Explore the vast range of titles available.

Antibiotic‐resistant enterococci represent a significant global health challenge. Unfortunately, most β‐lactam antibiotics are not applicable for enterococcal infections due to intrinsic resistance. To extend their antimicrobial spectrum, polycationic peptides are conjugated to examples from each of the four classes of β‐lactam antibiotics. Remarkably, the β‐lactam–peptide conjugates gained an up to 1000‐fold increase in antimicrobial activity against vancomycin‐susceptible and vancomycin‐resistant enterococci. Even against β‐lactam‐resistant Gram‐negative strains, the conjugates are found to be effective despite their size exceeding the exclusion volume of porins. The extraordinary gain of activity can be explained by an altered mode of killing. Of note, the conjugates showed a concentration‐dependent activity in contrast to the parent β‐lactam antibiotics that exhibited a time‐dependent mode of action. In comparison to the parent β‐lactams, the conjugates showed altered affinities to the penicillin‐binding proteins. Furthermore, it is found that peptide conjugation also resulted in a different elimination route of the compounds when administered to rodents. In mice systemically infected with vancomycin‐resistant enterococci, treatment with a β‐lactam–peptide conjugate reduced bacterial burden in the liver compared to its originator. Therefore, peptide modification of β–lactam antibiotics represents a promising platform strategy to broaden their efficacy spectrum, particularly against enterococci. Novel potent compounds are urgently required for the treatment of antibiotic‐resistant bacteria. Conjugation of polycationic peptides to β‐lactam antibiotics extends their efficacy spectrum against enterococci. The β‐lactam–peptide conjugates show significant differences in mechanism and biodistribution compared to their originators. Due to their high potency, the β‐lactam–peptide conjugates can serve as an alternative treatment option for severe enterococcal infections.

In order to improve the detection and classification of malignant melanoma, this paper describes an image-based method that can achieve AUROC values of up to 0.78 without additional clinical information. Furthermore, the importance of the domain gap between two different image sources is considered, as it is important to create usability independent of hardware components such as the high-resolution scanner used. Since for the application of machine learning methods, alterations of scanner-specific properties such as brightness, contrast or sharpness can have strong (negative) effects on the quality of the prediction methods, two ways to overcome this domain gap are discussed in this paper.

The phytohormone abscisic acid (ABA) plays a central role in organizing adaptive responses in plants to various abiotic stresses, helping the plant minimize the negative impact on growth and development. Rapid and direct detection of ABA is valuable for investigating plant responses to abiotic stress. In this work, we propose a novel label-free, non-competitive immunoassay for detecting and quantifying ABA easily and rapidly using a surface plasmon resonance (SPR) biosensor. The SPR sensor chip was functionalized with a commercial anti-ABA antibody, characterized for its affinity, binding kinetics, and specificity using the same platform. The direct assay demonstrated high specificity and sensitivity, with a calculated limit of detection of 1.36 ng/mL in buffer. The new immunosensor was applied to determine ABA concentrations directly in xylem sap samples from tomato plants subjected to abiotic stress (drought and high salinity) and was able to accurately reflect ABA levels corresponding to the applied stress. The results were comparable to the reference method, ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS), establishing this new immunosensor as a novel detection method for rapid and reliable monitoring of ABA levels associated with abiotic stress in tomato plants.

Crohn's disease (CD) is marked by recurring intestinal inflammation and tissue injury, often resulting in fibrostenosis and bowel obstruction, necessitating surgical intervention with high recurrence rates. To elucidate the mechanisms underlying fibrostenosis in CD, we analyzed the transcriptome of cells isolated from the transmural ileum of patients with CD, including a trio of lesions from each patient: non-affected, inflamed, and stenotic ileum samples, and compared them with samples from patients without CD. Our computational analysis revealed that profibrotic signals from a subset of monocyte-derived cells expressing CD150 induced a disease-specific fibroblast population, resulting in chronic inflammation and tissue fibrosis. The transcription factor TWIST1 was identified as a key modulator of fibroblast activation and extracellular matrix (ECM) deposition. Genetic and pharmacological inhibition of TWIST1 prevents fibroblast activation, reducing ECM production and collagen deposition. Our findings suggest that the myeloid-stromal axis may offer a promising therapeutic target to prevent fibrostenosis in CD.

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint—a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases. Metrics Reloaded is a comprehensive framework for guiding researchers in the problem-aware selection of metrics for common tasks in biomedical image analysis.

Background HER2-driven breast cancer is correlated with poor prognosis, especially during its later stages. Numerous studies have shown the importance of the integrin α3β1 during the initiation and progression of breast cancer; however, its role in this disease is complex and often opposite during different stages and in different types of tumors. In this study, we aim to elucidate the role of integrin α3β1 in a genetically engineered mouse model of HER2-driven mammary tumorigenesis. Methods To investigate the role of α3β1 in HER2-driven tumorigenesis in vivo, we generated a HER2-driven MMTV-cNeu mouse model of mammary tumorigenesis with targeted deletion of Itga3 (Itga3 KO mice). We have further used several established triple-negative and HER2-overexpressing human mammary carcinoma cell lines and generated ITGA3-knockout cells to investigate the role of α3β1 in vitro. Invasion of cells was assessed using Matrigel- and Matrigel/collagen I-coated Transwell assays under static or interstitial fluid flow conditions. The role of α3β1 in initial adhesion to laminin and collagen was assessed using adhesion assays and immunofluorescence. Results Tumor onset in mice was independent of the presence of α3β1. In contrast, the depletion of α3β1 reduced the survival of mice and increased tumor growth and vascularization. Furthermore, Itga3 KO mice were significantly more likely to develop lung metastases and had an increased metastatic burden compared to WT mice. In vitro, the deletion of ITGA3 caused a significant increase in the cellular invasion of HER2-overexpressing SKBR3, AU565, and BT474 cells, but not of triple-negative MDA-MB-231. This invasion suppressing function of α3β1 in HER2-driven cells depended on the composition of the extracellular matrix and the interstitial fluid flow. Conclusion Downregulation of α3β1 in a HER2-driven mouse model and in HER2-overexpressing human mammary carcinoma cells promotes progression and invasiveness of tumors. The invasion-suppressive role of α3β1 was not observed in triple-negative mammary carcinoma cells, illustrating the tumor type-specific and complex function of α3β1 in breast cancer.

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation. This Perspective presents a reliable and comprehensive source of information on pitfalls related to validation metrics in image analysis, with an emphasis on biomedical imaging.

An array of analytical methods including surface area determination by gas adsorption using the Brunauer, Emmett, Teller (BET) method, combustion analysis, XRD, ToF-SIMS, TEM and impedance spectroscopy has been used to investigate the interaction of gadolinia doped ceria (GDC) with hydrogen sulphide containing reducing atmospheres. It is shown that sulphur is incorporated into the GDC bulk and might lead to phase changes. Additionally, high concentrations of silicon are found on the surface of model composite microelectrodes. Based on these data, a model is proposed to explain the multi-facetted electrochemical degradation behaviour encountered during long term electrochemical measurements. While electrochemical bulk properties of GDC stay largely unaffected, the surface polarisation resistance is dramatically changed, due to silicon segregation and reaction with adsorbed sulphur.

Despite being well established, acute surgery in traumatic acute subdural haematoma is based on low-grade evidence. We aimed to compare the effectiveness of a strategy preferring acute surgical evacuation with one preferring initial conservative treatment in acute subdural haematoma. We did a prospective, observational, comparative effectiveness study using data from participants enrolled in the Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We included patients with no pre-existing severe neurological disorders who presented with acute subdural haematoma within 24 h of traumatic brain injury. Using an instrumental variable analysis, we compared outcomes between centres according to treatment preference for acute subdural haematoma (acute surgical evacuation or initial conservative treatment), measured by the case-mix-adjusted percentage of acute surgery per centre. The primary endpoint was functional outcome at 6 months as rated with the Glasgow Outcome Scale Extended, which was estimated with ordinal regression as a common odds ratio (OR) and adjusted for prespecified confounders. Variation in centre preference was quantified with the median OR (MOR). CENTER-TBI is registered with ClinicalTrials.gov, number NCT02210221, and the Resource Identification Portal (Research Resource Identifier SCR_015582). Between Dec 19, 2014 and Dec 17, 2017, 4559 patients with traumatic brain injury were enrolled in CENTER-TBI, of whom 1407 (31%) presented with acute subdural haematoma and were included in our study. Acute surgical evacuation was done in 336 (24%) patients, by craniotomy in 245 (73%) of those patients and by decompressive craniectomy in 91 (27%). Delayed decompressive craniectomy or craniotomy after initial conservative treatment (n=982) occurred in 107 (11%) patients. The percentage of patients who underwent acute surgery ranged from 5·6% to 51·5% (IQR 12·3–35·9) between centres, with a two-times higher probability of receiving acute surgery for an identical patient in one centre versus another centre at random (adjusted MOR for acute surgery 1·8; p<0·0001]). Centre preference for acute surgery over initial conservative treatment was not associated with improvements in functional outcome (common OR per 23·6% [IQR increase] more acute surgery in a centre 0·92, 95% CI 0·77–1·09). Our findings show that treatment for patients with acute subdural haematoma with similar characteristics differed depending on the treating centre, because of variation in the preferred approach. A treatment strategy preferring an aggressive approach of acute surgical evacuation over initial conservative treatment was not associated with better functional outcome. Therefore, in a patient with acute subdural haematoma for whom a neurosurgeon sees no clear superiority for acute surgery over conservative treatment, initial conservative treatment might be considered. The Hersenstichting Nederland (also known as the Dutch Brain Foundation), the European Commission Seventh Framework Programme, the Hannelore Kohl Stiftung (Germany), OneMind (USA), Integra LifeSciences Corporation (USA), and NeuroTrauma Sciences (USA).

A growing body of research uses field and survey experiments to examine ethnic discrimination. Central to these studies is the use of people’s names as a proxy for ethnic origin. However, names signal more than solely ethnic markers. Moreover, their signals might vary across national contexts. Scholars should pre-test the perception of names used in experiments in order to properly interpret their results and reveal the mechanisms underlying discrimination. There is, however, no comprehensive study yet in Europe which thoroughly pre-test the perception of names across countries with profoundly different migration histories. In this paper, we present the dataset ‘ Perceptions of names in Europe ’, containing the perceptions of 1078 names studied across nine European countries: Belgium, Czech Republic, Germany, Hungary, Ireland, the Netherlands, Spain, Switzerland, and the United Kingdom. The dataset includes 82.400 evaluations from 8.240 respondents about the distinctiveness of Sub-Sahara African, Muslim and Roma names in terms of minority-majority group status, gender, religiosity, socioeconomic status, skin colour, and language proficiency. Information on respondents’ background characteristics are also available.