Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrastructural Characteristics of Neuronal Death and White Matter Injury in Mouse Brain Tissues After Intracerebral Hemorrhage: Coexistence of Ferroptosis, Autophagy, and Necrosis

Although intracerebral hemorrhage (ICH) is a devastating disease worldwide, the pathologic changes in ultrastructure during the acute and chronic phases of ICH are poorly described. In this study, transmission electron microscopy was used to examine the ultrastructure of ICH-induced pathology. ICH was induced in mice by an intrastriatal injection of collagenase. Pathologic changes were observed in the acute (3 days), subacute (6 days), and chronic (28 days) phases. Compared with sham animals, we observed various types of cell death in the injured striatum during the acute phase of ICH, including necrosis, ferroptosis, and autophagy. Different degrees of axon degeneration in the striatum were seen in the acute phase, and axonal demyelination was observed in the ipsilateral striatum and corpus callosum at late time points. In addition, phagocytes, resident microglia, and infiltrating monocyte-macrophages were present around red blood cells and degenerating neurons and were observed to engulf red blood cells and other debris. Many synapses appeared abnormal or were lost. This systematic analysis of the pathologic changes in ultrastructure after ICH in mice provides information that will be valuable for future ICH pathology studies.
Origin-Destination Trajectory Diversity Analysis: Efficient Top-k Diversified Search

Given a pair of Origin-Destination (OD) locations, the set of trajectories passing from the original to destination, usually possesses the nature to reflect different traveling patterns between OD. In general, the higher diversity these trajectories have, the more various traveling behaviors and greater robustness of the connectivity can be revealed, which highly raises the value of transportation analysis towards the corresponding OD pair. Therefore, in this paper, we introduce a comprehensive and rational measure for trajectory diversity, on top of which we propose a novel query, Top-k Diversified Search (TkDS), that aims to find a set of k OD pairs among all the given OD pairs such that the trajectories traversing in-between have the highest diversity. Owing to the intrinsic characteristics of trajectory data, the computational cost for diversity is considerably high. Thus we present an efficient bounding algorithm with early termination to filter the candidates that are impossible to contribute the result. Finally, we demonstrate some case studies for trajectory diversity on real world dataset and give a comprehensive performance evaluation on the Top-k Diversified Search.
The Influence of the Timing of Cyclic Load Application on Cardiac Cell Contraction

Cardiac cells are subjected to mechanical load during each heart-beat. Normal heart load is essential for physiological development and cardiac function. At the same time, excessive load can induce pathologies such as cardiac hypertrophy. While the forces working on the heart as an organ are well-understood, information regarding stretch response at the cellular level is limited. Since cardiac stretch-response depends on the amplitude and pattern of the applied load as well as its timing during the beating cycle, the directionality of load application and its phase relative to action potential generation must be controlled precisely. Here, we design a new experimental setup, which enables high-resolution fluorescence imaging of cultured cardiac cells under cyclic uniaxial mechanical load and electrical stimulation. Cyclic stretch was applied in different phases relative to the electrical stimulus and the effect on cardiac cell beating was monitored. The results show a clear phase-dependent response and provide insight into cardiac response to excessive loading conditions.
The Effect of Mesenchymal Stem Cell-Derived Microvesicles on Erythroid Differentiation of Umbilical Cord Blood-Derived CD34+ Cells

Purpose: Mesenchymal stem cells (MSCs) play an important role in the proliferation and differentiation of hematopoietic stem cells (HSCs) in the bone marrow via cell-to-cell contact, as well as secretion of cytokines and microvesicles (MVs). In this study, we investigated the effect of mesenchymal stem cell-derived microvesicles (MSC-MVs) on erythroid differentiation of umbilical cord blood-derived CD34+ cells. Methods: In this descriptive study, CD34+ cells were cultured with mixture of SCF (10 ng/ml) and rhEPO (5 U/ml) cytokines in complete IMDM medium as positive control group. Then, in MV1- and MV2-groups, microvesicles at 10 and 20 µg/ml concentration were added. After 72 hours, erythroid specific markers (CD71 and CD235a) and genes (HBG1, GATA1, FOG1 and NFE2) were assessed by flow cytometry and qRT-PCR, respectively. Results: The expression of specific markers of the erythroid lineages (CD71 and GPA) in the presence of different concentration of microvesicles were lower than that of the control group (P<0.001). Also, the expression of specific genes of the erythroid lineages (NFE2, FOG1, GATA1, and HBG1) was investigated in comparison to the internal control (GAPDH). Among all of them, HBG1 and FOG1 genes were significantly decreased to the control group (P<0.0001) but GATA1 and NFE2 gene expressions was not significant. Conclusion: The results of this study showed that MSC-MVs decrease the erythroid differentiation of umbilical cord blood-derived CD34+ cells. Therefore, MSC-MVs play a key role in the regulation of normal erythropoiesis.
Automatic acoustic detection of birds through deep learning: The first Bird Audio Detection challenge

Assessing the presence and abundance of birds is important for monitoring specific species as well as overall ecosystem health. Many birds are most readily detected by their sounds, and thus, passive acoustic monitoring is highly appropriate. Yet acoustic monitoring is often held back by practical limitations such as the need for manual configuration, reliance on example sound libraries, low accuracy, low robustness, and limited ability to generalise to novel acoustic conditions. Here, we report outcomes from a collaborative data challenge. We present new acoustic monitoring datasets, summarise the machine learning techniques proposed by challenge teams, conduct detailed performance evaluation, and discuss how such approaches to detection can be integrated into remote monitoring projects. Multiple methods were able to attain performance of around 88% area under the receiver operating characteristic (ROC) curve (AUC), much higher performance than previous general‐purpose methods. With modern machine learning, including deep learning, general‐purpose acoustic bird detection can achieve very high retrieval rates in remote monitoring data, with no manual recalibration, and no pretraining of the detector for the target species or the acoustic conditions in the target environment.
Effectiveness of an intensive treatment programme combining prolonged exposure and eye movement desensitization and reprocessing for severe post-traumatic stress disorder

ABSTRACT Background: There is room for improvement regarding the treatment of severe post-traumatic stress disorder (PTSD). Intensifying treatment to increase patient retention is a promising development. Objective: The aim of this study was to determine the effectiveness of an intensive trauma-focused treatment programme over 8 days for individuals suffering from severe PTSD. Method: Treatment was provided for 347 PTSD patients (70% women; mean age = 38.32 years, SD = 11.69) and consisted of daily sessions of prolonged exposure and eye movement desensitization and reprocessing (EMDR) therapy (16 sessions in total), physical activity, and psycho-education. All participants had experienced multiple traumas, including sexual abuse (74.4%), and suffered from multiple comorbidities (e.g. 87.5% had a mood disorder). Suicidal ideation was frequent (73.9%). PTSD symptom severity was assessed by both clinician-rated [Clinician Administered PTSD Scale (CAPS)] and self-report [PTSD Symptom Scale Self Report (PSS-SR) and Impact of Event Scale (IES)] inventories. For a subsample (n = 109), follow-up data at 6 months were available. Results: A significant decline in symptom severity was found (e.g. CAPS intention-to-treat sample Cohen’s d = 1.64). At post-treatment, 82.9% showed a clinically meaningful response and 54.9% a loss of diagnosis. Dropout was very low (2.3%). Conclusions: Intensive trauma-focused treatment programmes including prolonged exposure, EMDR therapy, and physical activity can be effective for patients suffering from severe PTSD and are associated with low dropout rates.
Fe3O4@Resorcinol–Formaldehyde Resin/Cu2O Composite Microstructures: Solution-Phase Construction, Magnetic Performance, and Applications in Antibacterial and Catalytic Fields

Multifunctional Fe3O4@resorcinol–formaldehyde resin/Cu2O composite microstructures (denoted as Fe3O4@RF/Cu2O microstructures) were successfully constructed via a simple wet chemical route that has not been reported so far in the literature. The as-obtained Fe3O4@RF/Cu2O microstructures were characterized using field-emission scanning electron microscopy, (high-resolution) transmission electron microscopy, selected-area electron diffraction, X-ray diffraction, and X-ray energy dispersive spectroscopy. The investigations showed that the as-obtained microstructures presented not only excellent antibacterial activity to Staphylococcus aureus (Gram-positive bacteria) and Escherichia coli (Gram-negative bacteria) but also highly efficient catalytic ability for the reduction of 4-nitrophenol (4-NP) in a solution with excess NaBH4. Owing to the presence of Fe3O4, the antibacterial reagent and the catalyst could be readily collected from the mixed systems under the assistance of an external magnetic field. It was found that the as-obtained microstructures displayed good cycling stability in antibacterial and catalytic applications. Fe3O4@RF/Cu2O microstructures still retained more than 87% of the antibacterial efficiency after 5 cycles and 89% of the catalytic efficiency after 10 cycles.
OX40 Stimulation Enhances Protective Immune Responses Induced After Vaccination With Attenuated Malaria Parasites

Protection against a malaria infection can be achieved by immunization with live-attenuated Plasmodium sporozoites and while the precise mechanisms of protection remain unknown, T cell responses are thought to be critical in the elimination of infected liver cells. In cancer immunotherapies, agonistic antibodies that target T cell surface proteins, such as CD27, OX40 (CD134), and 4-1BB (CD137), have been used to enhance T cell function by increasing co-stimulation. In this study, we have analyzed the effect of agonistic OX40 monoclonal antibody treatment on protective immunity induced in mice immunized with genetically attenuated parasites (GAPs). OX40 stimulation enhanced protective immunity after vaccination as shown by an increase in the number of protected mice and delay to blood-stage infection after challenge with wild-type sporozoites. Consistent with the enhanced protective immunity enforced OX40 stimulation resulted in an increased expansion of antigen-experienced effector (CD11ahiCD44hi) CD8+ and CD4+ T cells in the liver and spleen and also increased IFN-γ and TNF producing CD4+ T cells in the liver and spleen. In addition, GAP immunization plus α-OX40 treatment significantly increased sporozoite-specific IgG responses. Thus, we demonstrate that targeting T cell costimulatory receptors can improve sporozoite-based vaccine efficacy.
Impact of the Ripening Stage of Wax Apples on Chemical Profiles of Juice and Cider

Wax apple fruit (Syzygium aqueum Alston cv. Taaptimjan) is a tropical fruit with many nutritional bioactive compounds and high economic value. However, when fully ripe, the thin-skinned fruit is highly susceptible to physical damage and microbial spoilage that significantly reduce its commercial value. The present study was aimed to find a suitable ripening stage between the ripe and overripe wax apple fruits for developing a value-added beverage specifically cider. The chemical profiles of ripe and overripe wax apple juice and cider were determined by measuring sugar, acid, alcohol, mineral, proximate, ascorbic acid, amino acid, antioxidant, and volatile levels. Overall, the results showed significant variations. The physicochemical and proximate analysis showed highest values for ripe fruit juice than overripe fruit juice and the cider samples. The amino acids in the samples were found almost at similar levels. Polyphenolic content and antioxidant activities were higher in ciders than in unfermented juices. In addition, the overripe fruit cider had more volatile compounds than ripe fruit cider and unfermented juices. Overall, the overripe fruit is suitable for producing cider, whereas the ripe fruit is more suitable for the unfermented beverages.
Relative Contribution of Vowel Quality and Duration to Native Language Identification in Foreign-Accented English

Automatic identification of a speaker's native language back-ground may have forensic applications. This paper explores the feasibility of automatic identification of the native language background of a foreign speaker of English, using phonetically interpretable measurements. The production of the ten mono-phthongs of (American) English by Dutch, Mandarin Chinese and American speakers was used as a test case. Vowel formants F1 (corresponding to articulatory vowel height), F2 (capturing vowel backness and lip rounding) and vowel duration were extracted. Clearly different duration and patterning of the vowels in the vowel space were seen. Automatic classification of the speaker's native language was 90 percent correct when all acoustic parameters were used as predictors. Language identification was slightly poorer when only formant data were used (85% correct) and substantially poorer -- but much better than chance -- when only vowel duration was used (60% correct). We conclude that vowel duration provides a weaker cue to foreign-accent identification in English than the spectral properties but that the combination of both information sources yields the best results.
Brain haemorrhage detection using a SVM classifier with electrical impedance tomography measurement frames

Brain haemorrhages often require urgent treatment with a consequent need for quick and accurate diagnosis. Therefore, in this study, we investigate Support Vector Machine (SVM) classifiers for detecting brain haemorrhages using Electrical Impedance Tomography (EIT) measurement frames. A 2-layer model of the head, along with a series of haemorrhages, is designed as both numerical models and physical phantoms. EIT measurement frames, taken from an electrode array placed on the head surface, are used to train and test linear SVM classifiers. Various scenarios are implemented on both platforms to examine the impact of variables such as noise level, lesion location, lesion size, variation in electrode positioning, and variation in anatomy, on the classifier performance. The classifier performed well in numerical models (sensitivity and specificity of 90%+) with signal-to-noise ratios of 60 dB+, was independent of lesion location, and could detect lesions reliably down to the tested minimum volume of 5 ml. Slight variations in electrode layout did not affect performance. Performance was affected by variations in anatomy however, emphasising the need for large training sets covering different anatomies. The phantom models proved more challenging, with maximal sensitivity and specificity of 75% when used with the linear SVM. Finally, the performance of two more complex classifiers is briefly examined and compared to the linear SVM classifier. These results demonstrate that a radial basis function (RBF) SVM classifier and a neural network classifier can improve detection accuracy. Classifiers applied to EIT measurement frames is a novel approach for lesion detection and may offer an effective diagnostic tool clinically. A challenge is to translate the strong results from numerical models into real world phantoms and ultimately human patients, as well as the selection and development of optimal classifiers for this application.
Data-efficient weakly supervised learning for low-resource audio event detection using deep learning

We propose a method to perform audio event detection under the common constraint that only limited training data are available. In training a deep learning system to perform audio event detection, two practical problems arise. Firstly, most datasets are "weakly labelled" having only a list of events present in each recording without any temporal information for training. Secondly, deep neural networks need a very large amount of labelled training data to achieve good quality performance, yet in practice it is difficult to collect enough samples for most classes of interest. In this paper, we propose a data-efficient training of a stacked convolutional and recurrent neural network. This neural network is trained in a multi instance learning setting for which we introduce a new loss function that leads to improved training compared to the usual approaches for weakly supervised learning. We successfully test our approach on two low-resource datasets that lack temporal labels.
Anxiolytic and Antiepileptic Properties of the Aqueous Extract of Cissus quadrangularis (Vitaceae) in Mice Pilocarpine Model of Epilepsy

Cissus quadrangularis (C. quadrangularis) is a plant of the Vitaceae family known for its anticonvulsant effects in traditional medicine. The objective of this study was to elucidate the anxiolytic and antiepileptic effects of aqueous extract of C. quadrangularis. The mice were divided into different groups and treated for seven consecutive days as follows: a negative control group that received distilled water, po, four test groups that received four doses of the plant (37.22, 93.05, 186.11, and 372.21 mg/kg, po), and a positive control group that received sodium valproate (300 mg/kg, ip). One hour after the first treatment (first day), epilepsy was induced by intraperitoneal administration of a single dose of pilocarpine (360 mg/kg). On the seventh day, the anxiolytic effects of the extract were evaluated in the epileptic mice using the elevated plus maze (EPM) and open field (OP) paradigms. Antioxidant activities and the involvement of gabaergic neurotransmission were determined by measuring the levels of malondialdehyde, reduced glutathione (GSH), GABA, and GABA-transaminase (GABA-T) in the hippocampus of sacrificed epileptic mice. The results show that the extract of C. quadrangularis significantly and dose-dependently increased the latency to clonic and generalized tonic–clonic seizures and decreased the number and duration of seizures. In the EPM, the extract of C. quadrangularis significantly increased the number of entries and the time spent into the open arms and reduced the number of entries and the time spent into the closed arms as well as the number of rearing. The extract of C. quadrangularis also increased the number of crossing, and the time spent in the center of the OP. The level of MDA and the activity of GABA-T were significantly decreased by the extract of C. quadrangularis while reduced GSH and GABA levels were increased. The results suggest that the anticonvulsant activities of C. quadrangularis are accompanied by its anxiolytics effects. These effects may be supported by its antioxidant properties and mediated at least in part by the GABA neurotransmission.
Pharmacokinetics of placental protein 13 after intravenous and subcutaneous administration in rabbits

Introduction Human placental protein 13 (PP13) is a galectin predominantly expressed by the placenta. Low serum concentrations of PP13 in early pregnancy indicate a higher risk of developing preeclampsia. Methods The pharmacokinetic disposition and bioavailability of PP13 were determined by single intravenous and subcutaneous administration to 12 healthy New Zealand White rabbits. The serum pharmacokinetic values were determined by enzyme-linked immunosorbent assay, and are best described by a two-compartment model. Results Both volume of distribution and the area under the curve were dose dependent for the intravenous group (p<0.01). PP13 elimination half-life was also found to be different between the groups (p<0.01). The bioavailability of PP13 following subcutaneous administration was found to be 57%. Conclusion This study shows that the concentration of total PP13 released into the maternal circulation during pregnancy might be much higher than previously estimated.
Germination ecology of Chloris truncata and its implication for weed management

Chloris truncata is a significant weed in summer crops in the subtropical region of Australia. A study was conducted to evaluate the effect of environmental factors on germination and emergence of two populations of C. truncata. Overall, germination was not affected by the populations. Seeds germinated at a wide range of alternating day/night temperatures, suggesting that seeds can germinate throughout the spring, winter and autumn seasons. Seed germination was stimulated by the presence of light; however, 51 to 71% of these seeds still germinated in the dark. The sodium chloride concentration and osmotic potential required to inhibit germination of 50% of the population were 179 mM and -0.52 MPa, respectively. A high proportion of seeds germinated over a wide pH range (4 to 10). Seeds placed on the soil surface had greatest germination (67%) and a burial depth of 3 cm resulted in complete inhibition of emergence. The sorghum residue amount required to reduce emergence by 50% was 1.8 t ha-1. The results suggest that, although this weed will be favored in no-till systems, residue retention on the soil surface will help in reducing its infestation. Seed bank buildup can be managed by burying seeds below the depth of emergence.
Computing with Spikes: The Advantage of Fine-Grained Timing

Abstract Neural-inspired spike-based computing machines often claim to achieve considerable advantages in terms of energy and time efficiency by using spikes for computation and communication. However, fundamental questions about spike-based computation remain unanswered. For instance, how much advantage do spike-based approaches have over conventional methods, and under what circumstances does spike-based computing provide a comparative advantage? Simply implementing existing algorithms using spikes as the medium of computation and communication is not guaranteed to yield an advantage. Here, we demonstrate that spike-based communication and computation within algorithms can increase throughput, and they can decrease energy cost in some cases. We present several spiking algorithms, including sorting a set of numbers in ascending/descending order, as well as finding the maximum or minimum or median of a set of numbers. We also provide an example application: a spiking median-filtering approach for image processing providing a low-energy, parallel implementation. The algorithms and analyses presented here demonstrate that spiking algorithms can provide performance advantages and offer efficient computation of fundamental operations useful in more complex algorithms.