The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

OpenSim Visualization of the Classification of Finger Movements Based on Electromyography Signal as the Single-Input Variable during Predefined Movements

A classifier is commonly generated for multifunctional prostheses control or also as input devices in human&ndash;computer interfaces. The complementary use of the open-access biomechanical simulation software, OpenSim, is demonstrated for the hand-movement classification performance visualization. A classifier was created from a previously captured database, which has 15 finger movements that were acquired during synchronized hand-movement repetitions with an 8-electrode sensor array placed on the forearm; a 92.89% recognition based on a complete movement was obtained. The OpenSim&rsquo;s upper limb wrist model is employed, with movement in each of the joints of the hand&ndash;fingers. Several hand-motion visualizations were then generated, for the ideal hand movements, and for the best and the worst (53.03%) reproduction, to perceive the classification error in a specific task movement. This demonstrates the usefulness of this simulation tool before applying the classifier to a multifunctional prosthesis

Lanthanide-Doped ZnO Nanoparticles: Unraveling Their Role in Cytotoxicity, Antioxidant Capacity, and Nanotoxicology

This study used a sonochemical synthesis method to prepare (La, Sm)-doped ZnO nanoparticles (NPs). The effect of incorporating these lanthanide elements on the structural, optical, and morphological properties of ZnO-NPs was analyzed. The cytotoxicity and the reactive oxygen species (ROS) generation capacity of ZnO-NPs were evaluated against breast (MCF7) and colon (HT29) cancer cell lines. Their antioxidant activity was analyzed using a DPPH assay, and their toxicity towards Artemia salina nauplii was also evaluated. The results revealed that treatment with NPs resulted in the death of 10.559–42.546% and 18.230–38.643% of MCF7 and HT29 cells, respectively. This effect was attributed to the ability of NPs to downregulate ROS formation within the two cell lines in a dose-dependent manner. In the DPPH assay, treatment with (La, Sm)-doped ZnO-NPs inhibited the generation of free radicals at IC50 values ranging from 3.898 to 126.948 μg/mL. Against A. salina nauplii, the synthesized NPs did not cause death nor induce morphological changes at the tested concentrations. A series of machine learning (ML) models were used to predict the biological performance of (La, Sm)-doped ZnO-NPs. Among the designed ML models, the gradient boosting model resulted in the greatest mean absolute error (MAE) (MAE 9.027, R2 = 0.86). The data generated in this work provide innovative insights into the influence of La and Sm on the structural arrangement and chemical features of ZnO-NPs, together with their cytotoxicity, antioxidant activity, and in vivo toxicity