Exploring historical changes in mountain river hydrodynamics induced by human impact.

During the 20th-century many mountain rivers in Europe were subjected to intensive human impacts which substantially modified their channel morphology. How these changes affected river hydrodynamics and response to floods remains uncertain. In this work, we perform hydraulic modelling using data from archival aerial photos to explore relations between hydraulic parameters of floods and human-induced channel incision occurring on the Czarny Dunajec River (Polish Carpathians) between 1964 and 2012. Data on vertical position of the channel used for two-dimensional modelling of flood flows were extracted (as Digital Elevation Models DEMs) from archival aerial photos from 1964 and 1983 and ALS (Airborne Laser Skanning)-derived DEM from 2012. Water depth, flow velocity, bed shear stress, and sediment critical diameter were modelled for four flood scenarios (2-year, 5-year, 20-year, and 50-year floods) as well as the extent of flooded area and additionally the grain size of channel sediment was calculated. The values of water depth, flow velocity, bed shear stress and sediment critical diameter increased significantly between 1964 and 1983, especially for 20-year and 50-year floods. Only the flow velocity within the floodplain zone did not increase for the two largest flood scenarios due to the expansion of riparian forest in the second half of the twentieth century. The increase in flow rate was accompanied by a progressive reduction of the extent of flooded area, especially between 1964 and 1983, as well as by increase in mean grain size of channel sediment. Between 1983 and 2012 changes in hydraulic parameters were less pronounced, and coarser and well packed channel sediment dominated on the river bed. Our work demonstrates that reconstruction of past river hydrodynamics, rather than river state at time horizons, can give essential insights into functioning of the river channel and floodplain during the intensification of human impacts after 1950s

Human Resting-State Complexity of BOLD fMRI in Ultra-High-Field MRI at 7T: a primer

Synopsis Keywords: fMRI Analysis, fMRI (resting state), complexity Motivation: BOLD-fMRI intrinsic functional connectivity has limited capability to assess the temporal dynamics of complex brain networks. The insufficient signal-to-noise ratio of 3T MRI might prevent the detection of subtle alterations. Goal(s): Detecting resting-state complexity alterations in healthy subsamples using 7T MRI. Approach: Multiscale entropy was computed for ten scales from 0.1 to 1 Hz. A whole-brain ANCOVA was conducted to assess entropy differences of the scales between 30 healthy adults with spider phobia and 45 without. Results: Spider phobia showed decreased entropy in several fear-related brain regions in all scales except 1 Hz. Impact: 7T fMRI detected reduced high-frequency resting-state multiscale entropy related to spider phobia, indicating worse local processing of fear and memory-related brain regions. Introduction Intrinsic functional connectivity (iFC) derived from BOLD-fMRI data is still widely used to map the brain’s functional architecture at rest. Despite the substantial insight gained into diseased brain networks and corroborated markers for cognitive symptomatology, the method’s major shortcoming, one correlative metric over the entire scanning time, fails at characterizing the temporal dynamics of complex brain systems. Recently, multiscale entropy (MSE) analyses of resting-state BOLD fMRI signals have gained increased attention in basic and clinical neuroscience. MSE detects self-similarity of complex signals across multiple time scales in a random noise environment [1]. The MSE’s main advantage is that it can assess alterations and interactions of neuronal circuits on spatial and temporal scales. Hence, numerous studies have yielded novel insights into temporal dynamics of the brain’s functional reorganization [2-4]. Both iFC and MSE rely on a sufficient temporal and spatial signal-to-noise ratio (SNR) of the data. With advances in image processing algorithms, and especially with the availability of 7T MRI, images with increased SNR allow the detection of more subtle effects [5,6]. Hence, this study explored the MSE of a set of 7T BOLD-fMRI data that consisted of healthy participants, who were subdivided into a spider phobia (PH) and a control group (HC) sample. The rationale was to test whether MSE at 7T is sufficiently sensitive to detect MSE differences between these groups even though no spider images, the fear-triggering stimulus defining spider phobia, were shown during data acquisition. Nevertheless, assuming a hyperactive fear circuit in PH, we hypothesized decreased local processing complexity as measured with high-frequency MSE in brain regions involving the amygdala, hippocampus, parahippocampus, medial temporal lobe, fusiform gyrus, and anterior cingulate cortex [7]. Methods Study participant demographics and statistics are depicted in Figure 1. Resting-state fMRI data was obtained with a 32-channel head/neck coil in a Siemens Magnetom Terra 7T machine at the University Hospital Bern. A multiband echo-planar protocol with 360 measurements, 60 slices, TR/TE = 1000/25 ms, and iso-voxel size = 2 mm^3 was applied. Image preprocessing included motion-realignment, slice-time correction, detrending, denoising, normalization, and 3-mm-smoothing. MSE was computed using the LOFT Complexity Toolbox [8] with pattern matching threshold r = 0.2, pattern length = 2, scales = 1 – 10 (1 – 0.1 Hz) [9-11]. All images were masked with a mean grey matter mask of all subjects. Voxel-wise statistics were computed in SPM12 and comprised an ANCOVA with factors scale (1 – 10) and diagnosis (HC, PH), and age as a covariate. The significance threshold was pFWE < 0.05 and a cluster-size threshold of 5 voxels. Significant clusters were overlaid with the aal atlas [12-14] and segmented accordingly for a post-hoc ROI analysis, a non-parametric ANOVA investigating mean ROI entropy for each scale between the diagnosis groups. Results The voxel-wise interaction of the 2 × 10 ANCOVA revealed several significant clusters (F(9,729) = 5.49, p(FWE) = 0.05, cluster-size threshold = 5 voxels), which were subdivided into seven major regions of interest (ROIs): amygdala, caudate nucleus, fusiform gyrus, hippocampus, parahippocampus, putamen, and thalamus (Figure 2). To disentangle the two-way interaction involving these ROIs, the post-hoc ANOVA revealed the main effects of diagnosis (F(1) = 5.26, p = 0.02), ROI (F(3.8) = 20.0, p < 0.0001), and scale (F(1.5) = 114.8, p < 0.0001, see Figure 3). Merely the scale × ROI two-way interaction was significant (F(14) = 5.0, p < 0.0001). Note that the three-way interaction diagnosis × ROI × scale was not significant. Discussion This proof-of-concept study revealed reduced entropy in anxiety, memory, and emotion-regulation brain regions in PH compared to HC. Most brain regions with decreased MSE, such as the amygdala, hippocampus, parahippocampus, and fusiform gyrus, are hyperactive in PH [7]. The thalamus has been linked with autonomous arousal in PH [15], while the striatum, including putamen and caudate nucleus, was shown active during threat monitoring [16]. These MSE reductions were found in 9 of 10 frequencies (0.1 – 0.5 Hz). In the 1 Hz frequency, no group differences could be observed (Figure 3). With the scanning protocol used in this study, lower frequencies could not be assessed (i.e., < 0.1 Hz), which is a limitation and might explain the uniformity of the effects between most scales. Conclusions MSE analysis is a promising method that takes advantage of the higher temporal SNR of 7T fMRI, as demonstrated in this study. Using MSE as an add-on to iFC measures, a more refined picture of the dynamics of complex neuronal systems can be achieved. Acknowledgements This study was supported by the University Hospital for Psychiatry and Psychotherapy Bern, Switzerland. We thank the following contributors: Andrea Federspiel and Piotr Radojewski of the Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland, for technical and clinical support at the MRI scanner site; Dilmini Wijesinghe of the Laboratory of FMRI Technology, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Keck School of Medicine, Los Angeles, California, USA, for providing valuable insight in fMRI complexity developments; Thomas Dierks of the Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland, for conceptual advice. References 1. Costa M, Goldberger AL, Peng CK. Multiscale Entropy Analysis of Complex Physiologic Time Series. Phys Rev Lett. 2002;89(6):068102 2. Jann K, Boudreau J, Albrecht D, Cen SY, Cabeen RP, Ringman JM, Wang DJJ. FMRI Complexity Correlates with Tau-PET and Cognitive Decline in Late-Onset and Autosomal Dominant Alzheimer’s Disease. J Alz Dis. 2023;95(2):437-451 3. Grieder M, Wang DJJ, Dierks T, Wahlund LO, Jann K. Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease. Front Neurosci. 2018;12(770) 4. Xin X, Long S, Sun M, Gao X. The Application of Complexity Analysis in Brain Blood-Oxygen Signal. Brain Sci. 2021;11(11):1415 5. Dumoulin SO, Fracasso A, van der Zwaag W, Siero JCW, Petridou N. Ultra-high field MRI: Advancing systems neuroscience towards mesoscopic human brain function. NeuroImage. 2018;168:345-357 6. Pohmann R, Speck O, Scheffler K. Signal-to-noise ratio and MR tissue parameters in human brain imaging at 3, 7, and 9.4 tesla using current receive coil arrays. Magn Res Med. 2016;5(2):801-809 7. Soravia LM, Orosz A, Schwab S, Nakataki M, Wiest R, Federspiel A. CBT reduces CBF: cognitive-behavioral therapy reduces cerebral blood flow in fear-relevant brain regions in spider phobia. Brain Behav. 2016;6(9):e00510 8. Laboratory of Functional MRI Technology (LOFT), Department of Neurology, USC Developed by Jothi A, Sharma N, Adhikari S, Wang DJJ, Jann K 9. Li X, Zhu Z, Zhao W, Sun Y, Wen D, Xie Y, Liu X, Niu H, Han Y. Decreased resting-state brain signal complexity in patients with mild cognitive impairment and Alzheimer’s disease: a multi-scale entropy analysis. Biomed Opt Express. 2018;9(4):1916-1929 10. Smith RX, Yan L, Wang DJJ. Multiple time scale complexity analysis of resting state FMRI. Brain Imaging Behav. 2014;8:284–291 11. Sokunbi MO. Sample entropy reveals high discriminative power between young and elderly adults in short fMRI data sets. Front Neuroinform. 2014;8:69 12. Maldjian JA, Laurienti PJ, Kraft RA, Burdette JH. An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. NeuroImage. 2003;19(3):1233-9 13. Maldjian JA, Laurienti PJ, Burdette JH. Precentral gyrus discrepancy in electronic versions of the Talairach atlas. NeuroImage. 2004;21(1):450-5 14. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage. 2002;15(1):273-89 15. Del Casale A, Ferracuti S, Rapinesi C, Serata D, Piccirilli M, Savoja V, Kotzalidis GD, Manfredi G, Angeletti G, Tatarelli R, Girardi P. Functional neuroimaging in specific phobia. Psychiatr Res Neuroimaging. 2012;202(3):181-197 16. Mobbs D, Yu R, Rowe JB, Eich H, FeldmanHall O, Dalgleish T. Neural activity associated with monitoring the oscillating threat value of a tarantula. Proc Natl Acad Sci U S A. 2010;107(47):20582-2058

TOLLIP and MUC5B modulate the effect of ambient NO2 on respiratory symptoms in infancy.

BACKGROUND Current knowledge suggests that the gene region containing MUC5B and TOLLIP plays a role in airway defence and airway inflammation, and hence respiratory disease. It is also known that exposure to air pollution increases susceptibility to respiratory disease. We aimed to study whether the effect of air pollutants on the immune response and respiratory symptoms in infants may be modified by polymorphisms in MUC5B and TOLLIP genes. METHODS 359 healthy term infants from the prospective Basel-Bern Infant Lung Development (BILD) birth cohort were included in the study. The main outcome was the score of weekly assessed respiratory symptoms in the first year of life. Using the candidate gene approach, we selected 10 single nucleotide polymorphisms (SNPs) from the MUC5B and TOLLIP regions. Nitrogen dioxide (NO2) and particulate matter ≤10μm in aerodynamic diameter (PM10) exposure was estimated on a weekly basis. We used generalised additive mixed models adjusted for known covariates. To validate our results in vitro, cells from a lung epithelial cell line were downregulated in TOLLIP expression and exposed to diesel particulate matter (DPM) and polyinosinic-polycytidylic acid. RESULTS Significant interaction was observed between modelled air pollution (weekly NO2 exposure) and 5 SNPs within MUC5B and TOLLIP genes regarding respiratory symptoms as outcome: E.g., infants carrying minor alleles of rs5744034, rs3793965 and rs3750920 (all TOLLIP) had an increased risk of respiratory symptoms with increasing NO2 exposure. In vitro experiments showed that cells downregulated for TOLLIP react differently to environmental pollutant exposure with DPM and viral stimulation. CONCLUSION Our findings suggest that the effect of air pollution on respiratory symptoms in infancy may be influenced by the genotype of specific SNPs from the MUC5B and TOLLIP regions. For validation of the findings, we provided in vitro evidence for the interaction of TOLLIP with air pollution

Hospital- and Ventilator-associated Pneumonia early after Lung Transplantation: a prospective Study on Incidence, Pathogen Origin and Outcome.

BACKGROUND Hospital- (HAP) and ventilator-associated pneumonia (VAP) are important complications early (<30 days) after lung transplantation (LT). However, current incidence, associated factors and outcomes are not well reported. METHODS LT recipients transplanted at our institution (07/2019-01/2020 and 10/2021-11/2022) were prospectively included. We assessed incidence and presentation of pneumonia and evaluated the impact of associated factors using regression models. In addition, we evaluated molecular relatedness of respiratory pathogens collected peri-transplant and at pneumonia occurrence using pulsed-field-gel-electrophoresis (PFGE). RESULTS In the first 30 days post-LT, 25/270 (9.3%) recipients were diagnosed with pneumonia (68% [17/25] VAP; 32% [8/25] HAP). Median time to pneumonia was 11 days (IQR 7-13). 49% (132/270) of donor and 16% (44/270) of recipient respiratory peri-transplant cultures were positive. However, pathogens associated with pneumonia were not genetically related to either donor or recipient cultures at transplant, as determined by PFGE.Diagnosed pulmonary hypertension (HR 4.42, 95% CI 1.62-12.08) and immunosuppression use (HR 2.87, 95% CI 1.30-6.56) were pre-transplant factors associated with pneumonia.Pneumonia occurrence was associated with longer hospital stay (HR 5.44, 95% CI 2.22-13.37) and VAP with longer ICU stay (HR 4.31, 95% CI: 1.73-10.75) within the first 30 days post-transplant; 30- and 90-day mortality were similar. CONCLUSIONS Prospectively assessed early pneumonia incidence occurred in around 10% of LT. Populations at increased risk for pneumonia occurrence include LT with pre-transplant pulmonary hypertension and pre-transplant immunosuppression. Pneumonia was associated with increased healthcare use, highlighting the need for further improvements by preferentially targeting higher-risk patients

Short cycles of random permutations with cycle weights: Point processes approach

We study the asymptotic behavior of short cycles of random permutations with cycle weights. More specifically, on a specially constructed metric space whose elements encode all possible cycles, we consider a point process containing all information on cycles of a given random permutation on 1,…,n. The main result of the paper is the distributional convergence with respect to the vague topology of the above processes towards a Poisson point process as n→∞ for a wide range of cycle weights. As an application, we give several limit theorems for various statistics of cycles

Family environment and self-esteem development in adolescence: A replication and extension

A study by Krauss et al. (2020) suggested that the family environment (e.g., parental warmth, economic conditions of family) plays an important role for self-esteem development in adolescence. The present research sought to closely replicate and extend the study, using 4-wave longitudinal data from the Iowa Youth and Families Project, including 451 families. To replicate the prior study, we conducted the same set of analyses with similar measures and multi-informant assessments of mothers, fathers, and children from the same families. To extend the previous study, we tested novel aspects (i.e., controlling for prior exposure and testing the effect of the quality of sibling relationships). Overall, the findings provide no evidence for prospective effects between family environment and self-esteem in adolescence

Drought alters aboveground biomass production efficiency: Insights from two European beech forests.

The fraction of photosynthetically assimilated carbon that trees allocate to long-lasting woody biomass pools (biomass production efficiency - BPE), is a key metric of the forest carbon balance. Its apparent simplicity belies the complex interplay between underlying processes of photosynthesis, respiration, litter and fruit production, and tree growth that respond differently to climate variability. Whereas the magnitude of BPE has been routinely quantified in ecological studies, its temporal dynamics and responses to extreme events such as drought remain less well understood. Here, we combine long-term records of aboveground carbon increment (ACI) obtained from tree rings with stand-level gross primary productivity (GPP) from eddy covariance (EC) records to empirically quantify aboveground BPE (= ACI/GPP) and its interannual variability in two European beech forests (Hainich, DE-Hai, Germany; Sorø, DK-Sor, Denmark). We found significant negative correlations between BPE and a daily-resolved drought index at both sites, indicating that woody growth is de-prioritized under water limitation. During identified extreme years, early-season drought reduced same-year BPE by 29 % (Hainich, 2011), 31 % (Sorø, 2006), and 14 % (Sorø, 2013). By contrast, the 2003 late-summer drought resulted in a 17 % reduction of post-drought year BPE at Hainich. Across the entire EC period, the daily-to-seasonal drought response of BPE resembled that of ACI, rather than that of GPP. This indicates that BPE follows sink dynamics more closely than source dynamics, which appear to be decoupled given the distinctive climate response patterns of GPP and ACI. Based on our observations, we caution against estimating the magnitude and variability of the carbon sink in European beech (and likely other temperate forests) based on carbon fluxes alone. We also encourage comparable studies at other long-term EC measurement sites from different ecosystems to further constrain the BPE response to rare climatic events