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ABSTRACTLactate plays an important role in shaping immune tolerance in tumor microenvironment (TME) and correlates with poor prognosis in various solid tumors. Overcoming the immune resistance in an acidic TME may improve the anti-tumor immunity. Here, this study elucidated that via G-protein-coupled receptor 81 (GPR81), lactate could modulate immune tolerance in TME by recruiting regulatory T cells (Tregs) in vitro and in vivo. A high concentration of lactate was detected in cell supernatant and tissues of gastric cancer (GC), which was modulated by lactic dehydrogenase A (LDHA). GPR81 was the natural receptor of lactate and was overexpressed in different GC cell lines and samples, which correlated with poor outcomes in GC patients. Lactate/GPR81 signaling could promote the infiltration of Tregs into TME by inducing the expression of chemokine CX3CL1. GPR81 deficiency could decrease the infiltration of Tregs into TME, thereby inhibiting GC progression by weakening the inhibition of CD8+T cell function in a humanized mouse model. In conclusion, targeting the lactate/GPR81 signaling may potentially serve as a critical process to overcome immune resistance in highly glycolytic GC.

ABSTRACTThe gut microbiota and Short-chain fatty acids (SCFAs) can influence the progression of diseases, yet the role of these factors on gastric cancer (GC) remains uncertain. In this work, the analysis of the gut microbiota composition and SCFA content in the blood and feces of both healthy individuals and GC patients indicated that significant reductions in the abundance of intestinal bacteria involved in SCFA production were observed in GC patients compared with the controls. ABX mice transplanted with fecal microbiota from GC patients developed more tumors during the induction of GC and had lower levels of butyric acid. Supplementation of butyrate during the induction of gastric cancer along with H. pylori and N-methyl-N-nitrosourea (MNU) in WT in GPR109A−/−mice resulted in fewer tumors and more IFN-γ+ CD8+ T cells, but this effect was significantly weakened after knockout of GPR109A. Furthermore, In vitro GC cells and co-cultured CD8+ T cells or CAR-Claudin 18.2+ CD8+ T cells, as well as in vivo tumor-bearing studies, have indicated that butyrate enhanced the killing function of CD8+ T cells or CAR-Claudin 18.2+ CD8+ T cells against GC cells through G protein-coupled receptor 109A (GPR109A) and homologous domain protein homologous box (HOPX). Together, these data highlighted that the restoration of gut microbial butyrate enhanced CD8+ T cell cytotoxicity via GPR109A/HOPX, thus inhibiting GC carcinogenesis, which suggests a novel theoretical foundation for GC management against GC.

Gastrointestinal cancer is among the most common cancers worldwide. Immune checkpoint inhibitor-based cancer immunotherapy has become an innovative approach in cancer treatment; however, its efficacy in gastrointestinal cancer is limited by the absence of infiltration of immune cells within the tumor microenvironment. Therefore, it is therefore urgent to develop a novel therapeutic drug to enhance immunotherapy. In this study, we describe a previously unreported potentiating effect of Icariside I (ICA I, GH01), the main bioactive compound isolated from the Epimedium species, on anti-tumor immune responses. Mechanistically, molecular docking and SPR assay result show that ICA I binding with TRPV4. ICA I induced intracellular Ca2+ increasing and mitochondrial DNA release by targeting TRPV4, which triggered cytosolic ox-mitoDNA release. Importantly, these intracellular ox-mitoDNA fragments were taken up by immune cells in the tumor microenvironment, which amplified the immune response. Moreover, our study shows the remarkable efficacy of sequential administration of ICA I and anti-α-PD-1 mAb in advanced tumors and provides a strong scientific rationale for recommending such a combination therapy for clinical trials. ICA I enhanced the anti-tumor effects with PD-1 inhibitors by regulating the TRPV4/Ca2+/Ox-mitoDNA/cGAS/STING axis. We expect that these findings will be translated into clinical therapies, which will benefit more patients with cancer in the near future.

The soybean cyst nematode (SCN), Heterodera glycines Ichinohe, 1952, is one of the most destructive plant-parasitic nematodes in soybean production worldwide. The use of resistant soybean is the most effective alternative for its management. However, SCN-resistant soybean cultivars with increased yield and favorable agronomic traits remain limited in the market. Here, we developed a new SCN-resistant soybean cultivar Nongqing 28 from the cross of the female parent cultivar An 02-318 and a male parent line F2 (Hei 99-980 × America Xiaoheidou). Resistance evaluation suggested that Nongqing 28 displayed stable resistance to SCN race 3 in pot assays and the 5-year field experiments, including inhibition of SCN development and reduction in female and cyst numbers. The average yields of Nongqing 28 were 2593 kg/ha and 2660 kg/ha in the 2-year regional trails and the 1-year production trials, with a yield increase of 6.2% and 8.1% compared with the local cultivar Nengfeng 18, respectively. The average seed fat contents in Nongqing 28 reached 21.26%. Additionally, RNA-seq analysis revealed that the resistance of Nongqing 28 to SCN infection is involved in pathogen perception and defense activation, such as reactive oxygen species burst, calcium-mediated defense signaling, hormonal signaling, the MAPK signaling cascade, and phenylpropanoid biosynthesis. In summary, this study provides a detailed characterization of a novel SCN-resistant soybean cultivar with high oil and yield potential.

Bipolaris sorokiniana, one of the most devastating hemibiotrophic fungal pathogens, causes root rot, crown rot, leaf blotching, and black embryos of gramineous crops worldwide, posing a serious threat to global food security. However, the host-pathogen interaction mechanism between B. sorokiniana and wheat remains poorly understood. To facilitate related studies, we sequenced and assembled the genome of B. sorokiniana LK93. Nanopore long reads and next generation sequencing short reads were applied in the genome assembly, and the final 36.4-Mb genome assembly contains 16 contigs with the contig N50 of 2.3 Mb. Subsequently, we annotated 11,811 protein-coding genes. Of these, 10,620 were functional genes, 258 of which were identified as secretory proteins, including 211 predicted effectors. Additionally, the 111,581-bp mitogenome of LK93 was assembled and annotated. The LK93 genomes presented in this study will facilitate research in the B. sorokiniana–wheat pathosystem for better control of crop diseases. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Gastric cancer (GC) is a serious disease with high morbidity and mortality rates worldwide. Chemotherapy plays a key role in GC treatment, while inevitable drug resistance and systematic side effects hinder its clinical application. Fenton chemistry-based chemodynamic therapy (CDT) has been used as a strategy for cancer ferroptosis, and the CDT efficiency could be enhanced by photothermal therapy (PTT). With the trend of treatment and diagnosis integration, the combination of magnetic resonance imaging (MRI) and CDT/PTT exhibits enormous progress. Herein, we constructed a platform based on PEGylated manganese-containing polydopamine (PDA) nanoparticles, named as PEG-PDA@Mn (PP@Mn) NPs. The PP@Mn NPs were stable and globular. Furthermore, they demonstrated near-infrared (NIR)-triggered PTT and Fenton-like reaction-based CDT effects and T1-weighted MRI capabilities. According to in vitro studies, the PP@Mn NPs trigger ferroptosis in cancer cells by producing abundant reactive oxygen species (ROS) via a Fenton-like reaction combined with PTT. Furthermore, in vivo studies showed that, under MRI guidance, the PP@Mn NPs combined with the PTT at the tumor region, have CDT anti-tumor effect. In conclusion, the PP@Mn NPs could provide an effective strategy for CDT/PTT synergistic ferroptosis therapy for GC.

The cytochrome P450 (CYP) genes of nematode play a crucial role in the metabolic detoxification of xenobiotics including pesticides. Heterodera glycines, also known as the soybean cyst nematode, is a sedentary endoparasite that infests plant roots, causing high annual economic losses in soybean production regions globally. In this study, we identified 36 CYP genes at a genome-wide level of the H. glycines isolate TN10 using all CYPs from Caenorhabditis elegans as queries. Subsequently, a full-length cDNA of HgCYP33E1 which was significantly up-regulated by the conventional nematicide abamectin was initially cloned from H. glycines. It presented significantly higher expressions in the second-stage juvenile (J2) compared to other parasitic stages of H. glycines. qRT-PCR analysis suggested that the expression of HgCYP33E1 was also xenobiotically induced by soybean root exudate and the metabolites of biocontrol agents. Using RNA interference (RNAi), we investigated the function of HgCYP33E1 in H. glycines parasitism and nematicide selectivity. Compared to the control and dsGFP-treated group, silencing of HgCYP33E1 did not affect the J2 behaviors and the early invasion ability, while it decreased the number of J4s in soybean roots after 18-d inoculation with the dsHgCYP33E1-treated nematodes. In addition, knockdown of HgCYP33E1 in H. glycines resulted in an increase in J2 mortality after 24-h incubation with abamectin compared to the GFP dsRNA-soaked and the control group. These findings revealed the potential role of HgCYP33E1 in the xenobiotic detoxification pathway of H. glycines. Moreover, our data also provided valuable gene information for studying the functions of the CYP family in H. glycines host adaption.

Abstract Anti‐angiogenic therapy has long been considered a promising strategy for solid cancers. Intrinsic resistance to hypoxia is a major cause for the failure of anti‐angiogenic therapy, but the underlying mechanism remains unclear. Here, it is revealed that N4‐acetylcytidine (ac4C), a newly identified mRNA modification, enhances hypoxia tolerance in gastric cancer (GC) cells by promoting glycolysis addiction. Specifically, acetyltransferase NAT10 transcription is regulated by HIF‐1α, a key transcription factor of the cellular response to hypoxia. Further, acRIP‐sequencing, Ribosome profiling sequencing, RNA‐sequencing, and functional studies confirm that NAT10 in turn activates the HIF‐1 pathway and subsequent glucose metabolism reprogramming by mediating SEPT9 mRNA ac4C modification. The formation of the NAT10/SEPT9/HIF‐1α positive feedback loop leads to excessive activation of the HIF‐1 pathway and induces glycolysis addiction. Combined anti‐angiogenesis and ac4C inhibition attenuate hypoxia tolerance and inhibit tumor progression in vivo. This study highlights the critical roles of ac4C in the regulation of glycolysis addiction and proposes a promising strategy to overcome resistance to anti‐angiogenic therapy by combining apatinib with ac4C inhibition.

Summary: Most gastric cancer (GC) patients with early stage often have no lymph node (LN) metastases, while LN metastases appear in the advanced stage. However, there are some patients who present with early stage LN metastases and no LN metastases in the advanced stage. To explore the deeper molecular mechanisms involved, we collected clinical samples from early and advanced stage GC with and without LN metastases, as well as metastatic lymph nodes. Herein, we identified a key target, HOXA11, that was upregulated in GC tissues and closely associated with lymphatic metastases. HOXA11 transcriptionally regulates TGFβ1 expression and activates the TGFβ1/Smad2 pathway, which not only promotes EMT development but also induces VEGF-C secretion and lymphangiogenesis. These findings provide a plausible mechanism for HOXA11-modulated tumor in lymphatic metastasis and suggest that HOXA11 may represent a potential therapeutic target for clinical intervention in LN-metastatic gastric cancer.

The integration of geospatial-analysis models is crucial for simulating complex geographic processes and phenomena. However, compared to non-geospatial models and traditional geospatial models, geospatial-analysis models face more challenges owing to extensive geographic data processing and complex computations involved. One core issue is how to eliminate model heterogeneity to facilitate model combination and capability integration. In this study, we propose a containerized service-based integration framework named GeoCSIF, specifically designed for heterogeneous-geospatial-analysis models. Firstly, by designing the model-servicized structure, we shield the heterogeneity of model structures so that different types of geospatial-analysis models can be effectively described and integrated based on standardized constraints. Then, to tackle the heterogeneity in model dependencies, we devise a prioritization-based orchestration method, facilitating optimized combinations of large-scale geospatial-analysis models. Lastly, considering the heterogeneity in execution modes, we design a heuristic scheduling method that establishes optimal mappings between models and underlying computational resources, enhancing both model stability and service performance. To validate the effectiveness and progressiveness of GeoCSIF, a prototype system was developed, and its integration process for flood disaster models was compared with mainstream methods. Experimental results indicate that GeoCSIF possesses superior performance in model management and service efficiency.

Tumour microenvironment has been linked with immunotherapy response in gastric cancer. Here, the authors use CT-based radiomics to predict neutrophils-to-lymphocyte ratio and response to immunotherapy.

Abstract Chemoresistance remains the primary challenge of clinical treatment of gastric cancer (GC), making the biomarkers of chemoresistance crucial for treatment decision. Our previous study has reported that p21-actived kinase 6 (PAK6) is a prognostic factor for selecting which patients with GC are resistant to 5-fluorouracil/oxaliplatin chemotherapy. However, the mechanistic role of PAK6 in chemosensitivity remains unknown. The present study identified PAK6 as an important modulator of the DNA damage response (DDR) and chemosensitivity in GC. Analysis of specimens from patients revealed significant associations between the expression of PAK6 and poorer stages, deeper invasion, more lymph node metastases, higher recurrence rates, and resistance to oxaliplatin. Cells exhibited chemosensitivity to oxaliplatin after knockdown of PAK6, but showed more resistant to oxaliplatin when overexpressing PAK6. Functionally, PAK6 mediates cancer chemoresistance by enhancing homologous recombination (HR) to facilitate the DNA double-strand break repair. Mechanistically, PAK6 moves into nucleus to promote the activation of ATR, thereby further activating downstream repair protein CHK1 and recruiting RAD51 from cytoplasm to the DNA damaged site to repair the broken DNA in GC. Activation of ATR is the necessary step for PAK6 mediated HR repair to protect GC cells from oxaliplatin-induced apoptosis, and ATR inhibitor (AZD6738) could block the PAK6-mediated HR repair, thereby reversing the resistance to oxaliplatin and even promoting the sensitivity to oxaliplatin regardless of high expression of PAK6. In conclusion, these findings indicate a novel regulatory mechanism of PAK6 in modulating the DDR and chemoresistance in GC and provide a reversal suggestion in clinical decision.

Radiotherapy (RT) incorporated multidisciplinary treatment is producing excellent clinical results, but its efficacy in treating late-stage gastric cancer is constrained by radioresistance and RT-related toxicity. Especially, since reactive oxygen species are the pivotal effectual molecules of ionizing radiation, improving ROS production by nanoparticles and other pharmacological modulation to amplify oxidation of polyunsaturated fatty acids and subsequent ferroptotic cell death is shown to enhance cancer cell radioresponse. Herein, we constructed a nanosystem by loading Pyrogallol (PG), a polyphenol compound and ROS generator, into mesoporous organosilica nanoparticles named as MON@pG. The nanoparticles exhibit proper size distribution with amplified ROS production and substantial glutathione depletion under X-ray radiation in gastric cancer cell line. Meanwhile, MON@PG enhanced radiosensitivity of gastric cancer in xenograft tumor model by ROS-mediated accumulation of DNA damage and apoptosis. Furthermore, this augmented oxidative process induced mitochondrial dysfunction and ferroptosis. In summary, MON@PG nanoparticles show the capacity to improve RT potency in gastric cancer by disrupting redox balance and augmenting ferroptosis.

Abstract. Background:. Previous studies have revealed that diabetes mellitus (DM) promotes disease progress of gastric cancer (GC). This study aimed to further investigating whether DM advanced lymph nodes (LNs) metastasis in GC. Methods:. The clinicopathologic data of GC patients with >15 examined LN (ELN) between October 2004 and December 2019 from a prospectively maintained database were included. The observational outcomes included the number (N3b status) and anatomical distribution (N3 stations) of metastatic LN (MLN). Results:. A total of 2142 eligible patients were included in the study between October 2004 and December 2019. N3 stations metastasis (26.8% in DM vs. 19.3% in non-DM, P = 0.026) and N3b status (18.8% in DM vs. 12.8% in non-DM, P = 0.039) were more advanced in the DM group, and multivariate logistic regression analyses confirmed that DM was an independent factor of developing N3 stations metastasis (odds ratio [OR] = 1.771, P = 0.011) and N3b status (OR = 1.752, P = 0.028). Also, multivariate analyses determined DM was independently associated with more MLN (β = 1.424, P = 0.047). The preponderance of N3 stations metastasis (DM vs. non-DM, T1–2: 2.2% vs. 4.9%, T3: 29.0% vs. 20.3%, T4a: 38.9% vs. 25.8%, T4b: 50.0% vs. 36.6%; ELN16–29: 8.6% vs. 10.4%, ELN30–44: 27.9% vs. 20.5%, ELN ≥ 45: 37.7% vs. 25.3%), N3b status (DM vs. non-DM, T1–2: 0% vs. 1.7%, T3: 16.1% vs. 5.1%, T4a: 27.8% vs. 19.1%, T4b: 44.0% vs. 28.0%; ELN16–29: 8.6% vs. 7.9%, ELN30–44: 18.0% vs. 11.8%, ELN ≥ 45: 26.4% vs. 17.3%), and the number of MLN (DM vs. non-DM, T1–2: 0.4 vs. 1.1, T3: 8.6 vs. 5.2, T4a: 9.7 vs. 8.6, T4b: 17.0 vs. 12.8; ELN16–29: 3.6 vs. 4.6, ELN30–44: 5.8 vs. 5.5, ELN ≥ 45: 12.0 vs. 7.7) of DM group increased with the advancement of primary tumor depth stage and raising of ELN. Conclusions:. DM was an independent risk factor for promoting LN metastasis. The preponderance of LN involvement in the DM group was aggravated with the advancement of tumor depth.

Abstract The Global Navigation Satellite System (GNSS) traditional dual‐frequency cycle slip detection and repair methods such as the TurboEdit algorithm are restricted by the availability and accuracy of pseudorange observations. Doppler observations represent the instantaneous variation of the carrier phase during the integration time, which are immune to cycle slips. They are less affected by multipath effects compared with the pseudorange observations. Hence, a real‐time cycle slip detection and repair approach for the BeiDou Navigation Satellite System (BDS) dual‐frequency signals is proposed by combining the carrier phase and Doppler observations. The proposed method adopts the phase‐Doppler combination and the geometry‐free combination to detect cycle slips, and uses the simple rounding method or the dual‐frequency least‐square ambiguity decorrelation adjustment (LAMBDA) method to repair cycle slips. The validity of the proposed method is verified by the static and kinematic observation data under 1 s sampling interval and steady ionosphere. The results show that the new method can successfully detect all the small, insensitive, and large cycle slips. Moreover, the fixing rates of the simple rounding method under static and kinematic conditions are above 94% and 83%, respectively, while those of the dual‐frequency LAMBDA method are both 100%.

Digestive tract-related cancers account for four of the top ten high-risk cancers worldwide. In recent years, cancer immunotherapy, which exploits the innate immune system to attack tumors, has led to a paradigm shifts in cancer treatment. Gut microbiota modification has been widely used to regulate cancer immunotherapy. Dietary compounds and traditional Chinese medicine (TCM) can alter the gut microbiota and its influence on toxic metabolite production, such as the effect of iprindole on lipopolysaccharide (LPS), and involvement in various metabolic pathways that are closely associated with immune reactions. Therefore, it is an effective strategy to explore new immunotherapies for gastrointestinal cancer to clarify the immunoregulatory effects of different dietary compounds/TCMs on intestinal microbiota. In this review, we have summarized recent progress regarding the effects of dietary compounds/TCMs on gut microbiota and their metabolites, as well as the relationship between digestive cancer immunotherapy and gut microbiota. We hope that this review will act as reference, providing a theoretical basis for the clinical immunotherapy of digestive cancer via gut microbiota modulation.

BackgroundImmune checkpoint inhibitors (ICIs) have been increasingly used for the treatment of advanced gastric cancer (AGC). However, the safety and the short-term outcomes of laparoscopic gastrectomy for patients with AGC after neoadjuvant immunotherapy (NAI) remain unknown.MethodsWe retrospectively analyzed the patients with AGC who underwent laparoscopic surgery after neoadjuvant therapy between 1 January 2019 and 31 October 2021. We further compared the differences in postoperative complications, overall response rate, adverse events, surgical parameters, and postoperative recovery between two cohorts: the NAI group (NAI plus chemotherapy) and the neoadjuvant chemotherapy (NAC) group. Multivariable regression analyses were used to determine the risk factors for the overall response rate.ResultsOverall, 80 patients were enrolled, of whom 30 cases were included in the NAI cohort and 50 were included in the NAC cohort. The overall rate of postoperative complications was 30.0% in both groups (p = 1.000). The overall response rate was 70.0% in the NAI cohort and 40% in the NAC cohort (p = 0.012). The adverse effects were found in 16 cases (53.3%) of the NAI cohort and 23 cases (46.0%) of the NAC cohort (p = 0.645). There was no statistical difference in intraoperative bleeding (50 ml vs. 50 ml, p = 0.983), operation time (320.9 min vs. 303.5 min, p = 0.382), dissected lymph node count (43.5 vs. 40.0, p = 0.364), first postoperative anal aerofluxus (3 days vs. 3 days, p = 0.091), first liquid diet (4 days vs. 5 days, p = 0.213), and postoperative length of stay in the hospital (8 days vs. 7 days, p = 0.508) between the two groups. NAI was estimated to be the independent protective factor [odds ratio (OR) 4.931, 95% confidence interval (CI) (1.385–17.559), p = 0.014] for odds to overall response rate, whereas vessel invasion was found to be the significant risk factor [OR 0.113, 95% CI (0.027–0.475), p = 0.003].ConclusionsLaparoscopic surgery after NAI combined with chemotherapy is a safe therapeutic choice for AGC and may bring better short-term outcomes due to a higher overall response rate.

Root-knot nematodes (RKNs; Meloidogyne spp.), one of the most economically important plant-parasitic nematodes (PPNs), cause severe yield and quality losses in agriculture annually. The application of biological control agents is an environmentally safe and effective approach to control RKNs. Here, we report the genomic characteristics of a Bacillus velezensis strain YS-AT-DS1 (Bv-DS1) isolated from the tidal soil, revealing that it has a 4.73 Mb circular chromosome with an average GC-content of 46.43%, 3,977 genes, 86 tRNAs, and 27 rRNAs, and contains secondary metabolite clusters for producing antimicrobial compounds. In vitro assays indicated that Bv-DS1 has not only antagonistic activities against fungal pathogens, but also shows nematicidal activity, with a mortality rate of 71.62% mortality rates in second-stage juvenile (J2s) Meloidogyne incognita. We then focused on the biocontrol efficiency of Bv-DS1 against M. incognita in pot assays. Preinoculation with Bv-DS1 enhanced tomato growth, and significantly reduced the infection rate of J2s, and the number of galls and egg masses on tomato roots. The underlying mechanism in Bv-DS1-induced resistance to M. incognita was further investigated through split-root experiments, and analysing the expression of the genes related to jasmonic acid (JA), salicylic acid (SA), and the tonoplast intrinsic protein (TIP). The results indicated that Bv-DS1 could not activate host systemic-induced resistance (ISR) in the split-root system of tomatoes. Additionally, the expression of JA- (LOX D and MC) and SA- (PAL2 and PR) responsive genes did not change in Bv-DS1-pretreated plants at 3 and 14 days after nematode inoculation. The presented data showed that JA-and SA-dependent pathways were not required for the biocontrol action of the Bv-DS1 against RKN. The TIP genes, responsible for transport of water and small substrates in plants, have previously been shown to negatively regulate the parasitism of PPNs. Surprisingly, Bv-DS1 compromised the downregulation of TIP1.1 and TIP1.3 by M. incognita. Together, our data suggest that Bv-DS1 exhibits a dual effect on plant growth promotion and protection against RKN, possibly related to the regulation of water and solute transport via TIPs. Thus, the Bv-DS1 strain could be used as a biocontrol agent for RKN control in sustainable agriculture.

Summary: Background: Exitron is a new type of non-canonical alternative splicing. Accumulating evidence implies exitron may have pathological function and contribute to another source of anti-tumor immunogenicity in various cancers. Its role in gastric cancer remains poorly understood. Large-scale, multi-omics analysis could comprehensively characterize the landscape of exitrons in gastric cancer, reveal undiscovered mechanism and hopefully identify molecular biomarkers for predicting immunotherapy response. Methods: We collected datasets from five studies for analysis. RNA sequencing was used for exitron identification. Somatic mutations were detected by whole exome sequencing. Neopeptides were confirmed by proteome mass spectrometry. Findings: 42174 gastric cancer-specific exitrons (GCSEs) were identified in 632 patients. GCSEs were clinically relevant to gender, age, Lauren type, tumor stage and prognosis. Tissue specificity test and pathogenic exitron prediction revealed their unique functional impact. GCSEs were mutually exclusive with mutations and demonstrated both unique and complementary function against TP53 mutation in gastric cancer. We further established splicing regulatory network to reveal upstream regulation of exitron splicing. We also evaluated the immunogenicity and diagnostic potential of GCSEs. Evidence of GCSEs-derived neopeptide expression was validated by whole proteome mass spectrometry. PD-1 and Siglecs were significantly increased in high neoantigen load patients. But exitron-related biomarkers failed to predict immunotherapy response, possibly due to small sample size and insufficient sequencing depth. Interpretation: The present study provided a comprehensive multidimensional landscape of gastric cancer exitrons and underscores insights into underexplored mechanism in gastric cancer pathology. Funding: The Guangdong Provincial Key Laboratory of Precision Medicine for Gastroinstestinal Cancer (2020B121201004), the Guangdong Provincial Major Talents Project (No. 2019JC05Y361) and National Natural Science Foundation of China (grant number:82172960 and 81872013).

Nematodes, which are highly important and abundant animals in the animal kingdom, demonstrate remarkable adaptability to various environments [...]

Abstract Background Paclitaxel (PTX) has been suggested to be a promising front-line drug for gastric cancer (GC), while P-glycoprotein (P-gp) could lead to drug resistance by pumping PTX out of GC cells. Consequently, it might be a hopeful way to combat drug resistance by inhibiting the out-pumping function of P-gp. Results In this study, we developed a drug delivery system incorporating PTX onto polyethylene glycol (PEG)-modified and oxidized sodium alginate (OSA)-functionalized graphene oxide (GO) nanosheets (NSs), called PTX@GO-PEG-OSA. Owing to pH/thermal-sensitive drug release properties, PTX@GO-PEG-OSA could induced more obvious antitumor effects on GC, compared to free PTX. With near infrared (NIR)-irradiation, PTX@GO-PEG-OSA could generate excessive reactive oxygen species (ROS), attack mitochondrial respiratory chain complex enzyme, reduce adenosine-triphosphate (ATP) supplement for P-gp, and effectively inhibit P-gp’s efflux pump function. Since that, PTX@GO-PEG-OSA achieved better therapeutic effect on PTX-resistant GC without evident toxicity. Conclusions In conclusion, PTX@GO-PEG-OSA could serve as a desirable strategy to reverse PTX’s resistance, combined with chemo/photothermal/photodynamic therapy. Graphic Abstract

With the development and popularization of remote sensing earth observation technology and the remote sensing satellite system, the problems of insufficient proactiveness, relevance and timeliness of large-scale remote sensing supporting services are increasingly prominent, which seriously restricts the application of remote sensing resources in multi-domain and cross-disciplinary. It is urgent to help terminal users make appropriate decisions according to real-time network environment and domain requirements, and obtain the optimal resources efficiently from the massive remote sensing resources. In this paper, we propose a recommendation algorithm using fusion of attention and multi-perspective (MRS_AMRA). Based on MRS_AMRA, we further implement an active service recommendation model (MRS_ASRM) for massive multi-source remote sensing resources by combining streaming pushing technology. Firstly, we construct value evaluation functions from multi-perspective in terms of remote sensing users, data and services to enable the adaptive provision of remote sensing resources. Then, we define multi-perspective heuristic policies to support resource discovery, and fusion these policies through the attention network, to achieve the accurate pushing of remote sensing resources. Finally, we implement comparative experiments to simulate accurate recommendation scenarios, compared with state-of-the-art algorithms, such as DIN and Geoportal. Furthermore, MRS_AMRA achieves an average improvement of 10.5% in the recommendation accuracy NDCG@K, and in addition, we developed a prototype system to verify the effectiveness and timeliness of MRS_ASRM.

Abstract Background The benefits of adjuvant chemotherapy for elderly patients with gastric cancer (GC) remain unknown because elderly patients are underrepresented in most clinical trials. This study aimed to evaluate the effectiveness and complications of adjuvant chemotherapy in patients > 65 years of age after laparoscopic D2 gastrectomy. Methods This was a single-center retrospective cohort study of elderly patients (> 65 years) with stage II/III GC who underwent curative laparoscopic D2 gastrectomy with R0 resection between 2004 and 2018. The adjuvant chemotherapy regimens included monotherapy (oral capecitabine) and doublet chemotherapy (oral capecitabine plus intravenous oxaliplatin [XELOX] or intravenous oxaliplatin, leucovorin, and 5-fluorouracil [FOLFOX]). The data were retrieved from a prospectively registered database maintained at the Department of General Surgery in Nanfang Hospital, China. The patients were divided as surgery alone and surgery plus adjuvant chemotherapy (chemo group). The overall survival (OS), disease-free survival (DFS), chemotherapy duration, and toxicity were examined. Results There were 270 patients included: 169 and 101 in the surgery and chemo groups, respectively. There were 10 (10/101) and six (6/101) patients with grade 3+ non-hematological and hematological adverse events. The 1−/3−/5-year OS rates of the surgery group were 72.9%/51.8%/48.3%, compared with 90.1%/66.4%/48.6% for the chemo group (log-rank test: P = 0.018). For stage III patients, the 1−/3−/5-year OS rates of the surgery group were 83.7%/40.7%/28.7%, compared with 89.9%/61.2%/43.6% for the chemo group (log-rank test: P = 0.015). Adjuvant chemotherapy was significantly associated with higher OS (HR = 0.568, 95%CI: 0.357–0.903, P = 0.017) and DFS (HR = 0.511, 95%CI: 0.322–0.811, P = 0.004) in stage III patients. Conclusions This study suggested that adjuvant chemotherapy significantly improves OS and DFS compared with surgery alone in elderly patients with stage III GC after D2 laparoscopic gastrectomy, with a tolerable adverse event profile.

Background: The enhanced recovery after surgery (ERAS) programme is feasible and effective in reducing the length of hospital stay, overall complication rates and medical costs when applied to cases involving colonic and rectal resections. However, a recent prospective, randomised, open, parallel-controlled trial (Chinese Laparoscopic Gastrointestinal Surgery Study-01 trial), initiated by our team, indicated that under conventional peri-operative management, the reduction of the post-operative hospital stay of laparoscopic distal gastrectomy (LDG) is quite limited compared with open gastrectomy. Thus, if we could provide valuable clinical evidence for demonstrating the efficacy of the ERAS programme for gastric cancer patients undergoing LDG, it would significantly enhance the peri-operative management of gastrectomy and benefit the patients. Methods: In this prospective single-arm trial, patients who are 18–75 years of age with gastric adenocarcinoma diagnosed with cT1-4aN0-3M0 and expected to undergo curative resection through LDG, are considered eligible for this study. All participants underwent LDG with peri-operative management under the ERAS programme. The primary outcome measures included the post-operative hospital stays and rehabilitative rate of the post-operative day 4. The secondary outcome measures are morbidity and mortality (time frame: 30 days), post-operative recovery index (time frame: 30 days), post-operative pain intensity (time frame: 3 days) and the medical costs from surgery to discharge. Conclusion: With reasonable and scientific designing, the trial may be a great help to further discuss the benefit of ERAS programme and thus improving the peri-operative management of patients with gastrectomy.

Dependency analysis can assist neural networks to capture semantic features within a sentence for entity relation extraction (RE). Both hard and soft strategies of encoding dependency tree structure have been developed to balance the beneficial extra information against the unfavorable interference in the task of RE. A wide application of graph convolutional network (GCN) in the field of natural language processing (NLP) has demonstrated its effectiveness in encoding the input sentence with the dependency tree structure, as well as its efficiency in parallel computation. This study proposes a novel GCN-based model using multiple representations to depict the dependency tree from various perspectives, and combines those dependency representations afterward to obtain a better sentence representation for relation classification. This model can maximally draw from the sentence the semantic features relevant to the relationship between entities. Results show that our model achieves state-of-the-art performance in terms of the F1 score (68.0) on the Text Analysis Conference relation extraction dataset (TACRED). In addition, we verify that the renormalization parameter in the GCN operation should be carefully chosen to help GCN-based models achieve its best performance.

With the rapid development of cloud computing and container technology, more and more applications are deployed to the cloud, and the scale of cloud platform is expanding. Due to the large number of container instances running in the platform, complex dependency relationship, fast version iteration and other characteristics, the update of business can often cause the change of the whole cloud resource environment, which triggers the repetitive scheduling problem of related tasks and affects stability of the business. In this paper, we propose a self-adapting task scheduling algorithm (ADATSA) using learning automata to solve these problems. Firstly, we design a learning automata model and objective function for the system on task scheduling problem. Then, we realize an effective reward-penalty mechanism for scheduling actions in combination with the idle state of resources and the running state of tasks in the current environment. Meanwhile, the environment is modeled by cluster, node and task, and the probability of action selected is optimized by scheduling execution, thus enhancing the adaptability to the cloud environment of the scheduling and accelerating convergence. Finally, we construct a framework of task load monitoring with buffer queue to achieve dynamic scheduling based on priority. The experimental part verifies the effectiveness of proposed algorithm with different angles such as resource imbalance degree, resource residual degree and QoS. Compared with other learning automata scheduling models such as LAEAS, non-automata technology based algorithms such as PSOS and K8S scheduling engine, ADATSA shows the better performance of environment adaptability, resource optimization efficiency and QoS in dynamic scheduling. The theoretical analysis was consistent with the experimental results.

A cell-free massive multiple-input multiple-output (MIMO) network-assisted full-duplex (NAFD) system has been proposed to satisfy the exploding demand of higher data transmission speed and more efficient communication. However, a growing number of users in a cell-free system inevitably leads to pilot contamination. In this paper, we analyze the ergodic spectral efficiency of cell-free massive MIMO NAFD system in the presence of pilot contamination. The cell-free massive MIMO NAFD system model has been investigated and both uplink and downlink channel state information (CSI) is estimated under spatially correlated channels. Under pilot contamination, the closed-form sum-rate expressions of the uplink with maximum ratio combination (MRC) receiver while downlink with maximum ratio transmission (MRT), and uplink with zero-forcing (ZF) receiver while downlink with ZF precoding schemes are derived based on large-scale random matrix theory. Numerical results show that under several environmental settings, the theoretical results match well with the simulated results and cell-free massive MIMO NAFD system has a better performance than time-division duplex (TDD) system. Moreover, simulation results show that the achievable sum-rate of using ZF/ZF could be more spectrally efficient compared to MRC/MRT because of its interference suppression capability.

Fine-grained entity typing, which aims to assign specific types to entity mentions in text, is attracting increasing attention in the field of natural language processing (NLP). However, it is quite a challenging problem due to the highly ambiguous nature of many entity mentions. Most existing entity typing methods based on attention mechanism generally extract the salient features separately from the entity mention and the contextual words. However, these approaches suffer from two main limitations: (1) They ignore the rich information contained by entity mentions when applying the attention mechanisms. (2) They do not consider the diversity of attention processes which can be beneficial in finding the discriminative features. To address these issues, we propose the diversified semantic attention model (DSAM) for fine-grained entity typing, and the main novelties are: (1) It explicitly pursues the diversity of attention and is able to maximally gather discriminative information. (2) It integrates two level attentions—the mention-level attention and the context-level attention— to jointly capture the rich information from mentions and contexts to enhance their mutual promotions. (3) It combines the attention maps constraint and the attention segments constrain to exploit the subtle semantic differences for distinguishing the subtypes. Importantly, the proposed DSAM approach can be trained end-to-end without employing ad-hoc features or post-processing. Extensive experiments using three benchmark datasets demonstrated that our DSAM approach achieves competitive performance compared to the current state-of-the-art methods used for fine-grained entity typing.

BackgroundAntibodies against programmed death 1 (PD-1) and its ligand, programmed death-ligand 1 (PD-L1) have recently shown promising results in gastric cancer (GC). However, clinicians still lack predictive biomarkers for the efficacy of anti-PD-1 therapy; thus, we investigated the expression of PD-L1 in GC and further assessed its clinical relevance with other clinicopathological features.MethodsWe retrospectively collected clinical data on 968 consecutive GC cases from Nanfang Hospital between November 2018 and August 2021. Discrepancy in the combined positive score (CPS) of PD-L1 protein expression between gastric mucosa biopsy and postoperative pathology were investigated. Correlations between CPS and clinicopathological parameters were determined using chi-squared test, multiple logistic aggression analysis, and linear regression analysis.ResultsAmong the 968 consecutive GC patients, 199 who did not receive preoperative chemotherapy or immunotherapy were tested for CPS both in gastric mucosa biopsy and postoperative pathology, and the results showed that the CPS of gastric mucosa biopsy was significantly lower than that of postoperative pathology [mean ± SD: 5.5 ± 9.4 vs. 13.3 ± 17.4; M(IQR): 2(5) vs. 5(12), p

DNA methylation is a widespread epigenetic mark that affects gene expression and transposon mobility during plant development and stress responses. However, the role of DNA methylation in regulating the expression of microRNA (miRNA) genes remains largely unexplored. Here, we analyzed DNA methylation changes of miRNA genes using a pair of soybean (Glycine max) near-isogenic lines (NILs) differing in their response to soybean cyst nematode (SCN; Heterodera glycines). Differences in global DNA methylation levels over miRNA genes in response to SCN infection were observed between the isogenic lines. miRNA genes with significant changes in DNA methylation levels in the promoter and primary transcript-coding regions were detected in both lines. In the susceptible isogenic line (NIL-S), 82 differentially methylated miRNAs were identified in response to SCN infection whereas, in the resistant isogenic line (NIL-R), only 16 differentially methylated miRNAs were identified. Interestingly, gma-miR5032, gma-miR5043, gma-miR1520b, and gma-2107-ch16 showed opposite methylation patterns in the isogenic lines. In addition, the miRNA paralogs gma-miR5770a and gma-miR5770b showed hypermethylation and hypomethylation in NIL-S and NIL-R, respectively. Gene expression quantification of gma-miR5032, gma-miR5043, gma-miR1520b, and gma-miR5770a/b and their confirmed targets indicated a role of DNA methylation in regulating miRNA expression and, thus, their targets upon SCN infection. Furthermore, overexpression of these four miRNAs in NIL-S using transgenic hairy root system enhanced plant resistance to SCN to various degrees with a key role observed for miR5032. Together, our results provide new insights into the role of epigenetic mechanisms in controlling miRNA regulatory function during SCN–soybean interactions.[Graphic: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Abstract Background CuS-modified hollow mesoporous organosilica nanoparticles (HMON@CuS) have been preferred as non-invasive treatment for cancer, as near infrared (NIR)-induced photo-thermal effect (PTT) and/or photo-dynamic effect (PDT) could increase cancer cells’ apoptosis. However, the certain role of HMON@CuS-produced-PTT&PDT inducing gastric cancer (GC) cells’ mitochondrial damage, remained unclear. Moreover, theranostic efficiency of HMON@CuS might be well improved by applying multi-modal imaging, which could offer an optimal therapeutic region and time window. Herein, new nanotheranostics agents were reported by Gd doped HMON decorated by CuS nanocrystals (called HMON@CuS/Gd). Results HMON@CuS/Gd exhibited appropriate size distribution, good biocompatibility, l-Glutathione (GSH) responsive degradable properties, high photo-thermal conversion efficiency (82.4%) and a simultaneous reactive oxygen species (ROS) generation effect. Meanwhile, HMON@CuS/Gd could efficiently enter GC cells, induce combined mild PTT (43–45 °C) and PDT under mild NIR power density (0.8 W/cm2). Surprisingly, it was found that PTT might not be the only factor of cell apoptosis, as ROS induced by PDT also seemed playing an essential role. The NIR-induced ROS could attack mitochondrial transmembrane potentials (MTPs), then promote mitochondrial reactive oxygen species (mitoROS) production. Meanwhile, mitochondrial damage dramatically changed the expression of anti-apoptotic protein (Bcl-2) and pro-apoptotic protein (Bax). Since that, mitochondrial permeability transition pore (mPTP) was opened, followed by inducing more cytochrome c (Cyto C) releasing from mitochondria into cytosol, and finally activated caspase-9/caspase-3-depended cell apoptosis pathway. Our in vivo data also showed that HMON@CuS/Gd exhibited good fluorescence (FL) imaging (wrapping fluorescent agent), enhanced T1 imaging under magnetic resonance imaging (MRI) and infrared thermal (IRT) imaging capacities. Guided by FL/MRI/IRT trimodal imaging, HMON@CuS/Gd could selectively cause mild photo-therapy at cancer region, efficiently inhibit the growth of GC cells without evident systemic toxicity in vivo. Conclusion HMON@CuS/Gd could serve as a promising multifunctional nanotheranostic platform and as a cancer photo-therapy agent through inducing mitochondrial dysfunction on GC.

Background. Little is known about the relation between perioperative inflammatory changes and long-term survival in cancer patients. The aim of the study was to assess the association of perioperative serum interleukin-6 (IL6) and tumor necrosis factor-α (TNFα) levels with the 5-year overall survival in locally advanced gastric cancer. Methods. The 135 eligible patients in one center of Nanfang Hospital were retrieved from CLASS-01 trial (NCT01609309), an open-label, multicenter, randomized clinical noninferiority trial conducted at 14 centers in China. Serum IL6 and TNFα levels were tested before surgery, and on postoperative day (POD) 1, POD3, and POD5, respectively, referring to IL6_0, IL6_1, IL6_3, and IL6_5 and TNFα_0, TNFα_1, TNFα_3, and TNFα_5. Kaplan-Meier methods and COX models were used for survival analysis. Results. High levels of IL6_0 (≥3.67 pg/mL) and TNFα_0 (≥14.8 pg/mL) presented worse disease-free survival (DFS) (P=0.0057 for IL6_0 and P=0.0014 for TNFα_0) and overall survival (OS) (P=0.0021 for IL6_0 and P=0.0019 for TNFα_0). Both high IL6_0 and high IL6_5 levels indicated worse prognosis than other combinations (P=0.0045 for DFS and P=0.0022 for OS). In multivariate analysis, both high IL6_0 and high IL6_5 levels were significantly associated with poor DFS (HR=4.29, 95% CI: 1.42-12.95, P=0.01) and OS (HR=4.11, 95% CI: 1.35-12.49, P=0.013) after adjustment of tumor stage and TNFα_0. Also, high IL6_5 level was identified as the independent-related factor for postoperative infectious complications (OR=2.69, 95% CI: 1.03-7.01, P=0.043). Conclusions. Perioperative high serum IL6 and TNFα levels are negatively associated with 5-year survival outcomes in patients with locally advanced gastric cancer, indicating the potential survival benefits from perioperative anti-inflammatory treatment.

Soybean cyst nematode Heterodera glycines (SCN) is a major threat to global soybean production. Effective management of this disease is dependent on the development of resistant cultivars. Two SCN HG Types, 7 and 1.3.4.7. were previously identified as prevalent H. glycines populations in Northeast China. In order to evaluate soybean cultivars resistant to local SCN populations, 110 domestic commercial soybeans from different regions of Northeast China were assessed in the greenhouse to determine their potential as novel sources of resistance. The results suggested that cultivars responded differently to the two HG types. Of the 110 soybean cultivars evaluated, 24 accessions were classified as resistant or moderately resistant to HG Type 7, and five cultivars were classified as resistant or moderately resistant to HG Type 1.3.4.7. Among the tested cultivars, Kangxian 12 and Qingdou 13 had resistance response to both HG types 7 and 1.3.4.7. Thus, these broad-based SCN cultivars will be the valuable materials in the SCN resistance breeding program.

The FMRFamide-like peptides (FLPs) represent the largest family of nematode neuropeptides and are involved in multiple parasitic activities. The immunoreactivity to FMRFamide within the nervous system of Heterodera glycines, the most economically damaging parasite of soybean [Glycine max L. (Merr)], has been reported in previous research. However, the family of genes encoding FLPs of H. glycines were not identified and functionally characterized. In this study, an FLP encoding gene Hg-flp-22 was cloned from H. glycines, and its functional characterization was uncovered by using in vitro RNA interference and application of synthetic peptides. Bioinformatics analysis showed that flp-22 is widely expressed in multiple nematode species, where they encode the highly conserved KWMRFamide motifs. Quantitative real-time (qRT)-PCR results revealed that Hg-flp-22 was highly expressed in the infective second-stage juveniles (J2s) and adult males. Silencing of Hg-flp-22 resulted in the reduced movement of J2s to the host root and reduced penetration ability, as well as a reduction in their subsequent number of females. Behavior and infection assays demonstrated that application of synthetic peptides Hg-FLP-22b (TPQGKWMRFa) and Hg-FLP-22c (KMAIEGGKWVRFa) significantly increased the head movement frequency and host invasion abilities in H. glycines but not in Meloidogyne incognita. In addition, the number of H. glycines females on the host roots was found to be significantly higher in Hg-FLP-22b treated nematodes than the ddH2O-treated control J2s. These results presented in this study elucidated that Hg-flp-22 plays a role in regulating locomotion and infection of H. glycines. This suggests the potential of FLP signaling as putative control targets for H. glycines in soybean production.

Abstract Background Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the induction of cancer through epigenetic regulation, transcriptional regulation, post-transcriptional regulation and other aspects, thus participating in various biological processes such as cell proliferation, differentiation and apoptosis. As a new nova of anti-tumor therapy, immunotherapy has been shown to be effective in many tumors of which PD-1/PD-L1 monoclonal antibodies has been proofed to increase overall survival rate in advanced gastric cancer (GC). Microsatellite instability (MSI) was known as a biomarker of response to PD-1/PD-L1 monoclonal antibodies therapy. The aim of this study was to identify lncRNAs signatures able to classify MSI status and create a predictive model associated with MSI for GC patients. Methods Using the data of Stomach adenocarcinoma from The Cancer Genome Atlas (TCGA), we developed and validated a lncRNAs model for automatic MSI classification using a machine learning technology – support vector machine (SVM). The C-index was adopted to evaluate its accuracy. The prognostic values of overall survival (OS) and disease-free survival (DFS) were also assessed in this model. Results Using the SVM, a lncRNAs model was established consisting of 16 lncRNA features. In the training cohort with 94 GC patients, accuracy was confirmed with AUC 0.976 (95% CI, 0.952 to 0.999). Veracity was also confirmed in the validation cohort (40 GC patients) with AUC 0.950 (0.889 to 0.999). High predicted score was correlated with better DFS in the patients with stage I-III and lower OS with stage I-IV. Conclusion This study identify 16 LncRNAs signatures able to classify MSI status. The correlation between lncRNAs and MSI status indicates the potential roles of lncRNAs interacting in immunotherapy for GC patients. The pathway of these lncRNAs which might be a target in PD-1/PD-L1 immunotherapy are needed to be further study.

This study aimed to develop and validate a prognostic nomogram for recurrence-free survival (RFS) after surgery in the absence of adjuvant therapy to guide the selection for adjuvant imatinib therapy based on Residual Neural Network (ResNet).The ResNet model was developed based on contrast-enhanced computed tomography (CE-CT) in a training cohort consisted of 80 patients pathologically diagnosed gastrointestinal sromal tumors (GISTs) and validated in internal and external validation cohort respectively. Independent clinicopathologic factors were integrated with the ResNet model to construct the individualized nomogram. The performance of the nomogram was evaluated in regard to discrimination, calibration, and clinical usefulness.The ResNet model was significantly associated with RFS. Integrable predictors in the individualized ResNet nomogram included the tumor site, size, and mitotic count. Compared with modified NIH, AFIP, and clinicopathologic nomogram, both ResNet nomogram and ResNet model showed a better discrimination capability with AUCs of 0·947(95%CI, 0·910–0·984) for 3-year-RFS, 0·918(0·852–0·984) for 5-year-RFS, and AUCs of 0·912 (0·851–0·973) for 3-year-RFS, 0·887(0·816–0·960) for 5-year-RFS, respectively. Calibration curve shows the good calibration of the nomogram in terms of the agreement between the estimated and the observed 3- and 5- year outcomes. Decision curve analysis showed that the ResNet nomogram had a higher overall net benefit.In conclusion, we presented a deep learning-based prognostic nomogram to predict RFS after resection of localized primary GISTs with excellent performance and could be a potential tool to select patients for adjuvant imatinib therapy. Keywords: Gastrointestinal Stromal Tumors, Deep Learning, Residual Neural Network, Recurrence-free Survival, Imatinib

PurposeGastric cancer (GC) is a product of multiple genetic abnormalities, including genetic and epigenetic modifications. This study aimed to integrate various biomolecules, such as miRNAs, mRNA, and DNA methylation, into a genome-wide network and develop a nomogram for predicting the overall survival (OS) of GC.Materials and MethodsA total of 329 GC cases, as a training cohort with a random of 150 examples included as a validation cohort, were screened from The Cancer Genome Atlas database. A genome-wide network was constructed based on a combination of univariate Cox regression and least absolute shrinkage and selection operator analyses, and a nomogram was established to predict 1-, 3-, and 5-year OS in the training cohort. The nomogram was then assessed in terms of calibration, discrimination, and clinical usefulness in the validation cohort. Afterward, in order to confirm the superiority of the whole gene network model and further reduce the biomarkers for the improvement of clinical usefulness, we also constructed eight other models according to the different combinations of miRNAs, mRNA, and DNA methylation sites and made corresponding comparisons. Finally, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were also performed to describe the function of this genome-wide network.ResultsA multivariate analysis revealed a novel prognostic factor, a genomics score (GS) comprising seven miRNAs, eight mRNA, and 19 DNA methylation sites. In the validation cohort, comparing to patients with low GS, high-GS patients (HR, 12.886; P < 0.001) were significantly associated with increased all-cause mortality. Furthermore, after stratification of the TNM stage (I, II, III, and IV), there were significant differences revealed in the survival rates between the high-GS and low-GS groups as well (P < 0.001). The 1-, 3-, and 5-year C-index of whole genomics-based nomogram were 0.868, 0.895, and 0.928, respectively. The other models have comparable or relatively poor comprehensive performance, while they had fewer biomarkers. Besides that, DAVID 6.8 further revealed multiple molecules and pathways related to the genome-wide network, such as cytomembranes, cell cycle, and adipocytokine signaling.ConclusionWe successfully developed a GS based on genome-wide network, which may represent a novel prognostic factor for GC. A combination of GS and TNM staging provides additional precision in stratifying patients with different OS prognoses, constituting a more comprehensive sub-typing system. This could potentially play an important role in future clinical practice.

Objective: The aim of this study is to evaluate whether radiomics imaging signatures based on computed tomography (CT) could predict peritoneal metastasis (PM) in gastric cancer (GC) and to develop a nomogram for preoperative prediction of PM status.Methods: We collected CT images of pathological T4 gastric cancer in 955 consecutive patients of two cancer centers to analyze the radiomics features retrospectively and then developed and validated the prediction model built from 292 quantitative image features in the training cohort and two validation cohorts. Lasso regression model was applied for selecting feature and constructing radiomics signature. Predicting model was developed by multivariable logistic regression analysis. Radiomics nomogram was developed by the incorporation of radiomics signature and clinical T and N stage. Calibration, discrimination, and clinical usefulness were used to evaluate the performance of the nomogram.Results: In training and validation cohorts, PM status was associated with the radiomics signature significantly. It was found that the radiomics signature was an independent predictor for peritoneal metastasis in multivariable logistic analysis. For training and internal and external validation cohorts, the area under the receiver operating characteristic curves (AUCs) of radiomics signature for predicting PM were 0.751 (95%CI, 0.703–0.799), 0.802 (95%CI, 0.691–0.912), and 0.745 (95%CI, 0.683–0.806), respectively. Furthermore, for training and internal and external validation cohorts, the AUCs of radiomics nomogram for predicting PM were 0.792 (95%CI, 0.748–0.836), 0.870 (95%CI, 0.795–0.946), and 0.815 (95%CI, 0.763–0.867), respectively.Conclusions: CT-based radiomics signature could predict peritoneal metastasis, and the radiomics nomogram can make a meaningful contribution for predicting PM status in GC patient preoperatively.

Background: The number of retrieved lymph nodes (RLNs) affects the likelihood of detecting metastatic lymph nodes (MLNs) for gastric cancer (GC), but the retrieval of LNs is not satisfactory worldwide. There is no standard for LN examination.Methods: We retrospectively analyzed 2,163 patients diagnosed with GC who underwent surgery at Nanfang Hospital between October 2004 and September 2016. According to the methods of LN examination, patients were classified into two groups: LN detection by pathologists (pathologist group) and LN examination by surgicopathologic team (surgicopathologist group). The relationship between RLNs and LN staging accuracy as well as the factors influencing the detection of MLNs were evaluated.Results: There were 472 males in pathologist group and 467 males in surgicopathologist group. The number of RLNs and MLNs in surgicopathologist group was significantly higher than that in pathologist group (RLNs: 53.8 ± 20.9 vs. 18.8 ± 11.5, p < 0.001; MLNs: 5.6 ± 9.8 vs. 3.9 ± 5.7, p < 0.001). Notably, the detection of N3b node status was significantly improved in surgicopathologist group [83 (11.9%) vs. 34 (4.8%), p < 0.001]. Additionally, the detection rate of N3b status gradually increased from 0 in patients with 1-16 RLNs to 16.6% in patients with more than 49 RLNs. The MLNs detected increased gradually from 2.3 ± 3.0 in patients with 1-16 RLNs to 7.3 ± 11.7 in patients with more than 49 RLNs. Univariate and multivariate analyses indicated that LN examination by surgicopathologic team, more advanced pT, tumor size ≥5 cm and combined organ(s) resection were related to detecting more MLNs.Conclusions: The retrieval of nodes immediately postoperatively by the surgicopathologic team could significantly improve the number of RLNs, detect more MLNs, and screen more patients with N3b node status.

To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and chemotherapeutic benefits. In this multicenter retrospective analysis, we analyzed the radiomics features of portal venous-phase computed tomography in 1591 consecutive patients. A radiomics signature was generated by using the Lasso-Cox regression model in 228 patients and validated in internal and external validation cohorts. Radiomics nomograms integrating the radiomics signature were constructed, demonstrating the incremental value of the radiomics signature to the traditional staging system for individualized survival estimation. The performance of the nomograms was assessed with respect to calibration, discrimination, and clinical usefulness. The radiomics signature consisted of 19 selected features and was significantly associated with DFS (disease-free survival) and OS (overall survival). Multivariate analysis demonstrated that the radiomics signature was an independent prognostic factor. Incorporating the radiomics signature into the radiomics-based nomograms resulted in better performance for the estimation of DFS and OS than the clinicopathological nomograms and TNM staging system, with improved accuracy of the classification of survival outcomes. Further analysis showed that stage II and III patients with higher radiomics scores exhibited a favorable response to chemotherapy. In conclusion, the newly developed radiomics signature is a powerful predictor of DFS and OS, and it may predict which patients with stage II and III GC benefit from chemotherapy. Keywords: Gastric cancer, Radiomics signature, Prognosis, Chemotherapy

Drug resistance is the major challenge facing cancer chemotherapy and nanoscale delivery systems based on natural materials, such as sericin, are a promising means of overcoming drug resistance. Yet, no attempt of introducing synthetic poly(γ-benzyl-L-glutamate) (PBLG) onto sericin polypeptide to fabricate a facile biocompatible and biodegradable micelle has been tried. Here, we prepared a polypeptide-based amphiphilic polymer containing hydrophilic sericin polypeptide backbone and PBLG side chains via ring-opening polymerization (ROP) strategy. The introduction of PBLG side chains remarkably enhances the stability of sericin micelles in water. Meanwhile, the micelles exhibited a high loading capacity and pH-responsive release ability for antitumor drug doxorubicin (DOX), called sericin-PBLG-DOX. Owing to the excellent cell membrane penetration of sericin-PBLG, the cellular uptake of DOX when loaded into micelles was improved. Subsequently, sericin-PBLG-DOX was transferred into perinuclear lysosomes, where the release rate of DOX was accelerated. Compared to the same dose of DOX, sericin-PBLG-DOX could induce a more efficient anti-tumor effect both in vitro and in vivo, and these micelles have promise for future clinical applications in overcoming cancer drug resistance with good biosafety, enhanced cellular uptake, pH-triggered drug release, efficient anti-tumor effects, and minimized systemic toxicity.

Maize is one of the most important crops in the world. Heilongjiang province has the largest maize area in China. Plant-parasitic nematodes are important agricultural pests, which cause huge economic losses every year and have attracted global attention. Potato rot nematode Ditylenchus destructor is a plant-parasitic nematode with a wide range of hosts and strong survival ability in different environments, which brings risks to agricultural production. In 2020, D. destructor was detected in seven maize fields in Heilongjiang province. Morphological identification and molecular approach were used to characterize the isolated D. destructor. The observed morphological and morphometric characteristics were highly similar and consistent with the existing description. The DNA sequencing on the D2/D3 region of the ribosomal DNA 28S and the phylogenetic analysis showed that D. destructor population obtained from maize and other isolates infesting carrot, sweet potato, and potato were in subclade I supported by a 96% bootstrap value. Additionally, the phylogenetic analysis of the ITS rRNA gene sequence further indicated that this D. destructor population from maize clustered in a clade I group and belonged to ITS rRNA haplotype C. An inoculation experiment revealed that D. destructor was pathogenic on the maize seedlings in pots and caused the disease symptoms in the stem base of maize seedlings. This is the first report of D. destructor causing stem rot of maize in Heilongjiang province, and contributes additional information on disease control and safe production of maize in the region.

It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means that the processing mode based on data ontology cannot meet requirements any more. On the other hand, the multi-dimensional features of remote sensing data bring more difficulties in data query and analysis, especially for datasets with a lot of noise. Therefore, data quality has become the bottleneck of data value discovery, and a single batch query is not enough to support the optimal combination of global data resources. In this paper, we propose a spatio-temporal local association query algorithm for remote sensing data (STLAQ). Firstly, we design a spatio-temporal data model and a bottom-up spatio-temporal correlation network. Then, we use the method of partition-based clustering and the method of spectral clustering to measure the correlation between spatio-temporal correlation networks. Finally, we construct a spatio-temporal index to provide joint query capabilities. We carry out local association query efficiency experiments to verify the feasibility of STLAQ on multi-scale datasets. The results show that the STLAQ weakens the barriers between remote sensing data, and improves their application value effectively.

To determine whether p21-activated Kinase (PAK) 6 is a prognostic and predictive marker in gastric cancer (GC) and to construct a classifier that can identify a subset of patients who are highly sensitive to 5-fluorouracil/oxaliplatin chemotherapy. We retrospectively analyzed the expression levels of PAK6, cyclooxygenase 2, p21WAF1, Ki-67, excision repair cross-complementing gene 1, and thymidylate synthase in 242 paraffin-embedded GC specimens of the training cohort by immunohistochemistry. Then, we used support vector machine (SVM)–based methods to develop a predictive classifier for chemotherapy (chemotherapy score – CS-SVM classifier). Further validation was performed in an independent cohort of 279 patients. High PAK6 expression was associated with poor prognosis and increased chemoresistance to 5-FU/oxaliplatin chemotherapy. The CS-SVM classifier distinguished patients with stage II and III GC into low- and high-CS-SVM groups, with significant differences in the 5-year disease-free survival (DFS) and overall survival (OS) in chemotherapy patients. Moreover, chemotherapy significantly prolonged the DFS and OS of the high CS-SVM patients in the training and validation cohorts. In conclusion, PAK6 was an independent prognostic factor and increased chemoresistance. The CS-SVM classifier distinguished a subgroup of stage II and III patients who would highly benefit from chemotherapy, thus facilitating patient counseling and individualizing the management.

Purpose: The purpose of this study was to analyze the frequency and prognosis of pulmonary metastases in newly diagnosed gastric cancer using population-based data from SEER.Methods: Patients with gastric cancer and pulmonary metastases (GCPM) at the time of diagnosis in advanced gastric cancer were identified using the Surveillance, Epidemiology and End Result (SEER) database of the National Cancer Institute from 2010 to 2014. Multivariable logistic regression was performed to identify predictors of the presence of GCPM at diagnosis. Receiver operator characteristics analysis was performed to significant predictors on multivariable logistic regression and was then assessed with Delong's test. Multivariable Cox regression was developed to identify factors associated with all-cause mortality and gastric cancer-specific mortality. Survival curves were obtained according to the Kaplan-Meier method and compared using the log-rank test.Results: We identified 1,104 patients with gastric cancer and pulmonary metastases at the time of diagnosis, representing 6.02% of the entire cohort and 15.19% of the subset with metastatic disease to any distant site. Among the entire cohort, multivariable logistic regression identified six factors (younger, upper 1/3 of stomach, intestinal-type, T4 staging, N1 staging, and presence of more extrapulmonary metastases to liver, bone, and brain) as positive predictors of the presence of pulmonary metastases at diagnosis. The value of AUC for the multivariable logistic regression model was 0.775. Median survival among the entire cohort with GCPM was 3.0 months (interquartile range: 1.0–9.0 mo). Multivariable Cox model in SEER cohort confirmed five factors (diagnosis at previous period, black race, adverse pathology grade, absence of chemotherapy, and presence of more extrapulmonary metastases to liver, bone, and brain) as negative predictors for overall survival.Conclusions: The findings of this study provided population-based estimates of the frequency and prognosis for GCPM at time of diagnosis. The multivariable logistic regression model had an acceptable performance to predict the presence of PM. These findings may provide preventive guidelines for the screening and treatment of PM in GC patients. Patients with high risk factors should be paid more attention before and after diagnosis.

Background: To evaluate whether radiomic feature-based computed tomography (CT) imaging signatures allow prediction of lymph node (LN) metastasis in gastric cancer (GC) and to develop a preoperative nomogram for predicting LN status.Methods: We retrospectively analyzed radiomics features of CT images in 1,689 consecutive patients from three cancer centers. The prediction model was developed in the training cohort and validated in internal and external validation cohorts. Lasso regression model was utilized to select features and build radiomics signature. Multivariable logistic regression analysis was utilized to develop the model. We integrated the radiomics signature, clinical T and N stage, and other independent clinicopathologic variables, and this was presented as a radiomics nomogram. The performance of the nomogram was assessed with calibration, discrimination, and clinical usefulness.Results: The radiomics signature was significantly associated with pathological LN stage in training and validation cohorts. Multivariable logistic analysis found the radiomics signature was an independent predictor of LN metastasis. The nomogram showed good discrimination and calibration.Conclusions: The newly developed radiomic signature was a powerful predictor of LN metastasis and the radiomics nomogram could facilitate the preoperative individualized prediction of LN status.

Background: The optimal extent of gastrectomy and lymphadenectomy for esophagogastric junction (EGJ) cancer is controversial. Our study aimed to compare the long-term survival of transhiatal proximal gastrectomy with extended periproximal lymphadenectomy (THPG with EPL) and transhiatal total gastrectomy with complete perigastric lymphadenectomy (THTG with CPL) for patients with the stomach-predominant EGJ cancer.Methods: Between January 2004, and August 2015, 306 patients with Siewert II tumors were divided into the THTG group (n = 148) and the THPG group (n = 158). Their long-term survival was compared according to Nishi's classification. The Kaplan–Meier method and Cox proportional hazards models were used for survival analysis.Results: There were no significant differences between the two groups in the distribution of age, gender, tumor size or Nishi's type (P > 0.05). However, a significant difference was observed in terms of pathological tumor stage (P < 0.05). The 5-year overall survival rates were 62.0% in the THPG group and 59.5% in the THTG group. The hazard ratio for death was 0.455 (95% CI, 0.337 to 0.613; log-rank P < 0.001). Type GE/E = G showed a worse prognosis compared with Type G (P < 0.05). Subgroup analysis stratified by Nishi's classification, Stage IA-IIB and IIIA, and tumor size ≤ 30 mm indicated significant survival advantages for the THPG group (P < 0.05). However, this analysis failed to show a survival benefit in Stage IIIB (P > 0.05).Conclusions: Nishi's classification is an effective method to clarify the subdivision of Siewert II tumors with a diameter ≤ 40 mm above or below the EGJ. THPG with EPL is an optimal procedure for the patients with the stomach-predominant EGJ tumors ≤30 mm in diameter and in Stage IA-IIIA. For more advanced and larger EGJ tumors, further studies are required to confirm the necessity of THTG with CPL.