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The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-β signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.

Background: Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature based on long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of LUAD patients.Methods: We selected ARlncRNAs associated with prognosis to construct a model, and divided each sample into different groups based on risk score. Subsequently, Kaplan-Meier survival analysis was performed to investigate the survival outcomes of LUAD patients in different group. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis explored the enriched pathways and functions. Several bioinformatics analyses were conducted to explore the TIME of LUAD patients in different group.Results: The ARlncRNAs signature could be recognized as an independent prognostic factor for LUAD patients, and patients in the low-risk group had a greater survival advantage. GO and KEGG enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden (TMB). Low-risk patients had a higher PD-1, CTLA-4 and HAVCR2 expression, and had a better efficacy of immune checkpoint inhibitor (ICIs), including PD-1/CTLA-4 inhibitor.Conclusions: A reliable signature based on ARlncRNAs was constructed to explore the TIME and prognosis of LUAD patients, which could provide valuable information for individualized LUAD treatment.

Nanosecond laser-induced fabrication of superhydrophobic surfaces has become a research focus of functional surfaces studies in recent years. In this study, we present a novel and highly efficient method for fabricating a superhydrophobic functional aluminum alloy surface. The method is based on large spot diameter (d = 960 μm) infrared nanosecond laser high-speed (linear velocity v = 3 m/s) scanning and ablation of the surface followed by low surface energy agent chemical treatment to attain a superhydrophobic state on the aluminum alloy surface. The textured roughness surfaces show three specific micro-morphology characteristics including corrugated, mastoid and flat zones all densely covered by cauliflower-like nanostructures. The hierarchical micro- and nanostructured surfaces demonstrated outstandingly stable superhydrophobicity during long-term exposure to an ambient atmosphere. The proposed method proves that large spot diameter high-speed scanning low-cost nanosecond lasers are also suitable for fabrication of large area metallic superhydrophobic surfaces for practical industrial application.

There is currently no standard treatment for multiple primary lung cancer (MPLC). We report a case of synchronous MPLC presenting as one ground-glass opacity (GGO) with predominant consolidation accompanied by at least parietal pleura involvement, and another with >30 GGOs distributed across bilateral lungs, which was ineligible for complete resection. CT-guided percutaneous biopsy of the nearly pure-solid mass showed invasive lung adenocarcinoma mainly composed of acinar type. Capture-based, ultra-deep targeted sequencing (Burning Rock, Guangzhou, China) was performed on the tumor tissue biopsy. The result revealed no druggable mutations according to the guideline and a high TMB of 34.1 Mb. Immunohistochemical staining (22C3; Dako, Denmark) was positive for PD-L1 expression with a tumor expression level of 30%. Based on the clinical information and patient's decision, he received 3 cycles of pemetrexed plus pembrolizumab and was subsequently forced to withdraw due to acquired immune-related pneumonitis. After discontinuation of corticosteroids, he was subjected to wedge resection for the nearly pure-solid lesion, and then refused further treatment for the other tumors. After a follow-up of 12 months from termination of immunotherapy, almost all GGOs achieved radiographically complete remission, attributed to the tailing effect of the programmed cell death protein 1 (PD-1) antibody of pembrolizumab. Through the case study we found that unresectable synchronous MPLC presenting as GGOs may respond well to immunotherapy.

BACKGROUND: In clinical oncology, targeted next-generation sequencing (NGS) has become an integral part of the routine molecular diagnostics repertoire. However, a consensus is yet to be agreed on the optimal mesenchymal-epithelial transition factor (MET) copy number (CN) cut-off value based on NGS data that could predict the MET-amplified non-small cell lung cancer (NSCLC) patients who could benefit from MET tyrosine kinase inhibitor (TKI) therapy. In this study, we aimed to identify the criteria to define MET amplification derived from NGS data. METHODS: Sequencing data from matched plasma and tissue samples from 40 MET-amplified NSCLC patients were used to derive a normalization method, referred to as adjusted copy number (adCN). Clinical outcomes from an additional 18 MET TKI-treated NSCLC patients with solely MET-amplified cancers were analyzed to validate the adCN cut-offs. RESULTS: AdCN, calculated as the absolute CN generated from NGS relative to the maximum mutant allele fraction (maxMAF) per sample, was demonstrated to have a high correlation with MET CN in tissue and plasma samples (R(2)=0.73). Using a cut-off value of 5.5 and 13, tertile stratification of adCN was able to distinguish patients with high-level MET amplification. The MET TKI-treated patients with adCN >13, categorized as high-level amplification, had significantly longer progression-free survival (PFS) than those with adCN

Objective To study the effects of saikosaponin D (SSD) on proliferation and apoptosis in human non-small cell lung cancer cell lines, and to explore underlying mechanisms. Methods Following treatment with saikosaponin D, A549 and H1299 cells were assessed for anti-proliferation effects using cell cycle kit-8 assays, changes in nuclear morphology using 4′,6-diamidino-2-phenylindole (DAPI) staining, and cell apoptosis using annexin V/propidium iodide double staining. Proliferation- and apoptosis-related proteins were detected by immunoblotting. Results Saikosaponin D had dose-dependent inhibitory effects on A549 cells (IC50, 3.57 µM) and H1299 cells (IC50, 8.46 µM). DAPI staining revealed decreased cell numbers, and most H1299 cells became round after treatment with 20 µM saikosaponin D. As saikosaponin D concentration increased, the proportions of cells in G0/G1 phase, and cells undergoing apoptosis, increased. Levels of phosphorylated p44/42 and signal transducer and activator of transcription (STAT)3 were significantly downregulated in both cell lines, while total STAT3 levels were not significantly affected. The cleaved form of caspase 3 was significantly upregulated. Conclusions Saikosaponin D inhibits proliferation, inducing cell cycle arrest and apoptosis, in lung cancer cells in a dose-dependent manner, possibly through inhibition of STAT3 phosphorylation and activation of caspase 3.

This study examines the effects of changes in microphysical structure of dried bituminous coal soaked in water on its propensity to spontaneously combust. A scanning electron microscope (SEM) and low temperature liquid nitrogen adsorption experiments were used to determine the changes in specific surface area, total pore volume, average pore size, and approximate fracture dimensions in the coal samples. Experimental results show that compared with raw coal samples, pores and fractures on the surface of dried bituminous coal soaked in water are enlarged and the pores and fractures also increased in numbers. The results also show that, for dried bituminous coal soaked in water, specific surface area and total pore volume decrease, average pore size increases, and the connectivity of pores and fractures is improved. This contributes to increased oxygen adsorption and increases the risk of coal oxidation and spontaneous combustion of bituminous coal.

Background Crizotinib is a multi-target inhibitor approved for the treatment of advanced non-small-cell lung cancer patients with a ROS1 rearrangement. However, interstitial lung disease is a rare but severe and fatal side effect of crizotinib that should lead to immediate discontinuation of the drug. Unfortunately, the pathophysiology, molecular mechanism and risk factors for crizotinib-induced interstitial lung disease remain poorly understood. Case presentation We first identified and reported interstitial lung disease induced de novo by crizotinib in a 47-year-old female patient who was diagnosed with advanced lung adenocarcinoma with a ROS1 rearrangement in a malignant pleural effusion. Subsequent next-generation sequencing analysis revealed both ROS1 rearrangement and an EGFR exon 19 deletion mutation in lung biopsy specimens, which were histologically confirmed to be interstitial lung disease. Although crizotinib treatment was ceased immediately and a shock treatment with high-dose methylprednisolone as well as other necessary treatment procedures was applied to reverse the interstitial lung disease process, the patient died. Conclusions The present case indicates that while treating non-small-cell lung cancer patients with crizotinib, it is important to constantly monitor any newly emerging respiratory symptoms and unexplained imaging changes, which may suggest an adverse effect related to drug-induced interstitial lung disease or even lethality. Histopathology and molecular pathological examination of lung biopsy specimens may help clinicians understand the development mechanism and exclude other causes.

Patients with stage IV non-small cell lung cancer (NSCLC) comprise a heterogeneous group, and the optimal treatment for this group of patients is complex and debatable. We aimed to assess the effect of local thoracic therapy combined with chemotherapy on cancer specific survival (CSS). To evaluate the CSS of four subgroups of patients with stage IV NSCLC according to four different treatment modalities: combined modality of Chemotherapy, Surgery, and Radiation (Chem+Sur+RT), Chemotherapy and Radiation (Chem+RT), Chemotherapy and Surgery (Chem+Sur), and Chemotherapy only (Chem Only) by analyzing the Surveillance, Epidemiology, and End Results (SEER)-registered database. Kaplan-Meier methods were adopted and multivariable Cox regression models were built for the analysis of survival outcomes and risk factors. The 3-year CSS was 33.5% in "Chem+Sur+RT" group, 9.3% in "Chem+RT" group, 42.7% in "Chem+Sur" group and 11.8% in "Chem Only" group, which had significant difference in univariate log-rank test (P

In this paper, we focus on the challenge of demand-scalable multicast routing in wireless sensor networks. Due to the ad-hoc nature of the placement of the sensor nodes as well as the variations in the available power of the nodes, centralized or stateful routing schemes are not applicable. Thus, in this paper, we first introduce a Geographic Multicast routing Protocol (GMP) for wireless sensor networks. The protocol is fully distributed and stateless. Given a set of the destinations, the transmitting node first constructs a virtual Euclidean Steiner tree rooted at itself and including the destinations, using a novel and highly efficient reduction ratio heuristic (called rrSTR). The simulation results on NS2 show that GMP requires 25% less hops and energy than the existing Position Based Multicasting, PBM, Location-Guided Steiner trees, LGS, approaches. The GMP algorithm as well as LGS and PBM all assume that each recipient receives the same copy of the multicast message. In reality, however, especially when the transmission includes streamed media, different recipients have different demands (in terms of the frequency of packets or the quality of media). Thus, in this paper, we investigate the suitability of the geographic multicasting schemes for situations where scalable transmission paths can save power. In particular, we propose intuitive mechanisms to extend the three schemes to cases where the data transmission can scale based on the demand. This leads to three new weighted multicast routing algorithms: wGMP, wLGS, and wPBM. The results show that the wGMP algorithm provides the best opportunities for scalability due to its flexible self-correcting decision making process, while other schemes, such as wLGS and wPBM are not directly suitable for scalable multicasting, due to their naively greedy structures.

Nodes in a sensor network, operating on power limited batteries, must save power to minimize the need for battery replacement. We note that the range of transmission has a significant effect on the power consumption of both the transmitting node and listeners. This paper first presents a Geographical Power Efficient Routing (GPER) protocol for sensor networks. Each sensor node makes local decisions as to how far to transmit: therefore, the protocol is power efficient, localized, highly distributed, and scalable. In GPER, given a final destination, each node first establishes a subdestination within its maximum radio range. The node, however, may decide to relay the packet to this subdestination through an intermediary node or alter the subdestination if this will preserve power. Traditional deterministic geographic routing algorithms aim at achieving close to the shortest weighted paths. However, they normally stick to the same paths for the same source/destination pairs. This may conversely drain the nodes on these paths and result in short network life when the communication in the network is unevenly distributed. Thus, we further investigate a set of probabilistic multipath routing algorithms, which generate braided multipaths based only on local information. The algorithms have less communication and storage overhead than conventional on-demand multipath routing algorithms, while providing greater resilience to node failures. Simulations on NS2 show that GPER almost halves the power consumption in the network relative to alternative geographic routing algorithms. Furthermore, in situations where the communication tasks are non-uniformly distributed, probabilistic multipath routing contributes up to an additional 30% to network lifetime.

When the underground coal mine gob area has been sealed due to the coal spontaneous combustion, under the low oxygen and potentially high temperature environment, the CO concentration could drop sharply and disappear quickly. But it could rise rapidly after re-opening. These indicate that the disappearance is the only index for coal burnt out. In order to find a way how let CO disappear, experiments have been conducted using the newly developed experiment setup for three samples, raw, watered and bacteria-free coal sample. The CO and CO2 concentration have been monitored and analyzed. The results show the bacteria in the coal do consume CO and increase the chance of CO transfer to CO2. These results reveal how let CO disappear in a sealed zone from a new aspect. And the accuracy was improved when used gas index to determine combustion status for coal spontaneous combustion.

Nodes in a sensor network, operating on power limited batteries, must save power to minimize the need for battery replacement. In this paper, we study the power efficiency issues related to geographic broadcast protocols in wireless sensor networks. Specifically, we study the problems in existing flooding based and pruning based broadcast algorithm and propose a new geographic power efficient broadcast algorithm to reduce the overlaps of broadcast coverage area and thus the total power consumption. The proposed algorithm is a hybrid protocol that combines broadcasts of maximum transmission radio range and forwards of much smaller transmission radio range. Through simulation, we show that the GPEB protocol proposed in this paper can save total power consumption up to 23% compared to existing geographic broadcast protocols.

In this paper, we propose a novel Geographic Multicast routing Protocol (GMP) for wireless sensor networks1. The proposed protocol is fully distributed and stateless. Given a set of the destinations, the transmitting node first constructs a virtual Euclidean Steiner tree rooted at itself and including the destinations, using a novel and highly efficient reduction ratio heuristic (called rrSTR). Based on this locally computed tree and the information regarding the locations of its immediate neighbors, the transmitting node then splits the destinations into a set of groups and calculates a next hop for each of these groups. A copy of the packet and the locations of the corresponding group of destination nodes are directed towards the corresponding hop. The simulation results on NS2 show that the average per-destination hop count obtained using GMP is comparable to the existing PBM [21] algorithm and significantly less than obtained by using LGS [5]. Most significantly, GMP requires 25% less hops and energy than alternative algorithms.

This work presents a new geographical power efficient routing (GPER) protocol for sensor networks. Each sensor node makes local decisions as to how far to transmit: therefore, the protocol is power efficient, highly distributed and scalable. In GPER, given a final destination, each node first establishes a sub-destination within its maximum radio range. The node, however, may decide to relay the packet to this sub-destination through an intermediary node, if this preserves power. Furthermore, this intermediary node may act independently and alter the subdestination based on its own power range and neighborhood status. Simulation results show that the routing power consumption using GPER is close to optimal obtainable based on full knowledge of the network. GPER provides 60%-90% savings over other power-sensitive routing solutions. For sensor networks with highly varying node densities, we propose an extension, GPER-2, which captures the network topology better. Simulations show that although GPER works well, GPER-2 can improve on GPER up to 20%, especially when variations are large.