This study investigated the color-related compounds of Salvia miltiorrhiza after sweating. Stereomicroscopy and Electronic eye system were employed to characterize color variation. UPLC-Q-Orbitrap-MS and HPLC identified differential compounds. Furthermore, μ-FTIR and MALDI-MSI visualized the spatial distribution of compounds, and the compounds distribution was confirmed via HPLC. Result showed that after sweating, the appearance characteristics of Salvia miltiorrhiza changed significantly, exhibiting a reddish-brown epidermis and purple-brown inner tissue. Among 49 significantly altered compounds, tanshinones accounted for 58%. HPLC further indicated that the content of tanshinones showed a significant increase. Integrated μ-FTIR and MALDI-MSI demonstrated tanshinones increased after sweating and accumulated in the epidermis. Further confirmation of the increase in tanshinones was achieved by HPLC analysis of epidermis and cortex isolated. These results reveal tanshinones as the color-related compounds and clarify their spatial distribution, providing insights into the chemical changes during the traditional sweating process of Salvia miltiorrhiza.

Objective: Delusional syndromes of misidentification and/or reduplication (DSMRs) are based on the misidentification or duplication of people, places, objects, or events. A qualitative and comprehensive investigation was conducted to shed light on the core neurological and neuropsychological features and, neural correlates of all DSMRs, particularly Reduplicative Paramnesia for Place (RPP). Method: A detailed and systematic approach based on clinical, experimental, and neuroimaging data was carried out in a single case. We investigated the role played by the co-presence of an alteration of the sense of familiarity and damage to the critical belief evaluation system as a necessary condition for the generation of all DSMRs, and in particular for RPP. Results: Unlike most of previously described cases, RPP syndrome persists during the chronic phase in the context of a well-preserved global cognitive status whereas other forms of DSMRs tend to recover over time. In addition, there is a persistent alteration in the sense of familiarity and absence of critical evaluation of delusional beliefs. A structural disconnection analysis relates cortical-subcortical damaged areas and the corresponding white matter fasciculi with the clinical manifestation of DSMRs syndromes. Conclusions: The striato-capsular stroke coupled with subcortical damages and bifrontal cortical atrophy may explain the clinical manifestations and experimental data obtained and are in agreement with the bicomponential model hypothesis highlighting the role played by altered sense of familiarity in generating all DSMRs.

Proteostasis, or protein homeostasis, is a tightly regulated network of cellular pathways essential for maintaining proper protein folding, trafficking, and degradation. Neurons are particularly vulnerable to proteostasis collapse due to their postmitotic and long-lived nature and thus represent a unique cell type to understand the dynamics of proteostasis throughout development and maturation. Here, we utilized a dual-species co-culture model of human excitatory neurons and mouse glia to recapitulate and investigate cell type-specific, maturation-related changes in the proteostasis network using data-independent acquisition LC-MS/MS proteomics. We quantified branch-specific unfolded protein response (UPR) activation by monitoring curated effector proteins downstream of the ATF6, IRE1/XBP1s, and PERK pathways, enabling a comprehensive, unbiased evaluation of UPR dynamics during in vitro neuronal maturation between 30 d and 60 d. Species-specific analysis revealed that mature neurons largely preserved proteostasis, although they showed some signs of collapse, primarily in endoplasmic reticulum (ER)-to-Golgi transport mechanisms. However, these changes were accompanied by upregulation of proteostasis-related machinery and activation of the ATF6 branch, as well as maintenance of the XBP1s and PERK branches of the UPR over time. In contrast, glia exhibited broad downregulation of proteostasis factors and UPR components, independent of neuronal presence. Furthermore, we quantified stimulus-specific modulation of select UPR branches in matured neurons exposed to pharmacologic ER stressors. These findings highlight distinct, cell-type-specific stress adaptations during in vitro maturation and provide a valuable proteomic resource for dissecting proteostasis and UPR regulation in human neurons.

Sialorrhea is a syndrome characterized by the overflow of saliva from the oral cavity, resulting from either hypersecretion of the salivary glands or dysphagia. As a common sequela in stroke patients, sialorrhea can induce feelings of low self-esteem, perioral and facial inflammation, aspiration pneumonia, and significantly increase healthcare costs. Current clinical management primarily relies on anticholinergic medications or botulinum toxin to inhibit saliva production. However, these treatments offer limited efficacy and are associated with adverse effects such as xerostomia and dysphagia. Consequently, non-pharmacological therapies, including acupuncture in traditional Chinese medicine and rehabilitation training, have emerged as effective alternatives. Fire needling, a traditional Chinese medicine technique, possesses dual properties: needle stimulation and a thermal effect. It is characterized by rapid operation, no needle retention, and transient pain. For patients with suboptimal response to pharmacotherapy, we developed an ultrasound-guided fire needling method to reduce salivary volume and salivation frequency while avoiding adverse effects. Details are described in the text. Ultrasound guidance allows preoperative visualization of muscular and glandular tissues and their surrounding structures, facilitating precise insertion of the fire needle into the targeted glandular or muscular layers, thereby optimizing treatment efficacy and safety.

Extended reality (XR) technologies provide immersive training environments in sport, but their effectiveness for skill development and performance analysis requires careful and systematic evaluation. This protocol presents an integrated XR training methodology for cricket batting that combines immersive simulation with physiological and biomechanical measurements. It outlines procedures to collect and analyze muscle activity, metabolic responses, and motion-capture data during XR-based batting to characterize physiological and biomechanical responses. The goal is to evaluate batting performance (including power hitting) within a controlled virtual scenario while measuring muscle activation via electromyography (EMG), metabolic demands via respiratory gas analysis (VO₂), heart rate (HR), and kinematic outputs via motion capture. A single batter (n = 1) wears a VR headset and inertial sensors to face a virtual bowler, with EMG electrodes on key upper-body muscles and a portable metabolic system for breath-by-breath analysis. The protocol outlines the setup of the XR system, sensor calibration, and execution of standardized batting trials, with representative results presented as time-synchronized outputs. EMG traces indicated peak muscle activation during stroke execution, while VO₂ and HR fluctuations suggested a moderate aerobic response. Joint kinematics, including elbow extension and trunk rotation, were captured through motion data. These results illustrate the feasibility of using XR-based training to capture physical and physiological responses, offering a novel framework for enhancing performance and analyzing responses. The critical implementation steps, advantages over traditional drills, potential troubleshooting issues, and considerations for integrating XR into cricket training programs are discussed. This confluence of immersive technology with sports science measurements provides a framework for objectively assessing and exploring batting performance metrics in an XR setting and could be replicated in other sports.

Acute ischemic stroke (AIS) is a major cause of death and long-term disability, and early prediction of functional recovery is important for guiding clinical decision-making and rehabilitation planning. Functional outcome at 90 days is commonly assessed using the modified Rankin Scale (mRS), but predicting long-term outcome from early clinical and imaging information remains challenging. We hypothesized that integrating multiparametric magnetic resonance imaging (MRI) with structured clinical variables using a hybrid convolutional neural network (CNN)-Vision Transformer (ViT) architecture would improve prediction of 90-day functional outcomes compared with single-modality models. A retrospective cohort of 300 AIS patients who underwent multiparametric MRI was analyzed and divided into a training-validation cohort (n = 250) and an internal independent test cohort (n = 50). An additional external test cohort of 37 AIS patients was included to assess model generalizability. A hybrid CNN-ViT model was developed to extract multiparametric MRI features, and imaging and clinical predictions were integrated using stacked logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Among the evaluated clinical models, the support vector machine achieved the highest internal test AUC (0.878). The imaging model achieved an AUC of 0.782. The multimodal fusion model achieved the best overall internal performance, with an AUC of 0.885, sensitivity of 0.920, specificity of 0.760, and accuracy of 0.840. Similar performance trends were observed in the external test cohort. These findings suggest that stacked fusion of multiparametric MRI and clinical predictions may improve 90-day functional outcome prediction after AIS. However, larger multicenter validation studies are required before clinical implementation.