Izloženost genotoksičnim agensima iz životnog okoliša tijekom prenatalnog razvoja i djetinjstva

Health disorders and diseases related to environmental exposure in children such as cancer and immunologic disturbances (asthma, allergies) are on the rise. However, complex transplacental and prepubertal genotoxicology is given very limited consideration, even though intrauterine development and early childhood may be critical for elucidating the cancer aetiology. The foetus is transplacentally exposed to contaminants in food and environment such as various chemicals, drugs, radiochemically contaminated water and air. Target organs of xenobiotic action may differ between the mother and the foetus due to specific stage of developmental physiology and enzyme distribution. This in turn may lead to different levels of clastogenic and aneugenic metabolites of the same xenobiotic in the mother and the foetus. Adult’s protective behaviour is not sufficient to isolate children from radioisotopes, pesticides, toxic metals and metalloids, environmental tobacco smoke, endocrine disrupting chemicals, and various food contaminants, which are just a part of the stressors present in a polluted environment. In order to improve legislation related to foetus and child exposure to genotoxic and possibly carcinogenic agents, oncologists, paediatricians, environmental health specialists, and genotoxicologists should work together much more closely to make a more effective use of accumulated scientific data, with the final aim to lower cancer incidence and mortality.Unatoč velikim naporima da se smanji okolišna izloženost u djece se dalje bilježi trend porasta pojavnosti karcinoma i imunosnih poremećaja (astma, alergije). Premda su intrauterini razvoj i rano djetinjstvo kritično razdoblje za tumačenje etiologije nastanka karcinoma, transplacentalna i prepubertetna genotoksikologija do danas su slabo istražene. Fetus je transplacentalno izložen brojnim fizikalnim i kemijskim čimbenicima: kontaminantima iz hrane i okoliša, radiokemijski kontaminiranoj vodi, zraku te lijekovima. Ciljna tkiva za djelovanje ksenobiotika mogu biti različita u majke i fetusa zbog različitosti u razvojnoj fiziologiji i distribuciji enzima. Zbog toga u organizmu majke i fetusa mogu nastati različite razine klastogenih i aneugenih metabolita istog ksenobiotika. Zaštitna uloga odraslih u namjeri da spriječe negativne utjecaje onečišćenog okoliša na djetetovo zdravlje često je ograničena jer su radioizotopi, olovo, PCB, pasivno pušenje, živa, endokrino aktivne tvari, pesticidi i kontaminanti prisutni u svim životnim područjima tijekom razvoja i rasta djeteta. Kako bi se poboljšalo zakonodavstvo vezano uz izloženost djece genotoksičnim i vjerojatno kancerogenim tvarima, tijekom razvoja potrebna je bolja suradnja onkologa, pedijatara, stručnjaka zdravstvene ekologije i genotoksikologa. Na taj način ostvarilo bi se uspješnije iskorištavanje postojećih znanstvenih podataka u cilju smanjenja incidencije karcinoma i mortaliteta

Detection of glomeruli in renal pathology by mutual comparison of multiple staining modalities

International audienceWe evaluate the detection of glomerular structures in whole slide images (WSIs) of histopathological slides stained with multiple histochemical and immuno-histochemical staining using a convolutional neural network (CNN) based approach. We mutually compare the CNN performance on different stainings (Jones H&E, PAS, Sirius Red and CD10) and we present a novel approach to improve glomeruli detection on one staining by taking into account the classification results from differently stained consecutive sections of the same tissue. Using this integrative approach, the detection rate (F1-score) on a single stain can be improved by up to 30%

Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning

Delayed graft function (DGF) is a strong risk factor for development of interstitial fibrosis and tubular atrophy (IFTA) in kidney transplants. Quantitative assessment of inflammatory infiltrates in kidney biopsies of DGF patients can reveal predictive markers for IFTA development. In this study, we combined multiplex tyramide signal amplification (mTSA) and convolutional neural networks (CNNs) to assess the inflammatory microenvironment in kidney biopsies of DGF patients (n = 22) taken at 6 weeks post-transplantation. Patients were stratified for IFTA development (&amp;lt;10% versus &amp;gt;= 10%) from 6 weeks to 6 months post-transplantation, based on histopathological assessment by three kidney pathologists. One mTSA panel was developed for visualization of capillaries, T- and B-lymphocytes and macrophages and a second mTSA panel for T-helper cell and macrophage subsets. The slides were multi spectrally imaged and custom-made python scripts enabled conversion to artificial brightfield whole-slide images (WSI). We used an existing CNN for the detection of lymphocytes with cytoplasmatic staining patterns in immunohistochemistry and developed two new CNNs for the detection of macrophages and nuclear-stained lymphocytes. F1-scores were 0.77 (nuclear-stained lymphocytes), 0.81 (cytoplasmatic-stained lymphocytes), and 0.82 (macrophages) on a test set of artificial brightfield WSI. The CNNs were used to detect inflammatory cells, after which we assessed the peritubular capillary extent, cell density, cell ratios, and cell distance in the two patient groups. In this cohort, distance of macrophages to other immune cells and peritubular capillary extent did not vary significantly at 6 weeks post-transplantation between patient groups. CD163(+) cell density was higher in patients with &amp;gt;= 10% IFTA development 6 months post-transplantation (p &amp;lt; 0.05). CD3(+)CD8(-)/CD3(+)CD8(+) ratios were higher in patients with &amp;lt;10% IFTA development (p &amp;lt; 0.05). We observed a high correlation between CD163(+) and CD4(+)GATA3(+) cell density (R = 0.74, p &amp;lt; 0.001). Our study demonstrates that CNNs can be used to leverage reliable, quantitative results from mTSA-stained, multi spectrally imaged slides of kidney transplant biopsies. This study describes a methodology to assess the microenvironment in sparse tissue samples. Deep learning, multiplex immunohistochemistry, and mathematical image processing techniques were incorporated to quantify lymphocytes, macrophages, and capillaries in kidney transplant biopsies of delayed graft function patients. The quantitative results were used to assess correlations with development of interstitial fibrosis and tubular atrophy.Funding Agencies|ERACoSysMed initiative (project SysMIFTA) as part of the European Unions Horizon 2020 Framework Programme by ZonMw [9003035004]; German Ministry of Research and Education (BMBF)Federal Ministry of Education &amp; Research (BMBF) [FKZ031L-0085A, FKZ01ZX1710A, FKZ01ZX1608A]; Dutch Kidney Foundation (project DEEPGRAFT) [17OKG23]</p