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Abstract Lipoproteins and apolipoproteins are crucial in lipid metabolism, functioning as essential mediators in the transport of cholesterol and triglycerides and being closely related to the pathogenesis of multiple systems, including cardiovascular. Lipoproteins a (Lp(a)), as a unique subclass of lipoproteins, is a low-density lipoprotein(LDL)-like particle with pro-atherosclerotic and pro-inflammatory properties, displaying high heritability. More and more strong evidence points to a possible link between high amounts of Lp(a) and cardiac conditions like atherosclerotic cardiovascular disease (ASCVD) and aortic stenosis (AS), making it a risk factor for heart diseases. In recent years, Lp(a)'s role in other diseases, including neurological disorders and cancer, has been increasingly recognized. Although therapies aimed at low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) have achieved significant success, elevated Lp(a) levels remain a significant clinical management problem. Despite the limited efficacy of current lipid-lowering therapies, major clinical advances in new Lp(a)-lowering therapies have significantly advanced the field. This review, grounded in the pathophysiology of lipoproteins, seeks to summarize the wide-ranging connections between lipoproteins (such as LDL-C and HDL-C) and various diseases, alongside the latest clinical developments, special emphasis is placed on the pivotal role of Lp(a) in cardiovascular disease, while also examining its future potential and mechanisms in other conditions. Furthermore, this review discusses Lp(a)-lowering therapies and highlights significant recent advances in emerging treatments, advocates for further exploration into Lp(a)'s pathogenic mechanisms and its potential as a therapeutic target, proposing new secondary prevention strategies for high-risk individuals.

Abstract Ensuring equitable access to health services is crucial for public welfare and social equity, and is a key objective of the United Nations’ Sustainable Development Goals (SDGs). However, existing datasets often define hospital accessibility using travel time to hospitals in geographic dimension only, without considering the supply (hospital capacity) and demand (population distribution) dynamics. To overcome this limitation, we developed and validated a national-scale 1 km map of both hospital travel time and hospital accessibility in China. We used the Gaussian two-step floating catchment area (Ga2SFCA) model to calculate hospital accessibility, incorporating hospital capacity and service population. Various file types and statistical indicators are provided, making the dataset highly accessible for non-specialists. The dataset fills the gap in publicly available nationwide hospital accessibility data for China and can serve as a critical tool in optimizing resource allocation and developing targeted strategies to improve healthcare equity.

Abstract Background Modified furosemide responsiveness index (mFRI) is a novel biomarker for assessing diuretic response and AKI progression in patients with early AKI. However, the comparative predictive performance of mFRI and novel renal biomarkers for adverse renal outcomes remains unclear. In a single-center prospective study, we aimed to evaluate the discriminatory abilities of mFRI and other novel renal biomarkers in predicting AKI progression and prognosis in patients with initial mild and moderate AKI (KDIGO stage 1 to 2). Results Patients with initial mild and moderate AKI within 48 h following cardiac surgery were included in this study. The mFRI, renal biomarkers (including serum or urinary neutrophil gelatinase-associated lipocalin [sNGAL or uNGAL], serum cystatin C, urinary N-acetyl-beta-D-glycosaminidase [uNAG], urinary albumin-to-creatinine ratio) and cytokines (TNF, IL-1β, IL-2R, IL-6, IL-8, and IL-10) were measured at AKI diagnosis. The mFRI was calculated for each patient, which was defined as 2-hour urine output divided by furosemide dose and body weight. Of 1013 included patients, 154 (15.2%) experienced AKI progression, with 59 (5.8%) progressing to stage 3 and 33 (3.3%) meeting the composite outcome of hospital mortality or receipt of renal replacement therapy (RRT). The mFRI showed non-inferiority or potential superiority to renal biomarkers and cytokines in predicting AKI progression (area under the curve [AUC] 0.80, 95% confidence interval [CI] 0.77–0.82), progression to stage 3 (AUC 0.87, 95% CI 0.85–0.89), and composite outcome of death and receipt of RRT (AUC 0.85, 95% CI 0.82–0.87). Furthermore, the combination of a functional biomarker (mFRI) and a urinary injury biomarker (uNAG or uNGAL) resulted in a significant improvement in the prediction of adverse renal outcomes than either individual biomarker (all P

Background The incidence of falls among elderly inpatients with psychiatric disorders is on the rise. A lack of adequate physical activity and a sedentary lifestyle have become prevalent among hospitalized elderly patients. Balance training has been demonstrated to be efficacious in reducing the occurrence of falls, yet its application within psychiatric care remains limited. Objective To explore the effect of balance intensive training on balance ability of hospitalized elderly patients with schizophrenia. Methods Seventy-two elderly patients with schizophrenia from a tertiary psychiatric hospital in Jiangxi Province were selected as objects for this research in 2023. Participants were randomly assigned into experimental group (n=36) and control group (n=36). The control group received standard rehabilitation training, whereas the experimental group was provided with a balance-strengthening training program in addition to the standard regimen. The Berg Balance Scale (BBS), the Chinese version of the Barthel Index (BI), and the International Falls Effectiveness Scale (FES-I) were utilized to assess patients at baseline and after 4 and 12 weeks of intervention. Results A total of 62 patients completed the study, with 30 in the experimental group and 32 in the control group. Two-factor repeated measurement ANOVA showed that there was interaction between group and time on BBS and BI scores (P0.05), and time had significant effect on BBS and BI scores (P0.05). The main effects of time on the total score of FES-I and indoor and outdoor activity scores were significant (P

Abstract Background The optimal sedative regime for noninvasive ventilation (NIV) intolerance remains uncertain. The present study aimed to assess the efficacy and safety of remifentanil (REM) compared to dexmedetomidine (DEX) in cardiac surgery patients with moderate-to-severe intolerance to NIV. Methods In this multicenter, prospective, single-blind, randomized controlled study, adult cardiac surgery patients with moderate-to-severe intolerance to NIV were enrolled and randomly assigned to be treated with either REM or DEX for sedation. The status of NIV intolerance was evaluated using a four-point NIV intolerance score at different timepoints within a 72-h period. The primary outcome was the mitigation rate of NIV intolerance following sedation. Results A total of 179 patients were enrolled, with 89 assigned to the REM group and 90 to the DEX group. Baseline characteristics were comparable between the two groups, including NIV intolerance score [3, interquartile range (IQR) 3–3 vs. 3, IQR 3–4, p = 0.180]. The chi-squared test showed that mitigation rate, defined as the proportion of patients who were relieved from their initial intolerance status, was not significant at most timepoints, except for the 15-min timepoint (42% vs. 20%, p = 0.002). However, after considering the time factor, generalized estimating equations showed that the difference was statistically significant, and REM outperformed DEX (odds ratio = 3.31, 95% confidence interval: 1.35–8.12, p = 0.009). Adverse effects, which were not reported in the REM group, were encountered by nine patients in the DEX group, with three instances of bradycardia and six cases of severe hypotension. Secondary outcomes, including NIV failure (5.6% vs. 7.8%, p = 0.564), tracheostomy (1.12% vs. 0%, p = 0.313), ICU LOS (7.7 days, IQR 5.8–12 days vs. 7.0 days, IQR 5–10.6 days, p = 0.219), and in-hospital mortality (1.12% vs. 2.22%, p = 0.567), demonstrated comparability between the two groups. Conclusions In summary, our study demonstrated no significant difference between REM and DEX in the percentage of patients who achieved mitigation among cardiac surgery patients with moderate-to-severe NIV intolerance. However, after considering the time factor, REM was significantly superior to DEX. Trial registration ClinicalTrials.gov (NCT04734418), registered on January 22, 2021. URL of the trial registry record: https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S000AM4S&selectaction=Edit&uid=U00038YX&ts=3&cx=eqn1z0 .

Abstract. Background:. Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD. Methods:. In the training cohort, 60 AIIRD with PE cases and 180 age-, gender-, and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022. Univariable logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) were used to select the clinical features for further training with machine learning (ML) methods, including random forest (RF), support vector machines (SVM), neural network (NN), logistic regression (LR), gradient boosted decision tree (GBDT), classification and regression trees (CART), and C5.0 models. The performances of these models were subsequently validated using a multicenter validation cohort. Results:. In the training cohort, 24 and 13 clinical features were selected by univariable LR and LASSO strategies, respectively. The five ML models (RF, SVM, NN, LR, and GBDT) showed promising performances, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.962–1.000 in the training cohort and 0.969–0.999 in the validation cohort. CART and C5.0 models achieved AUCs of 0.850 and 0.932, respectively, in the training cohort. Using D-dimer as a pre-screening index, the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort. These results markedly outperformed the use of D-dimer levels alone. Conclusion:. ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE. Trial Registration:. Chictr.org.cn: ChiCTR2200059599.

Spatial synergy is strengthened integration and connection between cities in a mega-city region, transcending administrative boundaries. The central flow theory suggests that the mega-city regions are formed by the interconnected flows of people across cities, making the spatial synergy can be measured by assessing the aggregation and intensity of flows and interactions between cities and regions. Human mobility data, such as mobile phone data and social media check-ins, enable the tracking of human movements, thus facilitating the transition of central flow theory from theoretical constructs to empirical research. To this end, this study presents an alternative data-driven framework to reveal the multi-scale spatial synergy of mega-city regions from a human mobility perspective. It uncovers homogeneously spatial communities with high inter-city integration using community detection. Strong internal spatial connections of 2.13 billion mobility are filtered using network backbone extraction. An experiment in the Pearl River Delta (PRD), China, demonstrates a multi-scale and multi-core hierarchical spatial synergy in the PRD region. The detailed findings are as follows: (1) Three cities attract the majority of human mobility. Mobility distance is short in urban centers and long in suburban areas. (2) The spatial integration pattern shows the detected communities reveal the hierarchical integration pattern with three main integrated regions: Guangzhou-Foshan-Zhaoqing, Shenzhen-Dongguan-Huizhou, and Zhuhai-Zhongshan-Jiangmen. (3) The spatial connection pattern illustrates the close ties of 9 cities and three core cities, including Guangzhou, Shenzhen, and Foshan. These results provide a human-centric understanding of urban synergy and deeper insights into central flow theory, which supports cooperative development in mega-city regions.

Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population, infrastructure, and socioeconomic activities. Scaling laws are basic but effective rules for evaluating a city’s internal growth logic and assessing its efficiency by investigating whether urban indicators scale with population. To date, only limited research has empirically explored the scaling relations between variables of urban mobility in mega-cities at an intra-urban scale of a few meters. Using multiple urban-sensed and human-sensed data, this study proposes a thorough framework for quantifying the scaling laws in a city. To begin, urban mobility networks are built by aggregating population flows using large-scale mobile phone tracking data. To demonstrate the spatiotemporal variability of urban mobility, various network-based mobility measures are proposed. Following that, three different features of urban mobility laws are exposed, explaining spatial agglomeration, spatial hierarchical structures, and the temporal growth process. The scaling correlations between urban indicators pertaining to socioeconomic features and infrastructure and a mobility-population measure are then quantified using multi-sourced urban-sensed data. Applying this framework to the case study of Shenzhen, China revealed (a) spatial travel heterogeneity, hierarchical spatial structures, and mobility growth, and (b) not only a robust sub-linear relationship between infrastructure volume and population, but also a sub-linear relationship for socioeconomic activity. The identified scaling laws, both in terms of mobility measures and urban indicators, provide a multi-faceted portrait of the spatio-temporal variations of urban settings, allowing us to better understand intra-urban developments and, consequently, provide critical policy evaluations and suggestions for improving intra-urban efficiency in the future.

Urban functional zones (UFZs) serve as the spatial carriers embodying urban economic and social activities, thus making the accurate mapping of UFZs imperative for urban planning, management, and sustainable development. Traditional remote sensing-based methods for mapping UFZs primarily capture the physical attributes of ground objects (such as land cover and spatial patterns) while overlooking the inherent social and economic characteristics, as well as the comprehensiveness, heterogeneity, and scale-dependency. With the rapid development of intelligent sensors, the available geospatial big data, reflecting individual human activities, have greatly increased and enable users to analyze UFZs from both physical and socioeconomic aspects. In this study, we provide a comprehensive review of the existing literature on UFZ mapping using remote sensing and geospatial big data. Specifically, this study summarizes the state of the art from three perspectives: spatial analysis units, representation features derived from multi-source data, and the function classification methods of UFZs. Spatial analysis units encompass regular grids, road blocks, image segmentation units, traffic analysis zones, and buildings. Data features consist of the remote sensing image-derived features (such as visual, spatial pattern, and abstract features) and the geospatial big data-derived features (such as spatial, attribute, and temporal features). For function classification, kernel density estimation, cluster analysis, supervised machine learning, probabilistic topic models, and deep learning methods have been applied. Finally, this study discusses the challenges and limitations of UFZ mapping units, the bias issues of geospatial big data, and the integration of remote sensing and geospatial big data. Meanwhile, future opportunities to these issues and the expansion of functions from 2D to 3D are discussed, in order to formulate an enhanced UFZ mapping framework.

Abstract Background No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery. Methods In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score. Results The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P

Abstract Background Skin mottling is a common manifestation of peripheral tissue hypoperfusion, and its severity can be described using the skin mottling score (SMS). This study aims to evaluate the value of the SMS in detecting peripheral tissue hypoperfusion in critically ill patients following cardiac surgery. Methods Critically ill patients following cardiac surgery with risk factors for tissue hypoperfusion were enrolled (n = 373). Among these overall patients, we further defined a hypotension population (n = 178) and a shock population (n = 51). Hemodynamic and perfusion parameters were recorded. The primary outcome was peripheral hypoperfusion, defined as significant prolonged capillary refill time (CRT, > 3.0 s). The characteristics and hospital mortality of patients with and without skin mottling were compared. The area under receiver operating characteristic curves (AUROC) were used to assess the accuracy of SMS in detecting peripheral hypoperfusion. Besides, the relationships between SMS and conventional hemodynamic and perfusion parameters were investigated, and the factors most associated with the presence of skin mottling were identified. Results Of the 373-case overall population, 13 (3.5%) patients exhibited skin mottling, with SMS ranging from 1 to 5 (5, 1, 2, 2, and 3 cases, respectively). Patients with mottling had lower mean arterial pressure, higher vasopressor dose, less urine output (UO), higher CRT, lactate levels and hospital mortality (84.6% vs. 12.2%, p

Summary: Background: Dual inhibition of cytotoxic T-lymphocyte associated protein 4 (CTLA-4) and programmed death ligand 1 (PD-L1) has been shown to be an effective treatment strategy in many cancers. We sought to determine the objective response rate of combination durvalumab (D) plus tremelimumab (TM) in parallel cohorts of patients with carefully selected rare cancer types in which these agents had not previously been evaluated in phase II trials and for which there was clinical or biological rationale for dual immune checkpoint inhibitor therapy to be active. Methods: We designed a multi-centre, non-blinded, open-label phase II basket trial with each of the following 8 rare cancers considered a separate phase II trial: salivary carcinoma, carcinoma of unknown primary (CUP) with tumour infiltrating lymphocytes and/or expressing PD-L1, mucosal melanoma, acral melanoma, osteosarcoma, undifferentiated pleomorphic sarcoma, clear cell carcinoma of the ovary (CCCO) or squamous cell carcinoma of the anal canal (SCCA). The primary objective was to evaluate the response rate of the combination of D and TM, and the secondary objectives were to evaluate the tolerability and safety of D and TM combination. Eligible patients had advanced, metastatic or recurrent, or unresectable cancer with no known life-prolonging treatment option, age ≥16 years, ECOG performance status 0 or 1. Patients received D (1500 mg IV) + TM (75 mg IV) on Day 1 q4 weeks for 4 cycles followed by D q4 weeks until disease progression. This trial is registered with ClinicalTrials.gov, NCT02879162. Findings: From December 14th, 2016, to August 14, 2019, 140 patients enrolled into seven cohorts. The rare melanoma cohorts were closed due to lack of accrual. Of the 140 patients enrolled, 138 were eligible, 138 were evaluable for toxicity and 128 (91%) were evaluable for response. Durable responses were noted in all cohorts except for osteosarcoma. The overall response rate for eligible patients was 16% (95% CI: 10–23%). The response rates in each cancer cohort were undifferentiated pleomorphic sarcoma 15% (n = 3/20; 95% CI 3–38%), salivary carcinoma 20% (n = 4/20; 95% CI: 6–44%), CUP 17% (n = 3/18; 95% CI 4–41%), SCCA 10% (n = 2/20; 95% CI 12–32%) and CCCO 21% (n = 8/39; 95% CI 9–37%). Grade 3/4 adverse events were rare, where 4 patients experienced grade 4 related events and39 patients experienced grade 3 events. Interpretation: Durvalumab + tremelimumab treatment resulted in meaningful responses in salivary carcinoma and CCCO and deserves further exploration in front-line studies. Funding: AstraZeneca and Canadian Cancer Society.

Abstract After intracerebral hemorrhage (ICH) occurs, the overproduction of reactive oxygen species (ROS) and iron ion overload are the leading causes of secondary damage. Removing excess iron ions and ROS in the meningeal system can effectively alleviate the secondary damage after ICH. This study synthesized ginsenoside Rb1 carbon quantum dots (RBCQDs) using ginsenoside Rb1 and ethylenediamine via a hydrothermal method. RBCQDs exhibit potent capabilities in scavenging ABTS + free radicals and iron ions in solution. After intrathecal injection, the distribution of RBCQDs is predominantly localized in the subarachnoid space. RBCQDs can eliminate ROS and chelate iron ions within the meningeal system. Treatment with RBCQDs significantly improves blood flow in the meningeal system, effectively protecting dying neurons, improving neurological function, and providing a new therapeutic approach for the clinical treatment of ICH.

Abstract. Aging is a significant risk factor for various diseases, including asthma, and it often leads to poorer clinical outcomes, particularly in elderly individuals. It is recognized that age-related diseases are due to a time-dependent accumulation of cellular damage, resulting in a progressive decline in cellular and physiological functions and an increased susceptibility to chronic diseases. The effects of aging affect not only the elderly but also those of younger ages, posing significant challenges to global healthcare. Thus, understanding the molecular mechanisms associated with aging in different diseases is essential. One intriguing factor is the aryl hydrocarbon receptor (AhR), which serves as a cytoplasmic receptor and ligand-activated transcription factor and has been linked to the aging process. Here, we review the literature on several major hallmarks of aging, including mitochondrial dysfunction, cellular senescence, autophagy, mitophagy, epigenetic alterations, and microbiome disturbances. Moreover, we provide an overview of the impact of AhR on these hallmarks by mediating responses to environmental exposures, particularly in relation to the immune system. Furthermore, we explore how aging hallmarks affect clinical characteristics, inflammatory features, exacerbations, and the treatment of asthma. It is suggested that AhR signaling may potentially play a role in regulating asthma phenotypes in elderly populations as part of the aging process.

Nonalcoholic fatty liver disease (NAFLD) emerges as the most predominant cause of liver disease, tightly linked to metabolic dysfunction. Bile acids (BAs), initially synthesized from cholesterol in the liver, undergo further metabolism by gut bacteria. Increasingly acknowledged as critical modulators of metabolic processes, BAs have been implicated as important signaling molecules. In this review, we will focus on the mechanism of BAs signaling involved in glucose homeostasis, lipid metabolism, energy expenditure, and immune regulation and summarize their roles in the pathogenesis of NAFLD. Furthermore, gut microbiota dysbiosis plays a key role in the development of NAFLD, and the interactions between BAs and intestinal microbiota is elucidated. In addition, we also discuss potential therapeutic strategies for NAFLD, including drugs targeting BA receptors, modulation of intestinal microbiota, and metabolic surgery.

In order to evaluate the bone density improvement function and safety of the Malugu capsule, rats were divided into sham surgery group, model control group (oophorectomy model), high-dose calcium carbonate group (positive control), and groups with different doses of Malugu capsule (200, 400 and 1200 mg/kg·bw) by 90 days of gavage administration. The bone mineral density of the left femur and the calcium content of the right femur was measured to evaluate the performance of the Malugu capsule in increasing bone density. The acute toxicity test of the Malugu capsule at the dose of 15 g/kg·bw was carried out. Moreover, the genotoxicity test and 4-week feeding test of rats were also performed to evaluate the safety of the Malugu capsule. The results showed that there was no significant difference in body weight of rats among the groups of Malugu capsule treatment compared with the model control group (P>0.05). The bone mineral density of the left femur in the three doses of Malugu capsule groups were 0.6651, 0.6560 and 0.6605 g/cm3, respectively, which was significantly higher than that of 0.6307 g/cm3 (P

Myofibroblastic sarcoma (MS) is a malignant tumor of soft tissue or bone that can occur in children or adults, with a high rate of recurrence and metastasis. We report a case of low-grade malignant MS of the left shoulder, diagnosed based on pathological examination and immunohistochemical staining. However, the patient had unexplained pleural maculopathy. The patient passed away 6 months after the diagnosis of myofibroblast sarcoma due to multiple metastases throughout the sarcoma. Combined with the patient’s history, ancillary findings, and after MDT discussion, the patient was ultimately considered to have a high probability of myofibroblast sarcoma combined with pleural maculopathy. In conclusion, when a patient is diagnosed with myofibroblast sarcoma in combination with pleural macula, in the absence of other causative factors, a deep tissue biopsy of the pleura should be actively performed to confirm the diagnosis.

Abstract Triple‐positive breast cancer (TPBC) poorly responds to current standard neoadjuvant therapy (trastuzumab plus pertuzumab and chemotherapy). Our previous MUKDEN 01 study showed a promising total pathological complete response (tpCR) rate of 30.4% with neoadjuvant pyrotinib (pan‐human epidermal growth factor receptor tyrosine kinase inhibitor) plus dalpiciclib (cyclin‐dependent kinase 4/6 inhibitor) and letrozole, but the efficacy remains suboptimal. This pilot study (NCT05228951) explored adding trastuzumab to this triplet neoadjuvant regimen in patients with stage II–III TPBC. The primary endpoint was tpCR (ypT0/is, ypN0) rate. Between February 2022 and June 2022, 12 patients were enrolled, and seven (58%; 95% confidence interval [CI], 27.7%–84.8%) patients achieved tpCR. The rate of residual cancer burden (RCB) 0–I was 75% (95% CI, 46.8%–91.1%). The objective response rate (ORR) was 92% (95% CI, 64.6%–98.5%). Mean Ki‐67 level was significantly reduced from 45.0% (95% CI, 19.5%–70.5%) at baseline to 17.2% (95% CI, 0.7%–33.7%) after neoadjuvant therapy (p = 0.03). The most common grade 3 adverse events were diarrhea (four [33%]) and decreased neutrophil count (three [25%]). No grade 4 adverse events or treatment‐related deaths occurred. This four‐drug neoadjuvant regimen shows promising pathological response with an acceptable safety profile in patients with TPBC. A randomized controlled trial (NCT05638594) of this regimen is being conducted.

N1-methyladenosine (m1A) modification is a crucial post-transcriptional regulatory mechanism of messenger RNA (mRNA) in living organisms. Few studies have focused on analysis of m1A regulators in lower-grade gliomas (LGG). We employed the Nonnegative Matrix Factorization (NMF) technique on The Cancer Genome Atlas (TCGA) dataset to categorize LGG patients into 2 groups. These groups exhibited substantial disparities in terms of both overall survival (OS) and levels of infiltrating immune cells. We collected the significantly differentially expressed immune-related genes between the 2 clusters, and performed LASSO regression analysis to obtain m1AScores, and established an m1A-related immune-related gene signature (m1A-RIGS). Next, we categorized all patients with LGG into high- and low-risk subgroups, predictive significance of m1AScore was confirmed by conducting univariate/multivariate Cox regression analyses. Additionally, we confirmed variations in immune-related cells and ssGSEA and among the high-/low-risk subcategories in the TCGA dataset. Finally, our study characterized the effects of MSR1 and BIRC5 on LGG cells utilizing Edu assay and flow cytometry to explore the effects of modulation of these genes on glioma. The results of this study suggested that m1A-RIGS may be an excellent prognostic indicator for patients with LGG, and could also promote development of novel immune-based treatment strategies for LGG. Additionally, BIRC5 and MSR1 may be potential therapeutic targets for LGG.