Transformations of one-dimensional Gibbs measures with infinite range interaction

We study single-site stochastic and deterministic transforma- tions of one-dimensional Gibbs measures in the uniqueness regime with infinite-range interactions. We prove conservation of Gibbsianness and give quantitative estimates on the decay of the transformed potential. As examples, we consider exponentially decaying potentials, and potentials decaying as a power-law

Gibbs-non-Gibbs transitions via large deviations: computable examples

We give new and explicitly computable examples of Gibbs-non-Gibbs transitions of mean-field type, using the large deviation approach introduced in [4]. These examples include Brownian motion with small variance and related diffusion processes, such as the Ornstein-Uhlenbeck process, as well as birth and death processes. We show for a large class of initial measures and diffusive dynamics both short-time conservation of Gibbsianness and dynamical Gibbs-non-Gibbs transitions

Automatic prediction of non-iodine-avid status in lung metastases for radioactive I131 treatment in differentiated thyroid cancer patients

ObjectivesThe growing incidence of differentiated thyroid cancer (DTC) have been linked to insulin resistance and metabolic syndrome. The imperative need for developing effective diagnostic imaging tools to predict the non-iodine-avid status of lung metastasis (LMs) in differentiated thyroid cancer (DTC) patients is underscored to prevent unnecessary radioactive iodine treatment (RAI).MethodsPrimary cohort consisted 1962 pretreated LMs of 496 consecutive DTC patients with pretreated initially diagnosed LMs who underwent chest CT and subsequent post-treatment radioiodine SPECT. After automatic lesion segmentation by SE V-Net, SE Net deep learning was trained to predict non-iodine-avid status of LMs. External validation cohort contained 123 pretreated LMs of 24 consecutive patients from other two hospitals. Stepwise validation was further performed according to the nodule’s largest diameter.ResultsThe SE-Net deep learning network yielded area under the receiver operating characteristic curve (AUC) values of 0.879 (95% confidence interval: 0.852–0.906) and 0.713 (95% confidence interval: 0.613–0.813) for internal and external validation. With the LM diameter decreasing from ≥10mm to ≤4mm, the AUCs remained relatively stable, for smallest nodules (≤4mm), the model yielded an AUC of 0.783. Decision curve analysis showed that most patients benefited using deep learning to decide radioactive I131 treatment.ConclusionThis study presents a noninvasive, less radioactive and fully automatic approach that can facilitate suitable DTC patient selection for RAI therapy of LMs. Further prospective multicenter studies with larger study cohorts and related metabolic factors should address the possibility of comprehensive clinical transformation

Natural Deep Eutectic Solvent-Assisted Extraction, Structural Characterization, and Immunomodulatory Activity of Polysaccharides from <i>Paecilomyces hepiali</i>

Polysaccharides, which can be affected by different preparations, play a crucial role in the biological function of Paecilomyces hepiali (PHPS) as a health food. To explore high-valued polysaccharides and reduce the negative influence of human involvement, a green tailorable deep eutectic solvent (DES) was applied to optimize the extraction of polysaccharides (PHPS-D), followed by the evaluation of the structural properties and immunomodulation by comparison with the hot-water method (PHPS-W). The results indicated that the best system for PHPS-D was a type of carboxylic acid-based DES consisting of choline chloride and succinic acid in the molar ratio of 1:3, with a 30% water content. The optimal condition was as follows: liquid–solid ratio of 50 mL/g, extraction temperature of 85 °C, and extraction time of 1.7 h. The actual PHPS-D yield was 12.78 ± 0.17%, which was obviously higher than that of PHPS-W. The structural characteristics suggested that PHPS-D contained more uronic acid (22.34 ± 1.38%) and glucose (40.3 ± 0.5%), with a higher molecular weight (3.26 × 105 g/mol) and longer radius of gyration (78.2 ± 3.6 nm), as well as extended chain conformation, compared with PHPS-W, and these results were confirmed by AFM and SEM. Immunomodulatory assays suggested that PHPS-D showed better performance than PHPS-W regarding pinocytic activity and the secretion of NO and pro-inflammatory cytokines (IL-6, TNF-α and IL-1β) by activating the corresponding mRNA expression in RAW264.7 cells. This study showed that carboxylic acid-based DES could be a promising tailorable green system for acidic polysaccharide preparation and the valorization of P. hepiali in functional foods