Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnostic Potential of Exosomal HypoxamiRs in the Context of Hypoxia–Sumoylation–HypoxamiRs in Early Onset Preeclampsia at the Preclinical Stage

As the search for non-invasive preclinical markers of preeclampsia (PE) expands, the number of studies on the diagnostic potential of exosomes is growing. Changes in the partial pressure of oxygen caused by impaired uteroplacental perfusion in PE are a powerful inducer of increased production and release of exosomes from cells, which also determine their cargo. At the same time, the expression pattern of oxygen-dependent microRNAs (miRNAs), called “hypoxamiRs”, is modulated, and their packing into exosomes is strictly regulated by sumoylation. In connection therewith, we emphasize the evaluation of exosomal hypoxamiR expression (miR-27b-3p, miR-92b-3p, miR-181a-5p, and miR-186-5p) using quantitative RT-PCR, as well as SUMO 1–4 and UBC9 (by Western blotting), in pregnant women with early-onset PE. The findings show that miR-27b-3p and miR-92b-3p expression was significantly changed at 11–14 and 24–26 weeks of gestation in the blood plasma of pregnant women with early-onset PE, which subsequently manifested. High sensitivity and specificity (AUC = 1) were demonstrated for these miRNAs in the first trimester, and significant correlations with a decrease in hemoglobin (r = 0.71, p = 0.002; r = −0.71, p = 0.002) were established. In mid-pregnancy, the miR-27b-3p expression was found to correlate with an increase in platelets (r = −0.95, p = 0.003), and miR-92b-3p was associated with a decrease in the prothrombin index (r = 0.95, p = 0.003). Specific exomotifs of studied miRNAs were also identified, to which the sumoylated ribonucleoprotein hnRNPA2/B1 binds, carrying out their packaging into exosomes. The expression of conjugated SUMO 1 (p = 0.05), SUMO 2/3/4 (p = 0.03), and UBC9 (p = 0.1) was increased in exosomes at early-onset PE, and the expression of free SUMO 1 (p = 0.03) and SUMO 2/3/4 (p = 0.01) was significantly increased in the placenta, as an adaptive response to hypoxia. Moreover, SUMO 2/3/4 was negatively correlated with miR-27b-3p expression in the placenta. In conclusion, the diagnostic potential of exosomal hypoxamiRs mediated by sumoylation may form the basis for the development of combined specific targets for the treatment of early-onset PE, as hnRNPA2/B1 is a target of miR-27b-3p, and its sumoylation creates miR-27b-3p–hnRNPA2/B1–SUMO 1–4 cross-talk.
Characteristics of Trees Infested by the Invasive Primary Wood-Borer Aromia bungii (Coleoptera: Cerambycidae)

Simple Summary The red-necked longhorn beetle Aromia bungii is an invasive species that causes damage to Rosaceae trees. In introduced countries, tree damage by A. bungii in many regions, such as orchards, forests, and ornamentals, is a serious problem. Information about the characteristics of pest-infested host trees is helpful for efficiently finding and controlling this beetle. In this study, we investigated the characteristics of infested and uninfested ornamental cherry trees in the field, and speculated as to the traits that are important to infestation. As a result, host trees with rough surface bark, large in size, and weakened conditions are prone to damage by A. bungii. These findings aid in the selection of trees or locations to be surveyed for intrusion detection surveillance, where a high probability of damage can be found, among many candidates in intruded areas. Moreover, this knowledge is useful for prioritizing preventive measures for host trees that are more likely to be attacked in already invaded areas. Abstract The expanding distribution and tree damage of the invasive, primary wood-borer Aromia bungii (Coleoptera: Cerambycidae), which kills trees of the Rosaceae family, is a problem in intruded areas. However, the tree characteristics associated with infestation by A. bungii, which are useful for early detection or prioritizing preventive measures, are not well examined. We investigated the presence or absence of tree damage (response variable) in pre- and post- surveys along with tree characteristics (four explanatory variables; bark roughness, size, species, and vigor) on monitoring trees in uninvaded sites (survey for the first trees to be damaged) and already invaded sites (survey for the next trees to be damaged). We evaluated the variables using generalized linear mixed models for each site (i.e., a first trees model and a next trees model). Three tree characteristics (bark roughness, size, and vigor) were included as explanatory variables in both best models, indicating that trees with rough surface bark, large in size, and weakened conditions were more susceptible to A. bungii infestation. The reasons for the difference between the two models (species was only chosen in the next trees model) will be considered in our future work.
Machine learning accurately predicts the multivariate performance phenotype from morphology in lizards

Completing the genotype-to-phenotype map requires rigorous measurement of the entire multivariate organismal phenotype. However, phenotyping on a large scale is not feasible for many kinds of traits, resulting in missing data that can also cause problems for comparative analyses and the assessment of evolutionary trends across species. Measuring the multivariate performance phenotype is especially logistically challenging, and our ability to predict several performance traits from a given morphology is consequently poor. We developed a machine learning model to accurately estimate multivariate performance data from morphology alone by training it on a dataset containing performance and morphology data from 68 lizard species. Our final, stacked model predicts missing performance data accurately at the level of the individual from simple morphological measures. This model performed exceptionally well, even for performance traits that were missing values for >90% of the sampled individuals. Furthermore, incorporating phylogeny did not improve model fit, indicating that the phenotypic data alone preserved sufficient information to predict the performance based on morphological information. This approach can both significantly increase our understanding of performance evolution and act as a bridge to incorporate performance into future work on phenomics.
Augmenting Social Science Research with Multimodal Data Collection: The EZ-MMLA Toolkit

While the majority of social scientists still rely on traditional research instruments (e.g., surveys, self-reports, qualitative observations), multimodal sensing is becoming an emerging methodology for capturing human behaviors. Sensing technology has the potential to complement and enrich traditional measures by providing high frequency data on people’s behavior, cognition and affects. However, there is currently no easy-to-use toolkit for recording multimodal data streams. Existing methodologies rely on the use of physical sensors and custom-written code for accessing sensor data. In this paper, we present the EZ-MMLA toolkit. This toolkit was implemented as a website and provides easy access to multimodal data collection algorithms. One can collect a variety of data modalities: data on users’ attention (eye-tracking), physiological states (heart rate), body posture (skeletal data), gestures (from hand motion), emotions (from facial expressions and speech) and lower-level computer vision algorithms (e.g., fiducial/color tracking). This toolkit can run from any browser and does not require dedicated hardware or programming experience. We compare this toolkit with traditional methods and describe a case study where the EZ-MMLA toolkit was used by aspiring educational researchers in a classroom context. We conclude by discussing future work and other applications of this toolkit, potential limitations and implications.
User experiences of a mobile phone-based health information and surveillance system (mHISS): A case of caregivers of children under-five in rural communities in Ghana

Background The rapid advancement of mobile technology has fueled the use of mobile devices for health interventions and for improving healthcare provision in underserved communities. Despite the potential of mHealth being used as a health information and surveillance tool, its scale-up has been challenging and, in most cases, unable to advance beyond the pilot stage of implementation. The purpose of this study was to explore user experiences of a mobile phone-based interactive voice response (IVR) system among caregivers of children under-five in rural communities in the Asante Akim North District of Ghana. Methods The study adopted an exploratory design. A convenience sampling technique was used to recruit 35 participants who had used an IVR system for at least six months for the study. About 11 in-depth interviews and three focus group discussions were conducted among participants using a semi-structured interview guide. Thematic content analysis was utilized for the analysis of data in this study. Result The system was found to be acceptable, and the attitude of caregivers towards the system was also positive. The study discovered that the mobile phone-based Health Information and Surveillance System (mHISS) was useful for improving access to healthcare, communicating with health professionals, served as a decision support system, and improved caregivers’ awareness about self-management of childhood illnesses. Poor network quality, unstable electricity power supply, and dropped/cut calls served as significant barriers to using the mHISS system. Conclusion The mHISS system was generally acceptable and could help improve access to healthcare and identify children with severe health conditions during outbreaks of diseases.
A Study on 3D Deep Learning-Based Automatic Diagnosis of Nasal Fractures

This paper reported a study on the 3-dimensional deep-learning-based automatic diagnosis of nasal fractures. (1) Background: The nasal bone is the most protuberant feature of the face; therefore, it is highly vulnerable to facial trauma and its fractures are known as the most common facial fractures worldwide. In addition, its adhesion causes rapid deformation, so a clear diagnosis is needed early after fracture onset. (2) Methods: The collected computed tomography images were reconstructed to isotropic voxel data including the whole region of the nasal bone, which are represented in a fixed cubic volume. The configured 3-dimensional input data were then automatically classified by the deep learning of residual neural networks (3D-ResNet34 and ResNet50) with the spatial context information using a single network, whose performance was evaluated by 5-fold cross-validation. (3) Results: The classification of nasal fractures with simple 3D-ResNet34 and ResNet50 networks achieved areas under the receiver operating characteristic curve of 94.5% and 93.4% for binary classification, respectively, both indicating unprecedented high performance in the task. (4) Conclusions: In this paper, it is presented the possibility of automatic nasal bone fracture diagnosis using a 3-dimensional Resnet-based single classification network and it will improve the diagnostic environment with future research.
High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection

Increasing demand for rail transportation results in denser and more high-speed usage of the existing railway network, making new and more advanced vehicle safety systems necessary. Furthermore, high traveling speeds and the large weights of trains lead to long braking distances—all of which necessitates a Long-Range Obstacle Detection (LROD) system, capable of detecting humans and other objects more than 1000 m in advance. According to current research, only a few sensor modalities are capable of reaching this far and recording sufficiently accurate data to distinguish individual objects. The limitation of these sensors, such as a 1D-Light Detection and Ranging (LiDAR), is however a very narrow Field of View (FoV), making it necessary to use high-precision means of orienting to target them at possible areas of interest. To close this research gap, this paper presents a high-precision pointing mechanism, for the use in a future novel railway obstacle detection system, capable of targeting a 1D-LiDAR at humans or objects at the required distance. This approach addresses the challenges of a low target price, restricted access to high-precision machinery and equipment as well as unique requirements of our target application. By combining established elements from 3D printers and Computer Numerical Control (CNC) machines with a double-hinged lever system, simple and low-cost components are capable of precisely orienting an arbitrary sensor platform. The system’s actual pointing accuracy has been evaluated using a controlled, in-door, long-range experiment. The device was able to demonstrate a precision of 6.179 mdeg, which is at the limit of the measurable precision of the designed experiment.
Naloxegol and Postoperative Urinary Retention: A Randomized Trial

Background: Naloxegol antagonizes peripheral opioid-related side effects without preventing opioid-related analgesia. However, the effect of naloxegol on opioid-induced bladder dysfunction remains unknown. Hypothesis: patients given naloxegol have lower residual bladder urine volume than those given placebo. Methods: 136 patients scheduled for elective hip and knee surgery were randomized to oral naloxegol or placebo given the morning of surgery, and on the first two postoperative mornings. Residual urine volume was measured ultrasonographically within 30 min after voiding once in the morning and once in the afternoon for two postoperative days. Opioid-related Symptom Distress Scale (ORSDS), the need for indwelling urinary catheterization, and quality of recovery (QoR) score were secondary outcomes. Results: 67 were randomized to naloxegol and 64 to placebo. We did not identify a significant effect on urine residual volume, with an estimated ratio of geometric means of 0.9 (0.3, 2.6), p = 0.84. There were no significant differences in ORSDS or QoR. There were 19 (29%) patients assigned to naloxegol who needed indwelling urination catheterization versus 7 (11%) patients in the placebo group, p = 0.012. Conclusions: Our results do not support use of naloxegol for postoperative urinary retention after hip and knee surgery.
Hospitalization costs for COVID-19 in Ethiopia: Empirical data and analysis from Addis Ababa’s largest dedicated treatment center

Background The COVID-19 pandemic has caused profound health, economic, and social disruptions globally. We assessed the full costs of hospitalization for COVID-19 disease at Ekka Kotebe COVID-19 treatment center in Addis Ababa, the largest hospital dedicated to COVID-19 patient care in Ethiopia. Methods and findings We retrospectively collected and analysed clinical and cost data on patients admitted to Ekka Kotebe with laboratory-confirmed COVID-19 infections. Cost data included personnel time and salaries, drugs, medical supplies and equipment, facility utilities, and capital costs. Facility medical records were reviewed to assess the average duration of stay by disease severity (either moderate, severe, or critical). The data collected covered the time-period March-November 2020. We then estimated the cost per treated COVID-19 episode, stratified by disease severity, from the perspective of the provider. Over the study period there were 2,543 COVID-19 cases treated at Ekka Kotebe, of which, 235 were critical, 515 were severe, and 1,841 were moderate. The mean patient duration of stay varied from 9.2 days (95% CI: 7.6–10.9; for moderate cases) to 19.2 days (17.9–20.6; for critical cases). The mean cost per treated episode was USD 1,473 (95% CI: 1,197–1,750), but cost varied by disease severity: the mean cost for moderate, severe, and critical cases were USD 1,266 (998–1,534), USD 1,545 (1,413–1,677), and USD 2,637 (1,788–3,486), respectively. Conclusions Clinical management and treatment of COVID-19 patients poses an enormous economic burden to the Ethiopian health system. Such estimates of COVID-19 treatment costs inform financial implications for resource-constrained health systems and reinforce the urgency of implementing effective infection prevention and control policies, including the rapid rollout of COVID-19 vaccines, in low-income countries like Ethiopia.
The Turtle Neck Sign: Identification of Severe Retracted Distal Biceps Tendon Rupture

Background: Chronic tendon retraction subsequent to distal biceps tendon rupture significantly increases repair difficulty and potential for tendon grafting. Biceps tendons that appear short or absent with magnetic resonance imaging (MRI) or that cannot be readily identified at surgery may erroneously be classified as irreparable. These apparent “absent” biceps tendons may actually be retracted and curled up inside the muscle, visually resembling the head-neck of a turtle retracted inside its shell (the “turtle neck sign”). When located, these tendons could be unfolded and repaired primarily. This type of tendon retraction seems to be associated with high-degree ruptures and larcertus fibrosus tears. Purpose: To test the hypothesis that tendon retractions with a turtle neck sign on MRI are more associated with high-degree ruptures and larcertus fibrosus tears versus tendon tears with simple linear retraction. Study Design: Cross-sectional study; Level of evidence, 3. Methods: Retracted distal biceps tendon ruptures on sagittal MRI were categorized as linear retraction or curled-up (turtle neck) retraction. Retraction length, injury severity, and lacertus fibrosus tears were analyzed. Results: The authors retrospectively analyzed the patient records of 85 consecutive traumatic distal biceps tendon ruptures from 2003 to 2019; the final study cohort was 37 patients. Injury-to-surgery timing was as follows: <3 weeks, 43% (16 cases); 3 weeks to 3 months, 32% (12 cases); and >3 months, 24% (9 cases). Overall, 19 patients had linear retraction <7 cm (mean, 3.3 ± 1.9 cm) and 18 patients had a turtle neck retraction ≥7 cm (mean, 9.1 ± 1.6 cm). The injury-to-surgery time (median [± interquartile range]) was 27 days (±90 days) in the linear retraction group and 23 days (±65 days) in the turtle neck retraction group. The turtle neck retraction group had a significantly higher occurrence of abnormal hook test findings, complete distal biceps tendon rupture, and lacertus fibrosus tears compared with the linear retraction group (100% vs 58%, 100% vs 68%, and 100% vs 37%, respectively; P ≤ .02). However, significant repairability differences were not found. Conclusion: Highly retracted distal biceps turtle neck sign tendon ruptures occur frequently in association with high-degree ruptures and lacertus fibrosus tears. The presence of a turtle neck retraction did not affect reparability. Surgeons should be aware of this curled-up retraction to avoid mistaking it for an absent tendon or a muscle-tendon disruption.
Green Extraction of Carotenoids from Fruit and Vegetable Byproducts: A Review

Carotenoids are characterized by a wide range of health-promoting properties. For example, they support the immune system and wound healing process and protect against UV radiation’s harmful effects. Therefore, they are used in the food industry and cosmetics, animal feed, and pharmaceuticals. The main sources of carotenoids are the edible and non-edible parts of fruit and vegetables. Therefore, the extraction of bioactive substances from the by-products of vegetable and fruit processing can greatly reduce food waste. This article describes the latest methods for the extraction of carotenoids from fruit and vegetable byproducts, such as solvent-free extraction—which avoids the costs and risks associated with the use of petrochemical solvents, reduces the impact on the external environment, and additionally increases the purity of the extract—or green extraction using ultrasound and microwaves, which enables a significant improvement in process efficiency and reduction in extraction time. Another method is supercritical extraction with CO2, an ideal supercritical fluid that is non-toxic, inexpensive, readily available, and easily removable from the product, with a high penetration capacity.
A Novel Two-Axis Differential Resonant Accelerometer Based on Graphene with Transmission Beams

In this paper, a novel two-axis differential resonant accelerometer based on graphene with transmission beams is presented. This accelerometer can not only reduce the cross sensitivity, but also overcome the influence of gravity, realizing fast and accurate measurement of the direction and magnitude of acceleration on the horizontal plane. The simulation results show that the critical buckling acceleration is 460 g, the linear range is 0–89 g, while the differential sensitivity is 50,919 Hz/g, which is generally higher than that of the resonant accelerometer reported previously. Thus, the accelerometer belongs to the ultra-high sensitivity accelerometer. In addition, increasing the length and tension of graphene can obviously increase the critical linear acceleration and critical buckling acceleration with the decreasing sensitivity of the accelerometer. Additionally, the size change of the force transfer structure can significantly affect the detection performance. As the etching accuracy reaches the order of 100 nm, the critical buckling acceleration can reach up to 5 × 104 g, with a sensitivity of 250 Hz/g. To sum up, a feasible design of a biaxial graphene resonant accelerometer is proposed in this work, which provides a theoretical reference for the fabrication of a graphene accelerometer with high precision and stability.
Flow and Heat Transfer Performances of Liquid Metal Based Microchannel Heat Sinks under High Temperature Conditions

Developments in applications such as rocket nozzles, miniature nuclear reactors and solar thermal generation pose high-density heat dissipation challenges. In these applications, a large amount heat must be removed in a limited space under high temperature. In order to handle this kind of cooling problem, this paper proposes liquid metal-based microchannel heat sinks. Using a numerical method, the flow and heat transfer performances of liquid metal-based heat sinks with different working fluid types, diverse microchannel cross-section shapes and various inlet velocities were studied. By solving the 3-D steady and conjugate heat transfer model, we found that among all the investigated cases, lithium and circle were the most appropriate choices for the working fluid and microchannel cross-section shape, respectively. Moreover, inlet velocity had a great influence on the flow and heat transfer performances. From 1 m/s to 9 m/s, the pressure drop increased as much as 65 times, and the heat transfer coefficient was enhanced by about 74.35%.