A local information based protocol for networks data exchange with application to mobile sensor networks

The paper presents a new protocol for multi hop data transmission between nodes in a mobile sensor network. The only requirement for the network is to be connected. The routing is handled locally on the basis of informations contained in the data transmitted. Global (time dependent) routing table as well as knowledge on the position of the nodes are not required, since the protocol itself contains an Hand-Shake phase for the neighbour detection. This allow to have high mobility for the nodes and, moreover, it is dynamically reconfigurable once the number of the nodes varies. A innovative data structure called "the Postman Bag" is introduced to spread data collected by sensor quickly and simply. Some considerations about the computational complexity and the performances of the proposed approach are reported on the basis of some simulations and some initial tests on small dimension networks

Quantum dot-doped silica nanoparticles as probes for targeting of T-lymphocytes

To enhance diagnostic or therapeutic efficacy, novel nanomaterials must be engineered to function in biologically relevant environments, be visible by conventional fluorescent microscopy, and have multivalent loading capacity for easy detection or effective drug delivery. Here we report the fabrication of silica nanoparticles doped with quantum dots and superficially functionalized with amino and phosphonate groups. The amino groups were acylated with a water-soluble biotin-labeling reagent. The biotinylated nanoparticles were subsequently decorated with neutravidin by exploiting the strong affinity between neutravidin and biotin. The resultant neutravidin-decorated fluorescent silica nanoparticles stably dispersed under physiological conditions, were visible by conventional optical and confocal fluorescent microscopy, and could be further functionalized with macromolecules, nucleic acids, and polymers. We also coated the surface of the nanoparticles with biotinylated mouse anti-human CD3 (αCD3). The resultant fluorescent nanoassembly was taken up by Jurkat T cells through receptor-mediated endocytosis and was partially released to lysosomes. Thus, quantum dot-doped silica nanoparticles decorated with neutravidin represent a potentially excellent scaffold for constructing specific intracellular nanoprobes and transporters

Pro- and anti-oxidant properties of near-infrared (NIR) light responsive carbon nanoparticles

Elemental carbon nanomaterials (ECNMs) are redox active agents that can be exploited to purposely modify the redox balance of cells. Both pro- or antioxidant properties have been reported. However, to the best of our knowledge, there are not comprehensive studies exploring both properties on the same material in view of a potential application in medicine. At the same time, the effect of the bulk structure on the pro/antioxidant properties is poorly known. Here, carbon nanoparticles (CNPs) derived by glucose with definite size and shape have been prepared, and their redox properties evaluated in cell free systems in the dark or following activation with a Near Infrared (NIR) laser beam (945 nm, 1.3 W/cm2). We found that, when irradiated with NIR, CNPs efficiently generate heat and singlet oxygen (1O2), a property that can be exploited for dual photo-thermal (PT)/photodynamic (PD) therapy in cancer. On the other hand, in the absence of photo-activation, CNPs react with both oxidant (hydroxyl radicals) and antioxidant (glutathione) species. When tested on a murine macrophages cell line (RAW 264.7) CNPs were clearly antioxidant. Furthermore, albeit efficiently internalized, CNPs do not exert cytotoxic effect up to 80 µg/ml and do not exacerbate TNF-α-mediated inflammation. Overall, the results reported herein suggest that CNPs may represent a new class of safe nanomaterials with potential applications in medicine

The BH4 domain of Bcl-XL rescues astrocyte degeneration in amyotrophic lateral sclerosis by modulating intracellular calcium signals

Collective evidence indicates that motor neuron degeneration in amyotrophic lateral sclerosis (ALS) is non-cell-autonomous and requires the interaction with the neighboring astrocytes. Recently, we reported that a subpopulation of spinal cord astrocytes degenerates in the microenvironment of motor neurons in the hSOD1G93A mouse model of ALS. Mechanistic studies in vitro identified a role for the excitatory amino acid glutamate in the gliodegenerative process via the activation of its inositol 1,4,5-triphosphate (IP3)-generating metabotropic receptor 5 (mGluR5). Since non-physiological formation of IP3 can prompt IP3 receptor (IP3R)-mediated Ca2+ release from the intracellular stores and trigger various forms of cell death, here we investigated the intracellular Ca2+ signaling that occurs downstream of mGluR5 in hSOD1G93A-expressing astrocytes. Contrary to wild-type cells, stimulation of mGluR5 causes aberrant and persistent elevations of intracellular Ca2+ concentrations ([Ca2+]i) in the absence of spontaneous oscillations. The interaction of IP3Rs with the anti-apoptotic protein Bcl-XL was previously described to prevent cell death by modulating intracellular Ca2+ signals. In mutant SOD1-expressing astrocytes, we found that the sole BH4 domain of Bcl-XL, fused to the protein transduction domain of the HIV-1 TAT protein (TAT-BH4), is sufficient to restore sustained Ca2+ oscillations and cell death resistance. Furthermore, chronic treatment of hSOD1G93A mice with the TAT-BH4 peptide reduces focal degeneration of astrocytes, slightly delays the onset of the disease and improves both motor performance and animal lifespan. Our results point at TAT-BH4 as a novel glioprotective agent with a therapeutic potential for AL

Addressing Heterogeneity in Direct Analysis of Extracellular Vesicles and Their Analogs by Membrane Sensing Peptides as Pan‐Vesicular Affinity Probes

: Extracellular vesicles (EVs), crucial mediators of cell-to-cell communication, hold significant diagnostic potential due to their ability to concentrate protein biomarkers in bodily fluids. However, challenges in isolating EVs from biological specimens hinder their widespread use. The preferred strategy involves direct analysis, integrating isolation and analysis solutions, with immunoaffinity methods currently dominating. Yet, the heterogeneous nature of EVs poses challenges, as proposed markers may not be as universally present as thought, raising concerns about biomarker screening reliability. This issue extends to EV-mimics, where conventional methods may lack applicability. Addressing these challenges, the study reports on Membrane Sensing Peptides (MSP) as pan-vesicular affinity ligands for both EVs and their non-canonical analogs, streamlining capture and phenotyping through Single Molecule Array (SiMoA). MSP ligands enable direct analysis of circulating EVs, eliminating the need for prior isolation. Demonstrating clinical translation, MSP technology detects an EV-associated epitope signature in serum and plasma, distinguishing myocardial infarction from stable angina. Additionally, MSP allow analysis of tetraspanin-lacking Red Blood Cell-derived EVs, overcoming limitations associated with antibody-based methods. Overall, the work underlines the value of MSP as complementary tools to antibodies, advancing EV analysis for clinical diagnostics and beyond, and marking the first-ever peptide-based application in SiMoA technology

Increasing biases can be more efficient than increasing weights

We introduce a novel computational unit for neural networks that features multiple biases, challenging the traditional perceptron structure. This unit emphasizes the importance of preserving uncorrupted information as it is passed from one unit to the next, applying activation functions later in the process with specialized biases for each unit. Through both empirical and theoretical analyses, we show that by focusing on increasing biases rather than weights, there is potential for significant enhancement in a neural network model's performance. This approach offers an alternative perspective on optimizing information flow within neural networks. See source code at https://github.com/CuriosAI/dac-dev.Comment: Major rewriting. Supersedes v1 and v2. Focusing on the fact that not all parameters are born equal: biases can be more important than weights. Accordingly, new title and new abstract, and many more experiments on fully connected architectures. This is the extended version of the paper published at WACV 202

Desmoplastic small round cell tumor:from state of the art to future clinical prospects

Introduction: Desmoplastic small round cell tumor (DSRCT) is an extremely rare and highly aggressive soft tissue sarcoma, presenting mainly in male adolescents and young adults with multiple nodules disseminated within the abdominopelvic cavity. Despite a multimodal approach including aggressive cytoreductive surgery, intensive multi-agent chemotherapy, and postoperative whole abdominopelvic radiotherapy, the prognosis for DSRCT remains dismal. Median progression-free survival ranges between 4 and 21 months, and overall survival between 17 and 60 months, with the 5-year overall survival rate in the range of 10–20%. Area covered: This review discusses the treatment strategies used for DSRCT over the years, the state of the art of current treatments, and future clinical prospects. Expert opinion: The unsatisfactory outcomes for patients with DSRCT warrant investigations into innovative treatment combinations. An international multidisciplinary and multi-stakeholder collaboration, involving both pediatric and adult sarcoma communities, is needed to propel preclinical model generation and drug development, and innovative clinical trial designs to enable the timely testing of treatments involving novel agents guided by biology to boost the chances of survival for patients with this devastating disease.</p

Protein fingerprints of cultured CA3-CA1 hippocampal neurons: comparative analysis of the distribution of synaptosomal and cytosolic proteins

<p>Abstract</p> <p>Background</p> <p>All studies aimed at understanding complex molecular changes occurring at synapses face the problem of how a complete view of the synaptic proteome and of its changes can be efficiently met. This is highly desirable when synaptic plasticity processes are analyzed since the structure and the biochemistry of neurons and synapses get completely reshaped. Because most molecular studies of synapses are nowadays mainly or at least in part based on protein extracts from neuronal cultures, this is not a feasible option: these simplified versions of the brain tissue on one hand provide an homogeneous pure population of neurons but on the other yield only tiny amounts of proteins, many orders of magnitude smaller than conventional brain tissue. As a way to overcome this limitation and to find a simple way to screen for protein changes at cultured synapses, we have produced and characterized two dimensional electrophoresis (2DE) maps of the synaptic proteome of CA3-CA1 hippocampal neurons in culture.</p> <p>Results</p> <p>To obtain 2D maps, hippocampal cultures were mass produced and after synaptic maturation, proteins were extracted following subfractionation procedures and separated by 2D gel electrophoresis. Similar maps were obtained for the crude cytosol of cultured neurons and for synaptosomes purified from CA3-CA1 hippocampal tissue. To efficiently compare these different maps some clearly identifiable reference points were molecularly identified by mass spectrometry and immunolabeling methods. This information was used to run a differential analysis and establish homologies and dissimilarities in these 2D protein profiles.</p> <p>Conclusion</p> <p>Because reproducible fingerprints of cultured synapses were clearly obtained, we believe that our mapping effort could represent a simple tool to screen for protein expression and/or protein localization changes in CA3-CA1 hippocampal neurons following plasticity.</p

Experiences and Lessons Learned from the SIGMOD Entity Resolution Programming Contests

We report our experience in running three editions (2020, 2021, 2022) of the SIGMOD programming contest, a well-known event for students to engage in solving exciting data management problems. During this period we had the opportunity of introducing participants to the entity resolution task, which is of paramount importance in the data integration community. We aim at sharing the executive decisions, made by the people co-authoring this report, and the lessons learned