Détermination de l'activation neuronale dans la moelle épinière par imagerie intrinsèque

Couplage entre activité neuronale et réponse hémodynamique -- Organisation neuronale de la moelle épinière -- Imagerie optique et mesure de concentration -- Imagerie par speckle et mesure de la vitesse -- Protocole chirurgical -- Instrumentation -- Manipulation du système -- Protocole de simulation -- Influence de choix de l'anesthésiant -- Analyse spatiotemporelle des données -- Analyse des données en stimulation par blocs -- Analyse des données en stimulation continue -- Validation du système -- Étude préliminaire -- Characterization of the hemodynamic and metabolic response in the in vivo rat lumbar spinal cord by intrinsic imaging -- Conséquences d'une section supérieure de la moelle -- Conséquences sur la concentration en HbR -- Conséquence sur la vitesse

Assessment of immunological features in muscle-invasive bladder cancer prognosis using ensemble learning

Funding: This research received financial support from Definiens GmbH and the Industrial Centre for AI Research in digital Diagnostics (iCAIRD) which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690].The clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes the assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quantifying immunological markers from tissue samples that can provide further insight into patient prognosis. In this paper, we apply multiplex immunofluorescence to MIBC tissue sections to capture whole-slide images and quantify potential prognostic markers related to lymphocytes, macrophages, tumour buds, and PD-L1. We propose a machine-learning-based approach for the prediction of 5 year prognosis with different combinations of image, clinical, and spatial features. An ensemble model comprising several functionally different models successfully stratifies MIBC patients into two risk groups with high statistical significance (p value < 1×10−5). Critical to improving MIBC survival rates, our method correctly classifies 71.4% of the patients who succumb to MIBC, which is significantly more than the 28.6% of the current clinical gold standard, the TNM staging system.Publisher PDFPeer reviewe

Reception of the Herzog Stjepan Vukcic Kosaca in Herzegovina in the Second Half of the 20th Century

U radu se nastoji prikazati recepcija hercega Stjepana Vukčića Kosače u Hercegovini u drugoj polovici 20. stoljeća s posebnim naglaskom na razdoblje u kojemu je Bosna i Hercegovina bila jedna od republika bivše Jugoslavije. S obzirom na činjenicu da bi se barem početno znanje o hercegu Stjepanu trebalo steći tijekom osnovnoga i srednjoškolskoga obrazovanja, najprije je dat osvrt na nastavne planove i programe u kojima su, između ostaloga, naznačeni ciljevi (zadatci) nastave povijesti, a zatim se analiziraju tekstovi u udžbenicima povijesti koji su bili u uporabi u bh. školama (osnovnim i gimnazijama), u kojima se u određenim nastavnim jedinicama obrađuje djelovanje hercega Stjepana. Sudeći prema nastavnim planovima i programima, kao i sadržaju udžbenika iz druge polovice 20. stoljeća (barem nama dostupnima), mladež u Hercegovini u razmatranom razdoblju nije mogla mnogo saznati i naučiti o ovoj povijesnoj osobi, s čijom je titulom povezano ime prostora u kojemu žive. Na kraju istražuje se hercegova prisutnost u nazivima ulica, trgova i institucija u hercegovačkim gradovima i općinama. Istraživanje pokazuje da je tek u novije vrijeme evidentan interes nekih pojedinaca i institucija koje žele ovoj povijesnoj osobi dati značenje koje joj pripada. Naime, sve ulice u Hercegovini koje nose njegovo ime, kao i jedna institucija, imenovane su nakon 1990. godine.With the aim of presenting the reception of the Herzog Stjepan Vukcic Kosaca in Hercegovina in the second half of the 20th century, the paper analyzes the contents of history textbooks that write about the life and work of the Herzog Stjepan and his presence in the names of streets, squares and institutions in Herzegovinian towns and municipalities. Considering the second half of the 20th century, most attention is paid to the period in which Bosnia and Herzegovina was one of the republics of the former Yugoslavia. To illustrate the contents from medieval history, or the ones related to Stjepan, most important are school curricula, in which, apart from the teaching units and lessons, the teaching of history was particularly indicative, when during this period the constant task was "spreading fraternity and unity" or "developing patriotic awareness among students", the emphasis being on teaching history of the "newer period". Judging by the curricula and the content of textbooks from the second half of the 20th century (at least those available to us), the youth of Herzegovina in the mentioned period could not learn much about this historical person whose name is associated with the name of the area in which they live. Namely, by looking at the texts of the textbooks up to the 90s, it is evident that the texts in the textbooks differ, both in scope and emphasis on certain facts. What all the authors mention is taking of the \u27Herzog\u27 title in 1448 and the fall of Herzegovina under the Ottoman rule, whereas all the other facts about the Herzog Stjepan vary from one text to another. As there were no official textbooks in the region of Herzegovina in the 90s of the 20th century, the paper, as an example, presents the texts only from two textbooks (one for elementary school and the other for grammar school) used in some schools in Herzegovina which worked according to the Croatian curriculum, where we can find hardly any information about the Herzog Stjepan. Finally, the results of the research of the Herzog\u27s presence in the names of streets, squares and institutions of the Herzegovinian cities and municipalities show that the interest of some individuals and institutions, who want to give this historical person the significance he deserves, has only recently become evident. Namely, all the streets in Herzegovina named after the Herzog, as well as one institution, got this name after 1990

In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium

Scattered inflammatory cells are commonly observed in mammary gland tissue, most likely in response to normal cell turnover by proliferation and apoptosis, or as part of immunosurveillance. In contrast, lymphocytic lobulitis (LLO) is a recurrent inflammation pattern, characterized by lymphoid cells infiltrating lobular structures, that has been associated with increased familial breast cancer risk and immune responses to clinically manifest cancer. The mechanisms and pathogenic implications related to the inflammatory microenvironment in breast tissue are still poorly understood. Currently, the definition of inflammation is mainly descriptive, not allowing a clear distinction of LLO from physiological immunological responses and its role in oncogenesis remains unclear. To gain insights into the prognostic potential of inflammation, we developed an agent-based model of immune and epithelial cell interactions in breast lobular epithelium. Physiological parameters were calibrated from breast tissue samples of women who underwent reduction mammoplasty due to orthopedic or cosmetic reasons. The model allowed to investigate the impact of menstrual cycle length and hormone status on inflammatory responses to cell turnover in the breast tissue. Our findings suggested that the immunological context, defined by the immune cell density, functional orientation and spatial distribution, contains prognostic information previously not captured by conventional diagnostic approaches. Several studies provided conclusive evidence that a delicate balance between mammary epithelial cell proliferation and apoptosis regulates homeostasis in the healthy breast tissue 1-7. After menarche, and in the absence of pregnancy, the adult female mammary gland is subjected to cyclic fluctuations depending on hormonal stimulation 1,8. In response to such systemic hormonal changes, the breast epithelium undergoes a tightly regulated sequence of cell proliferation and apoptosis during each ovarian/menstrual cycle 1-3. The peak of epithelial cell proliferation has been reported to occur during the luteal phase, suggesting a synergistic influence of steroid hormones, such as estrogen and progesterone 2-5. In turn, the peak of apoptotic activity would be expected in response to decreasing hormone levels towards the end of the menstrual cycle 2-5. However, recent histologic findings indicate that apoptosis reaches its maximum levels in the middle of the luteal phase, although there is also a peak at about the third day of the menstrual cycle 6,7. Experimental measurements of cell turnover, i.e. programmed cell death and proliferation, demonstrated that an imbalance between the mitotic and apoptotic activity might lead to malignant transformation of epithelial cells and tumorigenic processes 9-11. Indeed, excessive cell proliferation promotes accumulation of DNA damage due to insufficient timely repair and mutations 12,13. There is also recent evidence that hormones suppress effective DNA repair and alter DNA damage response (DDR) 13-15

Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis

Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine learning-based methodology was applied to accurately quantify tumour buds across immunofluorescence labelled whole slide images from 100 muscle invasive bladder cancer patients. Furthermore, tumour budding was found to be correlated to TNM (p = 0.00089) and pT (p = 0.0078) staging. A novel classification and regression tree model was constructed to stratify all stage II, III, and IV patients into three new staging criteria based on disease specific survival. For the stratification of non-metastatic patients into high or low risk of disease specific death, our decision tree model reported that tumour budding was the most significant feature (HR = 2.59, p = 0.0091), and no clinical feature was utilised to categorise these patients. Our findings demonstrate that tumour budding, quantified using automated image analysis provides prognostic value for muscle invasive bladder cancer patients and a better model fit than TNM staging.Publisher PDFPeer reviewe

Tissue Phenomics for prognostic biomarker discovery in low- and intermediate-risk prostate cancer

Tissue Phenomics is the discipline of mining tissue images to identify patterns that are related to clinical outcome providing potential prognostic and predictive value. This involves the discovery process from assay development, image analysis, and data mining to the final interpretation and validation of the findings. Importantly, this process is not linear but allows backward steps and optimization loops over multiple sub-processes. We provide a detailed description of the Tissue Phenomics methodology while exemplifying each step on the application of prostate cancer recurrence prediction. In particular, we automatically identified tissue-based biomarkers having significant prognostic value for low-and intermediate-risk prostate cancer patients (Gleason scores 6-7b) after radical prostatectomy. We found that promising phenes were related to CD8(+) and CD68(+) cells in the microenvironment of cancerous glands in combination with the local micro-vascularization. Recurrence prediction based on the selected phenes yielded accuracies up to 83% thereby clearly outperforming prediction based on the Gleason score. Moreover, we compared different machine learning algorithms to combine the most relevant phenes resulting in increased accuracies of 88% for tumor progression prediction. These findings will be of potential use for future prognostic tests for prostate cancer patients and provide a proof-of-principle of the Tissue Phenomics approach