Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective : To investigate the protective effect of dimethyl fumarate(DMF) on maternal intrahepatic cholestasis(ICP) during pregnancy induced by di(2-ethylhexyl) phthalate(DEHP) exposure and its mechanism. Methods : Thirty-two 8-week-old female institute of cancer research(ICR) mice were randomly divided into 4 groups: Ctrl group, DEHP group, DMF group and DEHP+DMF group. DEHP and DEHP+DMF groups were treated with DEHP(200 mg/kg) by gavage every morning at 9:00 a.m. DMF and DEHP+DMF groups were treated with DMF(150 mg/kg) from day 13 to day 16 of gestation by gavage. After completion of gavage on day 16 of pregnancy, maternal blood, maternal liver, placenta, and amniotic fluid were collected from pregnant mice after a six-hour abrosia. The body weight of the mother rats and the body weight of the fetus rats were sorted and analyzed; the levels of total bile acid(TBA), alkaline phosphatase(ALP), aspartate aminotransferase/alanine aminotransferase(AST/ALT) in serum and TBA in liver, amniotic fluid and placenta were detected by biochemical analyzer; HE staining was used to observe the pathological changes of liver tissue; Quantitative reverse transcription PCR(RT-qPCR) was used to detect the expression levels of tumor necrosis factor-α(TNF-α), interleukin(IL)-6, IL-1, IL-18 and NOD-like receptor thermal protein domain associated protein 3(NLRP3) in the liver; Western blot was used to detect the expression of the nuclear factor KappaB(NF-κB) and NLRP3. Results : Compared with the control group, the body weight of the DEHP-treated dams and pups decreased(P<0.05); the levels of TBA, ALP, AST/ALT in the serum of dams and the levels of TBA in the liver, amniotic fluid, and placenta of dams increased(P<0.05); the histopathological results showed that liver tissue was damaged, bile ducts were deformed, and there was inflammatory cell infiltration around them; the levels of inflammation-related factors TNF-α, IL-6, IL-1, IL-18 and NLRP3 transcription in maternal liver increased(P<0.05); the expression of NF-κB and NLRP3 protein in maternal liver significantly increased( P<0. 05). Compared with the DEHP group,the body weight of both dams and fetuses significantly increased in DEHP + DMF group( P<0. 05); the levels of TBA,ALP,AST/ALT in the serum of dams and amniotic fluid of fetuses decreased( P<0. 05); the degree of liver lesions was improved; the transcription levels of inflammation-related factors TNF-α,IL-6,IL-1,IL-18 and NLRP3 in maternal liver decreased( P<0. 05); the expression of NF-κB and NLRP3 protein in maternal liver significantly decreased( P<0. 05). Conclusion DMF can effectively protect the DEHP exposure to lead to female ICP,and its mechanism may be through inhibiting the NF-κB/NLRP3 pathway and reducing liver inflammation.

As a chronic and lifelong disease， diabetes mellitus occurs across all age groups and gender groups. Since the disease requires lifelong treatment， it seriously affects the quality of life of patients. With the rising incidence on a global scale， diabetes mellitus has become a global problem that seriously affects public health. Moreover， the complications of this disease have aroused concern from the global medical research community， the World Health Organization， and the public. In the past， Western medicine was used in the clinical treatment of diabetes mellitus， which， however， had drug dependence， unsatisfactory efficacy， and side effects. Long-term oral administration of antidiabetics may cause liver and kidney function damage， hypoglycemia and other adverse symptoms. The treatment of diabetes mellitus has been faced with challenges such as limited efficacy and obvious side effects. Therefore， exploring more effective treatment means， especially tapping the potential of traditional Chinese medicine （TCM） in the treatment of diabetes mellitus， is a major issue to be solved. TCM has shown a great application value and a broad prospect in the treatment of diabetes mellitus because of multi-target regulation， a holistic view， synergistic effects， and high safety. TCM has a history of thousands of years in the prevention and treatment of diabetes mellitus， with rich experience accumulated and remarkable results achieved. Particularly， TCM demonstrates definite therapeutic effects on the complications. The application of TCM in the treatment of complications has been recognized and accepted by patients because of the definite therapeutic effect. In recent years， great progress has been achieved in the treatment of diabetes mellitus by the combination of Chinese and western medicine， which has made important contributions to the control of diabetes mellitus. This paper reviews the articles about the treatment of diabetes mellitus with TCM classic prescriptions， summarizes the treatment of clinical cases regarding the indications of these prescriptions， and provides an overview of the treatment mechanisms， aiming to offer fresh insights and strategies for the clinical diagnosis and treatment of diabetes mellitus.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

BACKGROUND:It has been shown that Gushukang affects bone metabolism by regulating nucleotide and amino acid metabolism and immune mechanisms.Current research on the mechanism of Gushukang in the treatment of osteoporosis primarily focuses on osteoblast regulation and requires further improvement from the perspective of osteoclasts. OBJECTIVE:To investigate the mechanism by which Gushukang interferes with osteoclasts in the treatment of osteoporosis using RAW264.7 cells as the research model. METHODS:Twenty-four 8-week-old female Sprague-Dawley rats were randomly divided into four groups(n=6 per group):the three experimental groups were given 1,2 and 4 g/kg osteoporosis solution by gavage(2 times per day),and the control group was given an equal amount of distilled water by gavage(2 times per day).After 7 days of intragastric administration,aortic blood samples were extracted to collect serum samples using centrifugation,and serum samples from the same groups were combined to obtain the low-,medium-,and high-concentration Gushukang-containing and normal sera for the subsequent experiments.(1)RAW264.7 cells were cultured in six groups:normal serum was added to the control group;low,medium,and high concentration groups were added with low,medium,and high concentrations of Gushukang-containing serum,respectively;ML385,a nuclear factor erythroid 2-related factor 2(Nrf2)inhibitor was given in the Nrf2 inhibitor group;and t-BHQ,a Nrf2 activator,was added in the Nrf2 activator group.Cell viability was detected using the cell counting kit-8 assay.(2)The 3rd generation RAW 264.7 cells were cultured and divided into five groups:the blank control group was added with normal serum,the osteoclast group was added with receptor activator of nuclear factor κB ligand(RANKL),and the low-,medium-,and high-concentration groups were added with low-,medium-,and high-concentration Gushukang-containing serum based on the addition of RANKL.Tartrate-resistant acid phosphate staining was performed after 5 days of culture.(3)RAW264.7 cells were cultured and divided into five groups:blank control group was cultured with normal serum,osteoclast group cultured with normal serum and RANKL,high concentration+osteoclast group cultured with RANKL+high concentration Gushukang-containing serum,osteoclast+Nrf2 agonist group cultured with RANKL+t-BHQ,and high concentration+osteoclast+Nrf2 inhibitor group cultured with RANKL+high concentration Gushukang-containing serum+ML385.Western blot assay and determination of reactive oxygen content were performed after 5 days of culture. RESULTS AND CONCLUSION:The cell counting kit-8 results indicated that Gushukang-containing serum,NRF2 inhibitor or agonist had no significant effect on RAW264.7 cell viability.Tartrate-resistant acid phosphate staining results demonstrated that Gushukang-containing serum exhibited a concentration-dependent inhibitory effect on osteoclast differentiation.Western blot analysis and determination of reactive oxygen species revealed that compared with the blank control group,Nrf2 protein expression was decreased in the osteoclast group(P<0.05),while c-Fos and NFATc1 protein expression and reactive oxygen species content were elevated(P<0.05);compared with the osteoclast group,Nrf2 protein expression was elevated and reactive oxygen species content was decreased in the high-concentration+osteoclast group,osteoclast+Nrf2 agonist group,and high-concentration+osteoclast+Nrf2 inhibitor group(P<0.05),while c-Fos and NFATc1 protein expression was decreased in the high concentration+osteoclast group and osteoclast+Nrf2 agonist group(P<0.05);compared with the high concentration+osteoclast group,Nrf2 protein expression was decreased(P<0.05)and reactive oxygen species content was elevated(P<0.05)in the high concentration+osteoclast+Nrf2 inhibitor group.To conclude,Gushukang reduces reactive oxygen species production by activating Nrf2,thereby inhibiting downstream of the c-Fos/NFATc1 pathway and suppressing osteoclast differentiation.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Objective To introduce the modeling method of pendulum-like modified rat abdominal heart heterotopic transplantation model and evaluate the quality of the model. Methods An operator without transplantation experience performed 15 consecutive models, recorded the time of each step, changes in body weight and modified Stanford scores, and calculated the surgical success rate, postoperative 1-week survival rate and technical success rate. Ultrasound examinations was performed in 1 week postoperatively. Results The times for donor heart acquisition, donor heart processing, recipient preparation and transplantation anastomosis were (14.3±1.4) min, (3.5±0.6) min, (13.6±2.1) min and (38.3±5.2) min respectively. The surgical success rate was 87% (13/15), and the survival rate 1 week after operative was 100% (13/13). The improved Stanford score indicated a technical success rate of 92% (12/13), and the postoperative 1-week ultrasound examination showed that grafts with Stanford scores ≥3 had detectable pulsation and blood flow signals. Conclusions The pendulum-like modified rat abdominal heart heterotopic transplantation improved model further optimizes the operational steps with a high success rate and stable quality, may be chosen as a modeling option for basic research in heart transplantation in the future.

[Objective] To analyze the effects of different factors and red blood cell transfusion thresholds on the efficacy of neonatal red blood cell (RBC) transfusion, in order to provide more references for neonatal transfusions to better achieve rational and effective blood use. [Methods] A retrospective collection of data from 282 neonates who received RBC transfusions at our hospital from 2022 to 2023 was conducted, including birth weight, gestational age, number of blood transfusions, length of hospital stay, assisted ventilation during RBC transfusion, and laboratory test results before and after transfusion. SPSS software was used for statistical analysis to comprehensively analyze the impact of different factors on the efficacy of RBC transfusion in neonates. [Results] The results showed that the gestational age and weight of newborns at birth were negatively correlated with their length of hospital stay and the number of RBC transfusions during hospitalization. Newborns with younger gestational age and lower weight had longer hospital stays and more RBC transfusions during hospitalization. After administering RBCs according to the standard of 15 mL/kg, there was a statistically significant difference in the efficacy of RBC transfusion at different transfusion thresholds. In non-critical situations, RBC transfusions were ineffective when the pre-transfusion hemoglobin (Hb) level was >120 g/L. When the pre-transfusion Hb level was ≤70 g/L, RBC transfusions achieved higher efficacy in both critical and non-critical situations. [Conclusion] In critical situations, the group with pre-transfusion Hb values ≤ 70 g/L has the best RBC transfusion effect, while in non-critical situations, the group with pre-transfusion Hb levels between 81 and 90 g/L has the best RBC transfusion effect. Overall, the efficacy of RBC transfusion in non-critical situations is higher than that in critical situations.