Hypothermia and focal brain cooling (FBC) demonstrate neuroprotective effects in ischemic stroke, but their invasiveness limits clinical use. We explored transient receptor potential (TRP) channels as an alternative, focusing on TRP Ankyrin 1 (TRPA1), which operates within the temperature range of FBC. Activation of TRPA1 has been reported to offer neuroprotection, suggesting it may contribute to the effects seen with FBC. We hypothesized that pharmacological activation of TRPA1 could replicate the neuroprotective effects of FBC, providing a less invasive treatment for cerebral infarction. We examined the effects of a TRPA1 agonist and FBC in focal cerebral ischemia induced by photochemically triggered thrombosis in wild-type (WT) and TRPA1 knockout (KO) mice. In WT mice, intracerebroventricular administration of the TRPA1 agonist allyl isothiocyanate reduced infarct size by approximately half, comparable to FBC. TRPA1 KO mice had larger infarcts than WT, but FBC significantly reduced infarct size in both groups. Furthermore, Evans blue extravasation, used to assess the extent of blood-brain barrier disruption, was approximately twice as high in TRPA1KO mice compared to WT mice. These findings underscore the neuroprotective potential of TRPA1 agonists and the increased vulnerability against ischemia with TRPA1 deficiency. However, the neuroprotective effects of TRPA1 activation are likely mediated by a mechanism distinct from that of FBC. Our study suggests TRPA1 channels are crucial for ischemic stroke protection and may offer a novel therapeutic approach.

Focal brain cooling (FBC) at 15℃ and transient receptor potential vanilloid 4 (TRPV4) deficiency relieve brain infarction. TRPV4 channels are inactivated by cooling (< 27℃), suggesting that the anti-ischemic effects of FBC include those of TRPV4 inactivation. However, the extent to which TRPV4 inactivation contributes to the anti-ischemic, anti- blood-brain barrier (BBB) disruption, and anti-apoptosis effects of FBC on cerebral infarction remains unclear. We investigated the contribution and mechanisms of RN1734, a TRPV4 antagonist, in FBC for cerebral infarction using TRPV4 knockout and wild-type mice. Focal cerebral infarction was induced by photochemically induced thrombosis. Infarct volume, BBB disruption, and number of apoptotic cells were evaluated. The TRPV4 antagonist or deficiency showed similar anti-ischemic and anti-BBB disruptive effects to those of FBC. Intracerebroventricular injection of RN1734 showed a similar reduction in the number of apoptotic cells to that of FBC. These anti-ischemic and -apoptotic effects were completely inhibited with injection of GSK1016790A, a TRPV4 agonist, immediately before FBC. Our results showed that TRPV4 modulation is the primary factor contributing to the antiischemic effects of FBC, and TRPV4 channel inactivation relieve focal ischemic infarction by relieving BBB disruption and preventing apoptosis. Therefore, FBC treatment improves ischemic stroke through the modulation of TRPV4 channels.

A 70-year-old woman presented with acute fever, impaired consciousness, leukopenia, thrombocytopenia, and right inguinal lymphadenopathy. A lymph node biopsy was diagnosed as diffuse large B-cell lymphoma (DLBCL). However, her symptoms were consistent with severe fever with thrombocytopenia syndrome (SFTS), and RT-PCR for SFTS virus (SFTSV) RNA was positive. The patient’s condition and lymphadenopathy gradually improved with supportive measures and short-term steroid treatment and no lymphadenopathy recurrence was observed. Lymph node pathological examination revealed SFTSV-infected cells, leading to the final diagnosis of necrotizing lymphadenitis associated with SFTS. Careful consideration is required to differentiate necrotizing lymphadenitis associated with SFTS from that associated with DLBCL.

Blood-brain barrier (BBB) dysfunction found in the multiple sclerosis (MS) cases is generally considered as a consequence of neuroinflammation. In this study we challenge this view by developing and analyzing novel BBB model from MS patients using induced pluripotent stem cells (iPSCs). We differentiated iPSCs into brain microvascular endothelial cell (BMEC)-like cells to establish an in vitro BBB model. We found that BMEC-like cells from MS patients exhibited compromised barrier integrity, characterized by weakened junctions, heightened permeability, and an elevated inflammatory profile when compared to cells from healthy individuals. Notably, the activation of the Wnt/β-catenin signaling pathway led to improvements in barrier function and a reduction in inflammatory responses, indicating potential therapeutic targets for reinforcing BBB stability in MS.

Cardiac hypertrophy is widely recognized as a significant risk factor contributing to adverse outcomes in individuals with cardiovascular conditions. The disruption of intracellular calcium ( Ca^{2+} ) balance has been implicated in the development of cardiac hypertrophy, though the precise mechanisms remain poorly understood. In this research, we explored whether hypertrophy induced by pressure overload may arise from the destabilization of the cardiac ryanodine receptor (RyR2) triggered by the dissociation of calmodulin (CaM), leading to subsequent Ca^{2+} leakage. We also assessed whether genetically strengthening the binding affinity between CaM and RyR2 could potentially reverse this process. In the early phases of cardiac hypertrophy caused by pressure overload—when contractile function is still intact—we observed that RyR2 destabilization mediated by reactive oxygen species (ROS) coincides with impaired relaxation. Moreover, stabilizing RyR2 through enhanced CaM binding was found to completely inhibit hypertrophic signaling and improve survival rates. Our findings reveal a crucial connection between RyR2 destabilization and the progression of cardiac hypertrophy.

This study explores the innovative applications of depth cameras combined with Graph Convolutional Networks (GCN) for action recognition in two critical domains: elderly care and smart education. We harness the capabilities of depth cameras to capture spatial and temporal features, alongside our robust GCN algorithm, to develop models capable of accurately recognizing and classifying human actions. In elderly care, our model is particularly focused on detecting and analyzing falls, which are crucial for enhancing care safety and supporting the independence of elderly individuals. Experimental results demonstrate that our depth camera-based action recognition model achieved an impressive average accuracy of 96.3% in fall detection within real-world scenarios, while also maintaining low rates of false positives and false negatives. In the realm of smart education, our depth camera-based model is specifically designed to recognize students’ hand-raising actions in real-time, which is crucial for comprehensively assessing student engagement in the class, and accordingly adjusting teaching strategies. Experimental results show that our model achieves an average accuracy of 89.7% in realworld scenarios, while maintaining low rates of false positives and false negatives. Overall, this study showcases the powerful potential of integrating depth cameras with GCNs for action recognition, significantly enhancing both the safety and efficiency of elderly care, as well as the interactivity and educational quality of smart education.