Elderly patients with lung cancer have a significantly increased risk of perioperative cardiopulmonary complications due to physiological decline, high incidence of complications and reduced surgical tolerance, which directly affects postoperative recovery and long-term survival. Although the concepts of minimally invasive surgery and enhanced recovery after surgery have improved clinical outcomes, early recognition and intervention of postoperative complications in elderly patients remains a significant challenge in the field of thoracic surgery. By integrating recent literature and clinical practice, this paper systematically analyzes the pathophysiological mechanism and risk factors of perioperative cardiopulmonary complications in elderly patients with lung cancer, and discusses individualized intervention strategies based on risk stratification and multidisciplinary team, in order to provide theoretical basis and practical guidance for optimizing perioperative management and improving postoperative prognosis in elderly patients.

Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Background Long-term exposure to ambient fine particulate matter (PM_2.5) is a significant risk factor for cardiometabolic disorders. However, the mechanisms of its interaction with the endogenous circadian system remain incompletely understood. Objective To investigate whether chronic PM_2.5 exposure interferes with the rhythmic expression of the cardiac circadian clock, thereby disrupting downstream antioxidant defenses and metabolic homeostasis, and ultimately driving cardiometabolic dysfunction. Methods Seventy-two male C57BL/6 mice were randomly divided into a PM_2.5 exposure group (PM group) and a filtered air control group (FA group). Whole-body exposure was conducted for 8 weeks in a meteorological environmental animal exposure system. Samples were collected at six distinct zeitgeber time (ZT) points post-exposure. The 24 h ambulatory blood pressure and serum lipid profiles were monitored. Rhythm parameters were derived via cosinor analysis to compare differences in Midline statistic of rhythm (Mesor), amplitude, and phase between the two groups. The rhythmic expression of core circadian clock genes and antioxidant genes in the myocardium was detected by quantitative polymerase chain reaction (qPCR). Myocardial reactive oxygen species (ROS) levels and downstream pathway protein expression were analyzed by immunofluorescence and Western blot (WB), respectively. The expression changes of the clock gene retinoic acid receptor-related orphan receptor α (RORα) were assessed at both the mRNA and protein levels. Finally, Spearman correlation analysis was used to explore the relationships among myocardial RORα expression, lipid profiles, and oxidative stress indicators. Results Compared to the FA group, mice in the PM group exhibited a blunted circadian rhythm in blood pressure, characterized by sustained elevation throughout the day. Chronic PM_2.5 exposure showed a significant interaction with ZT on systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) (F-interaction=9.11, 5.70, and 6.02, respectively; P<0.05), as well as on serum triglycerides (TG), total cholesterol (T-CHO), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) (F-interaction=16.32, 11.12, 15.39, and 28.09, respectively; P<0.05). Cosinor analysis further revealed that the Mesor values of T-CHO, TG, and LDL-C were significantly increased (P<0.05), while that of HDL-C was significantly decreased in the PM group (P<0.05). The oscillation amplitudes of SBP, DBP, and MAP showed a decreasing trend, whereas those of TG and LDL-C were significantly increased (P<0.05). Furthermore, SBP, T-CHO, and HDL-C all exhibited a significant phase delay (P<0.05). Mechanistically, PM_2.5 exposure significantly suppressed the expression of the positive circadian regulator RORα in the myocardium, leading to disordered rhythmic expression of core clock genes (Bmal1, Clock, Per1/2, and Cry1/2). This exposure also inhibited the rhythmic expression of antioxidant genes (GPX1, SOD2, and CAT), resulting in increased ROS generation and elevated expression of calcium/calmodulin-dependent protein kinase II (CaMKII) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) proteins. Correlation analysis further revealed that myocardial RORα expression level was negatively correlated with T-CHO, TG, and LDL-C (r=−0.55, −0.63, and −0.51, respectively; P<0.001), and positively correlated with HDL-C (r=0.37, P=0.010), and antioxidant genes GPX1, SOD2, and CAT expression (r=0.34, 0.35, and 0.56, respectively; P < 0.001). Conclusion Chronic PM_2.5 exposure induces cardiometabolic dysfunction by suppressing myocardial RORα expression. This suppression disrupts the cardiac circadian clock and the diurnal balance of oxidative stress, triggering oxidative damage and elevating expression of CaMKII/NADPH pathway proteins. Collectively, these alterations precipitate the loss of cardiac metabolic rhythms and subsequent functional impairment.

Glycosylation constitutes a critical, highly intricate, and diverse co- and post-translational modification characterized by the covalent attachment of sugar moieties to proteins, lipids, or small RNAs. Complex glycans are ubiquitously present across nearly all living organisms. Despite their prevalence, our comprehension of glycan diversity remains limited, likely due to the inherent challenges associated with elucidating their structural complexity. Among post-translational modifications, protein glycosylation is notably prevalent, involving the enzymatic transfer of oligosaccharides to specific amino acid residues by glycosyltransferases. This modification plays a pivotal role in modulating protein function, including participation in various biological and biochemical recognition processes. G protein-coupled receptors (GPCRs), encoded by approximately one thousand genes, share a conserved architecture comprising seven transmembrane helices interconnected by three intracellular and three extracellular loops. Representing the largest family of human membrane proteins, GPCRs regulate a vast array of physiological and pathological processes, thereby constituting the most extensive class of therapeutic targets. In mammalian systems, the majority of GPCRs undergo glycosylation predominantly at their extracellular N-terminus or extracellular loops, primarily through N-linked and O-linked glycosylation. These covalent carbohydrate modifications exert profound effects on multiple facets of GPCR biology, including endoplasmic reticulum folding and quality control, membrane trafficking and surface expression, receptor internalization and recycling or degradation, ligand binding and signal transduction, biased signaling, and receptor dimerization. Notably, glycosylation can exert both positive and negative regulatory influences on these processes. Dysregulation of GPCR glycosylation has been implicated in a range of pathological conditions, such as cancer, diabetes, and neurological disorders, underscoring its physiological and pathological significance. Aberrant glycosylation patterns may lead to dysfunctional receptor signaling, thereby contributing to disease progression. Consequently, elucidating the precise roles of glycosylation in GPCR function not only enhances fundamental understanding of receptor biology but also facilitates the development of novel therapeutic strategies targeting glycosylation pathways or specific GPCR glycoforms. Although the functional consequences of glycosylation have been investigated for several decades, delineating their exact structural underpinnings has remained challenging due to the intrinsic flexibility and heterogeneity of carbohydrate structures. Recent advances in structural biology, particularly single-particle cryo-electron microscopy (cryo-EM) and X-ray crystallography, have catalyzed a paradigm shift in our understanding of GPCR glycosylation. The integration of these sophisticated structural techniques with biochemical approaches has redefined glycosylation as a complex structural element integral to receptor function. These developments provide a molecular framework for comprehending how glycans influence receptor pharmacology and open new avenues for the rational design of glyco-engineered biologics and allosteric modulators targeting specific extracellular motifs. This mini-review concentrates on glycosylation within the GPCR superfamily, summarizing the impact of glycosylation modifications on receptor function and regulatory mechanisms, recent progress in the structural biology of GPCR glycosylation, and prospective directions for future research in this field.

In the field of oral medicine, 3D-printed individualized titanium mesh technology is gradually becoming an important means for the treatment of severe alveolar bone defect augmentation. This article provides a comprehensive analysis of the advantages of this technology, the evaluation of osteogenic effects, and the progress of research in clinical applications. In response to the current issue of variability in bone augmentation outcomes, this paper delves into multiple factors affecting bone augmentation effects, including individualized titanium mesh design (involving the thickness, pore size, pore shape, porosity, contour shape, selection of titanium alloy materials, and 3D printing technology), intraoperative procedures (the accuracy of placement during 3D-printed individualized titanium mesh surgery), and postoperative care (including the prevention of complications, formation of pseudoperiosteum, and stability of the titanium mesh). By integrating the clinical experience and research findings of our team, we propose a series of targeted optimization strategies, including designing, manufacturing, and clinically applying self-positioning individualized titanium meshs (positioning wings + individualized titanium meshs) to improve the positioning accuracy of the titanium mesh; propose individualized treatment processes and titanium mesh design schemes based on specific conditions of alveolar bone defects and soft tissue status; and emphasize the importance of long-term stable fixation of the titanium mesh to reduce the risk of postoperative mesh loosening and displacement. In addition, we appropriately summarize the evaluation methods for the bone augmentation effects of 3D-printed individualized titanium meshes, covering the following key indicators: (1) vertical bone augmentation and horizontal bone augmentation; (2) changes in bone contour morphology; (3) bone volume increase; (4) clinical indicators (surgical success rate, titanium mesh exposure, infection rate, and postoperative recovery); (5) aesthetic effect evaluation; (6) long-term stability; (7) radiological assessment; (8) patient satisfaction; and (9) precision of surgical operation, aiming to assist doctors in comprehensively assessing and in-depth analyzing the surgical outcomes to achieve the best therapeutic effects. The purpose of this article is to provide a reference for the optimization and clinical application of 3D-printed individualized titanium mesh technology and to lay a theoretical foundation for achieving the best osteogenic effects.

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 systematically evaluate risk prediction models for chemotherapy-induced myelosuppression in breast cancer， and provide a scientific reference for clinical healthcare workers in selecting or developing effective predictive models. METHODS A systematic search was conducted for studies on predictive models of the risk of chemotherapy-induced myelosuppression in breast cancer across the CNKI， VIP， Wanfang， PubMed， Web of Science， Cochrane Library， Embase， and Scopus databases， with a time frame of the establishment of the database to May 7， 2024. Literature was independently screened by 2 investigators， data were extracted according to critical appraisal and data extraction for systematic reviews of predictive model studies， and the risk of bias evaluation tool for predictive model studies was used to analyze the risk of bias and applicability of the included studies. RESULTS There were totally 7 studies， comprising 12 models. Among them， 11 models indicated an area under the subject operating characteristic curve of 0.600-0.908； 2 models indicated calibration. The common predictor variables of the included models were age， pre-chemotherapy neutrophil count， pre-chemotherapy lymphocyte count， and pre-chemotherapy albumin. The overall risk of bias of the 7 studies was high， which was mainly attributed to the flaws in the study design， insufficient sample sizes， inappropriate treatment of variables， non-reporting of missing data， and the lack of indicators for the assessment of the models， but the applicability was good. CONCLUSIONS The predictive performance of risk predictive models for chemotherapy-induced myelosuppression in breast cancer remains to be further enhanced， and the overall risk of model bias is high. Future studies should follow the specifications of model development and reporting， then combine machine learning algorithms to develop risk predictive models with good predictive performance， high stability， and low risk of bias， so as to provide a decision-making basis for the clinic.

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 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.