bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning
Authors: Khasawneh Natheer , Fraiwan Mohammad , Fraiwan Luay 
Published: November 2022

Abstract
Background
The electroencephalography (EEG) signal carries important information about the electrical activity of the brain, which may reveal many pathologies. This information is carried in certain waveforms and events, one of which is the K-complex. It is used by neurologists to diagnose neurophysiologic and cognitive disorders as well as sleep studies.
Existing detection methods largely depend on tedious, time-consuming, and error-prone manual inspection of the EEG waveform.

Methods
In this paper, a highly accurate K-complex detection system is developed. Based on multiple convolutional neural network (CNN) feature extraction backbones and EEG waveform images, a regions with faster regions with convolutional neural networks (Faster R-CNN) detector was designed, trained, and tested. Extensive performance evaluation was performed using four deep transfer learning feature extraction models (AlexNet, ResNet-101, VGG19 and Inceptionv3). The dataset was comprised of 10948 images of EEG waveforms, with the location of the K-complexes included as separate text files containing the bounding boxes information.

Results
The Inceptionv3 and VGG19-based detectors performed consistently high (i.e., up to 99.8% precision and 0.2% miss rate) over different testing scenarios, in which the number of training images was varied from 60% to 80% and the positive overlap threshold was increased from 60% to 90%.

Conclusions
Our automated method appears to be a highly accurate automatic K-complex detection in real-time that can aid practitioners in speedy EEG inspection.

Graphical Abstract
Cost-effectiveness analysis of sintilimab plus bevacizumab biosimilar compared with lenvatinib as the first-line treatment of unresectable or metastatic hepatocellular carcinoma
Authors: Zhou Ting , Wang Xintian , Cao Yingdan , Yang Lan , Wang Zijing , Ma Aixia , Li Hongchao 
Published: November 2022

Abstract
Background
In recent years, programmed cell death protein-1 inhibitors, including sintilimab, have significantly prolonged the overall survival time of patients with unresectable or metastatic hepatocellular carcinoma (HCC); however, the cost-effectiveness of sintilimab is unclear. The aim of this study was to assess the cost-effectiveness of sintilimab plus bevacizumab biosimilar compared with lenvatinib as first-line treatment in patients with unresectable or metastatic HCC.

Methods
A lifetime partitioned survival model was developed to conduct a cost-effectiveness analysis of sintilimab plus bevacizumab biosimilar vs. lenvatinib for advanced HCC from a Chinese healthcare system perspective. The clinical and safety data were derived from two recent randomized clinical trials, the ORIENT-32 and REFLECT studies. Utility data were obtained from previous studies. Long-term direct medical costs and quality-adjusted life-years (QALYs) were predicted. Deterministic and probabilistic sensitivity analyses were performed to verify the robustness of the model.

Results
Compared with lenvatinib, combination therapy with sintilimab and bevacizumab biosimilar yielded an additional 0.493 QALYs at a higher cost ($33,102 vs. $21,037) (2021 US dollars). This resulted in a deterministic incremental cost-effectiveness ratio (ICER) of $24,462 per QALY in the base-case analysis. The ICERs were sensitive to the utility of post-progression and the cost of bevacizumab biosimilar. A lower ICER was estimated when the dose of bevacizumab biosimilar decreased from 15 mg to 7.5 mg per kilogram in the scenario analysis. In the probabilistic sensitivity analysis, the probability of being cost-effective for sintilimab treatment at willingness-to-pay (WTP) thresholds of one ($12,516) and three times the gross domestic product per capita in China ($37,547) were 11.6% and 88.6%, respectively.

Conclusion
Sintilimab plus bevacizumab biosimilar is likely to be a cost-effective treatment option as a first-line treatment for unresectable or metastatic HCC in China when WTP threshold is over $23,650.
Impact of mental disorders on the risk of atrial fibrillation in patients with diabetes mellitus: a nationwide population-based study
Authors: Bae Nan Young , Lee So-Ryoung , Choi Eue-Keun , Ahn Hyun Jin , Ahn Hyo-Jeong , Kwon Soonil , Han Kyung-Do , Lee Kyu-Na , Oh Seil , Lip Gregory Y. H. 
Published: November 2022

Abstract
Background
It is unclear whether mental disorders are an independent risk factor for atrial fibrillation (AF) in patients with diabetes. We aimed to investigate whether patients with diabetes who have mental disorders have an increased risk for AF.

Methods
Using the Korea National Health Insurance Service database, we enrolled 2,512,690 patients diagnosed with diabetes without AF between 2009 and 2012. We assessed five mental disorders: depression, insomnia, anxiety, bipolar disorder, and schizophrenia. Newly diagnosed AF was identified during the follow-up period, and multivariate Cox regression analysis was performed.

Results
Among the 2,512,690 patients (mean age 57.2 ± 12.3 years; 60.1% men), 828,929 (33.0%) had mental disorders. Among the five mental disorders, anxiety (68.1%) was the most common, followed by insomnia (40.0%). During a median follow-up duration of 7.1 years, new-onset AF was diagnosed in 79,525 patients (4.66 per 1,000 person-years). Patients with diabetes who had mental disorders showed a higher risk for AF (adjusted hazard ratio [HR] 1.19; 95% confidence interval [CI] 1.17–1.21; p-value < 0.001). Depression, insomnia, and anxiety were significantly associated with higher risk for AF (adjusted HR [95% CI]: 1.15 [1.12–1.17], 1.15 [1.13–1.18], and 1.19 [1.67–1.21], respectively; all p-values < 0.001), whereas bipolar disorder and schizophrenia were not.

Conclusions
Mental disorders, especially depression, insomnia, and anxiety, were associated with an increased risk for AF in patients with diabetes. Greater awareness with a prompt diagnosis of AF should be considered for patients with both DM and mental disorders.
Association of triglyceride-glucose index with ischemic stroke recurrence in nondiabetic patients with small vessel occlusion: a multicenter hospital-based prospective cohort study
Authors: Wu Li , Zhu Jinmao , Li Chenghao , Zhu Juehua , Dai Zheng , Jiang Yongjun 
Published: November 2022

Abstract
Background
Triglyceride-glucose (TyG) index is a simple and reliable surrogate marker of insulin resistance. Elevated TyG index was related to stroke recurrence. This study aimed to explore the associations between TyG index with ischemic stroke recurrence in nondiabetic patients with small vessel occlusion.

Methods
From November 1, 2016 to February 28, 2021, consecutive acute ischemic stroke patients admitted within 1 week after onset were screened. The stroke mechanism was determined based on medical history, laboratory examinations, cardiac examinations, vascular examinations and neuroimaging. Nondiabetic patients with small vessel occlusion were enrolled and followed up for 1 year. The primary outcome was ischemic stroke recurrence. Logistic regression and Kaplan–Meier survival curve were used to analyze the association of the TyG index and stroke recurrence.

Results
A total of 6100 acute ischemic stroke patients were screened, with 1970 nondiabetic patients with small vessel occlusion included and divided into 4 groups according to the TyG index quartiles (Q1: < 8.20; Q2: 8.20–8.53; Q3: 8.54–8.92; Q4: > 8.92). There were significant differences in age, body mass index, systolic blood pression, diastolic blood pressure, lipid-lowering agents, infarct location, fasting blood glucose, total cholesterol, triglyceride, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, uric acid, and stroke recurrence among the 4 groups. In the multi-adjusted models, compared to Q1 of the TyG index, the odds ratio for Q4 of the TyG index for stroke recurrence was 3.100 (1.366–8.019). The Kaplan–Meier survival (ischemic stroke-free) curves by quartiles of the TyG index also showed statistically significant differences (log-rank test, P = 0.004).

Conclusions
Our findings suggested that the TyG index was associated with ischemic stroke recurrence in nondiabetic patients with small vessel occlusion, and it could be a valuable biomarker for assessing the risk of ischemic stroke recurrence in these patients.
Status of the health information system in Ireland and its fitness to support health system performance assessment: a multimethod assessment based on stakeholder involvement
Authors: Ivanković Damir , Jansen Tessa , Barbazza Erica , Fernandes Óscar Brito , Klazinga Niek , Kringos Dionne 
Published: November 2022

Abstract
Background
Between 2019 and 2021, the first Irish health system performance assessment (HSPA) framework was developed. As routinely collected health data are necessary to continuously populate indicators of an HSPA framework, a purpose-driven assessment of the health information system (HIS) in Ireland and its fitness to support the implementation of an HSPA framework was conducted. This study reports on the status of the Irish HIS through a multimethod assessment based on continuous broad stakeholder involvement.

Methods
Between May and November 2020, over 50 informants were engaged in individual and group interviews and stakeholder consultation workshops as part of the HIS assessment process. Descriptive themes and high-level data availability heatmaps were derived from interview and workshop data using thematic analysis. Indicator “passports” for the HSPA framework were populated during stakeholder consultation workshops and analysed using univariate descriptive statistics.

Results
The HIS in Ireland was able to provide administrative, survey and registry-based data for public sector acute care services, focusing on structure, process and output metrics. Significant data availability gaps, most notably from primary care, private hospitals and community care, were reported, with little availability of electronic health record and people-reported data. Data on outcome metrics were mostly missing, as were linkage possibilities across datasets for care pathway monitoring. The COVID-19 pandemic highlighted the national HIS’s shortcomings but also the capacity for rapid development and improvement.

Conclusions
A tailor-made assessment of the HIS in Ireland, involving a broad set of relevant stakeholders, revealed strengths, weaknesses and areas for improvement in the Irish health data landscape. It also contributed to the development of a national HSPA framework and momentum to further strengthen data infrastructure and governance, while working towards a more data-driven and person-centred healthcare system. This work demonstrates the utility of an inclusive HIS assessment process and is applicable beyond Ireland, where this case study was conducted.
Diagnostic delay in rare diseases: data from the Spanish rare diseases patient registry
Authors: Benito-Lozano Juan , López-Villalba Blanca , Arias-Merino Greta , Posada de la Paz Manuel , Alonso-Ferreira Verónica 
Published: November 2022

Abstract
Background
According to the International Rare Diseases Research Consortium (IRDiRC), a known rare disease (RD) should be diagnosable within a year. This study sought: firstly, to ascertain how long it takes to obtain the diagnosis of a RD in Spain, along with its associated time trend; and secondly, to identify and measure diagnostic delay (defined by the IRDiRC as any period exceeding a year) by reference to the characteristics of RDs and the persons affected by them.

Methods
Using data sourced from the Spanish Rare Diseases Patient Registry, we performed a descriptive analysis of the time elapsed between symptom onset and diagnosis of each RD, by sex, age and date of symptom onset, and type of RD. We analysed the time trend across the period 1960–2021 and possible change points, using a Joinpoint regression model and assuming a Poisson distribution. The multivariate analysis was completed with backward stepwise logistic regression.

Results
Detailed information was obtained on 3304 persons with RDs: 56.4% had experienced delay in diagnosis of their RDs, with the mean time taken being 6.18 years (median = 2; IQR 0.2–7.5). Both the percentage of patients with diagnostic delay and the average time to diagnosis underwent a significant reduction across the study period (p < 0.001). There was a higher percentage of diagnostic delays: in women (OR 1.25; 95% CI 1.07–1.45); in cases with symptom onset at age 30–44 years (OR 1.48; 95% CI 1.19–1.84): and when analysed by type of RD, in mental and behavioural disorders (OR 4.21; 95% CI 2.26–7.85), followed by RDs of the nervous system (OR 1.39; 95% CI 1.02–1.88).

Conclusions
This is the first study to quantify time to diagnosis of RDs in Spain, based on data from a national registry open to any RD. Since over half of all persons affected by RDs experience delay in diagnosis, new studies are needed to ascertain the factors associated with this delay and the implications this has on the lives of patients and their families.
TREM2 and microglia exosomes: a potential highway for pathological tau
Authors: Jain Nimansha , Ulrich Jason D. 
Published: November 2022

AbstractTau pathology appears to spread along neuronal networks via the template misfolding of tau by pathological tau conformations. The mechanisms underlying neuron-to-neuron transmission of tau are unclear and recent work demonstrates a role for microglia in the spread of tau pathology. In this Commentary, we discuss a recent study that found that loss of TREM2 expression resulted in exacerbated spread of tau pathology that depended on microglial exosomes. These important findings highlight the role of the microglial endolysosomal system and TREM2 in the spread of tau pathology.
Protocol for the development of an international Core Outcome Set for treatment trials in adults with epilepsy: the EPilepsy outcome Set for Effectiveness Trials Project (EPSET)
Authors: Mitchell James W. , Noble Adam , Baker Gus , Batchelor Rachel , Brigo Francesco , Christensen Jakob , French Jacqueline , Gil-Nagel Antonio , Guekht Alla , Jette Nathalie , Kälviäinen Reetta , Leach John Paul , Maguire Melissa , O’Brien Terence , Rosenow Felix , Ryvlin Philippe , Tittensor Phil , Tripathi Manjari , Trinka Eugen , Wiebe Samuel , Williamson Paula R. , Marson Tony 
Published: November 2022

Abstract
Background
A Core Outcome Set (COS) is a standardised list of outcomes that should be reported as a minimum in all clinical trials. In epilepsy, the choice of outcomes varies widely among existing studies, particularly in clinical trials. This diminishes opportunities for informed decision-making, contributes to research waste and is a barrier to integrating findings in systematic reviews and meta-analyses. Furthermore, the outcomes currently being measured may not reflect what is important to people with epilepsy.
Therefore, we aim to develop a COS specific to clinical effectiveness research for adults with epilepsy using Delphi consensus methodology.

Methods
The EPSET Study will comprise of three phases and follow the core methodological principles as outlined by the Core Outcome Measures in Effectiveness Trials (COMET) Initiative. Phase 1 will include two focused literature reviews to identify candidate outcomes from the qualitative literature and current outcome measurement practice in phase III and phase IV clinical trials. Phase 2 aims to achieve international consensus to define which outcomes should be measured as a minimum in future trials, using a Delphi process including an online consensus meeting involving key stakeholders. Phase 3 will involve dissemination of the ratified COS to facilitate uptake in future trials and the planning of further research to identify the most appropriate measurement instruments to use to capture the COS in research practice.

Discussion
Harmonising outcome measurement across future clinical trials should ensure that the outcomes measured are relevant to patients and health services, and allow for more meaningful results to be obtained.

Core Outcome Set registration
COMET Initiative as study 118.
EC-18 prevents autoimmune arthritis by suppressing inflammatory cytokines and osteoclastogenesis
Authors: Park Jin-Sil , Yang Seung Cheon , Jeong Ha Yeon , Lee Seon-Young , Ryu Jun-Geol , Choi Jeong Won , Kang Hye Yeon , Kim Sung-Min , Hwang Sun-Hee , Cho Mi-La , Park Sung-Hwan 
Published: November 2022

Abstract
Background
EC-18, a synthetic monoacetyldiaglyceride, exhibits protective effects against lung inflammation, allergic asthma, and abdominal sepsis. However, there have been no investigations to determine whether EC-18 has preventive potential in autoimmune diseases, especially rheumatoid arthritis (RA).

Methods
To investigate the efficacy of EC-18 on the development of RA, EC-18 was administered in a collagen-induced arthritis (CIA) murine model and disease severity and the level of inflammatory cytokines in the joint were investigated. The effect of EC-18 on the inflammation-related factors was investigated by flow cytometry, ELISA, western blot, and real-time PCR in splenocytes from mice and in peripheral blood mononuclear cells from healthy and patients with RA. The effect of EC-18 on osteoclastogenesis was investigated.

Results
EC-18 effectively reduced the clinical and histological severity of arthritis, similar to Janus kinase inhibitors include tofacitinib and baricitinib, in CIA. Furthermore, EC-18 exhibited a synergistic effect with methotrexate in preventing CIA. Treatment with EC-18 effectively reduced the production of inflammatory cytokines in immune cells and osteoclast differentiation in mice and patients with RA.

Conclusion
These results suggest that EC-18 may be an effective strategy for RA.
Acute circulatory and femoral hemodynamic responses induced by standing core exercise at different rotational cadence: a crossover study
Authors: Lin Hsin-Fu , Chou Chun-Chung , Chao Hsiao-Han , Wang Soun-Cheng , Chen Chen-Huan 
Published: November 2022

Abstract
Background
Core exercise is often adopted as an adjunct in maintaining musculoskeletal health in rehabilitation; we previously showed that standing core rotational exercise improves femoral blood flow after training. This study aimed to investigate the effects of different rotational cadences on circulatory and hemodynamic responses after acute standing core exercise.

Methods
Sixteen healthy male adults (22 ± 1 yrs) were randomly assigned to participate in two 30-min standing core exercises of fast (75 rpm, FC) and slow cadence (20 rpm, SC) sessions after completing an acute bout of seated knee extension exercise session (KE) (80% of 1 repetition maximum × 12 repetitions × 3 sets). Impedance cardiography-derived circulatory responses and femoral hemodynamics by ultrasound imaging were measured pre- and 30, and 60 min post-exercise.

Results
KE acutely increased post-exercise cardiac output at 30 min (p = 0.008) and heart rate at 30 min (p = 0.04) and 60 min (p = 0.01), yet brachial blood pressure did not change. Systemic vascular resistance was significantly lower after FC and KE at 30 min (p = 0.008) and 60 (p = 0.04) min, respectively, compared with the baseline. In addition, KE acutely decreased post-exercise arterial stiffness (p = 0.05) at 30 min, increased femoral conductance (p = 0.03, p < 0.001), and blood flow (p = 0.009, p < 0.001) at 30 and 60 min. No significant changes were observed in absolute femoral blood flow after FC and SC, except that FC significantly increased relative femoral blood flow (p = 0.007) and conductance (p = 0.005). Post-exercise femoral diameter significantly increased in KE at 30 (p = 0.03) and 60 min (p = 0.01), but not in core exercise.

Conclusion
Our results suggest that standing core exercise elicits circulatory and hemodynamic changes only when the rotational cadence is set at a faster cadence, which provides preliminary scientific evidence for its use in exercise programs.
Regulation of alphaherpesvirus protein via post-translational phosphorylation
Authors: Zhou Tong , Wang Mingshu , Cheng Anchun , Yang Qiao , Tian Bin , Wu Ying , Jia Renyong , Chen Shun , Liu Mafeng , Zhao Xin-Xin , Ou Xuming , Mao Sai , Sun Di , Zhang Shaqiu , Zhu Dekang , Huang Juan , Gao Qun , Yu Yanling , Zhang Ling 
Published: November 2022

AbstractAn alphaherpesvirus carries dozens of viral proteins in the envelope, tegument and capsid structure, and each protein plays an indispensable role in virus adsorption, invasion, uncoating and release. After infecting the host, a virus eliminates unfavourable factors via multiple mechanisms to escape or suppress the attack of the host immune system. Post-translational modification of proteins, especially phosphorylation, regulates changes in protein conformation and biological activity through a series of complex mechanisms. Many viruses have evolved mechanisms to leverage host phosphorylation systems to regulate viral protein activity and establish a suitable cellular environment for efficient viral replication and virulence. In this paper, viral protein kinases and the regulation of viral protein function mediated via the phosphorylation of alphaherpesvirus proteins are described. In addition, this paper provides new ideas for further research into the role played by the post-translational modification of viral proteins in the virus life cycle, which will be helpful for understanding the mechanisms of viral infection of a host and may lead to new directions of antiviral treatment.
Adversarial bandit approach for RIS-aided OFDM communication
Authors: Ahmed Ouameur Messaoud , Anh Lê Dương Tuấn , Massicotte Daniel , Jeon Gwanggil , de Figueiredo Felipe Augusto Pereira 
Published: November 2022

AbstractTo assist sixth-generation wireless systems in the management of a wide variety of services, ranging from mission-critical services to safety-critical tasks, key physical layer technologies such as reconfigurable intelligent surfaces (RISs) are proposed. Even though RISs are already used in various scenarios to enable the implementation of smart radio environments, they still face challenges with regard to real-time operation. Specifically, high dimensional fully passive RISs typically need costly system overhead for channel estimation. This paper, however, investigates a semi-passive RIS that requires a very low number of active elements, wherein only two pilots are required per channel coherence time. While in its infant stage, the application of deep learning (DL) tools shows promise in enabling feasible solutions. We propose two low-training overhead and energy-efficient adversarial bandit-based schemes with outstanding performance gains when compared to DL-based reflection beamforming reference methods. The resulting deep learning models are discussed using state-of-the-art model quality prediction trends.