Label-Free Machine Learning Prediction of Chemotherapy on Tumor Spheroids Using a Microfluidics Droplet Platform.

An integrated approach is proposed to rapidly evaluate the effects of anticancer treatments in 3D models, combining a droplet-based microfluidic platform for spheroid formation and single-spheroid chemotherapy application, label-free morphological analysis, and machine learning to assess treatment response. Morphological features of spheroids, such as size and color intensity, are extracted and selected using the multivariate information-based inductive causation algorithm, and used to train a neural network for spheroid classification into viability classes, derived from metabolic assays performed within the same platform as a benchmark. The model is tested on Ewing sarcoma cell lines and patient-derived xenograft (PDX) cells, demonstrating robust performance across datasets.

CausalCCC: a web server to explore intracellular causal pathways enabling cell-cell communication.

Understanding cell-cell communication (CCC) pathways from single-cell or spatial transcriptomic data is key to unraveling biological processes. Recently, multiple CCC methods have been developed but primarily focus on refining ligand-receptor (L-R) interaction scores. A critical gap for a more comprehensive picture of cellular crosstalks lies in the integration of upstream and downstream intracellular pathways in the sender and receiver cells.

Health promotion in French national sports federations: the challenge of settings-based approach implementation.

Research has shown that sports clubs call upon support from national sports federations (NSFs) to develop into a setting to promote health. The present study investigates how French NSFs themselves promote health. A two-step case study design was undertaken.

CausalXtract, a flexible pipeline to extract causal effects from live-cell time-lapse imaging data.

Live-cell microscopy routinely provides massive amounts of time-lapse images of complex cellular systems under various physiological or therapeutic conditions. However, this wealth of data remains difficult to interpret in terms of causal effects. Here, we describe CausalXtract, a flexible computational pipeline that discovers causal and possibly time-lagged effects from morphodynamic features and cell-cell interactions in live-cell imaging data.

Learning interpretable causal networks from very large datasets, application to 400,000 medical records of breast cancer patients.

Discovering causal effects is at the core of scientific investigation but remains challenging when only observational data are available. In practice, causal networks are difficult to learn and interpret, and limited to relatively small datasets. We report a more reliable and scalable causal discovery method (iMIIC), based on a general mutual information supremum principle, which greatly improves the precision of inferred causal relations while distinguishing genuine causes from putative and latent causal effects.

Second Generation of Tissue-Engineered Ligament Substitutes for Torn ACL Replacement: Adaptations for Clinical Applications.

The anterior cruciate ligament (ACL) of the knee joint is one of the strongest ligaments of the body and is often the target of traumatic injuries. Unfortunately, its healing potential is limited, and the surgical options for its replacement are frequently associated with clinical issues. A bioengineered ACL (bACL) was developed using a collagen matrix, seeded with autologous cells and successfully grafted and integrated into goat knee joints.

Enhanced secretion of TIMP-1 by human hypertrophic scar keratinocytes could contribute to fibrosis.

Hypertrophic scars are a pathological process characterized by an excessive deposition of extracellular matrix components. Using a tissue-engineered reconstructed human skin (RHS) method, we previously reported that pathological keratinocytes induce formation of a fibrotic dermal matrix. We further investigated keratinocyte action using conditioned media.

New ligament healing model based on tissue-engineered collagen scaffolds.

The anterior cruciate ligament (ACL) is often the target of knee trauma. This ligament does not heal very well, leading to joint instability. Long-term instability of the knee can lead to early arthritis and loss of function.