bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vitamin K antagonist versus novel oral anticoagulants for management of cervical artery dissection: Interactive systematic review and meta-analysis
Authors: Essibayi Muhammed Amir , Lanzino Giuseppe , Keser Zafer 
Published: July 2022

Purpose: Cervical artery dissection (CAD) represents a unique clinical entity with a high risk of ischemic stroke. Vitamin K antagonists (VKA) showed good efficacy in CAD management but are cumbersome to use with potentially higher bleeding rates. Novel oral anticoagulants (NOAC) are easier to use and may have similar effects but lower hemorrhagic risk. In this systematic review, we compare the efficacy of NOAC to VKA as a potential alternative treatment. Methods: The literature was searched on Pubmed, PMC, and Embase via API through the Nested Knowledge AutoLit software in February 2022 for studies evaluating both NOAC and VKA. Baseline characteristics, clinical and radiographic outcomes, and hemorrhagic and ischemic complications were collected for single and double-arm studies and analyzed using random-effect subgroup meta-analysis. Findings: Overall, 11 studies were included with 699 patients treated with VKA and 53 treated with NOAC (from three studies; two were head-to-head comparative studies). There was no statistical difference in the baseline characteristics of VKA and NOAC patients. The rates of TIA/stroke in VKA and NOAC groups were 12.3% (95% CI; 0%, 28.6%) and 5.7% (95% CI; 0%, 12.2%), respectively. Major bleeding or intracranial bleeding were comparable between groups. Lesions treated with VKA showed angiographic recanalization with a rate of 51.4% (95% CI; 35.6%, 67.1%) and for those treated with NOAC was 58.4% (95% CI; 23.9%, 93.9%). The rates of good clinical outcomes were 79.9% (95% CI; 67.6%, 92.2%) in the VKA group and 91.4% (95% CI; 78.1%, 100%) in NOAC. No statistical difference was noted among any of the outcomes between the two treatment groups. Discussion and conclusion: We highlighted comparable efficacy and safety of NOAC to VKA for stroke prevention in CAD. Further head-to-head studies are warranted to validate these results.
Translation of cytoplasmic UBA1 contributes to VEXAS syndrome pathogenesis
Authors: Ferrada Marcela A. , Savic Sinisa , Cardona Daniela Ospina , Collins Jason C. , Alessi Hugh , Gutierrez-Rodrigues Fernanda , Kumar Dinesh Babu Uthaya , Wilson Lorena , Goodspeed Wendy , Topilow James S. , Paik Julie J. , Poulter James A. , Kermani Tanaz A. , Koster Matthew J. , Warrington Kenneth J. , Cargo Catherine , Tattersall Rachel S. , Duncan Christopher J. A. , Cantor Anna , Hoffmann Patrycja , Payne Elspeth M. , Bonnekoh Hanna , Krause Karoline , Cowen Edward W. , Calvo Katherine R. , Patel Bhavisha A. , Ombrello Amanda K. , Kastner Daniel L. , Young Neal S. , Werner Achim , Grayson Peter C. , Beck David B. 
Published: July 2022

AbstractSomatic mutations in UBA1 cause vacuoles, E1 ubiquitin-activating enzyme, X-linked, autoinflammatory somatic (VEXAS) syndrome, an adult-onset inflammatory disease with an overlap of hematologic manifestations. VEXAS syndrome is characterized by a high mortality rate and significant clinical heterogeneity. We sought to determine independent predictors of survival in VEXAS and to understand the mechanistic basis for these factors. We analyzed 83 patients with somatic pathogenic variants in UBA1 at p.Met41 (p.Met41Leu/Thr/Val), the start codon for translation of the cytoplasmic isoform of UBA1 (UBA1b). Patients with the p.Met41Val genotype were most likely to have an undifferentiated inflammatory syndrome. Multivariate analysis showed ear chondritis was associated with increased survival, whereas transfusion dependence and the p.Met41Val variant were independently associated with decreased survival. Using in vitro models and patient-derived cells, we demonstrate that p.Met41Val variant supports less UBA1b translation than either p.Met41Leu or p.Met41Thr, providing a molecular rationale for decreased survival. In addition, we show that these 3 canonical VEXAS variants produce more UBA1b than any of the 6 other possible single-nucleotide variants within this codon. Finally, we report a patient, clinically diagnosed with VEXAS syndrome, with 2 novel mutations in UBA1 occurring in cis on the same allele. One mutation (c.121 A&gt;T; p.Met41Leu) caused severely reduced translation of UBA1b in a reporter assay, but coexpression with the second mutation (c.119 G&gt;C; p.Gly40Ala) rescued UBA1b levels to those of canonical mutations. We conclude that regulation of residual UBA1b translation is fundamental to the pathogenesis of VEXAS syndrome and contributes to disease prognosis.
Protective role of trametenolic acid B against sevoflurane-induced cognitive impairments by its different regulatory modalities of mir-329-3p in neurons and microglia
Authors: Chen Jun , Feng Shuo , Li Linyan , Qiu Shujie , Jin Yanwu , Sun Yingui 
Published: July 2022

Abstract
Background
Postoperative cognitive dysfunction induced by anesthetics commonly occurs in elderly patients. This study aimed to evaluate the protective role of trametenolic acid B (TAB) in sevoflurane-induced cognitive impairments, and explore the underlying mechanisms.

Methods
Animal and cell experiments were performed in rats, differentiated PC12 and HAPI cells by exposing to 2% sevoflurane for 5 h. Different concentration (20, 40 and 80 µg/mL) of TAB was administrated in rats and cells. The cognitive function of rats was evaluated using the Morris water maze test and fear conditioning test. The cell proliferation and apoptosis were investigated using a CCK-8 assay and the flow cytometry. Pro-inflammatory cytokines in microglia were measured using ELISA kits. A miRNA microarray assay was conducted to screen differentially expressed miRNAs by TAB in both PC12 and HAPI cells. The luciferase reporter assay and western blot assay were used to assess the E2F1/CCNA2 and NF-κB pathways.

Results
TAB significantly alleviated sevoflurane-induced cognitive impairments in rats, improved PC12 cell viability, and inhibited the neuroinflammation of HAPI cells. miR-329-3p was downregulated in PC12 cells but upregulated in HAPI cells by TAB treatment, which mediated the effects of TAB on neurotoxicity and neuroinflammation. E2F1 and NF-κB P65 were two targets of miR-329-3p, and the E2F1/CCNA2 and NF-κB pathways were inhibited by miR-329-3p in PC12 and HAPI cells, respectively.

Conclusions
All the results provide evidence for the protective role of TAB against sevoflurane-induced cognitive impairments, which was achieved by alleviating neurotoxicity and neuroinflammation through differentially regulating miR-329-3p in neurons and microglia.
Assessment of deep learning and transfer learning for cancer prediction based on gene expression data
Authors: Hanczar Blaise , Bourgeais Victoria , Zehraoui Farida 
Published: July 2022

Abstract
Background
Machine learning is now a standard tool for cancer prediction based on gene expression data. However, deep learning is still new for this task, and there is no clear consensus about its performance and utility. Few experimental works have evaluated deep neural networks and compared them with state-of-the-art machine learning. Moreover, their conclusions are not consistent.

Results
We extensively evaluate the deep learning approach on 22 cancer prediction tasks based on gene expression data. We measure the impact of the main hyper-parameters and compare the performances of neural networks with the state-of-the-art. We also investigate the effectiveness of several transfer learning schemes in different experimental setups.

Conclusion
Based on our experimentations, we provide several recommendations to optimize the construction and training of a neural network model. We show that neural networks outperform the state-of-the-art methods only for very large training set size. For a small training set, we show that transfer learning is possible and may strongly improve the model performance in some cases.
Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts
Authors: Segura-Bedmar Isabel , Camino-Perdones David , Guerrero-Aspizua Sara 
Published: July 2022

AbstractBackground and objectiveAlthough rare diseases are characterized by low prevalence, approximately 400 million people are affected by a rare disease. The early and accurate diagnosis of these conditions is a major challenge for general practitioners, who do not have enough knowledge to identify them. In addition to this, rare diseases usually show a wide variety of manifestations, which might make the diagnosis even more difficult. A delayed diagnosis can negatively affect the patient’s life. Therefore, there is an urgent need to increase the scientific and medical knowledge about rare diseases. Natural Language Processing (NLP) and Deep Learning can help to extract relevant information about rare diseases to facilitate their diagnosis and treatments.MethodsThe paper explores several deep learning techniques such as Bidirectional Long Short Term Memory (BiLSTM) networks or deep contextualized word representations based on Bidirectional Encoder Representations from Transformers (BERT) to recognize rare diseases and their clinical manifestations (signs and symptoms).ResultsBioBERT, a domain-specific language representation based on BERT and trained on biomedical corpora, obtains the best results with an F1 of 85.2% for rare diseases. Since many signs are usually described by complex noun phrases that involve the use of use of overlapped, nested and discontinuous entities, the model provides lower results with an F1 of 57.2%.ConclusionsWhile our results are promising, there is still much room for improvement, especially with respect to the identification of clinical manifestations (signs and symptoms).
A retrospective analysis of maternal complications and newborn outcomes of general anesthesia for cesarean delivery in a single tertiary hospital in China
Authors: Bao Yang , Zhang Ting , Li Ling , Zhou Changqing , Liang Minxian , Zhou Jie , Wang Chunling 
Published: July 2022

Abstract
Background
Either neuraxial anesthesia or general anesthesia can be performed for cesarean delivery. Generally, neuraxial anesthesia is the first choice with the risk and benefit balance for both the mother and fetus. However, general anesthesia is also applicable most commonly in the emergent setting. This study analyzed maternal complications associated with general anesthesia for cesarean delivery and suggested lowering pregnancy-related maternal and newborn adverse outcomes.

Methods
With the approval of the Institutional Ethics Review Board (No: 2017016), data on cesarean delivery and related anesthesia were collected from the Electronic Health Record System from 1/1/2013 to 12/31/2016. Statistical software STATA version 15.1 was used for data analyses. All statistical tests were two-sided, and a level significance of 0.05 was assumed.

Results
The rate of general anesthesia for cesarean delivery increased steadily during 2013–2016, 3.71% in 2013 to 10.23% in 2016 (p < 0.001). Repeat cesarean delivery among general anesthesia group increased significantly from 16.22% in 2013 to 54.14% in 2016 (p < 0.001). Morbidly adherent placenta (MAP) was the first reason among pregnancy-related complications, which accounted for 33% in total in general anesthesia group (38% in 2013 to 44% in 2016). The laryngeal mask airway (LMA) was used in airway management, and the proportion of LMA increased from 28.38% in 2013 to 92.99% in 2016 (p < 0.001). There were significant differences in newborn outcomes between general anesthesia and neuraxial anesthesia groups, including newborn weight, newborn Apgar score at 1 min and 5 min and newborn admission to the NICU (p < 0.001).

Conclusions
The growing incidence of general anesthesia was consistent with the trend of rising repeat cesarean delivery and MAP. low newborn Apgar score and high newborn admission to the NICU in general anesthesia group compared with neuraxial anesthesia group. The LMA was performed safely for airway management with enough fasting and careful gastric volume evaluation.
Assessing equity and quality indicators for older people – Adaptation and validation of the Assessing Care of Vulnerable Elders (ACOVE) checklist for the Portuguese care context
Authors: Taveira Adriana , Macedo Ana Paula , Rego Nazaré , Crispim José 
Published: July 2022

Abstract
Background
Development has promoted longer and healthier lives, but the rise in the proportion of older adults poses new challenges to health systems. Susceptibilities of older persons resulting from lower knowledge about services availability, health illiteracy, lower income, higher mental decline, or physical limitations need to be identified and monitored to assure the equity and quality of health care. The aim of this study was to develop equity indicators for the Assessing Care of Vulnerable Elders (ACOVE)-3 checklist and perform the first cross-cultural adaptation and validation of this checklist into Portuguese.

Methods
A scoping literature review of determinants or indicators of health (in)equity in the care of older people was performed. A total of 5 language experts and 18 health professionals were involved in the development and validation of the equity and quality indicators through expert opinion and focus groups. Data collected from focus groups was analyzed through directed or conventional content analysis. The usefulness of the indicators was assessed by analyzing the clinical records of 30 patients.

Results
The literature review revealed that there was a worldwide gap concerning equity indicators for older people primary health care. A structured and complete checklist composed of equity and quality indicators was obtained, validated and assessed. A significant number of non-screened quality or equity related potential occurrences that could have been avoided if the proposed indicators were implemented were detected. The percentage of non-registered indicators was 76.6% for quality and 96.7% for equity.

Conclusions
Applying the proposed checklist will contribute to improve the monitoring of the clinical situation of vulnerable older people and the planning of medical and social actions directed at this group.
A predictive model for recurrence after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma (PDAC) by using preoperative clinical data and CT characteristics
Authors: Tian Ningzi , Wu Dong , Zhu Lei , Zeng Mengsu , Li Jianke , Wang Xiaolin 
Published: July 2022

Abstract
Background
The overall survival for patients with resectable PDAC following curative surgical resection hasn’t been improved significantly, as a considerable proportion of patients develop recurrence within a year. The purpose of this study was to develop and validate a predictive model to assess recurrence risk in patients with PDAC after upfront surgery by using preoperative clinical data and CT characteristics.

Methods
The predictive model was developed based on a retrospective set of 141 pancreatic cancer patients after surgery. A separate set of 77 patients was used to validate model. Between January 2017 and December 2019, all patients underwent multidetector pancreatic CT and upfront surgery. Univariable and multivariate Cox regression was used to determine the risk factors related to recurrence and then establish a nomogram to estimate the 1-year recurrence probability. The Harrell C-index was employed in evaluating the discrimination and calibration of the model.

Results
A total of 218 patients in this retrospective cohort. A recurrence model in nomogram form was developed with predictors including tumor size (hazard ratio [HR], 1.277; 95% CI 1.098, 1.495; P = 0.002), tumor density in the portal vein phase (HR, 0.598; 95% CI 0.424, 0.844; P = 0.003), peripancreatic infiltration (HR, 4.151; 95% CI 2.077, 8.298; P < 0.001), suspicious metastatic lymph node (HR, 2.561; 95% CI 1.653, 3.967; P < 0.001), Neutrophils/Lymphocytes ratio (HR, 1.111; 95% CI 1.016, 1.215; P = 0.020). The predictive nomogram had good discrimination capability with these predictors with an area under curve at 1 year of 0.84 (95%CI 0.77, 0.91) in the development set and 0.82 (95% CI 0.72, 0.92) and 0.84 (95% CI 0.74, 0.94) in the validation set for two radiologists reading respectively.

Conclusions
The model developed based on preoperative clinical data and CT characteristics of resectable pancreatic ductal adenocarcinoma patients, which can helpfully estimate the recurrence-free survival. It may be a useful tool for clinician to select optimal candidates for upfront surgery or neoadjuvant therapy.
A systematic review of health sciences students’ online learning during the COVID-19 pandemic
Authors: Abdull Mutalib Abdull Assyaqireen , Md. Akim Abdah , Jaafar Mohamad Hasif 
Published: July 2022

AbstractBackgroundThis study aims to analyse the effectiveness of distance learning during the COVID-19 pandemic among undergraduate health sciences students using systematic review. Online learning has been chosen as the best approach to continue offering education in this pandemic era. Method: The screening process was done using Scopus, ScienceDirect and PubMed based on the eligibility criteria. Out of 1486 studies, 1269 were screened. A total of 64 eligible studies obtained were included in the quantitative analysis. Results were categorized into i) student attitudes (perceptions/satisfactions/engagements), and ii) student learning outcomes, and compared to the Kirkpatrick model.ResultsAlthough facing difficulties, 50% of the studies was moderately satisfied with distance learning, while 36% was highly satisfied and 17% dissatisfied. Most studies (26%) reported flexibility in online learning. Internet issues (19%) and low interaction between learners and instructors (19%) were the most prevalent problems mentioned. Online education engages students better than traditional learning. The learning outcome was assessed using two categories: i) academic performance and ii) skill development. Most studies (72%) stated that online learning improves academic performance, 14% reported a drop, and 14% stated no effect, while an increase in clinical skills and communication skills were reported. Kirkpatrick evaluation revealed 80% of the studies obtained was evaluated at level 1 (reaction), 8% at level 2 (learning), 12% at level 3 (behaviour) and none at level 4 (results).ConclusionOverall, this systematic review found that the online learning performed better than expected during COVID-19, but the data gained is insufficient to say it is beneficial when compared to other types of teaching approaches.
Autonomous modeling of repetitive movement for rehabilitation exercise monitoring
Authors: Jatesiktat Prayook , Lim Guan Ming , Kuah Christopher Wee Keong , Anopas Dollaporn , Ang Wei Tech 
Published: July 2022

Abstract
Background
Insightful feedback generation for daily home-based stroke rehabilitation is currently unavailable due to the inefficiency of exercise inspection done by therapists. We aim to produce a compact anomaly representation that allows a therapist to pay attention to only a few specific sections in a long exercise session record and boost their efficiency in feedback generation.

Methods
This study proposes a data-driven technique to model a repetitive exercise using unsupervised phase learning on an artificial neural network and statistical learning on principal component analysis (PCA). After a model is built on a set of normal healthy movements, the model can be used to extract a sequence of anomaly scores from a movement of the same prescription.

Results
The method not only works on a standard marker-based motion capture system but also performs well on a more compact and affordable motion capture system based-on Kinect V2 and wrist-worn inertial measurement units that can be used at home. An evaluation of four different exercises shows its potential in separating anomalous movements from normal ones with an average area under the curve (AUC) of 0.9872 even on the compact motion capture system.

Conclusions
The proposed processing technique has the potential to help clinicians in providing high-quality feedback for telerehabilitation in a more scalable way.
Dengue and COVID-19: two sides of the same coin
Authors: Malavige Gathsaurie Neelika , Jeewandara Chandima , Ogg Graham S. 
Published: July 2022

Abstract
Background
Many countries in Asia and Latin America are currently facing a double burden of outbreaks due to dengue and COVID-19. Here we discuss the similarities and differences between the two infections so that lessons learnt so far from studying both infections will be helpful in further understanding their immunopathogenesis and to develop therapeutic interventions.

Main body
Although the entry routes of the SARS-CoV-2 and the dengue virus (DENV) are different, both infections result in a systemic infection, with some similar clinical presentations such as fever, headache, myalgia and gastrointestinal symptoms. However, while dengue is usually associated with a tendency to bleed, development of micro and macrothrombi is a hallmark of severe COVID-19. Apart from the initial similarities in the clinical presentation, there are further similarities between such as risk factors for development of severe illness, cytokine storms, endothelial dysfunction and multi-organ failure. Both infections are characterised by a delayed and impaired type I IFN response and a proinflammatory immune response. Furthermore, while high levels of potent neutralising antibodies are associated with protection, poorly neutralising and cross-reactive antibodies have been proposed to lead to immunopathology by different mechanisms, associated with an exaggerated plasmablast response. The virus specific T cell responses are also shown to be delayed in those who develop severe illness, while varying degrees of endothelial dysfunction leads to increased vascular permeability and coagulation abnormalities.

Conclusion
While there are many similarities between dengue and SARS-CoV-2 infection, there are also key differences especially in long-term disease sequelae. Therefore, it would be important to study the parallels between the immunopathogenesis of both infections for development of more effective vaccines and therapeutic interventions.