Machine Learning Accelerated Discovery of Corrosion-resistant High-entropy Alloys

Corrosion has a wide impact on society, causing catastrophic damage to structurally engineered components. An emerging class of corrosion-resistant materials are high-entropy alloys. However, high-entropy alloys live in high-dimensional composition and configuration space, making materials designs via experimental trial-and-error or brute-force ab initio calculations almost impossible. Here we develop a physics-informed machine-learning framework to identify corrosion-resistant high-entropy alloys. Three metrics are used to evaluate the corrosion resistance, including single-phase formability, surface energy and Pilling-Bedworth ratios. We used random forest models to predict the single-phase formability, trained on an experimental dataset. Machine learning inter-atomic potentials were employed to calculate surface energies and Pilling-Bedworth ratios, which are trained on first-principles data fast sampled using embedded atom models. A combination of random forest models and high-fidelity machine learning potentials represents the first of its kind to relate chemical compositions to corrosion resistance of high-entropy alloys, paving the way for automatic design of materials with superior corrosion protection. This framework was demonstrated on AlCrFeCoNi high-entropy alloys and we identified composition regions with high corrosion resistance. Machine learning predicted lattice constants and surface energies are consistent with values by first-principles calculations. The predicted single-phase formability and corrosion-resistant compositions of AlCrFeCoNi agree well with experiments. This framework is general in its application and applicable to other materials, enabling high-throughput screening of material candidates and potentially reducing the turnaround time for integrated computational materials engineering

Post-Operative Functional Outcomes in Early Age Onset Rectal Cancer

Background: Impairment of bowel, urogenital and fertility-related function in patients treated for rectal cancer is common. While the rate of rectal cancer in the young (<50 years) is rising, there is little data on functional outcomes in this group. Methods: The REACCT international collaborative database was reviewed and data on eligible patients analysed. Inclusion criteria comprised patients with a histologically confirmed rectal cancer, <50 years of age at time of diagnosis and with documented follow-up including functional outcomes. Results: A total of 1428 (n=1428) patients met the eligibility criteria and were included in the final analysis. Metastatic disease was present at diagnosis in 13%. Of these, 40% received neoadjuvant therapy and 50% adjuvant chemotherapy. The incidence of post-operative major morbidity was 10%. A defunctioning stoma was placed for 621 patients (43%); 534 of these proceeded to elective restoration of bowel continuity. The median follow-up time was 42 months. Of this cohort, a total of 415 (29%) reported persistent impairment of functional outcomes, the most frequent of which was bowel dysfunction (16%), followed by bladder dysfunction (7%), sexual dysfunction (4.5%) and infertility (1%). Conclusion: A substantial proportion of patients with early-onset rectal cancer who undergo surgery report persistent impairment of functional status. Patients should be involved in the discussion regarding their treatment options and potential impact on quality of life. Functional outcomes should be routinely recorded as part of follow up alongside oncological parameters

Malaria parasites both repress host CXCL10 and use it as a cue for growth acceleration

Pathogens are thought to use host molecular cues to control when to initiate life-cycle transitions, but these signals are mostly unknown, particularly for the parasitic disease malaria caused by Plasmodium falciparum. The chemokine CXCL10 is present at high levels in fatal cases of cerebral malaria patients, but is reduced in patients who survive and do not have complications. Here we show a Pf 'decision-sensing-system' controlled by CXCL10 concentration. High CXCL10 expression prompts P. falciparum to initiate a survival strategy via growth acceleration. Remarkably, P. falciparum inhibits CXCL10 synthesis in monocytes by disrupting the association of host ribosomes with CXCL10 transcripts. The underlying inhibition cascade involves RNA cargo delivery into monocytes that triggers RIG-I, which leads to HUR1 binding to an AU-rich domain of the CXCL10 3'UTR. These data indicate that when the parasite can no longer keep CXCL10 at low levels, it can exploit the chemokine as a cue to shift tactics and escape