Intensified Total Neoadjuvant Therapy in Patients With Locally Advanced Rectal Cancer: Long-term Results of a Prospective Phase II Study.

Aims: To analyze the long-term results of a prospective phase II trial testing intensified total neoadjuvant therapy (TNT) in patients with locally advanced rectal cancer (LARC).

Materials And Methods: Patients with histologically confirmed LARC adenocarcinoma were enrolled. Intensified TNT consisted of targeted agent (bevacizumab or panitumumab/cetuximab) plus FOLFOXIRI (5-fluorouracil, leucovorin, oxaliplatin and irinotecan) induction chemotherapy followed by intensified (oxaliplatin and 5-fluorouracil) chemoradiotherapy (CRT) and surgical resection.

Targeting BTN2A1 Enhances Vγ9Vδ2 T-Cell Effector Functions and Triggers Tumor Cell Pyroptosis.

Vγ9Vδ2 T cells are potent but elusive cytotoxic effectors. Butyrophilin subfamily 2 member A1 (BTN2A1) is a surface protein that has recently been shown to bind the Vγ9 chain of the γδ T-cell receptor, but its precise role in modulating Vγ9Vδ2 T-cell functions remains unknown. Here, we show that 107G3B5, a monoclonal BTN2A1 agonist antibody, was able to significantly enhance Vγ9Vδ2 T-cell functions against hematologic or solid cell lines and against primary cells from patients with adult acute lymphoblastic leukemia.

Dynamic label-free analysis of SARS-CoV-2 infection reveals virus-induced subcellular remodeling.

Assessing the impact of SARS-CoV-2 on organelle dynamics allows a better understanding of the mechanisms of viral replication. We combine label-free holotomographic microscopy with Artificial Intelligence to visualize and quantify the subcellular changes triggered by SARS-CoV-2 infection. We study the dynamics of shape, position and dry mass of nucleoli, nuclei, lipid droplets and mitochondria within hundreds of single cells from early infection to syncytia formation and death.

Intention Prediction and Human Health Condition Detection in Reaching Tasks with Machine Learning Techniques.

Detecting human motion and predicting human intentions by analyzing body signals are challenging but fundamental steps for the implementation of applications presenting human-robot interaction in different contexts, such as robotic rehabilitation in clinical environments, or collaborative robots in industrial fields. Machine learning techniques (MLT) can face the limit of small data amounts, typical of this kind of applications. This paper studies the illustrative case of the reaching movement in 10 healthy subjects and 21 post-stroke patients, comparing the performance of linear discriminant analysis (LDA) and random forest (RF) in: (i) predicting the subject's intention of moving towards a specific direction among a set of possible choices, (ii) detecting if the subject is moving according to a healthy or pathological pattern, and in the case of discriminating the damage location (left or right hemisphere).

Innate immune responses of young bulls to a novel environment.

Animal welfare during transportation has been investigated in several studies, as opposed to post-transportation phases. In this study, we evaluated the effect of a novel environment after transportation on 26 Friesian bulls, 242 ± 42 day-old, from ten different dairy farms. Animals were shipped to a breeding center in different seasons, and selected parameters of innate immunity (serum bactericidal activity, hemolytic complement, serum albumin, α, β, and γ-globulins, interleukin-6, TNF-α) were monitored before and after the arrival at days--4/0/4/15/30.