Search

ObjectiveThe commingled production of coalbed methane (CBM) serves as a significant means to increase single-well production. However, production practices reveal that the commingled production of CBM exhibits complex and varied effects and controlling factors, facing technical challenges of identifying gas-producing contributions, predicting gas-producing potential, and optimizing pay interval combinations. The superposition of desorption for gas production among different coal seams determines whether high CBM production can be achieved using commingled production. MethodsThis study proposed an analytical method for the desorption superposition effect in the commingled production of CBM, involving determining desorption sequences, analyzing the superposition of desorption intervals and the matching of desorption stages, and predicting well-controlled desorption capacities. The proposed method was applied to the Xiaotun mine field in western Guizhou Province, China. Results and conclusionsThe results indicate that coal reservoirs in the Xiaotun mine field feature high adsorption capacities, low gas saturation, and low critical desorption pressures. The CBM pay intervals can be categorized into the upper and lower desorption systems. The upper desorption system manifested a desorption sequence of the No.6 upper, No.7, No.6 middle, and No.6 lower coal seams, while the lower desorption system displayed a desorption sequence of the No.34 and No.33 coal seams. Using changes in the working fluid during the production process as an indicator, this study analyzed the desorption processes of coal seams during the commingled production of CBM. The analytical results reveal that the synchronous desorption of the No.6 upper, No.7, No.6 middle, and No.6 lower coal seams can be achieved within a working fluid of 45 m and the synchronous desorption of the No.33 and No.34 coal seams can be gained within a working fluid of 92 m. Isothermal adsorption curves discovered the matching of the coal seams' desorption stages. The low critical desorption pressures allowed various coal seams to directly enter the sensitive desorption stage after desorption, suggesting high desorption efficiency and effective matching. This creates favorable conditions for high CBM production. However, limitations like insufficient pressure drop space and long drainage periods impose high requirements for coal seam stimulation and CBM production. The well-controlled desorption capacities and their time-varying curves indicate that gas desorption capacities peaked in the case of the synchronous desorption of all pay intervals within the respective desorption systems. In this case, the upper and the lower desorption systems yielded well-controlled desorption capacities of 378.09×104 m3 (daily average: 4.20×104 m3) and 199.11×104 m3 (daily average: 1.08×104 m3), respectively. Both desorption systems demonstrated satisfactory desorption superposition effect, each forming a favorable pay interval combination for the commingled production of CBM. The proposed method will provide a reference for identifying gas-producing contributions, predicting gas-producing potential, and optimizing pay interval combinations for the commingled production of CBM.

Abstract Keloid formation is a pathological consequence resulting from cutaneous irritation and injury, primarily attributed to excessive collagen matrix deposition and fibrous tissue proliferation. Chronic inflammation, left uncontrolled over an extended period, also stands as a substantial contributing factor. The precise mechanisms underlying keloid formation remain unclear. Therefore, this study aimed to identify key genes for diagnostic purposes. To achieve this, we used two Gene Expression Omnibus (GEO) data sets to identify differentially expressed genes. We identified one particular gene, homeobox C9 (HOXC9), using a thorough strategy involving two algorithms (least absolute shrinkage and selection operator and support vector machine-recursive feature elimination) and weighted gene co-expression network analysis. We then assessed its expression in normal and keloid tissues. In addition, we explored its temporal expression patterns via Mfuzz time clustering analysis. In our comprehensive analysis, we observed that immune infiltration, as well as cell proliferation, are crucial to keloid formation. Thus, we investigated immune cell infiltration in the keloid and normal groups, as well as the correlation between HOXC9 and these immune cells. It was found that HOXC9 was closely associated with the immune microenvironment of keloids. This shows that HOXC9 can serve as a potential biomarker and therapeutic target for keloids.

BackgroundGastric epithelial neoplasm of the fundic-gland mucosa lineages (GEN-FGMLs) are rare forms of gastric tumors that encompass oxyntic gland adenoma (OGA), gastric adenocarcinoma of the fundic-gland type (GA-FG), and gastric adenocarcinoma of the fundic-gland mucosa type (GA-FGM). There is no consensus on the cause, classification, and clinicopathological features of GEN-FGMLs, and misdiagnosis is common because of similarities in symptoms.Methods37 cases diagnosed with GEN-FGMLs were included in this study. H&E-stained slides were reviewed and clinicopathological parameters were recorded. Immunohistochemical staining was conducted for MUC2, MUC5AC, MUC6, CD10, CD56, synaptophysin, chromograninA, p53, Ki67, pepsinogen-I, H+/K+-ATPase and Desmin.ResultsThe patients’ ages ranged from 42 to 79 years, with a median age of 60. 17 were male and 20 were female. Morphologically, 19 OGAs, 16 GA-FGs, and two GA-FGMs were identified. Histopathological similarities exist between OGA, GA-FG, and GA-FGM. The tumors demonstrated well-formed glands, expanding with dense growth patterns comprising pale, blue-grey columnar cells with mild nuclear atypia. These cells resembled fundic gland cells. None of the OGA invaded the submucosal layer. The normal gastric pit epithelium covered the entire surface of the OGA and GA-FG, but the dysplasia pit epithelium covered the GA-FGM. Non-atrophic gastritis was observed in more than half of the background mucosa. All cases were diffusely positive for MUC6 and pepsinogen-I on immunohistochemistry. H+/K+-ATPase staining was negative or showed a scattered pattern in most cases. MUC5AC was expressed on the surface of GA-FGMs. p53 was focally expressed and the Ki67 index was low (1%–20%). Compared with OGA, GA-FG and GA-FGM were more prominent in the macroscopic view (p < 0.05) and had larger sizes (p < 0.0001). Additionally, GA-FG and GA-FGM exhibited higher Ki67 indices than OGA (p < 0.0001). Specimens with Ki-67 proliferation indices >2.5% and size >4.5 mm are more likely to be diagnosed with GA-FG and GA-FGM than OGA.ConclusionGEN-FGMLs are group of well-differentiated gastric tumors with favourable biological behaviours, low cellular atypia, and low proliferation. Immunohistochemistry is critical for confirming diagnosis. Compared with OGA, GA-FG and GA-FGM have larger sizes and higher Ki67 proliferation indices, indicating that they play a critical role in the identification of GEN-FGML. Pathologists and endoscopists should be cautious to prevent misdiagnosis and overtreatment, especially in biopsy specimens.

Immunoglobulin G (IgG) N-glycosylation plays a crucial role in the development of inflammatory diseases. This study aimed to evaluate the diagnostic performance of IgG for gastrointestinal (GI) cancer subtypes. A total of 749 GI cancer patients were enrolled from the Cancer Hospital, Chinese Academy of Medical Sciences, including esophageal cancer (EC), gastric cancer (GC), colorectal cancer (CRC), and pancreatic cancer (PC) patients. Hydrophilic interaction liquid chromatography using ultra-performance liquid chromatography (HILIC-UPLC) was employed to analyze the composition of the plasma IgG N-glycome. The levels of circulating inflammatory cytokines were detected by means of a Bio-Plex Pro Human Th17 Cytokine Assay. Canonical correlation analysis (CCA) was used to explore the correlation between IgG N-glycosylation patterns and inflammatory cytokines. A Lasso algorithm, accompanied by a logistic regression model, was used to develop a glycan-based model for differentiating GI cancer patients from healthy individuals. The levels of sialylation and galactosylation were significantly decreased among EC, GC, CRC, and PC patients, whereas the abundance of glycans with bisecting N-acetylglucosamine (GlcNAc) was increased in GI cancer patients in comparison with the healthy controls. Moreover, only PC patients had a decreased level of fucosylation. The levels of interleukin 1β (IL-1β), IL-31, and soluble CD40 ligand (sCD40L) were significantly higher in GI cancer patients than in the controls. In addition, the composition of IgG N-glycans was correlated with that of inflammatory cytokines (r = 0.556). The glycan-based models for diagnosing GI cancers exhibited an excellent performance, with areas under the receiver operating characteristic curves (AUCs) of 0.972 for EC, 0.871 for GC, 0.867 for CRC, and 0.907 for PC. Our findings demonstrate that IgG N-glycosylation plays an important role in modulating the pathogenesis of GI cancers. Serological IgG N-glycosylation is thus a potential candidate for noninvasively assisting in the clinical diagnosis of GI cancer subtypes.

Abstract Lung cancer is one of the most common malignant tumors, and ranks high in the list of mortality due to cancers. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite progress in the diagnosis and treatment of lung cancer, the prognosis of these patients remains dismal. Therefore, it is crucial to identify the predictors and treatment targets of lung cancer to provide appropriate treatments and improve patient prognosis. In this study, the gene modules related to immunotherapy were screened by weighted gene co-expression network analysis (WGCNA). Using unsupervised clustering, patients in The Cancer Genome Atlas (TCGA) were divided into three clusters based on the gene expression. Next, gene clustering was performed on the prognosis-related differential genes, and a six-gene prognosis model (comprising PLK1, HMMR, ANLN, SLC2A1, SFTPB, and CYP4B1) was constructed using least absolute shrinkage and selection operator (LASSO) analysis. Patients with LUAD were divided into two groups: high-risk and low-risk. Significant differences were found in the survival, immune cell infiltration, Tumor mutational burden (TMB), immune checkpoints, and immune microenvironment between the high- and low-risk groups. Finally, the accuracy of the prognostic model was verified in the Gene Expression Omnibus (GEO) dataset in patients with LUAD (GSE30219, GSE31210, GSE50081, GSE72094).

In the hybrid video coding framework, quantization is the key technique to achieve lossy compression. The information loss caused by the quantization may be reduced to improve compression efficiency, by using either encoder-side rate-distortion optimized quantization or decoder-side filtering. Nonetheless, the existing studies did not extensively use the already encoded information, i.e., context, to reduce the quantization loss. We address this issue and propose a context-adaptive inverse quantization method, namely, CAIQ. Specifically, for inter-frame coding, we analyze the correlation between the prediction signal (generated by motion compensated prediction) and the residual signal, as well as the correlation within the residual signal itself. We then present linear as well as nonlinear yet lightweight models to exploit the observed correlations in the frequency domain. Our models provide an optional inverse quantization mode by referring to the prediction signal, which is available at the decoder side. Next, block-level mode selection regarding the CAIQ method is used at the encoder side. We integrate the proposed CAIQ method into the reference software of Versatile Video Coding. We perform an extensive study of the models and analyze their resulting compression efficiency gain and encoding/decoding complexity. Experimental results show that our CAIQ method improves compression performance especially for high-resolution videos and at high bit rates.

The support for region of interest (ROI) browsing, which allows dropping background part of video bitstreams, is a desirable feature for video applications. With the help of the slice group technique provided by H.264/SVC, rectangular ROI areas can be encoded into separate ROI slices. Additionally, by imposing certain constraints on motion estimation, ROI part of the bitstream can be decoded without background slices of the same layer. However, due to the additional spatial and temporal constraints applied to the encoder, overall coding efficiency would be significantly decreased. In this paper, a rate-distortion optimized (RDO) encoding scheme is proposed to improve the coding efficiency of ROI slices. When background slices are discarded, the proposed method uses base layer information to generate the prediction signal of the enhancement layer. Thus, the temporal constraints can be loosened during the encoding process. To do it in this way, the possible mismatch between generated reference frames and original ones is also considered during rate-distortion optimization so that a reasonable trade-off between coding efficiency and decoding drift can be made. Besides, a new Lagrange multiplier derivation method is developed for further coding performance improvement. Experimental results demonstrate that the proposed method achieves significant bitrate saving compared to existing methods.