Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating experimental model, LC-MS/MS chemical analysis, and systems biology approach to investigate the possible antidiabetic effect and mechanisms of Matricaria aurea (Golden Chamomile) in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a heterogeneous disease with numerous abnormal targets and pathways involved in insulin resistance, low-grade inflammation, oxidative stress, beta cell dysfunction, and epigenetic factors. Botanical drugs provide a large chemical space that can modify various targets simultaneously. Matricaria aurea (MA, golden chamomile) is a widely used herb in Middle Eastern communities for many ailments, including diabetes mellitus, without any scientific basis to support this tradition. For the first time, this study aimed to investigate the possible antidiabetic activity of MA in a type 2 diabetic rat model, identify chemical constituents by LC-MS/MS, and then elucidate the molecular mechanism(s) using enzyme activity assays, q-RTPCR gene expression analysis, network pharmacology analysis, and molecular docking simulation. Our results demonstrated that only the polar hydroethanolic extract of MA had remarkable antidiabetic activity. Furthermore, it improved dyslipidemia, insulin resistance status, ALT, and AST levels. LC-MS/MS analysis of MA hydroethanolic extract identified 62 compounds, including the popular chamomile flavonoids apigenin and luteolin, other flavonoids and their glycosides, coumarin derivatives, and phenolic acids. Based on pharmacokinetic screening and literature, 46 compounds were chosen for subsequent network analysis, which linked to 364 candidate T2DM targets from various databases and literature. The network analysis identified 123 hub proteins, including insulin signaling and metabolic proteins: IRS1, IRS2, PIK3R1, AKT1, AKT2, MAPK1, MAPK3, and PCK1, inflammatory proteins: TNF and IL1B, antioxidant enzymes: CAT and SOD, and others. Subsequent filtering identified 40 crucial core targets (major hubs) of MA in T2DM treatment. Functional enrichment analyses of the candidate targets revealed that MA targets were mainly involved in the inflammatory module, energy-sensing/endocrine/metabolic module, and oxidative stress module. q-RTPCR gene expression analysis showed that MA hydroethanolic extract was able to significantly upregulate PIK3R1 and downregulate IL1B, PCK1, and MIR29A. Moreover, the activity of the antioxidant hub enzymes was substantially increased. Molecular docking scores were also consistent with the networks’ predictions. Based on experimental and computational analysis, this study revealed for the first time that MA exerted antidiabetic action via simultaneous modulation of multiple targets and pathways, including inflammatory pathways, energy-sensing/endocrine/metabolic pathways, and oxidative stress pathways.
Beyond the brain-computer interface: Decoding brain activity as a tool to understand neuronal mechanisms subtending cognition and behavior

One of the major challenges in system neurosciences consists in developing techniques for estimating the cognitive information content in brain activity. This has an enormous potential in different domains spanning from clinical applications, cognitive enhancement to a better understanding of the neural bases of cognition. In this context, the inclusion of machine learning techniques to decode different aspects of human cognition and behavior and its use to develop brain–computer interfaces for applications in neuroprosthetics has supported a genuine revolution in the field. However, while these approaches have been shown quite successful for the study of the motor and sensory functions, success is still far from being reached when it comes to covert cognitive functions such as attention, motivation and decision making. While improvement in this field of BCIs is growing fast, a new research focus has emerged from the development of strategies for decoding neural activity. In this review, we aim at exploring how the advanced in decoding of brain activity is becoming a major neuroscience tool moving forward our understanding of brain functions, providing a robust theoretical framework to test predictions on the relationship between brain activity and cognition and behavior.
Nonlinear and direction connections

Nonlinear connections and direction connections are two types of connections arising in Finsler geometry. In his work on generalized sprays, P. Dazord showed that there is a relationship between these two types (nonlinear connections were called sections by him). This relationship has also been used by J. Grifone in a work on prolongation of direction connections. In this paper we examine this relationship in a general setting. In particular, we show that E. Cartan's condition "D" is necessary and sufficient for a direction connection to define a nonlinear one. Also, we prove a nonuniqueness result for direction connections associated to a given nonlinear one. 1. Connections on vector-bundles. We first recall our definition of a connection on a vector bundle [5], [6]. For a smooth (C0) vector bundle p E-*>M, set Eo = E -0 and po =p I Eo. The bundle p-'E over E is canonically isomorphic to the bundle VE of vertical vectors in the tangent bundle TE of E. Hence we have the exact sequence J p' (1) 0 p--'E--TE --p-'TM--*O of vector bundles over E, where J corresponds to the inclusion map VEC TE and p' is essentially the tangent map p*: TE--TM. A smooth nonlinear connection on the vector bundle p:E--M is a smooth splitting of (1) over Eo. Since TEj Eo = TEo and p-1EIEo =pO1E, such a splitting is given by a smooth linear map V: TEo -_+p0E (i.e. continuous linear on the fibres), satisfying the equation VJ = id. The splitting can be conveniently described by its connection map D: TEo--E defined as D = r o V, where r: p-'E--*E is the canonical surjection over p. D is continuous linear on the fibres and is smooth. The connection on p: E-M is homogeneous (resp. linear) if the map D is homogeneous of degree 1 (resp. linear) on the p* fibres of TE. For a linear connection, the splitting of (1) automatically extends to all of E; in fact, a linear connection can be defined as a splitting of (1) which is smooth over all of E. Received by the editors June 23, 1970. AMS 1969 subject classifications. Primary 5385, 5350.
Energy relaxation in one-dimensional polariton condensates

We study the kinetics of polariton condensation accounting for the condensation process as well as the energy relaxation of condensed polaritons due to their scattering with phonons and excitons. By assuming a Boltzmann kinetic description of the scattering process, we show that intracondensate relaxation can be accounted for by an additional time-dependent term in the Gross-Pitaevskii equation. As an example, we apply the formalism to the experimental results recently obtained in polariton microwires [E. Wertz, L. Ferrier, D. Solnyshkov, R. Johne, D. Sanvitto, A. Lemaitre, I. Sagnes, R. Grousson, A. V. Kavokin, P. Senellart, G. Malpuech, and J. Bloch, Nat. Phys. 6, 860 (2010)]. In the presence of a local nonresonant optical pump, a dynamic balance between spatially dependent relaxation and particle loss develops and excites a series of modes, roughly equally spaced in energy. Upon comparison, excellent agreement is found with the experimental data.
Virtual screening and activity evaluation of multitargeting inhibitors for idiopathic pulmonary fibrosis

Transforming growth factor β receptor (TGF-β1R) and receptor tyrosine kinases (RTKs), such as VEGFRs, PDGFRs and FGFRs are considered important therapeutic targets in blocking myofibroblast migration and activation of idiopathic pulmonary fibrosis (IPF). To screen and design innovative prodrug to simultaneously target these four classes of receptors, we proposed an approach based on network pharmacology combining virtual screening and machine learning activity prediction, followed by efficient in vitro and in vivo models to evaluate drug activity. We first constructed Collagen1A2-A549 cells with type I collagen as the main biomarker and evaluated the activity of compounds to inhibit collagen expression at the cellular level. The data from the first round of Collagen1A2-A549 cell screening were substituted into the machine learning model, and the model was optimized accordingly. As a result, the false positive rate of the model was reduced from 85.0% to 66.7%, and two prospective compounds, Z103080500 and Z104578368, were finally selected. Collagen levels were reduced effectively by both Z103080500 (67.88% reduction) and Z104578368 (69.54% reduction). Moreover, these two compounds showed low cellular cytotoxicity. Subsequently, the effect of Z103080500 and Z104578368 was evaluated in a bleomycin-induced C57BL/6 mouse IPF model. These results showed that 50 mg/kg Z103080500 and Z104578368 could effectively reduce the number of inflammatory cells and the expression level of α-SMA. Meanwhile, Z103080500 and Z104578368 reduced the expression of major markers and inflammatory factors of IPF, such as collagen, IFN-γ, IL-17 and HYP, indicating that these screened Z103080500 and Z104578368 effectively delayed lung tissue inflammation and had a potential therapeutic effect on IPF. Our findings demonstrate that a screening and evaluation model for prodrug against IPF has been successfully established. It is of great significance to further modify these compounds to enhance their potency and activity.
Association between coronary plaque volume and myocardial ischemia detected by dynamic perfusion CT imaging

Introduction We aimed to evaluate the relationship between quantitative plaque metrics derived from coronary CT angiography (CTA) and segmental myocardial ischemia using dynamic perfusion CT (DPCT). Methods In a prospective single-center study, patients with > 30% stenosis on rest CTA underwent regadenoson stress DPCT. 480 myocardium segments of 30 patients were analyzed. Quantitative plaque assessment included total plaque volume (PV), area stenosis, and remodeling index (RI). High-risk plaque (HRP) was defined as low-attenuation plaque burden > 4% or RI > 1.1. Absolute myocardial blood flow (MBF) and relative MBF (MBFi: MBF/75th percentile of all MBF values) were quantified. Linear and logistic mixed models correcting for intra-patient clustering and clinical factors were used to evaluate the association between total PV, area stenosis, HRP and MBF or myocardial ischemia (MBF < 101 ml/100 g/min). Results Median MBF and MBFi were 111 ml/100 g/min and 0.94, respectively. The number of ischemic segments were 164/480 (34.2%). Total PV of all feeding vessels of a given myocardial territory differed significantly between ischemic and non-ischemic myocardial segments (p = 0.001). Area stenosis and HRP features were not linked to MBF or MBFi (all p > 0.05). Increase in PV led to reduced MBF and MBFi after adjusting for risk factors including hypertension, diabetes, and statin use (per 10 mm3; β = −0.035, p < 0.01 for MBF; β = −0.0002, p < 0.01 for MBFi). Similarly, using multivariate logistic regression total PV was associated with ischemia (OR = 1.01, p = 0.033; per 10 mm3) after adjustments for clinical risk factors, area stenosis and HRP. Conclusion Total PV was independently associated with myocardial ischemia based on MBF, while area stenosis and HRP were not.
AntiVIRmiR: A repository of host antiviral miRNAs and their expression along with experimentally validated viral miRNAs and their targets

miRNAs play an essential role in promoting viral infections as well as modulating the antiviral defense. Several miRNA repositories have been developed for different species, e.g., human, mouse, and plant. However, ‘VIRmiRNA’ is the only existing resource for experimentally validated viral miRNAs and their targets. We have developed a ‘AntiVIRmiR’ resource encompassing data on host/virus miRNA expression during viral infection. This resource with 22,741 entries is divided into four sub-databases viz., ‘DEmiRVIR’, ‘AntiVmiR’, ‘VIRmiRNA2’ and ‘VIRmiRTar2’. ‘DEmiRVIR’ has 10,033 differentially expressed host-viral miRNAs for 21 viruses. ‘AntiVmiR’ incorporates 1,642 entries for host miRNAs showing antiviral activity for 34 viruses. Additionally, ‘VIRmiRNA2’ includes 3,340 entries for experimentally validated viral miRNAs from 50 viruses along with 650 viral isomeric sequences for 14 viruses. Further, ‘VIRmiRTar2’ has 7,726 experimentally validated targets for viral miRNAs against 21 viruses. Furthermore, we have also performed network analysis for three sub-databases. Interactions between up/down-regulated human miRNAs and viruses are displayed for ‘AntiVmiR’ as well as ‘DEmiRVIR’. Moreover, ‘VIRmiRTar2’ interactions are shown among different viruses, miRNAs, and their targets. We have provided browse, search, external hyperlinks, data statistics, and useful analysis tools. The database available at https://bioinfo.imtech. res.in/manojk/antivirmir would be beneficial for understanding the host-virus interactions as well as viral pathogenesis.
Periodontitis induced by orthodontic wire ligature drives oral microflora dysbiosis and aggravates alveolar bone loss in an improved murine model

Aim To assess the contribution of polymicrobial disruption of host homeostasis to periodontitis progression in orthodontic wire ligation murine model. Methods Orthodontic wire rings were inserted between the first and second molars of mice for 18 days for the orthodontic wire ligation mouse model, and Pg injection model and Pg-LPS injection model were used as controls. Alveolar bone loss and periodontal inflammation were analyzed by micro-CT, histological staining and qRT-PCR. Further, pyrosequencing of 16S rRNA gene amplicon was used to analyze the development of oral microorganism dysbiosis in the mice. Results Micro-CT, TRAP staining and qRT-PCR showed that orthodontic wire ligation model led to more severe alveolar bone loss than Pg and Pg-LPS models. H&E staining and qRT-PCR demonstrated that stronger inflammatory response was induced by the orthodontic wire treatment compared to the other models. In addition, pyrosequencing of 16S rRNA gene amplicons revealed that the composition of oral microbiota presented a transition as the disease progressed and significant differences emerged in oral microbiota communities between orthodontic ligature mice and healthy controls. Furthermore, antibiotic treatment decreased both inflammation and alveolar bone loss in response to microbial community dysbiosis. However, no significant difference in bacterial community composition was observed in Pg and Pg-LPS models. Conclusions Orthodontic wire ligation drove oral microbial community transitions that mimicked polymicrobial communities characterized by polymicrobial synergy and dysbiosis. Our improved model is suitable for further study of pathogenesis of periodontitis and exploration of corresponding treatment strategies.
Optic nerve sheath diameter and optic nerve sheath diameter/eyeball transverse diameter ratio in prediction of malignant progression in ischemic stroke

Background The optic nerve sheath diameter (ONSD)/eyeball transverse diameter (ETD) ratio has been suggested in the evaluation of intracranial pressure (ICP). The aim of this study was to evaluate the predictive value of ONSD and ONSD/ETD in relation to risk for secondary malignant middle cerebral artery infarction (MMI). Methods A total of 91 patients with MCA occlusion were included in this study. Data were divided into two groups based on development of MMI or not. ONSD and ETD were measured by unenhanced computed tomography (CT). The differences in ONSD and the ONSD/ETD ratios between the MMI and non-MMI groups were compared. Receiver operating characteristic curve analyses were used to test the diagnostic value of ONSD and ONSD/ETD independently, to predict MMI. Results The ONSD in the MMI group and non-MMI group were 5.744 ± 0.140 mm and 5.443 ± 0.315 mm, respectively (P = 0.001). In addition, the ONSD/ETD ratios in the MMI group and non-MMI group were 0.258 ± 0.008 and 0.245 ± 0.006, respectively (P = 0.001). The receiver operating characteristic (ROC) curve demonstrated an area under the curve (AUC) for ONSD of 0.812 [95% confidence interval (CI): 0.718–0.906, P = 0.001], with a sensitivity of 97.4% and a specificity of 66.0% at the cut-off value of 5.520 mm. The AUC for ONSD/ETD ratio in predicting occurrence of MMI was 0.895 (95% CI: 0.823–0.968, P = 0.001), with a sensitivity of 84.2% and a specificity of 92.5% at a cut-off value of 0.250. Conclusion In acute stroke patients with massive cerebral infarction, an increased ONSD or ONSD/ETD ratio increases the odds of malignant progression and may be used as an indicator for emergent therapeutic interventions. In addition, the ONSD/ETD ratio may be more valuable than ONSD in predicting the malignant progression of acute stroke patients.
On the Dirichlet problem associated with the Dunkl Laplacian

This paper is devoted to the study of the Dirichlet problem associated with the Dunkl Laplaciank. We establish, under some condition on a bounded domain D of R d , the existence of a unique continuous function h on R d such thatkh = 0 on D and h = f on R d \ D the complement of D in R d , where the function f is asumed to be continuous. We also give an analytic formula characterizing the solution h.
Upregulation of P2X3 receptors in primary afferent pathways involves in colon-to-bladder cross-sensitization in rats

Background: Clinical investigation indicates a high level of co-morbidity between bladder overactivity and irritable bowel syndrome. The cross-sensitization of afferent pathways has been demonstrated to be the main reason for the cross-organ sensitization, but the underlying mechanism is unclear. Methods: A single dose of 2, 4, 6-trinitrobenzene sulfonic acid (TNBS) was applied to induce the colitis rat models by intracolonic administration. All rats were randomly divided into three groups: control, TNBS-3-day, and TNBS-7-day groups. Western blot and immunofluorescent staining were performed to detect the expression of the P2X3 receptor. The spontaneous contractions of the detrusor strip were measured to evaluate the detrusor contractility function. The micturition function was measured by a cystometry experiment. The intercontractile interval (ICI) and maximum bladder pressure (BP) were recorded. Results: The distal colon from colitis showed serious tissue damage or chronic inflammation after TNBS instillation (p < 0.01). However, there were no detectable histological changes in bladder among groups (p > 0.05). TNBS-induced colitis significantly increased P2X3 receptor expression on the myenteric and submucosal plexus of the distal colon and urothelium of the bladder, especially at day 3 post-TNBS (p < 0.05). Meanwhile, the expression of the P2X3 receptor on DRG neurons was increased in TNBS-induced colitis (p < 0.01). The detrusor strip of rats exhibited detrusor overactivity after days 3 and 7 of TNBS administration (p < 0.01), but inhibition of the P2X3 receptor had no effect (p > 0.05). Moreover, the rats with colitis exhibited the micturition pattern of bladder overactivity, manifested by decreased ICI and increased maximum BP (p < 0.05). Interestingly, inhibition of the P2X3 receptor by intrathecal injection of A-317491 alleviated bladder overactivity evoked by TNBS-induced colitis (p < 0.05). Conclusion: The upregulation of the P2X3 receptor in an afferent pathway involved in bladder overactivity evoked by TNBS-induced colonic inflammation, suggesting that the P2X3 receptor antagonist may be an available and novel strategy for the control of bladder overactivity.
Multimodal resting-state connectivity predicts affective neurofeedback performance

Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into “connectivity summary scores” (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson’s correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = −0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation.
Fourier Analysis on Local Fields.

This book presents a development of the basic facts about harmonic analysis on local fields and the "n"-dimensional vector spaces over these fields. It focuses almost exclusively on the analogy between the local field and Euclidean cases, with respect to the form of statements, the manner of proof, and the variety of applications.The force of the analogy between the local field and Euclidean cases rests in the relationship of the field structures that underlie the respective cases. A complete classification of locally compact, non-discrete fields gives us two examples of connected fields (real and complex numbers); the rest are local fields (p-adic numbers, p-series fields, and their algebraic extensions). The local fields are studied in an effort to extend knowledge of the reals and complexes as locally compact fields.The author's central aim has been to present the basic facts of Fourier analysis on local fields in an accessible form and in the same spirit as in Zygmund's "Trigonometric Series" (Cambridge, 1968) and in "Introduction to Fourier Analysis on Euclidean Spaces" by Stein and Weiss (1971). Originally published in 1975.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These paperback editions preserve the original texts of these important books while presenting them in durable paperback editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Multiple randomizations

Summary. Multitiered experiments are characterized by involving multiple randomizations, in a sense that we make explicit. We compare and contrast six types of multiple randomizations, using a wide range of examples, and discuss their use in designing experiments. We outline a system of describing the randomizations in terms of sets of objects, their associated tiers and the factor nesting, using randomization diagrams, which give a convenient and readily assimilated summary of an experiment's randomization. We also indicate how to formulate a randomization‐based mixed model for the analysis of data from such experiments.