[Effects of Application of Different Organic Materials on Phosphorus Accumulation and Transformation in Vegetable Fields].

Presently, the improvement of soil organic matter is the basis to ensure food security, but the accumulation and transformation characteristics of soil phosphorus (P) as affected by organic matter remain unclear. The accumulation, transformation, and migration characteristics of soil P in different soil layers of vegetable fields were researched under the application of organic materials. Six treatments were set up in the experiment:control (no fertilization), traditional fertilizer application by farmers, biochar, chicken manure, food waste, and straw application. Available phosphorus (Olsen-P), water-soluble phosphorus (CaCl2-P) content, soil phosphorus forms, soil organic matter (SOM), and pH were determined during the pepper harvest period. In the 0-5 cm and 5-10 cm soil layers, the available phosphorus content of traditional fertilization of farmers was higher, and the available phosphorus content of the four organic materials was in the order of straw > biochar > chicken manure > food waste. Compared to that with food waste, the straw and biochar treatments increased soil available phosphorus by 59.6%-67.3% and 29.1%-36.9%, respectively. The straw treatment could easily enhance the soil labile P pool, and soil labile P in the 0-5 cm soil layer increased by 47.3% and 35.1% compared with that under the chicken manure and food waste treatments, respectively. With the increase in soil depth, the proportion of available phosphorus in the chicken manure treatment decreased the least, and available phosphorus of the 20-30 cm soil layer accounted for 55.9% of the topsoil layer but only accounted for 16.0%-34.0% under treatment with the other three materials. Compared with that under the traditional fertilization of farmers, the pH significantly increased by 0.18-0.36 units after the application of organic fertilizer, and the pH of the chicken manure and food waste treatments was significantly higher than that of biochar and straw (P < 0.05). SOM content under the biochar treatment significantly increased by 7.7%-17.6% compared to that under the other three organic materials. Among the four organic materials, the straw treatment boosted the labile P pool the most, which was conducive to the rapid increase in plant-available P. Phosphorus was most likely to migrate downward under the chicken manure treatment. In the field management based on soil fertility enhancement, the application of biochar could not only improve soil pH and SOM but also avoid excessive accumulation of phosphorus in the surface layer, which decreases environmental risks.

Application of interpretable machine learning algorithms to predict distant metastasis in ovarian clear cell carcinoma.

BACKGROUND: Ovarian clear cell carcinoma (OCCC) represents a subtype of ovarian epithelial carcinoma (OEC) known for its limited responsiveness to chemotherapy, and the onset of distant metastasis significantly impacts patient prognoses. This study aimed to identify potential risk factors contributing to the occurrence of distant metastasis in OCCC. METHODS: Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, we identified patients diagnosed with OCCC between 2004 and 2015. The most influential factors were selected through the application of Gaussian Naive Bayes (GNB) and Adaboost machine learning algorithms, employing a Venn test for further refinement. Subsequently, six machine learning (ML) techniques, namely XGBoost, LightGBM, Random Forest (RF), Adaptive Boosting (Adaboost), Support Vector Machine (SVM), and Multilayer Perceptron (MLP), were employed to construct predictive models for distant metastasis. Shapley Additive Interpretation (SHAP) analysis facilitated a visual interpretation for individual patient. Model validity was assessed using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and the area under the receiver operating characteristic curve (AUC). RESULTS: In the realm of predicting distant metastasis, the Random Forest (RF) model outperformed the other five machine learning algorithms. The RF model demonstrated accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and AUC (95% CI) values of 0.792 (0.762-0.823), 0.904 (0.835-0.973), 0.759 (0.731-0.787), 0.221 (0.186-0.256), 0.974 (0.967-0.982), 0.353 (0.306-0.399), and 0.834 (0.696-0.967), respectively, surpassing the performance of other models. Additionally, the calibration curve's Brier Score (95%) for the RF model reached the minimum value of 0.06256 (0.05753-0.06759). SHAP analysis provided independent explanations, reaffirming the critical clinical factors associated with the risk of metastasis in OCCC patients. CONCLUSIONS: This study successfully established a precise predictive model for OCCC patient metastasis using machine learning techniques, offering valuable support to clinicians in making informed clinical decisions.

Clinical manifestation, lifestyle, and treatment patterns of chronic erosive gastritis: A multicenter real-world study in China.

BACKGROUND: Although chronic erosive gastritis (CEG) is common, its clinical characteristics have not been fully elucidated. The lack of consensus regarding its treatment has resulted in varied treatment regimens. AIM: To explore the clinical characteristics, treatment patterns, and short-term outcomes in CEG patients in China. METHODS: We recruited patients with chronic non-atrophic or mild-to-moderate atrophic gastritis with erosion based on endoscopy and pathology. Patients and treating physicians completed a questionnaire regarding history, endoscopic findings, and treatment plans as well as a follow-up questionnaire to investigate changes in symptoms after 4 wk of treatment. RESULTS: Three thousand five hundred sixty-three patients from 42 centers across 24 cities in China were included. Epigastric pain (68.0%), abdominal distension (62.6%), and postprandial fullness (47.5%) were the most common presenting symptoms. Gastritis was classified as chronic non-atrophic in 69.9% of patients. Among those with erosive lesions, 72.1% of patients had lesions in the antrum, 51.0% had multiple lesions, and 67.3% had superficial flat lesions. In patients with epigastric pain, the combination of a mucosal protective agent (MPA) and proton pump inhibitor was more effective. For those with postprandial fullness, acid regurgitation, early satiety, or nausea, a MPA appeared more promising. CONCLUSION: CEG is a multifactorial disease which is common in Asian patients and has non-specific symptoms. Gastroscopy may play a major role in its detection and diagnosis. Treatment should be individualized based on symptom profile.

A Novel Necroptosis-Related Signature Can Predict Prognosis and Chemotherapy Sensitivity in Multiple Myeloma.

BACKGROUND: Necroptosis is an inflammatory cell death mode, and its association with multiple myeloma (MM) remains unclear. METHODS: This prospective study first analyzed the association between necroptosis-related signature as well as prognosis and chemotherapy sensitivity in MM using the necroptosis score. Consensus clustering was used to identify necroptosis-related molecular clusters. Least absolute shrinkage and selection operator analysis and multivariate Cox regression analysis were performed to establish the prognostic model of necroptosis-related genes (NRGs). RESULTS: A high necroptosis score was associated with poor prognosis and abundant immune infiltration. Two molecular clusters (clusters A and B) significantly differed in terms of prognosis and tumor microenvironment. Cluster B had a worse prognosis and higher tumor marker pathway activity than cluster A. The risk score model based on four NRGs can accurately predict the prognosis of patients with MM, which was validated in two validation cohorts. Receiver operating characteristic curve analysis showed that the area under the curves of the risk score in predicting the 1-, 3-, and 5-year survival rates were 0.710, 0.758, and 0.834, respectively. Further, the activity of pathways related to proliferation and genetic regulation in the high-risk group significantly increased. The drug prediction results showed that the low-risk score group was more sensitive to bortezomib, cytarabine, and doxorubicin than the high-risk score group. Meanwhile, the high-risk score group was more sensitive to lenalidomide and vinblastine than the low-risk score group. Finally, the upregulation of model genes CHMP1A, FAS, JAK3, and HSP90AA1 in clinical samples collected from patients with MM was validated via real-time polymerase chain reaction. CONCLUSION: A systematic analysis of NRGs can help identify potential necroptosis-related mechanisms and provide novel biomarkers for MM prognosis prediction, tumor microenvironment evaluation, and personalized treatment planning.

[Analysis on Driving Factors, Reduction Potential, and Environmental Effect of Inorganic Fertilizer Input in Chongqing].

In this study, we sought to quantify the effect of planting structure change on fertilizer input and environmental cost in Chongqing and develop scientific and rational strategies for chemical fertilizer reduction. Based on the crop fertilizer quota standard and large sample farmer survey data under the medium productivity level in Chongqing, we evaluated and analyzed the application reduction potential and environmental benefits of fertilizer with the difference method and life cycle assessment. The results showed that:① since Chongqing became a municipality directly under the central government (1997), Chongqing crop planting structure had greatly changed, and the proportion of food crop (rice, corn, wheat, bean, and potato) decreased by 21%. The area of fruits and vegetables increased from 3.36×105 hm2 to 1.05×106 hm2, and their proportion increased by 20%. ② Nearly 55% of fertilizers had been consumed by vegetable (37%) and citrus production systems, and 11%, 12%, and 12% of fertilizers were consumed by rice, corn, and potato, respectively. ③ The total fertilizer reduction of the Chongqing planting industry could reach up to 1.69×105 tons during the period of "the 14th Five-Year Plan," with a fertilizer reduction potential of 18.6%. The fertilizer reduction potential (reduction amount) of rice, corn, citrus, and vegetables would reach 0.3% (2.9×102 tons), 12% (1.45×104 tons), 21% (3.65×104 tons), and 30% (1.18×105 tons), respectively. On the other hand, the rape system was insufficient in phosphorus potassium fertilizers, and the corn tended to be insufficient in potash fertilizer. ④ The current production level was low, and the nitrogen loss, greenhouse gas emissions, and eutrophication potential in the planting industry of Chongqing reached 1.81×105 tons (N), 1.43×107 tons (CO2-eq), and 1.74×105 tons (PO4-eq). With the increase in the realization degree of the crop quota standard (60%-100%), the reactive nitrogen loss, greenhouse gas emissions, and eutrophication potential decreased by 14.9%-24.9%, 10.1%-16.7%, and 13.8%-23%, respectively. The structure of the planting industry in Chongqing significantly changed, the total fertilizer consumption in Chongqing tended to decline gradually, and the fertilization intensity of commercial crops stayed at a high level. The agricultural fertilizer reduction potential and the reactive nitrogen and greenhouse gas emission reduction potential were large, especially for citrus and vegetable production systems. However, it is also necessary to pay attention to insufficient corn potash fertilizer and rape phosphorus potassium fertilizer investment and carry out collaborative promotion of fertilizer reduction.

Racial and ethnic disparities in untreated patients with hepatitis C virus-related hepatocellular carcinoma but not in those with sustained virologic response.

BACKGROUND: Racial and ethnic disparities exist for hepatitis C virus (HCV) treatment and hepatocellular carcinoma (HCC) survival. AIM: To evaluate the impact of HCV treatment on such disparities. METHODS: In a retrospective cohort study, we analysed 6069 patients with HCV-related HCC (54.2% Asian, 30.1% White, 8.5% Black, and 7.3% Hispanic) from centres in the United States and Asia. RESULTS: The mean age was 61, 60, 59 and 68, respectively, for White, Black, Hispanic and Asian patients. Black patients were most likely to have Barcelona Clinic Liver Cancer stage D, vascular invasion and distant metastasis (23% vs. 5%-15%, 20% vs. 10%-17% and 10% vs. 5%-7%, respectively; all p < 0.0001). Treatment rate with direct-acting antiviral agents (DAA) was 35.9% for Asian, 34.9% for White, 30.3% for Hispanic (30.3%), and 18.7% for Black patients (p < 0.0001). Among those untreated or without sustained virologic response (SVR), 10-year survival rates were 35.4, 27.5, 19.3 and 14.0, respectively, for Asian, Hispanic, White and Black patients (p < 0.0001). There were no statistically significant differences among those with SVR (p = 0.44). On multivariable analysis adjusted for relevant confounders, there was no statistically significant association between survival and being Hispanic (aHR: 0.68, p = 0.26) or Black (aHR: 1.18, p = 0.60) versus White. There was a significant association between being Asian American and survival (aHR: 0.24, p = 0.001; non-U.S. Asian: aHR: 0.66, p = 0.05), and for SVR (aHR: 0.30, p < 0.0001). CONCLUSION: DAA treatment rates were suboptimal. Racial and ethnic disparities resolved with HCV cure. Early diagnosis and improved access to HCV treatment is needed for all patients with HCV infection.

Identification of cellular senescence-related signature for predicting prognosis and therapeutic response of acute myeloid leukemia.

Cellular senescence is closely related to the occurrence, development, and immune regulation of cancer. However, the predictive value of cellular senescence-related signature in clinical outcome and treatment response in acute myeloid leukemia (AML) remains unexplored. By analyzing the expression profile of cellular senescence-related genes (CSRGs) in AML samples in the TCGA database, we found that cellular senescence is closely related to the prognosis and tumor microenvironment of AML patients, and compared with normal samples, the overall expression level of senescent inducing genes in AML samples was down-regulated, while inhibitory genes were up-regulated. The risk score model further constructed and verified based on CSRGs could be used as an independent prognostic predictor for AML patients, and the overall survival (OS) of high-risk patients was significantly shortened. The area under ROC curve (AUC) values for the prediction of 1-, 3- and 5-year OS were 0.759, 0.749, and 0.806, respectively. In addition, patients with high-risk scores are more sensitive to treatment with cytarabine and may benefit from anti-PD-1 immunotherapy. In conclusion, our results suggest that the cellular senescence-related signature is a strong biomarker of immunotherapy response and prognosis in AML.

Molecular subtypes predict therapeutic responses and identifying and validating diagnostic signatures based on machine learning in chronic myeloid leukemia.

Chronic myeloid leukemia (CML) is a hematological tumor derived from hematopoietic stem cells. The aim of this study is to analyze the biological characteristics and identify the diagnostic markers of CML. We obtained the expression profiles from the Gene Expression Omnibus (GEO) database and identified 210 differentially expressed genes (DEGs) between CML and normal samples. These DEGs are mainly enriched in immune-related pathways such as Th1 and Th2 cell differentiation, primary immunodeficiency, T cell receptor signaling pathway, antigen processing and presentation pathways. Based on these DEGs, we identified two molecular subtypes using a consensus clustering algorithm. Cluster A was an immunosuppressive phenotype with reduced immune cell infiltration and significant activation of metabolism-related pathways such as reactive oxygen species, glycolysis and mTORC1; Cluster B was an immune activating phenotype with increased infiltration of CD4 + and CD8 + T cells and NK cells, and increased activation of signaling pathways such as interferon gamma (IFN-γ) response, IL6-JAK-STAT3 and inflammatory response. Drug prediction results showed that patients in Cluster B had a higher therapeutic response to anti-PD-1 and anti-CTLA4 and were more sensitive to imatinib, nilotinib and dasatinib. Support Vector Machine Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage Selection Operator (LASSO) and Random Forest (RF) algorithms identified 4 CML diagnostic genes (HDC, SMPDL3A, IRF4 and AQP3), and the risk score model constructed by these genes improved the diagnostic accuracy. We further validated the diagnostic value of the 4 genes and the risk score model in a clinical cohort, and the risk score can be used in the differential diagnosis of CML and other hematological malignancies. The risk score can also be used to identify molecular subtypes and predict response to imatinib treatment. These results reveal the characteristics of immunosuppression and metabolic reprogramming in CML patients, and the identification of molecular subtypes and biomarkers provides new ideas and insights for the clinical diagnosis and treatment.

The Daily Intake Levels of Copper, Selenium, and Zinc Are Associated with Osteoarthritis but Not with Rheumatoid Arthritis in a Cross-sectional Study.

The present study examined potential association between the daily intake and serum levels of copper (Cu), selenium (Se), and zinc (Zn) and the risk of osteoarthritis (OA) and rheumatoid arthritis (RA) using data from the National Health and Nutrition Examination Survey (NHANES). Daily intake and serum concentrations of Cu, Zn, and Se in 4200 adults from the 2011-2016 NHANES were examined and divided into normal, OA patients, and RA patients. The level of serum Cu was higher in OA and RA than in non-arthritis, while the levels of serum Se and Zn were no different in the three groups. Serum Se and Zn, but not Cu, concentrations were highly correlated with daily intake. Cu, Se, and Zn intake was independently associated with increased risk of OA, but not with RA. And there was a trend for higher odds of OA among participants in the higher Cu, Se, and Zn intake. Future large longitudinal studies are warranted to confirm these findings.

Splicing factor-mediated regulation patterns reveals biological characteristics and aid in predicting prognosis in acute myeloid leukemia.

BACKGROUND: Alternative splicing (AS) of RNA is a fundamental biological process that shapes protein diversity. Many non-characteristic AS events are involved in the onset and development of acute myeloid leukemia (AML). Abnormal alterations in splicing factors (SFs), which regulate the onset of AS events, affect the process of splicing regulation. Hence, it is important to explore the relationship between SFs and the clinical features and biological processes of patients with AML. METHODS: This study focused on SFs of the classical heterogeneous nuclear ribonucleoprotein (hnRNP) family and arginine and serine/arginine-rich (SR) splicing factor family. We explored the relationship between the regulation patterns associated with the expression of SFs and clinicopathological factors and biological behaviors of AML based on a multi-omics approach. The biological functions of SRSF10 in AML were further analyzed using clinical samples and in vitro experiments. RESULTS: Most SFs were upregulated in AML samples and were associated with poor prognosis. The four splicing regulation patterns were characterized by differences in immune function, tumor mutation, signaling pathway activity, prognosis, and predicted response to chemotherapy and immunotherapy. A risk score model was constructed and validated as an independent prognostic factor for AML. Overall survival was significantly shorter in the high-risk score group. In addition, we confirmed that SRSF10 expression was significantly up-regulated in clinical samples of AML, and knockdown of SRSF10 inhibited the proliferation of AML cells and promoted apoptosis and G1 phase arrest during the cell cycle. CONCLUSION: The analysis of splicing regulation patterns can help us better understand the differences in the tumor microenvironment of patients with AML and guide clinical decision-making and prognosis prediction. SRSF10 can be a potential therapeutic target and biomarker for AML.

Neoadjuvant Chemotherapy With CAPOX Versus Chemoradiation for Locally Advanced Rectal Cancer With Uninvolved Mesorectal Fascia (CONVERT): Initial Results of a Phase III Trial.

OBJECTIVE: To compare neoadjuvant chemotherapy (nCT) with CAPOX alone versus neoadjuvant chemoradiotherapy (nCRT) with capecitabine in locally advanced rectal cancer (LARC) with uninvolved mesorectal fascia (MRF). BACKGROUND DATA: nCRT is associated with higher surgical complications, worse long-term functional outcomes, and questionable survival benefits. Comparatively, nCT alone seems a promising alternative treatment in lower-risk LARC patients with uninvolved MRF. METHODS: Patients between June 2014 and October 2020 with LARC within 12 cm from the anal verge and uninvolved MRF were randomly assigned to nCT group with 4 cycles of CAPOX (Oxaliplatin 130 mg/m2 IV day 1 and Capecitabine 1000 mg/m2 twice daily for 14 d. Repeat every 3 wk) or nCRT group with Capecitabine 825 mg/m² twice daily administered orally and concurrently with radiation therapy (50 Gy/25 fractions) for 5 days per week. The primary end point is local-regional recurrence-free survival. Here we reported the results of secondary end points: histopathologic response, surgical events, and toxicity. RESULTS: Of the 663 initially enrolled patients, 589 received the allocated treatment (nCT, n=300; nCRT, n=289). Pathologic complete response rate was 11.0% (95% CI, 7.8-15.3%) in the nCT arm and 13.8% (95% CI, 10.1-18.5%) in the nCRT arm ( P =0.33). The downstaging (ypStage 0 to 1) rate was 40.8% (95% CI, 35.1-46.7%) in the nCT arm and 45.6% (95% CI, 39.7-51.7%) in the nCRT arm ( P =0.27). nCT was associated with lower perioperative distant metastases rate (0.7% vs. 3.1%, P =0.03) and preventive ileostomy rate (52.2% vs. 63.6%, P =0.008) compared with nCRT. Four patients in the nCT arm received salvage nCRT because of local disease progression after nCT. Two patients in the nCT arm and 5 in the nCRT arm achieved complete clinical response and were treated with a nonsurgical approach. Similar results were observed in subgroup analysis. CONCLUSIONS: nCT achieved similar pCR and downstaging rates with lower incidence of perioperative distant metastasis and preventive ileostomy compared with nCRT. CAPOX could be an effective alternative to neoadjuvant therapy in LARC with uninvolved MRF. Long-term follow-up is needed to confirm these results.

Ferroptosis-related molecular patterns reveal immune escape, inflammatory development and lipid metabolism characteristics of the tumor microenvironment in acute myeloid leukemia.

Background: An increasing number of studies have revealed the influencing factors of ferroptosis. The influence of immune cell infiltration, inflammation development and lipid metabolism in the tumor microenvironment (TME) on the ferroptosis of tumor cells requires further research and discussion. Methods: We explored the relationship between ferroptosis-related genes and acute myeloid leukemia (AML) from the perspective of large sample analysis and multiomics, used multiple groups to identify and verify ferroptosis-related molecular patterns, and analyzed the sensitivity to ferroptosis and the state of immune escape between different molecular pattern groups. The single-sample gene set enrichment analysis (ssGSEA) algorithm was used to quantify the phenotypes of ferroptosis-related molecular patterns in individual patients. HL-60 and THP-1 cells were treated with ferroptosis inducer RSL3 to verify the therapeutic value of targeted inhibition of GPX4. Results: Three ferroptosis-related molecular patterns and progressively worsening phenotypes including immune activation, immune exclusion and immunosuppression were found with the two different sequencing approaches. The FSscore we constructed can quantify the development of ferroptosis-related phenotypes in individual patients. The higher the FSscore is, the worse the patient's prognosis. The FSscore is also highly positively correlated with pathological conditions such as inflammation development, immune escape, lipid metabolism, immunotherapy resistance, and chemotherapy resistance and is negatively correlated with tumor mutation burden. Moreover, RSL3 can induce ferroptosis of AML cells by reducing the protein level of GPX4. Conclusions: This study revealed the characteristics of immunity, inflammation, and lipid metabolism in the TME of different AML patients and differences in the sensitivity of tumor cells to ferroptosis. The FSscore can be used as a biomarker to provide a reference for the clinical evaluation of the pathological characteristics of AML patients and the design of personalized treatment plans. And GPX4 is a potential target for AML treatment.

[Impact of Nitrification Inhibitors on Vegetable Production Yield, Nitrogen Fertilizer Use Efficiency and Nitrous Oxide Emission Reduction in China: Meta Analysis].

Due to the long-term excessive fertilization in the vegetable system in China, nitrogen use efficiency (NUE) is low, and the environmental problem is serious. Nitrogen fertilizer combined with nitrification inhibitor is an effective strategy to alleviate the loss of active nitrogen and increase vegetable yield. However, systematic research on the above is lacking. Meta-analysis was used to systematically analyze the effects of nitrogen fertilizer combined with nitrification inhibitors[dicyandiamide (DCD), 3,4-dimethylpyrazole phosphate (DMPP), and 2-chloro-6-(trichloromethyl)pyridine (NP)] on the yield, plant nitrogen uptake, nitrogen fertilizer use efficiency, and nitrous oxide emission reduction effects in vegetable production in China. This study further revealed the impacts of different field management measures on their effects. The results showed that the combination of nitrogen fertilizer and nitrification inhibitor could significantly increase vegetable yield (9.2%), plant nitrogen uptake (10.4%), and nitrogen fertilizer use efficiency (11.2%) but reduce nitrous oxide emissions (28.4%). Among the different types of nitrification inhibitors, NP had the highest impact on the yield-increasing effect and the nitrous oxide emission reduction effect, which were 16.1% and 32.0%, respectively, followed by that of DMPP and DCD. Nitrification inhibitors could significantly increase vegetable yield (6.7%-14.7%) and reduce N2O emissions (14.6%-36.8%) in different nitrogen fertilizer rates. In neutral and alkaline vegetable soil, the yield-increasing effect and the reduction effect of nitrous oxide were higher than those in acidic soil. Nitrification inhibitors had significant effects on yield increase and nitrous oxide reduction under the conditions of greenhouse or open-field cultivation, root vegetables, and leafy vegetables. Principal component analysis (PCA) showed that soil total nitrogen content and soil pH were the main factors that promoted the increase in vegetable yields and drove nitrous oxide emissions under the application of nitrification inhibitors. In summary, nitrification inhibitors were an important measure to achieve the goal of improving quality and fertilizer use efficiency, while saving fertilizer and reducing emissions in vegetable production. Farmers should choose suitable types of nitrification inhibitors according to soil and field management measures to maximize their effectiveness.

A novel fatty acid metabolism-related signature identifies features of the tumor microenvironment and predicts clinical outcome in acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is the most common malignancy of the hematological system, and there are currently a number of studies regarding abnormal alterations in energy metabolism, but fewer reports related to fatty acid metabolism (FAM) in AML. We therefore analyze the association of FAM and AML tumor development to explore targets for clinical prognosis prediction and identify those with potential therapeutic value. METHODS: The identification of AML patients with different fatty acid metabolism characteristics was based on a consensus clustering algorithm. The CIBERSORT algorithm was used to calculate the proportion of infiltrating immune cells. We used Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis to construct a signature for predicting the prognosis of AML patients. The Genomics of Drug Sensitivity in Cancer database was used to predict the sensitivity of patient samples in high- and low-risk score groups to different chemotherapy drugs. RESULTS: The consensus clustering approach identified three molecular subtypes of FAM that exhibited significant differences in genomic features such as immunity, metabolism, and inflammation, as well as patient prognosis. The risk-score model we constructed accurately predicted patient outcomes, with area under the receiver operating characteristic curve values of 0.870, 0.878, and 0.950 at 1, 3, and 5 years, respectively. The validation cohort also confirmed the prognostic evaluation performance of the risk score. In addition, higher risk scores were associated with stronger fatty acid metabolisms, significantly higher expression levels of immune checkpoints, and significantly increased infiltration of immunosuppressive cells. Immune functions, such as inflammation promotion, para-inflammation, and type I/II interferon responses, were also significantly activated. These results demonstrated that immunotherapy targeting immune checkpoints and immunosuppressive cells, such as myeloid-derived suppressor cells (MDSCs) and M2 macrophages, are more suitable for patients with high-risk scores. Finally, the prediction results of chemotherapeutic drugs showed that samples in the high-risk score group had greater treatment sensitivity to four chemotherapy drugs in vitro. CONCLUSIONS: The analysis of the molecular patterns of FAM effectively predicted patient prognosis and revealed various tumor microenvironment (TME) characteristics.

Lactobacillus plantarum improves LPS-induced Caco2 cell line intestinal barrier damage via cyclic AMP-PKA signaling.

Lactobacillus plantarum (LP) has been shown to exhibit protective effects on intestinal barrier function in septic rats, although the regulatory mechanism has not been established. We determined whether LP imparts such protective effects in a lipopolysaccharide (LPS)-induced Caco2 cell monolayer model and whether cAMP-PKA signaling is the underlying mechanism of action. The cyclic adenosine monophosphate (cAMP) agonist, forskolin (FSK), and the protein kinase A (PKA) inhibitor, HT89, were used to study the protective effect of LP on the destruction of the tight junction (TJ) structure of cells treated with LPS and the corresponding changes in cAMP-PKA signaling. Our experimental results demonstrated that LP promoted the expression of TJ proteins between Caco2 cells after LPS treatment, and increased the electrical barrier detection (TEER) between Caco2 cells. Moreover, transmission electron microscopy (TEM) revealed that the TJ structural integrity of cells treated with LPS + LP was improved compared to cells treated with LPS alone. In addition, our findings were consistent between the FSK and LP intervention group, while HT89 inhibited LP influence. Taken together, our results indicate that LP has an improved protective effect on LPS-induced damage to the monolayer membrane barrier function of Caco2 cells and is regulated by the cAMP-PKA pathway.

Inflammatory response mediates cross-talk with immune function and reveals clinical features in acute myeloid leukemia.

Accumulated genetic mutations are an important cause for the development of acute myeloid leukemia (AML), but abnormal changes in the inflammatory microenvironment also have regulatory effects on AML. Exploring the relationship between inflammatory response and pathological features of AML has implications for clinical diagnosis, treatment and prognosis evaluation. We analyzed the expression variation landscape of inflammatory response-related genes (IRRGs) and calculated an inflammatory response score for each sample using the gene set variation analysis (GSVA) algorithm. The differences in clinical- and immune-related characteristics between high- and low-inflammatory response groups were further analyzed. We found that most IRRGs were highly expressed in AML samples, and patients with high inflammatory response had poor prognosis and were accompanied with highly activated chemokine-, cytokine- and adhesion molecule-related signaling pathways, higher infiltration ratios of monocytes, neutrophils and M2 macrophages, high activity of type I/II interferon (IFN) response, and higher expression of immune checkpoints. We also used the Genomics of Drug Sensitivity in Cancer (GDSC) database to predict the sensitivity of AML samples with different inflammatory responses to common drugs, and found that AML samples with low inflammatory response were more sensitive to cytarabine, doxorubicin and midostaurin. SubMap algorithm also demonstrated that high-inflammatory response patients are more suitable for anti-PD-1 immunotherapy. Finally, we constructed a prognostic risk score model to predict the overall survival (OS) of AML patients. Patients with higher risk score had significantly shorter OS, which was confirmed in two validation cohorts. The analysis of inflammatory response patterns can help us better understand the differences in tumor microenvironment (TME) of AML patients, and guide clinical medication and prognosis prediction.

m(6)A Modification of lncRNA NEAT1 Regulates Chronic Myelocytic Leukemia Progression via miR-766-5p/CDKN1A Axis.

BACKGROUND: Chronic myeloid leukemia (CML) is an acquired hematopoietic stem malignant disease originating from the myeloid system. Long non-coding RNAs (lncRNAs) have been widely explored in cancer tumorigenesis. However, their roles in CML remain largely unclear. METHODS: The peripheral blood mononuclear cells (PBMCs) and CML cell lines (K562, KCL22, MEG01, BV173) were collected for in vitro research. Real-time quantitative polymerase chain reaction was used to determine the mRNA expression levels. Cell viability and apoptosis were analyzed by cell counting kit 8 and flow cytometry assays. The targeting relationships were predicted using Starbase and TargetScan and ulteriorly verified by RNA pull-down and luciferase reporter assays. Western blotting assay was performed to assess the protein expressions. N6-methyladenosine (m6A) modification sites were predicted by SRAMP and confirmed by Methylated RNA immunoprecipitation (MeRIP) assay. RESULTS: LncRNA nuclear-enriched abundant transcript 1 (NEAT1) expression levels were decreased in the CML cell lines and PBMCs of CML patients. Moreover, METTL3-mediated m6A modification induced the aberrant expression of NEAT1 in CML. Overexpression of NEAT1 inhibited cell viability and promoted the apoptosis of CML cells. Additionally, miR-766-5p was upregulated in CML PBMCs and abrogated the effects of NEAT1 on cell viability and apoptosis of the CML cells. Further, CDKN1A was proved to be the target gene of miR-766-5p and was downregulated in the CML PBMCs. Knockdown of CDKN1A reversed the effects of NEAT1. CONCLUSION: The current research elucidates a novel METTL3/NEAT1/miR-766-5p/CDKN1A axis which plays a critical role in the progression of CML.

Quantitative Proteomic Analysis of Plasma Exosomes to Identify the Candidate Biomarker of Imatinib Resistance in Chronic Myeloid Leukemia Patients.

BACKGROUND: Imatinib (IM), a tyrosine kinase inhibitor (TKI), has markedly improved the survival and life quality of chronic myeloid leukemia (CML) patients. However, the lack of specific biomarkers for IM resistance remains a serious clinical challenge. Recently, growing evidence has suggested that exosome-harbored proteins were involved in tumor drug resistance and could be novel biomarkers for the diagnosis and drug sensitivity prediction of cancer. Therefore, we aimed to investigate the proteomic profile of plasma exosomes derived from CML patients to identify ideal biomarkers for IM resistance. METHODS: We extracted exosomes from pooled plasma samples of 9 imatinib-resistant CML patients and 9 imatinib-sensitive CML patients by ultracentrifugation. Then, we identified the expression levels of exosomal proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS) based label free quantification. Bioinformatics analyses were used to analyze the proteomic data. Finally, the western blot (WB) and parallel reaction monitoring (PRM) analyses were applied to validate the candidate proteins. RESULTS: A total of 2812 proteins were identified in plasma exosomes from imatinib-resistant and imatinib-sensitive CML patients, including 279 differentially expressed proteins (DEPs) with restricted criteria (fold change≥1.5 or ≤0.667, p<0.05). Compared with imatinib-sensitive CML patients, 151 proteins were up-regulated and 128 proteins were down-regulated. Bioinformatics analyses revealed that the main function of the upregulated proteins was regulation of protein synthesis, while the downregulated proteins were mainly involved in lipid metabolism. The top 20 hub genes were obtained using STRING and Cytoscape, most of which were components of ribosomes. Moreover, we found that RPL13 and RPL14 exhibited exceptional upregulation in imatinib-resistant CML patients, which were further confirmed by PRM and WB. CONCLUSION: Proteomic analysis of plasma exosomes provides new ideas and important information for the study of IM resistance in CML. Especially the exosomal proteins (RPL13 and RPL14), which may have great potential as biomarkers of IM resistance.

A Novel Prognostic Score Based on ZG16 for Predicting CRC Survival.

BACKGROUND: Colorectal cancer (CRC) is one of the lethal malignant tumors worldwide. However, the underlying mechanism of CRC and its biomarkers remain unclear. The aim of this study was to identify the key genes associated with CRC and to further explore their prognostic significance. METHODS: Four expression profile datasets (GSE41657, GSE74602, GSE113513, and GSE40967) downloaded from Gene Expression Omnibus (GEO) and one RNAseq dataset of CRC from The Cancer Genome Atlas (TCGA) database were included in our study. The Cox model was utilized for univariate or multivariate survival analysis. GEPIA and HAP database were adopted for verification of DEGs (ZG16). The decision curve analysis (DCA) and time-dependent ROC were chosen for evaluating the prognostic effectiveness of biomarkers. RESULTS: In total, 88 differentially expressed genes (DEGs) were identified, and the GO and KEGG enrichment analyses of DEGs were processed. After, the protein-protein interaction (PPI) network was constructed and 15 hub genes including ZG16 were identified. The differential expression of ZG16 between tumor and normal colorectal tissues were further verified in GEPIA and HAP database. Subsequent survival indicated that expression of ZG16 is negatively correlated with overall survival of OS and is an independent prognostic factor for CRC patients. Furthermore, the construction of a prognostic score containing ZG16, TNM stage and age exhibited superior effectiveness for predicting long-term survival of CRC patients. Additionally, our results were verified using the GSE40967 dataset, which indicated an improved performance of combined risk score based on ZG16 for predicting OS of CRC patients. CONCLUSION: ZG16 is a potential parameter for predicting prognosis in CRC. Furthermore, a combination of ZG16, TNM stage, and age allows improved prognosis of CRC.

Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis.

This article aims to explore the underlying molecular mechanisms and prognosis-related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis-related gene chip data were downloaded from GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R-package pre-treatment. Functional annotations and related signalling pathways were analysed using DAVID software. GEPIA (Gene Expression Profiling Interactive Analysis) was used to perform prognostic analysis, and differential genes associated with prognosis were screened and validated using data from GEO. We screened 40 healthy patients, 40 primary pancreatic cancer and 40 metastatic pancreatic cancer patients, collected serum, designed primers and used qPCR to test the expression of prognosis-related genes in each group. 109 differentially expressed genes related with pancreatic cancer metastasis were screened, of which 49 were up-regulated and 60 were down-regulated. Functional annotation and pathway analysis revealed differentially expressed genes were mainly concentrated in protein activation cascade, extracellular matrix construction, decomposition, etc In the biological process, it is mainly involved in signalling pathways such as PPAR, PI3K-Akt and ECM receptor interaction. Prognostic analysis showed the expression levels of four genes were significantly correlated with the overall survival time of patients with pancreatic cancer, namely SCG5, CRYBA2, CPE and CHGB. qPCR experiments showed the expression of these four genes was decreased in both the primary pancreatic cancer group and the metastatic pancreatic cancer group, and the latter was more significantly reduced. Pancreatic cancer metastasis is closely related to the activation of PPAR pathway, PI3K-Akt pathway and ECM receptor interaction. SCG5, CRYBA2, CPE and CHGB genes are associated with the prognosis of pancreatic cancer, and their low expression suggests a poor prognosis.