120 research outputs found

    Electrochemical Treatment of Synthetic Wastewaters Contaminated by Organic Pollutants at Ti4O7 Anode. Study of the Role of Operative Parameters by Experimental Results and Theoretical Modelling

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    In the last years, an increasing attention has been devoted to the utilization of anodic oxidation (AO) technologies for the treatment of wastewater polluted by recalcitrant organics. Recently, Ti4O7 was proposed as a promising anode for AO for the treatment of various organics. Here the potential utilization of commercial Ti4O7 anodes has been evaluated considering the electrochemical treatment of synthetic wastewater contaminated by three very different organic molecules (namely, oxalic acid, phenol and Acid Orange 7), all characterized by a very high resistance to AO. The performances of Ti4O7 were compared with that of two largely investigated anodes: Boron-doped diamond (BDD), which is probably the most effective electrode for AO, and an Ir-based anode which presents a relatively low cost. Moreover, the effect of various operative conditions (current density, mixing rate and initial concentration of the organic) was evaluated by both experimental studies and the adoption of a theoretical model previously developed for BDD anodes. It was shown that the performances of the process can be improved by a proper selection of operative conditions. Moreover, it was found that the proposed model can be effectively used to predict the effect of operative parameters at Ti4O7 anodes, thus helping the process optimization

    A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma

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    Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM’s great heterogeneity and incurability, risk assessment and treatment choices are still difficult.Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes.Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study.Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients

    Non-Fossil Origin Explains the Large Seasonal Variation of Highly Processed Organic Aerosol in the Northeastern Tibetan Plateau (3,200 m a.s.l.)

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    Carbonaceous aerosol plays an important role in climate, but its sources and atmospheric processes are least understood in the Tibetan Plateau (TP), a remote yet climatically sensitive region. This study presents the first seasonal cycle of radiocarbon and stable isotope 13C of organic and elemental carbon (OC and EC) in the atmosphere of the northeastern TP. Large seasonal variations of EC and OC concentrations were explained by non-fossil sources. Regardless of the season, fossil contribution to OC was strongly correlated with inverse OC concentrations. This allowed the separating a constant background source and a source responsible for OC variability that was mostly of non-fossil origin. The 13C signature of OC shows that OC was highly atmospherically processed and thus less volatile than OC found near sources or in urban areas. The 13C-depleted secondary sources contributed strongly to more volatile OC, whereas the 13C-enriched less volatile OC suggests the influence of atmospheric aging.</p

    Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma

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    Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p &lt; 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients

    Identification and validation of a platelet-related signature for predicting survival and drug sensitivity in multiple myeloma

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    Background: Significant progress has been achieved in the management of multiple myeloma (MM) by implementing high-dose therapy and stem cell transplantation. Moreover, the prognosis of patients has been enhanced due to the introduction of novel immunomodulatory drugs and the emergence of new targeted therapies. However, predicting the survival rates of patients with multiple myeloma is still tricky. According to recent researches, platelets have a significant impact in affecting the biological activity of tumors and are essential parts of the tumor microenvironment. Nonetheless, it is still unclear how platelet-related genes (PRGs) connect to the prognosis of multiple myeloma.Methods: We analyzed the expression of platelet-related genes and their prognostic value in multiple myeloma patients in this study. We also created a nomogram combining clinical metrics. Furthermore, we investigated disparities in the biological characteristics, immunological microenvironment, and reaction to immunotherapy, along with analyzing the drug susceptibility within diverse risk groups.Results: By using the platelet-related risk model, we were able to predict patients’ prognosis more accurately. Subjects in the high-risk cohort exhibited inferior survival outcomes, both in the training and validation datasets, as compared to those in the low-risk cohort (p &lt; 0.05). Moreover, there were differences in the immunological microenvironments, biological processes, clinical features, and chemotherapeutic drug sensitivity between the groups at high and low risk. Using multivariable Cox regression analyses, platelet-related risk score was shown to be an independent prognostic influence in MM (p &lt; 0.001, hazard ratio (HR) = 2.001%, 95% confidence interval (CI): 1.467–2.730). Furthermore, the capacity to predict survival was further improved when a combined nomogram was utilized. In training cohort, this outperformed the predictive value of International staging system (ISS) alone from a 5-years area under curve (AUC) = 0.668 (95% CI: 0.611–0.725) to an AUC = 0.721 (95% CI: 0.665–0.778).Conclusion: Our study revealed the potential benefits of PRGs in terms of survival prognosis of MM patients. Furthermore, we verified its potential as a drug target for MM patients. These findings open up novel possibilities for prognostic evaluation and treatment choices for MM

    A Common Variant in CLDN14 is Associated with Primary Biliary Cirrhosis and Bone Mineral Density.

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    Primary biliary cirrhosis (PBC), a chronic autoimmune liver disease, has been associated with increased incidence of osteoporosis. Intriguingly, two PBC susceptibility loci identified through genome-wide association studies are also involved in bone mineral density (BMD). These observations led us to investigate the genetic variants shared between PBC and BMD. We evaluated 72 genome-wide significant BMD SNPs for association with PBC using two European GWAS data sets (n = 8392), with replication of significant findings in a Chinese cohort (685 cases, 1152 controls). Our analysis identified a novel variant in the intron of the CLDN14 gene (rs170183, Pfdr = 0.015) after multiple testing correction. The three associated variants were followed-up in the Chinese cohort; one SNP rs170183 demonstrated consistent evidence of association in diverse ethnic populations (Pcombined = 2.43 × 10(-5)). Notably, expression quantitative trait loci (eQTL) data revealed that rs170183 was correlated with a decline in CLDN14 expression in both lymphoblastoid cell lines and T cells (Padj = 0.003 and 0.016, respectively). In conclusion, our study identified a novel PBC susceptibility variant that has been shown to be strongly associated with BMD, highlighting the potential of pleiotropy to improve gene discovery

    Prognostic significance of β2-microglobulin decline index in multiple myeloma

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    PurposeTo assess the prognostic significance of β2-microglobulin decline index (β2M DI) in multiple myeloma (MM).Methods150 MM patients diagnosed with MM were enrolled in this study. Cox proportional hazards model was used to analyze the uni- and multivariate prognosis in training cohort (n=105). A new combined prognostic model containing β2M DI was built up based on the data in training cohort. The validation group was used to verify the model.Resultsβ2M DI showed significant correlation with prognosis in both uni- and multivariate analyses and had a good correlation with complete response (CR) rate and deep remission rate. The ROC and calibration curves in validation cohort (n=45) indicated a good predictive performance of the new model. Based on the median risk score of the training group, we classified patients into high- and low- risk groups. In both training and validation groups, patients in the low-risk group had longer overall survival (OS) time than that in the high-risk group (p&lt;0.05).Conclusionβ2M DI is a good predictive index for predicting treatment response and survival time in MM patients. The prognostic model added with β2M DI showed a better correlation with OS

    Cancer-associated fibroblast infiltration in osteosarcoma: the discrepancy in subtypes pathways and immunosuppression

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    Introduction: Osteosarcoma (OS), the primary malignant bone tumor, has a low survival rate for recurrent patients. Latest reports indicated that cancer-associated fibroblasts (CAFs) were the main component of tumor microenvironment, and would generate a variable role in the progression of tumors. However, the role of CAFs is still few known in osteosarcoma.Methods: The processed RNA-seq data and the corresponding clinical and molecular information were retrieved from the Cancer Genome Atlas Program (TCGA) database and processed data of tumor tissue was obtained from Gene Expression Omnibus (GEO) database. Xcell method was used in data processing, and Gene set variation analysis (GSVA) was used to calculates enrichment scores. Nomogram was constructed to evaluate prognostic power of the predictive model. And the construction of risk scores and assessment of prognostic predictive were based on the LASSO model.Results: This study classified Cancer Genome Atlas (TCGA) cohort into high and low CAFs infiltrate phenotype with different CAFs infiltration enrichment scores. Then TOP 9 genes were screened as prognostic signatures among 2,488 differentially expressed genes between the two groups. Key prognostic molecules were CGREF1, CORT and RHBDL2 and the risk score formula is: Risk-score = CGREF1*0.004 + CORT*0.004 + RHBDL2*0.002. The signatures were validated to be independent prognostic factors to predict tumor prognosis with single-factor COX and multi-factor COX regression analyses and Norton chart. The risk score expression of risk score model genes could predict the drug resistance, and significant differences could be found between the high and low scoring groups for 17-AAG, AZD6244, PD-0325901 and Sorafenib.Discussion: To sum up, this article validated the prediction role of CAF infiltration in the prognosis of OS, which might shed light on the treatment of OS

    A web-based appointment system to reduce waiting for outpatients: A retrospective study

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    <p>Abstract</p> <p>Background</p> <p>Long waiting times for registration to see a doctor is problematic in China, especially in tertiary hospitals. To address this issue, a web-based appointment system was developed for the Xijing hospital. The aim of this study was to investigate the efficacy of the web-based appointment system in the registration service for outpatients.</p> <p>Methods</p> <p>Data from the web-based appointment system in Xijing hospital from January to December 2010 were collected using a stratified random sampling method, from which participants were randomly selected for a telephone interview asking for detailed information on using the system. Patients who registered through registration windows were randomly selected as a comparison group, and completed a questionnaire on-site.</p> <p>Results</p> <p>A total of 5641 patients using the online booking service were available for data analysis. Of them, 500 were randomly selected, and 369 (73.8%) completed a telephone interview. Of the 500 patients using the usual queuing method who were randomly selected for inclusion in the study, responses were obtained from 463, a response rate of 92.6%. Between the two registration methods, there were significant differences in age, degree of satisfaction, and total waiting time (<it>P </it>< 0.001). However, gender, urban residence, and valid waiting time showed no significant differences (<it>P </it>> 0.05). Being ignorant of online registration, not trusting the internet, and a lack of ability to use a computer were three main reasons given for not using the web-based appointment system. The overall proportion of non-attendance was 14.4% for those using the web-based appointment system, and the non-attendance rate was significantly different among different hospital departments, day of the week, and time of the day (<it>P </it>< 0.001).</p> <p>Conclusion</p> <p>Compared to the usual queuing method, the web-based appointment system could significantly increase patient's satisfaction with registration and reduce total waiting time effectively. However, further improvements are needed for broad use of the system.</p
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