bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oxidative damage in the gastrocnemius predicts long-term survival in patients with peripheral artery disease
Authors: Koutakis Panagiotis , Hernandez Hernan , Miserlis Dimitrios , Thompson Jonathan R. , Papoutsi Evlampia , Mietus Constance J. , Haynatzki Gleb , Kim Julian K. , Casale George P. , Pipinos Iraklis I. 
Published: April 2024

AbstractPatients with peripheral artery disease (PAD) have increased mortality rates and a myopathy in their affected legs which is characterized by increased oxidative damage, reduced antioxidant enzymatic activity and defective mitochondrial bioenergetics. This study evaluated the hypothesis that increased levels of oxidative damage in gastrocnemius biopsies from patients with PAD predict long-term mortality rates. Oxidative damage was quantified as carbonyl adducts in myofibers of the gastrocnemius of PAD patients. The oxidative stress data were grouped into tertiles and the 5-year, all-cause mortality for each tertile was determined by Kaplan-Meier curves and compared by the Modified Peto test. A Cox-regression model was used to control the effects of clinical characteristics. Results were adjusted for age, sex, race, body mass index, ankle-brachial index, smoking, physical activity, and comorbidities. Of the 240 study participants, 99 died during a mean follow up of 37.8 months. Patients in the highest tertile of oxidative damage demonstrated the highest 5-year mortality rate. The mortality hazard ratios (HR) from the Cox analysis were statistically significant for oxidative damage (lowest vs middle tertile; HR = 6.33; p = 0.0001 and lowest vs highest; HR = 8.37; p < 0.0001). Survival analysis of a contemporaneous population of PAD patients identifies abundance of carbonyl adducts in myofibers of their gastrocnemius as a predictor of mortality rate independently of ankle-brachial index, disease stage and other clinical and myopathy-related covariates.
Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs
Authors: O’Leary Kevin , Zheng Deyou 
Published: April 2024

AbstractBy profiling gene expression in individual cells, single-cell RNA-sequencing (scRNA-seq) can resolve cellular heterogeneity and cell-type gene expression dynamics. Its application to time-series samples can identify temporal gene programs active in different cell types, for example, immune cells’ responses to viral infection. However, current scRNA-seq analysis has limitations. One is the low number of genes detected per cell. The second is insufficient replicates (often 1-2) due to high experimental cost. The third lies in the data analysis—treating individual cells as independent measurements leads to inflated statistics. To address these, we explore a new computational framework, specifically whether “metacells” constructed to maintain cellular heterogeneity within individual cell types (or clusters) can be used as “replicates” for increasing statistical rigor. Toward this, we applied SEACells to a time-series scRNA-seq dataset from peripheral blood mononuclear cells (PBMCs) after SARS-CoV-2 infection to construct metacells, and used them in maSigPro for quadratic regression to find significantly differentially expressed genes (DEGs) over time, followed by clustering expression velocity trends. We showed that such metacells retained greater expression variances and produced more biologically meaningful DEGs compared to either metacells generated randomly or from simple pseudobulk methods. More specifically, this approach correctly identified the known ISG15 interferon response program in almost all PBMC cell types and many DEGs enriched in the previously defined SARS-CoV-2 infection response pathway. It also uncovered additional and more cell type-specific temporal gene expression programs. Overall, our results demonstrate that the metacell-pseudoreplicate strategy could potentially overcome the limitation of 1-2 replicates.
Exploring the correlation and causation between alpha oscillations and one-second time perception through EEG and tACS
Authors: Mokhtarinejad Ehsan , Tavakoli Mahgol , Ghaderi Amir Hossein 
Published: April 2024

AbstractAlpha oscillations have been implicated in time perception, yet a consensus on their precise role remains elusive. This study directly investigates this relationship by examining the impact of alpha oscillations on time perception. Resting-state EEG recordings were used to extract peak alpha frequency (PAF) and peak alpha power (PAP) characteristics. Participants then performed a time generalization task under transcranial alternating current stimulation (tACS) at frequencies of PAF−2, PAF, and PAF+2, as well as a sham condition. Results revealed a significant correlation between PAP and accuracy, and between PAF and precision of one-second time perception in the sham condition. This suggests that alpha oscillations may influence one-second time perception by modulating their frequency and power. Interestingly, these correlations weakened with real tACS stimulations, particularly at higher frequencies. A second analysis aimed to establish a causal relationship between alpha peak modulation by tACS and time perception using repeated measures ANOVAs, but no significant effect was observed. Results were interpreted according to the state-dependent networks and internal clock model.
Use of artificial intelligence to develop predictive algorithms of cough and PCR-confirmed COVID-19 infections based on inputs from clinical-grade wearable sensors
Authors: Walter Jessica R. , Lee Jong Yoon , Yu Lian , Kim Brandon , Martell Knute , Opdycke Anita , Scheffel Jenny , Felsl Ingrid , Patel Soham , Rangel Stephanie , Serao Alexa , Edel Claire , Bharat Ankit , Xu Shuai 
Published: April 2024

AbstractThere have been over 769 million cases of COVID-19, and up to 50% of infected individuals are asymptomatic. The purpose of this study aimed to assess the use of a clinical-grade physiological wearable monitoring system, ANNE One, to develop an artificial intelligence algorithm for (1) cough detection and (2) early detection of COVID-19, through the retrospective analysis of prospectively collected physiological data from longitudinal wear of ANNE sensors in a multicenter single arm study of subjects at high risk for COVID-19 due to occupational or home exposures. The study employed a two-fold approach: cough detection algorithm development and COVID-19 detection algorithm development. For cough detection, healthy individuals wore an ANNE One chest sensor during scripted activity. The final performance of the algorithm achieved an F-1 score of 83.3% in twenty-seven healthy subjects during biomarker validation. In the COVID-19 detection algorithm, individuals at high-risk for developing COVID-19 because of recent exposures received ANNE One sensors and completed daily symptom surveys. An algorithm analyzing vital parameters (heart rate, respiratory rate, cough count, etc.) for early COVID-19 detection was developed. The COVID-19 detection algorithm exhibited a sensitivity of 0.47 and specificity of 0.72 for detecting COVID-19 in 325 individuals with recent exposures. Participants demonstrated high adherence (≥ 4 days of wear per week). ANNE One shows promise for detection of COVID-19. Inclusion of respiratory biomarkers (e.g., cough count) enhanced the algorithm's predictive ability. These findings highlight the potential value of wearable devices in early disease detection and monitoring.
An enhanced real-time human pose estimation method based on modified YOLOv8 framework
Authors: Dong Chengang , Du Guodong 
Published: April 2024

AbstractThe objective of human pose estimation (HPE) derived from deep learning aims to accurately estimate and predict the human body posture in images or videos via the utilization of deep neural networks. However, the accuracy of real-time HPE tasks is still to be improved due to factors such as partial occlusion of body parts and limited receptive field of the model. To alleviate the accuracy loss caused by these issues, this paper proposes a real-time HPE model called $${\textbf {CCAM-Person}}$$

CCAM
-
Person

based on the YOLOv8 framework. Specifically, we have improved the backbone and neck of the YOLOv8x-pose real-time HPE model to alleviate the feature loss and receptive field constraints. Secondly, we introduce the context coordinate attention module (CCAM) to augment the model’s focus on salient features, reduce background noise interference, alleviate key point regression failure caused by limb occlusion, and improve the accuracy of pose estimation. Our approach attains competitive results on multiple metrics of two open-source datasets, MS COCO 2017 and CrowdPose. Compared with the baseline model YOLOv8x-pose, CCAM-Person improves the average precision by 2.8% and 3.5% on the two datasets, respectively.
ALBI score combined with FIB-4 index to predict post-hepatectomy liver failure in patients with hepatocellular carcinoma
Authors: Tian Yi-Bo , Niu Hong , Xu Feng , Shang-Guan Peng-Wei , Song Wei-Wei 
Published: April 2024

AbstractPost-hepatectomy liver failure (PHLF) is a potentially life-threatening complication following liver resection. Hepatocellular carcinoma (HCC) often occurs in patients with chronic liver disease, which increases the risk of PHLF. This study aimed to investigate the ability of the combination of liver function and fibrosis markers (ALBI score and FIB-4 index) to predict PHLF in patients with HCC. Patients who underwent hepatectomy for HCC between August 2012 and September 2022 were considered for inclusion. Multivariable logistic regression analysis was used to identify factors associated with PHLF, and ALBI score and FIB-4 index were combined based on their regression coefficients. The performance of the combined ALBI-FIB4 score in predicting PHLF and postoperative mortality was compared with Child–Pugh score, MELD score, ALBI score, and FIB-4 index. A total of 215 patients were enrolled in this study. PHLF occurred in 35 patients (16.3%). The incidence of severe PHLF (grade B and grade C PHLF) was 9.3%. Postoperative 90‐d mortality was 2.8%. ALBI score, FIB-4 index, prothrombin time, and extent of liver resection were identified as independent factors for predicting PHLF. The AUC of the ALBI-FIB4 score in predicting PHLF was 0.783(95%CI: 0.694–0.872), higher than other models. The ALBI-FIB4 score could divide patients into two risk groups based on a cut-off value of − 1.82. High-risk patients had a high incidence of PHLF of 39.1%, while PHLF just occurred in 6.6% of low-risk patients. Similarly, the AUCs of the ALBI-FIB4 score in predicting severe PHLF and postoperative 90-d mortality were also higher than other models. Preoperative ALBI-FIB4 score showed good performance in predicting PHLF and postoperative mortality in patients undergoing hepatectomy for HCC, superior to the currently commonly used liver function and fibrosis scoring systems.
Advanced disk herniation computer aided diagnosis system
Authors: Ebrahim Maad , Alsmirat Mohammad , Al-Ayyoub Mahmoud 
Published: April 2024

AbstractOver recent years, researchers and practitioners have encountered massive and continuous improvements in the computational resources available for their use. This allowed the use of resource-hungry Machine learning (ML) algorithms to become feasible and practical. Moreover, several advanced techniques are being used to boost the performance of such algorithms even further, which include various transfer learning techniques, data augmentation, and feature concatenation. Normally, the use of these advanced techniques highly depends on the size and nature of the dataset being used. In the case of fine-grained medical image sets, which have subcategories within the main categories in the image set, there is a need to find the combination of the techniques that work the best on these types of images. In this work, we utilize these advanced techniques to find the best combinations to build a state-of-the-art lumber disc herniation computer-aided diagnosis system. We have evaluated the system extensively and the results show that the diagnosis system achieves an accuracy of 98% when it is compared with human diagnosis.
Association and mediation analyses among multiple metal exposure, mineralocorticoid levels, and serum ion balance in residents of northwest China
Authors: Zhang Honglong , Yan Jun , Nie Guole , Xie Danna , Zhu Xingwang , Niu Jingping , Li Xun 
Published: April 2024

AbstractToxic metals are vital risk factors affecting serum ion balance; however, the effect of their co-exposure on serum ions and the underlying mechanism remain unclear. We assessed the correlations of single metal and mixed metals with serum ion levels, and the mediating effects of mineralocorticoids by investigating toxic metal concentrations in the blood, as well as the levels of representative mineralocorticoids, such as deoxycorticosterone (DOC), and serum ions in 471 participants from the Dongdagou–Xinglong cohort. In the single-exposure model, sodium and chloride levels were positively correlated with arsenic, selenium, cadmium, and lead levels and negatively correlated with zinc levels, whereas potassium and iron levels and the anion gap were positively correlated with zinc levels and negatively correlated with selenium, cadmium and lead levels (all P < 0.05). Similar results were obtained in the mixed exposure models considering all metals, and the major contributions of cadmium, lead, arsenic, and selenium were highlighted. Significant dose–response relationships were detected between levels of serum DOC and toxic metals and serum ions. Mediation analysis showed that serum DOC partially mediated the relationship of metals (especially mixed metals) with serum iron and anion gap by 8.3% and 8.6%, respectively. These findings suggest that single and mixed metal exposure interferes with the homeostasis of serum mineralocorticoids, which is also related to altered serum ion levels. Furthermore, serum DOC may remarkably affect toxic metal-related serum ion disturbances, providing clues for further study of health risks associated with these toxic metals.
Effect of a nutraceutical combination on sleep quality among people with impaired sleep: a randomised, placebo-controlled trial
Authors: Gutiérrez-Romero Sebastián Antonio , Torres-Narváez Erika Sofía , Zamora-Gómez Adrián Camilo , Castillo-Castillo Silvana , Latorre-Velásquez Angela Liliana , Betancourt-Villamizar Carolina , Mendivil Carlos O. 
Published: April 2024

AbstractIn this randomised, placebo-controlled trial, adults with impaired sleep (Pittsburgh Sleep Quality Index ≥ 5) were randomly assigned using a minimization algorithm to receive a formulation containing l-theanine plus lemon balm, valerian, and saffron extracts, or placebo, during 6 weeks. Objective sleep quality parameters were measured using an actigraphy device. We enrolled and randomised 64 individuals, 31 from the active group and 27 from the placebo group completed the 6 week follow-up. Mean sleep efficiency remained unmodified in the active group, and increased by 3% in the placebo group, the between-group difference in the change was not statistically significant (p = 0.49). Total sleep time also improved more with placebo (13.0 vs. 1.33 min, p = 0.66). Time wake after sleep onset (WASO) decreased more in the active group (4.6% vs. 2.4%), but the difference was not significant (p = 0.33). Mean PSQI decreased by 3.11 points (32.3%) in the active group, and by 3.86 points (39.5%) in the placebo group (p = 0.41). SF-36 increased more with placebo (+ 18.3 in active, + 32.1 in placebo, p = 0.68). Salivary cortisol remained unchanged in both groups. No serious adverse events were reported. Among adults with impaired sleep, a nutraceutical combination did not improve objective or subjective sleep parameters more than a placebo infusion.
Development of a metasurface-based slot antenna for 5G MIMO applications with minimized cross-polarization and stable radiation patterns through mode manipulation
Authors: Hamlbar Gerami Hamed , Kazemi Robab , Fathy Aly E. 
Published: April 2024

AbstractThis paper presents an approach for designing metasurface antennas using the characteristic mode analysis method for 5G mm-wave multiple input–multiple output (MIMO) systems. The proposed metasurface antenna consists of a 3 × 3 array of modified patches with additional slits and stubs, which are fed by a coupling slot. This configuration reshapes surface currents and improves the radiation performance across a broad frequency range. The design offers significant advantages such as reduced antenna size, minimized influence of higher-order modes, and maintained low cross-polarization (XP) level. Experimental results demonstrate that the proposed metasurface-based slot antenna provides a bandwidth of 29.6% (23–31 GHz) with a return loss better than 10 dB. It achieves a peak gain of 9.43 dB and exhibits an XP level below − 26 dB and − 48 dB at $$\varphi = 0^{ \circ }$$

φ
=

0
∘

and $$\varphi = 90^{ \circ }$$

φ
=

90
∘

planes, respectively. The physical dimensions of the antenna are 0.9λ0 × 0.9λ0 × 0.08λ0, where λ0 is the free space wavelength at 27 GHz, resulting in an approximately 41% reduction compared to the conventional metasurface patch antenna. Moreover, the design proves to be well-suited for MIMO systems, enabling close placement of antenna elements without degrading their radiation patterns. The experimental results in 1 × 2 and 2 × 2 MIMO configurations represent that the isolation between antenna elements are better than 18 dB and 21 dB, respectively. The performance of the antennas remains stable in both configurations, effectively addressing concerns such as beam squint and eliminating the common issue of beam splitting observed in conventional metasurface MIMO antennas. Moreover, the envelope correlation coefficient value in both MIMO configurations is lower than 0.003. This significant advancement offers a promising solution for compact 5G mm-wave massive MIMO applications.
Microcrack monitoring and fracture evolution of coal and rock using integrated acoustic emission and digital image correlation techniques
Authors: Zhao Zhihui , Yang Jinhu , Kang Yueming , Xiao Yong 
Published: April 2024

AbstractThe mechanical properties of a coal–rock body were examined through uniaxial compression tests, and the rupture process of the coal–rock body was monitored in real time using a combined acoustic emission (AE) monitoring system and a digital image correlation (DIC) full-field strain measurement system. From a comparison of the mechanical properties of coal and sandstone, clear differences are apparent regarding the uniaxial compressive strength, deformation characteristics, and damage mode; the brittle failure characteristics of the coal samples are also more evident. The change in AE energy reflects the accumulation and release of elastic energy during the rupture process, and the evolution of AE localization points under different stress levels can effectively reflect rupture propagation. Further, the DIC full-field strain measurement method can quantitatively monitor the evolution of the displacement and strain fields at the marking point and surface simultaneously, thereby overcoming the limitations of traditional empirical and qualitative rupture processes. During monitoring, the AE focuses on the internal rupture of the specimen and the DIC focuses on the surface deformation. These complement each other and reflect the rupture process more comprehensively.
Scientific figures interpreted by ChatGPT: strengths in plot recognition and limits in color perception
Authors: Wang Jinge , Ye Qing , Liu Li , Guo Nancy Lan , Hu Gangqing 
Published: April 2024

AbstractEmerging studies underscore the promising capabilities of large language model-based chatbots in conducting basic bioinformatics data analyses. The recent feature of accepting image inputs by ChatGPT, also known as GPT-4V(ision), motivated us to explore its efficacy in deciphering bioinformatics scientific figures. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when color perception and quantitative analysis of visual elements were involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.
Deterministic entangling gates with nonlinear quantum photonic interferometers
Authors: Scala Francesco , Nigro Davide , Gerace Dario 
Published: April 2024

AbstractThe single-photon quantum computing paradigm currently relies on the multi-port interference in linear optical devices, which is intrinsically based on probabilistic measurements outcome, and thus non-deterministic. Devising a fully deterministic, universal, and practically achievable quantum computing platform based on single-photon encoding and integrated photonic circuits is still an open challenge. Here we propose to exploit the interplay of distributed self-Kerr nonlinearity and localized hopping in quantum photonic interferometers to implement deterministic entangling quantum gates with dual rail photonic qubits. It is shown that a universal set of single- and two-qubit gates can be designed by a suitable concatenation of few optical interferometric elements, reaching optimal fidelities arbitrarily close to 100% that are theoretically demonstrated through a bound constrained optimization algorithm. The actual realization would require the concatenation of a few tens of elementary operations, as well as on-chip optical nonlinearities that are compatible with some of the existing quantum photonic platforms, as it is finally discussed.
Reproducibility in research into metal-organic frameworks in nanomedicine
Authors: Forgan Ross S. 
Published: April 2024

AbstractMetal-organic frameworks (MOFs) are currently widely investigated for a number of potential biomedicinal applications, with particular focus on nanoscale drug delivery. Nanomedicine in general comes with specific challenges to ensure reproducibility of results, including batch-to-batch variations in ostensibly the same nanomaterial, differences in synthetic and analytical practices, intrinsic issues with in vitro culturing and assaying, and a lack of availability of raw data for comparative analysis. This perspective provides an overview of reproducibility issues in the context of MOFs in nanomedicine, covering their preparation and in vitro analysis. The commonly studied UiO-66 is used as an exemplar to highlight variability in synthetic and characterisation practices, as well as in the publication and availability of data. Some common roadblocks to reproducibility are highlighted, alongside suggestions and resources for best practice.