This study explored the potential therapeutic targets and mechanisms of Danggui Shaoyao San(DSS) in the prevention and treatment of Alzheimer's disease(AD) through transcriptomics and metabolomics, combined with animal experiments. Fifty male C57BL/6J mice, aged seven weeks, were randomly divided into the following five groups: control, model, positive drug, low-dose DSS, and high-dose DSS groups. After the intervention, the Morris water maze was used to assess learning and memory abilities of mice, and Nissl staining and hematoxylin-eosin(HE) staining were performed to observe pathological changes in the hippocampal tissue. Transcriptomics and metabolomics were employed to sequence brain tissue and identify differential metabolites, analyzing key genes and metabolites related to disease progression. Reverse transcription-quantitative polymerase chain reaction(RT-qPCR) was employed to validate the expression of key genes. The Morris water maze results indicated that DSS significantly improved learning and cognitive function in scopolamine(SCOP)-induced model mice, with the high-dose DSS group showing the best results. Pathological staining showed that DSS effectively reduced hippocampal neuronal damage, increased Nissl body numbers, and reduced nuclear pyknosis and neuronal loss. Transcriptomics identified seven key genes, including neurexin 1(Nrxn1) and sodium voltage-gated channel α subunit 1(Scn1a), and metabolomics revealed 113 differential metabolites, all of which were closely associated with synaptic function, oxidative stress, and metabolic regulation. RT-qPCR experiments confirmed that the expression of these seven key genes was consistent with the transcriptomics results. This study suggests that DSS significantly improves learning and memory in SCOP model mice and alleviates hippocampal neuronal pathological damage. The mechanisms likely involve the modulation of synaptic function, reduction of oxidative stress, and metabolic balance, with these seven key genes serving as important targets for DSS in the treatment of AD.
Animals ; Alzheimer Disease/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Mice, Inbred C57BL ; Metabolomics ; Transcriptome/drug effects* ; Maze Learning/drug effects* ; Hippocampus/metabolism* ; Humans ; Disease Models, Animal ; Memory/drug effects*

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

Objective To investigate the application effect of cold snare endoscopic mucosal resection(CS-EMR)in the treatment of 6 to 9 mm colorectal small polyps.Methods A total of 82 patients with small colonic polyps in our hospital from March 2022 to August 2023 were collected and divided into the observation group(45 cases received CS-EMR)and the control group[37 cases received hot snare endoscopic mucosal resection(HS-EMR)]according to different surgical methods.The clinical efficacy,polyp resection status,complete polyp resection rate,perioperative indicators and occurrence of complications were compared between the two groups.Results Follow-up for 1 month after operation,the effective rate of treatment in the observation group was higher than that in the control group(P<0.05).There was no statistically significant difference in the polyp resection status or perioperative indicators between the two groups(P>0.05).There was no statistically significant difference in the complete polyp resection rates of patients with different pathological types or total complete resection rate between the two groups(P>0.05).The incidence of delayed bleeding and endoscopic hemostasis rate in the observation group were lower than those in the control group(P<0.05).Conclusion The complete resection rate of 6～9 mm colorectal polyps through CS-EMR was comparable to that of HS-EMR,and CS-EMR has a better efficacy and lower risk of perioperative bleeding,along with higher safety.

Objective:To investigate the clinical features and prognostic factors of primary tonsil lymphoma(PTL).Methods:The clinical data of 41 patients diagnosed with PTL and treated in the Affiliated Hospital of Xuzhou Medical University from January 2015 to December 2022 were collected and retrospectively analyzed.Their clinical features and prognostic factors were analyzed.Results:All the 41 patients were newly diagnosed with PTL,and the median age of onset was 58(19-85)years.Among them,19 patients started with pharyngeal pain,12 patients presented with dysphagia,8 patients presented with pharyngeal mass,and 2 patients presented with blurred articulation.The most common pathological type was diffuse large B-cell lymphoma(24 cases,58.54％).All patients received chemotherapy,and 3 patients were combined with hematopoietic stem cell transplantation.Among 41 patients,11(26.83％)achieved complete response,14(34.15％)achieved partial response,and the total response rate was 60.98％(25/41).The median follow-up time was 37(6-107)months,the 5-year overall survival(OS)rate was 70.81％and 5-year progression-free survival(PFS)rate was 66.20％.Univariate analysis showed that B symptoms,Ki-67,β2-MG and IPI score had significant effects on PFS and OS of patients(all P＜0.05).Multivariate analysis showed that IPI score was an independent risk factor for PFS and OS of patients(P＜0.05).Conclusion:The clinical manifestations of PTL lack specificity,and the prognosis is relatively good.Most patients can achieve long-term survival after treatment.IPI score is related to the prognosis.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

With the increasing demand for dynamic,real-time and rapid qualitative analysis of chemical composition in areas such as emergency response and space exploration,chip-scale mass spectrometers have attracted significant attention.These devices are expected to drive the integration of mass spectrometry with micro/nano-fabrication and intelligent sensing technologies,fostering profound innovation and breakthroughs in analytical chemistry.As an excellent mass analyzer,the ion trap exhibits numerous advantages,and its miniaturization creates favorable conditions for the high-density integration of miniature mass spectrometers.However,the reduction in ion storage capacity may compromise its sensitivity and dynamic range,rendering the study of ion unidirectional ejection in highly miniaturized ion traps of significant practical importance.In this work,a research was conducted on achieving efficient ion unidirectional ejection while maintaining high mass resolution in the extremely miniature hyperbolic linear ion trap(M-HLIT)with a field radius of 1 mm,and an electric field compensation method was proposed,which combined asymmetric electrode stretching and unbalanced RF voltage to achieve high-precision optimization of the electric field composition.Simulations showed that in an ideal structure,this method achieved 100％unidirectional ejection efficiency with the mass resolution of 518,significantly outperforming traditional asymmetric structure method(365)and unbalanced voltage method(321).Following the introduction of ion ejection slots,further optimization through bidirectional stretching and electrical parameters improved the resolution to 790 while maintaining a unidirectional ejection efficiency of 93％.This method eliminated the requirement for additional excitation voltage,offering an ideal solution for the miniature mass analyzer with high detection performance of chip-level mass spectrometers.

Objective Performing physical tasks in the low-pressure environment of space poses a significant physiological challenge for astronauts.This study investigates the localized thermophysiological effects of typical physical tasks on different body segments and analyzes the mechanisms by which low-pressure environments influence human task performance.The findings aim to provide a theoretical basis for the thermal control design of spacesuits,focusing on both localized thermoregulation and overall task performance.Methods Two typical physical tasks—15 kg weighted walking and 25 kg load-carrying—were conducted in a simulated low-pressure composite environment chamber.The chamber was set to an altitude-equivalent pressure of 57 kPa(4500 m),with a temperature of 26℃and humidity of 40％.Six non-acclimatized adult male participants were recruited.After environmental stabilization,12-point skin temperatures were recorded throughout the tasks,and localized temperature data were statistically analyzed.Results Under low-pressure conditions,different body regions exhibited distinct thermal responses over time depending on the task type,while the same body region showed varied responses under different task conditions.During walking,temperatures in the primary active regions(thighs and calves)decreased,with most other body regions(except the pelvis and feet)gradually cooling as the task progressed.In contrast,during load-carrying,temperatures in the primary active regions(back and upper arm muscles)increased significantly.Conclusion Astronauts performing different tasks in low-pressure environments experience distinct localized thermophysiological effects.Therefore,spacesuit thermal control systems should not only account for task intensity and metabolic differences but also adapt localized heating/cooling based on task-specific thermal profiles.This approach enables targeted intelligent thermal regulation,enhancing operational support in specific mission scenarios.