The Columbus logistics support at the APMC: Requirements and implementation aspects

This paper focuses on the logistics support to be provided by the APM Center (APMC). Among the Columbus ground infrastructures, this center is tasked to provide logistics, sustaining engineering and P/L integration support to the ongoing missions of the APM, i.e. the Columbus Laboratory attached to the Freedom Space Station. The following is illustrated: an analysis of the requirements that are levied on the logistics support of the APM; how such requirements are reflected in the corresponding support to be available on-ground and at APMC; the functional components of the APMC logistics support and how such components interact each other; how the logistics support function interfaces with the other functions of the ground support; and how the logistics support is being designed in terms of resources (such as hardware, data bases, etc.). Emphasis is given to the data handling aspects and to the related data bases that will constitute for the logistics activities the fundamental source of information during the APM planned lifetime. Functional and physical architectures, together with trades for possible implementation, are addressed. Commonalities with other centers are taken into account and recommendations are made for possible reuse of tools already developed in the C/D phase. Finally, programmatic considerations are discussed for the actual implementation of the center

Sulfur-containing histidine compounds inhibit γ-glutamyl transpeptidase activity in human cancer cells

γ-Glutamyl transpeptidase (GGT) is an enzyme located on the surface of cellular membranes and involved in GSH metabolism and maintenance of redox homeostasis. High GGT expression on tumor cells is associated with increased cell proliferation and resistance against chemotherapy. GGT inhibitors evaluated so far in clinical trials are too toxic for human use. In this study, using enzyme kinetics analyses, we demonstrate that ovothiols, 5(Nπ)-methyl thiohistidines of marine origin, act as noncompetitive inhibitors of GGT, with an apparent Ki of 21 μM, when we fixed the concentrations of the donor substrate. We found that these compounds are more potent than the known GGT inhibitor 6-diazo-5-oxo-L-norleucine and are not toxic toward human embryonic cells. In particular, cellular process-specific fluorescence-based assays revealed that ovothiols induce a mixed cell-death phenotype of apoptosis and autophagy in GGT-overexpressing cell lines, including human liver cancer and chronic B leukemic cells. The findings of our study provide the basis for further development of 5-thiohistidines as therapeutics for GGT-positive tumors and highlight that GGT inhibition is involved in autophagy

Multimodal Classification of Parkinson's Disease in Home Environments with Resiliency to Missing Modalities

Parkinson’s disease (PD) is a chronic neurodegenerative condition that affects a patient’s everyday life. Authors have proposed that a machine learning and sensor-based approach that continuously monitors patients in naturalistic settings can provide constant evaluation of PD and objectively analyse its progression. In this paper, we make progress toward such PD evaluation by presenting a multimodal deep learning approach for discriminating between people with PD and without PD. Specifically, our proposed architecture, named MCPD-Net, uses two data modalities, acquired from vision and accelerometer sensors in a home environment to train variational autoencoder (VAE) models. These are modality-specific VAEs that predict effective representations of human movements to be fused and given to a classification module. During our end-to-end training, we minimise the difference between the latent spaces corresponding to the two data modalities. This makes our method capable of dealing with missing modalities during inference. We show that our proposed multimodal method outperforms unimodal and other multimodal approaches by an average increase in F1-score of 0.25 and 0.09, respectively, on a data set with real patients. We also show that our method still outperforms other approaches by an average increase in F1-score of 0.17 when a modality is missing during inference, demonstrating the benefit of training on multiple modalities

A multimodal dataset of real world mobility activities in Parkinson’s disease

Parkinson’s disease (PD) is a neurodegenerative disorder characterised by motor symptoms such as gait dysfunction and postural instability. Technological tools to continuously monitor outcomes could capture the hour-by-hour symptom fluctuations of PD. Development of such tools is hampered by the lack of labelled datasets from home settings. To this end, we propose REMAP (REal-world Mobility Activities in Parkinson’s disease), a human rater-labelled dataset collected in a home-like setting. It includes people with and without PD doing sit-to-stand transitions and turns in gait. These discrete activities are captured from periods of free-living (unobserved, unstructured) and during clinical assessments. The PD participants withheld their dopaminergic medications for a time (causing increased symptoms), so their activities are labelled as being “on” or “off” medications. Accelerometry from wrist-worn wearables and skeleton pose video data is included. We present an open dataset, where the data is coarsened to reduce re-identifiability, and a controlled dataset available on application which contains more refined data. A use-case for the data to estimate sit-to-stand speed and duration is illustrated

Cerebral organoids at the air-liquid interface generate diverse nerve tracts with functional output.

Neural organoids have the potential to improve our understanding of human brain development and neurological disorders. However, it remains to be seen whether these tissues can model circuit formation with functional neuronal output. Here we have adapted air-liquid interface culture to cerebral organoids, leading to improved neuronal survival and axon outgrowth. The resulting thick axon tracts display various morphologies, including long-range projection within and away from the organoid, growth-cone turning, and decussation. Single-cell RNA sequencing reveals various cortical neuronal identities, and retrograde tracing demonstrates tract morphologies that match proper molecular identities. These cultures exhibit active neuronal networks, and subcortical projecting tracts can innervate mouse spinal cord explants and evoke contractions of adjacent muscle in a manner dependent on intact organoid-derived innervating tracts. Overall, these results reveal a remarkable self-organization of corticofugal and callosal tracts with a functional output, providing new opportunities to examine relevant aspects of human CNS development and disease

Efficacy of the combination of cisplatin with either gemcitabine and vinorelbine or gemcitabine and paclitaxel in the treatment of locally advanced or metastatic non-small-cell lung cancer: a phase III randomised trial of the Southern Italy Cooperative Oncology Group (SICOG 0101)

Triplet regimens were occasionally reported to produce a higher response rate (RR) than doublets in locally advanced or metastatic non-small-cell lung cancer (NSCLC). This trial was conducted to assess (i) whether the addition of cisplatin (CDDP) to either gemcitabine (GEM) and vinorelbine (VNR) or GEM and paclitaxel (PTX) significantly prolongs overall survival (OS) and (ii) to compare the toxicity of PTX-containing and VNR-containing combinations

Secondary electron yield reduction by femtosecond pulse laser-induced periodic surface structuring

The electron-cloud phenomenon is one cause of beam instabilities in high intensity positive particle accelerators. Among the proposed techniques to mitigate or control this detrimental effect, micro-/nano-geometrical modifications of vacuum chamber surfaces are promising to reduce the number of emitted secondary electrons. Femtosecond laser surface structuring readily allows the fabrication of Laser Induced Periodic Surface Structures (LIPSS) and is utilized in several fields, but has not yet been tested for secondary electron emission reduction. In this study, such treatment is carried out on copper samples using linearly and circularly polarized femtosecond laser pulses. The influence of the formed surface textures on the secondary electron yield (SEY) is studied. We investigate the morphological properties as well as the chemical composition by means of SEM, AFM, Raman and XPS analyses. Surface modification with linearly polarized light is more effective than using circularly polarized light, leading to a significant SEY reduction. Even though the SEY maximum is only reduced to a value of ~1.7 compared to standard laser-induced surface roughening approaches, the femtosecond-LIPSS process enables to limit material ablation as well as the production of undesired dust, and drastically reduces the number of redeposited nanoparticles at the surface, which are detrimental for applications in particle accelerators. Moreover, conditioning tests reveal that LIPSS processed Cu can reach SEY values below unity at electron irradiation doses above 10−3 C/mm2