Evaluation and recommendations of the oral health, oral function, and orofacial aesthetics-related measures of the ICHOM Standard Set for Cleft Lip and Palate

This study was performed to evaluate the efficacy of outcome measures for the orofacial domain included in the International Consortium for Health Outcomes Measurement Standard Set for Cleft Lip and Palate (ICHOM-SCS). In this multicentre study involving two cleft centres, suggestions to optimize the type and timing of outcome measures were made based on data and clinical experience. Patient-reported outcome measures (PROMs) (CLEFT-Q Jaw, Teeth, Eating/Drinking; Child Oral Health Impact Profile—Oral Symptoms Scale (COHIP-OSS)) and clinical outcome measures (caries experience and dental occlusion) data were collected retrospectively for age 5, 8, 10, 12, 19, and 22 years. The data were categorized by cleft type and analysed within and between age groups using Spearman correlation, the distribution of responses per item, a two-sample test for equality of proportions, and effect plots. Most correlations between PROMs and clinical outcome measures were weak (r &lt; 0.5), suggesting PROMs and clinical outcome measures complement each other. The COHIP-OSS and CLEFT-Q Eating/Drinking barely detected problems in any patient category and are no longer recommended. A suitable alternative appears complex to find; outcomes of this study and the recent literature doubt an added value. Similar problems were found in the CLEFT-Q Jaw at time-point 12 years. Therefore, time-points 15 and 17 years are currently suggested.</p

Revealing the role of CO during CO2 hydrogenation on Cu surfaces with in situ soft X-ray spectroscopy

The reactions of H2, CO2, and CO gas mixtures on the surface of Cu at 200 °C, relevant for industrial methanol synthesis, are investigated using a combination of ambient pressure X-ray photoelectron spectroscopy (AP-XPS) and atmospheric-pressure near edge X-ray absorption fine structure (AtmP-NEXAFS) spectroscopy bridging pressures from 0.1 mbar to 1 bar. We find that the order of gas dosing can critically affect the catalyst chemical state, with the Cu catalyst maintained in a metallic state when H2 is introduced prior to the addition of CO2. Only on increasing the CO2 partial pressure is CuO formation observed that coexists with metallic Cu. When only CO2 is present, the surface oxidizes to Cu2O and CuO, and the subsequent addition of H2 partially reduces the surface to Cu2O without recovering metallic Cu, consistent with a high kinetic barrier to H2 dissociation on Cu2O. The addition of CO to the gas mixture is found to play a key role in removing adsorbed oxygen that otherwise passivates the Cu surface, making metallic Cu surface sites available for CO2 activation and subsequent conversion to CH3OH. These findings are corroborated by mass spectrometry measurements, which show increased H2O formation when H2 is dosed before rather than after CO2. The importance of maintaining metallic Cu sites during the methanol synthesis reaction is thereby highlighted, with the inclusion of CO in the gas feed helping to achieve this even in the absence of ZnO as the catalyst support

Privacy-Preserving Decision Trees Training and Prediction

In the era of cloud computing and machine learning, data has become a highly valuable resource. Recent history has shown that the benefits brought forth by this data driven culture come at a cost of potential data leakage. Such breaches have a devastating impact on individuals and industry, and lead the community to seek privacy preserving solutions. A promising approach is to utilize Fully Homomorphic Encryption (FHE) to enable machine learning over encrypted data, thus providing resiliency against information leakage. However, computing over encrypted data incurs a high computational overhead, thus requiring the redesign of algorithms, in an ``FHE-friendly manner, to maintain their practicality. In this work we focus on the ever-popular tree based methods (e.g., boosting, random forests), and propose a new privacy-preserving solution to training and prediction for trees. Our solution employs a low-degree approximation for the step-function together with a lightweight interactive protocol, to replace components of the vanilla algorithm that are costly over encrypted data. Our protocols for decision trees achieve practical usability demonstrated on standard UCI datasets encrypted with fully homomorphic encryption. In addition, the communication complexity of our protocols is independent of the tree size and dataset size in prediction and training, respectively, which significantly improves on prior works

Privacy-Preserving Decision Tree Training and Prediction against Malicious Server

Privacy-preserving machine learning enables secure outsourcing of machine learning tasks to an untrusted service provider (server) while preserving the privacy of the user\u27s data (client). Attaining good concrete efficiency for complicated machine learning tasks, such as training decision trees, is one of the challenges in this area. Prior works on privacy-preserving decision trees required the parties to have comparable computational resources, and instructed the client to perform computation proportional to the complexity of the entire task. In this work we present new protocols for privacy-preserving decision trees, for both training and prediction, achieving the following desirable properties: 1. Efficiency: the client\u27s complexity is independent of the training-set size during training, and of the tree size during prediction. 2. Security: privacy holds against malicious servers. 3. Practical usability: high accuracy, fast prediction, and feasible training demonstrated on standard UCI datasets, encrypted with fully homomorphic encryption. To the best of our knowledge, our protocols are the first to offer all these properties simultaneously. The core of our work consists of two technical contributions. First, a new low-degree polynomial approximation for functions, leading to faster protocols for training and prediction on encrypted data. Second, a design of an easy-to-use mechanism for proving privacy against malicious adversaries that is suitable for a wide family of protocols, and in particular, our protocols; this mechanism could be of independent interest

Substrate-Assisted Catalysis Unifies Two Families of Chitinolytic Enzymes

Hen egg-white lysozyme has long been the paradigm for enzymatic glycosyl hydrolysis with retention of configuration, with a protonated carboxylic acid and a deprotonated carboxylate participating in general acid-base catalysis. In marked contrast, the retaining chitin degrading enzymes from glycosyl hydrolase families 18 and 20 all have a single glutamic acid as the catalytic acid but lack a nucleophile on the enzyme. Both families have a catalytic (βα)8-barrel domain in common. X-ray structures of three different chitinolytic enzymes complexed with substrates or inhibitors identify a retaining mechanism involving a protein acid and the carbonyl oxygen atom of the substrate’s C2 N-acetyl group as the nucleophile. These studies unambiguously demonstrate the distortion of the sugar ring toward a sofa conformation, long postulated as being close to that of the transition state in glycosyl hydrolysis.

Microbes as engines of ecosystem function : When does community structure enhance predictions of ecosystem processes?

FUNDING This work was supported by NSF grant DEB-1221215 to DN, as well as grants supporting the generation of our datasets as acknowledged in their original publications and in Supplementary Table S1. ACKNOWLEDGMENT We thank the USGS Powell Center ‘Next Generation Microbes’ working group, anonymous reviews, Brett Melbourne, and Alan Townsend for valuable feedback on this project.Peer reviewedPublisher PD

The EMT transcription factor ZEB1 governs a fitness-promoting but vulnerable DNA replication stress response

The DNA damage response (DDR) and epithelial-to-mesenchymal transition (EMT) are two crucial cellular programs in cancer biology. While the DDR orchestrates cell cycle progression, DNA repair and cell death, EMT promotes invasiveness, cellular plasticity and intratumor heterogeneity. Therapeutic targeting of EMT transcription factors, such as ZEB1, remains challenging, but tumor-promoting DDR alterations elicit specific vulnerabilities. Using multi-omics, inhibitors and high-content microscopy, we discover a chemoresistant ZEB1 high expressing sub-population (ZEB1hi) with co-rewired cell cycle progression and proficient DDR across tumor entities. ZEB1 stimulates accelerated S-phase entry via CDK6, inflicting endogenous DNA replication stress. However, DDR buildups involving constitutive MRE11-dependent fork resection allow homeostatic cycling and enrichment of ZEB1hi cells during TGFβ-induced EMT and chemotherapy. Thus, ZEB1 promotes G1/S transition to launch a progressive DDR benefitting stress tolerance, which concurrently manifests a targetable vulnerability in chemoresistant ZEB1hi cells. Our study thus highlights the translationally relevant intercept of the DDR and EMT

Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions.

BACKGROUND: Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes. RESULTS: The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal. CONCLUSIONS: PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download