Retinal oximetry and fractal analysis of capillary maps in sickle cell disease patients and matched healthy volunteers

Graefe's Archive for Clinical and Experimental Ophthalmology - Fractal analysis can be used to quantitatively analyze the retinal microvasculature and might be a suitable method to quantify...     

Ocular injuries resulting from commercial cosmetic procedures

The prevalence of potentially precarious cosmetic facial procedures appears to be on the rise. A significant amount of these cosmetic procedures are offered and performed by operators without formal medical training and anatomical knowledge, and with variable degrees of skill. Some of these procedures can result in devastating sight-threatening complications, and many of the individuals undergoing such treatments are relatively young and healthy. Patients need to be aware of the potential risks, including permanent visual loss, before embarking on any cosmetic facial procedure. Optometrists may be the first point of contact for patients with ocular complaints following these treatments. Hence, the authors present here a review on the various ocular injuries that may result from commercial cosmetic procedures.     

A novel immune competent murine hypertrophic scar contracture model: A tool to elucidate disease mechanism and develop new therapies

Hypertrophic scar (HSc) contraction following burn injury causes contractures. Contractures are painful and disfiguring. Current therapies are marginally effective. To study pathogenesis and develop new therapies, a murine model is needed. We have created a validated immune‐competent murine HSc model. A third‐degree burn was created on dorsum of C57BL/6 mice. Three days postburn, tissue was excised and grafted with ear skin. Graft contraction was analyzed and tissue harvested on different time points. Outcomes were compared with human condition to validate the model. To confirm graft survival, green fluorescent protein (GFP) mice were used, and histologic analysis was performed to differentiate between ear and back skin. Role of panniculus carnosus in contraction was analyzed. Cellularity was assessed with 4′,6‐diamidino‐2‐phenylindole. Collagen maturation was assessed with Picro‐sirius red. Mast cells were stained with Toluidine blue. Macrophages were detected with F4/80 immune. Vascularity was assessed with CD31 immune. RNA for contractile proteins was detected by quantitative real‐time polymerase chain reaction (qRT‐PCR). Elastic moduli of skin and scar tissue were analyzed using a microstrain analyzer. Grafts contracted to ～45% of their original size by day 14 and maintained their size. Grafting of GFP mouse skin onto wild‐type mice, and analysis of dermal thickness and hair follicle density, confirmed graft survival. Interestingly, hair follicles disappeared after grafting and regenerated in ear skin configuration by day 30. Radiological analysis revealed that panniculus carnosus doesn't contribute to contraction. Microscopic analyses showed that grafts show increase in cellularity. Granulation tissue formed after day 3. Collagen analysis revealed increases in collagen maturation over time. CD31 stain revealed increased vascularity. Macrophages and mast cells were increased. qRT‐PCR showed up‐regulation of transforming growth factor beta, alpha smooth muscle actin, and rho‐associated protein kinase 2 in HSc. Tensile testing revealed that human skin and scar tissues are tougher than mouse skin and scar tissues.     

Distinct electrophysiological signatures of task-unrelated and dynamic thoughts

Humans spend much of their lives engaging with their internal train of thoughts. Traditionally, research focused on whether or not these thoughts are related to ongoing tasks, and has identified reliable and distinct behavioral and neural correlates of task-unrelated and task-related thought. A recent theoretical framework highlighted a different aspect of thinking—how it dynamically moves between topics. However, the neural correlates of such thought dynamics are unknown. The current study aimed to determine the electrophysiological signatures of these dynamics by recording electroencephalogram (EEG) while participants performed an attention task and periodically answered thought-sampling questions about whether their thoughts were 1) task-unrelated, 2) freely moving, 3) deliberately constrained, and 4) automatically constrained. We examined three EEG measures across different time windows as a function of each thought type: stimulus-evoked P3 event-related potentials and non–stimulus-evoked alpha power and variability. Parietal P3 was larger for task-related relative to task-unrelated thoughts, whereas frontal P3 was increased for deliberately constrained compared with unconstrained thoughts. Frontal electrodes showed enhanced alpha power for freely moving thoughts relative to non-freely moving thoughts. Alpha-power variability was increased for task-unrelated, freely moving, and unconstrained thoughts. Our findings indicate distinct electrophysiological patterns associated with task-unrelated and dynamic thoughts, suggesting these neural measures capture the heterogeneity of our ongoing thoughts.

Cognitive neuroscience has reached a consensus that the brain is not idle at rest (1). This rings intuitively true: When left alone, our minds rarely stay still. Moreover, recent evidence suggests that rest is not a homogeneous state (2), nor is the brain truly “at rest” as it fluctuates across time and contexts (3–6). This too is intuitive: What is striking is not just that we move from thought to thought unprompted but also the diverse ways that trains of thought unfold over time. Sometimes, our thoughts freely wander between topics. You might remember this morning’s run, then imagine gardening, then think about the dinner you’ll cook tonight. Other times, we deliberately constrain our thoughts and work diligently toward a goal. In a quiet moment, you might methodically contemplate the results of your latest experiment. Still other times, our thoughts get stuck on an affectively salient topic, from which it is difficult to break free. You might worry, over and over, about your niece who is going through major surgery next week.Research has traditionally examined the internal train of thought in the context of mind wandering. This field has expanded at such a rapid pace that some have dubbed this the “era of the wandering mind” (7). To date, the vast majority of mind-wandering research has focused on the static content of individual thoughts. In particular, mind-wandering studies have primarily focused on task-unrelated thought (8)—that is, thoughts that are unrelated to an ongoing, typically externally oriented, task (8–10). In the laboratory, subjects’ thoughts are often unrelated to the experimental task (9). Task-unrelated thought is also frequent in everyday life (11), as when a student becomes distracted during a lecture or while driving.Recent theories are less task-centric and instead focus on the dynamics of mind wandering—that is, how internal trains of thoughts unfold over time (12–17). In particular, the “dynamic framework” of spontaneous thought distinguishes three subtypes within the train of thoughts: 1) deliberately constrained, 2) automatically constrained, and 3) freely moving thoughts (12, 14). Constraints on the train of thoughts serve to focus internal attention on a topic for extended periods of time. For example, deliberately constrained thoughts occur when a person actively directs her thoughts to goal-relevant information (e.g., when you contemplate your latest experiment). This type of constraint is implemented through cognitive control. Automatically constrained thoughts focus on affectively or personally salient information that is difficult to disengage from (e.g., when you worry about your niece who will have surgery). This type of constraint is automatic in nature and thought to operate largely outside of cognitive control. In contrast, freely moving thoughts occur when both of these constraints are weak, allowing the mind to wander with no overarching purpose and direction (e.g., when your thoughts drift from a movie, to gardening, to dinner). Notably, the dynamic framework purports that these three subtypes of thoughts are independent of task relatedness. In other words, task-related and task-unrelated thoughts can both be deliberately constrained, automatically constrained, or freely moving. See SI Appendix for further details about the relationship between dynamic categories.Empirical research on the dynamics of thought is in its infancy. Behavioral research has focused on contrasting task-unrelated thoughts with the other three subtypes of thoughts, with a particular emphasis on freely moving thoughts. These findings suggest that self-reported freely moving and task-unrelated thoughts have distinct behavioral markers. For example, studies of mind wandering in everyday life found that self-reports of freely moving and task-unrelated thought fluctuate at different rates throughout the day (11). Consistent with predictions of the dynamic framework, these studies reported that task-unrelated and freely moving thoughts are only modestly correlated (r < 0.3) and they occurred independent of each other (8, 11). Specifically, although task-related thoughts are often deliberately constrained and task-unrelated thoughts sometimes move freely, the dynamic framework predicts that this is not always the case. In fact, task-related thoughts can move freely (e.g., when a graphic designer freely associate ideas for her new website design) or be automatically constrained (e.g., when someone obsesses over a problem at work). Task-unrelated thoughts can be deliberately or automatically constrained (e.g., when you construct a grocery list or worry about your niece’s surgery during a lecture). The only two empirical studies to date have focused explicitly on freely moving thought (8, 11). Although this provides some initial evidence that task-unrelated thought is different from dynamic thoughts, no studies have assessed the neural correlates of dynamic thought types. The identification of different electrophysiological signatures of these thought types would thus provide important validation that these categories reflect distinct entities.In the current study, we examined the electrophysiological signatures of the four types of thought by recording an electroencephalogram (EEG) while participants performed an attention task. Participants occasionally answered thought-sampling questions about the nature of their thoughts throughout the task. Thought sampling is the standard method in mind-wandering research: Participants are randomly interrupted as they perform a laboratory task and answer questions about their immediately preceding thoughts (9, 10). In line with previous studies, we ask the standard question about whether participants’ thoughts were task-unrelated (see ref. 8 for a review). In addition, we asked whether subjects’ trains of thought were freely moving, deliberately constrained, and automatically constrained.We used electroencephalography because this method has the temporal resolution necessary to capture the transient changes in neural activity corresponding to our trains of thoughts, including stimulus-evoked, task-dependent activity and stimulus-independent, intrinsic activity. We first examined event-related potentials (ERPs), which index the electrophysiological response evoked by task-relevant stimuli. Previous research suggests that task-unrelated thought attenuates the magnitude of ERP components associated with sensory (18–20) and cognitive (21–24) processing of task-relevant stimuli. ERPs therefore provide an electrophysiological signature of when a participant has disengaged from task-relevant stimuli. We predicted that task-unrelated thoughts would be associated with a reduced P3 ERP component.To index stimulus-independent, intrinsic neural activity, we examined spectral power in the alpha band (8 to 14 Hz) during a time window after the offset of ERPs, which is unlikely to be impacted by stimulus-evoked responses. This segregation of the poststimulus time window allowed us to disentangle stimulus-evoked, task-dependent responses captured by ERP components in the earlier window and stimulus-independent activity likely associated with the subject’s ongoing thoughts as captured by alpha power in the later time window (as illustrated in Fig. 1). Alpha-power increases recorded over posterior sites have been associated with internal attention (23, 25) as well as spontaneous brain activity recorded at rest that is not elicited by external stimuli (26, 27). In contrast, frontal alpha has been linked to creative, divergent thinking (28, 29). Accordingly, we hypothesized that task-unrelated thoughts would be associated with enhanced posterior alpha power, whereas freely moving thoughts would be associated with increased frontal alpha power. Given that our dynamic thought-sampling questions address variability within the train of thought over time, we examined the neural correlates of these thought dynamics by capturing momentary changes in alpha power (i.e., alpha-power variability) over the same ERP-free time window. We predicted that freely moving thought would be associated with increased alpha-power variability, whereas constrained thought would show reduced alpha-power variability.Open in a separate windowFig. 1.EEG measures across the poststimulus time window. We examined three EEG measures. Stimulus-evoked activity as captured by P3 ERP components was examined during the 0- to 0.6-s poststimulus time window. Alpha power and variability index intrinsic neural activity not impacted by an external stimulus examined after the offset of P3s during the 0.6- to 1.8-s poststimulus time window.