Parkinson's disease（PD） is the second most common neurodegenerative disease in the world， which seriously affects the lives of patients. With the acceleration of aging process， the number of patients continues to rise. Its main pathological features are aggregation of α-synuclein and degenerative death of dopaminergic neurons in the substantia nigra. However， the pathogenesis of PD is still unclear. According to reports， the brain-derived neurotrophic factor（BDNF）/tyrosine kinase receptor B（TrkB） signaling pathway is highly expressed and activated in dopaminergic neurons in the substantia nigra， which is closely related to neurophysiological processes such as neurogenesis， synaptic plasticity， neuroinflammation， and oxidative stress. It plays an important role in the occurrence and development of PD. At present， the treatment methods of Western medicine for PD are mainly based on drugs such as levodopa and dopamine agonists to alleviate motor symptoms， but with the increase of dose， the adverse reactions are significantly enhanced. Traditional Chinese medicine（TCM） has attracted people to explore its therapeutic effects on PD due to its characteristics of homology of medicine and food， economy， minor adverse reactions and multi-target action. Therefore， this paper systematically reviews the role of BNDF/TrkB pathway in the pathogenesis of PD and the mechanism of TCM formulas， extracts and monomers in the treatment of PD by regulating the BNDF/TrkB pathway according to retrieving the latest research reports at home and abroad， so as to provide a reference for the clinical application of related TCM and the development of new drugs for PD.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

ObjectiveFunctional near-infrared spectroscopy (fNIRS), a novel non-invasive technique for monitoring cerebral activity, can be integrated with upper limb rehabilitation robots to facilitate the real-time assessment of neurological rehabilitation outcomes. The rehabilitation robot is designed with 3 training modes: passive, active, and resistance. Among these, the resistance mode has been demonstrated to yield superior rehabilitative outcomes for patients with a certain level of muscle strength. The control modes in the resistance mode can be categorized into dynamic and static control. However, the effects of different control modes in the resistance mode on the motor function of patients with upper limb hemiplegia in stroke remain unclear. Furthermore, the effects of force, an important parameter of different control modes, on the activation of brain regions have rarely been reported. This study investigates the effects of dynamic and static resistance modes under varying resistance levels on cerebral functional alterations during motor rehabilitation in post-stroke patients. MethodsA cohort of 20 stroke patients with upper limb dysfunction was enrolled in the study, completing preparatory adaptive training followed by 3 intensity-level tasks across 2 motor paradigms. The bilateral prefrontal cortices (PFC), bilateral primary motor cortices (M1), bilateral primary somatosensory cortices (S1), and bilateral premotor and supplementary motor cortices (PM) were examined in both the resting and motor training states. The lateralization index (LI), phase locking value (PLV), network metrics were employed to examine cortical activation patterns and topological properties of brain connectivity. ResultsThe data indicated that both dynamic and static modes resulted in significantly greater activation of the contralateral M1 area and the ipsilateral PM area when compared to the resting state. The static patterns demonstrated a more pronounced activation in the contralateral M1 in comparison to the dynamic patterns. The results of brain network analysis revealed significant differences between the dynamic and resting states in the contralateral PFC area and contralateral M1 area (F=4.709, P=0.038), as well as in the contralateral PM area and ipsilateral M1 area (F=4.218, P=0.049). Moreover, the findings indicated a positive correlation between the activation of the M1 region and the increase in force in the dynamic mode, which was reversed in the static mode. ConclusionBoth dynamic and static resistance training modes have been demonstrated to activate the corresponding brain functional regions. Dynamic resistance modes elicit greater oxygen changes and connectivity to the region of interest (ROI) than static resistance modes. Furthermore, the effects of increasing force differ between the two modes. In patients who have suffered a stroke, dynamic modes may have a more pronounced effect on the activation of exercise-related functional brain regions.

Objective: To investigate the distribution of GP (B-A-B) hybrid glycophorins in several Chinese minority populations from southern regions of China (Guangdong & Guizhou). Methods: Whole blood samples were collected from 536 blood donors representing 15 different Chinese ethnic minority groups, including She, Bouyei, Yi and Miao, as well as Chuanqing populations. Genomic DNA was extracted and GYP (B-A-B) genotyping was conducted by high resolution melting (HRM) minority method using the GYPB pseudoexon 3-specific primers. Direct sequencing of GYPB pseudoexon 3 was performed in the samples with variant curves. Results: Only one genotype of GP (B-A-B) hybrid glycophorins (GYP Mur/GYPB) was identified among these 536 samples. In total, 15 She (15/162, 9.26%), 18 Bouyei (18/113, 15.93%), 3 Yi (3/79, 3.80%), 3 Chuanqing (3/45, 6.67%), 2 Bai (2/42, 4.76%), 3 Miao (3/40, 7.50%), 1 Shui (1/12, 8.33%), 2 Gelao (2/12, 16.67%), 1 Tujia (1/8, 12.50%) and 1 Dong (1/6, 16.67%) blood donors with heterozygous GYP Mur allele were identified. Among 8 Hui, 5 Manchu, 2 Mongolian, 1 Yao and 1 Li donors, no GYP (B-A-B) hybrid gene carrier was found. In addition, four nucleotide polymorphisms (SNPs) were identified in 6 samples with a variant melting curve detected by HRM. Conclusion: GP. Mur is the most common type of GP (B-A-B) hybrid glycophorins among Chinese minority populations, with frequency varying across different populations. It is recommended to involve GP. Mur reagent cells in the antibody screening cells for populations with a high frequency of GYP Mur allele.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

Animals ; Macaca mulatta ; Optic Disk ; Glaucoma ; Craniocerebral Trauma ; Intraocular Pressure ; Low Tension Glaucoma

Chemotherapy is one of the major approaches for the treatment of metastatic lung cancer, although it is limited by the low tumor delivery efficacy of anticancer drugs. Bacterial therapy is emerging for cancer treatment due to its high immune stimulation effect; however, excessively generated immunogenicity will cause serious inflammatory response syndrome. Here, we prepared cancer cell membrane-coated liposomal paclitaxel-loaded bacterial ghosts (LP@BG@CCM) by layer-by-layer encapsulation for the treatment of metastatic lung cancer. The preparation processes were simple, only involving film formation, electroporation, and pore extrusion. LP@BG@CCM owned much higher 4T1 cancer cell toxicity than LP@BG due to its faster fusion with cancer cells. In the 4T1 breast cancer metastatic lung cancer mouse models, the remarkably higher lung targeting of intravenously injected LP@BG@CCM was observed with the almost normalized lung appearance, the reduced lung weight, the clear lung tissue structure, and the enhanced cancer cell apoptosis compared to its precursors. Moreover, several major immune factors were improved after administration of LP@BG@CCM, including the CD4⁺/CD8a⁺ T cells in the spleen and the TNF-α, IFN-γ, and IL-4 in the lung. LP@BG@CCM exhibits the optimal synergistic chemo-immunotherapy, which is a promising medication for the treatment of metastatic lung cancer.

ObjectiveTo explore the effect of brain-computer interface (BCI) based on visual, auditory and motor feedback combined with transcranial direct current stimulation (tDCS) on upper limb function in stroke patients. MethodsFrom March to October, 2023, 45 stroke inpatients in Xuzhou Rehabilitation Hospital and Xuzhou Central Hospital were divided into BCI group (n = 15), tDCS group (n = 15) and combined group (n = 15) randomly. All the groups received routine rehabilitation, while BCI group received BCI training, tDCS group received tDCS, while the combined group received tDCS and followed by BCI training immediately, for four weeks. They were assessed with Fugl-Meyer Assessment-Upper Extremities (FMA-UE), Action Research Arm Test (ARAT), modified Barthel Index (MBI) and delta-alpha ratio (DAR) and power ratio index (PRI) of electroencephalogram before and after treatment. ResultsThe scores of FMA-UE, ARAT and MBI increased in all the groups after treatment (|t| > 5.350, P < 0.001), and all these indexes were the best in the combined group (F > 3.366, P < 0.05); while DAR and PRI decreased in all the groups (|t| > 2.208 , P < 0.05), they were the best in the combined group (F > 5.224, P < 0.01). ConclusionBCI based on visual, auditory and motor feedback combined with tDCS can further improve the motor function of upper limbs and the activities of daily living of stroke patients.