Miracle-dz/UniFAR-FTUs huggingface dataset:
Neisseria gonorrhoeae MtrCDE Efflux Pump During In Vivo Experimental Genital Tract Infection in Men and Mice Reveals the Presence of Within-Host Colonization Bottleneck

The MtrCDE efflux pump of Neisseria gonorrhoeae exports a wide range of antimicrobial compounds that the gonococcus encounters at mucosal surfaces during colonization and infection. Here, we evaluate the role of this efflux pump system in strain FA1090 in human male urethral infection with a Controlled Human Infection Model. Using the strategy of competitive multi-strain infection with wild-type FA1090 and an isogenic mutant strain that does not contain a functional MtrCDE pump, we found that the presence of the efflux pump during human experimental infection did not confer a competitive advantage. This finding is in contrast to previous findings in female mice, which demonstrated that gonococci of strain FA19 lacking a functional MtrCDE pump had a significantly reduced fitness compared to the wild type strain in the lower genital tract of female mice. We conducted competitive infections in female mice with FA19 and FA1090 strains, including mutants that do not assemble a functional Mtr efflux pump, demonstrating the fitness advantage provided byt the MtrCDE efflux pump during infection of mice is strain dependent. Our data indicate that new gonorrhea treatment strategies targeting the MtrCDE efflux pump functions may not be universally efficacious in naturally occurring infections. Owing to the equal fitness of FA1090 strains in men, our experiments unexpectedly demonstrated the likely presence of an early colonization bottleneck of N. gonorrhoeae in the human male urethra.
Prolonged grief during and beyond the pandemic: factors associated with levels of grief in a four time-point longitudinal survey of people bereaved in the first year of the COVID-19 pandemic

Background The COVID-19 pandemic has been a devastating and enduring mass-bereavement event, with uniquely difficult sets of circumstances experienced by people bereaved at this time. However, little is known about the long-term consequences of these experiences, including the prevalence of Prolonged Grief Disorder (PGD) and other conditions in pandemic-bereaved populations. Methods A longitudinal survey of people bereaved in the UK between 16 March 2020 and 2 January 2021, with data collected at baseline (n=711), c. 8 (n=383), 13 (n=295) and 25 (n=185) months post-bereavement. Using measures of Prolonged Grief Disorder (PGD) (Traumatic Grief Inventory), grief vulnerability (Adult Attitude to Grief Scale), and social support (Inventory of Social Support), this analysis examines how participant characteristics, characteristics of the deceased and pandemic-related circumstances (e.g. restricted visiting, social isolation, social support) are associated with grief outcomes, with a focus on levels of PGD. Results At baseline, 628 (88.6%) of participants were female, with a mean age of 49.5 (SD 12.9). 311 (43.8%) deaths were from confirmed/suspected COVID-19. Sample demographics were relatively stable across time points. 34.6% of participants met the cut-off for indicated PGD at c. 13 months bereaved and 28.6% at final follow-up. Social isolation and loneliness in early bereavement and lack of social support over time strongly contributed to higher levels of PGD, whilst feeling well supported by healthcare professionals following the death was associated with reduced levels of PGD. Characteristics of the deceased most strongly associated with lower PGD scores, were a more distant relationship (e.g. death of a grandparent), an expected death and death occurring in a care-home. Participant characteristics associated with higher levels of PGD included low level of formal education and existence of medical conditions. Conclusion Results suggest higher than expected levels of PGD compared with pre-pandemic times, with important implications for bereavement policy, provision and practice now (e.g. strengthening of social and specialist support) and in preparedness for future pandemics and mass-bereavement events (e.g. guidance on infection control measures and rapid support responses).
The Greek version of the Richards-Campbell Sleep Questionnaire: Reliability and validity assessment

Aim: To translate the RCSQ into Greek and to determine the reliability and validity of the Greek version of the RCSQ as a measure of sleep among ICU patients in a Greek hospital. Methods: This study investigated the nighttime sleep of 50 patients admitted to the general ICU of General Hospital of Athens G. Gennimatas between January 2022 and March 2023. The RCSQ questionnaire was used for the present study with the author's written permission. All guidelines for translating and adapting psychometric scales were followed for translating the RCSQ into Greek. Demographic, and clinical characteristics (sex, age, days in the hospital, days on mechanical ventilation, days on spontaneous breathing, whether they underwent a tracheotomy and the type of tracheotomy, and whether they received a mild sedation formulation to promote sleep) were collected from the participants. Reliability was tested using Cronbach correlation coefficient a. Results: The Cronbach correlation coefficient a was calculated at 0.906 revealing excellent reliability of the RCSQ. No question removal significantly increased the coefficient value. Conclusion: The Greek version of the Richards Campbell Sleep Questionnaire could be an alternative to polysomnography when assessing sleep quality in intensive care unit patients. Keywords: Sleep in the intensive care unit, polysomnography, interventions on sleep
Towards Recognition of Human Actions in Collaborative Tasks with Robots: Extending Action Recognition with Tool Recognition Methods

This paper presents a novel method for online tool recognition in manual assembly processes. The goal was to develop and implement a method that can be integrated with existing Human Action Recognition (HAR) methods in collaborative tasks. We examined the state-of-the-art for progress detection in manual assembly via HAR-based methods, as well as visual tool-recognition approaches. A novel online tool-recognition pipeline for handheld tools is introduced, utilizing a two-stage approach. First, a Region Of Interest (ROI) was extracted by determining the wrist position using skeletal data. Afterward, this ROI was cropped, and the tool located within this ROI was classified. This pipeline enabled several algorithms for object recognition and demonstrated the generalizability of our approach. An extensive training dataset for tool-recognition purposes is presented, which was evaluated with two image-classification approaches. An offline pipeline evaluation was performed with twelve tool classes. Additionally, various online tests were conducted covering different aspects of this vision application, such as two assembly scenarios, unknown instances of known classes, as well as challenging backgrounds. The introduced pipeline was competitive with other approaches regarding prediction accuracy, robustness, diversity, extendability/flexibility, and online capability.
Scalable Lightweight IoT-Based Smart Weather Measurement System

The Internet of Things (IoT) plays a critical role in remotely monitoring a wide variety of different application sectors, including agriculture, building, and energy. The wind turbine energy generator (WTEG) is a real-world application that can take advantage of IoT technologies, such as a low-cost weather station, where human activities can be significantly affected by enhancing the production of clean energy based on the known direction of the wind. Meanwhile, common weather stations are neither affordable nor customizable for specific applications. Moreover, due to weather forecast changes over time and location within the same city, it is not efficient to rely on a limited number of weather stations that may be located far away from a recipient’s location. Therefore, in this paper, we focus on presenting a low-cost weather station that relies on an artificial intelligence (AI) algorithm that can be distributed across a WTEG area with minimal cost. The proposed study measures multiple weather parameters, such as wind direction, wind velocity (WV), temperature, pressure, mean sea level, and relative humidity to provide current measurements to recipients and AI-based forecasts. In addition, the proposed study consists of several heterogeneous nodes and a controller for each station in a target area. The collected data can be transmitted through Bluetooth low energy (BLE). The experimental results reveal that the proposed study matches the standard of the National Meteorological Center (NMC), with a nowcast measurement of 95% accuracy for WV and 92% for wind direction (WD).
Subjective Quality Assessment of V-PCC-Compressed Dynamic Point Clouds Degraded by Packet Losses

This article describes an empirical exploration on the effect of information loss affecting compressed representations of dynamic point clouds on the subjective quality of the reconstructed point clouds. The study involved compressing a set of test dynamic point clouds using the MPEG V-PCC (Video-based Point Cloud Compression) codec at 5 different levels of compression and applying simulated packet losses with three packet loss rates (0.5%, 1% and 2%) to the V-PCC sub-bitstreams prior to decoding and reconstructing the dynamic point clouds. The recovered dynamic point clouds qualities were then assessed by human observers in experiments conducted at two research laboratories in Croatia and Portugal, to collect MOS (Mean Opinion Score) values. These scores were subject to a set of statistical analyses to measure the degree of correlation of the data from the two laboratories, as well as the degree of correlation between the MOS values and a selection of objective quality measures, while taking into account compression level and packet loss rates. The subjective quality measures considered, all of the full-reference type, included point cloud specific measures, as well as others adapted from image and video quality measures. In the case of image-based quality measures, FSIM (Feature Similarity index), MSE (Mean Squared Error), and SSIM (Structural Similarity index) yielded the highest correlation with subjective scores in both laboratories, while PCQM (Point Cloud Quality Metric) showed the highest correlation among all point cloud-specific objective measures. The study showed that even 0.5% packet loss rates reduce the decoded point clouds subjective quality by more than 1 to 1.5 MOS scale units, pointing out the need to adequately protect the bitstreams against losses. The results also showed that the degradations in V-PCC occupancy and geometry sub-bitstreams have significantly higher (negative) impact on decoded point cloud subjective quality than degradations of the attribute sub-bitstream.
Open Database for Accurate Upper-Limb Intent Detection Using Electromyography and Reliable Extreme Learning Machines

Surface Electromyography (sEMG) signal processing has a disruptive technology potential to enable a natural human interface with artificial limbs and assistive devices. However, this biosignal real-time control interface still presents several restrictions such as control limitations due to a lack of reliable signal prediction and standards for signal processing among research groups. Our paper aims to present and validate our sEMG database through the signal classification performed by the reliable forms of our Extreme Learning Machines (ELM) classifiers, used to maintain a more consistent signal classification. To perform the signal processing, we explore the use of a stochastic filter based on the Antonyan Vardan Transform (AVT) in combination with two variations of our Reliable classifiers (denoted R-ELM and R-Regularized ELM (RELM), respectively), to derive a reliability metric from the system, which autonomously selects the most reliable samples for the signal classification. To validate and compare our database and classifiers with related papers, we performed the classification of the whole of Databases 1, 2, and 6 (DB1, DB2, and DB6) of the NINAProdatabase. Our database presented consistent results, while the reliable forms of ELM classifiers matched or outperformed related papers, reaching average accuracies higher than 99% for the IEEdatabase, while average accuracies of 75.1%, 79.77%, and 69.83% were achieved for NINAPro DB1, DB2, and DB6, respectively.
AlphaFold2 and Deep Learning for Elucidating Enzyme Conformational Flexibility and Its Application for Design

The recent success of AlphaFold2 (AF2) and other deep learning (DL) tools in accurately predicting the folded three-dimensional (3D) structure of proteins and enzymes has revolutionized the structural biology and protein design fields. The 3D structure indeed reveals key information on the arrangement of the catalytic machinery of enzymes and which structural elements gate the active site pocket. However, comprehending enzymatic activity requires a detailed knowledge of the chemical steps involved along the catalytic cycle and the exploration of the multiple thermally accessible conformations that enzymes adopt when in solution. In this Perspective, some of the recent studies showing the potential of AF2 in elucidating the conformational landscape of enzymes are provided. Selected examples of the key developments of AF2-based and DL methods for protein design are discussed, as well as a few enzyme design cases. These studies show the potential of AF2 and DL for allowing the routine computational design of efficient enzymes.
Comparative Evaluation of the Effect of Two Platelet Concentrates (a-PRF and L-PRF) on the Cellular Activity of Pre-osteoblastic MG-63 Cell Line: An in vitro Study

Statement of the Problem: Currently, the reconstruction of bone defects with new platelet concentrates is considered a significant challenge in periodontics. Purpose: This study aimed to evaluate advanced- platelet rich fibrin (A-PRF) and leukocyte- and platelet rich fibrin’s (L-PRF) effects on the proliferation and differentiation of MG-63 cells. Materials and Method: In this in vitro study, blood samples of five healthy non-smoking volunteers were collected and immediately centrifuged according to the two protocols of Choukroun and Ghanaati, without adding any anticoagulants, to prepare L-PRF and A-PRF. After freezing the clots for one hour, they were crushed and centrifuged once more. After culturing MG-63 cells, the effects of 20%, 10%, 1%, and 0.5% concentrations of A-PRF and L-PRF extracts on cell proliferation and mineralization were evaluated by methyl thiazolyl tetrazolium (MTT) assay and Alizarin Red staining, respectively. Results: Generally, survival and proliferation in the L-PRF group at both time intervals were higher than the A-PRF group and increased with increasing the extract concentration. However, in the A-PRF group, there were no significant differences between the different concentrations, and only the number of cells increased over time. After three days, in the study on mineralization, nodule formation was observed only in the positive control group (osteogenic). In seven days, mineralized nodules were formed in all groups with different concentrations of A-PRF, but not in any of the L-PRF groups. Conclusion: According to the results, L-PRF increased proliferation, and A-PRF exerted a positive effect on the differentiation of MG-63 cells.
Image-Evoked Emotion Recognition for Hearing-Impaired Subjects with EEG Signals

In recent years, there has been a growing interest in the study of emotion recognition through electroencephalogram (EEG) signals. One particular group of interest are individuals with hearing impairments, who may have a bias towards certain types of information when communicating with those in their environment. To address this, our study collected EEG signals from both hearing-impaired and non-hearing-impaired subjects while they viewed pictures of emotional faces for emotion recognition. Four kinds of feature matrices, symmetry difference, and symmetry quotient based on original signal and differential entropy (DE) were constructed, respectively, to extract the spatial domain information. The multi-axis self-attention classification model was proposed, which consists of local attention and global attention, combining the attention model with convolution through a novel architectural element for feature classification. Three-classification (positive, neutral, negative) and five-classification (happy, neutral, sad, angry, fearful) tasks of emotion recognition were carried out. The experimental results show that the proposed method is superior to the original feature method, and the multi-feature fusion achieved a good effect in both hearing-impaired and non-hearing-impaired subjects. The average classification accuracy for hearing-impaired subjects and non-hearing-impaired subjects was 70.2% (three-classification) and 50.15% (five-classification), and 72.05% (three-classification) and 51.53% (five-classification), respectively. In addition, by exploring the brain topography of different emotions, we found that the discriminative brain regions of the hearing-impaired subjects were also distributed in the parietal lobe, unlike those of the non-hearing-impaired subjects.
Grading lumbar disc degeneration: a comparison between low- and high-field MRI

Background More advanced disc degeneration on magnetic resonance imaging (MRI) is found in individuals with low back pain. However, it is unclear whether this grading is independent of the scanner’s field strength. Purpose To compare disc degeneration on high- versus low-field MRI. Material and Methods Low back pain patients were enrolled to undergo high-field (3 T) MRI, followed by low-field (0.25 T) MRI of the lumbar spine within 3 h. Three radiologists graded the disc degeneration on Pfirrmann’s grading scale with a hiatus of 3 months. A subsample was regraded 6 months later. Reproducibility was measured by weighted kappa statistics (using PROC FREQ statement with AGREE in the TABLES statement for SAS), absolute agreement (i.e. 1:1 agreement/the total number) and the difference in the prevalence (McNemar test). Results Moderate to substantial agreement (κ = 0.52–0.62) and absolute agreement of 43.8–66.1% were found between field strengths. Low-field MRI tended to have numerically higher and lower grades than high-field MRI resulting in a significant difference in the prevalence of grades (p < 0.001). Both field strengths resulted in a moderate to substantial inter-reader agreement (low-field: κ = 0.63, 0.63, 0.54 and high-field: κ = 0.55, 0.43, 0.53) and intra-reader agreement (high-field: κ = 0.57, 0.77, 0.67 and low-field: κ = 0.51, 0.50, 0.70). Only, the reader with the shortest experience had better agreement with high-field compared to low-field. Conclusions There were a significant difference in the prevalence of disc degeneration grading between 0.25 T and 3 T MRI. Therefore, field strength should be taken into consideration when comparing studies using disc degeneration grading as an outcome.
The Reliability of PCL/Anti-VEGF Electrospun Scaffolds to Support Limbal Stem Cells for Corneal Repair

Since only few reported studies propose anti-vascular endothelial growth factor (anti-VEGF) delivery through electrospun scaffolds, this study greatly contributes to the potential prevention of patient’s vision loss, as it explores electrospun polycaprolactone (PCL) coated with anti-VEGF for the blockage of abnormal cornea vascularization. In terms of physicochemical properties, the biological component increased the PCL scaffold fiber diameter (by ~24%) and pore area (by ~82%), while ut slightly reduced its total porosity as the anti-VEGF solution filled the voids of the microfibrous structure. The addition of the anti-VEGF increased the scaffold stiffness almost three-fold at both strains of 5 and 10%, as well as its biodegradation rate (~36% after 60 days) with a sustained release profile after Day 4 of phosphate buffered saline incubation. In terms of scaffold application function, the PCL/Anti-VEGF scaffold proved to be more favorable for the adhesion of cultured limbal stem cells (LSCs); this was confirmed by the SEM images, where the cells showed flat and elongated conformations. Further support of the LSC growth and proliferation was confirmed by the identified p63 and CK3 markers after cell staining. These results demonstrate the advantageous effect of the surface-adsorbed anti-VEGF to stop vision loss and help damaged corneal tissue repair.
Long-Term Change in both Dietary Insulinemic and Inflammatory Potential Is Associated with Weight Gain in Adult Women and Men.

BACKGROUND The influence of long-term dietary patterns on weight gain and the underlying potential biological mechanisms are not fully understood. OBJECTIVE We prospectively examined the association of changes in 2 empirical hypothesis-oriented dietary patterns (insulinemic and inflammatory) and weight gain over 24 y at 4-y intervals. METHODS We followed 54,397 women in the Nurses' Health Study and 33,043 men in the Health Professionals Follow-Up Study (1986-2010), and computed the empirical dietary index for hyperinsulinemia (EDIH) and empirical dietary inflammatory pattern (EDIP) scores from food frequency questionnaires administered every 4 y. Both scores are weighted sums of 18 food groups, which characterize dietary insulinemic or inflammatory potential based on plasma levels of insulin response or inflammatory biomarkers. We used multivariable-adjusted linear regression to examine 4-y changes in the dietary scores and weight change within the same period. RESULTS The mean baseline body mass index (BMI, in kg/m2) was 25.4. Compared with participants who made minimal dietary changes (quintile 3) over 6 4-y periods; participants who changed their diets toward lower insulinemic or inflammatory potential (quintile 1) gained significantly less weight (in kilograms per 4 y) independent of total energy intake, BMI, physical activity, and smoking status: EDIH: -0.65 (95% CI: -0.73, -0.57), EDIP: -0.29 (-0.37, -0.21) among women; and EDIH: -0.60 (-0.71, -0.49), EDIP: -0.19 (-0.27, -0.07) among men. In contrast, those who changed their diets toward higher insulinemic or inflammatory potential (quintile 5) gained significantly more weight: EDIH: 0.43 (0.36, 0.51), EDIP: 0.15 (0.07, 0.23) among women; and EDIH: 0.49 (0.38, 0.59), EDIP: 0.22 (0.11, 0.33) among men (P-trend < 0.0001 for all comparisons). Associations were stronger among individuals who were overweight or obese, younger, less physically active, and had never smoked. CONCLUSIONS High dietary insulinemic and inflammatory potential is associated with substantial long-term weight gain in adult men and women independent of total energy intake. Dietary patterns with low insulinemic and inflammatory potential may aid in weight gain prevention.
Global gradient bounds for the parabolic p‐Laplacian system

A by now classical result due to DiBenedetto states that the spatial gradient of solutions to the parabolic p ‐Laplacian system is locally Hölder continuous in the interior. However, the boundary regularity is not yet well understood. In this paper, we prove a boundary L∞ ‐estimate for the spatial gradient Du of solutions to the parabolic p ‐Laplacian system ∂tu−div(|Du|p−2Du)=0inΩ×(0,T) with non‐homogeneous boundary data for p⩾2 , together with a quantitative estimate. In particular, this implies the global Lipschitz regularity of solutions. The result continues to hold for the so‐called asymptotically regular parabolic systems.