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.

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.

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.

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.

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.

OBJECTIVE: To determine the role of Tripterygium wilfordii multiglycoside (TGW) in the treatment of psoriatic dermatitis from a cellular immunological perspective. METHODS: Mouse models of psoriatic dermatitis were established by imiquimod (IMQ). Twelve male BALB/c mice were assigned to IMQ or IMQ₊TGW groups according to a random number table. Histopathological changes in vivo were assessed by hematoxylin and eosin staining. Ratios of immune cells and cytokines in mice, as well as PAM212 cell proliferation in vitro were assessed by flow cytometry. Pro-inflammatory cytokine expression was determined using reverse transcription quantitative polymerase chain reaction. RESULTS: TGW significantly ameliorated the severity of IMQ-induced psoriasis-like mouse skin lesions and restrained the activation of CD45⁺ cells, neutrophils and T lymphocytes (all P<0.01). Moreover, TGW significantly attenuated keratinocytes (KCs) proliferation and downregulated the mRNA levels of inflammatory cytokines including interleukin (IL)-17A, IL-23, tumor necrosis factor α, and chemokine (C-X-C motif) ligand 1 (P<0.01 or P<0.05). Furthermore, it reduced the number of γ δ T17 cells in skin lesion of mice and draining lymph nodes (P<0.01). CONCLUSIONS TGW improved psoriasis-like inflammation by inhibiting KCs proliferation, as well as the associated immune cells and cytokine expression. It inhibited IL-17 secretion from γ δ T cells, which improved the immune-inflammatory microenvironment of psoriasis.
Male ; Animals ; Mice ; Tripterygium ; Psoriasis/drug therapy* ; Keratinocytes ; Skin Diseases/metabolism* ; Cytokines/metabolism* ; Imiquimod/metabolism* ; Dermatitis/pathology* ; Disease Models, Animal ; Mice, Inbred BALB C ; Skin/metabolism*

BACKGROUND:Thromboelastography plays an important role in identifying the hypercoagulable state of blood and thrombosis in humans.Recent studies have shown a correlation between an increase in mean platelet volume and thrombosis.We can therefore ask whether the combined diagnosis of thromboelastography and mean platelet volume is a more accurate predictor of thrombosis. OBJECTIVE:To predict the status of blood and the occurrence of thrombosis after total knee arthroplasty by means of mean platelet volume combined with thromboelastography. METHODS:One hundred and twenty patients who underwent unilateral total knee arthroplasty between May 2015 and March 2022 were collected.Patients were divided into 60 patients in the thrombosis group and 60 patients in the control group based on ultrasound findings on postoperative day 7.Whole blood cell and thromboelastography were performed 1 day before,1 and 7 days after surgery,respectively.Multifactorial analysis was used to investigate independent predictors of thrombosis after total knee arthroplasty.The receiver operating characteristic curve and area under the curve were measured in the subjects. RESULTS AND CONCLUSION:Mean platelet volume correlated most strongly with maximum amplitude,followed by coagulation angle.Mean platelet volume and coagulation angle on postoperative day 1 were independent predictors of thrombosis.Mean platelet volume tended to rise and then fall in patients with thrombosis.The best critical value for mean platelet volume to predict thrombosis was 10.73 fL.The area under the receiver operating characteristic curve of subjects was 0.665(95%CI:0.568-0.762,P<0.05];whereas the area under the receiver operating characteristic curve for subjects using mean platelet volume combined with coagulation angle was 0.815(95%CI:0.750-0.879,P<0.05).In addition,the maximum amplitude,coagulation angle,coagulation index and mean platelet volume were significantly higher in the thrombosis group than in the control group postoperatively(P<0.05).The results suggest that the mean platelet volume can reflect the hypercoagulable state of blood after surgery,and the combination of mean platelet volume and coagulation angle on day 1 after total knee arthroplasty can improve the prediction of thrombosis.