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.

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.

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.

OBJECTIVES: To investigate the clinical features and prognosis of children with non-Down-syndrome-related acute megakaryoblastic leukemia (non-DS-AMKL). METHODS: A retrospective analysis was conducted on the medical data of 17 children with non-DS-AMKL who were admitted to Children's Hospital of The First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023, and their clinical features, treatment, and prognosis were summarized. RESULTS: Among the 17 children with non-DS-AMKL, there were 8 boys and 9 girls. Fourteen patients had an onset age of less than 36 months, with a median age of 21 months (range:13-145 months). Immunophenotyping results showed that 16 children were positive for CD61 and 13 were positive for CD41. The karyotype analysis was performed on 16 children, with normal karyotype in 6 children and abnormal karyotype in 9 children, among whom 5 had complex karyotype and 1 had no mitotic figure. Detected fusion genes included EVI1, NUP98-KDM5A, KDM5A-MIS18BP1, C22orf34-BRD1, WT1, and MLL-AF9. Genetic alterations included TET2, D7S486 deletion (suggesting 7q-), CSF1R deletion, and PIM1. All 17 children received chemotherapy, among whom 16 (94%) achieved complete remission after one course of induction therapy, and 1 child underwent hematopoietic stem cell transplantation (HSCT) and remained alive and disease-free. Of all children, 7 experienced recurrence, among whom 1 child received HSCT and died of graft-versus-host disease. At the last follow-up, six patients remained alive and disease-free. CONCLUSIONS Non-DS-AMKL primarily occurs in children between 1 and 3 years of age. The patients with this disorder have a high incidence rate of chromosomal abnormalities, with complex karyotypes in most patients. Some patients harbor fusion genes or gene mutations. Although the initial remission rate is high, the long-term survival rate remains low.
Humans ; Male ; Female ; Leukemia, Megakaryoblastic, Acute/etiology* ; Child, Preschool ; Infant ; Child ; Retrospective Studies ; Prognosis ; Down Syndrome/complications*

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

Liver transplantation (LT) has become a standard treatment for end-stage liver diseases, and graft injury is intricately associated with poor prognosis. Granzyme B (GZMB) plays a vital role in natural killer (NK) cell biology, but whether NK-derived GZMB affects graft injury remains elusive. Through the analysis of single-cell RNA-sequencing data obtained from human LT grafts and the isolation of lymphocytes from mouse livers following ischemia-reperfusion injury (IRI), we demonstrated that 2NK cells with high expression of GZMB are enriched in patients and mice. Both systemically and liver-targeted depletion of NK cells led to a notable reduction in GZMB⁺ cell infiltration, subsequently resulting in diminished graft injury. Notably, the reconstitution of Il2rg ^-/- Rag2 ^-/- mice with purified Gzmb-KO NK cells demonstrated superior outcomes compared to those with wild-type NK cells. Crucially, global knockout of GZMB and pharmacological inhibition exhibited remarkable improvements in liver function in both mouse IRI and rat LT models. Moreover, a phosphorylated derivative of FDA-approved vidarabine was identified as an effective inhibitor of mouse GZMB activity by molecular dynamics, which could provide a potential avenue for therapeutic intervention. Therefore, targeting NK cell-derived GZMB during the LT process suggests potential therapeutic strategies to improve post-transplant outcomes.

OBJECTIVES: To investigate the impact of high expression of transmembrane and coiled helix structural domain 1 (TMCO1) on prognosis of gastric cancer and the possible mechanisms. METHODS: TMCO1 expression in gastric cancer and its effect on gastric cancer progression and prognosis were analyzed using publicly available databases and clinical data of patients undergoing radical surgery in our hospital, and its possible biological functions were explored using KEGG and GO analyses. In gastric cancer HGC-27 cells, the effects of lentivirus-mediated TMCO1 overexpression and TMCO1 silencing on cell apoptosis, proliferation, invasion and migration were examined. RESULTS: TMCO1 expression was significantly elevated in gastric cancer tissues (P<0.05), and its high expression was positively correlated with cancer progression (P<0.001) and a lowered postoperative 5-year survival rate of the patients (P<0.05). Bioinformatic analyses suggested that TMCO1 may affect gastric cancer cell apoptosis via Wnt signaling. In HGC-27 cells, TMCO1 overexpression significantly promoted tumor cell proliferation, inhibited cell apoptosis, and enhanced cell migration and invasion, whereas TMCO1 silencing produced the opposite effects. Western blotting showed that β-catenin levels were significantly upregulated in TMCO1-overexpressing cells and downregulated in cells with TMCO1 silencing. CONCLUSIONS TMCO1 is overexpressed in gastric cancer tissues, and its high expression promotes gastric cancer progression and affects long-term prognosis of the patients possibly by activating the Wnt/ β-catenin signaling pathway to inhibit apoptosis of gastric cancer cells.
Humans ; Stomach Neoplasms/metabolism* ; Apoptosis ; Prognosis ; Cell Line, Tumor ; Cell Proliferation ; Cell Movement ; Wnt Signaling Pathway ; beta Catenin/metabolism* ; Gene Expression Regulation, Neoplastic

OBJECTIVES: To investigate YEATS2 expression in gastric cancer (GC), its prognostic value, and its regulatory role in epithelial-mesenchymal transition (EMT) of GC cells. METHODS: YEATS2 expression in GC was analyzed using publicly available databases. Paired GC and adjacent tissues were collected from 100 patients undergoing radical surgery for immunohistochemical detection of YEATS2 expression, and its correlations with the patients' clinicopathological parameters and Ki67 expression were analyzed. The prognostic value of YEATS2 was assessed using Kaplan-Meier analysis, Cox regression and ROC curves, and its regulatory mechanisms were analyzed using KEGG enrichment analysis. In cultured GC cell lines (HGC-27 and AGS), the effect of YEATS2 knockdown and overexpression on migration, invasion and EMT of the cells were examined with scratching assay, Transwell assay and Western blotting. RESULTS: YEATS2 was significantly overexpressed in GC tissues with a positive correlation with Ki67 (P<0.05). High YEATS2 expression was associated with elevated CEA (≥5 μg/L), CA19-9 (≥37 kU/L), T3-4 stage, and N2-3 stage (all P<0.05). Patients with high YEATS2 expression had significantly reduced 5-year survival (P<0.001); ROC analysis showed that YEATS2 expression levels had a sensitivity of 80.00% and a specificity of 66.67% for predicting patient survival (P<0.05). Cox regression identified high YEATS2 as an independent risk factor for poor postoperative 5-year survival outcome of GC patients (HR: 1.675, 95%CI: 1.013-2.771; P=0.045). KEGG enrichment analysis suggested involvement of YEATS2 in EMT in GC and Wnt/β-catenin signaling. In cultured GC cells, YEATS2 overexpression significantly promoted cell migration and invasion, upregulated the expressions of vimentin, N-cadherin, Wnt and active β-catenin, and downregulated E-cadherin expression, and these changes were obviously suppressed by treatment with XAV-939 (a Wnt/β-catenin inhibitor). CONCLUSIONS High YEATS2 expression activates Wnt/β-catenin signaling to promote EMT in GC and is correlated with poor prognosis of GC patients.
Humans ; Stomach Neoplasms/pathology* ; Epithelial-Mesenchymal Transition ; Wnt Signaling Pathway ; Cell Line, Tumor ; Prognosis ; Cell Movement ; Male ; Female ; beta Catenin/metabolism*