Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic Targeting of Breast Cancer Cells With the 2-Deoxy-D-Glucose and the Mitochondrial Bioenergetics Inhibitor MDIVI-1

Breast cancer cells have different requirements on metabolic pathways in order to sustain their growth. Triple negative breast cancer (TNBC), an aggressive breast cancer subtype relies mainly on glycolysis, while estrogen receptor positive (ER+) breast cancer cells possess higher mitochondrial oxidative phosphorylation (OXPHOS) levels. However, breast cancer cells generally employ both pathways to sustain their metabolic needs and to compete with the surrounding environment. In this study, we demonstrate that the mitochondrial fission inhibitor MDIVI-1 alters mitochondrial bioenergetics, at concentrations that do not affect mitochondrial morphology. We show that this effect is accompanied by an increase in glycolysis consumption. Dual targeting of glycolysis with 2-deoxy-D-glucose (2DG) and mitochondrial bioenergetics with MDIVI-1 reduced cellular bioenergetics, increased cell death and decreased clonogenic activity of MCF7 and HDQ-P1 breast cancer cells. In conclusion, we have explored a novel and effective combinatorial regimen for the treatment of breast cancer.
Epigenetic Crosstalk between the Tumor Microenvironment and Ovarian Cancer Cells: A Therapeutic Road Less Traveled

Metastatic dissemination of epithelial ovarian cancer (EOC) predominantly occurs through direct cell shedding from the primary tumor into the intra-abdominal cavity that is filled with malignant ascitic effusions. Facilitated by the fluid flow, cells distribute throughout the cavity, broadly seed and invade through peritoneal lining, and resume secondary tumor growth in abdominal and pelvic organs. At all steps of this unique metastatic process, cancer cells exist within a multidimensional tumor microenvironment consisting of intraperitoneally residing cancer-reprogramed fibroblasts, adipose, immune, mesenchymal stem, mesothelial, and vascular cells that exert miscellaneous bioactive molecules into malignant ascites and contribute to EOC progression and metastasis via distinct molecular mechanisms and epigenetic dysregulation. This review outlines basic epigenetic mechanisms, including DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA regulators, and summarizes current knowledge on reciprocal interactions between each participant of the EOC cellular milieu and tumor cells in the context of aberrant epigenetic crosstalk. Promising research directions and potential therapeutic strategies that may encompass epigenetic tailoring as a component of complex EOC treatment are discussed.
Feature Representation and Data Augmentation for Human Activity Classification Based on Wearable IMU Sensor Data Using a Deep LSTM Neural Network

Wearable inertial measurement unit (IMU) sensors are powerful enablers for acquisition of motion data. Specifically, in human activity recognition (HAR), IMU sensor data collected from human motion are categorically combined to formulate datasets that can be used for learning human activities. However, successful learning of human activities from motion data involves the design and use of proper feature representations of IMU sensor data and suitable classifiers. Furthermore, the scarcity of labelled data is an impeding factor in the process of understanding the performance capabilities of data-driven learning models. To tackle these challenges, two primary contributions are in this article: first; by using raw IMU sensor data, a spectrogram-based feature extraction approach is proposed. Second, an ensemble of data augmentations in feature space is proposed to take care of the data scarcity problem. Performance tests were conducted on a deep long term short term memory (LSTM) neural network architecture to explore the influence of feature representations and the augmentations on activity recognition accuracy. The proposed feature extraction approach combined with the data augmentation ensemble produces state-of-the-art accuracy results in HAR. A performance evaluation of each augmentation approach is performed to show the influence on classification accuracy. Finally, in addition to using our own dataset, the proposed data augmentation technique is evaluated against the University of California, Irvine (UCI) public online HAR dataset and yields state-of-the-art accuracy results at various learning rates.
Myasthenia gravis unmasked by imatinib

A 40-year-old man presented with drooping of both eyelids and generalized weakness of two weeks duration. The symptoms were worse during the evening. He had been diagnosed with chronic myeloid leukaemia (CML) in chronic phase, four months previously, and was receiving regular imatinib, 400 mg/day. After three weeks of therapy, he had achieved a complete haematological response, and his constitutional symptoms had subsided. After three months of therapy, he showed a two-log reduction of BCR-ABL1 transcript. On presentation, he had bilateral ptosis (left). Physical examination was otherwise normal. A provisional diagnosis of ocular myasthenia gravis was made. He showed improvement in ptosis after administration of neostigmine. Repetitive nerve stimulation and anti-acetylcholine receptor antibody serology were positive, confirming the diagnosis of myasthenia gravis. He was started on pyridostigmine and prednisolone. Computed tomography of his chest showed a 2 7 9 1 7 cm mass in the anterior mediastinum, for which he underwent thymectomy. Histopathological examination showed thymic hyperplasia. He is currently asymptomatic with marked improvement in ptosis (right) and has achieved a partial molecular response (BCR-ABL1 transcript level, 1 113%). Many cases of drug-induced myasthenia gravis have been reported. Drugs implicated include ribavirin, statins, fluoroquinolones, interferon, fludarabine, chloroquine, penicillamine, busulfan and carbamazepine. Development of myasthenia gravis during treatment with nilotinib has also been reported in a patient with CML. In the current case, myasthenia gravis was unmasked when the patient was treated with imatinib. Triggering of myasthenia by tyrosine kinase inhibitors and certain other drugs may be related to a disturbance of immune function. However, other possibilities, including a paraneoplastic manifestation of CML or co-incidental occurrence of myasthenia gravis and CML, cannot be ruled out.
Avoiding inappropriate therapy of single‐lead implantable cardioverter‐defibrillator by using atrial‐sensing electrodes

The single‐chamber implantable cardioverter‐defibrillator (ICD) can be associated with more frequent inappropriate therapies compared with dual‐chamber ICDs, when they are accompanied by a simpler implantation procedure. The aim of this study was to investigate whether the use of a single‐lead ICD system with atrial‐sensing electrodes results in a reduction of inappropriate ICD therapy.
Context-Free Transductions with Neural Stacks

This paper analyzes the behavior of stack-augmented recurrent neural network (RNN) models. Due to the architectural similarity between stack RNNs and pushdown transducers, we train stack RNN models on a number of tasks, including string reversal, context-free language modelling, and cumulative XOR evaluation. Examining the behavior of our networks, we show that stack-augmented RNNs can discover intuitive stack-based strategies for solving our tasks. However, stack RNNs are more difficult to train than classical architectures such as LSTMs. Rather than employ stack-based strategies, more complex networks often find approximate solutions by using the stack as unstructured memory.
The Protective Effect of a Long-Acting and Multi-Target HM-3-Fc Fusion Protein in Rheumatoid Arthritis

Current treatment of rheumatoid arthritis (RA) is limited by relative shortage of treatment targets. HM-3 is a novel anti-RA polypeptide consisting of 18 amino acids with integrin αVβ3 and α5β1 as targets. Previous studies confirmed that HM-3 effectively inhibited the synovial angiogenesis and the inflammatory response. However, due to its short half-life, the anti-RA activity was achieved by frequent administration. To extend the half-life of HM-3, we designed a fusion protein with name HM-3-Fc, by combination of modified Fc segment of immunoglobulin 4 (IgG4) with HM-3 polypeptide. In vitro cell experiments demonstrated that HM-3-Fc inhibited the proliferation of splenic lymphocytes and reduced the release of TNF-α from macrophages. The pharmacodynamics studies on mice paw in Collagen-Induced Arthritis (CIA) model demonstrated that HM-3-Fc administered once in 5 days in the 50 and 25 mg/kg groups, or once in 7 days in the 25 mg/kg group showed a better protective effect within two weeks than the positive control adalimumab and HM-3 group. Preliminary pharmacokinetic studies in cynomolgus confirmed that the in vivo half-life of HM-3-Fc was 15.24 h in comparison with 1.32 min that of HM-3, which demonstrated that an Fc fusion can effectively increase the half-life of HM-3 and make it possible for further reduction of subcutaneous injection frequency. Fc-HM-3 is a long-acting active molecule for RA treatment.
Correlation between Quality and Geographical Origins of Poria cocos Revealed by Qualitative Fingerprint Profiling and Quantitative Determination of Triterpenoid Acids

Poria cocos (Schw.) Wolf (PC) is a well-known saprophytic fungus, and its sclerotium without the epidermis (PCS) is widely used in traditional Chinese medicine and as a functional food in many countries. PCS is normally collected from multiple geographical regions, but whether and how the quality of PCS correlates with where it grows have not been determined. This correlation could be significant both for quality control and optimum utilization of PCS as a natural resource. In this study, a qualitative fingerprint profiling method performed by ultra-performance liquid chromatography (UHPLC) with diode array detection (DAD) combining quadrupole time-of-flight-mass spectrometry (QTOF-MS/MS) and a quantitative UHPLC coupled with triple quadrupole mass spectrometry (QqQ-MS/MS) approach were established to investigate whether and how the quality of PCS correlates with its collection location. A standard fingerprint of PCS was generated by median simulation of 25 tested samples collected from four main producing areas of China, and similarity analysis was applied to evaluate the similarities between the fingerprints of samples and the standard fingerprint. Twenty three common peaks occurring in the fingerprint were unequivocally or tentatively identified by UHPLC-QTOF-MS/MS. Meanwhile, principal component analysis (PCA), supervised orthogonal partial least squares-discriminate analysis (OPLS-DA) and hierarchical cluster analysis (HCA) were employed to classify 25 batches of PCS samples into four groups, which were highly consistent with the four geographical regions. Ten compounds were screened out as potential markers to distinguish the quality of PCS. Nine triterpene acids, including five compounds that played important roles in the clusters between different samples collected from the four collection locations, were simultaneously quantified by using the multiple reaction monitoring (MRM) mode of UHPLC-QqQ-MS/MS. The current strategy not only clearly expounded the correlation between quality and geographical origins of PCS, but also provided a fast, accurate and comprehensive qualitative and quantitative method for assessing the quality of PCS.
Correcting real-word spelling errors: A new hybrid approach

Spelling correction is one of the main tasks in the field of Natural Language Processing. Contrary to common spelling errors, real-word errors cannot be detected by conventional spelling correction methods. The real-word correction model proposed by Mays, Damerau and Mercer showed a great performance in different evaluations. In this research, however, a new hybrid approach is proposed which relies on statistical and syntactic knowledge to detect and correct real-word errors. In this model, Constraint Grammar (CG) is used to discriminate among sets of correction candidates in the search space. Mays, Damerau and Mercer's trigram approach is manipulated to estimate the probability of syntactically well-formed correction candidates. The approach proposed here is tested on the Wall Street Journal corpus. The model can prove to be more practical than some other models, such as WordNet-based method of Hirst and Budanitsky and fixed windows size method of Wilcox-O'Hearn and Hirst.
Attentional Multi-Reading Sarcasm Detection

Recognizing sarcasm often requires a deep understanding of multiple sources of information, including the utterance, the conversational context, and real world facts. Most of the current sarcasm detection systems consider only the utterance in isolation. There are some limited attempts toward taking into account the conversational context. In this paper, we propose an interpretable end-to-end model that combines information from both the utterance and the conversational context to detect sarcasm, and demonstrate its effectiveness through empirical evaluations. We also study the behavior of the proposed model to provide explanations for the model's decisions. Importantly, our model is capable of determining the impact of utterance and conversational context on the model's decisions. Finally, we provide an ablation study to illustrate the impact of different components of the proposed model.
Extraction of High-Precision Urban Impervious Surfaces from Sentinel-2 Multispectral Imagery via Modified Linear Spectral Mixture Analysis

This study explores the performance of Sentinel-2A Multispectral Instrument (MSI) imagery for extracting urban impervious surface using a modified linear spectral mixture analysis (MLSMA) method. Sentinel-2A MSI provided 10 m red, green, blue, and near-infrared spectral bands, and 20 m shortwave infrared spectral bands, which were used to extract impervious surfaces. We aimed to extract urban impervious surfaces at a spatial resolution of 10 m in the main urban area of Guangzhou, China. In MLSMA, a built-up image was first extracted from the normalized difference built-up index (NDBI) using the Otsu’s method; the high-albedo, low-albedo, vegetation, and soil fractions were then estimated using conventional linear spectral mixture analysis (LSMA). The LSMA results were post-processed to extract high-precision impervious surface, vegetation, and soil fractions by integrating the built-up image and the normalized difference vegetation index (NDVI). The performance of MLSMA was evaluated using Landsat 8 Operational Land Imager (OLI) imagery. Experimental results revealed that MLSMA can extract the high-precision impervious surface fraction at 10 m with Sentinel-2A imagery. The 10 m impervious surface map of Sentinel-2A is capable of recovering more detail than the 30 m map of Landsat 8. In the Sentinel-2A impervious surface map, continuous roads and the boundaries of buildings in urban environments were clearly identified.
Exploring teachers’ scaffolding practices in the teaching of primary school mathematics at a school in Swaziland.

The purpose of this study was to explore participants’ scaffolding practices in the teaching of primary mathematics at a school in Swaziland. Scaffolding refers to all the assistance a more knowledgeable other provides to learners in order to accomplish a task. The study was prompted by the observation that learners’ performance deteriorated as they progressed to upper grades. This study describes the participants’ understanding of scaffolding and how and why they implement scaffolding the way they do in the teaching of primary mathematics. This study is guided by an interpretive paradigm and a qualitative methodology. Two experienced primary school teachers were conveniently selected for the purpose of the study. Data were collected through a questionnaire, document analysis, lesson observations and one-on-one interviews. The captured data were later coded, organised analysed, and discussed. The participants understood scaffolding in the teaching of primary school mathematics to be diverse, developmental, fostering learning processes as well as being mediated in the zone of proximal development. They used scaffolding through practices such as excavating, questioning, explaining and parallel modelling, as well as collaboration. It also emerged that they sometimes used some of the scaffolding practices unknowingly. The participants’ personal conceptual understanding and contextual factors such as time, class size, availability of resources, the school’s expectations as well as their attitude influenced the implementation of scaffolding. This study contributes to a better understanding of teachers’ scaffolding practices in the teaching of primary school mathematics. It is envisaged that the findings will be of value to practicing primary mathematics teachers, professional development organisers, education officers, school principals and administrators.
PTPRT and PTPRD Deleterious Mutations and Deletion Predict Bevacizumab Resistance in Metastatic Colorectal Cancer Patients

Background: Bevacizumab-based regimens are used as standard treatments for colorectal cancer. Unfortunately, there are no established predictive markers for bevacizumab response. Methods: Tumor samples from 36 metastatic colorectal cancer patients treated with bevacizumab plus chemotherapy were analyzed by next-generation sequencing of all coding exons of more than 400 genes. Single gene and signaling pathway analyses were performed to correlate genomic data with response. Results: Among the genes most frequently mutated in our cohort, only mutations in PTPRT, a phosphatase involved in JAK/STAT signaling, were associated with response status, with deleterious mutations being enriched in non-responders. Pathway analysis revealed that deleterious mutations in genes of the JAK/STAT pathway, namely in PTPRT and the related gene PTPRD, correlated with resistance. Mutations in RTK/PI3K/RAS, Wnt and TGFβ pathways did not associate with response. Lack of response was observed in all patients with deleterious mutations or copy number loss of PTPRT/PTPRD (n = 10), compared to only 30.8% (n = 8) of patients without such alterations (relative risk, 3.25; 95% CI, 1.83–5.79, p = 0.0003). Similarly, PTPRT/PTPRD deleterious alterations were associated with shorter progression-free survival, an association that was retained in multivariate analysis (HR, 3.33; 95% CI, 1.47–7.54; p = 0.0038). Conclusion: Deleterious alterations in PTPRT/PTPRD are potential biomarkers for bevacizumab resistance.
Leptin attenuates oxidative stress and neuronal apoptosis in hyperglycemic condition

One of the main pathological mechanisms of neurotoxicity in diabetic situation is oxidative stress promoted by hyperglycemia. It has been shown that leptin has neuroprotective effects and may provide neuronal survival signals. This study was designed to reveal the possible neuroprotective effects of leptin in hyperglycemic conditions. Pheochromocytoma (PC12) cell viability was assessed via the MTT test. Cellular reactive oxygen species (ROS) generation was determined by DCFH‐DA analysis. The malondialdehyde (MDA) and glutathione (GSH) levels were measured in high‐glucose‐treated PC12 cells with and without leptin cotreatment. Western blotting was performed to measure apoptosis markers (Cleaved caspase‐3 and Bax/Bcl2 ratio). Elevation of glucose levels (100 mmol/L) consecutively increased intracellular ROS and MDA level, and apoptosis in PC12 cells after 24 h leptin administration (12 and 24 nmol/L) decreased the high‐glucose‐induced cell toxicity, caspase‐3 activation, and Bax/Bcl‐2 ratio. Also, cotreatment with leptin (12 and 24 nmol/L) significantly reduced oxidative damage to PC12 cells in high‐glucose condition, as reflected by the diminution in MDA and ROS levels and the increase in GSH content. Our finding demonstrates that leptin has protective effects against hyperglycemia‐induced neural damage. This could be related to the attenuation of oxidative stress and neural apoptosis.
Patient‐Focused Drug Development Methods for Benefit–Risk Assessments: A Case Study Using a Discrete Choice Experiment for Antiepileptic Drugs

Regulatory decisions may be enhanced by incorporating patient preferences for drug benefit and harms. This study demonstrates a method of weighting clinical evidence by patients’ benefit–risk preferences. Preference weights, derived from discrete choice experiments, were applied to clinical trial data to estimate the expected utility of alternative drugs. In a case study, the rank ordering of antiepileptic drugs (AEDs), as indicated from clinical studies, was compared with ordering based on weighting clinical evidence by patients’ preferences. A statistically significant change in rank ordering of AEDs was observed for women of childbearing potential who were prescribed monotherapy for generalized or unclassified epilepsy. Rank ordering inferred from trial data, valproate > topiramate > lamotrigine, was reversed. Modeling the expected utility of drugs might address the need to use more systematic, methodologically sound approaches to collect patient input that can further inform regulatory decision making.
Hyperactivation of MAPK Signaling Is Deleterious to RAS/RAF-mutant Melanoma

The most frequent genetic alterations in melanoma are gain-of-function (GOF) mutations in BRAF, which result in RAF–MEK–ERK signaling pathway addiction. Despite therapeutic success of RAF and MEK inhibitors in treating BRAFV600-mutant tumors, a major challenge is the inevitable emergence of drug resistance, which often involves reactivation of the MAPK pathway. Interestingly, resistant tumors are often sensitive to drug withdrawal, suggesting that hyperactivation of the MAPK pathway is not tolerated. To further characterize this phenomenon, isogenic models of inducible MAPK hyperactivation in BRAFV600E melanoma cells were generated by overexpression of ERK2. Using this model system, supraphysiologic levels of MAPK signaling led to cell death, which was reversed by MAPK inhibition. Furthermore, complete tumor regression was observed in an ERK2-overexpressing xenograft model. To identify mediators of MAPK hyperactivation–induced cell death, a large-scale pooled shRNA screen was conducted, which revealed that only shRNAs against BRAF and MAP2K1 rescued loss of cell viability. This suggested that no single downstream ERK2 effector was required, consistent with pleiotropic effects on multiple cellular stress pathways. Intriguingly, the detrimental effect of MAPK hyperactivation could be partially attributed to secreted factors, and more than 100 differentially secreted proteins were identified. The effect of ERK2 overexpression was highly context dependent, as RAS/RAF mutant but not RAS/RAF wild-type melanoma were sensitive to this perturbation. Implications: This vulnerability to MAPK hyperactivation raises the possibility of novel therapeutic approaches for RAS/RAF-mutant cancers.