Understanding the genetic variation underlying transcript splicing is essential for fully dissecting the molecular mechanisms of common diseases. The available evidence from splicing quantitative trait locus (sQTL) studies using pancreatic ductal adenocarcinoma (PDAC) tissues have been limited to small sample sizes. Here we present a genome-wide sQTL analysis to identify single nucleotide polymorphisms (SNPs) that control mRNA splicing in 176 PDAC samples from TCGA. From this analysis, 16,175 sQTLs were found to be significantly enriched in RNA binding protein (RBP) binding sites and chromatin regulatory elements and overlapped with known loci from PDAC genome-wide association studies (GWAS). sQTLs and expression QTLs (eQTL) showed mostly non-overlapping patterns, suggesting sQTLs provide additional insights into the etiology of disease. Target genes affected by sQTLs were closely related to cancer signaling pathways, high mutational burden, immune infiltration, and pharmaceutical targets, which will be helpful for clinical applications. Integration of a large-scale population consisting of 2,782 PDAC patients and 7,983 healthy controls identified an sQTL variant rs1785932-T allele that promotes alternative splicing of ELP2 exon 6 and leads to a lower level of the ELP2 full-length isoform (ELP2_V1) and a higher level of a truncated ELP2 isoform (ELP2_V2), resulting in decreased risk of PDAC (OR=0.83, 95%CI=0.77-0.89, P=1.16×10-6). The ELP2_V2 isoform functioned as a potential tumor suppressor gene, inhibiting PDAC cell proliferation by exhibiting stronger binding affinity to JAK1/STAT3 than ELP2_V1 and subsequently blocking the pathological activation of the p-STAT3 pathway. Collectively, these findings provide an informative sQTL resource and insights into the regulatory mechanisms linking splicing variants to PDAC risk.

Microorganisms are commonly detected in tumor tissues, and the species and abundance have been reported to affect cancer initiation, progression, and therapy. Host genetics have been associated with gut microbial abundances, while the relationships between genetic variants and the cancer microbiome still require systematic interrogation. Therefore, identification of cancer microbiome quantitative trait loci (mbQTL) across cancer types might elucidate the contributions of genetic variants to tumor development. Using genotype data from The Cancer Genome Atlas and microbial abundance levels from Kraken-derived data, we developed a computational pipeline to identify mbQTLs in 32 cancer types. This systematically identified 38,660 mbQTLs across cancers, ranging 50 in endometrial carcinoma to 3,133 in thyroid carcinoma. Furthermore, a strong enrichment of mbQTLs was observed among transcription factor binding sites and chromatin regulatory elements, such as H3K27ac. Notably, mbQTLs were significantly enriched in cancer GWAS loci and explained an average of 2% of cancer heritability, indicating that mbQTLs could provide additional insights into cancer etiology. Correspondingly, 24,443 mbQTLs overlapping with GWAS linkage disequilibrium regions were identified. Survival analyses identified 318 mbQTLs associated with patient overall survival. Moreover, we uncovered 135,248 microbiome-immune infiltration associations and 166,603 microbiome-drug response associations that might provide clues for microbiome-based biomarkers. Finally, a user-friendly database, Cancer-mbQTL (http://canmbqtl.whu.edu.cn/#/), was constructed for users to browse, search, and download data of interest. This study provides a valuable resource for investigating the roles of genetics and microorganisms in human cancer.

For the utilization of leftover materials from furniture factory, a two‐step pyrolysis, an initial treatment at mild temperature followed by a fast pyrolysis step, in a fluidized bed reactor was proposed in this study. The grindability of semi‐biochar samples after the mild temperature pyrolysis was studied. The fast pyrolysis characteristics and kinetics parameters of the semi‐biochar samples were also investigated by thermogravimetric analysis. Results showed that an improvement in the grindability characteristics was observed. The grinding of semi‐biochars that do not completely devolatilize mainly produces a mixture of fine particles and small fragments, whereas the semi‐biochars that completely devolatilize have good grinding characteristic, and the main ground products are short and round particles. Most differential thermogravimetric (DTG) curves of the semi‐biochar samples presented two peaks and four common stages. With increase of the temperature or residence time in mild temperature treatment process, the decomposition intensity of hemicellulose and cellulose in grinding residues decreased gradually, while the decomposition intensity of lignin changed little. Peak DTG value ranging from 4%/min to 6%/min can be adopted to estimate the optimal operation condition for mild temperature pyrolysis. Three‐dimensional diffusion model can accurately describe the fast pyrolysis of semi‐biochar.

In this study, an in situ weighting system was used to study the thermal behavior of dried municipal sludge (MS) in the flue gas exiting from calcium-looping (Ca-L) process. The results showed that mass loss peak, initial decomposition temperature, and decomposition complete temperature moved to high-temperature zone with increased heating rate. However, they moved to low-temperature zone at higher O 2 and CO 2 concentrations. Apparent activation energy (E) and preexponential factor (A) increased with the increase of heating rate and O 2 concentration and decreased with the increase of CO 2 concentration. The heating rate has the greatest effect on the thermal decomposition of dried MS. With the heating rate increasing, the maximum mass loss peak occurred from 301 to 493°C, the corresponding E and A increased from 36.14 to 45.69 kJ mol −1 and from 29.58 to 321.4 min, respectively.

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