Number distributions for fermions and fermionized bosons in periodic potentials

We compute the spatial population statistics for one-dimensional fermi-gases and for bose-gases with hard core repulsions in periodic potentials. We show how the statistics depend on the atomic density in the ground state of the system, and we present calculations for the dynamical turn-on of the potential.Comment: 8 pages, 4 figures, submitted to Phys. Rev.

Scaling of the Hysteresis Loop in Two-dimensional Solidification

The first order phase transitions between a two-dimensional (2d) gas and the 2d solid of the first monolayer have been studied for the noble gases Ar, Kr and Xe on a NaCl(100) surface in quasi-equilibrium with the three-dimensional gas phase. Using linear temperature ramps, we show that the widths of the hysteresis loops of these transitions as a function of the heating rate, r, scales with a power law r^alpha with alpha between 0.4 and 0.5 depending on the system. The hysteresis loops for different heating rates are similar. The island area of the condensed layer was found to grow initially with a t^4 time dependence. These results are in agreement with theory, which predicts alpha = 0.5 and hysteresis loop similarity.Comment: 4 pages, 5 figures, Revte

Imaging cell lineage with a synthetic digital recording system

Cell lineage plays a pivotal role in cell fate determination. Chow et al. demonstrate the use of an integrase-based synthetic barcode system called intMEMOIR, which uses the serine integrase Bxb1 to perform irreversible nucleotide edits. Inducible editing either deletes or inverts its target region, thus encoding information in three-state memory elements, or trits, and avoiding undesired recombination events. Using intMEMOIR combined with single-molecule fluorescence in situ hybridization, the authors were able to identify clonal structures as well as gene expression patterns in the fly brain, enabling both clonal analysis and expression profiling with intact spatial information. The ability to visualize cell lineage relationships directly within their native tissue context provides insights into development and disease

A mathematical description of nerve fiber bundle trajectories and their variability in the human retina

AbstractWe developed a mathematical model wherein retinal nerve fiber trajectories can be described and the corresponding inter-subject variability analyzed. The model was based on traced nerve fiber bundle trajectories extracted from 55 fundus photographs of 55 human subjects. The model resembled the typical retinal nerve fiber layer course within 20° eccentricity. Depending on the location of the visual field test point, the standard deviation of the calculated corresponding angular location at the optic nerve head circumference ranged from less than 1° to 18°, with an average of 8.8°

Male-female differences in thoracic aortic diameters at presentation of acute type A aortic dissection

Background: Acute type A aortic dissection (ATAAD) is a highly lethal event, associated with aortic dilatation. It is not well known if patient height, weight or sex impact the thoracic aortic diameter (TAA) at ATAAD. The study aim was to identify male–female differences in TAA at ATAAD presentation. Methods: This retrospective cross-sectional study analysed all adult patients who presented with ATAAD between 2007 and 2017 in two tertiary care centres and underwent contrast enhanced computed tomography (CTA) before surgery. Absolute aortic diameters were measured at the sinus of Valsalva (SoV), ascending (AA) and descending thoracic aorta (DA) using double oblique reconstruction, and indexed for body surface area (ASI) and height (AHI). Z-scores were calculated using the Campens formula. Results: In total, 59 % (181/308) of ATAAD patients had CT-scans eligible for measurements, with 82 female and 99 male patients. Females were significantly older than males (65.5 ± 12.4 years versus 60.3 ± 2.3, p = 0.024). Female patients had larger absolute AA diameters than male patients (51.0 mm [47.0–57.0] versus 49.0 mm [45.0–53.0], p = 0.023), and larger ASI and AHI at all three levels. Z-scores for the SoV and AA were significantly higher for female patients (2.99 ± 1.66 versus 1.34 ± 1.77, p &lt; 0.001 and 5.27 [4.38–6.26] versus 4.06 [3.14–5.02], p &lt; 0.001). After adjustment for important clinical factors, female sex remained associated with greater maximal TAA (p = 0.019). Conclusion: Female ATAAD patients had larger absolute ascending aortic diameters than males, implying a distinct timing in disease presentation or selection bias. Translational studies on the aortic wall and studies on growth patterns should further elucidate these sex differences.</p

Unlocking the potential of photon counting detector CT for paediatric imaging: a pictorial essay

Recent advancements in CT technology have introduced a revolutionary innovation to practice known as the Photon-Counting detector (PCD) CT imaging. The pivotal hardware enhancement of the PCD-CT scanner lies in its detectors, which consist of smaller pixels than standard detectors and allow direct conversion of individual X-rays to electrical signals. As a result, CT images are reconstructed at higher spatial resolution (as low as 0.2 mm) and reduced overall noise, at no expense of an increased radiation dose. These features are crucial for paediatric imaging, especially for infants and young children, where anatomical structures are notably smaller than in adults and in whom keeping dose as low as possible is especially relevant. Since January 2022, our hospital has had the opportunity to work with PCD-CT technology for paediatric imaging. This pictorial review will showcase clinical examples of PCD-CT imaging in children. The aim of this pictorial review is to outline the potential paediatric applications of PCD-CT across different anatomical regions, as well as to discuss the benefits in utilizing PCD-CT in comparison to conventional standard energy integrating detector CT

Imaging cell lineage with a synthetic digital recording system

Multicellular development depends on the differentiation of cells into specific fates with precise spatial organization. Lineage history plays a pivotal role in cell fate decisions, but is inaccessible in most contexts. Engineering cells to actively record lineage information in a format readable in situ would provide a spatially resolved view of lineage in diverse developmental processes. Here, we introduce a serine integrase-based recording system that allows in situ readout, and demonstrate its ability to reconstruct lineage relationships in cultured stem cells and flies. The system, termed intMEMOIR, employs an array of independent three-state genetic memory elements that can recombine stochastically and irreversibly, allowing up to 59,049 distinct digital states. intMEMOIR accurately reconstructed lineage trees in stem cells and enabled simultaneous analysis of single cell clonal history, spatial position, and gene expression in Drosophila brain sections. These results establish a foundation for microscopy-readable clonal analysis and recording in diverse systems

Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis - a proof of concept study

Introduction Prosthetic valve endocarditis (PVE) is a serious complication of prosthetic valve implantation, with an estimated yearly incidence of at least 0.4-1.0%. The Duke criteria and subsequent modifications have been developed as a diagnostic framework for infective endocarditis (IE) in clinical studies. However, their sensitivity and specificity are limited, especially for PVE. Furthermore, their most recent versions (ESC2015 and ESC2023) include advanced imaging modalities, e.g., cardiac CTA and [18F]FDG PET/CT as major criteria. However, despite these significant changes, the weighing system using major and minor criteria has remained unchanged. This may have introduced bias to the diagnostic set of criteria. Here, we aimed to evaluate and improve the predictive value of the modified Duke/ESC 2015 (MDE2015) criteria by using machine learning algorithms.Methods In this proof-of-concept study, we used data of a well-defined retrospective multicentre cohort of 160 patients evaluated for suspected PVE. Four machine learning algorithms were compared to the prediction of the diagnosis according to the MDE2015 criteria: Lasso logistic regression, decision tree with gradient boosting (XGBoost), decision tree without gradient boosting, and a model combining predictions of these (ensemble learning). All models used the same features that also constitute the MDE2015 criteria. The final diagnosis of PVE, based on endocarditis team consensus using all available clinical information, including surgical findings whenever performed, and with at least 1 year follow up, was used as the composite gold standard.Results The diagnostic performance of the MDE2015 criteria varied depending on how the category of 'possible' PVE cases were handled. Considering these cases as positive for PVE, sensitivity and specificity were 0.96 and 0.60, respectively. Whereas treating these cases as negative, sensitivity and specificity were 0.74 and 0.98, respectively. Combining the approaches of considering possible endocarditis as positive and as negative for ROC-analysis resulted in an excellent AUC of 0.917. For the machine learning models, the sensitivity and specificity were as follows: logistic regression, 0.92 and 0.85; XGBoost, 0.90 and 0.85; decision trees, 0.88 and 0.86; and ensemble learning, 0.91 and 0.85, respectively. The resulting AUCs were, in the same order: 0.938, 0.937, 0.930, and 0.941, respectively.Discussion In this proof-of-concept study, machine learning algorithms achieved improved diagnostic performance compared to the major/minor weighing system as used in the MDE2015 criteria. Moreover, these models provide quantifiable certainty levels of the diagnosis, potentially enhancing interpretability for clinicians. Additionally, they allow for easy incorporation of new and/or refined criteria, such as the individual weight of advanced imaging modalities such as CTA or [18F]FDG PET/CT. These promising preliminary findings warrant further studies for validation, ideally in a prospective cohort encompassing the full spectrum of patients with suspected IE

HIF-1 and SKN-1 Coordinate the Transcriptional Response to Hydrogen Sulfide in Caenorhabditis elegans

Hydrogen sulfide (H2S) has dramatic physiological effects on animals that are associated with improved survival. C. elegans grown in H2S are long-lived and thermotolerant. To identify mechanisms by which adaptation to H2S effects physiological functions, we have measured transcriptional responses to H2S exposure. Using microarray analysis we observe rapid changes in the abundance of specific mRNAs. The number and magnitude of transcriptional changes increased with the duration of H2S exposure. Functional annotation suggests that genes associated with protein homeostasis are upregulated upon prolonged exposure to H2S. Previous work has shown that the hypoxia-inducible transcription factor, HIF-1, is required for survival in H2S. In fact, we show that hif-1 is required for most, if not all, early transcriptional changes in H2S. Moreover, our data demonstrate that SKN-1, the C. elegans homologue of NRF2, also contributes to H2S-dependent changes in transcription. We show that these results are functionally important, as skn-1 is essential to survive exposure to H2S. Our results suggest a model in which HIF-1 and SKN-1 coordinate a broad transcriptional response to H2S that culminates in a global reorganization of protein homeostasis networks