bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative characterization study of LYSO:Ce crystals for timing applications
Authors: Addesa F.M. , Barria P. , Bianco R. , Campana M. , Cavallari F. , Cemmi A. , Cipriani M. , Dafinei I. , D'Orsi B. , del Re D. , Diemoz M. , D'Imperio G. , Di Marco E. , Di Sarcina I. , Enculescu M. , Longo E. , Lucchini M.T. , Marchegiani F. , Meridiani P. , Nisi S. , Organtini G. , Pandolfi F. , Paramatti R. , Pettinacci V. , Quaranta C. , Rahatlou S. , Rovelli C. , Santanastasio F. , Soffi L. , Tramontano R. , Tully C.G.
Published: August 2022

Cerium-doped Lutetium-Yttrium Oxyorthosilicate (LYSO:Ce) is
one of the most widely used Cerium-doped Lutetium based
scintillation crystals. Initially developed for medical detectors it
rapidly became attractive for High Energy Particle Physics (HEP)
applications, especially in the frame of high luminosity particle
colliders.

In this paper, a comprehensive and systematic study of LYSO:Ce
([Lu(1-x)Y
x
]2SiO5:Ce) crystals
is presented. It involves for the first time a large number of
crystal samples (180) of the same size from a dozen of producers.
The study consists of a comparative characterization of LYSO:Ce
crystal products available on the market by mechanical, optical and
scintillation measurements and aims specifically, to investigate key
parameters of timing applications for HEP.
Effect of powders on microstructure and performance of inconel 718 alloy prepared by SPS
Authors: Qinggong Jia , Qingxiang Wang , Shuhua Liang
Published: August 2022

In this paper, 15–53 μm spherical powders obtained by plasma rotating electrode (PREP) and argon atomization (VIGA) were used to prepare the Inconel 718 alloy through spark plasma sintering(SPS), and then the sintered alloy was treated by solid solution and aging heat treatment. The effect of different powders on the microstructure and properties of Inconel 718 alloy as sintered and heat treated was studied. The results show that high density Inconel 718 alloy can be obtained by SPS technology, and the original particle boundary of powder can be reduced, and the original particle boundary of PREP is less. According to the densification process of spherical powder during SPS process, the change law of powder microstructure in rapid sintering is established.
Associations Between Childhood Obesity and Pubertal Timing Stratified by Sex and Race/Ethnicity
Authors: Aghaee Sara , Deardorff Julianna , Quesenberry Charles P , Greenspan Louise C , Kushi Lawrence H , Kubo Ai
Published: August 2022

Earlier puberty has been associated with numerous adverse mental, emotional, and physical health outcomes. Obesity is a known risk factor for earlier puberty in girls, but research with boys has yielded inconsistent findings. We examined sex- and race/ethnicity-specific associations between childhood obesity and puberty in a multiethnic cohort of 129,824 adolescents born at a Kaiser Permanente Northern California medical facility between 2003 and 2011. We used Weibull regression models to explore associations between childhood obesity and breast development onset (thelarche) in girls, testicular enlargement onset (gonadarche) in boys, and pubic hair development onset (pubarche) in both sexes, adjusting for important confounders. Clear dose-response relationships were observed. Boys with severe obesity had the greatest risk for earlier gonadarche (hazard ratio = 1.23, 95% confidence limit: 1.15, 1.32) and pubarche (hazard ratio = 1.44, 95% confidence limit: 1.34, 1.55), while underweight boys had delayed puberty compared with peers with normal body mass index. A similar dose-response relationship was observed in girls. There were significant interactions between childhood body mass index and race/ethnicity. Childhood obesity is associated with earlier puberty in both boys and girls, and the magnitude of the associations may vary by race/ethnicity. Prevention of childhood obesity may delay pubertal timing and mitigate health risks associated with both conditions.
A Preliminary Study on Investigation of Blood–Brain Barrier Damage Markers in Patients with Alcohol Use Disorder Before and After Therapy
Authors: Cetin Ihsan , Yazla Ece , Akmese Bediha , Kayadibi Hüseyin
Published: August 2022

Aim

The use of alcohol affects the central nervous system and plays important roles in various neurological disorders through neurotoxicity resulting from blood–brain barrier (BBB) permeability. The BBB is regulated by tight junction proteins interacting closely with endothelial cells. This study evaluated the serum levels of proteins and spectrin degradation products associated with BBB damage in patients with alcohol use disorder.

Methods

This preliminary case–control study was conducted with 30 healthy volunteers and 26 alcohol use disorder patients. The serum levels of spectrin breakdown product 145 (SBDP145), spectrin breakdown product 150 (SBDP150), ubiquitin carboxy-terminal hydrolase L1 (UCHL1), ubiquitin ligase cullin-3 (ULC), occludin and claudin were measured with enzyme-linked immunosorbent assay.

Results

There was no significant difference between the levels of SBDP145, SBDP150, UCHL1, ULC, occludin and claudin before and after treatment in patients with alcohol use disorder. SBDP150 levels were significantly lower in patients than controls (P < 0.001). The area under the curve was 0.841 (0.733–0.949) with the 95% confidence interval for SPDP150.

Conclusion

A decrease of the serum SBDP150 levels appears to be associated with alcohol use disorder. Future studies might clarify whether diminished serum SBDP150 levels are associated with BBB damage in patients with alcohol use disorder.
The polyketide synthase StlA is involved in inducing aggregation in Polysphondylium violaceum
Authors: Yamasaki Daiki T , Araki Tsuyoshi , Narita Takaaki B
Published: August 2022

In the social amoeba Dictyostelium discoideum, the polyketide MPBD (4-methyl-5-pentylbenzene-1,3-diol) regulates the gene expressions of cAMP signaling to make cells aggregation-competent and also induces spore maturation. The polyketide synthase StlA is responsible for MPBD biosynthesis in D. discoideum and appears to be conserved throughout the major groups of the social amoeba (Dictyostelia). In this study, we analyzed the function of StlA in Polysphondylium violaceum by identifying the gene sequence and creating the knockout mutants. We found that Pv-stlA– mutants had defects only in cell aggregation but not in spore maturation, indicating that the function of StlA in inducing spore maturation is species-specific. We also found that MPBD could rescue the aggregation defect in Pv-stlA– mutants whereas the mutants normally exhibited chemotaxis to their chemoattractant, glorin. Our data suggest that StlA is involved in inducing aggregation in P. violaceum by acting on signaling pathways other than chemotaxis in P. violaceum.
CellDrift: inferring perturbation responses in temporally sampled single-cell data
Authors: Jin Kang , Schnell Daniel , Li Guangyuan , Salomonis Nathan , Prasath V B Surya , Szczesniak Rhonda , Aronow Bruce J
Published: August 2022

Cells and tissues respond to perturbations in multiple ways that can be sensitively reflected in the alterations of gene expression. Current approaches to finding and quantifying the effects of perturbations on cell-level responses over time disregard the temporal consistency of identifiable gene programs. To leverage the occurrence of these patterns for perturbation analyses, we developed CellDrift (https://github.com/KANG-BIOINFO/CellDrift), a generalized linear model-based functional data analysis method that is capable of identifying covarying temporal patterns of various cell types in response to perturbations. As compared to several other approaches, CellDrift demonstrated superior performance in the identification of temporally varied perturbation patterns and the ability to impute missing time points. We applied CellDrift to multiple longitudinal datasets, including COVID-19 disease progression and gastrointestinal tract development, and demonstrated its ability to identify specific gene programs associated with sequential biological processes, trajectories and outcomes.
NetTIME: a multitask and base-pair resolution framework for improved transcription factor binding site prediction
Authors: Yi Ren , Cho Kyunghyun , Bonneau Richard
Published: August 2022

Motivation

Machine learning models for predicting cell-type-specific transcription factor (TF) binding sites have become increasingly more accurate thanks to the increased availability of next-generation sequencing data and more standardized model evaluation criteria. However, knowledge transfer from data-rich to data-limited TFs and cell types remains crucial for improving TF binding prediction models because available binding labels are highly skewed towards a small collection of TFs and cell types. Transfer prediction of TF binding sites can potentially benefit from a multitask learning approach; however, existing methods typically use shallow single-task models to generate low-resolution predictions. Here, we propose NetTIME, a multitask learning framework for predicting cell-type-specific TF binding sites with base-pair resolution.

Results

We show that the multitask learning strategy for TF binding prediction is more efficient than the single-task approach due to the increased data availability. NetTIME trains high-dimensional embedding vectors to distinguish TF and cell-type identities. We show that this approach is critical for the success of the multitask learning strategy and allows our model to make accurate transfer predictions within and beyond the training panels of TFs and cell types. We additionally train a linear-chain conditional random field (CRF) to classify binding predictions and show that this CRF eliminates the need for setting a probability threshold and reduces classification noise. We compare our method’s predictive performance with two state-of-the-art methods, Catchitt and Leopard, and show that our method outperforms previous methods under both supervised and transfer learning settings.

Availability and implementation

NetTIME is freely available at https://github.com/ryi06/NetTIME and the code is also archived at https://doi.org/10.5281/zenodo.6994897.

Supplementary information

Supplementary data are available at Bioinformatics online.
‘Listening from a Personal Perspective’: Does Co-Designed Mental Health Education Shift Stigma? A Mixed Method Evaluation Study
Authors: Whitelaw Kerry , Seubert Liza , Lee Kenneth , Etherton-Beer Christopher , Clifford Rhonda , Sheers Carli , Loveny Julie , Brand Gabrielle
Published: August 2022

Mental health stigma by health care practitioners is well established with few education interventions implemented in Australia. Depth of field is a growing body of health humanities research that draws on healthcare consumers as legitimate experts (by experience) to co-design health professions education.

This research aimed to explore whether a co-designed (with mental health consumers) education intervention shifts knowledge, attitudes and behavioural intentions of current and future health care practitioners towards caring for people who have experienced mental health issues.

A convergent parallel mixed method design was used to collect data utilising a validated anti-stigma assessment tool at two time points pre- and post-intervention (n = 80) followed by qualitative data from semi-structured interviews (n = 10). Descriptive analysis, Wilcoxon Sign-Rank test to compare pre-post responses and interview data were thematically analysed.

Collectively, data showed positive shifts in knowledge, attitudes and behavioural intentions towards people who have experienced mental health issues. Three main themes: Making connections: The power of storytelling; Knowledge and attitudes towards Borderline Personality Disorder: Shape, strengthen, challenge; and Inspiring change in health care practice.

Co-designed education can positively impact health care practitioners’ knowledge, attitudes and behavioural intentions and has the potential to reframe mental health education toward recovery-oriented practice.
Skin biomechanics: a potential therapeutic intervention target to reduce scarring
Authors: Hosseini Motaharesadat , Brown Jason , Khosrotehrani Kiarash , Bayat Ardeshir , Shafiee Abbas
Published: August 2022

Pathological scarring imposes a major clinical and social burden worldwide. Human cutaneous wounds are responsive to mechanical forces and convert mechanical cues to biochemical signals that eventually promote scarring. To understand the mechanotransduction pathways in cutaneous scarring and develop new mechanotherapy approaches to achieve optimal scarring, the current study highlights the mechanical behavior of unwounded and scarred skin as well as intra- and extracellular mechanisms behind keloid and hypertrophic scars. Additionally, the therapeutic interventions that promote optimal scar healing by mechanical means at the molecular, cellular or tissue level are extensively reviewed. The current literature highlights the significant role of fibroblasts in wound contraction and scar formation via differentiation into myofibroblasts. Thus, understanding myofibroblasts and their responses to mechanical loading allows the development of new scar therapeutics. A review of the current clinical and preclinical studies suggests that existing treatment strategies only reduce scarring on a small scale after wound closure and result in poor functional and aesthetic outcomes. Therefore, the perspective of mechanotherapies needs to consider the application of both mechanical forces and biochemical cues to achieve optimal scarring. Moreover, early intervention is critical in wound management; thus, mechanoregulation should be conducted during the healing process to avoid scar maturation. Future studies should either consider combining mechanical loading (pressure) therapies with tension offloading approaches for scar management or developing more effective early therapies based on contraction-blocking biomaterials for the prevention of pathological scarring.
Deaf Student–Interpreter Relationships and Feedback Practices in K-12 Mainstream Deaf Education
Authors: Prinzi Lisa M
Published: August 2022

This study explores Deaf individuals’ and sign language interpreters’ perspectives on what it is like to work together in K-12 education. A group of 41 formerly mainstreamed Deaf individuals and interpreters offers insights into interactional dynamics (e.g., the deaf student–interpreter relationship) that influence interpreters’ work, deaf students’ participation and learning, and feedback practices. This study illustrates the significance of the deaf student–interpreter relationship and suggests a correlation between this relationship and deaf students’ participation and positioning in mainstream classrooms. In addition, the findings suggest a correlation between the deaf student–interpreter relationship and feedback practices in mainstream education. Finally, this study finds that deaf students do not always know that they can engage in feedback conversations with interpreters or know how to engage interpreters to ask for what they need to learn. This article concludes with considerations and recommendations for the deaf education and interpreter education communities.
Speeding up cardiac MR segmentation with semi-supervision: applications in cine imaging
Authors: Hooper S , Wu S , Davies R H , Moon J C , Kellman P , Xue H , Langlotz C , Re C
Published: August 2022

Funding Acknowledgements

Type of funding sources: Private company. Main funding source(s): This material is based upon work supported by the Google Cloud Research Credits program with the award GCP19980904.

Background

Segmentation is an important postprocessing step in cardiac magnetic resonance (CMR) imaging that enables quantitative assessment of functional parameters. Deep learning can automate the segmentation process, producing accurate contours of cardiac structures while reducing the time required to analyze images and the interobserver variation compared to manual analysis. However, common approaches to training neural networks (NNs) require large amounts of labeled data, which is costly to generate and slows down the development of CMR segmentation NNs for new applications. Semi-supervision is an approach to alleviate this labeling burden by relying on abundant unlabeled data and a smaller amount of labeled data to train NNs.

Purpose

We propose a novel semi-supervised method to train CMR segmentation NNs. We use the proposed method to train NNs to segment the left ventricle in CMR cine images. Ultimately, we aim to show that semi-supervision can drastically reduce the amount of labeled data required to develop machine learning segmentation applications for CMR while maintaining high performance.

Methods

Our dataset consists of 1,208 short-axis cine CMR images and 1,244 long-axis cine CMR images. An expert annotator manually segmented the endocardium on the end-diastolic and end-systolic short-axis and long-axis images and the epicardium on the end-diastolic short-axis images. We split the dataset randomly by patient into 60% training, 20% validation, and 20% testing data. We train semi-supervised segmentation networks using a supervised cross-entropy loss to learn from the labeled training data and a cosine embedding loss in addition to a pseudo-labeling step to learn from the unlabeled training data. To evaluate how performance changes with different amounts of labeled training data, we vary the percent of training data that has labels from <1%-100%. We evaluate the predicted segmentation masks using the Dice coefficient.

Results

Using only 100 labeled image slices, the semi-supervised segmentation NNs achieve a mean Dice coefficient within 1.10% of networks trained with fully labeled training sets, corresponding to >85% reduction in required labeled training data (Table 1). The proposed semi-supervised method improves performance over naïve training by 6.21% for the most limited labeled data setting (i.e., 10 labeled image slices; Figure 1).

Conclusion

We have shown that NNs trained with limited labeled data achieve high performance on left ventricle segmentation in short-axis and long-axis CMR cines. The proposed approach is flexible and broadly applicable to different CMR segmentation tasks, enabling rapid development of segmentation networks for many cardiac structures and applications. Table 1Figure 1
Improving the diagnostic accuracy of apical hypertrophic cardiomyopathy using machine learning
Authors: Shiwani H , Hughes R K , Camaioni C , Augusto J B , Knott K , Rosmini S , Khoury S , Malcolmson J , Kellman P , Xue H , Burke L , Pierce I , Moon J C , Davies R H
Published: August 2022

Funding Acknowledgements

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Dr Hughes is supported by the British Heart Foundation (grant number FS/17/82/33222).

Introduction

The imaging criteria for diagnosis of apical hypertrophic cardiomyopathy (ApHCM) is a maximum wall thickness (MWT) ≥15mm. CMR enables detection of subtle phenotypic features (e.g. loss of apical tapering, cavity obliteration) and coupled with characteristic electrocardiogram changes, ApHCM can be diagnosed without overt hypertrophy. However, these patients are not captured by current diagnostic criteria.

Purpose

We sought to use a machine learning tool to quantify wall thickness and identify patients with ‘relative’ ApHCM that do not reach current diagnostic thresholds.

Methods

CMR images from 4118 healthy participants from the UK Biobank were segmented automatically with a clinically validated machine learning algorithm and wall thickness measured at all point in the myocardium by solving a solution to Laplace’s equation. MWT were pooled into 16 AHA segments and indexed to body surface area (BSA). The non-indexed and indexed segmental upper limit of normal was calculated as the mean + 3 standard deviations (the equivalent of 95% confidence interval after correcting for multiple [16] comparisons using the Bonferroni method).

Results

73 overt ApHCM subjects (MWT>15mm) and 31 relative ApHCM subjects underwent CMR scanning. In healthy controls, the non-indexed (and indexed) upper limits were calculated for the apical-anterior 10.2mm (5.2 mm/m2), apical-septal 11.1mm (5.6 mm/m2), apical-inferior 10.5mm (5.3 mm/m2) and apical-lateral 10.1mm (5.2 mm/m2) segments. With a non-indexed cut-off, all (73 of 73) overt ApHCM and 84% (26 of 31) relative ApHCM were classified as having an abnormally thick apex. 3% (127 of 4118) of the healthy UK Biobank cohort were classified as abnormal, as expected. Using an indexed cut-off, all overt ApHCM and 87% (27/31) relative ApHCM were classified as abnormal, and 3% (123 of 4118) of the healthy UK Biobank cohort were misclassified.

Conclusion

We can successfully classify 87% of relative ApHCM patients from a normative reference range derived from a large cohort of healthy patients – a significant improvement on existing methods. We show that the specificity and sensitivity is increased when MWT is indexed to BSA. For practical clinical application, we recommend a cut-off of 10mm or an indexed cut-off of 5mm/m2 in any apical segment to diagnose apical LVH. Overt and relative apical HCM examplesHealthy controls AHA maps (non-indexed)
Adverse events prediction in nonischemic dilated cardiomyopathy by two machine learning models integrating clinical and cardiovascular magnetic resonance data
Authors: Coriano' M , Bray G , De Micheli L , Cecere A G , Perazzolo Marra M , Lanera C , Gregori D , Tona F
Published: August 2022

Funding Acknowledgements

Type of funding sources: None.

Background

Risk stratification of patients with nonischemic dilated cardiomyopathy (NIDCM) is challenging. Machine learning (ML) models represent novel technologic tools that promise to improve predictive ability of cardiovascular adverse outcomes.

Purpose

To implement two ML models to predict the risk of adverse outcome (composite endpoint of all-cause death, heart transplantation, implantation of ventricular assistant device), in patients with NIDCM using clinical and radiological data.

Methods

We retrospective collected data from patients affected by NIDCM referred to our cardiologic unit between 2002 and 2018. Two ML models, an extreme gradient boosting machine (XGBoost) and an artificial neural network (ANN), were developed using cardiovascular magnetic resonance (CMR) and clinical parameters. Both models were trained on 67% of patients and evaluated based on the other 33% as internal validation. To investigate the contribution of different features in our models, we used Shapley additive explanations (SHAP) analysis.

Results

The final cohort resulted of 161 patients (mean age 48.9±13.6 years, 71% males), with a mean follow up duration of 79.1 months. During the follow-up 29 adverse event were observed (16 deaths, 12 heart transplantation, 1 implantation of ventricular assistant device). ANN model resulted in an accuracy of 76% with an area under the receiver operating characteristic (ROC) curve of 0.66; SHAP analysis identified male sex, percentage of late gadolinium enhancement (LGE) and LGE distribution in the lateral wall of myocardium as the main markers of adverse outcomes. XGBoost model resulted in an accuracy of 78% with a ROC curve of 0.76; SHAP analysis identified NT-proBNP level, age and serum creatinine mainly related with adverse outcomes. About CMR parameters, left ventricular diameter and ejection fraction better related with adverse outcomes.

Conclusions

Our models achieved a good performance in prediction of adverse events, suggesting that ML could improve our ability of risk stratification of NIDCM. XGBoost better performed than ANN, and SHAP analysis suggested that both CMR parameters and clinical parameters contribute to the definition of risk. ANN performance and SHAP analysisXGBoost performance and SHAP analysis
Talent Discovery and Poaching Under Asymmetric Information
Authors: Ferreira Daniel , Nikolowa Radoslawa
Published: August 2022

We develop a model of the market for knowledge workers in which talent is discovered on the job. In the model, asymmetric information and firm-specific human capital combine to generate several predictions relating firm heterogeneity to talent discovery and poaching. We show that high-quality (i.e., large and high-productivity) firms are more likely to become talent poachers, while lower-quality firms are more likely to invest in talent discovery. Job-to-job flows are adversely selected, which implies that internally promoted managers are more productive than those who are externally promoted. The model generates several additional predictions linking firm heterogeneity to the distribution of managerial talent, productivity, compensation and promotions.
The effectiveness and usability of a novel mobile phone-based self-care intervention for patients with heart failure: a mixed-methods pilot study
Authors: Son Youn-Jung , Kim Eun Young
Published: August 2022

Aims

To evaluate the preliminary effectiveness and usability of a novel mobile phone-based self-care intervention (named WithUs) for patients with heart failure (HF).

Methods and results

We conducted a mixed-methods pilot study with group pre-test–post-test design and usability testing. Participants were 26 Korean HF patients (20 men; median age 62 years) who took part in this study after hospital discharge. Data were collected at baseline and after the 24-week intervention, using questionnaires and interviews. The outcome variables were eHealth literacy, disease knowledge, and self-care behaviours. The Wilcoxon signed-rank test was used to compare the pre- and post-intervention results. Thematic analysis was used for analysing qualitative data. The WithUs programme improved the eHealth literacy (P = 0.005), disease knowledge (P < 0.001), and self-care behaviours (P < 0.001) of patients with HF. The median score of total app usability was 4.1 out of 5 (interquartile range = 4.0–5.0). Four themes were identified which complemented the quantitative results. These were increased awareness of the importance of routine self-care behaviours, enhanced motivation toward self-care behaviours, challenges adapting to the new app, and suggestions for improving app adoption.

Conclusion

The app was effective in improving adherence to self-care behaviours, eHealth literacy, and disease knowledge in patients with HF. The usability evaluation results showed that the app is usable and has the potential to support HF patients in self-care. However, the app needs to be modified to improve its adoption.
Comparison between first and second wave of COVID-19 outbreak in older people: the COPE multicentre European observational cohort study
Authors: Verduri Alessia , Short Roxanna , Carter Ben , Braude Philip , Vilches-Moraga Arturo , Quinn Terence J , Collins Jemima , Lumsden Jane , McCarthy Kathryn , Evans Louis , Myint Phyo K , Hewitt Jonathan ,   COPE Study Team, Clini Enrico , Rickard Frances , Hesford James , Mitchell Emma , Hartrop Kerr , Murphy Caitlin , Aggrey Ken , Bilan Jimmy , Quinn Thomas , Kelly Joanna , Murphy Caroline , Moug Susan , Barlow-Pay Fanella- , Khan Amarah , Espinoza Maria Fernanda Ramon , Kneen Thomas , Allafi Hala , Dafnis Anna , Vidal Maria Narro , Price Angeline , Pearce Lyndsay , Einarsson Alice , Mccrorie Eilidh BruceKirsty
Published: August 2022

Background

Effective shielding measures and virus mutations have progressively modified the disease between the waves, likewise healthcare systems have adapted to the outbreak. Our aim was to compare clinical outcomes for older people with COVID-19 in Wave 1 (W1) and Wave 2 (W2).

Methods

All data, including the Clinical Frailty Scale (CFS), were collected for COVID-19 consecutive patients, aged ≥65, from 13 hospitals, in W1 (February–June 2020) and W2 (October 2020–March 2021). The primary outcome was mortality (time to mortality and 28-day mortality). Data were analysed with multilevel Cox proportional hazards, linear and logistic regression models, adjusted for wave baseline demographic and clinical characteristics.

Results

Data from 611 people admitted in W2 were added to and compared with data collected during W1 (N = 1340). Patients admitted in W2 were of similar age, median (interquartile range), W2 = 79 (73–84); W1 = 80 (74–86); had a greater proportion of men (59.4% vs. 53.0%); had lower 28-day mortality (29.1% vs. 40.0%), compared to W1. For combined W1–W2 sample, W2 was independently associated with improved survival: time-to-mortality adjusted hazard ratio (aHR) = 0.78 [95% confidence interval (CI) 0.65–0.93], 28-day mortality adjusted odds ratio = 0.80 (95% CI 0.62–1.03). W2 was associated with increased length of hospital stay aHR = 0.69 (95% CI 0.59–0.81). Patients in W2 were less frail, CFS [adjusted mean difference (aMD) = −0.50, 95% CI −0.81, −0.18], as well as presented with lower C-reactive protein (aMD = −22.52, 95% CI −32.00, −13.04).

Conclusions

COVID-19 older adults in W2 were less likely to die than during W1. Patients presented to hospital during W2 were less frail and with lower disease severity and less likely to have renal decline.
Electoral and religious correlates of COVID-19 vaccination rates in Dutch municipalities
Authors: Afonso Alexandre , Votta Fabio
Published: August 2022

Vaccination campaigns amid the coronavirus disease 2019 (COVID-19) pandemic have been extensively politicized in a number of countries. Controlling for a number of demographic, social and economic factors, we find a negative statistical relationship between the aggregate vote share of the populist-right wing Forum for Democracy and the vaccination rate against COVID-19 across Dutch municipalities. We also find a negative relationship between the proportion of individuals with reformed Protestant and Muslim religious beliefs. These relationships can possibly be related to religious worldviews or mistrust towards authority. These results show that the politicization of health behaviours can have detrimental effects on public health campaigns.
Decoding the Emeishan Permian mantle plume in the southeastern margin of Tibet from the seismic signature of the local lithosphere
Authors: Hu Jiafu , Yang Haiyan , Badal José , Peng Hengchu , Miao Suqiu
Published: August 2022

The Emeishan large igneous province (ELIP), which is located along the southeastern margin of Tibet, is widely regarded as the erosional remnants of voluminous Permian mafic volcanic successions that were associated with mantle plume activity. In addition, evidence for the eruption of the mantle plume and its signature of lithospheric modification should have been retained in the lithosphere after cooling of the plume. Here we use calculated compressional- and shear wave receiver functions (PRFs and SRFs, respectively) from >750 broad-band stations, together with heat flow and Bouguer gravity anomaly data, to investigate the seismic signature within the lithosphere beneath the southeastern margin of Tibet. Our results from the inner zone (INZ) of the ELIP indicate that the ∼60 km depth of the Moho interpreted from depth-migrated PRF images is consistent with that inferred from SRFs and is deeper than that in the region surrounding the INZ, which shows a continuous positive converted phase at ∼35–40 km depth. The crustal geometry and physical properties show a 15–20-km-thick mafic underplated layer that extends for 150–200 km in the E–W direction and ∼400 km in the N–S direction along the base of the crust in the northeastern INZ and its surrounding region. We interpret the underplated layer as the concealed Emeishan plume hotspot track and suggest that the head of the postulated mantle plume is centred approximately beneath Panzhihua City and its surroundings. We propose a new geodynamic model for the formation of the ELIP, in which the lower–middle crust has been strengthened by voluminous mafic intrusions and underplating, whereas the Yangtze Craton in the plume region has been destroyed by removing the base of the lithosphere.
Could thermal pressurization have induced the frequency-dependent rupture during the 2019 Mw8.0 Peru intermediate-depth earthquake?
Authors: Luo Heng , Zeng Hongyu , Shi Qibin , Wang Teng , Liao Mingsheng , Hu Jiashun , Wei Shengji
Published: August 2022

The rupture process of earthquakes at intermediate-depth (∼70–300 km) have rarely been illuminated by a joint analysis of geodetic and seismic observations, hindering our understanding of their dynamic rupture mechanisms. Here we present detailed rupture process of the 2019 Mw8.0 Peru earthquake at the depth of 122 km depth, derived with a holistic approach reconciling InSAR and broad-band seismic waveform data. The joint inversion of InSAR observations and teleseismic body waves results in a finite rupture model that extends ∼200 km along strike, with unilateral rupture towards north that lasted for ∼60 s. There are four major slip patches in the finite fault model which are well corresponding to the position and timing of the sources in back-projection and multiple points source results. The largest slip patch, which occurred ∼40 s after the rupture initiation, had a longer and smoother rise time, and radiated much weaker high-frequency seismic waves compared to other smaller slip patches. This distinct frequency-dependent rupture could be explained by a strong dynamic weakening mechanism. We question whether thermal pressurization of pore free water rather than thermal run away could be such a mechanism. Our frequency content analysis could be generalized to study other earthquakes including those deeper than 300 km.
Effects of large aftershocks on spatial aftershock forecasts during the 2017–2019 western Iran sequence
Authors: Asayesh Behnam M , Zafarani Hamid , Hainzl Sebastian , Sharma Shubham
Published: August 2022

On 12 November 2017, an earthquake with a moment magnitude of 7.3 struck the west of Iran near the Iraq border. This event was followed about 9 and 12 months later by two large aftershocks of magnitude 5.9 and 6.3, which together triggered intensive seismic activity known as the 2017–2019 Kermanshah sequence. In this study, we analyse this sequence regarding the potential to forecast the spatial aftershock distribution based on information about the main shock and its largest aftershocks. Recent studies showed that classical Coulomb failure stress (CFS) maps are outperformed by alternative scalar stress quantities, as well as a distance-slip probabilistic model (R) and deep neural networks (DNN). In particular, the R-model performed best. However, these test results were based on the receiver operating characteristic (ROC) metric, which is not well suited for imbalanced data sets such as aftershock distributions. Furthermore, the previous analyses also ignored the potential impact of large secondary earthquakes. For the complex Kermanshah sequence, we applied the same forecast models but used the more appropriate MCC-F1 metric for testing. Similar to previous studies, we also observe that the receiver independent stress scalars yield better forecasts than the classical CFS values relying on the specification of receiver mechanisms. However, detailed analysis based on the MCC-F1 metric revealed that the performance depends on the grid size, magnitude cut-off and test period. Increasing the magnitude cut-off and decreasing the grid size and period reduce the performance of all methods. Finally, we found that the performance of the best methods improves when the source information of large aftershocks is additionally considered, with stress-based models outperforming the R model. Our results highlight the importance of accounting for secondary stress changes in improving earthquake forecasts.
Joint inversion based on variation of information—a crustal model of Wilkes Land, East Antarctica
Authors: Lösing Mareen , Moorkamp Max , Ebbing Jörg
Published: August 2022

By combining gravity and magnetic data in a joint inversion approach, 3-D information on the crustal structure of Wilkes Land, East Antarctica, is obtained and possible geological features become evident. Both data sets are combined through a coupling method which decreases the variation of information (VI) so data misfit and model dissimilarity are minimized simultaneously. In this manner, statistically compatible inversion results are obtained. The suitability of the method is demonstrated through a synthetic example using magnetic data and pseudo-gravity. Subsequently, we apply the method to gravity residuals and magnetic data and identify matching features of high magnitude density and susceptibility. Prominent structures in NW–SE direction along the edge of the Mawson craton and at the presumed Australo-Antarctic and Indo-Antarctic terrane boundaries are enhanced. Given the structural similarity between inverted susceptibility and density, and a strong indication of a parameter relationship, we suggest a clustering approach in order to differentiate distinct groups with similar parameter properties. The spatial distribution of these clusters reveals possible geological structures that agree with previous 2-D studies and rock measurements from the Indian and Australian continents. This shows that the VI joint inversion is a convenient approach for remote regions like East Antarctica with sparse geological samples.
Does the conditional maternal benefit programme reduce infant mortality in India?
Authors: Aizawa Toshiaki
Published: August 2022

India, which suffers from the largest number of infant deaths in the world, introduced the conditional maternity benefit programme, ‘Indira Gandhi Matritva Sahyog Yojana’ (IGMSY), to provide cash directly to pregnant and lactating women contingent on specified maternal and infant healthcare uses. This study estimates the impact of this programme on infant mortality for the first 12 months after birth, exploiting the pilot phase of IGMSY as a natural experiment in which 52 districts were randomly chosen as pilot districts. In the matched-pair difference-in-differences framework, the treatment effect on survival rate is estimated through the fully data-driven random survival forest approach. The results show that IGMSY reduced the infant mortality rate by 8.32% in treatment districts, with 1.53 fewer deaths per 1000 live births [95% prediction interval: 1.26–1.80]. The size of the effect substantially varies even within the first 12 months, indicating larger reductions in the neonatal period, and after the first 6 months. The results also reveal greater reductions among boys and children in urban areas.
Disease correction in mucopolysaccharidosis type IIIB mice by intraparenchymal or cisternal delivery of a capsid modified AAV8 codon-optimized NAGLU vector
Authors: Rouse Courtney J , Hawkins Kimberley , Kabbej Nadia , Dalugdug Justin , Kunta Aishwarya , Kim Mi-Jung , Someya Shinichi , Herbst Zachary , Gelb Michael , Dinelli Isabella , Butterworth Elizabeth , Falk Darin J , Rosenkrantz Erinn , Elmohd Hamza , Khaledi Hamid , Mowafy Samar , Ashby Frederick , Heldermon Coy D
Published: August 2022

Mucopolysaccharidosis type IIIB (MPS IIIB) is an autosomal recessive lysosomal storage disease caused by mutations in the gene that encodes the protein N-acetyl-glucosaminidase (NAGLU). Defective NAGLU activity results in aberrant retention of heparan sulfate within lysosomes leading to progressive central nervous system (CNS) degeneration. Intravenous treatment options are limited by the need to overcome the blood–brain barrier and gain successful entry into the CNS. Additionally, we have demonstrated that AAV8 provides a broader transduction area in the MPS IIIB mouse brain compared with AAV5, 9 or rh10. A triple-capsid mutant (tcm) modification of AAV8 further enhanced GFP reporter expression and distribution. Using the MPS IIIB mouse model, we performed a study using either intracranial six site or intracisterna magna injection of AAVtcm8-codon-optimized (co)-NAGLU using untreated MPS IIIB mice as controls to assess disease correction. Disease correction was evaluated based on enzyme activity, heparan sulfate storage levels, CNS lysosomal signal intensity, coordination, activity level, hearing and survival. Both histologic and enzymatic assessments show that each injection method results in supranormal levels of NAGLU expression in the brain. In this study, we have shown correction of lifespan and auditory deficits, increased CNS NAGLU activity and reduced lysosomal storage levels of heparan sulfate following AAVtcm8-coNAGLU administration and partial correction of NAGLU activity in several peripheral organs in the murine model of MPS IIIB.
Fusobacterium nucleatum Extracellular Vesicles Promote Experimental Colitis by Modulating Autophagy via the miR-574-5p/CARD3 Axis
Authors: Wei Shuchun , Zhang Jixiang , Wu Xiaohan , Chen Meilin , Huang Hancheng , Zeng Suqi , Xiang Zixuan , Li Xiangyun , Dong Weiguo
Published: August 2022

Background

Ulcerative colitis (UC) may be exacerbated by Fusobacterium nucleatum (Fn) infection. However, the mechanism underlying Fn-mediated progression of UC has yet to be established. Here, we aimed to establish whether and how Fn-derived extracellular vesicles (Fn-EVs) participate in the development of experimental colitis through microRNAs (miRNAs).

Methods

EVs were isolated and purified by ultracentrifugation from Fn and Escherichia coli culture supernatants. Differentially expressed miRNAs in control intestinal epithelial cells (IECs) and Fn-EV–treated IECs were identified by miRNA sequencing. EVs were cocultured with IECs or administered to CARD3wt/CARD3–/– mice by gavage to assess inflammatory responses to and the mechanism of action of Fn-EVs.

Results

Fn-EVs promoted upregulation of proinflammatory cytokines (interleukin [IL]-1β, IL-6, tumor necrosis factor α), downregulation of anti-inflammatory IL-10 and intercellular tight junction proteins ZO-1 and occludin, and epithelial barrier dysfunction in IECs. Fn-EVs significantly aggravated experimental colitis in mice associated with Fn-EV–mediated downregulation of miR-574-5p expression and autophagy activation. Blockade of autophagy using chloroquine alleviates barrier damage exacerbated by Fn-EVs in vitro and in vivo. Inhibition of the miR-574-5p/CARD3 axis reduced the severity of colitis, epithelial barrier damage, and autophagy activation induced by Fn-EVs.

Conclusions

Here, we describe a new mechanism by which Fn-EVs mediate experimental colitis severity through miR-574-5p/CARD3–dependent autophagy activation, providing a novel target for UC monitoring and targeted therapy.
I-COPTIC: Implementation of community pharmacy-based testing for hepatitis C: Delphi consensus protocol
Authors:   The I-COPTIC Collaboration, Cook Charlotte , Reid Leila , Smith Stuart , Crockford Deborah , El Sharkawy Ahmed M , McPherson Stuart , Wright Mark , Radley Andrew , Malik Hassan , Keall Sandie , Catt Janet , Shah Sital , Hampton Helen , Powell Julia , Morris Danny , Boothman Helen , Khakoo Salim I , Parkes Julie , Buchanan Ryan M
Published: August 2022

Objective

The World Health Organisation aims to eliminate Hepatitis C (HCV) by 2030. To achieve this, targeted testing needs to be widely available. Studies have demonstrated that community pharmacies can deliver effective targeted testing for HCV and the National Health Service in England has commissioned a national service. However, a recent survey of HCV operational delivery networks has shown limited uptake of this service. The objective of this protocol is to guide the formation of a consensus statement to facilitate the widespread implementation of community pharmacy-based targeted testing for HCV.

Method

We will use a modified Delphi method. A purposive selection of panel participants will be identified and recruited from a national survey and via chain-referral sampling. The main inclusion criteria for selection is direct involvement in the implementation of an HCV testing service in pharmacies. We aim for a heterogenous group, encompassing all aspects of the testing service. We will conduct a three round Delphi. The first round will consist of open questions which will be qualitatively analysed using thematic analysis with a framework method based on the WHO Health Systems Framework. This analysis will generate statements, that will be sent to the participants in the second round. A third round will be used where consensus is not reached.

Conclusions

The findings from this Delphi consensus study will facilitate the widespread implementation of targeted testing for HCV in community pharmacies.
Inexact Newton-CG algorithms with complexity guarantees
Authors: Yao Zhewei , Xu Peng , Roosta Fred , Wright Stephen J , Mahoney Michael W
Published: August 2022

We consider variants of a recently developed Newton-CG algorithm for nonconvex problems (Royer, C. W. & Wright, S. J. (2018) Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477) in which inexact estimates of the gradient and the Hessian information are used for various steps. Under certain conditions on the inexactness measures, we derive iteration complexity bounds for achieving $\epsilon $-approximate second-order optimality that match best-known lower bounds. Our inexactness condition on the gradient is adaptive, allowing for crude accuracy in regions with large gradients. We describe two variants of our approach, one in which the step size along the computed search direction is chosen adaptively, and another in which the step size is pre-defined. To obtain second-order optimality, our algorithms will make use of a negative curvature direction on some steps. These directions can be obtained, with high probability, using the randomized Lanczos algorithm. In this sense, all of our results hold with high probability over the run of the algorithm. We evaluate the performance of our proposed algorithms empirically on several machine learning models. Our approach is a first attempt to introduce inexact Hessian and/or gradient information into the Newton-CG algorithm of Royer & Wright (2018, Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477).
Security in the Asia-Pacific and signaling at sea
Authors: Chao Brian C , Cho Hyun-Binn
Published: August 2022

How do states signal resolve and conduct coercive diplomacy differently on land and at sea? This question has important implications for security in the Asia-Pacific, which is predominantly a maritime region. While the field of International Relations has been criticized for exhibiting a Cold War and European bias, this article is based on the observation that the field may suffer from continentalism: a reliance on land-based issues and ideas. We thus examine the potential for incorporating the maritime domain more explicitly into IR to better address the challenges to security in the Asia-Pacific. Specifically, we consider how signaling restraint, costly signals of resolve, and engaging in limited conflicts to conduct violent coercive diplomacy differ on land and at sea. Our findings suggest that addressing the challenges to security in the Asia-Pacific can benefit from a deeper understanding of signaling, coercive diplomacy, and international relations in the maritime domain.
Labor Market Discrimination and Sorting: Evidence From South Africa
Authors: Abel Martin
Published: August 2022

This paper collects a unique data set of classified ads and exploits quasi-random variation in the applicant pool composition to show that there exists hiring discrimination against immigrants in South Africa’s informal sector. Consistent with a tournament models in which immigrants are penalised, I find that both immigrant and native job seekers receive more employer clicks on their profile when being pooled with immigrant job applicants. Results also show that immigrants search further away, especially if they live in areas with high employer discrimination. This spatial sorting presents an important cost of discrimination that has largely been ignored in the literature.