Miracle-dz/UniFAR-FTUs huggingface dataset:
Case report: biallelic DNMT3A mutations in acute myeloid leukemia

DNMT3A gene mutations, detected in 20-25% of de novo acute myeloid leukemia (AML) patients, are typically heterozygous. Biallelic variants are uncommon, affecting ~3% of cases and identifying a worse prognosis. Indeed, two concomitant DNMT3A mutations were recently associated with shorter event-free survival and overall survival in AML. We present an AML case bearing an unusual DNMT3A molecular status, strongly affecting its function and strangely impacting the global genomic methylation profile. A 56-year-old Caucasian male with a diagnosis of AML not otherwise specified (NOS) presented a complex DNMT3A molecular profile consisting of four different somatic variants mapping on different alleles (in trans). 3D modelling analysis predicted the effect of the DNMT3A mutational status, showing that all the investigated mutations decreased or abolished DNMT3A activity. Although unexpected, DNMT3A’s severe loss of function resulted in a global genomic hypermethylation in genes generally involved in cell differentiation. The mechanisms through which DNMT3A contributes to AML remain elusive. We present a unique AML case bearing multiple biallelic DNMT3A variants abolishing its activity and resulting in an unexpected global hypermethylation. The unusual DNMT3A behavior described requires a reflection on its role in AML development and persistence, highlighting the heterogeneity of its deregulation.
Parallel filtering scheme for fast symmetrical component extraction based on asynchronous coordinate transformation

The common shortage of the existing methods for extracting symmetrical components from unbalanced and distorted three-phase voltages is that they introduce significant time delay before reaching an accurate result. Therefore, this paper presents a new filtering method to fast extract the positive sequence component based on asynchronous coordinate transformation. Unlike the conventional methods that filter out the harmonics in sequence, resulting in cascading delay, the proposed method has two signal streams operating in parallel, which in particular refer to the negative sequence component extraction and harmonic filtering, respectively, and then the positive sequence component can be easily derived by skillfully combining the results of two signal streams. In theory, the proposed method only suffers the largest delay introduced by these two streams. By carefully designing the asynchronous coordinate transformation, the delay can be restricted, thus improving the overall performance. Simulation and experimental results verified the performance of the proposed method.
Pregnane X Receptor Activation Triggers Rapid ATP Release in Primed Macrophages That Mediates NLRP3 Inflammasome Activation

The pregnane X receptor (PXR) is a ligand-activated nuclear receptor that acts as a xenobiotic sensor, responding to compounds of foreign origin, including pharmaceutical compounds, environmental contaminants, and natural products, to induce transcriptional events that regulate drug detoxification and efflux pathways. As such, the PXR is thought to play a key role in protecting the host from xenobiotic exposure. More recently, the PXR has been reported to regulate the expression of innate immune receptors in the intestine and modulate inflammasome activation in the vasculature. In the current study, we report that activation of the PXR in primed macrophages triggers caspase-1 activation and interleukin-1β release. Mechanistically, we show that this response is nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain-containing 3-dependent and is driven by the rapid efflux of ATP and P2X purinoceptor 7 activation following PXR stimulation, an event that involves pannexin-1 gating, and is sensitive to inhibition of Src-family kinases. Our findings identify a mechanism whereby the PXR drives innate immune signaling, providing a potential link between xenobiotic exposure and the induction of innate inflammatory responses.
Genetic impairment of folate metabolism regulates cortical interneurons and social behavior

Introduction The implications of folate deficiency in neuropsychiatric disorders were demonstrated in numerous studies. Genetic deficiency in a key folate metabolism enzyme, MTHFR, is an example of the interaction between genetic and environmental risk factors: the maternal MTHFR deficiency governs in-utero nutrient availability, and the embryo’s Mthfr genotype influences its ability to metabolize folates. Here, we explore how the maternal and offspring Mthfr genotypes affect cortical interneuron densities and distributions, mouse social outcome, and the relation of the different interneuron patterns to cortical excitability. Methods Two experiments were conducted to examine the effects of maternal and offspring Mthfr-KO heterozygosity. Mice were tested for direct social interactions (DSIs), repetitive behavior and cortical laminar distribution of interneuron populations expressing glutamate-decarboxylase-65, parvalbumin and somatostatin. Susceptibility to seizure was tested by exposure to pentylenetetrazole (PTZ). Results Maternal Mthfr+/− genotype was associated with suppressed social activities and reduced interneuron densities in all layers of the retrosplenial cortex (RSC). Somatostatin density and the somatostatin/parvalbumin ratio in the RSC and frontal cortex positively correlated with social behavior in the mice. An interaction between maternal and offspring Mthfr genotypes resulted in higher susceptibility of wild-type offspring to PTZ induced seizure. Discussion Maternal folate metabolism was shown to be critical to interneuron ontogenesis. Our results demonstrate that interneurons have a specific susceptibility to folate deficiency that may mediate folate’s involvement in neuropsychiatric disease. The relations between cortical somatostatin interneuron patterns and social behavior highlight this subpopulation of interneurons as a target for further research.
L1 variation and L2 acquisition: L1 German /eː/-/ɛː/ overlap and its effect on the acquisition of L2 English /ɛ/-/æ/

A person’s first language (L1) affects the way they acquire speech in a second language (L2). However, we know relatively little about the role different varieties of the L1 play in the acquisition of L2 speech. This study focuses on German (L1) learners of English (L2) and asks whether the degree to which German speakers distinguish between the two vowels /eː/ and /ɛː/ in their L1 has an impact on how well these individuals identify /æ/ and discriminate between the two English vowels /ɛ/ and /æ/. These two English vowels differ in both vowel quality and duration (/æ/ is longer than /ɛ/). We report on an identification and a discrimination experiment. In the first study, participants heard a sound file and were asked to indicate whether they heard “pen” or “pan” (or “pedal” or “paddle”). The stimuli differed from each other in terms of both vowel quality (11 steps on a spectral continuum from an extreme /æ/ to an extreme /ɛ/) and duration (short, middle, long). In the second study, participants had to signal whether two sound files they were exposed to differed from each other. We modeled the percentage of /æ/ (“pan,” “paddle”) selection (identification task only, binomial logistic regression), accuracy (discrimination task only, binomial logistic regression), and reaction time (identification and discrimination tasks, linear mixed effects models) by implementing the German Pillai score as a measure of vowel overlap in our analysis. Each participant has an individual Pillai score, which ranges from 0 (= merger of L1 German /eː/ and /ɛː/) to 1 (=maintenance of the contrast between L1 German /eː/ and /ɛː/) and had been established, prior to the perception experiments reported here, in a production study. Although the findings from the discrimination study remain inconclusive, the results from the identification test support the hypothesis that maintaining the vowel contrast in the L1 German leads to a more native-like identification of /æ/ in L2 English. We conclude that sociolinguistic variation in someone’s L1 can affect L2 acquisition.
New anti-diabetic agents for the treatment of non-alcoholic fatty liver disease: a systematic review and network meta-analysis of randomized controlled trials

Objectives This network meta-analysis aims to compare the efficacy and safety of new anti-diabetic medications for the treatment of non-alcoholic fatty liver disease (NAFLD). Materials and methods PubMed and Scopus were searched from inception to 27th March 2022 to identify all randomized controlled trials (RCTs) in NAFLD patients. Outcomes included reductions in intrahepatic steatosis (IHS) and liver enzyme levels. The efficacy and safety of DPP-4 inhibitors, GLP-1 agonists, SGLT-2 inhibitors, and other therapies were indirectly compared using a NMA approach. Unstandardized mean difference (USMD) with 95% confidence intervals (CI) were calculated. Results 2,252 patients from 31 RCTs were included. “Add-on” GLP-1 agonists with standard of care (SoC) treatment showed significantly reduced IHS compared to SoC alone [USMD (95%CI) -3.93% (-6.54%, -1.33%)]. Surface under the cumulative ranking curve (SUCRA) identified GLP-1 receptor agonists with the highest probability to reduce IHS (SUCRA 88.5%), followed by DPP-4 inhibitors (SUCRA 69.6%) and pioglitazone (SUCRA 62.2%). “Add-on” GLP-1 receptor agonists were also the most effective treatment for reducing liver enzyme levels; AST [USMD of -5.04 (-8.46, -1.62)], ALT [USMD of -9.84 (-16.84, -2.85)] and GGT [USMD of -15.53 (-22.09, -8.97)] compared to SoC alone. However, GLP-1 agonists were most likely to be associated with an adverse event compared to other interventions. Conclusion GLP-1 agonists may represent the most promising anti-diabetic treatment to reduce hepatic steatosis and liver enzyme activity in T2DM and NAFLD patients. Nevertheless, longer-term studies are required to determine whether this delays progression of liver cirrhosis in patients with NAFLD and T2DM. Systematic review registration https://www.crd. york.ac. uk/prospero/, identifier CRD42021259336.1.
People's experiences living with peripheral neuropathy: a qualitative study

Introduction Peripheral neuropathy is a neurological disorder characterised by pain, numbness, or tingling due to nerve damage. Peripheral neuropathy is one of the main health issues in Kuwait and is a rising concern which affects a large proportion of the population, therefore the lived experience needs to be explored to identify areas for improvement in care. This qualitative study explored the experiences of people living with peripheral neuropathy in Kuwait. Methods Semi-structured interviews were conducted with 25 participants recruited from the Neurology Outpatient Clinic of the Ibn Sina Hospital in Kuwait. The interview questions explored their experiences and understanding of pain along with the impact on their daily life. The interviews were audio recorded, transcribed and translated into English then coded using NVivo 12. Thematic analysis was conducted to identify patterns and themes in the data. Results Three major themes were identified including treatment beliefs (perceived effectiveness of treatment and seeking alternative treatments), the barriers to pain management (medication side effects, relationships with healthcare professionals and lack of information and access to healthcare), and the impact on quality of life (impact on work and social, physical, and psychological consequences). Self-efficacy was a key construct and over-arching theme that was discussed in all aspects, which finds reflection in the protection motivation theory. Discussion This paper presents the experiences of people living with peripheral neuropathy and highlights there is scope for improvement of current treatments in Kuwait. Self-management strategies are recommended alongside prescribed medication and healthcare professionals are encouraged to use a patient-centered approach. More importantly, information and support on the condition to promote coping strategies and self-efficacy should be adopted to improve quality of life. These findings can be implemented locally and globally to improve the quality of care provided to people living with peripheral neuropathy.
Sex differences in long-term effects of collagen-induced arthritis in middle-aged mice

Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory disorder with high prevalence among middle-aged women. Collagen-induced arthritis (CIA) is the most widely used animal model of RA, however, sex differences and long-term effects of CIA in mice are poorly described in the literature. Aim: Therefore, the present study aimed to analyze the long-term effects of CIA on the joints of middle-aged mice of both sexes and to describe potential sex differences. Materials and methods: CIA was induced in middle-aged DBA/1J mice by immunization with bovine type II collagen and complete Freund’s adjuvant. Saline was administered to control mice. Arthritis score assessment, plethysmometry, and thermal imaging of the joints were performed weekly for 15 weeks. Locomotor activity, micro-computed tomography, joint histology and biochemical analyses were performed at the end of the experiment. Results: Our results indicate a similar prevalence of arthritis in both sexes of mice—67% (8/12) of females and 89% (8/9) males with an earlier onset in males (day 14 vs. day 35). After the arthritis scores peaked on day 56 for males and day 63 for females, they steadily declined until the end of the experiment on day 105. A similar dynamics was observed in paw volume and temperature analyzing different aspects of joint inflammation. Long-term consequences including higher proteinuria (by 116%), loss of bone density (by 33.5%) and joint damage in terms of synovial hyperplasia as well as bone and cartilage erosions were more severe in CIA males compared to CIA females. There were no significant differences in locomotor activity between CIA mice and CTRL mice of any sex. Conclusion: This is the first study to describe the long-term effects of the CIA model in terms of sex differences in DBA/1J mice. Our results indicate sex differences in the dynamics, but not in the extent of arthritis. An earlier onset of arthritis and more severe consequences on joints, bones and kidneys were found in males. The underlying immune pathomechanisms responsible for the limited duration of the arthritis symptoms and the opposite sex difference in comparison to RA patients require further investigation.
Epitranscriptomic investigation of myopia-associated RNA editing in the retina

Myopia is one of the most common causes of vision loss globally and is significantly affected by epigenetics. Adenosine-to-inosine (A-to-I RNA) editing is an epigenetic process involved in neurological disorders, yet its role in myopia remains undetermined. We performed a transcriptome-wide analysis of A-to-I RNA editing in the retina of form-deprivation myopia mice. Our study identified 91 A-to-I RNA editing sites in 84 genes associated with myopia. Notably, at least 27 (32.1%) of these genes with myopia-associated RNA editing showed existing evidence to be associated with myopia or related ocular phenotypes in humans or animal models, such as very low-density lipoprotein receptor (Vldlr) in retinal neovascularization and hypoxia-induced factor 1 alpha (Hif1a). Moreover, functional enrichment showed that RNA editing enriched in FDM was primarily involved in response to fungicides, a potentially druggable process for myopia prevention, and epigenetic regulation. In contrast, RNA editing enriched in controls was mostly involved in post-embryonic eye morphogenesis. Our results demonstrate altered A-to-I RNA editing associated with myopia in an experimental mouse model and warrant further study on its role in myopia development.
A Noise Suppression of LSTM algorithm combined with Kalman filter for Agriculture Automation

An immense volume of data is produced by sensor devices in the fields of aquaponics, hydroponics, and soil-based food production, where these devices track various environmental factors. Data stream mining is the method of retrieving data from fast-sampled data sources that are constantly streaming. The accuracy of data obtained through data stream mining is largely determined by the algorithm utilized to filter out noise. For threshold-based automation, an actuator can be activated when the value of sensor data is above a permissible threshold. Noise from sensors may activate the actuator. Several statistical and machine learning-based noise-suppression algorithms have been proposed in the literature. They have been evaluated based on the mean squared error metric (MSE). The Long Short-Term Memory – LSTM filter (MSE: 0.000999943) performs better noise suppression than other traditional filters – Kalman (MSE: 0.0015982). We propose a new noise suppression filter – LSTM combined with Kalman (LSTM-KF). In LSTM-KF, the Kalman filter acts as an encoder and the LSTM becomes the decoder, resulting in a significantly lower MSE – 0.000080789592. The LSTM-KF is installed in our threshold-based aquaponics automation to maximize sustainable food production at minimum cost.
‘Internet+’ comprehensive nursing training course in the post-epidemic era—an exploration of the mixed teaching mode: a randomized trial

Objective To explore the effect of the application of the ‘Internet+’ nursing teaching mode on the comprehensive teaching ‘Fundamentals of Nursing’. Trial design Parallel design and convenient sampling were used to select vocational nursing students from the Nursing College of Capital Medical University. Methods Selected students were randomly divided into two groups. The control group consisted of 30 students in Grade 2020 higher vocational nursing education (traditional teaching mode). The observation group consisted of 30 students in Grade 2021 higher vocational nursing education (Internet+ mixed teaching mode). Training assessment results, automatic learning ability, professional identity, and satisfaction were compared between the two groups. Results Compared with the control group, the students in the observation group scored higher in the following operation practices: venous blood sampling, intradermal injection, cardiopulmonary resuscitation (CPR), sputum aspiration, and putting on and taking off robes (84.01 ± 0.87 vs. 92.14 ± 1.23; 91.41 ± 0.82 vs. 96.86 ± 0.27; 87.56 ± 0.31 vs. 93.91 ± 2.79; 88.11 ± 0.51 vs. 93.75 ± 0.29; and 82.29 ± 0.29 vs. 90.96 ± 0.34, respectively, with p < 0.05 for all scores). The total scores for autonomous learning ability and subjective satisfaction were also higher in the observation group compared with the control group (82.98 ± 4.72 vs. 93.17 ± 5.01 and 96.67% vs. 90.00%, respectively, with p < 0.05 for all scores). Conclusion In the post-epidemic era, the ‘Internet+ hybrid teaching mode’ was applied to comprehensive nursing teaching. This changed the traditional education mode, which focuses only on professional knowledge. The ‘Internet+’ teaching mode results showed that the professional, ideological, and political courses exhibited the same value guidance, which improved students’ independent learning ability, practical operation ability, professional identity, and satisfaction.
Rethinking the network determinants of motor disability in Parkinson’s disease

For roughly the last 30 years, the notion that striatal dopamine (DA) depletion was the critical determinant of network pathophysiology underlying the motor symptoms of Parkinson’s disease (PD) has dominated the field. While the basal ganglia circuit model underpinning this hypothesis has been of great heuristic value, the hypothesis itself has never been directly tested. Moreover, studies in the last couple of decades have made it clear that the network model underlying this hypothesis fails to incorporate key features of the basal ganglia, including the fact that DA acts throughout the basal ganglia, not just in the striatum. Underscoring this point, recent work using a progressive mouse model of PD has shown that striatal DA depletion alone is not sufficient to induce parkinsonism and that restoration of extra-striatal DA signaling attenuates parkinsonian motor deficits once they appear. Given the broad array of discoveries in the field, it is time for a new model of the network determinants of motor disability in PD.
Optimizing strategies to identify high risk of developing type 2 diabetes

Introduction The success of diabetes prevention based on early treatment depends on high-quality screening. This study compared the diagnostic properties of currently recommended screening strategies against alternative score-based rules to identify those at high risk of developing diabetes. Methods The study used data from ELSA-Brasil, a contemporary cohort followed up for a mean (standard deviation) of 7.4 (0.54) years, to develop risk functions with logistic regression to predict incident diabetes based on socioeconomic, lifestyle, clinical, and laboratory variables. We compared the predictive capacity of these functions against traditional pre-diabetes cutoffs of fasting plasma glucose (FPG), 2-h plasma glucose (2hPG), and glycated hemoglobin (HbA1c) alone or combined with recommended screening questionnaires. Results Presenting FPG > 100 mg/dl predicted 76.6% of future cases of diabetes in the cohort at the cost of labeling 40.6% of the sample as high risk. If FPG testing was performed only in those with a positive American Diabetes Association (ADA) questionnaire, labeling was reduced to 12.2%, but only 33% of future cases were identified. Scores using continuously expressed clinical and laboratory variables produced a better balance between detecting more cases and labeling fewer false positives. They consistently outperformed strategies based on categorical cutoffs. For example, a score composed of both clinical and laboratory data, calibrated to detect a risk of future diabetes ≥20%, predicted 54% of future diabetes cases, labeled only 15.3% as high risk, and, compared to the FPG ≥ 100 mg/dl strategy, nearly doubled the probability of future diabetes among screen positives. Discussion Currently recommended screening strategies are inferior to alternatives based on continuous clinical and laboratory variables.
Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese

Natural Language Processing (NLP) techniques are increasingly powerful for interpreting a person’s feelings and reaction to a product or service. Sentiment analysis has become a fundamental tool for this interpretation, and it has studies in languages other than English. This type of application is uncommon and unheard of in Portuguese. This article presents a sentiment analysis classification based on Portuguese social media comments. Representation of word embeddings with both pre-trained Glove and Word2Vec models were generated through a corpus entirely in Portuguese. This article presents a set of results with different models of pre-trained layers and deep learning models exclusive to the Portuguese language on social networks. Two classification models were used and compared: (i) Bidirectional Long Short-Term Memory (BI-LSTM) and (ii) Bidirectional Gated Recurrent Unit (BI-GRU), achieving accuracy results of 99.1