Sarcopenia Is a Negative Prognostic Factor in Patients Undergoing Transarterial Chemoembolization (TACE) for Hepatic Malignancies

Background and Aims: While transarterial chemoembolization (TACE) represents a standard of therapy for intermediate-stage hepatocellular carcinoma (HCC) and is also routinely performed in patients with liver metastases, it is still debated which patients represent the ideal candidates for TACE therapy in terms of overall survival. Sarcopenia, the degenerative loss of skeletal muscle mass and strength, has been associated with an adverse outcome for various malignancies, but its role in the context of TACE has largely remained unknown. Here, we evaluated the role of sarcopenia on the outcome of patients undergoing TACE for primary and secondary liver cancer. Methods: The patients’ psoas muscle size was measured on axial computed tomography (CT) scans and normalized for the patients’ height squared. This value was referred to as the psoas muscle index (PMI). The PMI was correlated with clinical and laboratory markers. Results: While pre-interventional sarcopenia had no impact on the direct tumor response to TACE, sarcopenic patients with a pre-interventional PMI below our ideal cut-o value of 13.39 mm/m2 had a significantly impaired long-term outcome with a median overall survival of 491 days compared to 1291 days for patients with a high PMI. This finding was confirmed by uni- and multivariate Cox-regression analyses. Moreover, a progressive rapid decline in muscle mass after TACE was a predictor for an unfavorable prognosis. Conclusion: Our data suggest that sarcopenia represents a previously unrecognized prognostic factor for patients undergoing TACE therapy which might yield important information on the patients’ post-interventional outcome and should therefore be implemented into clinical stratification algorithms

Neutron scattering and polymer dynamics

4 páginas, 4 figuras.-- El pdf del artículo es la versión post-print.Nowadays polymers are ubiquitous in our daily life because they are durable, cheap to produce, easy to process and exhibit very versatile and favorable mechanical properties. For example, depending on temperature or time the same polymer may be viscous, rubber elastic, very tough with high impact strength or even brittle. Polymers are composed of macromolecules which are built up by a large number monomer units linked together by covalent bonds. Due to this connectivity, the relevant processes driving the dynamics in polymers depend on the length scale of observation. While at typical inter- and intra-macromolecular length scales (≈ 10 Å and below) polymer dynamics display the universal features of glass-forming systems, at larger distances the macromolecular character of the polymer chains prevails –there, entropy and topological constraints (‘entanglements’) play the major role. Carbon and Hydrogen are in most cases the main constituents of polymers. Therefore, neutron scattering combined with isotopic substitution (H/D labeling) is an extremely well-suited technique to study the dynamical processes of polymeric materials at a molecular level. Motions of particular molecular groups or given polymer chains, e. g. in a polymer blend, can be selectively investigated by neutron scattering. However, the restricted dynamic window offered by this technique prevents a complete characterization of the complex polymer dynamics, including several multi-scale processes the characteristic times of which span over many orders of magnitude. The combination with other experimental techniques is, in most cases, essential to fully characterize the processes; in addition, the use of complementary MD-simulations has proved to be crucial for the interpretation of the neutron-scattering results.Peer reviewe

Fire and resprouting in Mediterranean ecosystems: Insights from an external biogeographical region, the mexical shrubland

7 páginas, 3 tablas.We investigated modes of regeneration of dominant species of the mexical vegetation after fire. The mexical shrubland shows a remarkable structural, morphological, and floristic similarity to Mediterranean-type vegetation and is considered a relict of the Madro-Tertiary Geoflora under a non- mediterranean climate. This vegetation provides an ideal scenario to test the role of fire in Mediterranean ecosystems because historical fire occurrence is absent and the species assembly is constituted mostly by Madro-Tertiary elements and Neotropical species (some of them, endemic species from Mexico). The existence of congeneric species of the California chaparral allows us to determine the regeneration ability of these communities after fire in relation to resprouting and seeding strategies, which are widespread modes reported in the Mediterranean-type vegetation. By the experimental application of fire in the two biogeographical groups of species, we tested the hypothesis that low resprouting ability of California congeneric species (Madro-Tertiary species) after fire would indicate that fire has played an important selective force in the resprouting habit. A low resprouting ability in the Neotropical group of species would suggest that fire has molded the set of species dominating fire-prone environments. Our results indicated that resprouting is a widespread trait in the mexical species characterized by the presence of lignotubers and burls. Resprouting can be considered an ancient trait, probably linked to losses of aboveground biomass, that became a pre-adaptation in Mediterranean fire-prone communities. The Neotropical group of species showed less ability to regenerate after fire, and small plants were more likely to die after disturbance in this group than in the Madro-Tertiary group. The resprouting feature and the seeder strategy of other species after a fire in the mexical shrubland are similar to Mediterranean-type ecosystems, emphasizing their common origin and the relevance of phylogenetic and biogeographical studies to explain current patterns of vegetation.Peer reviewe

Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies

A knowledge gap persists between Machine Learning (ML) developers (e.g., data scientists) and practitioners (e.g., clinicians), hampering the full utilization of ML for clinical data analysis. We investigated the potential of the chatGPT Advanced Data Analysis (ADA), an extension of GPT-4, to bridge this gap and perform ML analyses efficiently. Real-world clinical datasets and study details from large trials across various medical specialties were presented to chatGPT ADA without specific guidance. ChatGPT ADA autonomously developed state-of-the-art ML models based on the original study's training data to predict clinical outcomes such as cancer development, cancer progression, disease complications, or biomarkers such as pathogenic gene sequences. Strikingly, these ML models matched or outperformed their published counterparts. We conclude that chatGPT ADA offers a promising avenue to democratize ML in medicine, making advanced analytics accessible to non-ML experts and promoting broader applications in medical research and practice

Національні інтереси держави в інформаційній сфері

На сьогодні Україна перебуває в умовах протиборства, в яких саме забезпечення інформаційної безпеки грає ключовий аспект в формуванні національних інтересів держави. В даній роботі розглянуто сучасний стан інформаційної сфери як пріоритетний напрямок національних інтересів України

Exchange-correlation effects on quantum wires with spin-orbit interactions under the influence of in-plane magnetic fields

12 pages.-- PACS numbers: 73.63.Nm, 71.70.Ej, 71.15.Mb, 71.70.Gm.-- Final full-text version of the paper available at: http://dx.doi.org/10.1103/PhysRevB.76.115306.Within the noncollinear local spin-density approximation, we have studied the ground state structure of a parabolically confined quantum wire submitted to an in-plane magnetic field, including both Rashba and Dresselhaus spin-orbit interactions. We have explored a wide range of linear electronic densities in the weak (strong) coupling regimes that appear when the ratio of spin-orbit to confining energy is small (large). These results are used to obtain the conductance of the wire. In the strong coupling limit, the interplay between the applied magnetic field irrespective of the in-plane direction, the exchange-correlation energy, and the spin-orbit energy produces anomalous plateaus in the conductance vs linear density plots that are otherwise absent, or washes out plateaus that appear when the exchange-correlation energy is not taken into account.This work has been performed under Grants No. FIS2005-01414 and No. FIS2005-02796 from DGI (Spain), Grant No. 2005SGR00343 from Generalitat de Catalunya, and under Grant No. INFN07-30 from the Italian INFN-Spanish DGI agreement.http://dx.doi.org/10.1103/PhysRevB.76.11530

Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels

Artificial intelligence (AI) methods are revolutionizing medical image analysis. However, robust AI models require large multi-site datasets for training. While multiple stakeholders have provided publicly available datasets, the ways in which these data are labeled differ widely. For example, one dataset of chest radiographs might contain labels denoting the presence of metastases in the lung, while another dataset of chest radiograph might focus on the presence of pneumonia. With conventional approaches, these data cannot be used together to train a single AI model. We propose a new framework that we call flexible federated learning (FFL) for collaborative training on such data. Using publicly available data of 695,000 chest radiographs from five institutions - each with differing labels - we demonstrate that large and heterogeneously labeled datasets can be used to train one big AI model with this framework. We find that models trained with FFL are superior to models that are trained on matching annotations only. This may pave the way for training of truly large-scale AI models that make efficient use of all existing data.Comment: 2 figures, 3 tables, 5 supplementary table

Time-efficient combined morphologic and quantitative joint MRI based on clinical image contrasts -- An exploratory in-situ study of standardized cartilage defects

OBJECTIVES: Quantitative MRI techniques such as T2 and T1$\rho$ mapping are beneficial in evaluating cartilage and meniscus. We aimed to evaluate the MIXTURE (Multi-Interleaved X-prepared Turbo-Spin Echo with IntUitive RElaxometry) sequences that provide morphologic images with clinical turbo spin-echo (TSE) contrasts and additional parameter maps versus reference TSE sequences in an in-situ model of human cartilage defects. MATERIALS AND METHODS: Prospectively, standardized cartilage defects of 8mm, 5mm, and 3mm diameter were created in the lateral femora of 10 human cadaveric knee specimens (81$\pm$10 years, nine male/one female). Using a clinical 3T MRI scanner and knee coil, MIXTURE sequences combining (i) proton-density weighted fat-saturated (PD-w FS) images and T2 maps and (ii) T1-weighted images and T1$\rho$ maps were acquired before and after defect creation, alongside the corresponding 2D TSE and 3D TSE reference sequences. Defect delineability, bone texture, and cartilage relaxation times were quantified. Inter-sequence comparisons were made using appropriate parametric and non-parametric tests. RESULTS: Overall, defect delineability and texture features were not significantly different between the MIXTURE and reference sequences. After defect creation, relaxation times increased significantly in the central femur (for T2) and all regions combined (for T1$\rho$). CONCLUSION: MIXTURE sequences permit time-efficient simultaneous morphologic and quantitative joint assessment based on clinical image contrasts. While providing T2 or T1$\rho$ maps in clinically feasible scan time, morphologic image features, i.e., cartilage defect delineability and bone texture, were comparable between MIXTURE and corresponding reference sequences.Comment: 12 pages (main body), 3 tables, 6 figure