Miracle-dz/UniFAR-FTUs huggingface dataset:
The Asteroid Catalog Using AKARI IRC Slow-Scan Observations

We present an asteroidal catalog from the mid-infrared wavelength region using the slow-scan observation mode obtained by the Infrared Camera (IRC) on-board the Japanese infrared satellite AKARI. An archive of IRC slowscan observations comprising about 1000 images was used to search for serendipitous encounters of known asteroids. We have determined the geometric albedos and diameters for 88 main-belt asteroids, including two asteroids in the Hilda region, and compared these, where possible, with previously published values. Approximately one-third of the acquired data reflects new asteroidal information. Some bodies classified as C or D-type with high albedo were also identified in the catalog.
Material property alterations for phenotypes of heart failure with preserved ejection fraction: A numerical study of subject-specific porcine models

A substantial proportion of heart failure patients have a preserved left ventricular (LV) ejection fraction (HFpEF). This condition carries a high burden of morbidity and mortality and has limited therapeutic options. left ventricular pressure overload leads to an increase in myocardial collagen content, causing left ventricular stiffening that contributes to the development of heart failure patients have a preserved left ventricular ejection fraction. Although several heart failure patients have a preserved left ventricular ejection fraction models have been developed in recent years to aid the investigation of mechanical alterations, none has investigated different phenotypes of the disease and evaluated the alterations in material properties. In this study, two similar healthy swine were subjected to progressive and prolonged pressure overload to induce diastolic heart failure characteristics, providing a preclinical model of heart failure patients have a preserved left ventricular ejection fraction. Cardiac magnetic resonance imaging (cMRI) scans and intracardiac pressures were recorded before and after induction. In both healthy and disease states, a corresponding finite element (FE) cardiac model was developed via mesh morphing of the Living Heart Porcine model. The material properties were derived by calibrating to its passive and active behavior. The change in the passive behavior was predominantly isotropic when comparing the geometries before and after induction. Myocardial thickening allowed for a steady transition in the passive properties while maintaining tissue incompressibility. This study highlights the importance of hypertrophy as an initial compensatory response and might also pave the way for assessing disease severity.
Interpretive JIVE: Connections with CCA and an application to brain connectivity

Joint and Individual Variation Explained (JIVE) is a model that decomposes multiple datasets obtained on the same subjects into shared structure, structure unique to each dataset, and noise. JIVE is an important tool for multimodal data integration in neuroimaging. The two most common algorithms are R.JIVE, an iterative approach, and AJIVE, which uses principal angle analysis. The joint structure in JIVE is defined by shared subspaces, but interpreting these subspaces can be challenging. In this paper, we reinterpret AJIVE as a canonical correlation analysis of principal component scores. This reformulation, which we call CJIVE, (1) provides an intuitive view of AJIVE; (2) uses a permutation test for the number of joint components; (3) can be used to predict subject scores for out-of-sample observations; and (4) is computationally fast. We conduct simulation studies that show CJIVE and AJIVE are accurate when the total signal ranks are correctly specified but, generally inaccurate when the total ranks are too large. CJIVE and AJIVE can still extract joint signal even when the joint signal variance is relatively small. JIVE methods are applied to integrate functional connectivity (resting-state fMRI) and structural connectivity (diffusion MRI) from the Human Connectome Project. Surprisingly, the edges with largest loadings in the joint component in functional connectivity do not coincide with the same edges in the structural connectivity, indicating more complex patterns than assumed in spatial priors. Using these loadings, we accurately predict joint subject scores in new participants. We also find joint scores are associated with fluid intelligence, highlighting the potential for JIVE to reveal important shared structure.
Reduction in chloroplastic ribulose-5-phosphate-3-epimerase decreases photosynthetic capacity in Arabidopsis

Chloroplast ribulose-5-phosphate-3-epimerase (RPE) is a critical enzyme involved in the Calvin-Benson cycle and oxidative pentose phosphate pathways in higher plants. Three Arabidopsis rpe mutants with reduced level of RPE were identified through their high NPQ (nonphotochemical quenching) phenotype upon illumination, and no significant difference of plant size was found between these rpe mutants and WT (wild type) plants under growth chamber conditions. A decrease in RPE expression to a certain extent leads to a decrease in CO2 fixation, V cmax and J max. Photosynthetic linear electron transport was partially inhibited and activity of ATP synthase was also decreased in the rpe mutants, but the levels of thylakoid protein complexes and other Calvin-Benson cycle enzymes in rpe mutants were not affected. These results demonstrate that some degree of reduction in RPE expression decreases carbon fixation in chloroplasts, which in turn feedback inhibits photosynthetic electron transport and ATP synthase activity due to the photosynthetic control. Taken together, this work provides evidence that RPE plays an important role in the Calvin-Benson cycle and influences the photosynthetic capacity of chloroplasts.
Identification of key pharmacodynamic markers of American ginseng against heart failure based on metabolomics and zebrafish model

Background: American ginseng (Panax quinquefolium L., AG) is a traditional Chinese medicine with multiple cardiovascular protective properties. Many bioactive components have been discovered in AG over these years. However, the understanding of these key pharmacodynamic components of activity against heart failure is insufficient. Methods: A heart failure model was established using AB line wild-type zebrafish (Danio rerio) to evaluate the anti-heart failure activity of AG. Untargeted metabolomics analysis based on ultra-high performance liquid chromatography-quadrupole electrostatic field orbitrap-mass spectrometry technology (UHPLC-QE-Orbitrap-MS) was performed to screen differential components from AG samples. The potential active components were verified using the zebrafish model. Simultaneously, network pharmacology and molecular docking techniques were used to predict the possible mechanism. Finally, the key targets of six key pharmacodynamic components were verified in zebrafish using quantitative real-time-polymerase chain reaction (Q-PCR) techniques. Results: The heart failure model was successfully established in 48 h of post-fertilization (hpf) zebrafish larvae by treating with verapamil hydrochloride. The zebrafish assay showed that the anti-heart failure effects of AG varied with producing regions. The result of the herbal metabolomic analysis based on UHPLC-QE-Orbitrap-MS indicated that ginsenoside Rg3, ginsenoside Rg5, ginsenoside Rg6, malic acid, quinic acid, L-argininosuccinic acid, 3-methyl-3-butenyl-apinosyl (1→6) glucoside, pseudoginsenoside F11, and annonaine were differential components, which might be responsible for variation in efficacy. Further analysis using zebrafish models, network pharmacology, and Q-PCR techniques showed that ginsenoside Rg3, ginsenoside Rg5, ginsenoside Rg6, malic acid, quinic acid, and pseudoginsenoside F11 were the pharmacodynamic markers (P-markers) responsible for anti-heart failure. Conclusion: We have rapidly identified the P-markers against heart failure in AG using the zebrafish model and metabolomics technology. These P-markers may provide new reference standards for quality control and new drug development of AG.
Recent advances in nutritional composition, phytochemistry, bioactive, and potential applications of Syzygium aromaticum L. (Myrtaceae)

Syzygium aromaticum is an aromatic plant native to Indonesia, and introduced to tropical regions worldwide. As an ingredient in perfumes, lotions, and food preservation, it is widely used in the food and cosmetic industries. Also, it is used to treat toothache, ulcers, type 2 diabetes, etc. A variety of nutrients such as amino acids, proteins, fatty acids, and vitamins are found in S. aromaticum. In addition to eugenol, isoeugenol, eugenol acetate, β-caryophyllene and α-humulene are the main chemical constituents. The chemical constituents of S. aromaticum exhibit a wide range of bioactivities, such as antioxidant, antitumor, hypoglycemic, immunomodulatory, analgesic, neuroprotective, anti-obesity, antiulcer, etc. This review aims to comprehend the information on its taxonomy and botany, nutritional composition, chemical composition, bioactivities and their mechanisms, toxicity, and potential applications. This review will be a comprehensive scientific resource for those interested in pursuing further research to explore its value in food.
Antibiofilm activity of secondary metabolites of sponge-associated bacterium Alcanivorax sp. from the Red Sea

Sponge-associated bacteria are a well-known source of unique and diverse natural products with potential biological activities. In this study, a rarely occurring sponge-associated bacterium from the genus Alcanivorax was isolated from the sponge Siphonochalina siphonella and subjected to extraction of metabolites. Metabolites were extracted from the culture supernatant and biomass of the bacterium using the solvent extraction method. Extracts were evaluated for antibacterial and antibiofilm activities against five different biofilm-forming bacteria isolated from the microfouling assemblage. The crude extracts were subjected to chemical profiling to identify their composition using gas chromatography-coupled mass spectrometry (GC-MS). The results obtained show mild to strong antibacterial activity of the extracts against the biofilm-forming bacteria with the minimum inhibitory concentration (MIC) of 3.125 mg ml-1. The percentage inhibition of biofilm formation ranged from 46% to 71%. Compounds detected in GC-MS analysis are mostly fatty acids and their derivatives that include compounds with known antibiofilm activity such as tetradecanoic acid, dodecanoic acid, and hexadecanol from the culture supernatant extract. Eicosane; hexadecanoic acid, methyl ester; and hexadecanoic acid, ethyl ester were detected from the biomass extract. Molecular docking analysis of the compounds from the bacterial extracts confirms their potential antibiofilm properties. The result indicated that Alcanivorax sp. associated with the sponge possess relevant antibiofilm activity and may serve as a novel source of secondary metabolites with the application as antibiofilm agents.
Placental galectin-3 is reduced in early-onset preeclampsia

Preeclampsia is a disease of pregnancy responsible for significant maternal and neonatal mortality. Galectin-3 is a β-Galactoside binding protein. This study aimed to characterise galectin-3 in women with preeclampsia and human trophoblast stem cells (hTSCs). Galectin-3 was measured in placental lysates and plasma collected from patients with early-onset preeclampsia (delivered <34 weeks’ gestation) and gestation matched controls. Placental galectin-3 protein was significantly reduced in 43 women with early-onset preeclampsia compared to 21 controls. mRNA expression of LGALS3 (galectin-3 encoding gene) was reduced in 29 women with early-onset preeclampsia, compared to 18 controls (p = 0.009). There was no significant difference in plasma galectin-3 protein in 46 women with early-onset preeclampsia compared to 20 controls. In a separate cohort of samples collected at 36 weeks’ gestation, circulating galectin-3 was not altered in 23 women who later developed preeclampsia, versus 182 who did not. In syncytialised hTSCs, hypoxia increased mRNA expression of LGALS3 (p = 0.01). Treatment with inflammatory cytokines (TNF-α and IL-6) had no effect on LGALS3 mRNA expression. However, TNF-α treatment caused an increase in mRNA expression of LGALS3BP (galectin-3 binding protein encoding gene) in hTSCs (p = 0.03). This study showed a reduction of galectin-3 in placenta from pregnancies complicated by early-onset preeclampsia. LGALS3 mRNA expression was dysregulated by hypoxia exposure in placental stem cells.
Prediction Model Risk-of-Bias Assessment Tool for coronary artery lesions in Kawasaki disease

Objective To review and critically appraise articles on prediction models for coronary artery lesions (CALs) in Kawasaki disease included in PubMed, Embase, and Web of Science databases from January 1, 1980, to December 23, 2021. Materials and methods Study screening, data extraction, and quality assessment were performed by two independent reviewers, with a statistics expert resolving discrepancies. Articles that developed or validated a prediction model for CALs in Kawasaki disease were included. The Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies checklist was used to extract data from different articles, and Prediction Model Risk-of-Bias Assessment Tool (PROBAST) was used to assess the bias risk in different prediction models. We screened 19 studies from a pool of 881 articles. Results The studies included 73–5,151 patients. In most studies, univariable logistic regression was used to develop prediction models. In two studies, external data were used to validate the developing model. The most commonly included predictors were C-reactive protein (CRP) level, male sex, and fever duration. All studies had a high bias risk, mostly because of small sample size, improper handling of missing data, and inappropriate descriptions of model performance and the evaluation model. Conclusion The prediction models were suitable for the subjects included in the studies, but were poorly effective in other populations. The phenomenon may partly be due to the bias risk in prediction models. Future models should address these problems and PROBAST should be used to guide study design.
Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care

Objective To implement an all-day online artificial intelligence (AI)-assisted detection of ST-elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) to facilitate patient triage for timely reperfusion therapy. Methods The proposed AI model combines a convolutional neural network and long short-term memory (CNN-LSTM) to predict STEMI on prehospital 12-lead ECGs obtained from mini-12-lead ECG devices equipped in ambulance vehicles in Central Taiwan. Emergency medical technicians (EMTs) from the 14 AI-implemented fire stations performed the on-site 12-lead ECG examinations using the mini portable device. The 12-lead ECG signals were transmitted to the AI center of China Medical University Hospital to classify the recordings as “STEMI” or “Not STEMI”. In 11 non-AI fire stations, the ECG data were transmitted to a secure network and read by available on-line emergency physicians. The response time was defined as the time interval between the ECG transmission and ECG interpretation feedback. Results Between July 17, 2021, and March 26, 2022, the AI model classified 362 prehospital 12-lead ECGs obtained from 275 consecutive patients who had called the 119 dispatch centers of fire stations in Central Taiwan for symptoms of chest pain or shortness of breath. The AI's response time to the EMTs in ambulance vehicles was 37.2 ± 11.3 s, which was shorter than the online physicians' response time from 11 other fire stations with no AI implementation (113.2 ± 369.4 s, P < 0.001) after analyzing another set of 335 prehospital 12-lead ECGs. The evaluation metrics including accuracy, precision, specificity, recall, area under the receiver operating characteristic curve, and F1 score to assess the overall AI performance in the remote detection of STEMI were 0.992, 0.889, 0.994, 0.941, 0.997, and 0.914, respectively. During the study period, the AI model promptly identified 10 STEMI patients who underwent primary percutaneous coronary intervention (PPCI) with a median contact-to-door time of 18.5 (IQR: 16–20.8) minutes. Conclusion Implementation of an all-day real-time AI-assisted remote detection of STEMI on prehospital 12-lead ECGs in the field is feasible with a high diagnostic accuracy rate. This approach may help minimize preventable delays in contact-to-treatment times for STEMI patients who require PPCI.
T-cell depleted haploidentical hematopoietic cell transplantation for pediatric malignancy

Access to allogenic hematopoietic cell transplantation (HCT), a potentially curative treatment for chemotherapy-resistant hematologic malignancies, can be limited if no human leukocyte antigen (HLA) identical related or unrelated donor is available. Alternative donors include Cord Blood as well as HLA-mismatched unrelated or related donors. If the goal is to minimize the number of HLA disparities, partially matched unrelated donors are more likely to share 8 or 9 of 10 HLA alleles with the recipient. However, over the last decade, there has been success with haploidentical HCT performed using the stem cells from HLA half-matched related donors. As the majority of patients have at least one eligible and motivated haploidentical donor, recruitment of haploidentical related donors is frequently more rapid than of unrelated donors. This advantage in the accessibility has historically been offset by the increased risks of graft rejection, graft-versus-host disease and delayed immune reconstitution. Various ex vivo T-cell depletion (TCD) methods have been investigated to overcome the immunological barrier and facilitate immune reconstitution after a haploidentical HCT. This review summarizes historical and contemporary clinical trials of haploidentical TCD-HCT, mainly in pediatric malignancy, and describes the evolution of these approaches with a focus on serial improvements in the kinetics of immune reconstitution. Methods of TCD discussed include in vivo as well as ex vivo positive and negative selection. In addition, haploidentical TCD as a platform for post-HCT cellular therapies is discussed. The present review highlights that, as a result of the remarkable progress over half a century, haploidentical TCD-HCT can now be considered as a preferred alternative donor option for children with hematological malignancy in need of allogeneic HCT.
Structure and dynamics of galaxies with a low surface-brightness disc – II. Stellar populations of bulges

We present the radial profiles of the Hβ, Mg and Fe line-strength indices for a sample of eight spiral galaxies with a low-surface-brightness stellar disc and a bulge. The correlations between the central values of the line-strength indices and velocity dispersion are consistent with those known for early-type galaxies and bulges of high-surface-brightness galaxies. The age, metallicity and α/Fe enhancement of the stellar populations in the bulge-dominated region are obtained using stellar population models with variable element abundance ratios. Almost all the sample bulges are characterized by a young stellar population, ongoing star formation and a solar α/Fe enhancement. Their metallicity spans from high to subsolar values. No significant gradient in age and α/Fe enhancement is measured, whereas a negative metallicity gradient is found only in a few cases. These properties suggest that a pure dissipative collapse cannot explain the formation of all the sample bulges and that other phenomena, such as mergers or acquisition events, need to be invoked. Such a picture is also supported by the lack of a correlation between the central value and the gradient of the metallicity in bulges with very low metallicity. The stellar populations of the bulges hosted by low-surface-brightness discs share many properties with those of high-surface-brightness galaxies. Therefore, they are likely to have common formation scenarios and evolution histories. A strong interplay between bulges and discs is ruled out by the fact that, in spite of being hosted by discs with extremely different properties, the bulges of low- and high-surface-brightness discs are remarkably similar.
A NUMERICAL METHOD FOR THE STEADY-STATE PROBABILITIES OF A G1/G/C QUEUING SYSTEM IN A GENERAL CLASS

A numerical method is proposed for solving the balance equations of the steady-state probabilities of a G~/G/c queueing system in a general class. The method is based on an iterative calculation of conditional prob­ abilities, instead of absolute probabilities, conditioned by the number of customers in the system. By skillfully exploiting a convergence property of the conditional probabilities, it provides a fairly accurate solution of the balance equations with relatively little computational burden. In this paper, a numerical method is proposed for solving the balance equa­ tions of the steady-state probabilities of a GI/G/c queueing system in a general class. The method is a direct application of the (modified) lumping method introduced in (6) for the stationary distribution of a Markov chain. It is based on an iterative calculation of conditional probabilities of the queueing system conditioned by the number of customers in the system. By using the conditional probabilities, rather than absolute probabilities, the system of linear equations of the steady-state probabilities is di,'ded into a set of smaller systems of linear equations, and it can be solved with less computational burden by exploiting convergence property of the conditional probabilities. Furthermore, errors included in the solution become fairly small. The computational time required for solving the balance equations by our method is nearly independent of the value of the utilization factor p. Hence, our method is effective even if p is near to l.
EVOLUTION OF SECOND-GENERATION STARS IN STELLAR DISKS OF GLOBULAR AND NUCLEAR CLUSTERS: ω CENTAURI AS A TEST CASE

Globular clusters (GCs) and many nuclear clusters (NCs) show evidence of hosting multiple generations of stellar populations. Younger stellar populations in NCs appear to reside in disk-like structures, including the NC in our own Galactic center as well as in M31. Kinematic studies of the anomalous GC ω Centauri, thought to possibly be a former dwarf galaxy (or a galactic nucleus), show evidence of hosting a central, kinematically cold disk component. These observations suggest that formation of second- (or multiple) generation stars may occur in flattened disk-like structures. Here, we use detailed N-body simulations to explore the possible evolution of such stellar disks embedded in GCs. We follow the long-term evolution of a disk-like structure similar to that observed in ω Centauri and study its properties. We find that a stellar-disk-like origin for second-generation stellar populations can leave behind significant kinematic signatures in properties of the clusters, including an anisotropic distribution and lower velocity dispersions, which can be used to constrain the origin of second-generations stars and their dynamical evolution.