Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-COVID-19 mortality in France, April 2020 - June 2022: reduction compared to pre-pandemic mortality patterns, relative increase during the Omicron period, and the importance of detecting SARS-CoV-2 infections

Aims: We compared the number of non-COVID-19 deaths between April 2020 and June 2022 to the expected number of deaths based on the patterns observed in the five years prior to the pandemic in France with the aims of (a) estimating the reduction in non-COVID-19 mortality, particularly due to reduction in the circulation of other respiratory viruses during the pandemic; (b) examining the degree to which SARS-CoV-2 infection was detected and characterized as a cause of death during different periods of the pandemic. Methods: Using a previously developed regression model, we expressed weekly mortality rates in the 5-year period prior to the pandemic as a combination of influenza-associated mortality rates and baseline and a linear trend for the rates of non-influenza mortality. Estimates for the baseline and trend for non-influenza mortality together with estimates of influenza-related mortality prior to the pandemic were used to estimate expected mortality during the pandemic period. Results: The number of recorded non-COVID-19 deaths between week 15, 2020 and week 26, 2022 in France was less than the expected number of deaths by 49,623 (95% CI (20364,78837)). Additionally, rates of non-COVID-19 mortality increased during the later part of the study period, with the difference between the number of non-COVID-19 deaths and the expected number of deaths during the last 52 weeks of the study period being greater than the corresponding difference for the first 52 weeks of the study period by 28,954 (24979,32918) deaths. Conclusions: Our results suggest (a) the effectiveness of mitigation measures during the pandemic for reducing the rates of non-COVID-19 mortality, particularly mortality related to circulation of other respiratory viruses, including influenza (that was responsible for an annual average of 15,334 (12593,18077) deaths between 2015-2019 in France); (b) detection of a high proportion of SARS-CoV-2 infections leading to deaths in France, and characterization of those infections as the underlying cause of death. Additionally, while the increase in non-COVID-19 mortality during the later part of the study period is partly related to the temporal increase in the circulation of other respiratory viruses, there was an increase, particularly during the period of the circulation of the Omicron variant, in the proportion of hospitalizations with a SARS-CoV-2 infection in France that were coded as hospitalizations with COVID-19 (rather than COVID-19 hospitalizations), suggesting an increasing proportion of SARS-COV-2-associated deaths not being coded as COVID-19 deaths. All of this suggests the importance of timely detection of infections with SARS-CoV-2, particularly the Omicron variant (for which manifestations of disease complications are different compared to the earlier variants), and of providing the necessary treatment to patients to avoid progression to fatal outcomes.
Clinical and economic impact of a community-based, hybrid model of in-person and virtual care in a Canadian rural setting: a cross-sectional population-based comparative study

Objectives To determine the clinical and economic impact of a community-based, hybrid model of in-person and virtual care by comparing health-system performance of the rural jurisdiction where this model was implemented with neighbouring jurisdictions without such a model and the broader regional health system. Design A cross-sectional comparative study. Setting Ontario, Canada, with a focus on three largely rural public health units from 1 April 2018 until 31 March 2021. Participants All residents of Ontario, Canada under the age of 105 eligible for the Ontario Health Insurance Plan during the study period. Interventions An innovative, community-based, hybrid model of in-person and virtual care, the Virtual Triage and Assessment Centre (VTAC), was implemented in Renfrew County, Ontario on 27 March 2020. Main outcome measures Primary outcome was a change in emergency department (ED) visits anywhere in Ontario, secondary outcomes included changes in hospitalisations and health-system costs, using per cent changes in mean monthly values of linked health-system administrative data for 2 years preimplementation and 1 year postimplementation. Results Renfrew County saw larger declines in ED visits (−34.4%, 95% CI −41.9% to −26.0%) and hospitalisations (−11.1%, 95% CI −19.7% to −1.5%) and slower growth in health-system costs than other rural regions studied. VTAC patients’ low-acuity ED visits decreased by −32.9%, high-acuity visits increased by 8.2%, and hospitalisations increased by 30.0%. Conclusion After implementing VTAC, Renfrew County saw reduced ED visits and hospitalisations and slower health-system cost growth compared with neighbouring rural jurisdictions. VTAC patients experienced reduced unnecessary ED visits and increased appropriate care. Community-based, hybrid models of in-person and virtual care may reduce the burden on emergency and hospital services in rural, remote and underserved regions. Further study is required to evaluate potential for scale and spread.
Scaling theory for ballistic aggregation

The authors develop a Smoluchowski-type mean-field treatment for a recently introduced model of ballistic agglomeration. The predictions of this mean-field theory for the exponent characterizing typical cluster size are in agreement with earlier results for all dimensions. Nevertheless, the predicted monomer decay and particle size distribution are totally at variance with the numerical observations in one dimension. The reason for this discrepancy is found to be the fact that high velocity particles coalesce rapidly independently of their mass, which introduces correlations not taken into account by the mean-field treatment. This is likely to persist in all dimensions, so that the model has no upper critical dimension. The case where the initial velocity distribution function of the particles has a power-law tail is also examined. It is found that, at least in one dimension, the typical cluster size behaves in a way that depends on the specific velocity distribution function, whereas the monomer decay does not.
DEEP LEARNING IN THE PREDICTION OF ANGIOGRAPHY-PROVEN SEVERE CORONARY STENOSIS IN PATIENTS WITH APPARENTLY NORMAL ELECTROCARDIOGRAMS

Patients with severe coronary artery stenosis may have apparently normal electrocardiograms (ECGs), making it difficult to detect the adverse health conditions during screening or physical examinations, resulting in them missing the optimal window of treatment. The goal of this study was to develop an artificial intelligence-based ECG model which can distinguish severe coronary stenosis ([≥] 90%) from no or mild coronary stenosis (< 50%) in patients with apparently normal ECGs. Deep learning (DL) models trained from scratch with pre-trained parameters (transfer learning) were tested on ECG alone as well as on ECG along with clinical information (age, sex, hypertension, diabetes, dyslipidemia and smoking status). We also compared the performance of logistic regression for clinical information only and found that DL models trained from scratch with ECG alone can achieve a specificity of 0.746; however, they have low sensitivity, which is comparable to the performance of logistic regression with clinical data. Although adding clinical information to the ECG DL model trained from scratch can improve the sensitivity, it can reduce the specificity. Combining clinical information with the ECG transfer learning model provides the best performance, with a 0.847 AUC, 0.848 sensitivity, and 0.704 specificity.
Two-dimensional turbulence and persistent zonal jets in a global barotropic model

Abstract The dynamics of two-dimensional turbulence on a rotating sphere are examined. The anisotropic Rhines scale is derived and verified in decaying turbulence simulations. Due to the anisotropic nature of the Rossby waves, the Rhines barrier is displaced toward small total wavenumber n with decreasing zonal wavenumber m. Up-scale energy transfer along the zonal axis (m = 0) is not directly arrested by beta. A forced dissipative model with high-wavenumber forcing is used to investigate the dynamics of persistent zonal jets. Persistent jets form in the low energy (strong rotation) cases with the root-mean-square velocity V*rms ≪ aΩ. Under a fixed rotation rate, the jet scale decreases with the energy. The equilibrated jets generally stay at fixed latitudes. The zonal bands are nearly uniformly distributed in latitude, except that bands in the high latitudes tend to be wider and weaker, as clearly affected by a decreasing beta with latitude. The time-mean zonal winds in the forced simulations appear to b.
A Direct Method for the Regularity of the Gain Term in the Boltzmann Equation

This paper presents an essentially simple and direct method to prove the regularizing properties of the collision gain term in the first equation of the Boltzmann hierarchy. Some corollaries of the main results of this paper are given to improve the previous results on the regularity of the gain term in the Boltzmann equation. An extension of a new fundamental result concerning separated variable kernels is also given to some general kernels.
Global feature extraction using efficient Hough transform

Novel Hough transform schemes are presented to provide two kinds of function expected of a global feature extractor. While the Hough transform was originally no more than a line segment detector, more complicated pattern features can be extracted by more intensive investigation of the Hough parameter space and/or more hierarchical usage of the Hough transform. As a typical example, a method to extract convex hulls and other related features from the transform space is introduced. In order to reduce the computing cost, a few efficient algorithms are introduced. A family of the functions applicable to the Houghlike feature extractor, the extended Hough transform, is proposed. As an example of hierarchical usage, the Hough transform is applied to the feature points of the Hough space. <<ETX>>
Analysis of inhibitors of the anoctamin‐1 chloride channel (transmembrane member 16A, TMEM16A) reveals indirect mechanisms involving alterations in calcium signalling

Pharmacological inhibitors of TMEM16A (ANO1), a Ca2+‐activated Cl− channel, are important tools of research and possible therapeutic agents acting on smooth muscle, airway epithelia and cancer cells. We tested a panel of TMEM16A inhibitors, including CaCCinh‐A01, niclosamide, MONNA, Ani9 and niflumic acid, to evaluate their possible effect on intracellular Ca2+.
Predictive Value of Anti- E6 Oncoprotein (High Risk- Human Papilloma Virus) and p16 Ink4a for Detecting HPV in Oral Epithelial Dysplasia

Aim: The aim of this study was to evaluate the expression of human papillomavirus (HPV) in oral potentially malignant disorders (OPMD) and to examine the association of HPV in histological grades of dysplasia using p16 and Anti-E6 oncoprotein immunohistochemistry (IHC). Subjects and methods: This study focused on clinically diagnosed oral potentially malignant disorders. Clinical parameters such as age, gender, habits, occupation, duration, site, and the type of the lesions were examined and the incisional biopsy was done on the selected cases for the histopathological diagnosis. Selected cases of OPMDs were screened immunohistochemically for HPV 16 and HPV 18 (high-risk group) positivity using p16INK4a and Anti-E6 oncoprotein. The immunohistochemical p16 expression was evaluated based on (a) percentage of p16 positive cases and (b) pattern of p16 staining in various grades of OPMD. Results: Anti-E6 oncoprotein (HR-HPV) expression level was only detected in 11 cases (37%), and positive expression of p16 was found in three cases (10%), with variation in cell proportion and intensity. Subsequently, the association between p16 expression level and clinicopathological characteristic factors was analyzed and a significant association was found between age and histopathology. Conclusion: There was an association between HPV and OPMD. Both biomarker tests, HPV E6 and p16 immunocytochemistry had a specific role in the detection of HR-HPV. Anti-E6 immunocytochemistry can be a valuable test with higher specificity for HPV DNA detection in oral epithelial dysplasia without losing sensitivity.
Euclidean Distance Matrices

Keywords: Euclidean Distance Matrices ; Calibration ; Sensor Localization ; S-stress ; Multidimensional Scaling ; Acoustics ; Heisenberg Uncertainty Principle ; Maximally Compact Sequences These Ecole polytechnique federale de Lausanne EPFL, n° 5971 (2013)Programme doctoral Informatique, Communications et InformationFaculte informatique et communicationsInstitut de systemes de communicationLaboratoire de communications audiovisuellesJury: Prof. E. Telatar (president), Prof. M. Vetterli (directeur), Prof. H. Bolcskei, Dr F. Quick, Prof. R. Urbanke (rapporteurs) Public defense: 2014-2-7 Reference doi:10.5075/epfl-thesis-5971Print copy in library catalog Record created on 2014-02-04, modified on 2017-05-12
Active learning for efficient analysis of high-throughput nanopore data

Abstract Motivation As the third-generation sequencing technology, nanopore sequencing has been used for high-throughput sequencing of DNA, RNA, and even proteins. Recently, many studies have begun to use machine learning technology to analyze the enormous data generated by nanopores. Unfortunately, the success of this technology is due to the extensive labeled data, which often suffer from enormous labor costs. Therefore, there is an urgent need for a novel technology that can not only rapidly analyze nanopore data with high-throughput, but also significantly reduce the cost of labeling. To achieve the above goals, we introduce active learning to alleviate the enormous labor costs by selecting the samples that need to be labeled. This work applies several advanced active learning technologies to the nanopore data, including the RNA classification dataset (RNA-CD) and the Oxford Nanopore Technologies barcode dataset (ONT-BD). Due to the complexity of the nanopore data (with noise sequence), the bias constraint is introduced to improve the sample selection strategy in active learning. Results: The experimental results show that for the same performance metric, 50% labeling amount can achieve the best baseline performance for ONT-BD, while only 15% labeling amount can achieve the best baseline performance for RNA-CD. Crucially, the experiments show that active learning technology can assist experts in labeling samples, and significantly reduce the labeling cost. Active learning can greatly reduce the dilemma of difficult labeling of high-capacity nanopore data. We hope active learning can be applied to other problems in nanopore sequence analysis. Availability and implementation The main program is available at https://github.com/guanxiaoyu11/AL-for-nanopore. Supplementary information Supplementary data are available at Bioinformatics online.
Factors associated with pre-loss grief and preparedness in relatives of people with cancer during the COVID-19 pandemic: A cross-sectional study

Objectives Before the loss of a loved one to cancer, relatives have time to adapt to the impending death. However, due to the current COVID-19 pandemic, adjustment to an imminent death may be more difficult. This study investigates factors related to pre-loss grief and preparedness during the COVID-19 pandemic and their relationship with COVID-19 related fears. Methods Data of 299 participants from a cross-sectional study was used. Participants were included if they were relatives of people with cancer, spoke German and were at least 18 years. Multivariate linear regression analyses were conducted to measure the relationship between predictors (dysfunctional coping, emotion-focused coping, problem-focused coping, attachment anxiety, attachment avoidance, COVID-19 related fears, prognosis, perceived depth of the relationship, perceived conflict in the relationship, health status) and pre-loss grief, preparedness for caregiving and preparedness for death as the dependent variables. Results Perceived depth (β = .365, p < .001), COVID-19 related fears (β = .141, p = .002), prognosis for death (β = .241, p < .001), dysfunctional coping strategies (β = .281, p < .001) and emotion-focused coping strategies (β = -.320, p < .001) significantly predicted pre-loss grief. Prognosis for death (β = .347, p < .001), dysfunctional coping strategies (β = -.229, p < .001), emotion-focused coping strategies (β = .242, p < .001), COVID-19 related fears (β = -.112, p = .037) and health status (β = .123, p = .025) significantly predicted preparedness for death. Dysfunctional coping (β = -.147, p = .009), problem-focused coping (β = .162, p = .009), emotion-focused coping (β = .148, p = .017), COVID-19 related fears (β = -.151, p = .006), attachment anxiety (β = -.169, p = .003), perceived conflict in the relationship with the patient with cancer (β = -.164, p = .004), perceived depth in the relationship (β = .116, p = .048) and health status (β = .157, p = .003) significantly predicted preparedness for caregiving. Conclusions This study shows COVID-19 pandemic impacts on the grieving process of relatives of patients with cancer. Consequently, screening for pre-loss grief, preparedness and their associated factors may help provide early support for relatives of people with cancer at need. However, further research is needed to help understand the stability of pre-loss grief and preparedness.
Bayesian Animal Survival Estimation

We present the Bayesian approach to estimating parameters associated with animal survival on the basis of data arising from mark recovery and recapture studies. We provide two examples, beginning with a discussion of band-return models and examining data gathered from observations of blue winged teal (Anas discors), ringed as nestlings. We then look at open population recapture models, focusing on the Cormack-Jolly-Seber model, and examine this model in the context of a data set on European dippers (Cinclus cinclus). The Bayesian procedures are shown to be straightforward and provide a convenient framework for model-averaging, which incorporates the uncertainty due to model selection into the inference process. Sufficient detail is provided so that readers who wish to employ the Bayesian approach in this field can do so with ease. An example of BUGS code is also provided.
Is prematurity a risk factor for developmental dysplasia of the hip? A systematic review and meta-analysis

Developmental dysplasia of the hip (DDH) is the most common orthopedic disorder in newborns. Early recognition and diagnosis are critical to prevent long-term complications. While several risk factors have been established, the association between prematurity and DDH remains unclear. Our analysis sought to analyze the literature exploring the relationship between prematurity and DDH. Articles evaluating the relationship between prematurity and DDH published between 1 January 2000 and 1 February 2022 were queried, with 11 studies included for analysis. Overall, a total of 8720 patients were included. The gestational age ranged from 23 to 36 weeks for preterm and ≥37 weeks for term births. Seven studies agreed that gestational age did not have a significant impact on DDH. Pooled analysis of available data demonstrated no significant difference in DDH among preterm and term infants (OR, 1.11; 95% CI, 0.82–1.51; P = 0.49). Sub-group analysis of two studies reporting data on very preterm (≤32 weeks) and term infants revealed no significant difference in the occurrence of DDH (OR, 4.58; 95% CI, 0.09–244.78; P = 0.45). Four studies found early gestational age is associated with a significantly higher incidence of mature hips compared to late preterm or term babies. Similarly, pooled analysis demonstrated significantly lower Graf classification among preterm infants (OR, 0.13; 95% CI, 0.03–0.61; P = 0.009). Based on the current literature, our analysis found that prematurity is not strongly associated with DDH. Furthermore, early gestational age was associated with a significantly higher incidence of mature hips measured by Graf classification.
Cross-sectional Associations of β-Amyloid, Tau, and Cerebrovascular Biomarkers With Neurodegeneration in Probable Dementia With Lewy Bodies

Background and Objectives Although alpha-synuclein–related pathology is the hallmark of dementia with Lewy bodies (DLB), cerebrovascular and Alzheimer disease pathologies are common in patients with DLB. Little is known about the contribution of these pathologies to neurodegeneration in DLB. We investigated associations of cerebrovascular, β-amyloid, and tau biomarkers with gray matter (GM) volume in patients with probable DLB. Methods We assessed patients with probable DLB and cognitively unimpaired (CU) controls with 11C-Pittsburgh compound B (PiB) and 18F-flortaucipir PET as markers of β-amyloid and tau, respectively. MRI was used to assess white matter hyperintensity (WMH) volume (a marker of cerebrovascular lesion load) and regional GM volume (a marker of neurodegeneration). We used correlations and analysis of covariance (ANCOVA) in the entire cohort and structural equation models (SEMs) in patients with DLB to investigate associations of WMH volume and regional β-amyloid and tau PET standardized uptake value ratios (SUVrs) with regional GM volume. Results We included 30 patients with DLB (69.3 ± 10.2 years, 87% men) and 100 CU controls balanced on age and sex. Compared with CU controls, patients with DLB showed a lower GM volume across all cortical and subcortical regions except for the cuneus, putamen, and pallidum. A larger WMH volume was associated with a lower volume in the medial and orbital frontal cortices, insula, fusiform cortex, and thalamus in patients with DLB. A higher PiB SUVr was associated with a lower volume in the inferior temporal cortex, while flortaucipir SUVr did not correlate with GM volume. SEMs showed that a higher age and absence of the APOE ε4 allele were significant predictors of higher WMH volume, and WMH volume in turn was a significant predictor of GM volume in medial and orbital frontal cortices, insula, and inferior temporal cortex. By contrast, we observed 2 distinct paths for the fusiform cortex, with age having an effect through PiB and flortaucipir SUVr on one path and through WMH volume on the other path. Discussion Patients with probable DLB have widespread cortical atrophy, most of which is likely influenced by alpha-synuclein–related pathology. Although cerebrovascular, β-amyloid, and tau pathologies often coexist in probable DLB, their contributions to neurodegeneration seem to be region specific.
Midazolam alleviates cellular senescence in SH‐SY5Y neuronal cells in Alzheimer's disease

Alzheimer's disease (AD) impacts the daily life of aging people. Oligomerized amyloid β (Aβ)‐associated neuronal senescence is involved in the pathological mechanism of AD. Blockage of neuronal senescence has been considered an important strategy for the treatment of AD. Midazolam is a hypnotic‐sedative drug with pleiotropic properties.