Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic construction of patient-specific finite-element mesh of the spine from IVDs and vertebra segmentations

Computational medicine aims at developing patient-specific models to help physicians in the diagnosis and treatment selection for patients. The spine, and other skeletal structures, is an articulated object, composed of rigid bones (vertebrae) and non-rigid parts (intervertebral discs (IVD), ligaments and muscles). These components are usually extracted from different image modalities, involving patient repositioning. In the case of the spine, these models require the segmentation of IVDs from MR and vertebrae from CT. In the literature, there exists a vast selection of segmentations methods, but there is a lack of approaches to align the vertebrae and IVDs. This paper presents a method to create patient-specific finite element meshes for biomechanical simulations, integrating rigid and non-rigid parts of articulated objects. First, the different parts are aligned in a complete surface model. Vertebrae extracted from CT are rigidly repositioned in between the IVDs, initially using the IVDs location and then refining the alignment using the MR image with a rigid active shape model algorithm. Finally, a mesh morphing algorithm, based on B-splines, is employed to map a template finite-element (volumetric) mesh to the patient-specific surface mesh. This morphing reduces possible misalignments and guarantees the convexity of the model elements. Results show that the accuracy of the method to align vertebrae into MR, together with IVDs, is similar to that of the human observers. Thus, this method is a step forward towards the automation of patient-specific finite element models for biomechanical simulations.
A Survey of Densest Subgraph Discovery on Large Graphs

With the prevalence of graphs for modeling complex relationships among objects, the topic of graph mining has attracted a great deal of attention from both academic and industrial communities in recent years. As one of the most fundamental problems in graph mining, the densest subgraph discovery (DSD) problem has found a wide spectrum of real applications, such as discovery of filter bubbles in social media, finding groups of actors propagating misinformation in social media, social network community detection, graph index construction, regulatory motif discovery in DNA, fake follower detection, and so on. Theoretically, DSD closely relates to other fundamental graph problems, such as network flow and bipartite matching. Triggered by these applications and connections, DSD has garnered much attention from the database, data mining, theory, and network communities. In this survey, we first highlight the importance of DSD in various real-world applications and the unique challenges that need to be addressed. Subsequently, we classify existing DSD solutions into several groups, which cover around 50 research papers published in many well-known venues (e.g., SIGMOD, PVLDB, TODS, WWW), and conduct a thorough review of these solutions in each group. Afterwards, we analyze and compare the models and solutions in these works. Finally, we point out a list of promising future research directions. It is our hope that this survey not only helps researchers have a better understanding of existing densest subgraph models and solutions, but also provides insights and identifies directions for future study.
Topic-Centric Explanations for News Recommendation

News recommender systems (NRS) have been widely applied for online news websites to help users find relevant articles based on their interests. Recent methods have demonstrated considerable success in terms of recommendation performance. However, the lack of explanation for these recommendations can lead to mistrust among users and lack of acceptance of recommendations. To address this issue, we propose a new explainable news model to construct a topic-aware explainable recommendation approach that can both accurately identify relevant articles and explain why they have been recommended, using information from associated topics. Additionally, our model incorporates two coherence metrics applied to assess topic quality, providing measure of the interpretability of these explanations. The results of our experiments on the MIND dataset indicate that the proposed explainable NRS outperforms several other baseline systems, while it is also capable of producing interpretable topics compared to those generated by a classical LDA topic model. Furthermore, we present a case study through a real-world example showcasing the usefulness of our NRS for generating explanations.
Homophily modulates double descent generalization in graph convolution networks

Significance Graph neural networks (GNNs) have been applied with great success across science and engineering, but we do not understand why they work so well. Motivated by experimental evidence of a rich phase diagram of generalization behaviors, we analyzed simple GNNs on a community graph model and derived precise expressions for generalization error as a function of noise in the graph, noise in the features, proportion of labeled data, and the nature of interactions in the graph. Computer experiments show that the analysis also qualitatively explains large “production-scale” networks and can thus be used to improve performance and guide hyperparameter tuning. This is significant both for the downstream science and for the theory of deep learning on graphs.
Mixed Membership Estimation for Weighted Networks

Community detection in overlapping un-weighted networks in which nodes can belong to multiple communities is one of the most popular topics in modern network science during the last decade. However, community detection in overlapping weighted networks in which edge weights can be any real values remains a challenge. In this article, to model overlapping weighted networks with latent community memberships, we propose a generative model called the degree-corrected mixed membership distribution-free model which can be viewed as generalizing several previous models. First, we address the community membership estimation of the proposed model by an application of a spectral algorithm and establish a theoretical guarantee of consistency. We then propose overlapping weighted modularity to measure the quality of overlapping community detection for weighted networks with positive and negative edge weights. To determine the number of communities for weighted networks, we incorporate the algorithm into the overlapping weighted modularity. We demonstrate the advantages of degree-corrected mixed membership distribution-free model and overlapping weighted modularity with applications to simulated data and eleven real-world networks.
The complete mitochondrial genome of Stibochiona nicea (Gray, 1846) (Lepidoptera: Nymphalidae) and phylogenetic analysis

Abstract In this study, the complete mitochondrial genome (mitogenome) of Stibochiona nicea (Gray, 1846) (Lepidoptera: Nymphalidae) was first reported with 15,298 bp in size, containing 13 protein-coding genes (PCGs), 22 tRNA genes, two rRNA genes (rrnL and rrnS), and one control region. The nucleotide composition of the entire mitogenome is highly A + T biased (81.5%). The gene content and arrangement of the newly sequenced mitogenome are identical to those of the other available mitogenomes of Nymphalidae. All PCGs start with the conventional ATN codons, except for cox1 initiating with atypical CGA(R). Nine PCGs (atp8, atp6, cox3, nad1, nad2, nad3, nad4l, nad6, and cob) utilize a typical stop codon TAA, whereas the remaining PCGs (cox1, cox2, nad4, and nad5) end with an incomplete stop codon T–. Phylogenetic analysis revealed that S. nicea is closely related to Dichorragia nesimachus within Pseudergolinae, which further forms the sister group to the grouping of (Nymphalinae + (Cyrestinae + (Biblidinae + Apaturinae))). The complete mitogenome of S. nicea will provide useful genetic information for improving the taxonomic system and phylogenetics of Nymphalidae.
Honey bees and bumble bees occupying the same landscape have distinct gut microbiomes and amplicon sequence variant-level responses to infections

The gut microbiome of bees is vital for the health of their hosts. Given the ecosystem functions performed by bees, and the declines faced by many species, it is important to improve our understanding of the amount of natural variation in the gut microbiome, the level of sharing of bacteria among co-occurring species (including between native and non-native species), and how gut communities respond to infections. We conducted 16S rRNA metabarcoding to discern the level of microbiome similarity between honey bees (Apis mellifera, N = 49) and bumble bees (Bombus spp., N = 66) in a suburban-rural landscape. We identified a total of 233 amplicon sequence variants (ASVs) and found simple gut microbiomes dominated by bacterial taxa belonging to Gilliamella, Snodgrassella, and Lactobacillus. The average number of ASVs per species ranged from 4.00–15.00 (8.79 ± 3.84, mean ± SD). Amplicon sequence variant of one bacterial species, G. apicola (ASV 1), was widely shared across honey bees and bumble bees. However, we detected another ASV of G. apicola that was either exclusive to honey bees, or represented an intra-genomic 16S rRNA haplotype variant in honey bees. Other than ASV 1, honey bees and bumble bees rarely share gut bacteria, even ones likely derived from outside environments (e.g., Rhizobium spp., Fructobacillus spp.). Honey bee bacterial microbiomes exhibited higher alpha diversity but lower beta and gamma diversities than those of bumble bees, likely a result of the former possessing larger, perennial hives. Finally, we identified pathogenic or symbiotic bacteria (G. apicola, Acinetobacter sp. and Pluralibacter sp.) that associate with Trypanosome and/or Vairimorpha infections in bees. Such insights help to determine bees’ susceptibility to infections should gut microbiomes become disrupted by chemical pollutants and contribute to our understanding of what constitutes a state of dysbiosis.
Predictors of sustained use of mobile health applications: Content analysis of user perspectives from a fever management app

Objectives Mobile health applications could be means of educating and changing behaviours of their users. Their features and qualities determine the sustainability of use. The FeverApp with two main features of information and documentation is a research-based app. In this observational cohort study, to evaluate the influential predictors of use, users’ feedback on the FeverApp, were analyzed. Methods Feedback is given using a structured questionnaire, four Likert items and two open questions regarding positive and negative impressions, available via app menu. Conventional content analysis (inductive approach) on the two open questions was performed. Comments were grouped into 12 codes. These codes were grouped hierarchically in an iterative process into nine subcategories and lastly into two main categories ‘format’ and ‘content’. Descriptive and quantitative analysis were performed. Results Out of 8243 users, 1804 of them answered the feedback questionnaire. The features of the app (N = 344), followed by the information aspect (N = 330) were most frequently mentioned. Documentation process (N = 226), request for new features or improvement of the current ones (N = 193), and functioning (N = 132) were also highlighted in users’ feedback. App's ease of use, design and being informative were important for the users. The first impression of the app seems important as the majority of feedback were given during the first month of using the app. Conclusion In-app feedback function could highlight shortcomings and strengths of mobile health apps. Taking users’ feedback into consideration could increase the chance of sustained use. Besides ease of use and clear, likeable designs, users want apps that serve their needs while saving time.
Arabic translation and cultural adaptation of sedentary behavior, dietary habits, and preclinical mobility limitation questionnaires: A cognitive interview study

Background Developing global evidence on the influence of health-related behaviors (e.g., sedentary behavior, diet) and mobility limitations on health requires global consortia from diverse sets of countries. Thus, the purpose was to translate and culturally adapt (i) the Sedentary Behavior Questionnaire (SBQ); (ii) the Dietary Habits Questionnaire adapted from the Survey of Health, Aging and Retirement in Europe (SHARE) study; (iii) the Preclinical Mobility Limitation questionnaire for use in the Saudi Arabian context. Method 50 adult Saudi participants (mean age 41.7±9.6, 48% female) participated in this study. We followed a systematic cross-cultural adaptation process that involved forward translation, synthesis, back-translation, expert panel, and pre-testing (cognitive interviewing). Four rounds of cognitive interviews were held with 40 participants for the SBQ, SHARE questionnaire, and the Preclinical Mobility Limitation questionnaire, an additional round was needed for the Preclinical Mobility Limitation questionnaire. Descriptive data (means ± standard deviations and frequencies with percentages) were reported for characteristics. Result With some minor changes to the questionnaires, the SBQ, Dietary Habits, and Preclinical Mobility Limitation questionnaires were translated and cross-culturally adapted into Arabic. 100% of the participants confirmed that the resulting Arabic versions of the SBQ, Dietary Habits questionnaire, and Preclinical Mobility Limitation questionnaires were appropriate and fully understandable for Arabic speakers in communicating the intended meanings of the items in each. For example, item SBQ1, ‘Watching television (including videos on VCR/DVD)’ was changed to ‘Sitting and watching television or videos (including smartphones, tablets)’. Conclusion The SBQ, Dietary Habits questionnaire, and Preclinical Mobility Limitation questionnaire were successfully cross-culturally adapted into Arabic and are now ready for use in Saudi Arabian.
Retrospective Phylodynamic and Phylogeographic Analysis of the Human Papillomavirus 16 E6 Gene in the Mediterranean Region

Human papillomavirus 16 (HPV16) is considered to be strongly correlated with the development of cervical cancer. Among the 8 HPV16 genes, the E6 constitutes a remarkable marker to follow the evolutionary history and spatial phylodynamics of HPV16 in the Mediterranean basin. Thus, this work aims to decipher the major evolutionary events and crosstalks in the Mediterranean basin with a focus on Tunisian strains regarding the E6 oncogene. In this study, we first extracted the available and annotated Mediterranean strains of HPV16 E6 gene sequences (n = 155) from the NCBI nucleotide database. These sequences were aligned, edited, and used for the downstream phylogenetic analyses. Finally, a Bayesian Markov Chain Monte Carlo approach was applied to reconstruct the evolutionary history of HPV16 migration. Our results showed that the HPV circulating in Tunisia derived from a Croatian ancestor around the year 1987. This starting point spreads to most European countries to reach northern Africa through the Moroccan gateway in 2004.
School‐based interventions on Mpox: A scoping review

The 2022 multicountry mpox outbreak necessitated the declaration of mpox as a public health emergency. This is the first time a wide mpox spread and human‐to‐human transmission are recorded in several countries outside West and Central Africa. The outbreak reveals a strong need for wider intervention to increase awareness and control measures on mpox, especially in schools. This scoping review aims to summarize the existing evidence concerning school‐based interventions on mpox globally.
Safety and Performance of Hemostatic Powders

Background Hemorrhage, a sudden and severe leakage of blood due to the disruption of blood vessels, is one of the most common causes of death from injuries worldwide. Severe bleeding accounts for more than 35% of pre-hospital deaths and about 40% of deaths recorded within 24 hours of injury. One of the methods for achieving homeostasis is the use of hemostatic powders. This study compares the basic safety and performance of the most popular hemostatic powders. Methods Basic safety of commercially available products were evaluated using MTT, MEM elution assay, and endotoxin testing. The in vitro performance was evaluated using water absorption capacity, water absorption rate, and adhesion strength assays. Results 4Seal, Starsil, and 4DryField extracts did not cause cytotoxicity in MTT and MEM elution assays. PerClot and SuperClot extracts demonstrated cytotoxic potential in MTT assay, while Arista extract was cytotoxic in both MEM elution and MTT assays. 4Seal has the lowest endotoxin contamination, followed by PerClot, 4DryField, SuperClot, Arista, and Starsil. 4Seal and Starsil showed significantly highest WAR among the tested samples, followed by 4DryField, Arista, PerClot, and SuperClot. Adhesion force is highest for 4Seal, followed by Starsil, PerClot, 4DryField Arista, and SuperClot. Conclusion 4Seal is the most versatile in terms of safety and functional properties compared to 4DryField, Arista, PerClot, Starsil, and SuperClot.
Assessment of Genetic Diversity of a Collection of Senna obtusifolia (L.) Irwin and Barneby Using SSRs Markers in Burkina Faso

Sennaobtusifolia (L.) is a plant in the genus Senna that contributes to improving nutritional quality, food security, and better health protection for rural populations. However, very few studies have been devoted to it in Burkina Faso. Consequently, its genetic diversity remains poorly known. Such neglect would lead to the erosion of its genetic resource. The general objective of this study is to contribute to a better knowledge of the genetic diversity of the species in order to be able to issue scientific bases for its conservation, valorization, and genetic improvement. Sixty (60) accessions of Senna obtusifolia were collected in the wild from five provinces of three climatic zones of Burkina Faso. Molecular characterization was carried out using 18 SSR markers. Fifteen were polymorphic microsatellite markers leading one hundred and one (101) alleles in total, with an average of seven (7) alleles per locus. The number of effective alleles was 2.33. Expected heterozygosity, Shannon diversity index, and polymorphism information content averaged 0.47, 1.05, and 0.47. Molecular characterization revealed the existence of genetic diversity within the collection. This diversity has been structured into three genetic groups. Genetic group 3 presents the highest genetic diversity parameters.
Combined MIGS: Comparing Additive Effects of Phacoemulsification, Endocyclophotocoagulation, and Kahook Dual Blade

Purpose Combining two or more MIGS (cMIGS) promises to be more efficacious than single MIGS (sMIGS). This study compared the efficacy of PEcK, which combines Phacoemulsification (Phaco), Endocyclophotocoagulation (ECP), and Kahook dual blade (KDB), relative to both of its constituent sMIGS, Phaco/ECP (Endo Optiks, NJ) and Phaco/KDB (New World Medical, CA) for the first time. Patients and methods Data was collected retrospectively from 1833 visits of 271 patients who underwent PEcK, Phaco/ECP, or Phaco/KDB from 2016–2021 at Massachusetts Eye and Ear. Primary outcomes included Generalized Estimating Equations (GEE) of intraocular pressure (IOP) and medication burden, as well as survival models. Results Mean preoperative IOP was 17.6 ± 5.0 (SD) mmHg on 3.0 ± 1.4 medications in the PEcK group (n = 128), 17.9 ± 5.1 mmHg on 2.2 ± 1.5 medications in the Phaco/ECP group (n = 78), and 16.1 ± 4.3 mmHg on 0.4 ± 1.0 medications in the Phaco/KDB group (n = 65). For more than 36 months, all procedures resulted in significant patterns of IOP and medication reduction (all p < 0.001), before and after statistical adjustment. The reduction pattern in IOP was significantly different when comparing all groups over time and favored PEcK (p = 0.04), but the reduction pattern in medications was not significantly different (p = 0.11). Procedures did not differ in procedural time (p = 0.18) or in survival to maintain ≥20% IOP reduction (p = 0.43) without additional medication or procedure. There was a trend toward significant difference in maintaining IOP ≤ goal IOP that favored PEcK over Phaco/ECP after adjustment (p = 0.09). Conclusion PEcK may confer greater IOP reduction without added procedural time compared to Phaco/ECP and Phaco/KDB in predominantly mild or moderate glaucoma. Further research on cMIGS may benefit from adopting this comparative analysis to constituent MIGS.
Association of digital health literacy and information-seeking behaviors among physicians during COVID-19 in Ethiopia: A cross-sectional study

Background Universal access to health information is a requirement for all global health strategies in the era of pandemics. Getting health information from the internet is a great concern for the quality of patient healthcare. This study aimed to determine the association between digital health literacy and information-seeking behavior among physicians during COVID-19. Methods An institutional-based cross-sectional study was conducted from December to February 2021 with a total sample size of 423. A pretest was performed among physicians before the actual data collection. After the data collection, the data were checked, cleaned, and exported into STATA v. 14. Descriptive statistics, binary logistic regression, and multivariable logistic regression analysis were applied. Then a 95% CI and a p-value of less than 0.05 were used to declare statistical significance. Results The study revealed that 53.81% of physicians had high digital health literacy and 52.46% had high information-seeking behaviors. Health information-seeking behaviors were determined by digital health literacy, which was 2.25 times more likely than those who had low digital health literacy (AOR = 2.25, 95% CI: [1.11–4.57]). Health-related websites (67.5%) were the most common sources of health information, and 63.30% of physicians find digital health literacy easy or very easy to learn. However, 206 (50.92%) find it difficult or very difficult to decide if the information is reliable, verified, and up-to-date. Internet access (AOR = 1.90, 95% CI: [1.16–3.12]), frequency of searching for information (AOR = 5.35, 95% CI: [2.01–14.29]). All were discovered to be significantly associated with physicians’ health information-seeking behaviors. Conclusions Digital health literacy is a key to seeking health information online for appropriate decision-making. Increasing internet access, and providing ICT training, and integrate it into the health information revolution agendas, helping to disseminate health information and provide timely, reliable, and relevant news and genuine information needed for their work.
Exploring the ethics of political PR professionals using moral foundations theory

This paper offers a multidimensional theoretical scheme to analyze professional ethics in the field of political public relations. We suggest investigating the decisions of these professionals using moral foundations theory because human ethical reasoning is contextual, and the examination of ethics in a one-dimensional manner as previous researchers have done overlooks the complexity of the moral choices that such professionals make. The prospects of the proposed theoretical approach are demonstrated on 16 interviews with post-soviet Russian political PR industry leaders that were conducted from March 2018 to April 2020. Our empirical findings show that Russian political PR specialists employ all moral foundations, however, in their narratives the “care/harm” and “authority/respect” foundations were not mentioned very often. Overall, this paper makes a critical contribution to research on professional ethics in political public relations, and it provides important insight into the specifics of moral reasoning in the Russian political PR industry that is insufficiently described in the current literature.