Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, functional impairment, and neuropsychiatric symptoms. It represents the most prevalent form of dementia among the elderly population. Accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of AD. Notably, elevated levels of oxidative stress have been observed in the brains of AD patients, where excessive reactive oxygen species (ROS) can cause extensive damage to lipids, proteins, and DNA, ultimately compromising neuronal structure and function. Amyloid β‑protein (Aβ) has been shown to induce mitochondrial dysfunction and calcium overload, thereby promoting the generation of ROS. This, in turn, exacerbates Aβ aggregation and enhances tau phosphorylation, leading to the formation of two pathological features of AD: extracellular Aβ plaque deposition and intracellular neurofibrillary tangles (NFTs). These events ultimately culminate in neuronal death, forming a vicious cycle. The interplay between oxidative stress and these pathological processes constitutes a core link in the pathogenesis of AD. The signaling pathways mediating oxidative stress in AD include Nrf2, RCAN1, PP2A, CREB, Notch1, NF‑κB, ApoE, and ferroptosis. Nrf2 signaling pathway serves as a key regulator of cellular redox homeostasis, exerts important antioxidant capacity and protective effects in AD. RCAN1 signaling pathway, as a calcineurin inhibitor, and modulates AD progression through multiple mechanisms. PP2A signaling pathway is involved in regulating tau phosphorylation and neuroinflammation processes. CREB signaling pathway contributes to neuroplasticity and memory formation; activation of CREB improves cognitive function and reduce oxidative stress. Notch1 signaling pathway regulates neuronal development and memory, participates in modulation of Aβ production, and interacts with Nrf2 toco-regulate antioxidant activity. NF‑κB signaling pathway governs immune and inflammatory responses; sustained activation of this pathway forms “inflammatory memory”, thereby exacerbating AD pathology. ApoE signaling pathway is associated with lipid metabolism; among its isoforms, ApoE-ε4 significantly increases the risk of AD, leading to elevated oxidative stress, abnormal lipid metabolism, and neuroinflammation. The ferroptosis signaling pathway is driven by iron-dependent lipid peroxidation, and the subsequent release of lipid peroxidation products and ROS exacerbate oxidative stress and neuronal damage. These interconnected pathways form a complex regulatory network that regulates the progression of AD through oxidative stress and related pathological cascades. In terms of therapeutic strategies targeting oxidative stress, among the drugs currently used in clinical practice for AD treatment, memantine and donepezil demonstrate significant therapeutic efficacy and can improve the level of oxidative stress in AD patients. Some compounds with antioxidant effects (such asα-lipoic acid and melatonin) have shown certain potential in AD treatment research and can be used as dietary supplements to ameliorate AD symptoms. In addition, non-drug interventions such as calorie restriction and exercise have been proven to exerted neuroprotective effects and have a positive effect on the treatment of AD. By comprehensively utilizing the therapeutic characteristics of different signaling pathways, it is expected that more comprehensive multi-target combination therapy regimens and combined nanomolecular delivery systems will be developed in the future to bypass the blood-brain barrier, providing more effective therapeutic strategies for AD.

Objective To explore the relationship and internal path between activities of daily living(ADL),sleep quality and mental health of community elderly people in Shanghai.Methods A questionnaire survey was conducted among community residents aged 60 years and older seeing doctors in community health care center of five streets in Shanghai during Sept to Dec,2021 using convenience sampling.Activities of Daily Living(ADL),Pittsburgh Sleep Quality Index(PSQI)and 10-item Kessler Psychological Distress Scale(K10)were adopted in the survey.Single factor analysis,correlation analysis and multiple linear regression were used to analyze the data.The effect relationship between the variables was tested using Bootstrap's mediated effects test.Results A total of 1 864 participants were included in the study.The average score was 15.53±4.47 for ADL,5.60±3.71 for PSQI and 15.50±6.28 for K10.The rate of ADL impairment,poor sleep quality,poor and very poor mental health of the elderly were 23.6%,27.3%,11.9%and 4.9%,respectively.ADL and sleep quality were all positively correlated with mental health(r=0.321,P＜0.001;r=0.466,P＜0.001);ADL was positively correlated with sleep quality(r=0.294,P＜0.001).Multiple linear results of factors influencing mental health showed that ADL(β= 0.457,95%CI:0.341-0.573),sleep quality(β =0.667,95%CI:0.598-0.737)and mental health were positively correlated(P＜0.001).Sleep quality partially mediated the relationship between ADL and mental health(95%CI:0.078-0.124)with an effect size of 33.0%.Conclusion Sleep quality is a mediator between ADL and mental health among community elderly people.Improving ADL and sleep quality may improve mental health in the population.

With the advent of an aging society,Alzheimer's disease(AD)has gradually become a major ailment affecting the elderly.AD is a neurodegenerative disorder associated with cognitive impairments.In AD patients,brain network connections are disrupted,and their topological properties are also affected,leading to the disintegration of anatomical and functional connections.Anatomical connections can be tracked and evaluated using structural magnetic imaging(MRI)and diffusion tensor imaging(DTI),while functional connections are detected through functional MRI to assess their connectivity status.This review incorporates the findings of previous scholars and summarizes the current research of AD.It mainly discusses the imaging characteristics of large-scale brain network changes in AD patients,so as to provide researchers with scientific and objective imaging markers for AD prediction and early diagnosis,as well as future research.

Currently,human health due to corona virus disease 2019(COVID-19)pandemic has been seriously threatened.The coronavirus severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)spike(S)protein plays a crucial role in virus transmission and several S-based therapeutic approaches have been approved for the treatment of COVID-19.However,the efficacy is compromised by the SARS-CoV-2 evolvement and mutation.Here we report the SARS-CoV-2 S protein receptor-binding domain(RBD)inhibitor licorice-saponin A3(A3)could widely inhibit RBD of SARS-CoV-2 variants,including Beta,Delta,and Omicron BA.1,XBB and BQ1.1.Furthermore,A3 could potently inhibit SARS-CoV-2 Omicron virus in Vero E6 cells,with EC50 of 1.016 pM.The mechanism was related to binding with Y453 of RBD deter-mined by hydrogen-deuterium exchange mass spectrometry(HDX-MS)analysis combined with quan-tum mechanics/molecular mechanics(QM/MM)simulations.Interestingly,phosphoproteomics analysis and multi fluorescent immunohistochemistry(mIHC)respectively indicated that A3 also inhibits host inflammation by directly modulating the JNK and p38 mitogen-activated protein kinase(MAPK)path-ways and rebalancing the corresponding immune dysregulation.This work supports A3 as a promising broad-spectrum small molecule drug candidate for COVID-19.

Objective:To extract the early result of postoperative echocardiographic evaluation in patients underwent left ventricular assist device (LVAD) implantation, and to assess the efficacy of surgical treatment for end-staged heart failure.Methods:Between June 2019 and May 2023, the patients underwent left ventricular assist device implantation were enrolled in this study. Demographic baseline characteristics and perioperative echocardiographic parameters were collected and analyzed.Results:A total of 28 patients were included in the study. After LVAD implantation, the heart sizes of the patients obviously reduced and the left heart contractibility function improved. The right ventricular contractibility remained stable. The proportion of the patients with moderate to severe mitral regurgitation was significantly reduced, but patients with mild to moderate aortic insufficiency increased. No serious complications such as death, pericardial tamponade and thrombosis events were observed during the follow-up period.Conclusion:LVAD implantation improved the left cardiac function, while the right cardiac function remained stable. However, it should be paid attention that the aortic valve function was impaired after the surgery. Generally, the early results of LVAD implantation for the treatment of end-stage heart failure were satisfactory.

Objective To explore the effect of Qingre Xiaoyanning tablets on chronic toxicity in SD rats.Methods A total of 120 SD rats were randomly divided into blank group(water)and experimental-L,-M,-H groups(2.63,5.25 and 10.50 g·kg 1 Qingre Xiaoyanning dry paste powder),with 30 rats per group.Four groups were administered continuously for 4 weeks with a recovery period of 4 weeks.SD rats were dissected as planned.The general condition,weight gain,hematological and biochemical indexes,major organ coefficients,macroscopic and microscopic tissue morphology were observed.Results There were no significant differences in the general condition,body mass growth,coagulation index and histopathology of rats between the experimental-L,-M,-H groups and the blank group.End of administration,the mean hemoglobin concentrations of experimental-H and blank groups were(370.70±3.78)and(365.90±5.77)g·L-1,glucose were(5.98±0.63)and(6.61±0.93)mmol·L-1,blood urea nitrogen(BUN)were(4.72±1.01)and(5.78±1.64)mmol·L-1,liver coefficients were 3.05±0.17 and 2.89±0.19,and the differences were statistically significant(P≤0.05,P≤0.01).Resumption of the final,direct bilirubin of experimental-L and blank groups were(0.38±0.18)and(0.19±0.18)pmol·L 1,BUN of experimental-M and blank groups were(4.45±0.56)and(5.65±1.16)mmol·L-1,and the differences were statistically significant(all P≤0.05).Conclusion Repeated administration of Qingre Xiaoyanning tablets showed no significant toxicity in SD rats.

Objective To study the factors influencing the blood concentration of caspofungin(CPFG),construct a prediction model,and validate the predictive effect of the model,so as to provide reference for the individualised dosing of patients with fungal infections in haematology.Methods Seventy-five patients admitted to the Department of Haematology,General Hospital of Tianjin Medical University,who were treated with CPFG for antifungal therapy during the period of March 2021 to June 2022 were selected as the study subjects,and CPFG blood concentration monitoring was carried out to explore the influencing factors of CPFG blood concentration and to construct a prediction model accordingly.Hosmer-Lemeshow(H-L)was used to test the goodness-of-fit of the model,and another 30 patients were selected as the verification group,and the predictive effect of the model was verified by the receiver's operating characteristics(ROC)curve.Results The mean blood concentrations of the patients at 0.5,9 and 24 h were(12.54±4.38),(6.80±2.76),(4.13±2.16)μg·mL-1,and the mean AUC0-24h were(152.05±57.60)μg·mL-1·h.AUC0-24h was lower than the reference value(98 μg·mL-1·h)in two patients.The results of correlation analysis showed that gender showed a correlation with 0.5 h blood concentration(P＜0.05),and there was no correlation with the rest of the two time points blood concentration and AUC0-24h(P＞0.05).Body weight and albumin(Alb)concentration showed correlation with 0.5,9,24 h blood drug concentration and AUC0-24 h(P＜0.05),and the rest of the indicators showed no correlation with blood drug concentration and AUC0_24h at each time point(P＞0.05).The results of multifactorial analysis showed that the factors influencing the patients'0.5 h blood concentration were gender,Alb concentration and body weight,and the factors influencing the 9 and 24 h blood concentration and AUC0-24h were Alb concentration and body weight(P＜0.05).Correlation analysis showed that the daily dose was positively correlated with the plasma concentration of CPFG at 0.5,9 and 24 h and AUC0-24h(P＜0.05).The results of multivariate analysis showed that the daily dose was also one of the influencing factors of the plasma concentration of CPFG(P＜0.05).ROC curve shows that the model has good prediction ability.Conclusion Body weight and Alb are significantly associated with CPFG blood concentrations and area under the drug-time curve,which can be used as a basis for preventive risk avoidance.

Ion concentration polarization (ICP) is an electrical transport phenomenon that occurs at the micro-nano interface under the action of an applied electric field, and the ICP phenomenon can be used to enrich charged particles with high efficiency. The microfluidic chip has the advantages of high precision, high efficiency, easy integration and miniaturization in biochemical analysis, which provides a new solution and technical way for biochemical analysis. In response to the demand for the detection of trace charged target analytes in sample solution, the advantages of high enrichment multiplicity, convenient operation and easy integration of ICP are utilized to provide an effective way for microfluidic biochemical detection. The combination of ICP phenomenon and microfluidic analysis technology has been widely used in the fields of pre-enrichment of charged particles, separation of targets, and detection of target analytes in biochemical analysis. In this paper, the principle of ICP and the microfluidic ICP chip are briefly introduced. Under the action of external electric field, the co-ions pass through the ion-selective nanochannel, the counterions are rejected at the boundary of nanochannel to form a depletion zone, and the charged samples will be enriched at the boundary of the depletion zone. Then the preparation techniques and methods of ICP chips are summarized. Among them, the design of microfluidic channel structure and the preparation and design of nanostructures are emphasized. The basic single-channel structure is analyzed, and the parallel-channel structure as well as the integrated multi-functional microfluidic ICP chip are sorted out and summarized. The preparation methods of nanostructures in ICP chips and their respective advantages and disadvantages are listed, and it is summarized that the current mainstream means are the embedding method and the self-assembly method, and attention is paid to the design of nanostructures preparation methods by both of them. In addition, this paper also discusses how to optimize the enrichment efficiency of ICP chip, through the introduction of multi-field coupling, valve control and other means to achieve the optimization of the enrichment efficiency of target substances. Meanwhile, this paper provides a classified overview of the progress of application of ICP chips in biochemical analysis and detection. ICP chips have been widely used in the research and development of biosensors, which can be used for the enrichment and separation of a variety of analytes including small molecules, nucleic acids, proteins, and cells, etc. By changing the design of microfluidic structures, integrating detection methods and modifying specific antibodies, ICP chips have shown great potential in the fields of rapid enrichment and pre-processing of targets, separation of targets and highly sensitive detection. Finally, it is pointed out that ICP chips are facing challenges in improving enrichment efficiency and selectivity, and solving the problems of fluid control, mixing and transport to match the biological properties of target assay, and that microfluidic ICP chips have been continuously promoting the development of ICP chips through the improvement of materials, chip design and integration of multifunctional units, opening up new possibilities in the field of biochemical analysis methods and applications. It can be seen that microfluidic ICP chips have the advantages of low sample flow rate, good separation and enrichment, high detection efficiency, and easy integration and miniaturization, which have shown good research significance and practical prospects in the field of biochemical detection.

Objective To construct a three-dimensional statistical shape model of the pelvis and analyze the individual variation and gender differences of the three-dimensional shape of the pelvis.Methods We collected CT data from 201 Chinese individuals and used deep learning to automatically reconstruct three-dimensional models of the pelvis.Through three-dimensional model registration,dense correspondence mesh mapping,and the use of statistical shape modelling(SSM)and principal component(PC)analysis method,we extracted models of variations(MoV)of pelvic shape changes and statistically compared the shape MoV between males and females.Results We analysed the top 10 principal components of shape variations,which accounted for 86.1％of the total variability.Among them,PC01,PC02,and PC04 showed significant differences between genders(P＜0.001),accounting for a total variability of 60.1％.PC08 and PC 10 demonstrated pelvic asymmetry,accounting for a total variability of 3.8％.Conclusion We constructed a three-dimensional statistical shape model of the pelvis in Chinese individuals,revealing the morphological variation and sex differences of Chinese pelvis.

Objective To explore the value of artificial intelligence federated learning system based on chest X-ray films for pathogen diagnosis of community-acquired pneumonia(CAP)in children.Methods Totally 900 cases of CAP children from 2 hospitals were retrospectively enrolled,including bacterial,viral and mycoplasma CAP(each n=300),and chest posteroanterior X-ray films were collected.Meanwhile,chest posteroanterior X-ray films of 5856 children from the publicly available dataset GWCMCx were collected,including 4273 CAP images and 1583 healthy chest images.All above 6756 images were divided into training set(n=5359)and validation set(n=1397)at the ratio of 8∶2.Then a pathogen diagnosis model of children CAP was established based on attention mechanism.Binary and ternary diagnostic algorithms were designed,and federated deployment training was performed.The efficacy of this system for pathogen diagnosis of children CAP was analyzed and compared with DenseNet model.Results Based on all data,the accuracy of the obtained artificial intelligence federated learning system model for diagnosing children CAP was 97.00%,with the area under the curve(AUC)of 0.990.Based on hospital data,the AUC of this system using single imaging data and clinical-imaging data for pathogen diagnosis of children CAP was 0.858 and 0.836,respectively,both better than that of DenseNet model(0.740,both P＜0.05).Conclusion The artificial intelligence federated learning system based on chest X-ray films could be used for pathogen diagnosis of children CAP.