Locomotion, a fundamental motor function encompassing various forms such as swimming, walking, running, and flying, is essential for animal survival and adaptation. The mesencephalic locomotor region (MLR), located at the midbrain-hindbrain junction, is a conserved brain area critical for controlling locomotion. This review highlights recent advances in understanding the MLR’s structure and function across species, from lampreys to mammals and birds, with a particular focus on insights gained from optogenetic studies in mammals. The goal is to uncover universal strategies for MLR-mediated locomotor control. Electrical stimulation of the MLR in species such as lampreys, salamanders, cats, and mice initiates locomotion and modulates speed and patterns. For example, in lampreys, MLR stimulation induces swimming, with increased intensity or frequency enhancing propulsive force. Similarly, in salamanders, graded stimulation transitions locomotor outputs from walking to swimming. Histochemical studies reveal that effective MLR stimulation sites colocalize with cholinergic neurons, suggesting a conserved neurochemical basis for locomotion control. In mammals, the MLR comprises two key nuclei: the cuneiform nucleus (CnF) and the pedunculopontine nucleus (PPN). Both nuclei contain glutamatergic and GABAergic neurons, with the PPN additionally housing cholinergic neurons. Optogenetic studies in mice by selectively activating glutamatergic neurons have demonstrated that the CnF and PPN play distinct roles in motor control: the CnF drives rapid escape behaviors, while the PPN regulates slower, exploratory movements. This functional specialization within the MLR allows animals to adapt their locomotion patterns and speed in response to environmental demands and behavioral objectives. Similar to findings in lampreys, the CnF and PPN in mice transmit motor commands to spinal effector circuits by modulating the activity of brainstem reticular formation neurons. However, they achieve this through distinct reticulospinal pathways, enabling the generation of specific behaviors. Further insights from monosynaptic rabies viral tracing reveal that the CnF and PPN integrate inputs from diverse brain regions to produce context-appropriate behaviors. For instance, glutamatergic neurons in the PPN receive signals from other midbrain structures, the basal ganglia, and medullary nuclei, whereas glutamatergic neurons in the CnF rarely receive inputs from the basal ganglia but instead are strongly influenced by the periaqueductal grey and inferior colliculus within the midbrain. These differential connectivity patterns underscore the specialized roles of the CnF and PPN in motor control, highlighting their unique contributions to coordinating locomotion. Birds exhibit exceptional flight capabilities, yet the avian MLR remains poorly understood. Comparative studies suggest that the pedunculopontine tegmental nucleus (PPTg) in birds is homologous to the mammalian PPN, which contains cholinergic neurons, while the intercollicular nucleus (ICo) or nucleus isthmi pars magnocellularis (ImC) may correspond to the CnF. These findings provide important clues for identifying the avian MLR and elucidating its role in flight control. However, functional validation through targeted experiments is urgently needed to confirm these hypotheses. Optogenetics and other advanced techniques in mice have greatly advanced MLR research, enabling precise manipulation of specific neuronal populations. Future studies should extend these methods to other species, particularly birds, to explore unique locomotor adaptations. Comparative analyses of MLR structure and function across species will deepen our understanding of the conserved and evolved features of motor control, revealing fundamental principles of locomotion regulation throughout evolution. By integrating findings from diverse species, we can uncover how the MLR has been adapted to meet the locomotor demands of different environments, from aquatic to aerial habitats.

Metachromatic leukodystrophy (MLD) is an inherited disease caused by a deficiency of the enzyme arylsulfatase A (ARSA). Lentivirus-modified autologous hematopoietic stem cell gene therapy (HSCGT) has recently been approved for clinical use in pre and early symptomatic children with MLD to increase ARSA activity. Unfortunately, this advanced therapy is not available for most patients with MLD who have progressed to more advanced symptomatic stages at diagnosis. Patients with late-onset juvenile MLD typically present with a slower neurological progression of symptoms and represent a significant burden to the economy and healthcare system, whereas those with early onset infantile MLD die within a few years of symptom onset. We conducted a pilot study to determine the safety and benefit of HSCGT in patients with postsymptomatic juvenile MLD and report preliminary results. The safety profile of HSCGT was favorable in this long-term follow-up over 9 years. The most common adverse events (AEs) within 2 months of HSCGT were related to busulfan conditioning, and all AEs resolved. No HSCGT-related AEs and no evidence of distorted hematopoietic differentiation during long-term follow-up for up to 9.6 years. Importantly, to date, patients have maintained remarkably improved ARSA activity with a stable disease state, including increased Functional Independence Measure (FIM) score and decreased magnetic resonance imaging (MRI) lesion score. This long-term follow-up pilot study suggests that HSCGT is safe and provides clinical benefit to patients with postsymptomatic juvenile MLD.
Humans ; Leukodystrophy, Metachromatic/genetics* ; Pilot Projects ; Genetic Therapy/methods* ; Hematopoietic Stem Cell Transplantation ; Male ; Follow-Up Studies ; Female ; Lentivirus/genetics* ; Child ; Child, Preschool ; Hematopoietic Stem Cells/metabolism* ; Cerebroside-Sulfatase/metabolism* ; Adolescent

Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials. Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction. However, traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules. Similarly, graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information. To address these limitations, we propose a novel fingerprint-enhanced hierarchical graph neural network (FH-GNN) for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints. The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks (D-MPNN) on a hierarchical molecular graph that integrates atomic-level, motif-level, and graph-level information along with their relationships. Additionally, we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features, creating a comprehensive molecular embedding that integrated hierarchical molecular structures with domain knowledge. Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction, validating its capability to comprehensively capture molecular information. By integrating molecular structure and chemical knowledge, FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

ObjectiveTo investigate the mechanism by which Huanglian Jiedutang （HLJDT） inhibits pyroptosis and neuroinflammation in Alzheimer's disease （AD） mice via the NOD-like receptor protein 3 （NLRP3）/cysteinyl aspartate-specific protease-1 （Caspase）-1/gasdermin D （GSDMD） pathway. MethodsThirty APP/PS1 double transgenic mice were randomly and evenly divided into the model group （model group）， the positive control group （Donepezil group， 0.65 mg·kg^-1）， and the HLJDT treatment group （HLJDT group， 5.2 g·kg^-1）. Ten C57BL/6 mice were assigned to the blank control group （control group）. The Morris water maze and novel object recognition tests were used to evaluate learning and memory abilities. Nissl staining was employed to observe the morphology， quantity， and distribution of neurons in the hippocampal region. Golgi staining was used to examine the morphology and density of neuronal dendritic spines in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was performed to detect the mRNA expression of neuroinflammation-related factors and genes in the NLRP3/Caspase-1/GSDMD pyroptosis pathway in the hippocampus. Western blot was used to detect the expression of postsynaptic density protein 95 （PSD95）， amyloid precursor protein （APP）， inflammatory factors including nuclear factor-κB （NF-κB）， phosphorylated NF-κB （p-NF-κB）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， as well as pyroptosis pathway-related proteins including NLRP3， Caspase-1， GSDMD， and GSDMD-N. ResultsCompared with the control group， the model group exhibited significantly decreased learning and memory abilities （P<0.01）， reduced numbers of neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly increased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.01）. Protein levels of PSD95 were markedly decreased， while the expression levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly elevated （P<0.01）. Compared with the model group， both the Donepezil and HLJDT groups showed significantly improved learning and memory abilities （P<0.05， P<0.01）， increased numbers of hippocampal neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly decreased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.05， P<0.01）. Protein levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly downregulated， while PSD95 expression was significantly upregulated （P<0.05， P<0.01）. There was no statistically significant difference in GSDMD-N levels in the Donepezil group， while GSDMD-N expression was significantly decreased in the HLJDT group （P<0.05）. ConclusionThis study confirms that HLJDT can improve learning and memory abilities in APP/PS1 double transgenic mice， and attenuate neuronal loss and synaptic damage， possibly through inhibition of pyroptosis via the NLRP3/Caspase-1/GSDMD pathway.

ObjectiveTo investigate the mechanism by which Huanglian Jiedutang （HLJDT） inhibits pyroptosis and neuroinflammation in Alzheimer's disease （AD） mice via the NOD-like receptor protein 3 （NLRP3）/cysteinyl aspartate-specific protease-1 （Caspase）-1/gasdermin D （GSDMD） pathway. MethodsThirty APP/PS1 double transgenic mice were randomly and evenly divided into the model group （model group）， the positive control group （Donepezil group， 0.65 mg·kg^-1）， and the HLJDT treatment group （HLJDT group， 5.2 g·kg^-1）. Ten C57BL/6 mice were assigned to the blank control group （control group）. The Morris water maze and novel object recognition tests were used to evaluate learning and memory abilities. Nissl staining was employed to observe the morphology， quantity， and distribution of neurons in the hippocampal region. Golgi staining was used to examine the morphology and density of neuronal dendritic spines in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was performed to detect the mRNA expression of neuroinflammation-related factors and genes in the NLRP3/Caspase-1/GSDMD pyroptosis pathway in the hippocampus. Western blot was used to detect the expression of postsynaptic density protein 95 （PSD95）， amyloid precursor protein （APP）， inflammatory factors including nuclear factor-κB （NF-κB）， phosphorylated NF-κB （p-NF-κB）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， as well as pyroptosis pathway-related proteins including NLRP3， Caspase-1， GSDMD， and GSDMD-N. ResultsCompared with the control group， the model group exhibited significantly decreased learning and memory abilities （P<0.01）， reduced numbers of neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly increased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.01）. Protein levels of PSD95 were markedly decreased， while the expression levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly elevated （P<0.01）. Compared with the model group， both the Donepezil and HLJDT groups showed significantly improved learning and memory abilities （P<0.05， P<0.01）， increased numbers of hippocampal neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly decreased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.05， P<0.01）. Protein levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly downregulated， while PSD95 expression was significantly upregulated （P<0.05， P<0.01）. There was no statistically significant difference in GSDMD-N levels in the Donepezil group， while GSDMD-N expression was significantly decreased in the HLJDT group （P<0.05）. ConclusionThis study confirms that HLJDT can improve learning and memory abilities in APP/PS1 double transgenic mice， and attenuate neuronal loss and synaptic damage， possibly through inhibition of pyroptosis via the NLRP3/Caspase-1/GSDMD pathway.

The plants of the genus Caragana Fabr. are desert plants of the Leguminosae family, which are widely used in traditional ethnomedicine, with the effects of nourishing Yin and nourishing blood, dispelling wind and removing dampness, clearing heat and detoxifying toxins. The anti-inflammatory effect of Caragana Fabr. has attracted much attention, the research on the related mechanism has made some progress, but it lacks systematic collation. By summarising the anti-inflammatory effects of the active ingredients of Caragana Fabr., the authors found that they have good anti-inflammatory activities on different inflammatory cell models in vitro, and have good improvement effects on rheumatoid arthritis, colitis, complex nephritis, and acute lung injury and other disease models. The anti-inflammatory effects of the active components of this genus mainly include the reduction of the levels of a variety of pro-inflammatory factors, and the signalling pathways involved mainly include TLR4/NF-κB, TLR4/MAPK, TLR4/NF-κB/IRF3, JAK/STAT-1, ERK/STAT-1 and so on. Therefore, the paper mainly reviews the research progress on the anti-inflammatory effects and mechanisms of the Caragana Fabr. plants and their active components according to disease types, with a view to providing reference for the in-depth study of their anti-inflammatory activities and the development of new products with related functions.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.