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Texas Register, Volume 49, Number 7, Pages 805-932, February 16, 2024 (open access)

Texas Register, Volume 49, Number 7, Pages 805-932, February 16, 2024

A weekly publication, the Texas Register serves as the journal of state agency rulemaking for Texas. Information published in the Texas Register includes proposed, adopted, withdrawn and emergency rule actions, notices of state agency review of agency rules, governor's appointments, attorney general opinions, and miscellaneous documents such as requests for proposals. After adoption, these rulemaking actions are codified into the Texas Administrative Code.
Date: February 16, 2024
Creator: Texas. Secretary of State.
Object Type: Journal/Magazine/Newsletter
System: The Portal to Texas History
Hedgehog signaling is involved in acquired resistance to KRASG12C inhibitors in lung cancer cells (open access)

Hedgehog signaling is involved in acquired resistance to KRASG12C inhibitors in lung cancer cells

Article states that although KRASG12C inhibitors have shown promising activity in lung adenocarcinomas harboring KRASG12C, acquired resistance to these therapies eventually occurs in most patients. The authors report that the hedgehog signal is induced by KRASG12C inhibitors and mediates KRAS re-expression in cancer cells treated with a KRASG12C inhibitor.
Date: January 16, 2024
Creator: Lee, Chaeyoung; Yi, Jawoon; Park, Jihwan; Ahn, Byungyong; Won, Young-Wook; Jeon, JiHeung et al.
Object Type: Article
System: The UNT Digital Library
Development and Utilization of Bridge Data of the United States for Predicting Deck Condition Rating Using Random Forest, XGBoost, and Artificial Neural Network (open access)

Development and Utilization of Bridge Data of the United States for Predicting Deck Condition Rating Using Random Forest, XGBoost, and Artificial Neural Network

Article describes how accurately predicting the condition rating of a bridge deck is crucial for effective maintenance and repair planning. This study aims to assess the effectiveness of these algorithms for deck condition rating prediction at the national level.
Date: January 16, 2024
Creator: Fard, Fariba & Fard, Fereshteh Sadeghi Naieni
Object Type: Article
System: The UNT Digital Library