Scleritis is a rare and severe ocular inflammatory disease that is often associated with potentially sight-threatening ocular complications. The aim of the present study was to characterize ocular complications in non-infectious scleritis and identify predictive variables for their development. Data for this registry-based study were extracted from the AutoInflammatory Disease Alliance Network for Scleritis Registry. Univariate analysis was performed to examine potential associations of demographic and clinical variables with the development of ocular complications. Uveitis and peripheral ulcerative keratitis were considered to be extensions of the inflammatory process and not to be true structural complications. Predictive factors of ocular complications were assessed using regression analysis. The impact of ocular complications on visual acuity—measured by best-corrected visual acuity (BCVA)—was also analyzed. A total of 154 patients (218 eyes) with non-infectious scleritis were enrolled. In 58 of these patients (87 eyes), 102 ocular complications were recorded, with cataract, scleral and corneal thinning, and glaucoma and/or increased ocular pressure being the most frequently recorded complications. Ocular complications were found to be significantly more frequent among patients affected by granulomatosis with polyangiitis (GPA) (p < 0.0001) and concomitant uveitis (p = 0.023). The mean severity score was significantly higher among eyes experiencing ocular complications (p < 0.0001). Regression analysis identified three variables capable of predicting the development of ocular complications: a diagnosis of GPA [odds ratio (OR) 7.747, p < 0.0001]; the presence of concomitant uveitis (OR 3.648, p = 0.019); and a high severity score (OR 1.138, p = 0.044). Mean (± standard deviation) BCVA converted to logMAR was found to be significantly higher among eyes without ocular complications (0.12 ± 0.24 vs 0.27 ± 0.49; p = 0.005). Scleritis was accompanied by irreversible ocular complications in a considerable proportion of the patients enrolled in this study. Patients with a diagnosis of GPA, concomitant uveitis, and a higher severity score are more likely to develop ocular complications, and thus warrant a tighter follow-up schedule and early treatment in order to minimize the risk of poor visual prognosis.
The experience of pain, like other interoceptive processes, has recently been conceptualized in terms of predictive coding and free energy frameworks. In these views, the brain integrates sensory, proprioceptive, and interoceptive signals to generate probabilistic inferences about upcoming events, which shape both the state and the perception of our inner body. Here, we ask whether it is possible to induce pain expectations by providing false faster (vs. slower) acoustic cardiac feedback before administering electrical cutaneous shocks. We test whether these expectations will shape both the perception of pain and the body’s physiological state toward prior predictions. Results confirmed that faster cardiac feedback elicited pain expectations that affected both perceptual pain judgments and the body’s physiological response. Perceptual pain judgments were biased toward the expected level of pain, such that participants illusorily perceived identical noxious stimuli as more intense and unpleasant. Physiological changes mirrored the predicted level of pain, such that participants’ actual cardiac response in anticipation of pain stimuli showed a deceleration in heart rate, in line with the well-known orienting cardiac response in anticipation of threatening stimuli (Experiment 1). In a control experiment, such perceptual and cardiac modulations were dramatically reduced when the feedback reproduced an exteroceptive, instead of interoceptive, cardiac feedback (Experiment 2). These findings show that cardiac perception can be understood as interoceptive inference that modulates both our perception and the physiological state of the body, thereby actively generating the interoceptive and autonomic consequences that have been predicted.
The cardiovascular and respiratory systems are anatomically and functionally integrated, suggesting that breathing continuously influences cardiac interoception. Previously, we demonstrated that the heartbeat-evoked potential (HEP), a neural marker of cardiac signal processing, is modulated by respiration, with enhanced late HEP positivity and increased interoceptive accuracy during exhalation. Here, we reanalysed our previous dataset in the time-frequency domain to investigate heartbeat-modulated cortical oscillations across respiratory phases during rest, cardiac interoception (heartbeat counting), and an exteroceptive control task. During heartbeat counting, exhalation was associated with increased late heartbeat-modulated alpha- and theta-band power and inter-trial coherence over fronto-parietal electrodes, compared with inhalation. Heartbeat-modulated alpha activity was related to HEP amplitude and predicted interoceptive accuracy. Exploratory analyses also indicated enhanced heartbeat-modulated functional connectivity during exhalation. These effects could not be accounted for by cardiac physiology alone and were absent during exteroception. We propose a mechanistic account of cardio-respiratory interactions grounded in interoceptive predictive coding, suggesting that exhalation enhances precision-weighting of cardiac signals by facilitating attentional allocation to interoceptive signals and suppressing task-irrelevant distractions.
Accurate vocal fold (VF) pose estimation is crucial for diagnosing larynx diseases that can eventually lead to VF paralysis. The videoendoscopic examination is used to assess VF motility, usually estimating the change in the anterior glottic angle (AGA). This is a subjective and time-consuming procedure requiring extensive expertise. This research proposes a deep learning framework to estimate VF pose from laryngoscopy frames acquired in the actual clinical practice. The framework performs heatmap regression relying on three anatomically relevant keypoints as a prior for AGA computation, which is estimated from the coordinates of the predicted points. The assessment of the proposed framework is performed using a newly collected dataset of 471 laryngoscopy frames from 124 patients, 28 of whom with cancer. The framework was tested in various configurations and compared with other state-of-the-art approaches (direct keypoints regression and glottal segmentation) for both pose estimation, and AGA evaluation. The proposed framework obtained the lowest root mean square error (RMSE) computed on all the keypoints (5.09, 6.56, and 6.40 pixels, respectively) among all the models tested for VF pose estimation. Also for the AGA evaluation, heatmap regression reached the lowest mean average error (MAE) ( 5 . 87 ∘ ). Results show that relying on keypoints heatmap regression allows to perform VF pose estimation with a small error, overcoming drawbacks of state-of-the-art algorithms, especially in challenging images such as pathologic subjects, presence of noise, and occlusion.
Parents play a fundamental role in the development of young people’s self-perceptions. In the context of education, psychological research has revealed that parental involvement (PI) is significantly related to students’ attitudes, beliefs, motivation, expectations, and academic outcomes. However, few studies have focused on a specific aspect of PI known as academic socialization, which refers to the importance that parents attribute to school and education, particularly in terms of how their educational values correspond with students’ psychological and academic adaptation. Thus, this study aimed to examine the associations between perceived parents’ educational values and students’ academic adjustment. A cross-sectional quantitative study was conducted on a sample of 477 Italian students (9th and 10th graders), with a mean age of 15.28 years (SD = .75; 50
