Modified spatial architecture of regulatory T cells after neoadjuvant chemotherapy in non-small cell lung cancer patients.

It is crucial to decipher the modulation of regulatory T cells (Tregs) in tumor microenvironment (TME) induced by chemotherapy, which may contribute to improving the efficacy of neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer (NSCLC). We retrospectively collected specimens from patients with II-III NSCLC, constituting two cohorts: a neoadjuvant chemotherapy (NAC) cohort (N = 141) with biopsy (N = 58) and postoperative specimens (N = 141), and a surgery-only cohort (N = 122) as the control group. Then, the cell density (Dens), infiltration score (InS), and Treg-cell proximity score (TrPS) were conducted using a panel of multiplex fluorescence staining (Foxp3, CD4, CD8, CK, CD31, ɑSMA). Subsequently, the association of Tregs with cancer microvessels (CMVs) and cancer-associated fibroblasts (CAFs) was analyzed. Patients with NAC treatment have a higher density of Tregs in both paired (P < 0.001) and unpaired analysis (P = 0.022). Additionally, patients with NAC treatment showed higher infiltration score (paired, P < 0.001; unpaired, P = 0.014) and more CD8+T cells around Tregs (paired/unpaired, both P < 0.001). Subgroup analysis indicated that tumors with a diameter of ≤ 5 cm exhibited increase in both Dens(Treg) and InS(Treg), and gemcitabine, pemetrexed and taxel enhanced Dens(Treg) and TrPS(CD8) following NAC. Multivariate analysis identified that the Dens(Tregs), InS(Tregs) and TrPS(CD8) were significantly associated with better chemotherapy response [OR = 8.54, 95%CI (1.69, 43.14), P = 0.009; OR = 7.14, 95%CI (1.70, 30.08), P = 0.024; OR = 5.50, 95%CI (1.09, 27.75), P = 0.039, respectively] and positive recurrence-free survival [HR = 3.23, 95%CI (1.47, 7.10), P = 0.004; HR = 2.70; 95%CI (1.27, 5.72); P = 0.010; HR = 2.55, 95%CI (1.21, 5.39), P = 0.014, respectively]. Moreover, TrPS(CD8) and TrPS(CD4) were negatively correlated with the CMVs and CAFs. These discoveries have deepened our comprehension of the immune-modulating impact of chemotherapy and underscored that the modified spatial landscape of Tregs after chemotherapy should be taken into account for personalized immunotherapy, aiming to ultimately improve clinical outcomes in patients with NSCLC.

Dysfunction of CD8+ T cells around tumor cells leads to occult lymph node metastasis in NSCLC patients.

Occult lymph node metastasis (OLNM) is one of the main causes of regional recurrence in inoperable N0 non-small cell lung cancer (NSCLC) patients following stereotactic ablation body radiotherapy (SABR) treatment. The integration of immunotherapy and SABR (I-SABR) has shown preliminary efficiency in mitigating this recurrence. Therefore, it is necessary to explore the functional dynamics of critical immune effectors, particularly CD8+ T cells in the development of OLNM. In this study, tissue microarrays (TMAs) and multiplex immunofluorescence (mIF) were used to identify CD8+ T cells and functional subsets (cytotoxic CD8+ T cells/predysfunctional CD8+ T cells (CD8+ Tpredys)/dysfunctional CD8+ T cells (CD8+ Tdys)/other CD8+ T cells) among the no lymph node metastasis, OLNM, and clinically evident lymph node metastasis (CLNM) groups. As the degree of lymph node metastasis escalated, the density of total CD8+ T cells and CD8+ Tdys cells, as well as their proximity to tumor cells, increased progressively and remarkably in the invasive margin (IM). In the tumor center (TC), both the density and proximity of CD8+ Tpredys cells to tumor cells notably decreased in the OLNM group compared with the group without metastasis. Furthermore, positive correlations were found between the dysfunction of CD8+ T cells and HIF-1α+CD8 and cancer microvessels (CMVs). In conclusion, the deterioration in CD8+ T cell function and interactive dynamics between CD8+ T cells and tumor cells play a vital role in the development of OLNM in NSCLC. Strategies aimed at improving hypoxia or targeting CMVs could potentially enhance the efficacy of I-SABR.

Characterizing Edible Oils by Oblique-Incidence Reflectivity Difference Combined with Machine Learning Algorithms.

Due to the significant price differences among different types of edible oils, expensive oils like olive oil are often blended with cheaper edible oils. This practice of adulteration in edible oils, aimed at increasing profits for producers, poses a major concern for consumers. Furthermore, adulteration in edible oils can lead to various health issues impacting consumer well-being. In order to meet the requirements of fast, non-destructive, universal, accurate, and reliable quality testing for edible oil, the oblique-incidence reflectivity difference (OIRD) method combined with machine learning algorithms was introduced to detect a variety of edible oils. The prediction accuracy of Gradient Boosting, K-Nearest Neighbor, and Random Forest models all exceeded 95%. Moreover, the contribution rates of the OIRD signal, DC signal, and fundamental frequency signal to the classification results were 45.7%, 34.1%, and 20.2%, respectively. In a quality evaluation experiment on olive oil, the feature importance scores of three signals reached 63.4%, 18.9%, and 17.6%. The results suggested that the feature importance score of the OIRD signal was significantly higher than that of the DC and fundamental frequency signals. The experimental results indicate that the OIRD method can serve as a powerful tool for detecting edible oils.

Clinical characteristics and MRI based radiomics nomograms can predict iPFS and short-term efficacy of third-generation EGFR-TKI in EGFR-mutated lung adenocarcinoma with brain metastases.

BACKGROUND: Predicting short-term efficacy and intracranial progression-free survival (iPFS) in epidermal growth factor receptor gene mutated (EGFR-mutated) lung adenocarcinoma patients with brain metastases who receive third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapy was of great significance for individualized treatment. We aimed to construct and validate nomograms based on clinical characteristics and magnetic resonance imaging (MRI) radiomics for predicting short-term efficacy and intracranial progression free survival (iPFS) of third-generation EGFR-TKI in EGFR-mutated lung adenocarcinoma patients with brain metastases. METHODS: One hundred ninety-four EGFR-mutated lung adenocarcinoma patients with brain metastases who received third-generation EGFR-TKI treatment were included in this study from January 1, 2017 to March 1, 2023. Patients were randomly divided into training cohort and validation cohort in a ratio of 5:3. Radiomics features extracted from brain MRI were screened by least absolute shrinkage and selection operator (LASSO) regression. Logistic regression analysis and Cox proportional hazards regression analysis were used to screen clinical risk factors. Single clinical (C), single radiomics (R), and combined (C + R) nomograms were constructed in short-term efficacy predicting model and iPFS predicting model, respectively. Prediction effectiveness of nomograms were evaluated by calibration curves, Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Kaplan-Meier analysis was used to compare the iPFS of high and low iPFS rad-score patients in the predictive iPFS R model and to compare the iPFS of high-risk and low-risk patients in the predictive iPFS C + R model. RESULTS: Overall response rate (ORR) was 71.1%, disease control rate (DCR) was 91.8% and median iPFS was 12.67 months (7.88-20.26, interquartile range [IQR]). There were significant differences in iPFS between patients with high and low iPFS rad-scores, as well as between high-risk and low-risk patients. In short-term efficacy model, the C-indexes of C + R nomograms in training cohort and validation cohort were 0.867 (0.835-0.900, 95%CI) and 0.803 (0.753-0.854, 95%CI), while in iPFS model, the C-indexes were 0.901 (0.874-0.929, 95%CI) and 0.753 (0.713-0.793, 95%CI). CONCLUSIONS: The third-generation EGFR-TKI showed significant efficacy in EGFR-mutated lung adenocarcinoma patients with brain metastases, and the combined line plot of C + R can be utilized to predict short-term efficacy and iPFS.

Cloning, Expression, and Functional Characterization of Two Highly Efficient Flavonoid-di-O-glycosyltransferases ZmUGT84A1 and ZmUGT84A2 from Maize (Zea mays L.).

The maize (Zea mays L.) glycosyltransferase family 1 comprises many uridine diphosphate glycosyltransferase (UGT) members. However, UGT activities and biochemical functions have seldom been revealed. In this study, the genes of two flavonoid di-O-glycosyltransferases ZmUGT84A1 and ZmUGT84A2 were cloned from maize plant and expressed in Escherichia coli. Phylogenetic analysis showed that the two enzymes were homologous to AtUGT84A1 and AtUGT84A3. The two recombinant enzymes showed a high conversion rate of luteolin to its glucosides, mainly 4',7-di-O-glucoside and minorly 3',7-di-O-glucoside in two-step glycosylation reactions in vitro. Moreover, the recombinant ZmUGT84A1 and ZmUGT84A2 had a broad substrate spectrum, converting eriodictyol, naringenin, apigenin, quercetin, and kaempferol to monoglucosides and diglucosides. The highly efficient ZmUGT84A1 and ZmUGT84A2 may be used as a tool for the effective synthesis of various flavonoid O-glycosides and as markers for crop breeding to increase O-glycosyl flavonoid content in food.

Spatial features of specific CD103+CD8+ tissue-resident memory T cell subsets define the prognosis in patients with non-small cell lung cancer.

BACKGROUND: Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it. METHODS: Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). RESULTS: The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1-Tim-3-TRM), TRM2 (PD-1+Tim-3-TRM), TRM3 (PD-1-Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63-3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of TRM cells. CONCLUSIONS: These findings reveal a significant heterogeneity in the functional status and spatial distribution of TRM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating TRM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.

The analysis of multiple omics and examination of pathological images revealed the prognostic and therapeutic significances of CD93 in lung squamous cell carcinoma.

As a potent pro-angiogenic factor, the role of CD93 in the prognosis and therapeutic outcomes of lung squamous cell carcinoma (LUSC) merits exploration. In this study, we systematically collected transcriptomic, genomic, and clinical data from various public databases, as well as pathological images from hospital-operated patients. Employing statistical analysis software like R (Version 4.2.2) and GraphPad (Version 8.0), we conducted comprehensive analyses of multi-omics data. The results revealed elevated CD93 expression in LUSC tissues, closely associated with various cancer-related pathways. High CD93 expression indicated advanced clinical stage and poorer prognosis. Furthermore, CD93 contributed to resistance against chemotherapy and immunotherapy by enhancing tumor cell stemness, reducing immune cell infiltration, and inducing T cell exhaustion. Patients with low CD93 expression exhibited higher response rates to both chemotherapy and immunotherapy. Immunohistochemistry validated the significance of CD93 in LUSC. CD93 emerges as a biomarker signaling unfavorable prognosis and influencing therapeutic outcomes, suggesting a potential LUSC treatment avenue.

Body Composition and Radiomics From 18 F-FDG PET/CT Together Help Predict Prognosis for Patients With Stage IV Non-Small Cell Lung Cancer.

PURPOSE: To determine whether integration of data on body composition and radiomic features obtained using baseline 18 F-FDG positron emission tomography/computed tomography (PET/CT) images can be used to predict the prognosis of patients with stage IV non-small cell lung cancer (NSCLC). METHODS: A total of 107 patients with stage IV NSCLC were retrospectively enrolled in this study. We used the 3D Slicer (The National Institutes of Health, Bethesda, Maryland) software to extract the features of PET and CT images. Body composition measurements were taken at the L3 level using the Fiji (Curtis Rueden, Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison) software. Independent prognostic factors were defined by performing univariate and multivariate analyses for clinical factors, body composition features, and metabolic parameters. Data on body composition and radiomic features were used to build body composition, radiomics, and integrated (combination of body composition and radiomic features) nomograms. The models were evaluated to determine their prognostic prediction capabilities, calibration, discriminatory abilities, and clinical applicability. RESULTS: Eight radiomic features relevant to progression-free survival (PFS) were selected. Multivariate analysis showed that the visceral fat area/subcutaneous fat area ratio independently predicted PFS ( P = 0.040). Using the data for body composition, radiomic features, and integrated features, nomograms were established for the training (areas under the curve = 0.647, 0.736, and 0.803, respectively) and the validation sets (areas under the receiver operating characteristic = 0.625, 0.723, and 0.866, respectively); the integrated model showed better prediction ability than that of the other 2 models. The calibration curves revealed that the integrated nomogram exhibited a better agreement between the estimation and the actual observation in terms of prediction of the probability of PFS than that of the other 2 models. Decision curve analysis revealed that the integrated nomogram was superior to the body composition and radiomics nomograms for predicting clinical benefit. CONCLUSION: Integration of data on body composition and PET/CT radiomic features can help in prediction of outcomes in patients with stage IV NSCLC.

Open spina bifida characterisation in a dog foetus.

BACKGROUND: Open spina bifida is an uncommon malformation in animals, and there is a lack of imaging, clinical, and pathological characterisation of this condition in dogs. OBJECTIVE: Open spina bifida is rarely observed in animals due to high levels of perinatal mortality and frequent euthanasia. To the best of our knowledge, we present the first case of spina bifida in a dog was diagnosed in-utero and then followed post-partum. METHODS: A 3-year-old Poodle was presented with twin pregnancy. Radiographic and ultrasonographic findings were suggestive of vertebral malformation and open spina bifida with myelomeningocele in one foetus. Conservative treatment was given but the puppy died 3 days after birth. Thereafter, anatomical and histopathological analysis of several organs was performed to characterise the disease. RESULTS: When the twins were born, one puppy had a linear dorsal midline cutaneous defect extending from the level of vertebrae L2-L6. R Radiographic examination showed several congenital vertebral malformations involving the thoracic segment, lumbar segment, sacrum and scapula. Histopathological examinations confirmed the presence of open spina bifida and identified additional abnormalities in several internal organs. CONCLUSIONS: This case presents a complete characterisation of open spina bifida, before birth and after death, using imaging and histopathology techniques.

18F-FDG PET/CT radiomics for prediction of lymphovascular invasion in patients with early stage non-small cell lung cancer.

Objective: To explore a prediction model for lymphovascular invasion (LVI) on cT1-2N0M0 radiologic solid non-small cell lung cancer (NSCLC) based on a 2-deoxy-2[18F]fluoro-D-glucose ([18F]F-FDG) positron emission tomography-computed tomography (PET-CT) radiomics analysis. Methods: The present work retrospectively included 148 patients receiving surgical resection and verified pathologically with cT1-2N0M0 radiologic solid NSCLC. The cases were randomized into training or validation sets in the ratio of 7:3. PET and CT images were used to select optimal radiomics features. Three radiomics predictive models incorporating CT, PET, as well as PET/CT images radiomics features (CT-RS, PET-RS, PET/CT-RS) were developed using logistic analyses. Furthermore, model performance was evaluated by ROC analysis for predicting LVI status. Model performance was evaluated in terms of discrimination, calibration along with clinical utility. Kaplan-Meier curves were employed to analyze the outcome of LVI. Results: The ROC analysis demonstrated that PET/CT-RS (AUCs were 0.773 and 0.774 for training and validation sets) outperformed both CT-RS(AUCs, 0.727 and 0.752) and PET-RS(AUCs, 0.715 and 0.733). A PET/CT radiology nomogram (PET/CT-model) was developed to estimate LVI; the model demonstrated conspicuous prediction performance for training (C-index, 0.766; 95%CI, 0.728-0.805) and validation sets (C-index, 0.774; 95%CI, 0.702-0.846). Besides, decision curve analysis and calibration curve showed that PET/CT-model provided clinically beneficial effects. Disease-free survival and overall survival varied significantly between LVI and non-LVI cases (P<0.001). Conclusions: The PET/CT radiomics models could effectively predict LVI on early stage radiologic solid lung cancer and provide support for clinical treatment decisions.

Efficacy and safety of immunoradiotherapy for advanced non-small cell lung cancer: a retrospective comparative cohort study.

Background: Treatment of radiotherapy (RT) combined with immune checkpoint inhibitor (ICI) may remarkably improve the prognosis in patients with metastatic non-small cell lung cancer (NSCLC). However, the treatment time of RT, irradiated lesion and the optimum combined scheme, have not been fully determined. Methods: Data regarding overall survival (OS), progression-free survival (PFS), treatment response, and adverse events of 357 patients with advanced NSCLC treated with ICI alone or in combination with RT prior to/during ICI treatment were retrospectively collected. Additionally, subgroup analyses for radiation dose, time interval between RT and immunotherapy, and number of irradiated lesions were performed. Results: Median PFS of the ICI alone and ICI + RT groups was 6 and 12 months, respectively (P<0.0001). The objective response rate (ORR) and disease control rate (DCR) were significantly higher in the ICI + RT group than in the ICI alone group (P=0.014; P=0.015, respectively). However, OS, the distant response rate (DRR), and the distant control rate (DCRt) did not differ significantly between the groups. Out-of-field DRR and DCRt were defined in unirradiated lesions only. Compared with RT application prior to ICI, its application concomitant with ICI led to higher DRR (P=0.018) and DCRt (P=0.002). Subgroup analyses revealed that single-site, high biologically effective dose (BED) (≥72 Gy), planning target volume (PTV) size (<213.7 mL) RT groups had better PFS. In multivariate analysis, PTV volume [≥213.7 vs. <213.7 mL: hazard ratio (HR), 1.89; 95% confidence interval (CI): 1.04-3.42; P=0.035] was an independent predictor of immunotherapy PFS. Additionally, radio-immunotherapy increased the incidence rate of grade 1-2 immune-related pneumonitis compared with ICI alone. Conclusions: Combination therapy using ICIs and radiation may improve PFS and tumor response rates in advanced NSCLC patients regardless of programmed cell death 1 ligand 1 (PD-L1) level or previous treatments. However, it may increase the incidence of immune-related pneumonitis.

18F-FDG PET/CT radiomics predicts brain metastasis in I-IIIA resected Non-Small cell lung cancer.

OBJECTIVE: To establish 18F-FDG PET/CT radiomics model for predicting brain metastasis in non-small cell lung cancer (NSCLC) patients. METHODS: This research comprised 203 NSCLC patients who had received surgical therapy at two institutions. To identify independent predictive factors of brain metastasis, metabolic indicators, CT features, and clinical features were investigated. A prediction model was established by incorporating radiomics signature and clinicopathological risk variables. The suggested model's performance was assessed from the perspective of discrimination, calibration, and clinical application. RESULTS: The C-indices of the PET/CT radiomics model in the training, internal validation, and external validation cohorts were 0.911, 0.825 and 0.800, respectively. According to the multivariate analysis, neuron-specific enolase (NSE) and air bronchogram were independent risk factors for brain metastasis (BM). Furthermore, the combined model integrating radiomics and clinicopathological characteristics related to brain metastasis performed better in terms of prediction, with C-indices of 0.927, 0.861, and 0.860 in the training, internal validation, and external validation cohorts, respectively. The decision curve analysis (DCA) suggested that the PET/CT nomogram was clinically beneficial. CONCLUSIONS: A predictive algorithm based on PET/CT imaging information and clinicopathological features may accurately predict the probability of brain metastasis in NSCLC patients following surgery. This presented doctors with a unique technique for screening NSCLC patients at high risk of brain metastasis.

Discrimination of wheat flour grade based on PSO-SVM of hyperspectral technique.

Rapid detection of wheat flour grade played an important role in the food industry. In this work, hyperspectral technology was used to detect five types of wheat flour. An analysis model was established based on the reflectance of samples at 968 ∼ 2576 nm. Moreover, multivariate scattering correction (MSC), standard normalized variate (SNV), and Savitzky-Golay (S-G) convolution smoothing were used for preprocessing, which was employed to reduce the influence of noise in the original spectrum. In order to simplify the model, competing adaptive reweighted sampling (CARS), successive projection algorithm (SPA), uninformative variable elimination (UVE) and the UVE-CARS algorithm were applied to extract feature wavelengths. Both partial least squares discriminant analysis (PLS-DA) model and support vector machine (SVM) model were established according to feature wavelengths. Furthermore, particle swarm optimization (PSO) algorithm was adopted to optimize the search of SVM model parameters, such as the penalty coefficient c and the regularization coefficient g. Experimental results suggested that the non-linear discriminant model for wheat flour grades was better than the linear discriminant model. It was considered that the MSC-UVE-CARS-PSO-SVM model achieved the best forecasting results for wheat flour grade discrimination, with 100% accuracy both in the calibration set and the validation set. It further shows that the classification of wheat flour grade can be effectively realized by using the hyperspectral and SVM discriminant analysis model, which proves the potential of hyperspectral reflectance technology in the qualitative analysis of wheat flour grade.

Characterization and clinical verification of immune-related genes in hepatocellular carcinoma to aid prognosis evaluation and immunotherapy.

BACKGROUND: Immune-related genes (IRGs) have been confirmed to play an important role in tumorigenesis and tumor microenvironment formation in hepatocellular carcinoma (HCC). We investigated how IRGs regulates the HCC immunophenotype and thus affects the prognosis and response to immunotherapy. METHODS: We investigated RNA expression of IRGs and developed an immune-related genes-based prognostic index (IRGPI) in HCC samples. Then, the influence of the IRGPI on the immune microenvironment was comprehensively analysed. RESULTS: According to IRGPI, HCC patients are divided into two immune subtypes. A high IRGPI was characterized by an increased tumor mutation burden (TMB) and a poor prognosis. More CD8 + tumor infiltrating cells and expression of PD-L1 were observed in low IRGPI subtypes. Two immunotherapy cohorts confirmed patients with low IRGPI demonstrated significant therapeutic benefits. Multiplex immunofluorescence staining determined that there were more CD8 + T cells infiltrating into tumor microenvironment in IRGPI-low groups, and the survival time of these patients was longer. CONCLUSIONS: This study demonstrated that the IRGPI serve as a predictive prognostic biomarker and potential indicator for immunotherapy.

Astrocyte-Neuronal Communication and Its Role in Stroke.

Astrocytes are the most abundant glial cells in the central nervous system. These cells are an important hub for intercellular communication. They participate in various pathophysiological processes, including synaptogenesis, metabolic transformation, scar production, and blood-brain barrier repair. The mechanisms and functional consequences of astrocyte-neuron signaling are more complex than previously thought. Stroke is a disease associated with neurons in which astrocytes also play an important role. Astrocytes respond to the alterations in the brain microenvironment after stroke, providing required substances to neurons. However, they can also have harmful effects. In this review, we have summarized the function of astrocytes, their association with neurons, and two paradigms of the inflammatory response, which suggest that targeting astrocytes may be an effective strategy for treating stroke.

Metabolic reprogramming regulates microglial polarization and its role in cerebral ischemia reperfusion.

The brain is quite sensitive to changes in energy supply because of its high energetic demand. Even small changes in energy metabolism may be the basis of impaired brain function, leading to the occurrence and development of cerebral ischemia/reperfusion (I/R) injury. Abundant evidence supports that metabolic defects of brain energy during the post-reperfusion period, especially low glucose oxidative metabolism and elevated glycolysis levels, which play a crucial role in cerebral I/R pathophysiology. Whereas research on brain energy metabolism dysfunction under the background of cerebral I/R mainly focuses on neurons, the research on the complexity of microglia energy metabolism in cerebral I/R is just emerging. As resident immune cells of the central nervous system, microglia activate rapidly and then transform into an M1 or M2 phenotype to correspond to changes in brain homeostasis during cerebral I/R injury. M1 microglia release proinflammatory factors to promote neuroinflammation, while M2 microglia play a neuroprotective role by secreting anti-inflammatory factors. The abnormal brain microenvironment promotes the metabolic reprogramming of microglia, which further affects the polarization state of microglia and disrupts the dynamic equilibrium of M1/M2, resulting in the aggravation of cerebral I/R injury. Increasing evidence suggests that metabolic reprogramming is a key driver of microglial inflammation. For example, M1 microglia preferentially produce energy through glycolysis, while M2 microglia provide energy primarily through oxidative phosphorylation. In this review, we highlight the emerging significance of regulating microglial energy metabolism in cerebral I/R injury.

FDG PET/CT Tumor Dissemination Characteristic Predicts the Outcome of First-Line Systemic Therapy in Non-small Cell Lung Cancer.

RATIONALE AND OBJECTIVES: To explore the correlation between the tumor dissemination characteristic at 18F-fluoro-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images and the outcome of first-line systemic therapy for stage IV non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: The current retrospective study included 101 NSCLC patients receiving first-line systemic therapy with baseline 18F-FDG PET/CT images available. The distance between the two lesions that were the farthest apart was defined as Dmax to calculate the tumor dissemination. The tumor metabolic volume (MTV) of the primary tumor and the MTV of the whole-body tumor lesions (MTVwb) were calculated using 18F-FDG PET/CT imaging. The Kaplan-Meier survival analyses and Cox predictive model were performed to assess the relationship between the parameters and survival. RESULTS: Dmax and MTVwb were independent prognostic factors for overall survival (OS) (p = 0.019 and p = 0.011, respectively) and progression-free survival (PFS) (p = 0.043 and p = 0.009, respectively). Poor PFS and OS were associated with high MTVwb (>54.0 cm3) and high Dmax (>48.5 cm) (p = 0.006 and p = 0.008, respectively). When MTVwb and Dmax were combined, three risk groups were stratified with no (score 0), one (score 1), or two (score 2) factors (p < 0.001 for PFS, p < 0.001 for OS). The group with a score of 0 had a considerably longer PFS and OS than those who received a score of 1 or 2 (PFS: 61.1%, 43.5%, and 21.1%, respectively, OS: 77.8%, 54.3%, and 36.8%, respectively). CONCLUSION: The combination of tumor dissemination characteristic (Dmax) and tumor burden (MTVwb) can further improve the prognosis stratification of NSCLC.

Functional status and spatial architecture of tumor-infiltrating CD8+ T cells are associated with lymph node metastases in non-small cell lung cancer.

BACKGROUND: Anti-PD-(L)1 immunotherapy has been recommended for non-small cell lung cancer (NSCLC) patients with lymph node metastases (LNM). However, the exact functional feature and spatial architecture of tumor-infiltrating CD8 + T cells remain unclear in these patients. METHODS: Tissue microarrays (TMAs) from 279 IA-IIIB NSCLC samples were stained by multiplex immunofluorescence (mIF) for 11 markers (CD8, CD103, PD-1, Tim3, GZMB, CD4, Foxp3, CD31, αSMA, Hif-1α, pan-CK). We evaluated the density of CD8 + T-cell functional subsets, the mean nearest neighbor distance (mNND) between CD8 + T cells and neighboring cells, and the cancer-cell proximity score (CCPS) in invasive margin (IM) as well as tumor center (TC) to investigate their relationships with LNM and prognosis. RESULTS: The densities of CD8 + T-cell functional subsets, including predysfunctional CD8 + T cells (Tpredys) and dysfunctional CD8 + T cells (Tdys), in IM predominated over those in TC (P < 0.001). Multivariate analysis identified that the densities of CD8 + Tpredys cells in TC and CD8 + Tdys cells in IM were significantly associated with LNM [OR = 0.51, 95%CI (0.29-0.88), P = 0.015; OR = 5.80, 95%CI (3.19-10.54), P < 0.001; respectively] and recurrence-free survival (RFS) [HR = 0.55, 95%CI (0.34-0.89), P = 0.014; HR = 2.49, 95%CI (1.60-4.13), P = 0.012; respectively], independent of clinicopathological factors. Additionally, shorter mNND between CD8 + T cells and their neighboring immunoregulatory cells indicated a stronger interplay network in the microenvironment of NSCLC patients with LNM and was associated with worse prognosis. Furthermore, analysis of CCPS suggested that cancer microvessels (CMVs) and cancer-associated fibroblasts (CAFs) selectively hindered CD8 + T cells from contacting with cancer cells, and were associated with the dysfunction of CD8 + T cells. CONCLUSION: Tumor-infiltrating CD8 + T cells were in a more dysfunctional status and in a more immunosuppressive microenvironment in patients with LNM compared with those without LNM.

Procyanidins Alleviated Cerebral Ischemia/Reperfusion Injury by Inhibiting Ferroptosis via the Nrf2/HO-1 Signaling Pathway.

Procyanidins (PCs), which are organic antioxidants, suppress oxidative stress, exhibit anti-apoptotic properties, and chelate metal ions. The potential defense mechanism of PCs against cerebral ischemia/reperfusion injury (CIRI) was investigated in this study. Pre-administration for 7 days of a PC enhanced nerve function and decreased cerebellar infarct volume in a mouse middle cerebral artery embolization paradigm. In addition, mitochondrial ferroptosis was enhanced, exhibited by mitochondrial shrinkage and roundness, increased membrane density, and reduced or absent ridges. The level of Fe2+ and lipid peroxidation that cause ferroptosis was significantly reduced by PC administration. According to the Western blot findings, PCs altered the expression of proteins associated with ferroptosis, promoting the expression of GPX4 and SLC7A11 while reducing the expression of TFR1, hence inhibiting ferroptosis. Moreover, the treatment of PCs markedly elevated the expression of HO-1 and Nuclear-Nrf2. The PCs' ability to prevent ferroptosis due to CIRI was decreased by the Nrf2 inhibitor ML385. Our findings showed that the protective effect of PCs may be achieved via activation of the Nrf2/HO-1 pathway and inhibiting ferroptosis. This study provides a new perspective on the treatment of CIRI with PCs.

Nudifloids A-N, structurally diverse 3,4-seco-labdane diterpenoids from Callicarpa nudiflora with inflammatory inhibitory activity.

Fourteen undescribed seco-type diterpenoids, named nudifloids A-N, together with ten known analogs, were isolated from the leaves of Callicarpa nudiflora. Nudifloids A-N had a characteristic 3,4-seco-labdane-type diterpenoid skeleton, whereas nudifloids A-C and K-N were 3,4-seco-norditerpenoids. Nudifloid A was the first example of a 3,4-seco-12,13,14,15,16-quartnor-labdane diterpenoid, with a seven-membered lactone ring formed through esterification between C-3 and C-11. Nudifloids B and C were a pair of highly modified 3,4-seco-labdane nor-diterpenoid epimers, of which C-2 and C-18 were cyclized together to form a cyclohexene fragment. The structures of these undescribed diterpenoids were established by spectroscopic analysis and reference data. The anti-inflammatory activity of diterpenoids in rich yield was evaluated by analyzing the inhibition of lipopolysaccharide plus nigericin-induced pyroptosis in J774A.1 cells. Nudifloids D and E exhibited prominent anti-NLRP3 inflammasome activity, with IC50 values of 1.80 and 1.59 µM, respectively. Cell permeability assays revealed that nudifloid D inhibited pyroptosis, which could ameliorate inflammation by blocking the activation of the NLRP3 inflammasome.