Penicillin Allergy in China: Consequences of Inappropriate Skin Testing Practices and Policies.

Penicillins are the most frequently prescribed class of medications worldwide and first-line antibiotic of choice for most bacterial infections. They are also commonly labelled as the culprit of drug 'allergy'; leading to obligatory use of second-line antibiotics, suboptimal antibiotic therapy and increased antimicrobial resistance. However, the majority of reported penicillin 'allergy' labels are found to be incorrect after allergy testing, emphasising the importance of proper drug allergy testing and evaluation. Penicillin skin testing (PST) remains an important component of drug allergy diagnosis; however, its practice and policies significantly differ across the world. Inappropriate and non-evidence-based PST practices can lead to consequences associated with allergy mislabelling. Even within different regions of China, with a population exceeding 1.4 billion, there are marked differences in the implementation, execution and interpretation of PST. This review aims to examine the differences in PST between Mainland China, Hong Kong and the rest of the world. We critically analyse the current practice of 'pre-emptive' PST in Mainland China, which has a significant false-positive rate leading to high levels of penicillin allergy mislabelling. Non-evidence-based practices further compound the high false-positive rates of indiscriminatory PST. We postulate that inappropriate PST policies and practices may exacerbate the mislabelling of penicillin allergy, leading to unnecessary overuse of inappropriate second-line antibiotics, increasing antimicrobial resistance and healthcare costs. We advocate for the importance of more collaborative research to improve the contemporary workflow of penicillin allergy diagnosis, reduce mislabelling and promote the dissemination of evidence-based methods for allergy diagnosis.

Predictive model for CAR-T cell therapy success in patients with relapsed/refractory B-cell acute lymphoblastic leukaemia.

Chimeric antigen receptor T-cell (CAR-T) therapy has demonstrated remarkable efficacy in treating relapsed/refractory acute B-cell lymphoblastic leukaemia (R/R B-ALL). However, a subset of patients does not benefit from CAR-T therapy. Our study aims to identify predictive indicators and establish a model to evaluate the feasibility of CAR-T therapy. Fifty-five R/R B-ALL patients and 22 healthy donors were enrolled. Peripheral blood lymphocyte subsets were analysed using flow cytometry. Sensitivity, specificity, accuracy, positive and negative predictive values and receiver operating characteristic (ROC) areas under the curve (AUC) were determined to evaluate the predictive values of the indicators. We identified B lymphocyte, regulatory T cell (Treg) and peripheral blood minimal residual leukaemia cells (B-MRD) as indicators for predicting the success of CAR-T cell preparation with AUC 0.936, 0.857 and 0.914. Furthermore, a model based on CD3+ T count, CD4+ T/CD8+ T ratio, Treg and extramedullary diseases (EMD) was used to predict the response to CAR-T therapy with AUC of 0.938. Notably, a model based on CD4+ T/CD8+ T ratio, B, Treg and EMD were used in predicting the success of CAR-T therapy with AUC 0.966 [0.908-1.000], with specificity (92.59%) and sensitivity (91.67%). In the validated group, the predictive model predicted the success of CAR-T therapy with specificity (90.91%) and sensitivity (100%). We have identified several predictive indicators for CAR-T cell therapy success and a model has demonstrated robust predictive capacity for the success of CAR-T therapy. These results show great potential for guiding informed clinical decisions in the field of CAR-T cell therapy.

Kinetic nitrogen isotope effects of 18 amino acids degradation during burning processes.

Understanding the nitrogen isotopic variations of individual amino acids (AAs) is essential for utilizing the nitrogen isotope values of individual amino acids (δ15N-AA) as source indicators to identify proteinaceous matter originating from biomass combustion processes. However, the nitrogen isotope effects (ε) associated with the degradation of individual amino acids during combustion processes have not been previously explored. In this study, we measured the nitrogen isotope values of residual free amino acids -following a series of controlled combustion experiments at temperatures of 160-240 °C and durations of 2 min to 8 h, as described in Part 1. δ15N values of proline, aspartate, alanine, valine, glycine, leucine, and isoleucine are more positive than their initial δ15N values after prolonged combustion. Variations in δ15N values of the most AAs conform to the Rayleigh fractionation during combustion and their nitrogen isotope effects (ε) are greatly impacted by their respective combustion degradation pathways. This is the first time the ε values associated with the degradation pathways of AAs during combustion have been characterized. Only the ε values associated with Pathway 1 (dehydration to form dipeptide) and 2 (simultaneous deamination and decarboxylation) are found to be significant and temperature-dependent, ranging from + 2.9 to 6.4‰ and + 0.9‰ to + 3.8‰, respectively. Conversely, ε values associated with other pathways are minor. This improves the current understanding on the degradation mechanisms of protein nitrogen during biomass burning.

Lysosome-Targeted and pH-Activatable Phototheranostics for NIR-II Fluorescence Imaging-Guided Nasopharyngeal Carcinoma Phototherapy.

Currently, clinical therapeutic strategies for nasopharyngeal carcinoma (NPC) confront insurmountable dilemmas in which surgical resection is incomplete and chemotherapy/radiotherapy has significant side effects. Phototherapy offers a maneuverable, effective, and noninvasive pattern for NPC therapy. Herein, we developed a lysosome-targeted and pH-responsive nanophototheranostic for near-infrared II (NIR-II) fluorescence imaging-guided photodynamic therapy (PDT) and photothermal therapy (PTT) of NPC. A lysosome-targeted S-D-A-D-S-type NIR-II phototheranostic molecule (IRFEM) is encapsulated within the acid-sensitive amphiphilic DSPE-Hyd-PEG2k to form IRFEM@DHP nanoparticles (NPs). The prepared IRFEM@DHP exhibits a good accumulation in the acidic lysosomes for facilitating the release of IRFEM, which could disrupt lysosomal function by generating an amount of heat and ROS under laser irradiation. Moreover, the guidelines of NIR-II fluorescence enhance the accuracy of PTT/PDT for NPC and avoid damage to normal tissues. Remarkably, IRFEM@DHP enable efficient antitumor effects both in vitro and in vivo, opening up a new avenue for precise NPC theranostics.

The effect of illness perception on psychosocial adjustment of patients with breast cancer and their spouses: actor-partner independence model.

OBJECTIVE: With the increase in the prevalence rate and improvements in the survival of breast cancer patients, there is a growing interest in understanding the level of psychosocial adjustment in these patients. The study aimed to describe the illness perception and psychosocial adjustment levels of both breast cancer patients and their spouses, to use the Actor-Partner Interdependence Model (APIM) to clarify the actor-partner relationships between spouses, and to explore the impact of illness perception on psychosocial adjustment to the disease within the joint actions of both spouses. METHODS: A total of 216 female patients with breast cancer and their spouses participated in the study. They were selected from two tertiary hospitals in Guangdong Province, China from October 2022 to May 2023 using a convenience sampling method. The participants were assessed using the Brief Illness Perception Questionnaire and the Psychosocial Adjustment to Illness Scale to examine the relationship between illness perception and psychosocial adjustment. AMOS24.0 was used to test and analyze the actor-partner interdependence model. RESULTS: The illness perception score (57.75 ± 10.91) was slightly higher than that of the spouse (57.10 ± 11.00), and the psychosocial adjustment score (64.67 ± 6.33) was slightly lower than that of the spouse (64.76 ± 7.49). The results of the actor-partner interdependence model indicated that there was a couple partner between breast cancer patients and their spouses: the spouse's illness perception significantly affected the patient's psychosocial adjustment (ß = 0.095, p = 0.015); the patient's illness perception also significantly affected the spouse's psychosocial adjustment (ß = 0.106, p = 0.033). Among them, the patient's psychosocial adjustment was found to be related to the patient's illness comprehensibility or coherence of illness (ß = 0.433, p = 0.009), the spouse's emotional illness representation (ß = 0.218, p = 0.037), and the spouse's illness comprehensibility or coherence of illness (ß = 0.416, p = 0.007), while the spouse's psychosocial adjustment was only related to the spouse's illness comprehensibility or coherence of illness (ß = 0.528, p = 0.007). CONCLUSIONS: The psychosocial adjustment of breast cancer patients is affected by both their own and spouse's illness perception. Therefore, in the future, the healthcare staff can implement early psychological interventions for patients diagnosed with breast cancer and their spouses as a unit to promote the psychosocial adjustment of them.

Identification and validation of lipid metabolism-related key genes as novel biomarkers in acute myocardial infarction and pan-cancer analysis.

BACKGROUND: Acute myocardial infarction (AMI) is associated with high morbidity and mortality, and is associated with abnormal lipid metabolism. We identified lipid metabolism related genes as biomarkers of AMI, and explored their mechanisms of action. METHODS: Microarray datasets were downloaded from the GEO database and lipid metabolism related genes were obtained from Molecular Signatures Database. WGCNA was performed to identify key genes. We evaluated differential expression and performed ROC and ELISA analyses. We also explored the mechanism of AMI mediated by key genes using gene enrichment analysis. Finally, immune infiltration and pan-cancer analyses were performed for the identified key genes. RESULTS: TRL2, S100A9, and HCK were identified as key genes related to lipid metabolism in AMI. Internal and external validation (including ELISA) showed that these were good biomarkers of AMI. In addition, the results of gene enrichment analysis showed that the key genes were enriched in inflammatory response, immune system process, and tumor-related pathways. Finally, the results of immune infiltration showed that key genes were concentrated in neutrophils and macrophages, and pan-cancer analysis showed that the key genes were highly expressed in most tumors and were associated with poor prognosis. CONCLUSIONS: TLR2, S100A9, and HCK were identified as lipid metabolism related novel diagnostic biomarkers of AMI. In addition, AMI and tumors may be related through the inflammatory immune response.

Comparison of systematic and combined biopsy for the detection of prostate cancer.

ABSTRACT: Systematic prostate biopsy has limitations, such as overdiagnosis of clinically insignificant prostate cancer and underdiagnosis of clinically significant prostate cancer. Magnetic resonance imaging (MRI)-guided biopsy, a promising alternative, might improve diagnostic accuracy. To compare the cancer detection rates of systematic biopsy and combined biopsy (systematic biopsy plus MRI-targeted biopsy) in Asian men, we conducted a retrospective cohort study of men who underwent either systematic biopsy or combined biopsy at two medical centers (Queen Mary Hospital and Tung Wah Hospital, Hong Kong, China) from July 2015 to December 2022. Descriptive statistics were calculated, and univariate and multivariate logistic regression analyses were performed. The primary and secondary outcomes were prostate cancer and clinically significant prostate cancer. A total of 1391 participants were enrolled. The overall prostate cancer detection rates did not significantly differ between the two groups (36.3% vs 36.6%, odds ratio [OR] = 1.01, 95% confidence interval [CI]: 0.81-1.26, P = 0.92). However, combined biopsy showed a significant advantage in detecting clinically significant prostate cancer (Gleason score ≥ 3+4) in patients with a total serum prostate-specific antigen (tPSA) concentration of 2-10 ng ml-1 (systematic vs combined: 11.9% vs 17.5%, OR = 1.58, 95% CI: 1.08-2.31, P = 0.02). Specifically, in the transperineal biopsy subgroup, combined biopsy significantly outperformed systematic biopsy in the detection of clinically significant prostate cancer (systematic vs combined: 12.6% vs 24.0%, OR = 2.19, 95% CI: 1.21-3.97, P = 0.01). These findings suggest that in patients with a tPSA concentration of 2-10 ng ml-1, MRI-targeted biopsy may be of greater predictive value than systematic biopsy in the detection of clinically significant prostate cancer.

Arginine and its metabolites stimulate proliferation, differentiation, and physiological function of porcine trophoblast cells through ß-catenin and mTOR pathways.

Arginine, which is metabolized into ornithine, proline, and nitric oxide, plays an important role in embryonic development. The present study was conducted to investigate the molecular mechanism of arginine in proliferation, differentiation, and physiological function of porcine trophoblast cells (pTr2) through metabolic pathways. The results showed that arginine significantly increased cell viability (P < 0.05). The addition of arginine had a quadratic tendency to increase the content of progesterone (P = 0.06) and protein synthesis rate (P = 0.03), in which the maximum protein synthesis rate was observed at 0.4 mM arginine. Arginine quadratically increased (P < 0.05) the intracellular contents of spermine, spermidine and putrescine, as well as linearly increased (P < 0.05) the intracellular content of NO in a dose-dependent manner. Arginine showed a quadratic tendency to increase the content of putrescine (P = 0.07) and a linear tendency to increase NO content (P = 0.09) in cell supernatant. Moreover, increasing arginine activated (P < 0.05) the mRNA expressions for ARG, ODC, iNOS and PCNA. Furthermore, inhibitors of arginine metabolism (L-NMMA and DFMO) both inhibited cell proliferation, while addition of its metabolites (NO and putrescine) promoted the cell proliferation and cell cycle, the mRNA expressions of PCNA, EGF and IGF-1, and increased (P < 0.05) cellular protein synthesis rate, as well as estradiol and hCG secretion (P < 0.05). In conclusion, our results suggested that arginine could promote cell proliferation and physiological function by regulating the metabolic pathway. Further studies showed that arginine and its metabolites modulate cell function mainly through ß-catenin and mTOR pathways.

Strategic control of combustion-induced ammonia emissions: A key initiative for substantial PM2.5 reduction in Tianjin, North China Plain.

Information on the temporal and spatial variations in the sources of ammonium salts (NH4+), a crucial alkaline component in PM2.5, is limited. Here, we simultaneously collected PM2.5 and gaseous ammonia (NH3) samples in both summer and winter from two sites in Tianjin: an urban site (Tianjin University, TJU) and a suburban site (Binhai New-region, BH). NH3 concentrations, the contents of major water-soluble inorganic ions in PM2.5, and the compositions of ammonium­nitrogen isotopes (δ15N-NH4+) were measured. As a result, (NH4)2SO4 and NH4NO3 were the predominant forms of NH4+ in PM2.5 during summer and winter, respectively. However, the NH4NO3 concentrations were notably greater at TJU (6.2 ± 7.3 µg m-3) than at BH (3.8 ± 4.7 µg m-3) in summer, with no regional differences observed in winter. Both sites displayed almost half the contribution of c-NH3 (combustion-related NH3) to NH4+, differing from the finding of previous isotope-based studies. This discrepancy could be attributed to the combined effects of NHx isotope fractionation and seasonal δ15N value variations in NH3 sources. The contribution fractions of v-NH3 (volatile NH3) and c-NH3 exhibited similar patterns at both sites seasonally, probably caused by coal combustion for heating in winter and temperature fluctuations. However, the contribution fraction of c-NH3 was lower at BH than at TJU in summer but greater in winter than at TJU. In summer, NH4NO3 was unstable and limited its delivery to TJU from BH, and the high contribution of c-NH3 to NH4+ at TJU could be attributed to local vehicle emissions. In winter, the stable particulate NH4NO3 that formed from the c-NH3 in the upwind area could be transported to the downwind area, increasing the NH4+ concentration at BH. Our study provides valuable insights for devising emission mitigation strategies to alleviate the increasing burden of NH3 in the local atmosphere.

Analysis of the fatigue status of medical security personnel during the closed-loop period using multiple machine learning methods: a case study of the Beijing 2022 Olympic Winter Games.

Using machine learning methods to analyze the fatigue status of medical security personnel and the factors influencing fatigue (such as BMI, gender, and wearing protective clothing working hours), with the goal of identifying the key factors contributing to fatigue. By validating the predicted outcomes, actionable and practical recommendations can be offered to enhance fatigue status, such as reducing wearing protective clothing working hours. A questionnaire was designed to assess the fatigue status of medical security personnel during the closed-loop period, aiming to capture information on fatigue experienced during work and disease recovery. The collected data was then preprocessed and used to determine the structural parameters for each machine learning algorithm. To evaluate the prediction performance of different models, the mean relative error (MRE) and goodness of fit (R2) between the true and predicted values were calculated. Furthermore, the importance rankings of various parameters in relation to fatigue status were determined using the RF feature importance analysis method. The fatigue status of medical security personnel during the closed-loop period was analyzed using multiple machine learning methods. The prediction performance of these methods was ranked from highest to lowest as follows: Gradient Boosting Regression (GBM) > Random Forest (RF) > Adaptive Boosting (AdaBoost) > K-Nearest Neighbors (KNN) > Support Vector Regression (SVR). Among these algorithms, four out of the five achieved good prediction results, with the GBM method performing the best. The five most critical parameters influencing fatigue status were identified as working hours in protective clothing, a customized symptom and disease score (CSDS), physical exercise, body mass index (BMI), and age, all of which had importance scores exceeding 0.06. Notably, working hours in protective clothing obtained the highest importance score of 0.54, making it the most critical factor impacting fatigue status. Fatigue is a prevalent and pressing issue among medical security personnel operating in closed-loop environments. In our investigation, we observed that the GBM method exhibited superior predictive performance in determining the fatigue status of medical security personnel during the closed-loop period, surpassing other machine learning techniques. Notably, our analysis identified several critical factors influencing the fatigue status of medical security personnel, including the duration of working hours in protective clothing, CSDS, and engagement in physical exercise. These findings shed light on the multifaceted nature of fatigue among healthcare workers and emphasize the importance of considering various contributing factors. To effectively alleviate fatigue, prudent management of working hours for security personnel, along with minimizing the duration of wearing protective clothing, proves to be promising strategies. Furthermore, promoting regular physical exercise among medical security personnel can significantly impact fatigue reduction. Additionally, the exploration of medication interventions and the adoption of innovative protective clothing options present potential avenues for mitigating fatigue. The insights derived from this study offer valuable guidance to management personnel involved in organizing large-scale events, enabling them to make informed decisions and implement targeted interventions to address fatigue among medical security personnel. In our upcoming research, we will further expand the fatigue dataset while considering higher precisionprediction algorithms, such as XGBoost model, ensemble model, etc., and explore their potential contributions to our research.

MOF-Derived CeO2 Nanorod as a Separator Coating Enabling Enhanced Performance for Lithium-Sulfur Batteries.

The deployment of Li-S batteries in the commercial sector faces obstacles due to their low electrical conductivity, slow redox reactions, quick fading of capacity, and reduced coulombic efficiency. These issues stem from the "shuttle effect" associated with lithium polysulfides (LiPSs). In this work, a haystack-like CeO2 derived from a cerium-based metal-organic framework (Ce-MOF) is obtained for the modification of a polypropylene separator. The carbon framework and CeO2 coexist in this haystack-like structure and contribute to a synergistic effect on the restriction of LiPSs shuttling. The carbon network enhances electron transfer in the conversion of LiPSs, improving the rate performance of the battery. Moreover, CeO2 enhances the redox kinetics of LiPSs, effectively reducing the "shuttle effect" in Li-S batteries. The Li-S battery with the optimized CeO2 modified separator shows an initial discharge capacity of 870.7 mAh/g at 2 C, maintaining excellent capacity over 500 cycles. This research offers insights into designing functional separators to mitigate the "shuttle effect" in Li-S batteries.

Multi-organ developmental toxicity and its characteristics in fetal mice induced by dexamethasone at different doses, stages, and courses during pregnancy.

Dexamethasone is widely used in pregnant women at risk of preterm birth to reduce the occurrence of neonatal respiratory distress syndrome and subsequently reduce neonatal mortality. Studies have suggested that dexamethasone has developmental toxicity, but there is a notable absence of systematic investigations about its characteristics. In this study, we examined the effects of prenatal dexamethasone exposure (PDE) on mother/fetal mice at different doses (0.2, 0.4, or 0.8 mg/kg b.i.d), stages (gestational day 14-15 or 16-17) and courses (single- or double-course) based on the clinical practice. Results showed that PDE increased intrauterine growth retardation rate, and disordered the serum glucose, lipid and cholesterol metabolic phenotypes, and sex hormone level of mother/fetal mice. PDE was further discovered to interfere with the development of fetal lung, hippocampus and bone, inhibits steroid synthesis in adrenal and testis, and promotes steroid synthesis in the ovary and lipid synthesis in the liver, with significant effects observed at high dose, early stage and double course. The order of severity might be: ovary > lung > hippocampus/bone > others. Correlation analysis revealed that the decreased serum corticosterone and insulin-like growth factor 1 (IGF1) levels were closely related to PDE-induced low birth weight and abnormal multi-organ development in offspring. In conclusion, this study systematically confirmed PDE-induced multi-organ developmental toxicity, elucidated its characteristics, and proposed the potential "glucocorticoid (GC)-IGF1" axis programming mechanism. This research provided an experimental foundation for a comprehensive understanding of the effect and characteristics of dexamethasone on fetal multi-organ development, thereby guiding the application of "precision medicine" during pregnancy.

Maternal resveratrol improves the intestinal health and weight gain of suckling piglets during high summer temperatures: The involvement of exosome-derived microRNAs and immunoglobin in colostrum.

Previous studies have shown that maternal resveratrol improved growth performance and altered the microbial composition of suckling piglets under hot summer conditions. However, it remains unclear how maternal resveratrol improves growth performance of suckling piglets during high summer temperatures. A total of 20 sows (Landrace × Large White; three parity) were randomly assigned to 2 groups (with or without 300 mg/kg resveratrol) from d 75 of gestation to d 21 of lactation during high ambient temperatures (from 27 to 30 °C). The results showed that maternal resveratrol supplementation increased total daily weight gain of piglets under hot summer conditions, which is consistent with previous studies. Furthermore, we found that maternal resveratrol improved the intestinal morphology and intestinal epithelial proliferation in suckling piglets. Dietary resveratrol supplementation affected the characteristics of exosome-derived microRNAs (miRNAs) in sow colostrum, as well as the genes targeted by differentially produced miRNAs. MiRNAs are concentrated in the tight junction pathway. As a result, the expression of intestinal tight junction proteins was increased in suckling piglets (P < 0.05). Notably, maternal resveratrol increased the intestinal secretory immunoglobulin A (sIgA) levels of suckling piglets via colostrum immunoglobin (P < 0.05), which could increase the abundance of beneficial microbiota to further increase the concentration of short chain fatty acids (SCFA) in suckling piglets' intestine (P < 0.05). Finally, our correlation analysis further demonstrated the positive associations between significantly differential intestinal microbiota, intestinal sIgA production and SCFA concentrations, as well as the positive relation between total daily weight gain and intestinal health of suckling piglets. Taken together, our findings suggested that maternal resveratrol could promote intestinal health to improve piglet growth during high summer temperatures, which might be associated with the immunoglobin and exosome-derived miRNAs in sows' colostrum.

A degressive quantum convolutional neural network for quantum state classification and code recognition.

With the rapid development of quantum computing, a variety of quantum convolutional neural networks (QCNNs) are proposed. However, only 1/2n2 features of an n-qubits input are transferred to the next layer in a quantum pooling layer, which results in the accuracy reduction. To solve this problem, a QCNN with a degressive circuit is proposed. In order to enhance the ability of extracting global features, we remove the parameters sharing strategy in the quantum convolutional layer and design a quantum convolutional kernel with global eyesight. In addition, to prevent a sharp feature reduction, a degressive parameterized quantum circuit is adopted to construct the pooling layer. Then the Z-basis measurement is only performed on the first qubit to control the operations on other qubits. Compared with the state-of-the-art QCNN, i.e., hybrid quantum-classical convolutional neural network, the accuracy of our model increased by 0.9%, 1%, and 3%, respectively, in three tasks: quantum state classification, binary code recognition, and quaternary code recognition.

Increased monocytic myeloid-derived suppressor cells in type 2 diabetes correlate with hyperglycemic and was a risk factor of infection and tumor occurrence.

To investigate the frequency of monocytic myeloid-derived suppressor cells (M-MDSCs) in type 2 diabetes mellitus (T2DM) patients and explore the potential associations between M-MDSCs, glycemic control, and the occurrence of infections and tumor. 102 healthy and 77 T2DM individuals were enrolled. We assessed the M-MDSCs frequency, levels of fasting plasma glucose (FPG), haemoglobin A1c (HbA1c), and other relevant indicators. Each patient underwent a follow-up of at least 6 months after M-MDSCs detection. The M-MDSCs frequency was significantly higher in patients with poor glycemic control (PGC) compared to the healthy population (P < 0.001), whereas there was no significant difference between patients with good glycemic control and the healthy (P > 0.05). There was a positive correlation between the M-MDSCs frequency and FPG, HbA1c (R = 0.517 and 0.315, P < 0.001, respectively). T2DM patients with abnormally increased M-MDSCs have a higher incidence of infection and tumor (48.57% and 11.43% respectively). Our results shed new light on the pathogenesis of T2DM, help to understand why T2DM patients are susceptible to infection and tumor and providing novel insights for future prevention and treatment of T2DM.

Treatment with glatiramer acetate in APPswe/PS1dE9 mice at an early stage of Alzheimer's disease prior to amyloid-beta deposition delays the disease's pathological development and ameliorates cognitive decline.

Background: Alzheimer's disease (AD) is characterized by neuroinflammation, which is frequently accompanied by immune system dysfunction. Although the mechanism of neurodegenerative lesions is unclear, various clinical trials have highlighted that early intervention in AD is crucial to the success of treatment. In order to explore the potential of immunotherapy in the early period of AD, the present study evaluated whether application of glatiramer acetate (GA), an immunomodulatory agent approved for remitting-relapsing multiple sclerosis (RRMS), in the early stages of AD prior to amyloid beta (Aß) deposition altered the Aß pathology and cognitive impairments in APPswe/PSEN1dE9 (APP/PS1) transgenic mice. Methods: We treated two cohorts of pre-depositing and amyloid-depositing (2- and 6-month-old) APP/PS1 mice with weekly-GA subcutaneous injection over a 12-week period. We then tested spatial learning and memory using the Morris water maze (MWM) and the Y maze. Immunohistochemistry staining was utilized to analyze Aß burden in the brain as well as activated microglia. Furthermore, the inflammatory cytokine milieu within brains was estimated by quantitative real-time polymerase chain reaction, and the peripheral CD4+CD25+Foxp3+ regulatory T cells (Tregs) in the spleen were measured by flow cytometry. Results: We found that early GA administration reduced Aß burden and ameliorated cognitive decline. Meanwhile, the immune microenvironment had changed in the brain, with an increase in the production of anti-inflammatory cytokines and a decrease in microglial activation. Interestingly, early GA administration also modulated the peripheral immune system through the amplification of Tregs in the spleen. Conclusion: Overall, our findings revealed that GA treatment might enhance the central and peripheral immune systems' protective capabilities in the early stages of AD, eventually improving cognitive deficits. Our research supports the advantages of immunomodulatory treatments for AD at an early stage.