Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

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.

Objective:To compare the short-term efficacy and the safety of microwave ablation (MWA) and radiofrequency ablation (RFA) in the treatment of benign thyroid nodules (BTNs).Methods:This prospective randomized controlled trial, performed from December 2019 to September 2021, included 36 patients with solid or predominantly solid BTNs who met the eligibility criteria and provided written informed consent at the Nanjing sub-center (Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine). Patients were assigned to either the MWA group or the RFA group (18 patients in each group) at a ratio of 1∶1 using a block randomization design and allocation concealment using sealed envelope randomization. The independent-sample t-test and χ2 test were used to compare the volume reduction rates (VRRs), effective rates (VRRs≥50%), cosmetic scores, and complication rates at 1, 3, and 6 months after treatment between the two groups. Results:The clinical characteristics of the two groups of patients were comparable. After ablation, the nodule volume was significantly reduced in both groups. At 1, 3, and 6 months, there was no significant difference in the volume between the two groups (all P>0.05). At 3 months, the RFA group had a larger VRRs than that in the MWA group (62.08%±12.46% vs. 46.90%±23.16%, t=-2.45, P=0.021). However, at 1 and 6 months, no statistical significance was observed (both P>0.05). No significant difference was observed in the effective rates at the last follow-up (14/18 vs. 18/18, P=0.104). However, the RFA group had a lower cosmetic score than that in the MWA group (1.78±0.43 vs. 2.17±0.51, t=-2.47, P=0.019). There was no statistically significant difference in the complication rates between the two groups (all P>0.05). Conclusions:Both MWA and RFA were effective and safe treatments for BTNs, with no significant differences in short-term efficacy and safety. In addition, the RFA group showed slightly more favorable outcomes than the MWA group in terms of cosmetic improvement.

In recent years, intestinal flora has gradually become the focus of research on the treatment of malignant neoplasms. Intestinal opportunistic pathogens (such as Fusobacterium nucleatum, Bacteroides fragilis), intestinal probiotics (such as Clostridium butyricum, Lactic acid bacteria) and intestinal pathogenic bacteria (such as Salmonella, Shigella) can affect the efficacy and related adverse reactions of radiotherapy, chemotherapy and immunotherapy for the colorectal cancer (CRC) by influencing signaling pathways, modulating autophagy, regulating immune response, producing metabolites and toxins, and transplanting fecal bacteria. At the same time, it provides a large number of potential targets for targeted therapy of the CRC. Further research on the relationship between intestinal flora and non-surgical treatment of the CRC can provide references for basic and clinical research of non-surgical treatment of the CRC.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

【Objective】 To investigate the association between genetic variations in the glucagon-like peptide-1 receptor (GLP-1R) gene and BP responses to sodium and potassium intake. 【Methods】 A total of 514 subjects from 124 families were recruited in Meixian County, Shaanxi Province, in 2004, resulting in the establishment of a "salt-sensitive hypertension study cohort" . The subjects followed a dietary regimen which involved a normal diet for 3 days, a low-salt diet for 7 days, a high-salt diet for 7 days, and a high-salt potassium-supplemented diet for 7 days. BP measurement was conducted at different intervention periods, and peripheral blood samples were collected. Additionally, eight single nucleotide polymorphisms (SNPs) of the GLP-1R gene were genotyped using the MassARRAY detection platform. 【Results】 The GLP-1R gene SNP rs9462472 exhibited a significant association with systolic BP, diastolic BP, and mean arterial pressure response to high-salt intervention. Similarly, SNP rs2268637 showed a significant association with systolic BP response to high-salt intervention. Furthermore, SNP rs2268637 was significantly associated with systolic BP and mean arterial pressure responses to high-salt plus potassium supplementation intervention. 【Conclusion】 Our findings indicate a significant association of genetic variations in the GLP-1R gene with BP responses to sodium and potassium intake. This suggests that the GLP-1R gene plays a role in the regulation of BP salt sensitivity and potassium sensitivity.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive dysfunction and behavioral impairment, and there is a lack of effective drugs to treat AD clinically. Existing medications for the treatment of AD, such as Tacrine, Donepezil, Rivastigmine, and Aducanumab, only serve to delay symptoms and but not cure disease. To add insult to injury, these medications are associated with very serious adverse effects. Therefore, it is urgent to explore effective therapeutic drugs for AD. Recently, studies have shown that a variety of enzyme inhibitors, such as cholinesterase inhibitors, monoamine oxidase (MAO)inhibitors, secretase inhibitors, can ameliorate cholinergic system dysfunction, Aβ production and deposition, Tau protein hyperphosphorylation, oxidative stress damage, and the decline of synaptic plasticity, thereby improving AD symptoms and cognitive function. Some plant extracts from natural sources, such as Umbelliferone, Aaptamine, Medha Plus, have the ability to inhibit cholinesterase activity and act to improve learning and cognition. Isochromanone derivatives incorporating the donepezil pharmacophore bind to the catalytic active site (CAS) and peripheral anionic site (PAS) sites of acetylcholinesterase (AChE), which can inhibit AChE activity and ameliorate cholinergic system disorders. A compound called Rosmarinic acid which is found in the Lamiaceae can inhibit monoamine oxidase, increase monoamine levels in the brain, and reduce Aβ deposition. Compounds obtained by hybridization of coumarin derivatives and hydroxypyridinones can inhibit MAO-B activity and attenuate oxidative stress damage. Quinoline derivatives which inhibit the activation of AChE and MAO-B can reduce Aβ burden and promote learning and memory of mice. The compound derived from the combination of propargyl and tacrine retains the inhibitory capacity of tacrine towards cholinesterase, and also inhibits the activity of MAO by binding to the FAD cofactor of monoamine oxidase. A series of hybrids, obtained by an amide linker of chromone in combine with the benzylpiperidine moieties of donepezil, have a favorable safety profile of both cholinesterase and monoamine oxidase inhibitory activity. Single domain antibodies (such as AAV-VHH) targeted the inhibition of BACE1 can reduce Aβ production and deposition as well as the levels of inflammatory cells, which ultimately improve synaptic plasticity. 3-O-trans-p-coumaroyl maslinic acid from the extract of Ligustrum lucidum can specifically inhibit the activity of γ-secretase, thereby rescuing the long-term potentiation and enhancing synaptic plasticity in APP/PS1 mice. Inhibiting γ-secretase activity which leads to the decline of inflammatory factors (such as IFN-γ, IL-8) not only directly improves the pathology of AD, but also reduces Aβ production. Melatonin reduces the transcriptional expression of GSK-3β mRNA, thereby decreasing the levels of GSK-3β and reducing the phosphorylation induced by GSK-3β. Hydrogen sulfide can inhibitGSK-3β activity via sulfhydration of the Cys218 site of GSK-3β, resulting in the suppression of Tau protein hyperphosphorylation, which ameliorate the motor deficits and cognitive impairment in mice with AD. This article reviews enzyme inhibitors and conformational optimization of enzyme inhibitors targeting the regulation of cholinesterase, monoamine oxidase, secretase, and GSK-3β. We are hoping to provide a comprehensive overview of drug development in the enzyme inhibitors, which may be useful in treating AD.