Explore the vast range of titles available.

Methazolamide is a carbonic anhydrase (CA) inhibitor with satisfactory safety. Our previous studies have demonstrated the elevation of CA1 expression and the therapeutic effect of Methazolamide in Ankylosing spondylitis (AS). In this study, we explored the pathogenic role of CA1 and the pharmacological mechanism of Methazolamide in AS through Gene Set Enrichment Analysis (GSEA) and network pharmacology. Seven out of twelve CA1 related gene sets were enriched in AS group. CA1 was core enriched in above seven gene sets involving zinc ion binding, arylesterase activity and one carbon metabolic process. Functional analysis of the candidate target genes obtained from the intersection of AS associated genes and Methazolamide target genes indicated that Methazolamide exerts therapeutic effects on AS mainly through inflammatory pathways which regulate the production of tumor necrosis factor, IL-6 and nitric oxide. PTGS2, ESR1, GSK3β, JAK2, NOS2 and CA1 were selected as therapeutic targets of Methazolamide in AS. Molecular docking and molecular dynamics simulations were performed successfully. In addition, we innovatively obtained the intersection of Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and GSEA results, and found that 18 GO terms and 5 KEGG terms were indicated in the pharmacological mechanism of Methazolamide in AS, involving bone mineralization, angiogenesis, inflammation, and chemokine signaling pathways. Nevertheless, validation for these mechanisms is needed in vivo/vitro experiments.

As the scale of power systems continue to expand and their structure becomes increasingly complex, it is likely that branch power flow exceedance may occur during the operation of power systems, posing threats to the safe and stable operation of entire systems. This paper addresses the issue of branch flow exceedance in power networks. To enhance the operational efficiency and optimize the adjustment effects, this paper proposes a method for eliminating branch power flow exceedance by improving the particle swarm optimization (PSO) algorithm through the introduction of sensitivity and distribution factors. Firstly, it introduces the basic theory and calculation methods of sensitivity analysis, focusing on deriving the calculation principles of power flow sensitivity and voltage sensitivity, used to predict the responses of power flow at each branch in the power network to power or voltage changes. Subsequently, the paper provides a detailed derivation of the calculation principles for the line outage distribution factor (LODF), which effectively assesses the changes in branch power flow in the power network under specific conditions. Finally, a method for eliminating branch power flow exceedance based on a combination of sensitivity analysis and PSO algorithm is proposed. Through case analysis, it is demonstrated how to use the sensitivity and distribution factor to predict and control the power flow exceedance issues in power systems, verifying the efficiency and practicality of the proposed method for eliminating branch power flow exceedance. The study shows that this method can rapidly and accurately predict and address branch power flow exceedance in power system, thereby enhancing the operational safety of the power system.

Effective prediction of molecular features is crucial for the prognostic assessment of glioma patients. This study aims to develop a nomogram model using fractal analysis and Visually AcceSAble Rembrandt Images (VASARI) features to predict the molecular characteristics of WHO Grade 3–4 diffuse gliomas. Retrospective analysis of clinical data and VASARI features of patients with WHO grade 3–4 diffuse gliomas confirmed by pathology between January 2020 and December 2023 at our institution. Preoperative T1-weighted contrast-enhanced and T2-weighted images were used to delineate the tumor and surrounding edema regions on 3D-Slicer. Fractal dimension (FD) and lacunarity of both the tumor and surrounding edema were extracted using ImageJ software. Univariate and multivariate logistic regression analyses were performed to identify independent predictive factors for the Ki_67 proliferation index (PI), p53, and telomerase reverse transcriptase promoter (TERTp) mutations. Based on these findings, a nomogram prediction model was constructed. Model performance was comprehensively assessed using the receiver operating characteristic curve (ROC), calibration curve (CRC), and decision curve analysis (DCA). Sex, Proportion Enhancing, and Pial invasion were identified as independent predictive factors for the Ki_67 PI. FD of the tumor (FD (T) ) was an independent predictor for p53 expression. FD (T) , Enhancement Quality, and Definition of the enhancing margin were independent predictors for TERTp mutations. The areas under the ROC for each nomogram model were 0.791, 0.739, and 0.601, respectively. Sensitivities were 68.75%, 78.12%, and 51.43%, and specificities were 81.03%, 64.86%, and 71.00%, respectively. CRC showed a high degree of concordance between predicted probabilities and actual observed values, while DCA demonstrated favorable net benefits for all models. VASARI features and fractal analysis effectively predict the Ki_67 PI, p53, and TERTp mutations in WHO grade 3–4 diffuse gliomas. Furthermore, combining these two approaches enhances the predictive performance for TERTp mutations.

Aims This study investigated the association of capillary blood glucose (CBG)‐assessed time in range (TIR) (3.9–10.0 mmol/L) with insulin sensitivity and islet β‐cell function. Materials and Methods We recruited 455 patients with type 2 diabetes mellitus. Seven‐point glucose‐profile data (pre‐ and 120 min post‐main meals, bedtime) were collected over three consecutive days. Plasma glucose and serum insulin concentrations were measured at 0, 60, and 120 min after a 100 g standard steamed bread meal test. The homeostasis model assessment of insulin resistance (HOMA‐IR) and Matsuda index were computed to evaluate insulin resistance. The HOMA of β‐cell function (HOMA‐β) and the area under the curve between insulin and blood glucose (IAUC0−120/GAUC0−120) were used to estimate β‐cell function. Results TIR was positively correlated with the 60 and 120 min insulin values, IAUC0−120, the Matsuda index, HOMA‐β, and IAUC0−120/GAUC0−120 (rs: 0.154, 0.129, 0.137, 0.194, 0.341, and 0.334, respectively; P < 0.05) but inversely correlated with HOMA‐IR (rs: –0.239, P < 0.001). After adjusting for confounders, multinomial multiple logistic regression analysis revealed that the odds ratios (ORs) of achieving the target time in range (>70%) increased by 12% (95% confidence interval [CI]: 3–21%), 7% (95% CI: 1–14%), 10% (95% CI: 5–16%), and 45% (95% CI: 25–68%) for each 10 mIU/L increase in the 60 and 120 min insulin values, 10 unit increase in HOMA‐β, and unit increase in IAUC0−120/GAUC0−120, respectively (P < 0.05). Nevertheless, the OR decreased by 10% (95% CI: 1–18%) for each unit increase in HOMA‐IR (P < 0.05). Conclusions Insulin resistance and islet β‐cell function are related to capillary blood glucose‐assessed TIR. 1. To our knowledge this is the first study looking at insulin resistance and TIR in patients with T2DM. 2. Insulin resistance is negatively correlated with TIR in patients with T2DM 3. Impaired ‐cell function has negative effects on TIR in patients with T2DM

Background Gliomas may impair glymphatic function and alter cerebrospinal fluid (CSF) dynamics through structural brain changes, potentially affecting peritumoral brain edema (PTBE) and fluid clearance. This study investigated the impact of gliomas on glymphatic system function and CSF volume via diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) and volumetric magnetic resonance imaging (MRI), which clarified the relationships between tumor characteristics and glymphatic system disruption. Methods In this prospective study, 112 glioma patients and 56 healthy controls underwent MRI to calculate DTI-ALPS indices and perform volumetric analyses of CSF, tumor, and PTBE. Statistical analyses were used to assess the relationships between the DTI-ALPS index, tumor volume, PTBE volume, and clinical characteristics. Results Glioma patients had significantly lower DTI-ALPS indices (1.266 ± 0.258 vs. 1.395 ± 0.174, p  < 0.001) and greater CSF volumes (174.53 ± 34.89 cm³ vs. 154.25 ± 20.89 cm³, p  < 0.001) than controls did. The DTI-ALPS index was inversely correlated with tumor volume ( r = -0.353, p  < 0.001) and PTBE volume ( r = -0.266, p  = 0.015). High-grade gliomas were associated with lower DTI-ALPS indices and larger PTBE volumes (all p  < 0.001). Tumor grade emerged as an independent predictor of the DTI-ALPS index in multivariate analysis (β = -0.244, p  = 0.011). Conclusion Gliomas are associated with significant glymphatic dysfunction, as evidenced by reduced DTI-ALPS indices and increased CSF and PTBE volumes. The DTI-ALPS index serves as a potential biomarker of glymphatic disruption in glioma patients, offering insights into tumor-related fluid changes and the pathophysiology of brain-tumor interactions.

Background 18p deletion (18p-) syndrome is a rare chromosomal abnormality with a wide range of phenotypes. Its main clinical features are short stature, intellectual disability, and facial dysmorphism, which are rarely accompanied by autoimmune thyroid disease (ATD) or pituitary abnormalities. Herein, we report the first Chinese patient with a de novo 18p deletion who presented with ATD and non-functioning pituitary adenoma. Case presentation A 24-year-old female patient presented with severe ptosis, intellectual disability, hypothyroidism associated with Hashimoto’s thyroiditis, and a non-functional pituitary adenoma. Deletion of the short arm of chromosome 18 was detected in a G-banded karyotyping (46, XX, del [18] [p11.1]). Chromosomal microarray analysis revealed a 14.9 Mb deletion in chromosome 18p11.32p11.21, defined as arr[GRCh38]18p11.32p11.21(136227–15079295)x1. The literature review indicated that patients with 18p- syndrome and ATD were predominantly female with early disease onset (mean age: 15 years). Conclusions 18p- syndrome is associated with ATD and pituitary abnormalities. Therefore, endocrine system evaluation and genetic analysis of the 18p breakpoint region are valuable for predicting patient prognosis.

Our research explores the immunomodulatory effects of sulforaphane (SFN), a well-known nuclear factor erythroid 2-related factor 2 (Nrf2) pathway agonist, on the sterile inflammation of and ischemia-reperfusion injuries to the liver after hemorrhagic shock (HS) followed by resuscitation (R). Male C57/BL6 wild-type and transgenic ARE- luc mice were exposed to mean arterial pressure-controlled HS. Fluid resuscitation was performed after 90 min of HS, and SFN was administrated intraperitoneally after that. The animals were sacrificed at 6 h, 24 h, and 72 h after resuscitation, and their livers were extracted to perform H&E staining and myeloperoxidase (MPO) activity analysis. The Kupffer cells were isolated for cytokines profile measurements and Nrf2 immunofluorescence staining. Further, the ARE- luc mice were used to assess hepatic Nrf2 activity in vivo . We identified that SFN-activated Kupffer cells’ Nrf2 pathway and modulated its cytokines expression, including TNF-α, MCP-1, KC/CXCL1, IL-6, and IL-10. Furthermore, SFN mitigated liver ischemia-reperfusion injury, as evidenced by the downregulation of the Suzuki score and the enhanced hepatic Nrf2 activity. The in vivo SFN treatment decreased neutrophils infiltration, as shown by the decreased MPO levels. Our study shows that SFN can decrease HS/R-induced hepatic ischemia-reperfusion injury and modulate the activity of Kupffer cells via an Nrf2-dependent pathway.

IntroductionStroke is a major cause of acquired disability globally, yet the neural mechanisms driving motor recovery post-stroke remain elusive. Recent research has underscored the growing significance of subcortical pathways in neural plasticity and motor control. Among these, the cortico-reticulospinal tract (CRST) has gained attention in rehabilitation due to its unique ascending and descending structural features as well as its cellular properties which position it as an excellent candidate to compensate for inadequate motor control post-stroke. However, the optimal strategies to harness the CRST for motor recovery remain unknown. Non-invasive modulation of the CRST presents a promising though challenging, therapeutic opportunity. Acoustic startle priming (ASP) training and intermittent theta burst stimulation (iTBS) are emerging as potential methods to regulate CRST function. This study aims to investigate the feasibility of segmentally modulating the cortico-reticular and reticulospinal tracts through ASP and iTBS while evaluating the resulting therapeutic effects.Methods and analysisThis is a randomised, blinded interventional trial with three parallel groups. A total of 36 eligible participants will be randomly assigned to one of three groups: (1) iTBS+ASP group, (2) iTBS+non-ASP group, (3) sham iTBS+ASP group. The trial comprises four phases: baseline assessment, post-first intervention assessment, assessment after 3 weeks of intervention and a 4-week follow-up. The primary outcomes are the changes in the Fugl-Meyer Assessment-Upper Extremity and Modified Ashworth Scale after the 3-week intervention. Secondary outcomes include neurophysiological metrics and neuroimaging results from diffusion tensor imaging and resting-state functional MRI.Ethics and disseminationThe trial is registered with the Chinese Clinical Trial Registry (Registration No. ChiCTR2400085220) and Medical Ethics Committee of Tongji Hospital, affiliated with Tongji Medical College, Huazhong University of Science and Technology (Registration No.TJ-IRB20231109). It will be conducted in the Departments of Rehabilitation Medicine and Radiology at Tongji Hospital in Wuhan, China. The findings will be disseminated through peer-reviewed journal publications and presentations at scientific conferences.Trial registration numberChiCTR2400085220.

This paper presents a control method for the problem of trajectory jitter and poor tracking performance of the end of a three-joint rigid manipulator. The control is based on a high-order particle swarm optimization algorithm with an improved sliding mode control neural network. Although the sliding mode variable structure control has a certain degree of robustness, because of its own switching characteristics, chattering can occur in the later stage of the trajectory tracking of the manipulator end. Hence, on the basis of the high-order sliding mode control, the homogeneous continuous control law and super-twisting adaptive algorithm were added to further improve the robustness of the system. The radial basis function neural network was used to compensate the errors in the modeling process, and an adaptive law was designed to update the weights of the middle layer of the neural network. Furthermore, an improved particle swarm optimization algorithm was established and applied to optimize the parameters of the neural network, which improved the trajectory tracking of the manipulator end. Finally, MATLAB simulation results indicated the validity and superiority of the proposed control method compared with other sliding mode control algorithms.

To determine whether the pneumonia severity index (PSI) can predict in-hospital mortality for AECOPD patients and compare its usefulness with the CURB65 and BAP65 indexes to predict mortality. Demographics, clinical signs and symptoms, comorbidities, and laboratory and radiographic findings of hospitalized AECOPD patients were obtained. Univariate and multiple logistic regression analyses were used to identify the risk factors for in-hospital mortality. The PSI, CURB65 and BAP65 scores were calculated. Receiver operating characteristic (ROC) curve analysis was used to identify the PSI, CURB65 and BAP65 scores that could discriminate between non-survivors and survivors. To control for the confounding factor of invasive mechanical ventilation (IMV) regarding the mortality of AECOPD, subgroup analysis was performed when excluded patients who had met the criteria of IMV but who had not received the cure of IMV according to their wishes. During the in-hospital period, 73 patients died and 679 patients recovered. Age, PaO2<60 mmHg, pH < 7.35, PaCO2≥50 mmHg, nursing home residency, congestive heart failure, liver disease, sodium<130 mmol/L, lower FEV1% and altered mental status were risk factors for in-hospital mortality. The areas under the ROC curves (AUCs) of the PSI for death were 0.847 (95% CI: 0.799-0.895). The cut-off value was 116.5 with a sensitivity of 82.2% and a specificity of 77.6%. However, the AUCs of the CURB65 and BAP65 for death were only 0.744 (95% CI: 0.680-0.809) and 0.665 (95% CI: 0.594-0.736), respectively. Subgroup analysis also showed that the PSI score could predict the mortality of AECOPD patients with an AUC = 0.857 (95% CI: 0.802-0.913), with exclusion of the patients who met the criteria of IMV but who did not receive the cure of IMV. The PSI score may be used to predict in-hospital mortality for hospitalized AECOPD patients, with a prognostic capacity superior to CURB65 and BAP65.