Brain mapping inflammatory-arthritis-related fatigue in the pursuit of novel therapeutics.

Despite developments in pharmacological treatments, chronic fatigue is an unresolved issue for most people with inflammatory arthritis that severely disrupts their personal and working lives. Fatigue in these patients is not strongly linked with peripheral disease activity but is associated with CNS-derived symptoms such as chronic pain, sleep disturbance, and depression. Therefore, a neurobiological basis should be considered when pursuing novel fatigue-specific therapeutics.

Characterizing the Neurobiological Mechanisms of Action of Exercise and Cognitive-Behavioral Interventions for Rheumatoid Arthritis Fatigue: A Magnetic Resonance Imaging Brain Study.

Objective: Chronic fatigue is a major clinical unmet need among patients with rheumatoid arthritis (RA). Current therapies are limited to nonpharmacological interventions, such as personalized exercise programs (PEPs) and cognitive-behavioral approaches (CBAs); however, most patients still continue to report severe fatigue. To inform more effective therapies, we conducted a magnetic resonance imaging (MRI) brain study of PEPs and CBAs, nested within a randomized controlled trial (RCT), to identify their neurobiological mechanisms of fatigue reduction in RA.

CMOS Image Sensor for Broad Spectral Range with >90% Quantum Efficiency.

Even though the recent progress made in complementary metal-oxide-semiconductor (CMOS) image sensors (CIS) has enabled numerous applications affecting our daily lives, the technology still relies on conventional methods such as antireflective coatings and ion-implanted back-surface field to reduce optical and electrical losses resulting in limited device performance. In this work, these methods are replaced with nanostructured surfaces and atomic layer deposited surface passivation. The results show that such surface nanoengineering applied to a commercial backside illuminated CIS significantly extends its spectral range and enhances its photosensitivity as demonstrated by >90% quantum efficiency in the 300-700 nm wavelength range.

Analysis of Behavior Classification in Motivational Interviewing.

Analysis of client and therapist behavior in counseling sessions can provide helpful insights for assessing the quality of the session and consequently, the client's behavioral outcome. In this paper, we study the automatic classification of standardized behavior codes (i.e.

Multimodal Automatic Coding of Client Behavior in Motivational Interviewing.

Motivational Interviewing (MI) is defined as a collaborative conversation style that evokes the client's own intrinsic reasons for behavioral change. In MI research, the clients' attitude (willingness or resistance) toward change as expressed through language, has been identified as an important indicator of their subsequent behavior change. Automated coding of these indicators provides systematic and efficient means for the analysis and assessment of MI therapy sessions.