Ketogenic Diet in Neonates with Drug-Resistant Epilepsy: Efficacy and Side Effects-A Single Center's Initial Experience.

BACKGROUND: For patients with pharmacoresistant epilepsy, a therapeutic option is ketogenic diet. Currently, data on young infants are scarce, particularly during hospitalization in the neonatal intensive care unit (NICU). OBJECTIVE: The aim of the present study was to evaluate the short-term (3-month) efficacy and side effects of ketogenic diet in infants with "drugs-resistant" epilepsy treated during NICU stay. METHODS: This retrospective study included infants aged under 2 months started on ketogenic diet during NICU hospitalization to treat drug-resistant epilepsy from April 2018 to November 2022. RESULTS: Thirteen term-born infants were included, three (23.1%) of whom were excluded because they did not respond to the ketogenic diet. Finally, we included 10 infants. Six (60%) patients took three antiepileptics before starting the ketogenic diet, while four (40%) took more drugs. Diet had a good response in four (40%) patients. In four patients, the ketogenic diet was suspended because of the onset of serious side effects. The emetic levels of sodium, potassium, and chlorine, pH, and onset of diarrhea, constipation, and gastroesophageal reflux showed significant differences. Ketonuria was higher and blood pH lower in the group that took more than three drugs than in the group taking fewer than three drugs. CONCLUSION: The ketogenic diet is efficacious and safe in infants, but the early and aggressive management of adverse reactions is important to improve the safety and effectiveness of the ketogenic treatment.

Short Efficacy Evaluation of External Ventricular Drains Versus Ventriculosubgaleal Shunt in the Management of Neonatal Posthemorrhagic Hydrocephalus: A Retrospective Single-Center Cohort Study.

BACKGROUND: Different temporizing neurosurgical procedures are available for the management of posthemorrhagic hydrocephalus in preterm newborns. OBJECTIVE: To evaluate the short efficacy of the external ventricular drains (EVDs) and the ventriculosubgaleal (VSG) shunt. METHODS: This is a Strengthening the Reporting of Observational Studies in Epidemiology-conformed retrospective cohort study. The inclusion criteria were (1) gestational age <37 weeks, (2) birth weight <1500 g, (3) posthemorrhagic hydrocephalus because of intraventricular hemorrhage grade II/III, and (4) EVD or VSG shunt procedure before ventriculoperitoneal (VP)-definite shunt. Twenty-four newborns were collected from 2006 to 2022. The end points considered were infectious events, proteinorrachia, reintervention rate, and time to conversion to definite VP shunt. RESULTS: Overall, 12/24 newborns underwent EVD, and the remnant had a VSG shunt. The results showed a statistically significant difference ( P = .02) concerning cerebrospinal fluid infections between the EVD group (50%) and VSG shunt 1 (8.33%). The reintervention rate of EVD was significantly higher (66.67%) compared with that of the VSG shunt group (8.33%). A statistically significant difference was stated between the 2 groups (t[13] = -8.250; P < .001) (mean difference ± standard error; 10.5 ± 1.273) in the mean number of days elapsed from the achievement of the ideal weight (2000 g) to the definitive VP drainage. CONCLUSION: The increased infectious risk and the higher reintervention rate in EVD were confirmed in this study. In addition, a significant delay in the time to -conversion from EVD to VP shunt was demonstrated. Despite these optimal results, the VSG shunt remains a low practiced intervention, probably because of the limited operator experience.

Modeling cancer drug response through drug-specific informative genes.

Recent advances in pharmacogenomics have generated a wealth of data of different types whose analysis have helped in the identification of signatures of different cellular sensitivity/resistance responses to hundreds of chemical compounds. Among the different data types, gene expression has proven to be the more successful for the inference of drug response in cancer cell lines. Although effective, the whole transcriptome can introduce noise in the predictive models, since specific mechanisms are required for different drugs and these realistically involve only part of the proteins encoded in the genome. We analyzed the pharmacogenomics data of 961 cell lines tested with 265 anti-cancer drugs and developed different machine learning approaches for dissecting the genome systematically and predict drug responses using both drug-unspecific and drug-specific genes. These methodologies reach better response predictions for the vast majority of the screened drugs using tens to few hundreds genes specific to each drug instead of the whole genome, thus allowing a better understanding and interpretation of drug-specific response mechanisms which are not necessarily restricted to the drug known targets.

Kinome-wide identification of phosphorylation networks in eukaryotic proteomes.

Motivation: Signaling and metabolic pathways are finely regulated by a network of protein phosphorylation events. Unraveling the nature of this intricate network, composed of kinases, target proteins and their interactions, is therefore of crucial importance. Although thousands of kinase-specific phosphorylations (KsP) have been annotated in model organisms their kinase-target network is far from being complete, with less studied organisms lagging behind. Results: In this work, we achieved an automated and accurate identification of kinase domains, inferring the residues that most likely contribute to peptide specificity. We integrated this information with the target peptides of known human KsP to predict kinase-specific interactions in other eukaryotes through a deep neural network, outperforming similar methods. We analyzed the differential conservation of kinase specificity among eukaryotes revealing the high conservation of the specificity of tyrosine kinases. With this approach we discovered 1590 novel KsP of potential clinical relevance in the human proteome. Availability and implementation: http://akid.bio.uniroma2.it. Supplementary information: Supplementary data are available at Bioinformatics online.

Hierarchical Organization Endows the Kinase Domain with Regulatory Plasticity.

The functional diversity of kinases enables specificity in cellular signal transduction. Yet how more than 500 members of the human kinome specifically receive regulatory inputs and convey information to appropriate substrates-all while using the common signaling output of phosphorylation-remains enigmatic. Here, we perform statistical co-evolution analysis, mutational scanning, and quantitative live-cell assays to reveal a hierarchical organization of the kinase domain that facilitates the orthogonal evolution of regulatory inputs and substrate outputs while maintaining catalytic function. We find that three quasi-independent "sectors"-groups of evolutionarily coupled residues-represent functional units in the kinase domain that encode for catalytic activity, substrate specificity, and regulation. Sector positions impact both disease and pharmacology: the catalytic sector is significantly enriched for somatic cancer mutations, and residues in the regulatory sector interact with allosteric kinase inhibitors. We propose that this functional architecture endows the kinase domain with inherent regulatory plasticity.

Structural Defects of Laminin ß3 N-terminus Underlie Junctional Epidermolysis Bullosa with Altered Granulation Tissue Response.

Mutations in the laminin-332 (α3Aß3γ2) genes cause junctional epidermolysis bullosa (JEB), a recessively inherited disease characterized by blistering and altered wound repair. In addition, specific mutations that affect the N-terminus of the α3A chain cause a JEB-related non-blistering condition characterized by chronic production of granulation tissue, suggesting a critical role of this region in epithelial-mesenchymal communication. We report here a 9-year-old patient with JEB with a few long-standing skin ulcers with prominent granulation tissue in the absence of active blistering. He bears a homozygous missense mutation, p.Gly254Asp, within the first laminin epidermal growth factor-like (LE) repeat of the ß3 short arm. We show that p.Gly254Asp causes mis-folding of the LE motif, leading to reduced secretion of laminin-332 and structural alterations of the cutaneous basement membrane zone. These findings demonstrate, in a patient in vivo, that the ß3 short arm is also involved in the outcome of the granulation tissue response.

Kinome-wide decoding of network-attacking mutations rewiring cancer signaling.

Cancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network rewiring, and the genesis and extinction of phosphorylation sites. We developed a computational platform (ReKINect) to identify NAMs and systematically interpreted the exomes and quantitative (phospho-)proteomes of five ovarian cancer cell lines and the global cancer genome repository. We identified and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase-inactivating hotspots in cancer. Our method pinpoints functional NAMs, scales with the complexity of cancer genomes and cell signaling, and may enhance our capability to therapeutically target tumor-specific networks.

Unmasking determinants of specificity in the human kinome.

Protein kinases control cellular responses to environmental cues by swift and accurate signal processing. Breakdowns in this high-fidelity capability are a driving force in cancer and other diseases. Thus, our limited understanding of which amino acids in the kinase domain encode substrate specificity, the so-called determinants of specificity (DoS), constitutes a major obstacle in cancer signaling. Here, we systematically discover several DoS and experimentally validate three of them, named the αC1, αC3, and APE-7 residues. We demonstrate that DoS form sparse networks of non-conserved residues spanning distant regions. Our results reveal a likely role for inter-residue allostery in specificity and an evolutionary decoupling of kinase activity and specificity, which appear loaded on independent groups of residues. Finally, we uncover similar properties driving SH2 domain specificity and demonstrate how the identification of DoS can be utilized to elucidate a greater understanding of the role of signaling networks in cancer (Creixell et al., 2015 [this issue of Cell]).

Exploiting holistic approaches to model specificity in protein phosphorylation.

Phosphate plays a chemically unique role in shaping cellular signaling of all current living systems, especially eukaryotes. Protein phosphorylation has been studied at several levels, from the near-site context, both in sequence and structure, to the crowded cellular environment, and ultimately to the systems-level perspective. Despite the tremendous advances in mass spectrometry and efforts dedicated to the development of ad hoc highly sophisticated methods, phosphorylation site inference and associated kinase identification are still unresolved problems in kinome biology. The sequence and structure of the substrate near-site context are not sufficient alone to model the in vivo phosphorylation rules, and they should be integrated with orthogonal information in all possible applications. Here we provide an overview of the different contexts that contribute to protein phosphorylation, discussing their potential impact in phosphorylation site annotation and in predicting kinase-substrate specificity.

Computational methods for analysis and inference of kinase/inhibitor relationships.

The central role of kinases in virtually all signal transduction networks is the driving motivation for the development of compounds modulating their activity. ATP-mimetic inhibitors are essential tools for elucidating signaling pathways and are emerging as promising therapeutic agents. However, off-target ligand binding and complex and sometimes unexpected kinase/inhibitor relationships can occur for seemingly unrelated kinases, stressing that computational approaches are needed for learning the interaction determinants and for the inference of the effect of small compounds on a given kinase. Recently published high-throughput profiling studies assessed the effects of thousands of small compound inhibitors, covering a substantial portion of the kinome. This wealth of data paved the road for computational resources and methods that can offer a major contribution in understanding the reasons of the inhibition, helping in the rational design of more specific molecules, in the in silico prediction of inhibition for those neglected kinases for which no systematic analysis has been carried yet, in the selection of novel inhibitors with desired selectivity, and offering novel avenues of personalized therapies.

A Proteome-wide Domain-centric Perspective on Protein Phosphorylation.

Phosphorylation is a widespread post-translational modification that modulates the function of a large number of proteins. Here we show that a significant proportion of all the domains in the human proteome is significantly enriched or depleted in phosphorylation events. A substantial improvement in phosphosites prediction is achieved by leveraging this observation, which has not been tapped by existing methods. Phosphorylation sites are often not shared between multiple occurrences of the same domain in the proteome, even when the phosphoacceptor residue is conserved. This is partly because of different functional constraints acting on the same domain in different protein contexts. Moreover, by augmenting domain alignments with structural information, we were able to provide direct evidence that phosphosites in protein-protein interfaces need not be positionally conserved, likely because they can modulate interactions simply by sitting in the same general surface area.

Enrichment of Leishmania donovani ATP-binding proteins using a staurosporine capture compound.

Trypanosomatid parasites of the genus Leishmania cause severe human diseases collectively termed leishmaniasis. Parasite ATP-binding proteins have emerged as potent targets for chemotherapeutic intervention. However, many parasite-specific ATP-binding proteins may escape current efforts in drug target identification, validation and deconvolution due to the lack of sequence conservation and functional annotation of these proteins in early branching eukaryotic trypanosomatids. Here, we selectively enriched for ATP-binding proteins from Leishmania donovani axenic promastigote and amastigote total protein extracts utilizing a Capture Compound™ (CC) linked to the ATP-competitive inhibitor staurosporine. As judged by in-gel kinase activity assay and competitive inhibition with free staurosporine, the CC specifically enriched for parasite phosphotransferases. Comparative nanoLC-MS(n) analysis identified 70 captured proteins, including 24 conserved protein kinases, and 32 hypothetical proteins with potential ATP-binding function. We identified conserved signature sequence motifs characteristic for staurosporine-binding protein kinases, and identified the hypothetical proteins LinJ.20.0280 and LinJ.09.1630 as novel ATP-binding proteins. Thus, functional enrichment procedures such as described here, combined with bio-informatics analyses and activity assays, provide powerful tools for the discovery of parasite-specific ATP-binding proteins that escape homology-based identification, which can be subsequently targeted for pharmacological intervention. BIOLOGICAL SIGNIFICANCE: Functional enrichment using a Capture Compound™ linked to the ATP-competitive inhibitor staurosporine provides a powerful new tool for the discovery of parasite-specific ATP-binding proteins that escape homology-based identification, which can be subsequently targeted for pharmacological intervention.

PhosTryp: a phosphorylation site predictor specific for parasitic protozoa of the family trypanosomatidae.

BACKGROUND: Protein phosphorylation modulates protein function in organisms at all levels of complexity. Parasites of the Leishmania genus undergo various developmental transitions in their life cycle triggered by changes in the environment. The molecular mechanisms that these organisms use to process and integrate these external cues are largely unknown. However Leishmania lacks transcription factors, therefore most regulatory processes may occur at a post-translational level and phosphorylation has recently been demonstrated to be an important player in this process. Experimental identification of phosphorylation sites is a time-consuming task. Moreover some sites could be missed due to the highly dynamic nature of this process or to difficulties in phospho-peptide enrichment. RESULTS: Here we present PhosTryp, a phosphorylation site predictor specific for trypansomatids. This method uses an SVM-based approach and has been trained with recent Leishmania phosphosproteomics data. PhosTryp achieved a 17% improvement in prediction performance compared with Netphos, a non organism-specific predictor. The analysis of the peptides correctly predicted by our method but missed by Netphos demonstrates that PhosTryp captures Leishmania-specific phosphorylation features. More specifically our results show that Leishmania kinases have sequence specificities which are different from their counterparts in higher eukaryotes. Consequently we were able to propose two possible Leishmania-specific phosphorylation motifs.We further demonstrate that this improvement in performance extends to the related trypanosomatids Trypanosoma brucei and Trypanosoma cruzi. Finally, in order to maximize the usefulness of PhosTryp, we trained a predictor combining all the peptides from L. infantum, T. brucei and T. cruzi. CONCLUSIONS: Our work demonstrates that training on organism-specific data results in an improvement that extends to related species. PhosTryp is freely available at http://phostryp.bio.uniroma2.it.