A Comprehensive Review of Recent Research into the Effects of Antimicrobial Peptides on Biofilms-January 2020 to September 2023.

Microbial biofilm formation creates a persistent and resistant environment in which microorganisms can survive, contributing to antibiotic resistance and chronic inflammatory diseases. Increasingly, biofilms are caused by multi-drug resistant microorganisms, which, coupled with a diminishing supply of effective antibiotics, is driving the search for new antibiotic therapies. In this respect, antimicrobial peptides (AMPs) are short, hydrophobic, and amphipathic peptides that show activity against multidrug-resistant bacteria and biofilm formation. They also possess broad-spectrum activity and diverse mechanisms of action. In this comprehensive review, 150 publications (from January 2020 to September 2023) were collected and categorized using the search terms 'polypeptide antibiotic agent', 'antimicrobial peptide', and 'biofilm'. During this period, a wide range of natural and synthetic AMPs were studied, of which LL-37, polymyxin B, GH12, and Nisin were the most frequently cited. Furthermore, although many microbes were studied, Staphylococcus aureus and Pseudomonas aeruginosa were the most popular. Publications also considered AMP combinations and the potential role of AMP delivery systems in increasing the efficacy of AMPs, including nanoparticle delivery. Relatively few publications focused on AMP resistance. This comprehensive review informs and guides researchers about the latest developments in AMP research, presenting promising evidence of the role of AMPs as effective antimicrobial agents.

NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.

In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for this task, supervised deep learning (DL) methods have shown superior segmentation performances compared to classical machine learning and image processing techniques. However, these models need fully annotated datasets for training which is challenging to acquire, especially in the medical domain. In this work, we release one of the biggest fully manually annotated datasets of nuclei in Hematoxylin and Eosin (H&E)-stained histological images, called NuInsSeg. This dataset contains 665 image patches with more than 30,000 manually segmented nuclei from 31 human and mouse organs. Moreover, for the first time, we provide additional ambiguous area masks for the entire dataset. These vague areas represent the parts of the images where precise and deterministic manual annotations are impossible, even for human experts. The dataset and detailed step-by-step instructions to generate related segmentation masks are publicly available on the respective repositories.

Improving generalization capability of deep learning-based nuclei instance segmentation by non-deterministic train time and deterministic test time stain normalization.

With the advent of digital pathology and microscopic systems that can scan and save whole slide histological images automatically, there is a growing trend to use computerized methods to analyze acquired images. Among different histopathological image analysis tasks, nuclei instance segmentation plays a fundamental role in a wide range of clinical and research applications. While many semi- and fully-automatic computerized methods have been proposed for nuclei instance segmentation, deep learning (DL)-based approaches have been shown to deliver the best performances. However, the performance of such approaches usually degrades when tested on unseen datasets. In this work, we propose a novel method to improve the generalization capability of a DL-based automatic segmentation approach. Besides utilizing one of the state-of-the-art DL-based models as a baseline, our method incorporates non-deterministic train time and deterministic test time stain normalization, and ensembling to boost the segmentation performance. We trained the model with one single training set and evaluated its segmentation performance on seven test datasets. Our results show that the proposed method provides up to 4.9%, 5.4%, and 5.9% better average performance in segmenting nuclei based on Dice score, aggregated Jaccard index, and panoptic quality score, respectively, compared to the baseline segmentation model.

The history of circadian rhythm research in Austria.

In view of the recent revival of interest in circadian biology and circadian epidemiology at the Medical University of Vienna, it seems appropriate to highlight the rich and pioneering history of circadian research in Austria. Among the forefathers of circadian research in Vienna are Otto Marburg (1874-1948), who discovered important elements of the pineal gland physiology, Robert Hofstätter (1883-1970), who used pineal gland extract in obstetrics/gynecology, and Paul Engel (1907-1997), who discovered that the pineal gland was controlled by light. More recently, Vera Lapin (1920-2007) showed that surgical removal of the pineal gland increased tumor growth, while Franz Waldhauser (*1946) investigated melatonin in conjunction with night work. Michael Kundi (*1950) and his team conducted among the first studies demonstrating differences in rhythms of night workers and early evidence for health impairments among them. Furthermore, Vienna-born Erhard Haus (1926-2013) pioneered the discovery of the role and importance of melatonin in relation to numerous diseases. This rich pioneering contribution of scientists in Vienna or with roots in Vienna is continued today by a new generation of chronobiologists, epidemiologists and clinicians in Vienna whose new insights contribute to the rapidly developing field of circadian rhythms research. Current topics and contributions relate to the impact of circadian rhythm disruption on health, and the application of chronotherapeutic approaches in clinical and preventive settings.

Human intestine and placenta exhibit tissue-specific expression of RAGE isoforms.

The receptor for advanced glycation end products (RAGE) is encoded by AGER, a gene that is subjected to tissue-specific alternative splicing. Splice variants of RAGE in intestine and placenta are unknown and contradictory data concerning RAGE protein expression in these tissues have been published. As a basis for future functional studies, we examined RAGE expression in small intestine, colon and placentas. PCR cloning revealed that full-length RAGE is the only RAGE transcript isoform expressed in placenta. In the small intestine, the major transcript isoform detected was RAGE_v1 encoding the C-terminally truncated soluble receptor. In the colon, both full-length RAGE as well as several splice variants were identified. Four antibodies were used to study protein expression by immunoblotting and were carefully validated. Appropriate controls were essential to avoid misinterpretation of bands caused by non-specific reactivity of antibodies. Only one of four antibodies tested detected full-length RAGE in placenta, whereas no RAGE-specific band was detected in intestinal tissues despite loading >30-fold more intestinal tissue than the positive control, human lung. RAGE expression levels in the placenta were 100-fold lower compared with human lung when analyzed by ELISA, and no significant differences in RAGE expression were detected between healthy placentas and placentas from women with preeclampsia, gestational diabetes mellitus, or fetal growth restriction. We conclude that healthy placental chorionic tissue expresses low levels of full-length RAGE, whereas expression of the tissue-specific intestinal isoforms is below the limit of detection. Low RAGE expression levels in combination with a lack of antibody validation may explain the conflicting published results on RAGE protein expression in intestine and placenta.

Peanut lipids influence the response of bronchial epithelial cells to the peanut allergens Ara h 1 and Ara h 2 by decreasing barrier permeability.

Background: Peanut-allergic individuals react upon their first known ingestion of peanuts, suggesting sensitization occurs through non-oral exposure. Increasing evidence suggests that the respiratory tract is a probable site for sensitization to environmental peanuts. However, the response of the bronchial epithelium to peanut allergens has never been explored. Furthermore, food matrix-derived lipids play an important role in allergic sensitization. Objective: To contribute to a better understanding of the mechanisms of allergic sensitization to peanuts via inhalation, by exploring the direct effect of the major peanut allergens Ara h 1 and Ara h 2 and peanut lipids on bronchial epithelial cells. Methods: Polarized monolayers of the bronchial epithelial cell line 16HBE14o- were stimulated apically with peanut allergens and/or peanut lipids (PNL). Barrier integrity, transport of allergens across the monolayers, and release of mediators were monitored. Results: Ara h 1 and Ara h 2 impacted the barrier integrity of the 16HBE14o- bronchial epithelial cells and crossed the epithelial barrier. Ara h 1 also induced the release of pro-inflammatory mediators. PNL improved the barrier function of the cell monolayers, decreased paracellular permeability and reduced the amount of allergens crossing the epithelial layer. Conclusion: Our study provides evidence of the transport of Ara h 1 and Ara h 2 across the airway epithelium, of the induction of a pro-inflammatory milieu, and identifies an important role for PNL in controlling the amount of allergens that can cross the epithelial barrier. These, all together, contribute to a better understanding of the effects of peanuts exposure on the respiratory tract.

Antibody Conjugates Bispecific for Pollen Allergens and ICAM-1 with Potential to Prevent Epithelial Allergen Transmigration and Rhinovirus Infection.

Allergy and rhinovirus (RV) infections are major triggers for rhinitis and asthma, causing a socioeconomic burden. As RVs and allergens may act synergistically to promote airway inflammation, simultaneous treatment strategies for both causative agents would be innovative. We have previously identified the transmembrane glycoprotein intercellular adhesion molecule 1 (ICAM-1) as an anchor for antibody conjugates bispecific for ICAM-1 and Phleum pratense (Phl p) 2, a major grass pollen allergen, to block allergen transmigration through the epithelial barrier. Since ICAM-1 is a receptor for the major group RVs, we speculated that our bispecific antibody conjugates may protect against RV infection. Therefore, we created antibody conjugates bispecific for ICAM-1 and the major grass pollen allergen Phl p 5 and analyzed their capacity to affect allergen penetration and RV infection. Bispecific antibody conjugates significantly reduced the trans-epithelial migration of Phl p 5 and thus the basolateral Phl p 5 concentration and allergenic activity as determined by humanized rat basophilic leukemia cells and inhibited RV infection of cultured epithelial cells. A reduction in allergenic activity was obtained only through the prevention of allergen transmigration because the Phl p 5-specific IgG antibody did not block the allergen-IgE interaction. Our results indicate the potential of allergen/ICAM-1-specific antibody conjugates as a topical treatment strategy for allergy and RV infections.

A dual decoder U-Net-based model for nuclei instance segmentation in hematoxylin and eosin-stained histological images.

Even in the era of precision medicine, with various molecular tests based on omics technologies available to improve the diagnosis process, microscopic analysis of images derived from stained tissue sections remains crucial for diagnostic and treatment decisions. Among other cellular features, both nuclei number and shape provide essential diagnostic information. With the advent of digital pathology and emerging computerized methods to analyze the digitized images, nuclei detection, their instance segmentation and classification can be performed automatically. These computerized methods support human experts and allow for faster and more objective image analysis. While methods ranging from conventional image processing techniques to machine learning-based algorithms have been proposed, supervised convolutional neural network (CNN)-based techniques have delivered the best results. In this paper, we propose a CNN-based dual decoder U-Net-based model to perform nuclei instance segmentation in hematoxylin and eosin (H&E)-stained histological images. While the encoder path of the model is developed to perform standard feature extraction, the two decoder heads are designed to predict the foreground and distance maps of all nuclei. The outputs of the two decoder branches are then merged through a watershed algorithm, followed by post-processing refinements to generate the final instance segmentation results. Moreover, to additionally perform nuclei classification, we develop an independent U-Net-based model to classify the nuclei predicted by the dual decoder model. When applied to three publicly available datasets, our method achieves excellent segmentation performance, leading to average panoptic quality values of 50.8%, 51.3%, and 62.1% for the CryoNuSeg, NuInsSeg, and MoNuSAC datasets, respectively. Moreover, our model is the top-ranked method in the MoNuSAC post-challenge leaderboard.

Generation of high affinity ICAM-1-specific nanobodies and evaluation of their suitability for allergy treatment.

The nasal cavity is an important site of allergen entry. Hence, it represents an organ where trans-epithelial allergen penetration and subsequent IgE-mediated allergic inflammation can potentially be inhibited. Intercellular adhesion molecule 1 (ICAM-1) is highly expressed on the surface of respiratory epithelial cells in allergic patients. It was identified as a promising target to immobilize antibody conjugates bispecific for ICAM-1 and allergens and thereby block allergen entry. We have previously characterized a nanobody specific for the major birch pollen allergen Bet v 1 and here we report the generation and characterization of ICAM-1-specific nanobodies. Nanobodies were obtained from a camel immunized with ICAM-1 and a high affinity binder was selected after phage display (Nb44). Nb44 was expressed as recombinant protein containing HA- and His-tags in Escherichia coli (E.coli) and purified via affinity chromatography. SDS-PAGE and Western blot revealed a single band at approximately 20 kDa. Nb44 bound to recombinant ICAM-1 in ELISA, and to ICAM-1 expressed on the human bronchial epithelial cell line 16HBE14o- as determined by flow cytometry. Experiments conducted at 4°C and at 37°C, to mimic physiological conditions, yielded similar percentages (97.2 ± 1.2% and 96.7 ± 1.5% out of total live cells). To confirm and visualize binding, we performed immunofluorescence microscopy. While Texas Red Dextran was rapidly internalized Nb44 remained localized on the cell surface. Additionally, we determined the strength of Nb44 and ICAM-1 interaction using surface plasmon resonance (SPR). Nb44 bound ICAM-1 with high affinity (10-10 M) and had slow off-rates (10-4 s-1). In conclusion, our results showed that the selected ICAM-1-specific nanobody bound ICAM-1 with high affinity and was not internalized. Thus, it could be further used to engineer heterodimers with allergen-specific nanobodies in order to develop topical treatments of pollen allergy.

Special Issue on "Advances in Skin Lesion Image Analysis Using Machine Learning Approaches".

Skin diseases are widespread and a frequent occurrence in general practice [...].

Plumbagin and Plumbago indica Differentially Modulated Cytochrome P450 and Transporter Profiles in BeWo and HepG2 Cells.

<b>Background and Objective:</b> The medicinal herb <i>Plumbago indica</i> (PI) and its major constituent plumbagin have reported pharmacological properties but there is a lack of information about their herb-drug interactions. The effects of methanolic (PI-MeOH) and ethanolic (PI-EtOH) crude extracts of PI and plumbagin on the expression of cytochrome P450s (<i>CYP1A2</i>, <i>CYP2E1</i> and <i>CYP3A4</i>) and transporters (<i>ABCC1</i>, <i>ABCG2</i> and <i>SLC22A11</i>) were investigated in BeWo and HepG2 cells. <b>Materials and Methods:</b> BeWo or HepG2 cells were treated with 0.5-5 µM plumbagin or 25-500 µg mL¹ of PI-MeOH or PI-EtOH for 24 hrs. Total RNA was extracted and mRNA expression of CYPs and transporters were determined using RT-qPCR. <b>Results:</b> PI and plumbagin affected mRNA expression differently in the two tested cell types. In BeWo cells, all concentrations of PI-MeOH induced <i>CYP2E1</i>, 100 and 500 µg Ml¹ PI-MeOH and PI-EtOH up-regulated <i>CYP1A2</i>, <i>CYP3A4 </i>and <i>ABCG2 </i>and 500 µg mL¹ PI-EtOH induced <i>ABCG2</i> expression. Plumbagin suppressed <i>CYP1A2</i> and induced <i>SLC22A11 </i>expression at the highest concentration, 5 µM. In HepG2 cells, 5 µM plumbagin and 500 µg Ml¹ PI-EtOH suppressed <i>CYP3A4 </i>expression and 500 µg mL¹ PI-MeOH and PI-EtOH up-regulated <i>CYP1A2</i> and <i>CYP2E1 </i>expression. <i>ABCC1</i> expression was induced by all treatments while <i>ABCG2</i> and <i>SLC22A11 </i>were induced only by 500 µg mL¹ PI-MeOH and PI-EtOH. <b>Conclusion:</b> The use of PI or plumbagin supplements in large quantities or for long periods should be carefully considered due to the risk of herbal drug interactions via modulated expression of CYPs and transporters.

Study of the Expression and Function of Calcium-Sensing Receptor in Human Skeletal Muscle.

Skeletal muscle has an outstanding capacity for regeneration in response to injuries, but there are disorders in which this process is seriously impaired, such as sarcopenia. Pharmacological treatments to restore muscle trophism are not available, therefore, the identification of suitable therapeutic targets that could be useful for the treatment of skeletal reduced myogenesis is highly desirable. In this in vitro study, we explored the expression and function of the calcium-sensing receptor (CaSR) in human skeletal muscle tissues and their derived satellite cells. The results obtained from analyses with various techniques of gene and protein CaSR expression and of its secondary messengers in response to calcium (Ca2+) and CaSR drugs have demonstrated that this receptor is not present in human skeletal muscle tissues, neither in the established satellite cells, nor during in vitro myogenic differentiation. Taken together, our data suggest that, although CaSR is a very important drug target in physiology and pathology, this receptor probably does not have any physiological role in skeletal muscle in normal conditions.

Investigating the Impact of the Bit Depth of Fluorescence-Stained Images on the Performance of Deep Learning-Based Nuclei Instance Segmentation.

Nuclei instance segmentation can be considered as a key point in the computer-mediated analysis of histological fluorescence-stained (FS) images. Many computer-assisted approaches have been proposed for this task, and among them, supervised deep learning (DL) methods deliver the best performances. An important criterion that can affect the DL-based nuclei instance segmentation performance of FS images is the utilised image bit depth, but to our knowledge, no study has been conducted so far to investigate this impact. In this work, we released a fully annotated FS histological image dataset of nuclei at different image magnifications and from five different mouse organs. Moreover, by different pre-processing techniques and using one of the state-of-the-art DL-based methods, we investigated the impact of image bit depth (i.e., eight bits vs. sixteen bits) on the nuclei instance segmentation performance. The results obtained from our dataset and another publicly available dataset showed very competitive nuclei instance segmentation performances for the models trained with 8 bit and 16 bit images. This suggested that processing 8 bit images is sufficient for nuclei instance segmentation of FS images in most cases. The dataset including the raw image patches, as well as the corresponding segmentation masks is publicly available in the published GitHub repository.

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge.

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

CryoNuSeg: A dataset for nuclei instance segmentation of cryosectioned H&E-stained histological images.

Nuclei instance segmentation plays an important role in the analysis of hematoxylin and eosin (H&E)-stained images. While supervised deep learning (DL)-based approaches represent the state-of-the-art in automatic nuclei instance segmentation, annotated datasets are required to train these models. There are two main types of tissue processing protocols resulting in formalin-fixed paraffin-embedded samples (FFPE) and frozen tissue samples (FS), respectively. Although FFPE-derived H&E stained tissue sections are the most widely used samples, H&E staining of frozen sections derived from FS samples is a relevant method in intra-operative surgical sessions as it can be performed more rapidly. Due to differences in the preparation of these two types of samples, the derived images and in particular the nuclei appearance may be different in the acquired whole slide images. Analysis of FS-derived H&E stained images can be more challenging as rapid preparation, staining, and scanning of FS sections may lead to deterioration in image quality. In this paper, we introduce CryoNuSeg, the first fully annotated FS-derived cryosectioned and H&E-stained nuclei instance segmentation dataset. The dataset contains images from 10 human organs that were not exploited in other publicly available datasets, and is provided with three manual mark-ups to allow measuring intra-observer and inter-observer variabilities. Moreover, we investigate the effects of tissue fixation/embedding protocol (i.e., FS or FFPE) on the automatic nuclei instance segmentation performance and provide a baseline segmentation benchmark for the dataset that can be used in future research. A step-by-step guide to generate the dataset as well as the full dataset and other detailed information are made available to fellow researchers at https://github.com/masih4/CryoNuSeg.

Amino Acid Transporter LAT1 (SLC7A5) Mediates MeHg-Induced Oxidative Stress Defense in the Human Placental Cell Line HTR-8/SVneo.

The placental barrier can protect the fetus from contact with harmful substances. The potent neurotoxin methylmercury (MeHg), however, is very efficiently transported across the placenta. Our previous data suggested that L-type amino acid transporter (LAT)1 is involved in placental MeHg uptake, accepting MeHg-L-cysteine conjugates as substrate due to structural similarity to methionine. The aim of the present study was to investigate the antioxidant defense of placental cells to MeHg exposure and the role of LAT1 in this response. When trophoblast-derived HTR-8/SVneo cells were LAT1 depleted by siRNA-mediated knockdown, they accumulated less MeHg. However, they were more susceptible to MeHg-induced toxicity. This was evidenced in decreased cell viability at a usually noncytotoxic concentration of 0.03 µM MeHg (~6 µg/L). Treatment with ≥0.3 µM MeHg increased cytotoxicity, apoptosis rate, and oxidative stress of HTR-8/SVneo cells. These effects were enhanced under LAT1 knockdown. Reduced cell number was seen when MeHg-exposed cells were cultured in medium low in cysteine, a constituent of the tripeptide glutathione (GSH). Because LAT1-deficient HTR-8/SVneo cells have lower GSH levels than control cells (independent of MeHg treatment), we conclude that LAT1 is essential for de novo synthesis of GSH, required to counteract oxidative stress. Genetic predisposition to decreased LAT1 function combined with MeHg exposure could increase the risk of placental damage.

Expression of Melatonin Receptor 1 in Rat Mesenteric Artery and Perivascular Adipose Tissue and Vasoactive Action of Melatonin.

Melatonin is released by the pineal gland and can modulate cardiovascular system function via the G protein-coupled melatonin receptors MT1 and MT2. Most vessels are surrounded by perivascular adipose tissue (PVAT), which affects their contractility. The aim of our study was to evaluate mRNA and protein expression of MT1 and MT2 in the mesenteric artery (MA) and associated PVAT of male rats by RT-PCR and Western blot. Receptor localization was further studied by immunofluorescence microscopy. Effects of melatonin on neurogenic contractions were explored in isolated superior MA ex vivo by measurement of isometric contractile tension. MT1, but not MT2, was present in MA, and MT1 was localized mainly in vascular smooth muscle. Moreover, we proved the presence of MT1, but not MT2 receptors, in MA-associated PVAT. In isolated superior MA with intact PVAT, neuro-adrenergic contractile responses were significantly smaller when compared to arteries with removed PVAT. Pre-treatment with melatonin of PVAT-stripped arterial rings enhanced neurogenic contractions, while the potentiating effect of melatonin was not detected in preparations with preserved PVAT. We hypothesize that melatonin can stimulate the release of PVAT-derived relaxing factor(s) via MT1, which can override the direct pro-contractile effect of melatonin on vascular smooth muscle. Our results suggest that melatonin is involved in the control of vascular tone in a complex way, which is vessel specific and can reflect a sum of action on different layers of the vessel wall and surrounding PVAT.

Human placental cell line HTR-8/SVneo accumulates cadmium by divalent metal transporters DMT1 and ZIP14.

Cadmium (Cd) is a global pollutant that accumulates in the placenta and can cause placental dysfunction. Although iron transporters have been suggested to participate in placental Cd uptake, it is still unknown which transporters are actually involved in this process. We specifically aimed to study the role of three iron transporters in the uptake of Cd into the placental cell line HTR-8/SVneo. For this purpose, Divalent Metal Transporter (DMT)1 and ZRT/IRT like protein (ZIP)8 and ZIP14 were downregulated and changes in cellular Cd levels analysed in relation to controls. As clearly shown by the reduction of the Cd content by ∼60% in DMT1- and ZIP14-downregulated cells, the two proteins are essential for Cd accumulation in HTR-8/SVneo cells. Using a validated antibody, we show DMT1 to be localised in situ in trophoblast and stromal cells. We further wanted to investigate how placental cells cope with Cd loading and which metallothionein (MT) isoforms they express. Cd-exposed cells accumulate Cd in a dose-dependent manner and upregulate MT2A accordingly (up to 15-fold induction upon 5 µM CdCl2 treatment for 72 h). 5 µM Cd exposure for 72 h decreased cell number to 60%, an effect that was aggravated by MT2A depletion (cell number reduced to 30%) indicating additive effects. In conclusion, our data suggest that DMT1 and ZIP14 are required for Cd uptake into human placental cells that upregulate MT2A to store and detoxify the metal. Cd storage in the placenta reduces Cd transport to the fetus, which, however, could impair placental functions and fetal development.

The effects of skin lesion segmentation on the performance of dermatoscopic image classification.

BACKGROUND AND OBJECTIVE: Malignant melanoma (MM) is one of the deadliest types of skin cancer. Analysing dermatoscopic images plays an important role in the early detection of MM and other pigmented skin lesions. Among different computer-based methods, deep learning-based approaches and in particular convolutional neural networks have shown excellent classification and segmentation performances for dermatoscopic skin lesion images. These models can be trained end-to-end without requiring any hand-crafted features. However, the effect of using lesion segmentation information on classification performance has remained an open question. METHODS: In this study, we explicitly investigated the impact of using skin lesion segmentation masks on the performance of dermatoscopic image classification. To do this, first, we developed a baseline classifier as the reference model without using any segmentation masks. Then, we used either manually or automatically created segmentation masks in both training and test phases in different scenarios and investigated the classification performances. The different scenarios included approaches that exploited the segmentation masks either for cropping of skin lesion images or removing the surrounding background or using the segmentation masks as an additional input channel for model training. RESULTS: Evaluated on the ISIC 2017 challenge dataset which contained two binary classification tasks (i.e. MM vs. all and seborrheic keratosis (SK) vs. all) and based on the derived area under the receiver operating characteristic curve scores, we observed four main outcomes. Our results show that 1) using segmentation masks did not significantly improve the MM classification performance in any scenario, 2) in one of the scenarios (using segmentation masks for dilated cropping), SK classification performance was significantly improved, 3) removing all background information by the segmentation masks significantly degraded the overall classification performance, and 4) in case of using the appropriate scenario (using segmentation for dilated cropping), there is no significant difference of using manually or automatically created segmentation masks. CONCLUSIONS: We systematically explored the effects of using image segmentation on the performance of dermatoscopic skin lesion classification.

In vitro function and in situ localization of Multidrug Resistance-associated Protein (MRP)1 (ABCC1) suggest a protective role against methyl mercury-induced oxidative stress in the human placenta.

Methyl mercury (MeHg) is an organic highly toxic compound that is transported efficiently via the human placenta. Our previous data suggest that MeHg is taken up into placental cells by amino acid transporters while mercury export from placental cells mainly involves ATP binding cassette (ABC) transporters. We hypothesized that the ABC transporter multidrug resistance-associated protein (MRP)1 (ABCC1) plays an essential role in mercury export from the human placenta. Transwell transport studies with MRP1-overexpressing Madin-Darby Canine Kidney (MDCK)II cells confirmed the function of MRP1 in polarized mercury efflux. Consistent with this, siRNA-mediated MRP1 gene knockdown in the human placental cell line HTR-8/SVneo resulted in intracellular mercury accumulation, which was associated with reduced cell viability, accompanied by increased cytotoxicity, apoptosis, and oxidative stress as determined via the glutathione (GSH) status. In addition, the many sources claiming different localization of MRP1 in the placenta required a re-evaluation of its localization in placental tissue sections by immunofluorescence microscopy using an MRP1-specific antibody that was validated in-house. Taken together, our results show that (1) MRP1 preferentially mediates apical-to-basolateral mercury transport in epithelial cells, (2) MRP1 regulates the GSH status of placental cells, (3) MRP1 function has a decisive influence on the viability of placental cells exposed to low MeHg concentrations, and (4) the in situ localization of MRP1 corresponds to mercury transport from maternal circulation to the placenta and fetus. We conclude that MRP1 protects placental cells from MeHg-induced oxidative stress by exporting the toxic metal and by maintaining the placental cells' GSH status in equilibrium.