The diffuse extragalactic background light consists of the sum of the starlight emitted by galaxies through the history of the Universe, and it could also have an important contribution from the 'first stars', which may have formed before galaxy formation began. Direct measurements are difficult and not yet conclusive, owing to the large uncertainties caused by the bright foreground emission associated with zodiacal light. An alternative approach is to study the absorption features imprinted on the gamma-ray spectra of distant extragalactic objects by interactions of those photons with the background light photons. Here we report the discovery of gamma-ray emission from the blazars H 2356 - 309 and 1ES 1101 - 232, at redshifts z = 0.165 and z = 0.186, respectively. Their unexpectedly hard spectra provide an upper limit on the background light at optical/near-infrared wavelengths that appears to be very close to the lower limit given by the integrated light of resolved galaxies. The background flux at these wavelengths accordingly seems to be strongly dominated by the direct starlight from galaxies, thus excluding a large contribution from other sources-in particular from the first stars formed. This result also indicates that intergalactic space is more transparent to gamma-rays than previously thought.
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http://dx.doi.org/10.1038/nature04680 | DOI Listing |
Biomark Res
January 2025
Department of Hematology and Medical Oncology, Emory University, 201 Dowman Dr, Atlanta, GA, 30322, USA.
Background: Oncolytic viruses (OVs) are increasingly recognized as promising tools for cancer therapy, as they selectively infect and destroy tumor cells while leaving healthy cells unharmed. Despite considerable progress, the limited therapeutic efficacy of OV-based virotherapy continues to be a significant challenge in cancer treatment.
Methods: The SMAC/DIABLO gene was inserted into the genome of vesicular stomatitis virus (VSV) to generate VSV-S.
BMC Med Inform Decis Mak
January 2025
Department of Pediatrics, School of Medicine, Ekbatan Hospital, Hamadan University of Medical Sciences, Hamadan, Iran.
Background: Urinary tract infection (UTI) is a frequent health-threatening condition. Early reliable diagnosis of UTI helps to prevent misuse or overuse of antibiotics and hence prevent antibiotic resistance. The gold standard for UTI diagnosis is urine culture which is a time-consuming and also an error prone method.
View Article and Find Full Text PDFJ Orthop Surg Res
January 2025
Department of Hand-Foot Microsurgery, Shenzhen Nanshan People's Hospital, The 6th Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, China.
Background: Steroid-induced osteonecrosis of the femoral head (SIONFH) is a universal hip articular disease and is very hard to perceive at an early stage. The understanding of the pathogenesis of SIONFH is still limited, and the identification of efficient diagnostic biomarkers is insufficient. This research aims to recognize and validate the latent exosome-related molecular signature in SIONFH diagnosis by employing bioinformatics to investigate exosome-related mechanisms in SIONFH.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Psychiatry and Psychotherapy (Campus Charité Mitte), Charité - Universitätsmedizin Berlin, Berlin, Germany.
Background: In Burkina Faso, nearly half of the population is under 15 years old, and one in four adolescents experience depression. This underscores the critical need to enhance mental health literacy among adolescents and youth, empowering them to manage their mental well-being effectively. Comic books offer an engaging approach to health education, yet their effectiveness in addressing mental health remains largely untested.
View Article and Find Full Text PDFCrit Care
January 2025
Department of Pediatric, West China Second University Hospital, Sichuan University, Chengdu, China.
Background: Patients supported by extracorporeal membrane oxygenation (ECMO) are at a high risk of brain injury, contributing to significant morbidity and mortality. This study aimed to employ machine learning (ML) techniques to predict brain injury in pediatric patients ECMO and identify key variables for future research.
Methods: Data from pediatric patients undergoing ECMO were collected from the Chinese Society of Extracorporeal Life Support (CSECLS) registry database and local hospitals.
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