bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring the performance of an artificial intelligence–based robot that classifies blood tubes and performs quality control in terms of preanalytical errors: A preliminary study
Authors: Şişman Ali Rıza , Başok Banu İşbilen , Karakoyun İnanç , Çolak Ayfer , Bilge Uğur , Demirci Ferhat , Başoglu Nuri 
Published: January 2024

Abstract

Objectives
Artificial intelligence–based robotic systems are increasingly used in medical laboratories. This study aimed to test the performance of KANKA (Labenko), a stand-alone, artificial intelligence–based robot that performs sorting and preanalytical quality control of blood tubes.

Methods
KANKA is designed to perform preanalytical quality control with respect to error control and preanalytical sorting of blood tubes. To detect sorting errors and preanalytical inappropriateness within the routine work of the laboratory, a total of 1000 blood tubes were presented to the KANKA robot in 7 scenarios. These scenarios encompassed various days and runs, with 5 repetitions each, resulting in a total of 5000 instances of sorting and detection of preanalytical errors. As the gold standard, 2 experts working in the same laboratory identified and recorded the correct sorting and preanalytical errors. The success rate of KANKA was calculated for both the accurate tubes and those tubes with inappropriate identification.

Results
KANKA achieved an overall accuracy rate of 99.98% and 100% in detecting tubes with preanalytical errors. It was found that KANKA can perform the control and sorting of 311 blood tubes per hour in terms of preanalytical errors.

Conclusions
KANKA categorizes and records problem-free tubes according to laboratory subunits while identifying and classifying tubes with preanalytical inappropriateness into the correct error sections. As a blood acceptance and tube sorting system, KANKA has the potential to save labor and enhance the quality of the preanalytical process.
Multiple augmented reduced rank regression for pan-cancer analysis
Authors: Wang Jiuzhou , Lock Eric F 
Published: January 2024

ABSTRACT
Statistical approaches that successfully combine multiple datasets are more powerful, efficient, and scientifically informative than separate analyses. To address variation architectures correctly and comprehensively for high-dimensional data across multiple sample sets (ie, cohorts), we propose multiple augmented reduced rank regression (maRRR), a flexible matrix regression and factorization method to concurrently learn both covariate-driven and auxiliary structured variations. We consider a structured nuclear norm objective that is motivated by random matrix theory, in which the regression or factorization terms may be shared or specific to any number of cohorts. Our framework subsumes several existing methods, such as reduced rank regression and unsupervised multimatrix factorization approaches, and includes a promising novel approach to regression and factorization of a single dataset (aRRR) as a special case. Simulations demonstrate substantial gains in power from combining multiple datasets, and from parsimoniously accounting for all structured variations. We apply maRRR to gene expression data from multiple cancer types (ie, pan-cancer) from The Cancer Genome Atlas, with somatic mutations as covariates. The method performs well with respect to prediction and imputation of held-out data, and provides new insights into mutation-driven and auxiliary variations that are shared or specific to certain cancer types.
Efficient estimation for left-truncated competing risks regression for case-cohort studies
Authors: Fang Xi , Ahn Kwang Woo , Cai Jianwen , Kim Soyoung 
Published: January 2024

Abstract
The case-cohort study design provides a cost-effective study design for a large cohort study with competing risk outcomes. The proportional subdistribution hazards model is widely used to estimate direct covariate effects on the cumulative incidence function for competing risk data. In biomedical studies, left truncation often occurs and brings extra challenges to the analysis. Existing inverse probability weighting methods for case-cohort studies with competing risk data not only have not addressed left truncation, but also are inefficient in regression parameter estimation for fully observed covariates. We propose an augmented inverse probability-weighted estimating equation for left-truncated competing risk data to address these limitations of the current literature. We further propose a more efficient estimator when extra information from the other causes is available. The proposed estimators are consistent and asymptotically normally distributed. Simulation studies show that the proposed estimator is unbiased and leads to estimation efficiency gain in the regression parameter estimation. We analyze the Atherosclerosis Risk in Communities study data using the proposed methods.
Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors
Authors: Zhang Qiyiwen , Chang Changgee , Shen Li , Long Qi 
Published: January 2024

ABSTRACTThere has been an increasing interest in decomposing high-dimensional multi-omics data into a product of low-rank and sparse matrices for the purpose of dimension reduction and feature engineering. Bayesian factor models achieve such low-dimensional representation of the original data through different sparsity-inducing priors. However, few of these models can efficiently incorporate the information encoded by the biological graphs, which has been already proven to be useful in many analysis tasks. In this work, we propose a Bayesian factor model with novel hierarchical priors, which incorporate the biological graph knowledge as a tool of identifying a group of genes functioning collaboratively. The proposed model therefore enables sparsity within networks by allowing each factor loading to be shrunk adaptively and by considering additional layers to relate individual shrinkage parameters to the underlying graph information, both of which yield a more accurate structure recovery of factor loadings. Further, this new priors overcome the phase transition phenomenon, in contrast to existing graph-incorporated approaches, so that it is robust to noisy edges that are inconsistent with the actual sparsity structure of the factor loadings. Finally, our model can handle both continuous and discrete data types. The proposed method is shown to outperform several existing factor analysis methods through simulation experiments and real data analyses.
Genetics in Parkinson’s disease, state-of-the-art and future perspectives
Authors: Trevisan L , Gaudio A , Monfrini E , Avanzino L , Di Fonzo A , Mandich P 
Published: January 2024

Abstract

Background
Parkinson’s disease (PD) is the second most common neurodegenerative disorder and is clinically characterized by the presence of motor (bradykinesia, rigidity, rest tremor and postural instability) and non-motor symptoms (cognitive impairment, autonomic dysfunction, sleep disorders, depression and hyposmia). The aetiology of PD is unknown except for a small but significant contribution of monogenic forms.

Sources of data
No new data were generated or analyzed in support of this review.

Areas of agreement
Up to 15% of PD patients carry pathogenic variants in PD-associated genes. Some of these genes are associated with mendelian inheritance, while others act as risk factors. Genetic background influences age of onset, disease course, prognosis and therapeutic response.

Areas of controversy
Genetic testing is not routinely offered in the clinical setting, but it may have relevant implications, especially in terms of prognosis, response to therapies and inclusion in clinical trials. Widely adopted clinical guidelines on genetic testing are still lacking and open to debate. Some new genetic associations are still awaiting confirmation, and selecting the appropriate genes to be included in diagnostic panels represents a difficult task. Finally, it is still under study whether (and to which degree) specific genetic forms may influence the outcome of PD therapies.

Growing points
Polygenic Risk Scores (PRS) may represent a useful tool to genetically stratify the population in terms of disease risk, prognosis and therapeutic outcomes.

Areas timely for developing research
The application of PRS and integrated multi-omics in PD promises to improve the personalized care of patients.
Reduced covariation between brain morphometry and local spontaneous activity in young children with ASD
Authors: Chen Bosi , Olson Lindsay , Rios Adriana , Salmina Madison , Linke Annika , Fishman Inna 
Published: January 2024

Abstract
While disruptions in brain maturation in the first years of life in ASD are well documented, little is known about how the brain structure and function are related in young children with ASD compared to typically developing peers. We applied a multivariate pattern analysis to examine the covariation patterns between brain morphometry and local brain spontaneous activity in 38 toddlers and preschoolers with ASD and 31 typically developing children using T1-weighted structural MRI and resting-state fMRI data acquired during natural sleep. The results revealed significantly reduced brain structure–function correlations in ASD. The resultant brain structure and function composite indices were associated with age among typically developing children, but not among those with ASD, suggesting mistiming of typical brain maturational trajectories early in life in autism. Additionally, the brain function composite indices were associated with the overall developmental and adaptive behavior skills in the ASD group, highlighting the neurodevelopmental significance of early local brain activity in autism.
Smelling of the mothers’ diet in amniotic fluid by adult noses
Authors: Gellrich Janine , Breidel Pauline , Birdir Cahit , Lohrer Elisabeth C , Schriever Valentin A 
Published: January 2024

Abstract
In this study, the transfer of odorants, namely vanilla, and garlic, into the amniotic fluid (AF) during the second trimester was investigated by examination of collected AF samples through healthy adults. Eleven AF samples were collected from pregnant women (aged 32.9 ± 4.9 yr, 16–25 wk of gestation) undergoing diagnostic amniocentesis after eating garlic oil or vanilla powder in high-fat yogurt. The control group did not receive food before amniocentesis. Two vanilla, 3 garlic, and 6 control samples were collected through amniocentesis 60–120 min after ingestion. Samples were collected at −80 °C and carefully defrosted over 12 h at the same time point. Sixteen healthy volunteers (8 males, aged 26.5 ± 5.0 yr) were asked to judge AF samples with potential garlic or vanilla odors from controls in a 2-alternative forced choice (2AFC) paradigm. Judges were able to identify vanilla in the AF samples with an estimated probability of 50%, resulting in a significant P-value of &lt; 0.001. In contrast, the identification of garlic was unsuccessful with a P-value of 0.86, and only 2 judges were able to identify both vanilla and garlic. According to the results of this study, the vanilla odor probably passes into the amniotic fluid.
Enhancing Aspect Category Detection Through Hybridised Contextualised Neural Language Models: A Case Study In Multi-Label Text Classification
Authors: Karaoglan Kursat Mustafa , Findik Oguz 
Published: January 2024

Abstract
Recently, the field of Natural Language Processing (NLP) has made significant progress with the evolution of Contextualised Neural Language Models (CNLMs) and the emergence of large LMs. Traditional and static language models exhibit limitations in tasks demanding contextual comprehension due to their reliance on fixed representations. CNLMs such as BERT and Semantic Folding aim to produce feature-rich representations by considering a broader linguistic context. In this paper, Deep Learning-based Aspect Category Detection approaches are introduced to perform text classification. The study extensively assesses classification model performance, emphasising enhanced representativeness and optimised feature extraction resolution using CNLMs and their hybridised variants. The effectiveness of the proposed approaches is evaluated on benchmark datasets of 4500 reviews from the laptop and restaurant domains. The results show that the proposed approaches using hybridised CNLMs outperform state-of-the-art methods with an f-score of 0.85 for the laptop and f-scores higher than 0.90 for the restaurant dataset. This study represents a pioneering work as one of the initial research efforts aiming to jointly evaluate the representation performance of CNLMs with different architectures to determine their classification capabilities. The findings indicate that the proposed approaches can enable the development of more effective classification models in various NLP tasks.
AHP DB: a reference database of proteins in the human aqueous humor
Authors: Lee Tae Jin , Goyal Arnav , Jones Garrett , Glass Joshua , Doshi Vishal , Bollinger Kathryn , Ulrich Lane , Ahmed Saleh , Kodeboyina Sai Karthik , Estes Amy , Töteberg-Harms Marc , Zhi Wenbo , Sharma Shruti , Sharma Ashok 
Published: January 2024

Abstract
The aqueous humor (AH) is a low-viscosity biofluid that continuously circulates from the posterior chamber to the anterior chamber of the eye. Recent advances in high-resolution mass-spectrometry workflows have facilitated the study of proteomic content in small-volume biofluids like AH, highlighting the potential clinical implications of the AH proteome. Nevertheless, in-depth investigations into the role of AH proteins in ocular diseases have encountered challenges due to limited accessibility to these workflows, difficulties in large-scale AH sample collection and the absence of a reference AH proteomic database. In response to these obstacles, and to promote further research on the involvement of AH proteins in ocular physiology and pathology, we have developed the web-based Aqueous Humor Proteomics Database (AHP DB). The current version of AHP DB contains proteomic data from 307 human AH samples, which were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The database offers comprehensive information on 1683 proteins identified in the AH samples. Furthermore, relevant clinical data are provided for each analyzed sample. Researchers also have the option to download these datasets individually for offline use, rendering it a valuable resource for the scientific community.
Database URL: https://ahp.augusta.edu/
Intestinal Epithelia and Myeloid Immune Cells Shape Colitis Severity and Colorectal Carcinogenesis via High-mobility Group Box Protein 1
Authors: Foelsch Katharina , Pelczar Penelope , Zierz Elisabeth , Kondratowicz Stephanie , Qi Minyue , Mueller Christian , Alawi Malik , Huebener Sina , Clauditz Till , Gagliani Nicola , Huber Samuel , Huebener Peter 
Published: January 2024

AbstractBackgroundHigh-mobility group box protein 1 [HMGB1] is a ubiquitous nucleoprotein with immune-regulatory properties following cellular secretion or release in sterile and in infectious inflammation. Stool and serum HMGB1 levels correlate with colitis severity and colorectal cancer [CRC] progression, yet recent reports indicate that HMGB1 mainly operates as an intracellular determinant of enterocyte fate during colitis, and investigations into the roles of HMGB1 in CRC are lacking.MethodsUsing mice with conditional HMGB1-knockout in enterocytes [Hmgb1ΔIEC] and myeloid cells [Hmgb1ΔLysM], respectively, we explored functions of HMGB1 in pathogenetically diverse contexts of colitis and colitis-associated CRC.ResultsHMGB1 is overexpressed in human inflammatory bowel disease and gastrointestinal cancers, and HMGB1 protein localises in enterocytes and stromal cells in colitis and CRC specimens from humans and rodents. As previously described, enterocyte HMGB1 deficiency aggravates severe chemical-induced intestinal injury, but not Citrobacter rodentium or T cell transfer colitis in mice. HMGB1-deficient enterocytes and organoids do not exhibit deviant apoptotic or autophagic activity, altered proliferative or migratory capacity, abnormal intestinal permeability, or aberrant DSS-induced organoid inflammation in vitro. Instead, we observed altered in vivo reprogramming of both intestinal epithelia and infiltrating myeloid cells in Hmgb1ΔIEC early during colitis, suggesting HMGB1-mediated paracrine injury signalling. Hmgb1ΔIEC had higher CRC burden than wild types in the Apc+/min model, whereas inflammatory CRC was attenuated in Hmgb1ΔLysM. Cellular and molecular phenotyping of Hmgb1ΔIEC and Hmgb1ΔLysM cancers indicates context-dependent transcriptional modulation of immune signalling and extracellular matrix remodelling via HMGB1.ConclusionEnterocytes and myeloid cells context-dependently regulate host responses to severe colitis and maladaptive intestinal wound healing via HMGB1.
Distinctive left ventricular–arterial and right ventricular–pulmonary arterial coupling observed in patients with heart failure and a higher left ventricular ejection fraction range
Authors: Ohte Nobuyuki , Kikuchi Shohei , Iwahashi Noriaki , Kinugasa Yoshiharu , Dohi Kaoru , Takase Hiroyuki , Masai Kumiko , Inoue Katsuji , Okumura Takahiro , Hachiya Kenta , Kitada Shuichi , Seo Yoshihiro ,   EASY HFpEF investigators, Ohte Nobuyuki , Kikuchi Shohei , Iwahashi Noriaki , Kinugasa Yoshiharu , Dohi Kaoru , Takase Hiroyuki , Masai Kumiko , Inoue Katsuji , Okumura Takahiro , Hachiya Kenta , Kitada Shuichi , Seo Yoshihiro , Murohara Toyoaki , Iwano Hiroyuki , Murata Mitsushige , Yamada Hirotsugu , Kusunose Kenya , Iwataki Mai , Sugiura Emiyo , Yuda Satoshi , Suzuki Takeshi 
Published: January 2024

Abstract

Aims
Higher left ventricular (LV) ejection fraction (EF) is related to unfavourable prognosis in patients with heart failure (HF) with preserved ejection fraction (HFpEF). The cause of this finding needs to be haemodynamically explained. Thus, we investigated this crucial issue from the perspective of LV–arterial (A) and right ventricular (RV)–pulmonary arterial (PA) coupling.

Methods and results
Study patients were derived from our prospective cohort study of patients hospitalized due to acute decompensated HF and LVEF &gt; 40%. We divided the 255 patients into three groups: HF with mildly reduced EF (HFmrEF), HFpEF with 50% ≤ LVEF &lt; 60%, and HFpEF with LVEF ≥ 60%. We compared LV end-systolic elastance (Ees), effective arterial elastance (Ea), and Ees/Ea as a representative of LV–A coupling among groups and compared the ratio of tricuspid annular plane excursion to peak pulmonary arterial systolic pressure (TAPSE/PASP) as a representative of RV–PA coupling. All-cause death and readmission due to HF-free survival was worse in the group with a higher LVEF range. Ees/Ea was greater in HFpEF patients with LVEF ≥ 60% (2.12 ± 0.57) than in those with 50% ≤ LVEF &lt; 60% (1.20 ± 0.14) and those with HFmrEF (0.82 ± 0.09) (P &lt; 0.001). PASP was increased in the groups with higher LVEF; however, TAPSE/PASP did not differ among groups (n = 168, P = 0.17). In a multivariate Cox proportional hazard model, TAPSE/PASP but not PASP was significantly related to event-free survival independent of LVEF.

Conclusion
HFpEF patients with higher LVEF have unfavourable prognosis and distinctive LV–A coupling: Ees/Ea is elevated up to 2.0 or more. Impaired RV–PA coupling also worsens prognosis in such patients.

Clinical trial registration
URL: https://www.umin.ac.jp/ctr/index.htm Unique identifier: UMIN000017725.
The Political Legacy of Nazi Annexation
Authors: Cannella Mario , Makarin Alexey , Pique Ricardo 
Published: January 2024

Abstract
We explore the legacy of foreign state repression by using the case of the de facto annexed Nazi operational zones in Italy and a spatial regression discontinuity design. We show that the operational zones experienced harsher political persecution and violence. After the war, these exhibited greater support for radical opposition at the expense of the moderate ruling party. Consistent with a mechanism of greater distrust in the government, formerly annexed areas are more likely to vote against laws suppressing dissent and report lower political trust. These results suggest that repressive annexation, even if temporary, has enduring political and social consequences.
Day-to-day home blood pressure variability and risk of atrial fibrillation in a general Japanese population: the Hisayama Study
Authors: Maezono Akihiro , Sakata Satoko , Hata Jun , Oishi Emi , Furuta Yoshihiko , Shibata Mao , Ide Tomomi , Kitazono Takanari , Tsutsui Hiroyuki , Ninomiya Toshiharu 
Published: January 2024

Abstract

Aims
Several prospective studies have reported that higher visit-to-visit blood pressure variability (BPV) is associated with atrial fibrillation (AF). However, no studies have investigated the association between day-to-day BPV assessed by home blood pressure measurement and the development of AF.

Methods and results
A total of 2829 community-dwelling Japanese aged ≥40 years without prior AF were followed up for 10 years (2007–17). Day-to-day home BPV [defined as coefficient of variation (CoV) of home systolic blood pressure (SBP) for 28 days] was categorized into four groups according to the quartiles: Q1, ≤ 4.64%; Q2, 4.65–5.70%; Q3, 5.71–7.01%; Q4, ≥ 7.02%. The hazard ratios for developing AF were estimated using a Cox proportional hazards model. During the follow-up period, 134 participants developed new-onset AF. The crude incidence rates of AF increased significantly with higher CoV levels of home SBP: 2.1, 4.9, 5.2, and 8.8 per 1000 person-years in the first, second, third, and fourth quartiles, respectively (P for trend &lt; 0.01). After adjusting for potential confounders, increased CoV levels of home SBP were associated significantly with a higher risk of AF (P for trend = 0.02). The participants in the highest quartile of CoV had a 2.20-fold (95% confidence intervals: 1.18–4.08) increased risk of developing AF compared with those in the lowest quartile.

Conclusion
The present findings suggest that increased day-to-day home BPV levels are associated with a higher risk of the development of AF in a general Japanese population.