Quaterpyridine Ligands for Panchromatic Ru(II) Dye Sensitizers

A new general synthetic access to carboxylated quaterpyridines (qpy), of interest as ligands for panchromatic dyesensitized solar cell organometallic sensitizers, is presented. The strategic step is a Suzuki−Miyaura cross-coupling reaction, which has allowed the preparation of a number of representative unsubstituted and alkyl and (hetero)aromatic substituted qpys. To bypass the poor inherent stability of 2-pyridylboronic acid derivatives, we successfully applied N-methyliminodiacetic acid (MIDA) boronates as key reagents, obtaining the qpy ligands in good yields up to (quasi)gram quantities. The structural, spectroscopic (NMR and UV−vis), electrochemical, and electronic characteristics of the qpy have been experimentally and computationally (DFT) investigated. The easy access to the bis-thiocyanato Ru(II) complex of the parent species of the qpy series, through an efficient route which bypasses the use of Sephadex column chromatography, is shown. The bis-thiocyanato Ru(II) complex has been spectroscopically (NMR and UV−vis), electrochemically, and computationally investigated, relating its properties to those of previously reported Ru(II)−qpy complexes.“This document is the Accepted Manuscript version of a Published Work that appeared in final form in [The Journal of Organic Chemistry], copyright © American Chemical Society after peer review and technical editing by the publisher

A 5-year retrospective longitudinal study on the incidence and the risk factors of osteonecrosis of the jaws in patients treated with zoledronic acid for bone metastases from solid tumors

Background: The aim of this study was to evaluate the incidence and the risk factors of osteonecrosis of the jaw (ONJ) in a group of patients treated with zoledronic acid (ZA) for bone metastases from solid tumors and enrolled in a preventive dental program. Material and Methods: This 5-year retrospective longitudinal study included all consecutive oncological patients who underwent at least one infusion with ZA between 2004 and 2011 for bone metastases due to solid neoplasms. Results: Of the 156 patients enrolled in the study, 17 developed ONJ (10.89%). At the multivariate analysis, severe periodontal disease (P=0.025), tooth extraction (P<0.0001) and starting the preventive dental program after the beginning of ZA therapy (P=0.02) were the only factors which showed a significant association with the occurrence of ONJ. Conclusions: This study demonstrated the importance of beginning dental prevention before zoledronic acid exposure in reducing ONJ occurrence, especially in the long term. The results of this research show that control of periodontal disease and an increase in the time between tooth extraction and the first ZA administration are recommended in order to reduce the risk of ONJ developmen

Deep learning and embeddings for problems of computational biology

The development of Next Generation Sequencing promotes Biology in the Big Data era. The ever-increasing gap between proteins with known sequences and those with a complete functional annotation requires computational methods for automatic structure and functional annotation. My research has been focusing on proteins and led so far to the development of three novel tools, DeepREx, E-SNPs&GO and ISPRED-SEQ, based on Machine and Deep Learning approaches. DeepREx computes the solvent exposure of residues in a protein chain. This problem is relevant for the definition of structural constraints regarding the possible folding of the protein. DeepREx exploits Long Short-Term Memory layers to capture residue-level interactions between positions distant in the sequence, achieving state-of-the-art performances. With DeepRex, I conducted a large-scale analysis investigating the relationship between solvent exposure of a residue and its probability to be pathogenic upon mutation. E-SNPs&GO predicts the pathogenicity of a Single Residue Variation. Variations occurring on a protein sequence can have different effects, possibly leading to the onset of diseases. E-SNPs&GO exploits protein embeddings generated by two novel Protein Language Models (PLMs), as well as a new way of representing functional information coming from the Gene Ontology. The method achieves state-of-the-art performances and is extremely time-efficient when compared to traditional approaches. ISPRED-SEQ predicts the presence of Protein-Protein Interaction sites in a protein sequence. Knowing how a protein interacts with other molecules is crucial for accurate functional characterization. ISPRED-SEQ exploits a convolutional layer to parse local context after embedding the protein sequence with two novel PLMs, greatly surpassing the current state-of-the-art. All methods are published in international journals and are available as user-friendly web servers. They have been developed keeping in mind standard guidelines for FAIRness (FAIR: Findable, Accessible, Interoperable, Reusable) and are integrated into the public collection of tools provided by ELIXIR, the European infrastructure for Bioinformatics

3D printed lattice metal structures for enhanced heat transfer in latent heat storage systems

The low thermal conductivity of Phase Change Materials (PCMs), e.g., paraffin waxes, is one of the main drawbacks of latent heat storage, especially when fast charging and discharging cycles are required. The introduction of highly conductive fillers in the PCM matrix may be an effective solution; however, it is difficult to grant their stable and homogeneous dispersion, which therefore limits the resulting enhancement of the overall thermal conductivity. Metal 3D printing or additive manufacturing, instead, allows to manufacture complex geometries with precise patterns, therefore allowing the design of optimal paths for heat conduction within the PCM. In this work, a device-scale latent heat storage system operating at medium temperatures (∼ 90 °C) was manufactured and characterized. Its innovative design relies on a 3D Cartesian metal lattice, fabricated via laser powder bed fusion, to achieve higher specific power densities. Numerical and experimental tests demonstrated remarkable specific power (approximately 714 ± 17 W kg−1 and 1310 ± 48 W kg−1 during heat charge and discharge, respectively). Moreover, the device performance remained stable over multiple charging and discharging cycles. Finally, simulation results were used to infer general design guidelines to further enhance the device performance. This work aims at promoting the use of metal additive manufacturing to design efficient and responsive thermal energy storage units for medium-sized applications, such as in the automotive sector (e.g. speed up of the engine warm up or as an auxiliary for other enhanced thermal management strategies

Enhanced latent thermal energy battery with additive manufacturing

The low thermal conductivity of Phase Change Materials (PCMs), such as paraffin waxes, hinders efficient latent heat storage, especially for rapid charging and discharging cycles. To address this issue, this study explores experimentally and numerically the use of metal additive manufacturing to create a latent heat storage system operating at medium temperatures (around 90°C). A 3D Cartesian metal lattice is manufactured through laser powder bed fusion to optimize heat conduction within the PCM. Experimental tests show impressive specific power densities (approximately 714 ± 17 W kg−1 during charging and 1310 ± 48 W kg−1 during discharging). Moreover, the device exhibits stability over multiple cycles. Finally, the validated finite-element model has the potential to provides a basis for general design guidelines to boost the system's performance further. Potential applications of this technology are highlighted in the automotive industry, where such systems could efficiently manage thermal energy, for instance, by capturing excess heat from an engine's cooling radiator to expedite the warm-up process during a cold start, which is a critical phase for reducing pollutant emissions

E-SNPs&GO: embedding of protein sequence and function improves the annotation of human pathogenic variants

Motivation: The advent of massive DNA sequencing technologies is producing a huge number of human single-nucleotide polymorphisms occurring in protein-coding regions and possibly changing their sequences. Discriminating harmful protein variations from neutral ones is one of the crucial challenges in precision medicine. Computational tools based on artificial intelligence provide models for protein sequence encoding, bypassing database searches for evolutionary information. We leverage the new encoding schemes for an efficient annotation of protein variants.Results: E-SNPs&amp;GO is a novel method that, given an input protein sequence and a single amino acid variation, can predict whether the variation is related to diseases or not. The proposed method adopts an input encoding completely based on protein language models and embedding techniques, specifically devised to encode protein sequences and GO functional annotations. We trained our model on a newly generated dataset of 101 146 human protein single amino acid variants in 13 661 proteins, derived from public resources. When tested on a blind set comprising 10 266 variants, our method well compares to recent approaches released in literature for the same task, reaching a Matthews Correlation Coefficient score of 0.72. We propose E-SNPs&amp;GO as a suitable, efficient and accurate large-scale annotator of protein variant datasets

Laparoscopic Nephron-Sparing Calycectomy for Treating Fraley&apos;s Syndrome

Background/Aims/Objectives: Various nephron-sparing approaches were described as part of surgical management for Fraley's syndrome, a rare anatomic variant of the renal vascular anatomy that compresses the upper pole infundibulum resulting in an upper calyceal obstruction and dilatation, with symptoms of flank pain and hematuria. To date, descriptions of minimally invasive correction techniques are anecdotal. METHODS: A retroperitoneal pure laparoscopic approach using the nephron-sparing technique was chosen in the presented case. RESULTS: In this report, we demonstrated that if laparoscopic calycectomy is performed without clamping of renal branches, parenchymal ischemia can be completely avoided. Additionally, the preservation of renal tissue surrounding the calyx enables the preservation of the intrasinusal segmental arteries flow, thereby avoiding their accidental closure by hemostatic sutures. CONCLUSIONS: In conclusion, Laparoscopic Nephron-Sparing Calycectomy is a safe and effective surgical procedure for the treatment of Fraley's syndrome. Consistent laparoscopic experience is required before embarking on this kind of surgery