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PR was seen in one (50%) of the 2 evaluable patients with Ewing sarcoma and one (14.3%) of the seven patients with osteosarcoma. Overall survival and progression-free survival rates were 79.3% and 33.9% at 1 year, and 45.5% and 25.4% at two years, respectively. read more There was no treatment-related mortality.

The VIT regimen was effective and relatively safe in our cohort of sarcoma patients.

The VIT regimen was effective and relatively safe in our cohort of sarcoma patients.

Machine learning (ML) is a strong candidate for making accurate predictions, as we can use large amount of data with powerful computational algorithms. We developed a ML based model to predict survival of patients with colorectal cancer (CRC) using data from 2 independent datasets.

A total of 364,316 and 1,572 CRC patients were included from the Surveillance, Epidemiology, and End results (SEER) and a Korean dataset, respectively. As SEER combines data from 18 cancer registries, internal validation was done using 18-Fold-Cross-Validation then external validation was performed by testing the trained model on the Korean dataset. Performance was evaluated using area under the receiver operating characteristic curve (AUROC), sensitivity and positive predictive values.

Clinicopathological characteristics were significantly different between the two datasets and the SEER showed a significant lower 5-year survival rate compared to the Korean dataset (60.1% vs. 75.3%, p<0.001). The ML based model using Light gradient boosting algorithm achieved a better performance in predicting 5-year-survival compared to AJCC stage (AUROC, 0.804 vs. 0.736, p<0.001). The most important features which influenced model performance were age, number of examined lymph nodes, and tumor size. Sensitivity and positive predictive values of predicting 5-year-survival for classes including dead or alive were reported as 68.14%, 77.51% and 49.88%, 88.1% respectively in the validation set. Survival probability can be checked using the web-based survival predictor (http//colorectalcancer.pythonanywhere.com).

ML based model achieved a much better performance compared to staging in individualized estimation of survival of patients with CRC.

ML based model achieved a much better performance compared to staging in individualized estimation of survival of patients with CRC.

The diagnosis and prediction of prognosis are important in patients with sepsis, and presepsin is helpful. In this study, we aimed to examine the usefulness of presepsin in predicting the prognosis of sepsis in Korea.

Patients diagnosed with sepsis according to the sepsis-3 criteria were recruited into the study and classified into surviving and non-surviving groups based on in-hospital mortality. A total of 153 patients (33 and 121 patients with sepsis and septic shock, respectively) were included from July 2019 to August 2020.

Among the 153 patients with sepsis, 91 and 62 were in the survivor and non-survivor groups, respectively. Presepsin (p=0.004) and lactate (p=0.003) levels and the sequential organ failure assessment (SOFA) scores (p<0.001) were higher in the non-survivor group. Receiver operating characteristic curve analysis revealed poor performances of presepsin and lactate in predicting the prognosis of sepsis (presepsin area under the curve [AUC]=0.656, p=0.001; lactate AUC=0.646, p=0.003). The SOFA score showed the best performance, with the highest AUC value (AUC=0.751, p<0.001). The prognostic cutoff point for presepsin was 1,176 pg/mL. Presepsin levels of >1,176 pg/mL (odds ratio [OR], 3.352; p<0.001), lactate levels (OR, 1.203; p=0.003), and SOFA score (OR, 1.249; p<0.001) were risk factors for in-hospital mortality.

Presepsin levels were higher in non-survivors than in survivors. Thus, presepsin may be a valuable biomarker in predicting the prognosis of sepsis.

Presepsin levels were higher in non-survivors than in survivors. Thus, presepsin may be a valuable biomarker in predicting the prognosis of sepsis.A novel Lanthanum phosphate polyaniline (LaPO4-PANI) nanocomposite was synthesized by the simple sol-gel technique. The nanocomposite prepared at 11 ratio provided the highest ion exchange capacity and selective adsorption of Cr(VI). The phase composition and particle morphology of the as-prepared material was evaluated by XRD, FESEM and TEM analyses. The FTIR, Raman, and TGA data inferred the definite chemical interaction between the organic and inorganic counterparts in the formation of LaPO4-PANI. The selective adsorption of Cr(VI) was estimated by evaluating the distribution coefficient, electrical double layer theory as well as valency and Pauling's ionic radii of interfering ions (phosphate, iodide, sulfate, chloride, sulfide). The high tolerance capability of LaPO4-PANI against the interfering ions made it appropriate for selective and efficient removal of Cr(VI) ions from solutions. The nanocomposite showed the highest removal percentage of 98.6% towards Cr(VI) in a wide pH range of 2-6 at room temperature, as compared to sole lanthanum phosphate (56%) and polyaniline (75%). The XPS analysis revealed the adsorption mechanism due to the combined effect of both adsorption and reduction. Cr(VI) is adsorbed through electrostatic interactions while the = N-/-NH- group facilitated the in situ chemical reduction. The procured results make the LaPO4-PANI nanocomposite a promising adsorbent for the removal of Cr(VI).Fine particles i.e., with an aerodynamic diameter lower than 2.5 μm (PM2.5) have potentially the most significant effects on human health compared to other air pollutants. The main objectives of this study were to i) investigate the temporal variations of ambient PM2.5 in Marseille (Southern France), where air pollution is again a major public health issue, and ii) estimate their short-term health effects and annual trend (Mann-Kendall test) over a 10-year period from 2010 to 2019. In Marseille, the main sources of PM2.5 could be related to road traffic, industrial complexes, and oil refineries surrounded the city. The number of premature deaths and hospital admissions attributable to ambient PM2.5 exposure for non-accidental causes, cardiovascular and respiratory diseases were estimated by using in-situ air quality data, city-specific relative risk values and baseline incidence. Despite significant reduction of PM2.5 (- 0.80 μg m-3 year-1), Marseille citizens were exposed to PM2.5 levels exceeding the World Health Organization (WHO) Air Quality Guideline for human health protection (10 μg m-3) during entire study period.