Cyclooxygenase-2-Prostaglandin E2 pathway: A key player in tumor-associated immune cells

Cyclooxygenases-2 (COX-2) and Prostaglandin E2 (PGE2), which are important in chronic inflammatory diseases, can increase tumor incidence and promote tumor growth and metastasis. PGE2 binds to various prostaglandin E receptors to activate specific downstream signaling pathways such as PKA pathway, β-catenin pathway, NF-κB pathway and PI3K/AKT pathway, all of which play important roles in biological and pathological behavior. Nonsteroidal anti-inflammatory drugs (NSAIDs), which play as COX-2 inhibitors, and EP antagonists are important in anti-tumor immune evasion. The COX-2-PGE2 pathway promotes tumor immune evasion by regulating myeloid-derived suppressor cells, lymphocytes (CD8+ T cells, CD4+ T cells and natural killer cells), and antigen presenting cells (macrophages and dendritic cells). Based on conventional treatment, the addition of COX-2 inhibitors or EP antagonists may enhance immunotherapy response in anti-tumor immune escape. However, there are still a lot of challenges in cancer immunotherapy. In this review, we focus on how the COX-2-PGE2 pathway affects tumor-associated immune cells

Optimal control and ultimate bounds of 1:2 nonlinear quantum systems

Using optimal control, we establish and link the ultimate bounds in time (referred to as quantum speed limit) and energy of two- and three-level quantum nonlinear systems which feature 1:2 resonance. Despite the unreachable complete inversion, by using the Pontryagin maximum principle, we determine the optimal time, pulse area, or energy, for a given arbitrary accuracy. We show that the third-order Kerr terms can be absorbed in the detuning in order to lock the dynamics to the resonance. In the two-level problem, we determine the non-linear counterpart of the optimal $\pi$-pulse inversion for a given accuracy. In the three-level problem, we obtain an intuitive pulse sequence similar to the linear counterpart but with different shapes. We prove the (slow) logarithmic increasing of the optimal time as a function of the accuracy

Beyond Keywords and Relevance: A Personalized Ad Retrieval Framework in E-Commerce Sponsored Search

On most sponsored search platforms, advertisers bid on some keywords for their advertisements (ads). Given a search request, ad retrieval module rewrites the query into bidding keywords, and uses these keywords as keys to select Top N ads through inverted indexes. In this way, an ad will not be retrieved even if queries are related when the advertiser does not bid on corresponding keywords. Moreover, most ad retrieval approaches regard rewriting and ad-selecting as two separated tasks, and focus on boosting relevance between search queries and ads. Recently, in e-commerce sponsored search more and more personalized information has been introduced, such as user profiles, long-time and real-time clicks. Personalized information makes ad retrieval able to employ more elements (e.g. real-time clicks) as search signals and retrieval keys, however it makes ad retrieval more difficult to measure ads retrieved through different signals. To address these problems, we propose a novel ad retrieval framework beyond keywords and relevance in e-commerce sponsored search. Firstly, we employ historical ad click data to initialize a hierarchical network representing signals, keys and ads, in which personalized information is introduced. Then we train a model on top of the hierarchical network by learning the weights of edges. Finally we select the best edges according to the model, boosting RPM/CTR. Experimental results on our e-commerce platform demonstrate that our ad retrieval framework achieves good performance

A Brief Online Mindfulness-Based Group Intervention for Psychological Distress Among Chinese Residents During COVID-19: a Pilot Randomized Controlled Trial

Objectives The coronavirus (COVID-19) global pandemic has increased psychological distress among the general population. The objective of this study is to evaluate a mindfulness-based intervention for psychological distress among Chinese residents during COVID-19. Methods This study used a switching replications design to test the feasibility and efficacy of a brief online mindfulness-based intervention for Chinese residents’ psychological distress. Fifty-one residents in the Hubei province were randomly allocated to two groups (experimental group and waitlist control group) with three waves of measurement at time 1, time 2, and time 3 for changes in mindfulness and psychological distress. Results In addition to significant within-group improvements over time for both groups, OLS linear regression with full information likelihood estimation revealed statistically significant between-group treatment effects across outcome domains, including mindfulness awareness, b = 2.84, p < 0.001, g = 6.92, psychological distress, b = −21.33, p < 0.001, g = 6.62, somatic symptoms, b = −6.22, p < 0.001, g = 4.42, depressive symptoms, b = −7.16, p < 0.001, g = 5.07, and anxiety symptoms, b = −8.09, p < 0.001, g = 6.84. Conclusions Results suggest that a brief online mindfulness-based intervention can be a feasible and promising intervention for improving mindfulness and decreasing psychological distress among Chinese residents staying at home during the COVID-19 outbreak. The study used a small convenience sample which led to a concern of external generalizability and with limited evaluation of long-term change.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167607/1/Zhang_2021_Article_ABriefOnlineMindfulness-BasedG.pdfDescription of Zhang_2021_Article_ABriefOnlineMindfulness-BasedG.pdf : Main articleSEL

FBXW7 and human tumors: mechanisms of drug resistance and potential therapeutic strategies

Drug therapy, including chemotherapy, targeted therapy, immunotherapy, and endocrine therapy, stands as the foremost therapeutic approach for contemporary human malignancies. However, increasing drug resistance during antineoplastic therapy has become a substantial barrier to favorable outcomes in cancer patients. To enhance the effectiveness of different cancer therapies, an in-depth understanding of the unique mechanisms underlying tumor drug resistance and the subsequent surmounting of antitumor drug resistance is required. Recently, F-box and WD Repeat Domain-containing-7 (FBXW7), a recognized tumor suppressor, has been found to be highly associated with tumor therapy resistance. This review provides a comprehensive summary of the underlying mechanisms through which FBXW7 facilitates the development of drug resistance in cancer. Additionally, this review elucidates the role of FBXW7 in therapeutic resistance of various types of human tumors. The strategies and challenges implicated in overcoming tumor therapy resistance by targeting FBXW7 are also discussed

Optimal and robust quantum control in low dimensional systems

La théorie du contrôle optimal (OCT) est une méthode pour obtenir les solutions optimales de systèmes quantiques contrôlés par des champs externes, fournissant un ensemble puissant d'outils et de concepts. L'un des objectifs de la thèse est d'adapter la technique OCT dans des systèmes quantiques à deux et trois états en tenant compte des pertes et de la robustesse, ce qui est primordial pour la mise en œuvre de techniques de contrôle dans une large classe de plateformes.Sur la base de techniques d'ingénierie inverse et du principe du maximum de Pontryagin (PMP), nous établissons et testons les différentes stratégies optimales montrant comment contrôler le transfert dans des systèmes quantiques à trois niveaux en considérant des solutions optimales en énergie et en temps minimum en tenant compte des pertes. Ces résultats montrent en particulier que le passage adiabatique habituel dans de tels systèmes, connu sous le nom de passage adiabatique Raman stimulé (STIRAP), qui conduit à un transfert imparfait, peut être rendu exact, réalisant ainsi le passage exact de Raman stimulé (STIREP) tout en réduisant l'énergie et la durée des contrôles.Un des objectifs consiste à développer une nouvelle technique qui permet de combiner robustesse et optimisation. Plutôt que d'utiliser une procédure d'optimisation directe comme la technique OCT, nous développons une technique d'optimisation géométrique qui permet de dériver des solutions optimales et robustes à partir d'une optimisation inverse. La méthode appelée optimisation inverse robuste (RIO) permet d'obtenir des trajectoires numériques qui peuvent être rendues aussi précises que nécessaire. La méthode est polyvalente et peut être appliquée à divers types d'erreurs et de problèmes de contrôle quantique.Optimal control theory (OCT) is the basic and comprehensive method to obtain the optimal solutions of quantum systems controlled by external fields. It provides a powerful set of tools and concepts. One of the goals of the thesis is to design the technique of OCT in two- and three-state quantum systems taking into account losses and robustness, which is of primary importance for the implementation of control techniques in a broad class of platforms.Based on inverse-engineering techniques and the Pontryagin maximum principle (PMP), we establish and test the different optimal strategies showing how to control the transfer in three-level quantum systems considering energy- and time-minimum optimal solutions taking into account losses. These results, in particular, show that the usual adiabatic passage in such systems, known as stimulated Raman adiabatic passage (STIRAP), which leads to imperfect transfer, can be made exact thus achieving stimulated Raman exact passage (STIREP) while reducing the energy and the duration costs respectively of the controls.We next combine robustness with optimization. Instead of using a direct optimization procedure from OCT, we develop a technique of geometric optimization that allows the derivation of optimal and robust solutions from an inverse optimization. The method named robust inverse optimization (RIO) allows one to obtain numerical trajectories that can be made as accurate as required. The method is versatile and can be applied to various types of errors and of quantum control problems

Contrôle quantique optimal et robuste dans des systèmes de petite dimension

Optimal control theory (OCT) is the basic and comprehensive method to obtain the optimal solutions of quantum systems controlled by external fields. It provides a powerful set of tools and concepts. One of the goals of the thesis is to design the technique of OCT in two- and three-state quantum systems taking into account losses and robustness, which is of primary importance for the implementation of control techniques in a broad class of platforms.Based on inverse-engineering techniques and the Pontryagin maximum principle (PMP), we establish and test the different optimal strategies showing how to control the transfer in three-level quantum systems considering energy- and time-minimum optimal solutions taking into account losses. These results, in particular, show that the usual adiabatic passage in such systems, known as stimulated Raman adiabatic passage (STIRAP), which leads to imperfect transfer, can be made exact thus achieving stimulated Raman exact passage (STIREP) while reducing the energy and the duration costs respectively of the controls.We next combine robustness with optimization. Instead of using a direct optimization procedure from OCT, we develop a technique of geometric optimization that allows the derivation of optimal and robust solutions from an inverse optimization. The method named robust inverse optimization (RIO) allows one to obtain numerical trajectories that can be made as accurate as required. The method is versatile and can be applied to various types of errors and of quantum control problems.La théorie du contrôle optimal (OCT) est une méthode pour obtenir les solutions optimales de systèmes quantiques contrôlés par des champs externes, fournissant un ensemble puissant d'outils et de concepts. L'un des objectifs de la thèse est d'adapter la technique OCT dans des systèmes quantiques à deux et trois états en tenant compte des pertes et de la robustesse, ce qui est primordial pour la mise en œuvre de techniques de contrôle dans une large classe de plateformes.Sur la base de techniques d'ingénierie inverse et du principe du maximum de Pontryagin (PMP), nous établissons et testons les différentes stratégies optimales montrant comment contrôler le transfert dans des systèmes quantiques à trois niveaux en considérant des solutions optimales en énergie et en temps minimum en tenant compte des pertes. Ces résultats montrent en particulier que le passage adiabatique habituel dans de tels systèmes, connu sous le nom de passage adiabatique Raman stimulé (STIRAP), qui conduit à un transfert imparfait, peut être rendu exact, réalisant ainsi le passage exact de Raman stimulé (STIREP) tout en réduisant l'énergie et la durée des contrôles.Un des objectifs consiste à développer une nouvelle technique qui permet de combiner robustesse et optimisation. Plutôt que d'utiliser une procédure d'optimisation directe comme la technique OCT, nous développons une technique d'optimisation géométrique qui permet de dériver des solutions optimales et robustes à partir d'une optimisation inverse. La méthode appelée optimisation inverse robuste (RIO) permet d'obtenir des trajectoires numériques qui peuvent être rendues aussi précises que nécessaire. La méthode est polyvalente et peut être appliquée à divers types d'erreurs et de problèmes de contrôle quantique