bluuebunny/crossref_metadata_2025 huggingface dataset:
Accurate, high-resolution dispersive Fourier-transform spectroscopy with undetected photons
Authors: Lindner Chiara , Kunz Jachin , Herr Simon J. , Kiessling Jens , Wolf Sebastian , Kühnemann Frank
Published: January 2022

We present dispersive Fourier-transform spectroscopy with undetected photons using a nonlinear interferometer based on spontaneous parametric down-conversion. The interferometer transfers mid-infrared information of sample interaction to the near-infrared, which allows using low-noise silicon-based detectors, enabling accurate measurements with extremely low light exposure. We demonstrate a dispersion measurement of gaseous methane with an accuracy greater than 1 part in 106, which is limited by random phase noise. The Fourier-transform approach allows high resolution, rotational-line resolving spectroscopy of both, the absorptive and dispersive properties of a sample in a simple and robust measurement concept.
Machine Learning Assisted Model of QoT Penalties for Photonics Switching Systems
Authors: Khan Ihtesham , Tunesi Lorenzo , Masood Muhammad Umar , Ghillino Enrico , Bardella Paolo , Carena Andrea , Curri Vittorio
Published: January 2022

We propose a data-driven approach to provide augmented knowledge of the QoT impairments of photonic switches in a software-defined networking context. The pro- posed framework is topological and technological agnostic and can be operated in real- time.
Feasibility Study of Scalable 16×16 SOA-Based Optical Switches on IMOS for Data Communication Application
Authors: Feyisa Desalegn Wolde , Patronas Giannis , Bakopoulos Paraskevas , Calabretta Nicola , Stabile Ripalta
Published: January 2022

We analyze the design of O-band SOA-based switch architectures in the IMOS platform. Emulated 16×16 switches, designed with different architectures, show a worst-case 3dB penalty for the case of 7 cascaded SOAs with 4-channel WDM@25Gbps.
Kerr Switch and Memory Based on Counterpropagating Light in Microresonators
Authors: Bino Leonardo Del , Moroney Niall , Del’Haye Pascal
Published: January 2022

We demonstrate how the Kerr nonreciprocity in microresonators can be used for all-optical switching, routing, and memories. We explore different materials allowing potential bitrates of 10 Gbps and power thresholds as low as 1 µW.
Adaptive and Dynamic RF Systems Enabled by Bio-Inspired Photonics and Microwave Photonics
Authors: Fok Mable , Liu Qidi
Published: January 2022

We introduce various bio-inspired and microwave photonic technologies for improving security, ensuring channel availability, and increase adaptability to environmental changes. Solutions from the nature are excellent candidates for tackling critical challenges in emerging RF systems.
Towards a Photonic Integrated Linear Algebra Processor for Complex Matrix Multiplication and Inversion
Authors: Cheng Qixiang , Chen Minjia , Ayata Masafumi , Holm Mark , Penty Richard
Published: January 2022

We propose the first on-chip optical linear algebra processor for complex-valued matrix multiplication and inversion, incorporating III-V gain blocks. Architecture properties and design considerations are discussed, with numerical analyses showing its superiority over electronic processors.
Inexact Silicon Photonics: From Devices to Applications
Authors: Shafiee Amin , Mirza Asif , Sunny Febin , Banerjee Sanmitra , Chakrabarty Krishnendu , Pasricha Sudeep , Nikdast Mahdi
Published: January 2022

We present an overview of our recent work on variation analysis in silicon photonic integrated circuits. We discuss the promise of design-space exploration and approximate communication to enhance robustness in systems employing silicon photonics.
Spectrum Allocation Exploiting Different Core Selection Patterns for Graceful Degradation of Inter-Core Crosstalk in Space-Division Multiplexing Elastic Optical Networks
Authors: Seki Yuya , Tanigawa Yosuke , Hirota Yusuke , Tode Hideki
Published: January 2022

We propose a spectrum allocation for graceful degradation of inter- core crosstalk in space-division multiplexed elastic optical networks, which utilizes pre-calculated thresholds based on coupled power theory with multiple core selection patterns.
Experimental Demonstration of Suppression of Cascaded Performance Degradation in Multi-core Fiber Networks with Burst-mode EDFA
Authors: Hirota Yusuke , Shiraiwa Masaki , Xu Sugang , Tornatore Massimo , Mukherjee Biswanath , Awaji Yoshinari
Published: January 2022

We experimentally demonstrate cascaded performance degradation caused by increased inter-core crosstalk due to optical power fluctuation of adjacent core in multi-core fiber networks, and we show that a burst-mode EDFA is a candidate solution.
A BB84 QKD Field-Trial in the Turin Metropolitan Area
Authors: Gatto Alberto , Brunero Marco , Ferrari Marco , Tarable Alberto , Bodanapu Dileepsai , Brito Juan P. , Mendez Ruben B. , Vicente Rafael J. , Bianchi Fabrizio , Frittelli Matteo , Martin Vicente , Comi Paolo , Martelli Paolo
Published: January 2022

We report experimental results on a QKD field trial over production optical fibers deployed in the metropolitan area of Turin in presence of high-bitrate classic channels. Stable performance on a week-long interval is demonstrated.
Titanium Dioxide Waveguide Based Grating Coupler for Fiber-to-Chip Vertical Coupling
Authors: Mukit M. , Mamun M. , Stabile R. , Calabretta N.
Published: January 2022

We present an efficient titanium dioxide-TiO2 grating coupler integrated with single mode waveguide, which allows fiber-to-chip coupling efficiency of 50%. This is so far reported the highest coupling efficiency with TiO2 based grating coupler.
Photonic-Electronic Co-Design: from Optical Phase Control to Signal Processing
Authors: Ashtiani Farshid , Sanjari Pouria , Idjadi Mohamad Hossein , Risi Angelina , Aflatouni Firooz
Published: January 2022

Photonic-electronic co-design significantly improves the performance of each area and enables new applications. This review focuses on our work on electrical control of optical phase for optical synthesis and optical processing of microwave signals for near-field imaging.
Noise analysis of SOA-based All-optical Photonic Deep Neural Network with WDM input
Authors: Shi Bin , Pan Bitao , Calabretta Nicola , Stabile Ripalta
Published: January 2022

We experimentally verify the noise modeling of SOA-based all-optical neural networks on the OSNR degradation of the neuron: The photonic neural network can scale up to 16×16 neurons per layer, resulting in NRMSE <0.10.
Photonic Machine Intelligence Hardware: From Photonic Memory and Photonic TPU to Optical CNN
Authors: Sorger Volker J.
Published: January 2022

Here, I review our latest work on a Photonic TPU (P-TPU), a PIC-based ASIC for vector matrix multiplication acceleration and introduce a programmable multi-level non-volatile photonic random access memory (P-RAM).
Power Efficiency Improvements in Coherent O-Band Data Center Interconnects
Authors: Seiler Pascal M. , Zimmermann Lars
Published: January 2022

We present and discuss considerations for energy efficient n ext generation data center coherent interconnects. Power savings in the digital signal processing due to a paradigm shift from C- to O-band photonics are estimated.
Autonomous Resource Assignment for Optimal Utilization in Optical Data Centre Infrastructures
Authors: Pagès Albert , Caro Jordi Biosca , Agraz Fernando , Spadaro Salvatore
Published: January 2022

We present an architectural solution based on data analytics for self-organizing optical data centers. Thanks to a reinforcement learning-based cognitive layer, an adaptive and autonomous resource assignment to deployed services is achieved.
Verification of Spatiotemporal Optical Properties of Quantum Dot Network by Regioselective Photon counting
Authors: Sakai Shunichi , Nakamura Akihiro , Shimomura Suguru , Nishimura Takahiro , Kozuka Jun , Tate Naoya , Ogura Yusuke , Tanida Jun
Published: January 2022

To determine the internal spatiotemporal dynamics of the optical energy in a quantum dot network for various applications, we use the photon-counting method to verify the fluorescence outputs of our original quantum dot network devices.
4096-way split, 60-km Transmission of 2-λ x 50-Gb/s PAM4 signal for PON Uplink Using Cascaded SOAs and MIMO Volterra Equalizer
Authors: Shimizu Satoshi , Shinada Satoshi , Furukawa Hideaki
Published: January 2022

MIMO Volterra equalizer successfully equalize the nonlinear interaction between two wavelengths in the SOA, and BERs have been improved from 10−2 to 10−5. The system has low dependence on the timing between two wavelength channels.
Spatial-Mode Evolution with the Superposition of Vectorial Optical-Fields in a Few-Mode Fiber Channel
Authors: Zhang Peng , Zhao Tianfeng , Wen Feng , Wu Baojian , Fan Feng , Qiu Kun
Published: January 2022

We investigate in details on the spatial-mode evolution with the superposition of vectorial optical-fields and the core eccentricity in a few-mode fiber channel, achieving the mode conversion between two orthogonal degenerate modes.
Joint Modulation/Demodulation Optimization without the Differentiable Channel Model in the Presence of Phase Noise
Authors: Sakano Jun , Mori Yojiro , Hasegawa Hiroshi
Published: January 2022

We propose a novel joint modulation and demodulation optimization scheme without the differentiable channel model. Simulations show that our proposed scheme realizes higher phase noise tolerance than the conventional strategies.
Easily Installable Optical Power Equalizing Subsystem for Quick Lightpath Establishment in Conventional Networks
Authors: Shiraiwa Masaki , Hirota Yusuke , Furukawa Hideaki , Awaji Yoshinari
Published: January 2022

We developed an easily installable optical power equalizing subsystem and demonstrated in a field trial that the subsystem is suitable for flexible optical networks with reducing a lightpath establishment time by more than 10 seconds.
Mode-coupling Crosstalk Compensation through Nonlinear- optical Loop Mirror (NOLM)-based Reservoir Computing
Authors: Yang Yinke , Wen Feng , Zhao Tianfeng , Yang Feng , Wu Baojian , Qiu Kun
Published: January 2022

We propose a nonlinear-optical loop mirror (NOLM)-based reservoir computing to deal with the collected data from the experiment of a 3-mode fiber system, enabling the mode-coupling crosstalk compensation with the Q2 improvement of 11.95dB.
Mode Group Division Multiplexing: transmission, node architecture, and provisioning
Authors: Sambo N. , Martelli P. , Parolari P. , Gatto A. , Cugini F. , Castoldi P. , Boffi P.
Published: January 2022

This paper presents Mode Group Division Multiplexing (MGDM), discussing transmission aspects, node architecture, and provisioning.
Optically enabled graphene-based transmitter for Gbit/s links at 93 GHz carrier frequency
Authors: Montanaro Alberto , Sorianello Vito , Giambra Marco Angelo , Mišeikis Vaidotas , Pezzini Sergio , Giorgi Luca , D’Errico Antonio , Bigongiari Alessandra , Cavaliere Fabio , Coletti Camilla , Romagnoli Marco
Published: January 2022

Integrated photonics is a promising technology for next generation sub-THz links. We propose a new transmitter based on a graphene optoelectronic mixer as active material and demonstrate its operation at ~100 GHz carrier frequency.
Experimental Investigation of High-Frequency-Precision All-Optical Wavelength Conversion Using Four Wave Mixing, an Optical Comb and SSB Modulation
Authors: Matsuo Shun , Uenohara Hiroyuki
Published: January 2022

We investigate all-optical wavelength conversion based on FWM, using an optical- comb-generated pump with SSB modulation. A minimum 2.5 GHz shift from the original pump, and clear eye-openings for the converted NRZ-QPSK signal was achieved.
Practical nano-artifact metrics based on lower-magnification of image retrieval
Authors: Yingchuan Liu , Sakamoto Aoi , Tate Naoya
Published: January 2022

For implementation of practical nano-artifact metrics under lower magnification rate of image retrieval using white light interferometer, original image processing flow was developed. As the result, sufficiently high security performance has been successfully demonstrated.
Universal photonic processors in a glass-based femtosecond laser writing platform
Authors: Ceccarelli Francesco , Pentangelo Ciro , Piacentini Simone , Albiero Riccardo , Urbinati Emanuele , Atzeni Simone , Crespi Andrea , Osellame Roberto
Published: January 2022

Femtosecond laser writing (FLW) can open new perspectives on universal photonic processors (UPPs). We propose here two building blocks for the realization of FLW-UPPs and we show the preliminary results obtained on a 6-mode device.
Photonically Integrated Multicast Switch on InP as a Transponder Aggregator for ROADM Nodes
Authors: Tessema N. , van den Hout M. , Sadiq U. , van der Heide S. , Albores-Mejia A. , Kleijn E. , Mariani G. , Y.Wang  , Prifti K. , Rasoulzadehzali A. , Stabile R. , Okonkwo C. , Calabretta N.
Published: January 2022

We report a multicast switch PIC serving as a transponder aggregator. Successful data transmission through InP multicast switch and reception in a fully packaged coherent receiver demonstrates the drop traffic flow of a ROADM node.
Optical Networking in Support of User Plane Functions in 5G Systems and Beyond
Authors: Tzanakaki Anna , Manolopoulos Alexandros , Anastasopoulos Markos , Simenidou Dimitra
Published: January 2022

This paper proposes a scalable 5G Use Plane Function (UPF) solution facilitated by an optical transport network. Experimental evaluation of the proposed solution confirms enhanced system performance when offloading processing at the optical edge.
Optical Modulation in a Si Microring Resonator Inspired by Biological Classical Conditioning
Authors: Du Yuxin , Sun Kai , Zheng Zihang , de Groot Cornelis H. , Fang Xu
Published: January 2022

We propose and numerically demonstrate photonic classical conditioning in a Si microring resonator, to emulate Pavlov’s dog experiment using the insulator-metal transition in a VO2 thin film patch integrated with the resonator.
SOA-based loss-less switch nodes for Tb/s multicarrier transmission
Authors: Parolari P. , Rapisarda M. , Gatto A. , Lipparini F. , Tessema N. , Calabretta N. , Neumeyr C. , Boffi P.
Published: January 2022

Loss-less nodes based on semiconductor optical amplifiers to enable add/drop functionalities are studied in order to preserve the traffic throughput when adopting high-capacity multicarrier signal formats in metropolitan area networks.
Photonic integrated neural network accelerators
Authors: De Marinis Lorenzo , Andriolli Nicola
Published: January 2022

The paper reports MZI-based photonic integrated devices fabricated in silicon- on-insulator and silicon nitride platforms acting as linear optical processors, and discusses their suitability for accelerating state-of-the-art neural networks for computer vision.
Task of leadership for intercultural opening strategies in organizations in adult and continuing education
Authors: Muders Sonja , Martin Andreas
Published: January 2022

In view of the growing number of people with a migration background, continuing education organizations are faced with strategic tasks of intercultural opening. These tasks require leaders to initiate and expand integration-promoting teaching work, to promote the intercultural sensitization of the members of the organization, and to develop an intercultural culture. This is a wide issue and concerns leadership action regarding funding, regular and special course programs, training for staff and lecturers, intercultural training, etc. In this qualitative study, the types of intercultural openness adopted by the management of adult education centers were categorized into proactive, reflexive, ambivalent, and symbolic types of openness. Using the procedure of exploratory sequential design, hypotheses were tested with the aim of gaining information that would facilitate broader statements about the field of adult education providers. The quantitative distribution was analyzed using a data set called ‘wbmonitor’ and a regional data set.
DAJIN enables multiplex genotyping to simultaneously validate intended and unintended target genome editing outcomes
Authors: Kuno Akihiro , Ikeda Yoshihisa , Ayabe Shinya , Kato Kanako , Sakamoto Kotaro , Suzuki Sayaka R. , Morimoto Kento , Wakimoto Arata , Mikami Natsuki , Ishida Miyuki , Iki Natsumi , Hamada Yuko , Takemura Megumi , Daitoku Yoko , Tanimoto Yoko , Dinh Tra Thi Huong , Murata Kazuya , Hamada Michito , Muratani Masafumi , Yoshiki Atsushi , Sugiyama Fumihiro , Takahashi Satoru , Mizuno Seiya
Published: January 2022

Genome editing can introduce designed mutations into a target genomic site. Recent research has revealed that it can also induce various unintended events such as structural variations, small indels, and substitutions at, and in some cases, away from the target site. These rearrangements may result in confounding phenotypes in biomedical research samples and cause a concern in clinical or agricultural applications. However, current genotyping methods do not allow a comprehensive analysis of diverse mutations for phasing and mosaic variant detection. Here, we developed a genotyping method with an on-target site analysis software named Determine Allele mutations and Judge Intended genotype by Nanopore sequencer (DAJIN) that can automatically identify and classify both intended and unintended diverse mutations, including point mutations, deletions, inversions, and cis double knock-in at single-nucleotide resolution. Our approach with DAJIN can handle approximately 100 samples under different editing conditions in a single run. With its high versatility, scalability, and convenience, DAJIN-assisted multiplex genotyping may become a new standard for validating genome editing outcomes.
A deep generative model of 3D single-cell organization
Authors: Donovan-Maiye Rory M. , Brown Jackson M. , Chan Caleb K. , Ding Liya , Yan Calysta , Gaudreault Nathalie , Theriot Julie A. , Maleckar Mary M. , Knijnenburg Theo A. , Johnson Gregory R.
Published: January 2022

We introduce a framework for end-to-end integrative modeling of 3D single-cell multi-channel fluorescent image data of diverse subcellular structures. We employ stacked conditional β-variational autoencoders to first learn a latent representation of cell morphology, and then learn a latent representation of subcellular structure localization which is conditioned on the learned cell morphology. Our model is flexible and can be trained on images of arbitrary subcellular structures and at varying degrees of sparsity and reconstruction fidelity. We train our full model on 3D cell image data and explore design trade-offs in the 2D setting. Once trained, our model can be used to predict plausible locations of structures in cells where these structures were not imaged. The trained model can also be used to quantify the variation in the location of subcellular structures by generating plausible instantiations of each structure in arbitrary cell geometries. We apply our trained model to a small drug perturbation screen to demonstrate its applicability to new data. We show how the latent representations of drugged cells differ from unperturbed cells as expected by on-target effects of the drugs.
Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach
Authors: Miski Marcell , Keömley-Horváth Bence Márk , Rákóczi Megyeriné Dorina , Csikász-Nagy Attila , Gáspári Zoltán
Published: January 2022

The postsynaptic density (PSD) is a dense protein network playing a key role in information processing during learning and memory, and is also indicated in a number of neurological disorders. Efforts to characterize its detailed molecular organization are encumbered by the large variability of the abundance of its constituent proteins both spatially, in different brain areas, and temporally, during development, circadian rhythm, and also in response to various stimuli. In this study we ran large-scale stochastic simulations of protein binding events to predict the presence and distribution of PSD complexes. We simulated the interactions of seven major PSD proteins (NMDAR, AMPAR, PSD-95, SynGAP, GKAP, Shank3, Homer1) based on previously published, experimentally determined protein abundance data from 22 different brain areas and 42 patients (altogether 524 different simulations). Our results demonstrate that the relative ratio of the emerging protein complexes can be sensitive to even subtle changes in protein abundances and thus explicit simulations are invaluable to understand the relationships between protein availability and complex formation. Our observations are compatible with a scenario where larger supercomplexes are formed from available smaller binary and ternary associations of PSD proteins. Specifically, Homer1 and Shank3 self-association reactions substantially promote the emergence of very large protein complexes. The described simulations represent a first approximation to assess PSD complex abundance, and as such, use significant simplifications. Therefore, their direct biological relevance might be limited but we believe that the major qualitative findings can contribute to the understanding of the molecular features of the postsynapse.
Ultrafast population coding and axo-somatic compartmentalization
Authors: Zhang Chenfei , Hofmann David , Neef Andreas , Wolf Fred
Published: January 2022

Populations of cortical neurons respond to common input within a millisecond. Morphological features and active ion channel properties were suggested to contribute to this astonishing processing speed. Here we report an exhaustive study of ultrafast population coding for varying axon initial segment (AIS) location, soma size, and axonal current properties. In particular, we studied their impact on two experimentally observed features 1) precise action potential timing, manifested in a wide-bandwidth dynamic gain, and 2) high-frequency boost under slowly fluctuating correlated input. While the density of axonal channels and their distance from the soma had a very small impact on bandwidth, it could be moderately improved by increasing soma size. When the voltage sensitivity of axonal currents was increased we observed ultrafast coding and high-frequency boost. We conclude that these computationally relevant features are strongly dependent on axonal ion channels’ voltage sensitivity, but not their number or exact location. We point out that ion channel properties, unlike dendrite size, can undergo rapid physiological modification, suggesting that the temporal accuracy of neuronal population encoding could be dynamically regulated. Our results are in line with recent experimental findings in AIS pathologies and establish a framework to study structure-function relations in AIS molecular design.
Longitudinally monitored immune biomarkers predict the timing of COVID-19 outcomes
Authors: Lasso Gorka , Khan Saad , Allen Stephanie A. , Mariano Margarette , Florez Catalina , Orner Erika P. , Quiroz Jose A. , Quevedo Gregory , Massimi Aldo , Hegde Aditi , Wirchnianski Ariel S. , Bortz Robert H. , Malonis Ryan J. , Georgiev George I. , Tong Karen , Herrera Natalia G. , Morano Nicholas C. , Garforth Scott J. , Malaviya Avinash , Khokhar Ahmed , Laudermilch Ethan , Dieterle M. Eugenia , Fels J. Maximilian , Haslwanter Denise , Jangra Rohit K. , Barnhill Jason , Almo Steven C. , Chandran Kartik , Lai Jonathan R. , Kelly Libusha , Daily Johanna P. , Vergnolle Olivia
Published: January 2022

The clinical outcome of SARS-CoV-2 infection varies widely between individuals. Machine learning models can support decision making in healthcare by assessing fatality risk in patients that do not yet show severe signs of COVID-19. Most predictive models rely on static demographic features and clinical values obtained upon hospitalization. However, time-dependent biomarkers associated with COVID-19 severity, such as antibody titers, can substantially contribute to the development of more accurate outcome models. Here we show that models trained on immune biomarkers, longitudinally monitored throughout hospitalization, predicted mortality and were more accurate than models based on demographic and clinical data upon hospital admission. Our best-performing predictive models were based on the temporal analysis of anti-SARS-CoV-2 Spike IgG titers, white blood cell (WBC), neutrophil and lymphocyte counts. These biomarkers, together with C-reactive protein and blood urea nitrogen levels, were found to correlate with severity of disease and mortality in a time-dependent manner. Shapley additive explanations of our model revealed the higher predictive value of day post-symptom onset (PSO) as hospitalization progresses and showed how immune biomarkers contribute to predict mortality. In sum, we demonstrate that the kinetics of immune biomarkers can inform clinical models to serve as a powerful monitoring tool for predicting fatality risk in hospitalized COVID-19 patients, underscoring the importance of contextualizing clinical parameters according to their time post-symptom onset.
Applied machine learning for the risk-stratification and clinical decision support of hospitalised patients with dengue in Vietnam
Authors: Ming Damien K. , Hernandez Bernard , Sangkaew Sorawat , Vuong Nguyen Lam , Lam Phung Khanh , Nguyet Nguyen Minh , Tam Dong Thi Hoai , Trung Dinh The , Tien Nguyen Thi Hanh , Tuan Nguyen Minh , Chau Nguyen Van Vinh , Tam Cao Thi , Chanh Ho Quang , Trieu Huynh Trung , Simmons Cameron P. , Wills Bridget , Georgiou Pantelis , Holmes Alison H. , Yacoub Sophie ,   on behalf of the Vietnam ICU Translational Applications Laboratory (VITAL) investigators
Published: January 2022

Background

Identifying patients at risk of dengue shock syndrome (DSS) is vital for effective healthcare delivery. This can be challenging in endemic settings because of high caseloads and limited resources. Machine learning models trained using clinical data could support decision-making in this context.

Methods

We developed supervised machine learning prediction models using pooled data from adult and paediatric patients hospitalised with dengue. Individuals from 5 prospective clinical studies in Ho Chi Minh City, Vietnam conducted between 12th April 2001 and 30th January 2018 were included. The outcome was onset of dengue shock syndrome during hospitalisation. Data underwent random stratified splitting at 80:20 ratio with the former used only for model development. Ten-fold cross-validation was used for hyperparameter optimisation and confidence intervals derived from percentile bootstrapping. Optimised models were evaluated against the hold-out set.

Findings

The final dataset included 4,131 patients (477 adults and 3,654 children). DSS was experienced by 222 (5.4%) of individuals. Predictors were age, sex, weight, day of illness at hospitalisation, indices of haematocrit and platelets over first 48 hours of admission and before the onset of DSS. An artificial neural network model (ANN) model had best performance with an area under receiver operator curve (AUROC) of 0.83 (95% confidence interval [CI], 0.76–0.85) in predicting DSS. When evaluated against the independent hold-out set this calibrated model exhibited an AUROC of 0.82, specificity of 0.84, sensitivity of 0.66, positive predictive value of 0.18 and negative predictive value of 0.98.

Interpretation

The study demonstrates additional insights can be obtained from basic healthcare data, when applied through a machine learning framework. The high negative predictive value could support interventions such as early discharge or ambulatory patient management in this population. Work is underway to incorporate these findings into an electronic clinical decision support system to guide individual patient management.
Genome-wide chromatin contacts of super-enhancer-associated lncRNA identify LINC01013 as a regulator of fibrosis in the aortic valve
Authors: Chignon Arnaud , Argaud Déborah , Boulanger Marie-Chloé , Mkannez Ghada , Bon-Baret Valentin , Li Zhonglin , Thériault Sébastien , Bossé Yohan , Mathieu Patrick
Published: January 2022

Calcific aortic valve disease (CAVD) is characterized by a fibrocalcific process. The regulatory mechanisms that drive the fibrotic response in the aortic valve (AV) are poorly understood. Long noncoding RNAs derived from super-enhancers (lncRNA-SE) control gene expression and cell fate. Herein, multidimensional profiling including chromatin immunoprecipitation and sequencing, transposase-accessible chromatin sequencing, genome-wide 3D chromatin contacts of enhancer-promoter identified LINC01013 as an overexpressed lncRNA-SE during CAVD. LINC01013 is within a loop anchor, which has contact with the promoter of CCN2 (CTGF) located at ~180 kb upstream. Investigation showed that LINC01013 acts as a decoy factor for the negative transcription elongation factor E (NELF-E), whereby it controls the expression of CCN2. LINC01013-CCN2 is part of a transforming growth factor beta 1 (TGFB1) network and exerts a control over fibrogenesis. These findings illustrate a novel mechanism whereby a dysregulated lncRNA-SE controls, through a looping process, the expression of CCN2 and fibrogenesis of the AV.
A nationwide school fruit and vegetable policy and childhood and adolescent overweight: A quasi-natural experimental study
Authors: Øvrebø Bente , Stea Tonje H. , Bergh Ingunn H. , Bere Elling , Surén Pål , Magnus Per , Juliusson Petur B. , Wills Andrew K.
Published: January 2022

Background

School free fruit and vegetable (FFV) policies are used to promote healthy dietary habits and tackle obesity; however, our understanding of their effects on weight outcomes is limited. We assess the effect of a nationwide FFV policy on childhood and adolescent weight status and explore heterogeneity by sex and socioeconomic position.

Methods and findings

This study used a quasi-natural experimental design. Between 2007 and 2014, Norwegian combined schools (grades 1–10, age 6 to 16 years) were obligated to provide FFVs while elementary schools (grades 1–7) were not. We used 4 nationwide studies (n = 11,215 children) from the Norwegian Growth Cohort with longitudinal or cross-sectional anthropometric data up to age 8.5 and 13 years to capture variation in FFV exposure. Outcomes were body mass index standard deviation score (BMISDS), overweight and obesity (OW/OB), waist circumference (WC), and weight to height ratio (WtHR) at age 8.5 years, and BMISDS and OW/OB at age 13 years. Analyses included longitudinal models of the pre- and post-exposure trajectories to estimate the policy effect. The participation rate in each cohort was >80%, and in most analyses <4% were excluded due to missing data. Estimates were adjusted for region, population density, and parental education. In pooled models additionally adjusted for pre-exposure BMISDS, there was little evidence of any benefit or unintended consequence from 1–2.5 years of exposure to the FFV policy on BMISDS, OW/OB, WC, or WtHR in either sex. For example, boys exposed to the FFV policy had a 0.05 higher BMISDS (95% CI: −0.04, 0.14), a 1.20-fold higher odds of OW/OB (95% CI: 0.86, 1.66) and a 0.3 cm bigger WC (95% CI: −0.3, 0.8); while exposed girls had a 0.04 higher BMISDS (95% CI: −0.04, 0.13), a 1.03 fold higher odds of OW/OB (95% CI: 0.75, 1.39), and a 0-cm difference in WC (95% CI: −0.6, 0.6). There was evidence of heterogeneity in the policy effect estimates at 8.5 years across cohorts and socioeconomic position; however, these results were inconsistent with other comparisons. Analysis at age 13 years, after 4 years of policy exposure, also showed little evidence of an effect on BMISDS or OW/OB. The main limitations of this study are the potential for residual confounding and exposure misclassification, despite efforts to minimize their impact on conclusions.

Conclusions

In this study we observed little evidence that the Norwegian nationwide FFV policy had any notable beneficial effect or unintended consequence on weight status among Norwegian children and adolescents.
An efficient and robust HPLC method to determine the sialylation levels of human epithelial cells
Authors: Kim Hyo Jeong , Schweiker Stephanie , Powell Katie , Levonis Stephan
Published: January 2022

Sialyltransferase, an enzyme responsible for attaching sialic acid to the cell surface, is reported to play a key role in cancer, making sialyltransferase a potential therapeutic target in drug development. Several methods have been developed to quantify sialic acids in biological samples however limitations exists and quantification in complex cell matrices lack investigation. Hence, this paper outlines a simple method to detect and quantify sialic acids in cancer cells for evaluating sialyltransferase activity of potential therapeutic compounds. An efficient method was developed using a reverse-phase ion-pairing HPLC-UV using triisopropanolamine as the ion-pairing agent with a C18 column. Neu5Ac was successfully eluted with the retention time 6.344 min with a flow rate of 0.4 mL/min. The proposed method was validated appropriately according to the AOAC guidelines (2013). This work demonstrates that the proposed method is not only relatively simple but also cost and time effective compared to pre-existing methods to successfully determine both free and protein-bound Neu5Ac in a complex cancer cell matrix. Furthermore, by applying the proposed method, a statistically significant decrease was observed for both HeLa and HuCCT1 cell lines with the application of deoxycholic acid–a known sialyltransferase inhibitor. Hence, the proposed method seems promisingly applicable to evaluate the effectiveness of potential sialyltransferase inhibitors.
An evidence-based, structured, expert approach to selecting essential indicators of primary care quality
Authors: Hysong Sylvia J. , Arredondo Kelley , Hughes Ashley M. , Lester Houston F. , Oswald Frederick L. , Petersen Laura A. , Woodard LeChauncy , Post Edward , DePeralta Shelly , Murphy Daniel R. , McKnight Jason , Nelson Karin , Haidet Paul
Published: January 2022

Background

The purpose of this article is to illustrate the application of an evidence-based, structured performance measurement methodology to identify, prioritize, and (when appropriate) generate new measures of health care quality, using primary care as a case example. Primary health care is central to the health care system and health of the American public; thus, ensuring high quality is essential. Due to its complexity, ensuring high-quality primary care requires measurement frameworks that can assess the quality of the infrastructure, workforce configurations, and processes available. This paper describes the use of the Productivity Measurement and Enhancement System (ProMES) to compile a targeted set of such measures, prioritized according to their contribution and value to primary care.

Methods

We adapted ProMES to select and rank existing primary care measures according to value to the primary care clinic. Nine subject matter experts (SMEs) consisting of clinicians, hospital leaders and national policymakers participated in facilitated expert elicitation sessions to identify objectives of performance, corresponding measures, and priority rankings.

Results

The SMEs identified three fundamental objectives: access, patient-health care team partnerships, and technical quality. The SMEs also selected sixteen performance indicators from the 44 pre-vetted, currently existing measures from three different data sources for primary care. One indicator, Team 2-Day Post Discharge Contact Ratio, was selected as an indicator of both team partnerships and technical quality. Indicators were prioritized according to value using the contingency functions developed by the SMEs.

Conclusion

Our article provides an actionable guide to applying ProMES, which can be adapted to the needs of various industries, including measure selection and modification from existing data sources, and proposing new measures. Future work should address both logistical considerations (e.g., data capture, common data/programming language) and lingering measurement challenges, such as operationalizating measures to be meaningful and interpretable across health care settings.
Moral panic about “covidiots” in Canadian newspaper coverage of COVID-19
Authors: Capurro Gabriela , Jardine Cynthia G. , Tustin Jordan , Driedger Michelle
Published: January 2022

Moral panics are moments of intense and widespread public concern about a specific group, whose behaviour is deemed a moral threat to the collective. We examined public health guidelines in the first months of the COVID-19 pandemic in Canadian newspaper editorials, columns and letters to the editor, to evaluate how perceived threats to public interests were expressed and amplified through claims-making processes. Normalization of infection control behaviours has led to a moral panic about lack of compliance with preventive measures, which is expressed in opinion discourse. Following public health guidelines was construed as a moral imperative and a civic duty, while those who failed to comply with these guidelines were stigmatized, shamed as “covidiots,” and discursively constructed as a threat to public health and moral order. Unlike other moral panics in which there is social consensus about what needs to be done, Canadian commentators presented a variety of possible solutions, opening a debate around infection surveillance, privacy, trust, and punishment. Public health communication messaging needs to be clear, to both facilitate compliance and provide the material conditions necessary to promote infection prevention behaviour, and reduce the stigmatization of certain groups and hostile reactions towards them.
Differences in cortical processing of facial emotions in broader autism phenotype
Authors: Soto-Icaza Patricia , Beffara-Bret Brice , Vargas Lorena , Aboitiz Francisco , Billeke Pablo
Published: January 2022

Autism Spectrum Disorder (ASD) is a heterogeneous condition that affects face perception. Evidence shows that there are differences in face perception associated with the processing of low spatial frequency (LSF) and high spatial frequency (HSF) of visual stimuli between non-symptomatic relatives of individuals with autism (broader autism phenotype, BAP) and typically developing individuals. However, the neural mechanisms involved in these differences are not fully understood. Here we tested whether face-sensitive event related potentials could serve as neuronal markers of differential spatial frequency processing, and whether these potentials could differentiate non-symptomatic parents of children with autism (pASD) from parents of typically developing children (pTD). To this end, we performed electroencephalographic recordings of both groups of parents while they had to recognize emotions of face pictures composed of the same or different emotions (happiness or anger) presented in different spatial frequencies. We found no significant differences in the accuracy between groups but lower amplitude modulation in the Late Positive Potential activity in pASD. Source analysis showed a difference in the right posterior part of the superior temporal region that correlated with ASD symptomatology of the child. These results reveal differences in brain processing of recognition of facial emotion in BAP that could be a precursor of ASD.
Prediction model of acute kidney injury induced by cisplatin in older adults using a machine learning algorithm
Authors: Okawa Takaya , Mizuno Tomohiro , Hanabusa Shogo , Ikeda Takeshi , Mizokami Fumihiro , Koseki Takenao , Takahashi Kazuo , Yuzawa Yukio , Tsuboi Naotake , Yamada Shigeki , Kameya Yoshitaka
Published: January 2022

Background

Early detection and prediction of cisplatin-induced acute kidney injury (Cis-AKI) are essential for the management of patients on chemotherapy with cisplatin. This study aimed to evaluate the performance of a prediction model for Cis-AKI.

Methods

Japanese patients, who received cisplatin as the first-line chemotherapy at Fujita Health University Hospital, were enrolled in the study. The main metrics for evaluating the machine learning model were the area under the curve (AUC), accuracy, precision, recall, and F-measure. In addition, the rank of contribution as a predictive factor of Cis-AKI was determined by machine learning.

Results

A total of 1,014 and 226 patients were assigned to the development and validation data groups, respectively. The current prediction model showed the highest performance in patients 65 years old and above (AUC: 0.78, accuracy: 0.77, precision: 0.38, recall: 0.70, F-measure: 0.49). The maximum daily cisplatin dose and serum albumin levels contributed the most to the prediction of Cis-AKI.

Conclusion

Our prediction model for Cis-AKI performed effectively in older patients.
Detecting selection using extended haplotype homozygosity (EHH)-based statistics in unphased or unpolarized data
Authors: Klassmann Alexander , Gautier Mathieu
Published: January 2022

Analysis of population genetic data often includes a search for genomic regions with signs of recent positive selection. One of such approaches involves the concept of extended haplotype homozygosity (EHH) and its associated statistics. These statistics typically require phased haplotypes, and some of them necessitate polarized variants. Here, we unify and extend previously proposed modifications to loosen these requirements. We compare the modified versions with the original ones by measuring the false discovery rate in simulated whole-genome scans and by quantifying the overlap of inferred candidate regions in empirical data. We find that phasing information is indispensable for accurate estimation of within-population statistics (for all but very large samples) and of cross-population statistics for small samples. Ancestry information, in contrast, is of lesser importance for both types of statistic. Our publicly available R package rehh incorporates the modified statistics presented here.
Urinary levels of pro-fibrotic transglutaminase 2 (TG2) may help predict progression of chronic kidney disease
Authors: Da Silva Lodge Michelle , Pullen Nick , Pereira Miguel , Johnson Timothy S.
Published: January 2022

Renal clinical chemistry only detects kidney dysfunction after considerable damage has occurred and is imperfect in predicting long term outcomes. Consequently, more sensitive markers of early damage and better predictors of progression are being urgently sought, to better support clinical decisions and support shorter clinical trials. Transglutaminase 2 (TG2) is strongly implicated in the fibrotic remodeling that drives chronic kidney disease (CKD). We hypothesized that urinary TG2 and its ε-(γ-glutamyl)-lysine crosslink product could be useful biomarkers of kidney fibrosis and progression. Animal models: a rat 4-month 5/6thsubtotal nephrectomy model of CKD and a rat 8-month streptozotocin model of diabetic kidney disease had 24-hour collection of urine, made using a metabolic cage, at regular periods throughout disease development. Patients: Urine samples from patients with CKD (n= 290) and healthy volunteers (n= 33) were collected prospectively, and progression tracked for 3 years. An estimated glomerular filtration rate (eGFR) loss of 2–5 mL/min/year was considered progressive, with rapid progression defined as > 5 mL/min/year. Assays: TG2 was measured in human and rat urine samples by enzyme-linked immunosorbent assay (ELISA) and ε-(γ-glutamyl)-lysine by exhaustive proteolytic digestion and amino acid analysis. Urinary TG2 and ε-(γ-glutamyl)-lysine increased with the development of fibrosis in both animal model systems. Urinary TG2 was 41-fold higher in patients with CKD than HVs, with levels elevated 17-fold by CKD stage 2. The urinary TG2:creatinine ratio (UTCR) was 9 ng/mmol in HV compared with 114 ng/mmol in non-progressive CKD, 1244 ng/mmol in progressive CKD and 1898 ng/mmol in rapidly progressive CKD. Both urinary TG2 and ε-(γ-glutamyl)-lysine were significantly associated with speed of progression in univariate logistic regression models. In a multivariate model adjusted for urinary TG2, ε-(γ-glutamyl)-lysine, age, sex, urinary albumin:creatinine ratio (UACR), urinary protein:creatinine ratio (UPCR), and CKD stage, only TG2 remained statistically significant. Receiver operating characteristic (ROC) curve analysis determined an 86.4% accuracy of prediction of progression for UTCR compared with 73.5% for UACR. Urinary TG2 and ε-(γ-glutamyl)-lysine are increased in CKD. In this pilot investigation, UTCR was a better predictor of progression in patients with CKD than UACR. Larger studies are now warranted to fully evaluate UTCR value in predicting patient outcomes.
Mate-value and relationship satisfaction: The moderating roles of mate retention behaviors
Authors: Babaeizad Ali , Fallahchai Reza , Abbasnejad Tayebeh
Published: January 2022

Previous research indicates that mate retention strategies are associated with mate value and affect relationship satisfaction. The current research aimed to replicate previous findings in a non-WEIRD society (Iran) and to extend this research by investigating the moderating roles of individual and coalitional mate retention. Participants (n = 754; 416 women) in a committed, heterosexual relationship from two independent samples reported (1) their relationship satisfaction, (2) their partner’s mate value, (3) the frequency of performing individual mate retention, and (4) the frequency of requesting coalitional mate retention. Results indicated that there were positive associations between mate value, individual and coalitional Benefit-Provisioning mate retention behaviors, and relationship satisfaction. We found negative associations between individual and coalitional Cost-Inflicting mate retention behaviors and relationship satisfaction. We found that mate retention moderated the relationship between mate value and relationship satisfaction. Limitations of the current study are noted, and future directions are discussed.
The impact of Movement Control Order during the COVID-19 pandemic on lifestyle behaviours and body weight changes: Findings from the MyNutriLifeCOVID-19 online survey
Authors: Chin Yit Siew , Woon Fui Chee , Chan Yoke Mun
Published: January 2022

Background

The COVID-19 pandemic lockdowns have affected daily lives of the communities worldwide. This study aims to determine the lifestyle behaviours and their associations with body weight changes among Malaysian adults during the Movement Control Order (MCO) due to COVID-19 pandemic.

Methods

A total of 1319 Malaysian adults participated in this cross-sectional online survey. Information on anthropometric data including body weight and height, and lifestyle behaviours including eating pattern, physical activity, and sleep pattern were self-reported by the respondents. A multivariable generalised linear mixed model was used to assess the associations between lifestyle behaviours and body weight changes with adjustment of confounding factors; namely, age, sex, ethnicity, and body weight status before MCO.

Results

During MCO, 41.2% of the respondents perceived that their eating patterns were healthier, but 36.3% reduced their physical activities, and 25.7% had a poorer sleep quality. Further, the proportion of adults who reported having lose weight (32.2%) was almost similar to those who reported having gained weight (30.7%). Lifestyle behaviours including less frequent practice of healthy cooking methods and lunch skipping were associated with weight gain, while less frequent consumption of high fat foods, more frequent physical activity, and good sleep latency were associated with lower risk of weight gain. In contrast, practicing healthy eating concept, skipped lunch, and more frequent physical activity were significantly associated with weight loss.

Conclusion

Lifestyle behaviours were associated with body weight changes during MCO. While the COVID-19 pandemic lockdown is necessary to prevent further spread of the disease, promoting healthy lifestyle practices during lockdown should be implemented for a healthy weight and better health.