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Background: Anterior cruciate ligament (ACL) injuries are common in pediatric and adolescent patients. Understanding this population's injury characteristics and treatment strategies is vital for managing this high-risk group.

Purpose: To report the descriptive epidemiology and treatment strategies of a large cohort of skeletally immature patients with complete ACL tears.

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The Intraperitoneal Carboplatin for Ovarian Cancer (iPocc) trial demonstrated that intraperitoneal (IP) administration of carboplatin is more effective than intravenous (IV) administration for advanced ovarian cancer, especially in cases with large residual tumors, challenging previous assumptions that IP chemotherapy is only beneficial for small residual tumors. Additionally, the iPocc trial showed that IP chemotherapy has a comparable safety profile to IV chemotherapy, with the exception of port-related toxicities. This review summarizes the principles, development, and significance of IP chemotherapy and discusses its future potential in light of recent studies.

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High-rate quantum error correcting (QEC) codes with moderate overheads in qubit number and control complexity are highly desirable for achieving fault-tolerant quantum computing. Recently, quantum error correction has experienced significant progress both in code development and experimental realizations, with neutral atom qubit architecture rapidly establishing itself as a leading platform in the field. Scalable quantum computing will require processing with QEC codes that have low qubit overhead and large error suppression, and while such codes do exist, they involve a degree of non-locality that has yet to be integrated into experimental platforms.

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Although microporous carbons can perform well for CO2 separations under high pressure conditions, their energy-demanding regeneration may render them a less attractive material option. Here, we developed a large-pore mesoporous carbon with pore sizes centered around 20-30 nm using a templated technical lignin. During the soft-templating process, unique cylindrical supramolecular assemblies form from the copolymer template.

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Rationale: Lung ultrasound, the most precise diagnostic tool for pleural effusions, is underutilized due to healthcare providers' limited proficiency. To address this, deep learning models can be trained to recognize pleural effusions. However, current models lack the ability to diagnose effusions in diverse clinical contexts, which presents significant challenges.

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