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.

Oral solid dosage forms require processes such as disintegration and dissolution to release the drug before it can be absorbed and utilized by the body. In this manuscript, imaging technology was used to continuously visualize and characterize the in vitro static drug release process of gliclazide modified release tablets from 15 manufacturers, combined with the traditional method of in vitro dissolution testing, to determine the release profile of gliclazide modified release tablets, to evaluate the similarity of the release profiles by using the similarity factor (f₂) method and based on the analysis of the release profiles fitted with a variety of mathematical models. The results indicate that the gliclazide modified release tablets produced by 14 companies are hydrophilic gel matrix tablets. Compared to the reference listed drug, the release profiles of formulations from 11 companies show high similarity (f₂ > 50) to the reference. Among these, formulations with visual characteristics similar to the reference exhibit similar release curves. This study provides an alternative method for the in vitro consistency evaluation of gliclazide modified release tablets, aiming to assess the in vitro release behaviour of generic formulations more accurately and comprehensively.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

BACKGROUND:It has been hypothesized that PANoptosis may be involved in the pathologic process of osteoporosis,but there have been no studies addressing the mechanisms of PANoptosis genes in osteoporosis. OBJECTIVE:To analyze the biological mechanism of PANoptosis regulators in the occurrence and development of osteoporosis. METHODS:The GSE56815 dataset was obtained from the Gene Expression Omnibus database and PANoptosis genes were extracted for differential analysis.The key genes of PANoptosis were screened by random forest tree model to construct a disease risk prediction model.Consensus clustering algorithm,single sample genome enrichment analysis and immune infiltration analysis were used to explore the differences between different PANoptosis molecular subtypes.Herbal drugs that regulate the key genes of PANoptosis were predicted through Coremine medical database,a medical ontology information retrieval platform. RESULTS AND CONCLUSION:Based on the four PANoptosis key genes(CASP1,CASP10,MEFV,and TNF),the diagnostic markers of osteoporosis were determined,and the risk prediction model was constructed and verified.Osteoporosis was divided into two different PANoptosis subtypes(clusters A,B and gene clusters A,B),and the PANoptosis scores of cluster B and gene cluster B were higher than those of cluster A and gene cluster A,respectively.Traditional Chinese drugs such as ginseng which can regulate the key genes of PANoptosis were predicted by the Coremine medical database.

Objective To explore the changes of metabonomics in blood of mice after high-voltage electric shock,then screen out the significantly changed differential metabolites and metabolic pathways.Methods The head of C57BL/6J mice was subjected to high-voltage electric shock(electric shock group)or exposed to acoustic and optical stimulation of high-voltage electric(control group),then the whole blood from mice were collected to separate serum.The dual platform combined metabonomic analysis based on gas chromatography-mass spectrometer(GC-MS)and liquid chromatography-mass spectrometer(LC-MS)was performed and orthogonal partial least squares discriminant analysis(OPLS-DA)was used to screen the differential metabolites and related metabolic pathways.Results A total of 415 differential metabolites were screened out in metabonomics in blood of mice after high-voltage electric shock,including 187 up-regulated and 228 down-regulated metabolites.These differentially metabolites were significantly enriched in metabolic pathways including central carbon metabolism in cancer,glucagon signaling pathway,etc.Conclusion By establishing the model of high-voltage electrical injury on experimental mice,this study reveals the significant change of metabolite content and metabolic pathway in blood by high-voltage electrical injury.Which provides a basis for the damage of blood metabolic activity by high-voltage electrical injury,and suggests the potential harm of high-voltage electrical injury to blood metabolic activity in the whole body.

AIM: To investigate the efficacy and safety of ZKY001 eye drops with different concentrations in the treatment of corneal epithelial defects(CED)after primary pterygium excision.METHODS: This was a multicenter, randomized, double-blinded, placebo-controlled phase II clinical trial. From March 15, 2022 to November 14, 2022, patients with primary pterygium who had undergone surgery were recruited from 12 tertiary hospitals across China. Using block randomization, 178 patients(178 eyes)were randomly assigned to 3 groups in a 1:1:1 ratio: 0.002% ZKY001 group(n=59), 0.004% ZKY001 group(n=59), and placebo group(n=60, receiving ZKY001 sham eye drops). Subjects in each group received 1 drop of the study drug 4 times per day for 4 d. The percentage of CED area recovery from baseline, the first complete healing time of CED area, the number of first complete healing cases of CED, and changes in visual analogue scale(VAS)scores for eye discomfort including eye pain, foreign body sensation, tearing and photophobia were observed.RESULTS: In terms of improvement in CED, there were no statistically significant differences among the three groups including the first healing time of CED, the percentage improvement in CED area compared to baseline, and the percentage of first healing cases at different follow-up visits(all P>0.05). Numerically, the first healing time of CED was shorter in the test groups compared to the placebo group(67.87±21.688 h for the 0.002% ZKY001 group, 61.48±22.091 h for the 0.004% ZKY001 group, and 68.85±20.851 h for the placebo group). On D1 morning, the percentage improvement in CED area compared to baseline was maximally different from the placebo group, and the numerical difference advantage was maintained at subsequent follow-up visits. The number of first healing cases in the CED area at different follow-up visits was higher in the test groups than the placebo group. In terms of improvement in ocular discomfort, the total VAS scores were lower in the test groups compared to the placebo group, mainly due to reductions in foreign body sensation and pain scores. At D3, the 0.004% ZKY001 group showed statistically significant improvement in foreign body sensation(P<0.017). In terms of safety, the overall incidence of adverse events was low(9.0%)and similar among groups.CONCLUSION: The use of ZKY001 eyedrops after primary pterygium surgery can safely improve the CED repair, and alleviate postoperative symptoms caused by CED.