Miracle-dz/UniFAR-FTUs huggingface dataset:
Prebiotics enhance persistence of fermented-food associated bacteria in in vitro cultivated fecal microbial communities

It is well established that the gastrointestinal (GI) microbiota plays a major role in human health. Dietary interventions, and consumption of fermented foods that contain live microbes, in particular, are among the approaches being investigated to modulate the GI microbiota and improve health. However, the persistence of fermented food-associated bacteria (FAB) within the GI tract is typically limited by host factors that limit colonization and competition with autochthonous microbes. In this research, we examined if the addition of prebiotics, dietary substrates that are selectively metabolized by microbes to improve health, would enhance the persistence of FAB. We evaluated the persistence of bacteria from three live microbe-containing fermented foods—kefir, sausage, and sauerkraut—in fecal microbial communities from four healthy adults. Fecal communities were propagated in vitro and were inoculated with fermented food-associated microbes from kefir, sausage, or sauerkraut at ~107 CFU/mL. Communities were diluted 1:100 every 24 h into fresh gut simulation medium to simulate microbial community turnover in the GI tract. We measured the persistence of Lactobacillaceae from fermented foods by quantitative PCR (qPCR) and the persistence of other FAB through 16S rRNA gene sequencing. FAB were unable to persist in vitro, reaching undetectable levels within 96 h. Addition of prebiotics, including xylooligosaccharides and a mixture of fructooligosaccharides and galactooligosaccharides enhanced the persistence of some species of FAB, but the level of persistence varied by fecal donor, fermented food, and prebiotic tested. Addition of prebiotics also increased the relative abundance of Bifidobacterium species, which most likely originated from the fecal microbiota. Collectively, our results support previous in vivo studies demonstrating the transient nature of FAB in the GI tract and indicate that consumption of prebiotics may enhance their persistence.
Role of extracellular matrix architecture and signaling in melanoma therapeutic resistance

The extracellular matrix (ECM) is critical for maintaining tissue homeostasis therefore its production, assembly and mechanical stiffness are highly regulated in normal tissues. However, in solid tumors, increased stiffness resulting from abnormal ECM structural changes is associated with disease progression, an increased risk of metastasis and poor survival. As a dynamic and key component of the tumor microenvironment, the ECM is becoming increasingly recognized as an important feature of tumors, as it has been shown to promote several hallmarks of cancer via biochemical and biomechanical signaling. In this regard, melanoma cells are highly sensitive to ECM composition, stiffness and fiber alignment because they interact directly with the ECM in the tumor microenvironment via cell surface receptors, secreted factors or enzymes. Importantly, seeing as the ECM is predominantly deposited and remodeled by myofibroblastic stromal fibroblasts, it is a key avenue facilitating their paracrine interactions with melanoma cells. This review gives an overview of melanoma and further describes the critical roles that ECM properties such as ECM remodeling, ECM-related proteins and stiffness play in cutaneous melanoma progression, tumor cell plasticity and therapeutic resistance. Finally, given the emerging importance of ECM dynamics in melanoma, future perspectives on therapeutic strategies to normalize the ECM in tumors are discussed.
Abnormal ECG detection based on an adversarial autoencoder

Automatic detection and alarm of abnormal electrocardiogram (ECG) events play an important role in an ECG monitor system; however, popular classification models based on supervised learning fail to detect abnormal ECG effectively. Thus, we propose an ECG anomaly detection framework (ECG-AAE) based on an adversarial autoencoder and temporal convolutional network (TCN) which consists of three modules (autoencoder, discriminator, and outlier detector). The ECG-AAE framework is trained only with normal ECG data. Normal ECG signals could be mapped into latent feature space and then reconstructed as the original ECG signal back in our model, while abnormal ECG signals could not. Here, the TCN is employed to extract features of normal ECG data. Then, our model is evaluated on an MIT-BIH arrhythmia dataset and CMUH dataset, with an accuracy, precision, recall, F1-score, and AUC of 0.9673, 0.9854, 0.9486, 0.9666, and 0.9672 and of 0.9358, 0.9816, 0.8882, 0.9325, and 0.9358, respectively. The result indicates that the ECG-AAE can detect abnormal ECG efficiently, with its performance better than other popular outlier detection methods.
The relationship between executive function, neurodevelopmental disorder traits, and academic achievement in university students

Difficulties with executive function have often been identified in individuals with various neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention-Deficit Hyperactivity Disorder (ADHD), and Developmental Co-ordination Disorder (DCD). Additionally, in childhood and adolescence, executive functioning is an important predictor of academic achievement. However, less research has explored these relationships in adult students, and those with a high level of neurodevelopmental disorder traits but no clinical diagnosis. Therefore, the current study aimed to assess whether ASD, ADHD, and DCD traits can predict academic achievement in university students, and whether traits of these neurodevelopmental conditions moderate the relationship between executive function and academic achievement. Both neurotypical students and those with a clinical diagnosis of a neurodevelopmental disorder were able to participate, with the majority being neurotypical. Participants completed four self-report questionnaires and provided a measure of academic achievement based on their university assignment results. Traits of ASD, ADHD, and DCD alone did not predict achievement, however, traits of ADHD and DCD significantly moderated the relationship between executive function and academic achievement. ASD traits did not significantly moderate this relationship. Implications and suggestions for future research are also discussed.
Genetic instability-related lncRNAs predict prognosis and influence the immune microenvironment in breast cancer

Genome instability is a hallmark of cancer, and the function of lncRNAs in regulating genomic stability has been gradually characterized. However, the prognostic value of lncRNAs related to genetic instability has not been found in breast cancer. Here we constructed a genetic instability-related lncRNA model including U62317.4, SEMA3B-AS1, MAPT-AS1, AC115837.2, LINC01269, AL645608.7, and GACAT2. This model can evaluate the risk and predict the survival outcomes of patients. Further analysis showed that the differentially expressed genes between the high- and low-risk groups were enriched in immunity and cornified envelope formation pathways. In addition, M2 macrophages infiltrated more obviously in the high-risk group. In summary, lncRNAs related to genetic instability may influence the development of breast cancer through immune infiltration and keratinization. This study provides a wider insight into breast cancer development and treatment.
Interannual variations of the North Equatorial Current/Undercurrent from mooring array observations

Interannual variability of the North Equatorial Current (NEC)/Undercurrent (NEUC) in the northwestern Pacific was investigated with the mooring array measurements at 130°E during 2014-2021, in combination with the satellite altimetry. Mooring observations indicate that the velocity of the NEC/NEUC in the upper 900 m exhibits significant variations on the interannual time scale. The westward-flowing NEC strengthens when the underlying eastward-flowing NEUC weakens, and the NEUC branch at 8.5°N is intensified during the mature phase of El Niño and reaches the maximum velocity during the decay phase of El Niño. The phase of the interannual variation of the currents delays with the increasing latitude, with the signal at 15°N lagging that at 8.5°N by about one year. Based on a 1.5 layer reduced gravity model, the interannual variation is suggested to be controlled mainly by the westward propagating baroclinic Rossby wave induced by the wind stress curl forcing in the central Pacific. Different propagating speed of the baroclinic Rossby wave at different latitudes explains the meridional phase lag of the interannual signal. Empirical Orthogonal Function and vertical mode decomposition analysis suggest that the interannual variation of the NEC/NEUC velocity in the northern part is dominated by surface-intensified signals with a vertical structure of the first baroclinic mode, while that in the southern part is dominated by subsurface-intensified signals which is associated with the combination of the first two baroclinic modes. The low-order mode baroclinic response of the ocean to the wind forcing accounts for the interannual fluctuation of the NEC/NEUC velocity observed by the mooring array.
Influence of Bacillus subtilis strain Z-14 on microbial communities of wheat rhizospheric soil infested with Gaeumannomyces graminis var. tritici

Wheat take-all disease caused by Gaeumannomyces graminis var. tritici (Ggt) spreads rapidly and is highly destructive, causing severe reductions in wheat yield. Bacillus subtilis strain Z-14 that significantly controlled wheat take-all disease effectively colonized the roots of wheat seedlings. Z-14 increased the metabolic activity and carbon source utilization of rhizospheric microorganisms, thus elevating average well-color development (AWCD) values and functional diversity indexes of soil microbial communities. Z-14 increased the abundance of Bacillus in the rhizosphere, which was positively correlated with AWCD and functional diversity indexes. The Z-14-treated samples acquired more linkages and relative connections between bacterial communities according to co-occurrence network analyses. After the application of Ggt, the number of linkages between fungal communities increased but later decreased, whereas Z-14 increased such interactions. Whole-genome sequencing uncovered 113 functional genes related to Z-14’s colonization ability and 10 secondary metabolite gene clusters in the strain, of which nine substances have antimicrobial activity. This study clarifies how bacterial agents like Z-14 act against phytopathogenic fungi and lays a foundation for the effective application of biocontrol agents.
Radically reframing studies on neurobiology and socioeconomic circumstances: A call for social justice-oriented neuroscience

Socioeconomic circumstances are associated with symptoms and diagnostic status of nearly all mental health conditions. Given these robust relationships, neuroscientists have attempted to elucidate how socioeconomic-based adversity “gets under the skin. ” Historically, this work emphasized individual proxies of socioeconomic position (e.g., income, education), ignoring the effects of broader socioeconomic contexts (e.g., neighborhood socioeconomic disadvantage) which may uniquely contribute to chronic stress. This omission represented a disconnect between neuroscience and other allied fields that have recognized health is undeniably linked to interactions between systems of power and individual characteristics. More recently, neuroscience work has considered how sociopolitical context affects brain structure and function; however, the products of this exciting line of research have lacked critical sociological and historical perspectives. While empirical evidence on this topic is burgeoning, the cultural, ethical, societal, and legal implications of this work have been elusive. Although the mechanisms by which socioeconomic circumstances impact brain structure and function may be similar across people, not everyone is exposed to these factors at similar rates. Individuals from ethnoracially minoritized groups are disproportionally exposed to neighborhood disadvantage. Thus, socioeconomic inequities examined in neuroscience research are undergirding with other forms of oppression, namely structural racism. We utilize a holistic, interdisciplinary approach to interpret findings from neuroscience research and interweave relevant theories from the fields of public health, social sciences, and Black feminist thought. In this perspective piece, we discuss the complex relationship that continues to exist between academic institutions and underserved surrounding communities, acknowledging the areas in which neuroscience research has historically harmed and/or excluded structurally disadvantaged communities. We conclude by envisioning how this work can be used; not just to inform policymakers, but also to engage and partner with communities and shape the future direction of human neuroscience research.
Aberrant expansion of follicular helper T cell subsets in patients with systemic lupus erythematosus

Objective Systemic lupus erythematosus (SLE) is a chronic and complex autoimmune disease characterized by multiple autoantibodies, resulting in multiple organ and tissue damages. These pathogenic autoantibodies produced by B cells are closely correlated with follicular helper T (Tfh) cell subsets that play a fundamental role in the pathogenesis of SLE. The aim of the present study was to study the phenotype and role of circulating Tfh (cTfh) cell subsets and associated B cell subpopulations in active and inactive SLE patients. Methods Thirty SLE outpatients and 24 healthy controls (HCs) were enrolled in this study. The frequency of cTfh cell and B cell subsets in peripheral blood mononuclear cells (PBMCs) and the plasma levels of eight cytokines were determined by flow cytometry, and plasma IL-21 levels were measured by ELISA. Meanwhile, we used MRL/lpr mice as the model of SLE to research the alterations of Tfh cells in the thymus and spleen of mice. Results Frequencies of CD4+CXCR5+CD45RA-effector cTfh cells, PD1+cTfh, PD1+ICOS+cTfh, PD1+cTfh1, PD1+cTfh2, PD1+cTfh17, and PD1+ICOS+cTfh1 cells as well as plasmablasts showed significant differences among HC, active and inactive SLE patients. Moreover, cytokines typically associated with cTfh cells, including IL-6 and IL-21, were elevated in active SLE patients compared to inactive SLE patients and HCs. Additionally, a positive correlation was observed between PD1+ICOS+ cTfh or PD1+ICOS+ cTfh1 cell frequencies and plasmablasts or IL-21 levels, as well as between plasmablasts. We also found PD1+ICOS+ Tfh cells expansion in both thymus and spleen of MRL/lpr mice, accompanied by increased frequencies in B cells and plasmablasts, meanwhile, cTfh1which expressing IFN-γ was increased in the peripheral blood of MRL/lpr mice. Conclusion Tfh cell subsets and plasmablasts may play a fundamental role in the pathogenesis of SLE and may provide potential targets for therapeutic interventions for SLE.
Curcumanes E and F, two rare sesquiterpenoids with a dicyclo[3.3.1]nonane moiety, from Curcuma longa and their vasorelaxant activities

Two new sesquiterpenoids, curcumanes E (1) and F (2), were isolated from the rhizome of Curcuma longa, and their structures and absolute configurations were examined using extensive spectroscopic analyses and ECD calculations. Interestingly, compounds 1 and 2 are diastereoisomers possessing a rare sesquiterpenoid skeleton that has been reported only once before. Both curcumanes E and F exhibit significant vasorelaxant effects against KCl-induced contraction of rat aortic rings, with EC50 values of 5.10 ± 0.79 and 5.58 ± 1.77 μM, respectively. These findings enrich the data concerning this rare type of sesquiterpenoids and further indicate that these rare sesquiterpenoids can effectively reduce blood pressure.
Achieving spatially precise diagnosis and therapy in the mammalian gut using synthetic microbial gene circuits

The mammalian gut and its microbiome form a temporally dynamic and spatially heterogeneous environment. The inaccessibility of the gut and the spatially restricted nature of many gut diseases translate into difficulties in diagnosis and therapy for which novel tools are needed. Engineered bacterial whole-cell biosensors and therapeutics have shown early promise at addressing these challenges. Natural and engineered sensing systems can be repurposed in synthetic genetic circuits to detect spatially specific biomarkers during health and disease. Heat, light, and magnetic signals can also activate gene circuit function with externally directed spatial precision. The resulting engineered bacteria can report on conditions in situ within the complex gut environment or produce biotherapeutics that specifically target host or microbiome activity. Here, we review the current approaches to engineering spatial precision for in vivo bacterial diagnostics and therapeutics using synthetic circuits, and the challenges and opportunities this technology presents.
Ensemble deep learning for brain tumor detection

With the quick evolution of medical technology, the era of big data in medicine is quickly approaching. The analysis and mining of these data significantly influence the prediction, monitoring, diagnosis, and treatment of tumor disorders. Since it has a wide range of traits, a low survival rate, and an aggressive nature, brain tumor is regarded as the deadliest and most devastating disease. Misdiagnosed brain tumors lead to inadequate medical treatment, reducing the patient's life chances. Brain tumor detection is highly challenging due to the capacity to distinguish between aberrant and normal tissues. Effective therapy and long-term survival are made possible for the patient by a correct diagnosis. Despite extensive research, there are still certain limitations in detecting brain tumors because of the unusual distribution pattern of the lesions. Finding a region with a small number of lesions can be difficult because small areas tend to look healthy. It directly reduces the classification accuracy, and extracting and choosing informative features is challenging. A significant role is played by automatically classifying early-stage brain tumors utilizing deep and machine learning approaches. This paper proposes a hybrid deep learning model Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) for classifying and predicting brain tumors through Magnetic Resonance Images (MRI). We experiment on an MRI brain image dataset. First, the data is preprocessed efficiently, and then, the Convolutional Neural Network (CNN) is applied to extract the significant features from images. The proposed model predicts the brain tumor with a significant classification accuracy of 99.1%, a precision of 98.8%, recall of 98.9%, and F1-measure of 99.0%.
A perspective on enhancing representative samples in developmental human neuroscience: Connecting science to society

Marginalized groups are often underrepresented in human developmental neuroscientific studies. This is problematic for the generalizability of findings about brain-behavior mechanisms, as well as for the validity, reliability, and reproducibility of results. In the present paper we discuss selection bias in cohort studies, which is known to contribute to the underrepresentation of marginalized groups. First, we address the issue of exclusion bias, as marginalized groups are sometimes excluded from studies because they do not fit the inclusion criteria. Second, we highlight examples of sampling bias. Recruitment strategies are not always designed to reach and attract a diverse group of youth. Third, we explain how diversity can be lost due to attrition of marginalized groups in longitudinal cohort studies. We provide experience- and evidence-based recommendations to stimulate neuroscientists to enhance study population representativeness via science communication and citizen science with youth. By connecting science to society, researchers have the opportunity to establish sustainable and equal researcher-community relationships, which can positively contribute to tackling selection biases.
Simultaneous pre-treatment of dietary Moringa oleifera leaf meal with polyethylene glycol and fibrolytic enzymes: Effect on growth performance, physiological indices, and meat quality parameters in jumbo quail

The utility of Moringa oleifera leaf meal (MOLM) as a source of biologically active substances and nutrients for Jumbo quail is limited by high concentrations of condensed tannins and fiber. Simultaneous application of polyethylene glycol (PEG), a tannin-binding compound, and exogenous fibrolytic multi-enzymes could ameliorate antinutritional effects of condensed tannins and fiber thus improving MOLM utilization in quail diets. This study investigated the effect of pre-treating dietary MOLM with PEG and fibrolytic enzymes on live performance, blood parameters, visceral organs, and carcass and meat quality characteristics in Jumbo quail. A total of 381, two-week-old quail chicks (57.5 ± 3.95 g live-weight) were randomly distributed to six dietary treatments replicated six times. The treatments were: T1 = a standard grower diet containing untreated MOLM (10%); T2 = a standard grower diet containing MOLM (10%) pre-treated with 5.4% PEG; and a standard grower diet containing MOLM (10%) pre-treated with 5.4% PEG and 1.25% (T3), 1.50% (T4), 1.75% (T5) and 2.0% (T6) fibrolytic multi-enzymes. Graded levels of enzymes did not induce linear or quadratic effects for overall feed intake, feed conversion efficiency, hematological, carcass, and meat quality parameters in response to increasing fibrolytic enzyme levels. However, weight gain in week 3 quadratically responded [R2 = 0.117, P = 0.043]. Three-week old birds reared on T3 had lower (p < 0.05) weight gains (40.9 g/bird) than those reared on the other treatment groups. Birds reared on T6 diet had longer caecum (14.1 cm) than those reared on T2, T3, T4 and T5 whose caeca lengths did not differ (P > 0.05). Birds reared on diet T5 had shorter small intestines (59.5 cm) than those reared on T1 and T2 diets. It can be concluded that simultaneous pre-treatment of dietary MOLM with PEG and fibrolytic enzymes did not improve live performance, blood parameters, and carcass and meat quality traits, but affected some visceral organ sizes in Jumbo quail.