Smokers\u27 Neurological Responses to Novel and Repeated Health Warning Labels (HWLs) From Cigarette Packages

Graphic health warning labels (HWLs) depicting bodily injury due to smoking are effective for producing changes in affect, cognition and smoking behavior in adult smokers. However, little is known about the effects of repeated presentation of graphic HWL’s on the aforementioned processes. The goal of this study was to examine neural and behavioral responses to graphic HWL’s and evaluate whether the repeated presentation of graphic HWL’s leads to repetition suppression (RS). Smokers (N = 16) performed an event-related HWL cue task while blood oxygen level dependent (BOLD) signal was collected during a functional magnetic resonance imaging (fMRI) experimental session. Consistent with prior literature, graphic HWL’s, as compared to scrambled images, elicited increased BOLD response in brain regions involved in self-referential and emotion processing. Importantly, BOLD response at sites in this network diminished during repeated presentation of the same HWL. These findings suggest that while novel graphic HWL’smay have a significant effect on smokers’ brain activity, repeated presentationmay lead to muted responses and thus limit their potential to induce behavioral change

Yoga Meditation Practitioners Exhibit Greater Gray Matter Volume and Fewer Reported Cognitive Failures: Results of a Preliminary Voxel-Based Morphometric Analysis

Hatha yoga techniques, including physical postures (asanas), breathing exercises (pranayama), and meditation, involve the practice of mindfulness. In turn, yoga meditation practices may induce the state of mindfulness, which, when evoked recurrently through repeated practice, may accrue into trait or dispositional mindfulness. Putatively, these changes may be mediated by experience-dependent neuroplastic changes. Though prior studies have identified differences in gray matter volume (GMV) between long-term mindfulness practitioners and controls, no studies to date have reported on whether yoga meditation is associated with GMV differences. The present study investigated GMV differences between yoga meditation practitioners (YMP) and a matched control group (CG). The YMP group exhibited greater GM volume in frontal, limbic, temporal, occipital, and cerebellar regions; whereas the CG had no greater regional greater GMV. In addition, the YMP group reported significantly fewer cognitive failures on the Cognitive Failures Questionnaire (CFQ), the magnitude of which was positively correlated with GMV in numerous regions identified in the primary analysis. Lastly, GMV was positively correlated with the duration of yoga practice. Results from this preliminary study suggest that hatha yoga practice may be associated with the promotion of neuroplastic changes in executive brain systems, which may confer therapeutic benefits that accrue with repeated practice

Meditation-State Functional Connectivity (msFC): Strengthening of the Dorsal Attention Network and Beyond

Meditation practice alters intrinsic resting-state functional connectivity (rsFC) in the default mode network (DMN). However, little is known regarding the effects of meditation on other resting-state networks. The aim of current study was to investigate the effects of meditation experience and meditation-state functional connectivity (msFC) on multiple resting-state networks (RSNs). Meditation practitioners (MPs) performed two 5-minute scans, one during rest, one while meditating. A meditation naïve control group (CG) underwent one resting-state scan. Exploratory regression analyses of the relations between years of meditation practice and rsFC and msFC were conducted. During resting-state, MP as compared to CG exhibited greater rsFC within the Dorsal Attention Network (DAN). Among MP, meditation, as compared to rest, strengthened FC between the DAN and DMN and Salience network whereas it decreased FC between the DAN, dorsal medial PFC, and insula. Regression analyses revealed positive correlations between the number of years of meditation experience and msFC between DAN, thalamus, and anterior parietal sulcus, whereas negative correlations between DAN, lateral and superior parietal, and insula. These findings suggest that the practice of meditation strengthens FC within the DAN as well as strengthens the coupling between distributed networks that are involved in attention, self-referential processes, and affective response

Quantification of the Calcification Phenotype of Abcc6-Deficient Mice with Microcomputed Tomography

Pseudoxanthoma elasticum in humans and dystrophic cardiac calcification in mice are heritable disorders characterized by dystrophic calcification of soft connective tissues related to the defective function of the ABCC6 (human)/Abcc6 (mouse) transporter. Of particular interest is the finding of calcified vibrissae in Abcc6−/− mice, which facilitates the study of dystrophic calcification by histological techniques. We aimed to determine whether mice prone to dystrophic cardiac calcification (C3H/HeOuJ and DBA/2J strains) presented similar vibrissae changes and to evaluate the value of microcomputed tomography to quantify the extent of mystacial vibrissae calcifications. These calcifications were absent in DBA/2J and C57BL/6J control mice. In both Abcc6−/− and C3H/HeOuJ mice, calcifications progressed in a caudal-rostral direction with aging. However, the calcification process was delayed in C3H/HeOuJ mice, indicating an incomplete expression of the calcification phenotype. We also found that the calcification process in the cephalic region was not limited to mystacial vibrissae but was also present in other periorbital sensorial vibrissae. The vibrissae calcification was circular and encompassed the medial region of the vibrissae capsule, adjacent to the ring and cavernous sinuses (the areas adjacent to blood and lymphatic vessels). Collectively, our findings confirm that Abcc6 acts as an inhibitor of spontaneous chronic mineralization and that microcomputed tomography is a valuable noninvasive tool for the assessment of the calcification phenotype in Abcc6-deficient mice

Regulation of proteinaceous effector expression in phytopathogenic fungi

Effectors are molecules used by microbial pathogens to facilitate infection via effector-triggered susceptibility or tissue necrosis in their host. Much research has been focussed on the identification and elucidating the function of fungal effectors during plant pathogenesis. By comparison, knowledge of how phytopathogenic fungi regulate the expression of effector genes has been lagging. Several recent studies have illustrated the role of various transcription factors, chromosome-based control, effector epistasis, and mobilisation of endosomes within the fungal hyphae in regulating effector expression and virulence on the host plant. Improved knowledge of effector regulation is likely to assist in improving novel crop protection strategies

Toward Concurrent Identification of Human Activities with a Single Unifying Neural Network Classification: First Step

The characterization of human behavior in real-world contexts is critical for developing a comprehensive model of human health. Recent technological advancements have enabled wearables and sensors to passively and unobtrusively record and presumably quantify human behavior. Better understanding human activities in unobtrusive and passive ways is an indispensable tool in understanding the relationship between behavioral determinants of health and diseases. Adult individuals (N = 60) emulated the behaviors of smoking, exercising, eating, and medication (pill) taking in a laboratory setting while equipped with smartwatches that captured accelerometer data. The collected data underwent expert annotation and was used to train a deep neural network integrating convolutional and long short-term memory architectures to effectively segment time series into discrete activities. An average macro-F1 score of at least 85.1 resulted from a rigorous leave-one-subject-out cross-validation procedure conducted across participants. The score indicates the method’s high performance and potential for real-world applications, such as identifying health behaviors and informing strategies to influence health. Collectively, we demonstrated the potential of AI and its contributing role to healthcare during the early phases of diagnosis, prognosis, and/or intervention. From predictive analytics to personalized treatment plans, AI has the potential to assist healthcare professionals in making informed decisions, leading to more efficient and tailored patient care