Explainable AI-based identification of contributing factors to the mood state change in children and adolescents with pre-existing psychiatric disorders in the context of COVID-19-related lockdowns in Greece

The COVID-19 pandemic and its accompanying restrictions have significantly impacted people’s lives globally. There is an increasing interest in examining the influence of this unprecedented situation on our mental well-being, with less attention towards the impact of the elongation of COVID-19-related measures on youth with a pre-existing psychiatric/developmental disorder. The majority of studies focus on individuals, such as students, adults, and youths, among others, with little attention being given to the elongation of COVID-19-related measures and their impact on a special group of individuals, such as children and adolescents with diagnosed developmental and psychiatric disorders. In addition, most of these studies adopt statistical methodologies to identify pair-wise relationships among factors, an approach that limits the ability to understand and interpret the impact of various factors. In response, this study aims to adopt an explainable machine learning approach to identify factors that explain the deterioration or amelioration of mood state in a youth clinical sample. The purpose of this study is to identify and interpret the impact of the greatest contributing features of mood state changes on the prediction output via an explainable machine learning pipeline. Among all the machine learning classifiers, the Random Forest model achieved the highest effectiveness, with 76% best AUC-ROC Score and 13 features. The explainability analysis showed that stress or positive changes derived from the imposing restrictions and COVID-19 pandemic are the top two factors that could affect mood state

Exercise rehabilitation after hip or knee joint replacement: The effects of illness representations and self-efficacy on adherence, physical recovery and emotional well-being

Joint replacements are effective surgical interventions, yet some patients report experiencing ongoing physical and psychological symptoms post-operatively. An important parameter of recovery is exercise rehabilitation, yet little is known about the role of adherence in patient outcomes. Guided by the Common Sense Model and the Social Cognitive Theory the aim of this thesis was: (a) to identify determinants of exercise adherence, physical and emotional outcomes (b) and to examine whether adherence mediates the relationships between determinants and outcomes. In order to address these objectives a longitudinal study was first conducted. Osteoarthritis patients undergoing total hip and knee replacements (T1, n=54) were assessed at pre-surgery and at six weeks and nine months after surgery (T3, n=40). As determinants of adherence are multifactorial, factors that influence exercise adherence were further explored from a patients’ (n=8), and physiotherapists’ (n=5) perspective in a qualitative study using focus groups. A systematic review indicated that post-operative self-efficacy is a more consistent predictor of outcomes compared to pre-operative self-efficacy. Before surgery, emotional health was related to negative emotional reactions and strong beliefs of general self-efficacy while pre-operative physical status was associated with higher perceived illness identity and general self-efficacy. In a time-frame from baseline to nine months following surgery physical outcomes improved, exercise adherence decreased, emotional health remained stable while changes in patients’ cognitions and emotions were variable. Subsequently, changes in cognitions and emotions influenced post-operative outcomes. Early decrease in general self-efficacy and increase in consequences predicted early emotional outcomes while late changes in emotional representations and general self-efficacy predicted late emotional indicators. Early increase in chronic timeline perceptions and decrease in challenge emotion predicted early adherence while decrease in early personal control predicted lower late adherence. Increase in perceived consequences was the most consistent predictor of early functional outcomes whereas late increase in rehabilitation self-efficacy was the most consistent predictor of late physical outcomes. The mediation hypotheses were not confirmed. The qualitative study indicated a number of factors relating to the health care system-, health care professional- and patient level that may contribute to patients’ exercise adherence. The findings of the series of studies presented have implications in terms of the content and the implementation timing of future interventions aiming to optimize outcomes in this group of patients

Exercise rehabilitation after hip or knee joint replacement: The effects of illness representations and self-efficacy on adherence, physical recovery and emotional well-being

Joint replacements are effective surgical interventions, yet some patients report experiencing ongoing physical and psychological symptoms post-operatively. An important parameter of recovery is exercise rehabilitation, yet little is known about the role of adherence in patient outcomes. Guided by the Common Sense Model and the Social Cognitive Theory the aim of this thesis was: (a) to identify determinants of exercise adherence, physical and emotional outcomes (b) and to examine whether adherence mediates the relationships between determinants and outcomes. In order to address these objectives a longitudinal study was first conducted. Osteoarthritis patients undergoing total hip and knee replacements (T1, n=54) were assessed at pre-surgery and at six weeks and nine months after surgery (T3, n=40). As determinants of adherence are multifactorial, factors that influence exercise adherence were further explored from a patients’ (n=8), and physiotherapists’ (n=5) perspective in a qualitative study using focus groups. A systematic review indicated that post-operative self-efficacy is a more consistent predictor of outcomes compared to pre-operative self-efficacy. Before surgery, emotional health was related to negative emotional reactions and strong beliefs of general self-efficacy while pre-operative physical status was associated with higher perceived illness identity and general self-efficacy. In a time-frame from baseline to nine months following surgery physical outcomes improved, exercise adherence decreased, emotional health remained stable while changes in patients’ cognitions and emotions were variable. Subsequently, changes in cognitions and emotions influenced post-operative outcomes. Early decrease in general self-efficacy and increase in consequences predicted early emotional outcomes while late changes in emotional representations and general self-efficacy predicted late emotional indicators. Early increase in chronic timeline perceptions and decrease in challenge emotion predicted early adherence while decrease in early personal control predicted lower late adherence. Increase in perceived consequences was the most consistent predictor of early functional outcomes whereas late increase in rehabilitation self-efficacy was the most consistent predictor of late physical outcomes. The mediation hypotheses were not confirmed. The qualitative study indicated a number of factors relating to the health care system-, health care professional- and patient level that may contribute to patients’ exercise adherence. The findings of the series of studies presented have implications in terms of the content and the implementation timing of future interventions aiming to optimize outcomes in this group of patients

Omics Analysis of Chemoresistant Triple Negative Breast Cancer Cells Reveals Novel Metabolic Vulnerabilities

The emergence of drug resistance in cancer poses the greatest hurdle for successful therapeutic results and is associated with most cancer deaths. In triple negative breast cancer (TNBC), due to the lack of specific therapeutic targets, systemic chemotherapy is at the forefront of treatments, but it only benefits a fraction of patients because of the development of resistance. Cancer cells may possess an innate resistance to chemotherapeutic agents or develop new mechanisms of acquired resistance after long-term drug exposure. Such mechanisms involve an interplay between genetic, epigenetic and metabolic alterations that enable cancer cells to evade therapy. In this work, we generated and characterized a chemoresistant TNBC cell line to be used for the investigation of mechanisms that drive resistance to paclitaxel. Transcriptomic analysis highlighted the important role of metabolic-associated pathways in the resistant cells, prompting us to employ 1H-NMR to explore the metabolome and lipidome of these cells. We identified and described herein numerous metabolites and lipids that were significantly altered in the resistant cells. Integrated analysis of our omics data revealed MSMO1, an intermediate enzyme of cholesterol biosynthesis, as a novel mediator of chemoresistance in TNBC. Overall, our data provide a critical insight into the metabolic adaptations that accompany acquired resistance in TNBC and pinpoint potential new targets

Does self-efficacy influence recovery and well-being in osteoarthritis patients undergoing joint replacement? A systematic review

Objective: To investigate the role of self-efficacy in functional recovery and well-being outcomes in osteoarthritis patients, undergoing hip or knee replacement surgery. Data sources: Studies were identified using MEDLINE via PUB med, PsycINFO and CINAHL from inception to July 2013. Methods: Three search strategies that combined key terms of ‘self-efficacy’, ‘functional recovery’, ‘well-being’ and ‘joint replacement’ were applied. Titles and abstracts were screened for eligibility and, accordingly, potentially eligible studies were retrieved for review. Included studies were assessed in terms of their quality, and data were extracted by two independent reviewers. A narrative synthesis of results was conducted. Results: In total, 836 articles were identified and after electronic de-duplication, 708 articles remained. After screening 15 articles were retrieved as potentially eligible and eight articles were included in the review. Of the eight studies (n = 967 patients), seven had a prospective design and all studies were considered of good quality. No fully conclusive evidence for the influence of self-efficacy upon functional recovery outcomes was found. When the timing of self-efficacy measurement was examined, post-operative self-efficacy was found to be related to functional recovery outcomes. Conclusion: Presurgical self-efficacy was the least consistent predictor of functional outcomes while postoperative self-efficacy was more consistently associated with recovery outcomes such as longer distance ambulation, exercise repetition and frequency, walking speed and disability

Explainable AI-based identification of contributing factors to the mood state change of children and adolescents with pre-existing psychiatric disorders in the context of COVID-19 related lockdowns in Greece

The COVID-19 pandemic and accompanying restrictions have significantly impacted lives globally. There is an increasing interest in examining the influence of this unprecedented situation on our mental well-being, with less attention towards the impact of elongation of COVID-19 related measures on youth with a pre-existing psychiatric/developmental disorder. The majority of studies are focusing on individuals, such as students, adults, youths, among others, with little attention to be given to the elongation of COVID-19 related measures and their impact to a special group of individuals, such as children and adolescents with diagnosed developmental and psychiatric disorders. In addition, most of these studies adopt statistical methodologies to identify pair-wise relationships among factors, an approach that limits the ability to understand and interpret the impact of various factors. In response, this study aims to adopt an explainable machine learning approach to identify factors that explain the deterioration or amelioration of mood state in youth clinical sample. The purpose of this study is to identify and interpret the impact of the most contributing features of mood states change to the prediction output, via an explainable machine learning pipeline. Among all the machine learning classifiers, Random Forest model achieved the highest accuracy, with 76% Best AUC-ROC Score and 13 features. Explainability analysis showed that stress or positive changes derived from the imposing restrictions and COVID-19 pandemic are the top two factors that could affect mood state

Correction: Ntakolia et al. An Explainable Machine Learning Approach for COVID-19’s Impact on Mood States of Children and Adolescents during the First Lockdown in Greece. <i>Healthcare</i> 2022, <i>10</i>, 149

Argyris Stringaris was initially included as an author in the original publication [...

An Explainable Machine Learning Approach for COVID-19’s Impact on Mood States of Children and Adolescents during the First Lockdown in Greece

The global spread of COVID-19 led the World Health Organization to declare a pandemic on 11 March 2020. To decelerate this spread, countries have taken strict measures that have affected the lifestyles and economies. Various studies have focused on the identification of COVID-19’s impact on the mental health of children and adolescents via traditional statistical approaches. However, a machine learning methodology must be developed to explain the main factors that contribute to the changes in the mood state of children and adolescents during the first lockdown. Therefore, in this study an explainable machine learning pipeline is presented focusing on children and adolescents in Greece, where a strict lockdown was imposed. The target group consists of children and adolescents, recruited from children and adolescent mental health services, who present mental health problems diagnosed before the pandemic. The proposed methodology imposes: (i) data collection via questionnaires; (ii) a clustering process to identify the groups of subjects with amelioration, deterioration and stability to their mood state; (iii) a feature selection process to identify the most informative features that contribute to mood state prediction; (iv) a decision-making process based on an experimental evaluation among classifiers; (v) calibration of the best-performing model; and (vi) a post hoc interpretation of the features’ impact on the best-performing model. The results showed that a blend of heterogeneous features from almost all feature categories is necessary to increase our understanding regarding the effect of the COVID-19 pandemic on the mood state of children and adolescents

From Drug Delivery Systems to Drug Release, Dissolution, IVIVC, BCS, BDDCS, Bioequivalence and Biowaivers

This is a summary report of the conference on drug absorption and bioequivalence issues held in Titania Hotel in Athens (Greece) from the 28(th) to the 30(th) of May 2009. The conference included presentations which were mainly divided into three sections. The first section focused on modern drug delivery systems such as polymer nanotechnology, cell immobilization techniques to deliver drugs into the brain, nanosized liposomes used in drug eluting stents, encapsulation of drug implants in biocompatible polymers, and application of differential scanning calorimetry as a tool to study liposomal stability. The importance of drug release and dissolution were also discussed by placing special emphasis on camptothecins and oral prolonged release formulations. The complexity of the luminal environment and the value of dissolution in lyophilized products were also highlighted. The second session of the conference included presentations on the Biopharmaceutics Classification Scheme (BCS), the Biopharmaceutics Drug Disposition Classification System (BDDCS), and the role of transporters in the classification of drugs. The current status of biowaivers and a modern view on non-linear in vitro-in vivo (IVIVC) correlations were also addressed. Finally, this section ended with a special topic on biorelevant dissolution media and methods. The third day of the conference was dedicated to bioequivalence. Emphasis was placed on high within-subject variability and its impact on study design. Two unresolved issues of bioequivalence were also discussed: the use of generic antiepileptic drugs and the role of metabolites in bioequivalence assessment. Finally, the conference closed with a presentation of the current regulatory status of WHO and EMEA