Miracle-dz/UniFAR-FTUs huggingface dataset:
OsWAK112, A Wall-Associated Kinase, Negatively Regulates Salt Stress Responses by Inhibiting Ethylene Production

The wall-associated kinase (WAK) multigene family plays critical roles in various cellular processes and stress responses in plants, however, whether WAKs are involved in salt tolerance is obscure. Herein, we report the functional characterization of a rice WAK, WAK112, whose expression is suppressed by salt. Overexpression of OsWAK112 in rice and heterologous expression of OsWAK112 in Arabidopsis significantly decreased plant survival under conditions of salt stress, while knocking down the OsWAK112 in rice increased plant survival under salt stress. OsWAK112 is universally expressed in plant and associated with cell wall. Meanwhile, in vitro kinase assays and salt tolerance analyses showed that OsWAK112 possesses kinase activity and that it plays a negative role in the response of plants to salt stress. In addition, OsWAK112 interacts with S-adenosyl-L-methionine synthetase (SAMS) 1/2/3, which catalyzes SAM synthesis from ATP and L-methionine, and promotes OsSAMS1 degradation under salt stress. Furthermore, in OsWAK112-overexpressing plants, there is a decreased SAMS content and a decreased ethylene content under salt stress. These results indicate that OsWAK112 negatively regulates plant salt responses by inhibiting ethylene production, possibly via direct binding with OsSAMS1/2/3.
Oligodendroglioma: A Review of Management and Pathways

Anaplastic oligodendrogliomas are a type of glioma that occurs primarily in adults but are also found in children. These tumors are genetically defined according to the mutations they harbor. Grade II and grade III tumors can be differentiated most of the times by the presence of anaplastic features. The earliest regimen used for the treatment of these tumors was procarbazine, lomustine, and vincristine. The treatment modalities have shifted over time, and recent studies are considering immunotherapy as an option as well. This review assesses the latest management modalities along with the pathways involved in the pathogenesis of this malignancies.
Cost-effective, high-throughput phenotyping system for 3D reconstruction of fruit form

Reliable phenotyping methods that are simple to operate and in-expensive to deploy are critical for studying quantitative traits in plants. Traditional fruit shape phenotyping relies on human raters or 2D analyses to assess form, e.g., size and shape. Systems for 3D imaging using multi-view stereo have been implemented, but frequently rely on commercial software and/or specialized hardware, which can lead to limitations in accessibility and scalability. We present a complete system constructed of consumer-grade components for capturing, calibrating, and reconstructing the 3D form of small-to-moderate sized fruits and tubers. Data acquisition and image capture sessions are 9 seconds to capture 60 images. The initial prototype cost was $1600 USD. We measured accuracy by comparing reconstructed models of 3D printed ground truth objects to the original digital files of those same ground truth objects. The R2 between length of the primary, secondary, and tertiary axes, volume, and surface area of the ground-truth object and the reconstructed models was > 0.97 and root-mean square error (RMSE) was <3mm for objects without locally concave regions. Measurements from 1mm and 2mm resolution reconstructions were consistent (R2 > 0.99). Qualitative assessments were performed on 48 fruit and tubers, including 18 strawberries, 12 potatoes, 5 grapes, 7 peppers, and 4 Bosch and 2 red Anjou pears. Our proposed phenotyping system is fast, relatively low cost, and has demonstrated accuracy for certain shape classes, and could be used for the 3D analysis of fruit form.
Bayesian machine learning analysis of single-molecule fluorescence colocalization images

Multi-wavelength single-molecule fluorescence colocalization (CoSMoS) methods allow elucidation of complex biochemical reaction mechanisms. However, analysis of CoSMoS data is intrinsically challenging because of low image signal-to-noise ratios, non-specific surface binding of the fluorescent molecules, and analysis methods that require subjective inputs to achieve accurate results. Here, we use Bayesian probabilistic programming to implement Tapqir, an unsupervised machine learning method that incorporates a holistic, physics-based causal model of CoSMoS data. This method accounts for uncertainties in image analysis due to photon and camera noise, optical non-uniformities, non-specific binding, and spot detection. Rather than merely producing a binary “spot/no spot” classification of unspecified reliability, Tapqir objectively assigns spot classification probabilities that allow accurate downstream analysis of molecular dynamics, thermodynamics, and kinetics. We both quantitatively validate Tapqir performance against simulated CoSMoS image data with known properties and also demonstrate that it implements fully objective, automated analysis of experiment-derived data sets with a wide range of signal, noise, and non-specific binding characteristics.
Online Learning Satisfaction During COVID-19 Pandemic Among Chinese University Students: The Serial Mediation Model

The aim of this study was to investigate the relationship between interaction and online learning satisfaction, whether this relationship is mediated by academic self-efficacy and student engagement among Chinese university students during the COVID-19 pandemic. A serial mediation model was developed to examine the proposed relationship. This study employed a cross-sectional, questionnaire-based research design. A sample of 1,504 Chinese university students (Mage=19.89years, SDage=1.93) from five provinces in China completed an online survey questionnaire from December 2020 to January 2021 to respond to questions on demographic characteristics and items to measure the variables in the research model. The partial least squares structural equation modeling was used to assess the measurement model and proposed serial mediation model. Data were analyzed using SmartPLS software version 3.3. 2. The results of the measurement model showed good reliability and validity for all constructs. The results of the structural model and hypothesis testing showed that all hypotheses were supported in this study. Particularly, there was a significant positive relationship between interaction and online learning satisfaction (Q1), interaction and academic self-efficacy (Q2), academic self-efficacy and student engagement (Q3), and the student engagement and online learning satisfaction (Q4). In addition, the results showed that academic self-efficacy and student engagement serial mediated the relationship between interaction and online learning satisfaction (Q5). The serial mediation model explained 34.6% of the variance of online learning satisfaction. The findings shed light on the underlying mechanisms that explain students’ online learning satisfaction during the COVID-19 pandemic. Universities and policymakers need to make better decisions that ultimately could lead to students’ academic outcomes and achievement.
Natural and designed proteins inspired by extremotolerant organisms can form condensates and attenuate apoptosis in human cells

Many organisms can survive extreme conditions and successfully recover to normal life. This extremotolerant behavior has been attributed in part to repetitive, amphipathic, and intrinsically disordered proteins that are upregulated in the protected state. Here, we assemble a library of approximately 300 naturally-occurring and designed extremotolerance-associated proteins to assess their ability to protect human cells from chemically-induced apoptosis. We show that several proteins from tardigrades, nematodes, and the Chinese giant salamander are apoptosis protective. Notably, we identify a region of the human ApoE protein with similarity to extremotolerance-associated proteins that also protects against apoptosis. This region mirrors the phase separation behavior seen with such proteins, like the tardigrade protein CAHS2. Moreover, we identify a synthetic protein, DHR81, that shares this combination of elevated phase separation propensity and apoptosis protection. Finally, we demonstrate that driving protective proteins into the condensate state increases apoptosis protection, and highlight the ability for DHR81 condensates to sequester caspase-7. Taken together, this work draws a link between extremotolerance-associated proteins, condensate formation, and designing human cellular protection.
Assessing Genomic Diversity and Productivity Signatures in Dianzhong Cattle by Whole-Genome Scanning

Dianzhong cattle is a classic Chinese indigenous cattle breed with historical records dating back to 200 BC. But with its genomic differences having not been clearly elucidated, the quest for genomic characterization will be an essential step towards understanding the genomic basis of productivity and adaptation to survival under Chinese farming systems. Here we compared 10 Dianzhong cattle (four newly sequenced and six downloaded) with 29 published genomes of three underlying ancestral populations (Chinese zebu, Indian zebu, and Yanbian cattle) to characterize the genomic variations of Dianzhong cattle. Dianzhong cattle has a high nucleotide diversity (0.0034), second only to Chinese zebu. Together with analyses of linkage disequilibrium decay and runs of homozygosity, Dianzhong cattle displayed higher genomic diversity and weaker artificial selection compared with Yanbian cattle. From a selective sweep analysis by four methods (Fst, π-ratio, XP-CLR, and XP-EHH), the positive selective signals were mainly manifested in candidate genes and pathways related to heat resistance, growth and development, fat deposition, and male reproduction. Missense mutations were detected in candidate genes, SDS (c.944C > A and p.Ala315Glu), PDGFD (c.473A > G and p.Lys158Arg), and DDX4 (rs460251486, rs722912933, and rs517668236), which related to heat resistance, fat deposition, and spermatogenesis, respectively. Our findings unravel, at the genome-wide level, the unique diversity of Dianzhong cattle while emphasizing the opportunities for improvement of livestock productivity in further breeding programs.
Efficient single copy integration via homology-directed repair (scHDR) by 5′modification of large DNA donor fragments in mice

CRISPR/Cas approaches have largely replaced conventional gene targeting strategies. However, homology-directed repair (HDR) in the mouse genome is not very efficient, and precisely inserting longer sequences using HDR remains challenging, given that donor constructs preferentially integrate as concatemers. Here, we show that injecting 5’biotinylated donor DNA in mouse embryos at the two-cell stage leads to efficient single-copy HDR (scHDR) alleles. Our dedicated genotyping strategy showed that these alleles occurred with a frequency of 19%, 20%, and 26%, respectively, in three independent gene loci, indicating that scHDR is dramatically boosted by 5’biotinylation. Thus, we suggest that a combination of a 5’biotinylated donor and diligent analysis of concatemer integration are prerequisites for efficiently and reliably generating conditional alleles or other large fragment knock-ins into the mouse genome.
Direct quantification of ligand-induced lipid and protein microdomains with distinctive signaling properties

Lipid rafts are known as highly ordered lipid domains that are enriched in saturated lipids such as the ganglioside GM1. While lipid rafts are believed to exist in cells and to serve as signaling platforms through their enrichment in signaling components, they have never been directly observed in the plasma membrane without treatments that artificially cluster GM1 into large lattices. Here we report that microscopic GM1-enriched domains can form, without lipid cross-linking, in the plasma membrane of live mammalian cells expressing the EphA2 receptor tyrosine kinase in response to its ligand ephrinA1-Fc. The GM1-enriched microdomains form concomitantly with EphA2-enriched microdomains, but only partially co-localize with them. To gain insight into how plasma membrane heterogeneity controls signaling, we quantify the degree of EphA2 segregation and study initial EphA2 signaling steps in both EphA2-enriched and EphA2-depleted domains. By measuring dissociation constants, we demonstrate that EphA2 oligomerization is the same in EphA2-enriched and -depleted domains. However, EphA2 interacts preferentially with its downstream effector SRC in EphA2-depleted domains. The ability to induce microscopic GM1-enriched domains in live cells using a ligand for a transmembrane receptor will give us unprecedented opportunities to study the biology of lipid rafts.
Drought, Salinity, and Low Nitrogen Differentially Affect the Growth and Nitrogen Metabolism of Sophora japonica (L.) in a Semi-Hydroponic Phenotyping Platform

Abiotic stresses, such as salinity, drought, and nutrient deficiency adversely affect nitrogen (N) uptake and assimilation in plants. However, the regulation of N metabolism and N pathway genes in Sophora japonica under abiotic stresses is unclear. Sophora japonica seedlings were subjected to drought (5% polyethylene glycol 6,000), salinity (75mM NaCl), or low N (0.01mM NH4NO3) for 3weeks in a semi-hydroponic phenotyping platform. Salinity and low N negatively affected plant growth, while drought promoted root growth and inhibited aboveground growth. The NH4+/NO3− ratio increased under all three treatments with the exception of a reduction in leaves under salinity. Drought significantly increased leaf NO2− concentrations. Nitrate reductase (NR) activity was unaltered or increased under stresses with the exception of a reduction in leaves under salinity. Drought enhanced ammonium assimilation with increased glutamate synthase (GOGAT) activity, although glutamine synthetase (GS) activity remained unchanged, whereas salinity and low N inhibited ammonium assimilation with decreased GS activity under salt stress and decreased GOGAT activity under low N treatment. Glutamate dehydrogenase (GDH) activity also changed dramatically under different stresses. Additionally, expression changes of genes involved in N reduction and assimilation were generally consistent with related enzyme activities. In roots, ammonium transporters, especially SjAMT1.1 and SjAMT2.1a, showed higher transcription under all three stresses; however, most nitrate transporters (NRTs) were upregulated under salinity but unchanged under drought. SjNRT2.4, SjNRT2.5, and SjNRT3.1 were highly induced by low N. These results indicate that N uptake and metabolism processes respond differently to drought, salinity, and low N conditions in S. japonica seedlings, possibly playing key roles in plant resistance to environmental stress.
Generation of a molecular interactome of the glioblastoma perivascular niche reveals Integrin Binding Sialoprotein as a key mediator of tumor cell migration

Glioblastoma (GBM) is characterized by extensive microvascular hyperproliferation. In addition to supplying blood to the tumor, GBM vessels also provide trophic support to glioma cells and serve as conduits for migration into the surrounding brain promoting recurrence. Here, we enriched CD31-expressing glioma vascular cells (GVC) and A2B5-expressing glioma tumor cells (GTC) from primary GBM and utilized RNA sequencing to create a comprehensive interaction map of the secreted and extracellular factors elaborated by GVC that can interact with receptors and membrane molecules on GTC. To validate our findings, we utilized functional assays, including a novel hydrogel-based migration assay and in vivo mouse models to demonstrate that one identified factor, the little-studied integrin binding sialoprotein (IBSP) enhances tumor growth and promotes the migration of GTC along the vasculature. This perivascular niche interactome will serve a resource to the research community in defining the potential functions of the GBM vasculature.
Prediction of Ovarian Cancer-Related Metabolites Based on Graph Neural Network

Ovarian cancer is one of the three most malignant tumors of the female reproductive system. At present, researchers do not know its pathogenesis, which makes the treatment effect unsatisfactory. Metabolomics is closely related to drug efficacy, safety evaluation, mechanism of action, and rational drug use. Therefore, identifying ovarian cancer-related metabolites could greatly help researchers understand the pathogenesis and develop treatment plans. However, the measurement of metabolites is inaccurate and greatly affects the environment, and biological experiment is time-consuming and costly. Therefore, researchers tend to use computational methods to identify disease-related metabolites in large scale. Since the hypothesis that similar diseases are related to similar metabolites is widely accepted, in this paper, we built both disease similarity network and metabolite similarity network and used graph convolutional network (GCN) to encode these networks. Then, support vector machine (SVM) was used to identify whether a metabolite is related to ovarian cancer. The experiment results show that the AUC and AUPR of our method are 0.92 and 0.81, respectively. Finally, we proposed an effective method to prioritize ovarian cancer-related metabolites in large scale.
Prolonged Sojourn at Very High Altitude Decreases Sea-Level Anaerobic Performance, Anaerobic Threshold, and Fat Mass

Background: The influence of high altitude on an organism’s physiology depends on the length and the level of hypoxic exposure it experiences. This study aimed to determine the effect of a prolonged sojourn at very high altitudes (above 3,500m) on subsequent sea-level physical performance, body weight, body composition, and hematological parameters. Materials and Methods: Ten alpinists, nine males and one female, with a mean age of 27±4years, participated in the study. All had been on mountaineering expeditions to 7,000m peaks, where they spent 30±1days above 3,500m with their average sojourn at 4,900±60m. Their aerobic and anaerobic performance, body weight, body composition, and hematological parameters were examined at an altitude of 100m within 7days before the expeditions and 7days after they descended below 3,500m. Results: We found a significant (p<0.01) decrease in maximal anaerobic power (MAPWAnT) from 9.9±1.3 to 9.2±1.3W·kg−1, total anaerobic work from 248.1±23.8 to 228.1±20.1J·kg−1, anaerobic threshold from 39.3±8.0 to 27.8±5.6 mlO2·kg−1·min−1, body fat mass from 14.0±3.1 to 11.5±3.3%, and a significant increase (p<0.05) in maximal tidal volume from 3.2 [3.0–3.2] to 3.5 [3.3–3.9] L after their sojourn at very high attitude. We found no significant changes in maximal aerobic power, maximal oxygen uptake, body weight, fat-free mass, total body water, hemoglobin, and hematocrit. Conclusion: A month-long exposure to very high altitude led to impaired sea-level anaerobic performance and anaerobic threshold, increased maximal tidal volume, and depleted body fat mass, but had no effect on maximal aerobic power, maximal oxygen uptake, or hemoglobin and hematocrit levels.
Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient?

Purpose Dynamic amino acid positron emission tomography (PET) has become essential in neuro-oncology, most notably for its prognostic value in the noninvasive prediction of isocitrate dehydrogenase (IDH) mutations in newly diagnosed gliomas. The 6-[18F]fluoro-l-DOPA (18F-FDOPA) kinetic model has an underlying complexity, while previous studies have predominantly used a semiquantitative dynamic analysis. Our study addresses whether a semiquantitative analysis can capture all the relevant information contained in time–activity curves for predicting the presence of IDH mutations compared to the more sophisticated graphical and compartmental models. Methods Thirty-seven tumour time–activity curves from 18F-FDOPA PET dynamic acquisitions of newly diagnosed gliomas (median age = 58.3 years, range = 20.3–79.9 years, 16 women, 16 IDH-wild type) were analyzed with a semiquantitative model based on classical parameters, with (SQ) or without (Ref SQ) a reference region, or on parameters of a fit function (SQ Fit), a graphical Logan model with input function (Logan) or reference region (Ref Logan), and a two-tissue compartmental model previously reported for 18F-FDOPA PET imaging of gliomas (2TCM). The overall predictive performance of each model was assessed with an area under the curve (AUC) comparison using multivariate analysis of all the parameters included in the model. Moreover, each extracted parameter was assessed in a univariate analysis by a receiver operating characteristic curve analysis. Results The SQ model with an AUC of 0.733 for predicting IDH mutations showed comparable performance to the other models with AUCs of 0.752, 0.814, 0.693, 0.786, and 0.863, respectively corresponding to SQ Fit, Ref SQ, Logan, Ref Logan, and 2TCM (p ≥ 0.10 for the pairwise comparisons with other models). In the univariate analysis, the SQ time-to-peak parameter had the best diagnostic performance (75.7% accuracy) compared to all other individual parameters considered. Conclusions The SQ model circumvents the complexities of the 18F-FDOPA kinetic model and yields similar performance in predicting IDH mutations when compared to the other models, most notably the compartmental model. Our study provides supportive evidence for the routine clinical application of the SQ model for the dynamic analysis of 18F-FDOPA PET images in newly diagnosed gliomas.
Advances in Implantable Optogenetic Technology for Cardiovascular Research and Medicine

Optogenetic technology provides researchers with spatiotemporally precise tools for stimulation, sensing, and analysis of function in cells, tissues, and organs. These tools can offer low-energy and localized approaches due to the use of the transgenically expressed light gated cation channel Channelrhodopsin-2 (ChR2). While the field began with many neurobiological accomplishments it has also evolved exceptionally well in animal cardiac research, both in vitro and in vivo. Implantable optical devices are being extensively developed to study particular electrophysiological phenomena with the precise control that optogenetics provides. In this review, we highlight recent advances in novel implantable optogenetic devices and their feasibility in cardiac research. Furthermore, we also emphasize the difficulties in translating this technology toward clinical applications and discuss potential solutions for successful clinical translation.