bluuebunny/crossref_metadata_2025_split huggingface dataset:
AIMD-Chig: Exploring the conformational space of a 166-atom protein Chignolin with ab initio molecular dynamics
Authors: Wang Tong , He Xinheng , Li Mingyu , Shao Bin , Liu Tie-Yan 
Published: August 2023

AbstractMolecular dynamics (MD) simulations have revolutionized the modeling of biomolecular conformations and provided unprecedented insight into molecular interactions. Due to the prohibitive computational overheads of ab initio simulation for large biomolecules, dynamic modeling for proteins is generally constrained on force field with molecular mechanics, which suffers from low accuracy as well as ignores the electronic effects. Here, we report AIMD-Chig, an MD dataset including 2 million conformations of 166-atom protein Chignolin sampled at the density functional theory (DFT) level with 7,763,146 CPU hours. 10,000 conformations were initialized covering the whole conformational space of Chignolin, including folded, unfolded, and metastable states. Ab initio simulations were driven by M06-2X/6-31 G* with a Berendsen thermostat at 340 K. We reported coordinates, energies, and forces for each conformation. AIMD-Chig brings the DFT level conformational space exploration from small organic molecules to real-world proteins. It can serve as the benchmark for developing machine learning potentials for proteins and facilitate the exploration of protein dynamics with ab initio accuracy.
Cell culture media dependent in vitro dynamics and culture characteristics of adult caprine dermal fibroblast cells
Authors: Pathak Juhi , Singh Shiva Pratap , Kharche Suresh Dinkar , Goel Anjana , Soni Yogesh K. , Kaushik Rakesh , Kose Megha , Kumar Ashish 
Published: August 2023

AbstractThe enhanced availability of functional fibroblasts from precious tissue samples requires an ideal cell-culture system. Therefore, this study was designed to investigate the performance of caprine adult fibroblast cells (cadFibroblast) when cultivated in different culture media. The cadFibroblast cell lines from adult Barbari (Capra hircus) bucks were established and the effect of different media viz. DMEM/F-12 [with low-glucose (5.5 mM; DL) and high-glucose (30 mM; DH)], α-MEM [with low-glucose (5.5 mM; ML) and with high-glucose (30 mM; MH)], and fibroblast growth medium (FGM) were evaluated. Cells were then compared for growth characteristics and in-vitro dynamics through cellular morphology, proliferation, population-doubling time, double-immunocytochemistry, colony-forming units, wound healing, transwell migration, and differential expression of fibroblast-specific markers (FSP-1 and vimentin). The results of immunocytochemistry, transwell migration/invasion, and wound healing assays showed the superiority of DH over DL and other media tested. Whereas, similar effects of glucose supplementation and expression of FSP-1 were not observed in α-MEM. Transwell migration was significantly (p < 0.05) lower in FGM compared with other media tested. Overall, our results illustrate the media-dependent deviation in in-vitro dynamics and culture characteristics of cadFibroblasts that may be useful to develop strategies to cultivate these cells efficiently for research and downstream applications.
Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel engines
Authors: Nath Kamaljyoti , Meng Xuhui , Smith Daniel J. , Karniadakis George Em 
Published: August 2023

AbstractThis paper presents a physics-informed neural network (PINN) approach for monitoring the health of diesel engines. The aim is to evaluate the engine dynamics, identify unknown parameters in a “mean value” model, and anticipate maintenance requirements. The PINN model is applied to diesel engines with a variable-geometry turbocharger and exhaust gas recirculation, using measurement data of selected state variables. The results demonstrate the ability of the PINN model to predict simultaneously both unknown parameters and dynamics accurately with both clean and noisy data, and the importance of the self-adaptive weight in the loss function for faster convergence. The input data for these simulations are derived from actual engine running conditions, while the outputs are simulated data, making this a practical case study of PINN’s ability to predict real-world dynamical systems. The mean value model of the diesel engine incorporates empirical formulae to represent certain states, but these formulae may not be generalizable to other engines. To address this, the study considers the use of deep neural networks (DNNs) in addition to the PINN model. The DNNs are trained using laboratory test data and are used to model the engine-specific empirical formulae in the mean value model, allowing for a more flexible and adaptive representation of the engine’s states. In other words, the mean value model uses both the PINN model and the DNNs to represent the engine’s states, with the PINN providing a physics-based understanding of the engine’s overall dynamics and the DNNs offering a more engine-specific and adaptive representation of the empirical formulae. By combining these two approaches, the study aims to offer a comprehensive and versatile approach to monitoring the health and performance of diesel engines.
Twist-assisted optoelectronic phase control in two-dimensional (2D) Janus heterostructures
Authors: Kar S. , Kumari P. , Kamalakar M. Venkata , Ray S. J. 
Published: August 2023

AbstractAtomically thin two-dimensional (2D) Janus materials and their Van der Waals heterostructures (vdWHs) have emerged as a new class of intriguing semiconductor materials due to their versatile application in electronic and optoelectronic devices. Herein, We have invstigated most probable arrangements of different inhomogeneous heterostructures employing one layer of transition metal dichalcogenide, TMD (MoS2, WS2, MoSe2, and WSe2) piled on the top of Janus TMD (MoSeTe or WSeTe) and investigated their structural, electronic as well as optical properties through first-principles based calculations. After that, we applied twist engineering between the monolayers from 0$$^{\circ } \rightarrow$$

∘

→

60$$^{\circ }$$

∘

twist angle, which delivers lattice reconstruction and improves the performance of the vdWHs due to interlayer coupling. The result reveals that all the proposed vdWHs are dynamically and thermodynamically stable. Some vdWHs such as MoS2/MoSeTe, WS2/WSeTe, MoS2/WSeTe, MoSe2/MoSeTe, and WS2/MoSeTe exhibit direct bandgap with type-II band alignment at some specific twist angle, which shows potential for future photovoltaic devices. Moreover, the electronic property and carrier mobility can be effectively tuned in the vdWHs compared to the respective monolayers. Furthermore, the visible optical absorption of all the Janus vdWHs at $$\theta$$
θ
= 0$$^{\circ }$$

∘

can be significantly enhanced due to the weak inter-layer coupling and redistribution of the charges. Therefore, the interlayer twisting not only provides an opportunity to observe new exciting properties but also gives a novel route to modulate the electronic and optoelectronic properties of the heterostructure for practical applications.
A machine learning approach for understanding the metabolomics response of children with autism spectrum disorder to medical cannabis treatment
Authors: Quillet Jean-Christophe , Siani-Rose Michael , McKee Robert , Goldstein Bonni , Taylor Myiesha , Kurek Itzhak 
Published: August 2023

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental condition impacting behavior, communication, social interaction and learning abilities. Medical cannabis (MC) treatment can reduce clinical symptoms in individuals with ASD. Cannabis-responsive biomarkers are metabolites found in saliva that change in response to MC treatment. Previously we showed levels of these biomarkers in children with ASD successfully treated with MC shift towards the physiological levels detected in typically developing (TD) children, and potentially can quantify the impact. Here, we tested for the first time the capabilities of machine learning techniques applied to our dynamic, high-resolution and rich feature dataset of cannabis-responsive biomarkers from a limited number of children with ASD before and after MC treatment and a TD group to identify: (1) biomarkers distinguishing ASD and TD groups; (2) non-cannabinoid plant molecules with synergistic effects; and (3) biomarkers associated with specific cannabinoids. We found: (1) lysophosphatidylethanolamine can distinguish between ASD and TD groups; (2) novel phytochemicals contribute to the therapeutic effects of MC treatment by inhibition of acetylcholinesterase; and (3) THC- and CBD-associated cannabis-responsive biomarkers are two distinct groups, while CBG is associated with some biomarkers from both groups.
Attention and impulsivity assessment using virtual reality games
Authors: Mendez-Encinas David , Sujar Aaron , Bayona Sofia , Delgado-Gomez David 
Published: August 2023

AbstractThe assessment of cognitive functions is mainly based on standardized neuropsychological tests, widely used in various fields such as personnel recruitment, education, or health. This paper presents a virtual reality game that allows collecting continuous measurements of both the performance and behaviour of the subject in an immersive, controllable, and naturalistic experience. The application registers variables related to the user’s eye movements through the use of virtual reality goggles, as well as variables of the game performance. We study how virtual reality can provide data to help predict scores on the Attention Control Scale Test and the Barratt Impulsiveness Scale. We design the application and test it with a pilot group. We build a random forest regressor model to predict the attention and impulsivity scales’ total score. When evaluating the performance of the model, we obtain a positive correlation with attention (0.434) and with impulsivity (0.382). In addition, our model identified that the most significant variables are the time spent looking at the target or at distractors, the eye movements variability, the number of blinks and the pupil dilation in both attention and impulsivity. Our results are consistent with previous results in the literature showing that it is possible to use data collected in virtual reality to predict the degree of attention and impulsivity.
Dysregulation of testis mRNA expression levels in hatchery-produced vs wild greater amberjack Seriola dumerili
Authors: Lavecchia Anna , Manzari Caterina , Pousis Chrysovalentinos , Mansi Luigi , Cox Sharon N. , Mylonas Constantinos C. , Zupa Rosa , Lo Giudice Claudio , De Virgilio Caterina , Picardi Ernesto , Ventriglia Gianluca , Pesole Graziano , Corriero Aldo 
Published: August 2023

AbstractReproductive dysfunctions have been recently documented in male greater amberjack Seriola dumerili caught from the wild and reared in captivity. In the present study, we compared testis transcriptome in wild fish (WILD), hatchery-produced fish with apparently normal spermatogenesis (Normal Farmed; NormalF) and hatchery-produced fish with evident reproductive dysfunction (Dysfunctional Farmed; DysF). Gene expression analysis identified 2157, 1985 and 74 differentially expressed genes (DEGs) in DysF vs WILD, NormalF vs DysF and NormalF vs WILD comparisons, respectively. In DysF, a dysregulation of several interconnected biological processes, including cell assembly, steroidogenesis and apoptosis was found. Gene enrichment of progesterone-mediated oocyte maturation, oocyte meiosis and cell cycle pathways were identified in the DysF vs NormalF comparison. Most of the DEGs involved in the enriched pathways were downregulated in DysF. The comparison of NormalF vs WILD showed that most of the DEGs were downregulated in NormalF, including a gene that encodes for a regulatory protein with a protective role in apoptosis regulation (ptpn6), indicating that spermatogenesis was dysfunctional also in the apparently “normal” hatchery-produced fish. Hence, rearing of male greater amberjack in captivity, from eggs produced by captive breeders, did not prevent the appearance of reproductive dysfunctions, and these dysfunctions involved several biological processes and metabolic pathways.
Controlled tumor heterogeneity in a co-culture system by 3D bio-printed tumor-on-chip model
Authors: Moghimi Nafiseh , Hosseini Seied Ali , Dalan Altay Burak , Mohammadrezaei Dorsa , Goldman Aaron , Kohandel Mohammad 
Published: August 2023

AbstractCancer treatment resistance is a caused by presence of various types of cells and heterogeneity within the tumor. Tumor cell–cell and cell-microenvironment interactions play a significant role in the tumor progression and invasion, which have important implications for diagnosis, and resistance to chemotherapy. In this study, we develop 3D bioprinted in vitro models of the breast cancer tumor microenvironment made of co-cultured cells distributed in a hydrogel matrix with controlled architecture to model tumor heterogeneity. We hypothesize that the tumor could be represented by a cancer cell-laden co-culture hydrogel construct, whereas its microenvironment can be modeled in a microfluidic chip capable of producing a chemical gradient. Breast cancer cells (MCF7 and MDA-MB-231) and non-tumorigenic mammary epithelial cells (MCF10A) were embedded in the alginate-gelatine hydrogels and printed using a multi-cartridge extrusion bioprinter. Our approach allows for precise control over position and arrangements of cells in a co-culture system, enabling the design of various tumor architectures. We created samples with two different types of cells at specific initial locations, where the density of each cell type was carefully controlled. The cells were either randomly mixed or positioned in sequential layers to create cellular heterogeneity. To study cell migration toward chemoattractant, we developed a chemical microenvironment in a chamber with a gradual chemical gradient. As a proof of concept, we studied different migration patterns of MDA-MB-231 cells toward the epithelial growth factor gradient in presence of MCF10A cells in different ratios using this device. Our approach involves the integration of 3D bioprinting and microfluidic devices to create diverse tumor architectures that are representative of those found in various patients. This provides an excellent tool for studying the behavior of cancer cells with high spatial and temporal resolution.
Development of a workflow for the selection, identification and optimization of lactic acid bacteria with high γ-aminobutyric acid production
Authors: Rehman Ateequr , Di Benedetto Giulio , Bird Julia K. , Dabene Valentina , Vadakumchery Lisa , May Ali , Schyns Ghislain , Sybesma Wilbert , Mak Tim N. 
Published: August 2023

AbstractLactic acid bacteria produce γ-aminobutyric acid (GABA) as an acid stress response. GABA is a neurotransmitter that may improve sleep and resilience to mental stress. This study focused on the selection, identification and optimization of a bacterial strain with high GABA production, for development as a probiotic supplement. The scientific literature and an industry database were searched for probiotics and potential GABA producers. In silico screening was conducted to identify genes involved in GABA production. Subsequently, 17 candidates were screened for in vitro GABA production using thin layer chromatography, which identified three candidate probiotic strains Levilactobacillus brevis DSM 20054, Lactococcus lactis DS75843and Bifidobacterium adolescentis DSM 24849 as producing GABA. Two biosensors capable of detecting GABA were developed: 1. a transcription factor-based biosensor characterized by the interaction with the transcriptional regulator GabR was developed in Corynebacterium glutamicum; and 2. a growth factor-based biosensor was built in Escherichia coli, which used auxotrophic complementation by expressing 4-aminobutyrate transaminase (GABA-T) that transfers the GABA amino group to pyruvate, hereby forming alanine. Consequently, the feasibility of developing a workflow based on co-culture with producer strains and a biosensor was tested. The three GABA producers were identified and the biosensors were encapsulated in nanoliter reactors (NLRs) as alginate beads in defined gut-like conditions. The E. coli growth factor-based biosensor was able to detect changes in GABA concentrations in liquid culture and under gut-like conditions. L. brevis and L. lactis were successfully encapsulated in the NLRs and showed growth under miniaturized intestinal conditions.
Operational prediction of solar flares using a transformer-based framework
Authors: Abduallah Yasser , Wang Jason T. L. , Wang Haimin , Xu Yan 
Published: August 2023

AbstractSolar flares are explosions on the Sun. They happen when energy stored in magnetic fields around solar active regions (ARs) is suddenly released. Solar flares and accompanied coronal mass ejections are sources of space weather, which negatively affects a variety of technologies at or near Earth, ranging from blocking high-frequency radio waves used for radio communication to degrading power grid operations. Monitoring and providing early and accurate prediction of solar flares is therefore crucial for preparedness and disaster risk management. In this article, we present a transformer-based framework, named SolarFlareNet, for predicting whether an AR would produce a $$\gamma$$
γ
-class flare within the next 24 to 72 h. We consider three $$\gamma$$
γ
classes, namely the $$\ge$$
≥
M5.0 class, the $$\ge$$
≥
M class and the $$\ge$$
≥
C class, and build three transformers separately, each corresponding to a $$\gamma$$
γ
class. Each transformer is used to make predictions of its corresponding $$\gamma$$
γ
-class flares. The crux of our approach is to model data samples in an AR as time series and to use transformers to capture the temporal dynamics of the data samples. Each data sample consists of magnetic parameters taken from Space-weather HMI Active Region Patches (SHARP) and related data products. We survey flare events that occurred from May 2010 to December 2022 using the Geostationary Operational Environmental Satellite X-ray flare catalogs provided by the National Centers for Environmental Information (NCEI), and build a database of flares with identified ARs in the NCEI flare catalogs. This flare database is used to construct labels of the data samples suitable for machine learning. We further extend the deterministic approach to a calibration-based probabilistic forecasting method. The SolarFlareNet system is fully operational and is capable of making near real-time predictions of solar flares on the Web.
Clinical significance of oxidative stress markers as angioinvasion and metastasis indicators in papillary thyroid cancer
Authors: Buczyńska Angelika , Sidorkiewicz Iwona , Kościuszko Maria , Adamska Agnieszka , Siewko Katarzyna , Dzięcioł Janusz , Szumowski Piotr , Myśliwiec Janusz , Szelachowska Małgorzata , Popławska-Kita Anna , Krętowski Adam 
Published: August 2023

AbstractAngioinvasion remains the important prognostic feature in papillary thyroid cancer (PTC) patients. Literature data indicates several markers that may be associated with oxidative stress and/or angioinvasion. Therefore, we assessed the utility of selected parameters in angioinvasion and metastasis screening in serum of PTC patients. Serum antioxidant capacity (TAC) and sirtuin 3 (SIRT3) levels were decreased (all p < 0.05) and both DNA/RNA oxidative stress damage products (DNA/RNA OSDP) and malondialdehyde (MDA) levels were increased in PTC patients with angioinvasion and metastasis (study group) when compared with PTC patients without these features (all p < 0.01). The highest screening utility in differentiation between angioinvasion and metastasis presence and absence in PTC patients was presented for DNA/RNA OSDP (AUC = 0.71), SIRT3 (AUC = 0.70), and TAC (AUC = 0.67) (all p < 0.05). Our study suggests that peripheral concentration of oxidative stress markers could be useful as angioinvasion and metastasis indicator in PTC patients.
Socioeconomic inequities of COVID-19 mortality in vulnerable Comunas of the City of Buenos Aires
Authors: Marconi Agustina M. , Castillo Salgado Carlos , Sarrouf Elena Beatriz , Zamora Rafael Jose , Irurzun Alejandra Maria , Islam Nazrul 
Published: August 2023

AbstractDuring the COVID-19 pandemic, the gap in health inequities was exposed and increased, showing how different vulnerable groups were affected. Our aim was to examine the correlation between an area-based health inequity index and mortality due to COVID-19 in people 60 years old or above in the City of Buenos Aires in 2020. We developed a Health Inequity Composite Index (HICI), including six core indicators. Each indicator value per Comuna was first standardized to a Z-score. All six Z-scores were summed into a final composite Z-score to rank the Comunas from lowest to highest social inequities. Comunas from the northern part of the city had lower inequities whereas those in the south had higher levels of inequities. COVID-19 age-standardized mortality rate in people 60 years or above was higher in the Comunas from the south and lower in those from the north. Finally, we found a strong positive correlation (Rho = 0.83, p < 0.0001 CI95% = 0.65–0.99) between HICI and age-standardized mortality rates from COVID-19 in people 60 years or above. Our finding of a strong correlation between the levels of health inequity and mortality calls for a concerted effort in narrowing or eliminating existing inequities.
Sex difference and risk factors in burden of urogenital congenital anomalies from 1990 to 2019
Authors: Huang Xiaoyu , Tang Jianming , Chen Mao , Xiao Ya , Zhu Fangyi , Chen Liying , Tian Xiaoyu , Hong Li 
Published: August 2023

AbstractUrogenital congenital anomalies (UCAs) is defined as “any live-birth with a urinary or genital condition” and affects millions of men and women worldwide. However, sex differences and related environmental risk factors in UCAs burden on a global scale have not been assessed. Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated prevalence, incidence, mortality and disability-adjusted life years (DALYs) of UCAs from 1990 to 2019 by sex, region, and socio-demographic Index (SDI) in 204 countries and territories. The disease burden of UCAs was also estimated attributable to each risk factor were estimated according to risk exposure. In 2019, UCAs caused 10,200 all-ages deaths (95% UI 7550–13,400). The combined global incidence rate was 8.38 per 1000 (95% UI 5.88–12.0) live births. The ASIR increased slightly, while the ASDR decreased from 1990 to 2019.The UCAs burden varies greatly depending on the development level and geographical location. The UCAs burden was significantly higher in men than in women, and the sex differences showed an enlarging trend. Health risks and issues, including pollution, child and maternal malnutrition, diet habits, unsafe sanitation and water source, were detected to be positively related to UCAs burden. Albeit the age-standardised prevalence, mortality, incidence, and DALYs of UCAs have decreased, they still cause a public health challenge worldwide. The high deaths and DALYs rates in low and low-middle SDI countries highlight the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for enhancing water safety, reducing pollution, and healthy diets are crucial steps in reducing the burden of UCAs.