Senescence is classically defined as an irreversible cell cycle arrest. There is now convincing evidence that senescent cells accumulate during human ageing, potentially driving age-related dysfunction through depletion of mitotically active cells and stimulation of chronic inflammation. Recently, a landmark paper demonstrated that removal of p16INK4A (p16)-positive senescent cells in mice prolonged healthy lifespan, suggesting a direct link between senescence and age-related dysfunction. As such, restraining the senescent pool or slowing their rate of accumulation presents an attractive therapeutic strategy for extending healthspan. Previously, our laboratory has demonstrated that siRNA transfection can reverse deep senescence in p16-positive primary adult human mammary epithelial cells using a panel of senescence markers. Subsequent siRNA screening revealed 28 hits which strongly induced reversal in the deeply senescent HMECs. In this project, siRNA knockdown of p16 combined with p21WAF1/CIP1 (p21) was found to reverse deep replicative senescence in primary adult human mammary fibroblasts, as defined by a panel of senescence markers. This discovery provided the opportunity to screen for novel siRNAs which induce reversal in both cell types. Screening in the deeply senescent HMFs of the 28 shortlisted candidates and 33 protein interactors identified using bioinformatics revealed 45 siRNAs which significantly increased cell number compared to the negative siRNA control. Subsequent immunofluorescence staining and high content analysis of the top 14 candidates identified 10 hit siRNAs which induced senescence reversal as defined by a panel of markers. Interestingly, these 10 hits were enriched for cytoskeletal and cell adhesion processes, suggesting an interplay between external forces and senescence induction. The top siRNA hit, early growth response 2 or EGR2, a transcription factor, was validated and selected for further exploration as a novel driver of senescence. Bioinformatics analysis revealed an enrichment for EGR2 binding sites within genes dynamically expressed in HMEC senescence, including p16, p21, and nine hits identified to reverse senescence in HMFs and HMECs. Furthermore, deeply senescent HMFs and HMECs were found to have a significantly increased nuclear EGR2 foci number compared to proliferating cells, and this was significantly decreased in reversed HMFs. In conclusion, it is proposed that EGR2 may represent a novel driver of both HMF and HMEC senescence.

Immune protection wanes during aging. This is evidenced by increased morbidity and mortality from infectious disease in aged individuals. As the aging population continues to increase worldwide, it will become increasingly important to determine both causes and therapeutic strategies for defects in the aged immune response. In particular, CD8 T cells have been shown to be highly susceptible to age-related defects. Recently, metabolic pathways have been implicated as critical factors in T cell fate decisions during immune responses. Of note, metabolic pathways are also considered primary determinants of lifespan in mammals. Therefore, we hypothesized that metabolic manipulations to extend lifespan would have significant effects on the aging immune system and protection during infection. In particular, we investigated the impact of rapamycin (rapa), both acute and chronic treatment regimens, on adult and old mice. Specifically, we tested how T cell development, peripheral homeostasis, and effector immunity became altered during treatment. We made side-by-side comparisons in calorically restricted (CR) old mice as a gold standard model of longevity extension. Importantly, both of these interventions have been reported to benefit immune function and extend lifespan in mice. However, our data strongly indicate that both rapa and CR induce distinct but deleterious consequences to overall immunity in mice. We conclude that neither rapa nor CR may be ideal candidates for extending lifespan in humans.

Emerging clinical evidence implicates cellular senescence in the pathogenesis of various inflammatory conditions including inflammatory bowel diseases (IBDs), demonstrating that the intestinal stem cell crypts of patients with early Crohn’s disease exhibit markers positive for cell cycle inhibitor proteins. This phenomenon coupled with chronic systemic inflammation, a term coined “inflammaging," triggers many age-related pathologies and accelerates mortality. Our research evaluates the efficacy of interventions that target these death-resistant senescent cells to improve overall health and vitality. Particularly, we investigated the effects of Fisetin, a potent flavanoid with senolytic properties, in a dextran sodium sulfate (DSS) induced mouse model of colitis. Our findings reveal that Fisetin significantly inhibits senescence and inflammation in the colon while simultaneously enhancing the relative abundance of beneficial microbes, especially Akkermansia muciniphila, showcasing its potential for managing IBDs. Additionally, given the profound restoration of the microbiome and the central role of resident microbes in the production of metabolites essential for facilitating immunomodulation, we extended our investigations to further explore the effects of fecal microbiota transplant (FMT) from long-living Ames dwarf mice, characterized by low inflammatory status, into normal mice. Our results show notable shifts in microbial diversity, indicating that FMT may combat dysbiosis, a precursor to several conditions, including autoimmune, metabolic, and neurodegenerative diseases. Lastly, our exploration of potential anti-aging pharmacological interventions including Metformin (MF) and Trodusquemine (MSI-1436) during the postnatal window has demonstrated robust transcriptomic alterations of key biomarkers in the GH/Igf1 axis, such as Pi3k, Akt, and Mtor, suggesting delayed aging and improved liver function in young mice. These epigenetic changes underscore that early-life pharmacological interventions may forestall the onset of age-related metabolic disorders. All in all, there remains an urgent need for breakthroughs that can enhance healthspan to ensure that the rapidly growing population of older adults enjoys life in these extended years

No description available.

Aging is a degenerative process characterized by a decline in physiological functions and cellular activities. Environmental and pharmacological interventions affecting longevity pathways have been extensively studied in model organisms. This study investigated the effect of chronic mild intermittent hypoxia (4 mg O2/L) or mild mitochondrial uncoupling with three doses of 0 (control), 0.1, 1, and 5 μM of 2,4-Dinitrophenol (DNP), on life history and gene expression in four clones of Daphnia magna. Interestingly, clones from intermittent ponds displayed better tolerance to hypoxia and DNP. Although neither treatments extended longevity, hypoxia increased fecundity and body size, and decreased food consumption and respiration rate. We uncovered 12 candidate genes that were differentially expressed in hypoxia-tolerant and sensitive clones in response to hypoxia. Unexpectedly, DNP increased fecundity and mitochondrial membrane potential without affecting food intake. This work opens up an opportunity for genomic determination of the potentially important phenotypes in a model organism.

DNA methylation is an important epigenetic mark spanning all of life's kingdoms. In humans, DNA methylation has been associated with a wide range of age-related pathologies, including type II diabetes and cancer. More recently, in humans, changes in DNA methylation at specific positions in the genome have been found to be predictive of chronological age. Interestingly, DNA methylation age is also predictive of health status and time-to-death. A better understanding of what these DNA methylation changes represent and whether they might be causative in the ageing process will be important to ascertain. However, at present there is no animal model system with which this process can be studied at a mechanistic level. Furthermore, it is becoming increasingly apparent that many disease states that increase in prevalence with age are not caused by all cells within the individual, but are often the result of changes to a subset of cells. This underscores the importance of studying these processes at the single cell level. The recent advances in single cell sequencing approaches now mean that we can study multiple layers of biology within the same single cell, such as the epigenome and the transcriptome (scM&T-Seq). Unfortunately, we are still only able to probe these important aspects of single cell biology in a static sense. This is a major limitation in the study of ageing because ageing and age-related disease processes are inherently dynamic. As such, it is incumbent upon us to develop approaches to assay single cell biology in a dynamic manner. 
In this thesis, I describe an epigenetic age predictor in the mouse. This predictor is tissue-independent and can accurately predict age (with an error of 3.33 weeks) and can record deviations in biological age upon interventions including ovariectomy and high fat diet both of which are known to reduce lifespan. Next, I describe the analysis of a homogeneous population of muscle satellite cells (MuSCs) that I have interrogated at the single cell level, using single cell combined transcriptome and methylome sequencing (scM&T-seq). I found that with age there was increased global transcriptional variability and increased feature-specific methylome variability. These findings explain the loss of functionality of these cells with age. Lastly, I describe two imaging approaches to study DNA methylation dynamically in single cells. Using these methods, I demonstrate that it is possible to accurately determine methylation status across a wide spectrum of global methylation levels and that by using such approaches novel information about dynamic methylation processes can be obtained. These methods represent the first to study DNA methylation dynamically.

Das Altern ist ein komplexer biologischer Prozess mit vermehrten Zellschäden und altersbedingten Krankheiten. Diese Studie erforscht das Anti-Aging-Potenzial pflanzlicher Extrakte der Traditionellen Chinesischen Medizin (TCM) anhand des Nematoden Caenorhabditis elegans. Von sieben getesteten Pflanzenextrakten wurden E. ulmoides und C. chinensis ausgewählt, da sie einen Überlebensvorteil in Stresssituationen bei gealterten C. elegans bewirkten. Diese Extrakte verlängerten die Lebensdauer und verbesserten das Überleben nach Hitzestress, oxidativem Stress und pathogenem Stress. Besonders bemerkenswert ist, dass nur der Extrakt von C. chinensis die körperliche Fitness signifikant steigerte, begleitet von Verbesserungen im Kurzzeitgedächtnis und mechanosensorischen Eigenschaften von C. elegans. Zudem unterdrückte dieser Extrakt die Darmautofluoreszenz, einen etablierten Marker für den Alterungsprozess. Chemische Analysen mittels UPLC-MS/MS und transkriptomische Analysen gealterter Würmer, die mit den Extrakten behandelt wurden, zeigten bioaktive Verbindungen, wobei Zingibroside R1 aus C. chinensis die Lebensdauer, das Überleben nach Hitzestress und die Fortbewegung verbesserte. Die transkriptomische Analyse enthüllte eine Immunantwortmodulation bei gealterten Nematoden, die mit C. chinensis behandelt wurden, und eine 150-fache Erhöhung der far-3-Expression, die ein Fettsäure-bindendes Protein kodiert. Interessanterweise zeigte sich, dass C. elegans, die mit dem far-3 RNAi-Stamm und C. chinensis behandelt wurden, keine Verbesserung der Gesundheitsspanne aufwiesen. Zusammenfassend hebt diese Studie die differenzierten Wirkungsweisen der getesteten Pflanzenextrakte hervor. Während E. ulmoides gezielt die physiologische Fitness förderte, erwies sich C. chinensis als umfassender Gesundheitsverlängerer. Die Identifizierung bioaktiver Verbindungen und die Aufdeckung molekularer Mechanismen bieten detaillierte Einblicke in die Anti-Aging-Effekte bei Nematoden. / Aging is one of the most complex biological processes leading to increased cell damage and age-related diseases. In this study, I aimed to uncover the potential anti-aging capacities of Traditional Chinese Medicine (TCM) plant extracts by using the nematode Caenorhabditis elegans. E. ulmoides and C. chinensis extracts, chosen from seven tested plant extracts, caused a survival advantage during stress in aged C. elegans by extending lifespan and survival after heat, oxidative and pathogenic stress. However, only C. chinensis could enhance physical fitness, short-term memory, and mechanosensory of C. elegans and suppressed intestinal autofluorescence, a marker of aging. Chemical analysis of the C. chinensis and E. ulmoides extracts using UPLC-MS/MS and transcriptomic analysis of aged worms treated with these extracts were applied. UPLC-MS/MS analysis revealed the presence of several known bioactive compounds. Three of these identified substances, namely astragalin, pinoresinol, and zingibroside R1, were isolated from the C. chinensis extract, and tested. Zingibroside R1 improved the lifespan, survival after heat stress, and locomotion. The transcriptomic analysis revealed a modulation of the immune response in C. chinensis-treated aged nematodes. The expression of far-3, which encodes a fatty acid binding protein, was increased with a 150-fold-change in C. chinensis treated worms, therefore, a far-3 RNA interference (RNAi) strain was created. C. elegans treated with the far-3 RNAi strain and with C. chinensis did not improve healthspan, thus demonstrating the importance of far-3 expression in C. chinensis benefits. In conclusion, this study underlines the different modes of action of the tested plant extracts. E. ulmoides improved specifically the physiological fitness while C. chinensis seems to be an overall healthspan enhancer. Additionally, it provides insights into the components and molecular mechanisms responsible for these anti-aging effects in nematodes.

Tesis por compendio / [ES] Esta tesis se centra en el desarrollo de nuevas técnicas automatizadas que permiten inspeccionar nematodos Caenorhabidits elegans (C. elegans) en placas de Petri estándar, para el análisis de sus comportamientos. C. elegans es un nemátodo de 1mm de longitud, con el cual se pueden realizar distintos experimentos para analizar los efectos de fármacos, compuestos o alteraciones genéticas en su longevidad, su salud física o su cognición. El campo principal metodológico del presente trabajo para el análisis de esos efectos es la visión por computador; y con ello, el desarrollo completo del sistema de visión activo: sistema de iluminación inteligente, sistema de captura óptimo, procesamiento de las imágenes para detección y clasificación de nematodos. Los campos secundarios en esta investigación son el control y robotización. Los C. elegans son animales sensibles a la luz y por ello el primero de los métodos está en la rama de la iluminación inteligente, con el cual se permite regular la intensidad y las longitudes de onda de la luz que reciben los nematodos. El siguiente método es el procesado para la detección y clasificación de movimiento a partir de las imágenes obtenidas con esa iluminación controlada. Tener el ambiente controlado es fundamental, los nematodos son muy sensibles a las condiciones ambientales por lo que puede alterarse su actividad biológica, y con ello los resultados, así que el tercer método es la integración de las técnicas en un nuevo dispositivo que permite automatizar ensayos de lifespan y validar los resultados automáticos comparándolos con los manuales. El movimiento del animal es clave para poder realizar inferencias estadísticas que puedan mostrar tendencias en sus comportamientos, por ello la estimulación automatizada que provoque una reacción de su movilidad es el cuarto de los métodos. Por último, el aumento de la resolución en las imágenes muestra mayor detalle, mejorando el procesamiento y extracción de características. El quinto método es un robot multivista que posibilita tomar imágenes a distintas resoluciones, lo que permite mantener el seguimiento global de los gusanos, al mismo tiempo que se toman imágenes con un encuadre de mayor detalle del nematodo objetivo. / [CA] Esta tesi doctoral se centra en el desentrollament de noves tècniques automatitzades que permeten inspeccionar nemàtodes Caenorhabidits elegans (C. elegans) en plaques de Petri estàndar, per a l'anàlisi dels seus comportaments. C. elegans és un nemàtode d'1mm de llargària, ab el qual se poden realitzar distints experiments per a analitzar els efectes de fàrmacs, composts o alteracions genètiques en sa longevitat, la seua salut física o la seua cognició. El camp principal metodològic del present treball per a l'anàlisi d'eixos efectes és la visió per computador; i ab açò, el desentrollament complet del sistema de visió actiu: sistema d'il.luminació inteligent, sistema de captura òptim, processament de les imàtgens per a detecció i classificació de nematode. Els camps secundaris en esta investigació són el control i robotització. Els C. elegans són animals sensibles a la llum i por ello el primer dels mètodes està en la branca de la il.luminació intel.ligent, ab el qual es permet regular la intensitat i les longituds d'ona de la llum que reben els nematodes. El següent mètode és el processat per a la detecció i classificació de moviment a partir de les imàtgens obtinguda ab eixa il.luminació controlada. Tindre l'ambient controlat és fonamental, els nemàtodes són molt sensibles a les condicions ambientals per lo que pot alterar-se la seua activitat biològica, i ab aço els resultats, aixina que el tercer mètode és la integració de les tècniques en un nou dispositiu que permet automatitzar ensajos de lifespan i validar els resultats automàtics comparant-los ab els manuals. El moviment de l'animal és clau per a poder realitzar inferencies estadístiques que puguen mostrar tendències en el seus comportaments, per això la estimulació automatitzada que provoque una reacció de la seua mobilitat és el quart dels mètodes. Per últim, l'augment de la resolució en les imàtgens mostra major detall, millorant el processament i extracció de característiques. El quint mètode és un robot multivista que possibilita prendre imàtgens a distintes resolucions, lo que permet mantindre el seguiment global dels cucs, al mateix temps que se prenguen imàtgens ab un enquadrament de major detall del nematode objectiu. / [EN] This thesis focuses on the development of new automated techniques that allow the inspection of Caenorhabidits elegans nematodes (C. elegans) in Petri dishes, for the analysis of their behavior. This nematode is a 1mm long worm, with which different experiments can be carried out to analyze the effects of drugs, compounds or genetic alterations on its longevity, physical health or cognition. The main methodological field of the present work for the analysis of these effects is computer vision; and with it, the complete development of the active vision system: intelligent lighting system, optimal capture system, image processing for detection and classification of nematodes. The secondary fields in this research are control and robotization. C. elegans are light-sensitive animals and therefore the first method is in the field of intelligent lighting, with which it is possible to regulate the intensity and wavelength of the light that nematodes receive. The next method is the processing for the detection and classification of movement from the images obtained with that controlled lighting. Having a controlled environment is essential, worms are very sensitive to environmental conditions so it can alter biological activity, and with it the results, so the third method is the integration of techniques in a new device that allows automating tests of lifespan and validate the automatic results comparing them with the manual ones. The movement of the animal is key to be able to carry out statistical conferences that can show trends in its behaviors, therefore the automated stimulation that causes a reaction of its mobility is the fourth of the methods. Finally, increasing the resolution in the images shows greater detail, improving the processing and extraction of features. The fifth method is a multiview robot that enables images to be taken at different resolutions, allowing global tracking of worms to be maintained, while at the same time taking images with a more detailed frame of the target worm. / Puchalt Rodríguez, JC. (2022). Development and Evaluation of New Methods for Automating Experiments with C. Elegans Based on Active Vision [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181359 / Compendio

Tesis por compendio / [ES] El objetivo principal de esta tesis es el desarrollo de técnicas avanzadas de seguimiento de posturas para reconocimiento de comportamientos del Caenorhabditis elegans o C. elegans. El C. elegans es una clase de nematodo utilizado como organismo modelo para el estudio y tratamientos de diferentes enfermedades patológicas así como neurodegenerativas. Su comportamiento ofrece información valiosa para la investigación de nuevos fármacos (o productos alimenticios y cosméticos saludables) en el estudio de lifespan y healthspan. Al día de hoy, muchos de los ensayos con C. elegans se realizan de forma manual, es decir, usando microscopios para seguirlos y observar sus comportamientos o en laboratorios más modernos utilizando programas específicos. Estos programas no son totalmente automáticos, requieren ajuste de parámetros. Y en otros casos, son programas para visualización de imágenes donde el operador debe etiquetar maualmente el comportamiento de cada C. elegans. Todo esto se traduce a muchas horas de trabajo, lo cual se puede automatizar utilizando técnicas de visión por computador. Además de poder estimar indicadores de movilidad con mayor precisión que un operador humano. El problema principal en el seguimiento de posturas de C. elegans en placas de Petri son las agregaciones entre nematodos o con ruido del entorno. La pérdida o cambios de identidad son muy comunes ya sea de forma manual o usando programas automáticos/semi-automáticos. Y este problema se vuelve más complicado aún en imágenes de baja resolución. Los programas que automatizan estas tareas de seguimiento de posturas trabajan con técnicas de visión por computador usando técnicas tradicionales de procesamiento de imágenes o técnicas de aprendizaje profundo. Ambas técnicas han demostrado excelentes resultados en la detección y seguimiento de posturas de C. elegan}. Por un lado, técnicas tradicionales utilizan algoritmos/optimizadores para obtener la mejor solución, mientras que las técnicas de aprendizaje profundo aprenden de forma automática características del conjunto de datos de entrenamiento. El problema con las técnicas de aprendizaje profundo es que necesitan un conjunto de datos dedicado y grande para entrenar los modelos. La metodología utilizada para el desarrollo de esta tesis (técnicas avanzadas de seguimiento de posturas) se encuadran dentro del área de investigación de la visión artificial. Y ha sido abordada explorando ambas ramas de visión por computador para resolver los problemas de seguimiento de posturas de C. elegans en imágenes de baja resolución. La primera parte, es decir, secciones 1 y 2, capítulo 2, utilizó técnicas tradicionales de procesamiento de imágenes para realizar la detección y seguimiento de posturas de los C. elegans. Para ello se propuso una nueva técnica de esqueletización y dos nuevos criterios de evaluación para obtener mejores resultados de seguimiento, detección, y segmentación de posturas. Las siguientes secciones del capítulo 2 utilizan técnicas de aprendizaje profundo, y simulación de imágenes sintéticas para entrenar modelos y mejorar los resultados de detección y predicción de posturas. Los resultados demostraron ser más rápidos y más precisos en comparación con técnicas tradicionales. También se demostró que los métodos de aprendizaje profundo son más robustos ante la presencia de ruido en la placa. / [CA] L'objectiu principal d'aquesta tesi és el desenvolupament de tècniques avançades de seguiment de postures per a reconeixement de comportaments del Caenorhabditis elegans o C. elegans. El C. elegans és una classe de nematodo utilitzat com a organisme model per a l'estudi i tractaments de diferents malalties patològiques així com neurodegeneratives. El seu comportament ofereix informació valuosa per a la investigació de nous fàrmacs (o productes alimentosos i cosmètics saludables) en l'estudi de lifespan i healthspan. Al dia de hui, molts dels assajos amb C. elegans es realitzen de manera manual, és a dir, usant microscopis per a seguir-los i observar els seus comportaments o en laboratoris més moderns utilitzant programes específics. Aquests programes no són totalment automàtics, requereixen ajust de paràmetres. I en altres casos, són programes per a visualització d'imatges on l'operador ha d'etiquetar maualment el comportament de cada C. elegans. Tot això es tradueix a moltes hores de treball, la qual cosa es pot automatitzar utilitzant tècniques de visió per computador. A més de poder estimar indicadors de mobilitat amb major precisió que un operador humà. El problema principal en el seguiment de postures de C. elegans en plaques de Petri són les agregacions entre nematodes o amb soroll de l'entorn. La pèrdua o canvis d'identitat són molt comuns ja siga de manera manual o usant programes automàtics/semi-automàtics. I aquest problema es torna més complicat encara en imatges de baixa resolució. Els programes que automatitzen aquestes tasques de seguiment de postures treballen amb tècniques de visió per computador usant tècniques tradicionals de processament d'imatges o tècniques d'aprenentatge profund. Totes dues tècniques han demostrat excel·lents resultats en la detecció i seguiment de postures de C. elegans. D'una banda, tècniques tradicionals utilitzen algorismes/optimizadors per a obtindre la millor solució, mentre que les tècniques d'aprenentatge profund aprenen de manera automàtica característiques del conjunt de dades d'entrenament. El problema amb les tècniques d'aprenentatge profund és que necessiten un conjunt de dades dedicat i gran per a entrenar els models. La metodologia utilitzada per al desenvolupament d'aquesta tesi (tècniques avançades de seguiment de postures) s'enquadren dins de l'àrea d'investigació de la visió artificial. I ha sigut abordada explorant totes dues branques de visió per computador per a resoldre els problemes de seguiment de postures de C. elegans en imatges de baixa resolució. La primera part, és a dir, secció 1 i 2, capítol 2, va utilitzar tècniques tradicionals de processament d'imatges per a realitzar la detecció i seguiment de postures dels C. elegans. Per a això es va proposar una nova tècnica de esqueletizació i dos nous criteris d'avaluació per a obtindre millors resultats de seguiment, detecció i segmentació de postures. Les següents seccions del capítol 2 utilitzen tècniques d'aprenentatge profund i simulació d'imatges sintètiques per a entrenar models i millorar els resultats de detecció i predicció de postures. Els resultats van demostrar ser més ràpids i més precisos en comparació amb tècniques tradicionals. També es va demostrar que els mètodes d'aprenentatge profund són més robustos davant la presència de soroll en la placa. / [EN] The main objective of this thesis is the development of advanced posture-tracking techniques for behavioural recognition of Caenorhabditis elegans or C. elegans. C. elegans is a kind of nematode used as a model organism for the study and treatment of different pathological and neurodegenerative diseases. Their behaviour provides valuable information for the research of new drugs (or healthy food and cosmetic products) in the study of lifespan and healthspan. Today, many of the tests on C. elegans are performed manually, i.e. using microscopes to track them and observe their behaviour, or in more modern laboratories using specific software. These programmes are not fully automatic, requiring parameter adjustment. And in other cases, they are programmes for image visualisation where the operator must label the behaviour of each C. elegans manually. All this translates into many hours of work, which can be automated using computer vision techniques. In addition to being able to estimate mobility indicators more accurately than a human operator. The main problem in tracking C. elegans postures in Petri dishes is aggregations between nematodes or with noise from the environment. Loss or changes of identity are very common either manually or using automatic/semi-automatic programs. And this problem becomes even more complicated in low-resolution images. Programs that automate these pose-tracking tasks work with computer vision techniques using either traditional image processing techniques or deep learning techniques. Both techniques have shown excellent results in the detection and tracking of C. elegans postures. On the one hand, traditional techniques use algorithms/optimizers to obtain the best solution, while deep learning techniques automatically learn features from the training dataset. The problem with deep learning techniques is that they need a dedicated and large dataset to train the models. The methodology used for the development of this thesis (advanced posture-tracking techniques) falls within the research area of computer vision. It has been approached by exploring both branches of computer vision to solve the posture-tracking problems of C. elegans in low-resolution images. The first part, i.e. sections 1 and 2, chapter 2, used traditional image processing techniques to perform posture detection and tracking of C. elegans. For this purpose, a new skeletonization technique and two new evaluation criteria were proposed to obtain better posture-tracking, detection, and segmentation results. The next sections of chapter 2 use deep learning techniques, and synthetic image simulation to train models and improve posture detection and prediction results. The results proved to be faster and more accurate compared to traditional techniques. Deep learning methods were also shown to be more robust in the presence of plate noise. / This research was supported by Ministerio de Ciencia, Innovación y Universidades [RTI2018-094312-B-I00 (European FEDER funds); FPI PRE2019-088214], and also was supported by Universitat Politècnica de València [“Funding for open access charge: Uni- versitat Politècnica de València”]. The author received a scholarship from the grant: Ayudas para contratos predoctorales para la formación de doctores 2019. / Layana Castro, PE. (2023). Desarrollo de técnicas avanzadas de seguimiento de posturas para reconocimiento de comportamientos de C. elegans [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/198879 / Compendio