bluuebunny/crossref_metadata_2025_split huggingface dataset:
White and gray matter integrity evaluated by MRI-DTI can serve as noninvasive and reliable indicators of structural and functional alterations in chronic neurotrauma
Authors: Wang Lan-Wan , Cho Kuan-Hung , Chao Pi-Yu , Kuo Li-Wei , Chiang Chia-Wen , Chao Chien-Ming , Lin Mao-Tsun , Chang Ching-Ping , Lin Hung-Jung , Chio Chung-Ching 
Published: March 2024

AbstractWe aimed to evaluate whether white and gray matter microstructure changes observed with magnetic resonance imaging (MRI)-based diffusion tensor imaging (DTI) can be used to reflect the progression of chronic brain trauma. The MRI-DTI parameters, neuropathologic changes, and behavioral performance of adult male Wistar rats that underwent moderate (2.1 atm on day “0”) or repeated mild (1.5 atm on days “0” and “2”) traumatic brain injury (TBI or rmTBI) or sham operation were evaluated at 7 days, 14 days, and 1–9 months after surgery. Neurobehavioral tests showed that TBI causes long-term motor, cognitive and neurological deficits, whereas rmTBI results in more significant deficits in these paradigms. Both histology and MRI show that rmTBI causes more significant changes in brain lesion volumes than TBI. In vivo DTI further reveals that TBI and rmTBI cause persistent microstructural changes in white matter tracts (such as the body of the corpus callosum, splenium of corpus callus, internal capsule and/or angular bundle) of both two hemispheres. Luxol fast blue measurements reveal similar myelin loss (as well as reduction in white matter thickness) in ipsilateral and contralateral hemispheres as observed by DTI analysis in injured rats. These data indicate that the disintegration of microstructural changes in white and gray matter parameters analyzed by MRI-DTI can serve as noninvasive and reliable markers of structural and functional level alterations in chronic TBI.
Exploring super-resolution spatial downscaling of several meteorological variables and potential applications for photovoltaic power
Authors: Damiani Alessandro , Ishizaki Noriko N. , Sasaki Hidetaka , Feron Sarah , Cordero Raul R. 
Published: March 2024

AbstractWe applied a perfect prognosis approach to downscale four meteorological variables that affect photovoltaic (PV) power output using four machine learning (ML) algorithms. In addition to commonly investigated variables, such as air temperature and precipitation, we also focused on wind speed and surface solar radiation, which are not frequently examined. The downscaling performance of the four variables followed the order of: temperature > surface solar radiation > wind speed > precipitation. Having assessed the dependence of the downscaling accuracy on the scaling factor, we focused on a super-resolution downscaling. We found that the convolutional neural network (CNN) generally outperformed the other linear and non-linear algorithms. The CNN was further able to reproduce extremes. With the rapid transition from coal to renewables, the need to evaluate low solar output conditions at a regional scale is expected to benefit from CNNs. Because weather affects PV power output in multiple ways, and future climate change will modify meteorological conditions, we focused on obtaining exemplary super-resolution application by evaluating future changes in PV power outputs using climate simulations. Our results confirmed the reliability of the CNN method for producing super-resolution climate scenarios and will enable energy planners to anticipate the effects of future weather variability.
In silico designed novel multi-epitope mRNA vaccines against Brucella by targeting extracellular protein BtuB and LptD
Authors: Shi Juan , Zhu Yuejie , Yin Zhengwei , He Yueyue , Li Yujiao , Haimiti Gulishati , Xie Xinru , Niu Ce , Guo Wenhong , Zhang Fengbo 
Published: March 2024

AbstractBrucella, a gram-negative intracellular bacterium, causing Brucellosis, a zoonotic disease with a range of clinical manifestations, from asymptomatic to fever, fatigue, loss of appetite, joint and muscle pain, and back pain, severe patients have developed serious diseases affecting various organs. The mRNA vaccine is an innovative type of vaccine that is anticipated to supplant traditional vaccines. It is widely utilized for preventing viral infections and for tumor immunotherapy. However, research regarding its effectiveness in preventing bacterial infections is limited. In this study, we analyzed the epitopes of two proteins of brucella, the TonB-dependent outer membrane receptor BtuB and the LPS assembly protein LptD, which is involved in nutrient transport and LPS synthesis in Brucella. In order to effectively stimulate cellular and humoral immunity, we utilize a range of immunoinformatics tools such as VaxiJen, AllergenFPv.1.0 and SignalP 5.0 to design proteins. Finally, five cytotoxic T lymphocyte (CTL) cell epitopes, ten helper T lymphocyte (HTL) cell epitopes, and eight B cell epitopes were selected to construct the vaccine. Computer simulations are also used to verify the immune response of the vaccine. The codon optimization, in silico cloning showed that the vaccine can efficiently transcript and translate in E. coli. The secondary structure of mRNA vaccines and the secondary and tertiary structures of vaccine peptides were predicted and then docked with TLR-4. Finally, the stability of the developed vaccine was confirmed through molecular dynamics simulation. These analyses showed that the design the multi-epitope mRNA vaccine could potentially target extracellular protein of prevalent Brucella, which provided novel strategies for developing the vaccine.
Identification of the pan-allergen tropomyosin from the common bed bug (Cimex lectularius)
Authors: Gordon Johnalyn M. , DeVries Zachary C. 
Published: March 2024

AbstractTropomyosin is a muscle contraction protein documented across all animal life. Despite its ubiquity, its unique structure in invertebrates leads to allergic responses in humans that vertebrate tropomyosin does not. High degrees of homology can explain cross-reactivity between tropomyosin derived from distantly-related arthropod species and establishes tropomyosin as a panallergen. Given this cross-reactivity and that they are commonly found in high numbers indoors, research on the potential of the common bed bug (Cimex lectularius L.) to contribute tropomyosin to the indoor environment is needed. Therefore, we investigated tropomyosin homology between bed bugs and known tropomyosin allergens from other taxa, tropomyosin in bed bug bodies, feces, and exuviae (cast skins), tropomyosin persistence over time, and impacts of common bed bug treatment strategies on detectable tropomyosin. Tropomyosin was detected in mechanically fractured bed bug cadavers and was detectable in bed bugs cadavers aged for 18 months. Additionally, a survey of pest management professionals showed dead bed bugs are not cleaned up following treatment. As such, dead bed bugs could act as tropomyosin reservoirs following bed bug treatment and exposure to tropomyosin from bed bugs could sensitize individuals and lead to increased responses to other arthropod tropomyosin.
The effect of cystic echinococcosis (hydatid disease) on carcase weight in cattle in eastern Australia
Authors: Brookes Victoria J. , Barnes Tamsin S. , Jenkins David J. , Van der Saag Matthew R. , Dempster Robert , Wilson Cara S. 
Published: March 2024

AbstractCystic echinococcosis is caused by the zoonotic tapeworm Echinococcus granulosus. There has been ongoing controversy over whether it causes weight loss in cattle. Recently implemented recording of comorbidities at processors has provided opportunity to investigate this effect. Using prevalence-based observational data from 1,648,049 adult cattle processed in seven states and territories in Australia (2019–2022), we explored associations between carcase weight, hydatid cysts, comorbidities, sex, age, and region. Linear mixed-effect regression models estimated the effect of cystic echinococcosis on carcase weight, guided by directed acyclic graphs to reduce bias. The highest, previously unreported, prevalence was in the southeast Queensland region. The estimated effect of cystic echinococcosis cysts on carcase weight ranged from a gain of 0.32 kg/carcase (standard error [se] 0.58 kg; two-tooth 2022) to a loss of −5.45 kg/carcase (se 0.63 kg; six-tooth 2019) with most point estimates (11/16) between 0 and −2.5 kg across all cattle grouped by year and dentition. This effect size would be practically undetectable in live cattle which is an important finding; cattle producers are unlikely to observe increased productivity through weight gain from cystic echinococcosis prevention in cattle, and awareness to strengthen prevention in domestic dogs around cattle properties to reduce human risk remains a public health focus.
Factors impacting antibody kinetics, including fever and vaccination intervals, in SARS-CoV-2-naïve adults receiving the first four mRNA COVID-19 vaccine doses
Authors: Matsuura Tomoka , Fukushima Wakaba , Nakagama Yu , Kido Yasutoshi , Kase Tetsuo , Kondo Kyoko , Kaku Natsuko , Matsumoto Kazuhiro , Suita Asae , Mukai Emiko , Nitahara Yuko , Konishi Ayako , Kasamatsu Ayane , Nakagama Sachie , Nakagami-Yamaguchi Etsuko , Ohfuji Satoko , Kaneko Yukihiro , Kaneko Akira , Kakeya Hiroshi , Hirota Yoshio 
Published: March 2024

AbstractTo evaluate the antibody response following the initial four doses of mRNA vaccines (BNT162b2 or mRNA-1273) in SARS-CoV-2-naïve healthy adults and investigate factors influencing antibody titer increases, this prospective cohort study was conducted in Japan from March 2021. The study included participants who received either the 1st and 2nd doses (n = 467), 3rd dose (n = 157), or 4th dose (n = 89). Blood samples were collected before and up to 6 months after each dose, and anti-receptor-binding domain antibody levels were measured. Multivariate analysis (usin multiple linear regression or linear mixed models) revealed several factors significantly associated with higher post-vaccination antibody levels, including mRNA-1273 vaccine (after the 1st and 2nd dose), male gender (after the 3rd and 4th doses), younger age (after the 1st and 2nd dose), non-smoking status (after the 2nd dose), non-use of immunosuppressive agents (after the 1st dose), higher pre-vaccination antibody titers (after the 2nd, 3rd, and 4th doses), and higher post-vaccination fever (after the 2nd and 4th doses). Furthermore, longer intervals since the last dose were significantly associated with higher antibody levels after the 3rd and 4th doses. These findings provide valuable insights for optimizing vaccination strategies.
Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data
Authors: Yamaguchi Takeshi , Adachi Yoshiaki , Tanida Takashi , Taguchi Katsutoshi , Oka Yoshinobu , Yoshida Takashi , Kim Wook-Cheol , Takahashi Kenji , Tanaka Masaki 
Published: March 2024

AbstractThe detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological evaluation of induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs). We report that deep learning with a dataset that combines magnetic signals estimated using numerical simulation and actual noise data is effective in the detection of weak biomagnetic signals. To verify the feasibility of this method, we measured artificially generated magnetic signals that mimic cellular magnetic fields using a superconducting quantum interference device and attempted peak detection using a long short-term memory network. We correctly detected 80.0% of the peaks and the method achieved superior detection performance compared with conventional methods. Next, we attempted peak detection for magnetic signals measured from mouse iPS-CMs. The number of detected peaks was consistent with the spontaneous beats counted using microscopic observation and the average peak waveform achieved good similarity with the prediction. We also observed the synchronization of peak positions between simultaneously measured field potentials and magnetic signals. Furthermore, the magnetic measurements of cell samples treated with isoproterenol showed potential for the detection of chronotropic effects. These results suggest that the proposed method is effective and has potential application in the safety assessment of regenerative medicine and drug screening.
Chemoprofiling and medicinal potential of underutilized leaves of Cyperus scariosus
Authors: Gandhi Yashika , Kumar Vijay , Singh Gagandeep , Prasad Shyam Baboo , Mishra Sujeet K. , Soni Hemant , Rawat Hemant , Singh Simranjeet , Charde Vaibhav , Gupta Akhil , Dhanjal Daljeet Singh , Jha Sudhanshu Kumar , Tandon Smriti , Bhagwat Prateeksha , Arya Jagdish C. , Ramamurthy Praveen C. , Acharya Rabinarayan , Narasimhaji Ch. Venkata , Singh Arjun , Singh Ravindra , Srikanth Narayanam , Webster Thomas J. 
Published: March 2024

AbstractAgro-waste is the outcome of the under-utilization of bioresources and a lack of knowledge to re-use this waste in proper ways or a circular economy approach. In the Indian medicinal system, the root of Cyperus scariosus (CS) is used at a large scale due to their vital medicinal properties. Unfortunately, the aerial part of CS is treated as agro-waste and is an under-utilized bioresource. Due to a lack of knowledge, CS is treated as a weed. This present study is the first ever attempt to explore CS leaves as medicinally and a nutrient rich source. To determine the food and nutritional values of the neglected part of Cyperus scariosus R.Br. (CS), i.e. CS leaves, phytochemicals and metal ions of CS were quantified by newly developed HPLC and ICPOES-based methods. The content of the phytochemicals observed in HPLC analysis for caffeic acid, catechin, epicatechin, trans-p-coumaric acid, and trans-ferulic acid was 10.51, 276.15, 279.09, 70.53, and 36.83 µg/g, respectively. In GC–MS/MS analysis, fatty acids including linolenic acid, phytol, palmitic acid, etc. were identified. In ICPOES analysis, the significant content of Na, K, Ca, Cu, Fe, Mg, Mn, and Zn was observed. The TPC and TFC of the CS leaves was 17.933 mg GAE eq./g and 130.767 mg QCE eq./g along with an IC50 value of 2.78 mg/mL in the DPPH assay and better antacid activity was measured than the standard (CaCO3). The methanolic extract of CS leaves showed anti-microbial activity against Staphylococcus aureus (15 ± 2 mm), Pseudomonas aeruginosa (12 ± 2 mm) and Escherichia coli (10 ± 2 mm). In silico studies confirmed the in vitro results obtained from the antioxidant, antiacid, and anti-microbial studies. In addition, in silico studies revealed the anti-cancerous and anti-inflammatory potential of the CS leaves. This study, thus, demonstrated the medicinal significance of the under-utilized part of CS and the conversion of agro-waste into mankind activity as a pharmaceutical potent material. Consequently, the present study highlighted that CS leaves have medicinal importance with good nutritional utility and have a large potential in the pharmaceutical industry along with improving bio-valorization and the environment.
Non-invasive geophysical methods for monitoring the shallow aquifer based on time-lapse electrical resistivity tomography, magnetic resonance sounding, and spontaneous potential methods
Authors: Li Kaitian , Yan Jianbo , Li Fan , Lu Kai , Yu Yongpeng , Li Yulin , Zhang Lin , Wang Peng , Li Zhenyu , Yang Yancheng , Wang Jiawen 
Published: March 2024

AbstractThe Ningdong coalfield has played a pivotal role in advancing local economic development and meeting national energy. Nevertheless, mining operations have engendered ecological challenges encompassing subterranean water depletion, land desertification, and ground subsidence, primarily stemming from the disruption of coal seam roof strata. Consequently, the local ecosystem has incurred substantial harm. Water-preserved coal mining presently constitutes the pivotal technology in mitigating this problem. The primary challenge of this technique lies in identifying critical aquifer layers and understanding the heights of water-conducting fracture zones. To obtain a precise comprehension of the seepage patterns within the upper coal seam aquifer during mining, delineate the extent of water-conducting fracture zones, non-invasive geophysical techniques such as time-lapse electrical resistivity tomography (TL-ERT), magnetic resonance sounding (MRS), and spontaneous potential (SP) have been employed to monitor alterations within the shallow coalfield’s aquifer throughout the mining process in the Ningdong coalfield. By conducting meticulous examinations of fluctuations in resistivity, moisture content, and self-potential within the superjacent strata during coal seam extraction, the predominant underground water infiltration strata were ascertained, concurrently enabling the estimation of the development elevation of water-conducting fracture zones. This outcome furnishes a geophysical underpinning for endeavors concerning local water-preserved coal mining and ecological rehabilitation.
Roadway rock burst prediction based on catastrophe theory
Authors: Pan Wang , Shuan-Cheng Gu , Wei Sun 
Published: March 2024

AbstractIn order to quantitatively calculate the critical depth and critical load of mines affected by rock burst, and to achieve effective prevention and control of rock burst in coal mines, this paper proposes a mechanical model for predicting the occurrence of rock burst in coal mine roadways based on catastrophe theory. Additionally, a theoretical calculation formula for initiating rock burst is derived. The first step was to establish a mechanical analysis model, which directly correlated with the in-situ stress, physical and mechanical characteristics of the coal-rock mass, and engineering structural parameters. Following this, a mechanical instability criterion was derived for the key load-bearing circle within the surrounding rock of the roadway. In the final step, the critical depth and load for rock burst initiation were verified for 25 distinct coal mines in China that were prone to rock burst hazards. The research results demonstrate that the discrepancy between the theoretically calculated critical depth and the actual measured statistical values was less than 35%. In addition, the difference between the theoretically determined critical depth and the value calculated by Pan Yishan was less than 32%. Notably, the ratio of the theoretically calculated critical load to the uniaxial compressive strength of the coal-rock mass ranged from 0.38 to 1.93. This aligns with empirical data on rock burst occurrences, as set out in the engineering classification standards for rock masses. These research outcomes substantiated the practical utility of the proposed theory, thereby laying a robust theoretical groundwork for the quantitative control of rock burst.
Non-invasive perfusion MR imaging of the human brain via breath-holding
Authors: Schulman J. B. , Kashyap S. , Kim S. G. , Uludağ K. 
Published: March 2024

AbstractDynamic susceptibility contrast (DSC) MRI plays a pivotal role in the accurate diagnosis and prognosis of several neurovascular diseases, but is limited by its reliance on gadolinium, an intravascularly injected chelated metal. Here, we determined the feasibility of measuring perfusion using a DSC analysis of breath-hold-induced gradient-echo-MRI signal changes. We acquired data at both 3 T and 7 T from ten healthy participants who engaged in eight consecutive breath-holds. By pairing a novel arterial input function strategy with a standard DSC MRI analysis, we measured the cerebral blood volume, flow, and transit delay, and found values to agree with those documented in the literature using gadolinium. We also observed voxel-wise agreement between breath-hold and arterial spin labeling measures of cerebral blood flow. Breath-holding resulted in significantly higher contrast-to-noise (6.2 at 3 T vs. 8.5 at 7 T) and gray matter-to-white matter contrast at higher field strength. Finally, using a simulation framework to assess the effect of dynamic vasodilation on perfusion estimation, we found global perfusion underestimation of 20–40%. For the first time, we have assessed the feasibility of and limitations associated with using breath-holds for perfusion estimation with DSC. We hope that the methods and results presented in this study will help pave the way toward contrast-free perfusion imaging, in both basic and clinical research.
The seasonal characteristics of English Channel storminess have changed since the 19th Century
Authors: Cornes Richard C. , Jones Philip D. 
Published: March 2024

AbstractInformation from a variety of sources has suggested that increased storminess was experienced across the British Isles in the late eighteenth/early nineteenth century. However, it is not clear how stormy that period was relative to current conditions. Using newly recovered barometric pressure data that extend back to 1748 we have constructed a measure of geostrophic wind speed for the English Channel region using a pressure-triangle approach. We show that the 1790−1820s was a period of increased storminess across the region. This storminess extended throughout the year, which is different to comparable increases observed since the 1990s, which were confined to the winter season. While a strengthened North Atlantic jet stream is implicated in both periods, in the earlier period it is likely that the storm track shifted slightly to a more southerly location. We discuss the potential forcing mechanisms responsible for the changes in storminess over this multi-century timeframe.
A feature‐enhanced hybrid attention network for traffic sign recognition in real scenes
Authors: He Lewei , Lan Fucai , Zhou Chuanzhe , Ye Yaoguang , Zhang Wencong , Chen Bingzhi , Pan Jiahui 
Published: March 2024

AbstractCurrently, traffic sign recognition techniques have been brought into the assistive driving of automobiles. However, small traffic sign recognition in real scenes is still a challenging task due to the class imbalance issue and the size limit of the traffic signs. To address the above issues, a feature‐enhanced hybrid attention network is proposed based on YOLOv5s for a small, fast, and accurate traffic sign detector. First, a series of online data augmentation strategies are designed in the preprocessing module for the model training. Second, the hybrid channel and spatial attention module CSAM are integrated into the backbone for a better feature extraction ability. Third, the channel attention module CAM is used in the detection head for a more efficient feature fusion ability. To validate the approach, extensive experiments are conducted based on the Tsinghua‐Tencent 100K dataset. It is found that the novel method achieves state‐of‐the‐art performance with only negligible increases in the model parameter and computational overhead. Specifically, the , parameters, and FLOPs are 85.8%, 7.13 M, and 16.1 G, respectively.