Bayesian Hierarchical Modeling and Application to Greenlab Model of Plant Growth

Η μοντελοποίηση ανάπτυξης φυτών έχει έχει σημειώσει σημαντική πρόοδο τις τελευταίες δύο δεκαετίες. Ο κύριος στόχος της μοντελοποίησης ανάπτυξης φυτών είναι η προσομοίωση της ανάπτυξης του φυτού όσο το δυνατόν πιο ρεαλιστικά. Αυτή η εργασία θα παρουσιάσει το μοντέλο Greenlab, περιγράφοντας την ανάπ- τυξη των φυτών μέσω ενός μαθηματικού πλαισίου, και θα παρουσιάσουμε περαιτέρω μεθόδους εκτίμησης σε τέτοια μοντέλα. Το πρώτο κεφάλαιο αυτής της εργασίας περιγράφει τη φυσιολογία των φυτών και τις κύριες διαδικασίες που καθορίζουν την ανάπτυξη των φυτών, όπως η φωτοσύνθεση. Το δεύτερο κεφάλαιο εισάγει τον αναγνώστη στην πλατφόρμα του φαινοσκοπίου και στην έννοια του θερμικού χρόνου. Και τα δύο εί- ναι απαραίτητα στοιχεία για την ανάλυσή μας στη συνέχεια. Η πλατφόρμα του φαινοσκοπίου μας παρέχει δεδομένα για την επικύρωση της ακρίβειας του μοντέλου μας. Ταυτόχρονα, ο θερμικός χρόνος είναι μια κεντρική έννοια που καθορίζει την ανάπτυξη των φυτών. Στο τρίτο κεφάλαιο παρουσιάζονται το μαθηματικο πλαισιο που περιγραφει την ανάπτυξη φυτών και όλες οι στατιστικές μέθοδοι που χρησιμοποιούμε για τη μοντελοποίησή μας και την εκτίμηση των ποσοτήτων εν- διαφέροντος. Κυρίως, εξηγούμε πώς το Greenlab μπορεί να αναπαρασταθεί ως μοντέλο χώρου κατάστασης και στη συνέχεια παρουσιάζουμε τις μεθόδους εκτίμησης που χρησιμοποιούμε σε αυτό το πλαίσιο. Το τέ- ταρτο κεφάλαιο αποτελείται από δύο μέρη. Αρχικά, προσομοιώσαμε δεδομένα χρησιμοποιώντας το μοντέλο Greenlab για Arabidospis Thaliana και τα χρησιμοποιήσαμε για να επικυρώσουμε τα αποτελέσματα των εκτιμήσεών μας. Στο δεύτερο μέρος, επαναλάβαμε τα ίδια βήματα, αλλά αυτή τη φορά χρησιμοποιήσαμε πραγματικά δεδομένα που ελήφθησαν από το φαινοσκόπιο. Τέλος, στο κεφάλαιο πέντε, αναθεωρούμε εν συντομία τα κύρια σημεία αυτής της εργασίας και παρουσιάζουμε προοπτικές για πιθανή πρόοδο στον τομέα της ανάπτυξης των φυτών.Plant growth modeling has made significant progress in the past two decades. The main goal of plant growth modeling is to simulate the plant’s growth as realistically as possible. This work will present the Greenlab model, describing plant growth through a mathematical framework, and we will further present estimation methods in such models. The first chapter of this work describes pants physiology and the main processes determining plant growth, such as photosynthesis. The second chapter introduces the reader to the phenoscope platform and the concept of thermal time. Both of them are essential components for our analysis afterward. The phenoscope platform provides us with data to validate the accuracy of our model. At the same time, thermal time is a central notion that determines plant development. In the third chapter, we present all the mathematical formulations of plant growth and all the statistical methods we use for our modelization and the estimation of quantities of interest. Mainly, we explain how Greenlab can be represented as a state space model, and then we present the estima- tion methods we use within this framework. The fourth chapter consists of two parts. Initially, we simulated data using the Greenlab for Arabidospis Thaliana model, and we used them to validate the results of our estimations. In the second part, we repeated the same steps, but this time we used real data obtained from the phenoscope. Lastly, in chapter five, we briefly revise the main points of this work and illustrate perspectives for potential progress in the field of plant growth

A Case Report of Pulmonary Exacerbation after Initiation of Lumacaftor/Ivacaftor Therapy in a CF Female with Complicated Lung Disease

Novel targeted treatments for Cystic Fibrosis give rise to new hope for an ever-growing number of CF patients with various mutations. However, very little evidence and guidelines exist to steer clinical decisions regarding patients whose illness takes an unexpected course. In such cases, the benefits and risks of discontinuing these treatments must be carefully and individually weighed, since their long-term effects remain mainly uncharted territory. In this report we document the case of a homozygous F508del CF patient with severe lung disease who presented with a pulmonary exacerbation shortly after the beginning of treatment with lumacaftor/ivacaftor and the complicated initial phase of therapy, which was followed by significant improvements

Tissue-Based Diagnostic Biomarkers of Aggressive Variant Prostate Cancer: A Narrative Review

Prostate cancer (PC) is a common malignancy among elderly men, characterized by great heterogeneity in its clinical course, ranging from an indolent to a highly aggressive disease. The aggressive variant of prostate cancer (AVPC) clinically shows an atypical pattern of disease progression, similar to that of small cell PC (SCPC), and also shares the chemo-responsiveness of SCPC. The term AVPC does not describe a specific histologic subtype of PC but rather the group of tumors that, irrespective of morphology, show an aggressive clinical course, dictated by androgen receptor (AR) indifference. AR indifference represents an adaptive response to androgen deprivation therapy (ADT), driven by epithelial plasticity, an inherent ability of tumor cells to adapt to their environment by changing their phenotypic characteristics in a bi-directional way. The molecular profile of AVPC entails combined alterations in the tumor suppressor genes retinoblastoma protein 1 (RB1), tumor protein 53 (TP53), and phosphatase and tensin homolog (PTEN). The understanding of the biologic heterogeneity of castration-resistant PC (CRPC) and the need to identify the subset of patients that would potentially benefit from specific therapies necessitate the development of prognostic and predictive biomarkers. This review aims to discuss the possible pathophysiologic mechanisms of AVPC development and the potential use of emerging tissue-based biomarkers in clinical practice

Comparison between lornoxicam quick-release and parecoxib for post-operative analgesia after laparoscopic cholecystectomy: A prospective randomized, placebo-controlled trial

Background: Non-steroidal anti-inflammatory drugs (NSAIDs) are valuable for post-operative pain as they reduce the use of opioids. Cyclooxygenase-2 inhibitors and traditional NSAIDs can be used. This is a prospective, randomized, placebo-controlled trial to study the efficacy and the safety of the oral administration of lornoxicam quick release tablets versus intravenously administered parecoxib for the management of pain after laparoscopic cholecystectomy (LC). Materials and Methods: One hundred and eight patients, American Society of Anesthesiologists I-II, were randomized to either group A (n = 36): Lornoxicam quick-release 8 mg PO, group B (n = 36): Parecoxib 40 mg intravenous (IV) or group C (n = 36) placebo, for post-operative analgesia, 30 min before the operation and 12 and 24 h post-operatively. All patients received a standard dose of meperidine 1 mg/kg intramuscularly before the incision and post-operatively as rescue analgesia, when visual analog scale (VAS) pain score was >4. Pain at rest and on movement was assessed at 20 min, 3, 6, 12, 18 and 24 h post-operatively. Total meperidine administration and adverse events were also recorded. Results: There were significantly lower VAS pain scores at 20 min, 3, 6, 12 and 18 h at rest or with movement in the lornoxicam quick release and parecoxib groups compared with the placebo group. The number of patients requiring rescue analgesia (meperidine) was significantly higher in the placebo group (P = 0.001). The average dose of meperidine administered was significantly higher in the placebo group, both at 20 min (P = 0.013/0.007) and 24 h (P = 0.037/0.023) post-operatively. VAS scores and meperidine requirements were similar in patients who received lornoxicam or parecoxib. Conclusions: Parecoxib 40 mg IV and lornoxicam quick-release 8 mg PO every 12 h are equivalent adjuvant analgesics with a greater efficacy than placebo for post-operative analgesia in patients undergoing LC