Hypothalamic communication with the rest of the brain is critical for accomplishing a wide variety of physiological and psychological functions, including the maintenance of neuroendocrine circadian rhythms and the management of affective processes. Evidence has shown that major depressive disorder (MDD) patients exhibit increased functioning of the hypothalamic-pituitary-adrenal (HPA) axis. Neurofibrillary tangles are also found in the hypothalamus of Alzheimer’s disease (AD) patients, and AD patients exhibit abnormal changes in the HPA. However, little is known of how the hypothalamus interacts with other brain regions in AD patients with depression (D-AD). Functional connectivity (FC) analysis explores the connectivity between brain regions that share functional properties. Here, we used resting-state (rs) magnetic resonance imaging (MRI) technology and the FC method to measure hypothalamic connectivity across the whole brain in 22 D-AD patients and 21 non-depressed AD patients (nD-AD). Our results showed that D-AD patients had reduced FC among the hypothalamus, the right middle temporal gyrus (MTG) and the right superior temporal gyrus (STG) compared with the FC of nD-AD patients, suggesting that the abnormal FC between the hypothalamus and the temporal lobe may play a key role in the pathophysiology of depression in AD patients.

Mild traumatic brain injury (mTBI) initiating long-term effects on white matter integrity resembles brain-aging changes, implying an aging process accelerated by mTBI. This longitudinal study aims to investigate the mTBI-induced acceleration of the brain-aging process by developing a neuroimaging model to predict brain age. The brain-age prediction model was defined using relevance vector regression based on fractional anisotropy from diffusion tensor imaging of 523 healthy individuals. The model was used to estimate the brain-predicted age difference (brain-PAD) between the chronological and estimated brain age in 116 acute mTBI patients and 63 healthy controls. Fifty patients were followed for 6 ∼ 12 months to evaluate the longitudinal changes in brain-PAD. We investigated whether brain-PAD was greater in patients of older age, post-concussion complaints, and apolipoprotein E (APOE) ɛ4 genotype, and whether it had the potential to predict neuropsychological outcomes. The brain-age prediction model predicted brain age accurately ( r = 0.96). The brains of mTBI patients in the acute phase were estimated to be “older,” with greater brain-PAD (2.59 ± 5.97 years) than the healthy controls (0.12 ± 3.19 years) ( p < 0.05), and remained stable 6–12 month post-injury (2.50 ± 4.54 years). Patients who were older or who had post-concussion complaints, rather than APOE ɛ4 genotype, had greater brain-PADs ( p < 0.001, p = 0.024). Additionally, brain-PAD in the acute phase predicted information processing speed at the 6 ∼ 12 month follow-up ( r = -0.36, p = 0.01). In conclusion, mTBI accelerates the brain-aging process, and brain-PAD may be capable of evaluating aging-associated issues post-injury, such as increased risks of neurodegeneration.

Flexible pressure sensors have attracted significant attention in both academic and industrial fields. However, how to design and fabricate a flexible pressure sensor having high sensitivity and good linearity in a wide detection range is still a challenge. To address this challenge, this article proposes a flexible piezoresistive pressure sensor with a multilayer structure consisting of microstructured composite layers (MCLs), which are sandwiched by indium tin oxide-polyethylene terephthalate electrodes and encapsulated by an ultrasoft elastomer frame. The preparation of the conductive composite and the fabrication procedure of the pressure sensor are presented. Due to the point-to-point hemisphere microstructures of the multilayer composite layers, the pressure sensor can perceive pressure with a sensitivity of 7.66 kPa ⁻¹ in a range of 0–583 kPa. Besides, the proposed sensor features good linearity of 5.86% and an $R^{2}$ of 0.99. The developed pressure sensor has excellent repeatability of 500 cycles and a fast response time of 80 ms. The proposed sensor is verified by the experiments with primary applications, and the obtained results indicate it could be potentially utilized as wearable detectors.

Mild traumatic brain injury (mTBI) is the most prevalent neurological insult and leads to long-lasting cognitive impairment. Neuroimaging studies have discovered abnormalities in brain network connectivity following mTBI as the underlying neural basis of cognitive deficits. However, the pathophysiologic mechanisms involved in imaging alterations remain elusive. Proteins neuron-specific enolase (NSE) and ubiquitin C terminal hydrolase 1 are reliable markers for neuronal cell-body damage, both of which have been demonstrated to be increased in serum following mTBI. Therefore, we conducted a longitudinal study to examine relationships between abnormal brain network connectivity and serum neuronal biomarkers and their associations with cognitive recovery following mTBI. Sixty patients were followed-up at 1 week and 3 months post-injury and 41 controls were recruited. Resting-state functional magnetic resonance imaging was used to build a functional connectivity matrix within large-scale intrinsic networks, and their topological properties were analyzed using graph theory measures. We found that, compared with controls, mTBI patients showed significant decreases in a number of nodal characteristics in default mode network (DMN), salience network, and executive network ( p < 0.05, false discovery rate corrected) at 3 months post-injury. Linear regression analysis found elevated serum NSE in acute phase could predict lower efficiency and degree centrality of anterior DMN at 3 months post-injury. In addition, efficiency and degree centrality of anterior DMN were negatively associated with working memory. Our study showed neuronal injury was associated with alterations in brain network connectivity after mTBI. These findings can facilitate capability to predict the brain functional outcomes and cognitive recovery in mTBI.

Background: Neuroanatomical alterations have been associated with cognitive deficits in mild traumatic brain injury (MTBI). However, most studies have focused on the abnormal gray matter volume in widespread brain regions using a cross-sectional design in MTBI. This study investigated the neuroanatomical restoration of key regions in salience network and the outcomes in MTBI. Methods: Thirty-six MTBI patients with posttraumatic headache (PTH) and 34 matched healthy controls were enrolled in this study. All participants underwent magnetic resonance imaging scans and were assessed with clinical measures during the acute and subacute phases. Surface-based morphometry was conducted to get cortical thickness (CT) and cortical surface area (CSA) of neuroanatomical regions which were defined by the Desikan atlas. Then mixed analysis of variance models were performed to examine CT and CSA restoration in patients from acute to subacute phase related to controls. Finally, mediation effects models were built to explore the relationships between neuroanatomical restoration and symptomatic improvement in patients. Results: MTBI patients with PTH showed reduced headache impact and improved cognitive function from the acute to subacute phase. Moreover, patients experienced restoration of CT of the left caudal anterior cingulate cortex (ACC) and left insula and cortical surface area of the right superior frontal gyrus from acute to subacute phase. Further mediation analysis found that CT restoration of the ACC and insula mediated the relationship between reduced headache impact and improved cognitive function in patients. Conclusions: These results showed that neuroanatomical restoration of key regions in salience network correlated reduced headache impact with cognitive function improvement in MTBI with PTH, which further substantiated the vital role of salience network and provided an alternative clinical target for cognitive improvement in MTBI patients with PTH. Graphical