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Abstract Introduction Lung adenocarcinoma (LUAD), a common subtype of NSCLC, has a high mortality rate. Telomere genes are influenced by radiation therapy, affecting treatment response. Additionally, immune cell presence in the tumor microenvironment plays a crucial role in cancer prognosis. However, the role of Radioresistant-Related Telomere Genes (RRTGs) in LUAD prognosis and immune infiltration remains unclear. Methods In this research, we utilized diverse bioinformatics techniques to examine our personally tested information along with publicly accessible datasets. We conducted a comprehensive study on the genetic and transcriptional differences, predictive significance, and expression profiles of RRTGs. Afterwards, a RRTGs score was developed to forecast the overall survival (OS) and ascertain its reliable predictive capacity for patients with LUAD. Following this, dependable nomograms were developed to enhance the practicality of RRTGs scoring in a clinical setting. Furthermore, the investigation delved into the associations among RRTGs, infiltration of immune cells, prognosis, and clinical treatments of patients. Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential mechanisms by which RRTGs influence the regulation of LUAD. Then, Western blot, qRT-PCR and Immunohistochemistry were used to detect the expression levels of RRTGs in cell lines and LUAD tumor tissues. Results Our research indicates that certain genes related to telomeres have a notable correlation with the prognosis of patients diagnosed with LUAD. The RRTGs score, which includes three key genes (ARRB1, PLK1, and DSG2), was developed to forecast the OS and its dependable predictive capability for individuals diagnosed with LUAD was ascertained. Afterwards, extremely reliable nomograms were developed to improve the practicality of the RRTGs score. Moreover, as illustrated, genetic characteristics can be utilized to assess the infiltration of immune cells in tumors, as well as clinical attributes and prognosis. RRTGs score characterizes tumor mutational burden, immune activity, and notable survival probabilities in addition. Furthermore, GSEA results revealed that RRTGs may influence LUAD by modulating immune-related pathways in high-risk groups and regulating cell cycle and DNA repair processes in low-risk groups. The RRTGs (ARRB1 and PLK1) were upregulated in A549 cells and radiosensitive NSCLC tissues compared to radioresistant A549 cells and NSCLC tissues. Conclusion In conclusion, this research emphasizes the significance of RRTGs in the outlook of LUAD. The findings contributed to a better understanding of the link between radiotherapy, telomere-related genes, and prognosis in LUAD, and identified potential therapeutic targets for patients with LUAD.

Abstract Background Reduced red blood cell deformability (RBCD) is associated with diabetic vascular complications, but early pathophysiological RBC changes and predictive demographic and clinical factors in populations with diabetes are unclear. An understanding of early diabetes-specific RBC changes associated with impaired RBCD is essential in investigating mechanisms that predispose to diabetic vascular complications. Methods We conducted an outpatient cross-sectional study of participants in a well-controlled diabetes cohort (N81) and nondiabetic controls (N78) at the National Institutes of Health. First, between-group differences in RBCD measures were assessed with shear stress-gradient ektacytometry. Differences in structural RBC parameters were assessed using osmotic gradient ektacytometry and NaCl osmotic fragility. Functional RBC changes were assessed using hemoglobin-oxygen dissociation: p50. Results All shear-stress gradient RBCD measures were significantly altered in the diabetes cohort vs. nondiabetic controls, even after adjustment for confounding covariates (p

Abstract Background Numerous studies have demonstrated that brain metastases patients may benefit from intracranial radiotherapy combined with immune checkpoint inhibitors (ICIs). However, it is unclear whether this treatment is effective for patients with small cell lung cancer brain metastases (SCLC‐BMs). Methods We conducted a retrospective study by analyzing medical records of patients with SCLC‐BMs from January 1, 2017 to June 1, 2022. Data related to median overall survival (mOS), median progression‐free survival (mPFS), and intracranial progression‐free survival (iPFS) were analyzed. Results A total of 109 patients were enrolled, of which 60 received WBRT and 49 received WBRT‐ICI. Compared to the WBRT alone cohort, the WBRT‐ICI cohort showed longer mOS (20.4 months vs. 29.3 months, p = 0.021), mPFS (7.9 months vs. 15.1 months, p

In the context of cancer expansion, epithelial-mesenchymal transition (EMT) plays an essential role in driving invasion and metastasis potential of cancer cells. Tumor-associated macrophages (TAMs)-derived factors involved in the initiation and progression of EMT. We assess the role of M2 macrophage in suppressing lung tumors of a natural compound (−)-Guaiol by using macrophage depleted model. Bone marrow-derived monocytes (BMDMs) were extracted and induced to M2-like phenotype in vitro. The co-culture of M2 macrophage and lung cancer cells was established to observe that inhibition of lung tumor growth by (−)-Guaiol requires presence of macrophages. This suppressed effect of (−)-Guaiol was alleviated when mice macrophage was depleted. The expression of M2-like macrophages was strongly reduced by (−)-Guaiol treated mice, but not the changes of M1-like macrophages. In vitro studies, we demonstrated that (−)-Guaiol suppressed M2 polarization of BMDMs, as well as migration, invasion, and EMT of lung cancer cells in co-culture. M2 macrophage-derived interleukin 10 (IL-10) was investigated as a critical signaling molecule between M2 macrophage and lung cancer cells. We have also verified that the mechanism of (−)-Guaiol inhibiting the EMT process of lung cancer is related to the activation of IL-10-mediated signal transducer and activator of transcription 3 (STAT3). These results suggested that the suppressive effect role of (−)-Guaiol in M2 macrophage promoting EMT of lung cancer, which was associated with inhibition of IL-10 mediated STAT3 signaling pathway.

Background: The novel coronavirus disease 2019 (COVID-19) has been spread widely in the world, causing a huge threat to the living environment of people.Objective: Under CT imaging, the structure features of COVID-19 lesions are complicated and varied greatly in different cases. To accurately locate COVID-19 lesions and assist doctors to make the best diagnosis and treatment plan, a deep-supervised ensemble learning network is presented for COVID-19 lesion segmentation in CT images.Methods: Since a large number of COVID-19 CT images and the corresponding lesion annotations are difficult to obtain, a transfer learning strategy is employed to make up for the shortcoming and alleviate the overfitting problem. Based on the reality that traditional single deep learning framework is difficult to extract complicated and varied COVID-19 lesion features effectively that may cause some lesions to be undetected. To overcome the problem, a deep-supervised ensemble learning network is presented to combine with local and global features for COVID-19 lesion segmentation.Results: The performance of the proposed method was validated in experiments with a publicly available dataset. Compared with manual annotations, the proposed method acquired a high intersection over union (IoU) of 0.7279 and a low Hausdorff distance (H) of 92.4604.Conclusion: A deep-supervised ensemble learning network was presented for coronavirus pneumonia lesion segmentation in CT images. The effectiveness of the proposed method was verified by visual inspection and quantitative evaluation. Experimental results indicated that the proposed method has a good performance in COVID-19 lesion segmentation.

In order to solve the immaturity of decision-making methods in the regulation of winter heating in greenhouses, this study proposed a solution to the problem of greenhouse winter heating regulation using a dynamic programming algorithm. A mathematical model that included indoor environmental state variables, optimization decision variables, and outdoor random variables was established. The temperature is kept close to the expected value and the energy consumption is low. The model predicts the control solution by considering the cost function within the next 10 steps. The two-stage planning method was used to optimize the state of each moment step by step. The temperature control strategy model was obtained by training the relationship between indoor temperature, outdoor temperature, and heating time after optimization using a regression algorithm. Based on a typical Internet of Things (IoT) structure, the greenhouse control system was designed to regulate the optimal control according to the feedback of the current environment. Through testing and verification, the optimized control method could stabilize the temperature near the target value. Compared to the threshold control (threshold interval of 2.0°C) under similar weather conditions, the optimized control method reduced the temperature fluctuation range by 0.9°C and saved 7.83 kW·h of electricity, which is about 14.56% of the total experimental electricity consumption. This shows that the dynamic programming method is feasible for environmental regulation in actual greenhouse production, and further research can be expanded in terms of decision variables and policy models to achieve a more comprehensive, scientific, and precise regulation. [ABSTRACT FROM AUTHOR]

Context • Lung squamous cell carcinoma (LUSC) accounts for 30% of non-small-cell lung cancers (NSCLC), and an effective pharmacological treatment for LUSC isn’t yet available. The Xihuang Pill is a potent Chinese medicinal preparation widely prescribed for the management of LUSC. Objective • The study intended to use the network-pharmacology method to ascertain the effective active ingredients, targets of action, and cellular-signal transduction involved in the prevention and treatment of LUSC when using the Xihuang Pill and to identify the mechanism of action of the pills against LUSC, to provide a more adequate scientific basis for subsequent studies. Design • The research team performed a genetic study. Setting • The study took place at Shanghai. Outcome Measures • The research team: (1) created the feature sets, for both the LUSC and normal features, using the Cancer Genome Atlas’ (TCGA’s) LUSC dataset; (2) performed a weighted correlation network analysis (WGCNA) of the differentially expressed genes (DEGs) using the R package WGCNA; (3) searched for the chemical components of the Xihuang Pill using the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform (TCMSP) and the Herb Group Identification Platform, and (4) selected the novel the Matthews correlation coefficient (MCC) algorithm to screen the hub genes. Results • The study found 8713 DEGs between the LUSC and normal groups. The top ten, important, downregulated genes included: (1) advanced glycosylation end product (AGER), (2) chitinase, acidic pseudogene 2 (CHIAP2), (3) CD300 molecule like family member G (CD300LG), (4) solute carrier family 6 member 4 (SLC6A4), (5) carboxypeptidase B2 (CPB2), (6) claudin 18 (CLDN18), (7) gamma-glutamyltransferase light chain 1 (GGTLC1), (8) gastrokine 2 (GKN2), (9) progastricsin (PGC), and (10) pulmonary surfactant-associated protein C (SFTPC). The top 10 upregulated genes included: (1) cancer susceptibility 9 (CASC9), (2) homeobox C13 (HOXC13), (3) keratin 6a (KRT6A), (4) desmoglein 3 (DSG3), (5) keratin 16 (KRT16), (6) forkhead box E1 (FOXE1), (7) preferentially expressed antigen in melanoma (PRAME), (8) calmodulin-like protein 3 (CALML3), (9) KRT68, and (10) aldo-keto reductase family 1 member B10 (AKR1B10). The study found 41 active ingredients and 843 targets for the Xihuang Pill. The PPI network included 10 hub genes, including cyclin dependent kinase 1 (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), pololike kinase 1 (PLK1), aurora kinase B (AURKB), baculoviral IAP repeat containing 5 (BIRC5), cyclin A2 (CCNA2), aurora kinase A (AURKA), centrosome-associated protein E (CENPE), and threonine tyrosine kinase (TTK), which were the principal target genes at the core of the gene-pathway network for the drug compound to central-target relationship. The enrichment analyses used the overlapping genes and the 10 hub genes and found 390 biological processes (BPs), 25 molecular functions (MFs), 43 cellular components (CCs), and 10 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The main enrichment occurred in the regulation of protein serine-threonine kinase activity, mitotic nuclear division, progesterone-mediated oocyte maturation, and the cell cycle. Conclusions • The study found the targets and relevant pathways of the hub genes of Xihuang Pill using biological analysis and molecular docking and demonstrated the interactions of critical chemical compounds with the hub’s targeted genes were. More research is necessary to further determine whether the Xihuang Pill can improve LUSC patients’ survival rate by regulation of those genes. [ABSTRACT FROM AUTHOR]