ObjectiveThe exacerbating trend of global population aging poses profound socioeconomic and public health challenges, making the comprehensive elucidation of biological aging mechanisms and the discovery of effective anti-aging interventions an urgent priority in the life sciences. Based on our previous serum metabolomics findings that dimethylglycine, an intermediate metabolite of amino acid metabolism naturally present in the human body, was significantly enriched in the serum of longevity families, this study aimed to systematically investigate the anti-aging effects of dimethylglycine both in living organisms and in controlled laboratory environments, and to preliminarily elucidate its underlying molecular mechanisms. While existing literature indicates that dimethylglycine possesses antioxidant and immunomodulatory properties, its direct anti-aging efficacy and the specific molecular pathways through which it operates remain largely unexplored. MethodsTo comprehensively evaluate the anti-aging properties of dimethylglycine, we utilized replicative senescent human embryonic lung fibroblasts, specifically the WI-38 cell line, as an experimental model in a controlled laboratory environment. Cell viability and safety were thoroughly assessed using Cell Counting Kit-8 and lactate dehydrogenase release assays across various concentrations of dimethylglycine. The impact of dimethylglycine on cellular senescence phenotypes, oxidative stress, and proliferative capacity was evaluated via senescence-associated beta-galactosidase staining, reactive oxygen species fluorescence detection, and 5-ethynyl-2'-deoxyuridine incorporation assays. Furthermore, the molecular alterations of senescence-associated secretory phenotype factors and core senescence signaling pathways were quantified using quantitative reverse transcription polymerase chain reaction for the messenger RNA levels of interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1, and enzyme-linked immunosorbent assay for the measurement of p16 and p21 protein expression levels. For the living organism model, the wild-type nematode Caenorhabditis elegans was used to evaluate systemic physiological effects. We conducted a comprehensive lifespan analysis at 20°C, heat stress resistance survival assays at 35℃, senescence-associated beta-galactosidase staining, lipofuscin accumulation tracking, intracellular reactive oxygen species measurement, and Oil Red O staining to ascertain systemic lipid accumulation. Additionally, network pharmacology bioinformatics tools, including PharmMapper and STRING databases, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were utilized to predict target pathways, alongside highly detailed molecular docking simulations utilizing SwissDock and Protein-Ligand Interaction Profiler to examine interactions with the cytochrome P450 family 2 subfamily C member 9 protein. ResultsThe experimental outcomes robustly demonstrate the potent anti-aging capabilities of dimethylglycine. At the cellular level, toxicity analyses firmly confirmed that dimethylglycine is highly safe; continuous treatment with 50 mol/L and 70 mol/L of dimethylglycine for 5 d did not induce any cellular membrane damage or cytotoxicity, but rather actively promoted cellular proliferation. Utilizing the optimal standardized concentration of 50 mol/L, dimethylglycine treatment significantly ameliorated senescent phenotypic markers in human embryonic lung fibroblasts, which was evidenced by a drastic and highly significant reduction in the senescence-associated beta-galactosidase positive cell percentage (P<0.000 1) and intracellular reactive oxygen species levels (P<0.000 1), alongside a marked increase in the 5-ethynyl-2'-deoxyuridine-positive proliferation rate (P=0.003 5). On a molecular expression scale, dimethylglycine significantly downregulated the messenger RNA expression of multiple core senescence-associated secretory phenotype inflammatory factors, including interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1. Concurrently, it effectively suppressed the protein expression of critical cell cycle arrest markers, diminishing p16 protein levels by 57.3% (P=0.000 4) and p21 protein levels by 27.2% (P=0.000 7). In the nematode Caenorhabditis elegans animal model, dimethylglycine significantly extended the mean lifespan from 20.402 d to an impressive 23.066 d (P<0.000 1) and notably enhanced overall survival rates under severe heat stress environmental conditions (P=0.017). Furthermore, systemic dimethylglycine intervention significantly mitigated age-related physiological decline by decreasing bodily lipofuscin accumulation (P<0.000 1), significantly reducing senescence-associated beta-galactosidase activity, lowering systemic reactive oxygen species fluorescence (P=0.008), and effectively alleviating overall fat accumulation (P<0.000 1). Mechanistically, extensive network pharmacology and Kyoto Encyclopedia of Genes and Genomes analyses strongly revealed that the potential targets of dimethylglycine are significantly enriched in fundamental drug metabolism and oxidative stress response pathways. Precision molecular docking simulations conclusively demonstrated that dimethylglycine forms highly stable structural interactions with the cytochrome P450 family 2 subfamily C member 9 protein, specifically highlighting the definitive formation of 5 stable hydrogen bonds involving serine 365, leucine 366, and serine 429 residues, as well as two critical salt bridge formations with arginine 97 and histidine 368 residues. It is additionally predicted to interact favorably with glutathione S-transferase family proteins. ConclusionDimethylglycine exhibits a profoundly significant and multifaceted anti-aging activity at both the cellular and entire living animal levels. By powerfully alleviating oxidative stress, heavily suppressing the core p16 and p21-dependent cellular senescence signaling pathways, and substantially mitigating the detrimental senescence-associated secretory phenotype, dimethylglycine effectively delays fundamental cellular senescence processes and drastically extends whole-organism lifespan. The biological mechanisms driving these robust protective effects are highly likely closely associated with its direct stable interactions with crucial metabolic and detoxifying enzyme systems, such as cytochrome P450 family 2 subfamily C member 9 and glutathione S-transferase family proteins, thereby systemically improving metabolic dysregulation and restoring critical redox homeostasis. This comprehensive study provides highly solid experimental evidence supporting dimethylglycine as a highly potent and safe potential anti-aging intervention agent, while simultaneously offering a clear molecular mechanistic explanation for the previously documented high abundance of dimethylglycine observed within exceptionally long-lived human populations.

[Objective] To study the molecular biological mechanism for a case of ABO blood group B subtype, and perform three-dimensional modeling of the mutant enzyme. [Methods] The ABO phenotype was identified by the tube method and microcolumn gel method; the ABO gene of the proband was detected by sequence-specific primer polymerase chain reaction (PCR-SSP), and the exon 6 and 7 of the ABO gene were sequenced and analyzed. Homologous modeling of Bw.03 glycosyltransferase (GT) was carried out by Modeller and analyzed by PyMOL2.5.0 software. [Results] The weakening B antigen was detected in the proband sample by forward typing, and anti-B antibody was detected by reverse typing. PCR-SSP detection showed B, O gene, and the sequencing results showed c.721 C>T mutation in exon 7 of the B gene, resulting in p. Arg 241 Trp. Compared with the wild type, the structure of Bw.03GT was partially changed, and the intermolecular force analysis showed that the original three hydrogen bonds at 241 position disappeared. [Conclusion] Blood group molecular biology examination is helpful for the accurate identification of ambiguous blood group. Homologous modeling more intuitively shows the key site for the weakening of Bw.03 GT activity. The intermolecular force analysis can explain the root cause of enzyme activity weakening.

ObjectiveTo analyze the differences in color， odor and volatile components of Citri Reticulatae Pericarpium（CRP） before and after being stir-fried with Halloysitum Rubrum， and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the volatile components were analyzed by principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）. According to the principle of variable importance in the projection（VIP） value>1.5， volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose， the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum， of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected， including α-pinene， β-myrcene， linalool， sabinene， ocimene isomer mixture， A-ocimene， and δ-elemene. After being processed with Halloysitum Rubrum， the brightness value（L^*）， yellow-blue value（b^*） and total chromatic value（E^*_ab） of CRP were decreased（P<0.01）， and red-green value（a^*） was increased（P<0.01）， the response values of S4， S5， S10 and S13 sensors were significantly increased（P<0.05）， and the response values of S3 and S8 sensors were significantly decreased（P<0.05）. Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L^* and E^*_ab， but positively correlated with a^*. Sabinene was positively correlated with L^* and E^*_ab. Linalool was positively correlated with L^* and E^*_ab， and negatively correlated with a^*. The ocimene isomer mixture was positively correlated with the L^*. ConclusionAfter being processed with Halloysitum Rubrum， the appearance color， odor and volatile components of CRP change significantly， and α-pinene， β-myrcene， sabinene， linalool and A-ocimene are the characteristic volatile components before and after processing， which can provide references for the quality evaluation and clinical application of CRP and its processed products.

ObjectiveTo analyze the differences in color， odor and volatile components of Citri Reticulatae Pericarpium（CRP） before and after being stir-fried with Halloysitum Rubrum， and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the volatile components were analyzed by principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）. According to the principle of variable importance in the projection（VIP） value>1.5， volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose， the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum， of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected， including α-pinene， β-myrcene， linalool， sabinene， ocimene isomer mixture， A-ocimene， and δ-elemene. After being processed with Halloysitum Rubrum， the brightness value（L^*）， yellow-blue value（b^*） and total chromatic value（E^*_ab） of CRP were decreased（P<0.01）， and red-green value（a^*） was increased（P<0.01）， the response values of S4， S5， S10 and S13 sensors were significantly increased（P<0.05）， and the response values of S3 and S8 sensors were significantly decreased（P<0.05）. Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L^* and E^*_ab， but positively correlated with a^*. Sabinene was positively correlated with L^* and E^*_ab. Linalool was positively correlated with L^* and E^*_ab， and negatively correlated with a^*. The ocimene isomer mixture was positively correlated with the L^*. ConclusionAfter being processed with Halloysitum Rubrum， the appearance color， odor and volatile components of CRP change significantly， and α-pinene， β-myrcene， sabinene， linalool and A-ocimene are the characteristic volatile components before and after processing， which can provide references for the quality evaluation and clinical application of CRP and its processed products.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

BACKGROUND: Durvalumab after chemoradiotherapy (CRT) failed to bring survival benefits to patients with epidermal growth factor receptor ( EGFR ) mutations in PACIFIC study (evaluating durvalumab in patients with stage III, unresectable NSCLC who did not have disease progression after concurrent chemoradiotherapy). We aimed to explore whether locally advanced inoperable patients with EGFR mutations benefit from tyrosine kinase inhibitors (TKIs) and the optimal treatment regimen. METHODS: We searched the PubMed, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases from inception to December 31, 2022 and performed a meta-analysis based on a Bayesian framework, with progression-free survival (PFS) and overall survival (OS) as the primary endpoints. RESULTS: A total of 1156 patients were identified in 16 studies that included 6 treatment measures, including CRT, CRT followed by durvalumab (CRT-Durva), TKI monotherapy, radiotherapy combined with TKI (RT-TKI), CRT combined with TKI (CRT-TKI), and TKI combined with durvalumab (TKI-Durva). The PFS of patients treated with TKI-containing regimens was significantly longer than that of patients treated with TKI-free regimens (hazard ratio [HR] = 0.37, 95% confidence interval [CI], 0.20-0.66). The PFS of TKI monotherapy was significantly longer than that of CRT (HR = 0.66, 95% CI, 0.50-0.87) but shorter than RT-TKI (HR = 1.78, 95% CI, 1.17-2.67). Furthermore, the PFS of RT-TKI or CRT-TKI were both significantly longer than that of CRT or CRT-Durva. RT-TKI ranked first in the Bayesian ranking, with the longest OS (60.8 months, 95% CI = 37.2-84.3 months) and the longest PFS (21.5 months, 95% CI, 15.4-27.5 months) in integrated analysis. CONCLUSIONS: For unresectable stage III EGFR mutant NSCLC, RT and TKI are both essential. Based on the current evidence, RT-TKI brings a superior survival advantage, while CRT-TKI needs further estimation. Large randomized clinical trials are urgently needed to explore the appropriate application sequences of TKI, radiotherapy, and chemotherapy. REGISTRATION PROSPERO; https://www.crd.york.ac.uk/PROSPERO/ ; No. CRD42022298490.
Humans ; Carcinoma, Non-Small-Cell Lung/therapy* ; ErbB Receptors/genetics* ; Lung Neoplasms/drug therapy* ; Mutation/genetics* ; Protein Kinase Inhibitors/therapeutic use* ; Chemoradiotherapy ; Antibodies, Monoclonal/therapeutic use*

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVE To investigate the targeting effect of folic acid-modified crebanine nanoparticles （FA-Cre@PEG- PLGA NPs， hereinafter referred to as “NPs”） combined with ultrasound irradiation on M109 cells in vitro and in vivo after administration， and explore the anti-tumor mechanism. METHODS CCK-8 assay was used to detect the inhibitory effect of NPs combined with ultrasound irradiation on the proliferation of M109 cells， and the best ultrasound time was selected. Using human lung cancer A549 cells as a control， the targeting of NPs combined with ultrasound irradiation to M109 cells was evaluated by free folic acid blocking assay and cell uptake assay. The effects of NPs combined with ultrasound irradiation on the migration， invasion， apoptosis， cell cycle and reactive oxygen species （ROS） levels of M109 cells were detected by cell scratch test， Transwell chamber test and flow cytometry at 1 h after 958401536@qq.com administration； the changes of mitochondrial membrane potential （MMP） were observed by fluorescence inverted microscope. A mouse subcutaneous tumor model of M109 cells was constructed， and the in vivo tumor targeting of NPs combined with ultrasound irradiation was investigated by small animal in vivo imaging technology. RESULTS NPs combined with ultrasound irradiation could significantly inhibit the proliferation of M109 cells， and the optimal ultrasound time was 1 h after administration. The free folic acid could antagonize the inhibitory effect of NPs on the proliferation of M109 cells， and combined with ultrasound irradiation could partially reverse this antagonism. Compared with A549 cells， the uptake rate of NPs in M109 cells was significantly higher （P＜0.01）， and ultrasound irradiation could promote cellular uptake. NPs combined with ultrasound irradiation could inhibit the migration and invasion of M109 cells and block the cell cycle in the G0/G1 and G2/M phases. Compared with control group， the apoptosis rate of M109 cells and ROS level were increased significantly （P＜0.01）， while the MMP decreased significantly （P＜0.01） in the different concentration （100， 200， 300 μg/mL） groups of M109 cells. Compared with the mice in non-ultrasound group， the fluorescence intensity and tumor-targeting index of the tumor site in the 0 h ultrasound group were significantly enhanced （P＜0.05 or P＜0.01）. CONCLUSIONS NPs combined with ultrasound irradiation have a strong targeting effect on M109 cells in vitro and in vivo， the anti-tumor mechanism includes inhibiting cell migration and invasion， blocking cell cycle， and inducing apoptosis.

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.