bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transdiagnostic clustering and network analysis for questionnaire-based symptom profiling and drug recommendation in the UK Biobank and a Korean cohort
Authors: Lee Eunjin , Lee Dongbin , Baek Ji Hyun , Kim So Yeon , Park Woong-yang 
Published: February 2024

AbstractClinical decision support systems (CDSSs) play a critical role in enhancing the efficiency of mental health care delivery and promoting patient engagement. Transdiagnostic approaches that utilize raw psychological and biological data enable personalized patient profiling and treatment. This study introduces a CDSS incorporating symptom profiling and drug recommendation for mental health care. Among the UK Biobank cohort, we analyzed 157,348 participants for symptom profiling and 14,358 participants with a drug prescription history for drug recommendation. Among the 1307 patients in the Samsung Medical Center cohort, 842 were eligible for analysis. Symptom profiling utilized demographic and questionnaire data, employing conventional clustering and community detection methods. Identified clusters were explored using diagnostic mapping, feature importance, and scoring. For drug recommendation, we employed cluster- and network-based approaches. The analysis identified nine clusters using k-means clustering and ten clusters with the Louvain method. Clusters were annotated for distinct features related to depression, anxiety, psychosis, drug addiction, and self-harm. For drug recommendation, drug prescription probabilities were retrieved for each cluster. A recommended list of drugs, including antidepressants, antipsychotics, mood stabilizers, and sedative–hypnotics, was provided to individual patients. This CDSS holds promise for efficient personalized mental health care and requires further validation and refinement with larger datasets, serving as a valuable tool for mental healthcare providers.
Tsunami deposits in Tunisia contemporaneous of the large 365 CE Crete earthquake and Mediterranean Sea catastrophic event
Authors: Bahrouni Nejib , Meghraoui Mustapha , Bayraktar Hafize Başak , Lorito Stefano , Zagrarni Mohamed Fawzi , Polonia Alina , Bel Mabrouk Nabil , Kamoun Fekri 
Published: February 2024

AbstractNew field investigations along the East Tunisian coastline reveal sedimentary deposits and damaged localities that may account for a catastrophic event during the late Holocene. North of Sfax city, ~ 3.4 m high cliff coastal marine and alluvial terraces show 20 to 50-cm-thick chaotic layer with sandy coarse gravels mixed with reworked pebbles, broken shells of gastropods and molluscs, organic matter and Roman pottery. The chaotic layer truncates sandy-silty paleosol, covers Roman settlements and is overlain by fire remains, a thin sandy-silty aeolian unit and ~ 1-m-thick alluvial deposits. Charcoal samples collected at 10 cm below and 4 cm above the catastrophic deposits provide radiocarbon dating that brackets the catastrophic unit between 286 and 370 CE. Other historical investigations on the Roman sites of Neapolis (Nabeul), Hadrumete (Sousse), Thyna (Sfax), Meninx in Girba (Djerba), Wadi Ennouili (Gulf of Gabes), and Sabratha (in Libya) evidenced major damage and abandonment of sites in the fourth century (16, 41, 42, 43, 44). The new identification of catastrophic deposits, offshore-onshore correlations with turbidites and modelling of tsunami waves suggest the relationship with the 21 July 365 tsunamigenic earthquake (Mw ~ 8) of west Crete (Greece) and call for a better estimate of tsunami risk on the Mediterranean coastlines.
Machine learning approaches to evaluate infants’ general movements in the writhing stage—a pilot study
Authors: Letzkus Lisa , Pulido J. Vince , Adeyemo Abiodun , Baek Stephen , Zanelli Santina 
Published: February 2024

AbstractThe goals of this study are to describe machine learning techniques employing computer-vision movement algorithms to automatically evaluate infants’ general movements (GMs) in the writhing stage. This is a retrospective study of infants admitted 07/2019 to 11/2021 to a level IV neonatal intensive care unit (NICU). Infant GMs, classified by certified expert, were analyzed in two-steps (1) determination of anatomic key point location using a NICU-trained pose estimation model [accuracy determined using object key point similarity (OKS)]; (2) development of a preliminary movement model to distinguish normal versus cramped-synchronized (CS) GMs using cosine similarity and autocorrelation of major joints. GMs were analyzed using 85 videos from 74 infants; gestational age at birth 28.9 ± 4.1 weeks and postmenstrual age (PMA) at time of video 35.9 ± 4.6 weeks The NICU-trained pose estimation model was more accurate (0.91 ± 0.008 OKS) than a generic model (0.83 ± 0.032 OKS, p < 0.001). Autocorrelation values in the lower limbs were significantly different between normal (5 videos) and CS GMs (5 videos, p < 0.05). These data indicate that automated pose estimation of anatomical key points is feasible in NICU patients and that a NICU-trained model can distinguish between normal and CS GMs. These preliminary data indicate that machine learning techniques may represent a promising tool for earlier CP risk assessment in the writhing stage and prior to hospital discharge.
Impact of motor task conditions on end-point kinematics and trunk movements during goal-directed arm reach
Authors: Kim Bokkyu , Girnis Jaimie , Sweet Vanessa , Nobiling Tobias , Agag Tarek , Neville Christopher 
Published: February 2024

AbstractTask conditions significantly impact human motor control. We investigated how task type, difficulty, and constraints influence the kinematics of goal-directed arm reaching. Non-disabled young adults performed two distinct goal-directed arm reaching tasks: pointing and picking up an object with chopsticks. These tasks were carried out under various conditions, including constrained and unconstrained elbow extension and two different task difficulties. We collected kinematic data using a 3-D motion capture system and analyzed the effects of different task conditions on kinematic variables using linear mixed-effects regression analysis. Our findings revealed statistically significant differences in kinematics between the two tasks. Arm reaching during the picking-up task was slower and exhibited jerkier movements compared to the pointing task. Additionally, when arm reaching was performed with constrained elbow extension, it led to slower and jerkier movements, with an increased involvement of trunk movements compared to the unconstrained condition. These findings show that complex manipulative motor tasks requiring higher hand dexterity necessitate feedback-based control of arm reaching, but simple pointing tasks requiring less hand dexterity do not. In conclusion, our study sheds light on the influence of task conditions on goal-directed arm reaching kinematics and provides valuable insights into the motor control strategies involved in different tasks.
Transcriptomic changes in barley leaves induced by alcohol ethoxylates indicate potential pathways of surfactant detoxification
Authors: Baales Johanna , Zeisler-Diehl Viktoria V. , Kreszies Tino , Klaus Alina , Hochholdinger Frank , Schreiber Lukas 
Published: February 2024

AbstractHardly anything is known regarding the detoxification of surfactants in crop plants, although they are frequently treated with agrochemical formulations. Therefore, we studied transcriptomic changes in barley leaves induced in response to spraying leaf surfaces with two alcohol ethoxylates (AEs). As model surfactants, we selected the monodisperse tetraethylene glycol monododecyl (C12E4) ether and the polydisperse BrijL4. Barley plants were harvested 8 h after spraying with a 0.1% surfactant solution and changes in gene expression were analysed by RNA-sequencing (RNA-Seq). Gene expression was significantly altered in response to both surfactants. With BrijL4 more genes (9724) were differentially expressed compared to C12E4 (6197). Gene families showing pronounced up-regulation were cytochrome P450 enzymes, monooxygenases, ABC-transporters, acetyl- and methyl- transferases, glutathione-S-transferases and glycosyltransferases. These specific changes in gene expression and the postulated function of the corresponding enzymes allowed hypothesizing three potential metabolic pathways of AE detoxification in barley leaves. (i) Up-regulation of P450 cytochrome oxidoreductases suggested a degradation of the lipophilic alkyl residue (dodecyl chain) of the AEs by ω- and β- oxidation. (ii) Alternatively, the polar PEG-chain of AEs could be degraded. (iii) Instead of surfactant degradation, a further pathway of detoxification could be the sequestration of AEs into the vacuole or the apoplast (cell wall). Thus, our results show that AEs lead to pronounced changes in the expression of genes coding for proteins potentially being involved in the detoxification of surfactants.
Utilizing the sublingual form of squalene in COVID-19 patients: a randomized clinical trial
Authors: Ebrahimi Mahmoud , Farhadian Nafiseh , Soflaei Sara Saffar , Amiri Alireza , Tanbakuchi Davoud , Oskooee Rozita Khatamian , Karimi Mohammad 
Published: February 2024

AbstractIn this study, the efficacy of sublingual squalene in decreasing the mortality rate among patients with COVID-19 was investigated. Squalene was extracted from pumpkin seed oil with a novel method. Then, the microemulsion form of squalene was prepared for sublingual usage. In the clinical study, among 850 admitted patients, 602 eligible COVID-19 patients were divided in two groups of control (N = 301) and cases (N = 301) between Nov 2021 and Jan 2022. Groups were statistically the same in terms of age, sex, BMI, lymphocyte count on 1st admission day, hypertension, chronic kidney disease, chronic respiratory disease, immunosuppressive disease, and required standard treatments. The treatment group received five drops of sublingual squalene every 4 h for 5 days plus standard treatment, while the control group received only standard treatment. Patients were followed up for 30 days after discharge from the hospital. The sublingual form of squalene in the microemulsion form was associated with a significant decrease in the mortality rate (p < 0.001), in which 285 (94.7%) cases were alive after one month while 245 (81.4%) controls were alive after 1 month of discharge from the hospital. In addition, squalene appears to be effective in preventing re-hospitalization due to COVID-19 (p < 0.001), with 141 of controls (46.8%) versus 58 cases (19.3%). This study suggests sublingual squalene in the microemulsion as an effective drug for reducing mortality and re-hospitalization rates in COVID-19 patients.Trial Registration Number: IRCT20200927048848N3.
Mosaic quadrivalent influenza vaccine single nanoparticle characterization
Authors: Yang Rong Sylvie , Traver Maria , Barefoot Nathan , Stephens Tyler , Alabanza Casper , Manzella-Lapeira Javier , Zou Guozhang , Wolff Jeremy , Li Yile , Resto Melissa , Shadrick William , Yang Yanhong , Ivleva Vera B. , Tsybovsky Yaroslav , Carlton Kevin , Brzostowski Joseph , Gall Jason G. , Lei Q. Paula 
Published: February 2024

AbstractRecent work by our laboratory and others indicates that co-display of multiple antigens on protein-based nanoparticles may be key to induce cross-reactive antibodies that provide broad protection against disease. To reach the ultimate goal of a universal vaccine for seasonal influenza, a mosaic influenza nanoparticle vaccine (FluMos-v1) was developed for clinical trial (NCT04896086). FluMos-v1 is unique in that it is designed to co-display four recently circulating haemagglutinin (HA) strains; however, current vaccine analysis techniques are limited to nanoparticle population analysis, thus, are unable to determine the valency of an individual nanoparticle. For the first time, we demonstrate by total internal reflection fluorescence microscopy and supportive physical–chemical methods that the co-display of four antigens is indeed achieved in single nanoparticles. Additionally, we have determined percentages of multivalent (mosaic) nanoparticles with four, three, or two HA proteins. The integrated imaging and physicochemical methods we have developed for single nanoparticle multivalency will serve to further understand immunogenicity data from our current FluMos-v1 clinical trial.
A novel interpretable deep transfer learning combining diverse learnable parameters for improved T2D prediction based on single-cell gene regulatory networks
Authors: Alghamdi Sumaya , Turki Turki 
Published: February 2024

AbstractAccurate deep learning (DL) models to predict type 2 diabetes (T2D) are concerned not only with targeting the discrimination task but also with learning useful feature representation. However, existing DL tools are far from perfect and do not provide appropriate interpretation as a guideline to explain and promote superior performance in the target task. Therefore, we provide an interpretable approach for our presented deep transfer learning (DTL) models to overcome such drawbacks, working as follows. We utilize several pre-trained models including SEResNet152, and SEResNeXT101. Then, we transfer knowledge from pre-trained models via keeping the weights in the convolutional base (i.e., feature extraction part) while modifying the classification part with the use of Adam optimizer to deal with classifying healthy controls and T2D based on single-cell gene regulatory network (SCGRN) images. Another DTL models work in a similar manner but just with keeping weights of the bottom layers in the feature extraction unaltered while updating weights of consecutive layers through training from scratch. Experimental results on the whole 224 SCGRN images using five-fold cross-validation show that our model (TFeSEResNeXT101) achieving the highest average balanced accuracy (BAC) of 0.97 and thereby significantly outperforming the baseline that resulted in an average BAC of 0.86. Moreover, the simulation study demonstrated that the superiority is attributed to the distributional conformance of model weight parameters obtained with Adam optimizer when coupled with weights from a pre-trained model.
Iterative pseudo balancing for stem cell microscopy image classification
Authors: Witmer Adam , Bhanu Bir 
Published: February 2024

AbstractMany critical issues arise when training deep neural networks using limited biological datasets. These include overfitting, exploding/vanishing gradients and other inefficiencies which are exacerbated by class imbalances and can affect the overall accuracy of a model. There is a need to develop semi-supervised models that can reduce the need for large, balanced, manually annotated datasets so that researchers can easily employ neural networks for experimental analysis. In this work, Iterative Pseudo Balancing (IPB) is introduced to classify stem cell microscopy images while performing on the fly dataset balancing using a student-teacher meta-pseudo-label framework. In addition, multi-scale patches of multi-label images are incorporated into the network training to provide previously inaccessible image features with both local and global information for effective and efficient learning. The combination of these inputs is shown to increase the classification accuracy of the proposed deep neural network by 3$$\%$$
%
over baseline, which is determined to be statistically significant. This work represents a novel use of pseudo-labeling for data limited settings, which are common in biological image datasets, and highlights the importance of the exhaustive use of available image features for improving performance of semi-supervised networks. The proposed methods can be used to reduce the need for expensive manual dataset annotation and in turn accelerate the pace of scientific research involving non-invasive cellular imaging.
Automated vertical cup-to-disc ratio determination from fundus images for glaucoma detection
Authors: Gao Xiaoyi Raymond , Wu Fengze , Yuhas Phillip T. , Rasel Rafiul Karim , Chiariglione Marion 
Published: February 2024

AbstractGlaucoma is the leading cause of irreversible blindness worldwide. Often asymptomatic for years, this disease can progress significantly before patients become aware of the loss of visual function. Critical examination of the optic nerve through ophthalmoscopy or using fundus images is a crucial component of glaucoma detection before the onset of vision loss. The vertical cup-to-disc ratio (VCDR) is a key structural indicator for glaucoma, as thinning of the superior and inferior neuroretinal rim is a hallmark of the disease. However, manual assessment of fundus images is both time-consuming and subject to variability based on clinician expertise and interpretation. In this study, we develop a robust and accurate automated system employing deep learning (DL) techniques, specifically the YOLOv7 architecture, for the detection of optic disc and optic cup in fundus images and the subsequent calculation of VCDR. We also address the often-overlooked issue of adapting a DL model, initially trained on a specific population (e.g., European), for VCDR estimation in a different population. Our model was initially trained on ten publicly available datasets and subsequently fine-tuned on the REFUGE dataset, which comprises images collected from Chinese patients. The DL-derived VCDR displayed exceptional accuracy, achieving a Pearson correlation coefficient of 0.91 (P = 4.12 × 10–412) and a mean absolute error (MAE) of 0.0347 when compared to assessments by human experts. Our models also surpassed existing approaches on the REFUGE dataset, demonstrating higher Dice similarity coefficients and lower MAEs. Moreover, we developed an optimization approach capable of calibrating DL results for new populations. Our novel approaches for detecting optic discs and optic cups and calculating VCDR, offers clinicians a promising tool that significantly reduces manual workload in image assessment while improving both speed and accuracy. Most importantly, this automated method effectively differentiates between glaucoma and non-glaucoma cases, making it a valuable asset for glaucoma detection.
Apigenin supplementation substantially improves rooster sperm freezability and post-thaw function
Authors: Najafi Abouzar , Mohammadi Hossein , Sharifi Seyed Davood , Rahimi Amin 
Published: February 2024

AbstractThis pioneering research investigated apigenin potential to augment rooster sperm cryosurvival in an extender model. Apigenin is a natural antioxidant flavonoid showing promise for improved post-thaw sperm function. However, its effects on avian semen cryopreservation remain unexplored. This first study supplemented rooster sperm Lake extender with 0, 50, 100, 200, 400 μmol/L apigenin to determine the optimal concentrations for post-thaw quality. Supplementation with 100 μmol/L apigenin resulted in significant enhancements in total motility (from 41.5% up to 71.5%), progressive motility (18.1% to 29.1%) (p < 0.05), membrane integrity (40% to 68%), mitochondrial function (p < 0.001), viability (37% to 62%) and total antioxidant capacity (p < 0.001) compared to the control. It also substantially reduced percentages of abnormal morphology, reactive oxygen species and apoptosis (p < 0.001). Although 200 μmol/L apigenin significantly enhanced some attributes, effects were markedly lower than 100 μmol/L. Higher doses did not improve cryoprotective parameters. This indicates 100 μmol/L as the optimal apigenin concentration. This represents the first report of apigenin protecting rooster sperm from cryodamage. The natural antioxidant improved post-thaw sperm quality, likely by suppressing oxidative stress and apoptosis. Apigenin shows promise for enhancing rooster sperm cryosurvival.
Optimized reamer geometry for controlled reaming of the proximal femur
Authors: Heinecke Markus , Layher Frank , Matziolis Georg 
Published: February 2024

AbstractPreparation of the femoral proximal medullary cavity by reaming is essential for intramedullary nail osteosynthesis and hip revision arthroplasty. The use of reamers sometimes exerts high torsional forces on the bone. Design and direction of rotation of the reamer are potential influencing factors. The aim of this biomechanical study is to evaluate the best combination of a right- or left-cutting reamer with a clockwise- or counterclockwise-rotating insert in terms of preparation and safety. Right- and left-cutting reamers with conical design were each introduced into five synthetic femurs in both clockwise and counterclockwise rotation with constant feed force. A specially constructed test system was used for this series of tests, with which the respective intramedullary channel were reamed step by step. This was then used to determine the required torque. In addition, the feed rate measurement was analyzed using a modified digital caliper. The feed rates of the reamers with rotation in the same direction as the cutting direction were significantly increased compared to rotation in the opposite cutting direction (CCRLC vs. CCRRC 76.8 ± 9.0 mm/s vs. 25.2 ± 8.3 mm/s and CRRC vs. CRLC 54.3 ± 12.3 mm/s vs. 19.3 ± 0.6 mm/s; p < 0.01). In contrast, the mean torque during the reaming process was identical in all four groups. When preparing the proximal femoral medullary cavity, especially in cases with fragile bone structure, the available reamers should be introduced in opposite rotation to the cutting direction to achieve a more controllable feed of the reamer. Left-cutting reamers represent an alternative, using them in the usual clockwise-rotating technique to reduce the risk of complications during reaming.
Comparison of Cas12a and Cas9-mediated mutagenesis in tomato cells
Authors: Slaman Ellen , Kottenhagen Lisanne , de Martines William , Angenent Gerco C. , de Maagd Ruud A. 
Published: February 2024

AbstractCas12a is a promising addition to the CRISPR toolbox, offering versatility due to its TTTV-protospacer adjacent motif (PAM) and the fact that it induces double-stranded breaks (DSBs) with single-stranded overhangs. We characterized Cas12a-mediated genome editing in tomato using high-throughput amplicon sequencing on protoplasts. Of the three tested variants, Lachnospiraceae (Lb) Cas12a was the most efficient. Additionally, we developed an easy and effective Golden-Gate-based system for crRNA cloning. We compared LbCas12a to SpCas9 by investigating on-target efficacy and specificity at 35 overlapping target sites and 57 (LbCas12a) or 100 (SpCas9) predicted off-target sites. We found LbCas12a an efficient, robust addition to SpCas9, with similar overall though target-dependent efficiencies. LbCas12a induced more and larger deletions than SpCas9, which can be advantageous for specific genome editing applications. Off-target activity for LbCas12a was found at 10 out of 57 investigated sites. One or two mismatches were present distal from the PAM in all cases. We conclude that Cas12a-mediated genome editing is generally precise as long as such off-target sites can be avoided. In conclusion, we have determined the mutation pattern and efficacy of Cas12a-mediated CRISPR mutagenesis in tomato and developed a cloning system for the routine application of Cas12a for tomato genome editing.