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Filename: drivers/Session_files_driver.php
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Filename: Session/Session.php
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Function: require_once
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Filename: controllers/Detail.php
Line Number: 249
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 249
Backtrace:
File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 249
Backtrace:
File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 249
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
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Filename: models/Detail_model.php
Line Number: 71
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File: /var/www/html/application/models/Detail_model.php
Line: 71
Function: strpos
File: /var/www/html/application/controllers/Detail.php
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Function: insertAPISummary
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Function: require_once
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Filename: helpers/my_audit_helper.php
Line Number: 8919
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File: /var/www/html/application/helpers/my_audit_helper.php
Line: 8919
Function: str_replace
File: /var/www/html/application/controllers/Detail.php
Line: 255
Function: formatAIDetailSummary
File: /var/www/html/index.php
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Function: require_once
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
Severity: Warning
Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 256
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File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler
File: /var/www/html/index.php
Line: 316
Function: require_once
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Function: require_once
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Filename: controllers/Detail.php
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Backtrace:
File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
Line: 316
Function: require_once
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
Line Number: 260
Backtrace:
File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
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Function: require_once
High throughput transcriptomics (HTTr) profiling has the potential to rapidly and comprehensively identify molecular targets of environmental chemicals that can be linked to adverse outcomes. We describe here the construction and characterization of a 50-gene expression biomarker designed to identify estrogen receptor (ER) active chemicals in HTTr datasets. Using microarray comparisons, the genes in the biomarker were identified as those that exhibited consistent directional changes when ER was activated (4 ER agonists; 4 ESR1 gene constitutively active mutants) and opposite directional changes when ER was suppressed (4 antagonist treatments; 4 ESR1 knockdown experiments). The biomarker was evaluated as a predictive tool using the Running Fisher algorithm by comparison to annotated gene expression microarray datasets including those evaluating the transcriptional effects of hormones and chemicals in MCF-7 cells. Depending on the reference dataset used, the biomarker had a predictive accuracy for activation of up to 96%. To demonstrate applicability for HTTr data analysis, the biomarker was used to identify ER activators in a set of 15 chemicals that are considered potential bisphenol A (BPA) alternatives examined at up to 10 concentrations in MCF-7 cells and analyzed by full-genome TempO-Seq. Using benchmark dose (BMD) modeling, the biomarker genes stratified the ER potency of BPA alternatives consistent with previous studies. These results demonstrate that the ER biomarker can be used to accurately identify ER activators in transcript profile data derived from MCF-7 cells.
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http://dx.doi.org/10.1016/j.cbi.2024.110952 | DOI Listing |
Arch Bone Jt Surg
January 2024
University of Health Sciences, Gulhane Faculty of Pharmacy, Department of Biochemistry, Ankara, Türkiye.
Objectives: In this study, the Kellgren and Lawrence system was used as the most common radiographic grading system for diagnosis of osteoarthritis in patients defined as Grade III and IV. It is aimed to reveal oxidative stress and cellular immunity status. In this context, the aim is to discuss possible risk parameters regarding disease process and treatment effectiveness.
View Article and Find Full Text PDFFront Psychiatry
December 2024
Department of Psychology, Sapienza University of Rome, Rome, Italy.
Introduction: With ageing there are changes in the ability to orient attention, which affect more endogenous than exogenous orienting. However, orienting attention by the gaze direction of others shares characteristics of both exogenous and endogenous attention and it is unclear how it is affected by ageing. Being able to orient attention by the gaze direction of others is important to establish successful social interactions (i.
View Article and Find Full Text PDFBiomed Rep
February 2025
Institute of Sports Medicine and Health, Chengdu Sport University, Chengdu, Sichuan 641418, P.R. China.
Obstructive sleep apnea (OSA) is the most common type of sleep apnea, which leads to episodes of intermittent hypoxia due to obstruction of the upper airway. A key feature of OSA is the upregulation and stabilization of hypoxia-inducible factor 1 (HIF-1), a crucial metabolic regulator that facilitates rapid adaptation to changes in oxygen availability. Adenosine A2A receptor (A2AR), a major adenosine receptor, regulates HIF-1 under hypoxic conditions, exerting anti-inflammatory properties and affecting lipid metabolism.
View Article and Find Full Text PDFFront Neurosci
December 2024
Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Objective: Targeted transcutaneous electrical nerve stimulation (tTENS) is a non-invasive neural stimulation technique that involves activating sensory nerve fibers to elicit tactile sensations in a distal, or referred, location. Though tTENS is a promising approach for delivering haptic feedback in virtual reality or for use by those with somatosensory deficits, it was not known how the perception of tTENS might be influenced by changing wrist position during sensorimotor tasks.
Approach: We worked with 12 able-bodied individuals and delivered tTENS by placing electrodes on the wrist, thus targeting the ulnar, median, and radial nerves, and eliciting tactile sensations in the hand.
Heliyon
December 2024
Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, Malaysia.
The agriculture sector is confronted with numerous challenges in the quest for accurate crop yield estimation, which is essential for efficient resource management and mitigating food scarcity in a rapidly growing global population. This research paper delves into the application of advanced Artificial Intelligence (AI) techniques to enhance crop yield estimation in the context of diverse agricultural challenges. Through a systematic literature review and analysis of relevant studies, this paper explores the role of AI methods, such as Machine Learning (ML) and Deep Learning (DL), in addressing the complexities posed by geographical variations, crop diversity, and cultivation areas.
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