Single-arm, phase II study of intra-arterial chemotherapy plus total neoadjuvant therapy to optimise complete response in distal rectal cancer: a study protocol.

INTRODUCTION: Organ preservation is now considered an acceptable alternative option in distal rectal cancer patients with clinical complete response (cCR) after neoadjuvant chemoradiation (CRT). But the cCR rate is low and about one-third of tumour will regrow, which requires more effective local treatment. CRT combined with intra-arterial chemotherapy (IAC) might be a promising approach. Additionally, total neoadjuvant therapy using FOLFIRINOX induction chemotherapy improved survival while consolidation chemotherapy improved organ preservation. We assess whether IAC plus CRT and FOLFIRINOX consolidation chemotherapy can improve the chance of organ preservation and survival in distal rectal cancer. METHODS AND ANALYSIS: This prospective, monocentric, open-label, single-arm phase II study will include 32 patients with cT3-4NanyM0 distal rectal adenocarcinoma. All patients will receive one cycle of IAC (irinotecan, raltitrexed and oxaliplatin), followed by CRT (50 Gy/25 fractions with concomitant capecitabine) and then with six cycles of FOLFIRINOX (leucovorin, 5-fluorouracil, oxaliplatin and irinotecan). After final evaluation, patients with cCR will receive non-operative management or surgery at their own discretion and others are mandatorily referred to surgery. Adjuvant chemotherapy with six cycles of mFOLFOX6 (leucovorin, 5-fluorouracil and oxaliplatin) will be used for patients with adverse pathological features. The primary endpoint is the rate of complete response (CR; pathological CR or sustained cCR≥2 years). The main secondary endpoints are toxicity, compliance, short-term and long-term oncological outcomes, surgical morbidity and quality of life. This protocol has been designed in accordance with the Standard Protocol Items: Recommendations for Interventional Trials 2013 guidelines. ETHICS AND DISSEMINATION: This study was approved by the Academic and Ethics Committee of The Affiliated Hospital of Youjiang Medical University for Nationalities in March 2023. Trial results will be published in peer-reviewed international journals and on the ChiCTR website. PROTOCOL VERSION: Registered on 18 April 2023; version #1. TRIAL REGISTRATION NUMBER: ChiCTR2300070620.

Single-Gate In-Transistor Readout of Current Superposition and Collapse Utilizing Quantum Tunneling and Ferroelectric Switching.

In nanostructure assemblies, the superposition of current paths forms microscopic electric circuits, and different circuit networks produce varying results, particularly when utilized as transistor channels for computing applications. However, the intricate nature of assembly networks and the winding paths of commensurate currents hinder standard circuit modeling. Inspired by the quantum collapse of superposition states for information decoding in quantum circuits, the implementation of analogous current path collapse to facilitate the detection of microscopic circuits by modifying their network topology is explored. Here, the superposition and collapse of current paths in gate-all-around polysilicon nanosheet arrays are demonstrated to enrich the computational resources within transistors by engineering the channel length and quantity. Switching the ferroelectric polarization of Hf0.5 Zr0.5 O2 gate dielectric, which drives these transistors out-of-equilibrium, decodes the output polymorphism through circuit topological modifications. Furthermore, a protocol for the single-electron readout of ferroelectric polarization is presented with tailoring the channel coherence. The introduction of lateral path superposition results into intriguing metal-to-insulator transitions due to transient behavior of ferroelectric switching. This ability to adjust the current networks within transistors and their interaction with ferroelectric polarization in polycrystalline nanostructures lays the groundwork for generating diverse current characteristics as potential physical databases for optimization-based computing.