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Schrödinger’s Cancer
Epidemiology of sickle cell disease in tribal population of Southern Rajasthan, India
Transcatheter Aortic-Valve Replacement for Asymptomatic Severe Aortic Stenosis
Study of physiochemical properties of trisubstituted pyrazole derivatives using polar aprotic solvents
Livedo Racemosa
Sex-specific response of intramuscular fat to diet-induced obesity in rats
Challenges to the Future of a Robust Physician Workforce in the United States
Author Correction: Design of retrofit flue gas (CO2) scrubber for dependable clean energy at the Duvha Coal Power Plant
Burnout, Depression, and Diminished Well-Being among Physicians
B cells enhance IL-1 beta driven invasiveness in triple negative breast cancer
Finerenone in Heart Failure with Preserved Ejection Fraction
Comparison of management options for spontaneous bleeding into soft tissues in patients with COVID-19
Case 2-2025: A 21-Year-Old Man with Loss of Consciousness and a Fall
High-resolution X-ray phase-contrast tomography of human placenta with different wavefront markers
Abstract Phase-contrast micro-tomography ( $$\upmu$$ CT) with synchrotron radiation can aid in the differentiation of subtle density variations in weakly absorbing soft tissue specimens. Modulation-based imaging (MBI) extracts phase information from the distortion of reference patterns, generated by periodic or randomly structured wavefront markers (e.g., gratings or sandpaper). The two approaches have already found application for the virtual inspection of biological samples. Here, we perform high-resolution $$\upmu$$ CT scans of an unstained human placenta specimen, using MBI with both a 2D grating and sandpaper as modulators, as well as conventional propagation-based imaging (PBI). The 3D virtual representation of placenta offers a valuable tool for analysing its intricate branching villous network and vascular structure, providing new insights into its complex architecture. Within this study, we assess reconstruction quality achieved with all three evaluated phase-contrast methods. Both MBI datasets are processed with the Unified Modulated Pattern Analysis (UMPA) model, a pattern-matching algorithm. In order to evaluate the benefits and suitability of MBI for virtual histology, we discuss how the complexities of the technique influence image quality and correlate the obtained volumes to 2D techniques, such as conventional histology and X-ray fluorescence (XRF) elemental maps.
Centrophilic retrotransposon integration via CENH3 chromatin in Arabidopsis
Fracture Prevention with Infrequent Zoledronate in Women 50 to 60 Years of Age
A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition
Publisher Correction: Preliminary investigation on the establishment of a new meibomian gland obstruction model and gene expression
Self-referential belief shares common neural correlates with general belief
Abstract Belief processing and self-referential processing have been consistently associated with cortical midline structures, and cortical regions such as the vmPFC have been implicated in general belief processing. The neural correlates of self-referential belief are yet to be investigated. In this fMRI study, we presented 120 statements with trait adjectives to N = 27 healthy participants, who subsequently judged whether they believed these trait adjectives applied to themselves, a close person, or a public person. Thereafter, participants rated their certainty in this judgment. Expectedly, self-referential processing evoked a large cluster in the vmPFC, ACC, and dmPFC. For belief, we found a cluster in the vmPFC, ACC, and amPFC during statement presentation, partially overlapping with that for self-referential processing. The cluster for self-belief vs. disbelief was similar in location and size to that for general belief processing. For uncertainty, we found dmPFC activation. We replicated vmPFC involvement in belief processing and found a common neural correlate for belief and self-belief in the vmPFC. Furthermore, we replicated the role of the dmPFC in uncertainty, supporting a dual neural process model of belief and certainty.