Objective To explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). Methods The Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. Gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients’ 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. Results Differentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. Conclusion The prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.

Objective: To develop a RHCE genotyping assay based on kompetitive allele-specific PCR (KASP) and assess its clinical accuracy for RhCE blood group determination. Methods: KASP primers were designed to interrogate three RHCE loci: the 109 bp insertion/deletion in intron 2, c. 307T>C, and c. 676C>G. A total of 1 194 RhD-positive inpatients from Chengdu were typed by both KASP genotyping and manual tube serology. Discordant samples (n=10) were retested by both methods and further resolved by Sanger sequencing. An additional 377 cases were tested for the c. 48C>G locus to evaluate the predictive accuracy of individual loci and combined locus testing for RhC antigen. Results: Genotyping concordance with serology was 100.0% for both the c. 676C>G locus (RhE/Rhe) and the c. 307T>C locus (Rhc). For RhC prediction using the 109 bp insertion, overall accuracy was 99.7% (1 191/1 194); the 3 discordant cases were confirmed by Sanger sequencing to be false negatives attributable to 109 bp deletion in intron 2. Testing the c. 48C>G allele for RhC prediction yielded 7 false positives, with an accuracy of 98.1% (370/377). RhC antigen status was determined by combining the 109 bp insertion and the c. 48C allele. After excluding 10 samples with inconsistent results between the two loci, the accuracy reached 100% in the remaining 367 samples. When both loci were applied in combination, accuracy reached 100% in the 367 cases with concordant results. Among the 1 194 patients, CCee (45.8%) and CcEe (31.7%) were the most common RhCE phenotypes. The e antigen had the highest positivity rate (92.2%), and the Ce haplotype was the most frequent (66.9%). Conclusion: The KASP-based RHCE genotyping method achieves high accuracy for clinical RhCE typing. Combining the 109 bp insertion/deletion with the c. 48C allele significantly improves RhC antigen prediction compared with either locus alone. This method was applied to RhCE genotyping of 1 194 RhD-positive inpatients in Chengdu, providing local RhCE phenotype and haplotype distribution data to support RhCE-matched transfusion practice.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Objective: To investigate the epidemiological characteristics of human brucellosis in Jiande City, Zhejiang Province from 2005 to 2024, so as to provide the evidence for strengthening the prevention and control of brucellosis. Methods: Data on brucellosis cases and surveillance in Jiande City from 2005 to 2024 were collected through the Chinese Disease Prevention and Control Information System, the annual brucellosis surveillance reports from the Jiande Center for Disease Control and Prevention, and the annual summaries of brucellosis prevention and control efforts. The epidemiological characteristics of human brucellosis were analyzed using a descriptive epidemiological method. Results: A total of 1 125 individuals were monitored in Jiande City from 2005 to 2024, with 18 seropositive cases identified and the seropositivity rate of 1.60%. The average annual seropositivity rate from 2015 to 2024 was 3.35%, which was significantly higher than that of 0.57% from 2005 to 2014 (P<0.05). There were 10 confirmed brucellosis cases and 8 asymptomatic infections, with no reported deaths. The peak incidence occurred between March and August. Among the 16 towns (streets) in Jiande City, 8 reported brucellosis cases. Of the brucellosis cases, 14 were male and 4 were female, with a male-to-female ratio of 3.5∶1. The majority of cases (13 cases) were aged between 40 and 60 years. Occupational exposure was identified in 16 cases, all of whom were infected through direct hand contact with the excreta, secretions, or animal products of infected sheep or cattle. The primary source of infection was sheep, followed by cattle. Five strains of Brucella were isolated and cultured, all identified as Brucella melitensis biovar 3. Conclusions The brucellosis epidemic in Jiande City remained at a sporadic and low prevalence level from 2005 to 2024, with an increasing trend observed from 2015 to 2024. Male occupational groups aged 40 to 60 years were the key population for brucellosis prevention and control, and sheep were the primary source of infection.

In recent years, due to the development of radiotherapy technology and nuclear energy, people have paid more and more attention to the various effects of ionizing radiation on organisms. Ionizing radiation can induce protein, DNA and other biological macromolecules to damage, resulting in apoptosis, senescence, cancer and a series of changes. For a long time, it has been believed that the main target of ionizing radiation damage is DNA in the nucleus. However, it has been reported in recent years that ionizing radiation has both direct and indirect effects, and the theory of ROS damage in the indirect effects believes that ionizing radiation has target uncertainty, so it is not comprehensive enough to evaluate only the DNA damage in the nucleus. It has been reported that ionizing radiation can cause damage to organelles as well as damage to cells. Mitochondria are important damaged organelles because mitochondria occupy as much as 30% of the entire cell volume in the cytoplasm, which contains DNA and related enzymes that are closely related to cellular ATP synthesis, aerobic respiration and other life activities. What is more noteworthy is that mitochondria are the only organelles in which DNA exists in the human body, which makes researchers pay attention to various damage to mitochondrial DNA caused by ionizing radiation (such as double-strand breaks, base mismatching, and fragment loss). Although these damages also occur in the nucleus, mitochondrial DNA is more severely damaged than nuclear DNA due to its lack of histone protection, so mitochondria are important targets of ionizing radiation damage in addition to the nucleus. Mitochondrial DNA is not protected by histones and has little repair ability. When exposed to ionizing radiation, common deletions occur at an increased frequency and are passed on to offspring. For large-scale mitochondrial DNA damage, mitochondria indirectly compensate for the amount of damaged DNA by increasing the number of DNA copies and maintaining the normal function of mitochondrial DNA. Mitochondria are in a state of oxidative stress after exposure to ionizing radiation, and this oxidative stress will promote the change in mitochondrial function. When mitochondria are damaged, the activity of proteins related to aerobic respiration decreases, and oxidative respiration is inhibited to a certain extent. At the same time, a large amount of active superoxide anions are continuously produced to stimulate mitochondrial oxidative stress, and the signal of such damage is transmitted to the surrounding mitochondria, resulting in a cascade of damage reaction, which further activates the signalling pathway between mitochondria and nucleus. The cell nucleus is also in a state of oxidative stress, and finally, the level of free radicals is high, causing secondary damage to the genetic material DNA of mitochondria and nucleus. In this paper, the damage effects of ionizing radiation on mitochondria are reviewed, to provide a new idea for radiation protection.

BACKGROUND:Ossification of the ligamentum flavum was previously considered to be rare in the population.As research has progressed,its incidence rate is increasing gradually,which has aroused the interest of a large number of researchers. OBJECTIVE:To visualize and analyze the research results on ossification of the ligamentum flavum from the Web of Science Core Collection since 1999 using bibliometric methods,and to review the research history of ossification of the ligamentum flavum,highlighting important literature,summarizing research hotspots,and providing ideas for researchers to find research directions. METHODS:Using the Web of Science Core Collection as the data source,relevant papers on ossification of the ligamentum flavum were searched and screened.VOSviewer 1.6.19 and CiteSpace 6.2.R6 were used to conduct the visual analysis of annual publication volume,research countries,institutions,citations,journals,authors,and keywords. RESULTS AND CONCLUSION:(1)A total of 347 papers were included.Since 1999,the number of published papers has increased in a spiral pattern.China's research started later than Japan's,but the number of publications has come up later,with Peking University being the institution with the most publications,and Prof.Chen Zhongqiang from Peking University being the scholar with the most publications.(2)Five of the 10 most frequently cited publications were related to the surgical treatment of the disease.(3)Excluding keywords directly related to the research topic and synthetically analyzing frequencies and betweenness centralities of key words,terms such as"thoracic myelopathy,""dural ossification,""minimally invasive surgery,"and"ossification of the posterior longitudinal ligament"occupied a central position in this field.(4)Keywords clustering analysis showed that clinical manifestations and surgical treatment of ossification of the ligamentum flavum accounted for a large proportion of study.(5)The timeline and burst analysis of keywords revealed that"minimally invasive surgery"appeared as a keyword around 2015,with the highest burst strength and the latest burst start time,and began to receive extensive attention from researchers in 2019.The burst of the keyword"dural ossification"has not yet ended.(6)Surgical treatment for ossification of the ligamentum flavum has been at the forefront of research.Development and research of minimally invasive surgery and research on dural ossification secondary to ossification of the ligamentum flavum are both current research hotspots and possible future research trends.

ObjectiveTo explore the effect of a novel initiation model on initiating behavioral requests in children with autism spectrum disorder (ASD). MethodsFrom November to December, 2022, 44 children with ASD were selected from Jiaxing Sunlight Rehabilitation Kindergarten, and divided into prelinguistic group (n = 23) and linguistic group (n = 21) according to the language function. The initiation-requested skills, and types and frequency of initiation-requested behaviors were observed under the novel initiation model and the conventional initiation model. ResultsBoth the groups scored higher in the novel initiation model than in the conventional initiation model for initiation-requested skills (|t| > 2.794, P < 0.05) and types of initiation-requested behaviors (|t| > 3.697, P < 0.01), and it increased for the frequency of the use of two- and three-behavioral initiation of requests (χ² > 7.986, P < 0.05). ConclusionThe novel initiation model can improve initiation request skills in children with ASD.

OBJECTIVE To explore the effects of meropenem exposure and degradation levels on clinical efficacy in patients with purulent meningitis （PM）. METHODS A total of 131 PM patients treated with meropenem at the Affiliated Suzhou Hospital of Nanjing Medical University from January 2022 to June 2025 were prospectively included. Relevant data were collected and divided into a cured group （91 cases） and a non-cured group （40 cases） based on the efficacy. High-performance liquid chromatography-tandem mass spectrometry was used to determine the concentration of meropenem and its open-loop metabolites. Risk factors that affect efficacy were screened， and their predictive power and correlation were evaluated by univariate analysis， and multivariate Logistic regression analysis， receiver operating characteristic （ROC） curves， and correlation analysis. RESULTS Univariate analysis showed that serum creatinine， creatinine clearance rate， minimum inhibitory concentration of meropenem ≥16 μg/mL， cerebrospinal fluid red blood cell count， cerebrospinal fluid white blood cell count， cerebrospinal fluid glucose content， blood trough concentration， blood open-loop metabolite concentration/trough concentration ratio， and intrathecal injection were all correlated with efficacy （P＜0.05）. The results of multiple Logistic regression analysis showed that serum creatinine blood open-loop metabolite concentration/trough concentration ratio， intrathecal injection， and cerebrospinal fluid glucose content were influencing factors for suboptimal anti-infective ltt efficacy （P＜0.05）. ROC curve analysis showed that when the blood open-loop metabolite concentration/trough concentration ratio was greater than 2.854 （AUC＝0.647）， serum creatinine was less than 59.5 μmol/L （AUC＝0.647）， and cerebrospinal fluid glucose content was less than 3.37 mmol/L （AUC＝0.709）， the risk of treatment failure significantly increased （P＜0.05）. Correlation analysis showed that the blood trough concentration of meropenem was positively correlated with the concentration of its open-loop metabolites （R 2＝0.134 5， P＜0.000 1）. CONCLUSIONS Insufficient exposure level and rapid degradation of meropenem are key mechanisms affecting the anti-infective efficacy of PM. Elevated blood open-loop metabolite concentration/ trough concentration ratio， low serum creatinine level， lack of intrathecal injection， and low cerebrospinal fluid glucose content are independent risk factors for poor efficacy.

Sarin(GB)is a typical representative of nerve agents with high toxicity,and very low amount can cause death.GB can cause water and atmospheric environment poisoning,so the detection of GB in water and air is of great significance.In this work,a colorimetric sensor array(CSA)based on GB inhibition of cholinesterase activity was constructed to detect GB with high selectivity.A 4×4 colorimetric array was constructed using acetylcholinesterase(AChE),butyryl cholinesterase(BuChE)and the corresponding substrate acetylthiocholine iodide(S-ACh),butyryl thiocholine iodide(S-BCh),acetylcholine chloride(ACh),butyryl choline chloride(BCh)and 2,6-dichloroindophenol ethyl ester(DCIE).The linear curve of the sensor was Y=131.3×lgC+271.6(R2=0.997),where Y was the array response Euclidean distance,C was the concentration of GB(mg/L),the linear range was 0.03?0.32 mg/L,and the detection limit was 27.6 μg/L.The method could effectively distinguish chemical warfare agents(CWA)such as VX,Soman(GD),mustard gas(HD),Louie reagent(L),and had high anti-interference ability,sensitivity and good repeatability.It was successfully applied to the detection of GB in simulated water and simulated air samples,and the sample recovery rate was 97.2% ?100.9%.This method would be potentially applied to the field rapid detection of nerve agents.

In the past, aortic dissection, aortic aneurysm, and other aortic diseases, primarily rely on surgical intervention. In recent years, due to breakthroughs in materials science, endovascular therapy has become the first choice for the surgical treatment of most aortic diseases. However, traditional endovascular repair cannot fully meet the clinical needs for certain complex lesions involving the aortic arch and the originations of visceral arteries. The emergence of physician-modified stent technology has brought new hope for the treatment of complex aortic diseases. This article provides a detailed introduction to the concept, development, technical characteristics, and applications of physician-modified stents in the treatment of aortic diseases, analyzing their advantages and limitations. Physician-modified stents serve as a powerful complement to traditional endovascular interventions and commercial branched stents, yet further research and refinement are still required.