bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patient Navigation Plus Tailored Digital Video Disc Increases Colorectal Cancer Screening Among Low-Income and Minority Patients Who Did Not Attend a Scheduled Screening Colonoscopy: A Randomized Trial
Authors: Rawl Susan M , Perkins Susan M , Tong Yan , Katz Mira L , Carter-Bawa Lisa , Imperiale Thomas F , Schwartz Peter H , Fatima Hala , Krier Connie , Tharp Kevin , Shedd-Steele Rivienne , Magnarella Mark , Malloy Caeli , Haunert Laura , Gebregziabher Netsanet , Paskett Electra D , Champion Victoria 
Published: March 2024

Abstract

Background
Up to 50% of people scheduled for screening colonoscopy do not complete this test and no studies have focused on minority and low-income populations. Interventions are needed to improve colorectal cancer (CRC) screening knowledge, reduce barriers, and provide alternative screening options. Patient navigation (PN) and tailored interventions increase CRC screening uptake, however there is limited information comparing their effectiveness or the effect of combining them.

Purpose
Compare the effectiveness of two interventions to increase CRC screening among minority and low-income individuals who did not attend their screening colonoscopy appointment—a mailed tailored digital video disc (DVD) alone versus the mailed DVD plus telephone-based PN compared to usual care.

Methods
Patients (n = 371) aged 45–75 years at average risk for CRC who did not attend a screening colonoscopy appointment were enrolled and were randomized to: (i) a mailed tailored DVD; (ii) the mailed DVD plus phone-based PN; or (iii) usual care. CRC screening outcomes were from electronic medical records at 12 months. Multivariable logistic regression analyses were used to study intervention effects.

Results
Participants randomized to tailored DVD plus PN were four times more likely to complete CRC screening compared to usual care and almost two and a half times more likely than those who were sent the DVD alone.

Conclusions
Combining telephone-based PN with a mailed, tailored DVD increased CRC screening among low-income and minority patients who did not attend their screening colonoscopy appointments and has potential for wide dissemination.
Standing ‘in’ and ‘out’ from the Crowd in a Small Genre: Proximity and Positioning in Applied Linguists’ Email Signatures
Authors: Aslan Erhan , Jaworska Sylvia 
Published: March 2024

Abstract
Neoliberal demands in higher education (HE) amplified by the affordances of digitalisation have led to the emergence of various academic branding practices, one of which is the use of email signatures for identity work and self-promotion. Examining a corpus of 200 email signatures created by applied linguists between 2011 and 2020, this study identifies core and optional moves and how the moves orient to proximity (scholarly communities) and positioning (reputational work). The quantitative analysis of the dataset supported by semi-structured interviews with a group of academics shows that while core moves provide basic identity information, optional moves are used strategically for positioning. A comparison by career stage reveals that mid-career academics utilize more positioning than early-career and established academics. The positioning moves in the second half of the decade draw more on academic achievements, multimodality, and digital presence. The study contributes to an enhanced understanding of how a small and originally inconspicuous genre becomes a space for academic branding and evaluates this development against the increasingly competitive and precarious conditions of the neoliberal HE sector.
Inferring a directed acyclic graph of phenotypes from GWAS summary statistics
Authors: Zilinskas Rachel , Li Chunlin , Shen Xiaotong , Pan Wei , Yang Tianzhong 
Published: March 2024

ABSTRACT
Estimating phenotype networks is a growing field in computational biology. It deepens the understanding of disease etiology and is useful in many applications. In this study, we present a method that constructs a phenotype network by assuming a Gaussian linear structure model embedding a directed acyclic graph (DAG). We utilize genetic variants as instrumental variables and show how our method only requires access to summary statistics from a genome-wide association study (GWAS) and a reference panel of genotype data. Besides estimation, a distinct feature of the method is its summary statistics-based likelihood ratio test on directed edges. We applied our method to estimate a causal network of 29 cardiovascular-related proteins and linked the estimated network to Alzheimer’s disease (AD). A simulation study was conducted to demonstrate the effectiveness of this method. An R package sumdag implementing the proposed method, all relevant code, and a Shiny application are available.
High-dimensional sparse vine copula regression with application to genomic prediction
Authors: Sahin Özge , Czado Claudia 
Published: March 2024

Abstract
High-dimensional data sets are often available in genome-enabled predictions. Such data sets include nonlinear relationships with complex dependence structures. For such situations, vine copula-based (quantile) regression is an important tool. However, the current vine copula-based regression approaches do not scale up to high and ultra-high dimensions. To perform high-dimensional sparse vine copula-based regression, we propose 2 methods. First, we show their superiority regarding computational complexity over the existing methods. Second, we define relevant, irrelevant, and redundant explanatory variables for quantile regression. Then, we show our method’s power in selecting relevant variables and prediction accuracy in high-dimensional sparse data sets via simulation studies. Next, we apply the proposed methods to the high-dimensional real data, aiming at the genomic prediction of maize traits. Some data processing and feature extraction steps for the real data are further discussed. Finally, we show the advantage of our methods over linear models and quantile regression forests in simulation studies and real data applications.
Merging or ensembling: integrative analysis in multiple neuroimaging studies
Authors: Shan Yue , Huang Chao , Li Yun , Zhu Hongtu 
Published: March 2024

ABSTRACT
The aim of this paper is to systematically investigate merging and ensembling methods for spatially varying coefficient mixed effects models (SVCMEM) in order to carry out integrative learning of neuroimaging data obtained from multiple biomedical studies. The ”merged” approach involves training a single learning model using a comprehensive dataset that encompasses information from all the studies. Conversely, the ”ensemble” approach involves creating a weighted average of distinct learning models, each developed from an individual study. We systematically investigate the prediction accuracy of the merged and ensemble learners under the presence of different degrees of interstudy heterogeneity. Additionally, we establish asymptotic guidelines for making strategic decisions about when to employ either of these models in different scenarios, along with deriving optimal weights for the ensemble learner. To validate our theoretical results, we perform extensive simulation studies. The proposed methodology is also applied to 3 large-scale neuroimaging studies.
Estimation of the causal effects of time-varying treatments in nested case-control studies using marginal structural Cox models
Authors: Takeuchi Yoshinori , Hagiwawa Yasuhiro , Komukai Sho , Matsuyama Yutaka 
Published: March 2024

ABSTRACT
When estimating the causal effects of time-varying treatments on survival in nested case-control (NCC) studies, marginal structural Cox models (Cox-MSMs) with inverse probability weights (IPWs) are a natural approach. However, calculating IPWs from the cases and controls is difficult because they are not random samples from the full cohort, and the number of subjects may be insufficient for calculation. To overcome these difficulties, we propose a method for calculating IPWs to fit Cox-MSMs to NCC sampling data. We estimate the IPWs using a pseudo-likelihood estimation method with an inverse probability of sampling weight using NCC samples, and additional samples of subjects who experience treatment changes and subjects whose follow-up is censored are required to calculate the weights. Our method only requires covariate histories for the samples. The confidence intervals are calculated from the robust variance estimator for the NCC sampling data. We also derive the asymptotic properties of the estimator of Cox-MSM under NCC sampling. The proposed methods will allow researchers to apply several case-control matching methods to improve statistical efficiency. A simulation study was conducted to evaluate the finite sample performance of the proposed method. We also applied our method to a motivating pharmacoepidemiological study examining the effect of statins on the incidence of coronary heart disease. The proposed method may be useful for estimating the causal effects of time-varying treatments in NCC studies.
A boosting method to select the random effects in linear mixed models
Authors: Battauz Michela , Vidoni Paolo 
Published: March 2024

ABSTRACT
This paper proposes a novel likelihood-based boosting method for the selection of the random effects in linear mixed models. The nonconvexity of the objective function to minimize, which is the negative profile log-likelihood, requires the adoption of new solutions. In this respect, our optimization approach also employs the directions of negative curvature besides the usual Newton directions. A simulation study and a real-data application show the good performance of the proposal.
Secukinumab in patients with moderate-to-severe hidradenitis suppurativa based on prior biologic exposure: an efficacy and safety analysis from the SUNSHINE and SUNRISE phase III trials
Authors: Zouboulis Christos C , Passeron Thierry , Pariser David , Wozniak Magdalena B , Li Xianjun , Uhlmann Lorenz , Lobach Iryna , Martinez Angela Llobet , Ravichandran Shoba , Alarcon Ivette , Offidani Annamaria , Alam Maryam S , Mendes-Bastos Pedro 
Published: March 2024

Lay Summary
Hidradenitis suppurativa (HS) is a chronic skin disease that causes painful boils. HS is common and affects about 0.4% of the world’s population. Treating the condition is difficult, but drugs called ‘biologics’ can help to improve the symptoms. For example, secukinumab is a biologic drug that has been shown to be effective and well-tolerated for the treatment of HS.
In this analysis, we investigated whether previous treatment with biologics could affect the effectiveness and tolerability of secukinumab. This analysis included data from two identical clinical trials (called SUNSHINE and SUNRISE) that recruited adult patients with HS who had moderate-to-severe disease. In these trials, patients took secukinumab 300 mg every 2 weeks or every 4 weeks for 1 year, or a placebo for 4 months and then switched to secukinumab until 1 year. At regular intervals, the effectiveness and tolerability of secukinumab were examined and the results were compared between patients who had previously used another biologic and patients who had never used a biologic before.
After 16 weeks, patients who took secukinumab had better results than the patients who took a placebo, independent of previous biologic use. Secukinumab was still effective and had improved results over 1 year of treatment in both subgroups. Regardless of whether patients had previously been taking another biologic, secukinumab was just as tolerable as placebo and there were no new safety risks.
Our analysis shows that secukinumab is effective and tolerable, regardless of whether patients have previously used another biologic drug.
Dysregulation of extracellular potassium distinguishes healthy ageing from neurodegeneration
Authors: Ding Fengfei , Sun Qian , Long Carter , Rasmussen Rune Nguyen , Peng Sisi , Xu Qiwu , Kang Ning , Song Wei , Weikop Pia , Goldman Steven A , Nedergaard Maiken 
Published: March 2024

Abstract
Progressive neuronal loss is a hallmark feature distinguishing neurodegenerative diseases from normal ageing. However, the underlying mechanisms remain unknown. Extracellular K+ homeostasis is a potential mediator of neuronal injury as K+ elevations increase excitatory activity. The dysregulation of extracellular K+ and potassium channel expressions during neurodegeneration could contribute to this distinction. Here we measured the cortical extracellular K+ concentration ([K+]e) in awake wild-type mice as well as murine models of neurodegeneration using K+-sensitive microelectrodes.
Unexpectedly, aged wild-type mice exhibited significantly lower cortical [K+]e than young mice. In contrast, cortical [K+]e was consistently elevated in Alzheimer’s disease (APP/PS1), amyotrophic lateral sclerosis (ALS) (SOD1G93A) and Huntington’s disease (R6/2) models. Cortical resting [K+]e correlated inversely with neuronal density and the [K+]e buffering rate but correlated positively with the predicted neuronal firing rate. Screening of astrocyte-selective genomic datasets revealed a number of potassium channel genes that were downregulated in these disease models but not in normal ageing. In particular, the inwardly rectifying potassium channel Kcnj10 was downregulated in ALS and Huntington’s disease models but not in normal ageing, while Fxyd1 and Slc1a3, each of which acts as a negative regulator of potassium uptake, were each upregulated by astrocytes in both Alzheimer’s disease and ALS models. Chronic elevation of [K+]e in response to changes in gene expression and the attendant neuronal hyperexcitability may drive the neuronal loss characteristic of these neurodegenerative diseases. These observations suggest that the dysregulation of extracellular K+ homeostasis in a number of neurodegenerative diseases could be due to aberrant astrocytic K+ buffering and as such, highlight a fundamental role for glial dysfunction in neurodegeneration.
TMEM16A inhibits autophagy and promotes the invasion of hypopharyngeal squamous cell carcinoma through mTOR pathway
Authors: Yang Xin , Cui Limei , Liu Zhonglu , Li Yumei , Wu Xinxin , Tian Ruxian , Jia Chuanliang , Ren Chao , Mou Yakui , Song Xicheng 
Published: March 2024

Abstract
Previous studies have indicated that transmembrane protein 16A (TMEM16A) plays a crucial role in the pathogenesis and progression of various tumors by influencing multiple signaling pathways. However, the role of TMEM16A in regulating autophagy via the mammalian target of rapamycin (mTOR) pathway and its impact on the development of hypopharyngeal squamous cell carcinoma (HSCC) remain unclear. Immunohistochemistry and western blotting were used to assess the expression of TMEM16A in HSCC tissues and metastatic lymph nodes. Manipulation of TMEM16A expression levels was achieved in the FaDu cell line through overexpression or knockdown, followed by assessment of its biological effects using cell colony formation, wound healing, transwell and invasion assays. Additionally, apoptosis and autophagy-related proteins, as well as autophagosome formation, were evaluated through western blotting, transmission electron microscopy and immunofluorescence following TMEM16A knockdown or overexpression in FaDu cells. Our study revealed significantly elevated levels of TMEM16A in both HSCC tissues and metastatic lymph nodes compared with normal tissues. In vitro experiments demonstrated that silencing TMEM16A led to a notable suppression of HSCC cell proliferation, invasion and migration. Furthermore, TMEM16A silencing effectively inhibited tumor growth in xenografted mice. Subsequent investigations indicated that knockdown of TMEM16A in HSCC cells could suppress mTOR activation, thereby triggering autophagic cell death by upregulating sequestosome-1 (SQSTM1/P62) and microtubule-associated protein light chain 3 II (LC3II). This study highlights the crucial role of TMEM16A in modulating autophagy in HSCC, suggesting its potential as a therapeutic target for the treatment of this malignancy.
Pulse azathioprine and low-dose methotrexate vs. standard-dose methotrexate in treatment of patients with moderate-to-severe psoriasis: a randomized controlled trial
Authors: El-Komy Mohamed Hussein Medhat , Sayed Khadiga S , Gawish Gehad , Elaguizy Menatallah Mohamed , Azzazi Yousra 
Published: March 2024

Abstract

Background
Psoriasis is a common chronic, immune-mediated inflammatory skin disease. Despite the availability of several systemic therapeutic agents, treatment of psoriasis remains a challenge because of the associated adverse effects and/or the financial burden of these medications, given the chronicity of the disease.

Objectives
We aimed to compare the efficacy and safety of combined pulse azathioprine (AZA) and low-dose methotrexate (MTX) vs. a conventional dose of MTX in patients with chronic plaque psoriasis.

Methods
In this randomized controlled trial, 67 patients with moderate-to-severe plaque psoriasis were randomized into two groups, receiving either combined pulse AZA (300 mg weekly dose) and low-dose MTX (10 mg weekly) or conventional-dose MTX (0.3 mg kg−1 per week) for 16 weeks. Patients were assessed for treatment response using the Psoriasis Area and Severity Index (PASI) score and for the development of any adverse effects at weeks 12 and 16, and for a further 3 months after stopping treatment.

Results
A statistically significantly higher proportion of the patients receiving combined pulse AZA and low-dose MTX achieved ≥ 90% improvement in PASI and 100% improvement (PASI 100) at week 12, and PASI 100 at week 16, compared with those receiving the conventional dose of MTX as monotherapy. No serious adverse events were reported during the entire study period in the two groups.

Conclusions
Combination therapy using pulse AZA and low-dose MTX can be an efficacious treatment for moderate-to-severe plaque psoriasis, with a relatively good safety profile.
Utilizing graph convolutional networks for identification of mild cognitive impairment from single modal fMRI data: a multiconnection pattern combination approach
Authors: He Jie , Wang Peng , He Jun , Sun Chenhao , Xu Xiaowen , Zhang Lei , Wang Xin , Gao Xin 
Published: March 2024

Abstract
Mild cognitive impairment plays a crucial role in predicting the early progression of Alzheimer’s disease, and it can be used as an important indicator of the disease progression. Currently, numerous studies have focused on utilizing the functional brain network as a novel biomarker for mild cognitive impairment diagnosis. In this context, we employed a graph convolutional neural network to automatically extract functional brain network features, eliminating the need for manual feature extraction, to improve the mild cognitive impairment diagnosis performance. However, previous graph convolutional neural network approaches have primarily concentrated on single modes of brain connectivity, leading to a failure to leverage the potential complementary information offered by diverse connectivity patterns and limiting their efficacy. To address this limitation, we introduce a novel method called the graph convolutional neural network with multimodel connectivity, which integrates multimode connectivity for the identification of mild cognitive impairment using fMRI data and evaluates the graph convolutional neural network with multimodel connectivity approach through a mild cognitive impairment diagnostic task on the Alzheimer’s Disease Neuroimaging Initiative dataset. Overall, our experimental results show the superiority of the proposed graph convolutional neural network with multimodel connectivity approach, achieving an accuracy rate of 92.2% and an area under the Receiver Operating Characteristic (ROC) curve of 0.988.
Auditory prediction errors in sound frequency and duration generated different cortical activation patterns in the human brain: an ECoG study
Authors: Takasago Megumi , Kunii Naoto , Fujitani Shigeta , Ishishita Yohei , Tada Mariko , Kirihara Kenji , Komatsu Misako , Uka Takanori , Shimada Seijiro , Nagata Keisuke , Kasai Kiyoto , Saito Nobuhito 
Published: March 2024

Abstract
Sound frequency and duration are essential auditory components. The brain perceives deviations from the preceding sound context as prediction errors, allowing efficient reactions to the environment. Additionally, prediction error response to duration change is reduced in the initial stages of psychotic disorders. To compare the spatiotemporal profiles of responses to prediction errors, we conducted a human electrocorticography study with special attention to high gamma power in 13 participants who completed both frequency and duration oddball tasks. Remarkable activation in the bilateral superior temporal gyri in both the frequency and duration oddball tasks were observed, suggesting their association with prediction errors. However, the response to deviant stimuli in duration oddball task exhibited a second peak, which resulted in a bimodal response. Furthermore, deviant stimuli in frequency oddball task elicited a significant response in the inferior frontal gyrus that was not observed in duration oddball task. These spatiotemporal differences within the Parasylvian cortical network could account for our efficient reactions to changes in sound properties. The findings of this study may contribute to unveiling auditory processing and elucidating the pathophysiology of psychiatric disorders.
Transcatheter aortic valve implantation for structural valve deterioration of homograft surgical aortic valve using SAPIEN3 Ultra RESILIA: a case report
Authors: Mizutani Kazuki , Ueno Masafumi , Sakaguchi Genichi , Nakazawa Gaku 
Published: March 2024

Abstract

Background
There are a few case reports regarding transcatheter aortic valve implantation (TAVI) for deteriorated surgical homograft.

Case summary
We present a case of severe structural valve deterioration (SVD) of homograft surgical aortic valve presenting severe aortic regurgitation in an 84-year-old man with decompensated heart failure. We performed TAVI in homograft valve using 23 mm SAPIEN3 Ultra RESILIA. The resulting grade of paravalvular regurgitation was trace, the post-operative effective orifice area (EOA) was 1.66 cm2 (index EOA: 1.19 cm2/m2), and device success was achieved.

Discussion
Stented bioprosthetic valves are more commonly implanted than mechanical and stentless bioprosthetic valves. In the 1980s and the early 1990s, homografts became particularly popular as alternatives to stented valves. There are several reports of TAVI for homograft SVD, but the paravalvular leakage grade is worse than that of redo-surgical aortic valve replacement, although the mortality rate is lower. However, the valves used in these reports were from older valves such as SAPIEN XT or SAPIEN3. There are no reports using SAPIEN3 Ultra RESILIA with a significant reduction in paravalvular leak due to an external textured polyethylene terephthalate skirt extending 40% higher above the valve inflow than the classical SAPIEN3, which is now available. Transcatheter aortic valve implantation using SAPIEN3 Ultra RESILIA showed good therapeutic efficacy.