A single cycle (two repeated treatments) with intrathecal autologous bone marrow-derived mesenchymal stem cells (BM-MSCs, 26-day interval) showed safety and provided therapeutic benefit lasting 6 months in pat...
Dengue is a serious public health concern in Brazil and globally. In the absence of a universal vaccine or specific treatments, prevention relies on vector control and disease surveillance. Accurate and early forecasts can help reduce the spread of the disease. In this study, we develop a model to predict monthly dengue cases in Brazilian cities one month ahead from 2007-2019. We compare different machine learning algorithms and feature selection methods using epidemiological and meteorological variables. We find that different models work best in different cities, and a random forests model trained on monthly dengue cases performs best overall. It produces lower errors than a seasonal naïve baseline model, gradient boosting regression, feed-forward neural network, and support vector regression. For each city, we compute the mean absolute error between predictions and true monthly dengue cases on the test set. For the median city, the error is 1 2.2 cases. This error is reduced to 11.9 when selecting the optimal combination of algorithm and input features for each city individually. Machine learning and especially decision tree ensemble models may contribute to dengue surveillance in Brazil, as they produce low out-of-sample prediction errors for a geographically diverse set of cities.
Objective: This phase III trial evaluated whether the no touch was superior to the conventional in patients with cT3/T4 colon cancer. Background: No touch involves ligating blood vessels that feed the primary tumor to limit cancer cell spreading. However, previous studies did not confirm the efficacy of the no touch. Methods: This open-label, randomized, phase III trial was conducted at 30 Japanese centers. The eligibility criteria were histologically proven colon cancer; clinical classification of T3–4, N0–2, andM0; and patients aged 20 to 80years. Patients were randomized (1:1) to undergo open surgery with conventional or the no touch. Patients with pathological stage III disease received adjuvant capecitabine chemotherapy. The primary endpoint was disease-free survival (DFS) according to the intention-to-treat principle. Results: Between January 2011 and November 2015, 853 patients were randomized to the conventional group (427 patients) or the no touch group (426 patients). The 3-year DFS were 77.3% [95% confidence interval (CI) 73.1%–81.0%] and 76.2% (95% CI 71.9%–80.0%) in the conventional and no touch groups, respectively. The superiority of no touch was not confirmed: hazard ratio for DFS = 1.029 (95% CI 0.800– 1.324; 1-sided P = 0.59). Operative morbidity was observed in 31 of 427 conventional patients (7%) and 26 of 426 no touch patients (6%). All grade adverse events were similar between the conventional and no touch groups. No in-hospital mortality occurred in either group. Conclusion: The present study failed to confirm the superiority of the no touch.