Estimating Systemic Cognitive States from a Mixture of Physiological and Brain Signals.

As human-machine teams are being considered for a variety of mixed-initiative tasks, detecting and being responsive to human cognitive states, in particular systematic cognitive states, is among the most critical capabilities for artificial systems to ensure smooth interactions with humans and high overall team performance. Various human physiological parameters, such as heart rate, respiration rate, blood pressure, and skin conductance, as well as brain activity inferred from functional near-infrared spectroscopy or electroencephalogram, have been linked to different systemic cognitive states, such as workload, distraction, or mind-wandering among others. Whether these multimodal signals are indeed sufficient to isolate such cognitive states across individuals performing tasks or whether additional contextual information (e.g., about the task state or the task environment) is required for making appropriate inferences remains an important open problem. In this paper, we introduce an experimental and machine learning framework for investigating these questions and focus specifically on using physiological and neurophysiological measurements to learn classifiers associated with systemic cognitive states like cognitive load, distraction, sense of urgency, mind wandering, and interference. Specifically, we describe a multitasking interactive experimental setting used to obtain a comprehensive multimodal data set which provided the foundation for a first evaluation of various standard state-of-the-art machine learning techniques with respect to their effectiveness in inferring systemic cognitive states. While the classification success of these standard methods based on just the physiological and neurophysiological signals across subjects was modest, which is to be expected given the complexity of the classification problem and the possibility that higher accuracy rates might not in general be achievable, the results nevertheless can serve as a baseline for evaluating future efforts to improve classification, especially methods that take contextual aspects such as task and environmental states into account.

Microneedle-based insulin transdermal delivery system: current status and translation challenges.

Diabetes mellitus is a metabolic disease manifested by hyperglycemia. For patients with type 1 and advanced type 2 diabetes mellitus, insulin therapy is essential. Subcutaneous injection remains the most common administration method. Non-invasive insulin delivery technologies are pursued because of their benefits of decreasing patients' pain, anxiety, and stress. Transdermal delivery systems have gained extensive attention due to the ease of administration and absence of hepatic first-pass metabolism. Microneedle (MN) technology is one of the most promising tactics, which can effectively deliver insulin through skin stratum corneum in a minimally invasive and painless way. This article will review the research progress of MNs in insulin transdermal delivery, including hollow MNs, dissolving MNs, hydrogel MNs, and glucose-responsive MN patches, in which insulin dosage can be strictly controlled. The clinical studies about insulin delivery with MN devices have also been summarized and grouped based on the study phase. There are still several challenges to achieve successful translation of MNs-based insulin therapy. In this review, we also discussed these challenges including safety, efficacy, patient/prescriber acceptability, manufacturing and scale-up, and regulatory authority acceptability.

Domain adaptation for robust workload level alignment between sessions and subjects using fNIRS.

SIGNIFICANCE: We demonstrated the potential of using domain adaptation on functional near-infrared spectroscopy (fNIRS) data to classify different levels of n-back tasks that involve working memory. AIM: Domain shift in fNIRS data is a challenge in the workload level alignment across different experiment sessions and subjects. To address this problem, two domain adaptation approaches-Gromov-Wasserstein (G-W) and fused Gromov-Wasserstein (FG-W) were used. APPROACH: Specifically, we used labeled data from one session or one subject to classify trials in another session (within the same subject) or another subject. We applied G-W for session-by-session alignment and FG-W for subject-by-subject alignment to fNIRS data acquired during different n-back task levels. We compared these approaches with three supervised methods: multiclass support vector machine (SVM), convolutional neural network (CNN), and recurrent neural network (RNN). RESULTS: In a sample of six subjects, G-W resulted in an alignment accuracy of 68 % ± 4 % (weighted mean ± standard error) for session-by-session alignment, FG-W resulted in an alignment accuracy of 55 % ± 2 % for subject-by-subject alignment. In each of these cases, 25% accuracy represents chance. Alignment accuracy results from both G-W and FG-W are significantly greater than those from SVM, CNN, and RNN. We also showed that removal of motion artifacts from the fNIRS data plays an important role in improving alignment performance. CONCLUSIONS: Domain adaptation has potential for session-by-session and subject-by-subject alignment of mental workload by using fNIRS data.

Factors associated with obesity alter matrix remodeling in breast cancer tissues.

Obesity is associated with a higher risk of developing breast cancer and with worse disease outcomes for women of all ages. The composition, density, and organization of the breast tissue stroma are also known to play an important role in the development and progression of the disease. However, the connections between obesity and stromal remodeling are not well understood. We sought to characterize detailed organization features of the collagen matrix within healthy and cancerous breast tissues acquired from mice exposed to either a normal or high fat (obesity inducing) diet. We performed second-harmonic generation and spectral two-photon excited fluorescence imaging, and we extracted the level of collagen-associated fluorescence (CAF) along with metrics of collagen content, three-dimensional, and two-dimensional organization. There were significant differences in the CAF intensity and overall collagen organization between normal and tumor tissues; however, obesity-enhanced changes in these metrics, especially when three-dimensional organization metrics were considered. Thus, our studies indicate that obesity impacts significantly collagen organization and structure and the related pathways of communication may be important future therapeutic targets.

[Effect and regulation mechanism of Chinese Bushen Huoxue prescriptions on endometrial receptivity].

Endometrial receptivity refers to the ability of endometrium to accept and accommodate endometrial implantation in the process of embryo implantation in implantation window period. It is an important factor affecting the rate of blastocyst implantation in assisted reproduction. It is worth mentioning that ovulation-promoting drugs in current assisted reproduction technology could reduce endometrial receptivity and inhibit blastocyst implantation, greatly affecting the success rate of assisted reproduction. By searching Chinese Scientific Citation Database, it was found that 121 studies from 2006 to 2017 showed that Chinese Bushen Huoxue prescriptions could significantly improve the development of pinopodes in the implantation window, promote the expression of endometrial receptors ER, PR, integrinß3, LIF, LPA3 and other molecules, and thus enhancing endometrial receptivity and improving embryo implantation. In the theory of traditional Chinese medicine, kidney deficiency is an important factor causing infertility. Chinese Bushen Huoxue prescriptions could nourish the kidney-essence, and promote blood circulation, playing an important role in treating infertility with combined application of western medicine and traditional Chinese medicine. These studies suggest that Chinese Bushen Huoxue prescriptions could improve endometrial receptivity, and their mechanisms are worth further investigation. This article has summarized the research progress of Chinese Bushen Huoxue prescriptions in the field of assisted reproduction, summarized the deficiency of current researches, and preliminarily discussed the potential application prospect of Chinese Bushen Huoxue prescriptions in the treatment of infertility.