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Vaccinations against COVID-19 are of the utmost importance in long-term care facilities. During the pandemic, mental health issues increased significantly. This cross-sectional analysis aimed to assess the associations of depression and anxiety with health literacy in people in need of care and the association of depression and burnout with vaccination readiness against COVID-19 in health care workers (HCWs). Within our cross-sectional study, people in need of care were assessed for symptoms of depression (PHQ-9), anxiety (GAD-7), and health literacy (HLS-EU-Q16). Among HCWs, we assessed symptoms of depression (PHQ-9) and burnout (MBI-HSS), as well as psychological antecedents of vaccination (5C) to measure vaccination readiness against COVID-19. A multivariate regression analysis was performed. Symptoms of a major depression were significantly associated with reduced health literacy (p = 0.010) in people in need of care. Among HCWs, symptoms of depression and burnout reduced vaccination readiness against COVID-19 significantly. In particular, collective responsibility was reduced in HCWs suffering from burnout symptoms (p = 0.001). People in need of care and their HCWs could benefit from intensified target group-specific vaccination counseling. Additionally, more attention should be paid to the protection of mental health in long-term care facilities.

Lichen planus (LP) is a highly prevalent inflammatory skin disease. While various clinical subtypes have been defined, detailed comparisons of these variants are lacking. This study aimed to elucidate differences in gene expression and cellular composition across LP subtypes. Lesional skin biopsies from 28 LP patients (classical, oral, genital, and lichen planopilaris) and seven non-diseased skin controls (NDC) were analyzed. Gene expression profiling of 730 inflammation-related genes was conducted using NanoString. Immune cell compositions were assessed by multiplex immunohistochemistry. Gene expression profiles revealed unique inflammatory signatures for each LP subtype. Lichen planopilaris exhibited the most divergence, with downregulated gene expression and upregulation of complement pathway genes (C5-7), along with elevated M2 macrophages. Oral and genital LP demonstrated similar profiles with strong upregulation of TNF-related and Toll-like receptor-associated genes. Oral LP showed the highest upregulation of cytotoxicity-associated genes, as well as high numbers of CD8+ IL-17A+ (Tc17) cells (8.02%). Interferon gene signatures were strongly upregulated in oral and classical LP. The study highlights distinct differences in inflammatory gene expression and cell composition across LP subtypes, emphasizing the need for tailored therapeutic approaches.

Background: Histogram indices (HIs) and texture features (TFs) are considered to play an important role in future oncologic PET-imaging and it is unknown how these indices are affected by changes of tracer doses. A randomized undersampling of PET list mode data enables a simulation of tracer dose reduction. We performed a phantom study to compare HIs/TFs of simulated and measured tracer dose reductions and evaluated changes of HIs/TFs in the liver of patients with PETs from simulated reduced tracer doses. Overall, 42 HIs/TFs were evaluated in a NEMA phantom at measured and simulated doses (stepwise reduction of [18 F] from 100% to 25% of the measured dose). [18 F]-FDG-PET datasets of 15 patients were simulated from 3.0 down to 0.5 MBq/kgBW in intervals of 0.25 MBq/kgBW. HIs/TFs were calculated from two VOIs placed in physiological tissue of the right and left liver lobe and linear correlations and coefficients of variation analysis were performed. Results: All 42 TFs did not differ significantly in measured and simulated doses (p > 0.05). Also, 40 TFs showed the same behaviour over dose reduction regarding differences in the same group (measured or simulated), and for 26 TFs a linear behaviour over dose reduction for measured and simulated doses could be validated. Out of these, 13 TFs could be identified, which showed a linear change in TF value in both the NEMA phantom and patient data and therefore should maintain the same informative value when transferred in a dose reduction setting. Out of this Homogeneity 2, Entropy and Zone size non-uniformity are of special interest because they have been described as preferentially considerable for tumour heterogeneity characterization. Conclusions: We could show that there was no significant difference of measured and simulated HIs/TFs in the phantom study and most TFs reveal a linear behaviour over dose reduction, when tested in homogeneous tissue. This indicates that texture analysis in PET might be robust to dose modulations.

Inflammasomes comprise a group of protein complexes with fundamental roles in the induction of inflammation. Upon sensing stress factors, their assembly induces the activation and release of the pro-inflammatory cytokines interleukin (IL)-1β and -18 and a lytic type of cell death, termed pyroptosis. Recently, CARD8 has joined the group of inflammasome sensors. The carboxy-terminal part of CARD8, consisting of a function-to-find-domain (FIIND) and a caspase activation and recruitment domain (CARD), resembles that of NLR family pyrin domain containing 1 (NLRP1), which is recognized as the main inflammasome sensor in human keratinocytes. The interaction with dipeptidyl peptidases 8 and 9 (DPP8/9) represents an activation checkpoint for both sensors. CARD8 and NLRP1 are activated by viral protease activity targeting their amino-terminal region. However, CARD8 also has some unique features compared to the established inflammasome sensors. Activation of CARD8 occurs independently of the inflammasome adaptor protein apoptosis-associated speck-like protein containing a CARD (ASC), leading mainly to pyroptosis rather than the activation and secretion of pro-inflammatory cytokines. CARD8 was also shown to have anti-inflammatory and anti-apoptotic activity. It interacts with, and inhibits, several proteins involved in inflammation and cell death, such as the inflammasome sensor NLRP3, CARD-containing proteins caspase-1 and -9, nucleotide-binding oligomerization domain containing 2 (NOD2), or nuclear factor kappa B (NF-κB). Single nucleotide polymorphisms (SNPs) of CARD8, some of them occurring at high frequencies, are associated with various inflammatory diseases. The molecular mechanisms underlying the different pro- and anti-inflammatory activities of CARD8 are incompletely understood. Alternative splicing leads to the generation of multiple CARD8 protein isoforms. Although the functional properties of these isoforms are poorly characterized, there is evidence that suggests isoform-specific roles. The characterization of the functions of these isoforms, together with their cell- and disease-specific expression, might be the key to a better understanding of CARD8’s different roles in inflammation and inflammatory diseases.

Tracking coffee roasting at an industrial scale for quality control is challenging. Bean color is a practical gauge for monitoring and regulating the process but only occurs before and after the process. This study highlights the feasibility of monitoring the process throughout using Raman spectroscopy. Strecker degradation and the Maillard reaction contribute to various aromatic compounds that can serve as markers in quality monitoring. Among these are chlorogenic acids (CGAs), recognized as pivotal factors determining the desired aroma. Here, drum and fluidized bed roaster processes were monitored, capitalizing on the chemical alterations induced by high temperatures (140–200 °C), particularly through the Maillard reaction. These chemical changes manifest in the scattered light signal. For real-time monitoring, Raman spectra were taken every 10 ms in selected ranges, with an average calculated every second. Utilizing a calibration matrix from a High-Pressure Liquid Chromatography (HPLC) method, CGA concentration becomes the control variable for assessing roasting progress. This study reveals the potential of Raman spectroscopy for tracking CGA during roasting. It establishes a correlation between inelastic scattered light and CGA validated through laboratory measurements and fixed roasting conditions, resulting in a theoretical CGA concentration that can be used as a process termination criterion.

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal form of pancreatic cancer characterized by therapy resistance and early metastasis, resulting in a low survival rate. Histone deacetylase (HDAC) inhibitors showed potential for the treatment of hematological malignancies. In PDAC, the overexpression of HDAC 2 is associated with the epithelial–mesenchymal transition (EMT), principally accompanied by the downregulation of the epithelial marker E-cadherin and increased metastatic capacity. The effector cytokine transforming growth factor-β (TGF β) is known to be a major inducer of the EMT in PDAC, leading to high metastatic and invasive potential. In addition, the overexpression of HDAC 6 in PDAC is associated with reduced apoptosis. Here, we have demonstrated that a novel HDAC 2/6 inhibitor not only significantly increased E-cadherin expression in PANC-1 cells (5.5-fold) and in 3D PDAC co-culture spheroids (2.5-fold) but was also able to reverse the TGF-β-induced downregulation of E-cadherin expression. Moreover, our study indicates that the HDAC inhibitor mediated re-differentiation resulting in a significant inhibition of tumor cell invasion by approximately 60% compared to control. In particular, we have shown that the HDAC inhibitor induces both apoptosis (2-fold) and cell cycle arrest. In conclusion, the HDAC 2/6 inhibitor acts by suppressing invasion via upregulating E-cadherin mediated by HDAC 2 blockade and by inducing cell cycle arrest leading to apoptosis via HDAC 6 inhibition. These results suggest that the HDAC 2/6 inhibitor might represent a novel therapeutic strategy for the treatment of PDAC tumorigenesis and metastasis.

Microbes and enzymes play essential roles in soil and plant rhizosphere ecosystem functioning. However, fungicides and plant root secretions may impact the diversity and abundance of microbiota structure and enzymatic activities in the plant rhizosphere. In this study, we analyzed soil samples from the rhizosphere of four cannabinoid-rich hemp (Cannabis sativa) cultivars (Otto II, BaOx, Cherry Citrus, and Wife) subjected to three different treatments (natural infection, fungal inoculation, and fungicide treatment). DNA was extracted from the soil samples, 16S rDNA was sequenced, and data were analyzed for diversity and abundance among different fungicide treatments and hemp cultivars. Fungicide treatment significantly impacted the diversity and abundance of the hemp rhizosphere microbiota structure, and it substantially increased the abundance of the phyla Archaea and Rokubacteria. However, the abundances of the phyla Pseudomonadota and Gemmatimonadetes were substantially decreased in treatments with fungicides compared to those without fungicides in the four hemp cultivars. In addition, the diversity and abundance of the rhizosphere microbiota structure were influenced by hemp cultivars. The influence of Cherry Citrus on the diversity and abundance of the hemp rhizosphere microbiota structure was less compared to the other three hemp cultivars (Otto II, BaOx, and Wife). Moreover, fungicide treatment affected enzymatic activities in the hemp rhizosphere. The application of fungicides significantly decreased enzyme abundance in the rhizosphere of all four hemp cultivars. Enzymes such as dehydrogenase, dioxygenase, hydrolase, transferase, oxidase, carboxylase, and peptidase significantly decreased in all the four hemp rhizosphere treated with fungicides compared to those not treated. These enzymes may be involved in the function of metabolizing organic matter and degrading xenobiotics. The ecological significance of these findings lies in the recognition that fungicides impact enzymes, microbiota structure, and the overall ecosystem within the hemp rhizosphere.

This paper presents an overview of integrating new research outcomes into the development of a structural health monitoring strategy for the floating cover at the Western Treatment Plant (WTP) in Melbourne, Australia. The size of this floating cover, which covers an area of approximately 470 m × 200 m, combined with the hazardous environment and its exposure to extreme weather conditions, only allows for monitoring techniques based on remote sensing. The floating cover is deformed by the accumulation of sewage matter beneath it. Our research has shown that the only reliable data for constructing a predictive model to support the structural health monitoring of this critical asset is obtained directly from the actual floating cover at the sewage treatment plant. Our recent research outcomes lead us towards conceptualising an advanced engineering analysis tool designed to support the future creation of a digital twin for the floating cover at the WTP. Foundational work demonstrates the effectiveness of an unmanned aerial vehicle (UAV)-based photogrammetry methodology in generating a digital elevation model of the large floating cover. A substantial set of data has been acquired through regular UAV flights, presenting opportunities to leverage this information for a deeper understanding of the interactions between operational conditions and the structural response of the floating cover. This paper discusses the current findings and their implications, clarifying how these outcomes contribute to the ongoing development of an advanced digital twin for the floating cover.

Arboviral diseases are serious threats to global health with increasing prevalence and potentially severe complications. Significant arthropod-borne viruses are the dengue viruses (DENV 1-4), the Zika virus (ZIKV), and the chikungunya virus (CHIKV). Among the areas most affected is the South Pacific Region (SPR). Here, arboviruses not only cause a high local burden of disease, but the region has also proven to contribute to their global spread. Outpatient serum samples collected between 08/2016 and 04/2017 on three islands of the island states of Vanuatu and the Cook Islands were tested for anti-DENV- and anti-ZIKV-specific antibodies (IgG) using enzyme-linked immunosorbent assays (ELISA). ELISA test results showed 89% of all test sera from the Cook Islands and 85% of the Vanuatu samples to be positive for anti-DENV-specific antibodies. Anti-ZIKV antibodies were identified in 66% and 52%, respectively, of the test populations. Statistically significant differences in standardized immunity levels were found only at the intranational level. Our results show that in both the Cook Islands and Vanuatu, residents were exposed to significant Flavivirus transmission. Compared to other seroprevalence studies, the marked difference between ZIKV immunity levels and previously published CHIKV seroprevalence rates in our study populations is surprising. We propose the timing of ZIKV and CHIKV emergence in relation to recurrent DENV outbreaks and the impact of seasonality as explanatory external factors for this observation. Our data add to the knowledge of arboviral epidemics in the SPR and contribute to a better understanding of virus spread, including external conditions with potential influence on outbreak dynamics. These data may support preventive and rapid response measures in the affected areas, travel-related risk assessment, and infection identification in locals and returning travelers.

This study aims to enhance diagnostic capabilities for optimising the performance of the anaerobic sewage treatment lagoon at Melbourne Water’s Western Treatment Plant (WTP) through a novel machine learning (ML)-based monitoring strategy. This strategy employs ML to make accurate probabilistic predictions of biogas performance by leveraging diverse real-life operational and inspection sensor and other measurement data for asset management, decision making, and structural health monitoring (SHM). The paper commences with data analysis and preprocessing of complex irregular datasets to facilitate efficient learning in an artificial neural network. Subsequently, a Bayesian mixture density neural network model incorporating an attention-based mechanism in bidirectional long short-term memory (BiLSTM) was developed. This probabilistic approach uses a distribution output layer based on the Gaussian mixture model and Monte Carlo (MC) dropout technique in estimating data and model uncertainties, respectively. Furthermore, systematic hyperparameter optimisation revealed that the optimised model achieved a negative log-likelihood (NLL) of 0.074, significantly outperforming other configurations. It achieved an accuracy approximately 9 times greater than the average model performance (NLL = 0.753) and 22 times greater than the worst performing model (NLL = 1.677). Key factors influencing the model’s accuracy, such as the input window size and the number of hidden units in the BiLSTM layer, were identified, while the number of neurons in the fully connected layer was found to have no significant impact on accuracy. Moreover, model calibration using the expected calibration error was performed to correct the model’s predictive uncertainty. The findings suggest that the inherent data significantly contribute to the overall uncertainty of the model, highlighting the need for more high-quality data to enhance learning. This study lays the groundwork for applying ML in transforming high-value assets into intelligent structures and has broader implications for ML in asset management, SHM applications, and renewable energy sectors.

This work provides an overview on micromirror arrays based on different material systems such as dielectrics, element silicon, compound semiconductors, metals, and novel 2D materials. The goal is to work out the particular strength of each material system to enable optimum performance for various applications. In particular, this review is intended to draw attention to the fact that MEMS micro-mirrors can be successful in many other material systems besides silicon. In particular, the review is intended to draw attention to two material systems that have so far been used less for MEMS micromirror arrays, that have been less researched, and of which fewer applications have been reported to date: metallic heterostructures and 2D materials. However, the main focus is on metallic MEMS micromirror arrays on glass substrates for applications like personalized light steering in buildings via active windows, energy management, active laser safety goggles, interference microscopy, and endoscopy. Finally, the different micromirror arrays are compared with respect to fabrication challenges, switching speed, number of mirrors, mirror dimensions, array sizes, miniaturization potential for individual mirrors, reliability, lifetime, and hinge methodology.

Highly reactive decomposition products of deuterated chloroform can deteriorate samples dissolved in this commonly used solvent for nuclear magnetic resonance (NMR) spectroscopy. Samples for metabolomics studies often contain a complex mixture of sensitive substances such as phospholipids, peptides, unsaturated fatty acids or vitamins. If these react with decomposition products (of chloroform), abnormal NMR spectra could result, e.g., signal shifts depending on pH, attenuation of signals over time due to chemical changes of analytes or new signals from reaction products. Such irreproducibly influenced spectra are especially problematic for non-targeted analysis methods using automated chemometrical data evaluation. To prevent these artefacts, chlorine, phosgene and hydrochloric acid need to be eliminated from deuterated chloroform before its use. Since the common stabilisation methods have proven to be insufficient for sensitive NMR samples, another purging method has been tested: Mitigation is easily and reliably achieved by washing the deuterated chloroform with concentrated disodium carbonate solution and subsequent desiccation with oven-dried disodium carbonate.

In various engineering applications, remote sensing images such as digital elevation models (DEMs) and orthomosaics provide a convenient means of generating 3D representations of physical assets, enabling the discovery of new insights and analyses. However, the presence of noise and artefacts, particularly unwanted natural features, poses significant challenges, and their removal requires the application of filtering techniques prior to conducting analysis. Unmanned aerial vehicle-based photogrammetry is used at Melbourne Water’s Western Treatment Plant as a cost-effective and efficient method of inspecting the floating covers on the anaerobic lagoons. The focus of interest is the elevation profile of the floating covers for these sewage-processing lagoons and its implications for sub-surface scum accumulation, which can compromise the structural integrity of the engineered assets. However, unwanted artefacts due to trapped rainwater, debris, dirt, and other irrelevant structures can significantly distort the elevation profile. In this study, a machine learning algorithm is utilised to group distinct features on the floating cover based on an image segmentation process. An unsupervised k-means clustering algorithm is employed, which operates on a stacked 4D array composed of the elevation of the DEM and the RGB channels of the associated orthomosaic. In the cluster validation process, seven cluster groups were considered optimal based on the Calinski–Harabasz criterion. Furthermore, by utilising the k-means method as a filtering technique, three clusters contain features related to the elevations associated with the floating cover membrane, collectively representing 84% of the asset, with each cluster contributing at least 19% of the asset. The artefact groups constitute less than 6% of the asset and exhibit significantly different features, colour characteristics, and statistical measurements from those of the membrane groups. The study found notable improvements using the k-means filtering method, including a 59.4% average reduction in outliers and a 36.3% decrease in standard deviation compared to raw data. Additionally, employing the proposed method in the scum hardness analysis improved correlation strength by 13.1%, removing approximately 16% of the artefacts in total assets, in contrast to a 3.6% improvement with the median filtering method. This improved imaging will lead to significant benefits when integrating imagery into deep learning models for structural health monitoring and asset performance.

As early as 1946, Felix Bloch and Edward Mills Purcell detected nuclear magnetic resonance signals, earning themselves the Nobel Prize in 1952. The same year saw the launch of the first commercial nuclear magnetic resonance (NMR) spectrometer. Since then, NMR has experienced significant progress in various fields of application. While in the 1970s NMR spectroscopy was solely employed for determining the structure and purity of synthesis products in the chemical field, it gradually gained popularity in the medical field for the investigation and rendering of images of human organs. Since then, the technique has developed significantly in terms of stability, reproducibility, and sensitivity, thereby forming the foundation for high-resolution imaging, the automation or standardization of analytical procedures, and the application of chemometric methods, particularly in relation to identifying food adulteration. This review objectively assesses the current state of implementing liquid NMR in the food, cosmetics, and pharmaceutical industries. Liquid NMR has transitioned from a structural elucidation tool to a widely recognized, multi-analytical method that incorporates multivariate techniques. The illustrations and sources provided aim to enhance novice readers’ understanding of this topic.

Martin C [...]

The roasting process is an important step in coffee production, leading to important physical and chemical changes that are responsible for the sensory quality of a coffee beverage. Besides the commonly used drum roasters, a newly developed infrared roaster can be used to roast green coffee beans. In this study, 1H nuclear magnetic resonance (NMR) spectroscopy was used to analyze the fat and aqueous extracts of coffee beans roasted to different degrees of roasting using a professional drum roaster, a hot air fluidized bed sample roaster and an infrared roaster. Caffeine-containing and decaffeinated Coffea arabica coffee samples were used to monitor the roasting process in the different roasters. Compared with the drum-roasted coffee sample, the formation and degradation of NMR-detectable components in the coffee sample roasted with the infrared roaster and the hot air roaster were time-dependent. In the decaffeinated coffee sample, compounds such as kahweol, caffeoylquinic acid and trigonelline were found to occur at lower levels. The formation and degradation of the NMR-detectable compounds in the decaffeinated coffee sample also occurred with a time lag or to a lesser extent than in the caffeine-containing coffee sample.

The mitochondrial amidoxime reducing component (mARC) is a human molybdoenzyme known to catalyze the reduction of various N-oxygenated substrates. The physiological function of mARC enzymes, however, remains unknown. In this study, we examine the reduction of hydrogen peroxide (H2O2) by the human mARC1 and mARC2 enzymes. Furthermore, we demonstrate an increased sensitivity toward H2O2 for HEK-293T cells with an MTARC1 knockout, which implies a role of mARC enzymes in the cellular response to oxidative stress. H2O2 is a reactive oxygen species (ROS) formed in all living cells involved in many physiological processes. Furthermore, H2O2 constitutes the first mARC substrate without a nitrogen–oxygen bond, implying that mARC enzymes may have a substrate spectrum going beyond the previously examined N-oxygenated compounds.

The importance of animal welfare and the organic production of chicken eggs has increased in the European Union in recent years. Legal regulation for organic husbandry makes the production of organic chicken eggs more expensive compared to conventional husbandry and thus increases the risk of food fraud. Therefore, the aim of this study was to develop a non-targeted lipidomic LC-ESI-IM-qToF-MS method based on 270 egg samples, which achieved a classification accuracy of 96.3%. Subsequently, surrogate minimal depth (SMD) was applied to select important variables identified as carotenoids and lipids based on their MS/MS spectra. The LC-MS results were compared with FT-NIR spectroscopy analysis as a low-resolution screening method and achieved 80.0% accuracy. Here, SMD selected parts of the spectrum which are associated with lipids and proteins. Furthermore, we used SMD for low-level data fusion to analyze relations between the variables of the LC-MS and the FT-NIR spectroscopy datasets. Thereby, lipid-associated bands of the FT-NIR spectrum were related to the identified lipids from the LC-MS analysis, demonstrating that FT-NIR spectroscopy partially provides similar information about the lipidome. In future applications, eggs can therefore be analyzed with FT-NIR spectroscopy to identify conspicuous samples that can subsequently be counter-tested by mass spectrometry.

Transcatheter aortic valve implantation (TAVI) is now a commonly used therapy in patients with severe aortic stenosis, even in those patients at low surgical risk. The indications for TAVI have broadened as the therapy has proven to be safe and effective. Most challenges associated with TAVI after its initial introduction have been impressively reduced; however, the possible need for post-TAVI permanent pacemaker implantation (PPI) secondary to conduction disturbances continues to be on the radar. Conduction abnormalities post-TAVI are always of concern given that the aortic valve lies in close proximity to critical components of the cardiac conduction system. This review will present a summary of noteworthy pre-and post-procedural conduction blocks, the best use of telemetry and ambulatory device monitoring to avoid unnecessary PPI or to recognize the need for late PPI due to delayed high-grade conduction blocks, predictors to identify those patients at greatest risk of requiring PPI, important CT measurements and considerations to optimize TAVI planning, and the utility of the MInimizing Depth According to the membranous Septum (MIDAS) technique and the cusp-overlap technique. It is stressed that careful membranous septal (MS) length measurement by MDCT during pre-TAVI planning is necessary to establish the optimal implantation depth before the procedure to reduce the risk of compression of the MS and consequent damage to the cardiac conduction system.

Aflatoxins are among the main carcinogens threatening food and feed safety while imposing major detection challenges to the agrifood industry. Today, aflatoxins are typically detected using destructive and sample-based chemical analysis that are not optimally suited to sense their local presence in the food chain. Therefore, we pursued the development of a non-destructive optical sensing technique based on fluorescence spectroscopy. We present a novel compact fluorescence sensing unit, comprising both ultraviolet excitation and fluorescence detection in a single handheld device. First, the sensing unit was benchmarked against a validated research-grade fluorescence setup and demonstrated high sensitivity by spectrally separating contaminated maize powder samples with aflatoxin concentrations of 6.6 µg/kg and 11.6 µg/kg. Next, we successfully classified a batch of naturally contaminated maize kernels within three subsamples showing a total aflatoxin concentration of 0 µg/kg, 0.6 µg/kg and 1647.8 µg/kg. Consequently, our novel sensing methodology presents good sensitivity and high potential for integration along the food chain, paving the way toward improved food safety.

Interleukin 10 (IL-10) exerts anti-inflammatory and immune regulatory roles through its fixation to the IL-10 receptor (IL-10R). The two subunits (IL-10Rα and IL-10Rβ) organise themselves to form a hetero-tetramer to induce the activation of the transcription factor STAT3. We analysed the activation patterns of the IL-10R, especially the contribution of the transmembrane (TM) domain of the IL-10Rα and IL-10Rβ subunits, as evidence accumulates that this short domain has tremendous implications in receptor oligomerisation and activation. We also addressed whether targeting the TM domain of IL-10R with peptides mimicking the TM sequences of the subunits translates into biological consequences. The results illustrate the involvement of the TM domains from both subunits in receptor activation and feature a distinctive amino acid crucial for the interaction. The TM peptide targeting approach also appears to be suitable for modulating the activation of the receptor through its action on the dimerization capabilities of the TM domains and thereby constitutes a potential new strategy for the modulation of the inflammation in pathologic contexts.

Elongation of the posterior body axis is distinct from that of the anterior trunk and head. Early drivers of posterior elongation are the neural plate/tube and notochord, later followed by the presomitic mesoderm (PSM), together with the neural tube and notochord. In axolotl, posterior neural plate-derived PSM is pushed posteriorly by convergence and extension of the neural plate. The PSM does not go through the blastopore but turns anteriorly to join the gastrulated paraxial mesoderm. To gain a deeper understanding of the process of axial elongation, a detailed characterization of PSM morphogenesis, which precedes somite formation, and of other tissues (such as the epidermis, lateral plate mesoderm and endoderm) is needed. We investigated these issues with specific tissue labelling techniques (DiI injections and GFP+ tissue grafting) in combination with optical tissue clearing and 3D reconstructions. We defined a spatiotemporal order of PSM morphogenesis that is characterized by changes in collective cell behaviour. The PSM forms a cohesive tissue strand and largely retains this cohesiveness even after epidermis removal. We show that during embryogenesis, the PSM, as well as the lateral plate and endoderm move anteriorly, while the net movement of the axis is posterior.

An improved moveable in vacuo XUV fluorescence detection system was employed for the laser cooling of bunched relativistic (β = 0.47) carbon ions at the Experimental Storage Ring (ESR) of GSI Helmholtzzentrum Darmstadt, Germany. Strongly Doppler boosted XUV fluorescence (∼90 nm) was emitted from the ions in a forward light cone after laser excitation of the 2s–2p transition (∼155 nm) by a new tunable pulsed UV laser system (257 nm). It was shown that the detected fluorescence strongly depends on the position of the detector around the bunched ion beam and on the delay (∼ns) between the ion bunches and the laser pulses. In addition, the fluorescence information could be directly combined with the revolution frequencies of the ions (and their longitudinal momentum spread), which were recorded using the Schottky resonator at the ESR. These fluorescence detection features are required for future laser cooling experiments at highly relativistic energies (up to γ∼ 13) and high intensities (up to 1011 particles) of ion beams in the new heavy ion synchrotron SIS100 at FAIR.

Plasma wakefield accelerators can be driven either by intense laser pulses (LWFA) or by intense particle beams (PWFA). A third approach that combines the complementary advantages of both types of plasma wakefield accelerator has been established with increasing success over the last decade and is called hybrid LWFA→PWFA. Essentially, a compact LWFA is exploited to produce an energetic, high-current electron beam as a driver for a subsequent PWFA stage, which, in turn, is exploited for phase-constant, inherently laser-synchronized, quasi-static acceleration over extended acceleration lengths. The sum is greater than its parts: the approach not only provides a compact, cost-effective alternative to linac-driven PWFA for exploitation of PWFA and its advantages for acceleration and high-brightness beam generation, but extends the parameter range accessible for PWFA and, through the added benefit of co-location of inherently synchronized laser pulses, enables high-precision pump/probing, injection, seeding and unique experimental constellations, e.g., for beam coordination and collision experiments. We report on the accelerating progress of the approach achieved in a series of collaborative experiments and discuss future prospects and potential impact.

Ticks are important vectors for Rickettsia spp. belonging to the Spotted Fever Group responsible for causing Rickettsiosis worldwide. Rickettsioses pose an underestimated health risk to tourists and local inhabitants. There is evidence of the presence of Rickettsia spp. in Zambia, however there is limited data. A total of 1465 ticks were collected in 20 different locations from dogs and cattle including one cat. Ticks were identified by morphological features or by sequencing of the 16S mitochondrial rRNA gene. Individual ticks were further tested for rickettsiae using a pan-Rickettsia real-time-PCR. Rickettsia species in PCR-positive ticks were identified by sequencing the 23S-5S intergenic spacer region or partial ompA gene, respectively. Seven tick species belonging to three different tick genera were found, namely: Amblyomma variegatum, Rhipicephalus appendiculatus, Rhipicephalus (Boophilus) microplus, Rhipicephalus simus, Rhipicephalus sanguineus, Rhipicephalus zambesiensis and Haemaphysalis elliptica. Out of the 1465 ticks collected, 67 (4.6%) tested positive in the pan-Rickettsia PCR. This study provides detailed data about the presence of Rickettsia species in South Luangwa Valley, Eastern Province, Zambia for the first time. High prevalence of Rickettsia africae in Amblyomma variegatum was found, which indicates the potential risk of infection in the investigated area. Furthermore, to our best knowledge, this is the first time Rickettsia massiliae, a human pathogen causing spotted fever, has been detected in Zambia.

To address the continued rise of multi-drug-resistant microorganisms, the development of novel drugs with new modes of action is urgently required. While humans biosynthesize the essential isoprenoid precursors isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP) via the established mevalonate pathway, pathogenic protozoa and certain pathogenic eubacteria use the less well-known methylerythritol phosphate pathway for this purpose. Important pathogens using the MEP pathway are, for example, Plasmodium falciparum, Mycobacterium tuberculosis, Pseudomonas aeruginosa and Escherichia coli. The enzymes of that pathway are targets for antiinfective drugs that are exempt from target-related toxicity. 2C-Methyl-D-erythritol 4-phosphate (MEP), the second enzyme of the non-mevalonate pathway, has been established as the molecular target of fosmidomycin, an antibiotic that has so far failed to be approved as an anti-infective drug. This review describes the development and anti-infective properties of a wide range of fosmidomycin derivatives synthesized over the last four decades. Here we discuss the DXR inhibitor pharmacophore, which comprises a metal-binding group, a phosphate or phosphonate moiety and a connecting linker. Furthermore, non-fosmidomycin-based DXRi, bisubstrate inhibitors and several prodrug concepts are described. A comprehensive structure–activity relationship (SAR) of nearly all inhibitor types is presented and some novel opportunities for further drug development of DXR inhibitors are discussed.

The study evaluates the performance of laboratory, single-layered particleboards made out of fructose-hydroxymethylfurfural-bishexamethylenetriamine (SusB) adhesive as a sustainable alternative. Several production parameters such as mat moisture content (MMC), adhesive amount and press time were varied and their effect on the bonding efficiency investigated. The internal bond strength (IB) and thickness swelling after 24 h of water immersion (TS) were taken as evaluation criteria for the bonding efficiency. pMDI-bonded particleboards were produced as fossil-based, formaldehyde-free reference. Particleboard testing was complemented by tensile shear strength measurements and thermal analysis. It was found that the MMC has the highest impact on the internal bond strength of SusB-bonded particleboards. In the presence of water, the reaction enthalpy of the main curing reaction (occurring at 117.7 °C) drops from 371.9 J/mol to 270.5 J/mol, leading to side reactions. By reducing the MMC from 8.7%, the IB increases to 0.61 N/mm2, thus surpassing P2 requirements of the European standard EN312. At a press factor of 10 s/mm, SusB-bonded particleboards have a similar IB strength as pMDI-bonded ones, with 0.59 ± 0.12 N/mm2 compared to 0.59 ± 0.09 N/mm2. Further research on the improvement of the dimensional stabilization of SusB-bonded PBs is needed, as the TS ranges from 30–40%.

Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system associated with chronic inflammation, demyelination, and axonal damage. MS is a highly heterogeneous disease that leads to discrepancies regarding the clinical appearance, progression, and therapy response of patients. Therefore, there is a strong unmet need for clinically relevant biomarkers capable of recapitulating the features of the disease. Experimental autoimmune encephalomyelitis (EAE) is a valuable model for studying the pathophysiology of MS as it recapitulates the main hallmarks of the disease: inflammation, blood-brain barrier (BBB) disruption, gliosis, myelin damage, and repair mechanisms. In this study, we used the EAE-PLP animal model and established a molecular RNA signature for each phase of the disease (onset, peak, remission). We compared variances of expression of known biomarkers by RT-qPCR in the brain and spinal cord of sham and EAE animals monitoring each of the five hallmarks of the disease. Using magnetic cell isolation technology, we isolated microglia and oligodendrocytes of mice of each category, and we compared the RNA expression variations. We identify genes deregulated during a restricted time frame, and we provide insight into the timing and interrelationships of pathological disease processes at the organ and cell levels.

The treatment of leukemias, especially acute myeloid leukemia (AML), is still a challenge as can be seen by poor 5-year survival of AML. Therefore, new therapeutic approaches are needed to increase the treatment success. Epigenetic aberrations play a role in pathogenesis and resistance of leukemia. Histone deacetylase (HDAC) inhibitors (HDACIs) can normalize epigenetic disbalance by affecting gene expression. In order to decrease side effects of so far mainly used pan-HDACIs, this paper introduces the novel highly selective class IIa HDACI YAK540. A synergistic cytotoxic effect was observed between YAK540 and the proteasome inhibitor bortezomib (BTZ) as analyzed by the Chou-Talalay method. The combination of YAK540 and BTZ showed generally increased proapoptotic gene expression, increased p21 expression, and synergistic, caspase 3/7-mediated apoptosis. Notably, the cytotoxicity of YAK540 is much lower than that of pan-HDACIs. Further, combinations of YAK540 and BTZ are clearly less toxic in non-cancer HEK293 compared to HL-60 leukemia cells. Thus, the synergistic combination of class IIa selective HDACIs such as YAK540 and proteasome inhibitors represents a promising approach against leukemias to increase the anticancer effect and to reduce the general toxicity of HDACIs.

Unmanned aerial vehicle (UAV) assisted photogrammetry has been used to perform a non-contact measurement of the covers on the anaerobic wastewater lagoons at Melbourne Water Corporation’s Western Treatment Plant (WTP). These floating covers are valuable assets that eliminate odour and greenhouse gas emissions and harvest the methane-rich biogas as a renewable resource to generate electricity. Hence, the state of deformation of the floating covers becomes an important engineering factor for structural integrity assessment. UAVs have been deployed to scan these covers and photogrammetry has been used to process the aerial images to construct the floating covers’ orthophoto and digital elevation model (DEM). This paper proposes to adopt the finite element formulation to improve the quantification of the in-plane movement of a floating cover. Distinguishable features on the floating cover are first identified and their (x, y and z) coordinates are recorded over time. The results show that the technique can be used to quantify the short-term and long-term relative global lateral movement of the floating covers at WTP. More importantly, the results not only highlight the usefulness of this analysis for the integrity management of the floating cover but also show the value of clearly defined markers on the floating cover to facilitate the calculation of the cover’s state of strain.

Besides tremendous treatment success in advanced melanoma patients, the rapid development of oncologic treatment options comes with increasingly high costs and can cause severe life-threatening side effects. For this purpose, predictive baseline biomarkers are becoming increasingly important for risk stratification and personalized treatment planning. Thus, the aim of this pilot study was the development of a prognostic tool for the risk stratification of the treatment response and mortality based on PET/MRI and PET/CT, including a convolutional neural network (CNN) for metastasized-melanoma patients before systemic-treatment initiation. The evaluation was based on 37 patients (19 f, 62 ± 13 y/o) with unresectable metastasized melanomas who underwent whole-body 18F-FDG PET/MRI and PET/CT scans on the same day before the initiation of therapy with checkpoint inhibitors and/or BRAF/MEK inhibitors. The overall survival (OS), therapy response, metastatically involved organs, number of lesions, total lesion glycolysis, total metabolic tumor volume (TMTV), peak standardized uptake value (SULpeak), diameter (Dmlesion) and mean apparent diffusion coefficient (ADCmean) were assessed. For each marker, a Kaplan–Meier analysis and the statistical significance (Wilcoxon test, paired t-test and Bonferroni correction) were assessed. Patients were divided into high- and low-risk groups depending on the OS and treatment response. The CNN segmentation and prediction utilized multimodality imaging data for a complementary in-depth risk analysis per patient. The following parameters correlated with longer OS: a TMTV < 50 mL; no metastases in the brain, bone, liver, spleen or pleura; ≤4 affected organ regions; no metastases; a Dmlesion > 37 mm or SULpeak < 1.3; a range of the ADCmean < 600 mm2/s. However, none of the parameters correlated significantly with the stratification of the patients into the high- or low-risk groups. For the CNN, the sensitivity, specificity, PPV and accuracy were 92%, 96%, 92% and 95%, respectively. Imaging biomarkers such as the metastatic involvement of specific organs, a high tumor burden, the presence of at least one large lesion or a high range of intermetastatic diffusivity were negative predictors for the OS, but the identification of high-risk patients was not feasible with the handcrafted parameters. In contrast, the proposed CNN supplied risk stratification with high specificity and sensitivity.

The continuous, worldwide spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) endanger the World Health Organization’s (WHO) goal to end the global TB pandemic by the year 2035. During the past 50 years, very few new drugs have been approved by medical agencies to treat drug-resistant TB. Therefore, the development of novel antimycobacterial drug candidates to combat the threat of drug-resistant TB is urgent. In this work, we developed and optimized a total synthesis of the antimycobacterial natural flavonoid chlorflavonin by selective ruthenium(II)-catalyzed ortho-C(sp2)-H-hydroxylation of a substituted 3′-methoxyflavonoid skeleton. We extended our methodology to synthesize a small compound library of 14 structural analogs. The new analogs were tested for their antimycobacterial in vitro activity against Mycobacterium tuberculosis (Mtb) and their cytotoxicity against various human cell lines. The most promising new analog bromflavonin exhibited improved antimycobacterial in vitro activity against the virulent H37Rv strain of Mtb (Minimal Inhibitory Concentrations (MIC90) = 0.78 μm). In addition, we determined the chemical and metabolic stability as well as the pKa values of chlorflavonin and bromflavonin. Furthermore, we established a quantitative structure–activity relationship model using a thermodynamic integration approach. Our computations may be used for suggesting further structural changes to develop improved derivatives.

Thin-walled features can be difficult to produce with traditional machining methods which often rely on excess stock material for stiffness. This challenge is increased in hybrid manufacturing where the feature is already near net shape before machining. Significant workpiece deflection can result in poor geometric and surface finish tolerances on the finished part. A potential solution to this problem is to implement sacrificial support structures to the as-printed geometry. The supports are then machined away during the finishing portion of the hybrid process. In the present work, several different design parameters for these sacrificial supports were evaluated to determine their impact on the quality of representative thin wall geometry samples. The angle, height, and spacing of triangular support structures were varied for each sample and then machined and examined. The addition of these supports relative to an unsupported configuration provided a deflection reduction of around 0.2 mm. Surface roughness was improved by approximately 1.5 µm. Increasing values of support height were found to correspond to reduced wall deflection. Similarly, decreasing values of support angle and support spacing improved geometric accuracy. Efficiency comparisons showed that increases in print time corresponded to rapidly diminishing gains in geometric accuracy but continued to improve surface roughness. Implications for hybrid finishing of additively manufactured thin-walled structures is briefly discussed.

Hypomyelinating leukodystrophies (HLDs) are a rare group of heterogeneously genetic disorders characterized by persistent deficit of myelin observed on magnetic resonance imaging (MRI). To identify a new disease-associated gene of HLD, trio-based whole exome sequencing was performed for unexplained patients with HLD. Functional studies were performed to confirm the phenotypic effect of candidate protein variants. Two de novo heterozygous variants, c.227T>G p.(L76R) or c.227T>C p.(L76P) in TMEM163 were identified in two unrelated HLD patients. TMEM163 protein is a zinc efflux transporter localized within the plasma membrane, lysosomes, early endosomes, and other vesicular compartments. It has not been associated with hypomyelination. Functional zinc flux assays in HeLa cells stably-expressing TMEM163 protein variants, L76R and L76P, revealed distinct attenuation or enhancement of zinc efflux, respectively. Experiments using a zebrafish model with knockdown of tmem163a and tmem163b (morphants) showed that loss of tmem163 causes dysplasia of the larvae, locomotor disability and myelin deficit. Expression of human wild type TMEM163 mRNAs in morphants rescues the phenotype, while the TMEM163 L76P and L76R mutants aggravated the condition. Moreover, poor proliferation, elevated apoptosis of oligodendrocytes, and reduced oligodendrocytes and neurons were also observed in zebrafish morphants. Our findings suggest an unappreciated role for TMEM163 protein in myelin development and add TMEM163 to a growing list of genes associated with hypomyelination leukodystrophy.

A new method is proposed in this paper to detect airborne nanoparticles, detecting the light scattering caused by both the particle and the surrounding molecules, which can surpass the limitations of conventional laser optical methods while maintaining simplicity and cost-effectiveness. This method is derived from a mathematical analysis that describes the particle light scattering phenomenon more exactly by including the influence of light scattered from surrounding gas molecules. The analysis shows that it is often too much of a simplification to consider only light scattering from the detected nanoparticle, because light scattering from the surrounding gas molecules, whether visible or invisible to the sensor, is important for nanoparticle detection. An image detection approach utilizing the light scattering from surrounding air molecules is described for the detection of airborne nanoparticles. Tests using monodisperse nanoparticles confirm that airborne particles of around 50 nm in size can even be detected using a low-cost testing device. This shows further that even when using a simple image processing code, captured particle light scattering images can be converted digitally into instantaneous particle counts or concentrations. The factors limiting conventional pulse detection are further discussed. This new method utilizes a simple static light scattering (SLS) approach to enable the development of new devices with better detection capabilities, paving the way for the further development of nanoparticle detection technology.

As a widely distributed parasitic nematode of ruminants, Haemonchus contortus has become resistant to most anthelmintic classes, there has been a major demand for new compounds against H. contortus and related nematodes. Recent phenotypic screening has revealed two compounds, designated as BLK127 and HBK4, that are active against H. contortus larvae. The present study was designed to assess the activity of these compounds against H. contortus eggs and adults, hepatotoxicity in rats and sheep, as well as biotransformation in H. contortus adults and the ovine liver. Both compounds exhibited no inhibitory effect on the hatching of eggs. The benzyloxy amide BLK127 significantly decreased the viability of adults in sensitive and resistant strains of H. contortus and showed no hepatotoxic effect, even at the highest concentration tested (100 µM). In contrast, HBK4 had no impact on the viability of H. contortus adults and exhibited significant hepatotoxicity. Based on these findings, HBK4 was excluded from further studies, while BLK127 seems to be a potential candidate for a new anthelmintic. Consequently, biotransformation of BLK127 was tested in H. contortus adults and the ovine liver. In H. contortus, several metabolites formed via hydroxylation, hydrolysis and glycosidation were identified, but the extent of biotransformation was low, and the total quantity of the metabolites formed did not differ significantly between the sensitive and resistant strains. In contrast, ovine liver cells metabolized BLK127 more extensively with a glycine conjugate of 4-(pentyloxy)benzoic acid as the main BLK127 metabolite.

Oncostatin M (OSM), a member of the interleukin-6 family, functions as a major mediator of cardiomyocyte remodeling under pathological conditions. Its involvement in a variety of human cardiac diseases such as aortic stenosis, myocardial infarction, myocarditis, cardiac sarcoidosis, and various cardiomyopathies make the OSM receptor (OSMR) signaling cascades a promising therapeutic target. However, the development of pharmacological treatment strategies is highly challenging for many reasons. In mouse models of heart disease, OSM elicits opposing effects via activation of the type II receptor complex (OSMR/gp130). Short-term activation of OSMR/gp130 protects the heart after acute injury, whereas chronic activation promotes the development of heart failure. Furthermore, OSM has the ability to integrate signals from unrelated receptors that enhance fetal remodeling (dedifferentiation) of adult cardiomyocytes. Because OSM strongly stimulates the production and secretion of extracellular proteins, it is likely to exert systemic effects, which in turn, could influence cardiac remodeling. Compared with the mouse, the complexity of OSM signaling is even greater in humans because this cytokine also activates the type I leukemia inhibitory factor receptor complex (LIFR/gp130). In this article, we provide an overview of OSM-induced cardiomyocyte remodeling and discuss the consequences of OSMR/gp130 and LIFR/gp130 activation under acute and chronic conditions.

The functional contribution of transient receptor potential vanilloid 4 (TRPV4) expression in maintaining human corneal endothelial cells (HCEC) homeostasis is unclear. Accordingly, we determined the effects of TRPV4 gene and protein overexpression on responses modulating the viability and survival of HCEC. Q-PCR, Western blot, FACS analyses and fluorescence single-cell calcium imaging confirmed TRPV4 gene and protein overexpression in lentivirally transduced 12V4 cells derived from their parent HCEC-12 line. Although TRPV4 overexpression did not alter the baseline transendothelial electrical resistance (TEER), its cellular capacitance (Ccl) was larger than that in its parent. Scanning electron microscopy revealed that only the 12V4 cells developed densely packed villus-like protrusions. Stimulation of TRPV4 activity with GSK1016790A (GSK101, 10 µmol/L) induced larger Ca2+ transients in the 12V4 cells than those in the parental HCEC-12. One to ten nmol/L GSK101 decreased 12V4 viability, increased cell death rates and reduced the TEER, whereas 1 µmol/L GSK101 was required to induce similar effects in the HCEC-12. However, the TRPV4 channel blocker RN1734 (1 to 30 µmol/L) failed to alter HCEC-12 and 12V4 morphology, cell viability and metabolic activity. Taken together, TRPV4 overexpression altered both the HCEC morphology and markedly lowered the GSK101 dosages required to stimulate its channel activity.

Macrophages and microglia are implicated in several diseases with divergent roles in physiopathology. This discrepancy can be explained by their capacity to endorse different polarization states. Theoretical extremes of these states are called M1 and M2. M1 are pro-inflammatory, microbicidal, and cytotoxic whereas M2 are anti-inflammatory, immunoregulatory cells in favor of tumor progression. In pathological states, these polarizations are dysregulated, thus restoring phenotypes could be an interesting treatment approach against diseases. In this review, we will focus on compounds targeting macrophages and microglia polarization in two very distinctive pathologies: multiple sclerosis and glioblastoma. Multiple sclerosis is an inflammatory disease characterized by demyelination and axon degradation. In this case, macrophages and microglia endorse a M1-like phenotype inducing inflammation. Promoting the opposite M2-like polarization could be an interesting treatment strategy. Glioblastoma is a brain tumor in which macrophages and microglia facilitate tumor progression, spreading, and angiogenesis. They are part of the tumor associated macrophages displaying an anti-inflammatory phenotype, thereby inhibiting anti-tumoral immunity. Re-activating them could be a method to limit and reduce tumor progression. These two pathologies will be used to exemplify that targeting the polarization of macrophages and microglia is a promising approach with a broad spectrum of applications deserving more attention.

Prostate cancer (PCa) is the most frequent malignancy in older men with a high propensity for bone metastases. Characteristically, PCa causes osteosclerotic lesions as a result of disrupted bone remodeling. Extracellular vesicles (EVs) participate in PCa progression by conditioning the pre-metastatic niche. However, how EVs mediate the cross-talk between PCa cells and osteoprogenitors in the bone microenvironment remains poorly understood. We found that EVs derived from murine PCa cell line RM1-BM increased metabolic activity, vitality, and cell proliferation of osteoblast precursors by >60%, while significantly impairing mineral deposition (−37%). The latter was further confirmed in two complementary in vivo models of ossification. Accordingly, gene and protein set enrichments of osteoprogenitors exposed to EVs displayed significant downregulation of osteogenic markers and upregulation of proinflammatory factors. Additionally, transcriptomic profiling of PCa-EVs revealed the abundance of three microRNAs, miR-26a-5p, miR-27a-3p, and miR-30e-5p involved in the suppression of BMP-2-induced osteogenesis in vivo, suggesting the critical role of these EV-derived miRNAs in PCa-mediated suppression of osteoblast activity. Taken together, our results indicate the importance of EV cargo in cancer-bone cross-talk in vitro and in vivo and suggest that exosomal miRNAs may contribute to the onset of osteosclerotic bone lesions in PCa.

Large sheets of high-density polyethene geomembrane are used as floating covers on some of the wastewater treatment lagoons at the Melbourne Water Corporation’s Western Treatment Plant. These covers provide an airtight seal for the anaerobic digestion of sewage and allow for harvesting the methane-rich biogas, which is then used to generate electricity. There is a potential for scum to develop under the covers during the anaerobic digestion of the raw sewage by microorganisms. Due to the nature of the operating environment of the lagoons and the vast size (450 m × 170 m) of these covers, a safe non-contact method to monitor the development and movement of the scum is preferred. This paper explores the potential of using a new thermographic approach to identify and monitor the scum under the covers. The approach exploits naturally occurring variations in solar intensity as a trigger for generating a transient thermal response that is then fitted to an exponential decay law to determine a cooling constant. This approach is investigated experimentally using a laboratory-scale test rig. A finite element (FE) model is constructed and shown to reliably predict the experimentally observed thermal transients and cooling constants. This FE model is then set up to simulate progressive scum accumulation with time, using a specified scumberg geometry and a stepwise change in thermal properties. The results indicate a detectable change in the cooling constant at different locations on the cover, thereby providing a quantitative basis for characterising the scum accumulation beneath the cover. The practical application and limitations of these results are briefly discussed.

Deep learning technologies and applications demonstrate one of the most important upcoming developments in radiology. The impact and influence of these technologies on image acquisition and reporting might change daily clinical practice. The aim of this review was to present current deep learning technologies, with a focus on magnetic resonance image reconstruction. The first part of this manuscript concentrates on the basic technical principles that are necessary for deep learning image reconstruction. The second part highlights the translation of these techniques into clinical practice. The third part outlines the different aspects of image reconstruction techniques, and presents a review of the current literature regarding image reconstruction and image post-processing in MRI. The promising results of the most recent studies indicate that deep learning will be a major player in radiology in the upcoming years. Apart from decision and diagnosis support, the major advantages of deep learning magnetic resonance imaging reconstruction techniques are related to acquisition time reduction and the improvement of image quality. The implementation of these techniques may be the solution for the alleviation of limited scanner availability via workflow acceleration. It can be assumed that this disruptive technology will change daily routines and workflows permanently.

Optical interferometric sensors have acquired significant importance in metrology and information technology, especially in terms of their potential application in launching size, selectivity, sensitivity, resolution, spectral tuning ranges, efficiency, and cost. However, these demands are often contradictory and counteract one another, and are thus difficult to simultaneously fulfill during their interaction. This review focuses on a detailed comparison of seven different strongly miniaturized sensor concepts investigating the limits of these demands. For the visible and near-infrared spectral range, seven optical sensors were reviewed based on the following methodologies: classical optical transmission and reflection gratings, arrayed waveguide gratings, static Fabry–Pérot (FP) filter arrays, MEMS tunable FP interferometers, MEMS tunable photonic crystals, plasmonic filters, and fiber tip sensors. The comparison between the selected concepts concentrates on (i) the minimum space required for a particular spectral range, (ii) resolution, (iii) the integration in optical fiber technology, (iv) tunability to save space, (v) efficiency in using available light, (vi) multiplexing, (vii) miniaturization limits, and (viii) the potential of nanoimprint for cost reduction. Technologies for enhancing efficiency to obtain more available light and their applicability to the different methodologies were studied.

Hybrid manufacturing machine tools have great potential to revolutionize manufacturing by combining both additive manufacturing (AM) and subtractive manufacturing (SM) processes on the same machine tool. A prominent issue that can occur when going from AM to SM is that the SM process toolpath does not account for geometric discrepancies caused by the previous AM step, which leads to increased production times and tool wear, particularly when wire-based directed energy deposition (DED) is used as the AM process. This work discusses a methodology for approximating a part’s surface topology using on-machine contact probing and formulating an optimized SM toolpath using the surface topology approximation. Three different geometric surface approximations were used: triangular, trapezoidal, and a hybrid of both. SM toolpaths were created using each geometric approximation and assessed according to three objectives: reducing total machining time, reducing surface roughness, and reducing cutting force. Different prioritization scenarios of the optimization goals were also investigated. The optimal surface approximation that yielded the most improvement in the optimization was determined to be the hybrid surface topology approximation. Furthermore, it was shown that when the machining time or cutting force optimization goals were prioritized, there was little improvement in the other optimization goals.

High-density polyethylene geomembranes are employed as covers for the sewage treatment lagoons at Melbourne Water Corporation’s Western Treatment Plant, to harvest the biogas produced during anaerobic degradation, which is then used to generate electricity. Due to its size, inspecting the cover for defects, particularly subsurface defects, can be challenging, as well as the potential for the underside of the membrane to come into contact with different substrates, viz. liquid sewage, scum (consolidated solid matter), and biogas. This paper presents the application of a novel quasi-active thermography inspection method for subsurface defect detection in the geomembrane. The proposed approach utilises ambient sunlight as the input thermal energy and cloud shading as the trigger for thermal transients. Outdoor laboratory-scale experiments were conducted to study the proposed inspection technique. A pyranometer was used to measure the intensity of solar radiation, and an infrared thermal camera was used to measure the surface temperature of the geomembrane. The measured temperature profile was analysed using three different algorithms for thermal transient analysis, based on (i) the cooling constant from Newton’s law of cooling, (ii) the peak value of the logarithmic second derivative, and (iii) a frame subtraction method. The outcomes from each algorithm were examined and compared. The results show that, while each algorithm has some limitations, when used in combination the three algorithms could be used to distinguish between different substrates and to determine the presence of subsurface defects.

Magnetic Resonance Imaging (MRI) of the musculoskeletal system is one of the most common examinations in clinical routine. The application of Deep Learning (DL) reconstruction for MRI is increasingly gaining attention due to its potential to improve the image quality and reduce the acquisition time simultaneously. However, the technology has not yet been implemented in clinical routine for turbo spin echo (TSE) sequences in musculoskeletal imaging. The aim of this study was therefore to assess the technical feasibility and evaluate the image quality. Sixty examinations of knee, hip, ankle, shoulder, hand, and lumbar spine in healthy volunteers at 3 T were included in this prospective, internal-review-board-approved study. Conventional (TSES) and DL-based TSE sequences (TSEDL) were compared regarding image quality, anatomical structures, and diagnostic confidence. Overall image quality was rated to be excellent, with a significant improvement in edge sharpness and reduced noise compared to TSES (p < 0.001). No difference was found concerning the extent of artifacts, the delineation of anatomical structures, and the diagnostic confidence comparing TSES and TSEDL (p > 0.05). Therefore, DL image reconstruction for TSE sequences in MSK imaging is feasible, enabling a remarkable time saving (up to 75%), whilst maintaining excellent image quality and diagnostic confidence.

Coffee silver skin is produced in large amounts as a by-product during the coffee roasting process. In this study, coffee silver skin of the species Coffea arabica L. and Coffea canephora Pierre ex A. Froehner as well as silver skin pellets produced in the coffee industry were characterized with respect to both nutritional value and potential heat-induced contaminants. Enzymatic-gravimetric/chromatographic determination of the dietary fiber content showed values ranging from 59 to 67 g/100 g with a comparably high portion of soluble fiber, whereas low molecular weight soluble fiber was not detected. Compositional and methylation analysis indicated the presence of cellulose and xylans in the insoluble dietary fiber fraction, whereas pectic polysaccharides dominate the soluble dietary fiber fraction. The protein content as determined by the Kjeldahl method was in the range of 18 to 22 g/100 g, and all essential amino acids were present in coffee silver skin; whereas fat contents were low, high ash contents were determined. Elemental analysis by inductively coupled plasma mass spectrometry (ICP-MS) showed the presence of macroelements in large amounts, whereas toxic mineral elements were only detected in trace amounts or being absent. Acrylamide was quantified with levels of 24–161 µg/kg. Although 5-hydroxymethylfurfural was detected, its concentration was below the limit of determination. Furfuryl alcohol was not detected.

In 2006, the BGR signed a contract with the International Seabed Authority (ISA) for the exploration of polymetallic nodules in the Clarion-Clipperton Zone of the northeast Pacific. During nine expeditions, in particular, “Area E1”, the eastern part of the contract area, with a size of ~60,000 km2, was explored in detail. Here, we outline BGR’s exploration methods and provide resource estimates for Area E1 and three sub-areas. The resource assessment is predominantly based on statistical analyses of data obtained by 12-kHz multibeam bathymetry and backscatter mapping, box core sampling and geochemical analysis of nodules. The main parameter for the assessment is the nodule abundance (kg/m2), as its coefficient of variation (CoV) over the entire eastern contract area is relatively high at 36%. In contrast, the metal contents of nodules show only minor variation, with a CoV of 8% for manganese and 8% for the sum of copper, nickel and cobalt. To estimate mineral resources for the entire Area E1, we used an artificial neural network approach with a multivariate statistical correlation between nodule abundance derived from box cores and hydro-acoustic data. The total estimated resources are 540 ± 189 million tonnes (Mt) of dry nodules, and the total estimated metal contents are 168 Mt of manganese, 7.5 Mt of nickel, 6.3 Mt of copper, 0.9 Mt of cobalt, 0.4 Mt of rare-earth elements and 0.3 Mt of molybdenum. A geostatistical resource estimate of three economically prospective areas with a total size of 4498 km2, intensively sampled by box cores, was carried out using ordinary kriging of nodule abundance and metal grades. Within these three nodule fields, 7.14 Mt of dry nodules are classified as measured mineral resources covering an area of 489 km2. Indicated mineral resources amount to 11.2 Mt, covering an area of 825 km2, and inferred mineral resources of 35.5 Mt of dry nodules were estimated for an area of 3184 km2. In total, the metal contents of the three prospective areas amount to 16.8 Mt of manganese, 0.74 Mt of nickel, 0.63 Mt of copper and 0.09 Mt of cobalt.

Toxicologically relevant levels of the psychoactive ∆9-tetrahydocannabinol (∆9-THC) as well as high levels of non-psychoactive cannabinoids potentially occur in CBD (cannabidiol) oils. For consumer protection in the fast-growing CBD oil market, facile and rapid quantitative methods to determine the cannabinoid content are crucial. However, the current standard method, i.e., liquid chromatography combined with tandem mass spectrometry (HPLC-MS/MS), requires a time-consuming multistep sample preparation. In this study, a quantitative nuclear magnetic resonance spectroscopy (qNMR) method for screening cannabinoids in CBD oils was developed. Contrary to the HPLC-MS/MS method, this qNMR features a simple sample preparation, i.e., only diluting the CBD oil in deuterochloroform. Pulse length-based concentration determination (PULCON) enables a direct quantification using an external standard. The signal intensities of the cannabinoids were enhanced during the NMR spectra acquisition by means of multiple suppression of the triglycerides which are a major component of the CBD oil matrix. The validation confirmed linearity for CBD, cannabinol (CBN), ∆9-THC and ∆8-THC in hemp seed oil with sufficient recoveries and precision for screening. Comparing the qNMR results to HPLC-MS/MS data for 46 commercial CBD oils verified the qNMR accuracy for ∆9-THC and CBD, but with higher limits of detection. The developed qNMR method paves the way for increasing the sample throughput as a complementary screening before HPLC-MS/MS.

Obesity, as a major risk factor of metabolic syndrome (MetS), represents a pandemic, especially in Western societies, and is considered a risk factor for malignancies. Helicobacter pylori (Hp), is a definite carcinogen with global distribution. We aimed to investigate, for the first time in Switzerland, the main gastric mucosa premalignant histological lesions of bariatric patients in correlation with MetS components and Hp Infection (Hp-I). By reviewing retrospectively 94304 patient cases, a total of 116 eligible patients having undergone bariatric surgery were identified. The mean patient age was 48.66 years. Hp(+) patients were 24% (28/116). Presence of gastric mucosa atrophy was documented in 8/28 Hp(+) patients (29%) and (2/88) Hp(−) ones (2%) (p = 0.006). Gastric mucosa intestinal metaplasia was observed in 14/28 (50%) Hp(+) patients versus 3/88 (3.4%) of Hp(-) group (p < 0.0001). Hp(+) patients exhibited statistically higher arterial hypertension (p = 0.033). The homeostatic model of assessment insulin resistance was also statistically significantly higher for the Hp(+) group (p < 0.001). In a multivariate analysis, including arterial hypertension, gastric mucosa atrophy, and intestinal metaplasia as variables, statistical significance remained only for intestinal metaplasia (p = 0.001). In conclusion, Hp-I is associated with premalignant gastric mucosa histologic lesions and MetS components, including arterial hypertension and IR. Further large-scale prospective studies are required to confirm these findings.