Experimenter bias compromises the integrity and advancement of science, especially when awarded as such. For example, the 2022 Nobel Prize in Physics awarded for the loophole-free experiments that tested physicist John S. Bell's inequality theorem. These experiments employed the logic of conducting local experiments to obtain local evidence that contradicted local realistic theories of nature, thereby validating quantum mechanics as a fundamental non-local theory. However, there was one loophole that was wittingly not tested by the Nobel laureates. The notable exception was Bell's "super-deterministic" loophole, which was validated (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) non-locally, thus compromising the subsequent Nobel Prize. More importantly, the discovery of two mutually exclusive and jointly exhaustive non-local hidden variables revealed why local scientific methods obtain false-positive and false-negative results. With knowledge of this fundamental omission, the inclusion of the non-local hidden variables in the local methods used in science can then advance it to be a complete study of nature.
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http://dx.doi.org/10.3389/frma.2024.1404371 | DOI Listing |
J Biomed Sci
January 2025
Key Laboratory of Molecular Epigenetics of Ministry of Education, College of Life Sciences, Northeast Normal University, Changchun, 130024, China.
ROS cause multiple forms of DNA damage, and among them, 8-oxoguanine (8-oxoGua), an oxidized product of guanine, is one of the most abundant. If left unrepaired, 8-oxoGua may pair with A instead of C, leading to a mutation of G: C to T: A during DNA replication. 8-Oxoguanine DNA glycosylase 1 (OGG1) is a tailored repair enzyme that recognizes 8-oxoGua in DNA duplex and initiates the base excision repair (BER) pathway to remove the lesion and ensure the fidelity of the genome.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
December 2024
Department of Health Informatics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Background: Digital health has emerged as a promising solution for enhancing health system in the recent years, showing significant potential in improving service outcomes, particularly in low and middle-income countries where accessing essential health service is challenging. This review aimed to determine the effectiveness of short message services on focused antenatal care, skilled birth attendance, and postnatal care improvement in low and middle-income countries.
Method: Electronic databases such as PubMed, EMBASE, Scopus, Cochrane, and Google and Google Scholar were searched.
J Med Genet
December 2024
Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands
Background: Clinical trials for rare disorders have unique challenges due to low prevalence, patient phenotype variability and high expectations. These challenges are highlighted by our study on clonazepam in patients, a common cause of intellectual disability. Previous studies on Arid1b-haploinsufficient mice showed positive effects of clonazepam on various cognitive aspects.
View Article and Find Full Text PDFPLoS One
December 2024
Graduate School of Informatics, Nagoya University, Nagoya, Aichi, Japan.
When playing on an sloped golf course, the ball often misses the hole to the front-lower side, which is also referred to as the "amateur side." This can be attributed to the difficulty in perceiving the green slope and choosing the appropriate launch direction and ball speed, especially for amateurs. The study had three main objectives.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan.
Kawasaki Disease (KD) is a rare febrile illness affecting infants and young children, potentially leading to coronary artery complications and, in severe cases, mortality if untreated. However, KD is frequently misdiagnosed as a common fever in clinical settings, and the inherent data imbalance further complicates accurate prediction when using traditional machine learning and statistical methods. This paper introduces two advanced approaches to address these challenges, enhancing prediction accuracy and generalizability.
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