The purpose of the present study was to correlate direct measurements of abdominal wall fat at the site of exam and appendiceal position with ultrasound (US) visualization of the appendix. The study took place at a large, urban pediatric teaching hospital. Demographic and imaging data of all patients who underwent both US and CT examinations within a 72-h period to evaluate for appendicitis were assessed. Two hundred eighteen patients met study criteria. Greater abdominal wall fat (p < 0.001) was observed in the subjects where the appendix was not visualized with ultrasound (17.04 mm, SD ± 13.52) than in subjects where the appendix was visualized with ultrasound (11.75 mm, SD ± 11.81) was significant. Using ROC curve analyses, there was no abdominal fat thickness cutoff threshold above which the appendix was significantly unlikely to be seen using US. Retrocecal location of the appendix was found to impair appendiceal visualization with US for both normal and inflamed appendices. Increased abdominal wall fat thickness was associated with decreased US appendiceal visualization rates, although there was no fat thickness value above which we could predict that the appendix would not be visualized with US. In patients with retrocecal appendices, the difference in visualization rates was significantly worse regardless of whether the appendix was normal or inflamed.
Background: Emerging evidence suggests that schizophrenia (ScZ) is associated with aberrant neural oscillatory activity, in particular at γ-band frequencies (>30 Hz). Our group has reported several studies showing impaired generation of high-gamma band oscillatory activity (~50-120 Hz) in chronic ScZ patients as well as in unmedicated patients with first-episode psychosis (FEP). Currently, however, it is unclear whether gamma-band activity is already impaired in individuals at Ultra High Risk (UHR) for schizophrenia. The current MEG study investigates this question, using a visual task that is known to induce strong high-γ band activity over visual cortical areas. Methods: MEG data were recorded, while 50 UHR and 30 healthy control (CON) participants performed an inward moving grating task. Participants fixated on sine-wave circular gratings and detected (by button-press) acceleration of inward movement, occurring at an unpredictable moment during trial presentation. MEG analysis focused on frequency domain reconstructed MEG data collected from central nodes placed in 80 (sub)cortical regions defined within the AAL-atlas, using LCMV beamformer sourceanalysis algorithms to optimally suppress both sensor-level noise sources and contributions from neighboring brain areas. Results: Independent of group (i.e., across all participants), 14 AAL-atlasderived regions in the visual cortex showed significantly increased sustained gamma-band (53-63 Hz) and significantly decreased sustained alphaband (8-12 Hz) activity during stimulus presentation, compared to baseline activity (False-Discovery-Rate corrected for multiple comparisons). Subsequently tested group effects (UHRs vs. CONs) across these 14 visual regions and across a time interval between 200 and 1200 ms postgrating onset revealed significantly decreased gamma-band responses for UHR, but no group differences in alpha-band responses. In addition, UHR participants' performance was characterized by elevated error rates, compared to CON participants. Conclusion: Gamma-band visual-cortex responses during perception are already impaired in individuals at UHR for psychosis development and therefore represent a potential candidate biomarker for psychosis prediction. Background: The neural mechanisms underlying antipsychotic treatment response are incompletely understood. The high proportion of patients with a diagnosis of schizophrenia who are refractory to treatment targeting the dopamine system suggests that more complex mechanisms give rise to symptoms of the illness. Reinforcement learning tasks have been employed frequently in schizophrenia as a whole in order to assess dopaminergic functioning and reward processing but have not yet been studied in the context of treatment response. Methods: We examined reward prediction error (RPE) signaling in a reinforcement learning task in 21 treatment-resistant (TRS) and 21 treatment responsive (NTR) patients with a diagnosis of schizophrenia as well as 24 healthy controls (HC) using functional magnetic resonance imaging. SA75....
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