bluuebunny/crossref_metadata_2025_split huggingface dataset:
Massive black hole evolution models confronting the n-Hz amplitude of the stochastic gravitational wave background
Authors: Izquierdo-Villalba David , Sesana Alberto , Bonoli Silvia , Colpi Monica 
Published: November 2021

ABSTRACT
We estimate the amplitude of the nano-Hz stochastic gravitational wave background (GWB) resulting from an unresolved population of inspiralling massive black hole binaries (MBHBs). To this aim, we use the L-Galaxies semi-analytical model applied on top of the Millennium merger trees. The dynamical evolution of MBHBs includes dynamical friction, stellar and gas binary hardening, and gravitational wave (GW) feedback. At the frequencies proved by the Pulsar Timing Array experiments, our model predicts an amplitude of ${\sim }1.2 \times 10^{-15}$ at ${\sim }3 \times 10^{-8}\, \rm Hz$ in agreement with current estimations. The contribution to the background comes primarily from equal-mass binaries with chirp masses above $\rm 10^{8}\, M_{\odot }$. We then consider the recently detected common red noise in NANOGrav, PPTA, and EPTA data, working under the hypothesis that it is indeed a stochastic GWB coming from MBHBs. By boosting the massive black hole growth via gas accretion, we show that our model can produce a signal with an amplitude $A\approx (2\!-\!3) \times 10^{-15}$. There are, however, difficulties in predicting this background level without mismatching key observational constraints such as the quasar bolometric luminosity functions or the local black hole mass function. This highlights how current and forthcoming GW observations can, for the first time, confront galaxy and black hole evolution models.
CoCoNet—boosting RNA contact prediction by convolutional neural networks
Authors: Zerihun Mehari B , Pucci Fabrizio , Schug Alexander 
Published: November 2021

Abstract
Co-evolutionary models such as direct coupling analysis (DCA) in combination with machine learning (ML) techniques based on deep neural networks are able to predict accurate protein contact or distance maps. Such information can be used as constraints in structure prediction and massively increase prediction accuracy. Unfortunately, the same ML methods cannot readily be applied to RNA as they rely on large structural datasets only available for proteins. Here, we demonstrate how the available smaller data for RNA can be used to improve prediction of RNA contact maps. We introduce an algorithm called CoCoNet that is based on a combination of a Coevolutionary model and a shallow Convolutional Neural Network. Despite its simplicity and the small number of trained parameters, the method boosts the positive predictive value (PPV) of predicted contacts by about 70% with respect to DCA as tested by cross-validation of about eighty RNA structures. However, the direct inclusion of the CoCoNet contacts in 3D modeling tools does not result in a proportional increase of the 3D RNA structure prediction accuracy. Therefore, we suggest that the field develops, in addition to contact PPV, metrics which estimate the expected impact for 3D structure modeling tools better. CoCoNet is freely available and can be found at https://github.com/KIT-MBS/coconet.
Position 34 of tRNA is a discriminative element for m5C38 modification by human DNMT2
Authors: Huang Zhi-Xuan , Li Jing , Xiong Qing-Ping , Li Hao , Wang En-Duo , Liu Ru-Juan 
Published: November 2021

Abstract
Dnmt2, a member of the DNA methyltransferase superfamily, catalyzes the formation of 5-methylcytosine at position 38 in the anticodon loop of tRNAs. Dnmt2 regulates many cellular biological processes, especially the production of tRNA-derived fragments and intergenerational transmission of paternal metabolic disorders to offspring. Moreover, Dnmt2 is closely related to human cancers. The tRNA substrates of mammalian Dnmt2s are mainly detected using bisulfite sequencing; however, we lack supporting biochemical data concerning their substrate specificity or recognition mechanism. Here, we deciphered the tRNA substrates of human DNMT2 (hDNMT2) as tRNAAsp(GUC), tRNAGly(GCC) and tRNAVal(AAC). Intriguingly, for tRNAAsp(GUC) and tRNAGly(GCC), G34 is the discriminator element; whereas for tRNAVal(AAC), the inosine modification at position 34 (I34), which is formed by the ADAT2/3 complex, is the prerequisite for hDNMT2 recognition. We showed that the C32U33(G/I)34N35 (C/U)36A37C38 motif in the anticodon loop, U11:A24 in the D stem, and the correct size of the variable loop are required for Dnmt2 recognition of substrate tRNAs. Furthermore, mammalian Dnmt2s possess a conserved tRNA recognition mechanism.
Evolutionary systems biology reveals patterns of rice adaptation to drought-prone agro-ecosystems
Authors: Groen Simon C , Joly-Lopez Zoé , Platts Adrian E , Natividad Mignon , Fresquez Zoë , Mauck William M , Quintana Marinell R , Cabral Carlo Leo U , Torres Rolando O , Satija Rahul , Purugganan Michael D , Henry Amelia 
Published: November 2021

Abstract
Rice (Oryza sativa) was domesticated around 10,000 years ago and has developed into a staple for half of humanity. The crop evolved and is currently grown in stably wet and intermittently dry agro-ecosystems, but patterns of adaptation to differences in water availability remain poorly understood. While previous field studies have evaluated plant developmental adaptations to water deficit, adaptive variation in functional and hydraulic components, particularly in relation to gene expression, has received less attention. Here, we take an evolutionary systems biology approach to characterize adaptive drought resistance traits across roots and shoots. We find that rice harbors heritable variation in molecular, physiological, and morphological traits that is linked to higher fitness under drought. We identify modules of co-expressed genes that are associated with adaptive drought avoidance and tolerance mechanisms. These expression modules showed evidence of polygenic adaptation in rice subgroups harboring accessions that evolved in drought-prone agro-ecosystems. Fitness-linked expression patterns allowed us to identify the drought-adaptive nature of optimizing photosynthesis and interactions with arbuscular mycorrhizal fungi. Taken together, our study provides an unprecedented, integrative view of rice adaptation to water-limited field conditions.
Beam optics for the compensation of third-order structure resonances
Authors: Yasui Takaaki , Igarashi Susumu , Sato Yoichi , Koseki Tadashi 
Published: November 2021

Abstract
The third-order structure resonance due to sextupole magnetic fields was compensated in the Japan Proton Accelerator Research Complex main ring synchrotron using new beam optics. In the present optics, the third-order structure resonance νx − 2νy = −21 was so strong that the working point was limited. The new optics cancels the resonance by adjusting the phase advances in the arc sections. The resonance compensation was verified by aperture survey simulations and further demonstrated by three types of experiment. First, transverse coupling measurements were performed. The coupling was observed only for the optics without the compensation. This was also verified with the tracking simulation. Second, beam losses were measured using the current and new optics. The measured beam losses were noticeably reduced at the tunes around the resonance using the new optics. The beam loss reduction was also verified with the space charge tracking simulation. Third, Fourier analyses of the transverse dipole oscillations were conducted for both optics. Fourier spectra derived from the resonances were observed, and their peaks were clearly suppressed with the new optics. This was also consistent with the results of the space charge simulations.
The Effect of Mat Pilates Training Combined With Aerobic Exercise Versus Mat Pilates Training Alone on Blood Pressure in Women With Hypertension: A Randomized Controlled Trial
Authors: da Silva Almeida Isabella , de Souza Andrade Letícia , de Sousa Alessandra Martins Melo , Junior Gerson Cipriano , Turri-Silva Natália , Cunha Nascimento Dahan da , Mota Yomara Lima , Durigan João Luiz Quagliotti 
Published: November 2021

Abstract

Objective
The purpose of this study was to determine the effects of mat Pilates (MP) versus MP plus aerobic exercise (AE) compared with the effects of no intervention on ambulatory blood pressure (BP) in women with hypertension.

Methods
This 3-arm, parallel-group randomized clinical trial assessed 60 women who had hypertension and were 30 to 59 years old. The intervention lasted 16 weeks, and the participants were allocated into 3 groups: MP only (MP group), MP with alternating bouts of AE on a treadmill (MP + AE group), and control group (CG) with no exercises. Primary outcomes were the effects of the interventions on ambulatory BP assessed in the 24-hour, awake, and asleep periods of analysis.

Results
A 2-way analysis of variance did not reveal statistically significant differences in between-group comparisons in the 24-hour period of analysis for systolic BP (CG vs MP = 3.3 [95% CI = −7.1 to 13.8]; MP vs MP + AE = 0.7 [95% CI = −4 to 5.4]; CG vs MP + AE = 4.0 [95% CI = −5.2 to 13.4]), diastolic BP (CG vs MP = 2.2 [95% CI = −5.6 to 10.0]; MP vs MP + AE = 1.1 [95% CI = −4.3 to 6.5]; CG vs MP + AE = 3.3 [95% CI = −3.8 to 10.4]), and heart rate (CG vs MP = 3.4 [95% CI = −2 to 8.8]; MP vs MP + AE = 2.0 [95% CI = −3.4 to 7.5]; CG vs MP + AE = 5.4 [95% CI = −0.8 to 11.8]). The awake and asleep periods of analyses also showed similar behavior and did not reveal statistically significant between-group differences. Furthermore, in the responsiveness analysis based on the minimal clinically important difference, no differences were observed between groups.

Conclusion
The magnitudes of the decrease in systolic BP during the 24-hour period of analysis were −3 and −5.48 mm Hg for the MP and MP + AE groups, without differences for responsiveness between groups. The results suggest that MP supplemented with AE or not may be an alternative adjuvant treatment for women who have hypertension and are using antihypertension medication.

Impact
Sixteen weeks of MP training reduced ambulatory BP in women who had hypertension. The MP + AE group displayed a BP reduction similar to that of the MP group. A reduction in ambulatory BP can decrease the risk of cardiovascular disease.
Perceived Factors of Influence on the Implementation of a Multidimensional Project to Improve Patients’ Movement Behavior During Hospitalization: A Qualitative Study
Authors: Bor Petra , van Delft Lotte , Valkenet Karin , Veenhof Cindy 
Published: November 2021

Abstract

Objective
The aim of this study was to explore perceived factors of influence on the implementation of Hospital in Motion, a multidimensional and multidisciplinary implementation project to improve inpatients’ movement behavior.

Methods
This qualitative study was conducted on 4 wards. Per ward, a tailored action plan was implemented consisting of multiple tools and interventions to stimulate the integration of inpatient physical activity in usual care processes. After implementation, semi-structured interviews were performed with health care professionals and patients to explore perceived factors of influence on the implementation of the Hospital in Motion project. A content analysis was performed using the framework of the Medical Research Council for complex interventions as guidance for the identification of categories and themes.

Results
In total, 16 interviews were conducted with health care professionals and 12 with patients. The results were categorized into the 3 key components of the Medical Research Council framework: implementation, mechanisms of impact, and context. An important factor of influence within the theme “implementation” was the iterative and multidisciplinary approach. Within the theme “mechanisms of impact,” continuous attention and the interaction of multiple interventions, tailored to the target group and targeting multiple dimensions (individual, inter-professional, community and society), were perceived as important. Within the theme “context,” the intrinsic motivation and inter-professional, community and societal culture towards physical activity was perceived to be of influence.

Conclusion
Impact can be achieved and maintained by creating continuous attention to inpatient physical activity and by the interaction between different interventions and dimensions during implementation. To maintain enough focus, the amount of activities at one time should be limited.

Impact
To improve inpatients’ movement behavior, implementation project teams should be multidisciplinary and should implement a small set of tailored interventions that target multiple dimensions. Intermediate evaluation of the implementation process, strategies, and interventions is recommended.
Predictors of self-harm and suicide in LGBT youth: The role of gender, socio-economic status, bullying and school experience
Authors: Jadva V , Guasp A , Bradlow J H , Bower-Brown S , Foley S 
Published: November 2021

AbstractBackgroundLesbian, gay and bisexual (LGB) young people’s increased risk of self-harm, suicidal attempts and suicide compared with heterosexual youth is well established. The current study sought to examine whether these findings also apply to the trans (T) population and which factors act as additional risk or protective factors.MethodsIn a national cross-sectional survey, 3713 LGBT adolescents, aged 11–19 years, reported on their own history of self-harm, suicidal ideation and suicide attempts, as well as their experiences of school and homophobic, biphobic and transphobic bullying. Logistic regressions tested the association between risk and protective factors on self-harm, suicidal ideation and suicide attempts.ResultsA high proportion of the sample reported self-harm (65.3%), suicidal ideation (73.8%) and suicide attempts (25.7%). Demographic risk factors included identifying as female, non-binary or trans and being from a low-income background. Bullying and online bullying were associated with an increased risk for each outcome, and positive school experience was associated with a reduced risk for each outcome.ConclusionsConsistent with minority stress theory, the study found high rates of mental health problems within LGBT youth. Interventions focused on improving young people’s experiences in schools appear useful targets to help improve mental health outcomes.
Years of life lost (YLL) associated with COVID-19 deaths in Khorasan-RAZAVI province, Iran
Authors: Yousefi Mehdi , Fazaeli Somayeh , Mohammad-pour Saeed 
Published: November 2021

AbstractBackgroundThe number of deaths among people with coronavirus disease 2019 (COVID-19) does not show the true impact of the disease on communities. Therefore, this study aimed to calculate years of life lost (YLL) due to premature death in patients with COVID-19.MethodsWe performed a descriptive cross-sectional study based on data from one of the largest provinces of Iran, in the period 13 February 2020 to 17 May 2021. We used WHO proposed guidelines for the calculation of the burden of diseases to calculate the YLL among patients with COVID-19, taking into consideration gender in different age groups.ResultsFindings showed that 13 628 deaths were due to COVID-19 with associated 249 309 YLL. The study reported higher mortality among men (1222 cases) in the age group over 85 years than in women (840) of the same age group. The minimum number of YLL for men was 1749 in the 5–9 years age group and that for women was 1551 years in the 14–10 years age group.ConclusionThe high number of deaths due to COVID-19 has led to high YLL due to premature death. The provision of adequate health care and appropriate policies will bring about a decrease in YLL due to COVID-19.
Rituximab for interstitial pneumonia with autoimmune features at two medical centres
Authors: D’Silva Kristin M , Ventura Iazsmin Bauer , Bolster Marcy B , Castelino Flavia V , Sharma Amita , Little Brent P , Adegunsoye Ayodeji , Strek Mary E , Choi Hyon , Montesi Sydney B 
Published: November 2021

Abstract

Objectives
Many patients with interstitial lung disease (ILD) have autoimmune manifestations but do not meet criteria for a systemic rheumatic disease. A subset meets criteria for interstitial pneumonia with autoimmune features (IPAF) and have ILD requiring therapy. We conducted a multicentre observational study to examine the use of rituximab (RTX) in IPAF.

Methods
Patients from Mass General Brigham (MGB) and University of Chicago Medicine (UCM) were included if they were ≥18 years old, met the 2015 classification criteria for IPAF and were treated with RTX. Clinical improvement was defined as improvement in four out of four domains at 1 year after RTX initiation: documented clinician global assessment; oxygen requirement; need for respiratory-related hospitalization; and survival.

Results
At MGB, 36 IPAF patients (mean age 61 years, 44% female) were treated with RTX. At 1 year, 18 (50%) were clinically improved, 12 (33%) were stable, and 6 (17%) died from progressive respiratory failure. At UCM, 14 IPAF patients (mean age 53 years, 71% female) were treated with RTX. At 1 year, eight (57%) were improved, two (14%) were stable, three (21%) died from progressive respiratory failure, and one (7%) was lost to follow-up. Two patients experienced minor infusion reactions, and two patients discontinued therapy owing to adverse events (infections).

Conclusion
In patients with IPAF treated with RTX at two medical centres, the majority (40 [80%]) demonstrated improvement/stability at 1 year. These findings call for prospective studies, including randomized clinical trials, to determine the risks, benefits and cost effectiveness of RTX in IPAF.
The effects of disease activity, inflammation, depression and cognitive fatigue on resting state fMRI in systemic lupus erythematosus
Authors: Barraclough Michelle , McKie Shane , Parker Ben , Elliott Rebecca , Bruce Ian N 
Published: November 2021

Abstract

Objectives
Cognitive dysfunction (CD) and depression are interlinked comorbidities of SLE. They may be the result of altered brain mechanisms. This study aimed to examine SLE effects on functional connectivity (FC) within the default mode network (DMN) using resting state fMRI, and how depression may impact this.

Methods
Demographic, clinical and psychiatric data were collected from 19 SLE-active, 23 SLE-stable and 30 healthy controls (HC) participants. A T2*-weighted rsfMR scan was acquired and analysed using independent component analysis. Group z-scores for nodes associated with the DMN were tested. Significant nodes were entered into a factor analysis. The combined factor was used in correlations with factors of interest. Significant variables were used in a mediation analysis.

Results
14 DMN nodes were defined using independent component analysis. In five nodes, the SLE groups had significantly reduced FC compared with the HC group (P &lt; 0.01). Factor analysis generated one factor that only depression score correlated with for both the HC group (rs = −0.510) and SLE groups combined (rs = −0.390). Mediation analysis revealed depression score accounted for 22% of the altered FC in the DMN. Disease state accounted for the remaining 78%.

Conclusions
Altered FC was evident in DMN nodes for SLE groups irrespective of disease activity. Depression accounts for some of this effect but SLE directly accounted for more. Further studies are needed to assess if these changes may be a precursor to CD in SLE. If so, rs-fMRI could be an early marker for CD in SLE and help in future CD in SLE treatment trials.
Resting-state functional brain connectivity for human mentalizing: biobehavioral mechanisms of theory of mind in multiple sclerosis
Authors: Isernia Sara , Pirastru Alice , Massaro Davide , Rovaris Marco , Marchetti Antonella , Baglio Francesca 
Published: November 2021

Abstract
Although neural hubs of mentalizing are acknowledged, the brain mechanisms underlying mentalizing deficit, characterizing different neurological conditions, are still a matter of debate. To investigate the neural underpinning of theory of mind (ToM) deficit in multiple sclerosis (MS), a region of interest (ROI)-based resting-state fMRI study was proposed. In total, 37 MS patients (23 females, mean age = 54.08 ± 11.37 years, median Expanded Disability Status Scale = 6.00) underwent an MRI and a neuro-psychosocial examination and were compared with 20 sex-age-education matched healthy subjects. A neuroanatomical ToM model was constructed deriving 11 bilateral ROIs and then between and within-functional connectivity (FCs) were assessed to test for group differences. Correlation with psychosocial scores was also investigated. Lower ToM performance was registered for MS both in cognitive and affective ToM, significantly associated with processing speed. A disconnection between limbic–paralimbic network and prefrontal execution loops was observed. A trend of aberrant intrinsic connectivity in MS within the anterior cingulate cortex (ACC) was also reported. Finally, a correlation between cognitive ToM and intrinsic FC was detected in ACC and dorsal striatum, belonging to the limbic–paralimbic network, likely explaining the behavioral deficit in MS. The results suggest that aberrant intrinsic and extrinsic connectivity constitutes a crucial neural mechanism underlying ToM deficit in MS.
Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials
Authors: Narkhede Sayli M , Luther Lauren , Raugh Ian M , Knippenberg Anna R , Esfahlani Farnaz Zamani , Sayama Hiroki , Cohen Alex S , Kirkpatrick Brian , Strauss Gregory P 
Published: November 2021

AbstractBackgroundDigital phenotyping has been proposed as a novel assessment tool for clinical trials targeting negative symptoms in psychotic disorders (PDs). However, it is unclear which digital phenotyping measurements are most appropriate for this purpose.AimsMachine learning was used to address this gap in the literature and determine whether: (1) diagnostic status could be classified from digital phenotyping measures relevant to negative symptoms and (2) the 5 negative symptom domains (anhedonia, avolition, asociality, alogia, and blunted affect) were differentially classified by active and passive digital phenotyping variables.MethodsParticipants included 52 outpatients with a PD and 55 healthy controls (CN) who completed 6 days of active (ecological momentary assessment surveys) and passive (geolocation, accelerometry) digital phenotyping data along with clinical ratings of negative symptoms.ResultsMachine learning algorithms classifying the presence of a PD diagnosis yielded 80% accuracy for cross-validation in H2O AutoML and 79% test accuracy in the Recursive Feature Elimination with Cross Validation feature selection model. Models classifying the presence vs absence of clinically significant elevations on each of the 5 negative symptom domains ranged in test accuracy from 73% to 91%. A few active and passive features were highly predictive of all 5 negative symptom domains; however, there were also unique predictors for each domain.ConclusionsThese findings suggest that negative symptoms can be modeled from digital phenotyping data recorded in situ. Implications for selecting the most appropriate digital phenotyping variables for use as outcome measures in clinical trials targeting negative symptoms are discussed.