Identifying important microbial biomarkers for the diagnosis of colon cancer using a random forest approach.

Colon cancer is one of the most common cancers, with 30-50 % of patients returning or metastasizing within 5 years of treatment. Increasingly, researchers have highlighted the influence of microbes on cancer malignant activity, while no studies have explored the relationship between colon cancer and the microbes in tumors. Here, we used tissue and blood samples from 67 colon cancer patients to identify pathogenic microorganisms associated with the diagnosis and prediction of colon cancer and evaluate the predictive performance of each pathogenic marker and its combination based on the next-generation sequencing data by using random forest algorithms. The results showed that we constructed a database of 13,187 pathogenic microorganisms associated with human disease and identified 2 pathogenic microorganisms (Synthetic.construct_32630 and Dicrocoelium.dendriticum_57078) associated with colon cancer diagnosis, and the constructed diagnostic prediction model performed well for tumor tissue samples and blood samples. In summary, for the first time, we provide new molecular markers for the diagnosis of colon cancer based on the expression of pathogenic microorganisms in order to provide a reference for improving the effective screening rate of colon cancer in clinical practice and ameliorating the personalized treatment of colon cancer patients.

PEX26 Functions as a Metastasis Suppressor in Colorectal Cancer.

BACKGROUND/AIMS: Aberrant Peroxisomal Biogenesis Factor 26 (PEX26) occurs in multiple cell process. However, the role of PEX26 in colorectal cancer (CRC) development remains unknown. We aimed to study PEX26 expression, regulation, and function in CRC cells. METHODS: Using the bioinformatic analysis, real-time quantitative PCR, and immunohistochemistry staining, we detected the expression of PEX26 in CRC and normal tissues. We performed functional experiments in vitro to elucidate the effect of PEX26 on CRC cells. We analyzed the RNA-seq data to reveal the downstream regulating network of PEX26. RESULTS: PEX26 is significantly down-regulated in CRC and its low expression correlates with the poor overall survival of CRC patients. We further demonstrated that PEX26 over-expression inhibits the ability of CRC cell migration, invasion, and epithelial-mesenchymal transition (EMT), while PEX26 knockdown promotes the malignant phenotypes of migration, invasion, and EMT via activating the Wnt pathway. CONCLUSION: Overall, our results showed that the loss of PEX26 contributes to the malignant phenotype of CRC. PEX26 may serve as a novel metastasis repressor for CRC.

Combined application of biochar and nitrogen fertilizer promotes the activity of starch metabolism enzymes and the expression of related genes in rice in a dual cropping system.

BACKGROUND: Overuse of chemical fertilizer highly influences grain filling rate and quality of rice grain. Biochar is well known for improving plant growth and grain yield under lower chemical fertilization. Therefore field trials were conducted in the early and late seasons of 2019 at Guangxi University, China to investigate the effects of combined biochar (B) and nitrogen (N) application on rice yield and yield components. There were a total of eight treatments: N1B0, 135 kg N ha- 1+ 0 t B ha- 1; N2B0,180 kg N ha- 1+ 0 t B ha- 1; N1B1,135 kg N ha- 1+ 10 t B ha- 1; N1B2,135kg N ha- 1+ 20 t B ha- 1; N1B3,135 kg N ha- 1+ 30 t B ha- 1; N2B1,180 kg N ha- 1+ 10 t B ha- 1; N2B2,180 kg N ha- 1+ 20 t B ha- 1; and N2B3,180 kg N ha- 1+ 30 t B ha- 1. RESULTS: Biochar application at 30 t ha- 1combined with low N application (135 kg ha- 1) increased the activity of starch-metabolizing enzymes (SMEs) during the early and late seasons compared with treatments without biochar. The grain yield, amylose concentration, and starch content of rice were increased in plots treated with 30 t B ha-1and low N. RT-qPCR analysis showed that biochar addition combined with N fertilizer application increased the expression of AGPS2b, SSS1, GBSS1, and GBSE11b, which increased the activity of SMEs during the grain-filling period. CONCLUSION: Our results suggest that the use of 20 to 30 t B ha- 1coupled with 135 kg N ha- 1 is optimal for improving the grain yield and quality of rice.

Impact of fertilization with reducing in nitrogen and phosphorous application on growth, yield and biomass accumulation of rice (Oryza sativa L.) under a dual cropping system.

The current farming system in China is heavily reliant on synthetic fertilizers, which adversely affect soil quality and crop production. Therefore, the aim of this study was to assess the effect of different nitrogen (N) and phosphorous (P) fertilizer application rate on the growth, yield, and yield components of rice cultivars in the Binyang, Beiliu and Liucheng sites of southern China in the early (March to July) and late season (August to December). The study consisted of three fertilization regimes-CK (N0P0); N180P90 (180 kg N + 90 kg P2O5 ha-1) and N90P45 (90 kg N ha-1 + 45 kg P2O5)-conducted at each of three different experimental sites with four cultivars (Baixang 139, Y Liangyou 1, Guiyu 9, and Teyou 582). Results showed that the leaf area index (LAI) was 38.8% found higher in Guiyu 9 compared with Baxiang at reduced fertilization (N90P45). N90P45 resulted higher dry matter production at the heading (9411.2 kg ha-1) and maturity (15319.5 kg ha-1) stages in Teyou 582 at Beiliu. Fertilization (N180P90) had higher effective panicle number (4,158,800 panicle ha-1) and grains panicle-1 (113.84 grains) compared with other treatments. Teyou 582 treated with N90P45 and Y Liangyou 1 treated with N180P90 improved seed setting rate average by 82.91% and 72.17% compared with other treatments at Beiliu in both seasons, respectively. N0P0 and N90P45 increased the thousand-grain weight (TGW) of Y Liangyou 1 at Binyang (27.07 g) and Liucheng (27.84 g) during the early and late seasons, respectively. In Beiliu, the N90P45 treatment (6611.7 kg ha-1) of Teyou 582 increased grain yield compared with other treatments. Overall, our results suggested that reducing N and P at the ratio of 90:45 kg ha-1 in Teyou 582 and Y Liangyou 1 could increase rice grain yield and yield components.

Automated measurement of hip-knee-ankle angle on the unilateral lower limb X-rays using deep learning.

Significant inherent extra-articular varus angulation is associated with abnormal postoperative hip-knee-ankle (HKA) angle. At present, HKA is manually measured by orthopedic surgeons and it increases the doctors' workload. To automatically determine HKA, a deep learning-based automated method for measuring HKA on the unilateral lower limb X-rays was developed and validated. This study retrospectively selected 398 double lower limbs X-rays during 2018 and 2020 from Jilin University Second Hospital. The images (n = 398) were cropped into unilateral lower limb images (n = 796). The deep neural network was used to segment the head of hip, the knee, and the ankle in the same image, respectively. Then, the mean square error of distance between each internal point of each organ and the organ's boundary was calculated. The point with the minimum mean square error was set as the central point of the organ. HKA was determined using the coordinates of three organs' central points according to the law of cosines. In a quantitative analysis, HKA was measured manually by three orthopedic surgeons with a high consistency (176.90 ° ± 12.18°, 176.95 ° ± 12.23°, 176.87 ° ± 12.25°) as evidenced by the Kandall's W of 0.999 (p < 0.001). Of note, the average measured HKA by them (176.90 ° ± 12.22°) served as the ground truth. The automatically measured HKA by the proposed method (176.41 ° ± 12.08°) was close to the ground truth, showing no significant difference. In addition, intraclass correlation coefficient (ICC) between them is 0.999 (p < 0.001). The average of difference between prediction and ground truth is 0.49°. The proposed method indicates a high feasibility and reliability in clinical practice.

Combined application of biochar and nitrogen fertilizer improves rice yield, microbial activity and N-metabolism in a pot experiment.

The excessive use of synthetic nitrogen (N) fertilizers in rice (Oryza sativa L.) has resulted in high N loss, soil degradation, and environmental pollution in a changing climate. Soil biochar amendment is proposed as a climate change mitigation tool that supports carbon sequestration and reduces N losses and greenhouse gas (GHG) emissions from the soil. The current study evaluated the impact of four different rates of biochar (B) (C/B0-0 t ha-1, B1-20 t ha-1, B2-40 t ha-1, and B3-60 t ha-1) and two N levels (N1; low (270 kg N ha-1) and N2; high (360 kg N ha-1)), on rice (cultivar Zhenguiai) grown in pots. Significant increases in the average soil microbial biomass N (SMBN) (88%) and carbon (87%) were recorded at the highest rate of 60-ton ha-1B and 360 kg N ha-1 compared to the control (N1C) during both seasons (S1 and S2). The photochemical efficiency (Fv/Fm), quantum yield of the photosystem (PS) II (ΦPS II), electron transport rate (ETR), and photochemical quenching (qP) were enhanced at low rates of biochar applications (20 to 40 t B ha-1) for high and low N rates across the seasons. Nitrate reductase (NR), glutamine synthetase (GS), and glutamine 2-oxoglutarate aminotransferase (GOGAT) activity were, on average, 39%, 55%, and 63% higher in the N1B3, N2B2, and N2B3 treatments, respectively than the N1C. The grain quality was higher in the N1B3 treatment than the N1C, i.e., the protein content (PC), amylose content (AC), percent brown rice (BRP), and percent milled rice (MRP) were, on average, 16%, 28%, 4.6%, and 5% higher, respectively in both seasons. The results of this study indicated that biochar addition to the soil in combination with N fertilizers increased the dry matter (DM) content, N uptake, and grain yield of rice by 24%, 27%, and 64%, respectively, compared to the N1C.