Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

G protein-coupled receptors (GPCRs) are the largest family of membrane proteins in eukaryotes, with nearly 800 genes coding for these proteins. They are involved in many physiological processes, such as light perception, taste and smell, neurotransmitter, metabolism, endocrine and exocrine, cell growth and migration. Importantly, GPCRs and their ligands are the targets of approximately one third of all marketed drugs. GPCRs are traditionally known for their role in transmitting signals from the extracellular environment to the cell's interior via the plasma membrane. However, emerging evidence suggests that GPCRs are also localized on mitochondria, where they play critical roles in modulating mitochondrial functions. These mitochondrial GPCRs (mGPCRs) can influence processes such as mitochondrial respiration, apoptosis, and reactive oxygen species (ROS) production. By interacting with mitochondrial signaling pathways, mGPCRs contribute to the regulation of energy metabolism and cell survival. Their presence on mitochondria adds a new layer of complexity to the understanding of cellular signaling, highlighting the organelle's role as not just an energy powerhouse but also a crucial hub for signal transduction. This expanding understanding of mGPCR function on mitochondria opens new avenues for research, particularly in the context of diseases where mitochondrial dysfunction plays a key role. Abnormalities in the phase conductance pathway of GPCRs located on mitochondria are closely associated with the development of systemic diseases such as cardiovascular disease, diabetes, obesity and Alzheimer's disease. In this review, we examined the various types of GPCRs identified on mitochondrial membranes and analyzed the complex relationships between mGPCRs and the pathogenesis of various diseases. We aim to provide a clearer understanding of the emerging significance of mGPCRs in health and disease, and to underscore their potential as therapeutic targets in the treatment of these conditions.

Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.

BACKGROUND: China is seeing a growing demand for rehabilitation treatments for post-stroke upper limb spastic paresis (PSSP-UL). Although acupuncture is known to be effective for PSSP-UL, there is room to enhance its efficacy. OBJECTIVE: This study explored a semi-personalized acupuncture approach for PSSP-UL that used three-dimensional kinematic analysis (3DKA) results to select additional acupoints, and investigated the feasibility, efficacy and safety of this approach. DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS: This single-blind, single-center, randomized, controlled trial involved 74 participants who experienced a first-ever ischemic or hemorrhagic stroke with spastic upper limb paresis. The participants were then randomly assigned to the intervention group or the control group in a 1:1 ratio. Both groups received conventional treatments and acupuncture treatment 5 days a week for 4 weeks. The main acupoints in both groups were the same, while participants in the intervention group received additional acupoints selected on the basis of 3DKA results. Follow-up assessments were conducted for 8 weeks after the treatment. MAIN OUTCOME MEASURES: The primary outcome was the Fugl-Meyer Assessment for Upper Extremity (FMA-UE) response rate (≥ 6-point change) at week 4. Secondary outcomes included changes in motor function (FMA-UE), Brunnstrom recovery stage (BRS), manual muscle test (MMT), spasticity (Modified Ashworth Scale, MAS), and activities of daily life (Modified Barthel Index, MBI) at week 4 and week 12. RESULTS: Sixty-four participants completed the trial and underwent analyses. Compared with control group, the intervention group exhibited a significantly higher FMA-UE response rate at week 4 (χ² = 5.479, P = 0.019) and greater improvements in FMA-UE at both week 4 and week 12 (both P < 0.001). The intervention group also showed bigger improvements from baseline in the MMT grades for shoulder adduction and elbow flexion at weeks 4 and 12 as well as thumb adduction at week 4 (P = 0.007, P = 0.049, P = 0.019, P = 0.008, P = 0.029, respectively). The intervention group showed a better change in the MBI at both week 4 and week 12 (P = 0.004 and P = 0.010, respectively). Although the intervention group had a higher BRS for the hand at week 12 (P = 0.041), no intergroup differences were observed at week 4 (all P > 0.05). The two groups showed no differences in MAS grades as well as in BRS for the arm at weeks 4 and 12 (all P > 0.05). CONCLUSION: Semi-personalized acupuncture prescription based on 3DKA results significantly improved motor function, muscle strength, and activities of daily living in patients with PSSP-UL. TRIAL REGISTRATION Chinese Clinical Trial Registry ChiCTR2200056216. Please cite this article as: Huang XY, Liao OP, Jiang SY, Tao JM, Li Y, Lu XY, Li YY, Wang C, Li J, Ma XP. Three-dimensional kinematic analysis can improve the efficacy of acupoint selection for post-stroke patients with upper limb spastic paresis: A randomized controlled trial. J Integr Med. 2025; 23(1): 15-24.
Humans ; Male ; Female ; Middle Aged ; Acupuncture Points ; Upper Extremity/physiopathology* ; Biomechanical Phenomena ; Single-Blind Method ; Aged ; Stroke/therapy* ; Acupuncture Therapy/methods* ; Stroke Rehabilitation/methods* ; Adult ; Muscle Spasticity/therapy* ; Paresis/physiopathology* ; Treatment Outcome

Microorganisms, abundant in nature, are prolific producers of a diverse array of natural products (NPs) that are fundamental in the development of innovative therapeutics. Despite their significant potential, the field faces considerable challenges, including the continuous emergence of potential health threats, as well as novel pathogen strains and viruses. The advent and implementation of advanced technologies, such as culture strategies, genomics mining, and artificial intelligence (AI), are facilitating a paradigm shift in pharmaceutical research, introducing innovative methodologies and perspectives. The development and maturation of these technologies have enhanced the exploration of microbial-derived NPs, thereby advancing pharmaceutical research and development. This review synthesizes recent developments in this context, emphasizing their applications in pharmaceutical discovery and development. Through systematic analysis and synthesis, it provides objective insights into the promising prospects and future direction of this essential field.
Biological Products/chemistry* ; Drug Discovery ; Humans ; Artificial Intelligence ; Bacteria/metabolism*

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Diterpenoid ferruginol is a key intermediate in biosynthesis of active ingredients such as tanshinone and carnosic acid.However, the traditional process of obtaining ferruginol from plants is often cumbersome and inefficient. In recent years, the increasingly developing gene editing technology has been gradually applied to the heterologous production of natural products, but the production of ferruginol in microbe is still very low, which has become an obstacle to the efficient biosynthesis of downstream chemicals, such as tanshinone. In this study, miltiradiene was produced by integrating the shortened diterpene synthase fusion protein,and the key genes in the MVA pathway were overexpressed to improve the yield of miltiradiene. Under the shake flask fermentation condition, the yield of miltiradiene reached about(113. 12±17. 4)mg·L~(-1). Subsequently, this study integrated the ferruginol synthase Sm CYP76AH1 and Sm CPR1 to reconstruct the ferruginol pathway and thereby realized the heterologous synthesis of ferruginol in Saccharomyces cerevisiae. The study selected the best ferruginol synthase(Il CYP76AH46) from different plants and optimized the expression of pathway genes through redox partner engineering to increase the yield of ferruginol. By increasing the copy number of diterpene synthase, CYP450, and CPR, the yield of ferruginol reached(370. 39± 21. 65) mg·L~(-1) in the shake flask, which was increased by 21. 57-fold compared with that when the initial ferruginol strain JMLT05 was used. Finally, 1 083. 51 mg·L~(-1) ferruginol was obtained by fed-batch fermentation, which is the highest yield of ferruginol from biosynthesis so far. This study provides not only research ideas for other metabolic engineering but also a platform for the construction of cell factories for downstream products.
Saccharomyces cerevisiae/genetics* ; Diterpenes/metabolism* ; Metabolic Engineering ; Fermentation ; Abietanes

OBJECTIVES: To construct a Z-score regression model for coronary artery diameter based on echocardiographic data from children in Sichuan Province and to establish a Z-score calculation formula. METHODS: A total of 744 healthy children who underwent physical examinations at Sichuan Provincial People's Hospital from January 2020 to December 2022 were selected as the modeling group, while 251 children diagnosed with Kawasaki disease at the same hospital from January 2018 to December 2022 were selected as the validation group. Pearson correlation analysis was conducted to analyze the relationships between coronary artery diameter values and age, height, weight, and body surface area. A regression model was constructed using function transformation to identify the optimal regression model and establish the Z-score calculation formula, which was then validated. RESULTS: The Pearson correlation analysis showed that the correlation coefficients for the diameters of the left main coronary artery, left anterior descending artery, left circumflex artery, and right coronary artery with body surface area were 0.815, 0.793, 0.704, and 0.802, respectively (P<0.05). Among the constructed regression models, the power function regression model demonstrated the best performance and was therefore chosen as the optimal model for establishing the Z-score calculation formula. Based on this Z-score calculation formula, the detection rate of coronary artery lesions was found to be 21.5% (54/251), which was higher than the detection rate based on absolute values of coronary artery diameter. Notably, in the left anterior descending and left circumflex arteries, the detection rate of coronary artery lesions using this Z-score calculation formula was higher than that of previous classic Z-score calculation formulas. CONCLUSIONS The Z-score calculation formula established based on the power function regression model has a higher detection rate for coronary artery lesions, providing a strong reference for clinicians, particularly in assessing coronary artery lesions in children with Kawasaki disease.
Humans ; Male ; Female ; Child, Preschool ; Child ; Coronary Artery Disease/diagnostic imaging* ; Infant ; Mucocutaneous Lymph Node Syndrome ; Regression Analysis ; Coronary Vessels/diagnostic imaging* ; Echocardiography ; Adolescent