bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fractional Brownian gyrator
Authors: Squarcini Alessio , Solon Alexandre , Viot Pascal , Oshanin Gleb 
Published: November 2022

Abstract
When a physical system evolves in a thermal bath kept at a constant temperature, it eventually reaches an equilibrium state which properties are independent of the kinetic parameters and of the precise evolution scenario. This is generically not the case for a system driven out of equilibrium which, on the contrary, reaches a steady-state with properties that depend on the full details of the dynamics such as the driving noise and the energy dissipation. How the steady state depends on such parameters is in general a non-trivial question. Here, we approach this broad problem using a minimal model of a two-dimensional nano-machine, the Brownian gyrator, that consists of a trapped particle driven by fractional Gaussian noises—a family of noises with long-ranged correlations in time and characterized by an anomalous diffusion exponent α. When the noise is different in the different spatial directions, our fractional Brownian gyrator persistently rotates. Even if the noise is non-trivial, with long-ranged time correlations, thanks to its Gaussian nature we are able to characterize analytically the resulting nonequilibrium steady state by computing the probability density function, the probability current, its curl and the angular velocity and complement our study by numerical results.
Bäcklund transformation and nonlinear superposition formula for the two-component short pulse equation
Authors: Mao Hui , Miao Yuanyuan 
Published: November 2022

Abstract
By means of the reciprocal transformation and the associated equation, a Bäcklund transformation (BT) containing both independent and dependent variables is worked out and studied for the two-component short pulse (2SP) equation. Based on it, the corresponding nonlinear superposition formula (NSF) is also constructed. Through reducing the BT and NSF of the 2SP equation, the BTs and NSFs for the SP equation, the focusing complex short pulse (cSP) equation and the defocusing cSP equation are obtained respectively. By analyzing the range of parameters in the solution, various solutions including soliton solitons, cuspon solitons, loop solitons, breather solutions are divided and their interaction are considered.
Recent progress of the ECRH system and initial experimental results on the J-TEXT tokamak
Authors: XIA Donghui , CHEN Xixuan , XU Dengfeng , FANG Jiangang , ZHANG Junli , WANG Nengchao , YANG Zhoujun , CHEN Zhongyong , DING Yonghua , ZHENG Wei , MA Shaoxiang , WANG Zhijiang , PAN Yuan 
Published: November 2022

Abstract
In order to broaden the range of the plasma parameters and provide experimental conditions for physical research into high-performance plasma, the development of the electron cyclotron resonance heating (ECRH) system for the J-TEXT tokamak was initiated in 2017. For the first stage, the ECRH system operated successfully with one 105 GHz/500 kW/1 s gyrotron in 2019. More than 400 kW electron cyclotron (EC) wave power has been injected into the plasma successfully, raising the core electron temperature to 1.5 keV. In 2022, another 105 GHz/500 kW/1 s gyrotron completed commissioning tests which signifies that the ECRH system could generate an EC wave power of 1 MW in total. Under the support of the ECRH system, various physical experiments have been carried out on J-TEXT. The electron thermal transport in ECRH plasmas has been investigated. When ECRH is turned on, the electron thermal diffusivity significantly increases. The runaway current is elevated when a disruption occurs during ECRH heating. When the injected EC wave power is 400 kW, the conversion efficiency of runaway current increases from 35% to 75%. Fast electron behavior is observed in electron cyclotron current drive (ECCD) plasma by the fast electron bremsstrahlung diagnostic (FEB). The increase in the FEB intensity implies that ECCD could generate fast electrons. A successful startup with a 200 kW ECW is achieved. With the upgrade of the ECRH system, the J-TEXT operational range could be expanded and further relevant research could be conducted.
Electrohydrodynamic printed nanoparticle-based resistive temperature sensor
Authors: Kamal Waqas , Rahman Khalid , Ahmad Salman , Shakeel Muhammad , Ali Taimoor 
Published: November 2022

Abstract
Temperature sensors based on the principle of a change of resistance are fabricated on polyethylene terephthalate (PET) substrates using a silver nanoparticles (AgNPs)-based ink using a bespoke drop-on-demand (DoD) electrohydrodynamic (EHD) printer. Two sensors consisting of either a single or double layer of silver were deposited using EHD printing and were found to exhibit an internal resistance of a few hundred ohms for the double-layer sensor compared to 1 kΩ for the single-layer sensor. The achieved pattern width was almost half the size of nozzle internal diameter (160 μm), and printed without treatment of substrate and nozzle. The sensors were characterized over a temperature range of 20 °C–110 °C. Both sensors showed a linear behavior with low hysteresis within the temperature ranges considered in this study and are found to recover the nominal resistance value with good reproducibility. The double-layer sensor showed high sensitivity with a temperature coefficient of resistance (TCR) of 3.4 × 10−3

∘

C

−
1

, which is an order of magnitude larger than that observed for the single-layered sensor with a TCR of 8.41 × 10−4

∘

C

−
1

. The sensors were also tested in a controlled humid environment and results are presented on the dependence of the internal resistance on the level of humidity. The proposed flexible printed sensors are promising for temperature monitoring systems and wearable technologies.
Perseverative Cognition as a Mediator Between Perceived Stress and Sleep Disturbance: A Structural Equation Modeling Meta-analysis (meta-SEM)
Authors: Zagaria Andrea , Ottaviani Cristina , Lombardo Caterina , Ballesio Andrea 
Published: November 2022

Abstract

Background
According to the perseverative cognition (PC) hypothesis, the repetitive chronic activation of the cognitive representations of stressors are associated with a concomitant prolonged and sustained physiological stress response, including sleep disruption.

Purpose
We conducted a systematic review and structural equation modeling meta-analysis (meta-SEM) on PC as mediator of the association between perceived stress and subjective sleep disturbance (i.e., difficulties falling asleep or maintaining sleep).

Methods
PubMed, Scopus, Medline, CINAHL, and PsycInfo were searched up to September 2021. To test mediation, only longitudinal studies assessing the predictor (perceived stress) at T0, the mediator (PC) at T1, and the outcome (sleep disturbance) at T2, were eligible.

Results
Findings on 3,733 individuals (k = 8) showed a significant component effect of perceived stress on PC (β = 0.340, p &lt; .001), which in turn was related to sleep disturbance (β = 0.258, p &lt; .001). The direct effect of stress on sleep disturbance was significant (β = 0.133, p &lt; .001). Lastly, the indirect effect between stress and sleep disturbance via PC supported the mediation hypothesis (β = 0.09, 95% CI 0.078–0.100). The mediation path remained significant (β = 0.03, 95% CI 0.020–0.036) after adjusting for baseline sleep disturbance. Further leave-one-out sensitivity and control analyses confirmed that all direct and indirect effects were not driven by any single study included in the meta-analysis, as well as their robustness when controlling for sex and age, respectively.

Conclusions
Overall, results of this meta-analysis indicate that PC may be one of the mechanisms explaining how perceived stressful experiences lead to subjective sleep disturbance.
Predicting drug–target binding affinity through molecule representation block based on multi-head attention and skip connection
Authors: Zhang Li , Wang Chun-Chun , Chen Xing 
Published: November 2022

Abstract
Exiting computational models for drug–target binding affinity prediction have much room for improvement in prediction accuracy, robustness and generalization ability. Most deep learning models lack interpretability analysis and few studies provide application examples. Based on these observations, we presented a novel model named Molecule Representation Block-based Drug-Target binding Affinity prediction (MRBDTA). MRBDTA is composed of embedding and positional encoding, molecule representation block and interaction learning module. The advantages of MRBDTA are reflected in three aspects: (i) developing Trans block to extract molecule features through improving the encoder of transformer, (ii) introducing skip connection at encoder level in Trans block and (iii) enhancing the ability to capture interaction sites between proteins and drugs. The test results on two benchmark datasets manifest that MRBDTA achieves the best performance compared with 11 state-of-the-art models. Besides, through replacing Trans block with single Trans encoder and removing skip connection in Trans block, we verified that Trans block and skip connection could effectively improve the prediction accuracy and reliability of MRBDTA. Then, relying on multi-head attention mechanism, we performed interpretability analysis to illustrate that MRBDTA can correctly capture part of interaction sites between proteins and drugs. In case studies, we firstly employed MRBDTA to predict binding affinities between Food and Drug Administration-approved drugs and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication-related proteins. Secondly, we compared true binding affinities between 3C-like proteinase and 185 drugs with those predicted by MRBDTA. The final results of case studies reveal reliable performance of MRBDTA in drug design for SARS-CoV-2.
Porechop_ABI: discovering unknown adapters in Oxford Nanopore Technology sequencing reads for downstream trimming
Authors: Bonenfant Quentin , Noé Laurent , Touzet Hélène 
Published: November 2022

Abstract

Motivation
Oxford Nanopore Technologies (ONT) sequencing has become very popular over the past few years and offers a cost-effective solution for many genomic and transcriptomic projects. One distinctive feature of the technology is that the protocol includes the ligation of adapters to both ends of each fragment. Those adapters should then be removed before downstream analyses, either during the basecalling step or by explicit trimming. This basic task may be tricky when the definition of the adapter sequence is not well documented.

Results
We have developed a new method to scan a set of ONT reads to see if it contains adapters, without any prior knowledge on the sequence of the potential adapters, and then trim out those adapters. The algorithm is based on approximate k-mers and is able to discover adapter sequences based on their frequency alone. The method was successfully tested on a variety of ONT datasets with different flowcells, sequencing kits and basecallers.

Availability and implementation
The resulting software, named Porechop_ABI, is open-source and is available at https://github.com/bonsai-team/Porechop_ABI.

Supplementary information
Supplementary data are available at Bioinformatics advances online.
DxFormer: a decoupled automatic diagnostic system based on decoder–encoder transformer with dense symptom representations
Authors: Chen Wei , Zhong Cheng , Peng Jiajie , Wei Zhongyu 
Published: November 2022

Abstract

Motivation
Symptom-based automatic diagnostic system queries the patient’s potential symptoms through continuous interaction with the patient and makes predictions about possible diseases. A few studies use reinforcement learning (RL) to learn the optimal policy from the joint action space of symptoms and diseases. However, existing RL (or Non-RL) methods focus on disease diagnosis while ignoring the importance of symptom inquiry. Although these systems have achieved considerable diagnostic accuracy, they are still far below its performance upper bound due to few turns of interaction with patients and insufficient performance of symptom inquiry. To address this problem, we propose a new automatic diagnostic framework called DxFormer, which decouples symptom inquiry and disease diagnosis, so that these two modules can be independently optimized. The transition from symptom inquiry to disease diagnosis is parametrically determined by the stopping criteria. In DxFormer, we treat each symptom as a token, and formalize the symptom inquiry and disease diagnosis to a language generation model and a sequence classification model, respectively. We use the inverted version of Transformer, i.e. the decoder–encoder structure, to learn the representation of symptoms by jointly optimizing the reinforce reward and cross-entropy loss.

Results
We conduct experiments on three real-world medical dialogue datasets, and the experimental results verify the feasibility of increasing diagnostic accuracy by improving symptom recall. Our model overcomes the shortcomings of previous RL-based methods. By decoupling symptom query from the process of diagnosis, DxFormer greatly improves the symptom recall and achieves the state-of-the-art diagnostic accuracy.

Availability and implementation
Both code and data are available at https://github.com/lemuria-wchen/DxFormer.

Supplementary information
Supplementary data are available at Bioinformatics online.
AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
Authors: Yu Dingquan , Chojnowski Grzegorz , Rosenthal Maria , Kosinski Jan 
Published: November 2022

Abstract

Summary
The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein–protein interactions (PPIs). Here, we present AlphaPulldown, a Python package that streamlines PPI screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command-line interface, a variety of confidence scores and a graphical analysis tool.

Availability and implementation
AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown.

Supplementary information
Supplementary note is available at Bioinformatics online.
University–School Partnerships: Successes and Challenges in Designing and Implementing Strategies to Promote Racial Equity
Authors: Jones Tiffany M , Malorni Angela , Lea Charles H , McCowan Kristin , Spencer Michael S 
Published: November 2022

Abstract
Research–practice partnerships play an important role in critically examining racial disparities in schools, as well as supporting the immediate adoption of practice improvement. This article outlines the results of a multisite case study with students, teachers, and administrators across two racially and ethnically diverse middle schools in the Pacific Northwest. Using a multisite case study approach (N = 2), authors explored practice challenges and successes in four phases of the research–practice partnership: (1) building the partnership, (2) designing the study, (3) data analysis, and (4) translating the data into action for racial justice. Data sources include field notes, observations, teacher and administrator interviews, and student focus groups. A cross-case synthesis analytical approach was used. Linking these perspectives offers an ecological approach to identifying, understanding, and interrupting racism in schools. Article concludes by discussing the importance of research–practice partnerships for racial justice in schools and the powerful role that student and teacher voices can play in the process.
Nur77-Tempo mice reveal T cell steady state antigen recognition
Authors: Elliot Thomas A E , Jennings Emma K , Lecky David A J , Rouvray Sophie , Mackie Gillian M , Scarfe Lisa , Sheriff Lozan , Ono Masahiro , Maslowski Kendle M , Bending David 
Published: November 2022

Abstract
In lymphocytes, Nr4a gene expression is specifically regulated by antigen receptor signalling, making them ideal targets for use as distal T cell receptor (TCR) reporters. Nr4a3-Timer of cell kinetics and activity (Tocky) mice are a ground-breaking tool to report TCR-driven Nr4a3 expression using Fluorescent Timer protein (FT). FT undergoes a time-dependent shift in its emission spectrum following translation, allowing for the temporal reporting of transcriptional events. Our recent work suggested that Nr4a1/Nur77 may be a more sensitive gene to distal TCR signals compared to Nr4a3, so we, therefore, generated Nur77-Timer-rapidly-expressed-in-lymphocytes (Tempo) mice that express FT under the regulation of Nur77. We validated the ability of Nur77-Tempo mice to report TCR and B cell receptor signals and investigated the signals regulating Nur77-FT expression. We found that Nur77-FT was sensitive to low-strength TCR signals, and its brightness was graded in response to TCR signal strength. Nur77-FT detected positive selection signals in the thymus, and analysis of FT expression revealed that positive selection signals are often persistent in nature, with most thymic Treg expressing FT Blue. We found that active TCR signals in the spleen are low frequency, but CD69+ lymphoid T cells are enriched for FT Blue+ Red+ T cells, suggesting frequent TCR signalling. In non-lymphoid tissue, we saw a dissociation of FT protein from CD69 expression, indicating that tissue residency is not associated with tonic TCR signals. Nur77-Tempo mice, therefore, combine the temporal dynamics from the Tocky innovation with increased sensitivity of Nr4a1 to lower TCR signal strengths.
Persistence with long-term PCSK9 inhibitor treatment and its effectiveness in familial hypercholesterolaemia: data from the SAFEHEART study
Authors: Alonso Rodrigo , Arroyo-Olivares Raquel , Muñiz-Grijalvo Ovidio , Díaz-Díaz Jose Luis , Muñoz-Torrero Juan Sanchez , Romero Manuel J , de Andrés Raimundo , Zambón Daniel , Mañas María Dolores , Fuentes-Jiménez Francisco , Aguado Rocío , Alvarez-Baños Pilar , Arrieta Francisco , Gonzalez-Bustos Pablo , Cepeda José , Martin-Ordiales Mercedes , Mosquera Daniel , Michan Alfredo , de Isla Leopoldo Perez , Argueso Rosa , Mata Pedro 
Published: November 2022

AbstractAimsMost heterozygous familial hypercholesterolaemia (FH) patients require intensive lipid-lowering therapy (LLT) including PCSK9 inhibitors (PCSK9is) to reach current low-density lipoprotein cholesterol (LDL-C) goals. Persistence with chronic treatment is important to reduce the burden of atherosclerotic cardiovascular disease. We analysed persistence, efficacy, and impact on quality of life (QoL) of PCSK9i in FH patients in clinical practice setting.Methods and resultsSpanish Familial Hypercholesterolaemia Cohort Study (SAFEHEART) is an open, prospective study in genetically defined FH patients in Spain. Patients ≥18 years of age (n = 696, 46% females) on stable LLT treated with PCSK9i were analysed. Median LDL-C at starting PCSK9i was 145 mg/dL [interquartile range (IQR), 123–177], 3.8 mmol/L (IQR 3.2–4.6). After a median follow up of 3.7 years (IQR 2.3–4.8), 27 patients (4%) discontinued PCSK9i treatment: 5 temporarily (0.7%) and 22 permanently (3.2%). Persistence with PCSK9i was 96.1% in the whole period. Median LDL-C levels and % LDL-C reduction attained after 1 year of treatment and in the last follow-up visit were 63 mg/dL (IQR 43–88), 1.6 mmol/L (IQR 1.1–2.23); 61 mg/dL (IQR 44–82), 1.6 mmol/L (IQR 1.1–2.1); 57.6% (IQR 39.5–69); and 58% (IQR 44–68), respectively. 2016 and 2019 ESC/EAS LDL-C goals were attained by 77 and 48% of patients, respectively, at the last follow-up visit (P &lt; 0.001). Mean QoL score increased slightly in the first year and remained stable.ConclusionLong-term persistence with PCSK9i in FH patients is very high, with a good QoL. Effectiveness in LDL-C reduction and LDL-C goal achievement dramatically improved with PCSK9i in this high-risk population in clinical practice setting.Trial registrationClinicalTrials.gov number NCT02693548.
Reduction in blood pressure for people with isolated diastolic hypertension and cardiovascular outcomes
Authors: Suzuki Yuta , Kaneko Hidehiro , Yano Yuichiro , Okada Akira , Matsuoka Satoshi , Fujiu Katsuhito , Michihata Nobuaki , Jo Taisuke , Takeda Norifumi , Morita Hiroyuki , Node Koichi , Yasunaga Hideo , Komuro Issei 
Published: November 2022

Abstract

Aims
Isolated diastolic hypertension (IDH) is a largely underrated risk factor for cardiovascular disease (CVD). It is currently unclear whether a reduction in blood pressure (BP) is associated with CVD events among adults with IDH. We aimed to elucidate the relationship between BP reduction and incident CVD in individuals with IDH.

Methods and results
We retrospectively analysed the data of 71 297 individuals with IDH. Isolated diastolic hypertension was defined as systolic BP of &lt; 140 mmHg and diastolic BP (DBP) of ≥90 mmHg (median age, 48 years; 83.1% men; median DBP, 92 mmHg). None of the participants took BP-lowering medications or had a history of CVD at baseline. Blood pressure was measured at baseline and 1-year follow-up, and participants were categorized into two groups based on DBP at 1 year (≥90 or &lt; 90 mmHg). The primary outcome was a composite endpoint that included myocardial infarction, stroke, and all-cause death. Over a mean follow-up period of 1100 ± 859 days, 1317 composite CVD endpoints were recorded. Participants with DBP of &lt; 90 mmHg at 1 year were at a lower risk of composite CVD events [hazard ratio (HR): 0.75, 95% confidence interval (CI): 0.67–0.83] than those with DBP of ≥90 mmHg at 1 year. A reduction in DBP per 5 mmHg during the 1-year follow-up was associated with a lower composite CVD event risk (HR: 0.92, 95% CI: 0.89–0.95). The results remained consistent across a multitude of sensitivity analyses.

Conclusion
Our analysis of a large-scale epidemiological dataset demonstrated a relationship of reduction in DBP with a reduced risk for CVD events in individuals with IDH.
European public mental health responses to the COVID-19 pandemic
Authors: Wilson Naomi , McDaid Shari , Wieber Frank , Lindert Jutta 
Published: November 2022

Abstract

Background
The coronavirus disease 2019 (COVID-19) pandemic increased multiple risk factors for mental health. Evidence-based, intersectoral public mental health responses are therefore critical. The primary aim of this study was to collate public mental health responses from across Europe.

Methods
We conducted a cross-sectional survey in March 2021. Participants were public and mental health professionals from across Europe. We developed an online instrument exploring five domains: changes in mental health supports during the pandemic; mental health support for vulnerable groups; multi-sectoral and service-user involvement; published mental health response plans; and perceived quality of overall country response.

Results
Fifty-two individuals from 20 European nations responded. Reported changes in mental health supports included an increase in online mental health supports (n = 18); but no change in long-term mental health funding (n = 13); and a decrease in access to early interventions (n = 9). Responses indicated mental health support for vulnerable groups was limited, as was multi-sectoral and service-user involvement. Few national mental health response plans existed (n = 9) and 48% of respondents felt their countries mental health response had been ‘poor’ or ‘very poor’.

Conclusions
Our results give insights into the changes in mental health support at a country level across Europe during the COVID-19 pandemic. They indicate countries were not prepared to respond and people with existing vulnerabilities were often neglected in response planning. To be prepared for future pandemics and environmental disasters Public Mental Health preparedness plans are highly needed. These must be developed cross-departmentally, and through the meaningful inclusion of vulnerable groups.