The increasing interest in innovative solutions for health and physiological monitoring has recently fostered the development of smaller biomedical devices. These devices are capable of recording an increasingly large number of biosignals simultaneously, while maximizing the user’s comfort. In this study, we have designed and realized a novel wearable multisensor ring-shaped probe that enables synchronous, real-time acquisition of photoplethysmographic (PPG) and galvanic skin response (GSR) signals. The device integrates both the PPG and GSR sensors onto a single probe that can be easily placed on the finger, thereby minimizing the device footprint and overall size. The system enables the extraction of various physiological indices, including heart rate (HR) and its variability, oxygen saturation (SpO₂), and GSR levels, as well as their dynamic changes over time, to facilitate the detection of different physiological states, e.g., rest and stress. After a preliminary SpO₂ calibration procedure, measurements have been carried out in laboratory on healthy subjects to demonstrate the feasibility of using our system to detect rapid changes in HR, skin conductance, and SpO₂ across various physiological conditions (i.e., rest, sudden stress-like situation and breath holding). The early findings encourage the use of the device in daily-life conditions for real-time monitoring of different physiological states.

The cell division cycle 25 (Cdc25) protein family plays a crucial role in controlling cell proliferation, making it an excellent target for cancer therapy. In this work, a set of small molecules were identified as Cdc25 modulators by applying a mixed ligand-structure-based approach and taking advantage of the correlation between the chemosensitivity of selected structures and the protein expression pattern of the proposed target. In the first step of the in silico protocol, a set of molecules acting as Cdc25 inhibitors were identified through a new ligand-based protocol and the evaluation of a large database of molecular structures. Subsequently, induced-fit docking (IFD) studies allowed us to further reduce the number of compounds biologically screened. In vitro antiproliferative and enzymatic inhibition assays on the selected compounds led to the identification of new structurally heterogeneous inhibitors of Cdc25 proteins. Among them, J3955, the most active inhibitor, showed concentration-dependent antiproliferative activity against HepG2 cells, with GI₅₀ in the low micromolar range. When J3955 was tested in cell-cycle perturbation experiments, it caused mitotic failure by G2/M-phase cell-cycle arrest. Finally, Western blotting analysis showed an increment of phosphorylated Cdk1 levels in cells exposed to J3955, indicating its specific influence in cellular pathways involving Cdc25 proteins.

CDK-1 and PARP-1 play crucial roles in breast cancer progression. Compounds acting as CDK-1 and/or PARP-1 inhibitors can induct cell death in breast cancer with a selective synthetic lethality mechanism. A mixed treatment by means of CDK-1 and PARP-1 inhibitors resulted in radical breast cancer cell growth reduction. Inhibitors with a dual target mechanism of action could arrest cancer progression by simultaneously blocking the DNA repair mechanism and cell cycle, resulting in advantageous monotherapy. To this aim, in the present work, we identified compound 645656 with a significant affinity for both CDK-1 and PARP-1 by a mixed ligand- and structure-based virtual screening protocol. The Biotarget Predictor Tool was used at first in a Multitarget mode to filter the large National Cancer Institute (NCI) database. Then, hierarchical docking studies were performed to further screen the compounds and evaluate the ligands binding mode, whose putative dual-target mechanism of action was investigated through the correlation between the antiproliferative activity data and the target proteins’ (CDK-1 and PARP-1) expression pattern. Finally, a Molecular Dynamics Simulation confirmed the high stability of the most effective selected compound 645656 in complex with both PARP-1 and CDK-1.

In this article, we present Distributed Computing for Constrained Devices (DC4CD), a novel software architecture that supports symbolic distributed computing on wireless sensor networks. DC4CD integrates the functionalities of a high-level symbolic interpreter, a compiler, and an operating system, and includes networking abstractions to exchange high-level symbolic code among peer devices. Contrarily to other architectures proposed in the literature, DC4CD allows for changes at runtime, even on deployed nodes of both application and system code. Experimental results show that DC4CD is more efficient in terms of memory usage than existing architectures, with which it also compares well in terms of execution efficiency.

In vitro antiproliferative assays still represent one of the most important tools in the anticancer drug discovery field, especially to gain insights into the mechanisms of action of anticancer small molecules. The NCI-DTP (National Cancer Institute Developmental Therapeutics Program) undoubtedly represents the most famous project aimed at rapidly testing thousands of compounds against multiple tumor cell lines (NCI60). The large amount of biological data stored in the National Cancer Institute (NCI) database and many other databases has led researchers in the fields of computational biology and medicinal chemistry to develop tools to predict the anticancer properties of new agents in advance. In this work, based on the available antiproliferative data collected by the NCI and the manipulation of molecular descriptors, we propose the new in silico Antiproliferative Activity Predictor (AAP) tool to calculate the GI₅₀ values of input structures against the NCI60 panel. This ligand-based protocol, validated by both internal and external sets of structures, has proven to be highly reliable and robust. The obtained GI₅₀ values of a test set of 99 structures present an error of less than ±1 unit. The AAP is more powerful for GI₅₀ calculation in the range of 4–6, showing that the results strictly correlate with the experimental data. The encouraging results were further supported by the examination of an in-house database of curcumin analogues that have already been studied as antiproliferative agents. The AAP tool identified several potentially active compounds, and a subsequent evaluation of a set of molecules selected by the NCI for the one-dose/five-dose antiproliferative assays confirmed the great potential of our protocol for the development of new anticancer small molecules. The integration of the AAP tool in the free web service DRUDIT provides an interesting device for the discovery and/or optimization of anticancer drugs to the medicinal chemistry community. The training set will be updated with new NCI-tested compounds to cover more chemical spaces, activities, and cell lines. Currently, the same protocol is being developed for predicting the TGI (total growth inhibition) and LC₅₀ (median lethal concentration) parameters to estimate toxicity profiles of small molecules.