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To ensure Europe increases its domestic production of high quality and responsibly produced raw materials, the development of innovative technologies for 3D geological modeling in mineral exploration is paramount. The Erzgebirge in Germany provides an excellent framework to showcase the application of artificial intelligence and in particular Artificial Neural Networks (ANN) for 3D mineral prospectivity mapping. The Erzgebirge belongs to the Variscan Belt, withholding 800 years of mining history and it is also famous for Ag, Sn, W, Fe, Cu, Li mineralizations among others. The Bockau deposit is located at the western section of the Erzgebirge. The target area is a Paleozoic metasediment body that was formed during the Variscan orogeny. The metasediment body consists primarily of alternating micaschist, phyllite and quartzite and dips mostly 25° to 240° SW. The metasediment is surrounded by Late Variscan plutons which partly led to contact metamorphic zones. In addition there is a large Quartzite body which was mined near to the surface in the 17th century for Sn, following a stratiform tin anomaly which can reach up to 4000 ppm Sn. Thanks to the long mining history, the Bockau deposit condenses a large amount of geological, geochemical, geophysical and mineral data. To increase mineralogical knowledge of the deposit and to help identify drilling targets, a hybrid approach for 3D mineral predictivity mapping is implemented. Potentially mineralisation-controlling factors are identified in knowledge-driven genetic exploration models, taking into account the borehole data, major faults, electromagnetic data, intrusive bodies, contact metamorphic zones and lithological borders, followed by data-driven weighted ANN predictive modelling implemented in the in-house developed advangeo® 3D Prediction Software. The predictive model is guided by structural variables such as the euclidean distance to fault planes, lithological surfaces and to metamorphic contact zones. The model is also constrained by geophysical data by a magnetic susceptibility model obtained from an airborne magnetic data inversion. Finally, Sn anomaly data from boreholes is implemented as training data for the prediction. The results show the probability distribution of Sn mineralisation occurrence in 3D over a voxel model formed by blocks of approximately 684 m3 13(x), 13.5(y) and 4(z), increasing the mineralogical knowledge of the deposit and guiding exploration efforts complementing the decision making process for drilling new targets. The results are validated by iteratively implementing the jackknife method, splitting the training data into validation and training subsets. The first prediction iteration is performed with a subset containing 77 % of the Sn content data from boreholes as training data, followed by 50 and 30 % subsets. Thus, allowing at each iteration to perform a quantitative evaluation of the prediction by comparing the validation subset with the Sn content of the borehole that was not used for the prediction. The paper has been prepared in the frame of the Horizon 2020 co-funded project GOLDENEYE, which has received funds through the Grant Agreement 869398.

Summary Substantial research efforts have gone into elucidating the role of protein misfolding and self-assembly in the onset and progression of Alzheimer’s disease (AD). Aggregation of the Amyloid-β (Aβ) peptide into insoluble fibrils is closely associated with AD. Here, we use biophysical techniques to study a peptide-based approach to target Aβ amyloid aggregation. A peptide construct, NCAM-PrP, consists of a largely hydrophobic signal sequence linked to a positively charged hexapeptide. The NCAM-PrP peptide inhibits Aβ amyloid formation by forming aggregates which are unavailable for further amyloid aggregation. In a membrane-mimetic environment, Aβ and NCAM-PrP form specific heterooligomeric complexes, which are of lower aggregation states compared to Aβ homooligomers. The Aβ:NCAM-PrP interaction appears to take place on different aggregation states depending on the absence or presence of a membrane-mimicking environment. These insights can be useful for the development of potential future therapeutic strategies targeting Aβ at several aggregation states., Graphical abstract, Highlights • A signal peptide construct, NCAM-PrP, inhibits Aβ peptide amyloid aggregation • Aβ and NCAM-PrP form co-aggregates which are not compatible with amyloid formation • The Aβ and NCAM-PrP interaction occurs both in aqueous solution and in membranes • Co-aggregates formed in solution and in the membrane have different properties, Molecular neuroscience; Structural biology; Biophysics

Uranium (U) is naturally present in ambient air, water, and soil, and depleted uranium (DU) is released into the environment via industrial and military activities. While the radiological damage from U is rather well understood, less is known about the chemical damage mechanisms, which dominate in DU. Heavy metal exposure is associated with numerous health conditions including Alzheimer’s disease (AD), the most prevalent age-related cause of dementia. The pathological hallmark of AD is deposition of amyloid plaques, consisting mainly of amyloid-β (Aβ) peptides aggregated into amyloid fibrils in the brain. However, the toxic species in AD are likely oligomeric Aβ aggregates. Exposure to heavy metals such as Cd, Hg, Mn, and Pb is known to increase Aβ production, and these metals bind to Aβ peptides and modulate their aggregation. Possible effects of U in AD pathology have been sparsely studied. Here, we use biophysical techniques to studyin vitrointeractions between Aβ peptides and uranyl ions, UO22+, of DU. We show for the first time that uranyl ions bind to Aβ peptides with affinities in the micromolar range, induce structural changes in Aβ monomers and oligomers, and inhibit Aβ fibrillization. General toxic mechanisms of uranyl ions could be modulation of protein folding, misfolding, and aggregation.

Non-biodegradable polymers are released as microplastics into the environments during the biodegradation of partially biodegradable polymer blends.

Strong acid mine drainage (AMD) processes in the flooded, formerly open pits in the Lusatia area present an enormous environmental challenge for the rehabilitation of the post-mining landscape. Extensive and costly monitoring is required for optimal AMD management and remediation planning and control. Because of the large size of the area and the dimension of the problem, the regular sampling can only provide limited point data, which needs to be extrapolated to the entire area. Consequently, the search for effective approaches for extrapolating the point data to the area of all water bodies is essential for rehabilitation success monitoring and for understanding the dependencies between AMD and environmental factors such as land use, weather conditions, geology, and hydrogeology. The main aim of this study was to investigate the suitability of Sentinel-2 multispectral imagery and artificial neural networks (ANNs) for the quantitative mapping of acid mine drainage (AMD) constituents, such as dissolved iron, pH value, and sulfate in large water bodies, for an area of approximately 7220 km2 (the area of the pit lakes is about 185 km2). Correlations between different chemical water parameters were also investigated. An extensive water monitoring dataset was used to train artificial neural networks for the identification of dependencies between the multispectral remote sensing data and the water quality ground measurements. Respective relationships have been identified, especially for dissolved iron and pH. These trained ANNs have been used to produce water quality maps with high spatial (10 × 10 m) and temporal (any cloud-free period) resolution, which show the wide variability of water quality in the different parts of the mining region. Concrete sources of AMD can be identified using the water quality maps of single lakes, and the success of sanitation measures such as liming was visualized. The approach opens many doors for the optimization of both the monitoring program and sanitation technology.

Interactions between molecules are fundamental in biology. They occur also between amyloidogenic polypeptides that are associated with different amyloid diseases, which makes it important to study their interactions. However, addressing such research questions with imaging techniques is hindered by the problem to distinguish different polypeptides without adding artificial probes for detection. Here we present a new method for this purpose. We show that 13C-labeling can be used to distinguish peptides in nanoscale images of their infrared absorption, even when they have similar secondary structure. We studied different aggregation states of the amyloid-β peptide (Aβ) and its interaction with an inhibitory cell-penetrating peptide (NCAM1-PrP) using scattering-type scanning near field microscopy. Labeled and unlabeled peptides could be discriminated by comparing images of the optical phase taken at wavenumbers characteristic for either the labeled or the unlabeled peptide. NCAM1-PrP seems to be able to dissolve or coat existing Aβ fibrils because "naked" Aβ fibrils are not detected after mixing.

Using a supervised machine learning framework on a large training set of questions and answers, we identify 1,364 trigrams that signal nonanswers in earnings call questions and answers (Q&A). We show that this glossary has economic relevance by applying it to contemporaneous stock market reactions after earnings calls. Our findings suggest that obstructing the flow of information leads to significantly lower cumulative abnormal stock returns and higher implied volatility. As both our method and glossary are free of financial context, we believe that the measure is applicable to other fields with a Q&A setup outside the contextual domain of financial earnings conference calls. This paper was accepted by Kay Giesecke, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.4597 .

A 37-year-old woman with a history of incomplete atrioventricular canal and an extensive history of corrective cardiac surgeries presented with recurrent episodes of acute decompensated heart failure in the presence of junctional bradycardia with chronotropic incompetence. The initial plan was to proceed with implantation of a dual chamber pacemaker but given high index of suspicion for the presence of atrial standstill in the context of her extensive cardiac surgical history, we performed electroanatomical mapping and echocardiography at the time of pacemaker implantation that confirmed atrial standstill. Islands of electrically functional atrial myocardium were detected. Pacing from these locations resulted in local atrial capture, but failed to result in global atrial electrical capture, mechanical atrial contraction, or atrioventricular conduction. In light of the dismal outcomes of right ventricular pacing in patients with atrial standstill, we implanted a left bundle branch pacing lead that resulted in improvement of patient’s cardiac output and prevented future admissions for decompensated heart failure in one year follow up.

This paper empirically analyzes the role of corporate culture in banking. We define culture based on the Competing Value Framework (Quinn and Rohrbaugh, 1983) and find that banks with a more pronounced competition-oriented culture have stronger bonus-focused compensation schemes. Banks with a strong focus on growth show higher stock returns and banks with a focus on stability show lower bankruptcy risk. These findings support various theories on bank culture (Thakor, 2012; Song and Thakor, 2019) and highlight the importance of corporate culture as a ‘softer’ aspects of governance to enhance banking stability.

Soluble oligomers of the amyloid-β(1-42) (Aβ42) peptide, widely considered to be among the relevant neurotoxic species involved in Alzheimer's disease, were characterized with a combination of biochemical and biophysical methods. Homogeneous and stable Aβ42 oligomers were prepared by treating monomeric solutions of the peptide with detergents. The prepared oligomeric solutions were analyzed with blue native and sodium dodecyl sulfate polyacrylamide gel electrophoresis, as well as with infrared (IR) spectroscopy. The IR spectra indicated a well-defined β-sheet structure of the prepared oligomers. We also found a relationship between the size/molecular weight of the Aβ42 oligomers and their IR spectra: The position of the main amide I' band of the peptide backbone correlated with oligomer size, with larger oligomers being associated with lower wavenumbers. This relationship explained the time-dependent band shift observed in time-resolved IR studies of Aβ42 aggregation in the absence of detergents, during which the oligomer size increased. In addition, the bandwidth of the main IR band in the amide I' region was found to become narrower with time in our time-resolved aggregation experiments, indicating a more homogeneous absorption of the β-sheets of the oligomers after several hours of aggregation. This is predominantly due to the consumption of smaller oligomers in the aggregation process.

Lithium (Li) was recently added to the list of critical raw materials by the European Union due to its significance for the green energy transition. Thus, the development of new toolchains to make Li exploration more economic and more effective is needed. Stream sediment analysis can play an important part in these new tool chains. In this work, two historical stream sediment datasets covering parts of the Fregeneda-Almendra pegmatite field in the Douro region (Portugal) were reprocessed considering two distinct approaches: spatial interpolation through inverse distance weighting (IDW) and the catchment basin approach using the concentration area (C-A) fractal analysis. The following objectives were delineated: (i) determine pathfinder elements for Li, considering relevant associations in the mineralization sources; (ii) compare the performance of both approaches; (iii) identify new target areas for Li. In the case of spatial interpolation, the highest Li values were associated to granites although the use of key elements allowed lithological discrimination and the delineation of target areas. In the catchment basin approach, fractal analysis proved to be effective in decreasing the number of areas of interest with high accuracy (>75%) when considering the previously mapped Li-pegmatites. One of the limitations identified was the number of anomalous basins related to the granites, despite the use of pathfinder elements allowing discriminating granite- from pegmatite-related Li anomalies. Comparing the two approaches, the spatial interpolation method is more adequate for the early stages of exploration (reconnaissance), while the catchment basin approach is more suited for prospect-scale exploration. Field validation of the results identified one pegmatite containing Li mineralization and three others with favorable signs for Li mineralization in the Douro region. The authors would like to thank the financial support provided by FCT– Fundação para a Ciência e a Tecnologia, I.P. (Portugal) and BMBF Jülich – Bundesministerium für Bildung und Forschung (Germany), with the ERA-MIN/0001/2017 – LIGHTS project. The work was also supported by Portuguese National Funds through the FCT projects UIDB/04683/2020 and UIDP/04683/2020 – ICT (Institute of Earth Sciences) and UIDB/50019/2020 – IDL (Instituto Dom Luiz). Joana Cardoso-Fernandes and Jéssica Lima are financially supported within the compass of their respective Ph.D. Thesis, ref. SFRH/BD/136108/2018 and ref. 2020.05793.BD, by national funds from MCTES through FCT, and co-financed by the European Social Fund (ESF) through POCH – Programa Operacional Capital Humano – and NORTE 2020 regional program. The Spanish Ministerio de Ciencia, Innovacion y Universidades (Project RTI2018-094097-B-100, with ERDF funds) and the University of the Basque Country (UPV/EHU) (grant GIU18/084) also contributed economically. The authors are also grateful to BRGM (Bureau de Recherches Géologiques et Minières) and LNEG (Laboratório Nacional de Energia e Geologia) for making the data available for this study.

Structured products like collateralized loan obligations (CLOs) tend to offer significantly higher yield spreads than corporate bonds (CBs) with the same rating. At the same time, empirical evidence does not indicate that this higher yield is reduced by higher default losses of CLOs. The evidence thus suggests that CLOs offer higher expected returns compared to CB with similar credit risk. This study aims to analyze whether this return difference is captured by asset pricing factors. We show that market risk is the predominant risk factor for both CBs and CLOs. CLO investors, however, additionally demand a premium for their risk exposure towards systemic risk. This premium is inversely related to the rating class of the CLO.

Radiographic identification of the cardiac implantable electronic device (CIED) manufacturer facilitates urgent interrogation of an unknown CIED. In the past, we relied on visualizing a manufacturer-specific X-ray logo. Recently, a free smartphone application ("Pacemaker-ID") was made available. A photograph of a chest X-ray was subjected to an artificial intelligence (AI) algorithm that uses manufacturer characteristics (canister shape, battery design) for identification. We sought to externally validate the accuracy of this smartphone application as a point-of-care (POC) diagnostic tool, compare on-axis to off-axis photo accuracy, and compare it to X-ray logo visualization for manufacturer identification. We reviewed operative reports and chest X-rays in 156 pacemaker and 144 defibrillator patients to visualize X-ray logos and to test the application with 3 standard (on-axis) and 4 non-standard (off-axis) photos (20° cranial; caudal, leftward, and rightward). Contingency tables were created and chi-squared analyses (P.05) were completed for manufacturer and CIED type. The accuracy of the application was 91.7% and 86.3% with single and serial application(s), respectively; 80.7% with off-axis photos; and helpful for all manufacturers (range, 85.4%-96.6%). Overall, the application proved superior to the X-ray logo, visualized in 56% overall (P.0001) but varied significantly by manufacturer (range, 7.7%-94.8%; P.00001). The accuracy of the Pacemaker-ID application is consistent with reports from its creators and superior to X-ray logo visualization. The accuracy of the application as a POC tool can be enhanced and maintained with further AI training using recent CIED models. Some manufacturers can enhance their X-ray logos by improving placement and design.

Spider silk is the toughest fiber found in nature, and bulk production of artificial spider silk that matches its mechanical properties remains elusive. Development of miniature spider silk proteins (mini-spidroins) has made large-scale fiber production economically feasible, but the fibers' mechanical properties are inferior to native silk. The spider silk fiber's tensile strength is conferred by poly-alanine stretches that are zipped together by tight side chain packing in β-sheet crystals. Spidroins are secreted so they must be void of long stretches of hydrophobic residues, since such segments get inserted into the endoplasmic reticulum membrane. At the same time, hydrophobic residues have high β-strand propensity and can mediate tight inter-β-sheet interactions, features that are attractive for generation of strong artificial silks. Protein production in prokaryotes can circumvent biological laws that spiders, being eukaryotic organisms, must obey, and the authors thus design mini-spidroins that are predicted to more avidly form stronger β-sheets than the wildtype protein. Biomimetic spinning of the engineered mini-spidroins indeed results in fibers with increased tensile strength and two fiber types display toughness equal to native dragline silks. Bioreactor expression and purification result in a protein yield of ≈9 g L

Perioperatively administered (leukocyte reduced) allogeneic red blood cell transfusions (lrRBCTs) may lead to transfusion-related immunomodulation and reduced overall survival (OS) in cancer patients. Herein, the effect of lrRBCT on local recurrence (LR), distant metastasis (DM), and OS in soft tissue sarcoma (STS) patients was analysed.Retrospective study on 432 STS patients (mean age: 60.0 ± 17.8 years; 46.1% female), surgically treated at a tertiary tumour centre. Uni- and multivariate survival models were calculated to analyse impact of perioperative lrRBCTs on LR, DM, OS.Perioperatively, 75 patients (17.4%) had received lrRBCTs. Older patients, deep, large, lower limb STS rather required lrRBCTs (all p 0.05). No significant association between lrRBCT administration and LR- (p = 0.582) or DM-risk (p = 0.084) was observed. LrRBCT was associated with worse OS in univariate analysis (HR: 2.222; p 0.001), with statistical significance lost upon multivariate analysis (HR: 1.658; p = 0.059; including age, histology, size, grading, amputation, depth). Adding preoperative haemoglobin in subgroup of 220 patients with laboratory parameters revealed significant negative impact of low haemoglobin on OS (p = 0.014), whilst effect of lrRBCT was further diminished (p = 0.167).Unfavourable prognostic factors prevail in STS patients requiring lrRBCTs. Low haemoglobin levels rather than lrRBCT seem to reduce OS.

Herein, we circle around a sound phenomenon that may appear trivial but that under closer investigation turns out to be both complex and manifold: The sound of water poured into a glass or mug. We use existing research from various disciplines as well as our own sound recordings, and thus explore both scientific and aesthetic aspects of the sound of hot and cold water, and the differences between the two. Drawing on the thinkers Bateson, Berlin, and Dewey, we discuss relations between «trivial issues» and «the large questions» (Bateson), whether a phenomenon can be more than one thing at the same time (Berlin), and human experiences in encounters with the phenomenon (Dewey). We discuss this against various forms of interdisciplinarity and collaboration across traditional epistemic boundaries and hierarchies. This way, we reflect upon how an everyday phenomenon can be a meeting place between the aesthetic, educational and scientific, both with regards to this specific phenomenon, and on a more general basis.