Myddosomes in Toll-like receptor signaling-one to bind and rule them all.

Toll-like receptors (TLRs) are innate immune sensors for the presence of pathogens and endogenous danger signals. TLR activation results in conserved intracellular signaling events that orchestrate inflammation and antimicrobial defense. While the identity and interplay of key TLR signaling components are well established, how these largely cytosolic proteins are physically connected is not well understood. For the activation of conserved intracellular signaling events, most TLRs engage the adapter MyD88 (myeloid differentiation primary response 88), which assembles into higher-order protein complexes, myddosomes. In their recent publication, Fisch et al. present evidence that oligomeric myddosomes detach from initiating TLRs and evolve into larger scaffolds that dynamically assemble not only proximal but also distal cytosolic elements required to execute the entire cascade of the TLR-MyD88 signaling pathway. Coinciding with decline in TLR signaling over time, myddosomes progressively recruit autophagy machinery that mediates myddosome clearance. These findings expand the current understanding of TLR signaling by positioning myddosomes as the central structural element that physically assembles the key executors and regulators of TLR-MyD88-dependent intracellular signaling cascades.

Correlated rotational alignment spectroscopy: a new tool for high-resolution spectroscopy and the analysis of heterogeneous samples.

Correlated rotational alignment spectroscopy correlates observables of ultrafast gas-phase spectroscopy with high-resolution, broad-band rotational Raman spectra. This article reviews the measurement principle of CRASY, existing implementations for mass-correlated measurements, and the potential for future developments. New spectroscopic capabilities are discussed in detail: signals for individual sample components can be separated even in highly heterogeneous samples. Isotopologue rotational spectra can be observed at natural isotope abundance. Fragmentation channels are readily assigned in molecular and cluster mass spectra. And finally, rotational Raman spectra can be measured with sub-MHz resolution, an improvement of several orders-of-magnitude as compared to preceding experiments.

Validation of the German version of the Asthma Impairment and Risk Questionnaire (AIRQ).

BACKGROUND: The Asthma Impairment and Risk Questionnaire (AIRQ), a 10-item, equally weighted, yes/no tool assessing symptom impairment and risk of exacerbations in patients with asthma aged ≥12 years, was developed and validated in a US patient population to evaluate varying levels of asthma control. This study aimed to validate the German language version of the AIRQ in patients aged ≥12 years with different levels of asthma control. METHODS: A cross-sectional, observational, multi-centre study comprising a single visit was conducted in multiple specialised asthma centres and general practices in Germany. A total of 300 patients completed the following measures: 1) Patient Sociodemographic and Clinical Questionnaire, 2) AIRQ, 3) Asthma Control Test (ACT), and 4) Asthma Control Questionnaire (ACQ-6). Logistic regression analyses were conducted to assess the AIRQ score cut points with the greatest predictive validity in discriminating between different control levels relative to a standard of ACT plus prior-year exacerbations or ACQ-6 plus prior-year exacerbations. RESULTS: The German version of the AIRQ demonstrated a robust capability to correctly identify well-controlled versus not well- or very poorly controlled (AUC values of 0.90 or higher) and well- or not well-controlled versus very poorly controlled asthma (AUC values of 0.89 or higher). CONCLUSIONS: The German version of the AIRQ is a suitable tool to identify adults with varying levels of asthma control, which in turn can help to accurately identify patients with uncontrolled asthma in clinical practice.

Spatially regularized low-rank tensor approximation for accurate and fast tractography.

Tractography based on diffusion Magnetic Resonance Imaging (dMRI) is the prevalent approach to the in vivo delineation of white matter tracts in the human brain. Many tractography methods rely on models of multiple fiber compartments, but the local dMRI information is not always sufficient to reliably estimate the directions of secondary fibers. Therefore, we introduce two novel approaches that use spatial regularization to make multi-fiber tractography more stable. Both represent the fiber Orientation Distribution Function (fODF) as a symmetric fourth-order tensor, and recover multiple fiber orientations via low-rank approximation. Our first approach computes a joint approximation over suitably weighted local neighborhoods with an efficient alternating optimization. The second approach integrates the low-rank approximation into a current state-of-the-art tractography algorithm based on the unscented Kalman filter (UKF). These methods were applied in three different scenarios. First, we demonstrate that they improve tractography even in high-quality data from the Human Connectome Project, and that they maintain useful results with a small fraction of the measurements. Second, on the 2015 ISMRM tractography challenge, they increase overlap, while reducing overreach, compared to low-rank approximation without joint optimization or the traditional UKF, respectively. Finally, our methods permit a more comprehensive reconstruction of tracts surrounding a tumor in a clinical dataset. Overall, both approaches improve reconstruction quality. At the same time, our modified UKF significantly reduces the computational effort compared to its traditional counterpart, and to our joint approximation. However, when used with ROI-based seeding, joint approximation more fully recovers fiber spread.

Distinct contributions of the innate immune receptors TLR2 and RP105 to formation and architecture of structured lung granulomas in mice infected with Mycobacterium tuberculosis.

Granulomas are key histopathological features of Mycobacterium tuberculosis (Mtb) infection, with complex roles in pathogen control and dissemination. Thus, understanding drivers and regulators of granuloma formation is important for improving tuberculosis diagnosis, treatment, and prevention. Yet, molecular mechanisms underpinning granuloma formation and dynamics remain poorly understood. Here we used low-dose Mtb infection of C57BL/6 mice, which elicits structured lung granulomas composed of central macrophage clusters encased by a lymphocyte mantle, alongside the disorganized lymphocyte and macrophage clusters commonly observed in Mtb-infected mice. Using gene-deficient mice, we observed that Toll-like receptor (TLR) 2 and the TLR-related Radioprotective 105 kDa protein (RP105) contributed to the extent and spatial positioning of pathology in infected lung tissues, consistent with functional cooperation between TLR2 and RP105 in the innate immune recognition of Mtb. In mice infected with the highly virulent Mtb clinical isolate HN878, TLR2, but not RP105, positively regulated the extent of central macrophage regions within structured granulomas. Moreover, RP105, but not TLR2, promoted the formation of structured lung granulomas, suggesting that the functions of RP105 as an innate immune sensor for Mtb reach beyond its roles as TLR2 co-receptor. TLR2 and RP105 contributions to lung pathology are governed by Mtb biology, as neither receptor affected the frequency or architecture of structured granulomas in mice infected with the reference strain Mtb H37Rv. Thus, by revealing distinctive as well as cooperative functions of TLR2 and RP105 in lung pathology, our data identify TLRs as molecular determinants of TB granuloma formation and architecture, and expand understanding of how interactions between innate immune receptors and Mtb shape TB disease manifestation.

Reducing instability of inter-subject covariance of FDG uptake networks using structure-weighted sparse estimation approach.

PURPOSE: Sparse inverse covariance estimation (SICE) is increasingly utilized to estimate inter-subject covariance of FDG uptake (FDGcov) as proxy of metabolic brain connectivity. However, this statistical method suffers from the lack of robustness in the connectivity estimation. Patterns of FDGcov were observed to be spatially similar with patterns of structural connectivity as obtained from DTI imaging. Based on this similarity, we propose to regularize the sparse estimation of FDGcov using the structural connectivity. METHODS: We retrospectively analyzed the FDG-PET and DTI data of 26 healthy controls, 41 patients with Alzheimer's disease (AD), and 30 patients with frontotemporal lobar degeneration (FTLD). Structural connectivity matrix derived from DTI data was introduced as a regularization parameter to assign individual penalties to each potential metabolic connectivity. Leave-one-out cross validation experiments were performed to assess the differential diagnosis ability of structure weighted SICE approach. A few approaches of structure weighted were compared with the standard SICE. RESULTS: Compared to the standard SICE, structural weighting has shown more stable performance in the supervised classification, especially in the differentiation AD vs. FTLD (accuracy of 89-90%, while unweighted SICE only 85%). There was a significant positive relationship between the minimum number of metabolic connection and the robustness of the classification accuracy (r = 0.57, P < 0.001). Shuffling experiments showed significant differences between classification score derived with true structural weighting and those obtained by randomized structure (P < 0.05). CONCLUSION: The structure-weighted sparse estimation can enhance the robustness of metabolic connectivity, which may consequently improve the differentiation of pathological phenotypes.

Engaging the Wisdom of Older Veterans to Enhance VA Healthcare, Research, and Services.

BACKGROUND: Stakeholder engagement helps ensure that research is relevant, clinical innovations are responsive, and healthcare services are patient-centered. OBJECTIVE: Establish and sustain a Veteran engagement board involving older Veterans and caregivers to provide input on aging-related research and clinical demonstration projects. DESIGN AND PARTICIPANTS: The Older Veteran Engagement Team (OVET)-a group of eight Veterans and one caregiver who range in age from 62 to 92-was formed in November 2017 and has met monthly since January 2018. The OVET provides feedback on topics that reflect the foci of the VA Eastern Colorado Geriatric Research Education and Clinical Center (GRECC) (e.g., physical functioning, hearing health, and emotional wellness/mental health). Ongoing evaluation documents the return on investment of Veteran engagement. MAIN MEASURES: The OVET member and provider/investigator meeting evaluations with longitudinal follow-up at 6 and 12 months. RESULTS: Return on investment of Veteran engagement is multi-faceted. For OVET, ROI ranges from grant support to improved healthcare quality/efficiency to social-emotional benefits. To date, funding awards total over $2.3 M for NIH and VA-funded projects to which OVET provided substantive feedback. Documented impacts on healthcare services include reductions in patient wait times, more appropriate utilization of services and increased patient satisfaction. Social-emotional benefits include generativity, as OVET members contribute to improving clinical and community-based supports for other Veterans. The OVET provides an opportunity for older Veterans to share their lived experience with trainees and early career investigators who are preparing for careers serving Veterans. CONCLUSION: The OVET is similar to other established stakeholder engagement groups; team members offer their individual viewpoints at any stage of research, clinical demonstration, or quality improvement projects. The OVET provides a mechanism for the voice of older Veterans and caregivers to shape aspects of individual projects. Importantly, these projects support patient-centered care and promote the characteristics of an age-friendly healthcare system.

German regional variation of acute and high oral corticosteroid use for asthma.

OBJECTIVE: To improve understanding of real-world asthma treatment and inform physician education, we evaluated regional variation in asthma prevalence and oral corticosteroid (OCS) use across Germany. METHODS: We developed a machine learning gradient-boosted tree model with IMS® Disease Analyzer electronic medical records, which cover 3% of German patients. This model had a 91% accuracy in predicting the presence of asthma and chronic obstructive pulmonary disease. We applied the model to the IMS® Longitudinal Prescription database, with 82% national coverage, to classify patients receiving treatment for airflow obstruction from October 2017-September 2018 in 63 regions in Germany. RESULTS: Of 2.4 million individuals under statutory health insurance predicted to have asthma, 13.7%, 18.7%, 36.5%, 29.4%, and 1.7% received treatment classified as Global Initiative for Asthma (GINA) Steps 1, 2, 3, 4, and 5, respectively. Approximately 7-15% of those at GINA Steps 1-4 and 35% at Step 5 treatment received ≥1 acute OCS prescription (duration <10 days). Of patients receiving GINA Steps 1-4 and Step 5 treatments, 1-3% and 86%, respectively, received ≥1 high-dosage OCS prescription. Cumulative OCS dosage and percentages of patients receiving OCS differed substantially across regions, and regions with lower OCS use had greater use of biologic therapies. CONCLUSIONS: Both acute and high OCS use varied regionally across Germany, with overall use suggesting patients are considerable risk of adverse effects and long-term health consequences.Supplemental data for this article can be accessed at publisher's website.

[Experiences with digital care of patients with chronic and acute lung diseases during the SARS-CoV-2 pandemic]. / Erfahrungen mit der digitalen Versorgung von Patienten mit chronischen und akuten Lungenerkrankungen während der SARS-CoV-2-Pandemie.

BACKGROUND: Management of patients with respiratory disorders, such as asthma or chronic obstructive pulmonary disease (COPD), became challenging during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic due to infection prevention measures. To maintain care, a remote monitoring program was initiated, comprising a smartphone app and a Bluetooth spirometry device. OBJECTIVE: To assess patient- and physician-related experience with remote monitoring. MATERIAL AND METHODS: Structured questionnaires were developed to rate experiences from the patient or physician perspective on six-level Likert scales. Interactions between patients and physicians via the digital platform and overall utilization was analyzed. RESULTS: A total of 745 patients with asthma, COPD, post-coronavirus disease 2019 (COVID-19) and other respiratory diseases were enrolled from 31 centers in Germany. Mean follow-up was 49.4 ± 12.6 weeks. Each participant submitted on average 289 measurements. Patient-reported experience with the remote monitoring program was positive, with the highest satisfaction reported for "Experience with home measurement" (1.4 ± 0.5; 99% positive), followed by "Communication/interaction" (1.8 ± 0.9; 83% positive) and "Overall satisfaction with program" (1.8 ± 0.8; 87% positive). In all, 70% reported subjective quality of life improvements related to participation in the program. Physician satisfaction with the program was also high with a mean rating of 2.2 ± 1.2. DISCUSSION: App-based remote monitoring was successfully implemented in routine care during the SARS-CoV­2 pandemic and demonstrated potential for improvements in care. Patient-relevant experience was positive in all dimensions and remote monitoring was well accepted. Physicians who participated in the program also expressed positive experiences, as demonstrated by a high level of interaction with the platform and positive evaluations of effects from the program.

Rab6b localizes to the Golgi complex in murine macrophages and promotes tumor necrosis factor release in response to mycobacterial infection.

The proinflammatory cytokine tumor necrosis factor (TNF) plays a central role in the host control of mycobacterial infections. Expression and release of TNF are tightly regulated, yet the molecular mechanisms that control the release of TNF by mycobacteria-infected host cells, in particular macrophages, are incompletely understood. Rab GTPases direct the transport of intracellular membrane-enclosed vesicles and are important regulators of macrophage cytokine secretion. Rab6b is known to be predominantly expressed in the brain where it functions in retrograde transport and anterograde vesicle transport for exocytosis. Whether it executes similar functions in the context of immune responses is unknown. Here we show that Rab6b is expressed by primary mouse macrophages, where it localized to the Golgi complex. Infection with Mycobacterium bovis bacille Calmette-Guérin (BCG) resulted in dynamic changes in Rab6b expression in primary mouse macrophages in vitro as well as in organs from infected mice in vivo. We further show that Rab6b facilitated TNF release by M. bovis BCG-infected macrophages, in the absence of discernible impact on Tnf messenger RNA and intracellular TNF protein expression. Our observations identify Rab6b as a positive regulator of M. bovis BCG-induced TNF trafficking and secretion by macrophages and positions Rab6b among the molecular machinery that orchestrates inflammatory cytokine responses by macrophages.

CRASY: correlated rotational alignment spectroscopy of pyridine. The rotational Raman spectrum of pyridine and asymmetric fragmentation of pyridine dimer cations.

We investigated the rotational Raman spectrum of pyridine monomers and pyridine dimers with mass-correlated rotational alignment spectroscopy (mass-CRASY) and ab initio calculations. The mass spectrum showed a strong signal for the protonated pyridine cation, which we assigned to asymmetric fragmentation of the dimer: ab initio calculations revealed facile proton transfer in the dimer cation and thermodynamically favorable asymmetric fragmentation. In the rotational spectrum correlated to the monomer mass channel, we assigned up to 40 lines for rotational states J ≤ 8. No spectrum could be assigned for the dimer, possibly due to the theoretically predicted presence of multiple dimer structures.

Mass-correlated rotational Raman spectra with high resolution, broad bandwidth, and absolute frequency accuracy.

We present mass-correlated rotational alignment spectroscopy, based on the optical excitation of a coherent rotational quantum wave and the observation of temporal wave interferences in a mass spectrometer. Combined electronic and opto-mechanical delays increased the observation time and energy resolution by an order of magnitude compared with preceding time-domain measurements. Rotational transition frequencies were referenced to an external clock for accurate absolute frequency measurements. Rotational Raman spectra for six naturally occurring carbon disulfide isotopologues were resolved with 3 MHz resolution over a spectral range of 500 GHz. Rotational constants were determined with single-kilohertz accuracy, competitive with state-of-the-art frequency domain measurements.

De novo structure determination of butadiene by isotope-resolved rotational Raman spectroscopy.

Isotope-selective rotational spectroscopy allows to calculate molecular structures independent of assumptions or theoretical predictions. Here, we present the first de novo structure determination based on mass-correlated rotational Raman spectroscopy, analyzing the carbon atom positions of butadiene. Mass correlation allowed us to analyze signals of rare 13C isotopologues at natural abundance, without interference from the main isotopologue signals. Fitted rotational constants and structural parameters confirm literature data from rovibrational spectroscopy of synthetic isotopologues and electron diffraction experiments.

Viewing Imaging Studies: How Patient Location and Imaging Site Affect Referring Physicians.

The purpose of this study was to assess if clinical indications, patient location, and imaging sites predict the viewing pattern of referring physicians for CT and MR of the head, chest, and abdomen. Our study included 166,953 CT/MR images of head/chest/abdomen in 2016-2017 in the outpatient (OP, n = 83,981 CT/MR), inpatient (IP, n = 51,052), and emergency (ED, n = 31,920) settings. There were 125,329 CT/MR performed in the hospital setting and 41,624 in one of the nine off-campus locations. We extracted information regarding body region (head/chest/abdomen), patient location, and imaging site from the electronic medical records (EPIC). We recorded clinical indications and the number of times referring physicians viewed CT/MR (defined as the number of separate views of imaging in the EPIC). Data were analyzed with the Microsoft SQL and SPSS statistical software. About 33% of IP CT and MR studies are viewed > 6 times compared to 7% for OP and 19% of ED studies (p < 0.001). Conversely, most OP studies (55%) were viewed 1-2 times only, compared to 21% for IP and 38% for ED studies (p < 0.001). In-hospital exams are viewed (≥ 6 views; 39% studies) more frequently than off-campus imaging (≥ 6 views; 17% studies) (p < 0.001). For head CT/MR, certain clinical indications (i.e., stroke) had higher viewing rates compared to other clinical indications such as malignancy, headache, and dizziness. Conversely, for chest CT, dyspnea-hypoxia had much higher viewing rates (> 6 times) in IP (55%) and ED (46%) than in OP settings (22%). Patient location and imaging site regardless of clinical indications have a profound effect on viewing patterns of referring physicians. Understanding viewing patterns of the referring physicians can help guide interpretation priorities and finding communication for imaging exams based on patient location, imaging site, and clinical indications. The information can help in the efficient delivery of patient care.

SHORE-based detection and imputation of dropout in diffusion MRI.

PURPOSE: In diffusion MRI, dropout refers to a strong attenuation of the measured signal that is caused by bulk motion during the diffusion encoding. When left uncorrected, dropout will be erroneously interpreted as high diffusivity in the affected direction. We present a method to automatically detect dropout, and to replace the affected measurements with imputed values. METHODS: Signal dropout is detected by deriving an outlier score from a simple harmonic oscillator-based reconstruction and estimation (SHORE) fit of all measurements. The outlier score is defined to detect measurements that are substantially lower than predicted by SHORE in a relative sense, while being less sensitive to measurement noise in cases of weak baseline signal. A second SHORE fit is based on detected inliers only, and its predictions are used to replace outliers. RESULTS: Our method is shown to reliably detect and accurately impute dropout in simulated data, and to achieve plausible results in corrupted in vivo dMRI measurements. Computational effort is much lower than with previously proposed alternatives. CONCLUSIONS: Deriving a suitable outlier score from SHORE results in a fast and accurate method for detection and imputation of dropout in diffusion MRI. It requires measurements with multiple b values (such as multi-shell or DSI), but is independent from the models used for analysis (such as DKI, NODDI, deconvolution, etc.).

Diffusion MRI visualization.

Modern diffusion magnetic resonance imaging (dMRI) acquires intricate volume datasets and biological meaning can only be found in the relationship between its different measurements. Suitable strategies for visualizing these complicated data have been key to interpretation by physicians and neuroscientists, for drawing conclusions on brain connectivity and for quality control. This article provides an overview of visualization solutions that have been proposed to date, ranging from basic grayscale and color encodings to glyph representations and renderings of fiber tractography. A particular focus is on ongoing and possible future developments in dMRI visualization, including comparative, uncertainty, interactive and dense visualizations.

Comparison of basis functions and q-space sampling schemes for robust compressed sensing reconstruction accelerating diffusion spectrum imaging.

Time constraints placed on magnetic resonance imaging often restrict the application of advanced diffusion MRI (dMRI) protocols in clinical practice and in high throughput research studies. Therefore, acquisition strategies for accelerated dMRI have been investigated to allow for the collection of versatile and high quality imaging data, even if stringent scan time limits are imposed. Diffusion spectrum imaging (DSI), an advanced acquisition strategy that allows for a high resolution of intra-voxel microstructure, can be sufficiently accelerated by means of compressed sensing (CS) theory. CS theory describes a framework for the efficient collection of fewer samples of a data set than conventionally required followed by robust reconstruction to recover the full data set from sparse measurements. For an accurate recovery of DSI data, a suitable acquisition scheme for sparse q-space sampling and the sensing and sparsifying bases for CS reconstruction need to be selected. In this work we explore three different types of q-space undersampling schemes and two frameworks for CS reconstruction based on either Fourier or SHORE basis functions. After CS recovery, diffusion and microstructural parameters and orientational information are estimated from the reconstructed data by means of state-of-the-art processing techniques for dMRI analysis. By means of simulation, diffusion phantom and in vivo DSI data, an isotropic distribution of q-space samples was found to be optimal for sparse DSI. The CS reconstruction results indicate superior performance of Fourier-based CS-DSI compared to the SHORE-based approach. Based on these findings we outline an experimental design for accelerated DSI and robust CS reconstruction of the sparse measurements that is suitable for the application within time-limited studies.

High-resolution rotational Raman spectroscopy of benzene.

We present a rotational Raman spectrum for benzene with single-MHz resolution, more than a 100-fold improvement on literature data and sufficient to partially resolve K-splitting in some bands. Spectra for a frequency range of 0 to 500 GHz were measured through the observation of a coherent rotational wave packet in the time domain over a time scale of 1 microsecond. Spectroscopic frequencies were referenced to a GPS-stabilized clock. Fitted molecular constants of B = 5689.2671(±52) MHz, DJ = 1178(±50) Hz, and DJK = -2300(±120) Hz agree with results from some high-resolution rovibrational and rovibronic spectra but contradict others.

Replicated Landscape Genomics Identifies Evidence of Local Adaptation to Urbanization in Wood Frogs.

Native species that persist in urban environments may benefit from local adaptation to novel selection factors. We used double-digest restriction-side associated DNA (RAD) sequencing to evaluate shifts in genome-wide genetic diversity and investigate the presence of parallel evolution associated with urban-specific selection factors in wood frogs (Lithobates sylvaticus). Our replicated paired study design involved 12 individuals from each of 4 rural and urban populations to improve our confidence that detected signals of selection are indeed associated with urbanization. Genetic diversity measures were less for urban populations; however, the effect size was small, suggesting little biological consequence. Using an FST outlier approach, we identified 37 of 8344 genotyped single nucleotide polymorphisms with consistent evidence of directional selection across replicates. A genome-wide association study analysis detected modest support for an association between environment type and 12 of the 37 FST outlier loci. Discriminant analysis of principal components using the 37 FST outlier loci produced correct reassignment for 87.5% of rural samples and 93.8% of urban samples. Eighteen of the 37 FST outlier loci mapped to the American bullfrog (Rana [Lithobates] catesbeiana) genome, although none were in coding regions. This evidence of parallel evolution to urban environments provides a powerful example of the ability of urban landscapes to direct evolutionary processes.

Intravenous radiographic contrast administered prior to high-dose methotrexate and subsequent toxicity requiring the use of glucarpidase.

Methotrexate is a dihydrofolate reductase inhibitor that interferes with DNA synthesis, DNA repair, and cellular replication. We present the first adult case of a patient who received intravenous contrast prior to administration of high-dose methotrexate, who subsequently experienced delayed methotrexate clearance and renal impairment necessitating the use of glucarpidase. This case displays a possible correlation between intravenous radiographic contrast administration and resulting toxicity due to delayed methotrexate clearance.