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Background: The accurate assessment of resting energy expenditure (REE) is essential for personalized nutrition, particularly in critically ill children. Indirect calorimetry (IC) is the gold standard for measuring REE. This methodology is based on the measurement of oxygen consumption (VO2) and carbon dioxide production (VCO2). These parameters are integrated into the Weir equation to calculate REE. Additionally, IC facilitates the determination of the respiratory quotient (RQ), offering valuable insights into a patient's carbohydrate and lipid consumption. IC validation is limited to spontaneously breathing and mechanically ventilated patients, but it is not validated in patients undergoing non-invasive ventilation (NIV). This study investigates the application of IC during NIV-CPAP (continuous positive airway pressure) and NIV-PS (pressure support). Methods: This study was conducted in the Pediatric Intensive Care Unit of IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, between 2019 and 2021. Children < 6 years weaning from NIV were enrolled. IC was performed during spontaneous breathing (SB), NIV-CPAP, and NIV-PS in each patient. A Bland-Altman analysis was employed to compare REE, VO2, VCO2, and RQ measured by IC. Results: Fourteen patients (median age 7 (4; 18) months, median weight 7.7 (5.5; 9.7) kg) were enrolled. The REE, VO2, VCO2, and RQ did not differ significantly between the groups. The Limits of Agreement (LoA) and bias of REE indicated good agreement between SB and NIV-CPAP (LoA +28.2, -19.4 kcal/kg/day; bias +4.4 kcal/kg/day), and between SB and NIV-PS (LoA -22.2, +23.1 kcal/kg/day; bias 0.4 kcal/kg/day). Conclusions: These preliminary findings support the accuracy of IC in children undergoing NIV. Further validation in a larger cohort is warranted.

Background Toll-like receptors (TLRs) are pattern-recognition sensors mainly expressed in innate immune cells that directly recognize conserved pathogen structures (pathogen-associated molecular patterns-PAMPs). Natural killer (NK) cells have been described to express different endosomal TLRs triggered by RNA and DNA sequences derived from both viruses and bacteria. This study was addressed to establish which endosomal TLR could directly mediate NK activation and function after proper stimuli. It was also important to establish the most suitable TLR agonist to be used as adjuvant in tumor vaccines or in combined cancer immunotherapies. Methods We assessed endosomal TLR expression in total NK cells by using RT-qPCR and western blotting technique. In some experiments, we purified CD56 bright CD16 - and CD56 dim CD16 + cells subsets by using NK Cell Isolation Kit Activation marker, cytokine production, CD107a expression and cytotoxicity assay were evaluated by flow cytometry. Cytokine release was quantified by ELISA. NK cells obtained from ovarian ascites underwent the same analyses. Results Although the four endosomal TLRs (TLR3, TLR7/8, and TLR9) were uniformly expressed on CD56 bright CD16 - and CD56 dim CD16 + cell subsets, the TLR7/8 (R848), TLR3 (polyinosinic-polycytidylic acid, Poly I:C) and TLR9 (ODN2395) ligands promoted NK-cell function only in the presence of suboptimal doses of cytokines, including interleukin (IL)-2, IL-12, IL-15, and IL-18, produced in vivo by other environmental cells. We showed that R848 rather than TLR3 and TLR9 agonists primarily activated CD56 bright CD16 - NK cells by increasing their proliferation, cytokine production and cytotoxic activity. Moreover, we demonstrated that R848, which usually triggers TLR7 and TLR8 on dendritic cells, macrophages and neutrophils cells, activated CD56 bright CD16 - NK-cell subset only via TLR8. Indeed, specific TLR8 but not TLR7 agonists increased cytokine production and cytotoxic activity of CD56 br

Background: Fluid therapy is a cornerstone of pediatric intensive care medicine. We aimed at quantifying the load of water, sodium and chloride due to different fluid indications in our pediatric intensive care unit (PICU).We were particularly interested in the role of fluid creep, i.e. fluid administered mainly as the vehicle for drugs, and the association between sodium load and water balance. Methods: Critically ill children aged ≤ 3 years and invasively ventilated for ≥48 hours between 2016 and 2019 in a single tertiary center PICU were retrospectively enrolled. Need for renal replacement therapy, plasmapheresis or parenteral nutrition constituted exclusion criteria. Quantity, quality and indication of fluids administered intravenously or enterally, urinary output and fluid balance were recorded for the first 48 hours following intubation. Concentrations of sodium and chloride provided by the manufacturers were used to compute the electrolyte load. Results: Forty-three patients (median 7 months (IQR 3-15)) were enrolled. Patients received 1004±284 ml of water daily (153±36 ml/kg/day), mainly due to enteral (39%), creep (34%) and maintenance (24%) fluids. Patients received 14.4±4.8 mEq/kg/day of sodium and 13.6± 4.7 mEq/kg/day of chloride, respectively. The majority of sodium and chloride derived from fluid creep (56 and 58%). Daily fluid balance was 417±221 ml (64±30 ml/kg/day) and was associated with total sodium intake (r2 = 0.49, p <0.001). Conclusions: Critically ill children are exposed, especially in the acute phase, to extremely high loads of water, sodium and chloride, possibly contributing to edema development. Fluid creep is quantitatively the most relevant fluid in the PICU and future research efforts should address this topic in order to reduce the inadvertent water and electrolyte burden and improve the quality of care of critically ill children.

The inaccuracy of resting energy expenditure (REE) prediction formulae to calculate energy metabolism in children may lead to either under- or overestimated real caloric needs with clinical consequences. The aim of this paper was to apply artificial neural networks algorithms (ANNs) to REE prediction. We enrolled 561 healthy children (2-17 years). Nutritional status was classified according to World Health Organization (WHO) criteria, and 113 were obese. REE was measured using indirect calorimetry and estimated with WHO, Harris-Benedict, Schofield, and Oxford formulae. The ANNs considered specific anthropometric data to model REE. The mean absolute error (mean ± SD) of the prediction was 95.8 ± 80.8 and was strongly correlated with REE values (R2 = 0.88). The performance of ANNs was higher in the subgroup of obese children (101 ± 91.8) with a lower grade of imprecision (5.4%). ANNs as a novel approach may give valuable information regarding energy requirements and weight management in children.

The local intrinsic dimensionality (LID) model enables assessment of the complexity of the local neighbourhood around a specific query object of interest. In this paper, we study variations in the LID of a query, with respect to different subspaces and local neighbourhoods. We illustrate the surprising phenomenon of how the LID of a query can substantially decrease as further features are included in a dataset. We identify the role of two key feature properties in influencing the LID for feature combinations: correlation and dominance. Our investigation provides new insights into the impact of different feature combinations on local regions of the data.

Osteosarcoma is the most common malignant bone tumor in children and young adults. The identification of proteins which exhibit different subcellular localization in low- versus high-risk osteosarcoma can be instrumental to obtain prognostic information and to develop innovative therapeutic strategies. Beside the well-characterized membrane and cytoplasmic localization of Src protein, this study evaluated the prognostic relevance of its so-far unknown nuclear compartmentalization. We analyzed the subcellular distribution of total and activated (pY418) Src in a tissue microarray including 60 osteosarcoma samples. Immunohistochemical analyses revealed a variable pattern of Src expression and localization, ranging from negative to high-stained nuclei combined with a substantial cytoplasmic staining for total and activated forms. The analysis of Kaplan–Meier survival curves in relationship to the diverse permutations of cytoplasmic and nuclear staining suggested a correlation between Src subcellular localization and the overall survival (OS) of osteosarcoma patients. In order to explain this different subcellular localization, normal osteoblasts and three osteosarcoma cell lines were used to investigate the molecular mechanism. Once confirmed a variable Src localization also in these cell lines, we demonstrated a correlation between the N-myristoyltransferase enzymes expression and activity and the Src nuclear content. In conclusion, these results described a so-far unknown Src nuclear localization in osteosarcoma cells, suggesting that the combined detection of nuclear and cytoplasmic Src levels can be used as a prognostic marker for osteosarcoma patient survival. A correlation between the N-myristoyltransferase enzymes and the Src subcellular localization was described as well.

In this paper we study the problem of detecting and grouping multi-variant audio tracks in large audio datasets. To address this issue, a fast and reliable retrieval method is necessary. But reliability requires elaborate representations of audio content, which challenges fast retrieval by similarity from a large audio database. To find a better tradeoff between retrieval quality and efficiency, we put forward an approach relying on local summarization and multi-level Locality-Sensitive Hashing (LSH). More precisely, each audio track is divided into multiple Continuously Correlated Periods (CCP) of variable length according to spectral similarity. The description for each CCP is calculated based on its Weighted Mean Chroma (WMC). A track is thus represented as a sequence of WMCs. Then, an adapted two-level LSH is employed for efficiently delineating a narrow relevant search region. The "coarse" hashing level restricts search to items having a non-negligible similarity to the query. The subsequent, "refined" level only returns items showing a much higher similarity. Experimental evaluations performed on a real multi-variant audio dataset confirm that our approach supports fast and reliable retrieval of audio track variants. Copyright 2009 ACM.

Though skyline queries in wireless sensor networks have been intensively studied in recent years, existing solutions are not optimized for multiple skyline queries as they focus on single full space skyline queries. It is not efficient to individually evaluate skyline queries especially in a wireless sensor network environment where power consumption should be minimized. In this paper, we propose an energy-efficient multi-skyline evaluation (EMSE) algorithm to effectively evaluate multiple skyline queries in wireless sensor networks. EMSE first utilizes a global optimization mechanism to reduce the number of skyline queries and save on query propagation cost and parts of redundant result transmission cost as a consequence. Then, it utilizes a local optimization mechanism to share the skyline results among skyline queries and uses some filtering policies to further eliminate unnecessary data transmission and save the skyline result transmission cost as a consequence. The experimental results show that the proposed algorithm is energy-efficient when evaluating multiple skyline queries over wireless sensor networks.

Multi-variant music tracks are those audio tracks of a particular song which are sung and recorded by different people (i.e., cover songs). As music social clubs grow on the Internet, more and more people like to upload music recordings onto such music social sites to share their own homeproduced albums and participate in Internet singing contests. Therefore it is very important to explore a computerassisted evaluation tool to detect these audio-based multivariant tracks. In this paper we investigate such a task: the original track of a song is embedded in datasets, with a batch of multi-variant audio tracks of this song as input, our retrieval system returns an ordered list by similarity and indicates the position of relevant audio track. To help process multi-variant audio tracks, we suggest a semantic indexing framework and propose the Federated Features (FF) scheme to generate the semantic summarization of audio feature sequences. The conjunction of federated features with three typical similarity searching schemes, K-Nearest Neighbor (KNN), Locality Sensitive Hashing (LSH), and Exact Euclidian LSH (E2LSH), is evaluated. From these findings, a computer-assisted evaluation tool for searching multi-variant audio tracks was developed to search over large musical audio datasets. Copyright 2008 ACM.

We develop a content-based audio COver Song IdeNtification (COSIN) system to detect/group cover songs.The COSIN takes music audio content as input and performs similarity searching to locate variants of the input (i.e., cover versions). Identified cover songs are returned in the rank order according to their similarity to the input.The COSIN also incorporates a set of tools to evaluate retrieval performance so researchers can explore different retrieval schemes and parameters (e.g. recall, precision).The COSIN utilizes a suite of techniques to detect cover songs including: Pitch + Dynamic Programming (DP), Chroma + DP, and Semantic Feature Summarization (SFS) + Hash-Based Approximate Matching (HBAM). Demonstration system shows that COSIN is a very potential music content retrieval tool. Running some music retrieval schemes on COSIN platform, recent experiments with SFS + LSH Variants demonstrate a nicely balanced efficiency (search speed) v. performance (search accuracy) tradeoff.