the collapsing confidence boundary model (CCB). According to CCB, a diffusion-process choice is followed by a second evidence-integration stage towards a stochastic collapsing confidence boundary. Despite its simplicity, CCB clears the entire list of hurdles.

Selective influence of working memory load on exceptionally slow reaction times.

The rate of exceptionally slow reaction times (RTs), described by the long tail of the RT distribution, was found to be amplified in a variety of special populations with cognitive deficits (e.g., early-stage Alzheimer's disease, attention-deficit/hyperactivity disorder, low intelligence, elderly). Previous individual differences studies found high correlations between working memory (WM) and parameters that characterize the magnitude of the long-RT tail. However, the causal direction remains unknown. In 3 choice-reaction task experiments, we examined this relationship by directly manipulating WM availability. In Experiment 1, the stimulus-response rules were either arbitrary (WM demanding) or nonarbitrary. In Experiment 2, the arbitrary rules were either novel (demanding) or practiced. In Experiment 3, WM was loaded with either declarative (stimulus-stimulus) or procedural (stimulus-response) arbitrary rules. Using an ex-Gaussian model fitting, we found across all experiments that WM demands uniquely influenced the τ parameter, mostly responsible for the long-RT distribution tail. Evidence accumulation modeling of the choice process indicated that WM load had little influence on the decision process itself and primarily affected the duration of an exponentially distributed nondecision component, assumed to reflect the process of rule retrieval. Theoretical interpretations and implications are discussed.

Synthesis and characterization of a novel controlled release zinc oxide/gentamicin-chitosan composite with potential applications in wounds care.

Freshly prepared ZnO nanoparticles were incorporated into a chitosan solution in weight ratios ranging from 1:1 to 12:1. Starting from the ratio of 3:1 the chitosan solution was transformed into a gel with a high consistency, which incorporates 15mL water for only 0.1g solid substance. The powders obtained after drying the gel were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM) and thermal analysis (TG-DSC). The electronic (UV-vis), infrared (FTIR) and photoluminescence (PL) spectra were also recorded. ZnO particles were coated with gentamicin and incorporated into the chitosan matrix, to yield a ZnO/gentamicin-chitosan gel. The release rate of gentamicin was monitored photometrically. This ZnO/gentamicin-chitosan gel proved great antimicrobial properties, inhibiting Staphylococcus aureus and Pseudomonas aeruginosa growth in both planktonic and surface-attached conditions. The results indicate that the obtained composite can be used in cutaneous healing for developing improved wound dressings, which combine the antibacterial activity of all three components with the controlled release of the antibiotic. This wound dressing maintains a moist environment at the wound interface, providing a cooling sensation and soothing effect, while slowly releasing the antibiotic. The system is fully scalable to any other soluble drug, as the entire solution remains trapped in the ZnO-chitosan gel.

Disentangling decision models: from independence to competition.

A multitude of models have been proposed to account for the neural mechanism of value integration and decision making in speeded decision tasks. While most of these models account for existing data, they largely disagree on a fundamental characteristic of the choice mechanism: independent versus different types of competitive processing. Five models, an independent race model, 2 types of input competition models (normalized race and feed-forward inhibition [FFI]) and 2 types of response competition models (max-minus-next [MMN] diffusion and leaky competing accumulators [LCA]) were compared in 3 combined computational and experimental studies. In each study, difficulty was manipulated in a way that produced qualitatively distinct predictions from the different classes of models. When parameters were constrained by the experimental conditions to avoid mimicking, simulations demonstrated that independent models predict speedups in response time with increased difficulty, while response competition models predict the opposite. Predictions of input-competition models vary between specific models and experimental conditions. Taken together, the combined computational and empirical findings provide support for the notion that decisional processes are intrinsically competitive and that this competition is likely to kick in at a late (response), rather than early (input), processing stage.