Potential Difference Research Articles

Sex differences in discrimination behavior and orbitofrontal engagement during context-gated reward prediction.

Animals, including humans, rely on contextual information to interpret ambiguous stimuli. Impaired context processing is a hallmark of several neuropsychiatric disorders, including schizophrenia, autism spectrum disorders, post-traumatic stress disorder, and addiction. While sex differences in the prevalence and manifestations of these disorders are well established, potential sex differences in context processing remain uncertain. Here, we examined sex differences in the contextual control over cue-evoked reward seeking and its neural correlates, in rats. Male and female rats were trained in a bidirectional occasion-setting preparation in which the validity of two auditory reward-predictive cues was informed by the presence, or absence, of a visual contextual feature (LIGHT: X+/DARK: X-/LIGHT: Y-/DARK: Y+). Females were significantly slower to acquire contextual control over cue-evoked reward seeking. However, once established, the contextual control over behavior was more robust in female rats; it showed less within-session variability (less influence of prior reward) and greater resistance to acute stress. This superior contextual control achieved by females was accompanied by an increased activation of the orbitofrontal cortex (OFC) compared to males. Critically, these behavioral and neural sex differences were specific to the contextual modulation process and not observed in simple, context-independent, reward prediction tasks. These results indicate a sex-biased trade-off between the speed of acquisition and the robustness of performance in the contextual modulation of cued reward seeking. The different distribution of sexes along the fast learning ↔ steady performance continuum might reflect different levels of engagement of the OFC, and might have implications for our understanding of sex differences in psychiatric disorders.

Impact and Interrelationships of Striatal Proteins, EPHB2, OPRM1, and PER2 on Mild Cognitive Impairment.

With the global increase in life expectancy, there has been a rise in the incidence of cognitive impairments attributed to diverse etiologies. Notably, approximately 50% of individuals diagnosed with mild cognitive impairment (MCI) progress to dementia within 3years. However, the precise mechanisms underlying MCI remain elusive. Therefore, this study aimed to elucidate potential mechanisms implicated in MCI utilizing Per2 knockout (KO) mice, which have previously been shown to have cognitive deficits. Behavioral (Y-maze, Barnes maze) and molecular (electrophysiology, RNA sequencing, western blot, and immunofluorescence) experiments were conducted in Per2 KO and wild-type (WT) mice. Per2 KO mice exhibited impaired spatial working memory in the Y-maze and Barnes maze. However, there were no significant group differences in hippocampal long-term potentiation (LTP) between Per2 KO and WT mice, whereas striatal LTP in Per2 KO mice was lower compared to WT mice. In RNA sequencing analysis, 58 genes were downregulated and 64 genes were upregulated in the striatum of Per2 KO mice compared to WT mice. Among the differentially expressed genes, four genes (Chrm2, EphB2, Htr1b, Oprm1) were identified. Optimal expression levels of EPHB2 and OPRM1 were found to significantly enhance cognitive performance in mice. Additionally, Per2 KO mice exhibited reduced EPHB2-NMDAR-LTP and OPRM-mTOR signaling, along with elevated amyloid beta (Aβ) levels, when compared to WT mice. However, these alterations were reversed upon administration of morphine treatment. Striatal OPRM1-mTOR signaling, EPHB2-NMDAR-LTP signaling, and Aβ expression levels may exert a combined effect on MCI under the control of Per2 expression.

Social well-being and problematic school absence among Danish adolescents: A nationwide cross-sectional study.

Adolescents' well-being and school absence are important factors for public health. The aim of this study was to examine the association between social well-being and problematic school absence among Danish adolescents in the ninth grade, as well as to examine potential sex differences, using a large cohort of adolescents. In this cross-sectional study, information on social well-being was obtained from the yearly Danish National Well-being Questionnaire mandatory in compulsory school. Data on school absence was obtained from the Ministry of Children and Education. The study population comprised 203,570 adolescents in the school years 2014/2015 to 2019/2020. The association between social well-being and problematic school-absence was analysed using logistic regression. A stratified analysis was made to investigate potential sex differences. A total of 17,555 (9.16%) adolescents had problematic school absence, defined as >10% illegal absence and/or sickness absence in the ninth grade. Adolescents with low social well-being had higher odds for having problematic school absence compared with adolescents with high social well-being, adjusted odds ratio=2.22 (95% confidence interval 2.10-2.34). When stratifying for sex, the association was strongest for girls. The results remained after adjustment for parents' educational level and family structure. Associations between adolescents' social well-being and problematic school absence were found, where girls had the strongest association. These findings might provide knowledge about social well-being as an important factor for problematic school absence, while underlining the importance of early focus and prevention, which is of importance for both the adolescents and society.

The Deep-Match Framework: R-Peak Detection in Ear-ECG.

The Ear-ECG provides a continuous Lead I like electrocardiogram (ECG) by measuring the potential difference related to heart activity by electrodes which are embedded within earphones. However, the significant increase in wearability and comfort enabled by Ear-ECG is often accompanied by a degradation in signal quality - an obstacle that is shared by the majority of wearable technologies. We aim to resolve this issue by introducing a Deep Matched Filter (Deep-MF) for the highly accurate detection of R-peaks in wearable ECG, thus enhancing the utility of Ear-ECG in real-world scenarios. The Deep-MF consists of an encoder stage, partially initialised with an ECG template, and an R-peak classifier stage. Through its operation as a Matched Filter, the encoder searches for matches with an ECG template in the input signal, prior to filtering these matches with the subsequent convolutional layers and selecting peaks corresponding to the ground-truth ECG. The latent representation of R-peak information is then fed into a R-peak classifier, of which the output provides precise R-peak locations. The proposed Deep Matched Filter is evaluated using leave-one-subject-out cross-validation over 36 subjects with an age range of 18-75, with the Deep-MF outperforming existing algorithms for R-peak detection in noisy ECG. The Deep-MF achieves a median R-peak recall of 94.9% and a median precision of 91.2% across subjects when evaluated with leave-one-subject-out cross validation. Overall, this Deep-Match framework serves as a valuable step forward for the real-world functionality of Ear-ECG and, through its interpretable operation, the acceptance of deep learning models in e-Health.

Anatomy-Guided Spatio-Temporal Graph Convolutional Networks (AG-STGCNs) for Modeling Functional Connectivity Between Gyri and Sulci Across Multiple Task Domains.

The cerebral cortex is folded as gyri and sulci, which provide the foundation to unveil anatomo-functional relationship of brain. Previous studies have extensively demonstrated that gyri and sulci exhibit intrinsic functional difference, which is further supported by morphological, genetic, and structural evidences. Therefore, systematically investigating the gyro-sulcal (G-S) functional difference can help deeply understand the functional mechanism of brain. By integrating functional magnetic resonance imaging (fMRI) with advanced deep learning models, recent studies have unveiled the temporal difference in functional activity between gyri and sulci. However, the potential difference of functional connectivity, which represents functional dependency between gyri and sulci, is much unknown. Moreover, the regularity and variability of the G-S functional connectivity difference across multiple task domains remains to be explored. To address the two concerns, this study developed new anatomy-guided spatio-temporal graph convolutional networks (AG-STGCNs) to investigate the regularity and variability of functional connectivity differences between gyri and sulci across multiple task domains. Based on 830 subjects with seven different task-based and one resting state fMRI (rs-fMRI) datasets from the public Human Connectome Project (HCP), we consistently found that there are significant differences of functional connectivity between gyral and sulcal regions within task domains compared with resting state (RS). Furthermore, there is considerable variability of such functional connectivity and information flow between gyri and sulci across different task domains, which are correlated with individual cognitive behaviors. Our study helps better understand the functional segregation of gyri and sulci within task domains as well as the anatomo-functional-behavioral relationship of the human brain.

Synthesis of Consequent Pole Vernier Permanent Magnet Machine Based on Oscillating Magnetic Potential Difference Model

Synthesis of Consequent Pole Vernier Permanent Magnet Machine Based on Oscillating Magnetic Potential Difference Model

Application of artificial intelligence in predicting major arrhythmic events based on clinical and left ventricular electro-anatomical mapping data

Abstract Introduction Artificial intelligence (AI) is a ground-breaking frontier in the analysis of intricate and extensive datasets, also within the medical domain. AI can be used to meticulously and systematically analyse data derived from electro-anatomical mapping, scrutinizing the numerical data extracted from the mapping engineering files. Purpose The primary objective of the project is to utilize machine learning methods to identify potential correlations between clinical, procedural, and substrate-mapping variables with major arrhythmic cardiac events (MaCE). Methods Machine learning algorithms were implemented using a database of 220 patients who underwent endocardial left ventricular electro-anatomical mapping (EAM). A total of 223 clinical-procedural variables were collected (analysis conducted for the 61 most interesting variables) and substrate mapping engineering files/data were extrapolated for analysis. Combinations of 4 and 5 variables are explored, resulting in 487,635 and 5,461,512 combinations, respectively. All the results obtained from all the combinations and different methods were evaluated by calculating the AUC (parameter indicating the probability that the prediction is in the correct order). For each patient, the numerical data extracted from the EAM files were assessed, specifically focusing on: 1. The late potentials extension and dispersion (%LatArea). 2. Point-to-point difference of the bipolar potential compared to the unipolar potential, with identification of regions where multiple points with high differences are clustered (%UniBip) 3. Areas of deceleration, characterized by very early and very late potentials within a short range, indicating a substantial difference in the activation timing (GradVal). Results Analyzing the best six 4-variable logistic regression models, we note that the variables that are most frequently correlated with a MaCE during follow-up are "NYHA class", "PAPs" and "GradVal" (AUC of the best models was: 0,96; 0,94; 0,91; 0,90; 0,90; 0,90). Analyzing the best six 5-variable logistic regression models emerges that the variables most frequently correlated with a MaCE during follow-up are "NYHA class", "PAPs", "GradVal", "Arrhythmic Storm", "TAPSE" and "%UniBip" (AUC of the best models was: 0,97; 0,93; 0,92; 0,92; 0,92; 0,92). EAM data added to clinical data increases the number of regression variables and the model complexity; "GradVal" and "%UniBip" seem to have greater relevance. Conclusion The study successfully employs machine learning algorithms to identify key variables influencing the prediction of MaCE. The analysis of EAM numerical data through AI can allow for the stratification of MaCE risk. The application of artificial intelligence allows to analyse a large amount of computer data that would not be analysable by human capabilities alone. Ongoing refinement and expansion of the dataset can enhance the models' predictive capabilities for clinical applications.

Relationship between ICD implantation volume and treatment parameters of patients receiving an ICD with remote monitoring.

Both highly specialized heart centres and less specialized hospitals care for patients with implantable ICDs/CRT-Ds with remote monitoring. To investigate potential differences in patient treatment according to centre's ICD implantation volume. Based on their 2012 ICD/CRT-D implantation volume, centres enrolled in the NORDIC ICD trial in Germany were assigned to one of three groups: high- (HV, n= 345), medium- (MV, n= 340) or low-volume (LV, n= 189). The HV-centres had a significant higher CRT-D proportion (41.7%; LV: 36.5%; MV: 23.2%; P𝑔𝑙𝑜𝑏𝑎𝑙< 0.001), significant shorter median procedure duration (49 min; MV: 58 min; LV: 60 min; P𝑔𝑙𝑜𝑏𝑎𝑙< 0.001) but significant longer median hospital stay (4 days; MV and LV: 3 days; P𝑔𝑙𝑜𝑏𝑎𝑙< 0.001) compared to MV- and LV-centres. The X-ray exposure was shorter in MV/HV-centres (MV: 3.4 min; HV: 3.6 min; LV: 5.5 min; P𝑔𝑙𝑜𝑏𝑎𝑙< 0.001). Only 3.5% (LV: 2.6%; HV: 3.5%; MV: 4.1%) patients received at least one delivered inappropriate shock and 2.5% (HV: 2.0%; LV: 2.6%; MV: 2.9%) patients had withheld inappropriate ICD shocks without subsequent inappropriate shock delivery within 24.5 months of median follow-up. Implantation volume-dependent differences were observed in the device selection, procedure duration and x-ray exposure duration. Remote monitoring in combination with adequate response pattern prevented imminent inappropriate shocks in all three groups.

Regional Evaluation Study of VFTO Interference to Secondary Side Cables Based on Cloud Model and MARCOS.

With the advent of the data era, most power secondary side equipment tends to be digitized. The power system needs more accurate numerical results to further improve its operating efficiency. Therefore, it is important to study the electromagnetic interferences of very fast transient overvoltage (VFTO) generated by gas-insulated switchgear (GIS). To protect the secondary side cable from interferences, the secondary side cable is wrapped with an outer shield and the shield is grounded. When the interference of VFTO comes, it will couple the interference current and interference voltage on the shield of the cable. By grounding, the interference is greatly discharged. However, due to the grounding resistance, there will be a potential difference between the grounding points at the two ends of the shield of the cable. This causes a corresponding interference current to flow through the shield, which will affect the transmission of signals inside the cable. In the actual substation, the resistivity of the soil, the ambient temperature and humidity of the area, and so on will have impacts on the grounding resistance. In addition, the irregularity of the cable arrangement and the time of the use of the cable will have impacts on the signal transmission of the cable. Based on the abovementioned issues, this article proposed a comprehensive assessment method based on the combination of the cloud model and measurement of alternatives and ranking according to compromise solution (MARCOS). The method brings the cloud model into MARCOS by the algorithm of the contribution of the cloud droplets. It overcomes the difficulty of cloud model quantification. By comparing the results of the proposed method with the actual conditions at the substation and the results of the common MARCOS assessment method, the validity of the method is verified, and a reference scheme is provided for substation optimization.

Characterization of chitosan nanoparticles extracted from maggot shell and paddy snail waste using the ionic gelation method

The aim this study was to characterize of chitosan nanoparticles extracted from maggot shell waste and paddy snail waste using the ionic gelation method. The Scanning Electron Microscope of nanochitosan extracted from maggot shell showed heterogeneity in particle size ranging from 218.60 to 279.04 nm by 73.5%. SEM results of nanochitosan extracted from paddy snail waste showed ranging from 193.48 to 356.20 nm by 60.4% and 740.89 to 945.74 nm by 14.35%. The zeta potential of nanochitosan particles of maggot shell waste and paddy snail waste were found to be 9.7 mV and -28.9 mV, respectively. The source of chitosan nanoparticles might produce the difference of particle size and zeta potential of chitosan nanoparticles.

Impact of Prolonged Sport Stoppage on Knee Injuries in High School Athletes: An Ecological Study.

In March 2020, public health concerns resulted in school closure throughout the United States. The prolonged sport cessation may affect knee injury risk in high school athletes. The purpose of this study was to describe and compare risk of knee injuries in high school athletes during 2019-2020 and 2020-2021 academic years, and stratify by gender, severity, mechanism of injury, injury type, and knee anatomic region. Historical-prospective cohort study. This historical-prospective cohort study included 176 schools in 6 states matched by sport participation in control and COVID years from July 1, 2019 to June 30, 2021. Injury rates per 1000 athletes per year were calculated with 95% confidence intervals. A negative binomial regression was performed to assess potential differences in knee injuries between academic years. 94,847 and 72,521 high school athletes participated in the 2019-2020 (19-20) and 2020-2021 (20-21) seasons. Knee injury risk was higher in the 20-21 season (19-20: 28.89% [27.82-29.96]; 20-21: 33.82% [32.50-35.14]). Risk increased for male athletes from 2019-2020 to 2020-2021 (19-20: 29.42% [28.01-30.83]; 20-21: 40.32% [38.89-41.75]). Female knee injury risk was similar between years (19-20: 25.78% [24.29-27.27]; 20-21: 26.03% [24.31-27.75]). Knee injuries increased by a ratio of 1.2 ([95% CI, 1.1-1.3], P < .001) during 2020-2021. Knee injury risk and relative risk increased among males in 2020-2021. Results indicate changes in knee injury risk following return from COVID shelter in place among high school athletes and implicate potential negative downstream effects of interrupted sports training and participation on high school injury risk.

Magnetic field based finite element method for magneto-static problems with discontinuous electric potential distributions

We introduce two finite element formulations to approximate magneto-static problems with discontinuous electric potential based respectively on the electrical scalar potential and the magnetic field. This work is motivated by our interest in Liquid Metal Batteries (LMBs), a promising technology for storing intermittent renewable sources of energy in large scale energy storage devices. LMBs consist of three liquid layers stably stratified and immiscible, with a light liquid metal on top (negative electrode), a molten salt in the middle (electrolyte) and a heavier liquid metal on bottom (positive electrode). Energy is stored in electrical potential differences that can be modeled as jumps at each electrode-electrolyte interface. This paper focuses on introducing new finite element methods for computing current and potential distributions, which account for internal voltage jumps in liquid metal batteries. Two different formulations that use as primary unknowns the electrical potential and magnetic field, respectively, are presented. We validate them using various manufactured test cases, and discuss their applications for simulating the current distribution during the discharge phase in a liquid metal battery.

A Study on Yield and Value Sustainability in Groundnut (Arachis hypogea) Through Cluster Frontline Demonstrations Approach in Cuddalore District of Tamil Nadu

Background: Groundnut is a prominent oilseed crop in India but its productivity is far below the potential yield due to lack of knowledge and adoption of improved varieties and technologies. Technology gap is a major problem in groundnut production in North Eastern zone of Tamil Nadu State in which Cuddalore district falls. A scientific and systematic effort was made to study the impact on yield by assessing technological gap existing in various components of groundnut cultivation through cluster frontline demonstrations (CFLDs) with scientific technologies. Methods: Cluster Frontline Demonstrations was implemented in groundnut to improve the production potential of improved varieties and new technologies through Krishi Vigyan Kendra (KVK). The study with one of its objective to assess yield and technology gap in groundnut was conducted with 175 demonstrations during the period from 2020-21 to 2022-23 covering seven blocks in an area of 70 hectares in Cuddalore district following cluster random sampling method. Two main varieties VRI 8 and VRI 10 along with improved technologies were demonstrated in farmer’s field by providing necessary critical inputs seed pods, bio control agents along with seed drill sowing, Result: There resulted 62.13 per cent increase in yield as observed in demonstration plots over farmers’ practices in groundnut. The study revealed that in groundnut, the average extension gap (difference of demo and farmer plot yield) is 16.26 q/ha, average technology gap (difference of potential and demo plot yield) is 12.21 q/ha and average technology index of demonstrations is 22.21 per cent. The higher average net returns (Rs. 149758/ha) were recorded in demonstration plot (BCR 2.3) compared to farmers’ plot. The Sustainability Yield Index (SYI) and Sustainability Value Index (SVI) in demo plot are higher consistently than farmers plot mainly due to the effect of cluster frontline demonstrations with proper application of inputs/technologies viz., VRI 8 and VRI 10 varieties, seed treatment with bio fertilizers, bio control agents, soil test based nutrient management, application of TNAU crop booster groundnut rich and gypsum application.

WITHDRAWN: Transdifferentiation of Human Neonatal Foreskin Fibroblasts into Keratinocyte-like Cells via Regulating the AKT/P53/WNT/LEF1 Axis

It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

Knowledge, Attitudes, and Practices Regarding Tropical Diseases among Nursing Students: A Comparative Cross-Sectional Study.

This study aimed to compare bachelor nursing students' knowledge, attitudes, and practices (KAP) regarding tropical diseases. This cross-sectional study was conducted with 128 participants who were recruited using stratified random sampling and completed a sociodemographics questionnaire and KAP questionnaire concerning tropical diseases. Descriptive statistics were used to present the data, and inferential statistics, including one-way analysis of variance and Mann-Whitney U tests, were calculated to identify potential differences between variables. The study found nursing students who took the tropical nursing courses had better knowledge and attitudes regarding preventing tropical diseases than those who did not. Participants who took the tropical nursing courses had a significantly higher median knowledge score of 22 with an interquartile range (IQR) of 2 (P <0.001) and a median attitude score of 31 (IQR: 6, P = 0.02) compared with those who did not take it. However, there were no significant differences between the two groups in practice regarding tropical diseases (P = 0.20). In conclusion, students who take tropical nursing courses may improve their knowledge and attitudes toward tropical diseases, but the two groups in this study did not significantly differ in practice, possibly because of self-reported practices rather than direct observation. This study highlights the potential of accurate digital information to provide credible resources in enhancing nursing students' KAP concerning tropical diseases.

Quantifying Exhaled Particles in Healthy Humans During Various Respiratory Activities Under Realistic Conditions.

Background: Quantitatively collecting and characterizing exhaled aerosols is vital for infection risk assessment, but the entire droplet size spectrum has often been neglected. We analyzed particle number and size distribution of healthy participants in various respiratory activities, considering inter-individual variability, and deployed a simplified far-field model to inform on infection risks. Methods: Participants repeated the same respiratory activities on two visits. Particles were collected using an airtight extraction helmet supplied with High Efficiency Particulate Air (HEPA) filtered air. The sampling volume flow was transported to two particle counters covering the small and large particle spectrum. The applied simple mass balance model included respiratory activity, viral load, room size, and air exchange rates. Results: Thirty participants completed the study. The major fraction of the number-based size distribution was <5 μm in all respiratory activities. In contrast, the major fraction of the volume-based size distribution was 2-12 μm in tidal breathing, but >60 μm in all other activities. Aerosol volume flow was lowest in tidal breathing, 10-fold higher in quiet/normal speaking, deep breathing, coughing, and 100-fold higher in loud speaking/singing. Intra-individual reproducibility was high. Between participants, aerosol volume flow varied by two orders of magnitude in droplets <80 μm, and three orders of magnitude in droplets >80 μm. Simple model calculations not accounting for potential particle size-dependent differences in viral load and infection-related differences were used to model airborne pathogen concentrations. Conclusions: Quantitative analysis of exhaled aerosols for the entire droplet size spectrum as well as the variability in aerosol emission between individuals provides information that can support infection research. Clinical Trial Registration number: NCT04771585.

Thrombolysis for Wake-Up Stroke Versus Non-Wake-Up Unwitnessed Stroke: EOS Individual Patient Data Meta-Analysis.

Stroke with unknown time of onset can be categorized into 2 groups; wake-up stroke (WUS) and unwitnessed stroke with an onset time unavailable for reasons other than wake-up (non-wake-up unwitnessed stroke, non-WUS). We aimed to assess potential differences in the efficacy and safety of intravenous thrombolysis (IVT) between these subgroups. Patients with an unknown-onset stroke were evaluated using individual patient-level data of 2 randomized controlled trials (WAKE-UP [Efficacy and Safety of MRI-Based Thrombolysis in Wake-Up Stroke], THAWS [Thrombolysis for Acute Wake-Up and Unclear-Onset Strokes With Alteplase at 0.6 mg/kg]) comparing IVT with placebo or standard treatment from the EOS (Evaluation of Unknown-Onset Stroke Thrombolysis trial) data set. A favorable outcome was prespecified as a modified Rankin Scale score of 0 to 1 at 90 days. Safety outcomes included symptomatic intracranial hemorrhage at 22 to 36 hours and 90-day mortality. The IVT effect was compared between the treatment groups in the WUS and non-WUS with multivariable logistic regression analysis. Six hundred thirty-four patients from 2 trials were analyzed; 542 had WUS (191 women, 272 receiving alteplase), and 92 had non-WUS (42 women, 43 receiving alteplase). Overall, no significant interaction was noted between the mode of onset and treatment effect (P value for interaction=0.796). In patients with WUS, the frequencies of favorable outcomes were 54.8% and 45.5% in the IVT and control groups, respectively (adjusted odds ratio, 1.47 [95% CI, 1.01-2.16]). Death occurred in 4.0% and 1.9%, respectively (P=0.162), and symptomatic intracranial hemorrhage in 1.8% and 0.3%, respectively (P=0.194). In patients with non-WUS, no significant difference was observed in favorable outcomes relative to the control (37.2% versus 29.2%; adjusted odds ratio, 1.76 [0.58-5.37]). One death and one symptomatic intracranial hemorrhage were reported in the IVT group, but none in the control. There was no difference in the effect of IVT between patients with WUS and non-WUS. IVT showed a significant benefit in patients with WUS, while there was insufficient statistical power to detect a substantial benefit in the non-WUS subgroup. URL: https://www.clinicaltrials.gov; Unique identifier: CRD42020166903.

Neural correlates of model-based behavior ininternet gaming disorder and alcohol usedisorder.

An imbalance between model-based and model-free decision-making systems is a commonfeature in addictive disorders. However, little is known about whether similar decision-making deficits appear in internet gaming disorder (IGD). This study compared neurocognitive featuresassociated with model-based and model-free systems in IGD and alcohol use disorder (AUD). Participants diagnosed with IGD (n = 22) and AUD (n = 22), and healthy controls (n = 30) performed the two-stage task inside the functional magnetic resonance imaging (fMRI) scanner. We used computational modeling and hierarchical Bayesian analysis to provide a mechanistic account of their choice behavior. Then, we performed a model-based fMRI analysis and functional connectivity analysis to identify neural correlates of the decision-making processes in each group. The computational modeling results showed similar levels of model-based behavior in the IGD and AUD groups. However, we observed distinct neural correlates of the model-based reward prediction error (RPE) between the two groups. The IGD group exhibited insula-specific activation associated with model-based RPE, while the AUD group showed prefrontal activation, particularly in the orbitofrontal cortex and superior frontal gyrus. Furthermore, individuals with IGD demonstrated hyper-connectivity between the insula and brain regions in the salience network in the context of model-based RPE. The findings suggest potential differences in the neurobiological mechanisms underlying model-based behavior in IGD and AUD, albeit shared cognitive features observed in computational modeling analysis. As the first neuroimaging study to compare IGD and AUD in terms of the model-based system, this study provides novel insights into distinct decision-making processes in IGD.

Exploring parenthood in first episode of psychosis: the potential role of the offspring in the outcome of women.

The study aimed to explore the role of parenthood at first episode of psychosis (FEP) on recovery, with a focus on potential sex differences. Sociodemographic, clinical, and neurocognitive information was considered on 610 FEP patients form the PAFIP cohort (Spain). Baseline and three-year follow-up comparisons were carried out. Chi-square tests and ANCOVA analysis were performed controlling for the effect of age and years of education. Men comprised 57.54% of the sample, with only 5.41% having offspring when compared to 36.29% of women. Parenthood was related to shorter duration of untreated illness (DUI) in women with children (12.08months mothers vs. 27.61months no mothers), showing mothers better premorbid adjustment as well. Childless men presented the worst premorbid adjustment and the highest cannabis and tobacco consumption rates. Mothers presented better global cognitive function, particularly in attention, motor dexterity and executive function at three-year follow-up. Diminished parental rates among FEP men could be suggested as a consequence of a younger age of illness onset. Sex roles in caregiving may explain the potential role of parenthood on premorbid phase, with a better and heathier profile, and a more favorable long-term outcome in women. These characteristics may be relevant when adjusting treatment specific needs in men and women with and without offspring.

Development, validation and feasibility of a Patient Satisfaction Questionnaire for evaluating the quality performance of a diagnostic small fibre neuropathy service: A qualitative study.

Small fibre neuropathy (SFN) is a peripheral neuropathy, leading to neuropathic pain and autonomic dysfunction. An evidence-based standardized patient diagnostic SFN service has been implemented in the Netherlands for improving patient-centred SFN care. However, the quality of care of this diagnostic SFN service has never been assessed from a patient perspective. The aim of this study was to develop and validate an SFN-Patient Satisfaction Questionnaire (SFN-PSQ) to measure the quality performance of a standardized diagnostic SFN service. A descriptive qualitative study to create the SFN-PSQ was performed using the (COREQ(Consolidated Criteria for Reporting Qualitative Research) checklist. For item generation and content development, domains and/or items from validated PSQs were selected. The content development and content validity were performed using a Delphi method with SFN expert caregivers with different backgrounds. By using the three-step-test method in individual cognitive interviews, the content validity by patients was finalized. In one online Delphi panel round, the content of the first concept of the SFN-PSQ was validated, which resulted in the second concept of the SFN-PSQ. From July 2019 till March 2020, nine patients consented to participate in the individual cognitive interviews. The most significant changes of the new questionnaire were adding domains and items concerning the waiting list, the diagnostic services and consultation by the hospital psychiatrist. Also, a differentiation was made for both an inpatient and outpatient diagnostic SFN service. Furthermore, the clarity and intelligibility of the domains/items were improved, resulting in an increased comprehension of the SFN-PSQ. Ultimately, the new developed SFN-PSQ consisted of 10 domains and 51 items, suitable for measuring patient satisfaction of the neurological analysis in patients with SFN. Through item generation, expert opinions and interviews with patients, the SFN-PSQ was developed and validated, and feasibility was confirmed. The structure of the questionnaire, based on the logistic and diagnostic SFN pathway, could be used as a model in other hospitals to improve the quality, continuity and access of SFN care and other chronic diseases taking into account potential cross-cultural differences. Caregivers were involved in the item generation and content development of the questionnaire. Patients were directly involved in testing the content validity and feasibility of the SFN-PSQ. Not applicable.