High-quality genome of a novel Thermosynechococcaceae species from Namibia and characterization of its protein expression patterns at elevated temperatures.

Thermophilic cyanobacteria thrive in extreme environments, making their thermoresistant enzymes valuable for industrial applications. Common habitats include hot springs, which act as evolutionary accelerators for speciation due to geographical isolation. The family Thermosynechococcaceae comprises thermophilic cyanobacteria known for their ability to thrive in high-temperature environments. These bacteria are notable for their photosynthetic capabilities, significantly contributing to primary production in extreme habitats. Members of Thermosynechococcaceae exhibit unique adaptations that allow them to perform photosynthesis efficiently at elevated temperatures, making them subjects of interest for studies on microbial ecology, evolution, and potential biotechnological applications. In this study, the genome of a thermophilic cyanobacterium, isolated from a hot spring near Okahandja in Namibia, was sequenced using a PacBio Sequel IIe long-read platform. Cultivations were performed at elevated temperatures of 40, 50, and 55°C, followed by proteome analyses based on the annotated genome. Phylogenetic investigations, informed by the 16S rRNA gene and aligned nucleotide identity (ANI), suggest that the novel cyanobacterium is a member of the family Thermosynechococcaceae. Furthermore, the new species was assigned to a separate branch, potentially representing a novel genus. Whole-genome alignments supported this finding, revealing few conserved regions and multiple genetic rearrangement events. Additionally, 129 proteins were identified as differentially expressed in a temperature-dependent manner. The results of this study broaden our understanding of cyanobacterial adaptation to extreme environments, providing a novel high-quality genome of Thermosynechococcaceae cyanobacterium sp. Okahandja and several promising candidate proteins for expression and characterization studies.

Rate of cardiovascular events up to 8 years after uncomplicated myocarditis: a nationwide cohort study.

AIMS: While prognosis of acute myocarditis with uncomplicated presentation is perceived as benign, data on long-term outcomes are scarce. We evaluated rates of myocarditis-associated cardiovascular events after a first-time hospitalization with uncomplicated acute myocarditis in patients without known heart disease. METHODS AND RESULTS: In this retrospective nationwide population-based cohort study from 2013 to 2020, hospitalized patients with uncomplicated acute myocarditis but without known heart disease were 1:1 propensity score-matched with surgical controls hospitalized for laparoscopic appendectomy. As assessed in time-to-event analyses, the primary outcome was a composite of rehospitalization for myocarditis, pericardial disease, heart failure and its complications, arrhythmias, implantation of cardiac devices, and heart transplant. After matching, we identified 1439 patients with uncomplicated acute myocarditis (median age of 35 years, 74.0% male) and 1439 surgical controls (median age of 36 years, 74.4% male). Over a median follow-up of 39 months, compared with surgical controls, the hazard ratio for the primary composite outcome was 42.3 [95% confidence interval (CI) 17.4-102.8], corresponding to an incidence rate of 43.7 vs. 0.9 per 1000 patient-years (py) and an incidence rate difference of 42.7 (95% CI 36.7-48.8) per 1000 py. CONCLUSION: Patients hospitalized with uncomplicated acute myocarditis and no known prior heart disease were associated with substantial risk for cardiovascular events over a follow-up of up to 8 years. This calls for a more efficient therapeutic management of this population of patients.

Neutrophil extracellular traps and DNases orchestrate formation of peritoneal adhesions.

Peritoneal adhesions are poorly understood but highly prevalent conditions that can cause intestinal obstruction and pelvic pain requiring surgery. While there is consensus that stress-induced inflammation triggers peritoneal adhesions, the molecular processes of their formation still remain elusive. We performed murine models and analyzed human samples to monitor the formation of adhesions and the treatment with DNases. Various molecular analyses were used to evaluate the adhesions. The experimental peritoneal adhesions of the murine models and biopsy material from humans are largely based on neutrophil extracellular traps (NETs). Treatment with DNASE1 (Dornase alfa) and the human DNASE1L3 analog (NTR-10), significantly reduced peritoneal adhesions in experimental models. We conclude that NETs serve as essential scaffold for the formation of adhesions; DNases interfere with this process. Herein, we show that therapeutic application of DNases can be employed to prevent the formation of murine peritoneal adhesions. If this can be translated into the human situation requires clinical studies.

Targeting NETs using dual-active DNase1 variants.

Background: Neutrophil Extracellular Traps (NETs) are key mediators of immunothrombotic mechanisms and defective clearance of NETs from the circulation underlies an array of thrombotic, inflammatory, infectious, and autoimmune diseases. Efficient NET degradation depends on the combined activity of two distinct DNases, DNase1 and DNase1-like 3 (DNase1L3) that preferentially digest double-stranded DNA (dsDNA) and chromatin, respectively. Methods: Here, we engineered a dual-active DNase with combined DNase1 and DNase1L3 activities and characterized the enzyme for its NET degrading potential in vitro. Furthermore, we produced a mouse model with transgenic expression of the dual-active DNase and analyzed body fluids of these animals for DNase1 and DNase 1L3 activities. We systematically substituted 20 amino acid stretches in DNase1 that were not conserved among DNase1 and DNase1L3 with homologous DNase1L3 sequences. Results: We found that the ability of DNase1L3 to degrade chromatin is embedded into three discrete areas of the enzyme's core body, not the C-terminal domain as suggested by the state-of-the-art. Further, combined transfer of the aforementioned areas of DNase1L3 to DNase1 generated a dual-active DNase1 enzyme with additional chromatin degrading activity. The dual-active DNase1 mutant was superior to native DNase1 and DNase1L3 in degrading dsDNA and chromatin, respectively. Transgenic expression of the dual-active DNase1 mutant in hepatocytes of mice lacking endogenous DNases revealed that the engineered enzyme was stable in the circulation, released into serum and filtered to the bile but not into the urine. Conclusion: Therefore, the dual-active DNase1 mutant is a promising tool for neutralization of DNA and NETs with potential therapeutic applications for interference with thromboinflammatory disease states.

Cardiac Involvement in Systemic and Local Vasculitides: The Value of Noninvasive Multimodality Imaging.

Despite significant advances in managing systemic vasculitides, cardiovascular morbidity, and mortality are still of primary concern. Advances in noninvasive imaging have broadened our understanding of the clinical heterogeneity of cardiac involvement in vasculitides. Common cardiovascular complications in primary or secondary vasculitides are; coronary artery aneurysms, acute coronary syndromes, myocarditis, pericarditis, endocarditis, and valvular dysfunction. Echocardiography, cardiac magnetic resonance , positron emission tomography, and computed tomography angiography are essential in identifying cardiac involvement and guiding treatment. Here, we present our experiences of cardiac involvement in systemic vasculitides, covering most aspects of common cardiac complications based on a multi-modality approach to challenging (real-world) cases. As many cardiac manifestations are clinically silent, heart function should be systemically assessed by a multimodality imaging-based approach, including ECG, serial echocardiograms with strain imaging and 3D, and cardiac magnetic resonance to detect early signs of cardiac manifestations. This enables timely intervention and optimal medical treatment, which is essential for a better prognosis. There is a need for better and closer collaboration in clinical practice and research fields between cardiologists and rheumatologists.

Mastering targeted genome engineering of GC-rich oleaginous yeast for tailored plant oil alternatives for the food and chemical sector.

BACKGROUND: Sustainable production of triglycerides for various applications is a major focus of microbial factories. Oleaginous yeast species have been targeted for commercial production of microbial oils. Among all the oleaginous yeasts examined in a previous comparative study, Cutaneotrichosporon oleaginosus showed the highest lipid productivity. Moreover, a new lipid production process for C. oleaginosus with minimal waste generation and energy consumption resulted in the highest lipid productivity in the history of oleaginous yeasts. However, productivity and product diversity are restricted because of the genetic intractability of this yeast. To date, successful targeted genetic engineering of C. oleaginosus has not yet been reported. RESULTS: The targeted gene editing was successfully carried out in C. oleaginosus using CRISPR/Cas system. A tailored enzyme system isolated to degrade the C. oleaginosus cell wall enabled the isolation of viable spheroplasts that are amenable to in-cell delivery of nucleic acids and proteins. The employment of both Cas9 protein and Cas mRNA was effective in obtaining strains with URA5 knockout that did not exhibit growth in the absence of uracil. Subsequently, we successfully created several strains with enhanced lipid yield (54% increase compared to that in wild type) or modified fatty acid profiles comparable with those of cocoa butter or sunflower oil compositions. CONCLUSION: This study establishes the first targeted engineering technique for C. oleaginosus using the CRISPR/Cas system. The current study creates the foundation for flexible and targeted strain optimizations towards building a robust platform for sustainable microbial lipid production. Moreover, the genetic transformation of eukaryotic microbial cells using Cas9 mRNA was successfully achieved.

Left ventricular function and volumes from gated [13N]-ammonia positron emission tomography myocardial perfusion imaging: A prospective head-to-head comparison against CMR using a hybrid PET/MR device.

BACKGROUND: Positron emission tomography (PET) myocardial perfusion imaging (MPI) can be used to evaluate left ventricular (LV) volumes and function. We performed a head-to-head comparison of LV function and volumes obtained simultaneously using [13N]-ammonia-PET and cardiac magnetic resonance (CMR), with the latter serving as the reference standard. METHODS AND RESULTS: In this prospective study, 51 patients underwent [13N]-ammonia-PET MPI and CMR using a hybrid PET/MR device. Left ventricular end-systolic volumes (LVESV), end-diastolic volumes (LVEDV), stroke volumes (LVSV), ejection fractions (LVEF), and segmental wall motion were analyzed for both methods and were compared using correlational and Bland-Altman (BA) analysis; segmental wall motion was compared using ANOVA. The agreement between [13N]-ammonia-PET and CMR for LVEF was good, with minimal bias (- .6%) and narrow BA limits of agreement (- 7.9% to 6.8%), but [13N]-ammonia-PET systematically underestimated LV volumes, with high bias in LVESV (- 11.2 ml), LVEDV (- 28.9 ml), and LVSV (- 17.5 ml). Mean segmental wall motion in [13N]-ammonia-PET differed significantly among the corresponding normokinetic (6.6 ± 2 mm), hypokinetic (5.1 ± 2 mm), and akinetic (3.3 ± 2 mm) segments in CMR (P < .01). CONCLUSION: LVEF and LV wall motion can be accurately assessed using [13N]-ammonia-PET MPI, although LV volumes are significantly underestimated compared to CMR.

Impact of deep learning image reconstructions (DLIR) on coronary artery calcium quantification.

BACKGROUND: Deep learning image reconstructions (DLIR) have been recently introduced as an alternative to filtered back projection (FBP) and iterative reconstruction (IR) algorithms for computed tomography (CT) image reconstruction. The aim of this study was to evaluate the effect of DLIR on image quality and quantification of coronary artery calcium (CAC) in comparison to FBP. METHODS: One hundred patients were consecutively enrolled. Image quality-associated variables (noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)) as well as CAC-derived parameters (Agatston score, mass, and volume) were calculated from images reconstructed by using FBP and three different strengths of DLIR (low (DLIR_L), medium (DLIR_M), and high (DLIR_H)). Patients were stratified into 4 risk categories according to the Coronary Artery Calcium - Data and Reporting System (CAC-DRS) classification: 0 Agatston score (very low risk), 1-99 Agatston score (mildly increased risk), Agatston 100-299 (moderately increased risk), and ≥ 300 Agatston score (moderately-to-severely increased risk). RESULTS: In comparison to standard FBP, increasing strength of DLIR was associated with a significant and progressive decrease of image noise (p < 0.001) alongside a significant and progressive increase of both SNR and CNR (p < 0.001). The use of incremental levels of DLIR was associated with a significant decrease of Agatston CAC score and CAC volume (p < 0.001), while mass score remained unchanged when compared to FBP (p = 0.232). The underestimation of Agatston CAC led to a CAC-DRS misclassification rate of 8%. CONCLUSION: DLIR systematically underestimates Agatston CAC score. Therefore, DLIR should be used cautiously for cardiovascular risk assessment. KEY POINTS: • In coronary artery calcium imaging, the implementation of deep learning image reconstructions improves image quality, by decreasing the level of image noise. • Deep learning image reconstructions systematically underestimate Agatston coronary artery calcium score. • Deep learning image reconstructions should be used cautiously in clinical routine to measure Agatston coronary artery calcium score for cardiovascular risk assessment.

Efficient Green Light Acclimation of the Green Algae Picochlorum sp. Triggering Geranylgeranylated Chlorophylls.

In analogy to higher plants, eukaryotic microalgae are thought to be incapable of utilizing green light for growth, due to the "green gap" in the absorbance profiles of their photosynthetic pigments. This study demonstrates, that the marine chlorophyte Picochlorum sp. is able to grow efficiently under green light emitting diode (LED) illumination. Picochlorum sp. growth and pigment profiles under blue, red, green and white LED illumination (light intensity: 50-200 µmol m-2 s-1) in bottom-lightened shake flask cultures were evaluated. Green light-treated cultures showed a prolonged initial growth lag phase of one to 2 days, which was subsequently compensated to obtain comparable biomass yields to red and white light controls (approx. 0.8 gDW L-1). Interestingly, growth and final biomass yields of the green light-treated sample were higher than under blue light with equivalent illumination energies. Further, pigment analysis indicated, that during green light illumination, Picochlorum sp. formed unknown pigments (X1-X4). Pigment concentrations increased with illumination intensity and were most abundant during the exponential growth phase. Mass spectrometry and nuclear magnetic resonance data indicated, that pigments X1-X2 and X3-X4 are derivatives of chlorophyll b and a, which harbor C=C bonds in the phytol side chain similar to geranylgeranylated chlorophylls. Thus, for the first time, the natural accumulation of large pools (approx. 12 mg gDW -1) of chlorophyll intermediates with incomplete hydrogenation of their phytyl chains is demonstrated for algae under monochromatic green light (Peak λ 510 nm, full width at half maximum 91 nm). The ability to utilize green light offers competitive advantages for enhancing biomass production, particularly under conditions of dense cultures, long light pathways and high light intensity. Green light acclimation for an eukaryotic microalgae in conjunction with the formation of new aberrant geranylgeranylated chlorophylls and high efficiency of growth rates are novel for eukaryotic microalgae. Illumination with green light could enhance productivity in industrial processes and trigger the formation of new metabolites-thus, underlying mechanisms require further investigation.

Risk stratification using coronary artery calcium scoring based on low tube voltage computed tomography.

To determine if coronary artery calcium (CAC) scoring using computed tomography at 80 kilovolt-peak (kVp) and 70-kVp and tube voltage-adapted scoring-thresholds allow for accurate risk stratification as compared to the standard 120-kVp protocol. We prospectively included 170 patients who underwent standard CAC scanning at 120-kVp and 200 milliamperes and additional scans with 80-kVp and 70-kVp tube voltage with adapted tube current to normalize image noise across scans. Novel kVp-adapted thresholds were applied to calculate CAC scores from the low-kVp scans and were compared to those from standard 120-kVp scans by assessing risk reclassification rates and agreement using Kendall's rank correlation coefficients (Τb) for risk categories bounded by 0, 1, 100, and 400. Interreader reclassification rates for the 120-kVp scans were assessed. Agreement for risk classification obtained from 80-kVp and 70-kVp scans as compared to 120-kVp was good (Τb = 0.967 and 0.915, respectively; both p < 0.001) with reclassification rates of 7.1% and 17.2%, respectively, mostly towards a lower risk category. By comparison, the interreader reclassification rate was 4.1% (Τb = 0.980, p < 0.001). Reclassification rates were dependent on body mass index (BMI) with 7.1% and 13.6% reclassifications for the 80-kVp and 70-kVp scans, respectively, in patients with a BMI < 30 kg/m2 (n = 140), and 2.9% and 7.4%, respectively, in patients with a BMI < 25 kg/m2 (n = 68). Mean effective radiation dose from the 120-kVp, the 80-kVp, and 70-kVp scans was 0.54 ± 0.03, 0.42 ± 0.02, and 0.26 ± 0.02 millisieverts. CAC scoring with reduced tube voltage allows for accurate risk stratification if kVp-adapted thresholds for calculation of CAC scores are applied.ClinicalTrials.gov NCT03637231.

Splenic switch-off as a novel marker for adenosine response in nitrogen-13 ammonia PET myocardial perfusion imaging: Cross-validation against CMR using a hybrid PET/MR device.

BACKGROUND: No methodology is available to distinguish truly reduced myocardial flow reserve (MFR) in positron emission tomography myocardial perfusion imaging (PET MPI) from seemingly impaired MFR due to inadequate adenosine response. The adenosine-induced splenic switch-off (SSO) sign has been proposed as a potential marker for adequate adenosine response in cardiac magnetic resonance (CMR). We assessed the feasibility of detecting SSO in nitrogen-13 ammonia PET MPI using SSO in CMR as the standard of reference. METHODS AND RESULTS: Fifty patients underwent simultaneous CMR and PET MPI on a hybrid PET/MR device with co-injection of a gadolinium-based contrast agent and nitrogen-13 ammonia during rest and adenosine-induced stress. In CMR, SSO was assessed visually (positive vs negative SSO) and quantitatively by calculating the ratio of the peak signal intensity of the spleen during stress over rest (SIR). In PET MPI, the splenic signal activity ratio (SAR) was calculated as the maximal standard uptake value of the spleen during stress over rest. The median SIR was significantly lower in patients with positive versus negative SSO in CMR (0.57 [IQR 0.49 to 0.62] vs 0.89 [IQR 0.76 to 0.98]; P < .001). Similarly, median SAR in PET MPI was significantly lower in patients with positive versus negative SSO (0.40 [IQR 0.32 to 0.45] vs 0.80 [IQR 0.47 to 0.98]; P < .001). CONCLUSION: Similarly to CMR, SSO can be detected in nitrogen-13 ammonia PET MPI. This might help distinguish adenosine non-responders from patients with truly impaired MFR due to microvascular dysfunction or multivessel coronary artery disease.

Transluminal attenuation gradient derived from coronary CT angiography to predict ischemia in SPECT myocardial perfusion imaging: Effect of coronary cross-sectional area.

BACKGROUND: Coronary computed tomography angiography (CCTA)-based transluminal attenuation gradient (TAG) was suggested to determine the functional significance of a stenosis. However, evidence that TAG acquired by wide-volume scanners can assess the hemodynamic significance of stenosis assessed by single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is lacking. Moreover, coronary cross-sectional area may influence TAG. Hence, we aimed at assessing the diagnostic value of TAG to predict ischemia in SPECT-MPI and the correlation between TAG and the transluminal cross-sectional area gradient (TCG). METHODS: Patients undergoing CCTA and SPECT-MPI for suspected coronary artery disease were included. TAG and TCG were calculated measuring the mean vessel attenuation and the cross-sectional area along major coronary vessels at 5-mm intervals. RESULTS: A total of 255 coronary arteries of 87 patients were included. TAG and TCG did not discriminate between coronary arteries with or without ischemia as assessed by SPECT-MPI (p = .44 and p = .25, respectively). The area under the curve to predict ischemia was not increased by adding TAG (0.88, 95% CI 0.83-0.92) or TCG (0.87, 95% CI 0.81-0.90) to CCTA alone (0.85, 95% CI 0.80-0.89). There was a significant correlation between TAG and TCG (r = 0.43; p < .001). CONCLUSIONS: CCTA-derived TAG and TCG do not offer any value in predicting ischemia assessed by SPECT-MPI. TAG is partly affected by differences in the coronary luminal area.

Impact of Adaptive Statistical Iterative Reconstruction-V on Coronary Artery Calcium Scores Obtained From Low-Tube-Voltage Computed Tomography - A Patient Study.

OBJECTIVE: To evaluate the impact of adaptive statistical iterative reconstruction-V (ASIR-V) on the accuracy of ultra-low-dose coronary artery calcium (CAC) scoring. MATERIALS AND METHOD: One-hundred-and-three patients who underwent computed tomography (CT) for CAC scoring were prospectively included. All underwent standard scanning with 120-kilovolt-peak (kVp) and with 80- and 70-kVp tube voltage. ASiR-V was applied to the 80- and 70-kVp scans at different levels. The 120-kVp scans reconstructed with filtered back projection served as the standard of reference. Recently published novel kVp-adapted thresholds were used for calculation of CAC scores from 80- and 70-kVp scans and the resulting CAC scores were compared against the standard of reference. Patients were stratified into six CAC score risk categories: 0, 1-10, 11-100, 101-400, 401-1000, and >1000. RESULTS: Increasing levels of ASIR-V led to an increasing underestimation of CAC scores with bias ranging from -128 to -118 and from -205 to -198 for the 80- and 70-kVp scans, respectively, when compared with the standard of reference. Reconstruction with 20% and 40% ASIR-V for the 80- and 70-kVp scans, respectively, yielded noise levels comparable to the standard of reference. Nevertheless, a change in risk-class was observed in 29 (28.6%) and 46 (44.7%) patients, exclusively to a lower risk-class, when CAC scores were derived from these reconstructions. CONCLUSION: ASIR-V leads to noise reduction in CT scans acquired with low tube-voltages. However, ASIR-V introduces substantial inaccuracies and marked underestimation of ultra-low-dose CAC scoring as compared with standard-dose CAC scoring despite normalization of noise.

Identifying carbohydrate-active enzymes of Cutaneotrichosporon oleaginosus using systems biology.

BACKGROUND: The oleaginous yeast Cutaneotrichosporon oleaginosus represents one of the most promising microbial platforms for resource-efficient and scalable lipid production, with the capacity to accept a wide range of carbohydrates encapsulated in complex biomass waste or lignocellulosic hydrolysates. Currently, data related to molecular aspects of the metabolic utilisation of oligomeric carbohydrates are sparse. In addition, comprehensive proteomic information for C. oleaginosus focusing on carbohydrate metabolism is not available. RESULTS: In this study, we conducted a systematic analysis of carbohydrate intake and utilisation by C. oleaginosus and investigated the influence of different di- and trisaccharide as carbon sources. Changes in the cellular growth and morphology could be observed, depending on the selected carbon source. The greatest changes in morphology were observed in media containing trehalose. A comprehensive proteomic analysis of secreted, cell wall-associated, and cytoplasmatic proteins was performed, which highlighted differences in the composition and quantity of secreted proteins, when grown on different disaccharides. Based on the proteomic data, we performed a relative quantitative analysis of the identified proteins (using glucose as the reference carbon source) and observed carbohydrate-specific protein distributions. When using cellobiose or lactose as the carbon source, we detected three- and five-fold higher diversity in terms of the respective hydrolases released. Furthermore, the analysis of the secreted enzymes enabled identification of the motif with the consensus sequence LALL[LA]L[LA][LA]AAAAAAA as a potential signal peptide. CONCLUSIONS: Relative quantification of spectral intensities from crude proteomic datasets enabled the identification of new enzymes and provided new insights into protein secretion, as well as the molecular mechanisms of carbo-hydrolases involved in the cleavage of the selected carbon oligomers. These insights can help unlock new substrate sources for C. oleaginosus, such as low-cost by-products containing difficult to utilize carbohydrates. In addition, information regarding the carbo-hydrolytic potential of C. oleaginosus facilitates a more precise engineering approach when using targeted genetic approaches. This information could be used to find new and more cost-effective carbon sources for microbial lipid production by the oleaginous yeast C. oleaginosus.

A Newly Designed Automatically Controlled, Sterilizable Flat Panel Photobioreactor for Axenic Algae Culture.

In context of the global climate change, microalgae processes are gaining momentum as a biotechnological tool for direct fixation and valorization of greenhouse gases. Algae have the metabolic capacity to photosynthetically convert CO2 into high value products, such as food additives, under economic boundary conditions. High cost, commercial flat panel gas-lift bioreactors for microalgae cultivation at laboratory scale provide either small volumes or no sterile operation, which limits academic research. This brief report presents initial data for a new type of sterile operating flat panel gas-lift bioreactor with a unique asymmetrical U-shape. It utilizes automatable process control technologies that adhere to industrial standards to enhance data reproducibility and aid industrial scale up. The practicability was demonstrated using a Chlorella sorokiniana cultivation, which showed the typical growth behavior. Due to the sophisticated implemented control engineering technology, pivotal parameters as pH and temperature can be determined within a range of ±0.1 units, which was confirmed experimentally. The new flat panel gas-lift photobioreactor presented in this brief report fills the technology gap at laboratory scale with an autoclavable volume of 7.2 L. Moreover, it is easy to rebuild by means of the hereby provided blueprint, while exhibiting a six-fold cost reduction compared to commercially available flat panel photobioreactors.

Prognostic value of regional myocardial flow reserve derived from 13N-ammonia positron emission tomography in patients with suspected coronary artery disease.

PURPOSE: To assess the prognostic value of regional quantitative myocardial flow measures as assessed by 13N-ammonia positron emission tomography (PET) myocardial perfusion imaging (MPI) in patients with suspected coronary artery disease (CAD). METHODS: We retrospectively included 150 consecutive patients with suspected CAD who underwent clinically indicated 13 N-ammonia PET-MPI and who did not undergo revascularization within 90 days of PET-MPI. The presence or absence of a decreased global myocardial flow reserve (i.e., MFR < 2) as well as decreased regional MFR (i.e., ≥ 2 adjacent segments with MFR < 2) was recorded, and patients were classified as having preserved global and regional MFR (MFR group 1), preserved global but decreased regional MFR (MFR group 2), or decreased global and regional MFR (MFR group 3). We obtained follow-up regarding major adverse cardiac events (MACE, i.e., a combined endpoint including all-cause death, non-fatal myocardial infarction, and late revascularization) and all-cause death. RESULTS: Over a median follow-up of 50 months (IQR 38-103), 30 events occurred in 29 patients. Kaplan-Meier analysis showed significantly reduced event-free and overall survival in MFR groups 2 and 3 compared to MFR group 1 (log-rank: p = 0.015 and p = 0.013). In a multivariable Cox regression analysis, decreased regional MFR was an independent predictor for MACE (adjusted HR 3.44, 95% CI 1.17-10.11, p = 0.024) and all-cause death (adjusted HR 4.72, 95% CI 1.07-20.7, p = 0.04). CONCLUSIONS: A decreased regional MFR as assessed by 13 N-ammonia PET-MPI confers prognostic value by identifying patients at increased risk for future adverse cardiac outcomes and all-cause death.

Collective human intelligence outperforms artificial intelligence in a skin lesion classification task.

BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNN) enable accurate diagnosis of medical images and perform on or above the level of individual physicians. Recently, collective human intelligence (CoHI) was shown to exceed the diagnostic accuracy of individuals. Thus, diagnostic performance of CoHI (120 dermatologists) versus individual dermatologists versus two state-of-the-art CNN was investigated. PATIENTS AND METHODS: Cross-sectional reader study with presentation of 30 clinical cases to 120 dermatologists. Six diagnoses were offered and votes collected via remote voting devices (quizzbox®, Quizzbox Solutions GmbH, Stuttgart, Germany). Dermatoscopic images were classified by a binary and multiclass CNN (FotoFinder Systems GmbH, Bad Birnbach, Germany). Three sets of diagnostic classifications were scored against ground truth: (1) CoHI, (2) individual dermatologists, and (3) CNN. RESULTS: CoHI attained a significantly higher accuracy [95 % confidence interval] (80.0 % [62.7 %-90.5 %]) than individual dermatologists (75.7 % [73.8 %-77.5 %]) and CNN (70.0 % [52.1 %-83.3 %]; all P < 0.001) in binary classifications. Moreover, CoHI achieved a higher sensitivity (82.4 % [59.0 %-93.8 %]) and specificity (76.9 % [49.7 %-91.8 %]) than individual dermatologists (sensitivity 77.8 % [75.3 %-80.2 %], specificity 73.0 % [70.6 %-75.4 %]) and CNN (sensitivity 70.6 % [46.9 %-86.7 %], specificity 69.2 % [42.4 %-87.3 %]). The diagnostic accuracy of CoHI was superior to that of individual dermatologists (P < 0.001) in multiclass evaluation, with the accuracy of the latter comparable to multiclass CNN. CONCLUSIONS: Our analysis revealed that the majority vote of an interconnected group of dermatologists (CoHI) outperformed individuals and CNN in a demanding skin lesion classification task.

Potential Impact of Statins on Neuronal Stress Responses in Patients at Risk for Cardiovascular Disease.

BACKGROUND: Recent studies indicate that enhanced neuronal stress responses are associated with adverse cardiovascular outcomes. A chronic inflammatory state seems to mediate this detrimental neuro-cardiac communication. Statins are among the most widely prescribed medications in primary and secondary cardiovascular disease (CVD) prevention and not only lower lipid levels but also exhibit strong anti-inflammatory and neuroprotective effects. We therefore sought to investigate the influence of statins on neuronal stress responses in a patient cohort at risk for CVD. METHODS: 563 patients (61.5 ± 14.0 years) who underwent echocardiography and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) were retrospectively identified. Metabolic activity of the amygdala, a part of the brain's salience network, was quantified by 18F-FDG uptake, while normal cardiac morphology and function were assured by echocardiography. Vertebral bone marrow metabolism, a marker of inflammatory activity, was measured by 18F-FDG PET. RESULTS: Increased neuronal stress responses were associated with an increased inflammatory activity in the bone marrow (r = 0.152, p = 0.015) as well as with a subclinical reduction in left ventricular ejection fraction (LVEF, r = -0.138, p = 0.025). In a fully-adjusted linear regression model, statin treatment was identified as an independent, negative predictor of amygdalar metabolic activity (B-coefficient -0.171, p = 0.043). CONCLUSIONS: Our hypothesis-generating investigation suggests a potential link between the anti-inflammatory actions of statins and reduced neuronal stress responses which could lead to improved cardiovascular outcomes. The latter warrants further studies in a larger and prospective population.

Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition.

BACKGROUND: Studies systematically unravelling possible causes for false diagnoses of deep learning convolutional neural networks (CNNs) are scarce, yet needed before broader application. OBJECTIVES: The objective of the study was to investigate whether scale bars in dermoscopic images are associated with the diagnostic accuracy of a market-approved CNN. METHODS: This cross-sectional analysis applied a CNN trained with more than 150,000 images (Moleanalyzer-pro®, FotoFinder Systems Inc., Bad Birnbach, Germany) to investigate seven dermoscopic image sets depicting the same 130 melanocytic lesions (107 nevi, 23 melanomas) without or with digitally superimposed scale bars of different manufacturers. Sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for the CNN's binary classification of images with or without superimposed scale bars were assessed. RESULTS: Six dermoscopic image sets with different scale bars and one control set without scale bars (overall 910 images) were submitted to CNN analysis. In images without scale bars, the CNN attained a sensitivity [95% confidence interval] of 87.0% [67.9%-95.5%] and a specificity of 87.9% [80.3%-92.8%]. ROC AUC was 0.953 [0.914-0.992]. Scale bars were not associated with significant changes in sensitivity (range 87%-95.7%, all p ≥ 1.0). However, four scale bars induced a decrease of the CNN's specificity (range 0%-43.9%, all p < 0.001). Moreover, ROC AUC was significantly reduced by two scale bars (range 0.520-0.848, both p ≤ 0.042). CONCLUSIONS: Superimposed scale bars in dermoscopic images may impair the CNN's diagnostic accuracy, mostly by increasing the rate of the false-positive diagnoses. We recommend avoiding scale bars in images intended for CNN analysis unless specific measures counteracting effects are implemented. CLINICAL TRIAL NUMBER: This study was registered at the German Clinical Trial Register (DRKS-Study-ID: DRKS00013570; URL: https://www.drks.de/drks_web/).