Toxicological Characterization of the Inorganic and Organic Arsenic Metabolite Thio-DMAV in Cultured Human Lung Cells

We synthesised and toxicologically characterised the arsenic metabolite thiodimethylarsinic acid (thio-DMAV). Successful synthesis of highly pure thio-DMAV was confirmed by state-of-the-art analytical techniques including 1H-NMR, HPLC-FTMS, and HPLC-ICPMS. Toxicological characterization was carried out in comparison to arsenite and its well-known trivalent and pentavalent methylated metabolites. It comprised cellular bioavailability as well as different cytotoxicity and genotoxicity end points in cultured human A549 lung cells. Of all arsenicals investigated, thio-DMAV exerted the strongest cytotoxicity. Moreover, thio-DMAV did not induce DNA strand breaks and an increased induction of both micronuclei and multinucleated cells occurred only at beginning cytotoxic concentrations, indicating that thio-DMAV does not act via a genotoxic mode of action. Finally, to assess potential implications of thio-DMAV for human health, further mechanistic studies are urgently necessary to identify the toxic mode of action of this highly toxic, unusual pentavalent organic arsenical

Phenomenological description of the nonlocal magnetization relaxation in magnonics, spintronics, and domain-wall dynamics

A phenomenological equation called Landau-Lifshitz-Baryakhtar (LLBar) equation, which could be viewed as the combination of Landau-Lifshitz (LL) equation and an extra "exchange damping" term, was derived by Baryakhtar using Onsager's relations. We interpret the origin of this "exchange damping" as nonlocal damping by linking it to the spin current pumping. The LLBar equation is investigated numerically and analytically for the spin wave decay and domain wall motion. Our results show that the lifetime and propagation length of short-wavelength magnons in the presence of nonlocal damping could be much smaller than those given by LL equation. Furthermore, we find that both the domain wall mobility and the Walker breakdown field are strongly influenced by the nonlocal damping.Comment: 10 pages, 6 figure

Toxicological Characterization of the Inorganic and Organic Arsenic Metabolite Thio-DMAV in Cultured Human Lung Cells

We synthesised and toxicologically characterised the arsenic metabolite thiodimethylarsinic acid (thio-DMAV). Successful synthesis of highly pure thio-DMAV was confirmed by state-of-the-art analytical techniques including 1H-NMR, HPLC-FTMS, and HPLC-ICPMS. Toxicological characterization was carried out in comparison to arsenite and its well-known trivalent and pentavalent methylated metabolites. It comprised cellular bioavailability as well as different cytotoxicity and genotoxicity end points in cultured human A549 lung cells. Of all arsenicals investigated, thio-DMAV exerted the strongest cytotoxicity. Moreover, thio-DMAV did not induce DNA strand breaks and an increased induction of both micronuclei and multinucleated cells occurred only at beginning cytotoxic concentrations, indicating that thio-DMAV does not act via a genotoxic mode of action. Finally, to assess potential implications of thio-DMAV for human health, further mechanistic studies are urgently necessary to identify the toxic mode of action of this highly toxic, unusual pentavalent organic arsenical.

Computer-assisted mitotic count using a deep learning–based algorithm improves interobserver reproducibility and accuracy

The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress in the field of artificial intelligence has allowed the development of high-performance algorithms that may improve standardization of the MC. As algorithmic predictions are not flawless, computer-assisted review by pathologists may ensure reliability. In the present study, we compared partial (MC-ROI preselection) and full (additional visualization of MF candidates and display of algorithmic confidence values) computer-assisted MC analysis to the routine (unaided) MC analysis by 23 pathologists for whole-slide images of 50 canine cutaneous mast cell tumors (ccMCTs). Algorithmic predictions aimed to assist pathologists in detecting mitotic hotspot locations, reducing omission of MFs, and improving classification against imposters. The interobserver consistency for the MC significantly increased with computer assistance (interobserver correlation coefficient, ICC = 0.92) compared to the unaided approach (ICC = 0.70). Classification into prognostic stratifications had a higher accuracy with computer assistance. The algorithmically preselected hotspot MC-ROIs had a consistently higher MCs than the manually selected MC-ROIs. Compared to a ground truth (developed with immunohistochemistry for phosphohistone H3), pathologist performance in detecting individual MF was augmented when using computer assistance (F1-score of 0.68 increased to 0.79) with a reduction in false negatives by 38%. The results of this study demonstrate that computer assistance may lead to more reproducible and accurate MCs in ccMCTs

Double trouble:Bacillus depends on a functional Tat machinery to avoid severe oxidative stress and starvation upon entry into a NaCl-depleted environment

The widely conserved twin-arginine translocases (Tat) allow the transport of fully folded cofactor-containing proteins across biological membranes. In doing so, these translocases serve different biological functions ranging from energy conversion to cell division. In the Gram-positive soil bacterium Bacillus subtilis, the Tat machinery is essential for effective growth in media lacking iron or NaCl. It was previously shown that this phenomenon relates to the Tat-dependent export of the heme-containing peroxidase EfeB, which converts Fe2+ to Fe3+ at the expense of hydrogen peroxide. However, the reasons why the majority of tat mutant bacteria perish upon dilution in NaCl-deprived medium and how, after several hours, a sub-population adapts to this condition was unknown. Here we show that, upon growth in the absence of NaCl, the bacteria face two major problems, namely severe oxidative stress at the membrane and starvation leading to death. The tat mutant cells can overcome these challenges if they are fed with arginine, which implies that severe arginine depletion is a major cause of death and resumed arginine synthesis permits their survival. Altogether, our findings show that the Tat system of B. subtilis is needed to preclude severe oxidative stress and starvation upon sudden drops in the environmental Na+ concentration as caused by flooding or rain

Alcohol consumption and liver phenotype of individuals with alpha‐1 antitrypsin deficiency

Background and Aims: Alpha‐1 antitrypsin deficiency is an inherited disorder caused by alpha‐1 antitrypsin (AAT) mutations. We analysed the association between alcohol intake and liver‐related parameters in individuals with the heterozygous/homozygous Pi*Z AAT variant (Pi*MZ/Pi*ZZ genotype) found in the United Kingdom Biobank and the European Alpha1 liver consortium. Methods: Reported alcohol consumption was evaluated in two cohorts: (i) the community‐based United Kingdom Biobank (17 145 Pi*MZ, 141 Pi*ZZ subjects, and 425 002 non‐carriers [Pi*MM]); and (ii) the European Alpha1 liver consortium (561 Pi*ZZ individuals). Cohort (ii) included measurements of carbohydrate‐deficient transferrin (CDT). Results: In both cohorts, no/low alcohol intake was reported by &gt;80% of individuals, while harmful consumption was rare (~1%). Among Pi*MM and Pi*MZ individuals from cohort (i), moderate alcohol consumption resulted in a &lt;30% increased rate of elevated transaminases and ~50% increase in elevated gamma-glutamyl transferase values, while harmful alcohol intake led to an at least twofold increase in the abnormal levels. In Pi*ZZ individuals from both cohorts, moderate alcohol consumption had no marked impact on serum transaminase levels. Among Pi*ZZ subjects from cohort (ii) who reported no/low alcohol consumption, those with increased CDT levels more often had signs of advanced liver disease.Conclusions: Pi*MZ/Pi*ZZ genotype does not seem to markedly aggravate the hepatic toxicity of moderate alcohol consumption. CDT values might be helpful to detect alcohol consumption in those with advanced fibrosis. More data are needed to evaluate the impact of harmful alcohol consumption.<br/

Nuclear Morphometry using a Deep Learning-based Algorithm has Prognostic Relevance for Canine Cutaneous Mast Cell Tumors

Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics (morphometry) can improve reproducibility, but manual methods are time consuming. In this study, we evaluated fully automated morphometry using a deep learning-based algorithm in 96 canine cutaneous mast cell tumors with information on patient survival. Algorithmic morphometry was compared with karyomegaly estimates by 11 pathologists, manual nuclear morphometry of 12 cells by 9 pathologists, and the mitotic count as a benchmark. The prognostic value of automated morphometry was high with an area under the ROC curve regarding the tumor-specific survival of 0.943 (95% CI: 0.889 - 0.996) for the standard deviation (SD) of nuclear area, which was higher than manual morphometry of all pathologists combined (0.868, 95% CI: 0.737 - 0.991) and the mitotic count (0.885, 95% CI: 0.765 - 1.00). At the proposed thresholds, the hazard ratio for algorithmic morphometry (SD of nuclear area $\geq 9.0 \mu m^2$) was 18.3 (95% CI: 5.0 - 67.1), for manual morphometry (SD of nuclear area $\geq 10.9 \mu m^2$) 9.0 (95% CI: 6.0 - 13.4), for karyomegaly estimates 7.6 (95% CI: 5.7 - 10.1), and for the mitotic count 30.5 (95% CI: 7.8 - 118.0). Inter-rater reproducibility for karyomegaly estimates was fair ($\kappa$ = 0.226) with highly variable sensitivity/specificity values for the individual pathologists. Reproducibility for manual morphometry (SD of nuclear area) was good (ICC = 0.654). This study supports the use of algorithmic morphometry as a prognostic test to overcome the limitations of estimates and manual measurements

Chromosome 10q26-driven age-related macular degeneration is associated with reduced levels of HTRA1 in human retinal pigment epithelium

Genome-wide association studies have identified the chromosome 10q26 (Chr10) locus, which contains the age-related maculopathy susceptibility 2 (ARMS2) and high temperature requirement A serine peptidase 1 (HTRA1) genes, as the strongest genetic risk factor for age-related macular degeneration (AMD) [L.G. Fritsche et al., Annu. Rev. Genomics Hum. Genet. 15, 151–171, (2014)]. To date, it has been difficult to assign causality to any specific single nucleotide polymorphism (SNP), haplotype, or gene within this region because of high linkage disequilibrium among the disease-associated variants [J. Jakobsdottir et al. Am. J. Hum. Genet. 77, 389–407 (2005); A. Rivera et al. Hum. Mol. Genet. 14, 3227–3236 (2005)]. Here, we show that HTRA1 messenger RNA (mRNA) is reduced in retinal pigment epithelium (RPE) but not in neural retina or choroid tissues derived from human donors with homozygous risk at the 10q26 locus. This tissue-specific decrease is mediated by the presence of a noncoding, cis-regulatory element overlapping the ARMS2 intron, which contains a potential Lhx2 transcription factor binding site that is disrupted by risk variant rs36212733. HtrA1 protein increases with age in the RPE–Bruch’s membrane (BM) interface in Chr10 nonrisk donors but fails to increase in donors with homozygous risk at the 10q26 locus. We propose that HtrA1, an extracellular chaperone and serine protease, functions to maintain the optimal integrity of the RPE–BM interface during the aging process and that reduced expression of HTRA1 mRNA and protein in Chr10 risk donors impairs this protective function, leading to increased risk of AMD pathogenesis. HtrA1 augmentation, not inhibition, in high-risk patients should be considered as a potential therapy for AMD

Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility

The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.e., anisokaryosis and/or shape) using a segmentation model. Its performance was evaluated on 46 cPC cases with comprehensive follow-up data regarding its accuracy in nuclear segmentation and its prognostic ability. Its assessment of NP was compared to manual morphometry and established prognostic tests (pathologists’ NP estimates (n = 11), mitotic count, histological grading, and TNM-stage). The standard deviation (SD) of the nuclear area, indicative of anisokaryosis, exhibited good discriminatory ability for tumor-specific survival, with an area under the curve (AUC) of 0.80 and a hazard ratio (HR) of 3.38. The algorithm achieved values comparable to manual morphometry. In contrast, the pathologists’ estimates of anisokaryosis resulted in HR values ranging from 0.86 to 34.8, with slight inter-observer reproducibility (k = 0.204). Other conventional tests had no significant prognostic value in our study cohort. Fully automated morphometry promises a time-efficient and reproducible assessment of NP with a high prognostic value. Further refinement of the algorithm, particularly to address undersegmentation, and application to a larger study population are required