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In the face of environmental deterioration and global climate change, the concept of carbon neutrality and carbon peaking has gained prominence as a means to balance development and environmental preservation worldwide. Energy-aware scheduling is becoming the key scenario for environment conservation in manufacturing. This study focuses on addressing the energy-aware distributed no-wait flow-shop scheduling problem in a heterogeneous factory system (EDNWFSP-HFS) to minimize total energy consumption (TEC) and total tardiness (TTDs). A mixed-integer linear programming (MILP) model is formulated and a policy-based meta-heuristic algorithm (MHA-PG) is specifically designed to solve EDNWFSP-HFS. First, the optimal allocation rules based on random sequence (OAR-RS) are designed to initialize the population. Second, a policy-based method is employed to guide the algorithm toward making a better decision. Third, the energy-saving strategy considering specific knowledge of EDNWFSP-HFS is summarized to further optimize the feasible solution. Extensive simulations are conducted, comparing the performance of MHA-PG against several state-of-the-art algorithms. The results demonstrate that the proposed algorithm outperforms the competing approaches in solving EDNWFSP-HFS, indicating its superior performance and effectiveness.

In acute myeloid leukemia (AML), malignant cells surviving chemotherapy rely on high mRNA translation and their microenvironmental metabolic support to drive relapse. However, the role of translational reprogramming in the niche is unclear. Here, we found that relapsing AML cells increase translation in their bone marrow (BM) niches, where BM mesenchymal stromal cells (BMSCs) become a source of eIF4A-cap-dependent translation machinery that is transferred to AML cells via extracellular vesicles (EVs) to meet their translational demands. In two independent models of highly chemo-resistant AML driven by MLL-AF9 or FLT3-ITD (internal tandem duplication) and nucleophosmin (NPMc) mutations, protein synthesis levels increase in refractory AML dependent on nestin+ BMSCs. Inhibiting cap-dependent translation in BMSCs abolishes their chemoprotective ability, while EVs from BMSCs carrying eIF4A boost AML cell translation and survival. Consequently, eIF4A inhibition synergizes with conventional chemotherapy. Together, these results suggest that AML cells rely on BMSCs to maintain an oncogenic translational program required for relapse.

Electrochemical nitrite (NO2–) is a promising technology for NO2–removal and a sustainable method for generating valuable ammonia (NH3), but this process is intricate and generates other byproducts. In this work, we propose a facile and low-cost method for the preparation of a Cu3Mo2O9nanosheet array, which can serve as an efficient electrocatalyst for the reduction of NO2–to NH3. The morphology of Cu3Mo2O9can be adjusted by controlling the synthesis conditions. In neutral solution, Cu3Mo2O9achieves a high NH3yield of 30.46 mg h–1cm–2and an outstanding faradaic efficiency of 98.6% with excellent long-term electrochemical stability for NO2–reduction. Density functional theory calculations further reveal the key role of the Cu3Mo2O9(202) surface and its possible reaction pathways in the electrocatalytic reduction of nitrite.

La leucoencefalopatía multifocal progresiva (LMP) es una enfermedad desmielinizante producto de la reactivación del virus John Cunningham (JC) en el sistema nervioso central (SNC) en pacientes que presentan diversos grados de inmunocompromiso. Sus manifestaciones clínicas e imagenológicas están bien descriptas, pero es necesaria una alta sospecha de la enfermedad para arribar al diagnóstico.