Miracle-dz/UniFAR-FTUs huggingface dataset:
Peptidylarginine Deiminases Post-Translationally Deiminate Prohibitin and Modulate Extracellular Vesicle Release and MicroRNAs in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most aggressive form of adult primary malignant brain tumour with poor prognosis. Extracellular vesicles (EVs) are a key-mediator through which GBM cells promote a pro-oncogenic microenvironment. Peptidylarginine deiminases (PADs), which catalyze the post-translational protein deimination of target proteins, are implicated in cancer, including via EV modulation. Pan-PAD inhibitor Cl-amidine affected EV release from GBM cells, and EV related microRNA cargo, with reduced pro-oncogenic microRNA21 and increased anti-oncogenic microRNA126, also in combinatory treatment with the chemotherapeutic agent temozolomide (TMZ). The GBM cell lines under study, LN18 and LN229, differed in PAD2, PAD3 and PAD4 isozyme expression. Various cytoskeletal, nuclear and mitochondrial proteins were identified to be deiminated in GBM, including prohibitin (PHB), a key protein in mitochondrial integrity and also involved in chemo-resistance. Post-translational deimination of PHB, and PHB protein levels, were reduced after 1 h treatment with pan-PAD inhibitor Cl-amidine in GBM cells. Histone H3 deimination was also reduced following Cl-amidine treatment. Multifaceted roles for PADs on EV-mediated pathways, as well as deimination of mitochondrial, nuclear and invadopodia related proteins, highlight PADs as novel targets for modulating GBM tumour communication.
How Does Diet Change with A Diagnosis of Diabetes? Protocol of the 3D Longitudinal Study

Diet quality influences glycemic control in people with type 2 diabetes (T2D), impacting their risk of complications. While there are many cross-sectional studies of diet and diabetes, there is little understanding of the extent to which people with T2D change their diet after diagnosis and of the factors that impact those changes. This paper describes the rationale for and design of the 3D longitudinal Study which aims to: (i) describe diet quality changes in the 12 months following T2D diagnosis, (ii) identify the demographic, physical and psychosocial predictors of sustained improvements in diet quality and glycemic control, and (iii) identify associations between glycemic control and diet quality in the 12 months following diagnosis. This cohort study will recruit adults registered with the Australian National Diabetes Services Scheme who have been recently diagnosed with T2D. Participants will be involved in five purposefully developed telephone surveys, conducted at 3 monthly intervals over a 12-month period. Diet quality will be determined using a 24-h dietary recall at each data collection point and the data will be scored using the Dietary Approaches to Stop Hypertension (DASH) diet-quality tool. This study is the first dedicated to observing how people newly diagnosed with T2D change their diet quality over time and the predictors of sustained improvements in diet and glycemic control.
A trial comparing emergency front of neck airway performance in a novel obese‐synthetic neck, meat‐modified obese neck and conventional slim manikin

Conventional emergency front of neck airway training manikins mimic slim patients and are associated with unrealistic procedural ease. We have described previously a pork belly‐modified manikin that more realistically simulated an obese patient's neck. In this study, we compared a novel obese‐synthetic manikin (obese‐synthetic manikin) with a pork belly‐modified manikin (obese‐meat manikin) and a conventional slim manikin (slim manikin). Thirty‐three experienced anaesthetists undertook simulated emergency front of neck airway procedures on each manikin (total 99 procedures). Time to ventilation was longer on both obese manikins compared with the slim manikin (median (IQR [range]) time to intubation 159 (126–243 [73–647]) s in the obese‐synthetic, 105 (72–138 [43–279]) s in the obese‐meat and 58 (47–74 [30–370]) s in the slim manikin; p < 0.001 between each manikin). Cricothyroidotomy success rate was similar in the both obese manikins but lower when compared with the slim manikin (15/33 obese‐synthetic vs. 14/33 obese‐meat vs. 27/33 slim manikin). Participant feedback indicated performance difficulty was similar between both obese manikins, which were both more difficult than the slim manikin. The tissues of the obese‐meat manikin were judged more realistic than those of either other manikin. Overall, the obese‐synthetic manikin performed broadly similarly to the obese‐meat manikin and was technically more difficult than the conventional slim manikin. The novel obese‐synthetic manikin maybe useful for training and research in front of neck airway procedures.
Body language reading of emotion and outcome in schizophrenia

ABSTRACT Introduction: Although considered a promising design for testing social cognition, it is not clear to what extent the EmoBio test of emotion recognition actually predicts community functioning. It is also not clear whether the test measures something unique or different from nonsocial cognition. The present study tests whether EmoBio accounts for GAF function score and two operationalised community outcome measures. The study also analyses cognitive predictors of EmoBio performance, testing whether stimulus modality affects prediction. Methods: Eighty-three patients with schizophrenia were tested with EmoBio, the cognitive battery MCCB and WAIS-IV. Results: EmoBio accounted for a significant portion of variance in all three outcome measures. Only EmoBio predicted Lifetime Relationship status, and EmoBio remained a significant predictor of Independent living beyond non-social cognition. All cognitive measures contributed significantly to the variance in EmoBio, but entered together explained only a third of total variance. Conclusion: The study shows that emotion recognition accounts for community outcome. There was no clear effect of test-modality in predicting EmoBio performance, indicating no method invariance problem with EmoBio. It also indicates that the mechanisms underlying impaired social cognition in schizophrenia are different from the hypothesised non-verbal learning deficits in the disorder.
A Decentralized Privacy-Preserving Healthcare Blockchain for IoT

Medical care has become one of the most indispensable parts of human lives, leading to a dramatic increase in medical big data. To streamline the diagnosis and treatment process, healthcare professionals are now adopting Internet of Things (IoT)-based wearable technology. Recent years have witnessed billions of sensors, devices, and vehicles being connected through the Internet. One such technology—remote patient monitoring—is common nowadays for the treatment and care of patients. However, these technologies also pose grave privacy risks and security concerns about the data transfer and the logging of data transactions. These security and privacy problems of medical data could result from a delay in treatment progress, even endangering the patient’s life. We propose the use of a blockchain to provide secure management and analysis of healthcare big data. However, blockchains are computationally expensive, demand high bandwidth and extra computational power, and are therefore not completely suitable for most resource-constrained IoT devices meant for smart cities. In this work, we try to resolve the above-mentioned issues of using blockchain with IoT devices. We propose a novel framework of modified blockchain models suitable for IoT devices that rely on their distributed nature and other additional privacy and security properties of the network. These additional privacy and security properties in our model are based on advanced cryptographic primitives. The solutions given here make IoT application data and transactions more secure and anonymous over a blockchain-based network.
Synchronized activation of striatal direct and indirect pathways underlies the behavior in unilateral dopamine‐depleted mice

For more than three decades it has been known, that striatal neurons become hyperactive after the loss of dopamine input, but the involvement of dopamine (DA) D1‐ or D2‐receptor‐expressing neurons has only been demonstrated indirectly. By recording neuronal activity using fluorescent calcium indicators in D1 or D2 eGFP‐expressing mice, we showed that following dopamine depletion, both types of striatal output neurons are involved in the large increase in neuronal activity generating a characteristic cell assembly of particular neurons that dominate the pattern. When we expressed channelrhodopsin in all the output neurons, light activation in freely moving animals, caused turning like that following dopamine loss. However, if the light stimulation was patterned in pulses the animals circled in the other direction. To explore the neuronal participation during this stimulation we infected normal mice with channelrhodopsin and calcium indicator in striatal output neurons. In slices made from these animals, continuous light stimulation for 15 s induced many cells to be active together and a particular dominant group of neurons, whereas light in patterned pulses activated fewer cells in more variable groups. These results suggest that the simultaneous activity of a large dominant group of striatal output neurons is intimately associated with parkinsonian symptoms.
Aspirin Use and Cardiovascular Outcome in Patients With Type 2 Diabetes Mellitus and Heart Failure: A Population‐Based Cohort Study

Background Aspirin is of uncertain benefit for primary prevention in patients with type 2 diabetes mellitus (T2D). We assessed whether primary prevention with aspirin is beneficial in patients with T2D and heart failure (HF). Methods and Results Data from The Health Improvement Network, a UK multicenter prospective primary care database, were analyzed. Those with T2D and HF, age ≥55 years, and no previous history of myocardial infarction and/or coronary artery disease, stroke, peripheral artery disease, or atrial fibrillation were included. We compared outcomes for those on aspirin to no aspirin after diagnosis of HF and T2D and assessed the role of a >75‐mg dose. The primary outcome was a composite of all‐cause mortality and hospitalization for HF; secondary outcomes were nonfatal stroke, nonfatal myocardial infarction, or major bleeding. There were 5967 participants on aspirin and 6567 not on aspirin. The mean age (SD) was 75.3 (9.6) years, 53.9% were men, and the mean follow‐up (SD) was for 5 (4.2) years. After propensity‐score matching and further multivariable adjustment, aspirin was significantly associated with a decrease in the primary outcome and all‐cause mortality (hazard ratio=0.88, 95% confidence interval 0.82‐0.93; 0.88, 0.83‐0.94], respectively); and an increased risk of nonfatal myocardial infarction (hazard ratio=1.66; 95% confidence interval 1.49‐1.85) and nonfatal stroke (hazard ratio=1.23, 1.01‐1.50). Major bleedings and hospitalization for HF were not significantly higher with aspirin (hazard ratio=0.68, 0.45‐1.03; 0.87, 0.66‐1.15, respectively). There was no additional benefit for a dose >75 mg. Conclusions Primary prevention with aspirin in patients with T2D and HF is associated with lower all‐cause mortality.
The finite state projection based Fisher information matrix approach to estimate information and optimize single-cell experiments

Modern optical imaging experiments not only measure single-cell and single-molecule dynamics with high precision, but they can also perturb the cellular environment in myriad controlled and novel settings. Techniques, such as single-molecule fluorescence in-situ hybridization, microfluidics, and optogenetics, have opened the door to a large number of potential experiments, which begs the question of how best to choose the best possible experiment. The Fisher information matrix (FIM) estimates how well potential experiments will constrain model parameters and can be used to design optimal experiments. Here, we introduce the finite state projection (FSP) based FIM, which uses the formalism of the chemical master equation to derive and compute the FIM. The FSP-FIM makes no assumptions about the distribution shapes of single-cell data, and it does not require precise measurements of higher order moments of such distributions. We validate the FSP-FIM against well-known Fisher information results for the simple case of constitutive gene expression. We then use numerical simulations to demonstrate the use of the FSP-FIM to optimize the timing of single-cell experiments with more complex, non-Gaussian fluctuations. We validate optimal simulated experiments determined using the FSP-FIM with Monte-Carlo approaches and contrast these to experiment designs chosen by traditional analyses that assume Gaussian fluctuations or use the central limit theorem. By systematically designing experiments to use all of the measurable fluctuations, our method enables a key step to improve co-design of experiments and quantitative models. Author summary A main objective of quantitative modeling is to predict the behaviors of complex systems under varying conditions. In a biological context, stochastic fluctuations in expression levels among isogenic cell populations have required modeling efforts to incorporate and even rely upon stochasticity. At the same time, new experimental variables such as chemical induction and optogenetic control have created vast opportunities to probe and understand gene expression, even at single-molecule and single-cell precision. With many possible measurements or perturbations to choose from, researchers require sophisticated approaches to choose which experiment to perform next. In this work, we provide a new tool, the finite state projection based Fisher information matrix (FSP-FIM), which considers all cell-to-cell fluctuations measured in modern data sets, and can design optimal experiments under these conditions. Unlike previous approaches, the FSP-FIM does not make any assumptions about the shape of the distribution being measured. This new tool will allow experimentalists to optimally perturb systems to learn as much as possible about single-cell processes with a minimum of experimental cost or effort.
RNA Switches for Synthetic Biology.

SummaryIn addition to coding for protein sequences, RNA molecules encode a diverse set of gene-regulatory elements. RNA switches are one class of gene-regulatory elements that control protein expression in a manner that is dependent on the concentration of specific ligand molecules. These allosteric gene-regulatory elements have been shown as useful tools in engineering diverse cell types to display novel function. In particular, RNA switches have been used as genetically encoded biosensors and conditional controllers to direct cellular decisions based on the system's changing environment. A significant focus in the field has been the generation of novel RNA switches that are tailored for different biological systems. We review approaches that have been used to generate RNA switches, which leverage the unique physical properties of RNA and the myriad ways in which RNA can modulate gene expression.
Toxin ζ Reduces the ATP and Modulates the Uridine Diphosphate-N-acetylglucosamine Pool

Toxin ζ expression triggers a reversible state of dormancy, diminishes the pool of purine nucleotides, promotes (p)ppGpp synthesis, phosphorylates a fraction of the peptidoglycan precursor uridine diphosphate-N-acetylglucosamine (UNAG), leading to unreactive UNAG-P, induces persistence in a reduced subpopulation, and sensitizes cells to different antibiotics. Here, we combined computational analyses with biochemical experiments to examine the mechanism of toxin ζ action. Free ζ toxin showed low affinity for UNAG. Toxin ζ bound to UNAG hydrolyzed ATP·Mg2+, with the accumulation of ADP, Pi, and produced low levels of phosphorylated UNAG (UNAG-P). Toxin ζ, which has a large ATP binding pocket, may temporally favor ATP binding in a position that is distant from UNAG, hindering UNAG phosphorylation upon ATP hydrolysis. The residues D67, E116, R158 and R171, involved in the interaction with metal, ATP, and UNAG, were essential for the toxic and ATPase activities of toxin ζ; whereas the E100 and T128 residues were partially dispensable. The results indicate that ζ bound to UNAG reduces the ATP concentration, which indirectly induces a reversible dormant state, and modulates the pool of UNAG.
Expanding Repertoire of Plant Positive-Strand RNA Virus Proteases

Many plant viruses express their proteins through a polyprotein strategy, requiring the acquisition of protease domains to regulate the release of functional mature proteins and/or intermediate polyproteins. Positive-strand RNA viruses constitute the vast majority of plant viruses and they are diverse in their genomic organization and protein expression strategies. Until recently, proteases encoded by positive-strand RNA viruses were described as belonging to two categories: (1) chymotrypsin-like cysteine and serine proteases and (2) papain-like cysteine protease. However, the functional characterization of plant virus cysteine and serine proteases has highlighted their diversity in terms of biological activities, cleavage site specificities, regulatory mechanisms, and three-dimensional structures. The recent discovery of a plant picorna-like virus glutamic protease with possible structural similarities with fungal and bacterial glutamic proteases also revealed new unexpected sources of protease domains. We discuss the variety of plant positive-strand RNA virus protease domains. We also highlight possible evolution scenarios of these viral proteases, including evidence for the exchange of protease domains amongst unrelated viruses.
Genistein induces apoptosis in vitro and has antitumor activity against human leukemia HL‐60 cancer cell xenograft growth in vivo

Genistein, a major isoflavone compound in soybeans, has been shown to have biological activities including anti‐cancer activates. In the present, we investigated the anti‐leukemia activity of genistein on HL‐60 cells in vitro. The percentage of viable cell, cell cycle distribution, apoptotic cell death, reactive oxygen species (ROS), and Ca2+ production and the level of ΔΨm were measured by flow cytometric assay. Cell apoptosis and endoplasmic reticulum (ER) stress associated protein expressions were examined by Western blotting assay. Calpain 1, GRP78, and GADD153 expression were measured by confocal laser microscopy. Results indicated that genistein‐induced cell morphological changes, decreased the total viable cells, induced G2/M phase arrest and DNA damage and fragmentation (cell apoptosis) in HL‐60 cells. Genistein promoted ROS and Ca2+ productions and decreased the level of ΔΨm in HL‐60 cells. Western blotting assay demonstrated that genistein increased ER stress‐associated protein expression such as IRE‐1α, Calpain 1, GRP78, GADD153, caspase‐7, caspase‐4, and ATF‐6α at 20‐50 μM treatment and increased apoptosis associated protein expression such as pro‐apoptotic protein Bax, PARP‐cleavage, caspase‐9, and ‐3, but decreased anti‐apoptotic protein such as Bcl‐2 and Bid in HL‐60 cells. Calpain 1, GRP78, and GADD153 were increased in HL‐60 cells after exposure to 40 μM of genistein. In animal xenografted model, mice were intraperitoneally injected with genistein (0, 0.2, and 0.4 mg/kg) for 28 days and the body weight and tumor volume were recorded. Results showed that genistein did not affect the body weights but significantly reduced the tumor weight in 0.4 mg/kg genistein‐treated group. Genistein also increased the expressions of ATF‐6α, GRP78, Bax, Bad, and Bak in tumor. In conclusion, genistein decreased cell number through G2/M phase arrest and the induction of cell apoptosis through ER stress‐ and mitochondria‐dependent pathways in HL‐60 cells and suppressed tumor properties in vivo.
Measurements of lycopene contents in fruit: A review of recent developments in conventional and novel techniques

Abstract Lycopene is a biologically active phytochemical reported in fruit. Conventional techniques such as high performance liquid chromatography (HPLC) and thin layer chromatography (TLC) have been in existence for measuring lycopene in fruit, but these methods are destructive with relative accuracy and speed. Other novel spectroscopic and imaging approaches, which are more reliable and fast, have recently been developed to investigate complex components such as lycopene, total soluble solids, etc. in fruit. The current review attempts to highlight the potential of both conventional and novel techniques in evaluating lycopene contents of fruit. The novel techniques include both spectroscopic methods such as near infrared spectroscopy and Raman spectroscopy and spectral imaging approaches such as multispectral imaging, hyperspectral imaging and Raman imaging. The principles of these techniques are summarized, their detailed applications are discussed, and future trends are also presented. Both traditional and novel techniques highlighted in the current review can be used for assessing the distribution and concentration of lycopene in various fruit. Although novel spectroscopic and spectral imaging approaches may in the near future replace conventional methods, because conventional methods are typically often offline, destructive and time-consuming, which also require the use of chemicals.
Motion-Based Educational Games: Using Multi-Modal Data to Predict Player’s Performance

Multi-Modal Data (MMD) can help educational games researchers understand the synergistic relationship between player’s movement and their learning experiences, and consequently uncover insights that may lead to improved design of movement-based game technologies for learning. Predicting player performance fosters opportunities to cultivate heightened educational experiences and outcomes. However, predicting player’s performance utilising player-generated MMD during their interactions with educational Motion-Based Touchless Games (MBTG) is challenging. To bridge this gap, we implemented an in-situ study where 26 users, age 11, played 2 maths MBTGs in a single 20-30 minute session. We collected player’s MMD (i.e., gaze data from eye-tracking glasses, physiological data from wristbands, and skeleton data from Kinect) produced during game-play. To investigate the potential of MMD for predicting player’s academic performance, we used machine learning techniques and MMD derived from player’s game-play. This allowed us to identify the MMD features that drive rapid highly accurate predictions of players’ academic performance in educational MBTGs. This might allow us to provide real-time proactive feedback to the player to support them through their educational gaming experience. Our analysis compared two data lengths corresponding to half and full duration of the player’s question solving time. We showed that all combinations of extracted features associated with gaze, physiological, and skeleton data, predicted student performance more accurately than the majority baseline. Additionally, the most accurate prediction of player’s performance derived from the combination of gaze and physiological data for both full and half data lengths. Our findings emphasise the significance of using MMD for real-time performance prediction in educational MBTG and offer implications for practice.