bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated body organ segmentation, volumetry and population-averaged atlas for 3D motion-corrected T2-weighted fetal body MRI
Authors: Uus Alena U. , Hall Megan , Grigorescu Irina , Avena Zampieri Carla , Egloff Collado Alexia , Payette Kelly , Matthew Jacqueline , Kyriakopoulou Vanessa , Hajnal Joseph V. , Hutter Jana , Rutherford Mary A. , Deprez Maria , Story Lisa 
Published: March 2024

AbstractStructural fetal body MRI provides true 3D information required for volumetry of fetal organs. However, current clinical and research practice primarily relies on manual slice-wise segmentation of raw T2-weighted stacks, which is time consuming, subject to inter- and intra-observer bias and affected by motion-corruption. Furthermore, there are no existing standard guidelines defining a universal approach to parcellation of fetal organs. This work produces the first parcellation protocol of the fetal body organs for motion-corrected 3D fetal body MRI. It includes 10 organ ROIs relevant to fetal quantitative volumetry studies. We also introduce the first population-averaged T2w MRI atlas of the fetal body. The protocol was used as a basis for training of a neural network for automated organ segmentation. It showed robust performance for different gestational ages. This solution minimises the need for manual editing and significantly reduces time. The general feasibility of the proposed pipeline was also assessed by analysis of organ growth charts created from automated parcellations of 91 normal control 3T MRI datasets that showed expected increase in volumetry during 22–38 weeks gestational age range.
Normative values of motor performance and their relationship with BMI status in Hong Kong preschoolers
Authors: Yip Ka-Man , So Hung-Kwan , Tung Keith T. S. , Wong Rosa S. , Tso Winnie W. Y. , Wong Ian C. K. , Yam Jason C. , Kwan Mike Y. W. , Louie Lobo H. T. , Lee Albert , Wong Wilfred H. S. , Hui Lai-Ling , Nelson E. A. S. , Ip Patrick 
Published: March 2024

AbstractThis study aimed to establish sex- and age-specific reference values for motor performance (MP) in Hong Kong preschoolers aged 3–5 years old and examine the relationship between MP and BMI status. A cross-sectional study was conducted among 5579 preschoolers in Hong Kong. Three MP tests were administered, and height and weight information were collected. GAMLSS was used to compute the normative values of the motor tests. Boys outperformed girls in activities requiring muscle strength and power, while girls outperformed boys in activities requiring balance and coordination. The MP scores increased with age for both overarm beanbag throw and standing long jump for both sexes, while the one-leg balance scores showed larger differences between P50 and P95 in older preschoolers. Children with excessive weight performed worse in standing long jump and one-leg balance compared to their healthy weight peers. This study provides valuable information on the MP of preschoolers in Hong Kong, including sex- and age-specific reference values and the association between BMI status and MP scores. These findings can serve as a reference for future studies and clinical practice and highlight the importance of promoting motor skill development in preschoolers, particularly those who are overweight or obese.
Relationship between prediction accuracy and uncertainty in compound potency prediction using deep neural networks and control models
Authors: Roth Jannik P. , Bajorath Jürgen 
Published: March 2024

AbstractThe assessment of prediction variance or uncertainty contributes to the evaluation of machine learning models. In molecular machine learning, uncertainty quantification is an evolving area of research where currently no standard approaches or general guidelines are available. We have carried out a detailed analysis of deep neural network variants and simple control models for compound potency prediction to study relationships between prediction accuracy and uncertainty. For comparably accurate predictions obtained with models of different complexity, highly variable prediction uncertainties were detected using different metrics. Furthermore, a strong dependence of prediction characteristics and uncertainties on potency levels of test compounds was observed, often leading to over- or under-confident model decisions with respect to the expected variance of predictions. Moreover, neural network models responded very differently to training set modifications. Taken together, our findings indicate that there is only little, if any correlation between compound potency prediction accuracy and uncertainty, especially for deep neural network models, when predictions are assessed on the basis of currently used metrics for uncertainty quantification.
Dynamic multi-pinhole collimated brain SPECT of Parkinson’s disease by [123I]FP-CIT: a feasibility study of fSPECT
Authors: Fredensborg Filip L. H. , Thilsing-Hansen Kasper , Simonsen Jane A. , Grupe Peter , Farahani Ziba A. , Andersen Christian W. , Gjedde Albert , Hvidsten Svend 
Published: March 2024

AbstractWe investigated the feasibility of using a dopamine transporter (DaT) tracer ligand ([123I]FP-CIT) along with novel multi-pinhole brain collimators for dynamic brain single photon emission computed tomography (SPECT) in suspected Parkinson's disease patients. Thirteen patients underwent dynamic tracer acquisitions before standard imaging. Uptake values were corrected for partial volume effects. Specific binding ratio (SBRcalc) was calculated, reflecting binding potential relative to non-displaceable binding (BPND) in the cortex. Additional pharmacokinetic parameters (BPND, R1, k2) were estimated using the simplified reference tissue model, revealing differences between Kahraman low-score (LS) and high-score (HS) groups. Results showed increasing striatal tracer uptake until 100 min post-injection, with consistent values afterward. Uptake and SBRcalc ratios matched visual assessment. LS patients had lower putamen than caudate nucleus tracer uptake, decreased BPND values, while R1 and k2 values were comparable to HS patients. In conclusion, dynamic multi-pinhole SPECT using DaT tracer with the extraction of pharmacokinetic parameters is feasible and could help enable early differentiation of reduced and normal DaT values.
Mapping of the central sulcus using non-invasive ultra-high-density brain recordings
Authors: Schreiner Leonhard , Jordan Michael , Sieghartsleitner Sebastian , Kapeller Christoph , Pretl Harald , Kamada Kyousuke , Asman Priscella , Ince Nuri F. , Miller Kai J. , Guger Christoph 
Published: March 2024

AbstractBrain mapping is vital in understanding the brain’s functional organization. Electroencephalography (EEG) is one of the most widely used brain mapping approaches, primarily because it is non-invasive, inexpensive, straightforward, and effective. Increasing the electrode density in EEG systems provides more neural information and can thereby enable more detailed and nuanced mapping procedures. Here, we show that the central sulcus can be clearly delineated using a novel ultra-high-density EEG system (uHD EEG) and somatosensory evoked potentials (SSEPs). This uHD EEG records from 256 channels with an inter-electrode distance of 8.6 mm and an electrode diameter of 5.9 mm. Reconstructed head models were generated from T1-weighted MRI scans, and electrode positions were co-registered to these models to create topographical plots of brain activity. EEG data were first analyzed with peak detection methods and then classified using unsupervised spectral clustering. Our topography plots of the spatial distribution from the SSEPs clearly delineate a division between channels above the somatosensory and motor cortex, thereby localizing the central sulcus. Individual EEG channels could be correctly classified as anterior or posterior to the central sulcus with 95.2% accuracy, which is comparable to accuracies from invasive intracranial recordings. Our findings demonstrate that uHD EEG can resolve the electrophysiological signatures of functional representation in the brain at a level previously only seen from surgically implanted electrodes. This novel approach could benefit numerous applications, including research, neurosurgical mapping, clinical monitoring, detection of conscious function, brain–computer interfacing (BCI), rehabilitation, and mental health.
Optimizing ensemble U-Net architectures for robust coronary vessel segmentation in angiographic images
Authors: Chang Shih-Sheng , Lin Ching-Ting , Wang Wei-Chun , Hsu Kai-Cheng , Wu Ya-Lun , Liu Chia-Hao , Fann Yang C. 
Published: March 2024

AbstractAutomated coronary angiography assessment requires precise vessel segmentation, a task complicated by uneven contrast filling and background noise. Our research introduces an ensemble U-Net model, SE-RegUNet, designed to accurately segment coronary vessels using 100 labeled angiographies from angiographic images. SE-RegUNet incorporates RegNet encoders and squeeze-and-excitation blocks to enhance feature extraction. A dual-phase image preprocessing strategy further improves the model's performance, employing unsharp masking and contrast-limited adaptive histogram equalization. Following fivefold cross-validation and Ranger21 optimization, the SE-RegUNet 4GF model emerged as the most effective, evidenced by performance metrics such as a Dice score of 0.72 and an accuracy of 0.97. Its potential for real-world application is highlighted by its ability to process images at 41.6 frames per second. External validation on the DCA1 dataset demonstrated the model's consistent robustness, achieving a Dice score of 0.76 and an accuracy of 0.97. The SE-RegUNet 4GF model's precision in segmenting blood vessels in coronary angiographies showcases its remarkable efficiency and accuracy. However, further development and clinical testing are necessary before it can be routinely implemented in medical practice.
Optimizing chili production in drought stress: combining Zn-quantum dot biochar and proline for improved growth and yield
Authors: Hareem Misbah , Danish Subhan , Pervez Mahnoor , Irshad Usman , Fahad Shah , Dawar Khadim , Alharbi Sulaiman Ali , Ansari Mohammad Javed , Datta Rahul 
Published: March 2024

AbstractThe reduction in crop productivity due to drought stress, is a major concern in agriculture. Drought stress usually disrupts photosynthesis by triggering oxidative stress and generating reactive oxygen species (ROS). The use of zinc-quantum dot biochar (ZQDB) and proline (Pro) can be effective techniques to overcome this issue. Biochar has the potential to improve the water use efficiency while proline can play an imperative role in minimization of adverse impacts of ROS Proline, functioning as an osmotic protector, efficiently mitigates the adverse effects of heavy metals on plants by maintaining cellular structure, scavenging free radicals, and ensuring the stability of cellular integrity. That’s why current study explored the impact of ZQDB and proline on chili growth under drought stress. Four treatments, i.e., control, 0.4%ZQDB, 0.1 mM Pro, and 0.4%ZQDB + Pro, were applied in 4 replications following the complete randomized design. Results exhibited that 0.4%ZQDB + Pro caused an increases in chili plant dry weight (29.28%), plant height (28.12%), fruit length (29.20%), fruit girth (59.81%), and fruit yield (55.78%) over control under drought stress. A significant increment in chlorophyll a (18.97%), chlorophyll b (49.02%), and total chlorophyll (26.67%), compared to control under drought stress, confirmed the effectiveness of 0.4%ZQDB + Pro. Furthermore, improvement in leaves N, P, and K concentration over control validated the efficacy of 0.4%ZQDB + Pro against drought stress. In conclusion, 0.4%ZQDB + Pro can mitigate drought stress in chili. More investigations are suggested to declare 0.4%ZQDB + Pro as promising amendment for mitigation of drought stress in other crops as well under changing climatic situations.
Clinical and laboratory characteristics of patients hospitalized with severe COVID-19 in New Orleans, August 2020 to September 2021
Authors: Drouin Arnaud , Plumb Ian D. , McCullough Matthew , James Gist Jade , Liu Sharon , Theberge Marc , Katz Joshua , Moreida Matthew , Flaherty Shelby , Chatwani Bhoomija , Briggs Hagen Melissa , Midgley Claire M. , Fusco Dahlene 
Published: March 2024

AbstractLouisiana experienced high morbidity and mortality from COVID-19. To assess possible explanatory factors, we conducted a cohort study (ClinSeqSer) of patients hospitalized with COVID-19 in New Orleans during August 2020–September 2021. Following enrollment, we reviewed medical charts, and performed SARS-CoV-2 RT-PCR testing on nasal and saliva specimens. We used multivariable logistic regression to assess associations between patient characteristics and severe illness, defined as ≥ 6 L/min oxygen or intubation. Among 456 patients, median age was 56 years, 277 (60.5%) were Black non-Hispanic, 436 (95.2%) had underlying health conditions, and 358 were unvaccinated (92.0% of 389 verified). Overall, 187 patients (40.1%) had severe illness; 60 (13.1%) died during admission. In multivariable models, severe illness was associated with age ≥ 65 years (OR 2.08, 95% CI 1.22–3.56), hospitalization > 5 days after illness onset (OR 1.49, 95% CI 1.01–2.21), and SARS CoV-2 cycle threshold (Ct) result of < 32 in saliva (OR 4.79, 95% CI 1.22–18.77). Among patients who were predominantly Black non-Hispanic, unvaccinated and with underlying health conditions, approximately 1 in 3 patients had severe COVID-19. Older age and delayed time to admission might have contributed to high case-severity. An association between case-severity and low Ct value in saliva warrants further investigation.
Trace metals and nutrient analysis of marine fish species from the Gwadar coast
Authors: Khawar Masooma , Masood Zubia , Ul Hasan Habib , Khan Wali , De los Ríos-Escalante Patricio R. , Aldamigh Mashael Abdullah , Al-Sowayan Noorah Saleh , Razzaq Wajeeha , Khan Tawseef , Said Mourad Ben 
Published: March 2024

AbstractTrace metals are naturally occurring metals found in very small concentrations in the environment. In the context of fish flesh, metals such as copper, calcium, potassium, sodium, zinc, iron, and manganese are absorbed by fish and play vital roles in various physiological functions. However, if these metals exceed the recommended limits set by WHO/FAO, they are termed 'toxic metals' due to their harmful impacts on both the fish and its consumers. Therefore, the present study aims to analyze the levels of protein, lipids, and certain metals—Aluminum (Al), Sodium (Na), Zinc (Zn), Titanium (Ti), Iron (Fe), Copper (Cu), Potassium (K), and Calcium (Ca) in three commercially important marine fishes i.e. Rastrelliger kanagurta, Sardinella abella, and Otolithes ruber. The study also aims to assess their potential impact on human health. The macro-Kjeldhal method and Soxhlet apparatus were used to estimate protein and lipid contents, while atomic absorption spectroscopy (AAS) was used to estimate trace metals found in fishes. The study found that these fish species are valuable sources of protein, lipids, and certain essential minerals. The protein content (CP) in these three species ranged from 63.35 to 86.57%, while lipid content was from 21.05 to 23.86%. The overall results of the trace metal concentrations analyzed in the present study revealed that Aluminum (Al), Sodium (Na), Zinc (Zn), Titanium (Ti), Copper (Cu), Potassium (K), and Calcium (Ca) were found in low concentration or traces and also within suitable ranges as set by WHO/FAO. However, Iron (Fe) was absent in all three species. Moreover, both copper and potassium were found in all three species, while Zinc was present in Rastrelliger kanagurta and Sardinella abella, calcium in Sardinella abella, and sodium in Otolithes ruber only. Titanium was recorded for the first time in S. abella. However, the total health risk assessment associated with these fish food consumption was measured by THQ and TTHQ and found to be less than 1, which shows no potential risk related to trace metals found in these fishes on human health upon their consumption. In conclusion, these commercially important marine fish species were found valuable sources of protein, lipids, and essential trace minerals that are necessary for human health. Thus, the current study provides useful information for the local population to make informed decisions about their daily diets and highlights the importance of sustainable fishing practices to maintain these valuable marine resources by periodical monitoring of their ecosystem.
An asynchronous wireless network for capturing event-driven data from large populations of autonomous sensors
Authors: Lee Jihun , Lee Ah-Hyoung , Leung Vincent , Laiwalla Farah , Lopez-Gordo Miguel Angel , Larson Lawrence , Nurmikko Arto 
Published: March 2024

AbstractNetworks of spatially distributed radiofrequency identification sensors could be used to collect data in wearable or implantable biomedical applications. However, the development of scalable networks remains challenging. Here we report a wireless radiofrequency network approach that can capture sparse event-driven data from large populations of spatially distributed autonomous microsensors. We use a spectrally efficient, low-error-rate asynchronous networking concept based on a code-division multiple-access method. We experimentally demonstrate the network performance of several dozen submillimetre-sized silicon microchips and complement this with large-scale in silico simulations. To test the notion that spike-based wireless communication can be matched with downstream sensor population analysis by neuromorphic computing techniques, we use a spiking neural network machine learning model to decode prerecorded open source data from eight thousand spiking neurons in the primate cortex for accurate prediction of hand movement in a cursor control task.
Accelerated nitrogen cycling on Mediterranean seagrass leaves at volcanic CO2 vents
Authors: Berlinghof Johanna , Montilla Luis M. , Peiffer Friederike , Quero Grazia M. , Marzocchi Ugo , Meador Travis B. , Margiotta Francesca , Abagnale Maria , Wild Christian , Cardini Ulisse 
Published: March 2024

AbstractSeagrass meadows form highly productive and diverse ecosystems in coastal areas worldwide, where they are increasingly exposed to ocean acidification (OA). Efficient nitrogen (N) cycling and uptake are essential to maintain plant productivity, but the effects of OA on N transformations in these systems are poorly understood. Here we show that complete N cycling occurs on leaves of the Mediterranean seagrass Posidonia oceanica at a volcanic CO2 vent near Ischia Island (Italy), with OA affecting both N gain and loss while the epiphytic microbial community structure remains largely unaffected. Daily leaf-associated N2 fixation contributes to 35% of the plant’s N demand under ambient pH, while it contributes to 45% under OA. Nitrification potential is only detected under OA, and N-loss via N2 production increases, although the balance remains decisively in favor of enhanced N gain. Our work highlights the role of the N-cycling microbiome in seagrass adaptation to OA, with key N transformations accelerating towards increased N gain.
Forecasts of fog events in northern India dramatically improve when weather prediction models include irrigation effects
Authors: Smith Daniel K. E. , Reka Srinivas , Dorling Stephen R. , Ross Andrew N. , Renfrew Ian A. , Jayakumar A. , Anurose T. J. , Parde Avinash N. , Ghude Sachin D. , Rumbold Heather 
Published: March 2024

AbstractDense wintertime fog regularly impacts Delhi, severely affecting road and rail transport, aviation and human health. Recent decades have seen an unexplained increase in fog events over northern India, coincident with a steep rise in wintertime irrigation associated with the introduction of double-cropping. Accurate fog forecasting is challenging due to a high sensitivity to numerous processes across many scales, and uncertainties in representing some of these in state-of-the-art numerical weather prediction models. Here we show fog event simulations over northern India with and without irrigation, revealing that irrigation counteracts a common model dry bias, dramatically improving the simulation of fog. Evaluation against satellite products and surface measurements reveals a better spatial extent and temporal evolution of the simulated fog events. Increased use of irrigation over northern India in winter provides a plausible explanation for the observed upward trend in fog events, highlighting the critical need for optimisation of irrigation practices.
Radar near-field sensing using metasurface for biomedical applications
Authors: Bagheri Mohammad Omid , Gharamohammadi Ali , Abu-Sardanah Serene , Ramahi Omar M. , Shaker George 
Published: March 2024

AbstractMetasurfaces, promising technology exemplified by their precise manipulation of incident wave properties and exquisite control over electromagnetic field propagation, offer unparalleled benefits when integrated into radar systems, providing higher resolution and increased sensitivity. Here, we introduce a metasurface-enhanced millimeter-wave radar system for advanced near-field bio-sensing, underscoring its adaptability to the skin-device interface, and heightened diagnostic precision in non-invasive healthcare monitoring. The low-profile planar metasurface, featuring a phase-synthesized array for near-field impedance matching, integrates with radar antennas to concentrate absorbed power density within the skin medium while simultaneously improving the received power level, thereby enhancing sensor signal-to-noise ratio. Measurement verification employs a phantom with material properties resembling human skin within the radar frequency range of 58 to 63 GHz. Results demonstrate a notable increase of over 11 dB in near-field Poynting power density within the phantom model, while radar signal processing analysis indicates a commensurate improvement in signal-to-noise ratio, thus facilitating enhanced sensing in biomedical applications.
Green biomanufacturing of edible antiviral therapeutics for managed pollinators
Authors: Ricigliano Vincent A. , McMenamin Alexander , Martin Ewert Allyson , Adjaye Daniela , Simone-Finstrom Michael , Rainey Victor P. 
Published: March 2024

AbstractManaged bees are important agricultural pollinators threatened by declines linked to multi-host RNA viruses. Here, we developed a novel antiviral platform for bees using the edible photosynthetic cyanobacterium Synechococcus elongatus UTEX 2973. Cyanobacterial biomass was engineered to induce RNA interference (RNAi) immune responses when fed to bees. Treatments targeting deformed wing virus—a notorious pathogen—suppressed viral infection and improved survival in honey bees. This design presents a versatile and sustainable therapeutic that can be directly incorporated into supplemental feeds for managed pollinators to mitigate viruses and support global food security.