LILRB2 inhibition enhances radiation sensitivity in non-small cell lung cancer by attenuating radiation-induced senescence.

Radiotherapy (RT) in non-small cell lung cancer (NSCLC) triggers cellular senescence, complicating tumor microenvironments and affecting treatment outcomes. This study examines the role of lymphocyte immunoglobulin-like receptor B2 (LILRB2) in modulating RT-induced senescence and radiosensitivity in NSCLC. Through methodologies including irradiation, lentivirus transfection, and various molecular assays, we assessed LILRB2's expression and its impact on cellular senescence levels and tumor cell behaviors. Our findings reveal that RT upregulates LILRB2, facilitating senescence and a senescence-associated secretory phenotype (SASP), which in turn enhances tumor proliferation and resistance to radiation. Importantly, LILRB2 silencing attenuates these effects by inhibiting the JAK2/STAT3 pathway, significantly increasing radiosensitivity in NSCLC models. Clinical data correlate high LILRB2 expression with reduced RT response and poorer prognosis, suggesting LILRB2's pivotal role in RT-induced senescence and its potential as a therapeutic target to improve NSCLC radiosensitivity.

Developing a prediction model in a lightweight packaging waste sorting plant using sensor-based sorting data combined with data of external near-infrared and LiDAR sensors.

Sensor-based material flow monitoring allows for continuously high output qualities, through quality management and process control. The implementation in the waste management sector, however, is inhibited by the heterogeneity of waste and throughput fluctuations. In this study, challenges and possibilities of using different types of sensors in a lightweight packaging waste sorting plant are investigated. Three external sensors have been mounted on different positions in an Austrian sorting plant: one Light Detection and Ranging (LiDAR) sensor for monitoring the volume flow and two near-infrared (NIR) sensors for measuring the pixel-based material composition and occupation density. Additionally, the data of an existing sensor-based sorter (SBS) were evaluated. To predict the newly introduced parameter material-specific occupation density (MSOD) of multi-coloured polyethylene terephthalate (PET) preconcentrate, different machine learning models were evaluated. The results indicate that using SBS data for both monitoring of throughput fluctuations caused by different bag opener settings as well as monitoring the material composition is feasible, if the pre-set teach-in is suitable. The ridge regression model based on SBS was comparable (RMSE = 3.59 px%, R² = 0.57) to the one based on NIR and LiDAR (RMSE = 3.1 px%, R² = 0.68). The demonstrated feasibility of the implementation at plant scale highlights the opportunities of sensor-based material flow monitoring for the waste management sector and paves the way towards a more circular plastics economy.

ILT4 facilitates angiogenesis in non-small cell lung cancer.

Antiangiogenic therapy targeting VEGF-A has become the standard of first-line therapy for non-small cell lung cancer (NSCLC). However, its clinical response rate is still less than 50%, and most patients eventually develop resistance, even when using combination therapy with chemotherapy. The major cause of resistance is the activation of complex bypass signals that induce angiogenesis and tumor progression. Therefore, exploring novel proangiogenic mechanisms and developing promising targets for combination therapy are crucial for improving the efficacy of antiangiogenic therapy. Immunoglobulin-like transcript (ILT) 4 is a classic immunosuppressive molecule that inhibits myeloid cell activation. Recent studies have shown that tumor cell-derived ILT4 drives tumor progression via the induction of malignant biologies and creation of an immunosuppressive microenvironment. However, whether and how ILT4 participates in NSCLC angiogenesis remain elusive. Herein, we found that enriched ILT4 in NSCLC is positively correlated with high microvessel density, advanced disease, and poor overall survival. Tumor cell-derived ILT4 induced angiogenesis both in vitro and in vivo and tumor progression and metastasis in vivo. Mechanistically, ILT4 was upregulated by its ligand angiopoietin-like protein 2 (ANGPTL2). Their interaction subsequently activated the ERK1/2 signaling pathway to increase the secretion of the proangiogenic factors VEGF-A and MMP-9, which are responsible for NSCLC angiogenesis. Our study explored a novel mechanism for ILT4-induced tumor progression and provided a potential target for antiangiogenic therapy in NSCLC.

Inhibition of CDC20 potentiates anti-tumor immunity through facilitating GSDME-mediated pyroptosis in prostate cancer.

BACKGROUND: Increasing evidence suggests that immunotherapy, especially immune checkpoint inhibitors (ICIs), has the potential to facilitate long-term survival in various cancer besides prostate cancer. Emerging evidence indicated that pyroptosis, an immunogenic form of cell death, could trigger an anti-tumor immune microenvironment and enhance the effectiveness of immunotherapy. Nevertheless, the mechanism underlying the regulation of pyroptosis signaling in prostate cancer remains unclear. METHODS: The differential expression of human E3 ligases in prostate cancer was integratedly analyzed from five independent public datasets. Moreover, the immunohistochemistry analysis of a tissue microarray derived from prostate cancer patients confirmed the results from the bioinformatic analysis. Furthermore, prostate cancer cell lines were evaluated via the next-generation RNA sequencing to assess transcriptomic profile upon CDC20 depletion. Next, qRT-PCR, Western blotting, cycloheximide assay, immunoprecipitation, and ubiquitination assay were employed to explore the correlation and interaction between CDC20 and GSDME. Both immune-deficient and immune-competent murine models were utilized to examine the anti-tumor efficacy of CDC20 inhibition with or without the anti-PD1 antibodies, respectively. To analyze the immune microenvironment of the xenografts, the tumor tissues were examined by immunohistochemistry and flow cytometry. RESULTS: The analysis of multiple prostate cancer cohorts suggested that CDC20 was the most significantly over-expressed E3 ligase. In addition, CDC20 exerted a negative regulatory effect on the pyroptosis pathway by targeting GSDME for ubiquitination-mediated proteolysis in a degron-dependent manner. Knockdown of CDC20 leads to increased GSDME abundance and a transition from apoptosis to pyroptosis in response to death signals. Furthermore, in our syngeneic murine models, we found that depletion of CDC20 significantly enhances the anti-tumor immunity by promoting the infiltration of CD8+ T lymphocytes dependent on the existence of GSDME, as well as reducing myeloid immune cells. More importantly, Apcin, a small molecular inhibitor that targets CDC20, exhibited synergistic effects with anti-PD1-based immunotherapy in murine models of prostate cancer. CONCLUSIONS: Overall, these findings provide new insights into the upstream regulation of GSDME-mediated pyroptosis by CDC20, which specifically interacts with GSDME and facilitates its ubiquitination in a degron-dependent manner. Importantly, our data highlight novel molecular pathways for targeting cellular pyroptosis and enhancing the effectiveness of anti-PD1-based immunotherapy.

ILT4 reprograms glucose metabolism to promote tumor progression in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most aggressive and poorly treated subtype of breast cancer. Identifying novel drivers and mechanisms for tumor progression is essential for precise targeted therapy of TNBC. Immunoglobulin-like transcript 4 (ILT4; also known as LILRB2) is a classic myeloid suppressor for their activation and immune response. Our recent results found that ILT4 is also highly expressed in lung cancer cells, where it has a role in promoting immune evasion and thus tumor formation. However, the expression and function of ILT4 in breast cancer remains elusive. Here, using our patient cohort and public database analysis, we found that TNBC displayed the most abundant ILT4 expression among all breast cancer subtypes. Functionally, enriched ILT4 promoted TNBC cell proliferation, migration and invasion in vitro, as well as tumor growth and metastasis in vivo. Further mechanistic analysis revealed that ILT4 reprogrammed aerobic glycolysis of tumor cells via AKT-mTOR signaling-mediated glucose transporter 3 (GLUT3; also known as SLC2A3) and pyruvate kinase muscle 2 (PKM2, an isoform encoded by PKM) overexpression. ILT4 inhibition in TNBC reduced tumor progression and GLUT3 and PKM2 expression in vivo. Our study identified a novel driver for TNBC progression and proposed a promising strategy to combat TNBC by targeting ILT4.

Inhibition of tumor intrinsic BANF1 activates antitumor immune responses via cGAS-STING and enhances the efficacy of PD-1 blockade.

BACKGROUND: BANF1 is well known as a natural opponent of cyclic GMP-AMP synthase (cGAS) activity on genomic self-DNA. However, the roles of BANF1 in tumor immunity remain unclear. Here, we investigate the possible impact of BANF1 on antitumor immunity and response to immunotherapy. METHODS: The Cancer Genome Atlas public data were analyzed to evaluate the relevance of the expression of BANF1, patients' survival and immune cell infiltration. We monitored tumor growth and explored the antitumor efficacy of targeting tumor-intrinsic BANF1 in combination with anti-programmed cell death protein-1 (PD-1) in MC38 or B16F10 tumor models in both immunocompetent and immunodeficient mice. Flow cytometry, immunofluorescence and T cells depletion experiments were used to validate the role of BANF1 in tumor immune microenvironment reprogramming. RNA sequencing was then used to interrogate the mechanisms how BANF1 regulated antitumor immunity. RESULTS: We show that upregulated expression of BANF1 in tumor tissues is significantly associated with poor survival and is negatively correlated with immune cell infiltration. Deficiency of BANF1 in tumor cells markedly antagonizes tumor growth in immunocompetent but not immunocompromised mice, and enhances the response to immunotherapy in murine models of melanoma and colon cancer. In the immunotherapy clinical cohort, patients with high BANF1 expression had a worse prognosis. Mechanistically, BANF1 knockout activates antitumor immune responses mediated by cGAS-synthase-stimulator of interferon genes (cGAS-STING) pathway, resulting in an immune-activating tumor microenvironment including increased CD8+ T cell infiltration and decreased myeloid-derived suppressor cell enrichment. CONCLUSIONS: BANF1 is a key regulator of antitumor immunity mediated by cGAS-STING pathway. Therefore, our study provides a rational that targeting BANF1 is a potent strategy for enhancing immunotherapy for cancer with BANF1 upregulation.

[Progress in antitumor activity of diterpenoid alkaloids in plants of Aconitum].

Small-molecule compounds with rich sources have diverse structures and activities. The active ingredients in traditional Chinese medicine(TCM) provide new sources for the discovery of new antitumor drugs. Aconitum plants as Chinese medicinal plants have the effects of dispelling wind, removing dampness, warming meridian, and relieving pain. They are mainly used to treat inflammation, pain, rheumatism, and tumors, improve heart function, and dilate blood vessels in clinical practice. Diterpenoid alkaloids are the main active components of Aconitum plants, including C20-, C19-, C18-diterpenoid alkaloids and bis-diterpenoid alkaloids. Stu-dies have demonstrated that diterpenoid alkaloids can effectively treat lung cancer, liver cancer, breast cancer, colon cancer and other cancers. Diterpenoid alkaloids are considered as the most promising natural compounds against cancers. In this review, we summarized the chemical structures and antitumor activities of C20-, C19-, C18-diterpenoid alkaloids and bis-diterpenoid alkaloids extracted from plants of Aconitum, aiming to provide reference for further development of diterpenoid alkaloids from Aconitum as antitumor drugs.

NIR-MFCO dataset: Near-infrared-based false-color images of post-consumer plastics at different material flow compositions and material flow presentations.

Determining mass-based material flow compositions (MFCOs) is crucial for assessing and optimizing the recycling of post-consumer plastics. Currently, MFCOs in plastic recycling are primarily determined through manual sorting analysis, but the use of inline near-infrared (NIR) sensors holds potential to automate the characterization process, paving the way for novel sensor-based material flow characterization (SBMC) applications. This data article aims to expedite SBMC research by providing NIR-based false-color images of plastic material flows with their corresponding MFCOs. The false-color images were created through the pixel-based classification of binary material mixtures using a hyperspectral imaging camera (EVK HELIOS NIR G2-320; 990 nm-1678 nm wavelength range) and the on-chip classification algorithm (CLASS 32). The resulting NIR-MFCO dataset includes n = 880 false-color images from three test series: (T1) high-density polyethylene (HDPE) and polyethylene terephthalate (PET) flakes, (T2a) post-consumer HDPE packaging and PET bottles, and (T2b) post-consumer HDPE packaging and beverage cartons for n = 11 different HDPE shares (0% - 50%) at four different material flow presentations (singled, monolayer, bulk height H1, bulk height H2). The dataset can be used, e.g., to train machine learning algorithms, evaluate the accuracy of inline SBMC applications, and deepen the understanding of segregation effects of anthropogenic material flows, thus further advancing SBMC research and enhancing post-consumer plastic recycling.

Cellular Atlas of Senescent Lineages in Radiation- or Immunotherapy-Induced Lung Injury by Single-Cell RNA-Sequencing Analysis.

PURPOSE: Although the combination of immunotherapy and radiation therapy to treat various malignancies is rapidly expanding, concerns regarding increased pulmonary toxicities remain. The mechanisms of immunotherapy- and irradiation-induced lung injury involve a complex interplay of cell types and signaling pathways, much of which remains to be elucidated. METHODS AND MATERIALS: C57/BL6 mice were treated with a single fraction (20 Gy) of radiation therapy to the right lung or 200 µg anti-Programmed cell death protein 1 antibody twice a week. At 7, 30, and 60 days after treatment, the lung tissues were obtained for unbiased single-cell RNA sequencing or histologic staining. The Seurat analysis pipeline, Cellchat, Monocol, and Single-Cell rEgulatory Network Inference and Clustering were used to define cell types, mechanisms, and mediators driving pathologic remodeling in response to this lung injury. Reverse transcription polymerase chain reaction, immunofluorescent staining, and multiplex immunohistochemistry were applied to validate the key results. RESULTS: Thirty distinct cell subsets encompassing 75,396 cells were identified. A comprehensive investigation of cell-cell crosstalk revealed that monokine signals derived from senescent fibroblasts were substantially elevated after lung injury. Independent analytical strategies revealed that senescence-like subtypes of fibroblasts, alveolar epithelial cells, B cells, and myeloid immune cells were functionally pathologic, with high expression of senescence-signature proteins, especially Apolipoprotein E, during injury response. Senescence markers were also elevated in irradiated human cell lines, mouse cell lines (B3T3 and L929), and the publicly available human pulmonary fibrosis data set. CONCLUSIONS: These findings demonstrate that the accumulation of senescence-like fibroblasts, macrophages, and alveolar epithelial cells is the primary common pathologic mechanism of immunotherapy- and irradiation-induced lung injury. These high-resolution transcriptomic data provide novel insights into therapeutic opportunities to predict or prevent therapy-induced lung injury.

Radiation combined with KRAS-MEK inhibitors enhances anticancer immunity in KRAS-mutated tumor models.

KRAS mutation is a common driver in solid tumors, and KRAS-mutated tumors are relatively resistant to radiotherapy. Therefore, we investigated the combined effect of radiation and KRAS-MEK inhibitors (AMG510 and trametinib) in KRAS-mutated tumors. The expression of programmed death-ligand 1 (PD-L1), major histocompatibility complex (MHC) class I molecules, and cytokines in KRAS-mutated cell lines was assessed using flow cytometry, western blot analysis, quantitative polymerase chain reaction, and enzyme-linked immunosorbent assay. In vivo, tumor growth, T cell infiltration, and gene sequencing analyses were conducted in 2 murine KRAS-mutated models. Both AMG510 and trametinib decreased the radiation-induced increase in PD-L1 expression. Radiation and trametinib additively induced the expression of CXCL10 and CXCL11 cytokines and MHC class I in murine CT26 and LLC cell lines. The combination of trametinib and radiation controlled tumor growth and induced more infiltration of CD4+ and CD8+ T cells in vivo, wherein tumor inhibition function and the survival period of mice could be reduced by CD8+ and/or CD4+ T cell depletion. The expression levels of immune-related genes also increased in the combination therapy group. Our results indicate that KRAS-MEK inhibitors in combination with radiotherapy can enhance antitumor immunity, providing new therapeutic strategies for KRAS-mutated tumors.

Optical sensors and machine learning algorithms in sensor-based material flow characterization for mechanical recycling processes: A systematic literature review.

Digital technologies hold enormous potential for improving the performance of future-generation sorting and processing plants; however, this potential remains largely untapped. Improved sensor-based material flow characterization (SBMC) methods could enable new sensor applications such as adaptive plant control, improved sensor-based sorting (SBS), and more far-reaching data utilizations along the value chain. This review aims to expedite research on SBMC by (i) providing a comprehensive overview of existing SBMC publications, (ii) summarizing existing SBMC methods, and (iii) identifying future research potentials in SBMC. By conducting a systematic literature search covering the period 2000 - 2021, we identified 198 peer-reviewed journal articles on SBMC applications based on optical sensors and machine learning algorithms for dry-mechanical recycling of non-hazardous waste. The review shows that SBMC has received increasing attention in recent years, with more than half of the reviewed publications published between 2019 and 2021. While applications were initially focused solely on SBS, the last decade has seen a trend toward new applications, including sensor-based material flow monitoring, quality control, and process monitoring/control. However, SBMC at the material flow and process level remains largely unexplored, and significant potential exists in upscaling investigations from laboratory to plant scale. Future research will benefit from a broader application of deep learning methods, increased use of low-cost sensors and new sensor technologies, and the use of data streams from existing SBS equipment. These advancements could significantly improve the performance of future-generation sorting and processing plants, keep more materials in closed loops, and help paving the way towards circular economy.

[Association of liver damage with coronary artery lesion and no response to intravenous immunoglobulin in the acute stage of Kawasaki disease]. / å·å´Žç— æ€¥æ€§æœŸè‚æŸå®³ä¸Žå† çŠ¶åŠ¨è„‰æŸä¼¤å’Œå ç–«çƒè›‹ç™½æ— ååº”çš„å ³ç³».

OBJECTIVES: To summarize the clinical features of liver damage in children in the acute stage of Kawasaki disease (KD), and to investigate the clinical value of liver damage in predicting coronary artery lesion and no response to intravenous immunoglobulin (IVIG) in children with KD. METHODS: The medical data were collected from 925 children who were diagnosed with KD for the first time in Beijing Children's Hospital from January 1, 2016 to December 31, 2017. According to the presence or absence of abnormal alanine aminotransferase (ALT) level on admission, the children were divided into a liver damage group (n=284) and a non-liver damage group (n=641). A logistic regression analysis was used to investigate the clinical value of the indicators including liver damage in predicting coronary artery lesion and no response to IVIG in children with KD. RESULTS: Compared with the non-liver damage group, the liver damage group had a significantly earlier admission time and significantly higher serum levels of inflammatory indicators (P<0.05). The liver damage group had a significantly higher incidence rate of coronary artery lesion on admission than the non-liver damage group (P=0.034). After initial IVIG therapy, the liver damage group had a significantly higher proportion of children with no response to IVIG than the non-liver damage group (P<0.001). In children with KD, coronary artery lesion was associated with the reduction in the hemoglobin level and the increases in platelet count, C-reactive protein, and ALT (P<0.05), and no response to IVIG was associated with limb changes, the reduction in the hemoglobin level, the increases in platelet count, C-reactive protein, and ALT, and coronary artery lesion (P<0.05). CONCLUSIONS: Compared with those without liver damage, the children in the early stage of KD with liver damage tend to develop clinical symptoms early and have higher levels of inflammatory indicators, and they are more likely to have coronary artery lesion and show no response to IVIG treatment.

Tumor-derived immunoglobulin like transcript 5 induces suppressive immunocyte infiltration in colorectal cancer.

Infiltration of immunosuppressive cells in the tumor microenvironment (TME) induced colorectal cancer (CRC) progression and its resistance to immunotherapy. Identification of tumor-specific factors to modulate inhibitory immunocyte infiltration would provide alternative and novel targets for CRC immunotherapy. Immunoglobulin-like transcript (ILT) 5 is a negative regulator of myeloid cell activation. However, its expression and functional role in solid tumors is still unknown. Using human CRC tissues and cell lines, we found that ILT5 was highly expressed in CRC cells compared with normal colorectal epithelial cells. Enriched ILT5 in tumor cells was correlated with advanced tumor stages and poor patient survival. Our subsequent in vitro and in vivo studies revealed that tumor-derived ILT5 inhibited the infiltration of T cells, especially that of CD8+ T cells in the TME, creating suppressive T-cell contexture. Furthermore, ILT5 directed M2-like polarization of tumor-associated macrophages (TAMs). Inhibition of tumor-derived ILT5 restored the immunosuppressive T-cell and TAM contexture, and restricted CRC progression. Our findings identified ILT5 expression in solid tumor cells for the first time and raised ILT5 as a potential immunotarget and prognostic predictor in CRC.

Neurturin promotes tumor cell motility and angiogenesis in colorectal cancer.

Neurturin (NRTN) is one of the glial cell line-derived neurotrophic factor family ligands crucial for neuron growth, differentiation and maintenance. Recent studies showed NRTN promotes an aggressive pancreatic cancer phenotype, and predicts shorter survival in lung cancer patients. However, its expression and function in colorectal cancer (CRC) remain unclear. Herein, we found NRTN was enriched in CRC cells, and predicted poor patients outcomes. Upregulated NRTN enhanced the migration and invasion of CRC cells and vascularization of endothelial cells. In mechanism, NRTN promoted ZEB1/N-cadherin and vascular endothelial growth factor (VEGF)-A expression in CRC cells, which were responsible for tumor cell motility and angiogenesis, respectively. More importantly, NRTN inhibition prevented CRC metastasis and angiogenesis in vivo. In conclusion, NRTN promotes CRC cells motility and tumor angiogenesis via inducing ZEB1/N-cadherin and VEGF-A overexpression. It is a potential therapeutic target and negative prognostic biomarker for CRC patients.

Influence of long-term natural degradation processes on near-infrared spectra and sorting of post-consumer plastics.

The large-amount production and application of plastics since the 1950s has led to different environmental problems, and the production amount is still increasing. In 2015, 79 wt% of all plastic waste was accumulated in landfills or the natural environment. Due to their negative influence to the environment, the problems of landfilling and marine litter need urgent treatments. Accordingly, measures like excavation of landfill sites and ocean clean-ups were conducted to reduce their environmental influences and move further towards a closed loop of material cycles. For a possible recycling, the valuable material fractions need to be separated from other materials. Besides, to ensure a high-quality recycling and enable the different recycling processes of plastics in different degradation levels, it is necessary to separate degraded and non-degraded plastics. In this study, the possibility to classify and sort landfill and marine litter plastics is investigated. For this purpose, waste plastics from different origins (lightweight packaging (LWP) waste, landfill, and marine litter) were collected and analyzed with the state-of-the-art technology in sorting plants: near-infrared spectroscopy. With self-developed programs, the classification possibility and performance was determined. The classification accuracy of degraded plastics (from landfill and marine litter) is improved from > 75% to > 97% through adjusting the sorting recipe. Besides, the long-term degraded plastics under natural environment were able to be separated from LWP waste: the same kind of materials can be classified according to their origin (LWP or after long-term degradation), which makes a quality control possible and enables an extra treatment for degraded plastics.

Sensor-based particle mass prediction of lightweight packaging waste using machine learning algorithms.

Sensor-based material flow characterization (SBMC) promises to improve the performance of future-generation sorting plants by enabling new applications like automatic quality monitoring or process control. Prerequisite for this is the derivation of mass-based material flow characteristics from pixel-based sensor data, which requires known individual particle masses. Since particle masses cannot be measured inline, the prediction of particle masses of lightweight packaging (LWP) waste using machine learning (ML) algorithms is investigated. Five LWP material classes were sampled, preprocessed, and scanned on a custom-made test rig, resulting in a dataset containing 3D laser triangulation (3DLT) images, RGB images, and corresponding masses of n = 3,830 particles. Based on 66 extracted shape measurements, six ML models were trained for particle mass prediction (PMP). Their performance was compared with two state-of-the-art reference models using (i) material-specific mean particle masses and (ii) grammages. Obtained particle masses showed a high variation and significant differences between material classes and particle size classes. After feature selection, both reference models achieving R2-scores of (i) 0.422 ± 0.121 and (ii) 0.533 ± 0.224 were outperformed by all investigated ML models. A random forest regressor with an R2-score of 0.763 ± 0.091 and a normalized mean absolute error of 0.243 ± 0.050 achieved the most accurate PMP. In contrast to studies on primary raw materials, PMP of LWP waste is challenging due to influences of packaging design and post-consumer disposal behavior. ML algorithms are a promising approach for PMP that outperform state-of-the-art methods by 43% higher R2-scores.

Influences of bioplastic polylactic acid on near-infrared-based sorting of conventional plastic.

Bioplastics are developed to replace oil-derived plastics due to the high consumption of oil and related environmental impacts of oil-derived plastics. It was predicted that bioplastics can potentially replace 94% of conventional plastic production. With their increasing market share, more bioplastics will end in conventional post-consumer plastic waste streams. Although part of bioplastics is biodegradable and could be biologically decomposed, mechanical recycling achieves higher ecological benefits mainly because of its low pollution risk and the reduction in requirement for virgin feedstock. In this study, the classification of lightweight packaging waste with inflow of bioplastics, more specifically polylactic acid (PLA), was analysed with near-infrared spectroscopy to evaluate the influence of bioplastics on sorting processes of conventional plastics. Besides which, the sortability of PLA was determined through investigating the physical and the spectroscopic characteristics of both non-degraded and degraded PLA. The results show that the classification of all the materials was possible with a pixel-based accuracy of higher than 97.4% and PLA does not influence the sorting process of conventional plastics regarding detection and classification. Furthermore, the sorting of PLA from post-consumer waste is possible, which makes further recycling theoretically achievable.

ILT4 inhibition prevents TAM- and dysfunctional T cell-mediated immunosuppression and enhances the efficacy of anti-PD-L1 therapy in NSCLC with EGFR activation.

Rationale: Immune checkpoint inhibitors (ICIs) against the PD-1/PD-L1 pathway showed limited success in non-small cell lung cancer (NSCLC) patients, especially in those with activating epidermal growth factor receptor (EGFR) mutations. Elucidation of the mechanisms underlying EGFR-mediated tumor immune escape and the development of effective immune therapeutics are urgently needed. Immunoglobulin-like transcript (ILT) 4, a crucial immunosuppressive molecule initially identified in myeloid cells, is enriched in solid tumor cells and promotes the malignant behavior of NSCLC. However, the upstream regulation of ILT4 overexpression and its function in tumor immunity of NSCLC with EGFR activation remains unclear. Methods: ILT4 expression and EGFR phosphorylation in human NSCLC tissues and cell lines were analyzed using immunohistochemistry (IHC), real-time PCR, Western blotting, immunofluorescence, and flow cytometry. The molecular signaling for EGFR-regulated ILT4 expression was investigated using mRNA microarray and The Cancer Genome Atlas (TCGA) database analyses and then confirmed by Western blotting. The regulation of tumor cell proliferation and apoptosis by ILT4 was examined by CCK8 proliferation and apoptosis assays. The impact of ILT4 and PD-L1 on tumor-associated macrophage (TAM) recruitment and polarization was evaluated using Transwell migration assay, flow cytometry, enzyme linked immunosorbent assay (ELISA) and real-time PCR, while their impact on T cell survival and cytotoxicity was analyzed by CFSE proliferation assay, apoptotic assay, flow cytometry, ELISA and cytolytic assay. Tumor immunotherapy models targeting at paired Ig-like receptor B (PIR-B, an ortholog of ILT4 in mouse)/ILT4 and/or PD-L1 were established in C57BL/6 mice inoculated with stable EGFR- overexpressing Lewis lung carcinoma (LLC) cells and in humanized NSG mice inoculated with EGFR mutant, gefitinib-resistant PC9 (PC9-GR) or EGFR-overexpressing wild type H1299 cells. PIR-B and ILT4 inhibition was implemented by infection of specific knockdown lentivirus and PD-L1 was blocked using human/mouse neutralizing antibodies. The tumor growth model was established in NSG mice injected with PIR-B-downregulated LLC cells to evaluate the effect of PIR-B on tumor proliferation. The frequencies and phenotypes of macrophages and T cells in mouse spleens and blood were detected by flow cytometry while those in tumor tissues were determined by IHC and immunofluorescence. Results: We found that ILT4 expression in tumor cells was positively correlated with EGFR phosphorylation in human NSCLC tissues. Using NSCLC cell lines, we demonstrated that ILT4 was upregulated by both tyrosine kinase mutation-induced and epidermal growth factor (EGF)-dependent EGFR activation and subsequent AKT/ERK1/2 phosphorylation. Overexpressed ILT4 in EGFR-activated tumor cells induced TAM recruitment and M2-like polarization, which impaired T cell function. ILT4 also directly inhibited T cell proliferation, cytotoxicity, and IFN-γ expression and secretion. In EGFR-activated cell lines in vitro and in wild-type EGFR-activated C57BL/6 and humanized NSG immunotherapy models in vivo, either ILT4 (PIR-B) or PD-L1 inhibition enhanced anti-tumor immunity and suppressed tumor progression by counteracting TAM- and dysfunctional T cell- induced immuno-suppressive TME; the combined inhibition of both molecules showed the most dramatic tumor retraction. Surprisingly, in EGFR mutant, TKI resistant humanized NSG immunotherapy model, ILT4 inhibition alone rather than in combination with a PD-L1 inhibitor suppressed tumor growth and immune evasion. Conclusions: ILT4 was induced by activation of EGFR-AKT and ERK1/2 signaling in NSCLC cells. Overexpressed ILT4 suppressed tumor immunity by recruiting M2-like TAMs and impairing T cell response, while ILT4 inhibition prevented immunosuppression and tumor promotion. Furthermore, ILT4 inhibition enhanced the efficacy of PD-L1 inhibitor in EGFR wild-type but not in EGFR mutant NSCLC. Our study identified novel mechanisms for EGFR-mediated tumor immune escape, and provided promising immunotherapeutic strategies for patients with EGFR-activated NSCLC.

Determining the composition of post-consumer flexible multilayer plastic packaging with near-infrared spectroscopy.

Flexible multilayer plastic packaging (MPP) has grown in popularity in the last years especially in food and medical sectors, and its share in the packaging industry is expected to increase further. Compared to traditional packaging with same functionalities, MPP is characterized by lower energy consumption in production and a reduced packaging weight. So far, the recycling of post-industrial MPP with specific material composition has been achieved by several companies. To our knowledge, all existing MPP recycling processes require a known material combination. In contrast to post-industrial MPP, post-consumer MPP still ends up in incinerators or as low-quality products, mainly because of the lacking ability to sort. This study investigates the detectability of post-consumer MPP with near-infrared spectroscopy, the state-of-the-art technology for sensor-based waste sorting. Firstly, MPP classification with near-infrared spectroscopy was analyzed with clean samples. Subsequently, the effect of waste collection and preprocessing in sorting plants on MPP classification was investigated. For this purpose, clean samples were covered with water and oil and mixed with lightweight packaging waste in a drum sieve. The results show it is possible to classify post-consumer MPP based on near-infrared spectra according to different sorting strategies. For the existing recycling processes which are suitable for post-consumer MPP, the corresponding object-based classification accuracy was found to exceed 96%.