Objective To evaluate the efficacy of Puerariae lobatae radix （PLR） and Anemarrhenae Rhizoma （AR） in preventing and treating Alzheimer’s disease （AD） and explore its potential mechanism of action by LC-MS serum metabolomics strategy. Methods The AD rat model was established by administering aluminum chloride （AlCl₃） and D-galactose （D-gal） for 20 weeks. The traditional Chinese medicine intervention group was given the PLR, AR, and PLR-AR extracts for 8 weeks by gavage. The model effect and efficacy were evaluated by Morris water maze test and biochemical indicators including SOD, NO, and MDA; Metabolomics research based on the UHPLC-Q/TOF-MS method was conducted, and relevant metabolic pathways were analyzed through the MetaboAnalyst online website. Results The learning and memory abilities of AD model rats were significantly decreased compared with the control group, and the levels of oxidative stress and lipid peroxides were significantly increased （P<0.05）, while the SOD content was decreased considerably （P<0.01）. The learning and memory abilities of AD model rats were improved, oxidative stress and lipid peroxidation levels were reversed, and serum SOD content was increased significantly after the intervention of PLR-AR, with better effects than single drugs. Through metabolomics, 70 differential metabolites were identified between the AD model group and the control group, mainly involving 10 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and unsaturated fatty acid biosynthesis, et.al. The intervention of PLR-AR could adjust 47 metabolites, with 20 metabolites showing significant differences （P<0.05）. The significantly adjusted metabolites involve 6 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, et al. Conclusion The combination of PLR and AR could significantly improve the learning and memory abilities of AD rat models. The mechanism may be related to the improvement of oxidative stress and lipid peroxidation levels, the increase of serum SOD content, and the regulation of phenylalanine, tyrosine, and tryptophan biosynthesis pathways.

Biosensor analysis technology is a kind of technology with high specificity that can convert biological reactions into optical and electrical signals. In the development of drugs for Alzheimer's disease (AD), according to different disease hypotheses and targets, this technology plays an important role in confirming targets and screening active compounds. This paper briefly describes the pathogenesis of AD and the current situation of therapeutic drugs, introduces three biosensor analysis techniques commonly used in the discovery of AD drugs, such as surface plasmon resonance (SPR), biolayer interferometry (BLI) and fluorescence analysis technology, explains its basic principle and application progress, and summarizes their advantages and limitations respectively.

Immunoassays are widely used in medicine, food, environment and other fields due to having the advantages of simpleness, rapidness and accuracy. Combining immunoassays with nanomaterials can improve the performance of immunoassays. Compared with traditional nanomaterials, upconversion nanoparticles (UCNPs) have excellent optical properties such as good photostability, long luminescence lifetime and narrow and tunable emission bands, which can significantly reduce background noise and improve analytical sensitivity when combined with immunoassay. This paper briefly introduces the luminescence mechanism of UCNPs, summarizes the synthesis and surface modification methods of UCNPs. And then 5 UCNPs-based immunoassay techniques, namely, fluorescence resonance energy transfer, inner filter effect, magnetic separation technique, upconversion-linked immunosorbent assay and upconversion immunochromatography, are discussed in detail. These sensing protocols of UCNPs-based immunoassays have been successfully utilized to detect various targets, including small molecules, macromolecules, and pathogens, all of which closely related to food safety, human health, and environmental pollution. Finally, the challenges and prospects of this technique are summarized and prospected. Although the UCNPs immunoassays based on antibodies and antigens have made great progress, most of the research is still in the stage of laboratory, and there is a long way to go to realize its social applications. There is a series of challenges need to be overcome. (1) Designing excellent water soluble and dispersive upconversion nanomaterials is needed. Hydrophilic ligands are bound to smaller upconversion nanoparticles and removing hydrophobic surface ligands are the most widely used methods to improve solubility and dispersity. (2) Multi-detection technology platforms and multi-mode simultaneous detection platforms have great potential, which will improve the efficiency of point of care detection. (3) The researchers also need to focus on some important problems. For examples, the upconversion luminescence efficiency of UCNPs is difficult to maintain, the synthesis method is complex, and the surface modification degree and functionalization are difficult to control.

【Objective】 To establish an effective quality indicator monitoring system, scientifically and objectively evaluate the quality management level of blood banks, and achieve continuous improvement of quality management in blood bank. 【Methods】 A quality monitoring indicator system that covers the whole process of blood collection and supply was established, the questionnaire of Quality Monitoring Indicators for Blood Collection and Supply Process with clear definition of indicators and calculation formulas was distributed to 17 blood banks in Shandong. Statistical analysis of 21 quality monitoring indicators in terms of blood donation service (10 indicators), blood component preparation (7 indicators ), and blood supply (4 indicators) from each blood bank from January to December 2022 were conducted using SPSS25.0 software The differences in quality monitoring indicators of blood banks of different scales were analyzed. 【Results】 The average values of quality monitoring indicators for blood donation service process of 17 blood banks were as follows: 44.66% (2 233/5 000) of regular donors proportion, 0.22% (11/50) of adverse reactions incidence, 0.46% (23/5 000) of non-standard whole blood collection rate, 0.052% (13/25 000) of missed HBsAg screening rate, 99.42% (4 971/5 000) of first, puncture successful rate, 86.49% (173/200) of double platelet collection rate, 66.50% (133/200) of 400 mL whole blood collection rate, 99.25% (397/400) of donor satisfaction rate, 82.68% (2 067/2 500) of use rate of whole blood collection bags with bypass system with sample tube, and 1 case of occupational exposure in blood collection.There was a strong positive correlation between the proportion of regular blood donors and the collection rate of 400 mL whole blood (P<0.05). The platelet collection rate, incidence of adverse reactions to blood donation, and non-standard whole blood collection rate in large blood banks were significantly lower than those in medium and small blood banks (P<0.05). The average quality monitoring indicators for blood component preparation process of 17 blood banks were as follows: the leakage rate of blood component preparation bags was 0.03% (3/10 000), the discarding rate of lipemic blood was 3.05% (61/2 000), the discarding rate of hemolysis blood was 0.13%(13/10 000). 0.06 case had labeling errors, 8 bags had blood catheter leaks, 2.76 bags had blood puncture/connection leaks, and 0.59 cases had non-conforming consumables. The discarding rate of hemolysis blood of large blood banks was significantly lower than that of medium and small blood banks (P<0.05), and the discarding rate of lipemic blood of large and medium blood banks was significantly lower than that of small blood banks (P<0.05). The average values of quality monitoring indicators for blood supply process of 17 blood banks were as follows: the discarding rate of expired blood was 0.023% (23/100 000), the leakage rate during storage and distribution was of 0.009%(9/100 000), the discarding rate of returned blood was 0.106% (53/50 000), the service satisfaction of hospitals was 99.16% (2 479/2 500). The leakage rate of blood components during storage and distribution was statistically different with that of blood component preparation bags between different blood banks (P<0.05). There were statistically significant differences in the proportion of regular blood donors, incidence of adverse reactions, non-standard whole blood collection rate, 400 mL whole blood collection rate, double platelet collection rate, the blood bag leakage rate during preparation process, the blood components leakage rate during storage and distribution as well as the discarding rate of lipemic blood, hemolysis blood, expired blood and returned blood among large, medium and small blood banks (all P<0.05). 【Conclusion】 The establishment of a quality monitoring indicator system for blood donation services, blood component preparation and blood supply processes in Shandong has good applicability, feasibility and effectiveness. It can objectively evaluate the quality management level, facilitate the continuous improvement of the quality management system, promote the homogenization of blood management in the province and lay the foundation for future comprehensive evaluation of blood banks.

Objective To explore characteristics of clinical parameters and cytokines in patients with drug-induced liver injury(DILI)caused by different drugs and their correlation with clinical indicators. Method The study was conducted on patients who were up to Review of Uncertainties in Confidence Assessment for Medical Tests(RUCAM)scoring criteria and clinically diagnosed with DILI.Based on Chinese herbal medicine,cardiovascular drugs,non-steroidal anti-inflammatory drugs(NSAIDs),anti-infective drugs,and other drugs,patients were divided into five groups.Cytokines were measured by Luminex technology.Baseline characteristics of clinical biochemical indicators and cytokines in DILI patients and their correlation were analyzed. Results 73 patients were enrolled.Age among five groups was statistically different(P=0.032).Alanine aminotransferase(ALT)(P=0.033)and aspartate aminotransferase(AST)(P=0.007)in NSAIDs group were higher than those in chinese herbal medicine group.Interleukin-6(IL-6)and tumor necrosis factor alpha(TNF-α)in patients with Chinese herbal medicine(IL-6:P<0.001;TNF-α:P<0.001)and cardiovascular medicine(IL-6:P=0.020;TNF-α:P=0.001)were lower than those in NSAIDs group.There was a positive correlation between ALT(r=0.697,P=0.025),AST(r=0.721,P=0.019),and IL-6 in NSAIDs group. Conclusion Older age may be more prone to DILI.Patients with NSAIDs have more severe liver damage in early stages of DILI,TNF-α and IL-6 may partake the inflammatory process of DILI.

Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with dysfunctions related to thinking, learning, and memory of the brain. AD has multiple pathological characteristics with complicated causes, constructing a suitable pathological model is crucial for the research of AD. Microfluidic chip technology integrates multiple functional units on a chip, which can realize microenvironmental control similar to the physiological environment. It is well applied in the construction of pathological model, early diagnosis as well as drug screening of AD. This paper focuses on the construction of AD microfluidic chips model from the perspective of cell type, culture formats and the chips structure as well as the research progress of microfluidic chips in AD application based on the pathological characteristics of AD, which will provide a reference for further elucidation of AD mechanism and drug development.

This experiment aims to study the taste-masking effects of different kinds of corrigent used individually and in combination on ibuprofen oral solution, in order to optimize the taste-masking formulation. Firstly, a wide range of corrigent and the mass fractions were extensively screened using electronic tongue technology. Subsequently, a combination of sensory evaluation, analytic hierarchy process (AHP)-fuzzy mathematics evaluation, and Box-Behnken experimental design were employed to comprehensively assess the taste-masking effects of different combinations of corrigent on ibuprofen oral solution, optimize the taste-masking formulation, and validate the results. The study received ethical approval from the Review Committee of the Beijing University of Chinese Medicine (ethical code: 2024BZYLL0102). The results showed that corrigent fractions and types were screened separately through single-factor experiments. Subsequently, a Box-Behnken response surface design combined with AHP and fuzzy mathematics evaluation was used to fit a functional model: Z = 688.310 11 - 3 023.722 22X₁ - 11.477 00X₂ + 62.721 67X₃ + 14.600 00X₁X₂ - 179.666 67X₁X₃ - 3.152 00X₂X₃ + 4 031.111 11X₁² + 0.525 28X₂² + 9.772 00X₃². This model is stable and reliable, determining the optimal taste-masking formulation to be 3.9 g·L^-1 of stevioside, 100 g L^-1 of xylitol, and 30 g L^-1 of methyl-β-cyclodextrin. The comprehensive score of the verification test is 88.14, with a relative RSD of 0.39%, indicating the feasibility of this model. This study achieved the improvement of the taste of ibuprofen oral solution through a combination of objective and subjective methods. Three types of corrigent were identified for enhancing drug taste, leading to the selection of the optimal taste-masking formulation for ibuprofen oral solution. This significantly enhanced the taste of the original formulation, improved patient compliance, and offered a new approach to mitigating the undesirable taste of formulations.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To explore the biomarkers and potential mechanisms of chronic restraint stress-induced myocardial injury in hyperlipidemia ApoE-/-mice.Methods The hyperlipidemia combined with the chronic stress model was established by restraining the ApoE-/-mice.Proteomics and bioinformatics techniques were used to describe the characteristic molecular changes and related regulatory mechanisms of chronic stress-induced myocardial injury in hyperlipidemia mice and to explore potential diagnostic biomarkers.Results Proteomic analysis showed that there were 43 significantly up-regulated and 58 sig-nificantly down-regulated differentially expressed proteins in hyperlipidemia combined with the restraint stress group compared with the hyperlipidemia group.Among them,GBP2,TAOK3,TFR1 and UCP1 were biomarkers with great diagnostic potential.KEGG pathway enrichment analysis indicated that fer-roptosis was a significant pathway that accelerated the myocardial injury in hyperlipidemia combined with restraint stress-induced model.The mmu_circ_0001567/miR-7a/Tfr-1 and mmu_circ_0001042/miR-7a/Tfr-1 might be important circRNA-miRNA-mRNA regulatory networks related to ferroptosis in this model.Conclusion Chronic restraint stress may aggravate myocardial injury in hyperlipidemia mice via ferrop-tosis.Four potential biomarkers are selected for myocardial injury diagnosis,providing a new direction for sudden cardiac death(SCD)caused by hyperlipidemia combined with the restraint stress.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.