Drug rehabilitation | EPFL Graph Search

Drug rehabilitation is the process of medical or psychotherapeutic treatment for dependency on psychoactive substances such as alcohol, prescription drugs, and street drugs such as cannabis, cocaine, heroin or amphetamines. The general intent is to enable the patient to confront substance dependence, if present, and stop substance misuse to avoid the psychological, legal, financial, social, and physical consequences that can be caused. Treatment includes medication for depression or other disorders, counseling by experts and sharing of experience with other addicts. Psychological dependency Psychological dependency is addressed in many drug rehabilitation programs by attempting to teach the person new methods of interacting in a drug-free environment. In particular, patients are generally encouraged, or possibly even required, to not associate with peers who still use the addictive substance. Twelve-step programs encourage addicts not only to stop using alcohol or other drug

Predictive Analysis of Errors During Robot-Mediated Gamified Training

Pierre Dillenbourg, Nevena Dresevic, Arzu Güneysu Özgür, Marija Katanic, Nihal Ezgi Yücetürk

This paper presents our approach to predicting future error-related events in a robot-mediated gamified phys- ical training activity for stroke patients. The ability to predict future error under such conditions suggests the existence of distinguishable features and separated class characteristics between the casual gameplay state and error prune state in the data. Identifying such features provides valuable insight to creating individually tailored, adaptive games as well as possible ways to increase rehabilitation success by patients. Considering the time-series nature of sensory data created by motor actions of patients we employed a predictive analysis strategy on carefully engineered features of sequenced data. We split the data into fixed time windows and explored logistic regression models, decision trees, and recurrent neural networks to predict the likelihood of a patient making an error based on the features from the time window before the error. We achieved an 84.4% F1-score with a 0.76 ROC value in our best model for predicting motion accuracy related errors. Moreover, we computed the permutation importance of the features to explain which ones are more indicative of future errors.

2022

Sensor-based control strategies for integration of epidural electrical stimulation in rehabilitation after spinal cord injury

Miroslav Caban

Spinal Cord Injury (SCI) results in damage to neural circuitry connecting the brain to the periphery. Consequently, sensory and motor function is lost, to varying degree, depending on the site and severity of the lesion. More than half of spinal cord injuries result in paraplegia, a partial or complete paralysis of the lower limbs. Despite the emergence of therapeutic interventions in recent decades, outcomes have been incremental, and few have transformed SCI rehabilitation.Epidural electrical stimulation (EES) stimulates paralyzed muscles. Anatomically intact neural circuits below the lesion can be reactivated to a functional state by stimulating afferent fibers in the dorsal roots. Recently, EES enabled independent stepping and improved functional recovery during activity-based rehabilitation. Neuroplasticity, the formation of new functional pathways based on neural activity above and below the lesion, allows for motor control recovery. However, it took months of individualized rehabilitation training to see functional recovery, making widespread application difficult.For the first time in humans, we use biomimetic EES to deliver temporal sequences of spatially selective stimulation trains to the spinal cord. During rehabilitation exercises, we target specific muscle groups to mimic a natural afferent firing pattern. We improve simultaneous descending and ascending activity by using closed-loop motor-intent sensors. We propose three goals to drive clinical translation of biomimetic EES.We first enable EES for locomotor training and outside of a dedicated research environment. Following a systematic review of gait-detection algorithms, we developed a novel neurostimulation platform the functions in closed-loop using inertial measurement units. We further designed a platform intended for independent use of stimulation by the patient. We investigated clinical outcomes of biomimetic EES applied during locomotor rehabilitation and found that performance improved with stimulation and after a few months, participants regained voluntary control over previously paralysed muscles without stimulation.Then we extend EES to patients with trunk impairments and complete leg motor loss. We modified our closed-loop paradigms for people with motor complete SCI and created an electrode lead that covers the thoracic spine. We evaluated biomimetic EES in complete SCI patients during locomotor and trunk rehabilitation. Three participants could walk and control trunk movements after neurorehabilitation.Finally, we incorporate EES into rehabilitation activities across the continuum-of-care. We created a graphical user interface for clinicians to easily create activity-specific simulation programs and synchronized stimulation with common robotic devices. Then we evaluated EES's clinical benefit in conventional and robotic rehab. Individuals could immediately stand, walk, cycle, swim, and move their trunks. Using EES and rehabilitation robotics restored physiologically relevant muscle activity and allowed for more challenging training. Recreational rehabilitation activities, that were otherwise inaccessible, could be performed.Biomimetic EES optimizes conditions for neuroplasticity and shows promise of delivering clinically relevant outcomes in a short timeframe. We thus bring the intervention closer to a clinical reality, offering a new hope to the SCI community.

EPFL2022

Intestinal stem cells differentiation and its application in cancer therapy

Maxim Norkin

Colorectal cancer (CRC) is one of the deadliest cancers worldwide. Despite extensive research in the field, new therapies targeting CRC are in urgent need. CRC is a highly heterogeneous disease with high levels of intra- and inter-patient heterogeneity. Cancer stem cells are the driving force of tumor development and metastasis. One of the approaches to treat CRC is differentiation therapy thereby induction of cancer stem cell differentiation may lead to tumor regression. Intestinal normal and cancer organoids represent an ideal model for studying the differentiation process ex vivo. Gene expression profiling of drug-treated organoids can be used for quantification of the differentiation process with high precision. RNA-seq based drug-screening platforms in organoids are not yet established. Here we developed a high-throughput high-content targeted RNA-seq-based platform (TORNADO-seq) for monitoring gene expression of large gene signatures in intestinal organoids which allowed us to quantify and evaluate complex cellular phenotypes and cellular alterations upon drug treatment. We applied TORNADO-seq in drug screening in wt and cancer intestinal organoids. We found many differentiation-inducing drugs in wt organoids, including some drugs specifically enriching for certain cell phenotypes, e.g. enteroendocrine cells. Further, we applied identified differentiation-inducing drugs to cancer organoids (APClof;KRASG12D;TP53lof) and discovered that the majority of those differentiation-inducing drugs also targeted cancer organoids. Differentiation induction seems to be a common mode of action of cancer-targeting drugs. Based on gene expression profiles of treated cancer organoids, we were able to propose and confirm the mechanism of action of several drugs indicating that cancer cells may to be sensitive to alterations in the cholesterol biosynthesis pathway. In general, utilization of TORNADO-seq allows predicting connections between cellular phenotypes and signaling pathways in organoids which can be used for hypothesis generation in a variety of biological systems. The second part of the thesis is devoted to the investigation of mechanisms underlying the accumulation of genetic alterations in CRC tumors. It is not known whether cancer driver genes affect the rate of mutation acquisition. Here we performed exome sequencing of single cell-derived organoids obtained from tumors with either APClof, APClof;KRASG12D or APClof;KRASG12D;TP53lof mutation phenotypes that reflect early stages of CRC development. We discovered that presence of KRAS and P53 mutations didn't affect the number of single nucleotide substitutions (SNSs) in tumors, while the latter was increased in APC mutated tumors compared to wt cells and was highly correlated with the tumor age. P53 inactivation was highly correlated with the presence of large-scale (>10 Mb) copy number alterations (CNAs).

EPFL2021